bims-tumhet 2026-08-23 papers

Front Oncol. 2026 ;16 1876327

Diversity within ovarian cancer subtypes and their tumor microenvironment.

Lacey Winstone, Breanne Bevelander, Michael Dean Chamberlain.

Ovarian cancer is the deadliest gynecologic cancer in individuals assigned female at birth. Patients diagnosed with ovarian cancer experience poor survival rates due to frequent late-stage diagnosis and aggressive metastases. Ovarian cancer is often diagnosed at stages III or IV, where survival rates decline substantially. Ovarian cancer comprises several subtypes, each with distinct biological characteristics, clinical behaviors, and treatment responses, thereby complicating the identification of effective therapeutic targets. This review focuses primarily on the most prevalent subtype, high-grade serous carcinoma (HGSC) while also considering less common subtypes such as low-grade serous carcinoma, endometrioid carcinoma, clear cell and mucinous carcinomas. The tumor microenvironment (TME) plays a central role in tumor progression, metastasis, and immune evasion, thereby influencing therapeutic response and patient outcomes. Therefore, understanding the interactions between cancer cells and their microenvironment is essential for developing innovative therapeutic strategies. By identifying subtype-specific biomarkers and disease mechanisms, we can enhance diagnostic accuracy and develop tailored treatment approaches. A deeper understanding of ovarian cancer subtypes and their unique characteristics is vital for advancing patient care, driving innovations in early detection, and ultimately improving survival rates in this complex disease. This review emphasizes the potential for identifying novel biomarkers within the TME, which could facilitate earlier diagnosis and the development of targeted treatments for specific ovarian cancer subtypes, ultimately reducing mortality rates in this challenging cancer landscape.

Keywords: clear cell ovarian carcinomas (CCOC); endometrioid carcinomas; epithelial ovarian cancer (EOC); high-grade serous carcinoma (HGSC); low-grade serous carcinoma (LGSC); mucinous carcinomas; tumor microenvironment (TME)

DOI: https://doi.org/10.3389/fonc.2026.1876327

Epigenomics. 2026 Aug 21. 1-9

Beyond tissue biopsy: ctDNA methylation analysis for prediction of colorectal cancer prognosis.

Takahiro Irie, Kiichi Sugimoto.

Accurate prognostic stratification remains a major challenge in colorectal cancer (CRC), as substantial heterogeneity in clinical outcomes persists even within the same pathological stage. While mutation-based circulating tumor DNA (ctDNA) analysis has transformed postoperative risk assessment by enabling detection of molecular residual disease (MRD), it primarily reflects the presence of tumor-derived genetic alterations and may not fully capture the biological processes underlying tumor progression. DNA methylation represents a complementary molecular layer that reflects coordinated regulatory states associated with tumor behavior, including transcriptional programs and cellular plasticity. Recent studies suggest that ctDNA methylation profiling may provide additional prognostic information beyond conventional clinicopathological factors and mutation-based assays, particularly in early-stage and postoperative settings. However, important challenges remain, including assay heterogeneity, lack of standardized metrics, and the need for robust external validation. In this Perspective, we examine the limitations of current prognostic frameworks and discuss the potential role of ctDNA methylation analysis as part of an integrated, multidimensional model for risk stratification in CRC. We propose that incorporating epigenetic information may refine prognostic assessment, while emphasizing the need for rigorous validation prior to clinical implementation.

Keywords: Colorectal cancer; DNA methylation; circulating tumor DNA (ctDNA); liquid biopsy; prognosis

DOI: https://doi.org/10.1080/17501911.2026.2719145

Obstet Gynecol. 2026 Aug 20.

Primary Prevention of Ovarian Cancer With Salpingectomy: The Time is Now!

Jason D Wright.

DOI: https://doi.org/10.1097/AOG.0000000000006421

J Mol Diagn. 2026 Aug 20. pii: S1525-1578(26)00142-X. [Epub ahead of print]

Highly Accurate Detection of Circulating Tumor DNA for Monitoring Minimal Residual Disease in Solid Tumors: Analytical and Clinical Validation of the Haystack MRD Assay.

Advances in cell-free DNA (cfDNA) processing and error-suppressed next-generation sequencing (NGS) have enabled detection of circulating tumor DNA (ctDNA) at low abundance for assessment of minimal residual disease (MRD). MRD testing requires high analytical specificity near the stochastic limit of rare-molecule sampling amid wild-type cfDNA background, i.e., the "needle-in-a-haystack" analytical challenge. This study reports the analytical and clinical validation of Haystack MRD, a tumor-informed ctDNA MRD assay that tracks patient-specific somatic mutations with background-noise suppression architecture to improve discrimination of ctDNA signal from technical and biological interferences. Analytical validation used reference materials and clinical specimens across 23 solid tumor types, followed by clinical validation in stage II-III colorectal cancer (CRC) patients from trial cohorts and real-world evaluation across 27 cancer types. Haystack MRD demonstrated a 95% limit of detection of 0.063 mean ctDNA molecules/mL and an analytical measurement range of 0.25-1,000 mean ctDNA molecules/mL. Concordance of tested samples with expected MRD status yielded 99% agreement (95% CI: 94.2%-99.9%). Quantitative mean ctDNA molecules/mL concentrations were highly concordant with an orthogonal method (R2=0.9998; slope=1.053), supporting accuracy and linearity. In early-stage CRC patients, post-treatment MRD status was highly associated with recurrence, demonstrating 100% sensitivity (72.3%-100.0%) and 100% specificity (92.9%-100.0%) at 3-year follow-up, and 83.3% sensitivity (55.2%-97.0%) and 100% specificity (92.6%-100.0%) at 5-year follow-up, outperforming CEA.

DOI: https://doi.org/10.1016/j.jmoldx.2026.07.006