Speakers Share

Emma Bowden, PhD

Director, Translational Medicine, Thermo-Fisher Scientific

BIOGRAPHY
Mary Ellen Urick, PhD

Staff Scientist, Bioinformatics, Thermo Fisher Scientific
Nickolay Khazanov, PhD

Staff Scientist, Bioinformatics, Thermo Fisher Scientific

BIOGRAPHY
Sean Eddy, PhD

Staff Scientist, Bioinformatics, Thermo Fisher Scientific

BIOGRAPHY

SEP 16, 2014

Advanced Genomics in Clinical and Translational Research - Informing end-to-end cancer drug development with bioinformatics

This event will highlight the innovative use of big data to inform cancer drug development and transform cancer clinical development. The wealth of curated and well-annotated cancer genomic and clinical trial data within the Oncomine® Knowledgebase powers a broad variety of systematic bioinformatics analysis. Several of the top pharma companies have utilized our services and software to help identify and understand relevant biomarkers and their potential for efficient and effective drug development strategies.

A group of scientists has been assembled to cover topics such as:

Expanding the potential of your drug programs with portfolio prioritization & label extension opportunities
Selecting the right population for your clinical trial
Exploring combination therapies based on biomarkers of sensitivity and resistance

This event intends to bring together drug developers, from executives to research scientists, to learn about advances in cancer bioinformatics.

This webinar offers an amazing opportunity, as it is free to participants and there will be no out-of-pocket expenses for travel. However, participants will still benefit from interacting with a global community of like-minded colleagues without leaving the comfort of their office or home.

Webinar participants will be able to:

Attend interactive live streaming video sessions
Have their questions answered in real time
Chat live with peers and speakers
Browse our exhibit booth for a spectrum of products

Speakers

Emma Bowden, PhD

Director, Translational Medicine, Thermo-Fisher Scientific
BIOGRAPHY
Mary Ellen Urick, PhD

Staff Scientist, Bioinformatics, Thermo Fisher Scientific
Nickolay Khazanov, PhD

Staff Scientist, Bioinformatics, Thermo Fisher Scientific
BIOGRAPHY
Sean Eddy, PhD

Staff Scientist, Bioinformatics, Thermo Fisher Scientific
BIOGRAPHY

Agenda Share

Download Agenda

SEP 16, 2014 10:00 AM PDT

Expanded clinical research opportunities for Crizotinib identified from an analysis of over 5,000 exomes

Sean Eddy, PhD

Staff Scientist, Bioinformatics, Thermo Fisher Scientific
BIOGRAPHY

Patients with chromosomal rearrangements resulting in fusion proteins are among the most responsive to published targeted therapy. For example, targeting of the EML4-ALK fusion in non-small cell lung cancer (NSCLC) with crizotinib has led to dramatic responses. While crizotinib is approved for use in EML4-ALK positive NSCLC for targeted inhibition of ALK, the drug also inhibits MET, MST1R (RON), ROS1, and more recently, has been reported to inhibit the ALK homolog LTK. To further understand the expanded therapeutic potential of crizotinib, a genomic survey to identify aberrations in ALK, MET, MST1R (RON), ROS1 and LTK was performed across >90,000 samples in the Oncomine Knowledgebase, including >7,000 samples subjected to full exome sequencing to identify known and novel fusion events. In this session, Dr. Eddy will reveal novel findings identified in this analysis including recurrent ALK fusions in colorectal adenocarcinoma, papillary renal cell carcinoma, thyroid gland carcinoma and sarcoma, as well as confirmation of the EML4-ALK fusion in lung adenocarcinoma. In this session, Dr. Eddy will highlight key findings of the analysis and provide an overall breakdown of molecular aberrations by cancer type.

Watch Webinar
SEP 16, 2014 9:30 AM PDT

Analysis of Oncomine Knowledgebase to identify NFE2L2 pathway as a novel therapeutic opportunity in multiple cancer types

Nickolay Khazanov, PhD

Staff Scientist, Bioinformatics, Thermo Fisher Scientific
BIOGRAPHY

Late-stage drug attrition rates in oncology remain higher than in other therapeutic areas. To reduce attrition, it is critical to identify appropriate drug targets and pre-clinical models. The integrative analysis framework was designed to systematically compute associations among driver mutations, fusions and copy alterations to define the driver aberration landscape of common cancers, then correlate the drivers to clinical metadata. Our driver selection methodology was developed through an interrogation of genomic aberrations in a training set of gold standard oncogenes such as EGFR, ALK and PIK3CA, and tumor suppressors such as TP53 and PTEN. The resulting platform was used to rank genes through an assessment of driver genomic aberrations, associations with patient survival, and potential clinical actionability. In this session, Dr. Khazanov will highlight proof of concept identification of a potentially clinically relevant candidate driver gene using a novel systematic integrative analysis of multi-dimensional cancer genomic data.

Watch Webinar
SEP 16, 2014 8:30 AM PDT

The use of transcriptional signatures for clinical population selection

Mary Ellen Urick, PhD

Staff Scientist, Bioinformatics, Thermo Fisher Scientific

The use of biomarkers for the stratification of populations for therapy is a concept that holds the potential to revolutionize clinical trial design, the economics of healthcare, and most importantly, the future treatment of cancer patients. While single-gene aberrations are currently being used as predictive biomarkers in oncology clinical trial design, the use of multi-gene biomarkers such as transcriptional signatures is not common, despite the fact that multi-gene signatures may be more likely to provide the high sensitivity and specificity required for biomarkers to be validated for clinical practice. The Compendia Bioscience Translational Bioinformatics Services team has expertise in generation and refinement of transcriptional biomarkers of response. These signatures of response and resistance can be utilized to support many aspects of drug development, including understanding mechanism of action, building a competitive differentiation plan, and identification of drug combination opportunities. In this session, Dr. Urick will discuss the potential utility of transcriptional signatures as predictive biomarkers as well as highlight the current techniques used by the Compendia Bioscience Translational Bioinformatics Services team to utilize transcriptional signatures for potential clinical trial population selection.

Watch Webinar
SEP 16, 2014 8:00 AM PDT

Overview

Emma Bowden, PhD

Director, Translational Medicine, Thermo-Fisher Scientific
BIOGRAPHY

Watch Webinar

Sessions
SEP 16, 2014 8:00 AM PDT

Overview

Emma Bowden, PhD

Director, Translational Medicine, Thermo-Fisher Scientific
BIOGRAPHY

Watch Webinar
SEP 16, 2014 8:30 AM PDT

The use of transcriptional signatures for clinical population selection

Mary Ellen Urick, PhD

Staff Scientist, Bioinformatics, Thermo Fisher Scientific

The use of biomarkers for the stratification of populations for therapy is a concept that holds the potential to revolutionize clinical trial design, the economics of healthcare, and most importantly, the future treatment of cancer patients. While single-gene aberrations are currently being used as predictive biomarkers in oncology clinical trial design, the use of multi-gene biomarkers such as transcriptional signatures is not common, despite the fact that multi-gene signatures may be more likely to provide the high sensitivity and specificity required for biomarkers to be validated for clinical practice. The Compendia Bioscience Translational Bioinformatics Services team has expertise in generation and refinement of transcriptional biomarkers of response. These signatures of response and resistance can be utilized to support many aspects of drug development, including understanding mechanism of action, building a competitive differentiation plan, and identification of drug combination opportunities. In this session, Dr. Urick will discuss the potential utility of transcriptional signatures as predictive biomarkers as well as highlight the current techniques used by the Compendia Bioscience Translational Bioinformatics Services team to utilize transcriptional signatures for potential clinical trial population selection.

Watch Webinar
SEP 16, 2014 9:30 AM PDT

Analysis of Oncomine Knowledgebase to identify NFE2L2 pathway as a novel therapeutic opportunity in multiple cancer types

Nickolay Khazanov, PhD

Staff Scientist, Bioinformatics, Thermo Fisher Scientific
BIOGRAPHY

Late-stage drug attrition rates in oncology remain higher than in other therapeutic areas. To reduce attrition, it is critical to identify appropriate drug targets and pre-clinical models. The integrative analysis framework was designed to systematically compute associations among driver mutations, fusions and copy alterations to define the driver aberration landscape of common cancers, then correlate the drivers to clinical metadata. Our driver selection methodology was developed through an interrogation of genomic aberrations in a training set of gold standard oncogenes such as EGFR, ALK and PIK3CA, and tumor suppressors such as TP53 and PTEN. The resulting platform was used to rank genes through an assessment of driver genomic aberrations, associations with patient survival, and potential clinical actionability. In this session, Dr. Khazanov will highlight proof of concept identification of a potentially clinically relevant candidate driver gene using a novel systematic integrative analysis of multi-dimensional cancer genomic data.

Watch Webinar
SEP 16, 2014 10:00 AM PDT

Expanded clinical research opportunities for Crizotinib identified from an analysis of over 5,000 exomes

Sean Eddy, PhD

Staff Scientist, Bioinformatics, Thermo Fisher Scientific
BIOGRAPHY

Patients with chromosomal rearrangements resulting in fusion proteins are among the most responsive to published targeted therapy. For example, targeting of the EML4-ALK fusion in non-small cell lung cancer (NSCLC) with crizotinib has led to dramatic responses. While crizotinib is approved for use in EML4-ALK positive NSCLC for targeted inhibition of ALK, the drug also inhibits MET, MST1R (RON), ROS1, and more recently, has been reported to inhibit the ALK homolog LTK. To further understand the expanded therapeutic potential of crizotinib, a genomic survey to identify aberrations in ALK, MET, MST1R (RON), ROS1 and LTK was performed across >90,000 samples in the Oncomine Knowledgebase, including >7,000 samples subjected to full exome sequencing to identify known and novel fusion events. In this session, Dr. Eddy will reveal novel findings identified in this analysis including recurrent ALK fusions in colorectal adenocarcinoma, papillary renal cell carcinoma, thyroid gland carcinoma and sarcoma, as well as confirmation of the EML4-ALK fusion in lung adenocarcinoma. In this session, Dr. Eddy will highlight key findings of the analysis and provide an overall breakdown of molecular aberrations by cancer type.

Watch Webinar

Help

Speakers Share

Emma Bowden, PhD

Mary Ellen Urick, PhD

Nickolay Khazanov, PhD

Sean Eddy, PhD

Advanced Genomics in Clinical and Translational Research - Informing end-to-end cancer drug development with bioinformatics

Emma Bowden, PhD

Mary Ellen Urick, PhD

Nickolay Khazanov, PhD

Sean Eddy, PhD

Agenda Share

ondemand

Topics

Expanded clinical research opportunities for Crizotinib identified from an analysis of over 5,000 exomes

Analysis of Oncomine Knowledgebase to identify NFE2L2 pathway as a novel therapeutic opportunity in multiple cancer types

The use of transcriptional signatures for clinical population selection

Overview

Overview

The use of transcriptional signatures for clinical population selection

Analysis of Oncomine Knowledgebase to identify NFE2L2 pathway as a novel therapeutic opportunity in multiple cancer types

Expanded clinical research opportunities for Crizotinib identified from an analysis of over 5,000 exomes

Speakers Share // Get the id and entity for ajax statistics window.entity = 'VirtualEvent'; window.entityId = '14';

Emma Bowden, PhD

Mary Ellen Urick, PhD

Nickolay Khazanov, PhD

Sean Eddy, PhD

Advanced Genomics in Clinical and Translational Research - Informing end-to-end cancer drug development with bioinformatics

Emma Bowden, PhD

Mary Ellen Urick, PhD

Nickolay Khazanov, PhD

Sean Eddy, PhD

Agenda Share // Get the id and entity for ajax statistics window.entity = 'VirtualEvent'; window.entityId = '14';

Speakers Share

Agenda Share