Hung-I Harry Chen

NGM Biopharmaceuticals (United States)

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Yidong Chen

The University of Texas Health Science Center at San Antonio

Tzu‐Hung Hsiao

Taichung Veterans General Hospital

Yufei Huang

UPMC Hillman Cancer Center

Panneerdoss Subbarayalu

The University of Texas Health Science Center at San Antonio

Manjeet K. Rao

The University of Texas Health Science Center at San Antonio

Eric Y. Chuang

National Taiwan University

Charles Keller

Children's Cancer Therapy Development Institute

Yidong Chen

The University of Texas Health Science Center at San Antonio

Tinghe Zhang

UPMC Hillman Cancer Center

Aparna Gorthi

The University of Texas Health Science Center at San Antonio

Cooperative Institutions

The University of Texas Health Science Center at San Antonio

The University of Texas Health Science Center at Houston

NGM Biopharmaceuticals (United States)

The University of Texas at San Antonio

Children's Cancer Center

Oregon Health & Science University

Cancer Research Institute of the Slovak Academy of Sciences

Mays Cancer Center at UT Health San Antonio

Children's Cancer Therapy Development Institute

The University of Texas MD Anderson Cancer Center

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Identification of genomic functional hotspots with copy number alteration in liver cancer

EURASIP Journal on Bioinformatics and Systems Biology (2013)

Tzu‐Hung Hsiao Hung-I Harry Chen Stephanie Roessler Xin Wei Wang Yidong Chen

Copy number alterations (CNAs) can be observed in most of cancer patients. Several oncogenes and tumor suppressor genes with CNAs have been identified in different kinds of tumor. However, the systematic survey of CNA-affected functions is still lack. By employing systems biology approaches, instead of examining individual genes, we directly identified the functional hotspots on human genome. A total of 838 hotspots on human genome with 540 enriched Gene Ontology functions were identified. Seventy-six aCGH array data of hepatocellular carcinoma (HCC) tumors were employed in this study. A total of 150 regions which putatively affected by CNAs and the encoded functions were identified. Our results indicate that two immune related hotspots had copy number alterations in most of patients. In addition, our data implied that these immune-related regions might be involved in HCC oncogenesis. Also, we identified 39 hotspots of which copy number status were associated with patient survival. Our data implied that copy number alterations of the regions may contribute in the dysregulation of the encoded functions. These results further demonstrated that our method enables researchers to survey biological functions of CNAs and to construct regulation hypothesis at pathway and functional levels.

Comparative genomic hybridization

Copy number analysis

10.1186/1687-4153-2013-14

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Citations (10)

Genomic Loss of Tumor Suppressor miRNA-204 Promotes Cancer Cell Migration and Invasion by Activating AKT/mTOR/Rac1 Signaling and Actin Reorganization

PLoS ONE (2012)

J. Saadi Imam Jason R. Plyler Hima Bansal Suresh I. Prajapati Sanjay Bansal

Increasing evidence suggests that chromosomal regions containing microRNAs are functionally important in cancers. Here, we show that genomic loci encoding miR-204 are frequently lost in multiple cancers, including ovarian cancers, pediatric renal tumors, and breast cancers. MiR-204 shows drastically reduced expression in several cancers and acts as a potent tumor suppressor, inhibiting tumor metastasis in vivo when systemically delivered. We demonstrated that miR-204 exerts its function by targeting genes involved in tumorigenesis including brain-derived neurotrophic factor (BDNF), a neurotrophin family member which is known to promote tumor angiogenesis and invasiveness. Analysis of primary tumors shows that increased expression of BDNF or its receptor tropomyosin-related kinase B (TrkB) parallel a markedly reduced expression of miR-204. Our results reveal that loss of miR-204 results in BDNF overexpression and subsequent activation of the small GTPase Rac1 and actin reorganization through the AKT/mTOR signaling pathway leading to cancer cell migration and invasion. These results suggest that microdeletion of genomic loci containing miR-204 is directly linked with the deregulation of key oncogenic pathways that provide crucial stimulus for tumor growth and metastasis. Our findings provide a strong rationale for manipulating miR-204 levels therapeutically to suppress tumor metastasis.

Tumor progression

10.1371/journal.pone.0052397

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Citations (160)

Correction to: Predicting drug response of tumors from integrated genomic profiles by deep neural networks

BMC Medical Genomics (2019)

Yu‐Chiao Chiu Hung-I Harry Chen Tinghe Zhang Songyao Zhang Aparna Gorthi

Following publication of the original article [1], the authors provided an updated funding statement to the article. The updated statement is as follows:

Statement (logic)

Drug response

Human genetics

10.1186/s12920-019-0569-5

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Citations (35)

Identification of functional genomic regions with copy number alteration in liver cancer

Tzu‐Hung Hsiao Hung-I Harry Chen Yidong Chen

Copy number alterations (CNAs) happen frequently in solid tumors. Several oncogenes and tumor suppressor genes have been identified with CNAs. However, the systematic survey of CNA regulated functions is still lack. By employing systems biology approaches, instead of examining individual genes, we directly identified the spatial functional hotspots in human genome. Total 249 genomic regions, or segments, with 410 enriched biological functions were identified. An aCGH data set of hepatocellular carcinoma (HCC) tumors was employed in this study and several putative affected functions of CNAs were identified. Our results indicate that 4 immune related segments were lost in most of patients. In addition, our data implied these immune related segments might be involved in HCC oncogenesis. The result further demonstrated that our method enables researchers to survey biological functions of CNAs and to construct regulation hypothesis at pathway and functional levels.

Identification

10.1109/gensips.2012.6507752

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Citations (1)

A computational framework for predicting drug Mode-of-Action

Chifeng Ma Hung-I Harry Chen Yufei Huang Yidong Chen

The problem of large scale computational drug screening is considered in this paper. A computational framework is developed for microarray profile of drug treatment from the Connectivity Map (cMap) project. The framework is proposed to address the deficiency of cMap prediction. This scheme includes construction of drug Mode-of-Actions (MoA) and subsequently Mode-of-Action (MoA) network, or MoANet and a MoA prediction algorithm based on MoAs. The scheme is tested on the cMap data and an independent data set. The result shows significant improvement over cMap.

Mode (computer interface)

10.1109/bibmw.2010.5703831

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Antibody-mediated inhibition of GDF15–GFRAL activity reverses cancer cachexia in mice

Nature Medicine (2020)

Rowena Suriben Michael Chen Jared Higbee Julie Oeffinger Richard Ventura

GDF15

10.1038/s41591-020-0945-x

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Citations (206)

Abstract 2904: An integrative analysis to identify putative drugs for acute myeloid leukemia.

Cancer Research (2013)

Yuheng Chen Tzu‐Hung Hsiao Hung-I Harry Chen Yidong Chen Eric Y. Chuang

Abstract It is a time-consuming procedure to find an effective drug under current drug development, but the response rates of most anti-cancer drugs were still not high. Furthermore, the survival time of malignant cancer patients were often not prolonged after treatment. Therefore, to facilitate the process of discovering promising drug treatment, we proposed a novel integrative analysis based on gene set enrichment and evaluate the proposed model in acute myeloid leukemia (AML). The analysis was comprised by two methods. First, the enriched biological functions of each drug were identified based on the enrichment analysis of connectivity map, which is an expression profile of more than 950 drug treatments in the HL60 AML cell line. Second, the tumor progression associated functions were identified by using survival analysis. Finally, we integrated the results of two methods to generate a “drug - biological function - cancer” network. Based on the identified network, the putative anti-cancer drugs can be further explored. We applied a AML cohort data set, GSE12417, which contains 163 expression profiles, to our analysis framework. The result showed 429 enriched biological functions were related to 948 drugs. Among them, 21 of the 429 functions were identified as tumor progression associated functions though cox regression analysis. By integrating the two results, finally 174 putative drugs for AML were discovered. Our preliminary results provide valuable information to revisit the putative drugs to “reposition” for cancer therapy through identified biological functions. Citation Format: Yu-Heng Chen, Tzu-Hung Hsiao, Hung-I Harry Chen, Yidong Chen, Eric Y Chuang. An integrative analysis to identify putative drugs for acute myeloid leukemia. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2904. doi:10.1158/1538-7445.AM2013-2904 Note: This abstract was not presented at the AACR Annual Meeting 2013 because the presenter was unable to attend.

Drug repositioning

10.1158/1538-7445.am2013-2904

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MEK1/2 in Rhabdomyosarcoma

bioRxiv (Cold Spring Harbor Laboratory) (2019)

Kenneth A. Crawford Megan M. Cleary Cora A. Ricker Matthew N. Svalina John Shern

Abstract Alveolar and embryonal rhabdomyosarcoma (RMS) are soft-tissue cancers that affect children, adolescents, and young adults. Sometimes referred to as muscle cancer, RMS is a cancer of muscle and non-muscle origin that phenocopies incompletely differentiated myoblasts or activated satellite (muscle stem) cells. Interestingly, embryonal RMS (ERMS) has been observed to undergo terminal myogenic differentiation in response to stress induced by chemotherapy and radiation therapy 4, 9, 24 . Given the propensity of rhabdomyosarcoma to differentiation, in this report we explore the use of differentiation therapy combining MEK inhibitor (MEKi) cobimetinib and chemotherapy as a strategy to halt RMS growth. We evaluated a representative panel of RMS cell lines with cobimetinib and chemotherapy in two dosing schedules that mimic clinical use followed by cell growth evaluation and high content analysis (differentiation) assays. We uncovered that cobimetinib does not have significant additive or synergistic effects on cell differentiation or cell growth with chemotherapy in RMS and can have unanticipated antagonistic effects; specifically, pre-exposure of cobimetinib to cells can decrease the effectiveness of chemotherapy-mediated cell growth inhibition in vitro . Although differentiation-therapy is still a potential viable strategy in RMS, our data do not support MEKi/chemotherapy co-treatment in this context.

Embryonal rhabdomyosarcoma

10.1101/629766

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Citations (1)

A probe-density-based analysis method for array CGH data: simulation, normalization and centralization

Bioinformatics (2008)

Hung-I Harry Chen Fang-Han Hsu Yuan Jiang Mong‐Hsun Tsai Pan‐Chyr Yang

Abstract Motivation: Genomic instability is one of the fundamental factors in tumorigenesis and tumor progression. Many studies have shown that copy-number abnormalities at the DNA level are important in the pathogenesis of cancer. Array comparative genomic hybridization (aCGH), developed based on expression microarray technology, can reveal the chromosomal aberrations in segmental copies at a high resolution. However, due to the nature of aCGH, many standard expression data processing tools, such as data normalization, often fail to yield satisfactory results. Results: We demonstrated a novel aCGH normalization algorithm, which provides an accurate aCGH data normalization by utilizing the dependency of neighboring probe measurements in aCGH experiments. To facilitate the study, we have developed a hidden Markov model (HMM) to simulate a series of aCGH experiments with random DNA copy number alterations that are used to validate the performance of our normalization. In addition, we applied the proposed normalization algorithm to an aCGH study of lung cancer cell lines. By using the proposed algorithm, data quality and the reliability of experimental results are significantly improved, and the distinct patterns of DNA copy number alternations are observed among those lung cancer cell lines. Contact: chuangey@ntu.edu.tw Supplementary information: Source codes and.gures may be found at http://ntumaps.cgm.ntu.edu.tw/aCGH_supplementary

Normalization

10.1093/bioinformatics/btn321

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Citations (25)

Using gene sets to identify putative drugs for breast cancer

Tzu‐Hung Hsiao Hung-I Harry Chen Yidong Chen Yuheng Chen Eric Y. Chuang

The number of current anti-cancer drugs was limited and the response rates were also not high. To "reposition" known drugs as anti-cancer drugs to increase the therapeutic efficiency, we presented a novel analysis framework to identify putative drugs for cancer. Using breast cancer as example, a "cancer - gene sets - drugs" network was constructed through two procedures. First, the "gene sets - drugs" network was built by applying the expression pattern of drugs for gene set enrichment analysis. Secondly, the breast cancer progression associated gene sets were identified by survival analysis of patient cohorts. By integrating the two results, 25 tumor progression associated gene sets and 360 putative anti-cancer drugs were identified. Our method has the ability to identify the "reposition" drugs and the potential affected mechanisms of tumor progression concurrently. It will be useful to speed up the development of anti-cancer drugs from bench to clinical application.

10.1109/bibm.2012.6392616

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Citations (1)