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Single-cell transcriptomes underscore genetically distinct tumor characteristics and microenvironment for hereditary kidney cancers.

ABSTRACT: Our understanding of how each hereditary kidney cancer adapts to its tissue microenvironment is incomplete. Here, we present single-cell transcriptomes of 108,342 cells from patient specimens including from six hereditary kidney cancers. The transcriptomes displayed distinct characteristics of the cell of origin and unique tissue microenvironment for each hereditary kidney cancer. Of note, hereditary leiomyomatosis and renal cell carcinoma (HLRCC)-associated kidney cancer retained some characteristics of proximal tubules, which were completely lost in lymph node metastases and present as an avascular tumor with suppressed T cells and TREM2-high macrophages, leading to immune tolerance. Birt-Hogg-Dubé (BHD)-associated kidney cancer exhibited transcriptomic intratumor heterogeneity (tITH) with increased characteristics of intercalated cells of the collecting duct and upregulation of FOXI1-driven genes, a critical transcription factor for collecting duct differentiation. These findings facilitate our understanding of how hereditary kidney cancers adapt to their tissue microenvironment.

SUBMITTER: Jikuya R

PROVIDER: S-EPMC9301876 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Single-cell transcriptomes underscore genetically distinct tumor characteristics and microenvironment for hereditary kidney cancers.

Jikuya Ryosuke R Murakami Koichi K Nishiyama Akira A Kato Ikuma I Furuya Mitsuko M Nakabayashi Jun J Ramilowski Jordan A JA Hamanoue Haruka H Maejima Kazuhiro K Fujita Masashi M Mitome Taku T Ohtake Shinji S Noguchi Go G Kawaura Sachi S Odaka Hisakazu H Kawahara Takashi T Komeya Mitsuru M Shinoki Risa R Ueno Daiki D Ito Hiroki H Ito Yusuke Y Muraoka Kentaro K Hayashi Narihiko N Kondo Keiichi K Nakaigawa Noboru N Hatano Koji K Baba Masaya M Suda Toshio T Kodama Tatsuhiko T Fujii Satoshi S Makiyama Kazuhide K Yao Masahiro M Shuch Brian M BM Schmidt Laura S LS Linehan W Marston WM Nakagawa Hidewaki H Tamura Tomohiko T Hasumi Hisashi H

iScience 20220525 6

Our understanding of how each hereditary kidney cancer adapts to its tissue microenvironment is incomplete. Here, we present single-cell transcriptomes of 108,342 cells from patient specimens including from six hereditary kidney cancers. The transcriptomes displayed distinct characteristics of the cell of origin and unique tissue microenvironment for each hereditary kidney cancer. Of note, hereditary leiomyomatosis and renal cell carcinoma (HLRCC)-associated kidney cancer retained some character ...[more]

PMID: 35874919

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Project description:PurposeRadiation therapy (RT) is a mainstay of cancer care, and accumulating evidence suggests the potential for synergism with components of the immune response. However, few data describe the tumor immune contexture in relation to RT sensitivity. To address this challenge, we used the radiation sensitivity index (RSI) gene signature to estimate the RT sensitivity of >10,000 primary tumors and characterized their immune microenvironments in relation to the RSI.Methods and materialsWe analyzed gene expression profiles of 10,469 primary tumors (31 types) within a prospective tissue collection protocol. The RT sensitivity of each tumor was estimated by the RSI and respective distributions were characterized. The tumor biology measured by the RSI was evaluated by differentially expressed genes combined with single sample gene set enrichment analysis. Differences in the expression of immune regulatory molecules were assessed and deconvolution algorithms were used to estimate immune cell infiltrates in relation to the RSI. A subset (n = 2368) of tumors underwent DNA sequencing for mutational frequency characterization.ResultsWe identified a wide range of RSI values within and across various tumor types, with several demonstrating nonunimodal distributions (eg, colon, renal, lung, prostate, esophagus, pancreas, and PAM50 breast subtypes; P < .05). Across all tumor types, stratifying RSI at a tumor type-specific median identified 7148 differentially expressed genes, of which 146 were coordinate in direction. Network topology analysis demonstrates RSI measures a coordinated STAT1, IRF1, and CCL4/MIP-1β transcriptional network. Tumors with an estimated high sensitivity to RT demonstrated distinct enrichment of interferon-associated signaling pathways and immune cell infiltrates (eg, CD8+ T cells, activated natural killer cells, M1-macrophages; q < 0.05), which was in the context of diverse expression patterns of various immunoregulatory molecules.ConclusionsThis analysis describes the immune microenvironments of patient tumors in relation to the RSI gene expression signature.

Project description:BackgroundPancreatic cancer (PC) is one of the most lethal malignancies and carries a dismal mortality and morbidity. Four types of RNA modification (namely m6A, m1A, APA and A-to-I) could be catalyzed by distinct enzymatic compounds ("writers"), mediating numerous epigenetic events in carcinogenesis and immunomodulation. We aim to investigate the interplay mechanism of these writers in immunogenomic features and molecular biological characteristics in PC.MethodsWe first accessed the specific expression pattern and transcriptional variation of 26 RNA modification writers in The Cancer Genome Atlas (TCGA) dataset. Unsupervised consensus clustering was performed to divide patients into two RNA modification clusters. Then, based on the differentially expressed genes (DEGs) among two clusters, RNA modification score (WM_Score) model was established to determine RNA modification-based subtypes and was validated in International Cancer Genome Consortium (ICGC) dataset. What's more, we manifested the unique status of WM_Score in transcriptional and post-transcriptional regulation, molecular biological characteristics, targeted therapies and immunogenomic patterns.ResultsWe documented the tight-knit correlations between transcriptional expression and variation of RNA modification writers. We classified patients into two distinct RNA modification patterns (WM_Score_high and _low), The WM_Score_high subgroup was correlated with worse prognosis, Th2/Th17 cell polarization and oncogenic pathways (e.g. EMT, TGF-β, and mTORC1 signaling pathways), whereas the WM_Score_low subgroup associated with favorable survival rate and Th1 cell trend. WM_Score model also proved robust predictive power in interpreting transcriptional and post-transcriptional events. Additionally, the potential targeted compounds with related pathways for the WM_Score model were further identified.ConclusionsOur research unfolds a novel horizon on the interplay network of four RNA modifications in PC. This WM_Score model demonstrated powerful predictive capacity in epigenetic, immunological and biological landscape, providing a theoretical basis for future clinical judgments of PC.

Dataset Information

Single-cell transcriptomes underscore genetically distinct tumor characteristics and microenvironment for hereditary kidney cancers.

Publications

Single-cell transcriptomes underscore genetically distinct tumor characteristics and microenvironment for hereditary kidney cancers.

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