Clinical Implication and the Hereditary Factors of NM23 in Hepatocellular Carcinoma Based on Bioinformatics Analysis and Genome-Wide Association Study

Molecular profiling in the management of hepatocellular carcinoma

PURPOSE OF REVIEW

The purpose of this review is to both summarize the current knowledge of hepatocellular carcinoma molecular biology and to suggest a framework in which to prospectively translate this knowledge into patient care. This is timely as recent guidelines recommend increased use of these technologies to advance personalized liver cancer care.

RECENT FINDINGS

The main themes covered here address germline and somatic genetic alterations recently discovered in hepatocellular carcinoma, largely owing to next generation sequencing technologies, and nascent efforts to translate these into contemporary practice.

SUMMARY

Early efforts of translating molecular profiling to hepatocellular carcinoma care demonstrate a growing number of potentially actionable alterations. Still lacking are a consensus on what biomarkers and technologies to adopt, at what scale and cost, and how to integrate them most effectively into care.

Development and validation of a novel hypoxia-related signature for prognostic and immunogenic evaluation in head and neck squamous cell carcinoma

Hypoxia plays a critical role in head and neck squamous cell carcinoma (HNSCC) prognosis. However, till now, robust and reliable hypoxia-related prognostic signatures have not been established for an accurate prognostic evaluation in HNSCC patients. This article focused on establishing a risk score model to evaluate the prognosis and guide treatment for HNSCC patients. RNA-seq data and clinical information of 502 HNSCC patients and 44 normal samples were downloaded from The Cancer Genome Atlas (TCGA) database. 433 samples from three Gene Expression Omnibus (GEO) datasets were incorporated as an external validation cohort. In the training cohort, prognostic-related genes were screened and LASSO regression analyses were performed for signature establishment. A scoring system based on SRPX, PGK1, STG1, HS3ST1, CDKN1B, and HK1 showed an excellent prediction capacity for an overall prognosis for HNSCC patients. Patients were divided into high- and low-risk groups, and the survival status of the two groups exhibited a statistically significant difference. Subsequently, gene set enrichment analysis (GSEA) was carried out to explore the underlying mechanisms for the prognosis differences between the high- and low-risk groups. The tumor immune microenvironment was evaluated by CIBERSORT, ESTIMATE, TIDE, and xCell algorithm, etc. Then, we explored the relationships between this prognostic model and the levels of immune checkpoint-related genes. Cox regression analysis and nomogram plot indicated the scoring system was an independent predictor for HNSCC. Moreover, a comparison of predictive capability has been made between the present signature and existing prognostic signatures for HNSCC patients. Finally, we detected the expression levels of proteins encoded by six-HRGs via immunohistochemical analysis in tissue microarray. Collectively, a novel integrated signature considering both HRGs and clinicopathological parameters will serve as a prospective candidate for the prognostic evaluation of HNSCC patients.

Identification and Validation of an EMT-Related LncRNA Signature for HNSCC to Predict Survival and Immune Landscapes

Long noncoding RNAs (lncRNAs) are increasingly recognized as decisive factors in the progression of head and neck squamous cell carcinoma (HNSCC), and they participate in the epithelial–mesenchymal transformation (EMT) of HNSCC. LncRNAs are closely related to the prognosis of patients with HNSCC; thus, it is essential to identify EMT-related lncRNAs with prognostic value for HNSCC. The coexpression network of EMT-related lncRNAs was constructed using The Cancer Genome Atlas (TCGA). An EMT-related eight-lncRNA-based prognostic signature was constructed using LASSO Cox regression and Cox proportional hazards analyses. Univariate and multivariate analyses and stratified prognosis confirmed that the prognostic signature was an independent predictive factor. Subsequently, we performed immune cell infiltration analysis, gene set enrichment analysis (GSEA), and single-sample GSEA (ssGSEA) pathway enrichment analysis to uncover the potential molecular mechanisms of prognostic differences in the high- and low-risk groups. Next, we discussed the relationship between the prognostic signature and immune checkpoint-related genes, their TIDE scores, and the sensitivity of common chemotherapeutics. Finally, we further verified the expression differences in lncRNAs that were included in our signature via RT–qPCR in eighteen paired tissues. In summary, this prognostic signature provides powerful prognostic biomarkers for HNSCC and could serve as a predictor for the sensitivity of common chemotherapeutics and immunotherapy responses as well as providing a reference for further personalized treatment.

Psoriasis Susceptibility 1 Candidate 1 (PSORS1C1) Polymorphism is Associated with Autoimmune Thyroid Disease in a Chinese Han Population

BACKGROUND

Autoimmune thyroid disease (AITD) is an inherited, complex gene- and immune-related disorder that mainly includes Graves' disease (GD) and Hashimoto's thyroiditis (HT). Psoriasis susceptibility 1 candidate 1 (PSORS1C1) is a susceptibility gene associated with many autoimmune diseases, but its role in an individual's predisposition to AITD is unknown.

METHODS

This study included 1065 Chinese Han patients with AITD and 943 matched healthy individuals. The rs3130983, rs3778638, rs3815087, and rs4959053 single nucleotide polymorphisms (SNPs) in PSORS1C1 were determined using multiplex polymerase chain reaction technology.

RESULTS

Of the four SNPs, only the distribution of the rs3778638 genotypes was different between the AITD (AA, 2.67%; AG, 19.15%; and GG, 78.18%) and control (AA, 1.52%; AG, 22.2%; and GG, 75.87%) groups (P = .046). An association between rs3778683 and GD was observed (p = .039) but not with HT. No linkage disequilibrium was observed for rs3130983, rs3815087, rs3778638, and rs4959053 in PSORS1C1 among the patients with AITD and controls.

CONCLUSION

This study suggests the influence of PSORS1C1 rs3778638 on the susceptibility to GDs, supporting this locus as a common autoimmunity risk factor.

Sex and Menopause Modify the Effect of Single Nucleotide Polymorphism Genotypes on Fibrosis in NAFLD

The development of fibrosis in nonalcoholic fatty liver disease (NAFLD) is influenced by genetics, sex, and menopausal status, but whether genetic susceptibility to fibrosis is influenced by sex and reproductive status is unclear. Our aim was to identify metabolism-related single nucleotide polymorphisms (SNPs), whose effect on NAFLD fibrosis is significantly modified by sex and menopausal status. We performed a cross-sectional, proof-of-concept study of 616 patients in the Duke NAFLD Clinical Database and Biorepository. The primary outcome was nonalcoholic steatohepatitis-Clinical Research Network (NASH-CRN) fibrosis stage. Menopause status was self-reported; age 51 years was used as a surrogate for menopause in patients with missing menopause data. The Metabochip was used to obtain 98,359 SNP genotypes in known metabolic pathway genes for each patient. We used additive genetic models to characterize sex and menopause-specific effects of SNP genotypes on NAFLD fibrosis stage. In the main effects analysis, none of the SNPs were associated with fibrosis at P < 0.05 after correcting for multiple comparisons. Twenty-five SNPs significantly interacted with sex/menopause to affect fibrosis stage (interaction P < 0.0001). After removal of loci in linkage disequilibrium, 10 independent loci were identified. Six were in the following genes: KCNIP4 (potassium voltage-gated channel interacting protein 4), PSORS1C1 (psoriasis susceptibility 1 candidate 1), KLHL8 (Kelch-like family member 8), GLRA1 (glycine receptor alpha 1), NOTCH2 (notch receptor 2), and PRKCH (protein kinase C eta), and four SNPs were intergenic. In stratified models, four SNPs were significant in premenopausal and postmenopausal women, three only in postmenopausal women, two in men and postmenopausal women, and one only in premenopausal women. Conclusion: We identified 10 loci with a significant sex/menopause interaction with respect to fibrosis. None of these SNPs were significant in all sex/menopause groups, suggesting modulation of genetic susceptibility to fibrosis by sex and menopause status. Future studies of genetic predictors of NAFLD progression should account for sex and menopause.

Identification of Three Autophagy-Related Long Non-Coding RNAs as a Novel Head and Neck Squamous Cell Carcinoma Prognostic Signature

Head and neck squamous cell carcinoma (HNSCC) has a poor prognosis. Considerable evidence indicates that autophagy and non-coding RNA play essential roles in the biological processes involved in cancers, but associations between autophagy-related long non-coding RNAs (lncRNAs) and HNSCC remain unclear. In the present study, HNSCC RNA sequences and autophagy-related gene data were extracted from The Cancer Genome Atlas database and the Human Autophagy Database. A total of 1,153 autophagy-related lncRNAs were selected via calculating Pearson’s correlation coefficient. Three prognosis-related autophagy lncRNAs were identified via univariate Cox regression, least absolute shrinkage and selection operator analysis, and multivariate Cox regression analysis. We also constructed a prognostic model based on these autophagy-related lncRNAs and evaluated its ability to accurately and independently predict the prognosis of HNSCC patients. The area under the curve (AUC) was 0.864 (3-year) and 0.836 (5-year), and our model can independently predict the prognosis of HNSCC. The prognostic value of the three autophagy lncRNAs was confirmed via analysis of samples from five databases. To further identify the functions of the three lncRNAs, a co-expression network was constructed and pathway analysis was performed. In that analysis the lncRNAs were correlated with 189 related genes and 20 autophagy-related genes, and these lncRNAs mainly involved homologous recombination, the Fanconi anemia pathway, the autophagy-related pathway, and immune-related pathways. In addition, we validated the expression levels of three lncRNAs and autophagy markers (ATG12, BECN1, and MAP1LC3B) based on TIMER, Oncomine, and HPA database analysis. Our results indicated that TTTY15 was increased in HPV positive and HPV negative HNSCC patients, and three autophagy markers were up-regulated in all HNSCCC patients. Lastly, association between three lncRNAs and autophagy markers was performed, and our results showed that TTTY15 and MIF-AS1 were associated with autophagy markers. Collectively, these results suggested that three autophagy-related lncRNAs have prognostic value in HNSCC patients.