Facilitating Integrative and Personalized Oncology Omics Analysis with UCSCXenaShiny

Overview

Journal Commun Biol

Specialty Biology

Date 2024 Sep 28

PMID 39341906

Authors

Shensuo Li

Yuzhong Peng

Minjun Chen

Yankun Zhao

Yi Xiong

Jianfeng Li

Peng Luo

Haitao Wang

Fei Zhao

Qi Zhao

Yanru Cui

Sujun Chen

Jian-Guo Zhou

Shixiang Wang

Affiliations

Soon will be listed here.

Abstract

The continuous generation of multi-omics and phenotype data is propelling advancements in precision oncology. UCSCXenaShiny was developed as an interactive tool for exploring thousands of cancer datasets available on UCSC Xena. However, its capacity for comprehensive and personalized pan-cancer data analysis is being challenged by the growing demands. Here, we introduce UCSCXenaShiny v2, a milestone update through a variety of improvements. Firstly, by integrating multidimensional data and implementing adaptable sample settings, we create a suite of robust TPC (TCGA, PCAWG, CCLE) analysis pipelines. These pipelines empower users to conduct in-depth analyses of correlation, comparison, and survival in three modes: Individual, Pan-cancer and Batch screen. Additionally, the tool includes download interfaces that enable users to access diverse data and outcomes, several features also facilitate the joint analysis of drug sensitivity and multi-omics of cancer cell lines. UCSCXenaShiny v2 is an open-source R package and a web application, freely accessible at https://github.com/openbiox/UCSCXenaShiny .

References

Barretina J, Caponigro G, Stransky N, Venkatesan K, Margolin A, Kim S . The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature. 2012; 483(7391):603-7. PMC: 3320027. DOI: 10.1038/nature11003. View

Kanehisa M, Furumichi M, Sato Y, Kawashima M, Ishiguro-Watanabe M . KEGG for taxonomy-based analysis of pathways and genomes. Nucleic Acids Res. 2022; 51(D1):D587-D592. PMC: 9825424. DOI: 10.1093/nar/gkac963. View

Wang S, Zhang J, He Z, Wu K, Liu X . The predictive power of tumor mutational burden in lung cancer immunotherapy response is influenced by patients' sex. Int J Cancer. 2019; 145(10):2840-2849. DOI: 10.1002/ijc.32327. View

Newman A, Liu C, Green M, Gentles A, Feng W, Xu Y . Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015; 12(5):453-7. PMC: 4739640. DOI: 10.1038/nmeth.3337. View

Li C, Tang Z, Zhang W, Ye Z, Liu F . GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA. Nucleic Acids Res. 2021; 49(W1):W242-W246. PMC: 8262695. DOI: 10.1093/nar/gkab418. View

Goldman M, Craft B, Hastie M, Repecka K, McDade F, Kamath A . Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol. 2020; 38(6):675-678. PMC: 7386072. DOI: 10.1038/s41587-020-0546-8. View

Sun K, Xu R, Ma F, Yang N, Li Y, Sun X . scRNA-seq of gastric tumor shows complex intercellular interaction with an alternative T cell exhaustion trajectory. Nat Commun. 2022; 13(1):4943. PMC: 9399107. DOI: 10.1038/s41467-022-32627-z. View

Wang S, Xiong Y, Zhao L, Gu K, Li Y, Zhao F . UCSCXenaShiny: an R/CRAN package for interactive analysis of UCSC Xena data. Bioinformatics. 2021; 38(2):527-529. PMC: 8723150. DOI: 10.1093/bioinformatics/btab561. View

Noubade R, Krementsov D, Del Rio R, Thornton T, Nagaleekar V, Saligrama N . Activation of p38 MAPK in CD4 T cells controls IL-17 production and autoimmune encephalomyelitis. Blood. 2011; 118(12):3290-300. PMC: 3179398. DOI: 10.1182/blood-2011-02-336552. View

10.

Aran D, Hu Z, Butte A . xCell: digitally portraying the tissue cellular heterogeneity landscape. Genome Biol. 2017; 18(1):220. PMC: 5688663. DOI: 10.1186/s13059-017-1349-1. View

11.

Feizi N, Kadambat Nair S, Smirnov P, Beri G, Eeles C, Esfahani P . PharmacoDB 2.0: improving scalability and transparency of in vitro pharmacogenomics analysis. Nucleic Acids Res. 2021; 50(D1):D1348-D1357. PMC: 8728279. DOI: 10.1093/nar/gkab1084. View

12.

Sturm G, Finotello F, Petitprez F, Zhang J, Baumbach J, Fridman W . Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 2019; 35(14):i436-i445. PMC: 6612828. DOI: 10.1093/bioinformatics/btz363. View

13.

Xian S, Dosset M, Castro A, Carter H, Zanetti M . Transcriptional analysis links B cells and TERT expression to favorable prognosis in head and neck cancer. PNAS Nexus. 2023; 2(3):pgad046. PMC: 10003760. DOI: 10.1093/pnasnexus/pgad046. View

14.

Li Y, Hu X, Lin R, Zhou G, Zhao L, Zhao D . Single-cell landscape reveals active cell subtypes and their interaction in the tumor microenvironment of gastric cancer. Theranostics. 2022; 12(8):3818-3833. PMC: 9131288. DOI: 10.7150/thno.71833. View

15.

Liu C, Hu F, Xie G, Miao Y, Li X, Zeng Y . GSCA: an integrated platform for gene set cancer analysis at genomic, pharmacogenomic and immunogenomic levels. Brief Bioinform. 2022; 24(1). DOI: 10.1093/bib/bbac558. View

16.

Liberzon A, Subramanian A, Pinchback R, Thorvaldsdottir H, Tamayo P, Mesirov J . Molecular signatures database (MSigDB) 3.0. Bioinformatics. 2011; 27(12):1739-40. PMC: 3106198. DOI: 10.1093/bioinformatics/btr260. View

17.

Saelens W, Cannoodt R, Todorov H, Saeys Y . A comparison of single-cell trajectory inference methods. Nat Biotechnol. 2019; 37(5):547-554. DOI: 10.1038/s41587-019-0071-9. View

18.

Rees M, Seashore-Ludlow B, Cheah J, Adams D, Price E, Gill S . Correlating chemical sensitivity and basal gene expression reveals mechanism of action. Nat Chem Biol. 2015; 12(2):109-16. PMC: 4718762. DOI: 10.1038/nchembio.1986. View

19.

Gu Z . Complex heatmap visualization. Imeta. 2024; 1(3):e43. PMC: 10989952. DOI: 10.1002/imt2.43. View

20.

Li H, Jiang W, Liu S, Yang M, Chen S, Pan Y . Connecting the mechanisms of tumor sex differences with cancer therapy. Mol Cell Biochem. 2023; 479(2):213-231. DOI: 10.1007/s11010-023-04723-1. View