Cell–cell interactions orchestrate organismal development, homeostasis and single-cell
functions. When cells do not properly interact or improperly decode molecular messages …

Artificial intelligence (AI) is rapidly reshaping cancer research and personalized clinical
care. Availability of high-dimensionality datasets coupled with advances in high …

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing
with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However …

Cancer represents an evolutionary process through which growing malignant populations
genetically diversify, leading to tumour progression, relapse and resistance to therapy. In …

Biological heterogeneity in diffuse large B cell lymphoma (DLBCL) is partly driven by cell-of-
origin subtypes and associated genomic lesions, but also by diverse cell types and cell …

Tumor heterogeneity is one of the hallmarks of cancer and a challenge in the field of
oncology. Tumor heterogeneity is the main cause of drug resistance, leading to therapeutic …

High‐throughput methods to profile the genome, transcriptome, proteome and metabolome
of various systems has become a routine in multiple research laboratories around the world …

The advent of single-cell RNA sequencing (scRNA-seq) has provided insight into the tumour
immune microenvironment (TIME). This review focuses on the application of scRNA-seq in …

Dendritic cells (DCs) contribute a small fraction of the tumor microenvironment but are
emerging as an essential antitumor component based on their ability to foster T cell …

Recent advances in neoantigen research have accelerated the development and regulatory
approval of tumor immunotherapies, including cancer vaccines, adoptive cell therapy and …