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Circulating Biomarkers for Cancer Detection: Could Salivary microRNAs Be an Opportunity for Ovarian Cancer Diagnostics? Biomedicines 2023; 11:biomedicines11030652. [PMID: 36979630 PMCID: PMC10044752 DOI: 10.3390/biomedicines11030652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 02/02/2023] [Accepted: 02/16/2023] [Indexed: 02/24/2023] Open
Abstract
MicroRNAs (miRNAs) are small non-coding RNAs with the crucial regulatory functions of gene expression at post-transcriptional level, detectable in cell and tissue extracts, and body fluids. For their stability in body fluids and accessibility to sampling, circulating miRNAs and changes of their concentration may represent suitable disease biomarkers, with diagnostic and prognostic relevance. A solid literature now describes the profiling of circulating miRNA signatures for several tumor types. Among body fluids, saliva accurately reflects systemic pathophysiological conditions, representing a promising diagnostic resource for the future of low-cost screening procedures for systemic diseases, including cancer. Here, we provide a review of literature about miRNAs as potential disease biomarkers with regard to ovarian cancer (OC), with an excursus about liquid biopsies, and saliva in particular. We also report on salivary miRNAs as biomarkers in oncological conditions other than OC, as well as on OC biomarkers other than miRNAs. While the clinical need for an effective tool for OC screening remains unmet, it would be advisable to combine within a single diagnostic platform, the tools for detecting patterns of both protein and miRNA biomarkers to provide the screening robustness that single molecular species separately were not able to provide so far.
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2
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Nisa KU, Tarfeen N, Humaira, Wani S, Nisa Q, Ali S, Wali AF. Proteomic approaches in the study of cancers. Proteomics 2023. [DOI: 10.1016/b978-0-323-95072-5.00002-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
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3
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Abstract
Two-dimensional difference gel electrophoresis (2D-DIGE) is an elegant gel electrophoretic analytical tool for comparative protein assessment. It is based on two-dimensional gel electrophoresis (2D-GE) separation of fluorescently labeled protein extracts. The tagging procedures are designed to not interfere with the chemical properties of proteins with respect to their pI and electrophoretic mobility, once a proper labeling protocol is followed. The use of an internal pooled standard makes 2D-DIGE a highly accurate quantitative method enabling multiple protein samples to be separated on the same two-dimensional gel. Technical limitations of this technique (i.e., underrating of low abundant, high molecular mass and integral membrane proteins) are counterbalanced by the incomparable separation power which allows proteoforms and unknown PTM (posttranslational modification) identification. Moreover, the image matching and cross-gel statistical analysis generates robust quantitative results making data validation by independent technologies successful.
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Affiliation(s)
- Cecilia Gelfi
- Department of Biomedical Sciences for Health, University of Milan, Segrate, Italy
- IRCCS Istituto Ortopedico Galeazzi, Milan, Italy
| | - Daniele Capitanio
- Department of Biomedical Sciences for Health, University of Milan, Segrate, Italy.
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4
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You D, Zhang S, Yan S, Ding Y, Li C, Cheng X, Wu L, Wang W, Zhang T, Li Z, He Y. SAMHD1 as a prognostic and predictive biomarker in stage II colorectal cancer: A multicenter cohort study. Front Oncol 2022; 12:939982. [PMID: 35978833 PMCID: PMC9376296 DOI: 10.3389/fonc.2022.939982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 07/11/2022] [Indexed: 11/19/2022] Open
Abstract
Background The identification of high-risk population patients is key to the personalized treatment options for the stage II colorectal cancers. The use of proteomics in the prognosis of patients with stage II colorectal cancer remains unclear. Methods Using quantitative proteomics, we analyzed proteins that are differentially expressed in the tumor and adjacent normal tissues of 11 paired colorectal cancer patients with and without recurrence selected by a nested case-control design. Of the 21 identified proteins, we selected one candidate protein. The association of the corresponding gene of the selected protein with overall survival (OS) and adjuvant chemotherapy was analyzed using two independent cohorts of patients with stages II colorectal cancer. Results Sterile α motif and histidine-aspartate domain-containing protein 1 (SAMHD1) was selected as the candidate biomarker. A group of 124 patients (12.5%) were stratified into SAMHD1-high subgroup. The 5-year OS rate of SAMHD1-high patients was lower than that of SAMHD1-low patients with stage II colorectal cancer (discovery cohort: hazard ratio [HR] = 2.89, 95% confidence interval [CI], 1.17-7.18, P = 0.016; validation cohort: HR = 2.25, 95% CI, 1.17-4.34, P = 0.013). The Cox multivariate analysis yielded similar results. In a pooled database, the 5-year OS rate was significantly different between patients with and without adjuvant chemotherapy among stage II SAMHD1-low tumors than in patients with stage II SAMHD1-high tumors (88% vs. 77%, P = 0.032). Conclusions SAMHD1-high expression could help in identifying patients with stage II colorectal cancer with poor prognosis and less benefit from adjuvant chemotherapy.
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Affiliation(s)
- Dingyun You
- Department of Dental Research, The Affiliated Stomatological Hospital of Kunming Medical University, Kunming, China
- Yunnan Key Laboratory of Stomatology, Kunming Medical University, Kunming, China
- Yunnan Key Laboratory of Stem Cell and Regenerative Medicine, Biomedical Engineering Research Center, Kunming Medical University, Kunming, China
| | - Shuai Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Shan Yan
- Yunnan Key Laboratory of Stem Cell and Regenerative Medicine, Biomedical Engineering Research Center, Kunming Medical University, Kunming, China
| | - Yingying Ding
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Chunxia Li
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Xianshuo Cheng
- Department of Colorectal Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Lin Wu
- Department of Pathology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Weizhou Wang
- Department of Orthopedics, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Tao Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- *Correspondence: Yongwen He, ; Zhenhui Li, ; Tao Zhang,
| | - Zhenhui Li
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
- *Correspondence: Yongwen He, ; Zhenhui Li, ; Tao Zhang,
| | - Yongwen He
- Department of Dental Research, The Affiliated Stomatological Hospital of Kunming Medical University, Kunming, China
- *Correspondence: Yongwen He, ; Zhenhui Li, ; Tao Zhang,
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5
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Wang WH, Chen SK, Huang HC, Juan HF. Proteomic Analysis Reveals That Metformin Suppresses PSMD2, STIP1, and CAP1 for Preventing Gastric Cancer AGS Cell Proliferation and Migration. ACS OMEGA 2021; 6:14208-14219. [PMID: 34124444 PMCID: PMC8190800 DOI: 10.1021/acsomega.1c00894] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 05/14/2021] [Indexed: 05/04/2023]
Abstract
Metformin is one of the most widely used anti-diabetic drugs in type-II diabetes treatment. The mechanism of decreasing blood glucose is believed to suppress hepatic gluconeogenesis by increasing muscular glucose uptake and insulin sensitivity. Recent studies suggest that metformin may reduce cancer risk; however, its anticancer mechanism in gastric cancers remains unclear. Here, we aim to evaluate the anticancer effects of metformin on human gastric adenocarcinoma (AGS) cells. Our results showed that metformin inhibited AGS cell proliferation in a dose-dependent manner. Using small-scale quantitative proteomics, we identified 177 differentially expressed proteins upon metformin treatment; among these, nine proteins such as 26S proteasome non-ATPase regulatory subunit 2 (PSMD2), stress-induced phosphoprotein 1 (STIP1), and adenylyl cyclase-associated protein 1 (CAP1) were significantly altered. We found that metformin induced cell cycle arrest at the G0/G1 phase, suppressed cell migration, and affected cytoskeleton distribution. Additionally, patients with highly expressed PSMD2, STIP1, and CAP1 have a poor clinical outcome. Our study provides a novel view of developing therapies for gastric cancer.
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Affiliation(s)
- Wei-Hsuan Wang
- Genome
and Systems Biology Degree Program, Academia
Sinica and National Taiwan University, Taipei 10617, Taiwan
| | - Szu-Kai Chen
- Department
of Life Science, National Taiwan University, Taipei 10617, Taiwan
| | - Hsuan-Cheng Huang
- Institute
of Biomedical Informatics, National Yang
Ming Chiao Tung University, Taipei 11221, Taiwan
- . Phone: +886-2-2826-7357
| | - Hsueh-Fen Juan
- Genome
and Systems Biology Degree Program, Academia
Sinica and National Taiwan University, Taipei 10617, Taiwan
- Department
of Life Science, National Taiwan University, Taipei 10617, Taiwan
- Graduate
Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan
- . Phone: +886-2-3366-4536
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6
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Yu WW, Fu XL, Cai XW, Sun MH, Guo YM. Identification of differentially expressed proteins in the locoregional recurrent esophageal squamous cell carcinoma by quantitative proteomics. J Gastrointest Oncol 2021; 12:991-1006. [PMID: 34295551 DOI: 10.21037/jgo-21-278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 06/15/2021] [Indexed: 11/06/2022] Open
Abstract
Background This study aimed to identify potential biomarkers associated with locoregional recurrence in patients with esophageal squamous cell carcinoma (ESCC) after radical resection. Methods We performed a quantitative proteomics analysis using isobaric tags for relative and absolute quantification (iTRAQ) with reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) to identify differential expression proteins (DEPs) between a locoregional recurrence group and good prognosis group of ESCC after radical esophagectomy. The bioinformatics analysis was performed with ingenuity pathway analysis software (IPA) and Gene Ontology (GO) database using the software of MAS 3.0. Kaplan-Meier (KM) Plotter Online Tool (http://www.kmplot.com) was used to evaluate the relationship between the differential expression of proteins and survival in patients with ESCC. Results More than 400 proteins were quantitated of which 27 proteins had upregulated expression and 55 proteins had downregulated expression in the locoregional recurrence group compared to the good prognosis group. These 82 DEPs were associated with biological procession of cancer development including cellular movement, cellular assembly and organization, cellular function and maintenance, cellular growth and proliferation, cell death and survival, DNA replication recombination and repair, and so on. Of these DEPs, SPTAN1 and AGT proteins were identified to be associated with RFS in ESCC. SPTAN1 was positively associated with RFS and AGT was negatively associated with RFS. Expression of SPTAN1 tended to have favorable OS while expression of AGT tended to have poor OS. Conclusions Our results demonstrated that quantitative proteomics is an effective discovery tool to identify biomarkers for prognosis prediction in ESCC. However, it needs more studies with large populations of ESCC to validate these potential biomarkers.
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Affiliation(s)
- Wei-Wei Yu
- Department of Radiation Oncology, Affiliated Hospital of Nantong University, Nantong, China
| | - Xiao-Long Fu
- Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Xu-Wei Cai
- Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Meng-Hong Sun
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Yan-Mei Guo
- Department of Gastroenterology, The Tenth People's Hospital of Tongji University, Shanghai, China
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7
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Zhang J, Jin J, Ai Y, Zhu K, Xiao C, Xie C, Jin X. Computer Tomography Radiomics-Based Nomogram in the Survival Prediction for Brain Metastases From Non-Small Cell Lung Cancer Underwent Whole Brain Radiotherapy. Front Oncol 2021; 10:610691. [PMID: 33643912 PMCID: PMC7905101 DOI: 10.3389/fonc.2020.610691] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Accepted: 12/14/2020] [Indexed: 12/25/2022] Open
Abstract
Prognostic parameters and models were believed to be helpful in improving the treatment outcome for patients with brain metastasis (BM). The purpose of this study was to investigate the feasibility of computer tomography (CT) radiomics based nomogram to predict the survival of patients with BM from non-small cell lung cancer (NSCLC) treated with whole brain radiotherapy (WBRT). A total of 195 patients with BM from NSCLC who underwent WBRT from January 2012 to December 2016 were retrospectively reviewed. Radiomics features were extracted and selected from pretherapeutic CT images with least absolute shrinkage and selection operator (LASSO) regression. A nomogram was developed and evaluated by integrating radiomics features and clinical factors to predict the survival of individual patient. Five radiomics features were screened out from 105 radiomics features according to the LASSO Cox regression. According to the optimal cutoff value of radiomics score (Rad-score), patients were stratified into low-risk (Rad-score <= −0.14) and high-risk (Rad-score > −0.14) groups. Multivariable analysis indicated that sex, karnofsky performance score (KPS) and Rad-score were independent predictors for overall survival (OS). The concordance index (C-index) of the nomogram in the training cohort and validation cohort was 0.726 and 0.660, respectively. An area under curve (AUC) of 0.786 and 0.788 was achieved for the short-term and long-term survival prediction, respectively. In conclusion, the nomogram based on radiomics features from CT images and clinical factors was feasible to predict the OS of BM patients from NSCLC who underwent WBRT.
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Affiliation(s)
- Ji Zhang
- Department of Radiotherapy Center, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Juebin Jin
- Department of Radiotherapy Center, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yao Ai
- Department of Radiotherapy Center, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Kecheng Zhu
- Department of Radiotherapy Center, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Chengjian Xiao
- Department of Radiotherapy Center, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Congying Xie
- Department of Radiotherapy Center, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.,Department of Radiation and Medical Oncology, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiance Jin
- Department of Radiotherapy Center, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
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Definition and Independent Validation of a Proteomic-Classifier in Ovarian Cancer. Cancers (Basel) 2020; 12:cancers12092519. [PMID: 32899818 PMCID: PMC7564837 DOI: 10.3390/cancers12092519] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Revised: 08/25/2020] [Accepted: 08/27/2020] [Indexed: 12/13/2022] Open
Abstract
Simple Summary The heterogeneity of epithelial ovarian cancer and its associated molecular biological characteristics are continuously integrated in the development of therapy guidelines. In a next step, future therapy recommendations might also be able to focus on the patient’s systemic status, not only the tumor’s molecular pattern. Therefore, new methods to identify and validate host-related biomarkers need to be established. Using mass spectrometry, we developed and independently validated a blood-based proteomic classifier, stratifying epithelial ovarian cancer patients into good and poor survival groups. We also determined an age dependence of the prognostic performance of this classifier and its association with important biological processes. This work highlights that, just like molecular markers of the tumor itself, the systemic condition of a patient (partly reflected in proteomic patterns) also influences survival and therapy response and could therefore be integrated into future processes of therapy planning. Abstract Mass-spectrometry-based analyses have identified a variety of candidate protein biomarkers that might be crucial for epithelial ovarian cancer (EOC) development and therapy response. Comprehensive validation studies of the biological and clinical implications of proteomics are needed to advance them toward clinical use. Using the Deep MALDI method of mass spectrometry, we developed and independently validated (development cohort: n = 199, validation cohort: n = 135) a blood-based proteomic classifier, stratifying EOC patients into good and poor survival groups. We also determined an age dependency of the prognostic performance of this classifier, and our protein set enrichment analysis showed that the good and poor proteomic phenotypes were associated with, respectively, lower and higher levels of complement activation, inflammatory response, and acute phase reactants. This work highlights that, just like molecular markers of the tumor itself, the systemic condition of a patient (partly reflected in proteomic patterns) also influences survival and therapy response in a subset of ovarian cancer patients and could therefore be integrated into future processes of therapy planning.
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9
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Karami E, Soliman H, Ruschin M, Sahgal A, Myrehaug S, Tseng CL, Czarnota GJ, Jabehdar-Maralani P, Chugh B, Lau A, Stanisz GJ, Sadeghi-Naini A. Quantitative MRI Biomarkers of Stereotactic Radiotherapy Outcome in Brain Metastasis. Sci Rep 2019; 9:19830. [PMID: 31882597 PMCID: PMC6934477 DOI: 10.1038/s41598-019-56185-5] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Accepted: 12/08/2019] [Indexed: 02/08/2023] Open
Abstract
About 20-40% of cancer patients develop brain metastases, causing significant morbidity and mortality. Stereotactic radiation treatment is an established option that delivers high dose radiation to the target while sparing the surrounding normal tissue. However, up to 20% of metastatic brain tumours progress despite stereotactic treatment, and it can take months before it is evident on follow-up imaging. An early predictor of radiation therapy outcome in terms of tumour local failure (LF) is crucial, and can facilitate treatment adjustments or allow for early salvage treatment. In this study, an MR-based radiomics framework was proposed to derive and investigate quantitative MRI (qMRI) biomarkers for the outcome of LF in brain metastasis patients treated with hypo-fractionated stereotactic radiation therapy (SRT). The qMRI biomarkers were constructed through a multi-step feature extraction/reduction/selection framework using the conventional MR imaging data acquired from 100 patients (133 lesions), and were applied in conjunction with machine learning techniques for outcome prediction and risk assessment. The results indicated that the majority of the features in the optimal qMRI biomarkers characterize the heterogeneity in the surrounding regions of tumour including edema and tumour/lesion margins. The optimal qMRI biomarker consisted of five features that predict the outcome of LF with an area under the curve (AUC) of 0.79, and a cross-validated sensitivity and specificity of 81% and 79%, respectively. The Kaplan-Meier analyses showed a statistically significant difference in local control (p-value < 0.0001) and overall survival (p = 0.01). Findings from this study are a step towards using qMRI for early prediction of local failure in brain metastasis patients treated with SRT. This may facilitate early adjustments in treatment, such as surgical resection or salvage radiation, that can potentially improve treatment outcomes. Investigations on larger cohorts of patients are, however, required for further validation of the technique.
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Affiliation(s)
- Elham Karami
- Department of Electrical Engineering and Computer Science, Lassonde School of Engineering, York University, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Hany Soliman
- Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Mark Ruschin
- Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Arjun Sahgal
- Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Sten Myrehaug
- Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Chia-Lin Tseng
- Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Gregory J Czarnota
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | | | - Brige Chugh
- Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Angus Lau
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Greg J Stanisz
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Neurosurgery and Pediatric Neurosurgery, Medical University, Lublin, Poland
| | - Ali Sadeghi-Naini
- Department of Electrical Engineering and Computer Science, Lassonde School of Engineering, York University, Toronto, ON, Canada.
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
- Physical Sciences Platform, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
- Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
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10
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He Y, Mohamedali A, Huang C, Baker MS, Nice EC. Oncoproteomics: Current status and future opportunities. Clin Chim Acta 2019; 495:611-624. [PMID: 31176645 DOI: 10.1016/j.cca.2019.06.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Revised: 06/05/2019] [Accepted: 06/05/2019] [Indexed: 02/07/2023]
Abstract
Oncoproteomics is the systematic study of cancer samples using omics technologies to detect changes implicated in tumorigenesis. Recent progress in oncoproteomics is already opening new avenues for the identification of novel biomarkers for early clinical stage cancer detection, targeted molecular therapies, disease monitoring, and drug development. Such information will lead to new understandings of cancer biology and impact dramatically on the future care of cancer patients. In this review, we will summarize the advantages and limitations of the key technologies used in (onco)proteogenomics, (the Omics Pipeline), explain how they can assist us in understanding the biology behind the overarching "Hallmarks of Cancer", discuss how they can advance the development of precision/personalised medicine and the future directions in the field.
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Affiliation(s)
- Yujia He
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu 610041, PR China
| | - Abidali Mohamedali
- Department of Molecular Sciences, Faculty of Science and Engineering, Macquarie University, New South Wales 2109, Australia
| | - Canhua Huang
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu 610041, PR China
| | - Mark S Baker
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, New South Wales 2109, Australia.
| | - Edouard C Nice
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu 610041, PR China; Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, New South Wales 2109, Australia; Department of Biochemistry and Molecular Biology, Monash University, Clayton, Australia.
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11
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Orlando E, Aebersold R. On the contribution of mass spectrometry-based platforms to the field of personalized oncology. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2018.10.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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12
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Bashizadeh Fakhar H, Rezaie-Tavirani M, Zali H, Darkhaneh RF, Nejad EK, Aghazadeh MH. Proteomic Analysis of Low-Grade Serous Ovarian Cancer and Comparing It with Non-cancerous Ovarian. INDIAN JOURNAL OF GYNECOLOGIC ONCOLOGY 2018. [DOI: 10.1007/s40944-018-0187-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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13
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14
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Wang PW, Hung YC, Li WT, Yeh CT, Pan TL. Systematic revelation of the protective effect and mechanism of Cordycep sinensis on diethylnitrosamine-induced rat hepatocellular carcinoma with proteomics. Oncotarget 2018; 7:60270-60289. [PMID: 27531890 PMCID: PMC5312383 DOI: 10.18632/oncotarget.11201] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2016] [Accepted: 07/18/2016] [Indexed: 12/15/2022] Open
Abstract
Cordyceps sinensis (C. sinensis) has been reported to treat liver diseases. Here, we investigated the inhibitory effect of C. sinensis on hepatocarcinoma in a diethylnitrosamine (DEN)-induced rat model with functional proteome tools.In the DEN-exposed group, levels of serum alanine aminotransferase and aspartate aminotransferase were increased while C. sinensis application remarkably inhibited the activities of these enzymes. Histopathological analysis also indicated that C. sinensis could substantially restore hypertrophic hepatocytes caused by DEN, suggesting that C. sinensis is effective in preventing DEN-induced hepatocarcinogenesis.We therefore comprehensively delineated the global protein alterations using a proteome platform. The most meaningful changes were found among proteins involved in oxidative stress and detoxification. Meanwhile, C. sinensis application could attenuate the carbonylation level of several enzymes as well as chaperone proteins. Network analysis implied that C. sinensis could obviously alleviate hepatocarcinoma via modulating redox imbalance, protein ubiquitination and tumor growth-associated transcription factors.Our findings provide new insight into the potential effects of C. sinensis in preventing carcinogenesis and might help in developing novel therapeutic strategies against chemical-induced hepatocarcinoma.
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Affiliation(s)
- Pei-Wen Wang
- School of Traditional Chinese Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Yu-Chiang Hung
- School of Traditional Chinese Medicine, Chang Gung University, Taoyuan, Taiwan.,Department of Chinese Internal Medicine, Chang Gung Memorial Hospital-Kaohsiung Medical Center, Kaohsiung City, Taiwan
| | - Wen-Tai Li
- National Research Institute of Chinese Medicine, Ministry of Health and Welfare, Taipei, Taiwan
| | - Chau-Ting Yeh
- Liver Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Tai-Long Pan
- School of Traditional Chinese Medicine, Chang Gung University, Taoyuan, Taiwan.,Liver Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan.,Research Center for Industry of Human Ecology, Chang Gung University of Science and Technology, Taoyuan, Taiwan.,Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan
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15
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Abstract
Two-dimensional difference gel electrophoresis (2-D DIGE) is an advanced and elegant gel electrophoretic analytical tool for comparative protein assessment. It is based on two-dimensional gel electrophoresis (2-DE) separation of fluorescently labeled protein extracts. The tagging procedures are designed to not interfere with the chemical properties of proteins with respect to their pI and electrophoretic mobility, once a proper labeling protocol is followed. The two-dye or three-dye systems can be adopted and their choice depends on specific applications. Furthermore, the use of an internal pooled standard makes 2-D DIGE a highly accurate quantitative method enabling multiple protein samples to be separated on the same two-dimensional gel. The image matching and cross-gel statistical analysis generates robust quantitative results making data validation by independent technologies successful.
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Affiliation(s)
- Cecilia Gelfi
- Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, via f.lli Cervi, 93, 20090, Segrate, Milan, Italy.
- U.O. Proteomica clinica, IRCCS Policlinico San Donato, 20097, San Donato, Milan, Italy.
- Istituto di Bioimmagini e Fisiologia Molecolare, CNR, 20090, Segrate, Milan, Italy.
| | - Daniele Capitanio
- Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, via f.lli Cervi, 93, 20090, Segrate, Milan, Italy
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Phosphoproteomics of Primary Cells Reveals Druggable Kinase Signatures in Ovarian Cancer. Cell Rep 2017; 18:3242-3256. [PMID: 28355574 PMCID: PMC5382236 DOI: 10.1016/j.celrep.2017.03.015] [Citation(s) in RCA: 72] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2016] [Revised: 01/04/2017] [Accepted: 03/02/2017] [Indexed: 12/20/2022] Open
Abstract
Our understanding of the molecular determinants of cancer is still inadequate because of cancer heterogeneity. Here, using epithelial ovarian cancer (EOC) as a model system, we analyzed a minute amount of patient-derived epithelial cells from either healthy or cancerous tissues by single-shot mass-spectrometry-based phosphoproteomics. Using a multi-disciplinary approach, we demonstrated that primary cells recapitulate tissue complexity and represent a valuable source of differentially expressed proteins and phosphorylation sites that discriminate cancer from healthy cells. Furthermore, we uncovered kinase signatures associated with EOC. In particular, CDK7 targets were characterized in both EOC primary cells and ovarian cancer cell lines. We showed that CDK7 controls cell proliferation and that pharmacological inhibition of CDK7 selectively represses EOC cell proliferation. Our approach defines the molecular landscape of EOC, paving the way for efficient therapeutic approaches for patients. Finally, we highlight the potential of phosphoproteomics to identify clinically relevant and druggable pathways in cancer. We analyze ex-vivo-cultured primary cells using phosphoproteomics We investigate epithelial ovarian cancer (EOC) and healthy tissue We uncover expression of cancer-specific proteins and kinase signatures The kinase CDK7 phosphorylates POLR2A and regulates EOC cell proliferation
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17
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Liu XX, Ye H, Wang P, Li LX, Zhang Y, Zhang JY. Proteomic-based identification of HSP70 as a tumor-associated antigen in ovarian cancer. Oncol Rep 2017; 37:2771-2778. [DOI: 10.3892/or.2017.5525] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2016] [Accepted: 11/21/2016] [Indexed: 11/06/2022] Open
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18
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Souza GHMF, Guest PC, Martins-de-Souza D. LC-MS E, Multiplex MS/MS, Ion Mobility, and Label-Free Quantitation in Clinical Proteomics. Methods Mol Biol 2017; 1546:57-73. [PMID: 27896757 DOI: 10.1007/978-1-4939-6730-8_4] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Proteomic tools can only be implemented in clinical settings if high-throughput, automated, sensitive, and accurate methods are developed. This has driven researchers to the edge of mass spectrometry (MS)-based proteomics capacity. Here we provide an overview of recent achievements in mass spectrometric technologies and instruments. This includes development of high and ultra definition-MSE (HDMSE and UDMSE) through implementation of ion mobility (IM) MS towards sensitive and accurate label-free proteomics using ultra performance liquid chromatography (UPLC). Label free UPLC-HDMSE is less expensive than labeled-based quantitative proteomics and has no limits regarding the number of samples that can be analyzed and compared, which is an important requirement for supporting clinical applications.
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Affiliation(s)
- Gustavo Henrique Martins Ferreira Souza
- Mass Spectrometry Applications & Development Laboratory, Waters Corporation, 125, Alphaville Industrial, Barueri, 06455-020, Campinas, São Paulo, SP, Brazil.
| | - Paul C Guest
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Daniel Martins-de-Souza
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, SP, Brazil
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Oronsky B, Carter C, Scicinska A, Oronsky A, Oronsky N, Lybeck M, Scicinski J. Medical Machiavellianism: the tradeoff between benefit and harm with targeted chemotherapy. Oncotarget 2016; 7:9041-5. [PMID: 26814434 PMCID: PMC4891024 DOI: 10.18632/oncotarget.6984] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2015] [Accepted: 01/17/2016] [Indexed: 01/06/2023] Open
Abstract
Machiavellianism is a word synonymous with the phrase "the end justifies the means", and in this article we have coined the term Medical Machiavellianism to describe the 'cruel-to-be-kind' administration of toxic chemotherapeutic agents in apparent violation of the precept first do no harm, while acknowledging the 'dirty hands' dilemma of having to decide between and choose the lesser of two evils in the setting of advanced cancer--i.e. to treat or not to treat. The perception that 'targeted' therapies are relatively non-toxic and therefore respect the Hippocratic First Commandment by virtue of their narrow selectivity is belied by their often inherent promiscuity, addressing multiple targets either inadvertently or deliberately, which may result in multiple side effects. The remarkable success of immunotherapy may have taken the bloom off the 'targeted agent' rose, however due to a lack of other approved treatment alternatives the toxicity of these agents may be overlooked or, at least, undervalued, especially given that the official measure of treatment success in oncology is overall survival (OS), not quality-of-life improvements. By analogy with the MACH-IV personality survey (1970), [1] which measures high and low Machiavellian orientation, we have defined in this article a rudimentary MACH scale for selected targeted chemotherapies, based on the means-to-ends ratio of toxicity and benefit. It is our hope that this comparison between targeted agents will itself function as a means to an end--to help oncologists strike the right balance between efficacy, toxicity and quality of life in the management of their patients.
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Affiliation(s)
| | - Corey Carter
- Walter Reed National Military Medical Center, Bethesda, MD, USA
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Panis C, Pizzatti L, Souza GF, Abdelhay E. Clinical proteomics in cancer: Where we are. Cancer Lett 2016; 382:231-239. [PMID: 27561426 DOI: 10.1016/j.canlet.2016.08.014] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2016] [Revised: 08/16/2016] [Accepted: 08/17/2016] [Indexed: 12/25/2022]
Abstract
Proteomics has emerged as a promising field in the post-genomic era. Notwithstanding the great advances provided by gene expression analysis in cancer, the lack of a correlation between gene expression and protein levels has highlighted the need for a proteomic focus on cancer. Although the increasing knowledge regarding cancer biology, a reliable marker to improve diagnosis, prognosis and treatment for cancer patients is not a reality at present. In this review, we address the main considerations regarding proteomics-based studies and their clinical applications on cancer research, highlighting some considerations related to strengths and limitations of proteomics-based studies and its application to clinical practice.
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Affiliation(s)
- Carolina Panis
- Laboratório de Células Tronco, Instituto Nacional de Câncer, INCA, Rio de Janeiro, Brazil; Laboratório de Mediadores Inflamatórios, Universidade Estadual do Oeste do Paraná, UNIOESTE, Campus Francisco Beltrão, Paraná, Brazil.
| | - Luciana Pizzatti
- Laboratório de Biologia Molecular e Proteômica do Sangue - LABMOPS, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Eliana Abdelhay
- Laboratório de Células Tronco, Instituto Nacional de Câncer, INCA, Rio de Janeiro, Brazil
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21
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Kohn EC, Ivy SP. Confronting the Care Delivery Challenges Arising from Precision Medicine. Front Oncol 2016; 6:106. [PMID: 27200294 PMCID: PMC4846663 DOI: 10.3389/fonc.2016.00106] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2016] [Accepted: 04/15/2016] [Indexed: 01/27/2023] Open
Abstract
Understanding the biology of cancer at the cellular and molecular levels, and the application of such knowledge to the patient, has opened new opportunities and uncovered new obstacles to quality cancer care delivery. Benefits include our ability to now understand that many, if not most, cancers are not one-size-fits-all. Cancers are a variety of diseases for which intervention may be very different. This approach is beginning to bear fruit in gynecologic cancers where we are investigating therapeutic optimization at a more focused level, that while not yet precision care, is perhaps much improved. Obstacles to quality care for patients come from many directions. These include incomplete understanding of the role of the mutant proteins in the cancers, the narrow spectrum of agents, broader mutational profiles in solid tumors, and sometimes overzealous application of the findings of genetic testing. This has been further compromised by the unbridled use of social media by all stakeholders in cancer care often without scientific qualification, where anecdote sometimes masquerades as a fact. The only current remedy is to wave the flag of caution, encourage all patients who undergo genetic testing, either germline or somatic, to do so with the oversight of genetic counselors and physician scientists knowledgeable in the pathways involved. This aspiration is accomplished with well-designed clinical trials that inform next steps in this complex and ever evolving process.
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Affiliation(s)
- Elise C Kohn
- Cancer Therapy Evaluation Program, Division of Cancer Therapy and Diagnosis, National Cancer Institute , Rockville, MD , USA
| | - S Percy Ivy
- Cancer Therapy Evaluation Program, Division of Cancer Therapy and Diagnosis, National Cancer Institute , Rockville, MD , USA
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22
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Lee JY, Kim HS, Suh DH, Kim MK, Chung HH, Song YS. Ovarian cancer biomarker discovery based on genomic approaches. J Cancer Prev 2014; 18:298-312. [PMID: 25337559 PMCID: PMC4189448 DOI: 10.15430/jcp.2013.18.4.298] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2013] [Revised: 12/15/2013] [Accepted: 12/16/2013] [Indexed: 12/20/2022] Open
Abstract
Ovarian cancer presents at an advanced stage in more than 75% of patients. Early detection has great promise to improve clinical outcomes. Although the advancing proteomic technologies led to the discovery of numerous ovarian cancer biomarkers, no screening method has been recommended for early detection of ovarian cancer. Complexity and heterogeneity of ovarian carcinogenesis is a major obstacle to discover biomarkers. As cancer arises due to accumulation of genetic change, understanding the close connection between genetic changes and ovarian carcinogenesis would provide the opportunity to find novel gene-level ovarian cancer biomarkers. In this review, we summarize the various gene-based biomarkers by genomic technologies, including inherited gene mutations, epigenetic changes, and differential gene expression. In addition, we suggest the strategy to discover novel gene-based biomarkers with recently introduced next generation sequencing.
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Affiliation(s)
- Jung-Yun Lee
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine
| | - Hee Seung Kim
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine
| | - Dong Hoon Suh
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine
| | - Mi-Kyung Kim
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine
| | - Hyun Hoon Chung
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine
| | - Yong-Sang Song
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine ; Cancer Research Institute, Seoul National University College of Medicine ; Major in Biomodulation, World Class University, Seoul National University, Seoul, Korea
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23
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Kohn EC, Romano S, Lee JM. Clinical implications of using molecular diagnostics for ovarian cancers. Ann Oncol 2014; 24 Suppl 10:x22-26. [PMID: 24265398 DOI: 10.1093/annonc/mdt464] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
In the era of morphologic diagnostics, any epithelial tumor on or involving the ovaries was presumed to come from and be strictly of ovarian origin, apart from the rare but clearly metastatic tumors. Thus, many women who might have had small fallopian tube primary cancers that rapidly extended on to or into the ovary were deemed to have ovarian cancer. Now, as we begin to better understand that there are different types of cancers of nonuterine Muellerian origin, we expand upon the morphologic to add the molecular characteristics. Morphomolecular characteristics are being applied to drive clinical advances including development and optimization of predictive and prognostic biomarkers, redefinition of historical controls, and consideration of novel clinical trial designs. Ovarian cancer, not a common cancer to start with, is now subdivided into types, making ever smaller clinical cohorts. The first studies evaluating tubo-ovarian Muellerian cancers of morphomolecular types have begun. Deleterious mutations in BRCA1 or 2 have been validated as the first new predictive and prognostic biomarker of the high-grade serous ovarian cancer type and polyADPribose polymerase inhibitors, the first targeted agents for this morphomolecular entity. Similar progress is developing in other tubo-ovarian cancer types. This new knowledge is driving the building of a structure-function-type relationship that is generating novel clinically applicable hypotheses for testing.
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Affiliation(s)
- E C Kohn
- Molecular Signaling Section, Medical Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda
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24
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Kohn EC. Molecular profiling and commercial predication assays in ovarian cancer: still not ready for prime time? Am Soc Clin Oncol Educ Book 2014:139-147. [PMID: 24857070 DOI: 10.14694/edbook_am.2014.34.139] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Short of early detection to allow curative primary intervention, the other major barrier to further success in treatment of ovarian cancers is matching the best treatment to the proper ovarian cancer type and to the individual patient. There are several decades of experience applying in vitro chemoresponse testing for solid tumors including ovarian cancer. This concept, first described in 1979, has yet to receive level one evidence supporting its application, despite the testing of numerous assays commercially as well as in academic centers and its use for tens of thousands of patients at a significant cost. The approach-rather than undergoing rigorous scientific examination-is now being muddied by the development of commercial molecular profiling assays from which treatment suggestions are provided. Molecular profiling as a research tool has added value to our understanding and treatment of patients with ovarian cancer. Morphologic and histochemical characterizations coupled now with increasing knowledge of ovarian cancer type-specific molecular patterns is improving our ability to properly diagnosis ovarian cancer type and thus guide therapy. With the exception of the role of germ-line and possibly somatic BRCA1 and BRCA2 mutations and their true predictiveness for probable response to poly(ADP-ribose) polymerase inhibition, molecular typing and profiling has yet to identify druggable molecular targets in ovarian cancer. Its use should be continued as a research and learning tool, and its results should be subjected to clinical trial validation. For very different reasons, neither chemoresponse assays nor molecular profiling are ready for prime time, yet.
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Affiliation(s)
- Elise C Kohn
- From the Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
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25
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Casado P, Alcolea MP, Iorio F, Rodríguez-Prados JC, Vanhaesebroeck B, Saez-Rodriguez J, Joel S, Cutillas PR. Phosphoproteomics data classify hematological cancer cell lines according to tumor type and sensitivity to kinase inhibitors. Genome Biol 2013; 14:R37. [PMID: 23628362 PMCID: PMC4054101 DOI: 10.1186/gb-2013-14-4-r37] [Citation(s) in RCA: 51] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2012] [Accepted: 04/29/2013] [Indexed: 01/08/2023] Open
Abstract
Background Tumor classification based on their predicted responses to kinase inhibitors is a major goal for advancing targeted personalized therapies. Here, we used a phosphoproteomic approach to investigate biological heterogeneity across hematological cancer cell lines including acute myeloid leukemia, lymphoma, and multiple myeloma. Results Mass spectrometry was used to quantify 2,000 phosphorylation sites across three acute myeloid leukemia, three lymphoma, and three multiple myeloma cell lines in six biological replicates. The intensities of the phosphorylation sites grouped these cancer cell lines according to their tumor type. In addition, a phosphoproteomic analysis of seven acute myeloid leukemia cell lines revealed a battery of phosphorylation sites whose combined intensities correlated with the growth-inhibitory responses to three kinase inhibitors with remarkable correlation coefficients and fold changes (> 100 between the most resistant and sensitive cells). Modeling based on regression analysis indicated that a subset of phosphorylation sites could be used to predict response to the tested drugs. Quantitative analysis of phosphorylation motifs indicated that resistant and sensitive cells differed in their patterns of kinase activities, but, interestingly, phosphorylations correlating with responses were not on members of the pathway being targeted; instead, these mainly were on parallel kinase pathways. Conclusion This study reveals that the information on kinase activation encoded in phosphoproteomics data correlates remarkably well with the phenotypic responses of cancer cells to compounds that target kinase signaling and could be useful for the identification of novel markers of resistance or sensitivity to drugs that target the signaling network.
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26
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Toss A, De Matteis E, Rossi E, Casa LD, Iannone A, Federico M, Cortesi L. Ovarian cancer: can proteomics give new insights for therapy and diagnosis? Int J Mol Sci 2013; 14:8271-90. [PMID: 23591842 PMCID: PMC3645742 DOI: 10.3390/ijms14048271] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2013] [Revised: 03/11/2013] [Accepted: 04/02/2013] [Indexed: 12/24/2022] Open
Abstract
The study of the ovarian proteomic profile represents a new frontier in ovarian cancer research, since this approach is able to enlighten the wide variety of post-translational events (such as glycosylation and phosphorylation). Due to the possibility of analyzing thousands of proteins, which could be simultaneously altered, comparative proteomics represent a promising model of possible biomarker discovery for ovarian cancer detection and monitoring. Moreover, defining signaling pathways in ovarian cancer cells through proteomic analysis offers the opportunity to design novel drugs and to optimize the use of molecularly targeted agents against crucial and biologically active pathways. Proteomic techniques provide more information about different histological types of ovarian cancer, cell growth and progression, genes related to tumor microenvironment and specific molecular targets predictive of response to chemotherapy than sequencing or microarrays. Estimates of specificity with proteomics are less consistent, but suggest a new role for combinations of biomarkers in early ovarian cancer diagnosis, such as the OVA1 test. Finally, the definition of the proteomic profiles in ovarian cancer would be accurate and effective in identifying which pathways are differentially altered, defining the most effective therapeutic regimen and eventually improving health outcomes.
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Affiliation(s)
- Angela Toss
- Department of Oncology & Haematology, University of Modena and Reggio Emilia, Modena 41125, Italy; E-Mails: (A.T.); (E.D.M.); (M.F.)
| | - Elisabetta De Matteis
- Department of Oncology & Haematology, University of Modena and Reggio Emilia, Modena 41125, Italy; E-Mails: (A.T.); (E.D.M.); (M.F.)
| | - Elena Rossi
- ProteoWork Lab, the Department of Biomedical Sciences, University of Modena and Reggio Emilia, Modena 41125, Italy; E-Mails: (E.R.); (L.D.C.); (A.I.)
| | - Lara Della Casa
- ProteoWork Lab, the Department of Biomedical Sciences, University of Modena and Reggio Emilia, Modena 41125, Italy; E-Mails: (E.R.); (L.D.C.); (A.I.)
| | - Anna Iannone
- ProteoWork Lab, the Department of Biomedical Sciences, University of Modena and Reggio Emilia, Modena 41125, Italy; E-Mails: (E.R.); (L.D.C.); (A.I.)
| | - Massimo Federico
- Department of Oncology & Haematology, University of Modena and Reggio Emilia, Modena 41125, Italy; E-Mails: (A.T.); (E.D.M.); (M.F.)
| | - Laura Cortesi
- Department of Oncology & Haematology, University of Modena and Reggio Emilia, Modena 41125, Italy; E-Mails: (A.T.); (E.D.M.); (M.F.)
- Author to whom correspondence should be addressed; E-Mail: ; Tel.: +39-059-4224-334; Fax: +39-059-4224-152
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Kipps E, Tan DSP, Kaye SB. Meeting the challenge of ascites in ovarian cancer: new avenues for therapy and research. Nat Rev Cancer 2013; 13:273-82. [PMID: 23426401 PMCID: PMC4673904 DOI: 10.1038/nrc3432] [Citation(s) in RCA: 395] [Impact Index Per Article: 35.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Malignant ascites presents a considerable clinical challenge to the management of ovarian cancer, but also provides a wealth of opportunities for translational research. The accessibility of ascitic fluid and its cellular components make it an excellent source of tumour tissue for the investigation of prognostic and predictive biomarkers, pharmacodynamic markers and for molecular profiling analysis. In this Opinion article, we discuss recent advances in our understanding of its pathophysiology, the development of new methods to characterize its molecular features and how these findings can be used to improve the treatment of malignant ascites, particularly in the context of ovarian cancer.
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Affiliation(s)
- Emma Kipps
- The Institute of Cancer Research/Royal Marsden Hospital, Medicine, Downs Road, Sutton SM2 5PT, UK
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28
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Luk VN, Fiddes LK, Luk VM, Kumacheva E, Wheeler AR. Digital microfluidic hydrogel microreactors for proteomics. Proteomics 2012; 12:1310-8. [PMID: 22589180 DOI: 10.1002/pmic.201100608] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Proteolytic digestion is an essential step in proteomic sample processing. While this step has traditionally been implemented in homogeneous (solution) format, there is a growing trend to use heterogeneous systems in which the enzyme is immobilized on hydrogels or other solid supports. Here, we introduce the use of immobilized enzymes in hydrogels for proteomic sample processing in digital microfluidic (DMF) systems. In this technique, preformed cylindrical agarose discs bearing immobilized trypsin or pepsin were integrated into DMF devices. A fluorogenic assay was used to optimize the covalent modification procedure for enzymatic digestion efficiency, with maximum efficiency observed at 31 μg trypsin in 2-mm diameter agarose gel discs. Gel discs prepared in this manner were used in an integrated method in which proteomic samples were sequentially reduced, alkylated, and digested, with all sample and reagent handling controlled by DMF droplet operation. Mass spectrometry analysis of the products revealed that digestion using the trypsin gel discs resulted in higher sequence coverage in model analytes relative to conventional homogenous processing. Proof-of-principle was demonstrated for a parallel digestion system in which a single sample was simultaneously digested on multiple gel discs bearing different enzymes. We propose that these methods represent a useful new tool for the growing trend toward miniaturization and automation in proteomic sample processing.
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Affiliation(s)
- Vivienne N Luk
- Department of Chemistry, University of Toronto, Toronto, ON, Canada
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29
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Moñux Ducaju G, Mateos Cáceres P, Zamorano León J, Serrano Hernando J, López Farré A. Genética, epigenética y proteómica de los aneurismas de aorta abdominal. ANGIOLOGIA 2012. [DOI: 10.1016/j.angio.2012.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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30
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Russo LL, Papale M, Perrone D, Ranieri E, Rubini C, Giannatempo G, Santarelli A, Colella G, Muzio LL. Salivary Proteomic Signatures of Oral Squamous Cell Carcinoma. EUR J INFLAMM 2012. [DOI: 10.1177/1721727x1201000107] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Delay in diagnosing oral squamous cell carcinoma (OSCC) can be still identified as a major cause of its high morbidity and mortality. To date, the early diagnosis for OSCC is mainly based on clinical oral examination and there is an urgent need for reliable markers; thus, advancements in molecular technologies has set the stage for investigating new markers, as well as new diagnostic matrices. The aim of the present study is to investigate the presence of proteomic signatures of OSCC in saliva and their use as potential biomarkers for early and non-invasive diagnosis. Saliva from 45 OSCC patients and 30 healthy controls was analysed by SELDI-TOF mass spectrometry and ProteinChip® technology. A supervised multivariate statistical analysis (Classification and Regression Tree - CART) was used to build models for discriminating between OSCC and controls, and between early (ES-OSCC) and late stage (LS-OSCC) cancers. The peptide with 8041 Da mass was 22-fold more expressed in OSCC, thus being a suitable potential biomarker. Classification and regression analysis allowed to build a model that was capable of correctly classifying all cancers and controls in an independent testing set, using the 8041 m/z peak as splitter. Eleven peaks were also differently expressed between ES-OSCCand LS-OSCC, but, basing on these differences, it was not possible to build an algorithm to predict tumour staging. These findings confirm that saliva proteome in OSCC patients is different from healthy controls and these variations might reflect different stages of disease progression and are worthy of further validation as diagnostic and prognostic biomarkers.
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Affiliation(s)
- L. Lo Russo
- Department of Surgical Sciences, University o/Foggia, Foggia, Italy
| | - M. Papale
- Department of BIOAGROMED, University of Foggia, Foggia, Italy
| | - D. Perrone
- Department of Surgical Sciences, University o/Foggia, Foggia, Italy
| | - E. Ranieri
- Department of BIOAGROMED, University of Foggia, Foggia, Italy
| | - C. Rubini
- Department of Neurosciences, Institute of Pathologic Anatomy, University of Ancona, Ancona, Italy
| | - G. Giannatempo
- Department of Surgical Sciences, University o/Foggia, Foggia, Italy
| | - A. Santarelli
- Department of Surgical Sciences, University o/Foggia, Foggia, Italy
| | - G. Colella
- Department of Head and Neck Pathology, Second University of Naples, Naples, Italy
| | - L. Lo Muzio
- Department of Surgical Sciences, University o/Foggia, Foggia, Italy
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31
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Feng JG, Liu Q, Qin X, Geng YH, Zheng ST, Liu T, Sheyhidin I, Lu XM. Clinicopathological pattern and Annexin A2 and Cdc42 status in patients presenting with differentiation and lymphnode metastasis of esophageal squamous cell carcinomas. Mol Biol Rep 2011; 39:1267-74. [PMID: 21603851 DOI: 10.1007/s11033-011-0859-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2010] [Accepted: 05/12/2011] [Indexed: 12/18/2022]
Abstract
Annexin A2 and Cdc42 were identified by 2-dimensional electrophoresis (2-DE) and MALDI-TOF-MS between esophageal squamous cell carcinomas (ESCC) and corresponding normal esophagus mucosa in our previous study. To assess clinico-pathological pattern and Annexin A2 and Cdc42 status with respect to cell differentiation and lymphnode metastasis in patients with ESCC. The expression of Annexin A2 and Cdc42 in 22 pairs of fresh ESCC and matched tissues were detected by qRT-PCR and western blot, respectively. And it was further confirmed by immunohistochemistry with 175 pairs of formalin-fixed, paraffin-embedded ESCC. Results showed that Annexin A2 expression was significantly down-regulated, and Cdc42 was up-regulated in ESCC compared to matched control on both mRNA and protein level (P < 0.05), which was in accordance with our previous results on proteomics data. Additionally, Annexin A2 and Cdc42 expression was significantly correlated with lymphoid node metastasis (P < 0.05) and pathological differentiation (P < 0.05). Taken together, we proposed that the aberrant expression of Annexin A2 and Cdc42 played a role in carcinogenesis, differentiation and metastasis of ESCC, which implied its potential target for clinical biomarkers in differentiation and lymph node metastasis.
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Affiliation(s)
- Jun-Guo Feng
- Medical Research Center, The Affiliated Hospital, Xinjiang Medical University, Urumqi 830054, Xinjiang Uygur Autonomous Region, People's Republic of China
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