Evidence map›Paper›PMID 38779018›Full record

ArticleHeliyon2024

Poria acid inhibit the growth and metastasis of renal cell carcinoma by inhibiting the PI3K/akt/NF-κb signaling pathway.

Haotian Yang, Yue Zhao, Bingnan Ren, Yin Wu, Zhihong Qiu, Yan Cheng, Bo Qiu

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

7 citing papers in PubMed.

  1. Article
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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

7 authors.

Haotian YangDepartment of Pharmacy, Hebei Key Laboratory of Clinical Pharmacy, Hebei General Hospital, Shijiazhuang 050051, China.
Yue ZhaoDepartment of Pharmacy, Hebei Key Laboratory of Clinical Pharmacy, Hebei General Hospital, Shijiazhuang 050051, China.
Bingnan RenDepartment of Pharmacy, Hebei Key Laboratory of Clinical Pharmacy, Hebei General Hospital, Shijiazhuang 050051, China.
Yin WuDepartment of Pharmacy, Hebei Key Laboratory of Clinical Pharmacy, Hebei General Hospital, Shijiazhuang 050051, China.
Zhihong QiuDepartment of Pharmacy, Hebei Key Laboratory of Clinical Pharmacy, Hebei General Hospital, Shijiazhuang 050051, China.
Yan ChengDepartment of Medical Oncology, Hebei General Hospital, Shijiazhuang 050051, China.
Bo QiuDepartment of Pharmacy, Hebei Key Laboratory of Clinical Pharmacy, Hebei General Hospital, Shijiazhuang 050051, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Poria acid (PAC) is a triterpene compound found in Methods: Cell viability and proliferative capacity of normal renal cells and RCC cells were investigated by MTT assay. In addition, 786-O cells were divided into four groups and treated with different concentrations of PAC (0, 20, 40, and 60 μM) for 48 h. Cell scratch test and cell invasion assay were performed to evaluate the effects of PAC on the invasion and migration of RCC cells, respectively. The effects of PAC on apoptosis of RCC cells and expression levels of PI3K/Akt/NF-kB signaling pathway-related biomarkers were investigated using TUNEL staining and Western blotting methods, respectively. Effects of PAC on the inhibitory activity of RCC tumor in mice were evaluated in a 786-O CDX model. Results: The study found that PAC inhibited the viability of RCC cells in a dose-dependent manner, as demonstrated by Conclusions: PAC can effectively suppress the proliferation, invasion and migration of RCC cells, and exhibit anti-tumor effects in RCC model by inhibiting the PI3K/Akt/NF-kB signaling pathway.

Indexed as

MetastasisPI3K/Akt/NF-κB signaling pathwayPoria acid (PAC)ProliferationRenal carcinoma cell (RCC)

Identifiers

PMID38779018
PMCPMC11109894

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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.