Biology subjects

Chiorazzi, N.

Publications and source records attributed to Chiorazzi, N..

3 recordsLinked to original sources

bioRxiv2025

IGLV3-21-R110-directed bispecific antibodies activate T cells and promote killing in a high-risk subset of chronic lymphocytic leukemia

We previously used a disease-specific B cell receptor (BCR) point mutation (IGLV3-21R110) for selective targeting of a poor-risk subset of chronic lymphocytic leukemia (CLL) with chimeric antigen receptor (CAR) T cells. Since CLL is a disease of the elderly and a significant fraction of patients is not able to physically tolerate CAR T cell treatment, we explored bispecific antibodies as an alternative for precision targeting of this tumor mutation. Heterodimeric IgG1-based antibodies consisting of a fragment crystallizable region (Fc) attached to either an anti-IGLV3-21R110 Fab or an anti-CD3 (UCHT1) single chain variable fragment (R110-bsAb) selectively killed cell lines engineered to express high levels of the neoepitope as well as primary CLL cells using healthy donor and CLL patient-derived T cells as effectors. R110-bsAb spared polyclonal human B cells (as opposed to CD19-targeting Blinatumomab) as well as CD34+ human stem cells. Yet, R110-bsAb induced lower T cell activation than Blinatumomab with primary CLL cells likely due to lower expression of target antigen. In vivo, R110-bsAb specifically killed IGLV3-21R110-expressing cell lines and CLL cells while sparing peripheral blood mononuclear cells. These findings highlight bispecific antibodies as a promising, off-the-shelf immunotherapy for high-risk CLL patients, offering selective targeting while preserving healthy B cells.

cancer biology↗

bioRxiv2023

Mutation-specific CAR T cells as precision therapy for IGLV3-21R110 expressing high-risk chronic lymphocytic leukemia

The concept of precision cell therapy targeting tumor-specific mutations is appealing but requires surface-exposed neoepitopes, which is a rarity in cancer. B cell receptors (BCR) of mature lymphoid malignancies are exceptional in that they harbor tumor-specific-stereotyped sequences in the form of point mutations that drive self-engagement of the BCR and autologous signaling. Here, we used a BCR light chain neoepitope defined by a characteristic point mutation (IGLV3-21R110) for selective targeting of a poor-risk subset of chronic lymphocytic leukemia (CLL) with chimeric antigen receptor (CAR) T cells. We developed murine and humanized CAR constructs expressed in T cells from healthy donors and CLL patients that eradicated IGLV3-21R110 expressing cell lines and primary CLL cells, but not polyclonal healthy B cells. In vivo experiments confirmed epitope-selective cytolysis in xenograft models using engrafted IGLV3-21R110 expressing cell lines or primary CLL cells. We further demonstrate in two humanized mouse models lack of cytotoxicity towards human B cells. These data provide the basis for novel avenues of resistance-preventive and biomarker-guided cellular targeting of functionally relevant lymphoma driver mutations sparing normal B cells.

cancer biology↗

bioRxiv2017

Highly sensitive detection of small variants in multi-sample ultra-deep tumor sequencing

One cause of cancer mortality is tumor evolution to therapy-resistant disease. First line therapy often targets the dominant clone, and drug resistance can emerges from preexisting clones that gain fitness through therapy-induced natural selection. Such mutations may be identified using targeted sequencing assays by analysis of noise in high-depth data. Here, we develop a comprehensive, unbiased model for sequencing error background. We find that noise in sufficiently deep DNA sequencing data can be approximated by aggregating negative binomial distributions. Mutations with frequencies above noise may have prognostic value. We evaluate our model with simulated exponentially expanded populations as well as data from cell line and patient sample dilution experiments, demonstrating its utility in prognosticating tumor progression. Our results may have the potential to identify significant mutations that can cause recurrence. These results are relevant in the pretreatment clinical setting to determine appropriate therapy and prepare for potential recurrence pretreatment.

bioinformatics↗