Genomic alterations in KMT2 family predict outcome of immune checkpoint therapy in multiple cancers.
Peng ZhangYixuan HuangPublished in: Journal of hematology & oncology (2021)
Immune checkpoint therapy (ICT) can produce durable antitumor responses in various cancer types; however, the responses are not universal, and the predictive biomarkers are urgently needed. Growing evidence points to a link between epigenetic regulation and anti-tumor immunity, while clinical data on the association of genomic alterations in transcriptional dysregulation-related genes and ICT clinical benefit are lacking. Histone-lysine N-methyltransferase 2 (KMT2) family proteins methylate lysine 4 on the histone H3 tail at important regulatory regions in the genome and thereby impart crucial functions through modulating chromatin structures and DNA accessibility, which is associated with tumorigenesis, mutagenesis, and immune tolerance in various cancers, indicating its possible correlation with the output of immune checkpoint therapy. We hypothesized that genomic mutations in the KMT2 family have the potential to be a novel predictor of immunotherapeutic efficacy. Through integrative cancer genomic analyses of baseline tumor tissues from multiple cohorts involving immunotherapeutic patients, we uncovered a remarkable correlation between KMT2 family mutation and better immune checkpoint therapy responses in multiple patient cohorts. Then, we gathered all the independent ICT-treated datasets as a combination cohort consisted of 418 patients. Significant enrichment of KMT2 family genomic alterations in responding tumors was observed (odds ratio = 2.60, P value = 1.67e-04). This work distinguished the mutations in the KMT2 family as a potential predictor of favorable ICT response in multiple cancers, highlighting the importance of genomic profiling in immunotherapy.
Keyphrases
- end stage renal disease
- copy number
- newly diagnosed
- ejection fraction
- gene expression
- chronic kidney disease
- peritoneal dialysis
- transcription factor
- prognostic factors
- dna methylation
- crispr cas
- stem cells
- genome wide
- dna damage
- oxidative stress
- high resolution
- big data
- signaling pathway
- patient reported outcomes
- case report
- young adults
- cell therapy
- artificial intelligence
- network analysis
- circulating tumor cells