Search

Introduction: Immune cells in the tumour microenvironment are associated with prognosis and response to therapy. We aimed to comprehensively characterise the spatial im-mune 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 thorn 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., De två sista författarna delar sistaförfattarskapet

Background Smoking has shown interactions with bladder cancer (BC) genetic variants, especially N-acetyltransferase-2 (NAT2), a tobacco smoke metabolism gene, on BC risk. The interactions by disease aggressiveness are unknown. Methods We investigated the interaction between smoking and 18 single nucleotide polymorphisms (SNPs) for BC, individually and in a genetic risk score (GRS), on urothelial cancer (UC) risk including BC. We analysed data from 25,453 individuals with 520 incident UCs during follow-up, 339 non-aggressive (non-fatal, non-muscle invasive) and 163 aggressive (all other) UCs. Hazard ratios (HRs), absolute risks and additive and multiplicative interactions for two-by-two combinations of never/ever smoking with low/high genetic risk were calculated. Results Smoking and NAT2 rs1495741 interacted strongly, positively on aggressive UC on both the multiplicative (p = 0.004) and additive (p = 0.0002) scale, which was not observed for non-aggressive UC (pinteractions ≥ 0.6). This manifested in a higher HR of aggressive UC by ever smoking for the slow acetylation NAT2 genotype (HR, 5.00 [95% confidence interval, 2.67–9.38]) than for intermediate/fast acetylation NAT2 (HR, 1.50 [0.83–2.71]), and in differences in absolute risks by smoking and NAT2 genotype. Smoking also interacted additively and positively with the GRS on any UC (p = 0.01) and non-aggressive UC (p = 0.02), but not on aggressive UC (p = 0.1). Gene-smoking interactions of lesser magnitude than for NAT2 were found for SNPs in APOBEC3A, SLC14A1 and MYNN. Conclusions This study suggests that smoking increases UC risk more than expected when combined with certain genetic risks. Individuals with the slow acetylation NAT2 variant might particularly benefit from smoking intervention to prevent lethal UC; however, replication in larger studies is needed.

Cartilage oligomeric matrix protein (COMP) is an emerging regulator of tumor progression. The aim of this study was to evaluate the expression of COMP in periampullary adenocarcinoma with respect to prognostic value for survival and relapse, levels of fibrosis and infiltrating immune cells. COMP expression was evaluated using immunohistochemistry in primary tumors and subsets of paired lymph node metastases in tissue microarrays including 175 patients with periampullary adenocarcinoma. Collagen content was assessed with Sirius Red-Fast Green staining. High COMP levels were detected in cancer cells and in stroma, in 46% and 57% of the patients, respectively. High COMP expression was strongly associated with more aggressive pancreatobiliary-type (PB-type) compared to intestinal-type tumors (p < .0001). Importantly, high expression of COMP correlated with the exclusion of cytotoxic T-cells from the cancer cell compartment of the tumors, particularly in PB-type tumors. Higher levels of fibrosis measured by the density of collagen fibers correlated with high COMP levels in both cancer cells and stroma. This in turn could lead to exclusion of cytotoxic T-cells from accessing the cancer cells, a recognized immunotherapy resistance mechanism. Targeting COMP could therefore be considered as a novel therapeutic strategy in PB-type periampullary adenocarcinoma.

Background: Caveolin-1 (CAV1) is associated with cholesterol-rich membrane raft domains and is a master regulator of cell signaling and membrane transport. Here, we investigated CAV1's role in cellular compartments of breast cancer in relation to signaling pathways, clinicopathological features, and clinical outcomes. Methods: CAV1 levels were evaluated with immunohistochemistry in cytoplasm of invasive tumor cells and stromal cells in tumor tissue microarrays from a cohort of 1018 breast cancer patients (inclusion 2002-2012, Sweden). Cytoplasmic and stromal CAV1 were categorized as positive/negative and strong/not strong, respectively. CAV1 expression in relation to clinical outcomes was assessed with Cox regression. Investigations into CAV1 functional pathways was conducted in the STRING, GOBO, and TCGA databases. Results: CAV1 expression was associated with non-luminal subtypes, cell cycle control, inflammation, epithelialmesenchymal transition, and the IGF/Insulin system. Generally, CAV1 was not associated with recurrence risk. Stromal CAV1's impact on recurrence risk was modified by BMI > 25 kg/m(2) (P-interaction = 0.002), waist > 80 cm (P-interaction = 0.005), and invasive tumor size (pT2/3/4) (P-interaction = 0.028). In low-risk patients only, strong stromal CAV1 significantly increased recurrence risk (HRs(adj) > 1.61). In all patients, positive cytoplasmic CAV1 conferred > 2-fold risk for contralateral disease HRadj 2.63 (95% CI 1.36-5.10). Strong stromal CAV1 conferred nearly 2-fold risk for locoregional recurrence HRadj 1.88 (95% CI 1.09-3.24). Conclusions: CAV1's prognostic impact depended on its localization, anthropometric, and tumor factors. Stromal CAV1 predicted high recurrence risk in a group of supposedly "low-risk' patients. Cytoplasmic CAV1 predicted metachronous contralateral disease. If confirmed, CAV1 could be used as treatment target and for risk stratification.