bims-tumhet 2025-06-29 papers

Issue of 2025–06–29
four papers selected by
Sergio Marchini, Humanitas Research

Cancers (Basel). 2025 Jun 17. pii: 2026. [Epub ahead of print]17(12):

Genome-Wide cfDNA Methylation Profiling Reveals Robust Hypermethylation Signatures in Ovarian Cancer.

Simone Karlsson Terp, Karen Guldbrandsen, Malene Pontoppidan Stoico, Lasse Ringsted Mark, Anna Poulsgaard Frandsen, Karen Dybkær, Inge Søkilde Pedersen.

Background: Ovarian cancer remains the most lethal gynecological cancer, primarily due to its asymptomatic nature in early stages and consequent late diagnosis. Early detection improves survival, but current biomarkers lack sensitivity and specificity. Cell-free DNA (cfDNA) released from tumor cells captures tumor-associated epigenetic alterations and represents a promising source for minimally invasive biomarkers. Among these, aberrant DNA methylation occurs early in tumorigenesis and may reflect underlying disease biology. This study aimed to investigate genome-wide cfDNA methylation profiles in patients with ovarian cancer, benign ovarian conditions, and healthy controls to identify cancer-associated methylation patterns that may inform future biomarker development. Results: We performed genome-wide cfDNA methylation profiling using cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq) on plasma samples from 40 patients with high-grade serous ovarian carcinoma, 38 patients with benign ovarian conditions, and 38 healthy postmenopausal women. A total of 536 differentially methylated regions (DMRs) were identified between ovarian cancer and controls (n = 76), with 97% showing hypermethylation in ovarian cancer. DMRs were enriched in CpG islands and gene bodies and depleted in repetitive elements, consistent with known cancer-associated methylation patterns. Fifteen genes showed robust hypermethylation across analyses. These genes exhibited methylation across intronic, exonic, and upstream regulatory regions. Separate comparisons of ovarian cancer to each control group (benign and healthy) supported the reproducibility of these findings. Gene Ontology enrichment analysis revealed enrichment in gland development, embryonic morphogenesis, and endocrine regulation, suggesting biological relevance to ovarian tumorigenesis. Conclusions: This study identifies consistent cfDNA hypermethylation patterns in ovarian cancer, affecting genes involved in developmental regulation and hormone-related processes. Our findings underscore the potential of cfMeDIP-seq for detecting tumor-specific methylation signatures in plasma and highlight these 15 hypermethylated genes as biologically relevant targets for future studies on cfDNA methylation in ovarian cancer.

Keywords: Cell-free DNA; DNA methylation; biomarkers; epigenetics; ovarian cancer

DOI: https://doi.org/10.3390/cancers17122026

Nat Genet. 2025 Jun 23.

Predicting resistance to chemotherapy using chromosomal instability signatures.

Chemotherapies are often given without precision biomarkers, exposing patients to toxic side effects without guaranteed benefit. Here we present chromosomal instability signature biomarkers that identify resistance to platinum-, taxane- and anthracycline-based treatments using a single genomic test. In retrospectively emulated randomized-control biomarker clinical trials using real-world cohorts (n = 840), predicted resistant patients had elevated treatment failure risk for taxane (hazard ratio (HR) of 7.44) and anthracycline (HR of 1.88) in ovarian, taxane (HR of 3.98) and anthracycline (HR of 3.69) in metastatic breast and taxane (HR of 5.46) in metastatic prostate. Nonrandomized emulations showed predictive capacity for platinum resistance in ovarian (HR of 1.46) and anthracycline in sarcoma (HR of 3.59). We demonstrate feasibility using whole-genome sequencing, capture-panel sequencing and cell-free DNA. Our findings highlight the clinical value of chromosomal instability signatures in predicting resistance to chemotherapies across multiple cancer types, with the potential to transform the one-size-fits-all chemotherapy approach into precise, tailored treatment.

DOI: https://doi.org/10.1038/s41588-025-02233-y

Int J Mol Sci. 2025 Jun 18. pii: 5839. [Epub ahead of print]26(12):

Refined Procedure to Purify and Sequence Circulating Cell-Free DNA in Prostate Cancer.

Samira Rahimirad, Seta Derderian, Lucie Hamel, Eleonora Scarlata, Ginette McKercher, Fadi Brimo, Raghu Rajan, Alexis Rompre-Brodeur, Wassim Kassouf, Rafael Sanchez-Salas, Armen Aprikian, Simone Chevalier.

Cell-free DNA (cfDNA), a fragmented DNA circulating in blood, is a promising biomarker for cancer diagnosis and monitoring. Standardization of cfDNA isolation to enhance the sensitivity of molecular analyses in prostate cancer (PCa) is required. Towards this goal, we optimized existing methods to obtain a high quantity and quality of cfDNA from low volumes of plasma. The protocol was applied to samples from healthy males and three patient categories: radical prostatectomy (RP), disease-free (>6 years post-RP), and metastatic castration-resistant PCa (mCRPC). The yield was significantly higher in mCRPC cases, and the size of fragments was shorter. We compared for the first time library preparation using two cfDNA inputs and low vs. high sequencing depth. Clonal events were observed irrespective of input and depth, but lower input showed more subclonal events. The clinical application of the refined protocols to cfDNA samples from an mCRPC patient showed no tumor fraction before RP, while it increased to 25% at the advanced stage. Among chromosomal changes and mutations, the androgen receptor gene amplification was detected. Altogether, this comprehensive study on improved cfDNA procedures is highly promising to enhance the quality of liquid biopsy-based research for discoveries and much-needed clinical applications.

Keywords: cell-free DNA; circulating tumor DNA; liquid biopsies; prostate cancer; whole genome sequencing

DOI: https://doi.org/10.3390/ijms26125839

Nucleic Acids Res. 2025 Jun 20. pii: gkaf536. [Epub ahead of print]53(12):

A comprehensive review of spatial transcriptomics data alignment and integration.

Muiz Khan, Suzan Arslanturk, Sorin Draghici.

Spatial data acquisition technologies enable high-throughput quantification of molecular expression in tissue sections maintaining spatial context information. However, performing downstream analysis on a whole tissue section requires the alignment and integration of multiple tissue slices. This is a nontrivial task due to tissue heterogeneity and plasticity. Although manual solutions exist, they are time-consuming and require technical expertise. Hence, automated and robust alignment and integration of multiple slices within and across datasets, individuals, and experiments becomes essential. This study aims to (i) present a comprehensive review of methodologies for spatial transcriptomics (ST) data alignment and integration, (ii) explain the problem, its scope and challenges, and (iii) propose a general pipeline. We review 24 tools addressing multi-slice ST alignment and integration, and tackling key challenges through downstream validation. Tools focusing solely on single-slice ST analyses or multi-omics integration are excluded. We categorize these approaches by methodology (statistical mapping, image processing and registration, and graph-based) in accordance with the generalized pipeline. We evaluate their strengths, limitations, and real-world applications based on task scope and their potential to advance biological insights. Despite improved spatial resolution and 3D tissue reconstruction, significant challenges persist in achieving robust alignment and integration across heterogeneous tissue slices.

DOI: https://doi.org/10.1093/nar/gkaf536