Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer

Background and Objectives: Breast cancer (BC) is one of the major causes of cancer-related death in women globally. Proper identification of BC-causing hub genes (HubGs) for prognosis, diagnosis, and therapies at an earlier stage may reduce such death rates. However, most of the previous studies detected HubGs through non-robust statistical approaches that are sensitive to outlying observations. Therefore, the main objectives of this study were to explore BC-causing potential HubGs from robustness viewpoints, highlighting their early prognostic, diagnostic, and therapeutic performance. Materials and Methods: Integrated robust statistics and bioinformatics methods and databases were used to obtain the required results. Results: We robustly identified 46 common differentially expressed genes (cDEGs) between BC and control samples from three microarrays (GSE26910, GSE42568, and GSE65194) and one scRNA-seq (GSE235168) dataset. Then, we identified eight cDEGs (COL11A1, COL10A1, CD36, ACACB, CD24, PLK1, UBE2C, and PDK4) as the BC-causing HubGs by the protein-protein interaction (PPI) network analysis of cDEGs. The performance of BC and survival probability prediction models with the expressions of HubGs from two independent datasets (GSE45827 and GSE54002) and the TCGA (The Cancer Genome Atlas) database showed that our proposed HubGs might be considered as diagnostic and prognostic biomarkers, where two genes, COL11A1 and CD24, exhibit better performance. The expression analysis of HubGs by Box plots with the TCGA database in different stages of BC progression indicated their early diagnosis and prognosis ability. The HubGs set enrichment analysis with GO (Gene ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways disclosed some BC-causing biological processes, molecular functions, and pathways. Finally, we suggested the top-ranked six drug molecules (Suramin, Rifaximin, Telmisartan, Tukysa Tucatinib, Lynparza Olaparib, and TG.02) for the treatment of BC by molecular docking analysis with the proposed HubGs-mediated receptors. Molecular docking analysis results also showed that these drug molecules may inhibit cancer-related post-translational modification (PTM) sites (Succinylation, phosphorylation, and ubiquitination) of hub proteins. Conclusions: This study's findings might be valuable resources for diagnosis, prognosis, and therapies at an earlier stage of BC.

MCM3 upregulation confers endocrine resistance in breast cancer and is a predictive marker of diminished tamoxifen benefit

Resistance to endocrine therapy in estrogen receptor-positive (ER+) breast cancer is a major clinical problem with poorly understood mechanisms. There is an unmet need for prognostic and predictive biomarkers to allow appropriate therapeutic targeting. We evaluated the mechanism by which minichromosome maintenance protein 3 (MCM3) influences endocrine resistance and its predictive/prognostic potential in ER+ breast cancer. We discovered that ER+ breast cancer cells survive tamoxifen and letrozole treatments through upregulation of minichromosome maintenance proteins (MCMs), including MCM3, which are key molecules in the cell cycle and DNA replication. Lowering MCM3 expression in endocrine-resistant cells restored drug sensitivity and altered phosphorylation of cell cycle regulators, including p53(Ser315,33), CHK1(Ser317), and cdc25b(Ser323), suggesting that the interaction of MCM3 with cell cycle proteins is an important mechanism of overcoming replicative stress and anti-proliferative effects of endocrine treatments. Interestingly, the MCM3 levels did not affect the efficacy of growth inhibitory by CDK4/6 inhibitors. Evaluation of MCM3 levels in primary tumors from four independent cohorts of breast cancer patients receiving adjuvant tamoxifen mono-therapy or no adjuvant treatment, including the Stockholm tamoxifen (STO-3) trial, showed MCM3 to be an independent prognostic marker adding information beyond Ki67. In addition, MCM3 was shown to be a predictive marker of response to endocrine treatment. Our study reveals a coordinated signaling network centered around MCM3 that limits response to endocrine therapy in ER+ breast cancer and identifies MCM3 as a clinically useful prognostic and predictive biomarker that allows personalized treatment of ER+ breast cancer patients.

RNAi-mediated knockdown of MCM7 gene on CML cells and its therapeutic potential for leukemia

MCM7 is one of the subunits of MCM2-7 complex, which is essential to DNA replication licensing and the control of cell cycle progression. It has been demonstrated that MCM7 participates in mRNA transcription and DNA damage regulation as well. MCM7 gene is found to be over-expressed in multiple cancers, but there are few reports about its effect in leukemia. Recent studies have proven that MCM7 expression has a relationship with diagnosis and prognosis, which has led to their potential clinical application as a marker for cancer screening. RNA interference (RNAi) is a biological process in which RNA molecules inhibit gene expression, typically by causing the destruction of specific mRNA molecules. It is a valuable research tool, which is widely used in cell culture and living organisms as well as in medicine recent years. It is indicated that RNAi application for targeting functional carcinogenic molecules, tumor resistance to chemotherapy and radiotherapy is required in cancer treatment. Gene products knockdown by RNAi technology exerts anti-proliferative and pro-apoptotic effects upon cell culture systems, animal models and in clinical trials in the most studies. In the present study, we found that MCM7 highly expressed in K562 cells rather than that in normal neutrophils. Thus, lentivirus-mediated shRNA targeting MCM7 was used to suppress its endogenous expression in K562 cells and develop a novel therapeutic strategy for leukemia.

Cyclin C interacts with steroid receptor coactivator 2 and upregulates cell cycle genes in MCF-7 cells

Steroid receptor coactivator 2 (SRC-2) is a coactivator that regulates nuclear receptor activity. We previously reported that SRC-2 protein is degraded through the action of cAMP-dependent protein kinase A (PKA) and cAMP response element binding protein (CREB). In the study presented here, we aimed to identify proteins that interact with and thereby regulate SRC-2. We isolated cyclin C (CCNC) as an interacting partner with the SRC-2 degradation domain aa 347-758 in a yeast two-hybrid assay and confirmed direct interaction in an in vitro assay. The protein level of SRC-2 was increased with CCNC overexpression in COS-1 cells and decreased with CCNC silencing in COS-1 and MCF-7 cells. In a pulse-chase assay, we further show that silencing of CCNC resulted in a different SRC-2 degradation pattern during the first 6 h after the pulse. Finally, we provide evidence that CCNC regulates expression of cell cycle genes upregulated by SRC-2. In conclusion, our results suggest that CCNC temporarily protects SRC-2 against degradation and this event is involved in the transcriptional regulation of SRC-2 cell cycle target genes.

Demethylzeylasteral exhibits dose-dependent inhibitory behaviour towards estradiol glucuronidation

The disturbance of estradiol level might induce the occurence of some diseases, including cancer. Estradiol is mainly metabolized through the conjugation reactions, including the sulfation and glucuronidation reactions. The present study tried to evaluate the inhibition of estradiol glucuronidation by the major ingredients of Tripterygium wilfordii Hook F. demethylzeylasteral. Selective ion monitoring at negative ion mode ([M⁺ H⁻] = 447) was employed to monitor the two glucuronides of estradiol. The reaction rate was determined through comparison of peak area of these two glucuronides. Lineweaver-Burk plot and Dixon plot were utilized to determine the inhibition kinetic type, and the inhibition kinetic parameters (K i) were calculated using the second plot. Competitive inhibition of demethylzeylasteral towards the formation of two glucuronides of estradiol was demonstrated, and the K i values were calculated to be 453.3 and 110.9 μM, respectively. All these results will remind us the risk of elevated serum concentrations of estradiol due to the inhibition of estradiol glucuronidation by demethylzeylasteral.