Genomic signatures in young and old Chinese patients with bone and soft tissue tumors.

Abstract

e23516 Background: The tumor onset of bone and soft tissue at young or old age was associated with different clinical features. However, the genomic differences between young and old patients with bone and soft tissue tumors were not well elucidated. Therefore, a comprehensive molecular profile in young and old patients should be defined, which will enhance our understanding of the unique biology of bone and soft tissue tumors and help to improve the treatment options for this population. Methods: Tumor tissue samples from 103 young (age < = 50 years) and 81 old (age > 50 years) patients with bone and soft tissue tumors were enrolled, between 2019 to 2021. Targeted sequencing of 539 cancer-related genes was conducted to characterize the genomic landscape. Genomic alterations including single nucleotide variation (SNV), insertions/deletions, copy number variations (CNV) and gene fusions were assessed and germline alterations were excluded. Tumor mutation burden (TMB) was calculated by counting all nonsynonymous mutations per megabase of coding sequences. Results: The most common mutant genes in the younger and elderly groups were TP53 (20%), MUC16 (13%), KRT2 (8%) and TP53 (37%), MUC16 (19%), LRP1B (10%), FAT3 (7%), respectively. KRT2 mutations were significantly higher in the younger group (7.8% vs. 1.2%, p = 0.041), while TP53 mutations were more common in the elderly group (20.4% vs. 37%, p = 0.012). MUC4 and FADS6 mutations were only observed in the younger group (5.8% and 4.9%). Mutation of some genes were observed simultaneously in certain patients, for instance, TRIOBP/ KRT2, GATSL3 / KRT2, GATSL3 / SSUH2 in the younger group and P53 / LRP1B, MUC16 / PTEN, MUC16 / FAT2, MUC16 / LRP1B, APC / CARD11 in the elderly group. The most frequently affected pathways in the younger and elderly groups were TP53(23.3% vs 37%), RTK-RAS (16.5% vs. 29.6%), NOTCH (16.5% vs.16%), PIK3 (7.8% vs18.5%), Hippo (8.7% vs. 17.2%), respectively. The tumor mutation burden (TMB) was positively correlated with age (Pearson's r = 0.33, p < 0.001), and the old patients had higher TMB. Up to 97.8% (180/184) evaluated samples were microsatellite stable. Conclusions: These findings revealed different molecular characterization between young and old Chinese patients with bone and soft tissue tumors, which may further provide novel insights for the personalized treatment.