T-cell receptor architecture and clonal tiding provide insight into the transformation trajectory of peripheral T-cell lymphomas.

While T cell lymphomas are classified as mature neoplasms, emerging evidence indicates that malignant transformation may occur at an earlier stage of T cell maturation. In this study, we determined clonal architectures in a broad range of T cell lymphomas. Our multidimensional profiling indicates that a large part of these lymphomas in fact emerge from an immature lymphoid T cell precursor at a maturation stage prior to V(D)J rearrangement that undergoes branching evolution.

Detection of disease-specific signatures in B cell repertoires of lymphomas using machine learning.

The classification of B cell lymphomas-mainly based on light microscopy evaluation by a pathologist-requires many years of training. Since the B cell receptor (BCR) of the lymphoma clonotype and the microenvironmental immune architecture are important features discriminating different lymphoma subsets, we asked whether BCR repertoire next-generation sequencing (NGS) of lymphoma-infiltrated tissues in conjunction with machine learning algorithms could have diagnostic utility in the subclassification of these cancers. We trained a random forest and a linear classifier via logistic regression based on patterns of clonal distribution, VDJ gene usage and physico-chemical properties of the top-n most frequently represented clonotypes in the BCR repertoires of 620 paradigmatic lymphoma samples-nodular lymphocyte predominant B cell lymphoma (NLPBL), diffuse large B cell lymphoma (DLBCL) and chronic lymphocytic leukemia (CLL)-alongside with 291 control samples.