bims-ovdlit Biomed News
on Ovarian cancer: early diagnosis, liquid biopsy and therapy
Issue of 2022‒06‒12
five papers selected by
Lara Paracchini
Humanitas Research

  1. Clin Epigenetics. 2022 Jun 09. 14(1): 74
      BACKGROUND: Ovarian cancer (OC) is a highly lethal gynecologic cancer, and it is hard to diagnose at an early stage. Clinically, there are no ovarian cancer-specific markers for early detection. Here, we demonstrate the use of cell-free DNA (cfDNA) methylomes to detect ovarian cancer, especially the early-stage OC.EXPERIMENTAL DESIGN: Plasma from 74 epithelial ovarian cancer patients, 86 healthy volunteers, and 20 patients with benign pelvic masses was collected. The cfDNA methylomes of these samples were generated by cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq). The differentially methylated regions (DMRs) were identified by the contrasts between tumor and non-tumor groups, and the discrimination performance was evaluated with the iterative training and testing method.
    RESULTS: The DMRs identified for cfDNA methylomes can well discriminate tumor groups and non-tumor groups (ROC values from 0.86 to 0.98). The late-stage top 300 DMRs are more late-stage-specific and failed to detect early-stage OC. However, the early-stage markers have the potential to discriminate all-stage OCs from non-tumor samples.
    CONCLUSIONS: This study demonstrates that cfDNA methylomes generated with cfMeDIP-seq could be used to identify OC-specific biomarkers for OC, especially early OC detection. To detect early-stage OC, the biomarkers should be directly identified from early OC plasma samples rather than mix-stage ones. Further exploration of DMRs from a k larger early-stage OC cohort is warranted.
    Keywords:  Biomarkers; Early cancer detection; Ovarian cancer; cfDNA methylation; cfMeDIP-seq
  2. Nature. 2022 Jun 08.
    Keywords:  Evolution; Genetics
  3. Clin Cancer Res. 2022 Jun 08. pii: clincanres.0296.2022-1-28 03:44:54.997. [Epub ahead of print]
      PURPOSE: The heterogeneity of high-grade serous ovarian cancer (HGSOC) is not well studied, which severely hinders clinical treatment of HGSOC. Thus, it is necessary to characterize the heterogeneity of HGSOC within its tumor microenvironment (TME).EXPERIMENTAL DESIGN: The tumors of seven treatment-naïve HGSOC patients at early or late stages and five age-matched non-malignant ovarian samples were analyzed by deep single-cell RNA sequencing (scRNA-seq).
    RESULTS: A total of 59,324 single cells obtained from HGSOC and non-malignant ovarian tissues were sequenced by scRNA-seq. Among those cells, tumor cells were characterized by a set of EMT-associated gene signature, in which NOTCH1, SNAI2, TGFBR1 and WNT11 was further selected as a genetic panel to predict the poor outcomes of HGSOC patients. Matrix CAFs (mCAFs) expressing α-SMA, vimentin, COL3A, COL10A and MMP11, were the dominant CAFs in HGSOC tumors and could induce epithelial-to-mesenchymal transition (EMT) properties of OC cells in the co-culture system. Specific immune cell subsets such as C7-APOBEC3A M1 macrophages, CD8+ TRM and TEX cells were preferentially enriched in early-stage tumors. Additionally, an immune co-inhibitory receptor TIGIT was highly expressed on CD8+ TEX cells and TIGIT blockade could significantly reduce OC tumor growth in mouse models.
    CONCLUSIONS: Our transcriptomic results analyzed by scRNA-seq delineate a ecosystemic landscape of HGSOC at early or late stages with a focus on its heterogeneity with TME. The major applications of our findings are a four EMT-gene model for prediction of HGSOC patient outcomes, mCAFs' capability of enhancing OC cell invasion and potential therapeutic value of anti-TIGIT treatment.
  4. Nature. 2022 06;606(7913): 250
    Keywords:  Funding; Peer review; Publishing