Comparison of cytokine expression and disease severity between plasma cell-dominant and eosinophil-dominant patients in chronic rhinosinusitis with nasal polyps.

PURPOSE: Chronic rhinosinusitis with nasal polyps (CRSwNP) is a heterogeneous disease characterized by inflammation of the nasal and sinus mucosa. The inflammatory patterns may differ among patients, leading to different subtypes based on the dominant inflammatory cell type. This study aimed to compare the differences in cytokine expression and disease severity between plasma cell-dominant and eosinophil-dominant subtypes in patients with CRSwNP. METHODS: This study included 53 CRSwNP patients and 19 control subjects who did not have asthma or a history of cigarette smoking. The expression of cytokines and inflammatory cells was assessed via enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry, respectively. RESULTS: Among the cytokines analyzed, only IL-6 was significantly different between the two subtypes. A greater proportion of mast cells and IgE cells was present in plasma cell-dominant CRSwNP patients than in eosinophil-dominant group. For the three disease severity scores (LMK-CT, TPS and SNOT-22), objective scores (LMK-CT and TPS) were greater in the eosinophil-dominant CRSwNP group, while the opposite result was shown for the subjective score (SNOT-22). Additionally, the percentage of plasma cell-dominant cells was significantly positively correlated with disease severity according to the TPS and SNOT-22 scores. CONCLUSIONS: Our data revealed that plasma cell-dominant inflammation, a subtype of type 2 CRS, was significantly correlated with subjective disease severity. The study also highlights the role of IL-6, IgE and mast cells as distinguishing factors between eosinophil-dominant and plasma cell-dominant CRSwNP. This information could be useful for clinical diagnosis and personalized treatment.

TOP2A modulates signaling via the AKT/mTOR pathway to promote ovarian cancer cell proliferation.

Ovarian cancer (OC) is a form of gynecological malignancy that is associated with worse patient outcomes than any other cancer of the female reproductive tract. Topoisomerase II α (TOP2A) is commonly regarded as an oncogene that is associated with malignant disease progression in a variety of cancers, its mechanistic functions in OC have yet to be firmly established. We explored the role of TOP2A in OC through online databases, clinical samples, in vitro and in vivo experiments. And initial analyses of public databases revealed high OC-related TOP2A expression in patient samples that was related to poorer prognosis. This was confirmed by clinical samples in which TOP2A expression was elevated in OC relative to healthy tissue. Kaplan-Meier analyses further suggested that higher TOP2A expression levels were correlated with worse prognosis in OC patients. In vitro, TOP2A knockdown resulted in the inhibition of OC cell proliferation, with cells entering G1 phase arrest and undergoing consequent apoptotic death. In rescue assays, TOP2A was confirmed to regulate cell proliferation and cell cycle through AKT/mTOR pathway activity. Mouse model experiments further affirmed the key role that TOP2A plays as a driver of OC cell proliferation. These data provide strong evidence supporting TOP2A as an oncogenic mediator and prognostic biomarker related to OC progression and poor outcomes. At the mechanistic level, TOP2A can control tumor cell growth via AKT/mTOR pathway modulation. These preliminary results provide a foundation for future research seeking to explore the utility of TOP2A inhibitor-based combination treatment regimens in platinum-resistant recurrent OC patients.

Oncological and reproductive outcomes of endometrial atypical hyperplasia and endometrial cancer patients undergoing conservative therapy with hysteroscopic resection: A systematic review and meta-analysis.

INTRODUCTION: Our objective was to conduct a systematic review and meta-analysis of studies evaluating the oncological and reproductive outcomes of patients with endometrial atypical hyperplasia (AH) and endometrioid endometrial cancer (EEC) undergoing conservative therapy with hysteroscopic resection (HR). MATERIAL AND METHODS: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement for systematic reviews and meta-analyses. The study strictly followed the methodological framework proposed by the Cochrane Handbook and was retrospectively registered in PROSPERO (CRD42023469986). Searches were conducted in PubMed, Embase, and the Cochrane Library, from inception to October 10, 2023. A checklist based on items of the Newcastle-Ottawa Scale and the Methodological Index for Non-randomized Studies was used for quality assessment. The primary end points for this meta-analysis were complete response (CR), pregnancy, and live birth rates following HR-based therapy in patients with EEC or AH. The secondary end point was the recurrence rate (RR). RESULTS: Twenty-one articles involving 407 patients with clinical stage IA, low or intermediate grade, EEC, and 444 patients with AH managed with HR-based conservative treatment were included for this systematic review. CR to HR-based conservative therapy was achieved in 88.6% of patients with EEC and 97.0% of patients with AH. Of these, 30.6% and 24.2%, respectively, had live births. The overall pooled disease RR was 18.3% and 10.8% in patients with EEC and AH, respectively. Further subset analyses revealed that EEC patients with body mass index (BMI) ≤28 kg/m2 had higher CR rates as well as higher chances of pregnancy and live birth (91.6% CR, 32.9% pregnancy, 31.1% live birth) compared with patients with BMI >28 kg/m2 (86.4% CR, 28.4% pregnancy, 23.0% live birth). The HR followed by oral progestogen subgroup had higher CR rates and higher chances of pregnancy and live birth (91.8% CR, 36.3% pregnancy, 28.2% live birth) than the HR followed by the levonorgestrel intrauterine system subgroup (82.5% CR, 25.3% pregnancy, 16.3% live birth). CONCLUSIONS: Hysteroscopic resection followed by progestins appears to be a promising choice for fertility-sparing treatment in young patients with AH and EEC, with effective and safe responses. The live birth rate remains to be improved by providing medical guidance and encouragement.

The Application of CT Radiomics in the Diagnosis of Vein Wall Invasion in Patients With Renal Cell Carcinoma Combined With Tumor Thrombus.

OBJECTIVE: The objective of this study was to explore the application of radiomics combined with machine learning to establish different models to assist in the diagnosis of venous wall invasion in patients with renal cell carcinoma and venous tumor thrombus and to evaluate the diagnostic efficacy. MATERIALS AND METHODS: We retrospectively reviewed the data of 169 patients in Peking University Third Hospital from March 2015 to January 21, who was diagnosed as renal mass with venous invasion. According to the intraoperative findings, 111 patients were classified to the venous wall invasion group and 58 cases in the non-invasion group. ITK-snap was used for tumor segmentation and PyRadiomics 3.0.1 package was used for feature extraction. A total of 1598 features could be extracted from each CT image. The patients were divided into training set and testing set by time. The elastic-net regression with 4-fold cross-validation was used as a dimension-reduction method. After feature selection, a support vector machines (SVM) model, a logistic regression (LR) model, and an extra trees (ET) model were established. Then the sensitivity, specificity, accuracy, and the area under the curve (AUC) were calculated to evaluate the diagnostic performance of each model on the testing set. RESULTS: Patients before September 2019 were divided into the training set, of which 88 patients were in the invasion group and 42 patients were in the non-invasion group. The others were in the testing set, of which 32 patients were in the invasion group and 16 patients were in the non-invasion group. A total of 34 radiomics features were obtained by the elastic-net regression. The SVM model had an AUC value of 0.641 (95% CI, 0.463-0.769), a sensitivity of 1.000, and a specificity of 0.062. The LR model had an AUC value of 0.769 (95% CI, 0.620-0.877), a sensitivity of 0.913, and a specificity of 0.312. The ET model had an AUC value of 0.853 (95% CI, 0.734-0.948), a sensitivity of 0.783, and a specificity of 0.812. Among the 3 models, the ET model had the best diagnostic effect, with a good balance of sensitivity and specificity. And the higher the tumor thrombus grade, the better the diagnostic efficacy of the ET model. In inferior vena cava tumor thrombus, the sensitivity, specificity, accuracy, and AUC of ET model can be improved to 0.889, 0.800, 0.857, 0.878 (95% CI, 0.745-1.000). CONCLUSION: Machine learning combined with radiomics method can effectively identify whether venous wall was invaded by tumor thrombus and has high diagnostic efficacy with an AUC of 0.853 (95% CI, 0.734-0.948).

[Predictive model of early urinary continence recovery based on prostate gland MRI parameters after laparoscopic radical prostatectomy].

OBJECTIVE: Constructing a predictive model for urinary incontinence after laparoscopic radical prostatectomy (LRP) based on prostatic gland related MRI parameters. METHODS: In this study, 202 cases were included. All the patients were diagnosed with prostate cancer by prostate biopsy and underwent LRP surgery in Peking University Third Hospital. The preoperative MRI examination of all the patients was completed within 1 week before the prostate biopsy. Prostatic gland related parameters included prostate length, width, height, prostatic volume, intravesical prostatic protrusion length (IPPL), prostate apex shape, etc. From the first month after the operation, the recovery of urinary continence was followed up every month, and the recovery of urinary continence was based on the need not to use the urine pad all day long. Logistic multivariate regression analysis was used to analyze the influence of early postoperative recovery of urinary continence. Risk factors were used to draw the receiver operator characteristic (ROC) curves of each model to predict the recovery of postoperative urinary continence, and the difference of the area under the curve (AUC) was compared by DeLong test, and the clinical net benefit of the model was evaluated by decision curve analysis (DCA). RESULTS: The average age of 202 patients was 69.0 (64.0, 75.5) years, the average prostate specific antigen (PSA) before puncture was 12.12 (7.36, 20.06) µg/L, and the Gleason score < 7 points and ≥ 7 points were 73 cases (36.2%) and 129 cases (63.9%) respectively, with 100 cases (49.5%) at T1/T2 clinical stage, and 102 cases (50.5%) at T3 stage. The prostatic volume measured by preoperative MRI was 35.4 (26.2, 51.1) mL, the ratio of the height to the width was 0.91 (0.77, 1.07), the membranous urethral length (MUL) was 15 (11, 16) mm, and the IPPL was 2 (0, 6) mm. The prostatic apex A-D subtypes were 67 cases (33.2%), 80 cases (39.6%), 24 cases (11.9%) and 31 cases (15.3%), respectively. The training set and validation set were 141 cases and 61 cases, respectively. The operations of all the patients were successfully completed, and the urinary continence rate was 59.4% (120/202) in the 3 months follow-up. The results of multivariate analysis of the training set showed that the MUL (P < 0.001), IPPL (P=0.017) and clinical stage (P=0.022) were independent risk factors for urinary incontinence in the early postoperative period (3 months). The nomogram and clinical decision curve were made according to the results of multivariate analysis. The AUC value of the training set was 0.885 (0.826, 0.944), and the AUC value of the validation set was 0.854 (0.757, 0.950). In the verification set, the Hosmer-Lemeshow goodness-of-fit test was performed on the model, and the Chi-square value was 5.426 (P=0.711). CONCLUSION: Preoperative MUL, IPPL, and clinical stage are indepen-dent risk factors for incontinence after LRP. The nomogram developed based on the relevant parameters of MRI glands can effectively predict the recovery of early urinary continence after LRP. The results of this study require further large-scale clinical research to confirm.

Comprehensive analyses of fatty acid metabolism-related lncRNA for ovarian cancer patients.

Ovarian cancer (OC) is a disease with difficult early diagnosis and treatment and poor prognosis. OC data profiles were downloaded from The Cancer Genome Atlas. Eight key fatty acid metabolism-related long non-coding RNAs (lncRNAs) were finally screened for building a risk scoring model by univariate/ multifactor and least absolute shrinkage and selection operator (LASSO) Cox regression. To make this risk scoring model more applicable to clinical work, we established a nomogram containing the clinical characteristics of OC patients after confirming that the model has good reliability and validity and the ability to distinguish patient prognosis. To further explore how these key lncRNAs are involved in OC progression, we explored their relationship with LUAD immune signatures and tumor drug resistance. The structure shows that the risk scoring model established based on these 8 fatty acid metabolism-related lncRNAs has good reliability and validity and can better predict the prognosis of patients with different risks of OC, and LINC00861in these key RNAs may be a hub gene that affects the progression of OC and closely related to the sensitivity of current OC chemotherapy drugs. In addition, combined with immune signature analysis, we found that patients in the high-risk group are in a state of immunosuppression, and Tfh cells may play an important role in it. We innovatively established a prognostic prediction model with excellent reliability and validity from the perspective of OC fatty acid metabolism reprogramming and lncRNA regulation and found new molecular/cellular targets for future OC treatment.

Minimally invasive, single-stage, multilevel surgery for obstructive sleep apnoea: A systematic review and meta-analysis.

OBJECTIVES: Minimally invasive, single-staged multilevel surgery (MISS MLS) could be an optimal treatment for selected patients with obstructive sleep apnea (OSA). We aim to systematically review the efficacy of MISS MLS for patients with OSA, as well as the clinical outcomes and possible complications in OSA patients before and after MISS MLS. DESIGN AND SETTING: Systematic review and meta-analysis. Six databases were searched, and the PRISMA guideline was followed. PARTICIPANTS: Patients with OSA receiving MISS MLS. MAIN OUTCOME MEASURES: The random-effects model was adopted for the statistical synthesis. The percentage and 95% confidence interval (CI) were adopted as the effect measurements of MISS MLS for OSA. Subgroup analyses and sensitivity analyses were also performed to identify the heterogeneity among the studies. RESULTS: There were initially 154 articles for identification. Eventually, six studies with a total of 848 OSA patients completely met the inclusion criteria and were further enrolled for analysis. The pooled analysis showed statistically significant lower AHI (apnea/hypopnea index, /hr.; mean difference: -8.931, 95% CI: -11.591 to -6.271, I2 = 87.4%), ESS (mean difference: -2.947, 95% CI: -4.465 to -1.429, I2 = 94.9%), and snoring severity with 0-10 visual analog scale after surgery (mean difference: -4.966, 95% CI: -5.804 to -4.128, I2 = 96.4%). The success rate was 46% in mild/moderate OSA; however, 18% in severe OSA. There were no major complications occurred. CONCLUSIONS: The acceptable surgical outcomes, esp. in mild/moderate OSA, and rare complications are the major advantages of MISS MLS. The evidence of this study could aid the decision making in selecting suitable treatment programs for OSA patients.

The prognostic utility of preoperative geriatric nutritional risk index on survival outcomes of locally advanced oral cancer.

PURPOSE: This retrospective cohort study was to assess the prognostic value of preoperative geriatric nutritional risk index (GNRI) on survival outcomes for patients with locally advanced oral squamous cell carcinoma (LAOSCC). METHODS: Patients with LAOSCC receiving upfront radical surgery at a single institute from January 2007 to February 2017 were enrolled. The primary outcomes in the study were 5-year overall survival (OS) and cancer-specific survival (CSS) rates, and a nomogram based on GNRI and other clinical-pathological factors was established for individualized OS prediction. RESULTS: There were 343 patients enrolled in this study. The optimal cut-off value of GNRI was observed to be 97.8. Patients in the high-GNRI group (GNRI ≥97.8) had statistically significantly better outcomes in 5-year OS (74.7% vs. 57.2%, p = 0.001) and CSS (82.2% vs. 68.9%, p = 0.005) when compared with the low-GNRI group (GNRI <97.8). In Cox models, low GNRI remained an independent negative prognosticator of OS (HR: 1.6; 95% CI: 1.124-2.277; p = 0.009) and CSS (HR: 1.907; 95% CI: 1.219-2.984; p = 0.005). The c-index of the proposed nomogram, incorporating assorted clinicopathological factors and GNRI, had a statistically significant increase compared with the predictive nomogram constructed by the TNM staging system alone (0.692 vs. 0.637, p < 0.001)." CONCLUSION: Preoperative GNRI is an independent prognostic factor of OS and CSS in patients with LAOSCC. A multivariate nomogram that includes GNRI may better help us to accurately estimate individual survival outcomes.

Lymph node ratio as a survival predictor for head and neck squamous cell carcinoma with multiple adverse pathological features.

BACKGROUND: The study investigates the prognostic significance of lymph node ratio (LNR) on patients with head and neck squamous cell carcinoma (HNSCC) with coexistence of multiple adverse pathological features. METHODS: In total, 100 patients with coexistence of perineural invasion, lymphovascular invasion, and extranodal extension of first primary HNSCC treated with radical surgery followed by adjuvant chemoradiotherapy were enrolled. RESULTS: The optimal LNR cut-off value for predicting overall survival (OS) and cancer specific survival (CSS) was 7%. In Cox model, we observed that LNR ≥7% was a statistically significant unfavorable predictor of OS (HR: 2.689; 95% CI: 1.228-5.889; p = 0.013) and CSS (HR: 3.162; 95% CI: 1.234-8.102; p = 0.016). CONCLUSION: For HNSCC patients with coexistence of multiple adverse pathological features, LNR is an independent survival predictor. Novel intensified treatments are needed for the subgroup of patients with a high LNR.

Development of Prognostic Biomarkers by TMB-Guided WSI Analysis: A Two-Step Approach.

The rapid development of computational pathology has brought new opportunities for prognosis prediction using histopathological images. However, the existing deep learning frameworks lack exploration of the relationship between images and other prognostic information, resulting in poor interpretability. Tumor mutation burden (TMB) is a promising biomarker for predicting the survival outcomes of cancer patients, but its measurement is costly. Its heterogeneity may be reflected in histopathological images. Here, we report a two-step framework for prognostic prediction using whole-slide images (WSIs). First, the framework adopts a deep residual network to encode the phenotype of WSIs and classifies patient-level TMB by the deep features after aggregation and dimensionality reduction. Then, the patients' prognosis is stratified by the TMB-related information obtained during the classification model development. Deep learning feature extraction and TMB classification model construction are performed on an in-house dataset of 295 Haematoxylin & Eosin stained WSIs of clear cell renal cell carcinoma (ccRCC). The development and evaluation of prognostic biomarkers are performed on The Cancer Genome Atlas-Kidney ccRCC (TCGA-KIRC) project with 304 WSIs. Our framework achieves good performance for TMB classification with an area under the receiver operating characteristic curve (AUC) of 0.813 on the validation set. Through survival analysis, our proposed prognostic biomarkers can achieve significant stratification of patients' overall survival (P 0.05) and outperform the original TMB signature in risk stratification of patients with advanced disease. The results indicate the feasibility of mining TMB-related information from WSI to achieve stepwise prognosis prediction.

V.I.P. Score: A Comprehensive Grading System to Predict Difficulty of HoLEP Procedure for Small-to-Moderate Sized Prostate (<120 mL).

OBJECTIVE: To develop a comprehensive scoring system in addition to the conventionally used prostatic volume (PV), for predicting the difficulty of holmium laser enucleation of the prostate (HoLEP) that may arise with small-to-moderate sized prostate. METHODS: We retrospectively reviewed 151 consecutive patients who underwent HoLEP and had a PV less than 120 mL. Based on previous literature, a difficult procedure was defined as a prolonged operative time (OT>90 minute) in 88 cases, while the control group (OT≤90 minute) consisted of 63 patients. The clinical data, including age, body mass index, PV, intravesical prostatic protrusion (IPP), prostate specific antigen (PSA), prostate specific antigen density, urinary tract infection, microscopic hematuria, prior biopsy, diabetes mellitus, hypertension, history of acute urinary retention, catheter dependency and use of antiplatelet / anticoagulation drugs or 5-alpha reductase inhibitor were compared between the 2 groups. RESULTS: Univariate analysis revealed significant differences between the 2 groups. Multivariate analysis identified 3 main independent predictors for difficulty, including volume (V) (60-90 mL OR = 9.812, P < .001) (≥90 mL OR = 18.173, P = .01), IPP (I) (OR = 3.157, P = .018), and PSA (P) (≥4 ng/ml OR = 16.738, P < .001). Therefore, a V.I.P. score was developed based on the regression model and ranged from 0 to 7 points. The area under the curve showed preferable predictive ability of the V.I.P. score compared to PV (0.906 vs 0.869). CONCLUSION: We developed a V.I.P. score that can accurately predict the difficulty of the HoLEP procedure for PV less than 120 mL in order to optimize clinical outcomes.

Analysis of the related factors of atypical squamous cells of undetermined significance (ASC-US) in cervical cytology of post-menopausal women.

Introduction: Atrophy of the reproductive tract mucosa caused by the decrease of estrogen may increase the detection rate of ASC-US in cervical cytology of post-menopausal women. In addition, other pathogenic infections and inflammation can change the cellular morphology and increase the detection rate of ASC-US. However, further studies are needed to elucidate whether the high detection rate of ASC-US in post-menopausal women leads to the high referral rate of colposcopy. Methods: This retrospective study was conducted to document ASC-US in cervical cytology reports at the Department of Cytology at Gynecology and Obstetrics, Tianjin Medical University General Hospital between January 2006 and February 2021. We then analyzed 2,462 reports of women with ASC-US at the Cervical Lesions Department. A total of 499 patients with ASC-US and 151 cytology with NILM participants underwent vaginal microecology tests. Results: The average reporting rate of ASC-US in cytology was 5.7%. The detection rate of ASC-US in women aged > 50 years (7.0%) was significantly higher than that in women aged ≤50 years (5.0%) (P<0.05). The CIN2+ detection rate was significantly lower in the post- (12.6%) than in pre-menopausal (20.5%) patients with ASC-US (P <0.05). The prevalence of abnormal reporting rate of vaginal microecology was significantly lower in the pre-menopausal group (56.2%) than that in the post-menopausal group (82.9%) (P<0.05). The prevalence of bacterial vaginosis (BV) (19.60%) was relatively high in the pre-menopausal group, but the abundance of bacteria-inhibiting flora (40.79%) was mainly an abnormality in the post-menopausal group. The vaginal microecological abnormality rate of the women with HR-HPV (-) of ASC-US was 66.22%, which was significantly higher than that of the HR-HPV (-) and the NILM group (52.32%; P<0.05). Discussion: The detection rate of ASC-US in women aged > 50 years was higher than that ≤50 years, but the detection rate of CIN2+ was lower in the post-menopausal women with ASC-US. However, vaginal microecological abnormalities may increase the false-positive diagnosis rate of ASC-US. The vaginal microecological abnormalities of the menopausal women with ASC-US are mainly attributed to infectious diseases such as BV, and it mainly occurs in the post-menopausal women was bacteria-inhibiting flora. Therefore, to avoid the high referral rate for colposcopy, more attention should be paid to the detection of vaginal microecology.

CCNE1 is a predictive and immunotherapeutic indicator in various cancers including UCEC: a pan-cancer analysis.

BACKGROUND: CCNE1 plays an important oncogenic role in several tumors, especially high-stage serous ovarian cancer and endometrial cancer. Nevertheless, the fundamental function of CCNE1 has not been explored in multiple cancers. Therefore, bioinformatics analyses of pan-cancer datasets were carried out to explore how CCNE1 regulates tumorigenesis. METHODS: A variety of online tools and cancer databases, including GEPIA2, SangerBox, LinkedOmics and cBioPortal, were applied to investigate the expression of CCNE1 across cancers. The pan-cancer datasets were used to search for links between CCNE1 expression and prognosis, DNA methylation, m6A level, genetic alterations, CCNE1-related genes, and tumor immunity. We verified that CCNE1 has biological functions in UCEC cell lines using CCK-8, EdU, and Transwell assays. RESULTS: In patients with different tumor types, a high mRNA expression level of CCNE1 was related to a poor prognosis. Genes related to CCNE1 were connected to the cell cycle, metabolism, and DNA damage repair, according to GO and KEGG enrichment analyses. Genetic alterations of CCNE1, including duplications and deep mutations, have been observed in various cancers. Immune analysis revealed that CCNE1 had a strong correlation with TMB, MSI, neoantigen, and ICP in a variety of tumor types, and this correlation may have an impact on the sensitivity of various cancers to immunotherapy. CCK-8, EdU and Transwell assays suggested that CCNE1 knockdown can suppress UCEC cell proliferation, migration and invasion. CONCLUSION: Our study demonstrated that CCNE1 is upregulated in multiple cancers in the TCGA database and may be a promising predictive biomarker for the immunotherapy response in some types of cancers. Moreover, CCNE1 knockdown can suppress the proliferation, migration and invasion of UCEC cells.

Follicular fluid progesterone downregulated HPGD and COX2 in granulosa cells via suppressing NF-ĸB in endometriosis†.

Increasing evidences showed that ovulatory dysfunction, possibly caused by luteinized unruptured follicular follicle syndrome (LUFS), is one of the reasons for endometriosis-related infertility. The present study was conducted to explore the potential effect of elevated progesterone in follicular fluid (FF) on ovulation in endometriosis. A prospective study including 50 ovarian endometriosis patients and 50 control patients with matched pairs design was conducted with alterations in FF and peritoneal fluid (PF) components identified by metabolomics analyses and differentially expressed genes in granulosa cells (GCs) identified by transcriptome analysis. Patients with endometriosis exhibited a significantly higher progesterone level in serum, FF, and PF. Granulosa cells from endometriosis patients revealed decreased expression of HPGD, COX-2, and suppressed NF-ĸB signaling. Similarly, progesterone treatment in vitro downregulated HPGD and COX2 expression and suppressed NF-ĸB signaling in granulosa tumor-like cell line KGN (Bena Culture Collection, China) and primarily cultured GCs, as manifested by decreased expressions of IL1R1, IRAK3, reduced pIĸBα/IĸBα ratio, and nucleus translocation of p65. On the contrary, TNF-α treatment increased expression of IL1R1, IRAK3, pIĸBα, p65, and HPGD in GCs. One potential p65 binding site was identified in the promoter region of HPGD by chromatin immunoprecipitation. In conclusion, we found that intrafollicular progesterone might downregulate HPGD and COX-2 in GCs via suppressing the NF-ĸB signaling pathway, shedding light on the mechanism underlying the endometriosis-related ovulatory dysfunction.

Leveraging 16S rRNA data to uncover vaginal microbial signatures in women with cervical cancer.

Microbiota-relevant signatures have been investigated for human papillomavirus-related cervical cancer (CC), but lack consistency because of study- and methodology-derived heterogeneities. Here, four publicly available 16S rRNA datasets including 171 vaginal samples (51 CC versus 120 healthy controls) were analyzed to characterize reproducible CC-associated microbial signatures. We employed a recently published clustering approach called VAginaL community state typE Nearest CentroId clAssifier to assign the metadata to 13 community state types (CSTs) in our study. Nine subCSTs were identified. A random forest model (RFM) classifier was constructed to identify 33 optimal genus-based and 94 species-based signatures. Confounder analysis revealed confounding effects on both study- and hypervariable region-associated aspects. After adjusting for confounders, multivariate analysis identified 14 significantly changed taxa in CC versus the controls (P < 0.05). Furthermore, predicted functional analysis revealed significantly upregulated pathways relevant to the altered vaginal microbiota in CC. Cofactor, carrier, and vitamin biosynthesis were significantly enriched in CC, followed by fatty acid and lipid biosynthesis, and fermentation of short-chain fatty acids. Genus-based contributors to the differential functional abundances were also displayed. Overall, this integrative study identified reproducible and generalizable signatures in CC, suggesting the causal role of specific taxa in CC pathogenesis.

Preoperative predictive model of early urinary continence recovery after laparoscopic radical prostatectomy.

PURPOSE: To develop and validate a predictive model include magnetic resonance imaging (MRI) parameters preoperatively which can assess the risk of incontinence after laparoscopic radical prostatectomy (LRP) accurately. METHODS: We retrospectively reviewed and included 170 patients with prostate cancer who underwent LRP between July 2015 and June 2018 in our institution. All 170 patients were randomly resampled and divided into training set (n = 124) and verification set (n = 46) according to the ratio of 7:3. The Nomogram prediction model of the risk of incontinence after LRP was established through the training set and verified by the verification set. Baseline patient characteristics were obtained, including age, body mass index, and prostate volume. Perioperative characteristics such as pre-biopsy prostate specific antigen, biopsy Gleason score, clinical staging, and NVB sparing status were also collected. MRI parameters preoperatively including membranous urethral length (MUL), prostate apex depth ratio (PADR), and intravesical prostatic protrusion length (IPPL) were obtained. The C index and visual inspection of calibration curve were used to evaluate the discrimination and calibration of the model. RESULTS: According to the urinary incontinence (UI) at 3 months postoperatively, the patients were divided into 104 cases (61.2%) in the group with no incontinence and 66 patients (38.8%) in the group with incontinence. Multivariate logistic regression analysis of training set showed that cT3a (OR = 0.427, 95% CI 0.142-1.281, P = 0.1288), MUL (OR = 0.237, 95% CI 0.102-0.551, P < 0.01), PADR (OR = 0.276, 95% CI 0.116-0.655, P < 0.01), and IPPL (OR = 0.073, 95% CI 0.030-0.179, P < 0.01) were independent predictors of urinary incontinence at 3 months postoperatively. The model showed good discrimination with an area under the receiver operating characteristic (ROC) curve of 0.880, with the sensitivity and specificity 0.800 and 0.816, respectively, and good calibration (Hosmer-Lemeshow test result of 5.57, P = 0.695). Decision curve analysis demonstrated that the model was clinically useful. CONCLUSION: This study developed and validated a preoperative model in the form of a nomogram to predict the risk of UI after LRP at 3 months. MUL, PADR, and IPPL were significant independent predictive factors of the postoperative early urinary continence.

Comparative analysis of surgical and oncologic outcomes of robotic, laparoscopic and open radical nephrectomy with venous thrombectomy: a propensity-matched cohort study.

OBJECTIVE: To provide insight into the surgical and oncological outcomes of robotic, laparoscopic and open radical nephrectomy with venous thrombectomy (RALRN-VT, LRN-VT, ORN-VT) in patients with renal tumor and venous thrombus. MATERIALS AND METHODS: A propensity-matched retrospective cohort study containing 324 patients with renal tumor and venous thrombus from January 2014 to August 2021 was analyzed. We compared surgical outcomes and we used the Kalan-Meier method to assess the overall survival (OS), tumor-specific survival (TSS), metastasis-free survival (MFS) and local recurrence-free survival (LRFS). The Pearson chi-square test and Fisher exact test, Wilcoxon rank sum test, Cox proportional hazards regression model and log-rank test were used. RESULTS: After matching, baseline characteristics were comparable in the RALRN-VT, LRN-VT and ORN-VT group. The RALRN-VT group had the least operative time (median 134 min vs 289 min vs 330 min, P < 0.001), the least blood loss (median 250 ml vs 500 ml vs 1000 ml, P < 0.001) and the fewest packed red blood cells transfusion (median 400 ml vs 800 ml vs 1200 ml, P < 0.001). The ORN-VT group had the highest complication rate (18.2 vs 22.7 vs 43.2%, P = 0.005), the highest Clavien grade (P = 0.001) and the longest postoperative hospital stay (median 7d vs 8d vs 10d, P < 0.001). No significant difference in OS, TSS and MFS between the minimally invasive procedures (MIP, including RALRN-VT and LRN-VT) group and ORN-VT group was found. The hazard ratio of LRFS for the MIP group was 0.20 (95% CI 0.06-0.70, P = 0.01) compared with ORN-VT group. CONCLUSIONS: RALRN-VT can result in the best surgical outcomes compared with LRN-VT and ORN-VT. The MIP group had a better LRFS compared with ORN-VT group.

Patterns of lymph node metastases and their implications in individualized radiotherapeutic clinical target volume delineation of regional lymph nodes in patients with endometrial cancer.

Purpose: To study the patterns of lymph node metastasis (LNM) of endometrial cancer (EC) and to clarify the individualized clinical target volume delineations of regional lymph nodes (CTVn). Methods: Data from a total of 556 patients with EC who had undergone total hysterectomy associated with bilateral salpingo-oophorectomy (TH/BSO) and systematic lymphadenectomy were retrospectively examined. The clinicopathological factors related to LNM were analyzed using logistic regression analysis. Results: LNM was found in 76 of 556 patients, resulting in a metastasis rate of 13.67%. The rates of LNM in patients with fundus and cornua lesions were 7.56% for para-aortic nodes and 14.41% for pelvic lymph nodes. The rates of LNM in patients with sidewall lesions were 3.15% for para-aortic nodes and 10.22% for pelvic lymph nodes. The rates of LNM in patients with lower uterine segment and cervix lesions were 12.50% for para-aortic nodes and 26.67% for pelvic lymph nodes. Deep myometrial invasion, histological type, histological differentiation, and lymphovascular space invasion (LVSI) emerged as statistically significant risk factors for pelvic LNM of EC (P = 0.008, 0.015, < 0.001, 0.005, respectively). Grade 3 differentiation had a strong influence on LNM to the para-aortic nodes (P = 0.015). Conclusions: Myometrial invasion, histological type, histological differentiation, and LVSI were related to pelvic LNM and grade 3 was associated with para-aortic LNM. These factors should be considered comprehensively to design the CTVn for intensity-modulated radiation therapy (IMRT) of EC. For patients with lower uterine segment/cervix and fundus/cornua lesions, delineating the irradiation field of the para-aortic nodal region may confer a benefit.

The Prognostic Value of Preoperative Albumin-to-Alkaline Phosphatase Ratio on Survival Outcome for Patients With Locally Advanced Oral Squamous Cell Carcinoma.

Background: This retrospective cohort study was to assess the prognostic value of preoperative albumin-to-alkaline phosphatase ratio (AAPR) on survival outcome for patients with locally advanced oral squamous cell carcinoma (LAOSCC). Methods: A total of 250 patients with LAOSCC receiving upfront radical surgery at a single institute from January 2008 to December 2017 were enrolled. The primary endpoint was the survival predictability of preoperative AAPR on the 5-year overall survival (OS), cancer-specific survival (CSS), and disease-free survival (DFS). Cox proportional hazards model was used for survival analysis. The X-tile software was used to estimate the optimal cut-off value of preoperative AAPR on survival prediction. A predictive nomogram incorporating the clinicopathological factors on OS was further generated. Results: The 5-year OS, CSS, and DFS rates were 68.6%, 79.7%, and 61.7%, respectively. The optimal cut-off of preoperative AAPR to predict the 5-year OS was observed to be 0.51. For those with preoperative AAPR≧0.51, the 5-year OS, CSS, and DFS were statistically significantly superior to those with preoperative AAPR<0.51 (OS: 76.1% vs 48.5%, P < .001; CSS: 84.3% vs 66.4%, P = .005; DFS: 68.9% vs 42.6%, P < .001). In Cox model, we observed that preoperative AAPR<0.51 was a significantly negative prognosticator of OS (HR: 2.22, 95% CI: 1.466-3.361, P < .001), CSS (HR: 2.037, 95% CI: 1.16-3.578, P = .013), and DFS (HR: 1.756, 95% CI: 1.075-2.868, P = .025). After adding the variable of preoperative AAPR, the c-index of the predictive nomogram incorporating assorted clinicopathological factors increases from 0.663 to 0.692 for OS. Conclusion: Our results suggest that preoperative AAPR serves as an independent survival predictor for patients with LAOSCC. The nomogram incorporating preoperative AAPR and various clinicopathological features may be a convenient tool to estimate the mortality risk for patients with LAOSCC.

Patient-level grading prediction of prostate cancer from mp-MRI via GMINet.

Magnetic resonance imaging (MRI) is considered the best imaging modality for non-invasive observation of prostate cancer. However, the existing quantitative analysis methods still have challenges in patient-level prediction, including accuracy, interpretability, context understanding, tumor delineation dependence, and multiple sequence fusion. Therefore, we propose a topological graph-guided multi-instance network (GMINet) to catch global contextual information of multi-parametric MRI for patient-level prediction. We integrate visual information from multi-slice MRI with slice-to-slice correlations for a more complete context. A novel strategy of attention folwing is proposed to fuse different MRI-based network branches for mp-MRI. Our method achieves state-of-the-art performance for Prostate cancer on a multi-center dataset (N = 478) and a public dataset (N = 204). The five-classification accuracy of Grade Group is 81.1 ± 1.8% (multi-center dataset) from the test set of five-fold cross-validation, and the area under curve of detecting clinically significant prostate cancer is 0.801 ± 0.018 (public dataset) from the test set of five-fold cross-validation respectively. The model also achieves tumor detection based on attention analysis, which improves the interpretability of the model. The novel method is hopeful to further improve the accurate prediction ability of MRI in the diagnosis and treatment of prostate cancer.