Targeting stromal components in the tumor microenvironment for cancer therapy

In the tumor microenvironment (TME), different cell components crosstalk with each other through various growth factors, cytokines, chemokines, and enzymes. They offered crucial survival signals for tumor cell proliferation and metastasis. Data presented in this thesis demonstrate approaches to target the stroma of the TME, which provided a novel paradigm for cancer therapy. It involves the conception of overcoming the resistance of conventional therapy, cut-out cancer cell energy support, and interrupting invasive assistance of cancer cells. We specifically focused on these two aspects: first, to resolve antiangiogenic drugs (AAD) resistance in those cancers with a lipid-rich environment or high FGF expression. In addition, to manipulate the brown adipose tissue (BAT) into mega BAT can be an approach in cancer therapy (Paper I-III). Second, we revealed the roles of stromal cells, including the cancerassociated fibroblasts (CAFs) and tumor-associated macrophages (TAMs), in pancreatic ductal adenocarcinoma (PDAC) (Paper IV); and the role of CAFs in the cancer hosts with disturbed circadian rhythm (CR) (Paper V). In Paper I, we revealed the mechanism of AAD drug resistance in tumors surrounded by adipose tissue or lipid-rich environment, for example, colorectal cancer (CRC), PDAC and hepatocellular carcinoma (HCC) in the steatotic liver. Anti-VEGF-based AAD failed to reduce tumor size but triggered vessel regression in tumor tissues, leading to severe hypoxia in the TME. Hypoxia resulted in tumor metabolic reprogramming from glucose-based metabolism to free fatty acids (FFAs)-based metabolism. FFAs provided energy support to tumor cells, leading to accelerate tumor cell proliferation. Inhibition of FFA transporter reversed AAD resistance in anti-tumor effect. Our data suggested a therapeutic approach to reverse the AAD resistance in tumors with a lipid-rich environment. Our previous study revealed the cold exposure and other β3-adrenorecptor stimuli induced the brown adipose tissue (BAT) activation by increasing the non-shivering thermogenesis (NST). The activated BAT decreased blood glucose and impeded glycolysis-based metabolism in cancer cells could suppress tumor growth. In Paper II, we addressed an approach to enlarge BAT into a mega-size BAT (megaBAT) in adult animals. In BAT, the differentiation of certain progenitor cells is controlled by the platelet-derived growth factor receptor α (PDGFRα). Using pharmacological approaches and genetic deletion, we downregulated the PDGFRα in BAT progenitor cells and promoted progenitor cells differentiation into functional brown adipocytes. We found a specific microRNA to target the PDGFRα signaling in vivo. The whole BAT tissue mass was markedly increased after PDGFRα inhibition owing to the increase of brown adipocyte numbers. We found that the obese mice with megaBAT under cold exposure showed improvement in blood glucose level, insulin tolerance, and blood lipid level. Histological analysis showed that the steatotic livers were markedly reversed in obese mice with megaBAT. The megaBAT could become a therapeutic approach to treat cancer and metabolic diseases. We previously reported that fibroblast growth factor 2 (FGF-2) as one of the angiogenic factors contributed to tumor vessel remodeling by recruiting NG2 positive pericytes onto tumor vessels through the PDGFRβ signaling. Therefore, monotherapy with anti-VEGF or anti-PDGFR had become resistant in tumors with high FGF-2 expression. So far, there are no potent anti-FGF drugs available. In Paper III, we found combination therapy with anti-VEGF and anti- PDGFRβ showed superior anti-tumor effects in high FGF-2 tumors. Anti-PDGFRβ treatment suppressed pericyte recruitment, and anti-VEGF precisely targeted tumor vessels. With this study, we provided a new paradigm for resolving AAD resistance by targeting FGF-2 off-target signaling, VEGF and PDGF in cancer therapy. In Paper IV, we identified the CAFs-TAMs crosstalk through the IL-33-ST2-CXCL3-CXCR2 axis in PDAC and triggered cancer cell metastasis. Mouse and human PDAC samples under unbiased genomic-wide profiling analysis and genetic and pharmacological gain/loss-offunction experiments demonstrated a high level of IL-33 expression. IL-33 bound to its receptor ST2 on the TAMs and induced TAMs infiltration. Transcriptomic analysis identified IL-33-ST2 induced high CXCL3 expression, which was produced by TMAs. CXCL3 bound to its receptors CXCR2 on CAFs induced CAFs-myoCAF transition and cell proliferation. CAFs transited to myoCAFs had a high expression of collagen III, which induced the formation of tumor cells and myofibroblast clusters. Tumor cells increased metastasis under this tumormyofibroblasts clusters. Pharmacological targeting of this pathway would provide a potential therapeutic strategy for treating PDAC. Paper V we presented the link between CR disruption and tumor metastasis. We explored CR disruption by using a genetic model of Bmal1 gene knockout (KO) mice. Various types of tumors in Bmal1 KO mice presented high growth speed with an elevated expression of myofibroblast markers. Unbiased genomic-wide profiling using the stromal vascular fraction (SVF) from the tumors of Bmal1 KO mice demonstrated a downregulated expression of the plasminogen activator inhibitor (PAI-1) gene. The BMAL1 protein directly regulated PAI-1 gene transcription. Lacking BMAL1 resulted in low PAI-1 expression, which continuously removed the inhibition of downstream proteins, including tissue plasmin activator (tPA) and urokinase (uPA). The tPA and uPA accumulation transformed plasminogen into plasmin, which converted the latent TGF-β into active form. The active TGF-β contributed to the CAFs transition into myofibroblasts, which induced tumor tissue mass expansion and increased metastasis. Inhibition of TGF-β in tumors with CR disruption or maintenance of CR homeostasis could be a therapeutic approach to tumor therapy. Collectively, the works in this thesis uncover important roles of stromal cellular components in the TME, which lay the ground for the development of novel pharmaceutical approaches in cancer therapy

Pricing Strategies in Dual-online Channels Based on Consumers’ Shopping Choice

AbstractBesides an official website mall (OWM), retail stores on the third party e-commerce platform(3PEP) is an another important online channel that manufacturers adopt to sell online. How to properly price products in these two channels simultaneously is a tough problem to firms and gains much attention by researchers. In this paper, we analyze their channel choice, and give demand functions of the two channels based on the consumers’ segmentation and preference. Then we design a sale model including two online channels: OWM and a retail store on 3PEP. According the Stackelberg game theory, we calculate and discuss the optimal pricing strategies of the manufacturer and retailer in three feasible regions. The result shows that manufacturers emphasizing channel sales prefer to choose pricing strategies that helps two online channels share the online market. But some manufacturers think adjusting the OWM's price and the wholesale price to control the retailer's pricing strategies is reasonable and necessary, even if nobody will prefer the OWM

AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework

This technical report presents AutoGen, a new framework that enables development of LLM applications using multiple agents that can converse with each other to solve tasks. AutoGen agents are customizable, conversable, and seamlessly allow human participation. They can operate in various modes that employ combinations of LLMs, human inputs, and tools. AutoGen's design offers multiple advantages: a) it gracefully navigates the strong but imperfect generation and reasoning abilities of these LLMs; b) it leverages human understanding and intelligence, while providing valuable automation through conversations between agents; c) it simplifies and unifies the implementation of complex LLM workflows as automated agent chats. We provide many diverse examples of how developers can easily use AutoGen to effectively solve tasks or build applications, ranging from coding, mathematics, operations research, entertainment, online decision-making, question answering, etc.Comment: 28 page

Room-temperature multiferroic hexagonal LuFeO3_3 films

The crystal and magnetic structures of single-crystalline hexagonal LuFeO$_3$ films have been studied using x-ray, electron and neutron diffraction methods. The polar structure of these films are found to persist up to 1050 K; and the switchability of the polar behavior is observed at room temperature, indicating ferroelectricity. An antiferromagnetic order was shown to occur below 440 K, followed by a spin reorientation resulting in a weak ferromagnetic order below 130 K. This observation of coexisting multiple ferroic orders demonstrates that hexagonal LuFeO$_3$ films are room-temperature multiferroics

EHRAgent: Code Empowers Large Language Models for Few-shot Complex Tabular Reasoning on Electronic Health Records

Large language models (LLMs) have demonstrated exceptional capabilities in planning and tool utilization as autonomous agents, but few have been developed for medical problem-solving. We propose EHRAgent, an LLM agent empowered with a code interface, to autonomously generate and execute code for multi-tabular reasoning within electronic health records (EHRs). First, we formulate an EHR question-answering task into a tool-use planning process, efficiently decomposing a complicated task into a sequence of manageable actions. By integrating interactive coding and execution feedback, EHRAgent learns from error messages and improves the originally generated code through iterations. Furthermore, we enhance the LLM agent by incorporating long-term memory, which allows EHRAgent to effectively select and build upon the most relevant successful cases from past experiences. Experiments on three real-world multi-tabular EHR datasets show that EHRAgent outperforms the strongest baseline by up to 29.6% in success rate. EHRAgent leverages the emerging few-shot learning capabilities of LLMs, enabling autonomous code generation and execution to tackle complex clinical tasks with minimal demonstrations.Comment: Work in Progres

Improving the stability and transdermal permeability of phycocyanin loaded cubosomes

Instability and low transdermal permeability of protein antioxidants are major obstacles to resist oxidative stress in transdermal drug delivery system. To overcome these shortcomings, cubosomes were developed as an advanced transdermal delivery system to improve stability and transdermal absorption of the model antioxidant phycocyanin in this study. Glyceryl monooleate and poloxamer 407 (P407) were used to prepare cubosomes as carrier matrix and stabilizer, respectively. Phycocyanin loaded cubosomes (PC-cubosomes) were prepared by the emulsification and homogenization method. A 33 full factorial design was used to optimize the cubosome formulations. The final optimal PC-cubosomes possessed an average particle size of 183.2 ± 0.5 nm and a negative surface charge as well as achieved a high encapsulation efficiency of 87.2% ± 2.7%. PC-cubosomes appeared as nano-sized and well-shaped spheres with highly ordered cubical structures. The residual amount of phycocyanin in PC-cubosomes was 3-fold higher than that in the free drug solution after 10 days ultraviolet radiation exposure. In vitro release kinetics of phycocyanin from PC-cubosomes fitted to the Higuchi kinetic model, indicating that phycocyanin released from cubosomes mainly attributed to drug diffusion and dissolution. PC-cubosomes also exhibited higher permeability (39.79 μg⋅cm−2⋅hour−1) across the rat skin than phycocyanin solution (16.33 μg⋅cm−2⋅hour−1). Furthermore, PC-cubosomes were easily taken up by keratinocytes, thereby achieving a prolonged anti-oxidative stress effect. These results therefore suggested that cubosomes could be a promising transdermal delivery system to improve the stability and transdermal permeability of phycocyanin

Divergence of a genomic island leads to the evolution of melanization in a halophyte root fungus

AbstractUnderstanding how organisms adapt to extreme living conditions is central to evolutionary biology. Dark septate endophytes (DSEs) constitute an important component of the root mycobiome and they are often able to alleviate host abiotic stresses. Here, we investigated the molecular mechanisms underlying the beneficial association between the DSE Laburnicola rhizohalophila and its host, the native halophyte Suaeda salsa, using population genomics. Based on genome-wide Fst (pairwise fixation index) and Vst analyses, which compared the variance in allele frequencies of single-nucleotide polymorphisms (SNPs) and copy number variants (CNVs), respectively, we found a high level of genetic differentiation between two populations. CNV patterns revealed population-specific expansions and contractions. Interestingly, we identified a ~20 kbp genomic island of high divergence with a strong sign of positive selection. This region contains a melanin-biosynthetic polyketide synthase gene cluster linked to six additional genes likely involved in biosynthesis, membrane trafficking, regulation, and localization of melanin. Differences in growth yield and melanin biosynthesis between the two populations grown under 2% NaCl stress suggested that this genomic island contributes to the observed differences in melanin accumulation. Our findings provide a better understanding of the genetic and evolutionary mechanisms underlying the adaptation to saline conditions of the L. rhizohalophila–S. salsa symbiosis.</jats:p

Room-Temperature Multiferroic Hexagonal LuFeO\u3csub\u3e3\u3c/sub\u3e Films

The crystal and magnetic structures of single-crystalline hexagonal LuFeO3 films have been studied using x-ray, electron, and neutron diffraction methods. The polar structure of these films are found to persist up to 1050 K; and the switchability of the polar behavior is observed at room temperature, indicating ferroelectricity. An antiferromagnetic order was shown to occur below 440 K, followed by a spin reorientation resulting in a weak ferromagnetic order below 130 K. This observation of coexisting multiple ferroic orders demonstrates that hexagonal LuFeO3 films are room-temperature multiferroics

A Hybrid Wavelet de-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series

Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, wavelet de-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. Compared to three other generic methods, the results generated by WD-REPA model presented invariably smaller error measures which means the forecasting capability of the WD-REPA model is better than other models. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series