Identifying an Eight-Gene Signature to Optimize Overall Survival Prediction of Esophageal Adenocarcinoma Using Bioinformatics Analysis of ceRNA Network

Molecular characteristics and multivariate survival analysis of 43 patients with locally advanced or metastatic esophageal squamous cell carcinoma

Background

Esophageal cancer (EC) is an aggressive malignant tumor with poor prognosis and high incidence. It is the sixth leading cause of cancer-related death in the world, and the 5-year overall survival (OS) rate is only 12-20%. The rapid development of next-generation sequencing (NGS) has provided powerful help for the treatment and management of EC patients.

Methods

Tumor tissue and blood samples of 43 Chinese patients with nonsurgical esophageal squamous cell carcinoma (ESCC) were sequenced using a 425 gene-panel. Genomic profiling was explored and and the Cox proportional hazards model was used to analyze the correlations between gene or signaling pathway alterations and prognosis.

Results

In this study, the most common mutated genes were TP53 (90.5%), CCND1 (45.2%), FGF19 (38.1%), NOTCH1 (26.2%), PI3KCA (21.4%) and CDKN2A (19%). Among these mutations, PI3KCA and NOTCH1 showed mutual exclusion to some extent. In the univariate model, mutations in NOTCH1, CBLB and TSC2 genes and tumor mutation burden (TMB) ≥7 were independent biomarkers of OS. NOTCH1 (P=0.007, HR =2.87), CBLB (P=0.011, HR =4.68) and TSC2 (P=0.024, HR =3.7) were significantly associated with poorer OS, and patients with TMB ≥7 had longer OS (P=0.151, HR =0.31). In addition, patients who carried alteration in NOTCH signaling pathway had reduced OS (P=0.014, HR =2.54).

Conclusions

NOTCH1, CBLB and TSC2 alterations were found to be potential indicators of poor prognosis in patients with ESCC. TMB was also positively correlated with the OS of ESCC patients, providing valuable insights for their treatment strategies.

Impacts of β-1, 3-N-acetylglucosaminyltransferases (B3GNTs) in human diseases

Glycosylation modification of proteins is a common post-translational modification that exists in various organisms and has rich biological functions. It is usually catalyzed by multiple glycosyltransferases located in the Golgi apparatus. β-1,3-N-acetylglucosaminyltransferases (B3GNTs) are members of the glycosyltransferases and have been found to be involved in the occurrence and development of a variety of diseases including autoimmunity diseases, cancers, neurodevelopment, musculoskeletal system, and metabolic diseases. The functions of B3GNTs represent the glycosylation of proteins is a crucial and frequently life-threatening step in progression of most diseases. In this review, we give an overview about the roles of B3GNTs in tumor, nervous system, musculoskeletal and metabolic diseases, describing the recent results about B3GNTs, in order to provide a research direction and exploration value for the prevention, diagnosis and treatment of these diseases.

Prognostic Roles of ceRNA Network-Based Signatures in Gastrointestinal Cancers

Gastrointestinal cancers (GICs) are high-incidence malignant tumors that seriously threaten human health around the world. Their complexity and heterogeneity make the classic staging system insufficient to guide patient management. Recently, competing endogenous RNA (ceRNA) interactions that closely link the function of protein-coding RNAs with that of non-coding RNAs, such as long non-coding RNA (lncRNA) and circular RNA (circRNA), has emerged as a novel molecular mechanism influencing miRNA-mediated gene regulation. Especially, ceRNA networks have proven to be powerful tools for deciphering cancer mechanisms and predicting therapeutic responses at the system level. Moreover, abnormal gene expression is one of the critical breaking events that disturb the stability of ceRNA network, highlighting the role of molecular biomarkers in optimizing cancer management and treatment. Therefore, developing prognostic signatures based on cancer-specific ceRNA network is of great significance for predicting clinical outcome or chemotherapy benefits of GIC patients. We herein introduce the current frontiers of ceRNA crosstalk in relation to their pathological implications and translational potentials in GICs, review the current researches on the prognostic signatures based on lncRNA or circRNA-mediated ceRNA networks in GICs, and highlight the translational implications of ceRNA signatures for GICs management. Furthermore, we summarize the computational approaches for establishing ceRNA network-based prognostic signatures, providing important clues for deciphering GIC biomarkers.

Identification of candidate genes associated with bacterial and viral infections in wild boars hunted in Tuscany (Italy)

Wild boar (Sus scrofa L.) is one of the large mammals most spread worldwide, highly adaptable, and its population rapidly increased in many areas in Europe, including Italy, where Tuscany is considered particularly suitable for wild boar. Wild boars are potential hosts for different etiological agents, such as Brucella spp., Leptospira spp. and Pseudorabies virus and they can contribute to maintain and/or to disseminate some bacterial or viral pathogens to humans and domestic animals, above all-in free-range farms. In order to identify hypothetical genomic regions associated with these infection diseases, 96 samples of wild boars hunted in Tuscany during the 2018-2019 and 2019-2020 hunting seasons were considered. Diagnosis was achieved by serological tests and 42 Pseudorabies, 31 Leptospira and 15 Brucella positive animals were identified. All animals were genotyped with Geneseek Genomic Profiler Porcine HD (70 k) and a genome-wide scan was then performed. Significant markers were highlighted for Pseudorabies (two SNPs), Brucella (seven SNPs), and Leptospira (four SNPs) and they were located within, or nearby, 29 annotated genes on chromosome 6, 9, 12, 13, 14 and 18. Eight genes are implicated in viral (SEC14L1, JMJD6, SRSF2, TMPRSS2, MX1, MX2) or bacterial (COL8A1, SPIRE1) infections, seven genes (MFSD11, METTL23, CTTNBP2, BACE2, IMPA2, MPPE1 and GNAL) are involved in mental disorders and one gene (MGAT5B) is related to the Golgi complex. Results presented here provide interesting starting points for future research, validation studies and fine mapping of candidate genes involved in bacterial and viral infections in wild boar.

LAMP2 as a Biomarker Related to Prognosis and Immune Infiltration in Esophageal Cancer and Other Cancers: A Comprehensive Pan-Cancer Analysis

Esophageal cancer (ESCA) is a common malignant tumor with poor prognosis. Accumulating evidence indicates an important role of lysosomal-associated membrane protein 2 (LAMP2) in the progression and development of various cancers. In this study, we obtained RNA-sequencing raw count data and the corresponding clinical information for ESCA samples from The Cancer Genome Atlas and Gene Expression Omnibus databases. We comprehensively investigated the expression and prognostic significance of LAMP2 and relationships between LAMP2 expression and prognosis, different clinicopathological parameters, and immune cell infiltration in ESCA. We also obtained the differentially expressed genes between the high LAMP2 expression and low LAMP2 expression groups in ESCA and performed a functional enrichment analysis of the 250 linked genes most positively related to LAMP2 expression. Moreover, we performed the pan-cancer analysis of LAMP2 to further analyze the role of LAMP2 in 25 commonly occurring types of human cancer. We also verified and compared the expression of LAMP2 in 40 samples of human ESCA tissue and adjacent tissues. The results indicated that LAMP2 expression was significantly upregulated in ESCA and various human cancers. In addition, LAMP2 expression was associated with certain clinicopathological parameters, prognosis, and immune infiltration in ESCA and the other types of cancer. Our study represents a comprehensive pan-cancer analysis of LAMP2 and supports the potential use of the modulation of LAMP2 in the management of ESCA and various cancers.

Prognostic Implications of Six Altered Genes in Asian Non-Surgical Esophageal Carcinoma Patients Treated with Chemoradiotherapy

Background

Esophageal cancer (EC), especially esophageal squamous cell carcinoma, remained as one of the most aggressive tumors in China with a five-year survival rate of around 40%. Molecular characteristics through next-generation sequencing are becoming an emerging method in identifying prognostic biomarkers for better treatment management for EC patients.

Methods

Targeted next-generation sequencing using a 422-gene pan-cancer panel was performed with tumor tissue samples from a total of 69 Asian non-surgical esophageal carcinoma patients (AEC) treated with chemoradiotherapy. A TCGA cohort of 143 EC patients and another Asian ESCC cohort of 47 patients were employed for validation.

Results

In the AEC cohort, alterations in TP53 (94.2%) and NOTCH1 (55.1%) were the two most frequently observed alterations, whereas in the TCGA cohort, only TP53 alterations were observed at a high ratio (85.3%). Co-amplifications of FGF19 and CCND1 were found at a similar ratio in both cohorts. Multiple alterations in the DNA damage pathway were identified but not associated with overall survival in AEC. Using univariate and multivariate Cox regression analyses, six gene alterations including YAP1 amplification, RB1 alteration, BAP1 mutation, MYC amplification, WRN mutation, and BRIP1 mutation were identified as adverse prognostic factors in the AEC cohort. A Cox proportional hazard model based on the six prognosis-related genes was constructed and showed the ability in distinguishing EC patients with poorer disease outcomes in AEC and two validation cohorts.

Conclusion

Six gene alterations were found to be potential unfavorable prognostic markers that might provide guidance in the treatment management for EC patients.

Identification of a Ten-Gene Signature of DNA Damage Response Pathways with Prognostic Value in Esophageal Squamous Cell Carcinoma

Molecular prognostic signatures are critical for treatment decision-making in esophageal squamous cell cancer (ESCC), but the robustness of these signatures is limited. The aberrant DNA damage response (DDR) pathway may lead to the accumulation of mutations and thus accelerate tumor progression in ESCC. Given this, we applied the LASSO Cox regression to the transcriptomic data of DDR genes, and a prognostic DDR-related gene expression signature (DRGS) consisting of ten genes was constructed, including PARP3, POLB, XRCC5, MLH1, DMC1, GTF2H3, PER1, SMC5, TCEA1, and HERC2. The DRGS was independently associated with overall survival in both training and validation cohorts. The DRGS achieved higher accuracy than six previously reported multigene signatures for the prediction of prognosis in comparable cohorts. Furtherly, a nomogram incorporating DRGS and clinicopathological features showed improved predicting performance. Taken together, the DRGS was identified as a novel, robust, and effective prognostic indicator, which may refine the scheme of risk stratification and management in ESCC patients.