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Biology subjects

Cherian, M.

Publications and source records attributed to Cherian, M..

2 recordsLinked to original sources

Estradiol Modulates Cytotoxic Responses to Topoisomerase II Targeting Agents in Estrogen Receptor Positive Breast Cancer Cells

Endocrine therapy is the primary treatment for estrogen receptor-positive (ER+) breast cancer. Paradoxically high dose estradiol can induce ER+ breast cancer cell death in an ER dependent manner. Although a well-established phenomenon, the mechanism of estradiol (E2)-induced breast cancer cell death has remained elusive. More recent evidence has revealed that E2 drives estrogen receptor alpha (ERa)-dependent transcription through TOP2 mediated DNA double-strand breaks. This raises two important questions. Firstly, is E2-dependent breast cancer cell death dependent on TOP2 mediated DNA double strand cleavage, and, secondly, does E2 signaling alter sensitivity of ER+ breast cancer cells to TOP2 poisons. Two ER+ breast cancer cell lines T47D and MCF-7 cells were treated with E2, doxorubicin (TOP2 poison) or T638 (catalytic TOP2 inhibitor), alone, and with each drug combined with E2 for 72 h. Viability was measured and normalized to untreated controls and IC50 values were calculated from dose-response curve. E2 enhanced doxorubicin potency in T47D and MCF7 ER+ breast cancer cell lines. E2 was toxic to T47D and MCF7 cells in a concentration dependent manner. The TOP2 catalytic inhibitor, T638, which blocks TOP2-mediated DNA cleavage reduced viability of both cell lines when used alone but decreased the cytotoxic effects of E2 about 7.6-fold, consistent with a role for TOP2-mediated DNA cleavage in the cytotoxic effects of E2. Thus, E2 sensitizes ER+ breast cancer cells to the TOP2 poison, whereas T638, the catalytic inhibitor, diminishes the cytotoxic response to E2. These opposing effects are consistent with E2 acting through TOP2-dependent DNA breaks.

cancer biology↗

Machine learning predicts rapid relapse of triple negative breast cancer

PurposeMetastatic relapse of triple-negative breast cancer (TNBC) within 2 years of diagnosis is associated with particularly aggressive disease and a distinct clinical course relative to TNBCs that relapse beyond 2 years. We hypothesized that rapid relapse TNBCs (rrTNBC; metastatic relapse or death <2 years) reflect unique genomic features relative to late relapse (lrTNBC; >2 years).\n\nPatients and MethodsWe identified 453 primary TNBCs from three publicly-available datasets and characterized each as rrTNBc, lrTNBC, or no relapse (nrTNBC: no relapse/death with at least 5 years follow-up). We compiled primary tumor clinical and multi-omic data, including transcriptome (n=453), copy number alterations (CNAs; n=317), and mutations in 171 cancer-related genes (n=317), then calculated published gene expression and immune signatures.\n\nResultsPatients with rrTNBC were higher stage at diagnosis (Chi-square p<0.0001) while lrTNBC were more likely to be non-basal PAM50 subtype (Chi-square p=0.03). Among 125 expression signatures, five immune signatures were significantly higher in nrTNBCs while lrTNBC were enriched for eight estrogen/luminal signatures (all FDR p<0.05). There was no significant difference in tumor mutation burden or percent genome altered across the groups. Among mutations, only TP53 mutations were significantly more frequent in rrTNBC compared to lrTNBC (Fisher exact FDR p=0.009). To develop an optimal classifier, we used 77 significant clinical and omic features to evaluate six modeling approaches encompassing simple, machine learning, and artificial neural network (ANN). Support vector machine outperformed other models with average receiver-operator characteristic area under curve >0.75.\n\nConclusionsWe provide a new approach to define TNBCs based on timing of relapse. We identify distinct clinical and genomic features that can be incorporated into machine learning models to predict rapid relapse of TNBC.

cancer biology↗