Cell death escape is one of the most prominent features of tumor cells and closely linked to the dysregulation of members of the Bcl-2 family of proteins. Among those, the anti-apoptotic family member myeloid cell leukemia-1 (MCL-1) acts as a master regulator of apoptosis in various human malignancies. Irrespective of its unfavorable structure profile, independent research efforts recently led to the generation of highly potent MCL-1 inhibitors that are currently evaluated in clinical trials. This offers new perspectives to target a so far undruggable cancer cell dependency. However, a detailed understanding about the tumor and tissue type specific implications of MCL-1 are a prerequisite for the optimal (i.e., precision medicine guided) use of this novel drug class. In this review, we summarize the major functions of MCL-1 with a special focus on cancer, provide insights into its different roles in solid vs. hematological tumors and give an update about the (pre)clinical development program of state-of-the-art MCL-1 targeting compounds. We aim to raise the awareness about the heterogeneous role of MCL-1 as drug target between, but also within tumor entities and to highlight the importance of rationale treatment decisions on a case by case basis.

Bispecific antibodies (BsAbs) are designed to recognize and bind to two different antigens or epitopes. In the last few decades, BsAbs have been developed within the context of cancer therapies and in particular for the treatment of hematologic B-cell malignancies. To date, more than one hundred different BsAb formats exist, including bispecific T-cell engagers (BiTEs), and new constructs are constantly emerging. Advances in protein engineering have enabled the creation of BsAbs with specific mechanisms of action and clinical applications. Moreover, a better understanding of resistance and evasion mechanisms, as well as advances in the protein engineering and in immunology, will help generating a greater variety of BsAbs to treat various cancer types. This review focuses on T-cell-engaging BsAbs and more precisely on the various BsAb formats currently being studied in the context of B-cell malignancies, on ongoing clinical trials and on the clinical concerns to be taken into account in the development of new BsAbs.

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Background: Background: Multiple Myeloma (MM) is an incurable plasma cell (PC) malignancy that evolves from two premalignant stages: Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smoldering Multiple Myeloma (SMM). The disease progression has been characterized to be driven by intrinsic genomic events in the myeloma cells and by gradual dysregulation of the immune system. Aims:Aims: We investigated how the interplay between tumor cells with their microenvironment and the underlying complex and dynamic immune biology evolve during this process. Methods:Methods: Single cell multi-omics profiling, including RNA, B-cell receptor (BCR) and antibody barcode-tagged 10x sequencing, was conducted on human bone marrow (BM) aspirates collected at 6 Belgian centers from 4 cohorts: 31 healthy elderly and 28 MGUS, 32 SMM and 32 newly diagnosed MM. Mononuclear cell isolation, freezing and transport to central facilities was optimizedand data were integrated and filtered using Scanpy and Scirpy. The main immune cell types were identified from the RNA and antibody data using SingleR. Further functional subtyping was done using Leiden clustering. Differential pathway expression analysis was performed with Muscat and FGSEA. Results:Results: From the tumor cell transcriptomes, our analyses confirmed the previously documented myeloma molecular hallmarks, such as MYC and IFN-a signaling, cell proliferation, energy metabolism and oxidative phosphorylation. Evidence was found for transcriptomic similarities and within-and between-patient malignant PC transcriptomic heterogeneity, as well as the existence of multiple transcriptomic clones in several patients. We observed a positive correlation between the antigen processing mechanism in the PCs with IFN response, suggesting that this mechanism associates with initiation of the immune recognition and activation against the tumor.The gradually increasing differential gene expression was also observed in the immune microenvironment: dysregulation of signaling pathways initiates early in MGUS and spreads throughout the various cell types surrounding the tumor cells. Cell population shifts were also found. In the CD1C+ DCs, that play a role in cancer immune control, a functional shift was observed that correlated with disease progression towards a more mature and antigen presenting phenotype with higher levels of CD83, HBEGF, MCL1 and CXCL16 as well as increased TNF-a pathway. Similarly, a shift was observed in the macrophage population, toward M1 state showing high IFN response along with expression of MS4A4A, STAT1, TNFSF13B and TRAIL in more severe disease. Interestingly, in the CD8+ T cells, we detected a pre-dysfunctional subpopulation with high expression of GZMK, activation markers CD69, CCL4, CXCR4 and genes associated with T cell pre-dysfunctionality NR4A2, RGS1, TOX and TIGIT, that was found to be associated with progression (Figure). In the CD4+ cytotoxic T cells, a proportion change was observed with more severe disease.

An amendment to this paper has been published and can be accessed via the original article.

Background: Despite the recent introduction of next-generation immunotherapeutic agents, multiple myeloma (MM) remains an incurable disease. Increasing the number of targeted antigens may result in a more effective therapy by preventing antigen escape, clonal evolution and/or disease progression. Moreover, combinatorial approaches (in which activation depends on the presence of 2 antigens) may result in more efficient and specific treatments that limit toxicity on normal tissues. In this work, we adapted an algorithm that integrates proteomic and transcriptomic results of myeloma cells to identify new antigens and possible antigen combinations. Methods: We performed cell surface proteomics on six myeloma cell lines based on biotin labeling, protein recovery using NeutrAvidin agarose beads and mass spectrometry. These results were combined with gene expression studies comparing myeloma cells with normal plasma cells and B cells and an annotated tissue distribution of identified proteins. The expression of retained proteins was further studied by flow cytometry on normal and malignant plasma cells, hematopoietic stem cells (HSC) and immune effector cells (T and NK cells). Results: Our algorithm identified 209 surface proteins that are overexpressed in myeloma cells from which 52 proteins could be selected for combinatorial pairing. This list could be further reduced to 23 proteins based on tissue distribution and pairing rules. Flow cytometry analysis of primary samples confirmed the expression of FCRL5, BCMA and ICAM2 in all samples and IL6R, ETRB, SLCO5A1 and PRL3 in more than 60%. Based on single cell RNA-sequencing studies, ETRB is mainly expressed on myeloma cells in the bone marrow and its expression has prognostic value. By analysing the expression on HSC, T and NK cells, different pairs could be proposed that can target myeloma cells and avoid toxicity on other organs. Conclusions: Our approach validated the expression and distribution of known and new antigens that can be integrated in single-antigen or combinatorial-antigen targeting strategies for novel immunotherapies.