Award ID: RP110471-C3 Project Title: C3: Bioinformatics Award ...

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29 Σεπ 2013 (πριν από 4 χρόνια και 13 μέρες)

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Award ID:
RP110471- C3
Project Title:
C3:Bioinformatics
Award Mechanism:
Multi- Investigator
Principal Investigator:
Wei Li
Entity:
Baylor College of Medicine
Lay Summary:
Breast cancer is a complex disease that strikes at least 200,000 women in the US and
2500 women in Texas every year.Part of the reason that this disease is so hard to treat
is that a number of different tumor types exist that respond differently to hormones such
as estrogen.For those tumors that retain response to hormones,drugs such as
tamoxifen offer great promise.However,few treatment options are available for those
tumors that no longer respond to hormones.To fight these cancers,we must uncover
their vulnerabilities by defining their molecular characteristics in more detail.The
behavior,identity,and growth characteristics of all cells are driven by the genes they
express.Gene expression patterns are dictated in large part by how the DNA genome is
folded inside the cell nucleus.The genome provides a blueprint for the creation of all cells
types in the body.However,the genome is folded differently in different cell types,so
that only the information important to a particular cell type is open and available for
reading.If the genome becomes mis- folded,then reading of the wrong part of the
blueprint may lead to abnormal cell behavior and disease formation.Because folding
patterns affect gene behavior without affecting the DNA sequence,and because these
changes can be inherited,these folded states are referred to as epigenetic.Importantly,
epigenetic changes can be reversed,so drugs that change a misfolded state back to a
more normal state could provide powerful weapons to fight breast cancers.Our project
brings together experts from across Texas to better define the molecular and epigenetic
signatures of different types of breast cancers.We will test the importance of particular
epigenetic factors in disease formation and recurrence using novel mouse models.These
studies will provide an important baseline for future analysis of patient samples and the
development of new diagnostic and prognostic markers for breast cancer.