Cilia at the Crossroads of Tumor Treating Fields and Chemotherapy

Mondrian Map: Piet Mondrian's Abstraction for Differential Pathway Analysis

Motivation

Visualizing complex biological networks is a significant challenge, as traditional tools often struggle to represent data clearly and intuitively. Drawing inspiration from Piet Mondrian's abstract art style, we introduce Mondrian Map, a novel visualization tool that transforms the complexity of biological networks into a more organized, meaningful, and aesthetically appealing form.

Results

In our case study of glioma progression, Mondrian Map reveals distinct pathway patterns across multiple patient profiles at different time points. Afterwards, the significance of these distinctive pathways in glioblastoma multiforme development is validated by recent literature. Mondrian Map's visually intuitive representation of complex biological networks enables researchers to easily identify crucial pathways and potential therapeutic targets. Moreover, The potential applications of Mondrian Map extend beyond biology, making it a versatile tool across domains.

Availability and Implementation

The code was implemented in Python version 3.10 and is available through GitHub (github.com/fuad021/mondrian-map). The datasets used in this paper were retrieved from Glioma Longitudinal AnalySiS (GLASS) consortium.

Clinical and molecular analysis of cilia-associated gene signature for prognostic prediction in glioma

PURPOSE

Glioma is a highly malignant and unfavorable cancer in the brain. Recent evidence highlights the vital role of cilia-related pathways as novel regulators of glioma development. However, the prognostic potential of ciliary pathways in glioma is still ambiguous. In this study, we aim to construct a gene signature using cilia-related genes to facilitate the prognostication of glioma.

METHODS

A multi-stage approach was employed to build the ciliary gene signature for prognostication of glioma. The strategy involved the implementation of univariate, LASSO, and stepwise multivariate Cox regression analyses based on TCGA cohort, followed by independent validation in CGGA and REMBRANDT cohort. The study further revealed molecular differences at the genomic, transcriptomic, and proteomic levels between distinct groups.

RESULTS

A prognostic tool utilizing a 9-gene signature based on ciliary pathways was developed to assess the clinical outcomes of glioma patients. The risk scores generated by the signature demonstrated a negative correlation with patient survival rates. The validation of the signature in an independent cohort reinforced its prognostic capabilities. In-depth analysis uncovered distinctive molecular characteristics at the genomic, transcriptomic, and protein-interactive levels in the high- and low-risk groups. Furthermore, the gene signature was able to predict the sensitivity of glioma patients to conventional chemotherapeutic drugs.

CONCLUSION

This study has established the utility of a ciliary gene signature as a reliable prognostic predictor of glioma patient survival. Findings not only enhance our comprehension of the intricate molecular mechanisms of cilia pathways in glioma, but also hold significant clinical implications in directing chemotherapeutic strategies.