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Immune-Proteome Profiling in Classical Hodgkin Lymphoma Tumor Diagnostic Tissue
In classical Hodgkin Lymphoma (cHL), immunoediting via protein signaling is key to evading tumor surveillance. We aimed to identify immune-related proteins that distinguish diagnostic cHL tissues (=diagnostic tumor lysates, = 27) from control tissues (reactive lymph node lysates, = 30). Further, we...
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| Published in: | Cancers 2022-01, Vol.14 (1), p.9 |
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| creator | Gholiha, Alex Reza Hollander, Peter Löf, Liza Larsson, Anders Hashemi, Jamileh Ulfstedt, Johan Mattsson Molin, Daniel Amini, Rose-Marie Freyhult, Eva Kamali-Moghaddam, Masood Enblad, Gunilla |
| description | In classical Hodgkin Lymphoma (cHL), immunoediting via protein signaling is key to evading tumor surveillance. We aimed to identify immune-related proteins that distinguish diagnostic cHL tissues (=diagnostic tumor lysates,
= 27) from control tissues (reactive lymph node lysates,
= 30). Further, we correlated our findings with the proteome plasma profile between cHL patients (
= 26) and healthy controls (
= 27). We used the proximity extension assay (PEA) with the OlinkTM multiplex Immuno-Oncology panel, consisting of 92 proteins. Univariate, multivariate-adjusted analysis and Benjamini-Hochberg's false discovery testing (=Padj) were performed to detect significant discrepancies. Proteins distinguishing cHL cases from controls were more numerous in plasma (30 proteins) than tissue (17 proteins), all Padj < 0.05. Eight of the identified proteins in cHL tissue (PD-L1, IL-6, CCL17, CCL3, IL-13, MMP12, TNFRS4, and LAG3) were elevated in both cHL tissues and cHL plasma compared with control samples. Six proteins distinguishing cHL tissues from controls tissues were significantly correlated to PD-L1 expression in cHL tissue (IL-6, MCP-2, CCL3, CCL4, GZMB, and IFN-gamma, all
≤0.05). In conclusion, this study introduces a distinguishing proteomic profile in cHL tissue and potential immune-related markers of pathophysiological relevance. |
| doi_str_mv | 10.3390/cancers14010009 |
| format | article |
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= 27) from control tissues (reactive lymph node lysates,
= 30). Further, we correlated our findings with the proteome plasma profile between cHL patients (
= 26) and healthy controls (
= 27). We used the proximity extension assay (PEA) with the OlinkTM multiplex Immuno-Oncology panel, consisting of 92 proteins. Univariate, multivariate-adjusted analysis and Benjamini-Hochberg's false discovery testing (=Padj) were performed to detect significant discrepancies. Proteins distinguishing cHL cases from controls were more numerous in plasma (30 proteins) than tissue (17 proteins), all Padj < 0.05. Eight of the identified proteins in cHL tissue (PD-L1, IL-6, CCL17, CCL3, IL-13, MMP12, TNFRS4, and LAG3) were elevated in both cHL tissues and cHL plasma compared with control samples. Six proteins distinguishing cHL tissues from controls tissues were significantly correlated to PD-L1 expression in cHL tissue (IL-6, MCP-2, CCL3, CCL4, GZMB, and IFN-gamma, all
≤0.05). In conclusion, this study introduces a distinguishing proteomic profile in cHL tissue and potential immune-related markers of pathophysiological relevance.</description><identifier>ISSN: 2072-6694</identifier><identifier>EISSN: 2072-6694</identifier><identifier>DOI: 10.3390/cancers14010009</identifier><identifier>PMID: 35008176</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Algorithms ; Biobanks ; Biomarkers ; Biopsy ; Cancer ; Cancer immunotherapy ; CCL17 protein ; CCL3 protein ; Epstein-Barr virus ; Gender ; Gene expression ; Hodgkin's lymphoma ; Interleukin 13 ; Interleukin 6 ; Lymph nodes ; Lymphatic system ; Lymphoma ; Lysates ; Patients ; PD-L1 protein ; Plasma ; Precision medicine ; Proteins ; Proteomes ; Proteomics ; Regression analysis ; Therapeutic targets ; Tumor microenvironment ; Tumors ; γ-Interferon</subject><ispartof>Cancers, 2022-01, Vol.14 (1), p.9</ispartof><rights>2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 by the authors. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c458t-7cd465a5d5b6ebbb4c45feb8117389f13811f8c830494350b811fe0fe18fa7503</citedby><cites>FETCH-LOGICAL-c458t-7cd465a5d5b6ebbb4c45feb8117389f13811f8c830494350b811fe0fe18fa7503</cites><orcidid>0000-0002-0226-5681 ; 0000-0003-3161-0402 ; 0000-0002-3393-1106 ; 0000-0003-0226-1047 ; 0000-0003-0682-7394</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2618209119/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2618209119?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35008176$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-455820$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><creatorcontrib>Gholiha, Alex Reza</creatorcontrib><creatorcontrib>Hollander, Peter</creatorcontrib><creatorcontrib>Löf, Liza</creatorcontrib><creatorcontrib>Larsson, Anders</creatorcontrib><creatorcontrib>Hashemi, Jamileh</creatorcontrib><creatorcontrib>Ulfstedt, Johan Mattsson</creatorcontrib><creatorcontrib>Molin, Daniel</creatorcontrib><creatorcontrib>Amini, Rose-Marie</creatorcontrib><creatorcontrib>Freyhult, Eva</creatorcontrib><creatorcontrib>Kamali-Moghaddam, Masood</creatorcontrib><creatorcontrib>Enblad, Gunilla</creatorcontrib><title>Immune-Proteome Profiling in Classical Hodgkin Lymphoma Tumor Diagnostic Tissue</title><title>Cancers</title><addtitle>Cancers (Basel)</addtitle><description>In classical Hodgkin Lymphoma (cHL), immunoediting via protein signaling is key to evading tumor surveillance. We aimed to identify immune-related proteins that distinguish diagnostic cHL tissues (=diagnostic tumor lysates,
= 27) from control tissues (reactive lymph node lysates,
= 30). Further, we correlated our findings with the proteome plasma profile between cHL patients (
= 26) and healthy controls (
= 27). We used the proximity extension assay (PEA) with the OlinkTM multiplex Immuno-Oncology panel, consisting of 92 proteins. Univariate, multivariate-adjusted analysis and Benjamini-Hochberg's false discovery testing (=Padj) were performed to detect significant discrepancies. Proteins distinguishing cHL cases from controls were more numerous in plasma (30 proteins) than tissue (17 proteins), all Padj < 0.05. Eight of the identified proteins in cHL tissue (PD-L1, IL-6, CCL17, CCL3, IL-13, MMP12, TNFRS4, and LAG3) were elevated in both cHL tissues and cHL plasma compared with control samples. Six proteins distinguishing cHL tissues from controls tissues were significantly correlated to PD-L1 expression in cHL tissue (IL-6, MCP-2, CCL3, CCL4, GZMB, and IFN-gamma, all
≤0.05). In conclusion, this study introduces a distinguishing proteomic profile in cHL tissue and potential immune-related markers of pathophysiological relevance.</description><subject>Algorithms</subject><subject>Biobanks</subject><subject>Biomarkers</subject><subject>Biopsy</subject><subject>Cancer</subject><subject>Cancer immunotherapy</subject><subject>CCL17 protein</subject><subject>CCL3 protein</subject><subject>Epstein-Barr virus</subject><subject>Gender</subject><subject>Gene expression</subject><subject>Hodgkin's lymphoma</subject><subject>Interleukin 13</subject><subject>Interleukin 6</subject><subject>Lymph nodes</subject><subject>Lymphatic system</subject><subject>Lymphoma</subject><subject>Lysates</subject><subject>Patients</subject><subject>PD-L1 protein</subject><subject>Plasma</subject><subject>Precision medicine</subject><subject>Proteins</subject><subject>Proteomes</subject><subject>Proteomics</subject><subject>Regression analysis</subject><subject>Therapeutic targets</subject><subject>Tumor microenvironment</subject><subject>Tumors</subject><subject>γ-Interferon</subject><issn>2072-6694</issn><issn>2072-6694</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNpdkcFPHCEUxknTphr13FszSS89dOpjGGbg0sSstZpsYg-rV8KwMGIH2MJg439f1lWjnvjy3u99PPgQ-oThOyEcjpX0SseEW8AAwN-h_Qb6pu463r5_offQUUq3hQBCcN_1H9EeoQCs6H10eeFc9rr-HcOsg9NVEcZO1o-V9dVikilZJafqPKzHP6WyvHebm-BktcouxOrUytGHNFtVrWxKWR-iD0ZOSR89ngfo6uznanFeLy9_XSxOlrVqKZvrXq3bjkq6pkOnh2FoS9nogWHcE8YNJkUZphiBlrdl223HaDAaMyN7CuQAfdv5pn96kwexidbJeC-CtOLUXp-IEEeRs2gpZc0W_7HDC-v0Wmk_Rzm9mnrd8fZGjOFOsHJZA7QYfH00iOFv1mkWzialp0l6HXISTYcZBw7QF_TLG_Q25OjLbzxQDXCMeaGOd5SKIaWozfMyGMQ2XvEm3jLx-eUbnvmnMMl_qSmiHA</recordid><startdate>20220101</startdate><enddate>20220101</enddate><creator>Gholiha, Alex Reza</creator><creator>Hollander, Peter</creator><creator>Löf, Liza</creator><creator>Larsson, Anders</creator><creator>Hashemi, Jamileh</creator><creator>Ulfstedt, Johan Mattsson</creator><creator>Molin, Daniel</creator><creator>Amini, Rose-Marie</creator><creator>Freyhult, Eva</creator><creator>Kamali-Moghaddam, Masood</creator><creator>Enblad, Gunilla</creator><general>MDPI AG</general><general>MDPI</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T5</scope><scope>7TO</scope><scope>7XB</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M2O</scope><scope>M7P</scope><scope>MBDVC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><scope>ACNBI</scope><scope>ADTPV</scope><scope>AOWAS</scope><scope>D8T</scope><scope>DF2</scope><scope>ZZAVC</scope><orcidid>https://orcid.org/0000-0002-0226-5681</orcidid><orcidid>https://orcid.org/0000-0003-3161-0402</orcidid><orcidid>https://orcid.org/0000-0002-3393-1106</orcidid><orcidid>https://orcid.org/0000-0003-0226-1047</orcidid><orcidid>https://orcid.org/0000-0003-0682-7394</orcidid></search><sort><creationdate>20220101</creationdate><title>Immune-Proteome Profiling in Classical Hodgkin Lymphoma Tumor Diagnostic Tissue</title><author>Gholiha, Alex Reza ; Hollander, Peter ; Löf, Liza ; Larsson, Anders ; Hashemi, Jamileh ; Ulfstedt, Johan Mattsson ; Molin, Daniel ; Amini, Rose-Marie ; Freyhult, Eva ; Kamali-Moghaddam, Masood ; Enblad, Gunilla</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c458t-7cd465a5d5b6ebbb4c45feb8117389f13811f8c830494350b811fe0fe18fa7503</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Biobanks</topic><topic>Biomarkers</topic><topic>Biopsy</topic><topic>Cancer</topic><topic>Cancer immunotherapy</topic><topic>CCL17 protein</topic><topic>CCL3 protein</topic><topic>Epstein-Barr virus</topic><topic>Gender</topic><topic>Gene expression</topic><topic>Hodgkin's lymphoma</topic><topic>Interleukin 13</topic><topic>Interleukin 6</topic><topic>Lymph nodes</topic><topic>Lymphatic system</topic><topic>Lymphoma</topic><topic>Lysates</topic><topic>Patients</topic><topic>PD-L1 protein</topic><topic>Plasma</topic><topic>Precision medicine</topic><topic>Proteins</topic><topic>Proteomes</topic><topic>Proteomics</topic><topic>Regression analysis</topic><topic>Therapeutic targets</topic><topic>Tumor microenvironment</topic><topic>Tumors</topic><topic>γ-Interferon</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gholiha, Alex Reza</creatorcontrib><creatorcontrib>Hollander, Peter</creatorcontrib><creatorcontrib>Löf, Liza</creatorcontrib><creatorcontrib>Larsson, Anders</creatorcontrib><creatorcontrib>Hashemi, Jamileh</creatorcontrib><creatorcontrib>Ulfstedt, Johan Mattsson</creatorcontrib><creatorcontrib>Molin, Daniel</creatorcontrib><creatorcontrib>Amini, Rose-Marie</creatorcontrib><creatorcontrib>Freyhult, Eva</creatorcontrib><creatorcontrib>Kamali-Moghaddam, Masood</creatorcontrib><creatorcontrib>Enblad, Gunilla</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Immunology Abstracts</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>ProQuest research library</collection><collection>ProQuest Biological Science Journals</collection><collection>Research Library (Corporate)</collection><collection>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</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>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>SWEPUB Uppsala universitet full text</collection><collection>SwePub</collection><collection>SwePub Articles</collection><collection>SWEPUB Freely available online</collection><collection>SWEPUB Uppsala universitet</collection><collection>SwePub Articles full text</collection><jtitle>Cancers</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gholiha, Alex Reza</au><au>Hollander, Peter</au><au>Löf, Liza</au><au>Larsson, Anders</au><au>Hashemi, Jamileh</au><au>Ulfstedt, Johan Mattsson</au><au>Molin, Daniel</au><au>Amini, Rose-Marie</au><au>Freyhult, Eva</au><au>Kamali-Moghaddam, Masood</au><au>Enblad, Gunilla</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Immune-Proteome Profiling in Classical Hodgkin Lymphoma Tumor Diagnostic Tissue</atitle><jtitle>Cancers</jtitle><addtitle>Cancers (Basel)</addtitle><date>2022-01-01</date><risdate>2022</risdate><volume>14</volume><issue>1</issue><spage>9</spage><pages>9-</pages><issn>2072-6694</issn><eissn>2072-6694</eissn><abstract>In classical Hodgkin Lymphoma (cHL), immunoediting via protein signaling is key to evading tumor surveillance. We aimed to identify immune-related proteins that distinguish diagnostic cHL tissues (=diagnostic tumor lysates,
= 27) from control tissues (reactive lymph node lysates,
= 30). Further, we correlated our findings with the proteome plasma profile between cHL patients (
= 26) and healthy controls (
= 27). We used the proximity extension assay (PEA) with the OlinkTM multiplex Immuno-Oncology panel, consisting of 92 proteins. Univariate, multivariate-adjusted analysis and Benjamini-Hochberg's false discovery testing (=Padj) were performed to detect significant discrepancies. Proteins distinguishing cHL cases from controls were more numerous in plasma (30 proteins) than tissue (17 proteins), all Padj < 0.05. Eight of the identified proteins in cHL tissue (PD-L1, IL-6, CCL17, CCL3, IL-13, MMP12, TNFRS4, and LAG3) were elevated in both cHL tissues and cHL plasma compared with control samples. Six proteins distinguishing cHL tissues from controls tissues were significantly correlated to PD-L1 expression in cHL tissue (IL-6, MCP-2, CCL3, CCL4, GZMB, and IFN-gamma, all
≤0.05). In conclusion, this study introduces a distinguishing proteomic profile in cHL tissue and potential immune-related markers of pathophysiological relevance.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>35008176</pmid><doi>10.3390/cancers14010009</doi><orcidid>https://orcid.org/0000-0002-0226-5681</orcidid><orcidid>https://orcid.org/0000-0003-3161-0402</orcidid><orcidid>https://orcid.org/0000-0002-3393-1106</orcidid><orcidid>https://orcid.org/0000-0003-0226-1047</orcidid><orcidid>https://orcid.org/0000-0003-0682-7394</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Algorithms Biobanks Biomarkers Biopsy Cancer Cancer immunotherapy CCL17 protein CCL3 protein Epstein-Barr virus Gender Gene expression Hodgkin's lymphoma Interleukin 13 Interleukin 6 Lymph nodes Lymphatic system Lymphoma Lysates Patients PD-L1 protein Plasma Precision medicine Proteins Proteomes Proteomics Regression analysis Therapeutic targets Tumor microenvironment Tumors γ-Interferon |
| title | Immune-Proteome Profiling in Classical Hodgkin Lymphoma Tumor Diagnostic Tissue |
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