BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:A Hallmarks of Cancer-based Oncology Models Fidelity Score.
DTSTART:20180625T110000
DTEND:20180625T120000
DTSTAMP:20260916T012408Z
UID:e83bbb1a80c3bd567a641f881f9ec9d0cac8c479542b2f663e6a7f77
CATEGORIES:Conferences - Seminars
DESCRIPTION:Theodore Goldstein\nABSTRACT:\nUnderstanding the molecular mec
 hanisms of disease pathogenesis and clinical therapeutics are central to t
 reating cancer. For decades\, mouse models have been a foundation of resea
 rch efforts in oncology. New tools for genomic manipulation such as CRISPE
 R and other technological advancements have served to accelerate the devel
 opment of a multitude of novel and powerful animal models. However\, chall
 enges remain that impede further progress in translating results from anim
 al models of cancer into improvements in patient care. Animal models do no
 t always faithfully recapitulate human cancer\, as evidenced by numerous t
 herapeutic agents that show promise in preclinical studies but fail in cli
 nical trials. Therefore\, it is critically important for researchers to ha
 ve tools that enable them to understand how accurately an animal model ref
 lects the human cancer they wish to study. We have developed a new scoring
  system called the Oncology Model Fidelity Scores (http://comphealth.ucsf.
 edu/hallmarks) to address the issue of the fidelity of animal models of ca
 ncer. This analytic tool uses gene expression data from RNA-Seq or microar
 ray studies for comparison. The conceptual framework and visualization for
  the scoring system is based on Hanahan and Weinberg’s Hallmarks of C
 ancer papers which describe a set of characteristic traits that define th
 e transformation into malignancy\, but which can also be used to classify 
 cancer therapeutics based on the perturbation of a particular Hallmark. Th
 erefore\, to give researchers a better understanding of the biologic proce
 sses in each animal model\, we have designed the Oncology Model Fidelity S
 cores to create metrics for each of the Hallmarks of Cancer. We have appli
 ed this scoring system to animal models available through the National Can
 cer Institute’s Oncology Model Forum (http://oncologymodels.org/)\, and 
 analyzed how these compare to the relevant human cancer based on data from
  The Cancer Genome Atlas. We present case examples of the application of t
 he Oncology Model Fidelity Scores to cancer models from a variety of diffe
 rent cancer types\, and show that our scoring system enables rapid identif
 ication of biological processes that are driving the malignancy or leading
  to drug resistance. Analysis of tumor samples from a mouse model for lung
  adenocarcinoma identify the biologic processes that are essential for dri
 ving the malignant evolution from primary tumor into metastatic lesions. W
 e also show that head and neck squamous cell cancer that has developed erl
 otinib resistance is driven by upregulation of pathways involved in the im
 mune response and inflammatory pathways. Ultimately\, the development of t
 he Oncology Model Fidelity Scores will help to advance patient care throug
 h efficient identification and validation of mouse models for a variety of
  applications\, from pre-clinical testing of novel therapeutics to the use
  of patient-specific animal models.\n 
LOCATION:SV 1717 https://plan.epfl.ch/?room==SV%201717
STATUS:CONFIRMED
END:VEVENT
END:VCALENDAR