Molecular and Immune Phenotypic Modifications during Metastatic Dissemination in Lung Carcinogenesis.
Drosos TsavlisTheodora KatopodiDoxakis AnestakisSavvas PetanidisCharalampos CharalampidisEvmorfia ChatzifotiouPanagiotis EskitzisPavlos ZarogoulidisKonstantinos PorpodisPublished in: Cancers (2022)
The tumor microenvironment plays a key role in the progression of lung tumorigenesis, progression, and metastasis. Recent data reveal that disseminated tumor cells (DTCs) appear to play a key role in the development and progression of lung neoplasiaby driving immune system dysfunction and established immunosuppression, which is vital for evading the host immune response. As a consequence, in this review we will discuss the role and function of DTCs in immune cell signaling routes which trigger drug resistance and immunosuppression. We will also discuss the metabolic biology of DTCs, their dormancy, and their plasticity, which are critical for metastasis and drive lung tumor progression. Furthermore, we will consider the crosstalk between DTCs and myeloid cells in tumor-related immunosuppression. Specifically, we will investigate the molecular immune-related mechanisms in the tumor microenvironment that lead to decreased drug sensitivity and tumor relapse, along with strategies for reversing drug resistance and targeting immunosuppressive tumor networks. Deciphering these molecular mechanisms is essential for preclinical and clinical investigations in order to enhance therapeutic efficacy. Furthermore, a better understanding of these immune cell signaling pathways that drive immune surveillance, immune-driven inflammation, and tumor-related immunosuppression is necessary for future personalized therapeutic approaches.
Keyphrases
- immune response
- induced apoptosis
- oxidative stress
- signaling pathway
- public health
- small cell lung cancer
- dendritic cells
- squamous cell carcinoma
- acute myeloid leukemia
- dna methylation
- poor prognosis
- bone marrow
- electronic health record
- epithelial mesenchymal transition
- machine learning
- big data
- current status
- artificial intelligence
- genome wide