Patients with myeloid neoplasms who relapsed after allogenic hematopoietic stem cell transplant (HSCT) have poor prognosis. Monitoring of chimerism and specific molecular markers as a surrogate measure of relapse is not always helpful; therefore, improved systems to detect early relapse are needed. We hypothesized that the use of next generation sequencing (NGS) could be a suitable approach for personalized follow-up post-HSCT. To validate our hypothesis, we analyzed by NGS, a retrospective set of peripheral blood (PB) DNA samples previously evaluated by high-sensitive quantitative PCR analysis using insertion/deletion polymorphisms (indel-qPCR) chimerism engraftment. Post-HCST allelic burdens assessed by NGS and chimerism status showed a similar time-course pattern. At time of clinical relapse in 8/12 patients, we detected positive NGS-based minimal residual disease (NGS-MRD). Importantly, in 6/8 patients, we were able to detect NGS-MRD at time points collected prior to clinical relapse. We also confirmed the disappearance of post-HCST allelic burden in non-relapsed patients, indicating true clinical specificity. This study highlights the clinical utility of NGS-based post-HCST monitoring in myeloid neoplasia as a complementary specific analysis to high-sensitive engraftment testing. Overall, NGS-MRD testing in PB is widely applicable for the evaluation of patients following HSCT and highly valuable to personalized early treatment intervention when mixed chimerism is detected.

Background: Follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL) exhibit substantial heterogeneity, reflecting the diversity of the germinal center (GC). Histologic transformation of FL to DLBCL is associated with poor prognosis, yet robust biomarkers predicting transformation remain limited. Methods: We integrated single-cell DNA sequencing, single-cell RNA sequencing, and spatial transcriptomics in diagnostic lymph-node biopsies from non-transformed FL (ntFL), transformed FL (tFL), and DLBCL to characterize clonal states and immune niches in GC lymphomas. T-cell signatures associated with transformation were evaluated in an independently published single-cell FL dataset. Results: Transcriptional profiling revealed similarities between tFL and DLBCL, consistent with a GC-related malignant program. The tFL microenvironment showed enrichment of exhausted CD4⁺ regulatory and CD8⁺ effector T cells, together with CD4⁺ follicular helper T cells (Tfh) displaying an adhesion-related phenotype. Spatial analysis suggested increased proximity of exhausted/immunosuppressive T cells and enhanced Tfh-B-cell interactions in tFL compared with ntFL. These immune signatures were also observed in an external cohort and were associated with early transformation. In addition, clonal hematopoiesis-associated mutations were detected in microenvironmental cells across samples, suggesting a potential contribution to the lymphoma microenvironment. Conclusions: This work demonstrates the feasibility of integrating single-cell and spatial analyses in GC lymphomas and provides a framework for investigating tumor heterogeneity and immune organization. These findings may inform future studies on biomarker development and the rational design of immunotherapies.