Desmoid tumors are proliferations of relatively benign appearing fibroblasts. Despite their histologic bland appearance, a significant subset of these tumors recurs aggressively and requires often debilitating surgery. Currently there are no molecular markers that predict the behavior of desmoid tumors.
AIM 1: To generate an extensive molecular dataset covering gene expression profiling and gene mutation analysis of desmoid tumors and scar samples.
AIM 2: To identify gene changes in expression level (for mRNA and non-coding RNAs) and gene mutations that correlate with risk for recurrence.
AIM 3: To use the same approach to identify genetic markers that can distinguish scar tissue from recurrent desmoid.
AIM 4: To explore the molecular heterogeneity of desmoid tumors based on the analysis of multiple regions sampled from a single tumor.
AIM 5: To search for low frequency CTNNB1/APC mutations in “wild-type” tumors.
The purpose of this study will be to perform a very broad molecular search for markers that can be used to address two clinically highly relevant questions. Using a carefully selected group of cases with known clinical outcome, we will use stranded RNA-Seq data (for mutation and expression level analysis) to generate a dataset that will characterize desmoid tumors in the broadest sense possible. First, this dataset will be searched for markers that can distinguish desmoid tumors that can be followed by “watchful waiting” at the time of their initial biopsy from tumors that require aggressive surgical therapy. When desmoid tumors recur, the distinction between recurrent tumor and scar tissue from prior surgery can be very difficult by histology, and immunohistochemistry for beta-catenin is insufficient. In the second approach that will use the dataset mentioned above, we will compare RNA-Seq findings on scar tissue with those seen in desmoid tumors to identify markers that distinguish scar from desmoid in an effort to find a novel immunohistochemistry marker to discern these two entities and that can be used in surgical pathology practice.
We also plan to perform deep targeted sequencing of CTNNB1 and APC genes in samples with no detectable mutations in Sanger sequencing/RNA-Seq data. According to the recent findings of Crago et al. (Genes Chromosomes Cancer. 2015 Oct;54(10):606-15), many of desmoid tumors initially considered as wild-type appear to carry low frequency mutations in CTNNB1/APC genes that can be detected using next generation sequencing. Our set of samples comprises relatively high portion of wild-type cases (27%) therefore we aim to further investigate this issue in order to better characterize our samples.
This work will build on an already existing large dataset in the van de Rijn laboratory and will benefit from the experience that we have generated in our laboratory for the use of archival formalin-fixed, paraffin-embedded tissue in high throughput studies using next generation sequencing. The project greatly benefits from the collaboration with Dr. Kristen Ganjoo at Stanford University Hospital and from the collaboration with Dr. Raffi Avedian, orthopedic surgeon at Stanford. We have also started a new collaboration with Dr. Justin Cates and Dr. Thomas Stricker from Vanderbilt University, and with Dr. Chiara Colombo from Milan, Italy. We have previously performed quantitative measurement of the expression levels for all know human protein-encoding genes in 9 desmoid tumor samples, 4 scars and 42 non-desmoid fibroblastic lesions. The number of scar samples that we have analyzed was too low but the preliminary results were encouraging. Our current dataset includes 29 primary, 20 recurrent desmoid tumors and 15 scars from 26 patients.
LAY VERSION OF ABSTRACT- Next generation sequencing approach to desmoid tumors