Research Interests

Cancer Genetics: Genetic and epigenetic alterations are regarded as major etiologic factors in carcinogenesis. My interests in cancer genetics are: (1) to identify and characterize genes involved in the development and progression of human cancers; (2) to understand mechanisms of the alterations in carcinogenesis; (3) to translate the basic research outcomes into clinical research that will eventually improve detection, diagnosis, prognosis, prevention and treatment of human cancers.  Using a technology termed random retrovirus insertion and specific growth selection developed in my laboratory, we have successfully generated the insulin-independent cell sublines, the anchorage-independent cell sublines, the tumorigenic cell sublines, and the invasive and metastatic cell sublines from the parental breast cancer cell line.  Of particularly interesting, these cell lines represent a spectrum of cellular behaviors ranging from no growth, to slow growth, rapid growth, invasive, or metastatic features, in homogeneous xenograft animal model. Collectively, the in vivo growth characteristics may represent clinical complexity of extremely heterogeneous breast cancer cells and therefore, provide us with the unique and representative biological resources to correlate the molecular changes to the cellular phenotypic characteristics in animal models. Further characterization of these cell lines in vitro and in vivo is in progress.

Microarray and Bioinformatics: Microarray and bioinformatics are unprecedented high-throughput technologies for basic and applied biomedical research.  Fascinating science and technology of microarray and bioinformatics attracted my laboratory to have developed, so far, 20 unique types of microarrays, 13 databases, 1 algorithm, and 7 software applications, which include DNA and antibody microarrays and related database, algorithm, and computing software for studies of gene expression (cRNA, ncRNA and protein), DNA methylation, DNA-protein interaction, and gene mutation.  These integrative tools increase the efficiency for research and maximize the potential for discovery.  Below is a list of microarray and bioinformatics tools we developed:

DNA and Antibody Microarrays:

• Su YA, Yang J. 1K breast cancer gene chips, 2000
• Su YA, Yang J. 1.2K cancer gene chips, 2000
• Su YA, Yang J. Cell cycle gene chips, 2001
• Yang J, Su YA. Mouse 5K gene chips A, B, and C., 2001
• Wu J, Su YA. Mouse 15K gene chips, 2002
• Wu J, Su YA. Mouse 7.4K gene chips, 2002
• Su YA, Wu J, Alesci S, Yang J. 1st mitochondrial gene chips, 2002
• Su YA, Wu J. Human 12K gene chips, 2003
• Su YA, Wu J. Human 40K gene chips (2 X 20K), 2003
• Wu J, Alesci S, Su YA. 2nd mitochondrial gene chips, 2003
• Su YA, Wu J. Mouse 23K gene chips, 2003  
• Wu J, Fareed J, Su YA. Hemostasis-thrombosis gene chips, 2003
• Wu J, Su YA. Zibrafish oligonucleotide gene chips, 2003
• Su YA. Antibody arrays, 2003
• Wu J, Huang T, Su YA. Human 9K CpG island promoter DNA chips, 2004
• Wu J, Alesci S, Manoli I, Su YA. 3rd mitochondrial gene chips, 2004
• Wu J, Chen WY, Rennert OM, Su YA. XY chromosome gene chips, 2004
• Wu J, Dogulu C, Chen WY, Rennert OM, Su YA.  1st ASO mutation chips, 2004.
• Wu J, Pang A, Chen WY, Rennert OM, Su YA. miRNA chips, 2005
• Wu J, Dogulu C, Chen WY, Rennert OM, Su YA.  2nd ASO mutation chips, 2007.

Gene Expression Database:

• Chen Y, Su YA. Human unigene database
• Chen Y, Su YA. Human unigene and clone ID links
• Su YA. Human 46K gene database
• Chen Y, Su YA. Mouse unigene database
• Chen Y, Su YA. Mouse unigene and clone ID links
• Su YA. Mouse 30K gene database
• Su YA. Human mitochondrial gene expression database
• Su YA. Human and mouse XY chromosome-encoded gene database
• Su YA. Apoptosis, mitochondria and chromosome-6 gene expression database
• Su YA. Apoptosis, mitochondria and chromosome-17 gene expression database
• Su YA. Breast cancer gene expression database
• Su YA. Gene Information database
• Su YA. Mitochondrial gene pathway database

Microarray Software:

• Su YA. hMito2 macro for filtering and extracting differentially expression genes from microarray gene expression database. January, 2003
• Bai X, Su YG, Su YA. "LMCI v1.0" to cluster gene expression profiles. May, 2004
• Su YA. Macro for standardized filtering and extracting of information from row microarray data. July, 2004
• Su YG, Bai X, Su YA. "UniGDataConverter v1.0" to fetch bio-information from unigene database in any combinations. August, 2004.
• Su YG, Bai X, Su YA. "LocalMaxCluster v1.2" to cluster gene expression profiles. September, 2004
• Su YG, Bai X, Su YA. "µArrayDataMiner v1.0" to evaluate microarray data and to extract informative data from row data for further analysis of gene expression profiles. October, 2004.
• Su YG, Bai X, Su YA. "µArrayDataMiner v1.2" to evaluate microarray data and to extract informative data from row microarray data for further analysis of gene expression profiles.

Mitochondria-focused Pathway and Network: Mitochondria, intracellular organelles widely known as the “energy factories” of the cell, play fundamental roles in many metabolic pathways, such as β-oxidation, the tricarboxylic acid and urea cycles, the synthesis of steroid hormones and heme, and calcium signaling.  Defects and abnormal expression of either nDNA- and/or mtDNA-encoded genes may cause abnormalities in mitochondrial structure and function, which has been recognized increasingly in common diseases, such as obesity, diabetes, cardiomyopathy, and migraine.  In addition, reactive oxygen species, an inevitable by-product of mitochondrial oxidative phosphorylation, can damage DNA, might cause genetic instability, and have been implicated in cancer, neurodegenerative diseases, and aging.  Furthermore, mitochondria at the intersection of many molecular pathways are a central target of diverse pharmacological agents.  Many drugs have direct effects on mitochondrial ultra-structure and function, either at the DNA level or upon targeting proteins located in the inner or outer mitochondrial membrane.  In order to systematically study mitochondria-focused molecular pathways and networks, my laboratory collaborated with our colleagues at the NICHD/NIH and the NCCAM/NIH and developed human mitochondria-focused gene chips and bioinformatic tools.  We are applying these novel tools to study the relationship between mitochondria-related gene expression changes and cellular apoptosis of human malignant melanoma induced by UV radiation, a major etiologic factor of skin cancer.  In addition, these tools are applied for study molecular mechanisms of the Warburg effect, that is, tumor cells using glycolysis rather than oxidative phosphorylation for ATP production.  Our results revealed significant alterations in gene expression patterns in melanoma cells in contrast to cutaneous melanocytes. 

Traditional Chinese Medicine (TCM): TCM is the traditional and evidence-based medicine that developed in China in thousands of years.  TCM emphasizes that the human body functions in one entity with complete and sophisticated interconnections and constant interactions among all parts of the body, and between human body and the environment, physically and emotionally, maintaining delicate balance for healthy body.  The philosophical TCM concept includes Yin-Yang and Five Elements, Jingqishen, Meridian, Zangfu, Qixuejingye, and many others.  Herbs are the most broadly-used remedy of TCM and are almost always used in combinations named Fangji.  Currently, my laboratory is studying therapeutic effects of Chinese herbs on gastroesophageal reflux disease for cancer prevention.  We are also studying inhibitory effects of Chinese herbs on solid tumor growth.  We are applying genomic, proteomic and bioinformatic tools for the clinical and translational studies of the TCM efficacy in order to develop novel therapeutic drugs.

Microarray and Bioinformatics Core Facility:

1. Equipment

      (A)  PolyPlexII high throughput oligonucleotide synthesizer;
      (B)  GeneMachine OmniGrid 100 Microarrayer;
      (C)  ScanArray Expression Microarray Scanner;
      (D)  Microarray Hybridization Oven

2. DNA and Antibody for Microarray

     (A)  46,000 cDNA of human genes
     (B)  22,400 cDNA of the NIA mouse gene clones
     (C)  9,000 gemonic DNA of human CpG island promoter
     (D)  37,459 cDNA of the NIH-BMAP mouse adult brain
     (E)  11,864 cDNA of the NIH-BMAP mouse retina
     (F)   500 antibodies from Epitomics

3. Database

      (A)  Human UniGene Database;
      (B)  Human 46K Gene Database;
      (C)  Mouse UniGene Database;
      (D)  Mouse 30K Gene Database;
      (E)  Human Mitochondria-focused Gene Database;
      (F)  Mouse Mitochondria-focused Gene Database;
      (G)  Human Gene Expression and Function Database;
      (H)  Rabbit Antibody database to human proteins

4. Microarray Data Analysis Software

      (A)  UniGDataConverter v1.0
      (B)  LocalMaxCluster v1.2
      (C)  uArrayDataMiner v1.2      

5. DNA and Antibody Microarrays

      (A)  Human mitochondrial focused microarray, hMitChip3
      (B)  miRNA microarray
      (C)  22.4K mouse cDNA microarray
      (D)  40K human cDNA microarray
      (E)  9K promoter DNA microarray
      (F)   XY chromosome-specific cDNA microarray
      (G)  The ASO mutation microarray
      (H)  Epitomics 500 antibody microarrays (in progress)

Selected Publications:

1. Su YA, Bittner ML, Chen Y, Tao L, Jiang Y, Zhang YH, Stephan DA, Trent JM.  Identification of Tumor Suppressor Genes in Human Melanoma Cell Lines UACC903, UACC903(+6), and SRS3 by Analysis of Expression Profiles.  Mol Carcinog.  28:119-127, 2000.
2. Luke A, Wu X, Zhu X, Kan D, Su YA, Cooper R. Linkage for BMI at 3q27 region confirmed in an African-American population.  Diabetes 52:1284-7, 2003.
3. Wu X, Chen Y, Brooks BR, Su YA.  The local maximum clustering method and its application in microarray gene expression data analysis.  EURASIP Journal on Applied Signal Processing, 1:53-63, 2004.
4. Manoli I, Le H, Alesci S, McFann KK, Su YA, Kino T, Chrousos GP, Blackman MR.  Monoamine oxidase-A is a major target gene in for glucocorticoids in human skeletal muscle cells.  FASEB J., 19:1359-1361, 2005.
5. Alesci A, Manoli I, Michopoulos VJ, Brouwers FM, Le H, Gold PW, Blackman MR, Rennert OM, Su YA, Chrousos GP.  Development of a human mitochondria-focused cDNA microarray (hMitChip): validation in skeletal muscle cells and implications for pharmaco- and mitogenomics.  The Pharmacogenomics J, 6:333-342, 2006. 
6. Zhang H, Su YA, Hu P, Yang J, Zheng B, Wu P, Peng J, Tang Y, Zhang L.  Signature patterns revealed by microarray analyses of mice infected with influenza virus A and Streptococcus pheumoniae.  Microbes Infect.  2006 Jun 2; 1-14.
7. Bai XY, Wu J, Zhang Q, Alesci A, Manoli I, Blackman MR, Chrousos GP,  Goldstein AL, Rennert OM, Su YA.  The Third Generation of Human Mitochondria-Focused cDNA Microarray (hMitChip3) and its Bioinformatics Tools for Analysis of Gene Expression.  BioTechniques.  March, 2007.  doi 10.2144/000112388.

Supplementary Information

For the publication: Bai XY, Wu J, Zhang Q, Alesci A, Manoli I, Blackman MR, Chrousos GP, Goldstein AL, Rennert OM, Su YA. The Third Generation of Human Mitochondria-Focused cDNA Microarray (hMitChip3) and its Bioinformatics Tools for Analysis of Gene Expression. BioTechniques. March, 2007. doi 10.2144/000112388.

1. Supplementary Table

(A) hMitChip3 ST1
(B) hMitChip3 ST2
(C) hMitChip3 ST3
(D) hMitChip3 ST4
(E) hMitChip3 ST5
(F) hMitChip3 ST6
(G) hMitChip3 ST7
(H) hMitChip3 ST8
(I) hMitChip3 ST9

2. hMitChip3 database template
The following files should be opened with FileMaker Pro or contact Dr. Yan Su
(A) Figure 3A template: Individual Expression File
(B) Figure 3B template: Relational Expression File
(C) Figure 4A template: Relational Gene Information File
(D) Figure 4B template: Category Gene Information File