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Poster session 19

1061P - Association of transcriptomic mapping of tumors with high expression of Tregs to identify surfaceome gene signatures with efficacy to check point inhibitors

Date

21 Oct 2023

Session

Poster session 19

Topics

Clinical Research;  Tumour Immunology;  Immunotherapy

Tumour Site

Breast Cancer

Presenters

María Del Mar Noblejas Lopez

Citation

Annals of Oncology (2023) 34 (suppl_2): S619-S650. 10.1016/S0923-7534(23)01940-3

Authors

M.D.M. Noblejas Lopez1, E. García-Gil2, P. Pérez Segura3, P. Gancarski4, L. Martín4, A. Pandiella5, B. Gyorffy6, A. Ocana Fernandez7

Author affiliations

  • 1 Oncología Traslacional Department, Universidad de Castilla-La Mancha, 02006 - Albacete/ES
  • 2 Oncología Traslacional Department, Complejo Hospitalario Universitario de Albacete, 02006 - Albacete/ES
  • 3 Dept. Medical Oncology, Hospital Clinico Universitario San Carlos, 28040 - Madrid/ES
  • 4 Artificial Intelligence To Optimize Cancer Drug Development, CancerAppy, 48950 - Erandio/ES
  • 5 Laboratorio 15, Universidad de Salamanca (USAL), Instituto de Biología Molecular y Celular del Cáncer (IBMCC), 37007 - Salamanca/ES
  • 6 Institute Of Enzymology, Research Centre for Natural Sciences, 1117 - Budapest/HU
  • 7 Experimental Therapeutics Unit, Medical Oncology Department, Hospital Clinico Universitario San Carlos, 28040 - Madrid/ES

Resources

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Abstract 1061P

Background

Immune cell populations within the tumor microenvironment modulate the host immune response against tumors. An example is the population of regulatory CD4+ T cells (Tregs) that produces an inhibitory effect against effector immune cells. In the present work we interrogated publicly available genomic datasets, to explore the transcriptomic profile of breast tumors with high expression of Tregs.

Methods

We used breast cancer datasets to identify genes whose expression correlated with high presence of regulatory T-cells infiltration. Immune cell infiltration was determined by using the normalized RNA-seq based transcriptome-wide gene expression data and the xCell algorithm. TIMER platform was employed to analyze the association between expression and the presence of tumor immune infiltrates. Datasets from patients treated with check point inhibitors were interrogated to evaluate response to immunotherapy.

Results

Only 0.5% of the total transcriptome correlated with the presence of Tregs and only four transcripts, BIRC6, MAP3K2, USP4 and SMG1, were commonly shared among the different breast cancer subtypes. Ten up-regulated genes (MSR1, CD80, OLR1, ABCA1, ADAM17, ANO6, TMEM245, ITGAV, CLEC5A and ATP13AE) coded for proteins expressed at the cell membrane. A statistically significant correlation was observed between the presence of CD80, ORL1 and MSR1 and the expression of PDL1 and PD1 in basal-like subtype. A similar association was observed between MSR1 and CD80 with macrophage presence in basal-like tumors and between OLR1, ABCA1, ITGAV, and CLEC5A and macrophages in HER2+ tumors. Some of the identified genes was linked with favorable outcome and response to checkpoint inhibitors. MSR1, CD80, OLR1, ABCA1, TMEM245, and ATP13A3 predicted outcome to anti-PD(L)1 and anti CTLA4 therapies. The activity, in terms of clinical response, of each single transcript was further confirmed, for some of them, using an additional cohort of patients treated with immune-based therapies.

Conclusions

In summary, we identify genes expressed in a subset of immune cells that predict efficacy to checkpoint inhibitors. Further prospective studies are ongoing to confirm these findings in patients.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

AO’s lab is supported by the Instituto de Salud Carlos III (ISCIII, PI19/00808); ACEPAIN; CRIS Cancer Foundation and Diputación de Albacete. This research is also supported by PI18/01020 from the Instituto de Salud Carlos III and co-financed by the European Development Regional Fund (FEDER) “A way to achieve Europe” (ERDF); MNL was supported by the Spanish Ministry of Education (FPU grant; Ref.: FPU18/01319). BG was financed by the 2018-2.1.17-TETKR- 00001, 2020-1.1.6-JÖVO˝ -2021-00013, and 2018-1.3.1-VKE-2018-00032 grants and by the Higher Education Institutional Excellence Programme (2020-4.1.1-TKP2020) of the Ministry for Innovation and Technology in Hungary. Work in Pandiella´s lab is supported by the Ministery of Science and Innovation of Spain (PID2020-115605RB-I00), the Instituto de Salud Carlos III through CIBERONC, Junta de Castilla y León (CSI146P20), and the private associations CRIS, ALMOM, ACMUMA and UCCTA.

Disclosure

P. Pérez Segura: Financial Interests, Personal, Advisory Role: MSD Oncology, BMSi and Merck; Financial Interests, Personal, Speaker’s Bureau: MSD Oncology, BMSi and Merck; Financial Interests, Personal, Other, Travel, Accommodations, Expenses: MSD Oncology, BMSi and Merck; Financial Interests, Personal and Institutional, Funding: MSD Oncology, BMSi and Merck; Financial Interests, Personal, Other, Honoraria: MSD Oncology, BMSi and Merck. P. Gancarski: Financial Interests, Personal, Full or part-time Employment: CancerAppy. L. Martín: Financial Interests, Personal, Full or part-time Employment: CancerAppy. A. Ocana Fernandez: Financial Interests, Personal, Full or part-time Employment: Symphogen; Financial Interests, Personal, Advisory Role: Servier. All other authors have declared no conflicts of interest.

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