Clinical utility of office hysteroscopy following failed in vitro fertilization-embryo transfer: A retrospective cohort study.

OBJECTIVE: Despite its widespread use, in vitro fertilization (IVF) outcomes are challenged by implantation failure, largely due to factors such as embryo quality and endometrial receptivity. In this study, we investigated the clinical effect of office hysteroscopy (OH) on the subsequent frozen-thawed embryo transfer (FET) in infertile women who experienced a failed IVF-embryo transfer (IVF-ET) cycle. METHODS: We included 577 infertile women who underwent OH because of a history of failed ET between October 2019 and September 2021. During OH, visible endometrial polyps (EPs) were diagnosed and removed by curette or biopsy forceps; chronic endometritis (CE) was diagnosed by histopathology and immunohistochemistry and treated with oral doxycycline (0.2 g/d) for 14 days. According to the hysteroscopic findings and endometrial pathology with immunohistochemistry, patients were divided into three groups: group A (n = 161) had CE with or without EPs, group B (n = 156) had EPs only, and group C (n = 260) had no CE or EPs. RESULTS: In the following FET cycle, the implantation rates were 47%, 51%, and 45% (P = 0.411); the clinical pregnancy rates were 56%, 62%, and 55% (P = 0.436); the live birth rates were 45%, 51%, and 42% (P = 0.205); and the miscarriage rates were 18%, 16%, and 22% (P = 0.497) in groups A, B, and C, respectively. There were no significant differences among groups (P > 0.05). CONCLUSION: OH is helpful for diagnosis and treatment of abnormal intrauterine environment in women with a failed IVF cycle and further improves their pregnancy outcome in the following FET.

Elucidation of clinical implications Arising from circadian rhythm and insights into the tumor immune landscape in breast cancer.

Background: Circadian rhythm is an internal timing system generated by circadian-related genes (CRGs). Disruption in this rhythm has been associated with a heightened risk of breast cancer (BC) and regulation of the immune microenvironment of tumors. This study aimed to investigate the clinical significance of CRGs in BC and the immune microenvironment. Methods: CRGs were identified using the GeneCards and MSigDB databases. Through unsupervised clustering, we identified two circadian-related subtypes in patients with BC. We constructed a prognostic model and nomogram for circadian-related risk scores using LASSO and Cox regression analyses. Using multi-omics analysis, the mutation profile and immunological microenvironment of tumors were investigated, and the immunotherapy response in different groups of patients was predicted based on their risk strata. Results: The two circadian-related subtypes of BC that were identified differed significantly in their prognoses, clinical characteristics, and tumor immune microenvironments. Subsequently, we constructed a circadian-related risk score (CRRS) model containing eight signatures (SIAH2, EZR, GSN, TAGLN2, PRDX1, MCM4, EIF4EBP1, and CD248) and a nomogram. High-risk individuals had a greater burden of tumor mutations, richer immune cell infiltration, and higher expression of immune checkpoint genes, than low-risk individuals, indicating a "hot tumor" immune phenotype and a more favorable treatment outcome. Conclusions: Two circadian-related subtypes of BC were identified and used to establish a CRRS prognostic model and nomogram. These will be valuable in providing guidance for forecasting prognosis and developing personalized treatment plans for BC.

The artificial intelligence-based model ANORAK improves histopathological grading of lung adenocarcinoma.

The introduction of the International Association for the Study of Lung Cancer grading system has furthered interest in histopathological grading for risk stratification in lung adenocarcinoma. Complex morphology and high intratumoral heterogeneity present challenges to pathologists, prompting the development of artificial intelligence (AI) methods. Here we developed ANORAK (pyrAmid pooliNg crOss stReam Attention networK), encoding multiresolution inputs with an attention mechanism, to delineate growth patterns from hematoxylin and eosin-stained slides. In 1,372 lung adenocarcinomas across four independent cohorts, AI-based grading was prognostic of disease-free survival, and further assisted pathologists by consistently improving prognostication in stage I tumors. Tumors with discrepant patterns between AI and pathologists had notably higher intratumoral heterogeneity. Furthermore, ANORAK facilitates the morphological and spatial assessment of the acinar pattern, capturing acinus variations with pattern transition. Collectively, our AI method enabled the precision quantification and morphology investigation of growth patterns, reflecting intratumoral histological transitions in lung adenocarcinoma.

Susceptibility of acute myeloid leukemia cells to ferroptosis and evasion strategies.

Acute myeloid leukemia (AML) is a highly aggressive hematologic malignancy with a 5-year survival rate of less than 30%. Continuous updating of diagnostic and therapeutic strategies has not been effective in improving the clinical benefit of AML. AML cells are prone to iron metabolism imbalance due to their unique pathological characteristics, and ferroptosis is a novel cell death mode that is dominated by three cellular biological processes: iron metabolism, oxidative stress and lipid metabolism. An in-depth exploration of the unique ferroptosis mechanism in AML can provide new insights for the diagnosis and treatment of this disease. This study summarizes recent studies on ferroptosis in AML cells and suggests that the metabolic characteristics, gene mutation patterns, and dependence on mitochondria of AML cells greatly increase their susceptibility to ferroptosis. In addition, this study suggests that AML cells can establish a variety of strategies to evade ferroptosis to maintain their survival during the process of occurrence and development, and summarizes the related drugs targeting ferroptosis pathway in AML treatment, which provides development directions for the subsequent mechanism research and clinical treatment of AML.

Self-supervised deep learning for highly efficient spatial immunophenotyping.

BACKGROUND: Efficient biomarker discovery and clinical translation depend on the fast and accurate analytical output from crucial technologies such as multiplex imaging. However, reliable cell classification often requires extensive annotations. Label-efficient strategies are urgently needed to reveal diverse cell distribution and spatial interactions in large-scale multiplex datasets. METHODS: This study proposed Self-supervised Learning for Antigen Detection (SANDI) for accurate cell phenotyping while mitigating the annotation burden. The model first learns intrinsic pairwise similarities in unlabelled cell images, followed by a classification step to map learnt features to cell labels using a small set of annotated references. We acquired four multiplex immunohistochemistry datasets and one imaging mass cytometry dataset, comprising 2825 to 15,258 single-cell images to train and test the model. FINDINGS: With 1% annotations (18-114 cells), SANDI achieved weighted F1-scores ranging from 0.82 to 0.98 across the five datasets, which was comparable to the fully supervised classifier trained on 1828-11,459 annotated cells (-0.002 to -0.053 of averaged weighted F1-score, Wilcoxon rank-sum test, P = 0.31). Leveraging the immune checkpoint markers stained in ovarian cancer slides, SANDI-based cell identification reveals spatial expulsion between PD1-expressing T helper cells and T regulatory cells, suggesting an interplay between PD1 expression and T regulatory cell-mediated immunosuppression. INTERPRETATION: By striking a fine balance between minimal expert guidance and the power of deep learning to learn similarity within abundant data, SANDI presents new opportunities for efficient, large-scale learning for histology multiplex imaging data. FUNDING: This study was funded by the Royal Marsden/ICR National Institute of Health Research Biomedical Research Centre.

Spatial Positioning of Immune Hotspots Reflects the Interplay between B and T Cells in Lung Squamous Cell Carcinoma.

Beyond tertiary lymphoid structures, a significant number of immune-rich areas without germinal center-like structures are observed in non-small cell lung cancer. Here, we integrated transcriptomic data and digital pathology images to study the prognostic implications, spatial locations, and constitution of immune rich areas (immune hotspots) in a cohort of 935 patients with lung cancer from The Cancer Genome Atlas. A high intratumoral immune hotspot score, which measures the proportion of immune hotspots interfacing with tumor islands, was correlated with poor overall survival in lung squamous cell carcinoma but not in lung adenocarcinoma. Lung squamous cell carcinomas with high intratumoral immune hotspot scores were characterized by consistent upregulation of B-cell signatures. Spatial statistical analyses conducted on serial multiplex IHC slides further revealed that only 4.87% of peritumoral immune hotspots and 0.26% of intratumoral immune hotspots were tertiary lymphoid structures. Significantly lower densities of CD20+CXCR5+ and CD79b+ B cells and less diverse immune cell interactions were found in intratumoral immune hotspots compared with peritumoral immune hotspots. Furthermore, there was a negative correlation between the percentages of CD8+ T cells and T regulatory cells in intratumoral but not in peritumoral immune hotspots, with tertiary lymphoid structures excluded. These findings suggest that the intratumoral immune hotspots reflect an immunosuppressive niche compared with peritumoral immune hotspots, independent of the distribution of tertiary lymphoid structures. A balance toward increased intratumoral immune hotspots is indicative of a compromised antitumor immune response and poor outcome in lung squamous cell carcinoma. SIGNIFICANCE: Intratumoral immune hotspots beyond tertiary lymphoid structures reflect an immunosuppressive microenvironment, different from peritumoral immune hotspots, warranting further study in the context of immunotherapies.

Protein kinase C epsilon promotes de novo lipogenesis and tumor growth in prostate cancer cells by regulating the phosphorylation and nuclear translocation of pyruvate kinase isoform M2.

Protein kinase C epsilon (PKCε) belongs to a family of serine/threonine kinases that control cell proliferation, differentiation and survival. Aberrant PKCε activation and overexpression is a frequent feature of numerous cancers. However, its role in regulation of lipid metabolism in cancer cells remains elusive. Here we report a novel function of PKCε in regulating of prostate cancer cell proliferation by modulation of PKM2-mediated de novo lipogenesis. We show that PKCε promotes de novo lipogenesis and tumor cell proliferation via upregulation of lipogenic enzymes and lipid contents in prostate cancer cells. Mechanistically, PKCε interacts with NABD (1-388) domain of C-terminal deletion on pyruvate kinase isoform M2 (PKM2) and enhances the Tyr105 phosphorylation of PKM2, leading to its nuclear localization. Moreover, forced expression of mutant Tyr105 (Y105F) or PKM2 inhibition suppressed de novo lipogenesis and cell proliferation induced by overexpression of PKCε in prostate cancer cells. In a murine tumor model, inhibitor of PKM2 antagonizes lipogenic enzymes expression and prostate cancer growth induced by overexpression of PKCε in vivo. These data indicate that PKCε is a critical regulator of de novo lipogenesis, which may represent a potential therapeutic target for the treatment of prostate cancer.

MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge.

Detecting various types of cells in and around the tumor matrix holds a special significance in characterizing the tumor micro-environment for cancer prognostication and research. Automating the tasks of detecting, segmenting, and classifying nuclei can free up the pathologists' time for higher value tasks and reduce errors due to fatigue and subjectivity. To encourage the computer vision research community to develop and test algorithms for these tasks, we prepared a large and diverse dataset of nucleus boundary annotations and class labels. The dataset has over 46,000 nuclei from 37 hospitals, 71 patients, four organs, and four nucleus types. We also organized a challenge around this dataset as a satellite event at the International Symposium on Biomedical Imaging (ISBI) in April 2020. The challenge saw a wide participation from across the world, and the top methods were able to match inter-human concordance for the challenge metric. In this paper, we summarize the dataset and the key findings of the challenge, including the commonalities and differences between the methods developed by various participants. We have released the MoNuSAC2020 dataset to the public.

Betaine-assisted recombinase polymerase assay for rapid hepatitis B virus detection.

Hepatitis B virus (HBV) is a worldwide epidemic pathogen that causes hepatitis B. On-site screening the HBV infection is of critical importance for preventing and diagnosing HBV infection. In this paper, a simple, visual, and rapid method for on-site detection of HBV-DNA has been developed. This method is based on betaine-assisted recombinase polymerase assay and followed with naked-eye detection via lateral flow assay (BRPA-LF). Result show that nonspecific amplification is prone to occur in recombinase polymerase amplification (RPA) if the assay was performed with serum sample without purification. This problem has been addressed by adding 0.8 M of betaine to the RPA reactions. It was demonstrated that BRPA-LF can detect 1,000 copies of HBV-DNA in 50 µL mixture, and achieved 90% sensitivity and 100% specificity for serum sample detection. These results demonstrated that BRPA-LF can resist serum interference and has great potential for on-site screening of HBV infection.

The Landscape of Immune Cells Infiltrating in Prostate Cancer.

BACKGROUND: This study was to explore the infiltration pattern of immune cells in the prostate cancer (PCa) microenvironment and evaluate the possibility of specific infiltrating immune cells as potential prognostic biomarkers in PCa. METHODS: Infiltrating percentage of 22 immune cells were extracted from 27 normalized datasets by CIBERSORT algorithm. Samples with CIBERSORT p-value < 0.05 were subsequently merged and divided into normal or tumor groups. The differences of 22 immune cells between normal and tumor tissues were analyzed along with potential infiltrating correlations among 22 immune cells and Gleason grades. SNV data from TCGA was used to calculate the TMB score. A univariate and multivariate regression were used to evaluate the prognostic effects of immune cells in PCa. RESULTS: Ten immune cells with significant differences were identified, including seven increased and three decreased infiltrating immune cells from 190 normal prostate tissues and 537 PCa tissues. Among them, the percentage of infiltration of resting NK cells increased the most, whereas the percentage of infiltration of resting mast cells decreased the most. In normal tissues, CD8+ T cells had the strongest infiltrating correlation with monocytes, while activated NK cells and naive B cells were the highest in PCa tissues. Moreover, the infiltration of five immune cells was significantly associated with TMB score and mutations of immune gene change the infiltration of immune cells. The Area Under Curve (AUC) of the multivariate regression model for the five- and 10-year survival prediction of PCa reached 0.796 and 0.862. The validation cohort proved that the model was reproducible. CONCLUSIONS: This study demonstrated that different infiltrating immune cells in prostate cancer, especially higher infiltrating M1 macrophages and neutrophils in PCa tissue, are associated with patients' prognosis, suggesting that these two immune cells might be potential targets for PCa diagnosis and prognosis of treatment.

Internet and WeChat used by patients with Crohn's disease in China: a multi-center questionnaire survey.

BACKGROUND: Currently, WeChat is widely used in disease education for patients with Crohn's disease (CD) in China. It is beneficial for the patients to actively engage in their disease management. METHODS: In this study, we examined the source and expectations of disease information for Chinese CD patients, analysing the content of popular WeChat public accounts and their potential association with medication adherence. RESULTS: Between November 24th, 2017 and April 10th, 2018, online questionnaires were sent to CD patients from eight different large urban hospitals in China. In all, 436 patients with CD were surveyed, and 342 patients responded. Patients most frequently visited Baidu (65%), WeChat (61%) and medical websites such as Haodaifu (35%) when searching for IBD-related information. Among ten WeChat IBD public accounts, the China Crohn's and Colitis Foundation (CCCF) (73%), "IBD Academic Officer" (21%) and "IBD in love" (21%) were the most popular. CD patients were most interested in information from the internet about diet and day-to-day health-related living with IBD (83%), an introduction to the disease (80%), and medication advances and side effects (80%). The correlation between the information provided by the top five WeChat public accounts and patients' expectations was low. Additionally, most patients (64%) had greater confidence in overcoming the disease after learning about CD through their internet searches. Medical adherence was also related to internet access and income (p < 0.05). CONCLUSIONS: WeChat has become a major source of information for IBD education in China, but the content of WeChat didn't fully meet patients' expectations. Therefore, future initiatives should aim to provide high-quality information that based on patients' demands.

Efficacy predictors of a 2-month exclusive enteral nutrition for inducing remission of active Crohn's disease.

In order to identify the factors that could predict the efficacy of exclusive enteral nutrition (EEN) in inducing remission of active CD. Baseline clinical and laboratory covariates were correlated with the outcome (clinical remission) of EEN in active CD (CDAI ≥150) by both univariable and multivariable analyses. A total of 67 from a consecutive of 136 active CD patients were enrolled. L4b (from treitz ligament to distal 1/3 ileum) involvement was negatively and high serum albumin (≥35 g/L) was positively associated with clinical remission (OR: 0.14, OR: 14.71). In conclusion, L4b sparing and high serum albumin might predict a favorable outcome of EEN in active CD (ClinicalTrials.gov ID: NCT 02942511).

LncRNA SNHG12 regulates gastric cancer progression by acting as a molecular sponge of miR­320.

Gastric cancer (GC) is one of the most common malignancies worldwide. Previous studies have focused on long non­coding RNAs (lncRNAs), which have important roles in the development and progression of GC. The present study aimed to clarify the expression and function of lncRNA small nucleolar RNA host gene 12 (SNHG12) in GC. The expression and the clinical characteristics of GC were analyzed in the samples from patients with GC and matched adjacent normal tissues. The present study determined that SNHG12 was significantly overexpressed in GC and its expression level was highly associated with tumor size, tumor­node­metastasis stage, distant metastasis, lymphatic metastasis. Patients with high SNHG12 expression had a short survival period. Additionally, inhibition of SNHG12 in GC cell lines SGC­7901 and AGS suppressed cell growth, colony formation, proliferation and invasion. MicroRNA (miR)­320, a putative target gene of SNHG12, was inversely correlated with SNHG12 expression in GC tissues and cell lines. In addition, the present study determined that miR­320 was directly regulated by SNHG12 and suppression of miR­320 expression reversed the inhibitory effects of SNHG12 siRNA on GC cell proliferation and invasion. These findings revealed that SNHG12 acts as a tumor promoter by directly targeting miR­320 in GC, suggesting a potential novel biomarker for the diagnosis and prognosis of GC.

Expression of IRAK­3 is associated with colitis­associated tumorigenesis in mice.

Interleukin­1 receptor­associated kinase­3 (IRAK­3) is a negative regulator in Toll­like receptor (TLR) pathways. The present study investigated the importance of IRAK­3 in a mouse model of chemically­induced colitis­associated tumorigenesis. The colitis­associated tumorigenesis was induced in ICR mice by the administration of 1,2­dimethyl hydrazine (DMH) and dextran sodium sulfate (DSS), termed the DMH + DSS group. In the DSS group, mice were administered with DSS; in the DMH group, mice were injected with DMH; in the control group, mice were injected with physiological saline. The clinical signs were examined for 20 weeks; tissue samples were analyzed at week 4, 9, 13 and 20. At week 20, the levels of IRAK­3 were analyzed using immunohistochemistry, western blot analysis, reverse transcription­quantitative polymerase chain reaction (RT­qPCR) analysis, and methylation­specific PCR. At week 20, the DMH + DSS group mice exhibited a decrease in total body weight and had developed canalicular adenoma or adenocarcinoma. The mice in the DSS group and DMH group presented with significant colitis at week 20. The mice with colitis­associated tumorigenesis were found to have decreased levels of IRAK­3, compared with the mice in the other groups, as evidenced by the results of the immunohistochemistry (P=0.002), RT­qPCR analysis (P<0.001) and western blot analysis (P<0.001). IRAK­3 methylation was observed in all experimental groups. Taken together, DMH + DSS induction in colitis led to increased inflammation and risk of tumorigenesis. IRAK­3 methylation may be a predictive factor in the transition from colitis to cancer.

Decreased expression of dual specificity phosphatase 22 in colorectal cancer and its potential prognostic relevance for stage IV CRC patients.

Dual specificity phosphatase 22 (DUSP22) is a novel dual specificity phosphatase that has been demonstrated to be a cancer suppressor gene associated with numerous biological and pathological processes. However, little is known of DUSP22 expression profiling in colorectal cancer and its prognostic value. Our study aims to investigate the role of DUSP22 expression in the prognosis of colorectal cancer. We detected the mRNA expression in 92 paired primary colorectal cancer tissues and the corresponding adjacent normal tissues by using QuantiGenePlex assay. The Friedman test was used to determine the statistical difference of gene expression. Kaplan-Meier survival analysis was performed. Mann-Whitney test and Kruskal-Wallis test were used to conduct data analyses to determine the prognostic value. Statistical significance was set at P < 0.05. In 74 of 92 cases, DUSP22 mRNA was reduced in primary colorectal cancer tissues, compared to the adjacent normal tissues. The mRNA levels of DUSP22 were significantly lower in colorectal cancer tissues than in adjacent normal tissues (0.0290 vs. 0.0658; P < 0.001). Low expression of DUSP22 correlated significantly with large tumor size (P = 0.013). No association was observed between DUSP22 mRNA expression and differentiation, histopathological type, tumor invasion, lymph node metastases, metastases, TNM stage, and Duke's phase (all P > 0.05). Kaplan-Meier analysis indicated that DUSP22 expression had no significant relationship with overall survival in all patients (P > 0.05). Interestingly, low expression level of DUSP22 in stage IV patients had a poor survival measures with a marginal P value (P = 0.07). Reduced DUSP22 expression was found in colorectal cancer specimens. Low expression level of DUSP22 in stage IV patients had a poor survival outcome. Further study is required for the investigation of the role of DUSP22 in colorectal cancer.