Risk factors for follow-up interruption of HIV patients in French Guiana.

French Guiana is the region of France where the HIV epidemic is most prevalent. To determine the risk factors for being lost for follow-up, we followed a cohort of 1,213 patients between 1992 and 2002 and determined which variables were related to two definitions of being lost to follow-up: permanently disappearing from HIV clinics and coming back after more than 1 year of missed appointments. The incidence rate for permanent follow-up interruption was 17.2 per 100 person-years. The median time to lost to follow-up was 4.3 years (interquartile range = 1.4-8.4 years). Cox modeling showed that the younger age groups, foreigners, patients with initial CD4 counts at the time of HIV diagnosis less than 500/mm3, and patients followed before the availability of highly active antiretroviral therapy (HAART) were significantly more likely to be permanently lost to follow-up, suggesting that some of the patients may have died. When looking at temporary loss to follow-up, younger age groups, untreated patients, patients consulting before the availability of HAART, and patients with CD4 counts more than 500/mm3 were more likely to not come back for a period of more than 1 year.

Increased incidence of disseminated histoplasmosis following highly active antiretroviral therapy initiation.

To determine whether the initiation of highly active antiretroviral therapy (HAART) had any influence on the incidence of disseminated histoplasmosis, a retrospective cohort study was performed on 1551 patients followed for up to 12 years. After controlling for CD4 counts, age, and sex, patients taking HAART for 2 months or less were more likely to develop disseminated histoplasmosis than untreated patients (respectively, hazard ratio, 3.7 [95% confidence interval, 1.57-8.7]; P = 0.003). In contrast, after 6 months of HAART, treated patients were less likely to develop disseminated histoplasmosis than untreated patients (hazard ratio, 0.6 [95% confidence interval, 0.37-0.98], P = 0.04). This increased incidence suggests that the initiation of HAART and the subsequent immune reconstitution may reveal undiagnosed latent disseminated histoplasmosis.

Risk factors for late HIV diagnosis in French Guiana.

Risk factors for delayed HIV diagnosis in French Guiana were studied in 1952 patients between 1992 and 2003. At the time of diagnosis, 30% of patients had less than 200 CD4 lymphocytes/mm3; age, male sex, and foreign nationality were independently associated with a low CD4 cell count. The availability of highly active antiretroviral therapy was not associated with an earlier HIV diagnosis. Promoting HIV information and testing should be done in several languages to reach minorities.

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 approximately 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 approximately 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.

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 approximately 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.

Transcriptional profiling reveals coordinated up-regulation of oxidative metabolism genes in thyroid oncocytic tumors.

Oncocytomas are large cell tumors characterized by an abnormal proliferation of mitochondria. To investigate this phenomenon in thyroid oncocytomas, we determined gene expression profiles of 87 samples using microarrays of 6720 PCR products from cDNA clones. Samples included 29 thyroid oncocytomas and six papillary carcinomas, the remainder representing other thyroid pathologies or mitochondria-rich tumor samples, normal thyroid samples, and two thyroid cell lines. Hierarchical clustering and supervised analysis identified two specific oncocytic clusters and 163 distinctly regulated genes between oncocytoma and normal thyroid. Differential expression of five selected genes (APOD, BCL-2, COX, CTSB, and MAP2) was confirmed by immunohistochemistry. The two specific oncocytic clusters were rich in mitochondrial genes and revealed coordinated expression of nuclear and mitochondrial respiratory chain genes. We also observed the up-regulation of genes involved in mitochondrial biogenesis, such as nuclear respiratory factor 1 and the endothelial nitric oxide synthase. Several oxidative metabolism genes were overexpressed in oncocytomas, including those from the tricarboxylic acid cycle (MDH1) and cytosolic glycolysis (GAPD, ENO1, and GPI). On the contrary, the lactate dehydrogenase A gene, involved in anaerobic metabolism, was down-regulated. Our results suggest that, unlike a large number of solid tumors, thyroid oncocytomas produce energy through an aerobic pathway.

Small lymphocytic lymphoma, marginal zone B-cell lymphoma, and mantle cell lymphoma exhibit distinct gene-expression profiles allowing molecular diagnosis.

Non-germinal center small B-cell lymphomas represent a heterogeneous group of non-Hodgkin lymphomas, the most frequent histologic subtypes being small lymphocytic lymphoma (SLL), splenic marginal zone B-cell lymphoma (MZL), and mantle cell lymphoma (MCL). In order to identify genomic signatures specific for each disease, we analyzed 128 primary tumors using high-density microarrays. Several clusters of genes significantly discriminated the 3 histologic subtypes. Genes associated with cell adhesion, angiogenesis, and inhibition of apoptosis were up-regulated in SLL. Genes associated with intracellular signaling via the AKT1 pathway were up-regulated in splenic MZL. Genes associated with cell cycle control and multidrug resistance were up-regulated in MCL. Using 44 genes selected within the gene clusters discriminant for the 3 lymphoma subtypes, we generated a class prediction score that allowed us to classify the 3 entities in 96% of the cases, including borderline cases. Whereas specific transcriptional profiles easily distinguished all MZL samples, SLL samples, and most of the MCL samples into separate groups, few MCL cases exhibited MZL-type transcriptional profiles. This study demonstrates that SLL, splenic MZL, and MCL possess specific transcriptional profiles that may be relevant to the pathogenesis and the diagnosis of these histologic subtypes.

Gene expression profiling of multiple myeloma reveals molecular portraits in relation to the pathogenesis of the disease.

Although multiple myeloma (MM) is a unique entity, a marked heterogeneity is actually observed among the patients, which has been first related to immunoglobulin (Ig) types and light chain subtypes and more recently to chromosomal abnormalities. To further investigate this genetic heterogeneity, we analyzed gene expression profiles of 92 primary tumors according to their Ig types and light chain subtypes with DNA microarrays. Several clusters of genes involved in various biologic functions such as immune response, cell cycle control, signaling, apoptosis, cell adhesion, and structure significantly discriminated IgA- from IgG-MM. Genes associated with inhibition of differentiation and apoptosis induction were up-regulated while genes associated with immune response, cell cycle control, and apoptosis were down-regulated in IgA-MM. According to the expression of the 61 most discriminating genes, BJ-MM represented a separate subgroup that did not express either the genes characteristic of IgG-MM or those of IgA-MM at a high level. This suggests that transcriptional programs associated to the switch could be maintained up to plasma cell differentiation. Several genes whose products are known to stimulate bone remodeling discriminate between kappa- and lambda-MM. One of these genes, Mip-1alpha, was overexpressed in the kappa subgroup. In addition, we established a strong association (P =.0001) between kappa subgroup expressing high levels of Mip-1alpha and active myeloma bone disease. This study shows that DNA microarrays enable us to perform a molecular dissection of the bioclinical diversity of MM and provide new molecular tools to investigate the pathogenesis of malignant plasma cells.

Breast cancer revisited using DNA array-based gene expression profiling.

Breast cancer is a complex genetic disease characterized by the accumulation of multiple molecular alterations. The resulting clinical heterogeneity makes current diagnostic and therapeutic strategies less than perfectly adapted to each patient. Pathological and clinical factors are insufficient to capture the complex cascade of events that drive the clinical behavior of tumors. High-throughput molecular technologies provide novel tools to tackle this complexity. In particular, DNA arrays allow the simultaneous and quantitative analysis of the mRNA expression levels of thousands of genes in a single assay. Potential applications are multiple in the cancer field and the first research results are promising; comprehensive gene expression profiles of breast tumors are providing insights into mammary oncogenesis and are revealing new tumor subgroups previously indistinguishable. Significant advances will be the identification of new diagnostic, prognostic and predictive biomarkers as well as the discovery of new potential therapeutic targets. This review presents recent applications of DNA arrays in breast cancer research and discusses some issues to address in the near future to allow the technology to reach its full potential.

Gene expression profiling of breast carcinomas using nylon DNA arrays.

Clinically very heterogeneous, breast cancer prognosis and treatment response are difficult to predict with the current prognostic histoclinical parameters. Mammary oncogenesis remains poorly understood. DNA array technology allows the simultaneous analysis of the mRNA expression levels of thousands of genes in biological samples. Applied to breast tumours, expression profiles will boost our knowledge of oncogenesis, will offer new potential therapeutic targets and new prognostic and predictive markers. Today, the most accessible approach for academic research teams is that of Nylon DNA arrays with radioactive detection, which in addition allows profiling of small clinical samples.

[Prognostic value of gene expression profiling using cDNA arrays in lymphomas]. / Profils d'expression génique par puces à ADN dans les lymphomes malins: intérêt pronostique.

Lymphomas are the most frequent haematological malignancies in France. Their histoclinical heterogeneity reflects their complex and combinatorial nature which remains poorly elucidated at the molecular level. Today, DNA arrays allow to tackle this diversity by measuring the mRNA expression level of thousands of genes simultaneously in one sample. Recent publications show the potential of DNA arrays to improve the prognostic classification of diffuse large B cell lymphomas and of Hodgkin's lymphoma, by identifying new tumour classes unrecognised by classical factors.

[Gene expression profiling using cDNA arrays and prognosis of breast cancer]. / Profils d'expression génique et puces à ADN dans le cancer du sein: intérêt pronostique.

Breast cancer is a major health problem. Clinical heterogeneity makes prognosis and sensitivity to treatment highly variable among patients. The recently developed cDNA array technology allows to analyse the expression of thousands of genes simultaneously. Results of the pioneering studies are promising: expression profiling of breast tumours using cDNA arrays seems able to identify new prognostic sub-classes unidentifiable using conventional parameters.

Gene expression profiles of poor-prognosis primary breast cancer correlate with survival.

The extensive heterogeneity of breast cancer complicates the precise assessment of tumour aggressiveness, making therapeutic decisions difficult and treatments inappropriate in some cases. Consequently, the long-term metastasis-free survival rate of patients receiving adjuvant chemotherapy is only 60%. There is a genuine need to identify parameters that might accurately predict the effectiveness of this treatment for each patient. Using cDNA arrays, we profiled tumour samples from 55 women with poor-prognosis breast cancer treated with adjuvant anthracycline-based chemotherapy. Gene expression monitoring was applied to a set of about 1000 candidate cancer genes. Differences in expression profiles provided molecular evidence of the clinical heterogeneity of disease. First, we confirmed the capacity of a 23-gene predictor set, identified in a previous study, to distinguish between tumours associated with different survival. Second, using a refined gene set derived from the previous one, we distinguished, among the 55 clinically homogeneous tumours, three classes with significantly different clinical outcome: 5-year overall survival and metastasis-free survival rates were respectively 100% and 75% in the first class, 65% and 56% in the second and 40% and 20% in the third. This discrimination resulted from the differential expression of two clusters of genes encoding proteins with diverse functions, including the estrogen receptor (ER). Another finding was the identification of two ER-positive tumour subgroups with different survival. These results indicate that gene expression profiling can predict clinical outcome and lead to a more precise classification of breast tumours. Furthermore, the characterization of discriminator genes might accelerate the development of new specific and alternative therapies, allowing more rationally tailored treatments that are potentially more efficient and less toxic.

Prognosis of breast cancer and gene expression profiling using DNA arrays.

Breast cancer is a complex genetic disease characterized by the accumulation of multiple molecular alterations. The resulting clinical heterogeneity makes current therapeutic strategies-based on clinicopathlogical factors-less than perfectly adapted to each patient. Today, DNA arrays, by allowing the simultaneous and quantitative analysis of the mRNA expression levels of thousands of genes in a single assay, provide novel tools to tackle this complexity. Potential applications are multiple in the cancer field and the first research results are promising. Using home-made DNA arrays in an approach easily compatible with academic research-nylon support and radioactive detection-we identified a predictor set of 23 genes whose expression patterns differentiated two groups of breast cancer patients with different survival after adjuvant chemotherapy. We then validated and further extended these results in a larger, independent and homogeneous series of poor prognosis primary breast cancers treated with adjuvant anthracyclin-based chemotherapy. We confirmed the prognostic classification provided by the 23-gene set predictor. We then improved the predictor set and refined the classification by sorting the tumors into three classes with significantly different long-term survival. These results show the potential of the technology with an accessible approach for academic research teams. We also showed that nylon DNA arrays with radioactive detection are associated with excellent sensitivity, an advantage in clinical situations where the amount of available material is limited.