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Cytotoxic T lymphocytes (CTLs) are important for the recognition of the hepatitis B virus (HBV), mediating immunoprotective mechanisms and determining the clinical outcome following HBV infection. CTLs recognize the invading virus via the T cell receptor (TCR). The aim of the current study was to investigate the variability of TCR in lymphocytes from patients with chronic hepatitis B and whether TCR genomic recombination is regulated by the current treatment strategies. Peripheral blood mononuclear cells (PBMCs) were isolated from patients with chronic hepatitis B and high‑throughput sequencing was performed to analyze the gene expression diversity of β chain complementarity determining region. High‑throughput sequencing produced ~380,000 reads. The sequences of V and J family mRNAs of the β chain V area were analyzed and databases were created for all 30 V family and J family genes. Using the Basic Local Alignment Search Tool, 15 genes were identified to be upregulated in the samples following treatment. Among them, the expression of T cell receptor β variable 28 (TRBV28)_T cell receptor β joining 1‑5 (TRBJ1.5) and TRBV6_TRBJ2.10 were significantly different in the treated samples compared with samples taken prior to treatment. Genomic recombination patterns of TRBV and TRBJ of the β chain V area were observed to be different in the samples following treatment. The data of the current study demonstrated that the genomic rearrangement of the V and J segments of TCR β chain V area may be associated with the chronic progression of HBV and impact on treatment efficacy.

Background Aberrant expression of up-regulated long non-coding RNA [LncRNA highly upregulated in liver cancer (HULC)] has been observed to play an important regulatory role in the development of multiple human diseases. However, the molecular mechanism underlying the role of HULC and miR-377-5p in HCC needs to be urgently explored. Methods The mRNA and protein expression levels of HULC were detected by quantitative real-time polymerase chain reaction (qRT-PCR) and western blot in hepatocellular carcinoma (HCC) cell line HB611, HepG2 and H22, respectively. HULC-shRNA was transfected into HepG-2 cells, which were randomly divided into the control, shRNA-NC, and sh-HULC groups. The correlation between HULC and miR-377-5p was analyzed by performing a luciferase reporter assay. The targeting relationship between miR-377-5p and hypoxia-inhibitory factor-1α (HIF-1α) was also investigated using a luciferase reporter assay. Sh-HULC and miR-377-5p inhibitors were transfected either alone or together into HepG2 cells, and which were divided into the control group, the sh-HULC group, the miR-377-5p inhibitor, and the sh-HULC + inhibitor group for subsequent experiments. HepG2 cell proliferation and invasion were measured by 5-Ethynyl-2-Deoxyuridine (EdU) staining and Transwell invasion assay, respectively. Western plot was carried out to detect the protein expression levels of Ki67, PCNA, E-cadherin, and N-cadherin. Tumor xenograft mouse models were established to confirm the effect of HULC down-regulation on the development of HCC in vivo. Results The mRNA and protein expression levels of HULC were markedly increased, whereas the mRNA expression levels of miR-377-5p were decreased in HCC cell lines. HepG2 cell proliferation and invasion were suppressed in the Sh-HULC group, while miR-377-5p showed the opposite. Further experiments exhibited that miR-377-5p was targeted by HULC, and an negative correlation between HULC and miR-377-5p was observed. Importantly, the in vivo experiments indicated that down-regulation of HULC could inhibit tumor growth. Taken together, our research demonstrated that down-regulation of HULC plays an anti-cancer role through restrainingHepG2 cell proliferation and invasion. Conclusions In summary, our in vitro and in vivo findings confirmed HULC to play a role in the progression of HCC, with the underlying mechanism possibly involving the miR-377-5p/HIF-1α pathway.

We aimed to evaluate the specificity of 12 tumor markers related to colon carcinoma and identify the most sensitive index. Bhattacharyya distance was used to evaluate the index. Then, different index combinations were used to establish a support vector machine (SVM) diagnosis model of malignant colon carcinoma. The accuracy of the model was checked. High accuracy was assumed to indicate the high specificity of the index. The Bhattacharyya distances of carcinoembryonic antigen, neuron-specific enolase, alpha-feto protein, and CA724 were the largest, and those of CYFRA21-І, CA125, and UGT1A83 were the second largest. The specificity of the combination of the above seven indexes was higher than that of other combinations, and the accuracy of the established SVM identification model was high. Using Bhattacharyya distance detection and establishing an SVM model based on different serum marker combinations can increase diagnostic accuracy, providing a theoretical basis for application of mathematical models in cancer diagnosis.