Search

Many studies correlate changes in human gut microbiome with the onset of various diseases, mostly by 16S rRNA gene sequencing. Setting up the optimal sampling and DNA isolation procedures is crucial for robustness and reproducibility of the results. We performed a systematic comparison of several sampling and DNA isolation kits, quantified their effect on bacterial gDNA quality and the bacterial composition estimates at all taxonomic levels. Sixteen volunteers tested three sampling kits. All samples were consequently processed by two DNA isolation kits. We found that the choice of both stool sampling and DNA isolation kits have an effect on bacterial composition with respect to Gram-positivity, however the isolation kit had a stronger effect than the sampling kit. The proportion of bacteria affected by isolation and sampling kits was larger at higher taxa levels compared to lower taxa levels. The PowerLyzer PowerSoil DNA Isolation Kit outperformed the QIAamp DNA Stool Mini Kit mainly due to better lysis of Gram-positive bacteria while keeping the values of all the other assessed parameters within a reasonable range. The presented effects need to be taken into account when comparing results across multiple studies or computing ratios between Gram-positive and Gram-negative bacteria.

The dysfunction of the DNA mismatch repair system results in microsatellite instability (MSI). MSI plays a central role in the development of multiple human cancers. In colon cancer, despite being associated with resistance to 5-fluorouracil treatment, MSI is a favourable prognostic marker. In gastric and endometrial cancers, its prognostic value is not so well established. Nevertheless, recognising the MSI tumours may be important for predicting the therapeutic effect of immune checkpoint inhibitors. Several gene expression signatures were trained on microarray data sets to understand the regulatory mechanisms underlying microsatellite instability in colorectal cancer. A wealth of expression data already exists in the form of microarray data sets. However, the RNA-seq has become a routine for transcriptome analysis. A new MSI gene expression signature presented here is the first to be valid across two different platforms, microarrays and RNA-seq. In the case of colon cancer, its estimated performance was (i) AUC = 0.94, 95% CI = (0.90 – 0.97) on RNA-seq and (ii) AUC = 0.95, 95% CI = (0.92 – 0.97) on microarray. The 25-gene expression signature was also validated in two independent microarray colon cancer data sets. Despite being derived from colorectal cancer, the signature maintained good performance on RNA-seq and microarray gastric cancer data sets (AUC = 0.90, 95% CI = (0.85 – 0.94) and AUC = 0.83, 95% CI = (0.69 – 0.97), respectively). Furthermore, this classifier retained high concordance even when classifying RNA-seq endometrial cancers (AUC = 0.71, 95% CI = (0.62 – 0.81). These results indicate that the new signature was able to remove the platform-specific differences while preserving the underlying biological differences between MSI/MSS phenotypes in colon cancer samples.

BackgroundLong-term dysbiosis of the gut microbiome has a significant impact on the development, progression and the aggressiveness of colorectal cancer (CRC) and may explain part of the observed heterogeneity of the disease from phenotypic, prognostic and response to treatment perspectives. Although the shifts in gut microbiome in the normal-adenoma-carcinoma sequence have been described, the landscape of microbiome within CRC and its associations with clinical variables remain under-explored. ResultsWe performed 16S rRNA gene sequencing of paired tumour tissue, adjacent visually-normal mucosa and stool swabs of N=186 patients with stage 0-IV CRC to describe the tumour microbiome and its association with clinical variable and to derive tumour microbial subtypes.We identified new genera never previously associated with CRC tumour mucosa (Flavonifractor, Haemophilus, Howardella, Pseudomonas, Sutterella, Treponema 2) or CRC (Actinobacillus, Aggregatibacter, Bergeyella, Phocaeiola, Defluviitaleaceae UCG-011, Massilia, Tyzzerella 4). The bacteria residing on tumour-mucosa were dominated by genera belonging to (potential) oral pathogens. Based on tumour microbial profiles, we stratified CRC patients into three subtypes. The subtypes were significantly associated with prognostic factors such as tumor grade, primary tumour sidedness and TNM staging, with one subtype enriched in tumours with poor prognosis. Further, we inspected the associations of microbiome with clinical variables in a subtype-agnostic setting. The primary tumour-associated clinical variables predominantly correlated with tumour mucosal microbiome, while the presence of local and distant metastases was mostly associated with the stool microbiome.ConclusionsUnderstanding the interactions of the bacteria residing on tumour mucosa within different CRC tumour microbiome subtypes will help to better understand the underlying biological background of the heterogeneity of this disease. Indeed, the tumour microbiome is a possible source of additional integrative markers of CRC patients’ survival and prognosis. We found that CRC microbiome is strongly correlated with clinical variables, but these associations are dependent on the microbial environment (tumour mucosa, normal mucosa, stool). Our study thus identifies limitations of the usage of microbiome composition as marker of CRC progression, suggesting the need of combining several sampling sites (e.g. stool and tumour swabs).

Biomarker-guided treatment for patients with colon cancer is needed. We tested ABCG2 and topoisomerase 1 (TOP1) mRNA expression as predictive biomarkers for irinotecan benefit in the PETACC-3 patient cohort. The present study included 580 patients with mRNA expression data from Stage III colon cancer samples from the PETACC-3 study, which randomized the patients to Fluorouracil/leucovorin (5FUL) +/&minus, irinotecan. The primary end-points were recurrence free survival (RFS) and overall survival (OS). Patients were divided into one group with high ABCG2 expression (above median) and low TOP-1 expression (below 75 percentile) (&ldquo, resistant&rdquo, ) (n = 216) and another group including all other combinations of these two genes (&ldquo, sensitive&rdquo, ) (n = 364). The rationale for the cut-offs were based on the distribution of expression levels in the PETACC-3 Stage II set of patients, where ABCG2 was unimodal and TOP1 was bimodal with a high expression level mode in the top quarter of the patients. Cox proportional hazards regression was used to estimate the hazard ratios and the association between variables and end-points and log-rank tests to assess the statistical significance of differences in survival between groups. Kaplan-Meier estimates of the survival functions were used for visualization and estimation of survival rates at specific time points. Significant differences were found for both RFS (Hazard ratio (HR): 0.63 (0.44&ndash, 0.92), p = 0.016) and OS (HR: 0.60 (0.39&ndash, 0.93), p = 0.02) between the two biomarker groups when the patients received FOLFIRI (5FUL+irinotecan). Considering only the Microsatellite Stable (MSS) and Microsatellite Instability-Low (MSI-L) patients (n = 470), the differences were even more pronounced. In contrast, no significant differences were observed between the groups when patients received 5FUL alone. This study shows that the combination of ABCG2 and TOP1 gene expression significantly divided the Stage III colon cancer patients into two groups regarding benefit from adjuvant treatment with FOLFIRI but not 5FUL.

Background Breast cancer is a leading cause of cancer-related death in women worldwide. Despite extensive studies in all areas of basic, clinical and applied research, accurate prognosis remains elusive, thus leading to overtreatment of many patients. Diagnosis could be improved by introducing multigene molecular scores in standard clinical practice. Several tests that work with formalin-fixed tissue have become routine. Molecular scores usually include several genes representing processes, response to oestrogens, progestogens and human epidermal growth factor receptor 2 (Her2), respectively, which are combined additively in single values. These multi-gene scores have the advantage of being more robust and reproducible than single-gene scores. Their utility may be further enhanced by combining them with classical diagnostic parameters. Here, we present an exploratory study comparing the RISK and research versions of Oncotype DX recurrence score (RS), Prosigna Risk of Recurrence (ROR) and EndoPredict (EP) with respect to their prognostic potential for ipsilateral recurrence and/or distant relapse in brain, and we compared the scores to the intrinsic subtypes based on PAM50. Methods RNA was extracted from formalin-fixed, paraffin-embedded (FFPE) tissue cores of primary tumours, local recurrences and brain metastases. Gene expression was measured on a NanoString nCounter Analysis System. Intrinsic subtypes and molecular scores were computed according to published literature and RISK, RS, ROR and EP were compared against each other and to the intrinsic subtypes Luminal A (lumA), Luminal B (lumB), Her2-enriched (Her2↑), Basal-like (basal), and Normal-like (normal) of PAM50. Local recurrences and brain metastases were compared to their corresponding primary tumours. Results All four molecular scores were highly correlated. Highest correlations were observed among genes related to proliferation while lower correlations were found among oestrogen-related genes. The scores were significantly higher in primary tumours progressing to brain metastases as compared to recurrence-free primary tumours and primary tumours that relapsed as local recurrences. Conclusions RISK and ROR-P are prognostic for primary tumours metastasizing to the brain. All four scores, RISK, RS, EP and ROR-P failed to discriminate between primary tumours that remained recurrence-free and primary tumours relapsing as local recurrences. Electronic supplementary material The online version of this article (10.1186/s12885-019-5752-8) contains supplementary material, which is available to authorized users.

BRAF V600E mutations occur in ∼10% of colorectal cancer cases, are associated with poor survival, and have limited responses to BRAF/MEK inhibition with or without EGFR inhibition. There is an unmet need to understand the biology of poor prognostic BRAFMT colorectal cancer. We have used differential gene expression and pathway analyses of untreated stage II and stage III BRAFMT (discovery set: n = 31; validation set: n = 26) colorectal cancer, and an siRNA screen to characterize the biology underpinning the BRAFMT subgroup with poorest outcome. These analyses identified the unfolded protein response (UPR) as a novel and druggable pathway associated with the BRAFMT colorectal cancer subgroup with poorest outcome. We also found that oncogenic BRAF drives endoplasmic reticulum (ER) stress and UPR pathway activation through MEK/ERK. Furthermore, inhibition of GRP78, the master regulator of the UPR, using siRNA or small molecule inhibition, resulted in acute ER stress and apoptosis, in particular in BRAFMT colorectal cancer cells. In addition, dual targeting of protein degradation using combined Carfilzomib (proteasome inhibitor) and ACY-1215 (HDAC6-selective inhibitor) treatment resulted in marked accumulation of protein aggregates, acute ER stress, apoptosis, and therapeutic efficacy in BRAFMT in vitro and xenograft models. Mechanistically, we found that the apoptosis following combined Carfilzomib/ACY-1215 treatment is mediated through increased CHOP expression. Taken together, our findings indicate that oncogenic BRAF induces chronic ER stress and that inducers of acute ER stress could be a novel treatment strategy for poor prognostic BRAFMT colorectal cancer. Mol Cancer Ther; 17(6); 1280–90. ©2018 AACR.

Gifted students with learning disabilities are a heterogeneous group of children, often described as twice exceptional students. They exhibit puzzling patterns of behavior, higher-level intellectual abilities, advanced vocabulary, and exceptional comprehension of abstract ideas and concepts intertwined with poor reading and writing skills, and poor phonemic awareness. Current identification procedures fail on certain children because of the “masking” effect (due to the compensation process). Some controversial issues regarding identification of gifted students with learning disabilities are discussed, as well as some common intervention strategies.

Self-concept pattern of people with intellectual disability is characterized by cognitive deficits, labile affects, and motivation immaturity, poor coping initiatives, competence overestimation, unrealistic self-image. Educational–recuperative strategies must be designed and implemented by special education teachers in order to ameliorate the self-concept in adolescent students with intellectual disability and, therefore, to facilitate their full or partial mainstreaming in regular education settings.

Background Genomics and proteomics are nowadays the dominant techniques for novel biomarker discovery. However, histopathology images contain a wealth of information related to the tumor histology, morphology and tumor-host interactions that is not accessible through these techniques. Thus, integrating the histopathology images in the biomarker discovery workflow could potentially lead to the identification of new image-based biomarkers and the refinement or even replacement of the existing genomic and proteomic signatures. However, extracting meaningful and robust image features to be mined jointly with genomic (and clinical, etc.) data represents a real challenge due to the complexity of the images. Results We developed a framework for integrating the histopathology images in the biomarker discovery workflow based on the bag-of-features approach – a method that has the advantage of being assumption-free and data-driven. The images were reduced to a set of salient patterns and additional measurements of their spatial distribution, with the resulting features being directly used in a standard biomarker discovery application. We demonstrated this framework in a search for prognostic biomarkers in breast cancer which resulted in the identification of several prognostic image features and a promising multimodal (imaging and genomic) prognostic signature. The source code for the image analysis procedures is freely available. Conclusions The framework proposed allows for a joint analysis of images and gene expression data. Its application to a set of breast cancer cases resulted in image-based and combined (image and genomic) prognostic scores for relapse-free survival. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1072-z) contains supplementary material, which is available to authorized users.

Molecular subtypes have been recently derived for various types of cancer, in an attempt to characterize the intertumoral heterogeneity. In this work we explore the possibility of constructing predictors for molecular subtypes based on histopathology images. For this, we introduce a novel 2-level bag-of-features method and we apply it to a collection of colorectal cancer samples. The resulting image features capture some relevant tumor morphology patterns and led to a classifier performing similarly to one constructed from features annotated by an expert pathologist. The significance of our results extends beyond subtype prediction since they demonstrate a possible approach to multimodal (histopathology and molecular) data mining and biomarker identification.

Purpose Our purpose was development and assessment of a BRAF-mutant gene expression signature for colon cancer (CC) and the study of its prognostic implications. Materials and Methods A set of 668 stage II and III CC samples from the PETACC-3 (Pan-European Trails in Alimentary Tract Cancers) clinical trial were used to assess differential gene expression between c.1799T>A (p.V600E) BRAF mutant and non-BRAF, non-KRAS mutant cancers (double wild type) and to construct a gene expression–based classifier for detecting BRAF mutant samples with high sensitivity. The classifier was validated in independent data sets, and survival rates were compared between classifier positive and negative tumors. Results A 64 gene-based classifier was developed with 96% sensitivity and 86% specificity for detecting BRAF mutant tumors in PETACC-3 and independent samples. A subpopulation of BRAF wild-type patients (30% of KRAS mutants, 13% of double wild type) showed a gene expression pattern and had poor overall survival and survival after relapse, similar to those observed in BRAF-mutant patients. Thus they form a distinct prognostic subgroup within their mutation class. Conclusion A characteristic pattern of gene expression is associated with and accurately predicts BRAF mutation status and, in addition, identifies a population of BRAF mutated-like KRAS mutants and double wild-type patients with similarly poor prognosis. This suggests a common biology between these tumors and provides a novel classification tool for cancers, adding prognostic and biologic information that is not captured by the mutation status alone. These results may guide therapeutic strategies for this patient segment and may help in population stratification for clinical trials.

Differences exist between the proximal and distal colon in terms of developmental origin, exposure to patterning genes, environmental mutagens, and gut flora. Little is known on how these differences may affect mechanisms of tumorigenesis, side-specific therapy response or prognosis. We explored systematic differences in pathway activation and their clinical implications.Detailed clinicopathological data for 3045 colon carcinoma patients enrolled in the PETACC3 adjuvant chemotherapy trial were available for analysis. A subset of 1404 samples had molecular data, including gene expression and DNA copy number profiles for 589 and 199 samples, respectively. In addition, 413 colon adenocarcinoma from TCGA collection were also analyzed. Tumor side-effect on anti-epidermal growth factor receptor (EGFR) therapy was assessed in a cohort of 325 metastatic patients. Outcome variables considered were relapse-free survival and survival after relapse (SAR).Proximal carcinomas were more often mucinous, microsatellite instable (MSI)-high, mutated in key tumorigenic pathways, expressed a B-Raf proto-oncogene, serine/threonine kinase (BRAF)-like and a serrated pathway signature, regardless of histological type. Distal carcinomas were more often chromosome instable and EGFR or human epidermal growth factor receptor 2 (HER2) amplified, and more frequently overexpressed epiregulin. While risk of relapse was not different per side, SAR was much poorer for proximal than for distal stage III carcinomas in a multivariable model including BRAF mutation status [N = 285; HR 1.95, 95% CI (1.6-2.4), P0.001]. Only patients with metastases from a distal carcinoma responded to anti-EGFR therapy, in line with the predictions of our pathway enrichment analysis.Colorectal carcinoma side is associated with differences in key molecular features, some immediately druggable, with important prognostic effects which are maintained in metastatic lesions. Although within side significant molecular heterogeneity remains, our findings justify stratification of patients by side for retrospective and prospective analyses of drug efficacy and prognosis.

BACKGROUND: Prognosis prediction for resected primary colon cancer is based on the T-stage Node Metastasis (TNM) staging system. We investigated if four well-documented gene expression risk scores can improve patient stratification. METHODS: Microarray-based versions of risk-scores were applied to a large independent cohort of 688 stage II/III tumors from the PETACC-3 trial. Prognostic value for relapse-free survival (RFS), survival after relapse (SAR), and overall survival (OS) was assessed by regression analysis. To assess improvement over a reference, prognostic model was assessed with the area under curve (AUC) of receiver operating characteristic (ROC) curves. All statistical tests were two-sided, except the AUC increase. RESULTS: All four risk scores (RSs) showed a statistically significant association (single-test, P < .0167) with OS or RFS in univariate models, but with HRs below 1.38 per interquartile range. Three scores were predictors of shorter RFS, one of shorter SAR. Each RS could only marginally improve an RFS or OS model with the known factors T-stage, N-stage, and microsatellite instability (MSI) status (AUC gains < 0.025 units). The pairwise interscore discordance was never high (maximal Spearman correlation = 0.563) A combined score showed a trend to higher prognostic value and higher AUC increase for OS (HR = 1.74, 95% confidence interval [CI] = 1.44 to 2.10, P < .001, AUC from 0.6918 to 0.7321) and RFS (HR = 1.56, 95% CI = 1.33 to 1.84, P < .001, AUC from 0.6723 to 0.6945) than any single score. CONCLUSIONS: The four tested gene expression-based risk scores provide prognostic information but contribute only marginally to improving models based on established risk factors. A combination of the risk scores might provide more robust information. Predictors of RFS and SAR might need to be different.

Microsatellite instability (MSI) occurs in 10–20% of colorectal tumours and is associated with good prognosis. Here we describe the development and validation of a genomic signature that identifies colorectal cancer patients with MSI caused by DNA mismatch repair deficiency with high accuracy. Microsatellite status for 276 stage II and III colorectal tumours has been determined. Full-genome expression data was used to identify genes that correlate with MSI status. A subset of these samples (n = 73) had sequencing data for 615 genes available. An MSI gene signature of 64 genes was developed and validated in two independent validation sets: the first consisting of frozen samples from 132 stage II patients; and the second consisting of FFPE samples from the PETACC-3 trial (n = 625). The 64-gene MSI signature identified MSI patients in the first validation set with a sensitivity of 90.3% and an overall accuracy of 84.8%, with an AUC of 0.942 (95% CI, 0.888–0.975). In the second validation, the signature also showed excellent performance, with a sensitivity 94.3% and an overall accuracy of 90.6%, with an AUC of 0.965 (95% CI, 0.943–0.988). Besides correct identification of MSI patients, the gene signature identified a group of MSI-like patients that were MSS by standard assessment but MSI by signature assessment. The MSI-signature could be linked to a deficient MMR phenotype, as both MSI and MSI-like patients showed a high mutation frequency (8.2% and 6.4% of 615 genes assayed, respectively) as compared to patients classified as MSS (1.6% mutation frequency). The MSI signature showed prognostic power in stage II patients (n = 215) with a hazard ratio of 0.252 (p = 0.0145). Patients with an MSI-like phenotype had also an improved survival when compared to MSS patients. The MSI signature was translated to a diagnostic microarray and technically and clinically validated in FFPE and frozen samples. Copyright © 2012 Pathological Society of Great Britain and Ireland.

RAS activating mutations occur in ∼55% of metastatic (m) CRC. RASMT and >50% of RASWT mCRC patients (pts) do not benefit from anti-EGFR antibodies. c-MET is overexpressed in ∼50-60%, amplified in ∼2-3% and mutated in ∼1-3% of mCRC. Preclinical data support the clinical evaluation of MEK1/2 and METi, in particular in RASMT tumours and RASWT with aberrant c-MET expression. The primary aim of the phase I study was to establish the maximum tolerated dose (MTD) and assess safety/toxicity profile of PD-0325901 MEKi & crizotinib METi in pts with advanced solid tumours using NCI CTCAE V4.03.

Introduction - MErCuRIC is a Phase Ib/II clinical trial study using a combined MEK1/2 - cMET inhibition in RAS MT and RAS WT (with aberrant c-MET) colorectal cancer patients. As part of the discovery efforts on the cases enrolled in Phase I, we aimed to analyze the mutation status of 10 genes that could potentially be associated to the doublet MEK/MET inhibition. This study compared the MEK/MET-specific panel with the Ion Torrent 50 gene panel, aiming to compare: long-established, commercially available panels against this newly developed panel; the Ion Torrent PGM2 platform against Illumina MiSeq v.3 600 bp chemistry; hot-spot-based against full exomes-designed; and to compare the use of different bioinformatics reporter systems. The overlapping genes between the panels were: EGFR (n = 3); BRAF (n = 4); KRAS (n = 8); NRAS (n = 1); MET (n = 8); PIK3CA (n = 6); and ERBB2 (n = 5). Summary of Method NGS Design - The Multiplicom - MErCuRIC specific MASTR assay includes PTEN, MAP2K1 (MEK), EGFR, KRAS, NRAS, BRAF, PIK3CA, ERBB2, MET and PIK3R1, involving 257 amplicons in 4 plexes covering all coding exons of the 10 genes. Of the 257, 21 are control amplicons to allow for gene deletions/amplifications. The average length of the amplicons is 198 bp ranging from 124 bp to 255 bp. Validation - From a pool of 120 routine tumour samples characterised with a 50 gene mutation panel (Ion Torrent PGM2) and confirmed by Sanger sequencing and/or COBAS (Roche) QPCR, 24 FFPE cases were selected representing colorectal cancer and 4 other solid tumour types; all included a variety of DNA quality, and DNA concentration was standardized prior to library preparation. Pre-analytical handling was in accordance with established protocols in a laboratory, clinically-accredited in the UK for tissue-based, anatomical pathology testing. Results The evaluation of this MEK/MET-specific panel (Illumina MiSeq platform) resulted in 100% coverage of all targets, a higher than 97% on target reads and higher than 99% of all amplicons within 20% of mean coverage. The design minimized the areas of low coverage. A small part of exon 9 of ERBB2 was covered suboptimally: the low covered region is 30 bp in size located at the 5’ end of exon 9. It is unlikely that this low coverage led to false negative results since no mutations are reported in the COSMIC database for this DNA fragment. The results were concordant in relation to mutations involved in the genes stated above. Importantly, the percentages of allele frequency between both methods were similar, with variations ranging from 0.2% to 11.5% with an average variation of 5.2%. Insertion/deletion (Indel) detection however, required alternative bioinformatics pathways. Conclusion After combining well-established quality metrics to cover pre-analytical aspects with suitable technologies such as the MiSeq platform (Illumina) and appropriate bioinformatics, we recognize that this MEK/MET-specific NGS panel is fit for purpose. Citation Format: Perry Maxwell, Jurgen Del Favero, Marc-Aurel Fuchs, Josep Tabernero, Tim Maughan, Mark Middleton, Richard Addams, Christian Rolfo, Brian Hennessey, Pierre Laurent-Puig, Alberto Bardelli, Thierry Andre, Vlad Popovici, Patrick Johnstone, Richard Wilson, Mark Lawler, Sandra Van Schaeybroeck, Manuel Salto Tellez. Validation of a MEK/MET-specific NGS panel for early phase trial interrogation. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1396.

Background The purpose of the work reported here is to test reliable molecular profiles using routinely processed formalin-fixed paraffin-embedded (FFPE) tissues from participants of the clinical trial BIG 1-98 with a median follow-up of 60 months. Methods RNA from fresh frozen (FF) and FFPE tumor samples of 82 patients were used for quality control, and independent FFPE tissues of 342 postmenopausal participants of BIG 1-98 with ER-positive cancer were analyzed by measuring prospectively selected genes and computing scores representing the functions of the estrogen receptor (eight genes, ER_8), the progesterone receptor (five genes, PGR_5), Her2 (two genes, HER2_2), and proliferation (ten genes, PRO_10) by quantitative reverse transcription PCR (qRT-PCR) on TaqMan Low Density Arrays. Molecular scores were computed for each category and ER_8, PGR_5, HER2_2, and PRO_10 scores were combined into a RISK_25 score. Results Pearson correlation coefficients between FF- and FFPE-derived scores were at least 0.94 and high concordance was observed between molecular scores and immunohistochemical data. The HER2_2, PGR_5, PRO_10 and RISK_25 scores were significant predictors of disease free-survival (DFS) in univariate Cox proportional hazard regression. PRO_10 and RISK_25 scores predicted DFS in patients with histological grade II breast cancer and in lymph node positive disease. The PRO_10 and PGR_5 scores were independent predictors of DFS in multivariate Cox regression models incorporating clinical risk indicators; PRO_10 outperformed Ki-67 labeling index in multivariate Cox proportional hazard analyses. Conclusions Scores representing the endocrine responsiveness and proliferation status of breast cancers were developed from gene expression analyses based on RNA derived from FFPE tissues. The validation of the molecular scores with tumor samples of participants of the BIG 1-98 trial demonstrates that such scores can serve as independent prognostic factors to estimate disease free survival (DFS) in postmenopausal patients with estrogen receptor positive breast cancer. Trial Registration Current Controlled Trials: NCT00004205

Fgfrl1 (also known as Fgfr5; OMIM 605830) homozygous null mice have thin, amuscular diaphragms and die at birth because of diaphragm hypoplasia. FGFRL1 is located at 4p16.3, and this chromosome region can be deleted in patients with congenital diaphragmatic hernia (CDH). We examined FGFRL1 as a candidate gene for the diaphragmatic defects associated with 4p16.3 deletions and re-sequenced this gene in 54 patients with CDH. We confirmed six known coding single nucleotide polymorphisms (SNPs): c.209G > A (p.Pro20Pro), c.977G > A (p.Pro276Pro), c.1040T > C (p.Asp297Asp), c.1234C > A (p.Pro362Gln), c.1420G > T (p.Arg424Leu), and c.1540C > T (p.Pro464Leu), but we did not identify any gene mutations. We genotyped additional CDH patients for four of these six SNPs, including the three non-synonymous SNPs, to make a total of 200 chromosomes, and found that the allele frequency for the four SNPs, did not differ significantly between patients and normal controls (p > or = 0.05). We then used Affymetrix Genechip Mouse Gene 1.0 ST arrays and found eight genes with significantly reduced expression levels in the diaphragms of Fgfrl1 homozygous null mice when compared with wildtype mice-Tpm3, Fgfrl1 (p = 0.004), Myl2, Lrtm1, Myh4, Myl3, Myh7 and Hephl1. Lrtm1 is closely related to Slit3, a protein associated with herniation of the central tendon of the diaphragm in mice. The Slit proteins are known to regulate axon branching and cell migration, and inhibition of Slit3 reduces cell motility and decreases the expression of Rac and Cdc42, two genes that are essential for myoblast fusion. Further studies to determine if Lrtm1 has a similar function to Slit3 and if reduced Fgfrl1 expression can cause diaphragm hypoplasia through a mechanism involving decreased myoblast motility and/or myoblast fusion, seem indicated.

Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.

TPS3632 Background: RAS is mutated (RASMT) in ~55% of mCRC, and phase III studies have shown that patients harbouring RAS mutations do not benefit from anti-EGFR MoAbs. In addition, ~50% of RAS Wil...

The EurOPDX Consortium is an initiative of translational and clinical researchers from 14 cancer centers and universities across 9 European countries, with the common goal of creating a network of clinically relevant models of human cancer, and in particular patient-derived xenograft (PDX) models. PDX models, which are generated by transplantation into an immunodeficient mouse of a patient's tumor obtained fresh from surgery, are broadly implemented for all cancer pathologies by translational laboratories (Tentler et al., 2012). Grafted tumors have been shown to maintain high similarities with the original patient tumor. Hence, preclinical trials in large panels of models recapitulating the intertumor heterogeneity of human cancer have been shown to reproduce data obtained in clinical trials (Bertotti et al., 2011; Julien et al., 2012). The primary goal of the EurOPDX Consortium is to share PDX models and perform collaborative multicenter and multipathology "xeno patient" trials within molecularly defined tumor subsets, resulting in hypothesis-driven personalized medicine strategies for cancer patients. Altogether, the Consortium displays a panel of more than 1,500 PDX subcutaneous and orthotopic models in more than 30 pathologies, including for instance 640 models obtained from primary tumors or metastases of colorectal cancer, 200 models of pancreatic cancer, and over 120 models of breast cancer. The characterization of models will be harmonized and will include deep molecular profiling and pharmacogenomic data corresponding to current anticancer therapies. Through implementation of a shared database and the emergence of a common biobank of patient-derived viable cancer specimens, the Consortium will use characterization data to identify novel strategies for pinpointing new targets and overcoming drug resistance, and will validate therapeutic hits in collaborative multicentric preclinical trials. Best practices for the performance of such trials in mice will be implemented, with the goal of advancing their predictivity for success in the clinic. The Consortium will also generate new PDX models and integrate complementary models such as ex vivo 2D and 3D assays to achieve research goals. Implementing PDX models in the discovery of predictive biomarkers for targeted therapies will be a key objective. This initiative will create a pipeline that will greatly accelerate and advance the development of novel therapeutic strategies and their validation for cancer treatment, through more predictive preclinical or "co-clinical" data. Through this collaborative effort that is to our knowledge, unique in Europe, and the participation of pharmaceutical companies and SMEs involved in drug development, we aim to reduce the duplication of efforts in oncology drug development, ultimately improving the quality of life and overall survival of cancer patients. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):A8. Citation Format: Emilie Vinolo, Elisabetta Marangoni, Violeta Serra, Frederic Amant, Andrea Bertotti, Andrew V. Biankin, Anne-Lise Børresen-Dale, Alejandra Bruna, Eva Budinská, Annette Byrne, Carlos Caldas, David Chang, Robert Clarke, Els Hermans, Manuel Hidalgo, Steven de Jong, Jos Jonkers, Pedro López, Gunhild Mari Mælandsmo, Vlad Popovici, Sergio Roman-Roman, Joan Seoane, Livio Trusolino, Alberto Villanueva, on behalf of the EurOPDX Consortium. The EurOPDX consortium: Sharing patient tumor-derived xenografts for collaborative multicentric preclinical trials. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr A8.

In a robust and unsupervised analysis of 1113 stage II-III CRC gene expression profiles from PETACC3 and 4 public datasets we defined a set of five gene expression subtypes which were validated in an independent set of 720 samples. We tested these subtypes with common clinico-pathological features, copy number variations, mutations in key cancer associated genes - such as BRAF or KRAS - and prognosis, and found important associations. The gene set enrichment analysis of groups of genes with similar gene expression patterns and existing CRC signatures followed by the literature search of gene members identified a number of biological motifs underlying the CRC gene expression heterogeneity, such as EMT/stroma, immune, proliferation, Wnt signaling, 20q chromosome, markers of enterocytes, secretory cell markers or lipid synthesis. Based on these results we named the subtypes A: Surface crypt, B: Lower crypt, C: CIMP-H-like, D: Mesenchymal and E: Mixed. Subtype A, specific by expression of markers of differentiated colon crypt cells was enriched for KRAS mutant tumors (77%); WNT-high proliferative subtype B had a good prognosis and comprised mainly MSS (100%) and left (76%); subtype C had the worse prognosis in SAR and was enriched for BRAFm (29%), right (73%), MSI (60%) and mucinous (38%) tumors. Subtype D, with the worse prognosis in OS and RFS was characteristic by high expression of EMT/stroma genes and subtype E enriched for p53 mutations (73%). We performed nuclear β-catenin immunoreactivity scoring of paraffin sections of 133 samples and found significant associations with the subtypes. The supervised histopathological assessment of the same set of paraffin sections resulted in an identification of subtype specific morphological patterns (serrated and papillary pattern in subtype A, complex tubular pattern in subtypes B and E, solid and mucinous in subtype C, desmoplastic reaction in D). Next, we concentrated our efforts on gene networks analysis in order to identify subtype specific gene-gene interactions. These results further refined between-subtype differences. The proposed CRC characterization provides a molecular basis to different morphological patterns in CRC and the identified molecular motifs allow subtypes to be further interrogated functionally in vitro for driving oncogenic events. Citation Format: Eva Budinska, Andrea Janotova, Sabine Tejpar, Vlad Popovici, Giovanni D'Ario, Nicolas Lapique, Katarzyna Otylia Sikora, Antonio Fabio Di Narzo, Pu Yan, John Graeme Hodgson, Scott Weinrich, Fred Bosman, Arnaud Roth, Mauro Delorenzi. Colorectal cancer heterogeneity from a gene expression perspective. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 823. doi:10.1158/1538-7445.AM2013-823

Background Approximately 8-15% of colorectal (CRC) patients carry an activating mutation in BRAF. This CRC subtype is associated with poor outcome and with resistance, both to chemotherapeutic treatments and to tailored drugs. We recently showed that BRAF (V600E) colon cancers (CCs) have a characteristic gene expression signature (1, 2) which is found also in subsets of KRAS mutant and KRAS-BRAF wild type (WT2) tumors. Tumors having this gene signature, referred as “BRAF-like," have a similar poor prognosis irrespective of the presence of the BRAF (V600E) mutation. By using a shRNA-based genetic screen in BRAF mutant CC cell lines we aimed to identify genes and pathways necessary for survival and growth of BRAF mutant CC. Such studies may reveal additional targets for therapy and potentially provide new biomarkers for patient stratification. Method We identified 363 genes that are selectively overexpressed in BRAF mutant tumors as compared to WT2 type tumors, based on gene expression profiles of the PETACC3 (1) and Agendia (1) datasets. The TRC human genome-wide shRNA collection (TRC-Hs1.0) was used to generate a 1815 hairpins sub-library targeting those identified genes (BRAF library). BRAF(V600E) CC cell lines were infected with the BRAF library and screened for shRNAs that cause lethality. LIM1215 CC cell line (WT2) was used as a control. Cells stably expressing the shRNA library were cultured for 13 days, after which shRNAs were recovered by PCR. Deep sequencing was applied to determine the specific depletion of shRNA in BRAF(V600E) cells as compared to LIM1215 cells. Results Candidate genes were identified by using following filtering criteria: depletion in BRAF(V600E) cells by at least 50% and depletion in BRAF(V600E) cells 1,5-fold higher than in control cells with the corresponding p-value to be ≤ 0.1. A total of 34 genes met our criteria of which 6 genes were presented with more than one hairpin and were concordant across the cell lines selected for validation. Conclusion We identified candidate synthetic lethal genes in BRAF mutant CC cell lines. Functional analysis is ongoing. Data will be presented. Citation Format: Loredana Vecchione, Valentina Gambino, Giovanni D'Ario, Tian Sun, Iris Simon, Vlad Popovici, Mauro Delorenzi, Rene’ Bernards, Sabine Tejpar. Identification of synthetic lethal interactions with the BRAF oncogene in colorectal cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1219. doi:10.1158/1538-7445.AM2013-1219

Background The mutation status of the BRAF and KRAS genes has been proposed as prognostic biomarker in colorectal cancer. Of them, only the BRAF V600E mutation has been validated independently as prognostic for overall survival and survival after relapse, while the prognostic value of KRAS mutation is still unclear. We investigated the prognostic value of BRAF and KRAS mutations in various contexts defined by stratifications of the patient population. Methods We retrospectively analyzed a cohort of patients with stage II and III colorectal cancer from the PETACC-3 clinical trial (N = 1,423), by assessing the prognostic value of the BRAF and KRAS mutations in subpopulations defined by all possible combinations of the following clinico-pathological variables: T stage, N stage, tumor site, tumor grade and microsatellite instability status. In each such subpopulation, the prognostic value was assessed by log rank test for three endpoints: overall survival, relapse-free survival, and survival after relapse. The significance level was set to 0.01 for Bonferroni-adjusted p-values, and a second threshold for a trend towards statistical significance was set at 0.05 for unadjusted p-values. The significance of the interactions was tested by Wald test, with significance level of 0.05. Results In stage II-III colorectal cancer, BRAF mutation was confirmed a marker of poor survival only in subpopulations involving microsatellite stable and left-sided tumors, with higher effects than in the whole population. There was no evidence for prognostic value in microsatellite instable or right-sided tumor groups. We found that BRAF was also prognostic for relapse-free survival in some subpopulations. We found no evidence that KRAS mutations had prognostic value, although a trend was observed in some stratifications. We also show evidence of heterogeneity in survival of patients with BRAF V600E mutation. Conclusions The BRAF mutation represents an additional risk factor only in some subpopulations of colorectal cancers, in others having limited prognostic value. However, in the subpopulations where it is prognostic, it represents a marker of much higher risk than previously considered. KRAS mutation status does not seem to represent a strong prognostic variable.

To develop a comprehensive overview of copy number aberrations (CNAs) in stage-II/III colorectal cancer (CRC), we characterized 302 tumors from the PETACC-3 clinical trial. Microsatellite-stable (MSS) samples (n = 269) had 66 minimal common CNA regions, with frequent gains on 20 q (72.5%), 7 (41.8%), 8 q (33.1%) and 13 q (51.0%) and losses on 18 (58.6%), 4 q (26%) and 21 q (21.6%). MSS tumors have significantly more CNAs than microsatellite-instable (MSI) tumors: within the MSI tumors a novel deletion of the tumor suppressor WWOX at 16 q23.1 was identified (p

3509 Background: Prognosis prediction for resected primary colon cancer is currently based on the tumor, nodes, metastasis (TNM) staging system. Gene expression based risk scores have been proposed, but need to be validated and integrated with clinical and TNM variables. We performed an independent assessment of the individual recurrence signatures developed for commercial use by Veridex and Genomic Health. Methods: The Veridex (aVDS) and Genomic Health (aGHS) risk scores were applied to existing gene expression data of 580 stage III and 108 stage II tumors from the PETACC-3 trial. Association of the scores with relapse-free (RFS) and overall survival (OS) of the patients was assessed singularly, and in a combination with TNM and other clinico-pathological variables, by univariate and multivariate Cox regression models and logrank methods. Results: Both risk scores were significantly associated with RFS in univariate and multivariate models (Table) for the stage III cohort. The scores contributed different and additive prognostic information, and reached highest effect sizes (approximate p-value 0.001 and HR per interquartile range 1.4 each) in a combined model (Table) that includes both scores as well as T-stage, N-stage and MSI status as significant factors. Analysis in the stage II cohort gave similar effect estimates. Conclusions: This study confirms in an independent colon cancer patient cohort that gene expression based risk scores improve current prognostic models. The best prognostic model was obtained by using clinico-pathological variables and both gene-expression risk-scores. [Table: see text]

3511 Background: From a clinical perspective colorectal cancer (CRC) is a heterogeneous disease whose biological background is insufficiently understood. In order to adapt targeted treatment to biologically different categories of CRC patients, in depth understanding of the molecular mechanisms involved in CRC heterogeneity is urgently needed. Methods: Consensus cluster analysis of 1113 stage II-III CRC gene expression profiles from PETACC3 and 4 public datasets defined a set of subtypes which were confirmed in an independent set of 720 samples. The similarity between tumors was based on a set of 54 meta-genes. This approach improves the robustness to measurement noise and gives equal chances to each biological process to be accounted for in the subtype definition. We tested the association of the subtypes with clinical variables, molecular markers and patient survival. Results: We identified and validated 5 major subtypes A-E, with different levels of expression in 6 main molecular processes: epithelial-mesenchymal transition (EMT), immune response, colon crypt differentiation, proliferation, Wnt signaling and chromosome 20q. Significant differences in survival and an enrichment for markers such as MSI, BRAF mutation, site or p53 status were found between the subtypes. In addition, the new subtype classification uncovered heterogeneity within groups defined by these commonly used markers. Survival analysis showed significant prognostic value for meta-genes connected to EMT, proliferation and differentiation. Identical data processing and clustering applied to the validation set on the same meta-genes resulted in subtypes with almost identical expression patterns. Conclusions: We identified and validated robust molecular subtypes in the largest set of stage II-III CRC samples as a combination of multiple molecular processes, that complement current disease stratification based on clinico-pathological variables and molecular markers. The biological relevance of these subtypes was reflected in significant differences in survival. These insights open new perspectives for improving prognostic models and rationalize the prediction of tumor-specific drug sensitivity.

Background: We previously identified highly conserved gene expression patterns associated with BRAF V600E mutant MSS colon cancer (Tejpar et al, ASCO 2010). Since these tumors have very poor overall survival and are refractory to therapy, a better understanding of their molecular characteristics is relevant. In this study we explored if the observed BRAF-mutated characteristic gene expression patterns are also present in any non BRAF-mutant subgroup of colon cancer and what the prognostic implications might be. Methods: A representative set of 667 stage II and III FFPE colon cancers from the PETACC3 clinical trial with 7 years follow up data were used for this study. Samples were characterized for KRAS (39% of samples) and BRAF (6.5%) mutation status, Microsatellite instability (9.7%) (Roth et al, JCO 2009) and gene expression data was obtained with the ALMAC “Colorectal Cancer DSA(tm)” platform. A BRAF signature was built using top scoring pairs and was validated internally (split-sample and cross-validation) and externally (in two independent data sets). It was then applied to KRAS mutant and KRAS wild type (WT) MSI and MSS colon carcinomas. Prognostic value of the signature for overall survival (OS) and survival after relapse (SAR) was assessed by Cox proportional hazard models and survival distributions were compared using likelihood ratio tests. Results: A novel 78-gene BRAF signature was identified and validated, with independent validation performance measured by area under the ROC curve between 0.83 and 0.95. The BRAF signature had high sensitivity in predicting BRAF mutants (>88% internal and >75% external validation) and, in addition, it identified a subpopulation of ‘BRAF-like’ patients with poor prognosis, consisting of 37% of all KRAS mutants and of 13% of all double WT (WT2 – non BRAF and non KRAS mutants). In the whole population and in the MSS subpopulation the signature was prognostic for OS (whole population: hazard ratio HR=1.63, p=0.001; MSS HR=2.25, p Conclusions: Using a BRAF mutated derived gene expression signature, we identified a new subgroup within the BRAF WT population that bears a similar gene expression pattern and displays a similar bad prognosis. The signature identifies patients for whom additional therapeutic interventions would be important and the genes included might provide new therapeutic targets. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4722. doi:10.1158/1538-7445.AM2011-4722

3597 Background: Microsatellite instability (MSI) is the hallmark of a deficient mismatch repair system (MMR) in about 15% of colorectal cancers (CRC). Other studies and our own confirm MSI as an i...

Reference EPFL-CONF-159813View record in Web of Science Record created on 2010-11-30, modified on 2017-05-10

Abstract #1073 BIG 1-98 is a randomized controlled clinical trial for postmenopausal patients with early, estrogen and/or progesterone receptor (ER/PgR) positive breast cancer. It compares adjuvant therapy with 5 years of tamoxifen (T) or letrozole (L), two years of T followed by 3 years of L (T→L) or vice versa (L→T). L improved disease free survival (DFS) over T by 18% (hazard ratio 0.82, JCO 2007;25:486ff). Switzerland contributed 598/8010 patients. The patient and tumor characteristics of Swiss patients was similar to the entire BIG 1-98 population. The purpose of this study was to test a prognostic score in RNA derived from FFPE tissues. Scores representing ER and progesterone receptor (PgR) function, proliferation (PRO14, AURKA/STK15, BIRC5/SURV, CCNB1, CCNB2, CCNE2, CDC2, ENPF, KIF20A, MKI67, MYBL2, ORC6L, PRC1, SPAG5, TOP2A), and HER-2 were built from multiple genes for each score. Genes were selected according to an analysis of publicly available cDNA array databases. In a prior set of 82 pairs of breast cancer samples the Pearson correlation coefficients of the scores between fresh frozen and FFPE tissues were at least 0.94. Cut-offs for ER and HER-2 scores were defined as the antimodes of fitted bimodal Gaussian distributions; the ER and HER-2 scores closely agreed with immunohistochemical (IHC) data (kappa(ER)=0.868, kappa(HER-2)=0.836). FFPE tissues were available from 437 Swiss BIG 1-98 patients. RNA of sufficient quantity and quality was extracted from 388 blocks (89%). Forty-seven genes were quantified by QRTPCR on TaqMan Low Density Arrays (TLDAs) as reported previously (Proc AACR 2008, Abstract 974). The PRO14 score was positively correlated with the histological grade. PRO14 scores greater than the median and PGR scores lower than the median were associated with shorter DFS. In patients with grade 2 tumors, PRO14 scores were significant predictors of DFS in univariate Cox regression analyses. Multivariate analyses will be presented. Our findings are in agreement with an analysis of fresh frozen tissues of Belgian participants in BIG 1-98 (European Breast Cancer Conference 2008, Abstract 481).We show that RNA can be extracted from FFPE in sufficient quantity and quality to be used in QRTPCR using TLDAs. This opens the possibility of using FFPE tumor banks from controlled clinical trials for the investigation of gene expression patterns. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 1073.

3505 Background: KRAS and BRAF activating mutations (mut) are frequent in colorectal cancer (CRC). Both genes act in the ERK pathway, but they occur in different CRC subtypes and have different prognostic implications, suggesting they might entail disruptions in different signaling pathways. Methods: RNA extracted from 1378 formalin-fixed tissues was used for expression profiling on the Affymetrix-based ALMAC platform Colorectal Cancer DSA. KRAS G12S, G13V, G13C, G13D, G12R, G13A, G12V, G12D, G12G, G12C, G12A, G12G mut and BRAF V600 were assessed. BRAF mut vs KRAS mut and BRAF or KRAS mut versus double wildtype (wt) were compared. Statistical analysis of differential expression was performed with standard methods in R. Classifiers were constructed using AdaBoost and DLDA algorithms and performance estimated by cross-validation. Results: KRAS mut were found in 37%, BRAF mut in 8%. Outcome correlations were reported (Roth A,JCO 2010). To date, 244 hybridized samples were analyzed (25 BRAF mut, 91 KRAS mut),...

3575 Background: The activation of the MEK/ERK signaling cascade by KRAS or BRAF mutations has a high incidence in colorectal cancer (CRC). While these mutations are mutually exclusive, we have identified a highly conserved gene expression pattern, characteristic to BRAF mutants, that can also be observed in KRAS mutants (AACR 2011, JCO 2012), and which defines a distinct subpopulation. Its characterization is important as it may shed a light on the observed survival and treatment response variability of this group of CRCs. Methods: A set of 257 stage II and III KRAS mutant CRCs from the PETACC3 clinical trial and a subset of 150 CRCs from TCGA project were used for this study. Gene expression data was available for all samples and, additionally, CNV and methylation data was available for some of the samples. Due to the limited number of MSI samples, the analyses were focused on MSS subpopulation. Results: The cluster analysis on the genes from the BRAF signature clearly indicated a major split of the KRAS mutants into two subgroups, that were further compared in terms of clinico-pathological and survival parameters. The BRAF-mutant-like (BML) subgroup was clearly enriched in MSI-H (p

e14544 Background: We identified CRC gene expression subtypes (ASCO 2012, #3511), which associate with established parameters of outcome as well as relevant biological motifs. We now substantiate their biological and potentially clinical significance by linking them with cell line data and drug sensitivity, primarily attempting to identify models for the poor prognosis subtypes Mesenchymal and CIMP-H like (characterized by EMT/stroma and immune-associated gene modules, respectively). Methods: We analyzed gene expression profiles of 35 publicly available cell lines with sensitivity data for 82 drug compounds, and our 94 cell lines with data on sensitivity for 7 compounds and colony morphology. As in vitro, stromal and immune-associated genes loose their relevance, we trained a new classifier based on genes expressed in both systems, which identifies the subtypes in both tissue and cell cultures. Cell line subtypes were validated by comparing their enrichment for molecular markers with that of our CRC subtypes. Drug sensitivity was assessed by linking original subtypes with 92 drug response signatures (MsigDB) via gene set enrichment analysis, and by screening drug sensitivity of cell line panels against our subtypes (Kruskal-Wallis test). Results: Of the cell lines 70% could be assigned to a subtype with a probability as high as 0.95. The cell line subtypes were significantly associated with their KRAS, BRAF and MSI status and corresponded to our CRC subtypes. Interestingly, the cell lines which in matrigel created a network of undifferentiated cells were assigned to the Mesenchymal subtype. Drug response studies revealed potential sensitivity of subtypes to multiple compounds, in addition to what could be predicted based on their mutational profile (e.g. sensitivity of the CIMP-H subtype to Dasatinib, p

3522 Background: The BRAF and KRAS mutations have been proposed as prognostic markers in colorectal cancer (CRC). Of them, only the BRAF V600E mutation has been validated as prognostic for overall survival and survival after relapse, while the value of KRAS mutation is still unclear. Methods: In a cohort of 1423 stage II-III patients from the PETACC-3 clinical trial, the prognostic value of the BRAF and KRAS mutations was retrospectively assessed in all possible stratifications defined by the 5 factors (T and N stage, tumor site and grade, and microsatellite instability status), by log rank test for overall survival (OS), relapse-free survival (RFS), and survival after relapse (SAR). The presence of interactions was tested by Wald test. The significance level was set to 0.01 for Bonferroni-adjusted p-values (P*), and a second level for a trend towards statistical significance was set at 0.05 for unadjusted p-values (P). Results: BRAF mutation was a marker of poor OS only in microsatellite stable (MSS) and left-sided tumors, with no prognostic value in microsatellite instable (MSI-H) or right-sided tumors. In MSS/left-sided tumors, BRAF mutation represents a marker of higher risk than previously reported: OS HR=6.4 [95% CI: 3.6-11.5], P* < 0.0001. For SAR, BRAF was prognostic in more stratifications, with higher risk in MSS/left-sided tumors (HR=3.9 [95% CI: 2.1-7.2], P* = 0.0002) than in MSS/right-sided (HR=2.3 [95% CI: 1.2-4.4], P=0.01). A novel observation was that BRAF mutation was prognostic also for RFS, but only in MSS/left-sided tumors (HR=3.6 [95% CI:2-6.3], P*=0.0005]). Additionally, heterogeneity in OS and RFS among BRAF mutants was observed. In general, KRAS mutation did not reach the significance level required, but showed a trend to become a prognostic marker for RFS in MSS tumors with early lymph node involvement (N1) (HR=1.6 [95% CI:1.1-2.2], P=0.01). Conclusions: The prognostic utility of the BRAF and KRAS mutations has to be interpreted in the context of other factors. For the BRAF mutation, a clear interaction with MSI status and tumor site was observed, with BRAF mutation indicating a much higher risk in MSS/left-sided tumors than previously considered.

403 Background: Approximately 8-15% of colorectal (CRC) patients carry an activating mutation in BRAF. This CRC subtype is associated with poor outcome and with resistance, both to chemotherapeutic treatments and to tailored drugs. We recently showed that BRAF (V600E) colon cancers (CCs) have a characteristic gene expression signature (1, 2) which is found also in subsets of KRAS mutant and KRAS-BRAF wild type (WT2) tumors. Tumors having this gene signature, referred as “BRAF-like”, have a similar poor prognosis irrespective of the presence of the BRAF (V600E) mutation. By using a shRNA-based genetic screen in BRAF mutant CC cell lines we aimed to identify genes and pathways necessary for survival and growth of BRAFmutant CC. Such studies may reveal additional targets for therapy and potentially provide new biomarkers for patient stratification Methods: We identified 363 genes that are selectively overexpressed in BRAF mutant tumors as compared to WT2 type tumors, based on gene expression profiles of the PETACC3 (1) and Agendia (2) datasets. The TRC human genome-wide shRNA collection (TRC-Hs1.0) was used to generate a 1815 hairpins sub-library targeting those identified genes (BRAF library). BRAF(V600E) CC cell lines were infected with the BRAF library and screened for shRNAs that cause lethality. LIM1215 CC cell line (WT2) was used as a control. Cells stably expressing the shRNA library were cultured for 13 days, after which shRNAs were recovered by PCR. Deep sequencing was applied to determine the specific depletion of shRNA in BRAF(V600E) cells as compared to LIM1215 cells Results: Candidate genes were identified by using following filtering criteria: depletion in BRAF(V600E) cells by at least 50% and depletion in BRAF(V600E) cells 1, 5-fold higher than in control cells with the corresponding p-value to be ≤ 0.1. A total of 34 genes met our criteria of which 6 genes were presented with more than one hairpin and were concordant across the cell lines selected for validation. Conclusions: We identified candidate synthetic lethal genes in BRAF mutant CC cell lines. Functional analysis is ongoing. Data will be presented. References 1. J Clin Oncol 2012 Apr 20;30(12):1288-9 2. Gut (2012). doi:10.1136/gutjnl-2012-302423

Simple Summary Dysbiosis of the gut microbiome may contribute to the heterogeneity of colorectal cancer from phenotypic, prognostic and response to treatment perspectives. We analysed CRC microbiome by 16S rRNA gene sequencing of paired tumour mucosa, adjacent visually normal mucosa and stool swabs of 178 patients with stage 0–IV CRC. We observed that tumour mucosa is dominated by pathogenic bacteria of oral origin and proposed a CRC tumour microbiome subtyping system. The subtypes and tumour mucosa genera were associated with prognostic clinical covariates (tumour grade, localisation, TNM, BRAF mutation and MSI). In contrast, changes in the stool microbiome were associated with lymph node involvement and the presence of synchronous metastases. We discovered new associations between microorganisms and CRC and clinical parameters. Our study represents a step forward in understanding the role of the microbiome and its interactions with factors involved in tumour progression, and it opens novel avenues for exploring new treatments and biomarkers. Abstract Long-term dysbiosis of the gut microbiome has a significant impact on colorectal cancer (CRC) progression and explains part of the observed heterogeneity of the disease. Even though the shifts in gut microbiome in the normal-adenoma-carcinoma sequence were described, the landscape of the microbiome within CRC and its associations with clinical variables remain under-explored. We performed 16S rRNA gene sequencing of paired tumour tissue, adjacent visually normal mucosa and stool swabs of 178 patients with stage 0–IV CRC to describe the tumour microbiome and its association with clinical variables. We identified new genera associated either with CRC tumour mucosa or CRC in general. The tumour mucosa was dominated by genera belonging to oral pathogens. Based on the tumour microbiome, we stratified CRC patients into three subtypes, significantly associated with prognostic factors such as tumour grade, sidedness and TNM staging, BRAF mutation and MSI status. We found that the CRC microbiome is strongly correlated with the grade, location and stage, but these associations are dependent on the microbial environment. Our study opens new research avenues in the microbiome CRC biomarker detection of disease progression while identifying its limitations, suggesting the need for combining several sampling sites (e.g., stool and tumour swabs).