Project description:Revealing targeted therapy for human cancer by gene module maps A major goal of cancer research is to match specific therapies to molecular targets in cancer. Genome-scale expression profiling has identified new subtypes of cancer based on consistent patterns of variation in gene expression, leading to improved prognostic predictions. However, how these new genetic subtypes of cancers should be treated is unknown. Here we show that a gene module map can guide the prospective identification of targeted therapies for genetic subtypes of cancer. By visualizing genome-scale gene expression in cancer as combinations of activated and deactivated functional modules, gene module maps can reveal specific functional pathways associated with each subtype that might be susceptible to targeted therapies. We show that in human breast cancers, activation of a poor prognosis âwound signatureâ is strongly associated with induction of a proteasome gene module. Inhibition of proteasome activity by bortezomib, a drug approved for human use in multiple myeloma, abrogated wound signature expression and selectively killed breast cells expressing the wound signature. Thus, gene module maps may enable rapid translation of complex genomic signatures in human disease to targeted therapeutic strategies. 8 breast cancer cell lines and a breast epithelial cell line were cultured in standard serum conditions. The breast cancer cell lines were profiled after both standard culture conditions (10% fetal bovine serum; FBS) and serum starvation. The epithelial cells after serum starvation. All cells were also profiled after treatment with a proteosome inhibitor (bortezomib). Changes in gene expression and changes in the previously described wound-response signature were measured.
Project description:Faratian2009 - Role of PTEN in Trastuzumab
resistance
This model is described in the article:
Systems biology
reveals new strategies for personalizing cancer medicine and
confirms the role of PTEN in resistance to trastuzumab.
Faratian D, Goltsov A, Lebedeva G,
Sorokin A, Moodie S, Mullen P, Kay C, Um IH, Langdon S, Goryanin
I, Harrison DJ.
Cancer Res. 2009 Aug; 69(16):
6713-6720
Abstract:
Resistance to targeted cancer therapies such as trastuzumab
is a frequent clinical problem not solely because of
insufficient expression of HER2 receptor but also because of
the overriding activation states of cell signaling pathways.
Systems biology approaches lend themselves to rapid in silico
testing of factors, which may confer resistance to targeted
therapies. Inthis study, we aimed to develop a new kinetic
model that could be interrogated to predict resistance to
receptor tyrosine kinase (RTK) inhibitor therapies and directly
test predictions in vitro and in clinical samples. The new
mathematical model included RTK inhibitor antibody binding,
HER2/HER3 dimerization and inhibition, AKT/mitogen-activated
protein kinase cross-talk, and the regulatory properties of
PTEN. The model was parameterized using quantitative
phosphoprotein expression data from cancer cell lines using
reverse-phase protein microarrays. Quantitative PTEN protein
expression was found to be the key determinant of resistance to
anti-HER2 therapy in silico, which was predictive of unseen
experiments in vitro using the PTEN inhibitor bp(V). When
measured in cancer cell lines, PTEN expression predicts
sensitivity to anti-HER2 therapy; furthermore, this
quantitative measurement is more predictive of response
(relative risk, 3.0; 95% confidence interval, 1.6-5.5; P <
0.0001) than other pathway components taken in isolation and
when tested by multivariate analysis in a cohort of 122 breast
cancers treated with trastuzumab. For the first time, a systems
biology approach has successfully been used to stratify
patients for personalized therapy in cancer and is further
compelling evidence that PTEN, appropriately measured in the
clinical setting, refines clinical decision making in patients
treated with anti-HER2 therapies.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000424.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
Project description:10X Genomics single cell RNAseq of MCF7 cells treated with bortezomib. Human cancer cell lines are the workhorse of cancer research. While cell lines are known to evolve in culture, the extent of the resultant genetic and transcriptional heterogeneity and its functional consequences remain understudied. Here, genomic analyses of 106 cell lines grown in two laboratories revealed extensive clonal diversity. Follow-up comprehensive genomic characterization of 27 strains of the common breast cancer cell line MCF7 uncovered rapid genetic diversification. Similar results were obtained with multiple strains of 13 additional cell lines. Importantly, genetic changes were associated with differential activation of gene expression programs and marked differences in cell morphology and proliferation. Barcoding experiments showed that cell line evolution occurs as a result of positive clonal selection that is highly sensitive to culture conditions. Analyses of single cell-derived clones showed that ongoing instability quickly translates into cell line heterogeneity. Testing of the 27 MCF7 strains against 321 anti-cancer compounds uncovered strikingly disparate drug response: at least 75% of compounds that strongly inhibited some strains were completely inactive in others. This study documents the extent, origin and consequence of genetic variation within cell lines, and provides a framework for researchers to measure such variation in efforts to support maximally reproducible cancer research.
Project description:This information was used to identify mutations associated with particular breast cancer subtypes, as well as associations with response to therapy. 75 breast cancer cell lines underwent exome sequencing to identify mutations.
Project description:As part of the RATHER (RAtional THERapy for breast cancer: individualized treatment for difficult-to-treat breast cancer subtypes) consortium, expression profiling of 144 untreated primary invasive lobular carcinoma (ILC) breast cancer tissues and 15 ILC cell lines was performed using microarray. Gene expression profiling of 144 ILC breast cancers and 15 ILC cell lines
Project description:As part of the RATHER (RAtional THERapy for breast cancer: individualized treatment for difficult-to-treat breast cancer subtypes) consortium, expression profiling of 144 untreated primary invasive lobular carcinoma (ILC) breast cancer tissues and 15 ILC cell lines was performed using microarray.
Project description:There is a great need of non-invasive tools that inform of an early molecular response to cancer therapeutic treatment. Here, we have tested the hypothesis that proteolytically resistant proteins could be candidate circulating tumor biomarkers for cancer therapy. Proteins resistant to proteolysis are drastically under-sampled by current proteomic workflows. These proteins could be reliable sensors for the response to therapy since they are likely to stay longer in circulation. We selected Manganese superoxide dismutase (SOD2), a mitochondrial redox enzyme, from a screening of proteolytic resistant proteins in breast cancer (BC). First, we confirmed the robustness of SOD2 and determined that its proteolytic resistance is mediated by its quaternary protein structure. We also proved that the release of SOD2 upon chemotherapy treatment correlates with cell death in BC cells. Then, after confirming that SOD2 is very stable in human serum, we sought to measure its circulating levels in a cohort of BC patients undergoing neoadjuvant therapy. The results showed that circulating levels of SOD2 increased when patients respond to the treatment according to the tumor shrinkage during neoadjuvant chemotherapy. Therefore, the measurement of SOD2 levels in plasma could improve the non-invasive monitoring of the therapeutic treatment in breast cancer patients. The identification of circulating biomarkers linked to the tumor cell death induced by treatment could be a useful for monitoring the action of the large number of cancer drugs currently used in the clinic. We envision that our approach could help uncover candidate tumor biomarkers to measure a tumor’s response to cancer therapy in real time by sampling the tumor throughout the course of treatment.