Wilfried Gouraud

Prediction of Survival in Multiple Myeloma Based on Gene Expression Profiles Reveals Cell Cycle and Chromosomal Instability Signatures in High-Risk Patients and Hyperdiploid Signatures in Low-Risk Patients: A Study of the Intergroupe Francophone du Myélome

PURPOSE Survival of patients with multiple myeloma is highly heterogeneous, from periods of a few weeks to more than 10 years. We used gene expression profiles of myeloma cells obtained at diagnosis to identify broadly applicable prognostic markers. PATIENTS AND METHODS In a training set of 182 patients, we used supervised methods to identify individual genes associated with length of survival. A survival model was built from these genes. The validity of our model was assessed in our test set of 68 patients and in three independent cohorts comprising 853 patients with multiple myeloma. RESULTS The 15 strongest genes associated with the length of survival were used to calculate a risk score and to stratify patients into low-risk and high-risk groups. The survival-predictor score was significantly associated with survival in both the training and test sets and in the external validation cohorts. The Kaplan-Meier estimates of rates of survival at 3 years were 90.5% (95% CI, 85.6% to 95.3%) and 47.4% (95% CI, 33.5% to 60.1%), respectively, in our patients having a low risk or high risk independently of traditional prognostic factors. High-risk patients constituted a homogeneous biologic entity characterized by the overexpression of genes involved in cell cycle progression and its surveillance, whereas low-risk patients were heterogeneous and displayed hyperdiploid signatures. CONCLUSION Gene expression-based survival prediction and molecular features associated with high-risk patients may be useful for developing prognostic markers and may provide basis to treat these patients with new targeted antimitotics.

Prognostic Significance of Copy-Number Alterations in Multiple Myeloma

PURPOSE Chromosomal aberrations are a hallmark of multiple myeloma but their global prognostic impact is largely unknown. PATIENTS AND METHODS We performed a genome-wide analysis of malignant plasma cells from 192 newly diagnosed patients with myeloma using high-density, single-nucleotide polymorphism (SNP) arrays to identify genetic lesions associated with prognosis. RESULTS Our analyses revealed deletions and amplifications in 98% of patients. Amplifications in 1q and deletions in 1p, 12p, 14q, 16q, and 22q were the most frequent lesions associated with adverse prognosis, whereas recurrent amplifications of chromosomes 5, 9, 11, 15, and 19 conferred a favorable prognosis. Multivariate analysis retained three independent lesions: amp(1q23.3), amp(5q31.3), and del(12p13.31). When adjusted to the established prognostic variables (ie, t(4;14), del(17p), and serum beta(2)-microglobulin [Sbeta(2)M]), del(12p13.31) remained the most powerful independent adverse marker (P < .0001; hazard ratio [HR], 3.17) followed by Sbeta(2)M (P < .0001; HR, 2.78) and the favorable marker amp(5q31.3) (P = .0005; HR, 0.37). Patients with amp(5q31.3) alone and low Sbeta(2)M had an excellent prognosis (5-year overall survival, 87%); conversely, patients with del(12p13.31) alone or amp(5q31.3) and del(12p13.31) and high Sbeta(2)M had a very poor outcome (5-year overall survival, 20%). This prognostic model was validated in an independent validation cohort of 273 patients with myeloma. CONCLUSION These findings demonstrate the power and accessibility of molecular karyotyping to predict outcome in myeloma. In addition, integration of expression of genes residing in the lesions of interest revealed putative features of the disease driving short survival.

Minor clone provides a reservoir for relapse in multiple myeloma

Recent studies have provided direct evidence for genetic variegation in subclones for various cancer types. However, little is known about subclonal evolutionary processes according to treatment and subsequent relapse in multiple myeloma (MM). This issue was addressed in a cohort of 24 MM patients treated either with conventional chemotherapy or with the proteasome inhibitor, bortezomib. As MM is a highly heterogeneous disease associated with a large number of chromosomal abnormalities, a subset of secondary genetic events that seem to reflect progression, 1q21 gain, NF-κB-activating mutations, RB1 and TP53 deletions, was examined. By using high-resolution single-nucleotide polymorphism arrays, subclones were identified with nonlinear complex evolutionary histories. Such reordering of the spectrum of genetic lesions, identified in a third of MM patients during therapy, is likely to reflect the selection of genetically distinct subclones, not initially competitive against the dominant population but which survived chemotherapy, thrived and acquired new anomalies. In addition, the emergence of minor subclones at relapse appeared to be significantly associated with bortezomib treatment. These data support the idea that new strategies for future clinical trials in MM should combine targeted therapy and subpopulations’ control to eradicate all myeloma subclones in order to obtain long-term remission.

Molecular characterization of the response to chemotherapy in conventional osteosarcomas: Predictive value of HSD17B10 and IFITM2

The therapy regimen of high‐grade osteosarcoma includes chemotherapy followed by surgical resection and postoperative chemotherapy. The degree of necrosis following definitive surgery remains the only reliable prognostic factor and is used to guide the choice of postoperative chemotherapy. The aim of this study was to find molecular markers able to classify patients with an osteosarcoma as good or poor responders to chemotherapy before beginning treatment. Gene expression screening of 20 nonmetastatic high‐grade osteosarcoma patients was performed using cDNA microarray. Expression of selected relevant genes was validated using QRT‐PCR. Immunohistochemistry on tissue microarrays sections of 73 biopsies was performed to investigate protein expression. Fluorescent in situ hybridization was performed for RPL8 gene. We have found that HSD17B10 gene expression was up‐regulated in poor responders and that immunohistochemistry expression of HSD17B10 on biopsy before treatment was correlatedto response to chemotherapy. Other results include correlationof IFITM2, IFITM3, and RPL8 gene expression to chemotherapy response. A statistical correlation was found between polysomy 8 or gain of RPL8 and good response to chemotherapy. These data suggest that HSD17B10, RPL8, IFITM2, and IFITM3 genes are involved in the response to the chemotherapy and that HSD17B10 may be a therapeutic target. RPL8 and IFITM2 may be useful in the assessment at diagnosis and for stratifying patients taking part in randomized trials.

c-Myc dependent expression of pro-apoptotic Bim renders HER2-overexpressing breast cancer cells dependent on anti-apoptotic Mcl-1

BackgroundAnti-apoptotic signals induced downstream of HER2 are known to contribute to the resistance to current treatments of breast cancer cells that overexpress this member of the EGFR family. Whether or not some of these signals are also involved in tumor maintenance by counteracting constitutive death signals is much less understood. To address this, we investigated what role anti- and pro-apoptotic Bcl-2 family members, key regulators of cancer cell survival, might play in the viability of HER2 overexpressing breast cancer cells.MethodsWe used cell lines as an in vitro model of HER2-overexpressing cells in order to evaluate how anti-apoptotic Bcl-2, Bcl-xL and Mcl-1, and pro-apoptotic Puma and Bim impact on their survival, and to investigate how the constitutive expression of these proteins is regulated. Expression of the proteins of interest was confirmed using lysates from HER2-overexpressing tumors and through analysis of publicly available RNA expression data.ResultsWe show that the depletion of Mcl-1 is sufficient to induce apoptosis in HER2-overexpressing breast cancer cells. This Mcl-1 dependence is due to Bim expression and it directly results from oncogenic signaling, as depletion of the oncoprotein c-Myc, which occupies regions of the Bim promoter as evaluated in ChIP assays, decreases Bim levels and mitigates Mcl-1 dependence. Consistently, a reduction of c-Myc expression by inhibition of mTORC1 activity abrogates occupancy of the Bim promoter by c-Myc, decreases Bim expression and promotes tolerance to Mcl-1 depletion. Western blot analysis confirms that naïve HER2-overexpressing tumors constitutively express detectable levels of Mcl-1 and Bim, while expression data hint on enrichment for Mcl-1 transcripts in these tumors.ConclusionsThis work establishes that, in HER2-overexpressing tumors, it is necessary, and maybe sufficient, to therapeutically impact on the Mcl-1/Bim balance for efficient induction of cancer cell death.

Molecular screening of interleukin-6 gene promoter and influence of 174G/C polymorphism on breast cancer

Interleukin-6 (IL-6) is a cytokine involved in different physiologic and pathophysiologic processes including carcinogenesis. In 2003, a single nucleotide polymorphism (-174G/C) of the IL-6 gene promoter has been linked to breast cancer prognosis in node-positive (N+) breast cancer patients. Since, different studies have led to conflicting conclusions about its role as a prognostic and/or diagnostic marker. The primary aim of our study was to investigate the link between -174G/C polymorphism and breast cancer risk on the one hand, and -174G/C polymorphism and prognosis in different groups of patients: sporadic N+breast cancers (n=138), sporadic N- breast cancers (n=95) and familial breast cancer (n=60) on the other hand. The variables of interest were disease-free survival and overall survival. The secondary aim of the study was to screen IL-6 gene promoter using direct sequencing to identify new polymorphisms in our French Caucasian breast cancer population. No association or trend of association between -174G/C polymorphism of IL-6 gene promoter gene and breast cancer diagnosis or prognosis was shown, even in meta-analyses. Furthermore, we have identified four novel polymorphic sites in the IL-6 gene promoter region: -764G-->A, -757C-->T, -233T-->A, 15C-->A.

Early dynamic transcriptomic changes during preoperative radiotherapy in patients with rectal cancer: a feasibility study.

AIM To develop novel biomarkers of rectal radiotherapy, we measured gene expression profiles on biopsies taken before and during preoperative radiotherapy. METHODS Six patients presenting with a locally advanced rectal cancer (T>T2, N0/Nx, M0) eligible for preoperative radiotherapy (45 Gy in 25 fractions) were selected in a pilot study. Six tumor and 3 normal tissues biopsies were taken before and during radiotherapy, after a dose of 7.2 Gy at a median time of 1 h following irradiation (0:27-2:12). Tumor or normal tissue purity was assessed by a pathologist prior to RNA extraction. Mean RNA content was 23 μg/biopsy (14-37) before radiotherapy and 22.7 μg/biopsy (12-35) during radiotherapy. After RNA amplification, biopsies were analysed with 54K HG-U133A Plus 2.0 Affymetrix expression micro-arrays. Data were normalized according to MAS5 algorithm. A gene expression ratio was calculated as: (gene expression during radiotherapy - gene expression before radiotherapy)/gene expression before radiotherapy. Were selected genes that showed a ratio higher than ± 0.5 in all 6 patients. RESULTS Microarray analysis showed that preoperative radiotherapy significantly up-regulated 31 genes and down-regulated 6 genes. According to the Gene Ontology project classification, these genes are involved in protein metabolism (ADAMDEC1; AKAP7; CAPN5; CLIC5; CPE; CREB3L1; NEDD4L; RAB27A), ion transport (AKAP7; ATP2A3; CCL28; CLIC5; F2RL2; NEDD4L; SLC6A8), transcription (AKAP7; CREB3L1; ISX; PABPC1L; TXNIP), signal transduction (CAPN5; F2RL2; RAB27A; TNFRSF11A), cell adhesion (ADAMDEC1; PXDN; SPON1; S100A2), immune response (CCL28; PXDN; TNFRSF11A) and apoptosis (ITM2C; PDCD4; PVT1). Up-regulation of 3 genes (CCL28; CLIC5; PDCD4) was detected by 2 different probes and up-regulation of 2 genes (RAB27A; TXNIP) by 3 probes. CONCLUSION Micro-arrays can efficiently assess early transcriptomic changes during preoperative radiotherapy for rectal cancer, and may help better understand tumor radioresistance.

A Genome-Wide Association Study Identifies a Novel Locus for Bortezomib-Induced Peripheral Neuropathy in European Patients with Multiple Myeloma

Purpose: Painful peripheral neuropathy is a frequent toxicity associated with bortezomib therapy. This study aimed to identify loci that affect susceptibility to this toxicity. Experimental Design: A genome-wide association study (GWAS) of 370,605 SNPs was performed to identify risk variants for developing severe bortezomib-induced peripheral neuropathy (BiPN) in 469 patients with multiple myeloma who received bortezomib–dexamethasone therapy prior to autologous stem cell in randomized clinical trials of the Intergroupe Francophone du Myelome (IFM) and findings were replicated in 114 patients with multiple myeloma of the HOVON-65/GMMG-HD4 clinical trial. Results: An SNP in the PKNOX1 gene was associated with BiPN in the exploratory cohort [rs2839629; OR, 1.89, 95% confidence interval (CI), 1.45–2.44; P = 7.6 × 10−6] and in the replication cohort (OR, 2.04; 95% CI, = 1.11–3.33; P = 8.3 × 10−3). In addition, rs2839629 is in strong linkage disequilibrium (r2 = 0.87) with rs915854, located in the intergenic region between PKNOX1 and cystathionine-ß-synthetase (CBS). Expression quantitative trait loci mapping showed that both rs2839629 and rs915854 genotypes have an impact on PKNOX1 expression in nerve tissue, whereas rs2839629 affects CBS expression in skin and blood. Conclusions: The use of GWAS in multiple myeloma pharmacogenomics has identified a novel candidate genetic locus mapping to PKNOX1 and in the immediate vicinity of CBS at 21q22.3 associated with the severe bortezomib-induced toxicity. The proximity of these two genes involved in neurologic pain whose tissue-specific expression is modified by the two variants provides new targets for neuroprotective strategies. Clin Cancer Res; 22(17); 4350–5. ©2016 AACR.

Inhibition of mTORC1 activity by REDD1 induction in myeloma cells resistant to bortezomib cytotoxicity

The combination of bortezomib and dexamethasone is becoming the reference induction treatment for multiple myeloma patients younger than 65 years. Despite its advantage over vincristin adryamicin dexamethasone induction treatment, bortezomib does not benefit all patients. We hypothesize that heterogeneity of the response experienced by myeloma patients is, at least in part, due to genomic variations in the malignant plasma cells. To test this hypothesis we used gene expression profiling to identify early responsive genes induced by bortezomib in resistant myeloma cells. Our study revealed: (i) a dramatic induction of REDD1, a negative regulator of mammalian target of rapamycin kinase complex 1 (mTORC1) activity, in these cells; (ii) a transient cell size decrease associated with REDD1 overexpression; and (iii) partial restoration of bortezomib sensitivity in REDD1 knockdown bortezomib‐resistant myeloma cells. Together, these results identify a possible novel mechanism of bortezomib resistance in myeloma patients mediated by REDD1 overexpression involving inhibition of mTORC1 activity and suggest that the use of mammalian target of rapamycin inhibitors in myeloma patients could be deleterious.

Logic programming reveals alteration of key transcription factors in multiple myeloma

Innovative approaches combining regulatory networks (RN) and genomic data are needed to extract biological information for a better understanding of diseases, such as cancer, by improving the identification of entities and thereby leading to potential new therapeutic avenues. In this study, we confronted an automatically generated RN with gene expression profiles (GEP) from a cohort of multiple myeloma (MM) patients and normal individuals using global reasoning on the RN causality to identify key-nodes. We modeled each patient by his or her GEP, the RN and the possible automatically detected repairs needed to establish a coherent flow of the information that explains the logic of the GEP. These repairs could represent cancer mutations leading to GEP variability. With this reasoning, unmeasured protein states can be inferred, and we can simulate the impact of a protein perturbation on the RN behavior to identify therapeutic targets. We showed that JUN/FOS and FOXM1 activities are altered in almost all MM patients and identified two survival markers for MM patients. Our results suggest that JUN/FOS-activation has a strong impact on the RN in view of the whole GEP, whereas FOXM1-activation could be an interesting way to perturb an MM subgroup identified by our method.