Gene expression profiling. Methods and clinical applications in oncology

Insights from clinical studies into the role of the MLL gene in infant and childhood leukemia

Translocations involving the Mixed Lineage Leukemia (MLL) gene at 11q23 are found in both acute lymphoblastic leukemia (ALL) and acute myeloblastic leukemia (AML), but have different prognostic implications depending on the phenotype of the leukemia in de novo pediatric cases. The majority of MLL gene rearrangements are associated with infant ALL, and their presence predicts a poor prognosis which worsens with earlier age of presentation. Rearrangements of the MLL gene are found in most cases of infant AML and regardless of age confer an intermediate risk. The treatment of MLL-rearranged ALL in children involves increased intensification of chemotherapy, and infants with ALL are treated with an intensive regimen of ALL- and AML-like chemotherapy, with the proportion of MLL-rearranged cases being responsible for the poor outcome in this age group. The use of DNA microarray analysis to distinguish a particular gene signature for MLL-rearranged leukemias is shedding light on the molecular mechanisms and potential therapeutic targets of these leukemias. It may also prove to have a useful role in both diagnosis and prognosis. This review considers recent advances in our understanding of the role of MLL gene rearrangements in pediatric clinical practice.

Transit tumor retrieval preserves RNA fidelity and obviates snap-freezing

Genetic expression profiling is enabling investigators to discover new diagnostic and possibly therapeutic pathways in sarcoma biology. To draw substantial conclusions from these molecular analyses, adequate tissue samples must be accrued. Beyond cohort size, the most variable and limiting aspect of doing gene expression analyses on fresh human tissue is the preservation of labile ribonucleic acids extracted from clinical specimens. We have developed a novel retrieval protocol that is readily amenable to the clinical constraints placed on surgeons and pathologists that minimizes variables that can corrupt ribonucleic acid fidelity. We evaluate critically genomic message integrity of mesenchymal tumors derived from transcontinental inter-institutional collaboration. Intact total ribonucleic acid was isolated and assessed for quality and quantity. Ribosomal RNA integrity was quantified using a bioanalyzer. Ribonucleic acid from 42 mesenchymal tumors was isolated and quantified, with selected samples amplified. The mean ribosomal ratios for collaborative institutions ranged from 1.0 to 1.18. Samples remained at 4 degrees C before processing from 1 to 17 days. Tumors stabilized using this protocol retained total ribonucleic acid integrity suitable for amplification and genomic expression analysis regardless of the institutional source or preprocessing duration, enabling a potential consortium of investigators to collaborate in the expression profiling of sarcomas.

LEVEL OF EVIDENCE

Diagnostic study, Level III-3 (no consistently applied gold standard). See the Guidelines for Authors for a complete description of levels of evidence.

Gastric adenocarcinoma: review and considerations for future directions

OBJECTIVE

This update reviews the epidemiology and surgical management, and the controversies of gastric adenocarcinoma. We provide the relevance of outcome data to surgical decision-making and discuss the application of gene-expression analysis to clinical practice.

SUMMARY BACKGROUND DATA

Gastric cancer mortality rates have remained relatively unchanged over the past 30 years, and gastric cancer continues to be one of the leading causes of cancer-related death. Well-conducted studies have stimulated changes to surgical decision-making and technique. Microarray studies linked to predictive outcome models are poised to advance our understanding of the biologic behavior of gastric cancer and improve surgical management and outcome.

METHODS

We performed a review of the English gastric adenocarcinoma medical literature (1980-2003). This review included epidemiology, pathology and staging, surgical management, issues and controversies in management, prognostic variables, and the application of outcome models to gastric cancer. The results of DNA microarray analysis in various cancers and its predictive abilities in gastric cancer are considered.

RESULTS

Prognostic studies have provided valuable data to better the understanding of gastric cancer. These studies have contributed to improved surgical technique, more accurate pathologic characterization, and the identification of clinically useful prognostic markers. The application of microarray analysis linked to predictive models will provide a molecular understanding of the biology driving gastric cancer.

CONCLUSIONS

Predictive models generate important information allowing a logical evolution in the surgical and pathologic understanding and therapy for gastric cancer. However, a greater understanding of the molecular changes associated with gastric cancer is needed to guide surgical and medical therapy.

Pharmacogenomics

The discovery of the human genome and subsequent expansion of proteomics research combined with emerging technologies such as functional imaging, biosensors and sophisticated computational biology are producing unprecedented changes in today's healthcare. The expanding knowledge of the molecular basis of cancer has shown that significant differences in gene expression patterns can guide therapy not only for neoplastic conditions, but also for a variety of diseases including inflammatory disorders, cardiovascular disease and neurodegenerative processes. As a result, the fields of pharmacogenetics and pharmacogenomics have emerged as potential new testing platforms for the individualized management of patients. An individual's response to a drug is the complex interaction of both genetic and non-genetic factors. Genetic variants in the drug target itself, disease pathway genes, or drug metabolizing enzymes may all be used as predictors of drug efficacy or toxicity. In oncology, the SNP technology has focused on detecting the predisposition for cancer, predicting of toxic responses to drugs and selecting the best individual and combinations of anti-cancer drugs. Pharmacogenomics involves the application of whole genome technologies (e.g., gene and protein expression data) for the prediction of the sensitivity or resistance of an individual's disease to a single or group of drugs. Genomic microarrays and transcriptional profiling have the ability to generate hundreds of thousands of data points requiring sophisticated and complex information systems necessary for accurate and useful data analysis. This technique has generated a wealth of new information in the fields of leukemia/lymphoma, and solid tumor classification and prediction of metastasis, drug and biomarker target discovery and pharmacogenomic drug efficacy testing.

Immunophenotypic and molecular studies in the diagnosis and classification of malignant lymphoma

Immunophenotypic and molecular studies play an increasingly important role in the diagnosis and classification of lymphoid neoplasms. These studies are not yet a substitute for expert histopathologic evaluation, but are a valuable adjunct to the examination of the hematoxylin and eosin-stained slide. Major applications include determination of lineage, determination of B and T cell monoclonality, detection of oncoprotein expression, and detection of oncogene rearrangements and chromosomal translocations. The recognition of the lymphomas as distinct biologic entities with specific immunophenotypic and genotypic features, as embodied in the Revised European-American Lymphoma (REAL) and World Health Organization (WHO) classifications, is a key to the future development and application of targeted biologic and molecular therapies. In the future, application of gene expression array analysis to the lymphoid neoplasms will permit classification of the lymphomas at a molecular level.

Pediatric acute lymphoblastic leukemia

The outcome for children with acute lymphoblastic leukemia (ALL) has improved dramatically with current therapy resulting in an event free survival exceeding 75% for most patients. However significant challenges remain including developing better methods to predict which patients can be cured with less toxic treatment and which ones will benefit from augmented therapy. In addition, 25% of patients fail therapy and novel treatments that are focused on undermining specifically the leukemic process are needed urgently. In Section I, Dr. Carroll reviews current approaches to risk classification and proposes a system that incorporates well-established clinical parameters, genetic lesions of the blast as well as early response parameters. He then provides an overview of emerging technologies in genomics and proteomics and how they might lead to more rational, biologically based classification systems. In Section II, Drs. Mary Relling and Stella Davies describe emerging findings that relate to host features that influence outcome, the role of inherited germline variation. They highlight technical breakthroughs in assessing germline differences among patients. Polymorphisms of drug metabolizing genes have been shown to influence toxicity and the best example is the gene thiopurine methyltransferase (TPMT) a key enzyme in the metabolism of 6-mercaptopurine. Polymorphisms are associated with decreased activity that is also associated with increased toxicity. The role of polymorphisms in other genes whose products play an important role in drug metabolism as well as cytokine genes are discussed. In Sections III and IV, Drs. James Downing and Cheryl Willman review their findings using gene expression profiling to classify ALL. Both authors outline challenges in applying this methodology to analysis of clinical samples. Dr. Willman describes her laboratory's examination of infant leukemia and precursor B-ALL where unsupervised approaches have led to the identification of inherent biologic groups not predicted by conventional morphologic, immunophenotypic and cytogenetic variables. Dr. Downing describes his results from a pediatric ALL expression database using over 327 diagnostic samples, with 80% of the dataset consisting of samples from patients treated on a single institutional protocol. Seven distinct leukemia subtypes were identified representing known leukemia subtypes including: BCR-ABL, E2A-PBX1, TEL-AML1, rearrangements in the MLL gene, hyperdiploid karyotype (i.e., > 50 chromosomes), and T-ALL as well as a new leukemia subtype. A subset of genes have been identified whose expression appears to be predictive of outcome but independent verification is needed before this type of analysis can be integrated into treatment assignment. Chemotherapeutic agents kill cancer cells by activating apoptosis, or programmed cell death. In Section V, Dr. John Reed describes major apoptotic pathways and the specific role of key proteins in this response. The expression level of some of these proteins, such as BCL2, BAX, and caspase 3, has been shown to be predictive of ultimate outcome in hematopoietic tumors. New therapeutic approaches that modulate the apoptotic pathway are now available and Dr. Reed highlights those that may be applicable to the treatment of childhood ALL.

Integration of molecular diagnostics with therapeutics: implications for drug discovery and patient care

The Introduction of targeted therapeutics into clinical practice has created major opportunities for further development of the molecular diagnostics industry. Emerging genomic and proteomic technologies and information are now resulting in the molecular subclassification of disease as the basis for diagnosis, prognosis and therapeutic selection. The ultimate goals of personalized medicine are to take advantage of a molecular understanding of disease, both to optimize drug development and direct preventive resources and therapeutic agents at the right population of people while they are still well. Single nucleotide polymorphisms identification and genotyping have uncovered predisposition markers from cancer and heart disease as well in the prediction of both drug efficacy and toxicity. Pharmacogenomic and pharmacodynamic assays are being developed to enhance the speed and decrease the cost of drug development, as well as reduce side effects and increase response rates in a variety of diseases. The traditional trial and error practice of medicine is progressively eroding in favor of more precise marker-assisted diagnosis and safer and more effective molecularly guided treatment of disease. For the diagnostics industry this represents an unprecedented opportunity for integration, increased value and commercial opportunities for molecularly-derived tests.

Pharmacogenetics and personalised medicine

The traditional concern of pharmacogenetics was Mendelian (monogenic) variation, which visibly affected some drug responses. Pharmacogenetics was broadened by the observation that multifactorial genetic influences, in conjunction with environmental factors, usually determine drug responses. Variability of gene expression, a new theme of the science of genetics, also affects pharmacogenetics; for example, enhanced enzyme activity does not necessarily indicate a mutation, but may be the consequence of a drug-induced enhancement of gene expression. Methodological advances permit the conversion of pharmacogenetics into the broad practice of pharmacogenomics; this improves the possibility of identifying genetic causes of common diseases, which means establishing new drug targets, thereby stimulating the search for new drugs. While the main medical effect of pharmacogenetics was an improvement of drug safety, pharmacogenomics is hoped to improve drug efficacy. On the way to personalized medicine, we may stepwise improve the chances of choosing the right drug for a patient by categorizing patients into genetically definable classes that have similar drug effects (as, for example, human races, or any population group carrying a particular set of genes). It is wise to expect that, even after we have reached the goal to establish personalized medicine, we will not have eliminated all uncertainties.