Faculty Profiles - Tanaka Shota

Papers - Tanaka Shota

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Hanako Numata, Maiko Noguchi-Watanabe, Akitake Mukasa, Shota Tanaka, Shunsaku Takayanagi, Nobuhito Saito, Noriko Yamamoto-Mitani

Global Qualitative Nursing Research 7 233339362096005 - 233339362096005 2020.1

Language：English Publishing type：Research paper (scientific journal) Publisher：SAGE Publications

Medical care-related decision-making among patients with malignant brain tumors has not been sufficiently discussed. This study aimed to develop a framework for understanding patients’ experiences in the decision-making process. Semi-structured interviews with 14 patients were analyzed using a grounded theory approach, focusing on their 48 decision-making points. Additionally, interviews with two family members and seven healthcare providers, and participant observations were used to gain contextual insight into patients’ experiences. Patients faced decisions while they struggled in vulnerability under shock, fear, and anxiety while hoping. Under this context, they showed four decision-making patterns: (1) led by the situation, (2) controlled by others, (3) entrusted someone with the decision, and (4) myself as a decision-making agent. Across these patterns, the patients were generally satisfied with their decisions even when they did not actively participate in the process. Healthcare providers need to understand patients’ contexts and their attitudes toward yielding decision-making to others.

DOI： 10.1177/2333393620960059

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Other Link： http://journals.sagepub.com/doi/full-xml/10.1177/2333393620960059

Exploring Predictors of Response to Dacomitinib in EGFR-Amplified Recurrent Glioblastoma. International journal

Andrew S Chi, Daniel P Cahill, David A Reardon, Patrick Y Wen, Tom Mikkelsen, David M Peereboom, Eric T Wong, Elizabeth R Gerstner, Jorg Dietrich, Scott R Plotkin, Andrew D Norden, Eudocia Q Lee, Lakshmi Nayak, Shota Tanaka, Hiroaki Wakimoto, Nina Lelic, Mara V Koerner, Lindsay K Klofas, Mia S Bertalan, Isabel C Arrillaga-Romany, Rebecca A Betensky, William T Curry, Darrel R Borger, Leonora Balaj, Robert R Kitchen, Sudipto K Chakrabortty, Michael D Valentino, Johan Skog, Xandra O Breakefield, A John Iafrate, Tracy T Batchelor

JCO precision oncology 4 2020

Language：English Publishing type：Research paper (scientific journal)

PURPOSE: Despite the high frequency of EGFR genetic alterations in glioblastoma (GBM), EGFR-targeted therapies have not had success in this disease. To improve the likelihood of efficacy, we targeted adult patients with recurrent GBM enriched for EGFR gene amplification, which occurs in approximately half of GBM, with dacomitinib, a second-generation, irreversible epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor that penetrates the blood-brain barrier, in a multicenter phase II trial. PATIENTS AND METHODS: We retrospectively explored whether previously described EGFR extracellular domain (ECD)-sensitizing mutations in the context of EGFR gene amplification could predict response to dacomitinib, and in a predefined subset of patients, we measured post-treatment intratumoral dacomitinib levels to verify tumor penetration. RESULTS: We found that dacomitinib effectively penetrates contrast-enhancing GBM tumors. Among all 56 treated patients, 8 (14.3%) had a clinical benefit as defined by a duration of treatment of at least 6 months, of whom 5 (8.9%) remained progression free for at least 1 year. Presence of EGFRvIII or EGFR ECD missense mutation was not associated with clinical benefit. We evaluated the pretreatment transcriptome in circulating extracellular vesicles (EVs) by RNA sequencing in a subset of patients and identified a signature that distinguished patients who had durable benefit versus those with rapid progression. CONCLUSION: While dacomitinib was not effective in most patients with EGFR-amplified GBM, a subset experienced a durable, clinically meaningful benefit. Moreover, EGFRvIII and EGFR ECD mutation status in archival tumors did not predict clinical benefit. RNA signatures in circulating EVs may warrant investigation as biomarkers of dacomitinib efficacy in GBM.

DOI： 10.1200/PO.19.00295

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Prediction of malignant glioma grades using contrast-enhanced T1-weighted and T2-weighted magnetic resonance images based on a radiomic analysis. Reviewed International journal

Takahiro Nakamoto, Wataru Takahashi, Akihiro Haga, Satoshi Takahashi, Shigeru Kiryu, Kanabu Nawa, Takeshi Ohta, Sho Ozaki, Yuki Nozawa, Shota Tanaka, Akitake Mukasa, Keiichi Nakagawa

Scientific reports 9 ( 1 ) 19411 - 19411 2019.12

Language：English Publishing type：Research paper (scientific journal)

We conducted a feasibility study to predict malignant glioma grades via radiomic analysis using contrast-enhanced T1-weighted magnetic resonance images (CE-T1WIs) and T2-weighted magnetic resonance images (T2WIs). We proposed a framework and applied it to CE-T1WIs and T2WIs (with tumor region data) acquired preoperatively from 157 patients with malignant glioma (grade III: 55, grade IV: 102) as the primary dataset and 67 patients with malignant glioma (grade III: 22, grade IV: 45) as the validation dataset. Radiomic features such as size/shape, intensity, histogram, and texture features were extracted from the tumor regions on the CE-T1WIs and T2WIs. The Wilcoxon-Mann-Whitney (WMW) test and least absolute shrinkage and selection operator logistic regression (LASSO-LR) were employed to select the radiomic features. Various machine learning (ML) algorithms were used to construct prediction models for the malignant glioma grades using the selected radiomic features. Leave-one-out cross-validation (LOOCV) was implemented to evaluate the performance of the prediction models in the primary dataset. The selected radiomic features for all folds in the LOOCV of the primary dataset were used to perform an independent validation. As evaluation indices, accuracies, sensitivities, specificities, and values for the area under receiver operating characteristic curve (or simply the area under the curve (AUC)) for all prediction models were calculated. The mean AUC value for all prediction models constructed by the ML algorithms in the LOOCV of the primary dataset was 0.902 ± 0.024 (95% CI (confidence interval), 0.873-0.932). In the independent validation, the mean AUC value for all prediction models was 0.747 ± 0.034 (95% CI, 0.705-0.790). The results of this study suggest that the malignant glioma grades could be sufficiently and easily predicted by preparing the CE-T1WIs, T2WIs, and tumor delineations for each patient. Our proposed framework may be an effective tool for preoperatively grading malignant gliomas.

DOI： 10.1038/s41598-019-55922-0

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Radiomics Analysis for Glioma Malignancy Evaluation Using Diffusion Kurtosis and Tensor Imaging. Reviewed International journal

Satoshi Takahashi, Wataru Takahashi, Shota Tanaka, Akihiro Haga, Takahiro Nakamoto, Yuichi Suzuki, Akitake Mukasa, Shunsaku Takayanagi, Yosuke Kitagawa, Taijun Hana, Takahide Nejo, Masashi Nomura, Keiichi Nakagawa, Nobuhito Saito

International journal of radiation oncology, biology, physics 105 ( 4 ) 784 - 791 2019.11

Language：English Publishing type：Research paper (scientific journal)

PURPOSE: A noninvasive diagnostic method to predict the degree of malignancy accurately would be of great help in glioma management. This study aimed to create a highly accurate machine learning model to perform glioma grading. METHODS AND MATERIALS: Preoperative magnetic resonance imaging acquired for cases of glioma operated on at our institution from October 2014 through January 2018 were obtained retrospectively. Six types of magnetic resonance imaging sequences (T2-weighted image, diffusion-weighted image, apparent diffusion coefficient [ADC], fractional anisotropy, and mean kurtosis [MK]) were chosen for analysis; 476 features were extracted semiautomatically for each sequence (2856 features in total). Recursive feature elimination was used to select significant features for a machine learning model that distinguishes glioblastoma from lower-grade glioma (grades 2 and 3). RESULTS: Fifty-five data sets from 54 cases were obtained (14 grade 2 gliomas, 12 grade 3 gliomas, and 29 glioblastomas), of which 44 and 11 data sets were used for machine learning and independent testing, respectively. We detected 504 features with significant differences (false discovery rate <0.05) between glioblastoma and lower-grade glioma. The most accurate machine learning model was created using 6 features extracted from the ADC and MK images. In the logistic regression, the area under the curve was 0.90 ± 0.05, and the accuracy of the test data set was 0.91 (10 out of 11); using a support vector machine, they were 0.93 ± 0.03 and 0.91 (10 out of 11), respectively (kernel, radial basis function; c = 1.0). CONCLUSIONS: Our machine learning model accurately predicted glioma tumor grade. The ADC and MK sequences produced particularly useful features.

DOI： 10.1016/j.ijrobp.2019.07.011

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NIMG-49. THE ACCURACY EVALUATION OF ARCUATE FASCICULUS OF DIFFUSION TENSOR TRACTOGRAPHY BY FUSION OF REAL SPACE AND VIRTUAL SPACE

Tsukasa Koike, Taichi Kin, Yasuhiro Takeda, Hiroki Uchikawa, Taketo Shiode, Shunsaku Takayanagi, Shota Tanaka, Nobuhito Saito

Neuro-Oncology 21 ( Supplement_6 ) vi172 - vi172 2019.11

Publishing type：Research paper (scientific journal) Publisher：Oxford University Press (OUP)

Abstract

PURPOSE

Diffusion tensor-based tractography (DTT) is a method to estimate the direction of white matter fibers, but it is difficult to verify the relationship with brain function spatially with high accuracy. We developed a registration method to fuse the real space (brain surface photograph) and preoperative fused 3D image (virtual space) using the landmark method and thin plate spline method. In our previous study, this method was able to achieve highly accurate alignment registration error 0.7±0.1mm (mean±SE) even after brain shift due to craniotomy. In this study, we proposed a method to examine spatial errors of DTT and direct cortical stimulation (DCS) and verify its accuracy.

METHODS

We included 7 gliomas performed awake surgery. We created the fused three – dimensional image before surgery and acquired the brain surface photograph immediately after craniotomy, then we aligned them using the proposed method. Sites that showed speech arrest by DCS were plotted on the fused image. A circle with a radius of 15 mm centered on the same site was taken as the range over which the current spreads. The surface area of each of the circles was calculated to make it true if there was arcuate fasciculus drawn with DTT in the circle, and false if it did not exist. By using this method, the accuracy of the DTT was verified. RESULT: In 7 cases, speech arrest was shown at 21 DCS plots. The probability of the presence of DTT within the current spread of DCS was 64.4%.

CONCLUSION

The proposed method indicates that DTT does not necessarily match the DCS results by verification using real space and virtual space. We present some illustrative cases.

DOI： 10.1093/neuonc/noz175.718

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Two cases of primary supratentorial intracranial rhabdomyosarcoma with DICER1 mutation which may belong to a "spindle cell sarcoma with rhabdomyosarcoma-like feature, DICER1 mutant". Reviewed

Maki Sakaguchi, Yoshiko Nakano, Mai Honda-Kitahara, Masashi Kinoshita, Shingo Tanaka, Masahiro Oishi, Kazuhiro Noguchi, Masaki Fukuda, Hideaki Maeba, Takuya Watanabe, Yutaka Hayashi, Hiroko Ikeda, Hiroshi Minato, Koichi Ichimura, Takayuki Nojima, Mitsutoshi Nakada

Brain tumor pathology 36 ( 4 ) 174 - 182 2019.10

Language：English Publishing type：Research paper (scientific journal)

Rhabdomyosarcoma is the most common soft-tissue sarcoma affecting children and adolescents. It is defined as a malignant neoplasm characterized by morphologic, immunohistochemical, ultrastructural, or molecular genetic evidence of primary skeletal muscle differentiation, usually in the absence of any other pattern of differentiation. Primary intracranial rhabdomyosarcoma (PIRMS) is an extremely rare neoplasm, with only 60 cases reported in the literature, and generally has poor prognosis with an overall survival of only 9.1 months. The DICER1 gene encodes an RNA endoribonuclease that plays a key role in gene expression regulation through the production of small RNAs. Herein, we report two cases of PIRMS with somatic DICER1 mutation showing morphological and immunohistochemical evidence of primary skeletal muscle differentiation; the two cases share common clinical features, including young age, supratentorial tumor, and onset of intratumoral bleeding. Although methylation profiling was not performed, both cases shared clinical and pathological characteristics in common with recently proposed methylation entity "spindle cell sarcoma with rhabdomyosarcoma-like features, DICER1 mutant (SCS-RMSlike-DICER1)''. Our cases provide further evidence of the link between primary intracranial sarcoma and DICER1 mutation which may form a distinct entity.

DOI： 10.1007/s10014-019-00352-z

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領域特異的な5-hydroxymethylcytosine(5hmC)の変動がGlioma悪性転化に関与する(Region-specific 5-hydroxymethylcytosine(5hmC) alteration affects the glioma malignant transformation)

花大洵, 野村昌志, 武笠晃丈, 田中將太, 永江玄太, 油谷浩幸

日本癌学会総会記事 78回 P - 1369 2019.9

領域特異的な5-hydroxymethylcytosine(5hmC)の変動がGlioma悪性転化に関与する(Region-specific 5-hydroxymethylcytosine(5hmC) alteration affects the glioma malignant transformation) Reviewed

花大洵, 野村昌志, 武笠晃丈, 田中將太, 永江玄太, 油谷浩幸

日本癌学会総会記事 78回 P - 1369 2019.9

Reduced Neoantigen Expression Revealed by Longitudinal Multiomics as a Possible Immune Evasion Mechanism in Glioma. Reviewed International journal

Takahide Nejo, Hirokazu Matsushita, Takahiro Karasaki, Masashi Nomura, Kuniaki Saito, Shota Tanaka, Shunsaku Takayanagi, Taijun Hana, Satoshi Takahashi, Yosuke Kitagawa, Tsukasa Koike, Yukari Kobayashi, Genta Nagae, Shogo Yamamoto, Hiroki Ueda, Kenji Tatsuno, Yoshitaka Narita, Motoo Nagane, Keisuke Ueki, Ryo Nishikawa, Hiroyuki Aburatani, Akitake Mukasa, Nobuhito Saito, Kazuhiro Kakimi

Cancer immunology research 7 ( 7 ) 1148 - 1161 2019.7

Language：English Publishing type：Research paper (scientific journal)

Immune-based therapies have shown limited efficacy in glioma thus far. This might be at least in part due to insufficient numbers of neoantigens, thought to be targets of immune attack. In addition, we hypothesized that dynamic genetic and epigenetic tumor evolution in gliomas might also affect the mutation/neoantigen landscape and contribute to treatment resistance through immune evasion. Here, we investigated changes in the neoantigen landscape and immunologic features during glioma progression using exome and RNA-seq of paired primary and recurrent tumor samples obtained from 25 WHO grade II-IV glioma patients (glioblastoma, IDH-wild-type, n = 8; grade II-III astrocytoma, IDH-mutant, n = 9; and grade II-III oligodendroglioma, IDH-mutant, 1p/19q-codeleted, n = 8). The number of missense mutations, predicted neoantigens, or expressed neoantigens was not significantly different between primary and recurrent tumors. However, we found that in individual patients the ratio of expressed neoantigens to predicted neoantigens, designated the "neoantigen expression ratio," decreased significantly at recurrence (P = 0.003). This phenomenon was particularly pronounced for "high-affinity," "clonal," and "passenger gene-derived" neoantigens. Gene expression and IHC analyses suggested that the decreased neoantigen expression ratio was associated with intact antigen presentation machinery, increased tumor-infiltrating immune cells, and ongoing immune responses. Our findings imply that decreased expression of highly immunogenic neoantigens, possibly due to persistent immune selection pressure, might be one of the immune evasion mechanisms along with tumor clonal evolution in some gliomas.

DOI： 10.1158/2326-6066.CIR-18-0599

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Publisher Correction: DNA demethylation is associated with malignant progression of lower-grade gliomas. Reviewed International journal

Masashi Nomura, Kuniaki Saito, Koki Aihara, Genta Nagae, Shogo Yamamoto, Kenji Tatsuno, Hiroki Ueda, Shiro Fukuda, Takayoshi Umeda, Shota Tanaka, Shunsaku Takayanagi, Ryohei Otani, Takahide Nejo, Taijun Hana, Satoshi Takahashi, Yosuke Kitagawa, Mayu Omata, Fumi Higuchi, Taishi Nakamura, Yoshihiro Muragaki, Yoshitaka Narita, Motoo Nagane, Ryo Nishikawa, Keisuke Ueki, Nobuhito Saito, Hiroyuki Aburatani, Akitake Mukasa

Scientific reports 9 ( 1 ) 7935 - 7935 2019.5

結節性硬化症診療連携チーム結成による患者受診状況の変化

佐藤敦志, 佐藤悠佑, 高柳俊作, 辛正廣, 田中將太, 國井尚人, 宮垣朝光, 澤村裕正, 漆山博和, 谷口豪, 大瀬戸久美子, 張香里, 岡明, 水口雅

脳と発達 51 ( Suppl. ) S313 - S313 2019.5

微小環境神経膠腫(1) グリオーマ悪性転化に於ける5-hydroxymethylcytosine(5hmC)変動の網羅的解析

花大洵, 武笠晃丈, 野村昌志, 田中將太, 池村雅子, 北川陽介, 根城尭英, 高柳俊作, 油谷浩幸, 斉藤延人

Brain Tumor Pathology 36 ( Suppl. ) 065 - 065 2019.5

PIK3CA activating mutations are associated with more disseminated disease at presentation and earlier recurrence in glioblastoma. Reviewed International journal

Shota Tanaka, Tracy T Batchelor, A John Iafrate, Dora Dias-Santagata, Darrell R Borger, Leif W Ellisen, Daniel Yang, David N Louis, Daniel P Cahill, Andrew S Chi

Acta neuropathologica communications 7 ( 1 ) 66 - 66 2019.4

Language：English Publishing type：Research paper (scientific journal)

Phosphatidylinositol 3-kinase signaling promotes cell growth and survival and is frequently activated in infiltrative gliomas. Activating mutations in PIK3CA gene are observed in 6-15% of glioblastomas, although their clinical significance is largely undescribed. The objective of this study was to examine whether PIK3CA mutations are associated with a specific clinical phenotype in glioblastoma. We retrospectively reviewed 157 consecutive newly diagnosed glioblastoma patients from December 2009 to June 2012 who underwent molecular profiling consisting of targeted hotspot genotyping, fluorescence in situ hybridization for gene amplification, and methylation-specific PCR for O6-methylguanine-DNA methyltransferase promoter methylation. Molecular alterations were correlated with clinical features, imaging and outcome. The Cancer Genome Atlas data was analyzed as a validation set. There were 91 males; median age was 58 years (range, 23-85). With a median follow-up of 20.9 months, median progression-free survival (PFS) and estimated overall survival (OS) were 11.9 and 24.0 months, respectively. Thirteen patients (8.3%) harbored PIK3CA mutation, which was associated with younger age (mean 49.4 vs. 58.1 years, p = 0.02). PIK3CA mutation correlated with shorter PFS (median 6.9 vs. 12.4 months, p = 0.01) and OS (median 21.2 vs. 24.2 months, p = 0.049) in multivariate analysis. A significant association between PIK3CA mutation and more disseminated disease at diagnosis, as defined by gliomatosis, multicentric lesions, or distant leptomeningeal lesions, was observed (46.2% vs. 11.1%, p = 0.004). In conclusion, despite the association with younger age, PIK3CA activating mutations are associated with earlier recurrence and shorter survival in adult glioblastoma. The aggressive course of these tumors may be related to their propensity for disseminated presentation.

DOI： 10.1186/s40478-019-0720-8

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Pattern of FDG and MET Distribution in High- and Low-Grade Gliomas on PET Images. Reviewed International journal

Miwako Takahashi, Tsutomu Soma, Akitake Mukasa, Shota Tanaka, Shunsuke Yanagisawa, Toshimitsu Momose

Clinical nuclear medicine 44 ( 4 ) 265 - 271 2019.4

Language：English Publishing type：Research paper (scientific journal)

PURPOSE OF THE REPORT: This study aimed to determine the most effective metabolic index of FDG-PET and MET-PET to differentiate high- and low-grade gliomas, and then to characterize tumor metabolism according to the 2016 WHO classification. We also developed a new calculation method of potential infiltrative tumor volume to overcome the current limitations of tumor evaluation according to metabolic index, which focuses solely on tumor core area. MATERIALS AND METHODS: Patients who underwent both FDG-PET and MET-PET, as well as surgical treatment, were retrospectively identified. All tumors were diagnosed histologically and included 44 high-grade and 19 low-grade gliomas. Metabolic indices of tumor-to-normal (T/N) ratio and maximum value within the tumor itself were compared between high- and low-grade tumors. A calculation method for potential infiltrative tumor volume was developed and compared between these 2 grades. RESULTS: T/N, calculated as tumor value divided by normal cortex value, was the most effective (area under the curve, 0.800 for FDG-PET; area under the curve, 0.773 for MET-PET) for differentiating high- and low-grade gliomas. Potential infiltrative volume effectively distinguished between high- and low-grade glioma (43.8 ± 30.2 mL vs 14.0 ± 12.6 mL; P = 0.005 [t test]). A combination of T/N, with a cutoff value of 0.9 or higher on FDG-PET and/or 3.0 or higher on MET-PET, and potential infiltrative volume, with a cutoff value of 20.0 mL or higher, provided a diagnostic accuracy of 89% in distinguishing high- from low-grade gliomas. CONCLUSIONS: Evaluation of potential infiltrative volume surrounding the tumor core area, in addition to the T/N ratio of the tumor core, may help distinguish between high- and low-grade gliomas.

DOI： 10.1097/RLU.0000000000002460

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脳転移巣で横紋筋肉腫様変化を示した胎児型消化管胃癌の遺伝子解析

山澤翔, 牛久哲男, 山下裕玄, 田中將太, 鈴木章浩, 油谷浩幸, 深山正久

日本病理学会会誌 108 ( 1 ) 365 - 365 2019.4

DNA demethylation is associated with malignant progression of lower-grade gliomas. Reviewed International journal

Scientific reports 9 ( 1 ) 1903 - 1903 2019.2

Language：English Publishing type：Research paper (scientific journal)

To elucidate the mechanisms of malignant progression of lower-grade glioma, molecular profiling using methylation array, whole-exome sequencing, and RNA sequencing was performed for 122, 36 and 31 gliomas, respectively. This cohort included 24 matched pairs of initial lower-grade gliomas and recurrent tumors, most of which showed malignant progression. Nearly half of IDH-mutant glioblastomas that had progressed from lower-grade gliomas exhibited characteristic partial DNA demethylation in previously methylated genomic regions of their corresponding initial tumors, which had the glioma CpG island methylator phenotype (G-CIMP). In these glioblastomas, cell cycle-related genes, RB and PI3K-AKT pathway genes were frequently altered. Notably, late-replicating domain was significantly enriched in the demethylated regions that were mostly located in non-regulatory regions, suggesting that the loss of DNA methylation during malignant transformation may involve mainly passive demethylation due to a delay in maintenance of methylation during accelerated cell division. Nonetheless, a limited number of genes including IGF2BP3, which potentially drives cell proliferation, were presumed to be upregulated due to demethylation of their promoter. Our data indicated that demethylation of the G-CIMP profile found in a subset of recurrent gliomas reflects accelerated cell divisions accompanied by malignant transformation. Oncogenic genes activated by such epigenetic change represent potential therapeutic targets.

DOI： 10.1038/s41598-019-38510-0

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Mining-Guided Machine Learning Analyses Revealed the Latest Trends in Neuro-Oncology. Reviewed International journal

Taijun Hana, Shota Tanaka, Takahide Nejo, Satoshi Takahashi, Yosuke Kitagawa, Tsukasa Koike, Masashi Nomura, Shunsaku Takayanagi, Nobuhito Saito

Cancers 11 ( 2 ) 2019.2

Language：English Publishing type：Research paper (scientific journal)

In conducting medical research, a system which can objectively predict the future trends of the given research field is awaited. This study aims to establish a novel and versatile algorithm that predicts the latest trends in neuro-oncology. Seventy-nine neuro-oncological research fields were selected with computational sorting methods such as text-mining analyses. Thirty journals that represent the recent trends in neuro-oncology were also selected. As a novel concept, the annual impact (AI) of each year was calculated for each journal and field (number of articles published in the journal × impact factor of the journal). The AI index (AII) for the year was defined as the sum of the AIs of the 30 journals. The AII trends of the 79 fields from 2008 to 2017 were subjected to machine learning predicting analyses. The accuracy of the predictions was validated using actual past data. With this algorithm, the latest trends in neuro-oncology were predicted. As a result, the linear prediction model achieved relatively good accuracy. The predicted hottest fields in recent neuro-oncology included some interesting emerging fields such as microenvironment and anti-mitosis. This algorithm may be an effective and versatile tool for prediction of future trends in a particular medical field.

DOI： 10.3390/cancers11020178

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Genetically distinct glioma stem-like cell xenografts established from paired glioblastoma samples harvested before and after molecularly targeted therapy. Reviewed International journal

Shota Tanaka, Samantha Luk, Juri Kiyokawa, Maristela L Onozato, A John Iafrate, Khalid Shah, Robert L Martuza, Samuel D Rabkin, Tracy T Batchelor, Daniel P Cahill, Andrew S Chi, Hiroaki Wakimoto

Scientific reports 9 ( 1 ) 139 - 139 2019.1

Language：English Publishing type：Research paper (scientific journal)

Intratumoural heterogeneity underlies tumour escape from molecularly targeted therapy in glioblastoma. A cell-based model preserving the evolving molecular profiles of a tumour during treatment is key to understanding the recurrence mechanisms and development of strategies to overcome resistance. In this study, we established a matched pair of glioblastoma stem-like cell (GSC) cultures from patient glioblastoma samples before and after epidermal growth factor receptor (EGFR)-targeted therapy. A patient with recurrent glioblastoma (MGG70R) harboring focal, high-level EGFR amplification received the irreversible EGFR tyrosine kinase inhibitor dacomitinib. The tumour that subsequently recurred (MGG70RR) showed diploid EGFR, suggesting inhibitor-mediated elimination of EGFR-amplified tumour cells and propagation of EGFR non-amplified cell subpopulations. The MGG70R-GSC line established from MGG70R formed xenografts retaining EGFR amplification and EGFR overexpression, while MGG70RR-GSC established from MGG70RR generated tumours that lacked EGFR amplification and EGFR overexpression. MGG70R-GSC-derived intracranial xenografts were more proliferative than MGG70RR-GSC xenografts, which had upregulated mesenchymal markers, mirroring the pathological observation in the corresponding patient tumours. In vitro MGG70R-GSC was more sensitive to EGFR inhibitors than MGG70RR-GSC. Thus, these molecularly distinct GSC lines recapitulated the subpopulation alteration that occurred during glioblastoma evasion of targeted therapy, and offer a valuable model facilitating therapeutic development for recurrent glioblastoma.

DOI： 10.1038/s41598-018-37437-2

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Brain Metastasis Mimicking Brain Abscess in ALK-Positive Non-Small-Cell Lung Cancer. Reviewed International journal

Toshio Sakatani, Hidenori Kage, Shunsaku Takayanagi, Kaoru Watanabe, Yoshihisa Hiraishi, Aya Shinozaki-Ushiku, Shota Tanaka, Tetsuo Ushiku, Nobuhito Saito, Takahide Nagase

Case reports in oncological medicine 2019 9141870 - 9141870 2019

Language：English

Brain metastasis frequently develops in non-small-cell lung cancer (NSCLC). Here, we report a patient who developed brain metastasis from ALK-positive NSCLC which mimicked brain abscess. He was admitted for suspected obstructive pneumonia nine months after curative lung resection. Head magnetic resonance imaging revealed a cavitary lesion, which was compatible with brain abscess but rare in brain metastasis. However, after treatment with antibiotics, the brain lesion increased in size. Aspiration of the liquid content of the brain lesion revealed cancer cells. When a brain lesion suggestive of abscess develops in a patient with ALK-positive NSCLC, aspiration may be necessary to differentiate metastasis from abscess.

DOI： 10.1155/2019/9141870

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Spray Fluorescent Probes for Fluorescence-Guided Neurosurgery. International journal

Yosuke Kitagawa, Shota Tanaka, Yugo Kuriki, Kyoko Yamamoto, Akira Ogasawara, Takahide Nejo, Reiko Matsuura, Tsukasa Koike, Taijun Hana, Satoshi Takahashi, Masashi Nomura, Shunsaku Takayanagi, Akitake Mukasa, Mako Kamiya, Yasuteru Urano, Nobuhito Saito

Frontiers in oncology 9 ( AUG ) 727 - 727 2019

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Papers - Tanaka Shota