Characterization of colorectal-cancer-related cDNA clones obtained by subtractive hybridization screening

1997 ◽  
Vol 123 (8) ◽  
pp. 447-451 ◽  
Author(s):  
Jiang Cao ◽  
Xinhan Cai ◽  
Lei Zheng ◽  
Liyi Geng ◽  
Zhengzheng Shi ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Subtractive Hybridization ◽  
Cdna Clones

Characterization of colorectal-cancer-related cDNA clones obtained by subtractive hybridization screening

1997 ◽  
Vol 123 (8) ◽  
pp. 447-451 ◽  
Author(s):  
Jiang Cao ◽  
Xinhan Cai ◽  
Lei Zheng ◽  
Liyi Geng ◽  
Zhengzheng Shi ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Subtractive Hybridization ◽  
Cdna Clones

scholarly journals Isolation and characterization of cDNA clones corresponding to two different human apoC-III alleles.

1985 ◽  
Vol 26 (4) ◽  
pp. 451-456
Author(s):  
S K Karathanasis ◽  
V I Zannis ◽  
J L Breslow
Keyword(s):  
Cdna Clones ◽  
Isolation And Characterization

scholarly journals Rabbit C-reactive protein. Biosynthesis and characterization of cDNA clones.

1986 ◽  
Vol 261 (12) ◽  
pp. 5473-5479 ◽  
Author(s):  
C Syin ◽  
E C Gotschlich ◽  
T Y Liu
Keyword(s):  
Protein Biosynthesis ◽  
Cdna Clones ◽  
C Reactive Protein ◽  
Reactive Protein

scholarly journals Molecular cloning and characterization of human atrial and ventricular myosin alkali light chain cDNA clones.

1988 ◽  
Vol 263 (27) ◽  
pp. 13930-13936
Author(s):  
M Kurabayashi ◽  
I Komuro ◽  
H Tsuchimochi ◽  
F Takaku ◽  
Y Yazaki
Keyword(s):  
Molecular Cloning ◽  
Light Chain ◽  
Cdna Clones ◽  
Ventricular Myosin

Cytometric Profiling of CD133+ Cells in Human Colon Carcinoma Cell Lines Identifies a Common core Phenotype and Cell Type-specific Mosaics

2013 ◽  
Vol 28 (3) ◽  
pp. 267-273 ◽  
Author(s):  
Marica Gemei ◽  
Rosa Di Noto ◽  
Peppino Mirabelli ◽  
Luigi Del Vecchio
Keyword(s):  
Colorectal Cancer ◽  
Stem Cells ◽  
Cancer Stem Cells ◽  
Colon Carcinoma ◽  
Cell Lines ◽  
Carcinoma Cell ◽  
Cell Type ◽  
Carcinoma Cell Lines ◽  
Cell Type Specific

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.

scholarly journals Scope of Artificial Intelligence in Screening and Diagnosis of Colorectal Cancer

2020 ◽  
Vol 9 (10) ◽  
pp. 3313 ◽  
Author(s):  
Hemant Goyal ◽  
Rupinder Mann ◽  
Zainab Gandhi ◽  
Abhilash Perisetti ◽  
Aman Ali ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Colorectal Cancer ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Narrow Band Imaging ◽  
Screening Methods ◽  
Polyp Detection ◽  
Mortality And Morbidity ◽  
Magnifying Chromoendoscopy

Globally, colorectal cancer is the third most diagnosed malignancy. It causes significant mortality and morbidity, which can be reduced by early diagnosis with an effective screening test. Integrating artificial intelligence (AI) and computer-aided detection (CAD) with screening methods has shown promising colorectal cancer screening results. AI could provide a “second look” for endoscopists to decrease the rate of missed polyps during a colonoscopy. It can also improve detection and characterization of polyps by integration with colonoscopy and various advanced endoscopic modalities such as magnifying narrow-band imaging, endocytoscopy, confocal endomicroscopy, laser-induced fluorescence spectroscopy, and magnifying chromoendoscopy. This descriptive review discusses various AI and CAD applications in colorectal cancer screening, polyp detection, and characterization.

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