4 research outputs found

    Heterogeneity and Cancer-Related Features in Lymphangioleiomyomatosis Cells and Tissue

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    Lymphangioleiomyomatosis (LAM) is a rare, low-grade metastasizing disease characterized by cystic lung destruction. LAM can exhibit extensive heterogeneity at the molecular, cellular, and tissue levels. However, the molecular similarities and differences among LAM cells and tissue, and their connection to cancer features are not fully understood. By integrating complementary gene and protein LAM signatures, and single-cell and bulk tissue transcriptome profiles, we show sources of disease heterogeneity, and how they correspond to cancer molecular portraits. Subsets of LAM diseased cells differ with respect to gene expression profiles related to hormones, metabolism, proliferation, and stemness. Phenotypic diseased cell differences are identified by evaluating lumican (LUM) proteoglycan and YB1 transcription factor expression in LAM lung lesions. The RUNX1 and IRF1 transcription factors are predicted to regulate LAM cell signatures, and both regulators are expressed in LAM lung lesions, with differences between spindle-like and epithelioid LAM cells. The cancer single-cell transcriptome profiles most similar to those of LAM cells include a breast cancer mesenchymal cell model and lines derived from pleural mesotheliomas. Heterogeneity is also found in LAM lung tissue, where it is mainly determined by immune system factors. Variable expression of the multifunctional innate immunity protein LCN2 is linked to disease heterogeneity. This protein is found to be more abundant in blood plasma from LAM patients than from healthy women.This research was partially supported by AELAM (ICO-IDIBELL agreement, to M.A. Pujana), The LAM Foundation Seed Grant 2019, to M.A. Pujana, Carlos III Institute of Health grant PI18/01029, to M.A. Pujana and ICI19/00047 to M. Molina-Molina [co-funded by European Regional Development Fund (ERDF), a way to build Europe], Generalitat de Catalunya SGR grant 2017-449, to M.A. Pujana, the CERCA Program for IDIBELL institutional support, and ZonMW-TopZorg grant 842002003, to C.H.M. van Moorsel. M. Plass was supported by a “Ramón y Cajal” contract of the Spanish Ministry of Science and Innovation (RYC2018-024564-I) and J. Moss was supported by the Intramural Research Program of NIH/NHLBI

    Biological basis of extensive pleiotropy between blood traits and cancer risk

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    Background: The immune system has a central role in preventing carcinogenesis. Alteration of systemic immune cell levels may increase cancer risk. However, the extent to which common genetic variation influences blood traits and cancer risk remains largely undetermined. Here, we identify pleiotropic variants and predict their underlying molecular and cellular alterations. Methods: Multivariate Cox regression was used to evaluate associations between blood traits and cancer diagnosis in cases in the UK Biobank. Shared genetic variants were identified from the summary statistics of the genome-wide association studies of 27 blood traits and 27 cancer types and subtypes, applying the conditional/conjunctional false-discovery rate approach. Analysis of genomic positions, expression quantitative trait loci, enhancers, regulatory marks, functionally defined gene sets, and bulk- and single-cell expression profiles predicted the biological impact of pleiotropic variants. Plasma small RNAs were sequenced to assess association with cancer diagnosis. Results: The study identified 4093 common genetic variants, involving 1248 gene loci, that contributed to blood-cancer pleiotropism. Genomic hotspots of pleiotropism include chromosomal regions 5p15-TERT and 6p21-HLA. Genes whose products are involved in regulating telomere length are found to be enriched in pleiotropic variants. Pleiotropic gene candidates are frequently linked to transcriptional programs that regulate hematopoiesis and define progenitor cell states of immune system development. Perturbation of the myeloid lineage is indicated by pleiotropic associations with defined master regulators and cell alterations. Eosinophil count is inversely associated with cancer risk. A high frequency of pleiotropic associations is also centered on the regulation of small noncoding Y-RNAs. Predicted pleiotropic Y-RNAs show specific regulatory marks and are overabundant in the normal tissue and blood of cancer patients. Analysis of plasma small RNAs in women who developed breast cancer indicates there is an overabundance of Y-RNA preceding neoplasm diagnosis. Conclusions: This study reveals extensive pleiotropism between blood traits and cancer risk. Pleiotropism is linked to factors and processes involved in hematopoietic development and immune system function, including components of the major histocompatibility complexes, and regulators of telomere length and myeloid lineage. Deregulation of Y-RNAs is also associated with pleiotropism. Overexpression of these elements might indicate increased cancer risk

    Stem cell-like transcriptional reprogramming mediates metastatic resistance to mTOR inhibition

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    Inhibitors of the mechanistic target of rapamycin (mTOR) are currently used to treat advanced metastatic breast cancer. However, whether an aggressive phenotype is sustained through adaptation or resistance to mTOR inhibition remains unknown. Here, complementary studies in human tumors, cancer models and cell lines reveal transcriptional reprogramming that supports metastasis in response to mTOR inhibition. This cancer feature is driven by EVI1 and SOX9. EVI1 functionally cooperates with and positively regulates SOX9, and promotes the transcriptional upregulation of key mTOR pathway components (REHB and RAPTOR) and of lung metastasis mediators (FSCN1 and SPARC). The expression of EVI1 and SOX9 is associated with stem cell-like and metastasis signatures, and their depletion impairs the metastatic potential of breast cancer cells. These results establish the mechanistic link between resistance to mTOR inhibition and cancer metastatic potential, thus enhancing our understanding of mTOR targeting failure
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