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Un modelo de patómica para predecir la respuesta a la quimioinmunoterapia en el carcinoma de pulmón de células

Dongying Wang¹, Shuai Mu², Minghui Zhang³

¹Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; Shanghai Key Laboratory of Thoracic Tumor Biotherapy, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China.

Lung cancer (Amsterdam, Netherlands)

|December 20, 2025

Abstracto

Background:

The identification of lung squamous cell carcinoma (LUSC) patients who may benefit from first-line chemo-immunotherapy (CIT) remains a challenge. This study aimed to develop a pathomics model to predict the T cell-inflamed gene-expression profile (GEP) status and validate its utility in identifying patients who derive survival benefit from CIT.

Methods:

The pathomics model was developed using whole-slide images and RNA-sequencing data from The Cancer Genome Atlas (TCGA) LUSC cohort (n = 334) to predict the GEP status and generate a pathomics score (PS). The predictive value of PS was validated in a prospective, multicenter trial (AK105-302, n = 267) by assessing its interaction with treatment (CIT vs. chemotherapy) for progression-free survival (PFS) and overall survival (OS). Two additional independent cohorts (n = 82 and n = 50) were used for external validation.

Results:

The pathomics model accurately predicted GEP status, achieving area under the curve (AUC) values of 0.80 and 0.71 in the TCGA training and validation sets, respectively. In the AK105-302 cohort, significant interactions were identified between PS and treatment modalities for both PFS (interaction p = 0.011) and OS (interaction p < 0.001). Patients with high PS who received CIT exhibited significantly prolonged PFS (hazard ratio [HR]: 0.31, 95 % confidence interval [CI]: 0.21-0.48, p < 0.001) and OS (HR: 0.30, 95 % CI: 0.18-0.50, p < 0.001) compared to high PS patients receiving chemotherapy. However, this survival benefit was not observed in the low-PS patients. These findings were corroborated in two independent clinical cohorts. Furthermore, biological assessments revealed a significant association between high PS and an immune-hot tumor microenvironment.

Conclusion:

We developed a GEP-based pathomics model that provides a practical, cost-effective strategy to identify patients most likely to derive superior survival benefit from first-line CIT over chemotherapy alone.

Palabras clave:

Biomarcador Quimioinmunoterapia Carcinoma de pulmón de células escamosas Modelo de patómica Perfil de expresión génica de células T inflamadas

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