CancerSCEM 2.0: an updated data resource of single-cell expression map across various human cancers

Abstract

The field of single-cell RNA sequencing (scRNA-seq) has advanced rapidly in the past decade, generating significant amounts of valuable data for researchers to study complex tumor profiles. This data is crucial for gaining innovative insights into cancer biology. CancerSCEM (https://ngdc.cncb.ac.cn/cancerscem) is a public resource that integrates, analyzes and visualizes scRNA-seq data related to cancer, and it provides invaluable support to numerous cancer-related studies. With CancerSCEM 2.0, scRNA-seq data have increased from 208 to 1466 datasets, covering tumor, matching-normal and peripheral blood samples across 127 research projects and 74 cancer types. The new version of this resource enhances transcriptome analysis by adding copy number variation evaluation, transcription factor enrichment, pseudotime trajectory construction, and diverse biological feature scoring. It also introduces a new cancer metabolic map at the single-cell level, providing an intuitive understanding of metabolic regulation across different cancer types. CancerSCEM 2.0 has a more interactive analysis platform, including four modules and 14 analytical functions, allowing researchers to perform cancer scRNA-seq data analyses in various dimensions. These enhancements are expected to expand the usability of CancerSCEM 2.0 to a broader range of cancer research and clinical applications, potentially revolutionizing our understanding of cancer mechanisms and treatments.