UTRN as a potential biomarker in breast cancer: a comprehensive bioinformatics and in vitro study.

Utrophin (UTRN), known as a tumor suppressor, potentially regulates tumor development and the immune microenvironment. However, its impact on breast cancer's development and treatment remains unstudied. We conducted a thorough examination of UTRN using both bioinformatic and in vitro experiments in this study. We discovered UTRN expression decreased in breast cancer compared to standard samples. High UTRN expression correlated with better prognosis. Drug sensitivity tests and RT-qPCR assays revealed UTRN's pivotal role in tamoxifen resistance. Furthermore, the Kruskal-Wallis rank test indicated UTRN's potential as a valuable diagnostic biomarker for breast cancer and its utility in detecting T stage of breast cancer. Additionally, our results demonstrated UTRN's close association with immune cells, inhibitors, stimulators, receptors, and chemokines in breast cancer (BRCA). This research provides a novel perspective on UTRN's role in breast cancer's prognostic and therapeutic value. Low UTRN expression may contribute to tamoxifen resistance and a poor prognosis. Specifically, UTRN can improve clinical decision-making and raise the diagnosis accuracy of breast cancer.

GBP2 enhances paclitaxel sensitivity in triple­negative breast cancer by promoting autophagy in combination with ATG2 and inhibiting the PI3K/AKT/mTOR pathway.

Chemoresistance is a major challenge in treating triple­negative breast cancer (TNBC); chemotherapy remains the primary approach. The present study aimed to elucidate the role of guanylate­binding protein 2 (GBP2) in activating autophagy in TNBC and its impact on the sensitivity of TNBC cells to paclitaxel (PTX). Transfection with lentivirus was performed to establish TNBC cell lines with stable, high GBP2 expression. The mRNA and protein levels of GBP2 expression were evaluated utilizing reverse transcription­quantitative PCR and western blotting, respectively. Autophagy in TNBC cells was evaluated using immunoblotting, transmission electron microscopy and fluorescence microscopy. The PI3K/AKT/mTOR pathway proteins and their phosphorylation were detected by immunoblotting, and fluorescence co­localization analysis was performed to evaluate the association between GBP2 and autophagy­related protein 2 (ATG2). BALB/c NUDE mice were subcutaneously injected with GBP2 wild­type/overexpressing MDA­MB­231 cells. Low GBP2 expression was detected in TNBC, which was associated with a poor prognosis. Overexpression of GBP2 suppressed cell growth, and especially enhanced autophagy in TNBC. Forced expression of GBP2 significantly increased the PTX sensitivity of TNBC cells, and the addition of autophagy inhibitors reversed this effect. GBP2 serves as a prognostic marker and exerts a notable inhibitory impact on TNBC. It functions as a critical regulator of activated autophagy by co­acting with ATG2 and inhibiting the PI3K/AKT/mTOR pathway, which contributes to increasing sensitivity of TNBC cells to PTX. Therefore, GBP2 is a promising therapeutic target for enhancing TNBC treatment.

USP46 enhances tamoxifen resistance in breast cancer cells by stabilizing PTBP1 to facilitate glycolysis.

Tamoxifen (TAM) is the primary drug for treating estrogen receptor alpha-positive (ER+) breast cancer (BC). However, resistance to TAM can develop in some patients, limiting its therapeutic efficacy. The ubiquitin-specific protease (USP) family has been associated with the development, progression, and drug resistance of various cancers. To explore the role of USPs in TAM resistance in BC, we used qRT-PCR to compare USP expression between TAM-sensitive (MCF-7 and T47D) and TAM-resistant cells (MCF-7R and T47DR). We then modulated USP46 expression and examined its impact on cell proliferation, drug resistance (via CCK-8 and EdU experiments), glycolysis levels (using a glycolysis detection assay), protein interactions (confirmed by co-IP), and protein changes (analyzed through Western blotting). Our findings revealed that USP46 was significantly overexpressed in TAM-resistant BC cells, leading to the inhibition of the ubiquitin degradation of polypyrimidine tract-binding protein 1 (PTBP1). Overexpression of PTBP1 increased the PKM2/PKM1 ratio, promoted glycolysis, and intensified TAM resistance in BC cells. Knockdown of USP46 induced downregulation of PTBP1 protein by promoting its K48-linked ubiquitination, resulting in a decreased PKM2/PKM1 ratio, reduced glycolysis, and heightened TAM sensitivity in BC cells. In conclusion, this study highlights the critical role of the USP46/PTBP1/PKM2 axis in TAM resistance in BC. Targeted therapy against USP46 may represent a promising strategy to improve the prognosis of TAM-resistant patients.

Label-Free DNA Hybridization Detection Using a Highly Sensitive Fiber Microcavity Biosensor.

A novel label-free optical fiber biosensor, based on a microcavity fiber Mach-Zehnder interferometer, was developed and practically demonstrated for DNA detection. The biosensor was fabricated using offset splicing standard communication single-mode fibers (SMFs). The light path of the sensor was influenced by the liquid sample in the offset open cavity. In the experiment, a high sensitivity of -17,905 nm/RIU was achieved in the refractive index (RI) measurement. On this basis, the probe DNA (pDNA) was immobilized onto the sensor's surface using APTES, enabling real-time monitoring of captured complementary DNA (cDNA) samples. The experimental results demonstrate that the biosensor exhibited a high sensitivity of 0.32 nm/fM and a limit of detection of 48.9 aM. Meanwhile, the sensor has highly repeatable and specific performance. This work reports an easy-to-manufacture, ultrasensitive, and label-free DNA biosensor, which has significant potential applications in medical diagnostics, bioengineering, gene identification, environmental science, and other biological fields.

Treatment of Thoracic Tuberculosis Through Posterior Costal Transverse Joint Window: A Clinical Study.

BACKGROUND: The surgical treatment of thoracic spinal tuberculosis has garnered enormous interest from researchers toward the development of posterior surgical techniques that have contributed to greater use of the 1-stage posterior approach. This study aims to demonstrate the initial clinical experience of a modified total posterior approach, in which the 1-stage posterior approach preserves the posterior spinal column structure by combining with the endoprosthetic implant fusion for thoracic spinal tuberculosis. METHODS: In this clinical study, we intended to report the initial idea of a modified total posterior approach. In detail, a 1-stage posterior approach was applied to preserve the posterior spinal column structure that could be applied to clinical practice. RESULTS: The employed practical procedure presented a reduced duration of surgical intervention and intraoperative trauma. Nevertheless, further studies with large samples and multiple centers are required to explore the idea comprehensively. CONCLUSIONS: This approach offered some advantages in terms of intraoperative exposure, blood loss volume, and length of surgery. Further, multicenter studies with large samples are needed to understand the precise effects and implications of the approach.

A Point-of-Care Testing Device Utilizing Graphene-Enhanced Fiber Optic SPR Sensor for Real-Time Detection of Infectious Pathogens.

Timely detection of highly infectious pathogens is essential for preventing and controlling public health risks. However, most traditional testing instruments require multiple tedious steps and ultimately testing in hospitals and third-party laboratories. The sample transfer process significantly prolongs the time to obtain test results. To tackle this aspect, a portable fiber optic surface plasmon resonance (FO-SPR) device was developed for the real-time detection of infectious pathogens. The portable device innovatively integrated a compact FO-SPR sensing component, a signal acquisition and processing system, and an embedded power supply unit. A gold-plated fiber is used as the FO-SPR sensing probe. Compared with traditional SPR sensing systems, the device is smaller size, lighter weight, and higher convenience. To enhance the detection capacity of pathogens, a monolayer graphene was coated on the sensing region of the FO-SPR sensing probe. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was used to evaluate the performance of the portable device. The device can accurately detect the SARS-CoV-2 spike S1 protein in phosphate-buffered saline (PBS) and artificial saliva within just 20 min, and the device successfully detected cultured SARS-CoV-2 virus. Furthermore, the FO-SPR probe has long-term stability, remaining stable for up to 8 days. It could distinguish between the SARS-CoV-2 spike protein and the MERS-CoV spike protein. Hence, this FO-SPR device provides reliable, rapid, and portable access to test results. It provides a promising point-of-care testing (POCT) tool for on-site screening of infectious pathogens.

Development and testing of a random forest-based machine learning model for predicting events among breast cancer patients with a poor response to neoadjuvant chemotherapy.

BACKGROUND: Breast cancer (BC) is the most common malignant tumor around the world. Timely detection of the tumor progression after treatment could improve the survival outcome of patients. This study aimed to develop machine learning models to predict events (defined as either (1) the first tumor relapse locally, regionally, or distantly; (2) a diagnosis of secondary malignant tumor; or (3) death because of any reason.) in BC patients post-treatment. METHODS: The patients with the response of stable disease (SD) and progressive disease (PD) after neoadjuvant chemotherapy (NAC) were selected. The clinicopathological features and the survival data were recorded in 1 year and 5 years, respectively. Patients were randomly divided into the training set and test set in the ratio of 8:2. A random forest (RF) and a logistic regression were established in both of 1-year cohort and the 5-year cohort. The performance was compared between the two models. The models were validated using data from the Surveillance, Epidemiology, and End Results (SEER) database. RESULTS: A total of 315 patients were included. In the 1-year cohort, 197 patients were divided into a training set while 87 were into a test set. The specificity, sensitivity, and AUC were 0.800, 0.833, and 0.810 in the RF model. And 0.520, 0.833, and 0.653 of the logistic regression. In the 5-year cohort, 132 patients were divided into the training set while 33 were into the test set. The specificity, sensitivity, and AUC were 0.882, 0.750, and 0.829 in the RF model. And 0.882, 0.688, and 0.752 of the logistic regression. In the external validation set, of the RF model, the specificity, sensitivity, and AUC were 0.765, 0.812, and 0.779. Of the logistics regression model, the specificity, sensitivity, and AUC were 0.833, 0.376, and 0.619. CONCLUSION: The RF model has a good performance in predicting events among BC patients with SD and PD post-NAC. It may be beneficial to BC patients, assisting in detecting tumor recurrence.

Study on disinfection effect of a 222-nm UVC excimer lamp on object surface.

Effective disinfection of contaminated surfaces is essential for preventing the transmission of pathogens. In this study, we investigated the UV irradiance and wavelength distribution of a 222-nm ultraviolet C (UVC) excimer lamp and its disinfection efficacy against microorganisms in laboratory conditions. By using a carrier quantitative germicidal test with stainless steel sheets as carriers, we examined the disinfection effect of the 222-nm UVC lamp on three standard strains-Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa. We tested the disinfection efficacy under different conditions by adjusting irradiation time, as well as the state and temperature of the stainless steel carriers. Our results indicated that a bacterial suspension in PBS and not-dried stainless steel carriers yielded better disinfection than in TSB and dried carriers. Additionally, carrier temperature had no significant impact on disinfection efficacy. When utilizing a bacterial suspension in PBS and non-dried carriers at a temperature of 20 °C, the three bacteria were eliminated by 222-nm UVC excimer lamp irradiation in just 15 s. In contrast, when using a bacterial suspension in TSB and dried carriers at temperatures of 20 °C, 4 °C, or - 20 °C, the three bacteria were eradicated by 222-nm UVC excimer lamp irradiation in 60 s. Comparatively, the LPM lamp required more than 10 min to achieve the same disinfection effect. Our data demonstrate that the 222-nm UVC excimer lamp has higher irradiance and a more potent microbial disinfection effect than the LPM lamp, requiring significantly less irradiation time to achieve the same disinfection effect under identical conditions. Furthermore, the 222-nm UVC excimer lamp exhibited a substantial disinfection effect on bacterial propagules at low temperatures. Our findings support the optimization of "tunnel-type" cold-chain goods disinfection devices, providing an alternative, highly efficient, and practical tool to combat the spread of SARS-CoV-2 through cold-chain systems.

Comparison of the pCR Rate and DFS Among Breast Cancer Patients with Different Hormone Receptor and HER2 Statuses.

Background: Recent studies have investigated the features of breast cancer (BC) with low human epidermal growth factor receptor 2 (HER2) expression or HER2-0 expression. However, the results were inconsistent. In this study, we investigated the differences in the pathological complete response (pCR) rate and disease-free survival (DFS) between HER2-low and HER2-0 BC patients and between subgroups. Methods: HER2-negative BC patients who received neoadjuvant chemotherapy between January 2013 and December 2019 in our hospital were retrospectively reviewed. First, the pCR rate and DFS were compared between HER2-low and HER2-0 patients and among different hormone receptor (HR) and HER2 statuses. Subsequently, DFS was compared between different HER2 status populations with or without pCR. Finally, a Cox regression model was used to identify the prognostic factors. Results: Overall, 693 patients were selected: 561 were HER2-low, and 132 were HER2-0. Between the two groups, there were significant differences in N stage (P = 0.008) and HR status (P = 0.007). No significant difference in the pCR rate (12.12% vs 14.39%, P = 0.468) or DFS was observed, independent of HR status. HR+/HER2-low patients had a significantly worse pCR rate (P < 0.001) and longer DFS (P < 0.001) than HR-/HER2-low or HER2-0 patients. In addition, a longer DFS was found in HER2-low patients versus HER2-0 patients among those who did not achieve pCR. Cox regression showed that N stage and HR status were prognostic factors in the overall and HER2-low populations, while no prognostic factor was found in the HER2-0 group. Conclusion: This study suggested that HER2 status is not associated with the pCR rate or DFS. Longer DFS was found only among patients who did not achieve pCR in the HER2-low versus HER2-0 population. We speculated that the interaction of HR and HER2 might have played a crucial role in this process.

Characterization of starvation response-related genes for predicting prognosis in breast cancer.

Breast cancer (BRCA) cells typically exist in nutrient-deficient microenvironments and quickly adapt to states with fluctuating nutrient levels. The tumor microenvironment of starvation is intensely related to metabolism and the malignant progression of BRCA. However, the potential molecular mechanism has not been thoroughly scrutinized. As a result, this study aimed to dissect the prognostic implications of mRNAs involved in the starvation response and construct a signature for forecasting the outcomes of BRCA. In this research, we investigated how starvation could affect BRCA cells' propensities for invasion and migration. The effects of autophagy and glucose metabolism mediated by starved stimulation were examined through transwell assays, western blot, and the detection of glucose concentration. A starvation response-related gene (SRRG) signature was ultimately generated by integrated analysis. The risk score was recognized as an independent risk indicator. The nomogram and calibration curves revealed that the model had excellent prediction accuracy. Functional enrichment analysis indicated this signature was significantly enriched in metabolic-related pathways and energy stress-related biological processes. Furthermore, phosphorylated protein expression of the model core gene EIF2AK3 increased after the stimulus of starvation, and EIF2AK3 may play an essential role in the progression of BRCA in the starved microenvironment. To sum up, we constructed and validated a novel SRRG signature that could accurately predict outcomes and may be developed as a therapeutic target for the precise treatment of BRCA.

An Angiogenesis-Related lncRNA Signature Is Associated with Prognosis and Tumor Immune Microenvironment in Breast Cancer.

Angiogenesis is crucial in the development and progression of tumors. This study examined the relationship between angiogenesis-related lncRNAs (AR-lncRNAs) and breast cancer (BC) immunity and prognosis. We used univariate Cox regression analysis to obtain AR-lncRNAs closely related to BC prognosis. Cluster analysis of BC patients was performed using non-negative matrix factorization (NMF) analysis according to the expression of AR-lncRNAs that were prognostically relevant. An AR-lncRNA risk model (AR-lncM) was created using LASSO regression analysis to predict the prognosis and survival of BC patients. Subsequently, the effect of LINC01614 on cell migration and invasion was verified by Transwell and Western blot assays, and the CCK-8 assay detected its impact on cell sensitivity to tamoxifen. Finally, we obtained 17 AR-lncRNAs from the TCGA database that were closely associated with the prognosis of BC patients. Based on the expression of these AR-lncRNAs, BC patients were divided into five clusters using NMF analysis. Cluster 1 was found to have a better prognosis, higher expression of immune checkpoints, and higher levels of immune cell infiltration. Furthermore, an AR-LncM model was created using ten prognostic-related AR-lncRNAs. The model's risk predictive performance was validated using survival analysis, timeROC curves, and univariate and multivariate Cox analysis. The most interesting gene in the model, LINC01614, was found to regulate epithelial-mesenchymal transition (EMT) and tamoxifen sensitivity in BC cells, implying that LINC01614 could be a potential therapeutic target for BC patients.

A plasma 3-marker microRNA biosignature distinguishes spinal tuberculosis from other spinal destructive diseases and pulmonary tuberculosis.

Accurate spinal tuberculosis (TB) diagnosis is of utmost importance for adequately treating and managing the disease. Given the need for additional diagnostic tools, this study aimed to investigate the utility of host serum miRNA biomarkers for diagnosing and distinguishing spinal tuberculosis (STB) from pulmonary tuberculosis (PTB) and other spinal diseases of different origins (SDD). For a case-controlled investigation, a total of 423 subjects were voluntarily recruited, with 157 cases of STB, 83 cases of SDD, 30 cases of active PTB, and 153 cases of healthy controls (CONT) in 4 clinical centers. To discover the STB-specific miRNA biosignature, a high-throughput miRNA profiling study was performed in the pilot study with 12 cases of STB and 8 cases of CONT using the Exiqon miRNA PCR array platform. A bioinformatics study identified that the 3-plasma miRNA combination (hsa-miR-506-3p, hsa-miR-543, hsa-miR-195-5p) might serve as a candidate biomarker for STB. The subsequent training study developed the diagnostic model using multivariate logistic regression in training data sets, including CONT(n=100) and STB (n=100). Youden's J index determined the optimal classification threshold. Receiver Operating Characteristic (ROC) curve analysis showed that 3-plasma miRNA biomarker signatures have an area under the curve (AUC) = 0.87, sensitivity = 80.5%, and specificity = 80.0%. To explore the possible potential to distinguish spinal TB from PDB and other SDD, the diagnostic model with the same classification threshold was applied to the analysis of the independent validation data set, including CONT(n=45), STB(n=45), brucellosis spondylitis (BS, n=30), PTB (n=30), spinal tumor (ST, n=30) and pyogenic spondylitis (PS, n=23). The results showed diagnostic model based on three miRNA signatures could discriminate the STB from other SDD groups with sensitivity=80%, specificity=96%, Positive Predictive Value (PPV)=84%, Negative Predictive Value (NPV)=94%, the total accuracy rate of 92%. These results indicate that this 3-plasma miRNA biomarker signature could effectively discriminate the STB from other spinal destructive diseases and pulmonary tuberculosis. The present study shows that the diagnostic model based on 3-plasma miRNA biomarker signature (hsa-miR-506-3p, hsa-miR-543, hsa-miR-195-5p) may be used for medical guidance to discriminate the STB from other spinal destructive disease and pulmonary tuberculosis.

A mitochondrial function-related LncRNA signature predicts prognosis and immune microenvironment for breast cancer.

Mitochondrial function, as the core of the cell's energy metabolism, is firmly connected to cancer metabolism and growth. However, the involvement of long noncoding RNAs (lncRNAs) related to mitochondrial function in breast cancer (BRCA) has not been thoroughly investigated. As a result, the objective of this research was to dissect the prognostic implication of mitochondrial function-related lncRNAs and their link to the immunological microenvironment in BRCA. The Cancer Genome Atlas (TCGA) database was used to acquire clinicopathological and transcriptome information for BRCA samples. Mitochondrial function-related lncRNAs were recognized by coexpression analysis of 944 mitochondrial function-related mRNAs obtained from the MitoMiner 4.0 database. A novel prognostic signature was built in the training cohort using integrated analysis of mitochondrial function-related lncRNA and the corresponding clinical information through univariate analysis, lasso regression, and stepwise multivariate Cox regression analysis. The prognostic worth was judged in the training cohort and validated in the test cohort. In addition, functional enrichment and immune microenvironment analyses were performed to explore the risk score on the basis of the prognostic signature. An 8-mitochondrial function-related lncRNA signature was generated by integrated analysis. Individuals within the higher-risk category had a worse overall survival rate (OS) (training cohort: P < 0.001; validation cohort: P < 0.001; whole cohort: P < 0.001). The risk score was identified as an independent risk factor by multivariate Cox regression analysis (training cohort: HR 1.441, 95% CI 1.229-1.689, P < 0.001; validation cohort: HR 1.343, 95% CI 1.166-1.548, P < 0.001; whole cohort: HR 1.241, 95% CI 1.156-1.333, P < 0.001). Following that, the predictive accuracy of the model was confirmed by the ROC curves. In addition, nomograms were generated, and the calibration curves revealed that the model had excellent prediction accuracy for 3- and 5-year OS. Besides, the higher-risk BRCA individuals have relatively decreased amounts of infiltration of tumor-killing immune cells, lower levels of immune checkpoint molecules, and immune function. We constructed and verified a novel mitochondrial function-related lncRNA signature that might accurately predict the outcome of BRCA, play an essential role in immunotherapy, and might be exploited as a therapeutic target for precise BRCA therapy.

Tunable composite lattice structure for low-frequency and ultra-broadband underwater sound absorption.

The underwater sound absorption technique in low-frequency and broadband has far-reaching prospects since it is essential for noise reduction of deep-sea operation requirements and evading advanced underwater target detection. Here, we propose an underwater sound-absorbing composite lattice with low-frequency and ultra-broadband characteristics. The composite lattice is constructed by regular spatially stacking cells with different sizes of metallic core spheres. All the core spheres are coated with silicon rubbers, and cells are embedded in the rubber matrix. In the composite lattice stereostructure, the lattice cells convert incident longitudinal waves into transverse waves through multiple local resonance coupling and multiple scattering. The energy is localized and dissipated in the composite lattice. We analyze the relationship among the corresponding absorption spectrums, the displacement clouds, and the resonance modes of lattice cells. Then, we construct a composite lattice and realize low-frequency broadband absorption from 693 to 1106 Hz with absorptance above 0.8. Further, our investigation demonstrates that the absorption bandwidth can be extended to ultra-broadband from 1077 to 10 000 Hz, where the thickness of the composite lattice is λ/17.05. The proposed composite lattice provides a practical approach to designing ultrathin low-frequency and ultra-broadband acoustic absorption coating for underwater noise suppression.

Nomograms for Predicting Disease-Free Survival Based on Core Needle Biopsy and Surgical Specimens in Female Breast Cancer Patients with Non-Pathological Complete Response to Neoadjuvant Chemotherapy.

PURPOSE: While a pathologic complete response (pCR) is regarded as a surrogate endpoint for pos-itive outcomes in breast cancer (BC) patients receiving neoadjuvant chemotherapy (NAC), fore-casting the prognosis of non-pCR patients is still an open issue. This study aimed to create and evaluate nomogram models for estimating the likelihood of disease-free survival (DFS) for non-pCR patients. METHODS: A retrospective analysis of 607 non-pCR BC patients was conducted (2012-2018). After converting continuous variables to categorical variables, variables entering the model were progressively identified by univariate and multivariate Cox regression analyses, and then pre-NAC and post-NAC nomogram models were developed. Regarding their discrimination, ac-curacy, and clinical value, the performance of the models was evaluated by internal and external validation. Two risk assessments were performed for each patient based on two models; patients were separated into different risk groups based on the calculated cut-off values for each model, including low-risk (assessed by the pre-NAC model) to low-risk (assessed by the post-NAC model), high-risk to low-risk, low-risk to high-risk, and high-risk to high-risk groups. The DFS of different groups was assessed using the Kaplan-Meier method. RESULTS: Both pre-NAC and post-NAC nomogram models were built with clinical nodal (cN) status and estrogen receptor (ER), Ki67, and p53 status (all p < 0.05), showing good discrimination and calibration in both internal and external validation. We also assessed the performance of the two models in four subtypes, with the tri-ple-negative subtype showing the best prediction. Patients in the high-risk to high-risk subgroup have significantly poorer survival rates (p < 0.0001). CONCLUSION: Two robust and effective nomo-grams were developed to personalize the prediction of DFS in non-pCR BC patients treated with NAC.

The impact of postmastectomy radiotherapy on cT1-2N1 breast cancer patients with ypN0 after neoadjuvant chemotherapy: a retrospective study based on real-world data.

BACKGROUND: The role of postmastectomy radiation therapy (PMRT) in clinical T1-2N1 breast cancer patients who achieve axillary pathological complete response (ypN0) after neoadjuvant chemotherapy (NAC) is controversial. METHODS: Data from cT1-2N1 breast cancer patients who converted to ypN0 after NAC and subsequent surgery were retrospectively analyzed. Disease-free survival (DFS) and overall survival (OS) were estimated using the Kaplan‒Meier method. Univariate and multivariate Cox regression models were applied to investigate the correlations between clinical or pathological parameters and survival. RESULTS: From 2012-2019, we identified 116 cases for analysis, including 31 (26.7%) who received PMRT and 85 (73.3%) who did not. At a median follow-up time of 56.4 months, the 5-year DFS and OS rates were 90.2% and 96.7% with PMRT and 93.7% and 97.3% without PMRT, respectively. PMRT did not affect either DFS (p = 0.234) or OS (p = 0.878). On multivariate analyses, no differences in DFS or OS between the two groups were detected, taking into consideration the following factors: age, molecular subtype, Ki67 index, cT stage, and in-breast pathologic complete response (DFS: HR 2.260; 95% CI 0.465-10.982; p = 0.312. OS: HR 1.400; 95% CI 0.138-14.202; p = 0.776). This nonsignificant difference was also consistent in subgroup analyses (all p > 0.05). CONCLUSIONS: PMRT has limited ability to confer DFS or OS benefits for cT1-2N1 breast cancer patients who achieved axillary pathological complete response after NAC and total mastectomy. It is imperative to conduct prospective studies to investigate the safety and feasibility of omitting PMRT. TRIAL REGISTRATION: This research was approved by the Ethics Committee of The First Affiliated Hospital of Chongqing Medical University (ID: No. 2021-442).

Development and Assessment of a Novel Core Biopsy-Based Prediction Model for Pathological Complete Response to Neoadjuvant Chemotherapy in Women with Breast Cancer.

Purpose: Pathological complete response (pCR), the goal of NAC, is considered a surrogate for favorable outcomes in breast cancer (BC) patients administrated neoadjuvant chemotherapy (NAC). This study aimed to develop and assess a novel nomogram model for predicting the probability of pCR based on the core biopsy. Methods: This was a retrospective study involving 920 BC patients administered NAC between January 2012 and December 2018. The patients were divided into a primary cohort (769 patients from January 2012 to December 2017) and a validation cohort (151 patients from January 2017 to December 2018). After converting continuous variables to categorical variables, variables entering the model were sequentially identified via univariate analysis, a multicollinearity test, and binary logistic regression analysis, and then, a nomogram model was developed. The performance of the model was assessed concerning its discrimination, accuracy, and clinical utility. Results: The optimal predictive threshold for estrogen receptor (ER), Ki67, and p53 were 22.5%, 32.5%, and 37.5%, respectively (all p < 0.001). Five variables were selected to develop the model: clinical T staging (cT), clinical nodal (cN) status, ER status, Ki67 status, and p53 status (all p ≤ 0.001). The nomogram showed good discrimination with the area under the curve (AUC) of 0.804 and 0.774 for the primary and validation cohorts, respectively, and good calibration. Decision curve analysis (DCA) showed that the model had practical clinical value. Conclusions: This study constructed a novel nomogram model based on cT, cN, ER status, Ki67 status, and p53 status, which could be applied to personalize the prediction of pCR in BC patients treated with NAC.

A dual-targeting near-infrared biomimetic drug delivery system for HBV treatment.

Hepatitis B virus (HBV) infection is a serious global public health threat. It remains elusive to achieve a functional HBV cure with currently available antivirals. Herein, a photo-responsive delivery vehicle composed of Nd3+ -sensitized core-shell upconversion nanoparticle (UCNP), mesoporous silica nanoparticle (MSN), antisense oligonucleotides (ASOs), and capsid-binding inhibitor C39 was established, which was named UMAC according to the initials of its components. Subsequently, the as-synthesized delivery vehicle was encapsulated by ß- D-galactopyranoside (Gal) modified red blood cell (RBC) membrane vesicles, which enabled precise targeting of the liver cells (UMAC-M-Gal). Both in vitro and in vivo experiments demonstrated that this biomimetic system could successfully achieve controlled drug release under light conditions at 808 nm, leading to effective suppression of HBV replication in this dual-targeted therapeutic approach. Together, these results substantiate the system has huge prospects for application to achieve functional HBV cure, and provides a promising novel strategy for drug delivery.

GPSAdb: a comprehensive web resource for interactive exploration of genetic perturbation RNA-seq datasets.

Gene knock-out/down methods are commonly used to explore the functions of genes of interest, but a database that systematically collects perturbed data is not available currently. Manual curation of all the available human cell line perturbed RNA-seq datasets enabled us to develop a comprehensive human perturbation database (GPSAdb, https://www.gpsadb.com/). The current version of GPSAdb collected 3048 RNA-seq datasets associated with 1458 genes, which were knocked out/down by siRNA, shRNA, CRISPR/Cas9, or CRISPRi. The database provides full exploration of these datasets and generated 6096 new perturbed gene sets (up and down separately). GPSAdb integrated the gene sets and developed an online tool, genetic perturbation similarity analysis (GPSA), to identify candidate causal perturbations from differential gene expression data. In summary, GPSAdb is a powerful platform that aims to assist life science researchers to easily access and analyze public perturbed data and explore differential gene expression data in depth.

Construction and validation of a prognostic nutritional index-based nomogram for predicting pathological complete response in breast cancer: a two-center study of 1,170 patients.

Background: Pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) is associated with favorable outcomes in breast cancer patients. Identifying reliable predictors for pCR can assist in selecting patients who will derive the most benefit from NAC. The prognostic nutritional index (PNI) serves as an indicator of nutritional status and systemic immune competence. It has emerged as a prognostic biomarker in several malignancies; however, its predictive value for pCR in breast cancer remains uncertain. The objective of this study is to assess the predictive value of pretreatment PNI for pCR in breast cancer patients. Methods: A total of 1170 patients who received NAC in two centers were retrospectively analyzed. The patients were divided into three cohorts: a training cohort (n=545), an internal validation cohort (n=233), and an external validation cohort (n=392). Univariate and multivariate analyses were performed to assess the predictive value of PNI and other clinicopathological factors. A stepwise logistic regression model for pCR based on the smallest Akaike information criterion was utilized to develop a nomogram. The C-index, calibration plots and decision curve analysis (DCA) were used to evaluate the discrimination, calibration and clinical value of the model. Results: Patients with a high PNI (≥53) had a significantly increased pCR rate (OR 2.217, 95% CI 1.215-4.043, p=0.009). Tumor size, clinical nodal status, histological grade, ER, Ki67 and PNI were identified as independent predictors and included in the final model. A nomogram was developed as a graphical representation of the model, which incorporated the PNI and five other factors (AIC=356.13). The nomogram demonstrated satisfactory calibration and discrimination in the training cohort (C-index: 0.816, 95% CI 0.765-0.866), the internal validation cohort (C-index: 0.780, 95% CI 0.697-0.864) and external validation cohort (C-index: 0.714, 95% CI 0.660-0.769). Furthermore, DCA indicated a clinical net benefit from the nomogram. Conclusion: The pretreatment PNI is a reliable predictor for pCR in breast cancer patients. The PNI-based nomogram is a low-cost, noninvasive tool with favorable predictive accuracy for pCR, which can assist in determining individualized treatment strategies for breast cancer patients.