Discrimination between non-functioning pituitary adenomas and hypophysitis using machine learning methods based on magnetic resonance imaging­derived texture features.

PURPOSE: Hypophysitis is a heterogeneous condition that includes inflammation of the pituitary gland and infundibulum, and it can cause symptoms related to mass effects and hormonal deficiencies. We aimed to evaluate the potential role of machine learning methods in differentiating hypophysitis from non-functioning pituitary adenomas. METHODS: The radiomic parameters obtained from T1A-C images were used. Among the radiomic parameters, parameters capable of distinguishing between hypophysitis and non-functioning pituitary adenomas were selected. In order to avoid the effects of confounding factors and to improve the performance of the classifiers, parameters with high correlation with each other were eliminated. Machine learning algorithms were performed with the combination of gray-level run-length matrix-low gray level run emphasis, gray-level co-occurrence matrix-correlation, and gray-level co-occurrence entropy. RESULTS: A total of 34 patients were included, 17 of whom had hypophysitis and 17 had non-functioning pituitary adenomas. Among the 38 radiomics parameters obtained from post-contrast T1-weighted images, 10 tissue features that could differentiate the lesions were selected. Machine learning algorithms were performed using three selected parameters; gray level run length matrix-low gray level run emphasis, gray-level co-occurrence matrix-correlation, and gray level co-occurrence entropy. Error matrices were calculated by using the machine learning algorithm and it was seen that support vector machines showed the best performance in distinguishing the two lesion types. CONCLUSIONS: Our analysis reported that support vector machines showed the best performance in distinguishing hypophysitis from non-functioning pituitary adenomas, emphasizing the importance of machine learning in differentiating the two lesions.

The Place and Prognostic Value of TERT Promoter Mutation in Molecular Classification in Grade II-III Glial Tumors and Primary Glioblastomas.

OBJECTIVE: Diffuse gliomas, the most common primary malignant brain tumors, have been classified by the World Health Organization as class II-IV gliomas. After 2016, two mutations in the promoter region of the telomerase reverse transcriptase (TERT) gene were identified in addition to the IDH, 1p / 19q, and ATRX status. MATERIAL AND METHOD: We identified 84 patients with grade II-IV glioma with IDH, ATRX, 1p / 19q and TERT status. All tumor samples were subjected to molecular genetic screening (Sanger sequencing for IDH and TERT mutations, fluorescence in situ hybridization for 1p/19q status) after histological diagnosis (immunohistochemistry for IDH1 R132H, ATRX, and p53) for a more precise molecular diagnosis. The confidence intervals were calculated at the 95% confidence level, and differences at p < 0.05 were considered statistically significant. RESULTS: Primary glioblastomas had the highest frequency of TERT promoter mutations (25 of 28, 89.2%, p=0.006) followed by oligodendrogliomas (29 of 35, 82.8%, p < 0.001) while astrocytomas showed the lowest frequency (3 of 15, 20%, p=0.107), and the positivity significantly differed among these three groups (p < 0.001). TERT promoter mutations were more frequent in patients older than 55 years of age at diagnosis (p=0.023). The group with TERT promoter mutations, and without IDH mutations showed the worst overall survival. However, the presence of both TERT promoter and IDH mutations, which resembled oligodendroglial progression, showed best overall survival (p=0.042). CONCLUSION: The discovery of TERT promoter mutations in numerous gliomas has opened the door for a better molecular classification of gliomas, and TERT status is associated with survival. Further studies will help in elucidating the value of TERT promoter mutations as biomarkers in clinical practice, and eventual therapeutic targets.

International real-world study of DLL3 expression in patients with small cell lung cancer.

OBJECTIVES: Expression of the Notch-family ligand delta-like protein 3 (DLL3), a potential therapeutic target in small cell lung cancer (SCLC), has not been assessed in the real-world setting. To identify the real-world utility of DLL3 as an SCLC therapeutic target, we performed the largest retrospective international noninterventional study to date to evaluate DLL3 prevalence in SCLC patients. MATERIALS AND METHODS: DLL3 expression was assessed using immunohistochemistry in archived histological and cytological specimens (independent and paired) and correlated to patient demographics, clinical disease characteristics, and survival. The primary endpoint was the proportion of patients with DLL3 expression in ≥25 % of tumor cells. DLL3 expression concordance was assessed in paired specimens. RESULTS: Independent tumor specimens were collected from 1073 patients. The mean age at biopsy was 66 years (SD, 10); 682 (64 %) patients were male. Paired specimens were collected from 36 patients. The mean age at biopsy was 62 years (SD, 11); 16 (44 %) patients were male. Most patients had ECOG performance status of 0-1, were smokers/ex-smokers, and received ≥1 prior therapy. Positive DLL3 expression (defined as ≥25 % of tumor cells) was identified in 895/1050 (85 %) patients with 1 specimen and evaluable DLL3 expression; 719/1050 (68 %) patients had high DLL3 expression (defined as ≥75 % of tumor cells). DLL3 expression concordance was 88 % between paired specimens (n = 17; Cohen's kappa P value, .9412). There was no significant difference in median overall survival from SCLC diagnosis for evaluable patients with nonmissing data based on DLL3 expression (negative DLL3 expression [n = 139], 9.5 months; positive DLL3 expression [n = 747], 9.5 months; all evaluable patients [n = 893, 9.5 months). CONCLUSION: These real-world epidemiologic findings indicate that DLL3 is robustly expressed across SCLC disease stages and remains stable despite treatment, consistent with available clinical trial data. There was no prognostic role for DLL3 observed in this study for overall survival.

Correlation of ROS1 Immunohistochemistry With ROS1 Fusion Status Determined by Fluorescence In Situ Hybridization.

CONTEXT.­: The ability to determine ROS1 status has become mandatory for patients with lung adenocarcinoma, as many global authorities have approved crizotinib for patients with ROS1-positive lung adenocarcinoma. OBJECTIVE.­: To present analytical correlation of the VENTANA ROS1 (SP384) Rabbit Monoclonal Primary Antibody (ROS1 [SP384] antibody) with ROS1 fluorescence in situ hybridization (FISH). DESIGN.­: The immunohistochemistry (IHC) and FISH analytical comparison was assessed by using 122 non-small cell lung cancer samples that had both FISH (46 positive and 76 negative cases) and IHC staining results available. In addition, reverse transcription-polymerase chain reaction (RT-PCR) as well as DNA and RNA next-generation sequencing (NGS) were used to further examine the ROS1 status in cases that were discrepant between FISH and IHC, based on staining in the cytoplasm of 2+ or above in more than 30% of total tumor cells considered as IHC positive. Here, we define the consensus status as the most frequent result across the 5 different methods (IHC, FISH, RT-PCR, RNA NGS, and DNA NGS) we used to determine ROS1 status in these cases. RESULTS.­: Of the IHC scoring methods examined, staining in the cytoplasm of 2+ or above in more than 30% of total tumor cells considered as IHC positive had the highest correlation with a FISH-positive status, reaching a positive percentage agreement of 97.8% and negative percentage agreement of 89.5%. A positive percentage agreement (100%) and negative percentage agreement (92.0%) was reached by comparing ROS1 (SP384) using a cutoff for staining in the cytoplasm of 2+ or above in more than 30% of total tumor cells to the consensus status. CONCLUSIONS.­: Herein, we present a standardized staining protocol for ROS1 (SP384) and data that support the high correlation between ROS1 status and ROS1 (SP384) antibody.

The Applicability of Haarlem Integrated Diagnostic System in Diffuse Glial Tumors and Molecular Methods Affecting Prognosis

Background: With the help of genetic studies, it is possible to obtain information about diagnosis and prognosis of glial tumors. Aims: To categorize the cases according to the new World Health Organization Central Nervous System classification by reconsidering the histologic features of oligodendrogliomas, astrocytomas and oligoastrocytomas. We also evaluated whether these genetic features have prognostic significance. Study Design: Diagnostic accuracy study. Methods: Between the years 2011 and 2016, 60 gliomas were examined. Archival material from the Department of Pathology was used for histopathological, immunohistochemical, and molecular analyses. All the cases were classified and graded according to the new 2016 World Health Organization criteria. IDH1 (R132H), alpha thalassemia/mental retardation syndrome, and p53 antibodies were applied immunohistochemically. The 1p/19q status and platelet-derived growth factor receptor-α/CEP4 amplification were evaluated by fluorescence in situ hybridization. After molecular tests, if the diagnosis of oligodendroglioma or astrocytoma is not diagnosed, case should be diagnosed as oligoastrocytoma. Sensitivity, specificity, positive predictive level, negative predictive level, and accuracy rate were evaluated in accordance with the specified threshold levels. Results: Except for 1 case (3.7%), all cases of grade 2 and grade 3 oligoastrocytoma were diagnosed with astrocytoma or oligodendroglioma without any change of grade. Except for 2 case (6.8%), all cases of grade 2 and grade 3 oligodendroglioma were diagnosed oligodendroglioma. All astrocytomas (100%) were given same diagnosis. There is no specific or sensitive test for the diagnosis of oligoastrocytoma. However, 1p/19q codeletion was spesific (100%) and sensitive (100%) for oligodendroglioma. ATRX and p53 mutation showed high spesificity (100% and 95.1% respectively) for diagnosing astrocytoma. Platelet-derived growth factor receptor-α/ CEP4 was not detected in any of the cases. There was association between isocitrate dehydrogenase mutation and 1p/19q loss with longer survival (respectively p=0.147 and p=0.178). Conclusion: In grade 2 and grade 3 glial tumors, pathological diagnosis is not possible only by histological examination. Overall, there was a diagnosis change in 28 cases (46.6%). Especially in cases of oligoastrocytoma, the diagnosis is changed by molecular tests.