A mutational process signature and genomic alterations associated with outcome and immunogenicity in cancers with brain metastasis.

BACKGROUND

Brain metastasis (BM) is one of the common ways of tumor metastasis and has a poor prognosis. This study aims to identify potential biomarkers from the perspective of somatic mutations, providing a basis for the prognosis evaluation and immunogenicity prediction of BM patients.

METHODS

This study collected the somatic mutation profiles and clinical information of a total of 421 patients with BM in Memorial Sloan Kettering Cancer Center (MSKCC). Non-negative matrix factorization was employed to extract the mutational process signatures operating in the genome. Consensus clustering analysis was utilized to identify mutation-related molecular subtypes. Through a comprehensive analysis of genomic mutations and copy number variations (CNV), biomarkers associated with outcomes and tumor immunogenicity were screened.

RESULTS

Non-small cell lung cancer, melanoma, and breast cancer were common primary tumors of BM, and these three tumor types exhibited better prognosis compared to other types. This study found that a higher tumor mutation burden (TMB) was significantly associated with a better prognosis of BM. A total of four mutational process signatures were extracted, and among them, a signature featured by C > T mutations and related to DNA damage repair was proven to be linked with an inferior outcome and a lower TMB. Through integrated genomic mutation analysis, mutation was determined to associate with improved prognosis of BM. More importantly, patients carrying this mutation also harbored a better response to immunotherapy. CNV analysis indicated that deletion and deletion were respectively associated with poorer and better outcomes in patients with BM.

CONCLUSIONS

By integrating the somatic mutation data of patients with BM, this study identified molecular biomarkers related to outcomes and immunogenicity from three perspectives: mutational process signatures, molecular subtypes, and genomic variations. Our findings provide clues for prognosis evaluation in BM patients. They also establish a theoretical basis for predicting immunotherapy efficacy.