Dataset Information

Towards integration of ⁶⁴Cu-DOTA-trastuzumab PET-CT and MRI with mathematical modeling to predict response to neoadjuvant therapy in HER2?+?breast cancer.

ABSTRACT: While targeted therapies exist for human epidermal growth factor receptor 2 positive (HER2?+) breast cancer, HER2?+?patients do not always respond to therapy. We present the results of utilizing a biophysical mathematical model to predict tumor response for two HER2?+?breast cancer patients treated with the same therapeutic regimen but who achieved different treatment outcomes. Quantitative data from magnetic resonance imaging (MRI) and ⁶⁴Cu-DOTA-trastuzumab positron emission tomography (PET) are used to estimate tumor density, perfusion, and distribution of HER2-targeted antibodies for each individual patient. MRI and PET data are collected prior to therapy, and follow-up MRI scans are acquired at a midpoint in therapy. Given these data types, we align the data sets to a common image space to enable model calibration. Once the model is parameterized with these data, we forecast treatment response with and without HER2-targeted therapy. By incorporating targeted therapy into the model, the resulting predictions are able to distinguish between the two different patient responses, increasing the difference in tumor volume change between the two patients by?>?40%. This work provides a proof-of-concept strategy for processing and integrating PET and MRI modalities into a predictive, clinical-mathematical framework to provide patient-specific predictions of HER2?+?treatment response.

SUBMITTER: Jarrett AM

PROVIDER: S-EPMC7688955 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Towards integration of <sup>64</sup>Cu-DOTA-trastuzumab PET-CT and MRI with mathematical modeling to predict response to neoadjuvant therapy in HER2 + breast cancer.

Jarrett Angela M AM Hormuth David A DA Adhikarla Vikram V Sahoo Prativa P Abler Daniel D Tumyan Lusine L Schmolze Daniel D Mortimer Joanne J Rockne Russell C RC Yankeelov Thomas E TE

Scientific reports 20201125 1

While targeted therapies exist for human epidermal growth factor receptor 2 positive (HER2 +) breast cancer, HER2 + patients do not always respond to therapy. We present the results of utilizing a biophysical mathematical model to predict tumor response for two HER2 + breast cancer patients treated with the same therapeutic regimen but who achieved different treatment outcomes. Quantitative data from magnetic resonance imaging (MRI) and <sup>64</sup>Cu-DOTA-trastuzumab positron emission tomograp ...[more]

PMID: 33239688

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Project description:UnlabelledWomen with human epidermal growth factor receptor 2 (HER2)-positive breast cancer are candidates for treatment with the anti-HER2 antibody trastuzumab. Assessment of HER2 status in recurrent disease is usually made by core needle biopsy of a single lesion, which may not represent the larger tumor mass or other sites of disease. Our long-range goal is to develop PET of radiolabeled trastuzumab for systemically assessing tumor HER2 expression and identifying appropriate use of anti-HER2 therapies. The purpose of this study was to evaluate PET/CT of (64)Cu-DOTA-trastuzumab for detecting and measuring tumor uptake of trastuzumab in patients with HER2-positive metastatic breast cancer.MethodsEight women with biopsy-confirmed HER2-positive metastatic breast cancer and no anti-HER2 therapy for 4 mo or longer underwent complete staging, including (18)F-FDG PET/CT. For 6 of the 8 patients, (64)Cu-DOTA-trastuzumab injection (364-512 MBq, 5 mg of trastuzumab) was preceded by trastuzumab infusion (45 mg). PET/CT (PET scan duration 1 h) was performed 21-25 (day 1) and 47-49 (day 2) h after (64)Cu-DOTA-trastuzumab injection. Scan fields of view were chosen on the basis of (18)F-FDG PET/CT. Tumor detection sensitivity and uptake analyses were limited to lesions identifiable on CT; lesions visualized relative to adjacent tissue on PET were considered PET-positive. Radiolabel uptake in prominent lesions was measured as maximum single-voxel standardized uptake value (SUVmax).ResultsLiver uptake of (64)Cu was reduced approximately 75% with the 45-mg trastuzumab predose, without significant effect on tumor uptake. The study included 89 CT-positive lesions. Detection sensitivity was 77%, 89%, and 93% for day 1, day 2, and (18)F-FDG, respectively. On average, tumor uptake was similar for (64)Cu-DOTA-trastuzumab and (18)F-FDG (SUVmax and range, 8.1 and 3.0-22.5 for day 1 [n = 48]; 8.9 and 0.9-28.9 for day 2 [n = 38]; 9.7 and 3.3-25.4 for (18)F-FDG [n = 56]), but same-lesion SUVmax was not correlated between the 2 radiotracers. No toxicities were observed, and estimated radiation dose from (64)Cu-DOTA-trastuzumab was similar to (18)F-FDG.Conclusion(64)Cu-DOTA-trastuzumab visualizes HER2-positive metastatic breast cancer with high sensitivity and is effective in surveying disseminated disease. A 45-mg trastuzumab predose provides a (64)Cu-DOTA-trastuzumab biodistribution favorable for tumor imaging. (64)Cu-DOTA-trastuzumab PET/CT warrants further evaluation for assessing tumor HER2 expression and individualizing treatments that include trastuzumab.

Project description:The development of improved breast cancer screening methods is hindered by a lack of cancer-specific imaging agents and effective small-animal models to test them. The purpose of this study was to evaluate 64Cu-DOTA-alendronate as a mammary microcalcification-targeting PET imaging agent, using an ideal rat model. Our long-term goal is to develop 64Cu-DOTA-alendronate for the detection and noninvasive differentiation of malignant versus benign breast tumors with PET. Methods: DOTA-alendronate was synthesized, radiolabeled with 64Cu, and administered to normal or tumor-bearing aged, female, retired breeder Sprague-Dawley rats for PET imaging. Mammary tissues were subsequently labeled and imaged with light, confocal, and electron microscopy to verify microcalcification targeting specificity of DOTA-alendronate and elucidate the histologic and ultrastructural characteristics of the microcalcifications in different mammary tumor types. Tumor uptake, biodistribution, and dosimetry studies were performed to evaluate the efficacy and safety of 64Cu-DOTA-alendronate. Results:64Cu-DOTA-alendronate was radiolabeled with a 98% yield. PET imaging using aged, female, retired breeder rats showed specific binding of 64Cu-DOTA-alendronate in mammary glands and mammary tumors. The highest uptake of 64Cu-DOTA-alendronate was in malignant tumors and the lowest uptake in benign tumors and normal mammary tissue. Confocal analysis with carboxyfluorescein-alendronate confirmed the microcalcification binding specificity of alendronate derivatives. Biodistribution studies revealed tissue alendronate concentrations peaking within the first hour, then decreasing over the next 48 h. Our dosimetric analysis demonstrated a 64Cu effective dose within the acceptable range for clinical PET imaging agents and the potential for translation into human patients. Conclusion:64Cu-DOTA-alendronate is a promising PET imaging agent for the sensitive and specific detection of mammary tumors as well as the differentiation of malignant versus benign tumors based on absolute labeling uptake.

Project description:Current noninvasive imaging methods for monitoring immune response were largely developed for interrogation of the local reaction. This study developed the radiotracer 64Cu-labeled anti-CD11b (64Cu-αCD11b) for longitudinal assessment of local and systemic immune response involving mobilization of CD11b+ myeloid cells by small-animal PET/CT. Methods: Acute or chronic inflammation in the ears of BALB/c mice was induced by 12-o-tetradecanoylphorbol-13-acetate. Acute lung inflammation was induced by intratracheal lipopolysaccharide inoculation. αCD11b was conjugated with p-SCN-Bn-DOTA followed by labeling with 64Cu. PET/CT and biodistribution were evaluated at different times after intravenous injection of 64Cu-αCD11b. Cell populations from bone marrow (BM) and spleen were analyzed by flow cytometry. Results: 64Cu-αCD11b was primarily taken up by BM and spleen in control mice. In comparison, 64Cu-αCD11b uptake was significantly reduced in the BM and spleen of CD11b-knockout mice, indicating that 64Cu-αCD11b selectively homed to CD11b+ myeloid cells in vivo. In mice with ear inflammation, for the local inflammatory response, 64Cu-αCD11b PET/CT revealed significantly higher 64Cu-αCD11b uptake in the inflamed ears in the acute inflammation phase than the chronic phase, consistent with markedly increased infiltration of CD11b+ cells into the inflammatory lesions at the acute phase. Moreover, imaging of 64Cu-αCD11b also showed the difference in mouse systemic response for different inflammatory stages. Compared with uptake in control mice, BM 64Cu-αCD11b uptake in mice with ear inflammation was significantly lower in the acute phase and higher in the chronic phase, reflecting an initial mobilization of CD11b+ cells from the BM to the inflammatory foci followed by a compensatory regeneration of CD11b+ myeloid cells in the BM. Similarly, in mice with lung inflammation, 64Cu-αCD11b PET/CT readily detected acute lung inflammation and recruitment of CD11b+ myeloid cells from the BM. Immunohistochemistry staining and flow cytometry results confirmed the noninvasive imaging of PET/CT. Conclusion: 64Cu-αCD11b PET/CT successfully tracked ear and pulmonary inflammation in mice and differentiated acute from chronic inflammation at the local and systemic levels. 64Cu-αCD11b PET/CT is a robust quantitative method for imaging of local and systemic immune responses.

Dataset Information

Towards integration of ⁶⁴Cu-DOTA-trastuzumab PET-CT and MRI with mathematical modeling to predict response to neoadjuvant therapy in HER2?+?breast cancer.

Publications

Towards integration of <sup>64</sup>Cu-DOTA-trastuzumab PET-CT and MRI with mathematical modeling to predict response to neoadjuvant therapy in HER2 + breast cancer.

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Dataset Information

Towards integration of 64Cu-DOTA-trastuzumab PET-CT and MRI with mathematical modeling to predict response to neoadjuvant therapy in HER2?+?breast cancer.

Publications

Towards integration of <sup>64</sup>Cu-DOTA-trastuzumab PET-CT and MRI with mathematical modeling to predict response to neoadjuvant therapy in HER2 + breast cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Towards integration of ⁶⁴Cu-DOTA-trastuzumab PET-CT and MRI with mathematical modeling to predict response to neoadjuvant therapy in HER2?+?breast cancer.