Multi-omics-based analysis of high grade serous ovarian cancer subtypes reveals distinct molecular processes linked to patient prognosis.

Despite advancements in treatment, high-grade serous ovarian cancer (HGSOC) is still characterized by poor patient outcomes. To understand the molecular heterogeneity of this disease, which underlies the challenge in selecting optimal treatments for HGSOC patients, we have integrated genomic, transcriptomic, and epigenetic information to identify seven new HGSOC subtypes using a multiscale clustering method. These subtypes not only have significantly distinct overall survival, but also exhibit unique patterns of gene expression, microRNA expression, DNA methylation, and copy number alterations. As determined by our analysis, patients with similar clinical outcomes have distinct profiles of activated or repressed cellular processes, including cell cycle, epithelial-to-mesenchymal transition, immune activation, interferon response, and cilium organization. Furthermore, we performed a multiscale gene co-expression network analysis to identify subtype-specific key regulators and predicted optimal targeted therapies based on subtype-specific gene expression. In summary, this study provides new insights into the cellular heterogeneity of the HGSOC genomic, epigenetic, and transcriptomic landscapes and provides a basis for future studies into precision medicine for HGSOC patients.

Elevated T-cell Exhaustion and Urinary Tumor DNA Levels Are Associated with Bacillus Calmette-Guérin Failure in Patients with Non-muscle-invasive Bladder Cancer.

BACKGROUND: The functional status of immune cells in the tumor microenvironment and tumor characteristics may explain bacillus Calmette-Guérin (BCG) failure in high-risk non-muscle-invasive bladder cancer (NMIBC). OBJECTIVE: To characterize molecular correlates of post-BCG high-grade (HG) recurrence using multiomics analysis. DESIGN, SETTING, AND PARTICIPANTS: Patients with BCG-treated NMIBC (n = 156) were included in the study. Metachronous tumors were analyzed using RNA sequencing (n = 170) and whole-exome sequencing (n = 195). Urine samples were analyzed for immuno-oncology-related proteins (n = 190) and tumor-derived DNA (tdDNA; n = 187). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary endpoint was post-BCG HG recurrence. Cox regression and Wilcoxon rank-sum, t, and Fisher's exact tests were used for analyses. RESULTS AND LIMITATIONS: BCG induced activation of the immune system regardless of clinical response; however, immunoinhibitory proteins were observed in the urine of patients with post-BCG HG recurrence (CD70, PD1, CD5). Post-BCG HG recurrence was associated with post-BCG T-cell exhaustion (p = 0.002). Pre-BCG tumors from patients with post-BCG T-cell exhaustion had high expression of genes related to cell division and immune function. A high predicted post-BCG exhaustion score for pre-BCG tumors was associated with worse post-BCG HG recurrence-free survival (HGRFS; p = 0.002). This was validated in independent cohorts. Pre-BCG class 2a and 2b tumors (UROMOL2021 scheme) were associated with worse post-BCG HGRFS (p = 0.015). Post-BCG exhaustion was observed in patients with high pre-BCG neoantigen load (p = 0.017) and MUC4 mutations (p = 0.002). Finally, the absence of post-BCG tdDNA clearance identified patients at high risk of recurrence (p = 0.018). The retrospective design and partial overlap for analyses are study limitations. CONCLUSIONS: Post-BCG HG recurrence may be caused by T-cell exhaustion. Tumor subtype and pre-BCG tumor characteristics may identify patients at high risk of post-BCG HG recurrence. Urinary measurements have potential for real-time assessment of treatment response. PATIENT SUMMARY: A dysfunctional immune response to bacillus Calmette-Guérin (BCG) therapy may explain high-grade recurrences of bladder cancer.

Molecular tracing of prostate cancer lethality.

Prostate cancer is diagnosed mostly in men over the age of 50 years, and has favorable 5-year survival rates due to early cancer detection and availability of curative surgical management. However, progression to metastasis and emergence of therapeutic resistance are responsible for the majority of prostate cancer mortalities. Recent advancement in sequencing technologies and computational capabilities have improved the ability to organize and analyze large data, thus enabling the identification of novel biomarkers for survival, metastatic progression and patient prognosis. Large-scale sequencing studies have also uncovered genetic and epigenetic signatures associated with prostate cancer molecular subtypes, supporting the development of personalized targeted-therapies. However, the current state of mainstream prostate cancer management does not take full advantage of the personalized diagnostic and treatment modalities available. This review focuses on interrogating biomarkers of prostate cancer progression, including gene signatures that correspond to the acquisition of tumor lethality and those of predictive and prognostic value in progression to advanced disease, and suggest how we can use our knowledge of biomarkers and molecular subtypes to improve patient treatment and survival outcomes.