Genetic alterations in cell cycle regulation-associated genes may promote primary progression of gastrointestinal stromal tumors

Comprehensive Multiomics Analyses Establish the Optimal Prognostic Model for Resectable Gastric Cancer : Prognosis Prediction for Resectable GC

BACKGROUND

Prognostic models based on multiomics data may provide better predictive capability than those established at the single-omics level. Here we aimed to establish a prognostic model for resectable gastric cancer (GC) with multiomics information involving mutational, copy number, transcriptional, methylation, and clinicopathological alterations.

PATIENTS AND METHODS

The mutational, copy number, transcriptional, methylation data of 268, 265, 226, and 252 patients with stages I-III GC were downloaded from the TCGA database, respectively. Alterations from all omics were characterized, and prognostic models were established at the individual omics level and optimized at the multiomics level. All models were validated with a cohort of 99 patients with stages I-III GC.

RESULTS

TTN, TP53, and MUC16 were among the genes with the highest mutational frequency, while UBR5, ZFHX4, PREX2, and ARID1A exhibited the most prominent copy number variations (CNVs). Upregulated COL10A1, CST1, and HOXC10 and downregulated GAST represented the biggest transcriptional alterations. Aberrant methylation of some well-known genes was revealed, including CLDN18, NDRG4, and SDC2. Many alterations were found to predict the patient prognosis by univariate analysis, while four mutant genes, two CNVs, five transcriptionally altered genes, and seven aberrantly methylated genes were identified as independent risk factors in multivariate analysis. Prognostic models at the single-omics level were established with these alterations, and optimized combination of selected alterations with clinicopathological factors was used to establish a final multiomics model. All single-omics models and the final multiomics model were validated by an independent cohort. The optimal area under the curve (AUC) was 0.73, 0.71, 0.71, and 0.85 for mutational, CNV, transcriptional, and methylation models, respectively. The final multiomics model significantly increased the AUC to 0.92 (P < 0.05).

CONCLUSIONS

Multiomics model exhibited significantly better capability in predicting the prognosis of resectable GC than single-omics models.

Novel Genomic Risk Stratification Model for Primary Gastrointestinal Stromal Tumors (GIST) in the Adjuvant Therapy Era

PURPOSE

Traditional risk stratification schemes in gastrointestinal stromal tumors (GIST) were defined in the pre-imatinib era and rely solely on clinicopathologic metrics. We hypothesize that genomic-based risk stratification is prognostically relevant in the current era of tyrosine kinase inhibitor (TKI) therapeutics.

EXPERIMENTAL DESIGN

Comprehensive mutational and copy-number profiling using MSK-IMPACT was performed. We integrated clinicopathologic and genomic parameters and utilized an elastic-net penalized Cox proportional hazards machine learning model for outcome risk stratification.

RESULTS

A 3-tier genomic risk stratification model for recurrence-free survival (RFS) in 152 primary localized gastric and 80 small bowel GISTs was proposed. Gastric GISTs were classified as high risk if chr1p deletion or SDHB loss was present, and intermediate risk if chr14q deletion was present or KIT exon 11 mutation was absent. Small bowel GISTs were classified as high risk if MAX/MGA/MYC, CDKN2A, or RB1 alterations were present, and intermediate risk if chr1p deletion or chr5q amplification was present. Compared with conventional risk stratification, genomic risk stratification both upgrades and downgrades, suggesting that conventional risk stratification may underestimate or overtreat some high-risk and low-risk patients, respectively. Longitudinal sequencing detected most KIT-independent genomic alterations at baseline. Subanalysis in 26 SDH-deficient GISTs revealed that presence of TP53 mutations or chr1q amplifications portends worse RFS and disease-free survival.

CONCLUSIONS

We developed a novel, next-generation genomic risk stratification model for primary gastric and small bowel GISTs, complementing traditional clinicopathologic models. Future independent validation of our model in external cohorts is essential.

Characterization of Aberrations in DNA Damage Repair Pathways in Gastrointestinal Stromal Tumors: The Clinicopathologic Relevance of γH2AX and 53BP1 in Correlation with Heterozygous Deletions of CHEK2, BRCA2, and RB1

Genetic aberrations involving DNA damage repair (DDR) remain underexplored in gastrointestinal stromal tumors (GISTs). We characterized DDR abnormalities using targeted next-generation sequencing and multiplex ligation-dependent probe amplification, and performed immunofluorescence (IF) and immunohistochemistry (IHC) analyses of γH2AX and 53BP1. Consistent with IF-validated nuclear co-localization, γH2AX and 53BP1 showed robust correlations in expression levels, as did both biomarkers between IF and IHC. Without recurrent pathogenic single-nucleotide variants, heterozygous deletions (HetDels) frequently targeted DNA damage-sensing genes, with CHEK2-HetDel being the most prevalent. Despite their chromosomal proximity, BRCA2 and RB1 were occasionally hit by HetDels and were seldom co-deleted. HetDels of CHEK2 and BRCA2 showed a preference for older age groups, while RB1-HetDel predominated in the non-gastric, high-risk, and 53BP1-overexpressing GISTs. Higher risk levels were consistently related to γ-H2AX or 53BP1 overexpression (all p < 0.01) in two validation cohorts, while only 53BP1 overexpression was associated with the deletion of KIT exon 11 (KITex11-del) among genotyped GISTs. Low expressers of dual biomarkers were shown by univariate analysis to have longer disease-free survival (p = 0.031). However, higher risk levels, epithelioid histology, and KITex11-del retained prognostic independence. Conclusively, IHC is a useful surrogate of laborious IF in the combined assessment of 53BP1 and γ-H2AX to identify potential DDR-defective GISTs, which were frequently aberrated by HetDels and a harbinger of progression.

Genomic Mutation Profile of Primary Gastrointestinal Diffuse Large B-Cell Lymphoma

Primary gastrointestinal diffuse large B-cell lymphoma (GI-DLBCL) is the most common gastrointestinal lymphoma, but its genetic features are poorly understood. We performed whole-exome sequencing of 25 primary tumor samples from patients with GI-DLBCL and 23 matched normal tissue samples. Oncogenic mutations were screened, and the correlations between genetic mutations and clinicopathological characteristics were analyzed. Twenty-five patients with GI-DLBCL were enrolled in the genetic mutation analysis with a median of 184 (range 79–382) protein-altering variants per patient. We identified recurrent oncogenic mutations in GI-DLBCL, including those in TP53, MUC16, B2M, CCND3, HIST1H1C, NEB, and ID3. Compared with nodal DLBCL, GI-DLBCL exhibited an increased mutation frequency of TP53 and reduced mutation frequencies of PIM1, CREBBP, BCL2, KMT2D, and EZH2. Moreover, GI-DLBCL exhibited fewer MYD88 and CD79B mutations than DLBCL in the testis and central nervous system. GI-DLBCLs with HLA-B, MEF2A, RHOA, and NAV3 mutations exhibited a tendency toward a high proliferation index. MUC16 and ETV6 mutations often occurred in tumors with early clinical staging. Our data provide a comprehensive understanding of the landscape of mutations in a small subset of GI-DLBCLs. The genetic mutation profiles of GI-DLBCL differ from those of nodal DLBCL and DLBCL in immune-privileged sites. The different mutated genes are related to the NF-κB and JAK-STAT pathways, and the different pathogenetic mechanisms leading to the development of DLBCL may be influenced by the tissue microenvironment. Differences in genetic alterations might influence the clinicopathological characteristics of GI-DLBCL.