The diagnostic application of RNA sequencing in patients with thyroid cancer: an analysis of 851 variants and 133 fusions in 524 genes.

BACKGROUND: Thyroid carcinomas are known to harbor oncogenic driver mutations and advances in sequencing technology now allow the detection of these in fine needle aspiration biopsies (FNA). Recent work by The Cancer Genome Atlas (TCGA) Research Network has expanded the number of genetic alterations detected in papillary thyroid carcinomas (PTC). We sought to investigate the prevalence of these and other genetic alterations in diverse subtypes of thyroid nodules beyond PTC, including a variety of samples with benign histopathology. This is the first clinical evaluation of a large panel of TCGA-reported genomic alterations in thyroid FNAs. RESULTS: In FNAs, genetic alterations were detected in 19/44 malignant samples (43% sensitivity) and in 7/44 histopathology benign samples (84% specificity). Overall, after adding a cohort of tissue samples, 38/76 (50%) of histopathology malignant samples were found to harbor a genetic alteration, while 15/75 (20%) of benign samples were also mutated. The most frequently mutated malignant subtypes were medullary thyroid carcinoma (9/12, 75%) and PTC (14/30, 47%). Additionally, follicular adenoma, a benign subtype of thyroid neoplasm, was also found to harbor mutations (12/29, 41%). Frequently mutated genes in malignant samples included BRAF (20/76, 26%) and RAS (9/76, 12%). Of the TSHR variants detected, (6/7, 86%) were in benign nodules. In a direct comparison of the same FNA also tested by an RNA-based gene expression classifier (GEC), the sensitivity of genetic alterations alone was 42%, compared to the 91% sensitivity achieved by the GEC. The specificity based only on genetic alterations was 84%, compared to 77% specificity with the GEC. CONCLUSIONS: While the genomic landscape of all thyroid neoplasm subtypes will inevitably be elucidated, caution should be used in the early adoption of published mutations as the sole predictor of malignancy in thyroid. The largest set of such mutations known to date detects only a portion of thyroid carcinomas in preoperative FNAs in our cohort and thus is not sufficient to rule out cancer. Due to the finding that variants are also found in benign nodules, testing only GEC suspicious nodules may be helpful in avoiding false positives and altering the extent of treatment when selected mutations are found.

Classification of usual interstitial pneumonia in patients with interstitial lung disease: assessment of a machine learning approach using high-dimensional transcriptional data.

BACKGROUND: Idiopathic pulmonary fibrosis is a progressive fibrotic lung disease that distorts pulmonary architecture, leading to hypoxia, respiratory failure, and death. Diagnosis is difficult because other interstitial lung diseases have similar radiological and histopathological characteristics. A usual interstitial pneumonia pattern is a hallmark of idiopathic pulmonary fibrosis and is essential for its diagnosis. We aimed to develop a molecular test that distinguishes usual interstitial pneumonia from other interstitial lung diseases in surgical lung biopsy samples. The eventual goal of this research is to develop a method to diagnose idiopathic pulmonary fibrosis without the patient having to undergo surgery. METHODS: We collected surgical lung biopsy samples from patients with various interstitial lung diseases at 11 hospitals in North America. Pathology diagnoses were confirmed by an expert panel. We measured RNA expression levels for 33 297 transcripts on microarrays in all samples. A classifier algorithm was trained on one set of samples and tested in a second set. We subjected a subset of samples to next-generation RNA sequencing (RNAseq) generating expression levels on 55 097 transcripts, and assessed a classifier trained on RNAseq data by cross-validation. FINDINGS: We took 125 surgical lung biopsies from 86 patients. 58 samples were identified by the expert panel as usual interstitial pneumonia, 23 as non-specific interstitial pneumonia, 16 as hypersensitivity pneumonitis, four as sarcoidosis, four as respiratory bronchiolitis, two as organising pneumonia, and 18 as subtypes other than usual interstitial pneumonia. The microarray classifier was trained on 77 samples and was assessed in a test set of 48 samples, for which it had a specificity of 92% (95% CI 81-100) and a sensitivity of 82% (64-95). Based on a subset of 36 samples, the RNAseq classifier had a specificity of 95% (84-100) and a sensitivity of 59% (35-82). INTERPRETATION: Our results show that the development of a genomic signature that predicts usual interstitial pneumonia is feasible. These findings are an important first step towards the development of a molecular test that could be applied to bronchoscopy samples, thus avoiding surgery in the diagnosis of idiopathic pulmonary fibrosis. FUNDING: Veracyte.

Machine learning from concept to clinic: reliable detection of BRAF V600E DNA mutations in thyroid nodules using high-dimensional RNA expression data.

The promise of personalized medicine will require rigorously validated molecular diagnostics developed on minimally invasive, clinically relevant samples. Measurement of DNA mutations is increasingly common in clinical settings but only higher-prevalence mutations are cost-effective. Patients with rare variants are at best ignored or, at worst, misdiagnosed. Mutations result in downstream impacts on transcription, offering the possibility of broader diagnosis for patients with rare variants causing similar downstream changes. Use of such signatures in clinical settings is rare as these algorithms are difficult to validate for commercial use. Validation on a test set (against a clinical gold standard) is necessary but not sufficient: accuracy must be maintained amidst interfering substances, across reagent lots and across operators. Here we report the development, clinical validation, and diagnostic accuracy of a pre-operative molecular test (Afirma BRAF) to identify BRAF V600E mutations using mRNA expression in thyroid fine needle aspirate biopsies (FNABs). FNABs were obtained prospectively from 716 nodules and more than 3,000 features measured using microarrays. BRAF V600E labels for training (n=181) and independent test (n=535) sets were established using a sensitive quantitative PCR (qPCR) assay. The resulting 128-gene linear support vector machine was compared to qPCR in the independent test set. Clinical sensitivity and specificity for malignancy were evaluated in a subset of test set samples (n=213) with expert-derived histopathology. We observed high positive- (PPA, 90.4%) and negative (NPA, 99.0%) percent agreement with qPCR on the test set. Clinical sensitivity for malignancy was 43.8% (consistent with published prevalence of BRAF V600E in this neoplasm) and specificity was 100%, identical to qPCR on the same samples. Classification was accurate in up to 60% blood. A double-mutant still resulting in the V600E amino acid change was negative by qPCR but correctly positive by Afirma BRAF. Non-diagnostic rates were lower (7.6%) for Afirma BRAF than for qPCR (24.5%), a further advantage of using RNA in small sample biopsies. Afirma BRAF accurately determined the presence or absence of the BRAF V600E DNA mutation in FNABs, a collection method directly relevant to solid tumor assessment, with performance equal to that of an established, highly sensitive DNA-based assay and with a lower non-diagnostic rate. This is the first such test in thyroid cancer to undergo sufficient analytical and clinical validation for real-world use in a personalized medicine context to frame individual patient risk and inform surgical choice.

Does addition of BRAF V600E mutation testing modify sensitivity or specificity of the Afirma Gene Expression Classifier in cytologically indeterminate thyroid nodules?

OBJECTIVE: The purpose of this study was to determine the frequency of BRAF mutation in cytologically indeterminate thyroid nodules and to investigate whether adding the BRAF test improves diagnostic accuracy of the Afirma Gene Expression Classifier (GEC). DESIGN: BRAF V600E mutational status was determined for DNA extracted from cytologically benign (n = 40), indeterminate (n = 208), and malignant (n = 48) fine-needle aspiration specimens previously categorized by GEC as molecularly Benign or Suspicious. Analytical performance of the BRAF assay was assessed to establish reproducibility and limits of detection. Molecular testing results were correlated with blinded expert histopathological diagnoses. RESULTS: The BRAF assay detected mutations reproducibly to 2.5% mutant allele frequency. The prevalence of BRAF mutations in cytologically benign specimens was 2 of 40 (5.0%, 95% confidence interval [CI], 0-16) and in cytologically malignant specimens was 36 of 48 (75.0%, 95% CI, 60-86). In the cytologically indeterminate category, 10.1% of specimens were BRAF+: 2 of 95 were subcategorized as atypia of undetermined significance or follicular lesion of undetermined significance (2.1%, 95% CI, 0-7); 1 of 70 as follicular neoplasm or suspicious for follicular neoplasm (1.4%, 95% CI, 0-9); and 18 of 43 as suspicious for malignancy (41.9%, 95% CI, 27-58). All BRAF+ specimens were classified as Suspicious by the GEC. CONCLUSIONS: BRAF mutations are uncommon in nodules with atypia of undetermined significance or follicular lesion of undetermined significance or follicular neoplasm or suspicious for follicular neoplasm cytology. Most cytologically indeterminate nodules that proved to be malignant were also BRAF-, and all nodules that were false-negative by GEC were also BRAF-. Similarly, all BRAF+ specimens were also GEC Suspicious. Neither GEC test sensitivity nor specificity was improved by addition of BRAF mutation testing.

Analytical performance verification of a molecular diagnostic for cytology-indeterminate thyroid nodules.

OBJECTIVE: Our objective was to verify the analytical performance of the Afirma gene expression classifier (GEC) in the classification of cytologically indeterminate thyroid nodule fine-needle aspirates (FNAs). DESIGN: Analytical performance studies were designed to characterize the stability of RNA in FNAs during collection and shipment, analytical sensitivity as applied to input RNA concentration and malignant/benign FNA mixtures, analytical specificity (i.e. potentially interfering substances) as tested on blood and genomic DNA, and assay performance studies including intra-nodule, intraassay, inter-assay, and inter-laboratory reproducibility. RESULTS: RNA content within FNAs preserved in FNAProtect is stable for up to 6 d at room temperature with no changes in RNA yield (P = 0.58) or quality (P = 0.56). FNA storage and shipping temperatures were found to have no significant effect on GEC scores (P = 0.55) or calls (100% concordance). Analytical sensitivity studies demonstrated tolerance to variation in RNA input (5-25 ng) and to the dilution of malignant FNA material down to 20%. Analytical specificity studies using malignant samples mixed with blood (up to 83%) and genomic DNA (up to 30%) demonstrated negligible assay interference with respect to false-negative calls, although benign FNA samples mixed with relatively high proportions of blood demonstrated a potential for false-positive calls. The test is reproducible from extraction through GEC result, including variation across operators, runs, reagent lots, and laboratories (sd of 0.158 for scores on a >6 unit scale). CONCLUSIONS: Analytical sensitivity, analytical specificity, robustness, and quality control of the GEC were successfully verified, indicating its suitability for clinical use.

Molecular classification of thyroid nodules using high-dimensionality genomic data.

OBJECTIVE: We set out to develop a molecular test that distinguishes benign and malignant thyroid nodules using fine-needle aspirates (FNA). DESIGN: We used mRNA expression analysis to measure more than 247,186 transcripts in 315 thyroid nodules, comprising multiple subtypes. The data set consisted of 178 retrospective surgical tissues and 137 prospectively collected FNA samples. Two classifiers were trained separately on surgical tissues and FNAs. The performance was evaluated using an independent set of 48 prospective FNA samples, which included 50% with indeterminate cytopathology. RESULTS: Performance of the tissue-trained classifier was markedly lower in FNAs than in tissue. Exploratory analysis pointed to differences in cellular heterogeneity between tissues and FNAs as the likely cause. The classifier trained on FNA samples resulted in increased performance, estimated using both 30-fold cross-validation and an independent test set. On the test set, negative predictive value and specificity were estimated to be 96 and 84%, respectively, suggesting clinical utility in the management of patients considering surgery. Using in silico and in vitro mixing experiments, we demonstrated that even in the presence of 80% dilution with benign background, the classifier can correctly recognize malignancy in the majority of FNA samples. CONCLUSIONS: The FNA-trained classifier was able to classify an independent set of FNAs in which substantial RNA degradation had occurred and in the presence of blood. High tolerance to dilution makes the classifier useful in routine clinical settings where sampling error may be a concern. An ongoing multicenter clinical trial will allow us to validate molecular test performance on a larger independent test set of prospectively collected thyroid FNAs.

Suppression of HIV-1 plasma viral load below detection preserves IL-17 producing T cells in HIV-1 infection.

IL-17 is proinflammatory cytokine secreted by a unique CD4+ T (Th17) cell subset and proposed to play a role in host defense. We hypothesized that Th17 cells are lost in HIV-1 infection. HIV-1-infected children with plasma viremia below 50 copies/ml had IL-17 production, whereas those with detectable viremia had minimal secretion. These results imply viral-mediated destruction or impairment of Th17 cells and argue for complete suppression of viremia for reconstitution of Th17 cells.