bims-ovdlit Biomed News
on Ovarian cancer: early diagnosis, liquid biopsy and therapy
Issue of 2022‒05‒08
six papers selected by
Lara Paracchini
Humanitas Research

  1. Methods Mol Biol. 2022 ;2477 3-20
      Single-cell RNA sequencing (scRNA-seq) is emerging as an essential technique for studying the physiology of individual cells in populations. Although well-established and optimized for mammalian cells, research of microorganisms has been faced with major technical challenges for using scRNA-seq, because of their rigid cell wall, smaller cell size and overall lower total RNA content per cell. Here, we describe an easy-to-implement adaptation of the protocol for the yeast Saccharomyces cerevisiae using the 10× Genomics platform, originally optimized for mammalian cells. Introducing Zymolyase, a cell wall-digesting enzyme, to one of the initial steps of single-cell droplet formation allows efficient in-droplet lysis of yeast cells, without affecting the droplet emulsion and further sample processing. In addition, we also describe the downstream data analysis, which combines established scRNA-seq analysis protocols with specific adaptations for yeast, and R-scripts for further secondary analysis of the data.
    Keywords:  10× Genomics; Saccharomyces cerevisiae; Single-cell RNA sequencing; Single-cell omics; Transcriptomics; Yeast
  2. Int J Gynecol Pathol. 2022 Mar 29.
      Peritoneal mesothelioma (PM) and serous neoplasms can be difficult to differentiate, particularly in small biopsies. BRCA1-associated protein 1 (BAP1) is expressed in benign tissues, but over 50% of PMs demonstrate complete loss of nuclear expression. Claudin-4, a tight junction protein, is expressed in most epithelial tumors but not in mesotheliomas. Methylthioadenosine phosphorylase (MTAP) is frequently co-deleted with cyclin-dependent kinase inhibitor 2a in mesotheliomas. These markers have proven useful in separating mesothelioma from its mimics, particularly when tumors are pleural based. In the peritoneum, BAP1 loss has been rarely reported in high-grade serous carcinomas, but overall, these markers have been minimally evaluated in ovarian serous borderline tumors and low-grade serous carcinomas. Thus, we assessed the utility of BAP1, claudin-4, and MTAP in the differential diagnosis of PM and low-grade serous neoplasms. Eighteen PM (16 epithelioid, 1 biphasic, and 1 sarcomatous), 24 low-grade serous carcinomas, and 25 serous borderline tumors were stained for BAP1, claudin-4, and MTAP. Loss of BAP1 nuclear expression was observed in 12 (67%) PM (11 epithelioid, 1 biphasic) but was retained in all serous tumors. Claudin-4 was positive in all serous tumors and negative in all PM. Complete loss of cytoplasmic MTAP was noted in 3 (17%) PMs and 1 (4%) serous borderline tumor, while all low-grade serous carcinomas showed retained expression. BAP1 loss reliably distinguishes PM from serous tumors, although it lacks sensitivity. Claudin-4 is a reliable marker to exclude PM. MTAP loss may occur in both PM and serous tumors, and thus is not useful in distinguishing these entities.
  3. Nat Rev Genet. 2022 May 02.
      Over time, the human DNA methylation landscape accrues substantial damage, which has been associated with a broad range of age-related diseases, including cardiovascular disease and cancer. Various age-related DNA methylation changes have been described, including at the level of individual CpGs, such as differential and variable methylation, and at the level of the whole methylome, including entropy and correlation networks. Here, we review these changes in the ageing methylome as well as the statistical tools that can be used to quantify them. We detail the evidence linking DNA methylation to ageing phenotypes and the longevity strategies aimed at altering both DNA methylation patterns and machinery to extend healthspan and lifespan. Lastly, we discuss theories on the mechanistic causes of epigenetic ageing.
  4. Nat Biotechnol. 2022 May 02.
      Many spatially resolved transcriptomic technologies do not have single-cell resolution but measure the average gene expression for each spot from a mixture of cells of potentially heterogeneous cell types. Here, we introduce a deconvolution method, conditional autoregressive-based deconvolution (CARD), that combines cell-type-specific expression information from single-cell RNA sequencing (scRNA-seq) with correlation in cell-type composition across tissue locations. Modeling spatial correlation allows us to borrow the cell-type composition information across locations, improving accuracy of deconvolution even with a mismatched scRNA-seq reference. CARD can also impute cell-type compositions and gene expression levels at unmeasured tissue locations to enable the construction of a refined spatial tissue map with a resolution arbitrarily higher than that measured in the original study and can perform deconvolution without an scRNA-seq reference. Applications to four datasets, including a pancreatic cancer dataset, identified multiple cell types and molecular markers with distinct spatial localization that define the progression, heterogeneity and compartmentalization of pancreatic cancer.
  5. Front Immunol. 2022 ;13 868813
      Breast cancer development and progression rely not only on the proliferation of neoplastic cells but also on the significant heterogeneity in the surrounding tumor microenvironment. Its unique microenvironment, including tumor-infiltrating lymphocytes, complex myeloid cells, lipid-associated macrophages, cancer-associated fibroblasts (CAFs), and other molecules that promote the growth and migration of tumor cells, has been shown to play a crucial role in the occurrence, growth, and metastasis of breast cancer. However, a detailed understanding of the complex microenvironment in breast cancer remains largely unknown. The unique pattern of breast cancer microenvironment cells has been poorly studied, and neither has the supportive role of these cells in pathogenesis been assessed. Single-cell multiomics biotechnology, especially single-cell RNA sequencing (scRNA-seq) reveals single-cell expression levels at much higher resolution, finely dissecting the molecular characteristics of tumor microenvironment. Here, we review the recent literature on breast cancer microenvironment, focusing on scRNA-seq studies and analyzing heterogeneity and spatial location of different cells, including T and B cells, macrophages/monocytes, neutrophils, and stromal cells. This review aims to provide a more comprehensive perception of breast cancer microenvironment and annotation for their clinical classification, diagnosis, and treatment. Furthermore, we discuss the impact of novel single-cell omics technologies, such as abundant omics exploration strategies, multiomics conjoint analysis mode, and deep learning network architecture, on the future research of breast cancer immune microenvironment.
    Keywords:  breast cancer; heterogeneity; microenvironment; single-cell RNA sequencing; single-cell omics