Comprehensive Analysis of the Prognostic Value and Immune Function of Immune Checkpoints in Stomach Adenocarcinoma

RPL22L1 is a novel biomarker for prognosis and immune infiltration in lung adenocarcinoma, promoting the growth and metastasis of LUAD cells by inhibiting the MDM2/P53 signaling pathway

The ribosomal protein L22-like1 (RPL22L1) is a constituent of the 60 S ribosomal subunit whose function in lung adenocarcinoma (LUAD) remains ambiguous. This study aims to elucidate the role of RPL22L1 in LUAD through a thorough analysis and experimental validation. Our findings indicate that RPL22L1 exhibits abnormal expression patterns in various cancer types, including LUAD. Moreover, a statistically significant association was observed between elevated levels of RPL22L1 expression in LUAD patients and several clinical parameters, such as pathological stage (p = 0.0083) and gender (p = 0.0038). The high expression of RPL22L1 in LUAD demonstrated a significant association with poorer overall survival (OS) (p = 0.005), progression-free survival (PFS) (p = 0.027), and disease-specific survival (p = 0.015). The expression of RPL22L1 in LUAD (p = 0.005) was identified as an independent prognostic factor. Additionally, RPL22L1 expression in LUAD was found to be correlated with immune infiltration, immune checkpoint genes, TMB/MSI, and mRNAsi. Notably, the expression of RPL22L1 exhibited significant negative correlations with 1-BET-762, Trametinib, and WZ3105 in LUAD. The RPL22L1 gene exhibited up-regulation in multiple individual cells of LUAD, leading to a comparatively shorter PFS in the RPL22L1 variant group as opposed to the RPL22L1 variant-free group in LUAD. Significantly increased expression of RPL22L1 was noted in LUAD cell lines, where it was found to enhance the growth and metastasis of LUAD cells by suppressing the MDM2/P53 signaling pathway. Therefore, RPL22L1 may serve as a promising prognostic biomarker and therapeutic target for patients with LUAD.

A prognostic risk model based on lactate metabolism and transport-related lncRNAs for gastric adenocarcinoma

BACKGROUND

Increased lactate levels and metastasis in tumours are strongly associated with dismal outcomes. But prognostic value of lactate metabolism and transport-related lncRNAs in gastric adenocarcinoma (GA) patients remains unaddressed.

METHODS

Gene expression data of GA were provided by The Cancer Genome Atlas. Lactate metabolism and transport-related gene data were accessed from GSEA. LncRNAs related to lactate metabolism and transport were identified by correlation analysis. A prognostic model was built by regression analysis. Validity of prognostic model was confirmed through survival analysis and receiver operating characteristic (ROC) curve. Immunity of each risk group was evaluated by immune correlation analysis .LncRNA-mRNA network was built by correlation analysis using Cytoscape software.

RESULTS

A 12-gene prognostic model based on lactate metabolism and transport-related lncRNAs was built in GA. Median riskscore was utilized to classify GA samples into high- and low-risk groups. Survival analysis and ROC curves demonstrated validity of prognostic model. Most immune checkpoint molecules and TIDE scores were lower in the low-risk group. LINC01303 and LINC01545 may be the key prognostic factors in patients with GA.

CONCLUSION

This study successfully built a prognostic model of lactate metabolism and transport-related lncRNAs in GA. The findings guide prognostic management of GA patients.

Identification of necroptosis-associated miRNA signature for predicting prognosis and immune landscape in stomach adenocarcinoma

PURPOSE

This study aims to identify the potential necroptosis related genes (NRGs)-associated miRNAs signature and explore the impact on the prognosis of stomach adenocarcinoma (STAD).

METHODS

Employing rigorous methodologies, we utilized univariate Cox, Lasso and multivariate Cox regression analyses to develop a prognostic signature. Kaplan-Meier (K-M) and ROC curves were applied to assess the prognostic value of signature in a training group and an independent test group. Furthermore, we conducted Gene Set Enrichment Analysis (GSEA) for enrichment of tumor-related pathways. The risk score was calculated for each patient based on the expression of miRNAs which were enrolled in the signature. Patients were stratified into high- and low-risk groups. The immune cell infiltration and immunotherapy were compared between the two groups. Finally, the diagnostic potential of the miRNA was explored by RT-qPCR.

RESULTS

We constructed a prognostic model based on 6 NRGs-associated miRNAs. K-M plots underscored superior survival outcomes in the low-risk group. GSEA results revealed the enrichment of several tumor-related pathways in the high-risk group. Notably, CD8+ T cells, Tregs and activated memory CD4+ T cells exhibited negative correlations with the risk score. Additionally, a few immune checkpoint genes, such as CTLA4, PD1 and PD-L1, were significantly upregulated in the low-risk group. Furthermore, the serum expression levels of all these 6 miRNAs were significantly elevated in STAD patients.

CONCLUSIONS

Our study identified a robust risk score derived from a signature of 6 NRGs-associated miRNAs, demonstrating high efficacy for prognosis of STAD. These results not only contributed to our understanding of STAD pathogenesis, but also held promise for potential clinical applications, particularly in the realm of personalized immunotherapy for STAD patients.

IL-15-secreting CAR natural killer cells directed toward the pan-cancer target CD70 eliminate both cancer cells and cancer-associated fibroblasts

BACKGROUND

It remains challenging to obtain positive outcomes with chimeric antigen receptor (CAR)-engineered cell therapies in solid malignancies, like colorectal cancer (CRC) and pancreatic ductal adenocarcinoma (PDAC). A major obstacle is the lack of targetable surface antigens that are not shared by healthy tissues. CD70 emerges as interesting target, due to its stringent expression pattern in healthy tissue and its apparent role in tumor progression in a considerable amount of malignancies. Moreover, CD70 is also expressed on cancer-associated fibroblasts (CAFs), another roadblock for treatment efficacy in CRC and PDAC. We explored the therapeutic potential of CD70 as target for CAR natural killer (NK) cell therapy in CRC, PDAC, focusing on tumor cells and CAFs, and lymphoma.

METHODS

RNA-seq data and immunohistochemical analysis of patient samples were used to explore CD70 expression in CRC and PDAC patients. In addition, CD70-targeting CAR NK cells were developed to assess cytotoxic activity against CD70+ tumor cells and CAFs, and the effect of cytokine stimulation on their efficacy was evaluated. The in vitro functionality of CD70-CAR NK cells was investigated against a panel of tumor and CAF cell lines with varying CD70 expression. Lymphoma-bearing mice were used to validate in vivo potency of CD70-CAR NK cells. Lastly, to consider patient variability, CD70-CAR NK cells were tested on patient-derived organoids containing CAFs.

RESULTS

In this study, we identified CD70 as a target for tumor cells and CAFs in CRC and PDAC patients. Functional evaluation of CD70-directed CAR NK cells indicated that IL-15 stimulation is essential to obtain effective elimination of CD70+ tumor cells and CAFs, and to improve tumor burden and survival of mice bearing CD70+ tumors. Mechanistically, IL-15 stimulation resulted in improved potency of CD70-CAR NK cells by upregulating CAR expression and increasing secretion of pro-inflammatory cytokines, in a mainly autocrine or intracellular manner.

CONCLUSIONS

We disclose CD70 as an attractive target both in hematological and solid tumors. IL-15 armored CAR NK cells act as potent effectors to eliminate these CD70+ cells. They can target both tumor cells and CAFs in patients with CRC and PDAC, and potentially other desmoplastic solid tumors.

ICOSLG acts as an oncogene to promote glycolysis, proliferation, migration, and invasion in gastric cancer cells

Gastric cancer (GC) has emerged as one of the most common malignancies in gastrointestinal system. Inducible T-cell costimulator ligand (ICOSLG) was found to be highly expressed in various cancers, which contributes to disease progression. This study aims to investigate the role of ICOSLG and its potential mechanism of action in dictating the aggressiveness of GC cell. ICOSLG and miR-331-3p expression patterns in cancerous and para-cancerous tissues from GC patients were examined by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The miRNAs targeting ICOSLG were predicted by "miRDB", "starBase," and "TargetScan" databases. The interplay of ICOSLG and miR-331-3p in dictating the aggressiveness and glycolysis of GC cells was investigated by CCK-8 proliferation assay and Transwell migration/invasion assays, as well as the detection of glucose uptake, lactate production and ATP levels. The tumorigenesis of GC cells after ICOSLG silencing was examined in the nude mice. ICOSLG was highly expressed in GC tissues, and GC patients with high ICOSLG expression showed a poorer prognosis than the low-expression group. Further, high ICOSLG level was correlated with more advanced TNM stages, more lymph-node metastases, and poorer tumor differentiation. ICOSLG knockdown inhibited the proliferation, migration, invasion and tumor formation of GC cells, which was concomitant with reduced glucose consumption, lactate production, and ATP levels. In contrast, ICOSLG overexpression enhanced the aggressiveness of GC cells, and this effect was abrogated after the treatment with glycolysis inhibitor. We further found that miR-331-3p was a negative regulator of ICOSLG4, and miR-331-3p overexpression reduced ICOSLG4 expression and suppressed the aggressive phenotype induced by ICOSLG4 in GC cells. Together, these findings indicate that ICOSLG4, as an oncogene, is upregulated to promote glycolysis and the malignant phenotype in GC cells. miR-331-3p, which is downregulated in GC tissues, functions as a negative regulator of ICOSLG4. Targeting miR-331-3p/ICOSLG4 axis could potentially suppress GC progression.

A five ferroptosis-related genes risk score for prognostic prediction of osteosarcoma

BACKGROUND

Osteosarcoma (OS) is the most common bone cancer in adolescents, and has a high propensity to metastasize. Ferroptosis is a unique modality of cell death, driving the metastasis of cancer cells. Identifying ferroptosis-related genes (FRGs) as prognostic factors will be critical to predict the outcomes of OS. This study aimed to explore the prognostic value of FRGs in OS and build a prognostic model to indirectly improve OS patients' outcomes.

METHODS

OS data were downloaded from the TARGET database and 2 Gene Expression Omnibus datasets. Univariate Cox regression was conducted to assess FRGs. A risk score model basing on 5 FRGs was constructed via LASSO-Cox regression. Multivariate Cox regression analysis was used to determine the independent prognostic factors. The Nomogram model was built using independent prognostic factors. The relationship between the risk score and the immune cell infiltration was estimated by CIBERSORT, and the correlation between the risk score and immune checkpoints was also analyzed.

RESULTS

Based on the prognosis-related FRGs, we built a regression model: Risk score = (-0.01382853 × ACSL4) - (0.05371778 × HMOX1) - (0.02434655 × GPX4) - (0.16432810 × PRNP) - (0.15567120 × ATG7). OS patients with high risk score tended to suffer from poor prognosis, validated in 2 Gene Expression Omnibus datasets. The Nomogram model showed the combination of the risk score and the tumour-node-metastasis stage improved predictive effectiveness. The risk score was also related to immune cell infiltration and immune checkpoint expression.

CONCLUSION

The risk score model based on 5 FRGs was a reliable prognostic predictive indicator for OS patients.

Downregulated PRNP Facilitates Cell Proliferation and Invasion and Has Effect on the Immune Regulation in Ovarian Cancer

Background. Ovarian cancer (OC) seriously threatens women’s life. Ferroptosis plays an essential role in the initiation and development of OC. However, more molecular targets and mechanisms for ferroptosis in OC remain to be further elucidated. Methods. Several OC datasets were integrated in this study and three candidate genes including PRNP were further screened out as the ferroptosis-related gene which was differentially expressed in OC. Then, comprehensive evaluations concerning gene expression, clinical implication, in vitro validation of expression and functional experiments, prediction of downstream molecules and related signal pathways, and immune-modulating function were performed. Results. PRNP was the only downregulated ferroptosis-related gene with prognostic value for OC patients. The decreased mRNA and protein expression was verified in OC tissues and cell lines. PRNP was significantly correlated with cancer stages, primary therapy outcomes, and age in OC patients. Moreover, we found that overexpression of PRNP inhibited the proliferation, migration, and invasion ability of OC cells through in vitro experiments. PRNP was enriched to the Ras signaling pathway. PRNP expression was positively correlated with the infiltration of immune cells, such as mast cells, T effector memory cells, plasmacytoid DC cells, NK cells, and eosinophils. In addition, the association of PRNP with other immune signatures was also found. Conclusion. This study demonstrated for the first time showed that ferroptosis-related gene PRNP exerted a tumor suppressive role in OC and the aberrant expression and function of PRNP making it a potential novel biomarker for OC diagnosis, prognosis, and response to immunotherapies.

Development of a prognostic metabolic signature in stomach adenocarcinoma

PURPOSE

The growth and aggressiveness of Stomach adenocarcinoma (STAD) is significantly affected by basic metabolic changes. This study aimed to identify metabolic gene prognostic signatures in STAD.

METHODS

An integrative analysis of datasets from the Cancer Genome Atlas and Gene Expression Omnibus was performed. A metabolic gene prognostic signature was developed using univariable Cox regression and Kaplan-Meier survival analysis. A nomogram model was developed to predict the prognosis of STAD patients. Finally, Gene Set Enrichment Analysis (GESA) was used to explore the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways significantly associated with the risk grouping.

RESULTS

A total of 327 metabolism-related differentially expressed genes were identified. Three subtypes of STAD were identified and nine immune cell types, including memory B cell, resting and activated CD4+ memory T cells, were significantly different among the three subgroups. A risk score model including nine survival-related genes which could separate high-risk patients from low-risk patients was developed. The prognosis of STAD patients likely benefited from lower expression levels of genes, including ABCG4, ABCA6, GPX8, KYNU, ST8SIA5, and CYP19A1. Age, radiation therapy, tumor recurrence, and risk score model status were found to be independent risk factors for STAD and were used for developing a nomogram. Nine KEGG pathways, including spliceosome, pentose phosphate pathway, and citrate TCA cycle were significantly enriched in GESA.

CONCLUSION

We propose a metabolic gene signature and a nomogram for STAD which might be used for predicting the survival of STAD patients and exploring prognostic markers.