Evidence map›Paper›PMID 35280504›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2022

FAM117A Is a New Prognostic Marker of Lung Adenocarcinoma and Predicts Sensitivity to PD0332991.

Chao Wu, Jiajin Zhang, Kuan Wang, Mengjiao Fan, Yi Hu

Open access · hybridAbstract read
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 46% of its field
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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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  4. Review
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 at 2 institutions in 1 country.

Chao WuDepartment of Oncology, Chinese PLA General Hospital, Beijing 100853, China.ORCID https://orcid.org/0000-0002-0671-1650
Jiajin ZhangDepartment of Systems Surgery, Chinese PLA General Hospital, Beijing 100853, China.ORCID https://orcid.org/0000-0002-7270-7545
Kuan WangDepartment of Respiratory Medicine, Fangshan Hospital, Beijing University of Chinese Medicine, Beijing 102400, China.ORCID https://orcid.org/0000-0003-0364-8956
Mengjiao FanDepartment of Oncology, Chinese PLA General Hospital, Beijing 100853, China.ORCID https://orcid.org/0000-0003-1951-0943
Yi HuDepartment of Oncology, Chinese PLA General Hospital, Beijing 100853, China.ORCID https://orcid.org/0000-0001-9319-5692
Chinese PLA General Hospital · CNBeijing University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is the second most common cancer and the leading cause for cancer mortality worldwide. Accelerated cell cycle progression is a well-characterized hallmark for cancer. The present study aims to identify biomarkers for clinical outcomes of lung cancer patients and their sensitivity to CDK inhibitors. To this end, bioinformatics analysis of transcriptome datasets from the Cancer Genome Atlas (TCGA) was first performed to identify survival-related genes; cell proliferation assay, colony formation assay, flow cell cytometry, western blot, EDU labelling, and xenograft models were then used to confirm the potential roles of the identified factors. Our results identified the decreased FAM117A expression as the most significant survival related factor for poor outcome. The cell cycle transition from G1 to S phase was suppressed upon FAM117A overexpression and was promoted upon FAM117A knockdown. Accordingly, the tumor cell growth induced by FAM117A depletion was completely blocked by treatment with PD0332991, which has been approved for cancer therapy. In summary, our work identified FAM117A as a new prognostic marker for poor outcomes of lung cancer patients, predicting sensitivity to PD0332991 treatment.

Identifiers

PMID35280504
PMCPMC8913056
OpenAlexW4214853508

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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.