bims-tumhet Biomed News
on Tumor Heterogeneity
Issue of 2025–01–26
ten papers selected by
Sergio Marchini, Humanitas Research
  1. Mechanisms and technologies in cancer epigenetics.
  2. MethylBERT enables read-level DNA methylation pattern identification and tumour deconvolution using a Transformer-based model.
  3. Ovarian clear cell carcinoma: open questions on the management and treatment algorithm.
  4. Quantifying intratumoral biomarker heterogeneity in tubo-ovarian high-grade serous carcinoma to optimize clinical translation.
  5. Optimization of pre-analytical handling to maintain DNA integrity in diagnostic Papanicolaou tests.
  6. Liquid biopsy in cancer management: Integrating diagnostics and clinical applications.
  7. A practical guide for choosing an optimal spatial transcriptomics technology from seven major commercially available options.
  8. PARP inhibitors differentially regulate immune responses in distinct genetic backgrounds of high-grade serous tubo-ovarian carcinoma models.
  9. Spatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneity.
  10. Benchmarking cell type annotation methods for 10x Xenium spatial transcriptomics data.
  1. Front Oncol. 2024 ;14 1513654
    Mechanisms and technologies in cancer epigenetics.
    Zaki A Sherif, Olorunseun O Ogunwobi, Habtom W Ressom.
      Cancer's epigenetic landscape, a labyrinthine tapestry of molecular modifications, has long captivated researchers with its profound influence on gene expression and cellular fate. This review discusses the intricate mechanisms underlying cancer epigenetics, unraveling the complex interplay between DNA methylation, histone modifications, chromatin remodeling, and non-coding RNAs. We navigate through the tumultuous seas of epigenetic dysregulation, exploring how these processes conspire to silence tumor suppressors and unleash oncogenic potential. The narrative pivots to cutting-edge technologies, revolutionizing our ability to decode the epigenome. From the granular insights of single-cell epigenomics to the holistic view offered by multi-omics approaches, we examine how these tools are reshaping our understanding of tumor heterogeneity and evolution. The review also highlights emerging techniques, such as spatial epigenomics and long-read sequencing, which promise to unveil the hidden dimensions of epigenetic regulation. Finally, we probed the transformative potential of CRISPR-based epigenome editing and computational analysis to transmute raw data into biological insights. This study seeks to synthesize a comprehensive yet nuanced understanding of the contemporary landscape and future directions of cancer epigenetic research.
    Keywords:  DNA methylation; cancer; chromatin; epigenetic therapy; epigenetics; histone modifications; non-coding RNAs; tumorigenesis
    DOI:  https://doi.org/10.3389/fonc.2024.1513654
  2. Nat Commun. 2025 Jan 17. 16(1): 788
    MethylBERT enables read-level DNA methylation pattern identification and tumour deconvolution using a Transformer-based model.
    Yunhee Jeong, Clarissa Gerhäuser, Guido Sauter, Thorsten Schlomm, Karl Rohr, Pavlo Lutsik.
      DNA methylation (DNAm) is a key epigenetic mark that shows profound alterations in cancer. Read-level methylomes enable more in-depth analyses, due to their broad genomic coverage and preservation of rare cell-type signals, compared to summarized data such as 450K/EPIC microarrays. Here, we propose MethylBERT, a Transformer-based model for read-level methylation pattern classification. MethylBERT identifies tumour-derived sequence reads based on their methylation patterns and local genomic sequence, and estimates tumour cell fractions within bulk samples. In our evaluation, MethylBERT outperforms existing deconvolution methods and demonstrates high accuracy regardless of methylation pattern complexity, read length and read coverage. Moreover, we show its applicability to cell-type deconvolution as well as non-invasive early cancer diagnostics using liquid biopsy samples. MethylBERT represents a significant advancement in read-level methylome analysis and enables accurate tumour purity estimation. The broad applicability of MethylBERT will enhance studies on both tumour and non-cancerous bulk methylomes.
    DOI:  https://doi.org/10.1038/s41467-025-55920-z
  3. Oncologist. 2025 Jan 17. pii: oyae325. [Epub ahead of print]30(1):
    Ovarian clear cell carcinoma: open questions on the management and treatment algorithm.
    Roberta Rosso, Margherita Turinetto, Fulvio Borella, Nicolas Chopin, Pierre Meeus, Alexandra Lainè, Isabelle Ray-Coquard, Olivia Le Saux, Domenico Ferraioli.
      Ovarian clear cell carcinoma (OCCC) accounts for ~10% of all epithelial ovarian cancers and is considered a different entity from the more common high-grade serous ovarian carcinoma (HGSC), with distinct clinical presentations, different risk, and prognostic factors, and specific molecular features. Most OCCCs are diagnosed at an early stage and show favorable outcomes, in contrast to those diagnosed at advanced stages, which exhibit intrinsic resistance to platinum-based chemotherapy regimens and a very poor prognosis. The standard treatment of advanced OCCC is currently based on primary debulking surgery followed by platinum-based chemotherapy according to recent international guidelines. However, these recommendations are extrapolated from several trials mainly featuring a large cohort of HGSC, with only a small minority of OCCC. Because of its rarity, many questions remain unanswered regarding the surgical and medical treatment. Lymph node staging, fertility-sparing treatment, the use of targeted therapies and radiotherapy as well as the adjuvant treatment for early-stage disease and second or further lines of chemotherapy are still under debate. This review aims to address these unresolved issues, by providing a comprehensive overview of the current data on this disease, and to suggest possible directions for future research.
    Keywords:  clear cell; clear cell ovarian carcinoma; management; ovarian cancer; prognosis; target therapy; treatment
    DOI:  https://doi.org/10.1093/oncolo/oyae325
  4. Sci Rep. 2025 Jan 20. 15(1): 2459
    Quantifying intratumoral biomarker heterogeneity in tubo-ovarian high-grade serous carcinoma to optimize clinical translation.
    Aline Talhouk, Derek S Chiu, Liliane Meunier, Kurosh Rahimi, Cécile Le Page, Monique Bernard, Diane Provencher, David G Huntsman, Anne Marie Mes Masson, Martin Köbel.
      Intratumoral heterogeneity (ITH) is spatial, phenotypic, or molecular differences within the same tumor that have important implications for accurate tumor classification and assessment of predictive biomarkers. The Canadian Ovarian Experimental Unified Resource (COEUR) has created a cohort of 437 FFPE tissue specimens from 108 tubo-ovarian high-grade serous carcinoma (HGSC) patients to quantify ITH across the anatomical sites and between primary and recurrence. We quantified the ITH of six clinically used immunohistochemical diagnostic and prognostic biomarkers (WT1, p53, p16, PR, CD8, and Ki67). Markers were stained on tissue microarrays and scored using a continuous or categorical interpretation of staining patterns. Two-way random effect and nested intraclass correlation were used to assess continuous markers, and Gwet's AC1 was used for categorical markers. All biomarkers showed at least substantial agreement over several spatial comparisons, with WT1, p53 and p16 showing almost perfect agreement for most spatial comparisons. Similarly, categorical WT1, p53 and p16 showed almost perfect agreement for temporal comparisons, while the agreement for primary versus recurrence for PR, CD8 and Ki67 was only fair. We provide power calculations to achieve reliability of > 0.60 and recommend testing emerging protein biomarkers to see whether they reach a clinically acceptable benchmark level of ITH.
    Keywords:  CD8; High-grade serous; Intratumoral heterogeneity; Ovarian cancer; TP53; WT1
    DOI:  https://doi.org/10.1038/s41598-024-82206-z
  5. J Mol Diagn. 2025 Jan 17. pii: S1525-1578(25)00011-X. [Epub ahead of print]
    Optimization of pre-analytical handling to maintain DNA integrity in diagnostic Papanicolaou tests.
    Sara Schumacher, Jacob Malchau Lauesgaard, Therese Carlsson, Anna Linder, Karin Sundfeldt.
      Cell-free DNA of ovarian tumor origin can be detected in samples from the gynecologic tract. This study aims to evaluate how pre-analytical handling, and storage conditions affect DNA profile and integrity in Pap tests, to optimize its potential for detection of ovarian cancers (OC). Analysis of archived Pap tests from OC patients, kept at RT for 48h and stored at -80°C was complemented by in vitro experiments. Temperature-associated effects on DNA fragmentation were evaluated in samples stored at 4°C, -20°C or -80°C. Time-dependent DNA degradation at RT was evaluated in comparison to storage at 4°C (0-96h). Results were validated in prospectively collected Pap tests. The DNA integrity was assessed by fragment analysis. Accumulation of short DNA fragments was observed in archived Pap tests from OC patients. In vitro, fragments of 100-350bp increased 11.5-fold within 48h at RT compared to 1.7-fold when stored at 4°C. Consistent with the in vitro findings, prospectively collected samples showed reduced fragmentation when stored at 4°C compared to RT (p=0.007). Long-term storage at 4°C had a significant negative effect on DNA stability (p=0.013), while freezing slowed down fragmentation. This study highlights the need for optimization of pre-analytical handling for cfDNA analysis. Immediate storage at 4°C after sampling markedly reduces DNA degradation suggesting a simple way to decrease unwanted fragmentation for cfDNA analysis in Pap tests.
    Keywords:  DNA fragmentation; Pap test; cell-free DNA (cfDNA); gynecologic cancer
    DOI:  https://doi.org/10.1016/j.jmoldx.2024.12.008
  6. Pract Lab Med. 2025 Jan;43 e00446
    Liquid biopsy in cancer management: Integrating diagnostics and clinical applications.
    Shashwat Pandey, Preeti Yadav.
      Liquid biopsy is an innovative, minimally invasive diagnostic tool revolutionizing cancer management by enabling the detection and analysis of cancer-related biomarkers from bodily fluids such as blood, urine, or cerebrospinal fluid. Unlike traditional tissue biopsies, which require invasive procedures, liquid biopsy offers a more accessible and repeatable method for tracking cancer progression, detecting early-stage cancers, and monitoring therapeutic responses. The technology primarily focuses on analyzing circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and other cancer-derived genetic materials. These biomarkers provide critical information on tumor heterogeneity, mutation profiles, and potential drug resistance. In clinical practice, liquid biopsy has demonstrated its utility in identifying actionable mutations, guiding personalized treatment strategies, and assessing minimal residual disease (MRD). While liquid biopsy holds immense promise, challenges related to its sensitivity, specificity, and standardization remain. Efforts to optimize pre-analytical and analytical processes, along with the establishment of robust regulatory frameworks, are crucial for its widespread clinical adoption. This abstract highlights the transformative potential of liquid biopsy in cancer diagnosis, prognosis, and treatment monitoring, emphasizing its role in advancing personalized oncology. Further research, clinical trials, and regulatory harmonization will be vital in realizing its full potential in precision cancer care.
    Keywords:  Cancer; Liquid biopsy; Personalized medicine; Tissue biopsy
    DOI:  https://doi.org/10.1016/j.plabm.2024.e00446
  7. BMC Genomics. 2025 Jan 20. 26(1): 47
    A practical guide for choosing an optimal spatial transcriptomics technology from seven major commercially available options.
    Hyun Ju Lim, Ye Wang, Anton Buzdin, Xinmin Li.
      Spatial transcriptomics technology enables the mapping of gene expression within tissues, allowing researchers to visualize the spatial distribution of RNA molecules and gain insights into cellular organization, interactions, and functions in their native environments. A variety of spatial technologies are now commercially available, each offering distinct technical parameters such as cellular resolution, detection sensitivity, gene coverage, and throughput. This wide range of options can make it challenges or create confusion for researchers to select the most appropriate platform for their specific research objectives. In this paper, we will analyze and compare seven major commercially available spatial platforms to guide researchers in choosing the most suitable option for their needs.
    Keywords:  10X Visium; 10X visium HD; CosMx SMI; GeoMx DSP; Merscope; RNA sequencing; Spatial transcriptomics; Stereoseq; Xenium
    DOI:  https://doi.org/10.1186/s12864-025-11235-3
  8. Cancer Res Commun. 2025 Jan 24.
    PARP inhibitors differentially regulate immune responses in distinct genetic backgrounds of high-grade serous tubo-ovarian carcinoma models.
    Luiza Doro Pereira, Monica Wielgos-Bonvallet, Selim Misirlioglu, Alireza Khodadadi-Jamayran, Petar Jelinic, Douglas A Levine.
      Immune checkpoint inhibitors (ICIs) have revolutionized treatment for several tumor indications without demonstrated benefit for ovarian cancer patients. To improve the therapeutic ratio of ICIs in ovarian cancer patients, several different clinical trials are testing combinations with poly (ADP-ribose) polymerase (PARP) inhibitors. Comparing the immunomodulatory effects of clinically advanced PARP inhibitors may help to identify the best partner to combine with ICIs. We examined the treatment effect of talazoparib (a PARP trapper) and veliparib (a solely PARP enzymatic inhibitor) in homologous recombination deficient (HRD) and homologous recombination proficient (HRP) high-grade serous tubo-ovarian carcinoma (HGSC) cell lines on immune-related gene expression. We discovered and validated that CXCL8, IL-6, and TNF gene expression were upregulated after talazoparib treatment in both OVCAR3 (HRD) and CAOV3 (HRP) HGSC cell lines. In contrast, veliparib treatment slightly elevated similar genes exclusively in a HRD HGSC cell line model. We expanded these studies to include olaparib, a PARP trapper less potent than talazoparib, and found effects specific to COV361 (BRCA1 mutant) and OVCAR8 (BRCA1 methylated) HGSC cells but not all HRD HGSC cell lines. Our studies also identified differences among PARP trappers versus veliparib on augmenting CXCL10 expression. Finally, we show that talazoparib modulates the CXCL10 response in cGAS-defective cell lines, independent of the cGAS-STING pathway. These mechanistic studies advance our understanding of how different PARP inhibitors affect the immune system in various genetic backgrounds.
    DOI:  https://doi.org/10.1158/2767-9764.CRC-24-0515
  9. Cell Biosci. 2025 Jan 23. 15(1): 7
    Spatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneity.
    Binbin Liu, Yumo Xie, Yu Zhang, Guannan Tang, Jinxin Lin, Ze Yuan, Xiaoxia Liu, Xiaolin Wang, Meijin Huang, Yanxin Luo, Huichuan Yu.
       BACKGROUND: Intratumoral heterogeneity emerges from accumulating genetic and epigenetic changes during tumorigenesis, which may contribute to therapeutic failure and drug resistance. However, the lack of a quick and convenient approach to determine the intratumoral epigenetic heterogeneity (eITH) limit the application of eITH in clinical settings. Here, we aimed to develop a tool that can evaluate the eITH using the DNA methylation profiles from bulk tumors.
    METHODS: Genomic DNA of three laser micro-dissected tumor regions, including digestive tract surface, central bulk, and invasive front, was extracted from formalin-fixed paraffin-embedded sections of colorectal cancer patients. The genome-wide methylation profiles were generated with methylation array. The most variable methylated probes were selected to construct a DNA methylation-based heterogeneity (MeHEG) estimation tool that can deconvolve the proportion of each reference tumor region with the support vector machine model-based method. A PCR-based assay for quantitative analysis of DNA methylation (QASM) was developed to specifically determine the methylation status of each CpG in MeHEG assay at single-base resolution to realize fast evaluation of epigenetic heterogeneity.
    RESULTS: In the discovery set with 79 patients, the differentially methylated CpGs among the three tumor regions were found. The 7 most representative CpGs were identified and subsequently selected to develop the MeHEG algorithm. We validated its performance of deconvolution of tumor regions in an independent cohort. In addition, we showed the significant association of MeHEG-based epigenetic heterogeneity with the genomic heterogeneity in mutation and copy number variation in our in-house and TCGA cohorts. Besides, we found that the patients with higher MeHEG score had worse disease-free and overall survival outcomes. Finally, we found dynamic change of epigenetic heterogeneity based on MeHEG score in cancer cells under the treatment of therapeutic drugs.
    CONCLUSION: By developing a 7-loci panel using a machine learning approach combined with the QASM assay for PCR-based application, we present a valuable method for evaluating intratumoral heterogeneity. The MeHEG algorithm offers novel insights into tumor heterogeneity from an epigenetic perspective, potentially enriching current knowledge of tumor complexity and providing a new tool for clinical and research applications in cancer biology.
    Keywords:  Colorectal cancer; DNA methylation; Epigenetic; Intratumor heterogeneity
    DOI:  https://doi.org/10.1186/s13578-024-01337-y
  10. BMC Bioinformatics. 2025 Jan 20. 26(1): 22
    Benchmarking cell type annotation methods for 10x Xenium spatial transcriptomics data.
    Jinming Cheng, Xinyi Jin, Gordon K Smyth, Yunshun Chen.
       BACKGROUND: Imaging-based spatial transcriptomics technologies allow us to explore spatial gene expression profiles at the cellular level. Cell type annotation of imaging-based spatial data is challenging due to the small gene panel, but it is a crucial step for downstream analyses. Many good reference-based cell type annotation tools have been developed for single-cell RNA sequencing and sequencing-based spatial transcriptomics data. However, the performance of the reference-based cell type annotation tools on imaging-based spatial transcriptomics data has not been well studied yet.
    RESULTS: We compared performance of five reference-based methods (SingleR, Azimuth, RCTD, scPred and scmapCell) with the marker-gene-based manual annotation method on an imaging-based Xenium data of human breast cancer. A practical workflow has been demonstrated for preparing a high-quality single-cell RNA reference, evaluating the accuracy, and estimating the running time for reference-based cell type annotation tools.
    CONCLUSIONS: SingleR was the best performing reference-based cell type annotation tool for the Xenium platform, being fast, accurate and easy to use, with results closely matching those of manual annotation.
    Keywords:  Cell type annotation; Imaging-based; Reference-based annotation; Single-cell; Spatial transcriptomics; Xenium
    DOI:  https://doi.org/10.1186/s12859-025-06044-0
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