Qing Wen

QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics

BackgroundGene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying potential small molecule compounds, which may be further investigated as candidates for repurposing to treat diseases. The public release of voluminous data from the Library of Integrated Cellular Signatures (LINCS) programme further enhanced the utilities and potentials of gene expression connectivity mapping in biomedicine.ResultsWe describe QUADrATiC (http://go.qub.ac.uk/QUADrATiC), a user-friendly tool for the exploration of gene expression connectivity on the subset of the LINCS data set corresponding to FDA-approved small molecule compounds. It enables the identification of compounds for repurposing therapeutic potentials. The software is designed to cope with the increased volume of data over existing tools, by taking advantage of multicore computing architectures to provide a scalable solution, which may be installed and operated on a range of computers, from laptops to servers. This scalability is provided by the use of the modern concurrent programming paradigm provided by the Akka framework. The QUADrATiC Graphical User Interface (GUI) has been developed using advanced Javascript frameworks, providing novel visualization capabilities for further analysis of connections. There is also a web services interface, allowing integration with other programs or scripts.ConclusionsQUADrATiC has been shown to provide an improvement over existing connectivity map software, in terms of scope (based on the LINCS data set), applicability (using FDA-approved compounds), usability and speed. It offers potential to biological researchers to analyze transcriptional data and generate potential therapeutics for focussed study in the lab. QUADrATiC represents a step change in the process of investigating gene expression connectivity and provides more biologically-relevant results than previous alternative solutions.

Connectivity mapping using a combined gene signature from multiple colorectal cancer datasets identified candidate drugs including existing chemotherapies

BackgroundWhile the discovery of new drugs is a complex, lengthy and costly process, identifying new uses for existing drugs is a cost-effective approach to therapeutic discovery. Connectivity mapping integrates gene expression profiling with advanced algorithms to connect genes, diseases and small molecule compounds and has been applied in a large number of studies to identify potential drugs, particularly to facilitate drug repurposing. Colorectal cancer (CRC) is a commonly diagnosed cancer with high mortality rates, presenting a worldwide health problem. With the advancement of high throughput omics technologies, a number of large scale gene expression profiling studies have been conducted on CRCs, providing multiple datasets in gene expression data repositories. In this work, we systematically apply gene expression connectivity mapping to multiple CRC datasets to identify candidate therapeutics to this disease.ResultsWe developed a robust method to compile a combined gene signature for colorectal cancer across multiple datasets. Connectivity mapping analysis with this signature of 148 genes identified 10 candidate compounds, including irinotecan and etoposide, which are chemotherapy drugs currently used to treat CRCs. These results indicate that we have discovered high quality connections between the CRC disease state and the candidate compounds, and that the gene signature we created may be used as a potential therapeutic target in treating the disease. The method we proposed is highly effective in generating quality gene signature through multiple datasets; the publication of the combined CRC gene signature and the list of candidate compounds from this work will benefit both cancer and systems biology research communities for further development and investigations.

The prognostic significance of DAPK1 in bladder cancer

Bladder cancer is one of the leading causes of cancer-related death in men, however, there was only limited effective treatment for invasive bladder cancer. DAPK1 has been shown to play important role in apoptosis and autophagy to suppress cancer progression. Previous results have shown that DAPK1 promoter was hypermethylated in the majority of bladder cancer specimens, however, the prognostic significance of DAPK1 in bladder cancer has yet to be demonstrated. In the present study, we found that DAPK1 expression was negatively associated with tumor stage and a low level expression of DAPK1 in bladder cancer specimens were associated with shorter survival in bladder cancer patients in 3 independent bladder cancer datasets (n = 462). Further investigation showed that FGFR3 knockdown resulted in downregulation of DAPK1 in bladder cancer cell line, suggesting that FGFR3 may be an upstream factor of DAPK1. Further analysis of the 3 independent bladder cancer datasets have identified ACOX1, UPK2, TRAK1, PLEKHG6 and MT1X genes had their expression significantly correlated with that of DAPK1. Knockdown of DAPK1 in bladder cancer T24 cells resulted in downregulation of ACOX1, UPK2 and TRAK1. Interestingly, TRAK1, by itself, was a favorable prognostic marker in the 3 independent bladder cancer datasets. Importantly, by using connectivity mapping with DAPK1-associated gene signature, we found that vemurafenib and trametinib could possibly reverse DAPK1-associated gene signature, suggesting that inhibition of Raf/MEK pathway may be a potential therapeutic approach for bladder cancer. Indeed, treatment of vemurafenib in T24 bladder cancer cells resulted in upregulation of DAPK1 confirming our connectivity mapping, while knockdown of DAPK1 resulted in reduced sensitivity towards inhibition of Braf signaling by vemurafenib. Together, our results suggest that DAPK1 is an important prognostic marker and therapeutic target for bladder cancer and have identified possible therapeutic agents for future testing in bladder cancer models with low DAPK1 expression.

Deubiquitinating Enzyme USP9X Suppresses Tumor Growth via LATS Kinase and Core Components of the Hippo Pathway

The core LATS kinases of the Hippo tumor suppressor pathway phosphorylate and inhibit the downstream transcriptional co-activators YAP and TAZ, which are implicated in various cancers. Recent studies have identified various E3 ubiquitin ligases that negatively regulate the Hippo pathway via ubiquitination, yet few deubiquitinating enzymes (DUB) have been implicated. In this study, we report the DUB USP9X is an important regulator of the core kinases of this pathway. USP9X interacted strongly with LATS kinase and to a lesser extent with WW45, KIBRA, and Angiomotin, and LATS co-migrated exclusively with USP9X during gel filtration chromatography analysis. Knockdown of USP9X significantly downregulated and destabilized LATS and resulted in enhanced nuclear translocation of YAP and TAZ, accompanied with activation of their target genes. In the absence of USP9X, cells exhibited an epithelial-to-mesenchymal transition phenotype, acquired anchorage-independent growth in soft agar, and led to enlarged, disorganized, three-dimensional acini. YAP/TAZ target gene activation in response to USP9X knockdown was suppressed by knockdown of YAP, TAZ, and TEAD2. Deletion of USP9X in mouse embryonic fibroblasts resulted in significant downregulation of LATS. Furthermore, USP9X protein expression correlated positively with LATS but negatively with YAP/TAZ in pancreatic cancer tissues as well as pancreatic and breast cancer cell lines. Overall, these results strongly indicate that USP9X potentiates LATS kinase to suppress tumor growth. Cancer Res; 77(18); 4921-33. ©2017 AACR.

The prognostic significance of Cdc6 and Cdt1 in breast cancer

DNA replication is a critical step in cell proliferation. Overexpression of MCM2-7 genes correlated with poor prognosis in breast cancer patients. However, the roles of Cdc6 and Cdt1, which work with MCMs to regulate DNA replication, in breast cancers are largely unknown. In the present study, we have shown that the expression levels of Cdc6 and Cdt1 were both significantly correlated with an increasing number of MCM2-7 genes overexpression. Both Cdc6 and Cdt1, when expressed in a high level, alone or in combination, were significantly associated with poorer survival in the breast cancer patient cohort (n = 1441). In line with this finding, the expression of Cdc6 and Cdt1 was upregulated in breast cancer cells compared to normal breast epithelial cells. Expression of Cdc6 and Cdt1 was significantly higher in ER negative breast cancer, and was suppressed when ER signalling was inhibited either by tamoxifen in vitro or letrozole in human subjects. Importantly, breast cancer patients who responded to letrozole expressed significantly lower Cdc6 than those patients who did not respond. Our results suggest that Cdc6 is a potential prognostic marker and therapeutic target in breast cancer patients.

DAPK1 as an independent prognostic marker in liver cancer

The death-associated protein kinase 1 (DAPK1) can act as an oncogene or a tumor suppressor gene depending on the cellular context as well as external stimuli. Our study aims to investigate the prognostic significance of DAPK1 in liver cancer in both mRNA and protein levels. The mRNA expression of DAPK1 was extracted from the Gene Expression Omnibus database in three independent liver cancer datasets while protein expression of DAPK1 was detected by immunohistochemistry in our Chinese liver cancer patient cohort. The associations between DAPK1 expression and clinical characteristics were tested. DAPK1 mRNA expression was down-regulated in liver cancer. Low levels of DAPK1 mRNA were associated with shorter survival in a liver cancer patient cohort (n = 115; p = 0.041), while negative staining of DAPK1 protein was significantly correlated with shorter time to progression (p = 0.002) and overall survival (p = 0.02). DAPK1 was an independent prognostic marker for both time to progression and overall survival by multivariate analysis. Liver cancer with the b-catenin mutation has a lower DAPK1 expression, suggesting that DAPK1 may be regulated under the b-catenin pathway. In addition, we also identified genes that are co-regulated with DAPK1. DAPK1 expression was positively correlated with IRF2, IL7R, PCOLCE and ZBTB16, and negatively correlated with SLC16A3 in both liver cancer datasets. Among these genes, PCOLCE and ZBTB16 were significantly down-regulated, while SLC16A3 was significantly upregulated in liver cancer. By using connectivity mapping of these co-regulated genes, we have identified amcinonide and sulpiride as potential small molecules that could potentially reverse DAPK1/PCOLCE/ZBTB16/SLC16A3 expression. Our study demonstrated for the first time that both DAPK1 mRNA and protein expression levels are important prognostic markers in liver cancer, and have identified genes that may contribute to DAPK1-mediated liver carcinogenesis.

A gene-signature progression approach to identifying candidate small-molecule cancer therapeutics with connectivity mapping

BackgroundGene expression connectivity mapping has gained much popularity recently with a number of successful applications in biomedical research testifying its utility and promise. Previously methodological research in connectivity mapping mainly focused on two of the key components in the framework, namely, the reference gene expression profiles and the connectivity mapping algorithms. The other key component in this framework, the query gene signature, has been left to users to construct without much consensus on how this should be done, albeit it has been an issue most relevant to end users. As a key input to the connectivity mapping process, gene signature is crucially important in returning biologically meaningful and relevant results. This paper intends to formulate a standardized procedure for constructing high quality gene signatures from a user’s perspective.ResultsWe describe a two-stage process for making quality gene signatures using gene expression data as initial inputs. First, a differential gene expression analysis comparing two distinct biological states; only the genes that have passed stringent statistical criteria are considered in the second stage of the process, which involves ranking genes based on statistical as well as biological significance. We introduce a “gene signature progression” method as a standard procedure in connectivity mapping. Starting from the highest ranked gene, we progressively determine the minimum length of the gene signature that allows connections to the reference profiles (drugs) being established with a preset target false discovery rate. We use a lung cancer dataset and a breast cancer dataset as two case studies to demonstrate how this standardized procedure works, and we show that highly relevant and interesting biological connections are returned. Of particular note is gefitinib, identified as among the candidate therapeutics in our lung cancer case study. Our gene signature was based on gene expression data from Taiwan female non-smoker lung cancer patients, while there is evidence from independent studies that gefitinib is highly effective in treating women, non-smoker or former light smoker, advanced non-small cell lung cancer patients of Asian origin.ConclusionsIn summary, we introduced a gene signature progression method into connectivity mapping, which enables a standardized procedure for constructing high quality gene signatures. This progression method is particularly useful when the number of differentially expressed genes identified is large, and when there is a need to prioritize them to be included in the query signature. The results from two case studies demonstrate that the approach we have developed is capable of obtaining pertinent candidate drugs with high precision.

The prognostic significance of protein tyrosine phosphatase 4a2 in breast cancer

Although PTP4A3 has been shown to be a very important factor in promoting cancer progression, the role of its close family member PTP4A2 is still largely unknown. Recent reports have shown contradicting results on the role of PTP4A2 in breast cancer progression. Considering this, we aimed to investigate the prognostic value of PTP4A2 in five independent breast cancer data sets (minimum 198 patients per cohort, totaling 1,124 patients) in the Gene Expression Omnibus Database. We found that high expression of PTP4A2 was a favorable prognostic marker in all five independent breast cancer data sets, as well as in the combined cohort, with a hazard ratio of 0.68 (95% confidence interval =0.56–0.83; P<0.001). Low PTP4A2 expression was associated with estrogen receptor-negative tumors and tumors with higher histological grading; furthermore, low expression was inversely correlated with the expression of genes involved in proliferation, including MKI67 and the MCM gene family encoding the minichromosome maintenance proteins. These findings suggest that PTP4A2 may play a role in breast cancer progression by dysregulating cell proliferation. PTP4A2 expression was positively correlated with ESR1, the gene encoding estrogen receptor-alpha, and inversely correlated with EGFR expression, suggesting that PTP4A2 may be involved in these two important oncogenic pathways. Together, our results suggest that expression of PTP4A2 is a favorable prognostic marker in breast cancer.

Identification of TWIST -interacting genes in prostate cancer

Prostate cancer is one of the most common cancers in men worldwide, and the number of diagnosed patients has dramatically increased in recent years. Currently, the clinical parameters used to diagnose prostate cancer, such as Gleason score, pathological tumor staging, and prostate-specific antigen (PSA) expression level, are considered insufficient to inform recommendation to guide clinical practice. Thus, identification of a novel biomarker is necessary. TWIST is one of the well-studied targets and is correlated with cancer invasion and metastasis in several human cancers. We have investigated two largest prostate cancer patient cohorts available in GEO database and found that TWIST expression is positive correlated with Gleason score and associated with poorer survival. By using a prostate cancer cohort and a prostate cancer cell line dataset, we have identified three potential downstream targets of TWIST, PPM1A, SRP72 and TBCB. TWIST’s prognostic capacity is lost when the gene is mutated. Further investigation in the prostate cancer cohort revealed that gene expression of SERPINA, STX7, PDIA2, FMP5, GP1BB, VGLL4, KCNMA1, SHMT2, SAA4 and DIDO1 influence the prognostic significance of TWIST and vice versa. Importantly, eight out of these ten genes are prognostic indicator by itself. In conclusion, our study has further confirmed that TWIST is a prognostic marker in prostate cancer, identified its potential downstream targets and genes that could possibly give additional prognostic value to predict TWIST-mediated prostate cancer progression.

KRAS mutant colorectal cancer gene signatures identified angiotensin II receptor blockers as potential therapies

Colorectal cancer (CRC) is a life-threatening disease with high prevalence and mortality worldwide. The KRAS oncogene is mutated in approximately 40% of CRCs. While antibody based EGFR inhibitors (cetuximab and panitumumab) represent a major treatment strategy for advanced KRAS wild type (KRAS-WT) CRCs, there still remains no effective therapeutic course for advanced KRAS mutant (KRAS-MT) CRC patients. In this study, we employed a novel and comprehensive approach of gene expression connectivity mapping (GECM) to identify candidate compounds to target KRAS-MT tumors. We first created a combined KRAS-MT gene signature with 248 ranked significant genes using 677 CRC clinical samples. A series of 248 sub-signatures was then created containing an increasing number of the top ranked genes. As an input to GECM analysis, each sub-signature was translated into a statistically significant therapeutic drugs list, which was finally combined to obtain a single list of significant drugs. We identify four antihypertensive angiotensin II receptor blockers (ARBs) within the top 30 significant drugs indicating that these drugs have a mechanism of action that can alter the KRAS-MT CRC oncogenic signaling. A hypergeometric test (p-value = 6.57 × 10−6) confirmed that ARBs are significantly enriched in our results. These findings support the hypothesis that ARB antihypertensive drugs may directly block KRAS signaling resulting in improvement in patient outcome or, through a reversion to a KRAS wild-type phenotype, improve the response to anti-EGFR treatment. Antihypertensive angiotensin II receptor blockers are therefore worth further investigation as potential therapeutic candidates in this difficult category of advanced colorectal cancers.