Mauro Delorenzi

Effects of KRAS, BRAF, NRAS, and PIK3CA mutations on the efficacy of cetuximab plus chemotherapy in chemotherapy-refractory metastatic colorectal cancer: a retrospective consortium analysis

BACKGROUNDnFollowing the discovery that mutant KRAS is associated with resistance to anti-epidermal growth factor receptor (EGFR) antibodies, the tumours of patients with metastatic colorectal cancer are now profiled for seven KRAS mutations before receiving cetuximab or panitumumab. However, most patients with KRAS wild-type tumours still do not respond. We studied the effect of other downstream mutations on the efficacy of cetuximab in, to our knowledge, the largest cohort to date of patients with chemotherapy-refractory metastatic colorectal cancer treated with cetuximab plus chemotherapy in the pre-KRAS selection era.nnnMETHODSn1022 tumour DNA samples (73 from fresh-frozen and 949 from formalin-fixed, paraffin-embedded tissue) from patients treated with cetuximab between 2001 and 2008 were gathered from 11 centres in seven European countries. 773 primary tumour samples had sufficient quality DNA and were included in mutation frequency analyses; mass spectrometry genotyping of tumour samples for KRAS, BRAF, NRAS, and PIK3CA was done centrally. We analysed objective response, progression-free survival (PFS), and overall survival in molecularly defined subgroups of the 649 chemotherapy-refractory patients treated with cetuximab plus chemotherapy.nnnFINDINGSn40.0% (299/747) of the tumours harboured a KRAS mutation, 14.5% (108/743) harboured a PIK3CA mutation (of which 68.5% [74/108] were located in exon 9 and 20.4% [22/108] in exon 20), 4.7% (36/761) harboured a BRAF mutation, and 2.6% (17/644) harboured an NRAS mutation. KRAS mutants did not derive benefit compared with wild types, with a response rate of 6.7% (17/253) versus 35.8% (126/352; odds ratio [OR] 0.13, 95% CI 0.07-0.22; p<0.0001), a median PFS of 12 weeks versus 24 weeks (hazard ratio [HR] 1.98, 1.66-2.36; p<0.0001), and a median overall survival of 32 weeks versus 50 weeks (1.75, 1.47-2.09; p<0.0001). In KRAS wild types, carriers of BRAF and NRAS mutations had a significantly lower response rate than did BRAF and NRAS wild types, with a response rate of 8.3% (2/24) in carriers of BRAF mutations versus 38.0% in BRAF wild types (124/326; OR 0.15, 95% CI 0.02-0.51; p=0.0012); and 7.7% (1/13) in carriers of NRAS mutations versus 38.1% in NRAS wild types (110/289; OR 0.14, 0.007-0.70; p=0.013). PIK3CA exon 9 mutations had no effect, whereas exon 20 mutations were associated with a worse outcome compared with wild types, with a response rate of 0.0% (0/9) versus 36.8% (121/329; OR 0.00, 0.00-0.89; p=0.029), a median PFS of 11.5 weeks versus 24 weeks (HR 2.52, 1.33-4.78; p=0.013), and a median overall survival of 34 weeks versus 51 weeks (3.29, 1.60-6.74; p=0.0057). Multivariate analysis and conditional inference trees confirmed that, if KRAS is not mutated, assessing BRAF, NRAS, and PIK3CA exon 20 mutations (in that order) gives additional information about outcome. Objective response rates in our series were 24.4% in the unselected population, 36.3% in the KRAS wild-type selected population, and 41.2% in the KRAS, BRAF, NRAS, and PIK3CA exon 20 wild-type population.nnnINTERPRETATIONnWhile confirming the negative effect of KRAS mutations on outcome after cetuximab, we show that BRAF, NRAS, and PIK3CA exon 20 mutations are significantly associated with a low response rate. Objective response rates could be improved by additional genotyping of BRAF, NRAS, and PIK3CA exon 20 mutations in a KRAS wild-type population.nnnFUNDINGnBelgian Federation against Cancer (Stichting tegen Kanker).

Strong Time Dependence of the 76-Gene Prognostic Signature for Node-Negative Breast Cancer Patients in the TRANSBIG Multicenter Independent Validation Series

Purpose: Recently, a 76-gene prognostic signature able to predict distant metastases in lymph node–negative (N−) breast cancer patients was reported. The aims of this study conducted by TRANSBIG were to independently validate these results and to compare the outcome with clinical risk assessment. Experimental Design: Gene expression profiling of frozen samples from 198 N− systemically untreated patients was done at the Bordet Institute, blinded to clinical data and independent of Veridex. Genomic risk was defined by Veridex, blinded to clinical data. Survival analyses, done by an independent statistician, were done with the genomic risk and adjusted for the clinical risk, defined by Adjuvant! Online. Results: The actual 5- and 10-year time to distant metastasis were 98% (88-100%) and 94% (83-98%), respectively, for the good profile group and 76% (68-82%) and 73% (65-79%), respectively, for the poor profile group. The actual 5- and 10-year overall survival were 98% (88-100%) and 87% (73-94%), respectively, for the good profile group and 84% (77-89%) and 72% (63-78%), respectively, for the poor profile group. We observed a strong time dependence of this signature, leading to an adjusted hazard ratio of 13.58 (1.85-99.63) and 8.20 (1.10-60.90) at 5 years and 5.11 (1.57-16.67) and 2.55 (1.07-6.10) at 10 years for time to distant metastasis and overall survival, respectively. Conclusion: This independent validation confirmed the performance of the 76-gene signature and adds to the growing evidence that gene expression signatures are of clinical relevance, especially for identifying patients at high risk of early distant metastases.

Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures

IntroductionBreast cancer subtyping and prognosis have been studied extensively by gene expression profiling, resulting in disparate signatures with little overlap in their constituent genes. Although a previous study demonstrated a prognostic concordance among gene expression signatures, it was limited to only one dataset and did not fully elucidate how the different genes were related to one another nor did it examine the contribution of well-known biological processes of breast cancer tumorigenesis to their prognostic performance.MethodTo address the above issues and to further validate these initial findings, we performed the largest meta-analysis of publicly available breast cancer gene expression and clinical data, which are comprised of 2,833 breast tumors. Gene coexpression modules of three key biological processes in breast cancer (namely, proliferation, estrogen receptor [ER], and HER2 signaling) were used to dissect the role of constituent genes of nine prognostic signatures.ResultsUsing a meta-analytical approach, we consolidated the signatures associated with ER signaling, ERBB2 amplification, and proliferation. Previously published expression-based nomenclature of breast cancer intrinsic subtypes can be mapped to the three modules, namely, the ER-/HER2- (basal-like), the HER2+ (HER2-like), and the low- and high-proliferation ER+/HER2- subtypes (luminal A and B). We showed that all nine prognostic signatures exhibited a similar prognostic performance in the entire dataset. Their prognostic abilities are due mostly to the detection of proliferation activity. Although ER- status (basal-like) and ERBB2+ expression status correspond to bad outcome, they seem to act through elevated expression of proliferation genes and thus contain only indirect information about prognosis. Clinical variables measuring the extent of tumor progression, such as tumor size and nodal status, still add independent prognostic information to proliferation genes.ConclusionThis meta-analysis unifies various results of previous gene expression studies in breast cancer. It reveals connections between traditional prognostic factors, expression-based subtyping, and prognostic signatures, highlighting the important role of proliferation in breast cancer prognosis.

Identification of molecular apocrine breast tumours by microarray analysis

Previous microarray studies on breast cancer identified multiple tumour classes, of which the most prominent, named luminal and basal, differ in expression of the oestrogen receptor α gene (ER). We report here the identification of a group of breast tumours with increased androgen signalling and a ‘molecular apocrine’ gene expression profile. Tumour samples from 49 patients with large operable or locally advanced breast cancers were tested on Affymetrix U133A gene expression microarrays. Principal components analysis and hierarchical clustering split the tumours into three groups: basal, luminal and a group we call molecular apocrine. All of the molecular apocrine tumours have strong apocrine features on histological examination (P=0.0002). The molecular apocrine group is androgen receptor (AR) positive and contains all of the ER-negative tumours outside the basal group. Kolmogorov–Smirnov testing indicates that oestrogen signalling is most active in the luminal group, and androgen signalling is most active in the molecular apocrine group. ERBB2 amplification is commoner in the molecular apocrine than the other groups. Genes that best split the three groups were identified by Wilcoxon test. Correlation of the average expression profile of these genes in our data with the expression profile of individual tumours in four published breast cancer studies suggest that molecular apocrine tumours represent 8–14% of tumours in these studies. Our data show that it is possible with microarray data to divide mammary tumour cells into three groups based on steroid receptor activity: luminal (ER+ AR+), basal (ER− AR−) and molecular apocrine (ER− AR+).

A stroma-related gene signature predicts resistance to neoadjuvant chemotherapy in breast cancer

To better understand the relationship between tumor-host interactions and the efficacy of chemotherapy, we have developed an analytical approach to quantify several biological processes observed in gene expression data sets. We tested the approach on tumor biopsies from individuals with estrogen receptor–negative breast cancer treated with chemotherapy. We report that increased stromal gene expression predicts resistance to preoperative chemotherapy with 5-fluorouracil, epirubicin and cyclophosphamide (FEC) in subjects in the EORTC 10994/BIG 00-01 trial. The predictive value of the stromal signature was successfully validated in two independent cohorts of subjects who received chemotherapy but not in an untreated control group, indicating that the signature is predictive rather than prognostic. The genes in the signature are expressed in reactive stroma, according to reanalysis of data from microdissected breast tumor samples. These findings identify a previously undescribed resistance mechanism to FEC treatment and suggest that antistromal agents may offer new ways to overcome resistance to chemotherapy.

Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen

BackgroundEstrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30–40% of ER+BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings.ResultsWe developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95%CI: 1.29–3.13; p = 0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response.ConclusionWe have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen.

FOXC2 controls formation and maturation of lymphatic collecting vessels through cooperation with NFATc1

The mechanisms of blood vessel maturation into distinct parts of the blood vasculature such as arteries, veins, and capillaries have been the subject of intense investigation over recent years. In contrast, our knowledge of lymphatic vessel maturation is still fragmentary. In this study, we provide a molecular and morphological characterization of the major steps in the maturation of the primary lymphatic capillary plexus into collecting lymphatic vessels during development and show that forkhead transcription factor Foxc2 controls this process. We further identify transcription factor NFATc1 as a novel regulator of lymphatic development and describe a previously unsuspected link between NFATc1 and Foxc2 in the regulation of lymphatic maturation. We also provide a genome-wide map of FOXC2-binding sites in lymphatic endothelial cells, identify a novel consensus FOXC2 sequence, and show that NFATc1 physically interacts with FOXC2-binding enhancers. As damage to collecting vessels is a major cause of lymphatic dysfunction in humans, our results suggest that FOXC2 and NFATc1 are potential targets for therapeutic intervention.

Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer

The recognition that colorectal cancer (CRC) is a heterogeneous disease in terms of clinical behaviour and response to therapy translates into an urgent need for robust molecular disease subclassifiers that can explain this heterogeneity beyond current parameters (MSI, KRAS, BRAF). Attempts to fill this gap are emerging. The Cancer Genome Atlas (TGCA) reported two main CRC groups, based on the incidence and spectrum of mutated genes, and another paper reported an EMT expression signature defined subgroup. We performed a prior free analysis of CRC heterogeneity on 1113 CRC gene expression profiles and confronted our findings to established molecular determinants and clinical, histopathological and survival data. Unsupervised clustering based on gene modules allowed us to distinguish at least five different gene expression CRC subtypes, which we call surface crypt‐like, lower crypt‐like, CIMP‐H‐like, mesenchymal and mixed. A gene set enrichment analysis combined with literature search of gene module members identified distinct biological motifs in different subtypes. The subtypes, which were not derived based on outcome, nonetheless showed differences in prognosis. Known gene copy number variations and mutations in key cancer‐associated genes differed between subtypes, but the subtypes provided molecular information beyond that contained in these variables. Morphological features significantly differed between subtypes. The objective existence of the subtypes and their clinical and molecular characteristics were validated in an independent set of 720 CRC expression profiles. Our subtypes provide a novel perspective on the heterogeneity of CRC. The proposed subtypes should be further explored retrospectively on existing clinical trial datasets and, when sufficiently robust, be prospectively assessed for clinical relevance in terms of prognosis and treatment response predictive capacity. Original microarray data were uploaded to the ArrayExpress database (http://www.ebi.ac.uk/arrayexpress/) under Accession Nos E‐MTAB‐990 and E‐MTAB‐1026.

Validation of Real-Time Methylation-Specific PCR to Determine O6-Methylguanine-DNA Methyltransferase Gene Promoter Methylation in Glioma

Epigenetic silencing of the DNA repair protein O(6)-methylguanine-DNA methyltransferase (MGMT) by promoter methylation predicts successful alkylating agent therapy, such as with temozolomide, in glioblastoma patients. Stratified therapy assignment of patients in prospective clinical trials according to tumor MGMT status requires a standardized diagnostic test, suitable for high-throughput analysis of small amounts of formalin-fixed, paraffin-embedded tumor tissue. A direct, real-time methylation-specific PCR (MSP) assay was developed to determine methylation status of the MGMT gene promoter. Assay specificity was obtained by selective amplification of methylated DNA sequences of sodium bisulfite-modified DNA. The copy number of the methylated MGMT promoter, normalized to the beta-actin gene, provides a quantitative test result. We analyzed 134 clinical glioma samples, comparing the new test with the previously validated nested gel-based MSP assay, which yields a binary readout. A cut-off value for the MGMT methylation status was suggested by fitting a bimodal normal mixture model to the real-time results, supporting the hypothesis that there are two distinct populations within the test samples. Comparison of the tests showed high concordance of the results (82/91 [90%]; Cohens kappa = 0.80; 95% confidence interval, 0.82-0.95). The direct, real-time MSP assay was highly reproducible (Pearson correlation 0.996) and showed valid test results for 93% (125/134) of samples compared with 75% (94/125) for the nested, gel-based MSP assay. This high-throughput test provides an important pharmacogenomic tool for individualized management of alkylating agent chemotherapy.

Molecular Markers Identify Subtypes of Stage III Colon Cancer Associated with Patient Outcomes

BACKGROUND & AIMSnCategorization of colon cancers into distinct subtypes using a combination of pathway-based biomarkers could provide insight into stage-independent variability in outcomes.nnnMETHODSnWe used a polymerase chain reaction-based assay to detect mutations in BRAF (V600E) and in KRAS in 2720 stage III cancer samples, collected prospectively from patients participating in an adjuvant chemotherapy trial (NCCTG N0147). Tumors deficient or proficient in DNA mismatch repair (MMR) were identified based on detection of MLH1, MSH2, and MSH6 proteins and methylation of the MLH1 promoter. Findings were validated using tumor samples from a separate set of patients with stage III cancer (n = 783). Association with 5-year disease-free survival was evaluated using Cox proportional hazards models.nnnRESULTSnTumors were categorized into 5 subtypes based on MMR status and detection of BRAF or KRAS mutations which were mutually exclusive. Three subtypes were MMR proficient: those with mutations in BRAF (6.9% of samples), mutations in KRAS (35%), or tumors lacking either BRAF or KRAS mutations (49%). Two subtypes were MMR deficient: the sporadic type (6.8%) with BRAF mutation and/or or hypermethylation of MLH1 and the familial type (2.6%), which lacked BRAF(V600E) or hypermethylation of MLH1. A higher percentage of MMR-proficient tumors with BRAF(V600E) were proximal (76%), high-grade (44%), N2 stage (59%), and detected in women (59%), compared with MMR-proficient tumors without BRAF(V600E) or KRAS mutations (33%, 19%, 41%, and 42%, respectively; all P < .0001). A significantly lower proportion of patients with MMR-proficient tumors with mutant BRAF (hazard ratio = 1.43; 95% confidence interval: 1.11-1.85; Padjusted = .0065) or mutant KRAS (hazard ratio = 1.48; 95% confidence interval: 1.27-1.74; Padjusted < .0001) survived disease-free for 5 years compared with patients whose MMR-proficient tumors lacked mutations in either gene. Disease-free survival rates of patients with MMR-deficient sporadic or familial subtypes was similar to those of patients with MMR-proficient tumors without BRAF or KRAS mutations. The observed differences in survival rates of patients with different tumor subtypes were validated in an independent cohort.nnnCONCLUSIONSnWe identified subtypes of stage III colon cancer, based on detection of mutations in BRAF (V600E) or KRAS, and MMR status that show differences in clinical and pathologic features and disease-free survival. Patients with MMR-proficient tumors and BRAF or KRAS mutations had statistically shorter survival times than patients whose tumors lacked these mutations. The tumor subtype found in nearly half of the study cohort (MMR-proficient without BRAF(V600E) or KRAS mutations) had similar outcomes to those of patients with MMR-deficient cancers.