Solid tumors are characterized by significant molecular and cellular heterogeneity, conferring adaptive plasticity and enabling diverse resistance mechanisms that substantially reduce the effectiveness of current cancer therapies. Despite substantial advancements in chemotherapy, targeted therapies, radiotherapy, and immunotherapy, clinical outcomes are frequently limited by drug resistance, tumor relapse, and unintended toxicities. Recently, multi-omics approaches, including genomic, transcriptomic, proteomic, and epigenomic analyses, alongside single-cell sequencing technologies, have emerged as critical tools for understanding the dynamics of tumor evolution and resistance mechanisms. Single-cell sequencing in particular provides unprecedented insights into rare, resistant tumor subpopulations, and multi-omic integration has begun to identify molecular signatures relevant for therapeutic intervention. Yet, significant gaps remain in our ability to fully integrate molecular signatures with actionable clinical strategies and to translate these complex data streams effectively for routine clinical use.
This Research Topic aims to leverage advanced multi-omics and single-cell sequencing technologies to thoroughly dissect the mechanisms underlying therapeutic resistance in solid tumors and thereby refine precision oncology strategies. The key aims include identifying pan-cancer and tumor-type-specific mechanisms of treatment resistance, discovering predictive biomarkers to guide therapy selection and manage toxicity, creating advanced computational frameworks to integrate complex multi-omics datasets into adaptive clinical decision-making, and fostering development of innovative therapeutic strategies (such as drug repurposing, epigenetic modulation, or nanoparticle drug delivery), guided explicitly by single-cell and multi-dimensional molecular characterization.
To gather further insights within the context of solid tumors and translational applicability, we welcome articles addressing, but not limited to, the following themes:
• Single-cell and spatial multi-omics analyses elucidating tumor heterogeneity and therapy-induced clonal selection across carcinoma, sarcoma, and metastatic disease. • Mechanistic investigations into resistance pathways, such as altered DNA repair mechanisms, metabolic adaptations, or drug efflux processes. • Application of multi-omics approaches to optimize existing treatments, individualize chemotherapy schedules, targeted therapy sequencing, and radiation protocol refinement. • Development and validation of computational models capable of predicting effective drug combinations, patient-specific therapeutic responses, and resistance evolution patterns. • Integration of emerging technologies including CRISPR screens, liquid biopsy diagnostics, and artificial intelligence-driven drug discovery platforms within precision oncology. • Translational implementation of multi-omics biomarker profiling in clinical trials, patient stratification approaches, and practical management of solid tumor patients.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Classification
Clinical Trial
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Hypothesis and Theory
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
