UHRF1 is regulated by miR-124-3p and promotes cell proliferation in intrahepatic cholangiocarcinoma

Ubiquitin-like with PHD and ring finger domains 1 (UHRF1) is abnormally overexpressed in multiple cancers and closely correlated with tumor-promoting effects, such as high proliferation. However, how UHRF1 functions in intrahepatic cholangiocarcinoma (ICC) has not yet been determined. Herein, we found that UHRF1 is overexpressed in ICC tissues. Downregulated UHRF1 attenuated the transition of the G1/S cell cycle and then suppressed cell proliferation in vitro and tumor growth in vivo. Moreover, upstream regulators of the UHRF1 expression were predicted, and we found that direct binding of miR-124-3p inhibited the UHRF1 expression. Elevated miR-124-3p suppressed proliferation and led to the arrest of the cell cycle. Furthermore, the expression of UHRF1 was positively correlated with PCNA. Clinically, we showed that elevated UHRF1 was associated with poor prognosis, and served as an independent prognostic factor in ICC patients. Together, these findings demonstrate that UHRF1, regulated by miR-124-3p, acts as a tumor promoter by promoting cell proliferation in ICC.     

Identification of EPHX2 and RMI2 as two novel key genes in cervical squamous cell carcinoma by an integrated bioinformatic analysis

Cervical cancer is the fourth most common malignancy in women worldwide and cervical squamous cell carcinoma (CESC) is the most common histological type of cervical cancer. The dysregulation of genes plays a significant role in cancer. In the present study, we screened out differentially expressed genes (DEGs) of CESC in the GSE63514 data set from the Gene Expression Omnibus database. An integrated bioinformatics analysis was used to select hub genes, as well as to investigate their related prognostic signature, functional annotation, methylation mechanism, and candidate molecular drugs. As a result, a total of 1907 DEGs were identified (944 were upregulated and 963 were downregulated). In the protein–protein interaction network, three hub modules and 30 hub genes were identified. And two hub modules and 116 hub genes were screened out from four CESC-related modules by the weighted gene coexpression network analysis. The gene ontology term enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis were performed to better understand functions and pathways. Genes with a significant prognostic value were found by prognostic signature analysis. And there were five genes (EPHX2, CHAF1B, KIAA1524, CDC45, and RMI2) identified as significant CESC-associated genes after expression validation and survival analysis. Among them, EPHX2 and RMI2 were noted as two novel key genes for the CESC-associated methylation and expression. In addition, four candidate small molecule drugs for CESC (camptothecin, resveratrol, vorinostat, and trichostatin A) were defined. Further studies are required to explore these significant CESC-associated genes for their potentiality in diagnosis, prognosis, and targeted therapy.     

Prognostic relevance of miR-137 and its liver microenvironment regulatory target gene AFM in hepatocellular carcinoma

MiR-137 has been identified as potential hepatocellular carcinoma (HCC) prognostic biomarkers. Highly relevant HCC prognostic biomarkers may be derived from combinations of miR-137 with its target genes involved in the regulation of liver microenvironment. This study aimed at the discovery of such a combination with improved HCC prognosis performance than miR-137 or its target gene alone in a significantly higher number of HCC patients than previous studies. Analysis of the differentially expressed micro RNAs (miRNAs) between cancer and noncancer tissues reconfirmed miR-137 to be among the most relevant prognostic miRNAs and the data of 375 HCC patients and 50 normal cases were from the Cancer Genome Atlas (TCGA) data sets. Target genes were identified by the established search methods and Kaplan–Meier survival analysis of HCC patients was used to evaluate the overall survival (OS) and recurrence-free survival (RFS). Cox proportional hazards regression indicated that the miR-137 and its target gene AFM combination is an independent prognostic factor for the OS and RFS in HCC. In vitro experiments validated that miR-137 could bind to 3′-untranslated region of the AFM and promote the invasion and metastasis of HCC cell lines. The expressions of miR-137 and its liver microenvironment regulatory target gene AFM in combination significantly correlated with HCC progression in a higher number of patients than in previous studies, which suggested their potential as prognostic biomarkers for HCC.     

Prognostic significance of X-linked inhibitor of apoptosis protein in solid tumors: A systematic review and meta-analysis

X-linked inhibitor of apoptosis protein (XIAP) is aberrantly expressed in solid tumors. Considering conflicting data, we conducted this meta-analysis to investigate its prognostic role. Electronic databases were searched to collect studies about associations between XIAP expressions and survival outcomes. Hazard ratio (HR), odds ratio (OR), and 95% confidence interval (CI) were utilized as effect size estimates. A total of 3,794 patients from 21 published studies were included. The results revealed that high XIAP expressions correlated with age (OR = 2.02; 95% CI, 1.07–3.84), lymph node metastasis (OR = 1.69; 95% CI, 1.02–2.77), histological grade (OR = 2.04; 95% CI, 1.01–4.11), and tumor stage (OR = 2.18; 95% CI, 1.20–3.96). The combined HR revealed that high XIAP expressions associated with poor overall survival (OS) (HR = 1.60; 95% CI, 1.22–2.10). Our study suggested high XIAP expressions may be indicative of poor prognosis in solid tumors.     

Identification of a five-gene signature with prognostic value in colorectal cancer

Colorectal cancer (CRC) ranks as one of the most commonly diagnosed malignancies worldwide. Although mortality rates have been decreasing, the prognosis of CRC patients is still highly dependent on the individual. Therefore, identifying and understanding novel biomarkers for CRC prognosis remains crucial. The gene expression profiles of five-gene expression omnibus (GEO) data sets of CRC were first downloaded. A total of 352 consistent differentially expressed genes (DEGs) were identified for CRC and paired with normal tissues. Functional analysis including gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment revealed that these DEGs were related to metabolic pathways, tight junctions, and the cell cycle. Ten hub DEGs were identified based on the search tool for the retrieval of interacting genes database and protein–protein interaction networks. By using univariate Cox proportional hazard regression analysis, we found 11 survival-related genes among these DEGs. We finally established a five-gene signature (kinesin family member 15, N-acetyltransferase 2, glutathione peroxidase 3, secretogranin II, and chloride channel accessory 1) with prognostic value in CRC by step multivariate Cox regression analysis. Based on this risk scoring system, patients in the high-risk group had significantly poorer survival results compared with those in the low-risk group (log-rank test, p < 0.0001). Finally, we validated our gene signature scoring system in two independent GEO cohorts (GSE17536 and GSE33113). We found all five of the signature genes to be DEGs in The Cancer Genome Atlas database. In conclusion, our findings suggest that our five DEG-based signature can provide a novel biomarker with useful applications in CRC prognosis.     

The roles of moonlight ribosomal proteins in the development of human cancers

“Moonlighting protein” is a term used to define a single protein with multiple functions and different activities that are not derived from gene fusions, multiple RNA splicing, or the proteolytic activity of promiscuous enzymes. Different proteinous constituents of ribosomes have been shown to have important moonlighting extra-ribosomal functions. In this review, we introduce the impact of key moonlight ribosomal proteins and dependent signal transduction in the initiation and progression of various cancers. As a future perspective, the potential role of these moonlight ribosomal proteins in the diagnosis, prognosis, and development of novel strategies to improve the efficacy of therapies for human cancers has been suggested.     

Clinicopathological and prognostic value of lncRNA PANDAR expression in solid tumors: Evidence from a systematic review and meta-analysis

PANDAR (promoter of CDKN1A antisense DNA damage activated RNA) has been shown to be aberrantly expressed in many types of cancer. Considering conflicting data, the current study was aimed to assess its potential role as a prognostic marker in malignant tumors. A comprehensive literature search of PubMed, Medline, and Web of Science was performed to identify all eligible studies describing the use of PANDAR as a prognostic factor for different types of cancer. Data related to overall survival (OS) and clinicopathologic features were collected and analyzed. The pooled hazard ratio (HR) and odds radio (OR) with a 95% confidence interval (CI) were used to estimate associations. Ten original studies containing 1,231 patients were included. The results showed that in patients with cancer, high PANDAR expression is correlated with lymph node metastasis (LNM; OR = 2.57; 95% CI, 1.76–3.81; p < 0.001), tumor stage (OR = 2.90; 95% CI, 1.25–6.75; p = 0.013), and tumor size (OR = 1.79; 95% CI, 1.11–2.91; p = 0.018). However, sensitivity analysis further demonstrated a significant association between high PANDAR expression and OS, both in multivariate and univariate analysis models (pooled HR 2.01; 95% CI, 1.17–3.44 and pooled HR 2.62; 95% CI, 1.98–3.47, respectively), after omitting one study. These results suggested that PANDAR expression might be indicative of advanced disease and poor prognosis in patients with cancer. Further studies are necessary to determine the value of this risk stratification biomarker in clinical management of patients with cancer.     

A novel LncRNA-based prognostic score reveals TP53-dependent subtype of lung adenocarcinoma with poor survival

The prognostic signatures play an essential role in the era of personalised therapy for cancer patients including lung adenocarcinoma (LUAD). Long noncoding RNA (LncRNA), a relatively novel class of RNA, has shown to play a crucial role in all the areas of cancer biology. Here, we developed and validated a robust LncRNA-based prognostic signature for LUAD patients using three different cohorts. In the discovery cohort, four LncRNAs were identified with 10% false discovery rate and a hazard ratio of >10 using univariate Cox regression analysis. A risk score, generated from the four LncRNAs’ expression, was found to be a significant predictor of survival in the discovery and validation cohort (p = 9.97 × 10 ⁻⁸ and 1.41 × 10 ⁻³, respectively). Further optimisation of four LncRNAs signature in the validation cohort, generated a three LncRNAs prognostic score (LPS), which was found to be an independent predictor of survival in both the cohorts ( p = 1.00 × 10 ⁻⁶ and 7.27 × 10 ⁻⁴, respectively). The LPS also significantly divided survival in clinically important subsets, including Stage I ( p = 9.00 × 10 ⁻⁴ and 4.40 × 10 ⁻², respectively), KRAS wild-type (WT), KRAS mutant ( p = 4.00 × 10 ⁻³ and 4.30 × 10 ⁻², respectively) and EGFR WT ( p = 2.00 × 10 ⁻⁴). In multivariate analysis LPS outperformed, eight previous prognosticators. Further, individual members of LPS showed a significant correlation with survival in microarray data sets. Mutation analysis showed that high-LPS patients have a higher mutation rate and inactivation of the TP53 pathway. In summary, we identified and validated a novel LncRNA signature LPS for LUAD.     

Identification of CD28 and PTEN as novel prognostic markers for cervical cancer

Cervical cancer (CC) is the most common malignant tumor with poor clinical outcome among women. Identification of novel biomarkers could be beneficial for the clinical diagnosis and treatment of CC. This study aimed to identify prognostic biomarkers for the prediction of prognostic status of CC patients, and explore the effect of the corresponding methylated genes in the occurrence and development of CC. The methylation microarray data of CC was extracted from The Cancer Genome Atlas (TCGA) dataset. The methylation genes associated with the prognostic status were identified based on the information of the relapse-free survival (RFS) of the CC patients. The prognostic gene pairs were further identified. Then, the prognostic signature was identified by the forward search algorithm based on the C-index method. The results were validated by independent dataset. Finally, the functional analysis was performed on the methylation genes. A total of 276 methylation genes and 2508 gene pairs associated with the prognostic status of the CC were identified. A signature composed of eight methylation gene pairs was obtained to predict the prognostic status of cervical patients. A series of genes that played an important role in the occurrence and development of CC were obtained by the functional enrichment analysis. To summary, a prognostic signature consisting of eight methylation gene pairs was obtained. Of note, the CD28 and PTEN gene pair were found to play important roles in the occurrence and development of CC.