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ePoster Display

996P - An immune-metabolic signature correlates with immune-suppressive patterns and with outcome, across tumor types

Date

16 Sep 2021

Session

ePoster Display

Topics

Tumour Immunology;  Targeted Therapy;  Translational Research

Tumour Site

Presenters

Leire Pedrosa

Citation

Annals of Oncology (2021) 32 (suppl_5): S829-S866. 10.1016/annonc/annonc705

Authors

L. Pedrosa1, C. Foguet2, H. Oliveres1, I. Archilla3, M. García de Herreros1, A. Rodriguez1, A. Postigo4, D. Benítez-Ribas5, J. Camps6, M. Cuatrecasas3, A. Castells7, A. Prat1, T.M. Thomson8, J. Maurel1, M. Cascante9

Author affiliations

  • 1 Medical Oncology Department, Hospital Clinic y Provincial de Barcelona, 08036 - Barcelona/ES
  • 2 Department Of Biochemistry And Molecular Medicine, Universitat de Barcelona, Barcelona/ES
  • 3 Pathology Department, Hospital Clínic de Barcelona, Barcelona/ES
  • 4 Biomedicine Department, IDIBAPS, Barcelona/ES
  • 5 Immunology, Hospital Clínic de Barcelona, 08036 - Barcelona/ES
  • 6 Oncology, IDIBAPS, Barcelona/ES
  • 7 Gastrointestinal And Pancreatic Oncology, IDIBAPS, 08036 - Barcelona/ES
  • 8 Hepatic And Digestive Diseases, CIBER of Hepatic and Digestive Diseases (CIBEREHD), Barcelona/ES
  • 9 Universitat De Barcelona, Universitat de Barcelona, Barcelona/ES

Resources

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Abstract 996P

Background

Globally, immune markers and TMB show modest predictive accuracies of immune-check-point inhibitors (ICI) efficacy.

Methods

We hypothesize that metabolic signatures in combination with previously published pro-immune signatures can better identify patients suitable for personalized ICI therapies. To test this hypothesis, an immune-metabolic signature (IMMETCOLS) was developed in a training set of 75 mCRC patients using the IO360 Signature with nCounter platform. IMMETCOLS was used to categorize 11 different tumor types in TCGA dataset.

Results

IMMETCOLS signature classifies patients into 3 distinct metabolic clusters and was cross-validated in the training set. Cluster 1 enhanced glycolysis, hexosamine, fatty acid and branched chain ketoacids (BCKA) synthesis. Cluster 1 is enriched in fibroblast and EMT markers, pro-immune signatures (GEPH, PD1H) and also exhausted CD8+ T-cells. Concomitant up-regulation of HIF-1a and specific isoforms of enzymes/transporters, suggest that the observed metabolic fingerprint may be mediated by a hypoxic and glutamine deprived tumour microenvironment with a high content of immune infiltrates that facilitat the metabolic cross-talk with cancer cells. Cluster 2 has enhanced glutamine/BCKA oxidation and gain of gluconeogenic/glycogenic ability which are needed for glucose-independent survival and up-regulated enzymes in b-oxidation and glutamine synthesis. Cluster 2 is enriched with bystander CD8+ T-cells. Finally, Cluster 3 is characterized by up-regulation of SLC1A5 and SLC7A11 that promotes cancer cell dependence on glucose and increases the need of cytosolic NADPH sustained by concomitant up-regulation of G6PD. Its metabolic signature also suggests the up-regulation of proline, one-carbon metabolism and key players of malate-aspartate shuttle, suggestive of a gain of reductive carboxylation ability. Cluster 1 was associated with the shortest median survival (HR 1.54; 95% CI 1.21-1.971 p<0.001).

Conclusions

The IMMETCOLS signature identifies three clusters with distinct immune-metabolic profiles across tumor types, paving the way for an improved selection of patient for ICI therapy, in conjunction with more precisely targeted immune-metabolic combinations.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Medical Oncology Department, Hospital Clínic of Barcelona, Translational Genomics and Targeted Therapeutics in Solid Tumors Group, IDIBAPS, University of Barcelona, Barcelona, Spain.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

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