Cancer initiation and progression are likely caused by the dysregulation of biological pathways. Gene set analysis (GSA) could improve the signal-to-noise ratio and identify potential biological insights on the gene set level. However, platforms exploring cancer multi-omics data using GSA methods are lacking. In this study, we upgraded our GSCALite to GSCA (gene set cancer analysis, http://bioinfo.life.hust.edu.cn/GSCA) for cancer GSA at genomic, pharmacogenomic and immunogenomic levels. In this improved GSCA, we integrated expression, mutation, drug sensitivity and clinical data from four public data sources for 33 cancer types. We introduced useful features to GSCA, including associations between immune infiltration with gene expression and genomic variations, and associations between gene set expression/mutation and clinical outcomes. GSCA has four main functional modules for cancer GSA to explore, analyze and visualize expression, genomic variations, tumor immune infiltration, drug sensitivity and their associations with clinical outcomes. We used case studies of three gene sets: (i) seven cell cycle genes, (ii) tumor suppressor genes of PI3K pathway and (iii) oncogenes of PI3K pathway to prove the advantage of GSCA over single gene analysis. We found novel associations of gene set expression and mutation with clinical outcomes in different cancer types on gene set level, while on single gene analysis level, they are not significant associations. In conclusion, GSCA is a user-friendly web server and a useful resource for conducting hypothesis tests by using GSA methods at genomic, pharmacogenomic and immunogenomic levels.

Chimeric antigen receptor (CAR) T cell therapy has exhibited dramatic anti-tumor efficacy in clinical trials. In this study, we reported the transcriptome profiles of bone marrow cells in four B cell acute lymphoblastic leukemia (B-ALL) patients before and after CD19-specific CAR-T therapy. CD19-CAR-T therapy remarkably reduced the number of leukemia cells, and three patients achieved bone marrow remission (minimal residual disease negative). The efficacy of CD19-CAR-T therapy on B-ALL was positively correlated with the abundance of CAR and immune cell subpopulations, e.g., CD8+ T cells and natural killer (NK) cells, in the bone marrow. Additionally, CD19-CAR-T therapy mainly influenced the expression of genes linked to cell cycle and immune response pathways, including the NK cell mediated cytotoxicity and NOD-like receptor signaling pathways. The regulatory network analyses revealed that microRNAs (e.g., miR-148a-3p and miR-375), acting as oncogenes or tumor suppressors, could regulate the crosstalk between the genes encoding transcription factors (TFs; e.g., JUN and FOS) and histones (e.g., HIST1H4A and HIST2H4A) involved in CD19-CAR-T therapy. Furthermore, many long non-coding RNAs showed a high degree of co-expression with TFs or histones (e.g., FOS and HIST1H4B) and were associated with immune processes. These transcriptome analyses provided important clues for further understanding the gene expression and related mechanisms underlying the efficacy of CAR-T immunotherapy.

SCAD-Brain: a public database of single cell RNA-seq data in human and mouse brains with Alzheimer's disease