bims-ovdlit 2023-03-05 papers

Issue of 2023–03–05
six papers selected by
Lara Paracchini, Humanitas Research

Nat Genet. 2023 Feb 27.

Multiomic analysis of homologous recombination-deficient end-stage high-grade serous ovarian cancer.

High-grade serous ovarian cancer (HGSC) is frequently characterized by homologous recombination (HR) DNA repair deficiency and, while most such tumors are sensitive to initial treatment, acquired resistance is common. We undertook a multiomics approach to interrogate molecular diversity in end-stage disease, using multiple autopsy samples collected from 15 women with HR-deficient HGSC. Patients had polyclonal disease, and several resistance mechanisms were identified within most patients, including reversion mutations and HR restoration by other means. We also observed frequent whole-genome duplication and global changes in immune composition with evidence of immune escape. This analysis highlights diverse evolutionary changes within HGSC that evade therapy and ultimately overwhelm individual patients.

DOI: https://doi.org/10.1038/s41588-023-01320-2

Nat Protoc. 2023 Feb 27.

cfSNV: a software tool for the sensitive detection of somatic mutations from cell-free DNA.

Shuo Li, Ran Hu, Colin Small, Ting-Yu Kang, Chun-Chi Liu, Xianghong Jasmine Zhou, Wenyuan Li.

Cell-free DNA (cfDNA) in blood, viewed as a surrogate for tumor biopsy, has many clinical applications, including diagnosing cancer, guiding cancer treatment and monitoring treatment response. All these applications depend on an indispensable, yet underdeveloped task: detecting somatic mutations from cfDNA. The task is challenging because of the low tumor fraction in cfDNA. Recently, we developed the computational method cfSNV, the first method that comprehensively considers the properties of cfDNA for the sensitive detection of mutations from cfDNA. cfSNV vastly outperformed the conventional methods that were developed primarily for calling mutations from solid tumor tissues. cfSNV can accurately detect mutations in cfDNA even with medium-coverage (e.g., ≥200×) sequencing, which makes whole-exome sequencing (WES) of cfDNA a viable option for various clinical utilities. Here, we present a user-friendly cfSNV package that exhibits fast computation and convenient user options. We also built a Docker image of it, which is designed to enable researchers and clinicians with a limited computational background to easily carry out analyses on both high-performance computing platforms and local computers. Mutation calling from a standard preprocessed WES dataset (~250× and ~70 million base pair target size) can be carried out in 3 h on a server with eight virtual CPUs and 32 GB of random access memory.

DOI: https://doi.org/10.1038/s41596-023-00807-w

Nat Rev Genet. 2023 Mar 02.

Methods and applications for single-cell and spatial multi-omics.

Katy Vandereyken, Alejandro Sifrim, Bernard Thienpont, Thierry Voet.

The joint analysis of the genome, epigenome, transcriptome, proteome and/or metabolome from single cells is transforming our understanding of cell biology in health and disease. In less than a decade, the field has seen tremendous technological revolutions that enable crucial new insights into the interplay between intracellular and intercellular molecular mechanisms that govern development, physiology and pathogenesis. In this Review, we highlight advances in the fast-developing field of single-cell and spatial multi-omics technologies (also known as multimodal omics approaches), and the computational strategies needed to integrate information across these molecular layers. We demonstrate their impact on fundamental cell biology and translational research, discuss current challenges and provide an outlook to the future.

DOI: https://doi.org/10.1038/s41576-023-00580-2

Climacteric. 2023 Mar 03. 1-7

BRCA carriers after risk-reducing bilateral salpingo-oophorectomy: menopausal hormone therapy knowledge gaps, and the impact of physicians' recommendations.

S Armon, T Miron-Shatz, P Mor, A Tomer, E Levy-Lahad, R Michaelson-Cohen, N Srebnik.

OBJECTIVE: Female carriers of BRCA1/2 gene mutations are at an increased lifetime risk for breast and ovarian cancers. They are recommended to undergo risk-reducing surgery, including bilateral salpingo-oophorectomy (RR-BSO), upon completion of childbearing. RR-BSO surgery decreases morbidity and mortality but results in early menopause. Menopausal hormone therapy (MHT) is under-utilized despite being shown as safe for carriers. We aim to evaluate the factors associated with decision-making regarding MHT use following RR-BSO in healthy BRCA mutation carriers.
METHODS: Female carriers aged <50 years who underwent RR-BSO and were followed in a multidisciplinary clinic completed online multiple-choice and free-text questionnaires.
RESULTS: A total of 142 women met the inclusion criteria and filled the questionnaire: 83 were MHT users and 59 were non-users. MHT users underwent RR-BSO earlier than non-users (40.82 ± 3.91 vs. 42.88 ± 4.34; p < 0.0001). MHT usage was positively associated with MHT explanation (odds ratio 4.318, 95% confidence interval [CI] [1.341-13.902], p = 0.014), and knowledge regarding the safety of MHT and its effects on general health (odds ratio 2.001, 95% CI [1.443-2.774], p < 0.0001). MHT users and non-users retrospectively evaluated their comprehension of RR-BSO consequences as significantly lower than before surgery (p < 0.001).
CONCLUSION: Post-RR-BSO outcomes, including the effects on women's quality of life and its possible mitigation through MHT use, need to be addressed pre surgery by healthcare providers.

Keywords: BRCA carrier; breast cancer; decision-making; menopausal hormone therapy; ovarian cancer; risk-reducing bilateral salpingo-oophorectomy

DOI: https://doi.org/10.1080/13697137.2023.2173567

Nat Methods. 2023 Mar 02.

In silico tissue generation and power analysis for spatial omics.

Ethan A G Baker, Denis Schapiro, Bianca Dumitrascu, Sanja Vickovic, Aviv Regev.

As spatially resolved multiplex profiling of RNA and proteins becomes more prominent, it is increasingly important to understand the statistical power available to test specific hypotheses when designing and interpreting such experiments. Ideally, it would be possible to create an oracle that predicts sampling requirements for generalized spatial experiments. However, the unknown number of relevant spatial features and the complexity of spatial data analysis make this challenging. Here, we enumerate multiple parameters of interest that should be considered in the design of a properly powered spatial omics study. We introduce a method for tunable in silico tissue (IST) generation and use it with spatial profiling data sets to construct an exploratory computational framework for spatial power analysis. Finally, we demonstrate that our framework can be applied across diverse spatial data modalities and tissues of interest. While we demonstrate ISTs in the context of spatial power analysis, these simulated tissues have other potential use cases, including spatial method benchmarking and optimization.

DOI: https://doi.org/10.1038/s41592-023-01766-6

Nat Commun. 2023 Feb 25. 14(1): 1074

A variational algorithm to detect the clonal copy number substructure of tumors from scRNA-seq data.

Antonio De Falco, Francesca Caruso, Xiao-Dong Su, Antonio Iavarone, Michele Ceccarelli.

Single-cell RNA sequencing is the reference technology to characterize the composition of the tumor microenvironment and to study tumor heterogeneity at high resolution. Here we report Single CEll Variational ANeuploidy analysis (SCEVAN), a fast variational algorithm for the deconvolution of the clonal substructure of tumors from single-cell RNA-seq data. It uses a multichannel segmentation algorithm exploiting the assumption that all the cells in a given copy number clone share the same breakpoints. Thus, the smoothed expression profile of every individual cell constitutes part of the evidence of the copy number profile in each subclone. SCEVAN can automatically and accurately discriminate between malignant and non-malignant cells, resulting in a practical framework to analyze tumors and their microenvironment. We apply SCEVAN to datasets encompassing 106 samples and 93,322 cells from different tumor types and technologies. We demonstrate its application to characterize the intratumor heterogeneity and geographic evolution of malignant brain tumors.

DOI: https://doi.org/10.1038/s41467-023-36790-9