Identification of key genes in the tumor microenvironment of lung adenocarcinoma

Machine-learning and combined analysis of single-cell and bulk-RNA sequencing identified a DC gene signature to predict prognosis and immunotherapy response for patients with lung adenocarcinoma

BACKGROUND

Innate immune effectors, dendritic cells (DCs), influence cancer prognosis and immunotherapy significantly. As such, dendritic cells are important in killing tumors and influencing tumor microenvironment, whereas their roles in lung adenocarcinoma (LUAD) are largely unknown.

METHODS

In this study, 1658 LUAD patients from different cohorts were included. In addition, 724 cancer patients who received immunotherapy were also included. To identify DC marker genes in LUAD, we used single-cell RNAsequencing data for analysis and determined 83 genes as DC marker genes. Following that, integrative machine learning procedure was developed to construct a signature for DC marker genes.

RESULTS

Using TCGA bulk-RNA sequencing data as the training set, we developed a signature consisting of seven genes and classified patients by their risk status. Another six independent cohorts demonstrated the signature' s prognostic power, and multivariate analysis demonstrated it was an independent prognostic factor. LUAD patients in the high-risk group displayed more advanced features, discriminatory immune-cell infiltrations and immunosuppressive states. Cell-cell communication analysis indicates that tumor cells with lower risk scores communicate more actively with the tumor microenvironment. Eight independent immunotherapy cohorts revealed that patients with low-risk had better immunotherapy responses. Drug sensitivity analysis indicated that targeted therapy agents exhibited greater sensitivity to low-risk patients, while chemotherapy agents displayed greater sensitivity to high-risk patients. In vitro experiments confirmed that CTSH is a novel protective factor for LUAD.

CONCLUSIONS

An unique signature based on DC marker genes that is highly predictive of LUAD patients' prognosis and response to immunotherapy. CTSH is a new biomarker for LUAD.

Clinicopathological value of hematopoietic cell kinase overexpression in laryngeal squamous cell carcinoma tissues

Laryngeal squamous cell carcinoma (LSCC) is the most lethal cancer in head and neck tumors. Although hematopoietic cell kinase (HCK) has been proven to be an oncogene in several solid tumors, its roles in LSCC remain obscure. This is the first study to evaluate the clinical value of HCK in LSCC, with the aim of exploring its expression status and potential molecular mechanisms underlying LSCC. LSCC tissue-derived gene chips and RNA-seq data were collected for a quantitive integration of HCK mRNA expression level. To confirm the protein expression level of HCK, a total of 82 LSCC tissue specimens and 56 non-tumor laryngeal epithelial controls were collected for in-house tissue microarrays and immunohistochemical staining. Kaplan-Meier curves were generated to determine the ability of HCK in predicting overall survival, progress-free survival, and disease-free survival of LSCC patients. LSCC overexpressed genes and HCK co-expressed genes were intersected to preliminarily explore the enriched signaling pathways of HCK. It was noticed that HCK mRNA was markedly overexpressed in 323 LSCC tissues compared with 196 non-LSCC controls (standardized mean difference = 0.81, p < 0.0001). Upregulated HCK mRNA displayed a moderate discriminatory ability between LSCC tissues and non-tumor laryngeal epithelial controls (area under the curve = 0.78, sensitivity = 0.76, specificity = 0.68). The higher expression level of HCK mRNA could predict worse overall survival and disease-free survival for LSCC patients (p = 0.041 and p = 0.013). Lastly, upregulated co-expression genes of HCK were significantly enriched in leukocyte cell-cell adhesion, secretory granule membrane, and extracellular matrix structural constituent. Immune-related pathways were the predominantly activated signals, such as cytokine-cytokine receptor interaction, Th17 cell differentiation, and Toll-like receptor signaling pathway. In conclusion, HCK was upregulated in LSCC tissues and could be utilized as a risk predictor. HCK may promote the development of LSCC by disturbing immune signaling pathways.

Identification of Ubiquitin-Related Gene-Pair Signatures for Predicting Tumor Microenvironment Infiltration and Drug Sensitivity of Lung Adenocarcinoma

Simple Summary

Lung adenocarcinoma (LUAD) has a high mortality and incidence rate. The therapeutic efficacy of LUAD varies with the individual heterogeneity of the tumor microenvironment (TME). It is necessary to explore more biomarkers and targets to improve the prognosis of patients. Ubiquitination pathways are involved in the biological process of regulating the anti-tumor immunity of immune cells and immunosuppression of tumor cells in the TME of patients. In this study, we clarified the characteristics of ubiquitin-related gene pairs (UbRGPs) and identified the relationship between the status of the TME and UbRGPs of patients with LUAD. A prognostic signature based on six UbRGPs was established, which performed well in predicting the immune infiltration and tumor mutation burden (TMB) in the TME and the response of LUAD to immuno-, chemo-, and targeted therapy. In conclusion, the UbRGPs signature is an independent prognostic indicator and has great potential in assisting the clinical therapy for patients with LUAD.

Abstract

Lung adenocarcinoma (LUAD) is a common pathological type of lung cancer worldwide, and new biomarkers are urgently required to guide more effective individualized therapy for patients. Ubiquitin-related genes (UbRGs) partially participate in the initiation and progression of lung cancer. In this study, we used ubiquitin-related gene pairs (UbRGPs) in tumor tissues to access the function of UbRGs in overall survival, immunocyte infiltration, and tumor mutation burden (TMB) of patients with LUAD from The Cancer Genome Atlas (TCGA) database. In addition, we constructed a prognostic signature based on six UbRGPs and evaluated its performance in an internal (TCGA testing set) and an external validation set (GSE13213). The prognostic signature revealed that risk scores were negatively correlated with the overall survival, immunocyte infiltration, and expression of immune checkpoint inhibitor-related genes and positively correlated with the TMB. Patients in the high-risk group showed higher sensitivity to partially targeted and chemotherapeutic drugs than those in the low-risk group. This study contributes to the understanding of the characteristics of UbRGPs in LUAD and provides guidance for effective immuno-, chemo-, and targeted therapy.

Identification of Tumor Antigens and Immune Subtypes of Esophageal Squamous Cell Carcinoma for mRNA Vaccine Development

Purpose: The applicability of mRNA vaccines against esophageal squamous cell carcinoma (ESCC) remains unclear. Here, we identified potential antigens for developing mRNA vaccines against ESCC and characterized immune subtypes to select appropriate patients for vaccination.

Methods: RNA-seq, genetic alteration data, and corresponding clinical information of ESCC patients were obtained from the Cancer Genome Atlas (TCGA) database. The RNA-seq data of normal esophageal tissue were obtained from the Genotype-Tissue Expression (GTEx) database. Potential tumor antigens were screened by analyzing differentially expressed and mutated genes and potential antigens with significant differences in prognosis were screened using the Kaplan-Meier method. The proportion of immune cell infiltration in the tumor microenvironment was estimated using CIBERSORT and MCPcounter, and the correlation of potential antigens with antigen-presenting cells and major histocompatibility complex class II was analyzed. Subsequently, immune subtypes were constructed using consensus clustering analysis and characterized by single-sample gene set enrichment analysis and weighted gene co-expression network analysis (WGCNA). The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to analyze the drug sensitivity of different immune subtypes.

Results: Four overexpressed and mutated tumor antigens associated with antigen presentation and poor prognosis were identified in ESCC, including NLRC5, FCRL4, TMEM229B, and LCP2. By consensus clustering, we identified two immune-associated ESCC subtypes, immune subtype 1 (IS1) and immune subtype 2 (IS2); the prognosis of the two subtypes was statistically different. In addition, the two immune subtypes had distinctly different cellular, molecular, and clinical characteristics. IS1 patients have a distinct immune “hot” phenotype with strong immune tolerance, whereas patients with IS2 have an immune “cold” phenotype. Differential expression of immune checkpoints and immunogenic cell death modulators was observed between the different immune subtypes. Finally, we found that IS1 and IS2 patients showed different drug sensitivities to common anti-tumor drugs, possibly facilitating the development of individualized treatment regimens for patients.

Conclusion: NLRC5, LCP2, TMEM229B, and FCRL4 are potential antigens for ESCC mRNA vaccines, and such vaccines may be more suitable for IS2 patients. This study provides a theoretical basis for mRNA vaccines against ESCC, by identifying the critical characteristics to predict ESCC prognosis and select suitable patients for vaccination.

Identification of the critical genes and miRNAs in hepatocellular carcinoma by integrated bioinformatics analysis

Hepatocellular carcinoma (HCC) is a global health problem with complex etiology and pathogenesis. Microarray data are increasingly being used as a novel and effective method for cancer pathogenesis analysis. An integrative analysis of genes and miRNA for HCC was conducted to unravel the potential prognosis of HCC. Two gene microarray datasets (GSE89377 and GSE101685) and two miRNA expression profiles (GSE112264 and GSE113740) were obtained from Gene Expression Omnibus database. A total of 177 differently expressed genes (DEGs) and 80 differently expressed miRNAs (DEMs) were screened out. Functional enrichment of DEGs was proceeded by Clue GO and these genes were significantly enriched in the chemical carcinogenesis pathway. A protein-protein interaction network was then established on the STRING platform, and ten hub genes (CDC20, TOP2A, ASPM, NCAPG, AURKA, CYP2E1, HMMR, PRC1, TYMS, and CYP4A11) were visualized via Cytoscape software. Then, a miRNA-target network was established to identify the hub dysregulated miRNA. A key miRNA (hsa-miR-124-3p) was filtered. Finally, the miRNA-target-transcription factor network was constructed for hsa-miR-124-3p. The network for hsa-miR-124-3p included two transcription factors (TFs) and five targets. These identified DEGs and DEMs, TFs, targets, and regulatory networks may help advance our understanding of the underlying pathogenesis of HCC.