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SOUTH SAN FRANCISCO, Calif.and SAO PAULO, Brazil, May 2, 2014 /PRNewswire/ --Veracyte, Inc. (Nasdaq: VCYT) and Fleury Medicine and Health today announced a new partnership that will make Veracyte's Afirma Gene Expression Classifier (GEC) available to patients in Brazil, helping to reduce unnecessary surgeries and potentially lower costs there as part of thyroid cancer diagnosis. Financial terms of the agreement were not disclosed.

Through the agreement, Fleury, which has diagnostics centers across Brazil, will exclusively offer the Afirma GEC when patients' thyroid nodule fine needle aspiration (FNA) results are indeterminate not clearly benign or malignant following cytopathology review. Genzyme, Veracyte's global co-promotion partner, will promote the Afirma GEC to physicians throughout Brazil, who will order the test through Fleury. FNA samples for the Afirma GEC will be sent to Veracyte's CLIA-certified laboratory in South San Francisco, Calif., for analysis.

"We are pleased that physicians and patients in Brazil will now be able to benefit from the Afirma Gene Expression Classifier, which has already helped spare thousands of patients in the United States from unnecessary thyroid surgeries since its commercial launch here in 2011," said Bonnie H. Anderson, president and chief executive officer of Veracyte. "Fleury is one of the largest and most respected diagnostics centers in Brazil and currently offers FNA cytopathology testing to patients across the country, making it an ideal partner to direct indeterminate thyroid nodule cases to the Afirma GEC."

Veracyte's genomic test is used to identify patients whose thyroid nodules are benign following an indeterminate cytopathology result and who can thus potentially avoid unnecessary diagnostic surgery. Based on 2014 Brazilian National Cancer Institute (INCA) estimates of 9,050 newly diagnosed thyroid cancers per year, Veracyte and Fleury estimate that nearly 100,000 thyroid nodule FNAs are performed each year on patients in Brazil, with 15% to 30% of such FNAs assumed to be inconclusive. Traditionally, these patients have been directed to surgery, with most of such thyroid nodules ultimately proving to be benign.

"Traditional techniques for evaluating thyroid nodules are limited, leading many patients to undergo surgery to remove all or part of their thyroids just to get a diagnostic result. These surgeries are invasive, costly and often result in lifelong thyroid hormone replacement therapy for the patient," said Dr. Rosa Paula Mello Biscolla, specialist in endocrinology at Fleury Medicine and Health. "Use of the Afirma GEC will enable physicians to help many patients avoid a surgery they do not need. This will improve patient care and should help reduce healthcare costs."

The Afirma GEC's clinical utility and cost-effectiveness have been demonstrated in multiple, peer-reviewed, published studies and its performance was established in a clinical validation study published in the New England Journal of Medicine in 2012. It is the only molecular test with published validation data demonstrating that it meets the performance criteria established in National Comprehensive Cancer Network (NCCN) guidelines for safely monitoring thyroid nodules in lieu of diagnostic surgery.

About Fleury Medicine and HealthFleury Medicine and Health is a national benchmark indiagnostic medicine and it offers over3,000differenttestsin 37differentmedical specialties.The brand is alsoa precursorin the concept ofintegratedmedical centerthat offersacomplete diagnostic solution,medical adviceanddifferentiated services.Fleuryhas 23patient service centers in So Paulo, the biggest and most important city in Brazil.According to the Brazilian Institute of Public Opinion and Statistics (IBOPE) 2012 Survey, 74% of the physicians in Sao Paulo acknowledge Fleury as the best and most trusted brand for diagnostic medicine.

About VeracyteVeracyte (Nasdaq: VCYT) is pioneering the field of molecular cytology, focusing on genomic solutions that resolve diagnostic ambiguity and enable physicians to make more informed treatment decisions at an early stage in patient care. By improving preoperative diagnostic accuracy, the company aims to help patients avoid unnecessary invasive procedures while reducing healthcare costs. Veracyte's first commercial solution, the Afirma Thyroid FNA Analysis, utilizes the proprietary Gene Expression Classifier (GEC) to resolve ambiguity in thyroid nodule diagnosis. Each year, of the more than 525,000 thyroid nodule FNAs performed in the U.S., approximately 115,000 patients undergo diagnostic thyroid surgery, with 70% to 80% of nodules proving benign and thus the surgery unnecessary. Since the commercial launch of Afirma in January 2011, Veracyte has received over 80,000 FNA samples for evaluation using Afirma and has performed approximately 16,000 GECs to resolve indeterminate cytopathology results, as of December 31, 2013. Backed by multiple, peer-reviewed, published studies and included in leading medical guidelines, Afirma is covered by Medicare and major commercial payers, which collectively represent more than 120 million covered lives. Afirma is marketed and sold through a global co-promotion agreement with Genzyme Corporation, a subsidiary of Sanofi. Veracyte intends to expand its molecular cytology franchise to other clinical areas and is in late biomarker discovery for its first product in pulmonology. For more information, please visit http://www.veracyte.com.

Forward-Looking Statements This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, including statements relating to the company's expectations regarding the adoption of the Afirma GEC by physicians and patients in Brazil, the ability of Fleury to successfully market and sell the Afirma GEC to physicians in Brazil, the ability to obtain any reimbursement necessary to the sale of such Afirma GEC and the potential regulation of the Afirma GEC by Brazilian regulatory bodies. Forward-looking statements involve risks and uncertainties, which could cause actual results to differ materially, and reported results should not be considered as an indication of future performance. These risks and uncertainties include, but are not limited to: our limited operating history and history of losses;our ability to increase usage of and reimbursement for Afirma, and any future products we may develop; our dependence on a few payers for a significant portion of our revenue; the complexity, time and expense associated with billing and collecting from payers for our test; laws and regulations applicable to our business, including potential regulation by the FDA or other regulatory bodies;our dependence on strategic relationships; our ability to develop and commercialize new products and the timing of commercialization; the occurrence and outcome of clinical studies; the applicability of clinical results to actual outcomes; the timing of publication of study results; our inclusion in clinical practice guidelines; our ability to compete; our ability to expand into international markets; our ability to obtain capital when needed; and other risks detailed under the heading "Risk Factors" in our filings with the Securities and Exchange Commission, including our Annual Report on Form 10-K for the year ended December 31, 2013. These forward-looking statements speak only as of the date hereof and Veracyte specifically disclaims any obligation to update these forward-looking statements.

Veracyte, Afirma, the Veracyte logo, and the Afirma logo are trademarks of Veracyte, Inc. This press release also contains trademarks and trade names that are the property of their respective owners.

Excerpt from:
Veracyte and Fleury Announce Partnership to Make the Afirma Gene Expression Classifier Available to Patients in Brazil

PUBLIC RELEASE DATE:

2-May-2014

Contact: Derik Hertel derik.hertel@dartmouth.edu 603-650-1211 The Geisel School of Medicine at Dartmouth

Dartmouth Institute for Quantitative Biomedical Sciences (iQBS) researchers developed a new gene expression analysis approach for identifying cancer genes. The paper entitled, "How to get the most from microarray data: advice from reverse genomics," was published online March 21, 2014 in BMC Genomics. The study results challenge the current paradigm of microarray data analysis and suggest that the new method may improve identification of cancer-associated genes.

Typical microarray-based gene expression analyses compare gene expression in adjacent normal and cancerous tissues. In these analyses, genes with strong statistical differences in expression are identified. However, many genes are aberrantly expressed in tumors as a byproduct of tumorigenesis. These "passenger" genes are differentially expressed between normal and tumor tissues, but they are not "drivers" of tumorigenesis. Therefore, better analytical approaches that enrich the list of candidate genes with authentic cancer-associated "driver" genes are needed.

Lead authors of the study, Ivan P. Gorlov, Ph.D., Associate Professor of Community and Family Medicine and Christopher Amos, Ph.D., Professor of Community and Family Medicine and Director of the Center for Genomic Medicine described a new method to analyze microarray data. The research team demonstrated that ranking genes based on inter-tumor variation in gene expression outperforms traditional analytical approaches. The results were consistent across 4 major cancer types: breast, colorectal, lung, and prostate cancer.

The team used text-mining to identify genes known to be associated with breast, colorectal, lung, and prostate cancers. Then, they estimated enrichment factors by determining how frequently those known cancer-associated genes occurred among the top gene candidates identified by different analysis methods. The enrichment factor described how frequently cancer associated genes were identified compared to the frequency of identification that one could expect by pure chance. Across all four cancer types, the new method of selecting candidate genes based on inter-tumor variation in gene expression outperformed the other methods, including the standard method of comparing mean expression in adjacent normal and tumor tissues. Dr. Gorlov and colleagues also used this approach to identify novel cancer-associated genes.

The authors cite tumor heterogeneity as the most likely reason for the success of their variance-based approach. The method is based on the knowledge that different tumors can be driven by different subsets of cancer genes. By identifying genes with high variation in expression between tumors, the method preferentially identifies genes specifically associated with cancer. This same feature, tumor heterogeneity, may reduce the ability to identify critical gene expression changes when comparing mean gene expression in adjacent tumor and normal tissues, as tumors of the same type may have different sets of genes differentially expressed.

The results of the study challenge the model that comparing mean gene expression in adjacent normal and cancer tissues is the best approach to identifying cancer-associated genes. Indeed, the team identified high variation in adjacent "normal" tissue samples, which are typically used as control samples for comparison in analyses based on mean gene expression. The study suggests that methods based on variance may help get the most from existing and future global gene expression studies.

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Novel analyses improve identification of cancer-associated genes from microarray data