Citations

Summary Cancer genome sequencing is essential for understanding tumor evolution and advancing precision medicine. 1 However, reference gaps and germline variants obscure detection of small and large somatic variants and methylation in repetitive regions. 1–3 It is common for tumor cells to gain or lose chromosome arms due to somatic structural changes that occur inside highly repetitive satellite DNA sequences in the centromeres. 4 To identify the full spectrum of somatic variants, including complex rearrangements, we construct and curate near-complete, haplotype-resolved assemblies of the most recent common ancestor of an early-passage broadly-consented hypodiploid pancreatic cancer cell line and matched normal tissues. The tumor assembly completely recapitulates all 35 tumor chromosomes observed with karyotyping, with multiple translocation-induced hybrid chromosomes. The hybrid chromosomes contain putative functional dicentric and fused centromeres, nested foldback inversions causing 14 breakpoints with a haplotype switch in a single event, and centromeric satellite tandem duplications up to 136 kbp. Direct comparison of tumor and normal assembly haplotypes uncovers >7,000 variants altering >1 Mbp of sequence in repetitive regions that have been hidden by reference gaps and germline variants. 44 % of somatic small variants change representation because they alter germline variants on GRCh38, impacting mutational signatures and kataegis/omikli clusters. Most somatic LINE insertions originate from two hypomethylated non-reference germline LINE insertions, highlighting their impact on insertion mutation burden. These assemblies demonstrate that centromeric, acrocentric, and telomeric regions conventionally excluded from analysis harbor extensive somatic and epigenetic changes. Resolving complete tumor genomes enables a deeper understanding of cancer structural plasticity and the endpoints of breakage-fusion-bridge cycles. These assembled, curated paired normal-tumor benchmarks will serve as a critical foundation for developing future algorithms to characterize the most intractable regions of cancer genomes.

Abstract Ferritin, consisting of ferritin heavy chain (FTH1) and light chain (FTL) subunits, is an essential intracellular iron storage protein fundamental for cellular function. However, the source and the biological role of extracellular ferritin (ex-ferritin) are less understood. Recent studies have linked elevated serum ex-ferritin with adverse outcomes in individuals with acute respiratory distress syndrome (ARDS). In this study, we demonstrate that both FTH1 and FTL are significantly enriched in the serum, blood monocytes, and alveolar macrophages (AMs) of individuals with ARDS, a phenomenon we successfully replicate in a murine hyperoxia-induced acute lung injury (HALI) model. We show that FTH1 is consistently upregulated in macrophages during lung injury development, and mice with a targeted deletion of FTH1 in myeloid (LysMcre) or resident lung macrophage (Cd11ccre) populations exhibit attenuated HALI. This reduced injury is linked to macrophage resistance to ferroptotic cell death, ferritinophagy, altered airway inflammatory responses, and lower lung extracellular iron and higher levels of FTL-ex-ferritin. Transplantation of FTL-ex-ferritin-enriched bronchoalveolar lavage fluid to wild-type mice protected against HALI. The ratio of FTL-ex-ferritin to FTH1 in the serum of individuals with ARDS who died was higher than that of those that survived, suggesting that the balance between FTH1 and FTL may play a role in injury modulation. Our findings highlight macrophage ferritin as a key regulator of macrophage survival and the response of the lung to injury, presenting a potentially targetable pathway for ARDS treatment.

Neurologic complications associated with regional anesthesia and pain medicine practice are extremely rare. The ASRA Practice Advisory on Neurologic Complications in Regional Anesthesia and Pain Medicine addresses the etiology, differential diagnosis, prevention, and treatment of these complications. This Advisory does not focus on hemorrhagic and infectious complications, because they have been addressed by other recent ASRA Practice Advisories. The current Practice Advisory offers recommendations to aid in the understanding and potential limitation of neurologic complications that may arise during the practice of regional anesthesia and pain medicine.

Breast cancer imposes a significant burden globally. While the survival rate is steadily improving, much remains to be elucidated. This observational, single time point, multiomic study utilizing genomics, proteomics, targeted and untargeted metabolomics, and metagenomics in a breast cancer survivor (BCS) and age-matched healthy control cohort (N = 100) provides deep molecular phenotyping of breast cancer survivors. In this study, the BCS cohort had significantly higher polygenic risk scores for breast cancer than the control group. Carnitine and hexanoyl carnitine were significantly different. Several bile acid and fatty acid metabolites were significantly dissimilar, most notably the Omega-3 Index (O3I) (significantly lower in BCS). Proteomic and metagenomic analyses identified group and pathway differences, which warrant further investigation. The database built from this study contributes a wealth of data on breast cancer survivorship where there has been a paucity, affording the ability to identify patterns and novel insights that can drive new hypotheses and inform future research. Expansion of this database in the treatment-naïve, newly diagnosed, controlling for treatment confounders, and through the disease progression, can be leveraged to profile and contextualize breast cancer and breast cancer survivorship, potentially leading to the development of new strategies to combat this disease and improve the quality of life for its victims.

Abstract Organismal adaptations to spaceflight have been characterized at the molecular level in model organisms, including Drosophila and C. elegans. Here we extend molecular work to energy metabolism and sex hormone signaling in mice and humans. We found spaceflight-induced changes in insulin and estrogen signaling in rodents and humans. Murine changes were most prominent in the liver, where we observed inhibition of insulin and estrogen receptor signaling with concomitant hepatic insulin resistance and steatosis. Based on the metabolic demand, metabolic pathways mediated by insulin and estrogen vary among muscles, specifically between the soleus and extensor digitorum longus. In humans, spaceflight induced changes in insulin and estrogen related genes and pathways. Pathway analysis demonstrated spaceflight-induced changes in insulin resistance, estrogen signaling, stress response, and viral infection. These data strongly suggest the need for further research on the metabolic and reproductive endocrinologic effects of space travel, if we are to become a successful interplanetary species

PURPOSETissue-based next-generation sequencing (NGS) in metastatic breast cancer (mBC) is limited by the inability to noninvasively track tumor evolution. Cell-free DNA (cfDNA) NGS has made sequential testing feasible; however, the relationship between cfDNA and tissue-based testing in mBC is not well understood. Here, we evaluate concordance between tissue and cfDNA NGS relative to cfDNA sampling frequency in a large, clinically annotated mBC data set.METHODSTempus LENS was used to analyze deidentified records of mBC cases with Tempus xT (tissue) and xF (cfDNA) sequencing results. Then, various metrics of concordance were assessed within overlapping probe regions of the tissue and cfDNA assays (104 genes), focusing on pathogenic variants. Variant allele frequencies of discordant and concordant pathogenic variants were also compared. Analyses were stratified by mBC subtype and time between tests.RESULTSRecords from 300 paired tissue and liquid biopsies were analyzed. Median time between tissue and blood collection was 78.5 days (standard deviation = 642.99). The median number of pathogenic variants/patient was one for cfDNA and two for tissue. Across the cohort, 77.8% of pathogenic tissue variants were found in cfDNA and 75.7% of pathogenic cfDNA variants were found in tissue when tests were ≤ 7 days apart, which decreased to 50.3% and 51.8%, respectively, for > 365 days. Furthermore, the median patient-level variant concordance was 67% when tests were ≤7 days apart and 30%-37% when > 30 days. The median variant allele frequencies of discordant variants were generally lower than those of concordant variants within the same time frame.CONCLUSIONWe observed high concordances between tissue and cfDNA results that generally decreased with longer durations between tests. Thus, cfDNA NGS reliably measures tissue genomics and is likely beneficial for longitudinal monitoring of molecular changes in mBC.

PURPOSE Provide evidence- and expert-based recommendations for optimal use of imaging in advanced prostate cancer. Due to increases in research and utilization of novel imaging for advanced prostate cancer, this guideline is intended to outline techniques available and provide recommendations on appropriate use of imaging for specified patient subgroups. METHODS An Expert Panel was convened with members from ASCO and the Society of Abdominal Radiology, American College of Radiology, Society of Nuclear Medicine and Molecular Imaging, American Urological Association, American Society for Radiation Oncology, and Society of Urologic Oncology to conduct a systematic review of the literature and develop an evidence-based guideline on the optimal use of imaging for advanced prostate cancer. Representative index cases of various prostate cancer disease states are presented, including suspected high-risk disease, newly diagnosed treatment-naïve metastatic disease, suspected recurrent disease after local treatment, and progressive disease while undergoing systemic treatment. A systematic review of the literature from 2013 to August 2018 identified fully published English-language systematic reviews with or without meta-analyses, reports of rigorously conducted phase III randomized controlled trials that compared ≥ 2 imaging modalities, and noncomparative studies that reported on the efficacy of a single imaging modality. RESULTS A total of 35 studies met inclusion criteria and form the evidence base, including 17 systematic reviews with or without meta-analysis and 18 primary research articles. RECOMMENDATIONS One or more of these imaging modalities should be used for patients with advanced prostate cancer: conventional imaging (defined as computed tomography [CT], bone scan, and/or prostate magnetic resonance imaging [MRI]) and/or next-generation imaging (NGI), positron emission tomography [PET], PET/CT, PET/MRI, or whole-body MRI) according to the clinical scenario.

Abstract Motivation: Using stable isotopes in global proteome scans, labeled molecules from one sample are pooled with unlabeled molecules from another sample and subsequently subjected to mass-spectral analysis. Stable-isotope methodologies make use of the fact that identical molecules of different stable-isotope compositions are differentiated in a mass spectrometer and are represented in a mass spectrum as distinct isotopic clusters with a known mass shift. We describe two multivariable linear regression models for 16O/18O stable-isotope labeled data that jointly model pairs of resolved isotopic clusters from the same peptide and quantify the abundance present in each of the two biological samples while concurrently accounting for peptide-specific incorporation rates of the heavy isotope. The abundance measure for each peptide from the two biological samples is then used in down-stream statistical analyses, e.g. differential expression analysis. Because the multivariable regression models are able to correct for the abundance of the labeled peptide that appear as an unlabeled peptide due to the inability to exchange the natural C-terminal oxygen for the heavy isotope, they are particularly advantageous for a two-step digestion/labeling procedure. We discuss how estimates from the regression model are used to quantify the variability of the estimated abundance measures for the paired samples. Although discussed in the context of 16O/18O stable-isotope labeled data, the multivariable regression models are generalizable to other stable-isotope labeled technologies. Contact: eckel@mayo.edu

AbstractBackground: One of the numerous proteins causing amyloidosis is transthyretin (TTR), a protein usually responsible for the transport of thyroxine and retinol-binding protein. Variants within TTR cause it to aggregate and form insoluble fibers that accumulate in tissue, leading to organ dysfunction.Methods: TTR was immunoprecipitated from serum by use of a polyclonal antibody and subsequently reduced with tris(2-carboxyethyl)phosphine. The purified TTR was then analyzed by fast-gradient liquid chromatography–dual-electrospray ionization Fourier-transform ion-cyclotron-resonance (FT-ICR) mass spectrometry. DNA sequencing was performed on all samples used in this study.Results: Because of the inherent limitations in achieving high mass measurement accuracy based on the most abundant isotopic mass, we applied a fitting procedure that allowed determination of monoisotopic mass. Wild-type TTR (mean molecular mass, 13 761 Da) and its associated variant forms could be distinguished because of the high molecular mass accuracy afforded by FT-ICR (≤3 ppm) except for instances involving isobaric species or when isotopic distributions overlapped significantly. The [M + 11 H+]11+ charge state for all samples was used to determine the mass accuracies for both wild-type and variant forms of the protein. We correctly assigned seven of seven TTR variants. Moreover, using a combination of proteomic and genomic technologies, we discovered and characterized a previously unreported cis double mutation with a mass only 2 Da different from wild-type TTR. Furthermore, DNA sequencing of the TTR gene for all individuals in this study completely agreed with the intact protein measurements.Conclusions: FT-ICR mass spectrometry has sufficient mass accuracy to identify genetic variants of immunoaffinity-purified TTR. We believe that 91% of known TTR variants could be detected by this technique.