Deep Learning Can Predict Bevacizumab Therapeutic Effect and Microsatellite Instability Directly from Histology in Epithelial Ovarian Cancer.

Epithelial ovarian cancer (EOC) remains a significant cause of mortality among gynecologic cancers, with the majority of cases being diagnosed at an advanced stage. Before targeted therapies were available, EOC treatment relied largely on debulking surgery and platinum-based chemotherapy. Vascular endothelial growth factors have been identified as inducing tumor angiogenesis. According to several clinical trials, anti-vascular endothelial growth factor-targeted therapy with bevacizumab was effective in all phases of EOC treatment. However, there are currently no biomarkers accessible for regular therapeutic use despite the importance of patient selection. Microsatellite instability (MSI), caused by a deficiency of the DNA mismatch repair system, is a molecular abnormality observed in EOC associated with Lynch syndrome. Recent evidence suggests that angiogenesis and MSI are interconnected. Developing predictive biomarkers, which enable the selection of patients who might benefit from bevacizumab-targeted therapy or immunotherapy, is critical for realizing personalized precision medicine. In this study, we developed 2 improved deep learning methods that eliminate the need for laborious detailed image-wise annotations by pathologists and compared them with 3 state-of-the-art methods to not only predict the efficacy of bevacizumab in patients with EOC using mismatch repair protein immunostained tissue microarrays but also predict MSI status directly from histopathologic images. In prediction of therapeutic outcomes, the 2 proposed methods achieved excellent performance by obtaining the highest mean sensitivity and specificity score using MSH2 or MSH6 markers and outperformed 3 state-of-the-art deep learning methods. Moreover, both statistical analysis results, using Cox proportional hazards model analysis and Kaplan-Meier progression-free survival analysis, confirm that the 2 proposed methods successfully differentiate patients with positive therapeutic effects and lower cancer recurrence rates from patients experiencing disease progression after treatment (P < .01). In prediction of MSI status directly from histopathology images, our proposed method also achieved a decent performance in terms of mean sensitivity and specificity score even for imbalanced data sets for both internal validation using tissue microarrays from the local hospital and external validation using whole section slides from The Cancer Genome Atlas archive.

The Potential Role of Complement System in the Progression of Ovarian Clear Cell Carcinoma Inferred from the Gene Ontology-Based Immunofunctionome Analysis.

Ovarian clear cell carcinoma (OCCC) is the second most common epithelial ovarian carcinoma (EOC). It is refractory to chemotherapy with a worse prognosis after the preliminary optimal debulking operation, such that the treatment of OCCC remains a challenge. OCCC is believed to evolve from endometriosis, a chronic immune/inflammation-related disease, so that immunotherapy may be a potential alternative treatment. Here, gene set-based analysis was used to investigate the immunofunctionomes of OCCC in early and advanced stages. Quantified biological functions defined by 5917 Gene Ontology (GO) terms downloaded from the Gene Expression Omnibus (GEO) database were used. DNA microarray gene expression profiles were used to convert 85 OCCCs and 136 normal controls into to the functionome. Relevant offspring were as extracted and the immunofunctionomes were rebuilt at different stages by machine learning. Several dysregulated pathogenic functions were found to coexist in the immunopathogenesis of early and advanced OCCC, wherein the complement-activation-alternative-pathway may be the headmost dysfunctional immunological pathway in duality for carcinogenesis at all OCCC stages. Several immunological genes involved in the complement system had dual influences on patients' survival, and immunohistochemistrical analysis implied the higher expression of C3a receptor (C3aR) and C5a receptor (C5aR) levels in OCCC than in controls.

Knockdown of POLDIP2 suppresses tumor growth and invasion capacity and is linked to unfavorable transformation ability and metastatic feature in non-small cell lung cancer.

The main problem in the treatment of non-small cell lung cancer (NSCLC) is metastasis. Epithelial-mesenchymal transition (EMT) is known as the critical signaling in tumor progression, metastasis, and also the drug resistance. In this study, we reported a novel gene Polymerase delta-interacting protein 2 (POLDIP2) was downregulated in NSCLC tissues and first demonstrated that overexpression of POLDIP2 increased the anchorage-independent growth (AIG) and invasiveness of H1299 cells. In addition, we examined that knockdown of POLDIP2 in H1299 and A549 cells reduced tumorigenicity and metastatic capacity in vitro and also in vivo. Moreover, downregulation of the cell proliferation marker cyclin D1 and EMT markers CDH2, Slug, and Twist was showed in H1299 cells by POLDIP2 knockdown, suggesting that the inhibition of malignancy was affected by modulating key genes for tumor growth and invasiveness. Taken together, our study is the first study that demonstrated that POLDIP2 gene was function as an oncogene in NSCLC and implied the oncogenic ability might be through promoting cell proliferation or EMT.

Key Immunological Functions Involved in the Progression of Epithelial Ovarian Serous Carcinoma Discovered by the Gene Ontology-Based Immunofunctionome Analysis.

Serous carcinoma (SC) is the most common and lethal subtype of epithelial ovarian carcinoma; immunotherapy is a potential treatment for SC, however, the global immunological functions of SC as well as their change during the progression of SC have not been investigated in detail till now. We conducted a genome-wide integrative analysis to investigate the immunofunctionomes of SC at four tumor stages by quantifying the immunological functions defined by the Gene Ontology gene sets. DNA microarray gene expression profiles of 1100 SCs and 136 normal ovarian tissue controls were downloaded from the Gene Expression Omnibus database and converted to the functionome. Then the immunofunctionomes were reconstructed by extracting the offspring from the functionome for the four SC staging groups. The key immunological functions extracted from immunofunctionomes with a series of filters revealed that the immunopathy of SC consisted of a group of deregulated functions with the core members including B cell activation and differentiation, regulation of leukocyte chemotaxis/cellular extravasation, antigen receptor mediated signaling pathway, T helper mediated immunity and macrophage activation; and the auxiliary elements included leukocyte mediated immunity, regulation of inflammatory response, T cell differentiation, mononuclear cell migration, megakaryocyte differentiation, complement activation and cytokine production. These deregulated immunological functions reveal the candidates to target in the immunotherapy.

Discovering the Deregulated Molecular Functions Involved in Malignant Transformation of Endometriosis to Endometriosis-Associated Ovarian Carcinoma Using a Data-Driven, Function-Based Analysis.

The clinical characteristics of clear cell carcinoma (CCC) and endometrioid carcinoma EC) are concomitant with endometriosis (ES), which leads to the postulation of malignant transformation of ES to endometriosis-associated ovarian carcinoma (EAOC). Different deregulated functional areas were proposed accounting for the pathogenesis of EAOC transformation, and there is still a lack of a data-driven analysis with the accumulated experimental data in publicly-available databases to incorporate the deregulated functions involved in the malignant transformation of EOAC. We used the microarray gene expression datasets of ES, CCC and EC downloaded from the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO) database. Then, we investigated the pathogenesis of EAOC by a data-driven, function-based analytic model with the quantified molecular functions defined by 1454 Gene Ontology (GO) term gene sets. This model converts the gene expression profiles to the functionome consisting of 1454 quantified GO functions, and then, the key functions involving the malignant transformation of EOAC can be extracted by a series of filters. Our results demonstrate that the deregulated oxidoreductase activity, metabolism, hormone activity, inflammatory response, innate immune response and cell-cell signaling play the key roles in the malignant transformation of EAOC. These results provide the evidence supporting the specific molecular pathways involved in the malignant transformation of EAOC.

Hypomethylation signature of tumor-initiating cells predicts poor prognosis of ovarian cancer patients.

DNA methylation contributes to tumor formation, development and metastasis. Epigenetic dysregulation of stem cells is thought to predispose to malignant development. The clinical significance of DNA methylation in ovarian tumor-initiating cells (OTICs) remains unexplored. We analyzed the methylomic profiles of OTICs (CP70sps) and their derived progeny using a human methylation array. qRT-PCR, quantitative methylation-specific PCR (qMSP) and pyrosequencing were used to verify gene expression and DNA methylation in cancer cell lines. The methylation status of genes was validated quantitatively in cancer tissues and correlated with clinicopathological factors. ATG4A and HIST1H2BN were hypomethylated in OTICs. Methylation analysis of ATG4A and HIST1H2BN by qMSP in 168 tissue samples from patients with ovarian cancer showed that HIST1H2BN methylation was a significant and independent predictor of progression-free survival (PFS) and overall survival (OS). Multivariate Cox regression analysis showed that patients with a low level of HIST1H2BN methylation had poor PFS (hazard ratio (HR), 4.5; 95% confidence interval (CI), 1.4-14.8) and OS (HR, 4.3; 95% CI, 1.3-14.0). Hypomethylation of both ATG4A and HIST1H2BN predicted a poor PFS (HR, 1.8; 95% CI, 1.0-3.6; median, 21 months) and OS (HR, 1.7; 95% CI, 1.0-3.0; median, 40 months). In an independent cohort of ovarian tumors, hypomethylation predicted early disease recurrence (HR, 1.7; 95% CI, 1.1-2.5) and death (HR, 1.4; 95% CI, 1.0-1.9). The demonstration that expression of ATG4A in cells increased their stem properties provided an indication of its biological function. Hypomethylation of ATG4A and HIST1H2BN in OTICs predicts a poor prognosis for ovarian cancer patients.

Paired boxed gene 1 expression: A single potential biomarker for differentiating endometrial lesions associated with favorable outcomes in patients with endometrial carcinoma.

AIM: Paired boxed gene 1 (PAX1) has previously been reported to be a methylation-silenced gene in cases of cervical and ovarian cancers. We evaluated the expression of PAX1 in normal endometrium, endometrial hyperplasia and endometrial carcinoma (EC), and investigated the prognostic value of PAX1 expression in patients with EC. METHODS: We conducted a hospital-based retrospective review of PAX1 distribution immunohistochemically in 201 samples of endometrium from biopsy or hysterectomy. PAX1 immunoreactivity was classified into low and high score groups based upon the extent and intensity of staining. RESULTS: There was intense intranuclear staining for PAX1 in premalignant endometrial lesions. A high PAX1 score was observed in a high percentage of samples of normal endometrium (93.3%), in endometrial hyperplasia without atypia (97.2%) and in endometrial atypical hyperplasia (87.5%), but this level was found in only one-third of the EC samples (30.1%). The PAX1 protein score was significantly higher in samples of premalignant endometrial lesions compared with those of EC (P < 0.001). Importantly, a higher PAX1 score in EC cases was correlated with good overall survival, with a hazard ratio of 0.22 for death (95% confidence interval, 0.05-0.96). CONCLUSIONS: PAX1 protein expression is a potential histopathology biomarker for the differential diagnosis of malignant and premalignant endometrial lesions. PAX1 is also a potential prognostic marker in cases of EC.

Concordance analysis of methylation biomarkers detection in self-collected and physician-collected samples in cervical neoplasm.

BACKGROUND: Non-attendance at gynecological clinics is a major limitation of cervical cancer screening and self-collection of samples may improve this situation. Although HPV testing of self-collected vaginal samples is acceptable, the specificity is inadequate. The current focus is increasing self-collection of vaginal samples to minimize clinic visits. In this study, we analyzed the concordance and clinical performance of DNA methylation biomarker (PAX1, SOX1, and ZNF582) detection in self-collected vaginal samples and physician-collected cervical samples for the identification of cervical neoplasm. METHODS: We enrolled 136 cases with paired methylation data identified from abnormal Pap smears (n = 126) and normal controls (n = 10) regardless of HPV status at gynecological clinics. The study group comprised 37 cervical intraepithelial neoplasm I (CIN1), 23 cervical intraepithelial neoplasm II (CIN2), 16 cervical intraepithelial neoplasm III (CIN3), 30 carcinoma in situ (CIS), 13 squamous cell carcinomas (SCCs) and seven adenocarcinomas (ACs)/adenosquamous carcinomas (ASCs). PAX1, SOX1 and ZNF582 methylation in study samples was assessed by real-time quantitative methylation-specific polymerase chain reaction analysis. We generated methylation index cutoff values for the detection of CIN3+ in physician-collected cervical samples for analysis of the self-collected group. Concordance between the physician-collected and self-collected groups was evaluated by Cohen's Kappa. Sensitivity, specificity and area under curve (AUC) were calculated for detection of CIN3+ lesions. Finally, we produced an optimal cutoff value with the best sensitivity from the self-collected groups. RESULTS: We generated a methylation index cutoff value from physician-collected samples for detection of CIN3+. There were no significant differences in sensitivity, specificity of PAX1, SOX1 and ZNF582 between the self-collected and physician-collected groups. The methylation status of all three genes in the normal control samples, and the CIN 1, CIN2, CIN3, CIS, ACs/ASCs and SCC samples showed reasonable to good concordance between the two groups (κ = 0.443, 0.427, and 0.609 for PAX1, SOX1, and ZNF582, respectively). In determining the optimal cutoff values from the self-collected group, ZNF582 showed the highest sensitivity (0.77; 95%CI, 0.65-0.87) using a cutoff value of 0.0204. CONCLUSIONS: Methylation biomarker analysis of the three genes for detection of CIN3+ lesions shows reasonable to good concordance between the self-collected and physician-collected samples. Therefore, self-collection of samples could be adopted to decrease non-attendance and improve cervical screening.

Methylomics analysis identifies epigenetically silenced genes and implies an activation of ß-catenin signaling in cervical cancer.

Using DNA methylation biomarkers in cancer detection is a potential direction in clinical testing. Some methylated genes have been proposed for cervical cancer detection; however, more reliable methylation markers are needed. To identify new hypermethylated genes in the discovery phase, we compared the methylome between a pool of DNA from normal cervical epithelium (n = 19) and a pool of DNA from cervical cancer tissues (n = 38) using a methylation bead array. We integrated the differentially methylated genes with public gene expression databases, which resulted in 91 candidate genes. Based on gene expression after demethylation treatment in cell lines, we confirmed 61 genes for further validation. In the validation phase, quantitative MSP and bisulfite pyrosequencing were used to examine their methylation level in an independent set of clinical samples. Fourteen genes, including ADRA1D, AJAP1, COL6A2, EDN3, EPO, HS3ST2, MAGI2, POU4F3, PTGDR, SOX8, SOX17, ST6GAL2, SYT9, and ZNF614, were significantly hypermethylated in CIN3+ lesions. The sensitivity, specificity, and accuracy of POU4F3 for detecting CIN3+ lesions were 0.88, 0.82, and 0.85, respectively. A bioinformatics function analysis revealed that AJAP1, EDN3, EPO, MAGI2, and SOX17 were potentially implicated in ß-catenin signaling, suggesting the epigenetic dysregulation of this signaling pathway during cervical cancer development. The concurrent methylation of multiple genes in cancers and in subsets of precancerous lesions suggests the presence of a driver of methylation phenotype in cervical carcinogenesis. Further validation of these new genes as biomarkers for cervical cancer screening in a larger population-based study is warranted.

DNA methylation as a biomarker for the detection of hidden carcinoma in endometrial atypical hyperplasia.

OBJECTIVE: Women with atypical hyperplasia (AH) are often found to have endometrial carcinoma (EC) at hysterectomy. The purpose of this study was to evaluate whether the hypermethylation of specific genes found by methylomic approaches to the study of gynecologic cancers is a biomarker for EC in women with AH. METHODS: We evaluated the methylation of AJAP1, HS3ST2, SOX1, and PTGDR from 61 AH patients undergoing hysterectomy. Endometrial biopsy samples were analyzed by bisulfite conversion and quantitative methylation-specific polymerase chain reaction. A methylation index was used to predict the presence of cancer. To confirm the silencing effects of DNA methylation, immunohistochemical analysis of AJAP1, HS3ST2, and SOX1 was performed using tissue microarray. RESULTS: Fourteen (23%) patients had EC at hysterectomy. AJAP1, HS3ST2, and SOX1 were highly methylated in the EC patients' biopsy samples (p≤0.023). AJAP1, HS3ST2, and SOX1 protein expression was significantly higher in patients with AH only (p≤0.038). The predictive value of AJAP1, HS3ST2, and SOX1 methylation for EC was 0.81, 0.72, and 0.70, respectively. Combined testing of both AJAP1 and HS3ST2 methylation had a positive predictive value of 56%, methylation of any one of AJAP1, SOX1, or HS3ST2 had a 100% negative predictive value. CONCLUSIONS: Hypermethylation of AJAP1, HS3ST2, and SOX1 is predictive of EC in AH patients. Testing for methylation of these genes in endometrial biopsy samples may be a hysterectomy-sparing diagnostic tool. Validation of these new genes as biomarkers for AH screening in a larger population-based study is warranted.

Methylated ZNF582 gene as a marker for triage of women with Pap smear reporting low-grade squamous intraepithelial lesions - a Taiwanese Gynecologic Oncology Group (TGOG) study.

OBJECTIVE: Our previous work revealed that host genes ZNF582, PTPRR, PAX1, and SOX1 are highly methylated in cervical intraepithelial neoplasias grade 3 or worse (CIN3(+)). In this study, we used a standardized testing assay to evaluate the clinical efficacy of these biomarkers in the triage of cytological diagnoses of low-grade squamous intraepithelial lesions (LSILs), and compared the performance with human papillomavirus (HPV) testing. METHODS: This 2-year multicenter prospective study examined a population of 230 women from 12 medical centers who were diagnosed with LSILs on cervical cytology. Cervical scrapings were obtained prior to a colposcopy-directed biopsy for quantitative methylation analysis of ZNF582, PTPRR, PAX1, and SOX1, and HPV testing. Using logistic regression and receiver operating characteristic curve analyses, the abilities of methylated genes and HPV to predict CIN3(+) were assessed. RESULTS: Fifteen (6.5%) of the 230 women with a cytological diagnosis of LSIL were confirmed to have CIN3(+) after a colposcopy-directed biopsy. Among the 4 methylated genes, ZNF582 was found to be the best biomarker for detecting CIN3(+). The sensitivities for methylated ZNF582 and HPV testing were 73% and 80%, and the specificities were 71% and 28%, respectively. The odds ratio for predicting CIN3(+) using methylated ZNF582 was 6.8 (95% confidence interval (CI) 2.1-22.1), which was much better than HPV testing (OR=1.6, 95% CI 0.4-5.8). CONCLUSION: This is the first study to show that ZNF582 methylation analysis of cervical swabs may be a promising choice in the positive triage of cytological diagnoses of LSILs.

High methylation rate of LMX1A, NKX6-1, PAX1, PTPRR, SOX1, and ZNF582 genes in cervical adenocarcinoma.

OBJECTIVE: This study aimed to investigate the status of DNA methylation of 6 genes, LMX1A, NKX6-1, PAX1, PTPRR, SOX1, and ZNF582, previously found from squamous cell carcinomas in adenocarcinomas (ACs) of the uterine cervix. METHODS: We assessed the methylation status of these genes in 40 ACs, cervical scrapings from 23 ACs, and 67 normal control cervices by real-time quantitative methylation-specific polymerase chain reaction. The results were validated by bisulfite pyrosequencing. RESULTS: The methylation levels of all the 6 genes in the ACs were significantly higher than those in normal cervical tissues, especially for PAX1, PTPRR, SOX1, and ZNF582. The odds ratios and 95% confidence intervals (CIs) of high methylation levels in PAX1, PTPRR, SOX1, and ZNF582 for the risk of developing an AC were 15.7 (95% CI, 7.0-40.6), 16.9 (95% CI, 7.6-43.0), 32.1 (95% CI, 12.1-124.3), and 25.4 (95% CI, 10.4-78.3), respectively (all P < 0.001). The methylation indices of PAX1, PTPRR, SOX1, and ZNF582 recovered from scrapings of ACs were significantly higher than in normal controls. The odds ratios of these indices for the risk of developing an AC in PAX1, PTPRR, SOX1, and ZNF582 were 6.2 (95% CI, 2.6-15.4), 12.1(95% CI, 3.8-46.4), 6.2 (95% CI, 2.6-15.8), and 20.6 (95% CI, 6.9-77.5), respectively (all P < 0.001). CONCLUSIONS: Cervical ACs carry aberrantly high methylation rates of PAX1, PTPRR, SOX1, and ZNF582--commonly methylated in squamous cell carcinomas--which might help for AC screening.

Deep learning to assess microsatellite instability directly from histopathological whole slide images in endometrial cancer.

Molecular classification, particularly microsatellite instability-high (MSI-H), has gained attention for immunotherapy in endometrial cancer (EC). MSI-H is associated with DNA mismatch repair defects and is a crucial treatment predictor. The NCCN guidelines recommend pembrolizumab and nivolumab for advanced or recurrent MSI-H/mismatch repair deficient (dMMR) EC. However, evaluating MSI in all cases is impractical due to time and cost constraints. To overcome this challenge, we present an effective and efficient deep learning-based model designed to accurately and rapidly assess MSI status of EC using H&E-stained whole slide images. Our framework was evaluated on a comprehensive dataset of gigapixel histopathology images of 529 patients from the Cancer Genome Atlas (TCGA). The experimental results have shown that the proposed method achieved excellent performances in assessing MSI status, obtaining remarkably high results with 96%, 94%, 93% and 100% for endometrioid carcinoma G1G2, respectively, and 87%, 84%, 81% and 94% for endometrioid carcinoma G3, in terms of F-measure, accuracy, precision and sensitivity, respectively. Furthermore, the proposed deep learning framework outperforms four state-of-the-art benchmarked methods by a significant margin (p < 0.001) in terms of accuracy, precision, sensitivity and F-measure, respectively. Additionally, a run time analysis demonstrates that the proposed method achieves excellent quantitative results with high efficiency in AI inference time (1.03 seconds per slide), making the proposed framework viable for practical clinical usage. These results highlight the efficacy and efficiency of the proposed model to assess MSI status of EC directly from histopathological slides.

Effectiveness of high-intensity focused ultrasound combined with gonadotropin-releasing hormone agonist or combined with levonorgestrel-releasing intrauterine system for adenomyosis: A systematic review and meta-analysis.

Gonadotropin-Releasing Hormone Agonist (GnRH-a) and levonorgestrel releasing intrauterine system (LNG-IUS) are conventional conservative treatments for adenomyosis, and high-intensity focused ultrasound (HIFU) is a novel ablation technique. This study aimed to investigate the effectiveness of HIFU combined with GnRH-a or LNG-IUS for adenomyosis patients. In this systematic review and meta-analysis, Pubmed, Embase, Cochrane Library and Scopus databases were searched up to December 2021. Published studies comparing HIFU plus GnRH-a with HIFU plus LNG-IUS in adenomyosis patients were assessed for eligibility by two independent authors. Risk of bias tool was utilized for risk evaluation. We selected treatment effective rate of dysmenorrhea (pain during menstruation) as the primary outcome; effective rate of menorrhagia severity and reduction rate of adenomyotic lesion as the secondary outcomes. Adverse effects were assessed. Four studies with a total 729 patients were enrolled in the meta-analysis. HIFU plus LNG-IUS showed lower dysmenorrhea [within 6 months: risk ratio (RR) 0.88, 95% confidence interval (CI) 0.83-0.93, p < 0.00001; over 1 year: RR 0.73, 95% CI 0.65-0.82, p < 0.00001] and less menorrhagia severity (RR 0.63, 95% CI 0.60-0.66, p < 0.00001) than HIFU plus GnRH-a. Both groups demonstrated equal efficacy in adenomyotic lesion reduction rate (RR 1.03, 95% CI 0.97-1.09, p = 0.30). Adverse effects happened equally in both groups. Combination therapy of HIFU and LNG-IUS revealed better effectiveness in treating dysmenorrhea and menorrhagia than that of HIFU and GnRH-a. However, interpreting the conclusion should be approached with caution as a result of significant heterogeneity.

Ensemble transformer-based multiple instance learning to predict pathological subtypes and tumor mutational burden from histopathological whole slide images of endometrial and colorectal cancer.

In endometrial cancer (EC) and colorectal cancer (CRC), in addition to microsatellite instability, tumor mutational burden (TMB) has gradually gained attention as a genomic biomarker that can be used clinically to determine which patients may benefit from immune checkpoint inhibitors. High TMB is characterized by a large number of mutated genes, which encode aberrant tumor neoantigens, and implies a better response to immunotherapy. Hence, a part of EC and CRC patients associated with high TMB may have higher chances to receive immunotherapy. TMB measurement was mainly evaluated by whole-exome sequencing or next-generation sequencing, which was costly and difficult to be widely applied in all clinical cases. Therefore, an effective, efficient, low-cost and easily accessible tool is urgently needed to distinguish the TMB status of EC and CRC patients. In this study, we present a deep learning framework, namely Ensemble Transformer-based Multiple Instance Learning with Self-Supervised Learning Vision Transformer feature encoder (ETMIL-SSLViT), to predict pathological subtype and TMB status directly from the H&E stained whole slide images (WSIs) in EC and CRC patients, which is helpful for both pathological classification and cancer treatment planning. Our framework was evaluated on two different cancer cohorts, including an EC cohort with 918 histopathology WSIs from 529 patients and a CRC cohort with 1495 WSIs from 594 patients from The Cancer Genome Atlas. The experimental results show that the proposed methods achieved excellent performance and outperforming seven state-of-the-art (SOTA) methods in cancer subtype classification and TMB prediction on both cancer datasets. Fisher's exact test further validated that the associations between the predictions of the proposed models and the actual cancer subtype or TMB status are both extremely strong (p<0.001). These promising findings show the potential of our proposed methods to guide personalized treatment decisions by accurately predicting the EC and CRC subtype and the TMB status for effective immunotherapy planning for EC and CRC patients.

Hyperventilation accelerates rise in arterial blood concentrations of sevoflurane in gynecologic patients.

PURPOSE: We investigated whether ventilation volumes affected arterial blood sevoflurane concentration (A (sev)) and its uptake into the body during general anesthesia. METHODS: Thirty female patients undergoing elective gynecologic surgery were randomly allocated into three groups: hyperventilation, normal ventilation, and hypoventilation. Inspiratory (CI(sev)) and end-tidal ((sev)) sevoflurane concentrations were routinely measured by infrared analysis, and A (sev) were analyzed by gas chromatography for 40 min after intubation. Cardiac index and total peripheral vascular resistance were measured with a Finometer. RESULTS: During the first 10 min after sevoflurane administration, A (sev) in the hyperventilation group was the highest and differed significantly from those in the normal ventilation group, followed by those in the hypoventilation group. In addition, hyperventilation significantly increased the slope of A (sev) over time in the first 5 min, but there were no differences in slopes in the 5-10, 10-20, and 20-40 min periods, which indicates no difference in sevoflurane bodily uptake among the three groups after 5 min. CONCLUSION: Hyperventilation accelerated the rate of A (sev) increase immediately after sevoflurane administration, which was time dependent with respect to different alveolar ventilation levels.

Robotic Hysterectomy with Ureter Identification and Uterine Artery Ligation for Benign Gynecological Conditions: An Early-Year Single-Center Experience.

The use and application of robotic systems with a high-definition, three-dimensional vision system and advanced EndoWrist technology have become widespread. We sought to share our clinical experience with ureter identification and preventive uterine artery ligation in robotic hysterectomy. The records of patients undergoing robotic hysterectomy between May 2014 and December 2015, including patient preoperative characteristics, operative time, and postoperative outcomes, were analyzed. We evaluated the feasibility and safety of using early ureteral identification and preventive uterine artery ligation in robotic hysterectomy in patients with benign gynecological conditions. Overall, 49 patients diagnosed with benign gynecological conditions were evaluated. The mean age of the patients and mean uterine weight were 46.2 ± 5.3 years and 348.7 ± 311.8 g, respectively. Robotic hysterectomy achieved satisfactory results, including a short postoperative hospital stay (2.7 ± 0.8 days), low conversion rate (n = 0), and low complication rate (n = 1; 2%). The average estimated blood loss was 109 ± 107.2 mL. Our results suggest that robotic hysterectomy using early ureteral identification and preventive uterine artery ligation is feasible and safe in patients with benign gynecological conditions.

A long-term follow-up study of 176 cases with adult-type ovarian granulosa cell tumors.

OBJECTIVE: Because of rarity, indolent clinical course, and of most importance, small sample size studies of previous ovarian granulosa cell tumors (GCTs), this study was conducted to report the clinical characteristics and long-term outcomes of 176 pathologically confirmed GCTs. METHODS: Between 1984 and 2010, we retrospectively evaluated 176 patients from multiple medical centers in Taiwan. RESULTS: The mean age at the diagnosis was 46 years and nearly half of the patients (45.7%) were in their fourth or fifth decades of life. The most common symptoms included abdominal pain (28.5%), followed by irregular menstruation (16.7%). The mean tumor size was 10.4 cm. The stage distribution at diagnosis was stage I in 77.8% of patients, stage II in 5.1%, stages III-V in 6.1%, and unknown in 11% of patients. The median follow-up period was 60.7 months. The recurrence rate was 21%. The overall 5- and 10-year survival rates were 96.5% and 94.1%, respectively. In univariate analysis, initial stage, presence of residual tumor after initial surgery, need for adjuvant chemotherapy, and tumor size were associated with disease recurrence. In the multivariate analysis, only the presence of residual tumor after initial surgery and tumor size were significantly associated with recurrence. CONCLUSIONS: The outcomes of patients with GCTs were good, with nearly to 95% of patients surviving 5 and 10 years. The prognosis was related to initial stage, presence of residual tumor after initial surgery, and tumor size (>13.5 cm). Different surgical methods and/or adjuvant therapy appear not to affect the outcome.

Predicting Long-Term Prognoses and Grading Platinum Sensitivity Using a Novel Progression-Free Interval Criterion in Ovarian Clear Cell Carcinoma: A Multi-Institutional Cohort Study.

This large-scale study aimed to determine the long-term influences of potential prognostic predictors and progression-free interval (PFI) criteria for grading platinum-sensitivity in ovarian clear cell carcinoma (OCCC). We retrospectively reviewed the medical records of OCCC patients presenting at nine tertiary centres (1995−2015), and evaluated patient characteristics, therapeutic factors, clinical outcomes, and hazard ratios for disease progression and death. We enrolled 536 patients (median follow-up, 36.6 months) and developed newly defined distributions of PFIs (seven and 14 months) for grading platinum sensitivity. In the multivariate model, preoperative CA125 levels and chemo-response independently predicted early-stage progression-free survival (PFS) risk. Post-progression cytoreduction correlated with reduced mortality risk. No unfavourable outcomes were observed with respect to coexisting endometriosis, fertility-sparing strategies, or platinum-based regimens. A PFI of <7 months, the strongest predictor of both post-progression mortality and second relapse risks, correlated with chemo-resistance, advanced tumour stage, and shortened post-progression survival. Chemotherapy regimens commonly used in front-line or relapse settings were limited in improving prognoses, especially in the advanced-stage cohort. Clinical trials of novel targeted agents and/or innovative biomarkers for chemoresistance should be comprehensively investigated and offered early to advanced-stage patients or those with OCCC progression occurring within seven months after receiving chemotherapy.