Prognostic Impact of Immune-Related Gene Expression in Preoperative Peripheral Blood from Gastric Cancer Patients

Measurement of soluble PD-1 and soluble PD-L1 as well as PD-L1 and PD-1 from perioperative patients with gastric carcinoma

BACKGROUND

Till now, no experiment has been performed to detect programmed death ligand 1 (PD-L1)/programmed death 1 (PD-1), soluble PD-L1/soluble PD-1 simultaneously in perioperative patients of gastric carcinoma. Our experiment aims at determining the clinical significance and possible mechanism of soluble PD-L1/soluble PD-1 in gastric carcinoma.

METHODS

Thirty patients undergone gastrectomy were selected as the experimental group. Tissue's programmed death ligand 1 and peripheral programmed death 1 were detected using immunofluorescence and flow cytometry. Soluble PD-L1 and soluble PD-1 were detected using enzyme-linked immunosorbent assay.

RESULTS

First, preoperative programmed death 1 was higher than control group and decreased to normal post-operatively. Preoperatively ,elevated levels of programmed death 1 on cluster of differentiation (CD)4 T cells indicated less lymphatic metastasis (P < 0.01) and small tumor volume (P < 0.01); elevated programmed death 1 of CD8 T cells indicated big tumor volume (P < 0.01) and well histological differentiation (P < 0.01). Second, preoperative soluble PD-L1 and soluble PD-1 are lower than in control group. Post-operatively, the soluble PD-1 rose to normal, but the soluble PD-L1 showed no change. Third, programmed death ligand 1 can be observed in carcinoma tissue. Fourth, the area under the curve of soluble PD-1 (0.675) for diagnosis was worse than that of soluble PD-L1 (0.885). Kaplan-Meier analysis showed that soluble PD-1 < 245.26 pg/ml in post-operative serum predicted a poor prognosis (overall survival percentage: 60%) at 2 years (P < 0.05). Multivariate analysis revealed that carcinoembryonic antigen (>5 ng/l) and soluble PD-1 after gastrectomy (>245.26 pg/ml) were independent prognostic factors for overall survival (hazard ratio: 20.812, 95% confidence interval: 1.217-355.916, P = 0.036; hazard ratio: 0.028, 95% confidence interval: 0.001-0.786, P = 0.036, respectively).

CONCLUSIONS

We propose that soluble PD-1 combined with programmed death ligand 1 are effective not only in protecting T cells from the adhesion by programmed death ligand 1 but also in preventing the occurrence and the development of tumor as well. Through multivariate analysis, we found that soluble PD-1 was an independent protective factor for post-operative prognosis of gastric carcinoma patients, which indirectly verified the vital function of soluble PD-1. Soluble PD-1 might be promising predictive biomarkers for the diagnosis and prognosis of gastric carcinoma patients.

Expression of Immune Checkpoints in Malignant Tumors: Therapy Targets and Biomarkers for the Gastric Cancer Prognosis

To increase the effectiveness of anticancer therapy based on immune checkpoint (IC) inhibition, some ICs are being investigated in addition to those used in clinic. We reviewed data on the relationship between PD-L1, B7-H3, B7-H4, IDO1, Galectin-3 and -9, CEACAM1, CD155, Siglec-15 and ADAM17 expression with cancer development in complex with the results of clinical trials on their inhibition. Increased expression of the most studied ICs—PD-L1, B7-H3, and B7-H4—is associated with poor survival; their inhibition is clinically significant. Expression of IDO1, CD155, and ADAM17 is also associated with poor survival, including gastric cancer (GC). The available data indicate that CD155 and ADAM17 are promising targets for immune therapy. However, the clinical trials of anti-IDO1 antibodies have been unsatisfactory. Expression of Galectin-3 and -9, CEACAM1 and Siglec-15 demonstrates a contradictory relationship with patient survival. The lack of satisfactory results of these IC inhibitor clinical trials additionally indicates the complex nature of their functioning. In conclusion, in many cases it is important to analyze the expression of other participants of the immune response besides target IC. The PD-L1, B7-H3, B7-H4, IDO1 and ADAM17 may be considered as candidates for prognosis markers for GC patient survival.

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.

Identification of a Novel Immune-Related Prognostic Biomarker and Small-Molecule Drugs in Clear Cell Renal Cell Carcinoma (ccRCC) by a Merged Microarray-Acquired Dataset and TCGA Database

Clear cell renal cell carcinoma (ccRCC) is one of the most common histological subtypes of renal cancer, with a poor prognosis. Our study aimed to identify a biomarker that is significantly associated with ccRCC prognosis and novel immunotherapeutic targets, as well as some novel molecular drugs for ccRCC. Based on the overlap of The Cancer Genome Atlas (TCGA)-Kidney Renal Clear Cell Carcinoma (KIRC) data and the ImmPort database, we obtained 1,292 immune-related genes (IRGs) and constructed a weighed co-expression network based on the IRGs. A total of 39 hub genes were screened out in three modules. CTLA4, which had the highest connectivity degree among the screened genes in a protein–protein interaction network (degree = 24), was selected. Internal validation based on the GEPIA database revealed that patients with a higher expression of CTLA4 had a significantly shorter overall survival time and disease-free survival time. Expression of CTLA4 was also closely correlated with local recurrence, pathologic stage, and immune infiltration level. External validation based on the Oncomine database and merged microarray-acquired dataset validated the mRNA expression level of hub genes. Gene-set enrichment analysis revealed that six KEGG signaling pathways, which were significantly associated with CTLA4, were enriched on immune-related pathways. Further analysis according to the TIMER database demonstrated that CTLA4 expression was positively related to dendritic cells (cor = 0.446, P = 1.32E-23) and negatively associated with tumor purity (cor = −0.267, P = 5.51E-09). Finally, we screened out 293 differentially expressed genes by integrating six datasets from the GEO database. The Connectivity Map (CMap) analysis revealed the strong potential of three small molecule drugs (monensin, quercetin, and fenbufen) for ccRCC treatment. In conclusion, CTLA4 was identified and validated in prognosis of ccRCC. CTLA4 may be a new prognostic biomarker and immunotherapeutic target for ccRCC. Monensin, quercetin, and fenbufen may be novel choices for ccRCC treatment.

A signature of 14 immune-related gene pairs predicts overall survival in gastric cancer

OBJECTIVE

Increasing evidence demonstrates that immune signature plays an important role in the prognosis of gastric cancer (GC). We aimed to develop and validate a robust immune-related gene pair (IRGP) signature for predicting the prognosis of GC patients.

METHODS

RNA-Seq data and corresponding clinical information of GC cohort were downloaded from the TCGA (The Cancer Genome Atlas Program) data portal. GSE84437 and GSE15459 microarray datasets were included as independent external cohorts. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to build the best prognostic signature. All patients were classified into the high immune-risk and low immune-risk groups via the optimal cut-off of the signature scores determined by time-dependent receiver-operating characteristic (ROC) curve analysis. The prognostic role of the signature was measured by a log-rank test and a Cox proportional hazard regression model.

RESULTS

14 immune gene pairs consisting of 25 unique genes were identified to construct the immune prognostic signature. High immune-risk groups showed poor prognosis in the TCGA datasets and GSE84437 datasets as well as in the GSE15459 datasets (all P < 0.001). The 14-IRGP signature was an independent prognostic factor of GC after adjusting for other clinical factors (P < 0.05). Functional analysis revealed that DNA integrity checkpoint, DNA replication, T-cell receptor signaling pathway, and B-cell receptor signaling pathway were enriched in the low immune-risk groups. B cells naive and Monocytes were significantly higher in the high-risk group, and B-cell memory and T-cell CD4 memory activated were significantly higher in the low-risk group. The prognostic signature based on IRGP reflected infiltration by several types of immune cells.

CONCLUSION

The novel proposed clinical-immune signature is a promising biomarker for prediction overall survival in patients with GC and providing new insights into the treatment strategies.

Prognostic Significance of PD-1, PD-L1 and CD8 Gene Expression Levels in Gastric Cancer

INTRODUCTION

Anti-programmed cell death 1 (PD-1) therapies have shown promising clinical activity against gastric cancer (GC). We evaluated the clinical significance of immune-related gene expression in GC tissues to better understand the tumor immune microenvironment.

METHODS

PD-1, PD-1 ligand 1 (PD-L1) and CD8 mRNA levels and clinicopathological factors, including survival, were examined by quantitative RT-PCR in 155 GC patients who underwent surgery. PD-1 and PD-L1 expression in tumor tissue from 24 GC patients was investigated by immunohistochemical analysis.

RESULTS

PD-1, PD-L1 and CD8 mRNA levels were significantly lower in tumor tissue than in normal tissue (p < 0.0001, p < 0.05, and p < 0.0001). GC patients with low PD-1, PD-L1 and CD8 mRNA levels had significantly poorer overall survival (OS) than those with high PD-1, PD-L1 and CD8 mRNA levels, respectively (p < 0.001, p < 0.01 and p < 0.05). Low PD-1, PD-L1 and CD8 mRNA levels were more significantly associated with poor prognosis in undifferentiated-type GC patients than in differentiated-type GC patients (PD-1: differentiated p = 0.0071 vs. undifferentiated p = 0.0024; PD-L1: p = 0.6527 vs. p < 0.0001; CD8: p = 0.4465 vs. p < 0.05). Multivariate analysis showed that lymph node metastasis, peritoneal dissemination, distant metastasis, low PD-1 mRNA levels and low CD8 mRNA levels were independent prognostic factors for worse OS (low PD-1 mRNA level: OR 2.16, 95% CI 1.10-4.58, p < 0.05; low CD8 mRNA level: OR 2.55, 95% CI 1.12-6.90, p < 0.05). PD-1 and PD-L1 mRNA levels in immune cells were significantly associated with PD-1 and PD-L1 protein levels (both p < 0.05), respectively.

CONCLUSIONS

PD-1, PD-L1 and CD8 mRNA levels may reflect antitumor immunity in GC, and low PD-1 and CD8 mRNA levels are potential predictive biomarkers for poor prognosis in GC patients who underwent surgery.

Circulating PD-1 mRNA in Peripheral Blood is a Potential Biomarker for Predicting Survival of Breast Cancer Patients

BACKGROUND

Programmed cell death 1 (PD-1) inhibitors have shown significant therapeutic promise in various cancers. However, the clinical significance of PD-1 expression remains not fully understood. In this study, we evaluated the clinical and prognostic relevance of PD-1 expression in breast cancer (BC).

METHODS

First, we analyzed PD-1 mRNA expression in BC tissues and performed a survival analysis using a dataset from The Cancer Genome Atlas. Next, we measured PD-1 mRNA expression in peripheral blood (PB) in BC patients by quantitative reverse-transcription polymerase chain reaction. We performed a survival analysis and evaluated the association between PD-1 mRNA expression in PB and the clinicopathological features of 372 BC patients who underwent curative resection. Flow cytometry (FCM) analysis was performed to identify PD-1-expressing cells in PB. Finally, we determined whether there was a correlation of PD-1 mRNA expression in PB and tumor tissue.

RESULTS

PD-1 mRNA expression was significantly higher in tumor tissues compared with normal tissues. Decreased PD-1 mRNA expression in tumor tissue was associated with poor overall survival (OS). PD-1 mRNA expression in PB of BC patients was higher than that of healthy volunteers, and increased PD-1 mRNA expression in PB was associated with poor OS. FCM revealed that PD-1 was mostly expressed on T cells in PB, predominantly in CD4⁺ T cells. PD-1 mRNA expression in PB was negatively correlated with PD-1 mRNA expression in tumor tissue.

CONCLUSION

High expression of PD-1 mRNA in preoperative PB could serve as an effective biomarker that indicates poor prognosis in BC.

Targeting Immune-Related Biological Processes in Solid Tumors: We do Need Biomarkers

Immunotherapy has become the standard-of-care in many solid tumors. Despite the significant recent achievements in the diagnosis and treatment of cancer, several issues related to patients’ selection for immunotherapy remain unsolved. Multiple lines of evidence suggest that, in this setting, the vision of a single biomarker is somewhat naïve and imprecise, given that immunotherapy does not follow the rules that we have experienced in the past for targeted therapies. On the other hand, additional immune-related biomarkers that are reliable in real-life clinical practice remain to be identified. Recently, the immune-checkpoint blockade has been approved in the US irrespective of the tumor site of origin. Further histology-agnostic approvals, coupled with with tumor-specific companion diagnostics and guidelines, are expected in this field. In addition, immune-related biomarkers can also have a significant prognostic value. In this review, we provide an overview of the role of these biomarkers and their characterization in the management of lung cancer, melanoma, colorectal cancer, gastric cancer, head and neck cancer, renal cell carcinoma, urothelial cancers, and breast cancer.