Robust Cluster Prediction Across Data Types Validates Association of Sex and Therapy Response in GBM
Simple Summary
Abstract
1. Introduction
2. Approach
2.1. Statistical Decision-Making Approach
2.2. Feature Selection for Cluster Prediction
2.3. Robust Ensemble Model Training
3. Results
3.1. Model Cross-Validation Using TCGA-GBM Array-Based Data
3.2. Validation of the Array-Based Model with Three Additional Datasets
3.3. Feature Refinement Improves Generalizability of Classification
3.4. Prediction on the TEMPUS and CPTAC3 RNA-Seq Datasets
3.5. Aggregating Information Rankings Across Datasets
3.6. Single-Cell RNA-Seq Provides the Source of the Signal
4. Discussion
5. Conclusions
6. Methods
6.1. Data Sources
6.2. Gene Microarray Data Processing
6.3. RNA-Seq Processing and Acquisition
6.4. Feature Selection
6.5. Param Search
6.6. Survival Curves
6.7. Classification Task Order
6.8. Feature Alignment
6.9. Single-Cell RNA-Seq
6.10. Code Repository
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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ClusterLabel | GeneA | GeneB | Datasets | Array PD (A < B) | RNA-Seq PD (A < B) |
---|---|---|---|---|---|
cluster1 | POSTN | C1QL1 | 3 | −0.51 | −0.46 |
cluster1 | CD46 | PDGFRA | 3 | −0.6 | −0.36 |
cluster1 | ACSL3 | TF | 3 | −0.51 | −0.42 |
cluster1 | DCX | LGR4 | 2 | 0.61 | 0.38 |
cluster1 | EGFR | PMP2 | 2 | −0.52 | −0.27 |
cluster1 | TMSB15A | LXN | 2 | 0.53 | 0.48 |
cluster1 | TCEAL2 | MYO5C | 2 | 0.5 | 0.44 |
cluster2 | HILPDA | BANF1 | 3 | −0.67 | −0.59 |
cluster2 | NDRG1 | APLP2 | 3 | −0.7 | −0.61 |
cluster2 | IFITM3 | BNIP3 | 2 | 0.57 | 0.53 |
cluster2 | MRFAP1L1 | ZNF395 | 2 | 0.68 | 0.48 |
cluster3 | PDPN | DLL3 | 3 | 0.9 | 0.56 |
cluster3 | TMEM100 | DYNLT3 | 3 | −0.86 | −0.81 |
cluster3 | EMP3 | FERMT1 | 3 | 0.7 | 0.53 |
cluster3 | RBP1 | BMP2 | 2 | 0.88 | 0.64 |
cluster3 | EPHB1 | IGFBP2 | 2 | −0.75 | −0.64 |
cluster3 | NNMT | SH3GL2 | 2 | 0.71 | 0.5 |
cluster4 | P4HA1 | LMO3 | 3 | 0.61 | 0.57 |
cluster4 | CDKN2A | MYC | 3 | −0.51 | −0.3 |
cluster4 | MAOB | VEGFA | 3 | −0.61 | −0.6 |
cluster4 | C21orf62 | SEMA5A | 2 | −0.79 | −0.77 |
cluster4 | APLNR | PHLDA1 | 2 | −0.64 | −0.7 |
cluster5 | GULP1 | CA10 | 3 | 0.69 | 0.69 |
cluster5 | SLC7A11 | NKX2-2 | 3 | 0.57 | 0.41 |
cluster5 | MYO5C | UGT8 | 3 | 0.58 | 0.48 |
cluster5 | C1QL1 | LTBP1 | 3 | −0.56 | −0.49 |
cluster5 | ECM2 | GPR17 | 2 | 0.51 | 0.32 |
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Gibbs, D.L.; Cioffi, G.; Aguilar, B.; Waite, K.A.; Pan, E.; Mandel, J.; Umemura, Y.; Luo, J.; Rubin, J.B.; Pot, D.; et al. Robust Cluster Prediction Across Data Types Validates Association of Sex and Therapy Response in GBM. Cancers 2025, 17, 445. https://doi.org/10.3390/cancers17030445
Gibbs DL, Cioffi G, Aguilar B, Waite KA, Pan E, Mandel J, Umemura Y, Luo J, Rubin JB, Pot D, et al. Robust Cluster Prediction Across Data Types Validates Association of Sex and Therapy Response in GBM. Cancers. 2025; 17(3):445. https://doi.org/10.3390/cancers17030445
Chicago/Turabian StyleGibbs, David L., Gino Cioffi, Boris Aguilar, Kristin A. Waite, Edward Pan, Jacob Mandel, Yoshie Umemura, Jingqin Luo, Joshua B. Rubin, David Pot, and et al. 2025. "Robust Cluster Prediction Across Data Types Validates Association of Sex and Therapy Response in GBM" Cancers 17, no. 3: 445. https://doi.org/10.3390/cancers17030445
APA StyleGibbs, D. L., Cioffi, G., Aguilar, B., Waite, K. A., Pan, E., Mandel, J., Umemura, Y., Luo, J., Rubin, J. B., Pot, D., & Barnholtz-Sloan, J. (2025). Robust Cluster Prediction Across Data Types Validates Association of Sex and Therapy Response in GBM. Cancers, 17(3), 445. https://doi.org/10.3390/cancers17030445