Discovery of Proteins Responsible for Resistance to Three Chemotherapy Drugs in Breast Cancer Cells Using Proteomics and Bioinformatics Analysis

Recent Contributions of Mass Spectrometry-Based "Omics" in the Studies of Breast Cancer

Breast cancer (BC) is one of the most heterogeneous groups of cancer. As every biotype of BC is unique and presents a particular "omic" signature, they are increasingly characterized nowadays with novel mass spectrometry (MS) strategies. BC therapeutic approaches are primarily based on the two features of human epidermal growth factor receptor 2 (HER2) and estrogen receptor (ER) positivity. Various strategic MS implementations are reported in studies of BC also involving data independent acquisitions (DIAs) of MS which report novel differential proteomic, lipidomic, proteogenomic, phosphoproteomic, and metabolomic characterizations associated with the disease and its therapeutics. Recently many "omic" studies have aimed to identify distinct subsidiary biotypes for diagnosis, prognosis, and targets of treatment. Along with these, drug-induced-resistance phenotypes are characterized by "omic" changes. These identifying aspects of the disease may influence treatment outcomes in the near future. Drug quantifications and characterizations are also done regularly and have implications in therapeutic monitoring and in drug efficacy assessments. We report these studies, mentioning their implications toward the understanding of BC. We briefly provide the MS instrumentation principles that are adopted in such studies as an overview with a brief outlook on DIA-MS strategies. In all of these, we have chosen a model cancer for its revelations through MS-based "omics".

Realm of proteomics in breast cancer management and drug repurposing to alleviate intricacies of treatment

Breast cancer, a multi-networking heterogeneous disease, has emerged as a serious impediment to progress in clinical oncology. Although technological advancements and emerging cancer research studies have mitigated breast cancer lethality, a precision cancer-oriented solution has not been achieved. Thus, this review will persuade the acquiescence of proteomics-based diagnostic and therapeutic options in breast cancer management. Recently, the evidence of breast cancer health surveillance through imaging proteomics, single-cell proteomics, interactomics, and post-translational modification (PTM) tracking, to construct proteome maps and proteotyping for stage-specific and sample-specific cancer subtyping have outperformed conventional ways of dealing with breast cancer by increasing diagnostic efficiency, prognostic value, and predictive response. Additionally, the paradigm shift in applied proteomics for designing a chemotherapy regimen to identify novel drug targets with minor adverse effects has been elaborated. Finally, the potential of proteomics in alleviating the occurrence of chemoresistance and enhancing reprofiled drugs' effectiveness to combat therapeutic obstacles has been discussed. Owing to the enormous potential of proteomics techniques, the clinical recognition of proteomics in breast cancer management can be achievable and therapeutic intricacies can be surmountable.

Biomarker Discovery for Early Diagnosis of Papillary Thyroid Carcinoma Using High-Throughput Enhanced Quantitative Plasma Proteomics

The incidence of thyroid cancer (TC) has been increasing over the last 50 years worldwide. A higher rate of overdiagnosis in indolent thyroid lesions has resulted in unnecessary treatment. An accurate detection of TC at an early stage is highly demanded. We aim to develop an enhanced isobaric labeling-based high-throughput plasma quantitative proteomics to identify biomarkers in a discovery cohort. Selected candidates were tested by enzyme-linked immunosorbent assay (ELISA) in the training cohort and validation cohort. In total, 1063 proteins were quantified, and 129 proteins were differentially expressed between patients and healthy subjects. Serum levels of ISG15 and PLXNB2 were significantly elevated in patients with papillary thyroid cancer (PTC) or thyroid adenoma, compared to healthy subjects (p < 0.001) and patients with nodular goiter (p < 0.001). Receiver operating characteristic (ROC) analysis of combined markers (ISG15 and PLXNB2) significantly distinguished PTC from healthy control (HC) subjects. Similar differentiations were also found between thyroid adenoma and HC subjects. Notably, this combined marker could distinguish stage-I PTC from HC subjects (area under the curve (AUC) = 0.872). Our results revealed that ISG15 and PLXNB2 are independent diagnostic biomarkers for PTC and thyroid adenoma, showing a promising value for the early detection of PTC.

The Efficacy of CB-103, a First-in-Class Transcriptional Notch Inhibitor, in Preclinical Models of Breast Cancer

BACKGROUND

The efficacy of CB-103 was evaluated in preclinical models of both ER+ and TNBC. Furthermore, the therapeutic efficacy of combining CB-103 with fulvestrant in ER+ BC and paclitaxel in TNBC was determined.

METHODS

CB-103 was screened in combination with a panel of anti-neoplastic drugs. We evaluated the anti-tumor activity of CB-103 with fulvestrant in ESR1-mutant (Y537S), endocrine-resistant BC xenografts. In the same model, we examined anti-CSC activity in mammosphere formation assays for CB-103 alone or in combination with fulvestrant or palbociclib. We also evaluated the effect of CB-103 plus paclitaxel on primary tumors and CSC in a GSI-resistant TNBC model HCC1187. Comparisons between groups were performed with a two-sided unpaired Students' t-test. A one-way or two-way ANOVA followed by Tukey's post-analysis was performed to analyze the in vivo efficacy study results.

THE RESULTS

CB-103 showed synergism with fulvestrant in ER+ cells and paclitaxel in TNBC cells. CB-103 combined with fulvestrant or paclitaxel potently inhibited mammosphere formation in both models. Combination of CB-103 and fulvestrant significantly reduced tumor volume in an ESR1-mutant, the endocrine-resistant BC model. In a GSI-resistant TNBC model, CB-103 plus paclitaxel significantly delayed tumor growth compared to paclitaxel alone.

CONCLUSION

our data indicate that CB-103 is an attractive candidate for clinical investigation in endocrine-resistant, recurrent breast cancers with biomarker-confirmed Notch activity in combination with SERDs and/or CDKis and in TNBCs with biomarker-confirmed Notch activity in combination with taxane-containing chemotherapy regimens.

The Role of ARHGAP1 in Rho GTPase Inactivation during Metastasizing of Breast Cancer Cell Line MCF-7 after Treatment with Doxorubicin

Breast cancer is the most prevalent cancer type in women worldwide. It proliferates rapidly and can metastasize into farther tissues at any stage due to the gradual invasiveness and motility of the tumor cells. These crucial properties are the outcome of the weakened intercellular adhesion, regulated by small guanosine triphosphatases (GTPases), which hydrolyze to the guanosine diphosphate (GDP)-bound conformation. We investigated the inactivating effect of ARHGAP1 on Rho GTPases involved signaling pathways after treatment with a high dose of doxorubicin. Label-free quantitative proteomic analysis of the proteome isolated from the MCF-7 breast cancer cell line, treated with 1 μM of doxorubicin, identified RAC1, CDC42, and RHOA GTPases that were inactivated by the ARHGAP1 protein. Upregulation of the GTPases involved in the transforming growth factor-beta (TGF-beta) signaling pathway initiated epithelial-mesenchymal transitions. These findings demonstrate a key role of the ARHGAP1 protein in the disruption of the cell adhesion and simultaneously allow for a better understanding of the molecular mechanism of the reduced cell adhesion leading to the subsequent metastasis. The conclusions of this study corroborate the hypothesis that chemotherapy with doxorubicin may increase the risk of metastases in drug-resistant breast cancer cells.

Enhanced Multiplexing Technology for Proteomics

The identification of thousands of proteins and their relative levels of expression has furthered understanding of biological processes and disease and stimulated new systems biology hypotheses. Quantitative proteomics workflows that rely on analytical assays such as mass spectrometry have facilitated high-throughput measurements of proteins partially due to multiplexing. Multiplexing allows proteome differences across multiple samples to be measured simultaneously, resulting in more accurate quantitation, increased statistical robustness, reduced analysis times, and lower experimental costs. The number of samples that can be multiplexed has evolved from as few as two to more than 50, with studies involving more than 10 samples being denoted as enhanced multiplexing or hyperplexing. In this review, we give an update on emerging multiplexing proteomics techniques and highlight advantages and limitations for enhanced multiplexing strategies.

Breast Cancer with Increased Drug Resistance, Invasion Ability, and Cancer Stem Cell Properties through Metabolism Reprogramming

Breast cancer is a heterogeneous disease, and the survival rate of patients with breast cancer strongly depends on their stage and clinicopathological features. Chemoradiation therapy is commonly employed to improve the survivability of patients with advanced breast cancer. However, the treatment process is often accompanied by the development of drug resistance, which eventually leads to treatment failure. Metabolism reprogramming has been recognized as a mechanism of breast cancer resistance. In this study, we established a doxorubicin-resistant MCF-7 (MCF-7-D500) cell line through a series of long-term doxorubicin in vitro treatments. Our data revealed that MCF-7-D500 cells exhibited increased multiple-drug resistance, cancer stemness, and invasiveness compared with parental cells. We analyzed the metabolic profiles of MCF-7 and MCF-7-D500 cells through liquid chromatography−mass spectrometry. We observed significant changes in 25 metabolites, of which, 21 exhibited increased levels (>1.5-fold change and p < 0.05) and 4 exhibited decreased levels (<0.75-fold change and p < 0.05) in MCF-7 cells with doxorubicin resistance. These results suggest the involvement of metabolism reprogramming in the development of drug resistance in breast cancer, especially the activation of glycolysis, the tricarboxylic acid (TCA) cycle, and the hexamine biosynthesis pathway (HBP). Furthermore, most of the enzymes involved in glycolysis, the HBP, and the TCA cycle were upregulated in MCF-7-D500 cells and contributed to the poor prognosis of patients with breast cancer. Our findings provide new insights into the regulation of drug resistance in breast cancer, and these drug resistance-related metabolic pathways can serve as targets for the treatment of chemoresistance in breast cancer.