Going beyond the curse of infinite data: unsupervised network learning for oncology data using Ollivier-Ricci curvature.

Genomic Network Analysis in Multiple Myeloma

Here, we used a novel measure of network robustness called Ollivier-Ricci curvature (ORC) to characterize cancers. This innovative geometric network analysis integrates complex gene-product interactions to uncover patterns in cancer biology that were previously undetectable.

ORC designed for -omic data was released as a stand-alone Python package, “ORCO,” available for download here. Details about the ORCO implementation can be found on biorxiv (PDF).

A.K. Simhal, C. Weistuch, K.A. Murgas, D. Grange, J. Zhu, J.H. Oh, R. Elkin, J.O. Deasy. “ORCO: Ollivier-Ricci Curvature-Omics: an unsupervised method for analyzing robustness in biological systems.” 2024. bioRxiv.

Using Ollivier-Ricci curvature (a measure of network robustness), we identified 118 genes previously unassociated with MM that identify a high risk subtype. This paper described a novel eight gene signature associated with high-risk multiple myeloma: BUB1, MCM6, NOSTRIN, PAM, RNF115, SNCAIP, SPRR2A, & WEE1.

A.K. Simhal, K.H. Maclachlan, R. Elkin, J. Zhu, L. Norton, J.O. Deasy, J.H. Oh, S.Z. Usmani, A. Tannenbaum. Gene interaction network analysis in multiple myeloma detects complex immune dysregulation associated with shorter survival. 2023. Blood Cancer Journal.

WEE1 is a strong prognostic marker of high-risk MM

Of all 8 genes, WEE1 was the most prognostic. When researching WEE1 expression further, WEE1 was found to be incredibly prognostic for MM outcomes independent of known MM biomarkers. Additionally, the results show WEE1 expression differentiates outcomes associated with known markers, is upregulated independently of its interacting neighbors, and is associated with dysregulated P53 pathways. This suggests that WEE1 expression levels may have clinical utility in prognosticating outcomes in newly diagnosed MM and may support the application of WEE1 inhibitors to MM preclinical models.

A.K. Simhal, R.S. Firestone, J.H. Oh, V. Avutu, L. Norton, M. Hultcrantz, S.Z. Usmani, K.H. Maclachlan, J.O. Deasy. “High WEE1 expression is independently linked to poor survival in multiple myeloma.” 2024. bioRxiv.

If you work on similar projects, I’d love to hear from you! Please email me at simhala [at] mskcc [dot] org.