TNBC is a heterogeneous disease and subtype classification is necessary for optimization of personalized treatment. TNBC subtyping using gene expression data has been implemented by several groups but gene expression data are impractical and expensive for clinical application. To aid in this subtyping effort, we developed a TNBC surrogate subtype classification to classify TNBC into four subtypes that correlate with the Vanderbilt subtypes. The TNBC surrogate subtyping adopts p16, AR, and TIL data for classification, which are widely used parameters in pathology clinics.
This is the first study to develop a TNBC surrogate subtype that correlates with the Vanderbilt subtypes. Zhao et al. developed an IHC-based approach for TNBC subtyping by comparison with mRNA-based subtypes used in the Fudan University Shanghai Cancer Center [26]. Other similar studies have attempted to classify TNBC subtypes by IHC panels but have focused on independent classifications that did not involve correlations with any gene expression data [13, 16].
The LAR subtype is universally identified among TNBC gene expression subtypes that use unsupervised clustering methods [4–7]. Notably, the LAR subtype is enriched in AR expression and its downstream gene targets and is relatively simple to identify using AR protein expression in IHC analysis [4, 27, 28]. In this study, we used an AR Allred score of 8 to identify the LAR subtype. This comprised 18% of the TNBC cohort, similar to previous reports in which 10–35% of TNBC tumors expressed AR [29–32]. The clinical significance of AR expression has been identified in several clinical trials, indicating the efficacy of anti-androgen treatment in patients with AR-positive metastatic TNBC [33, 34]. Clinical trials of anti-androgens have used cutoff values of 1% or 10%, which differ from our study. The predictive value of AR expression levels for anti-androgen treatment requires further investigation, but the present study implies that a higher cutoff value may be needed to identify a LAR subtype more specifically in patients with TNBC.
Another subtype consistently identified in distinct gene expression classification systems is the IM subtype [4, 6, 7, 11]. Gene expression data have shown that this subtype is highly enriched for immune cell signaling, and that it has a high prevalence of TILs [10, 11]. This correlates with the use of TIL as a marker to determine IM subtype in the surrogate subtype classification. The clinical implications of the IM subtype and TIL as a subtype marker are related to the use of immune checkpoint inhibitor therapies, which are currently a novel component of care for patients with TNBC [35]. Atezolizumab, a PD-L1 inhibitor, has been approved in combination with nab-paclitaxel for PD-L1-positive metastatic TNBCs and TIL is a predictive factor when tumors are PD-L1 positive [36, 37]. The predictive value of TILs has also been identified in clinical trials for pembrolizumab, a PD-1 inhibitor [38, 39]. In this study, both IM subtypes classified on the basis of RNA and IHC expression exhibited high CD8 + levels and high rates of PD-L1 positivity, which are additional biomarkers that serve as predictive factors for immune checkpoint inhibitors [40].
In contrast to the IM subtype, low TIL (< 20%) was the determining factor for the M subtype in the IHC classification. Lehmann et al. reported that M and IM subtypes had a negative correlation, which was consistent with the classification method in our study [10]. The negative correlation between the M and IM subtypes implies that the M subtype involves an immunosuppressed microenvironment, corresponding to the poor prognosis of patients with the M subtype [10]. The clinical significance of the M subtype as a target for novel therapeutics is unclear. Bioinformatics analysis of data derived from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and The Cancer Genome Atlas (TCGA) showed that the M subtype is associated with an elevated angiogenesis signature score and enrichment of the EGFR and Notch signaling pathways [17]. On the basis of these results, antiangiogenic therapy or EGFR inhibitors could be considered for patients with M subtype tumors, which have both failed to demonstrate a survival benefit in unselected TNBC populations [41, 42].
Immunostainings for basal cytokeratins including CK5/6, CK14, CK17, and EGFR have been regarded as surrogate markers of the BL subtype. However diffuse and strong staining of p16 immunostaining is the last condition of BL subtype in our TNBC surrogate subtype classification. This correlates with the TNBC cohort from the METABRIC and TCGA dataset, showing copy number amplifications in CDKN2A/B genes in the BL1 subtype [17]. p16 regulates the cell cycle by inhibition of phosphorylation of Rb via inactivation of CDK4/6 [43]. The positive immunostaining of p16 is suggested as a surrogate marker for Rb pathway loss, and Rb1 loss is associated with homologous recombination deficiency in high-grade serous ovarian cancer [45, 46]. This suggests that adopting p16 immunostaining as a surrogate marker for BL subtype in our TNBC surrogate subtype classification is related to Rb1 loss and homologous recombination deficiency. The BL subtype itself is characterized by high genomic instability and high copy number losses for BRCA1/2, which implies sensitivity to poly-ADP ribose polymerase(PARP) inhibitors. PARP inhibitors have shown considerable benefit in patients with advanced breast cancer and a germline BRCA1/2 mutation, especially those with TNBC tumors [48, 49]. Currently, the presence of germline BRCA 1/2 mutations is the main predictive factor for the effects of PARP inhibitors, but the BL subtype could also be regarded as a predictive factor, especially in patients with wild-type BRCA 1/2 with homologous recombination deficiency.
The strength of the TNBC surrogate subtype classification is that AR, p16 IHC, and TIL evaluation protocols are widely used in pathology clinics. Guidelines for IHC procedures and TIL assessment are already established [20, 24], so the clinical application of the surrogate subtype classification is easy and immediately available.
However, there were some weaknesses in this study. Tissue microarrays were used for TIL evaluation and IHC staining, which may not represent the entire tumor. RNA sequencing was performed using bulk tumor tissue, which does not reflect the intratumoral heterogeneity demonstrated by single-cell RNA sequencing [50]. Eighteen patients (13.2%) were unclassified in the surrogate subtype classification and could not be included in any specific Vanderbilt 4 subtype. This lack of classification requires further investigation. CART is a relatively unstable method, whereby a small change in the data can cause considerable variation in the model, especially when a small sample size is used [51]. The TNBC cohort in this study was relatively small and further validation is needed using a larger, external dataset. Also, all patients included in this study underwent primary surgery followed by adjuvant chemotherapy, which is deviated from current treatment guidelines that recommend preoperative systemic therapy in patients with TNBC tumors. An additional study using core needle biopsy tissues in patients undergoing neoadjuvant therapy is needed to confirm the application of the surrogate subtypes in current TNBC treatment.