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Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
Published on: October 25, 2011
Quantification of intratumoral heterogeneity using habitat-based MRI radiomics to identify HER2-positive, -low and
Haoquan Chen1, Yulu Liu1,2, Jiaqi Zhao3
1Department of Radiology, Peking University People's Hospital, No. 11, Xizhimen South St, Beijing, 100044, China.
Background:
Human epidermal growth factor receptor 2-targeted (HER2) therapy with antibody-drug conjugates has proven effective for patients with HER2-low breast cancer. However, intratumoral heterogeneity (ITH) poses a great challenge in identifying HER2-low tumors. ITH signatures were developed by quantifying ITH to differentiate HER2-positive, -low and -zero breast cancers.
Methods:
This retrospective study included 614 patients from two institutions. The study was structured into two primary tasks: task 1 was to differentiate between HER2-positive and -negative tumors, followed by task 2 to differentiate HER2-low and -zero tumors. Whole-tumor radiomics features and habitat radiomics features were extracted from MRI to construct the radiomics and ITH signatures. Multivariable logistic regression analysis was used to determine significant independent predictors. A combined model integrating significant clinicopathologic variables, radiomics signature, and ITH signature was developed for task (1) Subsequently, the better-performing model was established using the same approach for task (2) The area under the receiver operating characteristic curve (AUC) was used to assess the performance of each model.
Results:
Task 1 comprised 614 patients (training, n = 348; validation, n = 149; and test cohorts, n = 117). Task 2 encompassed 501 patients (training, n = 283; validation, n = 122; and test cohorts, n = 96). For task1, the ITH signature showed outstanding performance, achieving AUCs of 0.81, 0.81, and 0.81 in the training, validation and test cohorts, respectively. The combined model achieved improved performance, with AUCs of 0.83, 0.84 and 0.83 across the three cohorts, respectively. For task2, the ITH signature maintained superior performance, with AUCs of 0.94, 0.93 and 0.84 across the training, validation and test cohorts, respectively. Multivariable logistic regression analysis indicated that none of the clinicopathologic characteristics were retained as predictors associated with odds of HER2-low tumors.
Conclusions:
Our study developed ITH signatures that quantified ITH using habitat-based MRI radiomics, achieving outstanding performance in differentiating HER2-postive and -negative tumors, and further differentiating HER2-low and -zero breast cancers.
Insights
Intratumoral heterogeneity (ITH) signatures effectively differentiate HER2-positive, HER2-low, and HER2-zero breast cancers using MRI radiomics. This approach aids in identifying patients who can benefit from HER2-targeted therapies.
Area of Science:
- Oncology
- Radiology
- Biomedical Imaging
Background:
- HER2-targeted therapy is effective for HER2-low breast cancer.
- Intratumoral heterogeneity (ITH) complicates the identification of HER2-low tumors.
- Quantifying ITH is crucial for accurate tumor classification.
Purpose of the Study:
- To develop and validate ITH signatures for differentiating HER2 expression levels in breast cancer.
- To assess the performance of radiomics and ITH signatures in classifying HER2-positive, HER2-low, and HER2-zero breast cancers.
- To explore the utility of habitat-based MRI radiomics in capturing ITH.
Main Methods:
- Retrospective study of 614 breast cancer patients.
- Extraction of whole-tumor and habitat radiomics features from MRI.
- Development of radiomics and ITH signatures.
- Multivariable logistic regression and AUC analysis to evaluate model performance.
Main Results:
- ITH signatures demonstrated high performance in differentiating HER2-positive/negative tumors (AUCs up to 0.83) and HER2-low/zero tumors (AUCs up to 0.94).
- A combined model integrating clinicopathologic, radiomics, and ITH signatures improved classification accuracy.
- Clinicopathologic characteristics were not significant predictors of HER2-low tumors.
Conclusions:
- Habitat-based MRI radiomics can effectively quantify ITH.
- Developed ITH signatures show significant promise for accurate breast cancer subtyping.
- This method can improve patient selection for HER2-targeted therapies.
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