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

Morganti, Stefania; Ivanova, Mariia; Ferraro, Emanuela; Ascione, Liliana; Vivanet, Grazia; Bonizzi, Giuseppina; Curigliano, Giuseppe; Fusco, Nicola

doi:10.20517/cdr.2022.55

Cited by 15 publications

(8 citation statements)

References 69 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An accurate evaluation of human epidermal growth factor receptor 2 (HER2) expression is crucial for effective breast cancer treatment [ 93 , 94 , 95 , 96 ]. The current approach is transitioning from a binary HER2 assessment to recognizing HER2-low tumors (1+ or 2+ with negative in situ hybridization (ISH)), as emphasized by data with novel treatment, specifically trastuzumab deruxtecan in HER2-low BC [ 97 ].…”

Section: Prognostic and Predictive Models On Immunohistochemistry-sta...mentioning

confidence: 99%

Early Breast Cancer Risk Assessment: Integrating Histopathology with Artificial Intelligence

Ivanova,

Pescia,

Trapani

et al. 2024

Cancers

Self Cite

View full text Add to dashboard Cite

Effective risk assessment in early breast cancer is essential for informed clinical decision-making, yet consensus on defining risk categories remains challenging. This paper explores evolving approaches in risk stratification, encompassing histopathological, immunohistochemical, and molecular biomarkers alongside cutting-edge artificial intelligence (AI) techniques. Leveraging machine learning, deep learning, and convolutional neural networks, AI is reshaping predictive algorithms for recurrence risk, thereby revolutionizing diagnostic accuracy and treatment planning. Beyond detection, AI applications extend to histological subtyping, grading, lymph node assessment, and molecular feature identification, fostering personalized therapy decisions. With rising cancer rates, it is crucial to implement AI to accelerate breakthroughs in clinical practice, benefiting both patients and healthcare providers. However, it is important to recognize that while AI offers powerful automation and analysis tools, it lacks the nuanced understanding, clinical context, and ethical considerations inherent to human pathologists in patient care. Hence, the successful integration of AI into clinical practice demands collaborative efforts between medical experts and computational pathologists to optimize patient outcomes.

show abstract

Section: Prognostic and Predictive Models On Immunohistochemistry-sta...mentioning

confidence: 99%

Early Breast Cancer Risk Assessment: Integrating Histopathology with Artificial Intelligence

Ivanova,

Pescia,

Trapani

et al. 2024

Cancers

Self Cite

View full text Add to dashboard Cite

show abstract

“…One example is represented by activating mutations in the alfa catalytic subunit of PI3K (PI3KCA), found in up to 20% of HER2-positive BCs [48,49]. This gene is known to be involved in PI3K/AKT/mTOR cascade, activated by HER2 overexpression, and its upregulation may lead to increased cell proliferation and tumour progression [50,51]. Recent evidence demonstrates that enrichment of MAP kinase pathway mutations can promote a switch in pathway dependence from PI3K/AKT to MEK/ERK, leading to resistance to anti-HER2 therapies [52].…”

Section: Altered Intracellular Signallingmentioning

confidence: 99%

Unlocking the Resistance to Anti-HER2 Treatments in Breast Cancer: The Issue of HER2 Spatial Distribution

Giugliano

Schianca

Corti

et al. 2023

Cancers

Self Cite

View full text Add to dashboard Cite

Approximately 15% of breast cancers are classified as HER2-positive, with an amplification of the ERBB2 gene and/or an overexpression of the HER2 protein. Up to 30% of HER2-positive breast cancers shows heterogeneity in HER2 expression and different patterns of spatial distribution, i.e., the variability in the distribution and expression of the HER2 protein within a single tumour. Spatial heterogeneity may potentially affect treatment, response, assessment of HER2 status and consequently, may impact on the best treatment strategy. Understanding this feature can help clinicians to predict response to HER2-targeted therapies and patient outcomes, and to fine tune treatment decisions. This review summarizes the available evidence on HER2 heterogeneity and spatial distribution and how this may affect current available treatment choices, exploring possible opportunities for overcoming this issue, such as novel pharmacological agents, belonging to the group of antibody–drug conjugates.

show abstract

“…However, the potential challenges associated with HER2 IHC in the lower range of protein expression have not received sufficient attention [ 62 ]. It is now imperative to refine the performance of HER2 testing, considering all variables that may impact the documentation of HER2-low status in the pathology report [ 52 ]. By understanding the pitfalls of HER2 testing in light of the emerging clinical importance of HER2-low, improvements can be made in test sensitivity, specificity, and reproducibility [ 52 , 62 ].…”

Section: Introduction: Clinicopathological Contextmentioning

confidence: 99%

“…It is now imperative to refine the performance of HER2 testing, considering all variables that may impact the documentation of HER2-low status in the pathology report [ 52 ]. By understanding the pitfalls of HER2 testing in light of the emerging clinical importance of HER2-low, improvements can be made in test sensitivity, specificity, and reproducibility [ 52 , 62 ]. In this article, we address the current issues related to identifying HER2-low BC and offer practical recommendations for optimal testing approaches.…”

Section: Introduction: Clinicopathological Contextmentioning

confidence: 99%

Standardized pathology report for HER2 testing in compliance with 2023 ASCO/CAP updates and 2023 ESMO consensus statements on HER2-low breast cancer

Ivanova,

Porta,

D’Ercole

et al. 2023

Virchows Arch

Self Cite

View full text Add to dashboard Cite

Since the release of the DESTINY-Breast04 (DB-04) trial findings in June 2022, the field of pathology has seen a renaissance of HER2 as a predictive biomarker in breast cancer. The trial focused on patients with metastatic breast cancer who were classified as “HER2-low,” i.e., those with immunohistochemistry (IHC) HER2 1 + or 2 + and negative in situ hybridization (ISH) results. The study revealed that treating these patients with trastuzumab deruxtecan (T-DXd) instead of the oncologist’s chosen chemotherapy led to outstanding improvements in survival. This has challenged the existing binary HER2 pathological classification system, which categorized tumors as either positive (overexpression/amplification) or negative, as per the ASCO/CAP 2018 guideline reaffirmed by ASCO/CAP 2023 guideline update. Given that DB-04 excluded patients with HER2 IHC score 0 status, the results of the ongoing DB-06 trial may shed further light on the potential benefits of T-DXd therapy for these patients. Roughly half of all breast cancers are estimated to belong to the HER2-low category, which does not represent a distinct or specific subtype of cancer. Instead, it encompasses a diverse group of tumors that exhibit clinical, morphological, immunohistochemical, and molecular variations. However, HER2-low offers a distinctive biomarker status that identifies a specific therapeutic regimen (i.e., T-DXd) linked to a favorable prognosis in breast cancer. This unique association emphasizes the importance of accurately identifying these tumors. Differentiating between a HER2 IHC score 0 and score 1 + has not been clinically significant until now. To ensure accurate classification and avoid misdiagnosis, it is necessary to adopt standardized procedures, guidelines, and specialized training for pathologists in interpreting HER2 expression in the lower spectrum. Additionally, the utilization of artificial intelligence holds promise in supporting this endeavor. Here, we address the current state of the art and unresolved issues in assessing HER2-low status, with a particular emphasis on the score 0. We explore the dilemma surrounding the exclusion of HER2-zero patients from potentially beneficial therapy based on traditional HER2 testing. Additionally, we examine the clinical context, considering that DB-04 primarily involved heavily pretreated late-stage metastatic breast cancers. We also delve into emerging evidence suggesting that extrapolating HER2-low status from the original diagnosis may lead to misleading results. Finally, we provide recommendations for conducting high-quality testing and propose a standardized pathology report in compliance with 2023 ASCO/CAP updates and 2023 ESMO consensus statements on HER2-low breast cancer.

show abstract

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

Cited by 15 publications

References 69 publications

Early Breast Cancer Risk Assessment: Integrating Histopathology with Artificial Intelligence

Early Breast Cancer Risk Assessment: Integrating Histopathology with Artificial Intelligence

Unlocking the Resistance to Anti-HER2 Treatments in Breast Cancer: The Issue of HER2 Spatial Distribution

Standardized pathology report for HER2 testing in compliance with 2023 ASCO/CAP updates and 2023 ESMO consensus statements on HER2-low breast cancer

Contact Info

Product

Resources

About