Mammalian enabled protein enhances tamoxifen sensitivity of the hormone receptor-positive breast cancer patients by suppressing the AKT signaling pathway.

BACKGROUND: Mammalian enabled (MENA) protein is a member of the enabled/vasodilator stimulated phosphoprotein (Ena/VASP) protein family, which regulates cytoplasmic actin network assembly. It plays a significant role in breast cancer invasion, migration, and resistance against targeted therapy and chemotherapy. However, its role in the efficacy of endocrine therapy for the hormone receptor-positive (HR+) breast cancer patients is not known. This study investigated the role of MENA in the resistance against tamoxifen therapy in patients with HR+ breast cancer and the underlying mechanisms. METHODS: MENA expression levels in the clinical HR+ breast cancer samples (n = 119) were estimated using immunohistochemistry (IHC) to determine its association with the clinicopathological features, tamoxifen resistance, and survival outcomes. Western blotting (WB) and quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) analysis was performed to estimate the MENA protein and mRNA levels in the tamoxifen-sensitive and -resistant HR+ breast cancer cell lines. Furthermore, CCK8, colony formation, and the transwell invasion and migration assays were used to analyze the effects of MENA knockdown on the biological behavior and tamoxifen sensitivity of the HR+ breast cancer cell lines. Xenograft tumor experiments were performed in the nude mice to determine the tumor growth rates and tamoxifen sensitivity of the control and MENA knockdown HR+ breast cancer cells in the presence and absence of tamoxifen treatment. Furthermore, we estimated the growth rates of organoids derived from the HR+ breast cancer patients (n = 10) with high and low MENA expression levels when treated with tamoxifen. RESULTS: HR+ breast cancer patients with low MENA expression demonstrated tamoxifen resistance and poorer prognosis compared to those with high MENA expression. Univariate and multivariate Cox regression analysis demonstrated that MENA expression was an independent predictor of tamoxifen resistance in patients with HR+ breast cancer. MENA knockdown HR+ breast cancer cells showed significantly reduced tamoxifen sensitivity in the in vitro experiments and the in vivo xenograft tumor mouse model compared with the corresponding controls. Furthermore, MENA knockdown increased the in vitro invasion and migration of the HR+ breast cancer cells. HR+ breast cancer organoids with low MENA expression demonstrated reduced tamoxifen sensitivity than those with higher MENA expression. Mechanistically, P-AKT levels were significantly upregulated in the MENA-knockdown HR + breast cancer cells treated with or without 4-OHT compared with the corresponding controls. CONCLUSIONS: This study demonstrated that downregulation of MENA promoted tamoxifen resistance in the HR+ breast cancer tissues and cells by enhancing the AKT signaling pathway. Therefore, MENA is a promising prediction biomarker for determining tamoxifen sensitivity in patients with HR+ breast cancer.

LncRNA PCAT6 mediates UBFD1 expression via sponging miR-545-3p in breast cancer cells.

Background: LncRNA PCAT6 has been shown to involve in carcinogenesis of different tumors. In this study, we investigated underline mechanism by which PCAT6 promoted breast cancer cell progression. Methods: RIP was used to identify lncRNAs associated with IMP1. Bioinformatics assays were used to predict potential miRNAs that interact with PCAT6 and mRNAs that are targeted by miR-545-3p. RNA-seq and RT-qPCR were used to analyze differential expression of lncRNAs and miRNA-targeted genes. Luciferase reporter and RNA pull-down assays were performed to identify the molecular interactions between PCAT6 and individual miRNAs. The role of PCAT6-mediated cell proliferation and invasion were tested by CCK-8 and transwell assays following loss-of-function and gain-of-function effects. Results: We identified that PCAT6 is one of the lncRNAs that associated with IMP1. PCAT6 not only binds to IMP1, but also acts as a ceRNA to interact with multiple miRNAs, including miR-545-3p. Binding of IMP1 destabilized PCAT6, while competitive interaction with miR-545-3p allowed PCAT6 to positively regulate UBFD1 expression. Silencing UBFD1 mRNA could effectively rescue PCAT6-induced cell proliferation and invasive abilities. Conclusions: Our study provided evidence that PCAT6 activates UBFD1 expression via sponging miR-545-3p to increase carcinogenesis of breast cancer cells. Based on the nature of UBFD1 as a polyubiquitin binding protein, our study suggested that ubiquitin pathway might contribute to breast cancer progression.

Deep learning-based predictive model for pathological complete response to neoadjuvant chemotherapy in breast cancer from biopsy pathological images: a multicenter study.

Introduction: Early predictive pathological complete response (pCR) is beneficial for optimizing neoadjuvant chemotherapy (NAC) strategies for breast cancer. The hematoxylin and eosin (HE)-stained slices of biopsy tissues contain a large amount of information on tumor epithelial cells and stromal. The fusion of pathological image features and clinicopathological features is expected to build a model to predict pCR of NAC in breast cancer. Methods: We retrospectively collected a total of 440 breast cancer patients from three hospitals who underwent NAC. HE-stained slices of biopsy tissues were scanned to form whole-slide images (WSIs), and pathological images of representative regions of interest (ROI) of each WSI were selected at different magnifications. Based on several different deep learning models, we propose a novel feature extraction method on pathological images with different magnifications. Further, fused with clinicopathological features, a multimodal breast cancer NAC pCR prediction model based on a support vector machine (SVM) classifier was developed and validated with two additional validation cohorts (VCs). Results: Through experimental validation of several different deep learning models, we found that the breast cancer pCR prediction model based on the SVM classifier, which uses the VGG16 model for feature extraction of pathological images at ×20 magnification, has the best prediction efficacy. The area under the curve (AUC) of deep learning pathological model (DPM) were 0.79, 0.73, and 0.71 for TC, VC1, and VC2, respectively, all of which exceeded 0.70. The AUCs of clinical model (CM), a clinical prediction model established by using clinicopathological features, were 0.79 for TC, 0.73 for VC1, and 0.71 for VC2, respectively. The multimodal deep learning clinicopathological model (DPCM) established by fusing pathological images and clinicopathological features improved the AUC of TC from 0.79 to 0.84. The AUC of VC2 improved from 0.71 to 0.78. Conclusion: Our study reveals that pathological images of HE-stained slices of pre-NAC biopsy tissues can be used to build a pCR prediction model. Combining pathological images and clinicopathological features can further enhance the predictive efficacy of the model.

HER2-positive is an independent indicator for predicting pathological complete response to neoadjuvant therapy and Ki67-changed after neoadjuvant chemotherapy predicts favorable prognosis in Chinese women with locally advanced breast cancer.

The growing body of evidence suggests that breast cancer (BC) who achieve pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) may experience a more favorable prognosis. The objective of this study is to investigate the correlation between clinicopathologic parameters of locally advanced breast cancer (LABC) patients and the outcomes of NAC, with the aim of identifying predictive indicators for pCR. Additionally, we seek to examine the conversion of IHC markers in pCR patients following NAC and its impact on the prognosis of BC patients. We conducted a study involving 126 patients with LABC. Clinicopathological parameters associated with pCR were subjected to univariate and multivariate analysis. Kaplan-Meier (KM) curves and the log-rank test were used to compare the statistical difference in prognosis in different groups of patients. Additionally, we used difference and consistency tests to examine the conversion of immunohistochemistry (IHC) markers following NAC. The status of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and molecular subtypes of BC were associated with pCR in the univariate analysis (all P < .05), which may be potential markers to predict pCR. HER2 was identified as an independent factor for predicting pCR in the multivariate analysis. The pCR rate of HER2-positive patients who received NAC combined targeted therapy was higher than that of patients who only received NAC (P = .003). The disease-free survival (DFS) rate of TNBC patients who achieved pCR was significantly higher than that of non-pCR TNBC patients (P = .026). The IHC marker conversion after NAC mainly existed in PR (P = .041). Ki67 expression decreased in the luminal B subtype and increased in the HER2 enriched subtype after NAC (all P < .001). Patients with Ki67 expression change after NAC had longer overall survival (OS) and DFS than unchanged patients (all P < .05). HER2-positive is an independent indicator for predicting pCR, and HE2-positive patients who received NAC combined targeted therapy were favorable to achieving pCR. IHC markers of BC patients exhibit varying degrees of alterations after NAC, and changes in Ki67 expression after NAC could serve as a marker to predict a better prognosis.

Prognostic implication of novel immune-related signature in breast cancer.

Checkpoint inhibitor therapy has become increasingly important and has been endorsed as a treatment regimen in breast cancer. But benefits were limited to a small proportion of patients. We aimed to develop an improved signature on the basis of immune genes for detection of potential benefit from immunotherapy. Gene expression data of patients with breast cancer initially extracted from The Cancer Genome Atlas were analyzed. Ten genes were selected from the interaction of differentially expressed genes as well as immune-related genes to develop a survival signature. We compared the high-risk and low-risk groups by gene set enrichment analysis, immune infiltration, checkpoint molecule expression and immunophenoscore. Ten genes were extracted from interactions of differentially expressed and immune-related genes. The immune risk score was determined on the basis of the Cox regression coefficient of hub genes and validated with the GSE96058 dataset. Immune cell infiltrates, including CD8 + T cells, plasma cells, follicular helper T cells, CD4 + memory T cells, M1 macrophages, regulatory T cells and resting NK cells, were more highly infiltrated in the high-risk group as compared to the low-risk group. Checkpoint molecules, including CTLA-4, PD-L1, TIM-3, VISTA, ICOS, PD-1, and PD-L2, were expressed at markedly lower levels in the high-risk group as compared to the low-risk group. Immunophenoscores, as a surrogate of response to immune checkpoint therapy, was observed significant lower in the high-risk group. The 10-gene prognostic signature could identify patients' survival and was correlated with the biomarkers of immune checkpoint inhibitor therapy, which may guide precise therapeutic decisions in clinical practice.

Clinical significance and immune characteristics analysis of miR-221-3p and its key target genes related to epithelial-mesenchymal transition in breast cancer.

BACKGROUND: MicroRNA-221-3p (miR-221-3p) facilitates the advancement of breast cancer (BC) through the induction of epithelial-mesenchymal transition (EMT). Our research aimed to utilize bioinformatics to discover possible EMT-related target genes (ETGs) of miR-221-3p and examine their roles in breast cancer. METHODS: We employed bioinformatics techniques to identify ten key ETGs of miR-221-3p. Subsequently, we conducted an extensive analysis of both miR-221-3p and the ten ETGs, including clinical significance and immune characteristics. RESULTS: The expression of miR-221-3p was notably higher in Basal-like BC compared to other subtypes and adjacent normal tissue. Our pathway analysis suggested that miR-221-3p might regulate EMT through the MAPK signaling pathway by targeting its ETGs. Among the ETGs, seven core genes (EGFR, IGF1, KDR, FGF2, KIT, FGFR1, and FGF1) exhibited downregulation in BC. Conversely, ERBB2, SDC1, and MMP14 showed upregulation in BC and displayed potential diagnostic value. The analysis of prognostication indicated that increased levels of SDC1 and MMP14 were correlated with an unfavorable prognosis, whereas elevated expression of KIT was associated with a more favorable prognosis. The infiltration of various immune cells and the expression of immune checkpoint genes (ICGs) exhibited positive correlations with most ETGs and miR-221-3p. SDC1 exhibited a greater tumor mutational burden (TMB) score, while ERBB2, KDR, FGF2, KIT, FGFR1, and FGF1 showed lower TMB scores. Furthermore, decreased ERBB2 and KDR expression levels were correlated with elevated microsatellite instability (MSI) scores. Elevated expression of ETGs was linked to decreased mRNA stemness indices (mRNAsi), whereas miR-221-3p displayed the opposite pattern. Most ETGs and miR-221-3p expression exhibited a negative correlation with IC50 values for drugs. Among the ETGs, amplification was the most significant genetic alteration, except for IGF1. CONCLUSION: In conclusion, miR-221-3p acts as a unique indicator for Basal-like BC. The examination revealed ten essential ETGs of miR-221-3p, some of which show potential as diagnostic and prognostic markers. The in-depth examination of these ten ETGs and miR-221-3p indicates their participation in the development of BC, emphasizing their promise as innovative targets for therapy in BC patients.

Mesothelin-targeted CAR-NK Cells Derived From Induced Pluripotent Stem Cells Have a High Efficacy in Killing Triple-negative Breast Cancer Cells as Shown in Several Preclinical Models.

The emergence of immunotherapy has introduced a promising, novel approach to cancer treatment. While multiple chimeric antigen receptor (CAR) T-cell therapies have demonstrated remarkable clinical efficacy against leukemia, their effect on solid tumors has been limited. One potential option for treating solid tumors is the engineering of natural killer (NK) cells with CARs. Mesothelin (MSLN), a tumor differentiation antigen, is expressed on triple-negative breast cancer (TNBC) cells, making it a potential target for CAR-NK therapy in the treatment of TNBC. We first constructed induced pluripotent stem cells with stable anti-MSLN-CAR expression and subsequently differentiated these cells into mesothelin-targeted CAR-NK (MSLN-NK) cells. We then assessed the effects of MSLN-NK cells on TNBC cells both in vitro (using the MDA-MB-231 cell line), in vivo (in a CDX mouse model), and ex vivo (using patient-specific primary cells and patient-specific organoids), in which MSLN surface expression was confirmed. Our CDX study results indicated that MSLN-NK cells effectively killed MDA-MB-231 (MD231) cells in vitro, reduced tumor growth in the CDX mouse model of TNBC, and lysed patient-specific primary cells and patient-specific organoids derived from the tumor samples of TNBC patients. Our data demonstrated that MSLN-NK cells had high efficacy on killing TNBC cells in in vitro, in vivo, and ex vivo. Therefore, MSLN-NK could be a promising treatment option for TNBC patients.

Identification and comprehensive analysis of epithelial-mesenchymal transition related target genes of miR-222-3p in breast cancer.

Background: Epithelial-mesenchymal transition (EMT) is a crucial mechanism that microRNA-222-3p (miR-222-3p) promotes breast cancer (BC) progression. Our study aimed to identify EMT-associated target genes (ETGs) of miR-222-3p for further analysis of their roles in BC based on bioinformatics tools. Methods: Based on bioinformatics analysis, we identified 10 core ETGs of miR-222-3p. Then, we performed a comprehensive analysis of 10 ETGs and miR-222-3p, including pathway enrichment analysis of ETGs, differential expression, clinical significance, correlation with immune cell infiltration, immune checkpoint genes (ICGs) expression, tumor mutational burden (TMB), microsatellite instability (MSI), stemness, drug sensitivity, and genetic alteration. Results: The expression of miR222-3p in basal-like BC was significantly higher than in other subtypes of BC and the normal adjacent tissue. Pathway analysis suggested that the ETGs might regulate the EMT process via the PI3K-Akt and HIF-1 signaling pathway. Six of the 10 core ETGs of miR-222-3p identified were down-expressed in BC, which were EGFR, IL6, NRP1, NTRK2, LAMC2, and PIK3R1, and SERPINE1, MUC1, MMP11, and BIRC5 were up-expressed in BC, which also showed potential diagnostic values in BC. Prognosis analysis revealed that higher NTRK2 and PIK3R1 expressions were related to a better prognosis, and higher BIRC5 and miR-222-3p expressions were related to a worse prognosis. Most ETGs and miR-222-3p were positively correlated with various infiltration of various immune cells and ICGs expression. Lower TMB scores were correlated with higher expression of MUC1 and NTRK2, and higher BIRC5 was related to a higher TMB score. Lower expression of MUC1, NTRK2, and PIK3R1 were associated with higher MSI scores. Higher expression of ETGs was associated with lower mRNAsi scores, except BIRC5 and miR-222-3p conversely. Most ETGs and miR-222-3p expression were negatively correlated with the drug IC50 values. The analysis of the genetic alteration of the ETGs suggested that amplification was the main genetic alteration of eight ETGs except for NTRK2 and PIK3R1. Conclusion: MiR-222-3p might be a specific biomarker of basal-like BC. We successfully identify 10 core ETGs of miR-222-3p, some might be useful diagnostic and prognostic biomarkers. The comprehensive analysis of 10 ETGs and miR-222-3p indicated that they might be involved in the development of BC, which might be novel therapeutic targets for the treatment of BC.

Safety, immunogenicity, and efficacy of the mRNA vaccine CS-2034 as a heterologous booster versus homologous booster with BBIBP-CorV in adults aged ≥18 years: a randomised, double-blind, phase 2b trial.

BACKGROUND: Heterologous boosting is suggested to be of use in populations who have received inactivated COVID-19 vaccines. We aimed to assess the safety and immunogenicity of a heterologous vaccination with the mRNA vaccine CS-2034 versus the inactivated BBIBP-CorV as a fourth dose, as well as the efficacy against the SARS-CoV-2 omicron (BA.5) variant. METHODS: This trial contains a randomised, double-blind, parallel-controlled study in healthy participants aged 18 years or older (group A) and an open-label cohort in participants 60 years and older (group B), who had received three doses of inactivated whole-virion vaccines at least 6 months before enrolment. Pregnant women and people with major chronic illnesses or a history of allergies were excluded. Eligible participants in group A were stratified by age (18-59 years and ≥60 years) and then randomised by SAS 9.4 in a ratio of 3:1 to receive a dose of the mRNA vaccine (CS-2034, CanSino, Shanghai, China) or inactivated vaccine (BBIBP-CorV, Sinopharm, Beijing, China). Safety and immunogenicity against omicron variants of the fourth dose were evaluated in group A. Participants 60 years and older were involved in group B for safety observations. The primary outcome was geometric mean titres (GMTs) of the neutralising antibodies against omicron and seroconversion rates against BA.5 variant 28 days after the boosting, and incidence of adverse reactions within 28 days. The intention-to-treat group was involved in the safety analysis, while all patients in group A who had blood samples taken before and after the booster were involved in the immunogenicity analysis. This trial was registered at the Chinese Clinical Trial Registry Centre (ChiCTR2200064575). FINDINGS: Between Oct 13, and Nov 22, 2022, 320 participants were enrolled in group A (240 in the CS-2034 group and 80 in the BBIBP-CorV group) and 113 in group B. Adverse reactions after vaccination were more frequent in CS-2034 recipients (158 [44·8%]) than BBIBP-CorV recipients (17 [21·3%], p<0·0001). However, most adverse reactions were mild or moderate, with grade 3 adverse reactions only reported by eight (2%) of 353 participants receiving CS-2034. Heterologous boosting with CS-2034 elicited 14·4-fold (GMT 229·3, 95% CI 202·7-259·4 vs 15·9, 13·1-19·4) higher concentration of neutralising antibodies to SARS-CoV-2 omicron variant BA.5 than did homologous boosting with BBIBP-CorV. The seroconversion rates of SARS-CoV-2-specific neutralising antibody responses were much higher in the mRNA heterologous booster regimen compared with BBIBP-CorV homologous booster regimen (original strain 47 [100%] of 47 vs three [18·8%] of 16; BA.1 45 [95·8%] of 48 vs two [12·5%] 16; and BA.5 233 [98·3%] of 240 vs 15 [18·8%] of 80 by day 28). INTERPRETATION: Both the administration of mRNA vaccine CS-2034 and inactivated vaccine BBIBP-CorV as a fourth dose were well tolerated. Heterologous boosting with mRNA vaccine CS-2034 induced higher immune responses and protection against symptomatic SARS-CoV-2 omicron infections compared with homologous boosting, which could support the emergency use authorisation of CS-2034 in adults. FUNDING: Science and Technology Commission of Shanghai, National Natural Science Foundation of China, Jiangsu Provincial Science Fund for Distinguished Young Scholars, and Jiangsu Provincial Key Project of Science and Technology Plan. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Modeling and tracking control of dielectric elastomer actuators based on fractional calculus.

Dielectric elastomer actuators (DEAs) show broad application prospects in the area of soft robots since they offer merits of fast response, large deformation, light weight and high energy conversion efficiency. Practical soft robot applications would usually require the study on the modeling and control of the DEA. However, the DEA has a memory property, which results in a highly nonlinear characteristics, bringing difficulties to the subject. To address this issue, an effective strategy is the utilization of the fractional order model, which is a type of modeling approach that can accurately characterize the memory property of a material with a small amount of parameters. Meanwhile, the fractional order controller can better handler the memory property, and it owns a better flexibility than traditional integer order controllers. With the above considerations, this paper proposes a modeling strategy and a tracking control strategy for the DEA on the basis of the fractional calculus. In the proposed strategy, a fractional order model is established to characterize the complicated nonlinear characteristics of the DEA. Then, to facilitate the computer simulation, the Oustaloup filter is used to construct an integer order approximation model (IOAM) of the fractional order model. Since the IOAM is difficult to be employed in the system controller design due to its high order, the IOAM is further simplified into a reduced order model based on the square root balance truncation algorithm. To realize the high accuracy control of the DEA, a feedforward-feedback combined controller is devised, which is composed of a feedforward controller and a fractional order proportional integral feedback controller (FOPIFC). Among which, the feedforward controller is devised based on the analytical inverse of the reduced order model to compensate the complicated nonlinear characteristics of the DEA, and the FOPIFC is devised to handle the bad influence from the modeling error and uncertainties on the control performance. Based on the proposed strategy, control experiment was conducted, and the root-mean-square errors in experiment are all below 0.7%, indicating the superiority of the presented modeling and tracking control strategies.

Expression of CD22 in Triple-Negative Breast Cancer: A Novel Prognostic Biomarker and Potential Target for CAR Therapy.

Triple-negative breast cancer (TNBC) accounts for 15-20% of all breast cancer cases. Due to the lack of expression of well-known molecular targets [estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2)], there is a need for more alternative treatment approaches in TNBC. Chimeric antigen receptor (CAR)-T cell-based immunotherapy treatment is one of the latest treatment technologies with outstanding therapeutic advances in the past decade, especially in the treatment of hematologic malignancies, but the therapeutic effects of CAR-T cells against solid tumors have not yet shown significant clinical benefits. Identification of highly specific CAR-T targets in solid tumors is also crucial for its successful treatment. CD22 is reported to be a multifunctional receptor that is mainly expressed on the surface of mature B-cells (lymphocytes) and is also highly expressed in most B-cell malignancies. This study aimed to investigate the expression of CD22 in TNBC. Bioinformatic analysis was performed to evaluate the expression of CD22 in breast carcinoma and normal tissues. RNA-seq data of normal and breast carcinoma patients were downloaded from The Cancer Genome Atlas (TCGA), and differential gene expression was performed using R language. Additionally, online bioinformatics web tools (GEPIA and TNM plot) were used to evaluate the expression of CD22 in breast carcinoma and normal tissues. Western blot (WB) analysis and immunofluorescence (IF) were performed to characterize the expression of CD22 in TNBC cell lines. Immunohistochemical (IHC) staining was performed on tumor specimens from 97 TNBC patients for CD22 expression. Moreover, statistical analysis was performed to analyze the association of clinical pathological parameters with CD22 expression. Correlation analysis between overall survival data of TNBC patients and CD22 expression was also performed. Differential gene expression analysis of TCGA data revealed that CD22 is among the upregulated differentially expressed genes (DEGs) with high expression in breast cancer, as compared to normal breast tissues. WB and IF analysis revealed high expression of CD22 in TNBC cell lines. IHC results also showed that approximately 62.89% (61/97) of TNBC specimens were stained positive for CD22. Cell membrane expression of CD22 was evident in 23.71% (23/97) of TNBC specimens, and 39.18% (38/97) of TNBC specimens showed cytoplasmic/membrane expression, while 37.11% (36/97) specimens were negative for CD22. Furthermore, significant associations were found between the size of tumors in TNBC patients and CD22 expression, which unveils its potential as a prognostic biomarker. No significant correlation was found between the overall survival of TNBC patients and CD22 expression. In conclusion, we demonstrated for the first time that CD22 is highly expressed in TNBC. Based on our findings, we anticipated that CD22 could be used as a prognostic biomarker in TNBC, and it might be a potential CAR-T target in TNBC for whom few therapeutic options exist. However, more large-scale studies and clinical trials will ensure its potential usefulness as a CAR-T target in TNBC.

Modeling Based on a Two-Step Parameter Identification Strategy for Liquid Crystal Elastomer Actuator Considering Dynamic Phase Transition Process.

Liquid crystal elastomer (LCE) is a promising candidate for actuation in light-driven soft robot applications. Due to the fact that LCE has complex hysteretic nonlinearities, which are highly dependent on the environment, modeling of actuators made of LCE is a very challenging issue. In this article, a model is proposed to describe the deformation of the LCE actuator accurately and analytically by considering the dynamic phase transition process of LCE molecules. First, an overview of the physical process of LCE's deformation is presented, and the schematic of the LCE actuator, as well as the modeling scheme are then introduced. Next, a thermodynamic analysis of the system's free energy is performed to establish the model for the LCE actuator, which gives the relationship between the system's deformation and the temperature. Here, to describe the complex hysteretic nonlinearity in the model, the dynamic process of the phase transition of LCE molecules is exploited. To effectively identify the model parameters, a two-step parameter identification strategy based on the differential evolution algorithm and nonlinear least-squares method is utilized. Finally, experimental results verify the validity of the proposed model. This modeling provides an approach to describe LCE's deformation with high accuracy and can fully reflect the physical nature of LCE's deformation, especially hysteresis. It can be utilized as a basis for accurate control over LCE actuators in photoresponsive soft robot applications.

Genomic alteration profile and PD-L1 expression among different breast cancer subtypes in Chinese population and their correlations.

BACKGROUD: There were limitations existing in programmed cell-death ligand 1 (PD-L1) as predictive biomarkers for breast cancer (BC), hence exploring the correlation between PD-L1 levels and other biomarkers in BC may become a very useful therapeutic clinical tool. METHODS: A total of 301 Chinese patients with different BC subtypes including 47 HR+/HER2+, 185 HR+/HER2-, 38 HR-/HER2+, and 31 triple-negative breast cancer (TNBC) were enrolled in our study. Next-generation sequencing based Yuansu450 gene panel was used for genomic alteration identification and PD-L1 expression was tested using immunohistochemistry. RESULTS: The most prevalent BC-related mutations were TP53 mutations, followed by mutations in PIK3CA, ERBB2, CDK12, and GATA3 in our Chinese cohort. We found that mutations DDR2 and MYCL were only mutated in HR-/HER2+ subtype, whereas H3-3A and NRAS mutations were only occurred in HR-/HER2- subtype. The percentage of patients with PD-L1-positive expression was higher in patients with HR-/HER2- mainly due to the percentage of PD-L1-high level. Mutational frequencies of TP53, MYC, FAT4, PBRM1, PREX2 were observed to have significant differences among patients with different BC subtypes based on PD-L1 levels. Moreover, a positive correlation was observed between TMB and PD-L1 level in HR+/HER2- subtype, and showed that the proportion of patients with high PD-L1 expression was higher than that of patients with low PD-L1 expression in the HR+/HER2- and HR+/HER2+ cohorts with high Ki67 expression. CONCLUSIONS: The genomic alterations based on PD-L1 and other biomarkers of different cohorts may provide more possibilities for the treatment of BC with different subtypes.

Prognostic value of comprehensive typing based on m6A and gene cluster in TNBC.

BACKGROUND: Triple-negative breast cancer (TNBC) is resistant to targeted therapy with HER2 monoclonal antibodies and endocrine therapy, because it lacks the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). TNBC is a subtype of breast cancer with the worst prognosis and the highest mortality rate compared to other subtypes. N6-methyladenosine (m6A) modification is significant in cancer and metastasis, because it can alter gene expression and function at numerous levels, such as RNA splicing, stability, translocation, and translation. There are limited investigations into the connection between TNBC and m6A. MATERIALS AND METHODS: Breast cancer-related data were retrieved from the Cancer Genome Atlas (TCGA) database, and 116 triple-negative breast cancer cases were identified from the data. The GSE31519 data set, which included 68 cases of TNBC, was obtained from the Gene Expression Omnibus (GEO) database. Survival analysis was used to determine the prognosis of distinct m6A types based on their m6A group, gene group, and m6A score. To investigate the potential mechanism, GO and KEGG analyses were performed on the differentially expressed genes. RESULTS: The expression of m6A-related genes and their impact on prognosis in TNBC patients were studied. According to the findings, m6A was crucial in determining the prognosis of TNBC patients, and the major m6A-linked genes in this process were YTHDF2, RBM15B, IGFBP3, and WTAP. YTHDF2, RBM15B and IGFBP3 are associated with poor prognosis, while WTAP is associated with good prognosis. By cluster analysis, the gene cluster and the m6A cluster were beneficial in predicting the prognosis of TNBC patients. The m6A score based on m6A and gene clusters was more effective in predicting the prognosis of TNBC patients. Furthermore, the tumor microenvironment may play an important role in the process of m6A, influencing TNBC prognosis. CONCLUSIONS: N6-adenylic acid methylation (m6A) was important in altering the prognosis of TNBC patients, and the key m6A-associated genes in this process were YTHDF2, RBM15B, IGFBP3, and WTAP. Furthermore, the comprehensive typing based on m6A and gene clusters was useful in predicting TNBC patients' prognosis, showing potential as valuable evaluating tools for TNBC.

Diagnostic and prognostic significance of SLC50A1 expression in patients with primary early breast cancer.

There is a lack of validated biomarkers for the diagnosis of early breast cancer (EBC). The current study aimed to determine the diagnostic and prognostic value of solute carrier family 50 member 1 (SLC50A1) in patients with EBC. Therefore, 123 patients with EBC, 30 patients with benign breast disease (BBD) and 26 healthy controls (HCs) were recruited. The serum levels of SLC50A1 in paired sera of 40 postoperative patients were assessed by ELISA. Immunohistochemical staining for SLC50A1 was performed in surgical tissue derived from 83 patients with EBC and 30 patients with BBD. mRNA expression of SLC50A1 and its diagnostic and prognostic value in patients with EBC was evaluated using an RNA-sequencing database. The results showed that serum levels of SLC50A1 in patients with EBC were significantly higher compared with those in patients with BBD and HCs (both P<0.001). Additionally, receiver operating characteristic curve analysis revealed that the serum levels of SLC50A1 distinguished patients with EBC from patients with BBD and HCs with a sensitivity of 76.42% and specificity of 76.79% [area under the curve (AUC)=0.783; P<0.001]. The diagnostic value of SLC50A1 was significantly greater than that of carcinoembryonic (P<0.005) and carbohydrate antigen 15-3 (P<0.029). Furthermore, the number of SLC50A1 positive cells significantly increased in tissue of patients with EBC compared with patients with BBD (P<0.001). A positive association between serum levels of SLC50A1 and its expression in tissue samples was observed in patients with EBC (ρ=0.700; P<0.001). Additionally, bioinformatics analysis verified the diagnostic value of SLC50A1, with an AUC of 0.983 (P<0.001). Multivariate analysis demonstrated that SLC50A1 was an independent prognostic factor in patients with EBC with a hazard ratio of 1.917 (P=0.013). These findings indicated that SLC50A1 may be a potential diagnostic biomarker for primary EBC and that SLC50A1 upregulation may be associated with unfavorable prognosis in patients with EBC.

Two lncRNAs, MACC1-AS1 and UCA1, co-mediate the expression of multiple mRNAs through interaction with individual miRNAs in breast cancer cells.

Background: Increasing studies have shown that lncRNAs often play roles through interaction with miRNAs to control gene expression by inhibiting translation or facilitating degradation of target mRNAs. Here, we report that two lncRNAs, MACC1-AS1 and UCA1 are coordinately expressed in breast cancer cells and share the ability to interact with multiple miRNAs to mediate the expression of different genes. Methods: Targetscan, starBase and miRDB databases were used to predict the relationships of MACC1-AS1/UCA1-miRNA-mRNA network. qRT-PCR, and RNA sequencing were used to study the differential expression of lncRNAs and miRNA-targeted genes in breast cancer cells. RIP, RNA pull-down and luciferase assays were performed to confirm the molecular interactions of MACC1-AS1 or UCA1 with predicted miRNAs. The role of lncRNA-mediated miRNA-mRNA interactions in cell proliferation was examined by MTT assays following loss-of-function and gain-of-function effects. Results: We identified a lncRNA-miRNA-mRNA regulatory network in breast cancer cells, in which a number of mRNAs can be co-regulated by MACC1-AS1 and UCA1 lncRNAs. Each lncRNA possesses the capacity as a ceRNA to compete with various mRNA-targeting miRNAs. Interaction of MACC1-AS1 or UCA1 with individual miRNAs is able to increase the expression of the same target mRNAs, such as TBL1X and MEF2D, thus affecting cancer-cell growth phenotype. Conclusions: Our study suggests that in each cell type, there is a balance of interactions between certain lncRNAs and miRNAs. Disrupting the balance would eventually affect the expression of miRNA-targeted genes and cell proliferation.

Associations of Obesity, Physical Activity, and Screening With State-Level Trends and Racial and Ethnic Disparities of Breast Cancer Incidence and Mortality in the US.

Importance: Breast cancer causes disproportionate disease burden among various racial and ethnic groups in the US. However, state-level temporal trends and racial and ethnic disparities and whether metabolic and lifestyle factors and screening access are associated with temporal changes remain largely unknown. Objectives: To investigate temporal trends and racial and ethnic variations at the state level and ecological correlations between obesity, physical activity, and mammography screening and breast cancer incidence and mortality trends among women in the US. Design, Setting, and Participants: A cross-sectional study was conducted to analyze breast cancer incidence and mortality trends among women in the US from January 1, 1999, to December 31, 2017, whereas an ecological analysis was performed to assess the associations. Data were analyzed from March 1, 2021, to September 30, 2021. Population-based cancer registry data were obtained from US Cancer Statistics incidence and mortality data. Prevalence of obesity, physical activity, and mammography screening were obtained from the Behavioral Risk Factor Surveillance System. Exposures: Prevalence of obesity, physical activity, and mammography screening. Main Outcomes and Measures: Breast cancer incidence and mortality trends from 1999 to 2017 in the 50 US states and the District of Columbia. Results: A total of 4 136 123 breast cancer cases and 782 454 deaths were included in the analysis, with a significant reduction in incidence (average annual percent change [AAPC], -0.4% [95% CI, -0.6% to -0.2%)]) and mortality (AAPC, -1.7% [95% CI, -1.8% to -1.5%]) during the study period. A significant state-level variation in breast cancer incidence and mortality between White women and those of other races and ethnicities was observed. A significant positive correlation was found between obesity and breast cancer incidence (r = 0.316; P = .02) and mortality (r = 0.400; P = .004) and an inverse correlation was found between physical activity and incidence (r = -0.577; P < .001) in women 55 years or older and mammography screening and mortality trends (r = -0.644; P < .001) in women 40 years or older. Conclusions and Relevance: The findings of this cross-sectional study suggest that racial and ethnic disparities exist at the state level with regard to breast cancer incidence and mortality among women in the US. Metabolic and lifestyle factors and screening access were associated with the observed trends and racial and ethnic disparities. Interventions targeting these factors may help reduce the incidence of breast cancer and related deaths.

Overexpressed VDAC1 in breast cancer as a novel prognostic biomarker and correlates with immune infiltrates.

BACKGROUND: More and more evidence suggests that cancer is a mitochondrial metabolic disease recently and mitochondria dysfunction is critical to tumorigenesis. As a gatekeeper of mitochondria, the voltage-dependent anion channel 1 (VDAC1) is associated with the development of breast cancer (BC). However, its potential mechanism and clinical significance remain unclear; thus, in this research, we aimed to explore it. METHODS: VDAC1 expression in BC tissues and normal tissues was obtained from The Cancer Genome Atlas (TCGA) and validated by datasets from the gene expression omnibus (GEO) database. Then, the relationships between VDAC1 expression and clinicopathological features were analyzed. Receiver operating characteristics (ROC) curves were used to identify the diagnostic value of VDAC1. The prognostic value was evaluated by Kaplan-Meier survival curves and Cox regression analysis. VDAC1 with its co-expression genes were subjected to enrichment analysis to explore potential mechanisms in BC and the protein-protein interaction (PPI) network was constructed. At last, the association between VDAC1 expression and infiltration levels of immune cell infiltration by various methods, as well as their corresponding markers, was analyzed. We also analyzed the correction between VDAC1 expression and eight immune checkpoint genes and the tumor immune dysfunction and exclusion (TIDE) scores of each BC sample in TCGA were calculated and the differences between high and low VDAC1 expression groups were analyzed. RESULTS: VDAC1 expression was remarkably elevated in BC (p < 0.001), and high expression of VDAC1 was associated with the positive expression of ER (p = 0.004), PR (p = 0.033), and HER2 (p = 0.001). ROC analysis suggested that VDAC1 had diagnosed value in BC. The Kaplan-Meier analysis suggested that higher expression of VDAC1 was associated with shorter overall survival (OS), and further Cox regression analysis revealed that VDAC1 was an independent factor of unfavorable prognosis in BC patients. Enrichment analysis of VDAC1 and its co-expression suggested that VDAC1 was related to the regulation of mitochondrial energy metabolism and protein modification, and the HIF-1 singing pathway might be the potential mechanism in BC. Notably, we found that VDAC1 expression was infiltration levels of most types of immune cells, as well as the expression of marker genes of immune cells. The ICGs PDCD1, CTLA4, LAG3, SIGLEC15, and TIGIT were negatively corrected with VDAC1 expression in BC. TIDE scores between the low and high expression groups showed no difference. CONCLUSION: Overexpressed VDAC1 in BC could be severed as a novel biomarker for diagnosis and VDAC1 was an independent factor for adverse prognosis prediction. Our study revealed that VDAC1 might inhibit tumor immunity and might be a novel therapeutic target in BC.

A Predictive Model for Nonsentinel Node Status after Sentinel Lymph Node Biopsy in Sentinel Lymph Node-Positive Chinese Women with Early Breast Cancer.

BACKGROUND: Axial lymph node dissection (ALND) is needed in patients with positive sentinel lymph node (SLN). ALND is easy to cause upper limb edema. Therefore, accurate prediction of nonsentinel lymph nodes (non-SLN) which may not need ALND can avoid excessive dissection and reduce complications. We constructed a new prognostic model to predict the non-SLN metastasis of Chinese breast cancer patients. METHODS: We enrolled 736 patients who underwent sentinel lymph node biopsy (SLNB); 228 (30.98%) were diagnosed with SLNB metastasis which was determined by intraoperative pathological detection and further accepted ALND. We constructed a prediction model by univariate analysis, multivariate analysis, "R" language, and binary logistic regression in the abovementioned 228 patients and verified this prediction model in 60 patients. RESULTS: Based on univariate analysis using α = 0.05 as the significance level for type I error, we found that age (P=0.045), tumor size (P=0.006), multifocality (P=0.011), lymphovascular invasion (P=0.003), positive SLN number (P=0.009), and negative SLN number (P=0.034) were statistically significant. Age was excluded in multivariate analysis, and we constructed a predictive equation to assess the risk of non-SLN metastasis: Logit(P)=Ln(P/1 - P)=0.267∗a+1.443∗b+1.078∗c+0.471∗d - 0.618∗e - 2.541 (where "a" represents tumor size, "b" represents multifocality, "c" represents lymphovascular invasion, "d" represents the number of metastasis of SLN, and "e" represents the number of SLNs without metastasis). AUCs for the training group and validation group were 0.715 and 0.744, respectively. When setting the risk value below 22.3%, as per the prediction equation's low-risk interval, our model predicted that about 4% of patients could avoid ALND. CONCLUSIONS: This study established a model which demonstrated good prognostic performance in assessing the risk of non-SLN metastasis in Chinese patients with positive SLNs.

Mutant p53 and Twist1 Co-Expression Predicts Poor Prognosis and Is an Independent Prognostic Factor in Breast Cancer.

PURPOSE: The basic helix-loop-helix transcription factor (bHLH) transcription factor Twist1 plays a key role in embryonic development and tumorigenesis. p53 is a frequently mutated tumor suppressor in cancer. Both proteins play a key and significant role in breast cancer tumorigenesis. However, the regulatory mechanism and clinical significance of their co-expression in this disease remain unclear. The purpose of this study was to analyze the expression patterns of p53 and Twist1 and determine their association with patient prognosis in breast cancer. We also investigated whether their co-expression could be a potential marker for predicting patient prognosis in this disease. METHODS: Twist1 and mutant p53 expression in 408 breast cancer patient samples were evaluated by immunohistochemistry. Kaplan-Meier Plotter was used to analyze the correlation between co-expression of Twist1 and wild-type or mutant p53 and prognosis for recurrence-free survival (RFS) and overall survival (OS). Univariate analysis, multivariate analysis, and nomograms were used to explore the independent prognostic factors in disease-free survival (DFS) and OS in this cohort. RESULTS: Of the 408 patients enrolled, 237 (58%) had high mutant p53 expression. Two-hundred twenty patients (53.9%) stained positive for Twist1, and 188 cases were Twist1-negative. Furthermore, patients that co-expressed Twist1 and mutant p53 (T+P+) had significantly advanced-stage breast cancer [stage III, 61/89 T+P+ (68.5%) vs. 28/89 T-P- (31.5%); stage II, 63/104 T+P+ (60.6%)vs. 41/104 T-P- (39.4%)]. Co-expression was negatively related to early clinical stage (i.e., stages 0 and I; P = 0.039). T+P+ breast cancer patients also had worse DFS (95% CI = 1.217-7.499, P = 0.017) and OS (95% CI = 1.009-9.272, P = 0.048). Elevated Twist1 and mutant p53 expression predicted shorter RFS in basal-like patients. Univariate and multivariate analysis identified three variables (i.e., lymph node involvement, larger tumor, and T+P+) as independent prognostic factors for DFS. Lymph node involvement and T+P+ were also independent factors for OS in this cohort. The total risk scores and nomograms were reliable for predicting DFS and OS in breast cancer patients. CONCLUSIONS: Our results revealed that co-expression of mutant p53 and Twist1 was associated with advanced clinical stage, triple negative breast cancer (TNBC) subtype, distant metastasis, and shorter DFS and OS in breast cancer patients. Furthermore, lymph nodes status and co-expression of Twist1 and mutant p53 were classified as independent factors for DFS and OS in this cohort. Co-evaluation of mutant p53 and Twist1 might be an appropriate tool for predicting breast cancer patient outcome.