The mutational load and a T-cell inflamed tumour phenotype identify ovarian cancer patients rendering tumour-reactive T cells from PD-1+ tumour-infiltrating lymphocytes

Abstract

Background Adoptive immunotherapy with tumour-infiltrating lymphocytes (TIL) may benefit from the use of selective markers, such as PD-1, for tumour-specific T-cell enrichment, and the identification of predictive factors that help identify those patients capable of rendering tumour-reactive TILs. We have investigated this in ovarian cancer (OC) patients as candidates for TIL therapy implementation. Methods PD-1− and PD-1+ CD8 TILs were isolated from ovarian tumours and expanded cells were tested against autologous tumour cells. Baseline tumour samples were examined using flow cytometry, multiplexed immunofluorescence and Nanostring technology, for gene expression analyses, as well as a next-generation sequencing gene panel, for tumour mutational burden (TMB) calculation. Results Tumour-reactive TILs were detected in half of patients and were exclusively present in cells derived from the PD-1+ fraction. Importantly, a high TIL density in the fresh tumour, the presence of CD137+ cells within the PD-1+CD8+ TIL subset and their location in the tumour epithelium, together with a baseline T-cell-inflamed genetic signature and/or a high TMB, are features that identify patients rendering tumour-reactive TIL products. Conclusion We have demonstrated that PD-1 identifies ovarian tumour-specific CD8 TILs and has uncovered predictive factors that identify OC patients who are likely to render tumour-specific cells from PD-1+ TILs.

Characterizing the Invasive Tumor Front of Aggressive Uterine Adenocarcinoma and Leiomyosarcoma

“…A multiplex immunofluorescence panel was used to enable simultaneous examination of several cellular markers, including the phagocytic cell marker CD68 of macrophages, CD3 + and CD8 + T cells, and CD20 + B lymphocytes. Multiplex immunofluorescence development and validation workflow and protocols were implemented as previously described ( Schalper et al, 2019 ; Abengozar-Muela et al, 2020 ; Salas-Benito et al, 2021 ). Briefly, 5-μm sections of FFPE tissue were deparaffinized and antigen retrieval was performed using DAKO PT-Link heat-induced antigen retrieval with low pH (pH 6) or high pH (pH 9) target retrieval solution (DAKO).…”

“…Each whole-tissue section was scanned on a Vectra-Polaris Automated Quantitative Pathology Imaging System (Akoya Biosciences). Tissue imaging and spectral unmixing were performed using InForm software (version 2.4.8, Akoya Biosciences), as previously described ( Abengozar-Muela et al, 2020 ; Salas-Benito et al, 2021 ). Image analysis was performed on 5 × 4-mm and 1-mm 2 ROIs using the open-source digital pathology software QuPath version 0.2.3, as previously described ( Abengozar-Muela et al, 2020 ).…”

“…We applied this technology to evaluate the complex immune environment of the ITF of uADC and uLMS. A previously developed and validated multiplex immunolabeling panel was used to simultaneously assess the phagocytic cell marker CD68 of macrophages, CD3 + and CD8 + T cells, and CD20 + B lymphocytes in a single FFPE tissue ( Abengozar-Muela et al, 2020 ; Salas-Benito et al, 2021 ).…”

Heterogenous presence of neutrophil extracellular traps in human solid tumours is partially dependent on IL‐8

“…The validation pipeline and details of the multiplex immunolabelling protocol development have been described previously by our group [33,34]. A 6-colour multiplex quantitative immunofluorescence protocol for FFPE tissue specimens was developed for simultaneous detection of DAPI, CD15, MPO, H3Cit, CD8 and cytokeratin using isotype-specific antibodies and different fluorescence conjugates.…”

“…TMAs and whole tissue sections were scanned on a Vectra-Polaris Automated Quantitative Pathology Imaging System (Akoya Biosciences). Tissue imaging and spectral unmixing were performed using inForm software (version 2.4.8, Akoya Biosciences), as described previously [33,34]. Image analysis was then performed on whole TMA spots and whole-tumour area using the open-source digital pathology software QuPath version 0.2.3 (University of Edinburgh, Edinburgh, UK; https://qupath.github.io) and ImageJ software version 1.52c (NIH, Bethesda, MD, USA; http:// imagej.nih.gov/ij).…”