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Sökning: WFRF:(Abad Amaya)

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1.
  • Athie, Alejandro, et al. (författare)
  • Analysis of copy number alterations reveals the lncRNA ALAL-1 as a regulator of lung cancer immune evasion
  • 2020
  • Ingår i: The Journal of cell biology. - : Rockefeller University Press. - 1540-8140 .- 0021-9525. ; 219:9
  • Tidskriftsartikel (refereegranskat)abstract
    • Cancer is characterized by genomic instability leading to deletion or amplification of oncogenes or tumor suppressors. However, most of the altered regions are devoid of known cancer drivers. Here, we identify lncRNAs frequently lost or amplified in cancer. Among them, we found amplified lncRNA associated with lung cancer-1 (ALAL-1) as frequently amplified in lung adenocarcinomas. ALAL-1 is also overexpressed in additional tumor types, such as lung squamous carcinoma. The RNA product of ALAL-1 is able to promote the proliferation and tumorigenicity of lung cancer cells. ALAL-1 is a TNFα- and NF-κB-induced cytoplasmic lncRNA that specifically interacts with SART3, regulating the subcellular localization of the protein deubiquitinase USP4 and, in turn, its function in the cell. Interestingly, ALAL-1 expression inversely correlates with the immune infiltration of lung squamous tumors, while tumors with ALAL-1 amplification show lower infiltration of several types of immune cells. We have thus unveiled a pro-oncogenic lncRNA that mediates cancer immune evasion, pointing to a new target for immune potentiation.
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2.
  • Menkveld, Albert J., et al. (författare)
  • Nonstandard Errors
  • 2024
  • Ingår i: JOURNAL OF FINANCE. - : Wiley-Blackwell. - 0022-1082 .- 1540-6261. ; 79:3, s. 2339-2390
  • Tidskriftsartikel (refereegranskat)abstract
    • In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty-nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
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