Evidence map›Paper›PMID 39768999›Full record

ArticleInternational journal of molecular sciences2024

Integrated Proteomics and Machine Learning Approach Reveals PYCR1 as a Novel Biomarker to Predict Prognosis of Sinonasal Squamous Cell Carcinoma.

Watcharapong Panthong, Chamsai Pientong, Thawaree Nukpook, Sittiruk Roytrakul, Yodying Yingchutrakul, Watchareporn Teeramatwanich, Sirinart Aromseree, Tipaya Ekalaksananan

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. [Research Progress on the Role and Mechanisms of PYCR1 
in Tumorigenesis and Progression].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2026
    Review
  2. Article
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

8 authors.

Watcharapong PanthongDepartment of Microbiology, Faculty of Medicine, Khon Kaen University, Mueang Khon Kaen, Khon Kaen 40002, Thailand.ORCID 0009-0003-8599-7216
Chamsai PientongDepartment of Microbiology, Faculty of Medicine, Khon Kaen University, Mueang Khon Kaen, Khon Kaen 40002, Thailand.ORCID 0000-0003-2797-043X
Thawaree NukpookDepartment of Microbiology, Faculty of Medicine, Khon Kaen University, Mueang Khon Kaen, Khon Kaen 40002, Thailand.
Sittiruk RoytrakulFunctional Ingredients and Food Innovation Research Group, National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Khlong Luang, Pathum Thani 12120, Thailand.ORCID 0000-0003-3696-8390
Yodying YingchutrakulFunctional Ingredients and Food Innovation Research Group, National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Khlong Luang, Pathum Thani 12120, Thailand.ORCID 0000-0003-0701-4205
Watchareporn TeeramatwanichDepartment of Otorhinolaryngology, Faculty of Medicine, Khon Kaen University, Mueang Khon Kaen, Khon Kaen 40002, Thailand.ORCID 0000-0003-2095-5747
Sirinart AromsereeDepartment of Microbiology, Faculty of Medicine, Khon Kaen University, Mueang Khon Kaen, Khon Kaen 40002, Thailand.
Tipaya EkalaksanananDepartment of Microbiology, Faculty of Medicine, Khon Kaen University, Mueang Khon Kaen, Khon Kaen 40002, Thailand.ORCID 0000-0003-2406-2356

Funding

Faculty of Medicine, Khon Kaen University, Thailand IN64212Research and Graduate Studies, Khon Kaen University RP67-1-001Thailand Research Fund through the Royal Golden Jubilee Ph.D. Program PHD/0157/2561
6 · The paper itself

Abstract

Sinonasal squamous cell carcinoma (SNSCC) is a rare tumor with a high 5-year mortality rate. However, proteomic technologies have not yet been utilized to identify SNSCC-associated proteins, which could be used as biomarkers. In this study, we aimed to discover a biomarker to predict SNSCC patients using proteomic analysis integrated with machine learning models. Support vector machine (SVM), logistic regression (LR), random forest (RF), and gradient boost (GB) classifiers were developed to predict SNSCC based on proteomic profiles of SNSCC compared with nasal polyps (NP) as control. Seventeen feature proteins were found in all models, indicating possible biomarkers for SNSCC. Analysis of gene expression across multiple cancer types and their associations with cancer stage and patient survival in the TCGA-HNSC dataset identified a PYCR1 and MYO1B gene that could be a potential tumor-associated marker. The expression of PYCR1 was confirmed by RT-qPCR in SNSCC tissues, and its high expression was associated with poor overall survival, indicating PYCR1 as a potential tumor-associated biomarker to predict the prognosis of SNSCC.

Indexed as

Biomarkers, TumorCarcinoma, Squamous CellMachine LearningProteomicsAgedFemaleGene Expression Regulation, NeoplasticHumansMaleMiddle AgedParanasal Sinus NeoplasmsPrognosisBiomarkers, Tumorbiomarkermachine learningprognosisproteomicsinonasal squamous cell carcinoma

Identifiers

PMID39768999
PMCPMC11675701

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.