Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets.
Guan-Hua SuYi XiaoChao YouRen-Cheng ZhengShen ZhaoShi-Yun SunJia-Yin ZhouLu-Yi LinHe WangZhi-Ming ShaoYa-Jia GuYi-Zhou JiangPublished in: Science advances (2023)
Intratumor heterogeneity (ITH) profoundly affects therapeutic responses and clinical outcomes. However, the widespread methods for assessing ITH based on genomic sequencing or pathological slides, which rely on limited tissue samples, may lead to inaccuracies due to potential sampling biases. Using a newly established multicenter breast cancer radio-multiomic dataset ( n = 1474) encompassing radiomic features extracted from dynamic contrast-enhanced magnetic resonance images, we formulated a noninvasive radiomics methodology to effectively investigate ITH. Imaging ITH (IITH) was associated with genomic and pathological ITH, predicting poor prognosis independently in breast cancer. Through multiomic analysis, we identified activated oncogenic pathways and metabolic dysregulation in high-IITH tumors. Integrated metabolomic and transcriptomic analyses highlighted ferroptosis as a vulnerability and potential therapeutic target of high-IITH tumors. Collectively, this work emphasizes the superiority of radiomics in capturing ITH. Furthermore, we provide insights into the biological basis of IITH and propose therapeutic targets for breast cancers with elevated IITH.
Keyphrases
- poor prognosis
- single cell
- magnetic resonance
- high resolution
- long non coding rna
- rna seq
- contrast enhanced
- lymph node metastasis
- copy number
- climate change
- deep learning
- clinical trial
- squamous cell carcinoma
- human health
- gene expression
- convolutional neural network
- optical coherence tomography
- computed tomography
- fluorescence imaging
- risk assessment
- dna methylation
- genome wide