Dependence receptor UNC5A restricts luminal to basal breast cancer plasticity and metastasis

BACKGROUND: The majority of estrogen receptor-positive (ERα+) breast cancers respond to endocrine therapies. However, resistance to endocrine therapies is common in 30% of cases, which may be due to altered ERα signaling and/or enhanced plasticity of cancer cells leading to breast cancer subtype conversion. The mechanisms leading to enhanced plasticity of ERα-positive cancer cells are unknown. METHODS: We used short hairpin (sh)RNA and/or the CRISPR/Cas9 system to knockdown the expression of the dependence receptor UNC5A in ERα+ MCF7 and T-47D cell lines. RNA-seq, quantitative reverse transcription polymerase chain reaction, chromatin immunoprecipitation, and Western blotting were used to measure the effect of UNC5A knockdown on basal and estradiol (E2)-regulated gene expression. Mammosphere assay, flow cytometry, and immunofluorescence were used to determine the role of UNC5A in restricting plasticity. Xenograft models were used to measure the effect of UNC5A knockdown on tumor growth and metastasis. Tissue microarray and immunohistochemistry were utilized to determine the prognostic value of UNC5A in breast cancer. Log-rank test, one-way, and two-way analysis of variance (ANOVA) were used for statistical analyses. RESULTS: Knockdown of the E2-inducible UNC5A resulted in altered basal gene expression affecting plasma membrane integrity and ERα signaling, as evident from ligand-independent activity of ERα, altered turnover of phosphorylated ERα, unique E2-dependent expression of genes effecting histone demethylase activity, enhanced upregulation of E2-inducible genes such as BCL2, and E2-independent tumorigenesis accompanied by multiorgan metastases. UNC5A depletion led to the appearance of a luminal/basal hybrid phenotype supported by elevated expression of basal/stem cell-enriched ∆Np63, CD44, CD49f, epidermal growth factor receptor (EGFR), and the lymphatic vessel permeability factor NTN4, but lower expression of luminal/alveolar differentiation-associated ELF5 while maintaining functional ERα. In addition, UNC5A-depleted cells acquired bipotent luminal progenitor characteristics based on KRT14+/KRT19+ and CD49f+/EpCAM+ phenotype. Consistent with in vitro results, UNC5A expression negatively correlated with EGFR expression in breast tumors, and lower expression of UNC5A, particularly in ERα+/PR+/HER2- tumors, was associated with poor outcome. CONCLUSION: These studies reveal an unexpected role of the axon guidance receptor UNC5A in fine-tuning ERα and EGFR signaling and the luminal progenitor status of hormone-sensitive breast cancers. Furthermore, UNC5A knockdown cells provide an ideal model system to investigate metastasis of ERα+ breast cancers

Pharmacological Dual Inhibition of Tumor and Tumor-Induced Functional Limitations in a Transgenic Model of Breast Cancer

Breast cancer progression is associated with systemic effects, including functional limitations and sarcopenia without the appearance of overt cachexia. Autocrine/paracrine actions of cytokines/chemokines produced by cancer cells mediate cancer progression and functional limitations. The cytokine-inducible transcription factor NF-κB could be central to this process, as it displays oncogenic functions and is integral to the Pax7:MyoD:Pgc-1β:miR-486 myogenesis axis. We tested this possibility using the MMTV-PyMT transgenic mammary tumor model and the NF-κB inhibitor dimethylaminoparthenolide (DMAPT). We observed deteriorating physical and functional conditions in PyMT+ mice with disease progression. Compared with wild-type mice, tumor-bearing PyMT+ mice showed decreased fat mass, impaired rotarod performance, and reduced grip strength as well as increased extracellular matrix (ECM) deposition in muscle. Contrary to acute cachexia models described in the literature, mammary tumor progression was associated with reduction in skeletal muscle stem/satellite-specific transcription factor Pax7. Additionally, we observed tumor-induced reduction in Pgc-1β in muscle, which controls mitochondrial biogenesis. DMAPT treatment starting at 6 to 8 weeks age prior to mammary tumor occurrence delayed mammary tumor onset and tumor growth rates without affecting metastasis. DMAPT overcame cancer-induced functional limitations and improved survival, which was accompanied with restoration of Pax7, Pgc-1β, and mitochondria levels and reduced ECM levels in skeletal muscles. In addition, DMAPT restored circulating levels of 6 out of 13 cancer-associated cytokines/chemokines changes to levels seen in healthy animals. These results reveal a pharmacological approach for overcoming cancer-induced functional limitations, and the above-noted cancer/drug-induced changes in muscle gene expression could be utilized as biomarkers of functional limitations

Aging-associated skeletal muscle defects in HER2/Neu transgenic mammary tumor model

Background: Loss of skeletal muscle volume and resulting in functional limitations are poor prognostic markers in breast cancer patients. Several molecular defects in skeletal muscle including reduced MyoD levels and increased protein turn over due to enhanced proteosomal activity have been suggested as causes of skeletal muscle loss in cancer patients. However, it is unknown whether molecular defects in skeletal muscle are dependent on tumor etiology. Methods: We characterized functional and molecular defects of skeletal muscle in MMTV-Neu (Neu+) mice (n= 6-12), an animal model that represents HER2+ human breast cancer, and compared the results with well-characterized luminal B breast cancer model MMTV-PyMT (PyMT+). Functional studies such as grip strength, rotarod performance, and ex vivo muscle contraction were performed to measure the effects of cancer on skeletal muscle. Expression of muscle-enriched genes and microRNAs as well as circulating cytokines/chemokines were measured. Since NF-κB pathway plays a significant role in skeletal muscle defects, the ability of NF-κB inhibitor dimethylaminoparthenolide (DMAPT) to reverse skeletal muscle defects was examined. Results: Neu+ mice showed skeletal muscle defects similar to accelerated aging. Compared to age and sex-matched wild type mice, Neu+ tumor-bearing mice had lower grip strength (202±6.9 vs. 179±6.8 g grip force, p=0.0069) and impaired rotarod performance (108±12.1 vs. 30±3.9 seconds, P<0.0001), which was consistent with reduced muscle contractibility (p<0.0001). Skeletal muscle of Neu+ mice (n=6) contained lower levels of CD82+ (16.2±2.9 vs 9.0±1.6) and CD54+ (3.8±0.5 vs 2.4±0.4) muscle stem and progenitor cells (p<0.05), suggesting impaired capacity of muscle regeneration, which was accompanied by decreased MyoD, p53 and miR-486 expression in muscles (p<0.05). Unlike PyMT+ mice, which showed skeletal muscle mitochondrial defects including reduced mitochondria levels and Pgc1β, Neu+ mice displayed accelerated aging-associated changes including muscle fiber shrinkage and increased extracellular matrix deposition. Circulating "aging factor" and cachexia and fibromyalgia-associated chemokine Ccl11 was elevated in Neu+ mice (1439.56±514 vs. 1950±345 pg/ml, p<0.05). Treatment of Neu+ mice with DMAPT significantly restored grip strength (205±6 g force), rotarod performance (74±8.5 seconds), reversed molecular alterations associated with skeletal muscle aging, reduced circulating Ccl11 (1083.26 ±478 pg/ml), and improved animal survival. Conclusions: These results suggest that breast cancer subtype has a specific impact on the type of molecular and structure changes in skeletal muscle, which needs to be taken into consideration while designing therapies to reduce breast cancer-induced skeletal muscle loss and functional limitations

Optimizing QoS and security in agriculture IoT deployments: A bioinspired Q-learning model with customized shards

Agriculture Internet of Things (AIoTs) deployments require design of high-efficiency Quality of Service (QoS) &amp; security models that can provide stable network performance even under large-scale communication requests. Existing security models that use blockchains are either highly complex or require large delays &amp; have higher energy consumption for larger networks. Moreover, the efficiency of these models depends directly on consensus-efficiency &amp; miner-efficiency, which restricts their scalability under real-time scenarios. To overcome these limitations, this study proposes the design of an efficient Q-Learning bioinspired model for enhancing QoS of AIoT deployments via customized shards. The model initially collects temporal information about the deployed AIoT Nodes, and continuously updates individual recurring trust metrics. These trust metrics are used by a Q-Learning process for identification of miners that can participate in the block-addition process. The blocks are added via a novel Proof-of-Performance (PoP) based consensus model, which uses a dynamic consensus function that is based on temporal performance of miner nodes. The PoP consensus is facilitated via customized shards, wherein each shard is deployed based on its context of deployment, that decides the shard-length, hashing model used for the shard, and encryption technique used by these shards. This is facilitated by a Mayfly Optimization (MO) Model that uses PoP scores for selecting shard configurations. These shards are further segregated into smaller shards via a Bacterial Foraging Optimization (BFO) Model, which assists in identification of optimal shard length for underlying deployment contexts. Due to these optimizations, the model is able to improve the speed of mining by 4.5%, while reducing energy needed for mining by 10.4%, improving the throughput during AIoT communications by 8.3%, and improving the packet delivery consistency by 2.5% when compared with existing blockchain-based AIoT deployment models under similar scenarios. This performance was observed to be consistent even under large-scale attacks

Abstracts of National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020

This book presents the abstracts of the papers presented to the Online National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020 (RDMPMC-2020) held on 26th and 27th August 2020 organized by the Department of Metallurgical and Materials Science in Association with the Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, India. Conference Title: National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020Conference Acronym: RDMPMC-2020Conference Date: 26–27 August 2020Conference Location: Online (Virtual Mode)Conference Organizer: Department of Metallurgical and Materials Engineering, National Institute of Technology JamshedpurCo-organizer: Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, IndiaConference Sponsor: TEQIP-