Role of mutational signatures and clonality assessments in tailoring targeted therapies for lymphoma

Lymphomas are highly heterogeneous malignancies characterized by diverse genetic, epigenetic, and phenotypic profiles, which complicate diagnosis, prognosis, and treatment. Traditional bulk sequencing methods mask the complexity of intratumoral variation, often overlooking rare subclones that may drive disease progression and therapeutic resistance. Single-cell genomics has emerged as a transformative approach to decipher tumor heterogeneity at unprecedented resolution. This technology enables the dissection of individual cellular populations within lymphomas, offering insights into clonal evolution, transcriptional diversity, and microenvironmental interactions. By applying single-cell RNA sequencing (scRNA-seq), chromatin accessibility assays (scATAC-seq), and single-cell DNA sequencing (scDNA-seq), researchers can unravel lineage relationships, identify resistant subpopulations, and track dynamic changes in response to therapy. In lymphomas such as diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and mantle cell lymphoma (MCL), single-cell approaches have revealed distinct malignant and non-malignant cell states that correlate with treatment outcomes. Moreover, integrating single-cell data with spatial transcriptomics and immune profiling enhances the understanding of the tumor microenvironment, including immune evasion mechanisms. These insights can inform personalized treatment strategies, identify novel therapeutic targets, and enable early detection of relapse. Despite technical challenges such as data complexity, sample viability, and cost, the application of single-cell genomics in lymphoma research is rapidly advancing. Future directions include multi-omics integration, real-time patient monitoring, and clinical translation of predictive biomarkers. This review underscores the pivotal role of single-cell genomics in resolving tumor heterogeneity and predicting therapeutic resistance, positioning it as a cornerstone for next-generation precision oncology in lymphomas,