Data Sheet 1_Integrated liquid biopsy model for predicting metastasis and guiding PD-1 therapy in esophageal squamous cell carcinoma.pdf

Objective<p>This study endeavors to develop and validate an integrated biomarker signature (IBS) grounded in serum carbohydrate antigen 72-4 (CA72-4), vascular endothelial growth factor-C (VEGF-C), and the pepsinogen I/II ratio (PGI/PGII). A practical IBS model will be constructed to substanti...

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מחבר ראשי: Hailong Pang (12841991) (author)
מחברים אחרים: Shenshen Hao (22686440) (author), Shuiwang Hu (4603495) (author)
יצא לאור: 2025
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author Hailong Pang (12841991)
author2 Shenshen Hao (22686440)
Shuiwang Hu (4603495)
author2_role author
author
author_facet Hailong Pang (12841991)
Shenshen Hao (22686440)
Shuiwang Hu (4603495)
author_role author
dc.creator.none.fl_str_mv Hailong Pang (12841991)
Shenshen Hao (22686440)
Shuiwang Hu (4603495)
dc.date.none.fl_str_mv 2025-11-26T05:15:03Z
dc.identifier.none.fl_str_mv 10.3389/fonc.2025.1673946.s003
dc.relation.none.fl_str_mv https://figshare.com/articles/dataset/Data_Sheet_1_Integrated_liquid_biopsy_model_for_predicting_metastasis_and_guiding_PD-1_therapy_in_esophageal_squamous_cell_carcinoma_pdf/30717665
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Oncology and Carcinogenesis not elsewhere classified
esophageal squamous cell carcinoma
lymphnode metastasis
liquid biopsy
integrated biomarker signature
PD-1 inhibitor
dc.title.none.fl_str_mv Data Sheet 1_Integrated liquid biopsy model for predicting metastasis and guiding PD-1 therapy in esophageal squamous cell carcinoma.pdf
dc.type.none.fl_str_mv Dataset
info:eu-repo/semantics/publishedVersion
dataset
description Objective<p>This study endeavors to develop and validate an integrated biomarker signature (IBS) grounded in serum carbohydrate antigen 72-4 (CA72-4), vascular endothelial growth factor-C (VEGF-C), and the pepsinogen I/II ratio (PGI/PGII). A practical IBS model will be constructed to substantially enhance the accuracy of lymph node metastasis (LNM) risk stratification following surgery for esophageal squamous cell carcinoma (ESCC). This model is anticipated to refine prognostic assessments for patients and to identify novel research avenues within the field, thereby providing guidance for both prognostic determination and future investigations.</p>Methods<p>A prospective three-cohort design was adopted, encompassing a training cohort of 220 patients, a temporal validation cohort of 138 patients, and a regional external validation cohort of 94 patients. This design was selected for its robustness in ensuring the validity and reliability of the findings. A total of 452 patients with esophageal squamous cell carcinoma (ESCC) who underwent R0 resection were enrolled between March 2022 and June 2024. The predictive model was constructed using the XGBoost algorithm combined with Shapley Additive exPlanations (SHAP) for interpretability. Model performance was evaluated via receiver operating characteristic (ROC) curves, decision curve analysis, and net reclassification index.</p>Results<p>The IBS model demonstrated superior discriminative ability in the training cohort (n = 220; area under the receiver operating characteristic curve (AUC) = 0.936; 95% confidence interval (CI): 0.908–0.964) compared to the AJCC ninth edition staging system (ΔAUC = 0.154; p < 0.001). Performance was maintained in validation cohorts. High-risk patients (IBS > 0.5) receiving PD-1 inhibitor plus chemotherapy achieved a pathological complete response (pCR) rate of 28.6%, representing a 115% increase over conventional therapy (p = 0.009).</p>Conclusion<p>The validated IBS model provides high-precision prediction of postoperative LNM risk in ESCC. It offers a novel framework (“tumor antigen burden–lymphangiogenesis–immune microenvironment”) for improving patient risk stratification, guiding adjuvant therapy decisions (including immunotherapy response prediction), and optimizing resource allocation, thereby potentially impacting ESCC management paradigms.</p>
eu_rights_str_mv openAccess
id Manara_2d5b6867522fb94907b226a69b412a99
identifier_str_mv 10.3389/fonc.2025.1673946.s003
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/30717665
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling Data Sheet 1_Integrated liquid biopsy model for predicting metastasis and guiding PD-1 therapy in esophageal squamous cell carcinoma.pdfHailong Pang (12841991)Shenshen Hao (22686440)Shuiwang Hu (4603495)Oncology and Carcinogenesis not elsewhere classifiedesophageal squamous cell carcinomalymphnode metastasisliquid biopsyintegrated biomarker signaturePD-1 inhibitorObjective<p>This study endeavors to develop and validate an integrated biomarker signature (IBS) grounded in serum carbohydrate antigen 72-4 (CA72-4), vascular endothelial growth factor-C (VEGF-C), and the pepsinogen I/II ratio (PGI/PGII). A practical IBS model will be constructed to substantially enhance the accuracy of lymph node metastasis (LNM) risk stratification following surgery for esophageal squamous cell carcinoma (ESCC). This model is anticipated to refine prognostic assessments for patients and to identify novel research avenues within the field, thereby providing guidance for both prognostic determination and future investigations.</p>Methods<p>A prospective three-cohort design was adopted, encompassing a training cohort of 220 patients, a temporal validation cohort of 138 patients, and a regional external validation cohort of 94 patients. This design was selected for its robustness in ensuring the validity and reliability of the findings. A total of 452 patients with esophageal squamous cell carcinoma (ESCC) who underwent R0 resection were enrolled between March 2022 and June 2024. The predictive model was constructed using the XGBoost algorithm combined with Shapley Additive exPlanations (SHAP) for interpretability. Model performance was evaluated via receiver operating characteristic (ROC) curves, decision curve analysis, and net reclassification index.</p>Results<p>The IBS model demonstrated superior discriminative ability in the training cohort (n = 220; area under the receiver operating characteristic curve (AUC) = 0.936; 95% confidence interval (CI): 0.908–0.964) compared to the AJCC ninth edition staging system (ΔAUC = 0.154; p < 0.001). Performance was maintained in validation cohorts. High-risk patients (IBS > 0.5) receiving PD-1 inhibitor plus chemotherapy achieved a pathological complete response (pCR) rate of 28.6%, representing a 115% increase over conventional therapy (p = 0.009).</p>Conclusion<p>The validated IBS model provides high-precision prediction of postoperative LNM risk in ESCC. It offers a novel framework (“tumor antigen burden–lymphangiogenesis–immune microenvironment”) for improving patient risk stratification, guiding adjuvant therapy decisions (including immunotherapy response prediction), and optimizing resource allocation, thereby potentially impacting ESCC management paradigms.</p>2025-11-26T05:15:03ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.3389/fonc.2025.1673946.s003https://figshare.com/articles/dataset/Data_Sheet_1_Integrated_liquid_biopsy_model_for_predicting_metastasis_and_guiding_PD-1_therapy_in_esophageal_squamous_cell_carcinoma_pdf/30717665CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/307176652025-11-26T05:15:03Z
spellingShingle Data Sheet 1_Integrated liquid biopsy model for predicting metastasis and guiding PD-1 therapy in esophageal squamous cell carcinoma.pdf
Hailong Pang (12841991)
Oncology and Carcinogenesis not elsewhere classified
esophageal squamous cell carcinoma
lymphnode metastasis
liquid biopsy
integrated biomarker signature
PD-1 inhibitor
status_str publishedVersion
title Data Sheet 1_Integrated liquid biopsy model for predicting metastasis and guiding PD-1 therapy in esophageal squamous cell carcinoma.pdf
title_full Data Sheet 1_Integrated liquid biopsy model for predicting metastasis and guiding PD-1 therapy in esophageal squamous cell carcinoma.pdf
title_fullStr Data Sheet 1_Integrated liquid biopsy model for predicting metastasis and guiding PD-1 therapy in esophageal squamous cell carcinoma.pdf
title_full_unstemmed Data Sheet 1_Integrated liquid biopsy model for predicting metastasis and guiding PD-1 therapy in esophageal squamous cell carcinoma.pdf
title_short Data Sheet 1_Integrated liquid biopsy model for predicting metastasis and guiding PD-1 therapy in esophageal squamous cell carcinoma.pdf
title_sort Data Sheet 1_Integrated liquid biopsy model for predicting metastasis and guiding PD-1 therapy in esophageal squamous cell carcinoma.pdf
topic Oncology and Carcinogenesis not elsewhere classified
esophageal squamous cell carcinoma
lymphnode metastasis
liquid biopsy
integrated biomarker signature
PD-1 inhibitor