{"title":"肿瘤位置、基因组改变和放射学特征作为胶质母细胞瘤存活的预测因子：多模式分析。","authors":"Kavita Kundal, K Venkateswara Rao, Sandeep Kumar Dhanda, Neeraj Kumar, Rahul Kumar","doi":"10.1007/s00234-025-03742-7","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>This study aims to identify the impact of tumor location on the survival of glioblastoma (GBM) patients and the associated genetic alterations, using MRI scans from The Cancer Imaging Archive (TCIA) and genomic data from The Cancer Genome Atlas (TCGA). It also seeks to uncover non-invasive radiomic markers related to poor survival outcome for improved prognosis and treatment planning.</p><p><strong>Methods: </strong>We analysed pre-operative MRI scans and genomic data from 123 GBM patients (TCIA and TCGA). Tumor locations were determined using our in-house tool, \"tumorVQ\", followed by Kaplan-Meier survival analysis based on tumor position. Genomic analysis included somatic mutations, copy number variations, fusion genes, and differential gene expression to identify factors linked to poor survival. We extracted radiomic features from T1ce MRI scans using pyRadiomics to analyse their relationship with survival outcomes.</p><p><strong>Results: </strong>Kaplan-Meier analysis showed worse survival for tumors in the parietal lobe compared to other lobes, especially frontal lobe tumors. Genomic analysis revealed high prevalence of PTEN mutations, and exclusive fusion genes FGFR3-TACC3 and EGFR-SEPT14 in parietal lobe tumors. Differential gene expression showed upregulation of PITX2, HOXB13, and DTHD1, linked to tumor progression, while ALOX15 downregulation increased relapse risk. Copy number alterations, like LINC00290 deletions, were associated with aggressive parietal lobe tumors. Radiomic features, lower GLDM DependanceEntropy (LLL) and higher FirstOrder Mean (HLL), were strongly linked to increase risk.</p><p><strong>Conclusion: </strong>This study highlights poor survival outcomes in GBM patients with parietal lobe tumors. Key genetic alterations, such as PTEN mutations and fusion genes, drive tumor progression and chemoresistance in parietal lobe tumors. The association between radiomic features and survival indicates their potential as non-invasive prognostic biomarkers, which could aid in personalized treatment and improved patient management.</p>","PeriodicalId":19422,"journal":{"name":"Neuroradiology","volume":" ","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Tumor location, genomic alterations, and radiomic features as predictors of survival in glioblastoma: a Multi-Modal analysis.\",\"authors\":\"Kavita Kundal, K Venkateswara Rao, Sandeep Kumar Dhanda, Neeraj Kumar, Rahul Kumar\",\"doi\":\"10.1007/s00234-025-03742-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>This study aims to identify the impact of tumor location on the survival of glioblastoma (GBM) patients and the associated genetic alterations, using MRI scans from The Cancer Imaging Archive (TCIA) and genomic data from The Cancer Genome Atlas (TCGA). It also seeks to uncover non-invasive radiomic markers related to poor survival outcome for improved prognosis and treatment planning.</p><p><strong>Methods: </strong>We analysed pre-operative MRI scans and genomic data from 123 GBM patients (TCIA and TCGA). Tumor locations were determined using our in-house tool, \\\"tumorVQ\\\", followed by Kaplan-Meier survival analysis based on tumor position. Genomic analysis included somatic mutations, copy number variations, fusion genes, and differential gene expression to identify factors linked to poor survival. We extracted radiomic features from T1ce MRI scans using pyRadiomics to analyse their relationship with survival outcomes.</p><p><strong>Results: </strong>Kaplan-Meier analysis showed worse survival for tumors in the parietal lobe compared to other lobes, especially frontal lobe tumors. Genomic analysis revealed high prevalence of PTEN mutations, and exclusive fusion genes FGFR3-TACC3 and EGFR-SEPT14 in parietal lobe tumors. Differential gene expression showed upregulation of PITX2, HOXB13, and DTHD1, linked to tumor progression, while ALOX15 downregulation increased relapse risk. Copy number alterations, like LINC00290 deletions, were associated with aggressive parietal lobe tumors. Radiomic features, lower GLDM DependanceEntropy (LLL) and higher FirstOrder Mean (HLL), were strongly linked to increase risk.</p><p><strong>Conclusion: </strong>This study highlights poor survival outcomes in GBM patients with parietal lobe tumors. Key genetic alterations, such as PTEN mutations and fusion genes, drive tumor progression and chemoresistance in parietal lobe tumors. The association between radiomic features and survival indicates their potential as non-invasive prognostic biomarkers, which could aid in personalized treatment and improved patient management.</p>\",\"PeriodicalId\":19422,\"journal\":{\"name\":\"Neuroradiology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2025-08-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neuroradiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s00234-025-03742-7\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuroradiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00234-025-03742-7","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Tumor location, genomic alterations, and radiomic features as predictors of survival in glioblastoma: a Multi-Modal analysis.
Purpose: This study aims to identify the impact of tumor location on the survival of glioblastoma (GBM) patients and the associated genetic alterations, using MRI scans from The Cancer Imaging Archive (TCIA) and genomic data from The Cancer Genome Atlas (TCGA). It also seeks to uncover non-invasive radiomic markers related to poor survival outcome for improved prognosis and treatment planning.
Methods: We analysed pre-operative MRI scans and genomic data from 123 GBM patients (TCIA and TCGA). Tumor locations were determined using our in-house tool, "tumorVQ", followed by Kaplan-Meier survival analysis based on tumor position. Genomic analysis included somatic mutations, copy number variations, fusion genes, and differential gene expression to identify factors linked to poor survival. We extracted radiomic features from T1ce MRI scans using pyRadiomics to analyse their relationship with survival outcomes.
Results: Kaplan-Meier analysis showed worse survival for tumors in the parietal lobe compared to other lobes, especially frontal lobe tumors. Genomic analysis revealed high prevalence of PTEN mutations, and exclusive fusion genes FGFR3-TACC3 and EGFR-SEPT14 in parietal lobe tumors. Differential gene expression showed upregulation of PITX2, HOXB13, and DTHD1, linked to tumor progression, while ALOX15 downregulation increased relapse risk. Copy number alterations, like LINC00290 deletions, were associated with aggressive parietal lobe tumors. Radiomic features, lower GLDM DependanceEntropy (LLL) and higher FirstOrder Mean (HLL), were strongly linked to increase risk.
Conclusion: This study highlights poor survival outcomes in GBM patients with parietal lobe tumors. Key genetic alterations, such as PTEN mutations and fusion genes, drive tumor progression and chemoresistance in parietal lobe tumors. The association between radiomic features and survival indicates their potential as non-invasive prognostic biomarkers, which could aid in personalized treatment and improved patient management.
期刊介绍：
Neuroradiology aims to provide state-of-the-art medical and scientific information in the fields of Neuroradiology, Neurosciences, Neurology, Psychiatry, Neurosurgery, and related medical specialities. Neuroradiology as the official Journal of the European Society of Neuroradiology receives submissions from all parts of the world and publishes peer-reviewed original research, comprehensive reviews, educational papers, opinion papers, and short reports on exceptional clinical observations and new technical developments in the field of Neuroimaging and Neurointervention. The journal has subsections for Diagnostic and Interventional Neuroradiology, Advanced Neuroimaging, Paediatric Neuroradiology, Head-Neck-ENT Radiology, Spine Neuroradiology, and for submissions from Japan. Neuroradiology aims to provide new knowledge about and insights into the function and pathology of the human nervous system that may help to better diagnose and treat nervous system diseases. Neuroradiology is a member of the Committee on Publication Ethics (COPE) and follows the COPE core practices. Neuroradiology prefers articles that are free of bias, self-critical regarding limitations, transparent and clear in describing study participants, methods, and statistics, and short in presenting results. Before peer-review all submissions are automatically checked by iThenticate to assess for potential overlap in prior publication.
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