Background: Papillary thyroid cancer (PTC) is the most common subtype of thyroid cancer, and inflammation relates significantly to its initiation and prognosis. Systematic exploration of the immunogenomic landscape therein to assist in PTC prognosis is therefore urgent. The Cancer Genome Atlas (TCGA) project provides a large number of genetic PTC samples that enable a comprehensive and reliable immunogenomic study. Methods: We integrated the expression profiles of immune-related genes (IRGs) and progression-free intervals (PFIs) in survival in 493 PTC patients based on the TCGA dataset. Differentially-expressed and survivalassociated IRGs in PTC patients were estimated a computational difference algorithm and COX regression analysis. The potential molecular mechanisms and properties of these PTC-specific IRGs were also explored with the help of computational biology. A new prognostic index based on immune-related genes was developed by using multivariable COX analysis. Results: A total of 46 differentially expressed immune-related genes were significantly correlated with clinical outcome of PTC patients. Functional enrichment analysis revealed that these genes were actively involved in a cytokine-cytokine receptor interaction KEGG pathway. A prognostic signature based on IRGs (AGTR1, CTGF, FAM3B, IL11, IL17C, PTH2R and SPAG11A) performed moderately in prognostic predictions, and correlated with age, tumor stage, metastasis, number of lesions, and tumor burden. Intriguingly, the prognostic index based on IRGs reflected infiltration by several types of immune cells. Conclusions: Together, our results screened several IRGs of clinical significance, revealed drivers of the immune repertoire, and demonstrated the importance of a personalized, IRG-based immune signature in the recognition, surveillance, and prognosis of PTC.

Long non-coding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), also known as nuclear-enriched transcript 2 (NEAT2), is highly conserved among mammals and highly expressed in the nucleus. It was first identified in lung cancer as a prognostic marker for metastasis but is also associated with several other solid tumors. In hepatocellular carcinoma (HCC), MALAT1 is a novel biomarker for predicting tumor recurrence after liver transplantation. The mechanism of overexpression in tumor progression remains unclear. In the present study, we investigated the role of specificity protein 1/3 (Sp1/3) in regulation of MALAT1 transcription in HCC cells. The results showed a high expression of Sp1, Sp3 and MALAT1 in HCC vs. paired non-tumor liver tissues, which was associated with the AFP level (Sp1, r=7.44, P=0.0064; MALAT1, r=12.37, P=0.0004). Co-silencing of Sp1 and Sp3 synergistically repressed MALAT1 expression. Sp1 binding inhibitor, mithramycin A (MIT), also inhibited MALAT1 expression in HCC cells. In conclusion, the upstream of MALAT1 contains five Sp1/3 binding sites, which may be responsible for MALAT1 transcription. Inhibitors, such as MIT, provide a potential therapeutic strategy for HCC patients with MALAT1 overexpression.

BackgroundStudies which focused on the character of miR-144-3p in hepatocellular carcinoma (HCC) are limited. This study aimed to explore the expression, clinical significance and the potential targets of miR-144-3p in HCC.MethodsThe Cancer Genome Atlas (TCGA) and a cohort of 95 cases of HCC were applied to investigate aberrant miR-144-3p expression in HCC. A meta-analysis was performed to accumulate data on miR-144-3p expression in HCC based on TCGA, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Gene Expression Omnibus (GEO). Additionally, the potential regulatory mechanisms of miR-144-3p in HCC were explored by bioinformatics.ResultsMiR-144-3p expression was downregulated distinctly in HCC compared to para-HCC tissue both in TCGA data (8.9139±1.5986 vs 10.7721±0.9156, P<0.001) and in our qRT-PCR validation (1.3208±0.7594 vs 2.6200±0.9263, P<0.001). The meta-analysis based on TCGA, qRT-PCR and GEO data confirmed a consistent result (standard mean difference =−0.854, 95% CI: −1.224 to −0.484, P<0.001). The receiver operating characteristic curve of miR-144-3p gained a significant diagnostic value both in TCGA data (area under the curve [AUC] =0.852, 95% CI: 0.810 to 0.894, P<0.001) and in qRT-PCR validation (AUC =0.867, 95% CI: 0.817 to 0.916, P<0.001), especially in alpha-fetoprotein–negative HCC patients (AUC =0.900, 95% CI: 0.839 to 0.960, P<0.001). Furthermore, we identified 119 potential targets of miR-144-3p in HCC by bioinformatics. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that several significant biologic functions and pathways correlated with the pathogenesis of HCC, including the p53 signaling pathway.ConclusionMiR-144-3p may function as a cancer suppressor microRNA, which is essential for HCC progression through the regulation of various signaling pathways. Thus, interactions with miR-144-3p may provide a novel treatment strategy for HCC in the future.

Thyroid cancer (TC) is the most common endocrine malignancy, accounting for approximately 90% of all malignancies of the endocrine system. Despite the fact that patients with TC tend to have good prognoses, the high incidence rate and lymph node metastases remain unresolved issues. Autophagy is an indispensable process that maintains intracellular homeostasis; however, the role of autophagy in several steps of the initiation and progression of TC has not yet been elucidated. In this study, we first identified several autophagy-related genes (ARGs) that were provoked in the onset of TC. Subsequently, a bioinformatics analysis hinted that these genes were markedly disturbed in several proliferative signaling pathways. Moreover, we demonstrated that the differentially expressed ARGs were closely related to several aggressive clinical manifestations, including an advanced tumor stage and lymph node metastasis. Our study further selected prognostic ARGs and developed a prognostic signature based on three key genes (ATG9B, BID and B1DNAJB1), which displayed a moderate ability to predict the prognosis of TC. On the whole, the findings of this study demonstrate that ARGs disrupt proliferation-related pathways and consequently lead to aggressive clinical manifestations. These findings provide insight into the potential molecular mechanisms of action of ARGs and their clinical significance, and also provide classification information of potential therapeutic significance.