PIcKing the Right Treatment for the Right Patient : anti-hormonal therapy resistance in breast cancer: PIK3CA related biomarkers and signaling pathways

Breast cancer is the most common type of cancer in women and second most common cancer worldwide. Most breast cancers are ER-positive (75-80%), for which anti-hormonal therapy is used. For ER-positive metastatic breast cancer (MBC), the objective response rate to anti-hormonal treatment is only 20-40%. This shows an urgent need for biomarkers which can identify patients who will or will not benefit from the therapy. As such, for those patients, unnecessary exposure to undesirable adverse events of (anti-hormonal) therapy can be avoided. Therefore, the aim of this thesis was to find biomarkers able to predict anti-hormonal treatment responsiveness or resistance in mainly advanced ER-positive breast cancer patients. To reach this goal different research approaches were followed. Since mutations in PIK3CA are the most prevalent mutations (up to 45%) in ER-positive breast cancers, the thesis was mainly focused on the relationship between PIK3CA genotype and PI3K pathway with treatment outcome. It was shown that PIK3CA mutations detected in primary breast tumors have a predictive value for aromatase inhibitors (AI) response in the advanced disease setting, but not for tamoxifen response nor for prognosis. Related to the PIK3CA genotype, it was demonstrated that high expression of LRG1 can be used as biomarker for AI treatment response, which upon neo-adjuvant AI therapy showed decreased levels in patients with clinical response. At the proteomic level, high MAPK1/3 phosphorylation levels in luminal breast cancer was shown to be related with PIK3CA exon specific mutations. This MAPK1/3 phosphorylation, especially when localized in the nuclei, has prognostic value in breast cancer. In an alternative approach, using ER-positive breast cancers with an inflammatory breast cancer phenotype, a metagene was constructed. This metagene, ABAT and STC2 were not prognostic. However, decreased expression of ABAT and STC2 were shown to be predictive for tamoxifen resistance in MBC. In the adjuvant setting, only low expression of ABAT was related to tamoxifen resistance. Finally, using cell free DNA (cfDNA) from liquid biopsies, tumor-specific mutations were explored as biomarkers for tamoxifen resistance in MBC patients. Mutations in PIK3CA, TP53, AKAP9, CREBBP and SMAD4 were observed in serum cfDNA taken at disease progression and these mutations, except for AKAP9, were also seen in the primary tumor. When further validated, all above biomarkers hopefully will guide us better to be able to pick the right treatment for the right breast cancer patient

Decreased expression of ABAT and STC2 hallmarks ER-positive inflammatory breast cancer and endocrine therapy resistance in advanced disease

Background: Patients with Estrogen Receptor α-positive (ER+) Inflammatory Breast Cancer (IBC) are less responsive to endocrine therapy compared with ER+ non-IBC (nIBC) patients. The study of ER+ IBC samples might reveal biomarkers for endocrine resistant breast cancer. Materials & methods: Gene expression profiles of ER+ samples from 201 patients were explored for genes that discriminated between IBC and nIBC. Classifier genes were applied onto clinically annotated expression data from 947 patients with ER+ breast cancer and validated with RT-qPCR for 231 patients treated with first-line tamoxifen. Relationships with metastasis-free survival (MFS) and progression-free survival (PFS) following adjuvant and first-line endocrine treatment, respectively, were investigated using Cox regression analysis. Results: A metagene of six genes including the genes encoding for 4-aminobutyrate aminotransferase (ABAT) and Stanniocalcin-2 (STC2) were identified to distinguish 22 ER+ IBC from 43 ER+ nIBC patients and remained discriminatory in an independent series of 136 patients. The metagene and two genes were not prognostic in 517 (neo)adjuvant untreated lymph node-negative ER+ nIBC breast cancer patients. Only ABAT was related to outcome in 250 patients treated with adjuvant tamoxifen. Three independent series of in total 411 patients with advanced disease showed increased metagene scores and decreased expression of ABAT and STC2 to be correlated with poor first-line endocrine therapy outcome. The biomarkers remained predictive for first-line tamoxifen treatment outcome in multivariate analysis including traditional factors or published signatures. In an exploratory analysis, ABAT and STC2 protein expression levels had no relation with PFS after first-line tamoxifen. Conclusions: This study utilized ER+ IBC to identify a metagene including ABAT and STC2 as predictive biomarkers for endocrine therapy resistance