bims-tumhet Biomed News
on Tumor heterogeneity
Issue of 2026–01–04
ten papers selected by
Sergio Marchini, Humanitas Research
  1. Integrative sWGS: A New Paradigm for HRD Detection in Ovarian Cancer.
  2. Early Detection and Prevention of Ovarian Cancer.
  3. Distinct origins of high-grade serous ovarian carcinoma: genetic and epigenetic evidence linking ovarian and fallopian tube epithelium to clinical outcomes and early detection.
  4. Spatial omics at the forefront: emerging technologies, analytical innovations, and clinical applications.
  5. When the methylome becomes the microscope.
  6. Comparison of liquid biopsy-based technologies for cancer screening.
  7. Comprehensive Spatial Methods (CSM): A Toolbox for Spatially Analyzing Tissues in Histopathology.
  8. KELIM score: A marker of chemosensitivity in ovarian cancer.
  9. Optimizing Liquid Biopsy: Spike-In Panel Approach for ctDNA Copy Number Variation Analysis.
  10. Identification of DNA methylation based prognostic subtype and signature in epithelial ovarian cancer.
  1. Int J Mol Sci. 2025 Dec 12. pii: 11968. [Epub ahead of print]26(24):
    Integrative sWGS: A New Paradigm for HRD Detection in Ovarian Cancer.
    Dan Corneliu Jinga, Georgiana Duta-Cornescu, Danut Cimponeriu, Eirini Papadopoulou, Angeliki Meintani, George Tsaousis, Amalia Chirnogea, Irina Bucatariu, Polixenia-Georgeta Iorga, Diana Chetroiu, Sorin-Cornel Hosu, Amalia Hogea-Zah, Mircea-Dragos Median, Bogdan Diana, Dana-Lucia Stănculeanu, Raluca Mihaila, Dana-Sonia Nagy, Pompilia-Elena Motatu, Turcanu Eugeniu, Elena-Octaviana Cristea, Ion-Cristian Iaciu, Paul Kubelac, Andreea Truican.
      Homologous recombination deficiency (HRD) is a clinically relevant biomarker that predicts sensitivity to PARP inhibitors and enables personalized cancer therapy. Validated local HRD testing solutions are essential to ensure timely and equitable access, ultimately improving treatment outcomes. We evaluated a shallow whole-genome sequencing (sWGS) approach for genomic instability (GI) assessment combined with a 52-gene targeted panel in ovarian cancer. Validation used reference materials and 24 archival samples with prior HRD characterization, comparing performance with the Myriad myChoice® HRD test. A prospective cohort of 124 newly diagnosed ovarian cancer patients was then analyzed. sWGS-derived GI status showed strong concordance with the reference test (95.8% overall agreement; κ = 0.913; NPV 100%, PPV 93.3%). Pathogenic BRCA1/2 variants were detected in 30 patients (24.19%). An additional 22.76% were BRCA1/2-negative but GI-positive, giving an overall HRD prevalence of 47.15%. Platinum sensitivity occurred in 90.0% (18/20) of HRD-positive patients with follow-up. Among 12 patients assessed for PARP-inhibitor response, the overall response rate was 66.7% (95% CI 39.1-86.2) and disease control rate 83.3% (95% CI 55.2-95.3). TP53 alterations were most frequent (62.90%), followed by BRCA1 (19.35%) and BRCA2 (4.83%). Pathogenic variants in other HR-pathway genes (ATM, CHEK2, BRIP1, RAD51C, BARD1) appeared in 9.57% of BRCA-wild-type cases, with heterogeneous GI impact. Two cases showed concurrent BRCA2 variants and microsatellite instability, indicating possible eligibility for anti-PD-1/PD-L1 therapy in addition to PARPi. This first comprehensive analysis of Romanian ovarian cancer patients suggests that integrating sWGS-based genomic instability assessment with BRCA testing can improve HRD detection and reflects the heterogeneity of HR-pathway variants. Preliminary clinical observations were consistent with known HRD-associated treatment responses, although larger studies are needed to confirm these findings.
    Keywords:  PARP inhibitors; genomic instability; homologous recombination deficiency; ovarian cancer; sWGS
    DOI:  https://doi.org/10.3390/ijms262411968
  2. Cancers (Basel). 2025 Dec 16. pii: 4006. [Epub ahead of print]17(24):
    Early Detection and Prevention of Ovarian Cancer.
    Lauren Montemorano, Laura Huffman, Lisa Barroilhet.
      Background/Objectives: Epithelial ovarian cancer (EOC) encompasses ovarian, fallopian tube and peritoneal malignancies. It is a deadly disease and is rarely cured when diagnosed at advanced stages. Early-stage disease is often curable, but clinicians and researchers have been stymied in their attempts to reliably screen for this disease, even in high-risk populations. Effective prevention of ovarian cancer is usually limited to the use of combined oral contraceptives and removal of the ovaries and fallopian tubes. Methods and Results: We aim to review the current guidelines and the evidence reported for both the early detection and prevention of ovarian cancer. Novel imaging techniques, biomarkers, and surgical advances will be discussed. Conclusions: This review will offer (a) an understanding of the epidemiology of EOC (b) analysis and a discussion of relevant molecular markers that might be exploited for more accurate early detection (c) medical and surgical methods to prevent ovarian cancer.
    Keywords:  early detection; ovarian cancer; prevention
    DOI:  https://doi.org/10.3390/cancers17244006
  3. Mol Biol Rep. 2025 Dec 29. 53(1): 227
    Distinct origins of high-grade serous ovarian carcinoma: genetic and epigenetic evidence linking ovarian and fallopian tube epithelium to clinical outcomes and early detection.
    Mohammad Ghanbari, Aida Aghazadeh, Maitham Alhajamee, Mohammed Ismael Ibrahim Jebur, Dheyaa Obaid Alamara, Mustafa Mutashar Ghalib, Mehdi Haghi.
      High-grade serous ovarian carcinoma (HGSOC) is the most prevalent and aggressive subtype among ovarian cancers and is associated with poor prognosis. The molecular mechanism of HGSOC development and metastasis is complex and associated with genomic instability due to abnormal DNA repair systems. This leads to the loss of tumor suppressors and amplification of oncogenes that are accompanied by epigenetic alterations. Despite its name and complexity, there is debate about its origin; however, recent findings on genetic and epigenetic features in animal models and human samples suggest that fallopian tube epithelium (FTE) and ovarian surface epithelium (OSE) are the main origin sites of HGSOC development. Since OSE-derived tumors are associated with chemoresistance and poor survival rates, understanding HGSOC origin is clinically valuable for selecting appropriate treatment. This review focuses on the early genetic and epigenetic changes that characterize tumors originating from FTE versus OSE, highlighting how these differences may influence clinical behavior and treatment response. Uncovering the early molecular mechanisms that drive the distinct origins of HGSOC is essential for a deeper understanding of how this cancer develops. These insights could pave the way for the development of precise, biomarker-based strategies for early detection and more effective treatment. In line with this goal, the final section of our review highlights emerging non-invasive screening methods such as mutation and epigenetic profiling of circulating tumor DNA (ctDNA), along with transcriptomic analysis of microRNAs in body fluids. These emerging approaches show strong potential as biomarkers for early diagnosis and for predicting patients' therapy response.
    Keywords:  Biomarker; Clinical outcome; Early epigenetic alterations; Early genetic changes; Fallopian tube epithelium; High-grade serous ovarian carcinoma; Ovarian surface epithelium; Screening
    DOI:  https://doi.org/10.1007/s11033-025-11394-2
  4. Cancer Cell. 2025 Dec 31. pii: S1535-6108(25)00543-4. [Epub ahead of print]
    Spatial omics at the forefront: emerging technologies, analytical innovations, and clinical applications.
    Yunhe Liu, Yibo Dai, Linghua Wang.
      Spatial omics transforms our understanding of cancer by revealing how tumor cells and the microenvironment are organized, interact, and evolve within tissues. Here, we synthesize advances in spatial technologies that map tumor ecosystems with unprecedented fidelity. We highlighted analytical breakthroughs-including multimodal integration and emerging spatial foundation models-that resolve functional niches and spatial communities, converting spatial patterns into mechanistic insights. We summarize how spatially organized features, from immune hubs to microbiota and neural interfaces, shape tumor evolution and clinical outcomes. We then outline how spatial approaches illuminate precancer biology, metastatic adaptation, and therapy response. Bridging discovery and translation, we provide a practical roadmap for incorporating spatial readouts into clinically oriented study design. We conclude by discussing persistent challenges in standardization and scalability and how high-plex spatial discoveries may be distilled into scalable, AI-enabled, clinically deployable assays, positioning spatial omics as a cornerstone of next-generation predictive and precision oncology.
    Keywords:  AI; ML; TME; artificial intelligence; cell-cell interaction; cellular neighborhood; computational pathology; machine learning; molecular imaging; multi-omics; multimodal data integration; proteomics; spatial biomarkers; spatial heterogeneity; spatial niche; spatial omics; transcriptomics; tumor microenvironment
    DOI:  https://doi.org/10.1016/j.ccell.2025.12.009
  5. Cancer Cell. 2025 Dec 31. pii: S1535-6108(25)00540-9. [Epub ahead of print]
    When the methylome becomes the microscope.
    Houtan Noushmehr.
      DNA methylation patterns stratify tumors into distinct biological, prognostic, and therapeutic response features. In this issue of Cancer Cell, Sill et al. expand the Heidelberg CNS Tumor Methylation Classifier from 91 to 184 subclasses using 7,495 methylomes, enhancing diagnostic accuracy, revealing new tumor types, and making methylation-based classification more widely accessible.
    DOI:  https://doi.org/10.1016/j.ccell.2025.12.006
  6. Crit Rev Clin Lab Sci. 2025 Dec 27. 1-12
    Comparison of liquid biopsy-based technologies for cancer screening.
    Andreas P Papanastasiou, Miyo K Chatanaka, Eleftherios P Diamandis.
      Circulating plasma DNA has found important applications in diverse medical fields, including prenatal testing, transplantation, and especially cancer. Many companies have developed products for detecting minimal residual disease, selecting or monitoring therapy, assessing prognosis, and confirming diagnosis. One major application is in screening asymptomatic individuals for the presence of cancer. Screening may facilitate better clinical outcomes through earlier interventions. Collectively, these technologies are widely known as "liquid biopsies". After the extraction of free DNA from the circulation, it is analyzed by various molecular techniques to explore differences between DNA originating from normal cells and cancer cells. Circulating plasma DNA originating from tumors (ctDNA) is expected to harbor the same molecular changes as tumor tissue itself. Thus, ctDNA is considered a surrogate of cancer tissue, but without the need to perform invasive biopsies to obtain it. Many new diagnostic companies have taken advantage of this new biomarker and developed technologies for screening for one or multiple cancers. We previously estimated the amount of ctDNA in circulation, which is admixed with DNA originating from normal cells. We concluded that since only a small fraction of the whole plasma (3 liters) is used for testing (3 to 4 mL), it is possible that the retrieved ctDNA may not be enough for cancer diagnosis in all patients. This problem is more acute with small tumors. Here, we mention some companies in the "liquid biopsy" arena and analyze their clinical data to establish if their tests are close to entering the clinic. We conclude from this analysis that current data do not support the use of these technologies for population screening due to many false negative and false positive results.
    Keywords:  Liquid biopsy; cancer screening; cancer screening companies; circulating tumor DNA; early cancer diagnosis
    DOI:  https://doi.org/10.1080/10408363.2025.2606357
  7. Lab Invest. 2025 Dec 26. pii: S0023-6837(25)00187-4. [Epub ahead of print] 104276
    Comprehensive Spatial Methods (CSM): A Toolbox for Spatially Analyzing Tissues in Histopathology.
    Alvaro Lopez-Janeiro, Eduardo Miraval-Wong, Paulo Perez-Dominguez, Raluca Alexandru, Maria Guadalupe García Vazquez, David Hardisson, Alberto Peláez-Garcia, David Ruiz-Guillamon, Ignacio Melero, Carlos E de Andrea.
      The image-based determination of proteins with spatial context has revolutionized our understanding of biology in different fields, including developmental biology, immunology, and oncology. The popularization of multiplex and high-plex tissue imaging methods has allowed researchers to simultaneously interrogate multiple tissue proteins with high spatial resolution in a single tissue section. Although these technologies offer many opportunities, analytical challenges have also emerged. Currently, no single analytical pipeline covers the entire spectrum of analyses required to harness the potential of these spatial platforms. Here, we present Comprehensive Spatial Methods (CSM), an R-based analysis toolbox designed to analyze multiplex and high-plex omics with high spatial resolution. CSM covers all the analytical steps, from cell and tissue segmentation and protein expression normalization to cell phenotyping, spatial heterogeneity analysis, cell-to-cell spatial interaction determination and cellular neighborhood analysis. CSM relies on top-performing R libraries to deliver a user-friendly experience. We test the performance of CSM on a set of multiplex and high-plex images of endometrial, breast and colorectal carcinomas and non-tumoral lymph node, skin and lung tissue. We demonstrate that the ability of CSM to phenotype and quantify cells is better than that of other state-of-the-art resources. In addition, we show that the different approaches implemented in CSM for assessing cell phenotypes, spatial heterogeneity, cell-to-cell interactions and tissue neighborhoods cover a broad range of analytical scenarios. The freely available CSM toolbox covers many of the analytical needs of researchers working with spatially resolved histopathology data.
    Keywords:  Multiplex immunofluorescence; Spatial analysis; computational pathology; spatial omics
    DOI:  https://doi.org/10.1016/j.labinv.2025.104276
  8. Cancer Treat Rev. 2025 Dec 18. pii: S0305-7372(25)00193-8. [Epub ahead of print]143 103071
    KELIM score: A marker of chemosensitivity in ovarian cancer.
    Federica Adele Ambrosino, Carmela Pisano, Marilena Di Napoli, Jole Ventriglia, Rosa Tambaro, Sabrina Rossetti, Anna Passarelli, Ernesta Cavalcanti, Rossella De Cecio, Francesco Fiore, Sergio Venanzio Setola, Teresa Troiani, Lorenzo Lobianco, Erica Perri, Mariarosaria Lamia, Gabriele Calvanese, Sandro Pignata, Sabrina Chiara Cecere.
      Ovarian cancer is the gynecological cancer with the worst prognosis and the highest mortality rate, primarily because 75% of patients are diagnosed with advanced FIGO stage III-IV disease. About 50% of patients are now treated with neoadjuvant chemotherapy followed by interval debulking surgery. In that context, there is a need for accurate predictors of tumor primary chemosensitivity, as it may impact the feasibility of subsequent interval debulking surgery. The cancer antigen 125 ELIMination rate constant K (KELIM) score, a modeled kinetic parameter, is a potential marker of tumor chemosensitivity in patients with ovarian cancer treated with adjuvant or neoadjuvant chemotherapy before interval debulking surgery. This review aims to provide a comprehensive overview of potential predictive factors for response to platinum therapy, focusing on the KELIM score, a marker increasingly used in clinical practice.
    Keywords:  CA-125; Chemotherapy; KELIM score; Ovarian cancer
    DOI:  https://doi.org/10.1016/j.ctrv.2025.103071
  9. Cancer Genomics Proteomics. 2026 Jan-Feb;23(1):23(1): 127-134
    Optimizing Liquid Biopsy: Spike-In Panel Approach for ctDNA Copy Number Variation Analysis.
    Hyunji Kim, Byoung Mok Kim, Jinho Kim, Soo Hyun Seo, Sang Mee Hwang, Kyoung Un Park.
       BACKGROUND/AIM: Circulating tumor DNA (ctDNA) testing has emerged as a minimally invasive tool for precision oncology, enabling dynamic monitoring of tumor burden and treatment response. However, commercial ctDNA NGS assays often omit clinically important oncogenes, limiting accurate assessment of copy-number variation (CNV). Amplifications of MYC and MYCN are key drivers of tumor progression and therapeutic resistance, and their detection is required under the Korean National Health Insurance coverage criteria. We evaluated whether a custom spike-in panel added to the Avenio ctDNA Expanded Kit improves CNV detection for MYC and MYCN to meet these clinical and regulatory requirements.
    MATERIALS AND METHODS: Spike-in targets were designed with KAPA Target Enrichment Custom Designs and integrated into the Avenio panel. Reference materials (Horizon Structural Multiplex cfDNA Standard, 5% (MYCN ≈9.5 copies); Seraseq ctDNA Complete, 1% (MYC≈3.07 copies)) were measured in triplicate; Seraseq was additionally diluted 1:2 and 1:10. Eight cancer-free plasma samples established the baseline. Libraries were sequenced on a NextSeq 550Dx (high-output). CNV analysis used CNVkit v0.9.9 with custom parameters (reference spread threshold increased 1.0→1.5; GC upper limit relaxed 0.7→0.8, lower limit retained at 0.3). Log2 fold-change versus healthy controls assessed CNV signals.
    RESULTS: Mean exon coverage was 698.5 for MYCN (range=325.4-1081.2) and 740.3 for MYC (range=438.8-1221.7). In the Horizon material, all MYCN exons showed ≥3.6-fold change (mean 4.2; inferred CNV ≈8.2), concordant with expected amplification. Seraseq showed a mean MYC fold change of 1.46 (inferred CNV ≈2.94); diluted samples yielded CNV estimates of 2.79 (1:2) and 2.67 (1:10), indicating limited sensitivity below ~3 copies. One MYC exon reproducibly underperformed despite adequate coverage.
    CONCLUSION: Incorporation of a spike-in panel into the Avenio ctDNA assay enabled reliable detection of high-level MYC/MYCN amplifications and fulfilled practical requirements for local reimbursement. The estimated CNV limit of detection in this setting is ≈3 copies. Further replicate testing and validation with clinical specimens are warranted to refine sensitivity and interlaboratory robustness.
    Keywords:  Circulating tumor DNA; MYC; MYCN; copy number variation; liquid biopsy; next-generation sequencing; spike-in panel
    DOI:  https://doi.org/10.21873/cgp.20565
  10. Hum Genet. 2025 Dec 27. 145(1): 6
    Identification of DNA methylation based prognostic subtype and signature in epithelial ovarian cancer.
    Jingjing Zhou, Yuxin Chen, Wei Liu, Chao Wang, Lei Liu, Wei Geng, Linqing Chai, Dong Yang, Hongji Dai, Haixin Li, Yanrui Zhao, Kexin Chen, Hong Zheng, Lian Li.
      DNA methylation plays a crucial role in the development and progression of cancer and has been utilized for subtyping various tumors. This study focused on classifying epithelial ovarian cancer (EOC) based on DNA methylation and characterizing the subtypes through an integrated analysis of genomic, transcriptomic, and clinical data. We performed genome-wide DNA methylation profiling on 137 EOC tumor tissues using Infinium MethylationEPIC array and four methylation subtypes (MS1-MS4) were identified by non-negative matrix factorization (NMF) approach, showing significant differences in prognosis (P = 2.413 × 10⁻⁹). The MS1 group showed the best prognosis and the most favorable response to paclitaxel in combination with platinum-based chemotherapy. MS2 exhibited a gene expression pattern of relatively high immune cell infiltration and MS3 had a gene expression pattern associated with metabolic related pathway with a moderate prognosis. In contrast, MS4 had the poorest prognosis and was marked by the highest methylation levels among the four subtypes. A four-differential methylation position (DMP) signature was constructed for prognosis prediction and nomogram was also developed for enhancing clinical utility. Together, this study identified a novel molecular subtype for EOC, elucidating the heterogeneity of EOC from an epigenetic perspective and providing a new strategy for personalized treatment options for EOC patients.
    DOI:  https://doi.org/10.1007/s00439-025-02808-z
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