Mechanism exploration and model construction for small cell transformation in EGFR-mutant lung adenocarcinomas

Small-cell lung cancer (SCLC) transformation accounts for 3-14% of resistance in EGFR-TKI relapsed lung adenocarcinomas (LUADs), with unknown molecular mechanisms and optimal treatment strategies. We performed transcriptomic analyses (including bulk and spatial transcriptomics) and multiplex immunofluorescence on pre-treated samples from LUADs without transformation after EGFR-TKI treatment (LUAD-NT), primary SCLCs (SCLC-P) and LUADs with transformation after EGFR-TKI treatment (before transformation: LUAD-BT; after transformation: SCLC-AT). Our study found that LUAD-BT exhibited potential transcriptomic characteristics for transformation compared with LUAD-NT. We identified several pathways that shifted during transformation, and the transformation might be promoted by epigenetic alterations (such as HDAC10, HDAC1, DNMT3A) within the tumor cells instead of within the tumor microenvironment. For druggable pathways, transformed-SCLC were proved to be less dependent on EGF signaling but more relied on FGF signaling, while VEGF-VEGFR pathway remained active, indicating potential treatments after transformation. We also found transformed-SCLC showed an immuno-exhausted status which was associated with the duration of EGFR-TKI before transformation. Besides, SCLC-AT exhibited distinct molecular subtypes from SCLC-P. Moreover, we constructed an ideal 4-marker model based on transcriptomic and IHC data to predict SCLC transformation, which obtained a sensitivity of 100% and 87.5%, a specificity of 95.7% and 100% in the training and test cohorts, respectively. We provided insights into the molecular mechanisms of SCLC transformation and the differences between SCLC-AT and SCLC-P, which might shed light on prevention strategies and subsequent therapeutic strategies for SCLC transformation in the future.

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Publication Details

Journal
Signal Transduction and Targeted Therapy
Published
2024-10-02
DOI
https://doi.org/10.1038/s41392-024-01981-3
Citations
17
Primary Topic
Lung Cancer Research Studies
Type
article
Field-Weighted Citation Impact
4.80

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article

Mechanism exploration and model construction for small cell transformation in EGFR-mutant lung adenocarcinomas

Jianming Ying, Shouzheng Wang, Puyuan Xing, Tongji Xie et al.
17 citations
Signal Transduction and Targeted Therapy
Lung Cancer Research Studies
4.80
article

Mechanism exploration and model construction for small cell transformation in EGFR-mutant lung adenocarcinomas

Jianming Ying, Shouzheng Wang, Puyuan Xing, Tongji Xie, Xingsheng Hu, Xuezhi Hao, Junling Li, Lin Yang, Yan Li, Lin Wang, Yan Wang
article en
17 citations

Abstract

Small-cell lung cancer (SCLC) transformation accounts for 3-14% of resistance in EGFR-TKI relapsed lung adenocarcinomas (LUADs), with unknown molecular mechanisms and optimal treatment strategies. We performed transcriptomic analyses (including bulk and spatial transcriptomics) and multiplex immunofluorescence on pre-treated samples from LUADs without transformation after EGFR-TKI treatment (LUAD-NT), primary SCLCs (SCLC-P) and LUADs with transformation after EGFR-TKI treatment (before transformation: LUAD-BT; after transformation: SCLC-AT). Our study found that LUAD-BT exhibited potential transcriptomic characteristics for transformation compared with LUAD-NT. We identified several pathways that shifted during transformation, and the transformation might be promoted by epigenetic alterations (such as HDAC10, HDAC1, DNMT3A) within the tumor cells instead of within the tumor microenvironment. For druggable pathways, transformed-SCLC were proved to be less dependent on EGF signaling but more relied on FGF signaling, while VEGF-VEGFR pathway remained active, indicating potential treatments after transformation. We also found transformed-SCLC showed an immuno-exhausted status which was associated with the duration of EGFR-TKI before transformation. Besides, SCLC-AT exhibited distinct molecular subtypes from SCLC-P. Moreover, we constructed an ideal 4-marker model based on transcriptomic and IHC data to predict SCLC transformation, which obtained a sensitivity of 100% and 87.5%, a specificity of 95.7% and 100% in the training and test cohorts, respectively. We provided insights into the molecular mechanisms of SCLC transformation and the differences between SCLC-AT and SCLC-P, which might shed light on prevention strategies and subsequent therapeutic strategies for SCLC transformation in the future.

Signal Transduction and Targeted TherapyVol. 9(1)
Capital Medical University (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), National Cancer Center (US), Beijing Chest Hospital (CN)
National Natural Science Foundation of China, Chinese Academy of Medical Sciences, Cancer Institute and Hospital, Chinese Academy of Medical Sciences
Good health and well-being
Openalex Percentile: Top 4%
Lung Cancer Research Studies
4.80
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