Early Immune Remodeling Steers Clinical Response to First-Line Chemoimmunotherapy in Advanced Gastric Cancer.

Adding anti-programmed cell death protein 1 (anti-PD-1) to 5-fluorouracil (5-FU)/platinum improves survival in some advanced gastroesophageal adenocarcinomas (GEA). To understand the effects of chemotherapy and immunotherapy, we conducted a phase II first-line trial (n = 47) sequentially adding pembrolizumab to 5-FU/platinum in advanced GEA. Using serial biopsy of the primary tumor at baseline, after one cycle of 5-FU/platinum, and after the addition of pembrolizumab, we transcriptionally profiled 358,067 single cells to identify evolving multicellular tumor microenvironment (TME) networks. Chemotherapy induced early on-treatment multicellular hubs with tumor-reactive T-cell and M1-like macrophage interactions in slow progressors. Faster progression featured increased MUC5A and MSLN containing treatment resistance programs in tumor cells and M2-like macrophages with immunosuppressive stromal interactions. After pembrolizumab, we observed increased CD8 T-cell infiltration and development of an immunity hub involving tumor-reactive CXCL13 T-cell program and epithelial interferon-stimulated gene programs. Strategies to drive increases in antitumor immune hub formation could expand the portion of patients benefiting from anti-PD-1 approaches. SIGNIFICANCE: The benefit of 5-FU/platinum with anti-PD-1 in first-line advanced gastric cancer is limited to patient subgroups. Using a trial with sequential anti-PD-1, we show coordinated induction of multicellular TME hubs informs the ability of anti-PD-1 to potentiate T cell-driven responses. Differential TME hub development highlights features that underlie clinical outcomes. This article is featured in Selected Articles from This Issue, p. 695.

Patient-derived tumor spheroid-induced angiogenesis preclinical platform for exploring therapeutic vulnerabilities in cancer.

This study addresses the demand for research models that can support patient-treatment decisions and clarify the complexities of a tumor microenvironment by developing an advanced non-animal preclinical cancer model. Based on patient-derived tumor spheroids (PDTS), the proposed model reconstructs the tumor microenvironment with emphasis on tumor spheroid-driven angiogenesis. The resulting microfluidic chip system mirrors angiogenic responses elicited by PDTS, recapitulating patient-specific tumor conditions and providing robust, easily quantifiable outcomes. Vascularized PDTS exhibited marked angiogenesis and tumor proliferation on the microfluidic chip. Furthermore, a drug that targets the vascular endothelial growth factor receptor 2 (VEGFR2, ramucirumab) was deployed, which effectively inhibited angiogenesis and impeded tumor invasion. This innovative preclinical model was used for investigating distinct responses for various drug combinations, encompassing HER2 inhibitors and angiogenesis inhibitors, within the context of PDTS. This integrated platform could potentially advance precision medicine by harmonizing diverse data points within the tumor microenvironment with a focus on the interplay between cancer and the vascular system.

Patient-derived exosomes facilitate therapeutic targeting of oncogenic MET in advanced gastric cancer.

Gastric cancer (GC) with peritoneal metastases and malignant ascites continues to have poor prognosis. Exosomes mediate intercellular communication during cancer progression and promote therapeutic resistance. Here, we report the significance of exosomes derived from malignant ascites (EXOAscites) in cancer progression and use modified exosomes as resources for cancer therapy. EXOAscites from patients with GC stimulated invasiveness and angiogenesis in an ex vivo three-dimensional autologous tumor spheroid microfluidic system. EXOAscites concentration increased invasiveness, and blockade of their secretion suppressed tumor progression. In MET-amplified GC, EXOAscites contain abundant MET; their selective delivery to tumor cells enhanced angiogenesis and invasiveness. Exosomal MET depletion substantially reduced invasiveness; an additive therapeutic effect was induced when combined with MET and/or VEGFR2 inhibition in a patient-derived MET-amplified GC model. Allogeneic MET-harboring exosome delivery induced invasion and angiogenesis in a MET non-amplified GC model. MET-amplified patient tissues showed higher exosome concentration than their adjacent normal tissues. Manipulating exosome content and production may be a promising complementary strategy against GC.

Multi-faceted attributes of salivary cell-free DNA as liquid biopsy biomarkers for gastric cancer detection.

BACKGROUND: Recent advances in circulating cell-free DNA (cfDNA) analysis from biofluids have opened new avenues for liquid biopsy (LB). However, current cfDNA LB assays are limited by the availability of existing information on established genotypes associated with tumor tissues. Certain cancers present with a limited list of established mutated cfDNA biomarkers, and thus, nonmutated cfDNA characteristics along with alternative biofluids are needed to broaden the available cfDNA targets for cancer detection. Saliva is an intriguing and accessible biofluid that has yet to be fully explored for its clinical utility for cancer detection. METHODS: In this report, we employed a low-coverage single stranded (ss) library NGS pipeline "Broad-Range cell-free DNA-Seq" (BRcfDNA-Seq) using saliva to comprehensively investigate the characteristics of salivary cfDNA (ScfDNA). The identification of cfDNA features has been made possible by applying novel cfDNA processing techniques that permit the incorporation of ultrashort, ss, and jagged DNA fragments. As a proof of concept using 10 gastric cancer (GC) and 10 noncancer samples, we examined whether ScfDNA characteristics, including fragmentomics, end motif profiles, microbial contribution, and human chromosomal mapping, could differentiate between these two groups. RESULTS: Individual and integrative analysis of these ScfDNA features demonstrated significant differences between the two cohorts, suggesting that disease state may affect the ScfDNA population by altering nuclear cleavage or the profile of contributory organism cfDNA to total ScfDNA. We report that principal component analysis integration of several aspects of salivary cell-free DNA fragmentomic profiles, genomic element profiles, end-motif sequence patterns, and distinct oral microbiome populations can differentiate the two populations with a p value of < 0.0001 (PC1). CONCLUSION: These novel features of ScfDNA characteristics could be clinically useful for improving saliva-based LB detection and the eventual monitoring of local or systemic diseases.

Multi-Faceted Attributes of Salivary Cell-free DNA as Liquid Biopsy Biomarkers for Gastric Cancer Detection.

Background: Recent advances in circulating cell-free DNA (cfDNA) analysis from biofluids have opened new avenues for liquid biopsy (LB). However, current cfDNA LB assays are limited by the availability of existing information on established genotypes associated with tumor tissues. Certain cancers present with a limited list of established mutated cfDNA biomarkers, and thus, nonmutated cfDNA characteristics along with alternative biofluids are needed to broaden the available cfDNA targets for cancer detection. Saliva is an intriguing and accessible biofluid that has yet to be fully explored for its clinical utility for cancer detection. Methods: In this report, we employed a low-coverage single stranded (ss) library NGS pipeline "Broad-Range cell-free DNA-Seq" (BRcfDNA-Seq) using saliva to comprehensively investigate the characteristics of salivary cfDNA (ScfDNA). The identification of cfDNA features has been made possible by applying novel cfDNA processing techniques that permit the incorporation of ultrashort, ss, and jagged DNA fragments. As a proof of concept using 10 gastric cancer (GC) and 10 noncancer samples, we examined whether ScfDNA characteristics, including fragmentomics, end motif profiles, microbial contribution, and human chromosomal mapping, could differentiate between these two groups. Results: Individual and integrative analysis of these ScfDNA features demonstrated significant differences between the two cohorts, suggesting that disease state may affect the ScfDNA population by altering nuclear cleavage or the profile of contributory organism cfDNA to total ScfDNA. We report that principal component analysis integration of several aspects of salivary cell-free DNA fragmentomic profiles, genomic element profiles, end-motif sequence patterns, and distinct oral microbiome populations can differentiate the two populations with a p value of < 0.0001 (PC1). Conclusion: These novel features of ScfDNA characteristics could be clinically useful for improving saliva-based LB detection and the eventual monitoring of local or systemic diseases.

High tumor mutational burden predicts favorable response to anti-PD-(L)1 therapy in patients with solid tumor: a real-world pan-tumor analysis.

BACKGROUND: Tumor mutation burden (TMB) is an important biomarker to predict response to anti-PD-L1 treatment across cancer types. TruSight Oncology 500 (TSO500) is currently used globally as a routine assay for TMB. METHODS: Between 2019 and 2021, 1744 patients with cancer received TSO500 assay as part of a real-world clinical practice at the Samsung Medical Center, and 426 received anti-PD-(L)1 treatment. Correlations between TMB and clinical outcomes of anti-PD-(L)1 were analyzed. Digital spatial profiling (DSP) was used to investigate the tumor immune environment's influence on the treatment response to anti-PD-(L)1 in high TMB (TMB-H) patients (n=8). RESULTS: The incidence of TMB-H (≥10 mutations (mt)/megabase (Mb)) was 14.7% (n=257). Among TMB-H patients, the most common cancer type was colorectal cancer (n=108, 42.0%), followed by gastric cancer (GC; n=49, 19.1%), bladder cancer (n=21, 8.2%), cholangiocarcinoma (n=21, 8.2%), non-small cell lung cancer (n=17, 6.6%), melanoma (n=8, 3.1%), gallbladder cancer (GBC; n=7, 2.7%), and others (n=26, 10.1%). The response rate to anti-PD-(L)1 therapy was substantially higher in GC (71.4% vs 25.8%), GBC (50.0% vs 12.5%), head and neck cancer (50.0% vs 11.1%), and melanoma (71.4% vs 50.7%) among TMB-H patients when compared with low TMB (TMB-L) (<10 mt/Mb) patients with statistical significance. Additional analysis of patients with TMB ≥16 mt/Mb demonstrated prolonged survival after anti-PD-(L)1 therapy compared with patients with TMB-L (not reached vs 418 days, p=0.03). The benefit of TMB ≥16 mt/Mb was greater when combined with microsatellite status and PD-L1 expression profiles. Among the TMB-H patients, those who responded to anti-PD-L1 therapy had numerous active immune cells that infiltrated the tumor regions during the DSP analysis. Natural killer cells (p=0.04), cytotoxic T cells (p<0.01), memory T cells (p<0.01), naïve memory T cells (p<0.01), and proteins related to T-cell proliferation (p<0.01) were observed in a responder group compared with a non-responder group. In contrast, exhausted T-cell and M2 macrophage counts were increased in the non-responder group. CONCLUSIONS: The overall incidence of TMB status was analyzed by the TSO500 assay, and TMB-H was observed in 14.7% of the pan-cancer population. In a real-world setting, TMB-H identified by a target sequencing panel seemed to predict response to anti-PD-(L)1 therapy, especially in patients with a higher proportion of immune cells enriched in the tumor region.

Five-gene signature for the prediction of response to immune checkpoint inhibitors in patients with gastric and urothelial carcinomas.

BACKGROUND: Ample evidence supports the potential of programmed death-ligand 1 (PD-L1) expression, detected by immunohistochemistry, as a predictive biomarker for immunotherapy in patients with advanced cancers. To predict the response to immune checkpoint inhibitors in patients with gastric and urothelial carcinomas, we aimed to replace PD-L1 combined positive score (CPS) with CD274 mRNA in the original four-gene signature and PD-L1 CPS model developed by us. METHOD: We used quantitative real-time polymerase chain reaction (qRT-PCR) to measure the expression levels of five target genes in a cohort of 49 patients (33 with gastric cancer and 16 with urothelial carcinoma) who had received immunotherapy and whose therapeutic responses were available. The predictive performance was evaluated using R package maxstat. RESULTS: Cutoff values of mRNA expression level were measured using the log-rank statistics for progression-free survival (PFS). Based on these cutoffs, immunotherapy responses were predicted and sorted into responder (n = 12, 24.5%) and non-responder (n = 37, 75.5%) groups. The median PFS values of predicted responders and non-responders were 14.8 months (95% confidence interval [CI]: 0-34.7) and 4.7 months (95% CI: 1.0-8.4, p = 0.02), respectively. Among the 12 predicted responders, 10 had microsatellite-stable tumors with a low tumor mutational burden. The actual clinical responses (complete and partial) were higher in the responder group than those in the non-responder group: 83.3% and 16.2%, respectively. CONCLUSION: We modified a predictive biomarker for CD274 mRNA expression to predict the response to immunotherapy in patients with gastric or urothelial carcinomas.

Performance of Salivary Extracellular RNA Biomarker Panels for Gastric Cancer Differs between Distinct Populations.

Gastric cancer (GC) has the fifth highest incidence among cancers and is the fourth leading cause of cancer-related death GC has predominantly a higher number of cases in certain ethnic groups such as the Korean population. GC found at an early stage is more treatable and has a higher survival rate as compared with GC found at a late stage. However, a diagnosis of GC is often delayed due to the lack of early symptoms and available screening programs in United States. Extracellular RNA (exRNA) is an emerging paradigm; exRNAs have the potential to serve as biomarkers in panels aimed at early detection of cancer. We previously reported the successful use of a panel of salivary exRNA for detecting GC in a high-prevalence Korean cohort, and that genetic changes reflected cancer-associated salivary exRNA changes. The current study is a case-control study of salivary exRNA biomarkers for detecting GC in an ethnically distinct U.S. cohort. A model constructed for the U.S. cohort combined demographic characteristics and salivary miRNA and mRNA biomarkers for GC and yielded an area under the receiver operating characteristic (ROC) curve (AUC) of 0.78. However, the constituents of this model differed from that constructed for the Korean cohort, thus, emphasizing the importance of population-specific biomarker development and validation.

Plasma contains ultrashort single-stranded DNA in addition to nucleosomal cell-free DNA.

Plasma cell-free DNA is being widely explored as a biomarker for clinical screening. Currently, methods are optimized for the extraction and detection of double-stranded mononucleosomal cell-free DNA of ∼160bp in length. We introduce uscfDNA-seq, a single-stranded cell-free DNA next-generation sequencing pipeline, which bypasses previous limitations to reveal a population of ultrashort single-stranded cell-free DNA in human plasma. This species has a modal size of 50nt and is distinctly separate from mononucleosomal cell-free DNA. Treatment with single-stranded and double-stranded specific nucleases suggests that ultrashort cell-free DNA is primarily single-stranded. It is distributed evenly across chromosomes and has a similar distribution profile over functional elements as the genome, albeit with an enrichment over promoters, exons, and introns, which may be suggestive of a terminal state of genome degradation. The examination of this cfDNA species could reveal new features of cell death pathways or it can be used for cell-free DNA biomarker discovery.

Expression of CD274 mRNA Measured by qRT-PCR Correlates With PD-L1 Immunohistochemistry in Gastric and Urothelial Carcinoma.

Programmed death-ligand 1 (PD-L1) immunohistochemistry (IHC) is widely used to predict the clinical responses to immune checkpoint inhibitors (ICIs). However, PD-L1 IHC suffers from the complexity of multiple testing platforms and different cutoff values caused by the current one drug-one diagnostic test co-development approach for ICIs. We aimed to test whether PD-L1 (CD274) mRNA expression levels measured using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) can represent PD-L1 IHC and predict responses to ICI. The FDA-approved PD-L1 IHC results with 22C3 pharmDx (gastric cancer) and SP142 (urothelial carcinoma) were compared with CD274 mRNA expression levels via qRT-PCR using the same formalin-fixed, paraffin-embedded tissue blocks from 59 gastric cancer and 41 urothelial carcinoma samples. CD274 mRNA expression was identified using three independent sets of primers and TaqMan® probes targeting exon 1-2, exon 3-4, and exon 5-6. CD274 mRNA levels in spanning exon 1-2, exon 3-4, and exon 5-6 junctions of CD274 correlated well with PD-L1 expression (r2=0.81, 0.65, and 0.59, respectively). The area under the curve of exon 1-2 was the highest (0.783), followed by exon 3-4 (0.701), and exon 5-6 (0.671) of the CD274 gene against the PD-L1 combined positive score cutoff of 10. When CD274 mRNA expression was matched for response to immunotherapy, the overall response rate was higher in patients with high CD274 mRNA levels with a cutoff of 0.0722 (gastric cancer) and 0.0480 (urothelial carcinoma) than in those with low CD274 mRNA expression (P < 0.001 and P = 0.018, respectively). These results show that CD274 mRNA levels predicted ICI responses in patients with gastric or urothelial carcinomas and could be used as alternatives for PD-L1 IHC.

Early Tumor-Immune Microenvironmental Remodeling and Response to First-Line Fluoropyrimidine and Platinum Chemotherapy in Advanced Gastric Cancer.

Chemotherapy is ubiquitous in first-line treatment of advanced gastric cancer, yet responses are heterogeneous, and little is known about mediators of chemotherapy response. To move forward, an understanding of the effects of standard chemotherapy on the tumor-immune microenvironment (TME) is needed. Coupling whole-exome sequencing, bulk RNA and single-cell transcriptomics from paired pretreatment and on-treatment samples in treatment-naïve patients with HER2-positive and HER2-negative gastric cancer, we define features associated with response to platinum-based chemotherapy. Response was associated with on-treatment TME remodeling including natural killer (NK) cell recruitment, decreased tumor-associated macrophages, M1-macrophage repolarization, and increased effector T-cell infiltration. Among chemotherapy nonresponders, we observed low/absent PD-L1 expression or modulation, on-treatment increases in Wnt signaling, B-cell infiltration, and LAG3-expressing T cells coupled to an exodus of dendritic cells. We did not observe significant genomic changes in early on-treatment sampling. We provide a map of on-treatment TME modulation with standard chemotherapy and nominate candidate future approaches. SIGNIFICANCE: Using paired pretreatment and on-treatment samples during standard first-line chemotherapy, we identify chemotherapy-induced NK-cell infiltration, macrophage repolarization, and increased antigen presentation among responders. Increased LAG3 expression and decreased dendritic cell abundance were seen in nonresponders, emphasizing remodeling of the TME during chemotherapy response and resistance. This article is highlighted in the In This Issue feature, p. 873.

Deep learning-based virtual cytokeratin staining of gastric carcinomas to measure tumor-stroma ratio.

The tumor-stroma ratio (TSR) determined by pathologists is subject to intra- and inter-observer variability. We aimed to develop a computational quantification method of TSR using deep learning-based virtual cytokeratin staining algorithms. Patients with 373 advanced (stage III [n = 171] and IV [n = 202]) gastric cancers were analyzed for TSR. Moderate agreement was observed, with a kappa value of 0.623, between deep learning metrics (dTSR) and visual measurement by pathologists (vTSR) and the area under the curve of receiver operating characteristic of 0.907. Moreover, dTSR was significantly associated with the overall survival of the patients (P = 0.0024). In conclusion, we developed a virtual cytokeratin staining and deep learning-based TSR measurement, which may aid in the diagnosis of TSR in gastric cancer.

Validation of the Combined Biomarker for Prediction of Response to Checkpoint Inhibitor in Patients with Advanced Cancer.

Although immune checkpoint inhibitors can induce durable responses in patients with multiple types of advanced cancer, only a limited number of patients have a known reliable biomarker. This study aimed to validate the IMmunotherapy Against GastrIc Cancer (IMAGiC) model, which was developed based on a previous study of four-gene and PD-L1 level, to predict immunotherapy response. We developed a clinical assay for formalin-fixed paraffin-embedded samples using quantitative real-time polymerase chain reaction to measure the expression level of the previously published four-gene set. The predictive performance was validated in a cohort of 89 patients with several advanced tumor types. The IMAGiC score was derived from tumor samples of 89 patients consisting of eight cancer types, and 73 out of 89 patients available for clinical response were analyzed with clinicopathological factors. The IMAGiC group (responder vs. non-responder) was determined with a specific value of the IMAGiC score as a cutoff, which was set by log-rank statistics for progression-free survival (PFS) divided the patients into 56 (76.7%) non-responders and 17 (23.3%) responders. Clinical responders (complete response/partial response) were higher in the IMAGiC responder group than in the non-responder group (70.6 vs. 21.4%). The median PFS of the IMAGiC responder group and non-responder was 20.8 months (95% CI 9.1-not reached) and 6.7 months (95% CI 4.9-11.1, p = 0.007), respectively. Among the 17 IMAGiC responders, 11 patients had tumor mutation burden-low and microsatellite-stable tumors. This study validated a predictive model based on a four-gene expression signature. Along with conventional biomarkers, our model could be useful for predicting response to immunotherapy in patients with advanced cancer.

PD-L1 expression in paired biopsies and surgical specimens in gastric adenocarcinoma: A digital image analysis study.

Programmed death-ligand 1 (PD-L1) expression in biopsies of gastric carcinoma may predict the results in corresponding surgical specimens. We compared PD-L1 immunohistochemistry (IHC) 22C3 pharmDx expression in paired biopsy and resection specimens. We also characterized the validity of a new PD-L1 assay using digital image analysis. PD-L1 IHC with 22C3 pharmDx and clone 73-10 was performed in 224 gastric cancer tissues (112 biopsies and paired surgical tissues) and the specimens were analyzed with the Leica Aperio Imagescope. For statistical analyses, the area under the receiver operating characteristic curve and R package were used. With 22C3 pharmDx, a PD-L1 combined positive score of ≥1 was found in 36 biopsied (32.14 %) and 53 surgical (47.32 %) samples. PD-L1 expression results were concordant in 71 cases (63.4 %) and discordant in 41 (36.6 %). The overall discordance rate was 36.61 % (95 % confidence interval 2.101-8.983) and the κ value was 0.254 with fair agreement. The sensitivity and specificity of biopsy PD-L1 to predict the results of the surgical specimen was 62 % and 73 %, respectively. The correlation of 22C3 pharmDx and clone 73-10 was high (correlation coefficient = 0.88). When only tumor cell staining was compared, this correlation was increased (correlation coefficient = 0.95). Our results indicated moderate association of PD-L1 expression between gastric biopsies and corresponding resected tumors. Results of PD-L1 assay with 73-10 are comparable to 22C3 pharmDx results.

Digital image analysis in pathologist-selected regions of interest predicts survival more accurately than whole-slide analysis: a direct comparison study in 153 gastric carcinomas.

Automatic quantification of biomarkers such as tumor-infiltrating lymphocytes and PD-L1 is one of the most studied topics in digital pathology image analysis (DIA). However, direct comparison between the DIA of a whole-slide image (WSI) and that of regions of interest (ROIs) chosen by pathologists has not been performed. In this study, we aimed to compare the prognostic value of tumor microenvironment markers CD8 and PD-L1, measured by DIA of WSIs and ROIs. We selected 153 primary gastric cancer tissues and stained them with CD8 and PD-L1. All IHC slides were scanned at ×200 magnification and ratios of CD8 and PD-L1 were measured in WSIs and ROIs from the invasive front, within the tumor, and the mucosa. Patients with high CD8 and PD-L1 ratios showed more favorable outcomes compared to those with low ratios. Pathologist-aided DIA predicted the survival of patients more accurately than WSI analysis (CD8, p = 0.025 versus p = 0.068; PD-L1, p = 0.008 versus p = 0.2). Although a high density of CD8+ T cells at the invasive front correlated best with patient survival, CD8 ratio in the mucosa could also predict patient outcome. In conclusion, CD8 and PD-L1 ratios measured by pathologist-aided DIA predicted survival more accurately than WSI analyses and ROIs at the invasive front correlated best with patient outcome.

PTEN Protein Loss and Loss-of-Function Mutations in Gastric Cancers: The Relationship with Microsatellite Instability, EBV, HER2, and PD-L1 Expression.

Inactivation of phosphatase and tensin homolog (PTEN) is caused by multiple mechanisms, and loss of PTEN activity is related to the progression of various cancers. In gastric cancer (GC), the relationship between the loss of PTEN protein expression and various genetic alterations remains unclear. The effects of microsatellite instability (MSI), Epstein-Barr virus (EBV), HER2 overexpression, and PD-L1 expression on PTEN mutation have not been fully explored. We performed comprehensive cancer panel tests with a cohort of 322 tumor samples from patients with advanced GC. Immunohistochemistry for PTEN protein was performed in all cases, and the loss of protein expression was defined as a complete absence of nuclear staining. In total, 34 cases (10.6%) had pathogenic PTEN mutations, of which 19 (55.9%) showed PTEN protein loss. The most common PTEN variants associated with protein loss were p.R130 (n = 4) followed by p.R335, p.L265fs, and deletions (n = 2). All the ten nonsense mutations identified in the samples resulted in PTEN inactivation. In the remaining 288 GC cases with wild-type PTEN, protein loss was found in 35 cases (12.2%). Thus, PTEN mutations were significantly associated with PTEN protein loss (p = 5.232 × 10-10), high MSI (p = 3.936 × 10-8), and EBV-positivity (p = 0.0071). In conclusion, our results demonstrate that loss-of-function mutations in PTEN are a frequent genetic mechanism of PTEN inactivation in GC.

Tumor Mutational Burden Determined by Panel Sequencing Predicts Survival After Immunotherapy in Patients With Advanced Gastric Cancer.

Objective: Panel-based sequencing is widely used to measure tumor mutational burden (TMB) in clinical trials and is ready to enter routine diagnostics. However, cut-off points to distinguish "TMB-high" from "TMB-low" tumors are not consistent and the clinical implications of TMB in predicting responses to immune checkpoint blockade (ICB) in gastric cancer are not clearly defined. We aimed to assess whether TMB is associated with the response to immunotherapy and to examine its relation with other biomarkers of immunotherapy response in advanced gastric cancer. Design: In total, 63 patients with advanced gastric cancer treated with ICB were included in the study. Panel-based TMB in gastric tumor samples, treatment responses to ICB, clinicopathological data, and time to progression were retrospectively analyzed. Microsatellite instability (MSI) status, Epstein-Barr virus (EBV) positivity, and programmed death-ligand 1 (PD-L1) combined positive score (CPS) were also analyzed. Results: TMB ranged from 0 to 446 mutations/megabase (mt/mb) and was significantly associated with MSI (P < 0.001), PD-L1 CPS (P = 0.022), response to ICB (P = 0.04), chemotherapy (P = 0.02) and older patient age (≥65 years; P = 0.0014). The cut-off point of 14.31 mt/mb determined by log-rank statistics for progression-free survival divided the tumors into eight (12.7%) TMB-high and 55 (87.3%) TMB-low tumors. The median TMB of the chemo-refractory group was significantly higher (8.43 mt/mb) compared to that of chemo-naïve group (3.42 mt/mb) (P = 0.02). Patients with TMB-high tumors showed prolonged progression-free survival in univariate [HR, 0.32; 95% confidence interval (CI), 0.12-0.90] and multivariate (HR, 0.21; 95% CI, 0.07-0.69) analyses. In area under the receiver operating curve (AUC) analysis of TMB, PD-L1, EBV, MSI, and their combination, the AUC value was the highest for EBV (0.97), followed by MSI (0.96), PD-L1 (0.81), the combination (0.78), and TMB (0.56). Conclusion: In addition to EBV, MSI, and PD-L1 CPS, TMB could be used as a predictive biomarker in patients with advanced gastric cancer treated with ICB and may aid clinical decision making.

Dysregulated miRNA in a cancer-prone environment: A study of gastric non-neoplastic mucosa.

Understanding cancer-prone environments is important to efficiently detect and prevent cancers. The associations between miRNA and cancer-prone environments are still largely unknown in gastric cancer (GC). Six miRNAs that are differentially expressed during gastric carcinogenesis were selected, and quantitative real-time PCR was performed in an independent training set (fresh non-tumor and tumor samples from 18 GC patients) and validation sets (set 1 with formalin-fixed paraffin-embedded non-tumor and tumor samples from 19 solitary GC and set 2 with 37 multiple GC patients). The results were compared with those of 37 gastric mucosa from 20 healthy volunteers. The expression levels of miR-26a, miR-375, and miR-1260 in gastric mucosa from healthy volunteers were statistically higher than that of non-tumorous gastric mucosa located 3 cm apart from the GC in the training set (miR-26a, P < 0.0001; miR-375, P = 0.0049; miR-1260, P = 0.0172), validation set 1 (miR-26a and miR-375, P < 0.0001; miR-1260, P = 0.0008), and validation set 2 (miR-26a, miR-375, and miR-1260, P < 0.0001). And a combination of miR-26a and miR-1260 showed the highest area under the curve value of 0.89. miRNAs are differentially expressed in non-neoplastic gastric mucosa and can be used as a biomarker to predict cancer-prone environments.

CDH1 mutations in gastric cancers are not associated with family history.

CDH1 mutation is the most frequent genetic alteration in hereditary diffuse gastric cancer (GC) and early onset diffuse GC patients. However, the incidence of CDH1 mutations in sporadic GC with or without family history has not been studied. This retrospective study includes a total of 993 Korean patients with primary advanced GC who underwent surgery and received palliative chemotherapy. Targeted deep sequencing was performed in all cases and family history of GC was searched with survival analysis. We found CDH1 alterations in 146 of 993 patients (14.7 %) and 8 were germline (0.8 %). Out of 146 patients with CDH1 mutations, 25 (17.1 %) had a family history of GC in one of their first relatives, and 12 patients (8.2 %) were diagnosed with familial GC (FGC). All cases with FGC were diffuse type by Lauren classification, and only one harbored a previously reported germline mutation of CDH1 (c.2638 G > A) and the remaining 11 harbored known somatic CDH1 mutations. Among all patients with CDH1 mutation, there was no significant survival difference between patients with family history or FGC. In the 847 patients without CDH1 mutation, 189 (22.3 %) had a family history of GC and 92 patients (10.9 %) were FGC. CDH1 mutations were more frequent in patients with early onset (<45 years) GC (45.5 %) compared with patients with late onset GC (10.9 %) (p = 0.001), but were not significantly associated with the family history of GC (p > 0.05). CDH1 mutations are mostly somatic and typically are not associated with family history.