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

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Konstantina Charmpi ◽  
Tiannan Guo ◽  
Qing Zhong ◽  
Ulrich Wagner ◽  
Rui Sun ◽  
...  

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.

Author(s):  
Konstantina Charmpi ◽  
Tiannan Guo ◽  
Qing Zhong ◽  
Ulrich Wagner ◽  
Rui Sun ◽  
...  

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.


2018 ◽  
Vol 40 (7) ◽  
pp. 893-902 ◽  
Author(s):  
Teresa T Liu ◽  
Jonathan A Ewald ◽  
Emily A Ricke ◽  
Robert Bell ◽  
Colin Collins ◽  
...  

Abstract Detailed mechanisms involved in prostate cancer (CaP) development and progression are not well understood. Current experimental models used to study CaP are not well suited to address this issue. Previously, we have described the hormonal progression of non-tumorigenic human prostate epithelial cells (BPH1) into malignant cells via tissue recombination. Here, we describe a method to derive human cell lines from distinct stages of CaP that parallel cellular, genetic and epigenetic changes found in patients with cancers. This BPH1-derived Cancer Progression (BCaP) model represents different stages of cancer. Using diverse analytical strategies, we show that the BCaP model reproduces molecular characteristics of CaP in human patients. Furthermore, we demonstrate that BCaP cells have altered gene expression of shared pathways with human and transgenic mouse CaP data, as well as, increasing genomic instability with TMPRSS2–ERG fusion in advanced tumor cells. Together, these cell lines represent a unique model of human CaP progression providing a novel tool that will allow the discovery and experimental validation of mechanisms regulating human CaP development and progression. This BPH1-derived Cancer Progression (BCaP) model represents different stages of cancer. The BCaP model reproduces molecular characteristics of prostate cancer. The cells have altered gene expression with TMPRSS2-ERG fusion representing a unique model for prostate cancer progression.


BMC Urology ◽  
2005 ◽  
Vol 5 (1) ◽  
Author(s):  
Christy A Rothermund ◽  
Velliyur K Gopalakrishnan ◽  
James D Eudy ◽  
Jamboor K Vishwanatha

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 5017-5017
Author(s):  
R. B. Jenkins ◽  
T. Nakagawa ◽  
T. Kollmeyer ◽  
B. Morlan ◽  
E. Bergstrahl ◽  
...  

5017 Background: The majority of men with prostate cancer are diagnosed with cancers with low mortality. Such men are treated with radical prostatectomy, external beam radiotherapy, or brachytherapy and followed by serum PSA evaluations. Some men with a rising PSA therapy will have local recurrence or metastasis, but many will have no other evidence of recurrent disease other than a rising PSA. The PSA doubling time has been used to determine which of these men deserve adjuvant hormonal ablation, radiation therapy, or observation. We hypothesize that additional biomarkers will predict which men with a rising PSA post-definitive therapy would benefit from additional therapy. Methods: We designed a custom array containing 526 RNA targets whose expression has been reported to be altered in association with prostate cancer progression. We included targets from Mayo Clinic prostate cancer research. Together with a second commercial array, 530 genes implicated in prostate cancer progression and 420 other cancer-related genes were evaluated. A case-control design was used to test the association of the expression results with outcome. Cases were men post-radical prostatectomy who developed systemic progression within 5 years after PSA recurrence (N=213). Controls were matched men post-radical prostatectomy with PSA recurrence but no evidence of clinical progression within 5 years (N=213). Results: Of 426 eligible patients, paraffin blocks were available on 418 (98.1%). RNA was prepared from all 418 blocks, and both arrays were both successful on 405 (96.9%) RNAs. Upon univariate analysis, 40 genes were highly significantly over- or under-expressed in the cases versus controls (1x10-22 < p < 1x10-7). Recursive partitioning (RP) selected 4 genes (TPX2, FAM13C1, TOPO2A and TSP2) that distinguished cases from controls. Random Forest analysis selected 24 genes (including 3 of the RP 4). A multivariable ROC analysis using these 24 genes generated an AUC of 0.80 (95% CI: 0.75–0.84). Conclusions: A specific gene expression pattern was significantly associated with systemic progression after PSA recurrence. The measurement of gene expression pattern may be useful for determining which men may benefit from additional therapy after PSA recurrence. No significant financial relationships to disclose.


2011 ◽  
Vol 106 (1) ◽  
pp. 157-165 ◽  
Author(s):  
S E T Larkin ◽  
S Holmes ◽  
I A Cree ◽  
T Walker ◽  
V Basketter ◽  
...  

Author(s):  
Joonas Uusi-Mäkelä ◽  
Ebrahim Afyounian ◽  
Francesco Tabaro ◽  
Tomi Häkkinen ◽  
Alessandro Lussana ◽  
...  

AbstractAberrant oncogene functions and structural variation alter the chromatin structure in cancer cells. While gene regulation by chromatin states has been studied extensively, chromatin accessibility and its relevance in aberrant gene expression during prostate cancer progression is not well understood. Here, we report a genome-wide chromatin accessibility analysis of clinical tissue samples of benign prostatic hyperplasia (BPH), untreated primary prostate cancer (PC) and castration-resistant prostate cancer (CRPC) and integrative analysis with transcriptome, methylome, and proteome profiles of the same samples to uncover disease-relevant regulatory elements and their association to altered gene expression during prostate cancer progression. While promoter accessibility is consistent during disease initiation and progression, at distal sites chromatin accessibility is variable enabling transcription factors (TFs) binding patterns that are differently activated in different patients and disease stages. We identify consistent progression-related chromatin alterations during the progression to CRPC. By studying the TF binding patterns, we demonstrate the activation and suppression of androgen receptor-driven regulatory programs during PC progression and identify complementary TF regulatory modules characterized by e.g. MYC and glucocorticoid receptor. By correlation analysis we assign at least one putative regulatory region for 62% of genes and 85% of proteins differentially expressed during prostate cancer progression. Taken together, our analysis of the chromatin landscape in PC identifies putative regulatory elements for the majority of cancer-associated genes and characterizes their impact on the cancer phenotype.


Sign in / Sign up

Export Citation Format

Share Document