Engineering small-molecule and protein drugs for targeting bone tumors.

Bone cancer is common and severe. Both primary (e.g., osteosarcoma, Ewing sarcoma) and secondary (e.g., metastatic) bone cancers lead to significant health problems and death. Currently, treatments such as chemotherapy, hormone therapy, and radiation therapy are used to treat bone cancer, but they often only shrink or slow tumor growth and do not eliminate cancer completely. The bone microenvironment contributes unique signals that influence cancer growth, immunogenicity, and metastasis. Traditional cancer therapies have limited effectiveness due to off-target effects and poor distribution on bones. As a result, therapies with improved specificity and efficacy for treating bone tumors are highly needed. One of the most promising strategies involves the targeted delivery of pharmaceutical agents to the site of bone cancer by introduction of bone-targeting moieties, such as bisphosphonates or oligopeptides. These moieties have high affinities to the bone hydroxyapatite matrix, a structure found exclusively in skeletal tissue, and can enhance the targeting ability and efficacy of anticancer drugs when combating bone tumors. This review focuses on the engineering of small molecules and proteins with bone-targeting moieties for the treatment of bone tumors.

PancanQTLv2.0: a comprehensive resource for expression quantitative trait loci across human cancers.

Expression quantitative trait locus (eQTL) analysis is a powerful tool used to investigate genetic variations in complex diseases, including cancer. We previously developed a comprehensive database, PancanQTL, to characterize cancer eQTLs using The Cancer Genome Atlas (TCGA) dataset, and linked eQTLs with patient survival and GWAS risk variants. Here, we present an updated version, PancanQTLv2.0 (https://hanlaboratory.com/PancanQTLv2/), with advancements in fine-mapping causal variants for eQTLs, updating eQTLs overlapping with GWAS linkage disequilibrium regions and identifying eQTLs associated with drug response and immune infiltration. Through fine-mapping analysis, we identified 58 747 fine-mapped eQTLs credible sets, providing mechanic insights of gene regulation in cancer. We further integrated the latest GWAS Catalog and identified a total of 84 592 135 linkage associations between eQTLs and the existing GWAS loci, which represents a remarkable ∼50-fold increase compared to the previous version. Additionally, PancanQTLv2.0 uncovered 659516 associations between eQTLs and drug response and identified 146948 associations between eQTLs and immune cell abundance, providing potentially clinical utility of eQTLs in cancer therapy. PancanQTLv2.0 expanded the resources available for investigating gene expression regulation in human cancers, leading to advancements in cancer research and precision oncology.

Cell Population Growth Kinetics in the Presence of Stochastic Heterogeneity of Cell Phenotype.

Recent studies at individual cell resolution have revealed phenotypic heterogeneity in nominally clonal tumor cell populations. The heterogeneity affects cell growth behaviors, which can result in departure from the idealized uniform exponential growth of the cell population. Here we measured the stochastic time courses of growth of an ensemble of populations of HL60 leukemia cells in cultures, starting with distinct initial cell numbers to capture a departure from the uniform exponential growth model for the initial growth ("take-off"). Despite being derived from the same cell clone, we observed significant variations in the early growth patterns of individual cultures with statistically significant differences in growth dynamics, which could be explained by the presence of inter-converting subpopulations with different growth rates, and which could last for many generations. Based on the hypothesis of existence of multiple subpopulations, we developed a branching process model that was consistent with the experimental observations.

Cell population growth kinetics in the presence of stochastic heterogeneity of cell phenotype.

Recent studies at individual cell resolution have revealed phenotypic heterogeneity in nominally clonal tumor cell populations. The heterogeneity affects cell growth behaviors, which can result in departure from the idealized uniform exponential growth of the cell population. Here we measured the stochastic time courses of growth of an ensemble of populations of HL60 leukemia cells in cultures, starting with distinct initial cell numbers to capture a departure from the uniform exponential growth model for the initial growth ("take-off"). Despite being derived from the same cell clone, we observed significant variations in the early growth patterns of individual cultures with statistically significant differences in growth dynamics, which could be explained by the presence of inter-converting subpopulations with different growth rates, and which could last for many generations. Based on the hypothesis of existence of multiple subpopulations, we developed a branching process model that was consistent with the experimental observations.

Cell Population Growth Kinetics in the Presence of Stochastic Heterogeneity of Cell Phenotype.

Recent studies at individual cell resolution have revealed phenotypic heterogeneity in nominally clonal tumor cell populations. The heterogeneity affects cell growth behaviors, which can result in departure from the idealized exponential growth. Here we measured the stochastic time courses of growth of an ensemble of populations of HL60 leukemia cells in cultures, starting with distinct initial cell numbers to capture the departure from the exponential growth model in the initial growth phase. Despite being derived from the same cell clone, we observed significant variations in the early growth patterns of individual cultures with statistically significant differences in growth kinetics and the presence of subpopulations with different growth rates that endured for many generations. Based on the hypothesis of existence of multiple inter-converting subpopulations, we developed a branching process model that captures the experimental observations.

Fluorescent Platforms for RNA Chemical Biology Research.

Efficient detection and observation of dynamic RNA changes remain a tremendous challenge. However, the continuous development of fluorescence applications in recent years enhances the efficacy of RNA imaging. Here we summarize some of these developments from different aspects. For example, single-molecule fluorescence in situ hybridization (smFISH) can detect low abundance RNA at the subcellular level. A relatively new aptamer, Mango, is widely applied to label and track RNA activities in living cells. Molecular beacons (MBs) are valid for quantifying both endogenous and exogenous mRNA and microRNA (miRNA). Covalent binding enzyme labeling fluorescent group with RNA of interest (ROI) partially overcomes the RNA length limitation associated with oligonucleotide synthesis. Forced intercalation (FIT) probes are resistant to nuclease degradation upon binding to target RNA and are used to visualize mRNA and messenger ribonucleoprotein (mRNP) activities. We also summarize the importance of some fluorescence spectroscopic techniques in exploring the function and movement of RNA. Single-molecule fluorescence resonance energy transfer (smFRET) has been employed to investigate the dynamic changes of biomolecules by covalently linking biotin to RNA, and a focus on dye selection increases FRET efficiency. Furthermore, the applications of fluorescence assays in drug discovery and drug delivery have been discussed. Fluorescence imaging can also combine with RNA nanotechnology to target tumors. The invention of novel antibacterial drugs targeting non-coding RNAs (ncRNAs) is also possible with steady-state fluorescence-monitored ligand-binding assay and the T-box riboswitch fluorescence anisotropy assay. More recently, COVID-19 tests using fluorescent clustered regularly interspaced short palindromic repeat (CRISPR) technology have been demonstrated to be efficient and clinically useful. In summary, fluorescence assays have significant applications in both fundamental and clinical research and will facilitate the process of RNA-targeted new drug discovery, therefore deserving further development and updating.

A model for the intrinsic limit of cancer therapy: Duality of treatment-induced cell death and treatment-induced stemness.

Intratumor cellular heterogeneity and non-genetic cell plasticity in tumors pose a recently recognized challenge to cancer treatment. Because of the dispersion of initial cell states within a clonal tumor cell population, a perturbation imparted by a cytocidal drug only kills a fraction of cells. Due to dynamic instability of cellular states the cells not killed are pushed by the treatment into a variety of functional states, including a "stem-like state" that confers resistance to treatment and regenerative capacity. This immanent stress-induced stemness competes against cell death in response to the same perturbation and may explain the near-inevitable recurrence after any treatment. This double-edged-sword mechanism of treatment complements the selection of preexisting resistant cells in explaining post-treatment progression. Unlike selection, the induction of a resistant state has not been systematically analyzed as an immanent cause of relapse. Here, we present a generic elementary model and analytical examination of this intrinsic limitation to therapy. We show how the relative proclivity towards cell death versus transition into a stem-like state, as a function of drug dose, establishes either a window of opportunity for containing tumors or the inevitability of progression following therapy. The model considers measurable cell behaviors independent of specific molecular pathways and provides a new theoretical framework for optimizing therapy dosing and scheduling as cancer treatment paradigms move from "maximal tolerated dose," which may promote therapy induced-stemness, to repeated "minimally effective doses" (as in adaptive therapies), which contain the tumor and avoid therapy-induced progression.

Isolated Pyridoxine Deficiency Presenting as Muscle Spasms in a Patient With Type 2 Diabetes: A Case Report and Literature Review.

Pyridoxine is an important co-factor for many biochemical reactions in cellular metabolism related to the synthesis and catabolism of amino acids, fatty acids, neurotransmitters. Deficiency of pyridoxine results in impaired transcellular signaling between neurons and presents with muscular convulsions, hyperirritability, and peripheral neuropathy. Deficiency of pyridoxine is usually found in association with other vitamin B deficiencies such as folate (vitamin B9) and cobalamin (vitamin B12). Isolated pyridoxine deficiency is extremely rare. We present the case of a 59-year old female with type 2 diabetes who complained of painful muscle spasms. Her muscle spasms involved in both feet, which have spread proximally to her legs. She also experienced intermittent muscle spasms in her left arm, which is not alleviated by baclofen, cyclobenzaprine. Her plasma pyridoxal 5-phosphate confirmed pyridoxine deficiency. Vitamins B1, B3, B12, and folate were within normal limits. The patient received standard-dose intramuscular pyridoxine injections for three weeks followed by oral supplements for 3 months and her symptoms resolved. This case illustrates the rare instance of isolated pyridoxine deficiency in type 2 diabetes patient manifesting as myoclonic muscle spasms involving the legs and arms in the absence of objective polyneuropathy. Pyridoxine level should, therefore, be assessed in patients with type 2 diabetes, including newly diagnosed patients.

TGFß-blockade uncovers stromal plasticity in tumors by revealing the existence of a subset of interferon-licensed fibroblasts.

Despite the increasing interest in targeting stromal elements of the tumor microenvironment, we still face tremendous challenges in developing adequate therapeutics to modify the tumor stromal landscape. A major obstacle to this is our poor understanding of the phenotypic and functional heterogeneity of stromal cells in tumors. Herein, we perform an unbiased interrogation of tumor mesenchymal cells, delineating the co-existence of distinct subsets of cancer-associated fibroblasts (CAFs) in the microenvironment of murine carcinomas, each endowed with unique phenotypic features and functions. Furthermore, our study shows that neutralization of TGFß in vivo leads to remodeling of CAF dynamics, greatly reducing the frequency and activity of the myofibroblast subset, while promoting the formation of a fibroblast population characterized by strong response to interferon and heightened immunomodulatory properties. These changes correlate with the development of productive anti-tumor immunity and greater efficacy of PD1 immunotherapy. Along with providing the scientific rationale for the evaluation of TGFß and PD1 co-blockade in the clinical setting, this study also supports the concept of plasticity of the stromal cell landscape in tumors, laying the foundation for future investigations aimed at defining pathways and molecules to program CAF composition for cancer therapy.

Liraglutide improves insulin sensitivity in high fat diet induced diabetic mice through multiple pathways.

Glucagon like peptide-1 (GLP-1) promotes postprandial insulin secretion. Liraglutide, a full agonist of the GLP-1 receptor, reduces body weight, improve insulin sensitivity, and alleviate Non Alcoholic Fatty Liver Disease (NAFLD). However, the underlying mechanisms remain unclear. This study aims to explore the underlying mechanisms and cell signaling pathways involved in the anti-obesity and anti-inflammatory effects of liraglutide. Mice were fed a high fat high sucrose diet to induce diabetes, diabetic mice were divided into two groups and injected with liraglutide or vehicle for 14 days. Liraglutide treatment improved insulin sensitivity, accompanied with reduced expression of the phosphorylated Acetyl-CoA carboxylase-2 (ACC2) and upregulation of long chain acyl CoA dehydrogenase (LCAD) in insulin sensitive tissues. Furthermore, liraglutide induced adenosine monophosphate-activated protein kinase-α (AMPK-α) and Sirtuin-1(Sirt-1) protein expression in liver and perigonadal fat. Liraglutide induced elevation of fatty acid oxidation in these tissues may be mediated through the AMPK-Sirt-1 cell signaling pathway. In addition, liraglutide induced brown adipocyte differentiation in skeletal muscle, including induction of uncoupling protein-1 (UCP-1) and PR-domain-containing-16 (PRDM-16) protein in association with induction of SIRT-1. Importantly, liraglutide displayed anti-inflammation effect. Specifically, liraglutide led to a significant reduction in circulating interleukin-1 ß (IL-1 ß) and interleukin-6 (IL-6) as well as hepatic IL-1 ß and IL-6 content. The expression of inducible nitric oxide synthase (iNOS-1) and cyclooxygenase-2 (COX-2) in insulin sensitive tissues was also reduced following liraglutide treatment. In conclusion, liraglutide improves insulin sensitivity through multiple pathways resulting in reduction of inflammation, elevation of fatty acid oxidation, and induction of adaptive thermogenesis.

Evaluation of Stein-O'Brien et al.: To See a World in a Grain of Sand-How to Reveal a Common Latent Space through Multiple Platform Omics Data.

One snapshot of the peer review process for "Decomposing Cell Identity for Transfer Learning across Cellular Measurements, Platforms, Tissues, and Species" (Stein-O'Brien et al., 2019).

Predicting drug synergy for precision medicine using network biology and machine learning.

Identification of effective drug combinations for patients is an expensive and time-consuming procedure, especially for in vitro experiments. To accelerate the synergistic drug discovery process, we present a new classification model to identify more effective anti-cancer drug pairs using in silico network biology approach. Based on the hypotheses that the drug synergy comes from the collective effects on the biological network, therefore, we developed six network biology features, including overlap and distance of drug perturbation network, that were derived by using individual drug-perturbed transcriptome profiles and the relevant biological network analysis. Using publicly available drug synergy databases and three machine-learning (ML) methods, the model was trained to discriminate the positive (synergistic) and negative (nonsynergistic) drug combinations. The proposed models were evaluated on the test cases to predict the most promising network biology feature, which is the network degree activity, i.e. the synergistic effect between drug pairs is mainly accounted by the complementary signaling pathways or molecular networks from two drugs.

Berberine hydrochloride protects against cytokine-induced inflammation through multiple pathways in undifferentiated C2C12 myoblast cells.

Obesity is associated with skeletal muscle insulin resistance and the development of metabolic syndrome. Undifferentiated skeletal muscle cells are sensitive to oxidative stress. Berberine hydrochloride (BBR) improves insulin resistance and exhibits anti-inflammatory properties. However, the underlying mechanism and the cell signaling pathways involved remain largely elusive. We therefore investigated the anti-inflammatory effects of BBR and the signaling pathways using skeletal C2C12 myoblast cells. Undifferentiated C2C12 myoblast cells were treated with interleukin-1ß alone or in combination with tumor necrosis factor-α in the presence or absence of BBR. We found that BBR reduced the cytokine-induced expression of inducible nitric oxide synthase and stress-related kinases including p-38 mitogen-activated protein kinase, nuclear factor kappa B (NF-κB), and stress-activated protein kinases/Jun amino-terminal kinases (SAPK/JNK) in C2C12 myoblast cells. Furthermore, BBR reversed cytokine-mediated suppression of AMP-activated protein kinase (AMPKα), sirtuin-1 (SIRT-1), and PPAR-γ coactivator-1α (PGC-1α). In addition, cytokine-induced reduction of mitochondrial marker proteins and function were rescued after BBR treatment. Catalase, an antioxidant enzyme, was elevated after BBR treatment. Our results demonstrate that BBR ameliorates cytokine-induced inflammation. The anti-inflammatory effect of BBR in skeletal progenitor cells is mediated through pathways including activation of the AMPKα-SIRT-1-PGC-1α, inhibition of the mitogen-activated protein kinase 4 (MKK4)-SAPK/JNK-C-JUN, as well as protection of mitochondrial bioenergetics. BBR may be a potential medication for metabolic syndrome.

A novel approach to label bone marrow-derived mesenchymal stem cells with mixed-surface PAMAM dendrimers.

BACKGROUND: Transplantation of mesenchymal stem cells has created enormous opportunities as a potential treatment for various diseases including neurodegenerative diseases. Given current techniques, such as Hoechst labeling, have safety and leakage issues, our study focused, as a proof-of-concept, on a new dendrimer-based technique for labeling these stem cells to ensure their efficacy and safety following transplantation into the brain of a healthy mice. METHODS AND RESULTS: The bone marrow-derived mesenchymal stem cells (BM-MSCs) were labeled using polyaminoamine (PAMAM) dendrimers following which their stemness based on their proliferation and differentiation ability were analyzed by gold standard methods. These labeled BM-MSCs were transplanted into the striatum of C57BL/6J mice and were tracked using in vivo imaging system (IVIS) and analyzed using tissue imaging, 2 weeks after transplantation. Our results showed that the dendrimer-labeled BM-MSCs were able to successfully maintain their stemness and were tracked in vivo following transplantation. Unlike Hoechst, we did not find the dendrimers to be leaking out of the cells and were very specific to the cells that up took the dendrimers. Moreover, no adverse events were found in the transplanted animals proving that this is a safer method. CONCLUSIONS: Labeling BM-MSCs using fluorescently tagged PAMAM dendrimers can be used as a potentially safe and efficient method for labeling cells, particularly stem cells, in vitro and in vivo following transplantation in rodents.

A CD4+ T cell population expanded in lupus blood provides B cell help through interleukin-10 and succinate.

Understanding the mechanisms underlying autoantibody development will accelerate therapeutic target identification in autoimmune diseases such as systemic lupus erythematosus (SLE)1. Follicular helper T cells (TFH cells) have long been implicated in SLE pathogenesis. Yet a fraction of autoantibodies in individuals with SLE are unmutated, supporting that autoreactive B cells also differentiate outside germinal centers2. Here, we describe a CXCR5-CXCR3+ programmed death 1 (PD1)hiCD4+ helper T cell population distinct from TFH cells and expanded in both SLE blood and the tubulointerstitial areas of individuals with proliferative lupus nephritis. These cells produce interleukin-10 (IL-10) and accumulate mitochondrial reactive oxygen species as the result of reverse electron transport fueled by succinate. Furthermore, they provide B cell help, independently of IL-21, through IL-10 and succinate. Similar cells are generated in vitro upon priming naive CD4+ T cells with plasmacytoid dendritic cells activated with oxidized mitochondrial DNA, a distinct class of interferogenic toll-like receptor 9 ligand3. Targeting this pathway might blunt the initiation and/or perpetuation of extrafollicular humoral responses in SLE.

Liraglutide induces beige fat development and promotes mitochondrial function in diet induced obesity mice partially through AMPK-SIRT-1-PGC1-α cell signaling pathway.

PURPOSE: Glucagon like peptide-1 (GLP-1) is produced to induce postprandial insulin secretion. Liraglutide, a full agonist of the GLP-1 receptor, has a protective effect on weight gain in obese subjects. Brown adipose tissue plays a major role in the control of energy balance and is known to be involved in the weight loss regulated by liraglutide. The putative anti-obesity properties of liraglutide and the cell signaling pathways involved were examined. METHODS: Four groups of C57/BL6 mice fed with chow or HFHS diet were injected with either liraglutide or vehicle for four weeks. Western blotting was used to analyze protein expression. RESULTS: Liraglutide significantly attenuated the weight gain in mice fed with HFHS diet and was associated with significant reductions of epididymal fat and inguinal fat mass. Furthermore, liraglutide significantly upregulated the expression of brown adipose-specific markers in perigonadal fat in association with upregulation of AMPK-SIRT-1-PGC1-α cell signaling. However, elevation of brown fat markers in skeletal muscle was only observed in HFHS diet fed mice after liraglutide treatment, and AMPK-SIRT-1 cell signaling is not involved in this process. CONCLUSIONS: the anti-obesity effect of liraglutide occurs through adaptive thermogenesis and may act through different cell signaling pathways in fat and skeletal muscle tissue. Liraglutide induces beige fat development partially through the AMPK-SIRT-1-PGC1-α cell signaling pathway. Therefore, liraglutide is a potential medication for obesity prevention and in targeting pre-diabetics.

Author Correction: Extracting Intercellular Signaling Network of Cancer Tissues using Ligand-Receptor Expression Patterns from Whole-tumor and Single-cell Transcriptomes.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Diabetes and Associated Cardiovascular Complications in American Indians/Alaskan Natives: A Review of Risks and Prevention Strategies.

Diabetes mellitus (DM) is the seventh leading cause of death in the United States and the leading cause of death in the U.S. American Indian/Alaskan Natives (AI/ANs), who comprise only 2% of the total population. The AI/AN population has a high prevalence of DM in adults aged 20 years or older and is developing DM at a younger age than the general U.S. POPULATION: DM is a major risk factor for cardiovascular disease (CVD), and mortality from CVD is higher in AI/ANs than the general population, as is the prevalence of stroke and 1-year poststroke mortality for both genders when compared to non-Hispanic whites. A genome-wide scan found a number of chromosome linkages in the AI/AN population that suggest that genetic factors may contribute to their high risk of DM and CVD. Importantly, studies also suggest that in addition to race/ethnicity, cultural norms and historic conditions play important roles in the prevalence of DM and CVD in this population. Therefore, multiple factors should be taken into consideration when establishing prevention programs to decrease the prevalence of obesity, diabetes, and CVD incidence among adults and children in the AI/AN population. Prevention programs should focus on behavioral risk factors and lifestyle changes like encouraging smoking cessation, healthy diet, and increased physical activity while taking into consideration cultural, economic, and geographic factors.

Metformin: An Old Drug with New Applications.

Metformin is a biguanide drug that has been used to treat type 2 diabetes mellitus for more than 60 years. The United Kingdom Prospective Diabetic Study (UKPDS) has shown metformin to improve mortality rates in diabetes patients, and recent studies suggest metformin has additional effects in treating cancer, obesity, nonalcoholic fatty liver disease (NAFLD), polycystic ovary syndrome (PCOS), and metabolic syndrome. Metformin has also been shown to alleviate weight gain associated with antipsychotic medication. Metformin has recently been extensively studied and emerging evidence suggests metformin decreases hepatocyte triglyceride accumulation in NAFLD and prevents liver tumorigenesis. Interestingly, studies have also shown metformin reduces visceral fat, suppresses white-adipose-tissue (WAT) extracellular matrix remodeling, and inhibits obesity-induced inflammation. However, clinical evidence for using metformin to treat NAFLD, cancer, metabolic syndrome, or to prevent hepatocellular carcinoma in NAFLD patients is lacking. This review therefore addresses the potential beneficial effects of metformin on NAFLD, its role in protecting against cardiac ischemia⁻reperfusion (I/R) injury, atherosclerosis, glucotoxicity, and lipotoxicity induced oxidative and ER stress in pancreatic ß-cell dysfunction, as well as its underlying molecular mechanisms of action.