Clustering molecular dynamics conformations of the CC'-loop of the PD-1 immuno-checkpoint receptor.

Molecular mechanisms within the checkpoint receptor PD-1 are essential for its activation by PD-L1 as well as for blocking such an activation via checkpoint inhibitors. We use molecular dynamics to scrutinize patterns of atomic motion in PD-1 without a ligand. Molecular dynamics is performed for the whole extracellular domain of PD-1, and the analysis focuses on its CC'-loop and some adjacent Cα-atoms. We extend previous work by applying common nearest neighbor clustering (Cnn) and compare the performance of this method with Daura clustering as well as UMAP dimension reduction and subsequent agglomerative linkage clustering. As compared to Daura clustering, we found Cnn less sensitive to cutoff selection and better able to return representative clusters for sets of different 3D atomic conformations. Interestingly, Cnn yields results quite similar to UMAP plus linkage clustering.

Flexible Risk Evidence Combination Rules in Breast Cancer Precision Therapy.

Evidence theory by Dempster-Shafer for determination of hormone receptor status in breast cancer samples was introduced in our previous paper. One major topic pointed out here is the link between pieces of evidence found from different origins. In this paper the challenge of selecting appropriate ways of fusing evidence, depending on the type and quality of data involved is addressed. A parameterized family of evidence combination rules, covering the full range of potential needs, from emphasizing discrepancies in the measurements to aspiring accordance, is covered. The consequences for real patient samples are shown by modeling different decision strategies.

Molecular dynamics identifies semi-rigid domains in the PD-1 checkpoint receptor bound to its natural ligand PD-L1.

Cells in danger of being erroneously attacked by leucocytes express PD-L1 on their surface. These cells activate PD-1 on attacking leucocytes and send them to death, thus curbing erroneous, autoimmune attack. Unfortunately, cancer cells exploit this mechanism: By expressing PD-L1, they guard themselves against leucocyte attack and thereby evade immune clearance. Checkpoint inhibitors are drugs which re-enable immune clearance of cancer cells by blocking the binding of PD-L1 to PD-1 receptors. It is therefore of utmost interest to investigate these binding mechanisms. We use three 600 ns all-atom molecular dynamics simulations to scrutinize molecular motions of PD-1 with its binding partner, the natural ligand PD-L1. Usually, atomic motion patterns are evaluated against whole molecules as a reference, disregarding that such a reference is a dynamic entity by itself, thus degrading stability of the reference. As a remedy, we identify semi-rigid domains, lending themselves as more stable and reliable reference frames against which even minute differences in molecular motion can be quantified precisely. We propose an unsupervised three-step procedure. In previous work of our group and others, minute differences in motion patterns proved decisive for differences in function. Here, several highly reliable frames of reference are established for future investigations based on molecular motion.

SLCO4A1 expression is associated with activated inflammatory pathways in high-grade serous ovarian cancer.

Patients with high-grade serous ovarian cancer (HGSOC) have a very poor overall survival. Current therapeutic approaches do not bring benefit to all patients. Although genetic alterations and molecular mechanisms are well characterized, the molecular pathological conditions are poorly investigated. Solute carrier organic anion transporter family member 4A1 (SLCO4A1) encodes OATP4A1, which is an uptake membrane transporter of metabolic products. Its expression may influence various signaling pathways associated with the molecular pathophysiological conditions of HGSOC and consequently tumor progression. RNA sequencing of 33 patient-derived HGSOC cell lines showed that SLCO4A1 expression was diverse by individual tumors, which was further confirmed by RT-qPCR, Western blotting and immunohistochemistry. Gene Set Enrichment Analysis revealed that higher SLCO4A1 level was associated with inflammation-associated pathways including NOD-like receptor, adipocytokine, TALL1, CD40, NF-κB, and TNF-receptor 2 signaling cascades, while low SLCO4A1 expression was associated with the mitochondrial electron transport chain pathway. The overall gene expression pattern in all cell lines was specific to each patient and remained largely unchanged during tumor progression. In addition, genes encoding ABCC3 along with SLCO4A1-antisense RNA 1, were associated with higher expression of the SLCO4A1, indicating their possible involvement in inflammation-associated pathways that are downstream to the prostaglandin E2/cAMP axis. Taken together, increased SLCO4A1/OATP4A1 expression is associated with the upregulation of specific inflammatory pathways, while the decreased level is associated with mitochondrial dysfunction. These molecular pathophysiological conditions are tumor specific and should be taken into consideration by the development of therapies against HGSOC.

Conformational flexibility of a free and TCR-bound pMHC-I protein investigated by long-term molecular dynamics simulations.

BACKGROUND: Major histocompatibility complexes (MHCs) play a crucial role in the cell-mediated adaptive immune response as they present antigenic peptides (p) which are recognized by host T cells through a complex formation of the T cell receptor (TCR) with pMHC. In the present study, we report on changes in conformational flexibility within a pMHC molecule upon TCR binding by looking at molecular dynamics (MD) simulations of the free and the TCR-bound pMHC-I protein of the LC13-HLA-B*44:05-pEEYLQAFTY complex. RESULTS: We performed long-term MD simulations with a total simulation time of 8 µs, employing 10 independent 400 ns replicas for the free and the TCR-bound pMHC system. Upon TCR ligation, we observed a reduced dynamic flexibility in the central residues of the peptide and the MHC α1-helix, altered occurrences of hydrogen bonds between the peptide and the MHC, a reduced conformational entropy of the peptide-binding groove, as well as a decreased solvent accessible surface area. CONCLUSIONS: In summary, our results from 8 µs MD simulations indicate a restricted conformational space of the MHC peptide-binding groove upon TCR ligation and suggest a minimum simulation time of approximately 100 ns for biomolecules of comparable complexity to draw meaningful conclusions. Given the relatively long total simulation time, our results contribute to a more detailed view on conformational flexibility properties of the investigated free and TCR-bound pMHC-I system.

Decision Theory versus Conventional Statistics for Personalized Therapy of Breast Cancer.

Estrogen and progesterone receptors being present or not represents one of the most important biomarkers for therapy selection in breast cancer patients. Conventional measurement by immunohistochemistry (IHC) involves errors, and numerous attempts have been made to increase precision by additional information from gene expression. This raises the question of how to fuse information, in particular, if there is disagreement. It is the primary domain of Dempster-Shafer decision theory (DST) to deal with contradicting evidence on the same item (here: receptor status), obtained through different techniques. DST is widely used in technical settings, such as self-driving cars and aviation, and is also promising to deliver significant advantages in medicine. Using data from breast cancer patients already presented in previous work, we focus on comparing DST with classical statistics in this work, to pave the way for its application in medicine. First, we explain how DST not only considers probabilities (a single number per sample), but also incorporates uncertainty in a concept of 'evidence' (two numbers per sample). This allows for very powerful displays of patient data in so-called ternary plots, a novel and crucial advantage for medical interpretation. Results are obtained according to conventional statistics (ODDS) and, in parallel, according to DST. Agreement and differences are evaluated, and the particular merits of DST discussed. The presented application demonstrates how decision theory introduces new levels of confidence in diagnoses derived from medical data.

Galectin network in osteoarthritis: galectin-4 programs a pathogenic signature of gene and effector expression in human chondrocytes in vitro.

Galectin-4 (Gal-4) is a member of the galectin family, which have been identified as galactose-binding proteins. Gal-4 possesses two tandem repeat carbohydrate recognition domains and acts as a cross-linking bridge in sulfatide-dependent glycoprotein routing. We herein document its upregulation in osteoarthritis (OA) in correlation with the extent of cartilage degradation in vivo. Primary human OA chondrocytes in vitro respond to carbohydrate-inhibitable Gal-4 binding with the upregulation of pro-degradative/-inflammatory proteins such as interleukin-1ß (IL-1ß) and matrix metalloproteinase-13 (MMP-13), as documented by RT-qPCR-based mRNA profiling and transcriptome data processing. Activation of p65 by phosphorylation of Ser536 within the NF-κB pathway and the effect of three p65 inhibitors on Gal-4 activity support downstream involvement of such signaling. In 3D (pellet) cultures, Gal-4 presence causes morphological and biochemical signs of degradation. Taken together, our findings strongly support the concept of galectins acting as a network in OA pathogenesis and suggest that blocking their activity in disease progression may become clinically relevant in the future.

Decision theory for precision therapy of breast cancer.

Correctly estimating the hormone receptor status for estrogen (ER) and progesterone (PGR) is crucial for precision therapy of breast cancer. It is known that conventional diagnostics (immunohistochemistry, IHC) yields a significant rate of wrongly diagnosed receptor status. Here we demonstrate how Dempster Shafer decision Theory (DST) enhances diagnostic precision by adding information from gene expression. We downloaded data of 3753 breast cancer patients from Gene Expression Omnibus. Information from IHC and gene expression was fused according to DST, and the clinical criterion for receptor positivity was re-modelled along DST. Receptor status predicted according to DST was compared with conventional assessment via IHC and gene-expression, and deviations were flagged as questionable. The survival of questionable cases turned out significantly worse (Kaplan Meier p < 1%) than for patients with receptor status confirmed by DST, indicating a substantial enhancement of diagnostic precision via DST. This study is not only relevant for precision medicine but also paves the way for introducing decision theory into OMICS data science.

Erratum: Gruber, E.S.; et al. The Oncogene AF1Q is Associated with WNT and STAT Signaling and Offers a Novel Independent Prognostic Marker in Patients with Resectable Esophageal Cancer. Cells 2019, 8, 1357.

The authors wish to make the following change to their paper [...].

Molecular dynamics of the immune checkpoint programmed cell death protein I, PD-1: conformational changes of the BC-loop upon binding of the ligand PD-L1 and the monoclonal antibody nivolumab.

BACKGROUND: The immune checkpoint receptor programmed cell death protein I (PD-1) has been identified as a key target in immunotherapy. PD-1 reduces the risk of autoimmunity by inducing apoptosis in antigen-specific T cells upon interaction with programmed cell death protein ligand I (PD-L1). Various cancer types overexpress PD-L1 to evade the immune system by inducing apoptosis in tumor-specific CD8+ T cells. The clinically used blocking antibody nivolumab binds to PD-1 and inhibits the immunosuppressive interaction with PD-L1. Even though PD-1 is already used as a drug target, the exact mechanism of the receptor is still a matter of debate. For instance, it is hypothesized that the signal transduction is based on an active conformation of PD-1. RESULTS: Here we present the results of the first molecular dynamics simulations of PD-1 with a complete extracellular domain with a focus on the role of the BC-loop of PD-1 upon binding PD-L1 or nivolumab. We could demonstrate that the BC-loop can form three conformations. Nivolumab binds to the BC-loop according to the conformational selection model whereas PD-L1 induces allosterically a conformational change of the BC-loop. CONCLUSION: Due to the structural differences of the BC-loop, a signal transduction based on active conformation cannot be ruled out. These findings will have an impact on drug design and will help to refine immunotherapy blocking antibodies.

Pembrolizumab Induces an Unexpected Conformational Change in the CC'-loop of PD-1.

To improve cancer immunotherapy, a clearer understanding of key targets such as the immune checkpoint receptor PD-1 is essential. The PD-1 inhibitors nivolumab and pembrolizumab were recently approved by the FDA. The CC'-loop of PD-1 has been identified as a hotspot for drug targeting. Here, we investigate the influence of nivolumab and pembrolizumab on the molecular motion of the CC'-loop of PD-1. We performed molecular dynamics simulations on the complete extracellular domain of PD-1, in complex with PD-L1, and the blocking antibodies nivolumab and pembrolizumab. Conformations of the CC'-loop were analyzed unsupervised with the Daura et al. clustering algorithm and multidimensional scaling. Surprisingly, two conformations found were seen to correspond to the 'open' and 'closed' conformation of CC'-loop in apo-PD-1, already known from literature. Unsupervised clustering also surprisingly reproduced the natural ligand, PD-L1, exclusively stabilizing the 'closed' conformation, as also known from literature. Nivolumab, like PD-L1, was found to shift the equilibrium towards the 'closed' conformation, in accordance with the conformational selection model. Pembrolizumab, on the other hand, induced a third conformation of the CC'-loop which has not been described to date: Relative to the conformation 'open' the, CC'-loop turned 180° to form a new conformation which we called 'overturned'. We show that the combination of clustering and multidimensional scaling is a fast, easy, and powerful method in analyzing structural changes in proteins. Possible refined antibodies or new small molecular compounds could utilize the flexibility of the CC'-loop to improve immunotherapy.

Microarray Normalization Revisited for Reproducible Breast Cancer Biomarkers.

Precision medicine for breast cancer relies on biomarkers to select therapies. However, the reliability of biomarkers drawn from gene expression arrays has been questioned and calls for reassessment, in particular for large datasets. We revisit widely used data-normalization procedures and evaluate differences in outcome in order to pinpoint the most reliable reprocessing methods biomarkers can be based upon. We generated a database of 3753 breast cancer patients out of 38 studies by downloading and curating patient samples from NCBI-GEO. As gene-expression biomarkers, we select the assessment of receptor status and breast cancer subtype classification. Each normalization procedure is applied separately, and biomarkers are then evaluated for each patient. Differences between normalization pipelines are quantified as percentages of patients having outcomes different for each pipeline. Some normalization procedures lead to quite consistent biomarkers, differing only in 1-2% of patients. Other normalization procedures-some of them have been used in many clinical studies-end up with distrusting discrepancies (10% and more). A good deal of doubt regarding the reliability of microarrays may root in the haphazard application of inadequate preprocessing pipelines. Several modes of batch corrections are evaluated regarding a possible improvement of receptor prediction from gene expression versus the golden standard of immunohistochemistry. Finally, we nominate those normalization methods yielding consistent and trustable results. Adequate bioinformatics data preprocessing is key and crucial for any subsequent statistics to arrive at trustable results. We conclude with a suggestion for future bioinformatics development to further increase the reliability of cancer biomarkers.

The Oncogene AF1Q is Associated with WNT and STAT Signaling and Offers a Novel Independent Prognostic Marker in Patients with Resectable Esophageal Cancer.

AF1q impairs survival in hematologic and solid malignancies. AF1q expression is associated with tumor progression, migration, and chemoresistance, and acts as a transcriptional co-activator in WNT and STAT signaling. This study evaluates the role of AF1q in patients with resectable esophageal cancer (EC). A total of 278 patients operated on for esophageal cancer were retrospectively included, and the expression of AF1q, CD44, and pYSTAT3 was analyzed following immunostaining. Quantified data were processed to correlational and survival analysis. In EC patients, an elevated expression of AF1q was associated with CD44 (p = 0.004), and pYSTAT3 (p = 0.0002). High AF1q expression in primary tumors showed high AF1q expression in the corresponding lymph nodes (p= 0.016). AF1q expression was higher after neoadjuvant therapy (p= 0.0002). Patients with AF1q-positive EC relapsed and died earlier compared to patients with AF1q-negative EC (disease-free survival (DFS), p= 0.0005; disease-specific survival (DSS), p= 0.003); in the multivariable Cox regression model, AF1q proved to be an independent prognostic marker (DFS, p= 0.01; DSS, p= 0.03). AF1q is associated with WNT and STAT signaling; it impairs and independently predicts DFS and DSS in patients with resectable EC. The testing of AF1q could facilitate prognosis estimation and provide a possibility of identifying the patients responsive to the therapeutic blockade of its oncogenic downstream targets.

Intramolecular Domain Movements of Free and Bound pMHC and TCR Proteins: A Molecular Dynamics Simulation Study.

The interaction of antigenic peptides (p) and major histocompatibility complexes (pMHC) with T-cell receptors (TCR) is one of the most important steps during the immune response. Here we present a molecular dynamics simulation study of bound and unbound TCR and pMHC proteins of the LC13-HLA-B*44:05-pEEYLQAFTY complex to monitor differences in relative orientations and movements of domains between bound and unbound states of TCR-pMHC. We generated local coordinate systems for MHC α1- and MHC α2-helices and the variable T-cell receptor regions TCR Vα and TCR Vß and monitored changes in the distances and mutual orientations of these domains. In comparison to unbound states, we found decreased inter-domain movements in the simulations of bound states. Moreover, increased conformational flexibility was observed for the MHC α2-helix, the peptide, and for the complementary determining regions of the TCR in TCR-unbound states as compared to TCR-bound states.

Transforming Growth Factor-ß and Axl Induce CXCL5 and Neutrophil Recruitment in Hepatocellular Carcinoma.

Transforming growth factor (TGF)-ß suppresses early hepatocellular carcinoma (HCC) development but triggers pro-oncogenic abilities at later stages. Recent data suggest that the receptor tyrosine kinase Axl causes a TGF-ß switch toward dedifferentiation and invasion of HCC cells. Here, we analyzed two human cellular HCC models with opposing phenotypes in response to TGF-ß. Both HCC models showed reduced proliferation and clonogenic growth behavior following TGF-ß stimulation, although they exhibited differences in chemosensitivity and migratory abilities, suggesting that HCC cells evade traits of anti-oncogenic TGF-ß. Transcriptome profiling revealed differential regulation of the chemokine CXCL5, which positively correlated with TGF-ß expression in HCC patients. The expression and secretion of CXCL5 was dependent on Axl expression, suggesting that CXCL5 is a TGF-ß target gene collaborating with Axl signaling. Loss of either TGF-ß or Axl signaling abrogated CXCL5-dependent attraction of neutrophils. In mice, tumor formation of transplanted HCC cells relied on CXCL5 expression. In HCC patients, high levels of Axl and CXCL5 correlated with advanced tumor stages, recruitment of neutrophils into HCC tissue, and reduced survival. Conclusion: The synergy of TGF-ß and Axl induces CXCL5 secretion, causing the infiltration of neutrophils into HCC tissue. Intervention with TGF-ß/Axl/CXCL5 signaling may be an effective therapeutic strategy to combat HCC progression in TGF-ß-positive patients.

Co-expressed genes enhance precision of receptor status identification in breast cancer patients.

PURPOSE: Therapeutic decisions in breast cancer patients crucially depend on the status of estrogen receptor, progesterone receptor and HER2, obtained by immunohistochemistry (IHC). These are known to be inaccurate sometimes, and we demonstrate how to use gene-expression to increase precision of receptor status. METHODS: We downloaded data from 3241 breast cancer patients out of 36 clinical studies. For each receptor, we modelled the mRNA expression of the receptor gene and a co-gene by logistic regression. For each patient, predictions from logistic regression were merged with information from IHC on a probabilistic basis to arrive at a fused prediction result. RESULTS: We introduce Sankey diagrams to visualize the step by step increase of precision as information is added from gene expression: IHC-estimates are qualified as 'confirmed', 'rejected' or 'corrected'. Additionally, we introduce the category 'inconclusive' to spot those patients in need for additional assessments so as to increase diagnostic precision and safety. CONCLUSIONS: We demonstrate a sound mathematical basis for the fusion of information, even if partly contradictive. The concept is extendable to more than three sources of information, as particularly important for OMICS data. The overall number of undecidable cases is reduced as well as those assessed falsely. We outline how decision rules may be extended to also weigh consequences, being different in severity for false-positive and false-negative assessments, respectively. The possible benefit is demonstrated by comparing the disease free survival between patients whose IHC could be confirmed versus those for which it was corrected.

Galectin-8 induces functional disease markers in human osteoarthritis and cooperates with galectins-1 and -3.

The reading of glycan-encoded signals by tissue lectins is considered a major route of the flow of biological information in many (patho)physiological processes. The arising challenge for current research is to proceed from work on a distinct protein to family-wide testing of lectin function. Having previously identified homodimeric galectin-1 and chimera-type galectin-3 as molecular switches in osteoarthritis progression, we here provide proof-of-principle evidence for an intra-network cooperation of galectins with three types of modular architecture. We show that the presence of tandem-repeat-type galectin-8 significantly correlated with cartilage degeneration and that it is secreted by osteoarthritic chondrocytes. Glycan-inhibitable surface binding of galectin-8 to these cells increased gene transcription and the secretion of functional disease markers. The natural variant galectin-8 (F19Y) was less active than the prevalent form. Genome-wide array analysis revealed induction of a pro-degradative/inflammatory gene signature, largely under control of NF-κB signaling. This signature overlapped with respective gene-expression patterns elicited by galectins-1 and -3, but also presented supplementary features. Functional assays with mixtures of galectins that mimic the pathophysiological status unveiled cooperation between the three galectins. Our findings shape the novel concept to consider individual galectins as part of a so far not realized teamwork in osteoarthritis pathogenesis, with relevance beyond this disease.

Maternal embryonic leucine zipper kinase is a novel target for proliferation-associated high-risk myeloma.

Treatment of high-risk patients is a major challenge in multiple myeloma. This is especially true for patients assigned to the gene expression profiling-defined proliferation subgroup. Although recent efforts have identified some key players of proliferative myeloma, genetic interactions and players that can be targeted with clinically effective drugs have to be identified in order to overcome the poor prognosis of these patients. We therefore examined maternal embryonic leucine zipper kinase (MELK) for its implications in hyper-proliferative myeloma and analyzed the activity of the MELK inhibitor OTSSP167 both in vitro and in vivoMELK was found to be significantly overexpressed in the proliferative subgroup of myeloma. This finding translated into poor overall survival in patients with high vs low MELK expression. Enrichment analysis of upregulated genes in myeloma cells of MELKhigh patients confirmed the strong implications in myeloma cell proliferation. Targeting MELK with OTSSP167 impaired the growth and survival of myeloma cells, thereby affecting central survival factors such as MCL-1 and IRF4 This activity was also observed in the 5TGM.1 murine model of myeloma. OTSSP167 reduced bone marrow infiltration and serum paraprotein levels in a dose-dependent manner. In addition, we revealed a strong link between MELK and other proliferation-associated high-risk genes (PLK-1, EZH2, FOXM1, DEPDC1) and MELK inhibition also impaired the expression of those genes. We therefore conclude that MELK is an essential component of a proliferative gene signature and that pharmacological inhibition of MELK represents an attractive novel approach to overcome the poor prognosis of high-risk patients with a proliferative expression pattern.

Gene expression information improves reliability of receptor status in breast cancer patients.

Immunohistochemical (IHC) determination of receptor status in breast cancer patients is frequently inaccurate. Since it directs the choice of systemic therapy, it is essential to increase its reliability. We increase the validity of IHC receptor expression by additionally considering gene expression (GE) measurements. Crisp therapeutic decisions are based on IHC estimates, even if they are borderline reliable. We further improve decision quality by a responsibility function, defining a critical domain for gene expression. Refined normalization is devised to file any newly diagnosed patient into existing data bases. Our approach renders receptor estimates more reliable by identifying patients with questionable receptor status. The approach is also more efficient since the rate of conclusive samples is increased. We have curated and evaluated gene expression data, together with clinical information, from 2880 breast cancer patients. Combining IHC with gene expression information yields a method more reliable and also more efficient as compared to common practice up to now. Several types of possibly suboptimal treatment allocations, based on IHC receptor status alone, are enumerated. A 'therapy allocation check' identifies patients possibly miss-classified. Estrogen: false negative 8%, false positive 6%. Progesterone: false negative 14%, false positive 11%. HER2: false negative 2%, false positive 50%. Possible implications are discussed. We propose an 'expression look-up-plot', allowing for a significant potential to improve the quality of precision medicine. Methods are developed and exemplified here for breast cancer patients, but they may readily be transferred to diagnostic data relevant for therapeutic decisions in other fields of oncology.

Targeting of BMI-1 with PTC-209 shows potent anti-myeloma activity and impairs the tumour microenvironment.

BACKGROUND: The polycomb complex protein BMI-1 (BMI-1) is a putative oncogene reported to be overexpressed in multiple myeloma (MM). Silencing of BMI-1 was shown to impair the growth and survival of MM cells. However, therapeutic agents specifically targeting BMI-1 were not available so far. Here, we investigated PTC-209, a novel small molecule inhibitor of BMI-1, for its activity in MM. METHODS: BMI-1 expression was analysed in human MM cell lines and primary MM cells by using publically available gene expression profiling (GEP) data. The anti-MM activity of PTC-209 was investigated by viability testing, cell cycle analysis, annexin V and 7-AAD staining, quantification of cleaved poly(ADP-ribose) polymerase (PARP), JC-1 as well as colony formation assays. Deregulation of central myeloma growth and survival genes was studied by quantitative PCR and flow cytometry, respectively. In addition, the impact of PTC-209 on in vitro osteoclast, osteoblast and tube formation was analysed. RESULTS: We confirmed overexpression of BMI-1 in MM patients by using publically available GEP datasets. Of note, BMI-1 expression was further increased at relapse which translated into significantly shorter overall survival in relapsed/refractory patients treated with bortezomib or dexamethasone. Treatment with PTC-209 significantly decreased viable cell numbers in human MM cell lines, induced a G1 cell cycle arrest, promoted apoptosis and demonstrated synergistic activity with pomalidomide and carfilzomib. The anti-MM activity of PTC-209 was accompanied by a significant decrease of cyclin D1 (CCND1) and v-myc avian myelocytomatosis viral oncogene homolog (MYC) expression as well as upregulation of cyclin-dependent kinase inhibitor 1A (CDKN1A) and cyclin-dependent kinase inhibitor 1B (CDKN1B). We also observed upregulation of NOXA (up to 3.6 ± 1.2-fold induction, P = 0.009) and subsequent downregulation of myeloid cell leukemia 1 (MCL-1) protein levels, which likely mediates the apoptotic effects of PTC-209. Importantly, the anti-MM activity was upheld in the presence of stromal support or myeloma growth factors insulin-like growth factor 1 (IGF-1) and interleukin 6 (IL-6). In the MM microenvironment, PTC-209 impaired tube formation, impaired osteoclast development and decreased osteoblast formation in a dose-dependent manner (P < 0.01 at 1 µM, respectively). The latter might be attributed to an induction of DKK1 and was reversed by concurrent anti-DKK1 antibody treatment. CONCLUSIONS: We confirmed overexpression of BMI-1 in MM highlighting its role as an attractive drug target and reveal therapeutic targeting of BMI-1 by PTC-209 as a promising novel therapeutic intervention for MM.