BoxCar and Shotgun Proteomic Analyses Reveal Molecular Networks Regulated by UBR5 in Prostate Cancer

Repetitive, low-dose (metronomic; METRO) drug administration of some anticancer agents can overcome drug resistance and increase drug efficacy in many cancers, but the mechanisms are not understood fully. Previously, we showed that METRO dosing of topotecan (TOPO) is more effective than conventional (CONV) dosing in aggressive human prostate cancer (PCa) cell lines and in mouse tumor xenograft models. To gain mechanistic insights into METRO-TOPO activity, in this study we determined the effect of METRO- and CONV-TOPO treatment in a panel of human PCa cell lines representing castration-sensitive/resistant, androgen receptor (+/−), and those of different ethnicity on cell growth and gene expression. Differentially expressed genes (DEGs) were identified for METRO-TOPO therapy and compared to a PCa patient cohort and The Cancer Genome Atlas (TCGA) database. The top five DEGs were SERPINB5, CDKN1A, TNF, FOS, and ANGPT1. Ingenuity Pathway Analysis predicted several upstream regulators and identified top molecular networks associated with METRO dosing, including tumor suppression, anti-proliferation, angiogenesis, invasion, metastasis, and inflammation. Further, the top DEGs were associated with increase survival of PCa patients (TCGA database), as well as ethnic differences in gene expression patterns in patients and cell lines representing African Americans (AA) and European Americans (EA). Thus, we have identified candidate pharmacogenomic biomarkers and novel pathways associated with METRO-TOPO therapy that will serve as a foundation for further investigation and validation of METRO-TOPO as a novel treatment option for prostate cancers.

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Elucidation of the Genomic-Epigenomic Interaction Landscape of Aggressive Prostate Cancer

BioMed Research International ◽

10.1155/2021/6641429 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Tarun Karthik Kumar Mamidi ◽

Jiande Wu ◽

Chindo Hicks

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Association Studies ◽

Unmet Need ◽

The Cancer Genome Atlas ◽

Intermediate Phenotype ◽

Molecular Networks ◽

Signalling Pathways ◽

Genome Wide Association Studies ◽

Aberrant Dna Methylation

Background. Majority of prostate cancer (PCa) deaths are attributed to localized high-grade aggressive tumours which progress rapidly to metastatic disease. A critical unmet need in clinical management of PCa is discovery and characterization of the molecular drivers of aggressive tumours. The development and progression of aggressive PCa involve genetic and epigenetic alterations occurring in the germline, somatic (tumour), and epigenomes. To date, interactions between genes containing germline, somatic, and epigenetic mutations in aggressive PCa have not been characterized. The objective of this investigation was to elucidate the genomic-epigenomic interaction landscape in aggressive PCa to identify potential drivers aggressive PCa and the pathways they control. We hypothesized that aggressive PCa originates from a complex interplay between genomic (both germline and somatic mutations) and epigenomic alterations. We further hypothesized that these complex arrays of interacting genomic and epigenomic factors affect gene expression, molecular networks, and signaling pathways which in turn drive aggressive PCa. Methods. We addressed these hypotheses by performing integrative data analysis combining information on germline mutations from genome-wide association studies with somatic and epigenetic mutations from The Cancer Genome Atlas using gene expression as the intermediate phenotype. Results. The investigation revealed signatures of genes containing germline, somatic, and epigenetic mutations associated with aggressive PCa. Aberrant DNA methylation had effect on gene expression. In addition, the investigation revealed molecular networks and signalling pathways enriched for germline, somatic, and epigenetic mutations including the STAT3, PTEN, PCa, ATM, AR, and P53 signalling pathways implicated in aggressive PCa. Conclusions. The study demonstrated that integrative analysis combining diverse omics data is a powerful approach for the discovery of potential clinically actionable biomarkers, therapeutic targets, and elucidation of oncogenic interactions between genomic and epigenomic alterations in aggressive PCa.

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Evidence for the Presence of Disease-Perturbed Networks in Prostate Cancer Cells by Genomic and Proteomic Analyses: A Systems Approach to Disease

Cancer Research ◽

10.1158/0008-5472.can-04-3218 ◽

2005 ◽

Vol 65 (8) ◽

pp. 3081-3091 ◽

Cited By ~ 71

Author(s):

Biaoyang Lin ◽

James T. White ◽

Wei Lu ◽

Tao Xie ◽

Angelita G. Utleg ◽

...

Keyword(s):

Prostate Cancer ◽

Cancer Cells ◽

Systems Approach ◽

Prostate Cancer Cells ◽

Proteomic Analyses

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202 Discovery of urinary biomarker candidates for prostate cancer based on proteomic analyses

European Urology Supplements ◽

10.1016/s1569-9056(14)60199-8 ◽

2014 ◽

Vol 13 (1) ◽

pp. e202-e202a

Author(s):

Y. Miyazaki ◽

K. Nakayama ◽

S. Sekiya ◽

T. Inoue ◽

T. Goto ◽

...

Keyword(s):

Prostate Cancer ◽

Urinary Biomarker ◽

Proteomic Analyses

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An Integrative Genomics Approach for Associating Genome-Wide Association Studies Information With Localized and Metastatic Prostate Cancer Phenotypes

Biomarker Insights ◽

10.1177/1177271917695810 ◽

2017 ◽

Vol 12 ◽

pp. 117727191769581 ◽

Cited By ~ 2

Author(s):

Chindo Hicks ◽

Ritika Ramani ◽

Oliver Sartor ◽

Ritu Bhalla ◽

Lucio Miele ◽

...

Keyword(s):

Prostate Cancer ◽

Genetic Susceptibility ◽

Metastatic Prostate Cancer ◽

Association Studies ◽

Biological Pathways ◽

Genome Wide Association ◽

Molecular Networks ◽

Genome Wide Association Studies ◽

Disease States ◽

Genome Wide

High-throughput genotyping has enabled discovery of genetic variants associated with an increased risk of developing prostate cancer using genome-wide association studies (GWAS). The goal of this study was to associate GWAS information of patients with primary organ–confined and metastatic prostate cancer using gene expression data and to identify molecular networks and biological pathways enriched for genetic susceptibility variants involved in the 2 disease states. The analysis revealed gene signatures for the 2 disease states and a gene signature distinguishing the 2 patient groups. In addition, the analysis revealed molecular networks and biological pathways enriched for genetic susceptibility variants. The discovered pathways include the androgen, apoptosis, and insulinlike growth factor signaling pathways. This analysis established putative functional bridges between GWAS discoveries and the biological pathways involved in primary organ–confined and metastatic prostate cancer.

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Convergent network effects along the axis of gene expression during prostate cancer progression

Genome Biology ◽

10.1186/s13059-020-02188-9 ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

Konstantina Charmpi ◽

Tiannan Guo ◽

Qing Zhong ◽

Ulrich Wagner ◽

Rui Sun ◽

...

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Cancer Progression ◽

Network Effects ◽

Malignant Tumors ◽

Wide Spectrum ◽

Molecular Networks ◽

Prostate Cancer Progression ◽

Protein Levels ◽

Molecular Layers

Abstract Background Tumor-specific genomic aberrations are routinely determined by high-throughput genomic measurements. It remains unclear how complex genome alterations affect molecular networks through changing protein levels and consequently biochemical states of tumor tissues. Results Here, we investigate the propagation of genomic effects along the axis of gene expression during prostate cancer progression. We quantify genomic, transcriptomic, and proteomic alterations based on 105 prostate samples, consisting of benign prostatic hyperplasia regions and malignant tumors, from 39 prostate cancer patients. Our analysis reveals the convergent effects of distinct copy number alterations impacting on common downstream proteins, which are important for establishing the tumor phenotype. We devise a network-based approach that integrates perturbations across different molecular layers, which identifies a sub-network consisting of nine genes whose joint activity positively correlates with increasingly aggressive tumor phenotypes and is predictive of recurrence-free survival. Further, our data reveal a wide spectrum of intra-patient network effects, ranging from similar to very distinct alterations on different molecular layers. Conclusions This study uncovers molecular networks with considerable convergent alterations across tumor sites and patients. It also exposes a diversity of network effects: we could not identify a single sub-network that is perturbed in all high-grade tumor regions.

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Convergent network effects along the axis of gene expression during prostate cancer progression

10.1101/2020.02.16.950378 ◽

2020 ◽

Cited By ~ 1

Author(s):

Konstantina Charmpi ◽

Tiannan Guo ◽

Qing Zhong ◽

Ulrich Wagner ◽

Rui Sun ◽

...

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Cancer Progression ◽

Network Effects ◽

Malignant Tumors ◽

Wide Spectrum ◽

Molecular Networks ◽

Prostate Cancer Progression ◽

Protein Levels ◽

Molecular Layers

AbstractBackgroundTumor-specific genomic aberrations are routinely determined by high throughput genomic measurements. It remains unclear though, how complex genome alterations affect molecular networks through changing protein levels, and consequently biochemical states of tumor tissues.ResultsHere, we investigated the propagation of genomic effects along the axis of gene expression during prostate cancer progression. For that, we quantified genomic, transcriptomic and proteomic alterations based on 105 prostate samples, consisting of benign prostatic hyperplasia regions and malignant tumors, from 39 prostate cancer patients. Our analysis revealed convergent effects of distinct copy number alterations impacting on common downstream proteins, which are important for establishing the tumor phenotype. We devised a network-based approach that integrates perturbations across different molecular layers, which identified a sub-network consisting of nine genes whose joint activity positively correlated with increasingly aggressive tumor phenotypes and was predictive of recurrence-free survival. Further, our data revealed a wide spectrum of intra-patient network effects, ranging from similar to very distinct alterations on different molecular layers.ConclusionsThis study uncovered molecular networks with remarkably convergent alterations across tumor sites and patients, but it also exposed a diversity of network effects: we could not identify a single sub-network that was perturbed in all high-grade tumor regions.

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PTEN and ERG Molecular Networks in Prostate Cancer

Medical & Surgical Urology ◽

10.4172/2168-9857.1000e116 ◽

2016 ◽

Vol 5 (3) ◽

Author(s):

Athanasios Papatsoris ◽

Charalampos Fragkoulis

Keyword(s):

Prostate Cancer ◽

Molecular Networks

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Interactions between Germline and Somatic Mutated Genes in Aggressive Prostate Cancer

Prostate Cancer ◽

10.1155/2019/4047680 ◽

2019 ◽

Vol 2019 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Tarun Karthik Kumar Mamidi ◽

Jiande Wu ◽

Chindo Hicks

Keyword(s):

Prostate Cancer ◽

Somatic Mutations ◽

Association Studies ◽

Gene Signature ◽

Tumor Formation ◽

Biological Pathways ◽

The Cancer Genome Atlas ◽

Molecular Networks ◽

Genome Wide Association Studies ◽

Somatic Variation

Prostate cancer (PCa) is the most common diagnosed malignancy and the second leading cause of cancer-related deaths among men in the USA. Advances in high-throughput genotyping and next generation sequencing technologies have enabled discovery of germline genetic susceptibility variants and somatic mutations acquired during tumor formation. Emerging evidence indicates that germline variations may interact with somatic events in carcinogenesis. However, the possible oncogenic interactions and cooperation between germline and somatic variation and their role in aggressive PCa remain largely unexplored. Here we investigated the possible oncogenic interactions and cooperation between genes containing germline variation from genome-wide association studies (GWAS) and genes containing somatic mutations from tumor genomes of 305 men with aggressive tumors and 52 control samples from The Cancer Genome Atlas (TCGA). Network and pathway analysis were performed to identify molecular networks and biological pathways enriched for germline and somatic mutations. The analysis revealed 90 functionally related genes containing both germline and somatic mutations. Transcriptome analysis revealed a 61-gene signature containing both germline and somatic mutations. Network analysis revealed molecular networks of functionally related genes and biological pathways including P53, STAT3, NKX3-1, KLK3, and Androgen receptor signaling pathways enriched for germline and somatic mutations. The results show that integrative analysis is a powerful approach to uncovering the possible oncogenic interactions and cooperation between germline and somatic mutations and understanding the broader biological context in which they operate in aggressive PCa.

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