Deciphering the role of immunoglobulin classes in shaping Follicular Lymphoma molecular heterogeneity and evolution

Follicular lymphoma (FL) is the second most common B cell neoplasm, characterized by the t(14;18) chromosomal translocation, resulting in deregulated BCL2 oncoprotein (BCL2tx+).

In situ follicular neoplasia (ISFN) represents an early precursor lesion, histologically identified as BCL2+/CD10+ Germinal Centers (GC), that might progress into FL.

Spatial and temporal genomic analysis in FL revealed that its transformation into aggressive high-grade MYC/BCL2 Double-Hit lymphoma (DHL) arises predominantly from a common precursor that clonally diverges upon the acquisition of genetic hits through iterative GC transitions.

Expansion of FL B cells requires the presence of a functional B cell- receptor (BCR), which can be expressed in either unswitched (immunoglobulin M (IgM) or switched (IgG/IgA) isotype.

Preliminary data from the hosting laboratory showed an isotype-dependent regulation of Ig levels in FL and MYC/BCL2 DHLs prompting the hypothesis that specific IgH classes may differentially impact pre-tumoral FL lesions, shaping the transforming trajectory of ISFN cells, overt FL cells and finally giving rise to DHL.

Using state-of-the-art technologies, including single-cell and spatially-resolved transcriptomics and genetics analyses, I will define IgH-class dependent transcriptional changes in the transition from ISFN to FL and, eventually, DHL and the influence of specific isotype to shape intra and inter tumor heterogeneity and tumor mutational landscape.

Finally, I propose to determine whether the immunoregulatory activity of tumor-infiltrating immune/stromal cells is influenced by the expression of defined Ig-isotypes in lymphoma cells.

Overall, this action will establish previously uncharacterized roles for distinct IgH classes to determine transforming trajectories promoting the transformation of BCL2tx+ GC B cells into first FL, and later DHL, providing novel clinically relevant biomarkers predicting patient outcome and tumor evolution.