Gene-modified NK Cells Expressing CD64 and Pre-loaded with HIV-specific BNAbs Target Autologous HIV-1 Infected CD4+ T Cells by ADCC.
Tomescu, C.; Ortiz, A. O.; Lu, L. D.; Kong, H.; Riley, J. L.; Montaner, L. J.
Show abstract
NK cells can efficiently mediate antibody-dependent cellular cytotoxicity (ADCC) of antibody coated target cells via the low-affinity Fc-receptor, CD16, but cannot retain antibodies over time. To increase antibody retention and facilitate targeted ADCC, we genetically modified human NK cells with the high-affinity Fc receptor, CD64, so that we could pre-load them with HIV-specific BNAbs and enhance their capacity to target HIV infected cells via ADCC. Purified NK cells from the peripheral blood of Control Donors or Persons Living with HIV (PLWH) were activated with IL-2/IL-15/IL-21 cytokines and transduced with a lentivirus encoding CD64. High levels of CD64 surface expression were maintained for multiple weeks on NK cells and CD64 transduced NK cells were similar to control NK cells with strong expression of CD56, CD16, NKG2A, NKp46, CD69, HLA-DR, CD38, and CD57. CD64 transduced NK cells exhibited significantly greater capacity to bind HIV-specific BNAbs in short-term antibody binding assay as well as retain the BNAbs over time (1 week antibody retention assay) compared to Control NK cells only expressing CD16. BNAb pre-loaded CD64 transduced NK cells showed a significantly enhanced capacity to mediate ADCC against autologous HIV-1 infected CD4+ primary T cells in both a short term 3 hour degranulation assay as well as a 24 hour HIV p24 HIV Elimination Assay when compared to control NK cells. A chimeric CD64 enhanced NK cell strategy (NK Enhancement Strategy, "NuKES") retaining bound HIV-specific antibody and targeted ADCC represents a novel autologous primary NK cell immuno-therapy strategy against HIV.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Extensive proteomic and transcriptomic changes quench the TCR/CD3 activation signal of latently HIV-1 infected T cells 95%
- Biogenesis of P-TEFb in CD4+ T cells to reverse HIV latency is mediated by protein kinase C (PKC)-independent signaling pathways 94%
- Non-neutralizing antibodies targeting the immunogenic regions of HIV-1 envelope reduce mucosal infection and virus burden in humanized mice 94%
Similar papers in this journal
- Anti-apoptotic clone 11 derived peptides induce in vitro death of CD4+ T cells susceptible to HIV-1 infection 95%
- Three families of CD4-induced antibodies are associated with the capacity of plasma from people living with HIV to mediate ADCC in presence of CD4-mimetics 95%
- The combination of three CD4-induced antibodies targeting highly conserved Env regions with a small CD4-mimetic achieves potent ADCC activity 94%
Similar papers in this journal
- Enhancing natural killer cell function with gp41-targeting bispecific antibodies to combat HIV infection 97%
- TIGIT is upregulated by HIV-1 infection and marks a highly functional adaptive and mature subset of natural killer cells 96%
- No Evidence that Ongoing HIV-Specific Immune Responses Contribute to Persistent Inflammation and Immune Activation in Persons on Long-Term ART 91%
Similar papers in this journal
- Refined cell transfer model reveals roles for Ascl2 and Cxcr3 in splenic localization of mouse NK cells during virus infection 93%
- CD4+ Mucosal-associated Invariant T (MAIT) cells express highly diverse T cell receptors 92%
- Replication stress in activated human NK cells induces sensitivity to apoptosis 92%
Similar papers in this journal
- Design and validation of HIV peptide pools for detection of HIV-specific CD4 + and CD8 + T cells 95%
- Deficient uracil base excision repair leads to persistent dUMP in HIV proviruses during infection of monocytes and macrophages 93%
- A mechanistically novel peptide agonist of the IL-7 receptor that addresses limitations of IL-7 cytokine therapy 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.