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Integrating phenotypic and expression profiles to map arsenic-response networks.

BACKGROUND: Arsenic is a nonmutagenic carcinogen affecting millions of people. The cellular impact of this metalloid in Saccharomyces cerevisiae was determined by profiling global gene expression and sensitivity phenotypes. These data were then mapped to a metabolic network composed of all known biochemical reactions in yeast, as well as the yeast network of 20,985 protein-protein/protein-DNA interactions. RESULTS: While the expression data unveiled no significant nodes in the metabolic network, the regulatory network revealed several important nodes as centers of arsenic-induced activity. The highest-scoring proteins included Fhl1, Msn2, Msn4, Yap1, Cad1 (Yap2), Pre1, Hsf1 and Met31. Contrary to the gene-expression analyses, the phenotypic-profiling data mapped to the metabolic network. The two significant metabolic networks unveiled were shikimate, and serine, threonine and glutamate biosynthesis. We also carried out transcriptional profiling of specific deletion strains, confirming that the transcription factors Yap1, Arr1 (Yap8), and Rpn4 strongly mediate the cell's adaptation to arsenic-induced stress but that Cad1 has negligible impact. CONCLUSIONS: By integrating phenotypic and transcriptional profiling and mapping the data onto the metabolic and regulatory networks, we have shown that arsenic is likely to channel sulfur into glutathione for detoxification, leads to indirect oxidative stress by depleting glutathione pools, and alters protein turnover via arsenation of sulfhydryl groups on proteins. Furthermore, we show that phenotypically sensitive pathways are upstream of differentially expressed ones, indicating that transcriptional and phenotypic profiling implicate distinct, but related, pathways.

Arsenic↗

Genomic profiling and expanded use of targeted anticancer drugs in solid cancers with exhausted evidence-based treatment options (PRECODE): study protocol of a prospective, non-randomized, cohort study.

BACKGROUND: Genomic profiling of advanced solid cancer in patients with no further evidence based standard treatment options is a novel approach to identify potential experimental treatment options based on specific genomic alterations. Due to the expected short survival of these patients timely assessment of potential druggable targets is critical to minimize the risk of deterioration during the analysis. The primary objective of this prospective study is to evaluate the turnaround time for genomic profiling and the clinical investigational procedures. The secondary objectives are to investigate how often genomic alterations in tumor tissue gives rise to a matched treatment offer and evaluate the clinical outcome. METHODS: The PRECODE study is a prospective, non-randomized, single-center cohort study conducted at Departments of Oncology and Pathology, Odense University Hospital, Denmark. Enrollment between March 1, 2019 and December 31, 2024. Eligibility criteria are age ≥ 18 years, written informed consent, advanced solid tumors, exhausted treatment options, ECOG performance status 0-2, adequate organ function and life expectancy ≥ 3 months. A core needle biopsy is analyzed by next generation sequencing using a pan-cancer comprehensive panel. Results are discussed weekly at institutional/local and national multidisciplinary tumor boards. DISCUSSION: Strategies and methods for genomic profiling of advanced solid cancers differ. Rapid analysis and interpretation of sequencing data are key to avoiding delays in initiation potential experimental treatments, as these late-stage patients may quickly deteriorate. Although a highly optimized setup with fast-track clinical evaluation and genomic profiling has been established a subset will not be offered a targeted treatment due to deterioration. Local and national multidisciplinary teams have been established to optimize individualized treatment decisions. After genomic profiling a subset of patients will take part in clinical trials, which will constrain the reporting of overall survival or progression free survival. TRIAL REGISTRATION: Danish Ethics Committee, Projekt-ID: S-2018014, date of approval: 27- FEB- 2019) Danish Data Protection Agency (Journal no: 18/58329, date of approval: 23-NOV-2018). CLINICALTRIALS: gov Identifier: NCT05385081 (retrospectively registered).

Humans↗

Spinal low-grade ependymal tumors harboring telomerase reverse transcriptase promoter mutation and chromosome 7 gain with methylation profile of spinal subependymoma.

Spinal intramedullary tumors comprise a heterogeneous group of entities with diverse histopathological features, making their diagnosis particularly challenging. With the introduction of DNA methylation profiling, the underlying biological diversity of these tumors has been increasingly clarified and systematized; however, owing to the rarity of these tumors, case accumulation remains limited, and significant challenges persist. In this study, we identified two cases of spinal ependymal tumors exhibiting a methylation profile of spinal (SP-) subependymoma (SEPN). Both cases occurred in elderly patients and demonstrated circumscribed growth consistent with low-grade ependymal tumors; however, these tumors did not exhibit the typical histopathological features required for a diagnosis of SEPN in the 2021 WHO classification of central nervous system (CNS) tumors, showing indistinct cluster formation, an astrocytic immunohistochemical profile suggested by Olig2 expression, and relatively elevated Ki-67 labeling indices of 4.5% and 3.1%. At the molecular level, both cases harbored telomerase reverse transcriptase promoter mutations and whole chromosome 7 gain. On two-dimensional t-distributed stochastic neighbor embedding analysis, both clustered within the SP-SEPN methylation class at its periphery, with low classifier calibration scores (0.70 and 0.69). According to the current WHO classification, these cases are designated as low-grade ependymal tumors (CNS WHO grade 2) with methylation profile of SP-SEPN because they do not meet the essential WHO histopathological criteria. Ependymal tumors exhibiting a methylation profile consistent with SEPN, but discordant histopathological features have been increasingly recognized, and the appropriate classification of such tumors remains a subject of ongoing debate. These cases provide important insights into the histopathological diversity of ependymal tumors and contribute to establishing a more comprehensive and systematic classification of ependymal tumors.

Aged↗

Breast cancer prognosis determined by gene expression profiling: a quantitative reverse transcriptase polymerase chain reaction study.

PURPOSE: We sought to reproduce with quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) the results obtained with a 70-gene expression profile that has been described previously in breast cancer. PATIENTS AND METHODS: Frozen breast cancer samples from patients who were operated on were used to isolate tumor RNA. Ninety-six patients with stage I to II disease were included. Median age was 57 years (range, 27 to 80 years). Forty-eight patients had lymph node-negative and 48 lymph node-positive disease. qRT-PCR amplifications were performed and the results were correlated with clinical data. RESULTS: After a minimum follow-up of 5 years, 25 patients had a relapse. The gene profile divided patients into two groups with poor and good prognosis. Significant differences with regard to grade of differentiation, size and hormone receptors were seen between the two groups. The gene profile was significantly associated with relapse-free survival and overall survival in the whole group of 96 patients. Multivariate analysis showed that only lymph node status and gene profile were significantly correlated to overall survival. CONCLUSION: qRT-PCR reproduced the results obtained with microarrays for a prognostic gene profile in women with early-stage breast cancer.

Adult↗

Defining molecular profiles of poor outcome in patients with invasive bladder cancer using oligonucleotide microarrays.

PURPOSE: Bladder cancer is a common malignancy characterized by a poor clinical outcome when tumors progress into invasive disease. We sought to define genetic signatures characteristic of aggressive clinical behavior in advanced bladder tumors. METHODS: Oligonucleotide arrays were utilized to analyze the transcript profiles of 105 bladder tumors: 33 superficial, 72 invasive lesions, and 52 normal urothelium. Hierarchical clustering and supervised algorithms were used to classify and stratify bladder tumors on the basis of stage, node metastases, and overall survival. Immunohistochemical analyses on bladder cancer tissue arrays (n = 294 cases) served to validate associations between marker expression, staging and outcome. RESULTS: Hierarchical clustering classified normal urothelium, superficial, and invasive tumors with 82.2% accuracy, and stratified bladder tumors on the basis of clinical outcome. Predictive algorithms rendered an 89%-correct rate for tumor staging using genes differentially expressed between superficial and invasive tumors. Accuracies of 82% and 90% were obtained for predicting overall survival when considering all patients with bladder cancer or only patients with invasive disease, respectively. A genetic profile consisting of 174 probes was identified in those patients with positive lymph nodes and poor survival. Two independent Global Test runs confirmed the robust association of this profile with lymph node metastases (P = 7.3(-13)) and overall survival (P = 1.9(-14)) simultaneously. Immunohistochemical analyses on tissue arrays sustained the significant association of synuclein with tumor staging and clinical outcome (P = .002). CONCLUSION: Gene profiling provides a genomic-based classification scheme of diagnostic and prognostic utility for stratifying advanced bladder cancer. Identification of this poor outcome profile could assist in selecting patients who may benefit from more aggressive therapeutic intervention.

Gene Expression Profiling↗

Discriminating different classes of toxicants by transcript profiling.

Male rats were treated with various model compounds or the appropriate vehicle controls. Most substances were either well-known hepatotoxicants or showed hepatotoxicity during preclinical testing. The aim of the present study was to determine if biological samples from rats treated with various compounds can be classified based on gene expression profiles. In addition to gene expression analysis using microarrays, a complete serum chemistry profile and liver and kidney histopathology were performed. We analyzed hepatic gene expression profiles using a supervised learning method (support vector machines; SVMs) to generate classification rules and combined this with recursive feature elimination to improve classification performance and to identify a compact subset of probe sets with potential use as biomarkers. Two different SVM algorithms were tested, and the models obtained were validated with a compound-based external cross-validation approach. Our predictive models were able to discriminate between hepatotoxic and nonhepatotoxic compounds. Furthermore, they predicted the correct class of hepatotoxicant in most cases. We provide an example showing that a predictive model built on transcript profiles from one rat strain can successfully classify profiles from another rat strain. In addition, we demonstrate that the predictive models identify nonresponders and are able to discriminate between gene changes related to pharmacology and toxicity. This work confirms the hypothesis that compound classification based on gene expression data is feasible.

Algorithms↗

Combining congenic coverage with gene profiling in search of candidates for blood pressure quantitative trait loci in Dahl rats.

Chromosomes (Chr) 10 and 16 of the Dahl salt-sensitive (S) rat harbor quantitative trait loci (QTLs) for blood pressure (BP). To facilitate gene discovery of these QTLs, gene profiling based on microarrays was combined with fine QTL mapping to identify potential candidate genes that are differentially expressed. First, the region harboring the BP QTL on Chr 16 was narrowed by comparative congenic mapping. In this endeavor, a number of new chromosome markers were generated and used to physically define the chromosome interval in question. Second, in an effort to minimize the costs of gene profiling without sacrificing the chance of gene discovery, a combination congenic strain was produced by replacing one segment of Chr 10 along with one segment of Chr 16 of the hypertensive S rat by those of the normotensive Lewis (LEW) rat. Both of these regions are known to contain BP QTLs. Third, kidneys of this combination congenic strain and the S strain were employed for expression profiling studies. Finally, a comparison between the two strains yielded a number of potentially differentially expressed candidates. Six Established Sequence Tags (ESTs)/genes among them were located in Chr 10 regions and 1 was found in a Chr 16 region, and the genetic make-ups of all these regions were shown to be different between S and LEW. However, none of these ESTs/genes identified by gene profiling were located in an interval containing a QTL. Thus, the present study highlights the importance of correlating the results of gene expression profiling with fine congenic mapping.

Animals↗

Transcriptional profiling of aging in human muscle reveals a common aging signature.

We analyzed expression of 81 normal muscle samples from humans of varying ages, and have identified a molecular profile for aging consisting of 250 age-regulated genes. This molecular profile correlates not only with chronological age but also with a measure of physiological age. We compared the transcriptional profile of muscle aging to previous transcriptional profiles of aging in the kidney and the brain, and found a common signature for aging in these diverse human tissues. The common aging signature consists of six genetic pathways; four pathways increase expression with age (genes in the extracellular matrix, genes involved in cell growth, genes encoding factors involved in complement activation, and genes encoding components of the cytosolic ribosome), while two pathways decrease expression with age (genes involved in chloride transport and genes encoding subunits of the mitochondrial electron transport chain). We also compared transcriptional profiles of aging in humans to those of the mouse and fly, and found that the electron transport chain pathway decreases expression with age in all three organisms, suggesting that this may be a public marker for aging across species.

Adolescent↗

Development of cDNA microarray for expression profiling of estrogen-responsive genes.

Estrogen plays an important role in many physiological events including carcinogenesis and the development of human breast cancer. However, the molecular mechanisms of estrogen signaling in cancers have not been clarified hitherto and accurate therapeutic prediction of breast cancer is earnestly desired. We first carried out estrogen-responsive expression profiling of approximately 9000 genes in estrogen receptor-positive human MCF-7 breast cancer cells. Based on the results, estrogen-responsive genes were selected for production of a custom-made cDNA microarray. Using a microarray consisting of the narrowed-down gene subset, we first analyzed the time course of the estrogen-responsive gene expression profiles in MCF-7 cells, resulting in subdivision of the genes up-regulated by estrogen into early-responsive and late-responsive genes. The expression patterns of several genes were confirmed by Northern blot analysis. We also analyzed the effects of the estrogen antagonists ICI 182780 and 4-hydroxytamoxifen (OHT) on the estrogen-responsive gene expression profiles in MCF-7 cells. While the regulation of most of the genes by estrogen was completely abolished by ICI 182780, some genes were partially regulated by estrogen even in the presence of OHT. Furthermore, the estrogen-responsive gene expression profiles of twelve cancer cell lines derived from the breast, ovary, stomach and other tissues were obtained and analyzed by hierarchical clustering including the profiles in MCF-7 cells. Several genes also showed up-regulation or down-regulation by estrogen in cell lines other than MCF-7 cells. The significance of the estrogen-responsive genes identified in these analyses concerning the nature of cancer is discussed.

Blotting, Northern↗

Effects of globin mRNA reduction methods on gene expression profiles from whole blood.

Excessive globin mRNA in whole blood RNA decreases transcript detection sensitivity and increases signal variation on microarrays. Hence, methods based on peptide nucleic acid inhibitory oligos and biotinylated DNA capture oligos have been developed to reduce globin mRNA. However, there is limited information about the effects of these two methods on gene expression profiles. Thus, we systematically compared the facility and effects of the two globin reduction methods on profile measurements from Jurkat cell line RNA with or without spiked globin mRNA and human blood RNA isolated using PAXgene collection tubes. We showed that the methods were efficient at increasing the sensitivity of transcript detection without loss of specificity, but neither method could recover a profile equivalent to that of an identical RNA sample without globin mRNA excesses. The capture oligo method had slightly better transcript detection sensitivity for cell line RNA, lowered signal variation for PAXgene RNA, and more similar profiles to controls than the inhibitory method. However, the capture method required larger amounts of initial high-quality RNA to yield sufficient cRNA amounts, and its procedures were more complex and time consuming than the inhibitory method. These results inform the selection of methods suitable for multicenter surveillance of gene expression profiles.

Blood Specimen Collection↗

Meningioma methylation profiling as a complement to WHO grading: a single-center experience.

OBJECTIVE: The methylation profile of meningiomas is a promising predictive tool that may improve risk stratification beyond WHO grading. This study aimed to evaluate the clinical relevance and real-world applicability of routine epigenetic testing in meningioma management. METHODS: The authors retrospectively analyzed patients who underwent meningioma resection between January 2021 and December 2023. Histopathological grading (WHO 2021) and methylation profiling (methylation class [MC]) with the MethylationEPIC v1.0 (850k) chip were performed by an independent neuropathologist. RESULTS: A total of 106 patients were included; 81 tumors (76%) were classified as WHO grade 1, 20 (19%) as grade 2, and 5 (5%) as grade 3. Epigenetically, 55 tumors (52%) were classified as benign, 18 (17%) as intermediate, and 2 (2%) as malignant; 31 (29%) could not be classified. Discordances between WHO grading and methylation profiling were observed in 18 of 74 cases. Tumor board decisions were made after a median of 8 days postoperatively, guided by WHO grading; however, the epigenetic report was only available after a median of 23 days. During follow-up, 20 patients experienced tumor progression. Progression was significantly associated with the MC (r = -0.4, p < 0.001) and tumor volume (r = 0.4, p = 0.0005), but not with WHO grading (r = 0.17, p = 0.084). However, the relatively high rate of unclassified tumors and delayed result availability limited the direct impact of MC profiling on immediate clinical decision-making. Interestingly, progression-free survival in MC-unclassified tumors mirrored that of the intermediate group. CONCLUSIONS: Methylation profiling demonstrates superior predictive accuracy for meningioma progression and complements WHO grading, especially in identifying malignant meningiomas. However, its current clinical utility is constrained by technical and logistical limitations. In real-world practice, epigenetic classification should therefore be considered a complementary tool rather than a replacement for established histopathological assessment.

Humans↗

Gene expression profiling in DQA1*0501+ children with untreated dermatomyositis: a novel model of pathogenesis.

Juvenile dermatomyositis (JDM), the most common pediatric inflammatory myopathy, is a systemic vasculopathy affecting young children. Epidemiology studies documenting an antecedent illness in the 3 mo before the first definite symptom (rash and/or weakness) of JDM are supported by immunologic data that suggest that the disease pathophysiology is Ag driven. The purpose of this study was to compare the gene expression profiles in muscle biopsies of four untreated DQA1*0501(+) JDM children with profiles from children with a known necrotizing myopathy (Duchenne muscular dystrophy), as well as an in vitro antiviral model (NF90), and healthy pediatric controls. Nearly half (47%) of the dysregulated genes in JDM were associated with the immune response. In particular, increased expression of IFN-alphabeta-inducible genes 6-16, myxovirus resistance protein p78, latent cytosolic transcription factor, LMP2, and TAP1 was observed. This profile is consistent with an IFN-alphabeta transcription cascade seen in the in vitro viral resistance model. The IFN-alphabeta-inducible profile was superimposed on transcription profiles reflective of myofiber necrosis and regeneration shared with Duchenne muscular dystrophy. Expressed genes were confirmed by quantitative real-time PCR (6-16), immunofluorescence (thrombospondin 4), and immunolocalization (IFN-gamma, p21). We hypothesize that these data support a model of Ag (?viral) induction of an apparent autoimmune disease based on dynamic interaction between the muscle, vascular, and immune systems in the genetically susceptible (DQA1*0501(+)) child.

Adolescent↗

Global profiling of gene expression in cancer using genomics and proteomics.

Global profiling of gene expression at the genomic level using DNA microarrays and at the protein level using a variety of technologies have followed separate paths. Studies of gene expression for several types of tumors, using DNA microarrays, have been published recently that are informative with respect to delineating distinct patterns of gene expression among subsets of related tumors. Proteomics-based profiling uniquely allows delineation of global changes in protein expression patterns resulting from transcriptional and post-transcriptional control, post-translational modifications and shifts in proteins between different cellular compartments. Some of the current technologies for proteome profiling and the application of proteomics to the analysis of tumor tissues are reviewed. Given that comprehensive expression profiles obtained using genomics and proteomics are highly complementary, a combined approach to profiling may well uncover expression patterns that could not be predicted using a single approach.

Gene Expression Profiling↗

Multiplexed, targeted gene expression profiling and genetic analysis on electronic microarrays.

BACKGROUND: Electronic microarrays comprise independent microelectrode test sites that can be electronically biased positive or negative, or left neutral, to move and concentrate charged molecules such as DNA and RNA to one or more test sites. We developed a protocol for multiplexed gene expression profiling of mRNA targets that uses electronic field-facilitated hybridization on electronic microarrays. METHODS: A multiplexed, T7 RNA polymerase-mediated amplification method was used for expression profiling of target mRNAs from total cellular RNA; targets were detected by hybridization to sequence-specific capture oligonucleotides on electronic microarrays. Activation of individual test sites on the electronic microarray was used to target hybridization to designated subsets of sites and allow comparisons of target concentrations in different samples. We used multiplexed amplification and electronic field-facilitated hybridization to analyze expression of a model set of 10 target genes in the U937 cell line during lipopolysaccharide-mediated differentiation. Performance of multiple genetic analyses (single-nucleotide polymorphism detection, gene expression profiling, and splicing isoform detection) on a single electronic microarray was demonstrated using the ApoE and ApoER2 genes as a model system. RESULTS: Targets were detected after a 2-min hybridization reaction. With noncomplementary capture probes, no signal was detectable. Twofold changes in target concentration were detectable throughout the ( approximately 64-fold) range of concentrations tested. Levels of 10 targets were analyzed side by side across seven time points. By confining electronic activation to subsets of test sites, polymorphism detection, expression profiling, and splicing isoform analysis were performed on a single electronic microarray. CONCLUSIONS: Microelectronic array technology provides specific target detection and quantification with advantages over currently available methodologies for targeted gene expression profiling and combinatorial genomics testing.

Alternative Splicing↗

High-resolution profiling of an 11 Mb segment of human chromosome 22 in sporadic schwannoma using array-CGH.

Previous low-resolution schwannoma studies have reported diverse frequencies (30-80%) of 22q deletions, involving the neurofibromatosis-2 tumor suppressor (NF2) gene. We constructed an array spanning 11 million base pairs of 22q encompassing the NF2 gene, with 100% coverage and an average resolution of 58 kb. Moreover, the 220 kb genomic sequence encompassing the NF2 gene was covered by 13 cosmids to further enhance the resolution of analysis. The rationale of this array-CGH study was to map and size 22q deletions around the NF2 gene in sporadic schwannoma using a reliable method with maximal resolution. We studied tumor and constitutional DNA from 47 patients and detected heterozygous deletions in 21 (45%) tumors, which could be classified into three profiles. The predominant profile (12/21) was a continuous deletion of the 11 Mb segment, consistent with monosomy 22. The second profile, comprising five schwannomas, was also in agreement with a continuous 11 Mb heterozygous deletion. However, these displayed a distinctly different level of deletion when compared to the first profile, suggesting a considerable amount of normal tissue in the tumor samples. This is the first report demonstrating the sensitivity of array-CGH to discriminate such samples. The third profile was composed of four cases displaying interstitial deletions of various sizes. Two of these did not encompass the NF2 locus, which further emphasize the importance of other loci in schwannoma development. This is the first high-resolution study performed on a large series of tumors, using an array continuously covering 1/3 of a human chromosome. Our findings warrant further studies of an extended tumor series on a full 22q genomic array, to better define additional, putative 22q-located loci important for schwannoma development. Our array also provides a new diagnostic tool for analysis of NF2 gene deletions in patients affected with neurofibromatosis-2.

Adult↗

Profiling of genes differentially expressed between fetal liver and postnatal liver using high-density oligonucleotide DNA array.

The liver is an essential organ in humans not only for the production and storage of energy but also for detoxification of chemical compounds, but knowledge about changes in the gene expression profile in the human liver during the prenatal and postnatal periods is limited. Profiling of genes differentially expressed between the fetal liver (FL) and the postnatal liver (PNL) is one of the methods to investigate candidates affecting the difference in biological characteristics between FL and PNL. To identify genes differentially expressed between FL and PNL (childhood and adult liver), we analyzed the gene expression profiles across 9 FL and 14 PNL samples using a high-density oligonucleotide DNA array. Using Mann-Whitney U test followed by k-nearest-neighbors (supervised learning method) and hierarchical clustering (unsupervised learning method) algorithms, we found 33 genes clearly discriminating between the FL group and PNL group. The functional classification of the 33 genes identified was related to several kinds of biological pathways, regulating the cell cycle (PCNA, CDC7L1, CCND3, YWHA1, PKMYT1), DNA replication and repair (RFC4, RECQ2, PCNA, NAP1L1), cell growth (IGF2, IGFBP2, PRSS11), hormonal signals (AR, SRD5A1, NR1I3), and cellular metabolism (E2-EPF, WWP1, CYP2C9, CYP2E1, CYP2A6, CYP2A7, CYP2A13, CYP4F2, CYP3A4, DDT). The results presented herein provide evidence of a differential expression profile of genes regulating the cell cycle, DNA replication and repair, cell growth, regulation of hormonal signals, and cellular metabolism, between FL and PNL in humans. The 33 genes identified in this study are suggested to be useful markers clearly discriminating between FL and PNL using the gene expression profile.

Adult↗

[The expression profiles of human chromosome 21 orthologues in mouse M II oocyte].

OBJECTIVE: To analyse the expression profile of orthologues of human chromosome 21 (HC21) in mouse M II oocytes, and to discuss the relationship between this expression profile and early embryonic development and further to find the possible reasons of DS phenotypes genesis. METHODS: cDNA array and Global RT-PCR methods were used to analyse and identify the expression profile of 93 HC21 orthologues in mouse M II oocytes. RESULTS: 26 of 93 orthologues were proved to be expressed in mouse M II oocytes and these genes were involved in many biological procedure including transcriptional, metabolism, ionic channel, and ubiquitin pathway etc. CONCLUSION: To our knowledge, this is first report about the HC21 orthologues expression profile in M II oocytes and this expression profile indicates that 26 of 93 HC21 orthologues may directly play important role in early development, and the biological information obtained from this experiment would be beneficial to understand imbalance of HC21 genes expression and the molecular mechanism of DS phenotypes genesis.

Animals↗

Transcriptional profiles in peripheral blood mononuclear cells prognostic of clinical outcomes in patients with advanced renal cell carcinoma.

PURPOSE: Given their accessibility, surrogate tissues, such as peripheral blood mononuclear cells (PBMC), may provide potential predictive biomarkers in clinical pharmacogenomic studies. In leukemias and lymphomas, the prognostic value of peripheral blast expression profiles is clear; however, it is unclear whether circulating mononuclear cells of patients with solid tumors might yield profiles with similar prognostic associations. EXPERIMENTAL DESIGN: In this study, we evaluated the association of expression profiles in PBMCs with clinical outcomes in patients with advanced renal cell cancer. Transcriptional patterns in PBMCs of 45 renal cell cancer patients were compared with clinical outcome data at the conclusion of a phase II study of the mTOR kinase inhibitor CCI-779 to determine whether pretreatment transcriptional patterns in PBMCs were correlated with eventual patient outcomes. RESULTS: Unsupervised hierarchical clustering of the PBMC profiles using all expressed genes identified clusters of patients with significant differences in survival. Cox proportional hazards modeling showed that the expression levels of many PBMC transcripts were predictors for the patient outcomes of time to progression and overall survival (time to death). Supervised class prediction approaches identified multivariate expression patterns in PBMCs capable of assigning favorable outcomes of time to death and time to progression in a test set of renal cancer patients, with overall performance accuracies of 72% and 85%, respectively. CONCLUSIONS: The present study provides the first example of gene expression profiling in peripheral blood, a clinically accessible surrogate tissue, for identifying patterns of gene expression associated with higher likelihoods of positive outcome in patients with a solid tumor.

Adolescent↗