Epidemiologic studies have reported that frequent consumption of quercetin-rich foods is inversely associated with lung cancer incidence. A quercetin-rich diet might modulate microRNA (miR) expression; however, this mechanism has not been fully examined.
miR expression data were measured by a custom-made array in formalin-fixed paraffin-embedded tissue samples from 264 lung cancer cases (144 adenocarcinomas and 120 squamous cell carcinomas). Intake of quercetin-rich foods was derived from a food-frequency questionnaire. In individual-miR-based analyses, we compared the expression of miRs (n=198) between lung cancer cases consuming high-versus-low quercetin-rich food intake using multivariate ANOVA tests. In family-miR-based analyses, we used Functional Class Scoring (FCS) to assess differential effect on biologically functional miRs families. We accounted for multiple testing using 10,000 global permutations (significance at p-valueglobal <0.10). All multivariate analyses were conducted separately by histology and by smoking status (former and current smokers).
Family-based analyses showed that a quercetin-rich diet differentiated miR expression profiles of the tumor suppressor let-7 family among adenocarcinomas (p-valueFCS<0.001). Other significantly differentiated miR families included carcinogenesis-related miR-146, miR-26, and miR-17 (p-valuesFCS<0.05). In individual-based analyses, we found that among former and current smokers with adenocarcinoma, 33 miRs were observed to be differentiated between highest-and-lowest quercetin-rich food consumers (23 expected by chance; p-valueglobal = 0.047).
We observed differential expression of key biologically functional miRNAs between high-versus-low consumers of quercetin-rich foods in adenocarcinoma cases.
Our findings provide preliminary evidence on the mechanism underlying quercetin-related lung carcinogenesis.
The outcomes of clinical trials using bone marrow stromal cell (BMSC) are variable; the degree of the expansion of BMSCs during clinical manufacturing may contribute to this variability since cell expansion is limited by senescence. Human BMSCs from aspirates of healthy subjects were subcultured serially until cell growth stopped. Phenotype and functional measurers of BMSCs from two subjects including senescence-associated beta-galactosidase staining and colony formation efficiency changed from an early to a senescence pattern at passage 6 or 7. Transcriptome analysis of 10 early and 15 late passage BMSC samples from 5 subjects revealed 2122 differentially expressed genes, which were associated with immune response, development, and cell proliferation pathways. Analysis of 57 serial BMSC samples from 7 donors revealed that the change from an early to senescent profile was variable among subjects and occurred prior to changes in phenotypes. BMSC age expressed as a percentage of maximum population doublings (PDs) was a good indicator for an early or senescence transcription signature but this measure of BMSC life span can only be calculated after expanding BMSCs to senescence. In order to find a more useful surrogate measure of BMSC age, we used a computational biology approach to identify a set of genes whose expression at each passage would predict elapsed age of BMSCs. A total of 155 genes were highly correlated with BMSC age. A least angle regression algorithm identified a set of 24 BMSC age-predictive genes. In conclusion, the onset of senescence-associated molecular changes was variable and preceded changes in other indicators of BMSC quality and senescence. The 24 BMSC age predictive genes will be useful in assessing the quality of clinical BMSC products.
Bone marrow stromal cells; cellular therapy; gene expression profiling; Graft-versus-Host-Disease; regenerative medicine
Recent observations suggest that immune-mediated tissue destruction is dependent upon coordinate activation of immune genes expressed by cells of the innate and adaptive immune systems.
Here, we performed a retrospective pilot study to investigate whether the coordinate expression of molecular signature mostly associated with NK cells could be used to segregate breast cancer patients into relapse and relapse-free outcomes.
By analyzing primary breast cancer specimens derived from patients who experienced either 58–116 months (~5-9 years) relapse-free survival or developed tumor relapse within 9–76 months (~1-6 years) we found that the expression of molecules involved in activating signaling of NK cells and in NK cells: target interaction is increased in patients with favorable prognosis.
The parameters identified in this study, together with the prognostic signature previously reported by our group, highlight the cooperation between the innate and adaptive immune components within the tumor microenvironment.
Breast cancer prognosis; Molecular markers; Innate immunity; NK cells; Tumour relapse; Tumour microenvironment
The clinical significance of tumor-infiltrating immune cells has been reported in a variety of human carcinomas including breast cancer. However, molecular signature of tumor-infiltrating immune cells and their prognostic value in breast cancer patients remain elusive. We hypothesized that a distinct network of immune function genes at the tumor site can predict a low risk versus high risk of distant relapse in breast cancer patients regardless of the status of ER, PR, or HER-2/neu in their tumors. We conducted retrospective studies in a diverse cohort of breast cancer patients with a 1–5 year tumor relapse versus those with up to 7 years relapse-free survival. The RNAs were extracted from the frozen tumor specimens at the time of diagnosis and subjected to microarray analysis and real-time RT-PCR. Paraffin-embedded tissues were also subjected to immunohistochemistry staining. We determined that a network of immune function genes involved in B cell development, interferon signaling associated with allograft rejection and autoimmune reaction, antigen presentation pathway, and cross talk between adaptive and innate immune responses were exclusively upregulated in patients with relapse-free survival. Among the 299 genes, five genes which included B cell response genes were found to predict with >85% accuracy relapse-free survival. Real-time RT-PCR confirmed the 5-gene prognostic signature that was distinct from an FDA-cleared 70-gene signature of MammaPrint panel and from the Oncotype DX recurrence score assay panel. These data suggest that neoadjuvant immunotherapy in patients with high risk of relapse may reduce tumor recurrence by inducing the immune function genes.
Breast cancer prognosis; Tumor relapse; Tumor microenvironment; Immune response; Neoadjuvant immunotherapy
We have previously shown that within tumors, recombinant interleukin-2 (rIL-2, Aldesleukin) consistently activates tumor-associated macrophages and up-regulates interferon stimulated genes (ISGs) while inducing minimal migration, activation or proliferation of T-cells. These effects are independent of tumor response to treatment. Here, we prospectively evaluated transcriptional alterations induced by rIL-2 in peripheral blood mononuclear cells (PBMCs) and within melanoma metastases.
We evaluated gene expression changes by serially comparing pre- to post-treatment samples in 14 patients and also compared transcriptional differences among lesions displaying different responsiveness to therapy, focusing on 2 lesions decreasing in size and 2 remaining stable (responding lesions) compared to non-responding ones.
As previously described, the effects of rIL-2 were dramatic within PBMC, while effects within the tumor microenvironment were lesion-specific and limited. However, distinct signatures specific to response could be observed in responding lesions pre-treatment that were amplified following rIL-2 administration. These signatures match the functional profile observed in other human or experimental models in which immune-mediated tissue-specific destruction (TSD) occurs underlying a common pathways leading to rejection. Moreover, the signatures observed in pre-treatment lesions were qualitatively similar to those associated with TSD underlining a determinism to immune responsiveness that depends upon the genetic background of the host or the intrinsic genetic makeup of individual tumors.
This is the first prospectively collected insight on global transcriptional events occurring during high-dose rIL-2 therapy in melanoma metastases responding to treatment.
Abnormalities in the constitutive and IFN-γ–inducible HLA class I surface antigen expression of tumor cells is often associated with an impaired expression of components of the antigen processing machinery (APM). Hence, we analyzed whether there exists a link between the IFN-γ signaling pathway, constitutive HLA class I APM component expression, and IFN-γ resistance.
The basal and IFN-γ–inducible expression profiles of HLA class I APM and IFN-γ signal transduction cascade components were assessed in melanoma cells by real-time PCR (RT-PCR), Western blot analysis and/or flow cytometry, the integrity of the Janus activated kinase (JAK) 2 locus by comparative genomic hybridization. JAK2 was transiently overexpressed in JAK2− cells. The effect of IFN-γ on the cell growth was assessed by XTT [2,3-bis(2-methoxy-4-nitro-S-sulfophenynl)-H-tetrazolium-5-carboxanilide inner salt] assay.
The analysis of 8 melanoma cell lines linked the IFN-γ unresponsiveness of Colo 857 cells determined by lack of inducibility of HLA class I surface expression on IFN-γ treatment to a deletion of JAK2 on chromosome 9, whereas other IFN-γ signaling pathway components were not affected. In addition, the constitutive HLA class I APM component expression levels were significantly reduced in JAK2− cells. Furthermore, JAK2-deficient cells were also resistant to the antiproliferative effect of IFN-γ. Transfection of wild-type JAK2 into JAK2− Colo 857 not only increased the basal APM expression but also restored their IFN-γ sensitivity.
Impaired JAK2 expression in melanoma cells leads to reduced basal expression of MHC class I APM components and impairs their IFN-γ inducibility, suggesting that malfunctional IFN-γ signaling might cause HLA class I abnormalities.
Interferon regulatory factor (IRF)-5 is a transcription factor involved in type I interferon signaling whose germ line variants have been associated with autoimmune pathogenesis. Since relationships have been observed between development of autoimmunity and responsiveness of melanoma to several types of immunotherapy, we tested whether polymorphisms of IRF5 are associated with responsiveness of melanoma to adoptive therapy with tumor infiltrating lymphocytes (TILs).
140 TILs were genotyped for four single nucleotide polymorphisms (rs10954213, rs11770589, rs6953165, rs2004640) and one insertion-deletion in the IRF5 gene by sequencing. Gene-expression profile of the TILs, 112 parental melanoma metastases (MM) and 9 cell lines derived from some metastases were assessed by Affymetrix Human Gene ST 1.0 array.
Lack of A allele in rs10954213 (G > A) was associated with non-response (p < 0.005). Other polymorphisms in strong linkage disequilibrium with rs10954213 demonstrated similar trends. Genes differentially expressed in vitro between cell lines carrying or not the A allele could be applied to the transcriptional profile of 112 melanoma metastases to predict their responsiveness to therapy, suggesting that IRF5 genotype may influence immune responsiveness by affecting the intrinsic biology of melanoma.
This study is the first to analyze associations between melanoma immune responsiveness and IRF5 polymorphism. The results support a common genetic basis which may underline the development of autoimmunity and melanoma immune responsiveness.
IFNa was the first cytokine to demonstrate anti-tumor activity in advanced melanoma. Despite the ability of high-dose IFNa reducing relapse and mortality by up to 33%, large majority of patients experience side effects and toxicity which outweigh the benefits. The current study attempts to identify genetic markers likely to be associated with benefit from IFN-a2b treatment and predictive for survival.
We tested the association of variants in FOXP3 microsatellites, CTLA4 SNPs and HLA genotype in 284 melanoma patients and their association with prognosis and survival of melanoma patients who received IFNa adjuvant therapy.
Univariate survival analysis suggested that patients bearing either the DRB1*15 or HLA-Cw7 allele suffered worse OS while patients bearing either HLA-Cw6 or HLA-B44 enjoyed better OS. DRB1*15 positive patients suffered also worse RFS and conversely HLA-Cw6 positive patients had better RFS. Multivariate analysis revealed that a five-marker genotyping signature was prognostic of OS independent of disease stage. In the multivariate Cox regression model, HLA-B38 (p = 0.021), HLA-C15 (p = 0.025), HLA-C3 (p = 0.014), DRB1*15 (p = 0.005) and CT60*G/G (0.081) were significantly associated with OS with risk ratio of 0.097 (95% CI, 0.013–0.709), 0.387 (95% CI, 0.169–0.889), 0.449 (95% CI, 0.237–0.851), 1.948 (95% CI, 1.221–3.109) and 1.484 (95% IC, 0.953–2.312) respectively.
These results suggest that gene polymorphisms relevant to a biological occurrence are more likely to be informative when studied in concert to address potential redundant or conflicting functions that may limit each gene individual contribution. The five markers identified here exemplify this concept though prospective validation in independent cohorts is needed.
The weight that gene copy number plays in transcription remains controversial; although in specific cases gene expression correlates with copy number, the relationship cannot be inferred at the global level. We hypothesized that genes steadily expressed by 15 melanoma cell lines (CMs) and their parental tissues (TMs) should be critical for oncogenesis and their expression most frequently influenced by their respective copy number.
Functional interpretation of 3,030 transcripts concordantly expressed (Pearson's correlation coefficient p-value < 0.05) by CMs and TMs confirmed an enrichment of functions crucial to oncogenesis. Among them, 968 were expressed according to the transcriptional efficiency predicted by copy number analysis (Pearson's correlation coefficient p-value < 0.05). We named these genes, "genomic delegates" as they represent at the transcriptional level the genetic footprint of individual cancers. We then tested whether the genes could categorize 112 melanoma metastases. Two divergent phenotypes were observed: one with prevalent expression of cancer testis antigens, enhanced cyclin activity, WNT signaling, and a Th17 immune phenotype (Class A). This phenotype expressed, therefore, transcripts previously associated to more aggressive cancer. The second class (B) prevalently expressed genes associated with melanoma signaling including MITF, melanoma differentiation antigens, and displayed a Th1 immune phenotype associated with better prognosis and likelihood to respond to immunotherapy. An intermediate third class (C) was further identified. The three phenotypes were confirmed by unsupervised principal component analysis.
This study suggests that clinically relevant phenotypes of melanoma can be retraced to stable oncogenic properties of cancer cells linked to their genetic back bone, and offers a roadmap for uncovering novel targets for tailored anti-cancer therapy.
Melanoma; Melanoma genetics; Cancer; Tumor microenvironment
Cell type heterogeneity may have a substantial effect on gene expression profiling of human tissue. Several in silico methods for deconvoluting a gene expression profile into cell-type-specific subprofiles have been published but not widely used. Here, we consider recent methods and the experimental validations available for them. Shen-Orr et al. recently developed an approach called cell-type-specific significance analysis of microarray for deconvoluting gene expression. This method requires the measurement of the proportion of each cell type in each sample and the expression profiles of the heterogeneous samples. It determines how gene expression varies among pre-defined phenotypes for each cell type. Gene expression can vary substantially among cell types and sample heterogeneity can mask the identification of biologically important phenotypic correlations. Consequently, the deconvolution approach can be useful in the analysis of mixtures of cell populations in clinical samples.
The molecular drivers that determine histology in lung cancer are largely unknown. We investigated whether microRNA (miR) expression profiles can differentiate histological subtypes and predict survival for non-small cell lung cancer.
We analyzed miR expression in 165 adenocarcinoma (AD) and 125 squamous cell carcinoma (SQ) tissue samples from the Environmental And Genetics in Lung cancer Etiology (EAGLE) study using a custom oligo array with 440 human mature antisense miRs. We compared miR expression profiles using t-tests and F-tests and accounted for multiple testing using global permutation tests. We assessed the association of miR expression with tobacco smoking using Spearman correlation coefficients and linear regression models, and with clinical outcome using log-rank tests, Cox proportional hazards and survival risk prediction models, accounting for demographic and tumor characteristics.
MiR expression profiles strongly differed between AD and SQ (global p<0.0001), particularly in the early stages, and included miRs located on chromosome loci most often altered in lung cancer (e.g., 3p21-22). Most miRs, including all members of the let-7 family, were down-regulated in SQ. Major findings were confirmed by QRT-PCR in EAGLE samples and in an independent set of lung cancer cases. In SQ, low expression of miRs down-regulated in the histology comparison was associated with 1.2 to 3.6-fold increased mortality risk. A 5-miR signature significantly predicted survival for SQ.
We identified a miR expression profile that strongly differentiated AD from SQ and had prognostic implications. These findings may lead to histology-based therapeutic approaches.
Traditional Chinese Medicine (TCM) has been used for thousands of years to treat or prevent diseases, including cancer. Good manufacturing practices (GMP) and sophisticated product analysis (PhytomicsQC) to ensure consistency are now available allowing the assessment of its utility. Polychemical Medicines, like TCM, include chemicals with distinct tissue-dependent pharmacodynamic properties that result in tissue-specific bioactivity. Determining the mode of action of these mixtures was previously unsatisfactory; however, information rich RNA microarray technologies now allow for thorough mechanistic studies of the effects complex mixtures. PHY906 is a long used four herb TCM formula employed as an adjuvant to relieve the side effects associated with chemotherapy. Animal studies documented a decrease in global toxicity and an increase in therapeutic effectiveness of chemotherapy when combined with PHY906.
Using a systems biology approach, we studied tumor tissue to identify reasons for the enhancement of the antitumor effect of CPT-11 (CPT-11) by PHY906 in a well-characterized pre-clinical model; the administration of PHY906 and CPT-11 to female BDF-1 mice bearing subcutaneous Colon 38 tumors.
We observed that 1) individually PHY906 and CPT-11 induce distinct alterations in tumor, liver and spleen; 2) PHY906 alone predominantly induces repression of transcription and immune-suppression in tumors; 3) these effects are reverted in the presence of CPT-11, with prevalent induction of pro-apoptotic and pro-inflammatory pathways that may favor tumor rejection.
PHY906 together with CPT-11 triggers unique changes not activated by each one alone suggesting that the combination creates a unique tissue-specific response.
MicroRNAs (miRs) are endogenous, non-coding RNAs involved in many cellular processes and have been associated with the development and progression of cancer. There are many different ways to evaluate miRs.
We described some of the most commonly used and promising miR detection methods.
Each miR detection method has benefits and limitations. Microarray profiling and quantitative real-time reverse transcription PCR (qRT-PCR) are the two most common methods to evaluate miR expression. However, the results from microarray and qRT-PCR do not always agree. High-throughput, high-resolution next generation sequencing of small RNAs may offer the opportunity to quickly and accurately discover new miRs and confirm the presence of known miRs in the near future.
All of the current and new technologies have benefits and limitations to consider when designing miR studies. Results can vary across platforms, requiring careful and critical evaluation when interpreting findings.
Although miR detection and expression analyses are rapidly improving, there are still many technical challenges to overcome. The old molecular epidemiology tenet of rigorous biomarker validation and confirmation in independent studies remains essential.
To identify a pre-HAART gene expression signature in peripheral blood mononuclear cells (PBMCs) predictive of CD4+ T-cell recovery during HAART in HIV-infected individuals.
This retrospective study evaluated PBMC gene expression in 24 recently HIV-infected individuals before the initiation of HAART to identify genes whose expression is predictive of CD4+ T-cell recovery after 48 weeks of HAART.
The change in CD4+ T-cell count (ΔCD4) over the 48-week study period was calculated for each of the 24 participants. Twelve participants were assigned to the ‘good’ (ΔCD4 ≥ 200 cells/μl) and 12 to the ‘poor’ (ΔCD4 < 200 cells/μl) CD4+ T-cell recovery group. Gene expression profiling of the entire transcriptome using Illumina BeadChips was performed with PBMC samples obtained before HAART. Gene expression classifiers capable of predicting CD4+ T-cell recovery group (good vs. poor), as well as the specific ΔCD4 value, at week 48 were constructed using methods of Class Prediction.
The expression of 40 genes in PBMC samples taken before HAART predicted CD4+ T-cell recovery group (good vs. poor) at week 48 with 100% accuracy. The expression of 22 genes predicted a specific ΔCD4 value for each HIV-infected individual that correlated well with actual values (R = 0.82). Predicted ΔCD4 values were also used to assign individuals to good vs. poor CD4+ T-cell recovery groups with 79% accuracy.
Gene expression in PBMCs can be used as biomarkers to successfully predict disease outcomes among HIV-infected individuals treated with HAART.
CD4; gene expression; HIV; immune reconstitution; pathogenesis; prognosis
The traditional oncology drug development paradigm of single arm phase II studies followed by a randomized phase III study has limitations for modern oncology drug development. Interpretation of single arm phase II study results is difficult when a new drug is used in combination with other agents or when progression free survival is used as the endpoint rather than tumor shrinkage. Randomized phase II studies are more informative for these objectives but increase both the number of patients and time required to determine the value of a new experimental agent. In this paper, we compare different phase II study strategies to determine the most efficient drug development path in terms of number of patients and length of time to conclusion of drug efficacy on overall survival.
MiR arrays distinguish themselves from gene expression arrays by their more limited number of probes, and the shorter and less flexible sequence in probe design. Robust data processing and analysis methods tailored to the unique characteristics of miR arrays are greatly needed. Assumptions underlying commonly used normalization methods for gene expression microarrays containing tens of thousands or more probes may not hold for miR microarrays. Findings from previous studies have sometimes been inconclusive or contradictory. Further studies to determine optimal normalization methods for miR microarrays are needed.
We evaluated many different normalization methods for data generated with a custom-made two channel miR microarray using two data sets that have technical replicates from several different cell lines. The impact of each normalization method was examined on both within miR error variance (between replicate arrays) and between miR variance to determine which normalization methods minimized differences between replicate samples while preserving differences between biologically distinct miRs.
Lowess normalization generally did not perform as well as the other methods, and quantile normalization based on an invariant set showed the best performance in many cases unless restricted to a very small invariant set. Global median and global mean methods performed reasonably well in both data sets and have the advantage of computational simplicity.
Researchers need to consider carefully which assumptions underlying the different normalization methods appear most reasonable for their experimental setting and possibly consider more than one normalization approach to determine the sensitivity of their results to normalization method used.
There have been relatively few publications using linear regression models to predict a continuous response based on microarray expression profiles. Standard linear regression methods are problematic when the number of predictor variables exceeds the number of cases. We have evaluated three linear regression algorithms that can be used for the prediction of a continuous response based on high dimensional gene expression data. The three algorithms are the least angle regression (LAR), the least absolute shrinkage and selection operator (LASSO), and the averaged linear regression method (ALM). All methods are tested using simulations based on a real gene expression dataset and analyses of two sets of real gene expression data and using an unbiased complete cross validation approach. Our results show that the LASSO algorithm often provides a model with somewhat lower prediction error than the LAR method, but both of them perform more efficiently than the ALM predictor. We have developed a plug-in for BRB-ArrayTools that implements the LAR and the LASSO algorithms with complete cross-validation.
regression model; gene expression; continuous outcome
The three HLA class II alleles of the DR2 haplotype, DRB1*1501, DRB5*0101, and DQB1*0602, are in strong linkage disequilibrium and confer most of the genetic risk to multiple sclerosis. Functional redundancy in Ag presentation by these class II molecules would allow recognition by a single TCR of identical peptides with the different restriction elements, facilitating T cell activation and providing one explanation how a disease-associated HLA haplotype could be linked to a CD4+ T cell-mediated autoimmune disease. Using combinatorial peptide libraries and B cell lines expressing single HLA-DR/DQ molecules, we show that two of five in vivo-expanded and likely disease-relevant, cross-reactive cerebrospinal fluid-infiltrating T cell clones use multiple disease-associated HLA class II molecules as restriction elements. One of these T cell clones recognizes >30 identical foreign and human peptides using all DR and DQ molecules of the multiple sclerosis-associated DR2 haplotype. A T cell signaling machinery tuned for efficient responses to weak ligands together with structural features of the TCR-HLA/peptide complex result in this promiscuous HLA class II restriction.
The International Society for the Biological Therapy of Cancer (iSBTc) has initiated in collaboration with the United States Food and Drug Administration (FDA) a programmatic look at innovative avenues for the identification of relevant parameters to assist clinical and basic scientists who study the natural course of host/tumor interactions or their response to immune manipulation. The task force has two primary goals: 1) identify best practices of standardized and validated immune monitoring procedures and assays to promote inter-trial comparisons and 2) develop strategies for the identification of novel biomarkers that may enhance our understating of principles governing human cancer immune biology and, consequently, implement their clinical application. Two working groups were created that will report the developed best practices at an NCI/FDA/iSBTc sponsored workshop tied to the annual meeting of the iSBTc to be held in Washington DC in the Fall of 2009. This foreword provides an overview of the task force and invites feedback from readers that might be incorporated in the discussions and in the final document.
The need for fast, efficient, and less costly means to screen genetic variants associated with disease predisposition led us to develop an oligo-nucleotide array-based process for gene-specific single nucleotide polymorphism (SNP) genotyping. This cost-effective, high-throughput strategy has high sensitivity and the same degree of accuracy as direct sequencing, the current gold standard for genetic screening. We used the BRCA1 breast and ovarian cancer predisposing gene model for the validation of the accuracy and efficiency of our strategy. This process could detect point mutations, insertions or deletions of any length, of known and unknown variants even in heterozygous conditions without affecting sensitivity and specificity. The system could be applied to other disorders and can also be custom-designed to include a number of genes related to specific clinical conditions. This system is particularly useful for the screening of long genomic regions with relatively infrequent but clinically relevant variants, while drastically cutting time and costs in comparison to high-throughput sequencing.
Bovine tuberculosis (BTB) caused by Mycobacterium bovis continues to cause substantial losses to global agriculture and has significant repercussions for human health. The advent of high throughput genomics has facilitated large scale gene expression analyses that present a novel opportunity for revealing the molecular mechanisms underlying mycobacterial infection. Using this approach, we have previously shown that innate immune genes in peripheral blood mononuclear cells (PBMC) from BTB-infected animals are repressed in vivo in the absence of exogenous antigen stimulation. In the present study, we hypothesized that the PBMC from BTB-infected cattle would display a distinct gene expression program resulting from exposure to M. bovis. A functional genomics approach was used to examine the immune response of BTB-infected (n = 6) and healthy control (n = 6) cattle to stimulation with bovine tuberculin (purified protein derivative – PPD-b) in vitro. PBMC were harvested before, and at 3 h and 12 h post in vitro stimulation with bovine tuberculin. Gene expression changes were catalogued within each group using a reference hybridization design and a targeted immunospecific cDNA microarray platform (BOTL-5) with 4,800 spot features representing 1,391 genes.
250 gene spot features were significantly differentially expressed in BTB-infected animals at 3 h post-stimulation contrasting with only 88 gene spot features in the non-infected control animals (P ≤ 0.05). At 12 h post-stimulation, 56 and 80 gene spot features were differentially expressed in both groups respectively. The results provided evidence of a proinflammatory gene expression profile in PBMC from BTB-infected animals in response to antigen stimulation. Furthermore, a common panel of eighteen genes, including transcription factors were significantly expressed in opposite directions in both groups. Real-time quantitative reverse transcription PCR (qRT-PCR) demonstrated that many innate immune genes, including components of the TLR pathway and cytokines were differentially expressed in BTB-infected (n = 8) versus control animals (n = 8) after stimulation with bovine tuberculin.
The PBMC from BTB-infected animals exhibit different transcriptional profiles compared with PBMC from healthy control animals in response to M. bovis antigen stimulation, providing evidence of a novel gene expression program due to M. bovis exposure.
The pathogenesis of nasopharyngeal carcinoma (NPC) is a complicated process involving genetic predisposition, Epstein-Bar Virus infection, and genetic alterations. Although some oncogenes and tumor suppressor genes have been previously reported in NPC, a complete understanding of the pathogenesis of NPC in the context of global gene expression, transcriptional pathways and biomarker assessment remains to be elucidated.
Total RNA from 32 pathologically-confirmed cases of poorly-differentiated NPC was divided into pools inclusive of four consecutive specimens and each pool (T1 to T8) was co-hybridized with pooled RNA from 24 normal non-cancerous nasopharyngeal tissues (NP) to a human 8K cDNA array platform. The reliability of microarray data was validated for selected genes by semi-quantitative RT-PCR and immunohistochemistry.
Stringent statistical filtering parameters identified 435 genes to be up-regulated and 257 genes to be down-regulated in NPC compared to NP. Seven up-regulated genes including CYC1, MIF, LAMB3, TUBB2, UBE2C and TRAP1 had been previously proposed as candidate common cancer biomarkers based on a previous extensive comparison among various cancers and normal tissues which did not, however, include NPC or NP. In addition, nine known oncogenes and tumor suppressor genes, MIF, BIRC5, PTTG1, ATM, FOXO1A, TGFBR2, PRKAR1A, KLF5 and PDCD4 were identified through the microarray literature-based annotation search engine MILANO, suggesting these genes may be specifically involved in the promotion of the malignant conversion of nasopharyngeal epithelium. Finally, we found that these differentially expressed genes were involved in apoptosis, MAPK, VEGF and B cell receptor signaling pathways and other functions associated with cell growth, signal transduction and immune system activation.
This study identified potential candidate biomarkers, oncogenes/tumor suppressor genes involved in several pathways relevant to the oncogenesis of NPC. This information may facilitate the determination of diagnostic and therapeutic targets for NPC as well as provide insights about the molecular pathogenesis of NPC.
The explosion of available microarray data on human cancer increases the urgency for developing methods for effectively sharing this data among clinical cancer investigators. Lack of a smooth interface between the databases and statistical analysis tools limits the potential benefits of sharing the publicly available microarray data. To facilitate the efficient sharing and use of publicly available microarray data among cancer investigators, we have built a BRB-ArrayTools Data Archive including over one hundred human cancer microarray projects for 28 cancer types. Expression array data and clinical descriptors have been imported into BRB-ArrayTools and are stored as BRB-ArrayTools project folders on the archive. The data archive can be accessed from: http://linus.nci.nih.gov/~brb/DataArchive.html Our BRB-ArrayTools data archive and GEO importer represent ongoing efforts to provide effective tools for efficiently sharing and utilizing human cancer microarray data.
We amplified RNAs from 63 fine needle aspiration (FNA) samples from 37 s.c. melanoma metastases from 25 patients undergoing immunotherapy for hybridization to a 6108-gene human cDNA chip. By prospectively following the history of the lesions, we could correlate transcript patterns with clinical outcome. Cluster analysis revealed a tight relationship among autologous synchronously sampled tumors compared with unrelated lesions (average Pearson's r = 0.83 and 0.7, respectively, P < 0.0003). As reported previously, two subgroups of metastatic melanoma lesions were identified that, however, had no predictive correlation with clinical outcome. Ranking of gene expression data from pretreatment samples identified ∼30 genes predictive of clinical response (P < 0.001). Analysis of their annotations denoted that approximately half of them were related to T-cell regulation, suggesting that immune responsiveness might be predetermined by a tumor microenvironment conducive to immune recognition.
Bovine tuberculosis is an enduring disease of cattle that has significant repercussions for human health. The advent of high-throughput functional genomics technologies has facilitated large-scale analyses of the immune response to this disease that may ultimately lead to novel diagnostics and therapeutic targets. Analysis of mRNA abundance in peripheral blood mononuclear cells (PBMC) from six Mycobacterium bovis infected cattle and six non-infected controls was performed. A targeted immunospecific bovine cDNA microarray with duplicated spot features representing 1,391 genes was used to test the hypothesis that a distinct gene expression profile may exist in M. bovis infected animals in vivo.
In total, 378 gene features were differentially expressed at the P ≤ 0.05 level in bovine tuberculosis (BTB)-infected and control animals, of which 244 were expressed at lower levels (65%) in the infected group. Lower relative expression of key innate immune genes, including the Toll-like receptor 2 (TLR2) and TLR4 genes, lack of differential expression of indicator adaptive immune gene transcripts (IFNG, IL2, IL4), and lower BOLA major histocompatibility complex – class I (BOLA) and class II (BOLA-DRA) gene expression was consistent with innate immune gene repression in the BTB-infected animals. Supervised hierarchical cluster analysis and class prediction validation identified a panel of 15 genes predictive of disease status and selected gene transcripts were validated (n = 8 per group) by real time quantitative reverse transcription PCR.
These results suggest that large-scale expression profiling can identify gene signatures of disease in peripheral blood that can be used to classify animals on the basis of in vivo infection, in the absence of exogenous antigenic stimulation.