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Objective <p>Understanding the discordance between RNA and protein expression can help elucidate underlying disease mechanisms that cannot be fully explained using transcriptomic information alone. Unveiling novel mechanisms of tumorigenesis through multi-omics data using real-world data is central to advancing precision in oncology and tumor prevention. In this study, we investigated the expression discordance between non-tumor and tumor patient samples to elucidate the underlying mechanism of tumorigenesis in lung adenocarcinoma (LUAD).</p> Methods <p>We performed a correlation analysis of RNA and protein using normal tissue adjacent to tumor and tumor samples to identify distinct expression profiles to unveil tumorigenesis. Publicly available multi-omics data, including RNA, proteins, phosphoproteins, and acetyl proteins, were obtained from the Clinical Proteomic Tumor Analysis Consortium. Gene expression analysis at the single-cell level was performed using single-cell RNA sequencing data. A transformer model was used for in silico drug screening.</p> Results <p>Most genes in tumors showed a positive correlation between RNA and protein expression. DNA topoisomerase II alpha (TOP2A) and Cyclin-dependent kinase 1 showed a drastic correlation during tumorigenesis in patient with LUAD. TOP2A gene and protein expression were associated with overall survival in patients with LUAD. Single-cell RNA sequencing revealed that highly correlated genes were clustered as distinct subpopulations. TOP2A expression was associated with <i>TP53</i> genomic status and miR-26A1 expression, which targets TOP2A gene. In silico screening identified novel drugs that could specifically target TOP2A.</p> Conclusions <p>Our findings elucidated the multi-layer expression profiles of LUAD, revealing its tumorigenesis and potential clinical implications and interventions.</p>

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Deciphering RNA and protein expression discordance identifies TOP2A as a prognostic biomarker and potential therapeutic target in lung adenocarcinoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月28日

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  • Mika Miyabe,
  • Shuntaro Arimitsu,
  • Amina Bolatkan,
  • Hidenori Machino,
  • Ryuji Hamamoto,
  • Ken Asada

摘要

Objective

Understanding the discordance between RNA and protein expression can help elucidate underlying disease mechanisms that cannot be fully explained using transcriptomic information alone. Unveiling novel mechanisms of tumorigenesis through multi-omics data using real-world data is central to advancing precision in oncology and tumor prevention. In this study, we investigated the expression discordance between non-tumor and tumor patient samples to elucidate the underlying mechanism of tumorigenesis in lung adenocarcinoma (LUAD).

Methods

We performed a correlation analysis of RNA and protein using normal tissue adjacent to tumor and tumor samples to identify distinct expression profiles to unveil tumorigenesis. Publicly available multi-omics data, including RNA, proteins, phosphoproteins, and acetyl proteins, were obtained from the Clinical Proteomic Tumor Analysis Consortium. Gene expression analysis at the single-cell level was performed using single-cell RNA sequencing data. A transformer model was used for in silico drug screening.

Results

Most genes in tumors showed a positive correlation between RNA and protein expression. DNA topoisomerase II alpha (TOP2A) and Cyclin-dependent kinase 1 showed a drastic correlation during tumorigenesis in patient with LUAD. TOP2A gene and protein expression were associated with overall survival in patients with LUAD. Single-cell RNA sequencing revealed that highly correlated genes were clustered as distinct subpopulations. TOP2A expression was associated with TP53 genomic status and miR-26A1 expression, which targets TOP2A gene. In silico screening identified novel drugs that could specifically target TOP2A.

Conclusions

Our findings elucidated the multi-layer expression profiles of LUAD, revealing its tumorigenesis and potential clinical implications and interventions.