bims-ovdlit 2021-07-11 papers

Issue of 2021–07–11
five papers selected by
Lara Paracchini, Humanitas Research

Trends Cancer. 2021 Jul 01. pii: S2405-8033(21)00122-9. [Epub ahead of print]

Technical and biological constraints on ctDNA-based genotyping.

Circulating tumor DNA (ctDNA) enables real-time genomic profiling of cancer without the need for tissue biopsy. ctDNA-based technology is seeing rapid uptake in clinical practice due to the potential to inform patient management from diagnosis to advanced disease. In metastatic disease, ctDNA can identify somatic mutations, copy-number variants (CNVs), and structural rearrangements that are predictive of therapy response. However, the ctDNA fraction (ctDNA%) is unpredictable and confounds variant detection strategies, undermining confidence in liquid biopsy results. Assay design also influences which types of genomic alterations are identifiable. Here, we describe the relationships between ctDNA%, methodology, and sensitivity-specificity for major classes of genomic alterations in prostate cancer. We provide recommendations to navigate the technical complexities that constrain the detection of clinically relevant genomic alterations in ctDNA.

Keywords: biomarker; clonal hematopoiesis; ctDNA; detection sensitivity; genotyping; mCRPC

DOI: https://doi.org/10.1016/j.trecan.2021.06.001

Front Oncol. 2021 ;11 685065

Comprehensive Landscape of Ovarian Cancer Immune Microenvironment Based on Integrated Multi-Omics Analysis.

Jiacheng Shen, Tingwei Liu, Qiaoli Bei, Shaohua Xu.

Epithelial ovarian cancer has a low response rate to immunotherapy and a complex immune microenvironment that regulates its treatment outcomes. Understanding the immune microenvironment and its molecular basis is of great clinical significance in the effort to improve immunotherapy response and outcomes. To determine the characteristics of the immune microenvironment in ovarian cancer, we stratified ovarian cancer patients into three immune subtypes (C1, C2, and C3) using immune-related genes based on gene expression data from The Cancer Genome Atlas and found that these three subtypes had significant differences in immune characteristics and prognosis. Methylation and copy number variant analysis showed that the immune checkpoint genes that influenced immune response were significantly hypermethylated and highly deleted in the immunosuppressive C3 subtype, suggesting that epigenetic therapy may be able to reverse the efficacy of immunotherapy. In addition, the mutation frequencies of BRCA2 and CDK12 were significantly higher in the C2 subtype than in the other two subtypes, suggesting that mutation of DNA repair-related genes significantly affects the prognosis of ovarian cancer patients. Our study further elucidated the molecular characteristics of the immune microenvironment of ovarian cancer, which providing an effective hierarchical method for the immunotherapy of ovarian cancer patients, and has clinical relevance to the design of new immunotherapies and a reasonable combination strategies.

Keywords: immune classification; immune microenvironment; immunotherapy; multi-omics; ovarian cancer

DOI: https://doi.org/10.3389/fonc.2021.685065

Nat Commun. 2021 Jul 07. 12(1): 4172

Sensitive detection of tumor mutations from blood and its application to immunotherapy prognosis.

Shuo Li, Zorawar S Noor, Weihua Zeng, Mary L Stackpole, Xiaohui Ni, Yonggang Zhou, Zuyang Yuan, Wing Hung Wong, Vatche G Agopian, Steven M Dubinett, Frank Alber, Wenyuan Li, Edward B Garon, Xianghong Jasmine Zhou.

Cell-free DNA (cfDNA) is attractive for many applications, including detecting cancer, identifying the tissue of origin, and monitoring. A fundamental task underlying these applications is SNV calling from cfDNA, which is hindered by the very low tumor content. Thus sensitive and accurate detection of low-frequency mutations (<5%) remains challenging for existing SNV callers. Here we present cfSNV, a method incorporating multi-layer error suppression and hierarchical mutation calling, to address this challenge. Furthermore, by leveraging cfDNA's comprehensive coverage of tumor clonal landscape, cfSNV can profile mutations in subclones. In both simulated and real patient data, cfSNV outperforms existing tools in sensitivity while maintaining high precision. cfSNV enhances the clinical utilities of cfDNA by improving mutation detection performance in medium-depth sequencing data, therefore making Whole-Exome Sequencing a viable option. As an example, we demonstrate that the tumor mutation profile from cfDNA WES data can provide an effective biomarker to predict immunotherapy outcomes.

DOI: https://doi.org/10.1038/s41467-021-24457-2

Genome Med. 2021 Jul 09. 13(1): 111

High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification.

Siel Olbrecht, Pieter Busschaert, Junbin Qian, Adriaan Vanderstichele, Liselore Loverix, Toon Van Gorp, Els Van Nieuwenhuysen, Sileny Han, Annick Van den Broeck, An Coosemans, Anne-Sophie Van Rompuy, Diether Lambrechts, Ignace Vergote.

BACKGROUND: High-grade serous tubo-ovarian cancer (HGSTOC) is characterised by extensive inter- and intratumour heterogeneity, resulting in persistent therapeutic resistance and poor disease outcome. Molecular subtype classification based on bulk RNA sequencing facilitates a more accurate characterisation of this heterogeneity, but the lack of strong prognostic or predictive correlations with these subtypes currently hinders their clinical implementation. Stromal admixture profoundly affects the prognostic impact of the molecular subtypes, but the contribution of stromal cells to each subtype has poorly been characterised. Increasing the transcriptomic resolution of the molecular subtypes based on single-cell RNA sequencing (scRNA-seq) may provide insights in the prognostic and predictive relevance of these subtypes.
METHODS: We performed scRNA-seq of 18,403 cells unbiasedly collected from 7 treatment-naive HGSTOC tumours. For each phenotypic cluster of tumour or stromal cells, we identified specific transcriptomic markers. We explored which phenotypic clusters correlated with overall survival based on expression of these transcriptomic markers in microarray data of 1467 tumours. By evaluating molecular subtype signatures in single cells, we assessed to what extent a phenotypic cluster of tumour or stromal cells contributes to each molecular subtype.
RESULTS: We identified 11 cancer and 32 stromal cell phenotypes in HGSTOC tumours. Of these, the relative frequency of myofibroblasts, TGF-β-driven cancer-associated fibroblasts, mesothelial cells and lymphatic endothelial cells predicted poor outcome, while plasma cells correlated with more favourable outcome. Moreover, we identified a clear cell-like transcriptomic signature in cancer cells, which correlated with worse overall survival in HGSTOC patients. Stromal cell phenotypes differed substantially between molecular subtypes. For instance, the mesenchymal, immunoreactive and differentiated signatures were characterised by specific fibroblast, immune cell and myofibroblast/mesothelial cell phenotypes, respectively. Cell phenotypes correlating with poor outcome were enriched in molecular subtypes associated with poor outcome.
CONCLUSIONS: We used scRNA-seq to identify stromal cell phenotypes predicting overall survival in HGSTOC patients. These stromal features explain the association of the molecular subtypes with outcome but also the latter's weakness of clinical implementation. Stratifying patients based on marker genes specific for these phenotypes represents a promising approach to predict prognosis or response to therapy.

Keywords: High-grade serous tubo-ovarian cancer; Molecular subtypes; Overall survival; Prognosis; Single-cell RNA sequencing; Stromal heterogeneity; Transcriptomic markers; Tumour microenvironment

DOI: https://doi.org/10.1186/s13073-021-00922-x

Curr Opin Oncol. 2021 Jul 06.

Immunotherapy in rare ovarian cancer.

Tina Laga, Ignace Vergote, Els Van Nieuwenhuysen.

PURPOSE OF REVIEW: Ovarian cancer (OC) is a heterogeneous disease and a mounting body of evidence shows that a 'one-size-fits-all' approach is obsolete. Differences in epidemiology, tumor biology, genetic profiles and treatment responses of these different types necessitate a tumor and patient-specific approach. Ninety percentage consists of epithelial OC with 70% being high-grade serous OC. The other rarer subtypes are low-grade serous (5%), clear cell (12%), endometrioid (11%) and mucinous carcinoma (3%). The remaining 10% are nonepithelial rare OCs: germ cell (3%) and sex-cord stromal tumors (7%).
RECENT FINDINGS: Over the past few decades, the 5-year survival rates have only improved modestly, therefore novel therapies are urgently needed. Recently, immunotherapy has been introduced into clinical practice in a number of solid tumors. Although preclinical data confirm the presence of an immunogenic microenvironment in a number of ovarian tumor types, no single-agent immune checkpoint inhibitor has been approved hitherto. Identifying suitable treatment combinations, adequate patient selection and thus correct implementation of immunotherapy remain major challenges.
SUMMARY: In this review, we focus on the rationale of incorporating immune therapy in rare OC, we summarize the recent developments with preclinical data and results of clinical trials, with particular focus on rare ovarian histological subtypes.

DOI: https://doi.org/10.1097/CCO.0000000000000759