AI Article Synopsis

  • PD-1/PD-L1 blockade is an immunotherapy strategy with significant potential for cancer treatment, but effective biomarkers for predicting response are lacking.
  • Researchers used data from Cancer Treatment Response gene signature Database and various cancer datasets to identify and analyze potential biomarkers.
  • Key findings suggest that certain biomarkers can predict responses to PD-1/PD-L1 blockade, which may help in making more informed treatment decisions and optimize resource use in cancer care.

Article Abstract

Background: PD-1/PD-L1 blockade is a promising immunotherapeutic strategy with the potential to improve the outcomes of various cancers. However, there is a critically unmet need for effective biomarkers of response to PD-1/PD-L1 blockade.

Materials And Methods: Potential biomarkers of response to PD-1/PD-L1 blockade were obtained from the Cancer Treatment Response gene signature Database (CTR-DB). A comprehensive pan-cancer analysis was done on The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) datasets. Correlations between gene expression and infiltration by immune cells were assessed using TIMER, EPIC, MCPcounter, xCell, CIBERSORT, and quanTIseq. Immunophenoscore (IPS) was used to assess the potential application of the biomarkers to all TCGA tumors.

Results: Analysis of CTR-DB data identified and as potential biomarkers of response to PD-1/PD-L1 blockade. Correlation analysis revealed that in various TCGA cancer datasets, expression level correlated positively with most immune checkpoints and tumor-infiltrating immune cells, while expression level correlated negatively with infiltrating immune cells. IPS analysis demonstrated the ability of and to predict PD-1/PD-L1 blockade responses in various cancers.

Conclusion: and are potential predictors of response to cancer immunotherapy using PD-1/PD-L1 blockade. These biomarkers may guide treatment decisions, leading to precise treatment and minimizing the waste of medical resources.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9421049PMC
http://dx.doi.org/10.3389/fimmu.2022.952059DOI Listing

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