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<p>Weight loss is a firmly established negative survival factor for individuals with cancer, yet effective biomarkers and targeted therapies remain elusive. In this study, we collected skeletal muscle, noncancerous, and cancerous tissues using the Illumina EPIC array to identify conserved DNA methylation probes associated with weight loss following bariatric surgery. Next, the consistency of the probes is evaluated and then the probes are integrated into a generalizable pathway enrichment score. Our results emphasize the gene-centered design, identifying <i>KCNB1</i>, <i>PEAK1</i>, <i>SCG5</i>, and <i>TNIK</i> as key targets of DNA methylation, as confirmed by mouse phenotype data and druggability resources. Moreover, an illustrative test of protein abundance in cell lines is conducted. Utilizing the Clinical Proteomic Tumor Analysis Consortium data, a positive correlation is established between the chromosomal instability scores and our generated score in tumor tissues. In addition, considering these correlation findings, the presence of identifiable methylation blocks in the co-occurring gain samples. Our findings also suggest that upstream molecular drivers may influence this pathway enrichment score, potentially leading to dysregulated methylation associated with weight loss. In summary, DNA methylation analysis not only identifies functional targets but also uncovers new gene-disease connections.</p>

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Weight-loss associated DNA methylation patterns: targetable biomarkers and pathway insights

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月22日

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  • Longjin Zeng,
  • Xu Chen,
  • Longyao Zhang,
  • Yaxian Qi,
  • Lingchen Li,
  • Chenrui Yin,
  • Jianguo Sun

摘要

Weight loss is a firmly established negative survival factor for individuals with cancer, yet effective biomarkers and targeted therapies remain elusive. In this study, we collected skeletal muscle, noncancerous, and cancerous tissues using the Illumina EPIC array to identify conserved DNA methylation probes associated with weight loss following bariatric surgery. Next, the consistency of the probes is evaluated and then the probes are integrated into a generalizable pathway enrichment score. Our results emphasize the gene-centered design, identifying KCNB1, PEAK1, SCG5, and TNIK as key targets of DNA methylation, as confirmed by mouse phenotype data and druggability resources. Moreover, an illustrative test of protein abundance in cell lines is conducted. Utilizing the Clinical Proteomic Tumor Analysis Consortium data, a positive correlation is established between the chromosomal instability scores and our generated score in tumor tissues. In addition, considering these correlation findings, the presence of identifiable methylation blocks in the co-occurring gain samples. Our findings also suggest that upstream molecular drivers may influence this pathway enrichment score, potentially leading to dysregulated methylation associated with weight loss. In summary, DNA methylation analysis not only identifies functional targets but also uncovers new gene-disease connections.