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Cancers
Special Issues
Application of Proteomics in Cancers
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Application of Proteomics in Cancers

A special issue of Cancers (ISSN 2072-6694).

Deadline for manuscript submissions: closed (25 July 2023) | Viewed by 21212

Special Issue Editor

Prof. Dr. Hiroyuki Katayama

E-Mail Website
Guest Editor
Department of Clinical Cancer Prevention, MD Anderson Cancer Center, University of Texas, Houston, TX 77030, USA
Interests: cancer proteomics; biomarkers; therapeutic targets

Special Issue Information

Dear Colleagues,

Advancements in chromatography, mass spectrometry additionally coupled with ion-mobility and novel bioinformatic tools have led to in-depth characterization of the cancer proteome, resulting in the identification of novel proteins, protein isoforms, protein post-translational modifications (e.g. glycosylation, phosphorylation, citrullination), and protein-protein interactions. These tools are being increasingly implemented to establish key effector protein(s) that drive tumorigenesis, remodel of the tumor microenvironment, modulate the immune response, and support discovering biomarkers and novel targets for anti-cancer therapy. 

This special issue focuses on the application of proteomics in cancer with emphasis on cancer biology, the tumor microenvironment and modulation of the tumor immunophenotype. Novel methodologies related to proteomics that are applicable to cancer research are also welcomed.

We are soliciting original research articles as well as reviews to contribute to this special issue.

Prof. Dr. Hiroyuki Katayama
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • proteomics
  • cancer biology
  • biomarkers
  • therapeutic targets
  • technology development
  • bioinformatics

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Published Papers (5 papers)

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Research

Jump to: Review

12 pages, 2246 KiB  
Article
Motif-Targeting Phosphoproteome Analysis of Cancer Cells for Profiling Kinase Inhibitors
by Kosuke Ogata, Shunsuke Takagi, Naoyuki Sugiyama and Yasushi Ishihama
Cancers 2023, 15(1), 78; https://doi.org/10.3390/cancers15010078 - 23 Dec 2022
Viewed by 2269
Abstract
We present a motif-targeting phosphoproteome analysis workflow utilizing in vitro kinase reaction to enrich a subset of peptides with specific primary sequence motifs. Phosphopeptides are enriched and dephosphorylated with alkaline phosphatase, followed by in vitro kinase reaction to phosphorylate substrate peptides with specific [...] Read more.
We present a motif-targeting phosphoproteome analysis workflow utilizing in vitro kinase reaction to enrich a subset of peptides with specific primary sequence motifs. Phosphopeptides are enriched and dephosphorylated with alkaline phosphatase, followed by in vitro kinase reaction to phosphorylate substrate peptides with specific primary-sequence motifs. These phosphopeptides are enriched again, TMT-labeled, dephosphorylated to enhance MS-detectability, and analyzed by LC/MS/MS. We applied this approach to inhibitor-treated cancer cells, and successfully profiled the inhibitory spectra of multiple kinase inhibitors. We anticipate this approach will be applicable to target specific subsets of the phosphoproteome using the wide variety of available recombinant protein kinases. Full article
(This article belongs to the Special Issue Application of Proteomics in Cancers)
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17 pages, 6611 KiB  
Article
Novel UHRF1-MYC Axis in Acute Lymphoblastic Leukemia
by Soyoung Park, Ali H. Abdel Sater, Johannes F. Fahrmann, Ehsan Irajizad, Yining Cai, Hiroyuki Katayama, Jody Vykoukal, Makoto Kobayashi, Jennifer B. Dennison, Guillermo Garcia-Manero, Charles G. Mullighan, Zhaohui Gu, Marina Konopleva and Samir Hanash
Cancers 2022, 14(17), 4262; https://doi.org/10.3390/cancers14174262 - 31 Aug 2022
Cited by 5 | Viewed by 2945
Abstract
Ubiquitin-like, containing PHD and RING finger domain, (UHRF) family members are overexpressed putative oncogenes in several cancer types. We evaluated the protein abundance of UHRF family members in acute leukemia. A marked overexpression of UHRF1 protein was observed in ALL compared with AML. [...] Read more.
Ubiquitin-like, containing PHD and RING finger domain, (UHRF) family members are overexpressed putative oncogenes in several cancer types. We evaluated the protein abundance of UHRF family members in acute leukemia. A marked overexpression of UHRF1 protein was observed in ALL compared with AML. An analysis of human leukemia transcriptomic datasets revealed concordant overexpression of UHRF1 in B-Cell and T-Cell ALL compared with CLL, AML, and CML. In-vitro studies demonstrated reduced cell viability with siRNA-mediated knockdown of UHRF1 in both B-ALL and T-ALL, associated with reduced c-Myc protein expression. Mechanistic studies indicated that UHRF1 directly interacts with c-Myc, enabling ALL expansion via the CDK4/6-phosphoRb axis. Our findings highlight a previously unknown role of UHRF1 in regulating c-Myc protein expression and implicate UHRF1 as a potential therapeutic target in ALL. Full article
(This article belongs to the Special Issue Application of Proteomics in Cancers)
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14 pages, 17283 KiB  
Article
The Breast Cancer Protein Co-Expression Landscape
by Martín Ruhle, Jesús Espinal-Enríquez and Enrique Hernández-Lemus
Cancers 2022, 14(12), 2957; https://doi.org/10.3390/cancers14122957 - 15 Jun 2022
Cited by 3 | Viewed by 2490
Abstract
Breast cancer is a complex phenotype (or better yet, several complex phenotypes) characterized by the interplay of a large number of cellular and biomolecular entities. Biological networks have been successfully used to capture some of the heterogeneity of intricate pathophenotypes, including cancer. Gene [...] Read more.
Breast cancer is a complex phenotype (or better yet, several complex phenotypes) characterized by the interplay of a large number of cellular and biomolecular entities. Biological networks have been successfully used to capture some of the heterogeneity of intricate pathophenotypes, including cancer. Gene coexpression networks, in particular, have been used to study large-scale regulatory patterns. Ultimately, biological processes are carried out by proteins and their complexes. However, to date, most of the tumor profiling research has focused on the genomic and transcriptomic information. Here, we tried to expand this profiling through the analysis of open proteomic data via mutual information co-expression networks’ analysis. We could observe that there are distinctive biological processes associated with communities of these networks and how some transcriptional co-expression phenomena are lost at the protein level. These kinds of data and network analyses are a broad resource to explore cellular behavior and cancer research. Full article
(This article belongs to the Special Issue Application of Proteomics in Cancers)
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29 pages, 9715 KiB  
Article
Mutational Activation of the NRF2 Pathway Upregulates Kynureninase Resulting in Tumor Immunosuppression and Poor Outcome in Lung Adenocarcinoma
by Johannes F. Fahrmann, Ichidai Tanaka, Ehsan Irajizad, Xiangying Mao, Jennifer B. Dennison, Eunice Murage, Julian Casabar, Jeffrey Mayo, Qian Peng, Muge Celiktas, Jody V. Vykoukal, Soyoung Park, Ayumu Taguchi, Oliver Delgado, Satyendra C. Tripathi, Hiroyuki Katayama, Luisa Maren Solis Soto, Jaime Rodriguez-Canales, Carmen Behrens, Ignacio Wistuba, Samir Hanash and Edwin J. Ostrinadd Show full author list remove Hide full author list
Cancers 2022, 14(10), 2543; https://doi.org/10.3390/cancers14102543 - 21 May 2022
Cited by 19 | Viewed by 3771
Abstract
Activation of the NRF2 pathway through gain-of-function mutations or loss-of-function of its suppressor KEAP1 is a frequent finding in lung cancer. NRF2 activation has been reported to alter the tumor microenvironment. Here, we demonstrated that NRF2 alters tryptophan metabolism through the kynurenine pathway [...] Read more.
Activation of the NRF2 pathway through gain-of-function mutations or loss-of-function of its suppressor KEAP1 is a frequent finding in lung cancer. NRF2 activation has been reported to alter the tumor microenvironment. Here, we demonstrated that NRF2 alters tryptophan metabolism through the kynurenine pathway that is associated with a tumor-promoting, immune suppressed microenvironment. Specifically, proteomic profiles of 47 lung adenocarcinoma (LUAD) cell lines (11 KEAP1 mutant and 36 KEAP1 wild-type) revealed the tryptophan-kynurenine enzyme kynureninase (KYNU) as a top overexpressed protein associated with activated NRF2. The siRNA-mediated knockdown of NFE2L2, the gene encoding for NRF2, or activation of the NRF2 pathway through siRNA-mediated knockdown of KEAP1 or via chemical induction with the NRF2-activator CDDO-Me confirmed that NRF2 is a regulator of KYNU expression in LUAD. Metabolomic analyses confirmed KYNU to be enzymatically functional. Analysis of multiple independent gene expression datasets of LUAD, as well as a LUAD tumor microarray demonstrated that elevated KYNU was associated with immunosuppression, including potent induction of T-regulatory cells, increased levels of PD1 and PD-L1, and resulted in poorer survival. Our findings indicate a novel mechanism of NRF2 tumoral immunosuppression through upregulation of KYNU. Full article
(This article belongs to the Special Issue Application of Proteomics in Cancers)
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Review

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19 pages, 1305 KiB  
Review
Mass Spectrometry-Based Proteomics Workflows in Cancer Research: The Relevance of Choosing the Right Steps
by Paula Carrillo-Rodriguez, Frode Selheim and Maria Hernandez-Valladares
Cancers 2023, 15(2), 555; https://doi.org/10.3390/cancers15020555 - 16 Jan 2023
Cited by 15 | Viewed by 8893
Abstract
The qualitative and quantitative evaluation of proteome changes that condition cancer development can be achieved with liquid chromatography–mass spectrometry (LC-MS). LC-MS-based proteomics strategies are carried out according to predesigned workflows that comprise several steps such as sample selection, sample processing including labeling, MS [...] Read more.
The qualitative and quantitative evaluation of proteome changes that condition cancer development can be achieved with liquid chromatography–mass spectrometry (LC-MS). LC-MS-based proteomics strategies are carried out according to predesigned workflows that comprise several steps such as sample selection, sample processing including labeling, MS acquisition methods, statistical treatment, and bioinformatics to understand the biological meaning of the findings and set predictive classifiers. As the choice of best options might not be straightforward, we herein review and assess past and current proteomics approaches for the discovery of new cancer biomarkers. Moreover, we review major bioinformatics tools for interpreting and visualizing proteomics results and suggest the most popular machine learning techniques for the selection of predictive biomarkers. Finally, we consider the approximation of proteomics strategies for clinical diagnosis and prognosis by discussing current barriers and proposals to circumvent them. Full article
(This article belongs to the Special Issue Application of Proteomics in Cancers)
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