Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Mar 5;16(5):1062.
doi: 10.3390/cancers16051062.

High HER2 Intratumoral Heterogeneity Is a Predictive Factor for Poor Prognosis in Early-Stage and Locally Advanced HER2-Positive Breast Cancer

Affiliations

High HER2 Intratumoral Heterogeneity Is a Predictive Factor for Poor Prognosis in Early-Stage and Locally Advanced HER2-Positive Breast Cancer

Tomonori Tanei et al. Cancers (Basel). .

Abstract

Purpose: Breast cancer tumors frequently have intratumoral heterogeneity (ITH). Tumors with high ITH cause therapeutic resistance and have human epidermal growth factor receptor 2 (HER2) heterogeneity in response to HER2-targeted therapies. This study aimed to investigate whether high HER2 heterogeneity levels were clinically related to a poor prognosis for HER2-targeted adjuvant therapy resistance in primary breast cancers.

Methods: This study included patients with primary breast cancer (n = 251) treated with adjuvant HER2-targeted therapies. HER2 heterogeneity was manifested by the shape of HER2 fluorescence in situ hybridization amplification (FISH) distributed histograms with the HER2 gene copy number within a tumor sample. Each tumor was classified into a biphasic grade graph (high heterogeneity [HH]) group or a monophasic grade graph (low heterogeneity [LH]) group based on heterogeneity. Both groups were evaluated for disease-free survival (DFS) and overall survival (OS) for a median of ten years of annual follow-up.

Results: Of 251 patients with HER2-positive breast cancer, 46 (18.3%) and 205 (81.7%) were classified into the HH and LH groups, respectively. The HH group had more distant metastases and a poorer prognosis than the LH group (DFS: p < 0.001 (HH:63% vs. LH:91% at 10 years) and for the OS: p = 0.012 (HH:78% vs. LH:95% at 10 years).

Conclusions: High HER2 heterogeneity is a poor prognostic factor in patients with HER2-positive breast cancer. A novel approach to heterogeneity, which is manifested by the shape of HER2 FISH distributions, might be clinically useful in the prognosis prediction of patients after HER2 adjuvant therapy.

Keywords: HER2 gene expression; breast carcinoma; breast neoplasms; intratumoral heterogeneity; prognosis.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
HER2 intratumoral heterogeneity was identified by the shape of HER2 FISH amplification distributed histograms with the HER2 gene copy number within a tumor sample (A). Those histograms were classified into two groups: the biphasic grade graph (high heterogeneous [HH] group) and the monophasic biphasic grade graph (low heterogeneous [LH] group) magnification ×400 (B). Additionally, the LH group was divided into the ex-high amplification LH (Ex-High LH) group and the high amplification LH (High LH) group by the ratio of HER2 FISH (mean number of HER2 FISH signals/cell). Representative images on the left were HER2 FISH imaging with HER2 (red signals)/CEP17 (green signals) in tumor cell nuclei (DAPI: blue) magnification ×400.
Figure 2
Figure 2
Disease-free survival (DFS) and overall survival (OS) rates according to HER2 intratumoral heterogeneity. DFS (A) and OS rates (B) of patients with breast cancer comparing the high heterogeneous (HH) group to the low heterogeneous (LH) group (DFS: p < 0.001 (HH group: 63% vs. LH group: 91% at 10 years), and OS: p = 0.012 (HH group: 78% vs. LH group: 95% at 10 years)). DFS rates (C) and OS rates (D) of patients with breast cancer were compared between the HH, Ex-High LH, and High LH groups.

Similar articles

Cited by

References

    1. IJzerman M.J., Berghuis A.S., de Bono J.S., Terstappen L.W. Health Economic Impact of Liquid Biopsies in Cancer Management. Expert Rev. Pharmacoeconomics Outcomes Res. 2018;18:593–599. doi: 10.1080/14737167.2018.1505505. - DOI - PubMed
    1. Dagogo-Jack I., Shaw A.T. Tumour Heterogeneity and Resistance to Cancer Therapies. Nat. Rev. Clin. Oncol. 2018;15:81–94. doi: 10.1038/nrclinonc.2017.166. - DOI - PubMed
    1. Ramón y Cajal S., Sesé M., Capdevila C., Aasen T., De Mattos-Arruda L., Diaz-Cano S.J., Hernández-Losa J., Castellvί J. Clinical Implications of Intratumor Het- erogeneity: Challenges and Opportunities. J. Mol. Med. 2020;98:161–177. doi: 10.1007/s00109-020-01874-2. - DOI - PMC - PubMed
    1. Beca F., Polyak K. Intratumor Heterogeneity in Breast Cancer. Nov. Biomark. Contin. Breast Cancer. 2016;882:169–189. - PubMed
    1. Marusyk A., Polyak K. Tumor Heterogeneity: Causes and Consequences. Biochim. Biophys. Acta (BBA)-Rev. Cancer. 2010;1805:105–117. doi: 10.1016/j.bbcan.2009.11.002. - DOI - PMC - PubMed