Downregulation of T-cell cytotoxic marker IL18R1 promotes cancer proliferation and migration and is associated with dismal prognosis and immunity in lung squamous cell carcinoma.

Immunotherapy can improve the survival of patients with advanced lung squamous cell carcinoma (LUSC). T cytotoxic cells are one of the main members of the immune microenvironment. Herein, we aimed to identify the roles of T-cell cytotoxic markers interleukin 18 (IL18) receptor 1 (IL18R1) in the LUSC progression using bioinformatics, clinical tissue specimen, and cell experiment. We assessed the association between the IL18R1 expression and immune infiltration and IL18R1-related competing RNA network. The IL18R1 expression was downregulated in the LUSC tissues. The IL18R1 expression downregulation was associated with diagnosis and short overall survival and disease-specific survival, and it was also an independent risk factor for dismal survival time in LUSC. IL18R1-related nomograms predicted the survival time of patients with LUSC. IL18R1 overexpression inhibited the proliferation, migration, and invasion of LUSC cells. The IL18R1 expression was significantly associated with the microenvironment (stromal, immune, and estimate scores), immune cells (such as the T cells, cytotoxic cells, CD8 T cells), and immune cell markers (such as the CD8A, PD-1, and CTLA4) in LUSC. AC091563.1 and RBPMS-AS1 downregulation was positively associated with the IL18R1 expression, negatively associated with the miR-128-3p expression, and associated with short disease-specific survival and progression in LUSC. In conclusion, IL18R1 was significantly downregulated and associated with the prognosis and immune microenvironment. IL18R1 overexpression inhibits the growth and migration of cancer cells in LUSC. Furthermore, AC091563.1 and RBPMS-AS1 might compete with IL18R1 to bind miR-128-3p for participating in LUSC progression. These results showed that IL18R1 is a biomarker for evaluating the prognosis of patients with LUSC.

Decreased APOC1 expression inhibited cancer progression and was associated with better prognosis and immune microenvironment in esophageal cancer.

Several studies have demonstrated the involvement of apolipoprotein C1 (APOC1) in multiple cancers. However, the role of APOC1 in esophageal cancer (ESCA) has not been elucidated. Hence, we examined the expression of APOC1 in ESCA tissues acquired from The Cancer Genome Atlas (TCGA) database and clinical samples from our hospital. An investigation of the association of APOC1 with the clinicopathological characteristics, prognosis, and diagnosis of ESCA was carried out on the basis of survival, receiver operating characteristics, and correlation analyses. Gene ontology, KEGG analysis, and protein-protein interaction network showed that co-expressed APOC1 genes were involved in the functions, mechanisms, and action network. The effects of APOC1 expression on ESCA cells were explored using CCK-8, migration and invasion assays. The relationship between APOC1 expression and ESCA immune-infiltrating cells and cell markers were examined using correlation analysis. We found that APOC1 was overexpressed in TCGA ESCA tissues and the same was validated in clinical ESCA tissues, with the area under the curve for APOC1 being 0.887. Overexpression of APOC1 was associated with short overall survival, disease-specific survival, progression-free interval, T stage, pathological stage, body mass index, and histological grade. Inhibition of APOC1 expression significantly reduced the proliferation, migration, and invasion of ESCA cells. Furthermore, APOC1 expression positively correlated with the ESTIMATE, immune, and stromal scores in ESCA. Overexpression of APOC1 correlated with the tumor purity, B cells, T helper cells, natural killer cells, cytotoxic cells, and other immune cells. Moreover, APOC1 was involved in ESCA progression via T cell receptor, B cell receptor, and other immune signaling pathways. Thus, APOC1 overexpression is expected to be a biomarker for dismal prognosis and diagnosis of ESCA. Inhibition of APOC1 expression significantly reduced the proliferation, migration, and invasion of ESCA cells. Overexpression of APOC1 was associated with the immune microenvironment in ESCA. Thus, APOC1 may be an efficient biomarker for proper prognosis and diagnosis of ESCA.

The Risk Model Based on the Three Oxidative Stress-Related Genes Evaluates the Prognosis of LAC Patients.

Background: Oxidative stress plays a role in carcinogenesis. This study explores the roles of oxidative stress-related genes (OSRGs) in lung adenocarcinoma (LAC). Besides, we construct a risk score model of OSRGs that evaluates the prognosis of LAC patients. Methods: OSRGs were downloaded from the Gene Set Enrichment Analysis (GSEA) website. The expression levels of OSRGs were confirmed in LAC tissues of the TCGA database. GO and KEGG analyses were used to evaluate the roles and mechanisms of oxidative stress-related differentially expressed genes (DEGs). Survival, ROC, Cox analysis, and AIC method were used to screen the prognostic DEGs in LAC patients. Subsequently, we constructed a risk score model of OSRGs and a nomogram. Further, this work investigated the values of the risk score model in LAC progression and the relationship between the risk score model and immune infiltration. Results: We discovered 163 oxidative stress-related DEGs in LAC, involving cellular response to oxidative stress and reactive oxygen species. Besides, the areas under the curve of CCNA2, CDC25C, ERO1A, CDK1, PLK1, ITGB4, and GJB2 were 0.970, 0.984, 0.984, 0.945, 0.984, 0.771, and 0.959, respectively. This indicates that these OSRGs have diagnosis values of LAC and are significantly related to the overall survival of LAC patients. ERO1A, CDC25C, and ITGB4 overexpressions were independent risk factors for the poor prognosis of LAC patients and were associated with risk scores in the risk model. High-risk score levels affected the poor prognosis of LAC patients. Notably, a high-risk score may be implicated in LAC progression via cell cycle, DNA replication, mismatch repair, and other mechanisms. Further, ERO1A, CDC25C, and ITGB4 expression levels were related to the immune infiltrating cells of LAC, including mast cells, NK cells, and CD8 T cells. Conclusion: In summary, ERO1A, CDC25C, and ITGB4 of OSRGs are associated with poor prognosis of LAC patients. We confirmed that the risk model based on the ERO1A, CDC25C, and ITGB4 is expected to assess the prognosis of LAC patients.

SPDL1 Overexpression Is Associated With the 18F-FDG PET/CT Metabolic Parameters, Prognosis, and Progression of Esophageal Cancer.

Esophageal cancer (ESCA) is one of the common malignant tumors. The roles and signaling mechanisms of spindle apparatus coiled-coil protein 1 (SPDL1) in ESCA progression have not been reported previously. Therefore, the expression levels and potential clinical roles of SPDL1 were investigated using data from multiple databases and tissue samples of 53 ESCA patients who underwent 18F-FDG positron emission tomography (PET)/computed tomography (CT) before therapy. The signaling mechanisms of SPDL1 involved in ESCA progression were investigated via bioinformatics analysis. The effects of SPDL1 on the growth and migration of ESCA cells were investigated using CCK-8, Edu, and transwell assays. SPDL1 was upregulated in ESCA tissues. Increased SPDL1 expression was associated with age, grade, drinking history, cancer stage, lymph node metastasis, TP53 mutation, and poor prognosis in patients with ESCA. SPDL1 overexpression was significantly correlated with SUVmax, SUVmean, and TLG of PET/CT. SPDL1 silencing inhibited cell proliferation, migration, and invasion. SPDL1 was significantly enriched in cell cycle, spliceosome, DNA replication, and other processes. The hub genes of a constructed protein-protein interaction network included CDK1, BUB1, CCNB1, BUB1B, CCNA2, CDC20, MAD2L1, AURKB, NDC80, and PLK1, which were related to SPDL1 expression. The findings of this study suggest that SPDL1 may serve as a biomarker of ESCA prognosis.

Evaluation of the roles and regulatory mechanisms of PD-1 target molecules in NSCLC progression.

BACKGROUND: Targeted programmed cell death protein 1 (PD-1) therapy could effectively improve the long-term prognosis of patients with non-small cell lung cancer (NSCLC). The role of PD-1 targets in the progression of NSCLC has not been fully revealed. METHODS: The differentially expressed genes (DEGs) in patients' blood after NSCLC treatment with PD-1 blocker nivolumab in the GSE141479 dataset were analyzed by GEO2R and identified in the TCGA database. The mechanism of action involved in the PD-1 target molecules via the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The protein-protein interaction (PPI) network shows the relationship between PD-1 target molecules. The factors affecting the prognosis of NSCLC patients were identified via the COX regression analysis and survival analysis to build the risk model and nomogram. RESULTS: There were 64 DEGs in patients' blood after nivolumab treatment and 48 DEGs in NSCLC tissues. The PD-1 target molecules involved cell proliferation, DNA replication, cell cycle, lung cancer, and other cellular processes. The prognostic factors CCNA2, CHEK1, DLGAP5, E2F8, FOXM1, HIST1H2BH, HJURP, MKI67, PLK1, TPX2, and TYMS, and the independent factors HIST1H2BH and PLK1, influenced the prognosis of NSCLC patients. HIST1H2BH and PLK1 were overexpressed in LUAD and LUSC tissues. The elevated expression levels of HIST1H2BH and PLK1 were related to the overall survival (OS) and the progression-free survival of NSCLC patients. High-risk NSCLC patients had a poor prognosis and were an independent factor influencing the poor prognosis of NSCLC patients. The high-risk model group was enriched with signaling mechanisms such as cell cycle, DNA replication, and homologous recombination. CONCLUSIONS: The risk model based on PD-1 target molecules was helpful to assess the prognosis of NSCLC patients. HIST1H2BH and PLK1 might become prognostic biomarkers of NSCLC patients.

The roles of risk model based on the 3-XRCC genes in lung adenocarcinoma progression.

BACKGROUND: The abnormal expression of deoxyribonucleic acid (DNA) repair genes might be the cause of tumor development and resistance of malignant cells to chemotherapeutic drugs. A risk model based on the X-ray repair of cross-complementary (XRCC) genes was constructed to improve the diagnosis and treatment of lung adenocarcinoma (LUAD) patients. METHODS: The expression levels, diagnostic values, and prognostic values of XRCC genes were identified, and the roles and regulatory mechanisms of the risk model based on the XRCC4/5/6 in LUAD progression was explored via The Cancer Genome Atlas (TCGA) and Oncomine databases. RESULTS: XRCC1/2/3/4/5/6, XRCC7 (PRKDC), and XRCC9 (FANCG) were overexpressed, and had diagnostic value for LUAD. The XRCC genes were involved in DNA repair, and participated in the regulation of non-homologous end-joining, homologous recombination, etc. The overall survival (OS), tumor (T) stage, and survival status of patients were significantly different between the Cluster1 and Cluster2 groups. XRCC4/5/6 were independent risk factors affecting the prognosis of LUAD patients. The risk score was related to the prognosis, sex, clinical stage, T, lymph node (N), and metastasis (M) stage, as well as the survival status of LUAD patients. The clinical stage and risk score were independent risk factors for poor prognosis in LUAD patients. The risk model was involved in RNA degradation, cell cycle, basal transcription factors, DNA replication etc. The risk scores were significantly correlated with the expression levels of TGFBR1, CD160, TNFSF4, TNFRSF14, IL6R, CXCL16, TNFRSF25, TAPBP, CCL16, and CCL14. CONCLUSIONS: The risk model based on the XRCC4/5/6 genes could predict the progression of LUAD patients.

[Applied research on the physical model for calculating optical constant of metal oxide films].

In the present paper, two metal oxide films of HfO2 and Ta2 O5 were prepared by ion beam sputtering technology. Through measuring ellipsometric parameters of HfO2 and Ta2O5 films, their optical constants can be inversion-calculated by nonlinear least squares techniques. In the fitting process, eight experiment groups were arranged by the orthogonal table L8 (2(7)). After selecting Cauchy model, the largest influencing factor for fitting optical constant of HfO2 is surface layer model and the largest influencing factor for fitting optical constant of Ta2 O5 is refractive index gradient model. The impact of different physical model on MSE and the order for selecting model in the fitting process are determined. According to the selecting model and the determined fitting order, optical constants of the two metal oxide films were inversion-calculated with adding weak absorption model, and the obtained MSE can descend 79% and 39% according to the initial value. The results indicated that the selecting model possesses definite physical significance in the fitting process. The obtained method can be applied in inversion-calculating many metal oxide films with weak absorption. It has wide application value. At 500 nm, the refractive index gradient of Ta2O5 films is greater than HfO2 films, while the extinction coefficient of HfO2 films is greater than Ta2O5. It was shown that Hf metal is easier to form stable oxide than Ta metal. And the absorption of HfO2 films is larger than Ta2O5 films.