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Genomic and transcriptomic study of circulating tumor lymphocytes for the development of biomarkers associated with the response to treatment with inhibitors of the PD-L1 / PD1 pathway in patients with NSCLC

18th national competition for scientific and technical research

Immunotherapy and cancer

Senior Researcher : Ángel Carracedo Álvarez

Research Centre or Institution : Fundación Pública Gallega de Medicina Genómica. Santiago de Compostela.


In the transcriptomic analysis we observed a statistically significant difference in the variation of the % of CD8+ T cells in R vs NR between t0 and t1 (p = 0.049; Two-tailed unpaired student T test). A significant decrease was also found in this population of CD8 + cells in non-responders between t0 and t1 (p = 0.001). These data suggest that immunotherapy can revitalize T cell activity, and that this cell population is significantly reduced in patients who do not respond well to treatment.

The expression between PD1+ and PD1- cells in paired samples from the same patient was compared at different times and at different responses. The results show little overlap between the different comparative groups, which is indicative that there are different pathways that mediate response depending on PD1 status, response, or time point of treatment.

Pathway analysis was performed with three different methods: GSEA to determine differentially enriched gene sets between the different phenotypic groups, PANTHER classification to find enriched pathways for the lists of significantly expressed genes, and DAVID classification to find if the lists of significantly expressed or under-expressed genes form gene clusters classified by functional annotations.

Sequencing of ctDNA extracted from 52 plasma samples (25 at t0, 18 at t1, and 9 at t2) and DNA from 18 paired FFPE tumour samples has recently begun. Variants in 197 cancer-related genes may be observed, and it will be possible to compare variants detected in plasma and in the primary tumour of the same patient, observe changes in these variants over time in the same patient, and calculate the tumour mutation burden (TMB) to find a possible link between the number of non-synonymous mutations and the patient's response to treatment.

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