Correlation of histopathologic characteristics to protein expression and function in malignant melanoma
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. Howev...
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| creator | Welinder, Charlotte Pawłowski, Krzysztof Szasz, A Marcell Yakovleva, Maria Sugihara, Yutaka Malm, Johan Jönsson, Göran Ingvar, Christian Lundgren, Lotta Baldetorp, Bo Olsson, Håkan Rezeli, Melinda Laurell, Thomas Wieslander, Elisabet Marko-Varga, György |
| description | 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.
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.
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.
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 p |
| doi_str_mv | 10.1371/journal.pone.0176167 |
| format | Article |
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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.
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.
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.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0176167</identifier><identifier>PMID: 28445515</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adult ; Aged ; Analysis ; Biology and Life Sciences ; Biomarkers ; Biomarkers, Tumor - analysis ; Cancer and Oncology ; Cancer metastasis ; Cancer och onkologi ; Clinical Laboratory Medicine ; Clinical Medicine ; Data mining ; Data processing ; Development and progression ; Diagnosis ; Disease Progression ; Feasibility studies ; Female ; Gene Expression Regulation, Neoplastic ; Health aspects ; Hepatocyte nuclear factor 4 ; Hepatocyte Nuclear Factor 4 - genetics ; Hepatocyte Nuclear Factor 4 - metabolism ; Heterogeneity ; High resolution ; Histopathology ; Humans ; Kinases ; Klinisk laboratoriemedicin ; Klinisk medicin ; Lymph ; Lymph nodes ; Lymphatic Metastasis ; Male ; Mass spectrometry ; Mass spectroscopy ; Medical and Health Sciences ; Medicin och hälsovetenskap ; Medicine and Health Sciences ; Melanoma ; Melanoma - metabolism ; Melanoma - mortality ; Melanoma - pathology ; Metastases ; Middle Aged ; Myc protein ; Neoplasm Staging ; Pathology ; Patients ; Predictions ; Prognosis ; Proliferating cell nuclear antigen ; Protein composition ; Proteins ; Proteomics ; Proto-Oncogene Proteins c-myc - genetics ; Proto-Oncogene Proteins c-myc - metabolism ; Regulators ; Research and Analysis Methods ; Science ; Skin cancer ; Skin Neoplasms - metabolism ; Skin Neoplasms - pathology ; Spectroscopy ; Survival ; Survival Rate ; Transforming Growth Factor beta1 - genetics ; Transforming Growth Factor beta1 - metabolism ; Transforming growth factor-b1 ; Tumors</subject><ispartof>PloS one, 2017-04, Vol.12 (4), p.e0176167-e0176167</ispartof><rights>COPYRIGHT 2017 Public Library of Science</rights><rights>2017 Welinder et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2017 Welinder et al 2017 Welinder et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c761t-54124d0255d7fe59e789477a3d0e62775e342f1a1a566df5f12bff6a379692013</citedby><cites>FETCH-LOGICAL-c761t-54124d0255d7fe59e789477a3d0e62775e342f1a1a566df5f12bff6a379692013</cites><orcidid>0000-0001-9626-0576</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5405986/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5405986/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,552,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28445515$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://lup.lub.lu.se/record/4669321e-f34a-487f-8253-8ec19d565b24$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><contributor>Zmijewski, Michal</contributor><creatorcontrib>Welinder, Charlotte</creatorcontrib><creatorcontrib>Pawłowski, Krzysztof</creatorcontrib><creatorcontrib>Szasz, A Marcell</creatorcontrib><creatorcontrib>Yakovleva, Maria</creatorcontrib><creatorcontrib>Sugihara, Yutaka</creatorcontrib><creatorcontrib>Malm, Johan</creatorcontrib><creatorcontrib>Jönsson, Göran</creatorcontrib><creatorcontrib>Ingvar, Christian</creatorcontrib><creatorcontrib>Lundgren, Lotta</creatorcontrib><creatorcontrib>Baldetorp, Bo</creatorcontrib><creatorcontrib>Olsson, Håkan</creatorcontrib><creatorcontrib>Rezeli, Melinda</creatorcontrib><creatorcontrib>Laurell, Thomas</creatorcontrib><creatorcontrib>Wieslander, Elisabet</creatorcontrib><creatorcontrib>Marko-Varga, György</creatorcontrib><title>Correlation of histopathologic characteristics to protein expression and function in malignant melanoma</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>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.
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.
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.
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.</description><subject>Adult</subject><subject>Aged</subject><subject>Analysis</subject><subject>Biology and Life Sciences</subject><subject>Biomarkers</subject><subject>Biomarkers, Tumor - analysis</subject><subject>Cancer and Oncology</subject><subject>Cancer metastasis</subject><subject>Cancer och onkologi</subject><subject>Clinical Laboratory Medicine</subject><subject>Clinical Medicine</subject><subject>Data mining</subject><subject>Data processing</subject><subject>Development and progression</subject><subject>Diagnosis</subject><subject>Disease Progression</subject><subject>Feasibility studies</subject><subject>Female</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Health aspects</subject><subject>Hepatocyte nuclear factor 4</subject><subject>Hepatocyte Nuclear Factor 4 - genetics</subject><subject>Hepatocyte Nuclear Factor 4 - metabolism</subject><subject>Heterogeneity</subject><subject>High resolution</subject><subject>Histopathology</subject><subject>Humans</subject><subject>Kinases</subject><subject>Klinisk laboratoriemedicin</subject><subject>Klinisk medicin</subject><subject>Lymph</subject><subject>Lymph nodes</subject><subject>Lymphatic Metastasis</subject><subject>Male</subject><subject>Mass spectrometry</subject><subject>Mass spectroscopy</subject><subject>Medical and Health Sciences</subject><subject>Medicin och hälsovetenskap</subject><subject>Medicine and Health Sciences</subject><subject>Melanoma</subject><subject>Melanoma - metabolism</subject><subject>Melanoma - mortality</subject><subject>Melanoma - pathology</subject><subject>Metastases</subject><subject>Middle Aged</subject><subject>Myc protein</subject><subject>Neoplasm Staging</subject><subject>Pathology</subject><subject>Patients</subject><subject>Predictions</subject><subject>Prognosis</subject><subject>Proliferating cell nuclear antigen</subject><subject>Protein composition</subject><subject>Proteins</subject><subject>Proteomics</subject><subject>Proto-Oncogene Proteins c-myc - genetics</subject><subject>Proto-Oncogene Proteins c-myc - metabolism</subject><subject>Regulators</subject><subject>Research and Analysis Methods</subject><subject>Science</subject><subject>Skin cancer</subject><subject>Skin Neoplasms - metabolism</subject><subject>Skin Neoplasms - pathology</subject><subject>Spectroscopy</subject><subject>Survival</subject><subject>Survival Rate</subject><subject>Transforming Growth Factor beta1 - genetics</subject><subject>Transforming Growth Factor beta1 - metabolism</subject><subject>Transforming growth 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Medicine</topic><topic>Data mining</topic><topic>Data processing</topic><topic>Development and progression</topic><topic>Diagnosis</topic><topic>Disease Progression</topic><topic>Feasibility studies</topic><topic>Female</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Health aspects</topic><topic>Hepatocyte nuclear factor 4</topic><topic>Hepatocyte Nuclear Factor 4 - genetics</topic><topic>Hepatocyte Nuclear Factor 4 - metabolism</topic><topic>Heterogeneity</topic><topic>High resolution</topic><topic>Histopathology</topic><topic>Humans</topic><topic>Kinases</topic><topic>Klinisk laboratoriemedicin</topic><topic>Klinisk medicin</topic><topic>Lymph</topic><topic>Lymph nodes</topic><topic>Lymphatic Metastasis</topic><topic>Male</topic><topic>Mass spectrometry</topic><topic>Mass spectroscopy</topic><topic>Medical and Health Sciences</topic><topic>Medicin och hälsovetenskap</topic><topic>Medicine and Health Sciences</topic><topic>Melanoma</topic><topic>Melanoma - 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Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>SwePub</collection><collection>SWEPUB Lunds universitet full text</collection><collection>SwePub Articles</collection><collection>SWEPUB Freely available online</collection><collection>SWEPUB Lunds universitet</collection><collection>SwePub Articles full text</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Welinder, Charlotte</au><au>Pawłowski, Krzysztof</au><au>Szasz, A Marcell</au><au>Yakovleva, Maria</au><au>Sugihara, Yutaka</au><au>Malm, Johan</au><au>Jönsson, Göran</au><au>Ingvar, Christian</au><au>Lundgren, Lotta</au><au>Baldetorp, Bo</au><au>Olsson, Håkan</au><au>Rezeli, Melinda</au><au>Laurell, Thomas</au><au>Wieslander, Elisabet</au><au>Marko-Varga, György</au><au>Zmijewski, Michal</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Correlation of histopathologic characteristics to protein expression and function in malignant melanoma</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2017-04-26</date><risdate>2017</risdate><volume>12</volume><issue>4</issue><spage>e0176167</spage><epage>e0176167</epage><pages>e0176167-e0176167</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>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.
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.
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.
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.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>28445515</pmid><doi>10.1371/journal.pone.0176167</doi><tpages>e0176167</tpages><orcidid>https://orcid.org/0000-0001-9626-0576</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2017-04, Vol.12 (4), p.e0176167-e0176167 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1892318390 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; SWEPUB Freely available online; Public Library of Science (PLoS); PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Adult Aged Analysis Biology and Life Sciences Biomarkers Biomarkers, Tumor - analysis Cancer and Oncology Cancer metastasis Cancer och onkologi Clinical Laboratory Medicine Clinical Medicine Data mining Data processing Development and progression Diagnosis Disease Progression Feasibility studies Female Gene Expression Regulation, Neoplastic Health aspects Hepatocyte nuclear factor 4 Hepatocyte Nuclear Factor 4 - genetics Hepatocyte Nuclear Factor 4 - metabolism Heterogeneity High resolution Histopathology Humans Kinases Klinisk laboratoriemedicin Klinisk medicin Lymph Lymph nodes Lymphatic Metastasis Male Mass spectrometry Mass spectroscopy Medical and Health Sciences Medicin och hälsovetenskap Medicine and Health Sciences Melanoma Melanoma - metabolism Melanoma - mortality Melanoma - pathology Metastases Middle Aged Myc protein Neoplasm Staging Pathology Patients Predictions Prognosis Proliferating cell nuclear antigen Protein composition Proteins Proteomics Proto-Oncogene Proteins c-myc - genetics Proto-Oncogene Proteins c-myc - metabolism Regulators Research and Analysis Methods Science Skin cancer Skin Neoplasms - metabolism Skin Neoplasms - pathology Spectroscopy Survival Survival Rate Transforming Growth Factor beta1 - genetics Transforming Growth Factor beta1 - metabolism Transforming growth factor-b1 Tumors |
| title | Correlation of histopathologic characteristics to protein expression and function in malignant melanoma |
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