Transcriptional Signatures in Histologic Structures within Glioblastoma Tumors May Predict Personalized Treatment Sensitivity and Survival

Kersch C. N.; Claunch C.; Ambady P.; Muldoon L. L.; Neuwelt E. A.

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Transcriptional Signatures in Histologic Structures within Glioblastoma Tumors May Predict Personalized Treatment Sensitivity and Survival

机译：胶质母细胞瘤肿瘤内的组织学结构中的转录签名可能预测个性化的治疗敏感性和生存

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《International Journal of Radiation Oncology, Biology, Physics 》 |2019年第1suppla期| 共1页
作者
Kersch C. N.; Claunch C.; Ambady P.; Muldoon L. L.; Neuwelt E. A.;
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Oregon Hlth &

Sci Univ Portland OR 97201 USA;

Oregon Hlth &

Sci Univ Portland OR 97201 USA;

Oregon Hlth &

Sci Univ Portland OR 97201 USA;

Oregon Hlth &

Sci Univ Portland OR 97201 USA;

Oregon Hlth &

Sci Univ Portland OR 97201 USA;

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正文语种 eng
中图分类放射医学 ;
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1. Transcriptional Signatures in Histologic Structures within Glioblastoma Tumors May Predict Personalized Treatment Sensitivity and Survival [J] . Kersch C. N., Claunch C., Ambady P., International Journal of Radiation Oncology, Biology, Physics . 2019 ,第1Suppla期

机译：胶质母细胞瘤肿瘤内的组织学结构中的转录签名可能预测个性化的治疗敏感性和生存
2. Tumor-intrinsic and -extrinsic (immune) gene signatures robustly predict overall survival and treatment response in high grade serous ovarian cancer patients [J] . David P Mysona, Lynn Tran, Shan Bai, American Journal of Cancer Research . 2021 ,第1期

机译：肿瘤内在和 - inexcrinsic（免疫）基因签名鲁棒地预测高级浆液癌患者的整体存活和治疗反应
3. A novel gene signature based on five glioblastoma stem-like cell relevant genes predicts the survival of primary glioblastoma [J] . Chai Ruichao, Zhang Kenan, Wang Kuanyu, Journal of Cancer Research and Clinical Oncology . 2018 ,第3期

机译：基于五个胶质母细胞瘤干细胞相关基因的新型基因签名预测原发性胶质母细胞瘤的存活率
4. Technical Note: A radiomic signature of infiltration in peritumoral edema predicts subsequent recurrence in glioblastoma [C] . Saima Rathore, Hamed Akbari, Jimit Doshi, SPIE Medical Imaging Conference . 2018

机译：技术说明：肿瘤周围水肿浸润的放射学特征可预测胶质母细胞瘤的复发
5. Generalized singular value decomposition (GSVD) comparison of patient-matched normal and tumor aCGH profiles reveals global copy-number alterations predicting glioblastoma multiforme survival. [D] . Sankaranarayanan, Preethi. 2013

机译：患者匹配的正常和肿瘤aCGH谱的广义奇异值分解（GSVD）比较显示出预测胶质母细胞瘤多形体存活的总体拷贝数变化。
6. PATH-63. TRANSCRIPTIONAL SIGNATURES IN HISTOLOGIC STRUCTURES WITHIN GLIOBLASTOMA TUMORS MAY PREDICT PERSONALIZED TREATMENT SENSITIVITY AND SURVIVAL [O] . Cymon Kersch, Cheryl Claunch, Prakash Ambady, 2019

机译：路径-63。胶质母细胞瘤肿瘤内的组织学结构中的转录签名可能预测个性化的治疗敏感性和生存
7. Transcriptional Signatures in Histologic Structures within Glioblastoma Tumors May Predict Personalized Treatment Sensitivity and Survival [O] . C.N. Kersch, C. Claunch, P. Ambady, 2019

机译：胶质母细胞瘤肿瘤内的组织学结构中的转录签名可能预测个性化的治疗敏感性和生存

Transcriptional Signatures in Histologic Structures within Glioblastoma Tumors May Predict Personalized Treatment Sensitivity and Survival

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