Header

UZH-Logo

Maintenance Infos

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


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.

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.

Statistics

Citations

Altmetrics

Downloads

2 downloads since deposited on 22 Jan 2021
2 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Urological Clinic
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Life Sciences > Ecology, Evolution, Behavior and Systematics
Life Sciences > Genetics
Life Sciences > Cell Biology
Language:English
Date:14 December 2020
Deposited On:22 Jan 2021 09:14
Last Modified:01 Feb 2021 16:27
Publisher:BioMed Central
ISSN:1474-7596
OA Status:Gold
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1186/s13059-020-02188-9
PubMed ID:33317623

Download

Gold Open Access

Download PDF  'Convergent network effects along the axis of gene expression during prostate cancer progression'.
Preview
Content: Published Version
Filetype: PDF
Size: 4MB
View at publisher
Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)