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Background <p>Transcript-level analyses allow for the precise characterization of gene expression and its functional role in cancer. However, most of these studies rely on reanalyses of next-generation sequencing data, whose incomplete or inaccurate assemblies limit the comprehensive and faithful characterization of transcripts. To systematically elucidate transcriptomic expression in tumors and define broadly applicable therapeutic strategies, we investigated cancer-specific RNA transcripts (cancer-SRTs) expressed across multiple cancer types based on long-read sequencing data.</p> Methods <p>We characterized the expression profiles of 44,405 cancer-SRTs across multiple cancer types using t-SNE and correlation analyses. Transcripts expressed in more than 10 cancer types were further investigated through enrichment, survival, and correlation analyses to elucidate their functions and clinical relevance. To explore the mechanisms driving cancer-SRT generation, we analyzed alternative splicing events within these transcripts and integrated copy number variation, DNA methylation, and ATAC-seq data from matched TCGA tumor samples. Using the expression of 131 transcripts strongly associated with tumor hallmarks, we developed a risk-score model to evaluate associations with patient survival, tumor stage, immune characteristics, and responses to immune checkpoint blockade. Finally, the in vitro anti-tumor effects of siRNAs targeting two cancer-SRTs were evaluated using CCK-8 assay, colony formation, and transwell assays.</p> Results <p>Cancer-SRTs exhibit substantial structural diversity and are enriched in malignancy-associated pathways. The expression of these transcripts is associated with multiple genomic and epigenetic processes. We identify 131 transcripts that are strongly associated with tumor hallmarks and develop a risk-score model for evaluating patient prognosis and tumor progression. The model also exhibited strong associations with features of immune evasion.</p> Conclusions <p>Cancer-SRTs are widely expressed yet highly heterogeneous across tumor types, and are subject to multiple regulatory mechanisms underlying their functional and clinical significance. These findings advance our understanding of tumor biology and lay the groundwork for developing diagnostic, prognostic, and therapeutic strategies based on these transcripts. Future studies investigating their underlying mechanisms and applications in immunotherapy will be critical for precision cancer treatment.</p>

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The expression landscape and clinical significance of cancer-specific RNA transcripts across human cancers

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月21日

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  • Haochen Li,
  • Jie Ding,
  • Xianghuo He,
  • Zhiao Chen

摘要

Background

Transcript-level analyses allow for the precise characterization of gene expression and its functional role in cancer. However, most of these studies rely on reanalyses of next-generation sequencing data, whose incomplete or inaccurate assemblies limit the comprehensive and faithful characterization of transcripts. To systematically elucidate transcriptomic expression in tumors and define broadly applicable therapeutic strategies, we investigated cancer-specific RNA transcripts (cancer-SRTs) expressed across multiple cancer types based on long-read sequencing data.

Methods

We characterized the expression profiles of 44,405 cancer-SRTs across multiple cancer types using t-SNE and correlation analyses. Transcripts expressed in more than 10 cancer types were further investigated through enrichment, survival, and correlation analyses to elucidate their functions and clinical relevance. To explore the mechanisms driving cancer-SRT generation, we analyzed alternative splicing events within these transcripts and integrated copy number variation, DNA methylation, and ATAC-seq data from matched TCGA tumor samples. Using the expression of 131 transcripts strongly associated with tumor hallmarks, we developed a risk-score model to evaluate associations with patient survival, tumor stage, immune characteristics, and responses to immune checkpoint blockade. Finally, the in vitro anti-tumor effects of siRNAs targeting two cancer-SRTs were evaluated using CCK-8 assay, colony formation, and transwell assays.

Results

Cancer-SRTs exhibit substantial structural diversity and are enriched in malignancy-associated pathways. The expression of these transcripts is associated with multiple genomic and epigenetic processes. We identify 131 transcripts that are strongly associated with tumor hallmarks and develop a risk-score model for evaluating patient prognosis and tumor progression. The model also exhibited strong associations with features of immune evasion.

Conclusions

Cancer-SRTs are widely expressed yet highly heterogeneous across tumor types, and are subject to multiple regulatory mechanisms underlying their functional and clinical significance. These findings advance our understanding of tumor biology and lay the groundwork for developing diagnostic, prognostic, and therapeutic strategies based on these transcripts. Future studies investigating their underlying mechanisms and applications in immunotherapy will be critical for precision cancer treatment.