Dataset Information

Cancer-specific immune evasion and substantial heterogeneity within cancer types provide evidence for personalized immunotherapy.

ABSTRACT: The immune response against cancer is orchestrated by various parameters and site-dependent specificities have been poorly investigated. In our analyses of ten different cancer types, we describe elevated infiltration by regulatory T cells as the most common feature, while other lymphocyte subsets and also expression of immune-regulatory molecules on tumor-infiltrating lymphocytes showed site-specific variation. Multiparametric analyses of these data identified similarities of renal and liver or lung with head and neck cancer. Co-expression of immune-inhibitory ligands on tumor cells was most frequent in colorectal, lung and ovarian cancer. Genes related to antigen presentation were frequently dysregulated in liver and lung cancer. Expression of co-inhibitory molecules on tumor-infiltrating T cells accumulated in advanced stages while T-cell abundance was related to enhanced expression of genes related to antigen presentation. Our results promote evaluation of cancer-specific or even personalized immunotherapeutic combinations to overcome primary or secondary resistance as major limitation of immune-checkpoint inhibition.

SUBMITTER: Thelen M

PROVIDER: S-EPMC8208982 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Publications

Cancer-specific immune evasion and substantial heterogeneity within cancer types provide evidence for personalized immunotherapy.

Thelen Martin M Wennhold Kerstin K Lehmann Jonas J Garcia-Marquez Maria M Klein Sebastian S Kochen Elena E Lohneis Philipp P Lechner Axel A Wagener-Ryczek Svenja S Plum Patrick Sven PS Velazquez Camacho Oscar O Pfister David D Dörr Fabian F Heldwein Matthias M Hekmat Khosro K Beutner Dirk D Klussmann Jens Peter JP Thangarajah Fabinshy F Ratiu Dominik D Malter Wolfram W Merkelbach-Bruse Sabine S Bruns Christiane Josephine CJ Quaas Alexander A von Bergwelt-Baildon Michael M Schlößer Hans A HA

NPJ precision oncology 20210616 1

The immune response against cancer is orchestrated by various parameters and site-dependent specificities have been poorly investigated. In our analyses of ten different cancer types, we describe elevated infiltration by regulatory T cells as the most common feature, while other lymphocyte subsets and also expression of immune-regulatory molecules on tumor-infiltrating lymphocytes showed site-specific variation. Multiparametric analyses of these data identified similarities of renal and liver or ...[more]

PMID: 34135436

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Project description:Despite the remarkable progress in probing tumor transcriptomic heterogeneity by single-cell RNA sequencing (sc-RNAseq) data, several gaps exist in prior studies. Tumor heterogeneity is frequently mentioned but not quantified. Clustering analyses typically target cells rather than genes, and differential levels of transcriptomic heterogeneity of gene clusters are not characterized. Relations between gene clusters inferred from multiple datasets remain less explored. We provided a series of quantitative methods to analyze cancer sc-RNAseq data. First, we proposed two quantitative measures to assess intra-tumoral heterogeneity/homogeneity. Second, we established a hierarchy of gene clusters from sc-RNAseq data, devised an algorithm to reduce the gene cluster hierarchy to a compact structure, and characterized the gene clusters with functional enrichment and heterogeneity. Third, we developed an algorithm to align the gene cluster hierarchies from multiple datasets to a small number of meta gene clusters. By applying these methods to nine cancer sc-RNAseq datasets, we discovered that cancer cell transcriptomes were more homogeneous within tumors than the accompanying normal cells. Furthermore, many gene clusters from the nine datasets were aligned to two large meta gene clusters, which had high and low heterogeneity and were enriched with distinct functions. Finally, we found the homogeneous meta gene cluster retained stronger expression coherence and associations with survival times in bulk level RNAseq data than the heterogeneous meta gene cluster, yet the combinatorial expression patterns of breast cancer subtypes in bulk level data were not preserved in single-cell data. The inference outcomes derived from nine cancer sc-RNAseq datasets provide insights about the contributing factors for transcriptomic heterogeneity of cancer cells and complex relations between bulk level and single-cell RNAseq data. They demonstrate the utility of our methods to enable a comprehensive characterization of co-expressed gene clusters in a wide range of sc-RNAseq data in cancers and beyond.

Dataset Information

Cancer-specific immune evasion and substantial heterogeneity within cancer types provide evidence for personalized immunotherapy.

Publications

Cancer-specific immune evasion and substantial heterogeneity within cancer types provide evidence for personalized immunotherapy.

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