Validity and utility of HER2/ERBB2 copy number variation assessed in liquid biopsies from breast cancer patients: A systematic review

Verschoor, Noortje; Deger, Teoman; Jager, Agnes; Sleijfer, Stefan; Wilting, Saskia M.; Martens, John W.M.

doi:10.1016/j.ctrv.2022.102384

Cited by 15 publications

(12 citation statements)

References 84 publications

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“…One of them studied circulating tumor ctDNA with disease-free survival in patients with BC, 148 another described the clinical uses of LB in BC, 149 and the last one reported the validity of HER2/ERBB2 copy number variation in LB from BC patients. 150 This is the first SR aimed at establishing the main biomarkers obtained by LB, useful for the early diagnosis of BC. This evidence is highly relevant because the identification of biomarkers in the early diagnosis of BC would undoubtedly be valuable in reducing mortality rates resulting from this neoplasm.…”

Section: Discussionmentioning

confidence: 99%

Cancer Biomarkers in Liquid Biopsy for Early Detection of Breast Cancer: A Systematic Review

Duque

Manterola

Otzen

et al. 2022

Clin Med Insights Oncol

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Background: Breast cancer (BC) is the most common neoplasm in women worldwide. Liquid biopsy (LB) is a non-invasive diagnostic technique that allows the analysis of biomarkers in different body fluids, particularly in peripheral blood and also in urine, saliva, nipple discharge, volatile respiratory fluids, nasal secretions, breast milk, and tears. The objective was to analyze the available evidence related to the use of biomarkers obtained by LB for the early diagnosis of BC. Methods: Articles related to the use of biomarkers for the early diagnosis of BC due to LB, published between 2010 and 2022, from the databases (WoS, EMBASE, PubMed, and SCOPUS) were included. The MInCir diagnostic scale was applied in the articles to determine their methodological quality (MQ). Descriptive statistics were used, as well as determination of weighted averages of each variable, to analyze the extracted data. Sensitivity, specificity, and area under the curve values for specific biomarkers (individual or in panels) are described. Results: In this systematic review (SR), 136 articles met the selection criteria, representing 17 709 patients with BC. However, 95.6% were case-control studies. In 96.3% of cases, LB was performed in peripheral blood samples. Most of the articles were based on microRNA (miRNA) analysis. The mean MQ score was 25/45 points. Sensitivity, specificity, and area under the curve values for specific biomarkers (individual or in panels) have been found. Conclusions: The determination of biomarkers through LB is a useful mechanism for the diagnosis of BC. The analysis of miRNA in peripheral blood is the most studied methodology. Our results indicate that LB has a high sensitivity and specificity for the diagnosis of BC, especially in early stages.

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Section: Discussionmentioning

confidence: 99%

Cancer Biomarkers in Liquid Biopsy for Early Detection of Breast Cancer: A Systematic Review

Duque

Manterola

Otzen

et al. 2022

Clin Med Insights Oncol

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“…Further bias in HER2 assessment may result from sampling errors [56] . In the case of metastatic recurrence, guidelines recommend repeating HER2 testing in a metastatic site, if tissue sample is available, although a new biopsy cannot always be feasible [8] .…”

Section: Technical Pitfallsmentioning

confidence: 99%

“…In the case of metastatic recurrence, guidelines recommend repeating HER2 testing in a metastatic site, if tissue sample is available, although a new biopsy cannot always be feasible [ 8 ] . Additionally, false-negative results can be caused by technical pitfalls, as frequently occurs in bone lesions, or by sampling bias due to intratumor heterogeneity [ 57 ] .…”

Section: Technical Pitfallsmentioning

confidence: 99%

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Loss of HER2 in breast cancer: biological mechanisms and technical pitfalls

Morganti¹,

Ivanova²,

Ferraro³

et al. 2022

Cancer Drug Resist

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Loss of HER2 in previously HER2-positive breast tumors is not rare, occurring in up to 50% of breast cancers; however, clinical research and practice underestimate this issue. Many studies have reported the loss of HER2 after neoadjuvant therapy and at metastatic relapse and identified clinicopathological variables more frequently associated with this event. Nevertheless, the biological mechanisms underlying HER2 loss are still poorly understood. HER2 downregulation, intratumoral heterogeneity, clonal selection, and true subtype switch have been suggested as potential causes of HER2 loss, but translational studies specifically investigating the biology behind HER2 loss are virtually absent. On the other side, technical pitfalls may justify HER2 loss in some of these samples. The best treatment strategy for patients with HER2 loss is currently unknown. Considering the prevalence of this phenomenon and its apparent correlation with worse outcomes, we believe that correlative studies specifically addressing HER2 loss are warranted.

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“…Prior to the introduction of HER2-targeted drugs such as trastuzumab and patolizumab, HER2-positive patients had high recurrence rates and poor survival outcomes (3,5). Trastuzumab considerably increased progression-free survival and overall survival in patients with early and advanced HER2-positive breast cancer, according to landmark trial data till 2006 (5)(6)(7).. An accurate evaluation of HER2 status is essential in the treatment of breast cancer since HER2-targeted therapy is only effective in tumors with HER2 overexpression and/ or gene amplification (7)(8)(9).. Currently, in situ hybridization to assess HER2 gene amplification and immunohistochemistry (IHC) to assess protein overexpression are still the primary methods to detect HER2 expression status (10,11).…”

Section: Introductionmentioning

confidence: 99%

Deep learning radiomics model based on breast ultrasound video to predict HER2 expression status

et al. 2023

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PurposeThe detection of human epidermal growth factor receptor 2 (HER2) expression status is essential to determining the chemotherapy regimen for breast cancer patients and to improving their prognosis. We developed a deep learning radiomics (DLR) model combining time-frequency domain features of ultrasound (US) video of breast lesions with clinical parameters for predicting HER2 expression status.Patients and MethodsData for this research was obtained from 807 breast cancer patients who visited from February 2019 to July 2020. Ultimately, 445 patients were included in the study. Pre-operative breast ultrasound examination videos were collected and split into a training set and a test set. Building a training set of DLR models combining time-frequency domain features and clinical features of ultrasound video of breast lesions based on the training set data to predict HER2 expression status. Test the performance of the model using test set data. The final models integrated with different classifiers are compared, and the best performing model is finally selected.ResultsThe best diagnostic performance in predicting HER2 expression status is provided by an Extreme Gradient Boosting (XGBoost)-based time-frequency domain feature classifier combined with a logistic regression (LR)-based clinical parameter classifier of clinical parameters combined DLR, particularly with a high specificity of 0.917. The area under the receiver operating characteristic curve (AUC) for the test cohort was 0.810.ConclusionOur study provides a non-invasive imaging biomarker to predict HER2 expression status in breast cancer patients.

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Validity and utility of HER2/ERBB2 copy number variation assessed in liquid biopsies from breast cancer patients: A systematic review

Cited by 15 publications

References 84 publications

Cancer Biomarkers in Liquid Biopsy for Early Detection of Breast Cancer: A Systematic Review

Cancer Biomarkers in Liquid Biopsy for Early Detection of Breast Cancer: A Systematic Review

Loss of HER2 in breast cancer: biological mechanisms and technical pitfalls

Deep learning radiomics model based on breast ultrasound video to predict HER2 expression status

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