Genomic and micro-environmental insights into drug resistance in colorectal cancer liver metastases DOI Creative Commons
Junjie Kuang, Jun Li, Siwei Zhou

et al.

Discover Oncology, Journal Year: 2025, Volume and Issue: 16(1)

Published: Feb. 26, 2025

Colorectal cancer (CRC) is known for its high heterogeneity, with liver metastases significantly impairing survival outcomes. Understanding the tumor microenvironment (TME) and genomic alterations in metastatic sites crucial developing personalized therapies that overcome drug resistance improve prognosis. We profiled 54 CRC metastases, comparing them 198 other lesions normal tissues. By analyzing immune cell infiltration, stromal interactions, key alterations, we constructed an 11-gene prognostic model to predict immunotherapy high-risk profiles demonstrated enriched follicular helper T cells, activated dendritic M2 macrophages TME. Frequent mutations APC, TP53, KRAS, PIK3CA were identified, alongside altered EGFR signaling. The effectively stratified patients by prognosis predicted responses, emphasizing therapeutic potential of targeting mechanisms. This study reveals how TME-driven factors contribute metastases. Integrating these insights clinical data could advance precision therapies, addressing evolving challenge CRC.

Language: Английский

Genomic and micro-environmental insights into drug resistance in colorectal cancer liver metastases DOI Creative Commons
Junjie Kuang, Jun Li, Siwei Zhou

et al.

Discover Oncology, Journal Year: 2025, Volume and Issue: 16(1)

Published: Feb. 26, 2025

Colorectal cancer (CRC) is known for its high heterogeneity, with liver metastases significantly impairing survival outcomes. Understanding the tumor microenvironment (TME) and genomic alterations in metastatic sites crucial developing personalized therapies that overcome drug resistance improve prognosis. We profiled 54 CRC metastases, comparing them 198 other lesions normal tissues. By analyzing immune cell infiltration, stromal interactions, key alterations, we constructed an 11-gene prognostic model to predict immunotherapy high-risk profiles demonstrated enriched follicular helper T cells, activated dendritic M2 macrophages TME. Frequent mutations APC, TP53, KRAS, PIK3CA were identified, alongside altered EGFR signaling. The effectively stratified patients by prognosis predicted responses, emphasizing therapeutic potential of targeting mechanisms. This study reveals how TME-driven factors contribute metastases. Integrating these insights clinical data could advance precision therapies, addressing evolving challenge CRC.

Language: Английский

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