Two Different Immune Profiles Are Identified in Sentinel Lymph Nodes of Early-Stage Breast Cancer.
Joana Martins RibeiroJoão MendesInês GanteMargarida Figueiredo DiasVânia AlmeidaAna GomesFernando Jesus RegateiroFrederico Soares RegateiroFrancisco José CarameloHenriqueta Coimbra SilvaPublished in: Cancers (2024)
In the management of early-stage breast cancer (BC), lymph nodes (LNs) are typically characterised using the One-Step Nucleic Acid Amplification (OSNA) assay, a standard procedure for assessing subclinical metastasis in sentinel LNs (SLNs). The pivotal role of LNs in coordinating the immune response against BC is often overlooked. Our aim was to improve prognostic information provided by the OSNA assay and explore immune-related gene signatures in SLNs. The expression of an immune gene panel was analysed in SLNs from 32 patients with Luminal A early-stage BC (cT1-T2 N0). Using an unsupervised approach based on these expression values, this study identified two clusters, regardless of the SLN invasion: one evidencing an adaptive anti-tumoral immune response, characterised by an increase in naive B cells, follicular T helper cells, and activated NK cells; and another with a more undifferentiated response, with an increase in the activated-to-resting dendritic cells (DCs) ratio. Through a protein-protein interaction (PPI) network, we identified seven immunoregulatory hub genes: CD80 , CD40 , TNF , FCGR3A , CD163 , FCGR3B , and CCR2 . This study shows that, in Luminal A early-stage BC, SLNs gene expression studies enable the identification of distinct immune profiles that may influence prognosis stratification and highlight key genes that could serve as potential targets for immunotherapy.
Keyphrases
- early stage
- dendritic cells
- immune response
- lymph node
- sentinel lymph node
- genome wide
- nucleic acid
- protein protein
- gene expression
- poor prognosis
- genome wide identification
- nk cells
- bioinformatics analysis
- regulatory t cells
- dna methylation
- high throughput
- machine learning
- copy number
- magnetic resonance imaging
- minimally invasive
- heart rate
- healthcare
- induced apoptosis
- toll like receptor
- cell death
- blood pressure
- cell cycle arrest
- heart rate variability
- neoadjuvant chemotherapy
- hiv infected
- inflammatory response
- image quality
- network analysis
- cell migration
- climate change
- health information