Exploring the common targets of well-differentiated and dedifferentiated retroperitoneal liposarcoma via gene co-expression analysis.

Objective: This study aimed to identify common therapeutic targets for well-differentiated and dedifferentiated retroperitoneal liposarcoma. Methods: Patient clinical data were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, and survival differences were analyzed using the log-rank test. Gene expression data were sourced from the Gene Expression Omnibus (GEO) dataset GSE159659, with differential gene expression analysis conducted through GEO2R. Protein-protein interaction networks were developed using STRING and Cytoscape to identify key hub genes. Gene Ontology (GO) and KEGG pathway enrichment analyses were performed using R, and transcription factors associated with the hub genes were predicted with TRRUST. Results: Significant survival differences were found between patients with well-differentiated and dedifferentiated retroperitoneal liposarcoma. Ninety-six differentially expressed genes with similar expression patterns were identified in both types. A protein-protein interaction network highlighted 12 hub genes and 24 transcription factors. Enrichment analysis pointed to the importance of lipid localization, storage, cytokine signaling, and metal ion absorption in both liposarcoma subtypes. Four potential therapeutic drugs were successfully predicted. Conclusion: This study identifies common molecular targets in well-differentiated and dedifferentiated retroperitoneal liposarcoma, providing new avenues for mechanistic studies and potential therapeutic development.

Stimulator of Interferon Genes-Activated Biomimetic Dendritic Cell Nanovaccine as a Chemotherapeutic Booster to Enhance Systemic Fibrosarcoma Treatment.

Fibrosarcoma, a malignant mesenchymal tumor, is characterized by aggressive invasiveness and a high recurrence rate, leading to poor prognosis. Anthracycline drugs, such as doxorubicin (DOX), represent the frontline chemotherapy for fibrosarcoma, but often exhibit suboptimal efficacy. Recently, exploiting the stimulator of interferon genes (STING)-mediated innate immunity has emerged as a hopeful strategy for cancer treatment. Integrating chemotherapy with immunomodulators in chemo-immunotherapy has shown potential for enhancing treatment outcomes. Herein, we introduce an advanced dendritic cell (DC) nanovaccine, cGAMP@PLGA@CRTM (GP@CRTM), combined with low-dose DOX to enhance fibrosarcoma chemo-immunotherapy. The nanovaccine consists of poly(lactic-co-glycolic acid) (PLGA) nanoparticles encapsulating the STING agonist 2,3-cGAMP (cGAMP@PLGA, GP) as its core, and a calreticulin (CRT) high-expressing fibrosarcoma cell membrane (CRTM) as the shell. Exposing CRT on the vaccine surface aids in recruiting DCs and stimulating uptake, facilitating efficient simultaneous delivery of STING agonists and tumor antigens to DCs. This dual delivery method effectively activates the STING pathway in DCs, triggering sustained immune stimulation. Simultaneously, low-dose DOX reduces chemotherapy-related side effects, directly kills a subset of tumor cells, and increases tumor immunogenicity, thus further amplifying immune therapeutic performance. Hence, these findings demonstrate the potential of DC nanovaccine GP@CRTM as a booster for chemotherapy. Synergistically combining low-dose DOX with the DC nanovaccine emerges as a powerful chemo-immunotherapy strategy, optimizing systemic fibrosarcoma therapy.

Exploring the biological behavior differences between retroperitoneal and non-retroperitoneal liposarcomas.

Background: Liposarcoma is a malignant tumor that originates from adipose tissue and can occur in any part of the body. There is currently no clear conclusion on whether there are significant differences in prognosis between liposarcoma at different anatomical locations, especially retroperitoneal liposarcoma (RLPS) and non retroperitoneal liposarcoma (NRLPS). The aim of this study is to reveal whether there are differences in prognosis between these two locations of liposarcoma, and further explore the fundamental reasons behind these differences. Methods: We conducted an in-depth investigation into the factors affecting the prognosis of patients with liposarcoma by analyzing the data from the Surveillance, Epidemiology, and End Results Program (SEER) database. Then, we used propensity score matching (PSM) to balance these prognostic factors for comparative analysis of survival between RLPS and NRLPS. In addition, by analyzing transcriptome and whole exome data from TCGA and the Japan Genotypic Phenotype Archive (JGA), we identified genes with significant expression differences and explored changes in the immune microenvironment. Result: Through analysis of RLPS and NRLPS patients in the SEER database, we observed significant prognostic differences between the two groups, with RLPS exhibiting worse prognosis (p < 0.001). Even after adjusting for confounding factors through PSM, these survival rate differences remained significant, with RLPS still showing worse prognosis (p = 0.017). Furthermore, our analysis of transcriptomic data led to the identification of 467 differentially expressed genes. Additionally, we noted significant differences in the immune microenvironment and whole exome sequencing data between the two groups. Conclusion: There are significant differences between patients with RLPS and NRLPS. Therefore, from clinical research to treatment strategies, RLPS and NRLPS should be considered as two distinct types of tumors, necessitating differentiated approaches for their study and treatment.

Radiotherapy and surgery remain effective treatment options for retroperitoneal MPNST: a retrospective study based on SEER database.

Introduction: The proportion of retroperitoneal malignant peripheral nerve sheath tumours (RMPNST) in retroperitoneal tumors is less than 5%, but the mortality rate is very high. However, there is no relevant research focused on RMPNST only. Methods: We retrospectively analyzed data from the SEER database of patients with primary RMPNST from 2000 to 2019, by leveraging the advantages of the Seer database, we can explore the prognosis of such rare diseases. Kaplan-Meier method was used to construct the survival curve, and cox regression model was used to analyze the factors affecting the prognosis of patients. In addition, a model was developed to distinguish high-risk and low-risk patients. Results: This study included a total of 52 patients, with a median survival time of 39 months (95% CI 12.740-65.260) and a 5-year survival rate of 44.2% (95% CI 0.299-0.565). Radiotherapy (p = 0.004, OR: 1.475, 95% CI 0.718-3.033), metastasis disease (p = 0.002, OR: 5.596, 95% CI 2.449-47.079) and surgery (p = 0.003, OR: 5.003, 95% CI 0.011-0.409) were associated with overall survival (OS). The 5-year distant metastasis rate was 36% (95% CI 0.221-0.499). We used the above risk factors to separate patients into high and low groups and evaluate the results through the receiver operating characteristic (ROC) curve. This model is beneficial for guiding the selection of treatment strategies. Conclusion: The majority of RMPNST patients have a good prognosis after surgery, and the establishment of high-low group is helpful for clinical decision-making.

Nomogram development and external validation for predicting overall survival and cancer-specific survival in patients with primary retroperitoneal sarcoma: a retrospective cohort study.

BACKGROUND: Primary retroperitoneal sarcoma (RPS) comprises over 70 histologic subtypes, yet there are limited studies that have developed prognostic nomograms for RPS patients to predict overall survival (OS) and cancer-specific survival (CSS). The objective of this study was to construct prognostic nomograms for predicting OS and CSS in RPS patients. METHODS: We identified a total of 1166 RPS patients from the Surveillance, Epidemiology and End Results (SEER) database, and an additional 261 cases were collected from a tertiary cancer center. The study incorporated various clinicopathological and epidemiologic features as variables, and prediction windows for overall survival (OS) and cancer-specific survival (CSS) were set at 3, 5, and 7 years. Multivariable Cox models were utilized to develop the nomograms, and variable selection was performed using a backward procedure based on the Akaike Information Criterion. To evaluate the performance of the nomograms in terms of calibration and discrimination, we used calibration plots, coherence index, and area under the curve. FINDINGS: The study included 818 patients in the development cohort, 348 patients in the internal validation cohort, and 261 patients in the external validation cohort. The backward procedure selected the following variables: age, French Federation of Cancer Centers Sarcoma Group (FNCLCC) grade, pre-/postoperative chemotherapy, tumor size, primary site surgery, and tumor multifocality. The validation results demonstrated that the nomograms had good calibration and discrimination, with C-indices of 0.76 for OS and 0.81 for CSS. Calibration plots also showed good consistency between the predicted and actual survival rates. Furthermore, the areas under the time-dependent receiver operating characteristic curves for the 3-, 5-, and 7-year OS (0.84, 0.82, and 0.78, respectively) and CSS (0.88, 0.88, and 0.85, respectively) confirmed the accuracy of the nomograms. INTERPRETATION: Our study developed accurate nomograms to predict OS and CSS in patients with RPS. These nomograms have important clinical implications and can assist healthcare providers in making informed decisions regarding patient care and treatment options. They may also aid in patient counseling and stratification in clinical trials.

Identification of MDM2 as a prognostic and immunotherapeutic biomarker in a comprehensive pan-cancer analysis: A promising target for breast cancer, bladder cancer and ovarian cancer immunotherapy.

BACKGROUND: The murine double minute 2 (MDM2) gene is a crucial factor in the development and progression of various cancer types. Multiple rigorous scientific studies have consistently shown its involvement in tumorigenesis and cancer progression in a wide range of cancer types. However, a comprehensive analysis of the role of MDM2 in human cancer has yet to be conducted. METHODS: We used various databases, including TIMER2.0, TCGA, GTEx and STRING, to analyze MDM2 expression and its correlation with clinical outcomes, interacting genes and immune cell infiltration. We also investigated the association of MDM2 with immune checkpoints and performed gene enrichment analysis using DAVID tools. RESULTS: The pan-cancer MDM2 analysis found that MDM2 expression and mutation status were observably different in 25 types of cancer tissue compared with healthy tissues, and prognosis analysis showed that there was a significant correlation between MDM2 expression and patient prognosis. Furthermore, correlation analysis showed that MDM2 expression was correlated with tumor mutational burden, microsatellite instability and drug sensitivity in certain cancer types. We found that there was an association between MDM2 expression and immune cell infiltration across cancer types, and MDM2 inhibitors might enhance the effect of immunotherapy on breast cancer, bladder cancer and ovarian cancer. CONCLUSIONS: The first systematic pan-cancer analysis of MDM2 was conducted, and it demonstrated that MDM2 was a reliable prognostic biomarker and was closely related to cancer immunity, providing a potential immunotherapeutic target for breast cancer, bladder cancer and ovarian cancer.