Novel model of pyroptosis-related molecular signatures for prognosis prediction of clear cell renal cell carcinoma patients.

Background: Pyroptosis is a programmed death mode of inflammatory cells, which is closely related to tumor progression and tumor immunity. Clear cell renal cell carcinoma (ccRCC) is the major pathological type of renal cell carcinoma (RCC) with poor prognosis. Many theories have tried to clarify the mechanism in the development of ccRCC, but the role of pyroptosis in ccRCC has not been well described. The main purpose of this study is to explore the role of pyroptosis in ccRCC and establish a novel prognosis prediction model of pyroptosis-related molecular signatures for ccRCC. Methods: In the present study, we made a systematical analysis of the association between ccRCC RNA transcriptome sequencing data from The Cancer Genome Atlas (TCGA) database [which included 529 ccRCC patients who were randomized in a training cohort (n=265) and an internal validation cohort (n=264)] and 40 pyroptosis-related genes (PRGs), from which four genes (CASP9, GSDME, IL1B and TIRAP) were selected to construct a molecular prediction model of PRGs for ccRCC. In addition, a cohort of 114 ccRCC patients from Shanghai Eastern Hepatobiliary Surgery Hospital (EHSH) was used as external data to verify the effectiveness of the model by immunohistochemistry. Moreover, the biological functions of the four PRGs were also verified in ccRCC 786-O and 769-P cells by Western blot (WB), CCK-8 cell proliferation, and Transwell invasion assays. Results: The model was able to differentiate high-risk patients from low-risk patients, and this differentiation was consistent with their clinical survival outcomes. In addition, the four PRGs also affected the ability of cell proliferation and invasion in ccRCC. Conclusion: The prediction model of pyroptosis-related molecular markers developed in this study may prove to be a novel understanding for ccRCC.

Identification of ARAP3 as a regulator of tumor progression, macrophage infiltration and osteoclast differentiation in a tumor microenvironment-related prognostic model of Ewing sarcoma.

Understanding the specificity and complexity of the tumor microenvironment (TME) of Ewing sarcoma (ES) is essential for identifying the immune characteristics of ES, improving the prediction of immunotherapeutic response, and facilitating therapeutic target discovery. In this study, we not only evaluated the gene sets associated with TME in ES using ESTIMATE and WGCNA algorithms based on the transcriptome data of ES, but also constructed a prognostic model (ES Score) using univariate Cox regression and Lasso regression and assessed its predictive ability on immune cell infiltration. Subsequently, we identified ARAP3 as a key gene affecting the TME of ES. In addition, bioinformatic analyses and in vitro experiments proved that the high expression of ARAP3 regulated ES cell proliferation, migration, as well as apoptosis via the p53 signaling pathway and affected macrophage infiltration and osteoclast differentiation through regulating IL1B and IL11 secretion of tumor cells.

Extracellular RNA in melanoma: Advances, challenges, and opportunities.

Melanoma, a malignant mass lesion that originates in melanocytes and has a high rate of malignancy, metastasis, and mortality, is defined by these characteristics. Malignant melanoma is a kind of highly malignant tumor that produces melanin and has a high mortality rate. Its incidence accounts for 1%-3% of all malignant tumors and shows an obvious upward trend. The discovery of biomolecules for the diagnosis and treatment of malignant melanoma has important application value. So far, the exact molecular mechanism of melanoma development relevant signal pathway still remains unclear. According to previous studies, extracellular RNAs (exRNAs) have been implicated in tumorigenesis and spread of melanoma. They can influence the proliferation, invasion and metastasis of melanoma by controlling the expression of target genes and can also influence tumor progression by participating in signal transduction mechanisms. Therefore, understanding the relationship between exRNA and malignant melanoma and targeting therapy is of positive significance for its prevention and treatment. In this review, we did an analysis of extracellular vesicles of melanoma which focused on the role of exRNAs (lncRNAs, miRNAs, and mRNAs) and identifies several potential therapeutic targets. In addition, we discuss the typical signaling pathways involved in exRNAs, advances in exRNA detection and how they affect the tumor immune microenvironment in melanoma.

A novel molecular classification method for osteosarcoma based on tumor cell differentiation trajectories.

Subclassification of tumors based on molecular features may facilitate therapeutic choice and increase the response rate of cancer patients. However, the highly complex cell origin involved in osteosarcoma (OS) limits the utility of traditional bulk RNA sequencing for OS subclassification. Single-cell RNA sequencing (scRNA-seq) holds great promise for identifying cell heterogeneity. However, this technique has rarely been used in the study of tumor subclassification. By analyzing scRNA-seq data for six conventional OS and nine cancellous bone (CB) samples, we identified 29 clusters in OS and CB samples and discovered three differentiation trajectories from the cancer stem cell (CSC)-like subset, which allowed us to classify OS samples into three groups. The classification model was further examined using the TARGET dataset. Each subgroup of OS had different prognoses and possible drug sensitivities, and OS cells in the three differentiation branches showed distinct interactions with other clusters in the OS microenvironment. In addition, we verified the classification model through IHC staining in 138 OS samples, revealing a worse prognosis for Group B patients. Furthermore, we describe the novel transcriptional program of CSCs and highlight the activation of EZH2 in CSCs of OS. These findings provide a novel subclassification method based on scRNA-seq and shed new light on the molecular features of CSCs in OS and may serve as valuable references for precision treatment for and therapeutic development in OS.

Surgical efficacy and survival prediction of patients with unspecified malignant bone tumors.

BACKGROUND: The surgical efficacy and prognostic outcomes of patients with unspecific malignant bone tumors (UMBTs) remain unclear. The study is to address: 1) What are the clinicopathological features and prognostic determinants for patients with UMBTs? 2) Can a nomogram be developed for clinicians to predict the short and long-term outcomes for individuals with UMBTs? 3) Does surgery improve outcomes for UMBT patients who received radiotherapy or chemotherapy after balancing the confounding bias? METHODS: 400 UMBT patients were filtrated from the Surveillance, Epidemiology, and End Results database to assess the clinicopathological features, treatments, and factors affecting prognosis. The optimal cutoff values of continuous variables were identified by the x-tile software. Kaplan-Meier method and multivariate Cox proportional hazard modeling were performed to evaluate the independent prognostic factors. Nomogram was further developed by using R software with rms package. The surgical efficacy was further assessed for patients receiving radiotherapy or chemotherapy after performing propensity score matching. RESULTS: The enrolled cohort included 195 (48.8%) female and 205 (51.2%) male patients. The 2- and 5-year cancer-specific survival (CSS) and overall survival (OS) rate were 58.2 ± 3.0%, 46.8 ± 3.2%, and 46.5 ± 2.6%, 34.4 ± 2.5%, respectively. Nomogram was finally developed for CSS and OS according to the identified independent factors: age, tumor extent, primary tumor surgery, tumor size, and pathology grade. For UMBT patients who received radiotherapy or chemotherapy, surgical intervention was associated with better CSS (pr = 0.003, pc = 0.002) and OS (pr = 0.035, pc = 0.002), respectively. CONCLUSIONS: Nomogram was developed for individual UMBT patient to predict short and long-term CSS and OS rate, and more external patient cohorts are warranted for validation. Surgery improves outcomes for UMBT patients who received either radiotherapy or chemotherapy.

Identification of ATG7 as a Regulator of Proferroptosis and Oxidative Stress in Osteosarcoma.

Background: Ferroptosis has gained significant attention from oncologists as a vital outcome of oxidative stress. The aim of this study was to develop a prognostic signature that was based on the ferroptosis-related genes (FRGs) for osteosarcoma patients and explore their specific role in osteosarcoma. Methods: The training cohort dataset was extracted from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Different techniques like the univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, multivariate Cox regression analyses, and the Kaplan-Meier (KM) survival analyses were utilized to develop a prognostic signature. Then, the intrinsic relationship between the developed gene signature and the infiltration levels of the immune cells was further investigated. An external validation dataset from the Gene Expression Omnibus (GEO) database was employed to assess the predictive ability of the developed gene signature. Subsequently, the specific function of potential FRG in affecting the oxidative stress reaction and ferroptosis of osteosarcoma cells was identified. Results: A prognostic signature based on 5 FRGs (CBS, MUC1, ATG7, SOCS1, and PEBP1) was developed, and the patients were classified into the low- and high-risk groups (categories). High-risk patients displayed poor overall survival outcomes. The risk level was seen to be an independent risk factor for determining the prognosis of osteosarcoma patients (p < 0.001, hazard ratio: 7.457, 95% CI: 3.302-16.837). Additionally, the risk level was associated with immune function, which might affect the survival status of osteosarcoma patients. Moreover, the findings of the study indicated that the expression of ATG7 was related to the regulation of oxidative stress in osteosarcoma. Silencing the ATG7 gene promoted the proliferation and migration in osteosarcoma cells, suppressing the oxidative stress and ferroptosis process. Conclusions: A novel FRG signature was developed in this study to predict the prognosis of osteosarcoma patients. The results indicated that ATG7 might regulate the process of oxidative stress and ferroptosis in osteosarcoma cells and could be used as a potential target to develop therapeutic strategies for treating osteosarcoma.

PTBP1 as a Promising Predictor of Poor Prognosis by Regulating Cell Proliferation, Immunosuppression, and Drug Sensitivity in SARC.

Background: Sarcomas (SARC) have been found as rare and heterogeneous malignancies with poor prognosis. PTBP1, belonging to the hnRNPs family, plays an essential role in some biological functions (e.g., pre-mRNA splicing, cell growth, and nervous system development). However, the role of PTBP1 in SARC remains unclear. In this study, the aim was to investigate the potential role of PTBP1 with a focus on SARC. Methods: The expression, prognostic value, possible biological pathways of PTBP1, and its relationship with immune infiltration and drug sensitivity were comprehensively analyzed based on multiple databases. PTBP1 was further validated in osteosarcoma as the most prominent bone SARC. The expression of PTBP1 was investigated through IHC. The prognostic value of PTBP1 was verified in TARGET-OS databases. CRISPR/Cas9-mediated PTBP1 knockout HOS human osteosarcoma cell lines were used to assess the effect of PTBP1 on cell proliferation, migration, metastasis and cell cycle by CCK-8, Transwell migration, invasion, and FACS experiment. Result: PTBP1 was highly expressed and significantly correlated with poor prognosis in several cancers, especially in SARC, which was validated in the clinical cohort and osteosarcoma cell lines. The genetic alteration of PTBP1 was found most frequently in SARC. Besides, PTBP1 played a role in oncogenesis and immunity through cell cycle, TGFB, autophagy, and WNT pathways at a pan-cancer level. Knockout of PTBP1 was observed to negatively affect proliferation, migration, metastasis, and cell cycle of osteosarcoma in vitro. Furthermore, PTBP1 was significantly correlated with tumor immune infiltration, DNA methylation, TMB, and MSI in a wide variety of cancers. Moreover, the potential of the expression level of PTBP1 in predicting drug sensitivity was assessed. Conclusions: PTBP1 is highly expressed and correlated with prognosis and plays a vital pathogenic role in oncogenesis and immune infiltration of various cancers, especially for SARC, which suggests that it may be a promising prognostic marker and therapeutic target in the future.

A Novel Defined Hypoxia-Related Gene Signature for Prognostic Prediction of Patients With Ewing Sarcoma.

The therapeutic strategy of Ewing sarcoma (EWS) remains largely unchanged over the past few decades. Hypoxia is reported to have an impact on tumor cell progression and is regarded as a novel potential therapeutic target in tumor treatment. This study aimed at developing a prognostic gene signature based on hypoxia-related genes (HRGs). EWS patients from GSE17674 in the GEO database were analyzed as a training cohort, and differently expressed HRGs between tumor and normal samples were identified. The univariate Cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate Cox regression analyses were used in this study. A total of 57 EWS patients from the International Cancer Genome Consortium (ICGC) database were set as the validation cohort. A total of 506 differently expressed HRGs between tumor and normal tissues were identified, among which 52 were associated with the prognoses of EWS patients. Based on 52 HRGs, EWS patients were divided into two molecular subgroups with different survival statuses. In addition, a prognostic signature based on 4 HRGs (WSB1, RXYLT1, GLCE and RORA) was constructed, dividing EWS patients into low- and high-risk groups. The 2-, 3- and 5-years area under the receiver operator characteristic curve of this signature was 0.913, 0.97 and 0.985, respectively. It was found that the survival rates of patients in the high-risk group were significantly lower than those in the low-risk group (p < 0.001). The risk level based on the risk score could serve as an independent clinical factor for predicting the survival probabilities of EWS patients. Additionally, antigen-presenting cell (APC) related pathways and T cell co-inhibition were differently activated in two risk groups, which may result in different prognoses. CTLA4 may be an effective immune checkpoint inhibitor to treat EWS patients. All results were verified in the validation cohort. This study constructed 4-HRGs as a novel prognostic marker for predicting survival in EWS patients.

Identifying the Risk Factors and Estimating the Prognosis in Patients with Pelvis and Spine Ewing Sarcoma: A Population-Based Study.

STUDY DESIGN: Retrospective analysis. OBJECTIVE: The study was designed to: (1) figure out risk factors of metastasis; (2) explore prognostic factors and develop a nomogram for pelvis and spine Ewing sarcoma (PSES). SUMMARY OF BACKGROUND DATA: Tools to predict survival of PSES are still insufficient. Nomogram has been widely developed in clinical oncology. Moreover, risk factors of PSES metastasis are still unclear. METHODS: The data were collected and analyzed from the Surveillance, Epidemiology, and End Results (SEER) database. The optimal cutoff values of continuous variables were identified by X-tile software. The prognostic factors of survival were performed by Kaplan-Meier method and multivariate Cox proportional hazards modeling. Nomograms were further constructed for estimating 3- and 5-year cancer-specific survival (CSS) and overall survival (OS) by using R with rms package. Meanwhile, Pearson χ2 test or Fisher exact test, and logistic regression analysis were used to analyze the risk factors for the metastasis of PSES. RESULTS: A total of 371 patients were included in this study. The 3- and 5-year CSS and OS rate were 65.8 ±â€Š2.6%, 55.2 ±â€Š2.9% and 64.3 ±â€Š2.6%, 54.1 ±â€Š2.8%, respectively. The year of diagnosis, tumor size, and lymph node invasion were associated with metastasis of patients with PSES. A nomogram was developed based on identified factors including: age, tumor extent, tumor size, and primary site surgery. The concordance index (C-index) of CSS and OS were 0.680 and 0.679, respectively. The calibration plot showed the similar trend of 3-year, 5-year CSS, and OS of PSES patients between nomogram-based prediction and actual observation, respectively. CONCLUSION: PSES patients with earlier diagnostic year (before 2010), larger tumor size (>59 mm), and lymph node invasion, are more likely to have metastasis. We developed a nomogram based on age, tumor extent, tumor size, and surgical treatments for determining the prognosis for patients with PSES, while more external patient cohorts are warranted for validation.Level of Evidence: 3.

Comparing the characteristics and predicting the survival of patients with head and neck melanoma versus body melanoma: a population-based study.

BACKGROUND: Previous studies reported cutaneous melanoma in head and neck (HNM) differed from those in other regions (body melanoma, BM). Individualized tools to predict the survival of patients with HNM or BM remain insufficient. We aimed at comparing the characteristics of HNM and BM, developing and validating nomograms for predicting the survival of patients with HNM or BM. METHODS: The information of patients with HNM or BM from 2004 to 2015 was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The HNM group and BM group were randomly divided into training and validation cohorts. We used the Kaplan-Meier method and multivariate Cox models to identify independent prognostic factors. Nomograms were developed via the rms and dynnom packages, and were measured by the concordance index (C-index), the area under the curve (AUC) of the receiver operating characteristic (ROC) curve and calibration plots. RESULTS: Of 70,605 patients acquired, 21% had HNM and 79% had BM. The HNM group contained more older patients, male sex and lentigo maligna melanoma, and more frequently had thicker tumors and metastases than the BM group. The 5-year cancer-specific survival (CSS) and overall survival (OS) rates were 88.1 ± 0.3% and 74.4 ± 0.4% in the HNM group and 92.5 ± 0.1% and 85.8 ± 0.2% in the BM group, respectively. Eight variables (age, sex, histology, thickness, ulceration, stage, metastases, and surgery) were identified to construct nomograms of CSS and OS for patients with HNM or BM. Additionally, four dynamic nomograms were available on web. The internal and external validation of each nomogram showed high C-index values (0.785-0.896) and AUC values (0.81-0.925), and the calibration plots showed great consistency. CONCLUSIONS: The characteristics of HNM and BM are heterogeneous. We constructed and validated four nomograms for predicting the 3-, 5- and 10-year CSS and OS probabilities of patients with HNM or BM. These nomograms can serve as practical clinical tools for survival prediction and individual health management.