GPC3 fused to an alpha epitope of HBsAg acts as an immune target against hepatocellular carcinoma associated with hepatitis B virus

Immune gene prognostic signature for disease free survival of gastric cancer: Translational research of an artificial intelligence survival predictive system

The progress of artificial intelligence algorithms and massive data provide new ideas and choices for individual mortality risk prediction for cancer patients. The current research focused on depict immune gene related regulatory network and develop an artificial intelligence survival predictive system for disease free survival of gastric cancer.

Multi-task logistic regression algorithm, Cox survival regression algorithm, and Random survival forest algorithm were used to develop the artificial intelligence survival predictive system.

Nineteen transcription factors and seventy immune genes were identified to construct a transcription factor regulatory network of immune genes. Multivariate Cox regression identified fourteen immune genes as prognostic markers. These immune genes were used to construct a prognostic signature for gastric cancer. Concordance indexes were 0.800, 0.809, and 0.856 for 1-, 3- and 5- year survival. An interesting artificial intelligence survival predictive system was developed based on three artificial intelligence algorithms for gastric cancer. Gastric cancer patients with high risk score have poor survival than patients with low risk score.

The current study constructed a transcription factor regulatory network and developed two artificial intelligence survival prediction tools for disease free survival of gastric cancer patients. These artificial intelligence survival prediction tools are helpful for individualized treatment decision.

Integrated Bioinformatics Analysis of the Clinical Value and Biological Function of ATAD2 in Hepatocellular Carcinoma

ATPase family AAA domain-containing protein 2 (ATAD2), a chromatin regulator and an oncogenic transcription cofactor, is frequently overexpressed in many cancers, particularly in hepatocellular carcinoma (HCC). By integrating open-access online mRNA datasets and our institutional tissue data on HCC, the clinical role and functions of ATAD2 were analyzed by bioinformatic algorithms. We systematically examined ATAD2 expression in HCC based on a large sample population, integrating data from our institution and the GEO, Oncomine, and TCGA datasets. Aberrant ATAD2 expression related to pathways was identified by bioinformatic algorithms. The effects of ATAD2 downregulation on the cycle cell were also determined. A pooled analysis from 28 datasets indicated that ATAD2 overexpression was found in HCC (SMD = 8.88, 95% CI: 5.96–11.81, P < 0.001) and was correlated with poor survival. Subgroup analysis of Asian patients with a serum alpha-fetoprotein (AFP) concentration < 200 ng/ml in stage I + II showed that the ATAD2-high group had a more unfavorable overall survival (OS) rate than the ATAD2-low group. The receiver operating characteristic curve indicated that the efficiency of ATAD2 for HCC diagnosis was considerable (area under the curve = 0.89, 95% CI: 0.86–0.91). Functional analysis based on bioinformatic algorithms demonstrated that ATAD2 participates in cell division, mitotic nuclear division, DNA replication, repair, and cell cycle processes. ATAD2 knockout in HCC cells downregulated cyclin C and cyclin D1 protein levels and resulted in G1/S phase arrest in vitro. The kinesin family member C1 (KIFC1), shugoshin 1 (SGO1), GINS complex subunit 1 (GINS1), and TPX2 microtubule nucleation factor (TPX2) genes were closely related to ATAD2 upregulation. ATAD2 may interact with TTK protein kinase (TTK) to accelerate HCC carcinogenesis. ATAD2 plays a vital role in HCC carcinogenesis by disturbing the interaction between chromatin proteins and DNA. Targeting ATAD2 represents a promising method for the development of therapeutic treatments for cancer.

Tackling hepatitis B virus-associated hepatocellular carcinoma--the future is now

Hepatocellular carcinoma (HCC) is one of the most lethal and prevalent cancers in many developing countries including India. Among the various etiological factors being implicated in the cause of HCC, the most important cause, however, is hepatitis B virus (HBV) infection. Among all HBV genes, HBx is the most critical carcinogenic component, the molecular mechanisms of which have not been completely elucidated. Despite its clinical significance, there exists a very elemental understanding of the molecular, cellular, and environmental mechanisms that drive disease pathogenesis in HCC infected with HBV. Furthermore, there are only limited therapeutic options, the clinical benefits of which are insignificant. Therefore, the quest for novel and effective therapeutic regimen against HBV-related HCC is of paramount importance. This review attempts to epitomize the current state of knowledge of this most common and dreaded liver neoplasm, highlighting the putative treatment avenues and therapeutic research strategies that need to be implemented with immediate effect for tackling HBV-related HCC that has plagued the medical and scientific fraternity for decades. Additionally, this review proposes a novel "five-point" management algorithm for HBV-related HCC apart from portraying the unmet needs, principal challenges, and scientific perspectives that are relevant to controlling this accelerating global health crisis.