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.

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.

Immunoglobulin E signal inhibition during allergen ingestion leads to reversal of established food allergy and induction of regulatory T cells.

Immunoglobulin E (IgE) antibodies are known for triggering immediate hypersensitivity reactions such as food anaphylaxis. In this study, we tested whether they might additionally function to amplify nascent antibody and T helper 2 (Th2) cell-mediated responses to ingested proteins and whether blocking IgE would modify sensitization. By using mice harboring a disinhibited form of the IL-4 receptor, we developed an adjuvant-free model of peanut allergy. Mast cells and IgE were required for induction of antibody and Th2-cell-mediated responses to peanut ingestion and they impaired regulatory T (Treg) cell induction. Mast-cell-targeted genetic deletion of the FcεRI signaling kinase Syk or Syk blockade also prevented peanut sensitization. In mice with established allergy, Syk blockade facilitated desensitization and induction of Treg cells, which suppressed allergy when transferred to naive recipients. Our study suggests a key role for IgE in driving Th2 cell and IgE responses while suppressing Treg cells in food allergy.

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.

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.

Cell population structure prior to bifurcation predicts efficiency of directed differentiation in human induced pluripotent cells.

Steering the differentiation of induced pluripotent stem cells (iPSCs) toward specific cell types is crucial for patient-specific disease modeling and drug testing. This effort requires the capacity to predict and control when and how multipotent progenitor cells commit to the desired cell fate. Cell fate commitment represents a critical state transition or "tipping point" at which complex systems undergo a sudden qualitative shift. To characterize such transitions during iPSC to cardiomyocyte differentiation, we analyzed the gene expression patterns of 96 developmental genes at single-cell resolution. We identified a bifurcation event early in the trajectory when a primitive streak-like cell population segregated into the mesodermal and endodermal lineages. Before this branching point, we could detect the signature of an imminent critical transition: increase in cell heterogeneity and coordination of gene expression. Correlation analysis of gene expression profiles at the tipping point indicates transcription factors that drive the state transition toward each alternative cell fate and their relationships with specific phenotypic readouts. The latter helps us to facilitate small molecule screening for differentiation efficiency. To this end, we set up an analysis of cell population structure at the tipping point after systematic variation of the protocol to bias the differentiation toward mesodermal or endodermal cell lineage. We were able to predict the proportion of cardiomyocytes many days before cells manifest the differentiated phenotype. The analysis of cell populations undergoing a critical state transition thus affords a tool to forecast cell fate outcomes and can be used to optimize differentiation protocols to obtain desired cell populations.

Cell Fate Decision as High-Dimensional Critical State Transition.

Cell fate choice and commitment of multipotent progenitor cells to a differentiated lineage requires broad changes of their gene expression profile. But how progenitor cells overcome the stability of their gene expression configuration (attractor) to exit the attractor in one direction remains elusive. Here we show that commitment of blood progenitor cells to the erythroid or myeloid lineage is preceded by the destabilization of their high-dimensional attractor state, such that differentiating cells undergo a critical state transition. Single-cell resolution analysis of gene expression in populations of differentiating cells affords a new quantitative index for predicting critical transitions in a high-dimensional state space based on decrease of correlation between cells and concomitant increase of correlation between genes as cells approach a tipping point. The detection of "rebellious cells" that enter the fate opposite to the one intended corroborates the model of preceding destabilization of a progenitor attractor. Thus, early warning signals associated with critical transitions can be detected in statistical ensembles of high-dimensional systems, offering a formal theory-based approach for analyzing single-cell molecular profiles that goes beyond current computational pattern recognition, does not require knowledge of specific pathways, and could be used to predict impending major shifts in development and disease.

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.

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.

Gene-pair expression signatures reveal lineage control.

The distinct cell types of multicellular organisms arise owing to constraints imposed by gene regulatory networks on the collective change of gene expression across the genome, creating self-stabilizing expression states, or attractors. We curated human expression data comprising 166 cell types and 2,602 transcription-regulating genes and developed a data-driven method for identifying putative determinants of cell fate built around the concept of expression reversal of gene pairs, such as those participating in toggle-switch circuits. This approach allows us to organize the cell types into their ontogenic lineage relationships. Our method identifies genes in regulatory circuits that control neuronal fate, pluripotency and blood cell differentiation, and it may be useful for prioritizing candidate factors for direct conversion of cell fate.

MicroRNAs are key regulators of brown adipogenesis.

The recent discovery of microRNA, thousands of short, non-coding strands of RNA that regulate gene expressions on the transcriptional level throughout the body, raises the possibility of their roles as therapeutic targets in the treatment of a diverse range of diseases including diabetes, cancer, cardiovascular disease, and obesity. Specifically, their potential as therapeutic targets in the treatment of obesity has been highlighted. Brown adipose tissue containing a large number of mitochondria and expressing Ucp-1 is metabolically active through dissipating energy as heat in cold temperatures. Brown adipose, which was previously thought to be present only in neonatal and infants, has been recently unexpectedly identified in various anatomical regions of the adult human body. Furthermore, brown adipocytes have been shown to originate from skeletal and cardiovascular myoblast progenitor cells. Several identified microRNAs participate in the regulation of brown adipocyte differentiation through pathways involving the Prdm16 and C/ebp-ß program. These miRNAs are potential therapeutic targets in the induction of brown adipocyte lineage differentiation from myoblast and white adipose, through which the Ucp-1 expression is regulated to increase calorie expenditure and reduce body weight in obese individuals. This review focuses on the current understanding of miRNAs on the regulation of brown adipogenesis.

Oral immunotherapy induces IgG antibodies that act through FcγRIIb to suppress IgE-mediated hypersensitivity.

BACKGROUND: Food-induced anaphylaxis is triggered by specific IgE antibodies. Paradoxically, some subjects with significant IgE levels can ingest allergenic foods without incident. Similarly, subjects completing oral immunotherapy (OIT) tolerate food challenges despite persistent high-titer food-specific IgE. OBJECTIVE: We sought to test whether IgG antibodies induced by food immunotherapy prevent food-induced anaphylaxis and whether this occurs through the inhibitory receptor FcγRIIb. METHODS: Food allergy-susceptible Il4raF709 mice were enterally sensitized to ovalbumin (OVA). Similarly sensitized IgE-deficient (IgE(-/-)) Il4raF709 mice, which can ingest OVA without anaphylaxis, were subjected to a high-dose enteral OVA desensitization protocol (OIT). Sera from both groups were tested for the ability to activate or inhibit bone marrow mast cells (BMMCs) exposed to allergen or to passively transfer allergy to naive hosts. In parallel experiments sera obtained from patients with peanut allergy before and after undergoing OIT were interrogated for their ability to enhance or suppress peanut-induced activation in an indirect assay by using basophils from nonallergic donors. RESULTS: Il4raF709 mice exhibited strong OVA-specific IgE responses. Their sera efficiently sensitized BMMCs for activation by antigen challenge. Sera from Il4raF709/IgE(-/-) mice subjected to OVA OIT suppressed BMMC responses. This inhibition was IgG mediated and FcγRIIb dependent. Similarly, pre-OIT but not post-OIT sera from patients efficiently sensitized basophils for peanut-induced activation. IgG antibodies in post-OIT sera suppressed basophil activation by pre-OIT sera. This inhibition was blocked by antibodies against FcγRII. CONCLUSION: Food-specific IgG antibodies, such as those induced during OIT, inhibit IgE-mediated reactions. Strategies that favor IgG responses might prove useful in the management of food allergy.

A New Role for an Old Drug: Metformin Targets MicroRNAs in Treating Diabetes and Cancer.

MicroRNAs (miRNAs) are a family of short, noncoding, 19-23 base pair RNA molecules. Due to their unique role in gene regulation in various tissues, miRNAs play important roles in regulating insulin secretion, metabolic disease, and cancer biology. Emerging evidence demonstrates that miRNAs could also be novel diagnostic markers for a variety of disease states. Additionally, miRNAs have been found to function either as oncogenes, or tumor suppressor genes in cerian cancers. An increasing number of studies have been conducted investigating new drugs targeting miRNAs as a potential anticancer therapy. Metformin is the most widely prescribed medication for treating Type 2 diabetes (T2D). Recent clinical data suggests that metformin impacts the miRNA profile in T2D subjects. Most excitingly, studies have found that metformin is protective against cancer. The anticancer activity of metformin is mediated through a direct regulation of miRNAs, which further modulates several downstream genes in metabolic or preoncogenic pathways. These miRNAs are, therefore, prospective therapeutic targets for treating diabetes and cancer which is the topic of this review. Further study on the regulation of miRNAs by metformin could result in novel therapeutic strategies for recurrent or drug-esistant cancer, and as part of combinatorial approaches with conventional anticancer therapies.

Understanding gene circuits at cell-fate branch points for rational cell reprogramming.

Cell-type reprogramming, the artificial induction of a switch of cell lineage and developmental stage, holds great promise for regenerative medicine. However, how does the metazoan body itself 'program' the various cell lineages in the first place? Knowledge of how multipotent cells make cell-fate decisions and commit to a particular lineage is crucial for a rational reprogramming strategy and to avoid trial-and-error approaches in choosing the appropriate set of transcription factors to use. In the past few years, a general principle has emerged in which small gene circuits of cross-inhibition and self-activation govern the decision at branch points of cell development. A formal theoretical treatment of such circuits that deal with their dynamics on the 'epigenetic landscape' could offer some guidance to find the optimal way of cell reprogramming.

Toll-like receptors in breast cancer immunity and immunotherapy.

Toll-like receptors (TLRs) are a key family of pattern recognition receptors (PRRs) in the innate immune system. The activation of TLRs will not only prevent pathogen infection but also respond to damage-induced danger signaling. Increasing evidence suggests that TLRs play a critical role in breast cancer development and treatment. However, the activation of TLRs is a double-edged sword that can induce either pro-tumor activity or anti-tumor effect. The underlying mechanisms of these opposite effects of TLR signaling in cancer are not fully understood. Targeting TLRs is a promising strategy for improving breast cancer treatment, either as monotherapies or by improving other current therapies. Here we provide an update on the role of TLRs in breast cancer immunity and immunotherapy.

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.

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.

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.