Flyer

Archives in Cancer Research

  • ISSN: 2254-6081
  • Journal h-index: 14
  • Journal CiteScore: 3.77
  • Journal Impact Factor: 4.09
  • Average acceptance to publication time (5-7 days)
  • Average article processing time (30-45 days) Less than 5 volumes 30 days
    8 - 9 volumes 40 days
    10 and more volumes 45 days
Awards Nomination 20+ Million Readerbase
Indexed In
  • China National Knowledge Infrastructure (CNKI)
  • CiteFactor
  • OCLC- WorldCat
  • Publons
  • Geneva Foundation for Medical Education and Research
  • Euro Pub
  • Google Scholar
  • J-Gate
  • Secret Search Engine Labs
  • International Committee of Medical Journal Editors (ICMJE)
  • Zenodo
Share This Page

Research Article - (2022) Volume 10, Issue 12

Phosphoproteomics in translational research: a cancer perspective

Ronald Grane*
 
Division of Cancer Biology, the Institute of Cancer Research, London, UK
 
*Correspondence: Ronald Grane, Division of Cancer Biology, the Institute of Cancer Research, London, UK, Email:

Received: 01-Dec-2022, Manuscript No. ipacr-22-13188; Editor assigned: 05-Dec-2022, Pre QC No. ipacr-22-13188; Reviewed: 16-Dec-2022, QC No. ipacr-22-13188; Revised: 23-Dec-2022, Manuscript No. ipacr-22-13188; Published: 30-Dec-2022, DOI: 10.36648/2254-6081- 10.12-163

Abstract

Phosphoproteomics has been extensively used as a diagnosing analysis tool to characterize the phosphorylated parts of the cancer protein. Advances within the field have yielded insights into new drug targets, mechanisms of sickness progression and drug resistance, and biomarker discovery. However, application of this technology to clinical analysis has been difficult as a result of sensible problems with reference to specimen integrity and neoplasm nonuniformity. On the far side these limitations, phosphoproteomics has the potential to play a polar role in translational studies and contribute to advances in several neoplasm teams, together with rare sickness sites like cancer. During this review, we have a tendency to propose that deploying phosphoproteomic technologies in translational analysis could facilitate the identification of higher outlined prognostic biomarkers for patient stratification, inform drug choice in umbrella trials and determine new combos to beat drug resistance. We offer an summary of current phosphoproteomic technologies, like affinity-based assays and mass spectrometry-based approaches, and discuss their benefits and limitations. We have a tendency to use cancer.

Keywords

Phosphoproteomics; Sarcoma; Signal transduction; Clinical trials; Drug resistance

Introduction

Phosphoproteomics is that the comprehensive analysis of the phosphorylated parts of the cellular protein. Over the last decade, advances in phosphoproteomic technologies and application workflows have junction rectifier to its fast adoption as a tool of selection for assessing cellular signalling networks. This has been fuelled partly by large-scale genomic analyses and practical screens that have uncovered multiple genetic aberrations in kinases and phosphatases, the key regulators of supermolecule phosphorylation, in an exceedingly vary of various cancer varieties. Especially, phosphoproteomics has vied a crucial role in process the mechanistic links between oncogenic drivers and practical readouts. Distinguished early examples embrace the identification of oncogenic BRAF signalling targets in skin cancer, the in-depth analysis of EGFR signalling in neoplastic cell lines and also the determination of ATM and ATR repair networks in response to deoxyribonucleic acid injury. Despite its incontestible utility in characterizing cancer signalling, phosphoproteomic applications in clinical and translational analysis square measure still lacking. Associate in Nursing example for example these challenges in evaluating targeted enzyme therapies in clinical trials. We have a tendency to then highlight helpful lessons from diagnosing studies in cancer biology to demonstrate however phosphoproteomics could address a number of these challenges. Finally, we have a tendency to conclude by giving a perspective and list the key measures needed to translate and benchmark a mostly diagnosing technology into a useful gizmo for translational analysis [1-3].

In this review, we have a tendency to propose that deploying phosphoproteomics in clinical trials and translational analysis has the potential to facilitate the invention of higher outlined prognostic biomarkers for patient stratification, inform drug choice in umbrella trials and determine new combos to beat drug resistance. We have a tendency to initial offer a quick summary of the technical capabilities of phosphoproteomics, together with current tools obtainable and their benefits and limitations.

We have a tendency to then use cancer as associate in Nursing example for example the challenges facing the analysis of targeted enzyme therapies in medicine clinical trials. Helpful lessons from cancer diagnosing studies on however phosphoproteomics could address a number of these challenges are mentioned. To conclude, we have a tendency to list the key measures needed to translate and benchmark a mostly diagnosing technology into a useful gizmo for clinical trials and translational analysis.

Phosphoproteomics offers the aptitude to accurately map the activation states of multiple proteins at the same time and presents a pretty strategy for assessing enzyme targets and signalling pathway responses to targeted enzyme agents. These technologies offer important benefits over customary laboratory techniques like immunoblotting wherever the restricted dynamic vary and sensitivity makes precise quantification difficult. what is more, immunoblotting lacks multiplexing capability that limits the quantity of analytes which may be at the same time surveyed. Finally, this approach is inherently low turnout and so as to get large-scale signalling coverage and assess the phosphorylation states across multiple proteins among networks, important labour and comparatively massive sample quantities square measure needed.

Unlike different up to date molecular identification approaches like next-generation sequencing, there square measure presently no gold customary platforms for identification enzyme pathway activation by phosphoproteomics. As summarized in Table one, current technologies square measure loosely split into affinitybased assays and mass spectroscopy (MS)-based approaches. the selection of that technologies to use is essentially driven by sample amounts, availableness of phospho-specific antibodies, depth of signalling network coverage needed and availableness of specialist instrumentality and experience [4,5].

Discussion

Affinity-based methods utilize specific antibodies to capture phosphorylated proteins from cell lysates, that square measure then detected by a secondary protein recognizing the captured analyte labeled to come up with a colorimetrical or fluorescent signal. Examples embrace protein arrays and Luminex bead-based assays (Table 1). Another affinity-base format is reverse section supermolecule arrays (RPPA) wherever multiple sample lysates square measure immobilized on a microarray format that is then incubated with a phospho-specific protein before quantification. Affinity-based assays have sensible multiplexing capability and square measure able to assess many phosphoproteins per experiment. They need terribly low amounts of sample, creating them appropriate for clinical studies wherever patient specimens could also be limiting. These assays square measure amenable to high-throughput workflows and automation that permits for knowledge assortment from massive sample cohorts. Additionally, they are doing not trust specialised instrumentality, facilitating easy use and accessibility for many laboratories. The key disadvantage of this category of technologies is that the serious dependence on extremely specific antibodies to every protein of interest wherever protein specificity is commonly troublesome to assess.

MS facilitates the unbiased and measure of thousands of phosphoproteins at the same time in an exceedingly single experiment. MS-based approaches vary from centered studies that trust capture reagents like motif-specific antibodies to isolate phosphoproteins-bearing specific enzyme motifs to world approaches supported enrichment of cellular phosphoproteins mistreatment resins like immobilized metal affinity action or TiO2 to characterize the worldwide phosphorylation standing in cancer cells [8]. MS-based assays are often additional split into discovery or targeted experiments (Table 1). In discovery MS, additionally referred to as scattergun or data-independent acquisition, enriched phosphopeptides square measure eluted into the spectroscope sanctioning identification of huge numbers of phosphorylation sites in Associate in nursing unbiased fashion. Targeted MS depends on the generation of in silicon amide libraries which permit the instrument to scan and quantify specific phosphopeptides of interest the key advantage of MSbased approaches is its ability to produce alone depth in protein coverage in Associate in Nursing antibody-independent manner. However, compared with affinity-based assays, MS-based assays need a lot of higher amounts of sample (up to metric weight unit levels) and want substantial investment in infrastructure together with high-resolution mass spectrometers and specialist experience to accurately discover and quantify these signalling events. MS techniques square measure relatively low turnout, though recent developments in machine-controlled workflows square measure probably to beat this limitation.

Sarcomas square measure tumours of mesenchymal origin that comprise fifty completely different histologic subtypes. Several aminoalkanoic acid kinases are involved as oncogenes in much cancer that has junction rectifier to multiple clinical trials evaluating a variety of targeted enzyme therapies (readers square measure directed to a recent review for a wonderful summary of targeted therapies in sarcoma). These agents show restricted efficaciousness as single agents in cancer trials as a result of in several instances biomarkers that predict useful response to those agents have nevertheless to be determined. what is more, within the majority of cancer subtypes, the identity of the key oncogenic drivers (including activated kinases) that drive sickness progression remains elusive [6-8].

A recent combined analysis of the PALETTE cohort and phase II clinical trial EORTC trial knowledge showed that twenty second of cancer patients were each long responders (PFS ≥6 months) and long survivors (survived≥18 months) with twelve patients (3.5%) remaining on pazopanib for quite a pair of years. These sturdy responses square measure outstanding for TKI medical aid wherever nonheritable resistance is sort of universal.

These exceptional responders warrant nearer review to spot the biological basis by those tumours evade through nonheritable resistance mechanisms. It remains unresolved if this can be a particular feature peculiar to pazopanib or if it's distinctive to the biology of sarcomas. it's additionally unclear if these sturdy responses square measure the results of molecular alterations within the neoplasm cell compartment or changes in micro environmental factors like immune cell accomplishment. Lessons learnt from these patients could offer valuable insights within the style of novel methods to stop nonheritable resistance. This additionally highlights the importance of the incorporation of complimentary biomarker studies into run style, so as to tease out the potential mechanisms of response and resistance to a particular medical aid.

Based on the phase II clinical trial EORTC trial, pazopanib was deemed ineffective in liposarcoma; but, sarcoma consists of a minimum of 3 distinct biological subtypes: well-/dedifferentiated, myxoid/round cell and organic phenomenon. in progress clinical trials square measure evaluating the sensitivity of those sarcoma subtypes to pazopanib and additional work is needed to rationally determine candidate druggable targets for this category of neoplasm equally for the bulk of patients that eventually continue to develop nonheritable resistance to it'll be necessary to spot key bypass pathways and harness this info to develop new agents and combination methods to bypass pazopanib resistance.

Previous studies mistreatment each MS- and affinity-based phosphoproteomics have shed light-weight on attainable mechanisms of sensitivity to TKIs in cancer patients. in an exceedingly study to survey and outline the practical aminoalkanoic acid kinases driving cancer cell survival, used MS-based phosphotyrosine enrichment to profile ten cancer cell lines of five distinct subtypes. The authors found that multiple RTKs together with and PDGFRA were at the same time coactivated within the cancer cell lines examined. They afterward administered a drug screen with seven TKIs targeted against many of the RTKs known and showed that this approach was capable in every case of distinctive the particular driver RTK(s) that was answerable for neoplastic cell growth. The authors additional incontestible the potential clinical applications of this approach by analyzing the phosphoproteome of human patient-derived murine heterograft models comprising sarcoma, tiny spherical blue cell neoplasm and malignant peripheral nerve sheath neoplasm like the cell lines, multiple aminoalkanoic acid kinases were found to be activated within the human tissue, indicating that this strategy could have clinical utility for the identification of mechanisms and biomarkers of TKI sensitivity in cancer patients.

Along identical lines utilized affinity-based RTK protein arrays to screen 2 genetically distinct pathological process osteogenic sarcoma cell lines for aminoalkanoic acid enzyme activation. They found that these cell lines activated up to 9 RTKs at the same time that were functionally valid mistreatment siRNA approaches and inhibitors for multiple measures of tumorigenicity, together with cell motility, invasion, colony formation and cell growth. They showed that targeting ten of the twelve RTKs by siRNA was capable of inhibiting the in vitro makeup in a minimum of one in all the 2 cell lines used. The author’s additional incontestible mistreatment assay that one in all the known RTKs (AXL) was activated in 5 of six osteogenic sarcoma specimens examined, suggesting that this could be a replacement target for treating osteogenic sarcoma patients [9,10].

Conclusion

The observation of a phosphorylated enzyme is itself inadequate to predict its practical connection in cancer cell growth or invasion. as an example, IGF1R was found to be phosphorylated in nine of the ten cancer cell lines however solely the Ewing cancer cell lines were sensitive to Associate in Nursing IGF1R substance. Equally within study, none of the 9 RTKs that were found to be phosphorylated within the 2 cell lines were valid in each pathological process osteogenic sarcoma cellular models. This is a cautionary warning on the necessity to couple phosphoproteomic approaches with practical methods like RNAi, CRISPR or drug screens to tell apart the motive force kinases from traveler events. The prevalence of RTK co-activation events in cancer cell lines and tissues may additionally justify why sarcomas square measure thus difficult to treat mistreatment single-agent TKIs. The coinciding activation of multiple RTKs permits cancer cells to keep up strong counteractive survival signalling in response to targeted inhibition of a particular RTK so as to effectively close up oncogenic signalling and reach sturdy neoplasm responses, combos of TKIs that square measure capable of silencing multiple RTKs in individual patients.

Acknowledgement

I would like to thank my professor for his support and encouragement.

Conflict of Interest

The authors declare that there is no Conflict of interest.

REFERENCES

  1. Koichi A, Chun L, Sanyuan T, Sudipta V, Kang Q H et al. (2016) Tobacco carcinogen induces both lung cancer and non-alcoholic steatohepatitis and hepatocellular carcinomas in ferrets which can be attenuated by lycopene supplementation. Int J Cancer 139: 1171-1181.
  2. Indexed at, Google Scholar, Crossref

  3. Rashida A, Choong K R, Md Aminur R (2013) A stable and sensitive voltammetric immunosensor based on a new non-enzymatic label. Biosens Bioelectron 50: 118-124.
  4. Indexed at, Google Scholar, Crossref

  5. Samuel O A, Elizabeth C E, Corinna V S, Emma R L, Kieran M H et al. (2015) Exposure to environmental chemicals and heavy metals, and risk of pancreatic cancer. Cancer Causes Control 26: 1583-1591.
  6. Indexed at, Google Scholar, Crossref

  7. Calin C, Laura A P, Ovidiu B, Simona S C (2020) Early diagnosis and screening in lung cancer. Am J Cancer Res 10: 1993-2009.
  8. Indexed at, Google Scholar                     

  9. Ying F C, Huang Y, Kun M W, Amily F J, Neng Y S et al. (2019) Diagnosing the rgs11 lung cancer biomarker: the integration of competitive immunoassay and isothermal nucleic acid exponential amplification reaction. Anal Chem 91: 3327-3335.
  10. Indexed at, Google Scholar, Crossref

  11. Chen D, Hongbin F, Jinghong L (2012) Graphene oxide: preparation, functionalization, and electrochemical applications. Chem Rev 112: 6027-6053.
  12. Indexed at, Google Scholar, Crossref

  13. Ying C, Yu L, Dongmei D, Haibo H, Xiaoxia Y et al. (2018) Effective immobilization of Au nanoparticles on TiO2 loaded graphene for a novel sandwich-type immunosensors. Biosens Bioelectron 102: 301-306.
  14. Indexed at, Google Scholar, Crossref

  15. Elisabetta C (2006) Metal oxide nano-crystals for gas sensing. Anal Chim Acta 568: 28-40.
  16. Indexed at, Google Scholar, Crossref

  17. Fabiana S F, Angnes L (2018) Electrochemical immunosensors–a powerful tool for analytical applications. Biosens Bioelectron 102: 470-478.
  18. Indexed at, Google Scholar, Crossref

  19. Dexiang F, Lihua L, Junqing Z, Yuzhong Z (2015) Simultaneous electrochemical detection of multiple biomarkers using gold nanoparticles decorated multiwall carbon nanotubes as signal enhancers. Anal Biochem 482: 48-54.
  20. Indexed at, Google Scholar, Crossref

Citation: Grane R (2022) Phosphoproteomics in Translational Research: a Cancer Perspective. Archives Can Res, Vol.10 No. 12: 163.