Integrated Transcriptomic, Network Pharmacology, and Machine-Learning Framework Identifies Candidate Phytochemical-Associated Targets in Lung Adenocarcinoma

Awaji Y. Safhi Fahad Y. Sabei Ali Hanbashi Abdulmajeed M. Jali Hamad Al Shahi S. Alshahrani Abdullah Alsalhi O. Madkhali

Sep 2026 · Journal of Pharmaceutical Innovation · Vol 22 · 0 citations · 61 references

TL;DR

CA4 is prioritized as a reproducible LUAD-associated candidate supported by transcriptomic, machine-learning, immune, survival, and docking evidence, but the computational findings do not demonstrate direct phytochemical regulation of CA4 or therapeutic efficacy.

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