The origins and consequences of UPF1 variants in pancreatic adenosquamous carcinoma
Abstract
Pancreatic adenosquamous carcinoma (PASC) is an aggressive cancer whose mutational origins are poorly understood. An early study reported high-frequency somatic mutations affecting UPF1, a nonsense-mediated mRNA decay (NMD) factor, in PASC, but subsequent studies did not observe these lesions. The corresponding controversy about whether UPF1 mutations are important contributors to PASC has been exacerbated by a paucity of functional studies. Here, we modeled two UPF1 mutations in human and mouse cells to find no significant effects on pancreatic cancer growth, acquisition of adenosquamous features, UPF1 splicing, UPF1 protein, or NMD efficiency. We subsequently discovered that 45% of UPF1 mutations reportedly present in PASCs are identical to standing genetic variants in the human population, suggesting that they may be non-pathogenic inherited variants rather than pathogenic mutations. Our data suggest that UPF1 is not a common functional driver of PASC and motivate further attempts to understand the genetic origins of these malignancies.
Data availability
RNA-seq data generated as part of this study have been deposited in the Gene Expression Omnibus (accession number GSE163517). All original gel images are provided.
-
The origins and consequences of UPF1 variants in pancreatic adenosquamous carcinomaGene Expression Omnibus, GSE163517.
-
pancreatic ductal adenocarcinoma and panreatic adenosquamous carcinoma sequencingNCBI Sequence Read Archive, SRP107982.
Article and author information
Author details
Funding
National Cancer Institute (T32 CA009657)
- Jacob T Polaski
National Institute for General Medical Sciences (T32 GM007270)
- Dylan B Udy
National Cancer Institute (T32 CA160001)
- Ram Kannan
National Cancer Institute (R01 CA204228)
- Steven D D Leach
Leukemia & Lymphoma Society (1344-18)
- Robert K Bradley
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Eric J Wagner, University of Texas Medical Branch at Galveston, United States
Ethics
Animal experimentation: All animal studies were performed in accordance with institutional and national animal regulations. Animal protocols were approved by the Memorial Sloan-Kettering Cancer Center Institutional Animal Care and Use Committee (14-08-009 and 11-12-029).
Version history
- Received: August 18, 2020
- Accepted: January 5, 2021
- Accepted Manuscript published: January 6, 2021 (version 1)
- Version of Record published: January 29, 2021 (version 2)
Copyright
© 2021, Polaski et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,398
- Page views
-
- 178
- Downloads
-
- 6
- Citations
Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Cancer Biology
Chemoresistance is a major cause of treatment failure in many cancers. However, the life cycle of cancer cells as they respond to and survive environmental and therapeutic stress is understudied. In this study, we utilized a microfluidic device to induce the development of doxorubicin-resistant (DOXR) cells from triple negative breast cancer (TNBC) cells within 11 days by generating gradients of DOX and medium. In vivo chemoresistant xenograft models, an unbiased genome-wide transcriptome analysis, and a patient data/tissue analysis all showed that chemoresistance arose from failed epigenetic control of the nuclear protein-1 (NUPR1)/histone deacetylase 11 (HDAC11) axis, and high NUPR1 expression correlated with poor clinical outcomes. These results suggest that the chip can rapidly induce resistant cells that increase tumor heterogeneity and chemoresistance, highlighting the need for further studies on the epigenetic control of the NUPR1/HDAC11 axis in TNBC.
-
- Cancer Biology
- Computational and Systems Biology
Non-invasive early cancer diagnosis remains challenging due to the low sensitivity and specificity of current diagnostic approaches. Exosomes are membrane-bound nanovesicles secreted by all cells that contain DNA, RNA, and proteins that are representative of the parent cells. This property, along with the abundance of exosomes in biological fluids makes them compelling candidates as biomarkers. However, a rapid and flexible exosome-based diagnostic method to distinguish human cancers across cancer types in diverse biological fluids is yet to be defined. Here, we describe a novel machine learning-based computational method to distinguish cancers using a panel of proteins associated with exosomes. Employing datasets of exosome proteins from human cell lines, tissue, plasma, serum, and urine samples from a variety of cancers, we identify Clathrin Heavy Chain (CLTC), Ezrin, (EZR), Talin-1 (TLN1), Adenylyl cyclase-associated protein 1 (CAP1), and Moesin (MSN) as highly abundant universal biomarkers for exosomes and define three panels of pan-cancer exosome proteins that distinguish cancer exosomes from other exosomes and aid in classifying cancer subtypes employing random forest models. All the models using proteins from plasma, serum, or urine-derived exosomes yield AUROC scores higher than 0.91 and demonstrate superior performance compared to Support Vector Machine, K Nearest Neighbor Classifier and Gaussian Naive Bayes. This study provides a reliable protein biomarker signature associated with cancer exosomes with scalable machine learning capability for a sensitive and specific non-invasive method of cancer diagnosis.