NDLI: Connecting Prognostic Ligand Receptor Signaling Loops in Advanced Ovarian Cancer

Content Provider	PubMed Central
Author	Eng, Kevin H. Ruggeri, Christina
Editor	Müller, Rolf
Copyright Year	2014
Abstract	Understanding cancer cell signal transduction is a promising lead for uncovering therapeutic targets and building treatment-specific markers for epithelial ovarian cancer. To brodaly assay the many known transmembrane receptor systems, previous studies have employed gene expression data measured on high-throughput microarrays. Starting with the knowledge of validated ligand-receptor pairs (LRPs), these studies postulate that correlation of the two genes implies functional autocrine signaling. It is our goal to consider the additional weight of evidence that prognosis (progression-free survival) can bring to prioritize ovarian cancer specific signaling mechanism. We survey three large studies of epithelial ovarian cancers, with gene expression measurements and clinical information, by modeling survival times both categorically (long/short survival) and continuously. We use differential correlation and proportional hazards regression to identify sets of LRPs that are both prognostic and correlated. Of 475 candidate LRPs, 77 show reproducible evidence of correlation; 55 show differential correlation. Survival models identify 16 LRPs with reproduced, significant interactions. Only two pairs show both interactions and correlation (PDGFA PDGFRA and COL1A1 CD44) suggesting that the majority of prognostically useful LRPs act without positive feedback. We further assess the connectivity of receptors using a Gaussian graphical model finding one large graph and a number of smaller disconnected networks. These LRPs can be organized into mutually exclusive signaling clusters suggesting different mechanisms apply to different patients. We conclude that a mix of autocrine and endocrine LRPs influence prognosis in ovarian cancer, there exists a heterogenous mix of signaling themes across patients, and we point to a number of novel applications of existing targeted therapies which may benefit ovarian cancer.
Related Links	http://dx.doi.org/10.1371/journal.pone.0107193
Starting Page	107193
File Format	PDF
ISSN	19326203
e-ISSN	19326203
Journal	PLoS ONE
Issue Number	9
Volume Number	9
Language	English
Publisher	Public Library of Science
Publisher Date	2014-09-01
Access Restriction	Open
Rights Holder	Public Library of Science
Subject Keyword	Biochemistry, Genetics and Molecular Biology(all) Agricultural and Biological Sciences(all) Medicine(all) Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Interleukin 6 Receptor Is an Independent Prognostic Factor and a Potential Therapeutic Target of Ovarian Cancer

Imaging CXCL12-CXCR4 Signaling in Ovarian Cancer Therapy

Plasma miRNAs as Diagnostic and Prognostic Biomarkers for Ovarian Cancer

Genistein Increases Epidermal Growth Factor Receptor Signaling and Promotes Tumor Progression in Advanced Human Prostate Cancer

Tumor Stress-Induced Phosphoprotein1 (STIP1) as a Prognostic Biomarker in Ovarian Cancer

Prognostic Value of Circulating Tumor Cells in Ovarian Cancer: A Meta-Analysis

The MyD88+ Phenotype Is an Adverse Prognostic Factor in Epithelial Ovarian Cancer

Prognostic Value of Cancer Stem Cell Marker Aldehyde Dehydrogenase in Ovarian Cancer: A Meta-Analysis

Correction: The MyD88+ Phenotype Is an Adverse Prognostic Factor in Epithelial Ovarian Cancer

Connecting Prognostic Ligand Receptor Signaling Loops in Advanced Ovarian Cancer

Similar Documents

Interleukin 6 Receptor Is an Independent Prognostic Factor and a Potential Therapeutic Target of Ovarian Cancer

Imaging CXCL12-CXCR4 Signaling in Ovarian Cancer Therapy

Plasma miRNAs as Diagnostic and Prognostic Biomarkers for Ovarian Cancer

Genistein Increases Epidermal Growth Factor Receptor Signaling and Promotes Tumor Progression in Advanced Human Prostate Cancer

Tumor Stress-Induced Phosphoprotein1 (STIP1) as a Prognostic Biomarker in Ovarian Cancer

Prognostic Value of Circulating Tumor Cells in Ovarian Cancer: A Meta-Analysis

The MyD88+ Phenotype Is an Adverse Prognostic Factor in Epithelial Ovarian Cancer

Prognostic Value of Cancer Stem Cell Marker Aldehyde Dehydrogenase in Ovarian Cancer: A Meta-Analysis

Correction: The MyD88+ Phenotype Is an Adverse Prognostic Factor in Epithelial Ovarian Cancer

Connecting Prognostic Ligand Receptor Signaling Loops in Advanced Ovarian Cancer