Peripheral lymphocyte subset counts predict antibody response after SARS-CoV-2 mRNA-BNT162b2 vaccine in cancer patients: Results from the Vax-On-Profile study
•ROC curve analysis indicated T helper and B cells useful in predicting seroconversion.•T helper and B cells showed positive linear correlation with anti-RBD-S1 IgG titers.•High-level T and B cells resulted in improved antibody or seroconversion response.•Multivariate testing confirmed negative inte...
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| Veröffentlicht in: | International immunopharmacology 2022-07, Vol.108, p.108774-108774, Article 108774 |
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| creator | Nelli, Fabrizio Fabbri, Agnese Panichi, Valentina Giannarelli, Diana Topini, Giuseppe Giron Berrios, Julio R. Virtuoso, Antonella Marrucci, Eleonora Mazzotta, Marco Schirripa, Marta Signorelli, Carlo Chilelli, Mario G. Primi, Francesca Silvestri, Maria A. Ruggeri, Enzo M. |
| description | •ROC curve analysis indicated T helper and B cells useful in predicting seroconversion.•T helper and B cells showed positive linear correlation with anti-RBD-S1 IgG titers.•High-level T and B cells resulted in improved antibody or seroconversion response.•Multivariate testing confirmed negative interaction with low-level T helper and B cell.•Our results may identify high-risk recipients among actively treated cancer patients.
The adaptive immune response following COVID-19 vaccination is essential for humoral immunogenicity and clinical protection against symptomatic infections. We present the results of circulating lymphocyte profiling and their correlation with antibody response in cancer patients tested serologically six months after receiving a two-dose schedule of mRNA-BNT162b2 vaccine.
Absolute counts of lymphocyte subsets were determined using peripheral blood immunophenotyping. We collected samples for flow cytometry analysis alongside quantitative detection of IgG antibodies against the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein (S1). An IgG titer ≥ 50 AU/mL defined a positive seroconversion response.
311 patients were evaluable for lymphocyte profiling and serologic testing. A preliminary multivariate analysis revealed that cytotoxic chemotherapy was the most consistent factor associated with lower counts of all lymphocyte subpopulations. T helper and B cells were found to be useful in predicting the occurrence of a positive seroconversion response using ROC curve analysis. A significant positive linear correlation was shown when anti-RBD-S1 IgG titers were compared to these lymphocyte subset counts. Univariate analysis indicated that antibody titers and seroconversion rates were significantly improved in the high-level T and B cell subgroups. Multivariate analysis confirmed these significant interactions, as well as the negative predictive value of immunosuppressive corticosteroid therapy.
These findings suggest that simple and widely available peripheral counts of T helper and B cells correlate with humoral response to mRNA-BNT162b2 vaccine in actively treated cancer patients. Upon validation, our results could provide additional insights into the predictive assessment of vaccination efficacy. |
| doi_str_mv | 10.1016/j.intimp.2022.108774 |
| format | Article |
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The adaptive immune response following COVID-19 vaccination is essential for humoral immunogenicity and clinical protection against symptomatic infections. We present the results of circulating lymphocyte profiling and their correlation with antibody response in cancer patients tested serologically six months after receiving a two-dose schedule of mRNA-BNT162b2 vaccine.
Absolute counts of lymphocyte subsets were determined using peripheral blood immunophenotyping. We collected samples for flow cytometry analysis alongside quantitative detection of IgG antibodies against the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein (S1). An IgG titer ≥ 50 AU/mL defined a positive seroconversion response.
311 patients were evaluable for lymphocyte profiling and serologic testing. A preliminary multivariate analysis revealed that cytotoxic chemotherapy was the most consistent factor associated with lower counts of all lymphocyte subpopulations. T helper and B cells were found to be useful in predicting the occurrence of a positive seroconversion response using ROC curve analysis. A significant positive linear correlation was shown when anti-RBD-S1 IgG titers were compared to these lymphocyte subset counts. Univariate analysis indicated that antibody titers and seroconversion rates were significantly improved in the high-level T and B cell subgroups. Multivariate analysis confirmed these significant interactions, as well as the negative predictive value of immunosuppressive corticosteroid therapy.
These findings suggest that simple and widely available peripheral counts of T helper and B cells correlate with humoral response to mRNA-BNT162b2 vaccine in actively treated cancer patients. Upon validation, our results could provide additional insights into the predictive assessment of vaccination efficacy.</description><identifier>ISSN: 1567-5769</identifier><identifier>EISSN: 1878-1705</identifier><identifier>DOI: 10.1016/j.intimp.2022.108774</identifier><identifier>PMID: 35461110</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Antibodies, Viral ; Antibody Formation ; Antibody response ; B cell ; BNT162 Vaccine - immunology ; Cancer ; COVID-19 ; COVID-19 - prevention & control ; Humans ; Immunoglobulin G ; Lymphocyte Subsets ; Lymphocytes ; Neoplasms ; SARS-CoV-2 ; SARS-CoV-2 vaccine ; Spike Glycoprotein, Coronavirus ; T helper cell</subject><ispartof>International immunopharmacology, 2022-07, Vol.108, p.108774-108774, Article 108774</ispartof><rights>2022 Elsevier B.V.</rights><rights>Copyright © 2022 Elsevier B.V. All rights reserved.</rights><rights>2022 Elsevier B.V. All rights reserved. 2022 Elsevier B.V.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c463t-fcf2743a44a99f891df8072a583d2172288911c69684e8cd37276fc4019700783</citedby><cites>FETCH-LOGICAL-c463t-fcf2743a44a99f891df8072a583d2172288911c69684e8cd37276fc4019700783</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1567576922002582$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35461110$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Nelli, Fabrizio</creatorcontrib><creatorcontrib>Fabbri, Agnese</creatorcontrib><creatorcontrib>Panichi, Valentina</creatorcontrib><creatorcontrib>Giannarelli, Diana</creatorcontrib><creatorcontrib>Topini, Giuseppe</creatorcontrib><creatorcontrib>Giron Berrios, Julio R.</creatorcontrib><creatorcontrib>Virtuoso, Antonella</creatorcontrib><creatorcontrib>Marrucci, Eleonora</creatorcontrib><creatorcontrib>Mazzotta, Marco</creatorcontrib><creatorcontrib>Schirripa, Marta</creatorcontrib><creatorcontrib>Signorelli, Carlo</creatorcontrib><creatorcontrib>Chilelli, Mario G.</creatorcontrib><creatorcontrib>Primi, Francesca</creatorcontrib><creatorcontrib>Silvestri, Maria A.</creatorcontrib><creatorcontrib>Ruggeri, Enzo M.</creatorcontrib><title>Peripheral lymphocyte subset counts predict antibody response after SARS-CoV-2 mRNA-BNT162b2 vaccine in cancer patients: Results from the Vax-On-Profile study</title><title>International immunopharmacology</title><addtitle>Int Immunopharmacol</addtitle><description>•ROC curve analysis indicated T helper and B cells useful in predicting seroconversion.•T helper and B cells showed positive linear correlation with anti-RBD-S1 IgG titers.•High-level T and B cells resulted in improved antibody or seroconversion response.•Multivariate testing confirmed negative interaction with low-level T helper and B cell.•Our results may identify high-risk recipients among actively treated cancer patients.
The adaptive immune response following COVID-19 vaccination is essential for humoral immunogenicity and clinical protection against symptomatic infections. We present the results of circulating lymphocyte profiling and their correlation with antibody response in cancer patients tested serologically six months after receiving a two-dose schedule of mRNA-BNT162b2 vaccine.
Absolute counts of lymphocyte subsets were determined using peripheral blood immunophenotyping. We collected samples for flow cytometry analysis alongside quantitative detection of IgG antibodies against the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein (S1). An IgG titer ≥ 50 AU/mL defined a positive seroconversion response.
311 patients were evaluable for lymphocyte profiling and serologic testing. A preliminary multivariate analysis revealed that cytotoxic chemotherapy was the most consistent factor associated with lower counts of all lymphocyte subpopulations. T helper and B cells were found to be useful in predicting the occurrence of a positive seroconversion response using ROC curve analysis. A significant positive linear correlation was shown when anti-RBD-S1 IgG titers were compared to these lymphocyte subset counts. Univariate analysis indicated that antibody titers and seroconversion rates were significantly improved in the high-level T and B cell subgroups. Multivariate analysis confirmed these significant interactions, as well as the negative predictive value of immunosuppressive corticosteroid therapy.
These findings suggest that simple and widely available peripheral counts of T helper and B cells correlate with humoral response to mRNA-BNT162b2 vaccine in actively treated cancer patients. Upon validation, our results could provide additional insights into the predictive assessment of vaccination efficacy.</description><subject>Antibodies, Viral</subject><subject>Antibody Formation</subject><subject>Antibody response</subject><subject>B cell</subject><subject>BNT162 Vaccine - immunology</subject><subject>Cancer</subject><subject>COVID-19</subject><subject>COVID-19 - prevention & control</subject><subject>Humans</subject><subject>Immunoglobulin G</subject><subject>Lymphocyte Subsets</subject><subject>Lymphocytes</subject><subject>Neoplasms</subject><subject>SARS-CoV-2</subject><subject>SARS-CoV-2 vaccine</subject><subject>Spike Glycoprotein, Coronavirus</subject><subject>T helper cell</subject><issn>1567-5769</issn><issn>1878-1705</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kd9uFCEUxidGY2v1DYzh0htWYBhgvDBZN_5LmrbZ1t4Sljm4bGaGEZiN-zI-qzRbq954Bfk45_sO51dVLylZUELFm93Cj9kP04IRxoqkpOSPqlOqpMJUkuZxuTdC4kaK9qR6ltKOkKJz-rQ6qRsuKKXktPp5BdFPW4imR_1hmLbBHjKgNG8SZGTDPOaEpgidtxmZErgJ3QFFSFMYEyDjMkR0vVxf41W4xQwN64slfn9xQwXbMLQ31voRkB-RNaMtpZPJHornW7SGNPfF3MUwoLwFdGt-4MsRX8XgfF9GyHN3eF49caZP8OL-PKu-fvxws_qMzy8_fVktz7Hlos7YWcckrw3npm2damnnFJHMNKruGJWMqaJRK1qhOCjb1ZJJ4SwntJWESFWfVe-OvtO8GaCzZcSyET1FP5h40MF4_e_L6Lf6W9jrlhBFmSwGr-8NYvg-Q8p68MlC35sRwpw0Ew1nihRUpZQfS20MKUVwDzGU6Du0eqePaPUdWn1EW9pe_T3iQ9Nvln_-AGVRew9RJ1t2bQu7CDbrLvj_J_wCXL-4RA</recordid><startdate>20220701</startdate><enddate>20220701</enddate><creator>Nelli, Fabrizio</creator><creator>Fabbri, Agnese</creator><creator>Panichi, Valentina</creator><creator>Giannarelli, Diana</creator><creator>Topini, Giuseppe</creator><creator>Giron Berrios, Julio R.</creator><creator>Virtuoso, Antonella</creator><creator>Marrucci, Eleonora</creator><creator>Mazzotta, Marco</creator><creator>Schirripa, Marta</creator><creator>Signorelli, Carlo</creator><creator>Chilelli, Mario G.</creator><creator>Primi, Francesca</creator><creator>Silvestri, Maria A.</creator><creator>Ruggeri, Enzo M.</creator><general>Elsevier 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>7X8</scope><scope>5PM</scope></search><sort><creationdate>20220701</creationdate><title>Peripheral lymphocyte subset counts predict antibody response after SARS-CoV-2 mRNA-BNT162b2 vaccine in cancer patients: Results from the Vax-On-Profile study</title><author>Nelli, Fabrizio ; Fabbri, Agnese ; Panichi, Valentina ; Giannarelli, Diana ; Topini, Giuseppe ; Giron Berrios, Julio R. ; Virtuoso, Antonella ; Marrucci, Eleonora ; Mazzotta, Marco ; Schirripa, Marta ; Signorelli, Carlo ; Chilelli, Mario G. ; Primi, Francesca ; Silvestri, Maria A. ; Ruggeri, Enzo M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c463t-fcf2743a44a99f891df8072a583d2172288911c69684e8cd37276fc4019700783</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Antibodies, Viral</topic><topic>Antibody Formation</topic><topic>Antibody response</topic><topic>B cell</topic><topic>BNT162 Vaccine - immunology</topic><topic>Cancer</topic><topic>COVID-19</topic><topic>COVID-19 - prevention & control</topic><topic>Humans</topic><topic>Immunoglobulin G</topic><topic>Lymphocyte Subsets</topic><topic>Lymphocytes</topic><topic>Neoplasms</topic><topic>SARS-CoV-2</topic><topic>SARS-CoV-2 vaccine</topic><topic>Spike Glycoprotein, Coronavirus</topic><topic>T helper cell</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nelli, Fabrizio</creatorcontrib><creatorcontrib>Fabbri, Agnese</creatorcontrib><creatorcontrib>Panichi, Valentina</creatorcontrib><creatorcontrib>Giannarelli, Diana</creatorcontrib><creatorcontrib>Topini, Giuseppe</creatorcontrib><creatorcontrib>Giron Berrios, Julio R.</creatorcontrib><creatorcontrib>Virtuoso, Antonella</creatorcontrib><creatorcontrib>Marrucci, Eleonora</creatorcontrib><creatorcontrib>Mazzotta, Marco</creatorcontrib><creatorcontrib>Schirripa, Marta</creatorcontrib><creatorcontrib>Signorelli, Carlo</creatorcontrib><creatorcontrib>Chilelli, Mario G.</creatorcontrib><creatorcontrib>Primi, Francesca</creatorcontrib><creatorcontrib>Silvestri, Maria A.</creatorcontrib><creatorcontrib>Ruggeri, Enzo M.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>International immunopharmacology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nelli, Fabrizio</au><au>Fabbri, Agnese</au><au>Panichi, Valentina</au><au>Giannarelli, Diana</au><au>Topini, Giuseppe</au><au>Giron Berrios, Julio R.</au><au>Virtuoso, Antonella</au><au>Marrucci, Eleonora</au><au>Mazzotta, Marco</au><au>Schirripa, Marta</au><au>Signorelli, Carlo</au><au>Chilelli, Mario G.</au><au>Primi, Francesca</au><au>Silvestri, Maria A.</au><au>Ruggeri, Enzo M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Peripheral lymphocyte subset counts predict antibody response after SARS-CoV-2 mRNA-BNT162b2 vaccine in cancer patients: Results from the Vax-On-Profile study</atitle><jtitle>International immunopharmacology</jtitle><addtitle>Int Immunopharmacol</addtitle><date>2022-07-01</date><risdate>2022</risdate><volume>108</volume><spage>108774</spage><epage>108774</epage><pages>108774-108774</pages><artnum>108774</artnum><issn>1567-5769</issn><eissn>1878-1705</eissn><abstract>•ROC curve analysis indicated T helper and B cells useful in predicting seroconversion.•T helper and B cells showed positive linear correlation with anti-RBD-S1 IgG titers.•High-level T and B cells resulted in improved antibody or seroconversion response.•Multivariate testing confirmed negative interaction with low-level T helper and B cell.•Our results may identify high-risk recipients among actively treated cancer patients.
The adaptive immune response following COVID-19 vaccination is essential for humoral immunogenicity and clinical protection against symptomatic infections. We present the results of circulating lymphocyte profiling and their correlation with antibody response in cancer patients tested serologically six months after receiving a two-dose schedule of mRNA-BNT162b2 vaccine.
Absolute counts of lymphocyte subsets were determined using peripheral blood immunophenotyping. We collected samples for flow cytometry analysis alongside quantitative detection of IgG antibodies against the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein (S1). An IgG titer ≥ 50 AU/mL defined a positive seroconversion response.
311 patients were evaluable for lymphocyte profiling and serologic testing. A preliminary multivariate analysis revealed that cytotoxic chemotherapy was the most consistent factor associated with lower counts of all lymphocyte subpopulations. T helper and B cells were found to be useful in predicting the occurrence of a positive seroconversion response using ROC curve analysis. A significant positive linear correlation was shown when anti-RBD-S1 IgG titers were compared to these lymphocyte subset counts. Univariate analysis indicated that antibody titers and seroconversion rates were significantly improved in the high-level T and B cell subgroups. Multivariate analysis confirmed these significant interactions, as well as the negative predictive value of immunosuppressive corticosteroid therapy.
These findings suggest that simple and widely available peripheral counts of T helper and B cells correlate with humoral response to mRNA-BNT162b2 vaccine in actively treated cancer patients. Upon validation, our results could provide additional insights into the predictive assessment of vaccination efficacy.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>35461110</pmid><doi>10.1016/j.intimp.2022.108774</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | International immunopharmacology, 2022-07, Vol.108, p.108774-108774, Article 108774 |
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| source | MEDLINE; Elsevier ScienceDirect Journals |
| subjects | Antibodies, Viral Antibody Formation Antibody response B cell BNT162 Vaccine - immunology Cancer COVID-19 COVID-19 - prevention & control Humans Immunoglobulin G Lymphocyte Subsets Lymphocytes Neoplasms SARS-CoV-2 SARS-CoV-2 vaccine Spike Glycoprotein, Coronavirus T helper cell |
| title | Peripheral lymphocyte subset counts predict antibody response after SARS-CoV-2 mRNA-BNT162b2 vaccine in cancer patients: Results from the Vax-On-Profile study |
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