BlueCross and BlueShield of Montana Medical Policy/Codes
Gene Expression Profiling (GEP) Using Microarray Analysis
Chapter: Genetic Testing
Current Effective Date: October 25, 2013
Original Effective Date: June 07, 2010
Publish Date: October 25, 2013
Revised Dates: February 15, 2012; September 4, 2013
Description

Microarray-based evaluation of multiple marker probes may be done on blood, tissue, or fluid specimens.  The National Human Genome Research Institute describes microarray technology as follows.

“Although all of the cells in the human body contain identical genetic material, the same genes are not active in every cell.  Studying which genes are active and which are inactive in different cell types helps scientists to understand both how these cells function normally and how they are affected when various genes do not perform properly.  In the past, scientists have only been able to conduct these genetic analyses on a few genes at once.  With the development of DNA microarray technology, however, scientists can now examine how active thousands of genes are at any given time…DNA microarrays are created by robotic machines that arrange minuscule amounts of hundreds or thousands of gene sequences on a single microscope slide.  Researchers have a database of over 40,000 gene sequences that they can use for this purpose.  When a gene is activated, cellular machinery begins to copy certain segments of that gene.  The resulting product is known as messenger RNA (mRNA), which is the body's template for creating proteins.  The mRNA produced by the cell is complementary, and therefore will bind to the original portion of the DNA strand from which it was copied.  To determine which genes are turned on and which are turned off in a given cell, a researcher must first collect the messenger RNA molecules present in that cell.  The researcher then labels each mRNA molecule by attaching a fluorescent dye.  Next, the researcher places the labeled mRNA onto a DNA microarray slide.  The messenger RNA that was present in the cell will then hybridize - or bind - to its complementary DNA on the microarray, leaving its fluorescent tag.  A researcher must then use a special scanner to measure the fluorescent areas on the microarray.  If a particular gene is very active, it produces many molecules of messenger RNA, which hybridize to the DNA on the microarray and generate a very bright fluorescent area.  Genes that are somewhat active produce fewer mRNAs, which results in dimmer fluorescent spots.  If there is no fluorescence, none of the messenger molecules have hybridized to the DNA, indicating that the gene is inactive.  Researchers frequently use this technique to examine the activity of various genes at different times.”

Cancers of Unknown Primary

Cancers of unknown primary, or occult primary malignancies, are tumors that have metastasized from an unknown primary source, and make up approximately 2%–6% of all cancer cases in the United States.  Identifying the primary origin of a tumor can dictate cancer-specific treatment, expected outcome and prognosis. 

Most cancers of unknown primary are adenocarcinomas or undifferentiated tumors; less commonly they may be squamous carcinomas, melanoma, sarcoma, or neuroendocrine tumors.  The most common primary sites of cancers of unknown primary are lung and pancreas, followed by colon and stomach, then breast, ovary, prostate, and solid-organ carcinomas of the kidney, thyroid, and liver.  Conventional methods used to aid in the identification of the origin of a cancer of unknown primary include a thorough history and physical examination, computed tomography (CT) scans of the chest, abdomen, and pelvis; routine laboratory studies; and targeted evaluation of specific signs and symptoms.

Biopsy of a cancer of unknown primary with detailed pathology evaluation may include immunohistochemical (IHC) analysis of the tumor.  IHC identifies different antigens present on different types of tumors, and can usually distinguish an epithelial tumor (i.e., carcinoma) from a melanoma or sarcoma.  Detailed cytokeratin panels often allow further classification of a carcinoma; however, tumors of different origins may show overlapping cytokeratin expression.  The results of IHC may provide a narrow differential of possible sources of a tumor’s origin, but not necessarily a definitive answer. 

The current success rate of the diagnostic workup of a cancer of unknown primary is 20%–30%, including consideration of clinical, radiologic, and extensive histopathologic methods.  Recent advances in the understanding of gene expression in normal and malignant cells have led researchers to explore molecular classification as a way to improve the identification of the site of origin of a cancer of unknown primary.

Molecular Classification of Cancers

The molecular classification of cancers is based on the premise that, despite different degrees of dedifferentiation, tumors retain sufficient gene expression “signatures” as to their cell of origin, even after metastasis.  Theoretically, it is possible to build a gene expression database spanning many different tumor types to compare to the expression profile of very poorly differentiated tumors or a cancer of unknown primary to aid in the identification of the tumor type and organ of origin.  The feasibility of using molecular classification schemes with gene expression profiling to classify these tumors of uncertain origin has been demonstrated in several studies.

Ramaswamy and co-workers, using microarray gene expression analysis of over 16,000 genes, showed 78% classification accuracy of 14 common tumor types.  Su and colleagues, using large-scale RNA profiling with microarrays, accurately predicted the anatomical site of tumor origin for 90% of 175 carcinomas.  Bloom et al. combined multiple tumor microarray databases, creating a large collection of tumors, including 21 types, resulting in a molecular classification scheme that reached 85% accuracy.  Although microarray technology enables large numbers of genes to be evaluated at the same time, it is complex and time-consuming, and is limited in its use as mostly a research tool.  In addition, since formalin fixation can degrade RNA, fresh/frozen tissue is preferred for better accuracy with microarray technology; however, formalin-fixed is the standard for pathology material in current practice.

One such microarray technology is the Pathwork® Pathchip.  The test measures the expression of more than 1,500 genes and compares the similarity of the GEP of a cancer of unknown primary to a database of known profiles from 15 tissues with more than 60 histologic morphologies.  The report generated for each tumor consists of a “similarity score,” which is a measure of similarity of the GEP of the specimen to the profile of the 15 known tumors in the database.  Scores range from 0 (very low similarity) to 100 (very high similarity), and sum to 100 across all 15 tissues on the panel.  If a single similarity score is greater than or equal to 30, it indicates that this is likely the tissue of origin.  If every similarity score is between 5 and 30, the test result is considered indeterminate, and a similarity score of <5 rules out that tissue type as the likely origin.

An alternative method to measure gene expression is real-time quantitative polymerase chain reaction (RT-PCR).  RT-PCR can be used at the practice level; however, it can only measure, at most, a few hundred genes, limiting tumor categorization to seven or fewer types.  Tumor classification accuracy rates using RT-PCR have been reported to be as high as 87%, but less so (71%) the more undifferentiated the tumor tested.

In July 2008, the test “Pathwork® Tissue of Origin” (Pathwork Diagnostics, Inc., Sunnyvale, CA) was cleared with limitations* for marketing by the U.S Food and Drug Administration (FDA) through the 510(k) process.  The FDA determined that the test was substantially equivalent to existing tests for use in measuring the degree of similarity between the RNA expression pattern in a patient's fresh-frozen tumor and the RNA expression patterns in a database of tumor samples (poorly differentiated, undifferentiated, and metastatic cases) that were diagnosed according to current clinical and pathologic practice.  The database contains examples of RNA expression patterns for 15 common malignant tumor types: bladder, breast, colorectal, gastric, hepatocellular, kidney, non-small cell lung, ovarian, pancreatic, prostate, and thyroid carcinomas, melanoma, testicular germ cell tumor, non-Hodgkins lymphoma (not otherwise specified), and soft tissue sarcoma (not otherwise specified).  The Pathwork® Tissue of Origin Test result is intended for use in the context of the patient's clinical history and other diagnostic tests evaluated by a qualified clinician.

*Limitations to the FDA clearance were as follows:

“The Pathwork® Tissue of Origin Test is not intended to establish the origin of tumors that cannot be diagnosed according to current clinical and pathologic practice, (e.g., carcinoma of unknown primary).  It is not intended to sub-classify or modify the classification of tumors that can be diagnosed by current clinical and pathologic practice; nor to predict disease course, or survival or treatment efficacy; nor to distinguish primary from metastatic tumor.  Tumor types not in the Pathwork® Tissue of Origin Test database may have RNA expression patterns that are similar to RNA expression patterns in tumor types in the database, leading to indeterminate results or misclassifications.”

In June 2010, the “Pathwork® Tissue of Origin Test Kit-FFPE” (Pathwork Diagnostics) was cleared for marketing by the FDA through the 510(k) process.  The 2010 clearance is an expanded application, which allows the test to be run on a patient’s formalin-fixed, paraffin-embedded (FFPE) tumor and has the same indications and limitations.

Markers to Predict Response to Therapy

Target Now™, as described by the developer, Caris Diagnostics, Inc. (Caris Dx, Irving, Texas), analyzes cancerous tissue using a combination of diagnostic technologies, including immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), quantitative PCR, gene sequencing and microarray analysis.  The information provided by Target Now may identify biological markers in an individual’s cancer that are associated with targets for certain drugs, and help predict the likelihood of response to therapy.  Target Now can be performed on either formalin-fixed paraffin-embedded (FFPE) tissue or fresh frozen tissue samples.  When FFPE is provided, up to 18 biomarkers are performed by immunohistochemistry (IHC) to determine the levels of clinically relevant protein expression.  Depending on the resulting IHC expression report, additional chromosomal anomalies may be evaluated by FISH testing and DNA microarray sequencing.

Policy

Each benefit plan, summary plan description or contract defines which services are covered, which services are excluded, and which services are subject to dollar caps or other limitations, conditions or exclusions.  Members and their providers have the responsibility for consulting the member's benefit plan, summary plan description or contract to determine if there are any exclusions or other benefit limitations applicable to this service or supply.  If there is a discrepancy between a Medical Policy and a member's benefit plan, summary plan description or contract, the benefit plan, summary plan description or contract will govern.

Investigational

Blue Cross and Blue Shield of Montana (BCBSMT) considers gene expression profiling (GEP) using microarray analysis is considered experimental, investigational and unproven.  GEP tests that utilize microarray analysis include, but are not limited to, tests done in the presence of a disease process, (e.g., cancer, infectious disease) to diagnose, classify, monitor efficacy of therapy, or predict pathogenicity or response to therapy.   (Examples of GEP tests include, but are not limited to, the Pathwork® Tissue of Origin test,  the Pathwork® Tissue of Origin Test Kit-FFPE, and the TargetNow™ Test.)

Policy Guidelines

The preparation of the probes might be coded using a combination of the molecular diagnostic codes 83890-83913 and the analysis of the probes might be coded using array-based evaluation of multiple molecular probes codes 88384-88386 based on the number of probes analyzed.

Pathwork Diagnostics states that they use 84999 (unlisted chemistry procedure).

Rationale

DNA microarrays have been used increasingly in research and clinical applications; however, drawing conclusions from the results have been problematic because of difficulty with accurate reporting of results, experimental reproducibility, and identification and interpretation of relevant information.  In their 2008 review, Walker and Hughes point out that studies utilizing DNA microarrays for molecular profiling have been aimed at stratifying the severity of disease, identifying disease subtypes, predicting prognosis, and predicting benefit from adjuvant therapy.  They state that, while collectively these studies do provide evidence of improvements in understanding of disease and patient care, the high costs and doubts about reproducibility have limited clinical use of these new tools.  The analysis of the high volume of data is more complicated than anticipated.  Some inconsistencies include those between data from different experimental platforms, as well as between laboratories using the same experimental platform.  They concluded that the “original excitement surrounding DNA microarrays has given way to a feeling in the scientific community that expectations have exceeded reality.  There have been difficulties in applying the technology, in achieving reproducible results and in the management of high throughput data.”

Pathwork® Test

Analytic Validity (Technical performance, i.e., reproducibility)

Fresh Frozen Tumor Sample

In 2008, Dumar and colleagues analyzed performance characteristics of the Pathwork test in a cross-laboratory comparison study of 60 poorly and undifferentiated metastatic (77%) and primary (23%) tumors.  Three academic and one commercial laboratory received archived frozen tissue specimens for procurement and processing at their individual sites.  Steps performed by each of the four laboratories included tissue handling, RNA extraction, and microarray-based gene expression assays using standard microarray protocol.  The resulting microarray data generated at each laboratory were sent in a blinded fashion to Pathwork Diagnostics for generation of similarity scores for each type.  Reports of the similarity scores were sent back (blinded) to the pathologists at the four laboratories for their use in generating an interpretation.  Data were compared among the four laboratories to determine assay reproducibility.  Correlation coefficients were between 0.95 and 0.97 for pathologists’ interpretations of the similarity scores, and cross-laboratory comparisons showed an average 93.8% overall concordance between laboratories in terms of final tissue diagnosis.  A detailed summary of the data is available online at <http://www.accessdata.fda.gov>.

Formalin-fixed, paraffin-embedded (FFPE) Tumor Sample

Analytical performance characteristics of the Pathwork test for FFPE were analyzed in a cross-laboratory comparison study of 60 poorly and undifferentiated metastatic (45%) and primary (35%) tumors.  Each of the 15 tumor tissue types were represented by four specimens each, with the exception of breast (n=3) and soft tissue sarcoma (n=5).  Samples were distributed among three laboratories for procurement and processing at their individual sites.  Data were compared among the three laboratories to determine assay reproducibility.  Correlation coefficients were between 0.92 and 0.93 for pathologists’ interpretations of the similarity scores, and cross-laboratory comparisons showed an average 82.1% overall concordance between laboratories in terms of final tissue diagnosis.  A detailed summary of the data is available online at: <http://www.accessdata.fda.gov>.  Additional analyses of the analytic performance of the test have produced similar results.

Clinical Validity (Sensitivity and specificity)

Fresh Frozen Tumor sample

The clinical validation study for the Pathwork Tissue of Origin test that was submitted to the FDA involved a comparison of the gene expression profiles of 25 to 69 samples to each of the 15 known tumors on the Pathwork panel (average 36 specimens per known tumor).  The specimens included poorly differentiated, undifferentiated, and metastatic tumors.  A similarity score was given to 545 specimens and then compared to the available specimen diagnosis.  Based on the 545 results, the probability that a true tissue of origin call was obtained, when a similarity score of 30 or more was reported, was 92.9% (95% CI: 90.3–95.0), and the probability that a true negative tissue call was made, when a similarity score of five or less was reported, was 99.7% (95% CI: 99.6–99.8%).  Overall, the Pathwork performance comparing the profiles of the 545 specimens to the panel of 15 known tumor types showed a positive percent agreement of 89.4% (95% CI: 86.5-91.8%), negative percent agreement of 99.6% (95% CI: 98.6–100%], non-agreement of 6.2% (95% CI: 4.4–8.6%), and indeterminate of 4.4% (95% CI: 2.8–6.5%). 

Monzon and colleagues conducted a multicenter blinded validation study of the Pathwork test.  The specimens included poorly differentiated, undifferentiated, and metastatic tumors.  A total of 351 frozen specimens and electronic files of microarray data on 271 specimens were obtained, with 547 meeting all inclusion criteria.  A similarity score was given to the specimens, which was then compared to the original pathology report that accompanied the specimen.  Overall, the Pathwork performance comparing the profiles of the 547 specimens to the panel of 15 known tumor types showed an overall agreement of 87.8% (95% CI: 84.7–90.4%) with the reference diagnosis.  Sensitivity and specificity were 87.8% (95% CI: 84.7–90.4%) and 99.4% (95% CI: 98.3–99.9%), respectively, with the original pathology report acting as the reference standard.  The authors acknowledged that since there was no independent confirmation of the original pathology, using the pathology reports as the reference standard could introduce errors into the study results.  Agreement differed by site: 94.1% for breast, 72% for both gastric and pancreatic.  Performance differences between tissue sites were statistically different (chi-squared=42.02; p=0.04; degrees of freedom [df]=28; n=547).  Rates of agreement between test result and reference diagnosis varied by site: 88%, 84.4%, 92.3%, and 89.7% for Clinical Genomics facility, Cogenics, Mayo Clinic, and the International Genomics Consortium, respectively, but these differences were not statistically significant.

Formalin-fixed, paraffin-embedded (FFPE) tumor sample

The clinical validation study for the Pathwork Tissue of Origin Test Kit-FFPE that was submitted to the FDA involved a comparison of the gene expression profiles of 25 to 57 samples to each of the 15 known tumors on the Pathwork panel (average 31 specimens per known tumor).  The specimens included poorly differentiated, undifferentiated, and metastatic tumors.  A similarity score was given to 462 specimens and then compared to the available specimen diagnosis.  Based on the 462 results, the probability that a true tissue of origin call was obtained when a similarity score was reported was 88.5% (95% CI: 85.3-91.3%), and the probability that a true-negative tissue call was made when a similarity score of 5 or less was reported was 99.8% (95% CI: 99.7–99.9%).  Overall, the Pathwork performance comparing the profiles of the 462 specimens to the panel of 15 known tumor types showed a positive percent agreement of 88.5% (95% CI: 85.3-91.3%), negative percent agreement of 99.1% (95% CI: 97.6–99.7%], non-agreement of 11.5% (95% CI: 8.7–14.7%).  Further details of these data are available online at <http://www.accessdata.fda.gov>.

Few other studies have analyzed the clinical validity of using microarray gene expression technology.  One study used microarray technology (i.e., CupPrint, Agendia, Amsterdam, the Netherlands) that used formalin-fixed paraffin-embedded tumor samples.  The study analyzed 495 genes in 84 patients with tumors of known origin and 38 patients with cancer of unknown primary to assess the potential contribution to patient management.  Sixteen of the patients with cancer of unknown primary had their primary site of tumor origin identified by standard laboratory techniques.  Molecular testing identified the correct site of tumor origin in 94% of cases of cancers of unknown primary and 83% of the tumors of known origin.  Ferracin and colleagues published a report of microRNA profiling using 101 FFPE tumor samples from primary cancers and metastases.  Forty samples, of 10 cancer types, were used to build a cancer-type-specific microRNA signature.  This signature was then used to predict the primary site of metastatic cancer.  Overall accuracy was 100% for primary cancers and 78% for metastatic cancers in the cohort sample.  The signature was then applied to a published set of 170 samples where the prediction rates were consistent with the cohort results.

Clinical Utility (Impact on patient outcomes)

No clinical trials have been conducted that would provide direct evidence of the clinical utility of the Pathwork Tissue of Origin test, nor has the clinical application of gene expression profiling to direct patient management and tumor site-specific therapy been demonstrated in prospective studies. 

One small study using microarray technology (not Pathwork) on formalin-fixed paraffin-embedded tumor, retrospectively analyzed the gene expression profile of tumors from 21 patients with cancer of unknown primary.  The clinical relevance and implications of the results on patient management were reviewed.  In the 21 patients, standard methods had failed to determine a primary tumor origin.  Results of gene expression profiling were reviewed in the context of tumor histology and clinical suspicion of tumor origin.  Gene expression profiling confirmed the clinical suspicion in 16 of 21 cases, with a clinical/gene expression profile inconsistency in four of 21 and a pathological/gene profile inconsistency in one patient.  The authors concluded that the use of gene expression profiling would have influenced patient management in 12 of 21 of the cases. 

Clinical Trials

In June 2009, final data collection for the primary outcomes was completed in a study aimed at the identification of the tissue of origin in patients with metastatic tumors of unknown primary site.  As of October 2011, no results have been published in the peer-reviewed literature.

An October 2011 search of the National Cancer Institute and ClinicalTrials.gov databases returned no ongoing Phase II or III studies investigating the use of molecular gene expression profiling with microarray technology in patients with cancer of unknown primary.

Practice Guidelines and Position Statements

National Comprehensive Cancer Network (NCCN) guidelines for the workup of an occult primary malignancy address the use of molecular methods in the classification of tumors.  They conclude that there is insufficient data to confirm whether gene expression profiling can be used in choosing treatment options that would improve the prognosis of patients with occult primary cancers.  Therefore the panel does not recommend the testing as a part of routine evaluation of a cancer of unknown primary origin.

Summary

Limited data have been published on the clinical impact of the Pathwork test.  Without knowledge of how this test would affect clinical practice and clinical health outcomes (clinical utility) for patients diagnosed through the use of this test, the experimental, investigational and unproven coverage statement remains unchanged.  A trial where patients with a cancer of unknown primary were randomized to receive treatment based on the results of the Pathwork Tissue of Origin test or based on standard diagnostic procedures would be useful to determine the clinical utility of the Pathwork test.

Target Now™ Test

At the 100th Annual Meeting of the American Association for Cancer Research (AACR) in April 2009, lead researcher Dr. Daniel Von Hoff reported a pilot study of molecular profiling of tumors (Target Now), conducted in patients with advanced cancers that were progressing despite several previous treatments.  This study found that molecular profiling helped identify therapies that ultimately had an impact on the disease.  Shrinkage of tumors was shown in 47% of patients.  Also, 27% of the profiled patients showed improvement in progression-free survival, compared with that seen with the previous therapy, and there is a suggestion of improved overall survival in these patients.  Although Dr. Von Hoff said this is a promising result, he acknowledged that the study was small (66 patients) and that, because patients acted as their own controls, a larger randomized trial is needed. 

Summary

Although GEP (e.g., the Target Now Test) is promising, there remain problems with accuracy and reproducibility of results, and with identification and interpretation of information obtained.  A March 2009 report states Massachusetts General Hospital had decided to make gene testing standard in cancer treatment; it is believed to be the first hospital in the United States to do so.  However, the report also states that doctors acknowledge that it is unclear whether screening patients for an expanded library of tumor defects will actually save money on drugs, or whether it will translate into longer lives.  No peer reviewed clinical studies were identified that would change this conclusion.  Therefore, GEP using microarray technology is not supported by evidence in the peer-reviewed medical literature that:

  • Permits conclusions on the effect of GEP using microarray analysis on health outcomes.
  • Demonstrates an improvement in net health outcome through use of GEP using microarray analysis.
  • Demonstrates that improvement attainable by GEP using microarray analysis is attainable outside investigational settings.

A search of peer reviewed literature through January 2012 identified no new clinical trial publications or any additional information that would change the coverage position of this medical policy.

Coding

Disclaimer for coding information on Medical Policies          

Procedure and diagnosis codes on Medical Policy documents are included only as a general reference tool for each policy.  They may not be all-inclusive.           

The presence or absence of procedure, service, supply, device or diagnosis codes in a Medical Policy document has no relevance for determination of benefit coverage for members or reimbursement for providers.  Only the written coverage position in a medical policy should be used for such determinations.           

Benefit coverage determinations based on written Medical Policy coverage positions must include review of the member’s benefit contract or Summary Plan Description (SPD) for defined coverage vs. non-coverage, benefit exclusions, and benefit limitations such as dollar or duration caps. 

ICD-9 Codes

196.9, 199.0, 199.1, 199.2

ICD-10 Codes

C79.9, C80.0, C80.1

Procedural Codes: 84999, [Deleted 1/2013: 83891, 83892, 83893, 83894, 83896, 83897, 83898, 83900, 83901, 83902, 83903, 83904, 83905, 83906, 83907, 83908, 83909, 83912, 83913, 83914, 83890, 88384, 88385, 88386]
References
  1. Ramaswamy S, Tamayo P, Rifkin R et al. Multiclass cancer diagnosis using tumor gene expression signatures.  Proc Natl Acad Sci USA 2001; 98(26):15149-54.
  2. Su AI, Welsh JB, Sapinoso LM et al. Molecular classification of human carcinomas by use of gene expression signatures.  Cancer Res 2001; 61(20):7388-93.
  3. Ma XJ, Patel R, Wang X et al. Molecular classification of human cancers using a 92-gene real-time quantitative polymerase chain reaction assay.  Arch Pathol Lab Med 2006; 130(4):465-73.
  4. Tothill RW, Kowalczyk A, Rischin D et al.  An expression-based site of origin diagnostic method designed for clinical application to cancer of unknown origin.  Cancer Res 2005; 65(10):4031-40.
  5. Bloom G, Yang IV, Boulware D et al. Multi-platform, multi-site, microarray-based human tumor classification.  Am J Pathol 2004; 164(1):9-16.
  6. Talantov D, Baden J, Jatkoe T et al. A quantitative reverse transcriptase-polymerase chain reaction assay to identify metastatic carcinoma tissue of origin.  J Mol Diagn 2006; 8(3):320-9.
  7. Walker, S.W. and T.A. Hughes.  Messenger RNA expression profiling using DNA microarray technology: Diagnostic tool, scientific analysis or un-interruptable data?  International Journal of Molecular Medicine (2008) 21:13-17.
  8. Dumur CI, Lyons-Weiler M, Sciulli C et al. Interlaboratory performance of a microarray-based gene expression test to determine tissue of origin in poorly differentiated and undifferentiated cancers. J Mol Diagn 2008; 10(1):67-77.
  9. Bridgewater J, van Laar R, Floore A et al.  Gene expression profiling may improve diagnosis in patients with carcinoma of unknown primary.  Br J Cancer 2008; 98(8):1425-30.
  10. Molecular Karyotyping Summary.  Chicago, Illinois: Blue Cross Blue Shield Association – Technology Evaluation Center and Medical Policy (TEC-MP) Clearinghouse News (2008 April 25) p1-5.
  11. Horlings, H.M., van Laar, R.K., et al.  Gene expression profiling to identify the histogenetic origin of metastatic adenocarcinomas of unknown primary.  Journal of Clinical Oncology (2008) 26(27):4435-41.
  12. Oien KA, Evans TR. Raising the profile of cancer of unknown primary.  J Clin Oncol 2008; 26(27):4373-5.
  13. DNA Microarray Technology, DNA Microarray Fact Sheet.  National Human Genome Research Institute.  National Institutes of Health, U.S. Department of Health and Human Services.  (2009, January 28) Available at http://www.genome.gov (accessed – October, 2009).
  14. Smith, S.  MCH to use genetics to personalize cancer care.  Boston Globe (2009, March 3) Available at http://www.boston.com (accessed – October 2009).
  15. Chustecka, Z.  AACR 2009: Molecular profiling of tumors improves cancer treatment.  Medscape Medical News (2009, April 21) Available at <http://www.medscape.com> (accessed – October 2009).
  16. Monzon FA, Lyons-Weiler M, Buturovic LJ et al.  Multicenter validation of a 1,550-gene expression profile for identification of tumor tissue of origin.  Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2009; 27(15):2503-8.
  17. Target Now.  Molecular diagnostics, Caris Diagnostics, Inc.  Available at http://www.carisdx.com (accessed – January 2012).
  18. Microarray-based Gene Expression Testing for Cancers of Unknown Primary.  Chicago, Illinois: Blue Cross Blue Shield Association Medical Policy Reference Manual (2011 November) Medicine 2.04.54.
  19. NCI.  National Cancer Institute.  U.S. National Institutes of Health.  Physician data query (PDQ).  Carcinoma of unknown primary (PDQ®): treatment [2011 Update].  [Website].  2011.  Available online at: http://www.cancer.gov (accessed January 2012).
  20. Grenert JP, Smith A, Ruan W et al.  Gene expression profiling from formalin-fixed, paraffin-embedded tissue for tumor diagnosis.  Clinica chimica acta; international journal of clinical chemistry 2011; 412(15-16):1462-4.
  21. Pillai R, Deeter R, Rigl CT et al.  Validation and reproducibility of a microarray-based gene expression test for tumor identification in formalin-fixed, paraffin-embedded specimens.  The Journal of molecular diagnostics: JMD 2011; 13(1):48-56.
  22. Ferracin M, Pedriali M, Veronese A et al.  MicroRNA profiling for the identification of cancers with unknown primary tissue-of-origin.  The Journal of pathology 2011; 225(1):43-53.
  23. NCCN.  National Comprehensive Cancer Network.  Clinical Practice Guidelines in Oncology.  Occult Primary Version 2.2012 [Updated].  [Website].  2011. Available online at: http://www.nccn.org (accessed January 2012).
History
February 2012  Policy updated with literature search; references 11, 12 and 14 added. No change to policy statement.
October 2013 Policy formatting and language revised.  Policy statement unchanged.  Title changed from "Microarray-based Gene Expression Testing for Cancers of Unknown Primary" to "Gene Expression Profiling (GEP) Using Microarray Analysis".
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Gene Expression Profiling (GEP) Using Microarray Analysis