bioRxivCancer BiologyPreprint
Pathological angiogenesis RNA network analysis reveals a VEGF-independent gene signature with prognostic power for HER2+ breast cancer
Jhonatas Sirino MonteiroiD, Lilian Costa AlecrimiD, Ricardo J. GiordanoiD, João Carlos SetúbaliD
Abstract
Cancer and many ophthalmic diseases share angiogenesis as a common element for disease progression. Using a well-accepted animal model, we performed network coexpression analysis of mRNA and regulatory RNA to investigate the molecular landscape of pathological angiogenesis in the mouse retina. We assessed the relevance of the RNA coexpression analysis by building gene signatures for breast cancer (METABRIC cohort). Most of the gene signatures were prognostic, and one was prognostic for HER2+ breast cancer, outperforming previously reported HER2+ signatures. Interestingly, it did not include VEGF as variable, and multivariate Cox analysis further highlighted ANGPT2 as a key gene, suggesting that VEGF-independent neovascularization plays an important role in breast cancer. Next, we constructed a network linking mRNAs and regulatory RNAs involved in pathological angiogenesis; this analysis revealed three novel lncRNAs that may play a role in angiogenesis and tumor development. The novel prognostic gene signature and a comprehensive RNA-based regulatory network advance the understanding of angiogenic pathways and provide clinically relevant tools for HER2+ breast cancer stratification. Author SummaryThe formation of new blood vessels by angiogenesis is central in the origin and growth of cancer. Gene signatures are lists of genes that have strong correlation with a disease and/or its development. This study presents a novel angiogenesis gene signature with strong prognostic value for HER2+ breast cancer, an aggressive subtype of this disease. We also discovered novel long noncoding RNA genes that may have important roles in angiogenesis and in tumor development. These findings enhance our understanding of angiogenic mechanisms and offer clinically relevant tools for HER2+ breast cancer diagnosis, potentially guiding more precise therapeutic interventions.
- organism: mouse
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Single-cell mapping links neurogenesis and angiogenesis in aggressive breast cancer
E. Wik, S. Aziz, … L. A. Akslen·bioRxiv·Jan 28, 2022
- Functional Characterization of lncRNA152 as an Angiogenesis-Inhibiting Tumor Suppressor in Triple-Negative Breast Cancers
D. Kim, S. Gadad, … W. L. Kraus·bioRxiv·Feb 9, 2022
- Rapamycin as a potent and selective inhibitor of vascular endothelial growth factor receptor in breast carcinoma
W. F. Wan Abdul rahman, M. S. Muhammad Sakri, … V. Gopalan·bioRxiv·Aug 27, 2020
- LASSO Based Analysis for Prediction of Prognostic Signature Genes Associated with Breast Cancer
S. Guha·bioRxiv·Apr 2, 2024
- A novel signature derived from immunoregulatory and hypoxia genes predicts prognosis in liver and five other cancers
W. H. Chang, D. Forde, A. G. Lai·bioRxiv·Oct 14, 2018
- Laminin α1 orchestrates VEGFA functions in the ecosystem of colorectal carcinoma
E. Mammadova-Bach, T. Rupp, … O. Lefebvre·bioRxiv·Jan 10, 2017