# Presentation: 071065

## caBIG: Perspectives and Challenges Albert Einstein Cancer Centerand Collaborating Institutions

- For the AECC Informatics Group
- (presented by Erwin Bottinger)
- _Collaboratoring Institutions: _
- Montefiore Medical Center
- The Mount Sinai Medical Center

## Perspectives

- Research Portfolio
- Laboratory
- Animal model (strengths ‘colon cancer’)
- Translational (strengths ‘genomics’)
- Clinical (trials, outcomes, epidemiology)
- Informatics Portfolio
- Bioinformatics
- Medical Informatics

- prepared by Erwin Bottinger, M.D.

- 2/18/2004

## Challenges

- Vertical Data Integration ?
- 	Laboratory
- 	Animal model (strengths ‘colon cancer’)
- 	Translational (strengths ‘genomics’)
- 	Clinical (trials, outcomes, epidemiology)
- Bio-Medical-Informatics ?
- 	Bioinformatics
- 	Medical Informatics

- prepared by Erwin Bottinger, M.D.

- 2/18/2004

## Scientific Theme: Interaction of Environmental and Genetic Factors
Genes and Loci
Nutrition and metabolism
Environment
Intervention and Outcome

Mouse models of Colon Cancer
Mouse genetics
Functional genomics
Structural genomics
Biostatistics

Cellular and Molecular Mechanisms: 
Cells derived from tumor sites in animal models
Cells derived from human cancers

- Genes and Loci
- Nutrition and metabolism
- Environment
- Intervention and Outcome
- Mouse models of Colon Cancer
- Mouse genetics
- Functional genomics
- Structural genomics
- Biostatistics
- Cellular and Molecular Mechanisms:
- Cells derived from tumor sites in animal models
- Cells derived from human cancers

**Example****AECC Colon Cancer Program**(Len Augenlicht)

- prepared by Erwin Bottinger, M.D.

- 2/18/2004

**Notes:**
I think a lot has been sad about our problems with DNP.
We have decided to use functional genomics tool, which could simultaneously measure changes in all the genes in the genome to find answers to the following questions.

What are the changes in the transcriptional program of the kidneys in the diabetic state? 
Can these transcriptional changes be related to the pathophysiology of and clinical manifestations of diabetic renal disease? 
Can patterns of gene expression be used to diagnose different phenotypic manifestations of diabetic renal disease?
What functional role these newly discovered genes could play?
All these around the potential application for humans to predict that 30% of the patients who will develop dnp

## 
Molecular Classification of Colon Cancers:  A Clinical Trial
Gene expression database
SNP database
Clinical Trials Management System

Comparative genomics in mouse, rat, human
Linking experimental data and public genetic data across species
Automated gene and pathway annotation pipeline

- Molecular Classification of Colon Cancers:  A Clinical Trial
- Gene expression database
- SNP database
- Clinical Trials Management System
- Comparative genomics in mouse, rat, human
- Linking experimental data and public genetic data across species
- Automated gene and pathway annotation pipeline

**Example cont’d****AECC Colon Cancer Program**(Len Augenlicht)

- prepared by Erwin Bottinger, M.D.

- 2/18/2004

**Notes:**
I think a lot has been sad about our problems with DNP.
We have decided to use functional genomics tool, which could simultaneously measure changes in all the genes in the genome to find answers to the following questions.

What are the changes in the transcriptional program of the kidneys in the diabetic state? 
Can these transcriptional changes be related to the pathophysiology of and clinical manifestations of diabetic renal disease? 
Can patterns of gene expression be used to diagnose different phenotypic manifestations of diabetic renal disease?
What functional role these newly discovered genes could play?
All these around the potential application for humans to predict that 30% of the patients who will develop dnp

## Example cont’dAECC Cancer Epidemiology Program(Tom Rohan, Robert Burk)

| CANCER EPIDEMIOLOGYScientific Elements  |
| --- |
| Etiology 
HPV and cervical neoplasia 
Diet and cancer 
Genetic polymorphisms & cancer 
Gene discovery 
Pathogenesis 
Cervical and breast cancer 
Prevention 
Dietary 
Chemoprevention 
Behavioral  |

**Example cont’d****AECC Cancer Epidemiology Program**(Tom Rohan, Robert Burk)

- prepared by Erwin Bottinger, M.D.

- 2/18/2004

## 5. Push Through to           MEDICAL INFORMATICS SYSTEM

- _Determine __*Orthologues*__ (Hs., Mm., Rn.,)_
-   By sequence comparison (BLAST, Homologene, TIGR, RGD)
-   By synteny (Celera, UCSC Genome Browser, RGD, MGI)

*Chr. Map Position* of Orthologues (NCBI, UCSC, MGI, Celera)

*Pathways/Function*
- Gene Ontology
- InterPro
- KEGG

*Phenotype traits (QTLs)/Mutants)*
- MGI
- RGD

*Disease/Susceptibility*
- GAD
- OMIM

**Genes & Names **
**	****Orthologues**

**2. Maps & Sequences**

**4. Retrieve Annotations**

**Databases:**

- Orthologues ↔ *Disease Loci / QTLs*

**3. Phenotypes, **
**    ****Alleles & QTL’s **

**5. Push Through to           ****MEDICAL INFORMATICS SYSTEM**

**Bioinformatics Workspace: Comparative Genomics**

*caBIO & BioGOPHER ?*

*caCORE ? *

**Tools:**

- In-House

***Evaluation:***

**  ****Albert Einstein Genome Informatics System  **

- prepared by Erwin Bottinger, M.D.

- 2/18/2004

## Slide 8

- prepared by Erwin Bottinger, M.D.

- 2/18/2004

## Medical Informatics Resources - MSMC 

| Date Capture Start Date | Data Captured |
| --- | --- |
| 1-Aug-00 | Basic Demographic Information & Visit Summary for Hospital Patients |
| 14-Aug-00 | Radiology Inpatients and Outpatients Reports |
| 17-Aug-00 | Laboratory Inpatients Results and Micro Reports |
| 18-Aug-00 | Pathology Inpatients Reports |
| 13-Oct-00 | Laboratory Outpatient Results |
| 24-Jan-01 | Discharge Summary and Operative Reports |
| 19-Apr-01 | Pathology Outpatient Results |

- Enterprise Data Repository (EDR)
- - ICD-9, SNOMED, other vocabularies

- Sign-Out System Reports (SOSP)
- - Clinical vocabulary / real-time

**Goal:  Integration of Bioinformatics and Medical Informatics Domains**

- prepared by Erwin Bottinger, M.D.

- 2/18/2004

## What we will bring to caBIG :

- ‘Vertical Biomedical Informatics Environment’
- Data environment and expertise in cancer research
- Biology vocabs and DEs
- Genomic vocabs and Des
- Mouse model organism vocabs
- Infrastructure for Implementation in cancer research 		and cancer care environment

- prepared by Erwin Bottinger, M.D.

- 2/18/2004

## What we hope to gain from caBIG :

- Workgroup support and applications for
- Implementation and integration of clinical cancer domain vocabs and cancer biology vocabs
- Implementation of data standards
- Implementation of data exchange formats, i.e. XML
- Networking

- prepared by Erwin Bottinger, M.D.

- 2/18/2004