Quantitative nuclease protection assay in paraffin-embedded tissue replicates prognostic microarray gene expression in diffuse large-B-cell lymphoma

Review of Molecular Technologies for Investigating Canine Cancer

Genetic molecular testing is starting to gain traction as part of standard clinical practice for dogs with cancer due to its multi-faceted benefits, such as potentially being able to provide diagnostic, prognostic and/or therapeutic information. However, the benefits and ultimate success of genomic analysis in the clinical setting are reliant on the robustness of the tools used to generate the results, which continually expand as new technologies are developed. To this end, we review the different materials from which tumour cells, DNA, RNA and the relevant proteins can be isolated and what methods are available for interrogating their molecular profile, including analysis of the genetic alterations (both somatic and germline), transcriptional changes and epigenetic modifications (including DNA methylation/acetylation and microRNAs). We also look to the future and the tools that are currently being developed, such as using artificial intelligence (AI) to identify genetic mutations from histomorphological criteria. In summary, we find that the molecular genetic characterisation of canine neoplasms has made a promising start. As we understand more of the genetics underlying these tumours and more targeted therapies become available, it will no doubt become a mainstay in the delivery of precision veterinary care to dogs with cancer.

SurvIAE: Survival prediction with Interpretable Autoencoders from Diffuse Large B-Cells Lymphoma gene expression data

BACKGROUND

In Diffuse Large B-Cell Lymphoma (DLBCL), several methodologies are emerging to derive novel biomarkers to be incorporated in the risk assessment. We realized a pipeline that relies on autoencoders (AE) and Explainable Artificial Intelligence (XAI) to stratify prognosis and derive a gene-based signature.

METHODS

AE was exploited to learn an unsupervised representation of the gene expression (GE) from three publicly available datasets, each with its own technology. Multi-layer perceptron (MLP) was used to classify prognosis from latent representation. GE data were preprocessed as normalized, scaled, and standardized. Four different AE architectures (Large, Medium, Small and Extra Small) were compared to find the most suitable for GE data. The joint AE-MLP classified patients on six different outcomes: overall survival at 12, 36, 60 months and progression-free survival (PFS) at 12, 36, 60 months. XAI techniques were used to derive a gene-based signature aimed at refining the Revised International Prognostic Index (R-IPI) risk, which was validated in a fourth independent publicly available dataset. We named our tool SurvIAE: Survival prediction with Interpretable AE.

RESULTS

From the latent space of AEs, we observed that scaled and standardized data reduced the batch effect. SurvIAE models outperformed R-IPI with Matthews Correlation Coefficient up to 0.42 vs. 0.18 for the validation-set (PFS36) and to 0.30 vs. 0.19 for the test-set (PFS60). We selected the SurvIAE-Small-PFS36 as the best model and, from its gene signature, we stratified patients in three risk groups: R-IPI Poor patients with High levels of GAB1, R-IPI Poor patients with Low levels of GAB1 or R-IPI Good/Very Good patients with Low levels of GPR132, and R-IPI Good/Very Good patients with High levels of GPR132.

CONCLUSIONS

SurvIAE showed the potential to derive a gene signature with translational purpose in DLBCL. The pipeline was made publicly available and can be reused for other pathologies.

A refined cell-of-origin classifier with targeted NGS and artificial intelligence shows robust predictive value in DLBCL

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous entity of B-cell lymphoma. Cell-of-origin (COO) classification of DLBCL is required in routine practice by the World Health Organization classification for biological and therapeutic insights. Genetic subtypes uncovered recently are based on distinct genetic alterations in DLBCL, which are different from the COO subtypes defined by gene expression signatures of normal B cells retained in DLBCL. We hypothesize that classifiers incorporating both genome-wide gene-expression and pathogenetic variables can improve the therapeutic significance of DLBCL classification. To develop such refined classifiers, we performed targeted RNA sequencing (RNA-Seq) with a commercially available next-generation sequencing (NGS) platform in a large cohort of 418 DLBCLs. Genetic and transcriptional data obtained by RNA-Seq in a single run were explored by state-of-the-art artificial intelligence (AI) to develop a NGS-COO classifier for COO assignment and NGS survival models for clinical outcome prediction. The NGS-COO model built through applying AI in the training set was robust, showing high concordance with COO classification by either Affymetrix GeneChip microarray or the NanoString Lymph2Cx assay in 2 validation sets. Although the NGS-COO model was not trained for clinical outcome, the activated B-cell-like compared with the germinal-center B-cell-like subtype had significantly poorer survival. The NGS survival models stratified 30% high-risk patients in the validation set with poor survival as in the training set. These results demonstrate that targeted RNA-Seq coupled with AI deep learning techniques provides reproducible, efficient, and affordable assays for clinical application. The clinical grade assays and NGS models integrating both genetic and transcriptional factors developed in this study may eventually support precision medicine in DLBCL.

Molecular Subtyping of Diffuse Large B-Cell Lymphoma Using a Novel Quantitative RT-PCR Assay

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease. Cell-of-origin classification in DLBCL has identified activated B cell (ABC) and germinal center B cell (GCB) as two major subtypes. Patients with the ABC subtype show reduced overall survival with standard therapies. Development of a quantitative RT-PCR-based lymphoma cell-of-origin (LCOO) assay to determine ABC, GCB, and unclassifiable subtypes in formalin-fixed, paraffin-embedded tissue (FFPET) DLBCL samples is reported. The LCOO classifier was trained on two DLBCL cohorts with validation performed by using an analytical grade assay in an independent cohort of 60 FFPET DLBCL samples. In the validation cohort, LCOO classification was 88.1%, 84.7%, and 84.7% concordant with microarray, immunohistochemistry (Hans classification), and Lymphoma Subtyping Test, respectively. Importantly, LCOO and Lymphoma Subtyping Test assays commonly assigned subtypes in 17 (94.4%) of 18 ABC samples and 34 (89.5%) of 38 GCB DLBCL samples from this cohort. Progression-free survival and overall survival of ABC and GCB subtypes, as classified by all platforms, were not significantly different in the validation cohort. LCOO classification using publicly available microarray gene expression from two independent data sets (414 fresh frozen and 474 FFPET DLBCL biopsies) revealed a significantly worse outcome for the ABC subtype compared with that of the GCB subtype. Thus, a sensitive, reproducible, LCOO assay developed on an easy to standardize quantitative RT-PCR platform may be an important clinical tool for DLBCL cell-of-origin classification.

Gene expression analysis in formalin fixed paraffin embedded melanomas is associated with density of corresponding immune cells in those tissues

Immune cell infiltrates in melanoma have important prognostic value. Gene expression analysis may simultaneously quantify numbers and function of multiple immune cell subtypes in formalin-fixed paraffin-embedded (FFPE) tissues. Prior studies report single gene expression can represent individual immune cell subtypes, but this has not been shown in FFPE melanomas. We hypothesized that gene expression profiling of human melanomas using a new RNA expression technology in FFPE tissue would correlate with the same immune cells identified by immunohistochemistry (IHC). This retrospective study included melanoma specimens analyzed by IHC on tumor tissue microarray (TMA) cores and by gene expression profiling with EdgeSeq Immuno-Oncology Assay using qNPA technology on the corresponding tumors. Standardized gene expression levels were analyzed relative to enumerated cells by IHC using Spearman rank test to calculate r-values. Multivariate analysis was performed by Kruskal–Wallis test. 119 melanoma specimens had both IHC and gene expression information available. There were significant associations between the level of gene expression and its quantified IHC cell marker for CD45⁺, CD3⁺, CD8⁺, CD4⁺, and CD20⁺ cells (all p < 0.001). There were also significant associations with exhaustion markers FoxP3⁺, PD-1⁺, and PD-L1⁺ (all p ≤ 0.0001). This new qNPA technology is useful to quantify intratumoral immune cells on FFPE specimens through RNA gene expression in metastatic melanoma. As previous studies have shown on other solid human tumors, we also confirm that the expression level of a single gene may be used to represent a single IHC immune cell marker in melanoma.

A Nuclease Protection ELISA Assay for Colorimetric and Electrochemical Detection of Nucleic Acids

Early and accurate diagnosis is crucial to monitor infection outcomes and provide timely interventions. However, gold standard polymerase chain reaction assays (PCR) are labor-intensive and require expensive reagents and instrumentation. Nuclease protection has been used for decades to detect and quantify nucleic acid but has not yet been investigated as a diagnostic tool for infectious disease. In this work, we describe a nuclease protection enzyme-linked immunosorbent assay (NP-ELISA) for accurate and sensitive detection of nucleic acid. Briefly, binding of a nucleic acid target to an oligo probe protects it from digestion of un-hybridized nucleic acid by S1 nuclease. Following the workflow of an ELISA, a horseradish peroxidase (HRP)-conjugated antibody binds the probe and oxidizes its substrate to generate signal. The assay was validated with three HRP substrates for absorbance, chemiluminescence, and electrochemical readouts, demonstrating great versatility. Electrochemical detection with 3,3',5,5'-Tetramethylbenzidine (TMB) gave the highest assay sensitivity with a limit of detection of 3.72×103 molecules mL-1. Furthermore, non-complementary targets did not generate a response, indicating a high degree of specificity. This proof of principle serves as a stepping stone towards developing miniaturized, multiplexed nuclease protection assays for point-of-care diagnosis.

Transcriptomic and Protein Analysis of Small-cell Bladder Cancer (SCBC) Identifies Prognostic Biomarkers and DLL3 as a Relevant Therapeutic Target

PURPOSE

Transcriptomic profiling can shed light on the biology of small-cell bladder cancer (SCBC), nominating biomarkers, and novel therapeutic targets.

EXPERIMENTAL DESIGN

Sixty-three patients with SCBC had small-cell histology confirmed and quantified by a genitourinary pathologist. Gene expression profiling was performed for 39 primary tumor samples, 1 metastatic sample, and 6 adjacent normal urothelium samples (46 total) from the same cohort. Protein levels of differentially expressed therapeutic targets, DLL3 and PDL1, and also CD56 and ASCL1, were confirmed by IHC. A SCBC PDX model was utilized to assess in vivo efficacy of DLL3-targeting antibody-drug conjugate (ADC).

RESULTS

Unsupervised hierarchical clustering of 46 samples produced 4 clusters that correlated with clinical phenotypes. Patients whose tumors had the most "normal-like" pattern of gene expression had longer overall survival (OS) compared with the other 3 clusters while patients with the most "metastasis-like" pattern had the shortest OS (P = 0.047). Expression of DLL3, PDL1, ASCL1, and CD56 was confirmed by IHC in 68%, 30%, 52%, and 81% of tissue samples, respectively. In a multivariate analysis, DLL3 protein expression on >10% and CD56 expression on >30% of tumor cells were both prognostic of shorter OS (P = 0.03 each). A DLL3-targeting ADC showed durable antitumor efficacy in a SCBC PDX model.

CONCLUSIONS

Gene expression patterns in SCBC are associated with distinct clinical phenotypes ranging from more indolent to aggressive disease. Overexpression of DLL3 mRNA and protein is common in SCBC and correlates with shorter OS. A DLL3-targeted ADC demonstrated in vivo efficacy superior to chemotherapy in a PDX model of SCBC.

The MCL35 gene expression proliferation assay predicts high-risk MCL patients in a Norwegian cohort of younger patients given intensive first line therapy

Patients with mantle cell lymphoma (MCL) generally have a dismal prognosis. Intensified induction treatment with rituximab and high dose cytarabine (R_HDAC), and consolidation with high-dose therapy with autologous stem cell support has resulted in 10-year overall survival (OS) higher than 60%. However, the clinical course varies. Diagnostic tools capable of stratifying patients include the MCL International Prognostic Index (MIPI), gene expression-based proliferation signature, Ki-67 proliferation index or tumour cell morphology. Here, we tested the performance of a newly developed Nanostring-based RNA expression-based proliferation assay (MCL35) on formalin-fixed paraffin-embedded tumour tissue from younger patients recruited in or treated according to Nordic MCL protocols compared to the prognosticators listed above. Seventy-four patients were included and the assay performed well in all cases except four, which had inadequate RNA quality. The patients were evenly distributed in the MCL35 low-, intermediate- and high-risk categories. MCL35 low- and intermediate- risk groups had overlapping progression-free survival (PFS), while patients in the high-risk category had significantly inferior PFS. Combining MCL35 with MIPI or the MIPI-C (MIPI with the addition of binary Ki67 score +/-30%) showed a better discrimination than either assessment alone. In conclusion, the MCL35 assay alone or combined with MIPI or MIPI-C scores can identify patients who still have a dismal outcome despite intensified treatment.

An assessment of candidate genes to assist prognosis in gastric cancer

Background

Gastric cancer (GC) is the fourth commonest cancer worldwide, with the second highest mortality rate. Its poor mortality is linked to delayed presentation. There is a drive towards non-invasive biomarker screening and monitoring of many different types of cancer, although with limited success so far. We aimed to determine if any genes from a 32-gene panel could be used to determine GC prognosis.

Methods

We carried out a retrospective study on the expression of 32 genes, selected for their proven or potential links to GC, on historic formalin fixed paraffin-embedded (FFPE) GC specimens from our unit. Gene expression was measured using quantitative nuclease protection assays (qNPA) technology. Following statistical analysis of the results, immunohistochemical staining for eight genes, both discriminating and non-discriminating, was conducted in seven age and sex matched non-metastatic: metastatic GC pairings. The stained samples were reviewed by two blinded consultant histopathologists.

Results

Multivariate Cox analysis of the gene expression data revealed metastatic status, age, sex and five genes appeared to influence GC survival. Genes negatively influencing survival included BCAS1, P53 and HSP90AA1 (relative risks 2.20, 3.73 and 7.53 respectively). Genes conveying survival benefit included CASP3 and TERT (relative risks 0.10 and 0.24 respectively). Immunohistochemical staining of seven age and sex matched non-metastatic: metastatic pairs revealed no association between gene expression and protein expression.

Conclusions

Our study found several genes whose expression may affect GC prognosis. However, immunohistochemical analysis revealed no association between gene expression and protein expression. It remains to be determined whether gene expression or protein expression are reliable means of assessing GC prognosis.

Validation of a Multiplexed Gene Signature Assay for Diagnosis of Canine Cancers from Formalin-Fixed Paraffin-Embedded Tissues

Background

Use of molecular‐based diagnostics for companion animals is impeded by availability of technology platforms, tissue acquisition requirements, and species‐specific reagents.

Hypothesis/Objectives

To validate a quantitative nuclease protection assay (qNPA) to simultaneously measure RNA expression of multiple genes in archived formalin‐fixed paraffin‐embedded (FFPE) tumors from dogs.

Animals

All tumor biopsy samples were collected retrospectively from surgical biopsies and in the care of veterinarians.

Methods

Retrospective case series. A qNPA 96‐well ArrayPlate was built using 30 canine‐specific genes, 5 housekeeping genes, positive and negative controls with qualified gene‐specific oligonucleotides. Pearson's correlation, coefficient of variation (CV), and multivariate analysis were used to determine analytical performance using 40 FFPE dog tumors. Once validated, 70 FFPE dog tumors were analyzed for differences in gene expression using hierarchical clustering and analysis of variance of log transformed data. Immunohistochemistry (IHC) was performed to correlate gene expression and protein expression in a subset of tumors.

Results

The assay was linear with decreasing sample input (R² = 0.978), reproducible within and between 96‐well plates (r = 0.988 and 0.95, respectively) and between different laboratories (CV = 0.96). Hierarchical cluster analysis showed grouping of tumors by histogenesis and oncogenes. Significant differences were found between BCl2, E2F transcription factor 1, MDM2, COX‐2, MET proto‐oncogene receptor kinase, and other biologically relevant gene expression in tumor subtypes. Immunohistochemistry confirmed protein expression.

Conclusions and Clinical Implications

Because this technology works reliably on FFPE specimens, it can help expedite the broad introduction of multiplexed genomic information for improved diagnostics and discovery of new targets for therapies in veterinary oncology.

ESMO consensus conference on malignant lymphoma: general perspectives and recommendations for prognostic tools in mature B-cell lymphomas and chronic lymphocytic leukaemia

The European Society for Medical Oncology (ESMO) consensus conference on mature B-cell lymphomas and chronic lymphocytic leukaemia (CLL) was held on 20 June 2015 in Lugano, Switzerland, and included a multidisciplinary panel of 25 leading experts. The aim of the conference was to develop recommendations on critical subjects difficult to consider in detail in the ESMO Clinical Practice Guidelines. The following areas were identified: (i) the elderly patient, (ii) prognostic factors suitable for clinical use and (iii) the 'ultra-high-risk' group. Before the conference, the expert panel was divided into three working groups; each group focused on one of these areas in order to address four clinically relevant questions relating to that topic. All relevant scientific literature, as identified by the experts, was reviewed in advance. During the consensus conference, each working group developed recommendations to address each of the four questions assigned to their group. These recommendations were then presented to the entire panel and a consensus was reached. This manuscript presents recommendations dedicated to the second area of interest, i.e. prognostic factors suitable for clinical use. The four topics [i.e. interim positron emission tomography (PET), TP53 mutations, cell of origin (COO) and minimal residual disease (MRD)] were primarily chosen because of the bulk of available data together with the lack of clear guidance regarding their use in clinical practice and within clinical trials. Results, including a summary of evidence supporting each recommendation, are detailed in this manuscript. The panel acknowledged that detection of TP53 inactivation by deletion or mutation in CLL should be implemented in clinical practice (level of evidence I, strength of recommendation A). Due to their potentially high prognostic value, at least in some lymphoma entities, implementation of interim PET, COO and MRD was highly recommended in the context of clinical trials. All expert panel members approved this final article.

A phase II study of belinostat (PXD101) in relapsed and refractory aggressive B-cell lymphomas: SWOG S0520

Recent advances in diffuse large B-cell lymphomas (DLBCL) have underscored the importance of tumor microenvironment in escaping host anti-tumor responses. One mechanism is loss of major histocompatibility Class II antigens (MHCII) associated with decreased tumor infiltrating T lymphocytes (TIL) and poor survival. Transcription of MHCII is controlled by CIITA which in turn is regulated by histone acetylation. In this study, we hypothesized that HDAC inhibition with belinostat increases MHCII, CIITA expression, TIL and improves patient outcomes. Primary objective was evaluation of toxicity and response. Twenty-two patients were enrolled for the study. Belinostat was well tolerated with mild toxicity. Two partial responses were observed at 5, 13 months after registration for an overall response rate (ORR) (95% CI) of 10.5% (1.3-33.1%), and three patients had stable disease for 4.7, 42.3+, and 68.4 + months with minimum 3-year follow-up. Included correlative studies support the hypothesis and serve as the basis for SWOG S0806 combining vorinostat with R-CHOP.

RNA Sequencing of Formalin-Fixed, Paraffin-Embedded Specimens for Gene Expression Quantification and Data Mining

Background. Proper rRNA depletion is crucial for the successful utilization of FFPE specimens when studying gene expression. We performed a study to evaluate two major rRNA depletion methods: Ribo-Zero and RNase H. RNAs extracted from 4 samples were treated with the two rRNA depletion methods in duplicate and sequenced (N = 16). We evaluated their reducibility, ability to detect RNA, and ability to molecularly subtype these triple negative breast cancer specimens. Results. Both rRNA depletion methods produced consistent data between the technical replicates. We found that the RNase H method produced higher quality RNAseq data as compared to the Ribo-Zero method. In addition, we evaluated the RNAseq data generated from the FFPE tissue samples for noncoding RNA, including lncRNA, enhancer/super enhancer RNA, and single nucleotide variation (SNV). We found that the RNase H is more suitable for detecting high-quality, noncoding RNAs as compared to the Ribo-Zero and provided more consistent molecular subtype identification between replicates. Unfortunately, neither method produced reliable SNV data. Conclusions. In conclusion, for FFPE specimens, the RNase H rRNA depletion method performed better than the Ribo-Zero. Neither method generates data sufficient for SNV detection.

Characterization of gene expression profiling of mouse tissues obtained during the postmortem interval

Attempts to establish a tissue bank from autopsy samples have led to uncovering of the secrets of many diseases. Here, we examined the length of time that the RNA from postmortem tissues is available for microarray analysis and reported the gene expression profile for up- and down-regulated genes during the postmortem interval. We extracted RNA from fresh-frozen (FF) and formalin-fixed paraffin-embedded (FFPE) brains and livers of three different groups of mice: 1) mice immediately after death, 2) mice that were stored at room temperature for 3h after death, and 3) mice that were stored at 4°C for 18h after death, as this storage resembles the human autopsy process in Japan. The RNA quality of the brain and the liver was maintained up to 18h during the postmortem interval. Based on the microarray analysis, we selected genes that were altered by >1.3-fold or <0.77-fold and classified these genes using hierarchical cluster analysis following DAVID gene ontology analysis. These studies revealed that cytoskeleton-related genes were enriched in the set of up-regulated genes, while serine protease inhibitors were enriched in the set of down-regulated genes. Interestingly, although the RNA quality was maintained due to high RNA integrity number (RIN) values, up-regulated genes were not validated by quantitative PCR, suggesting that these genes may become fragmented or modified by an unknown mechanism. Taken together, our findings suggest that under typical autopsy conditions, gene expression profiles that reflect disease pathology can be examined by understanding comprehensive recognition of postmortem fluctuation of gene expression.

Evaluation of a hypoxia regulated gene panel in ovarian cancer

A panel of nine hypoxia regulated genes, selected from a previously published fifty gene panel, was investigated for its ability to predict hypoxic ovarian cancer phenotypes. All nine genes including vascular endothelial growth factor A, glucose transporter 1, phosphoglycerate mutase 1, lactate dehydrogenase A, prolyl 4-hydroxylase, alpha-polypeptide 1, adrenomedullin, N-myc downstream regulated 1, aldolase A, and carbonic anhydrase 9 were upregulated in the HEY and OVCAR-3 human ovarian cell lines cultured in vitro under hypoxic compared to normoxic conditions as measured by quantitative reverse transcription polymerase chain reaction (qRT-PCR). The gene panel was also elevated in HEY xenograft tumor tissue compared to HEY cells cultured in normoxia. The HEY xenograft tissue demonstrated heterogeneous positive immunohistochemical staining for the exogenous hypoxia biomarker pimonidazole, and the hypoxia regulated protein carbonic anhydrase IX. A quantitative nuclease protection assay (qNPA) was developed which included the nine hypoxia regulated genes. The qNPA assay provided similar results to those obtained using qRT-PCR for cultured cell lines. The qNPA assay was also evaluated using paraffin embedded fixed tissues including a set of five patient matched primary and metastatic serous cancers and four normal ovaries. In this small sample set the average gene expression was higher in primary and metastatic cancer tissue compared to normal ovaries for the majority of genes investigated. This study supports further evaluation by qNPA of this gene panel as an alternative or complimentary method to existing protein biomarkers to identify ovarian cancers with a hypoxic phenotype.

A quantitative multiplex nuclease protection assay reveals immunotoxicity gene expression profiles in the rabbit model for vaginal drug safety evaluation

Any vaginal product that alters the mucosal environment and impairs the immune barrier increases the risk of sexually transmitted infections, especially HIV infection, which thrives on mucosal damage and inflammation. The FDA-recommended rabbit vaginal irritation (RVI) model serves as a first line selection tool for vaginal products; however, for decades it has been limited to histopathology scoring, insufficient to select safe anti-HIV microbicides. In this study we incorporate to the RVI model a novel quantitative nuclease protection assay (qNPA) to quantify mRNA levels of 25 genes representing leukocyte differentiation markers, toll-like receptors (TLR), cytokines, chemokines, epithelial repair, microbicidal and vascular markers, by designing two multiplex arrays. Tissue sections were obtained from 36 rabbits (6 per treatment arm) after 14 daily applications of a placebo gel, saline, 4% nonoxynol-9 (N-9), and three combinations of the anti-HIV microbicides tenofovir (TFV) and UC781 in escalating concentrations (highest: 10% TFV+2.5%UC781). Results showed that increased expression levels of toll-like receptor (TLR)-4, interleukin (IL)-1β, CXCL8, epithelial membrane protein (EMP)-1 (P<0.05), and decreased levels of TLR2 (P<0.05), TLR3 and bactericidal permeability increasing protein (BPI) (P<0.001) were associated with cervicovaginal mucosal alteration (histopathology). Seven markers showed a significant linear trend predicting epithelial damage (up with CD4, IL-1β, CXCL8, CCL2, CCL21, EMP1 and down with BPI). Despite the low tissue damage RVI scores, the high-dose microbicide combination gel caused activation of HIV host cells (SLC and CD4) while N-9 caused proinflammatory gene upregulation (IL-8 and TLR4) suggesting a potential for increasing risk of HIV via different mechanisms depending on the chemical nature of the test product.

Gene expression profiling in non-Hodgkin lymphomas

Although the current WHO classification (Swerdlow et al. WHO classification of tumours of haematopoietic and lymphoid tissues. International Agency for Research on Cancer, Lyon, 2008 [1]) for hematolymphoid neoplasms has delineated lymphomas based on the combined morphologic, immunophenotypic, and genotypic findings, further refinement is necessary especially in regard to therapeutics and prognostic implications. High-throughput gene expression profiling (GEP) using microarray technology (Schena et al. Science 270:467-470, 1995 [2]; Augenlicht et al. Proc Natl Acad Sci USA 88:3286-3289, 1991 [3]) was developed about 20 years ago, and further refinement of the technology and analytical approaches has enabled us to routinely evaluate practically the entire transcriptome at a time. GEP has helped to improve the classification and prognostication of non-Hodgkin lymphomas (NHL) as well as improved our understanding of their pathophysiology and response to new therapeutics. In this paper, we will briefly review how this revolutionary tool has transformed our understanding of lymphomas and given us insight into targeted therapeutics. We will also discuss the current efforts in adapting the findings to routine clinical practice, the evolution of the research technology and directions in the future.

Reproducible, Quantitative, and Flexible Molecular Subtyping of Clinical DLBCL Samples Using the NanoString nCounter System

PURPOSE

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease with distinct molecular subtypes. The most established subtyping approach, the "Cell of Origin" (COO) algorithm, categorizes DLBCL into activated B-cell (ABC) and germinal center B-cell (GCB)-like subgroups through gene expression profiling. Recently developed immunohistochemical (IHC) techniques and other established methodologies can deliver discordant results and have various technical limitations. We evaluated the NanoString nCounter gene expression system to address issues with current platforms.

EXPERIMENTAL DESIGN

We devised a scoring system using 145 genes from published datasets to categorize DLBCL samples. After cell line validation, clinical tissue segmentation was tested using commercially available diagnostic DLBCL samples. Finally, we profiled biopsies from patients with relapsed/refractory DLBCL enrolled in the fostamatinib phase IIb clinical trial using three independent RNA expression platforms: NanoString, Affymetrix, and qNPA.

RESULTS

Diagnostic samples showed a typical spread of subtypes with consistent gene expression profiles across matched fresh, frozen, and formalin-fixed paraffin-embedded tissues. Results from biopsy samples across platforms were remarkably consistent, in contrast to published IHC data. Interestingly, COO segmentation of longitudinal fostamatinib biopsies taken at initial diagnosis and then again at primary relapse showed 88% concordance (15/17), suggesting that COO designation remains stable over the course of disease progression.

CONCLUSIONS

DLBCL segmentation of patient tumor samples is possible using a number of expression platforms. However, we found that NanoString offers the most flexibility and fewest limitations in regards to robust clinical tissue subtype characterization. These subtype distinctions should help guide disease prognosis and treatment options within DLBCL clinical practice.

Phase 2 study of imexon, a prooxidant molecule, in relapsed and refractory B-cell non-Hodgkin lymphoma

Lymphoma cells are subject to higher levels of oxidative stress compared with their normal counterparts and may be vulnerable to manipulations of the cellular redox balance. We therefore designed a phase 2 study of imexon (Amplimexon/NSC-714597), a prooxidant molecule, in patients with relapsed/refractory B-cell non-Hodgkin lymphoma (NHL). Imexon was administered at 1000 mg/m(2) IV daily for 5 days in 21-day cycles. Gene expression analysis performed on pretreatment tumor specimens included 13 transcripts used to generate a redox signature score, previously demonstrated to correlate with lymphoma prognosis. Twenty-two patients were enrolled having follicular (n = 9), diffuse large B-cell (DLBCL) (n = 5), mantle cell (n = 3), transformed follicular (n = 2), small lymphocytic (n = 2), and Burkitt (n = 1) lymphoma. The most common grade 3/4 adverse events were anemia (14%) and neutropenia (9%). The overall response rate was 30%, including responses in follicular lymphoma (4 of 9) and DLBCL (2 of 5). Gene expression analyses revealed CD68 and the redox-related genes, GPX1 and SOD2, as well as a higher redox score to correlate with clinical responses. Therefore, pretreatment markers of oxidative stress may identify patients likely to respond to this therapeutic approach. This trial was registered at www.clinicaltrials.gov as #NCT01314014.

In vivo molecular markers for pro-inflammatory cytokine M1 stage and resident microglia in trimethyltin-induced hippocampal injury

Microglia polarization to the classical M1 activation state is characterized by elevated pro-inflammatory cytokines; however, a full profile has not been generated in the early stages of a sterile inflammatory response recruiting only resident microglia. We characterized the initial M1 state in a hippocampal injury model dependent upon tumor necrosis factor (TNF) receptor signaling for dentate granule cell death. Twenty-one-day-old CD1 male mice were injected with trimethyltin (TMT 2.3 mg/kg, i.p.) and the hippocampus was examined at an early stage (24-h post-dosing) of neuronal death. Glia activation was assessed using a custom quantitative nuclease protection assay. We report elevated mRNA levels for glia response such as ionizing calcium-binding adapter molecule-1 and glial fibrillary acidic protein (Gfap); Fas, hypoxia inducible factor alpha, complement component 1qb, TNF-related genes (Tnf, Tnfaip3, Tnfrsfla); interleukin-1 alpha, Cd44, chemokine (C-C motif) ligand (Ccl)2, Cc14, integrin alpha M, lipocalin (Lcn2), and secreted phosphoprotein 1 (Spp1). These changes occurred in the absence of changes in matrix metalloproteinase 9 and 12, neural cell adhesion molecule, metabotropic glutamate receptor (Grm)3, and Ly6/neurotoxin 1 (Lynx1), as well as, a decrease in neurotrophin 3, glutamate receptor subunit epsilon (Grin)-2b, and neurotrophic tyrosine kinase receptor, type 3. The M2 anti-inflammatory marker, transforming growth factor beta-1 (Tgfb1) was elevated. mRNAs associated with early stage of injury-induced neurogenesis including fibroblast growth factor 21 and Mki67 were elevated. In the "non-injured" temporal cortex receiving projections from the hippocampus, Lynx1, Grm3, and Grin2b were decreased and Gfap increased. Formalin fixed-paraffin-embedded tissue did not generate a comparable profile.

Regulatory forum opinion piece: Tox21 and toxicologic pathology

Tox21 is a transformative effort on the part of several U.S. Federal agencies (the National Toxicology Program/National Institute of Environmental Health Sciences [NTP], the National Institutes of Health (NIH) Chemical Genomics Center/National Human Genome Research Institute [NCGC; now called the NIH Center for Translational Therapeutics, National Center for Advancing Translational Sciences] the Environmental Protection Agency's (EPA) National Center for Computational Toxicology, and recently the Food and Drug Administration) that are partnering to fundamentally change the science of safety toxicology. These agencies bring a comprehensive suite of capabilities and are working diligently together to develop, evaluate, and ultimately implement a new safety assessment paradigm. Toxicologic pathology has an important ongoing role in establishing the validity of this transformation, and may ultimately benefit as a discipline through an enhanced understanding of chemically induced disease mechanisms.

Prognostic significance and gene expression profiles of p53 mutations in microsatellite-stable stage III colorectal adenocarcinomas

Although the prognostic value of p53 abnormalities in Stage III microsatellite stable (MSS) colorectal cancers (CRCs) is known, the gene expression profiles specific to the p53 status in the MSS background are not known. Therefore, the current investigation has focused on identification and validation of the gene expression profiles associated with p53 mutant phenotypes in MSS Stage III CRCs. Genomic DNA extracted from 135 formalin-fixed paraffin-embedded tissues, was analyzed for microsatellite instability (MSI) and p53 mutations. Further, mRNA samples extracted from five p53-mutant and five p53-wild-type MSS-CRC snap-frozen tissues were profiled for differential gene expression by Affymetrix Human Genome U133 Plus 2.0 arrays. Differentially expressed genes were further validated by the high-throughput quantitative nuclease protection assay (qNPA), and confirmed by quantitative real-time polymerase chain reaction (qRT-PCR) and by immunohistochemistry (IHC). Survival rates were estimated by Kaplan-Meier and Cox regression analyses. A higher incidence of p53 mutations was found in MSS (58%) than in MSI (30%) phenotypes. Both univariate (log-rank, P = 0.025) and multivariate (hazard ratio, 2.52; 95% confidence interval, 1.25-5.08) analyses have demonstrated that patients with MSS-p53 mutant phenotypes had poor CRC-specific survival when compared to MSS-p53 wild-type phenotypes. Gene expression analyses identified 84 differentially expressed genes. Of 49 down-regulated genes, LPAR6, PDLIM3, and PLAT, and, of 35 up-regulated genes, TRIM29, FUT3, IQGAP3, and SLC6A8 were confirmed by qNPA, qRT-PCR, and IHC platforms. p53 mutations are associated with poor survival of patients with Stage III MSS CRCs and p53-mutant and wild-type phenotypes have distinct gene expression profiles that might be helpful in identifying aggressive subsets.

Developmental regulation of microRNA expression in Schwann cells

Schwann cell differentiation and subsequent myelination of the peripheral nervous system require the action of several transcription factors, including Sox10, which is vital at multiple stages of development. The transition from immature to myelinating Schwann cell is also regulated posttranscriptionally and depends upon Dicer-mediated processing of microRNAs (miRNAs). Although specific miRNA targets have begun to be identified, the mechanisms establishing the dynamic regulation of miRNA expression have not been elucidated. We performed expression profiling studies and identified 225 miRNAs differentially expressed during peripheral myelination. A subset of 9 miRNAs is positively regulated by Sox10, including miR-338 which has been implicated in oligodendrocyte maturation. In vivo chromatin immunoprecipitation (ChIP) of sciatic nerve cells revealed a Sox10 binding site upstream of an alternate promoter within the Aatk gene, which hosts miR-338. Sox10 occupied this site in spinal cord ChIP experiments, suggesting a similar regulatory mechanism in oligodendrocytes. Cancer profiling studies have identified clusters of miRNAs that regulate proliferation, termed "oncomirs." In Schwann cells, the expression of many of these proproliferative miRNAs was reduced in the absence of Sox10. Finally, Schwann cells with reduced Sox10 and oncomir expression have an increase in the CDK inhibitor p21 and a concomitant reduction in cell proliferation.

New strategies in diffuse large B-cell lymphoma: translating findings from gene expression analyses into clinical practice

Gene expression profiling has had a major impact on our understanding of the biology and heterogeneity of diffuse large B-cell lymphoma (DLBCL). Using this technology, investigators can identify biologic subgroups of DLBCL that provide unique targets for rational therapeutic intervention. This review summarizes these potential targets and updates the progress of clinical development of exciting novel agents for the treatment of DLBCL. Results of ongoing studies suggest that in the near future, we will be able to use gene expression profiling, or an accurate surrogate, to define the best therapeutic approach for individual patients with DLBCL.

A strategy for full interrogation of prognostic gene expression patterns: exploring the biology of diffuse large B cell lymphoma

BACKGROUND

Gene expression profiling yields quantitative data on gene expression used to create prognostic models that accurately predict patient outcome in diffuse large B cell lymphoma (DLBCL). Often, data are analyzed with genes classified by whether they fall above or below the median expression level. We sought to determine whether examining multiple cut-points might be a more powerful technique to investigate the association of gene expression with outcome.

METHODOLOGY/PRINCIPAL FINDINGS

We explored gene expression profiling data using variable cut-point analysis for 36 genes with reported prognostic value in DLBCL. We plotted two-group survival logrank test statistics against corresponding cut-points of the gene expression levels and smooth estimates of the hazard ratio of death versus gene expression levels. To facilitate comparisons we also standardized the expression of each of the genes by the fraction of patients that would be identified by any cut-point. A multiple comparison adjusted permutation p-value identified 3 different patterns of significance: 1) genes with significant cut-point points below the median, whose loss is associated with poor outcome (e.g. HLA-DR); 2) genes with significant cut-points above the median, whose over-expression is associated with poor outcome (e.g. CCND2); and 3) genes with significant cut-points on either side of the median, (e.g. extracellular molecules such as FN1).

CONCLUSIONS/SIGNIFICANCE

Variable cut-point analysis with permutation p-value calculation can be used to identify significant genes that would not otherwise be identified with median cut-points and may suggest biological patterns of gene effects.

Robust gene expression signature from formalin-fixed paraffin-embedded samples predicts prognosis of non-small-cell lung cancer patients

PURPOSE

The requirement of frozen tissues for microarray experiments limits the clinical usage of genome-wide expression profiling by using microarray technology. The goal of this study is to test the feasibility of developing lung cancer prognosis gene signatures by using genome-wide expression profiling of formalin-fixed paraffin-embedded (FFPE) samples, which are widely available and provide a valuable rich source for studying the association of molecular changes in cancer and associated clinical outcomes.

EXPERIMENTAL DESIGN

We randomly selected 100 Non-Small-Cell lung cancer (NSCLC) FFPE samples with annotated clinical information from the UT-Lung SPORE Tissue Bank. We microdissected tumor area from FFPE specimens and used Affymetrix U133 plus 2.0 arrays to attain gene expression data. After strict quality control and analysis procedures, a supervised principal component analysis was used to develop a robust prognosis signature for NSCLC. Three independent published microarray datasets were used to validate the prognosis model.

RESULTS

This study showed that the robust gene signature derived from genome-wide expression profiling of FFPE samples is strongly associated with lung cancer clinical outcomes and can be used to refine the prognosis for stage I lung cancer patients, and the prognostic signature is independent of clinical variables. This signature was validated in several independent studies and was refined to a 59-gene lung cancer prognosis signature.

CONCLUSIONS

We conclude that genome-wide profiling of FFPE lung cancer samples can identify a set of genes whose expression level provides prognostic information across different platforms and studies, which will allow its application in clinical settings.

Accurate classification of diffuse large B-cell lymphoma into germinal center and activated B-cell subtypes using a nuclease protection assay on formalin-fixed, paraffin-embedded tissues

Classification of diffuse large B-cell lymphoma (DLBCL) into cell-of-origin (COO) subtypes based on gene expression profiles has well-established prognostic value. These subtypes, termed germinal center B cell (GCB) and activated B cell (ABC) also have different genetic alterations and overexpression of different pathways that may serve as therapeutic targets. Thus, accurate classification is essential for analysis of clinical trial results and planning new trials by using targeted agents. The current standard for COO classification uses gene expression profiling (GEP) of snap frozen tissues, and a Bayesian predictor algorithm. However, this is generally not feasible. In this study, we investigated whether the qNPA technique could be used for accurate classification of COO by using formalin-fixed, paraffin-embedded (FFPE) tissues. We analyzed expression levels of 14 genes in 121 cases of R-CHOP-treated DLBCL that had previously undergone GEP by using the Affymetrix U133 Plus 2.0 microarray and had matching FFPE blocks. Results were evaluated by using the previously published algorithm with a leave-one-out cross-validation approach. These results were compared with COO classification based on frozen tissue GEP profiles. For each case, a probability statistic was generated indicating the likelihood that the classification by using qNPA was accurate. When data were dichotomized into GCB or non-GCB, overall accuracy was 92%. The qNPA technique accurately categorized DLBCL into GCB and ABC subtypes, as defined by GEP. This approach is quantifiable, applicable to FFPE tissues with no technical failures, and has potential for significant impact on DLBCL research and clinical trial development.

The 2008 WHO classification of lymphoid neoplasms and beyond: evolving concepts and practical applications

The World Health Organization classification of lymphoid neoplasms updated in 2008 represents a worldwide consensus on the diagnosis of these tumors and is based on the recognition of distinct diseases, using a multidisciplinary approach. The updated classification refined the definitions of well-recognized diseases, identified new entities and variants, and incorporated emerging concepts in the understanding of lymphoid neoplasms. However, some questions were unresolved, such as the extent to which specific genetic or molecular alterations define certain tumors, and the status of provisional entities, categories for which the World Health Organization working groups felt there was insufficient evidence to recognize as distinct diseases at this time. In addition, since its publication, new findings and ideas have been generated. This review summarizes the scientific rationale for the classification, emphasizing changes that have had an effect on practice guidelines. The authors address the criteria and significance of early or precursor lesions and the identification of certain lymphoid neoplasms largely associated with particular age groups, such as children and the elderly. The issue of borderline categories having overlapping features with large B-cell lymphomas, as well as several provisional entities, is reviewed. These new observations chart a course for future research in the field.

Increased MYC gene copy number correlates with increased mRNA levels in diffuse large B-cell lymphoma

BACKGROUND

Translocations involving the MYC gene and increased MYC mRNA levels are associated with poor outcome in diffuse large B-cell lymphoma. However, the presence of increased MYC gene copy number and/or polysomy of chromosome 8 have not been previously described.

DESIGN AND METHODS

Utilizing dual color chromogenic in situ hybridization, we investigated MYC gene copy and chromosome 8 centromere numbers in 52 cases of diffuse large B-cell lymphoma. Cases were divided into those with "increased" or "not increased" MYC gene copy number for comparison with MYC mRNA levels, Ki-67 values, and survival.

RESULTS

Increased MYC gene copy number was present in 38% of cases. Overall, the average MYC mRNA level was 2398 (range, 342 - 9783) and the percentage of nuclei positive for Ki-67 was 57.5% (range, 20-87%). Within the group with increased MYC copy number, the MYC mRNA values ranged from 816 to 5912 (average, 2843) and the Ki-67 values ranged from 23% to 83% (average, 57%). Within the group with not increased MYC copy number, MYC mRNA values ranged from 342 to 9783 (average, 2118) and the Ki-67 values ranged from 20% to 87% (average, 58%). There was a statistically significant relationship between increased MYC gene copy number and increased MYC mRNA (P=0.034) and a trend toward a relationship between increased mRNA and higher Ki-67 values.

CONCLUSIONS

This is the first report that low level copy number increases are common in diffuse large B-cell lymphoma and that these changes correlate with MYC mRNA in a statistically significant manner. MYC copy number changes are an additional possible molecular mechanism that may result in increased mRNA and, likely, high proliferation and poor outcome.

InterLymph hierarchical classification of lymphoid neoplasms for epidemiologic research based on the WHO classification (2008): update and future directions

After publication of the updated World Health Organization (WHO) classification of tumors of hematopoietic and lymphoid tissues in 2008, the Pathology Working Group of the International Lymphoma Epidemiology Consortium (InterLymph) now presents an update of the hierarchical classification of lymphoid neoplasms for epidemiologic research based on the 2001 WHO classification, which we published in 2007. The updated hierarchical classification incorporates all of the major and provisional entities in the 2008 WHO classification, including newly defined entities based on age, site, certain infections, and molecular characteristics, as well as borderline categories, early and "in situ" lesions, disorders with limited capacity for clinical progression, lesions without current International Classification of Diseases for Oncology, 3rd Edition codes, and immunodeficiency-associated lymphoproliferative disorders. WHO subtypes are defined in hierarchical groupings, with newly defined groups for small B-cell lymphomas with plasmacytic differentiation and for primary cutaneous T-cell lymphomas. We suggest approaches for applying the hierarchical classification in various epidemiologic settings, including strategies for dealing with multiple coexisting lymphoma subtypes in one patient, and cases with incomplete pathologic information. The pathology materials useful for state-of-the-art epidemiology studies are also discussed. We encourage epidemiologists to adopt the updated InterLymph hierarchical classification, which incorporates the most recent WHO entities while demonstrating their relationship to older classifications.

Optimization of nonlinear dose- and concentration-response models utilizing evolutionary computation

An essential part of toxicity and chemical screening is assessing the concentrated related effects of a test article. Most often this concentration-response is a nonlinear, necessitating sophisticated regression methodologies. The parameters derived from curve fitting are essential in determining a test article's potency (EC(50)) and efficacy (E(max)) and variations in model fit may lead to different conclusions about an article's performance and safety. Previous approaches have leveraged advanced statistical and mathematical techniques to implement nonlinear least squares (NLS) for obtaining the parameters defining such a curve. These approaches, while mathematically rigorous, suffer from initial value sensitivity, computational intensity, and rely on complex and intricate computational and numerical techniques. However if there is a known mathematical model that can reliably predict the data, then nonlinear regression may be equally viewed as parameter optimization. In this context, one may utilize proven techniques from machine learning, such as evolutionary algorithms, which are robust, powerful, and require far less computational framework to optimize the defining parameters. In the current study we present a new method that uses such techniques, Evolutionary Algorithm Dose Response Modeling (EADRM), and demonstrate its effectiveness compared to more conventional methods on both real and simulated data.

Translating gene expression into clinical care: sarcomas as a paradigm

Whereas most solid tumors are characterized by considerable genetic instability and molecular heterogeneity, sarcomas include many subtypes with very specific underlying molecular events driving oncogenesis. Gene expression profiling and other modern techniques have consequently had particular success in identifying the critical biologic pathways active in specific sarcomas, yielding insights which can be translated into useful diagnostic biomarkers. Public availability of data sets and new sequencing-based technologies will accelerate this process. Molecular studies have also identified oncogenic pathways of particular importance in sarcomas which can be targeted by investigational drugs. Examples include histone deacetylases in translocation-associated sarcomas of young adults, Akt/mammalian target of rapamycin in pleomorphic sarcomas, and macrophage colony-stimulating factor in tenosynovial giant cell tumor. Despite challenges in organization and accrual, future clinical trials of sarcomas need to be designed that take into account specific molecular subtypes as distinct diseases.

Xenobiotic-metabolizing enzyme and transporter gene expression in primary cultures of human hepatocytes modulated by ToxCast chemicals

Primary human hepatocyte cultures are useful in vitro model systems of human liver because when cultured under appropriate conditions the hepatocytes retain liver-like functionality such as metabolism, transport, and cell signaling. This model system was used to characterize the concentration- and time-response of the 320 ToxCast chemicals for changes in expression of genes regulated by nuclear receptors. Fourteen gene targets were monitored in quantitative nuclease protection assays: six representative cytochromes P-450, four hepatic transporters, three Phase II conjugating enzymes, and one endogenous metabolism gene involved in cholesterol synthesis. These gene targets are sentinels of five major signaling pathways: AhR, CAR, PXR, FXR, and PPARalpha. Besides gene expression, the relative potency and efficacy for these chemicals to modulate cellular health and enzymatic activity were assessed. Results demonstrated that the culture system was an effective model of chemical-induced responses by prototypical inducers such as phenobarbital and rifampicin. Gene expression results identified various ToxCast chemicals that were potent or efficacious inducers of one or more of the 14 genes, and by inference the 5 nuclear receptor signaling pathways. Significant relative risk associations with rodent in vivo chronic toxicity effects are reported for the five major receptor pathways. These gene expression data are being incorporated into the larger ToxCast predictive modeling effort.

Coordinate loss of MHC class II expression in the diffuse large B cell lymphoma cell line OCI-Ly2 is due to a novel mutation in RFX-AP

Loss of major histocompatibility complex class II (MHCII) antigen expression on diffuse large B cell lymphoma (DLBCL) corresponds closely with significant decreases in patient survival. However, the mechanisms accounting for MHCII loss in DLBCL have not been thoroughly characterized to date. In this report, we demonstrate that coordinate loss of MHCII expression in OCI-Ly2 DLBCL cells is associated with an 11-base deletion in the cDNA encoding RFX-AP, one of the subunits of the heterotrimeric regulatory factor X (RFX) that is required for activating MHCII transcription. This deletion results in a frameshift in the RFX-AP protein beginning at amino acid 234 and, therefore, in the loss of C-terminal amino acids that are required for function. Stable transfection of OCI-Ly2 DLBCL cells with an expression vector for wild-type RFX-AP restores MHCII expression, which strongly suggests that the defect in RFX-AP accounts for MHCII loss in these cells.

Polyanionic microbicides modify Toll-like receptor-mediated cervicovaginal immune responses

Topical microbicides are being developed as a preventative approach to reduce the sexual transmission of human immunodeficiency virus type 1 (HIV-1) and other infections. For them to be efficacious, it is believed that they should avoid inducing inflammation while allowing the vaginal epithelium to initiate protective Toll-like receptor (TLR)-mediated innate responses against pathogens. In this study, human cervical and vaginal epithelial cells were exposed to polyanionic HIV entry inhibitors and the following synthetic TLR ligands: (i) the bacterial lipoprotein Pam(3)CSK(4), binding cell surface TLR1/TLR2; (ii) macrophage activating lipopeptide 2 (MALP-2), binding cell surface TLR2/TLR6; and (iii) the viral double-stranded RNA analog poly(I:C), recognized by intracellular TLR3. Cell activation was assessed by nuclear factor kappaB (NF-kappaB) reporter gene transactivation and cytokine production. In spite of enhancing TLR-triggered NF-kappaB activation, the polyanionic microbicide compounds dextran sulfate and polystyrene sulfonate significantly inhibited TLR-mediated cytokine production. They decreased cytokine mRNA and protein levels of proinflammatory (interleukin-8 [IL-8] and IL-1beta) and antiviral (beta interferon) cytokines following epithelial cell stimulation with Pam(3)CSK(4), MALP-2, or poly(I:C). These activities were associated with the sulfate/sulfonate moieties of the polyanionic compounds, since the unsulfated dextran control did not show any effects. Our data demonstrate that these microbicide compounds are capable of selectively interfering with TLR-mediated epithelial responses at different points in their signaling pathways and underscore the importance of expanding the assessment of microbicide compatibility with vaginal innate immune function. Further studies are warranted to determine the impact of this interference on HIV-1 transmission risk.

Cytokine multiplex analysis

The ability to monitor gene expression in experimental and clinical samples is an essential element of modern molecular biology and cell biology research. However with the advent of a systems biology approach toward understanding cell and cancer biology, analysis of expression of a single gene is no longer desirable. Today, multiplex analysis, where the expression of 8-100 genes can be monitored in one sample, has become a routine aspect of gene expression analysis. In this chapter the various assays systems commercially available for multiplex analysis of both RNA and protein will be discussed.

Gene expression predicts overall survival in paraffin-embedded tissues of diffuse large B-cell lymphoma treated with R-CHOP

Gene expression profiling (GEP) on frozen tissues has identified genes predicting outcome in patients with diffuse large B-cell lymphoma (DLBCL). Confirmation of results in current patients is limited by availability of frozen samples and addition of monoclonal antibodies to treatment regimens. We used a quantitative nuclease protection assay (qNPA) to analyze formalin-fixed, paraffin-embedded tissue blocks for 36 previously identified genes (N = 209, 93 chemotherapy; 116 rituximab + chemotherapy). By qNPA, 208 cases were successfully analyzed (99.5%). In addition, 15 of 36 and 11 of 36 genes, representing each functional group previously identified by GEP, were associated with survival (P < .05) in the 2 treatment groups, respectively. In addition, 30 of 36 hazard ratios of death trended in the same direction versus the original studies. Multivariate and variable cut-off point analysis identified low levels of HLA-DRB (< 20%) and high levels of MYC (> 80%) as independent indicators of survival, together distinguishing cases with the worst prognosis. Our results solve a clinical research problem by demonstrating that prognostic genes can be meaningfully quantified using qNPA technology on formalin-fixed, paraffin-embedded tissues; previous GEP findings in DLBCL are relevant with current treatments; and 2 genes, representing immune escape and proliferation, are the common features of the most aggressive DLBCL.

Burkitt lymphoma in adults

This review will begin with a detail of the revision of the WHO classification, and pathological definitions of Burkitt lymphoma. Over the past several years, molecular understanding of Burkitt lymphoma has improved significantly. Using gene expression profiling, a genomic "signature" of Burkitt lymphoma may be identified, that has fidelity beyond c-myc expression, and the presence of the classical t(8;14). Then, evaluation and therapy of the adult patient with Burkitt lymphoma will be reviewed. Relatively few data exist on optimal therapy of the adult patient with Burkitt lymphoma. Principles of therapy should include high doses of alkylating agents, frequent administration of chemotherapy, and attention to central nervous system (CNS) prophylaxis with high doses of systemic chemotherapy, intrathecal therapy, or both. The outcome of adult patients with Burkitt lymphoma, particularly those over 40 years of age, is inferior to the outcome of younger patients, but may be improving over the past few years. Results from an international collaborative effort, which are helpful in evaluating results of Burkitt lymphoma therapy in adults, will be presented. HIV-associated Burkitt lymphoma, and elderly patients with Burkitt lymphoma, comprise special clinical situations that will be also covered in this review.