Radiogenomic analysis reveals tumor heterogeneity of triple-negative breast cancer

Jiang, Lin; You, Chao; Xiao, Yi; Wang, He; Su, Guan-Hua; Xia, Baojia; Zheng, Rencheng; Zhang, Dandan; Jiang, Yi‐Zhou; Gu, Yajia; Shao, Zhi-Ming

doi:10.1016/j.xcrm.2022.100694

Cited by 36 publications

(35 citation statements)

References 49 publications

(86 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It was demonstrated that patients with high IITH exhibited a significantly poor clinical outcome, regardless of RFS or OS. The consistency with previous studies and external validation in the DUKE DCE-MRI dataset supported the utility of imaging heterogeneity in reflecting cancer prognosis (25,26). Divergent from the holistic view of imaging heterogeneity provided in the present study, a previous work focused on habitat imaging features extracted from the spatial interaction of subregions with poor, moderate, and marked perfusion, yielding a detailed perspective for spatial heterogeneity measurement (27).…”

Section: Discussionsupporting

confidence: 86%

Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets

Su,

Xiao,

You

et al. 2023

Sci. Adv.

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionsupporting

confidence: 86%

Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets

Su,

Xiao,

You

et al. 2023

Sci. Adv.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The development of useful biomarkers may ultimately lead to the development of personalized treatments for breast cancer. Currently, many studies are looking for imaging markers that correlate with prognosis and the results appear promising [33,34]. These feature parameters may be considered as optical biomarkers to provide quantitative information to aid in monitoring morphological changes in tumor microenvironment.…”

Section: Discussionmentioning

confidence: 99%

Detection of pathological response of axillary lymph node metastasis after neoadjuvant chemotherapy in breast cancer using multiphoton microscopy

Zhou

Huang

Kang

et al. 2022

Journal of Biophotonics

View full text Add to dashboard Cite

Neoadjuvant treatment is often considered in breast cancer patients with axillary lymph node involvement, but most of patients do not have a pathologic complete response to therapy. The detection of residual nodal disease has a significant impact on adjuvant therapy recommendations which may improve survival. Here, we investigate whether multiphoton microscopy (MPM) could identify the pathological changes of axillary lymphatic metastasis after neoadjuvant chemotherapy in breast cancer. And furthermore, we find that there are obvious differences in seven collagen morphological features between normal node and residual axillary disease by combining with a semi‐automatic image processing method, and also find that there are significant differences in four collagen features between the effective and no‐response treatment groups. These research results indicate that MPM may help estimate axillary treatment response in the neoadjuvant setting and thereby tailor more appropriate and personalized adjuvant treatments for breast cancer patients.

show abstract

“…Radiomics is a non-invasive approach which can also identify and characterize the different TNBC molecular subtypes, analyzing the spatial domain features and sequential feature obtained by Contrast-Enhanced Magnetic Resonance Imaging (CE-MRI) [ 56 ]. Therefore, radiogenomics, in predicting gene mutations, plays a crucial role in the early detection of various BC subtypes, preventing patients from undergoing invasive procedures.…”

Section: Matching Molecular and Radiological Features To Enhance Char...mentioning

confidence: 99%

A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer

Bellini

Milan

Bordin

et al. 2023

IJMS

View full text Add to dashboard Cite

Radiological imaging is currently employed as the most effective technique for screening, diagnosis, and follow up of patients with breast cancer (BC), the most common type of tumor in women worldwide. However, the introduction of the omics sciences such as metabolomics, proteomics, and molecular genomics, have optimized the therapeutic path for patients and implementing novel information parallel to the mutational asset targetable by specific clinical treatments. Parallel to the “omics” clusters, radiological imaging has been gradually employed to generate a specific omics cluster termed “radiomics”. Radiomics is a novel advanced approach to imaging, extracting quantitative, and ideally, reproducible data from radiological images using sophisticated mathematical analysis, including disease-specific patterns, that could not be detected by the human eye. Along with radiomics, radiogenomics, defined as the integration of “radiology” and “genomics”, is an emerging field exploring the relationship between specific features extracted from radiological images and genetic or molecular traits of a particular disease to construct adequate predictive models. Accordingly, radiological characteristics of the tissue are supposed to mimic a defined genotype and phenotype and to better explore the heterogeneity and the dynamic evolution of the tumor over the time. Despite such improvements, we are still far from achieving approved and standardized protocols in clinical practice. Nevertheless, what can we learn by this emerging multidisciplinary clinical approach? This minireview provides a focused overview on the significance of radiomics integrated by RNA sequencing in BC. We will also discuss advances and future challenges of such radiomics-based approach.

show abstract

Radiogenomic analysis reveals tumor heterogeneity of triple-negative breast cancer

Cited by 36 publications

References 49 publications

Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets

Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets

Detection of pathological response of axillary lymph node metastasis after neoadjuvant chemotherapy in breast cancer using multiphoton microscopy

A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer

Contact Info

Product

Resources

About