ObjectiveThe subset of breast cancer patients with pathologic node-negative status (ypN0) after neoadjuvant chemotherapy (NAC) who benefit from postoperative radiotherapy (PORT) through a reduced risk of recurrence remains poorly defined. This study aimed to develop and validate an interpretable machine learning (ML) model to perform risk stratification for recurrence among ypN0 patients who all received PORT.MethodsWe conducted a retrospective analysis of 1450 breast cancer patients treated between January 2017 and January 2024. All patients received NAC, underwent radical surgery confirming ypN0 status, and subsequently received PORT. Based on follow-up outcomes after PORT, patients were classified as 'recurrence' or 'no-recurrence'. From 20 initial clinicopathological variables, feature selection was performed using LASSO regression, stepwise logistic regression, and the Boruta algorithm, retaining 16 key features identified by at least two methods. Predictive models were constructed using ten machine learning algorithms, with hyperparameters optimized via particle swarm optimization. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration curves, decision curve analysis (DCA), and standard metrics including accuracy, sensitivity, specificity, and F1-score. The optimal model was interpreted using the SHapley Additive exPlanations (SHAP) framework.ResultsThe Gradient Boosting Machine (GBM) model demonstrated superior predictive performance, achieving an AUC of 0.945 (95% CI: 0.917-0.972) on the test set. SHAP analysis identified breast reconstruction, perineural invasion, and the chemotherapy-to-surgery interval as the three most influential predictors. These features primarily exerted independent effects on recurrence risk.ConclusionWe developed and validated a highly accurate and interpretable ML model to stratify recurrence risk in ypN0 breast cancer patients after PORT. Functioning as a risk-stratification tool within this uniformly treated cohort, it may help identify patients at high risk of recurrence despite receiving PORT, who could be candidates for intensified surveillance or consideration of adjuvant therapy escalation. Its role in personalizing radiotherapy decisions requires prospective validation in studies including untreated control groups.

BACKGROUND:As the only approved oral medication for premature ejaculation (PE), dapoxetine faces a high discontinuation rate, primarily due to lower than expected efficacy. The impact of serum metabolites on PE treatment remains undetermined; therefore, we aimed to identify metabolites associated with dapoxetine efficacy. METHODS:Clinical data and blood samples were collected from 116 patients with lifelong PE before 8 weeks of dapoxetine treatment. Serum was analyzed by untargeted metabolomics profiling. Efficacy was assessed with the Clinical Global Impression of Change (CGIC) scale: scores ≥ 1 were classified as the effective group and ≤ 0 as the ineffective group. Differential serum metabolites between the two groups were identified using the Mann-Whitney U test. Enrichment analysis determined metabolic pathways significantly associated with efficacy. RESULTS:Compared to the ineffective group, indoleacrylic acid and (-)-riboflavin were significantly upregulated in the effective group, while 15-keto-13,14-dihydroprostaglandin A2, dienestrol, hippuric acid, and PC (16:0/16:0) were downregulated. The six metabolites showed a discriminatory ability of 0.646, 0.667, 0.633, 0.645, 0.651, and 0.635, respectively. Incorporating them significantly improved the accuracy of the model predicting efficacy (0.892 vs. 0.738, p = 0.001), suggesting that modulating these specific metabolites may be a novel strategy for PE treatment. Moreover, differential metabolic ions between the two groups were mostly enriched in the arachidonic acid metabolism pathway, indicating that this pathway may represent an additional route associated with dapoxetine response. CONCLUSIONS:This study revealed serum metabolites correlated with dapoxetine efficacy, paving the way for future research into novel therapeutic targets and personalized treatment strategies.

AIMS:Notable sex-based disparities exist in papillary thyroid carcinoma (PTC), necessitating male-specific models for predicting lateral lymph node metastasis (LLNM) to guide treatment. METHODS:We developed and validated two nomograms, based on central lymph node ratio (LNR) and preoperative ultrasound (US), respectively, using data from 433 male PTC patients who underwent total thyroidectomy (TT) with central and lateral neck lymph node dissection. Multivariable analysis identified key risk factors. Model performance was evaluated using ROC curves, calibration curves, and decision curve analysis (DCA) across training and validation sets. RESULTS:Male patients had 1.33-fold higher odds of central lymph node metastasis (CLNM) and 1.51-fold higher odds of LLNM than female patients (p < 0.05). Multivariable analysis identified multifocality, tumor size >20 mm, preoperative US nodal status, and an elevated LNR as independent risk factors for LLNM in males (p < 0.05). The LNR-based nomogram demonstrated superior predictive accuracy, with AUCs of 0.828 (training), 0.812 (internal validation), and 0.832 (external validation), outperforming the US-based model. Risk stratification using nomogram scores effectively categorized patients into three distinct groups with significantly different LLNM rates. CONCLUSIONS:The nomogram based on the central LNR provides a precise and clinically valuable tool for the individualized prediction of LLNM in male PTC patients.

Sensory impairments (SI), including vision (VI), hearing (HI), and dual sensory impairments (DSI), are prevalent with aging, but their impact on disease risk remains unclear. This study investigates the epidemiological and genetic associations between SIs and 10 chronic disease categories and multimorbidity. Using the CHARLS study, participants were classified by their self-reported VI/HI/DSI status in 2011 and 2013 into groups: “new onset, remission, persistent, and no SI.” Their chronic disease incidence was tracked until 2018 in sub-cohorts respectively. Mendelian randomization (MR) analyses used genetic instruments from UK Biobank GWAS data on 88,250/504,307 individuals for vision/hearing loss, with outcome datasets from consortia including FinnGen, DIAMANTE, CKDGen, PGC, GWAS Catalog, and International Parkinson’s Disease Genomics Consortium. The cohort study revealed that persistent HI significantly increased the risk of heart disease (P < 0.001, HR 1.63, 95

To establish a prognostic stratification nomogram for non-metastatic male breast cancer to determine which patients can benefit from chemotherapy. A population-based study was conducted using data collected from the surveillance, epidemiology, and end results database. Cox proportional hazards analysis identified significant prognostic factors for survival. A prognostic stratification model was developed using R software. Propensity score matching was implemented to balance characteristics between the chemotherapy cohort and the non-chemotherapy cohort. The multivariate analyses indicated that age, race, grade, surgery, primary tumor, marital status, T stage, and N stage were independent prognostic factors for overall survival in non-metastatic metastatic MBC patients who did not receive chemotherapy (all P < 0.05). The C-index was 0.786 (95% CI 0.662-0.870) in the training cohort and 0.763 (95% CI 0.517-0.852) in the validation cohort. The nomogram effectively discriminated between low-risk, moderate-risk, and high-risk groups concerning OS (P < 0.0001). The current study developed the first prognostic stratification nomogram for non-metastatic MBC and identified that patients in the moderate-risk and high-risk groups are more likely to benefit from chemotherapy.

In most cases, invasive ductal carcinoma (IDC) of the breast is identifiable when it presents with classic infiltrative growth patterns. However, a subset of IDC can present in a very sneaky way, significantly mimicking the appearance of ductal carcinoma in situ (DCIS). In this condition, it is much easier to miss the invasive component without pulling ancillary staining when morphologic findings are extremely compatible with DCIS, especially the diagnosis of DCIS was made on the previous biopsy. Here, we report the case of a 55-year-old female patient who was found to have microcalcifications at the 11:00 o'clock position in the right posterior breast during a routine mammographic examination. A biopsy of the calcification area performed at an outside hospital reported high-grade DCIS (ER+, PR-). Histologic examination of the subsequent mastectomy specimen at our institution showed two separate areas that closely resembled DCIS. Immunohistochemical (IHC) staining showed that all myoepithelial markers-smooth muscle myosin heavy chain (SMMHC), p63, CK5/6, and S100-were retained at the periphery of the expanded acini in one of the areas. Unexpectedly and surprisingly, myoepithelial markers were completely lost at the periphery of a subset of the DCIS-looking acini in another area, a finding that was immunohistochemically consistent with the diagnosis of invasive ductal carcinoma admixed with DCIS. Knowing that invasive ductal carcinoma of the breast can exhibit a DCIS-like morphology, especially in cases where a prior biopsy has already established a diagnosis of DCIS, will enhance the awareness of pathologists to recognize invasive ductal carcinoma that mimics DCIS. In turn, this will prevent misdiagnosis and undertreatment of patients with invasive ductal carcinoma of the breast.

Purpose Breast cancer (BC) is the most prevalent malignant tumor worldwide among women, with the highest incidence rate. The mechanisms underlying nucleotide metabolism on biological functions in BC remain incompletely elucidated.Materials and Methods We harnessed differentially expressed nucleotide metabolism-related genes from The Cancer Genome Atlas-BRCA, constructing a prognostic risk model through univariate Cox regression and LASSO regression analyses. A validation set and the GSE7390 dataset were used to validate the risk model. Clinical relevance, survival and prognosis, immune infiltration, functional enrichment, and drug sensitivity analyses were conducted.Results Our findings identified four signature genes (DCTPP1, IFNG, SLC27A2, and MYH3) as nucleotide metabolism-related prognostic genes. Subsequently, patients were stratified into high- and low-risk groups, revealing the risk model's independence as a prognostic factor. Nomogram calibration underscored superior prediction accuracy. Gene Set Variation Analysis (GSVA) uncovered activated pathways in low-risk cohorts and mobilized pathways in high-risk cohorts. Distinctions in immune cells were noted between risk cohorts. Subsequent experiments validated that reducing SLC27A2 expression in BC cell lines or using the SLC27A2 inhibitor, Lipofermata, effectively inhibited tumor growth.Conclusions We pinpointed four nucleotide metabolism-related prognostic genes, demonstrating promising accuracy as a risk prediction tool for patients with BC. SLC27A2 appears to be a potential therapeutic target for BC among these genes.

Background: Radiotherapy (RT) for breast cancer (BC) may raise the risk of second primary cancers (SPCs), a relationship inadequately studied. Methods: We analyzed 248268 female BC patients from 9 SEER registries, 1988-2018, identifying SPCs >5 years after initial treatment, comparing SPC risks between RT and non-RT cohorts using Fine-Gray and Poisson regressions. Results: Of all participants, 55.4 % received surgery and RT. The RT group had a higher SPC incidence, with excess incidence significantly dropped from 6.9 % in 1990 to 0.2 % in 2012. The 30-year SPC incidence was 24.69 % in the RT cohort and 18.11 % in the NRT cohort. RT increased the risk of SPCs(HR, 1.29 [95% CI,1.26-1.33]; P G 0.001), BC(HR, 1.58[1.52-1.64]; P G 0.001), cancer of respiratory system(HR, 1.21 [1.13-1.30]; P = 0.013), skin cancer(HR, 1.26[1.10-1.44]; P G 0.001), leukemia(HR, 1.30[1.11-1.54]; P = 0.001), soft tissue cancer(HR, 1.78[1.34-2.37]; P G 0.001), and eye & orbit cancer(HR, 2.21[1.02-4.80]; P = 0.044), except for reducing the risk of multiple myeloma (HR 0.76). Notably, RT-related risks(RR) for BC declined with increasing age and the year of BC diagnosed, increased with longer latency, but the dynamic RR for cancer of respiratory system presented the almost opposite trends. The RT cohort had higher standardized incidence ratios for SPCs compared to both the NRT cohort and the general population overall. Although 15-year overall survival for SPCs was similar between RT and NRT cohorts, SPC presence significantly lowered 30-year survival from 35.64 % to 23.90 %. Conclusions: RT might increase susceptibility to SPC in breast, respiratory system, skin, soft tissue, eye and orbit, and leukemia in BC survivors. Efforts should be made to timely diagnose SPCs based on their specific patterns to improve patient's quality of life.

Objective:To evaluate the role of tumor-infiltrating lymphocytes (TIL) in predicting the prognosis of HER-2 positive breast cancer patients.Methods:We retrospectively analyzed the clinicopathological data of 176 patients with HER-2 positive breast cancer treated with neoadjuvant therapy (NAT) in the First Affiliated Hospital of Air Force Medical University from January, 2013 to June 2018. According to the pathological results of surgically removed specimens after NAT, the patients were divided into pCR group (n=84) and non-pCR group (n=92).Using the TIL counting method recommended by the international TIL working group, we assessed TIL level in the area between the borders of invasive tumor and adjacent normal tissues. The overall survival (OS) and recurrence-free survival (RFS) curves were plotted using the Kaplan-Meier method and the values were compared using log-rank test. The influencing factors of OS and RFS were analyzed by Cox proportional hazards regression model. The Mann-Whitney U test was used to analyze the change of TIL level before and after NAT.Results:(1) The TIL level before NAT (pre-TIL) presented a significant difference between pCR group and non-pCR group (χ2=12.140, P<0.001). (2) Survival analysis showed that pre-TIL was related to OS and RFS (OS: χ2=14.243, P<0.001; RFS: χ2=3.881, P=0.049). Subgroup analysis showed that pre-TIL was related to OS and RFS (OS: χ2=5.272, P=0.022; RFS: χ2=6.033, P=0.014) in non-pCR patients, while TIL level after NAT (post-TIL) was not related to OS and RFS (OS: χ2=0.174, P=0.677; χ2=0.074, P=0.786). The pre-TIL was significantly lower than post-TIL in 92 non-pCR patients [6.0% (5.0%, 25.0%) vs 30.0% (11.3%, 63.8%), Z=-5.474, P<0.001]. The change of TIL level before and after NAT in non-pCR was not significantly related to OS and RFS (OS: χ2=2.342, P=0.126; RFS: χ2=3.853, P=0.051). (3) The Cox univariate analysis showed that the patients with lower pre-TIL had lower OS (HR=2.556, 95%CI: 1.458-4.482, P=0.001), but pre-TIL was not related to RFS (HR=1.362, 95%CI: 0.996-1.862, P=0.053); multivariate analysis showed that pre-TIL was an independent factor of OS (HR=2.556, 95%CI: 1.458-4.482, P=0.001). Among the patients with non-pCR, the patients with low pre-TIL had lower OS (HR=1.878, 95%CI: 1.058-3.333, P=0.031) and RFS (HR=1.670, 95%CI: 1.090-2.559, P=0.019). Post-TIL was not significantly related to OS (HR=1.534, 95%CI: 0.202-11.673, P=0.679) and RFS (HR=0.905, 95%CI: 0.438-1.866, P=0.786) in patients with non-pCR. The change of TIL level before and after NAT was not an independent factor of OS(HR=3.020, 95%CI: 0.681-13.396, P=0.146) and RFS (HR=3.152, 95%CI: 0.939-10.576, P=0.063).Conclusion:Pre-TIL is a potential prognostic factor for HER-2 positive early breast cancer, and the predictive value of TIL change before and after NAT in non-pCR patients is worth of further exploration.

BackgroundAs an emerging treatment strategy for triple-negative breast cancer (TNBC), immunotherapy acts in part by inducing ferroptosis. Recent studies have shown that protein arginine methyltransferase 5 (PRMT5) has distinct roles in immunotherapy among multiple cancers by modulating the tumor microenvironment. However, the role of PRMT5 during ferroptosis, especially for TNBC immunotherapy, is unclear.MethodsPRMT5 expression in TNBC was measured by IHC (immunohistochemistry) staining. To explore the function of PRMT5 in ferroptosis inducers and immunotherapy, functional experiments were conducted. A panel of biochemical assays was used to discover potential mechanisms.ResultsPRMT5 promoted ferroptosis resistance in TNBC but impaired ferroptosis resistance in non-TNBC. Mechanistically, PRMT5 selectively methylated KEAP1 and thereby downregulated NRF2 and its downstream targets which can be divided into two groups: pro-ferroptosis and anti-ferroptosis. We found that the cellular ferrous level might be a critical factor in determining cell fate as NRF2 changes. In the context of higher ferrous concentrations in TNBC cells, PRMT5 inhibited the NRF2/HMOX1 pathway and slowed the import of ferrous. In addition, a high PRMT5 protein level indicated strong resistance of TNBC to immunotherapy, and PRMT5 inhibitors potentiated the therapeutic efficacy of immunotherapy.ConclusionsOur results reveal that the activation of PRMT5 can modulate iron metabolism and drive resistance to ferroptosis inducers and immunotherapy. Accordingly, PRMT5 can be used as a target to change the immune resistance of TNBC.

Background and purpose:With the acceleration of the aging process of society, stroke has become a major health problem in the middle-aged and elderly population. A number of new stroke risk factors have been recently found. It is necessary to develop a predictive risk stratification tool using multidimensional risk factors to identify people at high risk for stroke.Methods:The study included 5,844 people (age ≥ 45 years) who participated in the China Health and Retirement Longitudinal Study in 2011 and its follow-up up to 2018. The population samples were divided into training set and validation set according to 1:1. A LASSO Cox screening was performed to identify the predictors of new-onset stroke. A nomogram was developed, and the population was stratified according to the score calculated through the X-tile program. Internal and external verifications of the nomogram were performed by ROC and calibration curves, and the Kaplan-Meier method was applied to identify the performance of the risk stratification system.Results:The LASSO Cox regression screened out 13 candidate predictors from 50 risk factors. Finally, nine predictors, including low physical performance and the triglyceride-glucose index, were included in the nomogram. The nomogram's overall performance was good in both internal and external validations (AUCs at 3-, 5-, and 7-year periods were 0.71, 0.71, and 0.71 in the training set and 0.67, 0.65, and 0.66 in the validation set, respectively). The nomogram was proven to excellently discriminate between the low-, moderate-, and high-risk groups, with a prevalence of 7-year new-onset stroke of 3.36, 8.32, and 20.13%, respectively (P < 0.001).Conclusion:This research developed a clinical predictive risk stratification tool that can effectively identify the different risks of new-onset stroke in 7 years in the middle-aged and elderly Chinese population.

Purpose:We aimed at establishing a nomogram to accurately predict the overall survival (OS) of non-metastatic invasive micropapillary breast carcinoma (IMPC).Methods:In the training cohort, data from 429 patients with non-metastatic IMPC were obtained through the Surveillance, Epidemiology, and End Results (SEER) database. Other 102 patients were enrolled at the Xijing Hospital as validation cohort. Independent risk factors affecting OS were ascertained using univariate and multivariate Cox regression. A nomogram was established to predict OS at 3, 5 and 8 years. The concordance index (C-index), the area under a receiver operating characteristic (ROC) curve and calibration curves were utilized to assess calibration, discrimination and predictive accuracy. Finally, the nomogram was utilized to stratify the risk. The OS between groups was compared through Kaplan-Meier survival curves.Results:The multivariate analyses revealed that race (p = 0.047), surgery (p = 0.003), positive lymph nodes (p = 0.027), T stage (p = 0.045) and estrogen receptors (p = 0.019) were independent prognostic risk factors. The C-index was 0.766 (95% CI, 0.682-0.850) in the training cohort and 0.694 (95% CI, 0.527-0.861) in the validation cohort. Furthermore, the predicted OS was consistent with actual observation. The AUCs for OS at 3, 5 and 8 years were 0.786 (95% CI: 0.656-0.916), 0.791 (95% CI: 0.669-0.912), and 0.774 (95% CI: 0.688-0.860) in the training cohort, respectively. The area under the curves (AUCs) for OS at 3, 5 and 8 years were 0.653 (95% CI: 0.498-0.808), 0.683 (95% CI: 0.546-0.820), and 0.716 (95% CI: 0.595-0.836) in the validation cohort, respectively. The Kaplan-Meier survival curves revealed a significant different OS between groups in both cohorts (p<0.001).Conclusion:Our novel prognostic nomogram for non-metastatic IMPC patients achieved a good level of accuracy in both cohorts and could be used to optimize the treatment based on the individual risk factors.

Patient Health Questionnaire-9 (PHQ-9) is the most widely used tool for screening for major depressive disorder (MDD). Although its reliability and validity have been proven, missed or misjudged cases during MDD screening are often encountered. A nomogram that considers the weights of depressive symptoms was developed using data from premature ejaculation patients to improve screening accuracy. During a 33-month prospective study, a training cohort comprising 605 participants from Xijing Hospital was used to develop and internally validate the nomogram. A validation cohort comprising 461 patients from Xi'an Daxing Hospital was also used to externally test the nomogram. The nomogram was established by integrating the LASSO regression-based optimal predictors of MDD according to their coefficients in a multivariate logistic regression model. The nomogram was well-calibrated during internal and external validations. Moreover, it showed a better discriminatory capacity and yielded more net benefits in both validations than PHQ-9. With better performance, the nomogram may help reduce the number of missed or misjudged cases during MDD screening. This study is the first to weigh the direct indicators of MDD under the DSM-5 criteria, presenting a fresh concept that can be applied to other populations to enhance screening accuracy.

Background: Few longitude cohort studies investigated the risk of the duration of nighttime sleep and naps to the new-onset common chronic disease conditions (CDCs) in middle-aged (45-60) and the elderly (age >= 60) populations using an age-stratified strategy. Methods: The 7025 participants from The China Health and Retirement Longitudinal Study were screened as eligible subjects. Established 13 cohorts with CDCs, acquired their' sleep records in 2011, and obtained new onset incidents of CDCs during follow-up in 2011-2018. Performed risk association analyses between sleep duration and 13 new-onset CDCs respectively.Results: New-onset risk of four CDCs decreased with increasing nighttime sleep (p-nonlinear>0.05). The risk threshold was approximately 7 hours in middle-aged people and 6 hours in the elderly. For the middle-aged population, compared with 7-9hours sleep, <5hour and 5-7hours nighttime sleep were associated with 1.312-1.675 times more risk of hypertension, kidney disease, diabetes or high blood sugar status, and multimorbidity; Compared with no nap, a 0-30 min nap was associated with 1.413(1.087-1.837) times the heart disease risk. In the elderly, < 5 hours of night sleep was a significant risk factor for four CDCs including kidney disease and multimorbidity, etc. A long night's sleep (>9 hours) was connected with 61.2% reduction in risk of memory disease, a >90 min nap increased 62% risk of memory disease, and a 0-30 min nap was associated with higher risks of heart disease, hypertension, and a lower kidney disease risk.Conclusions: Nighttime sleep and daytime naps may have their own implications for the new-onset CDCs' risk in the aging process.

Background:Although erectile dysfunction (ED) often occurs simultaneously with depression, not all patients with ED suffer major depression (MD), with a PHQ-9 score ≥15 indicating MD. Because the PHQ-9 questionnaire includes phrases such as "I think I am a loser" and "I want to commit suicide," the psychological burdens of ED patients are likely to increase inevitably after using the PHQ-9, which, in turn, may affect ED therapeutic effects. Accordingly, we endeavored to develop a nomogram to predict individual risk of PHQ-9 score ≥15 in these patients.Methods:The data of 1,142 patients with ED diagnosed in Xijing Hospital and Northwest Women and Children's Hospital from January 2017 to May 2020 were analyzed. While the Least Absolute Shrinkage and Selection Operator regression was employed to screen PHQ-9 score ≥15 related risk factors, multivariate logistic regression analysis was performed to verify these factors and construct the nomogram. The training cohort and an independent cohort that comprised 877 prospectively enrolled patients were used to demonstrate the efficacy of the nomogram.Results:The IIEF-5 score, PEDT score, physical pain score, frequent urination, and feeling of endless urination were found to be independent factors of PHQ-9 score ≥15 in patients with ED. The nomogram developed by these five factors showed good calibration and discrimination in internal and external validation, with a predictive accuracy of 0.757 and 0.722, respectively. The sensitivity and specificity of the nomogram in the training cohort were 0.86 and 0.52, respectively. Besides, the sensitivity and specificity of the nomogram in the validation cohort were 0.73 and 0.62, respectively. Moreover, based on the nomogram, the sample was divided into low-risk and high-risk groups.Conclusion:This study established a nomogram to predict individual risk of PHQ-9 score ≥15 in patients with ED. It is deemed that the nomogram may be employed initially to avoid those with a low risk of MD completing questionnaires unnecessarily.

Objective:To analyze the risk factors of recurrence and metastasis in female patients with hormone receptor(HR)-positive/HER-2-negative T1-3N0M0 invasive breast cancer.Methods:The clinicopathological data of 1 064 patients with HR-positive/HER-2-negative T1-3N0M0 invasive breast cancer in the Xijing Hospital of Air Force Medical University from January 1, 2008 to December 31, 2017 were retrospectively analyzed. Kaplan-Meier method was used to make survival analysis. The Cox proportional risk regression model was used to explore independent prognostic factors for recurrence and metastasis. Receiver operating characteristic (ROC) curve was drawn and area under the curve (AUC) was calculated to assess the accuracy of independent factors in predicting the recurrence-free survival.Results:The 5-year and 10-year recurrence-free survival in these patients were 93.90% (95%CI: 92.30%-95.40%) and 87.10% (95%CI: 84.00%-90.20%), respectively. Univariate Cox proportional risk regression analysis showed that endocrine therapy, maximum diameter of the tumor and Ki-67 expression were affecting factors for recurrence and metastasis (HR=5.39, 95%CI: 3.25-8.94, P<0.001; HR=1.28, 95%CI: 1.11-1.48, P=0.001; HR=1.92, 95%CI: 1.24-2.96, P=0.003). Multivariate Cox proportional risk regression analysis showed that endocrine therapy, maximum diameter of the tumor and Ki-67 expression were independent prognostic factors of recurrence and metastasis (HR=4.76, 95%CI: 2.83-8.02, P<0.001; HR=1.17, 95%CI: 1.01-1.37, P=0.043; HR=1.79, 95%CI: 1.16-2.76, P=0.009). The risk of postoperative recurrence and metastasis in patients who did not receive endocrine therapy was 4.76 times as high as that in patients with endocrine therapy; the risk of postoperative recurrence and metastasis in patients with Ki-67 level >20% was 1.79 times as high as that in patients with Ki-67 level ≤20%. The AUC indicated that the above-mentioned three variables had high accuracy in predicting postoperative recurrence-free survival in HR-positive/HER-2-negative T1-3N0M0 invasive breast cancer. The 3-year, 5-year, and 10-year AUC was 0.73 (95%CI: 0.67-0.80, P<0.001), 0.72 (95%CI: 0.66-0.78, P<0.001), 0.68 (95%CI: 0.62-0.75, P<0.001), respectively.Conclusion:In patients with HR-positive/ HER-2-negative T1-3N0M0 invasivebreast cancer, the combination of these three factors (endocrine therapy, maximum diameter of the tumor and Ki-67 expression)can predict postoperative recurrence-free survival and provide guidance for individualized treatment.

Abstract Background and Purpose: With the aging of society, stroke has become a vital health problem for the middle-aged and elderly. Amounts of stroke's new risk factors have been found recently. It is necessary to develop a predictive risk stratification tool containing multi-dimensional risk factors for identifying high-risk people.Methods: The study included 5844 people (Age≥45) who participated in the China Health and Retirement Longitudinal Study, in 2011 and follow-up to 2018. Randomly divided the population into training and validation set by 1:1. Lasso Cox screened predictors for new-onset stroke. Developed a nomogram and stratified the population according to the score calculated in the nomogram through the X-tile program. Internal and external verification of nomogram was performed by ROC and calibration curves, and the Kaplan-Meier method was applied to identify the performance of the risk stratification system.Results: Lasso COX regression screened out 13 candidate predictors from 50 risk factors. Finally, nine predictors, including low physical performance, triglyceride-glucose index, etc., were included in the nomogram. The nomogram's overall performance was good in both internal and external validation (AUCs of three-year, five-year, seven-year in the training set was 0.71, 0.71, 0.71, and 0.67, 0.65, 0.66 in the validation set, respectively). The nomogram was proven to could excellently discriminate between low-, moderate-, and high-risk groups with the 7-year new-onset stroke of 3.36%, 8.32%, and 20.13%, respectively (P<0.001).Conclusions: This research developed a clinical predictive risk stratification tool that can effectively identify the different risks of new-onset stroke incidents in 7-years in the middle-aged and elderly Chinese.

Cancer cells respond to various stressful conditions through the dynamic regulation of RNA m6A modification. Doxorubicin is a widely used chemotherapeutic drug that induces DNA damage. It is interesting to know whether cancer cells regulate the DNA damage response and doxorubicin sensitivity through RNA m6A modification. Here, we found that doxorubicin treatment significantly induced RNA m6A methylation in breast cancer cells in both a dose- and a time-dependent manner. However, protein arginine methyltransferase 5 (PRMT5) inhibited RNA m6A modification under doxorubicin treatment by enhancing the nuclear translocation of the RNA demethylase AlkB homolog 5 (ALKBH5), which was previously believed to be exclusively localized in the nucleus. Then, ALKBH5 removed the m6A methylation of BRCA1 for mRNA stabilization and further enhanced DNA repair competency to decrease doxorubicin efficacy in breast cancer cells. Importantly, we identified the approved drug tadalafil as a novel PRMT5 inhibitor that could decrease RNA m6A methylation and increase doxorubicin sensitivity in breast cancer. The strategy of targeting PRMT5 with tadalafil is a promising approach to promote breast cancer sensitivity to doxorubicin through RNA methylation regulation.

In the tumor microenvironment, tumor-infiltrating immune cells (TIICs) are a key component. Different types of TIICs play distinct roles. CD8+ T cells and natural killer (NK) cells could secrete soluble factors to hinder tumor cell growth, whereas regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs) release inhibitory factors to promote tumor growth and progression. In the meantime, a growing body of evidence illustrates that the balance between pro- and anti-tumor responses of TIICs is associated with the prognosis in the tumor microenvironment. Therefore, in order to boost anti-tumor response and improve the clinical outcome of tumor patients, a variety of anti-tumor strategies for targeting TIICs based on their respective functions have been developed and obtained good treatment benefits, including mainly immune checkpoint blockade (ICB), adoptive cell therapies (ACT), chimeric antigen receptor (CAR) T cells, and various monoclonal antibodies. In recent years, the tumor-specific features of immune cells are further investigated by various methods, such as using single-cell RNA sequencing (scRNA-seq), and the results indicate that these cells have diverse phenotypes in different types of tumors and emerge inconsistent therapeutic responses. Hence, we concluded the recent advances in tumor-infiltrating immune cells, including functions, prognostic values, and various immunotherapy strategies for each immune cell in different tumors.