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Analytical performance of the ThyroSeq v3 genomic classifier for cancer diagnosis in thyroid nodules.

ABSTRACT: BACKGROUND:Molecular tests have clinical utility for thyroid nodules with indeterminate fine-needle aspiration (FNA) cytology, although their performance requires further improvement. This study evaluated the analytical performance of the newly created ThyroSeq v3 test. METHODS:ThyroSeq v3 is a DNA- and RNA-based next-generation sequencing assay that analyzes 112 genes for a variety of genetic alterations, including point mutations, insertions/deletions, gene fusions, copy number alterations, and abnormal gene expression, and it uses a genomic classifier (GC) to separate malignant lesions from benign lesions. It was validated in 238 tissue samples and 175 FNA samples with known surgical follow-up. Analytical performance studies were conducted. RESULTS:In the training tissue set of samples, ThyroSeq GC detected more than 100 genetic alterations, including BRAF, RAS, TERT, and DICER1 mutations, NTRK1/3, BRAF, and RET fusions, 22q loss, and gene expression alterations. GC cutoffs were established to distinguish cancer from benign nodules with 93.9% sensitivity, 89.4% specificity, and 92.1% accuracy. This correctly classified most papillary, follicular, and Hurthle cell lesions, medullary thyroid carcinomas, and parathyroid lesions. In the FNA validation set, the GC sensitivity was 98.0%, the specificity was 81.8%, and the accuracy was 90.9%. Analytical accuracy studies demonstrated a minimal required nucleic acid input of 2.5 ng, a 12% minimal acceptable tumor content, and reproducible test results under variable stress conditions. CONCLUSIONS:The ThyroSeq v3 GC analyzes 5 different classes of molecular alterations and provides high accuracy for detecting all common types of thyroid cancer and parathyroid lesions. The analytical sensitivity, specificity, and robustness of the test have been successfully validated and indicate its suitability for clinical use. Cancer 2018;124:1682-90. © 2018 American Cancer Society.

SUBMITTER: Nikiforova MN

PROVIDER: S-EPMC5891361 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Analytical performance of the ThyroSeq v3 genomic classifier for cancer diagnosis in thyroid nodules.

Nikiforova Marina N MN Mercurio Stephanie S Wald Abigail I AI Barbi de Moura Michelle M Callenberg Keith K Santana-Santos Lucas L Gooding William E WE Yip Linwah L Ferris Robert L RL Nikiforov Yuri E YE

Cancer 20180118 8

<h4>Background</h4>Molecular tests have clinical utility for thyroid nodules with indeterminate fine-needle aspiration (FNA) cytology, although their performance requires further improvement. This study evaluated the analytical performance of the newly created ThyroSeq v3 test.<h4>Methods</h4>ThyroSeq v3 is a DNA- and RNA-based next-generation sequencing assay that analyzes 112 genes for a variety of genetic alterations, including point mutations, insertions/deletions, gene fusions, copy number ...[more]

PMID: 29345728

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Project description:ImportanceUse of next-generation sequencing of RNA and machine learning algorithms can classify the risk of malignancy in cytologically indeterminate thyroid nodules to limit unnecessary diagnostic surgery.ObjectiveTo measure the performance of a genomic sequencing classifier for cytologically indeterminate thyroid nodules.Design, setting, and participantsA blinded validation study was conducted on a set of cytologically indeterminate thyroid nodules collected by fine-needle aspiration biopsy between June 2009 and December 2010 from 49 academic and community centers in the United States. All patients underwent surgery without genomic information and were assigned a histopathology diagnosis by an expert panel blinded to all genomic information. There were 210 potentially eligible thyroid biopsy samples with Bethesda III or IV indeterminate cytopathology that constituted a cohort previously used to validate the gene expression classifier. Of these, 191 samples (91.0%) had adequate residual RNA for validation of the genomic sequencing classifier. Algorithm development and independent validation occurred between August 2016 and May 2017.ExposuresThyroid nodule surgical histopathology diagnosis by an expert panel blinded to all genomic data.Main outcomes and measuresThe primary end point was measurement of genomic sequencing classifier sensitivity, specificity, and negative and positive predictive values in biopsies from Bethesda III and IV nodules. The secondary end point was measurement of classifier performance in biopsies from Bethesda II, V, and VI nodules.ResultsOf the 183 included patients, 142 (77.6%) were women, and the mean (range) age was 51.7 (22.0-85.0) years. The genomic sequencing classifier had a sensitivity of 91% (95% CI, 79-98) and a specificity of 68% (95% CI, 60-76). At 24% cancer prevalence, the negative predictive value was 96% (95% CI, 90-99) and the positive predictive value was 47% (95% CI, 36-58).Conclusions and relevanceThe genomic sequencing classifier demonstrates high sensitivity and accuracy for identifying benign nodules. Its 36% increase in specificity compared with the gene expression classifier potentially increases the number of patients with benign nodules who can safely avoid unnecessary diagnostic surgery.

Project description:BackgroundMolecular tests are being used increasingly as an auxiliary diagnostic tool so as to avoid a diagnostic surgery approach for cytologically indeterminate thyroid nodules (ITNs). Previous test versions, Thyroseq v2 and Afirma Gene Expression Classifier (GEC), have proven shortcomings in malignancy detection performance.ObjectiveThis study aimed to evaluate the diagnostic performance of the established Thyroseq v3, Afirma Gene Sequencing Classifier (GSC), and microRNA-based assays versus prior iterations in ITNs, in light of "rule-in" and "rule-out" concepts. It further analyzed the impact of noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) reclassification and Bethesda cytological subtypes on the performance of molecular tests.MethodsPubmed, Scopus, and Web of Science were the databases used for the present research, a process that lasted until September 2020. A random-effects bivariate model was used to estimate the summary sensitivity, specificity, positive (PLR) and negative likelihood ratios (NLR), and area under the curve (AUC) for each panel. The conducted sensitivity analyses addressed different Bethesda categories and NIFTP thresholds.ResultsA total of 40 eligible studies were included with 7,831 ITNs from 7,565 patients. Thyroseq v3 showed the best overall performance (AUC 0.95; 95% confidence interval: 0.93-0.97), followed by Afirma GSC (AUC 0.90; 0.87-0.92) and Thyroseq v2 (AUC 0.88; 0.85-0.90). In terms of "rule-out" abilities Thyroseq v3 (NLR 0.02; 95%CI: 0.0-2.69) surpassed Afirma GEC (NLR 0.18; 95%CI: 0.10-0.33). Thyroseq v2 (PLR 3.5; 95%CI: 2.2-5.5) and Thyroseq v3 (PLR 2.8; 95%CI: 1.2-6.3) achieved superior "rule-in" properties compared to Afirma GSC (PLR 1.9; 95%CI: 1.3-2.8). Evidence for Thyroseq v3 seems to have higher quality, notwithstanding the paucity of studies. Both Afirma GEC and Thyroseq v2 performance have been affected by NIFTP reclassification. ThyGenNEXT/ThyraMIR and RosettaGX show prominent preliminary results.ConclusionThe newly emerged tests, Thyroseq v3 and Afirma GSC, designed for a "rule-in" purpose, have been proved to outperform in abilities to rule out malignancy, thus surpassing previous tests no longer available, Thyroseq 2 and Afirma GEC. However, Thyroseq v2 still ranks as the best rule-in molecular test.Systematic review registrationhttp://www.crd.york.ac.uk/PROSPERO, identifier CRD42020212531.

Project description:ImportanceApproximately 20% of fine-needle aspirations (FNA) of thyroid nodules have indeterminate cytology, most frequently Bethesda category III or IV. Diagnostic surgeries can be avoided for these patients if the nodules are reliably diagnosed as benign without surgery.ObjectiveTo determine the diagnostic accuracy of a multigene classifier (GC) test (ThyroSeq v3) for cytologically indeterminate thyroid nodules.Design, setting, and participantsProspective, blinded cohort study conducted at 10 medical centers, with 782 patients with 1013 nodules enrolled. Eligibility criteria were met in 256 patients with 286 nodules; central pathology review was performed on 274 nodules.InterventionsA total of 286 FNA samples from thyroid nodules underwent molecular analysis using the multigene GC (ThyroSeq v3).Main outcomes and measuresThe primary outcome was diagnostic accuracy of the test for thyroid nodules with Bethesda III and IV cytology. The secondary outcome was prediction of cancer by specific genetic alterations in Bethesda III to V nodules.ResultsOf the 286 cytologically indeterminate nodules, 206 (72%) were benign, 69 (24%) malignant, and 11 (4%) noninvasive follicular thyroid neoplasms with papillary-like nuclei (NIFTP). A total of 257 (90%) nodules (154 Bethesda III, 93 Bethesda IV, and 10 Bethesda V) had informative GC analysis, with 61% classified as negative and 39% as positive. In Bethesda III and IV nodules combined, the test demonstrated a 94% (95% CI, 86%-98%) sensitivity and 82% (95% CI, 75%-87%) specificity. With a cancer/NIFTP prevalence of 28%, the negative predictive value (NPV) was 97% (95% CI, 93%-99%) and the positive predictive value (PPV) was 66% (95% CI, 56%-75%). The observed 3% false-negative rate was similar to that of benign cytology, and the missed cancers were all low-risk tumors. Among nodules testing positive, specific groups of genetic alterations had cancer probabilities varying from 59% to 100%.Conclusions and relevanceIn this prospective, blinded, multicenter study, the multigene GC test demonstrated a high sensitivity/NPV and reasonably high specificity/PPV, which may obviate diagnostic surgery in up to 61% of patients with Bethesda III to IV indeterminate nodules, and up to 82% of all benign nodules with indeterminate cytology. Information on specific genetic alterations obtained from FNA may help inform individualized treatment of patients with a positive test result.

Project description:BackgroundFine-needle aspiration (FNA) cytology is a common approach to evaluating thyroid nodules, although 20% to 30% of FNAs have indeterminate cytology, which hampers the appropriate management of these patients. Follicular (or oncocytic) neoplasm/suspicious for a follicular (or oncocytic) neoplasm (FN/SFN) is a common indeterminate diagnosis with a cancer risk of approximately 15% to 30%. In this study, the authors tested whether the most complete next-generation sequencing (NGS) panel of genetic markers could significantly improve cancer diagnosis in these nodules.MethodsThe evaluation of 143 consecutive FNA samples with a cytologic diagnosis of FN/SFN from patients with known surgical outcomes included 91 retrospective samples and 52 prospective samples. Analyses were performed on a proprietary sequencer using the targeted ThyroSeq v2 NGS panel, which simultaneously tests for point mutations in 13 genes and for 42 types of gene fusions that occur in thyroid cancer. The expression of 8 genes was used to assess the cellular composition of FNA samples.ResultsIn the entire cohort, histologic analysis revealed 104 benign nodules and 39 malignant nodules. The most common point mutations involved the neuroblastoma RAS viral oncogene homolog (NRAS), followed by the Kirsten rat sarcoma viral oncogene homolog (KRAS), the telomerase reverse transcriptase (TERT) gene, and the thyroid-stimulating hormone receptor (TSHR) gene. The identified fusions involved the thyroid adenoma associated (THADA) gene; the peroxisome proliferator-activated receptor γ (PPARG) gene; and the neurotrophic tyrosine kinase, receptor, type 3 (NTRK3) gene. Performance characteristics were similar in the retrospective and prospective groups. Among all FN/SFN nodules, preoperative ThyroSeq v2 performed with 90% sensitivity (95% confidence interval [CI], 80%-99%), 93% specificity (95% CI, 88%-98%), a positive predictive value of 83% (95% CI, 72%-95%), a negative predictive value of 96% (95% CI, 92%-100%), and 92% accuracy (95% CI, 88%-97%).ConclusionsThe current results indicate that comprehensive genotyping of thyroid nodules using a broad NGS panel provides a highly accurate diagnosis for nodules with FN/SFN cytology and should facilitate the optimal management of these patients.

Project description:ImportanceDefinitive diagnosis of a thyroid nodule in a child is obtained through diagnostic surgery. This is problematic because pediatric thyroid surgery is associated with higher rates of complications. In adults, preoperative molecular testing improves the management of thyroid nodules, but this has not been validated in children.ObjectiveTo determine whether the molecular landscape of pediatric thyroid nodules is amenable to detection by a multigene genomic classifier (GC) test (ThyroSeq v3; Sonic Healthcare USA).Design, setting, and participantsThis was a retrospective consecutive case series and GC testing of fine-needle aspiration (FNA) and formalin-fixed paraffin-embedded (FFPE) tissues from sequential pediatric thyroidectomies performed between January 2003 and December 2019 at a single tertiary academic medical center. The study included 95 patients (median [range] age, 16.3 [4.8 to 21.1] years; 75 [79%] female) who underwent surgery for a thyroid nodule.InterventionsA total of 118 thyroid nodule samples (95 FFPE, 23 companion FNAs) yielded informative next-generation sequencing data and multigene GC.Main outcomes and measuresThe primary outcome was the determination of the pediatric thyroid molecular landscape. The secondary outcome was the diagnostic accuracy of the GC test for pediatric thyroid nodules.ResultsOf the 95 patients, 75 (79%) were female, and the median (IQR) age was 16.3 (14.0-17.3) years. Next-generation sequencing confirmed the unique molecular landscape of malignant pediatric thyroid nodules (compared with adults), which is dominated by gene fusions (most commonly RET and NTRK), rare BRAF/RAS alterations, and no TP53 or TERT promoter pathogenic variants. Several poorly differentiated thyroid cancers harbored DICER1 variants. Benign nodules appeared to be almost exclusively associated with TSHR and DICER1 alterations. The test demonstrated a 96% sensitivity (95% CI, 87%-99%) and 78% specificity (95% CI, 64%-88%). The negative predictive value was 95% (95% CI, 88%-98%) and the positive predictive value was 83% (95% CI, 74-89%). The concordance of GC between 23 pairs of matched FFPE and FNA tissues was 96%.Conclusions and relevanceThe study results of this retrospective consecutive case series suggest that the molecular landscape of pediatric nodules is unique but remains amenable to molecular classification. The multigene GC test, with high sensitivity and reasonably high specificity, represents a potential addition to the diagnostic workup of children with thyroid nodules and may decrease the use of diagnostic surgery.

Project description:BackgroundBronchoscopy is a common procedure used for evaluation of suspicious lung nodules, but the low diagnostic sensitivity of bronchoscopy often results in inconclusive results and delays in treatment. Percepta Genomic Sequencing Classifier (GSC) was developed to assist with patient management in cases where bronchoscopy is inconclusive. Studies have shown that exposure to tobacco smoke alters gene expression in airway epithelial cells in a way that indicates an increased risk of developing lung cancer. Percepta GSC leverages this idea of a molecular "field of injury" from smoking and was developed using RNA sequencing data generated from lung bronchial brushings of the upper airway. A Percepta GSC score is calculated from an ensemble of machine learning algorithms utilizing clinical and genomic features and is used to refine a patient's risk stratification.MethodsThe objective of the analysis described and reported here is to validate the analytical performance of Percepta GSC. Analytical performance studies characterized the sensitivity of Percepta GSC test results to input RNA quantity, the potentially interfering agents of blood and genomic DNA, and the reproducibility of test results within and between processing runs and between laboratories.ResultsVarying the amount of input RNA into the assay across a nominal range had no significant impact on Percepta GSC classifier results. Bronchial brushing RNA contaminated with up to 10% genomic DNA by nucleic acid mass also showed no significant difference on classifier results. The addition of blood RNA, a potential contaminant in the bronchial brushing sample, caused no change to classifier results at up to 11% contamination by RNA proportion. Percepta GSC scores were reproducible between runs, within runs, and between laboratories, varying within less than 4% of the total score range (standard deviation of 0.169 for scores on 4.57 scale).ConclusionsThe analytical sensitivity, analytical specificity, and reproducibility of Percepta GSC laboratory results were successfully demonstrated under conditions of expected day to day variation in testing. Percepta GSC test results are analytically robust and suitable for routine clinical use.

Dataset Information

Analytical performance of the ThyroSeq v3 genomic classifier for cancer diagnosis in thyroid nodules.

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Analytical performance of the ThyroSeq v3 genomic classifier for cancer diagnosis in thyroid nodules.

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