Candidate Prognostic Biomarker Research Articles

HOTTIP Functions as a Key Candidate Biomarker in Head and Neck Squamous Cell Carcinoma by Integrated Bioinformatic Analysis.

Background Accumulating evidence has demonstrated the pivotal role of long noncoding RNAs (lncRNAs) in competing endogenous RNA (ceRNA) networks for predicting survival and evaluating prognosis in cancer patients. However, the pathogenesis of head and neck squamous cell carcinoma (HNSCC) remains unclear, and prognostic biomarkers for HNSCC are still lacking. Methods A total of 546 RNA sequencing profiles of HNSCC patients with clinical outcome data were obtained from the Cancer Genome Atlas (TCGA) database, providing a large sample of RNA sequencing data. From these, 71 Long noncoding RNAs lncRNAs, 8 microRNAs (miRNAs), and 16 messenger RNAs (mRNAs) were identified to construct a HNSCC-specific ceRNA network (fold change >2, P < 0.05). Univariate and multivariate Cox proportional regression models were used to assess independent indicators of prognosis. Then the expression of lncRNAs harboring prognostic value was validated in human HNSCC cell lines and tumor samples from our cohort and another two datasets from GEO (Gene Expression Omnibus) databases. Results As a result, a 3-mRNA signature and 6-lncRNA signature were identified. The six-lncRNA signature exhibited the highest prognostic value. Notably, in the six lncRNAs, HOTTIP showed the greatest prognostic value and was significantly correlated with clinical stage and histological grade of HNSCC patients. Furthermore, it was proved that HOTTIP was upregulated in HNSCC cell lines and cancerous tissues compared with corresponding normal cell lines and normal tissues. Functional assessment analysis revealed that HOTTIP might play a key role in the oncogenesis and progression of HNSCC. Conclusion The present study deepened our understanding of the ceRNA-related regulatory mechanism in the pathogenesis of HNSCC and identified candidate prognostic biomarkers for clinical outcome prediction in HNSCC. HOTTIP may function as a key candidate biomarker in HNSCC and serve as a prognostic marker for HNSCC patients.

Long Noncoding RNA Expression Signatures of Colon Cancer Based on the ceRNA Network and Their Prognostic Value.

Background The specific functional roles of long noncoding RNAs (lncRNAs) as ceRNAs in colon cancer and their potential implications for colon cancer prognosis remain unclear. In the present study, a genome-wide analysis was performed to investigate the potential lncRNA-mediated ceRNA interplay in colon cancer based on the “ceRNA hypothesis.” The prognostic value of the lncRNAs was evaluated. Methods A dysregulated lncRNA-associated ceRNA network was constructed based on the miRNA, lncRNA, and mRNA expression profiles in combination with the miRNA regulatory network by using an integrative computational method. Molecular biological techniques, including qPCR and gene knockdown techniques, were used to verify candidate targets in colon cancer. Survival analysis was performed to identify the candidate lncRNAs with prognostic value. Results Our network analysis uncovered several novel lncRNAs as functional ceRNAs through crosstalk with miRNAs. The QRT-PCR assays of patient tissues as well as gene knockdown colon cancer cells confirmed the expression of top lncRNAs and their correlation with target genes in the ceRNA network. Functional enrichment analysis predicted that differentially expressed lncRNAs might participate in broad biological functions associated with tumor progression. Moreover, these lncRNAs may be involved in a range of cellular pathways, including the apoptosis, PI3K-AKT, and EGFR signaling pathways. The survival analysis showed that the expression level of several lncRNAs in the network was correlated with the prognosis of patients with colon cancer. Conclusions This study uncovered a dysregulated lncRNA-associated ceRNA network in colon cancer. The function of the identified lncRNAs in colon cancer was preliminarily explored, and their potential prognostic value was evaluated. Our study demonstrated that lncRNAs could potentially serve as important regulators in the development and progression of colon cancer. Candidate prognostic lncRNA biomarkers in colon cancer were identified.

Long noncoding RNAs predict the survival of patients with colorectal cancer as revealed by constructing an endogenous RNA network using bioinformation analysis.

Long noncoding RNAs (lncRNAs) are aberrantly expressed in various cancers types and can function as competing endogenous RNAs (ceRNAs), which promote and maintain tumor initiation and progression. In this study, we explored the functional roles and regulatory mechanisms of lncRNAs as ceRNAs in colorectal cancer and their clinical potential as biomarkers. The RNA sequencing profiles of patients with colorectal cancer were downloaded from TCGA database, and 62 lncRNAs, 30miRNAs, and 59 mRNAs were identified to comprise the ceRNA network (fold change > 2, P < 0.01). Functional enrichment analysis suggested that the target genes of the ceRNA network may be involved in the pathways related to cancer, including the signaling pathway that regulates the pluripotency of stem cells, wnt signaling pathway, hippo signaling pathway, basal cell carcinoma, and colorectal cancer. Univariate and multivariate Cox's proportional hazard regression model revealed that five (H19, MIR31HG, HOTAIR, WT1‐AS, and LINC00488) out of 62 lncRNAs were closely related to the overall survival (OS) (P < 0.05). Furthermore, the five‐lncRNA model could be an independent prognostic model in colorectal cancer. We computed for the risk function and constructed a risk score based on the five lncRNAs. Results showed that patients with high‐risk scores have poor survival rates. Additionally, combing the risk score and other clinicopathological features, we can better predict the patient's survival probabilities. Furthermore, we validate our model in the GSE38832 dataset. Collectively, our study has provided a deeper understanding of the lncRNA‐related ceRNA regulatory mechanism in CRC and identified five‐lncRNA model, which could be considered as candidate prognostic biomarkers and therapeutic targets.

MACC1 expression as a candidate prognostic biomarker in colorectal cancer patients receiving adjuvant oxaliplatin-based therapy.

567 Background: MACC1, part of the HGF-MET pathway, drives proliferation and regulation of MET expression in vitro. In vivo, MACC1 is associated with tumor progression and studies suggest greater MACC1 expression is associated with resistance to platinum-based chemotherapy. We hypothesized that MACC1 may be a prognostic biomarker in colorectal cancer (CRC). Methods: MACC1 expression was evaluated by immunohistochemistry on tumor microarrays (N = 428). Patients were stage I-III CRC who received an oxaliplatin-based regimen (either with 5-FU (FOLFOX) or capecitabine (XELOX)) within the HeCOG 6C/08 observational study. MACC1 expression was assessed by a blinded GI pathologist using a scale ranging from 0 (no staining) to 3+ (strong expression). Each patient had at least 3 samples and the strongest result was used for the final score. MACC1 positivity was defined as ≥2+ expression and 0-1+ as MACC1-. Cox regression models were used to estimate hazard ratios (HR) for the association of MACC1 expression with patient characteristics, disease-free (DFS), and overall survival (OS). Results: 400/428 CRC tumors were evaluable: 322 (80.5%) were MACC1+ and 78 (19.5%) MACC1-. Mucinous features were less likely in MACC1+ patients (24% vs. 38%, p = 0.02). Other unfavorable features including grade, lymphovascular invasion, perineural invasion, and tumor mutational burden were not significantly different. There was no difference for stage, microsatellite instability, BRAF, KRAS, or NRASstatus between MACC1+/- cancers. There was a trend towards worse survival in MACC1+ patients regardless of treatment (DFS HR 1.55 [95% CI: 0.87, 2.76], OS HR 1.59 [95% CI 0.74, 3.4]). This difference was not statistically significant for OS (p = 0.26) or DFS (p = 0.08) even when stratified by clinicopathologic variables. Conclusions: Patients with MACC1+ CRC tumors who received adjuvant oxaliplatin-based therapy were less likely to have mucinous histology. They had a trend toward independently worse survival that was not significant when accounting for stage and clinicopathologic variables. Studies focused on the predictive role of MACC1 and oxaliplatin in stage III CRC are in progress.

Down-regulation of miR-1181 indicates a dismal prognosis for nasopharyngeal carcinoma and promoted cell proliferation and metastasis by modulating Wnt/β-catenin signaling.

Our study aimed to investigate the expression pattern, clinicopathological feature and prognostic role of miR-1181 in nasopharyngeal carcinoma (NPC), and to determine the functional effects and potential mechanism of miR-1181 in NPC. The expression levels of miR-1181 were determined in NPC tissues and cell lines by RT-PCR. The clinical data were interpreted by chi-square test, univariate analysis, and multivariate analysis. The effect of PVT1 on proliferation was evaluated by CCK-8 and colony formation assays, and migration and invasion ability were evaluated by transwell and wound-healing assays. The association between miR-1181 and Wnt/β-catenin pathway was analyzed by Western blot. We found that miR-1181 expression was significantly down-regulated in both NPC tissues and cell lines. Low expression of miR-1181 was significantly associated with N stage (p=0.013), clinical stage (p=0.037) and grade (p=0.033). Clinical assays showed that patients with low miR-1181 expression had shorter overall survival time than those with high miR-1181 expression (p=0.0007). Multivariate analysis revealed that miR-1181 expression was independently associated with the overall survival. Functional investigations indicated that overexpression of miR-1181 suppressed NPC cells proliferation, migration and invasion. Mechanistically, forced miR-1181 expression suppressed the activity of Wnt/β-catenin pathway. Our findings proved that miR-1181 may serve as a candidate prognostic biomarker and target for new therapies in NPC patients.

Downregulation of long non-coding RNA DBH-AS1 inhibits osteosarcoma progression by PI3K-AKT signaling pathways and indicates good prognosis.

Long non-coding RNA DBH-AS1 (DBH-AS1) has emerged as a novel regulator in cancer initiation and progression of several tumors. However, the expression of DBH-AS1 in osteosarcoma and its effect on the tumorigenesis of osteosarcoma are unclear. The purpose of this study was to determine the role of DBH-AS1 in osteosarcoma progression. The expression level of DBH-AS1 in 119 pairs of osteosarcoma tissues and five cell lines was detected by quantitative Real Time-Polymerase Chain Reaction (qRT-PCR). The association of DBH-AS1 expression with clinicopathological factors and prognosis was also analyzed. Cell proliferation was measured by Cell Counting Kit-8 (CCK-8), EdU and cell colony formation assays and apoptosis in MG63 and U2OS cells was examined by flow cytometry. Following that, transwell invasion and wound-healing assays were used to explore cell migration and invasion, respectively. The expression of the PI3K/Akt pathway-related proteins was examined by Western blot analysis. We observed that DBH-AS1 was distinctly overexpressed in osteosarcoma tissue and cells, and associated with lymph node status and metastasis status. Osteosarcoma patients with a higher DBH-AS1 expression showed significantly poorer overall survival than those with lower DBH-AS1 expression. Multivariate analysis demonstrated that high DBH-AS1 expression was an independent poor prognostic factor for osteosarcoma patients. Functional assays revealed that knockdown of DBH-AS1 inhibited cell proliferation, migration and invasion, while promoted apoptosis in osteosarcoma. Moreover, suppression of DBH-AS1 could inhibit the activation of the PI3K/Akt pathway, which was demonstrated by examining the expression levels of p-PI3K and p-Akt. Our data first reported that DBH-AS1 may act as an oncogenic lncRNA by modulating the PI3K/Akt pathway in osteosarcoma, which may serve as a candidate prognostic biomarker and target for new therapies in osteosarcoma.

Low P4HA2 and high PRTN3 expression predicts poor survival in patients with pancreatic cancer

Background: The tumor microenvironment in pancreatic cancer has a multifaceted role in disease development and progression. Prolyl 4-hydroxylase subunit alpha 2 (P4HA2) and proteinase 3 (PRTN3) are involved in the synthesis and degradation of collagen in the tumor microenvironment and have been identified as prognostic biomarker candidates for pancreatic cancer in our previous mass spectrometric study. This study aimed at validating prognostic performance of P4HA2 and PRTN3 in a larger cohort of patients.Methods: The expression of P4HA2 and PRTN3 was evaluated with tissue microarrays and immunohistochemistry in 140 patients with pancreatic cancer who underwent surgical resection. Kaplan–Meier and Cox proportional hazards regression modeling were used to explore the association of P4HA2 and PRTN3, either separately or combined, with clinicopathological factors and survival.Results: Most tumors were positive for P4HA2 (133/140, 95%), whereas 77 tumors (55%) were positive for PRTN3. Expression levels of P4HA2 and PRTN3 did not separately correlate with disease-free or overall survival, in either uni- or multivariable analysis. However, a low P4HA2 and high PRTN3 expression correlated with shorter disease-free survival (median 7.0 vs. 13.4 months, adjusted HR 3.24, 95% CI: 1.13–9.25, p = .028) and overall survival (median 8.5 vs. 25.8 months, adjusted HR 8.14, 95% CI: 3.41–19.44, p < .001).Conclusion: Our data show that a low P4HA2 and high PRTN3 expression correlates with poor survival in patients with pancreatic cancer, indicating the involvement of collagen deposition in the restraint of the tumor. The tumoral expression of PRTN3 reinforces the therapeutic potential of PR1-targeting immunotherapy in pancreatic cancer.

TREM2 acts as a tumor suppressor in hepatocellular carcinoma by targeting the PI3K/Akt/\u03b2-catenin pathway

Triggering receptor expressed on myeloid cells 2 (TREM2) is involved in nonmalignant pathological processes. However, TREM2’s function in malignant diseases, especially in hepatocellular carcinoma (HCC) remains unknown. In the present study, we report that TREM2 is a novel tumor suppressor in HCC. TREM2 expression was obviously decreased in hepatoma cells (especially metastatic HCC cells), and in most human HCC tissues (especially extrahepatic metastatic tumors). Reduced tumor TREM2 expression was correlated with poor prognosis of HCC patients, and with aggressive pathological features (BCLC stage, tumor size, tumor encapsulation, vascular invasion, and tumor differentiation). TREM2 knockdown substantially promoted cell growth, migration, and invasion in vitro and in vivo, while TREM2 overexpression produced the opposite effect. TREM2 suppressed HCC metastasis by inhibiting epithelial-mesenchymal transition, accompanied by abnormal expression of epithelial and mesenchymal markers. Further study revealed that downregulation of TREM2 in HCC was regulated by miR-31-5p. Moreover, by directly interacting with β-catenin, TREM2 attenuated oncogenic and metastatic behaviors by inhibiting Akt and GSK3β phosphorylation, and activating β-catenin. TREM2 suppressed carcinogenesis and metastasis in HCC by targeting the PI3K/Akt/β-catenin pathway. Thus, we propose that TREM2 may be a candidate prognostic biomarker in malignant diseases and TREM2 restoration might be a prospective strategy for HCC therapy.

Identification of Prognostic Biomarker Signatures and Candidate Drugs in Colorectal Cancer: Insights from Systems Biology Analysis.

Background and objectives: Colorectal cancer (CRC) is the second most common cause of cancer-related death in the world, but early diagnosis ameliorates the survival of CRC. This report aimed to identify molecular biomarker signatures in CRC. Materials and Methods: We analyzed two microarray datasets (GSE35279 and GSE21815) from the Gene Expression Omnibus (GEO) to identify mutual differentially expressed genes (DEGs). We integrated DEGs with protein–protein interaction and transcriptional/post-transcriptional regulatory networks to identify reporter signaling and regulatory molecules; utilized functional overrepresentation and pathway enrichment analyses to elucidate their roles in biological processes and molecular pathways; performed survival analyses to evaluate their prognostic performance; and applied drug repositioning analyses through Connectivity Map (CMap) and geneXpharma tools to hypothesize possible drug candidates targeting reporter molecules. Results: A total of 727 upregulated and 99 downregulated DEGs were detected. The PI3K/Akt signaling, Wnt signaling, extracellular matrix (ECM) interaction, and cell cycle were identified as significantly enriched pathways. Ten hub proteins (ADNP, CCND1, CD44, CDK4, CEBPB, CENPA, CENPH, CENPN, MYC, and RFC2), 10 transcription factors (ETS1, ESR1, GATA1, GATA2, GATA3, AR, YBX1, FOXP3, E2F4, and PRDM14) and two microRNAs (miRNAs) (miR-193b-3p and miR-615-3p) were detected as reporter molecules. The survival analyses through Kaplan–Meier curves indicated remarkable performance of reporter molecules in the estimation of survival probability in CRC patients. In addition, several drug candidates including anti-neoplastic and immunomodulating agents were repositioned. Conclusions: This study presents biomarker signatures at protein and RNA levels with prognostic capability in CRC. We think that the molecular signatures and candidate drugs presented in this study might be useful in future studies indenting the development of accurate diagnostic and/or prognostic biomarker screens and efficient therapeutic strategies in CRC.

Identification of candidate diagnostic and prognostic biomarkers for pancreatic carcinoma.

BackgroundPancreatic carcinoma (PC) is one of the most aggressive cancers affecting human health. It is essential to identify candidate biomarkers for the diagnosis and prognosis of PC. The present study aimed to investigate the diagnosis and prognosis biomarkers of PC.MethodsDifferentially expressed genes (DEGs) were identified from the mRNA expression profiles of GSE62452, GSE28735 and GSE16515. Functional analysis and the protein-protein interaction network analysis was performed to explore the biological function of the identified DEGs. Diagnosis markers for PC were identified using ROC curve analysis. Prognosis markers were identified via survival analysis of TCGA data. The protein expression pattern of the identified genes was verified in clinical tissue samples. A retrospective clinical study was performed to evaluate the correlation between the expression of candidate proteins and survival time of patients. Moreover, comprehensive analysis of the combination of multiple genes/proteins for the prognosis prediction of PC was performed using both TCGA data and clinical data. In vitro studies were undertaken to elaborate the potential roles of these biomarkers in clonability and invasion of PC cells.FindingsIn total, 389 DEGs were identified. These genes were mainly associated with pancreatic secretion, protein digestion and absorption, cytochrome P450 drug metabolism, and energy metabolism pathway. The top 10 genes were filtered out following Fisher's exact test. ROC curve analysis demonstrated that TMPRSS4, SERPINB5, SLC6A14, SCEL, and TNS4 could be used as biomarkers for the diagnosis of PC. Survival analysis of TCGA data and clinical data suggested that TMC7, TMPRSS4, SCEL, SLC2A1, CENPF, SERPINB5 and SLC6A14 can be potential biomarkers for the prognosis of PC. Comprehensive analysis show that a combination of identified genes/proteins can predict the prognosis of PC. Mechanistically, the identified genes attributes to clonability and invasiveness of PC cells.InterpretationWe synthesized several sets of public data and preliminarily clarified pathways and functions of PC. Candidate molecular markers were identified for diagnosis and prognosis prediction of PC including a novel gene, TMC7. Moreover, we found that the combination of TMC7, TMPRSS4, SCEL, SLC2A1, CENPF, SERPINB5 and SLC6A14 can serve as a promising indicator of the prognosis of PC patients. The candidate proteins may attribute to clonability and invasiveness of PC cells. This research provides a novel insight into molecular mechanisms as well as diagnostic and prognostic markers of PC.FundNational Natural Science Foundation of China [No. 81602646 & 81802339], Natural Science Foundation of Guangdong Province [No. 2016A030310254] and China Postdoctoral Science Foundation [No. 2016M600648].

Something Old, Something New: The Tumor Microenvironment Comes of Age.

In this issue, Weeraratna and colleagues demonstrate that observed differences in melanoma aggressiveness in younger versus older patients can be explained not just by cell-intrinsic alterations over time, but by age-dependent changes in fibroblasts and the extracellular matrix they help create. Their findings identify novel cellular targets for melanoma therapy, as well as candidate prognostic biomarkers to better inform clinical decisions for patients with melanoma.See related article by Kaur et al., p. 64.See related article by Ecker et al., p. 82.

Identification of Prognostic Biomarkers and Drugs Targeting Them in Colon Adenocarcinoma: A Bioinformatic Analysis.

Objective: To identify prognostic biomarkers and drugs that target them in colon adenocarcinoma (COAD) based on the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. Methods: The TCGA dataset was used to identify the top 50 upregulated differentially expressed genes (DEGs), and Gene Expression Omnibus profiles were used for validation. Survival analyses were conducted with the TCGA dataset using the RTCGAToolbox package in the R software environment. Drugs targeting the candidate prognostic biomarkers were searched in the DrugBank and herbal databases. Results: Among the top 50 upregulated DEGs in patients with COAD in the TCGA dataset, the Wnt signaling pathway and cytokine-cytokine receptor interactions and pathways in cancer Kyoto Encyclopedia of Genes and Genomes pathway analysis were enriched in DEGs. Tissue development and regulation of cell proliferation were the main Gene Ontology biological processes associated with upregulated DEGs. MYC and KLK6 were overexpressed in tumors validated in the TCGA, GSE41328, and GSE113513 databases (all P < .001) and were significantly associated with overall survival in patients with COAD (P = .021 and P = .047). Nadroparin and benzamidine were identified as inhibitors of MYC and KLK6 in DrugBank, and 8 herbs targeting MYC, including Da Huang (Radix Rhei Et Rhizome), Hu Zhang (Polygoni Cuspidati Rhizoma Et Radix), Huang Lian (Coptidis Rhizoma), Ban Xia (Arum Ternatum Thunb), Tu Fu Ling (Smilacis Glabrae Rhixoma), Lei Gong Teng (Tripterygii Radix), Er Cha (Catechu), and Guang Zao (Choerospondiatis Fructus), were identified. Conclusion: MYC and KLK6 may serve as candidate prognostic predictors and therapeutic targets in patients with COAD.

Determining consistent prognostic biomarkers of overall survival and vascular invasion in hepatocellular carcinoma.

Background: Potential prognostic biomarker candidates for hepatocellular carcinoma (HCC) are abundant, but their generalizability is unexplored. We cross-validated markers of overall survival (OS) and vascular invasion in independent datasets. Methods: The literature search yielded 318 genes related to survival and 52 related to vascular invasion. Validation was performed in three datasets (RNA-seq, n = 371; Affymetrix arrays, n = 91; Illumina gene chips, n = 135) by uni- and multivariate Cox regression and Mann–Whitney U-test, separately for Asian and Caucasian patients. Results: One hundred and eighty biomarkers remained significant in Asian and 128 in Caucasian subjects at p < 0.05. After multiple testing correction BIRC5 (p = 1.9 × 10−10), CDC20 (p = 2.5 × 10−9) and PLK1 (p = 3 × 10−9) endured as best performing genes in Asian patients; however, none remained significant in the Caucasian cohort. In a multivariate analysis, significance was reached by stage (p = 0.0018) and expression of CENPH (p = 0.0038) and CDK4 (p = 0.038). KIF18A was the only gene predicting vascular invasion in the Affymetrix and Illumina cohorts (p = 0.003 and p = 0.025, respectively). Conclusion: Overall, about half of biomarker candidates failed to retain prognostic value and none were better than stage predicting OS. Impact: Our results help to eliminate biomarkers with limited capability to predict OS and/or vascular invasion.

Circulating CEA-dNLR score predicts clinical outcome of metastatic gallbladder cancer patient.

Cancer-related inflammation promotes gallbladder tumorigenesis and metastasis of gallbladder cancer (mGBC). The levels of circulating inflammatory-related cell and protein as well as the ratios of them may imply the severity of chronic inflammation in GBC patients, and all of them are candidate prognostic biomarkers for mGBC. In our study, pre-treatment circulating immune cell, fibrinogen (Fib), albumin (Alb), and pre-albumin (pAlb) were detected in 220 mGBC patients, and we calculated neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), Alb-to-Fib ratio (AFR), and Fib-to-pAlb ratio (FPR) replying on the detection. Three years' follow-up was carried out in those patients, and we investigated the possible associations between those biomarkers and three years' overall survival (OS) of these patients using X-tile software, Kaplan-Meier curve, Cox regression, and time-dependent receiver operating characteristics (ROC). Our results showed that OS of the patients with high pAlb and LMR was significantly superior to the cases with the low biomarkers, respectively. However, survival of the cases with high CEA, dNLR, and FPR was significantly inferior to the patients with low levels of those biomarkers. Area under the curve (AUC) of time-dependent ROC of CEA and dNLR was higher than pAlb, LMR, and FPR, respectively. Additionally, higher CEA-dNLR score (adjusted HR=3.09, 95% CI=1.01-4.51 for the score one; adjusted HR=4.99, 95% CI=2.32-7.21 for the score two) was significantly associated with reduced survival of the patients, and AUC of the score for predicting clinical outcome of mGBC patients was 0.756, and it was significantly higher than the single CEA and dNLR, respectively. Our findings implied that pretreatment CEA-dNLR score was superior to the other biomarkers to predict OS of mGBC patients, and it was an independent prognostic factor for the disease.

Functional Long Noncoding RNAs (lncRNAs) in Clear Cell Kidney Carcinoma Revealed by Reconstruction and Comprehensive Analysis of the lncRNA-miRNA-mRNA Regulatory Network.

BackgroundA variety of treatment strategies have been developed for clear cell kidney carcinoma (KIRC); however, there is still a need for effective therapeutic targets and prognostic molecular biomarkers. Given that long noncoding RNAs (lncRNAs) has been emerging as an important regulator in tumorigenesis, we explored potential functional lncRNAs in KIRC by comprehensively analyzing the lncRNA–miRNA–mRNA regulatory network with bioinformatics processing tools.Material/MethodsRNA-seq/miRNA-seq data of KIRC in The Cancer Genome Atlas (TCGA) were obtained and analyzed. The “edgeR” package in R software was used to identify differentially expressed lncRNAs (DElncRNAs, differentially expressed long noncoding RNAs), miRNAs (DEmiRNAs, differentially expressed micro RNAs), and mRNAs (DEmRNAs, differentially expressed messenger RNAs) in KIRC and normal samples. A global triple network was conducted based on the competing endogenous RNA (ceRNA) theory, and survival analysis was conducted by “survival” package in R software.ResultsA total of 4246 DElncRNAs, 179 DEmiRNAs, and 5758 DEmRNAs were identified, among which a subset of them (321 lncRNAs, 26 miRNAs, and 1068 mRNAs) were found to constitute a global ceRNA network in KIRC. Four lncRNAs (ENTPD3-AS1, FGD5-AS1, LIFR-AS1, and UBAC2-AS1) were revealed to be potential therapeutic targets as well as prognostic biomarkers of KIRC by our extensive functional analysis.ConclusionsWe reported here the identification of functional lncRNAs in KIRC via a TCGA data-based bioinformatics analysis. We believe that this study might contribute to improving the comprehension of the lncRNA-mediated ceRNA regulatory mechanisms in the tumorigenesis of KIRC. Meanwhile, our results suggested that 4 lncRNAs might act as potential therapeutic targets or candidate prognostic biomarkers in KIRC.

Downregulation of ZC3H14 driven by chromosome 14q31 deletion promotes hepatocellular carcinoma progression by activating integrin signaling.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality worldwide. Genomic copy number deletion at chromosome 14q31.1-32.13 was frequently observed in HCC; however, the relevant functional target(s) at that locus is not well determined. Here, we performed integrative genomic analyses and identified zinc finger CCCH-type containing 14 (ZC3H14) as a promising candidate at 14q31.1-32.13. We observed frequent copy number deletion (17.1%) and downregulation of ZC3H14 in primary HCC tissues. Downregulation of ZC3H14 was significantly associated with poor outcomes of patients with HCC. Overexpression of ZC3H14 in HCC cell lines significantly suppressed HCC cells growth in vitro and metastasis in vivo. In contrast, RNA interference silencing of ZC3H14 inhibited its tumor-suppressive function. Mechanismly, through combing bioinformatics analyses and experimental investigation, we demonstrated that loss of ZC3H14 promotes HCC progression through enhancing integrin pathway. This study suggests that ZC3H14 functions as a novel tumor suppressor and is a candidate prognostic biomarker for HCC patients.

RPLP1 promotes tumor metastasis and is associated with a poor prognosis in triple-negative breast cancer patients

BackgroundCancer metastasis is the major reason for cancer related deaths, and the mechanism of cancer metastasis still unclear. RPLP1, a member of a group of proteins known as ribosomal proteins, is associated with tumorigenesis and primary cell immortalization and is involved in cellular transformation. However, the expression and potential function of RPLP1 in TNBC remain unclear.MethodsThe expression of RPLP1 in TNBC tissues and cell lines were detected with Real-Time PCR and western blotting. 81 cases of TNBC tissue samples and adjacent non-tumor tissue samples were tested by immunochemistry to determine the correlation between the RPLP1 expression and clinicopathological characteristics. In vitro, we determined the role and mechanistic pathways of RPLP1 in tumor metastasis in TNBC cell lines.ResultsIn this study, we detected high levels of RPLP1 expression in TNBC samples and cell lines. RPLP1 is upregulated in triple-negative breast cancer (TNBC) tissues and cells, and high expression levels correlate with an increased risk of recurrence and metastasis. Furthermore, high RPLP1 expression was associated with a poor prognosis and was an independent prognostic marker for TNBC. In RPLP1-induced cancer metastasis, RPLP1 may increase cancer cell invasion, which is likely the result of its effect on the cancer cell epithelial-mesenchymal transition.ConclusionsAltogether, our findings indicate RPLP1 is a poor prognostic potential biomarker and anti-metastasis candidate therapeutic target in triple-negative breast cancer.

Novel Genomic Biomarker Panel Predictive of Aggressive Disease in African American Men with Prostate Cancer

Mutations in the E26 transforming specific (ETS) transcription factors occur early in the oncogenic process of prostate cancer. These mutations behave in a race dependent manner with the majority of European American (EA) men possessing ERG positive (ERG+) tumors while ≥75% of African American (AA) men have ERG negative (ERG-) tumors. In order to establish clinically relevant biomarkers in AA men, we studied ETS gene expression differences among AA men and EA men and identified race specific ETS negative (ETS-) genes that predict for clinically relevant outcomes. Previously published datasets from the Decipher Genomic Resource Information Database (GRID) were used to obtain microarray data. The validated microarray-based ETS positive (ETS+) (ERG or ETV1/4/5) over expression was used to determine ETS+ status in the GRID database. Samples with overexpression of ERG, ETV1-5, and FLI1 were categorized as ETS+. Chi square (X2)/Fisher Exact method was used to assess the race differences in clinico-pathologic endpoints such as extraprostatic extension, seminal vesicle invasion, pathologic Gleason Score, and the post-surgical Cancer of the Prostate Risk Assessment Score (CAPRA-S) . Logistic regression model was used to analyze the association between aforementioned clinico-pathologic endpoints and ETS status. Genes that showed differential expression were evaluated. On multivariable logistic regression analysis, race was found to be the strongest predictor of ETS- status. Analysis showed that AA men were four times more likely to be ETS- than EA men (p<0.001). Using a q value ≤0.05 and an expression fold change level of 0.05, we identified 3047 genes (6.6%) that were differentially expressed based on ETS status. Of these, 248 were found to be differentially expressed in a race-specific manner. Using a false-discovery rate q<0.1 we identified 143 genes that predicted for one or more clinical endpoint. In order to determine which of these race specific ETS- genes are significantly overexpressed in tumors we selected genes that met all three of the following criteria; significantly overexpressed in ETS- compared to ETS+ tumors, preferentially overexpressed in AA and not in EA, and predictive for one or more adverse outcome in a race-specific manner. Using this criteria, we have identified a 19-gene panel that includes ADAMTS1, AFF3, ANKRD20, ANPEP, CCL3, CYP4F35, FAR2P1, INPP4B, MAP1LC3, MIPEP, NPIPB7, NPNT, OPHN1, OR4K7P, PCGEM1, RLN2, SCIN, SPINK1, and TTN. In an effort to elucidate biologic features associated with aggressiveness of prostate cancer in AA men, we have identified ETS- biomarkers that predict for one or more adverse clinical outcome in AA men. Our investigation found 19 ETS- genes that are both overexpressed in AA men and predictive of clinical outcomes thus representing ideal candidates for prognostic biomarkers.

Comprehensive Bioinformatic Analysis Genes Associated to the Prognosis of Liposarcoma.

BackgroundLiposarcoma is the most common type of soft tissue sarcoma, but its molecular mechanism is poorly defined. This study aimed to identify genes crucial to the pathogenesis of liposarcoma and to explore their functions, related pathways, and prognostic value.Material/MethodsDifferentially expressed genes (DEGs) in the GSE59568 dataset were screened. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to investigate the DEGs at the functional level. Protein-protein interaction (PPI) networks and module analysis were applied to identify hub genes from among the DEGs. The GSE30929 dataset was used to validate the relationship between hub genes and the distant recurrence-free survival (DRFS) of liposarcoma patients using Cox model analysis.ResultsA total of 1111 DEGs were identified. GO and KEGG pathway analysis indicated that the DEGs were mainly associated with lipopolysaccharides and pathways in cancer. The PPI network and module analysis identified 10 hub genes from the DEG network. The Cox model identified 3 genes (NIP7, RPL10L, and MCM2) significantly associated with DRFS. The risk score calculated by the Cox model of the NIP7-RPL10L-MCM2 signature could largely predict the 1-, 3-, and 5-year DRFS of liposarcoma patients, and the prognostic value was even higher for subtypes of liposarcoma.ConclusionsThis study identified genes that might play critical roles in liposarcoma pathogenesis as well as a 3-gene-based signature that could be used as a candidate prognostic biomarker for patients with liposarcoma.

P2.01-69 EZH2-Mediated Epigenetic Suppression Of GDF15 Predicts a Poor Prognosis and Regulates Cell Proliferation in Non-Small Cell Lung Cancer

Growth differentiation factor 15 (GDF15), a member of the TGF-β superfamily of cytokines, has been reported to exert very heterogeneous functions in various tumors. However, the role of GDF15 and its underlying mechanism in mediating non-small cell lung cancer (NSCLC) progression remain unknown. GDF15 expression level was analyzed in 66 NSCLC tissues by quantitative reverse transcription PCR (qRT-PCR). The effect of GDF15 on proliferation was evaluated by MTT and colony formation assays, flow cytometric analysis. NSCLC cells transfected with pcDNA-GDF15 or empty vector were injected into nude mice to study the effect of GDF15 on tumorigenesis in vivo. Chromatin immunoprecipitation (ChIP) assay was used to investigate the mechanism of action of GDF15 in the NSCLC cells. In this study, we found that GDF15 is down-regulated in paired NSCLC tissues and is correlated with poor clinical outcomes in NSCLC. Further experiments demonstrated that overexpression of GDF15 significantly repressed NSCLC proliferation both in vitro and in vivo. Mechanistic studies reveal that inhibition of EZH2 expression prevented its binding to the GDF15 promoter region and reduced the trimethylation modification pattern of H3K27. Together, our data uncover that GDF15 is a direct target of EZH2, and as a regulator of proliferation, might serve as a candidate prognostic biomarker and target for new therapies in human NSCLC.