Tumors and inflammatory diseases present formidable challenges worldwide due to their escalating prevalence and significant impact on health systems and economies. Current insights from the Global Burden of Disease (GBD) study reveal that evolving demographic factors and lifestyle shifts are contributing to higher disease incidence and mortality across various regions. To combat these trends, comprehensive research efforts are essential to unravel the intricate pathogenesis of these diseases, and to innovate in therapeutic approaches and preventive strategies.

The advent of multi-omics paired with frontier technologies like single-cell genomics, spatial transcriptomics, and machine learning has paved the way for unprecedented exploration of the molecular underpinnings of tumors and inflammation. These approaches provide a layered understanding of disease landscapes encompassing genetic, proteomic, and metabolomic dimensions while highlighting the heterogeneity embedded within disease environments. Additionally, machine learning offers a robust tool for processing large datasets, identifying subtle patterns, and propelling forward novel discoveries in disease research.

This Research Topic aims to delve into the confluence of advanced technological methodologies with oncological and immunological research to yield actionable insights. By addressing the complex interactions within the immune microenvironment and evaluating resistance mechanisms to existing therapies, we are looking to uncover new therapeutic targets, refine drug sensitivity analysis, and ultimately enhance patient outcomes.

To gather further insights into tumor and inflammation research, we welcome articles addressing, but not limited to, the following themes:
• The correlation between disease burden and molecular mechanisms using GBD data.
• Treatment response and drug sensitivity shaped by immune contexture.
• Discovery and validation of novel targets for immunotherapy.
• Rational combination immunotherapies for overcoming resistance.
• Machine-learning models linking immune features with drug sensitivity and immune-related toxicities.
• Immune cell dynamics within disease ecosystems.
• Translational immunology from bench to bedside.
• Immunology-linked epidemiology for prevention.

Please Note: Manuscripts that rely solely on bioinformatics or computational analysis of public databases without substantial validation (clinical or laboratory-based) fall outside the scope of this Research Topic. Articles on these topics but not related to immunology are out of scope for Frontiers in Immunology.

Are you interested in contributing a manuscript to this Research Topic?

Exploring pathogenesis and immune mechanisms in tumors with multi-omics and innovative technologies