Factors associated with urinary tract infection in the early phase after performing intermittent catheterization in individuals with spinal cord injury: a retrospective study.

Objectives: To investigate the occurrence rate of urinary tract infections (UTIs) in the early phase after performing intermittent catheterization (IC) and to explore the possible factors associated with UTIs after performing IC among people with spinal cord injury (SCI). Setting: An inpatient rehabilitation department of a teaching hospital in China. Design: Retrospective chart review. Methods: A retrospective chart review was carried out for traumatic and non-traumatic SCI patients after performing IC during their inpatient stay. Demographic information, comorbidity of diabetes, urine analysis results before IC, method of IC (sterile or clean), use of bladder irrigation, cessation of IC and its reasons, and UTI events were collected. Results: A total of 183 adult individuals were included, of which 60 (32.8%) of them were women. The median age was 49.0 years. The median time post-injury was 2 months. The overall occurrence rate of UTI after performing IC was 1.31 (95% confidence intervals: 0.96-1.77) events per 100 days. Sixty-nine (37.7%) patients discontinued IC during hospitalization, and UTIs were the leading reason for cessation (50.7%). Female sex, use of antibiotics for infections other than UTI, and use of bladder irrigation were found to be associated with a lower occurrence rate of UTI in the early phase after performing IC, with an odds ratio of 0.38 (p = 0.019), 0.20 (p = 0.022), and 0.24 (p < 0.001), respectively. Conclusion: UTI after performing IC is prevalent among people with SCI. The study indicated that antibiotic prophylaxis and routine bladder irrigation might be associated with the reduction in UTI in the early phase after performing IC. Further research is needed to provide more evidence.

CK1δ and CK1ε Signaling Sustains Mitochondrial Metabolism and Cell Survival in Multiple Myeloma.

Multiple myeloma remains an incurable malignancy due to acquisition of intrinsic programs that drive therapy resistance. Here we report that casein kinase-1δ (CK1δ) and CK1ε are therapeutic targets in multiple myeloma that are necessary to sustain mitochondrial metabolism. Specifically, the dual CK1δ/CK1ε inhibitor SR-3029 had potent in vivo and ex vivo anti-multiple myeloma activity, including against primary multiple myeloma patient specimens. RNA sequencing (RNA-seq) and metabolic analyses revealed inhibiting CK1δ/CK1ε disables multiple myeloma metabolism by suppressing genes involved in oxidative phosphorylation (OxPhos), reducing citric acid cycle intermediates, and suppressing complexes I and IV of the electron transport chain. Finally, sensitivity of multiple myeloma patient specimens to SR-3029 correlated with elevated expression of mitochondrial genes, and RNA-seq from 687 multiple myeloma patient samples revealed that increased CSNK1D, CSNK1E, and OxPhos genes correlate with disease progression and inferior outcomes. Thus, increases in mitochondrial metabolism are a hallmark of multiple myeloma progression that can be disabled by targeting CK1δ/CK1ε. SIGNIFICANCE: CK1δ and CK1ε are attractive therapeutic targets in multiple myeloma whose expression increases with disease progression and connote poor outcomes, and that are necessary to sustain expression of genes directing OxPhos.

Nociceptor neurons affect cancer immunosurveillance.

Solid tumours are innervated by nerve fibres that arise from the autonomic and sensory peripheral nervous systems1-5. Whether the neo-innervation of tumours by pain-initiating sensory neurons affects cancer immunosurveillance remains unclear. Here we show that melanoma cells interact with nociceptor neurons, leading to increases in their neurite outgrowth, responsiveness to noxious ligands and neuropeptide release. Calcitonin gene-related peptide (CGRP)-one such nociceptor-produced neuropeptide-directly increases the exhaustion of cytotoxic CD8+ T cells, which limits their capacity to eliminate melanoma. Genetic ablation of the TRPV1 lineage, local pharmacological silencing of nociceptors and antagonism of the CGRP receptor RAMP1 all reduced the exhaustion of tumour-infiltrating leukocytes and decreased the growth of tumours, nearly tripling the survival rate of mice that were inoculated with B16F10 melanoma cells. Conversely, CD8+ T cell exhaustion was rescued in sensory-neuron-depleted mice that were treated with local recombinant CGRP. As compared with wild-type CD8+ T cells, Ramp1-/- CD8+ T cells were protected against exhaustion when co-transplanted into tumour-bearing Rag1-deficient mice. Single-cell RNA sequencing of biopsies from patients with melanoma revealed that intratumoral RAMP1-expressing CD8+ T cells were more exhausted than their RAMP1-negative counterparts, whereas overexpression of RAMP1 correlated with a poorer clinical prognosis. Overall, our results suggest that reducing the release of CGRP from tumour-innervating nociceptors could be a strategy to improve anti-tumour immunity by eliminating the immunomodulatory effects of CGRP on cytotoxic CD8+ T cells.

Transcriptional neural-like signaling contributes to an immune-suppressive tumor microenvironment.

Tumor innervation has recently been documented and characterized in various settings and tumor types. However, the role that nerves innervating tumors play in the pathogenesis of cancer has not been clarified. In this study, we searched for neural signaling from bulk RNA sequencing from The Cancer Genome Atlas (TCGA) dataset and looked for patterns of interactions between different cell types within the tumor environment. Using a presynapse signature (PSS) as a probe, we showed that multiple stromal cell types crosstalk and/or contribute to neural signals. Based on the correlation and linear regression, we hypothesized that neural signals contribute to an immune-suppressive tumor microenvironment (TME). To test this hypothesis, we performed in vitro dorsal root ganglion (DRG)/macrophage coculture experiments. Compared to the M2 macrophage monoculture, the DRG/M2 macrophage coculture prevented anti-inflammatory M2 to pro-inflammatory M1 polarization by LPS stimulation. Finally, a survey of different TCGA tumor types indicated that higher RNA neural signature is predictive of poor patient outcomes in multiple tumor types.

Plasma cell dependence on histone/protein deacetylase 11 reveals a therapeutic target in multiple myeloma.

The clinical utility of histone/protein deacetylase (HDAC) inhibitors in combinatorial regimens with proteasome inhibitors for patients with relapsed and refractory multiple myeloma (MM) is often limited by excessive toxicity due to HDAC inhibitor promiscuity with multiple HDACs. Therefore, more selective inhibition minimizing off-target toxicity may increase the clinical effectiveness of HDAC inhibitors. We demonstrated that plasma cell development and survival are dependent upon HDAC11, suggesting this enzyme is a promising therapeutic target in MM. Mice lacking HDAC11 exhibited markedly decreased plasma cell numbers. Accordingly, in vitro plasma cell differentiation was arrested in B cells lacking functional HDAC11. Mechanistically, we showed that HDAC11 is involved in the deacetylation of IRF4 at lysine103. Further, targeting HDAC11 led to IRF4 hyperacetylation, resulting in impaired IRF4 nuclear localization and target promoter binding. Importantly, transient HDAC11 knockdown or treatment with elevenostat, an HDAC11-selective inhibitor, induced cell death in MM cell lines. Elevenostat produced similar anti-MM activity in vivo, improving survival among mice inoculated with 5TGM1 MM cells. Elevenostat demonstrated nanomolar ex vivo activity in 34 MM patient specimens and synergistic activity when combined with bortezomib. Collectively, our data indicated that HDAC11 regulates an essential pathway in plasma cell biology establishing its potential as an emerging theraputic vulnerability in MM.

Multiple Myeloma DREAM Challenge reveals epigenetic regulator PHF19 as marker of aggressive disease.

While the past decade has seen meaningful improvements in clinical outcomes for multiple myeloma patients, a subset of patients does not benefit from current therapeutics for unclear reasons. Many gene expression-based models of risk have been developed, but each model uses a different combination of genes and often involves assaying many genes making them difficult to implement. We organized the Multiple Myeloma DREAM Challenge, a crowdsourced effort to develop models of rapid progression in newly diagnosed myeloma patients and to benchmark these against previously published models. This effort lead to more robust predictors and found that incorporating specific demographic and clinical features improved gene expression-based models of high risk. Furthermore, post-challenge analysis identified a novel expression-based risk marker, PHF19, which has recently been found to have an important biological role in multiple myeloma. Lastly, we show that a simple four feature predictor composed of age, ISS, and expression of PHF19 and MMSET performs similarly to more complex models with many more gene expression features included.

A Molecular Epidemiological Analysis Of Programmed Cell Death Ligand-1 (PD-L1) Protein Expression, Mutations And Survival In Non-Small Cell Lung Cancer.

PURPOSE: To characterize programmed cell death ligand-1 (PD-L1) expression in relation to survival and gene mutation status in patients with advanced NSCLC. The study also explored the influence of tumor mutational burden (TMB) on PD-L1 expression and patient characteristics. PATIENTS AND METHODS: Adult patients with histologically or cytologically documented Stage IIIB/Stage IV/recurrent/progressive NSCLC, Eastern Cooperative Oncology Group performance status 0 to 3, and >2 lines of prior systemic treatment regimens were included in this retrospective analysis. Patients were treated from 1997 to 2015 at H. Lee Moffitt Cancer Center and Research Institute, Tampa, or at 7 community centers across the United States. PD-L1 expression level was determined using the VENTANA PD-L1 (SP263) Assay. EGFR and KRAS mutation status and ALK rearrangements were determined by targeted DNA sequencing; these were obtained from clinical records where targeted DNA sequencing was not performed. TMB was calculated as the total number of somatic mutations per sample. RESULTS: From a total of 136 patients included in the study, 23.5% had tumors with high PD-L1 expression (≥25%). There were no significant differences in patient characteristics, overall survival (OS), and progression-free survival (PFS) between patients with high PD-L1 expression (median OS: 39.5 months; median PFS: 15.8 months) vs low PD-L1 expression (<25%; median OS: 38.1 months; median PFS: 18.6 months). PD-L1 expression level correlated (P=0.05) with TMB and was consistent with The Cancer Genome Atlas data. CONCLUSION: In this retrospective analysis, survival outcomes of patients with advanced NSCLC were comparable by PD-L1 expression level. EGFR and KRAS mutation status were not found to be significantly associated with PD-L1 expression level, while TMB was weakly associated with PD-L1 expression level. Overall, PD-L1 expression level was not observed to be an independent prognostic biomarker in this cohort of patients with advanced NSCLC treated with chemotherapy.

Circulating T Cell Subpopulations Correlate With Immune Responses at the Tumor Site and Clinical Response to PD1 Inhibition in Non-Small Cell Lung Cancer.

Agents targeting the PD1-PDL1 axis have transformed cancer therapy. Factors that influence clinical response to PD1-PDL1 inhibitors include tumor mutational burden, immune infiltration of the tumor, and local PDL1 expression. To identify peripheral correlates of the anti-tumor immune response in the absence of checkpoint blockade, we performed a retrospective study of circulating T cell subpopulations and matched tumor gene expression in melanoma and non-small cell lung cancer (NSCLC) patients. Notably, both melanoma and NSCLC patients whose tumors exhibited increased inflammatory gene transcripts presented high CD4+ and CD8+ central memory T cell (CM) to effector T cell (Eff) ratios in blood. Consequently, we evaluated CM/Eff T cell ratios in a second cohort of NSCLC. The data showed that high CM/Eff T cell ratios correlated with increased tumor PDL1 expression. Furthermore, of the 22 patients within this NSCLC cohort who received nivolumab, those with high CM/Eff T cell ratios, had longer progression-free survival (PFS) (median survival: 91 vs. 215 days). These findings show that by providing a window into the state of the immune system, peripheral T cell subpopulations inform about the state of the anti-tumor immune response and identify potential blood biomarkers of clinical response to checkpoint inhibitors in melanoma and NSCLC.

Use of the Total Cancer Care System to Enrich Screening for CD30-Positive Solid Tumors for Patient Enrollment Into a Brentuximab Vedotin Clinical Trial: A Pilot Study to Evaluate Feasibility.

BACKGROUND: One approach to identify patients who meet specific eligibility criteria for target-based clinical trials is to use patient and tumor registries to prescreen patient populations. OBJECTIVE: Here we demonstrate that the Total Cancer Care (TCC) Protocol, an ongoing, observational study, may provide a solution for rapidly identifying patients with CD30-positive tumors eligible for CD30-targeted therapies such as brentuximab vedotin. METHODS: The TCC patient gene expression profiling database was retrospectively screened for CD30 gene expression determined using HuRSTA-2a520709 Affymetrix arrays (GPL15048). Banked tumor tissue samples were used to determine CD30 protein expression by semiquantitative immunohistochemistry. Statistical comparisons of Z- and H-scores were performed using R statistical software (The R Foundation), and the predictive value, accuracy, sensitivity, and specificity of CD30 gene expression versus protein expression was estimated. RESULTS: As of March 2015, 120,887 patients have consented to the institutional review board-approved TCC Protocol. A total of 39,157 fresh frozen tumor specimens have been collected, from which over 14,000 samples have gene expression data available. CD30 RNA was expressed in a number of solid tumors; the highest median CD30 RNA expression was observed in primary tumors from lymph node, soft tissue (many sarcomas), lung, skin, and esophagus (median Z-scores 1.011, 0.399, 0.202, 0.152, and 1.011, respectively). High level CD30 gene expression significantly enriches for CD30-positive protein expression in breast, lung, skin, and ovarian cancer; accuracy ranged from 72% to 79%, sensitivity from 75% to 100%, specificity from 70% to 76%, positive predictive value from 20% to 40%, and negative predictive value from 95% to 100%. CONCLUSIONS: The TCC gene expression profiling database guided tissue selection that enriched for CD30 protein expression in a number of solid tumor types. Such an approach may improve screening efficiency for enrolling patients into biomarker-based clinical trials.

Endosialin and Associated Protein Expression in Soft Tissue Sarcomas: A Potential Target for Anti-Endosialin Therapeutic Strategies.

Endosialin (CD248, TEM-1) is expressed in pericytes, tumor vasculature, tumor fibroblasts, and some tumor cells, including sarcomas, with limited normal tissue expression, and appears to play a key role in tumor-stromal interactions, including angiogenesis. Monoclonal antibodies targeting endosialin have entered clinical trials, including soft tissue sarcomas. We evaluated a cohort of 94 soft tissue sarcoma samples to assess the correlation between gene expression and protein expression by immunohistochemistry for endosialin and PDGFR-ß, a reported interacting protein, across available diagnoses. Correlations between the expression of endosialin and 13 other genes of interest were also examined. Within cohorts of soft tissue diagnoses assembled by tissue type (liposarcoma, leiomyosarcoma, undifferentiated sarcoma, and other), endosialin expression was significantly correlated with a better outcome. Endosialin expression was highest in liposarcomas and lowest in leiomyosarcomas. A robust correlation between protein and gene expression data for both endosialin and PDGFR-ß was observed. Endosialin expression positively correlated with PDGFR-ß and heparin sulphate proteoglycan 2 and negatively correlated with carbonic anhydrase IX. Endosialin likely interacts with a network of extracellular and hypoxia activated proteins in sarcomas and other tumor types. Since expression does vary across histologic groups, endosialin may represent a selective target in soft tissue sarcomas.

Genome-wide identification of RNA editing in hepatocellular carcinoma.

We did whole-transcriptome sequencing and whole-genome sequencing on nine pairs of Hepatocellular carcinoma (HCC) tumors and matched adjacent tissues to identify RNA editing events. We identified mean 26,982 editing sites with mean 89.5% canonical A→G edits in each sample using an improved bioinformatics pipeline. The editing rate was significantly higher in tumors than adjacent normal tissues. Comparing the difference between tumor and normal tissues of each patient, we found 7 non-synonymous tissue specific editing events including 4 tumor-specific edits and 3 normal-specific edits in the coding region, as well as 292 edits varying in editing degree. The significant expression changes of 150 genes associated with RNA editing were found in tumors, with 3 of the 4 most significant genes being cancer related. Our results show that editing might be related to higher gene expression. These findings indicate that RNA editing modification may play an important role in the development of HCC.

A candidate plasma protein classifier to identify Alzheimer's disease.

Biomarkers currently used in the aid for the diagnosis of Alzheimer's disease (AD) are cerebrospinal fluid (CSF) protein markers and brain neuroimaging markers. These biomarkers, however, either involve semi-invasive procedures or are costly to measure. Thus, AD biomarkers from more easily accessible body fluids, such as plasma, are very enticing. Using an aptamer-based proteomic technology, we profiled 1,129 plasma proteins of AD patients and non-demented control individuals. A 5-protein classifier for AD identification was constructed in the discovery study with excellent 10-fold cross-validation performance (90.1% sensitivity, 84.2% specificity, 87.9% accuracy, and AUC as 0.94). In an independent validation study, the classifier was applied and correctly predicted AD with 100.0% sensitivity, 80.0% specificity, and 90.0% accuracy, matching or outperforming the CSF Aß42 and tau biomarkers whose performance were assessed in individual-matched CSF samples obtained at the same visit as plasma sample collection. Moreover, the classifier also correctly predicted mild cognitive impairment, an early pre-dementia state of the disease, with 96.7% sensitivity, 80.0% specificity, and 92.5% accuracy. These studies demonstrate that plasma proteins could be used effectively and accurately to contribute to the clinical diagnosis of AD. Although additional and more diverse cohorts are needed for further validation of the robustness, including the support of postmortem diagnosis, the 5-protein classifier appears to be a promising blood test to contribute diagnosis of AD.

Genomic landscape and genetic heterogeneity in gastric adenocarcinoma revealed by whole-genome sequencing.

Gastric cancer (GC) is the second most common cause of cancer-related deaths. It is known to be a heterogeneous disease with several molecular and histological subtypes. Here we perform whole-genome sequencing of 49 GCs with diffuse (N=31) and intestinal (N=18) histological subtypes and identify three mutational signatures, impacting TpT, CpG and TpCp[A/T] nucleotides. The diffuse-type GCs show significantly lower clonality and smaller numbers of somatic and structural variants compared with intestinal subtype. We further divide the diffuse subtype into one with infrequent genetic changes/low clonality and another with relatively higher clonality and mutations impacting TpT dinucleotide. Notably, we discover frequent and exclusive mutations in Ephrins and SLIT/ROBO signalling pathway genes. Overall, this study delivers new insights into the mutational heterogeneity underlying distinct histologic subtypes of GC that could have important implications for future research in the diagnosis and treatment of GC.

Whole-genome sequencing identifies recurrent mutations in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most deadly cancers worldwide and has no effective treatment, yet the molecular basis of hepatocarcinogenesis remains largely unknown. Here we report findings from a whole-genome sequencing (WGS) study of 88 matched HCC tumor/normal pairs, 81 of which are Hepatitis B virus (HBV) positive, seeking to identify genetically altered genes and pathways implicated in HBV-associated HCC. We find beta-catenin to be the most frequently mutated oncogene (15.9%) and TP53 the most frequently mutated tumor suppressor (35.2%). The Wnt/beta-catenin and JAK/STAT pathways, altered in 62.5% and 45.5% of cases, respectively, are likely to act as two major oncogenic drivers in HCC. This study also identifies several prevalent and potentially actionable mutations, including activating mutations of Janus kinase 1 (JAK1), in 9.1% of patients and provides a path toward therapeutic intervention of the disease.

Integrative analysis of a cross-loci regulation network identifies App as a gene regulating insulin secretion from pancreatic islets.

Complex diseases result from molecular changes induced by multiple genetic factors and the environment. To derive a systems view of how genetic loci interact in the context of tissue-specific molecular networks, we constructed an F2 intercross comprised of >500 mice from diabetes-resistant (B6) and diabetes-susceptible (BTBR) mouse strains made genetically obese by the Leptin(ob/ob) mutation (Lep(ob)). High-density genotypes, diabetes-related clinical traits, and whole-transcriptome expression profiling in five tissues (white adipose, liver, pancreatic islets, hypothalamus, and gastrocnemius muscle) were determined for all mice. We performed an integrative analysis to investigate the inter-relationship among genetic factors, expression traits, and plasma insulin, a hallmark diabetes trait. Among five tissues under study, there are extensive protein-protein interactions between genes responding to different loci in adipose and pancreatic islets that potentially jointly participated in the regulation of plasma insulin. We developed a novel ranking scheme based on cross-loci protein-protein network topology and gene expression to assess each gene's potential to regulate plasma insulin. Unique candidate genes were identified in adipose tissue and islets. In islets, the Alzheimer's gene App was identified as a top candidate regulator. Islets from 17-week-old, but not 10-week-old, App knockout mice showed increased insulin secretion in response to glucose or a membrane-permeant cAMP analog, in agreement with the predictions of the network model. Our result provides a novel hypothesis on the mechanism for the connection between two aging-related diseases: Alzheimer's disease and type 2 diabetes.

Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers.

Common inflammatome gene signatures as well as disease-specific signatures were identified by analyzing 12 expression profiling data sets derived from 9 different tissues isolated from 11 rodent inflammatory disease models. The inflammatome signature significantly overlaps with known drug targets and co-expressed gene modules linked to metabolic disorders and cancer. A large proportion of genes in this signature are tightly connected in tissue-specific Bayesian networks (BNs) built from multiple independent mouse and human cohorts. Both the inflammatome signature and the corresponding consensus BNs are highly enriched for immune response-related genes supported as causal for adiposity, adipokine, diabetes, aortic lesion, bone, muscle, and cholesterol traits, suggesting the causal nature of the inflammatome for a variety of diseases. Integration of this inflammatome signature with the BNs uncovered 151 key drivers that appeared to be more biologically important than the non-drivers in terms of their impact on disease phenotypes. The identification of this inflammatome signature, its network architecture, and key drivers not only highlights the shared etiology but also pinpoints potential targets for intervention of various common diseases.

Genome-wide survey of recurrent HBV integration in hepatocellular carcinoma.

To survey hepatitis B virus (HBV) integration in liver cancer genomes, we conducted massively parallel sequencing of 81 HBV-positive and 7 HBV-negative hepatocellular carcinomas (HCCs) and adjacent normal tissues. We found that HBV integration is observed more frequently in the tumors (86.4%) than in adjacent liver tissues (30.7%). Copy-number variations (CNVs) were significantly increased at HBV breakpoint locations where chromosomal instability was likely induced. Approximately 40% of HBV breakpoints within the HBV genome were located within a 1,800-bp region where the viral enhancer, X gene and core gene are located. We also identified recurrent HBV integration events (in ≥ 4 HCCs) that were validated by RNA sequencing (RNA-seq) and Sanger sequencing at the known and putative cancer-related TERT, MLL4 and CCNE1 genes, which showed upregulated gene expression in tumor versus normal tissue. We also report evidence that suggests that the number of HBV integrations is associated with patient survival.

Novel transcriptome profiling analyses demonstrate that selective peroxisome proliferator-activated receptor γ (PPARγ) modulators display attenuated and selective gene regulatory activity in comparison with PPARγ full agonists.

Selective peroxisome proliferator-activated receptor γ (PPARγ) modulators (SPPARγMs) have been actively pursued as the next generation of insulin-sensitizing antidiabetic drugs, because the currently marketed PPARγ full agonists, pioglitazone and rosiglitazone, have been reported to produce serious adverse effects among patients with type 2 diabetes mellitus. We conducted extensive transcriptome profiling studies to characterize and to contrast the activities of 70 SPPARγMs and seven PPARγ full agonists. In both 3T3-L1 adipocytes and adipose tissue from db/db mice, the SPPARγMs generated attenuated and selective gene-regulatory responses, in comparison with full agonists. More importantly, SPPARγMs regulated the expression of antidiabetic efficacy-associated genes to a greater extent than that of adverse effect-associated genes, whereas PPARγ full agonists regulated both gene sets proportionally. Such SPPARγM selectivity demonstrates that PPARγ ligand regulation of gene expression can be fine-tuned, and not just turned on and off, to achieve precise control of complex cellular and physiological functions. It also provides a potential molecular basis for the superior therapeutic window previously observed with SPPARγMs versus full agonists. On the basis of our profiling results, we introduce two novel, gene expression-based scores, the γ activation index and the selectivity index, to aid in the detection and characterization of novel SPPARγMs. These studies provide new insights into the gene-regulatory activity of SPPARγMs as well as novel quantitative indices to facilitate the identification of PPARγ ligands with robust insulin-sensitizing activity and improved tolerance among patients with type 2 diabetes, compared with presently available PPARγ agonist drugs.

Clinicopathologic and gene expression parameters predict liver cancer prognosis.

BACKGROUND: The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model. METHODS: Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction. RESULTS: HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis. CONCLUSION: When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome.

Gene signatures derived from a c-MET-driven liver cancer mouse model predict survival of patients with hepatocellular carcinoma.

Biomarkers derived from gene expression profiling data may have a high false-positive rate and must be rigorously validated using independent clinical data sets, which are not always available. Although animal model systems could provide alternative data sets to formulate hypotheses and limit the number of signatures to be tested in clinical samples, the predictive power of such an approach is not yet proven. The present study aims to analyze the molecular signatures of liver cancer in a c-MET-transgenic mouse model and investigate its prognostic relevance to human hepatocellular carcinoma (HCC). Tissue samples were obtained from tumor (TU), adjacent non-tumor (AN) and distant normal (DN) liver in Tet-operator regulated (TRE) human c-MET transgenic mice (n = 21) as well as from a Chinese cohort of 272 HBV- and 9 HCV-associated HCC patients. Whole genome microarray expression profiling was conducted in Affymetrix gene expression chips, and prognostic significances of gene expression signatures were evaluated across the two species. Our data revealed parallels between mouse and human liver tumors, including down-regulation of metabolic pathways and up-regulation of cell cycle processes. The mouse tumors were most similar to a subset of patient samples characterized by activation of the Wnt pathway, but distinctive in the p53 pathway signals. Of potential clinical utility, we identified a set of genes that were down regulated in both mouse tumors and human HCC having significant predictive power on overall and disease-free survival, which were highly enriched for metabolic functions. In conclusions, this study provides evidence that a disease model can serve as a possible platform for generating hypotheses to be tested in human tissues and highlights an efficient method for generating biomarker signatures before extensive clinical trials have been initiated.