©The Author(s) 2026.
World J Gastroenterol. Feb 21, 2026; 32(7): 113973
Published online Feb 21, 2026. doi: 10.3748/wjg.v32.i7.113973
Published online Feb 21, 2026. doi: 10.3748/wjg.v32.i7.113973
Figure 6 Multi-algorithm identification of lactate metabolism-related feature genes.
A: Importance of signature genes evaluated in random forest; B: Importance of signature genes generated from gradient boosting machine; C: Optimal lambda tuning and cross-validation in least absolute shrinkage and selection operator; D: Importance of signature genes generated from decision tree; E: Candidate optimal signature genes obtained in adaptive best subset selection; F: Intersection diagram summarizing overlapping genes across the five algorithms, identifying 12 shared lactate metabolism-associated genes. GBM: Gradient boosting machine; DT: Decision tree; ABESS: Adaptive best subset selection; LASSO: Least absolute shrinkage and selection operator.
- Citation: Wu AK, Li JY, Zhang K, Meng M, Wang X, Liu Y, Xie P, Rong WQ, Wu F, Wang HG, Meng X, Wu JX. Lactate metabolism-driven tumor heterogeneity and molecular signatures in intrahepatic cholangiocarcinoma. World J Gastroenterol 2026; 32(7): 113973
- URL: https://www.wjgnet.com/1007-9327/full/v32/i7/113973.htm
- DOI: https://dx.doi.org/10.3748/wjg.v32.i7.113973