Open Access
A proteomic atlas of lineage and cancer-polarized expression modules in myeloid cells modeling immunosuppressive tumor-infiltrating subsets
(MDPI, 2021) Blanco, Ester; Ibañez Vea, María; Hernández, Carlos; Drici, Lylia; Martínez de Morentin Iribarren, Xabier; Gato Cañas, María; Ausín, Karina; Bocanegra Gondán, Ana Isabel; Zuazo Ibarra, Miren; Chocarro de Erauso, Luisa; Arasanz Esteban, Hugo; Fernández Hinojal, Gonzalo; Fernández Irigoyen, Joaquín; Smerdou, Cristian; Garnica, Maider; Echaide Górriz, Míriam; Fernández Rubio, Leticia; Morente Sancho, Pilar; Ramos-Castellanos, Pablo; Llopiz, Diana; Santamaría Martínez, Enrique; Larsen, Martin R.; Escors Murugarren, David; Kochan, Grazyna; Osasun Zientziak; Institute for Multidisciplinary Research in Applied Biology - IMAB; Ciencias de la Salud; Gobierno de Navarra / Nafarroako Gobernua
Monocytic and granulocytic myeloid-derived suppressor cells together with tumor-infiltrating macrophages constitute the main tumor-infiltrating immunosuppressive myeloid populations. Due to the phenotypic resemblance to conventional myeloid cells, their identification and purification from within the tumors is technically difficult and makes their study a challenge. We differentiated myeloid cells modeling the three main tumor-infiltrating types together with uncommitted macrophages, using ex vivo differentiation methods resembling the tumor microenvironment. The phenotype and proteome of these cells was compared to identify linage-dependent relationships and cancer-specific interactome expression modules. The relationships between monocytic MDSCs and TAMs, monocytic MDSCs and granulocytic MDSCs, and hierarchical relationships of expression networks and transcription factors due to lineage and cancer polarization were mapped. Highly purified immunosuppressive myeloid cell populations that model tumor-infiltrating counterparts were systematically analyzed by quantitative proteomics. Full functional interactome maps have been generated to characterize at high resolution the relationships between the three main myeloid tumor-infiltrating cell types. Our data highlights the biological processes related to each cell type, and uncover novel shared and differential molecular targets. Moreover, the high numbers and fidelity of ex vivo-generated subsets to their natu-ral tumor-shaped counterparts enable their use for validation of new treatments in high-throughput experiments.
Open Access
PD-L1 expression in systemic immune cell populations as a potential predictive biomarker of responses to PD-L1/PD-1 blockade therapy in lung cancer
(MDPI, 2019) Bocanegra Gondán, Ana Isabel; Fernández Hinojal, Gonzalo; Zuazo Ibarra, Miren; Arasanz Esteban, Hugo; García Granda, María Jesús; Hernández, Carlos; Ibañez Vea, María; Hernandez Marin, Berta; Martínez Aguillo, Maite; Lecumberri, María José; Fernández de Lascoiti, Ángela; Teijeira, Lucía; Morilla Ruiz, Idoia; Vera García, Ruth; Escors Murugarren, David; Kochan, Grazyna; Ciencias de la Salud; Osasun Zientziak; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
PD-L1 tumor expression is a widely used biomarker for patient stratification in PD-L1/PD-1 blockade anticancer therapies, particularly for lung cancer. However, the reliability of this marker is still under debate. Moreover, PD-L1 is widely expressed by many immune cell types, and little is known on the relevance of systemic PD-L1+ cells for responses to immune checkpoint blockade. We present two clinical cases of patients with non-small cell lung cancer (NSCLC) and PD-L1-negative tumors treated with atezolizumab that showed either objective responses or progression. These patients showed major differences in the distribution of PD-L1 expression within systemic immune cells. Based on these results, an exploratory study was carried out with 32 cases of NSCLC patients undergoing PD-L1/PD-1 blockade therapies, to compare PD-L1 expression profiles and their relationships with clinical outcomes. Significant differences in the percentage of PD-L1+ CD11b+ myeloid cell populations were found between objective responders and non-responders. Patients with percentages of PD-L1+ CD11b+ cells above 30% before the start of immunotherapy showed response rates of 50%, and 70% when combined with memory CD4 T cell profiling. These findings indicate that quantification of systemic PD-L1+ myeloid cell subsets could provide a simple biomarker for patient stratification, even if biopsies are scored as PD-L1 null

Ibañez Vea, María

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