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Abstract Aim To compare and analyze the clinical efficacy of modified Koyanagi and staged Duckett for proximal hypospadias. Method The clinical and prognostic data of children were treated and underwent surgery (modified Koyanagi or stage Duckett) in the Department of Urology, Kunming Children’s Hospital from January 2020 to January 2023 were retrospectively analyzed. According to different surgical methods, the subjects were divided into the modified Koyanagi group and the staged Duckett group. Patients in both groups were followed up for more than 6 months after surgery. The success rate and complications of postoperative surgery in both groups were analyzed. Result A total of 63 patients were included in this study, 34 in the modified Koyanagi group and 29 in the staged Duckett group. A total of 14 patients in the modified Koyanagi group experienced postoperative complications, the success rate of the surgery was 58.82%, and 5 among them experienced more than two kinds of complications. A total of 5 children in the staging Duckett group experienced postoperative complications, and the success rate of the operation was 82.75%. There were significant differences in the incidence of overall complications and fistula between the two surgical methods (P = 0.028). Conclusion Compare with modified Koyanagi, staged Duckett can significantly reduce the incidence of overall complications and urethral fistula in patients, and have obvious advantages in the treatment of proximal hypospadias.

Zinc is an essential trace element in the human body, playing a crucial role in cellular metabolism.Dysregulation of zinc homeostasis can lead to abnormal cellular metabolism, contributing to diseases and closely related to tumor development. Adequate zinc intake can maintain zinc homeostasis in the body and support normal cellular metabolism. This review discusses the metabolic processes of zinc in the human body and its close relationship with tumorigenesis. It briefly describes zinc absorption, transport, storage, and release, as well as its important role in gene expression, signal transduction, oxidative stress, immune response, and apoptosis. It focuses on the abnormal cellular metabolism caused by excessive or insufficient zinc, the relationship between zinc homeostasis disruption and metabolic syndrome, and the mechanisms involved in tumor development. It analyzes how changes in the expression and activity of zinc transporters may lead to disrupted zinc homeostasis in tumor tissues. It points out that zinc deficiency is associated with various cancers, including prostate cancer, hepatocellular carcinoma, pancreatic cancer, lung cancer, ovarian cancer, esophageal squamous cell carcinoma, and breast cancer. The summary emphasizes that zinc metalloproteins could serve as potential targets for cancer therapy, and regulating the expression and activity of zinc transport proteins may offer new methods and strategies for clinical cancer treatment.

Abstract Objective Mucinous breast cancer (MBC) is a kind of breast cancer (BC), which is rare in clinic, mainly for women, because of the low incidence rate, so there is no unified standard treatment protocol. Elderly patients have a poor prognosis due to their combined comorbidities. This study aims to investigate the effect of surgery and chemoradiotherapy on the prognosis of elderly female MBC patients and construct nomograms for predicting the OS and CSS in elderly female MBC patients. Methods Data for female MBC patients over 65 years are obtained from the Surveillance, Epidemiology and End Results (SEER) database, patients were divided into two groups: the training set and the validation set. External validation data of the prediction model were provided by Kunming Hospital of Traditional Chinese Medicine. We used Cox regression modeling, which was used to identify independent risk factors affecting patient prognosis. After avoiding confounding bias according to the multifactorial Cox regression model, we used these screened statistically significant results to construct column‐line plots. The performance of the model was tested using the consistency index (c‐index), the calibration curve, and the area under the operating characteristic curve of the receiver (AUC). Subsequently, we used decision curve analysis (DCA) to examine the potential clinical value of our nomograms. Results A total of 8103 elderly MBC female patients were extracted from the database SEER and were assigned to the training and validation set, randomly. A total of 83 patients from Kunming Hospital of Traditional Chinese Medicine were used in the external verification set. After multifactorial Cox regression analysis, we found that age, race, T‐stage, M‐stage, surgical approach, radiotherapy, and tumor size were independent risk factors for OS in elderly MBC patients. Similarly, independent risk factors of CSS included age, marital status, N stage, M stage, surgical approach, chemotherapy, and tumor size. The C‐index for the OS training, validation, and external verification set were 0.731 (95%CI 0.715–0.747), 0.738 (95%CI 0.724–0.752), and 0.809 (95%CI 0.731–0.8874). The C‐index of the training set, the validation set, and external verification set for CSS were 0.786 (95%CI 0.747–0.825), 0.776 (95%CI 0.737–0.815), and 0.84 (95%CI0.754–0.926), respectively. The AUC, calibration curves and DCA also showed good accuracy. Conclusions In this study, we construct a new nomogram to predict the prognosis of elderly patients with MBC. The nomograms have undergone internal and external validation and have been confirmed to have good clinical applicability. At the same time, we found that for elderly female MBC patients, surgery and radiotherapy significantly benefit their survival, but chemotherapy is not conducive to patient survival.

Abstract Heterotopic brain tissue is rare and has not been reported. Our center made the first report. 4 years and 2 months old Girl presented with a cystic mass in the right adrenal gland 2 weeks after right upper abdominal pain. The operation was successful, and the diagnosis was confirmed by postoperative pathology. 6 months after the procedure, the incision healed well without recurrence. This case report has a detailed diagnosis and treatment process and satisfactory examination results. It can provide a reference for diagnosing and treating clinical HBT and reduce the risk of misdiagnosis and mistreatment.

Abstract Objective Prostate cancer (PC) is a significant disease affecting men’s health worldwide. More than 60% of patients over 65 years old and more than 80% are diagnosed with localized PC. The current choice of treatment modalities for localized PC and whether overtreatment is controversial. Therefore, we wanted to construct a nomogram to predict the risk factors associated with cancer-specific survival (CSS) and overall survival (OS) in elderly patients with localized PC while assessing the survival differences in surgery and radiotherapy for elderly patients with localized PC. Methods Data of patients with localized PC over 65 years were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models were used to determine independent risk factors for CSS and OS. Nomograms predicting CSS and OS were built using multivariate Cox regression models. The consistency index (C-index), the area under the subject operating characteristic curve (AUC), and the calibration curve were used to test the accuracy and discrimination of the prediction model. Decision curve analysis (DCA) was used to test the potential clinical value of this model. Results A total of 90,434 patients over 65 years and diagnosed with localized PC from 2010 to 2018 were included in the study. All patients were randomly assigned to the training set (n = 63,328) and the validation set (n = 27,106). Univariate and multivariate Cox regression model analysis showed that age, race, marriage, T stage, surgical, radiotherapy, prostate-specific antigen (PSA), and Gleason score (GS) were independent risk factors for predicting CSS in elderly patients with localized PC. Age, race, marriage, surgery, radiotherapy, PSA, and GS were independent risk factors for predicting OS in elderly patients with localized PC. The c-index of the training and validation sets for the predicted CSS is 0.802(95%CI:0.788–0.816) and 0.798(95%CI:0.776–0.820, respectively). The c-index of the training and validation sets for predicting OS is 0.712(95%:0.704–0.720) and 0.724(95%:0.714–0.734). It shows that the nomograms have excellent discriminatory ability. The AUC and the calibration curves also show good accuracy and discriminability. Conclusion We have developed new nomograms to predict CSS and OS in elderly patients with localized PC. After internal validation and external temporal validation with reasonable accuracy, reliability and potential clinical value, the model can be used for clinically assisted decision-making.

Background: Thyroid cancer (TC) is the most common malignant tumor in the endocrine system, is also one of the head and neck tumor. Follicular Thyroid Carcinoma (FTC) plays an important role in the pathological classification of thyroid cancer. This study aimed to develop an innovative predictive tool, a nomogram, for predicting cancer specific survival (CSS) in middle-aged FTC patients. Methods: We collected patient data from the Surveillance, Epidemiology, and End Results (SEER) database. The data from patients between 2004 and 2015 were used as the training set, and the data from patients between 2016 and 2018 were used as the validation set. To identify independent risk factors affecting patient survival, univariate and multivariate Cox regression analyses were performed. Based on this, we developed a nomogram model aimed at predicting CSS in middle-aged patients with FTC. The consistency index (C-index), the area under the receiver operating characteristic (ROC) curve (AUC), and the calibration curve were used to evaluate the accuracy and confidence of the model. Results: A total of 2470 patients were enrolled in this study, in which patients from 2004 to 2015 were randomly assigned to the training cohort (N = 1437) and validation cohort (N = 598), and patients from 2016 to 2018 were assigned to the external validation cohort (N = 435) in terms of time. Univariate and multivariate Cox regression analysis showed that marriage, histological grade and TNM stage were independent risk factors for survival. The C-index for the training cohort was 0.866 (95 % CI: 0.805–0.927), for the validation cohort it was 0.944 (95 % CI: 0.903–0.985), and for the external validation cohort, it reached 0.999 (95 % CI: 0.997–1.001). Calibration curves and AUC suggest that the model has good accuracy. Conclusions: We developed an innovative nomogram to predict CSS in middle-aged patients with FTC. Our model after a rigorous internal validation and external validation process, based on the time proved that the high level of accuracy and reliability. This tool helps healthcare professionals and patients make informed clinical decisions.

Abstract Prostate Cancer (PC) is the most common male nonskin tumour in the world, and most diagnosed patients are over 65 years old. The main treatment for PC includes surgical treatment and nonsurgical treatment. Currently, for nonsurgically treated elderly patients, few studies have evaluated their prognostic factors. Our aim was to construct a nomogram that could predict cancer-specific survival (CSS) in nonsurgically treated elderly PC patients to assess their prognosis-related independent risk factors. Patient information was obtained from the Surveillance, Epidemiology and End Results (SEER) database, and our target population was nonsurgically treated PC patients who were over 65 years old. Independent risk factors were determined using both univariate and multivariate Cox regression models. A nomogram was built using a multivariate Cox regression model. The accuracy and discrimination of the prediction model were tested using the consistency index (C-index), the area under the subject operating characteristic curve (AUC), and the calibration curve. Decision curve analysis (DCA) was used to examine the potential clinical value of this model. A total of 87,831 elderly PC patients with nonsurgical treatment in 2010–2018 were included in the study and were randomly assigned to the training set (N = 61,595) and the validation set (N = 26,236). Univariate and multivariate Cox regression model analyses showed that age, race, marital status, TNM stage, chemotherapy, radiotherapy modality, PSA and GS were independent risk factors for predicting CSS in nonsurgically treated elderly PC patients. The C-index of the training set and the validation set was 0.894 (95% CI 0.888–0.900) and 0.897 (95% CI 0.887–0.907), respectively, indicating the good discrimination ability of the nomogram. The AUC and the calibration curves also show good accuracy and discriminability. We developed a new nomogram to predict CSS in elderly PC patients with nonsurgical treatment. The model is internally validated with good accuracy and reliability, as well as potential clinical value, and can be used for clinical aid in decision-making.

PurposeWilms' tumor (WT), also known as nephroblastoma, is the predominant form of primary malignant renal cancer. The unfavorable prognoses linked to anaplastic nephroblastoma and recurrent nephroblastoma emphasize the crucial requirement for the exploration of innovative treatment modalities for WT.MethodsOur study conducted one-way Cox regression and Kaplan-Meier analyses using TARGET-WT nephroblastoma data to identify differentially expressed genes in nephroblastoma and evaluate their prognostic relevance. Utilizing the Connectivity Map database, ZSTK474 emerged as a viable therapeutic option for WT. The effect of ZSTK474 on WT and related underlying mechanisms were further investigated through in vitro and in vivo investigations.ResultsThe in vivo experiment results indicated that ZSTK474 effectively inhibited subcutaneous tumor growth in WT mice. CCK-8 assays revealed two nephroblastoma cell lines exhibited half-inhibitory concentrations of 2μM and 2.51μM for ZSTK474, respectively. ZSTK474 was shown to inhibit the migration and invasion capabilities of WT cells in both Transwell and wound healing assays. Flow cytometry apoptosis and TUNEL assays demonstrated that ZSTK474 induced apoptosis in WT cells. Cell cycle analysis revealed that ZSTK474 led to the induction of G0/G1 phase arrest. Sequencing of ZSTK474-treated WiT49 cells suggested that the impact of ZSTK474 on WT might be mediated by the PI3K/Akt pathway, specifically by inhibiting PIK3R3. Knock-down of PIK3R3 confirmed that ZSTK474 downregulated PIK3R3, reducing Akt phosphorylation, cyclin D and CDK4 levels and elevating P21 expression in nephroblastoma cells. However, current research has limitations, including a lack of understanding of the long-term effects and potential resistance mechanisms of new therapies.ConclusionThis research provides insight into the potential of ZSTK474 and other PI3K inhibitors for treating nephroblastoma.

Abstract Small cell carcinoma of the bladder (SCCB) is a rare urological tumor. The prognosis of SCCB is abysmal. Therefore, this study aimed to construct nomograms that predict overall survival (OS) and cancer-specific survival (CSS) in SCCB patients. Information on patients diagnosed with SCCB during 2004–2018 was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models analyzed Independent risk factors affecting patients' OS and CSS. Nomograms predicting the OS and CSS were constructed based on the multivariate Cox regression model results. The calibration curve verified the accuracy and reliability of the nomograms, the concordance index (C-index), and the area under the curve (AUC). Decision curve analysis (DCA) assessed the potential clinical value. 975 patients were included in the training set (N = 687) and the validation set (N = 288). Multivariate COX regression models showed that age, marital status, AJCC stage, T stage, M stage, surgical approach, chemotherapy, tumor size, and lung metastasis were independent risk factors affecting the patients' OS. However, distant lymph node metastasis instead AJCC stage is the independent risk factor affecting the CSS in the patients. We successfully constructed nomograms that predict the OS and CSS for SCCB patients. The C index of the training set and the validation set of the OS were 0.747 (95% CI 0.725–0.769) and 0.765 (95% CI 0.736–0.794), respectively. The C index of the CSS were 0.749 (95% CI 0.710–0.773) and 0.786 (95% CI 0.755–0.817), respectively, indicating that the predictive models of the nomograms have excellent discriminative power. The calibration curve and the AUC also show good accuracy and discrimination of the nomograms. To sum up, We established nomograms to predict the OS and CSS of SCCB patients. The nomograms have undergone internal cross-validation and show good accuracy and reliability. The DCA shows that the nomograms have an excellent clinical value that can help doctors make clinical-assisted decision-making.

Objective: Partial bladder outlet obstruction(pBOO) is the most common cause of lower urinary tract symptoms (LUTS) and significantly affects the quality of life. Long-term pBOO can cause changes in bladder structure and function, referred to as bladder remodeling. The pathogenesis of pBOO-induced bladder remodeling has yet to be fully understood, so effective treatment options are lacking. Our study aimed to explore how pBOO-induced bladder remodeling brings new strategies for treating pBOO. Methods: A rat model of pBOO was established by partial ligation of the bladder neck, and the morphological changes and fibrosis changes in the bladder tissues were detected by H&E and Masson trichrome staining. Furthermore, EMT(epithelial-mesenchymal transition) related indicators and related pathway changes were further examined after TGF- β treatment of urothelial cells SV-HUC-1. Finally, the above indicators were tested again after using the PI3K inhibitor. Subsequently, RNA sequencing of bladder tissues to identify differential genes and related pathways enrichment and validated by immunofluorescence and western blotting analysis. Results: The pBOO animal model was successfully established by partially ligating the bladder neck. H&E staining showed significant changes in the bladder structure, and Masson trichrome staining showed significantly increased collagen fibers. RNA sequencing results significantly enriched in the cytoskeleton, epithelial-mesenchymal transformation, and the PI3K-AKT-mTOR signaling pathway. Immunofluorescence and western blotting revealed EMT and cytoskeletal remodeling in SV-HUC-1 cells after induction of TGF- β and in the pBOO bladder tissues. The western blotting showed significant activation of the PI3K-AKT-mTOR signaling pathway in SV-HUC-1 cells after induction of TGF-β and in pBOO bladder tissues. Furthermore, EMT and cytoskeletal damage were partially reversed after PI3K pathway inhibition using PI3K inhibitors. Conclusions: In the pBOO rat model, the activation of the PI3K-AKT-mTOR signaling pathway can mediate the cytoskeletal remodeling and the EMT to induce fibrosis in the bladder tissues. PI3K inhibitors partially reversed EMT and cytoskeletal damage.

Osteosarcoma is a bone tumor with a high incidence in children and adolescents. Chemotherapy for osteosarcoma is limited, and effective targeted drugs are urgently needed to treat osteosarcoma. Exosomes as a natural nano drug delivery platform have been widely studied and proven to have good drug delivery performance. However, the low production of exosomes hinders its development as a carrier. Exosome mimetics (EMs) as an alternative product of exosomes solve the problem of low production of exosomes and maintain the good performance of exosomes as carriers. In this study, bone marrow mesenchymal stem cells (BMSCs) were sequentially extruded to generate EMs to encapsulate doxorubicin (EM-Dox) to treat osteosarcoma. The results showed that we successfully prepared EMs of BMSC, and EM-Dox was prepared using an active-loading approach. Our engineered EM-Dox demonstrated significantly more potent tumor inhibition activity and fewer side effects than free doxorubicin. This novel biological nanomedicine system provides a promising opportunity to develop novel precision medicine for osteosarcoma.

Abstract Objective To discuss the clinical and prognostic indicators of pediatric malignant rhabdoid tumor of the kidney (MRTK), and to increase the understanding of the occurrence and development of MRTK. Methods From July 2014 to September 2021, all cases were confirmed by postoperative pathological examination. Among the 42 patients, there were 25 males and 17 females, with a median age of 10 (1–84) months. Abdominal mass or hematuria were the main clinical manifestations. Preoperative chemotherapy was performed in 9 cases (VC). The tumor stages were stage I-IV. Preoperative metastasis was found in 9 cases; the most common site was the lung. Postoperative patients received conventional chemotherapy, including VDACE regimen and UH-1 regimen. Among the 42 children in this group, survival at follow-up in this study was 26.2%(11/42). Results Preoperative anemia was found by univariate analysis, hypertension and hypercalcemia had shorter survival time. In addition, tumor-related factors had a significant impact on survival, with incomplete tumor resection, lymph node metastasis, stage III-IV had a lower survival rate. The impact of postoperative factors on survival included postoperative complications had a lower survival rate. The children were younger than 12 months, preoperative metastasis, no chemotherapy was performed after surgery was an independent risk factor for the prognosis of MRTK. Conclusion The main clinical manifestations about MRTK were abdominal mass and hematuria. Preoperative chemotherapy did not significantly improve the prognosis. Postoperative chemotherapy can significantly improve the survival rate. Diagnosis depends on clinical manifestations, imaging, histopathology, immunohistochemistry and other comprehensive judgment. Age less than 12 months, preoperative metastasis, and no postoperative chemotherapy were independent risk factors for prognosis.

Bilateral adrenal myelolipoma is rare in clinics and patients with disorders of sex development (DSDs). One case was reported in our center. A 45-year-old patient was admitted to the hospital after discovering a left abdominal mass for more than a year and worsening abdominal pain for 18 days. An imaging examination showed bilateral adrenal masses. Physical examination showed clitoris hypertrophy with patelliform changes, thick and dense pubic hair, normal development of bilateral labia majora without labia minora, and urethral opening. After the relevant preoperative examinations, bilateral adrenal mass resection was performed under general anesthesia. The postoperative pathology confirmed adrenal myelolipoma. The incision healed well without recurrence over 10 years after the operation. Her enlarged clitoris decreased in size. This case report has a detailed diagnosis and treatment process and sufficient examination results. It can provide a reference for diagnosing and treating patients with bilateral adrenal myelolipoma and DSD and reduce the risk of misdiagnosis and mistreatment.

BackgroundHamartoma is a mass formed by the proliferation and disorder of two or more kinds of cells inherent in normal organs or anatomical parts, which can occur in any part of the body. The most common hamartoma are kidney hamartoma, spleen hamartoma, liver hamartoma, and lung hamartoma. Urethral hamartoma is extremely rare in clinical practice.Case reportCombined with literature review, the diagnosis and treatment process of a child with posterior urethral hamartoma and hypospadias in our hospital were analyzed. The patient was cured after surgical treatment, the lesion was completely removed, the appearance was satisfactory, and there was no recurrence, urethral stricture, urethral fistula, and other complications. The pathological results of this case support the histological diagnosis of hamartoma, which provides reference for the clinical diagnosis and treatment of congenital malformation and tumor of urogenital in children.ConclusionWhen a child has posterior urethral hamartoma, the symptoms may not be very typical, and it is often combined with urethral malformation. Therefore, it is necessary to perform careful physical examination combined with pathological examination to be able to make an accurate diagnosis. Under normal circumstances, the prognosis of urethral hamartoma is good. However, more cases are needed to be observed for verification, and a long-term effective follow-up after surgery is needed.

ObjectiveTo investigate the correlation between FGA gene polymorphisms and coronary artery lesion in Kawasaki disease.MethodsTwo hundred and thirty four children with Kawasaki disease (KD group), 200 healthy children (normal group) and 208 children with non-KD fever (fever group) were enrolled. General clinical indicators, the concentration of serum MMPs, TIMP-1, FG-α,fibrinogen level, molecular function (FMPV/ODmax) and FGA Thr312Ala polymorphism were detected individually by testing peripheral venous blood after fasting in the morning.ResultsThere was no significant difference in average age among the three groups, which were 3.03 ± 1.22 years, 3.17 ± 1.30 years, and 3.21 ± 1.31 years, respectively. Compared with those in the fever group, the levels of white blood cell count (WBC), platelet count (PLT), procalcitonin (PCT), C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), interleukin-6 (IL-6), monocyte chemoattractant protein-1 (MCP-1), and fibrinogen (Fg) levels were significantly increased in the KD group. Red blood cell count (RBC) and hemoglobin (Hb) levels were significantly decreased (p 0.05). Compared with normal group, the FGA GG, GA, and AA genotype and G, A allele frequency of the FGA gene polymorphism in the KD group showed no significant difference (p > 0.05). In the KD group, the most common type in children with CAL was GA, while the most common type in children without CAL was GG.ConclusionMMPs and FG-α were significantly upregulated in KD patients. The proportion of FGA genotype GA in children with CAL was significantly higher than that in children without CAL, suggesting that FGA gene polymorphisms affect coronary artery lesion in children with KD.

Giant fibroepithelial polyp (FP) of the scrotum in infants is a rare disease. We reported the first case of FP in China. The child was only 9 months and 12 days old and was admitted to the hospital due to rapid growth and rupture of the scrotal mass. The patient underwent scrotal exploration under general anesthesia, and the mass was cystic-solid with clear boundaries. The tumor did not invade the sarcolemma of the scrotum and testicular tissue. The intraoperative pathological frozen section tended to be benign, and the scrotum's tumor and subcutaneous pedicle tissue were removed entirely after 0.5 cm from the boundary of the mass. The operation was successful. The mass was confirmed as FP by postoperative pathology. 6 months after the operation, the incision healed well without recurrence. This case report has a detailed diagnosis and treatment process and adequate examination results. It can provide a reference for diagnosing and treating FP in infants and reduce the risk of misdiagnosis and mistreatment.

Abstract Objective Thyroid carcinoma (TC) is the most common endocrine tumor in the human body. Papillary thyroid carcinoma (PTC) accounts for more than 80% of thyroid cancers. Accurate prediction of elderly PTC can help reduce the mortality of patients. We aimed to construct a nomogram predicting cancer-specific survival (CSS) in elderly patients with PTC. Methods Patient information was downloaded from the Surveillance, Epidemiology, and End Results (SEER) program. Univariate and multivariate Cox regression models were used to screen the independent risk factors for patients with PTC. The nomogram of elderly patients with PTC was constructed based on the multivariate Cox regression model. We used the concordance index (C-index), the area under the receiver operating characteristic curve (AUC) and the calibration curve to test the accuracy and discrimination of the prediction model. Decision curve analysis (DCA) was used to test the clinical value of the model. Results A total of 14,138 elderly patients with PTC were included in this study. Patients from 2004 to 2015 were randomly divided into a training set (N = 7379) and a validation set (N = 3141), and data from 2016 to 2018 were divided into an external validation set (N = 3618). Proportional sub-distribution hazard model showed that age, sex, tumor size, histological grade, TNM stage, surgery and chemotherapy were independent risk factors for prognosis. In the training set, validation set and external validation set, the C-index was 0.87(95%CI: 0.852–0.888), 0.891(95%CI: 0.866–0.916) and 0.931(95%CI:0.894–0.968), respectively, indicating that the nomogram had good discrimination. Calibration curves and AUC suggest that the prediction model has good discrimination and accuracy. Conclusions We constructed a new nomogram to predict CSS in elderly patients with PTC. Internal cross-validation and external validation indicate that the model has good discrimination and accuracy. The predictive model can help doctors and patients make clinical decisions.

Abstract Background Exosomes derived from mesenchymal stem cells (MSCs) have shown to have effective application prospects in the medical field, but exosome yield is very low. The production of exosome mimetic vesicles (EMVs) by continuous cell extrusion leads to more EMVs than exosomes, but whether the protein compositions of MSC-derived EMVs (MSC-EMVs) and exosomes (MSC-exosomes) are substantially different remains unknown. The purpose of this study was to conduct a comprehensive proteomic analysis of MSC-EMVs and MSC-exosomes and to simply explore the effects of exosomes and EMVs on wound healing ability. This study provides a theoretical basis for the application of EMVs and exosomes. Methods In this study, EMVs from human umbilical cord MSCs (hUC MSCs) were isolated by continuous extrusion, and exosomes were identified after hUC MSC ultracentrifugation. A proteomic analysis was performed, and 2315 proteins were identified. The effects of EMVs and exosomes on the proliferation, migration and angiogenesis of human umbilical vein endothelial cells (HUVECs) were evaluated by cell counting kit-8, scratch wound, transwell and tubule formation assays. A mouse mode was used to evaluate the effects of EMVs and exosomes on wound healing. Results Bioinformatics analyses revealed that 1669 proteins in both hUC MSC-EMVs and hUC MSC-exosomes play roles in retrograde vesicle-mediated transport and vesicle budding from the membrane. The 382 proteins unique to exosomes participate in extracellular matrix organization and extracellular structural organization, and the 264 proteins unique to EMVs target the cell membrane. EMVs and exosomes can promote wound healing and angiogenesis in mice and promote the proliferation, migration and angiogenesis of HUVECs. Conclusions This study presents a comprehensive proteomic analysis of hUC MSC-derived exosomes and EMVs generated by different methods. The tissue repair function of EMVs and exosomes was herein verified by wound healing experiments, and these results reveal their potential applications in different fields based on analyses of their shared and unique proteins.

Background: Thyroid cancer (TC) accounts for more than 90% of endocrine tumours and is a typical head and neck tumour in adults. The aim of this study was to develop a predictive tool to predict cancer-specific survival (CSS) in middle-aged patients with papillary thyroid carcinoma (PTC). Methods: The patients from 2004 to 2015 were randomly divided into a training cohort (n = 25,342) and a internal validation cohort (n = 10,725). The patients from 2016 to 2018 were treated as an external validation cohort (n = 11353). COX proportional hazard model was used to screen meaningful independent risk factors. These factors were constructed into a nomogram to predict CSS in middle-aged patients with PTC. The performance and accuracy of the nomogram were then evaluated using the concordance index (C-index), calibration curve and the area under the curve (AUC). The clinical value of nomogram was evaluated by decision curve analysis (DCA). Results: Age, gender, marriage, tumour grade, T stage, N stage, M stage, surgery, chemotherapy, and tumour size were independent prognostic factors. The C-indexes of the training, internal validation, and external validation cohorts were 0.906, 0.887, and 0.962, respectively. The AUC and calibration curves show good accuracy. DCA shows that the clinical value of the nomogram is higher than that of Tumour, Node and Metastasis (TNM) staging. Conclusion: We developed a new prediction tool to predict CSS in middle-aged patients with PTC. The model has good performance after internal and external validation, which can be friendly to help doctors and patients predict CSS.

BackgroundRenal cell carcinoma (RCC) is a common malignant tumor in the elderly, with an increasing trend in recent years. We aimed to construct a nomogram of cancer-specific survival (CSS) and overall survival (OS) in elderly patients with nonmetastatic renal cell carcinoma (nmRCC).MethodsClinicopathological information was downloaded from the Surveillance, Epidemiology, and End Results (SEER) program in elderly patients with nmRCC from 2010 to 2015. All patients were randomly assigned to a training cohort (70%) or a validation cohort (30%). Univariate and multivariate Cox regression analyses were used to identify independent risk factors for patient outcomes in the training cohort. A nomogram was constructed based on these independent risk factors to predict the 1-, 3-, and 5-year CSS and OS in elderly patients with nmRCC. We used a range of methods to validate the accuracy and reliability of the model, including the calibration curve, consistency index (C-index), and the area under the receiver operating curve (AUC). Decision curve analysis (DCA) was used to test the clinical utility of the model.ResultsA total of 12,116 patients were enrolled in the study. Patients were randomly assigned to the training cohort (N = 8,514) and validation cohort (N = 3,602). In the training cohort, univariate and multivariate Cox regression analysis showed that age, marriage, tumor histological type, histological tumor grade, TN stage, tumor size, and surgery are independent risk factors for prognosis. A nomogram was constructed based on independent risk factors to predict CSS and OS at 1-, 3-, and 5- years in elderly patients with nmRCC. The C-index of the training and validation cohorts in CSS were 0.826 and 0.831; in OS, they were 0.733 and 0.734, respectively. The AUC results of the training and validation cohort were similar to the C-index. The calibration curve indicated that the observed value is highly consistent with the predicted value, meaning the model has good accuracy. DCA results suggest that the clinical significance of the nomogram is better than that of traditional TNM staging.ConclusionsWe built a nomogram prediction model to predict the 1-, 3- and 5-year CSS and OS of elderly nmRCC patients. This model has good accuracy and discrimination and can help doctors and patients make clinical decisions and active monitoring.

ObjectiveAccording to statistics, patients with high-risk prostate cancer (PC) account for about 15% of prostate cancer diagnoses, and high-risk patients usually have a poor prognosis due to metastasis and recurrence and have a high mortality rate. Therefore, the accurate prediction of prognostic-related risk factors in middle-aged high-risk PC patients between 50 and 65 can help reduce patient mortality. We aimed to construct new nomograms for predicting cancer-specific survival (CSS) and Overall survival (OS) in middle-aged high-risk PC patients.MethodsData for patients aged between 50 and 65 years old and diagnosed with high-risk PC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models were used to identify independent risk factors for CSS and OS in patients. Nomograms predicting CSS and OS were developed based on multivariate Cox regression models. The concordance index (C-index), the area under the receiver operating characteristic curve (AUC), and the calibration curve are used to detect the accuracy and discrimination of the model. Decision curve analysis (DCA) is used to detect the potential clinical value of this model.ResultsBetween 2010 and 2018, 1,651 patients diagnosed with high-risk PC and aged 50–65 years were included. In this study, the training group (n = 1,146) and the validation group (n = 505) were randomly assigned in a ratio of 7:3. The results showed that M stage, Gleason (GS) and surgical mode were independent risk factors for CSS; marital status, T stage, M stage, surgical mode, and GS were independent risk factors for OS. The C-index for predicting CSS in the training and validation groups are 0.84 and 0.811, respectively; the C-index for predicting OS in the training and validation groups are 0.824 and 0.784, respectively. The AUC and the calibration curves also showed good accuracy and discrimination.ConclusionsWe constructed new nomograms to predict CSS and OS in middle-aged high-risk PC patients. The prediction tools showed good accuracy and reliability, which can help clinicians and patients to make better clinical decisions.

BackgroundNeuroblastoma (NB) is the most frequent solid tumor in pediatrics, which accounts for roughly 15% of cancer-related mortality in children. NB exhibited genetic, morphologic, and clinical heterogeneity, which limited the efficacy of available therapeutic approaches. Recently, a new term ‘cuproptosis’ has been used to denote a unique biological process triggered by the action of copper. In this instance, selectively inducing copper death is likely to successfully overcome the limitations of conventional anticancer drugs. However, there is still a gap regarding the role of cuproptosis in cancer, especially in pediatric neuroblastoma.MethodsWe characterized the specific expression of cuproptosis-related genes (CRGs) in NB samples based on publicly available mRNA expression profile data. Consensus clustering and Lasso-Cox regression analysis were applied for CRGs in three independent cohorts. ESTIMATE and Xcell algorithm was utilized to visualize TME score and immune cell subpopulations’ relative abundances. Tumor Immune Dysfunction and Exclusion (TIDE) score was used to predict tumor response to immune checkpoint inhibitors. To decipher the underlying mechanism, GSVA was applied to explore enriched pathways associated with cuproptosis signature and Connectivity map (CMap) analysis for drug exploration. Finally, qPCR verified the expression levels of risk-genes in NB cell lines. In addition, PDHA1 was screened and further validated by immunofluorescence in human clinical samples and loss-of-function assays.ResultsWe initially classified NB patients according to CRGs and identified two cuproptosis-related subtypes that were associated with prognosis and immunophenotype. After this, a cuproptosis-related prognostic model was constructed and validated by LASSO regression in three independent cohorts. This model can accurately predict prognosis, immune infiltration, and immunotherapy responses. These genes also showed differential expression in various characteristic groups of all three datasets and NB cell lines. Loss-of-function experiments indicated that PDHA1 silencing significantly suppressed the proliferation, migration, and invasion, in turn, promoted cell cycle arrest at the S phase and apoptosis of NB cells.ConclusionsTaken together, this study may shed light on new research areas for NB patients from the cuproptosis perspective.

Wilms tumour (WT) is the most common kidney malignancy in children. Chemoresistance is the leading cause of tumour recurrence and poses a substantial therapeutic challenge. Increasing evidence has underscored the role of the tumour immune microenvironment (TIM) in cancers and the potential for immunotherapy to improve prognosis. There remain no reliable molecular markers for reflecting the immune landscape and predicting patient survival in WT. Here, we examine differences in gene expression by high-throughput RNA sequencing, focused on differentially expressed immune-related genes (IRGs) based on the ImmPort database. Via univariate Cox regression analysis and Lasso-penalized Cox regression analysis, IRGs were screened out to establish an immune signature. Kaplan-Meier curves, time-related ROC analysis, univariate and multivariate Cox regression studies, and nomograms were used to evaluate the accuracy and prognostic significance of this signature. Furthermore, we found that the immune signature could reflect the immune status and the immune cell infiltration character played in the tumour microenvironment (TME) and showed significant association with immune checkpoint molecules, suggesting that the poor outcome may be partially explained by its immunosuppressive TME. Remarkably, TIDE, a computational method to model tumour immune evasion mechanisms, showed that this signature holds great potential for predicting immunotherapy responses in the TARGET-wt cohort. To decipher the underlying mechanism, GSEA was applied to explore enriched pathways and biological processes associated with immunophenotyping and Connectivity map (CMap) along with DeSigN analysis for drug exploration. Finally, four candidate immune genes were selected, and their expression levels in WT cell lines were monitored via qRT-PCR. Meanwhile, we validated the function of a critical gene, NRP2. Taken together, we established a novel immune signature that may serve as an effective prognostic signature and predictive biomarker for immunotherapy response in WT patients. This study may give light on therapeutic strategies for WT patients from an immunological viewpoint.

ObjectiveProstate cancer (PC) is the second leading cause of cancer death in men in the United States after lung cancer in global incidence. Elderly male patients over 65 years old account for more than 60% of PC patients, and the impact of surgical treatment on the prognosis of PC patients is controversial. Moreover, there are currently no predictive models that can predict the prognosis of elderly PC patients undergoing surgical treatment. Therefore, we aimed to construct a new nomogram to predict cancer-specific survival (CSS) in elderly PC patients undergoing surgical treatment.MethodsData for surgically treated PC patients aged 65 years and older were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models were used to identify independent risk factors for elderly PC patients undergoing surgical treatment. A nomogram of elderly PC patients undergoing surgical treatment was developed based on the multivariate Cox regression model. The consistency index (C-index), the area under the subject operating characteristic curve (AUC), and the calibration curve were used to test the accuracy and discrimination of the predictive model. Decision curve analysis (DCA) was used to examine the potential clinical value of this model.ResultsA total of 44,975 elderly PC patients undergoing surgery in 2010–2018 were randomly assigned to the training set (N = 31705) and validation set (N = 13270). the training set was used for nomogram development and the validation set was used for internal validation. Univariate and multivariate Cox regression model analysis showed that age, marriage, TNM stage, surgical style, chemotherapy, radiotherapy, Gleason score(GS), and prostate-specific antigen(PSA) were independent risk factors for CSS in elderly PC patients undergoing surgical treatment. The C index of the training set and validation indices are 0.911(95%CI: 0.899–0.923) and 0.913(95%CI: 0.893–0.933), respectively, indicating that the nomogram has a good discrimination ability. The AUC and the calibration curves also show good accuracy and discriminability.ConclusionsTo our knowledge, our nomogram is the first predictive model for elderly PC patients undergoing surgical treatment, filling the gap in current predictive models for this PC patient population. Our data comes from the SEER database, which is trustworthy and reliable. Moreover, our model has been internally validated in the validation set using the C-index,AUC and the and the calibration curve, showed that the model have good accuracy and reliability, which can help clinicians and patients make better clinical decision-making. Moreover, the DCA results show that our nomogram has a better potential clinical application value than the TNM staging system.

Cervical cancer (CC) is a prominent cancer around the globe, with a high incidence, and fatality rate. Numerous recent investigations have shown that various non-coding RNAs are associated with the progression of CC. Circular RNAs, a novel class of non-coding RNAs, have a single chain covalent closed-loop structure and are involved in cell growth and other physiological processes. These dysregulated circRNAs seem to have environment-specific functions. They have been demonstrated in certain studies to have a dual involvement in oncogene production and tumor inhibition in different cell settings. Simultaneously, some evidence indicates that circRNAs are abnormally expressed in CC and contributes to its progression. Thus, the distinctive expression profile of circRNAs is associated with the diagnosis, prognosis, and treatment outcomes of CC. We summarized numerous CC-specific circles and their function in revealing the molecular processes of carcinogenesis and progression in CC in this review. Taken together, these data suggest that circRNA may be used as an early detection biomarker and potential therapeutic target in patients with CC.

ObjectiveProstate cancer (PC) is the most common non-cutaneous malignancy in men worldwide. Accurate predicting the survival of elderly PC patients can help reduce mortality in patients. We aimed to construct nomograms to predict cancer-specific survival (CSS) and overall survival (OS) in elderly PC patients.MethodsInformation on PC patients aged 65 years and older was downloaded from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models were used to determine independent risk factors for PC patients. Nomograms were developed to predict the CSS and OS of elderly PC patients based on a multivariate Cox regression model. The accuracy and discrimination of the prediction model were tested by the consistency index (C-index), the area under the subject operating characteristic curve (AUC), and the calibration curve. Decision curve analysis (DCA) was used to test the clinical value of the nomograms compared with the TNM staging system and D’Amico risk stratification system.Results135183 elderly PC patients in 2010-2018 were included. All patients were randomly assigned to the training set (N=94764) and the validation set (N=40419). Univariate and multivariate Cox regression model analysis revealed that age, race, marriage, histological grade, TNM stage, surgery, chemotherapy, radiotherapy, biopsy Gleason score (GS), and prostate-specific antigen (PSA) were independent risk factors for predicting CSS and OS in elderly patients with PC. The C-index of the training set and the validation set for predicting CSS was 0.883(95%CI:0.877-0.889) and 0.887(95%CI:0.877-0.897), respectively. The C-index of the training set and the validation set for predicting OS was 0.77(95%CI:0.766-0.774)and 0.767(95%CI:0.759-0.775), respectively. It showed that the proposed model has excellent discriminative ability. The AUC and the calibration curves also showed good accuracy and discriminability. The DCA showed that the nomograms for CSS and OS have good clinical potential value.ConclusionsWe developed new nomograms to predict CSS and OS in elderly PC patients. The models have been internally validated with good accuracy and reliability and can help doctors and patients to make better clinical decisions.

ObjectiveTo investigate the role of chemokines in Wilms tumours, especially their chemotaxis to immune cells and the role of DNA methylation in regulating the expression level of chemokines.MethodsRNAseqV2 gene expression and clinical data were downloaded from the TARGET database. DNA methylation data were downloaded from the GEO and cBioPortal database. The difference analysis and Kaplan-Meier(KM) analysis of chemokines were performed by edgeR package. Then predictive model based on chemokines was constructed by lasso regression and multivariate COX regression. ROC curve, DCA curve, Calibration curve, and Nomogram were used to evaluate the prognostic model. MCPcounter and Cibersort algorithm was used to calculate the infiltration of immune cells in Wilms tumour and para-tumour samples. Then the difference analysis of the immune cells was performed. The relationship between chemokines and immune cells were calculated by Pearson correlation. In addition, DNA methylation differences between Wilms tumour and para-tumour samples was performed. The correlation between DNA methylation and mRNA expression was calculated by Pearson correlation. Western blot(WB)and immunofluorescence were used to confirm the differential expression of CX3CL1 and T cells, and the correlation between them.ResultsA total of 16 chemokines were differentially expressed in tumour and para-tumour samples. A total of seven chemokines were associated with survival. CCL2 and CX3CL1 were positively correlated with prognosis, while high expression of CCL3, CCL8, CCL15, CCL18 and CXCL9 predicted poor prognosis. By lasso regression and multivariate COX regression, CCL3, CCL15, CXCL9 and CX3CL1 were finally included to construct a prediction model. The model shows good prediction ability. MCPcounter and Cibersort algorithm both showed that T cells were higher in para-tumour tissues than cancer tissues. Correlation analysis showed that CX3CL1 had a strong correlation with T cells. These were verified by Weston blot and immunofluorescence. DNA methylation analysis showed that various chemokines were different in para-tumours and tumours. CX3CL1 was hypermethylated in tumours, and the degree of methylation was negatively correlated with mRNA expression.Conclusion1. There is low T cell infiltration in nephroblastoma. 2. Chemokines such as CX3CL1 indicate a favourable prognosis and positively correlate with the number of T cells. 3. chemokines such as CX3CL1 are negatively regulated by DNA hypermethylation.

Background: Malignant rhabdoid tumor of the kidney (MRTK) is an infrequent malignant tumor in childhood, accounting for approximately 2% of all childhood kidney tumors. Although the development of current treatments, the overall survival (OS) rate of MRTK patients is only 25%. The aim of this research was to explore the prognostic value of genes associated with the mTORC1 signaling pathway in MRTK.Methods: The transcriptome data of MRTK samples were downloaded from the TARGET database. The 200 genes of HALLMARK_MTORC1_SIGNALING were downloaded from the Molecular Signatures Database (MSigDB). Furthermore, we applied gene set variation analysis (GSVA) to screen differentially expressed gene sets between the MRTK and normal samples. The 200 genes were combined with differentially expressed genes (DEGs) identified from differentially expressed gene sets. Then, a gene signature of mTORC1 pathway-related genes (mTRGs) was constructed in MRTK. The molecular mechanism of prognostic factors in MRTK was further analyzed using gene set enrichment analysis (GSEA). The target drugs based on these prognostic factors were explored from The Comparative Toxicogenomics Database (CTD). Moreover, six paired fresh tumor tissues and paraneoplastic tissues from children with MRTK were collected to validate the expressions of P4HA1, MLLT11, AURKA, and GOT1 in clinical samples via real-time fluorescence quantitative PCR and Western blot.Results: A four-gene signature (P4HA1, MLLT11, AURKA, and GOT1) related to the mTORC1 pathway was developed in MRTK, which divided the MRTK patients into high-risk and low-risk groups. The patients with high-risk scores were strongly associated with reduced OS. Receiver operating characteristic (ROC) analysis indicated a good prediction performance of the four biomarker signatures. GSEA revealed that the mTOR signaling pathway was significantly enriched. The risk score was demonstrated to be an independent predictor for MRTK outcome. According to the correlation of tumor stem cell index and prognostic factors, the target drugs were obtained for the treatment of MRTK patients. Furthermore, the expressions of RT-qPCR and Western blot were consistent with RNA-sequencing data such that their expressions were significantly elevated in tumor tissues.Conclusion: A total of four genes (P4HA1, MLLT11, AURKA, and GOT1) were screened as prognostic markers, further providing a new understanding for the treatment of patients with MRTK.

ObjectivePapillary renal cell carcinoma (pRCC) is the second most common type of renal cell carcinoma and an important disease affecting older patients. We aimed to establish a nomogram to predict cancer-specific survival (CSS) in elderly patients with pRCC.MethodsPatient information was downloaded from the Surveillance, Epidemiology, and End Results (SEER) project, and we included all elderly patients with pRCC from 2004 to 2018. All patients were randomly divided into a training cohort and a validation cohort. Univariate and multivariate Cox proportional risk regression models were used to identify patient independent risk factors. We constructed a nomogram based on a multivariate Cox regression model to predict CSS for 1-, 3-, and 5- years in elderly patients with pRCC. A series of validation methods were used to validate the accuracy and reliability of the model, including consistency index (C-index), calibration curve, and area under the Subject operating curve (AUC).ResultsA total of 13,105 elderly patients with pRCC were enrolled. Univariate and multivariate Cox regression analysis suggested that age, tumor size, histological grade, TNM stage, surgery, radiotherapy and chemotherapy were independent risk factors for survival. We constructed a nomogram to predict patients' CSS. The training and validation cohort's C-index were 0.853 (95%CI: 0.859–0.847) and 0.855 (95%CI: 0.865–0.845), respectively, suggesting that the model had good discrimination ability. The AUC showed the same results. The calibration curve also indicates that the model has good accuracy.ConclusionsIn this study, we constructed a nomogram to predict the CSS of elderly pRCC patients, which has good accuracy and reliability and can help doctors and patients make clinical decisions.

BackgroundClear cell renal cell carcinoma (ccRCC) is expected in the elderly and poor prognosis. We aim to explore prognostic factors of ccRCC in the elderly and construct a nomogram to predict cancer-specific survival (CSS) in elderly patients with ccRCC.MethodsClinicopathological information for all elderly patients with ccRCC from 2004 to 2018 was downloaded from the Surveillance, Epidemiology, and End Results (SEER) program. All patients were randomly assigned to a training cohort (70%) or a validation cohort (30%). Univariate and multivariate Cox regression models were used to identify the independent risk factors for CSS. A new nomogram was constructed to predict CSS at 1-, 3-, and 5 years in elderly patients with ccRCC based on independent risk factors. Subsequently, we used the consistency index (C-index), calibration curves, and the area under the receiver operating curve (AUC) and decision curve analysis (DCA) to test the prediction accuracy of the model.ResultsA total of 33,509 elderly patients with ccRCC were enrolled. Univariate and multivariate Cox regression analyses results showed that age, sex, race, marriage, tumor size, histological grade, tumor, nodes, and metastases (TNM) stage, and surgery were independent risk factors for CSS in elderly patients with ccRCC. We constructed a nomogram to predict CSS in elderly patients with ccRCC. The C-index of the training cohort and validation cohort was 0.81 (95% CI: 0.802–0.818) and 0.818 (95% CI: 0.806–0.830), respectively. The AUC of the training cohort and validation cohort also suggested that the prediction model had good accuracy. The calibration curve showed that the observed value of the prediction model was highly consistent with the predicted value. DCA showed good clinical application value of the nomogram.ConclusionIn this study, we explored prognostic factors in elderly patients with ccRCC. We found that age, sex, marriage, TNM stage, surgery, and tumor size were independent risk factors for CSS. We constructed a new nomogram to predict CSS in elderly patients with ccRCC with good accuracy and reliability, providing clinical guidance for patients and physicians.

BackgroundOsteosarcoma (OSC) and Ewing's sarcoma (EWS) are children's most common primary bone tumors. The purpose of the study is to develop and validate a new nomogram to predict the cancer-specific survival (CSS) of childhood OSC and EWS.MethodsThe clinicopathological information of all children with OSC and EWS from 2004 to 2018 was downloaded from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression analyses were used to screen children's independent risk factors for CSS. These risk factors were used to construct a nomogram to predict the CSS of children with OSC and EWS. A series of validation methods, including calibration plots, consistency index (C-index), and area under the receiver operating characteristic curve (AUC), were used to validate the accuracy and reliability of the prediction model. Decision curve analysis (DCA) was used to validate the clinical application efficacy of predictive models. All patients were divided into low- and high-risk groups based on the nomogram score. Kaplan-Meier curve and log-rank test were used to compare survival differences between the two groups.ResultsA total of 2059 children with OSC and EWS were included. All patients were randomly divided into training cohort 60% (N = 1215) and validation cohort 40% (N = 844). Univariate and multivariate analysis suggested that age, surgery, stage, primary site, tumor size, and histological type were independent risk factors. Nomograms were established based on these factors to predict 3-, 5-, and 8-years CSS of children with OSC and EWS. The calibration plots showed that the predicted value was highly consistent with the actual value. In the training cohort and validation cohort, the C-index was 0.729 (0.702–0.756) and 0.735 (0.702–0.768), respectively. The AUC of the training cohort and the validation cohort also showed similar results. The DCA showed that the nomogram had good clinical value.ConclusionWe constructed a new nomogram to predict the CSS of OSC and EWS in children. This predictive model has good accuracy and reliability and can help doctors and patients develop clinical strategies.

ObjectiveWith the development of osteosarcoma treatment, limb salvage surgery is gradually replacing amputation as the primary surgical option. Most pediatric osteosarcomas of the limbs undergo limb-salvage surgery. We aimed to use propensity score matching (PSM) analysis test the difference in cancer-specific mortality (CSM) between amputation and limb-salvage surgery in pediatric patients with Osteosarcoma of the limbs. PSM is a statistical method used to deal with data from an Observational Study. The PSM method is designed to reduce the influence of biases and confounding variables to make a more reasonable comparison between experimental and control groups.MethodsPatient information was downloaded from the SEER (surveillance, epidemiology, and End Results) database from 2004 to 2018. We included all primary pediatric osteosarcoma patients who underwent limb salvage or amputation. Multivariate logistic regression models were used to explore the factors influencing patient choice of amputation. Differences in CSM and other causes of mortality (OSM) between limb salvage and amputation were analyzed using cumulative incidence plots and competitive risk regression tests after 1:1 proportional propensity score matching.ResultsA total of 1,058 pediatric patients with limbs Osteosarcoma were included. Patients who underwent amputations were more likely to be male (OR 1.4, P = 0.024) and more likely to have distant metastasis (OR 2.1, P < 0.001). Before propensity matching, CSM was 1.4 times higher in patients undergoing amputation than in patients undergoing limb salvage (P = 0.017) and 3.4 times higher in OSM (P = 0.007). After adjustment for propensity matching, CSM was 1.5 times higher in patients undergoing amputation than in patients undergoing limb salvage (P = 0.028), but there was no significant difference in OSM (HR 3.2, P = 0.078).ConclusionsOur results suggested that amputation is associated with a 1.5-fold increase in CSM in pediatric patients with limbs Osteosarcoma. Therefore, in the surgical selection of pediatric patients with Osteosarcoma, limb salvage surgery should be the first choice in the absence of other contraindications.

BackgroundRenal cell carcinoma (RCC) is the most common renal malignancy in adults, and chromophobe renal cell carcinoma (chRCC) is the third most common subtype of RCC. We aimed to construct a competitive risk model to predict cancer-specific survival (CSS) in elderly patients with chRCC.MethodsThe clinicopathological information of the patients was downloaded from the SEER database, and the patients were randomly divided into the training and validation cohorts. Patients' risk factors for cancer-specific death (CSM) were analyzed using proportional subdistribution hazard (SH). We constructed a competitive risk model to predict the CSS of elderly chRCC patients. Consistency index (C-index), the area under receiver operating curve (AUC), and a calibration curve were used to validate the model's accuracy. Decision curve analysis (DCA) was used to test the clinical value of the model.ResultsA total of 3,522 elderly patients with chRCC were included in the analysis. Patients were randomly assigned to either the training cohort (N = 2,474) or the validation cohort (N = 1,048). SH analysis found that age, race, T, N, and M stage, tumor size, and surgery were risk factors for CSM. We constructed a competitive risk model to predict patients' CSS. In the training set, the model predicted patients' 1-, 3-, and 5-year CSS with C-indices of 82.2, 80.8, and 78.2, respectively. The model predicted patient 1-, 3-, and 5-year CSS in the validation cohort with C-indices of 84.7, 83.4, and 76.9, respectively. The calibration curve showed that the model's predicted value is almost consistent with the observed value, which indicated that the model has good accuracy. The AUC of the training set and validation queue also suggested that the model has good discrimination. The clinical utility of the DCA model in predicting patients' CSS is higher than that of traditional TNM staging.ConclusionsWe constructed a competitive risk model to predict CSS in elderly patients with chRCC. The model has good accuracy and reliability, which can help doctors and patients to make clinical decisions and follow-up strategies.

BackgroundRenal cell carcinoma (RCC) is the most common renal malignant tumor in elderly patients. The prognosis of renal cell carcinoma with distant metastasis is poor. We aim to construct a nomogram to predict the risk of distant metastasis in elderly patients with RCC to help doctors and patients with early intervention and improve the survival rate.MethodsThe clinicopathological information of patients was downloaded from SEER to identify all elderly patients with RCC over 65 years old from 2010 to 2018. Univariate and multivariate logistic regression analyzed the training cohort's independent risk factors for distant metastasis. A nomogram was established to predict the distant metastasis of elderly patients with RCC based on these risk factors. We used the consistency index (C-index), calibration curve, and area under the receiver operating curve (AUC) to evaluate the accuracy and discrimination of the prediction model. Decision curve analysis (DCA) was used to assess the clinical application value of the model.ResultsA total of 36,365 elderly patients with RCC were included in the study. They were randomly divided into the training cohort (N = 25,321) and the validation cohort (N = 11,044). In the training cohort, univariate and multivariate logistic regression analysis suggested that race, tumor histological type, histological grade, T stage, N stage, tumor size, surgery, radiotherapy, and chemotherapy were independent risk factors for distant metastasis elderly patients with RCC. A nomogram was constructed to predict the risk of distant metastasis in elderly patients with RCC. The training and validation cohort's C-indexes are 0.949 and 0.954, respectively, indicating that the nomogram has excellent accuracy. AUC of the training and validation cohorts indicated excellent predictive ability. DCA suggested that the nomogram had a better clinical application value than the traditional TN staging.ConclusionThis study constructed a new nomogram to predict the risk of distant metastasis in elderly patients with RCC. The nomogram has excellent accuracy and reliability, which can help doctors and patients actively monitor and follow up patients to prevent distant metastasis of tumors.

BackgroundMalignant rhabdoid tumor of the kidney (MRTK) is a rare type of tumor that lacks typical clinical manifestations. Herein, we presented clinical data of 2 children with MRTK. In addition, we used a high-throughput RNA-sequencing (RNA-seq), GO analysis, and KEGG signaling pathway analysis to examine gene expression differences at the transcripts level between 2 patients with MRTK and 3 patients with non-tumor diseases without other symptoms.Case reportPreoperative B-scan ultrasonography and computed tomography (CT) examination in 2 cases suggested nephroblastoma. Both patients were treated with radical nephrectomy. After the operation, MRTK was confirmed by pathological examination. Child 1 and Child 2 then received 7 courses and 12 courses of regular chemotherapy, respectively. Child 1 was followed up for 2 years, and Child 2 for 3.1 years without showing symptoms. RNA-seq results showed 2203 differential genes (DEGs) in the kidney tissue of children with MRTK compared to normal tissue (p