Tumor to liver maximum standardized uptake value ratio of FDG-PET/CT parameters predicts tumor treatment response and survival of stage III non-small cell lung cancer.

BACKGROUND: To assess the predictive values of primary tumor FDG uptake for patients with inoperable stage III non-small cell lung cancer (NSCLC) after concurrent chemoradiotherapy (CCRT). METHODS: A total of 107 patients with diagnosis of stage III NSCLC and CCRT were enrolled. The tumor maximum uptake value (SUVmax) was standardized by calculating several ratios between tumor and each background tissues. The receiver operating characteristics curve (ROC) was used to compare the predictive power of prognostic models. The tumor objective response rate (ORR) and overall survival (OS) were compared and analyzed by the Kaplan-Meier method and univariate and multivariate Cox regression models. RESULTS: The areas under ROC curve (AUCs) ranged from 0.72 to 0.81 among these tumor SUVmax and standardized SUVmax ratios, and the tumor SUVmax and tumor SUVmax-to-liver SUVmean ratio (TLMR) were more predictive of ORR (AUC, 0.81; 95% CI, 0.73-0.88 for tumor SUVmax and AUC, 0.84; 95%CI, 0.76-0.91 for TLMR) than any of other SUVmax ratios. The patients with lower tumor SUVmax, SUVmean and SUVmax ratios had a significantly better OS than those with their corresponding higher ones. Moreover, both univariate and multivariable analyses revealed that TLMR was significantly associated with better ORR and OS after adjustment with other prognostic variables. CONCLUSIONS: TLMR, a standardized tumor SUVmax, was an independent prognostic predictor for tumor ORR and OS of patients with stage III NSCLC after CCRT.

Analysis and Validation of the Prognosis ability of the M7GRelated miRNAs in Lung Adenocarcinoma.

BACKGROUND: N7-methylguanosine (m7G) modification plays a crucial role in the development and progression of lung cancers. MicroRNAs (miRNAs) are closely involved in programmed cell death and the mechanism of tumor growth. The m7G-associated miRNAs genes in lung adenocarcinoma (LUAD), and their prognosis prediction ability of LUAD, however, had not been investigated. METHODS: The RNA transcriptomes, clinical indices, and immune scores of LUAD patients were searched and downloaded from The Cancer Genome Atlas (TCGA) and the ESTIMATE database. The miRNAs targeting METTL1 and WDR4 were extracted from the TargetScan database. Differentially expressed m7G-related miRNAs were identified and their prediction power of LUAD prognosis was systematically investigated. RESULTS: Among 40 the differentially expressed m7G-related miRNAs in LUAD, five (hsa-miR-31-5p, hsa-miR-5571-3p, hsa-miR-4697-3p, hsa-miR-6858-5p, and hsa-miR-873-3p) demonstrate significant predictive value for prognosis. The risk score constructed by these five miRNAs was an independent prognostic factor (univariate Cox regression results: hazard ratio (HR) = 1.6619, 95% confidential interval (CI) = 1.2103-2.2819, p = 0.0017; multivariate Cox regression results: HR = 1.6004, 95% CI = 1.1633-2.2017, p = 0.0039). The survival curves showed that patients with high-risk scores had a poor prognosis. Calibration curves indicated good predictability in a nomogram constructed combining the miRNA and the clinical indices of age, sex, chemotherapy, radiotherapy, stage, and risk score. GO and KEGG analysis of the overlapping genes showed that the prognostic miRNAs were closely associated with the neuropeptide signaling pathway. Besides, the immune infiltration analysis showed that the expression of the AMPD1 gene was strongly associated with immune cells and immunology functions in LUAD. CONCLUSION: This study identified DE m7G-related miRNAs and demonstrated their prediction ability in the prognosis of LUAD patients. The risk signature based on these miRNAs demonstrates high accuracy in predicting the prognosis of LUAD patients.

Prognostic roles of a novel basement membranes-related gene signature in lung adenocarcinoma.

Background: The basement membranes (BMs) are involved in tumor progression, while few comprehensive analyses to date are performed on the role of BM-related gene signatures in lung adenocarcinoma (LUAD). Thus, we aimed to develop a novel prognostic model in LUAD based on BMs-related gene profiling. Methods: The LUAD BMs-related gene profiling and corresponding clinicopathological data were obtained from the basement membrane BASE, The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) databases. The Cox regression and least absolute shrinkage and selection operator (LASSO) methods were used to construct a BMs-based risk signature. The concordance index (C-index), receiver operating characteristic (ROC), and calibration curves were generated to evaluate the nomogram. The GSE72094 dataset was used to validate prediction of the signature. The differences in functional enrichment, immune infiltration, and drug sensitivity analyses were compared based on risk score. Results: In TCGA training cohort, 10 BMs-related genes were found, (e.g., ACAN, ADAMTS15, ADAMTS8, BCAN, etc). The signal signature based on these 10 genes was categorized into high- and low-risk groups regarding survival differences (p < 0.001). Multivariable analysis showed that the signature of combined 10 BMs-related genes was an independent prognostic predictor. Such a prognostic value of BMs-based signature in validation cohort of the GSE72094 were further verified. The GEO verification, C-index, and ROC curve showed that the nomogram had accurate prediction performance. The functional analysis suggested that BMs were mainly enriched in extracellular matrix-receptor (ECM-receptor) interaction. Moreover, the BMs-based model was correlated with immune checkpoint. Conclusion: This study identified BMs-based risk signature genes and demonstrated their ability to predict prognosis and guide personalized treatment of patients with LUAD.

Association of High Expression of Mitochondrial Fission Regulator 2 with Poor Survival of Patients with Esophageal Squamous Cell Carcinoma.

Mitochondrial fission regulator 2 (MTFR2) is associated with mitochondrial fission, while few studies have assessed the associations between MTFR2 expression and clinical characteristics or prognosis of esophageal squamous cell carcinoma (ESCC). In this study, we compared the expression of MTFR2 in 6 ESCC tumors and relative normal tissues by immunohistochemistry (IHC). To assess the effect of MTFR2 expression on clinicopathologic characteristics and survival, 115 paraffin embedded ESCC tissue samples were assessed by IHC staining. Furthermore, the association between clinicopathological properties and MTFR2 expression in patients with ESCC was examined. The survival analysis was performed using the Cox regression models. We found that MTFR2 expression was significantly increased in ESCC tumors compared with normal esophageal epithelial cells. IHC analysis of 115 paraffin embedded ESCC tumor specimens of the patients showed that the expression of MTFR2 was significantly associated with clinical stage (P < 0.001), tumor classification (P < 0.001), histological grade (P < 0.001), and other clinicopathological characteristics. Both univariate and multivariate analyses showed that MTFR2 expression was inversely correlated with the survival of ESCC patients. In conclusion, the expression of MTFR2 is significantly associated with clinicopathologic characteristics and prognosis of ESCC. Thus, MTFR2 expression could serve as a potentially important prognostic biomarker and clinical target for patients with ESCC.