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A novel metabolism-related prognostic gene development and validation in gastric cancer

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Abstract

Background

The importance of metabolism-related alterations in the development of gastric cancer (GC) is increasingly recognized. The present study aimed to identify metabolism-related genes to facilitate prognosis of GC patients.

Methods

Gene expression datasets and clinical information of GC patients were downloaded from TCGA and GEO databases. We scored the enrichment of human metabolism-related pathways (n = 86) in GC samples by GSV, constructed prognostic risk models using LASSO algorithm and multivariate Cox regression analysis, combined with clinical information to construct a nomogram, and finally cis score algorithm to analyze the abundance of immune-related cells in different subtypes. We used Weka software to screen for prognosis-related marker genes and finally validated the expression of the selected genes in clinical cancer patient tissues.

Results

We identified that two GC metabolism-related signatures were strongly associated with OS and the levels of immune cell infiltration. Moreover, a survival prediction model for GC was established based on six GC metabolism-related genes. Time-dependent ROC analysis showed good stability of the risk prediction scoring model. The model was successfully validated in an independent ACRG cohort, and the expression trends of key genes were also verified in the GC tissues of patients. DLX1, LTBP2, FGFR1 and MMP2 were highly expressed in the cluster with poorer prognosis while SLC13A2 and SLCO1B3 were highly expressed in the cluster with better prognosis.

Conclusions

We identified a risk predictive score model based on six metabolism-related genes related to survival, which may serve as prognostic indicators and potential therapeutic targets for GC.

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Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.

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Acknowledgements

Not applicable.

Funding

This study was supported by National Natural Science Foundation of China (No.81973782, No.81704031), Science and Technology Planning Project of Jiangsu Province, China (No. BK20211392), Postgraduate Research & Practice Innovation Program of Jiangsu Province (SJCX22_0749, SJCX21_0692, SJCX21-0740), The Nanjing Medical Science and Technique Development Foundation (ZKX19022), Jiangsu Provincial High level health talent “six one project” (LGY2019005).

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Author notes

  1. Xingxing Zhang, Xu Chen and Jiayun Liu have contributed equally to this work.

Authors and Affiliations

  1. Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, Jiangsu, China

    Xingxing Zhang, Xu Chen, Jiayun Liu, Yaqi Li, Jian Wu, Menglin Chen, Ruijuan Zhang, Xintian Xu & Qingmin Sun

  2. No. 1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu, China

    Xu Chen, Yaqi Li, Menglin Chen & Ruijuan Zhang

  3. National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China

    Tianyi Xu

  4. China National Center for Bioinformation, Beijing, 100101, China

    Tianyi Xu

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  1. Xingxing Zhang
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Contributions

XXZ, XC, YQL, JW, MLC, RJZ, XTX, QMS and TYX: jointly designed the study and drafted the manuscript. JYL: was responsible for the collection of clinical specimens. JW, QMS, and TYX: supervised the study. All the authors contributed to the data collection, analysis and interpretation, manuscript writing and revision. All the authors read and approved the final manuscript.

Corresponding authors

Correspondence to Tianyi Xu or Qingmin Sun.

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Conflict of interest

The authors declare no potential conflicts of interest.

Ethics approval

This retrospective observational study involving human participants was in accordance with the ethical standards of the institutional research committee. The Ethics Committee of the Affiliated Hospital of Nanjing University of Traditional Chinese Medicine (Jiangsu Provincial Hospital of Traditional Chinese Medicine) approved this study (No. 20221NL18702).

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Zhang, X., Chen, X., Liu, J. et al. A novel metabolism-related prognostic gene development and validation in gastric cancer. Clin Transl Oncol 25, 447–459 (2023). https://doi.org/10.1007/s12094-022-02958-w

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