Blood-Based Biomarker Analysis for Predicting Efficacy of Chemoradiotherapy and Durvalumab in Patients with Unresectable Stage III Non-Small Cell Lung Cancer
We recruited 50 patients with unresectable stage III NSCLC who received CCRT between March 2020 and March 2021. Durvalumab consolidation (DC) was administered to patients ( = 23) without progression after CCRT and programmed death-ligand 1 (PD-L1) ≥ 1%. Blood samples were collected before (C0) and a...
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| Veröffentlicht in: | Cancers 2023-02, Vol.15 (4), p.1151 |
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| description | We recruited 50 patients with unresectable stage III NSCLC who received CCRT between March 2020 and March 2021. Durvalumab consolidation (DC) was administered to patients (
= 23) without progression after CCRT and programmed death-ligand 1 (PD-L1) ≥ 1%. Blood samples were collected before (C0) and after CCRT (C1) to calculate PBC counts and analyze CTCs. CTCs, isolated by the CD-PRIME
system, exhibited EpCAM/CK+/CD45- phenotype in BioViewCCBS
. At median follow-up of 27.4 months, patients with residual CTC clusters at C1 had worse median PFS than those without a detectable CTC cluster (11.0 vs. 27.8 months,
= 0.032), and this trend was noted only in the DC group (
= 0.034). Patients with high platelets at C1 (PLT
, >252 × 10
/µL) had worse median PFS than those with low platelets (PLT
) (5.9 vs. 17.1 months,
< 0.001). In multivariable analysis, PLT
and residual CTC clusters at C1 were independent risk factors for PFS, and DC group with PLT
and residual CTC clusters at C1 showed the worst median PFS (2.6 months, HR 45.16,
= 0.001), even worse than that of the CCRT alone group with PLT
(5.9 months, HR 15.39,
= 0.001). The comprehensive analysis of CTCs and PBCs before and after CCRT revealed that the clearance of CTC clusters and platelet counts at C1 might be potential biomarkers for predicting survival. |
| doi_str_mv | 10.3390/cancers15041151 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9953836</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A743010267</galeid><sourcerecordid>A743010267</sourcerecordid><originalsourceid>FETCH-LOGICAL-c488t-cf76d8efa8a2a56aeb2e7e6b2b8f23c267909829517fb2a5d3940b5d599cfd503</originalsourceid><addsrcrecordid>eNptkl1vFCEUhidGY5vaa-8MiTfeTAvDfHFjsrvWuslGm9RekzNw2KXOwAozNftj_K9lba1tIyRA4Dnv4T05WfaW0RPOBT1V4BSGyCpaMlaxF9lhQZsir2tRvnx0PsiOY7ymaXDOmrp5nR3wuuWsFOVh9nvee6_zOUTUZG79AOEHBjJz0O-ijcT4QC4CaqtG69bkzBirQO2IN2SxwcEH0NaPGwyw3RFwmnyawg300wAdsY5cwGjRjZH8suOGXLmAEdUIXY_kcoQ1kuVySb56l18O0PdkgWlZTSnR4o-3N9krA33E4_v9KLv6fPZ98SVffTtfLmarXJVtO-bKNLVu0UALBVQ1YFdgg3VXdK0puCrqRlDRFqJijekSobkoaVfpSghldEX5UfbxTnc7dQNqlb4coJfbYFM9dtKDlU9fnN3Itb-RQlS85XUS-HAvEPzPCeMoBxtVcgMO_RRl0bSUNowzkdD3z9BrP4VU7z3ViLKijFb_qDX0KK0zPuVVe1E5a0qemOQqUSf_odLUOFjlHRqb7p8EnN4FqOBjDGgePDIq900lnzVVinj3uDQP_N8W4rfWUsn7</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2779450105</pqid></control><display><type>article</type><title>Blood-Based Biomarker Analysis for Predicting Efficacy of Chemoradiotherapy and Durvalumab in Patients with Unresectable Stage III Non-Small Cell Lung Cancer</title><source>PubMed Central Open Access</source><source>MDPI - Multidisciplinary Digital Publishing Institute</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><creator>Park, Cheol-Kyu ; Lee, Sung-Woo ; Cho, Hyun-Ju ; Oh, Hyung-Joo ; Kim, Young-Chul ; Kim, Yong-Hyub ; Ahn, Sung-Ja ; Cho, Jae-Ho ; Oh, In-Jae</creator><creatorcontrib>Park, Cheol-Kyu ; Lee, Sung-Woo ; Cho, Hyun-Ju ; Oh, Hyung-Joo ; Kim, Young-Chul ; Kim, Yong-Hyub ; Ahn, Sung-Ja ; Cho, Jae-Ho ; Oh, In-Jae</creatorcontrib><description>We recruited 50 patients with unresectable stage III NSCLC who received CCRT between March 2020 and March 2021. Durvalumab consolidation (DC) was administered to patients (
= 23) without progression after CCRT and programmed death-ligand 1 (PD-L1) ≥ 1%. Blood samples were collected before (C0) and after CCRT (C1) to calculate PBC counts and analyze CTCs. CTCs, isolated by the CD-PRIME
system, exhibited EpCAM/CK+/CD45- phenotype in BioViewCCBS
. At median follow-up of 27.4 months, patients with residual CTC clusters at C1 had worse median PFS than those without a detectable CTC cluster (11.0 vs. 27.8 months,
= 0.032), and this trend was noted only in the DC group (
= 0.034). Patients with high platelets at C1 (PLT
, >252 × 10
/µL) had worse median PFS than those with low platelets (PLT
) (5.9 vs. 17.1 months,
< 0.001). In multivariable analysis, PLT
and residual CTC clusters at C1 were independent risk factors for PFS, and DC group with PLT
and residual CTC clusters at C1 showed the worst median PFS (2.6 months, HR 45.16,
= 0.001), even worse than that of the CCRT alone group with PLT
(5.9 months, HR 15.39,
= 0.001). The comprehensive analysis of CTCs and PBCs before and after CCRT revealed that the clearance of CTC clusters and platelet counts at C1 might be potential biomarkers for predicting survival.</description><identifier>ISSN: 2072-6694</identifier><identifier>EISSN: 2072-6694</identifier><identifier>DOI: 10.3390/cancers15041151</identifier><identifier>PMID: 36831494</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Apoptosis ; Biological markers ; Biomarkers ; Biopsy ; Blood ; Blood cells ; Blood platelets ; Blood tests ; Cancer ; Cancer therapies ; Care and treatment ; CD45 antigen ; Chemoradiotherapy ; Chemotherapy ; Diagnosis ; Feasibility studies ; Health aspects ; Lung cancer ; Lung cancer, Non-small cell ; Lymphocytes ; Medical imaging ; Medical prognosis ; Mutation ; Neutrophils ; Non-small cell lung carcinoma ; Patient outcomes ; Patients ; PD-L1 protein ; Peripheral blood ; Phenotypes ; Platelets ; Radiation ; Radiotherapy ; Risk factors ; Small cell lung carcinoma ; Tumor cells</subject><ispartof>Cancers, 2023-02, Vol.15 (4), p.1151</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 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>2023 by the authors. 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c488t-cf76d8efa8a2a56aeb2e7e6b2b8f23c267909829517fb2a5d3940b5d599cfd503</citedby><cites>FETCH-LOGICAL-c488t-cf76d8efa8a2a56aeb2e7e6b2b8f23c267909829517fb2a5d3940b5d599cfd503</cites><orcidid>0000-0003-4837-1321 ; 0000-0002-3066-2617 ; 0000-0002-9420-9096</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/PMC9953836/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9953836/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36831494$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Park, Cheol-Kyu</creatorcontrib><creatorcontrib>Lee, Sung-Woo</creatorcontrib><creatorcontrib>Cho, Hyun-Ju</creatorcontrib><creatorcontrib>Oh, Hyung-Joo</creatorcontrib><creatorcontrib>Kim, Young-Chul</creatorcontrib><creatorcontrib>Kim, Yong-Hyub</creatorcontrib><creatorcontrib>Ahn, Sung-Ja</creatorcontrib><creatorcontrib>Cho, Jae-Ho</creatorcontrib><creatorcontrib>Oh, In-Jae</creatorcontrib><title>Blood-Based Biomarker Analysis for Predicting Efficacy of Chemoradiotherapy and Durvalumab in Patients with Unresectable Stage III Non-Small Cell Lung Cancer</title><title>Cancers</title><addtitle>Cancers (Basel)</addtitle><description>We recruited 50 patients with unresectable stage III NSCLC who received CCRT between March 2020 and March 2021. Durvalumab consolidation (DC) was administered to patients (
= 23) without progression after CCRT and programmed death-ligand 1 (PD-L1) ≥ 1%. Blood samples were collected before (C0) and after CCRT (C1) to calculate PBC counts and analyze CTCs. CTCs, isolated by the CD-PRIME
system, exhibited EpCAM/CK+/CD45- phenotype in BioViewCCBS
. At median follow-up of 27.4 months, patients with residual CTC clusters at C1 had worse median PFS than those without a detectable CTC cluster (11.0 vs. 27.8 months,
= 0.032), and this trend was noted only in the DC group (
= 0.034). Patients with high platelets at C1 (PLT
, >252 × 10
/µL) had worse median PFS than those with low platelets (PLT
) (5.9 vs. 17.1 months,
< 0.001). In multivariable analysis, PLT
and residual CTC clusters at C1 were independent risk factors for PFS, and DC group with PLT
and residual CTC clusters at C1 showed the worst median PFS (2.6 months, HR 45.16,
= 0.001), even worse than that of the CCRT alone group with PLT
(5.9 months, HR 15.39,
= 0.001). The comprehensive analysis of CTCs and PBCs before and after CCRT revealed that the clearance of CTC clusters and platelet counts at C1 might be potential biomarkers for predicting survival.</description><subject>Apoptosis</subject><subject>Biological markers</subject><subject>Biomarkers</subject><subject>Biopsy</subject><subject>Blood</subject><subject>Blood cells</subject><subject>Blood platelets</subject><subject>Blood tests</subject><subject>Cancer</subject><subject>Cancer therapies</subject><subject>Care and treatment</subject><subject>CD45 antigen</subject><subject>Chemoradiotherapy</subject><subject>Chemotherapy</subject><subject>Diagnosis</subject><subject>Feasibility studies</subject><subject>Health aspects</subject><subject>Lung cancer</subject><subject>Lung cancer, Non-small cell</subject><subject>Lymphocytes</subject><subject>Medical imaging</subject><subject>Medical prognosis</subject><subject>Mutation</subject><subject>Neutrophils</subject><subject>Non-small cell lung carcinoma</subject><subject>Patient outcomes</subject><subject>Patients</subject><subject>PD-L1 protein</subject><subject>Peripheral blood</subject><subject>Phenotypes</subject><subject>Platelets</subject><subject>Radiation</subject><subject>Radiotherapy</subject><subject>Risk factors</subject><subject>Small cell lung carcinoma</subject><subject>Tumor cells</subject><issn>2072-6694</issn><issn>2072-6694</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNptkl1vFCEUhidGY5vaa-8MiTfeTAvDfHFjsrvWuslGm9RekzNw2KXOwAozNftj_K9lba1tIyRA4Dnv4T05WfaW0RPOBT1V4BSGyCpaMlaxF9lhQZsir2tRvnx0PsiOY7ymaXDOmrp5nR3wuuWsFOVh9nvee6_zOUTUZG79AOEHBjJz0O-ijcT4QC4CaqtG69bkzBirQO2IN2SxwcEH0NaPGwyw3RFwmnyawg300wAdsY5cwGjRjZH8suOGXLmAEdUIXY_kcoQ1kuVySb56l18O0PdkgWlZTSnR4o-3N9krA33E4_v9KLv6fPZ98SVffTtfLmarXJVtO-bKNLVu0UALBVQ1YFdgg3VXdK0puCrqRlDRFqJijekSobkoaVfpSghldEX5UfbxTnc7dQNqlb4coJfbYFM9dtKDlU9fnN3Itb-RQlS85XUS-HAvEPzPCeMoBxtVcgMO_RRl0bSUNowzkdD3z9BrP4VU7z3ViLKijFb_qDX0KK0zPuVVe1E5a0qemOQqUSf_odLUOFjlHRqb7p8EnN4FqOBjDGgePDIq900lnzVVinj3uDQP_N8W4rfWUsn7</recordid><startdate>20230210</startdate><enddate>20230210</enddate><creator>Park, Cheol-Kyu</creator><creator>Lee, Sung-Woo</creator><creator>Cho, Hyun-Ju</creator><creator>Oh, Hyung-Joo</creator><creator>Kim, Young-Chul</creator><creator>Kim, Yong-Hyub</creator><creator>Ahn, Sung-Ja</creator><creator>Cho, Jae-Ho</creator><creator>Oh, In-Jae</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><orcidid>https://orcid.org/0000-0003-4837-1321</orcidid><orcidid>https://orcid.org/0000-0002-3066-2617</orcidid><orcidid>https://orcid.org/0000-0002-9420-9096</orcidid></search><sort><creationdate>20230210</creationdate><title>Blood-Based Biomarker Analysis for Predicting Efficacy of Chemoradiotherapy and Durvalumab in Patients with Unresectable Stage III Non-Small Cell Lung Cancer</title><author>Park, Cheol-Kyu ; Lee, Sung-Woo ; Cho, Hyun-Ju ; Oh, Hyung-Joo ; Kim, Young-Chul ; Kim, Yong-Hyub ; Ahn, Sung-Ja ; Cho, Jae-Ho ; Oh, In-Jae</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c488t-cf76d8efa8a2a56aeb2e7e6b2b8f23c267909829517fb2a5d3940b5d599cfd503</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Apoptosis</topic><topic>Biological markers</topic><topic>Biomarkers</topic><topic>Biopsy</topic><topic>Blood</topic><topic>Blood cells</topic><topic>Blood platelets</topic><topic>Blood tests</topic><topic>Cancer</topic><topic>Cancer therapies</topic><topic>Care and treatment</topic><topic>CD45 antigen</topic><topic>Chemoradiotherapy</topic><topic>Chemotherapy</topic><topic>Diagnosis</topic><topic>Feasibility studies</topic><topic>Health aspects</topic><topic>Lung cancer</topic><topic>Lung cancer, Non-small cell</topic><topic>Lymphocytes</topic><topic>Medical imaging</topic><topic>Medical prognosis</topic><topic>Mutation</topic><topic>Neutrophils</topic><topic>Non-small cell lung carcinoma</topic><topic>Patient outcomes</topic><topic>Patients</topic><topic>PD-L1 protein</topic><topic>Peripheral blood</topic><topic>Phenotypes</topic><topic>Platelets</topic><topic>Radiation</topic><topic>Radiotherapy</topic><topic>Risk factors</topic><topic>Small cell lung carcinoma</topic><topic>Tumor cells</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Park, Cheol-Kyu</creatorcontrib><creatorcontrib>Lee, Sung-Woo</creatorcontrib><creatorcontrib>Cho, Hyun-Ju</creatorcontrib><creatorcontrib>Oh, Hyung-Joo</creatorcontrib><creatorcontrib>Kim, Young-Chul</creatorcontrib><creatorcontrib>Kim, Yong-Hyub</creatorcontrib><creatorcontrib>Ahn, Sung-Ja</creatorcontrib><creatorcontrib>Cho, Jae-Ho</creatorcontrib><creatorcontrib>Oh, In-Jae</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 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>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>Research Library</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>Publicly Available Content 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>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Cancers</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Park, Cheol-Kyu</au><au>Lee, Sung-Woo</au><au>Cho, Hyun-Ju</au><au>Oh, Hyung-Joo</au><au>Kim, Young-Chul</au><au>Kim, Yong-Hyub</au><au>Ahn, Sung-Ja</au><au>Cho, Jae-Ho</au><au>Oh, In-Jae</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Blood-Based Biomarker Analysis for Predicting Efficacy of Chemoradiotherapy and Durvalumab in Patients with Unresectable Stage III Non-Small Cell Lung Cancer</atitle><jtitle>Cancers</jtitle><addtitle>Cancers (Basel)</addtitle><date>2023-02-10</date><risdate>2023</risdate><volume>15</volume><issue>4</issue><spage>1151</spage><pages>1151-</pages><issn>2072-6694</issn><eissn>2072-6694</eissn><abstract>We recruited 50 patients with unresectable stage III NSCLC who received CCRT between March 2020 and March 2021. Durvalumab consolidation (DC) was administered to patients (
= 23) without progression after CCRT and programmed death-ligand 1 (PD-L1) ≥ 1%. Blood samples were collected before (C0) and after CCRT (C1) to calculate PBC counts and analyze CTCs. CTCs, isolated by the CD-PRIME
system, exhibited EpCAM/CK+/CD45- phenotype in BioViewCCBS
. At median follow-up of 27.4 months, patients with residual CTC clusters at C1 had worse median PFS than those without a detectable CTC cluster (11.0 vs. 27.8 months,
= 0.032), and this trend was noted only in the DC group (
= 0.034). Patients with high platelets at C1 (PLT
, >252 × 10
/µL) had worse median PFS than those with low platelets (PLT
) (5.9 vs. 17.1 months,
< 0.001). In multivariable analysis, PLT
and residual CTC clusters at C1 were independent risk factors for PFS, and DC group with PLT
and residual CTC clusters at C1 showed the worst median PFS (2.6 months, HR 45.16,
= 0.001), even worse than that of the CCRT alone group with PLT
(5.9 months, HR 15.39,
= 0.001). The comprehensive analysis of CTCs and PBCs before and after CCRT revealed that the clearance of CTC clusters and platelet counts at C1 might be potential biomarkers for predicting survival.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>36831494</pmid><doi>10.3390/cancers15041151</doi><orcidid>https://orcid.org/0000-0003-4837-1321</orcidid><orcidid>https://orcid.org/0000-0002-3066-2617</orcidid><orcidid>https://orcid.org/0000-0002-9420-9096</orcidid><oa>free_for_read</oa></addata></record> |
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| source | PubMed Central Open Access; MDPI - Multidisciplinary Digital Publishing Institute; EZB-FREE-00999 freely available EZB journals; PubMed Central |
| subjects | Apoptosis Biological markers Biomarkers Biopsy Blood Blood cells Blood platelets Blood tests Cancer Cancer therapies Care and treatment CD45 antigen Chemoradiotherapy Chemotherapy Diagnosis Feasibility studies Health aspects Lung cancer Lung cancer, Non-small cell Lymphocytes Medical imaging Medical prognosis Mutation Neutrophils Non-small cell lung carcinoma Patient outcomes Patients PD-L1 protein Peripheral blood Phenotypes Platelets Radiation Radiotherapy Risk factors Small cell lung carcinoma Tumor cells |
| title | Blood-Based Biomarker Analysis for Predicting Efficacy of Chemoradiotherapy and Durvalumab in Patients with Unresectable Stage III Non-Small Cell Lung Cancer |
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