bims-tumhet Biomed News
on Tumor heterogeneity
Issue of 2026–02–15
twelve papers selected by
Sergio Marchini, Humanitas Research
  1. High-Grade Serous Ovarian Carcinoma in the Genomics Era: Current Applications, Challenges and Future Directions.
  2. Concordance of Genomic Alterations in Ovarian Cancer Tissues and Circulating-Tumor DNA: A Pilot Study.
  3. Tertiary lymphoid structures in the era of cancer therapy.
  4. Clinical validation of a tissue-agnostic genome-wide methylome enrichment assay to monitor response to pembrolizumab.
  5. Integrating liquid biopsies in non-small cell lung cancer diagnosis and management: opportunities and challenges.
  6. Single-cell spatial atlas of high-grade serous ovarian cancer uncovers MHC class II as a key predictor of spatial tumor ecosystems and clinical outcomes.
  7. Exploiting synthetic lethality in epithelial ovarian cancer: multi-dimensional approaches beyond DNA damage repair.
  8. Interpreting cancer genetics through a two-step "evolutionary cascade hypothesis": bridging neutral and selective perspectives.
  9. Circulating tumor DNA dynamics and clinical outcomes in patients with advanced Colorectal Cancer treated with cetuximab-based induction and maintenance treatment.
  10. Immune cells could be protected from 'exhaustion' by flipping genetic switches.
  11. Hereditary Endometrial Cancer: Lynch Syndrome, Mismatch Repair Deficiency, and Emerging Genetic Predispositions-A Comprehensive Review with Clinical and Laboratory Guidelines.
  12. Attention-guided enhanced deconvolution enables reference-free cell type estimation in spatial transcriptomics.
  1. Int J Mol Sci. 2026 Feb 06. pii: 1617. [Epub ahead of print]27(3):
    High-Grade Serous Ovarian Carcinoma in the Genomics Era: Current Applications, Challenges and Future Directions.
    Molly Elizabeth Lewis, Chiara Caricato, Hannah Leigh Roberts, Subhasheenee Ganesan, Nadia Amel Seksaf, Eleni Maniati, Michail Sideris.
      High-grade serous ovarian carcinoma (HGSOC) is characterised by profound genomic instability and limited durable responses to standard therapy, leading to poor prognosis. The use of next-generation sequencing technologies has improved understanding of its molecular landscape, revealing consistent Tumour Protein p53 (TP53) mutations, homologous recombination defects, pathway alterations, and epigenetic dysregulation. Such genomic profiling now underpins the classification criteria between the ovarian cancer subtypes described by the Cancer Genome Atlas. Widespread chromosomal instability and pathogenic variants in multiple genes distinguish HGSOC from other subtypes of ovarian cancer and, further, from low-grade serous ovarian cancer. Importantly, the new-found understanding of the genomic landscape of HGSOC guides the use of platinum-based chemotherapies and Poly(ADP-ribose) Polymerase (PARP) inhibitors, with homologous recombination deficiency emerging as a cancer vulnerability that enhances treatment response. A combined multi-omics approach integrates transcriptomics, proteomics, metabolomics, and epigenomics to further the understanding of the characteristics, therapeutic targets and treatment resistance within HGSOC. Despite these advances, major challenges persist, including intratumoural heterogeneity and the poor diversity of genomic datasets. Artificial Intelligence (AI) technology, Clustered regularly interspaced short palindromic repeats (CRISPR)-based gene editing, neoantigen-guided immunotherapy and ovarian cancer vaccination indicate a promising future for genomics-guided interventions and support the integration of genomics within multi-omic approaches to improve HGSOC outcomes.
    Keywords:  BRCA; TP53; genomics; high-grade serous ovarian carcinoma; homologous recombination
    DOI:  https://doi.org/10.3390/ijms27031617
  2. Int J Mol Sci. 2026 Jan 28. pii: 1305. [Epub ahead of print]27(3):
    Concordance of Genomic Alterations in Ovarian Cancer Tissues and Circulating-Tumor DNA: A Pilot Study.
    Bowon Kang, Seongmin Kim, Sanghoon Lee, Jae Yun Song.
      High-grade serous ovarian carcinoma (HGSOC) is characterized by profound genomic instability and spatial heterogeneity. Liquid biopsy, utilizing circulating tumor DNA (ctDNA), offers a non-invasive approach to capture the comprehensive mutational landscape of the disease. This pilot study evaluated the concordance of genomic alterations between cell-free DNA (cfDNA) and matched tumor tissue in patients with HGSOC. Twelve patients with HGSOC undergoing primary cytoreductive surgery were enrolled. Using the Macrogen® Axen™ Cancer Panel 2 with unique molecular identifier (UMI) technology for error suppression, we achieved a theoretical limit of detection of ~0.36% VAF. The mean cfDNA concentration was 107.3 ng/mL, showing a significant positive correlation with FIGO stage (p = 0.016). While the sensitivity of cfDNA to detect tissue-confirmed mutations was 57.6%, the overall gene-level concordance was 95.3%, largely driven by negative agreement in wild-type genes. Liquid biopsy revealed a significantly broader mutational spectrum (mean 9.67 alterations/patient) compared to tissue (5.50/patient). Crucially, concordant mutations exhibited high variant allele frequencies (VAFs) (mean 41.4%), whereas plasma-unique discordant mutations showed significantly lower VAFs (mean 7.31%, p < 0.001). These preliminary findings suggest that while tissue biopsy likely reflects the dominant clonal population, liquid biopsy may serve as a potential molecular mirror, capturing subclonal variants from spatially distinct metastatic sites and hypoxic niches.
    Keywords:  UMI sequencing; cell-free DNA; liquid biopsy; molecular residual disease; ovarian cancer; tumor heterogeneity
    DOI:  https://doi.org/10.3390/ijms27031305
  3. J Exp Clin Cancer Res. 2026 Feb 11. 45(1): 48
    Tertiary lymphoid structures in the era of cancer therapy.
    Isaias Hernández-Verdin, Anna Dimberg, Daniela S Thommen, Camilla Engblom, Lucile Vanhersecke, Karina Silina, Tullia C Bruno, Wolf H Fridman, Paola Nisticò, Catherine Sautès-Fridman.
      
    Keywords:  Heterogeneity; Immunotherapy; Spatial multi-omics; Tertiary lymphoid structures; Tumor microenvironment
    DOI:  https://doi.org/10.1186/s13046-026-03644-3
  4. NPJ Precis Oncol. 2026 Feb 13.
    Clinical validation of a tissue-agnostic genome-wide methylome enrichment assay to monitor response to pembrolizumab.
    Eric Y Stutheit-Zhao, Yongqi Zhong, Collin A Melton, Elizabeth D Lightbody, Michael A Hinterberg, Yarong Wang, Owen Hall, Eduardo V Sosa, Jeremy B Provance, Junjun Zhang, Abel Licon, Zhihui Amy Liu, Albiruni R Abdul Razak, Anna Spreafico, Philippe L Bedard, Aaron R Hansen, Stephanie Lheureux, Pamela S Ohashi, Alan Williams, Scott V Bratman, Brian A Allen, Jing Zhang, Daniel D De Carvalho, Anne-Renee Hartman, Lillian L Siu, Enrique Sanz-Garcia.
      Immunotherapy has significantly improved the treatment of metastatic solid tumors; however, detecting early signs of response to enable timely intervention for resistant tumors remains challenging. A blood-only circulating tumor DNA (ctDNA) test may provide a rapid assessment of tumor response without reliance on matched tumor tissue. We applied a tissue-agnostic, genome-wide methylation enrichment assay, based on cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq), to plasma samples from patients in a phase 2 trial evaluating pembrolizumab across multiple solid tumors (NCT02644369). A decrease in ctDNA from baseline to pre-cycle 3 was significantly associated with higher objective response and clinical benefit rates and longer progression-free and overall survival in univariate analyses, with these associations remaining significant in multivariable models except for overall survival. These results validate a commercial-grade, tissue-agnostic plasma cfDNA methylation platform for immunotherapy response monitoring, which may facilitate earlier, more informed treatment decisions and improve patient outcomes.
    DOI:  https://doi.org/10.1038/s41698-026-01327-y
  5. Expert Rev Anticancer Ther. 2026 Feb 08.
    Integrating liquid biopsies in non-small cell lung cancer diagnosis and management: opportunities and challenges.
    Jeong Uk Lim, Yuko Oya, Rui Fu, Kenneth Sooi, Yvonne L E Ang, Ross A Soo.
       INTRODUCTION: Liquid biopsy has emerged as an important approach to capture tumor-derived material from blood and other body fluids, offering a minimally invasive window into cancer biology. In non - small cell lung cancer (NSCLC), it enables comprehensive molecular profiling that informs patient management, from guiding therapy choices to monitoring disease status and assessing minimal residual disease (MRD).
    AREAS COVERED: Its main advantages over tissue biopsy lie in being noninvasive, capable of reflecting tumor heterogeneity and real-time biological changes. These strengths allow liquid biopsy to be applied at different clinical timepoints, including diagnosis, treatment decision-making, evaluation during therapy, detection of resistance, and surveillance for recurrence. Although circulating tumor DNA (ctDNA) remains the most established analyte, the scope is broadening to include circulating RNAs, circulating tumor cells, exosomes, DNA methylation signatures, and tumor-educated platelets, each providing complementary insights. A literature search of PubMed, EMBASE, and Web of Science was conducted without restrictions, supplemented by screening reference lists and major oncology conference abstracts.
    EXPERT OPINION: While significant progress has been made integrating liquid biopsies in NSCLC, challenges persist, encompassing issues of standardization, cost, and clinical integration.
    Keywords:  DNA; Liquid biopsy; NSCLC; Next-generation sequencing; RNA; mutation; targeted therapy
    DOI:  https://doi.org/10.1080/14737140.2026.2630026
  6. Cancer Discov. 2026 Feb 09.
    Single-cell spatial atlas of high-grade serous ovarian cancer uncovers MHC class II as a key predictor of spatial tumor ecosystems and clinical outcomes.
    Fernando Perez-Villatoro, Aleksandra Shabanova, Lilian van Wagensveld, Ada Junquera, Iga Niemiec, María M Hincapié-Otero, Ziqi Kang, Matias M Falco, Kürşat Birgin, Sarah Wolf, Ella Anttila, Gayani Anandagoda, Julia Casado, Eric Marcus, Duco Gaillard, Essi Kahelin, Foteini Chamchougia, Matilda Salko, Saundarya Shah, Salvatore Russo, Jacopo Chiaro, Mikaela Grönholm, Joseph Ndika, Otto K Kari, iCAN iCAN, Gabe S Sonke, Koen K Van de Vijver, Rutgerus Fpm Kruitwagen, Maaike van der Aa, Anni Virtanen, Vincenzo Cerullo, Anna Vähärautio, Peter K Sorger, Hugo M Horlings, Anniina Farkkila.
      The tumor microenvironment in high-grade serous ovarian carcinoma (HGSC) is a complex network of malignant-host cell interactions, yet its orchestration remains poorly understood. We present a single-cell spatial atlas of metastatic HGSC from 280 patients, integrating high-dimensional imaging and molecular profiling. Analyzing 929 single-cell maps, we identify spatial domains with diverse cell compositions and show that immune cell co-infiltration at the tumor-stroma interface impacts clinical outcomes. Using CEFIIRA, we find that tumor cell MHCII expression is a key predictor of prolonged survival. Validation with deconvoluted, single-cell, and two distinct spatial transcriptomic datasets, along with immunopeptidomic analysis, confirms that MHCII expression correlates with immune activation, antigen presentation, and TCR clonality. Using a patient-derived immuno-oncology platform, we demonstrate that tumor MHCII expression associates with increased CD8+ T cell cytotoxicity after PD-1 blockade, while blocking MHCII inhibits this activation. Our atlas offers new insights into immune activation, potentially improving patient stratification in HGSC.
    DOI:  https://doi.org/10.1158/2159-8290.CD-25-1492
  7. Mol Cancer. 2026 Feb 10.
    Exploiting synthetic lethality in epithelial ovarian cancer: multi-dimensional approaches beyond DNA damage repair.
    Mandana Bigdeli, Elizabeth Tremblay, Diane Provencher, Anne-Marie Mes-Masson, Francis Rodier.
      Synthetic lethality (SL) is a therapeutic approach that selectively target cancer cells via the disruption of two interdependent molecular targets, which together become essential in the cancer context to ensure cancer cell survival. Among anticancer SL strategies, poly ADP-ribose polymerase (PARP) inhibitors have revolutionized the treatment of homologous recombination repair deficient breast and ovarian cancers by targeting the remaining DNA repair mechanisms. However, resistance emergence is nearly universal providing the rationale to expand beyond classical DNA repair targets. Severe DNA lesions like double-strand breaks or extended single-strand stretches trigger the complex DNA damage response signaling cascade (DDR), which provides many SL targets in addition to direct DNA repair mechanisms. Epithelial ovarian cancer is the deadliest gynecologic malignancy, in part because of late detection and treatment resistance, which provides a rich environment to explore the concept of combining multiple targets to produce SL synergies that kill cancer cells. In this context we discuss the interplay among varied components of the DDR including DNA damage signalers, cell cycle regulation, metabolism, epigenetics, and subsequent cell fate decisions like apoptosis or senescence. Based on this knowledge we further explore innovative SL approaches that may elicit or restore drug sensitivity in resistant tumors. Overall, we provide the rationale for multidimensional strategies linking classic DNA repair mechanisms to various molecular vulnerabilities sometimes apparently unrelated or downstream from DNA damage to improve cancer treatment outcomes via more effective and durable therapeutic responses, offering additional options for the personalized treatment of this highly heterogeneous disease.
    Keywords:  Cell fate decisions; DNA Repair; Drug resistance; Epithelial ovarian cancer; Metabolism
    DOI:  https://doi.org/10.1186/s12943-025-02562-w
  8. J Transl Med. 2026 Feb 13.
    Interpreting cancer genetics through a two-step "evolutionary cascade hypothesis": bridging neutral and selective perspectives.
    Alessandro Ottaiano, Mariachiara Santorsola, Francesco Sabbatino, Roberto Sirica, Francesco Caraglia, Anna Ceccarelli, Vincenza Granata, Ines Simeone, Silvia Zappavigna, Massimiliano Berretta, Giovanni Savarese, Michele Caraglia.
       BACKGROUND: DNA mutations are the fundamental engines of cancer, driving its initiation and progression. The forces that fuel malignancy are also the architects of evolution, shaping life through genetic variations. Mutations, in fact, can emerge naturally from endogenous processes, such as oxidative DNA damage or errors in replication, as well as induced by external factors, including cosmic radiation and chemical carcinogens.
    MAIN BODY: A key question in cancer research is whether tumor evolution is primarily governed by selective bottlenecks, neutral evolution, or dynamic genetic plasticity. In this work, we examine cancer as a disease driven by evolutionary processes rooted in fundamental biological requirements, including sustained proliferation and nutrient utilization. We hypothesize that the accumulation of mutations activates an evolutionary switch, enabling tumor cells to acquire an enhanced capacity for survival, adaptation, and growth at rates far exceeding typical evolutionary timescales. We propose the "evolutionary cascade hypothesis," a unifying framework that integrates these models into a coherent sequence. At its core lies the failure of DNA repair mechanisms, representing a critical transition in cancer progression. This shift marks the transition from an initial non-Darwinian, neutral phase to a Darwinian, more deterministic phase.
    CONCLUSIONS: As predictive models of tumor evolution advance through genomic big data and artificial intelligence-driven analysis, the future of cancer treatment may extend beyond targeting individual mutations to disrupting the underlying evolutionary mechanisms that sustain malignancy. This paradigm shift could redefine therapeutic strategies and ultimately improve patient outcomes.
    Keywords:  Cancer evolution; Cancer genetics; DNA mutations; DNA repair; Genomic instability
    DOI:  https://doi.org/10.1186/s12967-026-07869-w
  9. Clin Cancer Res. 2026 Feb 11.
    Circulating tumor DNA dynamics and clinical outcomes in patients with advanced Colorectal Cancer treated with cetuximab-based induction and maintenance treatment.
    Valérie Boige, Olivier Bouché, Claire Mulot, Ludovic Evesque, Meher Ben Abdelghani, Jean-Marc Phelip, Laurent Mineur, Marie-Pierre Galais, Anne-Laure Villing, Vincent Hautefeuille, Christelle De La Fouchardière, Dominique Genet, Slim Lassoued, Aurélien Carnot, Emmanuel Mitry, Stéphane Jacquot, Delphine Serazin, Camille Bourreau, Justine Abdelli, Emilie Brument, Pierre Laurent-Puig, Lise Roca, Hélène Blons.
       PURPOSE: We investigated whether circulating tumor DNA (ctDNA) changes may be useful to assess clinical outcomes in metastatic colorectal cancer (mCRC) patients randomized in the TIME-PRODIGE28 trial comparing bi-weekly maintenance with cetuximab alone to observation after 4-month FOLFIRI plus cetuximab induction chemotherapy.
    EXPERIMENTAL DESIGN: ctDNA samples were collected at four time points from baseline until disease progression during the first chemotherapy-free interval, and analyzed using next generation sequencing and methylation markers approaches. Progression-free (PFS) and overall (OS) survival from randomization were analyzed according to ctDNA kinetics and EGFR-MAPK pathway alterations.
    RESULTS: Among 139 randomized patients, 104 (74.8%) had paired samples available. Patients with negative baseline ctDNA remaining negative after 4-month induction chemotherapy had significantly longer PFS from randomization (9.6 months) as compared to patients with ctDNA decrease of ≥ 80% (3.4 months) or ctDNA decrease of < 80% (2.1 months, p=0.013). Patients with EGFR-MAPK pathway alterations identified either in tissue or baseline ctDNA had worse PFS and OS from randomization. Acquired alterations found in 17/63 (26.9%) patients at disease progression during the first chemotherapy-free interval were associated with worse OS from reintroduction of the full induction chemotherapy (14.9 vs 19.4 months, p=0.025).
    CONCLUSIONS: Our findings show the prognostic impact of both ctDNA kinetics and EGFR-MAPK pathway alterations dynamics following induction chemotherapy with FOLFIRI-cetuximab in mCRC patients. Prospective studies evaluating ctDNA-guided treatment strategies are needed to validate the clinical utility of ctDNA monitoring to improve patient selection for first-line treatment de-escalation and anti-EGFR-based maintenance regimens, including treatment adaptation over time. TRIAL REGISTRATION clinicaltrials.gov identifier NCT02404935.
    DOI:  https://doi.org/10.1158/1078-0432.CCR-25-3555
  10. Nature. 2026 Feb 11.
    Immune cells could be protected from 'exhaustion' by flipping genetic switches.
      
    Keywords:  Cancer; Immunology
    DOI:  https://doi.org/10.1038/d41586-026-00391-5
  11. Int J Mol Sci. 2026 Jan 28. pii: 1304. [Epub ahead of print]27(3):
    Hereditary Endometrial Cancer: Lynch Syndrome, Mismatch Repair Deficiency, and Emerging Genetic Predispositions-A Comprehensive Review with Clinical and Laboratory Guidelines.
    Andrzej Kluk, Hanna Gryczka, Małgorzata Braszka, Rafał Ałtyn, Hanna Markiewicz, Jan K Ślężak, Ewa Dwojak, Joanna Czerniak, Paweł Zieliński, Bartosz J Płachno, Paula Dobosz.
      Endometrial cancer is the most common gynaecologic malignancy in high-income countries, with a rising incidence largely driven by reproductive factors, obesity, and prolonged exposure to unopposed oestrogens. Although most cases are sporadic, approximately 2-5% are associated with hereditary cancer syndromes, of which Lynch syndrome represents the most important contributor. Lynch syndrome results from germline mutations in DNA mismatch repair (MMR) genes and is associated with a substantially increased lifetime risk of endometrial cancer, reaching up to 71% in carriers of MutS homologue 6 (MSH6) mutations. Hereditary cancer predisposition typically follows an autosomal dominant inheritance pattern and may be suspected based on clinical warning signs such as early disease onset, multiple primary malignancies, a strong family history, or the presence of microsatellite instability in tumour tissue. In addition to Lynch syndrome, rarer genetic conditions-including Cowden syndrome (PTEN), Li-Fraumeni syndrome (TP53), polymerase proofreading-associated polyposis (POLE/POLD1), and hereditary breast and ovarian cancer syndromes (BRCA1/2)-also contribute to hereditary endometrial cancer risk. Recognition of these genetic backgrounds is essential for accurate diagnosis, personalised surveillance, and the implementation of targeted preventive and therapeutic strategies. Despite major advances in molecular diagnostics, hereditary endometrial cancer remains frequently underdiagnosed, leading to missed opportunities for cancer prevention among affected individuals and their families. This comprehensive review summarises current evidence on hereditary predispositions to endometrial cancer, with a particular emphasis on Lynch syndrome, and discusses underlying genetic mechanisms, inheritance patterns, diagnostic strategies, and clinical implications for screening, genetic counselling, and treatment optimisation.
    Keywords:  Lynch syndrome; endometrial cancer; genetic predisposition; hereditary cancer syndromes; mismatch repair deficiency
    DOI:  https://doi.org/10.3390/ijms27031304
  12. Sci Rep. 2026 Feb 10.
    Attention-guided enhanced deconvolution enables reference-free cell type estimation in spatial transcriptomics.
    Xiao Yang, Yujiao Wang, Xiaozhou Chen.
      Spatial transcriptomics technologies profile gene expression across tissue sections while retaining spatial information, yet most platforms capture signals from multiple cells per measurement location, requiring computational methods to determine the underlying cellular composition. Current deconvolution approaches either depend on single-cell reference atlases-which may be unavailable for rare tissues or specific disease contexts-or employ unsupervised methods that struggle with complex spatial patterns and typically need manual specification of how many cell types to identify. We developed Attention-Guided Enhanced Deconvolution (AGED), a two-stage framework combining probabilistic modeling with neural attention architectures for reference-free analysis. The first stage uses a Performer-based network with linear-complexity attention to systematically evaluate models with different numbers of cell types, automatically selecting the optimal configuration through composite scoring of reconstruction quality, cluster separation, and topic diversity. The second stage, Attention-Guide, stars with hierarchical probabilistic initialization. It progressively refines cell type features through multiple attention mechanisms: cross-attention based on statistical priors, spatial attention aggregating neighborhood information, and collaborative attention capturing theme-gene associations. A dynamic gating mechanism enables the model to balance global statistical patterns with locally data-driven features, while regularization promotes sparse solutions consistent with biological reality-each position containing only a few dominant cell types. Testing on Mouse Olfactory Bulb (MOB) tissue, AGED automatically identified four anatomical structures and achieved superior reconstruction performance (r=0.86) with characteristic sparsity patterns. When similarly applied to human pancreatic ductal adenocarcinoma (PDAC) and human thymus tissue, it revealed detailed relationships between dissected structures and cell types. The learned cell type distributions aligned well with established neuroanatomical boundaries and known molecular markers, indicating the attention-based refinement maintains biological interpretability throughout training. This framework offers a practical solution for spatial transcriptomics analysis across diverse experimental systems without requiring matched single-cell data.
    Keywords:  Attention mechanisms; Deep learning; Reference-free deconvolution; Spatial transcriptomics; Topic modeling
    DOI:  https://doi.org/10.1038/s41598-026-39703-0
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