Tumor mutation burden as a biomarker in resected gastric cancer via its association with immune infiltration and hypoxia

Immune landscape and heterogeneity of cervical squamous cell carcinoma and adenocarcinoma

Despite the differences in disease outcomes and pathological features between cervical squamous cell carcinoma (CSCC) and adenocarcinoma (ADC), the molecular characteristics in immune heterogeneity of the tumor microenvironment remain unclear. Here, we explored the immune landscape and heterogeneity between CSCC and ADC. Gene expression and clinical characteristics of cervical carcinoma from The Cancer Genome Atlas (TCGA) were downloaded. Differentially expressed genes (DEGs), immune cell infiltration, and pathway enrichment analyses were used to explore the immune landscape and heterogeneity between CSCC and ADC. Furthermore, distinct immune signatures between CSCC and ADC were validated based on clinical samples. In total, 4,132 upregulated DEGs and 2,307 down-regulated DEGs were identified between CSCC and ADC, with enrichments in immune related-pathways in CSCC. In addition, 54 hub DEGs correlated with patients' prognosis and immunocytes infiltration were identified. The CSCC patients had a higher ImmuneScore and more abundant immunocytes infiltration compared to ADC patients, as validated by immunohistochemistry (IHC) and multicolor immunofluorescence (mIF) analyses of collected samples. Furthermore, CSCC displayed higher inhibitory immune checkpoints expression, tumor mutation burden (TMB), and microsatellite instability (MSI) compared to ADC, which indicated CSCC patients were more likely to benefit from immunotherapy. In summary, our results revealed the huge immune heterogeneity between CSCC and ADC, and provided guidance for immunotherapy selection for different pathological types of cervical cancer.

An oncogene regulating chromatin favors response to immunotherapy: Oncogene CHAF1A and immunotherapy outcomes

Many biological processes related to cell function and fate begin with chromatin alterations, and many factors associated with the efficacy of immune checkpoint inhibitors (ICIs) are actually downstream events of chromatin alterations, such as genome changes, neoantigen production, and immune checkpoint expression. However, the influence of genes as chromatin regulators on the efficacy of ICIs remains elusive, especially in gastric cancer (GC). In this study, thirty out of 1593 genes regulating chromatin associated with a favorable prognosis were selected for GC. CHAF1A, a well-defined oncogene, was identified as the highest linkage hub gene. High CHAF1A expression were associated with microsatellite instability (MSI), high tumor mutation burden (TMB), high tumor neoantigen burden (TNB), high expressions of PD-L1 and immune effector genes, and live infiltration of immune cells. High CHAF1A expression indicated a favorable response and prognosis in immunotherapy of several cohorts, which was independent of MSI, TMB, TNB, PD-L1 expression, immune phenotype and transcriptome scoring, and improved patient selection based on these classic biomarkers. In vivo, CHAF1A knockdown alone inhibited tumor growth but it impaired the effect of an anti-PD-1 antibody by increasing the relative tumor proliferation rate and decreasing the survival benefit, potentially through the activation of TGF-β signaling. In conclusion, CHAF1A may be a novel biomarker for improving patient selection in immunotherapy.

Expression and prognostic value of APOBEC2 in gastric adenocarcinoma and its association with tumor-infiltrating immune cells

BACKGROUND

Apolipoprotein B mRNA editing enzyme catalytic polypeptide-like 2 (APOBEC2) is associated with nucleotide alterations in the transcripts of tumor-related genes which are contributed to carcinogenesis. Expression and prognosis value of APOBEC2 in stomach adenocarcinoma (STAD) remains unclear.

METHODS

The APOBEC2 gene alteration frequency of STAD and APOBEC2 gene expression in STAD and normal tissues were investigated in cBioportal and GEPIA, respectively. We detected expression of APOBEC2, infiltration of CD66b+ tumor-associated neutrophils and CD163+ tumor-associated macrophages in tissue microarrays by immunohistochemistry. APOBEC2 gene expression was explored by western blot and qRT-PCR. Relationships between APOBEC2 and CD66b, CD163, and other clinicopathological characteristics were investigated. Associations among APOBEC2 expression status and patient survival outcome were further analyzed.

RESULTS

APOBEC2 gene alteration frequency was 5%, and APOBEC2 gene was downexpressed in STAD compared to normal tissues (P < 0.05). APOBEC2 expression status were associated with the infiltration of CD66b+ TANs, differentiation grade, TNM stage, histological type and gender (all P < 0.05) in STAD. Little or no APOBEC2 expression was detected in STAD and adjacent normal tissues by western blot. We failed to show that APOBEC2 was an independent risk factor for OS (Hazard Ratio 0.816, 95%CI 0.574-1.161, P = 0.259) or DFS (Hazard Ratio 0.821, 95%CI 0.578-1.166, P = 0.270) in STAD by multivariate Cox regression analysis, but APOBEC2 negative subgroup has a worse OS and DFS among patients with adjuvant chemotherapy.

CONCLUSIONS

APOBEC2 correlates with CD66b, differentiation grade, TNM stages, histological classification, and gender in STAD. APOBEC2 is not an independent prognostic factor for STAD, our results suggest that patients with positive APOBEC2 can benefit from postoperative chemotherapy, and combination of APOBEC2 and CD66b is helpful to further stratify patients into different groups with distinct prognoses.

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.

Association of genes in hereditary metabolic diseases with diagnosis, prognosis, and treatment outcomes in gastric cancer

Background

Aberrant metabolism is a major hallmark of cancers and hereditary diseases. Genes associated with inborn metabolic errors may also play roles in cancer development. This study evaluated the overall impact of these genes on gastric cancer (GC).

Methods

In total, 162 genes involved in 203 hereditary metabolic diseases were identified in the Human Phenotype Ontology database. Clinical and multi-omic data were acquired from the GC cohort of the Affiliated Hospital of Jiangsu University and other published cohorts. A 4-gene and 32-gene signature was established for diagnosis and prognosis or therapeutic prediction, respectively, and corresponding abnormal metabolism scores (AMscores) were calculated.

Results

The diagnostic AMscore showed high sensitivity (0.88-1.00) and specificity (0.89-1.00) to distinguish between GC and paired normal tissues, with area under the receiver operating characteristic curve (AUC) ranging from 0.911 to 1.000 in four GC cohorts. The prognostic or predictive AMscore was an independent predictor of overall survival (OS) in five GC cohorts and a predictor of the OS and disease-free survival benefit of postoperative chemotherapy or chemoradiotherapy in one GC cohort with such data. The AMscore adversely impacts immune biomarkers, including tumor mutation burden, tumor neoantigen burden, microsatellite instability, programmed death-ligand 1 protein expression, tumor microenvironment score, T cell receptor clonality, and immune cell infiltration detected by multiplex immunofluorescence staining. The AUC of the AMscore for predicting immunotherapy response ranging from 0.780 to 0.964 in four cohorts involving GC, urothelial cancer, melanoma, and lung cancer. The objective response rates in the low and high AMscore subgroups were 78.6% and 3.2%, 40.4% and 7%, 52.6% and 0%, and 72.7% and 0%, respectively (all p<0.001). In cohorts with survival data, a high AMscore was hazardous for OS or progression-free survival, with hazard ratios ranged from 5.79 to 108.59 (all p<0.001). Importantly, the AMscore significantly improved the prediction of current immune biomarkers for both response and survival, thus redefining the advantaged and disadvantaged immunotherapy populations.

Conclusions

Signatures based on genes associated with hereditary metabolic diseases and their corresponding scores could be used to guide the diagnosis and treatment of GC. Therefore, further validation is required.

The predictive value of tumor mutation burden on survival of gastric cancer patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis

BACKGROUND

Tumor mutation burden (TMB) is a complement to traditional biomarkers related to the efficacy of immune checkpoint inhibitors (ICIs). The relationship between TMB and the efficacy of ICIs in gastric cancer was controversial. The systematic review and meta-analysis were conducted to investigate the predictive value of TMB on survival of gastric cancer patients treated with ICIs.

METHODS

We searched the databases PubMed, Embase, and Web of Science for articles, then screened eligible articles according to inclusion criteria. The effective data were extracted to calculate the pooled effects of hazard ratio (HR) for overall survival (OS) and progression-free survival (PFS), then perform publication bias, sensitivity analysis, and subgroup analysis by STATA 16.0.

RESULTS

The high TMB patients showed significantly longer survival than the low TMB patients (OS: HR 0.65,95% CI 0.55, 0.77, p < 0.001; PFS: HR 0.51, 95% CI 0.33, 0.77, p = 0.001). In the Asian subgroup, patients with high TMB exhibited better prognosis compared to low TMB (OS: HR 0.56, 95% CI 0.43, 0.72, p < 0.001; PFS: HR 0.45, 95% CI 0.28, 0.72, p = 0.001). In the non-Asian subgroup, the survival benefit was observed to be skewed toward patients with high TMB, but it was not statistically significant (OS:HR 0.61, 95% CI 0.32, 1.16, p = 0.133; PFS:HR 0.68, 95% CI 0.31, 1.48, p = 0.322).

CONCLUSIONS

This meta-analysis demonstrated that gastric cancer patients with high TMB showed significant benefits from ICIs compared to those with low TMB patients, particularly in Asian populations.

Genomic and transcriptomic profiling indicates the prognosis significance of mutational signature for TMB-high subtype in Chinese patients with gastric cancer

INTRODUCTION

Gastric cancer (GC)is the third leading cause of cancer-related deaths in China and immunotherapy emerging as a revolutionary treatment for GC recently. Tumor mutational burden (TMB) is a predictive biomarker of immunotherapy in multiple cancers. However, the prognostic significance and subtype of TMB in GC is not fully understood.

OBJECTIVES

This study aims to evaluate the prognostic value of TMB in Chinese GC and further classify TMB-high GC (GCTMB-H) patients combing with mutational signatures.

METHODS

Genomic profiling of 435 cancer-gene panel was performed using 206 GC samples from Chinese people. Actionable genetic alterations were compared across all the samples to generate actionable subtyping. The prognostic value of TMB in Chinese GC was evaluated. Mutational signatures were analyzed on TMB-H subtype to stratify the prognosis of TMB. Transcriptomic analysis was applied to compare the distributed immunocytes among different subtypes.

RESULTS

88.3% (182/206) of GC samples had at least one mutation, while 45.1% (93/206) had at least one somatic copy number alteration (SCNA). 29.6% (61/206) of GC samples were TMB-H, including 13 MSI-H and 48 MSS tumors. According to distinct genetic alteration profiles of 69 actionable genes, we classified GC samples into eight molecular subtypes, including TMB-H, ERBB2 amplified, ATM mutated, BRCA2 mutated, CDKN2A/B deleted, PI3KCA mutated, KRAS mutated, and less-mutated subtype. TMB-H subtype presented a remarkable immune-activated phenotype as determined by transcriptomic analysis that was further validated in the TCGA GC cohort. GCTMB-H patients exhibited significantly better survival (P = 0.047). But Signature 1-high GCTMB-H patients had relatively worse prognosis (P = 0.0209, HR = 2.571) than Signature 1-low GCTMB-H patients from Chinese GC cohort, also validated in TCGA GC cohort, presenting highly activated carbohydrate, fatty acid or lipid metabolism.

CONCLUSION

The Signature 1-high GCTMB-H could be a marker of poor prognosis and is associated with metabolism disorder.

Prognostic value of tumor mutation burden in patients with advanced gastric cancer receiving first-line chemotherapy

Background

Tumor mutation burden (TMB) is a promising biomarker positively associated with the benefit of immunotherapy and that might predict the outcome of chemotherapy. We described the prognostic value of TMB in advanced gastric cancer and explored the underlying mechanism.

Methods

We enrolled 155 TMB-evaluated advanced gastric cancer patients and analyzed the relationship between clinicopathological characteristics and both overall survival (OS) and progression-free survival (PFS) among 40 patients treated with first-line chemotherapy. We further verified the distribution of TMB and analyzed the potential mechanism underlying the prognosis based on The Cancer Genome Atlas (TCGA) database.

Results

Among the 155 patients, 29 (18.7%) were TMB-high (TMB ≥ 10), roughly the same as the proportion in the TCGA data. Of the 40 patients receiving first-line chemotherapy, the median OS (7.9 vs. 12.1 months; HR 3.18; p = 0.0056) and PFS (4.4 vs. 6.2 months; HR 2.94; p = 0.0099) of the tissue-tested TMB (tTMB)-high patients were inferior to those of the tTMB-low patients. Similarly, unfavorable median OS (9.9 vs. 12.1 months; HR 2.11; p = 0.028) and PFS (5.3 vs. 6.5 months; HR 2.49; p = 0.0054) were shown in the blood-tested TMB (bTMB)-high than in the bTMB-low patients. The Cox analysis demonstrated that both tTMB-high and bTMB-high were significant independent predictors of dreadful OS and PFS. The differentially expressed genes (DEGs) according to TMB status were most significantly enriched in the downregulated metabolic pathway among the TMB-high patients.

Conclusions

TMB-high advanced gastric cancer patients accounted for around one-sixth and had a poorer prognosis than TMB-low patients when treated with first-line chemotherapy. The potential mechanism might be the downregulated metabolic activity in TMB-high patients.

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.

Recent progress and current challenges of immunotherapy in advanced/metastatic esophagogastric adenocarcinoma

The new era of immunotherapy is successfully implemented in the treatment of metastatic/locally advanced esophagogastric adenocarcinoma (EGAC), as it has been investigated in combinations with/without chemotherapy in human epidermal growth factor receptor 2 (Her2)-positive and Her2-negative tumors. Recent approvals of immune checkpoint inhibitors (ICI) enrich the therapeutic landscape in nearly every therapeutic line. Based on CHECKMATE-649, the combination of nivolumab and chemotherapy in first-line therapy of programmed cell death protein 1 (PD-L1)-positive patients with advanced gastroesophageal junction cancer (GEJC), esophageal cancer (EC), and gastric cancer (GC) was approved in Europe for PD-L1 combined positivity score (CPS) ≥ 5 patients and independently from PD-L1 score in the USA and Asia. Based on KEYNOTE-590, patients with advanced GEJC and EC qualify for the combination of pembrolizumab plus chemotherapy in Europe (CPS ≥ 10) and the USA. For Her2-positive patients, trastuzumab with first-line chemotherapy plus pembrolizumab has beneficial response rates and resulted in approval in the USA (KEYNOTE-811). In third-line therapy, superior overall survival (OS) was achieved by the administration of nivolumab (approval in Japan, ATTRACTION-02), and pembrolizumab shows a positive effect on the duration of response (KEYNOTE-059). Questions of resistance to immunotherapy or the role of gender in response to ICI need to be clarified. This review provides an overview of the current approvals of ICI in advanced EGAC and reflects results of relevant phase II/III trials with focus on possible biomarkers, including PD-L1 CPS and microsatellite-instability (MSI) status.

Significance of a Tumor Mutation Burden Gene Signature with Prognosis and Immune Feature of Gastric Cancer Patients

Gastric cancer (GC) is a common digestive tumor which ranks the fourth most common malignancy worldwide. Immunotherapy is a promising treatment for GC, especially for advanced gastric cancer (AGC). However, in clinical practice, not all patients are sensitive to immunotherapy. Recent studies showed that tumor mutation burden (TMB) is closely correlated with the response of immunotherapy. The current study identified a TMB-related genes' signature to predict the prognosis and immune feature of GC patients. Firstly, we acquired the TMB data and expression data from The Cancer Genome Atlas (TCGA) and the National Center for Biotechnology Information (NCBI) GEO databases. Then, we extracted TMB-related genes from the expression data of TCGA and two GEO cohorts. By using univariate Cox analysis, we identified that the 429 genes were correlated to GC patients' overall survival. Subsequently, an immune prognostic signature was constructed by using the least absolute shrinkage and selection operator analysis (LASSO) and multivariate Cox regression analysis. The signature could be utilized to predict the prognosis of GC patients. In addition, the signature showed a closed correlation with immune feature of GC patients. In conclusion, our risk signature could offer hints for the prognosis of GC patients and might provide insights to formulate new immunotherapy strategies for GC patients.

Focal Adhesion-Related Signatures Predict the Treatment Efficacy of Chemotherapy and Prognosis in Patients with Gastric Cancer

Background

The current tumor-node-metastasis (TNM) staging system is insufficient for predicting the efficacy of chemotherapy in patients with gastric cancer (GC). This study aimed to analyze the association between the focal adhesion pathway and therapeutic efficacy of chemotherapy in patients with GC.

Methods

RNA sequencing was performed on 33 clinical samples from patients who responded or did not respond to treatment prior to neoadjuvant chemotherapy. The validation sets containing 696 GC patients with RNA data from three cohorts (PKUCH, TCGA, and GSE14210) were analyzed. A series of machine learning and bioinformatics approaches was combined to build a focal adhesion-related signature model to predict the treatment efficacy and prognosis of patients with GC.

Results

Among the various signaling pathways associated with cancer, focal adhesion was identified as a risk factor related to the treatment efficacy of chemotherapy and prognosis in patients with GC. The focal adhesion-related gene model (FAscore) discriminated patients with a high FAscore who are insensitive to neoadjuvant chemotherapy in our training cohort, and the predicted value was further verified in the GSE14210 cohort. Survival analysis also demonstrated that patients with high FAscores had a relatively shorter survival compared to those with low FAscores. In addition, we found that the levels of tumor mutation burden (TMB) and microsatellite instability (MSI) increased with an increase in FAscore, and the tumor microenvironment (TME) also shifted to a pro-tumor immune microenvironment.

Conclusion

The FAscore model can be used to predict the treatment efficacy of chemotherapy and select appropriate treatment strategies for patients with GC.

A Genomic Signature Reflecting Fibroblast Infiltration Into Gastric Cancer Is Associated With Prognosis and Treatment Outcomes of Immune Checkpoint Inhibitors

Background: The immunotherapy efficacy in gastric cancer (GC) is limited. Cancer-associated fibroblasts (CAFs) induce primary resistance to immunotherapy. However, CAF infiltration in tumors is difficult to evaluate due to the lack of validated and standardized quantified methods. This study aimed to investigate the impact of infiltrating CAFs alternatively using fibroblast-associated mutation scoring (FAMscore). Methods: In a GC cohort from Affiliated Hospital of Jiangsu University (AHJU), whole exon sequencing of genomic mutations, whole transcriptome sequencing of mRNA expression profiles, and immunofluorescence staining of tumor-infiltrating immune cells were performed. GC data from The Cancer Genome Atlas were used to identify genetic mutations which were associated with overall survival (OS) and impacted infiltrating CAF abundance determined by transcriptome-based estimation. FAMscore was then constructed through a least absolute shrinkage and selection operator Cox regression model and further validated in AHJU. The predictive role of FAMscore for immunotherapy outcomes was tested in 1 GC, one melanoma, and two non-small-cell lung cancer (NSCLC-1 and -2) cohorts wherein participants were treated by immune checkpoint inhibitors. Results: FAMscore was calculated based on a mutation signature consisting of 16 genes. In both TCGA and AHJU, a high FAMscore was an independent predictor for poor OS of GC patients. FAMscore was associated with immune-associated genome biomarkers, immune cell infiltration, and signaling pathways of abnormal immunity. Importantly, patients with high FAMscore presented inferiority in the objective response rate of immunotherapy compared to those with low FAMscore, with 14.6% vs. 66.7% (p<0.001) in GC, 19.6% vs. 68.2% (p<0.001) in NSCLC-1, 23.1% vs 75% (p = 0.007) in NSCLC-2, and 40.9% vs 75% (p = 0.037) in melanoma. For available survival data, a high FAMscore was also an independent predictor of poor progression-free survival in NSCLC-1 (HR = 2.55, 95% CI: 1.16-5.62, p = 0.02) and NSCLC-2 (HR = 5.0, 95% CI: 1.13-22.19, p = 0.034) and poor OS in melanoma (HR = 3.48, 95% CI: 1.27-9.55, p = 0.015). Conclusions: Alternative evaluation of CAF infiltration in GC by determining the FAMscore could independently predict prognosis and immunotherapy outcomes. The FAMscore may be used to optimize patient selection for immunotherapy.

Associations of HER2 Mutation With Immune-Related Features and Immunotherapy Outcomes in Solid Tumors

Background

HER2 is one of the most extensively studied oncogenes in solid tumors. However, the association between tumor microenvironment (TME) and HER2 mutation remains elusive, and there are no specific therapies for HER2-mutated tumors. Immune checkpoint inhibitors (ICIs) have been approved for some tumor subgroups that lack targeted therapies, while their effects are still unclear in HER2-mutated tumors. We examined whether HER2 mutation impacts treatment outcomes of ICIs in solid tumors via its association with anticancer immunity.

Methods

Multi-omics data of solid tumors from The Cancer Genome Atlas (TCGA), the Asian Cancer Research Group and the Affiliated Hospital of Jiangsu University were used to analyze the association between HER2 mutations and tumor features. Data of patients with multiple microsatellite-stable solid tumors, who were treated by ICIs including antibodies against programmed cell death-1 (PD-1), programmed cell death ligand-1 (PD-L1), or cytotoxic T lymphocyte-associated protein 4 (CTLA-4) in eight studies, were collected to investigate the effects of HER2 mutations on immunotherapy outcomes.

Results

The mutation rate of HER2 varied in solid tumors of TCGA, with an overall incidence of 3.13%, ranged from 0.39% to 12.2%. Concurrent HER2 mutations and amplifications were rare (0.26%). HER2 mutation was not associated with HER2 protein expression but was positively associated with microsatellite instability, tumor mutation and neoantigen burdens, infiltrating antitumor immune cells, and signal activities of antitumor immunity. Of 321 ICI-treated patients, 18 carried HER2 mutations (5.6%) and showed improved objective response rates compared with those with HER2 wild-type (44.4% vs. 25.7%, p=0.081), especially in the anti-PD-1/anti-PD-L1 subgroup (62.5% vs. 28.4%, p=0.04). Heterogeneity was observed among tumor types. Patients with HER2 mutations also had superior overall survival than those with HER2 wild-type (HR=0.47, 95%CI: 0.23-0.97, p=0.04), especially in the presence of co-mutations in ABCA1 (HR = 0.23, 95% CI: 0.07-0.73, p=0.013), CELSR1 (HR = 0.24, 95% CI: 0.08-0.77, p=0.016), LRP2 (HR = 0.24, 95% CI: 0.07-0.74, p=0.014), or PKHD1L1 (HR = 0.2, 95% CI: 0.05-0.8, p=0.023).

Conclusions

HER2 mutations may improve the TME to favor immunotherapy. A prospective basket trial is needed to further investigate the impacts of HER2 mutations on immunotherapy outcomes in solid tumors.

Glutamine Metabolism Scoring Predicts Prognosis and Therapeutic Resistance in Hepatocellular Carcinoma

Glutamine metabolism (GM) plays a critical role in hepatocellular carcinoma (HCC); however, a comprehensive methodology to quantify GM activity is still lacking. We developed a transcriptome-based GMScore to evaluate GM activity and investigated the association of GMScore with prognosis and therapeutic resistance. Two independent HCC cohorts with transcriptome data were selected from The Cancer Genome Atlas (TCGA, n = 365) and the International Cancer Genome Consortium (ICGC, n = 231). The expression of 41 GM-associated genes were used to construct and validate GMScore. Several genomic or transcriptomic biomarkers were also estimated. Tumor response to immune checkpoint inhibitors (ICIs) was predicted using the tumor immune dysfunction and exclusion algorithm. GMScore was closely correlated with patient characteristics, including stage, histology grade, alpha-fetoprotein level, and vascular invasion. High GMScore was an independent risk factor for overall survival (OS) in both cohorts (HR = 4.2 and 3.91, both p < 0.001), superior to clinical indices and other biomarkers. High GMScore presented transcriptome features to indicate cell growth advantages and genetic stability, which was associated with poor OS of patients who received transcatheter arterial chemoembolization (TACE). High GMScore was also related to high expression of immune checkpoint genes, increased infiltration of regulatory T cells, and decreased infiltration of M1 macrophages. More importantly, high GMScore indicated poor predicted responses to ICIs, which could be verified in an ICI-treated melanoma cohort. In conclusion, GMScore is a strong prognostic index that may be integrated into existing clinical algorithms. A high GMScore may indicate resistance to TACE and ICIs based on its transcriptome and immune features. Validations using other HCC cohorts, especially ICI-treated HCC cohorts, are necessary.

Prediction of Two Molecular Subtypes of Gastric Cancer Based on Immune Signature

Gastric cancer is the fifth most common type of human cancer and the third leading cause of cancer-related death. The purpose of this study is to investigate the immune infiltration signatures of gastric cancer and their relation to prognosis. We identified two distinct subtypes of gastric cancer (C1/C2) characterized by different immune infiltration signatures. C1 is featured by immune resting, epithelial–mesenchymal transition, and angiogenesis pathways, while C2 is featured by enrichment of the MYC target, oxidative phosphorylation, and E2F target pathways. The C2 subtype has a better prognosis than the C1 subtype (HR = 0.61, 95% CI: 0.44–0.85; log-rank test, p = 0.0029). The association of C1/C2 with prognosis remained statistically significant (HR = 0.62, 95% CI: 0.44–0.87; p = 0.006) after controlling for age, gender, and stage. The prognosis prediction of C1/C2 was verified in four independent cohorts (including an internal cohort). In summary, our study is helpful for better understanding of the association between immune infiltration and the prognosis of gastric cancer.

Derivation of a Novel CIHI in Patients with Lung Adenocarcinoma for Estimating Tumor Microenvironment and Clinical Prognosis

An interaction between hypoxia and immunity has been confirmed in tumor tissue. However, there is no combined biomarker for diagnosis on this basis. Therefore, we developed a scoring formula based on markers of hypoxia and immunity. Firstly, the hypoxia-immune formula of lung adenocarcinoma (LUAD) was derived using LASSO-Cox regression in three cohorts from public database, and the corresponding score was calculated for each patient. The formula is as follows: combined hypoxia and immune index (CIHI) = LDHA expression × 0.2252 + GAPDH expression × 0.0727 + ANGPTL4 expression × 0.0724 + VEGFC expression × 0.1911 + DKK1 expression × 0.1355 + ADM expression × 0.0588 + BTK expression × −0.1659. Meanwhile, patients were divided into groups according to high and low CIHI, and expression profiles of hypoxia markers and immune markers were analyzed in different groups. CIHI was used to confirm that patients with high CIHI represented a state of hypoxia^high-immunity^low, which had worse overall survival. We also discussed the evaluation value in the immune microenvironment and clinical application of CIHI. In conclusion, this study developed and validated a hypoxia-immune formula that can guide hypoxia modifier treatment and immunotherapy in LUAD.

Genomic alterations in biliary tract cancer predict prognosis and immunotherapy outcomes

BACKGROUND

Recently, immunotherapy with immune checkpoint inhibitors (ICIs) has shown promising efficacy in biliary tract cancer (BTC), which includes gallbladder cancer (GBC) and cholangiocarcinoma (CHOL). Understanding the association between immunotherapy outcomes and the genomic profile of advanced BTC may further improve the clinical benefits from immunotherapy.

METHODS

Genomic tumor DNA was isolated from 98 Chinese patients with advanced BTC and used for targeted next-generation sequencing of 416 cancer-related genes to identify the genomic alterations common to advanced BTC. Thirty-four patients had received ICI camrelizumab plus gemcitabine and oxaliplatin (from the NCT03486678 trial) as a first-line treatment. Tumor-infiltrating immune cells were evaluated using immunofluorescence staining.

RESULTS

KRAS and TP53 mutations were much more frequent in the advanced-stage BTC cohort than in other cohorts with mostly early stage disease. Specifically, KRAS-TP53 co-mutations were favored in advanced CHOL, with a favorable response to immunotherapy, while single KRAS mutations predicted poor prognosis and immunotherapy outcomes for CHOL. Compared with GBC, CHOL had more mutations in genes involved in KRAS signaling; a high mutation load in these genes correlated with poor immunotherapy outcomes and may subsequently cause inferior immunotherapy outcomes for CHOL relative to GBC. Furthermore, a genomic signature including 11 genes was developed; their mutated subtype was associated with poor prognosis and immunotherapy outcomes in both CHOL and GBC. Transcriptome analyses suggested immune dysfunction in the signature mutated subtype, which was validated by tumor microenvironment (TME) evaluation based on detection of immune cell infiltration. Importantly, the signature wild-type subtype with favorable TME may be an advantageous population of immunotherapy.

CONCLUSIONS

Genomic alterations in advanced BTC were associated with specific prognosis and immunotherapy outcomes. Combining genomic classification with TME evaluation further improved the stratification of immunotherapy outcomes.

Identification of a Gene Prognostic Model of Gastric Cancer Based on Analysis of Tumor Mutation Burden

Introduction: Gastric cancer is one of the most common cancers. Although some progress has been made in the treatment of gastric cancer with the improvement of surgical methods and the application of immunotherapy, the prognosis of gastric cancer patients is still unsatisfactory. In recent years, there has been increasing evidence that tumor mutational load (TMB) is strongly associated with survival outcomes and response to immunotherapy. Given the variable response of patients to immunotherapy, it is important to investigate clinical significance of TMB and explore appropriate biomarkers of prognosis in patients with gastric cancer (GC).

Material and Methods: All data of patients with gastric cancer were obtained from the database of The Cancer Genome Atlas (TCGA). Samples were divided into two groups based on median TMB. Differently expressed genes (DEGs) between the high- and low-TMB groups were identified and further analyzed. We identified TMB-related genes using Lasso, univariate and multivariate Cox regression analysis and validated the survival result of 11 hub genes using Kaplan-Meier Plotter. In addition, “CIBERSORT” package was utilized to estimate the immune infiltration.

Results: Single nucleotide polymorphism (SNP), C > T transition were the most common variant type and single nucleotide variant (SNV), respectively. Patients in the high-TMB group had better survival outcomes than those in the low-TMB group. Besides, eleven TMB-related DEGs were utilized to construct a prognostic model that could be an independent risk factor to predict the prognosis of patients with GC. What’s more, the infiltration levels of CD4⁺ memory-activated T cells, M0 and M1 macrophages were significantly increased in the high-TMB group compared with the low-TMB group.

Conclusions: Herein, we found that patients with high TMB had better survival outcomes in GC. In addition, higher TMB might promote immune infiltration, which could provide new ideas for immunotherapy.

Applying immune-related lncRNA pairs to construct a prognostic signature and predict the immune landscape of stomach adenocarcinoma

Background: Long noncoding RNAs (lncRNAs) are associated with the survival of cancer patients. We constructed an immune-related lncRNA (irlncRNA) pair signature for stomach adenocarcinoma (STAD).Research design and methods: irlncRNAs were identified via coexpression analysis with immune-related genes. Differentially expressed irlncRNAs (DEirlncRNAs) were paired. Least absolute shrinkage and selection operator (LASSO) and multivariate Cox proportional hazards regression methods were used to construct the signature. We calculated the area under the receiver operating characteristic (ROC) curve and determined the best cutoff value according to the Akaike information criterion (AIC). Patients were divided into high - and low-risk groups, and differences in immune cell infiltration, tumor mutation burden (TMB) and drug treatment effects between the groups were explored according to the risk score.Results: An 8-irlncRNA-pair signature was constructed and proven to be a strong prognosis predictor in STAD patients through external verification. Moreover, the risk score was identified as an independent prognostic factor. There were significant differences in immune cell infiltration and the response to several drug treatments between patients with high and low risk scores, and the risk score was negatively correlated with TMB.Conclusions: The signature consisting of 8 irlncRNA pairs showed good prognostic predictive value.