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Background <p>The efficacy of immune checkpoint inhibitor plus chemotherapy (ICI-chemo) following third-generation EGFR-TKI resistance in EGFR-mutant lung adenocarcinoma (LUAD) is variable and lacks reliable predictive biomarkers. This study investigated associations between treatment-naïve primary tumor transcriptomic profiles, tumor immune microenvironment (TIME) characteristics, and subsequent ICI-chemo efficacy.</p> Methods <p>This retrospective study enrolled 12 advanced LUAD patients who received ICI-chemo after progressing on third-generation EGFR-TKIs. Patients were stratified into Better (<i>N</i> = 7) and Worse (<i>N</i> = 5) efficacy groups using 6-month progression-free survival (PFS) as cutoff. Treatment-naïve tumor specimens were analyzed using Digital Spatial Profiling (DSP) whole transcriptome sequencing and multiplex immunofluorescence (mIF) to assess compartment-specific gene expression, pathway enrichment, and infiltration of 19 immune cell types. LASSO-Cox regression was performed to identify key prognostic genes.</p> Results <p><i>SFTPC</i> expression was significantly elevated across all compartments in the Worse efficacy group. Enrichment analysis revealed that the efficacy of ICI-chemo in EGFR-mutant patients arises from a combination of proliferative tumor cells and an activated TIME. A total of eight key prognostic genes were identified: <i>DNM1L</i>_Immune, <i>ADPGK</i>_Immune, <i>SLC12A4</i>_Stroma, <i>PLA2G6</i>_Immune, <i>FKBP1A</i>_Immune, <i>CHST15</i>_Tumor, <i>TRMT5</i>_Immune, <i>TAX1BP1</i>_Immune. Complex correlations were observed between these key genes and the expression of immune checkpoints. mIF revealed significantly higher infiltration of cancer-associated fibroblast subtype I (CAFI) in the Worse group, while the Better efficacy group exhibited a more activated antitumor TIME.</p> Conclusions <p>Baseline upregulation of <i>SFTPC</i>, enrichment of CAFI, and specific immune checkpoint expression patterns are associated with poor response to ICI-chemo following EGFR-TKI resistance in EGFR-mutant LUAD. The eight spatially resolved genes identified may serve as potential predictive biomarkers for patient stratification. These findings underscore the functional interdependence between tumor-intrinsic properties and TIME characteristics in determining immunotherapy outcomes, and provide biologically plausible candidates warranting independent validation in larger cohorts.</p>

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Biomarker exploration for immunotherapy plus chemotherapy following resistance to third-generation EGFR-TKIs in lung adenocarcinoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月14日

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  • Lige Wu,
  • Tongji Xie,
  • Yan Li,
  • Xuezhi Hao,
  • Xin Zhang,
  • Jianming Ying,
  • Junling Li,
  • Puyuan Xing

摘要

Background

The efficacy of immune checkpoint inhibitor plus chemotherapy (ICI-chemo) following third-generation EGFR-TKI resistance in EGFR-mutant lung adenocarcinoma (LUAD) is variable and lacks reliable predictive biomarkers. This study investigated associations between treatment-naïve primary tumor transcriptomic profiles, tumor immune microenvironment (TIME) characteristics, and subsequent ICI-chemo efficacy.

Methods

This retrospective study enrolled 12 advanced LUAD patients who received ICI-chemo after progressing on third-generation EGFR-TKIs. Patients were stratified into Better (N = 7) and Worse (N = 5) efficacy groups using 6-month progression-free survival (PFS) as cutoff. Treatment-naïve tumor specimens were analyzed using Digital Spatial Profiling (DSP) whole transcriptome sequencing and multiplex immunofluorescence (mIF) to assess compartment-specific gene expression, pathway enrichment, and infiltration of 19 immune cell types. LASSO-Cox regression was performed to identify key prognostic genes.

Results

SFTPC expression was significantly elevated across all compartments in the Worse efficacy group. Enrichment analysis revealed that the efficacy of ICI-chemo in EGFR-mutant patients arises from a combination of proliferative tumor cells and an activated TIME. A total of eight key prognostic genes were identified: DNM1L_Immune, ADPGK_Immune, SLC12A4_Stroma, PLA2G6_Immune, FKBP1A_Immune, CHST15_Tumor, TRMT5_Immune, TAX1BP1_Immune. Complex correlations were observed between these key genes and the expression of immune checkpoints. mIF revealed significantly higher infiltration of cancer-associated fibroblast subtype I (CAFI) in the Worse group, while the Better efficacy group exhibited a more activated antitumor TIME.

Conclusions

Baseline upregulation of SFTPC, enrichment of CAFI, and specific immune checkpoint expression patterns are associated with poor response to ICI-chemo following EGFR-TKI resistance in EGFR-mutant LUAD. The eight spatially resolved genes identified may serve as potential predictive biomarkers for patient stratification. These findings underscore the functional interdependence between tumor-intrinsic properties and TIME characteristics in determining immunotherapy outcomes, and provide biologically plausible candidates warranting independent validation in larger cohorts.