Project description:For the understanding of intrinsic cancer cell signatures and the surrounding microenvironment, we provide single-cell 3’ RNA sequencing data on 27,414 cells from 6 CRC patients in core and border tumor regions, as well as in matched normal mucosa. Analysis of primary colorectal cancer and normal mucosa samples depicts a comprehensive cellular landscape of colorectal cancer and potential cellular interactions, which would be a valuable resource for the development of therapeutic strategies.
Project description:For the understanding intrinsic cancer cell signatures and the surrounding microenviroment, we provide single-cell 3' RNA sequencing dataon 63,689 cells from 23 CRC patients with 23 primary colorectal cancer and 10 matched normal mucosa samples. Analysis of primary colorectal cancer and normal mucosa samples depicts a comprehensive cellular landscape of colorectal cancer and potential cellular interaction, which would be a valuable resource for the development of therapeutic strategies.
Project description:We profile single cells from patients with colorectum cancer using Chromium 3’ and 5’ single-cell RNA-sequencing. Patients EXT001, EXT009, and EXT012 from the KUL dataset were first analyzed by Lee et al., 2020, and the raw data are available in ArrayExpress under the accession codes E-MTAB-8410 and E-MTAB-8107. Patients EXT018, EXT048, EXT113, and EXT121 from KUL dataset were previously analyzed by Joanito et al., 2022. The raw data of those patients are available in EGA under the accession codes EGAD00001008584 and EGAD00001008585.
Project description:Microarray analyses for the identification of differences in gene expression patterns have increased our understanding of the molecular genetic events in colorectal cancer. We used gene expression analysis data from recurrent and non-recurrent patients with colorectal cancer to identify differentially expressed probes. Tumor tissues were taken from 81 patients with colorectal cancer, rapidly frozen in RNAlater, and isolated using Trizol. Gene expression pro?les were determined using Affymetrix HG-U133 Plus 2.0 GeneChips.We aimed to identify a molecular signature that can reliably identify colorectal cancer patients at high risk for recurrence.
Project description:Although genomic instability, epigenetic abnormality, and gene expression dysregulation are hallmarks of colorectal cancer, these features have not been simultaneously analyzed at single-cell resolution. Using optimized single-cell multi-omics sequencing together with multi-regional sampling of the primary tumor, lymphatic and distant metastases, we provide insights beyond intratumoral heterogeneity. Genome-wide DNA methylation levels were relatively consistent within a single genetic sub-lineage. The genome-wide DNA demethylation patterns of cancer cells were consistent in all 10 sequenced patients. Our work demonstrates the feasibility of reconstructing genetic lineages, and tracing their epigenomic and transcriptomic dynamics with single-cell multi-omics sequencing.