Table 2.

List of online resources with comprehensive genomic, transcriptomic, and proteomic datasets derived from cancer cell lines.

Resource Name	Website	Description	Reference
Cancer Cell Line Encyclopedia	https://portals.broadinstitute.org/ccle	The Cancer Cell Line Encyclopedia (CCLE) database was conceived to conduct a detailed genetic and pharmacologic characterization of a large panel of human cancer models (approximately 110 models). Gene expression, mutation, methylation, RNAseq and metabolomics data are downloadable.	[14]
Genomics of Drug Sensitivity in Cancer	https://www.cancerrxgene.org/	This project aims at screening >1000 genetically characterized human cancer cell lines with a wide range of anticancer therapeutics. The sensitivity patterns of the cell lines are correlated with extensive genomic data to identify genetic features that are predictive of sensitivity.	[47]
MD Anderson Cell Lines Project	https://tcpaportal.org/mclp/#/	The MD Anderson Cell Lines Project depicts the expression levels of approximately 230 key cancer-related proteins in 650 independent cell lines. This bioinformatic resource is a comprehensive resource for accessing, visualizing, and analyzing functional proteomics of cancer cell lines.	[17]
Project Achilles	https://depmap.org/portal/achilles/	Project Achilles systematically identifies and catalogs gene essentiality across hundreds of genomically characterized cancer cell lines. For each cell line, a list of genes able to alter cell survival is reported as a result of RNAi and/or CRISPR-Cas9 genetic silencing or knockout of the individual gene. Additionally, these results are linked to the genetic or molecular features of the tumors to provide a “cancer dependency map”.	[53]
Cell Model Passports	https://cellmodelpassports.sanger.ac.uk/	This resource provides large-scale genomic datasets for approximately 1200 cancer cell line and organoid models cataloged. For each model system, it is possible to display associated somatic nucleotide variants, gene expression, copy number variations or methylation data. Its accessibility format is also useful for noncomputational, wet laboratory scientists.	[56]