Immunotherapy of gastric cancer: Past, future perspective and challenges

Xie, Jun; Fu, Liping; Li, Jin

doi:10.1016/j.prp.2020.153322

Cited by 62 publications

(55 citation statements)

References 97 publications

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“…Immune‐checkpoint molecules PD‐1, LAG3, CTLA4, TIGIT, and HAVCR2 (TIM‐3) have been identified and studied in various cancers including liver hepatocellular carcinoma, lung adenocarcinoma, stomach adenocarcinoma, ovarian cancer, and peritoneal carcinoma 59,60 . These immune‐checkpoint molecules have been reported in the different metastatic organs of GC 61,62 . The expression of these immune‐checkpoint molecules in CD8 + T cells in the samples from the same patients was similar (Figure S8 and Table S7).…”

Section: Resultsmentioning

confidence: 67%

Revealing the transcriptional heterogeneity of organ‐specific metastasis in human gastric cancer using single‐cell RNA Sequencing

Jiang

Yang

et al. 2022

Clinical & Translational Med

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Background Deciphering intra‐ and inter‐tumoural heterogeneity is essential for understanding the biology of gastric cancer (GC) and its metastasis and identifying effective therapeutic targets. However, the characteristics of different organ‐tropism metastases of GC are largely unknown. Methods Ten fresh human tissue samples from six patients, including primary tumour and adjacent non‐tumoural samples and six metastases from different organs or tissues (liver, peritoneum, ovary, lymph node) were evaluated using single‐cell RNA sequencing. Validation experiments were performed using histological assays and bulk transcriptomic datasets. Results Malignant epithelial subclusters associated with invasion features, intraperitoneal metastasis propensity, epithelial–mesenchymal transition‐induced tumour stem cell phenotypes, or dormancy‐like characteristics were discovered. High expression of the first three subcluster‐associated genes displayed worse overall survival than those with low expression in a GC cohort containing 407 samples. Immune and stromal cells exhibited cellular heterogeneity and created a pro‐tumoural and immunosuppressive microenvironment. Furthermore, a 20‐gene signature of lymph node‐derived exhausted CD8+ T cells was acquired to forecast lymph node metastasis and validated in GC cohorts. Additionally, although anti‐NKG2A (KLRC1) antibody have not been used to treat GC patients even in clinical trials, we uncovered not only malignant tumour cells but one endothelial subcluster, mucosal‐associated invariant T cells, T cell‐like B cells, plasmacytoid dendritic cells, macrophages, monocytes, and neutrophils may contribute to HLA‐E‐KLRC1/KLRC2 interaction with cytotoxic/exhausted CD8+ T cells and/or natural killer (NK) cells, suggesting novel clinical therapeutic opportunities in GC. Additionally, our findings suggested that PD‐1 expression in CD8+ T cells might predict clinical responses to PD‐1 blockade therapy in GC. Conclusions This study provided insights into heterogeneous microenvironment of GC primary tumours and organ‐specific metastases and provide support for precise diagnosis and treatment.

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Section: Resultsmentioning

confidence: 67%

Revealing the transcriptional heterogeneity of organ‐specific metastasis in human gastric cancer using single‐cell RNA Sequencing

Jiang

Yang

et al. 2022

Clinical & Translational Med

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“…The usage of immunotherapy in the field of GC treatment has increased annually worldwide (7,21). Based on the current clinical trial results, the positive effect of immune checkpoint inhibitors is very apparent (22).…”

Section: Discussionmentioning

confidence: 99%

A Composite Biomarker of Derived Neutrophil–Lymphocyte Ratio and Platelet–Lymphocyte Ratio Correlates With Outcomes in Advanced Gastric Cancer Patients Treated With Anti-PD-1 Antibodies

Pan

Deng

et al. 2022

Front. Oncol.

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BackgroundThe highly heterogeneous characteristics of GC may limit the accuracy of a single biomarker for screening populations benefiting from immunotherapy. However, the combination of multiple indicators can provide more directed information for the detection of potential immune benefit subgroups. At present, there are no recognized complex indexes to identify advanced GC (AGC) in patients who likely benefited from immunotherapy. The objective of this research is to explore whether the composite biomarker of derived neutrophil–lymphocyte ratio (dNLR) and platelet–lymphocyte ratio (PLR) can be used as a reliable prognostic factor for the survival of AGC patients receiving immunotherapy.MethodsFrom December 2014 to May 2021, a total 238 AGC patients at a single Center were included in this retrospective cohort research study. The cutoff value of dNLR was obtained by the ROC curves to predict the disease progression rate at the 8th month and the cutoff value of PLR was estimated by the median value. The cutoff values of dNLR and PLR were 1.95 and 163.63, respectively. The high levels of dNLR (≥1.95) and PLR (≥163.63) were considered to be risk factors. Based on these two risk factors, patients were categorized into 3 groups: the risk factor number for the “good” group was 0, that for the “intermediate” group was 1, and that for the “poor” group was 2. The subjects were divided into two groups: dNLR/PLR-good and dNLR/PLR-intermediate/poor.ResultsOf the 238 patients, the median overall survival (mOS) and progression-free survival (mPFS) were 12.5 and 4.7 months, respectively. Multivariate analysis revealed that the good dNLR/PLR group was independently associated with better prognosis. The intermediate/poor dNLR/PLR group was independently correlated with an over 1.4 times greater risk of disease progression (4.1 months vs. 5.5 months; p = 0.016) and an over 1.54 times greater risk of death (11.1 months vs. 26.3 months; p = 0.033) than the good dNLR/PLR group. However, no clear differences in the disease control rate (DCR) and overall response rate (ORR) were observed between the intermediate/poor dNLR/PLR group and the good dNLR/PLR group (51.5% vs. 56.3%, 26.3% vs. 29.6%; p = 0.494, p = 0.609).ConclusionOur study firstly verifies that the composite biomarker of dNLR and PLR is an independent prognostic factor affecting survival of advanced AGC patients receiving immunotherapy. It may be difficult for patients with the intermediate/poor dNLR/PLR group to benefit from immunotherapy.

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“…M2 macrophages are a well-known tumor-promoting immunosuppressive cell type, and they have been proposed as a therapeutic target in GC ( Gambardella et al, 2020 ). Immunotherapy has been established as a novel treatment in GC, but as monotherapy, PD-1 antibodies have limited benefit because the majority of patients do not respond ( Xie et al, 2021 ). Novel combination options with immunotherapy are in great need in GC.…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Prognostic Classifier Based on Lipid Metabolism–Related Genes in Gastric Cancer

Wei

Luo

et al. 2021

Front. Mol. Biosci.

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Background: Dysregulation of lipid metabolism plays important roles in the tumorigenesis and progression of gastric cancer (GC). The present study aimed to establish a prognostic model based on the lipid metabolism–related genes in GC patients.Materials and Methods: Two GC datasets from the Gene Expression Atlas, GSE62254 (n = 300) and GSE26942 (n = 217), were used as training and validation cohorts to establish a risk predictive scoring model. The efficacy of this model was assessed by ROC analysis. The association of the risk predictive scores with patient characteristics and immune cell subtypes was evaluated. A nomogram was constructed based on the risk predictive score model and other prognostic factors.Results: A risk predictive score model was established based on the expression of 19 lipid metabolism–related genes (LPL, IPMK, PLCB3, CDIPT, PIK3CA, DPM2, PIGZ, GPD2, GPX3, LTC4S, CYP1A2, GALC, SGMS1, SMPD2, SMPD3, FUT6, ST3GAL1, B4GALNT1, and ACADS). The time-dependent ROC analysis revealed that the risk predictive score model was stable and robust. Patients with high risk scores had significantly unfavorable overall survival compared with those with low risk scores in both the training and validation cohorts. A higher risk score was associated with more aggressive features, including a higher tumor grade, a more advanced TNM stage, and diffuse type of Lauren classification of GC. Moreover, distinct immune cell subtypes and signaling pathways were found between the high–risk and low–risk score groups. A nomogram containing patients’ age, tumor stage, adjuvant chemotherapy, and the risk predictive score could accurately predict the survival probability of patients at 1, 3, and 5 years.Conclusion: A novel 19-gene risk predictive score model was developed based on the lipid metabolism–related genes, which could be a potential prognostic indicator and therapeutic target of GC.

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Immunotherapy of gastric cancer: Past, future perspective and challenges

Cited by 62 publications

References 97 publications

Revealing the transcriptional heterogeneity of organ‐specific metastasis in human gastric cancer using single‐cell RNA Sequencing

Revealing the transcriptional heterogeneity of organ‐specific metastasis in human gastric cancer using single‐cell RNA Sequencing

A Composite Biomarker of Derived Neutrophil–Lymphocyte Ratio and Platelet–Lymphocyte Ratio Correlates With Outcomes in Advanced Gastric Cancer Patients Treated With Anti-PD-1 Antibodies

Development and Validation of a Prognostic Classifier Based on Lipid Metabolism–Related Genes in Gastric Cancer

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