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:lncRNAs contributes to the development of colorectal cancer (CRC). Analysis of tumor tissues and adjacent non-tumor tissues from 6 colorectal cancer patients was conducted. Results indicate insight into molecular signature of the tumorigenesis of CRC.
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.
Project description:DNA methylation in colorectal cancer diagnosis. The Illumina GoldenGate Methylation Cancer Panel I was used to select a set of candidates markers informative of colorectal cancer diagnosis from 807 cancer-related genes. In the discovery phase, tumor tissue and paired adjacent normal mucosa from 92 colorectal patients were analyzed.
Project description:Colorectal Cancer (CRC) is one of most common cancers in the world and a main treatment in postoperative chemotherapy is oxaliplatin and fluorouracil (FOLFOX), But the effect is different among CRC patients. In this study, LC-MS/MS strategy was used to profile the plasma proteome in FOLFOX benefit and futile group. As a result, a panel of plasma proteins by machine learning from our data was verified for a possible prediction tool in postdiagnosis.
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.