Immune Subtypes and Immune Landscape Analysis of Endometrial Carcinoma.

Some patients with endometrial cancer (EC) suffer from limited survival benefits after immunotherapy, suggesting that there may be a specific pattern associated with immunotherapy. Immune-related genes were extracted from The Cancer Genome Atlas databases. We analyzed the differences among immune subtypes (ISs) in the distribution of the tumor mutational burden, chemotherapy-induced immune response markers, immune checkpoint-related genes, immunotherapy, and chemotherapy. We applied dimensionality reduction and defined the immune landscape of EC. Then, we used the Weighted Gene Co-Expression Network Analysis package to identify the coexpression modules of these immune genes. Finally, hub genes were selected and detected by quantitative PCR and immunohistochemistry. We obtained three ISs. There were differences in the distribution of the tumor mutational burden, chemotherapy-induced immune response markers, and immune checkpoint-related genes among the ISs. Regarding immunotherapy and chemotherapy, the IS2 subtypes were more sensitive to programmed cell death protein 1 inhibitors. In addition, different positions in the immune landscape map exhibited different prognostic characteristics, providing further evidence of the ISs. The IS2 subtypes were significantly positively correlated with yellow module gene list, indicating a good prognosis with high score. SIRPG and SLAMF1 were identified as the final characteristic genes. The quantitative PCR and immunohistochemistry results showed that the expression levels of SIRPG and SLAMF1 were low in human EC tissue. In this study, we identified three reproducible ISs of EC. The immune landscape analysis further revealed the intraclass heterogeneity of the ISs. SIRPG and SLAMF1 were identified to be associated with progression, suggesting that they may be novel immune-related biomarkers of EC.

CircNUP50 is a novel therapeutic target that promotes cisplatin resistance in ovarian cancer by modulating p53 ubiquitination.

BACKGROUND: Most patients with ovarian cancer (OC) treated with platinum-based chemotherapy have a dismal prognosis owing to drug resistance. However, the regulatory mechanisms of circular RNA (circRNA) and p53 ubiquitination are unknown in platinum-resistant OC. We aimed to identify circRNAs associated with platinum-resistant OC to develop a novel treatment strategy. METHODS: Platinum-resistant circRNAs were screened through circRNA sequencing and validated using quantitative reverse-transcription PCR in OC cells and tissues. The characteristics of circNUP50 were analysed using Sanger sequencing, oligo (dT) primers, ribonuclease R and fluorescence in situ hybridisation assays. Functional experimental studies were performed in vitro and in vivo. The mechanism underlying circNUP50-mediated P53 ubiquitination was investigated through circRNA pull-down analysis and mass spectrometry, luciferase reporters, RNA binding protein immunoprecipitation, immunofluorescence assays, cycloheximide chase assays, and ubiquitination experiments. Finally, a platinum and si-circNUP50 co-delivery nanosystem (Psc@DPP) was constructed to treat platinum-resistant OC in an orthotopic animal model. RESULTS: We found that circNUP50 contributes to platinum-resistant conditions in OC by promoting cell proliferation, affecting the cell cycle, and reducing apoptosis. The si-circNUP50 mRNA sequencing and circRNA pull-down analysis showed that circNUP50 mediates platinum resistance in OC by binding p53 and UBE2T, accelerating p53 ubiquitination. By contrast, miRNA sequencing and circRNA pull-down experiments indicated that circNUP50 could serve as a sponge for miR-197-3p, thereby upregulating G3BP1 to mediate p53 ubiquitination, promoting OC platinum resistance. Psc@DPP effectively overcame platinum resistance in an OC tumour model and provided a novel idea for treating platinum-resistant OC using si-circNUP50. CONCLUSIONS: This study reveals a novel molecular mechanism by which circNUP50 mediates platinum resistance in OC by modulating p53 ubiquitination and provides new insights for developing effective therapeutic strategies for platinum resistance in OC.

Prognostic evaluation models for primary thyroid lymphoma, based on the SEER database and an external validation cohort.

PURPOSE: Primary thyroid lymphoma (PTL) is a rare malignancy, and the literature is limited to small case series and case reports. This study aimed to assess the epidemiologic characteristics, survival, and prognostic factors of patients with PTL. METHODS: We analyzed 2215 PTL patients from the Surveillance, Epidemiology, and End Results database medical records, between 1983 and 2015, as the training cohort. We enrolled 105 patients from the Cancer Hospital, Chinese Academy of Medical Sciences, for the external validation cohort. The nomograms for predicting the 1-, 5-, and 10-year overall survival (OS) and lymphoma-specific survival (LSS) were constructed. RESULTS: PTL incidence steadily increased from 1977 to 1994, with an annual percentage change of 3.2% (95% confidence interval [CI]: 1.2-5.2, P < 0.05). The 1-, 5-, and 10-year OS and LSS rates were 84.66%, 71.61%, and 55.95%; and 90.5%, 85.7%, and 82.2%, respectively. Multivariate Cox regression analysis revealed that shorter OS association with age ≥ 60 years (hazard ratio [HR], 3.94; 95% CI 3.31-4.69; P < 0.001), unmarried status (HR, 1.55; 95% CI 1.37-1.75; P < 0.001), Ann Arbor stage III-IV (HR, 1.55; 95% CI 1.37-1.75; P = 0.020), diffuse large B-cell lymphoma (HR, 2.60; 95% CI 1.15-5.87; P = 0.022), and T cell non-Hodgkin lymphoma (HR, 3.53; 95% CI 1.12-11.10; P = 0.031). In the multivariate competing-risk analyzes, age, stages III-IV, year of diagnosis, surgery, radiation, chemotherapy, and histology were strongly predictive of PTL-specific risk of death. To estimate the 1-, 5-, and 10-year LSS and OS rates, respectively, nomograms were built. In the validation cohort, the results also confirmed the utility. CONCLUSIONS: This study presents the first prognostic model with an external validation that could help clinicians identify patients with high-risk PTL to improve their prognosis.

Agitation Prevalence in People With Dementia in Australian Residential Aged Care Facilities: Findings From Machine Learning of Electronic Health Records.

Using a suite of artificial intelligence technologies, the current study sought to determine the prevalence of agitated behaviors in people with dementia in residential aged care facilities (RACFs) in Australia. Computerized natural language processing allowed extraction of agitation instances from the free-text nursing progress notes, a component of electronic health records in RACFs. In total, 59 observable agitated behaviors were found. No difference was found in dementia prevalence between female and male clients (44.1%), across metropolitan and regional facilities (42.1% [SD = 17.9%]), or for agitation prevalence in dementia (76.5% [SD = 18.4%]). The top 10 behaviors were resisting, wandering, speaking in excessively loud voice, pacing, restlessness, pushing, shouting, complaining, frustration, and using profane language. Four to 17 agitated behaviors coexisted in 53% of people with dementia agitation, indicating high caregiver burden in these RACFs. Improving workforce training and redesigning care models are urgent for sustainability of dementia care in RACFs. [Journal of Gerontological Nursing, 48(4), 57-64.].

A Five-Step Workflow to Manually Annotate Unstructured Data into Training Dataset for Natural Language Processing.

Natural Language Processing (NLP) is a powerful technique for extracting valuable information from unstructured electronic health records (EHRs). However, a prerequisite for NLP is the availability of high-quality annotated datasets. To date, there is a lack of effective methods to guide the research effort of manually annotating unstructured datasets, which can hinder NLP performance. Therefore, this study develops a five-step workflow for manually annotating unstructured datasets, including (1) annotator training and familiarising with the text corpus, (2) vocabulary identification, (3) annotation schema development, (4) annotation execution, and (5) result validation. This framework was then applied to annotate agitation symptoms from the unstructured EHRs of 40 Australian residential aged care facilities. The annotated corpus achieved an accuracy rate of 96%. This suggests that our proposed annotation workflow can be used in manual data processing to develop annotated training corpus for developing NLP algorithms.

Extracting Symptoms of Agitation in Dementia from Free-Text Nursing Notes Using Advanced Natural Language Processing.

Nursing staff record observations about older people under their care in free-text nursing notes. These notes contain older people's care needs, disease symptoms, frequency of symptom occurrence, nursing actions, etc. Therefore, it is vital to develop a technique to uncover important data from these notes. This study developed and evaluated a deep learning and transfer learning-based named entity recognition (NER) model for extracting symptoms of agitation in dementia from the nursing notes. We employed a Clinical BioBERT model for word embedding. Then we applied bidirectional long-short-term memory (BiLSTM) and conditional random field (CRF) models for NER on nursing notes from Australian residential aged care facilities. The proposed NER model achieves satisfactory performance in extracting symptoms of agitation in dementia with a 75% F1 score and 78% accuracy. We will further develop machine learning models to recommend the optimal nursing actions to manage agitation.

Developing an Instrument to Evaluate the Quality of Dementia Websites.

In today's digital era, health information, especially for conditions like dementia, is crucial. This study aims to develop an instrument, demenTia wEbsite measSurement insTrument (TEST), through four steps: identifying existing instruments, determining criteria, selecting and revising measurement statements, and validating the instrument from March to August 2020. Five health informatics experts used the content validity ratio (CVR) test for validation. Thirteen evaluators compared Fleiss Kappa and intraclass correlation coefficient (ICC) values across four dementia websites using TEST and another tool, DISCERN. TEST consists of seven criteria and 25 measurement statements focusing on content quality (relevance, credibility, currency) and user experience (accessibility, interactivity, attractiveness, privacy). CVR = 1 confirmed all statements as essential. The TEST demonstrated stronger consistency and assessor agreement compared to DISCERN, measured by Fleiss Kappa and ICC. Overall, it is a robust tool for reliable and user-friendly dementia resources, ensuring health holistic information accessibility.

Establishing Molecular Subgroups of CD8+ T Cell-Associated Genes in the Ovarian Cancer Tumour Microenvironment and Predicting the Immunotherapy Response.

BACKGROUND: The mechanism by which infiltrating CD8+ T lymphocytes in the tumour microenvironment influence the survival of patients with ovarian cancer (OC) remains unclear. METHODS: To identify biomarkers to optimise OC treatment, 13 immune-cell-line-associated datasets, RNA sequencing data, and clinical data from the GEO, TCGA, and the ICGC were collected. Gene expression in OC was assessed using quantitative reverse transcription polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) staining. RESULTS: We identified 520 genes and three immunological clusters (IC1, IC2, and IC3) associated with CD8+ T cells. Higher IFN scores, immune T cell lytic activity, and immune cell infiltration and upregulated expression of immune-checkpoint-related genes indicated that IC3 is more responsive to immunotherapy, whereas IC1 and IC2 have a poorer prognosis. A 10-gene signature, including SEMA4F, CX3CR1, STX7, PASK, AKIRIN2, HEMGN, GBP5, NSG1, and CXorf65, was constructed, and a multivariate Cox regression analysis revealed a significant association between the 10-gene signature-based risk model and overall survival (p < 0.001). A nomogram was constructed with age and the 10-gene signature. Consistent with the bioinformatics analysis, IHC and qRT-PCR confirmed the accuracy of the signatures in OC tissue samples. The predictive ability of the risk model was demonstrated using the Imvigor210 immunotherapy dataset. CONCLUSIONS: The development of a novel gene signature associated with CD8+ T cells could facilitate more accurate prognostics and prediction of the immunotherapeutic response of patients with OC.

ALKBH5-mediated m6A modification of circCCDC134 facilitates cervical cancer metastasis by enhancing HIF1A transcription.

BACKGROUND: Metastasis is the main cause of mortality in cervical cancer (CC). Circular RNAs (circRNAs) have been demonstrated to play a crucial role in carcinoma biology. However, the expression and function of circRNAs in cervical cancer metastasis are still unclear. METHODS: In the present study, we identified a circRNA with an N6-methyladenosine (m6A) modification, circCCDC134, whose expression was increased in CC tissues by circRNA-Seq and qPCR. CircCCDC134 upregulation in CC was fine-tuned by ALKBH5-mediated m6A modification, which enhanced its stability in a YTHDF2-dependent manner. The functional experiments illustrated that circCCDC134 enhanced tumour proliferation and metastasis in vitro and in vivo. For the comprehensive identification of RNA-binding proteins, circRNA pull-down and mass spectrometry (ChIRP-MS), chromatin immunoprecipitation-seq (Chip-seq), RNA binding protein immunoprecipitation (RIP) and luciferase reporter assays were used to perform mechanistic investigations. RESULTS: The results revealed that circCCDC134 recruited p65 in the nucleus and acted as a miR-503-5p sponge to regulate the expression of MYB in the cytoplasm, ultimately stimulating HIF1A transcription and facilitating CC growth and metastasis. CONCLUSION: These findings indicate that circCCDC134 is an important therapeutic target and provide new regulatory model insights for exploring the carcinogenic mechanism of circCCDC134 in CC.

Establishment of a molecular risk model for the prognosis of cervical cancer based on microRNA expression.

Background: Globally, the incidence of cervical cancer (CC) is highest among all tumors of the female reproductive system. Numerous studies have shown that the expression level of microRNA (miRNA) is highly correlated with cancer. This study aimed to establish a molecular prognostic model of CC based on miRNAs in order to provide more individualized treatment to CC patients. Methods: Human tissues were selected from the Cancer Hospital (Chinese Academy of Medical Sciences and Peking Union Medical College) for miRNA gene sequencing. CC transcriptome expression and clinical data were downloaded from The Cancer Genome Atlas (TCGA). We distinguished between common differentially expressed miRNAs of CC miRNA-seq and TCGA-CC. To obtain a molecular prognostic model, R package was used to perform univariate Cox proportional hazard regression and least absolute shrinkage and selection operator (LASSO) Cox regression for common differentially-expressed miRNAs. Next, the model performance was evaluated by survival analysis, receiver operating characteristic (ROC) curve analysis, as well as univariate and multivariate analyses in the TCGA-CC dataset. Quantitative Real-time polymerase chain reaction (qPCR) detection was to verify the expression changes of miRNA. Transwell was used to verify the role of molecules in CC cell migration and invasion. Results: Thirty-nine miRNAs were distinguished in TCGA-CC and CC miRNA-seq, LASSO regression analysis to obtain the risk model (risk score =-0.310× expression of hsa-miR-142-3p +0.439× expression of hsa-miR-100-3p). The survival analysis, ROC curve analysis, patient risk assessment, and univariate and multivariate analyses showed that the risk score model had good predictive ability in assessing patient survival (P<0.01), risk of death, and independent prognosis (P<0.01). qPCR detection of clinical samples and cells showed that the expression of hsa-miR-142-3p and hsa-miR-100-3p was consistent with the results of the database analysis. The Transwell results indicated that miR-142-3p is an inhibiting factor and miR-100-3p serves as a promoting factor in CC cell migration and invasion. Conclusions: Twelve miRNA-seq and TCGA-CC tissues were used to build a prognostic model for CC. We have obtained a two-miRNA risk score model. Our results provide a new strategy for the individualized diagnosis and treatment of CC.

Characteristics of TP53 germline variants and their correlations with Li-Fraumeni syndrome or Li-Fraumeni-like syndrome in Chinese tumor patients.

Li-Fraumeni syndrome (LFS), a rare autosomal-dominant inheritance condition, is associated with a family cancer history as well as pathogenic/likely-pathogenic TP53 germline variants (P/LP TP53 GV). The current clinical methods for detecting LFS are limited. Here, we retrospectively investigate P/LP TP53 GV among Chinese cancer patients by next-generation sequencing and evaluate its relationship with a family cancer history. A total of 270 out of 19,226 cancer patients have TP53 GV, including 53 patients with P/LP TP53 GV. Patients with P/LP TP53 GV are mainly found in male with glioma, lung cancer or sarcoma. The median age of diagnosis for P/LP TP53 GV patients is significantly lower than that of non-P/LP TP53 GV patients (31-years vs. 53-years; P < 0.01). One LFS patient and 3 Li-Fraumeni-like syndrome (LFL) patients are among the 26 followed-up P/LP TP53 GV patients. Among 25 types of P/LP TP53 GV, the highest variant frequencies occurred at codon 175 and 248. p.M237I, p.R158H, p.C238Y and p.C275R, are firstly identified among the Chinese LFS/LFL patients. This study reports the (P/LP) TP53 GV characteristics of Chinese pan-cancer patients. These findings suggest analyzing the P/LP TP53 GV in cancer patients is an effective strategy for identifying cancer predisposition syndrome.

Developing Methods to Evaluate Content Quality of Dementia Websites.

With the popularity of the Internet, consumers are likely to resort to websites for dementia information. However, they may not have the knowledge or experience in distinguishing quality information from opinion pieces. This study investigated the developing methods, instruments and parameters for evaluating the content quality of dementia websites. By reviewing 18 existing instruments from the relevant literature, we identified four developing methods - questionnaire survey, automatic evaluation, Delphi method and focus group discussion. These instruments include six parameters - reliability, currency, readability, disclosure, objectivity and relevance - to evaluate the content quality. With the significant social and economic impact of dementia, developing specific instruments to measure the content quality of dementia websites is necessary.

Nimotuzumab plus platinum-based chemotherapy versus platinum-based chemotherapy alone in patients with recurrent or metastatic nasopharyngeal carcinoma.

BACKGROUND: Palliative chemotherapy has been the mainstay treatment for patients with recurrent or metastatic nasopharyngeal carcinoma (R/M-NPC). However, little is known about the efficacy and toxicity of nimotuzumab (NTZ) - a monoclonal antibody drug targeting epidermal growth factor receptor - plus chemotherapy (CT) versus CT alone for these patients. METHODS: The database at Cancer Hospital of Chinese Academy of Medical Sciences was queried for patients diagnosed with NPC who received CT with or without NTZ between 2004 and 2018. Treatment compliance, survival outcomes, and adverse effects were compared among these groups. RESULTS: Records of 70 patients with R/M-NPC were reviewed: 21 (30%) received NTZ plus CT (NTZ+CT) and 49 (70%) received CT. CT regimens included gemcitabine plus platinum, taxane plus platinum (TP), and fluorouracil plus platinum. Comparing the CT group with NTZ+CT group, the median follow up was 62 months (range = 3-133) versus 59 months (range = 9-117); median progression free survival was 7.5 [95% confidence interval (CI) 6.552-8.381] months versus 8.5 (95% CI 6.091-10.976) months, p = 0.424; median overall survival (OS) was 25.6 (95% CI 18.888-32.379) months versus 48.6 (95% CI 35.619-61.581) months, p = 0.017, respectively. Multivariable analysis established treatment group (CT versus NTZ+CT) as an independent prognostic factor for OS (hazard ratio, 0.5; 95% CI 0.255-0.979; p = 0.043). No significant difference with regard to toxicities was observed between the two groups. Among them, a subgroup analysis was performed in 53 (75.7%) patients who received TP with or without NTZ, which showed similar results. CONCLUSION: Our findings suggested that NTZ+CT provides a novel treatment option and prolongs survival significantly for R/M-NPC.