Gender differences in health-related quality of life of adolescents with cystic fibrosis

BACKGROUND: Female patients with cystic fibrosis (CF) have consistently poorer survival rates than males across all ages. To determine if gender differences exist in health-related quality of life (HRQOL) of adolescent patients with CF, we performed a cross-section analysis of CF patients recruited from 2 medical centers in 2 cities during 1997–2001. METHODS: We used the 87-item child self-report form of the Child Health Questionnaire to measure 12 health domains. Data was also collected on age and forced expiratory volume in 1 second (FEV(1)). We analyzed data from 98 subjects and performed univariate analyses and linear regression or ordinal logistic regression for multivariable analyses. RESULTS: The mean (SD) age was 14.6 (2.5) years; 50 (51.0%) were female; and mean FEV(1 )was 71.6% (25.6%) of predicted. There were no statistically significant gender differences in age or FEV(1). In univariate analyses, females reported significantly poorer HRQOL in 5 of the 12 domains. In multivariable analyses controlling for FEV(1 )and age, we found that female gender was associated with significantly lower global health (p < 0.05), mental health (p < 0.01), and general health perceptions (p < 0.05) scores. CONCLUSION: Further research will need to focus on the causes of these differences in HRQOL and on potential interventions to improve HRQOL of adolescent patients with CF

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Interferon-gamma signature as prognostic and predictive marker in macroscopic stage III melanoma

BACKGROUND: A substantial proportion of patients with macroscopic stage III melanoma do not benefit sufficiently from adjuvant anti-PD-1 therapy, as they either recur despite therapy or would never have recurred. To better inform adjuvant treatment selection, we have performed translational analyses to identify prognostic and predictive biomarkers. PATIENTS AND METHODS: Two cohorts of patients with macroscopic stage III melanoma from an ongoing biobank study were included. Clinical data were compared between an observation cohort (cohort 1) and an adjuvant intention cohort (cohort 2). RNA sequencing for translational analyses was performed and treatment subgroups (cohort 1A and cohort 2A) were compared for possible biomarkers, using a cut-off based on the treatment-naïve patients. In addition, two validation cohorts (Melanoma Institute Australia (MIA) and University Medical Centre Utrecht (UMCU)) were obtained. RESULTS: After a median follow-up of 26 months of the 98 patients in our discovery set, median recurrence-free survival (RFS) was significantly longer for the adjuvant intention cohort (cohort 2, n=49) versus the observation cohort (cohort 1, n=49). Median overall survival was not reached for either cohort, nor significantly different. In observation cohort 1A (n=24), RFS was significantly longer for patients with high interferon-gamma (IFNγ) score (p=0.002); for adjuvant patients of cohort 2A (n=24), a similar trend was observed (p=0.086). Patients with high B cell score had a longer RFS in cohort 1A, but no difference was seen in cohort 2A. The B cell score based on RNA correlated with CD20 + cells in tumor area but was not independent from the IFNγ score. In the MIA validation cohort (n=44), longer RFS was observed for patients with high IFNγ score compared with low IFNγ score (p=0.046), no difference in RFS was observed according to the B cell score. In both the observation (n=11) and the adjuvant (n=11) UMCU validation cohorts, no difference in RFS was seen for IFNγ and B cell. CONCLUSIONS: IFNγ has shown to be a prognostic marker in both patients who were and were not treated with adjuvant therapy. B cell score was prognostic but did not improve accuracy over IFNγ. Our study confirmed RFS benefit of adjuvant anti-PD-1 for patients with macroscopic stage III melanoma

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Targeted agents and immunotherapies: optimizing outcomes in melanoma

Treatment options for patients with metastatic melanoma, and especially BRAF-mutant melanoma, have changed dramatically in the past 5 years, with the FDA approval of eight new therapeutic agents. During this period, the treatment paradigm for BRAF-mutant disease has evolved rapidly: the standard-of-care BRAF-targeted approach has shifted from single-agent BRAF inhibition to combination therapy with a BRAF and a MEK inhibitor. Concurrently, immunotherapy has transitioned from cytokine-based treatment to antibody-mediated blockade of the cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4) and, now, the programmed cell-death protein 1 (PD-1) immune checkpoints. These changes in the treatment landscape have dramatically improved patient outcomes, with the median overall survival of patients with advanced-stage melanoma increasing from approximately 9 months before 2011 to at least 2 years - and probably longer for those with BRAF-V600-mutant disease. Herein, we review the clinical trial data that established the standard-of-care treatment approaches for advanced-stage melanoma. Mechanisms of resistance and biomarkers of response to BRAF-targeted treatments and immunotherapies are discussed, and the contrasting clinical benefits and limitations of these therapies are explored. We summarize the state of the field and outline a rational approach to frontline-treatment selection for each individual patient with BRAF-mutant melanoma

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation