To compare diffusion-kurtosis imaging (DKI) and diffusion-weighted imaging (DWI) parameters of single-shot echo-planar imaging (ss-EPI) and readout-segmented echo-planar imaging (rs-EPI) in the differentiation of luminal vs. non-luminal breast cancer using histogram analysis. One hundred and sixty women with 111 luminal and 49 non-luminal breast lesions were enrolled in this study. All patients underwent ss-EPI and rs-EPI sequences on a 3.0T scanner. Histogram metrics were derived from mean kurtosis (MK), mean diffusion (MD) and the apparent diffusion coefficient (ADC) maps of two DWI sequences respectively. Student\'s t test or Mann-Whitney U test was performed for differentiating luminal subtype from non-luminal subtype. The ROC curves were plotted for evaluating the diagnostic performances of significant histogram metrics in differentiating luminal from non-luminal BC. The histogram metrics MKmean, MK50th, MK75th of luminal BC were significantly higher than those of non-luminal BC for both two DWI sequences (all P<0.05). Histogram metrics from rs-EPI sequence had better diagnostic performance in differentiating luminal from non-Luminal breast cancer compared to those from ss-EPI sequence. MK75th derived from rs-EPI sequence was the most valuable single metric (AUC, 0.891; sensitivity, 78.4%; specificity, 87.8%) for differentiating luminal from non-luminal BC among all the histogram metrics. Histogram metrics of MK derived from rs-EPI yielded better diagnostic performance for distinguishing luminal from non-luminal BC than that from ss-EPI. MK75th was the most valuable metric among all the histogram metrics.

UNASSIGNED: Breast cancer is a heterogeneous disease with different morphological and biological characteristics. The molecular subtypes of breast cancer are closely related to the treatment and prognosis of patients. In order to predict the luminal type of breast cancer in a noninvasive manner, our study developed and validated a radiomics nomogram combining clinical factors with a radiomics score based on the features of the intratumoral subregion to distinguish between luminal and nonluminal breast cancer.
UNASSIGNED: From January 2018 to January 2020, 153 women with clinically and pathologically diagnosed breast cancer with an average age of 50.08 years were retrospectively analyzed. Using a semiautomatic segmentation method, the whole tumor was divided into 3 subregions on the basis of the time required for the contrast agent to reach its peak; 540 features were extracted from 3 subregions and the whole tumor region. Subsequently, 2 machine learning classifiers were developed. The least absolute shrinkage and selection operator method was used for feature selection and radiomics score (Rad-score) construction. Moreover, multivariable logistic regression analysis was applied to select independent factors from the Rad-score and clinical factors to establish a prediction model in the form of a nomogram. The performance of the nomogram was evaluated through calibration, discrimination, and clinical usefulness.
UNASSIGNED: The prediction performance of texture features from the rapid subregion was the best in the 3 intratumoral subregions, and the area under the receiver operating characteristic curve (AUC) values in the training and validation cohort were 0.805 (95% CI: 0.719-0.892) and 0.737 (95% CI: 0.581-0.893), respectively. The Rad-score, consisting of 5 features from the rapid subregion, was associated with the luminal type of breast cancer (P=0.001 and P=0.035 in the training and validation cohorts, respectively). The predictors included in the personalized prediction nomogram included Rad-score, human epidermal growth factor receptor 2 (HER2) status, and tumor histological grade. The nomogram showed good discrimination, with an area under the receiver operating characteristic curve in the training and validation cohorts of 0.830 (95% CI: 0.746-0.896) and 0.879 (95% CI: 0.748-0.957), respectively. The calibration curve of the 2 cohorts and decision curve analysis demonstrated that the nomogram had good calibration and clinical usefulness.
UNASSIGNED: We proposed a nomogram model that combined clinical factors and Rad-score, which showed good performance in predicting the luminal type of breast cancer.

BACKGROUND: Microcystic urothelial carcinoma (MUC) is a rare variant of urothelial carcinoma with histological appearances similar to begin lesions. Thus far, approximately 50 cases have been reported. Here, we investigated the clinicopathological features of MUC.
METHODS: Clinical data and paraffin-embedded tissue blocks were collected. Immunohistochemical staining and polymerase chain reaction-Sanger sequencing were performed to detect the phenotype and TERT mutation status of MUC, respectively.
RESULTS: The mean patient age was 58.8 ± 14.5 years, with a male predominance (8:2). The pathological stage was T1 in one case, T2 in three cases, T3 in four cases, and T4 in two cases. Tumor metastases or death occurred in all five patients who were followed up within 1-3 years. Histological analyses revealed microcystic, tubular, cribriform, and occasionally cord-like structures, which generally lacked interstitial reactions. The lumens were empty, contained eosinophilic secretion, or were filled with mucin. The microcysts/tubules/cribriform patterns were lined by flat, cuboid, signet ring, or columnar types of epithelia. The cuboid, signet ring, and columnar types represented \"glandular metaplasia\" or glandular differentiation of urothelial carcinoma. Immunohistochemistry analyses revealed distinct co-expression patterns involving the luminal markers FOXA1 and GATA3, as well as the basal markers CK5/6 and CD44. All 10 cases exhibited a luminal phenotype according to the GATA3+/CK14- criterion, whereas nine cases exhibited a luminal phenotype according to the FOXA1+/CK14- criterion. The telomerase reverse transcriptase-C228T mutation was detected in seven cases.
CONCLUSIONS: MUC is a rare variant with a deceptively benign form of urothelial carcinoma, which is generally identified as a late-stage tumor with a poor prognosis. It exhibits distinct co-expression of luminal and basal markers, along with the TERT-C228T mutation.

UNASSIGNED: The goal of this study was to develop and validate a radiomics signature based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) preoperatively differentiating luminal and non-luminal molecular subtypes in patients with invasive breast cancer.
UNASSIGNED: One hundred and thirty-five invasive breast cancer patients with luminal (n = 78) and non-luminal (n = 57) molecular subtypes were divided into training set (n = 95) and testing set (n = 40) in a 7:3 ratio. Demographics and MRI radiological features were used to construct clinical risk factors. Radiomics signature was constructed by extracting radiomics features from the second phase of DCE-MRI images and radiomics score (rad-score) was calculated. Finally, the prediction performance was evaluated in terms of calibration, discrimination, and clinical usefulness.
UNASSIGNED: Multivariate logistic regression analysis showed that no clinical risk factors were independent predictors of luminal and non-luminal molecular subtypes in invasive breast cancer patients. Meanwhile, the radiomics signature showed good discrimination in the training set (AUC, 0.86; 95% CI, 0.78-0.93) and the testing set (AUC, 0.80; 95% CI, 0.65-0.95).
UNASSIGNED: The DCE-MRI radiomics signature is a promising tool to discrimination luminal and non-luminal molecular subtypes in invasive breast cancer patients preoperatively and noninvasively.

Both the canonical Wnt and androgen receptor (AR) signaling pathways are important for prostate organogenesis and homeostasis. How they crosstalk to regulate prostate stem cell behaviors remains unclear. Here, we show in lineage-tracing mouse models that although Wnt is essential for basal stem cell multipotency, ectopic Wnt activity promotes basal cell over-proliferation and squamous phenotypes, which are counteracted by elevated levels of androgen. In prostate basal cell organoids, dihydrotestosterone (DHT) antagonizes R-spondin-stimulated growth in a concentration-dependent manner. DHT down-regulates the expressions of a Wnt reporter and target genes, and RNA sequencing (RNA-seq) analyses identify Wnt signaling as a key altered pathway. Mechanistically, DHT enhances AR and β-catenin protein binding, and CUT&RUN analyses reveal that ectopic AR sequesters β-catenin away from its Wnt-related cistrome. Our results suggest that an intermediate level of Wnt activity in prostate basal stem cells, achieved via AR-β-catenin interaction, is essential for normal prostate homeostasis.

OBJECTIVE: CD58 is an immune adhesion molecule on the cellular surface. It was previously found that a high expression of CD58 predicted a poor prognosis of patients with lower-grade gliomas. Therefore, the aim of this paper was to investigate the association between CD58 and breast cancer.
METHODS: CD58 gene expression data downloaded from cBioPortal was compared between the different subtypes of breast cancer. Clinical prognosis was examined using Kaplan-Meier analysis and multivariable Cox regression analysis. The association between CD58 expression and immune cell infiltration was estimated using the TIMER 2.0 web platform. Finally, the tumour sphere formation of aldehyde dehydrogenase 1 (ALDH1)high basal-like breast cancer stem cells in which CD58 was knocked down using siRNA was measured.
RESULTS: CD58 mRNA was mainly enriched in claudin-low and basal-like subtypes. The high expression of CD58 predicted a good prognosis in patients with luminal A and luminal B breast cancer. This prediction may be due to the association of immune cell infiltration with CD58. Notably, patients with luminal A breast cancer with a high expression of CD58 in association with ALDH1A3 exhibited a good prognosis; however, this did not apply to patients with basal-like breast cancer. The in vitro experiments revealed that knockdown of CD58 inhibited the tumour sphere formation ability of ALDH1high basal-like cancer cells.
CONCLUSIONS: CD58 may function as a potential prognostic biomarker and therapeutic target in ALDH-positive basal-like cancer stem cells.

UNASSIGNED: The molecular subtype plays an important role in breast cancer, which is the main reference to guide treatment and is closely related to prognosis. The objective of this study was to explore the potential of the non-contrast-enhanced chest CT-based radiomics to predict breast cancer molecular subtypes non-invasively.
UNASSIGNED: A total of 300 breast cancer patients (153 luminal types and 147 non-luminal types) who underwent routine chest CT examination were included in the study, of which 220 cases belonged to the training set and 80 cases to the time-independent test set. Identification of the molecular subtypes is based on immunohistochemical staining of postoperative tissue samples. The region of interest (ROI) of breast masses was delineated on the continuous slices of CT images. Forty-two models to predict the luminal type of breast cancer were established by the combination of six feature screening methods and seven machine learning classifiers; 5-fold cross-validation (cv) was used for internal validation. Finally, the optimal model was selected for external validation on the independent test set. In addition, we also took advantage of SHapley Additive exPlanations (SHAP) values to make explanations of the machine learning model.
UNASSIGNED: During internal validation, the area under the curve (AUC) values for different models ranged from 0.599 to 0.842, and the accuracy ranged from 0.540 to 0.775. Eventually, the LASSO_SVM combination was selected as the final model, which included 9 radiomics features. The AUC, accuracy, sensitivity, and specificity of the model to distinguish luminal from the non-luminal type were 0.842 [95% CI: 0.728-0.957], 0.773, 0.818, and 0.773 in the training set and 0.757 [95% CI: 0.640-0.866], 0.713, 0.767, and 0.676 in the test set.
UNASSIGNED: The radiomics based on chest CT may provide a new idea for the identification of breast cancer molecular subtypes.

UNASSIGNED: Luminal mucus plugging in small airways is associated with lung function decline and death of patients with chronic obstructive pulmonary disease (COPD). However, little attention has been paid to the possible role of mucus in large airways in acute exacerbation of COPD (AECOPD). Therefore, this study aimed to explore the relationship between the luminal mucus score of large airways and other physiological parameters of severe AECOPD.
UNASSIGNED: A total of 74 AECOPD inpatients were enrolled in this cross-sectional study. All patients underwent lung function tests and bronchoscopy, and their luminal mucus was observed and scored through bronchoscopy. Four questionnaires, including the St. George Respiratory Questionnaire (SGRQ), modified Medical Research Council dyspnea scale (mMRC), COPD Assessment Test (CAT) and Exacerbation of Chronic pulmonary disease Tool (EXACT), were used to assess health-related quality of life (HRQoL).
UNASSIGNED: The luminal mucus score of large airways was significantly correlated with spirometry parameters and HRQoL score. Both mMRC grade and SGRQ score were significantly positively correlated with luminal mucus score (ρ=0.527, P<0.001; ρ=0.441, P<0.001, respectively). Forced expiratory flow at 25% to 75% of the FVC (FEF25%-75%) and FEV1% predicted, as functional measures reflecting small airway disease, were significantly negatively correlated with luminal mucus score (ρ=-0.518, P<0.001; ρ=-0.498, P<0.001, respectively). The stepwise multiple linear regression model suggested that mMRC grade and FEV1% predicted could predict luminal mucus score (R 2=0.348, F=18.960, P<0.001).
UNASSIGNED: For severe acute exacerbation of COPD, bronchoscopy-identified luminal mucus in large airways is associated with reduced lung function and worse health-related quality of life.

The present study aimed to investigate the value of liver fructose 1,6-bisphophatase (FBP1) and hypoxia-inducible factor-1α (HIF-1α) in the molecular subtyping of breast carcinoma. Tissue obtained from 60 surgical specimens from patients with breast carcinoma underwent immunohistochemical staining for cytokeratin 5/6, HIF-1α and FBP1. The variation in the expression levels of these markers and clinicopathological factors were compared between molecular subtypes. In addition, disease-free survival was compared between basal-like and luminal breast carcinoma, according to differing expression levels of HIF-1α and FBP1. The results revealed that HIF-1α expression was detectable in 20/60 (33.3%) of the breast carcinoma cases, and was positively associated with lymph node metastasis (P=0.007). HIF-1α-positive patients exhibited a shorter disease-free survival, compared with HIF-1α-negative patients with invasive breast cancer. The expression levels of FBP1 were positive in 33/60 tumor tissues (55%; P<0.001), and FBP1 expression was associated with nuclear grade (P=0.017) and tumor stage (P=0.012). In breast carcinoma, HIF-1α expression levels were significantly negatively correlated with FBP1 levels (r=-0.711; P<0.001). Cox regression analysis identified FBP1 and tumor size as independent prognostic factors. Therefore, the present study demonstrated that patients with basal-like breast carcinoma exhibited lower levels of FBP1 expression in tumor tissues, compared with patients with luminal type breast cancer, and that low or absent expression levels of FBP1 may be associated with reduced disease-free survival.

In this study, C57BL/6J mice were fed diets supplemented with different proportions of lactulose (0%, 5%, and 15%) for 2 weeks to study its effects on the luminal and mucosal microbiota. The luminal and mucosal samples of cecum and colon were investigated. After high-lactulose treatment (15%), pH of the luminal contents decreased from 6.90-7.72 to 5.95-6.21 from the cecum to distal colon, and the amount of total short-chain fatty acids in the cecum was significantly increased. The luminal content was mostly dominated by Firmicutes, Actinobacteria, and Bacteroidetes, while the mucus was dominated by Firmicutes, Proteobacteria, and Bacteroidetes. The abundance of Actinobacteria was significantly increased in the content, and Proteobacteria was the most abundant phylum (∼50%) in the mucus after high-lactulose treatment. At the genus level, Bifidobacterium and Akkermansia were both significantly increased in the content, and Helicobacter was the most abundant in the mucus.