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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Immunol.</journal-id>
<journal-title>Frontiers in Immunology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Immunol.</abbrev-journal-title>
<issn pub-type="epub">1664-3224</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fimmu.2024.1370860</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Immunology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Effectiveness of PD-1 inhibitor-based first-line therapy in Chinese patients with metastatic gastric cancer: a retrospective real-world study</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Duan</surname>
<given-names>Yichun</given-names>
</name>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2613809"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Li</surname>
<given-names>Jielang</given-names>
</name>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1182988"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhou</surname>
<given-names>Shuang</given-names>
</name>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Bi</surname>
<given-names>Feng</given-names>
</name>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1360882"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
</contrib-group>
<aff id="aff1">
<institution>Division of Abdominal Cancer, Department of Medical Oncology, Cancer Center and Laboratory of Molecular Targeted Therapy in Oncology, West China Hospital, Sichuan University</institution>, <addr-line>Chengdu, Sichuan</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Yih-Horng Shiao, United States Patent and Trademark Office, United States</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Zhanjun Guo, Fourth Hospital of Hebei Medical University, China</p>
<p>Keren Jia, Peking University, China</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Feng Bi, <email xlink:href="mailto:bifeng@scu.edu.cn">bifeng@scu.edu.cn</email>
</p>
</fn>
<fn fn-type="equal" id="fn003">
<p>&#x2020;These authors have contributed equally to this work</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>12</day>
<month>06</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>15</volume>
<elocation-id>1370860</elocation-id>
<history>
<date date-type="received">
<day>15</day>
<month>01</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>21</day>
<month>05</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2024 Duan, Li, Zhou and Bi</copyright-statement>
<copyright-year>2024</copyright-year>
<copyright-holder>Duan, Li, Zhou and Bi</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Objective</title>
<p>Programmed cell death protein-1 (PD-1) inhibitor-based therapy has demonstrated promising results in metastatic gastric cancer (MGC). However, the previous researches are mostly clinical trials and have reached various conclusions. Our objective is to investigate the efficacy of PD-1 inhibitor-based treatment as first-line therapy for MGC, utilizing real-world data from China, and further analyze predictive biomarkers for efficacy.</p>
</sec>
<sec>
<title>Methods</title>
<p>This retrospective study comprised 105 patients diagnosed with MGC who underwent various PD-1 inhibitor-based treatments as first-line therapy at West China Hospital of Sichuan University from January 2018 to December 2022. Patient characteristics, treatment regimens, and tumor responses were extracted. We also conducted univariate and multivariate analyses to assess the relationship between clinical features and treatment outcomes. Additionally, we evaluated the predictive efficacy of several commonly used biomarkers for PD-1 inhibitor treatments.</p>
</sec>
<sec>
<title>Results</title>
<p>Overall, after 28.0 months of follow-up among the 105 patients included in our study, the objective response rate (ORR) was 30.5%, and the disease control rate (DCR) was 89.5% post-treatment, with two individuals (1.9%) achieving complete response (CR). The median progression-free survival (mPFS) was 9.0 months, and the median overall survival (mOS) was 22.0 months. According to both univariate and multivariate analyses, favorable OS was associated with patients having Eastern Cooperative Oncology Group performance status (ECOG PS) of 0&#x2013;1. Additionally, normal baseline levels of carcinoembryonic antigen (CEA), as well as the combination of PD-1 inhibitors with chemotherapy and trastuzumab in patients with human epidermal growth factor receptor 2 (HER2)-positive MGC, independently predicted longer PFS and OS. However, microsatellite instability/mismatch repair (MSI/MMR) status and Epstein-Barr virus (EBV) infection status were not significantly correlated with PFS or OS extension.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>As the first-line treatment, PD-1 inhibitors, either as monotherapy or in combination therapy, are promising to prolong survival for patients with metastatic gastric cancer. Additionally, baseline level of CEA is a potential predictive biomarker for identifying patients mostly responsive to PD-1 inhibitors.</p>
</sec>
</abstract>
<kwd-group>
<kwd>PD-1 inhibitors</kwd>
<kwd>gastric cancer</kwd>
<kwd>immunotherapy</kwd>
<kwd>real-word study</kwd>
<kwd>drug response biomarkers</kwd>
</kwd-group>
<counts>
<fig-count count="2"/>
<table-count count="4"/>
<equation-count count="0"/>
<ref-count count="37"/>
<page-count count="10"/>
<word-count count="4112"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Cancer Immunity and Immunotherapy</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>Gastric cancer ranks among the most prevalent cancers globally, standing as the fourth most common cause of cancer-related deaths in 2020, with an estimated 769,000 fatalities (<xref ref-type="bibr" rid="B1">1</xref>). The incidence of gastric cancer exhibits regional variation, with a higher prevalence observed in East Asia, particularly in China. In 2022, it ranked as the fifth most common cancer in China, with estimated incidence and mortality rates of 10.5% and 12.4%, respectively (<xref ref-type="bibr" rid="B2">2</xref>). Regrettably, alongside the high incidence of this disease, the majority of patients are diagnosed at an advanced stage upon detection. This is often due to the early clinical symptoms of gastric cancer being mild and easily overlooked. In patients with advanced or metastatic gastric cancer (AGC/MGC), conventional systemic chemotherapy remains the predominant treatment option. Commonly used regimens typically revolve around fluorouracil-based and platinum-based treatments such as SOX (oxaliplatin + S-1), XELOX (oxaliplatin + capecitabine), FOLFOX (calcium folinate + fluorouracil + oxaliplatin) and so on. However, chemotherapy shows limited effect, with a median survival of 11&#x2013;12 months (<xref ref-type="bibr" rid="B3">3</xref>). For human epidermal growth factor receptor 2 (HER2)-positive patients, the recommended first-line treatment option for advanced cancers is the combination of the anti-HER2 antibody trastuzumab with chemotherapy (<xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B5">5</xref>). Nonetheless, patient benefit remains constrained, underscoring the imperative to investigate further treatment alternatives.</p>
<p>Immune checkpoint inhibitors (ICIs), including antibodies against programmed cell death protein-1 (PD-1) or its ligand (PD-L1), have been rapidly developed over the past few years and are now established treatments for chemotherapy-refractory gastric cancers (cancers that progress after two or more lines of chemotherapy) (<xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B7">7</xref>). Previous clinical studies have confirmed that some gastric cancer patients may benefit from PD-1 inhibitor therapy. Regarding first-line treatments for AGC/MGC, the KEYNOTE-062 trial, the first global randomized phase III trial comparing the efficacy and safety of pembrolizumab, a humanized anti-PD-1 monoclonal antibody, with chemotherapeutic agents in AGC/MGC, demonstrated that pembrolizumab alone was not inferior to chemotherapy [median overall survival (mOS): 10.6 vs. 11.1 months, hazard ratio (HR): 0.91, 95% confidence interval (CI): 0.69&#x2013;1.18]. Moreover, pembrolizumab even extended OS in patients with a combined positive score (CPS) of 10 or greater (mOS: 17.4 vs. 10.8 months, HR: 0.69, 95% CI: 0.49&#x2013;0.97). However, pembrolizumab in combination with chemotherapy did not result in an improvement in OS or progression-free survival (PFS) compared to chemotherapy, either in patients with CPS &#x2265;1 or CPS &#x2265;10 (<xref ref-type="bibr" rid="B8">8</xref>). In another phase III trial, KEYNOTE-859, pembrolizumab in combination with chemotherapy prolonged patients&#x2019; OS and PFS compared to chemotherapy alone (<xref ref-type="bibr" rid="B9">9</xref>). For nivolumab, another clinically utilized PD-1 inhibitor, the combination of nivolumab with a chemotherapeutic agent notably enhanced PFS across all CPS subgroups in both the CheckMate 649 and ATTRACTION-4 trials. Additionally, in the CheckMate 649 trial, overall survival was prolonged. However, there was no significant difference between the two treatment modalities in the ATTRACTION-4 trial (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B11">11</xref>). Regarding second- and third-line therapy, two trials conducted globally and in Asia showed favorable activity and a manageable safety profile for PD-1 inhibitors in patients with refractory advanced gastric cancer or gastroesophageal junction cancer (GEJC) who had received at least two prior therapies (<xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B13">13</xref>). In contrast, another phase III trial, JAVELIN Gastric 300, which explored the efficacy of avelumab, a complete human IgG1 monoclonal antibody, as maintenance therapy in patients with AGC/GEJC, led to the conclusion that avelumab did not improve OS or PFS compared to chemotherapy as third-line treatment (<xref ref-type="bibr" rid="B14">14</xref>).</p>
<p>Most of the above trials have demonstrated the effectiveness of PD-1 inhibitors in AGC/MGC, but the treatment response varies among the studies [objective response rate (ORR): 20%-65.1%] (<xref ref-type="bibr" rid="B8">8</xref>&#x2013;<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B15">15</xref>). Findings on the benefits of OS, PFS, and ORR were also inconsistent. The clinical application of PD-1 inhibitor-based therapies is increasingly prevalent; however, there is limited real-world evidence regarding the use of PD-1 inhibitors as monotherapy or in combination treatments. This study endeavors to investigate the effectiveness of PD-1 inhibitor monotherapy or combination therapy in patients with metastatic gastric cancer through analysis of real-world clinical data. Furthermore, we conducted an additional analysis to explore the relationship between clinical characteristics and treatment efficacy, aiming to identify potential biomarkers for predicting the effectiveness of anti-PD-1 therapy.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<title>Materials and methods</title>
<sec id="s2_1">
<title>Study population</title>
<p>This retrospective, single-center study involved patients treated with PD-1 inhibitors monotherapy or a combination of chemotherapeutic agents and targeted agents, as documented by their medical history. We retrospectively collected information on MGC patients who received different PD-1 inhibitor-based treatments between January 2018 and December 2022 at West China Hospital of Sichuan University. The inclusion criteria were as follows: 1) pathologically confirmed gastric cancer; 2) no surgical options available after the initial diagnosis, or disease progression, metastasis, or recurrence after surgical cure; 3) receiving PD-1 inhibitor monotherapy or combination therapy in first line; 4) receiving at least 2 cycles of PD-1 inhibitor-based therapy; and 5) at least one measurable lesion; The major exclusion criteria included: 1) involvement of primary malignant tumors from other systems; and 2) loss to follow up for unknown reasons. We retrieved and integrated clinical information and basic characteristics from the records of the enrolled patients, including age, sex, HER2 expression status, Epstein-Barr virus (EBV) infection status, microsatellite instability/mismatch repair (MSI/MMR) status, carcinoembryonic antigen (CEA) baseline level, Eastern Cooperative Oncology Group performance status (ECOG PS), tumor stage, pathology type, metastatic organs, previous immunotherapy status, and treatment regimen. Patients were included regardless of their statuses of MMR proteins through immunohistochemical method or MSI through Next-Generation sequencing testing. The study was approved by the Ethics Committee of West China Hospital of Sichuan University, in accordance with the Declaration of Helsinki and the International Ethical Guidelines for Human Biomedical Research (Ethics Approval Number: 2023&#x2013;2073).</p>
</sec>
<sec id="s2_2">
<title>Study design and treatment regimens</title>
<p>The chemotherapy regimens used SOX (oxaliplatin + S-1), TP (albumin paclitaxel + cisplatin), and XELOX (oxaliplatin + capecitabine), and the targeted drugs was the injectable trastuzumab (herceptin) for HER2-positive patients. The regimen of each PD-1 inhibitor for the concurrent use with chemotherapy drugs or targeted drugs is as follows: pembrolizumab (200mg), cedilimumab (200mg), tislelizumab (200mg) or toripalimab (240mg) for IV infusion every 3 weeks; or carrelizumab (200mg) or nivolumab (3mg/kg) for IV infusion every 2 weeks.</p>
</sec>
<sec id="s2_3">
<title>Assessment</title>
<p>The primary endpoint of this study was overall survival, defined as the time from the start of the patient&#x2019;s PD-1 inhibitor-based therapy to the time of death from any cause, and the secondary endpoint was progression-free survival, defined as the time from the start of the patient&#x2019;s PD-1 inhibitor-based therapy to the time of disease progression or death from any cause. Based on the Response Evaluation Criteria in Solid Tumors 1.1, the additional efficacy assessment metrics included: complete response (CR), partial response (PR), stable disease (SD), progressive disease (PD), the objective response rate which is the sum of the proportions of complete response and partial response, as well as the disease control rate (DCR) which is defined as the proportion of cases achieving remission (CR+PR) and disease stability (SD) after treatment, representing the percentage of patients without disease progression.</p>
</sec>
<sec id="s2_4">
<title>Statistical analysis</title>
<p>Variables are presented as median (range) for continuous variables and numbers (%) for categorical variables. Relationships between categorical variables were examined by means of the Chi-square test. Univariate and multivariate analyses were performed to evaluate the prognostic impact on PFS and OS. The Kaplan&#x2013;Meier method was applied to estimate survival probabilities and the log-rank test was carried out to assess heterogeneity within each prognostic factor. The HR was estimated using the Cox proportional hazard model. Cox proportional hazards regression analysis was carried out as a multivariate analysis to assess the prognostic value of the markers adjusted for the possible confounding effect of all the other factors included in the same model. All the statistical tests were two-sided, and differences for which p values were less than 0.05 were considered significant. All statistical analyses were performed using SPSS 27.0 software.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<sec id="s3_1">
<title>Patients&#x2019; characteristics and treatment</title>
<p>Our study included 105 patients whose median age was 55 years (range: 27&#x2013;85). Among these patients, 51 (48.6%) were male, 103 (98.1%) had an ECOG PS score of 0&#x2013;1, 97 (92.4%) had adenocarcinomas, 72 (68.6%) had poorly differentiated cancers. The numbers of tumors that metastasized to the liver, lung, lymph nodes, bone and peritoneum/pleura were 28 (26.7%), 9 (8.6%), 80 (75.5%), 8 (7.6%) and 48(11.9%), respectively. The PD-1 inhibitors used by patients included nivolumab (n=46, 43.8%), pembrolizumab (n=4, 3.8%), cedilimumab (n=26, 24.8%), carrelizumab (n=20, 19.0%), tislelizumab (n=7, 6.7%), toripalimab (n=2, 1.9%). A total of 3 (2.9%) individuals received treatment with PD-1 inhibitors alone, 92 (87.6%) received combined PD-1 inhibitor and chemotherapy, and 10 (9.5%) received combined PD-1 inhibitor, chemotherapy and targeted therapy. A total of 10 (9.5%) had positive HER2 status, 5 (4.8%) had deficient mismatch repair/microsatellite instability-high (dMMR/MSI-H) status, and 6 (5.7%) had positive EBV status, and 39 (37.1%) had CEA baseline level greater than normal baseline level. <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref> shows more detailed information.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Patients and tumor characteristics.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="center">Characteristic</th>
<th valign="top" align="center">N (%)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center">
<bold>Age (range)<sup>*</sup>
</bold>
</td>
<td valign="top" align="center">55 (27&#x2013;85)</td>
</tr>
<tr>
<td valign="top" align="center">&#x2264;60y</td>
<td valign="top" align="center">65 (61.9)</td>
</tr>
<tr>
<td valign="top" align="center">&gt;60y</td>
<td valign="top" align="center">40 (38.1)</td>
</tr>
<tr>
<th valign="top" colspan="2" align="left">Gender</th>
</tr>
<tr>
<td valign="top" align="center">Male</td>
<td valign="top" align="center">51 (48.6)</td>
</tr>
<tr>
<td valign="top" align="center">Female</td>
<td valign="top" align="center">54 (51.4)</td>
</tr>
<tr>
<th valign="top" colspan="2" align="left">ECOG PS</th>
</tr>
<tr>
<td valign="top" align="center">0&#x2013;1</td>
<td valign="top" align="center">103 (98.1)</td>
</tr>
<tr>
<td valign="top" align="center">&#x2265;2</td>
<td valign="top" align="center">2 (1.9)</td>
</tr>
<tr>
<th valign="top" colspan="2" align="left">Pathological type</th>
</tr>
<tr>
<td valign="top" align="center">Adenocarcinoma</td>
<td valign="top" align="center">97 (92.4)</td>
</tr>
<tr>
<td valign="top" align="center">Non-adenocarcinoma</td>
<td valign="top" align="center">8 (7.6)</td>
</tr>
<tr>
<th valign="top" colspan="2" align="left">Histological differentiation</th>
</tr>
<tr>
<td valign="top" align="center">Poorly</td>
<td valign="top" align="center">72 (68.6)</td>
</tr>
<tr>
<td valign="top" align="center">Moderately/Well</td>
<td valign="top" align="center">33 (31.4)</td>
</tr>
<tr>
<th valign="top" colspan="2" align="left">HER2 status</th>
</tr>
<tr>
<td valign="top" align="center">Negative</td>
<td valign="top" align="center">84 (80.0)</td>
</tr>
<tr>
<td valign="top" align="center">Positive</td>
<td valign="top" align="center">10 (9.5)</td>
</tr>
<tr>
<td valign="top" align="center">Unknown</td>
<td valign="top" align="center">11 (10.5)</td>
</tr>
<tr>
<th valign="top" colspan="2" align="left">MSI/MMR status</th>
</tr>
<tr>
<td valign="top" align="center">pMMR/MSS</td>
<td valign="top" align="center">75 (71.4)</td>
</tr>
<tr>
<td valign="top" align="center">dMMR/MSI-H</td>
<td valign="top" align="center">5 (4.8)</td>
</tr>
<tr>
<td valign="top" align="center">Unknown</td>
<td valign="top" align="center">25 (23.8)</td>
</tr>
<tr>
<th valign="top" colspan="2" align="left">EBV status</th>
</tr>
<tr>
<td valign="top" align="center">Negative</td>
<td valign="top" align="center">72 (68.6)</td>
</tr>
<tr>
<td valign="top" align="center">Positive</td>
<td valign="top" align="center">6 (5.7)</td>
</tr>
<tr>
<td valign="top" align="center">Unknown</td>
<td valign="top" align="center">27 (25.7)</td>
</tr>
<tr>
<th valign="top" colspan="2" align="left">CEA level</th>
</tr>
<tr>
<td valign="top" align="center">&#x2264; normal baseline CEA levels</td>
<td valign="top" align="center">66 (62.9)</td>
</tr>
<tr>
<td valign="top" align="center">&gt; normal baseline CEA levels</td>
<td valign="top" align="center">39 (37.1)</td>
</tr>
<tr>
<th valign="top" colspan="2" align="left">Metastatic site</th>
</tr>
<tr>
<td valign="top" align="center">Liver</td>
<td valign="top" align="center">28 (26.7)</td>
</tr>
<tr>
<td valign="top" align="center">Lung</td>
<td valign="top" align="center">9 (8.6)</td>
</tr>
<tr>
<td valign="top" align="center">Lymph node</td>
<td valign="top" align="center">80 (75.5)</td>
</tr>
<tr>
<td valign="top" align="center">Bone</td>
<td valign="top" align="center">8 (7.6)</td>
</tr>
<tr>
<td valign="top" align="center">Peritoneum/Pleura</td>
<td valign="top" align="center">48 (11.9)</td>
</tr>
<tr>
<th valign="top" colspan="2" align="left">Anti-PD-1 therapy</th>
</tr>
<tr>
<td valign="top" align="center">Monotherapy</td>
<td valign="top" align="center">3 (2.9)</td>
</tr>
<tr>
<td valign="top" align="center">Plus chemo</td>
<td valign="top" align="center">92 (87.6)</td>
</tr>
<tr>
<td valign="top" align="center">Plus chemo + trastuzumab</td>
<td valign="top" align="center">10 (9.5)</td>
</tr>
<tr>
<th valign="top" colspan="2" align="left">Anti-PD-1 therapy type</th>
</tr>
<tr>
<td valign="top" align="center">Nivolumab</td>
<td valign="top" align="center">46 (43.8)</td>
</tr>
<tr>
<td valign="top" align="center">Pembrolizumab</td>
<td valign="top" align="center">4 (3.8)</td>
</tr>
<tr>
<td valign="top" align="center">Cedilimumab</td>
<td valign="top" align="center">26 (24.8)</td>
</tr>
<tr>
<td valign="top" align="center">Carrelizumab</td>
<td valign="top" align="center">20 (19.0)</td>
</tr>
<tr>
<td valign="top" align="center">Tislelizumab</td>
<td valign="top" align="center">7 (6.7)</td>
</tr>
<tr>
<td valign="top" align="center">Toripalimab</td>
<td valign="top" align="center">2 (1.9)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>* The difference between the maximum and minimum values.</p>
</fn>
<fn>
<p>ECOG PS Eastern Cooperative Oncology Group performance status, HER2 human epidermal growth factor receptor 2, MSI/MMR microsatellite instability/mismatch repair, pMMR/MSS proficient mismatch repair/microsatellite stable, dMMR/MSI-H deficient mismatch repair/microsatellite instability-high, EBV Epstein-Barr virus, CEA carcinoembryonic antigen, PD-1 programmed cell death protein-1, chemo chemotherapy.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_2">
<title>Efficacy</title>
<p>As of October 17, 2023, among the 105 individuals enrolled in the study, 2 (1.9%) patients achieved CR, and an ORR of 30.5% and a DCR of 89.5% were observed in the total population. Specific information can be found in <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>. After 28.0 months (95% CI: 25.114&#x2013;30.886) of follow-up, the median OS in the total population was 22.0 months (95% CI: 16.204&#x2013;22.796; <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1A</bold>
</xref>), and the median PFS was 9.0 months (95% CI: 7.184&#x2013;10.816; <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1B</bold>
</xref>). At the cut-off date, 40 patients were still alive.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Response outcome.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="bottom" align="center">Response</th>
<th valign="bottom" align="center">N(%)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="bottom" align="center">CR</td>
<td valign="middle" align="center">2 (1.9)</td>
</tr>
<tr>
<td valign="bottom" align="center">PR</td>
<td valign="middle" align="center">30 (28.6)</td>
</tr>
<tr>
<td valign="bottom" align="center">SD</td>
<td valign="middle" align="center">62 (59.0)</td>
</tr>
<tr>
<td valign="bottom" align="center">PD</td>
<td valign="middle" align="center">11 (10.5)</td>
</tr>
<tr>
<td valign="bottom" align="center">ORR(CR+PR)</td>
<td valign="middle" align="center">32 (30.5)</td>
</tr>
<tr>
<td valign="bottom" align="center">DCR(CR+PR+SD)</td>
<td valign="bottom" align="center">94 (89.5)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>CR complete response, PR partial response, SD stable disease, PD progressive disease, ORR objective response rate, DCR disease control rate.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>K-M plot of overall survival (OS) <bold>(A)</bold> and progression-free survival (PFS) <bold>(B)</bold> in all patients.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-15-1370860-g001.tif"/>
</fig>
</sec>
<sec id="s3_3">
<title>Univariate analysis and multivariate analysis</title>
<p>According to the results of the univariate analysis and multivariate analysis, favorable prognostic factors for OS included an ECOG PS score &lt;2, CEA at the normal level, and the addition of targeted therapy for HER2-positive MGC patients (<xref ref-type="table" rid="T3">
<bold>Tables&#xa0;3</bold>
</xref>, <xref ref-type="table" rid="T4">
<bold>4</bold>
</xref>). The median OS for patients with ECOG PS score of 0&#x2013;1 was 22.0 months, while for those with a score &#x2265;2, it was 1.0 months (HR: 6.327, 95% CI: 1.502&#x2013;26.648; p=0.012, <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2A</bold>
</xref>). In the subgroups, patients with elevated CEA levels at baseline exhibited poorer immunotherapy responsiveness than those with normal CEA level: mOS (15.0 vs. 27.0 months, HR: 1.754, 95% CI: 1.031&#x2013;2.985; p=0.038, <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2B</bold>
</xref>) and mPFS (6.0 vs. 9.0 months, HR: 1.533, 95% CI: 0.992&#x2013;2.369; p=0.054). Additionally, the combination of PD-1 inhibitors with chemotherapy and trastuzumab, compared to PD-1 inhibitors monotherapy or combined with chemotherapy alone, may result in a better mOS (&gt;28.0 vs. 21.0 months, HR: 0.299, 95% CI: 0.093&#x2013;0.962; p=0.043, <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2C</bold>
</xref>, <xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>) and mPFS (12.0 vs. 8.0 months, HR: 0.597, 95% CI: 0.308&#x2013;1.158; p=0.127, <xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>), however, PFS were not significantly different between the two subgroups.</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Univariate analysis and multivariate analysis of clinical variables for the prediction of overall survival.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="center"/>
<th valign="top" colspan="3" align="center">Univariate Cox model</th>
<th valign="top" colspan="3" align="center">Multivariate Cox model</th>
</tr>
<tr>
<th valign="top" align="center">Characteristics</th>
<th valign="top" align="center">HR</th>
<th valign="top" align="center">95%CI</th>
<th valign="top" align="center">P value</th>
<th valign="top" align="center">HR</th>
<th valign="top" align="center">95%CI</th>
<th valign="top" align="center">P value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center">
<bold>Gender</bold>
</td>
<td valign="top" align="center">1.108</td>
<td valign="top" align="center">0.678&#x2013;1.810</td>
<td valign="top" align="center">0.682</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Male vs Female</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Age</bold>
</td>
<td valign="top" align="center">0.940</td>
<td valign="top" align="center">0.573&#x2013;1.544</td>
<td valign="top" align="center">0.808</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">&gt;60 vs &#x2264;60</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>ECOG PS</bold>
</td>
<td valign="top" align="center">6.327</td>
<td valign="top" align="center">1.502&#x2013;26.648</td>
<td valign="top" align="center">
<bold>0.012</bold>
</td>
<td valign="top" align="center">5.439</td>
<td valign="top" align="center">1.153&#x2013;25.645</td>
<td valign="top" align="center">
<bold>0.032</bold>
</td>
</tr>
<tr>
<td valign="top" align="center">&#x2265;2 vs 0&#x2013;1</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Pathological type</bold>
</td>
<td valign="top" align="center">0.431</td>
<td valign="top" align="center">0.135&#x2013;1.378</td>
<td valign="top" align="center">0.156</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Non-adenocarcinoma vs Adenocarcinoma</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Histological differentiation</bold>
</td>
<td valign="top" align="center">0.711</td>
<td valign="top" align="center">0.407&#x2013;1.241</td>
<td valign="top" align="center">0.230</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Moderately/Well vs Poorly</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>HER2 status</bold>
</td>
<td valign="top" align="center">0.310</td>
<td valign="top" align="center">0.096&#x2013;1.0</td>
<td valign="top" align="center">0.050</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Positive vs Negative</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>MSI/MMR status</bold>
</td>
<td valign="top" align="center">0.546</td>
<td valign="top" align="center">0.132&#x2013;2.254</td>
<td valign="top" align="center">0.403</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Positive vs Negative</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>EBV status</bold>
</td>
<td valign="top" align="center">0.193</td>
<td valign="top" align="center">0.026&#x2013;1.405</td>
<td valign="top" align="center">0.104</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Positive vs Negative</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>CEA level &gt; normal baseline CEA levels</bold>
</td>
<td valign="top" align="center">1.754</td>
<td valign="top" align="center">1.031&#x2013;2.985</td>
<td valign="top" align="center">
<bold>0.038</bold>
</td>
<td valign="top" align="center">1.926</td>
<td valign="top" align="center">1.077&#x2013;3.444</td>
<td valign="top" align="center">
<bold>0.027</bold>
</td>
</tr>
<tr>
<td valign="top" align="center">Yes vs No</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Liver metastasis</bold>
</td>
<td valign="top" align="center">1.040</td>
<td valign="top" align="center">0.601&#x2013;1.80</td>
<td valign="top" align="center">0.890</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Yes vs No</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Lung metastasis</bold>
</td>
<td valign="top" align="center">1.0</td>
<td valign="top" align="center">0.425&#x2013;2.353</td>
<td valign="top" align="center">1.0</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Yes vs No</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Bone metastasis</bold>
</td>
<td valign="top" align="center">1.330</td>
<td valign="top" align="center">0.533&#x2013;3.317</td>
<td valign="top" align="center">0.541</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Yes vs No</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Lymph node metastasis</bold>
</td>
<td valign="top" align="center">0.870</td>
<td valign="top" align="center">0.504&#x2013;1.50</td>
<td valign="top" align="center">0.616</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Yes vs No</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Peritoneum/Pleura metastasis</bold>
</td>
<td valign="top" align="center">1.512</td>
<td valign="top" align="center">0.922&#x2013;2.481</td>
<td valign="top" align="center">0.101</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Yes vs No</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Anti-PD-1+ trastuzumab</bold>
</td>
<td valign="top" align="center">0.299</td>
<td valign="top" align="center">0.093&#x2013;0.962</td>
<td valign="top" align="center">
<bold>0.043</bold>
</td>
<td valign="top" align="center">0.283</td>
<td valign="top" align="center">0.084&#x2013;0.947</td>
<td valign="top" align="center">
<bold>0.041</bold>
</td>
</tr>
<tr>
<td valign="top" align="center">Yes vs No</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>ECOG PS Eastern Cooperative Oncology Group performance status, HER2 human epidermal growth factor receptor 2, MSI/MMR microsatellite instability/mismatch repair, EBV Epstein-Barr virus, CEA carcinoembryonic antigen, PD-1 programmed cell death protein-1. bold value: this value &lt; 0.05.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>Univariate analysis and multivariate analysis of clinical variables for the prediction of progression free survival.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="center"/>
<th valign="top" colspan="3" align="center">Univariate Cox model</th>
<th valign="top" colspan="3" align="center">Multivariate Cox model</th>
</tr>
<tr>
<th valign="top" align="center">Characteristics</th>
<th valign="top" align="center">HR</th>
<th valign="top" align="center">95%CI</th>
<th valign="top" align="center">P value</th>
<th valign="top" align="center">HR</th>
<th valign="top" align="center">95%CI</th>
<th valign="top" align="center">P value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center">
<bold>Gender</bold>
</td>
<td valign="top" align="center">0.928</td>
<td valign="top" align="center">0.628&#x2013;1.369</td>
<td valign="top" align="center">0.705</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Male vs Female</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Age</bold>
</td>
<td valign="top" align="center">0.720</td>
<td valign="top" align="center">0.482&#x2013;1.077</td>
<td valign="top" align="center">0.110</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">&gt;60 vs &#x2264;60</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>ECOG PS</bold>
</td>
<td valign="top" align="center">2.557</td>
<td valign="top" align="center">0.623&#x2013;10.492</td>
<td valign="top" align="center">0.192</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">&#x2265;2 vs 0&#x2013;1</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Pathological type</bold>
</td>
<td valign="top" align="center">0.677</td>
<td valign="top" align="center">0.328&#x2013;1.397</td>
<td valign="top" align="center">0.291</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Non-adenocarcinoma vs Adenocarcinoma</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Histological differentiation</bold>
</td>
<td valign="top" align="center">0.874</td>
<td valign="top" align="center">0.569&#x2013;1.342</td>
<td valign="top" align="center">0.538</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Moderately/Well vs Poorly</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>HER2 status</bold>
</td>
<td valign="top" align="center">0.628</td>
<td valign="top" align="center">0.322&#x2013;1.224</td>
<td valign="top" align="center">0.172</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Positive vs Negative</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>MSI/MMR status</bold>
</td>
<td valign="top" align="center">1.076</td>
<td valign="top" align="center">0.428&#x2013;2.702</td>
<td valign="top" align="center">0.877</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Positive vs Negative</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>EBV status</bold>
</td>
<td valign="top" align="center">0.632</td>
<td valign="top" align="center">0.274&#x2013;1.460</td>
<td valign="top" align="center">0.283</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Positive vs Negative</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>CEA level &gt; normal baseline CEA level</bold>
</td>
<td valign="top" align="center">1.533</td>
<td valign="top" align="center">0.992&#x2013;2.369</td>
<td valign="top" align="center">0.054</td>
<td valign="top" align="center">12.423</td>
<td valign="top" align="center">1.377&#x2013;4.266</td>
<td valign="top" align="center">
<bold>0.002</bold>
</td>
</tr>
<tr>
<td valign="top" align="center">Yes vs No</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Liver metastasis</bold>
</td>
<td valign="top" align="center">0.998</td>
<td valign="top" align="center">0.637&#x2013;1.563</td>
<td valign="top" align="center">0.993</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Yes vs No</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Lung metastasis</bold>
</td>
<td valign="top" align="center">0.983</td>
<td valign="top" align="center">0.470&#x2013;2.054</td>
<td valign="top" align="center">0.964</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Yes vs No</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Bone metastasis</bold>
</td>
<td valign="top" align="center">1.327</td>
<td valign="top" align="center">0.642&#x2013;2.742</td>
<td valign="top" align="center">0.445</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Yes vs No</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Lymph node metastasis</bold>
</td>
<td valign="top" align="center">0.903</td>
<td valign="top" align="center">0.569&#x2013;1.433</td>
<td valign="top" align="center">0.664</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">Yes vs No</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Peritoneum/Pleura metastasis</bold>
</td>
<td valign="top" align="center">1.713</td>
<td valign="top" align="center">1.146&#x2013;2.561</td>
<td valign="top" align="center">
<bold>0.009</bold>
</td>
<td valign="top" align="center">1.295</td>
<td valign="top" align="center">0.787&#x2013;2.131</td>
<td valign="top" align="center">0.309</td>
</tr>
<tr>
<td valign="top" align="center">Yes vs No</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="center">
<bold>Anti-PD-1+ trastuzumab</bold>
</td>
<td valign="top" align="center">0.597</td>
<td valign="top" align="center">0.308&#x2013;1.158</td>
<td valign="top" align="center">0.127</td>
<td valign="top" align="center">0.393</td>
<td valign="top" align="center">0.172&#x2013;0.898</td>
<td valign="top" align="center">
<bold>0.027</bold>
</td>
</tr>
<tr>
<td valign="top" align="center">Yes vs No</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>ECOG PS Eastern Cooperative Oncology Group performance status, HER2 human epidermal growth factor receptor 2, MSI/MMR microsatellite instability/mismatch repair, EBV Epstein-Barr virus, CEA carcinoembryonic antigen, PD-1 programmed cell death protein-1. bold value: this value &lt; 0.05.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>K-M plot of overall survival for patients with different ECOG PS scores <bold>(A)</bold>, CEA level <bold>(B)</bold>, therapy strategy <bold>(C)</bold>. <bold>(A)</bold> <italic>ECOG PS</italic> Eastern Cooperative Oncology Group performance status. <bold>(B)</bold> <italic>CEA</italic> carcinoembryonic antigen. <bold>(C)</bold> <italic>NR</italic> not reached.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-15-1370860-g002.tif"/>
</fig>
<p>In the univariate analysis, considering that true effect of these factors may be masked by the effects of other confounding factors in single-factor analysis, we selected several indicators that were meaningful in the univariate analysis of OS for multivariate analysis, with favorable prognostic factors including CEA at the normal level (HR: 12.423, 95% CI: 1.377&#x2013;4.266; p=0.002) and the addition of targeted therapy, trastuzumab, to immunotherapy (HR: 0.393, 95% CI: 0.172&#x2013;0.898; p=0.027).</p>
</sec>
<sec id="s3_4">
<title>Molecular features associated with OS and PFS</title>
<p>MSI/MMR status and EBV infection status are commonly used molecular biomarkers for immunotherapy. However, this study found no significant correlation between different MSI/MMR status (positive vs. negative) and EBV infection status (positive vs. negative) with changes in mOS (MSI/MMR: 24.0 vs. 22.0 months, p=0.403; EBV: &gt;28.0 vs. 22.0 months, p=0.104) and mPFS (MSI/MMR: 6.0 vs. 9.0 months, p=0.877; EBV: 17.0 vs. 9.0 months, p=0.283). Therefore, these two biomarkers cannot currently be deemed predictive of responsiveness to immunotherapy.</p>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>Progressive gastric cancer has a poor prognosis and current treatment options are limited. With the rise of immunotherapy in recent years, PD-1 inhibitors such as nivolumab and pembrolizumab in combination with chemotherapy also have been recommended for treatment of metastatic gastric cancer (<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B16">16</xref>, <xref ref-type="bibr" rid="B17">17</xref>). However, most previous conclusions were drawn from clinical trials, and there is considerable variation in patient outcomes, with ORR ranging from 20% to 65.1% (<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B18">18</xref>). Hence, it is imperative to investigate the real-world benefits that gastric cancer patients derive from first-line treatment with immune checkpoint inhibitors. To the best of our knowledge, this study represents a largest single-center real-world analysis among Chinese patients with MGC undergoing first-line treatment with anti-PD-1 therapy. Our findings suggest that first-line treatment with PD-1 inhibitors yields significant efficacy, particularly show that the median OS was 22.0 months (95% CI: 16.204&#x2013;22.796), and the median PFS was 9.0 months (95% CI: 7.184&#x2013;10.816) with an ORR of 30.5% and a DCR of 89.5%. Furthermore, compared to chemotherapy regimens alone in previous studies (OS:6.2&#x2013;14 months, PFS: 4.3&#x2013;12.1 months), the efficacy of chemotherapy combined with PD-1 inhibitors was indeed superior (<xref ref-type="bibr" rid="B3">3</xref>). Our patients obtained a longer OS.</p>
<p>It appears that patients may potentially benefit more from combination therapy with chemotherapy plus trastuzumab compared to PD-1 monotherapy or combination with chemotherapy alone. After a follow-up period of 28.0 months in our study, patients treated with PD-1 inhibitors exhibit a mOS of 21 months, while those receiving the combination of PD-1 inhibitors and trastuzumab remain alive, and thus have not yet reached their mOS. For HER2-positive patients, the current recommended standard treatment entails combining chemotherapy with trastuzumab. Recent studies have shown that adding PD-1 inhibitors to the combination of chemotherapy and trastuzumab can enhance efficacy in HER2-positive patients (<xref ref-type="bibr" rid="B19">19</xref>&#x2013;<xref ref-type="bibr" rid="B21">21</xref>). Our study further supports this evidence. Nevertheless, due to the limited number of HER2-positive cases, further analysis and expansion of this patient subgroup are warranted.</p>
<p>Although anti-PD-1 treatment has improved patient prognosis compared to early studies, a considerable portion of patients still do not benefit from it, and there is also an increase of the risk of severe immune-related adverse effects. Therefore, researchers continue to explore and identify biomarkers to select the most suitable candidates for immunotherapy. Previous experiments have explored various biomarkers for predicting the efficacy of immunotherapy, including two gastric cancer genomic subtypes identified by The Cancer Genome Atlas (TCGA) studies: EBV infection status and MSI status (<xref ref-type="bibr" rid="B22">22</xref>). EBV infection can upregulate PD-L1 expression (<xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B24">24</xref>), while DNA replication defects caused by dMMR/MSI-H result in the accumulation of mutations and the expression of new antigens, which may serve as potential targets for immune cells (<xref ref-type="bibr" rid="B25">25</xref>). Clinical trial findings suggest that patients with EBV infection or dMMR/MSI-H tumors may be more sensitive to immunotherapy (<xref ref-type="bibr" rid="B26">26</xref>&#x2013;<xref ref-type="bibr" rid="B29">29</xref>). However, some experiments also demonstrate that these two biomarkers may not predict the response to immunotherapy in gastric cancer effectively (<xref ref-type="bibr" rid="B30">30</xref>&#x2013;<xref ref-type="bibr" rid="B32">32</xref>). In this study, the ORR for two biomarkers EBV-positive and dMMR/MSI-H were 66.7% and 40%, respectively, which align with previous research findings (<xref ref-type="bibr" rid="B28">28</xref>, <xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B33">33</xref>). However, there were no significant statistical differences in OS and PFS between the subgroups. This lack of significance may be attributed to the low proportion of patients testing positive for these indicators. Consequently, the small sample size of these patients may have limited statistical power, underscoring the necessity to expand the sample size.</p>
<p>Currently, these biomarkers have limited clinical utility due to their uncertain predictive value, low positivity rates, and high cost. Therefore, we are striving to identify a more effective and convenient biomarker to predict the efficacy of immunotherapy. CEA is a widely used tumor marker in gastric cancer, playing a significant role in disease diagnosis and prognosis (<xref ref-type="bibr" rid="B34">34</xref>, <xref ref-type="bibr" rid="B35">35</xref>). Additionally, research has demonstrated ability of CEA to predict the efficacy of PD-1 inhibitors, in non-small cell lung cancer. CEA values have been identified as predictors of patient responsiveness to immune checkpoint inhibitors (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B37">37</xref>). In the current study, patients with CEA levels above the normal level had a mOS of 15.0 months, while those with normal CEA levels had a mOS of 27.0 months. Similarly, the mPFS was 6.0 months for patients with CEA levels above the standard level and 9.0 months for those with normal level, with statistically significant differences observed. It can be inferred that patients with CEA baseline levels below the standard threshold may derive greater benefits from immunotherapy. In the future, CEA levels might be utilized to predict patients&#x2019; response to anti-PD-1 therapy.</p>
<p>This study also has some limitations. Firstly, our study is a retrospective analysis, which inevitably introduces biases. Secondly, despite being the largest single-center, retrospective study to date, the sample size remains insufficient, for instance, efficacy comparisons among various PD-1 inhibitors were not feasible. Thirdly, due to the retrospective nature of the study, certain molecular markers in patients were not assessed, such as PD-L1 expression and tumor mutation burden (TMB), thus preventing analysis of these markers&#x2019; predictive value for treatment efficacy.</p>
</sec>
<sec id="s5" sec-type="conclusions">
<title>Conclusion</title>
<p>In conclusion, our study illustrates the effectiveness of PD-1 inhibitor-based therapy for patients with metastatic gastric cancer. Additionally, we found that carcinoembryonic antigen shows promise as a predictor of immunotherapy efficacy.</p>
</sec>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec id="s7" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>The studies involving humans were approved by Biomedical Research Ethics Committee of West China Hospital of Sichuan University. The studies were conducted in accordance with the local legislation and institutional requirements. The ethics committee/institutional review board waived the requirement of written informed consent for participation from the participants or the participants&#x2019; legal guardians/next of kin because studies utilizing medical records were obtained from previous clinical consultations.</p>
</sec>
<sec id="s8" sec-type="author-contributions">
<title>Author contributions</title>
<p>YD: Writing &#x2013; original draft, Writing &#x2013; review &amp; editing. JL: Writing &#x2013; review &amp; editing. SZ: Writing &#x2013; review &amp; editing. FB: Writing &#x2013; review &amp; editing.</p>
</sec>
</body>
<back>
<sec id="s9" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>Thanks to my colleagues who contributed to this article.</p>
</ack>
<sec id="s10" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s11" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
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