No abstract

Tuberculosis (TB) is the leading cause of death of any single infectious agent, having led to 1.4 million deaths in 2019 alone. Moreover, an estimated one-quarter of the global population is latently infected with Mycobacterium tuberculosis (MTB), presenting a huge pool of potential future disease. Nonetheless, the only currently licensed TB vaccine fails to prevent the activation of latent TB infections (LTBI). These facts together illustrate the desperate need for a more effective TB vaccine strategy that can prevent both primary infection and the activation of LTBI. In this study, we employed a machine learning-based reverse vaccinology approach to predict the likelihood that each protein within the proteome of MTB laboratory reference strain H37Rv would be a protective antigen (PAg). The proteins predicted most likely to be a PAg were assessed for their belonging to a protein family of previously established PAgs, the relevance of their biological processes to MTB virulence and latency, and finally the immunogenic potential that they may provide in terms of the number of promiscuous epitopes within each. This study led to the identification of 16 proteins with the greatest vaccine potential for further in vitro and in vivo studies. It also demonstrates the value of computational methods in vaccine development.

Chromosome 11q23 translocations are present in ~10% of acute leukemia, which generate the oncogenic MLL fusion (MLL-r hereinafter) proteins and drive a subset of aggressive leukemia. Mechanistic studies of MLL-r leukemias implicated several complexes involved in RNA polymerase II-mediated transcription: the Super Elongation Complex (SEC), the DOT1L Complex (DotCom) and the Polymerase Associated Factor 1 Complex (PAF1c). These protein complexes are dysregulated in MLL-r leukemias and amplify transcription of pro-leukemic target genes. The proteins ENL and AF9 are two common MLL fusion partners and share high homology within their N-terminal YEATS domains that function as epigenetic reader domains. Recently, the importance of the wild type ENL (but not AF9) and its epigenetic reader function has been demonstrated in acute leukemias. However, the importance of the YEATS domain in the context of MLL-ENL fusions has not been explored. In patients, we found that most MLL-ENL fusions (84.1%; N=302 patients), but not MLL-AF9 fusions, retain the YEATS domain. These findings prompted us to investigate 1) how the YEATS domain contributes to MLL-ENL leukemogenesis, 2) whether the YEATS domain affects MLL-ENL fusion protein functions, and 3) if YEATS domain presence in MLL-ENL fusion exposes a vulnerability to YEATS inhibitors. Using published YEATS epigenetic reader mutations, we found that the YEATS epigenetic reader function significantly contributes to MLL-ENL leukemogenesis. Disrupting the YEATS epigenetic reader function in MLL-ENL fusion proteins significantly impacts leukemic stem cell frequency. Using an MLL-ENL construct relevant in patients (ΔYEATS hereinafter), we discovered a subset of MLL-ENL targets with altered expression. GSEA revealed several gene signatures enriched in ΔYEATS cells, most interestingly genes downregulated in leukemic stem cells. Specifically, the MLL-ENL target Eya1 is severely disrupted in MLL-ENL YEATS epigenetic reader mutants and ΔYEATS cells. Our mechanistic data suggest that while MLL-ENL binding at Eya1 is impacted in ΔYEATS, YEATS epigenetic reader mutants do not significantly alter MLL-ENL and PAF1c localization. However, YEATS epigenetic reader mutations severely impact epigenetic modifications associated with active transcription, including H3K4me3, H3K9ac and H3K79me2 at the Eya1 locus. Finally, we tested the YEATS inhibitor sensitivity in AML cell lines. We found that the cell line HB1119, which is driven by MLL-ENL fusion with an intact YEATS domain, is among the most sensitive lines to the YEATS inhibitor SGC-iMLLT. Together, our study provides the biological and mechanistic characterizations of the YEATS domain in MLL-ENL leukemias and contributes to the theoretical framework for YEATS inhibitor development in the majority of MLL-ENL patients. Citation Format: Hsiangyu Hu, Nirmalya Saha, Yuting Yang, Ejaz Ahmad, Lauren Lachowski, Uttar Shrestha, Vidhya Premkumar, James P. Ropa, Lili Chen, Blaine Teahan, Sierrah Grigsby, Rolf Marschalek, Zaneta Nikolovska-Coleska, Andrew G. Muntean. The ENL YEATS domain links leukemic stem cell frequency and enhances YEATS inhibitor sensitivity in MLL-ENL leukemias. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3550.

MLL1 (KMT2A) translocations are found in ~10% of acute leukemia and give rise to an aggressive form of leukemia in infant, pediatric and adult patients. MLL1 fusion driven acute leukemia is characterized by deregulated activity of the Super Elongation Complex (SEC) and the H3K79 methyltransferase DOT1L, which alter the epigenetic landscape and transcription of pro-leukemic MLL1 fusion targets like HoxA9 and Meis1. The Eleven-Nineteen-Leukemia gene (ENL or MLLT1) is a common MLL1 fusion partner and a SEC component. The ENL protein contains a highly conserved N-terminal epigenetic reader YEATS domain that recognizes acetylated H3K9/K18/K27 (H3Kac hereinafter). Wild type ENL was recently found to be essential for leukemic cell growth, which is dependent on its YEATS domain interaction with H3Kac. While this finding highlighted the YEATS domain importance in wild type ENL function in leukemic cells, the inclusion and importance of the YEATS domain in MLL-ENL fusion protein remain to be elucidated. Here, we investigated the clinical relevance and importance of the ENL YEATS domain in MLL-ENL leukemias. We analyzed >300 t(11;19) MLL-ENL leukemia patients for the breakpoint location within the ENL gene and found that the YEATS domain is retained in the resultant MLL-ENL fusion protein in 84.1% of t(11;19) leukemia patients. We tested the importance of the YEATS domain in MLL-ENL mouse models and found that the YEATS domain and downstream sequence is required for MLL-ENL leukemogenesis in vivo. YEATS deletion decreased expression of pro-leukemic targets such as Meis1, an important factor for leukemic stem cells (LSC). To interrogate the contribution of the YEATS epigenetic reader function in MLL-ENL leukemogenesis, we introduced YEATS point mutations rendering the domain defective in interacting with H3Kac and found that this significantly increased leukemia latency in vivo. Further investigation revealed that YEATS point mutations disrupting H3Kac binding significantly decreased MLL-ENL LSC frequency while not affecting homing to the bone marrow. We attribute this LSC frequency change to altered Meis1 expression. Additionally, disruption of the YEATS epigenetic reader function in MLL-ENL leukemia cells does not induce differentiation, apoptosis nor cell cycle arrest. Therapeutically, we predicted the YEATS domain in MLL-ENL would sensitize MLL-ENL leukemia to YEATS domain inhibitors. Indeed, MLL-ENL leukemia cells are more sensitive to the ENL/AF9 YEATS domain inhibitor, SGC-iMLLT, compared to acute leukemia cells driven by other fusions. Together, our results demonstrate that YEATS-H3Kac binding plays an important role in MLL-ENL fusion mediated leukemogenesis. Our data establishes a strong rationale for future exploration of small molecules aimed at disrupting the YEATS-H3Kac interaction as a targeted therapeutics for treating t(11;19) leukemia patients. Citation Format: Hsiangyu Hu, Nirmalya Saha, Ejaz Ahmad, Yuting Yang, Lili Chen, Lauren Lachowski, Blaine Teahan, Sierrah Grigsby, Rolf Marschalek, Zaneta Nikolovska-Coleska, Andrew G. Muntean. The epigenetic reader function of the YEATS domain in MLL-ENL fusion critically affects leukemic stem cell frequency in MLL-ENL leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2966.