Citations

AbstractBreast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large‐scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65–70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose‐response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96–98%), but yielded many false positives (positive predictive value = 30–32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large‐scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker‐specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results.

AbstractObjectivesApproximately 15% of patients with multiple myeloma (MM) exhibit a t(4;14) translocation, which often results in constitutive activation of the receptor tyrosine kinase (RTK) fibroblast growth factor receptor 3 (FGFR3). This study evaluated the efficacy and safety of dovitinib, an RTK inhibitor with in vitro inhibitory activity against FGFR, in patients with relapsed or refractory MM with or without t(4;14) translocation.MethodsAdult patients with relapsed or refractory MM who had received ≥2 prior regimens were enrolled in this multicenter, 2‐stage, phase 2 trial. Patients were grouped based on their t(4;14) status. Dovitinib (500 mg/day orally) was administered on a 5‐days‐on/2‐days‐off schedule. The primary endpoint was overall response rate by local investigator review (per International Myeloma Working Group criteria). In non‐responding patients, treatment could continue with the addition of low‐dose dexamethasone.ResultsIn total, 43 patients (median age, 63 years) were enrolled (13 t(4;14) positive, 26 t(4;14) negative, and 4 t(4;14) status non‐interpretable). Patients had received a median of 5 prior regimens. Median duration of treatment was 8.7 weeks in the t(4;14)‐positive group and 3.7 weeks in the t(4;14)‐negative group. None of the patients on dovitinib had objective responses. The stable disease rate was 61.5% in the t(4;14)‐positive group and 34.6% in the t(4;14)‐negative group. Overall, 39 patients (90.7%) had adverse events suspected to be related to study drug, most commonly diarrhea (60.5%), nausea (58.1%), vomiting (46.5%), and fatigue (32.6%).ConclusionDovitinib showed no single‐agent activity in relapsed or refractory MM but may stabilize disease in some t(4;14)‐positive patients.

ScopeWe reevaluated previously reported associations between variants in pathways of one‐carbon (1‐C) (folate) transfer genes and ovarian carcinoma (OC) risk, and in related pathways of purine and pyrimidine metabolism, and assessed interactions with folate intake.Methods and resultsOdds ratios (OR) for 446 genetic variants were estimated among 13 410 OC cases and 22 635 controls, and among 2281 cases and 3444 controls with folate information. Following multiple testing correction, the most significant main effect associations were for dihydropyrimidine dehydrogenase (DPYD) variants rs11587873 (OR = 0.92; p = 6 × 10−5) and rs828054 (OR = 1.06; p = 1 × 10−4). Thirteen variants in the pyrimidine metabolism genes, DPYD, DPYS, PPAT, and TYMS, also interacted significantly with folate in a multivariant analysis (corrected p = 9.9 × 10−6) but collectively explained only 0.2% of OC risk. Although no other associations were significant after multiple testing correction, variants in SHMT1 in 1‐C transfer, previously reported with OC, suggested lower risk at higher folate (pinteraction = 0.03–0.006).ConclusionVariation in pyrimidine metabolism genes, particularly DPYD, which was previously reported to be associated with OC, may influence risk; however, stratification by folate intake is unlikely to modify disease risk appreciably in these women. SHMT1 SNP‐by‐folate interactions are plausible but require further validation. Polymorphisms in selected genes in purine metabolism were not associated with OC.

Abstract Major discoveries in the biology of nervous system tumors have raised the question of how non‐histological data such as molecular information can be incorporated into the next W orld H ealth O rganization ( WHO ) classification of central nervous system tumors. To address this question, a meeting of neuropathologists with expertise in molecular diagnosis was held in H aarlem, the N etherlands, under the sponsorship of the I nternational S ociety of N europathology ( ISN ). Prior to the meeting, participants solicited input from clinical colleagues in diverse neuro‐oncological specialties. The present “white paper” catalogs the recommendations of the meeting, at which a consensus was reached that incorporation of molecular information into the next WHO classification should follow a set of provided “ ISN ‐ H aarlem” guidelines. Salient recommendations include that (i) diagnostic entities should be defined as narrowly as possible to optimize interobserver reproducibility, clinicopathological predictions and therapeutic planning; (ii) diagnoses should be “layered” with histologic classification, WHO grade and molecular information listed below an “integrated diagnosis”; (iii) determinations should be made for each tumor entity as to whether molecular information is required, suggested or not needed for its definition; (iv) some pediatric entities should be separated from their adult counterparts; (v) input for guiding decisions regarding tumor classification should be solicited from experts in complementary disciplines of neuro‐oncology; and (iv) entity‐specific molecular testing and reporting formats should be followed in diagnostic reports. It is hoped that these guidelines will facilitate the forthcoming update of the fourth edition of the WHO classification of central nervous system tumors.