Evidence map›Paper›PMID 42461333›Full record

ArticleJournal of molecular histology2026

Experimental investigation and network pharmacology-based analysis of the anticancer mechanisms of Fei Jin Sheng formula.

Zhen Yan, Qian Li, Jian-Xiang Chen, Ying-Gen Sheng, Tian Xie

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Article in Journal of molecular histology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zhen YanDepartment of Gerontology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310000, Zhejiang, China.
Qian LiSchool of Pharmacy, Hangzhou Normal University, No. 2318, Yuhangtang Road, Cangqian Street, Yuhang District, Hangzhou, 311121, Zhejiang, China.
Jian-Xiang ChenSchool of Pharmacy, Hangzhou Normal University, No. 2318, Yuhangtang Road, Cangqian Street, Yuhang District, Hangzhou, 311121, Zhejiang, China.
Ying-Gen ShengChinese Medicine Pharmacy, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310000, Zhejiang, China.
Tian XieSchool of Pharmacy, Hangzhou Normal University, No. 2318, Yuhangtang Road, Cangqian Street, Yuhang District, Hangzhou, 311121, Zhejiang, China. xbs@hznu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study involves the evaluation of the Fei Jin Sheng formula (FJS), a well-established traditional Chinese medicine (TCM) treatment for non-small cell lung cancer (NSCLC), aiming to address the heightened mortality rates associated with this form of lung cancer. By examining its multi-targeted routes and activities in vivo, we hope to clarify its complex molecular mechanisms. Liquid chromatography-tandem mass spectrometry and network pharmacology were used to identify FJS components and targets. Using organ histology and bi-weekly weight assessments of tumors and bodies and Lewis tumor model tumors, FJS efficacy and safety were assessed, while immunohistochemistry of tumor tissues was used to elucidate anti-tumor mechanisms. Based on research that had been previously conducted, FJS controls over 30 pathways and targets 15 critical proteins, including the MAPK pathway, in treating NSCLC. In vivo studies demonstrate that FJS reduces tumor proliferation by decreasing expression of ERK1/2, p-ERK1/2, MEK1/2, and p-MEK1/2, without affecting the structure of the liver, spleen, or kidney in mice. FJS is non-toxic and has the potential to treat NSCLC in vivo by inhibiting the MAPK signaling pathway.

Indexed as

Antineoplastic AgentsCarcinoma, Non-Small-Cell LungDrugs, Chinese HerbalLung NeoplasmsNetwork PharmacologyAnimalsCell Line, TumorCell ProliferationHumansMAP Kinase Signaling SystemMiceSignal TransductionTandem Mass SpectrometryAntineoplastic AgentsDrugs, Chinese HerbalComponent identificationFei Jin Sheng formulaMAPK signaling pathwayNetwork pharmacologyNon-small cell lung cancerTranscriptomics

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.