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Purpose: We hypothesized that integrated analysis of cancer types from different lineages would reveal novel molecularly defined subgroups with unique therapeutic vulnerabilities. On the basis of the molecular similarities between subgroups of breast and ovarian cancers, we analyzed these cancers as a single cohort to test our hypothesis.
Experimental Design: Identification of transcriptional subgroups of cancers and drug sensitivity analyses were performed using mined data. Cell line sensitivity to Hsp90 inhibitors (Hsp90i) was tested . The ability of a transcriptional signature to predict Hsp90i sensitivity was validated using cell lines, and cell line- and patient-derived xenograft (PDX) models. Mechanisms of Hsp90i sensitivity were uncovered using immunoblot and RNAi.
Results: Transcriptomic analyses of breast and ovarian cancer cell lines uncovered two mixed subgroups comprised primarily of triple-negative breast and multiple ovarian cancer subtypes. Drug sensitivity analyses revealed that cells of one mixed subgroup are significantly more sensitive to Hsp90i compared with cells from all other cancer lineages evaluated. A gene expression classifier was generated that predicted Hsp90i sensitivity , and in cell line- and PDXs. Cells from the Hsp90i-sensitive subgroup underwent apoptosis mediated by Hsp90i-induced upregulation of the proapoptotic proteins Bim and PUMA.
Conclusions: Our findings identify Hsp90i as a potential therapeutic strategy for a transcriptionally defined subgroup of ovarian and breast cancers. This study demonstrates that gene expression profiles may be useful to identify therapeutic vulnerabilities in tumor types with limited targetable genetic alterations, and to identify molecularly definable cancer subgroups that transcend lineage.
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http://dx.doi.org/10.1158/1078-0432.CCR-18-2213 | DOI Listing |
Int J Surg
September 2025
State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China.
Introduction: Recent advancements in surgical techniques and perioperative care have improved cancer survival rates, yet postoperative comorbidity and mortality remain a critical concern. Despite progress in cancer control, systematic analyses of long-term mortality trends and competing risks in surgery-intervened cancer populations are lacking. This study aimed to quantify temporal patterns of postoperative mortality causes across 21 solid cancers and identify dominant non-cancer risk factors to inform survivorship care strategies.
View Article and Find Full Text PDFNat Commun
September 2025
Department of Preventive Medicine, Keck School of Medicine, University of Southern California Norris Comprehensive Cancer Center, Los Angeles, 90033, California, USA.
Am J Hum Genet
September 2025
Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, Fulham Road, London, UK. Electronic address:
Multiplex assays of variant effect (MAVEs) provide promising new sources of functional evidence, potentially empowering improved classification of germline genomic variants, particularly rare missense variants, which are commonly assigned as variants of uncertain significance (VUSs). However, paradoxically, quantification of clinically applicable evidence strengths for MAVEs requires construction of "truthsets" comprising missense variants already robustly classified as pathogenic and benign. In this study, we demonstrate how benign truthset size is the primary driver of applicable functional evidence toward pathogenicity (PS3).
View Article and Find Full Text PDFPLoS One
September 2025
Institute of Computational Science and Technology, Guangzhou University, Guangzhou, China.
MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology, yet their spatial dynamics within tumor microenvironments (TMEs) remain underexplored due to technical limitations in current spatial transcriptomics (ST) technologies. To address this gap, we present STmiR, a novel XGBoost-based framework for spatially resolved miRNA activity prediction. STmiR integrates bulk RNA-seq data (TCGA and CCLE) with spatial transcriptomics profiles to model nonlinear miRNA-mRNA interactions, achieving high predictive accuracy (Spearman's ρ > 0.
View Article and Find Full Text PDFTher Adv Med Oncol
September 2025
Division of Surgical Oncology, Department of Surgery, University of California, Los Angeles, 15503 Ventura Blvd, Suite 150, Los Angeles, CA 90095, USA.
The relationship between pregnancy and breast cancer is complicated. On one hand, pregnancy can influence breast cancer risk and tumor biology, and on the other, a breast cancer diagnosis and its subsequent management can significantly affect fertility, family planning, and future pregnancies. This interaction presents challenges unique to young women with breast cancer (YWBC).
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