As cancer-fighting therapies become more targeted, clinicians are looking increasingly toward emerging technologies to help confirm the primary site of a patient's disease.
William David Henner, MD, PhD chief medical officer of Pathwork Diagnostics
As cancer-fighting therapies become more targeted, clinicians are looking increasingly toward emerging technologies to help confirm the primary site of a patient’s disease. Nevertheless, a positive identification of the initial tumor site remains a problem of unknown proportions. The National Cancer Institute estimates that the primary site is never identified in approximately 2% to 4% of all cancer patients; the American Cancer Society says >30,000 people a year are diagnosed with cancers of unknown primary origin.
Pathwork Diagnostics, Inc, is an 8-year-old company based in Redwood City, California, that has developed a gene-based test that helps identify tumor types. In June, the FDA cleared the test as safe and effective, paving the way for its broad laboratory usage.
Here, William David Henner, MD, PhD, chief medical officer of Pathwork Diagnostics, discusses the technology.
ONCPlease describe how the Pathwork® Tissue of Origin Test works. Henner: The Tissue of Origin Test uses a tumor’s own genomic information to help healthcare professionals determine what type of cancer cells are present in a malignant tumor, helping identify the primary site for metastatic, poorly differentiated, and undifferentiated cancers. It is the only FDA-cleared molecular diagnostic test for tissue of origin.
The test measures the gene expression pattern of more than 2000 genes in the patient’s tumor and compares it with expression patterns of 15 known tumor types, representing 58 morphologies and 90% of all solid tumors. It then provides a report with an objective Similarity Score for each tumor type in the panel.
Knowing the primary site with greater certainty helps physicians prescribe prompt treatment with the most appropriate regimens and more effective targeted therapies. Patients may benefit from less exposure to broad-spectrum therapies that may be more toxic and ineffective.
Traditional diagnostic approaches for metastatic, poorly differentiated, and undifferentiated cancers—including imaging and immunohistochemistry (IHC)—are time-consuming, require a complex iterative process, and often do not produce a definitive diagnosis.
IHC, microscopic examination in which specific antigens are detected using fluorescent dye or enzyme markers, has proven to be a highly useful tool to distinguish among different candidate tissues. However, choosing among 3 or more candidate tissues remains a challenge, given the limited specificity and sensitivity of available IHCs. One meta-analysis showed that IHC was only 66% accurate at identifying the primary site of metastatic tumors.1 In addition, currently available IHC markers do not address the full range of potential tumor types, and the most commonly used staining phenotypes (CK7 and CK20) produce sufficient numbers of false positives and false negatives to make a definitive diagnosis difficult.2
Cytogenetic methods, which assess chromosomal abnormalities to pinpoint the primary tumor site, can provide insights in a number of specific situations, but generally not in a comprehensive manner. This technique is limited because only a few diagnostic chromosomal abnormalities have been identified to date.3
Imaging is also a standard tool used to assess patients with tumors that are difficult to classify. Computed tomography scans, mammography, magnetic resonance imaging, and fluorodeoxyglucose positron emission tomography can be helpful to pinpoint the anatomic locations of the tumor, but cannot confirm its origin.
In a key validation study, the Tissue of Origin Test has demonstrated 89% positive agreement (akin to sensitivity) with available diagnoses.
The Tissue of Origin Test is supported by extensive analytical and clinical validation data. In 462 formalin-fixed, paraffin-embedded (FFPE) specimens that had been identified as 1 of the 15 tumor types on the panel using existing methods, the test demonstrated 89% positive agreement (akin to sensitivity) and greater than 99% negative agreement (akin to specificity) with available diagnoses.4
In a second independent confirmatory validation study, conducted with University of California, San Francisco investigators, the test demonstrated 95% positive agreement.5 Additionally, in a study conducted with investigators at The Methodist Hospital in Houston, Texas, a study of body fluid specimens demonstrated 94% positive agreement.6 In reproducibility studies, the Tissue of Origin Test demonstrated an average 94% overall concordance across 4 laboratories in a cross-laboratory comparison study of 60 metastatic and poorly differentiated and undifferentiated tissue specimens.7
A recent study of 111 cases derived from >65 academic and community practices showed that after receiving the Tissue of Origin Test results for patients with difficult-to-diagnose primary cancers, the determination of the primary diagnosis site was changed for 54% of patients and treatment management was changed for 65% of patients.8
The Pathwork Tissue of Origin Test can provide no information about a tumor that is not 1 of the 15 known tumor types in the Pathwork Tissue of Origin Test database. The test is intended as an aid to diagnosis and should be considered along with all of the available information about clinical history, histology, IHC, and imaging to allow the physician to determine the final diagnosis of tumor type.
This illustration shows the work flow from sample to a report that covers 15 different tumor types.
The Tissue of Origin Test is FDA-cleared to help identify metastatic, poorly differentiated, and undifferentiated cancers. It should be used as an adjunct to standard diagnostic techniques such as IHC and imaging. Specific instances in which physicians are likely to order the test include when:
The problem of accurately measuring RNA expression was solved through a combination of assay development and Pathwork’s proprietary informatics. Recent advances in molecular assays have allowed fragmented RNA from FFPE tissues to be processed successfully on microarrays. Pathwork incorporated such advances in the test, and then utilized advanced informatics to develop a robust classification algorithm with the microarray data. These informatics use large numbers of genes so the score is not dependent on any single gene. Furthermore, the algorithm has sophisticated standardization techniques. If 1 particular gene or some number of genes are degraded, as often happens with FFPE specimens, the algorithm is still able to generate a robust result.
The cost to classify the primary tumor site can be significant, given that traditional approaches involve multiple diagnostic technologies that are often run in parallel. A recent study indicated that most patients with difficult-to-diagnose primary cancers undergo an average of 10 IHC tests.8 Another study showed that, for certain challenging cases, the primary cancer site was found in only 4 (7.1%) of the 56 cases studied, and the average cost of diagnosis was $17,973.9
The cost of the Tissue of Origin Test is approximately $4000, which is similar to other genomic tests on the market, and a small fraction of the overall cost of cancer care. For example, a study of metastatic colon cancer patients showed that their average annual healthcare cost was more than $100,000.10 By classifying a tumor’s origin, clinicians can potentially initiate standard-of-care, cancer-specific therapies, allowing improved patient outcomes and management of healthcare resources by reducing the use of less targeted, broad-based therapies.
It was a challenge to strike the right balance of implementing quality systems, creating a structured process, and creating a robust design history file for FDA purposes, without overburdening a small organization. So we took the development in phases, starting with core processes. We brought in talented people with project management expertise and combined them with others with scientific expertise to move the process along.
Another challenge, and a notable success, was how to conduct the complex data analysis required to solve the informatics questions. As part of our solution, we innovated in cloud computing to bring the required computer horsepower to bear to meet that challenge in a timely way.
Challenges that we will continue to face include commercial challenges such as reimbursement, which we are addressing through a combination of the highest-quality science and the development of key advocates.