Methods for determining prognosis of colorectal cancer
Inventors
O'Shannessy, Daniel John • Nicolaides, Nicholas C. • SOMERS, Elizabeth B.
Assignees
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Publication Number
US-9915660-B2
Publication Date
2018-03-13
Expiration Date
Abstract
Provided herein are methods for determining the risk that a subject diagnosed with colorectal cancer will develop a recurrence of colorectal cancer and methods of predicting clinical outcome for a subject diagnosed with colorectal cancer by a) determining the level of expression for each marker of a panel of markers in a panel of tumor compartments in a tumor tissue sample from the subject, wherein the panel of markers comprises at least two of TEM1, HIF2α, CAIX, PDGFRβ, fibronectin, collagen I, collagen IV, and CD31 and wherein the panel of tumor compartments comprises at least three tumor compartments of pure stroma, tumor, stromal vessel, and tumor vessel; b) determining the TAPPS score for said subject; and c) comparing the TAPPS score of the subject to the TAPPS score of a population of subjects diagnosed with colorectal cancer. Also provided are related computer-implemented methods and systems, kits, and tumor microarrays.
Core Innovation
The document describes methods and systems for colorectal cancer prognosis and recurrence risk classification by profiling a TEM1-associated biomarker panel across multiple histological compartments. Compartment-specific expression profiling is described using biomarkers including TEM1, HIF2α, CAIX, PDGFRβ, fibronectin, collagen I/IV, and CD31 in at least three histological compartments, including pure stroma, tumor, stromal vessel, and tumor vessel.
A computational prognostic signature is described that uses TAPPS risk/prognostic signature scoring derived from multivariate Cox proportional hazards modeling. The document describes computing a subject TAPPS score and comparing the subject TAPPS score to a colorectal cancer population to classify recurrence risk categories such as low/high recurrence risk.
The document further describes localization of tumor compartment markers using quantitative image analysis to assign marker measurements to tumor compartments. Quantitative immunofluorescence and immunohistochemistry localization are described using quantitative image analysis approaches such as AQUA® with compartment masks and tissue microarray or tissue sample array formats.
Claims Coverage
The partial content provided includes two independent claims, both directed to tissue sample arrays for colorectal cancer that are labeled with specified antibody panels. Across these independent claims, the inventive features primarily differ by the specific marker set included on the array.
Colorectal cancer tissue sample array with cytokeratin, vimentin, TEM1, fibronectin-1, and collagen IV
A tissue sample array comprising colorectal cancer tissue samples, wherein the array is labeled with antibodies consisting of an antibody that specifically binds cytokeratin, an antibody that specifically binds vimentin, an antibody that specifically binds TEM1, an antibody that specifically binds fibronectin-1, and an antibody that specifically binds collagen IV.
Colorectal cancer tissue sample array with cytokeratin, vimentin, TEM1, fibronectin-1, collagen IV, CD31, and HIF2α
A tissue sample array comprising colorectal cancer tissue samples, wherein the array is labeled with antibodies consisting of an antibody that specifically binds cytokeratin, an antibody that specifically binds vimentin, an antibody that specifically binds TEM1, an antibody that specifically binds fibronectin-1, an antibody that specifically binds collagen IV, an antibody that specifically binds CD31, and an antibody that specifically binds HIF2α.
The independent claims cover colorectal cancer tissue sample arrays labeled with marker-specific antibody panels. One independent claim requires a five-marker TEM1-associated panel including cytokeratin, vimentin, TEM1, fibronectin-1, and collagen IV, while the other independent claim expands the panel to include CD31 and HIF2α.
Stated Advantages
Documented Applications
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