A Living Biobank of Breast Cancer Organoids Captures Disease Heterogeneity.

Breast cancer (BC) comprises multiple distinct subtypes that differ genetically, pathologically, and clinically. Here, we describe a robust protocol for long-term culturing of human mammary epithelial organoids. Using this protocol, >100 primary and metastatic BC organoid lines were generated, broadly recapitulating the diversity of the disease. BC organoid morphologies typically matched the histopathology, hormone receptor status, and HER2 status of the original tumor. DNA copy number variations as well as sequence changes were consistent within tumor-organoid pairs and largely retained even after extended passaging. BC organoids furthermore populated all major gene-expression-based classification groups and allowed in vitro drug screens that were consistent with in vivo xeno-transplantations and patient response. This study describes a representative collection of well-characterized BC organoids available for cancer research and drug development, as well as a strategy to assess in vitro drug response in a personalized fashion.

Preserved genetic diversity in organoids cultured from biopsies of human colorectal cancer metastases.

Tumor organoids are 3D cultures of cancer cells. They can be derived from the tumor of each individual patient, thereby providing an attractive ex vivo assay to tailor treatment. Using patient-derived tumor organoids for this purpose requires that organoids derived from biopsies maintain the genetic diversity of the in vivo tumor. In this study tumor biopsies were obtained from 14 patients with metastatic colorectal cancer (i) to test the feasibility of organoid culture from metastatic biopsy specimens and (ii) to compare the genetic diversity of patient-derived tumor organoids and the original tumor biopsy. Genetic analysis was performed using SOLiD sequencing for 1,977 cancer-relevant genes. Copy number profiles were generated from sequencing data using CopywriteR. Here we demonstrate that organoid cultures can be established from tumor biopsies of patients with metastatic colorectal cancer with a success rate of 71%. Genetic analysis showed that organoids reflect the metastasis from which they were derived. Ninety percent of somatic mutations were shared between organoids and biopsies from the same patient, and the DNA copy number profiles of organoids and the corresponding original tumor show a correlation of 0.89. Most importantly, none of the mutations that were found exclusively in either the tumor or organoid culture are in driver genes or genes amenable for drug targeting. These findings support further exploration of patient-derived organoids as an ex vivo platform to personalize anticancer treatment.

Genomic and transcriptomic plasticity in treatment-naive ovarian cancer.

Intra-tumor heterogeneity is a hallmark of many cancers and may lead to therapy resistance or interfere with personalized treatment strategies. Here, we combined topographic mapping of somatic breakpoints and transcriptional profiling to probe intra-tumor heterogeneity of treatment-naïve stage IIIC/IV epithelial ovarian cancer. We observed that most substantial differences in genomic rearrangement landscapes occurred between metastases in the omentum and peritoneum versus tumor sites in the ovaries. Several cancer genes such as NF1, CDKN2A, and FANCD2 were affected by lesion-specific breakpoints. Furthermore, the intra-tumor variability involved different mutational hallmarks including lesion-specific kataegis (local mutation shower coinciding with genomic breakpoints), rearrangement classes, and coding mutations. In one extreme case, we identified two independent TP53 mutations in ovary tumors and omentum/peritoneum metastases, respectively. Examination of gene expression dynamics revealed up-regulation of key cancer pathways including WNT, integrin, chemokine, and Hedgehog signaling in only subsets of tumor samples from the same patient. Finally, we took advantage of the multilevel tumor analysis to understand the effects of genomic breakpoints on qualitative and quantitative gene expression changes. We show that intra-tumor gene expression differences are caused by site-specific genomic alterations, including formation of in-frame fusion genes. These data highlight the plasticity of ovarian cancer genomes, which may contribute to their strong capacity to adapt to changing environmental conditions and give rise to the high rate of recurrent disease following standard treatment regimes.

Next generation sequencing of triple negative breast cancer to find predictors for chemotherapy response.

INTRODUCTION: In triple negative breast cancers (TNBC) the initial response to chemotherapy is often favorable, but relapse and chemotherapy resistance frequently occur in advanced disease. Hence there is an urgent need for targeted treatments in this breast cancer subtype. In the current study we deep sequenced DNA of tumors prior to chemotherapy to search for predictors of response or resistance. METHODS: Next generation sequencing (NGS) was performed for 1,977 genes involved in tumorigenesis. DNA from 56 pre-treatment TNBC-biopsies was sequenced, as well as matched normal DNA. Following their tumor biopsy, patients started neoadjuvant chemotherapy with doxorubicin and cyclophosphamide. We studied associations between genetic alterations and three clinical variables: chemotherapy response, relapse-free survival and BRCA proficiency. RESULTS: The mutations observed were diverse and few recurrent mutations were detected. Most mutations were in TP53, TTN, and PIK3CA (55 %, 14 %, and 9 %, respectively). The mutation rates were similar between responders and non-responders (average mutation rate 9 vs 8 mutations). No recurrent mutations were associated with chemotherapy response or relapse. Interestingly, PIK3CA mutations were exclusively observed in patients proficient for BRCA1. Samples with a relapse had a higher copy number alteration rate, and amplifications of TTK and TP53BP2 were associated with a poor chemotherapy response. CONCLUSIONS: In this homogenous cohort of TNBCs few recurrent mutations were found. However, PIK3CA mutations were associated with BRCA proficiency, which can have clinical consequences in the near future.

Targeted next-generation sequencing: a novel diagnostic tool for primary immunodeficiencies.

BACKGROUND: Primary immunodeficiency (PID) disorders are a heterogeneous group of inherited disorders caused by a variety of monogenetic immune defects. Thus far, mutations in more than 170 different genes causing PIDs have been described. A clear genotype-phenotype correlation is often not available, which makes a genetic diagnosis in patients with PIDs complex and laborious. OBJECTIVE: We sought to develop a robust, time-effective, and cost-effective diagnostic method to facilitate a genetic diagnosis in any of 170 known PID-related genes by using next-generation sequencing (NGS). METHODS: We used both targeted array-based and in-solution enrichment combined with a SOLiD sequencing platform and a bioinformatic pipeline developed in house to analyze genetic changes in the DNA of 41 patients with PIDs with known mutations and 26 patients with undiagnosed PIDs. RESULTS: This novel NGS-based method accurately detected point mutations (sensitivity and specificity >99% in covered regions) and exonic deletions (100% sensitivity and specificity). For the 170 genes of interest, the DNA coverage was greater than 20× in 90% to 95%. Nine PID-related genes proved not eligible for evaluation by using this NGS-based method because of inadequate coverage. The NGS method allowed us to make a genetic diagnosis in 4 of 26 patients who lacked a genetic diagnosis despite routine functional and genetic testing. Three of these patients proved to have an atypical presentation of previously described PIDs. CONCLUSION: This novel NGS tool facilitates accurate simultaneous detection of mutations in 161 of 170 known PID-related genes. In addition, these analyses will generate more insight into genotype-phenotype correlations for the different PID disorders.

PRI-CAT: a web-tool for the analysis, storage and visualization of plant ChIP-seq experiments.

Although several tools for the analysis of ChIP-seq data have been published recently, there is a growing demand, in particular in the plant research community, for computational resources with which such data can be processed, analyzed, stored, visualized and integrated within a single, user-friendly environment. To accommodate this demand, we have developed PRI-CAT (Plant Research International ChIP-seq analysis tool), a web-based workflow tool for the management and analysis of ChIP-seq experiments. PRI-CAT is currently focused on Arabidopsis, but will be extended with other plant species in the near future. Users can directly submit their sequencing data to PRI-CAT for automated analysis. A QuickLoad server compatible with genome browsers is implemented for the storage and visualization of DNA-binding maps. Submitted datasets and results can be made publicly available through PRI-CAT, a feature that will enable community-based integrative analysis and visualization of ChIP-seq experiments. Secondary analysis of data can be performed with the aid of GALAXY, an external framework for tool and data integration. PRI-CAT is freely available at http://www.ab.wur.nl/pricat. No login is required.

Comprehensive characterization of pre- and post-treatment samples of breast cancer reveal potential mechanisms of chemotherapy resistance.

When locally advanced breast cancer is treated with neoadjuvant chemotherapy, the recurrence risk is significantly higher if no complete pathologic response is achieved. Identification of the underlying resistance mechanisms is essential to select treatments with maximal efficacy and minimal toxicity. Here we employed gene expression profiles derived from 317 HER2-negative treatment-naïve breast cancer biopsies of patients who underwent neoadjuvant chemotherapy, deep whole exome, and RNA-sequencing profiles of 22 matched pre- and post-treatment tumors, and treatment outcome data to identify biomarkers of response and resistance mechanisms. Molecular profiling of treatment-naïve breast cancer samples revealed that expression levels of proliferation, immune response, and extracellular matrix (ECM) organization combined predict response to chemotherapy. Triple negative patients with high proliferation, high immune response and low ECM expression had a significantly better treatment response and survival benefit (HR 0.29, 95% CI 0.10-0.85; p = 0.02), while in ER+ patients the opposite was seen (HR 4.73, 95% CI 1.51-14.8; p = 0.008). The characterization of paired pre-and post-treatment samples revealed that aberrations of known cancer genes were either only present in the pre-treatment sample (CDKN1B) or in the post-treatment sample (TP53, APC, CTNNB1). Proliferation-associated genes were frequently down-regulated in post-treatment ER+ tumors, but not in triple negative tumors. Genes involved in ECM were upregulated in the majority of post-chemotherapy samples. Genomic and transcriptomic differences between pre- and post-chemotherapy samples are common and may reveal potential mechanisms of therapy resistance. Our results show a wide range of distinct, but related mechanisms, with a prominent role for proliferation- and ECM-related genes.

Differential Survival and Therapy Benefit of Patients with Breast Cancer Are Characterized by Distinct Epithelial and Immune Cell Microenvironments.

PURPOSE: Extensive work in preclinical models has shown that microenvironmental cells influence many aspects of cancer cell behavior, including metastatic potential and their sensitivity to therapeutics. In the human setting, this behavior is mainly correlated with the presence of immune cells. Here, in addition to T cells, B cells, macrophages, and mast cells, we identified the relevance of nonimmune cell types for breast cancer survival and therapy benefit, including fibroblasts, myoepithelial cells, muscle cells, endothelial cells, and seven distinct epithelial cell types. EXPERIMENTAL DESIGN: Using single-cell sequencing data, we generated reference profiles for all these cell types. We used these reference profiles in deconvolution algorithms to optimally detangle the cellular composition of more than 3,500 primary breast tumors of patients that were enrolled in the SCAN-B and MATADOR clinical trials, and for which bulk mRNA sequencing data were available. RESULTS: This large data set enables us to identify and subsequently validate the cellular composition of microenvironments that distinguish differential survival and treatment benefit for different treatment regimens in patients with primary breast cancer. In addition to immune cells, we have identified that survival and therapy benefit are characterized by various contributions of distinct epithelial cell types. CONCLUSIONS: From our study, we conclude that differential survival and therapy benefit of patients with breast cancer are characterized by distinct microenvironments that include specific populations of immune and epithelial cells.

Genomic analysis defines clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancer.

Ductal carcinoma in situ (DCIS) is the most common form of preinvasive breast cancer and, despite treatment, a small fraction (5-10%) of DCIS patients develop subsequent invasive disease. A fundamental biologic question is whether the invasive disease arises from tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial DCIS lesion and paired invasive recurrent tumors in 95 patients together with single-cell DNA sequencing in a subset of cases. Our data show that in 75% of cases the invasive recurrence was clonally related to the initial DCIS, suggesting that tumor cells were not eliminated during the initial treatment. Surprisingly, however, 18% were clonally unrelated to the DCIS, representing new independent lineages and 7% of cases were ambiguous. This knowledge is essential for accurate risk evaluation of DCIS, treatment de-escalation strategies and the identification of predictive biomarkers.

Drug-Induced Epigenomic Plasticity Reprograms Circadian Rhythm Regulation to Drive Prostate Cancer toward Androgen Independence.

In prostate cancer, androgen receptor (AR)-targeting agents are very effective in various disease stages. However, therapy resistance inevitably occurs, and little is known about how tumor cells adapt to bypass AR suppression. Here, we performed integrative multiomics analyses on tissues isolated before and after 3 months of AR-targeting enzalutamide monotherapy from patients with high-risk prostate cancer enrolled in a neoadjuvant clinical trial. Transcriptomic analyses demonstrated that AR inhibition drove tumors toward a neuroendocrine-like disease state. Additionally, epigenomic profiling revealed massive enzalutamide-induced reprogramming of pioneer factor FOXA1 from inactive chromatin sites toward active cis-regulatory elements that dictate prosurvival signals. Notably, treatment-induced FOXA1 sites were enriched for the circadian clock component ARNTL. Posttreatment ARNTL levels were associated with patients' clinical outcomes, and ARNTL knockout strongly decreased prostate cancer cell growth. Our data highlight a remarkable cistromic plasticity of FOXA1 following AR-targeted therapy and revealed an acquired dependency on the circadian regulator ARNTL, a novel candidate therapeutic target. SIGNIFICANCE: Understanding how prostate cancers adapt to AR-targeted interventions is critical for identifying novel drug targets to improve the clinical management of treatment-resistant disease. Our study revealed an enzalutamide-induced epigenomic plasticity toward prosurvival signaling and uncovered the circadian regulator ARNTL as an acquired vulnerability after AR inhibition, presenting a novel lead for therapeutic development. See related commentary by Zhang et al., p. 2017. This article is highlighted in the In This Issue feature, p. 2007.

A case-control study to identify molecular risk factors for local recurrence in young breast cancer patients.

PURPOSE: To investigate risk factors for local recurrence (LR) after breast conserving therapy in young breast cancer patients randomized in the "Young Boost Trial". MATERIAL & METHODS: In the "Young Boost Trial" 2421 patients ≤50 years old were randomized between a 16 Gy and 26 Gy boost after breast conserving surgery and whole breast radiation (50 Gy). We performed a case-control study comparing patients who developed a LR (cases) and for each of them three control patients free of recurrence (controls). Clinicopathological factors, copy number- and gene expression profiles of primary tumors were compared between cases and controls, and between primary tumors and local recurrences. RESULTS: The cumulative 5-year LR rate was 1.07% (95% CI 0.72-1.59%) and 10-year LR rate 2.56% (1.81-3.62%). Analysis of a subset of primary tumors and local recurrences showed similar histopathological characteristics (n = 15), copy number (n = 13) and gene expression profiles (n = 14). Basal subtype was strongly associated with LR in univariable and multivariable analysis. Gains of CCND1 were identified more frequently among controls, while more frequent gains of FGFR1 and IGF1R were observed among cases. Upregulation of genes involved in the p53-pathway was observed in recurring tumors compared to non-recurring tumors. We could not identify a genomic classifier for LR. CONCLUSIONS: All investigated local recurrences were true genomic recurrences. Although differences in copy number variation and gene expression pathways were observed in recurring tumors compared to non-recurring tumors, no genomic classifier for LR could be identified.

Reduced NCOR2 expression accelerates androgen deprivation therapy failure in prostate cancer.

This study addresses the roles of nuclear receptor corepressor 2 (NCOR2) in prostate cancer (PC) progression in response to androgen deprivation therapy (ADT). Reduced NCOR2 expression significantly associates with shorter disease-free survival in patients with PC receiving adjuvant ADT. Utilizing the CWR22 xenograft model, we demonstrate that stably reduced NCOR2 expression accelerates disease recurrence following ADT, associates with gene expression patterns that include neuroendocrine features, and induces DNA hypermethylation. Stably reduced NCOR2 expression in isogenic LNCaP (androgen-sensitive) and LNCaP-C4-2 (androgen-independent) cells revealed that NCOR2 reduction phenocopies the impact of androgen treatment and induces global DNA hypermethylation patterns. NCOR2 genomic binding is greatest in LNCaP-C4-2 cells and most clearly associates with forkhead box (FOX) transcription factor FOXA1 binding. NCOR2 binding significantly associates with transcriptional regulation most when in active enhancer regions. These studies reveal robust roles for NCOR2 in regulating the PC transcriptome and epigenome and underscore recent mutational studies linking NCOR2 loss of function to PC disease progression.

Functional mapping of androgen receptor enhancer activity.

BACKGROUND: Androgen receptor (AR) is critical to the initiation, growth, and progression of prostate cancer. Once activated, the AR binds to cis-regulatory enhancer elements on DNA that drive gene expression. Yet, there are 10-100× more binding sites than differentially expressed genes. It is unclear how or if these excess binding sites impact gene transcription. RESULTS: To characterize the regulatory logic of AR-mediated transcription, we generated a locus-specific map of enhancer activity by functionally testing all common clinical AR binding sites with Self-Transcribing Active Regulatory Regions sequencing (STARRseq). Only 7% of AR binding sites displayed androgen-dependent enhancer activity. Instead, the vast majority of AR binding sites were either inactive or constitutively active enhancers. These annotations strongly correlated with enhancer-associated features of both in vitro cell lines and clinical prostate cancer samples. Evaluating the effect of each enhancer class on transcription, we found that AR-regulated enhancers frequently interact with promoters and form central chromosomal loops that are required for transcription. Somatic mutations of these critical AR-regulated enhancers often impact enhancer activity. CONCLUSIONS: Using a functional map of AR enhancer activity, we demonstrated that AR-regulated enhancers act as a regulatory hub that increases interactions with other AR binding sites and gene promoters.

An androgen receptor switch underlies lineage infidelity in treatment-resistant prostate cancer.

Cancers adapt to increasingly potent targeted therapies by reprogramming their phenotype. Here we investigated such a phenomenon in prostate cancer, in which tumours can escape epithelial lineage confinement and transition to a high-plasticity state as an adaptive response to potent androgen receptor (AR) antagonism. We found that AR activity can be maintained as tumours adopt alternative lineage identities, with changes in chromatin architecture guiding AR transcriptional rerouting. The epigenetic regulator enhancer of zeste homologue 2 (EZH2) co-occupies the reprogrammed AR cistrome to transcriptionally modulate stem cell and neuronal gene networks-granting privileges associated with both fates. This function of EZH2 was associated with T350 phosphorylation and establishment of a non-canonical polycomb subcomplex. Our study provides mechanistic insights into the plasticity of the lineage-infidelity state governed by AR reprogramming that enabled us to redirect cell fate by modulating EZH2 and AR, highlighting the clinical potential of reversing resistance phenotypes.

Response to Preoperative Radiation Therapy in Relation to Gene Expression Patterns in Breast Cancer Patients.

PURPOSE: We aimed to study radiation-induced gene expression changes and to identify differences in gene expression between patients with and without response to radiation therapy (RT) for invasive breast cancer with the purpose of exploring whether a predictive signature could be developed. Such a signature could assist in optimizing individualized locoregional treatment. METHODS AND MATERIALS: RNA-seq using next-generation sequencing was performed on fresh frozen samples from pretreatment biopsies and post-RT surgery specimens from patients with low-risk breast cancer treated within the multicenter preoperative accelerated partial breast irradiation trial. Patients were treated with preoperative RT (10 × 4 Gy in 10 days or 5 × 6 Gy in 5 days) and a lumpectomy 6 weeks thereafter. The response of the tumor to RT was evaluated by pathologic assessment. To analyze the gene expression data, unsupervised and supervised clustering was performed. Gene expression profiles were compared between biopsies of responders and nonresponders and between samples before and after RT. RESULTS: Ninety-four samples from 77 patients were analyzed: 68 pretreatment biopsies and 26 post-RT surgery specimens. Six patients had a (near) complete pathologic response, 3 patients had a good response, 32 patients had a partial response, and 22 patients had no or very limited response. Comparing patients with and without response to RT, 25 genes were significantly differentially expressed and were not linked to a pathway. Comparison of samples before and after RT identified significant changes in gene expression. Genes involved in p53 signaling, TNFA1 signaling, apoptosis, epithelial mesenchymal transition, and inflammatory response were upregulated. Genes involved in mitotic spindle, G2M checkpoint, and E2F targets were downregulated. CONCLUSIONS: Radiation-induced gene expression changes mainly involved p53 signaling, cell cycle regulation, DNA repair, and inflammatory response. No clinically significant differences could be identified in gene expression between patients with and without response to RT.

The molecular genetic make-up of male breast cancer.

Male breast cancer (MBC) is extremely rare and accounts for less than 1% of all breast malignancies. Therefore, clinical management of MBC is currently guided by research on the disease in females. In this study, DNA obtained from 45 formalin-fixed paraffin-embedded (FFPE) MBCs with and 90 MBCs (52 FFPE and 38 fresh-frozen) without matched normal tissues was subjected to massively parallel sequencing targeting all exons of 1943 cancer-related genes. The landscape of mutations and copy number alterations was compared to that of publicly available estrogen receptor (ER)-positive female breast cancers (smFBCs) and correlated to prognosis. From the 135 MBCs, 90% showed ductal histology, 96% were ER-positive, 66% were progesterone receptor (PR)-positive, and 2% HER2-positive, resulting in 50, 46 and 4% luminal A-like, luminal B-like and basal-like cases, respectively. Five patients had Klinefelter syndrome (4%) and 11% of patients harbored pathogenic BRCA2 germline mutations. The genomic landscape of MBC to some extent recapitulated that of smFBC, with recurrent PIK3CA (36%) and GATA3 (15%) somatic mutations, and with 40% of the most frequently amplified genes overlapping between both sexes. TP53 (3%) somatic mutations were significantly less frequent in MBC compared to smFBC, whereas somatic mutations in genes regulating chromatin function and homologous recombination deficiency-related signatures were more prevalent. MDM2 amplifications were frequent (13%), correlated with protein overexpression (P = 0.001) and predicted poor outcome (P = 0.007). In conclusion, despite similarities in the genomic landscape between MBC and smFBC, MBC is a molecularly unique and heterogeneous disease requiring its own clinical trials and treatment guidelines.

GPCR-SAS: A web application for statistical analyses on G protein-coupled receptors sequences.

G protein-coupled receptors (GPCRs) are one of the largest protein families in mammals. They mediate signal transduction across cell membranes and are important targets for the pharmaceutical industry. The G Protein-Coupled Receptors-Sequence Analysis and Statistics (GPCR-SAS) web application provides a set of tools to perform comparative analysis of sequence positions between receptors, based on a curated structural-informed multiple sequence alignment. The analysis tools include: (i) percentage of occurrence of an amino acid or motif and entropy at a position or range of positions, (ii) covariance of two positions, (iii) correlation between two amino acids in two positions (or two sequence motifs in two ranges of positions), and (iv) snake-plot representation for a specific receptor or for the consensus sequence of a group of selected receptors. The analysis of conservation of residues and motifs across transmembrane (TM) segments may guide the design of more selective ligands or help to rationalize activation mechanisms, among others. As an example, here we analyze the amino acids of the "transmission switch", that initiates receptor activation following ligand binding. The tool is freely accessible at http://lmc.uab.cat/gpcrsas/.

Mammary tumor-derived CCL2 enhances pro-metastatic systemic inflammation through upregulation of IL1ß in tumor-associated macrophages.

Patients with primary solid malignancies frequently exhibit signs of systemic inflammation. Notably, elevated levels of neutrophils and their associated soluble mediators are regularly observed in cancer patients, and correlate with reduced survival and increased metastasis formation. Recently, we demonstrated a mechanistic link between mammary tumor-induced IL17-producing γδ T cells, systemic expansion of immunosuppressive neutrophils and metastasis formation in a genetically engineered mouse model for invasive breast cancer. How tumors orchestrate this systemic inflammatory cascade to facilitate dissemination remains unclear. Here we show that activation of this cascade relies on CCL2-mediated induction of IL1ß in tumor-associated macrophages. In line with these findings, expression of CCL2 positively correlates with IL1Β and macrophage markers in human breast tumors. We demonstrate that blockade of CCL2 in mammary tumor-bearing mice results in reduced IL17 production by γδ T cells, decreased neutrophil expansion and enhanced CD8+ T cell activity. These results highlight a new role for CCL2 in facilitating the breast cancer-induced pro-metastatic systemic inflammatory γδ T cell - IL17 - neutrophil axis.

Predicting clinical benefit from everolimus in patients with advanced solid tumors, the CPCT-03 study.

BACKGROUND: In this study, our aim was to identify molecular aberrations predictive for response to everolimus, an mTOR inhibitor, regardless of tumor type. METHODS: To generate hypotheses about potential markers for sensitivity to mTOR inhibition, drug sensitivity and genomic profiles of 835 cell lines were analyzed. Subsequently, a multicenter study was conducted. Patients with advanced solid tumors lacking standard of care treatment options were included and underwent a pre-treatment tumor biopsy to enable DNA sequencing of 1,977 genes, derive copy number profiles and determine activation status of pS6 and pERK. Treatment benefit was determined according to TTP ratio and RECIST. We tested for associations between treatment benefit and single molecular aberrations, clusters of aberrations and pathway perturbation. RESULTS: Cell line screens indicated several genes, such as PTEN (P = 0.016; Wald test), to be associated with sensitivity to mTOR inhibition. Subsequently 73 patients were included, of which 59 started treatment with everolimus. Response and molecular data were available from 43 patients. PTEN aberrations, i.e. copy number loss or mutation, were associated with treatment benefit (P = 0.046; Fisher's exact test). CONCLUSION: Loss-of-function aberrations in PTEN potentially represent a tumor type agnostic biomarker for benefit from everolimus and warrants further confirmation in subsequent studies.

Long-term prognosis of young breast cancer patients (≤40 years) who did not receive adjuvant systemic treatment: protocol for the PARADIGM initiative cohort study.

INTRODUCTION: Currently used tools for breast cancer prognostication and prediction may not adequately reflect a young patient's prognosis or likely treatment benefit because they were not adequately validated in young patients. Since breast cancers diagnosed at a young age are considered prognostically unfavourable, many treatment guidelines recommend adjuvant systemic treatment for all young patients. Patients cured by locoregional treatment alone are, therefore, overtreated. Lack of prognosticators for young breast cancer patients represents an unmet medical need and has led to the initiation of the PAtients with bReAst cancer DIaGnosed preMenopausally (PARADIGM) initiative. Our aim is to reduce overtreatment of women diagnosed with breast cancer aged ≤40 years. METHODS AND ANALYSIS: All young, adjuvant systemic treatment naive breast cancer patients, who had no prior malignancy and were diagnosed between 1989 and 2000, were identified using the population based Netherlands Cancer Registry (n=3525). Archival tumour tissues were retrieved through linkage with the Dutch nationwide pathology registry. Tissue slides will be digitalised and placed on an online image database platform for clinicopathological revision by an international team of breast pathologists. Immunohistochemical subtype will be assessed using tissue microarrays. Tumour RNA will be isolated and subjected to next-generation sequencing. Differences in gene expression found between patients with a favourable and those with a less favourable prognosis will be used to establish a prognostic classifier, using the triple negative patients as proof of principle. ETHICS AND DISSEMINATION: Observational data from the Netherlands Cancer Registry and left over archival patient material are used. Therefore, the Dutch law on Research Involving Human Subjects Act (WMO) is not applicable. The PARADIGM study received a 'non-WMO' declaration from the Medical Ethics Committee of the Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, waiving individual patient consent. All data and material used are stored in a coded way. Study results will be presented at international (breast cancer) conferences and published in peer-reviewed, open-access journals.