Background: Glioma is caused by multiple genomic alterations. The evolving classification of glio-mas emphasizes the significance of molecular testing. Next generation sequencing (NGS) offers the assessment of parallel combinations of multiple genetic alterations and identifying actionable mutations that guide treatment. This study comprehensively analyzed glioma patients using multi-gene NGS panels, providing powerful insights to inform diagnostic classification and targeted therapies. Methods: We conducted a targeted panel-based NGS analysis on formalin-fixed and paraffin-embedded nucleic acids extracted from a total of 147 glioma patients. These samples underwent amplicon capture-based library preparation and sequenced using the Oncomine Comprehensive Assay platform. The resulting sequencing data were then analyzed using the bioinformatics tools. Results: A total of 301 mutations, were found in 132 out of 147 tumors (89.8%). These muta-tions were in 68 different genes. In 62 tumor samples (42.2%), copy number variations (CNVs) with gene amplifications occurred in 25 genes. Moreover, 25 tumor samples (17.0%) showed gene fusions in 6 genes and intragenic deletion in a gene. Our analysis identified actionable targets in several genes, including 11 with mutations, 8 with CNVs, and 3 with gene fusions and intragenic deletion. These findings could impact FDA-approved therapies, NCCN guideline-based treatments, and clinical trials. Conclusion We analyzed precisely diagnosing the classification of gliomas, detailing the frequency and co-occurrence of genetic alterations and identifying genetic alterations with potential therapeutic targets by NGS-based molecular analysis. The high-throughput NGS analysis is an efficient and powerful tool to comprehensively support molecular testing in neurooncology.

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Objective: To evaluate the added value of diffusion-weighted imaging (DWI)-based quantitative parameters to distinguish uterine sarcomas from atypical leiomyomas on preoperative magnetic resonance imaging (MRI). Materials and Methods: A total of 138 patients (age, 43.7 ± 10.3 years) with uterine sarcoma (n = 44) and atypical leiomyoma (n = 94) were retrospectively collected from four institutions. The cohort was randomly divided into training (84/138, 60.0%) and validation (54/138, 40.0%) sets. Two independent readers evaluated six qualitative MRI features and two DWI-based quantitative parameters for each index tumor. Multivariable logistic regression was used to identify the relevant qualitative MRI features. Diagnostic classifiers based on qualitative MRI features alone and in combination with DWI-based quantitative parameters were developed using a logistic regression algorithm. The diagnostic performance of the classifiers was evaluated using a cross-table analysis and calculation of the area under the receiver operating characteristic curve (AUC). Results: Mean apparent diffusion coefficient value of uterine sarcoma was lower than that of atypical leiomyoma (mean ± standard deviation, 0.94 ± 0.30 10-3 mm2 /s vs. 1.23 ± 0.25 10-3 mm2 /s; P < 0.001), and the relative contrast ratio was higher in the uterine sarcoma (8.16 ± 2.94 vs. 4.19 ± 2.66; P < 0.001). Selected qualitative MRI features included ill-defined margin (adjusted odds ratio [aOR], 17.9; 95% confidence interval [CI], 1.41–503, P = 0.040), intratumoral hemorrhage (aOR, 27.3; 95% CI, 3.74–596, P = 0.006), and absence of T2 dark area (aOR, 83.5; 95% CI, 12.4–1916, P < 0.001). The classifier that combined qualitative MRI features and DWI-based quantitative parameters showed significantly better performance than without DWI-based parameters in the validation set (AUC, 0.92 vs. 0.78; P < 0.001). Conclusion The addition of DWI-based quantitative parameters to qualitative MRI features improved the diagnostic performance of the logistic regression classifier in differentiating uterine sarcomas from atypical leiomyomas on preoperative MRI.

Purpose: Triple-negative breast cancer (TNBC) is an aggressive type of breast cancer.Currently, no effective treatment options for this condition exist. Nuclear factor erythroid 2-related factor 2 (NRF2), encoded by nuclear factor erythroid-derived 2-like 2 (NFE2L2) gene and its endogenous inhibitor, Kelch-like ECH-associated protein 1 (KEAP1), both participate in cellular defense mechanisms against oxidative stress and contribute to chemoresistance and tumor progression in numerous types of cancers. This study aimed to evaluate the expression patterns of NRF2 and KEAP1 and their prognostic value in operable TNBC. Methods: Tissue microarrays were prepared using tumor tissues collected from 203 patients with TNBC who underwent surgery. Immunohistochemical staining analyses of NRF2 and KEAP1 were performed. The expression of each immunomarker was categorized into two groups (low or high) based on the median H-score. We analyzed the association between the expression of each immunomarker and clinicopathological information to predict survival.A total of 225 TNBC samples from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset were used to validate our results. Results: NRF2 immunoreactivity was detected in the nucleus and was associated with histologic grade and Ki-67 index, whereas KEAP1 immunoreactivity was detected in the cytoplasm and was associated with the Ki-67 index. Survival analyses showed that NRF2 and KEAP1 expressions were independent prognostic factors for overall survival (OS) (hazard ratio [HR], 2.45 and 0.30; p = 0.015 and 0.016, respectively) and disease-free survival (HR, 2.27 and 0.42; p = 0.019 and 0.022, respectively). NFE2L2 mRNA expression was an independent prognostic factor for OS (HR, 0.59; p = 0.009) in the METABRIC dataset. Conclusion High NRF2 and low KEAP1 expressions independently predicted poor survival in patients with operable TNBC. Further investigations are warranted to examine the possible therapeutic benefits of targeting the KEAP1-NRF2 pathway for TNBC treatment.

Background: and Purpose Cognitive and behavioral changes are common in amyotrophic lateral sclerosis (ALS), with about 15% of patients presenting with overt frontotemporal dementia and 30%–50% with varying degrees of impairments. We aimed to develop and validate the Korean version of the Edinburgh Cognitive and Behavioral ALS Screen (ECAS-K), a brief multidomain assessment tool developed for ALS patients with physical disability. Methods: We developed the ECAS-K according to the translation guidelines, and administered it to 38 patients with ALS and 26 age- and education-level-matched controls. We also administered the Montreal Cognitive Assessment (MoCA) and Frontal Assessment Battery (FAB) to investigate convergent validity, and the Center for Neurologic Study-Liability Scale to assess the association between pseudobulbar affect and cognitive/behavioral changes. Results: Internal consistency among the ECAS-K test items was found to be high, with a Cronbach’s alpha of 0.87. Significant differences were found between patients with ALS and the controls in language, fluency, and memory functions (p<0.05). Abnormal performance based on the ECAS total score was noted in 39.4% of patients, and 66.6% presented behavioral changes in at least one domain. Significant correlations were observed between the scores of the ECAS-K and those of other cognitive screening tools (MoCA and FAB, with correlation coefficients of 0.69 and 0.55, respectively; p<0.01). Conclusions We developed and validated the ECAS-K which could be used as an effective tool to screen the cognitive and behavioral impairments in Korean patients with ALS.

Background: The metastatic brain tumor is the most common brain tumor. The aim of this study was to demonstrate the clinicopathological and molecular pathologic features of brain metastases (BM). Methods: A total of 269 patients were diagnosed with BM through surgical resection at Seoul St. Mary’s Hospital from January 2010 to March 2020. We reviewed the clinicopathological features and molecular status of primary and metastatic brain tissues using immunohistochemistry and molecular pathology results. Results: Among 269 patients, 139 males and 130 females were included. The median age of primary tumor was 58 years (range, 13 to 87 years) and 86 patients (32.0%) had BM at initial presentation. Median BM free interval was 28.0 months (range, 1 to 286 months). The most frequent primary site was lung 46.5% (125/269), and followed by breast 15.6% (42/269), colorectum 10.0% (27/269). Epidermal growth factor receptor (EGFR) mutation was found in 50.8% (32/63) and 58.0% (40/69) of lung primary and BM, respectively. In both breast primary and breast cancer with BM, luminal B was the most frequent subtype at 37.9% (11/29) and 42.9% (18/42), respectively, followed by human epidermal growth factor receptor 2 with 31.0% (9/29) and 33.3% (14/42). Triple-negative was 20.7% (6/29) and 16.7% (7/42), and luminal A was 10.3% (3/29) and 7.1% (3/42) of breast primary and BM, respectively. In colorectal primary and colorectal cancer with BM, KRAS mutation was found in 76.9% (10/13) and 66.7% (2/3), respectively. Conclusions We report the clinicopathological and molecular pathologic features of BM that can provide useful information for understanding the pathogenesis of metastasis and for clinical trials based on the tumor’s molecular pathology.