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Biological subtyping of early breast cancer: a study comparing RT-qPCR with immunohistochemistry.

ABSTRACT: The biological subtype of breast cancer influences the selection of systemic therapy. Distinction between luminal A and B cancers depends on consistent assessment of Ki-67, but substantial intra-observer and inter-observer variability exists when immunohistochemistry (IHC) is used. We compared RT-qPCR with IHC in the assessment of Ki-67 and other standard factors used in breast cancer subtyping. RNA was extracted from archival breast tumour tissue of 769 women randomly assigned to the FinHer trial. Cancer ESR1, PGR, ERBB2 and MKI67 mRNA content was quantitated with an RT-qPCR assay. Local pathologists assessed ER, PgR and Ki-67 expression using IHC. HER2 amplification was identified with chromogenic in situ hybridization (CISH) centrally. The results were correlated with distant disease-free survival (DDFS) and overall survival (OS). qPCR-based and IHC-based assessments of ER and PgR showed good concordance. Both low tumour MKI67 mRNA (RT-qPCR) and Ki-67 protein (IHC) levels were prognostic for favourable DDFS [hazard ratio (HR) 0.42, 95 % CI 0.25-0.71, P = 0.001; and HR 0.56, 0.37-0.84, P = 0.005, respectively] and OS. In multivariable analyses, cancer MKI67 mRNA content had independent influence on DDFS (adjusted HR 0.51, 95 % CI 0.29-0.89, P = 0.019) while Ki-67 protein expression had not any influence (P = 0.266) whereas both assessments influenced independently OS. Luminal B patients treated with docetaxel-FEC had more favourable DDFS and OS than those treated with vinorelbine-FEC when the subtype was defined by RT-qPCR (for DDFS, HR 0.52, 95 % CI 0.29-0.94, P = 0.031), but not when defined using IHC. Breast cancer subtypes approximated with RT-qPCR and IHC show good concordance, but cancer MKI67 mRNA content correlated slightly better with DDFS than Ki-67 expression. The findings based on MKI67 mRNA content suggest that patients with luminal B cancer benefit more from docetaxel-FEC than from vinorelbine-FEC.

SUBMITTER: Wirtz RM

PROVIDER: S-EPMC4903103 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Biological subtyping of early breast cancer: a study comparing RT-qPCR with immunohistochemistry.

Wirtz Ralph M RM Sihto Harri H Isola Jorma J Heikkilä Päivi P Kellokumpu-Lehtinen Pirkko-Liisa PL Auvinen Päivi P Turpeenniemi-Hujanen Taina T Jyrkkiö Sirkku S Lakis Sotiris S Schlombs Kornelia K Laible Mark M Weber Stefan S Eidt Sebastian S Sahin Ugur U Joensuu Heikki H

Breast cancer research and treatment 20160524 3

The biological subtype of breast cancer influences the selection of systemic therapy. Distinction between luminal A and B cancers depends on consistent assessment of Ki-67, but substantial intra-observer and inter-observer variability exists when immunohistochemistry (IHC) is used. We compared RT-qPCR with IHC in the assessment of Ki-67 and other standard factors used in breast cancer subtyping. RNA was extracted from archival breast tumour tissue of 769 women randomly assigned to the FinHer tri ...[more]

PMID: 27220750

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Project description:BackgroundMany methodologies have been used in research to identify the "intrinsic" subtypes of breast cancer commonly known as Luminal A, Luminal B, HER2-Enriched (HER2-E) and Basal-like. The PAM50 gene set is often used for gene expression-based subtyping; however, surrogate subtyping using panels of immunohistochemical (IHC) markers are still widely used clinically. Discrepancies between these methods may lead to different treatment decisions.MethodsWe used the PAM50 RT-qPCR assay to expression profile 814 tumors from the GEICAM/9906 phase III clinical trial that enrolled women with locally advanced primary invasive breast cancer. All samples were scored at a single site by IHC for estrogen receptor (ER), progesterone receptor (PR), and Her2/neu (HER2) protein expression. Equivocal HER2 cases were confirmed by chromogenic in situ hybridization (CISH). Single gene scores by IHC/CISH were compared with RT-qPCR continuous gene expression values and "intrinsic" subtype assignment by the PAM50. High, medium, and low expression for ESR1, PGR, ERBB2, and proliferation were selected using quartile cut-points from the continuous RT-qPCR data across the PAM50 subtype assignments.ResultsESR1, PGR, and ERBB2 gene expression had high agreement with established binary IHC cut-points (area under the curve (AUC) ≥ 0.9). Estrogen receptor positivity by IHC was strongly associated with Luminal (A and B) subtypes (92%), but only 75% of ER negative tumors were classified into the HER2-E and Basal-like subtypes. Luminal A tumors more frequently expressed PR than Luminal B (94% vs 74%) and Luminal A tumors were less likely to have high proliferation (11% vs 77%). Seventy-seven percent (30/39) of ER-/HER2+ tumors by IHC were classified as the HER2-E subtype. Triple negative tumors were mainly comprised of Basal-like (57%) and HER2-E (30%) subtypes. Single gene scoring for ESR1, PGR, and ERBB2 was more prognostic than the corresponding IHC markers as shown in a multivariate analysis.ConclusionsThe standard immunohistochemical panel for breast cancer (ER, PR, and HER2) does not adequately identify the PAM50 gene expression subtypes. Although there is high agreement between biomarker scoring by protein immunohistochemistry and gene expression, the gene expression determinations for ESR1 and ERBB2 status was more prognostic.

Project description:PurposeDecades of quality control efforts have raised the standards of immunohistochemistry (IHC), the principle method used for biomarker testing in breast cancer; however, computational pathology and reverse transcription quantitative PCR (RT-qPCR) may also hold promise for additional substantial improvements.MethodsHerein, we investigated discrepancies in the assessment of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and marker of proliferation Ki67 comparing routinely obtained IHC (and FISH) data (ORI) with the results of manual (REV) and semi-automated (DIA) re-evaluation of the original IHC slides and then with RNA expression data from the same tissue block using the MammaTyper® (MT) gene expression assay.ResultsCorrelation for ER and PR was high between ORI IHC and the other three study methods (REV, DIA and RT-qPCR). For HER2, 10 out of 96 discrepant cases can be detected between ORI and REV that involved at least one call in the equivocal category (except for one case). For Ki67, 22 (29.1%) cases were categorized differently by either REV alone (n = 17), DIA alone (n = 15) or both (n = 10) and 28 cases (29.2%) for RT-qPCR. Most of the discrepant Ki67 cases changed from low to high between the original and following assessment and belonged to the intermediate Ki67 expression range (between 9 and 30%).ConclusionsDetermination of the breast cancer biomarkers ER, PR, HER2 and Ki67 at the mRNA level shows high degree of correlation with IHC and compares well with correlations between original with subsequent independent manual or semi-automated IHC assessments. The use of methods with wider dynamic range and higher reproducibility such as RT-qPCR may offer more precise assessment of endocrine responsiveness, improve Ki67 standardization and help resolve HER2 cases that remain equivocal or ambiguous by IHC/FISH. In summary, our findings seem to configure RT-qPCR as a complementary method to be used in cases of either equivocal results or presenting, at the traditional determination assays, biomarkers expressions close to the cut-off values.

Project description:BackgroundMolecular subtyping of triple-negative breast cancers (TNBCs) via gene expression profiling is essential for understanding the molecular essence of this heterogeneous disease and for guiding individualized treatment. We aim to devise a clinically practical method based on immunohistochemistry (IHC) for the molecular subtyping of TNBCs.Materials and methodsBy analyzing the RNA sequencing data on TNBCs from Fudan University Shanghai Cancer Center (FUSCC) (n = 360) and The Cancer Genome Atlas data set (n = 158), we determined markers that can identify specific molecular subtypes. We performed immunohistochemical staining on tumor sections of 210 TNBCs from FUSCC, established an IHC-based classifier, and applied it to another two cohorts (n = 183 and 214).ResultsWe selected androgen receptor (AR), CD8, FOXC1, and DCLK1 as immunohistochemical markers and classified TNBCs into five subtypes based on the staining results: (a) IHC-based luminal androgen receptor (IHC-LAR; AR-positive [+]), (b) IHC-based immunomodulatory (IHC-IM; AR-negative [-], CD8+), (c) IHC-based basal-like immune-suppressed (IHC-BLIS; AR-, CD8-, FOXC1+), (d) IHC-based mesenchymal (IHC-MES; AR-, CD8-, FOXC1-, DCLK1+), and (e) IHC-based unclassifiable (AR-, CD8-, FOXC1-, DCLK1-). The κ statistic indicated substantial agreement between the IHC-based classification and mRNA-based classification. Multivariate survival analysis suggested that our IHC-based classification was an independent prognostic factor for relapse-free survival. Transcriptomic data and pathological observations implied potential treatment strategies for different subtypes. The IHC-LAR subtype showed relative activation of HER2 pathway. The IHC-IM subtype tended to exhibit an immune-inflamed phenotype characterized by the infiltration of CD8+ T cells into tumor parenchyma. The IHC-BLIS subtype showed high expression of a VEGF signature. The IHC-MES subtype displayed activation of JAK/STAT3 signaling pathway.ConclusionWe developed an IHC-based approach to classify TNBCs into molecular subtypes. This IHC-based classification can provide additional information for prognostic evaluation. It allows for subgrouping of TNBC patients in clinical trials and evaluating the efficacy of targeted therapies within certain subtypes.Implications for practiceAn immunohistochemistry (IHC)-based classification approach was developed for triple-negative breast cancer (TNBC), which exhibited substantial agreement with the mRNA expression-based classification. This IHC-based classification (a) allows for subgrouping of TNBC patients in large clinical trials and evaluating the efficacy of targeted therapies within certain subtypes, (b) will contribute to the practical application of subtype-specific treatment for patients with TNBC, and (c) can provide additional information beyond traditional prognostic factors in relapse prediction.

Dataset Information

Biological subtyping of early breast cancer: a study comparing RT-qPCR with immunohistochemistry.

Publications

Biological subtyping of early breast cancer: a study comparing RT-qPCR with immunohistochemistry.

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