TY - JOUR
T1 - Decoupling the correlation between cytotoxic and exhausted T lymphocyte states enhances melanoma immunotherapy response prediction
AU - Wang, Binbin
AU - Wang, Kun
AU - Wu, Di
AU - Sahni, Sahil
AU - Jiang, Peng
AU - Ruppin, Eytan
N1 - Publisher Copyright:
© 2024
PY - 2024/6/21
Y1 - 2024/6/21
N2 - Cytotoxic T lymphocyte (CTL) and terminal exhausted T lymphocyte (ETL) activities crucially influence immune checkpoint inhibitor (ICI) response. Despite this, the efficacy of ETL and CTL transcriptomic signatures for response prediction remains limited. Investigating this across the TCGA and publicly available single-cell cohorts, we find a strong positive correlation between ETL and CTL expression signatures in most cancers. We hence posited that their limited predictability arises due to their mutually canceling effects on ICI response. Thus, we developed DETACH, a computational method to identify a gene set whose expression pinpoints to a subset of melanoma patients where the CTL and ETL correlation is low. DETACH enhances CTL's prediction accuracy, outperforming existing signatures. DETACH signature genes activity also demonstrates a positive correlation with lymphocyte infiltration and the prevalence of reactive T cells in the tumor microenvironment (TME), advancing our understanding of the CTL cell state within the TME.
AB - Cytotoxic T lymphocyte (CTL) and terminal exhausted T lymphocyte (ETL) activities crucially influence immune checkpoint inhibitor (ICI) response. Despite this, the efficacy of ETL and CTL transcriptomic signatures for response prediction remains limited. Investigating this across the TCGA and publicly available single-cell cohorts, we find a strong positive correlation between ETL and CTL expression signatures in most cancers. We hence posited that their limited predictability arises due to their mutually canceling effects on ICI response. Thus, we developed DETACH, a computational method to identify a gene set whose expression pinpoints to a subset of melanoma patients where the CTL and ETL correlation is low. DETACH enhances CTL's prediction accuracy, outperforming existing signatures. DETACH signature genes activity also demonstrates a positive correlation with lymphocyte infiltration and the prevalence of reactive T cells in the tumor microenvironment (TME), advancing our understanding of the CTL cell state within the TME.
KW - Biocomputational method
KW - Biological sciences
KW - Cancer
KW - Computational bioinformatics
KW - Immunology
UR - http://www.scopus.com/inward/record.url?scp=85193813732&partnerID=8YFLogxK
U2 - 10.1016/j.isci.2024.109926
DO - 10.1016/j.isci.2024.109926
M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???
C2 - 38832027
AN - SCOPUS:85193813732
SN - 2589-0042
VL - 27
JO - iScience
JF - iScience
IS - 6
M1 - 109926
ER -