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Biology subjects

Vago, L.

Publications and source records attributed to Vago, L..

2 recordsLinked to original sources

Therapy-induced senescence upregulates antigen presentation machinery and triggers anti-tumor immunity in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is an aggressive hematological malignancy often curable only by using intensive chemotherapy. Nonetheless, resistance/early relapses are frequent, underscoring the need to investigate the molecular events occurring shortly after chemotherapy. Therapy-induced senescence (TIS) is a fail-safe tumor suppressive mechanism that may elicit immune-mediated responses contributing to senescent cell clearance. Yet, TIS functional role in AML eradication and immune surveillance early post-chemotherapy remains ill-defined. By combining transcriptional and cellular-based evaluation of senescence markers in AML patient samples, we found upregulation of senescence-associated genes and interferon gene categories with concomitant induction of HLA class I and class II molecules, pointing to a causal link between TIS and leukemia immunogenicity. Consistently, senescence-competent AML samples activated autologous CD4+ and CD8+ T cells and improved leukemia recognition by both T-cell subsets. Lastly, the anti-leukemic activity of Immune Checkpoint Blockades (ICBs) was enhanced upon senescence engagement in AML. Altogether, our results identify senescence as a potent immune-related anti-leukemic mechanism that may rapidly translate into innovative senescence-based strategies to prevent AML relapse. STATEMENT OF SIGNIFICANCEOur findings uncover a novel link between senescence induction and leukemia immune recognition by T cells via upregulation of antigen presentation machinery components, providing the basis for conceptually novel senescence-based targeted immunotherapeutic regimens for AML patients.

cancer biology↗

Robust and efficient coding with grid cells

The neuronal code arising from the coordinated population activity of grid cells in the rodent entorhinal cortex can uniquely represent space across large distances but the precise conditions for efficient coding are unknown. Here we present a number-theoretic analysis of grid coding and derive an upper bound on the distance that a population of grid cells can represent without error. We show that in the absence of neuronal noise, the capacity of the system would be extremely sensitive to the choice of the grid periods. However, when the accuracy of the representation is limited by neuronal noise, the capacity becomes gradually more robust against the choice of grid scales as the number of modules increases and remains near optimal even for random scale choices. Our study reveals that robust and efficient coding can be achieved without parameter tuning in the case of grid cell representation.

neuroscience↗