Spatial immunophenotyping of the tumour microenvironment in non–small cell lung cancer

Checkpoint therapy; Lung cancer; Tumour microenvironmentTerapia de puntos de control; Cáncer de pulmón; Microambiente tumoralTeràpia de punts de control; Càncer de pulmó; Microambient tumoralIntroduction: Immune cells in the tumour microenvironment are associated with prognosis and response to therapy. We aimed to comprehensively characterise the spatial immune phenotypes in the mutational and clinicopathological background of non-small cell lung cancer (NSCLC). Methods: We established a multiplexed fluorescence imaging pipeline to spatially quantify 13 immune cell subsets in 359 NSCLC cases: CD4 effector cells (CD4-Eff), CD4 regulatory cells (CD4-Treg), CD8 effector cells (CD8-Eff), CD8 regulatory cells (CD8-Treg), B-cells, natural killer cells, natural killer T-cells, M1 macrophages (M1), CD163+ myeloid cells (CD163), M2 macrophages (M2), immature dendritic cells (iDCs), mature dendritic cells (mDCs) and plasmacytoid dendritic cells (pDCs). Results: CD4-Eff cells, CD8-Eff cells and M1 macrophages were the most abundant immune cells invading the tumour cell compartment and indicated a patient group with a favourable prognosis in the cluster analysis. Likewise, single densities of lymphocytic subsets (CD4-Eff, CD4-Treg, CD8-Treg, B-cells and pDCs) were independently associated with longer survival. However, when these immune cells were located close to CD8-Treg cells, the favourable impact was attenuated. In the multivariable Cox regression model, including cell densities and distances, the densities of M1 and CD163 cells and distances between cells (CD8-Treg-B-cells, CD8-Eff-cancer cells and B-cells-CD4-Treg) demonstrated positive prognostic impact, whereas short M2-M1 distances were prognostically unfavourable. Conclusion: We present a unique spatial profile of the in situ immune cell landscape in NSCLC as a publicly available data set. Cell densities and cell distances contribute independently to prognostic information on clinical outcomes, suggesting that spatial information is crucial for diagnostic use.This study was partly supported by Swedish Cancer Society, The Lions Cancer Foundation Uppsala, Sweden, Selanders Foundation and The Sjöberg Foundation, Sweden

Prognostic and predictive impact of stroma cells defned by PDGFRb expression in early breast cancer: results from the randomized SweBCG91RT trial

Purpose Predictive biomarkers are needed to aid the individualization of radiotherapy (RT) in breast cancer. Cancer-associated fibroblasts have been implicated in tumor radioresistance and can be identified by platelet-derived growth factor receptor-beta (PDGFRb). This study aims to analyze how PDGFRb expression affects RT benefit in a large randomized RT trial. Methods PDGFRb was assessed by immunohistochemistry on tissue microarrays from 989 tumors of the SweBCG91RT trial, which enrolled lymph node-negative, stage I/IIA breast cancer patients randomized to RT after breast-conserving surgery. Outcomes were analyzed at 10 years for ipsilateral breast tumor recurrence (IBTR) and any recurrence and 15 years for breast cancer specific death (BCSD). Results PDGFRb expression correlated with estrogen receptor negativity and younger age. An increased risk for any recurrence was noted in univariable analysis for the medium (HR 1.58, CI 95% 1.11–2.23, p = 0.011) or PDGFRb high group (1.49, 1.06–2.10, p = 0.021) compared to the low group. No differences in IBTR or BCSD risk were detected. RT benefit regarding IBTR risk was significant in the PDGFRb low (0.29, 0.12–0.67, p = 0.004) and medium (0.31, 0.16–0.59, p < 0.001) groups but not the PDGFRb high group (0.64, 0.36–1.11, p = 0.110) in multivariable analysis. Likewise, risk reduction for any recurrence was less pronounced in the PDGFRb high group. No significant interaction between RT and PDGFRb-score could be detected. Conclusion A higher PDGFRb-score conferred an increased risk of any recurrence, which partly can be explained by its association with estrogen receptor negativity and young age. Reduced RT benefit was noted among patients with high PDGFRb, however without significant interaction.publishedVersio

Fibroblast subsets in non-small cell lung cancer : Associations with survival, mutations, and immune features

Background Cancer-associated fibroblasts (CAFs) are molecularly heterogeneous mesenchymal cells that interact with malignant cells and immune cells and confer anti- and protumorigenic functions. Prior in situ profiling studies of human CAFs have largely relied on scoring single markers, thus presenting a limited view of their molecular complexity. Our objective was to study the complex spatial tumor microenvironment of non-small cell lung cancer (NSCLC) with multiple CAF biomarkers, identify novel CAF subsets, and explore their associations with patient outcome. Methods Multiplex fluorescence immunohistochemistry was employed to spatially profile the CAF landscape in 2 population-based NSCLC cohorts (n = 636) using antibodies against 4 fibroblast markers: platelet-derived growth factor receptor-alpha (PDGFRA) and -beta (PDGFRB), fibroblast activation protein (FAP), and alpha-smooth muscle actin (alpha SMA). The CAF subsets were analyzed for their correlations with mutations, immune characteristics, and clinical variables as well as overall survival. Results Two CAF subsets, CAF7 (PDGFRA-/PDGFRB+/FAP+/alpha SMA+) and CAF13 (PDGFRA+/PDGFRB+/FAP-/alpha SMA+), showed statistically significant but opposite associations with tumor histology, driver mutations (tumor protein p53 [TP53] and epidermal growth factor receptor [EGFR]), immune features (programmed death-ligand 1 and CD163), and prognosis. In patients with early stage tumors (pathological tumor-node-metastasis IA-IB), CAF7 and CAF13 acted as independent prognostic factors. Conclusions Multimarker-defined CAF subsets were identified through high-content spatial profiling. The robust associations of CAFs with driver mutations, immune features, and outcome suggest CAFs as essential factors in NSCLC progression and warrant further studies to explore their potential as biomarkers or therapeutic targets. This study also highlights multiplex fluorescence immunohistochemistry-based CAF profiling as a powerful tool for the discovery of clinically relevant CAF subsets.Peer reviewe

Stroma-regulated HMGA2 is an independent prognostic marker in PDAC and AAC

Background: The HMGA2 protein has experimentally been linked to EMT and cancer stemness. Recent studies imply that tumour-stroma interactions regulate these features and thereby contribute to tumour aggressiveness. Methods: We analysed 253 cases of pancreatic ductal adenocarcinoma (PDAC) and 155 cases of ampullary adenocarcinoma (AAC) for HMGA2 expression by IHC. The data were correlated with stroma abundance and supplemented by experimental studies. Results: HMGA2 acts as an independent prognostic marker associated with a significantly shorter overall survival in both tumour types. Overall, HMGA2-positivity was more frequent in patients with PDAC than with AAC. The HMGA2 status in tumour cells significantly correlated with the abundance of PDGFRβ-defined stroma cells. In vivo co-injection of Panc-1 cancer cells with pancreatic stellate cells increased tumour growth in a manner associated with increased HMGA2 expression. Furthermore, in vitro treatment of Panc-1 with conditioned media from PDGF-BB-activated stellate cells increased their ability to form tumour spheroids. Conclusions: This study identifies HMGA2 expression in tumour cells as an independent prognostic marker in PDAC and AAC. Correlative data analysis gives novel tissue-based evidence for a heterotypic cross-talk with stroma cells as a possible mechanism for HMGA2 induction, which is further supported by experimental models

Survival-associated heterogeneity of marker-defined perivascular cells in colorectal cancer

Perivascular cells (PC) were recently implied as regulators of metastasis and immune cell activity. Perivascular heterogeneity in clinical samples, and associations with other tumor features and outcome, remain largely unknown. Here we report a novel method for digital quantitative analyses of vessel characteristics and PC, which was applied to two collections of human metastatic colorectal cancer (mCRC). Initial analyses identified marker-defined subsets of PC, including cells expressing PDGFR-beta or alpha-SMA or both markers. PC subsets were largely independently expressed in a manner unrelated to vessel density and size. Association studies implied specific oncogenic mutations in malignant cells as determinants of PC status. Semi-quantitative and digital-image-analyses-based scoring of the NORDIC-VII cohort identified significant associations between low expression of perivascular PDGFR-alpha and -beta and shorter overall survival. Analyses of the SPCRC cohort confirmed these findings. Perivascular PDGFR-alpha and -beta remained independent factors for survival in multivariate analyses. Overall, our study identified host vasculature and oncogenic status as determinants of tumor perivascular features. Perivascular PDGFR-alpha and -beta were identified as novel independent markers predicting survival in mCRC. The novel methodology should be suitable for similar analyses in other tumor collections

Fibroblasts—a key host cell type in tumor initiation, progression, and metastasis

Tumor initiation, growth, invasion, and metastasis occur as a consequence of a complex interplay between the host environment and cancer cells. Fibroblasts are now recognized as a key host cell type involved in host–cancer signaling. This review discusses some recent studies that highlight the roles of fibroblasts in tumor initiation, early progression, invasion, and metastasis. Some clinical studies describing the prognostic significance of fibroblast-derived markers and signatures are also discussed

Extravasation of leukocytes in comparison to tumor cells

The multi-step process of the emigration of cells from the blood stream through the vascular endothelium into the tissue has been termed extravasation. The extravasation of leukocytes is fairly well characterized down to the molecular level, and has been reviewed in several aspects. Comparatively little is known about the extravasation of tumor cells, which is part of the hematogenic metastasis formation. Although the steps of the process are basically the same in leukocytes and tumor cells, i.e. rolling, adhesion, transmigration (diapedesis), the molecules that are involved are different. A further important difference is that leukocyte interaction with the endothelium changes the endothelial integrity only temporarily, whereas tumor cell interaction leads to an irreversible damage of the endothelial architecture. Moreover, tumor cells utilize leukocytes for their extravasation as linkers to the endothelium. Thus, metastasis formation is indirectly susceptible to localization signals that are literally specific for the immune system. We herein compare the extravasation of leukocytes and tumor cells with regard to the involved receptors and the localization signals that direct the cells to certain organs and sites of the body

The prognostic impact of the tumour stroma fraction: A machine learning-based analysis in 16 human solid tumour types

Background: The development of a reactive tumour stroma is a hallmark of tumour progression and pronounced tumour stroma is generally considered to be associated with clinical aggressiveness. The variability between tumour types regarding stroma fraction, and its prognosis associations, have not been systematically analysed.Methods: Using an objective machine-learning method we quantified the tumour stroma in 16 solid cancer types from 2732 patients, representing retrospective tissue collections of surgically resected primary tumours. Image analysis performed tissue segmentation into stromal and epithelial compartment based on pan-cytokeratin staining and autofluorescence patterns.Findings: The stroma fraction was highly variable within and across the tumour types, with kidney cancer showing the lowest and pancreato-biliary type periampullary cancer showing the highest stroma proportion (median 19% and 73% respectively). Adjusted Cox regression models revealed both positive (pancreato-biliary type periampullary cancer and oestrogen negative breast cancer, HR(95%CI)=0.56(0.34-0.92) and HR (95%CI)=0.41(0.17-0.98) respectively) and negative (intestinal type periampullary cancer, HR(95%CI)=3.59 (1.49-8.62)) associations of the tumour stroma fraction with survival.Interpretation: Our study provides an objective quantification of the tumour stroma fraction across major types of solid cancer. Findings strongly argue against the commonly promoted view of a general associations between high stroma abundance and poor prognosis. The results also suggest that full exploitation of the prognostic potential of tumour stroma requires analyses that go beyond determination of stroma abundance.</p