Overexpression of C16orf74 is involved in aggressive pancreatic cancers

Nakamura, Tõru; Katagiri, Toyomasa; Sato, Sunao; Kubota, Toshihiro; Hontani, Koji; Tsuchikawa, Takahiro; Hirano, Satoshi; Nakamura, Yusuke

doi:10.18632/oncotarget.10912

Cited by 15 publications

(25 citation statements)

References 42 publications

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“…Analysis of the peptide from CACNA1H (which contains a previously identified LxVP sequence (Huang et al, 2013)) showed that co-purification with CN WT was reduced upon mutation of LxV or IxIT residues ( Figure 1H), and that binding to CN NIR or CN WF was significantly reduced (undetectable) relative to CN WT ( Figure S2A). Thus, both PxIxIT and LxVP-type binding modes were evident in this single peptide, properties also displayed by the peptide from C16orf74 (previously identified as a PxIxIT (Nakamura et al, 2017)) (data not shown).…”

Section: Validation Of Peptide Binding To Cnsupporting

confidence: 61%

Systematic discovery of Short Linear Motifs decodes calcineurin phosphatase signaling

Wigington

Roy

Damle

et al. 2019

Preprint

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Short linear motifs (SLiMs) form dynamic protein-protein interactions essential for signaling, but sequence degeneracy and low binding affinities make them difficult to identify. We harnessed unbiased systematic approaches for SLiM discovery to elucidate the regulatory network of calcineurin (CN), the Ca 2+ -regulated phosphatase that recognizes LxVP and PxIxIT motifs. In vitro proteome-wide detection of CN-binding peptides, in situ SLiM-dependent proximity labeling, and in silico modeling of motif determinants uncovered unanticipated CN interactors, including Notch1, which we establish as a CN substrate. Unexpectedly, CN shows SLiMdependent proximity to centrosomal and nuclear pore complex (NPC) proteins -structures where Ca 2+ signaling is largely uncharacterized. CN dephosphorylates human and yeast NPC proteins and promotes accumulation of a nuclear reporter, suggesting conserved NPC regulation by CN. The CN network assembled here provides a resource to investigate Ca 2+ and CN signaling and the demonstrated synergy between experimental and computational methods establishes a blueprint for examining SLiM-based networks.

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Section: Validation Of Peptide Binding To Cnsupporting

confidence: 61%

Systematic discovery of Short Linear Motifs decodes calcineurin phosphatase signaling

Wigington

Roy

Damle

et al. 2019

Preprint

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“…Consistent with our findings that acidic residues at the -1 position decrease affinity, JNK kinase regulates CN signaling by phosphorylating a serine that immediately precedes the PxIxIT of NFAT4 40 . Similarly, our demonstration that phosphorylated residues downstream of the core PxIxIT sequence at position 9 enhance PVIVIT affinity echoes observations that phosphorylation of at threonine in this position is required for binding of CN to a PxIxIT site in C16ORF74, and for its ability to promote invasiveness of pancreatic ductal adenocarcinoma (PDAC) 41 . This positive effect on binding is context-dependent, increasing PVIVIT binding 50-fold but having little or no effect on other PxIxIT sequences, reinforcing the importance of systematic analyses for generating predictive information.…”

Section: Discussionsupporting

confidence: 74%

Quantitative mapping of protein-peptide affinity landscapes using spectrally encoded beads

Nguyen

Roy

Harink

et al. 2018

Preprint

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Weak, transient binding of globular protein domains to Short Linear Motifs (SLiMs) in disordered regions of other proteins drive cellular signaling. Mapping the energy landscape of such interactions is essential for deciphering signaling networks and developing therapeutic inhibitors, but is complicated by technical challenges associated with quantitatively measuring weak interactions in high-throughput. Here, we synthesize peptide libraries on spectrally encoded beads with each peptide sequence uniquely linked to a spectral code (MRBLE-pep), allowing high-throughput quantification of protein-peptide binding via imaging. Using computational modeling and MRBLEpep assays, we map the affinity landscape for human calcineurin (CN), a conserved protein phosphatase essential for the immune response and target of immunosuppressants, interacting with a known SLiM (PxIxIT). We find that PxIxIT recognition depends critically on flanking residues and is regulated by post-translational modifications. Using this information, we designed PxIxIT peptides with unprecedented affinity and therapeutic potential that strongly inhibit CN function in vivo.

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“…For example, FK866, a non-competitive highly specific inhibitor of NAMPT, shows potent anti-tumor activity both in vitro and in vivo [ 61 ] on pancreatic cancer samples overexpressing NAMPT mRNA. Among the other genes of our signature upregulated in STS samples are C16orf74 and KRT13 , which are associated with poor OS in pancreatic [ 62 ] and prostate [ 63 ] cancers.…”

Section: Discussionmentioning

confidence: 99%

A 25-gene classifier predicts overall survival in resectable pancreatic cancer

Birnbaum

Finetti

Lopresti

et al. 2017

BMC Med

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BackgroundPancreatic carcinoma is one of the most lethal human cancers. In patients with resectable tumors, surgery followed by adjuvant chemotherapy is the only curative treatment. However, the 5-year survival is 20%. Because of a strong metastatic propensity, neoadjuvant chemotherapy is being tested in randomized clinical trials. In this context, improving the selection of patients for immediate surgery or neoadjuvant chemotherapy is crucial, and high-throughput molecular analyses may help; the present study aims to address this.MethodsClinicopathological and gene expression data of 695 pancreatic carcinoma samples were collected from nine datasets and supervised analysis was applied to search for a gene expression signature predictive for overall survival (OS) in the 601 informative operated patients. The signature was identified in a learning set of patients and tested for its robustness in a large independent validation set.ResultsSupervised analysis identified 1400 genes differentially expressed between two selected patient groups in the learning set, namely 17 long-term survivors (LTS; ≥ 36 months after surgery) and 22 short-term survivors (STS; dead of disease between 2 and 6 months after surgery). From these, a 25-gene prognostic classifier was developed, which identified two classes (“STS-like” and “LTS-like”) in the independent validation set (n = 562), with a 25% (95% CI 18–33) and 48% (95% CI 42–54) 2-year OS (P = 4.33 × 10–9), respectively. Importantly, the prognostic value of this classifier was independent from both clinicopathological prognostic features and molecular subtypes in multivariate analysis, and existed in each of the nine datasets separately. The generation of 100,000 random gene signatures by a resampling scheme showed the non-random nature of our prognostic classifier.ConclusionThis study, the largest prognostic study of gene expression profiles in pancreatic carcinoma, reports a 25-gene signature associated with post-operative OS independently of classical factors and molecular subtypes. This classifier may help select patients with resectable disease for either immediate surgery (the LTS-like class) or neoadjuvant chemotherapy (the STS-like class). Its assessment in the current prospective trials of adjuvant and neoadjuvant chemotherapy trials is warranted, as well as the functional analysis of the classifier genes, which may provide new therapeutic targets.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-017-0936-z) contains supplementary material, which is available to authorized users.

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Overexpression of C16orf74 is involved in aggressive pancreatic cancers

Cited by 15 publications

References 42 publications

Systematic discovery of Short Linear Motifs decodes calcineurin phosphatase signaling

Systematic discovery of Short Linear Motifs decodes calcineurin phosphatase signaling

Quantitative mapping of protein-peptide affinity landscapes using spectrally encoded beads

A 25-gene classifier predicts overall survival in resectable pancreatic cancer

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