Prognostic Gene Expression Profiles Research Articles

Analysis of Gene Expression Identifies Differentially Expressed Genes and Pathways Associated with Lymphatic Dissemination in Patients with Adenocarcinoma of the Esophagus

The presence of lymphatic dissemination is an important predictor of survival in esophageal adenocarcinoma (EA). The aim of this study was to discover a prognostic gene expression profile for lymphatic dissemination in EA and to identify genes and pathways that provide oncological insight in lymphatic dissemination. Patients who had lymphatic dissemination (N = 55) were compared with patients without lymphatic dissemination (N = 22). Whole-genome oligonucleotide microarrays were used to evaluate the genetic signature of 77 esophageal cancers. Multiple random validation was used to analyze the stability of the molecular signature and predictive power. Gene set enrichment analysis (GSEA) was applied to elucidate oncogenetic pathways. Lymphatic dissemination was correctly predicted in 75 +/- 14% of lymph node positive patients. The absence of lymphatic dissemination was correctly predicted in 41 +/- 23% of lymph-node-negative patients. Argininosuccinate synthetase (ASS) was selected for validation on the protein level because it was present in most prognostic signatures as well as the list of differentially expressed genes. ASS expression was lower (P = 0.048) in patients with lymphatic dissemination than in patients without. GSEA identified that arginine metabolism pathways and lipid metabolism pathways are related to less chance of developing lymphatic dissemination. The predictive profile does not outperform current clinical practice to predict the presence of lymphatic dissemination in patients with EA. Several genes, including ASS, and genetic pathways which are important in the development of lymphatic dissemination in EA, were identified.

Benefit of Complete Response in Multiple Myeloma Limited to High-Risk Subgroup Identified by Gene Expression Profiling

To determine whether the clinical benefit of complete remission (CR) may depend on prognostic subgroups of patients with multiple myeloma. Newly diagnosed patients with myeloma received a tandem autotransplant regimen. Using multivariate regression analyses, we examined the prognostic implications of time-dependent onset of CR on overall survival and event-free survival in the context of standard prognostic factors (SPF) and gene expression profiling-derived data available for 326 patients. CR benefited patients regardless of risk status when only SPFs were examined. With knowledge of gene array data, a survival (and event-free survival) benefit of CR only pertained to the small high-risk subgroup of 13% of patients (hazard ratio, 0.23; P = 0.001), whereas the majority of patients with low-risk disease had similar survival expectations whether or not CR was achieved (hazard ratio, 0.68; P = 0.128). Access to gene expression information permitted the recognition of a small very high-risk subgroup of 13% of patients, in whom prolonged survival critically depended on achieving CR. Absence of such benefit in the remainder should lead to a reassessment of clinical trial designs that rely on this end point as a surrogate for long-term prognosis.

Gene-Expression and Immunohistochemical Study of Specific T-Cell Subsets and Accessory Cell Types in the Transformation and Prognosis of Follicular Lymphoma

Despite the generally favorable clinical course in follicular lymphoma (FL), a minority of patients have a poor prognosis-with death within 3 years of diagnosis-most often due to transformation to aggressive disease. In this study, we analyzed the potential of predicting early transformation on the basis of gene expression and immunologic parameters in FL biopsy samples taken at diagnosis. At the gene-expression level, FL is a highly uniform disease at the time of diagnosis, precluding the detection of sufficiently validated prognostic gene-expression profiles suitable for a clinical setting. Combinations of differentially expressed genes indicate that immunologic mechanisms play a differential role in the risk of early transformation. Using immunohistochemistry for specific cell populations, the spatial distribution to neoplastic follicles and the activation of CD4-positive T-helper cells (P = .002) and specifically T-helper 1 (P = .004) were shown to be highly discriminatory to predict early transformation. A role for functional modulation of follicular dendritic cells could also be supported (P = .04). Other cell populations, including CD68-positive macrophages and regulatory T cells, were not differentially present. These results support the identification of FL as an immunologically functional disease in which an interaction of the tumor cells and the functional composition of the microenvironment determines the clinical behavior.

An Update on the Role of Thalidomide (THAL) in Total Therapy 2 (TT2) for Newly Diagnosed Patients with Multiple Myeloma (MM): Analysis of Subgroups Defined by Standard Prognostic Factors (SPF) and Gene Expression Profiling (GEP)-Derived Subgroups.

Background: THAL, whose activity in MM was discovered in the setting of advanced and refractory disease in the late 1990's (Singhal, NEJM, 2000), has become the standard front-line therapy in combination with dexamethasone (DEX). In a randomized phase III tandem transplant trial, TT2, a higher complete response (CR) rate and longer event-free survival (EFS) had been observed on the THAL arm (Barlogie, NEJM, 2006). The similar overall survival (OS) on THAL and control arms had been attributed to the routine use of THAL as salvage therapy for the patients randomized to the No-THAL arm and the shorter post-relapse OS among patients randomized to the THAL arm.Patients and Methods: With a median follow-up on TT2 of 53mo, 107 patients have relapsed and 219 died. Subset analyses were performed to determine whether THAL confers an OS advantage in any subgroup of patients.Results: 6-yr EFS and OS rates are 48%/63% on THAL and 38%/58% on control arm (p=0.01/0.67). Post-relapse OS is now similar with median durations of 5.3mo/4.3mo among control/THAL arms (p=0.11). According to multivariate analyses of 11 standard prognostic factors, EFS was shorter among patients treated without THAL, in the presence of cytogenetic abnormalities (CA), B2M and LDH elevations and low albumin, whereas CR was favorable; OS was inferior with CA, high LDH, low albumin and in patients not receiving 2nd transplant or not achieving CR. Randomization to THAL was beneficial only in the >2 risk factor group: 6-yr OS was 47% in 31 patients on THAL and 12% in 31 control patients (Figure 1, p=0.01). When examined in the context of GEP (70 gene model-based high versus low risk groups) and inter-phase FISH data (amp1q21), available in 260 patients, the 57 with GEP low risk and absence of amp1q21 receiving THAL had 5-yr OS of 90% compared to 74% among 73 controls (p=0.13).Conclusion: With longer follow-up of 53mo on TT2, EFS remains superior among patients randomized to THAL; post-relapse survival is no longer inferior among those randomized to THAL; THAL benefited a high-risk subgroup with >2 standard risk factors, whereas no significant ‘difference has yet emerged among genetically defined subgroups. [Display omitted]

Molecular profiling of breast cancer

This review is a comprehensive survey of molecular-profiling literature published since 2004. More microarray-based gene-expression profiles that are prognostic for breast cancer have been published, strengthening the possibility that the microarray gene-expression profile may indeed provide clinically meaningful results. Requirement for snap-frozen tissue, however, will continue to be a limiting factor in clinical application. Results from a multicenter validation study were less spectacular than the original findings. A prognostic model based on classical markers performed well in a comparative study. Further clinical validation, with a large sample size, is needed. A prognostic gene-expression profile of 21 genes, which can be assayed using routinely processed formalin-fixed paraffin-embedded tumor tissue, has been introduced and this assay has also been shown to correlate with degree of benefit from chemotherapy. Two large clinical trials to validate gene-expression-based assays are to be launched in North America (TAILORx) and the European Union (MINDACCT). The usefulness of these genomic tools is still being debated, because clinicopathologic factors also are still important. Gene-expression-based prognostic tests are now available as commercial reference laboratory tests. Their successful implementation will depend on the seamless integration with existing clinicopathologic markers.

Prediction of clinical outcome using gene expression profiling and artificial neural networks for patients with neuroblastoma.

Currently, patients with neuroblastoma are classified into risk groups (e.g., according to the Children's Oncology Group risk-stratification) to guide physicians in the choice of the most appropriate therapy. Despite this careful stratification, the survival rate for patients with high-risk neuroblastoma remains <30%, and it is not possible to predict which of these high-risk patients will survive or succumb to the disease. Therefore, we have performed gene expression profiling using cDNA microarrays containing 42,578 clones and used artificial neural networks to develop an accurate predictor of survival for each individual patient with neuroblastoma. Using principal component analysis we found that neuroblastoma tumors exhibited inherent prognostic specific gene expression profiles. Subsequent artificial neural network-based prognosis prediction using expression levels of all 37,920 good-quality clones achieved 88% accuracy. Moreover, using an artificial neural network-based gene minimization strategy in a separate analysis we identified 19 genes, including 2 prognostic markers reported previously, MYCN and CD44, which correctly predicted outcome for 98% of these patients. In addition, these 19 predictor genes were able to additionally partition Children's Oncology Group-stratified high-risk patients into two subgroups according to their survival status (P = 0.0005). Our findings provide evidence of a gene expression signature that can predict prognosis independent of currently known risk factors and could assist physicians in the individual management of patients with high-risk neuroblastoma.