Evidence map›Paper›PMID 42674820›Full record

ArticleCancer genomics & proteomics

Multi-level Transcriptomic and Machine-learning Analyses Identify

Dahlak Daniel Solomon, Hui-Ru Lin, Yung-Kuo Lee, Sachin Kumar, Ching-Chung Ko, Kai-Fu Chang, Chung-Hsien Lin, Ngoc Uyen Nhi Nguyen, DO Thi Minh Xuan, Neethu Palekkode and 2 more

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Article in Cancer genomics & proteomics. 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

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

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

12 authors.

Dahlak Daniel SolomonPh.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science, Taipei Medical University, Taipei, Taiwan, R.O.C.
Hui-Ru LinNursing Department, Kaohsiung Armed Forces General Hospital, Kaohsiung, Taiwan, R.O.C.
Yung-Kuo LeeInstitute of Medical Science and Technology, National Sun Yat-sen University, Kaohsiung, Taiwan, R.O.C.
Sachin KumarPh.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science, Taipei Medical University, Taipei, Taiwan, R.O.C.
Ching-Chung KoDepartment of Medical Imaging, Chi-Mei Medical Center, Tainan, Taiwan, R.O.C.
Kai-Fu ChangInstitute of Medical Science and Technology, National Sun Yat-sen University, Kaohsiung, Taiwan, R.O.C.
Chung-Hsien LinInstitute of Medical Science and Technology, National Sun Yat-sen University, Kaohsiung, Taiwan, R.O.C.
Ngoc Uyen Nhi NguyenCenter for Regenerative Medicine, University of South Florida Health Heart Institute, Tampa, FL, U.S.A.
DO Thi Minh XuanFaculty of Pharmacy, Van Lang University, Binh Loi Trung Ward, Ho Chi Minh City, Vietnam.
Neethu PalekkodePh.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science, Taipei Medical University, Taipei, Taiwan, R.O.C.
Chih-Yang WangPh.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science, Taipei Medical University, Taipei, Taiwan, R.O.C.; chihyang@tmu.edu.tw mysing@gmail.com.
Yun-Shih LinDepartment of Psychiatry, Kaohsiung Armed Forces General Hospital, Kaohsiung, Taiwan, R.O.C. chihyang@tmu.edu.tw mysing@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

aimLung adenocarcinoma (LUAD) exhibits substantial molecular heterogeneity and variable clinical outcomes, highlighting the need for biomarkers that reflect core tumor biological processes. Centrosome-associated proteins regulate mitotic fidelity and genome stability, yet their roles in LUAD remain incompletely defined. In this study, we systematically characterized mitotic spindle organizing protein 1 ( MATERIALS AND

methodsWe performed integrated analyses combining bulk transcriptomic datasets, survival modeling, gene set enrichment, immune deconvolution, machine-learning based prognostic modeling, and single-cell RNA sequencing. Expression patterns and clinical associations of

results

conclusion

Indexed as

Adenocarcinoma of LungBiomarkers, TumorCell Cycle ProteinsCentrosomal Associated ProteinsLung NeoplasmsMachine LearningMicrotubule-Associated ProteinsTranscriptomeCell ProliferationGene Expression ProfilingGene Expression Regulation, NeoplasticHumansPrognosisBiomarkers, TumorCell Cycle ProteinsCentrosomal Associated ProteinsMicrotubule-Associated ProteinsNUSAP1 protein, humancell cycleLung adenocarcinomamachine learningMZT1single-cell RNA sequencing

Identifiers

PMID42674820
PMCPMC13531167

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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.