Early and metastatic breast cancers can exhibit heterogeneity, among patients and even within the same individual. Response to therapy in metastatic breast cancer patients with multiple metastases can also be heterogeneous, with different degrees of responsiveness to the same drug(s) across metastatic sites, termed "mixed response," within the same patient. If the variability of this treatment response is influenced by intrinsic tumor characteristics of metastatic lesions and/or the microenvironment remains unknown. Through genomic analysis of multiple metastases from the same patient, assayed in 6 different patients who had exhibited mixed response on imaging, we identified that higher regulatory T cells (T reg) and CDKN2A gene expression values correlate with non-response, while the KRAS gene, KRAS amplicon, and CD8T cells were associated with response in individual metastases. These genomic features may explain mixed clinical responses and offer valuable insights into intra-patient variations in treatment sensitivity.
UNDERSTANDING METASTASIS MIXED - TREATMENT RESPONSES THROUGH GENOMIC ANALYSES.
ZAGAMI, PAOLA
2024
Abstract
Early and metastatic breast cancers can exhibit heterogeneity, among patients and even within the same individual. Response to therapy in metastatic breast cancer patients with multiple metastases can also be heterogeneous, with different degrees of responsiveness to the same drug(s) across metastatic sites, termed "mixed response," within the same patient. If the variability of this treatment response is influenced by intrinsic tumor characteristics of metastatic lesions and/or the microenvironment remains unknown. Through genomic analysis of multiple metastases from the same patient, assayed in 6 different patients who had exhibited mixed response on imaging, we identified that higher regulatory T cells (T reg) and CDKN2A gene expression values correlate with non-response, while the KRAS gene, KRAS amplicon, and CD8T cells were associated with response in individual metastases. These genomic features may explain mixed clinical responses and offer valuable insights into intra-patient variations in treatment sensitivity.File | Dimensione | Formato | |
---|---|---|---|
phd_unimi_R13404.pdf
embargo fino al 09/06/2025
Dimensione
4.2 MB
Formato
Adobe PDF
|
4.2 MB | Adobe PDF |
I documenti in UNITESI sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/20.500.14242/188123
URN:NBN:IT:UNIMI-188123