Cancer-associated fi broblasts (CAF) are major players in the progression and drug resistance of pancreatic ductal adenocarcinoma (PDAC). CAFs constitute a diverse cell population consisting of several recently described subtypes, although the extent of CAF heterogeneity has remained undefi ned. Here we use single-cell RNA sequencing to thoroughly characterize the neoplastic and tumor microenvironment content of human and mouse PDAC tumors. We corroborate the presence of myofi broblastic CAFs and infl ammatory CAFs and defi ne their unique gene signatures in vivo. Moreover, we describe a new population of CAFs that express MHC class II and CD74, but do not express classic costimulatory molecules. We term this cell population "antigenpresenting CAFs" and fi nd that they activate CD4 + T cells in an antigen-specifi c fashion in a model system, confi rming their putative immune-modulatory capacity. Our cross-species analysis paves the way for investigating distinct functions of CAF subtypes in PDAC immunity and progression. SIGNIFICANCE : Appreciating the full spectrum of fi broblast heterogeneity in pancreatic ductal adenocarcinoma is crucial to developing therapies that specifi cally target tumor-promoting CAFs. This work identifi es MHC class II-expressing CAFs with a capacity to present antigens to CD4 + T cells, and potentially to modulate the immune response in pancreatic tumors.
Intratumoral heterogeneity is a major obstacle to cancer treatment and a significant confounding factor in bulk-tumor profiling. We performed an unbiased analysis of transcriptional heterogeneity in colorectal tumors and their microenvironments using single-cell RNA-seq from 11 primary colorectal tumors and matched normal mucosa. To robustly cluster single-cell transcriptomes, we developed reference component analysis (RCA), an algorithm that substantially improves clustering accuracy. Using RCA, we identified two distinct subtypes of cancer-associated fibroblasts (CAFs). Additionally, epithelial-mesenchymal transition (EMT)-related genes were found to be upregulated only in the CAF subpopulation of tumor samples. Notably, colorectal tumors previously assigned to a single subtype on the basis of bulk transcriptomics could be divided into subgroups with divergent survival probability by using single-cell signatures, thus underscoring the prognostic value of our approach. Overall, our results demonstrate that unbiased single-cell RNA-seq profiling of tumor and matched normal samples provides a unique opportunity to characterize aberrant cell states within a tumor.
Glioma intratumoral heterogeneity enables adaptation to challenging microenvironments and contributes to therapeutic resistance. We integrated 914 single-cell DNA methylomes, 55,284 single-cell transcriptomes, and bulk multi-omic profiles across 11 adult IDH-mutant or IDH-wild-type gliomas to delineate sources of intratumoral heterogeneity. We show that local DNA methylation disorder associates with cell-to-cell DNA methylation differences, is elevated in more aggressive tumors, links with transcriptional disruption, and is altered during environmental stress response. Glioma cells under
in vitro
hypoxic and irradiation stress increased local DNA methylation disorder and shifted cell states. We identified a positive association between genetic and epigenetic instability that was supported in bulk longitudinally collected DNA methylation data. Increased DNA methylation disorder associated with accelerated disease progression, and recurrently selected DNA methylation changes were enriched for environmental stress response pathways. Our work identifies an epigenetically facilitated adaptive stress response process and highlights the importance of epigenetic heterogeneity in shaping therapeutic outcomes.
Sample heterogeneity often masks DNA methylation signatures in subpopulations of cells. Here, we present a method to genotype single cells while simultaneously interrogating gene expression and DNA methylation at multiple loci. We used this targeted multimodal approach, implemented on an automated, high-throughput microfluidic platform, to assess primary lung adenocarcinomas and human fibroblasts undergoing reprogramming by profiling epigenetic variation among cell types identified through genotyping and transcriptional analysis.
Endometriosis is characterized by growth of endometrial-like tissue outside of the uterus affecting many women in their reproductive age, causing years of pelvic pain and potential infertility. Its pathophysiology remains largely unknown, limiting diagnosis and treatment. We characterized peritoneal and ovarian lesions at single-cell transcriptome resolution and compared to matched eutopic endometrium, control endometrium, and organoids derived from these tissues, generating data on over 100,000 cells across 12 individuals. We spatially localized many of the cell types using imaging mass cytometry. We identify a perivascular mural cell unique to the peritoneal lesions with dual roles in angiogenesis promotion and immune cell trafficking. We define an immunotolerant peritoneal niche, fundamental differences in eutopic endometrium and between lesions microenvironments, and a novel progenitor-like epithelial cell subpopulation. Altogether, this study provides a holistic view of the endometriosis microenvironment representing the first comprehensive cell atlas of the disease, essential information for advancing therapeutics and diagnostics.
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