Background <p>Obesity is a known risk factor for colorectal cancer (CRC), but its impact on prognosis and tumor biology remains unclear. This study aimed to identify molecular biomarkers that reflect obesity-associated tumor characteristics and stratify patient outcomes.</p> Methods <p>We conducted a multi-step analysis integrating transcriptomic data, clinical validation, and spatial profiling. Candidate genes were first screened in the TCGA-COADREAD dataset based on expression trends across normal, healthy-weight CRC, and obese CRC samples. Prognostically relevant genes were then validated in an independent cohort using immunohistochemistry (IHC). Finally, spatial transcriptomic analysis using GeoMx DSP was performed to elucidate the tumor microenvironment associated with the top candidate.</p> Results <p>Among six shortlisted genes, NNT showed a significant association with overall survival specifically in obese patients and was validated at the protein level by IHC. High NNT expression was independent of TNM stage and associated with improved prognosis. Spatial transcriptomic profiling revealed that NNT-high tumors were enriched for antioxidant, apoptotic, and metabolic programs, while oncogenic and proliferative pathways were suppressed. These patterns suggest that NNT contributes to a redox-balanced and metabolically adaptive tumor state.</p> Conclusions <p>Through integrative molecular and spatial analyses, NNT was identified as a potential prognostic biomarker in obesity-associated CRC. This study highlights the importance of combining clinical data with spatial transcriptomics to uncover context-specific tumor biology.</p>

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Multi-modal molecular and spatial profiling reveals NNT as a prognostic biomarker in obesity-associated colorectal cancer

  • Sungjin Park,
  • Jae-Ghi Lee,
  • Ilkyu Park,
  • Soyeon Jeong,
  • Jungsuk An,
  • Jisup Kim,
  • Myunghee Kang,
  • Seungyoon Nam,
  • Jung Ho Kim

摘要

Background

Obesity is a known risk factor for colorectal cancer (CRC), but its impact on prognosis and tumor biology remains unclear. This study aimed to identify molecular biomarkers that reflect obesity-associated tumor characteristics and stratify patient outcomes.

Methods

We conducted a multi-step analysis integrating transcriptomic data, clinical validation, and spatial profiling. Candidate genes were first screened in the TCGA-COADREAD dataset based on expression trends across normal, healthy-weight CRC, and obese CRC samples. Prognostically relevant genes were then validated in an independent cohort using immunohistochemistry (IHC). Finally, spatial transcriptomic analysis using GeoMx DSP was performed to elucidate the tumor microenvironment associated with the top candidate.

Results

Among six shortlisted genes, NNT showed a significant association with overall survival specifically in obese patients and was validated at the protein level by IHC. High NNT expression was independent of TNM stage and associated with improved prognosis. Spatial transcriptomic profiling revealed that NNT-high tumors were enriched for antioxidant, apoptotic, and metabolic programs, while oncogenic and proliferative pathways were suppressed. These patterns suggest that NNT contributes to a redox-balanced and metabolically adaptive tumor state.

Conclusions

Through integrative molecular and spatial analyses, NNT was identified as a potential prognostic biomarker in obesity-associated CRC. This study highlights the importance of combining clinical data with spatial transcriptomics to uncover context-specific tumor biology.