Genomic analysis and clinical implications of immune cell infiltration in gastric cancer

Tumor and Peritoneum-Associated Macrophage Gene Signature as a Novel Molecular Biomarker in Gastric Cancer

A spectrum of immune states resulting from tumor resident macrophages and T-lymphocytes in the solid tumor microenvironment correlates with patient outcomes. We hypothesized that in gastric cancer (GC), macrophages in a polarized immunosuppressive transcriptional state would be prognostic of poor survival. We derived transcriptomic signatures for M2 (M2TS, MRC1; MS4A4A; CD36; CCL13; CCL18; CCL23; SLC38A6; FGL2; FN1; MAF) and M1 (M1TS, CCR7; IL2RA; CXCL11; CCL19; CXCL10; PLA1A; PTX3) macrophages, and cytolytic T-lymphocytes (CTLTS, GZMA; GZMB; GZMH; GZMM; PRF1). Primary GC in a TCGA stomach cancer dataset was evaluated for signature expressions, and a log-rank test determined overall survival (OS) and the disease-free interval (DFI). In 341 TCGA GC entries, high M2TS expression was associated with histological types and later stages. Low M2TS expression was associated with significantly better 5-year OS and DFI. We validated M2TS in prospectively collected peritoneal fluid of a GC patient cohort (n = 28). Single-cell RNA sequencing was used for signature expression in CD68+CD163+ cells and the log-rank test compared OS. GC patients with high M2TS in CD68+CD163+ cells in their peritoneal fluid had significantly worse OS than those with low expression. Multivariate analyses confirmed M2TS was significantly and independently associated with survival. As an independent predictor of poor survival, M2TS may be prognostic in primary tumors and peritoneal fluid of GC patients.

Biological Clock Genes are Crucial and Promising Biomarkers for the Therapeutic Targets and Prognostic Assessment in Gastric Cancer

BACKGROUND

Gastric cancer is one of the major public health problems worldwide. Circadian rhythm disturbances driven by circadian clock genes play a role in the development of cancer. However, whether circadian clock genes can serve as potential therapeutic targets and prognostic biomarkers for gastric cancer remains elusive.

METHODS

In this study, we comprehensively analyzed the potential relationship between circadian clock genes and gastric cancer using online bioinformatics databases such as GEPIA, cBioPortal, STRING, GeneMANIA, Metascape, TIMER, TRRUST, and GEDS.

RESULTS

Biological clock genes are expressed differently in human tumors. Compared with normal tissues, only PER1, CLOCK, and TIMELESS expression differences were statistically significant in gastric cancer (p < 0.05). PER1 (p = 0.0169) and CLOCK (p = 0.0414) were associated with gastric cancer pathological stage (p < 0.05). Gastric cancer patients with high expression of PER1 (p = 0.0028) and NR1D1 (p = 0.016) had longer overall survival, while those with high expression of PER1 (p = 0.042) and NR1D1 (p = 0.016) had longer disease-free survival. The main function of the biological clock gene is related to the circadian rhythms and melatonin metabolism and effects. CLOCK, NPAS2, and KAT2B were key transcription factors for circadian clock genes. In addition, we also found important correlations between circadian clock genes and various immune cells in the gastric cancer microenvironment.

CONCLUSIONS

This study may establish a new gastric cancer prognostic indicator based on the biological clock gene and develop new drugs for the treatment of gastric cancer using biological clock gene targets.

CGB5, INHBA and TRAJ19 Hold Prognostic Potential as Immune Genes for Patients with Gastric Cancer

BACKGROUND

Gastric cancer (GC) seriously threatens people's health and life quality worldwide.

AIM

The current study sought to explore prognostic immune genes and their regulatory network in GC.

METHODS

First, expression data in GC and normal samples were analyzed based on bioinformatics analysis. Immune-related genes were identified and confirmed with univariate/multivariate Cox analysis and receiver-operating characteristic curve. The upstream transcription factors of immune genes were subsequently predicted, and their regulatory network was constructed. GC and adjacent normal tissues were obtained from 76 patients with GC to determine the expression patterns of immune genes and their correlation with overall prognosis. CD8⁺ T-cell infiltration of patients with high or low risk was detected by means of immunohistochemistry.

RESULTS

Bioinformatics analysis highlighted 3689 differentially expressed genes in GC, including 87 immune genes, 8 of which were significantly associated with patient survival. CGB5 and INHBA were high-risk genes, while TRAJ19 was identified as a low-risk gene, all of which were found to be regulated by 11 different transcription factors. Furthermore, CGB5 and INHBA exhibited negative correlation with the prognosis of GC patients; however, TRAJ19 was positively correlated with GC patient prognosis. The incidence of lymph node metastasis was higher, the pathological stage was advanced and the infiltrated CD8⁺ T cells were fewer in the high-risk GC group.

CONCLUSIONS

Overall, our findings identified the key roles of CGB5, INHBA and TRAJ19 in prognosis GC patients, serving as an important gene set for prognostic prediction.

Non-coding ribonucleic acid-mediated CAMSAP1 upregulation leads to poor prognosis with suppressed immune infiltration in liver hepatocellular carcinoma

Liver hepatocellular carcinoma (LIHC) is well-known for its unfavorable prognosis due to the lack of reliable diagnostic and prognostic biomarkers. Calmodulin-regulated spectrin-associated protein 1 (CAMSAP1) is a non-centrosomal microtubule minus-end binding protein that regulates microtubule dynamics. This study aims to investigate the specific role and mechanisms of CAMSAP1 in LIHC. We performed systematical analyses of CAMSAP1 and demonstrated that differential expression of CAMSAP1 is associated with genetic alteration and DNA methylation, and serves as a potential diagnostic and prognostic biomarker in some cancers, especially LIHC. Further evidence suggested that CAMSAP1 overexpression leads to adverse clinical outcomes in advanced LIHC. Moreover, the AC145207.5/LINC01748-miR-101–3p axis is specifically responsible for CAMSAP1 overexpression in LIHC. In addition to the previously reported functions in the cell cycle and regulation of actin cytoskeleton, CAMSAP1-related genes are enriched in cancer- and immune-associated pathways. As expected, CAMSAP1-associated LIHC is infiltrated in the suppressed immune microenvironment. Specifically, except for immune cell infiltration, it is significantly positively correlated with immune checkpoint genes, especially CD274 (PD-L1), and cancer-associated fibroblasts. Prediction of immune checkpoint blockade therapy suggests that these patients may benefit from therapy. Our study is the first to demonstrate that besides genetic alteration and DNA methylation, AC145207.5/LINC01748-miR-101-3p-mediated CAMSAP1 upregulation in advanced LIHC leads to poor prognosis with suppressed immune infiltration, representing a potential diagnostic and prognostic biomarker as well as a promising immunotherapy target for LIHC.

Identifies microtubule-binding protein CSPP1 as a novel cancer biomarker associated with ferroptosis and tumor microenvironment

Centrosome and spindle pole-associated protein (CSPP1) is a centrosome and microtubule-binding protein that plays a role in cell cycle-dependent cytoskeleton organization and cilia formation. Previous studies have suggested that CSPP1 plays a role in tumorigenesis; however, no pan-cancer analysis has been performed. This study systematically investigates the expression of CSPP1 and its potential clinical outcomes associated with diagnosis, prognosis, and therapy. CSPP1 is widely present in tissues and cells and its aberrant expression serves as a diagnostic biomarker for cancer. CSPP1 dysregulation is driven by multi-dimensional mechanisms involving genetic alterations, DNA methylation, and miRNAs. Phosphorylation of CSPP1 at specific sites may play a role in tumorigenesis. In addition, CSPP1 correlates with clinical features and outcomes in multiple cancers. Take brain low-grade gliomas (LGG) with a poor prognosis as an example, functional enrichment analysis implies that CSPP1 may play a role in ferroptosis and tumor microenvironment (TME), including regulating epithelial-mesenchymal transition, stromal response, and immune response. Further analysis confirms that CSPP1 dysregulates ferroptosis in LGG and other cancers, making it possible for ferroptosis-based drugs to be used in the treatment of these cancers. Importantly, CSPP1-associated tumors are infiltrated in different TMEs, rendering immune checkpoint blockade therapy beneficial for these cancer patients. Our study is the first to demonstrate that CSPP1 is a potential diagnostic and prognostic biomarker associated with ferroptosis and TME, providing a new target for drug therapy and immunotherapy in specific cancers.

A Multiomics Profiling Based on Online Database Revealed Prognostic Biomarkers of BLCA

Background

Bladder cancer (BLCA) is one of the most common urological malignancies globally, posing a severe threat to public health. In combination with protein-protein interaction (PPI) network analysis of proteomics, Gene Set Variation Analysis (GSVA) and “CancerSubtypes” package of R software for transcriptomics can help identify biomarkers related to BLCA prognosis. This will have significant implications for prevention and treatment.

Method

BLCA data were downloaded from The Cancer Genome Atlas (TCGA) database and GEO database (GSE13507). GSVA analysis converted the gene expression matrix to the gene set expression matrix. “CancerSubtypes” classified patients into three subtypes and established a prognostic model based on differentially expressed gene sets (DEGSs) among the three subtypes. For genes from prognosis-related DEGSs, functional and pathway enrichment analyses and PPI network analysis were carried out. The Human Protein Atlas (HPA) database was used for validation. Finally, the proportion of tumor-infiltrating immune cells (TIICs) was determined using the CIBERSORT algorithm.

Results

In total, 414 tumor samples and 19 adjacent-tumor samples were obtained from TCGA, with 145 samples belonging to subtype A, 126 samples belonging to subtype B, and 136 samples belonging to subtype C. Then, we identified 83 DEGSs and constituted a prognostic signature with two of them: “GSE1460_CD4_THYMOCYTE_VS_THYMIC_STROMAL_CELL_DN” and “MODULE_253.” Finally, five subnets of two PPI networks were established, and nine core proteins were obtained: CDH2, COL1A1, EIF2S2, PSMA3, NAA10, DNM1L, TUBA4A, KIF11, and KIF23. The HPA database confirmed the expression of the nine core proteins in BLCA tissues. Furthermore, EIF2S2, PSMA3, DNM1L, and TUBA4A could be novel BLCA prognostic biomarkers.

Conclusions

In this study, we discovered two gene sets linked to BLCA prognosis. PPI analysis confirmed the network's core proteins, and several newly discovered biomarkers of BLCA prognosis were identified.

An immune-related nomogram model that predicts the overall survival of patients with lung adenocarcinoma

Background

Lung adenocarcinoma accounts for approximately 40% of all primary lung cancers; however, the mortality rates remain high. Successfully predicting progression and overall (OS) time will provide clinicians with more options to manage this disease.

Methods

We analyzed RNA sequencing data from 510 cases of lung adenocarcinoma from The Cancer Genome Atlas database using CIBERSORT, ImmuCellAI, and ESTIMATE algorithms. Through these data we constructed 6 immune subtypes and then compared the difference of OS, immune infiltration level and gene expression between these immune subtypes. Also, all the subtypes and immune cells infiltration level were used to evaluate the relationship with prognosis and we introduced lasso-cox method to constructe an immune-related prognosis model. Finally we validated this model in another independent cohort.

Results

The C3 immune subtype of lung adenocarcinoma exhibited longer survival, whereas the C1 subtype was associated with a higher mutation rate of MUC17 and FLG genes compared with other subtypes. A multifactorial correlation analysis revealed that immune cell infiltration was closely associated with overall survival. Using data from 510 cases, we constructed a nomogram prediction model composed of clinicopathologic factors and immune signatures. This model produced a C-index of 0.73 and achieved a C-index of 0.844 using a validation set.

Conclusions

Through this study we constructed an immune related prognosis model to instruct lung adenocarcinoma’s OS and validated its value in another independent cohost. These results will be useful in guiding treatment for lung adenocarcinoma based on tumor immune profiles.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-01902-6.

Enhancer RNA SLIT2 Inhibits Bone Metastasis of Breast Cancer Through Regulating P38 MAPK/c-Fos Signaling Pathway

BACKGROUND

Breast cancer (BRCA) is the most common cancer in women, while the bones are one of the most common sites of metastasis. Although new diagnostic methods or radiation or chemotherapies and targeted therapies have made huge advances, the occurrence of bone metastasis is also linked with poorer survival. Enhancer RNAs (eRNAs) have been demonstrated to participate in the progression of tumorigenesis and metastasis. However, the role of eRNAs in BRCA bone metastasis remains largely unclear.

METHOD

Gene expression profiling of 1,211 primary BRCA and 17 bone metastases samples were retrieved from The Cancer Genome Atlas (TCGA) database, and the significant prognostic eRNAs were identified by Cox regression and least absolute shrinkage and selection operator (LASSO) regression. The acceptable accuracy and discrimination of the nomogram were indicated by the receiver operating characteristic (ROC) and the calibration curves. Then target genes of eRNA, immune cell percentage by CIBERSORT analysis, immune genes by single-sample gene set enrichment analysis (ssGSEA), hallmark of cancer signaling pathway by gene set variation analysis (GSVA), and reverse phase protein array (RPPA) protein chip were used to build a co-expression regulation network and identified the key eRNAs in bone metastasis of BRCA. Finally, Cell Counting Kit-8 (CCK8) assay, cell cycle assay, and transwell assay were used to study changes in cell proliferation, migration, and invasiveness. Immunoprecipitation assay and Western blotting were used to test the interaction and the regulation signaling pathways.

RESULTS

The 27 hub eRNAs were selected, and a survival-related linear risk assessment model with a relatively high accuracy (area under curve (AUC): 0.726) was constructed. In addition, seven immune-related eRNAs (SLIT2, CLEC3B, LBPL1, FRY, RASGEF1B, DST, and ITIH5) as prognostic signatures for bone metastasis of BRCA were further confirmed by LASSO and multivariate Cox regression and CIBERSORT analysis. Finally, in vitro assay demonstrated that overexpression of SLIT2 reduced proliferation and metastasis in BRCA cells. Using high-throughput co-expression regulation network, we identified that SLIT2 may regulating P38 MAPK/c-Fos signaling pathway to promote the effects of metastasis.

CONCLUSION

Based on the co-expression network for bone metastasis of BRCA, we screened key eRNAs to explore a prognostic model in predicting the bone metastasis by bioinformatics analysis. Besides, we identified the potential regulatory signaling pathway of SLIT2 in BRCA bone metastasis, which provides a promising therapeutic strategy for metastasis of BRCA.

Effect of LAMA4 on Prognosis and Its Correlation with Immune Infiltration in Gastric Cancer

Background

Laminin alpha 4 (LAMA4) is widely distributed in the basement membranes of various tissues. It can regulate cancer cell proliferation and migration. We investigated the effects of LAMA4 in gastric cancer (GC).

Methods

LAMA4 expression patterns were analyzed in GC using the Gene Expression Omnibus (GEO), Gene Expression Profiling Interactive Analysis (GEPIA), and UALCAN. Correlations between LAMA4 expression and clinicopathological characteristics were evaluated using data from The Cancer Genome Atlas (TCGA). The survival analysis was examined using the Kaplan-Meier plotter and GEPIA and ascertained by multivariate Cox analysis. Genetic alterations and DNA methylation of LAMA4 were analyzed using cBioPortal and MethSurv. LinkedOmics was applied to identify coexpressed genes of LAMA4. The association between LAMA4 and infiltration of immune cells was explored using Tumor Immune Estimation Resource (TIMER) and GEPIA.

Results

LAMA4 was highly expressed in GC, and its upregulation significantly correlated with T classification (P = 0.040). LAMA4 expression was an independent risk factor for overall survival (OS, P = 0.033). Patients with genetic alterations of LAMA4 showed a significantly better disease-free survival (DFS, P = 0.022). Ten CpG sites of LAMA4 were significantly associated with prognosis in GC. The functions of LAMA4 and coexpression genes were mainly involved in extracellular matrix (ECM) receptor interaction. LAMA4 expression significantly correlated with infiltration of macrophages (P < 0.001), CD4+ T cells (P < 0.001), and dendritic cells (P < 0.001). Furthermore, LAMA4 expression was significantly associated with markers of M2 and tumor-associated macrophages (TAMs).

Conclusion

LAMA4 expression was linked to GC prognosis and immune cell infiltration, indicating its potential use as a prognostic biomarker and therapeutic target.

A Non-canonical Wnt Signature Correlates With Lower Survival in Gastric Cancer

Genetic evidence suggests a role for the Wnt/β-catenin pathway in gastric cancer. However, Wnt5a, regarded as a prototypical non-canonical Wnt ligand, has also been extensively associated with this disease. Therefore, the roles of the Wnt signaling pathway in gastric cancer initiation and progression, and particularly the precise mechanisms by which the non-canonical Wnt pathway might promote the development and progression of gastric cancer, are not entirely well understood. This article analyzes publicly available gene and protein expression data and reveals the existence of a WNT5A/FZD2/FZD7/ROR2 signature, which correlates with tumor-infiltrating and mesenchymal cell marker expression. High expression of FZD7 and ROR2 correlates with a shared gene and protein expression profile, which in turn correlates with poor prognosis. In summary, the findings presented in this article provide an updated view of the relative contributions of the Wnt/β-catenin and non-canonical Wnt pathways in gastric cancer.

Development and validation of an immune-related gene prognostic model for stomach adenocarcinoma

Purpose: Stomach adenocarcinoma (STAD) is one of the most common malignant tumors, and its occurrence and prognosis are closely related to inflammation. The aim of the present study was to identify gene signatures and construct an immune-related gene (IRG) prognostic model in STAD using bioinformatics analysis.

Methods: RNA sequencing data from healthy samples and samples with STAD, IRGs, and transcription factors were analyzed. The hub IRGs were identified using univariate and multivariate Cox regression analyses. Using the hub IRGs, we constructed an IRG prognostic model. The relationships between IRG prognostic models and clinical data were tested.

Results: A total of 289 differentially expressed IRGs and 20 prognostic IRGs were screened with a threshold of P<0.05. Through multivariate stepwise Cox regression analysis, we developed a prognostic model based on seven IRGs. The prognostic model was validated using a GEO dataset (GSE 84437). The IRGs were significantly correlated with the clinical outcomes (age, histological grade, N, and M stage) of STAD patients. The infiltration abundances of dendritic cells and macrophages were higher in the high-risk group than in the low-risk group.

Conclusions: Our results provide novel insights into the pathogenesis of STAD. An IRG prognostic model based on seven IRGs exhibited the predictive value, and have potential application value in clinical decision-making and individualized treatment.