Recent evidence suggests immunomodulatory effects of daratumumab in heavily pre-treated Multiple Myeloma (MM) patients (pts); however, the precise effects remain under-characterized, particularly at the molecular level. REBUILD is an ongoing prospective, multicenter, non-comparative, open-label, phase II study that evaluates the effects of daratumumab monotherapy on bone metabolism of pts with relapsed and/or refractory MM (RRMM) who have had ≥2 prior lines of therapy, including lenalidomide and a proteasome inhibitor. Secondary endpoint of the study included the evaluation of T cell dynamics by comprehensive analysis of the T cell receptor (TR) repertoire employing next generation sequencing (NGS) and multi-color flow cytometry. Herein we report the results of this secondary endpoint for the first 14 pts who completed 3 cycles of daratumumab monotherapy. In total, we analyzed 28 paired samples collected at screening (n=14) and on Day 1 of Cycle 4 (C4D1, n=14) of treatment in order to assess potential changes in relation to treatment and clinical response. Patients were grouped based on best responses into responders (i.e. patients with partial response [PR, n=1] and very good PR [VGPR, n=6]), and non-responders (i.e. patients with minimal response [MR, n=2], stable disease [SD, n=4], or progressive disease [PD, n=1]). Starting material was peripheral blood mononuclear cells. TRBV-TRBD-TRBJ gene rearrangements were RT-PCR amplified and subjected to paired-end NGS. Raw NGS reads (n=6,715,406 | median 221,145/sample) were processed through a previously published, purpose-built bioinformatics pipeline. Only productive TRBV-TRBD-TRBJ rearrangements were taken into consideration (n=3,097,565 | median 101,670/sample) for the computation of clonotypes (i.e. TRB rearrangements with identical TRBV gene usage and amino acid complementarity-determining region 3 sequence). Overall, 151,153 distinct clonotypes (median 5,084 clonotypes/sample) were assessed. Both groups (responders/non-responders) displayed clonal T cell expansions both pre- and post-treatment. Clonality was found to be increased after treatment for both responders and non-responders, with statistical significance in the former (median cumulative frequency of the 10 most expanded T cell clonotypes/sample: 31% pre-treatment versus 40% post-treatment, respectively | p=0.04). In both groups, the clonotype repertoire appeared to be renewed with only a small fraction of pre-treatment clonotypes remaining after treatment (1% for non-responders; 0.6% for responders). Interestingly, in the responders' group we noticed a significant shift in the major clonotype repertoire at screening vs C4D1. In particular, in the responders' group the 10 most expanded clonotypes/sample at C4D1 represented expansions of clonotypes present at very low frequency at screening, whereas the most expanded clonotypes at screening decreased or even diminished post-treatment, suggesting that daratumumab treatment led to the emergence of anti-myeloma T cell clones which contributed to clinical response. On the contrary, the 10 most expanded pre-treatment clonotypes in the non-responders' group tended to dominate also the post-treatment repertoire. Of note, 13 shared clonotypes were identified amongst the post-treatment repertoires of different patients (responders/non-responders); shared clonotypes were not found in other entities in public databases, raising the possibility that they may be "disease-specific" and selected by common tumor-associated antigens. With a single exception, shared clonotypes were detected in cases with relevant HLA restrictions, which is noteworthy given the random HLA background of our cohort. Finally, flow cytometry analysis revealed a significant increase post treatment in the percentage of CD3+ T cells (median frequency at screening 60% versus 83% at C4D1 | p=0.003), driven mostly by the expansion of the CD8+ T cell compartment (median frequency at screening 30.8% versus 48.9% at C4D1 | p=0.03) in both groups. In conclusion, TR clonality increases post-treatment through a renewal mechanism; however, pre-treatment clones significantly expanded post-treatment in responders, alluding to the existence of clonotypes with anti-MM properties that may be activated after treatment with daratumumab, arguably contributing to clinical response. Disclosures Kastritis: Janssen: Honoraria, Research Funding; Takeda: Honoraria; Pfizer: Honoraria; Prothena: Honoraria; Genesis: Honoraria; Amgen: Honoraria, Research Funding. Hatjiharissi:Janssen: Honoraria. Katodritou:Genesis: Honoraria; Janssen: Honoraria; Takeda: Honoraria; Amgen: Honoraria. Gavriatopoulou:Genesis: Honoraria, Other: Travel expenses; Janssen: Honoraria, Other: Travel expenses; Takeda: Honoraria, Other: Travel expenses; Amgen: Honoraria. Delimpasi:Takeda: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Genesis: Honoraria, Other: Travel grant. Symeonidis:Sanofi: Research Funding; MSD: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tekeda: Membership on an entity's Board of Directors or advisory committees, Research Funding. Stamatopoulos:Janssen: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding. Dimopoulos:Sanofi Oncology: Research Funding. Terpos:Janssen: Honoraria, Other: Travel expenses, Research Funding; Medison: Honoraria; Genesis: Honoraria, Other: Travel expenses, Research Funding; Amgen: Honoraria, Research Funding; Celgene: Honoraria; Takeda: Honoraria, Other: Travel expenses, Research Funding. Chatzidimitriou:Janssen: Honoraria.