Top

Breast Cancer Research and Treatment

Published in:

Open Access 27-05-2022 | Breast Cancer | Clinical trial

The risk of PD-L1 expression misclassification in triple-negative breast cancer

Authors: Shani Ben Dori, Asaf Aizic, Asia Zubkov, Shlomo Tsuriel, Edmond Sabo, Dov Hershkovitz

Published in: Breast Cancer Research and Treatment | Issue 2/2022

Abstract

Purpose

Stratification of patients with triple-negative breast cancer (TNBC) for anti-PD-L1 therapy is based on PD-L1 expression in tumor biopsies. This study sought to evaluate the risk of PD-L1 misclassification.

Methods

We conducted a high-resolution analysis on ten surgical specimens of TNBC. First, we determined PD-L1 expression pattern distribution via manual segmentation and measurement of 6666 microscopic clusters of positive PD-L1 immunohistochemical staining. Then, based on these results, we generated a computer model to calculate the effect of the positive PD-L1 fraction, aggregate size, and distribution of PD-L1 positive cells on the diagnostic accuracy.

Results

Our computer-based model showed that larger aggregates of PD-L1 positive cells and smaller biopsy size were associated with higher fraction of false results (P < 0.001, P < 0.001, respectively). Additionally, our model showed a significant increase in error rate when the fraction of PD-L1 expression was close to the cut-off (error rate of 12.1%, 0.84%, and 0.65% for PD-L1 positivity of 0.5–1.5%, ≤ 0.5% ,and ≥ 1.5%, respectively, P < 0.0001). Interestingly, false positive results were significantly higher than false negative results (0.51–22.62%, with an average of 6.31% versus 0.11–11.36% with an average of 1.58% for false positive and false negative results, respectively, P < 0.05). Furthermore, heterogeneous tumors with different aggregate sizes in the same tumor, were associated with increased rate of false results in comparison to homogenous tumors (P < 0.001).

Conclusion

Our model can be used to estimate the risk of PD-L1 misclassification in biopsies, with potential implications for treatment decisions.

Available only for authorised users

Doepker MP, Holt SD, Durkin MW et al (2018) Triple-negative breast cancer: a comparison of race and survival. Am Surg 84:881–887. https://doi.org/10.1177/000313481808400636CrossRefPubMed

den Brok WD, Speers CH, Gondara L et al (2017) Survival with metastatic breast cancer based on initial presentation, de novo versus relapsed. Breast Cancer Res Treat 161:549–556. https://doi.org/10.1007/s10549-016-4080-9CrossRef

Yin L, Duan JJ, Bian XW, Yu SC (2020) Triple-negative breast cancer molecular subtyping and treatment progress. Breast Cancer Res 22:1–13. https://doi.org/10.1186/s13058-020-01296-5CrossRef

Narayan P, Wahby S, Gao JJ et al (2020) FDA approval summary: atezolizumab plus paclitaxel protein-bound for the treatment of patients with advanced or metastatic TNBC whose tumors express PD-L1. Clin Cancer Res 26:2284–2289. https://doi.org/10.1158/1078-0432.CCR-19-3545CrossRefPubMed

Csőszi T, Fülöp A, Gottfried M et al (2016) Pembrolizumab versus chemotherapy for PD-L1–positive non–small-cell lung cancer. N Engl J Med. https://doi.org/10.1056/NEJMoa1606774CrossRefPubMed

Zhang T, Xie J, Arai S et al (2016) The efficacy and safety of anti-PD-1/PD-L1 antibodies for treatment of advanced or refractory cancers: a meta-analysis. Oncotarget 7:73068–73079. https://doi.org/10.18632/oncotarget.12230CrossRefPubMedPubMedCentral

Philips GK, Atkins M (2015) Therapeutic uses of anti-PD-1 and anti-PD-L1 antibodies. Int Immunol 27:39–46. https://doi.org/10.1093/intimm/dxu095CrossRefPubMed

Emens LA, Adams S, Barrios CH et al (2021) First-line atezolizumab plus nab-paclitaxel for unresectable, locally advanced, or metastatic triple-negative breast cancer: IMpassion130 final overall survival analysis. Ann Oncol 32:983–993. https://doi.org/10.1016/j.annonc.2021.05.355CrossRefPubMed

Schmid P, Adams S, Rugo HS et al (2018) Atezolizumab and nab-paclitaxel in advanced triple-negative breast cancer. N Engl J Med 379:2108–2121. https://doi.org/10.1056/nejmoa1809615CrossRefPubMed

10.

Di Spazio L, Rivano M, Cancanelli L et al (2022) The degree of programmed death-ligand 1 (PD-L1) positivity as a determinant of outcomes in metastatic triple-negative breast cancer treated with first-line immune checkpoint inhibitors. Cureus 1:1–5. https://doi.org/10.7759/cureus.21065CrossRef

11.

Badve SS, Penault-Llorca F, Reis-Filho JS et al (2021) Determining PD-L1 status in patients with triple-negative breast cancer: lessons learned From IMpassion130. JNCI J Natl Cancer Inst 00:1–12. https://doi.org/10.1093/jnci/djab121CrossRef

12.

Schmid P, Cortes J, Pusztai L et al (2020) Pembrolizumab for early triple-negative breast cancer. N Engl J Med 382:810–821. https://doi.org/10.1056/nejmoa1910549CrossRefPubMed

13.

Wang Y, Zhou S, Yang F et al (2019) Treatment-related adverse events of PD-1 and PD-L1 inhibitors in clinical trials: a systematic review and meta-analysis. JAMA Oncol 5:1008–1019. https://doi.org/10.1001/jamaoncol.2019.0393CrossRefPubMedPubMedCentral

14.

Gagné A, Wang E, Bastien N et al (2019) Impact of specimen characteristics on PD-L1 testing in non-small cell lung cancer: validation of the IASLC PD-L1 testing recommendations. J Thorac Oncol 14:2062–2070. https://doi.org/10.1016/j.jtho.2019.08.2503CrossRefPubMed

15.

Focke CM, Decker T, Van Diest PJ (2016) The reliability of histological grade in breast cancer core needle biopsies depends on biopsy size: a comparative study with subsequent surgical excisions. Histopathology 69:1047–1054. https://doi.org/10.1111/his.13036CrossRefPubMed

16.

McLaughlin J, Han G, Schalper KA et al (2016) Quantitative assessment of the heterogeneity of PD-L1 expression in non–small-cell lung cancer. JAMA Oncol 2:46–54. https://doi.org/10.1001/jamaoncol.2015.3638CrossRefPubMedPubMedCentral

17.

Munari E, Zamboni G, Lunardi G et al (2018) PD-L1 expression heterogeneity in non-small cell lung cancer: defining criteria for harmonization between biopsy specimens and whole sections. J Thorac Oncol 13:1113–1120. https://doi.org/10.1016/j.jtho.2018.04.017CrossRefPubMed

18.

Madore J, Vilain RE, Menzies AM et al (2015) PD-L1 expression in melanoma shows marked heterogeneity within and between patients: Implications for anti-PD-1/PD-L1 clinical trials. Pigment Cell Melanoma Res 28:245–253. https://doi.org/10.1111/pcmr.12340CrossRefPubMed

19.

Ben Dori S, Aizic A, Sabo E, Hershkovitz D (2020) Spatial heterogeneity of PD-L1 expression and the risk for misclassification of PD-L1 immunohistochemistry in non-small cell lung cancer. Lung Cancer 147:91–98. https://doi.org/10.1016/j.lungcan.2020.07.012CrossRefPubMed

20.

Gniadek TJ, Li QK, Tully E et al (2017) Heterogeneous expression of PD-L1 in pulmonary squamous cell carcinoma and adenocarcinoma: implications for assessment by small biopsy. Mod Pathol 30:530–538. https://doi.org/10.1038/modpathol.2016.213CrossRefPubMed

21.

Dill EA, Gru AA, Atkins KA et al (2017) PD-L1 expression and intratumoral heterogeneity across breast cancer subtypes and stages: an assessment of 245 primary and 40 metastatic tumors. Am J Surg Pathol 41:334–342. https://doi.org/10.1097/PAS.0000000000000780CrossRefPubMed

22.

Stovgaard ES, Bokharaey M, List-Jensen K et al (2020) PD-L1 diagnostics in the neoadjuvant setting: implications of intratumoral heterogeneity of PD-L1 expression in triple negative breast cancer for assessment in small biopsies. Breast Cancer Res Treat 181:553–560. https://doi.org/10.1007/s10549-020-05655-wCrossRefPubMed

Title: The risk of PD-L1 expression misclassification in triple-negative breast cancer
Authors: Shani Ben Dori
Asaf Aizic
Asia Zubkov
Shlomo Tsuriel
Edmond Sabo
Dov Hershkovitz
Publication date: 27-05-2022
Publisher: Springer US
Keywords: Breast Cancer
Breast Cancer
Published in: Breast Cancer Research and Treatment / Issue 2/2022
Print ISSN: 0167-6806
Electronic ISSN: 1573-7217
DOI: https://doi.org/10.1007/s10549-022-06630-3

Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Watch now

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras

Prof. Fabrice Barlesi

Developed by: Springer Medicine

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusion

Please log in to get access to this content

Other articles of this Issue 2/2022

Limiting systemic endocrine overtreatment in postmenopausal breast cancer patients with an ultralow classification of the 70-gene signature

Biomarker profile of invasive lobular carcinoma: pleomorphic versus classic subtypes, clinicopathological characteristics and prognosis analyses

Accuracy of the Breast Cancer Surveillance Consortium Model Among Women with LCIS

Insulin resistance and weight gain in women treated for early stage breast cancer

Breast cancer diagnosis and treatment during the COVID-19 pandemic in a nationwide, insured population

Breast reconstruction and quality of life five years after cancer diagnosis: VICAN French National cohort

Keynote webinar | Spotlight on antibody–drug conjugates in cancer