Association of ERCC family mutations with prognosis and immune checkpoint inhibitors response in multiple cancers

Abstract The proteins encoded by the excision repair cross-complementing (ERCC) family are pivotal in DNA damage repair and maintaining genome stability. However, the precise role of the ERCC family in tumor prognosis and the effectiveness of immune checkpoint inhibitors (ICI) therapy remain uncertain. This study aimed to explore the connection between ERCC mutations and prognosis as well as the response to ICI. We observed that patients with ERCC mutations exhibited enhanced progression-free survival (PFS) and overall survival (OS) in two independent pan-cancer cohorts. Furthermore, this mutant subgroup showed higher tumor mutation burden (TMB) compared to the wild-type subgroup. Notably, ERCC mutations were associated with better OS (HR 0.54, 95% CI 0.42–0.70; P < 0.001) in pan-cancer patients who underwent ICI therapy (N = 1661). These findings were validated in a separate cohort, where patients in the ERCC mutant subgroup demonstrated improved clinical outcomes (HR 0.56, 95% CI 0.37–0.84; P = 0.03) and higher response rates (51.9% vs. 26.8%) than the wild-type subgroup. Further analysis revealed that patients with ERCC mutations displayed elevated tumor neoantigen burden (TNB) levels and increased infiltration of immune-response cells. Our study suggests that ERCC mutations are linked to enhanced immunogenicity and improved ICI efficacy, thus potentially serving as a biomarker for ICI therapy

Changes and Trends—Efficiency of Physical Blowing Agents in Polyurethane Foam Materials

This work developed a novel method for measuring the effective rate of a PBA (physical blowing agent) and solved the problem that the effective rate of a PBA could not be directly measured or calculated in previous studies. The results show that the effectiveness of different PBAs under the same experimental conditions varied widely, from approximately 50% to almost 90%. In this study, the overall average effective rates of the PBAs HFC-245fa, HFO-1336mzzZ, HFC-365mfc, HFCO-1233zd(E), and HCFC-141b are in descending order. In all experimental groups, the relationship between the effective rate of the PBA, rePBA, and the initial mass ratio of the PBA to other blending materials in the polyurethane rigid foam, w, demonstrated a trend of first decreasing and then gradually stabilizing or slightly increasing. This trend is caused by the interaction of PBA molecules among themselves and with other component molecules in the foamed material and the temperature of the foaming system. In general, the influence of system temperature dominated when w was less than 9.05 wt%, and the interaction of PBA molecules among themselves and with other component molecules in the foamed material dominated when w was greater than 9.05 wt%. The effective rate of the PBA is also related to the states of gasification and condensation when they reach equilibrium. The properties of the PBA itself determine the overall efficiency, while the balance between the gasification and condensation processes of the PBA further leads to a regular change in efficiency with respect to w around the overall average level

High Power All-Fiber Supercontinuum System Based on Graded-Index Multimode Fibers

An all-fiber supercontinuum source based on graded-index multimode fibers is reported. The supercontinuum source is based on a homemade mode-locked oscillator and a three-stage picosecond amplifier, which obtained the supercontinuum by a graded-index multimode fiber. The laser output with a spectral range of 480–2440 nm, an average power of 25 W, and a repetition frequency of 8.27 MHz is obtained. To the best of our knowledge, this is the highest average power for generating a supercontinuum with an all-fiber structure based on the graded-index fiber. The effects of GRIN fiber length and different pump peak powers on the supercontinuum generation are also verified. The results showed that the graded-index multimode fiber can effectively obtain a supercontinuum with high power

FAT1 upregulation is correlated with an immunosuppressive tumor microenvironment and predicts unfavorable outcome of immune checkpoint therapy in non-small cell lung cancer

Background: Previous studies found that FAT1 was recurrently mutated and aberrantly expressed in multiple cancers, and the loss function of FAT1 promoted the formation of cancer-initiating cells in several cancers. However, in some types of cancer, FAT1 upregulation could lead to epithelial-mesenchymal transition (EMT). The role of FAT1 in cancer progression, which appears to be cancer-type-specific, is largely unknown. Methods: QRT-PCR and immunochemistry were used to verify the expression of FAT1 in non-small cell lung cancer (NSCLC). QRT-PCR and Western blot were used to detect the influence of siFAT1 knockdown on the expression of potential targets of FAT1 in NSCLC cell lines. GEPIA, KM-plotter, CAMOIP, and ROC-Plotter were used to evaluate the association between FAT1 and clinical outcomes based on expression and clinical data from TCGA and immune checkpoint inhibitors (ICI) treated cohorts. Results: We found that FAT1 upregulation was associated with the activation of TGF-β and EMT signaling pathways in NSCLC. Patients with a high FAT1 expression level tend to have a poor prognosis and hard to benefit from ICI therapy. Genes involved in TGF-β/EMT signaling pathways (SERPINE1, TGFB1/2, and POSTN) were downregulated upon knockdown of FAT1. Genomic and immunologic analysis showed that high cancer-associated fibroblast (CAF) abundance, decreased CD8+ T cells infiltration, and low TMB/TNB were correlated with the upregulation of FAT1, thus promoting an immunosuppressive tumor microenvironment (TME) which influence the effect of ICI-therapy. Conclusion: Our findings revealed the pattern of FAT1 upregulation in the TME of patients with NSCLC, and demonstrated its utility as a biomarker for unfavorable clinical outcomes, thereby providing a potential therapeutic target for NSCLC treatment

Screening and validation of prognostic indicator genes in the progression of HBV related hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a rapidly progressing cancer and the main reason for cancer-related deaths. There are numerous risk factors for HCC, of which hepatitis B virus (HBV) infection is recognized as a high risk. HBV infection is accompanied by gene integration, and the liver has undergone the process of continuous and repeated damage and repair. However, predictive factors of HBV-related HCC are still limited, and the prognostic regulatory genes have not been fully elucidated. This study aims to use bioinformatics analysis to search potential prognostic genes of HBV-related HCC. Based on the full utilization of the GEO database, we screened out prognostic-related genes by performing systematic Kaplan-Meier survival analysis. The differences of the transcriptional information and protein expression were verified in the TCGA and HPA databases respectively, and the clinical characteristics of the screened genes were described by the boxplot. Five prognostic-related genes we screened, including CDK1, MAD2L1, SPP1, TYMS, and CCNA2, are strongly linked with poor prognosis in HBV-related HCC. The five prognostic-related genes have realistic clinical significance and potential as prognostic markers, and may provide new directions for basic research and clinical diagnosis

Multidimensional landscape of non‐alcoholic fatty liver disease‐related disease spectrum uncovered by big omics data: Profiling evidence and new perspectives

Abstract Characterized by hepatic lipid accumulation, non‐alcoholic fatty liver disease (NAFLD) is a multifactorial metabolic disorder that could promote the progression of non‐alcoholic steatohepatitis (NASH), cirrhosis, and hepatocellular carcinoma (HCC). Benefiting from recent advances in omics technologies, such as high‐throughput sequencing, voluminous profiling data in HCC‐integrated molecular science into clinical medicine helped clinicians with rational guidance for treatments. In this review, we conclude the majority of publicly available omics data on the NAFLD‐related disease spectrum and bring up new insights to inspire next‐generation therapeutics against this increasingly prevalent disease spectrum in the post‐genomic era

Investigations of robotics and laparoscopy in minimally invasive hepatectomy

The concept of minimally invasive liver surgery has been widely accepted due to the advantages of fast recovery. Robotic hepatectomy is different from laparoscopic hepatectomy due to its fixed joint instruments, operation mode and magnification. This manuscript aims to compare the safety and efficacy of robotic and laparoscopic hepatectomy in the treatment of liver diseases. In this manuscript, we retrospectively studied 246 patients (143 with robotic hepatectomy and 103 with laparoscopic hepatectomy). The clinical basic information, operation time, intraoperative bleeding, conversion to laparotomy, postoperative hospital stay, anal exhaust time, postoperative eating time, ambulation time, and postoperative hematological indicators were analyzed. Robotic hepatectomy has certain advantages in shortening the length of hospital stay (4.9 ​± ​1.3 VS 6.8 ​± ​2.2 days, P ​< ​0.001) and reducing intraoperative bleeding (174.8 ​± ​142.7 VS 341.2 ​± ​187.3 ​ml, P ​< ​0.001) compared with laparoscopic hepatectomy. It is demonstrated that robotic hepatectomy is an outstanding surgical strategy for clinical application

Identification of molecular subgroups and establishment of risk model based on the response to oxidative stress to predict overall survival of patients with lung adenocarcinoma

Abstract Objective Oxidative stress is associated with the occurrence and development of lung cancer. However, the specific association between lung cancer and oxidative stress is unclear. This study aimed to investigate the role of oxidative stress in the progression and prognosis of lung adenocarcinoma (LUAD). Methods The gene expression profiles and corresponding clinical information were collected from GEO and TCGA databases. Differentially expressed oxidative stress-related genes (OSRGs) were identified between normal and tumor samples. Consensus clustering was applied to identify oxidative stress-related molecular subgroups. Functional enrichment analysis, GSEA, and GSVA were performed to investigate the potential mechanisms. xCell was used to assess the immune status of the subgroups. A risk model was developed by the LASSO algorithm and validated using TCGA-LUAD, GSE13213, and GSE30219 datasets. Results A total of 40 differentially expressed OSRGs and two oxidative stress-associated subgroups were identified. Enrichment analysis revealed that cell cycle-, inflammation- and oxidative stress-related pathways varied significantly in the two subgroups. Furthermore, a risk model was developed and validated based on the OSRGs, and findings indicated that the risk model exhibits good prediction and diagnosis values for LUAD patients. Conclusion The risk model based on the oxidative stress could act as an effective prognostic tool for LUAD patients. Our findings provided novel genetic biomarkers for prognosis prediction and personalized clinical treatment for LUAD patients