Background Esophageal squamous cell carcinoma (ESCC) is one of the most lethal malignancies with poor prognosis. Cancer-testis genes (CTGs) have been vigorously pursued as targets for cancer immunotherapy, but the expressive patterns and functional roles of CTGs remain unclear in ESCC. Methods A systematic screening strategy was adopted to screen CTGs in ESCC by integrating multiple public databases and RNA expression microarray data from 119 ESCC subjects. For the newly identified ESCC prognosis-associated CTGs, an independent cohort of 118 patients with ESCC was recruited to validate the relationship via immunohistochemistry. Furthermore, functional assays were performed to determine the underlying mechanisms. Findings 21 genes were recognized as CTGs, in particular, CDCA5 was aberrantly upregulated in ESCC tissues and significantly associated with poor prognosis (HR = 1.85, 95%CI: 1.14–3.01, P = .013). Immunohistochemical staining confirmed that positive CDCA5 expression was associated with advanced TNM staging and a shorter overall survival rate (45.59% vs 28.00% for CDCA5−/+ subjects, P = 1.86 × 10 −3 ). H3K27 acetylation in CDCA5 promoter might lead to the activation of CDCA5 during ESCC tumorigenesis. Functionally, in vitro assay of gain- and loss-of-function of CDCA5 suggested that CDCA5 could promote ESCC cells proliferation, invasion, migration, apoptosis resistance and reduce chemosensitivity to cisplatin. Moreover, in vivo assay showed that silenced CDCA5 could inhibit tumor growth. Mechanistically, CDCA5 knockdown led to an arrest in G2/M phase and changes in the expression of factors that played fundamental roles in the cell cycle pathway. Interpretation CDCA5 contributed to ESCC progression and might serve as an attractive target for ESCC immunotherapy. Fund This work was supported by the Natural Science Foundation of Jiangsu Province (No. BK20181083 and BK20181496), Jiangsu Top Expert Program in Six Professions (No. WSW-003 and WSW-007), Major Program of Science and Technology Foundation of Jiangsu Province (No. BE2016790 and BE2018746), Jiangsu Medical Young Talent Project (No. QNRC2016566), the Program of Jiangsu Medical Innovation Team (No. CXTDA2017006), Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX18_1487) and Jiangsu Province 333 Talents Project (No. BRA2017545).

Background:In recent years, long non-coding RNAs (lncRNAs) have been shown to be a novel class of regulators of cancer biological processes. Although lncRNAs are dysregulated in numerous cancer types, limited data are available on the expression profiles and potential functions of lncRNAs in lung adenocarcinoma (LUAD). This study evaluated the expression and biological roles of lncRNA SOX21 antisense RNA 1 (SOX21-AS1) in LUAD. Methods: Quantitative reverse transcription PCR (qRT-PCR) was performed to detect the expression levels of SOX21-AS1 in 68 pairs of LUAD tissues and corresponding non-tumor tissues. The effect of SOX21-AS1 on proliferation was evaluated by MTT, colony formation, EdU assays, flow-cytometric analysis and in vivo tumor formation assays. Real-time PCR, western-blot and immunohistochemistry were used to evaluate the mRNA and protein expression of p57. Results: Higher expression levels of SOX21-AS1 positively correlated with tumor size and advanced tumor-node-metastasis (TNM) stage. Multivariate analyses indicated that SOX21-AS1 expression could serve as an independent prognostic factor for overall survival of LUAD. Furthermore, knockdown of SOX21-AS1 significantly inhibited LUAD cell proliferation both in vitro and in vivo and induced cell cycle phase arrest and cell apoptosis. Importantly, through qRT-PCR and western blot analysis, we found that inhibition of SOX21-AS1 remarkably induced p57 expression. Conclusions: Collectively, our study demonstrates that SOX21-AS1 is involved in the development and progression of LUAD and that SOX21-AS1 may be a potential diagnostic factor as well as a target for new therapies for patients with LUAD.X. Lu, C. Huang and X. He contributed equally to this work.

Increasing evidence confirms that exosome-mediated transfer of microRNAs can influence cancer progression including tumor cell invasion, cell proliferation, and drug resistance via cell-cell communication. However, the potential role of exosomal-miR-1260b in lung adenocarcinoma (LAC) remains poorly understood.Thus, this study focused on investigating the function of exosomal-miR-1260b on cell invasion. Exosomal-miR-1260b was found to be higher in plasma of patients with LAC than that of healthy persons via quantitative real-time polymerase chain reaction assay. The sensitivity and specificity of exosomal-miR-1260b (cutoff point: 2.027) were 72% and 86%, and area under the curve of 0.845 (95% CI = 0.772-0.922). Elevated expression of miR-1260b in LAC tissues was positively correlated with exosomal-miR-1260b in plasma (r = .642, p < .05). Furthermore, ceramide biosynthesis regulated exosomal-miR-1260b secretion. Exosomemediated transfer of miR-1260b promoted A549 cell invasion and was still functional inside A549 cells. Moreover, exosomal-miR-1260b regulated Wnt/ β-catenin signaling pathway by inhibiting sFRP1 and Smad4. This study identified a new regulation mechanism involving in cell invasion by exosome-mediated tumorcell-to-tumor-cell communication. Targeting exosome-microRNAs may provide new insights into the diagnosis and treatment of LAC.

Copy number variations (CNVs) represent one of the most common genomic alterations. This study aimed to evaluate the roles of genes within highly aberrant genome regions in the prognosis of esophageal squamous cell cancer (ESCC). Exome sequencing data from 81 paired ESCC tissues were used to screen aberrant genomic regions. The associations between CNVs and gene expression were evaluated using gene expression data from the same individuals. Then, an RNA expression array profile from 119 ESCC samples was adopted for differential gene expression and prognostic analyses. Two independent ESCC cohorts with 315 subjects were further recruited to validate the prognostic value using immunohistochemistry tests. Finally, we explored the potential mechanism of our identified novel oncogene in ESCC. In total, 2003 genes with CNVs were observed, of which 76 genes showed recurrent CNVs in more than three samples. Among them, 32 genes were aberrantly expressed in ESCC tumor tissues and statistically correlated with CNVs. Strikingly, 4 (CTTN, SHANK2, INPPL1 and ANO1) of the 32 genes were significantly associated with the prognosis of ESCC patients. Patients with a positive expression of ANO1 had a poorer prognosis than ANO1 negative patients (overall survival rate: 42.91% versus 26.22% for ANO1−/+ samples, P < 0.001). Functionally, ANO1 promoted ESCC cell proliferation, migration and invasion by activating transforming growth factor-β pathway. Knockdown of ANO1 significantly inhibited tumor progression in vitro and in vivo. In conclusion, ANO1 is a novel oncogene in ESCC and may serve as a prognostic biomarker for ESCC.

Predictive prognostic markers for immunotherapy are crucial and desperately required for clinical precise medicine. This retrospective study aimed to assess the efficacy of anti-PD-1 (programmed cell death protein 1) treatment and find the therapeutic prognostic biomarkers in advanced biliary tract cancer (BTC). A total of 60 patients of advanced BTC who received at least one dose of anti-PD-1 therapy between June 2016 and October 2019 were recruited and followed up till April 2020. Systemic immuneinflammation index (SII) and neutrophils-to-lymphocytes ration (NLR) were obtained from the routine circulating hematologic analysis before treatment. Serum 45-Plex Panel cytokines were detected using multiplexed bead immunoassays. Logistic regression nomogram was used to construct the algorithm model for prognosis prediction.Of the 60 patients, the overall benefit rate (OBR) was 38.3%, the median progression free survival (PFS), and overall survival (OS) were 4.0 mo (95% confidence interval [CI]: 2.28-5.72) and 13.0 mo (95% CI: 8.05-17.95), respectively. High levels of SII (≥720), NLR (≥4.3) and cytokine IFN-inducible protein-10 (IP-10; ≥45 pg/ml) indicated worse OS. Those with high SII (≥720) and high IP-10 (≥45 pg/ml) also had shorter PFS. The nomogram algorithm combining above three independent factors (SII, IP-10, and macrophage inflammatory protein-1β) had better efficacy in predicting OBR. Our study offers a simple, affordable, and noninvasive method to help physicians predict therapeutic response in BTC patients receiving anti-PD-1 antibody treatment.

The involvement of miR-367 in lung cancer development remains unclear. In the present study, we analyzed the expression of miR-367 in tumor and adjacent tissue samples from 113 patients with non-small cell lung cancer (NSCLC) utilizing real-time PCR. miR-367 expression was significantly upregulated in the cancer tissues compared with non-cancer controls. Based on the median value of the miR-367 expression level, we divided the NSCLC patients into miR-367 high-expression and miR-367 low-expression groups. Overexpression of miR-367 was correlated with a poorer prognosis of NSCLC patients Chi-square (χ2) test showed a significant statistical correlation between tumor size, tumor stage, metastasis and miR-367 expression. Additionally, miR-367 expression was found to be negatively correlated with FBXW7 expression. Based on the above correlations, we performed a series of functional experiments to further confirm the effect of miR-367 on NSCLC. Our results indicated that miR-367 may be involved in the development and progression of NSCLC by promoting proliferation and invasion and impeding apoptosis in NSCLC cells. Furthermore, FBXW7 was identified as a potential target of miR-367, and FBXW7 silencing partially compromised the invasive, proliferative and migratory capacities in the cells with low miR-367 expression. Thus, the miR-367/FBXW7 axis may be involved in the development and progression of NSCLC and may be valuable as a therapeutic target for the treatment of human NSCLC, especially cancers with high invasive potential.

Background Hepatitis B virus (HBV) infection is one of the main leading causes of hepatocellular carcinoma (HCC) worldwide. However, how reverse transcriptase (rt) gene contributes to HCC progression remains uncertain. Methods We enrolled a total of 307 chronic hepatitis B (CHB) and 237 HBV related HCC patients from 13 medical centers. Sequence features comprised multi-dimensional attributes of rt nucleic acid and rt/s amino acid sequences. Machine learning (ML) models were used to establish HCC predictive algorithms. Model performances were tested in the training and independent validation cohorts using receiver operating characteristic (ROC) and calibration plots. Results Random forest (RF) model based on combined metrics (10 features) demonstrated the best predictive performances in both cross and independent validation (RFAUC=0.96, RFACC=0.90), irrespective of HBV genotypes and sequencing depth. Moreover, HCC risk score for individuals obtained from the RF model (AUC =0.966, 95% CI=0.922-0.989) outperformed α-fetal protein (AUC=0.713, 95% CI=0.632-0.784) in identifying HCC from CHB patients. Conclusions Our study provides evidence for the first time that HBV rt sequences contain vital HBV quasispecies features in predicting HCC. Integrating deep sequencing with feature extraction and ML models benefits the longitudinal surveillance of CHB and HCC risk assessment.

Alpha-fetoprotein (AFP)-negative hepatocellular carcinoma (ANHCC) patients account for more than 30% of the whole entity of HCC patients and are easily misdiagnosed. This three-phase study was designed to find and validate new ANHCC N-glycan markers which identified from The Cancer Genome Atlas (TCGA) database and noninvasive detection. Differentially expressed genes (DEGs) of N-glycan biosynthesis and degradation related genes were screened from TCGA database. Serum N-glycan structure abundances were analyzed using N-glycan fingerprint (NGFP) technology. Totally 1340 participants including ANHCC, chronic liver diseases and healthy controls were enrolled after propensity score matching (PSM). The Lasso algorithm was used to select the most significant N-glycan structures abundances.Three machine learning models [random forest (RF), support vector machine (SVM) and logistic regression (LR)] were used to construct the diagnostic algorithms. All 13N-glycan structure abundances analyzed by NGFP demonstrated significant and was enrolled by Lasso. Among the three machine learning models, LR algorithm demonstrated the best diagnostic performance for identifying ANHCC in training cohort