About this Research Topic
This Research Topic aims to develop a novel risk evaluation system related to target and immunotherapy resistance at the multi-omics level, which might improve the design and outcome of clinical studies. We also encourage exploring the heterogeneity of urological cancers at the multi-omics level, single-cell sequence, patient-derived tumor xenograft model, and retrospective or prospective cohorts with the application of machine learning algorithms to better understand the perturbation of tumor microenvironment components. We welcome submissions covering but not limited to the following sub-topics:
1) Novel molecular subtypes of tumors benefiting precision medicine for urologic cancers.
2) Novel molecular mechanisms to predict sensitivity to targeted therapy, immunotherapy, and/or combination therapy.
3) Metabolism mechanisms in targeted therapy, immunotherapy, and/or combination therapy for urologic cancers.
4) Discovery of novel cell subcluster involved in therapy resistance by combining bulk sequencing and single cell sequencing.
Please note: manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.
All other Guest Editors declare no competing interests with regards to the Research Topic subject.
Keywords: targeted therapy, immunotherapy, resistance, combination therapy, urologic tumors, tumor heterogeneity
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.