The construction and analysis of tumor-infiltrating immune cells and ceRNA networks in metastatic adrenal cortical carcinoma

Removing the association of random gene sets and survival time in cancers with positive random bias using fixed-point gene set

Cancer research aims to identify genes that cause or control disease progression. Although a wide range of gene sets have been published, they are usually in poor agreement with one another. Furthermore, recent findings from a gene-expression cohort of different cancer types, known as positive random bias, showed that sets of genes chosen randomly are significantly associated with survival time much higher than expected. In this study, we propose a method based on Brouwer's fixed-point theorem that employs significantly survival-associated random gene sets and reveals a small fixed-point gene set for cancers with a positive random bias property. These sets significantly correspond to cancer-related pathways with biological relevance for the progression and metastasis of the cancer types they represent. Our findings show that our proposed significant gene sets are biologically related to each cancer type available in the cancer genome atlas with the positive random bias property, and by using these sets, positive random bias is significantly more reduced in comparison with state-of-the-art methods in this field. The random bias property is removed in 8 of these 17 cancer types, and the number of random sets of genes associated with survival time is significantly reduced in the remaining 9 cancers.

Identification of an immune-related gene signature as a prognostic target and the immune microenvironment for adrenocortical carcinoma

BACKGROUND

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy. Even with complete tumor resection and adjuvant therapies, the prognosis of patients with ACC remains unsatisfactory. In the microtumor environment, the impact of a disordered immune system and abnormal immune responses is enormous. To improve treatment, novel prognostic predictors and treatment targets for ACC need to be identified. Hence, credible prognostic biomarkers of immune-associated genes (IRGs) should be explored and developed.

MATERIAL AND METHODS

We downloaded RNA-sequencing data and clinical data from The Cancer Genome Atlas (TCGA) data set, Genotype-Tissue Expression data set, and Gene Expression Omnibus data set. Gene set enrichment analysis (GSEA) was applied to reveal the potential functions of differentially expressed genes.

RESULTS

GSEA indicated an association between ACC and immune-related functions. We obtained 332 IRGs and constructed a prognostic signature on the strength of 3 IRGs (INHBA, HELLS, and HDAC4) in the training cohort. The high-risk group had significantly poorer overall survival than the low-risk group (p < .001). Multivariate Cox regression was performed with the signature as an independent prognostic indicator for ACC. The testing cohort and the entire TCGA ACC cohort were utilized to validate these findings. Moreover, external validation was conducted in the GSE10927 and GSE19750 cohorts. The tumor-infiltrating immune cells analysis indicated that the quantity of T cells, natural killer cells, macrophage cells, myeloid dendritic cells, and mast cells in the immune microenvironment differed between the low-risk and high-risk groups.

CONCLUSION

Our three-IRG prognostic signature and the three IRGs can be used as prognostic indicators and potential immunotherapeutic targets for ACC. Inhibitors of the three novel IRGs might activate immune cells and play a synergistic role in combination therapy with immunotherapy for ACC in the future.

H2AFX might be a prognostic biomarker for hepatocellular carcinoma

BACKGROUND

H2AFX can play a central role in DNA repair, replication, transcription regulation, and chromosomal stability. However, there is little research to explore the expression of H2AFX in cancers. Moreover, the correlation between the expression of H2AFX and tumor immunity, which affects the prognosis of hepatocellular carcinoma (HCC), is not clear. This article aimed to observe the correlation between H2AFX and tumor tissue infiltration biomarkers in HCC and its prognostic potential in HCC.

METHOD

Oncomine and TIMER database were used to assess the expression level of H2AFX mRNA, and GEPIA and Kaplan-Meier databases were used to evaluate its prognostic potential. The TIMER database analyzed the relationship between h2afx expression level and tumor immune cell infiltration markers in liver cancer tissues.

RESULTS

The results showed that H2AFX was overexpressed in tumor tissues than normal tissues in HCC via analysis, and its expression level was correlated with the survival rate of HCC. Moreover, the expression level of H2AFX was related to various immune biomarkers. These results show that overexpression of H2AFX would reflect the poor prognosis of HCC, and these would also reflect that the gene H2AFX can affect the infiltration of HCC immune cells and then play a role in regulating tumor immunity.

CONCLUSION

Our study showed that the gene H2AFX might be a potential poor prognostic biomarker in HCC and might be involved in the infiltration of HCC immune cells.

Therapeutic targeting miR130b counteracts diffuse large B-cell lymphoma progression via OX40/OX40L-mediated interaction with Th17 cells

MicroRNAs (miRNAs) are involved in lymphoma progression by regulating the tumor microenvironment. Serum miR130b is overexpressed in diffuse large B-cell lymphoma (DLBCL), inducing Th17 cell alterations. To further illustrate its biological significance and therapeutic rationale, miR130b was detected by quantitative real-time PCR in the serum samples of 532 newly diagnosed DLBCL patients. The mechanism of miR130b on lymphoma progression and the tumor microenvironment was investigated both in vitro and in vivo. Therapeutic targeting miR130b was also evaluated, including OX40 agonistic antibody and lipid nanoparticles (LNPs)-miR130b antagomir. The results showed that serum miR130b significantly correlated with tumor miR130b and serum interleukin-17, indicating lymphoma relapse and inferior survival of DLBCL patients. MiR130b overexpression altered tumor microenvironment signaling pathways and increased Th17 cell activity. As mechanism of action, miR130b downregulated tumor OX40L expression by directly targeting IFNAR1/p-STAT1 axis, recruiting Th17 cells via OX40/OX40L interaction, thereby promoting immunosuppressive function of Th17 cells. In co-culture systems of B-lymphoma cells with immune cells, miR130b inhibited lymphoma cell autophagy, which could be counteracted by OX40 agonistic antibody and LNPs-miR130b antagomir. In murine xenograft model established with subcutaneous injection of A20 cells, both OX40 agonistic antibody and LNPs-miR130b antagomir remarkably inhibited Th17 cells and retarded miR130b-overexpressing tumor growth. In conclusion, as an oncogenic biomarker of DLBCL, miR130b was related to lymphoma progression through modulating OX40/OX40L-mediated lymphoma cell interaction with Th17 cells, attributing to B-cell lymphoma sensitivity towards OX40 agonistic antibody. Targeting miR130b using LNPs-miR130b antagomir could also be a potential immunotherapeutic strategy in treating OX40-altered lymphoid malignancies.

Oncogene or tumor suppressor gene: An integrated pan-cancer analysis of NBPF1

Neuroblastoma breakpoint family, member 1 (NBPF1), appears to be a double-edged sword with regard to its role in carcinogenesis. On the one hand, the tumor-suppressing functions of NBPF1 have been definitively observed in neuroblastoma, prostate cancer, cutaneous squamous cell carcinoma, and cervical cancer. On the other hand, there is evidence that NBPF1 regulates the colony formation, invasion, and maintenance of liver cancer cells and hence functions as an oncogene. The roles of NBPF1 are strictly dependent on the biological context and type of organization. However, a systematic pan-cancer analysis has thus far not been undertaken, and the significance of NBPF1 in the occurrence and progression of many malignancies is uncertain. In this paper, bioinformatics techniques were employed to analyze NBPF1 expression across different cancers and investigate the relationship between NBPF1 and clinical features, prognosis, genetic alteration, and tumor immune microenvironment, respectively. Our results show that NBPF1 is variably expressed in distinct tumor tissues and is also closely linked to clinical outcomes. In particular, compared to other tumor types, there was a strong negative correlation between NBPF1 expression and various components of the tumor microenvironment in adrenocortical carcinoma (ACC). We thus developed an NBPF1-derived immune risk model based on NBPF1-related immune genes; ACC patients with a high-risk score tended to have a poorer prognosis, accompanied by immune hyporesponsiveness. NBPF1 can be used as a prognostic biomarker for multiple cancers. Moreover, anti-NBPF1 immunotherapy may be suitable for treating ACC patients.

Identification of Novel Biomarkers Associated With the Prognosis and Potential Pathogenesis of Breast Cancer via Integrated Bioinformatics Analysis

Background:

Breast cancer is the most commonly diagnosed malignancy and a major cause of cancer-related deaths in women globally. Identification of novel prognostic and pathogenesis biomarkers play a pivotal role in the management of the disease.

Methods:

Three data sets from the GEO database were used to identify differentially expressed genes (DEGs) in breast cancer. Gene Ontology (GO) enrichment and Kyoto Encyclopaedia of Genes and Genomes pathway analyses were performed to elucidate the functional roles of the DEGs. Besides, we investigated the translational and protein expression levels and survival data of the DEGs in patients with breast cancer from the Gene Expression Profiling Interactive Analysis (GEPIA), Oncomine, Human Protein Atlas, and Kaplan Meier plotter tool databases. The corresponding change in the expression level of microRNAs in the DEGs was also predicted using miRWalk and TargetScan, and the expression profiles were analyzed using OncomiR. Finally, the expression of novel DEGs were validated in Chinese breast cancer tissues by RT-qPCR.

Results:

A total of 46 DEGs were identified, and GO analysis revealed that these genes were mainly associated with biological processes involved in fatty acid, lipid localization, and regulation of lipid metabolism. Two novel biomarkers, ADH1A and IGSF10, and 4 other genes (APOD, KIT, RBP4, and SFRP1) that were implicated in the prognosis and pathogenesis of breast cancer, exhibited low expression levels in breast cancer tissues. Besides, 14/25 microRNAs targeting 6 genes were first predicted to be associated with breast cancer prognosis. RT-qPCR results of ADH1A and IGSF10 expression in Chinese breast cancer tissues were consistent with the database analysis and showed significant down-regulation.

Conclusion:

ADH1A, IGSF10, and the 14 microRNAs were found to be potential novel biomarkers for the diagnosis, treatment, and prognosis of breast cancer.

Construction of Bone Metastasis-Specific Regulation Network Based on Prognostic Stemness-Related Signatures in Breast Invasive Carcinoma

Background

Bone is the most common metastatic site of Breast invasive carcinoma (BRCA). In this study, the bone metastasis-specific regulation network of BRCA was constructed based on prognostic stemness-related signatures (PSRSs), their upstream transcription factors (TFs) and downstream pathways.

Methods

Clinical information and RNA-seq data of 1,080 primary BRCA samples (1,048 samples without bone metastasis and 32 samples with bone metastasis) were downloaded from The Cancer Genome Atlas (TCGA). The edgeR method was performed to identify differential expressed genes (DEGs). Next, mRNA stemness index (mRNAsi) was calculated by one-class logistic regression (OCLR). To analyze DEGs by classification, similar genes were integrated into the same module by weighted gene co-expression network analysis (WGCNA). Then, univariate and multivariate Cox proportional hazard regression were applied to find the PSRSs. Furthermore, PSRSs, 318 TFs obtained from Cistrome database and 50 hallmark pathways quantified by GSVA were integrated into co-expression analysis. Significant co-expression patterns were used to construct the bone metastasis-specific regulation network. Finally, spatial single-cell RNA-seq and chromatin immunoprecipitation sequence (ChIP-seq) data and multi-omics databases were applied to validate the key scientific hypothesis in the regulation network. Additionally, Connectivity Map (CMap) was utilized to select the potential inhibitors of bone metastasis-specific regulation network in BRCA.

Results

Based on edgeR and WGCNA method, 43 PSRSs were identified. In the bone metastasis-specific regulation network, MAF positively regulated CD248 (R = 0.435, P < 0.001), and hallmark apical junction was the potential pathway of CD248 (R = 0.353, P < 0.001). This regulatory pattern was supported by spatial single-cell RNA sequence, ChIP-seq data and multi-omics online databases. Additionally, alexidine was identified as the possible inhibitor for bone metastasis of BRCA by CMap analysis.

Conclusion

PSRSs played important roles in bone metastasis of BRCA, and the prognostic model based on PSRSs showed good performance. Especially, we proposed that CD248 was the most significant PSRS, which was positively regulated by MAF, influenced bone metastasis via apical junction pathway. And this axis might be inhibited by alexidine, which providing a potential treatment strategy for bone metastasis of BRCA.

The Construction and Analysis of Tumor-Infiltrating Immune Cells and ceRNA Networks in Bladder Cancer

Background

Bladder cancer (BLCA) is the 11th most common malignancy worldwide. Although significant improvements have been made in screening, diagnosis, and precise management in recent years, the prognosis of BLCA remains bleak.

Objectives

This study aimed to investigate the prognostic significance of tumor-infiltrating immune cells and construct ceRNA networks in BLCA patients.

Methods

The expression data of BLCA patients were obtained from The Cancer Genome Atlas (TCGA) database. A competing endogenous RNA (ceRNA) network was constructed to identify the hub genes involved in the prognosis of BLCA. The CIBERSORT algorithm was utilized to investigate the infiltration levels of 22 subsets of immune cells. Ultimately, the nomogram was generated to visualize the survival probability of each patient, with the calibration curve being performed to assess its performance. Furthermore, the Pearson correlation test was used to explore the correlation between the identified hub genes in the ceRNA network and the prognostic-related immune cells.

Results

A total of eight elements in the ceRNA network were considered as key members and correlated with the prognosis of BLCA, including ELN, SREBF1, DSC2, TTLL7, DIP2C, SATB1, hsa-miR-20a-5p, and hsa-miR-29c-3p. T cells CD8, T cells follicular helper (Tfh), and neutrophils were identified as independent prognostic factors in BLCA. The co-expression analysis showed that there was a significant correlation between the identified hub genes and immune cells.

Conclusion

Our results suggest that the mechanism of hsa-miR-29c-3p regulates the expression of ELN and DSC2, and the infiltration of Tfh and neutrophils might play pivotal roles in the progression of BLCA.

The benefits of smoking cessation on survival in cancer patients by integrative analysis of multi-omics data

Few studies have examined the association between smoking status (including former smokers) at diagnosis and overall survival among cancer patients. We aimed to assess the benefits of quitting smoking on cancer prognosis in cohorts of cancer patient smokers obtained from the Cancer Genome Atlas (TCGA) database. Hazard ratios (HR) were calculated to evaluate smoking behavior at cancer diagnosis (reformed smokers vs. current smokers) in association with overall survival using multivariate‐adjusted Cox regressions analysis. According to our analyses, quitting smoking was the independent protective factor for overall survival in lung squamous cell carcinoma (LUSC) (HR = 0.67, 95% CI = 0.48–0.94). Comprehensive analysis of multicomponent data across reformed and current smokers identified a total of 85 differential expressed genes (DEGs) affected by different modes of genetic and epigenetic regulation, potentially representing cancer drivers in smokers. Moreover, we provided a smoking‐associated gene expression signature, which could evaluate the true effect on prognosis with high power (HR = 1.70, 95% CI = 1.19–2.43, AUC = 0.65, 0.67, and 0.70 for 2‐, 3‐, and 5‐year survival, respectively). This signature was also applicable in other smoking‐related cancers, including bladder urothelial carcinoma (HR = 1.70, 95% CI = 1.01–2.88), cervical carcinoma (HR = 5.69, 95% CI = 1.37–23.69), head and neck squamous cell carcinoma (HR = 1.97, 95% CI = 1.41–2.76), lung adenocarcinoma (HR = 1.73, 95% CI = 1.16–2.57), and pancreatic adenocarcinoma (HR = 4.28, 95% CI = 1.47–12.47). In conclusion, this study demonstrates that quitting smoking at diagnosis decreases risk of death in cancer patients. We also provide a smoking‐associated gene expression signature to evaluate the effect of smoking on survival. Lastly, we suggest that smoking cessation could comprise a part of cancer treatment to improve survival rates of cancer patients.