Identifying Predictive Factors of Recurrence after Radical Resection in Gastric Cancer by RNA Immune-oncology Panel

An immune-related gene prognostic prediction risk model for neoadjuvant chemoradiotherapy in rectal cancer using artificial intelligence

Background

This study aimed to establish and validate a prognostic model based on immune-related genes (IRGPM) for predicting disease-free survival (DFS) in patients with locally advanced rectal cancer (LARC) undergoing neoadjuvant chemoradiotherapy, and to elucidate the immune profiles associated with different prognostic outcomes.

Methods

Transcriptomic and clinical data were sourced from the Gene Expression Omnibus (GEO) database and the West China Hospital database. We focused on genes from the RNA immune-oncology panel. The elastic net approach was employed to pinpoint immune-related genes significantly impacting DFS. We developed the IRGPM for rectal cancer using the random forest technique. Based on the IRGPM, we calculated prognostic risk scores to categorize patients into high-risk and low-risk groups. Comparative analysis of immune characteristics between these groups was conducted.

Results

In this study, 407 LARC samples were analyzed. The elastic net identified a signature of 20 immune-related genes, forming the basis of the IRGPM. Kaplan-Meier survival analysis revealed a lower 5-year DFS in the high-risk group compared to the low-risk group. The receiver operating characteristic (ROC) curve affirmed the model's robust predictive capability. Validation of the model was performed in the GSE190826 cohort and our institution's cohort. Gene expression differences between high-risk and low-risk groups predominantly related to cytokine-cytokine receptor interactions. Notably, the low-risk group exhibited higher immune scores. Further analysis indicated a greater presence of activated B cells, activated CD8 T cells, central memory CD8 T cells, macrophages, T follicular helper cells, and type 2 helper cells in the low-risk group. Additionally, immune checkpoint analysis revealed elevated PDCD1 expression in the low-risk group.

Conclusions

The IRGPM, developed through random forest and elastic net methodologies, demonstrates potential in distinguishing DFS among LARC patients receiving standard treatment. Notably, the low-risk group, as defined by the IRGPM, showed enhanced activation of adaptive immune responses within the tumor microenvironment.

Involvement of CXC chemokines (CXCL1-CXCL17) in gastric cancer: Prognosis and therapeutic molecules

Gastric cancer (GC) is the fifth-most prevalent and second-most deadly cancer worldwide. Due to the late onset of symptoms, GC is frequently treated at a mature stage. In order to improve the diagnostic and clinical decision-making processes, it is necessary to establish more specific and sensitive indicators valuable in the early detection of the disease whenever a cancer is asymptomatic. In this work, we gathered information about CXC chemokines and GC by using scientific search engines including Google Scholar, PubMed, SciFinder, and Web of Science. Researchers believe that GC chemokines, small proteins, class CXC chemokines, and chemokine receptors promote GC inflammation, initiation, and progression by facilitating angiogenesis, tumor transformation, invasion, survival, metastatic spread, host response safeguards, and inter-cell interaction. With our absolute best professionalism, the role of CXC chemokines and their respective receptors in GC diagnosis and prognosis has not been fully explained. This review article updates the general characteristics of CXC chemokines, their unique receptors, their function in the pathological process of GC, and their potential application as possible indicators for GC. Although there have only recently been a few studies focusing on the therapeutic efficacy of CXC chemokine inhibitors in GC, growing experimental evidence points to the inhibition of CXC chemokines as a promising targeted therapy. Therefore, further translational studies are warranted to determine whether specific antagonists or antibodies designed to target CXC chemokines alone or in combination with chemotherapy are useful for diagnosing advanced GC.

Correlation between the expressions of metastasis-associated factor-1 in colon cancer and vacuolar ATP synthase

BACKGROUND

Clinical prognosis often worsens due to high recurrence rates following radical surgery for colon cancer. The examination of high-risk recurrence factors post-surgery provides critical insights for disease evaluation and treatment planning.

AIM

To explore the relationship between metastasis-associated factor-1 in colon cancer (MACC1) and vacuolar ATP synthase (V-ATPase) expression in colon cancer tissues, and recurrence rate in patients undergoing radical colon cancer surgery.

METHODS

We selected 104 patients treated with radical colon cancer surgery at our hospital from January 2018 to June 2021. Immunohistochemical staining was utilized to assess the expression levels of MACC1 and V-ATPase in these patients.

RESULTS

The rates of MACC1 and V-ATPase positivity were 64.42% and 67.31%, respectively, in colon cancer tissues, which were significantly higher than in paracancerous tissues (P < 0.05). Among patients with TNM stage III, medium to low differentiation, and lymph node metastasis, the positive rates of MACC1 and V-ATPase were significantly elevated in comparison to patients with TNM stage I-II, high differentiation, and no lymph node metastasis (P < 0.05). The rate of MACC1 positivity was 76.67% in patients with tumor diameters > 5 cm, notably higher than in patients with tumor diameters ≤ 5 cm (P < 0.05). We observed a positive correlation between MACC1 and V-ATPase expression (rs = 0.797, P < 0.05). The positive rates of MACC1 and V-ATPase were significantly higher in patients with recurrence compared to those without (P < 0.05). Logistic regression analysis revealed TNM stage, lymph node metastasis, MACC1 expression, and V-ATPase expression as risk factors for postoperative colon cancer recurrence (OR = 6.322, 3.435, 2.683, and 2.421; P < 0.05).

CONCLUSION

The upregulated expression of MACC1 and V-ATPase in colon cancer patients appears to correlate with clinicopathological features and post-radical surgery recurrence.

A novel prognostic index of stomach adenocarcinoma based on immunogenomic landscape analysis and immunotherapy options

Stomach adenocarcinoma (STAD) is one of the most common malignant tumors worldwide. In this study, we attempted to construct a valid immune-associated gene prognostic index risk model that can predict the survival of patients with STAD and the efficacy of immune checkpoint inhibitors (ICIs) treatment. Transcriptome, clinical, and gene mutational data were obtained from the TCGA database. Immune-related genes were downloaded from the ImmPort and InnateDB databases. A total of 493 immune-related genes were identified to be enriched in functions associated with immune response, as well as in immune and tumor-related pathways. Further, 36 candidate genes related to the overall survival (OS) of STAD were obtained by weighted gene co-expression network analysis (WGCNA). Next, based on a Cox regression analysis, we constructed an immune-associated gene prognostic index (IAGPI) risk model based on eight genes, which was verified using the GEO STAD cohort. The patients were divided into two subsets according to their risk score. Patients in the low-risk group had better OS than those in the high-risk group. In the low-risk group, there were more CD8, activated memory CD4, and follicular helper T cells, and M1 macrophages, whereas monocytes, M2 macrophages, eosinophils, and neutrophils were more abundant in the high-risk group. The patients in the low-risk group were more sensitive to ICIs therapy. The IAGPI risk model can precisely predict the prognosis, reflect the tumor immune microenvironment, and predict the efficacy of ICIs therapy in patients with STAD.

Kinases and therapeutics in pathogen mediated gastric cancer

INTRODUCTION

Many pathogens have coexisted with humans for millennia and can cause chronic inflammation which is the cause of gastritis. Gastric cancer (GC) is associated with 8.8% of cancer related deaths, making it one of the leading causes of cancer related deaths worldwide. This review is intended to give brief information about Helicobacter pylori (H. pylori), Epstein-Barr virus (EBV), human cytomegalovirus (HCMV) role in GC and associated kinases. These organisms can trigger multiple cellular pathways aiming for unnatural cellular proliferation, apoptosis, migration and inflammatory response. Kinases also can activate and deactivate the signalling leading to aforementioned pathways. Therefore, studying kinases is inevitable.

MATERIAL AND METHODS

This review is the comprehensive collection of information from different data sources such as journals, book, book chapters and verified online information.

CONCLUSION

Kinase amplifications could be used as diagnostic, prognostic, and predictive biomarkers in various cancer types. Hence targeting kinase and related signalling molecules could be considered as a potential approach to prevent cancer through these organisms. Here we summarize the brief information about the role of kinases, signalling and their therapeutics in GC concerning H. pylori, EBV and HCMV.

A Novel Overall Survival Prediction Signature Based on Cancer Stem Cell-Related Genes in Osteosarcoma

Background: Osteosarcoma is the most general bone malignancy that mostly affects children and adolescents. Numerous stem cell-related genes have been founded in distinct forms of cancer. This study aimed at identifying a stem cell-related gene model for the expected assessment of the prognosis of osteosarcoma patients.

Methods: We obtained the genes expression data and relevant clinical materials from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. We identified differentially expressed genes (DEGs) from the GEO dataset, whereas prognostic stem cell-related genes were obtained from the TARGET database. Subsequently, univariate, LASSO and multivariate Cox regression analyses were applied to establish the stem cell-related signature. Finally, the prognostic value of the signature was validated in the GEO dataset.

Results: Twenty-five genes were prognostic ferroptosis-related DEGs. Consequently, we identified eight stem cell-related genes as a signature of prognosis of osteosarcoma patients. Then, the Kaplan–Meier (K-M) curve, the AUC value of ROC, and Cox regression analysis verified that the eight stem cell-related gene model were a new and substantial prognostic marker independent of other clinical traits. Moreover, the nomogram on the foundation of risk score and other clinical traits was established for predicting the survival rate of osteosarcoma patients. Biological function analyses displayed that tumor related pathways were affluent.

Conclusion: The expression level of stem cell-related genes offers novel prognostic markers as well as underlying therapeutic targets for the therapy and prevention of osteosarcoma.

An Immune-Related Gene Panel for Preoperative Lymph Node Status Evaluation in Advanced Gastric Cancer

Background and Aim: Gastric cancer (GC) is the common leading cause of cancer-related death worldwide. Immune-related genes (IRGs) may potentially predict lymph node metastasis (LNM). We aimed to develop a preoperative model to predict LNM based on these IRGs. Methods: In this paper, we compared and evaluated three machine learning models to predict LNM based on publicly available gene expression data from TCGA-STAD. The Pearson correlation coefficient (PCC) method was utilized to feature selection according to its relationships with LN status. The performance of the model was assessed using the area under the curve (AUC) and F1 score. Results: The Naive Bayesian model showed better performance and was constructed based on 26 selected gene features, with AUCs of 0.741 in the training set and 0.688 in the test set. The F1 score in the training set and test set was 0.652 and 0.597, respectively. Furthermore, Naive Bayesian model based on 26 IRGs is the first diagnostic tool for the identification of LNM in advanced GC. Conclusion: These results indicate that our new methods have the value of auxiliary diagnosis with promising clinical potential.

Eomes promotes esophageal carcinoma progression by recruiting Treg cells through the CCL20-CCR6 pathway

Eomesodermin (Eomes) is a T‐box transcription factor that drives the differentiation and function of cytotoxic lymphocytes. However, the underlying function and mechanism of Eomes in tumor cells remains elusive. Here, we studied the role of Eomes in human esophageal squamous cell carcinoma (ESCC). Using 2 human ESCC cell lines, we found that Eomes knockdown reduced esophageal cancer cell proliferation and that the esophageal cancer cell cycle was blocked in the G2/M phase. Mechanistically, we identified CCL20 as the main downstream target of Eomes. Furthermore, we found that CCL20 could chemoregulate regulatory T cells (Tregs) through their specific receptor CCR6, then promoting the proliferation of esophageal cancer cells. Eomes knockdown also delayed the growth of human ESCC xenografts in BALB/c nude mice. Importantly, in 133 human ESCC tissues, high Eomes levels were associated with poor clinical prognosis. Overall, our findings suggested that the Eomes‐CCL20‐CCR6 pathway plays a vital role in human ESCC progress. Therefore, targeting this pathway may represent a promising strategy for controlling human ESCC.