Immune Score Predicts Outcomes of Gastric Cancer Patients Treated with Adjuvant Chemoradiotherapy

Development of a Prognostic Nomogram for Overall Survival in Gastric Cancer Patients Who Underwent Adjuvant Chemoradiotherapy

PURPOSE

The aim of this study was to identify prognostic factors influencing overall survival (OS) in patients with gastric cancer treated with adjuvant chemoradiotherapy (CRT) and to develop a predictive model.

METHODS

We retrospectively evaluated 245 non-metastatic gastric cancer patients who received adjuvant CRT or radiotherapy from 2010 to 2020. Survival analyses were performed using the Kaplan-Meier method. Prognostic factors were identified through univariate and multivariate Cox regression analyses. A nomogram was constructed based on significant predictive factors for OS, including lymph node ratio, T classification, tumor location, and local recurrence.

RESULTS

The median follow-up duration was 41.5 months (range, 6-144.8 months). The 2- and 5-year OS and progression-free survival were 77% and 53% and 64% and 49%, respectively. In multivariate analysis, tumor location (distal vs. proximal), pT classification (pT1-2 vs. pT3-4), lymph node ratio (< 0.18 vs. ≥ 0.18), and presence of local recurrence were independent prognostic factors for OS. The optimal cut-off value for the total nomogram score predicting OS was 116 points. Patients with < 116 points had 2- and 5-year OS rates of 87% and 73%, respectively, compared to 67% and 30% for those with ≥ 116 points.

CONCLUSION

A nomogram was constructed incorporating lymph node ratio, T classification, tumor site, and local recurrence for gastric cancer patients receiving adjuvant CRT. Patients with a total score below 116 demonstrated higher survival rates. This nomogram may aid in defining optimal follow-up intervals.

Characteristics of auto-quantified tumor-infiltrating lymphocytes and the prognostic value in adenocarcinoma of the esophagogastric junction, gastric adenocarcinoma, and esophageal squamous cell carcinoma

BACKGROUND

Adenocarcinoma of the esophagogastric junction (AEGJ) with a specific pathological profile and poor prognosis has limited therapeutic options. Previous studies have found that TILs exhibit distinct characteristics in different tumors and are correlated with tumor prognosis. We established cellular training sets to obtain auto-quantified TILs in pathological images. And we compared the characteristics of TILs in AEGJ with those in esophageal squamous cell carcinoma (ESCC) and gastric adenocarcinoma (GAC) to gain insight into the unique immune environments of these three tumors and investigate the prognostic value of TILs in these three tumors.

METHODS

Utilizing a case-control study design, we analyzed 214 AEGJ, 256 GAC, and 752 ESCC cases. The TCGA dataset was used to validate prognostic value of auto-quantified TILs. The specific cellular training sets were established by experienced pathologists to determine TILs counts. Kruskal-Wallis test and multi-variable linear regression were conducted to explore TILs characteristics. Survival analyses were performed with Kaplan-Meier method and Cox proportional hazards model.

RESULTS

The three cellular training sets of these cancers achieved a classification accuracy of 87.55 at least. The median auto-quantified TILs of AEGJ, GAC, and ESCC cases were 4.82%, 1.92%, and 0.12%, respectively. The TILs demonstrated varied characteristics under distinctive clinicopathological traits. The higher TILs proportion was associated with better prognosis in esophagogastric cancers (all P < 0.05) and was an independent prognostic biomarker on AEGJ in both datasets (Taixing: HR = 0.965, 95% CI = 0.938-0.994; TCGA: HR = 0.811, 95% CI = 0.712-0.925).

CONCLUSIONS

We found variations in TILs across ESCC, GAC, and AEGJ, as assessed by image processing algorithms. Additionally, TILs in these three cancers are an independent prognostic factor. This enhances our understanding of the unique immune characteristics of the three tumors, improving patient outcomes.

The molecular mechanism of actions and clinical utilities of tumor infiltrating lymphocytes in gastrointestinal cancers: a comprehensive review and future prospects toward personalized medicine

Gastrointestinal (GI) cancers remain a significant global health burden, accounting for a substantial number of cases and deaths. Regrettably, the inadequacy of dependable biomarkers hinders the precise forecasting of patient prognosis and the selection of appropriate therapeutic sequencing for individuals with GI cancers, leading to suboptimal outcomes for numerous patients. The intricate interplay between tumor-infiltrating lymphocytes (TILs) and the tumor immune microenvironment (TIME) has been shown to be a pivotal determinant of response to anti-cancer therapy and consequential clinical outcomes across a multitude of cancer types. Therefore, the assessment of TILs has garnered global interest as a promising prognostic biomarker in oncology, with the potential to improve clinical decision-making substantially. Moreover, recent discoveries in immunotherapy have progressively changed the landscape of cancer treatment and significantly prolonged the survival of patients with advanced cancers. Nonetheless, the response rate remains constrained within solid tumor sufferers, even when TIL landscapes appear comparable, which calls for the development of our understanding of cellular and molecular cross-talk between TIME and tumor. Hence, this comprehensive review encapsulates the extant literature elucidating the TILs' underlying molecular pathogenesis, prognostic significance, and their relevance in the realm of immunotherapy for patients afflicted by GI tract cancers. Within this review, we demonstrate that the type, density, and spatial distribution of distinct TIL subpopulations carries pivotal implications for the prediction of anti-cancer treatment responses and patient survival. Furthermore, this review underscores the indispensable role of TILs in modulating therapeutic responses within distinct molecular subtypes, such as those characterized by microsatellite stability or programmed cell death ligand-1 expression in GI tract cancers. The review concludes by outlining future directions in TIL-based personalized medicine, including integrating TIL-based approaches into existing treatment regimens and developing novel therapeutic strategies that exploit the unique properties of TILs and their potential as a promising avenue for personalized cancer treatment.

Development of an immunogenic cell death prognostic signature for predicting clinical outcome and immune infiltration characterization in stomach adenocarcinoma

Stomach adenocarcinoma (STAD) is a common gastric histological cancer type with a high mortality rate. Immunogenic cell death (ICD) plays a key factor during carcinogenesis progress, whereas the prognostic value and role of ICD-related genes (ICDRGs) in STAD remain unclear. The MSigDB database collecting ICDRGs were selected by univariate Cox regression analysis and LASSO algorithm to establish a novel risk model. The Kaplan-Meier survival analysis indicated a significant difference of OS rate of patients by risk score stratification. ESTIMATE, CIBERSORT, and single sample gene set enrichment analysis (ssGSEA) algorithms were conducted to estimate the immune infiltration landscape by risk stratification. Subgroup analysis and tumor mutation burden analysis were also analyzed to identify characteristics between groups. Differences in therapeutic responsiveness to chemotherapeutic drugs and targeted drugs were also analyzed between high-risk group and low-risk group. The impact of one ICDRG, GPX1, on the proliferation, migration and invasiveness of was confirmed by in vitro experiments in GC cells to test the reliability of bioinformatics results. This study gives evidence of the involvement of ICD process in STAD and provides a new perspective for further accurate assessment of prognosis and therapeutic efficacy in STAD patients. Stomach adenocarcinoma (STAD) is a common gastric histological cancer type with a high mortality rate. Immunogenic cell death (ICD) plays a key factor during carcinogenesis progress, whereas the prognostic value and role of ICD-related genes (ICDRGs) in STAD remains unclear. The MSigDB database collected ICDRGs were selected by univariate Cox regression analysis and LASSO algorithm to establish a novel risk model. The Kaplan-Meier survival analysis indicated a significant difference of OS rate of patients by risk score stratification. ESTIMATE, CIBERSORT, and single sample gene set enrichment analysis (ssGSEA) algorithms were conducted to estimate the immune infiltration landscape by risk stratification. Subgroup analysis and tumor mutation burden analysis were also analyzed to identify characteristics between groups. Differences in therapeutic responsiveness to chemotherapeutic drugs and targeted drugs were also analyzed between high-risk group and low-risk group. The impact of one ICDRG, GPX1, on the proliferation, migration and invasiveness of was confirmed by in vitro experiments in GC cells to test the reliability of bioinformatics results. This study gives evidence of the involvement of ICD process in STAD and provides a new perspective for further accurate assessment of prognosis and therapeutic efficacy in STAD patients.

Increased CD4/CD8 Lymphocyte ratio predicts favourable neoadjuvant treatment response in gastric cancer: A prospective pilot study

BACKGROUND

Despite optimal neoadjuvant chemotherapy only 40% of gastric cancer tumours achieve complete or partial treatment response. In the absence of treatment response, neoadjuvant chemotherapy in gastric cancer contributes to adverse events without additional survival benefit compared to adjuvant treatment or surgery alone. Additional strategies and methods are required to optimize the allocation of existing treatment regimens such as FLOT chemotherapy (5-Fluorouracil, Leucovorin, Oxaliplatin and Docetaxel). Predictive biomarkers detected using immunohistochemistry (IHC) methods may provide useful data regarding treatment response.

AIM

To investigate the utility of CD4, CD8, Galectin-3 and E-cadherin in predicting neoadjuvant FLOT chemotherapy tumour response in gastric adenocarcinoma.

METHODS

Forty-three adult patients with gastric adenocarcinoma, of which 18 underwent neoadjuvant chemotherapy, were included in a prospective clinical cohort. Endoscopic biopsies were obtained from gastric cancer and normal adjacent gastric mucosa. Differences in expression of Galectin-3, E-cadherin, CD4⁺ and CD8⁺ molecules between tumours with and without treatment response to neoadjuvant chemotherapy were assessed with IHC. Treatment response was graded by clinical pathologists using the Tumour Regression Score according to the College of American Pathologists criteria. Treatment response was defined as complete or near complete tumour response, whereas partial or poor/no response was defined as incomplete. Digital IHC images were annotated and quantitatively assessed using QuPath 0.3.1. Biomarker expression between responsive and incomplete response tumours was assessed using a two-sided Wilcoxon test. Biomarker expression was also compared between normal and cancer tissue and between 15 paired tumour samples before and after chemotherapy. We performed a preliminary multivariate analysis and power analysis to guide future study. Statistical analyses were completed using R 4.1.2.

RESULTS

The ratio between CD4⁺ and CD8⁺ lymphocytes was significantly greater in treatment responsive tumours (Wilcoxon, P = 0.03). In univariate models, CD4⁺/CD8⁺ ratio was the only biomarker that significantly predicted favourable treatment response (Accuracy 86%, P < 0.001). Using a glmnet multivariate model, high CD4⁺/CD8⁺ ratio and low Galectin-3 expression were the most influential variables in predicting a favourable treatment response. Analyses of paired samples found that FLOT chemotherapy also results in increased expression of CD4⁺ and CD8⁺ tumour infiltrating lymphocytes (Paired Wilcoxon, P = 0.002 and P = 0.008, respectively). Our power analysis suggests future study requires at least 35 patients in each treatment response group for CD8 and Galectin-3 molecules, whereas 80 patients in each treatment response group are required to assess CD4 and E-cadherin biomarkers.

CONCLUSION

We demonstrate that an elevated CD4⁺/CD8⁺ Ratio is a promising IHC-based biomarker to predict favourable treatment response to FLOT neoadjuvant chemotherapy in locally advanced gastric cancer.

Bioinformatics Analysis and Structure of Gastric Cancer Prognosis Model Based on Lipid Metabolism and Immune Microenvironment

OBJECTIVES

The reprogramming of lipid metabolism is a new trait of cancers. However, the role of lipid metabolism in the tumor immune microenvironment (TIME) and the prognosis of gastric cancer remains unclear.

METHODS

Consensus clustering was applied to identify novel subgroups. ESTIMATE, TIMER, and MCPcounter algorithms were used to determine the TIME of the subgroups. The underlying mechanisms were elucidated using functional analysis. The prognostic model was established using the LASSO algorithm and multivariate Cox regression analysis.

RESULTS

Three molecular subgroups with significantly different survival were identified. The subgroup with relatively low lipid metabolic expression had a lower immune score and immune cells. The differentially expressed genes (DEGs) were concentrated in immune biological processes and cell migration via GO and KEGG analyses. GSEA analysis showed that the subgroups were mainly enriched in arachidonic acid metabolism. Gastric cancer survival can be predicted using risk models based on lipid metabolism genes.

CONCLUSIONS

The TIME of gastric cancer patients is related to the expression of lipid metabolism genes and could be used to predict cancer prognosis accurately.

Upregulated LINC00922 Promotes Epithelial-Mesenchymal Transition and Indicates a Dismal Prognosis in Gastric Cancer

BACKGROUND

LINC00922 has been found to promote epithelial-mesenchymal transition (EMT) in a variety of tumors. But its functions in gastric cancer (GC) remain unclear. We attempt to investigate the correlation between LINC00922 and GC via bioinformatics analysis, in vitro and in vivo experiments.

METHODS

TCGA and GTEx databases were utilized to obtain the RNAseq and clinical data of GC, and then, identified the correlation of LINC00922 with patients' clinicopathological characteristics and prognosis. GSEA and GO/KEGG enrichment analyses were performed to explore the potential functions or signaling pathways that LINC00922 participated in GC. Infiltration levels of immune cells were employed by ssGSEA algorithm, and then Wilcoxon rank sum test was applied to analyze their correlations with LINC00922. Scratch and transwell assays were conducted to detect the invasion and migration abilities of GC cells. Western blot was performed to explore the expression level of EMT-related proteins. Furthermore, we constructed the xenograft tumor model and metastatic tumor model in nude mice to explore the effect of LINC00922 downregulating on metastasis of GC cells in vivo.

RESULTS

Compared with normal tissues, LINC00922 was highly expressed in GC tissues and positively correlated with poor prognosis. The correlation existed between LINC00922 and immune infiltration in GC. Downregulation of LINC00922 inhibited the EMT process of GC cells. In addition, both in vitro and in vivo experiments showed that LINC00922 affects the invasion and migration abilities of GC.

CONCLUSIONS

LINC00922 promotes the migration, invasion, and EMT in GC and has the potential to be used as a prognostic biomarker and therapeutic target for GC.