ITGB2 as a prognostic indicator and a predictive marker for immunotherapy in gliomas
Purpose Glioma is the most common primary tumor in the brain, accounting for 81% of intracranial malignancies. Nowadays, cancer immunotherapy has become a novel and revolutionary treatment for patients with advanced, highly aggressive tumors. However, to date, there are no effective biomarkers to re...
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| Veröffentlicht in: | Cancer Immunology, Immunotherapy Immunotherapy, 2022-03, Vol.71 (3), p.645-660 |
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| creator | Xu, Houshi Zhang, Anke Han, Xiaying Li, Yanning Zhang, Zeyu Song, Liying Wang, Wei Lou, Meiqing |
| description | Purpose
Glioma is the most common primary tumor in the brain, accounting for 81% of intracranial malignancies. Nowadays, cancer immunotherapy has become a novel and revolutionary treatment for patients with advanced, highly aggressive tumors. However, to date, there are no effective biomarkers to reflect the response of glioma patients to immunotherapy. In this study, we aimed to assess the clinical predictive value of ITGB2 in patients with glioma.
Methods
The correlation between ITGB2 expression levels and glioma progression was explored and validated using data from CGGA, TCGA, GEO datasets, and patient samples from our hospital. Univariate and multivariate cox regression models were developed to determine the predictive role of ITGB2 on the prognosis of patients with glioma. The relationship between ITGB2 and immune activation was then analyzed. Finally, we predicted the immunotherapy response in both high and low ITGB2 expression subgroups.
Results
ITGB2 was significantly elevated in gliomas with higher malignancy and predicted poor prognosis. In multivariate analysis, the hazard ratio for ITGB2 expression (low versus high) was 0.71 with 95% CI (0.59–0.85) (
P |
| doi_str_mv | 10.1007/s00262-021-03022-2 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10992927</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2629521860</sourcerecordid><originalsourceid>FETCH-LOGICAL-c431t-f59a294b79bec67210414be6b4fc3c940d1b98037186e8cd73f8c5d1117fd7403</originalsourceid><addsrcrecordid>eNp9UcFu1TAQtBCIPgo_wAFF4sIlZb124viEoIJSqRKXx9lyHOfVJbEfdlKpf8-2rxTKgZOtndnZ2R3GXnM44QDqfQHAFmtAXoMAxBqfsA2Xgkpdw5-yDQgJtQKQR-xFKVf0QdD6OTsSUnDRId-w7fn27BNWtlS22ue0i6kswVUhDsHZJeXKxuEO8lRYwrWvZpt_-FyNhIV5XmNaLn22-xvqqXZTSLMtL9mz0U7Fv7p_j9n3L5-3p1_ri29n56cfL2pH85d6bLRFLXule-9ahRwkl71vezk64bSEgfe6A6F41_rODUqMnWsGzrkaByVBHLMPB9392s9-cD4u2U5mnwOZvDHJBvMYieHS7NK14XQG1KhI4d29Qk4_V18WM4fi_DTZ6NNaDDZN04pOyoaob_-hXqU1R9rPUAq6QXJ5awkPLJdTKdmPD244mNvUzCE1Q6mZu9QMUtObv_d4aPkdExHEgVAIijuf_8z-j-wv_Fyh8w</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2629521860</pqid></control><display><type>article</type><title>ITGB2 as a prognostic indicator and a predictive marker for immunotherapy in gliomas</title><source>MEDLINE</source><source>SpringerNature Journals</source><source>PubMed Central</source><creator>Xu, Houshi ; Zhang, Anke ; Han, Xiaying ; Li, Yanning ; Zhang, Zeyu ; Song, Liying ; Wang, Wei ; Lou, Meiqing</creator><creatorcontrib>Xu, Houshi ; Zhang, Anke ; Han, Xiaying ; Li, Yanning ; Zhang, Zeyu ; Song, Liying ; Wang, Wei ; Lou, Meiqing</creatorcontrib><description>Purpose
Glioma is the most common primary tumor in the brain, accounting for 81% of intracranial malignancies. Nowadays, cancer immunotherapy has become a novel and revolutionary treatment for patients with advanced, highly aggressive tumors. However, to date, there are no effective biomarkers to reflect the response of glioma patients to immunotherapy. In this study, we aimed to assess the clinical predictive value of ITGB2 in patients with glioma.
Methods
The correlation between ITGB2 expression levels and glioma progression was explored and validated using data from CGGA, TCGA, GEO datasets, and patient samples from our hospital. Univariate and multivariate cox regression models were developed to determine the predictive role of ITGB2 on the prognosis of patients with glioma. The relationship between ITGB2 and immune activation was then analyzed. Finally, we predicted the immunotherapy response in both high and low ITGB2 expression subgroups.
Results
ITGB2 was significantly elevated in gliomas with higher malignancy and predicted poor prognosis. In multivariate analysis, the hazard ratio for ITGB2 expression (low versus high) was 0.71 with 95% CI (0.59–0.85) (
P
< 0.001). Furthermore, we found that ITGB2 stratified glioma patients into high and low ITGB2 expression subgroups, exhibiting different clinical outcomes and immune activation status. At last, we demonstrated that glioma patients with high ITGB2 expression levels had better immunotherapy response.
Conclusions
This study demonstrated ITGB2 as a novel predictor for clinical prognosis and response to immunotherapy in gliomas. Assessing expression levels of ITGB2 is a promising method to discover patients that may benefit from immunotherapy.</description><identifier>ISSN: 0340-7004</identifier><identifier>EISSN: 1432-0851</identifier><identifier>DOI: 10.1007/s00262-021-03022-2</identifier><identifier>PMID: 34313821</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Biomarkers, Tumor ; Brain Neoplasms - etiology ; Brain Neoplasms - metabolism ; Brain Neoplasms - mortality ; Brain Neoplasms - therapy ; Brain tumors ; Cancer immunotherapy ; Cancer Research ; Computational Biology - methods ; Databases, Genetic ; Disease Progression ; Gene Expression Profiling ; Glioma ; Glioma - diagnosis ; Glioma - metabolism ; Glioma - mortality ; Glioma - therapy ; Humans ; Immune response ; Immunology ; Immunotherapy ; Integrin beta1 - genetics ; Integrin beta1 - metabolism ; Lymphocytes, Tumor-Infiltrating - immunology ; Lymphocytes, Tumor-Infiltrating - metabolism ; Malignancy ; Medicine ; Medicine & Public Health ; Multivariate analysis ; Neoplasm Grading ; Neoplasm Metastasis ; Neoplasm Staging ; Oncology ; Original ; Original Article ; Patients ; Prognosis ; Proportional Hazards Models ; Regression analysis ; Transcriptome ; Tumor Microenvironment - genetics ; Tumor Microenvironment - immunology ; Tumor-Associated Macrophages - immunology ; Tumor-Associated Macrophages - metabolism</subject><ispartof>Cancer Immunology, Immunotherapy, 2022-03, Vol.71 (3), p.645-660</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021</rights><rights>2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.</rights><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c431t-f59a294b79bec67210414be6b4fc3c940d1b98037186e8cd73f8c5d1117fd7403</citedby><cites>FETCH-LOGICAL-c431t-f59a294b79bec67210414be6b4fc3c940d1b98037186e8cd73f8c5d1117fd7403</cites><orcidid>0000-0001-6427-5503</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/PMC10992927/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10992927/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,41488,42557,51319,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34313821$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Xu, Houshi</creatorcontrib><creatorcontrib>Zhang, Anke</creatorcontrib><creatorcontrib>Han, Xiaying</creatorcontrib><creatorcontrib>Li, Yanning</creatorcontrib><creatorcontrib>Zhang, Zeyu</creatorcontrib><creatorcontrib>Song, Liying</creatorcontrib><creatorcontrib>Wang, Wei</creatorcontrib><creatorcontrib>Lou, Meiqing</creatorcontrib><title>ITGB2 as a prognostic indicator and a predictive marker for immunotherapy in gliomas</title><title>Cancer Immunology, Immunotherapy</title><addtitle>Cancer Immunol Immunother</addtitle><addtitle>Cancer Immunol Immunother</addtitle><description>Purpose
Glioma is the most common primary tumor in the brain, accounting for 81% of intracranial malignancies. Nowadays, cancer immunotherapy has become a novel and revolutionary treatment for patients with advanced, highly aggressive tumors. However, to date, there are no effective biomarkers to reflect the response of glioma patients to immunotherapy. In this study, we aimed to assess the clinical predictive value of ITGB2 in patients with glioma.
Methods
The correlation between ITGB2 expression levels and glioma progression was explored and validated using data from CGGA, TCGA, GEO datasets, and patient samples from our hospital. Univariate and multivariate cox regression models were developed to determine the predictive role of ITGB2 on the prognosis of patients with glioma. The relationship between ITGB2 and immune activation was then analyzed. Finally, we predicted the immunotherapy response in both high and low ITGB2 expression subgroups.
Results
ITGB2 was significantly elevated in gliomas with higher malignancy and predicted poor prognosis. In multivariate analysis, the hazard ratio for ITGB2 expression (low versus high) was 0.71 with 95% CI (0.59–0.85) (
P
< 0.001). Furthermore, we found that ITGB2 stratified glioma patients into high and low ITGB2 expression subgroups, exhibiting different clinical outcomes and immune activation status. At last, we demonstrated that glioma patients with high ITGB2 expression levels had better immunotherapy response.
Conclusions
This study demonstrated ITGB2 as a novel predictor for clinical prognosis and response to immunotherapy in gliomas. Assessing expression levels of ITGB2 is a promising method to discover patients that may benefit from immunotherapy.</description><subject>Biomarkers, Tumor</subject><subject>Brain Neoplasms - etiology</subject><subject>Brain Neoplasms - metabolism</subject><subject>Brain Neoplasms - mortality</subject><subject>Brain Neoplasms - therapy</subject><subject>Brain tumors</subject><subject>Cancer immunotherapy</subject><subject>Cancer Research</subject><subject>Computational Biology - methods</subject><subject>Databases, Genetic</subject><subject>Disease Progression</subject><subject>Gene Expression Profiling</subject><subject>Glioma</subject><subject>Glioma - diagnosis</subject><subject>Glioma - metabolism</subject><subject>Glioma - mortality</subject><subject>Glioma - therapy</subject><subject>Humans</subject><subject>Immune response</subject><subject>Immunology</subject><subject>Immunotherapy</subject><subject>Integrin beta1 - genetics</subject><subject>Integrin beta1 - metabolism</subject><subject>Lymphocytes, Tumor-Infiltrating - immunology</subject><subject>Lymphocytes, Tumor-Infiltrating - metabolism</subject><subject>Malignancy</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Multivariate analysis</subject><subject>Neoplasm Grading</subject><subject>Neoplasm Metastasis</subject><subject>Neoplasm Staging</subject><subject>Oncology</subject><subject>Original</subject><subject>Original Article</subject><subject>Patients</subject><subject>Prognosis</subject><subject>Proportional Hazards Models</subject><subject>Regression analysis</subject><subject>Transcriptome</subject><subject>Tumor Microenvironment - genetics</subject><subject>Tumor Microenvironment - immunology</subject><subject>Tumor-Associated Macrophages - immunology</subject><subject>Tumor-Associated Macrophages - metabolism</subject><issn>0340-7004</issn><issn>1432-0851</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9UcFu1TAQtBCIPgo_wAFF4sIlZb124viEoIJSqRKXx9lyHOfVJbEfdlKpf8-2rxTKgZOtndnZ2R3GXnM44QDqfQHAFmtAXoMAxBqfsA2Xgkpdw5-yDQgJtQKQR-xFKVf0QdD6OTsSUnDRId-w7fn27BNWtlS22ue0i6kswVUhDsHZJeXKxuEO8lRYwrWvZpt_-FyNhIV5XmNaLn22-xvqqXZTSLMtL9mz0U7Fv7p_j9n3L5-3p1_ri29n56cfL2pH85d6bLRFLXule-9ahRwkl71vezk64bSEgfe6A6F41_rODUqMnWsGzrkaByVBHLMPB9392s9-cD4u2U5mnwOZvDHJBvMYieHS7NK14XQG1KhI4d29Qk4_V18WM4fi_DTZ6NNaDDZN04pOyoaob_-hXqU1R9rPUAq6QXJ5awkPLJdTKdmPD244mNvUzCE1Q6mZu9QMUtObv_d4aPkdExHEgVAIijuf_8z-j-wv_Fyh8w</recordid><startdate>20220301</startdate><enddate>20220301</enddate><creator>Xu, Houshi</creator><creator>Zhang, Anke</creator><creator>Han, Xiaying</creator><creator>Li, Yanning</creator><creator>Zhang, Zeyu</creator><creator>Song, Liying</creator><creator>Wang, Wei</creator><creator>Lou, Meiqing</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T5</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</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>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-6427-5503</orcidid></search><sort><creationdate>20220301</creationdate><title>ITGB2 as a prognostic indicator and a predictive marker for immunotherapy in gliomas</title><author>Xu, Houshi ; Zhang, Anke ; Han, Xiaying ; Li, Yanning ; Zhang, Zeyu ; Song, Liying ; Wang, Wei ; Lou, Meiqing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c431t-f59a294b79bec67210414be6b4fc3c940d1b98037186e8cd73f8c5d1117fd7403</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Biomarkers, Tumor</topic><topic>Brain Neoplasms - etiology</topic><topic>Brain Neoplasms - metabolism</topic><topic>Brain Neoplasms - mortality</topic><topic>Brain Neoplasms - therapy</topic><topic>Brain tumors</topic><topic>Cancer immunotherapy</topic><topic>Cancer Research</topic><topic>Computational Biology - methods</topic><topic>Databases, Genetic</topic><topic>Disease Progression</topic><topic>Gene Expression Profiling</topic><topic>Glioma</topic><topic>Glioma - diagnosis</topic><topic>Glioma - metabolism</topic><topic>Glioma - mortality</topic><topic>Glioma - therapy</topic><topic>Humans</topic><topic>Immune response</topic><topic>Immunology</topic><topic>Immunotherapy</topic><topic>Integrin beta1 - genetics</topic><topic>Integrin beta1 - metabolism</topic><topic>Lymphocytes, Tumor-Infiltrating - immunology</topic><topic>Lymphocytes, Tumor-Infiltrating - metabolism</topic><topic>Malignancy</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Multivariate analysis</topic><topic>Neoplasm Grading</topic><topic>Neoplasm Metastasis</topic><topic>Neoplasm Staging</topic><topic>Oncology</topic><topic>Original</topic><topic>Original Article</topic><topic>Patients</topic><topic>Prognosis</topic><topic>Proportional Hazards Models</topic><topic>Regression analysis</topic><topic>Transcriptome</topic><topic>Tumor Microenvironment - genetics</topic><topic>Tumor Microenvironment - immunology</topic><topic>Tumor-Associated Macrophages - immunology</topic><topic>Tumor-Associated Macrophages - metabolism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xu, Houshi</creatorcontrib><creatorcontrib>Zhang, Anke</creatorcontrib><creatorcontrib>Han, Xiaying</creatorcontrib><creatorcontrib>Li, Yanning</creatorcontrib><creatorcontrib>Zhang, Zeyu</creatorcontrib><creatorcontrib>Song, Liying</creatorcontrib><creatorcontrib>Wang, Wei</creatorcontrib><creatorcontrib>Lou, Meiqing</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Immunology Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science 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>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Cancer Immunology, Immunotherapy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xu, Houshi</au><au>Zhang, Anke</au><au>Han, Xiaying</au><au>Li, Yanning</au><au>Zhang, Zeyu</au><au>Song, Liying</au><au>Wang, Wei</au><au>Lou, Meiqing</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>ITGB2 as a prognostic indicator and a predictive marker for immunotherapy in gliomas</atitle><jtitle>Cancer Immunology, Immunotherapy</jtitle><stitle>Cancer Immunol Immunother</stitle><addtitle>Cancer Immunol Immunother</addtitle><date>2022-03-01</date><risdate>2022</risdate><volume>71</volume><issue>3</issue><spage>645</spage><epage>660</epage><pages>645-660</pages><issn>0340-7004</issn><eissn>1432-0851</eissn><abstract>Purpose
Glioma is the most common primary tumor in the brain, accounting for 81% of intracranial malignancies. Nowadays, cancer immunotherapy has become a novel and revolutionary treatment for patients with advanced, highly aggressive tumors. However, to date, there are no effective biomarkers to reflect the response of glioma patients to immunotherapy. In this study, we aimed to assess the clinical predictive value of ITGB2 in patients with glioma.
Methods
The correlation between ITGB2 expression levels and glioma progression was explored and validated using data from CGGA, TCGA, GEO datasets, and patient samples from our hospital. Univariate and multivariate cox regression models were developed to determine the predictive role of ITGB2 on the prognosis of patients with glioma. The relationship between ITGB2 and immune activation was then analyzed. Finally, we predicted the immunotherapy response in both high and low ITGB2 expression subgroups.
Results
ITGB2 was significantly elevated in gliomas with higher malignancy and predicted poor prognosis. In multivariate analysis, the hazard ratio for ITGB2 expression (low versus high) was 0.71 with 95% CI (0.59–0.85) (
P
< 0.001). Furthermore, we found that ITGB2 stratified glioma patients into high and low ITGB2 expression subgroups, exhibiting different clinical outcomes and immune activation status. At last, we demonstrated that glioma patients with high ITGB2 expression levels had better immunotherapy response.
Conclusions
This study demonstrated ITGB2 as a novel predictor for clinical prognosis and response to immunotherapy in gliomas. Assessing expression levels of ITGB2 is a promising method to discover patients that may benefit from immunotherapy.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>34313821</pmid><doi>10.1007/s00262-021-03022-2</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0001-6427-5503</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Biomarkers, Tumor Brain Neoplasms - etiology Brain Neoplasms - metabolism Brain Neoplasms - mortality Brain Neoplasms - therapy Brain tumors Cancer immunotherapy Cancer Research Computational Biology - methods Databases, Genetic Disease Progression Gene Expression Profiling Glioma Glioma - diagnosis Glioma - metabolism Glioma - mortality Glioma - therapy Humans Immune response Immunology Immunotherapy Integrin beta1 - genetics Integrin beta1 - metabolism Lymphocytes, Tumor-Infiltrating - immunology Lymphocytes, Tumor-Infiltrating - metabolism Malignancy Medicine Medicine & Public Health Multivariate analysis Neoplasm Grading Neoplasm Metastasis Neoplasm Staging Oncology Original Original Article Patients Prognosis Proportional Hazards Models Regression analysis Transcriptome Tumor Microenvironment - genetics Tumor Microenvironment - immunology Tumor-Associated Macrophages - immunology Tumor-Associated Macrophages - metabolism |
| title | ITGB2 as a prognostic indicator and a predictive marker for immunotherapy in gliomas |
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