Mapping trabecular disconnection "hotspots" in aged human spine and hip

Trabecular bone disconnection is an independent factor in age-related skeletal failure where real termini (ReTm; rare in youth) may cause weakness disproportionate to tissue loss, yet their structural contribution at vulnerable locations remains uncertain. ReTm (previously recorded at the iliac crest) were mapped in "normal" aged vertebral bodies (T11-L5 autopsy; 20 females, 10 males) and corresponding proximal femora (autopsy; 10 females). Results were compared with biomechanically failed femora from orthopaedic subjects aged >. 58. yr (osteoporosis OP, 10 females; osteoarthritis OA, 10 females). A novel direct 2D/3D histological method was applied to large, thick (300. μm) slices superficially silver-stained to separate ReTm (unstained) from apparent termini (planar artefacts, brown). Light microscope field co-ordinates enabled ReTm mapping and statistical testing relative to i) sex, ii) tissue sector and iii) slicing plane. In men ReTm populations were small and random while in women they were large and sector-specific. In vertebrae they clustered anterior/superior being rare posterior/inferior; in the femoral head they concentrated distal/superior and also near the fovea, being fewer distal/inferior. A distribution polarity was evident with 100% more ReTm observed transversely (i.e., on tensile-related cross struts) than longitudinally (i.e., on compression-related vertical struts). Their numbers rose in OP (BV/TV. . 14%), remaining polarised and sector-specific in OP only. Comparative experimentation by marrow elution of an OP animal model demonstrated "floating segments" as a possible outcome. Conclusions were supported statistically that trabecular disconnection "hotspots" at vulnerable locations are sex- and sector-specific, mainly transaxial, and subject to disease modulation

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

Identification of women at risk for developing postmenopausal osteoporosis with vertebral fractures: role of history and single photon absorptiometry

Putative risk factors for the development of postmenopausal osteoporosis (PMO) with vertebral fractures were examined in a retrospective study of 663 postmenopausal white females aged 45-75 years (266 women with non-traumatic vertebral compression fractures (VF+), 134 non-fractured women from a general medicine clinic (controls) and 263 non-fractured women who were evaluated when they presented specifically for osteoporosis screening (VF-)). The VF+ women differed from control women in several respects. The VF+ group reported a higher prevalence of a positive family history of osteoporosis, and a higher prevalence of a history of medical or surgical conditions known to be independently associated with metabolic bone disease, had fewer children, were smaller (weight, height) and were slightly older. The two groups, VF+ and controls, did not differ with respect to cigarette smoking, alcohol consumption, exercise habits, menstrual or menopausal history, dietary intake of milk and cheese or in amount taking calcium supplements during pregnancy.The VF+ group also differed in certain respects from the VF- group. The VF+ group were smaller (weight, height) and were older. The VF+ group had lower cortical bone mass (measured by single photon absorptiometry of the non-dominant forearm) than either the control or VF- groups. The latter two groups did not differ from each other with respect to this measurement.These markers demonstrated limited sensitivity and specificity as estimated from a confirmatory data set, particularly for the historical and anthropometric variables. We conclude that an assessment of the risk of developing PMO with vertebral fractures cannot be based on the putative risk factors as measured in our study, but must be based on measurement of bone mass.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/27770/1/0000164.pd

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics

The Cancer Genome Atlas (TCGA) has catalyzed systematic characterization of diverse genomic alterations underlying human cancers. At this historic junction marking the completion of genomic characterization of over 11,000 tumors from 33 cancer types, we present our current understanding of the molecular processes governing oncogenesis. We illustrate our insights into cancer through synthesis of the findings of the TCGA PanCancer Atlas project on three facets of oncogenesis: (1) somatic driver mutations, germline pathogenic variants, and their interactions in the tumor; (2) the influence of the tumor genome and epigenome on transcriptome and proteome; and (3) the relationship between tumor and the microenvironment, including implications for drugs targeting driver events and immunotherapies. These results will anchor future characterization of rare and common tumor types, primary and relapsed tumors, and cancers across ancestry groups and will guide the deployment of clinical genomic sequencing