Rémi Houlgatte

Gene expression profiling of colon cancer by DNA microarrays and correlation with histoclinical parameters

Different diagnostic and prognostic groups of colorectal carcinoma (CRC) have been defined. However, accurate diagnosis and prediction of survival are sometimes difficult. Gene expression profiling might improve these classifications and bring new insights into underlying molecular mechanisms. We profiled 50 cancerous and noncancerous colon tissues using DNA microarrrays consisting of ∼8000 spotted human cDNA. Global hierarchical clustering was to some extent able to distinguish clinically relevant subgroups, normal versus cancer tissues and metastatic versus nonmetastatic tumours. Supervised analyses improved these segregations by identifying sets of genes that discriminated between normal and tumour tissues, tumours associated or not with lymph node invasion or genetic instability, and tumours from the right or left colon. A similar approach identified a gene set that divided patients with significantly different 5-year survival (100% in one group and 40% in the other group; P=0.005). Discriminator genes were associated with various cellular processes. An immunohistochemical study on 382 tumour and normal samples deposited onto a tissue microarray subsequently validated the upregulation of NM23 in CRC and a downregulation in poor prognosis tumours. These results suggest that microarrays may provide means to improve the classification of CRC, provide new potential targets against carcinogenesis and new diagnostic and/or prognostic markers and therapeutic targets.

Gene expression profiling of primary breast carcinomas using arrays of candidate genes

Breast cancer is characterized by an important histoclinical heterogeneity that currently hampers the selection of the most appropriate treatment for each case. This problem could be solved by the identification of new parameters that better predict the natural history of the disease and its sensitivity to treatment. A large-scale molecular characterization of breast cancer could help in this context. Using cDNA arrays, we studied the quantitative mRNA expression levels of 176 candidate genes in 34 primary breast carcinomas along three directions: comparison of tumor samples, correlations of molecular data with conventional histoclinical prognostic features and gene correlations. The study evidenced extensive heterogeneity of breast tumors at the transcriptional level. A hierarchical clustering algorithm identified two molecularly distinct subgroups of tumors characterized by a different clinical outcome after chemotherapy. This outcome could not have been predicted by the commonly used histoclinical parameters. No correlation was found with the age of patients, tumor size, histological type and grade. However, expression of genes was differential in tumors with lymph node metastasis and according to the estrogen receptor status; ERBB2 expression was strongly correlated with the lymph node status (P < 0.0001) and that of GATA3 with the presence of estrogen receptors (P < 0.001). Thus, our results identified new ways to group tumors according to outcome and new potential targets of carcinogenesis. They show that the systematic use of cDNA array testing holds great promise to improve the classification of breast cancer in terms of prognosis and chemosensitivity and to provide new potential therapeutic targets.

Gene Expression Profiling Identifies Molecular Subtypes of Inflammatory Breast Cancer

Breast cancer is a heterogeneous disease. Comprehensive gene expression profiles obtained using DNA microarrays have revealed previously indistinguishable subtypes of noninflammatory breast cancer (NIBC) related to different features of mammary epithelial biology and significantly associated with survival. Inflammatory breast cancer (IBC) is a rare, particular, and aggressive form of disease. Here we have investigated whether the five molecular subtypes described for NIBC (luminal A and B, basal, ERBB2 overexpressing, and normal breast-like) were also present in IBC. We monitored the RNA expression of approximately 8,000 genes in 83 breast tissue samples including 37 IBC, 44 NIBC, and 2 normal breast samples. Hierarchical clustering identified the five subtypes of breast cancer in both NIBC and IBC samples. These subtypes were highly similar to those defined in previous studies and associated with similar histoclinical features. The robustness of this classification was confirmed by the use of both alternative gene set and analysis method, and the results were corroborated at the protein level. Furthermore, we show that the differences in gene expression between NIBC and IBC and between IBC with and without pathologic complete response that we have recently reported persist in each subtype. Our results show that the expression signatures defining molecular subtypes of NIBC are also present in IBC. Obtained using different patient series and different microarray platforms, they reinforce confidence in the expression-based molecular taxonomy but also give evidence for its universality in breast cancer, independently of a specific clinical form.

The Germinal Center/Activated B-Cell Subclassification Has a Prognostic Impact for Response to Salvage Therapy in Relapsed/Refractory Diffuse Large B-Cell Lymphoma: A Bio-CORAL Study

PURPOSE To evaluate the prognostic value of the cell of origin (COO) in patients with relapsed/refractory diffuse large B-cell lymphoma (DLBLC), prospectively treated by rituximab, dexamethasone, high-dose cytarabine, and cisplatin (R-DHAP) versus rituximab, ifosfamide, carboplatin, and etoposide and followed by intensive therapy plus autologous stem-cell transplantation on the Collaborative Trial in Relapsed Aggressive Lymphoma (CORAL) trial. PATIENTS AND METHODS Among the 396 patients included on the trial, histologic material was available for a total of 249 patients at diagnosis (n = 189 patients) and/or at relapse (n = 147 patients), which included 87 matched pairs. The patient data were analyzed by immunochemistry for CD10, BCL6, MUM1, FOXP1, and BCL2 expression and by fluorescent in situ hybridization for BCL2, BCL6 and c-MYC breakpoints. The correlation with survival data was performed by using the log-rank test and the Cox model. RESULTS Characteristics of immunophenotype and chromosomal abnormalities were statistically highly concordant in the matched biopsies. In univariate analysis, the presence of c-MYC gene rearrangement was the only parameter to be significantly correlated with a worse progression-free survival (PFS; P = .02) and a worse overall survival (P = .04). When treatment interaction was tested, the germinal center B (GCB) -like DLBCL that was based on the algorithm by Hans was significantly associated with a better PFS in the R-DHAP arm. In multivariate analysis, independent prognostic relevance was found for the GCB/non-GCB the Hans phenotype interaction treatment (P = .04), prior rituximab exposure (P = .0052), secondary age-adjusted International Prognostic Index (P = .039), and FoxP1 expression (P = .047). Confirmation was obtained by gene expression profiling in a subset of 39 patients. CONCLUSION COO remains a major and independent factor in relapsed/refractory DLBCL, with a better response to R-DHAP in GCB-like DLBCL. This needs confirmation by a prospective study.

Gene Expression Profiling for Molecular Characterization of Inflammatory Breast Cancer and Prediction of Response to Chemotherapy

Inflammatory breast cancer (IBC) is a rare but aggressive form of breast cancer with a 5-year survival limited to ∼40%. Diagnosis, based on clinical and/or pathological criteria, may be difficult. Optimal systemic neoadjuvant therapy and accurate predictors of pathological response have yet to be defined for increasing response rate and survival. Using DNA microarrrays containing ∼8,000 genes, we profiled breast cancer samples from 81 patients, including 37 with IBC and 44 with noninflammatory breast cancer (NIBC). Global unsupervised hierarchical clustering was able to some extent to distinguish IBC and NIBC cases and revealed subclasses of IBC. Supervised analysis identified a 109-gene set the expression of which discriminated IBC from NIBC samples. This molecular signature was validated in an independent series of 26 samples, with an overall performance accuracy of 85%. Discriminator genes were associated with various cellular processes possibly related to the aggressiveness of IBC, including signal transduction, cell motility, adhesion, and angiogenesis. A similar approach, with leave-one-out cross-validation, identified an 85-gene set that divided IBC patients with significantly different pathological complete response rate (70% in one group and 0% in the other group). These results show the potential of gene expression profiling to contribute to a better understanding of IBC, and to provide new diagnostic and predictive factors for IBC, as well as for potential therapeutic targets.

Large-Scale Temporal Gene Expression Profiling During Gonadal Differentiation and Early Gametogenesis in Rainbow Trout

Abstract The overall understanding of the sex differentiation cascade in vertebrates is still growing slowly, probably because of the variety of vertebrate models used and the number of molecular players yet to be discovered. Finding conserved mechanisms among vertebrates should provide a better view of the key factors involved in this process. To this end, we used real-time reverse transcription-polymerase chain reaction to produce a temporal map of fluctuations in mRNA expression of 102 genes during sex differentiation and early gametogenesis in the rainbow trout (Oncorhynchus mykiss). We used these 102 temporal gene expression patterns as a basis for a hierarchical clustering analysis to find characteristic clusters of coexpressed genes. Analysis of some of these gene clusters suggested a conserved overall expression profile between the sex differentiation cascade in fish and mammals. Among these conserved molecular mechanisms, sox9, dmrt1, amh, nr5a1, nr0b1, igf1, and igf1ra are, for instance, characterized as early expressed genes involved in trout testicular differentiation as it is known or suggested in mammals. On the contrary, foxl2, fst, and lhr are characterized as early expressed genes during trout ovarian differentiation, as also found in mammals. Apart from this high conservation, our analysis suggests some potential new players, such as the fshb subunit gene, which is detected here for the first time, to our knowledge, in the female differentiating gonad of a vertebrate species and displays a specific overexpression that coincides in timing with the occurrence of first oocyte meioses, or the pax2 gene, which displays an early and testis-specific expression profile.

Gene expression profiling identifies molecular subgroups among nodal peripheral T-cell lymphomas.

The classification of peripheral T-cell lymphomas (PTCL) is still a matter of debate. To establish a molecular classification of PTCL, we analysed 59 primary nodal T-cell lymphomas using cDNA microarrays, including 56 PTCL and three T-lymphoblastic lymphoma (T-LBL). The expression profiles could discriminate angioimmunoblastic lymphoma, anaplastic large-cell lymphoma and T-LBL. In contrast, cases belonging to the broad category of ‘PTCL, unspecified’ (PTCL-U) did not share a single molecular profile. Using a multiclass predictor, we could separate PTCL-U into three molecular subgroups called U1, U2 and U3. The U1 gene expression signature included genes known to be associated with poor outcome in other tumors, such as CCND2. The U2 subgroup was associated with overexpression of genes involved in T-cell activation and apoptosis, including NFKB1 and BCL-2. The U3 subgroup was mainly defined by overexpression of genes involved in the IFN/JAK/STAT pathway. It comprised a majority of histiocyte-rich PTCL samples. Gene Ontology annotations revealed different functional profile for each subgroup. These results suggest the existence of distinct subtypes of PTCL-U with specific molecular profiles, and thus provide a basis to improve their classification and to develop new therapeutic targets.

Distinct and Complementary Information Provided by Use of Tissue and DNA Microarrays in the Study of Breast Tumor Markers

Emerging high-throughput screening technologies are rapidly providing opportunities to identify new diagnostic and prognostic markers and new therapeutic targets in human cancer. Currently, cDNA arrays allow the quantitative measurement of thousands of mRNA expression levels simultaneously. Validation of this tool in hospital settings can be done on large series of archival paraffin-embedded tumor samples using the new technique of tissue microarray. On a series of 55 clinically and pathologically homogeneous breast tumors, we compared for 15 molecules with a proven or suspected role in breast cancer, the mRNA expression levels measured by cDNA array analysis with protein expression levels obtained using tumor tissue microarrays. The validity of cDNA array and tissue microarray data were first verified by comparison with quantitative reverse transcriptase-polymerase chain reaction measurements and immunohistochemistry on full tissue sections, respectively. We found a good correlation between cDNA and tissue array analyses in one-third of the 15 molecules, and no correlation in the remaining two-thirds. Furthermore, protein but not RNA levels may have prognostic value; this was the case for MUC1 protein, which was studied further using a tissue microarray containing approximately 600 tumor samples. For THBS1 the opposite was observed because only RNA levels had prognostic value. Thus, differences extended to clinical prognostic information obtained by the two methods underlining their complementarity and the need for a global molecular analysis of tumors at both the RNA and protein levels.

MYC+ diffuse large B-cell lymphoma is not salvaged by classical R-ICE or R-DHAP followed by BEAM plus autologous stem cell transplantation

Approximately 5-10% of diffuse large B-cell lymphomas (DLBCL) harbor a 8q24/MYC rearrangement (MYC(+)). We determined the prognostic significance of MYC rearrangement in patients with relapsed/refractory DLBCL prospectively treated by R-ICE or R-DHAP followed by high-dose therapy and autologous stem cell transplantation. Twenty-eight (17%) of the 161 patients analyzed presented a MYC(+) rearrangement, targeted as either simple hit (25%) or complex hits (n=75%) including MYC/BCL2, MYC/BCL6, and MYC/BCL2/BCL6. Results were statistically highly concordant in matched primary and relapsed biopsies (n = 45). Compared to the MYC(-) DLBCL patients, the MYC(+) DLBCL patients presented with a more elevated lactico-deshydrogenase level (P = .0006) and a more advanced age adjusted international prognostic index (P = .0039). The 4-year PFS and OS were significantly lower in the MYC(+) DLBCL patients than those in the MYC(-) DLBCL patients, with rates of 18% vs 42% (P = .0322), and of 29% vs 62% (P = .0113), respectively. Type of treatment, R-DHAP or R-ICE, had no impact on survivals, with 4-year PFS rates of 17% vs 19% and 4-year OS rates of 26% vs 31%. In conclusion, MYC rearrangement is an early event in DLBCL. MYC(+) DLBCL patients have a significant inferior prognosis than MYC(-) DLBCL patients. Their outcome was not influenced by the proposed salvage therapy.

Gene expression profiling defines molecular subtypes of classical Hodgkin's disease

Although the prognosis of Hodgkins disease is relatively good, around 20% of patients do not benefit from current therapies and succumb to their disease. A large-scale molecular characterization of disease might help improve HD management. Using cDNA arrays, we studied the mRNA expression levels of ∼1000 selected genes in 34 benign and malignant lymphoid samples including 21 classical Hodgkins disease (HD) tissue samples. Hierarchical clustering identified three main molecular groups of HD tumours relevant with respect to histology and clinical outcome (response to therapy and survival). Samples from all bad outcome HD (BOHD) patients clustered in one group whereas the two other groups contained most good outcome HD (GOHD) cases. The nodular sclerosis GOHD samples overexpressed genes involved in apoptotic induction and cell signalling, including cytokines, while the BOHD samples were characterized by the upregulation of genes involved in fibroblast activation, angiogenesis, extracellular matrix remodelling, cell proliferation, and the downregulation of tumour suppressor genes. Our results establish a molecular taxonomy of HD correlating with response to therapy and clinical outcome, thereby suggesting the possibility of improving the current prognostic classification.