82 research outputs found
Detecting Cancer Outlier Genes with Potential Rearrangement Using Gene Expression Data and Biological Networks
Genomic biomarker discovery in disease progression and therapy response in bladder cancer utilizing machine learning
Cancer in all its forms of expression is a major cause of death. To identify the genomic reason behind cancer, discovery of biomarkers is needed. In this paper, genomic data of bladder cancer are examined for the purpose of biomarker discovery. Genomic biomarkers are indicators stemming from the study of the genome, either at a very low level based on the genome sequence itself, or more abstractly such as measuring the level of gene expression for different disease groups. The latter method is pivotal for this work, since the available datasets consist of RNA sequencing data, transformed to gene expression levels, as well as data on a multitude of clinical indicators. Based on this, various methods are utilized such as statistical modeling via logistic regression and regularization techniques (elastic-net), clustering, survival analysis through Kaplan–Meier curves, and heatmaps for the experiments leading to biomarker discovery. The experiments have led to the discovery of two gene signatures capable of predicting therapy response and disease progression with considerable accuracy for bladder cancer patients which correlates well with clinical indicators such as Therapy Response and T-Stage at surgery with Disease Progression in a time-to-event manner
ERG protein expression reflects hormonal treatment response and is associated with Gleason score and prostate cancer specific mortality
Abstract Background: ERG (ETS regulated gene) protein expression has been shown to reflect ERG genomic rearrangements in prostate cancer (PCA). However, ERG protein expression prognostic value has not been yet investigated. Design: ERG protein expression was investigated in a cohort of 312 men with PCA diagnosed in transurethral resection of the prostate. Results: ERG expression was detected in 76/293 (25.9%) of patients. Overall ERG expression was associated with Gleason score (GS) (p < 0.0001), tumour volume (p = 0.04) and with cancer specific mortality (p = 0.15). Low ERG intensity was significantly associated with higher GS (p = 0.02) and marginally with cancer specific mortality (p = 0.11). The association with caner specific mortality was more significant in patients without any hormonal manipulation (p = 0.02). Multivariate Cox model using GS, tumour volume and ERG intensity to predict time to cancer specific death yielded a marginally significant effect for high versus low ERG protein expression (hazard ratio (HR) = 0.36; 95% confidence interval (CI): 0.10-1.38; p = 0.14) and a non-significant effect for GS >7 (HR = 4.85; 95% CI: 0.48, 48.65; 0959-8049/$ -see front matter
High Serine-arginine Protein Kinase 1 Expression with PTEN Loss Defines Aggressive Phenotype of Prostate Cancer Associated with Lethal Outcome and Decreased Overall Survival
Background: Serine-arginine protein kinase 1 (SRPK1) has been implicated in prostate cancer (PCa) progression. However, its prognostic value and association with ERG and PTEN expression, two of the most common genetic alterations, have not been explored fully.
Objective: We assessed the prognostic value of SRPK1 in association with ERG and PTEN in a cohort of patients managed nonsurgically by androgen deprivation therapy (ADT) for advanced disease.
Design, setting, and participants: The study cohort consisted of men diagnosed with PCa by transurethral resection of the prostate (TURP; n = 480). The patients were divided into three main groups: incidental (patients with Gleason score [GS] ≤7 with no prior ADT), advanced (patients with GS ≥8 with no prior ADT), and castrate-resistant PCa (patients with prior ADT). Outcome measurements and statistical analysis: A total of 480 TURP samples were assessed by immunohistochemistry for SRPK1, ERG, and PTEN, and results were correlated with Gleason grade group (GG), overall survival (OS), and PCa-specific mortality (PCSM).
Results and limitations: High SRPK1 expression was noted in 105/455 (23%) available patient cores. Expression of SRPK1 was associated with Gleason grade grouping (p \u3c 0.0001) with high expression detected in 22/74 (33%) with GG 5. High SRPK1 was not associated with ERG positivity (p = 0.18) but was significantly associated with PTEN intensity (p = 0.001). High SRPK1 was associated with OS (hazard ratio [HR] 1.99; confidence interval [CI]: 1.57–2.54, p \u3c 0.0001) and PCSM (HR 1.64; CI: 1.19–2.26, p \u3c 0.002). Adjusting for Gleason score, patients with high SRPK1 and negative PTEN had the worst clinical outcome for both OS and PCSM compared with other patients (p \u3c 0.0001, HR: 3.02; CI: 1.87–4.88 and HR: 6.40, CI: 3.19–12.85, respectively).
Conclusions: High SRPK1 is associated with worse OS and PCSM. Moreover, patients with high SRPK1 expression and loss of PTEN had the worst clinical outcome for OS and cancer-specific mortality. Combined status of SRPK1 and PTEN may provide added value in stratifying patients into various prognostic groups.
Patient summary: The expression of serine-arginine protein kinase 1 (SRPK1) combined with PTEN has a significant prognostic role in prostate cancer patients. Patients with high SRPK1 expression and negative PTEN had the worst clinical outcome for overall survival and cancer-specific mortality
Serrate RNA effector molecule (SRRT) is associated with prostate cancer progression and is a predictor of poor prognosis in lethal prostate cancer
Arsenite-resistance protein 2, also known as serrate RNA effector molecule (ARS2/SRRT), is known to be involved in cellular proliferation and tumorigenicity. However, its role in prostate cancer (PCa) has not yet been established. We investigated the potential role of SRRT in 496 prostate samples including benign, incidental, advanced, and castrate-resistant patients treated by androgen deprivation therapy (ADT). We also explored the association of SRRT with common genetic aberrations in lethal PCa using immunohistochemistry (IHC) and performed a detailed analysis of SRRT expression using The Cancer Genome Atlas (TCGA PRAD) by utilizing RNA-seq, clinical information (pathological T category and pathological Gleason score). Our findings indicated that high SRRT expression was significantly associated with poor overall survival (OS) and cause-specific survival (CSS). SRRT expression was also significantly associated with common genomic aberrations in lethal PCa such as PTEN loss, ERG gain, mutant TP53, or ATM. Furthermore, TCGA PRAD data revealed that high SRRT mRNA expression was significantly associated with higher Gleason scores, PSA levels, and T pathological categories. Gene set enrichment analysis (GSEA) of RNAseq data from the TCGA PRAD cohort indicated that SRRT may play a potential role in regulating the expression of genes involved in prostate cancer aggressiveness. Conclusion: The current data identify the SRRT's potential role as a prognostic for lethal PCa, and further research is required to investigate its potential as a therapeutic target.Prostate Cancer Foundation Young Investigator Award ; Prostate Cancer Canada ; Canadian Cancer Society (CCS
Filamin A regulates focal adhesion disassembly and suppresses breast cancer cell migration and invasion
The actin cross-linking protein filamin A reduces migration, invasion, and metastasis of breast cancer cells
ING3 promotes prostate cancer growth by activating the androgen receptor
Background The androgen receptor (AR) is a major driver of prostate cancer, and increased AR levels and co-activators of the receptor promote the development of prostate cancer. INhibitor of Growth (ING) proteins target lysine acetyltransferase or lysine deacetylase complexes to the histone H3K4Me3 mark of active transcription, to affect chromatin structure and gene expression. ING3 is a stoichiometric member of the TIP60 lysine acetyltransferase complex implicated in prostate cancer development. Methods Biopsies of 265 patients with prostate cancer were stained for ING3, pan-cytokeratin, and DNA. LNCaP and C4-2 androgen-responsive cells were used for in vitro assays including immunoprecipitation, western blotting, Luciferase reporter assay and quantitative polymerase chain reaction. Cell viability and migration assays were performed in prostate cancer cell lines using scrambled siRNA or siRNA targeting ING3. Results We find that ING3 levels and AR activity positively correlate in prostate cancer. ING3 potentiates androgen effects, increasing expression of androgen-regulated genes and androgen response element-driven reporters to promote growth and anchorage-independent growth. Conversely, ING3 knockdown inhibits prostate cancer cell growth and invasion. ING3 activates the AR by serving as a scaffold to increase interaction between TIP60 and the AR in the cytoplasm, enhancing receptor acetylation and translocation to the nucleus. Activation is independent of ING3's ability to target the TIP60 complex to H3K4Me3, identifying a previously unknown chromatin-independent cytoplasmic activity for ING3. In agreement with in vitro observations, analysis of The Cancer Genome Atlas (TCGA) data (n = 498) and a prostate cancer tissue microarray (n = 256) show that ING3 levels are higher in aggressive prostate cancers, with high levels of ING3 predicting shorter patient survival in a low AR subgroup. Including ING3 levels with currently used indicators such as the Gleason score provides more accurate prognosis in primary prostate cancer. Conclusions In contrast to the majority of previous reports suggesting tumor suppressive functions in other cancers, our observations identify a clear oncogenic role for ING3, which acts as a co-activator of AR in prostate cancer. Data from TCGA and our previous and current tissue microarrays suggest that ING3 levels correlate with AR levels and that in patients with low levels of the receptor, ING3 level could serve as a useful prognostic biomarker
Identification of a novel truncating PALB2 mutation and analysis of its contribution to early-onset breast cancer in French-Canadian women
Abstract
Background
PALB2 has recently been identified as a breast cancer susceptibility gene. PALB2 mutations are rare causes of hereditary breast cancer but may be important in countries such as Finland where a founder mutation is present. We sought to estimate the contribution of PALB2 mutations to the burden of breast cancer in French Canadians from Quebec.
Methods
We screened all coding exons of PALB2 in a sample of 50 French-Canadian women diagnosed with either early-onset breast cancer or familial breast cancer at a single Montreal hospital. The genetic variants identified in this sample were then studied in 356 additional women with breast cancer diagnosed before age 50 and in 6,448 newborn controls.
Results
We identified a single protein-truncating mutation in PALB2 (c.2323 C>T, resulting in Q775X) in 1 of the 50 high-risk women. This variant was present in 2 of 356 breast cancer cases and in none of 6,440 newborn French-Canadian controls (P = 0.003). We also identified two novel new non-synonymous single nucleotide polymorphisms in exon 4 of PALB2 (c.5038 A>G [I76V] and c.5156 G>T [G115V]). G115V was found in 1 of 356 cases and in 15 of 6,442 controls (P = 0.6). The I76V variant was not identified in either the extended case series or the controls.
Conclusion
We have identified a novel truncating mutation in PALB2. The mutation was found in approximately 0.5% of unselected French-Canadian women with early-onset breast cancer and appears to have a single origin. Although mutations are infrequent, PALB2 can be added to the list of breast cancer susceptibility genes for which founder mutations have been identified in the French-Canadian population
Detecting Cancer Outlier Genes with Potential Rearrangement Using Gene Expression Data and Biological Networks
Gene alterations are a major component of the landscape of tumor genomes. To assess the significance of these alterations in the development of prostate cancer, it is necessary to identify these alterations and analyze them from systems biology perspective. Here, we present a new method (EigFusion) for predicting outlier genes with potential gene rearrangement. EigFusion demonstrated excellent performance in identifying outlier genes with potential rearrangement by testing it to synthetic and real data to evaluate performance. EigFusion was able to identify previously unrecognized genes such as FABP5 and KCNH8 and confirmed their association with primary and metastatic prostate samples while confirmed the metastatic specificity for other genes such as PAH, TOP2A, and SPINK1. We performed protein network based approaches to analyze the network context of potential rearranged genes. Functional gene rearrangement Modules are constructed by integrating functional protein networks. Rearranged genes showed to be highly connected to well-known altered genes in cancer such as AR, RB1, MYC, and BRCA1. Finally, using clinical outcome data of prostate cancer patients, potential rearranged genes demonstrated significant association with prostate cancer specific death.Peer Reviewe
Detecting Cancer Outlier Genes with Potential Rearrangement Using Gene Expression Data and Biological Networks
Article deposited according to Hindawi Publishing Corporation policy for Advances in Bioinformatics: http://www.hindawi.com/journals/abi/guidelines/, August 22, 2012.YesFunding provided by the Open Access Authors Fund
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