Tumor location, genomic alterations, and radiomic features as predictors of survival in glioblastoma: a Multi-Modal analysis.

IF 2.6 3区医学 Q2 CLINICAL NEUROLOGY

Neuroradiology Pub Date : 2025-08-12 DOI:10.1007/s00234-025-03742-7

Kavita Kundal, K Venkateswara Rao, Sandeep Kumar Dhanda, Neeraj Kumar, Rahul Kumar

{"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":"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.","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}

引用次数: 0

Abstract

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.

查看原文本刊更多论文

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。

目的：本研究旨在利用来自癌症成像档案（TCIA）的MRI扫描和来自癌症基因组图谱（TCGA）的基因组数据，确定肿瘤位置对胶质母细胞瘤（GBM）患者生存的影响以及相关的遗传改变。它还寻求发现与不良生存结果相关的非侵入性放射学标志物，以改善预后和治疗计划。方法：我们分析了123例GBM患者（TCIA和TCGA）的术前MRI扫描和基因组数据。使用我们的内部工具“tumorVQ”确定肿瘤位置，然后根据肿瘤位置进行Kaplan-Meier生存分析。基因组分析包括体细胞突变、拷贝数变异、融合基因和差异基因表达，以确定与生存率低相关的因素。我们使用pyRadiomics从T1ce MRI扫描中提取放射学特征，分析它们与生存结果的关系。结果：Kaplan-Meier分析显示，顶叶肿瘤的生存率较其他叶差，尤其是额叶肿瘤。基因组分析显示，在顶叶肿瘤中，PTEN突变和FGFR3-TACC3和EGFR-SEPT14的特异性融合基因非常普遍。差异基因表达显示PITX2、HOXB13和DTHD1的上调与肿瘤进展有关，而ALOX15的下调增加了复发风险。拷贝数改变，如LINC00290缺失，与侵袭性顶叶肿瘤相关。放射学特征、较低的GLDM依赖熵（LLL）和较高的第一der平均值（HLL）与风险增加密切相关。结论：本研究强调了GBM合并顶叶肿瘤患者的生存预后较差。关键的遗传改变，如PTEN突变和融合基因，驱动肿瘤进展和顶叶肿瘤的化疗耐药。放射学特征与生存之间的关联表明它们作为非侵入性预后生物标志物的潜力，可以帮助个性化治疗和改善患者管理。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Neuroradiology 医学-核医学

CiteScore

5.30

自引率

3.60%

发文量

214

审稿时长

4-8 weeks

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.