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- Szász, Marcell, et al.
(författare)
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Cancer heterogeneity determined by functional proteomics
- 2017
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Ingår i: Seminars in Cell and Developmental Biology. - : Elsevier BV. - 1084-9521. ; 64, s. 132-142
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Tidskriftsartikel (refereegranskat)abstract
- Current manuscript gives a synopsis of tumor heterogeneity related to patient samples analyzed by proteomics, protein expression analysis and imaging mass spectrometry.First, we discuss the pathophysiologocal background of cancer biology as a multifactorial and challenging diseases. Disease pathology forms the basis for protein target selection. Therefore, histopathological diagnostics and grading of tumors is highlighted. Pathology is the cornerstone of state-of-the-art diagnostics of tumors today both by establishing dignity and - when needed - describing molecular properties of the cancers. Drug development by the pharmaceutical industry utilizes proteomics studies to pinpoint the most relevant targets. Molecular studies profiling affinity-interactions of the protein(s) with targeted small drug molecules to reach efficacy and optimal patient safety are today requested by the FDA and other agencies for new drug development.An understading of basic mechanisms, controlling drug action and drug binding is central, as a new era of personalized medicine becomes an important milestone solution for the healthcare sector as well as the Pharma and Biotech industry. Development of further diagnostic, prognostic and predictive tests will aid current and future treatment of cancer patients.In the paper we present current status of Proteomics that we believe requires attention in order to collectively advance forward in the fight against cancer, addressing the burning opportunities and challenges.
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| 2. |
- Welinder, Charlotte, et al.
(författare)
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Correlation of histopathologic characteristics to protein expression and function in malignant melanoma
- 2017
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 12:4
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Tidskriftsartikel (refereegranskat)abstract
- Background Metastatic melanoma is still one of the most prevalent skin cancers, which upon progression has neither a prognostic marker nor a specific and lasting treatment. Proteomic analysis is a versatile approach with high throughput data and results that can be used for characterizing tissue samples. However, such analysis is hampered by the complexity of the disease, heterogeneity of patients, tumors, and samples themselves. With the long term aim of quest for better diagnostics biomarkers, as well as predictive and prognostic markers, we focused on relating high resolution proteomics data to careful histopathological evaluation of the tumor samples and patient survival information. Patients and methods Regional lymph node metastases obtained from ten patients with metastatic melanoma (stage III) were analyzed by histopathology and proteomics using mass spectrometry. Out of the ten patients, six had clinical follow-up data. The protein deep mining mass spectrometry data was related to the histopathology tumor tissue sections adjacent to the area used for deep-mining. Clinical follow-up data provided information on disease progression which could be linked to protein expression aiming to identify tissue-based specific protein markers for metastatic melanoma and prognostic factors for prediction of progression of stage III disease.Results In this feasibility study, several proteins were identified that positively correlated to tumor tissue content including IF6, ARF4, MUC18, UBC12, CSPG4, PCNA, PMEL and MAGD2. The study also identified MYC, HNF4A and TGFB1 as top upstream regulators correlating to tumor tissue content. Other proteins were inversely correlated to tumor tissue content, the most significant being; TENX, EHD2, ZA2G, AOC3, FETUA and THRB. A number of proteins were significantly related to clinical outcome, among these, HEXB, PKM and GPNMB stood out, as hallmarks of processes involved in progression from stage III to stage IV disease and poor survival. Conclusion In this feasibility study, promising results show the feasibility of relating proteomics to histopathology and clinical outcome, and insight thus can be gained into the molecular processes driving the disease. The combined analysis of histological features including the sample cellular composition with protein expression of each metastasis enabled the identification of novel, differentially expressed proteins. Further studies are necessary to determine whether these putative biomarkers can be utilized in diagnostics and prognostic prediction of metastatic melanoma.
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