Disorder-tuned conductivity in amorphous monolayer carbon.

Correlating atomic configurations-specifically, degree of disorder (DOD)-of an amorphous solid with properties is a long-standing riddle in materials science and condensed matter physics, owing to difficulties in determining precise atomic positions in 3D structures1-5. To this end, 2D systems provide insight to the puzzle by allowing straightforward imaging of all atoms6,7. Direct imaging of amorphous monolayer carbon (AMC) grown by laser-assisted depositions has resolved atomic configurations, supporting the modern crystallite view of vitreous solids over random network theory8. Nevertheless, a causal link between atomic-scale structures and macroscopic properties remains elusive. Here we report facile tuning of DOD and electrical conductivity in AMC films by varying growth temperatures. Specifically, the pyrolysis threshold temperature is the key to growing variable-range-hopping conductive AMC with medium-range order (MRO), whereas increasing the temperature by 25 °C results in AMC losing MRO and becoming electrically insulating, with an increase in sheet resistance of 109 times. Beyond visualizing highly distorted nanocrystallites embedded in a continuous random network, atomic-resolution electron microscopy shows the absence/presence of MRO and temperature-dependent densities of nanocrystallites, two order parameters proposed to fully describe DOD. Numerical calculations establish the conductivity diagram as a function of these two parameters, directly linking microstructures to electrical properties. Our work represents an important step towards understanding the structure-property relationship of amorphous materials at the fundamental level and paves the way to electronic devices using 2D amorphous materials.

Genetic modifiers of Huntington disease differentially influence motor and cognitive domains.

Genome-wide association studies (GWASs) of Huntington disease (HD) have identified six DNA maintenance gene loci (among others) as modifiers and implicated a two step-mechanism of pathogenesis: somatic instability of the causative HTT CAG repeat with subsequent triggering of neuronal damage. The largest studies have been limited to HD individuals with a rater-estimated age at motor onset. To capitalize on the wealth of phenotypic data in several large HD natural history studies, we have performed algorithmic prediction by using common motor and cognitive measures to predict age at other disease landmarks as additional phenotypes for GWASs. Combined with imputation with the Trans-Omics for Precision Medicine reference panel, predictions using integrated measures provided objective landmark phenotypes with greater power to detect most modifier loci. Importantly, substantial differences in the relative modifier signal across loci, highlighted by comparing common modifiers at MSH3 and FAN1, revealed that individual modifier effects can act preferentially in the motor or cognitive domains. Individual components of the DNA maintenance modifier mechanisms may therefore act differentially on the neuronal circuits underlying the corresponding clinical measures. In addition, we identified additional modifier effects at the PMS1 and PMS2 loci and implicated a potential second locus on chromosome 7. These findings indicate that broadened discovery and characterization of HD genetic modifiers based on additional quantitative or qualitative phenotypes offers not only the promise of in-human validated therapeutic targets but also a route to dissecting the mechanisms and cell types involved in both the somatic instability and toxicity components of HD pathogenesis.

DP2LM: leveraging deep learning approach for estimation and hypothesis testing on mediation effects with high-dimensional mediators and complex confounders.

Traditional linear mediation analysis has inherent limitations when it comes to handling high-dimensional mediators. Particularly, accurately estimating and rigorously inferring mediation effects is challenging, primarily due to the intertwined nature of the mediator selection issue. Despite recent developments, the existing methods are inadequate for addressing the complex relationships introduced by confounders. To tackle these challenges, we propose a novel approach called DP2LM (Deep neural network-based Penalized Partially Linear Mediation). This approach incorporates deep neural network techniques to account for nonlinear effects in confounders and utilizes the penalized partially linear model to accommodate high dimensionality. Unlike most existing works that concentrate on mediator selection, our method prioritizes estimation and inference on mediation effects. Specifically, we develop test procedures for testing the direct and indirect mediation effects. Theoretical analysis shows that the tests maintain the Type-I error rate. In simulation studies, DP2LM demonstrates its superior performance as a modeling tool for complex data, outperforming existing approaches in a wide range of settings and providing reliable estimation and inference in scenarios involving a considerable number of mediators. Further, we apply DP2LM to investigate the mediation effect of DNA methylation on cortisol stress reactivity in individuals who experienced childhood trauma, uncovering new insights through a comprehensive analysis.

Bioinformatics toolbox for exploring target mutation-induced drug resistance.

Drug resistance is increasingly among the main issues affecting human health and threatening agriculture and food security. In particular, developing approaches to overcome target mutation-induced drug resistance has long been an essential part of biological research. During the past decade, many bioinformatics tools have been developed to explore this type of drug resistance, and they have become popular for elucidating drug resistance mechanisms in a low cost, fast and effective way. However, these resources are scattered and underutilized, and their strengths and limitations have not been systematically analyzed and compared. Here, we systematically surveyed 59 freely available bioinformatics tools for exploring target mutation-induced drug resistance. We analyzed and summarized these resources based on their functionality, data volume, data source, operating principle, performance, etc. And we concisely discussed the strengths, limitations and application examples of these tools. Specifically, we tested some predictive tools and offered some thoughts from the clinician's perspective. Hopefully, this work will provide a useful toolbox for researchers working in the biomedical, pesticide, bioinformatics and pharmaceutical engineering fields, and a good platform for non-specialists to quickly understand drug resistance prediction.

Conversion of chirality to twisting via sequential one-dimensional and two-dimensional growth of graphene spirals.

The properties of two-dimensional (2D) van der Waals materials can be tuned through nanostructuring or controlled layer stacking, where interlayer hybridization induces exotic electronic states and transport phenomena. Here we describe a viable approach and underlying mechanism for the assisted self-assembly of twisted layer graphene. The process, which can be implemented in standard chemical vapour deposition growth, is best described by analogy to origami and kirigami with paper. It involves the controlled induction of wrinkle formation in single-layer graphene with subsequent wrinkle folding, tearing and re-growth. Inherent to the process is the formation of intertwined graphene spirals and conversion of the chiral angle of 1D wrinkles into a 2D twist angle of a 3D superlattice. The approach can be extended to other foldable 2D materials and facilitates the production of miniaturized electronic components, including capacitors, resistors, inductors and superconductors.

Species-specific partial gene duplication in Arabidopsis thaliana evolved novel phenotypic effects on morphological traits under strong positive selection.

Gene duplication is increasingly recognized as an important mechanism for the origination of new genes, as revealed by comparative genomic analysis. However, how new duplicate genes contribute to phenotypic evolution remains largely unknown, especially in plants. Here, we identified the new gene EXOV, derived from a partial gene duplication of its parental gene EXOVL in Arabidopsis thaliana. EXOV is a species-specific gene that originated within the last 3.5 million years and shows strong signals of positive selection. Unexpectedly, RNA-sequencing analyses revealed that, despite its young age, EXOV has acquired many novel direct and indirect interactions in which the parental gene does not engage. This observation is consistent with the high, selection-driven substitution rate of its encoded protein, in contrast to the slowly evolving EXOVL, suggesting an important role for EXOV in phenotypic evolution. We observed significant differentiation of morphological changes for all phenotypes assessed in genome-edited and T-DNA insertional single mutants and in double T-DNA insertion mutants in EXOV and EXOVL. We discovered a substantial divergence of phenotypic effects by principal component analyses, suggesting neofunctionalization of the new gene. These results reveal a young gene that plays critical roles in biological processes that underlie morphological evolution in A. thaliana.

Single-cell transcriptome analysis reveals the association between histone lactylation and cisplatin resistance in bladder cancer.

Patients with bladder cancer (BCa) frequently acquires resistance to platinum-based chemotherapy, particularly cisplatin. This study centered on the mechanism of cisplatin resistance in BCa and highlighted the pivotal role of lactylation in driving this phenomenon. Utilizing single-cell RNA sequencing, we delineated the single-cell landscape of Bca, pinpointing a distinctive subset of BCa cells that exhibit marked resistance to cisplatin with association with glycolysis metabolism. Notably, we observed that H3 lysine 18 lactylation (H3K18la) plays a crucial role in activating the transcription of target genes by enriching in their promoter regions. Targeted inhibition of H3K18la effectively restored cisplatin sensitivity in these cisplatin-resistant epithelial cells. Furthermore, H3K18la-driven key transcription factors YBX1 and YY1 promote cisplatin resistance in BCa. These findings enhance our understanding of the mechanisms underlying cisplatin resistance, offering valuable insights for identifying novel intervention targets to overcome drug resistance in Bca.

Structural mechanisms for the activation of human cardiac KCNQ1 channel by electro-mechanical coupling enhancers.

The cardiac KCNQ1 potassium channel carries the important IKs current and controls the heart rhythm. Hundreds of mutations in KCNQ1 can cause life-threatening cardiac arrhythmia. Although KCNQ1 structures have been recently resolved, the structural basis for the dynamic electro-mechanical coupling, also known as the voltage sensor domain-pore domain (VSD-PD) coupling, remains largely unknown. In this study, utilizing two VSD-PD coupling enhancers, namely, the membrane lipid phosphatidylinositol 4,5-bisphosphate (PIP2) and a small-molecule ML277, we determined 2.5-3.5 Å resolution cryo-electron microscopy structures of full-length human KCNQ1-calmodulin (CaM) complex in the apo closed, ML277-bound open, and ML277-PIP2-bound open states. ML277 binds at the "elbow" pocket above the S4-S5 linker and directly induces an upward movement of the S4-S5 linker and the opening of the activation gate without affecting the C-terminal domain (CTD) of KCNQ1. PIP2 binds at the cleft between the VSD and the PD and brings a large structural rearrangement of the CTD together with the CaM to activate the PD. These findings not only elucidate the structural basis for the dynamic VSD-PD coupling process during KCNQ1 gating but also pave the way to develop new therapeutics for anti-arrhythmia.

FOXCUT regulates the malignant phenotype of triple-negative breast Cancer via the miR-337-3p/ANP32E Axis.

BACKGROUND: The lack of specific molecular targets and the rapid spread lead to a worse prognosis of triple-negative breast cancer (TNBC). Therefore, identifying new therapeutic and prognostic biomarkers helps to develop effective treatment strategies for TNBC. METHODS: Through preliminary bioinformatics analysis, FOXCUT was found to be significantly overexpressed in breast cancer, especially in TNBC. Tissue samples were collected from 15 TNBC patients, and qRT-PCR was employed to validate the expression of FOXCUT in both TNBC patient tissues and TNBC cell lines. We also carried out the GSEA analysis and KEGG enrichment analysis of FOXCUT. Additionally, the effects of FOXCUT knockdown on TNBC cell malignant behaviors, and aerobic glycolysis were assessed by methods including CCK-8, Transwell, western blot, and Seahorse XF 96 analyses. Moreover, utilizing databases predicting interactions between ceRNAs, corresponding lncRNA-miRNA binding relationships, and miRNA-mRNA interactions were predicted. These predictions were subsequently validated through RNA immunoprecipitation and dual-luciferase reporter assays. RESULTS: FOXCUT exhibited high expression in both TNBC tissues and cell lines, fostering cell malignant behaviors and glycolysis. FOXCUT was found to sponge miR-337-3p, while miR-337-3p negatively regulated the expression of ANP32E. Consequently, FOXCUT ultimately facilitated the malignant phenotype of TNBC by upregulating ANP32E expression. CONCLUSION: This study elucidated the role of FOXCUT in elevating aerobic glycolysis levels in TNBC and driving malignant cancer cell development via the miR-337-3p/ANP32E regulatory axis.

Manipulation of Moiré Superlattice in Twisted Monolayer-multilayer Graphene by Moving Nanobubbles.

In the heterostructure of two-dimensional (2D) materials, many novel physics phenomena are strongly dependent on the Moiré superlattice. How to achieve the continuous manipulation of the Moiré superlattice in the same sample is very important to study the evolution of various physical properties. Here, in minimally twisted monolayer-multilayer graphene, we found that bubble-induced strain has a huge impact on the Moiré superlattice. By employing the AFM tip to dynamically and continuously move the nanobubble, we realized the modulation of the Moiré superlattice, like the evolution of regular triangular domains into long strip domain structures with single or double domain walls. We also achieved controllable modulation of the Moiré superlattice by moving multiple nanobubbles and establishing the coupling of nanobubbles. Our work presents a flexible method for continuous and controllable manipulation of Moiré superlattices, which will be widely used to study novel physical properties in 2D heterostructures.

Chondroitin polymerizing factor promotes development and progression of colorectal cancer via facilitating transcription of VEGFB.

Colorectal cancer (CRC) is a highly prevalent malignancy affecting the digestive system on a global scale. This study aimed to explore the previously unexplored role of CHPF in the progression of CRC. Our results revealed a significant upregulation of CHPF expression in CRC tumour tissues compared to normal tissues, with its levels correlating with tumour malignancy. In vitro experiments using CRC cell lines demonstrated that inhibiting CHPF expression suppressed cell proliferation, colony formation and cell migration, while promoting apoptosis. Conversely, overexpressing CHPF had the opposite effect. Additionally, our xenograft models in mice confirmed the inhibitory impact of CHPF knockdown on CRC progression using various cell models. Mechanistic investigations unveiled that CHPF may enhance VEGFB expression through E2F1-mediated transcription. Functionally, suppressing VEGFB expression successfully mitigated the oncogenic effects induced by CHPF overexpression. Collectively, these findings suggest that CHPF may act as a tumour promoter in CRC, operating in a VEGFB-dependent manner and could be a potential target for therapeutic interventions in CRC treatment.

CmCNIH1 improves salt tolerance by influencing the trafficking of CmHKT1;1 in pumpkin.

Pumpkin is often used as a rootstock for other Cucurbitaceae crops due to its resistance to soil-borne diseases and abiotic stress. Pumpkin rootstocks use a sodium transporter (CmHKT1;1) to promote the transport of Na+ from the shoot to the root effectively and improve the salt tolerance of the scion. However, the molecular regulatory mechanisms that influence the activity of CmHKT1;1 during salt stress response remain unknown. In this study, CmCNIH1, a cornichon homolog, was identified as a potential cargo receptor for CmHKT1;1. Yeast two-hybrid, biomolecular fluorescence complementation and luciferase complementary assays demonstrated that CmCNIH1 and CmHKT1;1 could interact. CmCNIH1 was a key component of the cellular vesicle transport machinery located in the endoplasmic reticulum (ER), ER export site and Golgi apparatus. A CmCNIH1 knockout mutant was more sensitive to salt stress than the wild-type (WT). In addition, ion homeostasis was disrupted in cmcnih1 mutants, which had higher Na+ and lower K+ content in shoots and roots than the WT. Two-electrode voltage-clamp experiment displayed that CmCNIH1 could not influence the Na+ current that passed through the plasma membrane (PM) in CmHKT1;1-expressing Xenopus laevis oocytes. Data from co-localization assays indicated that intact CmCNIH1 protein could alter the subcellular localization of CmHKT1;1 in tobacco leaf, pumpkin root and yeast. In summary, CmCNIH1 may function as a cargo receptor that regulates the localization of CmHKT1;1 to the PM to improve salt tolerance in pumpkin.

The Comparative Effectiveness of Perioperative Antibiotic Regimens to Prevent Surgical Site Infections in Pediatric Liver Transplant Recipients.

INTRODUCTION: Surgical site infections (SSIs) are a common complication in liver transplant(LT) recipients. Lack of pediatric prophylaxis guidelines results in variation in preventative antibiotic regimens. METHODS: We performed a retrospective observational study of LT recipients under 18 years using a merged dataset that included data from PHIS and UNOS between 2006 and 2017. The exposure was defined as the antibiotic(s) received within 24 hours of LT; with 6 categories, ranging from narrow (category 1: cefazolin), to broad). The primary outcome was presence or absence of SSI in the index admission. Mixed-effects logistic regression compared the effectiveness of each category relative to category 1 in preventing SSI. RESULTS: Of the 2586 LT, 284 (11%) met SSI criteria. SSI rate was higher (16.2%) in the younger sub-cohort compared to older (8.6%), necessitating a stratified analysis. Antibiotics from category 5 were most commonly used. In the younger sub-cohort, the adjusted risk was increased in all categories compared to the reference, most notably in category 3 (OR 2.58; 0.69-9.59) and category 6 (OR 2.76; 0.66-11.56). In the older sub-cohort, estimated ORs were also increased for each category, most notably in category 4 (2.49; 0.99-6.27). None of the ORs suggested benefit from broader-spectrum prophylaxis. Our E value assessment suggests it's unlikely there is unmeasured confounding by indication to the degree necessary to revert ORs to protective. CONCLUSION: There was wide variation in antibiotic prophylaxis. Adjusted analyses did not reveal a protective benefit of broader-spectrum prophylaxis in either sub-cohort, suggesting that narrower regimens may be adequate.

Identifying Veterans Who Benefit From Nirmatrelvir-Ritonavir: A Target Trial Emulation.

BACKGROUND: Nirmatrelvir-ritonavir is recommended for persons at risk for severe coronavirus disease 2019 (COVID-19) but remains underutilized. Information on which eligible groups are likely to benefit from treatment is needed. METHODS: We conducted a target trial emulation study in the Veterans Health Administration comparing nirmatrelvir-ritonavir treated versus matched untreated veterans at risk for severe COVID-19 who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from April 2022 through March 2023. We measured incidence of any hospitalization or all-cause mortality at 30 days. Outcomes were measured for the entire cohort, as well as among subgroups defined by 30-day risk of death or hospitalization, estimated using an ensemble risk prediction model. RESULTS: Participants were 87% male with median age 66 years and 16% unvaccinated. Compared with matched untreated participants, those treated with nirmatrelvir-ritonavir (n = 24 205) had a lower 30-day risk for hospitalization (1.80% vs 2.30%; risk difference [RD], -0.50% points [95% confidence interval {CI}: -.69 to -.35]) and death (0.11% vs 0.30%; RD, -0.20 [95% CI: -.24 to -.13]). The greatest reductions in combined hospitalization or death were observed in the highest risk quartile (RD -2.85 [95% CI: -3.94 to -1.76]), immunocompromised persons (RD -1.91 [95% CI: -3.09 to -.74]), and persons aged ≥75 years (RD -1.16 [95% CI: -1.73 to -.59]). No reductions were observed in the 2 lowest risk quartiles or persons younger than 65 years. CONCLUSIONS: Nirmatrelvir-ritonavir was effective in reducing 30-day hospitalization and death in older veterans, those at highest predicted risk for severe outcomes, and immunocompromised groups. Benefit was not observed in younger veterans or groups at lower predicted risk for hospitalization and death.

Steering CO2 Electroreduction Selectivity U-Turn to Ethylene by Cu-Si Bonded Interface.

Copper (Cu), with the advantage of producing a deep reduction product, is a unique catalyst for the electrochemical reduction of CO2 (CO2RR). Designing a Cu-based catalyst to trigger CO2RR to a multicarbon product and understanding the accurate structure-activity relationship for elucidating reaction mechanisms still remain a challenge. Herein, we demonstrate a rational design of a core-shell structured silica-copper catalyst (p-Cu@m-SiO2) through Cu-Si direct bonding for efficient and selective CO2RR. The Cu-Si interface fulfills the inversion in CO2RR product selectivity. The product ratio of C2H4/CH4 changes from 0.6 to 14.4 after silica modification, and the current density reaches a high of up to 450 mA cm-2. The kinetic isotopic effect, in situ attenuated total reflection Fourier-transform infrared spectra, and density functional theory were applied to elucidate the reaction mechanism. The SiO2 shell stabilizes the *H intermediate by forming Si-O-H and inhibits the hydrogen evolution reaction effectively. Moreover, the direct-bonded Cu-Si interface makes bare Cu sites with larger charge density. Such bare Cu sites and Si-O-H sites stabilized the *CHO and activated the *CO, promoting the coupling of *CHO and *CO intermediates to form C2H4. This work provides a promising strategy for designing Cu-based catalysts with high C2H4 catalytic activity.

Ir Single Atoms Boost Metal-Oxygen Covalency on Selenide-Derived NiOOH for Direct Intramolecular Oxygen Coupling.

This investigation probes the intricate interplay of catalyst dynamics and reaction pathways during the oxygen evolution reaction (OER), highlighting the significance of atomic-level and local ligand structure insights in crafting highly active electrocatalysts. Leveraging a tailored ion exchange reaction followed by electrochemical dynamic reconstruction, we engineered a novel catalytic structure featuring single Ir atoms anchored to NiOOH (Ir1@NiOOH). This novel approach involved the strategic replacement of Fe with Ir, facilitating the transition of selenide precatalysts into active (oxy)hydroxides. This elemental substitution promoted an upward shift in the O 2p band and intensified the metal-oxygen covalency, thereby altering the OER mechanism toward enhanced activity. The shift from a single-metal site mechanism (SMSM) in NiOOH to a dual-metal-site mechanism (DMSM) in Ir1@NiOOH was substantiated by in situ differential electrochemical mass spectrometry (DEMS) and supported by theoretical insights. Remarkably, the Ir1@NiOOH electrode exhibited exceptional electrocatalytic performance, achieving overpotentials as low as 142 and 308 mV at current densities of 10 and 1000 mA cm-2, respectively, setting a new benchmark for the electrocatalysis of OER.

Association of the social disorganization index with time to first septic shock event in children with acute myeloid leukemia.

BACKGROUND: Pediatric acute myeloid leukemia (AML) chemotherapy increases the risk of life-threatening complications, including septic shock (SS). An area-based measure of social determinants of health, the social disorganization index (SDI), was hypothesized to be associated with SS and SS-associated death (SS-death). METHODS: Children treated for de novo AML on two Children's Oncology Group trials at institutions contributing to the Pediatric Health Information System (PHIS) database were included. The SDI was calculated via residential zip code data from the US Census Bureau. SS was identified via PHIS resource utilization codes. SS-death was defined as death within 2 weeks of an antecedent SS event. Patients were followed from 7 days after the start of chemotherapy until the first of end of front-line therapy, death, relapse, or removal from study. Multivariable-adjusted Cox regressions estimated hazard ratios (HRs) comparing time to first SS by SDI group. RESULTS: The assembled cohort included 700 patients, with 207 (29.6%) sustaining at least one SS event. There were 233 (33%) in the SDI-5 group (highest disorganization). Adjusted time to incident SS did not statistically significantly differ by SDI (reference, SDI-1; SDI-2: HR, 0.84 [95% confidence interval (CI), 0.51-1.41]; SDI-3: HR, 0.70 [95% CI, 0.42-1.16]; SDI-4: HR, 0.97 [95% CI, 0.61-1.53]; SDI-5: HR, 0.72 [95% CI, 0.45-1.14]). Nine patients (4.4%) with SS experienced SS-death; seven of these patients (78%) were in SDI-4 or SDI-5. CONCLUSIONS: In a large, nationally representative cohort of trial-enrolled pediatric patients with AML, there was no significant association between the SDI and time to SS.

Bayesian finite mixture of regression analysis for cancer based on histopathological imaging-environment interactions.

Cancer is a heterogeneous disease. Finite mixture of regression (FMR)-as an important heterogeneity analysis technique when an outcome variable is present-has been extensively employed in cancer research, revealing important differences in the associations between a cancer outcome/phenotype and covariates. Cancer FMR analysis has been based on clinical, demographic, and omics variables. A relatively recent and alternative source of data comes from histopathological images. Histopathological images have been long used for cancer diagnosis and staging. Recently, it has been shown that high-dimensional histopathological image features, which are extracted using automated digital image processing pipelines, are effective for modeling cancer outcomes/phenotypes. Histopathological imaging-environment interaction analysis has been further developed to expand the scope of cancer modeling and histopathological imaging-based analysis. Motivated by the significance of cancer FMR analysis and a still strong demand for more effective methods, in this article, we take the natural next step and conduct cancer FMR analysis based on models that incorporate low-dimensional clinical/demographic/environmental variables, high-dimensional imaging features, as well as their interactions. Complementary to many of the existing studies, we develop a Bayesian approach for accommodating high dimensionality, screening out noises, identifying signals, and respecting the "main effects, interactions" variable selection hierarchy. An effective computational algorithm is developed, and simulation shows advantageous performance of the proposed approach. The analysis of The Cancer Genome Atlas data on lung squamous cell cancer leads to interesting findings different from the alternative approaches.

Advances in common in vitro cellular models of pulmonary fibrosis.

The development of in vitro models is essential for a comprehensive understanding and investigation of pulmonary fibrosis (PF) at both cellular and molecular levels. This study presents a literature review and an analysis of various cellular models used in scientific studies, specifically focusing on their applications in elucidating the pathogenesis of PF. Our study highlights the importance of taking a comprehensive approach to studing PF, emphasizing the necessity of considering multiple cell types and organs and integrating diverse analytical perspectives. Notably, primary cells demonstrate remarkable cell growth characteristics and gene expression profiles; however, their limited availability, maintenance challenges, inability for continuous propagation and susceptibility to phenotypic changes over time significantly limit their utility in scientific investigation. By contrast, immortalized cell lines are easily accessible, cultured and continuously propagated, although they may have some phenotypic differences from primary cells. Furthermore, in vitro coculture models offer a more practical and precise method to explore complex interactions among cells, tissues and organs. Consequently, when developing models of PF, researchers should thoroughly assess the advantages, limitations and relevant mechanisms of different cell models to ensure their selection is consistent with the research objectives.

Palbociclib sensitizes ER-positive breast cancer cells to fulvestrant by promoting the ubiquitin-mediated degradation of ER-α via SNHG17/Hippo-YAP axis.

PURPOSE: Endocrine therapy is the anti-tumor therapy for human breast cancer but endocrine resistance was a major burden. It has been reported that Palbociclib and fulvestrant can be used in combination for the treatment of patients who are experiencing endocrine resistance. However, the underlying mechanism is unclear. In this study, we aimed to investigate the mechanism by which Palbocicilib affected ER-positive breast cancer, combined with fulvestrant. METHODS: We first detected the effect of palbociclib on cell survival, growth and cycle distribution separately by MTT, colony formation and flow cytometry. Then SNHG17 was screened as palbociclib-targeted LncRNA by LncRNA-seq, and the SNHG17-targeted mRNAs were selected by mRNA-seq for further determination. Subsequently, the underlying mechanism by which palbociclib promoted the cytotoxicity of fulvestrant was confirmed by qRT-PCR, western blot, and immunoprecipitation. Eventually, the xenograft model and immunohistochemistry experiments were used to validate the sensitization effect of palbociclib on fulvestrant and its mechanism in vivo. RESULTS: Palbociclib significantly enhanced the cytotoxicity of fulvestrant in fulvestrant-resistant breast cancer cell lines. Interestingly, this might be related to the lncRNA SNHG17 and the Hippo signaling pathway. And our subsequent western blotting experiments confirmed that overexpressing SNHG17 induced the down-regulation of LATS1 and up-regulated YAP expression. Furthermore, we found that the increased sensitivity of breast cancer cells was closely associated with the LATS1-mediated degradation of ER-α. The following animal experiments also indicated that overexpressing SNHG17 obviously impaired the anti-cancer effect of co-treatment of palbociclib and fulvestrant accompanied by decreased LATS1 and increased ER-α levels. CONCLUSION: Palbociclib might sensitize the cytotoxicity of fulvestrant in ER-positive breast cancer cells by down-regulating SNHG17 expression, and then resulted in the LATS1-inactivated oncogene YAP and LATS1-mediated degradation of ER-α.