KRAS mutation as a predictor of insufficient trastuzumab efficacy and poor prognosis in HER2-positive advanced gastric cancer

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.

The genomic and immune landscapes of gastric cancer and their correlations with HER2 amplification and PD-L1 expression

BACKGROUND

Anti-PD1/PD-L1 antibody plus human epidermal growth factor receptor 2 (HER2) antibody and chemotherapy have become the new first-line therapy for HER2 overexpression-positive advanced gastric cancers (GC), suggesting that HER2 and PD-L1 play a vital role in guiding systemic treatment for patients with GC. This study aimed to depict the genomic and immune landscapes of Chinese patients with GC and investigate their correlations with HER2 amplification and PD-L1 expression.

PATIENTS AND METHODS

Next-generation targeted sequencing and PD-L1 immunohistochemistry were performed on tumor samples from 735 patients with pathologically diagnosed GC. The genomic and immune landscapes and their correlations with HER2 amplification and PD-L1 expression were analyzed.

RESULTS

The most commonly mutated genes in Chinese GC were TP53 (64%), CDH1 (20%), ARID1A (18%), HMCN1 (15%), KMT2D (11%), and PIK3CA (11%). Seventy-six (10%) patients were HER2 amplification, and 291 (40%) had positive PD-L1 expression. Classifying the total population based on HER2 amplification and PD-L1 expression level, 735 patients were divided into four subgroups: HER2+/PD-L1+ (4.5%), HER2+/PD-L1- (5.9%), HER2-/PD-L1+ (35.1%), and HER2-/PD-L1- (54.5%). The HER2+/PD-L1- and HER2+/PD-L1+ subgroups exhibited dramatically higher rate of TP53 mutations, CCNE1 and VEGF amplifications. The HER2+/PD-L1- subgroup also had a markedly higher rate of MYC amplification and KRAS mutations. The HER2-/PD-L1+ subgroup had significantly higher rate of PIK3CA mutations. HER2+/PD-L1- subgroup had the highest TMB level and HER2-/PD-L1+ subgroup had the highest proportion of patients with microsatellite instability-high than other subgroups. Furthermore, we observed that different HER2 amplification levels had distinct impacts on the correlations between PD-L1 expression and therapeutic genomic alterations, but no impact on the prognosis.

CONCLUSION

The combination of HER2 amplification and PD-L1 expression in Chinese patients with GC could stratify the total populations into several subgroups with distinctive genomic and immune landscapes, which should be considered when making personalized treatment decisions.

KRAS Mutations in Solid Tumors: Characteristics, Current Therapeutic Strategy, and Potential Treatment Exploration

Kristen rat sarcoma (KRAS) gene is one of the most common mutated oncogenes in solid tumors. Yet, KRAS inhibitors did not follow suit with the development of targeted therapy, for the structure of KRAS has been considered as being implausible to target for decades. Chemotherapy was the initial recommended therapy for KRAS-mutant cancer patients, which was then replaced by or combined with immunotherapy. KRAS G12C inhibitors became the most recent breakthrough in targeted therapy, with Sotorasib being approved by the Food and Drug Administration (FDA) based on its significant efficacy in multiple clinical studies. However, the subtypes of the KRAS mutations are complex, and the development of inhibitors targeting non-G12C subtypes is still at a relatively early stage. In addition, the monotherapy of KRAS inhibitors has accumulated possible resistance, acquiring the exploration of combination therapies or next-generation KRAS inhibitors. Thus, other non-target, conventional therapies have also been considered as being promising. Here in this review, we went through the characteristics of KRAS mutations in cancer patients, and the prognostic effect that it poses on different therapies and advanced therapeutic strategy, as well as cutting-edge research on the mechanisms of drug resistance, tumor development, and the immune microenvironment.

The AGAMENON-SEOM model for prediction of survival in patients with advanced HER2-positive oesophagogastric adenocarcinoma receiving first-line trastuzumab-based therapy

Background

Trastuzumab and chemotherapy is the standard first-line treatment in human epidermal growth factor receptor 2 (HER2)-positive advanced gastro-oesophageal cancer. The objective was to develop a predictive model for overall survival (OS) and progression-free survival (PFS) in patients treated with trastuzumab.

Methods

Patients with HER2-positive advanced gastro-oesophageal adenocarcinoma (AGA) from the Spanish Society of Medical Oncology (SEOM)-AGAMENON registry and treated first line with trastuzumab and chemotherapy between 2008 and 2021 were included. The model was externally validated in an independent series (The Christie NHS Foundation Trust, Manchester, UK).

Results

In all, 737 patients were recruited (AGAMENON-SEOM, n = 654; Manchester, n = 83). Median PFS and OS in the training cohort were 7.76 [95% confidence interval (CI), 7.13-8.25] and 14.0 months (95% CI, 13.0-14.9), respectively. Six covariates were significantly associated with OS: neutrophil-to-lymphocyte ratio, Eastern Cooperative Oncology Group performance status, Lauren subtype, HER2 expression, histological grade and tumour burden. The AGAMENON-HER2 model demonstrated adequate calibration and fair discriminatory ability with a c-index for corrected PFS/OS of 0.606 (95% CI, 0.578-0.636) and 0.623 (95% CI, 0.594-0.655), respectively. In the validation cohort, the model is well calibrated, with a c-index of 0.650 and 0.683 for PFS and OS, respectively.

Conclusion

The AGAMENON-HER2 prognostic tool stratifies HER2-positive AGA patients receiving trastuzumab and chemotherapy according to their estimated survival endpoints.

Fusobacterium Nucleatum-Induced Tumor Mutation Burden Predicts Poor Survival of Gastric Cancer Patients

Co-infection of Helicobacter pylori and Fusobacterium nucleatum is a microbial biomarker for poor prognosis of gastric cancer patients. Fusobacterium nucleatum is associated with microsatellite instability and the accumulation of mutations in colorectal cancer. Here, we investigated the mutation landscape of Fusobacterium nucleatum-positive resected gastric cancer tissues using Illumina TruSight Oncology 500 comprehensive panel. Sequencing data were processed to identify the small nucleotide variants, small insertions and deletions, and unstable microsatellite sites. The bioinformatic algorithm also calculated copy number gains of preselected genes and tumor mutation burden. The recurrent genetic aberrations were identified in this study cohort. For gene amplification events, ERBB2, cell cycle regulators, and specific FGF ligands and receptors were the most frequently amplified genes. Pathogenic activation mutations of ERBB2, ERBB3, and PIK3CA, as well as loss-of-function of TP53, were identified in multiple patients. Furthermore, Fusobacterium nucleatum infection is positively correlated with a higher tumor mutation burden. Survival analysis showed that the combination of Fusobacterium nucleatum infection and high tumor mutation burden formed an extremely effective biomarker to predict poor prognosis. Our results indicated that the ERBB2-PIK3-AKT-mTOR pathway is frequently activated in gastric cancer and that Fusobacterium nucleatum and high mutation burden are strong biomarkers of poor prognosis for gastric cancer patients.