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<p>To investigate how spatial constraints shape cancer metabolism, we devised the spatial Flux Balance Analysis (spFBA) framework for the enrichment of spatial transcriptomics data with relative estimates of metabolic fluxes. Applying spFBA to newly generated high-resolution datasets of paired primary colorectal tumors (CRC) and liver metastases revealed lactate consumption in both primary and metastatic regions. The presence of lactate-consuming niches was confirmed in an independent public dataset, suggesting this may be a recurrent metabolic feature of CRC. Importantly, application to public datasets of renal cancer showed widespread lactate production, consistent with a dominant but heterogeneous Warburg phenotype, ruling out general prediction biases or algorithmic artifacts. spFBA also consistently identified regions of increased proliferation across datasets, supporting the biological validity of its predictions. The framework is applicable to any sequencing-based spatial dataset to effectively uncover metabolic programs that remain invisible to gene expression analysis alone.</p>

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Spatial FBA reveals heterogeneous Warburg niches in renal tumors and lactate consumption in colorectal cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月27日

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  • Davide Maspero,
  • Giovanni Marteletto,
  • Francesco Lapi,
  • Bruno G. Galuzzi,
  • Irene Ruano,
  • Ben Vandenbosch,
  • Ke Yin,
  • Sabine Tejpar,
  • Alex Graudenzi,
  • Holger Heyn,
  • Anna Pascual-Reguant,
  • Chiara Damiani

摘要

To investigate how spatial constraints shape cancer metabolism, we devised the spatial Flux Balance Analysis (spFBA) framework for the enrichment of spatial transcriptomics data with relative estimates of metabolic fluxes. Applying spFBA to newly generated high-resolution datasets of paired primary colorectal tumors (CRC) and liver metastases revealed lactate consumption in both primary and metastatic regions. The presence of lactate-consuming niches was confirmed in an independent public dataset, suggesting this may be a recurrent metabolic feature of CRC. Importantly, application to public datasets of renal cancer showed widespread lactate production, consistent with a dominant but heterogeneous Warburg phenotype, ruling out general prediction biases or algorithmic artifacts. spFBA also consistently identified regions of increased proliferation across datasets, supporting the biological validity of its predictions. The framework is applicable to any sequencing-based spatial dataset to effectively uncover metabolic programs that remain invisible to gene expression analysis alone.