A guide for developing comprehensive systems biology maps of disease mechanisms: planning, construction and maintenance.

As a conceptual model of disease mechanisms, a disease map integrates available knowledge and is applied for data interpretation, predictions and hypothesis generation. It is possible to model disease mechanisms on different levels of granularity and adjust the approach to the goals of a particular project. This rich environment together with requirements for high-quality network reconstruction makes it challenging for new curators and groups to be quickly introduced to the development methods. In this review, we offer a step-by-step guide for developing a disease map within its mainstream pipeline that involves using the CellDesigner tool for creating and editing diagrams and the MINERVA Platform for online visualisation and exploration. We also describe how the Neo4j graph database environment can be used for managing and querying efficiently such a resource. For assessing the interoperability and reproducibility we apply FAIR principles.

Increased MAPK1/3 Phosphorylation in Luminal Breast Cancer Related with PIK3CA Hotspot Mutations and Prognosis.

INTRODUCTION: While mutations in PIK3CA are most frequently (45%) detected in luminal breast cancer, downstream PI3K/AKT/mTOR pathway activation is predominantly observed in the basal subtype. The aim was to identify proteins activated in PIK3CA mutated luminal breast cancer and the clinical relevance of such a protein in breast cancer patients. MATERIALS AND METHODS: Expression levels of 171 signaling pathway (phospho-)proteins established by The Cancer Genome Atlas (TCGA) using reverse phase protein arrays (RPPA) were in silico examined in 361 breast cancers for their relation with PIK3CA status. MAPK1/3 phosphorylation was evaluated with immunohistochemistry on tissue microarrays (TMA) containing 721 primary breast cancer core biopsies to explore the relationship with metastasis-free survival. RESULTS: In silico analyses revealed increased phosphorylation of MAPK1/3, p38 and YAP, and decreased expression of p70S6K and 4E-BP1 in PIK3CA mutated compared to wild-type luminal breast cancer. Augmented MAPK1/3 phosphorylation was most significant, i.e. in luminal A for both PIK3CA exon 9 and 20 mutations and in luminal B for exon 9 mutations. In 290 adjuvant systemic therapy naïve lymph node negative (LNN) breast cancer patients with luminal cancer, high MAPK phosphorylation in nuclei (HR=0.49; 95% CI, 0.25-0.95; P=.036) and in tumor cells (HR=0.37; 95% CI, 0.18-0.79; P=.010) was related with favorable metastasis-free survival in multivariate analyses including traditional prognostic factors. CONCLUSION: Enhanced MAPK1/3 phosphorylation in luminal breast cancer is related to PIK3CA exon-specific mutations and correlated with favorable prognosis especially when located in the nuclei of tumor cells.

LRG1 mRNA expression in breast cancer associates with PIK3CA genotype and with aromatase inhibitor therapy outcome.

BACKGROUND: PIK3CA is the most frequent somatic mutated oncogene in estrogen receptor (ER) positive breast cancer. We previously observed an association between PIK3CA genotype and aromatase inhibitors (AI) treatment outcome. This study now evaluates whether expression of mRNAs and miRs are linked to PIK3CA genotype and are independently related to AI therapy response in order to define potential expressed biomarkers for treatment outcome. MATERIALS AND METHODS: The miR and mRNA expression levels were evaluated for their relationship with the PIK3CA genotype in two breast tumor datasets, i.e. 286 luminal cancers from the TCGA consortium and our set of 84 ER positive primary tumors of metastatic breast cancer patients who received first line AI. BRB Array tools class comparison was performed to define miRs and mRNAs whose expression associate with PIK3CA exon 9 and 20 status. Spearman correlations established miR-mRNA pairs and mRNAs with related expression. Next, a third dataset of 25 breast cancer patients receiving neo-adjuvant letrozole was evaluated, to compare expression levels of identified miRs and mRNAs in biopsies before and after treatment. Finally, to identify potential biomarkers miR and mRNA levels were related with overall survival (OS) and progression free survival (PFS) after first-line AI therapy. RESULTS: Expression of 3 miRs (miR-449a, miR-205-5p, miR-301a-3p) and 9 mRNAs (CCNO, FAM81B, LRG1, NEK10, PLCL1, PGR, SERPINA3, SORBS2, VTCN1) was related to the PIK3CA status in both datasets. All except miR-301a-3p had an increased expression in tumors with PIK3CA mutations. Validation in a publicly available dataset showed that LRG1, PGR, and SERPINA3 levels were decreased after neo-adjuvant AI-treatment. Six miR-mRNA pairs correlated significantly and stepdown analysis of all 12 factors revealed 3 mRNAs (PLCL1, LRG1, FAM81B) related to PFS. Further analyses showed LRG1 and PLCL1 expression to be unrelated with luminal subtype and to associate with OS and with PFS, the latter independent from traditional predictive factors. CONCLUSION: We showed in two datasets of ER positive and luminal breast tumors that the expression of 3 miRs and 9 mRNAs associate with the PIK3CA status. Expression of LRG1 is independent of luminal (A or B) subtype, decreased after neo-adjuvant AI-treatment, and is proposed as potential biomarker for AI therapy outcome.

Cell-free DNA mutations as biomarkers in breast cancer patients receiving tamoxifen.

The aim was to identify mutations in serum cell-free DNA (cfDNA) associated with disease progression on tamoxifen treatment in metastatic breast cancer (MBC). Sera available at start of therapy, during therapy and at disease progression were selected from 10 estrogen receptor (ER)-positive breast cancer patients. DNA from primary tumor and normal tissue and cfDNA from minute amounts of sera were analyzed by targeted next generation sequencing (NGS) of 45 genes (1,242 exons). At disease progression, stop-gain single nucleotide variants (SNVs) for CREBBP (1 patient) and SMAD4 (1 patient) and non-synonymous SNVs for AKAP9 (1 patient), PIK3CA (2 patients) and TP53 (2 patients) were found. Mutations in CREBBP and SMAD4 have only been occasionally reported in breast cancer. All mutations, except for AKAP9, were also present in the primary tumor but not detected in all blood specimens preceding progression. More sensitive detection by deeper re-sequencing and digital PCR confirmed the occurrence of circulating tumor DNA (ctDNA) and these biomarkers in blood specimens.

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.

Hotspot mutations in PIK3CA associate with first-line treatment outcome for aromatase inhibitors but not for tamoxifen.

PIK3CA mutations occur frequently in breast cancer, predominantly in exons 9 and 20. The aim of this retrospective study is to evaluate the PIK3CA mutation status for its relationship with prognosis and first-line endocrine therapy outcome. PIK3CA exon 9 and 20 were evaluated for mutations in 1,352 primary breast cancer specimens by SnaPshot multiplex analyses. The mutation status was studied for their relationship with metastasis-free survival (MFS) in 342 untreated lymph node-negative (LNN) patients and to time to progression (TTP) in estrogen receptor (ER)-positive patients with metastatic disease treated with first-line tamoxifen (N = 447) or aromatase inhibitors (AIs; N = 84). We detected in 423 patients hotspot mutations for PIK3CA (31 %). Mutations in exon 20 were detected in 251 patients (59 %), with H1047L and H1047R mutations in 37 (15 %) and 214 (85 %) cases, respectively. Mutations in PIK3CA exon 9 were discovered in 173 patients (41 %), with E542K and E545K mutations in 57 (32 %) and 104 (60 %) cases as most prevalent ones. Evaluation of the untreated LNN patients for prognosis showed no relationship between MFS and PIK3CA mutations, neither for exon 9 [HR = 1.04 (95 % CI 0.57-1.89), P = 0.90] nor for exon 20 [HR = 0.98 (95 % CI 0.63-1.54); P = 0.94] when compared to wild-type. The PIK3CA mutation status was also not associated with treatment outcome after first-line tamoxifen. On the other hand, patients treated with first-line AIs showed a longer TTP when having a PIK3CA mutation in exon 9 [HR = 0.40 (95 % CI 0.17-0.95); P = 0.038] or exon 20 [HR = 0.50 (95 % CI 0.27-0.91); P = 0.024] compared to wild-types, both significant in uni- and multivariate analysis including traditional predictive factors. All results remained when only HER2-negative patients were evaluated for each cohort. PIK3CA mutations in ER-positive tumors were significantly associated with a favorable outcome after first-line AIs, which needs further confirmation in other datasets. Mutations were not associated with prognosis in untreated LNN patients nor predictive outcome after first-line tamoxifen therapy in advanced disease patients.