Emerging Techniques of Translational Research in Immuno-Oncology: A Focus on Non-Small Cell Lung Cancer

Abstract

The advent of personalized medicine and novel therapeutic strategies has transformed the treatment landscape of non-small cell lung cancer (NSCLC), significantly improving patient survival. However, only a minority of patients experience a durable benefit, as intrinsic or acquired resistance remains a major challenge. Understanding the complex mechanisms of resistance-linked to tumor biology, the tumor microenvironment (TME), and host factors-is crucial to overcoming these barriers. Recent innovations in diagnostics, including artificial intelligence and liquid biopsy, offer promising tools to refine therapeutic decisions. Machine Learning and Deep Learning provide predictive algorithms that enhance diagnostic accuracy and prognostic assessment. Techniques like single-cell RNA sequencing and pathomics offer deeper insights into the role of the TME. Liquid biopsy, as a minimally invasive method, enables real-time detection of circulating tumor components, facilitating the identification of predictive and prognostic biomarkers and illuminating tumor heterogeneity. These translational research advances are revolutionizing the understanding of cancer biology and are key to optimizing personalized treatment strategies. This review highlights emerging tools aimed at improving diagnostic and therapeutic precision in NSCLC, underscoring their role in decoding the interplay between tumor cells, the TME, and the host to ultimately improve patient outcomes.

Keywords: artificial intelligence; immune biomarkers; immune checkpoint blockers (ICB); liquid biopsy; mechanisms of resistance; non-small cell lung cancer (NSCLC); translational medicine.

Figure 1

Prognostic and predictive biomarkers that have been previously described to impact ICB response in NSCLC. It is shown how the host, the tumor, and its microenvironment might also impact prognosis and response to ICB treatment, generating a complex interplay. Figure created with Biorender.com. NLR = Neutrophil/lymphocyte ratio; dNLR = derived NLR; LDH = Lactate dehydrogenase; LIPI = Lung immune prognostic score; TME = Tumor microenvironment; TILs = Tumor infiltrating lymphocytes; TANs = Tumor infiltrating neutrophils; TAM = Tumor associated macrophages; TMB = Tumor mutational burden; PD-L1 = Programmed-death ligand 1; TNM = Tumor, node, metastasis; SUV = Standardized Uptake Value; MSI-H = Microsatellite instability-high.

Figure 2

New pathology techniques in translational oncology era, which may influence patient approach and treatment strategies. Figure created with Biorender.com. ctDNA = circulating-tumor DNA; ctRNA = circulating-tumor RNA; CTCs = circulating tumor cells; EVs = extracellular vesicles.