Gene Expression Classifier Research Articles

Genomic classifier (ColoPrint) to predict outcome and chemotherapy benefit in stage II and III colon cancer patients.

3612 Background: Although benefit of chemotherapy in stage II and III colorectal cancer patients is significant, many patients might not need adjuvant chemotherapy because they have a good prognosis even without additional treatment. ColoPrint is a gene expression classifier that distinguish patients with low or high risk of disease relapse. It was developed using whole genome expression data and validated in independent validation studies (JCO 2011, Ann Surg 2013). Methods: In this study, ColoPrint was validated in stage II (n=96) and III patients (n=95) treated at the MD Anderson Cancer Center. Frozen tissue specimen, clinical parameters and follow-up data (median follow-up 64 months) were available. Stage II patients from this study were pooled with patients from previous studies (n=416) and ColoPrint performance was compared to clinical risk factors described in the NCCN Guidelines 2013. Results: In the MDACC patient cohort, ColoPrint classified 56% of stage II and III patients as being at Low Risk. The 3-year Relapse-Free-Survival (RFS) was 90.5% for Low Risk and 78.1% for High Risk patients with a HR of 2.42 (p=0.025). In uni-and multivariate analysis, ColoPrint and stage were the only significant factors to predict outcome. Low Risk ColoPrint patients had a good outcome independent of stage or chemotherapy treatment (91% 3-year RFS for treated patients, 90% for untreated patients) while ColoPrint High Risk patients treated with adjuvant chemotherapy had 3-year RFS of 84%, compared to 70% 3-year RFS in untreated patients (p=0.037). In the pooled stage II dataset, ColoPrint identified 63% of patients as Low Risk with a 3-year RFS of 93% while High Risk patients had a 3-year RFS of 82.3% with a HR of 2.7 (p=0.001). In the univariate analysis, no clinical factor reached statistical significance. Using clinical high risk factors as described in the NCCN guidelines as classification, 56% of patients were classified as low risk with a 3-year RFS of 90.3% while high risk patients had a 3-year RFS of 87.7% with a HR of 0.6 (p=0.63). Conclusions: ColoPrint significantly improves prognostic accuracy, thereby facilitating the identification of patients at higher risk who might be considered for additional treatment.

Prognostic and predictive effects of a gene expression signature for NRF2 pathway activation in lung squamous cell carcinoma (SqCC).

7517 Background: Genomic profiling of SqCC in TCGA identified somatic alterations that activate the NRF2 transcriptional program – a master regulator of the oxidative stress response – in ~35% of tumors (NFE2L2 mutations/amplifications, KEAP1 or CUL3 mutations/deletions). This pathway has been implicated in resistance to chemotherapy. To evaluate the clinical significance of this molecular subset, we developed a gene expression classifier and tested this signature as a predictor of adjuvant chemotherapy benefit with cisplatin/vinorelbine (cis/vin) in a subset of SqCC patients with microarray data from the NCIC JBR.10 Phase III clinical trial. Methods: Logistic regression (LR) and SAM analysis were independently applied to 104 TCGA SqCC cases that had both microarray gene expression and mutation data to identify genes associated with NRF2 pathway mutational status. Overlapping genes were used to define the signature, which was then tested in 3 independent SqCC datasets (62 JBR.10; 54 UHN; 129 UM) to evaluate the prognostic and predictive values of putative NRF2 pathway activation. Results: 29 genes comprising the signature were identified by overlap between LR (291 genes) and SAM (45 genes). The signature consistently separated SqCC into 2 groups in all datasets, corresponding to putatively activated and wild type (WT) NRF2 pathway tumors. No prognostic effect of the activated signature was observed in independent datasets (UHN HR 0.86, 95%CI 0.28 – 2.67; UM HR 1.43, 95%CI 0.82 – 2.48). Similarly, in JBR10, no prognostic effect was observed in the observation arm (n=24, HR 0.66, 95%CI 0.13 – 3.29). A trend toward improved survival with adjuvant chemotherapy was observed in patients with the WT signature (HR 0.34, 95%CI 0.08 – 1.78, p=0.13), but not in patients with the activated signature (HR 1.16, 95%CI 0.19 – 6.97, p=0.87; interaction p=0.18). Conclusions: A gene expression signature based on mutational activation of the NRF2 pathway may be predictive of benefit from adjuvant cis/vin in SqCC. Patients with NRF2 pathway activating somatic alterations may have reduced benefit from this therapy. Validation of this potentially "actionable" finding in additional datasets is necessary.

Indeterminate thyroid nodules—added testing, added value?

Combination of the gene-expression classifier (GEC), with its high negative predictive value, and the BRAF mutation test, with its high specificity, might have a synergistic effect in the diagnosis of thyroid nodules with indeterminate cytology. However, Kloos et al. demonstrate that the BRAF test is of no additional benefit in nodules categorized as 'benign' by GEC.

Detection ofCEBPADouble Mutants in Acute Myeloid Leukemia Using a Custom Gene Expression Array

Double (bi-allelic) mutations in the gene encoding the CCAAT/enhancer-binding protein-alpha (CEBPA) transcription factor have a favorable prognostic impact in acute myeloid leukemia (AML). Double mutations in CEBPA can be detected using various techniques, but it is a notoriously difficult gene to sequence due to its high GC-content. Here we developed a two-step gene expression classifier for accurate and standardized detection of CEBPA double mutations. The key feature of the two-step classifier is that it explicitly removes cases with low CEBPA expression, thereby excluding CEBPA hypermethylated cases that have similar gene expression profiles as a CEBPA double mutant, which would result in false-positive predictions. In the second step, we have developed a 55 gene signature to identity the true CEBPA double-mutation cases. This two-step classifier was tested on a cohort of 505 unselected AML cases, including 26 CEBPA double mutants, 12 CEBPA single mutants, and seven CEBPA promoter hypermethylated cases, on which its performance was estimated by a double-loop cross-validation protocol. The two-step classifier achieves a sensitivity of 96.2% (95% confidence interval [CI] 81.1 to 99.3) and specificity of 100.0% (95% CI 99.2 to 100.0). There are no false-positive detections. This two-step CEBPA double-mutation classifier has been incorporated on a microarray platform that can simultaneously detect other relevant molecular biomarkers, which allows for a standardized comprehensive diagnostic assay. In conclusion, gene expression profiling provides a reliable method for CEBPA double-mutation detection in patients with AML for clinical use.

Does Addition ofBRAFV600E Mutation Testing Modify Sensitivity or Specificity of the Afirma Gene Expression Classifier in Cytologically Indeterminate Thyroid Nodules?

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). 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. 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. 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.

A 36-gene Signature Predicts Clinical Progression in a Subgroup of ERG-positive Prostate Cancers

BackgroundThe molecular basis of the clinical heterogeneity of prostate cancer (PCa) is not well understood. ObjectiveThe purpose of our study was to identify and characterize genes in a clinically relevant gene expression signature in a subgroup of primary PCa positive for transmembrane protease, serine 2 (TMPRSS2)–v-ets erythroblastosis virus E26 oncogene homolog (avian) (ERG). Design, setting, and participantsWe studied gene expression profiles by unsupervised hierarchical clustering in 48 primary PCas from patients with a long clinical follow-up. Results were correlated with clinical outcome and validated in an independent patient cohort. Selected genes from a defined classifier were tested in vitro for biologic properties. InterventionInitial treatment of primary tumors was radical prostatectomy. Outcome measurements and statistical analysisAssociations between clinical and histopathologic variables were evaluated by the Pearson χ2 test, Mann-Whitney U test, or Kruskal-Wallis test, where appropriate. The log-rank test or Breslow method was used for statistical analysis of Kaplan-Meier survival curves. Results and limitationsMost tumors that overexpressed ERG clustered separately from other primary PCas. No differences in any clinical end points between ERG-positive and ERG-negative cancers were detected. Importantly, within the ERG-positive samples, two subgroups were identified, which differed significantly in prostate-specific antigen recurrence-free survival, and cancer-specific and overall survival. From our findings, we defined a gene expression classifier of 36 genes. In a second, completely independent tumor set, the classifier also distinguished ERG-positive subgroups with different clinical outcome. In both patient cohorts, the classifier was not predictive in ERG-negative tumors. Biologic processes regulated by genes in the classifier included cell adhesion and bone remodeling. Tumor growth factor-β signaling was indicated as the main differing signaling pathway between the two ERG subgroups. In vitro biologic assays of two selected genes from the classifier (inhibin, beta A [INHBA] and cadherin 11, type 2, OB-cadherin (osteoblast) [CDH11]) supported a functional role in PCa progression. Possible multifocality and limited number of PCa samples can be limitations of the study. ConclusionsThe classifier identified can contribute to prediction of tumor progression in ERG-positive primary prostate tumors and might be instrumental in therapy decisions.

Molecular markers in the diagnosis of thyroid nodules

An indeterminate thyroid nodule cytology result occurs about every sixth fine-needle aspiration. These indeterminate nodules harbor a 24% risk of malignancy (ROM); too high to ignore, but driving surgery where most nodules are benign. Molecular diagnostics have emerged to ideally avoid surgery when appropriate, and to trigger the correct therapeutic surgery when indicated, as opposed to an incomplete diagnostic surgery. No current molecular test offers both high sensitivity and high specificity. A molecular diagnostic test with high sensitivity (e.g. Afirma Gene Expression Classifier sensitivity 90%) offers a high Negative Predictive Value when the ROM is relatively low, such as < 30%. Only such tests can "rule-out" cancer. In this setting, a molecularly benign result suggests the same ROM as that of operated cytologically benign nodules (~6%). Thus, clinical observation can replace diagnostic surgery; increasing quality of life and decreasing medical costs. However, its low specificity cannot "rule-in" cancer as a suspicious result has a Positive Predictive Value (PPV) of ~40%, perhaps too low to routinely reflex to definitive cancer surgery. Conversely, high specificity tests (BRAF, RAS, PPAR/PAX-8, RET/PTC, PTEN) offer high PPV results, and only these tests can "rule-in" cancer. Here a positive molecular result warrants definitive therapeutic surgery. However, their low sensitivity cannot "rule-out" cancer and a negative molecular result cannot dissuade diagnostic surgery; limiting their cost-effectiveness. Whether or not there is a useful and cost-effective role to sequentially combine these approaches, or to modify existing approaches, is under investigation.

Genomic classifiers (ColoPrint/MSI-Print) predict outcome and chemotherapy benefit in stage II and III colon cancer patients.

378 Background: Although the benefit of chemotherapy in stage II and III colon cancer patients is significant, many patients might not need adjuvant chemotherapy because they have a good prognosis even without additional treatment. ColoPrint is a gene expression classifier that distinguish patients with low or high risk of disease relapse. It was developed using whole genome expression data and has been validated in public datasets, independent European patient cohorts and technical studies (Salazar 2011 JCO, Maak 2012 Ann Surg). Methods: In this study, the commercial ColoPrint test was validated in stage II (n=96) and III patients (n=95) treated at the MD Anderson Cancer Center from 2003 to 2009. Frozen tissue specimen, clinical parameters, MSI-status and follow-up data (median follow-up 64 months) were available. The 64-gene MSI-signature developed to identify patients with deficient mismatch repair system (Tian 2012 J Path) was evaluated for its accuracy to identify MSI patients and also for prognosis. Results: In this cohort, ColoPrint classified 56% of stage II and III patients as being at low risk. The 3-year Relapse-Free-Survival (RFS) was 90.6% for Low Risk and 78.4% for High Risk patients with a HR of 2.33 (p=0.025). In uni-and multivariate analysis ColoPrint and stage were the only significant factors to predict outcome. The MSI-signature classified 47 patients (24.6%) as MSI-H and most MSI-H patients were ColoPrint low risk (81%). Patients who were ColoPrint low risk and MSI-H by signature had the best outcome with a 3-year RFS of 95% while patients with ColoPrint high risk had a worse outcome independently of the MSI-status. Low risk ColoPrint patients had a good outcome independent of stage or chemotherapy treatment (90.1% 3-year RFS for treated patients, 91.4% for untreated patients) while ColoPrint high risk patients treated with adjuvant chemotherapy had 3-year RFS of 84%, compared to 70.1% 3-year RFS in untreated patients (p=0.026). Conclusions: The combination of ColoPrint and MSI-Print improves the prognostic accuracy in stage II and stage III patients and may help the identification of patients at higher risk who are more likely to benefit from additional treatment

Can a gene‐expression classifier with high negative predictive value solve the indeterminate thyroid fine‐needle aspiration dilemma?

The recent study by Alexander et al validates the effectiveness of the Afirma test, and suggests a potential ancillary role for this unique test when appropriately applied in the evaluation of thyroid nodules classified by fine-needle aspiration as indeterminate.

A blood gene expression marker of early Alzheimer's disease.

A marker of Alzheimer's disease (AD) that can accurately diagnose disease at the earliest stage would significantly support efforts to develop treatments for early intervention. We have sought to determine the sensitivity and specificity of peripheral blood gene expression as a diagnostic marker of AD using data generated on HT-12v3 BeadChips. We first developed an AD diagnostic classifier in a training cohort of 78 AD and 78 control blood samples and then tested its performance in a validation group of 26 AD and 26 control and 118 mild cognitive impairment (MCI) subjects who were likely to have an AD-endpoint. A 48 gene classifier achieved an accuracy of 75% in the AD and control validation group. Comparisons were made with a classifier developed using structural MRI measures, where both measures were available in the same individuals. In AD and control subjects, the gene expression classifier achieved an accuracy of 70% compared to 85% using MRI. Bootstrapping validation produced expression and MRI classifiers with mean accuracies of 76% and 82%, respectively, demonstrating better concordance between these two classifiers than achieved in a single validation population. We conclude there is potential for blood expression to be a marker for AD. The classifier also predicts a large number of people with MCI, who are likely to develop AD, are more AD-like than normal with 76% of subjects classified as AD rather than control. Many of these people do not have overt brain atrophy, which is known to emerge around the time of AD diagnosis, suggesting the expression classifier may detect AD earlier in the prodromal phase. However, we accept these results could also represent a marker of diseases sharing common etiology.

Gene Expression-Based Classifiers Identify Staphylococcus aureus Infection in Mice and Humans

Staphylococcus aureus causes a spectrum of human infection. Diagnostic delays and uncertainty lead to treatment delays and inappropriate antibiotic use. A growing literature suggests the host’s inflammatory response to the pathogen represents a potential tool to improve upon current diagnostics. The hypothesis of this study is that the host responds differently to S. aureus than to E. coli infection in a quantifiable way, providing a new diagnostic avenue. This study uses Bayesian sparse factor modeling and penalized binary regression to define peripheral blood gene-expression classifiers of murine and human S. aureus infection. The murine-derived classifier distinguished S. aureus infection from healthy controls and Escherichia coli-infected mice across a range of conditions (mouse and bacterial strain, time post infection) and was validated in outbred mice (AUC>0.97). A S. aureus classifier derived from a cohort of 94 human subjects distinguished S. aureus blood stream infection (BSI) from healthy subjects (AUC 0.99) and E. coli BSI (AUC 0.84). Murine and human responses to S. aureus infection share common biological pathways, allowing the murine model to classify S. aureus BSI in humans (AUC 0.84). Both murine and human S. aureus classifiers were validated in an independent human cohort (AUC 0.95 and 0.92, respectively). The approach described here lends insight into the conserved and disparate pathways utilized by mice and humans in response to these infections. Furthermore, this study advances our understanding of S. aureus infection; the host response to it; and identifies new diagnostic and therapeutic avenues.

Use of the Afirma® Gene Expression Classifier for Preoperative Identification of Benign Thyroid Nodules with Indeterminate Fine Needle Aspiration Cytopathology

Ruling out malignancy in thyroid nodules historically depended on thyroid resection and histopathological evaluation until fine needle aspiration (FNA) biopsy was introduced into the United States in the 1970's. Thyroid FNA biopsy identified a majority of thyroid nodules as benign, obviating the need for surgery in over half of the patients. However, 15%-30% of thyroid FNAs have indeterminate cytology that still requires operation, even though most of these operated nodules prove to be benign post-operatively. In order to predict which cytologically indeterminate thyroid nodules are benign and to potentially avoid surgery on these nodules, a recently described commercially available Gene Expression Classifier (GEC) test (Afirma®, Veracyte, Inc., South San Francisco, CA) has been developed that can be run on the FNA sample. This paper reviews the published literature and technology assessments/guidelines by independent parties and professional groups regarding the clinical utility as well as the analytic and clinical validity of the Afirma GEC.

Abstract P2-10-20: A tumor DNA complexity index is an independent predictor of survival in a dataset of 1950 breast cancers; a METABRIC group study.

Abstract Background: Cancer genomes undergo substantial alterations during carcinogenesis. Patterns of such rearrangements differ with respect to cancer subtypes and may affect crucial parts of the genome. DNA based markers would make clinical implementation more feasible as markers based on RNA expression are challenging due to the intrinsic problem of RNA stability and volatility in expression patterns. Complex genomic rearrangements in breast cancer genomes, quantified by the complex arm-wise aberration index (CAAI), have previously been shown to be of prognostic value. However this finding has not been validated in independent large-scale breast cancer cohorts or compared with other molecular predictors. Methods: A total of 1950 breast carcinomas from the METABRIC cohort with log term follow up were included in this study. Microarray based copy number and expression data from fresh frozen primary tumors were available. Cases were classified as CAAI positive if at least one complex event was present in the tumor genome. The clinical end points were breast cancer specific survival (BCSS) and overall survival (OS). Results: A total of 33 % of breast cancer cases were CAAI positive with a Cox proportional hazard ratio (HR) of 1.78 (95% CI, 1.49–2.12) for BCSS. Using multivariate Cox regression the adjusted HR for BCSS of 1.42 (95% CI, 1.12–1.80) and 1.44 (95% CI, 1.02–2.03) in estrogen receptor positive (ER+) and estrogen receptor negative breast cancers, respectively. Gene expression classifiers based on OncotypeDX and MammaPrint were not independently prognostic in the ER− subset. Significant difference in survival was both seen in patients that received systemic treatment, and in patients that did not. Conclusions: DNA based prognostic profiling is a robust method for both fresh frozen and FFPE tumor material. This study shows that complex genomic alterations of tumor DNA, measured as CAAI, is an independent predictor of survival in breast cancer, in both ER+ and ER− disease in a large scale breast cancer cohort with long term follow up. The effect seems unrelated to systemic endocrine treatment or chemotherapy. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P2-10-20.

SOCS1 Mutation Subtypes Predict Divergent Outcomes in Diffuse Large B-Cell Lymphoma (DLBCL) Patients

Suppressor of cytokine signaling 1 (SOCS1) is frequently mutated in primary mediastinal and diffuse large B-cell lymphomas (DLBCL). Currently, the prognostic relevance of these mutations in DLBCL is unknown. To evaluate the value of the SOCS1 mutation status as a prognostic biomarker in DLBCL patients, we performed full-length SOCS1 sequencing in tumors of 154 comprehensively characterized DLBCL patients. We identified 90 SOCS1 mutations in 16% of lymphomas. With respect to molecular consequences of mutations, we defined two distinct subtypes: those with truncating (major) and those with non-truncating mutations (minor), respectively. The SOCS1 mutated subgroup or the minor/major subtypes cannot be predicted on clinical grounds; however, assignment of four established gene-expression profile-based classifiers revealed significant associations of SOCS1 major cases with germinal center and specific pathway activation pattern signatures. Above all, SOCS1 major cases have an excellent overall survival, even better than the GCB-like subgroup. SOCS1 minor cases had a dismal survival, even worse than the ABC gene signature group. The SOCS1 mutation subsets retained prognostic significance in uni- and multivariate analyses. Together our data indicate that assessment of the SOCS1 mutation status is a single gene prognostic biomarker in DLBCL.

Microarray-based gene expression profiling in patients with cryopyrin-associated periodic syndromes defines a disease-related signature and IL-1-responsive transcripts

ObjectiveTo analyse gene expression patterns and to define a specific gene expression signature in patients with the severe end of the spectrum of cryopyrin-associated periodic syndromes (CAPS). The molecular consequences...

Analytical Performance Verification of a Molecular Diagnostic for Cytology-Indeterminate Thyroid Nodules

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). 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. 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). Analytical sensitivity, analytical specificity, robustness, and quality control of the GEC were successfully verified, indicating its suitability for clinical use.

522PD - Development and Validation of a Robust Molecular Diagnostic Test (COLOPRINT) for Predicting Outcome in Stage II Colon Cancer Patients

ABSTRACT Background Only between 25 to 35% of stage II and IIIA colon cancer patients will experience a relapse of their disease and may benefit from adjuvant chemotherapy. ColoPrint is a gene expression classifier that can predict disease relapse in patients with early-stage colorectal cancer and helps to identify patients with higher risk of relapse. Methods ColoPrint was developed using whole genome expression data and was validated in public datasets and an independent patient cohort of 206 patients (Salazar et al., JCO 2011). The signature was translated to a customized 8-pack microarray. Positive and negative hybridization control genes monitor the quality of hybridization and a colon specific normalization gene set (n = 461) guarantee reliability of results. Reproducibility and precision studies with 20 times 6 samples were performed by multiple operators on multiple days. Additional independent patient cohorts were validated on the customized arrays. Uni- and multi-variate analyses were performed on the pooled stage II patient set (n = 320), the subset of T3/ MSS patients (n = 227) and stage IIIA (n = 16). Results The prognostic classifier was evaluated in reproducibility and stability assays and stringent quality controls were established following the successful lead of the FDA-cleared MammaPrint assay. Results of all tests met the pre-set criteria. In the analysis of all stage II and IIIA patients, ColoPrint classified two-third of patients as being at low risk. The 3-year Relapse-Free-Survial (RFS) RFS was 92% and 77% for low and high risk patients respectively with a HR of 2.9 (p = 0.001). Clinical and pathological risk parameters from the NCCN guidelines can be combined with ColoPrint for even more personalized risk assessment. ColoPrint is also able to distinguish risk groups in the subgroup of patients with T3 and MSS phenotype (HR= 2.7, p = 0.01) and IIIA (HR= 3.6, p = 0.08). Conclusions ColoPrint was technically and clinically validated and is now available for diagnostic use. ColoPrint significantly improves prognostic accuracy, thereby facilitating the identification of patients at higher risk who might be considered for additional treatment. Disclosure I. Simon: Employee of Agendia (maker of ColoPrint). J. van der Akker: Employee of Agendia (maker of ColoPrint). Y. Li: Employee of Agendia (maker of ColoPrint). B. Chan: Employee of Agendia (maker of ColoPrint). A. Glas: Employee of Agendia (maker of ColoPrint). All other authors have declared no conflicts of interest.

Preoperative Diagnosis of Benign Thyroid Nodules with Indeterminate Cytology

BackgroundApproximately 15 to 30% of thyroid nodules evaluated by means of fine-needle aspiration are not clearly benign or malignant. Patients with cytologically indeterminate nodules are often referred for diagnostic surgery, though most of these nodules prove to be benign. A novel diagnostic test that measures the expression of 167 genes has shown promise in improving preoperative risk assessment.MethodsWe performed a 19-month, prospective, multicenter validation study involving 49 clinical sites, 3789 patients, and 4812 fine-needle aspirates from thyroid nodules 1 cm or larger that required evaluation. We obtained 577 cytologically indeterminate aspirates, 413 of which had corresponding histopathological specimens from excised lesions. Results of a central, blinded histopathological review served as the reference standard. After inclusion criteria were met, a gene-expression classifier was used to test 265 indeterminate nodules in this analysis, and its performance was assessed.ResultsOf the 265 indeterminate nodules, 85 were malignant. The gene-expression classifier correctly identified 78 of the 85 nodules as suspicious (92% sensitivity; 95% confidence interval [CI], 84 to 97), with a specificity of 52% (95% CI, 44 to 59). The negative predictive values for “atypia (or follicular lesion) of undetermined clinical significance,” “follicular neoplasm or lesion suspicious for follicular neoplasm,” or “suspicious cytologic findings” were 95%, 94%, and 85%, respectively. Analysis of 7 aspirates with false negative results revealed that 6 had a paucity of thyroid follicular cells, suggesting insufficient sampling of the nodule.ConclusionsThese data suggest consideration of a more conservative approach for most patients with thyroid nodules that are cytologically indeterminate on fine-needle aspiration and benign according to gene-expression classifier results. (Funded by Veracyte.)

The Impact of Benign Gene Expression Classifier Test Results on the Endocrinologist–Patient Decision to Operate on Patients with Thyroid Nodules with Indeterminate Fine-Needle Aspiration Cytopathology

Seventy-five percent of thyroid nodules with indeterminate fine-needle aspiration (FNA) cytology are found to be benign postoperatively. A novel genomic test, the Afirma gene expression classifier (AGEC), has been available for clinical use in the United States, since late 2010. In 2010, two modest-sized validation studies showed that the AGEC could identify a benign gene expression signature in indeterminate cytology thyroid FNA samples with a negative predictive value >95%. The objective of this study was to evaluate how the AGEC impacted the joint decision of the endocrinologist and patient to operate when FNA cytology was indeterminate, but the AGEC reading of the nodule was benign. In this cross-sectional cohort study, data were contributed retrospectively by 51 endocrinologists at 21 practice sites that had previously obtained ≥3 benign AGEC readings in ≥1 cm nodules with indeterminate FNA cytology readings. Information regarding demographic data, nodule size and location, decision to operate, surgery type (hemithyroidectomy [HT] or total thyroidectomy [TT]), and reason for recommending surgery was retrospectively collected. Compared to a 74% previous historical rate of surgery for cytologically indeterminate nodules, the operative rate fell to 7.6% during the period that AGEC were obtained in the clinical practices, a highly significant reduction in the decision to operate (p<0.001). The rate of surgery on cytologically indeterminate nodules that were benign by the AGEC reading did not differ from the historically reported rate of operation on cytologically benign nodules (p=0.41). The four primary reasons reported by the physicians for operating on nodules with a benign AGEC reading, in descending order: large nodule size (46.4%), symptomatic nodules (25.0%), rapidly growing nodules (10.7%), or a second suspicious or malignant nodule in the same patient (10.7%). These reasons are concordant with those typically given for operation on cytologically benign nodules. In a substantial group of medical practices, obtaining an AGEC test in patients with cytologically indeterminate nodules was associated with a striking reduction in the rate of diagnostic thyroidectomy. Approximately, one surgery was avoided for every two AGEC tests run on thyroid FNAs with indeterminate cytology.

The Impact of Benign Gene Expression Classifier Test Results on the Endocrinologist-Patient Decision to Operate on Patients with Thyroid Nodules with Indeterminate FNA Cytopathology

The Impact of Benign Gene Expression Classifier Test Results on the Endocrinologist-Patient Decision to Operate on Patients with Thyroid Nodules with Indeterminate FNA Cytopathology