bims-tumhet Biomed News
on Tumor heterogeneity
Issue of 2026–08–09
eight papers selected by
Sergio Marchini, Humanitas Research
  1. Liquid biopsy biomarkers for cancer detection, treatment monitoring, and clinical outcome prediction.
  2. Multifeature sequencing-based liquid biopsy for cancer diagnosis and monitoring.
  3. Mechanisms of T cell-mediated antitumor immunity within tertiary lymphoid structures.
  4. A compendium of next-generation patient-derived models for diverse cancers.
  5. Charting intratumor heterogeneity from bench to bedside.
  6. Homologous recombination deficiency (HRD) testing of high-grade serous carcinoma using cytological samples.
  7. cfDNA-inferred putative clonal hematopoiesis during first-line platinum-to-PARP inhibitor maintenance in ovarian cancer.
  8. Integrative cfDNA profiling from low-pass whole-genome sequencing enables tissue-of-origin prediction in cancer.
  1. Front Cell Dev Biol. 2026 ;14 1874565
    Liquid biopsy biomarkers for cancer detection, treatment monitoring, and clinical outcome prediction.
    Akshee Batra, Xena Zheng, Dan Morgenstern-Kaplan, Carey C Thomson, Gilberto Lopes, Chinmay Jani.
      Liquid biopsy now provides minimally invasive access to tumor-derived genomic and epigenetic information across the lung cancer continuum, and its clinical role continues to expand. This review examines that role across cancer detection (screening and diagnosis), treatment monitoring (advanced-disease genotyping, minimal residual disease (MRD) assessment, and resistance profiling at progression), and clinical outcome prediction. Plasma-based genotyping is now well established in advanced non-small cell lung cancer (NSCLC), while circulating tumor DNA (ctDNA)-based MRD detection in the curative-intent setting has accumulated a substantial evidence base over the past 5 years. Cell-free DNA (cfDNA) methylation, fragmentomics, and circulating tumor RNA (ctRNA) are emerging as complementary modalities, particularly when tumor shedding is low. We also consider concordance between liquid and tissue biopsies, the use of cerebrospinal fluid (CSF) ctDNA in central nervous system (CNS)-involved disease, and the practical issues of cost, reimbursement, and access that shape clinical adoption. The current state of the field can be framed across three tiers of evidence, with established applications, applications under prospective evaluation, and applications not yet ready for routine clinical use. No multi-cancer early detection (MCED) test has shown a mortality benefit to date, and ctDNA-guided treatment changes in metastatic disease still lack randomized overall-survival data.
    Keywords:  circulating tumor RNA; circulating tumor cell (CTC); liquid biopsy; lung cancer; methylation and prognosis
    DOI:  https://doi.org/10.3389/fcell.2026.1874565
  2. Genome Med. 2026 Aug 01. pii: 116. [Epub ahead of print]18(1):
    Multifeature sequencing-based liquid biopsy for cancer diagnosis and monitoring.
    Mariano A Molina, Martina De Simoni, Norbert Moldovan, Florent Mouliere, Daniel W Hagey.
      Liquid biopsy has emerged as a transformative development in oncology, enabling the minimally invasive detection and monitoring of cancer through the analysis of tumor-derived material in blood. Moving beyond single-variable analysis, multifeature sequencing-based liquid biopsy (MSLB) integrates diverse classes of data from a single blood sample to provide deep multifactorial insight into tumor biology. In this review, MSLB is defined as the extraction of multiple biological signals from a single sequencing dataset and is put in the context of other layers of multimodal diagnostics. We focus on how recent advances in patient-, and potentially microbe-derived, cell-free nucleic acid analysis expand the biological information that can be extracted from a single blood sample. MSLB enables this by allowing the concurrent assessment of, for example, DNA methylation, copy number, fragmentation, and, in exploratory workflows, microbe-associated signals. This provides a broader view of tumor, immune, and microenvironment states. When combined with emerging bioinformatic and machine-learning frameworks, these complementary signals may improve early detection, disease monitoring, and treatment selection. Addressing challenges in standardization, validation, and regulatory alignment will be essential to determine how MSLB can be integrated into routine oncologic practice.
    Keywords:  Liquid biopsy; Microbial DNA; Multifeature; cfDNA; cfRNA
    DOI:  https://doi.org/10.1186/s13073-026-01739-2
  3. Front Immunol. 2026 ;17 1883563
    Mechanisms of T cell-mediated antitumor immunity within tertiary lymphoid structures.
    Yuqin Wang, Wenlong Cao, Min Wu, Hui Wang.
      Tertiary lymphoid structures (TLS) are ectopic lymphoid-like organs formed under chronic inflammatory stimulation, which have been increasingly recognized as indicators of favorable clinical prognosis and enhanced immunotherapy response in multiple solid tumors. T cells are essential constituents of TLS, involved in their formation, maintenance, and immune function. They exhibit substantial heterogeneity in quantity, phenotype, and spatial localization across different tumor types. Follicular helper T (Tfh) cells act as a central subset in TLS by promoting B cell activation, germinal center (GC) development, and antibody production. They have been widely regarded as key predictors of favorable therapeutic response and prolonged survival. In addition, peripheral helper T (Tph) cells, regulatory T (Treg) cells, and follicular regulatory T (Tfr) cells also perform immunomodulatory functions within TLS. Their effects can either enhance or suppress antitumor responses, depending on the tumor type, TLS spatial distribution, and maturation status. This review examines the phenotypic heterogeneity, functional fate, and intercellular interactions of T cells within TLS. It also explores the immunoregulatory role of TLS and their potential in novel immunotherapy strategies. Further research should aim to the evolution process of immune populations within TLS and standardized model establishment, in order to accelerate their clinical translation in precision immunotherapy.
    Keywords:  T cell subsets; antitumor immunity; immunotherapy; tertiary lymphoid structures; tumor microenvironment
    DOI:  https://doi.org/10.3389/fimmu.2026.1883563
  4. Nature. 2026 Aug 05.
    A compendium of next-generation patient-derived models for diverse cancers.
    HCMI Network
      The development of new therapeutics and the validation of pathogenetic cancer mechanisms require representative laboratory models1,2. However, existing collections represent only a fraction of the diversity observed in human cancer2-4. Recent technologies have enabled efficient in vitro model derivation (for example, tumour organoids)5. However, whether these maintain essential properties of patient tumours during long-term expansion has not been systematically investigated. Here we present results of a large-scale international programme-the Human Cancer Models Initiative-which involved the generation of a resource of 665 next-generation models from 2,780 donors with 25 cancer types and integrated tumour-model whole genome, exome, methylome and transcriptome analyses. The resource provides 522 models with comprehensive clinical data, 153 models of rare cancers and 71 models from participants with non-European ancestry. Analyses of 421 matched tumour-model pairs reveal high genetic (97.8%) and epigenetic (95%) concordance and define correlates of model discordance. Single-nucleus RNA sequencing of tumour-model pairs reveals subsets of models in which culture conditions significantly influence cell states. Finally, we characterize model preservation of extrachromosomal DNA and post-treatment mutational signatures to provide opportunities to study therapeutic resistance. This model repository is being made available to the community-including multimodal molecular profiling, clinical information and integrative software tools-thus providing a valuable resource for preclinical investigation of cancer pathogenesis and treatment response.
    DOI:  https://doi.org/10.1038/s41586-026-10806-y
  5. Nat Cancer. 2026 Aug 07.
    Charting intratumor heterogeneity from bench to bedside.
    Jonathan C M Wan, Nicholas McGranahan, Charles Swanton.
      Intratumor heterogeneity poses a fundamental challenge across the cancer care continuum, from diagnosis to treatment resistance and metastasis. Over recent decades, multiregion and multiomic profiling of tissue, together with functional studies and longitudinal plasma sampling, have revealed the dynamic and multidimensional evolution of tumor ecosystems. This complexity spans genetic and non-genetic mechanisms within cancer cells and their microenvironment. In this Review, we synthesize the current understanding of heterogeneity and evolution and discuss how these insights can inform the development of evolution-aware diagnostic and therapeutic strategies.
    DOI:  https://doi.org/10.1038/s43018-026-01198-z
  6. BJC Rep. 2026 Aug 07. pii: 43. [Epub ahead of print]4(1):
    Homologous recombination deficiency (HRD) testing of high-grade serous carcinoma using cytological samples.
    Izadora Demmer, Michael Bento Schmid, Diana Born, Gabriel Handschin, Wolfram Jochum.
       BACKGROUND: Homologous recombination deficiency (HRD) is associated with increased sensitivity to PARP inhibitor therapy in various cancer types, including high-grade serous carcinoma (HGSC). Current guidelines recommend HRD testing to guide treatment decisions in HGSG. The majority of HRD assays rely on tumour tissue analysis. The main objective of this study was to assess cytological HGSC samples for HRD testing.
    METHODS: Next generation sequencing using the Oncomine™ Comprehensive Assay Plus (OCAP) panel was performed on 110 matched cytological and histological samples from 55 treatment-naïve HGSC patients to determine the mutational status of 15 homologous recombination repair (HRR)-associated genes including BRCA1/2, and the HRD status based on BRCA1/2 mutational status and genomic instability metric (GIM). Concordance analysis was performed.
    RESULTS: Compared to matched histological samples, cytological HGSC samples revealed an overall concordance rate of 89.7% for HRR-associated gene mutations and of 100% for BRCA1/2 mutations, respectively. A moderate correlation between GIM values (Pearson correlation coefficient 0.48), but an overall concordance rate of 90.9% for the HRD status was observed.
    CONCLUSIONS: Our findings demonstrate that cytological HGSC samples can be employed for HRR-associated gene mutation and HRD testing using next generation sequencing with the OCAP panel.
    DOI:  https://doi.org/10.1038/s44276-026-00241-x
  7. J Gynecol Oncol. 2026 Jul 27.
    cfDNA-inferred putative clonal hematopoiesis during first-line platinum-to-PARP inhibitor maintenance in ovarian cancer.
    Mika Okazawa-Sakai, Takao Fujisawa, Tatsuyuki Chiyoda, Hiroshi Yagi, Ichinosuke Hyodo, Shogen Boku, Yoh Hayasaki, Masanori Isobe, Daisuke Shintani, Kosei Hasegawa, Tomomi Egawa-Takata, Kimihiko Ito, Kei Ihira, Hidemichi Watari, Kazuhiro Takehara, Kiyoko Kato, Hiromichi Nakajima, Kenichi Harano, Yoshiaki Nakamura, Hideaki Bando, Takayuki Yoshino, Daisuke Aoki.
       OBJECTIVE: To describe cell-free DNA (cfDNA)-inferred putative clonal hematopoiesis (CH) candidates during first-line platinum-based chemotherapy followed by poly(ADP-ribose) polymerase inhibitor (PARPi) maintenance in ovarian cancer.
    METHODS: In SCRUM-Japan MONSTAR-SCREEN-1, we analyzed clinically reported paired tumor tissue and plasma cfDNA profiling (324-gene assays). Baseline (B1) data were assessed in 35 treatment-naïve patients; longitudinal cfDNA was available at B1, after platinum without progression (B2), and during/after PARPi without progression (B3) in 8 patients. Putative CH candidates were defined as pathogenic variants (variant allele frequency <40%) in prespecified CH-related genes detected in plasma but not detected in matched tumor tissue at clinical reporting thresholds.
    RESULTS: At B1, putative CH candidates were reported in 19/35 patients (54.3%), most commonly DNMT3A; positivity was associated with age ≥60 years. In the longitudinal cohort, tumor-derived TP53 variants were below the assay reporting threshold at B3 in all patients, whereas putative CH TP53 variants were reported in 0/8 patients at B1 and 6/8 patients at B3. DNA damage response gene candidates (TP53/ATM/CHEK2) more frequently became detectable above the reporting threshold during B2-B3 than during B1-B2, while epigenetic-gene candidates showed relatively stable detectability. No therapy-related myeloid neoplasm events were observed during follow-up.
    CONCLUSION: This paired tissue-plasma longitudinal analysis highlights an interpretive challenge in cfDNA testing during first-line platinum-to-PARPi maintenance therapy: putative CH candidates may become detectable as tumor-derived cfDNA declines. Given cfDNA-only inference without matched WBC sequencing and the small serial cohort, these observations are supportive of prior reports of CH dynamics but require validation in larger WBC-integrated cohorts.
    TRIAL REGISTRATION: UMIN-CTR Clinical Trial Identifier: UMIN000036749.
    Keywords:  Cell-Free Nucleic Acids; Clonal Hematopoiesis; DNA Damage Response; Ovarian Neoplasms; Poly(ADP-ribose) Polymerase Inhibitors; TP53 Genes
    DOI:  https://doi.org/10.3802/jgo.2027.38.e11
  8. Mol Biomed. 2026 Aug 05. pii: 125. [Epub ahead of print]7(1):
    Integrative cfDNA profiling from low-pass whole-genome sequencing enables tissue-of-origin prediction in cancer.
    Yunjian Zhang, Liang Liu, Hua Bao, Ke Xu, Hao Zhang, Song Wang, Shuang Chang, Dongqin Zhu, Zongyao Huang, Zheng Wang, Liu Yang, Bingzhong Zhang, Ji Tao, Wenhua Liang, Jierong Chen, Shanshan Yang, Xue Wu, Yang Shao, Wenquan Wang, Dongyuan Zhu.
      Cancer type classification is challenging due to tumor heterogeneity and undefined tissue of origin (TOO), particularly in cancers of unknown primary (CUP) and multiple primary cancers (MPC). Accurate TOO identification is critical for guiding treatment and prognosis. We developed a stacked ensemble machine learning classifier that integrates 11 multidimensional cfDNA features spanning genomic, fragmentomic, methylation/repeat, and microbial signals. Base models were constructed using five algorithms, including Deep Learning, Distributed Random Forest, Gradient Boosting Machine, Generalized Linear Model, and XGBoost, within a five-fold cross-validation framework, and their predictions were aggregated into a final ensemble optimized for top-1 accuracy. The classifier achieved robust performance across 17 cancer types, with top-1 and top-2 accuracies of 78% and 89% in the training cohort (n = 1,814), and 80% and 90% in an independent validation cohort (n = 1,221). Notably, predictive performance was retained in samples with low tumor fraction (71% top-1, 85% top-2). Sensitivity varied across tumor types, with the highest performance observed in head and neck and colorectal cancers. Among CUP cases, 11 of 15 (73.3%) predictions matched clinically inferred primary sites based on multimodal diagnostics. Feature importance analysis identified nucleosome positioning, fragment size distribution, and repeat elements as key contributors to model performance. Collectively, this cfDNA-based classifier provides a robust and non-invasive approach for accurate cancer type identification and has the potential to support clinical decision-making.
    Keywords:  Multi-cancer classification; Tissue-of-origin; Whole genome sequencing; cfDNA profiling
    DOI:  https://doi.org/10.1186/s43556-026-00497-2
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