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White adipose tissue (WAT) is an essential regulator of energy storage and systemic metabolic homeostasis. Regulatory networks consisting of immune and structural cells are necessary to maintain WAT metabolism, which can become impaired during obesity in mammals. Using single-cell transcriptomics and flow cytometry, we unveil a large-scale comprehensive cellular census of the stromal vascular fraction of healthy lean and obese human WAT. We report new subsets and developmental trajectories of adipose-resident innate lymphoid cells, dendritic cells and monocyte-derived macrophage populations that accumulate in obese WAT. Analysis of cell–cell ligand–receptor interactions and obesity-enriched signaling pathways revealed a switch from immunoregulatory mechanisms in lean WAT to inflammatory networks in obese WAT. These results provide a detailed and unbiased cellular landscape of homeostatic and inflammatory circuits in healthy human WAT. Immune cells exert important effects on white adipose tissue (WAT) in metabolic diseases. O’Sullivan and colleagues generate a comprehensive single-cell atlas of WAT cells in both health and disease to identify new cellular networks and differentiation trajectories.

A common complementary strategy in Genome-Wide Association Studies (GWAS) is to perform Gene Set Analysis (GSA), which tests for the association between one phenotype of interest and an entire set of Single Nucleotide Polymorphisms (SNPs) residing in selected genes. While there exist many tools for performing GSA, popular methods often include a number of ad-hoc steps that are difficult to justify statistically, provide complicated interpretations based on permutation inference, and demonstrate poor operating characteristics. Additionally, the lack of gold standard gene set lists can produce misleading results and create difficulties in comparing analyses even across the same phenotype. We introduce the Generalized Berk-Jones (GBJ) statistic for GSA, a permutation-free parametric framework that offers asymptotic power guarantees in certain set-based testing settings. To adjust for confounding introduced by different gene set lists, we further develop a GBJ step-down inference technique that can discriminate between gene sets driven to significance by single genes and those demonstrating group-level effects. We compare GBJ to popular alternatives through simulation and re-analysis of summary statistics from a large breast cancer GWAS, and we show how GBJ can increase power by incorporating information from multiple signals in the same gene. In addition, we illustrate how breast cancer pathway analysis can be confounded by the frequency of FGFR2 in pathway lists. Our approach is further validated on two other datasets of summary statistics generated from GWAS of height and schizophrenia.

Over the past two decades of successive clinical trials in metastatic colorectal cancer (CRC), the median overall survival of both control and experimental arms has steadily improved. However, the incremental change in survival for metastatic CRC patients not treated on trial has not yet been quantified. We performed a retrospective review of 1420 patients with de novo metastatic CRC who received their primary treatment at the University of Texas M.D. Anderson Cancer Center (UTMDACC) from 2004 through 2019. Median OS was roughly stable for patients diagnosed between 2004 and 2012 (22.6 months) but since has steadily improved for those diagnosed in 2013 to 2015 (28.8 months), and 2016 to 2019 (32.4 months). Likewise, 5-year survival rate has increased from 15.7% for patients diagnosed from 2004 to 2006 to 26% for those diagnosed from 2013 to 2015. Notably, survival improved for patients with BRAF V600E mutant as well as microsatellite unstable (MSI-H) tumors. Multivariate regression analysis identified surgical resection of liver metastasis (HR = 0.26, 95% CI, 0.19–0.37), use of immunotherapy (HR = 0.44, 95% CI, 0.29–0.67) and use of third line chemotherapy (regorafenib or trifluridine/tipiracil, HR = 0.74, 95% CI, 0.58–0.95), but not year of diagnosis (HR = 0.99, 95% CI, 0.98–1), as associated with better survival, suggesting that increased use of these therapies are the drivers of the observed improvement in survival.

Immune checkpoint therapy (ICT) provides substantial clinical benefits to cancer patients, but a large proportion of cancers do not respond to ICT. To date, the genomic underpinnings of primary resistance to ICT remain elusive. Here, we performed immunogenomic analysis of data from TCGA and clinical trials of anti-PD-1/PD-L1 therapy, with a particular focus on homozygous deletion of 9p21.3 (9p21 loss), one of the most frequent genomic defects occurring in ~13% of all cancers. We demonstrate that 9p21 loss confers “cold” tumor-immune phenotypes, characterized by reduced abundance of tumor-infiltrating leukocytes (TILs), particularly, T/B/NK cells, altered spatial TILs patterns, diminished immune cell trafficking/activation, decreased rate of PD-L1 positivity, along with activation of immunosuppressive signaling. Notably, patients with 9p21 loss exhibited significantly lower response rates to ICT and worse outcomes, which were corroborated in eight ICT trials of >1,000 patients. Further, 9p21 loss synergizes with PD-L1/TMB for patient stratification. A “response score” was derived by incorporating 9p21 loss, PD-L1 expression and TMB levels in pre-treatment tumors, which outperforms PD-L1, TMB, and their combination in identifying patients with high likelihood of achieving sustained response from otherwise non-responders. Moreover, we describe potential druggable targets in 9p21-loss tumors, which could be exploited to design rational therapeutic interventions. The molecular mechanisms of resistance to immune checkpoint therapy remain elusive. Here, the authors perform immunogenomic analysis of TCGA data and data from clinical trials for antiPD-1/PD-L1 therapy and highlight the association of 9p21 loss with a cold tumor microenvironment and resistance to therapy.

Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program cohort (approximately 95% male cases) and a previous study of European-ancestry individuals, jointly comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We then carry out conditional meta-analyses on cigarettes per day and identify two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in squamous cell lung carcinoma. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma, and squamous cell lung carcinoma, nine of which are externally replicated. Finally, we perform PheWAS on polygenic risk scores for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer polygenic risk score is associated with smoking status in controls, illustrating a reduced predictive utility in non-smokers. Additionally, our polygenic risk score demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits. Lung cancer is the leading cause of cancer mortality, despite declining smoking rates. Gorman et al. report multi-ancestry GWAS meta-analyses of lung cancer providing insights into smoking-independent genetic predisposition to the disease.

Arsenic (As) exposure adversely affects neurodevelopment in children. Accumulation of misfolded proteins in cells exposed to As leads to endoplasmic reticulum (ER) stress response, which, if not relieved, results in cell death. Despite the potential role of ER stress for As-induced neurotoxicity, the underlying mechanisms remain poorly understood. Here we aimed to investigate the roles of microRNA(miR)-124, a novel ER stress suppressor, in As-induced ER stress response and cytotoxicity in neural cells. We further aimed to link these in vitro findings to neurodevelopmental outcomes in children who were exposed to As. Using Quantitative RT-PCR and Cyquant assay, we showed that miR-124 protects against As-induced cytotoxicity in neural cells with concomitant suppression of As-induced ER stress. In addition, As-induced cytotoxicity was exacerbated in miR-124 knockout cells generated by CRISPR-based gene editing compared scramble control. Furthermore, we identified two miR-124 SNPs rs67543816 (p = 0.0003) and rs35418153 (p = 0.0004) that are significantly associated with a mental composite score calculated from the Bayley Scales of Infant Development III in Bangladesh children. Our study reveals As-induced ER stress as a crucial mechanism underlying the toxic effects of As on neural cell function and neurodevelopment and identifies miR-124 as a potential preventative and therapeutic target against detrimental effects of As exposure in children.

Ras plays an essential role in the development of acinar-to-ductal metaplasia (ADM) and pancreatic ductal adenocarcinoma (PDAC). However, mutant Kras is an inefficient driver for PDAC development. The mechanisms of the switching from low Ras activity to high Ras activity that are required for development and progression of pancreatic intraepithelial neoplasias (PanINs) are unclear. In this study, we found that hematopoietic progenitor kinase 1 (HPK1) was upregulated during pancreatic injury and ADM. HPK1 interacted with the SH3 domain and phosphorylated Ras GTPase-activating protein (RasGAP) and upregulated RasGAP activity. Using transgenic mouse models of HPK1 or M46, a kinase-dead mutant of HPK1, we showed that HPK1 inhibited Ras activity and its downstream signaling and regulated acinar cell plasticity. M46 promoted the development of ADM and PanINs. Expression of M46 in KrasG12D Bac mice promoted the infiltration of myeloid-derived suppressor cells and macrophages, inhibited the infiltration of T cells, and accelerated the progression of PanINs to invasive and metastatic PDAC, while HPK1 attenuated mutant Kras-driven PanIN progression. Our results showed that HPK1 plays an important role in ADM and the progression of PanINs by regulating Ras signaling. Loss of HPK1 kinase activity promotes an immunosuppressive tumor microenvironment and accelerates the progression of PanINs to PDAC.

Complex interplay between genetic and environmental factors characterizes the etiology of many diseases. Modeling gene-environment (GxE) interactions is often challenged by the unknown functional form of the environment term in the true data-generating mechanism. We study the impact of misspecification of the environmental exposure effect on inference for the GxE interaction term in linear and logistic regression models. We first examine the asymptotic bias of the GxE interaction regression coefficient, allowing for confounders as well as arbitrary misspecification of the exposure and confounder effects. For linear regression, we show that under gene-environment independence and some confounder-dependent conditions, when the environment effect is misspecified, the regression coefficient of the GxE interaction can be unbiased. However, inference on the GxE interaction is still often incorrect. In logistic regression, we show that the regression coefficient is generally biased if the genetic factor is associated with the outcome directly or indirectly. Further, we show that the standard robust sandwich variance estimator for the GxE interaction does not perform well in practical GxE studies, and we provide an alternative testing procedure that has better finite sample properties.

High stromal tumor-infiltrating lymphocytes (sTILs) are associated with improved pathologic complete response (pCR) in triple-negative breast cancer (TNBC). We hypothesize that integrating high sTILs and additional clinicopathologic features associated with pCR could enhance our ability to predict the group of patients on whom treatment de-escalation strategies could be tested. In this prospective early-stage TNBC neoadjuvant chemotherapy study, pretreatment biopsies from 408 patients were evaluated for their clinical and demographic features, as well as biomarkers including sTILs, Ki-67, PD-L1 and androgen receptor. Multivariate logistic regression models were developed to generate a computed response score to predict pCR. The pCR rate for the entire cohort was 41%. Recursive partitioning analysis identified ≥20% as the optimal cutoff for sTILs to denote 35% (143/408) of patients as having high sTILs, with a pCR rate of 59%, and 65% (265/408) of patients as having low sTILs, with a pCR rate of 31%. High Ki-67 (cutoff > 35%) was identified as the only predictor of pCR in addition to sTILs in the training set. This finding was verified in the testing set, where the highest computed response score encompassing both high sTILa and high Ki-67 predicted a pCR rate of 65%. Integrating Ki67 and sTIL may refine the selection of early stage TNBC patients for neoadjuvant clinical trials evaluating de-escalation strategies.

Background Survivors of childhood cancer are at risk for therapy-related dental diseases. The purpose of the study was to investigate the associations between clinical, socioeconomic, and demographic factors and oral diseases in the St. Jude Lifetime Cohort (SJLIFE) participants. Methods We performed a retrospective medical chart review and evaluated longitudinal self-reported dental outcomes in 4856 childhood cancer survivors and 591 community controls participating in the St. Jude Lifetime Cohort (SJLIFE) study. Univariate and multivariable logistic regression models were used to assess the impact of socioeconomic factors, treatment exposures and patient demographics on dental outcomes. Results Cancer survivors were more likely to report microdontia (odds ratio (OR) = 7.89, 95% confidence interval (CI) [4.64, 14.90]), abnormal root development (OR = 6.19, CI [3.38, 13.00]), hypodontia (OR = 2.75, CI [1.83, 4.33]), enamel hypoplasia (OR = 4.24, CI [2.9, 6.49]), xerostomia (OR = 7.72, CI [3.27, 25.10]), severe gingivitis (OR = 2.04, CI [1.43, 3.03]), and ≥ 6 missing teeth (OR = 3.73, CI [2.46, 6.00]) compared to controls without cancer history. Survivors who received classic alkylating agents (OR = 1.6, CI [1.36, 1.88]), anthracycline antibiotics (OR = 1.22, CI [1.04, 1.42] or radiation therapy potentially exposing the oral cavity (OR = 1.48, CI [1.26, 1.72]) were more likely to report at least one dental health problem after controlling for socioeconomic factors, age at last follow-up and diagnosis, other treatment exposures, and access to dental services. Survivors who had radiation therapy potentially exposing the oral cavity (OR = 1.52, CI [1.25, 1.84]) were also more likely to report at least one soft tissue abnormality after controlling for socioeconomic factors, age at last follow-up and diagnosis, other treatment exposures, and access and utilization of dental services. Conclusions Childhood cancer survivors have a higher prevalence of oral-dental abnormalities than the controls without a cancer history. Cancer treatment, socioeconomic factors, and access to oral health care contribute to the prevalence of dental abnormalities.