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Introduction: The aim of the study was to investigate the clinical characteristics, surgical treatment, and long-term efficacy of primary right heart tumors. Methods: This study is retrospective analysis of the clinical data of 70 patients with primary right heart tumors admitted to our department between 1980 and 2022 (observation group) and 70 patients with left heart tumors during the same period (control group). The surgical treatment was performed under cardiopulmonary bypass after differential diagnosis by echocardiography, cardiac CTA, and PET-CT before the surgery. The perioperative characteristics, recurrence rate, and long-term survival rates of right heart tumor versus left heart tumor were compared. Results: The most common pathological types of right heart tumors were myxoma (60%), lipoma (8.57%), and papillary elastofibroma (7.14%). During the perioperative period, there were 1 case of systemic embolism in the observation group, compared with 6 in the control group (p = 0.026), 13 cases of malignant tumor in the observation group versus 1 in the control group (p = 0.01). During the follow-up period, there were 15 cases of tumor recurrence and 17 cases of death in the observation group versus 4 (p = 0.002) and 7 in the control group (p = 0.006), comparatively. Conclusion: Compared with left heart tumors, primary right heart tumors had a higher incidence of malignant tumors and a lower risk of systemic embolism during perioperative period. During the follow-up period, primary right heart tumors had a higher rate of tumor recurrence and a lower long-term survival rate. [ABSTRACT FROM AUTHOR]

Background: Alterations in kidney function and increased risk of kidney diseases in patients with inflammatory bowel disease (IBD) have been reported, but the causal relationship remains unclear. Herein, Mendelian randomization was employed to identify the causal effect of inflammatory bowel disease on kidney function and the risk of chronic kidney disease (CKD), urolithiasis, and IgA nephropathy. Methods: The International Inflammatory Bowel Disease Genetics Consortium provided the summary-level genome-wide association study (GWAS) data that correlates with Crohn's disease (CD) and ulcerative colitis (UC). GWAS data for estimated glomerular filtration rate from serum creatinine (eGFRcrea), urine albumin–creatinine ratio (uACR), and CKD were obtained from the CKDGen Consortium, and GWAS data for urolithiasis were obtained from the FinnGen consortium. The summary-level GWAS data for IgA nephropathy were obtained from the meta-analysis of UK-biobank, FinnGen, and Biobank Japan. Inverse-variance weighted was used as the primary estimate. Furthermore, the Steiger test was used to validate the direction of causality. Results: The inverse-variance weighted data revealed that genetically predicted UC significantly increased uACR levels, while genetically predicted CD significantly increased the risk of urolithiasis. Conclusions: UC increases the levels of uACR, and CD increases the risk of urolithiasis. [ABSTRACT FROM AUTHOR]

Background: The tumor microenvironment (TME) has a central role in the oncogenesis of osteosarcomas. The composition of the TME is essential for the interaction between tumor and immune cells. The aim of this study was to establish a prognostic index (TMEindex) for osteosarcoma based on the TME, from which estimates about patient survival and individual response to immune checkpoint inhibitor (ICI) therapy can be deduced. Methods: Based on osteosarcoma samples from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, the ESTIMATE algorithm was used to estimate ImmuneScore and StromalScore. Combined differentially expressed gene analysis, weighted gene co-expression network analyses, the Least Absolute Shrinkage and Selection Operator regression and stepwise regression to construct the TMEindex. The prognostic role of TMEindex was validated in three independent datasets. The molecular and immune characteristics of TMEindex and the impact on immunotherapy were then comprehensively investigated. The expression of TMEindex genes in different cell types and its effects on osteosarcoma cells were explored by scRNA-Seq analysis and molecular biology experiments. Results: Fundamental is the expression of MYC, P4HA1, RAMP1 and TAC4. Patients with high TMEindex had worse overall survival, recurrence-free survival, and metastasis-free survival. TMEindex is an independent prognostic factor in osteosarcoma. TMEindex genes were mainly expressed in malignant cells. The knockdown of MYC and P4HA1 significantly inhibited the proliferation, invasion and migration of osteosarcoma cells. A high TME index is related to the MYC, mTOR, and DNA replication-related pathways. In contrast, a low TME index is related to immune-related signaling pathways such as the inflammatory response. The TMEindex was negatively correlated with ImmuneScore, StromalScore, immune cell infiltration, and various immune-related signature scores. Patients with a higher TMEindex had an immune-cold TME and higher invasiveness. Patients with a low TME index were more likely to respond to ICI therapy and achieve clinical benefit. In addition, the TME index correlated with response to 29 oncologic drugs. Conclusions: The TMEindex is a promising biomarker to predict the prognosis of patients with osteosarcoma and their response to ICI therapy, and to distinguish the molecular and immune characteristics. [ABSTRACT FROM AUTHOR]

Catchment modelling is an effective approach to simulating the rainfall-runoff process. Estimating parameters is challenging in urban catchments with heterogeneous land use land cover (LULC). This paper describes a novel and reproducible approach to initialise the parameters for modelling catchment hydrology. The Alexandra canal catchment, Australia, was selected as the study catchment. A pixel-based LULC map was generated from the catchment's orbital image using the Deep Learning (DL) techniques. Integrate the LULC map with subcatchment delineation and hydraulic layout, group LULC attributes to compute the area and imperviousness fraction at pixel scale. The distance from each pixel to the subcatchment outlet was vectorised to estimate flow length. The cumulative likelihood and Kolmogorov–Smirnov (KS) were adopted to describe the parameter distributions, evaluate the goodness-of-fit and LULC effect. Results reflect a limited effect of LULC on flow length, and the approach can initialise the parameters for conceptual catchment modelling systems. [ABSTRACT FROM AUTHOR]

Despite various treatment attempts, the heterogenous group of soft tissue sarcomata (STS) with more than 100 subtypes still shows poor outcomes. Therefore, effective biomarkers for prognosis prediction and personalized treatment are of high importance. The Procollagen-Lysine, 2-Oxoglutarate 5-Dioxygenase (PLOD) gene family, which is related to multiple cancer entities, consists of three members which encode important enzymes for the formation of connective tissue. The relation to STS, however, has not yet been explored. In this study, data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases were used to analyze the role of PLOD1–3 in STS. It was found that an overexpression of PLOD family members correlates with poor prognosis, which might be due to an increased infiltration of immune-related cells in the tumor microenvironment. In STS, the expression of PLOD genes could be a novel biomarker for prognosis and a personalized, more aggressive treatment in these patients. [ABSTRACT FROM AUTHOR]

Kinesin family member C1 (KIFC1) is a minus-end-directed motor protein that is critically involved in microtubule crosslinking and spindle formation. KIFC1 is essential for supernumerary centrosomes, and it is associated with the initiation and progression of cancers. In the present study, we initially reviewed the The Cancer Genome Atlas database and observed that KIFC1 is abundantly expressed in most types of tumors. We then analyzed the gene alteration profiles, protein expressions, prognoses, and immune reactivities of KIFC1 in more than 10,000 samples from several well-established databases. In addition, we conducted a gene set enrichment analysis to investigate the potential mechanisms for the roles of KIFC1 in carcinogenesis. The pan-cancer analysis of KIFC1 demonstrates significant statistical correlations of the KIFC1 expression with the clinical prognoses, the oncogenic signature gene sets, the myeloid-derived suppressor cell infiltration, the ImmunoScore, the immune checkpoints, the microsatellite instabilities, and the tumor mutational burdens across multiple tumors. These data may provide important information on the understanding of the role and mechanisms of KIFC1 in carcinogenesis and immunotherapy, as well as on the clinical progression of a variety of cancers. [ABSTRACT FROM AUTHOR]

Pituitary tumor-transforming gene 1 (PTTG1) encodes a multifunctional protein that is involved in many cellular processes. However, the potential role of PTTG1 in tumor formation and its prognostic function in human pan-cancer is still unknown. The analysis of gene alteration, PTTG1 expression, prognostic function, and PTTG1-related immune analysis in 33 types of tumors was performed based on various databases such as The Cancer Genome Atlas database, the Genotype-Tissue Expression database, and the Human Protein Atlas database. Additionally, PTTG1-related gene enrichment analysis was performed to investigate the potential relationship and possible molecular mechanisms between PTTG1 and tumors. Overexpression of PTTG1 may lead to tumor formation and poor prognosis in various tumors. Consequently, PTTG1 acts as a potential oncogene in most tumors. Additionally, PTTG1 is related to immune infiltration, immune checkpoints, tumor mutational burden, and microsatellite instability. Thus, PTTG1 could be potential biomarker for both prognosis and outcomes of tumor treatment and it could also be a promising target in tumor therapy. [ABSTRACT FROM AUTHOR]

Lower-grade glioma (LGG) is a group of tumors arising from the cells of the central nervous system. Although various therapy interventions are used, the prognosis remains different. Novel biomarkers are needed for the prognosis of disease and novel therapeutic strategies in LGG. The procollagen-lysine, 2-oxoglutarate 5-dioxygenase (PLOD) family contains three members and is related to multiple cancers, yet it was not investigated in LGG. Data from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) cohorts were used to analyze the role of PLOD in LGG. As the PLOD family is involved in processes, such as tumor formation and cancer metastasis, we focused on its relationship to the tumor microenvironment (TME) in LGG. A high expression of the PLOD family relates to poor prognosis and high infiltration of immune cells within the TME. The expression level of the PLOD family might become a novel biomarker for prognosis and is a potential target for individual treatment decisions in LGG. [ABSTRACT FROM AUTHOR]

Obesity is associated with significantly higher mortality rates, and excess adipose tissue is involved in respective pathologies. Here we established a human adipose tissue slice cultures (HATSC) model ex vivo. HATSC match the in vivo cell composition of human adipose tissue with, among others, mature adipocytes, mesenchymal stem cells as well as stroma tissue and immune cells. This is a new method, optimized for live imaging, to study adipose tissue and cell-based mechanisms of obesity in particular. HATSC survival was tested by means of conventional and immunofluorescence histological techniques, functional analyses and live imaging. Surgery-derived tissue was cut with a tissue chopper in 500 μm sections and transferred onto membranes building an air-liquid interface. HATSC were cultured in six-well plates filled with Dulbecco's Modified Eagle's Medium (DMEM), insulin, transferrin, and selenium, both with and without serum. After 0, 1, 7 and 14 days in vitro, slices were fixated and analyzed by morphology and Perilipin A for tissue viability. Immunofluorescent staining against IBA1, CD68 and Ki67 was performed to determine macrophage survival and proliferation. These experiments showed preservation of adipose tissue as well as survival and proliferation of monocytes and stroma tissue for at least 14 days in vitro even in the absence of serum. The physiological capabilities of adipocytes were functionally tested by insulin stimulation and measurement of Phospho-Akt on day 7 and 14 in vitro. Viability was further confirmed by live imaging using Calcein-AM (viable cells) and propidium iodide (apoptosis/necrosis). In conclusion, HATSC have been successfully established by preserving the monovacuolar form of adipocytes and surrounding macrophages and connective tissue. This model allows further analysis of mature human adipose tissue biology ex vivo. [ABSTRACT FROM AUTHOR]

Simple Summary: Soft tissue sarcomas (STS) are a group of rare malignant tumors with high tissue heterogeneity and poor prognosis, and which are still without effective individualized immunotherapy approaches. In this study, four potential tumor antigens, six STS immune subtypes, and six functional gene modules were identified. The different immune subtypes have different molecular, cellular, and clinical characteristics. The superiority of mRNA vaccine therapies has been demonstrated during the current pandemic as well as in tumor vaccine studies, and the present study provides guidance for future mRNA vaccine development. Furthermore, in future individualized immunotherapies for STS, it is possible to select different immunotherapies based on the different immune subtypes identified in this study. In fact, the immune subtypes identified in this study explain, to some extent, the failure of immunotherapy for certain STS subtypes in previous clinical trials, and facilitate further understanding of strategy selection for the immunotherapy of STS. To our knowledge, this is the first study to address STS mRNA vaccine development and immunophenotyping. This study provides a theoretical framework for STS mRNA vaccine development and the selection of patients for vaccination and provides a reference for promoting individualized immunotherapy. Soft tissue sarcomas (STS) are a rare disease with high recurrence rates and poor prognosis. Missing therapy options together with the high heterogeneity of this tumor type gives impetus to the development of individualized treatment approaches. This study identifies potential tumor antigens for the development of mRNA tumor vaccines for STS and explores potential immune subtypes, stratifying patients for immunotherapy. RNA-sequencing data and clinical information were extracted from 189 STS samples from The Cancer Genome Atlas (TCGA) and microarray data were extracted from 103 STS samples from the Gene Expression Omnibus (GEO). Potential tumor antigens were identified using cBioportal, the Oncomine database, and prognostic analyses. Consensus clustering was used to define immune subtypes and immune gene modules, and graph learning-based dimensionality reduction analysis was used to depict the immune landscape. Finally, four potential tumor antigens were identified, each related to prognosis and antigen-presenting cell infiltration in STS: HLTF, ITGA10, PLCG1, and TTC3. Six immune subtypes and six gene modules were defined and validated in an independent cohort. The different immune subtypes have different molecular, cellular, and clinical characteristics. The immune landscape of STS reveals the immunity-related distribution of patients and intra-cluster heterogeneity of immune subtypes. This study provides a theoretical framework for STS mRNA vaccine development and the selection of patients for vaccination, and provides a reference for promoting individualized immunotherapy. [ABSTRACT FROM AUTHOR]

Simple Summary: Soft tissue sarcomas (STS) still lack effective clinical stratification and prognostic models. The aim of this study is to establish a reliable prognostic gene signature in STS. Using 189 STS samples from the TCGA database, a four-gene signature (including DHRS3, JRK, TARDBP and TTC3) and nomograms that can be used to predict the overall survival and relapse free survival of STS patients was developed. The predictive ability for metastasis free survival was externally verified in the GEO cohort. We demonstrated that the novel gene signature provides an attractive platform for risk stratification and prognosis prediction of STS patients, which is of great importance for individualized clinical treatment and long-term management of patients with this rare and severe disease. Soft tissue sarcomas (STS), a group of rare malignant tumours with high tissue heterogeneity, still lack effective clinical stratification and prognostic models. Therefore, we conducted this study to establish a reliable prognostic gene signature. Using 189 STS patients' data from The Cancer Genome Atlas database, a four-gene signature including DHRS3, JRK, TARDBP and TTC3 was established. A risk score based on this gene signature was able to divide STS patients into a low-risk and a high-risk group. The latter had significantly worse overall survival (OS) and relapse free survival (RFS), and Cox regression analyses showed that the risk score is an independent prognostic factor. Nomograms containing the four-gene signature have also been established and have been verified through calibration curves. In addition, the predictive ability of this four-gene signature for STS metastasis free survival was verified in an independent cohort (309 STS patients from the Gene Expression Omnibus database). Finally, Gene Set Enrichment Analysis indicated that the four-gene signature may be related to some pathways associated with tumorigenesis, growth, and metastasis. In conclusion, our study establishes a novel four-gene signature and clinically feasible nomograms to predict the OS and RFS. This can help personalized treatment decisions, long-term patient management, and possible future development of targeted therapy. [ABSTRACT FROM AUTHOR]

The overexpression of the enzymes involved in the degradation of procollagen lysine is correlated with various tumor entities. Procollagen-lysine, 2-oxoglutarate 5-dioxygenase 3 (PLOD3) expression was found to be correlated to the progression and migration of cancer cells in gastric, lung and prostate cancer. Here, we analyzed the gene expression, protein expression, and the clinical parameters of survival across 33 cancers based on the Clinical Proteomic Tumor Analysis Consortium (CPTAC), function annotation of the mammalian genome 5 (FANTOM5), Gene Expression Omnibus (GEO), Genotype-Tissue Expression (GTEx), Human Protein Atlas (HPA) and The Cancer Genome Atlas (TCGA) databases. Genetic alteration, immune infiltration and relevant cellular pathways were analyzed in detail. PLOD3 expression negatively correlated with survival periods and the infiltration level of CD8+ T cells, but positively correlated to the infiltration of cancer associated fibroblasts in diverse cancers. Immunohistochemistry in colon carcinomas, glioblastomas, and soft tissue sarcomas further confirm PLOD 3 expression in human cancer tissue. Moreover, amplification and mutation accounted for the largest proportion in esophageal adenocarcinoma and uterine corpus endometrial carcinoma, respectively; the copy number alteration of PLOD3 appeared in all cancers from TCGA; and molecular mechanisms further proved the effect of PLOD3 on tumorigenesis. In particular, PLOD3 expression appears to have a tumor immunological effect, and is related to multiple immune cells. Furthermore, it is also associated with tumor mutation burden and microsatellite instability in various tumors. PLOD3 acts as an inducer of various cancers, and it could be a potential biomarker for prognosis and targeted treatment. [ABSTRACT FROM AUTHOR]

Regulator of Chromatin Condensation 1 (RCC1) is the only known guanine nucleotide exchange factor that acts on the Ras-like G protein Ran and plays a key role in cell cycle regulation. Although there is growing evidence to support the relationship between RCC1 and cancer, detailed pancancer analyses have not yet been performed. In this genome database study, based on The Cancer Genome Atlas, Genotype-Tissue Expression and Gene Expression Omnibus databases, the potential role of RCC1 in 33 tumors' entities was explored. The results show that RCC1 is highly expressed in most human malignant neoplasms in contrast to healthy tissues. RCC1 expression is closely related to the prognosis of a broad variety of tumor patients. Enrichment analysis showed that some tumor-related pathways such as "cell cycle" and "RNA transport" were involved in the functional mechanism of RCC1. In particular, the conducted analysis reveals the relation of RCC1 to multiple immune checkpoint genes and suggests that the regulation of RCC1 is closely related to tumor infiltration of cancer-associated fibroblasts and CD8+ T cells. Coherent data demonstrate the association of RCC1 with the tumor mutation burden and microsatellite instability in various tumors. These findings provide new insights into the role of RCC1 in oncogenesis and tumor immunology in various tumors and indicate its potential as marker for therapy prognosis and targeted treatment strategies. [ABSTRACT FROM AUTHOR]