Transcriptional regulatory network analysis identifies GRN as a key regulator bridging chemotherapy and immunotherapy response in small cell lung cancer
Abstract Small cell lung cancer (SCLC) is an aggressive and heterogeneous subtype, representing 15% of lung cancer cases. Although SCLC initially responds to etoposide and platinum (EP) chemotherapy, nearly all patients relapse with resistant tumors. While recent advances in immunotherapy have shown...
Saved in:
Main Authors: | , , , , , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2025-02-01
|
Series: | Journal of Hematology & Oncology |
Online Access: | https://doi.org/10.1186/s13045-025-01667-5 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
_version_ | 1823861638616317952 |
---|---|
author | Seungyeul Yoo Ayushi S. Patel Sarah Karam Yi Zhong Li Wang Feng Jiang Ranran Kong Sharon Bikvan Wenhui Wang Abhilasha Sinha Charles A. Powell Jun Zhu Hideo Watanabe |
author_facet | Seungyeul Yoo Ayushi S. Patel Sarah Karam Yi Zhong Li Wang Feng Jiang Ranran Kong Sharon Bikvan Wenhui Wang Abhilasha Sinha Charles A. Powell Jun Zhu Hideo Watanabe |
author_sort | Seungyeul Yoo |
collection | DOAJ |
description | Abstract Small cell lung cancer (SCLC) is an aggressive and heterogeneous subtype, representing 15% of lung cancer cases. Although SCLC initially responds to etoposide and platinum (EP) chemotherapy, nearly all patients relapse with resistant tumors. While recent advances in immunotherapy have shown promise, only 10–20% of patients benefit, and effective stratification methods are lacking. The mechanisms of resistance to both therapeutics remain obscure. In this study, we aimed to gain insights into those leveraging a recent surge in the field of SCLC genomics. We constructed a regulatory network for SCLC and identified granulin precursor (GRN) as a hub of EP response associated genes. GRN-low patients showed improved survival with chemotherapy, while GRN-high patients exhibited resistance. GRN overexpression in SCLC cells conferred resistance to EP treatment and suppressed neuroendocrine features. GRN and its associated genes were linked to cancer cell intrinsic immunogenicity, and single-cell RNA-seq data revealed that GRN expression is particularly high in subsets of tumor-associated macrophages. In concordance with these findings, GRN-low tumors showed significantly better survival with chemo-immunotherapy, while GRN-high tumors did not benefit from additional immunotherapy. GRN-high tumors, associated with non-neuroendocrine (non-NE) subtypes, had a higher level of macrophage infiltration, potentially contributing to immunotherapy resistance. These results highlight GRN as a critical regulator of chemo-resistance and a potential biomarker for immunotherapy resistance in SCLC. Targeted therapeutic strategies for GRN-low patients could improve outcomes, while new approaches are needed for GRN-high patients. Overall, our findings implicate GRN as a bridge between chemotherapy and immunotherapy resistance through GRN-mediated mechanisms. |
format | Article |
id | doaj-art-595c95af260b48498f4f3cd3f5cca801 |
institution | Kabale University |
issn | 1756-8722 |
language | English |
publishDate | 2025-02-01 |
publisher | BMC |
record_format | Article |
series | Journal of Hematology & Oncology |
spelling | doaj-art-595c95af260b48498f4f3cd3f5cca8012025-02-09T12:51:22ZengBMCJournal of Hematology & Oncology1756-87222025-02-011811610.1186/s13045-025-01667-5Transcriptional regulatory network analysis identifies GRN as a key regulator bridging chemotherapy and immunotherapy response in small cell lung cancerSeungyeul Yoo0Ayushi S. Patel1Sarah Karam2Yi Zhong3Li Wang4Feng Jiang5Ranran Kong6Sharon Bikvan7Wenhui Wang8Abhilasha Sinha9Charles A. Powell10Jun Zhu11Hideo Watanabe12GeneDxDivision of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount SinaiDivision of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount SinaiGeneDxGeneDxDivision of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount SinaiDivision of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount SinaiDivision of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount SinaiGeneDxDivision of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount SinaiDivision of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount SinaiGeneDxDivision of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount SinaiAbstract Small cell lung cancer (SCLC) is an aggressive and heterogeneous subtype, representing 15% of lung cancer cases. Although SCLC initially responds to etoposide and platinum (EP) chemotherapy, nearly all patients relapse with resistant tumors. While recent advances in immunotherapy have shown promise, only 10–20% of patients benefit, and effective stratification methods are lacking. The mechanisms of resistance to both therapeutics remain obscure. In this study, we aimed to gain insights into those leveraging a recent surge in the field of SCLC genomics. We constructed a regulatory network for SCLC and identified granulin precursor (GRN) as a hub of EP response associated genes. GRN-low patients showed improved survival with chemotherapy, while GRN-high patients exhibited resistance. GRN overexpression in SCLC cells conferred resistance to EP treatment and suppressed neuroendocrine features. GRN and its associated genes were linked to cancer cell intrinsic immunogenicity, and single-cell RNA-seq data revealed that GRN expression is particularly high in subsets of tumor-associated macrophages. In concordance with these findings, GRN-low tumors showed significantly better survival with chemo-immunotherapy, while GRN-high tumors did not benefit from additional immunotherapy. GRN-high tumors, associated with non-neuroendocrine (non-NE) subtypes, had a higher level of macrophage infiltration, potentially contributing to immunotherapy resistance. These results highlight GRN as a critical regulator of chemo-resistance and a potential biomarker for immunotherapy resistance in SCLC. Targeted therapeutic strategies for GRN-low patients could improve outcomes, while new approaches are needed for GRN-high patients. Overall, our findings implicate GRN as a bridge between chemotherapy and immunotherapy resistance through GRN-mediated mechanisms.https://doi.org/10.1186/s13045-025-01667-5 |
spellingShingle | Seungyeul Yoo Ayushi S. Patel Sarah Karam Yi Zhong Li Wang Feng Jiang Ranran Kong Sharon Bikvan Wenhui Wang Abhilasha Sinha Charles A. Powell Jun Zhu Hideo Watanabe Transcriptional regulatory network analysis identifies GRN as a key regulator bridging chemotherapy and immunotherapy response in small cell lung cancer Journal of Hematology & Oncology |
title | Transcriptional regulatory network analysis identifies GRN as a key regulator bridging chemotherapy and immunotherapy response in small cell lung cancer |
title_full | Transcriptional regulatory network analysis identifies GRN as a key regulator bridging chemotherapy and immunotherapy response in small cell lung cancer |
title_fullStr | Transcriptional regulatory network analysis identifies GRN as a key regulator bridging chemotherapy and immunotherapy response in small cell lung cancer |
title_full_unstemmed | Transcriptional regulatory network analysis identifies GRN as a key regulator bridging chemotherapy and immunotherapy response in small cell lung cancer |
title_short | Transcriptional regulatory network analysis identifies GRN as a key regulator bridging chemotherapy and immunotherapy response in small cell lung cancer |
title_sort | transcriptional regulatory network analysis identifies grn as a key regulator bridging chemotherapy and immunotherapy response in small cell lung cancer |
url | https://doi.org/10.1186/s13045-025-01667-5 |
work_keys_str_mv | AT seungyeulyoo transcriptionalregulatorynetworkanalysisidentifiesgrnasakeyregulatorbridgingchemotherapyandimmunotherapyresponseinsmallcelllungcancer AT ayushispatel transcriptionalregulatorynetworkanalysisidentifiesgrnasakeyregulatorbridgingchemotherapyandimmunotherapyresponseinsmallcelllungcancer AT sarahkaram transcriptionalregulatorynetworkanalysisidentifiesgrnasakeyregulatorbridgingchemotherapyandimmunotherapyresponseinsmallcelllungcancer AT yizhong transcriptionalregulatorynetworkanalysisidentifiesgrnasakeyregulatorbridgingchemotherapyandimmunotherapyresponseinsmallcelllungcancer AT liwang transcriptionalregulatorynetworkanalysisidentifiesgrnasakeyregulatorbridgingchemotherapyandimmunotherapyresponseinsmallcelllungcancer AT fengjiang transcriptionalregulatorynetworkanalysisidentifiesgrnasakeyregulatorbridgingchemotherapyandimmunotherapyresponseinsmallcelllungcancer AT ranrankong transcriptionalregulatorynetworkanalysisidentifiesgrnasakeyregulatorbridgingchemotherapyandimmunotherapyresponseinsmallcelllungcancer AT sharonbikvan transcriptionalregulatorynetworkanalysisidentifiesgrnasakeyregulatorbridgingchemotherapyandimmunotherapyresponseinsmallcelllungcancer AT wenhuiwang transcriptionalregulatorynetworkanalysisidentifiesgrnasakeyregulatorbridgingchemotherapyandimmunotherapyresponseinsmallcelllungcancer AT abhilashasinha transcriptionalregulatorynetworkanalysisidentifiesgrnasakeyregulatorbridgingchemotherapyandimmunotherapyresponseinsmallcelllungcancer AT charlesapowell transcriptionalregulatorynetworkanalysisidentifiesgrnasakeyregulatorbridgingchemotherapyandimmunotherapyresponseinsmallcelllungcancer AT junzhu transcriptionalregulatorynetworkanalysisidentifiesgrnasakeyregulatorbridgingchemotherapyandimmunotherapyresponseinsmallcelllungcancer AT hideowatanabe transcriptionalregulatorynetworkanalysisidentifiesgrnasakeyregulatorbridgingchemotherapyandimmunotherapyresponseinsmallcelllungcancer |