scholarly journals Drug Resistance Mechanisms in Colorectal Cancer Dissected with Cell Type–Specific Dynamic Logic Models

2017 ◽  
Vol 77 (12) ◽  
pp. 3364-3375 ◽  
Author(s):  
Federica Eduati ◽  
Victoria Doldàn-Martelli ◽  
Bertram Klinger ◽  
Thomas Cokelaer ◽  
Anja Sieber ◽  
...  
2013 ◽  
Vol 28 (3) ◽  
pp. 267-273 ◽  
Author(s):  
Marica Gemei ◽  
Rosa Di Noto ◽  
Peppino Mirabelli ◽  
Luigi Del Vecchio

In colorectal cancer, CD133+ cells from fresh biopsies proved to be more tumorigenic than their CD133– counterparts. Nevertheless, the function of CD133 protein in tumorigenic cells seems only marginal. Moreover, CD133 expression alone is insufficient to isolate true cancer stem cells, since only 1 out of 262 CD133+ cells actually displays stem-cell capacity. Thus, new markers for colorectal cancer stem cells are needed. Here, we show the extensive characterization of CD133+ cells in 5 different colon carcinoma continuous cell lines (HT29, HCT116, Caco2, GEO and LS174T), each representing a different maturation level of colorectal cancer cells. Markers associated with stemness, tumorigenesis and metastatic potential were selected. We identified 6 molecules consistently present on CD133+ cells: CD9, CD29, CD49b, CD59, CD151, and CD326. By contrast, CD24, CD26, CD54, CD66c, CD81, CD90, CD99, CD112, CD164, CD166, and CD200 showed a discontinuous behavior, which led us to identify cell type-specific surface antigen mosaics. Finally, some antigens, e.g. CD227, indicated the possibility of classifying the CD133+ cells into 2 subsets likely exhibiting specific features. This study reports, for the first time, an extended characterization of the CD133+ cells in colon carcinoma cell lines and provides a “dictionary” of antigens to be used in colorectal cancer research.


2006 ◽  
Vol 14 (4) ◽  
pp. 693-702 ◽  
Author(s):  
F Comes ◽  
A Matrone ◽  
P Lastella ◽  
B Nico ◽  
F C Susca ◽  
...  

2021 ◽  
Vol 5 (1 (January)) ◽  
pp. 88-93
Author(s):  
Hasan KURTER ◽  
Janberk YEŞİL ◽  
Ezgi DASKIN ◽  
Gizem ÇALIBAŞI KOÇAL ◽  
Hülya ELLİDOKUZ ◽  
...  

2018 ◽  
Author(s):  
Sha Cao ◽  
Wennan Chang ◽  
Changlin Wan ◽  
Yong Zhang ◽  
Jing Zhao ◽  
...  

In light of the marked differences in the intrinsic biological underpinnings and prognostic outcomes among different subtypes, Consensus Molecular Subtype (CMS) classification provides a new taxonomy of colorectal cancer (CRC) solely based on transcriptomics data and has been accepted as a standard rule for CRC stratification. Even though CMS was built on highly cancer relevant features, it suffers from limitations in capturing the promiscuous mechanisms in a clinical setting. There are at least two facts about using transcriptomic data for prognosis prediction: the engagement of genes or pathways that execute the clinical response pathway are highly dynamic and interactive with others; and a predefined patient stratification not only largely decrease the statistical analysis power, but also excludes the fact that clusters of patients that confer similar clinical outcomes may or may not overlap with a pre-defined subgrouping. To enable a flexible and prospective stratified exploration, we here present a novel computational framework based on bi-clustering aiming to identify gene regulatory mechanisms associated with various biological, clinical and drug-resistance features, with full recognition of the transiency of transcriptional regulation and complicacies of patients subgrouping with regards to different biological and clinical settings. Our analysis on multiple large scale CRC transcriptomics data sets using a bi-clustering based formulation suggests that the detected local low rank modules can not only generate new biological understanding coherent to CMS stratification, but also identify predictive markers for prognosis that are general to CRC or CMS dependent, as well as novel alternative drug resistance mechanisms. Our key results include: (1) a comprehensive annotation of the local low rank module landscape of CRC; (2) a mechanistic relationship between different clinical subtypes and outcomes, as well as their characteristic biological underpinnings, visible through a novel consensus map; and (3) a few (novel) resistance mechanisms of Oxaliplatin, 5-Fluorouracil, and the FOLFOX therapy are revealed, some of which are validated on independent datasets.


2016 ◽  
Vol 48 (4) ◽  
pp. 257-273 ◽  
Author(s):  
Alan Barnicle ◽  
Cathal Seoighe ◽  
Aaron Golden ◽  
John M. Greally ◽  
Laurence J. Egan

Region and cell-type specific differences in the molecular make up of colon epithelial cells have been reported. Those differences may underlie the region-specific characteristics of common colon epithelial diseases such as colorectal cancer and inflammatory bowel disease. DNA methylation is a cell-type specific epigenetic mark, essential for transcriptional regulation, silencing of repetitive DNA and genomic imprinting. Little is known about any region-specific variations in methylation patterns in human colon epithelial cells. Using purified epithelial cells and whole biopsies ( n = 19) from human subjects, we generated epigenome-wide DNA methylation data (using the HELP-tagging assay), comparing the methylation signatures of the proximal and distal colon. We identified a total of 125 differentially methylated sites (DMS) mapping to transcription start sites of protein-coding genes, most notably several members of the homeobox ( HOX) family of genes. Patterns of differential methylation were validated with MassArray EpiTYPER. We also examined DNA methylation in whole biopsies, applying a computational technique to deconvolve variation in methylation within cell types and variation in cell-type composition across biopsies. Including inferred epithelial proportions as a covariate in differential methylation analysis applied to the whole biopsies resulted in greater overlap with the results obtained from purified epithelial cells compared with when the covariate was not included. Results obtained from both approaches highlight region-specific methylation patterns of HOX genes in colonic epithelium. Regional variation in methylation patterns has implications for the study of diseases that exhibit regional expression patterns in the human colon, such as inflammatory bowel disease and colorectal cancer.


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