HDACi vorinostat protects muscle from degeneration after acute rotator cuff injury in mice.

Aims: Rotator cuff (RC) injuries are characterized by tendon rupture, muscle atrophy, retraction, and fatty infiltration, which increase injury severity and jeopardize adequate tendon repair. Epigenetic drugs, such as histone deacetylase inhibitors (HDACis), possess the capacity to redefine the molecular signature of cells, and they may have the potential to inhibit the transformation of the fibro-adipogenic progenitors (FAPs) within the skeletal muscle into adipocyte-like cells, concurrently enhancing the myogenic potential of the satellite cells. Methods: HDACis were added to FAPs and satellite cell cultures isolated from mice. The HDACi vorinostat was additionally administered into a RC injury animal model. Histological analysis was carried out on the isolated supra- and infraspinatus muscles to assess vorinostat anti-muscle degeneration potential. Results: Vorinostat, a HDACi compound, blocked the adipogenic transformation of muscle-associated FAPs in culture, promoting myogenic progression of the satellite cells. Furthermore, it protected muscle from degeneration after acute RC in mice in the earlier muscle degenerative stage after tenotomy. Conclusion: The HDACi vorinostat may be a candidate to prevent early muscular degeneration after RC injury.

An atlas of cells in the human tonsil.

Palatine tonsils are secondary lymphoid organs (SLOs) representing the first line of immunological defense against inhaled or ingested pathogens. We generated an atlas of the human tonsil composed of >556,000 cells profiled across five different data modalities, including single-cell transcriptome, epigenome, proteome, and immune repertoire sequencing, as well as spatial transcriptomics. This census identified 121 cell types and states, defined developmental trajectories, and enabled an understanding of the functional units of the tonsil. Exemplarily, we stratified myeloid slan-like subtypes, established a BCL6 enhancer as locally active in follicle-associated T and B cells, and identified SIX5 as putative transcriptional regulator of plasma cell maturation. Analyses of a validation cohort confirmed the presence, annotation, and markers of tonsillar cell types and provided evidence of age-related compositional shifts. We demonstrate the value of this resource by annotating cells from B cell-derived mantle cell lymphomas, linking transcriptional heterogeneity to normal B cell differentiation states of the human tonsil.

Modulation of tumor microenvironment by targeting histone acetylation in bladder cancer.

Alterations in the epigenetic machinery in both tumor and immune cells contribute to bladder cancer (BC) development, constituting a promising target as an alternative therapeutic option. Here, we have explored the effects of a novel histone deacetylase (HDAC) inhibitor CM-1758, alone or in combination with immune checkpoint inhibitors (ICI) in BC. We determined the antitumor effects of CM-1758 in various BC cell lines together with the induction of broad transcriptional changes, with focus on the epigenetic regulation of PD-L1. Using an immunocompetent syngeneic mouse model of metastatic BC, we studied the effects of CM-1758 alone or in combination with anti-PD-L1 not only on tumor cells, but also in the tumor microenvironment. In vitro, we found that CM-1758 has cytotoxic and cytostatic effects either by inducing apoptosis or cell cycle arrest in BC cells at low micromolar levels. PD-L1 is epigenetically regulated by histone acetylation marks and is induced after treatment with CM-1758. We also observed that treatment with CM-1758 led to an important delay in tumor growth and a higher CD8 + T cell tumor infiltration. Moreover, anti-PD-L1 alone or in combination with CM-1758 reprogramed macrophage differentiation towards a M1-like polarization state and increased of pro-inflammatory cytokines systemically, yielding potential further antitumor effects. Our results suggest the possibility of combining HDAC inhibitors with immunotherapies for the management of advanced metastatic BC.

Lipid nanoparticles for siRNA delivery in cancer treatment.

RNA-based therapies, and siRNAs in particular, have attractive therapeutic potential for cancer treatment due to their ability to silence genes that are imperative for tumor progression. To be effective and solve issues related to their poor half-life and poor pharmacokinetic properties, siRNAs require adequate drug delivery systems that protect them from degradation and allow intracellular delivery. Among the various delivery vehicles available, lipid nanoparticles have emerged as the leading choice. These nanoparticles consist of cholesterol, phospholipids, PEG-lipids and most importantly ionizable cationic lipids. These ionizable lipids enable the binding of negatively charged siRNA, resulting in the formation of stable and neutral lipid nanoparticles with exceptionally high encapsulation efficiency. Lipid nanoparticles have demonstrated their effectiveness and versatility in delivering not only siRNAs but also multiple RNA molecules, contributing to their remarkable success. Furthermore, the advancement of efficient manufacturing techniques such as microfluidics, enables the rapid mixing of two miscible solvents without the need for shear forces. This facilitates the reproducible production of lipid nanoparticles and holds enormous potential for scalability. This is shown by the increasing number of preclinical and clinical trials evaluating the potential use of siRNA-LNPs for the treatment of solid and hematological tumors as well as in cancer immunotherapy. In this review, we provide an overview of the progress made on siRNA-LNP development for cancer treatment and outline the current preclinical and clinical landscape in this area. Finally, the translational challenges required to bring siRNA-LNPs further into the clinic are also discussed.

Preclinical models for prediction of immunotherapy outcomes and immune evasion mechanisms in genetically heterogeneous multiple myeloma.

The historical lack of preclinical models reflecting the genetic heterogeneity of multiple myeloma (MM) hampers the advance of therapeutic discoveries. To circumvent this limitation, we screened mice engineered to carry eight MM lesions (NF-κB, KRAS, MYC, TP53, BCL2, cyclin D1, MMSET/NSD2 and c-MAF) combinatorially activated in B lymphocytes following T cell-driven immunization. Fifteen genetically diverse models developed bone marrow (BM) tumors fulfilling MM pathogenesis. Integrative analyses of ∼500 mice and ∼1,000 patients revealed a common MAPK-MYC genetic pathway that accelerated time to progression from precursor states across genetically heterogeneous MM. MYC-dependent time to progression conditioned immune evasion mechanisms that remodeled the BM microenvironment differently. Rapid MYC-driven progressors exhibited a high number of activated/exhausted CD8+ T cells with reduced immunosuppressive regulatory T (Treg) cells, while late MYC acquisition in slow progressors was associated with lower CD8+ T cell infiltration and more abundant Treg cells. Single-cell transcriptomics and functional assays defined a high ratio of CD8+ T cells versus Treg cells as a predictor of response to immune checkpoint blockade (ICB). In clinical series, high CD8+ T/Treg cell ratios underlie early progression in untreated smoldering MM, and correlated with early relapse in newly diagnosed patients with MM under Len/Dex therapy. In ICB-refractory MM models, increasing CD8+ T cell cytotoxicity or depleting Treg cells reversed immunotherapy resistance and yielded prolonged MM control. Our experimental models enable the correlation of MM genetic and immunological traits with preclinical therapy responses, which may inform the next-generation immunotherapy trials.

Revealing cell populations catching the early stages of human embryo development in naive pluripotent stem cell cultures.

Naive human pluripotent stem cells (hPSCs) are defined as the in vitro counterpart of the human preimplantation embryo's epiblast and are used as a model system to study developmental processes. In this study, we report the discovery and characterization of distinct cell populations coexisting with epiblast-like cells in 5iLAF naive human induced PSC (hiPSC) cultures. It is noteworthy that these populations closely resemble different cell types of the human embryo at early developmental stages. While epiblast-like cells represent the main cell population, interestingly we detect a cell population with gene and transposable element expression profile closely resembling the totipotent eight-cell (8C)-stage human embryo, and three cell populations analogous to trophectoderm cells at different stages of their maturation process: transition, early, and mature stages. Moreover, we reveal the presence of cells resembling primitive endoderm. Thus, 5iLAF naive hiPSC cultures provide an excellent opportunity to model the earliest events of human embryogenesis, from the 8C stage to the peri-implantation period.

The transcriptomic landscape of elderly acute myeloid leukemia identifies B7H3 and BANP as a favorable signature in high-risk patients.

Acute myeloid leukemia (AML) in the elderly remains a clinical challenge, with a five-year overall survival rate below 10%. The current ELN 2017 genetic risk classification considers cytogenetic and mutational characteristics to stratify fit AML patients into different prognostic groups. However, this classification is not validated for elderly patients treated with a non-intensive approach, and its performance may be suboptimal in this context. Indeed, the transcriptomic landscape of AML in the elderly has been less explored and it might help stratify this group of patients. In the current study, we analyzed the transcriptome of 224 AML patients > 65 years-old at diagnosis treated in the Spanish PETHEMA-FLUGAZA clinical trial in order to identify new prognostic biomarkers in this population. We identified a specific transcriptomic signature for high-risk patients with mutated TP53 or complex karyotype, revealing that low expression of B7H3 gene with high expression of BANP gene identifies a subset of high-risk AML patients surviving more than 12 months. This result was further validated in the BEAT AML cohort. This unique signature highlights the potential of transcriptomics to identify prognostic biomarkers in in elderly AML.

Aptamers, a New Therapeutic Opportunity for the Treatment of Multiple Myeloma.

Multiple Myeloma (MM) remains an incurable disease due to high relapse rates and fast development of drug resistances. The introduction of monoclonal antibodies (mAb) has caused a paradigm shift in MM treatment, paving the way for targeted approaches with increased efficacy and reduced toxicities. Nevertheless, antibody-based therapies face several difficulties such as high immunogenicity, high production costs and limited conjugation capacity, which we believe could be overcome by the introduction of nucleic acid aptamers. Similar to antibodies, aptamers can bind to their targets with great affinity and specificity. However, their chemical nature reduces their immunogenicity and production costs, while it enables their conjugation to a wide variety of cargoes for their use as delivery agents. In this review, we summarize several aptamers that have been tested against MM specific targets with promising results, establishing the rationale for the further development of aptamer-based strategies against MM. In this direction, we believe that the study of novel plasma cell surface markers, the development of intracellular aptamers and further research on aptamers as building blocks for complex nanomedicines will lead to the generation of next-generation targeted approaches that will undoubtedly contribute to improve the management and life quality of MM patients.

NGS-Based Molecular Karyotyping of Multiple Myeloma: Results from the GEM12 Clinical Trial.

Next-generation sequencing (NGS) has greatly improved our ability to detect the genomic aberrations occurring in multiple myeloma (MM); however, its transfer to routine clinical labs and its validation in clinical trials remains to be established. We designed a capture-based NGS targeted panel to identify, in a single assay, known genetic alterations for the prognostic stratification of MM. The NGS panel was designed for the simultaneous study of single nucleotide and copy number variations, insertions and deletions, chromosomal translocations and V(D)J rearrangements. The panel was validated using a cohort of 149 MM patients enrolled in the GEM2012MENOS65 clinical trial. The results showed great global accuracy, with positive and negative predictive values close to 90% when compared with available data from fluorescence in situ hybridization and whole-exome sequencing. While the treatments used in the clinical trial showed high efficacy, patients defined as high-risk by the panel had shorter progression-free survival (p = 0.0015). As expected, the mutational status of TP53 was significant in predicting patient outcomes (p = 0.021). The NGS panel also efficiently detected clonal IGH rearrangements in 81% of patients. In conclusion, molecular karyotyping using a targeted NGS panel can identify relevant prognostic chromosomal abnormalities and translocations for the clinical management of MM patients.

Explainable artificial intelligence for precision medicine in acute myeloid leukemia.

Artificial intelligence (AI) can unveil novel personalized treatments based on drug screening and whole-exome sequencing experiments (WES). However, the concept of "black box" in AI limits the potential of this approach to be translated into the clinical practice. In contrast, explainable AI (XAI) focuses on making AI results understandable to humans. Here, we present a novel XAI method -called multi-dimensional module optimization (MOM)- that associates drug screening with genetic events, while guaranteeing that predictions are interpretable and robust. We applied MOM to an acute myeloid leukemia (AML) cohort of 319 ex-vivo tumor samples with 122 screened drugs and WES. MOM returned a therapeutic strategy based on the FLT3, CBFß-MYH11, and NRAS status, which predicted AML patient response to Quizartinib, Trametinib, Selumetinib, and Crizotinib. We successfully validated the results in three different large-scale screening experiments. We believe that XAI will help healthcare providers and drug regulators better understand AI medical decisions.

Identifying Lethal Dependencies with HUGE Predictive Power.

Recent functional genomic screens­such as CRISPR-Cas9 or RNAi screening­have fostered a new wave of targeted treatments based on the concept of synthetic lethality. These approaches identified LEthal Dependencies (LEDs) by estimating the effect of genetic events on cell viability. The multiple-hypothesis problem is related to a large number of gene knockouts limiting the statistical power of these studies. Here, we show that predictions of LEDs from functional screens can be dramatically improved by incorporating the "HUb effect in Genetic Essentiality" (HUGE) of gene alterations. We analyze three recent genome-wide loss-of-function screens­Project Score, CERES score and DEMETER score­identifying LEDs with 75 times larger statistical power than using state-of-the-art methods. Using acute myeloid leukemia, breast cancer, lung adenocarcinoma and colon adenocarcinoma as disease models, we validate that our predictions are enriched in a recent harmonized knowledge base of clinical interpretations of somatic genomic variants in cancer (AUROC > 0.87). Our approach is effective even in tumors with large genetic heterogeneity such as acute myeloid leukemia, where we identified LEDs not recalled by previous pipelines, including FLT3-mutant genotypes sensitive to FLT3 inhibitors. Interestingly, in-vitro validations confirm lethal dependencies of either NRAS or PTPN11 depending on the NRAS mutational status. HUGE will hopefully help discover novel genetic dependencies amenable for precision-targeted therapies in cancer. All the graphs showing lethal dependencies for the 19 tumor types analyzed can be visualized in an interactive tool.

Inhibiting Histone and DNA Methylation Improves Cancer Vaccination in an Experimental Model of Melanoma.

Immunotherapy has improved the treatment of malignant skin cancer of the melanoma type, yet overall clinical response rates remain low. Combination therapies could be key to meet this cogent medical need. Because epigenetic hallmarks represent promising combination therapy targets, we studied the immunogenic potential of a dual inhibitor of histone methyltransferase G9a and DNA methyltransferases (DNMTs) in the preclinical B16-OVA melanoma model. Making use of tumor transcriptomic and functional analyses, methylation-targeted epigenetic reprogramming was shown to induce tumor cell cycle arrest and apoptosis in vitro coinciding with transient tumor growth delay and an IFN-I response in immune-competent mice. In consideration of a potential impact on immune cells, the drug was shown not to interfere with dendritic cell maturation or T-cell activation in vitro. Notably, the drug promoted dendritic cell and, to a lesser extent, T-cell infiltration in vivo, yet failed to sensitize tumor cells to programmed cell death-1 inhibition. Instead, it increased therapeutic efficacy of TCR-redirected T cell and dendritic cell vaccination, jointly increasing overall survival of B16-OVA tumor-bearing mice. The reported data confirm the prospect of methylation-targeted epigenetic reprogramming in melanoma and sustain dual G9a and DNMT inhibition as a strategy to tip the cancer-immune set-point towards responsiveness to active and adoptive vaccination against melanoma.

BOSO: A novel feature selection algorithm for linear regression with high-dimensional data.

With the frenetic growth of high-dimensional datasets in different biomedical domains, there is an urgent need to develop predictive methods able to deal with this complexity. Feature selection is a relevant strategy in machine learning to address this challenge. We introduce a novel feature selection algorithm for linear regression called BOSO (Bilevel Optimization Selector Operator). We conducted a benchmark of BOSO with key algorithms in the literature, finding a superior accuracy for feature selection in high-dimensional datasets. Proof-of-concept of BOSO for predicting drug sensitivity in cancer is presented. A detailed analysis is carried out for methotrexate, a well-studied drug targeting cancer metabolism.

G9a inhibition by CM-272: Developing a novel anti-tumoral strategy for castration-resistant prostate cancer using 2D and 3D in vitro models.

Castration-resistant prostate cancer (CRPC) is an incurable form of prostate cancer (PCa), with DNMT1 and G9a being reported as overexpressed, rendering them highly attractive targets for precision medicine. CM-272 is a dual inhibitor of both methyltransferases' activity. Herein, we assessed the response of different PCa cell lines to CM-272, in both 2D and 3D models, and explored the molecular mechanisms underlying CM-272 inhibitory effects. CRPC tissues displayed significantly higher DNMT1, G9a and H3K9me2 expression than localized PCa. In vitro, CM-272 caused a significant decrease in PCa cell viability and proliferation alongside with increased apoptotic levels. We disclose that, under the evaluated dose, CM-272 led to G9a activity inhibition, while not significantly affecting DNMT1 activity. Upon G9a knockdown, DU145 and PC3 showed decreased cell viability. Remarkably, DU145 cells treated with CM-272 or with G9a knockdown displayed no differences in viability, suggesting a SET-dependent mechanism. Contrarily, PC3 cell viability impact was higher in G9a knockdown, compared with CM-272 treatment, suggesting an additional G9a function. Moreover, DU145 cells overexpressing catalytically functional G9a disclosed higher resistance to CM-272 treatment, reinforcing that the drug mechanism of action is dependent on G9a catalytic function. Importantly, we successfully assembled spheroids from several prostate cell lines. Our results showed that CM-272 retained its anti-tumoral effects in 3D PCa models, leading to a clear reduction in cancer cell survival. We concluded that inhibition of G9a methyltransferase activity by CM-272 has anti-tumor effect in PCa cells, holding therapeutic potential against CRPC.

A network-based approach to integrate nutrient microenvironment in the prediction of synthetic lethality in cancer metabolism.

Synthetic Lethality (SL) is currently defined as a type of genetic interaction in which the loss of function of either of two genes individually has limited effect in cell viability but inactivation of both genes simultaneously leads to cell death. Given the profound genomic aberrations acquired by tumor cells, which can be systematically identified with -omics data, SL is a promising concept in cancer research. In particular, SL has received much attention in the area of cancer metabolism, due to the fact that relevant functional alterations concentrate on key metabolic pathways that promote cellular proliferation. With the extensive prior knowledge about human metabolic networks, a number of computational methods have been developed to predict SL in cancer metabolism, including the genetic Minimal Cut Sets (gMCSs) approach. A major challenge in the application of SL approaches to cancer metabolism is to systematically integrate tumor microenvironment, given that genetic interactions and nutritional availability are interconnected to support proliferation. Here, we propose a more general definition of SL for cancer metabolism that combines genetic and environmental interactions, namely loss of gene functions and absence of nutrients in the environment. We extend our gMCSs approach to determine this new family of metabolic synthetic lethal interactions. A computational and experimental proof-of-concept is presented for predicting the lethality of dihydrofolate reductase (DHFR) inhibition in different environments. Finally, our approach is applied to identify extracellular nutrient dependences of tumor cells, elucidating cholesterol and myo-inositol depletion as potential vulnerabilities in different malignancies.

Association of ABCA4 Gene Polymorphisms with Cleft Lip with or without Cleft Palate in the Polish Population.

BACKGROUND: Non-syndromic cleft lip with/without cleft palate (NSCL/P) is a common congenital condition with a complex aetiology reflecting multiple genetic and environmental factors. Single nucleotide polymorphisms (SNPs) in ABCA4 have been associated with NSCL/P in several studies, although there are some inconsistent results. This study aimed to evaluate whether two SNPs in ABCA4, namely rs4147811 and rs560426, are associated with NSCL/P occurrence in the Polish population. METHODS: The study included 627 participants: 209 paediatric patients with NSCL/P and 418 healthy newborn controls. DNA was isolated from the saliva of NSCL/P patients and from umbilical cord blood in the controls. Genotyping of rs4147811 and rs560426 was performed using quantitative PCR. RESULTS: The rs4147811 (AG genotype) SNP in ABCA4 was associated with a decreased risk of NSCL/P (odds ratio (OR) 0.57; 95% confidence interval (CI) 0.39-0.84; p = 0.004), whereas the rs560426 (GG genotype) SNP was associated with an increased risk of NSCL/P (OR 2.13; 95% CI 1.31-3.48; p = 0.002). LIMITATIONS: This study-based on the correlation between single genetic variants and the occurrence of different phenotypes-might have limited power in detecting relevant, complex inheritance patterns. ORs are often low to moderate when investigating the association of single genes with the risk of a complex trait. Another limitation was the small number of available NSCL/P samples. CONCLUSIONS: The results suggest that genetic variations in ABCA4 are important risk markers of NSCL/P in the Polish population. Further investigation in a larger study group is warranted.

Cereblon enhancer methylation and IMiD resistance in multiple myeloma.

Cereblon is the direct binding target of the immunomodulatory drugs (IMiDs) that are commonly used to treat multiple myeloma (MM), the second most frequent hematologic malignancy. Patients respond well to initial treatment with IMiDs, but virtually all patients develop drug resistance over time, and the underlying mechanisms are poorly understood. We identified an as yet undescribed DNA hypermethylation in an active intronic CRBN enhancer. Differential hypermethylation in this region was found to be increased in healthy plasma cells, but was more pronounced in IMiD-refractory MM. Methylation significantly correlated with decreased CRBN expression levels. DNA methyltransferase inhibitor (DNTMi) in vitro experiments induced CRBN enhancer demethylation, and sensitizing effects on lenalidomide treatment were observed in 2 MM cell lines. Thus, we provide first evidence that aberrant CRBN DNA methylation is a novel mechanism of IMiD resistance in MM and may predict IMiD response prior to treatment.