Identification and verification of a prognostic autophagy-related gene signature in hepatocellular carcinoma.

This study aimed to investigate the potential of autophagy-related genes (ATGs) as a prognostic signature for HCC and explore their relationships with immune cells and immune checkpoint molecules. A total of 483 samples were collected from the GEO database (n = 115) and The Cancer Genome Atlas (TCGA) database (n = 368). The GEO dataset was used as the training set, while the TCGA dataset was used for validation. The list of ATGs was obtained from the human autophagy database (HADB). Using Cox regression and LASSO regression methods, a prognostic signature based on ATGs was established. The independent use of this prognostic signature was tested through subgroup analysis. Additionally, the predictive value of this signature for immune-related profiles was explored. Following selection through univariate Cox regression analysis and iterative LASSO Cox analysis, a total of 11 ATGs were used in the GEO dataset to establish a prognostic signature that stratified patients into high- and low-risk groups based on survival. The robustness of this prognostic signature was validated using an external dataset. This signature remained a prognostic factor even in subgroups with different clinical features. Analysis of immune profiles revealed that patients in the high-risk group exhibited immunosuppressive states characterized by lower immune scores and ESTIMATE scores, greater tumour purity, and increased expression of immune checkpoint molecules. Furthermore, this signature was found to be correlated with the infiltration of different immune cell subpopulations. The results suggest that the ATG-based signature can be utilized to evaluate the prognosis of HCC patients and predict the immune status within the tumour microenvironment (TME). However, it is important to note that this study represents a preliminary attempt to use ATGs as prognostic indicators for HCC, and further validation is necessary to determine the predictive power of this signature.

PPTPS: Building privacy-preserving auditable service with traceable timeliness for public cloud storage.

Many works are designed to improve efficiency or enhance security and privacy of publicly-auditable cloud storage. However, building timeliness for cloud storage has not been well studied. Few works presented time-sensitive cloud storage and only focused on specific issues, such as the earliest creation time of files or resistance against a procrastinating auditor. Therefore, there leaves an absence of building traceable timeliness for publicly-auditable cloud storage. In this paper, we propose a solution PPTPS to build Privacy-Preserving auditable service with Traceable timeliness for Public cloud Storage. First, we use the security properties of the blockchain to provide a time-stamp for each phase. It enables the timeliness of cloud storage. Second, we construct efficient publicly-verifiable cloud storage. Third, a customized random mask solution is proposed to prevent privacy leakage during the auditing phase. Moreover, we formally proved the security of PPTPS. At last, experimental results demonstrate that PPTPS is economically sound and technically viable.

Prognostic Autophagy-Related Genes of Gastric Cancer Patients on Chemotherapy.

Background: Chemotherapy resistance based on fluorouracil and cisplatin is one of the most encountered postoperative clinical problems in patients diagnosed with gastric cancer (GC), resulting in poor prognosis. Aim of the Study: This study aimed to combine autophagy-related genes (ARGs) to investigate the susceptibility patients with GC to postoperative chemotherapy. Methods: Based on The Cancer Genome Atlas (TCGA) database, gene expression data for GC patients undergoing chemotherapy were integrated and analyzed. Prognostic genes were screened based on univariate and multivariate analysis regression analysis. Subjects were divided into high-risk and low-risk groups according to the median risk score. Kaplan-Meier method was used to evaluate OS and DFS. The accuracy of the prediction was determined by the subject operating characteristic curve analysis. In addition, stratified analyses based on different clinical variables was performed to assess the correlation between risk scores and clinical variables. Quantitative real-time (qRT) PCR was used to verify the expression of CXCR4 in GC tissues and cell lines. Results: A total of nine ARGs related to the prognosis of chemotherapy patients were screened out. Compared with normal gastric mucosa cell, CXCR4 showed elevated expression in GC and was significantly associated with survival. Based on GEO and TCGA databases, the model accurately predicted DFS and OS after chemotherapy. Conclusion: This study established prognostic markers based on nine genes, predicting that ARGs are related to chemotherapy susceptibility of GC patients, which can provide better individualized treatment regimens for clinical practice.

PER1 Is a Prognostic Biomarker and Correlated With Immune Infiltrates in Ovarian Cancer.

Background: Period circadian protein homolog 1 (PER1) is an important component of the biorhythm molecular oscillation system and plays an important part in the development and progression of mammalian cancer. However, the correlations of PER1 with prognosis and tumor-infiltrating lymphocytes in ovarian cancer (OV) remain unclear. Methods: The Oncomine and TIMER databases were used to examine the expression of PER1 in OV. Kaplan-Meier Plotter and PrognoScan were used to evaluate the relationship between PER1 and prognosis. Kaplan-Meier Plotter was used to analyze the relationships between PER1 and clinicopathological features of OV patients. The relationship between PER1 expression and immune infiltration in OV was investigated using the TIMER database and CIBERSORT algorithm. The STRING database was used to analyze PER1-related protein functional groups, the GeneMANIA online tool was used to analyze gene groups with similar functions to those of PER1, and Network Analyst was used to identify transcription factors that regulate PER1. The correlation between PER1 and immunoinvasion of OV was analyzed using TIMER. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was performed to detect PER1 expression. Results: PER1 was differentially expressed in different cancer tissues, and its expression in various OV subtypes was lower than that in normal ovarian tissue. OV patients with low PER1 expression had a reduced overall survival rate. Decreased PER1 expression in stage 1 and stage 1+2 OV patients was related to poor prognosis, while increased PER1 expression in stage 3+4 patients and TP53 mutation were related to poor overall survival and progression-free survival. We identified eight genes whose expression was strongly correlated with that of PER1, as well as four transcription factors that regulate PER1. In OV, PER1 expression levels were positively correlated with infiltration levels of cells including neutrophils, regulatory T cells, and M2 macrophages, and closely related to a variety of immune markers. Reduced expression of PER1 was significantly associated with poor overall survival. Conclusion: These findings suggest that PER1 could be used as a prognostic biomarker to determine prognosis and immune infiltration in OV patients.

Comparative investigation of early-onset gastric cancer.

Early-onset gastric cancer (EOGC) is a serious social burden. For patients with EOGC, typically considered as those aged <45 years, the underlying cause of the disease remains unclear. In addition, several misunderstandings of EOGC remain in clinical practice. Upon diagnosis, numerous patients with EOGC are already at an advanced stage (stage IV) of the disease and are unable to benefit from treatment. Moreover, several conclusions and data obtained from different EOGC studies appear to be to contradictory. The literature indicates that the incidence of EOGC is gradually rising, and that EOGC differs from traditional and familial gastric cancer in terms of clinicopathological characteristics. Patients with EOGC typically exhibit low survival rates, poor prognosis, rapid disease progression, a low degree of differentiation (signet-ring cell tumors are common) and rapid lymph node and distant metastasis, among other characteristics. The molecular genetic mechanisms of EOGC are also significantly different from those of traditional gastric cancer. An improved definition of EOCG may provide a reference for clinical diagnosis and treatment, and clear guidelines may serve as a basis for more accurate diagnosis and the development of effective treatment strategies.