University of Birmingham > Talks@bham > CCB seminars > Immune deconvolution methods and their applications on cancer patients

Immune deconvolution methods and their applications on cancer patients

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Jordan McCormick.

Immune deconvolutions methods help us to estimate how much immune cell infiltration for particular cancer type. I will discuss basics of the immune deconvolution’s algorithms/methods and their applications in the colonic adenocarcinoma (COAD). In this study, we analysed the prognostic and diagnostic features of such immune-related genes in the context of colonic adenocarcinoma (COAD). We analysed 17 overlapping gene expression profiles (Bisht et al., 2021) of COAD and healthy samples obtained from TCGA -COAD and public single-cell sequencing resources, to identify potential therapeutic COAD targets. We evaluated the abundance of immune infiltration with those genes using the TIMER (Tumor Immune Estimation Resource) deconvolution method. Subsequently, we developed predictive and survival models to assess the prognostic value of these genes. The LGALS4 (Galectin-4) gene was found to be significantly (P

References 1- Acharjee A, Agarwal P, Nash K, Bano S, Rahman T, Gkoutos GV. Immune infiltration and prognostic and diagnostic use of LGALS4 in colon adenocarcinoma and bladder urothelial carcinoma. Am J Transl Res. 2021 Oct 15;13(10):11353-11363. PMID : 34786063; 2- Bisht V, Nash K, Xu Y, Agarwal P, Bosch S, Gkoutos GV, Acharjee A. Integration of the Microbiome, Metabolome and Transcriptomics Data Identified Novel Metabolic Pathway Regulation in Colorectal Cancer. Int J Mol Sci. 2021 May 28;22(11):5763. doi: 10.3390/ijms22115763.

This talk is part of the CCB seminars series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.


Talks@bham, University of Birmingham. Contact Us | Help and Documentation | Privacy and Publicity.
talks@bham is based on from the University of Cambridge.