Protein Expression of PTTG1 as a Diagnostic Biomarker in Adrenocortical Carcinoma

PTTG1 induces pancreatic cancer cell proliferation and promotes aerobic glycolysis by regulating c-myc

This study aimed to clarify the role of pituitary tumor-transforming gene 1 (PTTG1) in proliferation, migration, invasion, and aerobic glycolysis of pancreatic cancer cells, and evaluate the potential of PTTG1 as a therapeutic target. PTTG1 expression in pancreatic cancers was analyzed using the GEPIA databank. In the Panc1 cell with the PTTG1 knockdown or Mia-PaCa2 cells with PTTG1 overexpression, the cell proliferation was evaluated using cell viability curves and colony formation, and wound heal assay and transwell assay were performed to evaluate the migration and invasion, respectively. Furthermore, a western blot was performed to evaluate the expressions of PTTG1, proliferating cell nuclear antigen, E-cadherin, N-cadherin, and c-myc. Meanwhile, the glucose uptake, extracellular acidification rates (ECAR), and oxygen consumption rates (OCR) were analyzed. Our results showed that PTTG1 expression is upregulated in pancreatic cancer, which promoted cell proliferation. Low PTTG1 contributed to higher disease-free survival and overall survival. In Panc1 cell, PTTG1 knockdown resulted in reduced cell viability and colony formation. The migration and invasion abilities of the cells were also reduced in Panc1 with PTTG1 knockdown. Correspondingly, PTTG1 knockdown decreased c-myc expression, glucose uptake, ECAR, and OCR in Panc1 cells. In Mia-PaCa2 cells, PTTG1 overexpression promoted cell proliferation, aerobic glycolysis, and translocation of β-catenin to the nucleus by regulating c-myc. In conclusion, PTTG1 induces proliferation, migration, and invasion, and promotes aerobic glycolysis in pancreatic cancer cells via regulating c-myc, demonstrating the potential of PTTG1 as a therapeutic target.

Bioinformatic Analysis of PTTG Family and Prognosis and Immune Cell Infiltration in Gastric Cancer

Gastric cancer is the sixth highest incidence rate in the world. Although treatment has made progress, the prospect of gastric cancer patients is bleak. Difficulties and future prospects of immunotherapy in cancer treatment. Adaptive cell therapy, cancer vaccines, gene therapy, and monoclonal antibody therapy have all been used in gastric cancer with some initial success. PTTGs (pituitary tumor-transforming genes) have been proven to be closely related to the prognosis of many malignant tumors. However, the prognosis and immune cell infiltration of gastric adenocarcinoma (STAD) remain unclear. We retrieved multiple databases to understand the possible activity of PTTGs and their expression in gastric cancer, as well as their relationship with clinical data, overall survival rate, first progression, and survival rate after progression. PTTGs are overexpressed in STAD tumor tissues. Many clinical variables are closely related to PTTGs. In addition, PTTG was associated with overall survival independent of disease. In addition, the expression of PTTG1/2 was positively correlated with the molecular status of the immune checkpoint and negatively correlated with the infiltration of various immune cells. Data research shows that PTTG and STAD are closely related. This paved the way for future research, revealed the complex pathophysiology of gastric cancer, and introduced an effective new treatment.

Elevated PTTG1 predicts poor prognosis in kidney renal clear cell carcinoma and correlates with immunity

Background

PTTG1 has been reported to be linked with the prognosis and progression of various cancers, including kidney renal clear cell carcinoma (KIRC). In this article, we mainly investigated the associations between prognosis, immunity, and PTTG1 in KIRC patients.

Method

We downloaded transcriptome data from the TCGA-KIRC database. PCR and immunohistochemistry were used, respectively, to validate the expression of PTTG1 in KIRC at the cell line and the protein levels. Survival analyses as well as univariate or multivariate Cox hazard regression analyses were used to prove whether PTTG1 alone could affect the prognosis of KIRC. The most important point was to study the relationship between PTTG1 and immunity.

Results

The results of the paper revealed that the expression levels of PTTG1 were elevated in KIRC compared with para-cancerous normal tissues, validated by PCR and immunohistochemistry at the cell line and the protein levels (P < 0.05). High PTTG1 expression was related to shorter overall survival (OS) in patients with KIRC (P < 0.05). Through univariate or multivariate regression analysis, PTTG1 was confirmed to be an independent prognostic factor for OS of KIRC (P < 0.05), and its related seven pathways were obtained through gene set enrichment analysis (GSEA; P < 0.05). Moreover, tumor mutational burden (TMB) and immunity were found to be significantly connected with PTTG1 in KIRC (P < 0.05). Correlations between PTTG1 and immunotherapy responses implied that the low-PTTG1 group was more sensitive to immunotherapy (P < 0.05).

Conclusions

PTTG1 was closely associated with TMB or immunity, and it had a superior ability to forecast the prognosis of KIRC patients.

A Comprehensive Pan-Cancer Analysis for Pituitary Tumor-Transforming Gene 1

Pituitary tumor-transforming gene 1 (PTTG1) encodes a multifunctional protein that is involved in many cellular processes. However, the potential role of PTTG1 in tumor formation and its prognostic function in human pan-cancer is still unknown. The analysis of gene alteration, PTTG1 expression, prognostic function, and PTTG1-related immune analysis in 33 types of tumors was performed based on various databases such as The Cancer Genome Atlas database, the Genotype-Tissue Expression database, and the Human Protein Atlas database. Additionally, PTTG1-related gene enrichment analysis was performed to investigate the potential relationship and possible molecular mechanisms between PTTG1 and tumors. Overexpression of PTTG1 may lead to tumor formation and poor prognosis in various tumors. Consequently, PTTG1 acts as a potential oncogene in most tumors. Additionally, PTTG1 is related to immune infiltration, immune checkpoints, tumor mutational burden, and microsatellite instability. Thus, PTTG1 could be potential biomarker for both prognosis and outcomes of tumor treatment and it could also be a promising target in tumor therapy.

Mass Spectrometry-Based Proteomic Discovery of Prognostic Biomarkers in Adrenal Cortical Carcinoma

Simple Summary

Adrenal cortical carcinoma (ACC) is an extremely rare disease with a variable prognosis. Current prognostic markers have limitations in identifying patients with a poor prognosis and who require adjuvant therapy. We developed the prognostic biomarker candidates of ACC using mass-spectrometry-based proteomics and machine learning algorithm. We further validated them in The Cancer Genome Atlas data and performed the survival analysis according to the expression levels of each protein. In addition, HNRNPA1, the protein identified as a prognostic marker of ACC based on proteomics, was validated in the immunohistochemistry staining. The prognostic protein biomarkers of ACC found in this study are expected to help determine the appropriate treatment plan for patients.

Abstract

Adrenal cortical carcinoma (ACC) is an extremely rare disease with a variable prognosis. Current prognostic markers have limitations in identifying patients with a poor prognosis. Herein, we aimed to investigate the prognostic protein biomarkers of ACC using mass-spectrometry-based proteomics. We performed the liquid chromatography–tandem mass spectrometry (LC–MS/MS) using formalin-fixed paraffin-embedded (FFPE) tissues of 45 adrenal tumors. Then, we selected 117 differentially expressed proteins (DEPs) among tumors with different stages using the machine learning algorithm. Next, we conducted a survival analysis to assess whether the levels of DEPs were related to survival. Among 117 DEPs, HNRNPA1, C8A, CHMP6, LTBP4, SPR, NCEH1, MRPS23, POLDIP2, and WBSCR16 were significantly correlated with the survival of ACC. In age- and stage-adjusted Cox proportional hazard regression models, only HNRNPA1, LTBP4, MRPS23, POLDIP2, and WBSCR16 expression remained significant. These five proteins were also validated in TCGA data as the prognostic biomarkers. In this study, we found that HNRNPA1, LTBP4, MRPS23, POLDIP2, and WBSCR16 were protein biomarkers for predicting the prognosis of ACC.

A Critical Appraisal of Contemporary and Novel Biomarkers in Pheochromocytomas and Adrenocortical Tumors

Simple Summary

Pheochromocytomas/paragangliomas (PPGLs) and adrenocortical tumors are neoplasms that originate from different regions of the adrenal gland and display significant heterogeneity with respect to their biological and clinical behavior. They may be sporadic or develop in the context of hereditary syndromes. Adrenocortical tumors are mostly benign but less than 2% are carcinomas associated with a poor outcome when diagnosed in advanced disease. The majority of PPGLS are benign, but a subset may develop metastatic disease. In particular, for PPGLs, it is mandatory to identify biomarkers of high sensitivity and specificity that lead to accurate diagnosis and predict patients with a malignant potential that would benefit from aggressive surveillance and administration of early treatment. Current biomarkers include mostly histopathological and genetic parameters but none of them can be considered independent predictive factors. Recent genomic studies have implemented new molecular biomarkers of high accuracy for the diagnosis and management of PPGLs and adrenocortical tumors. In this review, we summarize the current and novel biomarkers that may be considered valuable tools for diagnosis and prediction of malignancy in patients with PPGLs and adrenocortical tumors.

Abstract

Pheochromocytomas/Paragangliomas (PPGLs) and adrenocortical tumors are rare neoplasms with significant heterogeneity in their biologic and clinical behavior. Current diagnostic and predictive biomarkers include hormone secretion, as well as histopathological and genetic features. PPGL diagnosis is based on biochemical measurement of catecholamines/metanephrines, while histopathological scoring systems have been proposed to predict the risk of malignancy. Adrenocortical tumors are mostly benign, but some can be malignant. Currently, the stage of disease at diagnosis and tumor grade, appear to be the most powerful prognostic factors. However, recent genomic and proteomic studies have identified new genetic and circulating biomarkers, including genes, immunohistochemical markers and micro-RNAs that display high specificity and sensitivity as diagnostic or prognostic tools. In addition, new molecular classifications have been proposed that divide adrenal tumors in distinct subgroups with different clinical outcomes.

Overexpressing PTTG family genes predict poor prognosis in kidney renal clear cell carcinoma

Background

Pituitary tumor transforming genes (PTTG1, PTTG2, and PTTG3P) play key roles in the pathogenesis and development of human cancers. The studies show that overexpression of the PTTG genes is associated with tumor progression and migration. However, the function of the PTTG genes in the prognostic value of kidney renal clear cell carcinoma is rarely known by people.

Methods

The expression of PTTG family genes was analyzed by the ONCOMINE, Human Protein Atlas, GEPIA2, and UALCAN database. The relationship between PTTG family genes expression level and clinical indicators including prognostic data in kidney renal clear cell carcinoma was analyzed by GEPIA2, TCGA portal, and UALCAN. cBioPortal database was used to analyze the genetic mutations of differentially expressed PTTG family members. Similar genes of the PTTG family (90 in total) obtained from GEPIA2 and Metascape were used for GO enrichment to explore the interaction among similar genes. The online tools of Metascape and STRING were used for functional and pathway enrichment analysis.

Results

PTTG1, 2, and 3P mRNA and protein expression upregulated in kidney renal clear cell carcinoma kidney renal clear cell carcinoma patients compared with normal tissues. And higher expression level of PTTG family genes was associated with shorter overall survival (OS) and disease-free survival (DFS). Furthermore, overexpression of the PTTG family genes had been found correlated with individual cancer stages and pathological tumor grades. In addition, 18% of mutations in the PTTG family genes were associated with short-term survival in kidney renal clear cell carcinoma patients.

Conclusions

A single PTTG gene or PTTG family genes as a whole may be a potential prognostic biomarker for kidney renal clear cell carcinoma.

Expression patterns and prognostic value of m6A RNA methylation regulators in adrenocortical carcinoma

Adrenocortical carcinoma (ACC) is considered a rare cancer with poor prognosis. We used public datasets from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases to assess the relationships between N6-methyladenosine (m6A)-related genes and ACC.We used the Wilcoxon signed-rank test to compare m6A-related gene expression in ACC tissues with that in normal tissues. Then, ACC patients were grouped based on a cluster analysis of m6A-related gene expression. m6A-related genes that were significantly associated with survival were incorporated into a risk signature, and 2 groups were divided according to median risk score. Fisher exact tests were utilized to analyze differences in clinical variables between groups. We compared the overall survival (OS) rates of the groups by means of Kaplan-Meier curves and Cox regression analyses.We found that RBM15, ZC3H3, YTDHF1, YTDHF2, and ALBH5 were overexpressed in ACC and that KIAA1429, YTHDC1, HNRNPC, WTAP, METTL3, and FTO were down regulated in ACC. In addition, membership in cluster 2 or the high-risk group was associated with advanced clinical factors and poor prognosis. The univariable and multivariable Cox regression analyses showed that risk score can be considered an independent prognostic factor for ACC.We found that the expression of m6A-related genes could be used as an independent prognostic factor in ACC. However, the current study has some limitations, and further studies of m6A-related genes in ACC are needed.

Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer and has poor outcomes. However, the potential molecular biological process underpinning the occurrence and development of HCC is still largely unknown. The purpose of this study was to identify the core genes related to HCC and explore their potential molecular events using bioinformatics methods. HCC-related expression profiles GSE25097 and GSE84005 were selected from the Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) between 306 HCC tissues and 281 corresponding noncancerous tissues were identified using GEO2R online tools. The protein-protein interaction network (PPIN) was constructed and visualized using the STRING database. Gene Ontology (GO) and KEGG pathway enrichment analyses of the DEGs were carried out using DAVID 6.8 and KOBAS 3.0. Additionally, module analysis and centrality parameter analysis were performed by Cytoscape. The expression differences of key genes in normal hepatocyte cells and HCC cells were verified by quantitative real-time fluorescence polymerase chain reaction (qRT-PCR). Additionally, survival analysis of key genes was performed by GEPIA. Our results showed that a total of 291 DEGs were identified including 99 upregulated genes and 192 downregulated genes. Our results showed that the PPIN of HCC was made up of 287 nodes and 2527 edges. GO analysis showed that these genes were mainly enriched in the molecular function of protein binding. Additionally, KEGG pathway analysis also revealed that DEGs were mainly involved in the metabolic, cell cycle, and chemical carcinogenesis pathways. Interestingly, a significant module with high centrality features including 10 key genes was found. Among these, CDK1, NDC80, HMMR, CDKN3, and PTTG1, which were only upregulated in HCC patients, have attracted much attention. Furthermore, qRT-PCR also confirmed the upregulation of these five key genes in the normal human hepatocyte cell line (HL-7702) and HCC cell lines (SMMC-7721, MHCC-97L, and MHCC-97H); patients with upregulated expression of these five key genes had significantly poorer survival and prognosis. CDK1, NDC80, HMMR, CDKN3, and PTTG1 can be used as molecular markers for HCC. This finding provides potential strategies for clinical diagnosis, accurate treatment, and prognosis analysis of liver cancer.

The Role of Biomarkers in Adrenocortical Carcinoma: A Review of Current Evidence and Future Perspectives

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy arising from the adrenal cortex often with unexpected biological behavior. It can occur at any age, with two peaks of incidence: in the first and between fifth and seventh decades of life. Although ACC are mostly hormonally active, precursors and metabolites, rather than end products of steroidogenesis are produced by dedifferentiated and immature malignant cells. Distinguishing the etiology of adrenal mass, between benign adenomas, which are quite frequent in general population, and malignant carcinomas with dismal prognosis is often unfeasible. Even after pathohistological analysis, diagnosis of adrenocortical carcinomas is not always straightforward and represents a great challenge for experienced and multidisciplinary expert teams. No single imaging method, hormonal work-up or immunohistochemical labelling can definitively prove the diagnosis of ACC. Over several decades' great efforts have been made in finding novel reliable and available diagnostic and prognostic factors including steroid metabolome profiling or target gene identification. Despite these achievements, the 5-year mortality rate still accounts for approximately 75% to 90%, ACC is frequently diagnosed in advanced stages and therapeutic options are unfortunately limited. Therefore, imperative is to identify new biological markers that can predict patient prognosis and provide new therapeutic options.

The Clinical Significance and Potential Molecular Mechanism of PTTG1 in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is the major histological type of esophageal cancers worldwide. Transcription factor PTTG1 was seen highly expressed in a variety of tumors and was related to the degree of tumor differentiation, invasion, and metastasis. However, the clinical significance of PTTG1 had yet to be verified, and the mechanism of abnormal PTTG1 expression in ESCC was not clear. In this study, the comprehensive analysis and evaluation of PTTG1 expression in ESCC were completed by synthesizing in-house immunohistochemistry (IHC), clinical sample tissue RNA-seq (in-house RNA-seq), public high-throughput data, and literature data. We also explored the possible signaling pathways and target genes of PTTG1 in ESCC by combining the target genes of PTTG1 (displayed by ChIP-seq), differentially expressed genes (DEGs) of ESCC, and PTTG1-related genes, revealing the potential molecular mechanism of PTTG1 in ESCC. In the present study, PTTG1 protein and mRNA expression levels in ESCC tissues were all significantly higher than in non-cancerous tissues. The pool standard mean difference (SMD) of the overall PTTG1 expression was 1.17 (95% CI: 0.72-1.62, P < 0.01), and the area under curve (AUC) of the summary receiver operating characteristic (SROC) was 0.86 (95% CI: 0.83-0.89). By combining the target genes displayed by ChIP-seq of PTTG1, DEGs of ESCC, and PTTG1-related genes, it was observed that PTTG1 may interact with these genes through chemokines and cytokine signaling pathways. By constructing a protein-protein interaction (PPI) network and combining ChIP-seq data, we obtained four PTTG1 potential target genes, SPTAN1, SLC25A17, IKBKB, and ERH. The gene expression of PTTG1 had a strong positive correlation with SLC25A17 and ERH, which suggested that PTTG1 might positively regulate the expression of these two genes. In summary, the high expression of PTTG1 may play an important role in the formation of ESCC. These roles may be completed by PTTG1 regulating the downstream target genes SLC25A17 and ERH.

Alteration of Pituitary Tumor Transforming Gene 1 by MicroRNA-186 and 655 Regulates Invasion Ability of Human Oral Squamous Cell Carcinoma

Background: Pituitary tumor-transforming gene 1 (PTTG1) was recently shown to be involved in the progression as well as the metastasis of cancers. However, their expression and function in the invasion of oral squamous cell carcinoma (SCC) remain unclear. Methods: The expressions of PTTG1 and PTTG1-targeted miRNA in oral SCC cell lines and their invasion capability depended on PTTG1 expression were analyzed by quantitative RT-PCR, Western blots, the transwell insert system and Zymography. Results: Invasion abilities were decreased in oral SCC cells treated with siRNA-PTTG1. When PTTG1 were downregulated in oral SCC cells treated with microRNA-186 and -655 inhibited their invasion abilities via MMP-9 activity. Conclusions: These results indicate that alteration of expression of PTTG1 in oral SCC cells by newly identified microRNA-186 and -655 can regulate invasion activity. Therefore, these data offer new insights into further understanding PTTG1 function in oral SCC and should provide new strategies for diagnostic markers for oral SCC.

[Expression of pituitary tumor-transforming gene-1 and its pathogenic role in systemic sclerosis]

OBJECTIVE

To investigate the expression of tumor-transforming gene-1 (PTTG1) in systemic sclerosis (SSc) and its role in fibrosis.

METHODS

Skin biopsy samples were collected from 21 patients with SSc and 22 patients with healthy skin for detecting the mRNA and protein expressions of PTTG1 using real-time PCR (RT-PCR) and immunohistochemistry, respectively. In cultured primary human dermal fibroblasts, PTTG1 expression was knocked down via RNA interference (siRNA), and the mRNA expression levels of PTTG1 and the fibrosis-related genes α-SMA, COL1A1, COL1A2, and COL3A1 were detected using RT-PCR; the proliferation of the cells was assessed using a real-time cell proliferation detection system.

RESULTS

Compared with those in normal skin samples, the mRNA and protein expressions of PTTG1 increased significantly in the skin tissue of patients with SSc (P < 0.05). In cultured primary skin fibroblasts, the expression of PTTG1 mRNA was positively correlated with those of α-SMA (R²=0.8192, P < 0.05), COL1A1 (R²=0.6398, P < 0.05), COL1A2 (R²=0.316, P < 0.05) and COL3A1 mRNAs (R²=0.3727, P < 0.05). Interference of PTTG1 expression significantly inhibited the cell proliferation, obviously lowered the expressions of fibrosis-related genes, and down-regulated the expression of collagen in the fibroblasts.

CONCLUSIONS

PTTG1 is highly expressed in skin tissues of patients with SSc, and PTTG1 knockdown can reduce the activity of the dermal fibroblasts, suggesting a close correlation of PTTG1 with fibrosis in SSc.

Identification of Subtype-Specific Metastasis-Related Genetic Signatures in Sarcoma

Background: Sarcomas are heterogeneous rare malignancies constituting approximately 1% of all solid cancers in adults and including more than 70 histological and molecular subtypes with different pathological and clinical development characteristics.

Method: We identified prognostic biomarkers of sarcomas by integrating clinical information and RNA-seq data from TCGA and GEO databases. In addition, results obtained from cell cycle, cell migration, and invasion assays were used to assess the capacity for Tanespimycin to inhibit the proliferation and metastasis of sarcoma.

Results: Sarcoma samples (N = 536) were divided into four pathological subtypes including DL (dedifferentiated liposarcoma), LMS (leiomyosarcoma), UPS (undifferentiated pleomorphic sarcomas), and MFS (myxofibrosarcoma). RNA-seq expression profile data from the TCGA dataset were used to analyze differentially expressed genes (DEGs) within metastatic and non-metastatic samples of these four sarcoma pathological subtypes with DEGs defined as metastatic-related signatures (MRS). Prognostic analysis of MRS identified a group of genes significantly associated with prognosis in three pathological subtypes: DL, LMS, and UPS. ISG15, NUP50, PTTG1, SERPINE1, and TSR1 were found to be more likely associated with adverse prognosis. We also identified Tanespimycin as a drug exerting inhibitory effects on metastatic LMS subtype and therefore can serve a potential treatment for this type of sarcoma.

Conclusions: These results provide new insights into the pathogenesis, diagnosis, treatment, and prognosis of sarcomas and provide new directions for further study of sarcoma.

Bioinformatic screening and identification of downregulated hub genes in adrenocortical carcinoma

The molecular mechanisms of adrenocortical carcinoma (ACC) carcinogenesis and progression remain unclear. In the present study, three microarray datasets from the Gene Expression Omnibus database were screened, which identified a total of 96 differentially expressed genes (DEGs). A protein-protein interaction network (PPI) was established for these DEGs and module analysis was performed using STRING and Cytoscape. A total of eight hub genes were identified from the most significant module; namely, calponin 1 (CNN1), myosin light chain kinase (MYLK), cysteine and glycine rich protein 1 (CSRP1), myosin heavy chain 11 (MYH11), fibulin extracellular matrix protein 2 (EFEMP2), fibulin 1 (FBLN1), microfibril associated protein 4 (MFAP4) and fibulin 5 (FBLN5). The biological functions of these hub genes were analyzed using the DAVID online tool. Changes in the expression of hub genes did not affect overall survival; however, downregulated EFEMP2 decreased disease-free survival. CSRP1 and MFAP4 expression levels were associated with adverse clinicopathological features. In conclusion, although all eight hub genes were downregulated in ACC, they appeared to have important functions in ACC carcinogenesis and progression. Identification of these genes complements the genetic expression profile of ACC and provides insight for the diagnosis, treatment and prognosis of ACC.

Screening and identification of key biomarkers in lung squamous cell carcinoma by bioinformatics analysis

The high mortality rate of lung squamous cell carcinoma (LUSC) is in part due to the lack of early detection of its biomarkers. The identification of key molecules involved in LUSC is therefore required to improve clinical diagnosis and treatment outcomes. The present study used the microarray datasets GSE31552, GSE6044 and GSE12428 from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were conducted to construct the protein-protein interaction network of DEGs and hub genes module using STRING and Cytoscape. The 67 DEGs identified consisted of 42 upregulated genes and 25 downregulated genes. The pathways predicted by KEGG and GO enrichment analyses of DEGs mainly included cell cycle, cell proliferation, glycolysis or gluconeogenesis, and tetrahydrofolate metabolic process. Further analysis of the University of California Santa Cruz and ONCOMINE databases identified 17 hub genes. Overall, the present study demonstrated hub genes that were closely associated with clinical tissue samples of LUSC, and identified TYMS, CCNB2 and RFC4 as potential novel biomarkers of LUSC. The findings of the present study contribute to an improved understanding of the molecular mechanisms of carcinogenesis and progression of LUSC, and assist with the identification of potential diagnostic and therapeutic targets of LUSC.

Identification of key modules and prognostic markers in adrenocortical carcinoma by weighted gene co-expression network analysis

Adrenocortical carcinoma (ACC) is a rare and aggressive cancer with a high relapse rate and limited treatment options. Therefore, the identification of potential prognostic markers in patients with ACC may improve early detection, survival rates and may additionally provide novel insights into the early detection of recurrence. In the present study, clinical traits and RNA-seq data of 79 patients with ACC were obtained from The Cancer Genome Atlas (TCGA). Weighted gene co-expression network analysis was carried out and 17 distinct co-expression modules were built to examine the association between the modules and the clinical traits. Of the 17 modules, two co-expression modules, which contained 214 and 168 genes, were significantly correlated with two clinical traits, tumor stage and vital status. Functional enrichment analysis was performed on the selected modules. The results showed that one of the modules was primarily enriched in cell division and the other module was enriched in metabolic pathways, suggesting their involvement in tumor progression. Furthermore, cyclin dependent kinase 1 (CDK1) and ubiquitin C (UBC) were identified as hub genes in both modules. Survival analysis revealed that the high expression of the hub genes significantly correlated with the poor survival rate of patients, suggesting that CDK1 and UBC have vital roles in the progression of ACC. In the present study, a co-expression gene module of ACC was provided and the prognostic genes that may serve as new diagnostic markers in the future were defined.

Molecular markers of prognosis in canine cortisol-secreting adrenocortical tumours

Hypercortisolism is caused by a cortisol‐secreting adrenocortical tumour (ACT) in approximately 15%‐20% of cases in dogs. Little is known about which molecular markers are associated with malignant behaviour of canine ACTs. The objective of this study was to identify molecular markers of prognosis, which could be useful to refine prognostic prediction and to identify potential treatment targets. Cortisol‐secreting ACTs were included from 40 dogs, of which follow‐up information was available. The ACTs were classified as low risk of recurrence tumours (LRT; n = 14) or moderate‐high risk of recurrence tumours (MHRT; n = 26), based on the novel histopathological Utrecht score. Normal adrenals (NAs) were included from 11 healthy dogs as reference material. The mRNA expression of 14 candidate genes was analysed in the 40 ACTs and in 11 NAs with quantitative RT‐PCR. The genes' expression levels were statistically compared between NAs, LRTs and MHRTs. Univariate and multivariate analyses were performed to determine the association of the genes' expression levels with survival. Seven genes were differentially expressed between NAs and ACTs, of which pituitary tumour‐transforming gene‐1 (PTTG1) and topoisomerase II alpha (TOP2A) were also differentially expressed between LRTs and MHRTs. In survival analyses, high expression levels of Steroidogenic factor‐1 (SF‐1), PTTG1 and TOP2A were significantly associated with poor survival. In conclusion, we have identified several genes that are part of the molecular signature of malignancy in canine ACTs. These findings can be used to refine prognostic prediction, but also offer insights for future studies on druggable targets.

Association of PTTG1 polymorphism rs1895320, rs2910200 and rs6882742 with non-functioning pituitary adenomas in Chinese Han population: a case-control study

Due to absence of clinical manifestations of hormonal hyper secretion, the treatment of Nonfunctioning pituitary adenoma (NFPA) was always delayed. PTTG1 was reported to be overexpressed in most of pituitary tumors, however, the polymorphism of PTTG1 rs1895320, rs2910200 and rs6882742 with NFPA were still not fully elucidated in NFPA. Thus, a hospital based case control study which included 79 patients and 142 healthy control participants were conducted. DNA was extracted from peripheral blood samples and genotyped by Mass Array methods. In addition, a meta-analysis of rs2910200 was also employed to further testify the conclusion. Significant difference were observed between patients and healthy controls under rs2910200 locus between allelic genotype (p = 0.0219). However, no other significant difference was observed in rs1895329 and rs6882742. In addition, a logistic regression analysis showed that the dominant model of rs2910200 were closely correlated with the NFPA susceptibility (OR = 1.951, 95% CI:1.075-3.542, p = 0.028). While no significant difference was observed in the rs1895320 and rs6882742 under dominant model, recessive model and additive model The meta-analysis results showed that the dominant model and heterozygote model can significantly increase the risk of PA (p = 0.007, OR = 1.57, 95% CI:1.14-2.18; p = 0.009, OR = 1.57, 95% CI:1.12-2.19). Whereas no significant difference were observed under the homozygous model and recessive model. In conclusion, the polymorphism of PTTG1 rs2910200 dominant model and T allelic might increase the risk of NFPA.

The long non-coding RNA PTTG3P promotes cell growth and metastasis via up-regulating PTTG1 and activating PI3K/AKT signaling in hepatocellular carcinoma

Background

Dysfunctions of long non-coding RNA (lncRNAs) have been associated with the initiation and progression of hepatocellular carcinoma (HCC), but the clinicopathologic significance and potential role of lncRNA PTTG3P (pituitary tumor-transforming 3, pseudogene) in HCC remains largely unknown.

Methods

We compared the expression profiles of lncRNAs in 3 HCC tumor tissues and adjacent non-tumor tissues by microarrays. In situ hybridization (ISH) and quantitative real-time polymerase chain reaction (qRT-PCR) were applied to assess the level of PTTG3P and prognostic values of PTTG3P were assayed in two HCC cohorts (n = 46 and 90). Artificial modulation of PTTG3P (down- and over-expression) was performed to explore the role of PTTG3P in tumor growth and metastasis in vitro and in vivo. Involvement of PTTG1 (pituitary tumor-transforming 1), PI3K/AKT signaling and its downstream signals were validated by qRT-PCR and western blot.

Results

We found that PTTG3P was frequently up-regulated in HCC and its level was positively correlated to tumor size, TNM stage and poor survival of patients with HCC. Enforced expression of PTTG3P significantly promoted cell proliferation, migration, and invasion in vitro, as well as tumorigenesis and metastasis in vivo. Conversely, PTTG3P knockdown had opposite effects. Mechanistically, over-expression of PTTG3P up-regulated PTTG1, activated PI3K/AKT signaling and its downstream signals including cell cycle progression, cell apoptosis and epithelial-mesenchymal transition (EMT)-associated genes.

Conclusions

Our findings suggest that PTTG3P, a valuable marker of HCC prognosis, promotes tumor growth and metastasis via up-regulating PTTG1 and activating PI3K/AKT signaling in HCC and might represent a potential target for gene-based therapy.

Electronic supplementary material

The online version of this article (10.1186/s12943-018-0841-x) contains supplementary material, which is available to authorized users.