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    Bone mineral density in women newly diagnosed with breast cancer: a prospective cohort study

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    Estrogen may have opposing effects on health, namely increasing the risk of breast cancer and improving bone health by increasing bone mineral density (BMD). The objective of this study was to compare dual-energy X-ray absorptiometry (DXA) BMD between women newly diagnosed with breast cancer and matched controls without breast cancer. Women newly diagnosed with breast cancer treated between April 2012 and October 2017 were prospectively enrolled. A control group was established of women with negative mammography or breast ultrasound, matched 1:1 by age, body mass index, parity, and the use of hormone replacement therapy. All those included had DXA BMD, and lab assessments at enrollment. Of 869 women with newly diagnosed breast cancer, 464 signed informed consent. Of the 344 who completed the study protocol, 284 were matched to controls. Overall, the mean age was 58 years. Compared to the control group, for the breast cancer group, the mean vitamin D level was lower (48.9 ± 19.0 vs. 53.8 ± 28.8 nmol/L, p = 0.022); and mean values were higher of total hip BMD (0.95 ± 0.14 vs. 0.92 ± 0.12 g/cm2, p = 0.002), T score (-0.38 ± 1.17 vs. -0.68 ± 0.98, p = 0.002), and Z score (0.32 ± 1.09 vs. 0.01 ± 0.88, p < 0.001). Among the women with breast cancer, no correlations were found of baseline BMD with tumor size or grade, nodal involvement, or breast cancer stage. We concluded that women with newly diagnosed breast cancer tend to have higher BMD than women with similar characteristics but without breast cancer. This implies that BMD might be considered a biomarker for breast cancer risk

    Redox signaling by glutathione peroxidase 2 links vascular modulation to metabolic plasticity of breast cancer

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    In search of redox mechanisms in breast cancer, we uncovered a striking role for glutathione peroxidase 2 (GPx2) in oncogenic signaling and patient survival. GPx2 loss stimulates malignant progression due to reactive oxygen species/hypoxia inducible factor-α (HIF1α)/VEGFA (vascular endothelial growth factor A) signaling, causing poor perfusion and hypoxia, which were reversed by GPx2 reexpression or HIF1α inhibition. Ingenuity Pathway Analysis revealed a link between GPx2 loss, tumor angiogenesis, metabolic modulation, and HIF1α signaling. Single-cell RNA analysis and bioenergetic profiling revealed that GPx2 loss stimulated the Warburg effect in most tumor cell subpopulations, except for one cluster, which was capable of oxidative phosphorylation and glycolysis, as confirmed by coexpression of phosphorylated-AMPK and GLUT1. These findings underscore a unique role for redox signaling by GPx2 dysregulation in breast cancer, underlying tumor heterogeneity, leading to metabolic plasticity and malignant progression

    Familial long-read sequencing increases yield of de novo mutations

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    Studies of de novo mutation (DNM) have typically excluded some of the most repetitive and complex regions of the genome because these regions cannot be unambiguously mapped with short-read sequencing data. To better understand the genome-wide pattern of DNM, we generated long-read sequence data from an autism parent-child quad with an affected female where no pathogenic variant had been discovered in short-read Illumina sequence data. We deeply sequenced all four individuals by using three sequencing platforms (Illumina, Oxford Nanopore, and Pacific Biosciences) and three complementary technologies (Strand-seq, optical mapping, and 10X Genomics). Using long-read sequencing, we initially discovered and validated 171 DNMs across two children-a 20% increase in the number of de novo single-nucleotide variants (SNVs) and indels when compared to short-read callsets. The number of DNMs further increased by 5% when considering a more complete human reference (T2T-CHM13) because of the recovery of events in regions absent from GRCh38 (e.g., three DNMs in heterochromatic satellites). In total, we validated 195 de novo germline mutations and 23 potential post-zygotic mosaic mutations across both children; the overall true substitution rate based on this integrated callset is at least 1.41 × 10-8 substitutions per nucleotide per generation. We also identified six de novo insertions and deletions in tandem repeats, two of which represent structural variants. We demonstrate that long-read sequencing and assembly, especially when combined with a more complete reference genome, increases the number of DNMs by >25% compared to previous studies, providing a more complete catalog of DNM compared to short-read data alone

    Epigenetic patterns in a complete human genome

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    The completion of a telomere-to-telomere human reference genome, T2T-CHM13, has resolved complex regions of the genome, including repetitive and homologous regions. Here, we present a high-resolution epigenetic study of previously unresolved sequences, representing entire acrocentric chromosome short arms, gene family expansions, and a diverse collection of repeat classes. This resource precisely maps CpG methylation (32.28 million CpGs), DNA accessibility, and short-read datasets (166,058 previously unresolved chromatin immunoprecipitation sequencing peaks) to provide evidence of activity across previously unidentified or corrected genes and reveals clinically relevant paralog-specific regulation. Probing CpG methylation across human centromeres from six diverse individuals generated an estimate of variability in kinetochore localization. This analysis provides a framework with which to investigate the most elusive regions of the human genome, granting insights into epigenetic regulation

    Contiguously hydrophobic sequences are functionally significant throughout the human exome

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    SignificanceProteins rely on the hydrophobic effect to maintain structure and interactions with the environment. Surprisingly, natural selection on amino acid hydrophobicity has not been detected using modern genetic data. Analyses that treat each amino acid separately do not reveal significant results, which we confirm here. However, because the hydrophobic effect becomes more powerful as more hydrophobic molecules are introduced, we tested whether unbroken stretches of hydrophobic amino acids are under selection. Using genetic variant data from across the human genome, we find evidence that selection increases with the length of the unbroken hydrophobic sequence. These results could lead to improvements in a wide range of genomic tools as well as insights into protein-aggregation disease etiology and protein evolutionary history

    Accurate and robust inference of genetic ancestry from cancer-derived molecular data across genomic platforms

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    Genetic ancestry-oriented cancer research requires the ability to perform accurate and robust ancestry inference from existing cancer-derived data, including whole exomes, transcriptomes and targeted gene panels, very often in the absence of matching cancer-free genomic data. In order to optimize and assess the performance of the ancestry inference for any given input cancer-derived molecular profile, we develop a data synthesis framework. In its core procedure, the ancestral background of the profiled patient is replaced with one of any number of individuals with known ancestry. Data synthesis is applicable to multiple profiling platforms and makes it possible to assess the performance of inference separately for each continental-level ancestry. This ability extends to all ancestries, including those without statistically sufficient representation in the existing cancer data. We further show that our inference procedure is accurate and robust in a wide range of sequencing depths. Testing our approach for three representative cancer types, and across three molecular profiling modalities, we demonstrate that global, continental-level ancestry of the patient can be inferred with high accuracy, as quantified by its agreement with the golden standard of the ancestry derived from matching cancer-free molecular data. Our study demonstrates that vast amounts of existing cancer-derived molecular data potentially are amenable to ancestry-oriented studies of the disease, without recourse to matching cancer-free genomes or patients’ self-identification by ancestry

    PASS-01: Pancreatic adenocarcinoma signature stratification for treatment-01

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    TPS635 Background: Over 70% of patients with pancreatic ductal adenocarcinoma (PDAC) present with metastatic disease where the mainstay of treatment is combination chemotherapy. Two pivotal phase III trials showed survival benefit of mFOLFIRINOX (mFFX) and gemcitabine/nab-paclitaxel (GnP), respectively, compared to gemcitabine alone. Both are considered standard 1st line treatment options but have not been compared prospectively. Other than the BRCA phenotype there are no predictive molecular markers to identify which patients will benefit from mFFX versus GnP. Growing data suggests that RNA signatures and GATA6 expression may predict response to chemotherapy. Genomic platforms do identify small subsets of patients who may benefit from a targeted approach however, impact has been small. Patient-derived organoids (PDOs) are now feasible to passage for drug pharmacotyping that could inform drug therapy approaches. Combining all molecular strategies in real time including genomics, RNA signatures and adding PDO drug sensitivities could enable better precision choices for more patients with metastatic PDAC. Methods: PASS-01 is a multi-institutional randomized phase II trial evaluating the benefit of 1st line mFFX vs GnP in de novo metastatic PDAC patients with good PS who have undergone baseline tumor biopsies with tissue prepared for whole genome (WGS) and RNA sequencing and PDO generation/pharmacotyping using standard and novel drugs. The 10 objective is to determine the PFS benefit of mFFX compared to GnP as 1st line treatment with 80% power to detect a median PFS of 7 vs 5 months, favoring mFFX. 27 of a planned 150 patients have been accrued to date. Secondary endpoints include ORR (RECIST), DOR, OS by chemotherapy and biomarkers of therapy response including GATA-6 as a surrogate biomarker for the Moffit RNA classifier. Exploratory objectives include: to evaluate if each PDO DNA/RNA signature matches the patient and if the PDO chemotherapy sensitivities correlate to the patient’s 1st line response; to evaluate the benefit in switching patients to 2nd line treatment based on PDO drug sensitivity; to evaluate novel agents derived from PDO pharmacotyping and potential findings from profiling in 2nd/3rd line treatment; to explore retrospectively whether serial cell-free circulating tumor DNA analysis, circulating tumor cells and CA19.9 could reflect potential early predictors of emerging or de novo resistance and explore biomarkers of immune-oncologic sensitivity with multiplex immunohistochemistry. Each patient’s WGS and PDO data is discussed at a combined tumor board with study investigators immediately following their 1st 8-week CT and ongoing as data develops with the goal of recommending precision treatment choices back to their treating investigator. References: Conroy T et al. NEJM, 2011.; Von Hoff DD et al. NEJM,2013; Aung KL et al. CCR 2017; O’Kane G et al. CCR 2019; Tiriac H et al. Can Discov, 2018. Clinical trial information: NCT04469556. </jats:p

    BMP2/SMAD pathway activation in JAK2/p53-mutant Megakaryocyte/Erythroid Progenitors Promotes Leukemic Transformation

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    Leukemic transformation (LT) of myeloproliferative neoplasm (MPN) has a dismal prognosis and is largely fatal. Mutational inactivation of TP53 is the most common somatic event in LT, however the mechanisms by which TP53 mutations promote LT remain unresolved. Using an allelic series of mouse models of Jak2/Trp53 mutant MPN, we identify that only biallelic inactivation of Trp53 results in LT (to a pure erythroleukemia (PEL)). This PEL arises from the megakaryocyte erythroid progenitor (MEP) population. Importantly, the BMP2/SMAD pathway is aberrantly activated during LT, and results in abnormal self-renewal of MEPs. Finally, we identify that Jak2/Trp53 mutant PEL is characterized by recurrent copy number alterations and DNA damage. Using a synthetic-lethality strategy, by targeting active DNA-repair pathways, we demonstrate that this PEL is highly sensitive to combination WEE1 and PARP inhibition. These observations yield new mechanistic insights into the process of p53 mutant LT, and offer new, clinically-translatable therapeutic approaches

    Computational validity: using computation to translate behaviours across species

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    We propose a new conceptual framework (computational validity) for translation across species and populations based on the computational similarity between the information processing underlying parallel tasks. Translating between species depends not on the superficial similarity of the tasks presented, but rather on the computational similarity of the strategies and mechanisms that underlie those behaviours. Computational validity goes beyond construct validity by directly addressing questions of information processing. Computational validity interacts with circuit validity as computation depends on circuits, but similar computations could be accomplished by different circuits. Because different individuals may use different computations to accomplish a given task, computational validity suggests that behaviour should be understood through the subject's point of view; thus, behaviour should be characterized on an individual level rather than a task level. Tasks can constrain the computational algorithms available to a subject and the observed subtleties of that behaviour can provide information about the computations used by each individual. Computational validity has especially high relevance for the study of psychiatric disorders, given the new views of psychiatry as identifying and mediating information processing dysfunctions that may show high inter-individual variability, as well as for animal models investigating aspects of human psychiatric disorders. This article is part of the theme issue 'Systems neuroscience through the lens of evolutionary theory'

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