The disabled homolog 2 (DAB2) gene was recently identified as a tumor suppressor gene with its expression down-regulated in multiple cancer types. The role of DAB2 in lung tumorigenesis, however, is not fully characterized, and the mechanisms of DAB2 dysregulation in lung cancer are not defined. Here we show that low DAB2 levels in lung tumor specimens are significantly correlated with poor patient survival, and that DAB2 over-expression significantly inhibits cell growth in cultured lung cancer cells, indicating its potent tumor suppressor function. We next identify that microRNA miR-93 functions as a potent repressor of DAB2 expression by directly targeting the 3′UTR of the DAB2 mRNA. Using in vitro and in vivo approaches, we demonstrate that miR-93 over-expression plays an important role in promoting lung cancer cell growth, and that its oncogenic function is primarily mediated by down-regulating DAB2 expression. Our clinical investigations further indicate that high tumor levels of miR-93 are correlated with poor survival of lung cancer patients. The correlations of both low DAB2 and high miR-93 expression with poor patient survival strongly support the critical role of the miR-93/DAB2 pathway in determining lung cancer progression.
DAB2; miRNA; miR-93; lung cancer
Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm.
Negative elongation factor (NELF) is known to enforce promoter-proximal pausing of RNA polymerase II (Pol II), a pervasive phenomenon observed across multicellular genomes. However, the physiological impact of NELF on tissue homeostasis remains unclear. Here, we show that whole-body conditional deletion of the B subunit of NELF (NELF-B) in adult mice results in cardiomyopathy and impaired response to cardiac stress. Tissue-specific knockout of NELF-B confirms its cell-autonomous function in cardiomyocytes. NELF directly supports transcription of those genes encoding rate-limiting enzymes in fatty acid oxidation (FAO) and the tricarboxylic acid (TCA) cycle. NELF also shares extensively transcriptional target genes with peroxisome proliferator-activated receptor α (PPARα), a master regulator of energy metabolism in the myocardium. Mechanistically, NELF helps stabilize the transcription initiation complex at the metabolism-related genes. Our findings strongly indicate that NELF is part of the PPARα-mediated transcription regulatory network that maintains metabolic homeostasis in cardiomyocytes.
DNA methylation is a common epigenetic marker that regulates gene expression. A robust and cost-effective way for measuring whole genome methylation is Methyl-CpG binding domain-based capture followed by sequencing (MBDCap-seq). In this study, we proposed BIMMER, a Hidden Markov Model (HMM) for differential Methylation Regions (DMRs) identification, where HMMs were proposed to model the methylation status in normal and cancer samples in the first layer and another HMM was introduced to model the relationship between differential methylation and methylation statuses in normal and cancer samples. To carry out the prediction for BIMMER, an Expectation-Maximization algorithm was derived. BIMMER was validated on the simulated data and applied to real MBDCap-seq data of normal and cancer samples. BIMMER revealed that 8.83% of the breast cancer genome are differentially methylated and the majority are hypo-methylated in breast cancer.
DNA methylation; differential methylation; MBDCap-seq; Hidden Markov Model (HMM)
Osteosarcoma is the most common bone tumor in children, adolescents, and young adults. In contrast to other childhood malignancies, no biomarkers have been consistently identified as predictors of outcome. This study was conducted to assess the microRNAs(miRs) expression signatures in pre-treatment osteosarcoma specimens and correlate with outcome to identify biomarkers for disease relapse.
A 42-miRs signature whose expression levels were associated with overall and relapse-free survival waas identified. There were 8 common miRs between the two sets of survival-associated miRs. Bioinformatic analyses of these survival-associated miRs suggested that they might regulate genes involved in ubiquitin proteasome system, TGFb, IGF, PTEN/AKT/mTOR, MAPK, PDGFR/RAF/MEK/ERK, and ErbB/HER pathways.
The cohort consisted of 27 patients of 70% Mexican-American ethnicity. High-throughput RT-qPCR approach was used to generate quantitative expression of 754 miRs in the human genome. We examined tumor recurrence status, survival time and their association with miR expression levels by Cox proportional hazard regression analysis. TargetScan was used to predict miR/genes interactions, and functional analyses using KEGG, BioCarta, Gene Ontology were applied to these potential targets to predict deregulated pathways.
Our findings suggested that these miRs might be potentially useful as prognostic biomarkers and therapeutic targets in pediatric osteosarcoma.
osteosarcoma; microRNA expression; prognosis; pathways; pediatric cancers
A causal role of gene amplification in tumorigenesis is well-known, while amplification of DNA regulatory elements as an oncogenic driver remains unclear. In this study, we integrated next-generation sequencing approaches to map distant estrogen response elements (DEREs) that remotely control transcription of target genes through chromatin proximity. Two densely mapped DERE regions located on chromosomes 17q23 and 20q13 were frequently amplified in ERα-positive luminal breast cancer. These aberrantly amplified DEREs deregulated target gene expression potentially linked to cancer development and tamoxifen resistance. Progressive accumulation of DERE copies was observed in normal breast progenitor cells chronically exposed to estrogenic chemicals. These findings may extend to other DNA regulatory elements, the amplification of which can profoundly alter target transcriptome during tumorigenesis.
Motivation: Fragmented RNA immunoprecipitation combined with RNA sequencing enabled the unbiased study of RNA epigenome at a near single-base resolution; however, unique features of this new type of data call for novel computational techniques.
Result: Through examining the connections of RNA epigenome sequencing data with two well-studied data types, ChIP-Seq and RNA-Seq, we unveiled the salient characteristics of this new data type. The computational strategies were discussed accordingly, and a novel data processing pipeline was proposed that combines several existing tools with a newly developed exome-based approach ‘exomePeak’ for detecting, representing and visualizing the post-transcriptional RNA modification sites on the transcriptome.
Availability: The MATLAB package ‘exomePeak’ and additional details are available at http://compgenomics.utsa.edu/exomePeak/.
firstname.lastname@example.org or email@example.com
Supplementary data are available at Bioinformatics online.
Neuroblastoma, the most common extracranial solid tumor of childhood, arises from neural crest cell precursors that fail to differentiate. Inducing cell differentiation is an important therapeutic strategy for neuroblastoma. We developed a direct functional high-content screen to identify differentiation-inducing microRNAs, in order to develop microRNA-based differentiation therapy for neuroblastoma. We discovered novel microRNAs, and more strikingly, three microRNA seed families that induce neuroblastoma cell differentiation. In addition, we showed that microRNA seed families were overrepresented in the identified group of fourteen differentiation-inducing microRNAs, suggesting that microRNA seed families are functionally more important in neuroblastoma differentiation than microRNAs with unique sequences. We further investigated the differentiation-inducing function of the microRNA-506-3p/microRNA-124-3p seed family, which was the most potent inducer of differentiation. We showed that the differentiation-inducing function of microRNA-506-3p/microRNA-124-3p is mediated, at least partially, by down-regulating expression of their targets CDK4 and STAT3. We further showed that expression of miR-506-3p, but not miR-124-3p, is dramatically upregulated in differentiated neuroblastoma cells, suggesting the important role of endogenous miR-506-3p in differentiation and tumorigenesis. Overall, our functional screen on microRNAs provided the first comprehensive analysis on the involvements of microRNA species in neuroblastoma cell differentiation and identified novel differentiation-inducing microRNAs. Further investigations are certainly warranted to fully characterize the function of the identified microRNAs in order to eventually benefit neuroblastoma therapy.
neuroblastoma; microRNA; high-content screen; differentiation; differentiation therapy
Rapamycin (Rapa) and dietary restriction (DR) have consistently been shown to increase lifespan. To investigate whether Rapa and DR affect similar pathways in mice, we compared the effects of feeding mice ad libitum (AL), Rapa, DR, or a combination of Rapa and DR (Rapa + DR) on the transcriptome and metabolome of the liver. The principal component analysis shows that Rapa and DR are distinct groups. Over 2500 genes are significantly changed with either Rapa or DR when compared with mice fed AL; more than 80% are unique to DR or Rapa. A similar observation was made when genes were grouped into pathways; two-thirds of the pathways were uniquely changed by DR or Rapa. The metabolome shows an even greater difference between Rapa and DR; no metabolites in Rapa-treated mice were changed significantly from AL mice, whereas 173 metabolites were changed in the DR mice. Interestingly, the number of genes significantly changed by Rapa + DR when compared with AL is twice as large as the number of genes significantly altered by either DR or Rapa alone. In summary, the global effects of DR or Rapa on the liver are quite different and a combination of Rapa and DR results in alterations in a large number of genes and metabolites that are not significantly changed by either manipulation alone, suggesting that a combination of DR and Rapa would be more effective in extending longevity than either treatment alone.
dietary restriction; metabolome; rapamycin; transcriptome
Exon recognition is a fundamental task in bioinformatics to identify the exons of DNA sequence. Currently, exon recognition algorithms based on digital signal processing techniques have been widely used. Unfortunately, these methods require many calculations, resulting in low recognition efficiency. In order to overcome this limitation, a two-stage exon recognition model is proposed and implemented in this paper. There are three main works. Firstly, we use synergetic neural network to rapidly determine initial exon intervals. Secondly, adaptive sliding window is used to accurately discriminate the final exon intervals. Finally, parameter optimization based on artificial fish swarm algorithm is used to determine different species thresholds and corresponding adjustment parameters of adaptive windows. Experimental results show that the proposed model has better performance for exon recognition and provides a practical solution and a promising future for other recognition tasks.
Although somatic cell reprogramming to generate inducible pluripotent stem cells (iPSCs) is associated with profound epigenetic changes, the roles and mechanisms of epigenetic factors in this process remain poorly understood. Here we identify Jmjd3 as a potent negative regulator of reprogramming. Jmjd3-deficient MEFs produced significantly more iPSC colonies than did wild-type cells, while ectopic expression of Jmjd3 markedly inhibited reprogramming. We show that the inhibitory effects of Jmjd3 are produced through both histone demethylase-dependent and -independent pathways. The latter pathway is entirely novel and involves Jmjd3 targeting of PHF20 for ubiquitination and degradation via recruitment of an E3 ligase, Trim26. Importantly, PHF20-deficient MEFs could not be converted to fully reprogrammed iPSCs, even with knockdown of Jmjd3, Ink4a or p21, indicating that this protein exerts predominant effects on reprogramming. Our findings demonstrate a previously unrecognized role of Jmjd3 in cellular reprogramming and provide molecular insight into the mechanisms by which the Jmjd3-PHF20 axis controls this process.
Rapamycin was found to increase (11% to 16%) the lifespan of male and female C57BL/6J mice most likely by reducing the increase in the hazard for mortality (i.e., the rate of aging) term in the Gompertz mortality analysis. To identify the pathways that could be responsible for rapamycin's longevity effect, we analyzed the transcriptome of liver from 25-month-old male and female mice fed rapamycin starting at 4 months of age. Few changes (<300 transcripts) were observed in transcriptome of rapamycin-fed males; however, a large number of transcripts (>4,500) changed significantly in females. Using multidimensional scaling and heatmap analyses, the male mice fed rapamycin were found to segregate into two groups: one group that is almost identical to control males (Rapa-1) and a second group (Rapa-2) that shows a change in gene expression (>4,000 transcripts) with more than 60% of the genes shared with female mice fed Rapa. Using ingenuity pathway analysis, 13 pathways were significantly altered in both Rapa-2 males and rapamycin-fed females with mitochondrial function as the most significantly changed pathway. Our findings show that rapamycin has a major effect on the transcriptome and point to several pathways that would likely impact the longevity.
Connectivity map (cMap) is a recent developed dataset and algorithm for uncovering and understanding the treatment effect of small molecules on different cancer cell lines. It is widely used but there are still remaining challenges for accurate predictions.
Here, we propose BRCA-MoNet, a network of drug mode of action (MoA) specific to breast cancer, which is constructed based on the cMap dataset. A drug signature selection algorithm fitting the characteristic of cMap data, a quality control scheme as well as a novel query algorithm based on BRCA-MoNet are developed for more effective prediction of drug effects.
BRCA-MoNet was applied to three independent data sets obtained from the GEO database: Estrodial treated MCF7 cell line, BMS-754807 treated MCF7 cell line, and a breast cancer patient microarray dataset. In the first case, BRCA-MoNet could identify drug MoAs likely to share same and reverse treatment effect. In the second case, the result demonstrated the potential of BRCA-MoNet to reposition drugs and predict treatment effects for drugs not in cMap data. In the third case, a possible procedure of personalized drug selection is showcased.
The results clearly demonstrated that the proposed BRCA-MoNet approach can provide increased prediction power to cMap and thus will be useful for identification of new therapeutic candidates.
Website: The web based application is developed and can be access through the following link http://compgenomics.utsa.edu/BRCAMoNet/
Connectivity Map; Mode of Action (MoA); Breast Cancer Mode of Action Network (BRCA-MoNet)
Alveolar rhabdomyosarcoma (aRMS) is a myogenic childhood sarcoma frequently associated with a translocation-mediated fusion gene, Pax3:Foxo1a.
We investigated the complementary role of Rb1 loss in aRMS tumor initiation and progression using conditional mouse models.
Rb1 loss was not a necessary and sufficient mutational event for rhabdomyosarcomagenesis, nor a strong cooperative initiating mutation. Instead, Rb1 loss was a modifier of progression and increased anaplasia and pleomorphism. Whereas Pax3:Foxo1a expression was unaltered, biomarkers of aRMS versus embryonal rhabdomyosarcoma were both increased, questioning whether these diagnostic markers are reliable in the context of Rb1 loss. Genome-wide gene expression in Pax3:Foxo1a,Rb1 tumors more closely approximated aRMS than embryonal rhabdomyosarcoma. Intrinsic loss of pRb function in aRMS was evidenced by insensitivity to a Cdk4/6 inhibitor regardless of whether Rb1 was intact or null. This loss of function could be attributed to low baseline Rb1, pRb and phospho-pRb expression in aRMS tumors for which the Rb1 locus was intact. Pax3:Foxo1a RNA interference did not increase pRb or improve Cdk inhibitor sensitivity. Human aRMS shared the feature of low and/or heterogeneous tumor cell pRb expression.
Rb1 loss from an already low pRb baseline is a significant disease modifier, raising the possibility that some cases of pleomorphic rhabdomyosarcoma may in fact be Pax3:Foxo1a-expressing aRMS with Rb1 or pRb loss of function.
Alveolar rhabdomyosarcoma; Disease modifier; Sarcoma; Rb1; Spindle cell; Retinoblastoma
Copy number alterations (CNAs) can be observed in most of cancer patients. Several oncogenes and tumor suppressor genes with CNAs have been identified in different kinds of tumor. However, the systematic survey of CNA-affected functions is still lack. By employing systems biology approaches, instead of examining individual genes, we directly identified the functional hotspots on human genome. A total of 838 hotspots on human genome with 540 enriched Gene Ontology functions were identified. Seventy-six aCGH array data of hepatocellular carcinoma (HCC) tumors were employed in this study. A total of 150 regions which putatively affected by CNAs and the encoded functions were identified. Our results indicate that two immune related hotspots had copy number alterations in most of patients. In addition, our data implied that these immune-related regions might be involved in HCC oncogenesis. Also, we identified 39 hotspots of which copy number status were associated with patient survival. Our data implied that copy number alterations of the regions may contribute in the dysregulation of the encoded functions. These results further demonstrated that our method enables researchers to survey biological functions of CNAs and to construct regulation hypothesis at pathway and functional levels.
Copy number alteration; Gene set enrichment; Pathway analysis; Liver cancer
The role of adjuvant radiotherapy (RT) for patients with stage III thymoma after complete resection is not definite. Some authors have advocated postoperative RT after complete tumor resection, but some others suggested observation. In this study, we retrospectively evaluated the effect of postoperative RT on survival as well as tumor control in patients with Masaoka stage III thymoma.
Between June 1982 and December 2010, 65 patients who underwent complete resection of stage III thymoma entered the study. Fifty-three patients had adjuvant RT after surgery (S + R) and 12 had surgery only (S alone). Of patients who had adjuvant RT, 28 had three-dimensional conformal RT (3D-CRT)/intensity modulated RT (IMRT) and 25 had conventional RT. A median prescribed dose of 56 Gy (range, 28–60 Gy) was given.
The median follow-up time was 50 months (range, 5–360 months). Five- and 10-year overall survival (OS) rates were 91.7% and 71.6%, respectively, for S + R and 81.5% and 65.2% for S alone (P = 0.5), respectively. In the subgroup analysis, patients with 3D-CRT/IMRT showed a trend of improved 5-year OS rate compared with conventional RT (100% vs. 86.9%, P =0.12). Compared with S alone, the 5-year OS rate was significantly improved (100% vs. 81.5%, P = 0.049). Relapses occurred in 15 patients (23.1%). There was a trend of lower crude local recurrence rates for S + R (3.8%) compared with S alone (16.7%) (P = 0.09), whereas the crude regional recurrence rates were similar (P = 0.9). No clear dose–response relationship was found according to prescribed doses.
Adjuvant 3D-CRT/IMRT showed potential advantages in improving survival and reducing relapse in patients with stage III thymoma after complete resection, whereas adjuvant RT did not significantly improve survival or reduce recurrence for the cohort as a whole. Doses of ≤ 50 Gy may be effective and could be prescribed for adjuvant RT. To confirm the role of adjuvant 3D-CRT/IMRT in patients who undergo a complete resection of thymoma, a multicenter randomized study should be performed.
Thymoma; Radiation; Surgery; Failure pattern
Extracting maximal information from gene signature sets (GSSs) via microarray-based transcriptional profiling involves assigning function to up and down regulated genes. Here we present a novel sample scoring method called Signature-score (S-score) which can be used to quantify the expression pattern of tumor samples from previously identified gene signature sets. A simulation result demonstrated an improved accuracy and robustness by S-score method comparing with other scoring methods. By applying the S-score method to cholangiocarcinoma (CAC), an aggressive hepatic cancer that arises from bile ducts cells, we identified enriched oncogenic pathways in two large CAC data sets. Thirteen pathways were enriched in CAC compared with normal liver and bile duct. Moreover, using S-score, we were able to dissect correlations between CAC-associated oncogenic pathways and Gene Ontology function. Two major oncogenic clusters and associated functions were identified. Cluster 1, which included beta-catenin and Ras, showed a positive correlation with the cell cycle, while cluster 2, which included TGF-beta, cytokeratin 19 and EpCAM was inversely correlated with immune function. We also used S-score to identify pathways that are differentially expressed in CAC and hepatocellular carcinoma (HCC), the more common subtype of liver cancer. Our results demonstrate the utility and effectiveness of S-score in assigning functional roles to tumor-associated gene signature sets and in identifying potential therapeutic targets for specific liver cancer subtypes.
gene signature set; pathway analysis; S-score method; tumor classification
DNA methylation of promoter CpG islands is associated with gene suppression, and its unique genome-wide profiles have been linked to tumor progression. Coupled with high-throughput sequencing technologies, it can now efficiently determine genome-wide methylation profiles in cancer cells. Also, experimental and computational technologies make it possible to find the functional relationship between cancer-specific methylation patterns and their clinicopathological parameters.
Cancer methylome system (CMS) is a web-based database application designed for the visualization, comparison and statistical analysis of human cancer-specific DNA methylation. Methylation intensities were obtained from MBDCap-sequencing, pre-processed and stored in the database. 191 patient samples (169 tumor and 22 normal specimen) and 41 breast cancer cell-lines are deposited in the database, comprising about 6.6 billion uniquely mapped sequence reads. This provides comprehensive and genome-wide epigenetic portraits of human breast cancer and endometrial cancer to date. Two views are proposed for users to better understand methylation structure at the genomic level or systemic methylation alteration at the gene level. In addition, a variety of annotation tracks are provided to cover genomic information. CMS includes important analytic functions for interpretation of methylation data, such as the detection of differentially methylated regions, statistical calculation of global methylation intensities, multiple gene sets of biologically significant categories, interactivity with UCSC via custom-track data. We also present examples of discoveries utilizing the framework.
CMS provides visualization and analytic functions for cancer methylome datasets. A comprehensive collection of datasets, a variety of embedded analytic functions and extensive applications with biological and translational significance make this system powerful and unique in cancer methylation research. CMS is freely accessible at: http://cbbiweb.uthscsa.edu/KMethylomes/.
microRNAs (miRNAs) have been implicated in the control of many biological processes and their deregulation has been associated with many cancers. In recent years, the cancer stem cell (CSC) concept has been applied to many cancers including pediatric. We hypothesized that a common signature of deregulated miRNAs in the CSCs fraction may explain the disrupted signaling pathways in CSCs.
Using a high throughput qPCR approach we identified 26 CSC associated differentially expressed miRNAs (DEmiRs). Using BCmicrO algorithm 865 potential CSC associated DEmiR targets were obtained. These potential targets were subjected to KEGG, Biocarta and Gene Ontology pathway and biological processes analysis. Four annotated pathways were enriched: cell cycle, cell proliferation, p53 and TGF-beta/BMP. Knocking down hsa-miR-21-5p, hsa-miR-181c-5p and hsa-miR-135b-5p using antisense oligonucleotides and small interfering RNA in cell lines led to the depletion of the CSC fraction and impairment of sphere formation (CSC surrogate assays).
Our findings indicated that CSC associated DEmiRs and the putative pathways they regulate may have potential therapeutic applications in pediatric cancers.
Background & Aims
Hepatocellular carcinoma (HCC) is an aggressive malignancy; its mechanisms of development and progression are poorly understood. We used an integrative approach to identify HCC driver genes, defined as genes whose copy numbers associate with gene expression and cancer progression.
We combined data from high-resolution, array-based comparative genomic hybridization (CGH) and transcriptome analysis of HCC samples from 76 patients with hepatitis B virus infection with data on patient survival times. Candidate genes were functionally validated using in vitro and in vivo models.
Unsupervised analyses of array CGH data associated loss of chromosome 8p with poor outcome (reduced survival time); somatic copy number alterations correlated with expression of 27.3% of genes analyzed. We associated expression levels of 10 of these genes with patient survival times in 2 independent cohorts (comprising 319 cases of HCC with mixed etiology) and 3 breast cancer cohorts (637 cases). Among the 10-gene signature, a cluster of 6 genes on 8p, (DLC1, CCDC25, ELP3, PROSC, SH2D4A, and SORBS3) were deleted in HCCs from patients with poor outcomes. In vitro and in vivo analyses indicated that the products of PROSC, SH2D4A, and SORBS3 have tumor-suppressive activities, along with the known tumor suppressor gene, DLC1.
We used an unbiased approach to identify 10 genes associated with HCC progression. These might be used in assisting diagnosis and to stage tumors based on gene expression patterns.
Liver Cancer; Tumor Profiling; Cancer Driver Genes
Myelodysplastic syndrome (MDS) is a complex family of pre-leukemic diseases in which hematopoietic stem cell defects lead to abnormal differentiation in one or more blood lineages. Disease progression is associated with increasing genomic instability and a large proportion of patients go on to develop acute myeloid leukemia. Primarily a disease of the elderly, it can also develop following chemotherapy. We have previously reported that CREB binding protein (Crebbp) heterozygous mice have an increased incidence of hematological malignancies, and others have shown that CREBBP is one of the genes altered by chromosomal translocations found in patients suffering from therapy-related MDS. This led us to investigate whether hematopoietic tumor development in Crebbp+/- mice is preceded by a myelodysplastic phase and whether we could uncover molecular mechanisms that might contribute to its development. We report here that Crebbp+/- mice invariably develop myelodysplastic/myeloproliferative neoplasm within 9-12 months of age. They are also hypersensitive to ionizing radiation and show a marked decrease in PARP1 activity after irradiation. In addition, protein levels of XRCC1 and APEX1, key components of base excision repair machinery, are reduced in unirradiated Crebbp+/- cells or upon targeted knock down of CREBBP levels. Our results thus provide validation of a novel myelodysplastic/myeloproliferative neoplasm mouse model and, more importantly, point to defective repair of DNA damage as a contributing factor to the pathogenesis of this currently incurable disease.
CREBBP; MDS/MPN; DNA repair; radiation hypersensitivity; PARP1
Common microarray and next-generation sequencing data analysis concentrate on tumor subtype classification, marker detection, and transcriptional regulation discovery during biological processes by exploring the correlated gene expression patterns and their shared functions. Genetic regulatory network (GRN) based approaches have been employed in many large studies in order to scrutinize for dysregulation and potential treatment controls. In addition to gene regulation and network construction, the concept of the network modulator that has significant systemic impact has been proposed, and detection algorithms have been developed in past years. Here we provide a unified mathematic description of these methods, followed with a brief survey of these modulator identification algorithms. As an early attempt to extend the concept to new RNA regulation mechanism, competitive endogenous RNA (ceRNA), into a modulator framework, we provide two applications to illustrate the network construction, modulation effect, and the preliminary finding from these networks. Those methods we surveyed and developed are used to dissect the regulated network under different modulators. Not limit to these, the concept of “modulation” can adapt to various biological mechanisms to discover the novel gene regulation mechanisms.
Increasing evidence suggests that chromosomal regions containing microRNAs are functionally important in cancers. Here, we show that genomic loci encoding miR-204 are frequently lost in multiple cancers, including ovarian cancers, pediatric renal tumors, and breast cancers. MiR-204 shows drastically reduced expression in several cancers and acts as a potent tumor suppressor, inhibiting tumor metastasis in vivo when systemically delivered. We demonstrated that miR-204 exerts its function by targeting genes involved in tumorigenesis including brain-derived neurotrophic factor (BDNF), a neurotrophin family member which is known to promote tumor angiogenesis and invasiveness. Analysis of primary tumors shows that increased expression of BDNF or its receptor tropomyosin-related kinase B (TrkB) parallel a markedly reduced expression of miR-204. Our results reveal that loss of miR-204 results in BDNF overexpression and subsequent activation of the small GTPase Rac1 and actin reorganization through the AKT/mTOR signaling pathway leading to cancer cell migration and invasion. These results suggest that microdeletion of genomic loci containing miR-204 is directly linked with the deregulation of key oncogenic pathways that provide crucial stimulus for tumor growth and metastasis. Our findings provide a strong rationale for manipulating miR-204 levels therapeutically to suppress tumor metastasis.
MicroRNAs (miRNAs) are 19-25 nucleotides non-coding RNAs known to have important post-transcriptional regulatory functions. The computational target prediction algorithm is vital to effective experimental testing. However, since different existing algorithms rely on different features and classifiers, there is a poor agreement among the results of different algorithms. To benefit from the advantages of different algorithms, we proposed an algorithm called BCmicrO that combines the prediction of different algorithms with Bayesian Network. BCmicrO was evaluated using the training data and the proteomic data. The results show that BCmicrO improves both the sensitivity and the specificity of each individual algorithm. All the related materials including genome-wide prediction of human targets and a web-based tool are available at http://compgenomics.utsa.edu/gene/gene_1.php.
Despite initial response in adjuvant chemotherapy, ovarian cancer patients treated with the combination of paclitaxel and carboplatin frequently suffer from recurrence after few cycles of treatment, and the underlying mechanisms causing the chemoresistance remain unclear. Recently, The Cancer Genome Atlas (TCGA) research network concluded an ovarian cancer study and released the dataset to the public. The TCGA dataset possesses large sample size, comprehensive molecular profiles, and clinical outcome information; however, because of the unknown molecular subtypes in ovarian cancer and the great diversity of adjuvant treatments TCGA patients went through, studying chemotherapeutic response using the TCGA data is difficult. Additionally, factors such as sample batches, patient ages, and tumor stages further confound or suppress the identification of relevant genes, and thus the biological functions and disease mechanisms.
To address these issues, herein we propose an analysis procedure designed to reduce suppression effect by focusing on a specific chemotherapeutic treatment, and to remove confounding effects such as batch effect, patient's age, and tumor stages. The proposed procedure starts with a batch effect adjustment, followed by a rigorous sample selection process. Then, the gene expression, copy number, and methylation profiles from the TCGA ovarian cancer dataset are analyzed using a semi-supervised clustering method combined with a novel scoring function. As a result, two molecular classifications, one with poor copy number profiles and one with poor methylation profiles, enriched with unfavorable scores are identified. Compared with the samples enriched with favorable scores, these two classifications exhibit poor progression-free survival (PFS) and might be associated with poor chemotherapy response specifically to the combination of paclitaxel and carboplatin. Significant genes and biological processes are detected subsequently using classical statistical approaches and enrichment analysis.
The proposed procedure for the reduction of confounding and suppression effects and the semi-supervised clustering method are essential steps to identify genes associated with the chemotherapeutic response.