Digital Spatial Profiling to Predict Recurrence in Grade 3 Stage I Lung Adenocarcinoma

医学 腺癌 阶段(地层学) 生存分析 肿瘤科 聚类分析 内科学 辅助治疗 癌症 生物 古生物学 机器学习 计算机科学
作者
Stephanie H. Chang,Valeria Mezzano-Robinson,Hua Zhou,André L. Moreira,Raymond Pillai,Sitharam Ramaswami,Cynthia A. Loomis,Adriana Heguy,Aristotelis Tsirigos,Harvey I. Pass
出处
期刊:The Journal of Thoracic and Cardiovascular Surgery [American Association for Thoracic Surgery]
标识
DOI:10.1016/j.jtcvs.2023.10.047
摘要

Objective Early-stage lung adenocarcinoma (LUAD) is treated with local therapy alone, though patients with grade 3 stage I LUAD a 50% 5-year recurrence rate. Our objective is to determine if analysis of the tumor microenvironment can create a predictive model for recurrence. Methods Thirty-four grade 3 stage I LUAD patients underwent surgical resection. Digital spatial profiling was utilized to perform genomic (n=31) and proteomic (n=34) analysis of pancytokeratin positive (PanCK+) and negative (PanCK-) tumor cells. K-means clustering was performed on the top 50 differential genes and top 20 differential proteins, with Kaplan-Meier recurrence curves based on patient clustering. External validation of high expression genes was performed with Kaplan-Meier Plotter. Results There were no significant clinicopathologic differences between patients who did (n=14) and did not (n=20) recur. Median time to recurrence was 806 days; median follow up with no recurrence was 2897 days. K-means clustering of PanCK+ genes resulted in a model with a Kaplan-Meier curve with C-index of 0.75. K-means clustering for PanCK- genes was less successful at differentiating recurrence (C-index 0.6). Genes upregulated or downregulated for recurrence were externally validated using available public databases. Proteomic data did not reach statistical significance but did internally validate the genomic data described above. Conclusions Genomic difference in LUAD may be able to predict risk of recurrence. After further validation, stratifying patients by this risk may help guide who will benefit from adjuvant therapy. Early-stage lung adenocarcinoma (LUAD) is treated with local therapy alone, though patients with grade 3 stage I LUAD a 50% 5-year recurrence rate. Our objective is to determine if analysis of the tumor microenvironment can create a predictive model for recurrence. Thirty-four grade 3 stage I LUAD patients underwent surgical resection. Digital spatial profiling was utilized to perform genomic (n=31) and proteomic (n=34) analysis of pancytokeratin positive (PanCK+) and negative (PanCK-) tumor cells. K-means clustering was performed on the top 50 differential genes and top 20 differential proteins, with Kaplan-Meier recurrence curves based on patient clustering. External validation of high expression genes was performed with Kaplan-Meier Plotter. There were no significant clinicopathologic differences between patients who did (n=14) and did not (n=20) recur. Median time to recurrence was 806 days; median follow up with no recurrence was 2897 days. K-means clustering of PanCK+ genes resulted in a model with a Kaplan-Meier curve with C-index of 0.75. K-means clustering for PanCK- genes was less successful at differentiating recurrence (C-index 0.6). Genes upregulated or downregulated for recurrence were externally validated using available public databases. Proteomic data did not reach statistical significance but did internally validate the genomic data described above. Genomic difference in LUAD may be able to predict risk of recurrence. After further validation, stratifying patients by this risk may help guide who will benefit from adjuvant therapy.

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