Genetics Research

Papillary thyroid carcinoma (PTC) is the most common type of thyroid neoplasms, characterized by evidence of follicular cell differentiation. Orthodenticle homeobox 1 (OTX1) is a transcription factor which has been implicated in numerous diseases, including malignancies. The objective of this research was to explore the function of OTX1 in PTC. Immunohistochemistry (IHC) was employed to determine the protein level of OTX1 in PTC specimens. Cell viability was assessed by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Furthermore, a xenograft model on nude mice was established to investigate in vivo effects of OTX1. Our results revealed that OTX1 was significantly upregulated within specific PTC tissues and was remarkably correlated with unfavorable clinical outcomes in PTC. Silencing OTX1 resulted in a significant inhibition in cell viability and suppressed cell proliferation. In addition, in vivo experiments demonstrated that OTX1 silencing resulted in a significant suppression of tumor growth in nude mice. Collectively, these results suggest that OTX1 may play crucial roles in promoting PTC progression.

Immunoregulation is crucial to septic shock (SS) but has not been clearly explained. Our aim was to explore potential biomarkers for SS by pathway and transcriptional analyses of immune-related genes to improve early detection. GSE57065 and GSE95233 microarray data were used to screen differentially expressed genes (DEGs) in SS. Gene Ontology and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses of DEGs were performed, and correlations between immune cell and pathway enrichment scores were analyzed. The predictive value of candidate genes was evaluated by receiver operating characteristic (ROC) curves. GSE66099, GSE4607, and GSE13904 datasets were used for external validation. Blood samples from six patients and six controls were collected for validation by qRT-PCR and western blotting. In total, 550 DEGs in SS were identified; these genes were involved in the immune response, inflammation, and infection. Immune-related pathways and levels of infiltration of CD4 + TCM, CD8 + T cells, and preadipocytes differed between SS cases and controls. Seventeen genes were identified as potential biomarkers of SS (areas under ROC curves >0.9). The downregulation of CD8A, CD247, CD3G, LCK, and HLA-DRA in SS was experimentally confirmed. We identified several immune-related biomarkers in SS that may improve early identification of disease risk.

Background. The role of disulfidptosis-related lncRNAs remains unclear in lung adenocarcinoma. Methods. Analysis in R software was conducted using different R packages, which are based on the public data from The Cancer Genome Atlas (TCGA) database. The transwell assay was used to evaluate the invasion and migration abilities of lung cancer cells. Results. In our study, we identified 1401 lncRNAs significantly correlated with disulfidptosis-related genes (|Cor| > 0.3 and ). Then, we constructed a prognosis model consisting of 11 disulfidptosis-related lncRNAs, including AL133445.2, AL442125.1, AC091132.2, AC090948.1, AC020765.2, CASC8, AL606834.1, LINC00707, OGFRP1, U91328.1, and GASAL1. This prognosis model has satisfactory prediction performance. Also, the risk score and clinical information were combined to develop a nomogram. Analyses of biological enrichment and immune-related data were used to identify underlying differences between patients at high-risk and low-risk groups. Moreover, we noticed that the immunotherapy nonresponders have higher risk scores. Meanwhile, patients at a high risk responded more strongly to docetaxel, paclitaxel, and vinblastine. Furthermore, further analysis of the model lncRNA OGFRP1 was conducted, including clinical, immune infiltration, biological enrichment analysis, and a transwell assay. We discovered that by inhibiting OGFRP1, the invasion and migration abilities of lung cancer cells could be remarkably hindered. Conclusion. The results of our study can provide directions for future research in the relevant areas. Moreover, the prognosis signature we identified has the potential for clinical application.

Background. The problem of prognostic stratification in acute myeloid leukemia (AML) patients still has limitations. Methods. The expression profile data and clinical features of AML patients were obtained from multiple publicly available sources, including GSE71014, TCGA-LAML, and TARGET-AML. Single-cell analysis was performed using the TISCH project. All the analysis was conducted in the R software. Results. In our study, three public AML cohorts, GSE71014, TARGET-AML, and TCGA-AML, were selected. Then, we identified the prognosis-related molecules through bioinformatic analysis. Finally, the DUSP7 was noticed as a risk factor for AML patients, which has not been reported previously. Biological enrichment analysis and immune-related analysis were performed to illustrate the role of DUSP7 in AML. Single-cell analysis indicated that the DUSP7 was widely distributed in various cells, especially in monocyte/macrophages and malignant. Following this, a prognosis model based on DUSP7-derived genes was constructed, which showed a good prognosis prediction ability in all cohorts. Conclusions. Our results preliminarily reveal the role and potential mechanism of DUSP7 in AML, providing direction for future research.

Background. Advanced glycation end products’ receptor (AGER) is a multiligand receptor that interacts with a wide range of ligands. Previous studies have shown that abnormal AGER expression is closely related to immune infiltration and tumorigenesis. However, the AGER DNA methylation relationship between prognosis and infiltrating immune cells in LUAD and LUSC is still unclear. Methods. AGER expression in pan-cancer was obtained by using the UALCAN databases. Kaplan–Meier plotter showed the correlation of AGER mRNA expression levels and clinicopathological parameters. The protein expression levels for AGER were derived from Human Protein Atlas Database Analysis. The copy number, somatic mutation, and DNA methylation of AGER were presented with UCSC Xena database. TIMER platform and TISIDB website were used to show the correlation between AGER expression and tumor immune cell infiltration level. Results. The expression level of AGER was significantly reduced in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Low expression of AGER was significantly correlated with histology, stage, lymph node metastasis, and tumor protein 53 (TP53) mutation and could be used as a potential indicator of poor prognosis of LUAD and LUSC. Moreover, AGER expression was positively correlated with the infiltrating immune cells. Further analysis showed that copy number variation (CNV), mutation, and DNA methylation were involved in AGER downregulation. In addition, we also found that hypermethylated AGER was significantly correlated with tumor-infiltrating lymphocytes. Conclusion. AGER may be a candidate for the prognostic biomarker of LUAD and LUSC related to tumor immune microenvironment.

Background. PANoptosis has been a research hotspot, but the role of PANoptosis in hepatocellular carcinoma (HCC) remains widely unknown. Drug resistance and low response rate are the main limitations of chemotherapy and immunotherapy in HCC. Thus, construction of a prognostic signature to predict prognosis and recognize ideal patients for corresponding chemotherapy and immunotherapy is necessary. Method. The mRNA expression data of HCC patients was collected from TCGA database. Through LASSO and Cox regression, we developed a prognostic signature based on PANoptosis-related genes. KM analysis and ROC curve were implemented to evaluate the prognostic efficacy of this signature, and ICGC and GEO database were used as external validation cohorts. The immune cell infiltration, immune status, and IC50 of chemotherapeutic drugs were compared among different risk subgroups. The relationships between the signature and the efficacy of ICI therapy, sorafenib treatment, and transcatheter arterial chemoembolization (TACE) therapy were investigated. Result. A 3-gene prognostic signature was constructed which divided the patients into low- and high-risk subgroups. Low-risk patients had better prognosis, and the risk score was proved to be an independent predictor of overall survival (OS), which had a well predictive effect. Patients in high-risk population had more immunosuppressive cells (Tregs, M0 macrophages, and MDSCs), higher TIDE score and TP53 mutation rate, and elevated activity of base excision repair (BER) pathways. Patients with low risk benefited more from ICI, TACE, and sorafenib therapy. The predictive value of the risk score was comparable with TIDE and MSI for OS under ICI therapy. The risk score could be a biomarker to predict the response to ICI, TACE, and sorafenib therapy. Conclusion. The novel signature based on PANoptosis is a promising biomarker to distinguish the prognosis predict the benefit of ICI, TACE, and sorafenib therapy, and forecast the response to them.