Gene Expression Classifier Research Articles

Molecular Testing of Thyroid Nodules: A Review of Current Available Tests for Fine-Needle Aspiration Specimens.

- Fine-needle aspiration of thyroid nodules is a reliable diagnostic method to determine the nature of thyroid nodules. Nonetheless, indeterminate cytology diagnoses remain a diagnostic challenge. The development of multiplex molecular techniques and the identification of genetic alterations associated with different follicular cell-derived cancers in the thyroid have led to the introduction of several commercially available tests. - To summarize the most common commercially available molecular testing in thyroid cancer, focusing on the technical features and test performance validation. - Peer-reviewed original articles, review articles, and published conference abstracts were reviewed to analyze the advantages and limitations of the most common tests used in the evaluation of thyroid needle aspirations. - The most common tests available include the Afirma Gene Expression Classifier, ThyGenX, and ThyroSeq. The excellent negative predictive value (NPV) of the Afirma test allows it to be used as a "rule out" test. ThyGenX analyzes a panel of DNA mutations and RNA translocation fusion markers to assess the risk of malignancy with good NPV and positive predictive value. ThyroSeq is a next-generation sequencing-based gene mutation and fusion test that has been reported to have the best NPV and positive predictive value combined, suggesting that it can be used as a "rule in" and "rule out" test. Molecular testing of cytology specimens from thyroid nodules has the potential to play a major role in the evaluation of indeterminate thyroid lesions.

Initial development of a multigene ⿿omics-based exposure biomarker for pyrethroid pesticides

Omics technologies have long since promised to address a number of long standing issues related to environmental regulation. Despite considerable resource investment, there are few examples where these tools have been adopted by the regulatory community, which is in part due to a focus of most studies on discovery rather than assay development. The current work describes the initial development of an omics based assay using 48h Pimephales promelas (FHM) larvae for identifying aquatic exposures to pyrethroid pesticides. Larval FHM were exposed to seven concentrations of each of four pyrethroids (permethrin, cypermethrin, esfenvalerate and bifenthrin) in order to establish dose response curves. Then, in three separate identical experiments, FHM were exposed to a single equitoxic concentration of each pyrethroid, corresponding to 33% of the calculated LC50. All exposures were separated by weeks and all materials were either cleaned or replaced between runs in an attempt to maintain independence among exposure experiments. Gene expression classifiers were developed using the random forest algorithm for each exposure and evaluated first by cross-validation using hold out organisms from the same exposure experiment and then against test sets of each pyrethroid from separate exposure experiments. Bifenthrin exposed organisms generated the highest quality classifier, demonstrating an empirical Area Under the Curve (eAUC) of 0.97 when tested against bifenthrin exposed organisms from other exposure experiments and 0.91 against organisms exposed to any of the pyrethroids. An eAUC of 1.0 represents perfect classification with no false positives or negatives. Additionally, the bifenthrin classifier was able to successfully classify organisms from all other pyrethroid exposures at multiple concentrations, suggesting a potential utility for detecting cumulative exposures. Considerable run-to-run variability was observed both in exposure concentrations and molecular responses of exposed fish across exposure experiments. The application of a calibration step in analysis successfully corrected this, resulting in a significantly improved classifier. Classifier evaluation suggested the importance of considering a number of aspects of experimental design when developing an expression based tool for general use in ecological monitoring and risk assessment, such as the inclusion of multiple experimental runs and high replicate numbers.

Gene Expression Classifier Testing and the Surgical Decision-Making Process for Patients With Thyroid Nodules

Gene Expression Classifier Testing and the Surgical Decision-Making Process for Patients With Thyroid Nodules

Abstract 1954: microRNA expression in bronchial epithelium for lung cancer detection

Abstract Introduction We have previously shown that gene expression alterations in the cytologically-normal mainstem bronchus can be leveraged as a biomarker for lung cancer detection (Silvestri et al. NEJM 2015), a test that is now used clinically. Extending this approach, we hypothesized that bronchial microRNA (miRNA) expression is altered in patients with lung cancer and that incorporating miRNA expression into the mRNA classifier may improve its performance. Methods Using bronchial brushes collected prospectively from current and former smokers undergoing bronchoscopy for suspect lung cancer across 28 medical centers as part of the AEGIS 1 and 2 clinical trials, we profiled miRNA expression via small RNA sequencing of 341 patients for which gene expression data was also available on the same bronchial brush sample. Patients were followed for up to one year post-bronchoscopy until a final diagnosis was established. 138 patients from AEGIS 1 (88 cancer-positive and 50 cancer-free) served as a discovery set, while other 203 patients from AEGIS 1 and 2 (103 cancer-positive and 100 cancer-free) were used as an independent test set. First, we identified miRNAs whose expression is associated with cancer by linear modeling in the discovery set. We next explored the relationships between the expression of these miRNAs and their predicted mRNA targets. Lastly, using logistic regression, we incorporated a cancer miRNA feature into our bronchial gene-expression classifier (Silvestri et al., NEJM 2015) and validated its performance in the test set. Results We found that expression profiles of 42 miRNAs were associated with cancer status in the discovery set (p<0.05, 23 miRNAs expected by chance). The top four differentially expressed miRNAs (q<0.2) were all decreased in the bronchial epithelium of cancer patients. The expression values of these miRNAs were significantly negatively correlated with the expression of their predicted mRNA targets (p<0.05). The predicted gene targets of the top miRNAs were significantly enriched (p<0.05) for cancer-related processes including the PDGF signaling pathway, insulin/IGF pathway-mitogen and activated protein kinase/MAP kinase cascade. Moreover, we found that the addition of one of the top differentially expressed miRNAs in the discovery set to the existing gene expression biomarker significantly improved the classifier's performance (ROC AUC) in the test set (p = 0.025). Conclusions We have established that there are alterations in miRNA expression in the cytologically normal mainstem bronchus of smokers with lung cancer. Importantly, we demonstrated the potential of these miRNA alterations to improve the performance of an existing bronchial gene expression biomarker for lung cancer detection. Citation Format: Ana Brandusa Pavel, Joshua Campbell, Gang Liu, Sherry Zhang, Hanqiao Liu, Ji Xiao, Kate Porta, Duncan Whitney, Steven Dubinett, David Elashoff, Marc Lenburg, Avrum Spira. microRNA expression in bronchial epithelium for lung cancer detection. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1954.

Molecular-Directed Treatment of Differentiated Thyroid Cancer: Advances in Diagnosis and Treatment.

Thyroid cancer incidence is increasing, and when fine-needle aspiration biopsy results are cytologically indeterminate, the diagnosis is often still established only after thyroidectomy. Molecular marker testing may be helpful in guiding patient-oriented and tailored management of thyroid nodules and thyroid cancer. To summarize available data on the use of molecular testing to improve the diagnosis and prognostication of thyroid cancer. A MEDLINE review was conducted using the primary search terms molecular, thyroid cancer, thyroid nodule, and gene expression classifier in search strings. Articles were restricted to those published between January 1, 2010, and June 1, 2015, inclusive of adult humans, and reported in the English language only. Of 867 titles screened, 67 articles were further identified for review of the full text. The 2 most studied molecular marker testing techniques for indeterminate thyroid nodules include gene expression classifier analysis and evaluation for somatic mutations or rearrangements that are commonly found in thyroid cancer (7-gene panel). Nodules with benign results on gene expression classifier analysis can be associated with less than a 5% risk of cancer and may be observed, while nodules with positive results on the 7-gene panel may have a higher risk of cancer (80%-100%) and definitive surgery can be recommended. However, cancer prevalence and geographic variations in histologic subtypes may affect accuracy and clinical applicability of both tests. Molecular marker tests such as ThyroSeq version 2.1 are more comprehensive, but they need further validation. Preoperative risk stratification using molecular markers also may be used to better define the optimal extent of thyroidectomy for patients with thyroid cancer. Molecular markers potentially can augment the diagnostic specificity of fine-needle aspiration biopsy to better differentiate cytologically indeterminate nodules that can be safely observed from cytologically indeterminate nodules that may be associated with differentiated thyroid cancer. Long-term follow-up data are still needed; in the end, patient preference regarding the relative risks and benefits of molecular testing is at the crux of decision making.

Noninvasive Follicular Variant of Papillary Thyroid Carcinoma and the Afirma Gene-Expression Classifier.

It is now recognized that noninvasive follicular variant of papillary thyroid carcinoma (NFVPTC) is a distinct subset of FVPTC with an exceedingly indolent clinical course. The Afirma gene-expression classifier (GEC) helps guide clinicians in the management of thyroid nodules with indeterminate fine-needle aspiration (FNA) results. Thyroid surgery is recommended for nodules with a suspicious Afirma result, whereas observation is deemed reasonable for most nodules with a benign result. The aim of this study was to confirm that the Afirma test detects NFVPTCs and to determine how many carcinomas detected by the Afirma GEC represent NFVPTCs. From a database of 249 FNAs sent for Afirma testing between January 2012 and October 2014, a search was conducted for cases with a preceding FNA diagnosis of atypia/follicular lesion of undetermined significance (AUS/FLUS) or suspicious for a follicular neoplasm (SFN), a suspicious Afirma result, and a corresponding resection specimen reviewed at Brigham and Women's Hospital. The diagnoses of the prior FNAs and subsequent resection specimens were recorded. Slides for all resection specimens with a diagnosis of FVPTC were reviewed to identify NFVPTCs. Sixty-three cases met the inclusion criteria. The preceding FNA diagnosis was AUS/FLUS in 34 (54%) cases and SFN in 29 (46%) cases. The surgical resection specimen demonstrated 16 (25%) FVPTCs, five (8%) follicular thyroid carcinomas, one (2%) classical type PTC, and 41 (65%) benign tumors/nodules. Of the 16 FVPTCs, 14 (88%) were NFVPTCs. Thus, NFVPTCs accounted for 64% of the carcinomas in the cohort. These results indicate that the Afirma GEC detects NFVPTCs and that many of the carcinomas detected by Afirma are NFVPTCs. While all care should be individualized and include clinical and sonographic assessment, these results suggest lobectomy as opposed to total thyroidectomy should be considered for nodules with a preceding AUS/FLUS or SFN on cytology and a suspicious Afirma result.

Use of the Afirma Gene Expression Classifier Increased the Number of Indeterminate Diagnoses but Did Not Reduce the Frequency of Thyroid Surgery

Use of the Afirma Gene Expression Classifier Increased the Number of Indeterminate Diagnoses but Did Not Reduce the Frequency of Thyroid Surgery

Impact of Afirma gene expression classifier on cytopathology diagnosis and rate of thyroidectomy.

The Afirma gene expression classifier (GEC) assesses malignancy risk in patients with indeterminate thyroid nodules. Afirma putatively reduces costs by classifying certain nodules as benign and thereby avoiding unnecessary surgery. Prior studies have evaluated its impact exclusively on GEC-tested nodules. The objective of the current study was to analyze the effect of Afirma on 1) cytopathology diagnosis, 2) the rate of surgery, and 3) the rate of malignancy on all indeterminate nodules at a high-volume thyroid center. A retrospective cohort analysis of indeterminate (Bethesda III/IV) thyroid nodules from 2012 through 2014 was performed. Cases were evaluated from January 2012 to July 2013 (pre-Afirma), and from July 2013 to December 2014 (post-Afirma). Of 4292 fine-needle aspirations (FNAs) performed, 13.2% were classified as indeterminate. The GEC was used in 45.3% of post-Afirma cases, with the GEC-Benign call rate at 37.1%. In comparing pre-Afirma and post-Afirma cohorts, a significant increase in Bethesda III (10.7% vs 13.4%; P<.005) and Bethesda IV (1.8% vs 2.9%; P<.01) rates were observed. Conversely, the incidence of Bethesda II was found to be significantly decreased (74.6% vs 68.8%; P<.001). The rate of surgery did not change significantly between pre-Afirma and post-Afirma cohorts (37.7% vs 45.1%; P = .11), nor did the malignancy rate (25.3% vs 36.0%; P = .12). The incidence of indeterminate FNA diagnoses significantly increased after Afirma became routinely available, whereas the incidence of benign diagnoses significantly decreased. These data suggest that Afirma may shift FNA interpretation toward Bethesda III/IV, in which molecular testing is used. Moreover, the institutional rates of surgery and malignancy did not appear to change, raising uncertainty regarding the benefits of molecular assay risk stratification. Afirma may produce unintended collateral effects, increasing the number of indeterminate FNA diagnoses while not affecting the institutional thyroidectomy rate or malignancy yield. Cancer Cytopathol 2016;124:722-8. © 2016 American Cancer Society.

Impact of the Afirma Gene Expression Classifier Result on the Surgical Management of Thyroid Nodules with Category III/IV Cytology and Its Correlation with Surgical Outcome

Objective: The Afirma gene expression classifier (GEC) is a molecular test to further classify indeterminate fine-needle aspiration (FNA) as benign or suspicious for malignancy. Study Design: A total of 158 FNAs with Bethesda category III/IV cytology were sent for an Afirma GEC test. We correlated the Afirma GEC results with surgical outcome and also compared the data after Afirma's implementation with the data before. Results: Among the 158 FNAs, the Afirma result was benign in 63 (40%), suspicious in 85 (54%) and unsatisfactory in 10 (6%). In total, 73 (86%) suspicious Afirma cases had surgery and 28 (38%) showed carcinoma. In contrast, only 8 (13%) benign Afirma cases had surgery and all of them were benign. The sensitivity, specificity, negative predictive value and positive predictive value (PPV) of Afirma were 100, 15, 100 and 38%, respectively. The PPV was 20% in cases with follicular lesion of undetermined significance, but was 50% in cases suspicious for follicular neoplasm (SFN). The surgical excisional rate was significantly decreased in SFN cases after the Afirma test. Conclusions: The Afirma GEC is useful for further risk stratifying SFN cases.

Clinical Factors Influencing the Performance of Gene Expression Classifier Testing in Indeterminate Thyroid Nodules.

Molecular diagnostic testing is increasingly used in the management of indeterminate thyroid nodules. Limited data exist regarding the influence of clinical factors on gene expression classifier (GEC) test performance. This study examined the positive and negative predictive value of GEC as stratified by nodule size. A prospectively maintained pathology database from a single tertiary referral center was queried from 2012 to 2015 for indeterminate thyroid nodules that underwent GEC testing. Nodule size, patient demographics, Bethesda classification, and Hürthle cell-predominant nodules (HCNs) were evaluated as predictors of GEC performance. Two hundred and thirty-one patients with 245 indeterminate nodules were examined. Assuming all nodules to be benign unless proven malignant on histopathology, the sensitivity and specificity of GEC testing were 95.2% and 60.1%, respectively. The malignancy rate among resected nodules was 25.3%. The positive predictive value was consistent across nodule sizes: 45.5% for nodules <1 cm, 42.9% for nodules 1-1.9 cm, 36.0% for nodules 2-2.9 cm, 54.2% for nodules 3-3.9 cm, and 50.0% for nodules ≥4 cm. The negative predictive value ranged from 93.3% to 100% and was not affected by nodule size. HCNs had a high rate of GEC suspicious results (77.4% vs. 50.5% for nodules without Hürthle cell predominance, p < 0.01), though this did not correspond to a difference in the rate of malignancy (25.8% vs. 25.3%). Nodule size did not affect GEC test performance in the present cohort. GEC benign results remain reliable in large nodules. GEC suspicious nodules >3 cm carry a similar risk of malignancy compared to smaller nodules, and do not warrant more aggressive treatment. GEC testing has limited clinical utility for HCNs due to the high rate of false-positive results.

Utility and cost-effectiveness of molecular testing in thyroid nodules with indeterminate cytology.

Molecular testing on biopsies from thyroid nodules with indeterminate cytology can improve patient management by preventing unnecessary surgeries on benign nodules. The aim of the study was to determine the health outcome benefits and cost-effectiveness of molecular testing in nodules with AUS/FLUS or FN/SFN cytology. The initial diagnosis and treatment of a hypothetical cohort of adult U.S. patients with solitary thyroid nodules ≥1 cm was simulated by decision analytic modelling using Medicare cost estimates for three management strategies, standard of care without molecular testing (StC), gene expression classifier (GEC) and mutation and miRNA testing (MMT). Gene expression classifier decreased the rate of unnecessary surgeries by 32% relative to StC, yielding incremental costs of $1008 per patient or $5070 per unnecessary surgery avoided. MMT decreased the surgery rate by 67%, yielding incremental savings of -$1384 per patient or -$3170 per unnecessary surgery avoided. Results remained robust in deterministic sensitivity analyses; MMT was dominant for every variable tested. Independent of cancer prevalence, MMT yielded 52% fewer unnecessary surgeries relative to GEC #bib70% fewer two-stage thyroidectomies and correctly identified 70% more benign nodules. Test specificity had to be >68% for molecular testing to be cost-effective and decrease by >50% the rate of unnecessary surgeries performed on benign nodules. Molecular testing with high benign diagnostic yield can generate both positive health outcomes (less surgeries) and positive economic outputs (cost savings). These results are consistent with previously reported cost-utility data and provide valuable insights for informed decision-making by patients, physicians and payers.

Long-Term Nonoperative Rate of Thyroid Nodules with Benign Results on the Afirma Gene Expression Classifier

The primary objective was to assess the operative rate in patients with a benign result from the Afirma gene expression classifier (GEC) during long-term follow-up at nonacademic medical facilities. The secondary endpoint of this study was the treating physician's opinion regarding the safety of GEC use compared to the hypothetical situation of providing thyroid nodule management without the GEC. This was a retrospective study of nonacademic medical practices utilizing the GEC. Those clinicians utilizing the GEC testing who had three or more 'benign' results during the data collection period (September 2010 through June 2014) were invited to participate. Operative status and patient demographics were documented for patients with GEC testing at least 36 months (± 3 months) prior to the date of data collection. A survey also was administered to the treating physicians to assess their perceived safety of using the GEC in patient care. During 36 months (± 3 months) of follow-up, 17 of 98 patients (17.3%) with a 'benign' GEC result underwent surgery. Within the first 2 years after a 'benign' GEC, 88% of surgeries were performed. Regarding safety of the GEC, the treating physicians reported that patient safety was improved by using the GEC compared to not using the GEC in 78 of 91 cases (86%). It appears that a 'benign' result on the GEC is associated with a reduction in the rate of thyroid surgeries compared to published data when patients are followed for 36 months after testing. A nonoperative approach to follow-up was felt to be a safe alternative to diagnostic surgery by the majority of responsible physicians in the study. AUS = atypia of undetermined significance FLUS = follicular lesion of undetermined significance FN = follicular neoplasm FNA = fine-needle aspiration GEC = gene expression classifier.

Derivation of gene expression classifiers for the non-invasive detection of bladder cancer in the hematuria and recurrence surveillance populations.

11522Background: The detection of bladder cancer in patients presenting with hematuria or for recurrence surveillance is routinely accomplished with a combination of urine cytology and cystoscopy, ...

Building a Quality Management System for a Thyroid Nodule Clinic.

There are few published quality metrics relevant to fine-needle aspirations (FNA) of the thyroid and endocrinology. With the development of a Thyroid Nodule Clinic within an academic practice, the Division of Endocrinology, in collaboration with the Department of Medicine Quality Improvement Team, established a system to monitor the results and follow-up of thyroid biopsies to ensure patient safety and to prevent adverse clinical outcomes attributable to delayed or incomplete follow-up. All FNA performed are identified using billing data from the Thyroid Nodule Clinic. Results were followed using the Beth Israel Deaconess Online Medical Record (OMR) system, and information is collected on documented follow-up plan and actions taken. Missing data are flagged for review. Over the reporting period, the monitoring process and categories were modified to account for adoption of the Bethesda reporting criteria and implementation of gene expression classifier testing. Specific workflow plans were developed for each cytopathologic classification. Between July 2007 and June 2014, 3895 FNAs were performed. The quality improvement tracking process found that 3856/3895 (99%) biopsy cases had documented follow-up since initiation of the project. This monitoring process has ensured quality patient care, with confidence that patients having FNAs are receiving documented necessary follow-up for treatment of their nodular conditions. This system serves as a potential model for others to use in their endocrine practice in managing the results of thyroid nodule biopsies.

The Effect of Implementing Gene Expression Classifier on Outcomes of Thyroid Nodules with Indeterminate Cytology.

Thyroid nodules are classified into six cytological categories under the Bethesda classification system. Two of these categories, atypical of undetermined significance (AUS) and suspicious for a follicular neoplasm (SFN), are further labeled as "indeterminate" diagnosis. Starting in June, 2012, Kansas University-Wichita Endocrine clinic implemented Afirma® Gene Expression Classifier (AGEC) to evaluate the need for surgical resection of thyroid nodules in patients with an indeterminate diagnosis. Electronic medical records of patients who underwent thyroid nodule fine-needle aspiration from 2004-2014 were reviewed. The aim of this study was to find whether implementing AGEC was associated with decreased surgical recommendation rate, decreased cost, and increased incidence of thyroid malignancy diagnosed by surgery in patients with indeterminate diagnosis. A total of 299 consecutive patients' charts were screened. Sixty-one (20%) patients had an indeterminate diagnosis. Out of these, 27 (44%) patients underwent evaluation before and 34 (56%) patients underwent evaluation after AGEC implementation, respectively. Surgical recommendation for patients with indeterminate finding decreased from 81.5 to 50% (p = 0.01) after AGEC implementation. Surgical pathology was read as malignant in 20 and 85.7% (p < 0.01) of patients before and after AGEC implementation, respectively. Primary cost-benefit estimate showed implementing AGEC has saved $1048/patient in medical evaluation and initial management of patients with indeterminate diagnosis. AGEC implementation has decreased the number of surgical recommendations, has lowered financial burden, and has increased incidence of thyroid malignancy diagnosed by surgical pathology in patients with indeterminate diagnosis of thyroid nodules.

Impact of a gene expression classifier on the long-term management of patients with cytologically indeterminate thyroid nodules

Objectives: The gene expression classifier (GEC, Afirma) reclassifies as molecularly benign approximately one half of thyroid nodule fine-needle aspiration (FNA) biopsies with an initial indeterminate cytopathology diagnosis, facilitating clinical monitoring in lieu of diagnostic thyroid surgery. This study evaluated the long-term management patterns and thyroid surgery rates of GEC benign patients compared to a control group of cytopathology benign patients and also described the costs of thyroid surgery. Methods: This retrospective cohort study used laboratory test results linked to payer medical claims data. Patients who underwent FNA biopsy between 1 January 2011 and 31 July 2013 were selected. GEC benign patients were matched 1:3 to cytopathology benign patients on biopsy year, gender, nodule size and age. Outcomes measured included thyroid-related follow-up clinic visits, ultrasound examinations and surgeries. Results: Out of 2059 patients, matched groups consisting of 201 GEC benign patients and 603 cytopathology benign patients were evaluated over an average follow-up of 20 months. The proportions of GEC benign and cytopathology benign patients that underwent thyroid surgery (11.4% versus 10.1%, p = 0.594), and received a follow-up ultrasound exam (60.2% versus 61.7%, p = 0.706), respectively, were not significantly different. Average thyroid-related medical cost for the surgical episode and during 6 months following surgery were $10,432.00 (SD $8301) and $10,939.00 (SD $9656) respectively. Limitations: The study cohort included only patients whose diagnostic laboratory test results and administrative claims data were uniquely identifiable and could be linked on multiple identifiers; the rigorous matching and patient selection algorithms utilized improved the robustness and internal validity of the study. Claims were used as a proxy for clinical utilization without chart review confirmation. Conclusion: Patients with GEC and cytopathology benign diagnoses were managed similarly. The majority of patients in both groups did not undergo surgery and were managed with usual care, consisting of clinical follow-up and ultrasound exams.

Highlights of This Issue

Evens, et al, investigated the use of abexinostat, an oral pan-histone deacetylase inhibitor in patients with relapsed/refractory lymphoma. Abexinostat was particularly efficacious in follicular lymphoma with a 64% response rate in evaluable patients. Furthermore, responses were durable with median duration of response not reached and median progression-free survival of 20.5 months. Using unique intermittent dosing, abexinostat was well tolerated with thrombocytopenia, fatigue, and neutropenia as the only grade 3/4 adverse events occurring in ≥10% of patients. Altogether, abexinostat represents a potential new treatment for lymphoma and further investigation is warranted.Sundaresan and colleagues evaluated T790M genotypes in 40 patients with progressing EGFR-mutant lung cancer, comparing concurrently obtained tumor biopsies, circulating tumor cells (CTCs), and circulating tumor DNA (ctDNA). Concordance between the blood-based methods and tissue biopsy was approximately 70%, and when used in combination, the two blood-based methods enabled successful genotyping in all patients. Blood-based genotyping also identified the T790M mutation in 35% of patients in whom the concurrent tumor biopsy was negative or nondiagnostic. Discrepant genotyping results between biopsy, CTCs, and ctDNA likely reflect both technical variation as well as biological differences in the tumor material sampled by these assays. Without a reliable “gold standard,” the clinical utility of different T790M-genotyping strategies will ultimately be determined by their ability to predict clinical responses to novel EGFR inhibitors.Defects in apoptotic signaling, including overexpression of BCL2 antiapoptotic proteins, contribute to increased survival of diffuse large B-cell lymphoma (DLBCL) cells and might result in resistance to conventional genotoxic agents. By targeting BCL2 and MCL1 proteins, Klanova and colleagues demonstrated that DLBCL can be divided into BCL2- and MCL1-dependent subgroups. In addition, the authors showed that concurrent inhibition of BCL2 and MCL1 was highly synergistic in vitro and in vivo using primary cell-based murine xenograft models of DLBCL. These findings might have implications for concepts of early clinical trials in DLBCL.Primary uveal melanomas are conventionally divided into Class 1 tumors (low metastatic risk) and Class 2 tumors (high metastatic risk) based on a prospectively validated gene expression classifier. In this study, a new subgroup of Class 1 uveal melanomas with intermediate metastatic risk is identified based on expression of the immunogenic oncoprotein PRAME. This discovery further optimizes the prognostic accuracy of the gene expression classifier and identifies patients who may be good candidates for immunotherapy.

Correlating thyroid cytology and histopathology: Implications for molecular testing.

A gene expression classifier (GEC) has been advocated in management of some indeterminate nodules without surgery. We assessed the potential negative predictive value (NPV) of the GEC at our academic center. Retrospectively, all cytologically indeterminate fine-needle aspirates (FNAs) diagnosed by University of Iowa cytopathologists over a 3-year period were identified. Histopathologic findings were recorded. Using published sensitivity and specificity, NPVs were calculated. Of 178 nodules (17, 135, and 26 in classes III, IV, and V, respectively), 71 (40%) were malignant. Prevalence of malignancy was 41%, 29%, and 96% for classes III, IV, and V, respectively. Using sensitivities and specificities for the GEC, NPVs were 91% for the cohort: 88%, 92%, and 26% for classes III, IV, and V, respectively. Molecular testing should be associated with an NPV no lower than that from clinical criteria alone. With the prevalences reported, GEC use may result in more missed cancer diagnoses. © 2016 Wiley Periodicals, Inc. Head Neck 38: 1104-1106, 2016.

Abstract P3-07-28: BRCA1-like profile as predictive biomarker in non myeloablative chemotherapy (GAIN study)

Abstract Background: The BRCA1-like copy number (CN) profile can be used as a biomarker to predict which stage III breast cancer patients benefit from myeloablative, DNA double-strand-break (DSB)-inducing chemotherapy. In addition, a BRCA1-like gene expression classifier, derived from the BRCA1-like CN profile, can predict which patient group will achieve an increased pathological complete remission rate on a standard neoadjuvant regimen complemented with carboplatin/veliparib. A non-myeloablative, dose-dense schedule of epirubicin, paclitaxel and cyclophosphamide (ETC) is used in the clinic to treat stage III patients. Since ETC contains an intensified dose of DNA DSB-inducing cyclophosphamide, we tested the BRCA1-like CN profile as a predictive biomarker for ETC benefit in the GAIN trial. Methods: The GAIN trial was a prospective, multi-center, non-blinded, randomized phase III trial. Eligibility comprised histologically confirmed invasive breast cancer with at least one positive axillary or internal mammary lymph node and no signs of distant metastases. The allocated adjuvant treatment was intensified chemotherapy with sequential E (150 mg/m2), T (225 mg/m2) and C (2500, after amendment 2000 mg/m2) each 3 cycles every 2 weeks (ETC) or concurrent E (112.5 mg/m2) and C (600 mg/m2) for 4 cycles every 2 weeks followed by 10 cycles of weekly T (67.5 mg/m2) combined with 4 cycles of capecitabine (2000mg/m2) on day 1-14 in a 3-weekly cycle (EC-TX). Only the triple negative patients were used for these analyses. For samples with good quality DNA extracted from formalin-fixed paraffin-embedded tumor tissue, a library was prepared and sequenced on an Illumina HiSeq2000 platform. Copy number estimates were extracted from the sequence data by normalizing GC-content and mappability corrected read counts to the average read count. These CN profiles were classified as either BRCA1-like or non-BRCA1-like using a previously established shrunken centroid classifier with an established cut-off. Disease-free survival (DFS) and overall survival (OS) were estimated using the Kaplan-Meier method, the difference in survival was analysed using log-rank tests. Multivariate analyses were done by generating Cox regression models with important prognostic factors. Results: Out of 424 triple negative patients, 166 patients with available tissue and a tumour cell content of at least 60% were analysed for BRCA1-like status and included in the analyses (classified as BRCA1-like: n=122). Based on clinicopathological characteristics, these patients were similar to the total group of triple negative participants. In the BRCA1-like patients, there was no significant difference in DFS or OS between ETC and EC-TX (log-rank tests n.s.). In accordance, Cox regression models confirmed these findings. Conclusion: In contrast to the predictive value of the BRCA1-like profile in myeloablative chemotherapy, it could not predict survival benefit for a non-myeloablative, non-platinum-/veliparib-containing regimen in this study population. An intensified dose of cyclophosphamide resulted in similar outcomes in BRCA1-like patients as addition of capecitabine to standard chemotherapy. These results help to define the appropriate application of the BRCA1-like profile as a predictive biomarker. Citation Format: van Rossum AGJ, Schouten PC, Weber KE, Nekljudova V, Denkert C, von Minckwitz G, Karn T, Möbus VJ, Linn SC, Loibl S, Marmé F. BRCA1-like profile as predictive biomarker in non myeloablative chemotherapy (GAIN study). [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P3-07-28.

A functional SNP in MRPL43 modulates lung cancer susceptibility and survival through alternative splicing of its isoforms

two cohorts by incorporating the resulting coefficients of multivariable Cox regression model into a score that utilizes linear gene expression values. This gene expression classifier was validated in 6 additional publicly available datasets of stage I/II lung SCC (N 1⁄4 358). The classifier identified high-risk patients in multiple large-scale and geographically diverse cohorts (N 1⁄4 570). The results appear to be independent of race and gene expression platform. Canonical pathways associated with this signature encompass proteins involved in signal transduction, tissue remodeling, and cell motility that would broadly lead to cancer cell migration, invasion and proliferation, suggesting that the gene signature identifies molecular subsets of patients with clinical relevance. This gene classifier could be used to guide clinical decisions after surgical resection. Thus, we would advocate that this classifier be incorporated into prospective trials for further evaluation of its clinical effectiveness.