A web-based nomogram to predict overall survival for postresection leiomyosarcoma patients with lung metastasis.

To investigate the overall survival of post-resection leiomyosarcoma (LMS) patients with lung metastasis, data of post-resection LMS patients with lung metastasis between 2010 and 2016 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The clinical characteristics and survival data for post-resection LMS patients with lung metastasis at Tianjin Medical University Cancer Hospital & Institute (TJMUCH) between October 2010 and July 2018 were collected. Patients derived from the SEER database and TJMUCH were divided into training and validation cohorts, respectively. Univariate and multivariate Cox regression analyses were performed and a nomogram was established. The area under the curve (AUC) and the calibration curve were used to evaluate the nomogram. A web-based nomogram was developed based on the established nomogram. Eventually, 226 patients from the SEER database who were diagnosed with LMS and underwent primary lesion resection combined with lung metastasis were enrolled in the training cohort, and 17 patients from TJMUCH were enrolled in the validation cohort. Sex, race, grade, tumor size, chemotherapy, and bone metastasis were correlated with overall survival in patients with LMS. The C-index were 0.65 and 0.75 in the SEER and Chinese set, respectively. Furthermore, the applicable AUC values of the ROC curve in the SEER cohort to predict the 1-, 3-, 5- years survival rate were 0.646, 0.682, and 0.689, respectively. The corresponding AUC values in the Chinese cohort were 0.970, 0.913, and 0.881, respectively. The calibration curve showed that the nomogram performed well in predicting the overall survival in post-resection LMS patients with lung metastasis. A web-based nomogram (https://weijunqiang.shinyapps.io/survival_lms_lungmet/) was established. The web-based nomogram (https://weijunqiang.shinyapps.io/survival_lms_lungmet/) is an accurate and personalized tool for predicting the overall survival of post-resection LMS with lung metastasis.

Comparison of various prediction models in the effect of Roux-en-Y gastric bypass on type 2 diabetes in the Chinese population 5 years after surgery.

BACKGROUND: Various prediction models of type 2 diabetes (T2D) remission have been externally verified internationally. However, long-term validated results after Roux-en-Y gastric bypass (RYGB) surgery are lacking. The best model for the Chinese population is also unknown. OBJECTIVES: To evaluate the prediction effect of various prediction models on the long-term diabetes remission after RYGB in the Chinese population and to provide reference for clinical use. SETTING: A retrospective clinical study at a university hospital. METHODS: We retrospectively analyzed Chinese population data 5 years after RYGB and externally validated 11 predictive models to evaluate the predictive effect of each model on long-term T2D remission after RYGB. RESULTS: We enrolled 84 patients. The mean body mass index was 41 kg/m2, and the percentage of excess weight loss (%EWL) was 72.3%. The mean glycated hemoglobin level was 8.4% preoperatively and decreased to 5.9% after 5 years. The 5-year postoperative complete and partial remission rates of T2D were 31% and 70.2%, respectively. The ABCD scoring model (sensitivity, 84%; specificity, 76%; area under the curve [AUC], .866) and the Panuzi et al. [34] study (sensitivity, 84%; specificity, 81%; AUC, .842) showed excellent results. In the Hosmer-Lemeshow goodness-of-fit test, calibration values for ABCD and Panuzi et al. [34] were .14 and .21, respectively. The predicted-to-observed ratios of ABCD and Panuzi et al. [34] were .83 and .88, respectively. CONCLUSIONS: T2D was relieved to varying degrees 5 years after RYGB in patients with obesity. The prediction models in ABCD and the Panuzi et al. [34] studies showed the best prediction effects. ABCD was recommended for clinical use because of excellent predictive performance, good statistical test results, and simple and practical design features.

Analysis of Correlation between Age and Satisfied Total Weight Loss Percentage Outcome at 1 Year after Bariatric Surgery using the Restricted Cubic Spline Function: A Retrospective Study in China.

OBJECTIVE: This study aims to explore the relationship between age and whether the percentage of total weight loss (TWL%) is ≥ 25% or not at 1 year after bariatric surgery (BS). We aimed to provide evidence for the stratified treatment of spatients with obesity at different ages. METHODS: The primary outcome evaluated was whether TWL% was no less than 25% at 1 year after BS. A TWL% ≥ 25% was defined as a satisfied TWL% outcome. Logistic regression analysis and the restricted cubic spline (RCS) function were used to analyze the relationship between age and the satisfied TWL% outcome at 1 year after BS. RESULTS: Two hundred and ninety-one patients were included in our study. After adjusting for potential confounders, the odds ratios (ORs) of the corresponding quartiles of age associated with satisfied TWL% outcome were 1.00 (reference), 1.117 [95% confidence interval (95% CI) = 0.540-2.311], 1.378 (95% CI = 0.647-2.935), and 0.406 (95% CI = 0.184-0.895). RCS analysis revealed a non-linear inverted L-shaped association between age and satisfied TWL% outcome at 1 year after BS (non-linear P = 0.033). CONCLUSION: Age was an independent predictor of satisfied TWL% outcome one year following BS, and our study considered 32 years as a potential cut-off point. For Chinese patients over the age of 32 who are eligible for BS, it may be beneficial to do BS earlier as the probability of achieving a satisfied TWL% outcome may decrease with age.

Web-based nomogram to predict postresection risk of distant metastasis in patients with leiomyosarcoma: retrospective analysis of the SEER database and a Chinese cohort.

OBJECTIVES: This study investigated risk factors and constructed an online tool to predict distant metastasis (DM) risk in patients with leiomyosarcoma (LMS) after surgical resection. METHODS: Data regarding patients with LMS who underwent surgical resection between 2010 and 2018 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Data were collected regarding patients with LMS who underwent surgical resection at Tianjin Medical University Cancer Hospital and Institute (TJMUCH) between October 2010 and July 2018. Patients were randomly divided into training and validation sets. Logistic regression analyses were performed; a nomogram was established. The area under the curve (AUC) and calibration curve were used to evaluate the nomogram, which served as the basis for a web-based nomogram. RESULTS: This study included 4461 and 76 patients from the SEER database and TJMUCH, respectively. Age, ethnicity, grade, T stage, N stage, radiotherapy, and chemotherapy were associated with DM incidence. C-index values were 0.815 and 0.782 in the SEER and Chinese datasets, respectively; corresponding AUC values were 0.814 and 0.773, respectively. A web-based nomogram (https://weijunqiang-leimyosarcoma-seer.shinyapps.io/dynnomapp/) was established. CONCLUSIONS: Our web-based nomogram is an accurate and user-friendly tool to predict DM risk in patients with LMS; it can aid clinical decision-making.

Network pharmacology-based research on the effect of angelicin on osteosarcoma and the underlying mechanism.

To explore the antitumor effects of angelicin on osteosarcoma and the underlying mechanism. We aimed to elucidate the mechanism by network pharmacology, molecular docking, and in vitro experiments. We analyzed a PPI network of potential angelicin targets in the treatment of osteosarcoma and identified hub targets. We systematically performed GO and KEGG enrichment analyses of the potential targets of angelicin, and we predicted it function in osteosarcoma treatment and the underlying molecular mechanism. Through molecular docking, the interactions between hub targets and angelicin were simulated, and then, the hub targets of angelicin were identified. Based on these results, we validated the effects of angelicin on osteosarcoma cells by conducting in vitro experiments. The PPI network analysis of potential therapeutic targets identified four apoptosis-related hub targets, namely, BCL-2, Casp9, BAX and BIRC 2. GO and KEGG enrichment analyses demonstrated that angelicin regulates osteosarcoma cell apoptosis. Molecular docking results indicated that angelicin can freely bind to the hub targets listed above. In vitro experiments showed that angelicin promoted osteosarcoma cell apoptosis in a dose-dependent manner and inhibited osteosarcoma cell migration and proliferation in a time- and dose-dependent manner. The RT-PCR results showed that angelicin simultaneously promoted the mRNA expression of Bcl-2 and Casp9 and inhibited the mRNA expression of BAX and BIRC 2. Angelicin promotes osteosarcoma cell apoptosis and inhibits osteosarcoma cell proliferation and migration by activating a signaling network that is composed of hub targets that link multiple signaling pathways. Angelicin could become an alternative drug for the treatment of osteosarcoma.

Establishment of a Nomogram Based on Inflammatory Response-Related Methylation Sites in Intraoperative Visceral Adipose Tissue to Predict EWL% at One Year After LSG.

Background: Laparoscopic sleeve gastrectomy (LSG) is considered as an effective bariatric and metabolic surgery for patients with severe obesity. Chronic low-grade inflammation of adipose tissue is associated with obesity and obesity-related complications. Objective: This study intends to establish a nomogram based on inflammatory response-related methylation sites in intraoperative visceral adipose tissue (VAT) to predict excess weight loss (EWL)% at one-year after LSG. Methods: Based on EWL% at one-year after LSG, patients were divided into two groups: the satisfied group (group-A, EWL%≥50%) and the unsatisfied group (group-B, EWL%<50%). Next, we defined genes corresponding to the methylation sites in the 850 K methylation microarray as methylation-related genes (MRGs). We then took the intersection of MRGs and inflammatory response-related genes. After that, inflammatory response-related methylation sites were identified based on overlapping genes. Moreover, difference analysis was carried out to obtain inflammatory response-related differentially methylated sites (IRRDMSs) between group-A and group-B. LASSO analysis was used to identify the hub methylation sites. Finally, we developed a nomogram based on the hub methylation sites. Results: There were 26 patients in the study, with 13 in group-A and 13 in group-B. After data filtering and difference analysis, 200 IRRDMSs were identified (143 hypermethylated sites and 57 hypomethylated sites). Then, we identified three hub methylation sites (cg03610073, cg03208951, and cg18746357) by LASSO analysis and built a predictive nomogram (Area under the curve=0.953). Conclusion: The predictive nomogram based on three inflammatory-related methylation sites (cg03610073, cg03208951, and cg18746357) in intraoperative visceral adipose tissue can predict one-year EWL% after LSG effectively.

Identification of optimal primary tumor resection candidates for metastatic gastric cancer: Nomograms based on propensity score matching.

BACKGROUND: This study sought to develop and validate nomograms for screening patients with metastatic gastric cancer (mGC) who are candidates for primary tumor resection (PTR) and evaluating the prognosis of mGC patients after PTR. METHODS: From 2010 to 2016, we screened mGC patients with complete data from the Surveillance, Epidemiology, and End Results (SEER) database. Depending on whether or not PTR was performed, we categorized patients into surgery and non-surgery groups. A 1:1 propensity score matching (PSM) analysis was used to balance the characteristics of the two groups. The endpoints were overall survival (OS) and cancer-specific survival (CSS). Two predictive nomograms were developed using logistic regression to assess the likelihood of benefit. Two additional prognostic nomograms were developed to assess prognosis in mGC patients after PTR by Cox regression. Finally, nomograms were evaluated using a variety of methodologies. RESULTS: Our study included 3594 mGC patients who met the criteria. PTR was associated with improved OS and CSS time (median OS time after PSM: 15 vs. 7 months, P < 0.05; median CSS time after PSM: 17 vs. 7 months, P < 0.05). The OS-related predictive nomogram, including age, histologic type, grade, T stage, and chemotherapy, was developed. Moreover, the CSS-related predictive nomogram, including age, histologic type, grade, and chemotherapy, was developed. Sex, histologic type, grade, T stage, N stage, and chemotherapy were found to be correlated with OS. Furthermore, the CSS correlated with histologic type, grade, T stage, N stage, and chemotherapy. Both predictive and prognostic nomograms were found to be valuable and reliable after different types of validation. CONCLUSION: Predictive nomograms were developed and validated for identifying the optimal PTR mGC candidates. Prognostic nomograms were developed and validated for assessing the prognosis of mGC patients after PTR.

A nomogram based on adipogenesis-related methylation sites in intraoperative visceral fat to predict EWL% at 1 year following laparoscopic sleeve gastrectomy.

BACKGROUND: Laparoscopic sleeve gastrectomy (LSG) is a crucial surgical procedure for patients with obesity. However, epigenetic research in LSG is still in its infancy from the perspective of adipogenesis. OBJECTIVES: This work aims to develop a model to predict 1 year excess weight loss percentage (EWL)% following LSG in Chinese patients with obesity by examining the DNA methylation profiles of intraoperative visceral fat. SETTING: University hospital, Beijing, China. METHODS: Firstly, we classified patients with obesity as either the satisfied group or unsatisfied group depending on whether their EWL% was 50% or higher at 1 year following LSG. After that, we analyzed differentially methylated sites (DMSs) between the satisfied group and unsatisfied group. DMSs were mapped to the corresponding differentially methylated genes. Then, we took the intersection of adipogenesis-related genes and differentially methylated genes and obtained adipogenesis-related DMSs. Next, hub methylation sites were identified by least absolute shrinkage and selection operator analysis. Finally, a nomogram was developed to predict EWL% of Chinese patients with obesity at 1 -year following LSG. RESULTS: A total of 26 patients with obesity were enrolled in the study, including 13 in the satisfied group and 13 in the unsatisfied group. A total of 16 genes and 31 DMSs were involved in the adipogenesis signaling pathway. Finally, 4 hub methylation sites (cg06093355, cg00294552, cg00753924, and cg17092065) were identified and a predictive nomogram was established. CONCLUSIONS: The predictive nomogram based on methylation sites including cg06093355, cg00294552, cg00753924, and cg17092065 can predict EWL% at 1 year following LSG in Chinese patients with obesity efficiently.

An Assessment of the Effect of Bariatric Surgery on Cardiovascular Disease Risk in the Chinese Population Using Multiple Cardiovascular Risk Models.

Background: Many studies have reported that bariatric surgery may reduce postoperative cardiovascular risk in patient with obesity, but few have addressed this risk in the Chinese population. Objective: To assess the impact of bariatric surgery on cardiovascular disease (CVD) risk in the Chinese population using the World Health Organization (WHO) risk model, the Global risk model, and the Framingham Risk Score. Methods: We retrospectively analyzed data collected on patient with obesity who underwent bariatric surgery at our institution between March 2009 and January 2021. Their demographic characteristics, anthropometric variables, and glucolipid metabolic parameters were assessed preoperatively and at their 1-year postoperative follow-up. Subgroup analysis compared body mass index (BMI) < 35 kg/m2 and BMI ≥ 35 kg/m2, as well as gender. We used the 3 models to calculate their CVD risk. Results: We evaluated 61 patients, of whom 26 (42.62%) had undergone sleeve gastrectomy (SG) surgery and 35 (57.38%) Roux-en-Y gastric bypass (RYGB) surgery. Of the patients with BMI ≥ 35 kg/m2, 66.67% underwent SG, while 72.97% with BMI < 35 kg/m2 underwent RYGB. HDL levels were significantly higher at 12 months postoperatively relative to baseline. When the models were applied to calculate CVD risk in Chinese patients with obesity, the 1-year CVD risk after surgery were reduced lot compared with the preoperative period. Conclusion: Patient with obesity had significantly lower CVD risks after bariatric surgery. This study also demonstrates that the models are reliable clinical tools for assessing the impact of bariatric surgery on CVD risk in the Chinese population.

Network pharmacology and molecular docking reveal the mechanism of Angelica dahurica against Osteosarcoma.

Osteosarcoma (OS) is a malignant bone tumor of mesenchymal origin. Angelica dahurica is a typical traditional Chinese herb. Angelica dahurica is used in the treatment of a variety of tumors. However, the studies of Angelica dahurica for OS have not been reported. To investigate Angelica dahurica's potential mechanism of action in the treatment of OS, we used network pharmacology and molecular docking methods in this study. Of which the network pharmacology includes the collection of active ingredients of Angelica dahurica, the collection of predicted targets of Angelica dahurica and predicted targets of OS, the analysis of therapeutic targets of Angelica dahurica, gene ontology (GO) enrichment, and Kyoto encyclopedia of genes and genomes (KEGG) enrichment. The Venn plot performance showed that there were 225 predicted targets of Angelica dahurica for the treatment of OS. The therapeutic targets enrichment analysis results showed that Angelica dahurica treated OS through multiple targets and pathways. Angelica dahurica could affect OS's proliferation, apoptosis, migration, infiltration, and angiogenesis through a signaling network formed by pivotal genes crosstalking numerous signaling pathways. In addition, molecular docking results showed that sen-byakangelicol, beta-sitosterol, and Prangenin, have a relatively high potential to become a treatment for patients with OS and improve 5-year survival in OS patients. We used network pharmacology and molecular docking methods to predict the active ingredients and significant targets of Angelica dahurica for the treatment of OS and, to a certain extent, elucidated the potential molecular mechanism of Angelica dahurica in the treatment of OS. This study provided a theoretical basis for Angelica dahurica in the treatment of OS.

A novel inflammatory signature for evaluating immune microenvironment status in soft tissue sarcoma.

Background: Tumorigenesis and progression are intimately associated with inflammation. However, the inflammatory landscape in soft tissue sarcoma (STS) and its clinical consequences are yet unknown, and more investigation is needed. Methods: RNA-seq expression data for STS and corresponding normal tissues were downloaded from The Cancer Genome Atlas database and the Genotype-Tissue Expression Portal. Differential and prognostic analyses were performed based on known inflammatory response genes from Gene Set Enrichment Analysis (GSEA). We utilized LASSO-Cox analysis to determine hub genes and built an inflammatory score (INFscore) and risk stratification model. Furthermore, a nomogram, including the risk stratification model, was established to predict the prognosis. We further elucidated the characteristics among different risk STS patients by GSEA, gene set variation analysis, and detailed immune infiltration analysis. Finally, the INFscore and risk stratification model in predicting prognosis and depicting immune microenvironment status were verified by pan-cancer analysis. Results: Five hub genes (HAS2, IL1R1, NMI, SERPINE1, and TACR1) were identified and were used to develop the INFscore. The risk stratification model distinguished the immune microenvironment status and evaluated the efficacy of immunotherapy and chemotherapy in STS. The novel nomogram had good efficacy in predicting the prognosis of STS patients. Finally, a pan-cancer investigation verified the association of INFscore with prognosis and immunity. Conclusions: According to the present study, the risk stratification model can be used to evaluate STS prognosis, tumor microenvironment status, immunotherapy, and chemotherapy efficacy. The novel nomogram has an excellent predictive value. Thus, the INFscore and risk stratification model has potential value in assessing the prognosis and immune status of multiple malignancies.

A New Nomogram for Predicting the Postoperative Overall Survival in Patients with Middle-Aged and Elderly Rectal Cancer: A Single Center Retrospective Study in Chinese Population.

Purpose: Patients with middle-aged and elderly rectal cancer (MERC) usually have poor prognosis after surgery. This study aimed to develop a nomogram to achieve individualized prediction of overall survival (OS) in patients with MERC and to guide follow-up and subsequent diagnosis and treatment plans. Patients and Methods: A total of 349 patients were randomly assigned to the training and validation cohorts in a 7:3 ratio. Multivariate Cox regression analysis was performed using the results of univariate Cox regression analysis to confirm independent prognostic factors of OS. Thereafter, the nomogram was built using the "rms" package. Subsequently, discriminative ability and calibration of the nomogram were evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Integrated discrimination improvement (IDI), net reclassification improvement (NRI), and the area under the ROC curves (AUC) were compared between the nomogram and the tumor-node-metastasis (TNM) staging system (8th edition). Finally, we established a predictive model to assess the survival benefit of patients with MERC by calculating nomogram scores for each patient. Results: Six variables were identified as independent prognostic factors and included in the nomogram: smoking history, family history, hematochezia, tumor size, N stage, and M stage. Based on these factors, we successfully constructed a nomogram and evaluated its discriminative and predictive abilities using ROC curves, calibration curves, and DCA. ROC curves, IDI, and NRI showed that the nomogram had outstanding clinical utility compared with the TNM staging system (8th edition) for OS prediction. The predictive model successfully distinguished between high-, medium-, and low-risk MERC patients. Conclusion: Our nomogram provided a more satisfactory survival prediction ability than the TNM staging system (8th edition) for MERC patients. In addition, the nomogram was able to accurately categorize patients into different risk groups after surgery.

Clinical effects of prophylactic transverse colostomy in patients undergoing completely laparoscopic transabdominal approach partial intersphincteric resection.

OBJECTIVE: To investigate the clinical effects of prophylactic transverse colostomy on gastrointestinal function recovery and complications in patients undergoing completely laparoscopic transabdominal approach partial intersphincteric resection (CLAPISR) of low rectal cancer. METHODS: We retrospectively analyzed the data of 74 patients with low rectal cancer who were treated with prophylactic transverse colostomy (Group A, n = 34) or without prophylactic transverse colostomy (Group B, n = 40). Surgery-related indicators, nutritional status indicators, systemic stress response indicators, and complications were compared between the two groups. RESULTS: On postoperative day 5, the C-reactive protein concentration and white blood cell count were not significantly different between the two groups; however, the serum concentrations of total protein and albumin were higher in Group A than in Group B. Within 26 months postoperatively, the total incidence rate of complications was not significantly different, but the incidence rate of anastomotic leakage was lower in Group A than in Group B. CONCLUSION: Prophylactic transverse colostomy based on CLAPISR can lead to faster recovery of gastrointestinal function, better improvement of postoperative nutritional indicators, and a lower incidence of anastomotic leakage. These characteristics are conducive to the rapid recovery of patients, making this procedure worthy of clinical application.

Knockdown of CD44 inhibits proliferation, migration and invasion of osteosarcoma cells accompanied by downregulation of cathepsin S.

BACKGROUND: Osteosarcoma (OS) is a malignant bone tumour of mesenchymal origin. These tumours are characterised by rich vascularisation, therefore promoting rapid proliferation and facilitating metastasis. CD44 has been reported to be involved in OS, but its role and molecular mechanisms in the pathogenesis of the disease are not fully determined. METHODS: In this study, we investigated the antitumor effect of CD44 on the development of OS and further explored the molecular mechanisms. The expression of CD44, cathepsin S and MMP-9 was detected by Western blot (WB) and reverse transcription-polymerase chain reaction (RT-qPCR) in different cell lines (MG63, U2OS OS and hFOB 1.19). To elucidate the role of CD44 in OS, MG63 and U2OS cells were treated with small interference RNA (siRNA) to knock down CD44, and the knockdown efficiency was validated with GFP and RT-qPCR. Furthermore, cell proliferation was assayed using Cell Counting Kit­8 (CCK-8) and colony formation assays, and cell migration and invasion were assayed by transwell and wound-healing assays. RESULTS: We found that CD44 expression in the MG63 and U2OS OS cell lines was markedly increased compared to that of the human osteoblast hFOB 1.19 cell line. Knockdown of CD44 inhibited proliferation, migration and invasion of MG63 and U2OS cells. Cathepsin S expression in the MG63 and U2OS OS cell lines was increased compared to that of the human osteoblast hFOB 1.19 cell line. When CD44 was knocked down, its expression level went down. CONCLUSION: Taken together, our data reinforced the evidence that CD44 knockdown inhibited cell proliferation, migration and invasion of OS cells accompanied by altered expression of cathepsin S. These findings offer new clues for OS development and progression, suggesting CD44 as a potential therapeutic target for OS.

A Case of Forearm Soft Tissue Infection Caused by Hypervirulent K. pneumoniae in an Otherwise Healthy 24-Year-Old Woman.

In recent years, hypervirulent Klebsiella pneumoniae (hvKp) has received greater attention. It mainly infects diabetic patients and typically causes a hepatic abscess. Here, we report a case of hvKp that caused forearm muscle and soft tissue infection in addition to bacteremia, hepatic and pulmonary abscess, and hyperglycemia. The patient's condition stabilized after comprehensive treatment. She eventually recovered and was discharged after several debridement and flap operations. At 9 months of follow-up, no signs of infectious recurrence were noted, and the hyperglycemia resolved. Here, we detail important clinical features of a severe hvKp case diagnosed in an otherwise healthy individual. This report underscores the potential of hvKp to cause deep tissue infection and present with clinical symptoms similar to gas gangrene. Symptom onset in the setting of hvKp infection is usually gradual and misdiagnosis is common. The diagnosis of hvKp should be routinely considered in the clinical setting, and be strongly suspected when presenting with characteristic epidemiological, clinical and laboratory features. Although diabetes is a predisposing factor to hvKp infection, hyperglycemia appeared to manifest as a consequence of hvKp infection in this patient.

Immune-related lncRNA pairs as novel signature to predict prognosis and immune landscape in melanoma patients.

ABSTRACT: To investigate immune-related long non-coding RNA (irlncRNA) signatures for predicting survival and the immune landscape in melanoma patients.We retrieved gene expression files from The Cancer Genome Atlas and the Genotype-Tissue Expression database and extracted all the long non-coding RNAs from the original data. Then, we selected immune-related long non-coding RNAs (irlncRNAs) using co-expression networks and screened differentially expressed irlncRNAs (DEirlncRNAs) to form pairs. We also performed univariate analysis and Least absolute shrinkage and selection operator (LASSO) penalized regression analysis to identify prognostic DEirlncRNA pairs, constructed receiver operating characteristic curves, compared the areas under the curves, and calculated the optimal cut-off point to divide patients into high-risk and low-risk groups. Finally, we performed multivariate Cox regression analysis, Kaplan-Meier (K-M) survival analysis, clinical correlation analysis, and investigated correlations with tumor-infiltrating immune cells, chemotherapeutic effectiveness, and immunogene biomarkers.A total of 297 DEirlncRNAs were identified, of which 16 DEirlncRNA pairs were associated with prognosis in melanoma. After grouping patients by the optimal cut-off value, we could better distinguish melanoma patients with different survival outcomes, clinical characteristics, tumor immune status changes, chemotherapeutic drug sensitivity, and specific immunogene biomarkers.The DEirlncRNA pairs showed potential as novel biomarkers to predict the prognosis of melanoma patients. Furthermore, these DEirlncRNA pairs could be used to evaluate treatment efficacy in the future.

The new horizon of biomarker in melanoma patients: A study based on autophagy-related long non-coding RNA.

ABSTRACT: Autophagy-related long non-coding RNAs (arlncRNAs) play a crucial role in the pathogenesis and development of the tumor. However, there is a lack of systematic analysis of arlncRNAs in melanoma patients.Melanoma data for analysis were obtained from The Cancer Genome Atlas (TCGA) database. By establishing a co-expression network of autophagy-related mRNAs-lncRNAs, we identified arlncRNAs in melanoma patients. We evaluated the prognostic value of arlncRNAs by univariate and multivariate Cox analysis and constructed an arlncRNAs risk model. Patients were divided into high- and low-risk groups based on the arlncRNAs risk score. This model was evaluated by Kaplan-Meier (K-M) analysis, univariate-multivariate Cox regression analysis, and receiver operating characteristic (ROC) curve analysis. Characteristics of autophagy genes and co-expressive tendency were analyzed by principal component analysis and Gene Set Enrichment Analysis (GSEA) functional annotation.Nine arlncRNAs (USP30-AS1, LINC00665, PCED1B-AS1, LINC00324, LINC01871, ZEB1-AS1, LINC01527, AC018553.1, and HLA-DQB1-AS1) were identified to be related to the prognosis of melanoma patients. Otherwise, the 9 arlncRNAs constituted an arlncRNAs prognostic risk model. K-M analysis and ROC curve analysis showed that the arlncRNAs risk model has good discrimination. Univariate and multivariate Cox regression analysis showed that arlncRNAs risk model was an independent prognostic factor in melanoma patients. Principal component analysis and GSEA functional annotation showed different autophagy and carcinogenic status in the high- and low-risk groups.This novel arlncRNAs risk model plays an essential role in predicting of the prognosis of melanoma patients. The model reveals new prognosis-related biomarkers for autophagy, promotes precision medicine, and provides a lurking target for melanoma's autophagy-related treatment.

m6A regulator-mediated methylation modification patterns and tumor immune microenvironment in sarcoma.

BACKGROUND: Studies have shown that the RNA N6-methyladenosine (m6A) modification patterns are extensively involved in the development of multiple tumors. However, the association between the m6A regulator expression patterns and the sarcoma tumor immune microenvironment (TIME) remains unclear. METHODS: We systematically evaluated the m6A regulator expression patterns in patients with sarcoma based on known 23 m6A regulators. Different m6A regulator expression patterns were analyzed using gene set variation analysis and a single-sample gene set enrichment analysis algorithm. According to the results of consensus clustering, we classified the patients into four different clusters. Next, we subjected the four clusters to differential genetic analysis and established m6A-related differentially expressed genes (DEGs). We then calculated the m6A-related DEGs score and constructed the m6A-related gene signature, named m6A score. Finally, the 259 sarcoma samples were divided into high- and low-m6A score groups. We further evaluated the TIME landscape between the high- and low-m6A score groups. RESULTS: We identified four different m6A modification clusters and found that each cluster had unique metabolic and immunological characteristics. Based on the 19 prognosis-related DEGs, we calculated the principal component analysis scores for each patient with sarcoma and classified them into high- and low-m6A score groups. CONCLUSIONS: The m6A regulator expression patterns and complexity of the sarcoma TIME landscape are closely related to each other. Systematic evaluation of m6A regulator expression patterns and m6A scores in patients with sarcoma will enhance our understanding of TIME characteristics.

A Retrospective Study on the Feasibility of Completely Laparoscopic Transabdominal Approach Partial Intersphincteric Resection.

Background: With the development of surgical techniques, gastrointestinal surgeons seek ways to improve the quality of life (QOL) for postoperative patients, while ensuring the tumor radical effect, such as reducing trauma, alleviating pain, and preserving the anus. This article discusses the postoperative outcomes of completely laparoscopic transabdominal approach partial intersphincteric resection (CLTPISR). Materials and Methods: The clinical data of 68 patients who underwent CLTPISR at the Affiliated Hospital of Chengde Medical College between May 2017 and June 2020, including procedure-related data, general postoperative conditions, and postoperative anal function data, were retrospectively analyzed to investigate the feasibility and safety of CLTPISR. Results: All 68 rectal cancer patients completed the CLTPISR. The average age was (60.47 ± 7.08) years, the average operative time was (196.22 ± 8.15) minutes, the mean operative bleeding was (49.12 ± 29.61) mL, and the average postoperative hospital stay was (13.46 ± 4.78) days. The postoperative pathology showed that the circumferential margins and distal margins were all negative, the maximum tumor diameter was (3.26 ± 1.11) cm, the distance from the anal verge was (3.92 ± 0.89) cm, and the average number of lymph nodes cleared was (11.06 ± 3.67). There were 28 stage I patients (41.18%), 21 stage II patients (30.88%), and 19 stage III patients (27.94%). The median follow-up time after surgery was 28 months, and the rates of distant metastasis, disease-free survival, and overall survival of the patients were 8.82%, 91.18%, and 95.59%, respectively. The patient's postoperative anal function gradually recovered as time increased. Conclusions: Under the premise of strictly grasping the indications, the CLTPISR is a safe and feasible surgery. It could achieve maximum anal preservation and improve patients' QOL, while maintaining the tumor radical effect, and had the advantages of the short operation time, low intraoperative bleeding, and quick recovery. The Clinical Trial Registration number is LL2020397.

Development, validation, and visualization of a web-based nomogram for predicting the incidence of leiomyosarcoma patients with distant metastasis.

BACKGROUND: Leiomyosarcoma (LMS) is one of the most common soft tissue sarcomas. LMS is prone to distant metastasis (DM), and patients with DM have a poor prognosis. AIM: In this study, we investigated the risk factors of DM in LMS patients and the prognostic factors of LMS patients with DM. METHODS AND RESULTS: LMS patients diagnosed between 2010 and 2016 were extracted from the Surveillance, Epidemiology, and End Result (SEER) database. Patients were randomly divided into the training set and validation set. Univariate and multivariate logistic regression analyses were performed, and a nomogram was established. The area under the curve (AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the nomogram. Based on the nomogram, a web-based nomogram is established. The univariate and multivariate Cox regression analyses were used to assess the prognostic risk factors of LMS patients with DM. Eventually, 2184 patients diagnosed with LMS were enrolled, randomly divided into the training set (n = 1532, 70.14%) and validation set (n = 652, 29.86%). Race, primary site, grade, T stage, and tumor size were correlated with DM incidence in LMS patients. The AUC of the nomogram is 0.715 in training and 0.713 in the validation set. The calibration curve and DCA results showed that the nomogram performed well in predicting the DM risk. A web-based nomogram was established to predict DM's risk in LMS patients (https://wenn23.shinyapps.io/riskoflmsdm/). Epithelioid LMS, in uterus, older age, giant tumor, multiple organ metastasis, without surgery, and chemotherapy had a poor prognosis. CONCLUSIONS: The established web-based nomogram (https://wenn23.shinyapps.io/riskoflmsdm/) is an accurate and personalized tool to predict the risks of LMS developing DM. Advanced age, larger tumor, multiple organ metastasis, epithelioid type, uterine LMS, no surgery, and no chemotherapy were associated with poor prognosis in LMS patients with DM.