Project description:To understand the diversity of expression states in cancer cell lines, we profiled 198 cancer cell lines by single-cell RNA-seq with 10X chromium.
Project description:This pan-cancer cell line proteomic atlas comprises proteomic data acquired by data independent acquisition (specifically, SWATH) mass spectrometry for 949 cancer cell lines. Cell lines were processed in technical triplicate, with duplicates acquired on different mass spectrometers, alongside HEK293T cell line control samples processed across the experimental period. For further details, refer to the publication that accompanies this data deposition.
Project description:Cancer arises from somatic mutations whose effects are executed through dysregulated gene-regulatory programs that reshape chromatin, transcription, and malignant phenotypes. To uncover gene regulatory principles underlying heterogeneous cancer cell states and their linked environmental features, here we present a pan-cancer single-cell, multi-omic atlas of human cancer cell lines, including a compendium of 240,957 transcriptomes and 223,347 chromatin-accessibility profiles from primary cancers spanning 20 tumor types. We revealed extensive pan-cancer cell-state heterogeneity, core gene-regulatory networks, and consensus epithelial–mesenchymal transition (EMT) trajectories that transcend tissue of origin and are governed by conserved epigenomic and transcriptomic features. In addition, our copy-number variation analysis implicated transcription factor amplification, followed by hyperactive downstream regulation, as a major driver of malignant states. Further focused analysis of acral versus cutaneous melanoma cell lines uncovers a universal inflammation-suppressive program in acral melanoma versus an inflamed regulatory landscape in cutaneous melanoma, highlighting the JAK–STAT axis as a key discriminator. Finally, by integrating single-cell and bulk datasets across models and patient cohorts, we revealed tumor–microenvironment co-adaptation in vivo, and this was associated with immunotherapy responsiveness.
Project description:Uncovering dark mass in population proteomics: Pan-analysis of Single Amino-acid Polymorphism (Pan-SAP) revealed quantitative relevance with cognition and aging
Project description:diaPASEF proteomic analysis of KRASG12D mutant cell lines treated with MRTX1133. This dataset is part of a multiomic study featuring the metabolomics and single cell proteomics of 3,000 cells treated with drug. Files are broken into multiple repositories to simplify the deposition and reanalysis of these files.
Project description:Metabolome analysis of 180 cancer cell lines. Intracellular extracts. Flow injection analysis - TOF (negative mode, no LC). Sample description is included in Metadata_File_CellLines.txt