Genomic approaches to hematologic malignancies

Quality and Reliability of 2D and 3D Clinical Photographs in Plastic Surgery: A Scoping Review

BACKGROUND

Clinical photography is a critical tool in plastic surgery practice. The primary aim of this scoping review was to assess the quality and reliability of various 2D and 3D photography modalities in plastic surgery.

METHODS

The databases, MEDLINE via PubMed, Embase via Elsevier, and Scopus via Elsevier, were searched from inception to March 15, 2023, for any papers focused on evaluation of quality and/or reliability of photography in plastic surgery-related applications. Data regarding general article characteristics, study characteristics, participants, and study results were extracted by two reviewers and qualitatively synthesized.

RESULTS

A total of 17 studies published from 1999 to 2023 were eligible for inclusion in the final analysis. Thirteen (76.5%) were cross-sectional and four (23.5%) were cohort studies. Photographed locations included craniomaxillofacial and oral (n = 11, 64.7%), scars (n = 3, 17.6%), breast and torso (n = 2, 11.8%), and wounds (n = 1, 5.9%). Assessed photographic modalities were found to be on par or better than comparators in almost all applicable cases (n = 13/14, 92.9%).

CONCLUSIONS

Multiple photographic modalities were found to have adequate quality and reliability. 3D photography was found to be a superior imaging modality for craniomaxillofacial and oral applications. For scar and wound assessment and images of the breast and torso region, 2D photography was sufficient. Overall, 2D photography using smartphone devices is sufficient for reliable and quality images in most clinical settings. With continued advances in technology, the ability to capture clinical images will undoubtedly improve, and there is a need for future studies to assess and compare these modalities.

LEVEL OF EVIDENCE III

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

The Expression of the RUVBL1 Component of the R2TP Complex Correlates with Poor Prognosis in DLBCL

INTRODUCTION

Diffuse large B-cell lymphoma (DLBCL) is the most prevalent subtype of non-Hodgkin's lymphoma (NHL) accounting for 30% of adult NHL worldwide and 50% in developing countries like India. DNA damage and Myc-induced transformation are well-known contributing factors towards development of DLBCL. A recently identified HSP90 co-chaperone complex R2TP has been shown to contribute towards DNA damage and Myc-induced transformation. This study aimed to analyse the immunohistochemical (IHC) expression of R2TP complex components RUVBL1, PIH1D1, and RPAP3 in DLBCL patients and correlate with prognosis.

METHODS

DLBCL (n = 54) histological slides were retrieved from archives, and detailed histomorphological and clinical features were noted. IHC staining of R2TP complex components RUVBL1, PIH1D1, and RPAP3 was performed on 54 cases (FFPE) of DLBCL. Expression data were correlated with survival and clinical features.

RESULTS

Out of the 54 DLBCL cases, 59.26% (n = 32) stained positive for RUVBL1. The RUVBL1 expression was associated with poor prognosis in both progression-free survival (PFS) (p = 0.0146) and overall survival (OS) (p = 0.0328). The expression was positively correlated with bone marrow involvement (p = 0.0525). The expression of PIH1D1 was observed in 68.51% (n = 32) of DLBCL cases, and positive correlation was observed with international prognostic index score (p = 0.0246); however, no correlation was observed with PFS or OS. Finally, RPAP3 was found immunopositive in only 1 case of DLBCL.

CONCLUSIONS

Immunopositivity for RUVBL1 is associated with poor prognosis along with a higher relapse rate amongst the DLBCL patients. PIH1D1 immunopositivity correlated with a higher IPI score.

A Six-Gene Risk Model Based on the Immune Score Reveals Prognosis in Intermediate-Risk Acute Myeloid Leukemia

Tumor microenvironment (TME) has been revealed as an important determinant of diagnosis and treatment response in AML patients. The scores of immune and stromal cell scores of AML in the intermediate-risk group from The Cancer Genome Atlas (TCGA) database were calculated using the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm. Differentially expressed genes were identified between high and low scores. Gene set enrichment and pathway analyses were performed. A risk score model based on TME for six immune-related genes was established and validated. Patients with a lower immune score had a longer overall survival than those with a higher score (P = 0.044). A total of 805 intersected genes as differentially expressed genes were identified and selected according to the comparison of both immune and stromal scores. The functional enrichment analysis shows that these genes are mainly associated with the immune/inflammatory response. The risk score model based on TME for six immune-related genes (including MEF2C, ENPP2, FAM107A, CD37, TNFAIP8L2, and CASS4) was established and validated in the TCGA database and well validated in the TARGET database (P = 0.005). A key microenvironment-related gene signature was identified that affects the outcomes of AML patients in the intermediate-risk group and might serve as therapeutic targets.

Matched Targeted Therapy for Pediatric Patients with Relapsed, Refractory, or High-Risk Leukemias: A Report from the LEAP Consortium

Despite a remarkable increase in the genomic profiling of cancer, integration of genomic discoveries into clinical care has lagged behind. We report the feasibility of rapid identification of targetable mutations in 153 pediatric patients with relapsed/refractory or high-risk leukemias enrolled on a prospective clinical trial conducted by the LEAP Consortium. Eighteen percent of patients had a high confidence Tier 1 or 2 recommendation. We describe clinical responses in the 14% of patients with relapsed/refractory leukemia who received the matched targeted therapy. Further, in order to inform future targeted therapy for patients, we validated variants of uncertain significance, performed ex vivo drug-sensitivity testing in patient leukemia samples, and identified new combinations of targeted therapies in cell lines and patient-derived xenograft models. These data and our collaborative approach should inform the design of future precision medicine trials. SIGNIFICANCE: Patients with relapsed/refractory leukemias face limited treatment options. Systematic integration of precision medicine efforts can inform therapy. We report the feasibility of identifying targetable mutations in children with leukemia and describe correlative biology studies validating therapeutic hypotheses and novel mutations.See related commentary by Bornhauser and Bourquin, p. 1322.This article is highlighted in the In This Issue feature, p. 1307.

Artificial Intelligence in Plastic Surgery: Current Applications, Future Directions, and Ethical Implications

Background:

Artificial intelligence (AI) in healthcare delivery has become an important area of research due to the rapid progression of technology, which has allowed the growth of many processes historically reliant upon human input. AI has become particularly important in plastic surgery in a variety of settings. This article highlights current applications of AI in plastic surgery and discusses future implications. We further detail ethical issues that may arise in the implementation of AI in plastic surgery.

Methods:

We conducted a systematic literature review of all electronically available publications in the PubMed, Scopus, and Web of Science databases as of February 5, 2020. All returned publications regarding the application of AI in plastic surgery were considered for inclusion.

Results:

Of the 89 novel articles returned, 14 satisfied inclusion and exclusion criteria. Articles procured from the references of those of the database search and those pertaining to historical and ethical implications were summarized when relevant.

Conclusions:

Numerous applications of AI exist in plastic surgery. Big data, machine learning, deep learning, natural language processing, and facial recognition are examples of AI-based technology that plastic surgeons may utilize to advance their surgical practice. Like any evolving technology, however, the use of AI in healthcare raises important ethical issues, including patient autonomy and informed consent, confidentiality, and appropriate data use. Such considerations are significant, as high ethical standards are key to appropriate and longstanding implementation of AI.

An Analytically and Diagnostically Sensitive RNA Extraction and RT-qPCR Protocol for Peripheral Blood Mononuclear Cells

Reliable extraction and sensitive detection of RNA from human peripheral blood mononuclear cells (PBMCs) is critical for a broad spectrum of immunology research and clinical diagnostics. RNA analysis platforms are dependent upon high-quality and high-quantity RNA; however, sensitive detection of specific responses associated with high-quality RNA extractions from human samples with limited PBMCs can be challenging. Furthermore, the comparative sensitivity between RNA quantification and best-practice protein quantification is poorly defined. Therefore, we provide herein a critical evaluation of the wide variety of current generation of RNA-based kits for PBMCs, representative of several strategies designed to maximize sensitivity. We assess these kits with a reverse transcription quantitative PCR (RT-qPCR) assay optimized for both analytically and diagnostically sensitive cell-based RNA-based applications. Specifically, three RNA extraction kits, one post-extraction RNA purification/concentration kit, four SYBR master-mix kits, and four reverse transcription kits were tested. RNA extraction and RT-qPCR reaction efficiency were evaluated with commonly used reference and cytokine genes. Significant variation in RNA expression of reference genes was apparent, and absolute quantification based on cell number was established as an effective RT-qPCR normalization strategy. We defined an optimized RNA extraction and RT-qPCR protocol with an analytical sensitivity capable of single cell RNA detection. The diagnostic sensitivity of this assay was sufficient to show a CD8⁺ T cell peptide epitope hierarchy with as few as 1 × 10⁴ cells. Finally, we compared our optimized RNA extraction and RT-qPCR protocol with current best-practice immune assays and demonstrated that our assay is a sensitive alternative to protein-based assays for peptide-specific responses, especially with limited PBMCs number. This protocol with high analytical and diagnostic sensitivity has broad applicability for both primary research and clinical practice.

H3K27me3 Signal in the Cis Regulatory Elements Reveals the Differentiation Potential of Progenitors During Drosophila Neuroglial Development

Drosophila neural development undergoes extensive chromatin remodeling and precise epigenetic regulation. However, the roles of chromatin remodeling in establishment and maintenance of cell identity during cell fate transition remain enigmatic. Here, we compared the changes in gene expression, as well as the dynamics of nucleosome positioning and key histone modifications between the four major neural cell types during Drosophila neural development. We find that the neural progenitors can be separated from the terminally differentiated cells based on their gene expression profiles, whereas nucleosome distribution in the flanking regions of transcription start sites fails to identify the relationships between the progenitors and the differentiated cells. H3K27me3 signal in promoters and enhancers can not only distinguish the progenitors from the differentiated cells but also identify the differentiation path of the neural stem cells (NSCs) to the intermediate progenitor cells to the glial cells. In contrast, H3K9ac signal fails to identify the differentiation path, although it activates distinct sets of genes with neuron-specific and glia-related functions during the differentiation of the NSCs into neurons and glia, respectively. Together, our study provides novel insights into the crucial roles of chromatin remodeling in determining cell type during Drosophila neural development.

Distinct transcriptomic and exomic abnormalities within myelodysplastic syndrome marrow cells

To provide biologic insights into mechanisms underlying myelodysplastic syndromes (MDS) we evaluated the CD34⁺ marrow cells transcriptome using high-throughput RNA sequencing (RNA-Seq). We demonstrated significant differential gene expression profiles (GEPs) between MDS and normal and identified 41 disease classifier genes. Additionally, two main clusters of GEPs distinguished patients based on their major clinical features, particularly between those whose disease remained stable versus patients who transformed into acute myeloid leukemia within 12 months. The genes whose expression was associated with disease outcome were involved in functional pathways and biologic processes highly relevant for MDS. Combined with exomic analysis we identified differential isoform usage of genes in MDS mutational subgroups, with consequent dysregulation of distinct biologic functions. This combination of clinical, transcriptomic and exomic findings provides valuable understanding of mechanisms underlying MDS and its progression to a more aggressive stage and also facilitates prognostic characterization of MDS patients.

Global Gene Expression Profiling: A Complement to Conventional Histopathologic Analysis of Neoplasia

Transcriptional profiling of entire tumors has yielded considerable insight into the molecular mechanisms of heterogeneous cell populations within different types of neoplasms. The data thus acquired can be further refined by microdissection methods that enable the analyses of subpopulations of neoplastic cells. Separation of the various components of a neoplasm (i.e., stromal cells, inflammatory infiltrates, and blood vessels) has been problematic, primarily because of a paucity of tools for accurate microdissection. The advent of laser capture microdissection combined with powerful tools of linear amplification of RNA and high-throughput microarray-based assays have allowed the transcriptional mapping of intricate and highly complex networks within pure populations of neoplastic cells. With this approach, specific “molecular signatures” can be assigned to tumors of distinct or even similar histomorphology, thereby aiding the desired objective of pattern recognition, tumor classification, and prognostication. This review highlights the potential benefits of global gene expression profiling of tumor cells as a complement to conventional histopathologic analyses.

Genomic Discoveries and Personalized Medicine in Neurological Diseases

In the past decades, we have witnessed dramatic changes in clinical diagnoses and treatments due to the revolutions of genomics and personalized medicine. Undoubtedly we also met many challenges when we use those advanced technologies in drug discovery and development. In this review, we describe when genomic information is applied in personal healthcare in general. We illustrate some case examples of genomic discoveries and promising personalized medicine applications in the area of neurological disease particular. Available data suggest that individual genomics can be applied to better treat patients in the near future.

Blood cell mRNAs and microRNAs: optimized protocols for extraction and preservation

Assessing messenger RNA (mRNA) and microRNA levels in peripheral blood cells may complement conventional parameters in clinical practice. Working with small, precious samples requires optimal RNA yields and minimal RNA degradation. Several procedures for RNA extraction and complementary DNA (cDNA) synthesis were compared for their efficiency. The effect on RNA quality of freeze-thawing peripheral blood cells and storage in preserving reagents was investigated. In terms of RNA yield and convenience, quality quantitative polymerase chain reaction signals per nanogram of total RNA and using NucleoSpin and mirVana columns is preferable. The SuperScript III protocol results in the highest cDNA yields. During conventional procedures of storing peripheral blood cells at -180°C and thawing them thereafter, RNA integrity is maintained. TRIzol preserves RNA in cells stored at -20°C. Detection of mRNA levels significantly decreases in degraded RNA samples, whereas microRNA molecules remain relatively stable. When standardized to reference targets, mRNA transcripts and microRNAs can be reliably quantified in moderately degraded (quality index 4-7) and severely degraded (quality index <4) RNA samples, respectively. We describe a strategy for obtaining high-quality and quantity RNA from fresh and stored cells from blood. The results serve as a guideline for sensitive mRNA and microRNA expression assessment in clinical material.

Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection in archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p=0.009), whilst high expression of HOXA9 (p<0.0001), Meis1 (p=0.005) and DNMT3A (p=0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.

Time series analysis as input for clinical predictive modeling: modeling cardiac arrest in a pediatric ICU

Background

Thousands of children experience cardiac arrest events every year in pediatric intensive care units. Most of these children die. Cardiac arrest prediction tools are used as part of medical emergency team evaluations to identify patients in standard hospital beds that are at high risk for cardiac arrest. There are no models to predict cardiac arrest in pediatric intensive care units though, where the risk of an arrest is 10 times higher than for standard hospital beds. Current tools are based on a multivariable approach that does not characterize deterioration, which often precedes cardiac arrests. Characterizing deterioration requires a time series approach. The purpose of this study is to propose a method that will allow for time series data to be used in clinical prediction models. Successful implementation of these methods has the potential to bring arrest prediction to the pediatric intensive care environment, possibly allowing for interventions that can save lives and prevent disabilities.

Methods

We reviewed prediction models from nonclinical domains that employ time series data, and identified the steps that are necessary for building predictive models using time series clinical data. We illustrate the method by applying it to the specific case of building a predictive model for cardiac arrest in a pediatric intensive care unit.

Results

Time course analysis studies from genomic analysis provided a modeling template that was compatible with the steps required to develop a model from clinical time series data. The steps include: 1) selecting candidate variables; 2) specifying measurement parameters; 3) defining data format; 4) defining time window duration and resolution; 5) calculating latent variables for candidate variables not directly measured; 6) calculating time series features as latent variables; 7) creating data subsets to measure model performance effects attributable to various classes of candidate variables; 8) reducing the number of candidate features; 9) training models for various data subsets; and 10) measuring model performance characteristics in unseen data to estimate their external validity.

Conclusions

We have proposed a ten step process that results in data sets that contain time series features and are suitable for predictive modeling by a number of methods. We illustrated the process through an example of cardiac arrest prediction in a pediatric intensive care setting.

[From conventional cytogenetics to microarrays. Fifty years of Philadelphia chromosome]

In 1960 Ph-chromosome was found associated with the presence of chronic myelogenous leukemia. In these 50 years an increasing number of cytogenetic abnormalities have been found associated with hematological malignancies. The presence of these abnormalities is not only important for the diagnosis of the patient, but it also contributes to the prognosis of patients with leukemia or lymphoma. For this reason the WHO classification of hematological disease has included these studies for the correct characterization of leukemias and lymphomas. In addition, the use of FISH and micromatrix methodologies have refined the genetic lesions present in these malignancies. The cytogenetic changes observed also provide further information in relation to the therapy.

Densely interconnected transcriptional circuits control cell states in human hematopoiesis

Though many individual transcription factors are known to regulate hematopoietic differentiation, major aspects of the global architecture of hematopoiesis remain unknown. Here, we profiled gene expression in 38 distinct purified populations of human hematopoietic cells and used probabilistic models of gene expression and analysis of cis-elements in gene promoters to decipher the general organization of their regulatory circuitry. We identified modules of highly coexpressed genes, some of which are restricted to a single lineage but most of which are expressed at variable levels across multiple lineages. We found densely interconnected cis-regulatory circuits and a large number of transcription factors that are differentially expressed across hematopoietic states. These findings suggest a more complex regulatory system for hematopoiesis than previously assumed.

Quantum dots brighten biological imaging

Quantum dots (QDs) are novel photostable semiconductor nanocrystals possessing wide excitation spectra and narrow, symmetrical emission spectra and can be conjugated to a wide range of biological targets, including proteins, antibodies and nucleic acid probes. These characteristics have provoked considerable interest in their use for bioimaging. Much investigation has been performed into their use for multiplex immunohistochemistry and in situ hybridisation which, when combined with multispectral imaging, has enabled quantitation and colocalisation of gene expression in clinical tissue. Many advances have recently been made using QDs for live cell and in vivo imaging, in which QD-labelled molecules can be tracked and visualised in 3-D. This review aims to outline the beneficial properties presented by QDs along with important advances in their biological application.

Chromatin structure and gene expression programs of human embryonic and induced pluripotent stem cells

Knowledge of both the global chromatin structure and the gene expression programs of human embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) should provide a robust means to assess whether the genomes of these cells have similar pluripotent states. Recent studies have suggested that ESCs and iPSCs represent different pluripotent states with substantially different gene expression profiles. We describe here a comparison of global chromatin structure and gene expression data for a panel of human ESCs and iPSCs. Genome-wide maps of nucleosomes with histone H3K4me3 and H3K27me3 modifications indicate that there is little difference between ESCs and iPSCs with respect to these marks. Gene expression profiles confirm that the transcriptional programs of ESCs and iPSCs show very few consistent differences. Although some variation in chromatin structure and gene expression was observed in these cell lines, these variations did not serve to distinguish ESCs from iPSCs.

CD11b is a therapy resistance- and minimal residual disease-specific marker in precursor B-cell acute lymphoblastic leukemia

A consistently increased mRNA expression of the adhesion receptor CD11b is a hallmark of the reported genomewide gene expression changes in precursor B-cell acute lymphoblastic leukemia (PBC-ALL) after 1 week of induction therapy. To investigate its clinical relevance, CD11b protein expression in leukemic blasts has been prospectively measured at diagnosis (159 patients) and during therapy (53 patients). The initially heterogeneous expression of CD11b inversely correlated with cytoreduction rates measured at clinically significant time points of induction therapy in the ALL-Berlin-Frankfurt-Münster 2000 protocol. CD11b positivity conferred a 5-fold increased risk of minimal residual disease (MRD) after induction therapy (day 33) and of high-risk group assignment after consolidation therapy (day 78). In the multivariate analysis CD11b expression was an independent prognostic factor compared with other clinically relevant parameters at diagnosis. During therapy, CD11b expression increased early in most ALL cases and remained consistently increased during induction/consolidation therapy. In more than 30% of MRD-positive cases, the CD11b expression on blast cells exceeded that of mature memory B cells and improved the discrimination of residual leukemic cells from regenerating bone marrow. Taken together, CD11b expression has considerable implications for prognosis, treatment response monitoring, and MRD detection in childhood PBC-ALL.

A novel strategy for mechanism based computational drug discovery

Glioma, the common brain tumor, which arises from the glial cells, offers worse prognosis and therapy than any other tumors. Despite the genetic and pathological diversities of malignant gliomas, common signaling pathways that drive cellular proliferation, survival, invasion and angiogenesis have been identified. Very often, various tyrosine kinase receptors are inappropriately activated in human brain tumors and contribute to tumor malignancy. During such tumourous states where multiple pathways are involved, a few of them are responsbile for cell differentiation, proliferation and anti-apoptosis. Computational simulation studies of normal EGFR signaling in glioma together with the mutant EGFR mediated signaling and the MAPK signaling in glioma were carried out. There were no significant cross talks observed between the mutant EGFR and the MAPK pathways and thus from the simulation results, we propose a novel concept of 'multiple-targeting' that combines EGFR and Ras targeted therapy thereby providing a better therapeutic value against glioma. Diallyl Disulfide (DADS) that has been commonly used for Ras inhibition in glioma was taken for analyses and the effect of inhibiting the EGFR downstream signaling protein with this DADS was analyzed using the simulation and docking studies.

Gene expression signatures in childhood acute leukemias are largely unique and distinct from those of normal tissues and other malignancies

BACKGROUND

Childhood leukemia is characterized by the presence of balanced chromosomal translocations or by other structural or numerical chromosomal changes. It is well know that leukemias with specific molecular abnormalities display profoundly different global gene expression profiles. However, it is largely unknown whether such subtype-specific leukemic signatures are unique or if they are active also in non-hematopoietic normal tissues or in other human cancer types.

METHODS

Using gene set enrichment analysis, we systematically explored whether the transcriptional programs in childhood acute lymphoblastic leukemia (ALL) and myeloid leukemia (AML) were significantly similar to those in different flow-sorted subpopulations of normal hematopoietic cells (n = 8), normal non-hematopoietic tissues (n = 22) or human cancer tissues (n = 13).

RESULTS

This study revealed that e.g., the t(12;21) [ETV6-RUNX1] subtype of ALL and the t(15;17) [PML-RARA] subtype of AML had transcriptional programs similar to those in normal Pro-B cells and promyelocytes, respectively. Moreover, the 11q23/MLL subtype of ALL showed similarities with non-hematopoietic tissues. Strikingly however, most of the transcriptional programs in the other leukemic subtypes lacked significant similarity to approximately 100 gene sets derived from normal and malignant tissues.

CONCLUSIONS

This study demonstrates, for the first time, that the expression profiles of childhood leukemia are largely unique, with limited similarities to transcriptional programs active in normal hematopoietic cells, non-hematopoietic normal tissues or the most common forms of human cancer. In addition to providing important pathogenetic insights, these findings should facilitate the identification of candidate genes or transcriptional programs that can be used as unique targets in leukemia.

Adult acute lymphoblastic leukemia: concepts and strategies

Acute lymphoblastic leukemia (ALL), a clonal expansion of hematopoietic blasts, is a highly heterogeneous disease comprising many entities for which distinct treatment strategies are pursued. Although ALL is a success story in pediatric oncology, results in adults lag behind those in children. An expansion of new drugs, more reliable immunologic and molecular techniques for the assessment of minimal residual disease, and efforts at more precise risk stratification are generating new aspects of adult ALL therapy. For this review, the authors summarized pertinent and recent literature on ALL biology and therapy, and they discuss current strategies and potential implications of novel approaches to the management of adult ALL. Cancer 2010. (c) 2010 American Cancer Society.

Relationship of differential gene expression profiles in CD34+ myelodysplastic syndrome marrow cells to disease subtype and progression

Microarray analysis with 40 000 cDNA gene chip arrays determined differential gene expression profiles (GEPs) in CD34(+) marrow cells from myelodysplastic syndrome (MDS) patients compared with healthy persons. Using focused bioinformatics analyses, we found 1175 genes significantly differentially expressed by MDS versus normal, requiring a minimum of 39 genes to separately classify these patients. Major GEP differences were demonstrated between healthy and MDS patients and between several MDS subgroups: (1) those whose disease remained stable and those who subsequently transformed (tMDS) to acute myeloid leukemia; (2) between del(5q) and other MDS patients. A 6-gene "poor risk" signature was defined, which was associated with acute myeloid leukemia transformation and provided additive prognostic information for International Prognostic Scoring System Intermediate-1 patients. Overexpression of genes generating ribosomal proteins and for other signaling pathways was demonstrated in the tMDS patients. Comparison of del(5q) with the remaining MDS patients showed 1924 differentially expressed genes, with underexpression of 1014 genes, 11 of which were within the 5q31-32 commonly deleted region. These data demonstrated (1) GEPs distinguishing MDS patients from healthy and between those with differing clinical outcomes (tMDS vs those whose disease remained stable) and cytogenetics [eg, del(5q)]; and (2) molecular criteria refining prognostic categorization and associated biologic processes in MDS.

Overexpression of X-linked inhibitor of apoptosis protein (XIAP) is an independent unfavorable prognostic factor in childhood de novo acute myeloid leukemia

The overexpression of X-linked inhibitor of apoptosis protein (XIAP), a member of IAP family protein, is intuitively expected to be associated with unfavorable clinical features in malignancies; however, there have been only a very limited number of studies reporting the clinical relevance of XIAP expression. This study was performed to investigate the prognostic relevance of XIAP expression in childhood acute myeloid leukemia (AML). In 53 children with de novo AML, the level of XIAP expression was determined by using quantitative reverse transcriptase-polymerase chain reaction and was analyzed with respect to the clinical characteristics at diagnosis and treatment outcomes. As a result, the XIAP expression was found to be higher in patients with extramedullary disease than in those without (P=0.014). In addition, XIAP overexpression (>or=median expression) was associated with an unfavorable day 7 response to induction chemotherapy and also associated with a worse 3-yr relapsefree survival rate (52.7+/-20.9% vs. 85.9+/-14.8%, P=0.014). Multivariate analyses revealed that XIAP overexpression was an independent unfavorable prognostic factor for relapse-free survival (hazard ratio, 6.16; 95% confidence interval, 1.48-25.74; P=0.013). Collectively, XIAP overexpression may be used as an unfavorable prognostic marker in childhood AML.

Identification of pediatric septic shock subclasses based on genome-wide expression profiling

BACKGROUND

Septic shock is a heterogeneous syndrome within which probably exist several biological subclasses. Discovery and identification of septic shock subclasses could provide the foundation for the design of more specifically targeted therapies. Herein we tested the hypothesis that pediatric septic shock subclasses can be discovered through genome-wide expression profiling.

METHODS

Genome-wide expression profiling was conducted using whole blood-derived RNA from 98 children with septic shock, followed by a series of bioinformatic approaches targeted at subclass discovery and characterization.

RESULTS

Three putative subclasses (subclasses A, B, and C) were initially identified based on an empiric, discovery-oriented expression filter and unsupervised hierarchical clustering. Statistical comparison of the three putative subclasses (analysis of variance, Bonferonni correction, P < 0.05) identified 6,934 differentially regulated genes. K-means clustering of these 6,934 genes generated 10 coordinately regulated gene clusters corresponding to multiple signaling and metabolic pathways, all of which were differentially regulated across the three subclasses. Leave one out cross-validation procedures indentified 100 genes having the strongest predictive values for subclass identification. Forty-four of these 100 genes corresponded to signaling pathways relevant to the adaptive immune system and glucocorticoid receptor signaling, the majority of which were repressed in subclass A patients. Subclass A patients were also characterized by repression of genes corresponding to zinc-related biology. Phenotypic analyses revealed that subclass A patients were younger, had a higher illness severity, and a higher mortality rate than patients in subclasses B and C.

CONCLUSION

Genome-wide expression profiling can identify pediatric septic shock subclasses having clinically relevant phenotypes.

Genomic expression profiling across the pediatric systemic inflammatory response syndrome, sepsis, and septic shock spectrum

OBJECTIVES

To advance our biological understanding of pediatric septic shock, we measured the genome-level expression profiles of critically ill children representing the systemic inflammatory response syndrome (SIRS), sepsis, and septic shock spectrum.

DESIGN

Prospective observational study involving microarray-based bioinformatics.

SETTING

Multiple pediatric intensive care units in the United States.

PATIENTS

Children

INTERVENTIONS

None other than standard care.

MEASUREMENTS AND MAIN RESULTS

Longitudinal analyses were focused on gene expression relative to control samples and patients having paired day 1 and day 3 samples. The longitudinal analysis focused on up-regulated genes revealed common patterns of up-regulated gene expression, primarily corresponding to inflammation and innate immunity, across all patient groups on day 1. These patterns of up-regulated gene expression persisted on day 3 in patients with septic shock, but not to the same degree in the other patient classes. The longitudinal analysis focused on down-regulated genes demonstrated gene repression corresponding to adaptive immunity-specific signaling pathways and was most prominent in patients with septic shock on days 1 and 3. Gene network analyses based on direct comparisons across the SIRS, sepsis, and septic shock spectrum, and all available patients in the database, demonstrated unique repression of gene networks in patients with septic shock corresponding to major histocompatibility complex antigen presentation. Finally, analyses focused on repression of genes corresponding to zinc-related biology demonstrated that this pattern of gene repression is unique to patients with septic shock.

CONCLUSIONS

Although some common patterns of gene expression exist across the pediatric SIRS, sepsis, and septic shock spectrum, septic shock is particularly characterized by repression of genes corresponding to adaptive immunity and zinc-related biology.

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Key Words

• microarray
• t cell
• antigen presentation
• children
• inflammation
• zinc

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MESH Headings

• Case-Control Studies
• Child
• Child, Preschool
• Critical Care/methods
• Critical Illness
• Female
• Gene Expression Profiling
• Gene Expression Regulation, Bacterial
• Gene Regulatory Networks
• Genome
• Humans
• Intensive Care Units, Pediatric
• Longitudinal Studies
• Male
• Oligonucleotide Array Sequence Analysis
• Prospective Studies
• RNA/analysis
• Reference Values
• Sensitivity and Specificity
• Sepsis/blood
• Sepsis/genetics
• Shock, Septic/blood
• Shock, Septic/genetics
• Systemic Inflammatory Response Syndrome/blood
• Systemic Inflammatory Response Syndrome/genetics

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Grants

• R01 GM064619 NIGMS NIH HHS
• R01 GM066839 NIGMS NIH HHS

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Affiliation(s)

Hector R Wong Department of Pediatrics, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
Natalie Cvijanovich
Geoffrey L Allen
Richard Lin
Nick Anas
Keith Meyer
Robert J Freishtat
Marie Monaco
Kelli Odoms
Bhuvaneswari Sakthivel
Thomas P Shanley
Genomics of Pediatric SIRS/Septic Shock Investigators

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Collaborators Collapse

Molecular classification of rhabdomyosarcoma--genotypic and phenotypic determinants of diagnosis: a report from the Children's Oncology Group

Rhabdomyosarcoma (RMS) in children occurs as two major histological subtypes, embryonal (ERMS) and alveolar (ARMS). ERMS is associated with an 11p15.5 loss of heterozygosity (LOH) and may be confused with nonmyogenic, non-RMS soft tissue sarcomas. ARMS expresses the product of a genomic translocation that fuses FOXO1 (FKHR) with either PAX3 or PAX7 (P-F); however, at least 25% of cases lack these translocations. Here, we describe a genomic-based classification scheme that is derived from the combined gene expression profiling and LOH analysis of 160 cases of RMS and non-RMS soft tissue sarcomas that is at variance with conventional histopathological schemes. We found that gene expression profiles and patterns of LOH of ARMS cases lacking P-F translocations are indistinguishable from conventional ERMS cases. A subset of tumors that has been histologically classified as RMS lack myogenic gene expression. However, classification based on gene expression is possible using as few as five genes with an estimated error rate of less than 5%. Using immunohistochemistry, we characterized two markers, HMGA2 and TFAP2ss, which facilitate the differential diagnoses of ERMS and P-F RMS, respectively, using clinical material. These objectively derived molecular classes are based solely on genomic analysis at the time of diagnosis and are highly reproducible. Adoption of these molecular criteria may offer a more clinically relevant diagnostic scheme, thus potentially improving patient management and therapeutic RMS outcomes.

Musings on genome medicine: cancer genetics and the promise of effective treatment

Cancer is the most common acquired genetic disease. Great progress has been made in documenting the genetic abnormalities that cause the disease, and in the future each tumor will be subjected to genetic analysis and the appropriate combination of drugs selected. Although there are serious technological and cost hurdles to surmount and resistance and continued mutation will be a constant problem, the way is clear to rational therapy.

Expression profile of orphan receptor tyrosine kinase (ROR1) and Wilms' tumor gene 1 (WT1) in different subsets of B-cell acute lymphoblastic leukemia

Recent molecular investigations have demonstrated over-expression of a large number of tumor associated antigens (TAAs) in a variety of malignancies. Over-expression of ROR1 gene, a member of the receptor tyrosine kinase family, has recently been reported in B-cell chronic lymphocytic leukemia. Wilms' tumor gene 1 (WT1) has long been known as a universal TAA expressed in a variety of solid and hematopoietic malignancies. In the present study, the expression profile of ROR1 and WT1 was investigated in different immunophenotypic subsets of B-cell acute lymphoblastic leukemia (B-ALL) patients. RT-PCR method was used to determine the ROR1 and WT1 genes expression in bone marrow (BM) and peripheral blood (PB) samples from 51 newly diagnosed Iranian B-ALL patients. Isolated tumor cells from all patients were immunophenotyped by flow cytometry. Based on immunophenotypic results, our B-ALL patients were classified in four differentiation subsets; Pro-B (n = 7), Pre-B I (n = 29), Pre-B II (n = 13) and Immature/mature B-ALL (n = 2). Although ROR1 was over-expressed in more mature subsets (16.7%, 42.9%, 45.5% and 100%, respectively), WT1 was more represented in immature subsets of B-ALL patients (57.1%, 64.3%, 38.5% and 0%, respectively). Comparison of the frequency of ROR1 and WT1 positive samples at each immunophenotypic subtype revealed statistically significant difference only in Pre B I subtype (p = 0.02). Our results suggest that expression of ROR1 and WT1 in B-ALL is associated with the differentiation stage of the leukemic cells.

The Immunological Genome Project: networks of gene expression in immune cells

The Immunological Genome Project combines immunology and computational biology laboratories in an effort to establish a complete 'road map' of gene-expression and regulatory networks in all immune cells.

A decade of genome-wide gene expression profiling in acute myeloid leukemia: flashback and prospects

The past decade has shown a marked increase in the use of high-throughput assays in clinical research into human cancer, including acute myeloid leukemia (AML). In particular, genome-wide gene expression profiling (GEP) using DNA microarrays has been extensively used for improved understanding of the diagnosis, prognosis, and pathobiology of this heterogeneous disease. This review discusses the progress that has been made, places the technologic limitations in perspective, and highlights promising future avenues.

MicroRNA expression profiling in relation to the genetic heterogeneity of acute myeloid leukemia

Acute myeloid leukemia (AML) is a highly diverse disease characterized by various cytogenetic and molecular abnormalities. MicroRNAs are small noncoding RNAs that show variable expression during myeloid differentiation. MicroRNA expression in marrow blasts in 215 cases of newly diagnosed and (cyto)genetically defined AML was assessed using quantitative reverse-transcription-polymerase chain reaction (RT-PCR) for 260 human microRNAs. In the same series, mRNA gene expression profiles were established, allowing a direct comparison between microRNA and mRNA expression. We show that microRNA expression profiling following unsupervised analysis reveals distinctive microRNA signatures that correlate with cytogenetic and molecular subtypes of AML (ie, AMLs with t(8;21), t(15;17), inv(16), NPM1, and CEBPA mutations). Significantly differentially expressed microRNAs for genetic subtypes of AML were identified. Specific microRNAs with established oncogenic and tumor suppressor functions, such as microRNA-155, microRNA-21, and let-7, appear to be associated with particular subtypes. Combinations of selected sets of microRNAs could predict cytogenetically normal AML with mutations in the genes of NPM1 and CEBPA and FLT3-ITD with similar accuracy as mRNA probe set combinations defined by gene expression profiling. MicroRNA expression apparently bears specific relationships to the heterogeneous pathobiology of AML. Distinctive microRNA signatures appear of potential value in the clinical diagnosis of AML.

The changing scene of adult acute lymphoblastic leukemia

PURPOSE OF REVIEW

The review focuses on the most recent advances in the diagnostic and prognostic work-up of adult acute lymphoblastic leukemia (ALL) and its implications in the clinical management of the disease.

RECENT FINDINGS

ALL can be identified on the basis of morphologic, cytochemical and immunophenotypic criteria; modern management of ALL is also based on cytogenetic and genetic evaluations. New technologies, such as gene expression profile analysis, may allow us to further unravel the intrinsic biology of the disease, to improve diagnostic and prognostic stratification, and to design innovative therapeutic strategies. In potentially all cases, specific markers of the disease can be found and utilized together with the rearrangement of immunoglobulin and T-cell receptor genes to monitor minimal residual disease during clinical follow-up. These biologically-defined subgroups of patients may have a different clinical course, response to treatment and variable prognosis.

SUMMARY

Recent biologic advancements are progressively realising the possibility of designing targeted and individualized therapeutic strategies according to the more refined, molecularly defined features of leukemic cells and the presence or absence of residual disease in adult ALL.

Clinical quantitation of immune signature in follicular lymphoma by RT-PCR-based gene expression profiling

Microarray gene expression profiling studies have demonstrated immune response gene signatures that appear predictive of outcome in follicular lymphoma (FL). However, measurement of these marker genes in routine practice remains difficult. We have therefore investigated the immune response in FL using real-time polymerase chain reaction (PCR) to measure expression levels of 35 candidate Indicator genes, selected from microarray studies, to polyA cDNAs prepared from 60 archived human frozen lymph nodes, in parallel with immunohistochemical analysis for CD3, CD4, CD7, CD8, CD10, CD20, CD21, and CD68. High levels of CCR1, a marker of monocyte activation, were associated with a shorter survival interval, and high levels of CD3 with better survival, while immunohistochemistry demonstrated association of high numbers of CD68(+) macrophages with a shorter survival interval and of high numbers of CD7(+) T cells with a longer survival interval. The results confirm the role of the host immune response in outcome in FL and identify CCR1 as a prognostic indicator and marker of an immune switch between macrophages and a T cell-dominant response. They demonstrate the utility of polyA DNA and real-time PCR for measurement of gene signatures and the applicability of using this type of "molecular block" in clinical practice.

MicroRNA expression signatures accurately discriminate acute lymphoblastic leukemia from acute myeloid leukemia

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer, whereas acute myeloid leukemia (AML) is the most common acute leukemia in adults. In general, ALL has a better prognosis than AML. To understand the distinct mechanisms in leukemogenesis between ALL and AML and to identify markers for diagnosis and treatment, we performed a large-scale genome-wide microRNA (miRNA, miR) expression profiling assay and identified 27 miRNAs that are differentially expressed between ALL and AML. Among them, miR-128a and -128b are significantly overexpressed, whereas let-7b and miR-223 are significantly down-regulated in ALL compared with AML. They are the most discriminatory miRNAs between ALL and AML. Using the expression signatures of a minimum of two of these miRNAs resulted in an accuracy rate of >95% in the diagnosis of ALL and AML. The differential expression patterns of these four miRNAs were validated further through large-scale real-time PCR on 98 acute leukemia samples covering most of the common cytogenetic subtypes, along with 10 normal control samples. Furthermore, we found that overexpression of miR-128 in ALL was at least partly associated with promoter hypomethylation and not with an amplification of its genomic locus. Taken together, we showed that expression signatures of as few as two miRNAs could accurately discriminate ALL from AML, and that epigenetic regulation might play an important role in the regulation of expression of miRNAs in acute leukemias.

The peripheral-blood transcriptome: new insights into disease and risk assessment

Future personalized medicine strategies for assessing an individual's health require, ideally, a noninvasive system that is capable of integrating numerous interactive factors, including gender, age, genetics, behavior, environment and comorbidities. Several microarray-based methods developed to meet this goal are currently under investigation. However, most rely on tissue biopsies, which are not readily available or accessible. As an alternative, several recent studies have investigated the use of human peripheral blood cells as surrogate biopsy material. Such studies are based on the assumption that molecular profiling of circulating blood might reflect physiological and pathological events occurring in different tissues of the body. This has led to the development of novel methods for identifying and monitoring blood biomarkers to probe an individual's health status. Here, we discuss the rationale and clinical potential of profiling the peripheral-blood transcriptome.

A Marfan syndrome gene expression phenotype in cultured skin fibroblasts

BACKGROUND

Marfan syndrome (MFS) is a heritable connective tissue disorder caused by mutations in the fibrillin-1 gene. This syndrome constitutes a significant identifiable subtype of aortic aneurysmal disease, accounting for over 5% of ascending and thoracic aortic aneurysms.

RESULTS

We used spotted membrane DNA macroarrays to identify genes whose altered expression levels may contribute to the phenotype of the disease. Our analysis of 4132 genes identified a subset with significant expression differences between skin fibroblast cultures from unaffected controls versus cultures from affected individuals with known fibrillin-1 mutations. Subsequently, 10 genes were chosen for validation by quantitative RT-PCR.

CONCLUSION

Differential expression of many of the validated genes was associated with MFS samples when an additional group of unaffected and MFS affected subjects were analyzed (p-value < 3 x 10-6 under the null hypothesis that expression levels in cultured fibroblasts are unaffected by MFS status). An unexpected observation was the range of individual gene expression. In unaffected control subjects, expression ranges exceeding 10 fold were seen in many of the genes selected for qRT-PCR validation. The variation in expression in the MFS affected subjects was even greater.

Microarrays for Cancer Diagnosis and Classification

Microarray analysis has yet to be widely accepted for diagnosis and classification of human cancers, despite the exponential increase in microarray studies reported in the literature. Among several methods available, a few refined approaches have evolved for the analysis of microarray data for cancer diagnosis. These include class comparison, class prediction and class discovery. Using as examples some of the major experimental contributions recently provided in the field of both hematological and solid tumors, we discuss the steps required to utilize microarray data to obtain general and reliable gene profiles that could be universally used in clinical laboratories. As we show, microarray technology is not only a new tool for the clinical lab but it can also improve the accuracy of the classical diagnostic techniques by suggesting novel tumor-specific markers. We then highlight the importance of publicly available microarray data and the development of their integrated analysis that may fulfill the promise that this new technology holds for cancer diagnosis and classification.

Lesional gene expression profiling in cutaneous T-cell lymphoma reveals natural clusters associated with disease outcome

Cutaneous T-cell lymphoma (CTCL) is defined by infiltration of activated and malignant T cells in the skin. The clinical manifestations and prognosis in CTCL are highly variable. In this study, we hypothesized that gene expression analysis in lesional skin biopsies can improve understanding of the disease and its management. Based on 63 skin samples, we performed consensus clustering, revealing 3 patient clusters. Of these, 2 clusters tended to differentiate limited CTCL (stages IA and IB) from more extensive CTCL (stages IB and III). Stage IB patients appeared in both clusters, but those in the limited CTCL cluster were more responsive to treatment than those in the more extensive CTCL cluster. The third cluster was enriched in lymphocyte activation genes and was associated with a high proportion of tumor (stage IIB) lesions. Survival analysis revealed significant differences in event-free survival between clusters, with poorest survival seen in the activated lymphocyte cluster. Using supervised analysis, we further characterized genes significantly associated with lower-stage/treatment-responsive CTCL versus higher-stage/treatment-resistant CTCL. We conclude that transcriptional profiling of CTCL skin lesions reveals clinically relevant signatures, correlating with differences in survival and response to treatment. Additional prospective long-term studies to validate and refine these findings appear warranted.

New data on robustness of gene expression signatures in leukemia: comparison of three distinct total RNA preparation procedures

BACKGROUND

Microarray gene expression (MAGE) signatures allow insights into the transcriptional processes of leukemias and may evolve as a molecular diagnostic test. Introduction of MAGE into clinical practice of leukemia diagnosis will require comprehensive assessment of variation due to the methodologies. Here we systematically assessed the impact of three different total RNA isolation procedures on variation in expression data: method A: lysis of mononuclear cells, followed by lysate homogenization and RNA extraction; method B: organic solvent based RNA isolation, and method C: organic solvent based RNA isolation followed by purification.

RESULTS

We analyzed 27 pediatric acute leukemias representing nine distinct subtypes and show that method A yields better RNA quality, was associated with more differentially expressed genes between leukemia subtypes, demonstrated the lowest degree of variation between experiments, was more reproducible, and was characterized with a higher precision in technical replicates. Unsupervised and supervised analyses grouped leukemias according to lineage and clinical features in all three methods, thus underlining the robustness of MAGE to identify leukemia specific signatures.

CONCLUSION

The signatures in the different subtypes of leukemias, regardless of the different extraction methods used, account for the biggest source of variation in the data. Lysis of mononuclear cells, followed by lysate homogenization and RNA extraction represents the optimum method for robust gene expression data and is thus recommended for obtaining robust classification results in microarray studies in acute leukemias.

Quality control of human tissues--experience from the Indiana University Cancer Center-Lilly Research Labs human tissue bank

The success of molecular research and its applications in both the clinical and basic research arenas is strongly dependent on the collection, handling, storage, and quality control of fresh human tissue samples. This tissue bank was set up to bank fresh surgically obtained human tissue using a Clinical Annotated Tissue Database (CATD) in order to capture the associated patient clinical data and demographics using a one way patient encryption scheme to protect patient identification. In this study, we determined that high quality of tissue samples is imperative for both genomic and proteomic molecular research. This paper also contains a brief compilation of the literature involved in the patient ethics, patient informed consent, patient de-identification, tissue collection, processing, and storage as well as basic molecular research generated from the tissue bank using good clinical practices. The current applicable rules, regulations, and guidelines for handling human tissues are briefly discussed. More than 6,610 cancer patients have been consented (97% of those that were contacted by the consenter) and 16,800 tissue specimens have been banked from these patients in 9 years. All samples collected in the bank were QC'd by a pathologist. Approximately 1,550 tissue samples have been requested for use in basic, clinical, and/or biomarker cancer research studies. Each tissue aliquot removed from the bank for a research study were evaluated by a second H&E, if the samples passed the QC, they were submitted for genomic and proteomic molecular analysis/study. Approximately 75% of samples evaluated were of high histologic quality and used for research studies. Since 2003, we changed the patient informed consent to allow the tissue bank to gather more patient clinical follow-up information. Ninety two percent of the patients (1,865 patients) signed the new informed consent form and agreed to be re-contacted for follow-up information on their disease state. In addition, eighty five percent of patients (1,584) agreed to be re-contacted to provide a biological fluid sample to be used for biomarker research.

Semiautomated multiplexed quantum dot-based in situ hybridization and spectral deconvolution

Gene expression profiling has identified several potentially useful gene signatures for predicting outcome or for selecting targeted therapy. However, these signatures have been developed in fresh or frozen tissue, and there is a need to apply them to routinely processed samples. Here, we demonstrate the feasibility of a potentially high-throughput methodology combining automated in situ hybridization with quantum dot-labeled oligonucleotide probes followed by spectral imaging for the detection and subsequent deconvolution of multiple signals. This method is semiautomated and quantitative and can be applied to formalin-fixed, paraffin-embedded tissues. We have combined dual in situ hybridization with immunohistochemistry, enabling simultaneous measurement of gene expression and cell lineage determination. The technique achieves levels of sensitivity and specificity sufficient for the potential application of known expression signatures to biopsy specimens in a semiquantitative way, and the semiautomated nature of the method enables application to high-throughput studies.

Is Molecular Profiling Ready for Use in Clinical Decision Making?

Molecular profiling, the classification of tissue or other specimens for diagnostic, prognostic, and predictive purposes based on multiple gene expression, is a technology that holds major promise for optimizing the management of patients with cancer. However, the use of these tests for clinical decision making presents many challenges to overcome. Assay development and data analysis in this field have been largely exploratory, and leave numerous possibilities for the introduction of bias. Standardization of profiles remains the exception. Classifier performance is usually overinterpreted by presenting the results as p-values or multiplicative effects (e.g., relative risks), while the absolute sensitivity and specificity of classification remain modest at best, especially when tested in large validation samples. Validation has often been done with suboptimal attention to methodology and protection from bias. The postulated classifier performance may be inflated compared to what these profiles can achieve. With the exception of breast cancer, we have little evidence about the incremental discrimination that molecular profiles can provide versus classic risk factors alone. Clinical trials have started to evaluate the utility of using molecular profiles for breast cancer management. Until we obtain data from these trials, the impact of these tests and the net benefit under real-life settings remain unknown. Optimal incorporation into clinical practice is not straightforward. Finally, cost-effectiveness is difficult to appreciate until these other challenges are addressed. Overall, molecular profiling is a fascinating and promising technology, but its incorporation into clinical decision making requires careful planning and robust evidence.