Differences in Immune Gene Expression Profiles of Colorectal Cancer Between African-American and European-American Patients

2020 ◽  
Vol 231 (4) ◽  
pp. S265-S266
Author(s):  
Ernest Ramsay Camp ◽  
Brielle Gerry ◽  
Dongjun Chung ◽  
Victoria Findlay ◽  
Marvella Ford ◽  
...  
2013 ◽  
Vol 162 (2-4) ◽  
pp. 519-529 ◽  
Author(s):  
Chun-Ming Lin ◽  
Chian-Ren Jeng ◽  
Jen-Pei Liu ◽  
En-Chung Lin ◽  
Chih-Cheng Chang ◽  
...  

2004 ◽  
Vol 11 (5) ◽  
pp. 977-982 ◽  
Author(s):  
Paul J. McLaren ◽  
Michael Mayne ◽  
Stuart Rosser ◽  
Teri Moffatt ◽  
Kevin G. Becker ◽  
...  

ABSTRACT Advances in microarray technology have allowed for the monitoring of thousands of genes simultaneously. This technology is of particular interest to immunologists studying infectious diseases, because it provides tremendous potential for investigating host-pathogen interactions at the level of immune gene expression. To date, many studies have focused either on cell lines, where the physiological relevance is questionable, or on mixed cell populations, where the contributions of individual subpopulations are unknown. In the present study, we perform an intrasubject comparison of antigen-stimulated immune gene expression profiles between a mixed population of peripheral blood mononuclear cells (PBMC) and the two predominant cell types found in PBMC, CD4+ and CD8+ T lymphocytes. We show that the microarray profiles of CD4+ and CD8+ T lymphocytes differ from each other as well as from that of the mixed cell population. The independence of the gene expression profiles of different cell types is demonstrated with a ubiquitous antigen (Candida albicans) as well as with a disease-specific antigen (human immunodeficiency virus p24). This study has important implications for microarray studies of host immunity and underscores the importance of profiling the expression of specific cell types.


Meta Gene ◽  
2021 ◽  
pp. 100944
Author(s):  
Masoud Keikha ◽  
Mohammad Ali-Hassanzadeh ◽  
Ramin Bagheri ◽  
Mohsen Karbalaei

Head & Neck ◽  
2015 ◽  
Vol 38 (S1) ◽  
pp. E694-E704 ◽  
Author(s):  
Swati Tomar ◽  
Christian A. Graves ◽  
Diego Altomare ◽  
Sangeeta Kowli ◽  
Susannah Kassler ◽  
...  

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Ben Wan ◽  
Renxian Wang ◽  
Jingjun Nie ◽  
Yuyang Sun ◽  
Bowen Zhang ◽  
...  

Background. Osteosarcoma (OS) patients have a poor response to immunotherapy due to the sheer complexity of the immune system and the nuances of the tumor-immune microenvironment. Methodology. To gain insights into the immune heterogeneity of OS, we identified robust clusters of patients based on the immune gene expression profiles of OS patients in the TARGET database and assessed their reproducibility in an independent cohort collected from the GEO database. The association of comprehensive molecular characterization with reproducible immune subtypes was accessed with ANOVA. Furthermore, we visualized the distribution of individual patients in a tree structure by the graph structure learning-based dimensionality reduction algorithm. Results. We found that 87 OS samples can be divided into 5 immune subtypes, and each of them was associated with distinct clinical outcomes. The immune subtypes also demonstrated widely different patterns in tumor genetic aberrations, tumor-infiltrating, immune cell composition, and cytokine profiles. The immune landscape of OS uncovered the significant intracluster heterogeneity within each subtype and depicted a continuous immune spectrum across patients. Conclusion. The established five immune subtypes in our study suggested immune heterogeneity in OS patients and may provide optimal individual immunotherapy for patients exhibiting OS.


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