Diagnosis of metastatic neoplasms: Molecular approaches for identification of tissue of origin
Tumors of uncertain or unknown origin are estimated to constitute 3% to 5% of all metastatic cancer cases. Patients with these types of tumors show worse outcomes when compared to patients in which a primary tumor is identified. New molecular tests that identify molecular signatures of a tissue of origin have become available.
To review the literature on existing molecular approaches to the diagnosis of metastatic tumors of uncertain origin and discuss the current status and future developments in this area.
Published peer-reviewed literature, available information from medical organizations (National Comprehensive Cancer Network), and other publicly available information from tissue-of-origin test providers and/or manufacturers.
Molecular tests for tissue-of-origin determination in metastatic tumors are available and have the potential to significantly impact patient management. However, available validation data indicate that not all tests have shown adequate performance characteristics for clinical use. Pathologists and oncologists should carefully evaluate claims for accuracy and clinical utility for tissue-of-origin tests before using test results in patient management. The personalized medicine revolution includes the use of molecular tools for identification/confirmation of the site of origin for metastatic tumors, and in the future, this strategy might also be used to determine specific therapeutic approaches.
Available from: Yongzhong Zhao
- "CUP can be identified based on conserved tissue-specific gene expression . It has been shown that gene expression profiling can identify tissue of origin with an accuracy rate between 33% and 93% . Anthony et al. applied a 92-gene CUP assay to tumor samples from patients with CUP. "
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ABSTRACT: Gastric cancer, a highly heterogeneous disease, is the second leading cause of cancer death and the fourth most common cancer globally, with East Asia accounting for more than half of cases annually. Alongside TNM staging, gastric cancer clinic has two well-recognized classification systems, the Lauren classification that subdivides gastric adenocarcinoma into intestinal and diffuse types and the alternative World Health Organization system that divides gastric cancer into papillary, tubular, mucinous (colloid), and poorly cohesive carcinomas. Both classification systems enable a better understanding of the histogenesis and the biology of gastric cancer yet have a limited clinical utility in guiding patient therapy due to the molecular heterogeneity of gastric cancer. Unprecedented whole-genome-scale data have been catalyzing and advancing the molecular subtyping approach. Here we cataloged and compared those published gene expression profiling signatures in gastric cancer. We summarized recent integrated genomic characterization of gastric cancer based on additional data of somatic mutation, chromosomal instability, EBV virus infection, and DNA methylation. We identified the consensus patterns across these signatures and identified the underlying molecular pathways and biological functions. The identification of molecular subtyping of gastric adenocarcinoma and the development of integrated genomics approaches for clinical applications such as prediction of clinical intervening emerge as an essential phase toward personalized medicine in treating gastric cancer.
Computational and Structural Biotechnology Journal 09/2015; 13:448-58. DOI:10.1016/j.csbj.2015.08.001
Available from: sciencedirect.com
- "Studies have recognized limitations—for example , with respect to consistency, reproducibility, sensitivity, specificity , and result interpretation or reporting—of conventional morphological evaluation and IHC testing, prompting a search for more reliable and accurate methods of identifying the primary site in poorly differentiated carcinomas    . The gene-expression profiling (GEP) TOO Test (Pathwork Diagnostics , Inc., Redwood City, CA) of biopsy material has been cleared by the US Food and Drug Administration and validated to provide independent information on the TOO    . The processing laboratory has Clinical Laboratory Improvement Amendments certification. "
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ABSTRACT: Gene-expression profiling (GEP) reliably supplements traditional clinicopathological information on the tissue of origin (TOO) in metastatic or poorly differentiated cancer. A cost-effectiveness analysis of GEP TOO testing versus usual care was conducted from a US third-party payer perspective.
Data on recommendation changes for chemotherapy, surgery, radiation therapy, blood tests, imaging investigations, and hospice care were obtained from a retrospective, observational study of patients whose physicians received GEP TOO test results. The effects of chemotherapy recommendation changes on survival were based on the results of trials cited in National Comprehensive Cancer Network and UpToDate guidelines. Drug and administration costs were based on average doses reported in National Comprehensive Cancer Network guidelines. Other unit costs came from Centers for Medicare & Medicaid Services fee schedules. Quality-of-life weights were obtained from literature. Bootstrap analysis estimated sample variability; probabilistic sensitivity analysis addressed parameter uncertainty.
Chemotherapy regimen recommendations consistent with guidelines for final tumor-site diagnoses increased significantly from 42% to 65% (net difference 23%; P<0.001). Projected overall survival increased from 15.9 to 19.5 months (mean difference 3.6 months; two-sided 95% confidence interval [CI] 3.2-3.9). The average increase in quality-adjusted life-months was 2.7 months (95% CI 1.5-4.3), and average third-party payer costs per patient increased by $10,360 (95% CI $2,982-$19,192). The cost per quality-adjusted life-year gained was $46,858 (95% CI $13,351-$104,269).
GEP TOO testing significantly altered clinical practice patterns and is projected to increase overall survival, quality-adjusted life-years, and costs, resulting in an expected cost per quality-adjusted life-year of less than $50,000.
Value in Health 02/2013; 16(1):46-56. DOI:10.1016/j.jval.2012.09.005 · 3.28 Impact Factor
Available from: Torik Ayoubi
- "Several studies have already demonstrated that it is possible to use genome-wide gene expression analysis using micro-array technology in the determination of the tissue of origin of CUPs (Monzon and Koen, 2010). A major problem with the published approaches is that they are not easily implemented and interpreted in a clinical setting, as pathologist and clinicians will not be likely to set up support vector machine based classifiers or other complicated mathematical procedures for the interpretation of gene expression micro-array results. "
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ABSTRACT: We have used TCLASS® a multi-class tumour classifier that interprets gene expression microarray data and allows the identification of the primary site of CUPs. The classifier is implemented as a web-based tool and is an extremely simple and straightforward approach for molecular characterisation of tumour samples. We randomly selected 100 metastatic cancer samples from the large Expression Project for Oncology and show an accuracy of TCLASS of 88% on these samples. We conclude that TCLASS is a user friendly tool that will allow the molecular characterisation of tumour samples of unknown origin analysed with Affymetrix U133 Plus 2.0 GeneChips.
International Journal of Healthcare Technology and Management 04/2011; 12(2):179 - 193. DOI:10.1504/IJHTM.2011.039628
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