bims-ovdlit Biomed News
on Ovarian cancer: early diagnosis, liquid biopsy and therapy
Issue of 2026–08–09
nine papers selected by
Lara Paracchini, Humanitas Research
  1. Response to Correspondence of Cheng W. et al. on "Decoding BRCA1 and BRCA2 mutations in high-grade serous ovarian cancer: impact of location and type of mutation on prognosis and PARP inhibitor treatment" by Momi M. et al.
  2. Multifeature sequencing-based liquid biopsy for cancer diagnosis and monitoring.
  3. cfDNA-inferred putative clonal hematopoiesis during first-line platinum-to-PARP inhibitor maintenance in ovarian cancer.
  4. A compendium of next-generation patient-derived models for diverse cancers.
  5. Opportunities to improve detection of genetic predisposition for ovarian cancer applying the Tumor-First workflow.
  6. A complete diploid human genome benchmark for personalized genomics.
  7. Filling the holes in whole genomes: A vision for personalized genomics from telomere to telomere.
  8. Inference of tumor spatial habitats.
  9. Somatic mutations and genome mosaicism in aging and disease.
  1. Int J Gynecol Cancer. 2026 Jul 12. pii: S1048-891X(26)00403-2. [Epub ahead of print] 104872
    Response to Correspondence of Cheng W. et al. on "Decoding BRCA1 and BRCA2 mutations in high-grade serous ovarian cancer: impact of location and type of mutation on prognosis and PARP inhibitor treatment" by Momi M. et al.
    Antonella Ravaggi, Elisa Salviato, Eliana Bignotti.
      
    DOI:  https://doi.org/10.1016/j.ijgc.2026.104872
  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. 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
  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. Fam Cancer. 2026 Aug 04. pii: 82. [Epub ahead of print]25(3):
    Opportunities to improve detection of genetic predisposition for ovarian cancer applying the Tumor-First workflow.
    Vera M Witjes, Joanne A de Hullu, Angela van Remortele, Lilian Vreede, Michiel Simons, Nicoline Hoogerbrugge, Marjolijn J L Ligtenberg.
      Genetic testing in ovarian carcinoma (OC) patients is very important for patients and their relatives. The Tumor-First workflow uses a tumor DNA test to stratify germline testing for hereditary cancer predisposition as well as treatment options with PARP inhibitors. This workflow is adopted and successfully implemented nationwide. Here, we evaluated recent tumor DNA testing rates in the Netherlands to identify untested OC patient groups and optimize tumor DNA testing rates. OC patients diagnosed in 2023 or 2024 were selected from the Netherlands Cancer Registry. We analyzed patient characteristics associated with the likelihood of tumor DNA testing using multivariable logistic regression. Tumor-First testing was performed for 1765 out of the 2221 (79%) OC patients. Patients diagnosed with advanced stage OC were more likely to receive tumor DNA testing (OR = 2.5, p < 0.001) than those with low-stage disease. Compared with patients who underwent surgery as primary treatment, those who received chemotherapy or no primary treatment were less likely to be tested (OR = 0.21 and OR = 0.07, respectively, p < 0.001). Patients who died within 100 days were less likely to receive testing (OR = 0.57, p = 0.003). Patients without resection after diagnosis on biopsy/cytology had the lowest Tumor-First testing rates (58% vs. 87-95%, χ2 p < 0.001). Tumor-First testing rates are high. However, OC patients that do not undergo a resection are less likely to undergo testing. With these data strategies to identify hereditary cancer predisposition in patients and their relatives can be further improved.
    Keywords:  BRCA; Genetic testing; Germline; Hereditary cancer; Ovarian cancer; Tumor DNA
    DOI:  https://doi.org/10.1007/s10689-026-00592-x
  6. Cell. 2026 Aug 06. pii: S0092-8674(26)00703-8. [Epub ahead of print]189(16): 4857-4875.e31
    A complete diploid human genome benchmark for personalized genomics.
    Nancy F Hansen, Nathan Dwarshuis, Hyun Joo Ji, Arang Rhie, Hailey Loucks, Glennis A Logsdon, Mitchell R Vollger, Jessica M Storer, Juhyun Kim, Eleni Adam, Nicolas Altemose, Dmitry Antipov, Mobin Asri, Sofia Barreira, Stephanie C Bohaczuk, Andrey V Bzikadze, Sara A Carioscia, Andrew Carroll, Kuan-Hao Chao, Yanan Chu, Arun Das, Peter Ebert, Adam English, Mark Fleharty, Laura E Fleming, Giulio Formenti, Andrea Guarracino, Gabrielle A Hartley, Katharine Jenike, Jenna Kalleberg, Yu Kang, Robert King, Josipa Lipovac, Mira Mastoras, Matthew W Mitchell, Shloka Negi, Nathan D Olson, Keisuke K Oshima, Luis F Paulin, Brandon D Pickett, David Porubsky, Jane Ranchalis, Desh Ranjan, Mikko Rautiainen, Harold Riethman, Robert D Schnabel, Fritz J Sedlazeck, Kishwar Shafin, Mile Sikic, Steven J Solar, Alexander P Sweeten, Winston Timp, Justin Wagner, DongAhn Yoo, Ying Zhou, Erik Garrison, Evan E Eichler, Michael C Schatz, Andrew B Stergachis, Rachel J O'Neill, Karen H Miga, Steven L Salzberg, Sergey Koren, Justin M Zook, Adam M Phillippy.
      Human genome sequencing typically relies on mapping reads to a reference genome to call variants, but this approach introduces technical biases, excluding duplicated and structurally polymorphic regions of the genome. To overcome this, we present a telomere-to-telomere genome benchmark with near-perfect accuracy across 99.4% of the diploid HG002 genome. This benchmark adds 701.4 Mb of autosomal sequence and both sex chromosomes (216.8 Mb), which were absent from prior benchmarks. We annotated genes and repeats on both haplotypes, including 19,956 protein-coding genes on the maternal haplotype and 19,190 on the paternal haplotype, and developed new methods to measure the accuracy of reads, phased variant call sets, and assemblies against a diploid reference. Genome-wide analyses show that de novo assembly resolves 2%-7% more sequence and outperforms variant calling accuracy by an order of magnitude, expanding the reach of genomic medicine to the entire genome and enabling a new era of personalized genomics.
    Keywords:  benchmarking; diploid; genome annotation; genome assembly; genome sequencing; genomics; haplotypes; telomere-to-telomere
    DOI:  https://doi.org/10.1016/j.cell.2026.06.016
  7. Cell. 2026 Aug 06. pii: S0092-8674(26)00817-2. [Epub ahead of print]189(16): 4825-4828
    Filling the holes in whole genomes: A vision for personalized genomics from telomere to telomere.
    Adam M Phillippy, Yafei Mao, Yu Kang, Mile Šikić, Karen H Miga.
      Two decades after the Human Genome Project, we finally have the ability to read the complete genome of any human and (nearly) any species. These sequences provide the ideal foundation for training predictive models of the genome that will accelerate basic research, enable accurate diagnostics, and guide precision medicine.
    DOI:  https://doi.org/10.1016/j.cell.2026.07.019
  8. Nat Methods. 2026 Aug;23(8): 1487
    Inference of tumor spatial habitats.
    Lin Tang.
      
    DOI:  https://doi.org/10.1038/s41592-026-03192-w
  9. Exp Mol Med. 2026 Aug 07.
    Somatic mutations and genome mosaicism in aging and disease.
    Elizabeth Pan, Alexander Maslov, Jan Vijg.
      Age-related genome mosaicism is an inherent feature of multicellularity and genomic instability. It occurs because of DNA mutations, the accumulation of which leads to diverse genomic landscapes across different tissues. DNA mutations in the genome are consequences of DNA damage, changes in the chemical structure of DNA, such as strand breaks or loss of bases. DNA damage is very frequent and normally repaired quickly. However, errors intrinsic to DNA repair or replication can give rise to permanent changes in genome sequence information. Such DNA mutations are diverse and include single-nucleotide variants, small insertions and deletions, and larger genome structural variants. Since the 1950s, somatic mutations have been proposed to be a major cause of aging. Indeed, somatic mutations are the cause of cancer, the risk of which increases exponentially with age, and possibly other age-related diseases, such as neurodegenerative diseases and cardiomyopathies. Somatic mutations vary from cell to cell owing to the innate stochasticity of their occurrence, from error-prone processing of randomly inflicted DNA damage. With the emergence of single-cell and single-molecule sequencing, it has become possible to quantitatively analyze somatic mutations in human cells and tissues. Here, we discuss a possible causal relationship between mutation-driven mosaicism of the somatic genome and aging-related functional decline and disease by exploring several predictions of the somatic mutation theory of aging.
    DOI:  https://doi.org/10.1038/s12276-026-01791-3
This page is being maintained by Thomas Krichel. It was last updated on 2026‒09‒05 at 16:01.