Immune profiling of vulvar squamous cell cancer discovers a macrophage-rich subtype associated with poor prognosis.
Mateja CondicAndrea RohrSoheila RiemannChristian StaerkTiyasha H AyubAnna DoeserThomas ZillingerSabine Merkelbach-BruseReinhard ButtnerWinfried BarchetChristian RudlowskiAlexander MusteaKirsten KüblerPublished in: Cancer research communications (2024)
The incidence rates of vulvar squamous cell cancer (VSCC) have increased over the past decades, requiring personalized oncologic approaches. Currently, lymph node involvement is a key factor in determining prognosis and treatment options. However, there is a need for additional immune-related biomarkers to provide more precise treatment and prognostic information. Here, we used immunohistochemistry and expression data to characterize immune cells and their spatial distribution in VSCC. Hierarchical clustering analysis identified distinct immune subtypes, of which the macrophage-rich subtype was associated with adverse outcome. This is consistent with our findings of increased lymphogenesis, lymphatic invasion, and lymph node involvement associated with high macrophage infiltration. Further in vitro studies showed that VSCC-associated macrophages expressed vascular endothelial growth factor A (VEGF-A) and subsequently induced VEGF-A in the VSCC cell line A-431, providing experimental support for a pro-lymphangiogenic role of macrophages in VSCC. Taken together, immune profiling in VSCC revealed tumor processes, identified a subset of patients with adverse outcome and provided a valuable biomarker for risk stratification and therapeutic decision making for anti-VEGF treatment, ultimately contributing to the advancement of precision medicine in VSCC.
Keyphrases
- squamous cell
- vascular endothelial growth factor
- poor prognosis
- lymph node
- endothelial cells
- long non coding rna
- sentinel lymph node
- single cell
- adipose tissue
- decision making
- papillary thyroid
- prostate cancer
- high glucose
- emergency department
- rna seq
- radiation therapy
- electronic health record
- risk factors
- minimally invasive
- machine learning
- deep learning
- adverse drug
- anti inflammatory
- cell migration
- binding protein
- artificial intelligence
- data analysis
- case control