A Predictive Model of Adaptive Resistance to BRAF/MEK Inhibitors in Melanoma
Abstract
:1. Introduction
2. Results
2.1. The 18 Proteomic Panel Is Deregulated in the Resistant Human Melanoma Model
2.2. The 13-Risk Panel Predicts the Resistance Stage
2.3. The 13-Risk Score Is Highly Differentiated according to the Resistance Stage
2.4. Signaling Pathways and Therapeutic Sensitivity
2.5. Pathways Score Distribution according to the 13-Risk Score
2.6. The 105. Genes Involved in the Resistance-Related Pathways
2.7. A Novel Model of Therapeutic Resistance
3. Discussion
4. Methods
4.1. Datasets
4.2. The 13-Risk Panel Establishment and 13-Risk Score Calculation
4.3. KEGG Pathways Enrichment Analyses
4.4. Protein-Protein Interaction Network
4.5. Statistical Tests and Plots Design
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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HO-1/HMOX1 |
---|
Endoglin/CD105 |
CXCL8/IL8 |
CTSS |
GRN |
LGALS3 |
BIRC5 |
GM-CSF |
ICAM-1 |
DKK-1 |
SPARC/BM-40 |
CAPG |
P53 |
FGF2 |
ENO2 |
MMP2 |
EGFR |
VIM |
Classifier Markers | |||
---|---|---|---|
PPV | NPV | AUC | |
ENG | 0.636 | 0.684 | 0.633 |
HMOX1 | 0.700 | 0.700 | 0.706 |
ICAM1 | 0.778 | 0.714 | 0.697 |
GRN | 0.778 | 0.714 | 0.674 |
VIM | 0.667 | 0.722 | 0.624 |
TP53 | 0.600 | 0.733 | 0.683 |
MMP2 | 0.750 | 0.778 | 0.796 |
SPARC | 0.769 | 0.824 | 0.76 |
FGF2 | 0.520 | 1.000 | 0.615 |
BIRC5 | 0.750 | 0.682 | 0.606 |
CTSS | 0.522 | 0.857 | 0.593 |
CAPG | 0.667 | 0.667 | 0.588 |
CXCL8 | 0.800 | 0.640 | 0.579 |
DKK1 | 0.500 | 0.833 | 0.552 |
LGALS3 | 0.529 | 0.692 | 0.548 |
ENO2 | 0.625 | 0.636 | 0.511 |
CSF2 | 0.464 | 1.000 | 0.507 |
EGFR | 0.464 | 1.000 | 0.498 |
Kruskal-Wallis Test | Linear Regression | Classifier Markers | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
p-Value | Adjusted p-Value | OR | 95%CI OR | p-Value | Adjusted p-Value | Sensitivity | Specificity | PPV | NPV | AUC | 95%CI AUC | |
GSE99898 | 8.30 × 10−6 | 4.26 × 10−5 | 7.38 | 3.58–15.19 | 8.70× 10−6 | 2.10 × 10−5 | 0.923 | 1.000 | 1.000 | 0.944 | 0.982 | 0.943–1.021 |
GSE61992 | 1.92 × 10−3 | 6.55 × 10−3 | 7.29 | 2.96–17.95 | 4.60 × 10−4 | 1.67 × 10−3 | 0.800 | 1.000 | 1.000 | 0.818 | 0.922 | 0.797–1.047 |
GSE50509 | 8.64 × 10−5 | 2.53 × 10−4 | 3.53 | 2.00–6.25 | 7.43 × 10−5 | 2.34 × 10−4 | 0.793 | 0.800 | 0.852 | 0.727 | 0.833 | 0.709–0.957 |
GSE65185 | 3.40 × 10−4 | 1.07 × 10−3 | 2.94 | 1.70–5.09 | 2.80 × 10−4 | 8.21 × 10−4 | 0.932 | 0.556 | 0.837 | 0.769 | 0.792 | 0.67–0.913 |
GSE77940 | 3.95 × 10−3 | 2.05 × 10−2 | 8163.08 | 2632–25310 | 2.40 × 10−8 | 4.91 × 10−7 | 1.000 | 1.000 | 1.000 | 1.000 | 1 | 1−1 |
FiveDataBase | 1.47 × 10−6 | 3.76 × 10−6 | 2.11 | 1.56–2.86 | 3.37 | 8.63 × 10−6 | 0.814 | 0.571 | 0.735 | 0.678 | 0.716 | 0.639–0.794 |
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Ruiz, E.M.; Alhassan, S.A.; Errami, Y.; Abd Elmageed, Z.Y.; Fang, J.S.; Wang, G.; Brooks, M.A.; Abi-Rached, J.A.; Kandil, E.; Zerfaoui, M. A Predictive Model of Adaptive Resistance to BRAF/MEK Inhibitors in Melanoma. Int. J. Mol. Sci. 2023, 24, 8407. https://doi.org/10.3390/ijms24098407
Ruiz EM, Alhassan SA, Errami Y, Abd Elmageed ZY, Fang JS, Wang G, Brooks MA, Abi-Rached JA, Kandil E, Zerfaoui M. A Predictive Model of Adaptive Resistance to BRAF/MEK Inhibitors in Melanoma. International Journal of Molecular Sciences. 2023; 24(9):8407. https://doi.org/10.3390/ijms24098407
Chicago/Turabian StyleRuiz, Emmanuelle M., Solomon A. Alhassan, Youssef Errami, Zakaria Y. Abd Elmageed, Jennifer S. Fang, Guangdi Wang, Margaret A. Brooks, Joe A. Abi-Rached, Emad Kandil, and Mourad Zerfaoui. 2023. "A Predictive Model of Adaptive Resistance to BRAF/MEK Inhibitors in Melanoma" International Journal of Molecular Sciences 24, no. 9: 8407. https://doi.org/10.3390/ijms24098407
APA StyleRuiz, E. M., Alhassan, S. A., Errami, Y., Abd Elmageed, Z. Y., Fang, J. S., Wang, G., Brooks, M. A., Abi-Rached, J. A., Kandil, E., & Zerfaoui, M. (2023). A Predictive Model of Adaptive Resistance to BRAF/MEK Inhibitors in Melanoma. International Journal of Molecular Sciences, 24(9), 8407. https://doi.org/10.3390/ijms24098407