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Book: LC-MS MS in proteomics

Cutillas, Pedro R.

methods and applications

(Methods in molecular biology ; 658 ; Springer protocols)

2010

Author's details	ed. by Pedro R. Cutillas
Series title	Methods in molecular biology ; 658 Springer protocols
Collection
Language	English
Size	X, 357 S. : Ill., graph. Darst.
Publisher	Humana Press
Publishing place	New York u.a.
Publishing country	United States
Document type	Book
Note	Teilw. als Printed-on-demand-Ausg.
HBZ-ID	HT016351367
ISBN	978-1-60761-779-2 ; 1-60761-779-X ; 9781607617808 ; 1607617803
Database	Catalogue ZB MED Medicine, Health

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Article ; Online: Proteomic Characterization of Acute Myeloid Leukemia for Precision Medicine.

Casado, Pedro / Cutillas, Pedro R

Molecular & cellular proteomics : MCP

2023 Volume 22, Issue 4, Page(s) 100517

Abstract: Acute myeloid leukemia (AML) is a highly heterogeneous cancer of the hematopoietic system with no cure for most patients. In addition to chemotherapy, treatment options for AML include recently approved therapies that target proteins with roles in AML ... ...

Abstract	Acute myeloid leukemia (AML) is a highly heterogeneous cancer of the hematopoietic system with no cure for most patients. In addition to chemotherapy, treatment options for AML include recently approved therapies that target proteins with roles in AML pathobiology, such as FLT3, BLC2, and IDH1/2. However, due to disease complexity, these therapies produce very diverse responses, and survival rates are still low. Thus, despite considerable advances, there remains a need for therapies that target different aspects of leukemic biology and for associated biomarkers that define patient populations likely to respond to each available therapy. To meet this need, drugs that target different AML vulnerabilities are currently in advanced stages of clinical development. Here, we review proteomics and phosphoproteomics studies that aimed to provide insights into AML biology and clinical disease heterogeneity not attainable with genomic approaches. To place the discussion in context, we first provide an overview of genetic and clinical aspects of the disease, followed by a summary of proteins targeted by compounds that have been approved or are under clinical trials for AML treatment and, if available, the biomarkers that predict responses. We then discuss proteomics and phosphoproteomics studies that provided insights into AML pathogenesis, from which potential biomarkers and drug targets were identified, and studies that aimed to rationalize the use of synergistic drug combinations. When considered as a whole, the evidence summarized here suggests that proteomics and phosphoproteomics approaches can play a crucial role in the development and implementation of precision medicine for AML patients.
MeSH term(s)	Humans ; Precision Medicine ; Proteomics ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use ; Leukemia, Myeloid, Acute/genetics ; Molecular Targeted Therapy
Language	English
Publishing date	2023-02-18
Publishing country	United States
Document type	Journal Article ; Review ; Research Support, Non-U.S. Gov't
ZDB-ID	2075924-1
ISSN	1535-9484 ; 1535-9476
ISSN (online)	1535-9484
ISSN	1535-9476
DOI	10.1016/j.mcpro.2023.100517
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Article ; Online: Systematic identification of biochemical networks in cancer cells by functional pathway inference analysis.

Badshah, Irbaz I / Cutillas, Pedro R

Bioinformatics (Oxford, England)

2022 Volume 39, Issue 1

Abstract: Motivation: Pathway inference methods are important for annotating the genome, for providing insights into the mechanisms of biochemical processes and allow the discovery of signalling members and potential new drug targets. Here, we tested the ... ...

Abstract	Motivation: Pathway inference methods are important for annotating the genome, for providing insights into the mechanisms of biochemical processes and allow the discovery of signalling members and potential new drug targets. Here, we tested the hypothesis that genes with similar impact on cell viability across multiple cell lines belong to a common pathway, thus providing a conceptual basis for a pathway inference method based on correlated anti-proliferative gene properties. Methods: To test this concept, we used recently available large-scale RNAi screens to develop a method, termed functional pathway inference analysis (FPIA), to systemically identify correlated gene dependencies. Results: To assess FPIA, we initially focused on PI3K/AKT/MTOR signalling, a prototypic oncogenic pathway for which we have a good sense of ground truth. Dependencies for AKT1, MTOR and PDPK1 were among the most correlated with those for PIK3CA (encoding PI3Kα), as returned by FPIA, whereas negative regulators of PI3K/AKT/MTOR signalling, such as PTEN were anti-correlated. Following FPIA, MTOR, PIK3CA and PIK3CB produced significantly greater correlations for genes in the PI3K-Akt pathway versus other pathways. Application of FPIA to two additional pathways (p53 and MAPK) returned expected associations (e.g. MDM2 and TP53BP1 for p53 and MAPK1 and BRAF for MEK1). Over-representation analysis of FPIA-returned genes enriched the respective pathway, and FPIA restricted to specific tumour lineages uncovered cell type-specific networks. Overall, our study demonstrates the ability of FPIA to identify members of pro-survival biochemical pathways in cancer cells. Availability and implementation: FPIA is implemented in a new R package named 'cordial' freely available from https://github.com/CutillasLab/cordial. Supplementary information: Supplementary data are available at Bioinformatics online.
MeSH term(s)	Proto-Oncogene Proteins c-akt/metabolism ; Tumor Suppressor Protein p53 ; Phosphatidylinositol 3-Kinases/genetics ; Phosphatidylinositol 3-Kinases/metabolism ; Class I Phosphatidylinositol 3-Kinases/genetics ; Class I Phosphatidylinositol 3-Kinases/metabolism ; TOR Serine-Threonine Kinases/genetics ; TOR Serine-Threonine Kinases/metabolism ; Neoplasms/genetics
Chemical Substances	Proto-Oncogene Proteins c-akt (EC 2.7.11.1) ; Tumor Suppressor Protein p53 ; Phosphatidylinositol 3-Kinases (EC 2.7.1.-) ; Class I Phosphatidylinositol 3-Kinases (EC 2.7.1.137) ; TOR Serine-Threonine Kinases (EC 2.7.11.1)
Language	English
Publishing date	2022-11-30
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btac769
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Article ; Online: Comparison of multiple modalities for drug response prediction with learning curves using neural networks and XGBoost.

Branson, Nikhil / Cutillas, Pedro R / Bessant, Conrad

Bioinformatics advances

2023 Volume 4, Issue 1, Page(s) vbad190

Abstract: Motivation: Anti-cancer drug response prediction is a central problem within stratified medicine. Transcriptomic profiles of cancer cell lines are typically used for drug response prediction, but we hypothesize that proteomics or phosphoproteomics might ...

Abstract	Motivation: Anti-cancer drug response prediction is a central problem within stratified medicine. Transcriptomic profiles of cancer cell lines are typically used for drug response prediction, but we hypothesize that proteomics or phosphoproteomics might be more suitable as they give a more direct insight into cellular processes. However, there has not yet been a systematic comparison between all three of these datatypes using consistent evaluation criteria. Results: Due to the limited number of cell lines with phosphoproteomics profiles we use learning curves, a plot of predictive performance as a function of dataset size, to compare the current performance and predict the future performance of the three omics datasets with more data. We use neural networks and XGBoost and compare them against a simple rule-based benchmark. We show that phosphoproteomics slightly outperforms RNA-seq and proteomics using the 38 cell lines with profiles of all three omics data types. Furthermore, using the 877 cell lines with proteomics and RNA-seq profiles, we show that RNA-seq slightly outperforms proteomics. With the learning curves we predict that the mean squared error using the phosphoproteomics dataset would decrease by Availability and implementation: See https://github.com/Nik-BB/Learning-curves-for-DRP for the code used.
Language	English
Publishing date	2023-12-23
Publishing country	England
Document type	Journal Article
ISSN	2635-0041
ISSN (online)	2635-0041
DOI	10.1093/bioadv/vbad190
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Article ; Online: Principles of phosphoproteomics and applications in cancer research.

Higgins, Luke / Gerdes, Henry / Cutillas, Pedro R

The Biochemical journal

2023 Volume 480, Issue 6, Page(s) 403–420

Abstract: Phosphorylation constitutes the most common and best-studied regulatory post-translational modification in biological systems and archetypal signalling pathways driven by protein and lipid kinases are disrupted in essentially all cancer types. Thus, the ... ...

Abstract	Phosphorylation constitutes the most common and best-studied regulatory post-translational modification in biological systems and archetypal signalling pathways driven by protein and lipid kinases are disrupted in essentially all cancer types. Thus, the study of the phosphoproteome stands to provide unique biological information on signalling pathway activity and on kinase network circuitry that is not captured by genetic or transcriptomic technologies. Here, we discuss the methods and tools used in phosphoproteomics and highlight how this technique has been used, and can be used in the future, for cancer research. Challenges still exist in mass spectrometry phosphoproteomics and in the software required to provide biological information from these datasets. Nevertheless, improvements in mass spectrometers with enhanced scan rates, separation capabilities and sensitivity, in biochemical methods for sample preparation and in computational pipelines are enabling an increasingly deep analysis of the phosphoproteome, where previous bottlenecks in data acquisition, processing and interpretation are being relieved. These powerful hardware and algorithmic innovations are not only providing exciting new mechanistic insights into tumour biology, from where new drug targets may be derived, but are also leading to the discovery of phosphoproteins as mediators of drug sensitivity and resistance and as classifiers of disease subtypes. These studies are, therefore, uncovering phosphoproteins as a new generation of disruptive biomarkers to improve personalised anti-cancer therapies.
MeSH term(s)	Humans ; Proteomics/methods ; Phosphorylation ; Protein Processing, Post-Translational ; Neoplasms/drug therapy ; Phosphoproteins/metabolism ; Proteome/metabolism
Chemical Substances	Phosphoproteins ; Proteome
Language	English
Publishing date	2023-01-25
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2969-5
ISSN	1470-8728 ; 0006-2936 ; 0306-3275 ; 0264-6021
ISSN (online)	1470-8728
ISSN	0006-2936 ; 0306-3275 ; 0264-6021
DOI	10.1042/BCJ20220220
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Article ; Online: Community detection in empirical kinase networks identifies new potential members of signalling pathways.

Basanta, Celia De Los Angeles Colomina / Bazzi, Marya / Hijazi, Maruan / Bessant, Conrad / Cutillas, Pedro R

PLoS computational biology

2023 Volume 19, Issue 6, Page(s) e1010459

Abstract: Phosphoproteomics allows one to measure the activity of kinases that drive the fluxes of signal transduction pathways involved in biological processes such as immune function, senescence and cell growth. However, deriving knowledge of signalling network ... ...

Abstract	Phosphoproteomics allows one to measure the activity of kinases that drive the fluxes of signal transduction pathways involved in biological processes such as immune function, senescence and cell growth. However, deriving knowledge of signalling network circuitry from these data is challenging due to a scarcity of phosphorylation sites that define kinase-kinase relationships. To address this issue, we previously identified around 6,000 phosphorylation sites as markers of kinase-kinase relationships (that may be conceptualised as network edges), from which empirical cell-model-specific weighted kinase networks may be reconstructed. Here, we assess whether the application of community detection algorithms to such networks can identify new components linked to canonical signalling pathways. Phosphoproteomics data from acute myeloid leukaemia (AML) cells treated separately with PI3K, AKT, MEK and ERK inhibitors were used to reconstruct individual kinase networks. We used modularity maximisation to detect communities in each network, and selected the community containing the main target of the inhibitor used to treat cells. These analyses returned communities that contained known canonical signalling components. Interestingly, in addition to canonical PI3K/AKT/mTOR members, the community assignments returned TTK (also known as MPS1) as a likely component of PI3K/AKT/mTOR signalling. We drew similar insights from an external phosphoproteomics dataset from breast cancer cells treated with rapamycin and oestrogen. We confirmed this observation with wet-lab laboratory experiments showing that TTK phosphorylation was decreased in AML cells treated with AKT and MTOR inhibitors. This study illustrates the application of community detection algorithms to the analysis of empirical kinase networks to uncover new members linked to canonical signalling pathways.
MeSH term(s)	Humans ; Proto-Oncogene Proteins c-akt/metabolism ; Phosphatidylinositol 3-Kinases/metabolism ; Signal Transduction ; TOR Serine-Threonine Kinases/metabolism ; Phosphotransferases/metabolism ; Leukemia, Myeloid, Acute
Chemical Substances	Proto-Oncogene Proteins c-akt (EC 2.7.11.1) ; Phosphatidylinositol 3-Kinases (EC 2.7.1.-) ; TOR Serine-Threonine Kinases (EC 2.7.11.1) ; Phosphotransferases (EC 2.7.-)
Language	English
Publishing date	2023-06-23
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1010459
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Article ; Online: Role of phosphoproteomics in the development of personalized cancer therapies.

Cutillas, Pedro R

Proteomics. Clinical applications

2015 Volume 9, Issue 3-4, Page(s) 383–395

Abstract: Cell signalling pathways driven by protein and lipid kinases contribute to the onset and progression of virtually all cancer types. Consequently, several inhibitors against these enzymes have clinical utility for the treatment of different forms of ... ...

Abstract	Cell signalling pathways driven by protein and lipid kinases contribute to the onset and progression of virtually all cancer types. Consequently, several inhibitors against these enzymes have clinical utility for the treatment of different forms of cancer. A problem that hampers further development is that not all patients respond equally well to kinase inhibitors and a significant proportion of those that initially respond eventually develop resistance. This review considers how an integrative analysis of kinase signalling may be used to address this issue. Advances in the biophysics of mass spectrometry, in biochemical procedures for phosphopeptide enrichment, and in computational approaches for label-free quantification have contributed to the development of phosphoproteomics workflows compatible with the analysis of clinical material. These developments, together with new bioinformatics tools to derive information on signalling circuitry from phosphoproteomics data, allow investigating kinase networks with unprecedented depth. Phosphoproteomics technology is starting to be used in translational research and, with further developments, such methods may also be able to measure the circuitry of cancer signalling networks in routine clinical assays. This review reflects on how this information could be used to accurately predict the best kinase inhibitor for each individual cancer patient.
MeSH term(s)	Humans ; Mass Spectrometry/methods ; Neoplasms/metabolism ; Phosphopeptides/analysis ; Phosphoproteins/analysis ; Precision Medicine/methods ; Proteomics/methods ; Systems Biology/methods
Chemical Substances	Phosphopeptides ; Phosphoproteins
Language	English
Publishing date	2015-02-27
Publishing country	Germany
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	2261788-7
ISSN	1862-8354 ; 1862-8346
ISSN (online)	1862-8354
ISSN	1862-8346
DOI	10.1002/prca.201400104
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Article: The cytotoxic action of BCI is not dependent on its stated DUSP1 or DUSP6 targets in neuroblastoma cells

Thompson, Elliott M. / Patel, Vruti / Rajeeve, Vinothini / Cutillas, Pedro R / Stoker, Andrew W.

FEBS Open Bio. 2022 July, v. 12, no. 7

2022

Abstract: Neuroblastoma (NB) is a heterogeneous cancer of the sympathetic nervous system, which accounts for 7–10% of paediatric malignancies worldwide. Due to the lack of targetable molecular aberrations in NB, most treatment options remain relatively nonspecific. ...

Abstract	Neuroblastoma (NB) is a heterogeneous cancer of the sympathetic nervous system, which accounts for 7–10% of paediatric malignancies worldwide. Due to the lack of targetable molecular aberrations in NB, most treatment options remain relatively nonspecific. Here, we investigated the therapeutic potential of BCI, an inhibitor of DUSP1 and DUSP6, in cultured NB cells. BCI was cytotoxic in a range of NB cell lines and induced a short‐lived activation of the AKT and stress‐inducible MAP kinases, although ERK phosphorylation was unaffected. Furthermore, a phosphoproteomic screen identified significant upregulation of JNK signalling components and suppression in mTOR and R6K signalling. To assess the specificity of BCI, CRISPR‐Cas9 was employed to introduce insertions and deletions in the DUSP1 and DUSP6 genes. Surprisingly, BCI remained fully cytotoxic in NB cells with complete loss of DUSP6 and partial depletion of DUSP1, suggesting that BCI exerts cytotoxicity in NB cells through a complex mechanism that is unrelated to these phosphatases. Overall, these data highlight the risk of using an inhibitor such as BCI as supposedly specific DUSP1/6, without understanding its full range of targets in cancer cells.
Keywords	CRISPR-Cas systems ; cytotoxicity ; mitogen-activated protein kinase ; phosphorylation ; risk ; sympathetic nervous system ; therapeutics
Language	English
Dates of publication	2022-07
Size	p. 1388-1405.
Publishing place	John Wiley & Sons, Ltd
Document type	Article
Note	JOURNAL ARTICLE
ZDB-ID	2651702-4
ISSN	2211-5463
ISSN	2211-5463
DOI	10.1002/2211-5463.13418
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Article ; Online: Implementation of Clinical Phosphoproteomics and Proteomics for Personalized Medicine.

Casado, Pedro / Hijazi, Maruan / Gerdes, Henry / Cutillas, Pedro R

Methods in molecular biology (Clifton, N.J.)

2021 Volume 2420, Page(s) 87–106

Abstract: The identification of biomarkers for companion diagnostics is revolutionizing the development of treatments tailored to individual patients in different disease areas including cancer. Precision medicine is most frequently based on the detection of ... ...

Abstract	The identification of biomarkers for companion diagnostics is revolutionizing the development of treatments tailored to individual patients in different disease areas including cancer. Precision medicine is most frequently based on the detection of genomic markers that correlate with the efficacy of selected targeted therapies. However, since nongenetic mechanisms also contribute to disease biology, there is a considerable interest of using proteomic techniques as additional source of biomarkers to personalize therapies. In this chapter, we describe label-free mass spectrometry methods for proteomic and phosphoproteomic analysis compatible with routine analysis of clinical samples. We also outline bioinformatic pipelines based on statistical learning that use these proteomics datasets as input to quantify kinase activities and predict drug responses in cancer cells.
MeSH term(s)	Biomarkers, Tumor ; Humans ; Mass Spectrometry ; Neoplasms/diagnosis ; Neoplasms/genetics ; Precision Medicine ; Proteomics
Chemical Substances	Biomarkers, Tumor
Language	English
Publishing date	2021-12-14
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1940-6029
ISSN (online)	1940-6029
DOI	10.1007/978-1-0716-1936-0_8
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Article ; Online: Targeting the lysine-specific demethylase 1 rewires kinase networks and primes leukemia cells for kinase inhibitor treatment.

Pedicona, Federico / Casado, Pedro / Hijazi, Maruan / Gribben, John G / Rouault-Pierre, Kevin / Cutillas, Pedro R

Science signaling

2022 Volume 15, Issue 730, Page(s) eabl7989

Abstract: Most tumor types either fail to respond or become resistant to kinase inhibitors, often because of compensatory prosurvival pathways in the cancer cell's broader signaling circuitry. Here, we found that intrinsic resistance to kinase inhibitors in ... ...

Abstract	Most tumor types either fail to respond or become resistant to kinase inhibitors, often because of compensatory prosurvival pathways in the cancer cell's broader signaling circuitry. Here, we found that intrinsic resistance to kinase inhibitors in cultured primary acute myeloid leukemia (AML) cells may be overcome by reshaping kinase networks into topologies that confer drug sensitivity. We identified several antagonists of chromatin-modifying enzymes that sensitized AML cell lines to kinase inhibitors. Of these, we confirmed that inhibitors of the lysine-specific demethylase (LSD1; also known as KDM1A) rewired kinase signaling in AML cells in a way that increased the activity of the kinase MEK and that broadly suppressed the activity of other kinases and feedback loops. As a result, AML cell lines and about half of primary human AML samples were primed for sensitivity to the MEK inhibitor trametinib. Primary human cells with
MeSH term(s)	Antineoplastic Agents/pharmacology ; Cell Line, Tumor ; Histone Demethylases ; Humans ; Leukemia, Myeloid, Acute/drug therapy ; Leukemia, Myeloid, Acute/genetics ; Leukemia, Myeloid, Acute/pathology ; Lysine ; Mitogen-Activated Protein Kinase Kinases ; Protein Kinase Inhibitors/pharmacology ; Protein Kinase Inhibitors/therapeutic use
Chemical Substances	Antineoplastic Agents ; Protein Kinase Inhibitors ; Histone Demethylases (EC 1.14.11.-) ; KDM1A protein, human (EC 1.5.-) ; Mitogen-Activated Protein Kinase Kinases (EC 2.7.12.2) ; Lysine (K3Z4F929H6)
Language	English
Publishing date	2022-04-19
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2417226-1
ISSN	1937-9145 ; 1945-0877
ISSN (online)	1937-9145
ISSN	1945-0877
DOI	10.1126/scisignal.abl7989
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