bims-ovdlit Biomed News
on Ovarian cancer: early diagnosis, liquid biopsy and therapy
Issue of 2023‒01‒22
five papers selected by
Lara Paracchini
Humanitas Research

  1. J Ovarian Res. 2023 Jan 14. 16(1): 11
      BACKGROUND: Cell-free DNA (cfDNA) is emerging as a potential biomarker for the detection of ovarian cancer (OC). Recently, we reported a method based upon cfDNA whole-genome sequencing data including the nucleosome distribution (nucleosome footprinting NF), terminal signature sequence (motif), DNA fragmentation (fragment), and copy number variation (CNV).In the present study, we explored whether multiomics early screening technology in cfDNA can be applied for early screening of ovarian cancer.METHODS: Fifty-nine patients with OC and 100 healthy controls were included in this prospective study. Cell-free DNA was extracted from plasma and analyzed by low-pass whole-genome sequencing. Genomic features were obtained for all samples of the cohort, including copy number variation (CNV), 5'-end motifs, fragmentation profiles, and nucleosome footprinting (NF). An integrated scoring system termed the OC score was developed based on the performance of these four features.
    RESULTS: All four features showed diagnostic potential for OC. Based on the unique genome features of cfDNA, the OC score has high accuracy in distinguishing OC patients from healthy controls (AUC 97.7%; sensitivity 94.7%; specificity 98.0%) as a new comprehensive diagnostic method for OC. The OC score showed a gradual trend from healthy controls to OC patients with different stages, especially for early OC monitoring of concern, which achieved a satisfactory sensitivity (85.7%) at a high specificity.
    CONCLUSIONS: This is the first study evaluating the potential of cell-free DNA for the diagnosis of primary OC using multidimensional early screening technology. We present a promising method to increase the accuracy of prediction in patients with OC.
  2. Ther Adv Med Oncol. 2023 ;15 17588359221148024
      The treatment of high-grade serous ovarian cancer and high-grade endometrioid ovarian cancer has seen significant improvements in recent years, with BRCA1/2 and homologous recombination status guiding a personalized approach which has resulted in improved patient outcomes. However, for other epithelial ovarian cancer subtypes, first-line treatment remains unchanged from the platinum-paclitaxel trials of the early 2000s. In this review, we explore novel therapeutic approaches being adopted in the treatment of clear cell, mucinous, carcinosarcoma and low-grade serous ovarian cancer and the biological rational behind them. We discuss why such disparities exist, the challenges faced in conducting dedicated trials in these rarer histologies and look towards new approaches being adopted to overcome them.
    Keywords:  clear-cell ovarian cancer; clinical trials; epithelial ovarian cancer; low-grade serous ovarian cancer; mucinous ovarian cancer; novel therapeutics
  3. Nat Commun. 2023 Jan 18. 14(1): 287
      Plasma cell-free DNA (cfDNA) are small molecules generated through a non-random fragmentation procedure. Despite commendable translational values in cancer liquid biopsy, however, the biology of cfDNA, especially the principles of cfDNA fragmentation, remains largely elusive. Through orientation-aware analyses of cfDNA fragmentation patterns against the nucleosome structure and integration with multidimensional functional genomics data, here we report a DNA methylation - nuclease preference - cutting end - size distribution axis, demonstrating the role of DNA methylation as a functional molecular regulator of cfDNA fragmentation. Hence, low-level DNA methylation could increase nucleosome accessibility and alter the cutting activities of nucleases during DNA fragmentation, which further leads to variation in cutting sites and size distribution of cfDNA. We further develop a cfDNA ending preference-based metric for cancer diagnosis, whose performance has been validated by multiple pan-cancer datasets. Our work sheds light on the molecular basis of cfDNA fragmentation towards broader applications in cancer liquid biopsy.
  4. Brief Bioinform. 2023 Jan 18. pii: bbad015. [Epub ahead of print]
      DNA-methylation alterations are common in cancer and display unique characteristics that make them ideal markers for tumor quantification and classification. Here we present MIMESIS, a computational framework exploiting minimal DNA-methylation signatures composed by a few dozen informative DNA-methylation sites to quantify and classify tumor signals in tissue and cell-free DNA samples. Extensive analyses of multiple independent and heterogenous datasets including >7200 samples demonstrate the capability of MIMESIS to provide precise estimations of tumor content and to enable accurate classification of tumor type and molecular subtype. To assess our framework for clinical applications, we designed a MIMESIS-informed assay incorporating the minimal signatures for breast cancer. Using both artificial samples and clinical serial cell-free DNA samples from patients with metastatic breast cancer, we show that our approach provides accurate estimations of tumor content, sensitive detection of tumor signal and the ability to capture clinically relevant molecular subtype in patients' circulation. This study provides evidence that our extremely parsimonious approach can be used to develop cost-effective and highly scalable DNA-methylation assays that could support and facilitate the implementation of precision oncology in clinical practice.
    Keywords:  DNA-methylation; bioinformatics; breast cancer; cancer; cell-free DNA; deconvolution; liquid biopsy; precision medicine; tumor content; tumor subtype