Integrated immune gene expression signature and molecular classification in gastric cancer: New insights.
Maria Grazia RefoloClaudio LotesoriereCaterina MessaMaria Gabriella CarusoRosalba D'AlessandroPublished in: Journal of leukocyte biology (2020)
Gastric cancer (GC) is characterized by extreme heterogeneity due to histopathological differences, molecular characteristics, and immune gene expression signature. Until recently, several targeted therapies failed due to this complexity. The recent immunotherapy resulted in more effective and safe approaches in several malignancies. All tumors could be considered potentially immunogenic and the new knowledge regarding the interactions among tumor cells, immune cells, and tumor microenvironment (TME) allowed to reverse possible immune resistance. The immune response is a complex multisteps process that finely regulates the balance between the recognition of non-self and the prevention of autoimmunity. Cancer cells can use these pathways to suppress tumor immunity as a major mechanism of immune resistance. The recent molecular classifications of GCs by The Cancer Genome Atlas (TCGA) and by the Asian Cancer Research (ACRG) networks, together with the identification of multiple biomarkers, open new perspectives for stratification of patients who might benefit from a long-term immune checkpoint therapy. One of the major processes that contribute to an immunosuppressive microenvironment is represented by tumor angiogenesis. The cellular mechanisms inducing both angiogenesis and immunosuppressive responses are often reached by the same cell types and soluble factors, such as vascular endothelial growth factor A (VEGFA). Recent studies point out that combinatorial strategies should be adapted as useful therapeutic approach to reverse the immunosuppressive status of microenvironment occurring in a relevant percentage of gastric tumors.
Keyphrases
- vascular endothelial growth factor
- gene expression
- single cell
- immune response
- endothelial cells
- papillary thyroid
- dna methylation
- stem cells
- squamous cell
- healthcare
- machine learning
- deep learning
- minimally invasive
- climate change
- cell therapy
- mesenchymal stem cells
- young adults
- dendritic cells
- inflammatory response
- genome wide
- bone marrow
- wound healing