Studying Lymphatic Metastasis in Breast Cancer: Current Models, Strategies, and Clinical Perspectives

To, Briana; Isaac, Daniel; Andrechek, Eran R.

doi:10.1007/s10911-020-09460-5

Cited by 23 publications

(13 citation statements)

References 111 publications

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“…Specific and sensitive visualisation of LNMs in early-stage cancer can maximise the benefits of early tumour staging and guidance of treatment selection [ 32 , 33 ]. We developed a unique ATP-responsive and breast cancer-targeting imaging probe to visualise MLNs in breast cancer in an actively targeted, specific, and sensitive manner.…”

Section: Discussionmentioning

confidence: 99%

Sensitive and specific detection of breast cancer lymph node metastasis through dual-modality magnetic particle imaging and fluorescence molecular imaging: a preclinical evaluation

Wang

Shi

et al. 2022

Eur J Nucl Med Mol Imaging

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Purpose A sensitive and specific imaging method to detect metastatic cancer cells in lymph nodes to detect the early-stage breast cancer is still a challenge. The purpose of this study was to investigate a novel breast cancer–targeting and tumour microenvironment ATP-responsive superparamagnetic iron oxide nanoparticles (SPIOs) imaging probe (abbreviated as SPIOs@A-T) that was developed to detect lymph node metastasis through fluorescence molecular imaging (FMI) and magnetic particle imaging (MPI). Methods The conjugation of the targeted peptide CREKA and SPIOs was via linker sulfo-SMCC, while the dsDNA-Cy5.5 was modified on SPIOs through the conjugation between maleimide group in sulfo-SMCC and sulfydryl group in dsDNA-Cy5.5. SPIOs@A-T was characterised for its imaging properties, targeting ability and toxicity in vitro. Mice with metastatic lymph node (MLN) of breast cancer were established to evaluate the FMI and MPI imaging strategy in vivo. Healthy mice with normal lymph node (NLN) were used as control group. Histological examination and biosafety evaluation were performed for further assessment. Results After injection with SPIOs@A-T, the obvious high fluorescent intensity and MPI signal were observed in MLN group than those in NLN group. FMI can specifically light up MLN using an ATP-responsive fluorescence design. On the other hand, MPI could complement the limitation of imaging depth from FMI and could detect MLN more sensitively. Besides, the biosafety evaluation results showed SPIOs@A-T had no detectable biological toxicity. Conclusion SPIOs@A-T imaging probe in combination with FMI and MPI can provide a promising novel method for the precise detection of MLN in vivo.

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Section: Discussionmentioning

confidence: 99%

Sensitive and specific detection of breast cancer lymph node metastasis through dual-modality magnetic particle imaging and fluorescence molecular imaging: a preclinical evaluation

Wang

Shi

et al. 2022

Eur J Nucl Med Mol Imaging

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“…ALNM is not only an important prognostic factor for BC but also a key indicator for determining the stage and guiding treatment of this disease [ 23 ]. The present study developed and validated a radiomics nomogram that was constructed by the intratumoral combined peritumoral radiomics signature, the MR-reported maximum lesion diameter, and the MR-reported ALN status.…”

Section: Discussionmentioning

confidence: 99%

Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer Based on Intratumoral and Peritumoral DCE‐MRI Radiomics Nomogram

Liu

Zhu

et al. 2022

Contrast Media & Molecular Imaging

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Objective. To investigate the value of preoperative prediction of breast cancer axillary lymph node metastasis based on intratumoral and peritumoral dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) radiomics nomogram. Material and Methods. In this study, a radiomics model was developed based on a training cohort involving 250 patients with breast cancer (BC) who had undergone axillary lymph node (ALN) dissection between June 2019 and January 2021. The intratumoral and peritumoral radiomics features were extracted from the second postcontrast images of DCE-MRI. Based on filtered radiomics features, the radiomics signature was built by using the least absolute shrinkage and selection operator method. The Support Vector Machines (SVM) learning algorithm was used to construct intratumoral, periatumoral, and intratumoral combined periatumoral models for predicting axillary lymph node metastasis (ALNM) in BC. Nomogram performance was determined by its discrimination, calibration, and clinical value. Multivariable logistic regression was adopted to establish a radiomics nomogram. Results. The intratumoral combined peritumoral radiomics signature, which was composed of fifteen ALN status-related features, showed the best predictive performance and was associated with ALNM in both the training and validation cohorts ( P < 0.001 ). The prediction efficiency of the intratumoral combined peritumoral radiomics model was higher than that of the intratumoral radiomics model and the peritumoral radiomics model. The AUCs of the training and verification cohorts were 0.867 and 0.785, respectively. The radiomics nomogram, which incorporated the radiomics signature, MR-reported ALN status, and MR-reported maximum diameter of the lesion, showed good calibration and discrimination in the training (AUC = 0.872) and validation cohorts (AUC = 0.863). Conclusion. The intratumoral combined peritumoral radiomics model derived from DCE-MRI showed great predictive value for ALNM and may help to improve clinical decision-making for BC.

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“…The most common site of breast cancer is the lymph node. Lymph node metastasis is also one of the important prognostic indicators of patients ( Nathanson et al, 2018 ; To et al, 2020 ). According to previous studies, there are many factors affecting the mechanism of lymph node metastasis in breast cancer, such as the role of chemokines, gene expression, gastrin-releasing peptide and so on ( Eccles et al, 2007 ; Ni et al, 2012 ; Hayasaka et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

PAIP2 is a potential diagnostic and prognostic biomarker of breast cancer and is associated with immune infiltration

Wang

Jiang

et al. 2022

Front. Genet.

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Breast cancer is the second highest incidence of cancer in the world. It is of great significance to find biomarkers to diagnose breast cancer and predict the prognosis of breast cancer patients. PAIP2 is a poly (A) -binding protein interacting protein that regulates the expression of VEGF. However, the possible role of PAIP2 in the progression of breast cancer is still unknown. RT-qRCR and Western blotting were used to verify the expression of PAIP2 in breast cancer cells and normal breast cells. The data of breast cancer samples were obtained in the TCGA database and the HPA database to analyze the expression of PAIP2 in breast cancer samples. Transwell experiment and CCK8 experiment confirmed the changes in the invasion and proliferation ability of PAIP2 after siRNA was down-regulated. Using bioinformatics technology to explore the prognostic value of PAIP2 and its possible biological function, and its effect on tumor immunity and immunotherapy. Studies have shown that PAIP2 has higher expression in breast cancer tissues and breast cancer cells. PAIP2 can promote the proliferation and invasion of breast cancer cells and has significantly high expression in higher tumor stages. The high expression of PAIP2 is associated with better OS in breast cancer patients and is negatively correlated with most chemotherapeutic drug sensitivity and IPS in cancer immunotherapy. Our study explored the potential value of PAIP2 as a biomarker for diagnosis and prognosis and may predict the efficacy of immunotherapy, providing reference for the follow-up study on the role of PAIP2 in breast cancer.

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Studying Lymphatic Metastasis in Breast Cancer: Current Models, Strategies, and Clinical Perspectives

Cited by 23 publications

References 111 publications

Sensitive and specific detection of breast cancer lymph node metastasis through dual-modality magnetic particle imaging and fluorescence molecular imaging: a preclinical evaluation

Sensitive and specific detection of breast cancer lymph node metastasis through dual-modality magnetic particle imaging and fluorescence molecular imaging: a preclinical evaluation

Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer Based on Intratumoral and Peritumoral DCE‐MRI Radiomics Nomogram

PAIP2 is a potential diagnostic and prognostic biomarker of breast cancer and is associated with immune infiltration

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