The Use of HCG‐Based Combination Therapy for Recovery of Spermatogenesis after Testosterone Use

Introduction and AimAbout 3 million men take testosterone in the United States with many reproductive‐age men unaware of the negative impact of testosterone supplementation on fertility. Addressing this population, we provide an early report on the use of human chorionic gonadotropin (HCG)‐based combination therapy in the treatment of a series of men with likely testosterone‐related azoospermia or severe oligospermia. MethodsWe retrospectively reviewed charts from two tertiary care infertility clinics to identify men presenting with azoospermia or severe oligospermia (<1 million sperm/mL) while taking exogenous testosterone. All were noted to have been placed on combination therapy, which included 3,000 units HCG subcutaneously every other day supplemented with clomiphene citrate, tamoxifen, anastrozole, or recombinant follicle‐stimulating hormone (or combination) according to physician preference.Main Outcome MeasureClinical outcomes, including hormone values, semen analyses, and clinical pregnancies, were tracked. ResultsForty‐nine men were included in this case series. Return of spermatogenesis for azoospermic men or improved counts for men with severe oligospermia was documented in 47 men (95.9%), with one additional man (2.1%) having a documented pregnancy without follow‐up semen analysis. The average time to return of spermatogenesis was 4.6 months with a mean first density of 22.6 million/mL. There was no significant difference in recovery by type of testosterone administered or supplemental therapy. No men stopped HCG or supplemental medications because of adverse events. ConclusionsWe here provide an early report of the feasibility of using combination therapy with HCG and supplemental medications in treating men with testosterone‐related infertility. Future discussion and studies are needed to further characterize this therapeutic approach and document the presumed improved tolerability and speed of recovery compared with unaided withdrawal of exogenous testosterone. Wenker EP, Dupree JM, Langille GM, Kovac J, Ramasamy R, Lamb D, Mills JN, and Lipshultz LI. The use of HCG‐based combination therapy for recovery of spermatogenesis after testosterone use. J Sex Med 2015;12:1334–1337.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111925/1/jsm12890.pd

Succinate Dehydrogenase Supports Metabolic Repurposing of Mitochondria to Drive Inflammatory Macrophages.

Activated macrophages undergo metabolic reprogramming, which drives their pro-inflammatory phenotype, but the mechanistic basis for this remains obscure. Here, we demonstrate that upon lipopolysaccharide (LPS) stimulation, macrophages shift from producing ATP by oxidative phosphorylation to glycolysis while also increasing succinate levels. We show that increased mitochondrial oxidation of succinate via succinate dehydrogenase (SDH) and an elevation of mitochondrial membrane potential combine to drive mitochondrial reactive oxygen species (ROS) production. RNA sequencing reveals that this combination induces a pro-inflammatory gene expression profile, while an inhibitor of succinate oxidation, dimethyl malonate (DMM), promotes an anti-inflammatory outcome. Blocking ROS production with rotenone by uncoupling mitochondria or by expressing the alternative oxidase (AOX) inhibits this inflammatory phenotype, with AOX protecting mice from LPS lethality. The metabolic alterations that occur upon activation of macrophages therefore repurpose mitochondria from ATP synthesis to ROS production in order to promote a pro-inflammatory state

Trends in non-metastatic prostate cancer management in the Northern and Yorkshire region of England, 2000–2006

Background: Our objective was to analyse variation in non-metastatic prostate cancer management in the Northern and Yorkshire region of England. Methods: We included 21 334 men aged ⩾55, diagnosed between 2000 and 2006. Principal treatment received was categorised into radical prostatectomy (11%), brachytherapy (2%), external beam radiotherapy (16%), hormone therapy (42%) and no treatment (29%). Results: The odds ratio (OR) for receiving a radical prostatectomy was 1.53 in 2006 compared with 2000 (95% CI 1.26–1.86), whereas the OR for receiving hormone therapy was 0.57 (0.51–0.64). Age was strongly associated with treatment received; radical treatments were significantly less likely in men aged ⩾75 compared with men aged 55–64 years, whereas the odds of receiving hormone therapy or no treatment were significantly higher in the older age group. The OR for receiving radical prostatectomy, brachytherapy or external beam radiotherapy were all significantly lower in the most deprived areas when compared with the most affluent (0.64 (0.55–0.75), 0.32 (0.22–0.47) and 0.83 (0.74–0.94), respectively) whereas the OR for receiving hormone therapy was 1.56 (1.42–1.71). Conclusions: This study highlights the variation and inequalities that exist in the management of non-metastatic prostate cancer in the Northern and Yorkshire region of England

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

The Role of Whole Blood Impedance Aggregometry and Its Utilisation in the Diagnosis and Prognosis of Patients with Systemic Inflammatory Response Syndrome and Sepsis in Acute Critical Illness

Objective: To assess the prognostic and diagnostic value of whole blood impedance aggregometry in patients with sepsis and SIRS and to compare with whole blood parameters (platelet count, haemoglobin, haematocrit and white cell count). Methods: We performed an observational, prospective study in the acute setting. Platelet function was determined using whole blood impedance aggregometry (multiplate) on admission to the Emergency Department or Intensive Care Unit and at 6 and 24 hours post admission. Platelet count, haemoglobin, haematocrit and white cell count were also determined. Results: 106 adult patients that met SIRS and sepsis criteria were included. Platelet aggregation was significantly reduced in patients with severe sepsis/septic shock when compared to SIRS/uncomplicated sepsis (ADP: 90.7±37.6 vs 61.4±40.6; p<0.001, Arachadonic Acid 99.9±48.3 vs 66.3±50.2; p = 0.001, Collagen 102.6±33.0 vs 79.1±38.8; p = 0.001; SD ± mean)). Furthermore platelet aggregation was significantly reduced in the 28 day mortality group when compared with the survival group (Arachadonic Acid 58.8±47.7 vs 91.1±50.9; p<0.05, Collagen 36.6±36.6 vs 98.0±35.1; p = 0.001; SD ± mean)). However haemoglobin, haematocrit and platelet count were more effective at distinguishing between subgroups and were equally effective indicators of prognosis. Significant positive correlations were observed between whole blood impedance aggregometry and platelet count (ADP 0.588 p<0.0001, Arachadonic Acid 0.611 p<0.0001, Collagen 0.599 p<0.0001 (Pearson correlation)). Conclusions: Reduced platelet aggregometry responses were not only significantly associated with morbidity and mortality in sepsis and SIRS patients, but also correlated with the different pathological groups. Whole blood aggregometry significantly correlated with platelet count, however, when we adjust for the different groups we investigated, the effect of platelet count appears to be non-significant

The effect of sepsis and its inflammatory response on mechanical clot characteristics: a prospective observational study

Purpose: Sepsis and its progression are known to have a major influence on the coagulation system. Current coagulation tests are of limited use when assessing coagulation in sepsis patients. This study aims to assess the potential for a new functional biomarker of clot microstructure, fractal dimension, to identify changes in the mechanical properties of clot microstructure across the sepsis spectrum (sepsis, severe sepsis and septic shock). Methods: A total of 100 patients that presented acutely to a large teaching hospital were included in this prospective observational study (50 sepsis, 20 severe sepsis and 30 septic shock) against a matched control of 44 healthy volunteers. Fractal analysis was performed, as well as standard markers of coagulation, and six plasma markers of inflammation. Results: Fractal dimension was significantly higher in the sepsis and severe sepsis groups than the healthy control (1.78 ± 0.07 and 1.80 ± 0.05 respectively vs 1.74 ± 0.03) (p < 0.001), indicating a significant increase in mechanical clot strength and elasticity consistent with a hypercoagulable state. Conversely, fractal dimension was significantly lower in septic shock (1.66 ± 0.10, p < 0.001), indicating a significant reduction in mechanical clot strength and functionality consistent with a hypocoagulable state. This corresponded with a significant increase in the inflammatory response. Conclusions: This study confirms that clot microstructure is significantly altered through the various stages of sepsis. Of particular importance was the marked change in clot development between severe sepsis and septic shock, which has not been previously reported

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

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

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