Dataset.

DataSheet_3_A novel gene signature unveils three distinct immune-metabolic rewiring patterns conserved across diverse tumor types and associated with outcomes.docx

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331351
Digital.CSIC. Repositorio Institucional del CSIC
  • Pedrosa, Leire
  • Foguet, Carles
  • Oliveres, Helena
  • Archilla, Iván
  • García de Herreros, Marta
  • Rodríguez, Adela
  • Postigo, Antonio
  • Benítez-Ribas, Daniel
  • Camps, Jordi
  • Cuatrecasas, Miriam
  • Castells, Antoni
  • Prat, Aleix
  • Thomson, Timothy M.
  • Maurel, Joan
  • Cascante, Marta
Supplementary Figure S3: Heatmap (A) and statistic results (B) studding the expression of genes related with autophagy in IMMETCOLS Clusters. (A) Heatmap representing the average expression of genes related to autophagy in IMMETCOLS Cluster. Gene expression values are range-scaled between -1 and 1. In top the Cluster classification is showed with red, green or blue, for Cluster 1, Cluster 2 and Cluster 3 respectively. The genes of canonical autophagy are in orange circle and the LAP genes are in blue circles. (B) Important features identified by One-way ANOVA and post-hoc analysis (Fisher’s LSD) comparing the expression of genes related to autophagy in the IMMETCOLS Clusters., Existing immune signatures and tumor mutational burden have only modest predictive capacity for the efficacy of immune check point inhibitors. In this study, we developed an immune-metabolic signature suitable for personalized ICI therapies. A classifier using an immune-metabolic signature (IMMETCOLS) was developed on a training set of 77 metastatic colorectal cancer (mCRC) samples and validated on 4,200 tumors from the TCGA database belonging to 11 types. Here, we reveal that the IMMETCOLS signature classifies tumors into three distinct immune-metabolic clusters. Cluster 1 displays markers of enhanced glycolisis, hexosamine byosinthesis and epithelial-to-mesenchymal transition. On multivariate analysis, cluster 1 tumors were enriched in pro-immune signature but not in immunophenoscore and were associated with the poorest median survival. Its predicted tumor metabolic features suggest an acidic-lactate-rich tumor microenvironment (TME) geared to an immunosuppressive setting, enriched in fibroblasts. Cluster 2 displays features of gluconeogenesis ability, which is needed for glucose-independent survival and preferential use of alternative carbon sources, including glutamine and lipid uptake/β-oxidation. Its metabolic features suggest a hypoxic and hypoglycemic TME, associated with poor tumor-associated antigen presentation. Finally, cluster 3 is highly glycolytic but also has a solid mitochondrial function, with concomitant upregulation of glutamine and essential amino acid transporters and the pentose phosphate pathway leading to glucose exhaustion in the TME and immunosuppression. Together, these findings suggest that the IMMETCOLS signature provides a classifier of tumors from diverse origins, yielding three clusters with distinct immune-metabolic profiles, representing a new predictive tool for patient selection for specific immune-metabolic therapeutic approaches., Peer reviewed
 
DOI: http://hdl.handle.net/10261/331351
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331351

HANDLE: http://hdl.handle.net/10261/331351
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331351
 
Ver en: http://hdl.handle.net/10261/331351
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331351

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331351
Dataset. 2022

DATASHEET_3_A NOVEL GENE SIGNATURE UNVEILS THREE DISTINCT IMMUNE-METABOLIC REWIRING PATTERNS CONSERVED ACROSS DIVERSE TUMOR TYPES AND ASSOCIATED WITH OUTCOMES.DOCX

Digital.CSIC. Repositorio Institucional del CSIC
  • Pedrosa, Leire
  • Foguet, Carles
  • Oliveres, Helena
  • Archilla, Iván
  • García de Herreros, Marta
  • Rodríguez, Adela
  • Postigo, Antonio
  • Benítez-Ribas, Daniel
  • Camps, Jordi
  • Cuatrecasas, Miriam
  • Castells, Antoni
  • Prat, Aleix
  • Thomson, Timothy M.
  • Maurel, Joan
  • Cascante, Marta
Supplementary Figure S3: Heatmap (A) and statistic results (B) studding the expression of genes related with autophagy in IMMETCOLS Clusters. (A) Heatmap representing the average expression of genes related to autophagy in IMMETCOLS Cluster. Gene expression values are range-scaled between -1 and 1. In top the Cluster classification is showed with red, green or blue, for Cluster 1, Cluster 2 and Cluster 3 respectively. The genes of canonical autophagy are in orange circle and the LAP genes are in blue circles. (B) Important features identified by One-way ANOVA and post-hoc analysis (Fisher’s LSD) comparing the expression of genes related to autophagy in the IMMETCOLS Clusters., Existing immune signatures and tumor mutational burden have only modest predictive capacity for the efficacy of immune check point inhibitors. In this study, we developed an immune-metabolic signature suitable for personalized ICI therapies. A classifier using an immune-metabolic signature (IMMETCOLS) was developed on a training set of 77 metastatic colorectal cancer (mCRC) samples and validated on 4,200 tumors from the TCGA database belonging to 11 types. Here, we reveal that the IMMETCOLS signature classifies tumors into three distinct immune-metabolic clusters. Cluster 1 displays markers of enhanced glycolisis, hexosamine byosinthesis and epithelial-to-mesenchymal transition. On multivariate analysis, cluster 1 tumors were enriched in pro-immune signature but not in immunophenoscore and were associated with the poorest median survival. Its predicted tumor metabolic features suggest an acidic-lactate-rich tumor microenvironment (TME) geared to an immunosuppressive setting, enriched in fibroblasts. Cluster 2 displays features of gluconeogenesis ability, which is needed for glucose-independent survival and preferential use of alternative carbon sources, including glutamine and lipid uptake/β-oxidation. Its metabolic features suggest a hypoxic and hypoglycemic TME, associated with poor tumor-associated antigen presentation. Finally, cluster 3 is highly glycolytic but also has a solid mitochondrial function, with concomitant upregulation of glutamine and essential amino acid transporters and the pentose phosphate pathway leading to glucose exhaustion in the TME and immunosuppression. Together, these findings suggest that the IMMETCOLS signature provides a classifier of tumors from diverse origins, yielding three clusters with distinct immune-metabolic profiles, representing a new predictive tool for patient selection for specific immune-metabolic therapeutic approaches., Peer reviewed




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