Immunological biomarkers in prostate cancer - A retrospective cohort study utilizing immunohistochemistry on tissue microarrays for evaluation of immune biomarker expression and experimental in vitro assays

Background: Prostate cancer is a very common, but particularly heterogenic cancer form. Whilst some patients have a very aggressive course with a fatal outcome, the majority of patients have slow-growing disease with low risk of death or significant symptoms. Unfortunately, doctors do not possess sufficient prognostic tools, and there is a high risk of overtreatment with unnecessary side-effects. We set out to find new biomarkers for prognostic stratification of prostate cancer patients, and possibly at the same time generate hypotheses for potential therapeutic targets. We chose to analyze different immune system markers as the immune system is known to be a key player in cancer development. Material and methods: Patient data and prostatectomy specimens from 535 Norwegian patients with primary prostate cancer was collected retrospectively. Tissue microarrays were constructed from tumor areas as well as non-malignant areas. Immunohistochemistry was used to evaluate amount of intratumoral CD3+, CD4+, CD8+, CD20+ and PD-L1+ lymphocytes as well as expression of PD-L1, CXCR6 and CXCL16 by both prostate cancer cells and tumor stromal cells. Further, we investigated the independent prognostic effect of each biomarker, as well as their correlation with each other and well-known clinical- and histopathological parameters. Main results: A high amount/expression of CD8+ lymphocytes, PD-1+ lymphocytes, CXCR6 and CXCL16 independently predicted a worse prognosis. PD-L1 expression was commonly expressed by prostate cancer cells, and a high expression consistently correlated to worse prognosis, but results were not statistically significant. Conclusions: Based on our observations, we propose further investigation of the biological mechanisms and prognostic effect of CD8, PD-1, PD-L1, CXCR6 and CXCL16 in prostate cancer. Hopefully one or more of these markers may improve risk stratification of PCa patients and may even be of value as targets of therapy in future PCa treatment

Disease-specific outcomes of Radical Prostatectomies in Northern Norway; A case for the impact of perineural infiltration and postoperative PSA-doubling time

Background Prostate cancer is the most common male malignancy and a mayor cause of mortality in the western world. The impact of clinicopathological variables on disease related outcomes have mainly been reported from a few large US series, most of them not reporting on perineural infiltration. We therefore wanted to investigate relevant cancer outcomes in patients undergoing radical prostatectomy in two Norwegian health regions with an emphasis on the impact of perineural infiltration (PNI) and prostate specific antigen- doubling time (PSA-DT). Methods We conducted a retrospective analysis of 535 prostatectomy patients at three hospitals between 1995 and 2005 estimating biochemical failure- (BFFS), clinical failure- (CFFS) and prostate cancer death-free survival (PCDFS) with the Kaplan-Meier method. We investigated clinicopathological factors influencing risk of events using cox proportional hazard regression. Results After a median follow-up of 89 months, 170 patients (32%) experienced biochemical failure (BF), 36 (7%) experienced clinical failure and 15 (3%) had died of prostate cancer. pT-Stage (p = 0.001), preoperative PSA (p = 0.047), Gleason Score (p = 0.032), non-apical positive surgical margins (PSM) (p = 0.003) and apical PSM (p = 0.031) were all independently associated to BFFS. Gleason score (p = 0.019), PNI (p = 0.012) and non-apical PSM (p = 0.002) were all independently associated to CFFS while only PNI (P = 0.047) and subgroups of Gleason score were independently associated to PCDFS. After BF, patients with a shorter PSA-DT had independent and significant worse event-free survivals than patients with PSA-DT > 15 months (PSA-DT = 3-9 months, CFFS HR = 6.44, p < 0.001, PCDFS HR = 13.7, p = 0.020; PSA-DT < 3 months, CFFS HR = 11.2, p < 0.001, PCDFS HR = 27.5, p = 0.006). Conclusions After prostatectomy, CFFS and PCDFS are variable, but both are strongly associated to Gleason score and PNI. In patients with BF, PSA-DT was most strongly associated to CF and PCD. Our study adds weight to the importance of PSA-DT and re-launches PNI as a strong prognosticator for clinically relevant endpoints

Assessing PDL-1 and PD-1 in NoneSmall Cell Lung Cancer: A Novel Immunoscore Approach

Published version. Source at http://dx.doi.org/10.1016/j.cllc.2016.09.009 Novel immune biomarkers could complement the TNM classification for nonesmall cell cancer (NSCLC), improving the prognostic accuracy. The present study evaluated the prognostic significance of the immune checkpoint molecules programmed cell death protein 1 (PD-1) and PD-1 ligand (PD-L1) in 536 patients with stage I to IIIA NSCLC using an Immunoscore approach. Independently, and in combination, the infiltration of immune cells expressing PD-L1 and PD-1 predicted patient survival, supplementing the TNM classification in each stage. Introduction: Immune checkpoint inhibitors targeting programmed cell death protein 1 (PD-1) or its ligand, PD-L1, have gained momentum in the treatment of nonesmall cell lung cancer (NSCLC). However, their prognostic significance remains controversial. The present study evaluated the expression of PD-L1 and PD-1 and their potential role in an Immunoscore, supplementing the TNM classification of NSCLC. Materials and Methods: Tissue microarrays constructed from tumor tissue samples from 2 cohorts of a total of 536 patients (University Hospital of North Norway, n ¼ 285; Nordland Hospital, n ¼ 251) with primary resected stage I to IIIA NSCLC. PD-L1 and PD-1 were evaluated by immunohistochemistry in the primary tumor and metastatic lymph node tissue. Results: In univariate analysis, a high density of PD-L1þ immune cells in the stromal compartment (S-PD-L1) and PD-1þ intraepithelial tumor infiltrating lymphocytes (T-PD-1) was associated with favorable disease-specific survival (DSS; S-PD-L1, P ¼ .004; T-PD-1, P ¼ .012), both limited to the squamous cell carcinoma histologic subgroup (S-PD-L1, P ¼ .002; T-PD-1, P ¼ .034). A combined low S-PD-L1 and T-PD-1 was associated with poor survival in all patients (DSS: hazard ratio [HR], 1.81; 95% confidence interval [CI], 1.37-2.40; P < .001) at both centers and for all pathologic stages. In multivariate analysis, S-PD-L1 and T-PD-1 were independent positive prognostic factors, and combined low scores remained an independent prognosticator for poor survival (DSS: HR, 1.72; 95% CI, 1.29-2.28; P < .001; disease-free survival, P ¼ .001; overall survival, P ¼ .005). Conclusion: Our study identified S-PD-L1 and T-PD-1 as independent positive prognostic factors for NSCLC patients. Their combination added significant prognostic impact within each pathologic stage and hence are feasible to include in a TNM Immunoscore

Inequalities in health: a comparative study between ethnic Norwegians and Pakistanis in Oslo, Norway

BACKGROUND: The objective of the study was to observe the inequality in health from the perspective of socio-economic factors in relation to ethnic Pakistanis and ethnic Norwegians in Oslo, Norway. METHOD: Data was collected by using an open and structured questionnaire, as a part of the Oslo Health Study 2000–2001. Accordingly 13581 ethnic Norwegians (45% of the eligible) participated as against 339 ethnic Pakistanis (38% of the eligible). RESULTS: The ethnic Pakistanis reported a higher prevalence of poor self-rated health 54.7% as opposed to 22.1% (p < 0.001) in ethnic Norwegians, 14% vs. 2.6% (p < 0.001) in diabetes, and 22.0% vs. 9.9% (p < 0.001) in psychological distress. The socio-economic conditions were inversely related to self- rated health, diabetes and distress for the ethnic Norwegians. However, this was surprisingly not the case for the ethnic Pakistanis. Odd ratios did not interfere with the occurrence of diabetes, even after adjusting all the markers of socio-economic status in the multivariate model, while self-reported health and distress showed moderate reduction in the risk estimation. CONCLUSION: There is a large diversity of self-rated health, prevalence of diabetes and distress among the ethnic Pakistanis and Norwegians. Socio-economic status may partly explain the observed inequalities in health. Uncontrolled variables like genetics, lifestyle factors and psychosocial factors related to migration such as social support, community participation, discrimination, and integration may have contributed to the observed phenomenon. This may underline the importance of a multidisciplinary approach in future studies

Shared heritability and functional enrichment across six solid cancers

Correction: Nature Communications 10 (2019): art. 4386 DOI: 10.1038/s41467-019-12095-8Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.Peer reviewe

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types.

UNLABELLED: Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis. SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.The Breast Cancer Association Consortium (BCAC), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL), and the Ovarian Cancer Association Consortium (OCAC) that contributed breast, prostate, and ovarian cancer data analyzed in this study were in part funded by Cancer Research UK [C1287/A10118 and C1287/A12014 for BCAC; C5047/A7357, C1287/A10118, C5047/A3354, C5047/A10692, and C16913/A6135 for PRACTICAL; and C490/A6187, C490/A10119, C490/A10124, C536/A13086, and C536/A6689 for OCAC]. Funding for the Collaborative Oncological Gene-environment Study (COGS) infrastructure came from: the European Community's Seventh Framework Programme under grant agreement number 223175 (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, and C8197/A16565), the US National Institutes of Health (CA128978) and the Post-Cancer GWAS Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (1U19 CA148537, 1U19 CA148065, and 1U19 CA148112), the US Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund [with donations by the family and friends of Kathryn Sladek Smith (PPD/RPCI.07)]. Additional financial support for contributing studies is documented under Supplementary Financial Support.This is the author accepted manuscript. The final version is available from the American Association for Cancer Research via http://dx.doi.org/10.1158/2159-8290.CD-15-122

Global urban environmental change drives adaptation in white clover

Urbanization transforms environments in ways that alter biological evolution. We examined whether urban environmental change drives parallel evolution by sampling 110,019 white clover plants from 6169 populations in 160 cities globally. Plants were assayed for a Mendelian antiherbivore defense that also affects tolerance to abiotic stressors. Urban-rural gradients were associated with the evolution of clines in defense in 47% of cities throughout the world. Variation in the strength of clines was explained by environmental changes in drought stress and vegetation cover that varied among cities. Sequencing 2074 genomes from 26 cities revealed that the evolution of urban-rural clines was best explained by adaptive evolution, but the degree of parallel adaptation varied among cities. Our results demonstrate that urbanization leads to adaptation at a global scale

Shared heritability and functional enrichment across six solid cancers

Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis