Role of Differentially Expressed Proteins in Acquired Resistance to Cdk4/6 Inhibitor in Breast Cancer

Role of Differentially Expressed Proteins in Acquired Resistance to Cdk4/6 Inhibitor in Breast Cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Role of Differentially Expressed Proteins in Acquired Resistance to Cdk4/6 Inhibitor in Breast Cancer Binayak Kumar, Peeyush Prasad, Ragini Singh, Ram Krishana Sahu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-556331/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract CDK4/6 inhibitors (Abemaciclib, Ab and Palbociclib, Pb) stop the G1-phase in cell-cycle being used to cure advanced stage of breast cancer (BC). Acquired resistance is a major challenge in BC therapy. The molecular signature of the therapy resistance for Ab and Pb drugs in BC should be explored. Here, we developed Ab/Pb-resistant cell-models and explored the molecular changes. Drug’s resistance cells were developed in MCF-7 cells by continuous drug treatment and it was confirmed by MTT-assay, PI-staining-microscopy, and real-time-qPCR. Global proteome profiling done by Labelled-free-Proteome-Orbitrap-Fusion-MS-MS technique. Bioinformatics tools used to analyse the proteome data. Ab-resistant and Pb-resistant MCF-7 cells showed increased tolerance for the respective drug. The BCL-2 and MCL-1 survival genes were up-regulated, while the apoptosis genes BAD, BAX, CASP-3 and PARP-1were down-regulated in the resistant cells. Expression of the MDR-1, ABCG2, ESR-1, CDK4, CDK6, and Cyclin-D1 genes were increased in both resistance cells. For proteomics, 237 and 239 proteins were expressed differently in the resistant Ab and Pb cells, respectively. The NUDT5, PEPD, ABAT, ATP1B1, GGCT, and SELENBP1 proteins were down-regulated and the SBSN, HSD17B10, CD9, PDIA3, PSMB4, SLC2A1, and VTN proteins were up-regulated in Ab-resistant cells. The NUDT5, PEPD, and GGCT proteins were down-regulated, while CD47, HIST1H2BN, LMNA, VTN, PSMB5, HBB, PSMA7, FLNB, PRDX4, VDAC1, GOT2, HSPA5, SERPINH1, EIF4A2, FTH, and VIM proteins were up-regulated in Pb-resistant cells. These proteins are a new set of prognostic markers and drug targets for overcoming the respective drug resistance. However, it is necessary to perform an in vivo or clinical assessment. Cancer Biology Oncology Drug-resistance Breast Cancer Apoptosis Cell-cycle and Proteome. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Breast cancer is the second most commonly diagnosed cancer in the world, after lung cancer; however, it is the most prevalent in the Indian population [ 1 – 3 ]. Breast cancers are classified by the presence or absence of a surface receptor, that is, the estrogen receptor (ER), the progesterone receptor (RP), and the human epidermal growth factor receptor 2 (HER-2). Radiotherapy, chemotherapy, hormone therapy, and targeted therapy are all common treatment methods [ 4 ]. To treat primary and metastatic breast cancer, chemotherapy drugs such as 5-fluorouracil, methotrexate, cyclophosphamide, doxorubicin, and epirubicin are used. [ 5 , 6 ].ER inhibitors (tamoxifen, letrozole, and fulvestrant) are used to treat estrogen-positive breast cancer in hormone therapy. Tumor cells develop tolerance to drug cytotoxicity, resulting in the therapeutic resistance phenotype, which contributes to disease progression and recurrence. [ 5 , 6 ]. Tumor cells triggered other pathways essential for their survival in the process of acquiring the resistance trait [ 5 , 6 ].The investigation of the molecular mechanisms underlying therapeutic resistance in cancer care has resulted in a transition in drug development toward targeted therapy.By inhibiting certain proteins necessary for tumor cell proliferation and survival, targeted therapy prevents cancer progression. Proteins such as receptor tyrosine kinase, cytokine receptors, and intracellular serine-threonine kinases can be targeted. Abemaciclib (Ab) and Palbociclib (Pb) are two synthetic (small-molecule) inhibitors of cyclin-dependent kinase 4 and 6 (CDK4 and CDK6) [ 7 ]. CDK 4 and 6 are intracellular, serine-threonine protein kinase enzyme associated with cell-cycle progression from G1 to S-phase. Inhibition of CDK4 and CDK6 will halt the G1 phase of the cells. The U.S. FDA approved Palbociclib in 2016, while Abemaciclib approved in 2017 to treat advanced breast cancer with ER, PR positive and HER2-negative receptors [ 8 , 9 ]. Deregulation of CDK4/6 causes uncontrolled cell proliferation, which may occur due to amplification of cyclin D1, a gain of CDK4/6, loss of p18, elevated Rb1, and loss of p16, etc. [ 10 – 13 ]. CDK4/6 inhibitors have emerged as breakthrough for breast cancer treatment. Recently, resistance to CDK4/6 inhibitors has been identified as a concern in the management of breast cancer [ 14 – 16 ]. PI3K-AKT-mTOR signal mediated resistance to CDK4/6 inhibitors is reported for a similar medicine ribociclib. [ 17 ]. However, resistance mechanisms for Ab and Pb drugs in breast cancer therapy have not been reported. This study aims to develop drug-resistant cell models for the drugs Abemaciclib and Palbociclib in the breast cancer cell lineage and further assess the molecular changes involved in resistance. Materials And Methods Abemaciclib and Palbociclib drugs were purchased from Selleck Chem, USA. MCF-7 was bought from NCCS Pune in India. Cell culture media (Lonza), FBS (Gibco life technology), Plastic-wares for cell-culture (Corning), 96-well plate for real-time-qPCR of Thermo Scientific, RNA isolation kit (Qiagen), cDNA synthesis kit (Takara), 2x SYBR Green-Master mix (Promega) and Primers synthesized from Imperial Life Sciences Pvt. Ltd. Both, control and resistant cells were maintained in high glucose DMEM medium supplemented with 10% FBS and 1% Penicillin and streptomycin antibiotics in 5% CO2, humidified air and at 37 0C temperature. To develop resistance models, MCF-7 cells were treated with Abemaciclib and Palbociclib drugs in separate T-25 flasks at initial 5 nm concentrations. The drug doses were gradually increased up to 200 nm concentrations and keep maintaining cells at the same. Cell-viability Assay MCF-7 and continued drug-treated cells called Ab-R-MCF-7 and Pb-R-MCF-7 with Ab and Pb drug, respectively, are seeded in a 96-well plate with 2. 5x10 4 cells count in each well. After 24 h of incubation, cells were treated with the respective drug from 100 nm to 6 μM concentrations in drug-sensitive MCF-7 cells and up to 8μM for drug-resistant MCF-7 cells for 48 and 72 h. Add 100 µl of 0.5 μg/μl MTT to each well and incubated for 2.5 h than lysed the cells with detergent (DMSO). OD-value was measured at 595 nm wavelength into micro-plate reader and percent cell viability was calculated. PI-Staining-microscopy MCF-7, Ab-R-MCF-7, and Pb-R-MCF-7 cells were seeded (4x10 4 cells/well) in a 12-well plate and incubated into a CO2 incubator for 24 hrs. Cells were treated with Ab and Pb of 1.5 and 2.0 μM concentrations for 48 and 72 h, respectively. Cells were stained with 25 μg/ml propidium iodide (PI) for 15 min. PI-stained cells exposed to green mono-chromatic light and red-emission light were captured along with white light. Images were taken on 20x magnification into a Nikon inverted fluorescence microscope. Real-Time-qPCR MCF-7, Ab-R-MCF-7, and Pb-R-MCF-7 cells were seeded (7.5x104 cells/well) into 6-well plates and incubated into CO2 incubator for 24 hrs. Cells were treated with Ab (0.25 μM) and Pb (2.0 μM) drugs for 48 h. Cells detached and washed with cold PBS. Total RNA is extracted from cells palette using total RNA isolation kit followed the kit protocols. The quantity and quality of total RNA was measured by Nano-Drop. 0.5 μg total RNA is used for cDNA synthesis following the protocols mentioned in cDNA synthesis kit. Real-time-qPCR was performed in triplicate using Bio-Red connect real-time-qPCR system using the 2X Master mix of SYBR Green (from Promega) and gene-specific primers.18S gene was selected as an internal control for normalization. Relative quantity (RQ) - value for each gene were analyzed for each sample from their Ct-value. The list of genes and primer sequences is listed in Supplemental Table 1. Labelle free-Proteome-Orbitrap-Fusion MS-MS Samples were prepared for a proteomics experiment for MCF-7 control, Ab-R-MCF-7 and Pb-R-MCF-7 cells. Cells were seeded (7.5 x 10 4 cells/well) in T-25 flasks, incubated in a CO 2 incubator for 48 h, after those cells were harvested and lysed in a cell lysis buffer (6 M urea, 2M thiourea, 2% CHAPS and 0.5% SDS) containing 1% protease inhibitor cocktail. Cell samples were sonicated on ice for 30 sec pulse with 10 sec gaps for 5 times, centrifuged the cell-lysate at 12000 rpm for 15 min at 4 0 C than supernatant was collected. Proteins were estimated using Bradford reagent (Sigma) and measured the OD value in the microplate reader at 595 nm wavelength light exposed. Protein quality was checked by Coomassie blue after running SDS-PAGE. Protein samples were sent to the proteomics laboratory, MASSFIITB facility supported by DBT (BT/PR13114/INF/22/206/2015), IIT Bombay, Mumbai. The technique was used for proteomics is labelled free-Proteome- Orbitrap-Fusion MS-MS. The protein search is performed against the Homo sapiens database downloaded from UniProt using Proteome Discoverer 2.2. Bioinformatics Bioinformatics tools were used to analyse proteomics data. Venny tool used to select common proteins in replicating data. The reactome pathway database was used to find the role of proteins in different reaction pathways. Gene Ontology (GO) analysis was performed using the STRING database. A network analyst tool used to find the proteins hub. Generic PPI was analysed without any filter, but the subnetwork having maximum seed. miR-Net tool used for miRNA-Gene interaction analysis to explore the post-transcriptional regulation of gene expressions. Here, identified protein IDs were searched against the background of breast cancer tissues. The minimum network option was selected for the analysis. Results Increased tolerance to Abemaciclib and Palbociclib in Ab-R-MCF-7 and Pb-R-MCF-7 cells MCF-7 cells were treated with Abemaciclib and Palbociclib and the inhibitory concentration values were calculated. Cells treated with Ab exhibited an IC50 value of 1.5 µM at 48 h and cells treated with Pb showed an IC50 3.0 µM after 72 h. These sensitive MCF-7 cells were treated continuously with an increasing concentration ranging from 0.1 to 8 µM. As shown in Figure-1 cytotoxicity was assessed in the continuously drug-exposed cells and it was found that Ab treated cells could tolerate the drug up to a concentration of 7.0 µM after 48hrs and the Pb treated cells could tolerate up to 7.5 µM after 72 h. When increased IC50 values were compared to the sensitive cells could survive higher drug concentration, indicating that these cells develop resistance to the drugs. Reduced Cell Death In Drug-resistant Cells Further to reconfirm the cytotoxicity results obtained in the above experiments Propidium Iodide exclusion experiment was performed. Control-sensitive-cells and the Ab and Pb-resistant MCF-7 cells were treated with the respective drug for 48 h, and stained with propidium iodide. Control-MCF-7 cells without any drug treatment looked healthy and, few cells stained red with PI, whereas the MCF-7 cells treated with Ab and Pb exhibited stressed phenotype and a great number of cells picked-up PI-stain. However, only a few drug-resistant cells picked up PI stain and the rest of the cells looked healthier (Fig. 1. C, D, E). Again, confirming the tolerance of the resistant cells to these drugs. Up-regulation Of Pro-survival And Down-regulation Of Apoptotic Genes To check the cell death at the mRNA level the expression of pro-survival and apoptosis-associated genes were checked. qPCR results as shown in Fig. 2B, the expression of pro-survival genes BCL-2 and MCL-1 were found to be up-regulated in resistant cells. BCL-2 expression was enhanced by 3.13 and 1.60-fold in Ab-RMCF-7 and Pb-R-MCF-7 cells, respectively, whereas, MCL-1 were 4.90 and 5.80-fold higher expression in Ab-R-MCF-7 and Pb-R-MCF-7 respectively as compare to the control. Pro-apoptotic genes BAX, BAD, Casp-3 and PARP1 expressions in Ab-R-MCF-7 were similar to the control cells. They exhibited a change of 1.04, 0.80, 1.14, and 1.28 folds, respectively. However, in Ab-treated drug-sensitive cells, these gene expressions were found to be 2.25, 2.17, 2.14, and 5.17-folds higher, respectively (Fig. 2. C). BAX, BAD, Casp-3 and PARP1 expression in Pb-RMCF-7 was 1.15, 0.95, 1.0, and 1.20-fold changed, respectively, however, in Pb-treated, drug-sensitive cells, these were 2.25, 2.15, 2.51, and 3.86-fold higher, respectively, compared to the control (Fig. 2. D). MDR-1 and ABCG-2 are two efflux proteins that are involved in drug expulsion and have been linked to cancer cell survival and resistance evolution. As depicted in Fig. 2A. MDR1 expression was found to be identical in control and drug-treated responsive cells. It was shown to be increased 3.0-fold and 8.2-folds in Ab-R-MCF-7 and Pb-R-MCF-7 cells, respectively. The expression of the ABCG2 gene was comparable in control and drug-treated responsive cells, but it was 4.0 and 5.9 times higher in Ab-RMCF-7 and Pb-R-MCF-7 cells, respectively. ESR1 genes are overexpressed in cancer cells, especially in breast cancer, and both Ab and Pb are CDK4/6 inhibitors. In this analysis, the expression of ESR-1, CDK-4, and CDK-6 in control and responsive cells was found to be identical, whereas the level of cyclin D1 decreased 0.55-fold.However, ESR-1, CDK-4, CDK-6, and Cyclin D1 genes increased 11.9, 3.6, 15.5, and 4.1-fold in Ab-resistant cells, respectively. In Pb-responsive cells ESR-1, CDK-4, and CDK-6 gene expression was unchanged compared to the controls, whereas, Cyclin-D1 was 0.43-fold down-regulated. However, in Pb-resistant cells, ESR-1, CDK-4, CDK-6, and Cyclin-D1 gene expression were increased 20.3, 2.8, 6.4, and 6.0-fold, respectively (Fig. 2. F). As a result, the upregulation of survival genes and the downregulation of apoptotic genes in qPCR results illustrate how these molecular modifications facilitate cell survival and drug tolerance. Differentially Expressed Proteins (Deps) In Global-profiling Global proteome profiling was used to assess altered protein expressions in Ab and Pb-resistant MCF-7 cells. In Ab-R-MCF-7 cells, 237 proteins were identified as DEPs, with 162 proteins were down-regulated and 75 being up-regulated. In Pb-R-MCF-7 cells, 239 proteins were identified as DEPs, with 153 proteins were down-regulated and 86 being up-regulated (Fig. 3A, B). Venn-diagram analysis in Fig. 3. C and D, has shown common proteins among different set of samples (Ab-RMCF- 7/MCF-7 control (Set1 F2/F1 and Set-2 F5/F4) and Pb-R-MCF-7/MCF-7control (Set-1 F3/F1 and Set-2 F6/F4)).DEPs in Ab-R-MCF-7 and Pb-R-MCF-7 cells were manually curated from the PubMed literature search engine, and their cancer-related functions were revealed. Down-regulation of NUDT5, PEPD, ABAT, ATP1B1, GGCT, SELENBP1, M6PR, STOM, and ACTN1 proteins in Ab-R-MCF-7 cells has been identified as a prognostic indicator or a new drug target for breast cancer. (Supplementary Table 2 and Table 1 ). The upregulation of SBSN, HSD17B10, CD9, PDIA3, PSMB4, SLC2A1, and VTN proteins in Ab-R-MCF-7 cells has been identified as a poor prognostic indicator or involved in acquired drug resistance, and has been proposed as a novel drug target for BC treatment (Supplementary Table 3 and Table 1 ). NUDT5, PEPD, and GGCT proteins, which have been identified as prognosis or drug-sensitive markers, were downregulated in Pb-R-MCF-7 cells (Supplementary Table 4 and Table 1 ). CD47, HIST1H2BN, LMNA, VTN, PSMB5, HBB, PSMA7, FLNB, PRDX4, VDAC1, GOT2, HSPA5, SERPINH1, EIF4A2, FTH1, and VIM proteins have been found to be up-regulated in Pb-R-MCF-7 cells, which are associated with poor prognosis or drug resistance markers (Supplementary Table 5 and Table 1 ). Table 1 , Differentially expressed proteins (DEPs) in drug resistance MCF-7 vs MCF-7 control with p-value ≤ 0.05 showed their molecular functions and role in BC. DEPs Fold Change Molecular function Earlier Reports Ref. Ab-R-MCF-7 Vs MCF-7 SBSN 3.45 Upregulated SBSN enhances Wnt/β-catenin signalling and promote proliferation and tumorigenicity 36 37 PDIA3 3.1 Catalyzes the rearrangement of -S-S -bonds in proteins High expression of PDIA3 drive production of secretory proteins and create favourable tumor microenvironment for invasion and metastasis 40 41 CD9 2.2 Integral membrane protein associated with integrins, regulates platelet activation and aggregation, and cell adhesion Tumor microenvironment facilitate CD9 mediated crosstalk between bone marrow-derived mesenchymal stem cells and breast cancer cells (via CCL5, CCR5, and CXCR12) that contributes to chemo resistance 39 SLC2A1 2.2 Facilitative glucose transporter responsible for glucose uptake Aggressive growth of breast cancer activate hypoxia inducing factor HIF1 result in GLUT1 expression 42 43 HSD17B10 1.88 Involved in fatty acid, branched-chain amino acid and steroid metabolism pathways High level of HSD17B10 was indicator for poor responders to the chemotherapy in osteosarcoma 38 VTN 1.8 A cell adhesion and spreading factor Downstream of VEGF/VEGFR and PI3K/AKT signalling induces cell migration and metastasis in breast cancer 33 34 35 PSMB4 1.59 Proteolytic degradation of mostly intra- cellular proteins PSMB4 overexpression enhances the cell growth and viability of breast cancer cells leading to a poor prognosis 29 NUDT5 0.67 Act as ADP-sugar pyrophosphatase in absence of diphosphate or catalyse the synthesis of ATP in presence of diphosphate Associated with low overall survival in clear cell renal cell carcinoma and poor prognosis 23 GGCT 0.63 Glutathione homeostasis, release cyto-c from mitochondria, induces apoptosis. Component of GSH-pathway, its lower expression led to chemotherapy resistance in breast cancer 25 SELENBP1 0.51 Involved in intra-Golgi protein transport ER + ve breast cancer patient with low SELENBP1 have poorer survival rate and induce resistance to the anti-proliferative effects of Selenium 28 ATP1B1 0.48 ATP hydrolysis coupled with Na/K ions exchange across plasma membrane. Associated with metastasis is an important cell energy conversion system 27 ABAT 0.15 Catalyzes the conversion of gamma-amino butyrate and L-beta-aminoisobutyrate to succinate semialdehyde and methyl-malonate semialdehyde, respectively Inverse-correlation between ABAT expression and therapy resistance in inflammatory breast cancer 26 PEPD 0.14 Collagen metabolism Exogenous PEPD bind and inhibit Her-2 and EGFR signalling result in growth inhibition in cancer cells. 24 Pb-R-MCF-7 Vs MCF-7 Control VIM 38.0 Vimentins are class-III intermediate filaments found in various non-epithelial cells, especially mesenchymal cells Activation of Erk-signalling promotes VIM over-expression whereas, its elevated expression in methotrexate and tamoxifen-resistant breast cancer 5859 SERPINH1 36.5 Chaperone protein involved in collagen folding Showed positive correlation between its expression and aggressive phenotype of gastric cancer 3637 HSPA5 20.3 Endoplasmic reticulum chaperone that plays a key role in protein folding HSPA5 were upregulated in Lapatinib resistance breast cancer cells 53 54 FTH1 14.5 Iron homeostasis Up-regulated in doxorubicin resistant breast cancer and promotes EMT 57 GOT2 11.1 Phenylalanine metabolism and Glucose metabolism ZBRK1 and BRCA1 complex bind to the GOT2 promoter and regulate its expression. Impaired complex binding results in uncontrolled expression result in aspartate and α- ketoglutarate production leads to cell proliferation 52 VDAC1 9.6 Present on outer mitochondrial membrane regulating metabolite and ion exchange ElVDAC1upregulation promote cell proliferation, indicator of poor prognosis, involved in therapy resistance towards BRD inhibitors in breast cancer 50 PRDX4 9.2 Catalyse hydrogen peroxide and regulate hydrogen peroxide signalling Elevated expression may lead to therapy resistance and tumor recurrence 50 51 HBB 8.4 Oxygen transport from the lung to the various peripheral tissue Promote aggressiveness in breast cancer cells and poor prognosis 48 FLNB 6.6 Connects cell membrane constituents to the actin cytoskeleton Induces EMT by releasing FOXC1 transcription factor and expression of EMT gene signatured in tumorigenesis 49 LMNA 5.2 Nuclear lamina component, maintaining nuclear integrity Lower expression is indicator of poor prognosis and shorter outcome 47 EIF4A2 5.5 ATP-dependent RNA helicase which is a subunit of the eIF4F complex involved in cap recognition and is required for mRNA binding to ribosome Targeting EIF4A2 by miR-5195-3p reverse chemoresistance in TNBC cells 56 PSMA7 4.9 Proteolytic degradation of intracellular proteins Elevated expression of PSMA7 in gastric cancer is associated with tumor invasion, metastasis, poor survival and having prognostic as well as diagnostic value 32 PSMB5 4.1 Proteolytic degradation of intracellular proteins High expression of PSMB5 indicates worse survival and can be severed as novel drug target 30 31 VTN 3.9 Extracellular matrix (ECM) protein may be associated with cell adhesion and migration VTN is downstream of VEGF/VEGFR and PI3K/AKT signalling induces cell migration and metastasis in breast cancer 34 35 HIST1H2BN 2.7 Core component of nucleosome Uncontrolled HIST1H2BN expression contributes to cancer initiation, progression, and indicator of poor prognosis in ovarian cancer 46 CD47 2.2 Membrane transport and signal transduction HIF-1 activates CD47 transcription in hypoxic condition, CD47 maintains cancer stem cells, induce EMT and serve as indicator of poor prognosis in breast cancer 44 45 GGCT 0.61 Glutathione homeostasis, induces release of cytochrome c from mitochondria to induce apoptosis Component of GSH-pathway, its lower expression led to chemotherapy resistance in breast cancer 25 PEPD 0.28 Collagen metabolism Exogenous PEPD bind and inhibit Her-2 and EGFR signalling result in growth inhibition in cancer cells 24 NUDT5 0.22 Act as ADP-sugar pyrophosphatase in absence of diphosphate or catalyse the synthesis of ATP in presence of diphosphate Associated with low overall survival in clear cell renal cell carcinoma and poor prognosis 23 GO-terms of DEPs in drug-resistant-MCF-7 cells were conducted. Ab-resistant cells' down-regulated proteins have been related to 87 bioprocesses, 23 molecular functions, and 63 cellular components and further KEGG pathway analysis identified 11 signaling pathways. Similarly, Ab-resistant cells' up-regulated proteins have been related to 29 bioprocesses, 30 molecular functions, 30 cellular components and further KEGG pathway analysis identified 9 signaling pathways (Fig. 4. B). GO-term analysis in Pb-resistant cells’ down-regulated proteins have been related to 143 bioprocesses, 31 molecular functions, 63 cell components, and further KEGG pathway analysis identified 32 signaling pathways. Similarly, Ab-resistant cells' up-regulated proteins have been related to 30 bioprocess, 28 molecular functions, 30 cellular components and further KEGG pathway analysis identified 30 signaling pathways. (Fig. 5. A, B).We analysed both drug resistance samples using the Reactome pathway database to investigate the reactome pathway associated with these two conditions. DEPs are implicated in metabolism, immunity, signal transduction, programmed cell death, cellular response to external stimuli, DNA replication, cell cycle, and vesicle transport in this study. (Fig. 6A, B, C, and D). Hub molecules in DEP’s dataset were identified by the Network Analysis tool. FLNA, SSBP, SLC3A2, ATP5B, DLD, and SOD1 were found to be major hubs among down-regulated proteins, whereas, S100A7, VTN, and RAD are up-regulated proteins were identified as major hubs in Ab-resistance cells. YWHAZ, DDB1, HSPB1, S100A9, and ANXA2 were found to be major hubs among down-regulated proteins, while SERPINH1, AHCY, FBP1, TXNRD1, PSMA6, HSP90B1, and PKM were found to be major hubs among up-regulated proteins in Pb-resistance cells. (Fig. 7. A, B, C, and D). The miR-Net tool was used to analyse miRNA-protein interactions and find an inverse association between miRNAs and their targeted DEPs. In Ab-resistance cells, hsa-mir-1-3p, hsa-mir-155-5p, and hsa-mir-24-p with down-regulated proteins and hsa-mir-155-5p, hsa-mir-23b-3p, hsa-mir-124-3p, and has-mir-30a-5p with up-regulated DEPs showed an inverse relationship. hsa-mir-155-5p, has-mir-1-3p, hsa-mir-20a-5p, and hsa-mir-182-5p with down-regulated proteins and hsa-mir-130a-3p, hsa-mir-101-3p, hsa-mir-19a-3p, hsa-mir-34a-5p, and hsa-let-7a-5p with up-regulated proteins showed an inverse correlation in Pb-resistance cells. Discussion Drug-resistant MCF-7 cells showed to tolerate the drug at higher concentrations compared to control cells. Microscopic images of PI-stained cells confirmed the findings.MDR-1 and ABCG-2 are xenobiotic transporters that help cells eliminate toxins. These proteins have been linked to the phenotype of drug resistance in various cancers [ 18 , 19 ].Increased MDR-1 and ABCG-2 expression in MCF-7 cells exposed with Ab and Pb for a long-time result in drug efflux, which may be one of the reasons for drug resistance in these cells. As shown in Fig. 2B, C, and D, the drug-resistance models were re-confirmed by increased expression of survival (Bcl-2 and MCL-1) genes and suppressed expression of pro-apoptotic (BAX, BAD, Caspase-3, and PARP1) genes.Bcl-2 blocks the intrinsic apoptosis signal by inhibiting Bax and Bak interactions on the mitochondrial outer membrane. Drug-resistant, cells have elevated levels of Bcl-2 and MCL-1 [ 20 , 21 ]. Estrogen activates ER, which leads to DNA replication and cell division, as encoded by the ESR1 gene [ 22 ].Increased ESR1 expression suggests that it can contribute to therapy resistance. CDK4 and CDK6 are targeted by Ab and Pb, which stimulates cyclin-D1 and promotes cell cycle progression. Increased CDK4/6 and cyclin D1 expression in our cells promotes successful cell division, which is a hallmark of drug resistance. The roles of proteins in therapy resistance in Ab-R-MCF-7 and Pb-R-MCF-7 cells are described in Supplementary table 2–5. DEPs are manually curated from the PubMed literature search engine to determine their molecular functions, roles in cancer progression, therapy resistance, and prognostic importance (see Table 1 ). NUDT5 is linked to a poor prognosis and low overall survival in clear cell renal cell carcinoma [ 23 ]. PEPD binds to Her-2 and inhibits EGFR signaling, resulting in cancer cell growth inhibition [ 24 ]. Lower expression of GGCT, a crucial component of the GSH-pathway, has been linked to chemo-resistance [ 25 ]. Inflammatory BC has an inverse association between ABAT expression and therapy resistance [ 26 ]. A high level of ATP1B1 is linked to metastasis and it is an essential energy transfer system for cells [ 27 ]. Low levels of SELENBP1 in ER + ve BC result in poor survival and selenium tolerance [ 28 ] (Supplementary table 2 and 4) and Table 1 . PSMB is a group β-subunit of the 20S proteasome (PSMB4 and PSMB5), and α-subunit PSMA7 are involved in the proteolytic degradation of intracellular proteins. PSMB4 overexpression promotes cell cycle progression from G1 to S phase and cell viability through NF-B signaling [ 29 ]. A high PSMB5 level suggests a poor prognosis [ 30 , 31 ]. PSMA7 levels in gastric cancer have been related to invasion, metastasis, and poor prognosis [ 32 ]. VTN is a part of the extracellular matrix that promotes integrin signaling. VTN, which is downstream of VEGF/VEGFR and PI3K/AKT signaling, promotes cell migration and metastasis in breast cancer [ 33 , 34 , 35 ]. SBSN is an oncoprotein that promotes tumorigenicity by increasing Wnt/β-catenin signaling [ 36 , 37 ]. The mitochondrial enzyme HSB17B10 is responsible for the oxidation of steroids, alcohol, and fatty acids. In osteosarcoma, a high level of HSD17B10 indicated a poor response to chemotherapy [ 38 ]. Chemo-resistance is caused by the tumour microenvironment facilitating CD9-mediated crosstalk between mesenchymal stem cells and BC cells via CCL5, CCR5, and CXCR12 [ 39 ]. PDIA3 expression in the tumor microenvironment is high, which favors invasion and metastasis [ 40 , 41 ].GLUT1 proteins encoded by SLC2A1 aid glucose transport. Hypoxia inducing factor-1(HIF-1) is activated as breast cancer grows aggressively. Due to hypoxic environments, HIF1 triggers GLUT1 expression [ 42 , 43 ].Under hypoxic conditions, HIF-1 also activates CD47 transcription. In BC, CD47 retains stemness, induces EMT and leads to a poor prognosis [ 44 , 45 ]. HIST1H2BN is a part of the H2B protein family whose unregulated expression causes cancer and is a predictor of poor prognosis in ovarian cancer [ 46 ]. Hemoglobin beta (HBB) is an oxygen transporter that promotes BC cell aggression and a poor prognosis [ 48 ]. By releasing FOXC1 transcription factor, FLNB exon 30 skipping (gene splicing) induces EMT, and expression of EMT gene signature induces tumorigenicity [ 49 ]. Cancer stem cell survival and proliferation are influenced by redox control and oxidative stress. Peroxiredoxin 4 (PRDX4) catalyses hydrogen peroxide and regulate hydrogen peroxide signaling leading to tumor recurrence and therapy resistance [ 50 , 51 ]. BRD4 is a downstream target of voltage-dependent anion channels (VDAC1), which are found on the outer mitochondrial membrane. VDAC1 overexpression causes breast cancer proliferation, is associated with a poor prognosis, and is linked to therapy resistance to BRD inhibitors in BC [ 50 ]. The GOT2 promoter is regulated by the ZBRK1 and BRCA1 complex, which binds to it and regulates its expression. Impaired complex binding contributes to uncontrollable expression, which promotes cell proliferation [ 52 ]. In lapatinib-resistant BC, a high level of HSPA5 was found [ 53 , 54 ]. SERPINH1 is a chaperone protein, and its high expression has been linked to a more aggressive phenotype of gastric cancer, implying a poor prognosis [ 36 , 37 ]. miR-5195-3p targets EIF4A2, which can reverse chemoresistance in TNBC cells [ 56 ]. FTH1 is a subunit of the ferritin complex that promotes EMT in doxorubicin-resistant breast cancer [ 57 ]. Vimentin (VIM) is a member of the intermediate filament protein family that contributes to cell invasion, migration, and signaling. VIM expression is promoted by Erk signaling activation. Its increased expression has been identified in methotrexate and tamoxifen-resistant BC. [ 58 , 59 ]. GO-terms of down-regulated DEPs in Ab and Pb-resistant cells were as follows: biological processes were identified asapoptosis, cell adhesion, small molecule catabolic processes, cofactor metabolic processes, nucleotide metabolic processes, and carbohydrate metabolic processes, etc.The cell surface, mitochondria, endoplasmic reticulum, extracellular matrix, and chaperone complex, among other cellular components were established. Signaling pathways such as estrogen, metabolic pathway and pyruvate metabolism, gluconeogenesis, TCA-cycle, and MAPK-pathway were established (Fig. 4. A). Up-regulated DEPs in Ab and Pb resistance cells are linked to biological processes such as cell activation, generation of precursor metabolites, and energy, lung development, cellular response to chemical stimuli, response to hypoxia, cellular response to cytokine stimulus and small molecule metabolic processes. Cellular components localized in the mitochondrial membrane, cytoplasmic vesicle, extracellular matrix, secretory-vesicle and outer membrane. Signaling pathways such as metabolic pathways, insulin signaling, Choline metabolism in cancer, CGMP-PKG-signalling, Gluconeogenesis, ECM receptor interaction and MAPK signaling, NOTCH signaling, Wnt/β-catenin, PI3K/AKT/mTOR, JAK-STAT, TGF-β signaling these terms are more active in tumor progression, cancer recurrence and therapy resistance. During the treatment of a breast cancer patient, tumor cells can develop therapy resistance to Abemaciclib and Palbociclib drugs. In Ab-resistant cells, a set of down-regulated proteins (NUDT5, PEPD, ABAT, ATP1B1, GGCT, SELENBP1, M6PR, STOM, and ACTN1) as well as up-regulated proteins (SBSN, HSD17B10, CD9, PDIA3, PSMB4, SLC2A1, and VTN) may be useful for prognosis and may be a new drug target.Similarly, in Pb-resistant cells, a series of down-regulated proteins (NUDT5, PEPD, and GGCT) as well as up-regulated proteins (CD47, HIST1H2BN, LMNA, VTN, PSMB5, HBB, PSMA7, FLNB, PRDX4, VDAC1, GOT2, HSPA5, SERPINH1, EIF4A2, FTH, and VIM) may be useful for prognosis and may be a new drug target. However, further confirmation of these DEPs for their prognostic and therapeutic roles in BC would involve either an in vivo analysis or a study on clinical samples. Many miRNAs need to be confirmed for their functional role in therapy resistance, according to a miRNA-protein network review of DEPs. Abbreviations DEPs: Differentially expressed proteins CDK: cyclin-dependent kinase, PI: Propidium Iodide, Ab-R-MCF-7 Abemacilcib resistance MCF-7 Pb-R-MCF-7: Palbociclib resistance MCF-7, Ab: Abemaciclib, Pb: Palbocilcib and BC: Breast cancer. Declarations Authors’ contributions Conceptualization: Binayak Kumar, Data curation: Ram Krishna Sahu and Ragini Singh, Funding acquisition: Binayak Kumar, Project administrator and Supervision: Suresh T. Hedau, Visualization: Ashutosh Singh, Peeyush Prasad, Writing original draft: Binayak Kumar. Writing, review and editing Binayak Kumar, Srikrishna Jayadev M and Suresh T. Hedau. Acknowledgments I want to thank the Indian Council of Medical Research for providing Post-Doctoral fellowship, National Institute of Cancer Prevention and Research for providing lab facility to conduct proposed work. I want to thank School of Life Sciences, Shiv Nadar University to conduct part of work there. I want to thank MASSFIITB facility at IIT Bombay, Mumbai for conducting non-labelled global proteome profiling. Funding The Project was supported by the Indian Council of Medical Research, India in 2018, No. 3/1/3/PDF (17)/2017-HRD. Conflict of interest: Authors declare that they have no conflict of interest. Supplementary data Supplementary Table 1: List of genes and their primer sequences. Supplementary Table 2: List of down-regulated proteins in Ab-R-MCF-7 and their references. Supplementary Table 3: List of Up-regulated genes in Ab-R-MCF-7 cells and their references. Supplementary Table 4: List of down-regulated Proteins in Pb-R-MCF-7 cells and their references. Supplementary Table 5: List of Proteins up-regulated in Pb-R-MCF-7 cells and their references. Ethics approval and consent to participate. Not Applicable. 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SupplimentaryTable2.docx Supplementary Table 2: List of down-regulated proteins in Ab-R-MCF-7 and their references. SupplimentaryTable3.docx Supplementary Table 3: List of Up-regulated genes in Ab-R-MCF-7 cells and their references. SupplimentaryTable4.docx Supplementary Table 4: List of down-regulated Proteins in Pb-R-MCF-7 cells and their references. SupplimentaryTable5.docx Supplementary Table 5: List of Proteins up-regulated in Pb-R-MCF-7 cells and their references. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-556331","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":29318533,"identity":"4d40d8bf-a44b-4084-8ac4-cbfd6d9e8bba","order_by":0,"name":"Binayak Kumar","email":"","orcid":"","institution":"National Institute of Cancer Prevention and Research","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Binayak","middleName":"","lastName":"Kumar","suffix":""},{"id":29318534,"identity":"df365625-4cf5-4594-91aa-8ef612575257","order_by":1,"name":"Peeyush Prasad","email":"","orcid":"","institution":"SGRH: Sir Ganga Ram Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Peeyush","middleName":"","lastName":"Prasad","suffix":""},{"id":29318535,"identity":"56c1b412-d06c-43c9-9f2a-81f234b0afa4","order_by":2,"name":"Ragini Singh","email":"","orcid":"","institution":"National Institute of Cancer Prevention and Research","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ragini","middleName":"","lastName":"Singh","suffix":""},{"id":29318536,"identity":"283e96c3-3cd2-4283-b6cf-5befc2513723","order_by":3,"name":"Ram Krishana Sahu","email":"","orcid":"","institution":"National Institute of Cancer Prevention and Research","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ram","middleName":"Krishana","lastName":"Sahu","suffix":""},{"id":29318537,"identity":"9262570d-a76f-45ab-8046-4a8b8c51b066","order_by":4,"name":"Ashutosh Singh","email":"","orcid":"","institution":"Shiv Nadar University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ashutosh","middleName":"","lastName":"Singh","suffix":""},{"id":29318538,"identity":"9b4da92e-7995-4495-ae85-0b9ec3b65113","order_by":5,"name":"Srikrishna Jayadev M","email":"","orcid":"","institution":"Shiv Nadar University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Srikrishna","middleName":"Jayadev","lastName":"M","suffix":""},{"id":29318539,"identity":"b9be32ee-0c84-4e8d-96eb-61955c55d19a","order_by":6,"name":"Suresh Hedau","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYLACxgaGBAYQ+gDiMZOihXEGyVqYeYhRLT8j9+HDnzsY8vjZk59J2/yySWxg5z2AV4vBjXRjY94zDMWSPc/MpHP70hIbmPkS8GuRSGOTZmxjSNxwIwGopeewMdB5BgQclsb+8ydQy/4b6d+kLYnRwnAjjY2BF2SLRI6ZNMOPw3IEtRicecYszdsmkTjjzJtiy96GNDk2gg5rT2P8+LPNJrG/PX3jjR9/bHj4+c8QcBgESEAoYDgwsBGjHgn8IVH9KBgFo2AUjAgAAMcaP6asL1LJAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-9576-1341","institution":"Institute of Cytology and Preventive Oncology: National Institute of Cancer Prevention and Research","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Suresh","middleName":"","lastName":"Hedau","suffix":""}],"badges":[],"createdAt":"2021-05-24 06:24:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-556331/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-556331/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":9670349,"identity":"1fc13ca5-ae88-4e86-849c-74ddd40974cc","added_by":"auto","created_at":"2021-05-27 15:29:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":683315,"visible":true,"origin":"","legend":"Cell-viability assay: (A) Ab-resistant and sensitive MCF-7 cells treated with Ab for 48 hrs. (B) Pb-resistant and sensitive MCF-7 cells treated with Pb for 72 hrs. PI-Staining and microscopy at 20x magnification: (C) MCF-7 control, MCF-7 Ab treated, and Ab-R-MCF-7 Ab treated for 48 hrs (D) MCF-7 control, MCF-7 Pb treated, and Pb-R-MCF-7 cells Pb treated for 72 hrs (E) Cells picked-up PI-stain in C and D samples.","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-556331/v1/ff97d8a1ff9d9b636ef060e1.png"},{"id":9669966,"identity":"4115e132-5521-4780-bbfe-639883a3cc2c","added_by":"auto","created_at":"2021-05-27 15:26:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":59815,"visible":true,"origin":"","legend":"mRNA expression by real-time-qPCR. (A) MDR-1 and ABCG-2 genes expression in MCF-7 control, MCF-7 Ab or Pb treated and Ab-R-MCF-7 Ab or Pb treated. (B) BCL-2 and MCL-1 expression in MCF-7 control, MCF-7 Ab or Pb treated and Ab-R-MCF-7 Ab or Pb treated, (C) BAX, BAD, CASP-3 and PARP1 expression in MCF-7 control, MCF-7 Ab treated and Ab-R-MCF-7 Ab treated (D) BAX, BAD, CASP-3 and PARP1 expression in MCF-7 control, MCF-7 Pb treated and Pb-R-MCF-7 Pb treated (E) ESR-1, CDK-4, CDK-6 and CYCLIN D1 expressions in MCF-7 control, MCF-7 Ab treated and Ab-R-MCF-7 Ab treated and (F) ESR-1, CDK-4, CDK-6 and CYCLIN D1 expressions in MCF-7 control, MCF-7 Pb treated and Pb-R-MCF-7 Pb treated.","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-556331/v1/da119d891a87fba5082aef90.png"},{"id":9669958,"identity":"08aff78d-5d97-4097-b7f8-ede01630312e","added_by":"auto","created_at":"2021-05-27 15:26:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":309305,"visible":true,"origin":"","legend":"Differential expression of proteins. (A) Ab-R-MCF-7 vs MCF-7 control and (B) Pb-R-MCF-7 vs MCF-7 control. Venn-diagram of two set of differentially expressed proteins Ab-R-MCF-7 Vs control (F2/F1 and F5/F4) and Pb-R-MCF-7 Vs MCF-7 control (F3/F1 and F6/F4) in (C) down-regulated and (D) up-regulated proteins.","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-556331/v1/1c63350118ab3db0a7e88cc0.png"},{"id":9670348,"identity":"ae2f2f69-e141-43dc-909a-e058c36fbf49","added_by":"auto","created_at":"2021-05-27 15:29:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":77353,"visible":true,"origin":"","legend":"KEGG pathway and GO term analysis of differentially expressed proteins in Ab-R-MCF-7 cells compare to MCF-7 control cells (A) Down-regulated protein and (B) Up-regulated protein.","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-556331/v1/aa242a6daaa48f5de9b5d4f5.png"},{"id":9670346,"identity":"39ca06c9-8030-47ed-b79e-54d2208be97d","added_by":"auto","created_at":"2021-05-27 15:29:30","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":77876,"visible":true,"origin":"","legend":"KEGG pathway and GO term analysis of differentially expressed proteins in Pb-R-MCF-7 cells compare to MCF-7 control cells (A) Down-regulated proteins and (B) Up-regulated proteins.","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-556331/v1/f4ef1eb0e746c37fd6c2292e.png"},{"id":9670814,"identity":"d3756830-73ac-4b2f-b4a3-3b4b3b8e4edf","added_by":"auto","created_at":"2021-05-27 15:32:31","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":675976,"visible":true,"origin":"","legend":"Reactome pathway analysis of differentially expressed proteins. (A) Common down-regulated Proteins in Ab-R-MCF-7/MCF-7 control in Set1 and Set 2 (Cut off 0.89), (B) Common up-regulated Proteins in Ab-R-MCF-7/MCF-7 control in Set1 and Set 2 (Cut off 1.3) (C) Common Protein down-regulated in Ab-R-MCF-7/MCF-7 control (Cut off 0.89) and (D) Common proteins up-regulated in Ab-R-MCF-7/MCF-7 control (Cut off 1.3).","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-556331/v1/9ee31c71b7b24a7db542d7ac.png"},{"id":9670815,"identity":"62e83195-c588-4eb3-8fbf-8b271a1bbda7","added_by":"auto","created_at":"2021-05-27 15:32:31","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1419826,"visible":true,"origin":"","legend":"PPI-Network analysis (A) Common down-regulated Proteins in Ab-R-MCF-7/ MCF-7 control in Set1 and Set 2 (Cut off 0.89) (B) ) Common up-regulated Proteins in Ab-R-MCF-7/MCF-7 control in Set1 and Set 2 (Cut off 0.89) Interaction study (C) Common Protein down-regulated in Ab-R-MCF-7/MCF-7 control and (D) Common proteins up-regulated in Ab-R-MCF-7/MCF-7 control (Cut off 1.3).","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-556331/v1/540fdf51a94dbb06740ee28e.png"},{"id":9670353,"identity":"b656c95e-fbd6-4e96-b602-0650fdb8187f","added_by":"auto","created_at":"2021-05-27 15:29:31","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":571275,"visible":true,"origin":"","legend":"Common proteins and miRNA Minimum-network for differentially expressed common proteins in two biological set of experiment and their known miRNAs which target mRNA coding for the respective protein. (A) down-regulated proteins in Ab-R-MCF-7/MCF-7 control (F2/F1 and F5/F4) (Cut off 0.89), (B) up-regulated proteins in Ab-R-MCF-7/MCF-7 control (F2/F1 and F5/F4), (Cut off 1.3), (C) down-regulated proteins in Pb-R-MCF-7/MCF-7 control (F3/F1 and F6/F4) and (D) up-regulated protein in Pb-R-MCF-7/MCF-7 control (F3/F1 and F6/F4) (Cut off 1.3).","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-556331/v1/b4fccdad29b8ed33ebb086a4.png"},{"id":13695318,"identity":"489ad415-a359-4b68-b0bb-e24804fd3dae","added_by":"auto","created_at":"2021-09-17 12:57:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3798036,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-556331/v1/2dde0954-3317-4e2d-98b4-e32a49caf820.pdf"},{"id":9670347,"identity":"f2163d3a-b986-4cba-9910-a0232c408988","added_by":"auto","created_at":"2021-05-27 15:29:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16132,"visible":true,"origin":"","legend":"Supplementary Table 1: List of genes and their primer sequences.","description":"","filename":"SupplimentaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-556331/v1/192d5227e03a7bc50f40f115.docx"},{"id":9670969,"identity":"aa5a0988-6426-48ab-8d63-8aeea2ece22d","added_by":"auto","created_at":"2021-05-27 15:35:31","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":17900,"visible":true,"origin":"","legend":"Supplementary Table 2: List of down-regulated proteins in Ab-R-MCF-7 and their references.","description":"","filename":"SupplimentaryTable2.docx","url":"https://assets-eu.researchsquare.com/files/rs-556331/v1/7edd01069fdaafec272d6d66.docx"},{"id":9670812,"identity":"1d379106-e041-4b4b-895e-005272e648dd","added_by":"auto","created_at":"2021-05-27 15:32:31","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":21493,"visible":true,"origin":"","legend":"Supplementary Table 3: List of Up-regulated genes in Ab-R-MCF-7 cells and their references.","description":"","filename":"SupplimentaryTable3.docx","url":"https://assets-eu.researchsquare.com/files/rs-556331/v1/a47c4d32b7a0c1b006b9c1a9.docx"},{"id":9669968,"identity":"eaecfea7-9867-470f-9138-fbdb2690331b","added_by":"auto","created_at":"2021-05-27 15:26:32","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":13706,"visible":true,"origin":"","legend":"Supplementary Table 4: List of down-regulated Proteins in Pb-R-MCF-7 cells and their references.","description":"","filename":"SupplimentaryTable4.docx","url":"https://assets-eu.researchsquare.com/files/rs-556331/v1/a818cd3342c5e7d5098c4318.docx"},{"id":9670355,"identity":"d12b5093-97cb-434f-bd93-80783b99150a","added_by":"auto","created_at":"2021-05-27 15:29:31","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":36350,"visible":true,"origin":"","legend":"Supplementary Table 5: List of Proteins up-regulated in Pb-R-MCF-7 cells and their references.","description":"","filename":"SupplimentaryTable5.docx","url":"https://assets-eu.researchsquare.com/files/rs-556331/v1/0a0c987b6d7ee769d74ff2e7.docx"}],"financialInterests":"","formattedTitle":"Role of Differentially Expressed Proteins in Acquired Resistance to Cdk4/6 Inhibitor in Breast Cancer","fulltext":[{"header":"Introduction","content":" \u003cp\u003eBreast cancer is the second most commonly diagnosed cancer in the world, after lung cancer; however, it is the most prevalent in the Indian population [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Breast cancers are classified by the presence or absence of a surface receptor, that is, the estrogen receptor (ER), the progesterone receptor (RP), and the human epidermal growth factor receptor 2 (HER-2). Radiotherapy, chemotherapy, hormone therapy, and targeted therapy are all common treatment methods [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. To treat primary and metastatic breast cancer, chemotherapy drugs such as 5-fluorouracil, methotrexate, cyclophosphamide, doxorubicin, and epirubicin are used. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].ER inhibitors (tamoxifen, letrozole, and fulvestrant) are used to treat estrogen-positive breast cancer in hormone therapy. Tumor cells develop tolerance to drug cytotoxicity, resulting in the therapeutic resistance phenotype, which contributes to disease progression and recurrence. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Tumor cells triggered other pathways essential for their survival in the process of acquiring the resistance trait [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].The investigation of the molecular mechanisms underlying therapeutic resistance in cancer care has resulted in a transition in drug development toward targeted therapy.By inhibiting certain proteins necessary for tumor cell proliferation and survival, targeted therapy prevents cancer progression. Proteins such as receptor tyrosine kinase, cytokine receptors, and intracellular serine-threonine kinases can be targeted.\u003c/p\u003e \u003cp\u003eAbemaciclib (Ab) and Palbociclib (Pb) are two synthetic (small-molecule) inhibitors of cyclin-dependent kinase 4 and 6 (CDK4 and CDK6) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. CDK 4 and 6 are intracellular, serine-threonine protein kinase enzyme associated with cell-cycle progression from G1 to S-phase. Inhibition of CDK4 and CDK6 will halt the G1 phase of the cells. The U.S. FDA approved Palbociclib in 2016, while Abemaciclib approved in 2017 to treat advanced breast cancer with ER, PR positive and HER2-negative receptors [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Deregulation of CDK4/6 causes uncontrolled cell proliferation, which may occur due to amplification of cyclin D1, a gain of CDK4/6, loss of p18, elevated Rb1, and loss of p16, etc. [\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. CDK4/6 inhibitors have emerged as breakthrough for breast cancer treatment. Recently, resistance to CDK4/6 inhibitors has been identified as a concern in the management of breast cancer [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. PI3K-AKT-mTOR signal mediated resistance to CDK4/6 inhibitors is reported for a similar medicine ribociclib. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, resistance mechanisms for Ab and Pb drugs in breast cancer therapy have not been reported.\u003c/p\u003e \u003cp\u003eThis study aims to develop drug-resistant cell models for the drugs Abemaciclib and Palbociclib in the breast cancer cell lineage and further assess the molecular changes involved in resistance.\u003c/p\u003e "},{"header":"Materials And Methods","content":"\u003cp\u003eAbemaciclib and Palbociclib drugs were purchased from Selleck Chem, USA. MCF-7 was bought from NCCS Pune in India. Cell culture media (Lonza), FBS (Gibco life technology), Plastic-wares for cell-culture (Corning), 96-well plate for real-time-qPCR of Thermo Scientific, RNA isolation kit (Qiagen), cDNA synthesis kit (Takara), 2x SYBR Green-Master mix (Promega) and Primers synthesized from Imperial Life Sciences Pvt. Ltd. Both, control and resistant cells were maintained in high glucose DMEM medium supplemented with 10% FBS and 1% Penicillin and streptomycin antibiotics in 5% CO2, humidified air and at 37 0C temperature. To develop resistance models, MCF-7 cells were treated with Abemaciclib and Palbociclib drugs in separate T-25 flasks at initial 5 nm concentrations. The drug doses were gradually increased up to 200 nm concentrations and keep maintaining cells at the same.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell-viability Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMCF-7 and continued drug-treated cells called Ab-R-MCF-7 and Pb-R-MCF-7 with Ab and Pb drug, respectively, are seeded in a 96-well plate with 2.\u0026nbsp;5x10\u003csup\u003e4\u003c/sup\u003e cells count in each well. After 24 h of incubation, cells were treated with the respective drug from 100 nm to 6 \u0026mu;M concentrations in drug-sensitive MCF-7 cells and up to 8\u0026mu;M for drug-resistant MCF-7 cells for 48 and 72 h. Add 100 \u0026micro;l of 0.5 \u0026mu;g/\u0026mu;l MTT to each well and incubated for 2.5 h than lysed the cells with detergent (DMSO). OD-value was measured at 595 nm wavelength into micro-plate reader and percent cell viability was calculated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePI-Staining-microscopy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMCF-7, Ab-R-MCF-7, and Pb-R-MCF-7 cells were seeded (4x10\u003csup\u003e4\u003c/sup\u003e cells/well) in a 12-well plate and incubated into a CO2 incubator for 24 hrs. Cells were treated with Ab and Pb of 1.5 and 2.0 \u0026mu;M concentrations for 48 and 72 h, respectively. Cells were stained with 25 \u0026mu;g/ml propidium iodide (PI) for 15 min. PI-stained cells exposed to green mono-chromatic light and red-emission light were captured along with white light. Images were taken on 20x magnification into a Nikon inverted fluorescence microscope.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReal-Time-qPCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMCF-7, Ab-R-MCF-7, and Pb-R-MCF-7 cells were seeded (7.5x104 cells/well) into 6-well plates and incubated into CO2 incubator for 24 hrs. Cells were treated with Ab (0.25 \u0026mu;M) and Pb (2.0 \u0026mu;M) drugs for 48 h. Cells detached and washed with cold PBS. Total RNA is extracted from cells palette using total RNA isolation kit followed the kit protocols. The quantity and quality of total RNA was measured by Nano-Drop. 0.5 \u0026mu;g total RNA is used for cDNA synthesis following the protocols mentioned in cDNA synthesis kit. Real-time-qPCR was performed in triplicate using Bio-Red connect real-time-qPCR system using the 2X Master mix of SYBR Green (from Promega) and gene-specific primers.18S gene was selected as an internal control for normalization. Relative quantity (RQ) - value for each gene were analyzed for each sample from their Ct-value. The list of genes and primer sequences is listed in Supplemental Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLabelle free-Proteome-Orbitrap-Fusion MS-MS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSamples were prepared for a proteomics experiment for MCF-7 control, Ab-R-MCF-7 and Pb-R-MCF-7 cells. Cells were seeded (7.5 x 10\u003csup\u003e4\u003c/sup\u003e cells/well) in T-25 flasks, incubated in a CO\u003csub\u003e2\u003c/sub\u003e incubator for 48 h, after those cells were harvested and lysed in a cell lysis buffer (6 M urea, 2M thiourea, 2% CHAPS and 0.5% SDS) containing 1% protease inhibitor cocktail. Cell samples were sonicated on ice for 30 sec pulse with 10 sec gaps for 5 times, centrifuged the cell-lysate at 12000 rpm for 15 min at 4\u003csup\u003e0\u003c/sup\u003eC than supernatant was collected. Proteins were estimated using Bradford reagent (Sigma) and measured the OD value in the microplate reader at 595 nm wavelength light exposed. Protein quality was checked by Coomassie blue after running SDS-PAGE. Protein samples were sent to the proteomics laboratory, MASSFIITB facility supported by DBT (BT/PR13114/INF/22/206/2015), IIT Bombay, Mumbai. The technique was used for proteomics is labelled free-Proteome- Orbitrap-Fusion MS-MS. The protein search is performed against the Homo sapiens database downloaded from UniProt using Proteome Discoverer 2.2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBioinformatics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBioinformatics tools were used to analyse proteomics data. Venny tool used to select common proteins in replicating data. The reactome pathway database was used to find the role of proteins in different reaction pathways. Gene Ontology (GO) analysis was performed using the STRING database. A network analyst tool used to find the proteins hub. Generic PPI was analysed without any filter, but the subnetwork having maximum seed. miR-Net tool used for miRNA-Gene interaction analysis to explore the post-transcriptional regulation of gene expressions. Here, identified protein IDs were searched against the background of breast cancer tissues. The minimum network option was selected for the analysis.\u003c/p\u003e"},{"header":"Results","content":" \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eIncreased tolerance to Abemaciclib and Palbociclib in Ab-R-MCF-7 and Pb-R-MCF-7 cells\u003c/h2\u003e \u003cp\u003eMCF-7 cells were treated with Abemaciclib and Palbociclib and the inhibitory concentration values were calculated. Cells treated with Ab exhibited an IC50 value of 1.5 \u0026micro;M at 48 h and cells treated with Pb showed an IC50 3.0 \u0026micro;M after 72 h. These sensitive MCF-7 cells were treated continuously with an increasing concentration ranging from 0.1 to 8 \u0026micro;M. As shown in Figure-1 cytotoxicity was assessed in the continuously drug-exposed cells and it was found that Ab treated cells could tolerate the drug up to a concentration of 7.0 \u0026micro;M after 48hrs and the Pb treated cells could tolerate up to 7.5 \u0026micro;M after 72 h. When increased IC50 values were compared to the sensitive cells could survive higher drug concentration, indicating that these cells develop resistance to the drugs.\u003c/p\u003e \u003c/div\u003e \n\u003ch2\u003eReduced Cell Death In Drug-resistant Cells\u003c/h2\u003e\n \u003cp\u003eFurther to reconfirm the cytotoxicity results obtained in the above experiments Propidium Iodide exclusion experiment was performed. Control-sensitive-cells and the Ab and Pb-resistant MCF-7 cells were treated with the respective drug for 48 h, and stained with propidium iodide. Control-MCF-7 cells without any drug treatment looked healthy and, few cells stained red with PI, whereas the MCF-7 cells treated with Ab and Pb exhibited stressed phenotype and a great number of cells picked-up PI-stain. However, only a few drug-resistant cells picked up PI stain and the rest of the cells looked healthier (Fig.\u0026nbsp;1. C, D, E). Again, confirming the tolerance of the resistant cells to these drugs.\u003c/p\u003e \n\u003ch2\u003eUp-regulation Of Pro-survival And Down-regulation Of Apoptotic Genes\u003c/h2\u003e\n \u003cp\u003eTo check the cell death at the mRNA level the expression of pro-survival and apoptosis-associated genes were checked. qPCR results as shown in Fig.\u0026nbsp;2B, the expression of pro-survival genes BCL-2 and MCL-1 were found to be up-regulated in resistant cells. BCL-2 expression was enhanced by 3.13 and 1.60-fold in Ab-RMCF-7 and Pb-R-MCF-7 cells, respectively, whereas, MCL-1 were 4.90 and 5.80-fold higher expression in Ab-R-MCF-7 and Pb-R-MCF-7 respectively as compare to the control. Pro-apoptotic genes BAX, BAD, Casp-3 and PARP1 expressions in Ab-R-MCF-7 were similar to the control cells. They exhibited a change of 1.04, 0.80, 1.14, and 1.28 folds, respectively. However, in Ab-treated drug-sensitive cells, these gene expressions were found to be 2.25, 2.17, 2.14, and 5.17-folds higher, respectively (Fig.\u0026nbsp;2. C). BAX, BAD, Casp-3 and PARP1 expression in Pb-RMCF-7 was 1.15, 0.95, 1.0, and 1.20-fold changed, respectively, however, in Pb-treated, drug-sensitive cells, these were 2.25, 2.15, 2.51, and 3.86-fold higher, respectively, compared to the control (Fig.\u0026nbsp;2. D).\u003c/p\u003e \u003cp\u003eMDR-1 and ABCG-2 are two efflux proteins that are involved in drug expulsion and have been linked to cancer cell survival and resistance evolution. As depicted in Fig.\u0026nbsp;2A. MDR1 expression was found to be identical in control and drug-treated responsive cells. It was shown to be increased 3.0-fold and 8.2-folds in Ab-R-MCF-7 and Pb-R-MCF-7 cells, respectively. The expression of the ABCG2 gene was comparable in control and drug-treated responsive cells, but it was 4.0 and 5.9 times higher in Ab-RMCF-7 and Pb-R-MCF-7 cells, respectively.\u003c/p\u003e \u003cp\u003eESR1 genes are overexpressed in cancer cells, especially in breast cancer, and both Ab and Pb are CDK4/6 inhibitors. In this analysis, the expression of ESR-1, CDK-4, and CDK-6 in control and responsive cells was found to be identical, whereas the level of cyclin D1 decreased 0.55-fold.However, ESR-1, CDK-4, CDK-6, and Cyclin D1 genes increased 11.9, 3.6, 15.5, and 4.1-fold in Ab-resistant cells, respectively. In Pb-responsive cells ESR-1, CDK-4, and CDK-6 gene expression was unchanged compared to the controls, whereas, Cyclin-D1 was 0.43-fold down-regulated. However, in Pb-resistant cells, ESR-1, CDK-4, CDK-6, and Cyclin-D1 gene expression were increased 20.3, 2.8, 6.4, and 6.0-fold, respectively (Fig.\u0026nbsp;2. F). As a result, the upregulation of survival genes and the downregulation of apoptotic genes in qPCR results illustrate how these molecular modifications facilitate cell survival and drug tolerance.\u003c/p\u003e \n\u003ch2\u003eDifferentially Expressed Proteins (Deps) In Global-profiling\u003c/h2\u003e\n \u003cp\u003eGlobal proteome profiling was used to assess altered protein expressions in Ab and Pb-resistant MCF-7 cells. In Ab-R-MCF-7 cells, 237 proteins were identified as DEPs, with 162 proteins were down-regulated and 75 being up-regulated. In Pb-R-MCF-7 cells, 239 proteins were identified as DEPs, with 153 proteins were down-regulated and 86 being up-regulated (Fig.\u0026nbsp;3A, B). Venn-diagram analysis in Fig.\u0026nbsp;3. C and D, has shown common proteins among different set of samples (Ab-RMCF- 7/MCF-7 control (Set1 F2/F1 and Set-2 F5/F4) and Pb-R-MCF-7/MCF-7control (Set-1 F3/F1 and Set-2 F6/F4)).DEPs in Ab-R-MCF-7 and Pb-R-MCF-7 cells were manually curated from the PubMed literature search engine, and their cancer-related functions were revealed. Down-regulation of NUDT5, PEPD, ABAT, ATP1B1, GGCT, SELENBP1, M6PR, STOM, and ACTN1 proteins in Ab-R-MCF-7 cells has been identified as a prognostic indicator or a new drug target for breast cancer. (Supplementary Table\u0026nbsp;2 and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The upregulation of SBSN, HSD17B10, CD9, PDIA3, PSMB4, SLC2A1, and VTN proteins in Ab-R-MCF-7 cells has been identified as a poor prognostic indicator or involved in acquired drug resistance, and has been proposed as a novel drug target for BC treatment (Supplementary Table\u0026nbsp;3 and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). NUDT5, PEPD, and GGCT proteins, which have been identified as prognosis or drug-sensitive markers, were downregulated in Pb-R-MCF-7 cells (Supplementary Table\u0026nbsp;4 and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). CD47, HIST1H2BN, LMNA, VTN, PSMB5, HBB, PSMA7, FLNB, PRDX4, VDAC1, GOT2, HSPA5, SERPINH1, EIF4A2, FTH1, and VIM proteins have been found to be up-regulated in Pb-R-MCF-7 cells, which are associated with poor prognosis or drug resistance markers (Supplementary Table\u0026nbsp;5 and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e, Differentially expressed proteins (DEPs) in drug resistance MCF-7 vs MCF-7 control with p-value\u0026thinsp;\u0026le;\u0026thinsp;0.05 showed their molecular functions and role in BC.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDEPs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFold\u003c/p\u003e \u003cp\u003eChange\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMolecular function\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEarlier Reports\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAb-R-MCF-7 Vs MCF-7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBSN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUpregulated SBSN enhances Wnt/β-catenin signalling and promote proliferation and tumorigenicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36\u003c/p\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePDIA3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCatalyzes the rearrangement of -S-S -bonds in proteins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh expression of PDIA3 drive production of secretory proteins and create favourable tumor microenvironment for invasion and metastasis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntegral membrane protein associated with integrins, regulates platelet activation and aggregation, and cell adhesion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTumor microenvironment facilitate CD9 mediated crosstalk between bone marrow-derived mesenchymal stem cells and breast cancer cells (via CCL5, CCR5, and CXCR12) that contributes to chemo resistance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLC2A1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFacilitative glucose transporter responsible for glucose uptake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAggressive growth of breast cancer activate hypoxia inducing factor HIF1 result in GLUT1 expression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42 43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSD17B10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInvolved in fatty acid, branched-chain amino acid and steroid metabolism pathways\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh level of HSD17B10 was indicator for poor responders to the chemotherapy in osteosarcoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVTN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA cell adhesion and spreading factor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDownstream of VEGF/VEGFR and PI3K/AKT signalling induces cell migration and metastasis in breast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33\u003c/p\u003e \u003cp\u003e34\u003c/p\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePSMB4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProteolytic degradation of mostly intra- cellular proteins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePSMB4 overexpression enhances the cell growth and viability of breast cancer cells leading to a poor prognosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNUDT5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAct as ADP-sugar pyrophosphatase in absence of diphosphate or catalyse the synthesis of ATP in presence of diphosphate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAssociated with low overall survival in clear cell renal cell carcinoma and poor prognosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGGCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGlutathione homeostasis, release cyto-c from mitochondria, induces apoptosis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eComponent of GSH-pathway, its lower expression led to chemotherapy resistance in breast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSELENBP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInvolved in intra-Golgi protein transport\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eER\u0026thinsp;+\u0026thinsp;ve breast cancer patient with low SELENBP1 have poorer survival rate and induce resistance to the anti-proliferative effects of Selenium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eATP1B1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eATP hydrolysis coupled with Na/K ions exchange across plasma membrane.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAssociated with metastasis is an important cell energy conversion system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCatalyzes the conversion of gamma-amino butyrate and L-beta-aminoisobutyrate to succinate semialdehyde and methyl-malonate semialdehyde, respectively\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInverse-correlation between ABAT expression and therapy resistance in inflammatory breast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePEPD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCollagen metabolism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExogenous PEPD bind and inhibit Her-2 and EGFR signalling result in growth inhibition in cancer cells.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePb-R-MCF-7 Vs MCF-7 Control\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVIM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVimentins are class-III intermediate filaments found in various non-epithelial cells, especially mesenchymal cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eActivation of Erk-signalling promotes VIM over-expression whereas, its elevated expression in methotrexate and tamoxifen-resistant breast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5859\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSERPINH1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChaperone protein involved in collagen folding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eShowed positive correlation between its expression and aggressive phenotype of gastric cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3637\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSPA5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEndoplasmic reticulum chaperone that plays a key role in protein folding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHSPA5 were upregulated in Lapatinib resistance breast cancer cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53\u003c/p\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFTH1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIron homeostasis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUp-regulated in doxorubicin resistant breast cancer and promotes EMT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGOT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePhenylalanine metabolism\u0026nbsp;and\u0026nbsp;Glucose metabolism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZBRK1 and BRCA1 complex bind to the GOT2 promoter and regulate its expression. Impaired complex binding results in uncontrolled expression result in aspartate and α- ketoglutarate production leads to cell proliferation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVDAC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePresent on outer mitochondrial membrane regulating metabolite and ion exchange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eElVDAC1upregulation promote cell proliferation, indicator of poor prognosis, involved in therapy resistance towards BRD inhibitors in breast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePRDX4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCatalyse hydrogen peroxide and regulate hydrogen peroxide signalling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eElevated expression may lead to therapy resistance and tumor recurrence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOxygen transport from the lung to the various peripheral tissue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePromote aggressiveness in breast cancer cells and poor prognosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFLNB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConnects cell membrane constituents to the actin cytoskeleton\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInduces EMT by releasing FOXC1 transcription factor and expression of EMT gene signatured in tumorigenesis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLMNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNuclear lamina component, maintaining nuclear integrity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLower expression is indicator of poor prognosis and shorter outcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEIF4A2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eATP-dependent RNA helicase which is a subunit of the eIF4F complex involved in cap recognition and is required for mRNA binding to ribosome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTargeting EIF4A2 by miR-5195-3p reverse chemoresistance in TNBC cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSMA7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProteolytic degradation of intracellular proteins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eElevated expression of PSMA7 in gastric cancer is associated with tumor invasion, metastasis, poor survival and having prognostic as well as diagnostic value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSMB5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProteolytic degradation of intracellular proteins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh expression of PSMB5 indicates worse survival and can be severed as novel drug target\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVTN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExtracellular matrix (ECM) protein may be associated with cell adhesion and migration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVTN is downstream of VEGF/VEGFR and PI3K/AKT signalling induces cell migration and metastasis in breast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34\u003c/p\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIST1H2BN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCore component of nucleosome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUncontrolled HIST1H2BN expression contributes to cancer initiation, progression, and indicator of poor prognosis in ovarian cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMembrane transport and signal transduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHIF-1 activates CD47 transcription in hypoxic condition, CD47 maintains cancer stem cells, induce EMT and serve as indicator of poor prognosis in breast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44\u003c/p\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGGCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGlutathione homeostasis, induces release of cytochrome c from mitochondria to induce apoptosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eComponent of GSH-pathway, its lower expression led to chemotherapy resistance in breast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePEPD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCollagen metabolism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExogenous PEPD bind and inhibit Her-2 and EGFR signalling result in growth inhibition in cancer cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNUDT5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAct as ADP-sugar pyrophosphatase in absence of diphosphate or catalyse the synthesis of ATP in presence of diphosphate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAssociated with low overall survival in clear cell renal cell carcinoma and poor prognosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eGO-terms of DEPs in drug-resistant-MCF-7 cells were conducted. Ab-resistant cells' down-regulated proteins have been related to 87 bioprocesses, 23 molecular functions, and 63 cellular components and further KEGG pathway analysis identified 11 signaling pathways. Similarly, Ab-resistant cells' up-regulated proteins have been related to 29 bioprocesses, 30 molecular functions, 30 cellular components and further KEGG pathway analysis identified 9 signaling pathways (Fig.\u0026nbsp;4. B). GO-term analysis in Pb-resistant cells\u0026rsquo; down-regulated proteins have been related to 143 bioprocesses, 31 molecular functions, 63 cell components, and further KEGG pathway analysis identified 32 signaling pathways. Similarly, Ab-resistant cells' up-regulated proteins have been related to 30 bioprocess, 28 molecular functions, 30 cellular components and further KEGG pathway analysis identified 30 signaling pathways. (Fig.\u0026nbsp;5. A, B).We analysed both drug resistance samples using the Reactome pathway database to investigate the reactome pathway associated with these two conditions. DEPs are implicated in metabolism, immunity, signal transduction, programmed cell death, cellular response to external stimuli, DNA replication, cell cycle, and vesicle transport in this study. (Fig.\u0026nbsp;6A, B, C, and D).\u003c/p\u003e \u003cp\u003eHub molecules in DEP\u0026rsquo;s dataset were identified by the Network Analysis tool. FLNA, SSBP, SLC3A2, ATP5B, DLD, and SOD1 were found to be major hubs among down-regulated proteins, whereas, S100A7, VTN, and RAD are up-regulated proteins were identified as major hubs in Ab-resistance cells. YWHAZ, DDB1, HSPB1, S100A9, and ANXA2 were found to be major hubs among down-regulated proteins, while SERPINH1, AHCY, FBP1, TXNRD1, PSMA6, HSP90B1, and PKM were found to be major hubs among up-regulated proteins in Pb-resistance cells. (Fig.\u0026nbsp;7. A, B, C, and D).\u003c/p\u003e \u003cp\u003eThe miR-Net tool was used to analyse miRNA-protein interactions and find an inverse association between miRNAs and their targeted DEPs. In Ab-resistance cells, hsa-mir-1-3p, hsa-mir-155-5p, and hsa-mir-24-p with down-regulated proteins and hsa-mir-155-5p, hsa-mir-23b-3p, hsa-mir-124-3p, and has-mir-30a-5p with up-regulated DEPs showed an inverse relationship. hsa-mir-155-5p, has-mir-1-3p, hsa-mir-20a-5p, and hsa-mir-182-5p with down-regulated proteins and hsa-mir-130a-3p, hsa-mir-101-3p, hsa-mir-19a-3p, hsa-mir-34a-5p, and hsa-let-7a-5p with up-regulated proteins showed an inverse correlation in Pb-resistance cells.\u003c/p\u003e "},{"header":"Discussion","content":" \u003cp\u003eDrug-resistant MCF-7 cells showed to tolerate the drug at higher concentrations compared to control cells. Microscopic images of PI-stained cells confirmed the findings.MDR-1 and ABCG-2 are xenobiotic transporters that help cells eliminate toxins. These proteins have been linked to the phenotype of drug resistance in various cancers [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].Increased MDR-1 and ABCG-2 expression in MCF-7 cells exposed with Ab and Pb for a long-time result in drug efflux, which may be one of the reasons for drug resistance in these cells.\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;2B, C, and D, the drug-resistance models were re-confirmed by increased expression of survival (Bcl-2 and MCL-1) genes and suppressed expression of pro-apoptotic (BAX, BAD, Caspase-3, and PARP1) genes.Bcl-2 blocks the intrinsic apoptosis signal by inhibiting Bax and Bak interactions on the mitochondrial outer membrane. Drug-resistant, cells have elevated levels of Bcl-2 and MCL-1 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Estrogen activates ER, which leads to DNA replication and cell division, as encoded by the ESR1 gene [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].Increased ESR1 expression suggests that it can contribute to therapy resistance. CDK4 and CDK6 are targeted by Ab and Pb, which stimulates cyclin-D1 and promotes cell cycle progression. Increased CDK4/6 and cyclin D1 expression in our cells promotes successful cell division, which is a hallmark of drug resistance.\u003c/p\u003e \u003cp\u003eThe roles of proteins in therapy resistance in Ab-R-MCF-7 and Pb-R-MCF-7 cells are described in Supplementary table 2\u0026ndash;5. DEPs are manually curated from the PubMed literature search engine to determine their molecular functions, roles in cancer progression, therapy resistance, and prognostic importance (see Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). NUDT5 is linked to a poor prognosis and low overall survival in clear cell renal cell carcinoma [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. PEPD binds to Her-2 and inhibits EGFR signaling, resulting in cancer cell growth inhibition [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Lower expression of GGCT, a crucial component of the GSH-pathway, has been linked to chemo-resistance [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Inflammatory BC has an inverse association between ABAT expression and therapy resistance [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. A high level of ATP1B1 is linked to metastasis and it is an essential energy transfer system for cells [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Low levels of SELENBP1 in ER\u0026thinsp;+\u0026thinsp;ve BC result in poor survival and selenium tolerance [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] (Supplementary table 2 and 4) and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003ePSMB is a group β-subunit of the 20S proteasome (PSMB4 and PSMB5), and α-subunit PSMA7 are involved in the proteolytic degradation of intracellular proteins. PSMB4 overexpression promotes cell cycle progression from G1 to S phase and cell viability through NF-B signaling [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. A high PSMB5 level suggests a poor prognosis [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. PSMA7 levels in gastric cancer have been related to invasion, metastasis, and poor prognosis [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. VTN is a part of the extracellular matrix that promotes integrin signaling. VTN, which is downstream of VEGF/VEGFR and PI3K/AKT signaling, promotes cell migration and metastasis in breast cancer [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. SBSN is an oncoprotein that promotes tumorigenicity by increasing Wnt/β-catenin signaling [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The mitochondrial enzyme HSB17B10 is responsible for the oxidation of steroids, alcohol, and fatty acids. In osteosarcoma, a high level of HSD17B10 indicated a poor response to chemotherapy [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Chemo-resistance is caused by the tumour microenvironment facilitating CD9-mediated crosstalk between mesenchymal stem cells and BC cells via CCL5, CCR5, and CXCR12 [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. PDIA3 expression in the tumor microenvironment is high, which favors invasion and metastasis [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].GLUT1 proteins encoded by SLC2A1 aid glucose transport. Hypoxia inducing factor-1(HIF-1) is activated as breast cancer grows aggressively. Due to hypoxic environments, HIF1 triggers GLUT1 expression [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].Under hypoxic conditions, HIF-1 also activates CD47 transcription. In BC, CD47 retains stemness, induces EMT and leads to a poor prognosis [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. HIST1H2BN is a part of the H2B protein family whose unregulated expression causes cancer and is a predictor of poor prognosis in ovarian cancer [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Hemoglobin beta (HBB) is an oxygen transporter that promotes BC cell aggression and a poor prognosis [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. By releasing FOXC1 transcription factor, FLNB exon 30 skipping (gene splicing) induces EMT, and expression of EMT gene signature induces tumorigenicity [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Cancer stem cell survival and proliferation are influenced by redox control and oxidative stress. Peroxiredoxin 4 (PRDX4) catalyses hydrogen peroxide and regulate hydrogen peroxide signaling leading to tumor recurrence and therapy resistance [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. BRD4 is a downstream target of voltage-dependent anion channels (VDAC1), which are found on the outer mitochondrial membrane. VDAC1 overexpression causes breast cancer proliferation, is associated with a poor prognosis, and is linked to therapy resistance to BRD inhibitors in BC [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. The GOT2 promoter is regulated by the ZBRK1 and BRCA1 complex, which binds to it and regulates its expression. Impaired complex binding contributes to uncontrollable expression, which promotes cell proliferation [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. In lapatinib-resistant BC, a high level of HSPA5 was found [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. SERPINH1 is a chaperone protein, and its high expression has been linked to a more aggressive phenotype of gastric cancer, implying a poor prognosis [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. miR-5195-3p targets EIF4A2, which can reverse chemoresistance in TNBC cells [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. FTH1 is a subunit of the ferritin complex that promotes EMT in doxorubicin-resistant breast cancer [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Vimentin (VIM) is a member of the intermediate filament protein family that contributes to cell invasion, migration, and signaling. VIM expression is promoted by Erk signaling activation. Its increased expression has been identified in methotrexate and tamoxifen-resistant BC. [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGO-terms of down-regulated DEPs in Ab and Pb-resistant cells were as follows: \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003ebiological processes\u003c/span\u003e were identified asapoptosis, cell adhesion, small molecule catabolic processes, cofactor metabolic processes, nucleotide metabolic processes, and carbohydrate metabolic processes, etc.The cell surface, mitochondria, endoplasmic reticulum, extracellular matrix, and chaperone complex, among other \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003ecellular components\u003c/span\u003e were established. \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eSignaling pathways\u003c/span\u003e such as estrogen, metabolic pathway and pyruvate metabolism, gluconeogenesis, TCA-cycle, and MAPK-pathway were established (Fig.\u0026nbsp;4. A). Up-regulated DEPs in Ab and Pb resistance cells are linked to \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003ebiological processes\u003c/span\u003e such as cell activation, generation of precursor metabolites, and energy, lung development, cellular response to chemical stimuli, response to hypoxia, cellular response to cytokine stimulus and small molecule metabolic processes. \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eCellular components\u003c/span\u003e localized in the mitochondrial membrane, cytoplasmic vesicle, extracellular matrix, secretory-vesicle and outer membrane. \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eSignaling pathways\u003c/span\u003e such as metabolic pathways, insulin signaling, Choline metabolism in cancer, CGMP-PKG-signalling, Gluconeogenesis, ECM receptor interaction and MAPK signaling, NOTCH signaling, Wnt/β-catenin, PI3K/AKT/mTOR, JAK-STAT, TGF-β signaling these terms are more active in tumor progression, cancer recurrence and therapy resistance.\u003c/p\u003e \u003cp\u003eDuring the treatment of a breast cancer patient, tumor cells can develop therapy resistance to Abemaciclib and Palbociclib drugs. In Ab-resistant cells, a set of down-regulated proteins (NUDT5, PEPD, ABAT, ATP1B1, GGCT, SELENBP1, M6PR, STOM, and ACTN1) as well as up-regulated proteins (SBSN, HSD17B10, CD9, PDIA3, PSMB4, SLC2A1, and VTN) may be useful for prognosis and may be a new drug target.Similarly, in Pb-resistant cells, a series of down-regulated proteins (NUDT5, PEPD, and GGCT) as well as up-regulated proteins (CD47, HIST1H2BN, LMNA, VTN, PSMB5, HBB, PSMA7, FLNB, PRDX4, VDAC1, GOT2, HSPA5, SERPINH1, EIF4A2, FTH, and VIM) may be useful for prognosis and may be a new drug target. However, further confirmation of these DEPs for their prognostic and therapeutic roles in BC would involve either an in vivo analysis or a study on clinical samples. Many miRNAs need to be confirmed for their functional role in therapy resistance, according to a miRNA-protein network review of DEPs.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eDEPs: Differentially expressed proteins\u003c/p\u003e\n\u003cp\u003eCDK: cyclin-dependent kinase,\u003c/p\u003e\n\u003cp\u003ePI: Propidium Iodide,\u003c/p\u003e\n\u003cp\u003eAb-R-MCF-7 Abemacilcib resistance MCF-7\u003c/p\u003e\n\u003cp\u003ePb-R-MCF-7: Palbociclib resistance MCF-7,\u003c/p\u003e\n\u003cp\u003eAb: Abemaciclib,\u003c/p\u003e\n\u003cp\u003ePb: Palbocilcib and\u003c/p\u003e\n\u003cp\u003eBC: Breast cancer.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: Binayak Kumar, Data curation: Ram Krishna Sahu and Ragini Singh, Funding acquisition: Binayak Kumar, Project administrator and Supervision: Suresh T. Hedau, Visualization: Ashutosh Singh, Peeyush Prasad, Writing original draft: Binayak Kumar. Writing, review and editing Binayak Kumar, Srikrishna Jayadev M and Suresh T. Hedau.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI want to thank the Indian Council of Medical Research for providing Post-Doctoral fellowship, National Institute of Cancer Prevention and Research for providing lab facility to conduct proposed work. I want to thank School of Life Sciences, Shiv Nadar University to conduct part of work there. I want to thank MASSFIITB facility at IIT Bombay, Mumbai for conducting non-labelled global proteome profiling.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Project was supported by the Indian Council of Medical Research, India in 2018,\u003c/p\u003e\n\u003cp\u003eNo. 3/1/3/PDF (17)/2017-HRD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest: \u003c/strong\u003eAuthors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary Table 1: List of genes and their primer sequences.\u003c/p\u003e\n\u003cp\u003eSupplementary Table 2: List of down-regulated proteins in Ab-R-MCF-7 and their references.\u003c/p\u003e\n\u003cp\u003eSupplementary Table 3: List of Up-regulated genes in Ab-R-MCF-7 cells and their references.\u003c/p\u003e\n\u003cp\u003eSupplementary Table 4: List of down-regulated Proteins in Pb-R-MCF-7 cells and their references.\u003c/p\u003e\n\u003cp\u003eSupplementary Table 5: List of Proteins up-regulated in Pb-R-MCF-7 cells and their references.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article [and its\u003c/p\u003e\n\u003cp\u003eSupplementary information files].\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A (2020 Jul;70(4):313]) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries [published correction appears in CA Cancer J Clin. 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Cancer Microenviron 10(1\u0026ndash;3):25\u0026ndash;37. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12307-017-0194-9\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Drug-resistance, Breast Cancer, Apoptosis, Cell-cycle, and Proteome.","lastPublishedDoi":"10.21203/rs.3.rs-556331/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-556331/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCDK4/6 inhibitors (Abemaciclib, Ab and Palbociclib, Pb) stop the G1-phase in cell-cycle being used to cure advanced stage of breast cancer (BC). Acquired resistance is a major challenge in BC therapy. The molecular signature of the therapy resistance for Ab and Pb drugs in BC should be explored. Here, we developed Ab/Pb-resistant cell-models and explored the molecular changes. Drug\u0026rsquo;s resistance cells were developed in MCF-7 cells by continuous drug treatment and it was confirmed by MTT-assay, PI-staining-microscopy, and real-time-qPCR. Global proteome profiling done by Labelled-free-Proteome-Orbitrap-Fusion-MS-MS technique. Bioinformatics tools used to analyse the proteome data. Ab-resistant and Pb-resistant MCF-7 cells showed increased tolerance for the respective drug. The BCL-2 and MCL-1 survival genes were up-regulated, while the apoptosis genes BAD, BAX, CASP-3 and PARP-1were down-regulated in the resistant cells. Expression of the MDR-1, ABCG2, ESR-1, CDK4, CDK6, and Cyclin-D1 genes were increased in both resistance cells. For proteomics, 237 and 239 proteins were expressed differently in the resistant Ab and Pb cells, respectively. The NUDT5, PEPD, ABAT, ATP1B1, GGCT, and SELENBP1 proteins were down-regulated and the SBSN, HSD17B10, CD9, PDIA3, PSMB4, SLC2A1, and VTN proteins were up-regulated in Ab-resistant cells. The NUDT5, PEPD, and GGCT proteins were down-regulated, while CD47, HIST1H2BN, LMNA, VTN, PSMB5, HBB, PSMA7, FLNB, PRDX4, VDAC1, GOT2, HSPA5, SERPINH1, EIF4A2, FTH, and VIM proteins were up-regulated in Pb-resistant cells. These proteins are a new set of prognostic markers and drug targets for overcoming the respective drug resistance. However, it is necessary to perform an in vivo or clinical assessment.\u003c/p\u003e","manuscriptTitle":"Role of Differentially Expressed Proteins in Acquired Resistance to Cdk4/6 Inhibitor in Breast Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-05-27 15:26:28","doi":"10.21203/rs.3.rs-556331/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e760a95d-bd43-4654-9043-0ca3da088b7c","owner":[],"postedDate":"May 27th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":4617868,"name":"Cancer Biology"},{"id":4617869,"name":"Oncology"}],"tags":[],"updatedAt":"2021-05-27T15:26:30+00:00","versionOfRecord":[],"versionCreatedAt":"2021-05-27 15:26:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-556331","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-556331","identity":"rs-556331","version":["v1"]},"buildId":"i_I_jhV-QviBjPLXJga9V","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}