Role Of Gene Expression Profiling Research Articles

Selective Sentinel Node Dissection in Melanoma with Trends and Future Directions

Starting with its earliest descriptions, melanoma has been recognized as a tumor with a predilection for metastasis to regional lymph nodes. This tendency led to initial recommendations for very aggressive early surgical management of the regional nodal basin. However, those recommendations were the source of much controversy over nearly a century, until the minimally invasive surgical technique of sentinel lymph node (SLN) biopsy was developed by Morton, Cochran and colleagues. This technique has been evaluated in a series of prospective clinical trials, which have clarified its role and the management of lymph nodes in this disease. Current controversies relating to SLN biopsy include optimal selection of patients for the procedure, the role of gene expression profiling in initial melanoma management, and the potential therapeutic effects of SLN biopsy-based management. In addition, the SLN appears to be a rich source of data relating to the host–tumor interface and the immune microenvironment, which may advance our understanding of the biology of melanoma. Finally, although the surgical technique is well developed at this point, there may be additional technical improvements that are possible as well.

Role of Gene Expression Profiling in Colorectal Cancer by Using Docetaxel and Lapatinib.

Aim: 1-Determine cell viability by using docetaxel and lapatinib. 2-Determine the effect of the clinically relevant drugs on the regulation genes. Methods: We employed MTT assays to evaluate the cell viability of three colorectal cancer cell lines (HT-29, HCT-116, and SW-620) following treatment with docetaxel and lapatinib. Subsequently, RNA was isolated from both treated and untreated HT-29 and HCT-116 cells. HT-29 cells were exposed to 3.9uM lapatinib and 0.027uM docetaxel, while HCT-116 cells were treated with 5.6uM lapatinib and 0.038uM docetaxel. The concentrations used were based on the IC50 values for docetaxel and lapatinib in HT-29 and HCT-116 cells. Real-time PCR analysis was conducted to confirm data. Results: The results of MTT assays demonstrated a decrease in cell viability for HT29, HCT-116, and SW-620 cells as the concentrations of docetaxel and lapatinib increased. This indicates the effectiveness of both drugs in reducing the viability of these colorectal cancer cell lines. In addition, the gene expression analysis revealed that docetaxel and lapatinib had notable effects on the genetic activity of these cells. Specifically, these drugs down-regulated genes that play crucial roles in cell proliferation, cell cycle progression, transcription factors, cell signaling, and oncogenesis. On the positive side, there was an up-regulation of genes related to inducing apoptosis, causing cell cycle arrest, and promoting cellular differentiation in all three cell lines. However, a potential concern emerged as docetaxel and lapatinib also up-regulated genes associated with chemotherapeutic resistance. This suggests a potential challenge in the form of induced resistance to these drugs by the cancer cells. Conclusions: Docetaxel and lapatinib altered numerous genes, and many of these changes may be related to the molecular processes by which these drugs inhibit the growth of colorectal cancer cells. This data may be applied to future mechanistic studies and to the development of improved therapies for colorectal cancer.

The Significance of mRNA in the Biology of Multiple Myeloma and Its Clinical Implications.

Multiple myeloma (MM) is a genetically complex disease that results from a multistep transformation of normal to malignant plasma cells in the bone marrow. However, the molecular mechanisms responsible for the initiation and heterogeneous evolution of MM remain largely unknown. A fundamental step needed to understand the oncogenesis of MM and its response to therapy is the identification of driver mutations. The introduction of gene expression profiling (GEP) in MM is an important step in elucidating the molecular heterogeneity of MM and its clinical relevance. Since some mutations in myeloma occur in non-coding regions, studies based on the analysis of mRNA provide more comprehensive information on the oncogenic pathways and mechanisms relevant to MM biology. In this review, we discuss the role of gene expression profiling in understanding the biology of multiple myeloma together with the clinical manifestation of the disease, as well as its impact on treatment decisions and future directions.

The Changing Role of Gene-Expression Profiling in the Era of De-escalating Adjuvant Chemotherapy in Early-Stage Breast Cancer

PurposeWe assessed the recent trends in the administration of adjuvant chemotherapy thereby evaluating the role of the 70-gene signature (70-GS) testing in decision-making in the systemic treatment of patients with lymph node negative (N0) and lymph node positive (N+) breast cancer.MethodsPatients with a national guideline directed indication for 70-GS use treated between 2013 and 2016 were selected from the Netherlands Cancer Registry. Time trends in the administration of adjuvant chemotherapy were evaluated within guideline- and age-delineated subgroups. The influence of the 70-GS on chemotherapy use was assessed with logistic regression.ResultsDuring the study period, the overall administration of adjuvant chemotherapy decreased from 49 to 23% and 70-GS use increased from 24 to 51%. The 70-GS was not associated with a decreased likelihood for N0 patients to receive chemotherapy (odds ratio [OR] 1.0; 95% confidence interval [CI] 0.86–1.17), as the proportion of N0 patients who received chemotherapy in the absence of 70-GS use decreased during the study period. In patients with N1a disease, 70-GS testing was associated with a decreased likelihood to receive chemotherapy (OR 0.21; 95% CI 0.15–0.29). In patients < 50 years and 50–59 years of age, 70-GS use was associated with a consistent lower proportion of patients receiving chemotherapy throughout the study period (OR 0.17; 95% CI 0.13–0.23 and OR 0.53; 95% CI 0.43–0.65, respectively).ConclusionsIn this population-based study, the administration of adjuvant chemotherapy in ER+ breast cancer strongly declined. For node-positive and younger patients, 70-GS use was associated with a decreased probability for patients to receive adjuvant chemotherapy.

Gene Expression Profiling Predicts Clinical Outcomes in Newly Diagnosed Multiple Myeloma Patients in a Standard of Care Setting

Introduction: Multiple Myeloma is a heterogeneous cancer that affects the bone marrow. Given this heterogeneity, we aimed to elucidate the role of gene expression profiling (GEP) in identifying different MM subtypes and explore their relationship to clinical outcomes in a standard of care setting.Methods: We retrospectively analyzed all NDMM patients with baseline GEP analysis. 55 patients from April 2014 until March 2016 were identified and included in our analysis. GEP was performed using CD138+ cells from bone marrow samples through MyPRS® (Signal Genetics, Little Rock, AR). Fisher’s exact test was used to evaluate the associations between two categorical variables. The Wilcoxon rank sum test was used to evaluate the difference in continuous variables between patient groups. Kaplan-Meier method was used to estimate the time to event endpoints including relapse free survival (RFS) and overall survival. The log-rank test was used to evaluate the differences in the time to event endpoints between/among patient groups. Univariate Cox proportional hazards model was used to evaluate the association between a continuous variable and relapse free survival.Results: Median age was 61 (38-76). Patients presented with lytic lesions (80%), anemia (78%), kidney dysfunction (24%) and hypercalcemia (31%). One patient did not meet CRAB criteria, but had 60% plasma cells in the bone marrow and an involved/uninvolved sFLC ratio of 199. All patients were treated with bortezomib (88%) or carfilzomib (12%) initial therapy in combination with lenalidomide (83%) or cyclophosphamide (17%). All patients received triple therapy as initial treatment, with 60% of patients receiving an upfront autologous transplant. With median follow-up of 12 months (1.64-24.54 months) 75% of patients had not relapsed and median overall survival had not been reached. 13 (24%) patients were characterized as high risk (HR) by GEP. GEP risk category predicted RFS (p=0.0014) in this series of patients (Fig. 1). Table 1 shows GEP risk subtypes with clinical outcomes and association to FISH abnormalities. We previously reported that HR FISH abnormalities are present in GEP low risk (LR) patients. LR GEP patients with CKS1B gene gain by FISH (n=9, 23%) had 100% RFS at 21 months, while 60% of HR GEP patients with CKS1B gene gain had relapsed by 24 months (p=0.0297, Fig. 2). All patients with HR GEP and 17p deletion relapsed by 14 months whereas only one patient with LR GEP and 17p deletion died 1 year from diagnosis, with an unknown cause of death (p=0.18, Fig. 3).Conclusion: Cytogenetics and FISH are still the current standard of care to predict prognosis in NDMM, direct care and inclusion in clinical trials. This study in a standard of care setting shows that GEP further refines prognosis in patients with HR FISH abnormalities. Future studies in larger cohorts of patients are warranted to confirm our findings. [Display omitted] [Display omitted] [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Role of gene expression profiling in defining indeterminate thyroid nodules in addition to BRAF analysis.

Fine-needle aspiration (FNA) is routinely used in the preoperative evaluation of thyroid nodules. However, 15% to 30% of aspirations yield indeterminate cytologic findings. Because the assessment of BRAF mutations seems to improve the diagnostic accuracy, this study evaluated BRAF mutations with Sanger sequencing and real-time methods in 650 consecutive thyroid aspirates. In addition, the expression of a large number of genes involved in basement membrane remodeling, extracellular matrix proteolysis, and cell adhesion was studied in both benign and malignant nodules to identify new diagnostic tools. In this prospective series, despite the use of a very sensitive BRAF mutational testing method, the frequency of a BRAF alteration being identified in indeterminate FNA samples was 3 of 68. Expression analysis revealed several genes that were differentially expressed between benign and malignant nodules (transforming growth factor, cadherin 1, collagen α1, catenin α1, integrin α3, and fibronectin 1 [FN1]), between follicular adenomas and follicular variant of papillary thyroid carcinoma (FN1, laminin γ1, integrin β2, connective tissue growth factor, catenin δ1, and integrin αV), and between BRAF-wild-type and BRAF-mutated papillary thyroid carcinomas (TIMP metallopeptidase inhibitor 1; catenin α1; secreted phosphoprotein 1; FN1; ADAM metallopeptidase with thrombospondin type 1 motif, 1; and selectin L). These data were partially confirmed with real-time polymerase chain reaction analysis and immunohistochemistry. When the cost/benefit ratio of the procedures was taken into account, BRAF mutational testing failed to increase diagnostic accuracy in cytologically indeterminate nodules. However, the additional analysis of the expression of specific molecular markers could have possible utility as a diagnostic tool, although further evidence based on a large series of samples is needed before definitive conclusions can be drawn. Cancer Cytopathol 2016;124:340-9. © 2015 American Cancer Society.

Use of Gene Expression Profiling May Predict Clinical Outcomes in Newly Diagnosed Multiple Myeloma Patients in a Standard of Care Setting

Introduction: Multiple myeloma (MM) is characterized by malignant plasma cell (PC) proliferation. Gene expression profiling (GEP) of CD138+ bone marrow PC has emerged as a new way to identify patients with worse clinical outcomes so that an individualized treatment approach can be undertaken in the clinic. The majority of data with GEP come from clinical trials. We aimed to evaluate the use of GEP in a standard clinical setting.Methods: We retrospectively searched our database of newly diagnosed MM patients with GEP completed prior to initial treatment. 35MM patients from April 2014 until June 2015 were identified and included in our analysis. GEP was performed through MyPRS® (Signal Genetics, Little Rock, AR). Fisher's exact test was used to evaluate the associations between complete response status and other categorical variables. The Wilcoxon rank sum test was used to evaluate the difference in continuous variables between patients that achieved a complete remission after 6 months of initial treatment and those who did not. Responses were assessed using IMWG criteria.Results: Median age was 60 (38-76). Patients presented with lytic lesions (60%), anemia (80%), kidney dysfunction (11%) and hypercalcemia (20%). All patients with known initial therapy were treated with bortezomib (n=29) or carfilzomib (n=1) based therapy. 10 patients had upfront autologous stem cell transplant. 18 patients had available response at 6 months. 37% (n=13) of patients were characterized as high risk by GEP, of which 46% (n=6) had the proliferation (PR) subtype. Most low risk patients had hyperdiploidy (HY) subtype (n=12, 55%). Patients with high risk GEP presented more often with complex karyotypes whereas low risk GEP patients most often had normal or hyperdiploid karyotypes. FISH abnormalities that are usually present in high risk myeloma were also present in patients classified as GEP low risk (Table 1). At 6 months after diagnosis, lower baseline total protein, serum M-spike, serum free light chain ratio and serum kappa light chain levels were significantly associated with achieving a stringent complete response (sCR) (p<0.05). High risk patients were more likely to achieve a CR (n= 6/10, 60%) than low risk patients (n=5/16, 31%) at 6 months. Despite this, high risk patients seemed more likely to lose CR and relapse or die. Within one year of diagnosis, one patient relapsed after achieving a VGPR (high risk, PR subtype) and one patient died due to MM progressive disease after achieving an sCR (high risk, CD-1 subtype) (Table 1).Conclusion: In a standard clinical setting, GEP seems to identify MM patients that are at higher risk of adverse clinical outcomes early after diagnosis. GEP may be an adjunct to cytogenetics/FISH in MM risk stratification, as high risk FISH abnormalities were also found in low risk GEP patients. Larger studies with longer follow up may help address the particular role of GEP in the individualized treatment of MM. [Display omitted] DisclosuresOrlowski:Array BioPharma: Consultancy, Research Funding; Acetylon: Membership on an entity's Board of Directors or advisory committees; Onyx Pharmaceuticals: Consultancy, Research Funding; Spectrum Pharmaceuticals: Research Funding; Celgene: Consultancy, Research Funding; Genentech: Consultancy; Millennium Pharmaceuticals: Consultancy, Research Funding; Forma Therapeutics: Consultancy; BioTheryX, Inc.: Membership on an entity's Board of Directors or advisory committees; Janssen Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Consultancy, Research Funding.

Use of blood based biomarkers in the evaluation of Crohn's disease and ulcerative colitis.

Despite significant improvements in our understanding of Crohn's disease (CD) and ulcerative colitis (UC) in recent years, questions remain regarding the best approaches to assessment and management of these chronic diseases during periods of both relapse and remission. Various serologic biomarkers have been used in the evaluation of patients with both suspected and documented inflammatory bowel disease (IBD), and while each has potential utility in the assessment of patients with IBD, potential limitation remain with each method of assessment. Given these potential shortcomings, there has been increased interest in other means of evaluation of patients with IBD, including an expanding interest in the role of gene expression profiling. Among patients with IBD, gene expression profiles obtained from whole blood have been used to differentiate active from inactive CD, as well as to differentiate between CD, UC, and non-inflammatory diarrheal conditions. There are many opportunities for a non-invasive, blood based test to aid in the assessment of patients with IBD, particularly when considering more invasive means of evaluation including endoscopy with biopsy. Furthermore, as the emphasis on personalized medicine continues to increase, the potential ability of gene expression analysis to predict patient response to individual therapies offers great promise. While whole blood gene expression analysis may not completely replace more traditional means of evaluating patients with suspected or known IBD, it does offer significant potential to expand our knowledge of the underlying genes involved in the development of these diseases.

Characterizing sepsis: Another small piece of the puzzle

Sepsis - infection associated with a dysregulated host inflammatory response leading to some degree of organ dysfunction[1] - is a common occurrence in critically ill-patients and is associated with considerable morbidity and mortality in this population. With no known specific curative therapy for sepsis, treatment essentially relies on eradication of the causative microorganism and support of individual organs. To optimize chances of survival, rapid diagnosis enabling such management to be started in a timely manner is essential.[2] Diagnosis of sepsis in critically ill-patients can, however, be difficult due to the variable and nonspecific signs and symptoms of sepsis in the critically ill-population. Better characterization of the immune response and likely prognosis in individual patients may also help to improve outcomes and hence that interventions can be better targeted at the individual patient needs. With advances in molecular analysis and genomics testing, attention has been drawn to the potential role of gene expression profiling in identifying and characterizing patients with sepsis. It is well-known that patients vary in their individual immune response to infection and genetic diversity can influence the development of and outcomes from sepsis. A number of studies have now been published demonstrating that the carriage of one or more single nucleotide polymorphisms (SNP) of genes that encode for inflammatory mediators can influence risk of developing sepsis and/or outcome from sepsis.[3,4,5] In this issue of the Indian Journal of Critical Care Medicine, Ramakrishna et al.[6] reported that the results of a study assessing the role of SNPs in the heat shock protein 70 gene (HSP70) on outcomes in medical intensive care unit (ICU) patients with sepsis. The HSP70 family, comprising at least 14 members in humans,[7] is one of a large group of ubiquitous, evolutionarily conserved intracellular proteins first discovered in the early 1960s. Importantly, HSP70 proteins also exist extracellularly, where they are involved in various aspects of intercellular signaling and in controlling immune and inflammatory reactions.[7] The HSP70 family is now known to have multiple diverse functions including molecular chaperoning, apoptosis, innate immune signaling, and cytokine like stimulation of the production of pro- and anti-inflammatory mediators.[7] HSP70 proteins are upregulated by temperature (hence the name), but also by other forms of stress, including sepsis, inflammation, exercise, hypoxia, etc., Increased expression of HSP70 is found in various diseases characterized by inflammation, including sepsis, pancreatitis, auto-immune disease, and certain tumors. As reported by Ramakrishna et al.,[6] polymorphisms of HSP70 have been reported in various groups of patients, including those with diabetes, sarcoidosis, inflammatory bowel disease, coronary artery disease as well as patients with sepsis, and the presence of such polymorphisms has been associated with worse outcomes. In this study by Ramakrishna et al.,[6] 108 patients were studied, of whom 101 (94%) patients had at least one SNP; although, there was considerable variation in the frequency of the different alleles. The presence of one or more SNPs was associated with the development of hematological dysfunction and the need for mechanical ventilation. Interestingly, organ dysfunction occurred in just one of the seven patients without an SNP. Different polymorphisms were associated with different patterns of organ dysfunction and prolonged ICU length of stay. This study was not powered to detect differences in mortality. This study is limited by the relatively small number of patients for such an association study. The included patients also represent quite a specific population with one third presenting with viral H1N1 disease and one-fourth with scrub typhus; patients with malaria, leptospirosis, melioidosis and dengue fever also formed part of the population, limiting the generalizability of these results to other patients populations. Nevertheless, despite these limitations, the observations made by Ramakrishna et al.[6] are interesting and potentially important. Although the clinical implications in terms of diagnosis, prognosis and therapeutics may not yet be obvious, the ability to better characterize patients with sepsis can only be beneficial as we struggle to provide more individualized patient care. The results of this study provide another small piece of the seemingly increasingly complex puzzle of sepsis.

Breast Cancer Prognosis and Management: Role of Gene Expression Profiling

Gene expression profiling has shown that molecular heterogeneity is a hallmark of breast cancer. Authors of a recent review present a comprehensive update of the molecular subtypes of breast cancer and their clinical ramifications. Microarray-based analyses first allowed identification of seven intrinsic subgroups of breast cancer (luminal A, …

The role of gene expression profiling in drug discovery

Monitoring gene expression through the dual approaches of transcriptomics (RNA profiling) and proteomics (protein profiling) has become a key component in our efforts to understand complex biological processes. From the molecular stratification of disease states and the selection of potential drug targets, to patient selection and the confirmation of engagement of pharmacology in clinical studies, we are seeing the impact of gene expression profiling across all phases of the drug discovery process. Ongoing technological advances have driven an expansion in the use of these techniques, demonstrated utility in preclinical and clinical settings and increased regulatory and clinical acceptance. As technologies continue to advance apace, gene expression profiling is likely to play an increasingly important role in the future development of drug discovery.

The role of gene expression profiling in early-stage non-small cell lung cancer.

For patients with identical clinical-pathological characteristics or the same stage of lung cancer, great uncertainties remain regarding how some patients will be cured while other patients will have cancer recurrence, metastasis, or death after surgical resection. Identification of patients at high risk of recurrence, those who are unlikely to respond to specific chemotherapeutic agents, is the rationale for measuring specific biochemical markers. Thus, main investigational studies nowadays are focused in identifying molecular markers of recurrence, beyond pathologic stage, after surgical treatment and factors that can predict a benefit from adjuvant chemotherapy in poor prognosis subgroups, to individualize treatments. Advances in genomics and proteomics have generated many candidate markers with potential clinical value. Gene expression profiling (GEP) by microarray or real-time quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) can be useful in the classification or prognosis of various types of cancer, including lung cancer. A number of prognostic gene expression signatures have been reported to predict survival in non-small cell lung cancer (NSCLC). In this review, we focus on the role of GEP in early-stage NSCLC as predictive and prognostic biomarker and its potential use for a 'personalized' medicine in the years to come.

13 The role of gene expression profiling in early drug development

The development of packaging systems able to maintain the food quality and safety of a food has benefited consumers and food manufacturers. Among others, antimicrobial packaging presents an excellent potential to be implemented as an innovative solution in food technology to reduce the microbial growth in food systems and extend food shelf life. Biobased and synthetic polymers are being functionalized with well-known antimicrobials such as enzymes, bacteriocins, natural extracts, organic acids, chelators and metal ions, showing excellent controlled release opportunities when used directly in contact with the food matrix or as part of combined strategies. However, the evaluation of the efficiency consists of a multidisciplinary approach and its effect in a food has to be studied case by case. This chapter provides an overview on the most recent scientific advances, state-of-the-art legislative requirements and a critical view of the benefits and limitations of the different antimicrobial packaging strategies.

Role of gene-expression profiling in chronic myeloid leukemia

Gene-expression profiling enables disease classification and risk stratification, and provides important insights into possible pathogenetic mechanisms. The clinical management and prognosis of chronic myeloid leukemia (CML) has substantially changed after the introduction of targeted therapies, such as imatinib and the second-generation tyrosine kinase inhibitors nilotinib and dasatinib. Although exact characterization of CML pathogenetics has been performed by showing the causal pathogenetic relevance of the reciprocal translocation between chromosomes 9 and 22 for CML development, the disease still exhibits a marked clinical and biological heterogenicity. Thus, prognostic scores for a more exact disease classification, as well as for prediction of response to tyrosine kinase inhibitor therapy are warranted, especially because scores established within the interferon era have lost their prognostic value when applied to patients treated with imatinib. Gene-expression profiling has been proven to represent a powerful tool for early identification of nonresponders to cancer therapy. Several profiling studies in CML have been reported thus far. However, the available data are inconsistent, which is mainly due to technical reasons, such as the use of various different chips, different biostatistical algorithms for data analysis and, most importantly, the use of various different cellular sources (i.e., mononuclear cells from peripheral blood, whole bone marrow cells or selected bone marrow-derived stem/progenitor cells). This review will summarize the recent literature on gene-expression profiling for CML classification and response prediction.

Molecular characterization of acute myeloid leukemia and its impact on treatment

Molecular aberrations are playing an ever increasing role in guiding classification, prognosis, and therapeutic strategies in patients with acute myeloid leukemia. This review outlines recent strides in our understanding of the molecular characteristics of acute myeloid leukemia. We highlight the novel concept of preferential co-expression of certain mutations, summarize recent data on the clinically relevant prognostic role of known and novel molecular aberrations, and emphasize the emerging role of gene expression profiling and minimal residual disease monitoring. We review the molecular heterogeneity within already established categories of acute myeloid leukemia and discuss how these data may translate into prognostic, molecular-based therapy stratification to improve patient outcome.

Gene Expression Profiling and Clinical Outcome in Breast Cancer

Pathologic and clinical heterogeneity of breast cancer reflects the poorly documented, complex, and combinatory molecular basis of the disease and is in part responsible for therapeutic failures. The DNA microarray technique allows the analysis of RNA expression of several thousands of genes simultaneously in a sample. There are multiple potential applications of the technique in cancer research. A number of recent studies have shown the promising role of gene expression profiling in breast cancer by identifying new prognostic subclasses unidentifiable by conventional parameters and new prognostic and/or predictive gene signatures, whose predictive impact is superior to conventional histoclinical prognostic factors. In this review we describe current use of DNA microarrays in the prognosis of breast cancer. We also discuss issues that need to be addressed in the near future to allow the method to reach its full potential.

The role of gene expression profiling in the clinical management of ovarian cancer

Several studies have addressed the clinical value of gene expression profiling in the field of ovarian cancer. This paper reviews the current status of knowledge that can be derived from such studies. Gene expression profiles can be used to reveal sets of genes that can distinguish normal ovarian tissue from invasive ovarian carcinomas. Independent validation of these sets may result in the identification of (a set of) markers valuable for the detection in an early stage. Microarray analysis has shown that different histological subtypes of ovarian cancer might be partly reflected by a different aetiology through the deregulation and activation of different pathways. In addition, this heterogeneity could therefore also lead to different tumour behaviours. Worldwide, the combination of paclitaxel and platinum chemotherapy has been incorporated in the standard protocol for the management of patients with advanced stage ovarian cancer, although the outcome in individual patients is uncertain. Gene expression profiling was found to be a prognostic tool with respect to chemosensitivity and had a predictive performance of 78–86%. With increasing numbers of data from published reports, access to these data for the reproducibility of its results and pooling becomes more and more important and will possibly lead to more individualisation of therapy.

The role of gene expression profiling by microarray analysis for prognostic classification of breast cancer

Prognostic and predictive factors play important roles in the treatment of breast cancer. Genome-wide monitoring of gene expression using DNA microarrays makes it possible to study thousands of genes in a tumour sample in a single experiment. By looking for an association between the gene expression pattern and tumour behaviour, it should be possible to identify new prognostic and predictive factors.

Role of gene expression profiling in distinguishing biologically and clinically distinct subclasses of endometrial carcinoma

This presentation will highlight a series on ongoing studies designed to exploit the power of comprehensive, genome-wide, gene expression profiling in distinguishing biologically and clinically relevant subclasses of endometrial carcinoma. Two distinct studies, one directed toward a biological problem and one toward a clinical problem will be presented here. The type I/type II paradigm for endometrial carcinoma is now widely accepted as representing a set clinicopathologic criteria that define two distinct types of endometrial cancer with different outcomes. Although a small number of specific genetic alterations have been attributed to each (e.g., MLH1 methylation and PTEN mutation in type I tumors and TP53 mutation in type II tumors), this candidate gene approach has only begun to define the complex genetic basis for these two classes of endometrial cancers. In the first study, we hypothesized that a supervised class comparison between tamoxifen-associated endometrial cancers and matched cases not associated with tamoxifen exposure may provide insights into the molecular mechanism through which estrogen contributes to endometrial tumorigenesis. No statistically significant difference between the two groups was evident (P = 0.48). However, unsupervised hierarchical clustering of the entire sample of tumors revealed two groups with extremely diverse molecular profiles (P < 108) that were independent of tamoxifen exposure. Of recognized clinicopathologic factors, histologic grade correlated best with these two molecular classes. The first finding suggests that tamoxifen may function to stimulate the progression of clinically occult endometrial carcinomas, such that the spectrum of tumors that is observed in both groups is essentially the same. The second finding provides strong support for the definition of two biologically distinct classes of endometrial carcinoma, and that these two molecular classes may underlie the frequently cited but ill-defined type I and type II distinction. In the second study, we tested the hypothesis that women with intermediate risk endometrial carcinomas could be stratified into subgroups at high-risk (and thus appropriately treated with adjuvant therapy) or low-risk (and thus not likely to benefit from adjuvant therapy) for recurrence. Despite there being no single gene significantly associated with time to recurrence after correcting for multiple comparisons, there was a significant difference in time to recurrence between high-risk and low-risk patients, as defined using a statistical risk score (the basis of which will be presented). The estimated hazard ratio was 3.07 (95% CI, 1.00–9.43, P = 0.04). We conclude that women with intermediate risk endometrial cancers identified as high-risk for recurrence according to a gene expression-based risk score have a significantly increased risk of recurrence compared to those classified as low-risk. This suggests that gene expression profiling may contribute to the clinical management of intermediate risk endometrial cancer patients.

Gene Expression Profiling, Frozen and Paraffin Section Immunohistochemistry, and In Situ Hybridization for Determination of Monoclonality in Diffuse Large B-Cell Lymphoma.

Background: Determining monotypia of surface immunoglobulin (SIg) is often an important step in the diagnosis of B-cell lymphomas. Many competing methods have been developed and are commonly used in clinical practice. The role of gene expression profiling (GEP) in determining light chain restriction is yet to be clarified. The goal of this study was to compare 4 methods by which light chain restriction can be determined: frozen section immunohistochemistry (FS-IHC), paraffin section IHC (PS-IHC), in-situ hybridization (ISH), and GEP.Design: 40 cases of DLBCL, part of a previous GEP study of DLBCL (Rosenwald et al, NEJM 2002), were made into a tissue microarray (TMA). FS-IHC slides, previously stained using by-hand streptavidin and diaminobenzidine, were re-examined for κ:λ restriction. PS-IHC was done on the TMA using the Benchmark system according to manufacturer's protocols for κ/λ staining (Ventana Medical Systems VMSI, Tucson, AZ). ISH was performed on the TMA with a newly developed sensitive ISH procedure from VMSI which uses a purified streptavidin reagent to reduce background and increase sensitivity. The FS-IHC, PS-IHC, and ISH arrays were reviewed and scored as κ/λ monotypic, SIg-negative or indeterminate by 3 pathologists. The averaged gene expression ratios for microarray elements probing for κ and λ on each case were plotted on a log2 scale. Monoclonality was determined using 2 different GEP criteria: (1) κ-monoclonal if κ:λ expression was >2log2 or λ-monoclonal if expression was λ>κ or (2) κ and λ light chain relative expression on either side of the median. These data from all 4 techniques were used to determine a consensus clonality in which the majority of the results agreed. The results for each technique were then compared to the consensus for that case.Results: 7 Cases had a 4/4 consensus, 9 cases a 3/4, 11 cases a 3/3, 7 cases a 2/3, and 1 case a 2/2. 5 cases were excluded from the study because there was no majority consensus. 19 cases (47.5%) were κ monoclonal, 10 (25%) λ monoclonal, 6 (15%) SIg-negative, and 5 cases (12.5%) indeterminate. Compared to the consensus clonality FS-IHC was accurate in 21/26 (81%), PS-IHC in 28/32 (87%), sensitive ISH in 29/29 (100%) cases. GEP was accurate in 31/35 (89%) cases using either criteria (1) or (2); in 27/35 (77%) using criterion (1) alone, in 28/35 (80%) using criterion (2) alone, and 24/35 (69%) of cases when both criteria (1) and (2) were met. 6 SIg-negative cases failed all GEP criterion, but were considered correctly classified as neitherκ nor λ monoclonal.Discussion: The technique with the highest accuracy compared to consensus was the sensitive ISH assay, in part because samples were eliminated if the mRNA control (polyT probe) staining was suboptimal. GEP was also accurate using either of our criteria. The SIg-negative cases were not classified as either κ or λ monoclonal using any of our criteria. Given the increasing role GEP is likely to play in hematopathology, the application of GEP to B cell clonality may have diganostic utility.