Correlative Study on the Relationship between the Expression of m6a-Related Genes and the Prognosis and Immunotherapy of Soft Tissue Sarcoma
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ABSTRACT:
SUBMITTER: Qiu Y
PROVIDER: S-EPMC10667055 | biostudies-literature | 2022 Jan
REPOSITORIES: biostudies-literature
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Project description:N6-methyladenosine (m6A) methylation, one of the most crucial RNA modifications, has been proven to play a key role that affect prognosis of soft tissue sarcoma (STS). However, m6A methylation potential role in STS metabolic processes remains unknown. We comprehensively estimated the m6A metabolic molecular subtypes and corresponding survival, immunity, genomic and stemness characteristics based on 568 STS samples and m6A related metabolic pathways. Then, to quantify the m6A metabolic subtypes, machine learning algorithms were used to develop the m6A-metabolic Scores of individual patients. Finally, two distinct m6A metabolic subtypes (Cluster A and Cluster B) among the STS patients were identified. Compared to Cluster B subtype, the Cluster A subtype was mainly characterized by better survival advantages, activated anti-tumor immune microenvironment, lower gene mutation frequency and higher anti-PD-1 immunotherapy response rates. We also found that the m6A-metabolic Scores could accurately predict the molecular subtype of STS, prognosis, the abundance of immune cell infiltration, tumor metastasis status, sensitivity to chemotherapeutics and immunotherapy response. In general, this study revealed that m6A-regulated tumor metabolism processes played a key role in terms of prognosis of STS, tumor progression, and immune microenvironment. The identification of metabolic molecular subtypes and the construction of m6A-metabolic Score will help to more effectively guide immunotherapy, metabolic therapy and chemotherapy in STS.
| S-EPMC9374037 | biostudies-literature
Project description:Soft-tissue sarcoma (sts) is a rare mesenchymal malignancy that accounts for less than 1% of all adult tumours. Despite the successful advancement of localized therapies such as surgery and radiotherapy, these tumours can, for many, recur-often with metastatic disease. In the advanced setting, the role of systemic therapies is modest and is associated with poor survival. With the discovery of immunotherapies in other tumour types such as melanoma and lung cancer, interest has been renewed in exploring immunotherapy in sts. The biology of some stss makes them ripe for immunotherapy intervention; for example, some stss might have chromosomal translocations resulting in pathognomonic fusion products that have been shown to express cancer/testis antigens. Here, we present a targeted review of the published data and ongoing clinical trials for immunotherapies in patients with sarcoma, which comprise immune checkpoint inhibitors, adoptive cell therapies, and cancer vaccines.
| S-EPMC7050043 | biostudies-literature
Project description:Several studies have highlighted the potential of pyroptosis as a target for cancer treatment. This article focuses on the specific roles and clinical implications of pyroptosis-related genes (PRGs) in soft tissue sarcoma (STS). By analyzing differentially expressed PRGs in STS compared to normal tissue, our study evaluates the interactions, biological functions, and prognostic values of PRGs in STS. Through LASSO COX regression analysis, a five-gene survival related-risk score (PLCG1, PYCARD, CASP8, NOD1, and NOD2) was created, which examined both in TCGA cohort and training cohort (GSE21050, GSE30929, and GSE63157). Furthermore, we developed a nomogram incorporating clinic factors and the risk scores of the PRGs, which showed decent accuracy of prediction as evidenced by calibration curves. Additionally, our study analyzed the Tumor Immune Dysfunction and Exclusion Algorithm (TIDE) and IMvigor 210 cohorts to investigate the immunotherapy response, and found that immunotherapy was more beneficial for patients with minimal risk of PRGs than those exhibiting greater risk. Finally, GDSC and CAMP databases were used to screen for effective chemotherapy or targeted drugs that are sensitive to the high-risk populations, including doxorubicin, imatinib, and sorafenib. In conclusion, this study provides a comprehensive analysis of the PRG landscape in STS and constructs a novel risk model to predict prognosis and different therapeutic responses of STS patients, which is helpful for achieving precision medicine.
| S-EPMC10196039 | biostudies-literature
Project description:Background: Soft tissue sarcoma (STS) is the malignancy that exhibits remarkable histologic diversity. The diagnosis and treatment of STS is currently challenging, resulting in a high lethality. Chronic inflammation has also been identified as a key characteristic of tumors, including sarcomas. Although senescence plays an important role in the progression of various tumors, its molecular profile remains unclear in STS. Methods: We identified the senescence-related genes (SRGs) in database and depicted characteristics of genomic and transcriptomic profiling using cohort within TCGA and GEO database. In order to investigate the expression of SRGs in different cellular subtypes, single-cell RNA sequencing data was applied. The qPCR and our own sequencing data were utilized for further validation. We used unsupervised consensus clustering analysis to establish senescence-related clusters and subtypes. A senescence scoring system was established by using principal component analysis (PCA). The evaluation of clinical and molecular characteristics was conducted among distinct groups. Results: These SRGs showed differences in SCNV, mutation and mRNA expression in STS tissues compared to normal tissues. Across several cancer types, certain shared features of SRGs were identified. Several SRGs closely correlated with immune cell infiltration. Four clusters related to senescence and three subtypes related to senescence, each with unique clinical and biological traits, were established. The senescence scoring system exhibited effectiveness in predicting outcomes, clinical traits, infiltrations of immune cells and immunotherapy responses. Conclusion: Overall, the current study provided a comprehensive review of molecular profiling for SRGs in STS. The SRGs based clustering and scoring model could help guiding the clinical management of STS.
| S-EPMC10367114 | biostudies-literature
Project description:BackgroundDysfunction of the circadian clock and polymorphisms of some circadian genes have been linked to cancer development and progression. We investigated the relationship between circadian genes germline variation and susceptibility or prognosis of patients with soft tissue sarcoma.Patients and methodsWe considered the 14 single nucleotide polymorphisms (SNPs) of 6 core circadian genes that have a minor allele frequency > 5% and that are known to be associated with cancer risk or prognosis. Genotyping was performed by q-PCR. Peripheral blood and clinic-pathological data were available for 162 patients with liposarcoma or leiomyosarcoma and 610 healthy donors. Associations between the selected clock genes polymorphisms and sarcoma susceptibility or prognosis were tested assuming 3 models of inheritance: additive, recessive and dominant. Subgroup analysis based on sarcoma histotype was performed under the additive genetic model. Multivariate logistic regression and multivariate Cox proportional hazard regression analyses were utilized to assess the association between SNPs with patient susceptibility and survival, respectively. Pathway variation analysis was conducted employing the Adaptive Rank Truncated Product method.ResultsSix out of the 14 analyzed SNPs were statistically significantly associated with susceptibility or prognosis of soft tissue sarcoma (P < 0.05). The present analysis suggested that carriers of the minor allele of the CLOCK polymorphism rs1801260 (C) or of PER2 rs934945 (T) had a reduced predisposition to sarcoma (26% and 35% respectively with the additive model) and liposarcoma (33% and 41% respectively). The minor allele (A) of NPAS2 rs895520 was associated with an increased predisposition to sarcoma of 33% and leiomyosarcoma of 44%. RORA rs339972 C allele was associated with a decreased predisposition to develop sarcoma assuming an additive model (29%) and leiomyosarcoma (36%). PER1 rs3027178 was associated with a reduced predisposition only in liposarcoma subgroup (32%). rs7602358 located upstream PER2 was significantly associated with liposarcoma survival (HR: 1.98; 95% CI 1.02-3.85; P = 0.04). Germline genetic variation in the circadian pathway was associated with the risk of developing soft tissue sarcoma (P = 0.035).ConclusionsGenetic variation of circadian genes appears to play a role in the determinism of patient susceptibility and prognosis. These findings prompt further studies to fully dissect the molecular mechanisms.
| S-EPMC6280400 | biostudies-literature
Project description:Background: Soft-tissue sarcomas (STSs) are a rare type of cancer, accounting for about 1% of all adult cancers. Treatments for STSs can be difficult to implement because of their diverse histological and molecular features, which lead to variations in tumor behavior and response to therapy. Despite the growing importance of NETosis in cancer diagnosis and treatment, researches on its role in STSs remain limited compared to other cancer types. Methods: The study thoroughly investigated NETosis-related genes (NRGs) in STSs using large cohorts from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis and Support Vector Machine Recursive Feature Elimination (SVM-RFE) were employed for screening NRGs. Utilizing single-cell RNA-seq (scRNA-seq) dataset, we elucidated the expression profiles of NRGs within distinct cellular subpopulations. Several NRGs were validated by quantitative PCR (qPCR) and our proprietary sequencing data. To ascertain the impact of NRGs on the sarcoma phenotype, we conducted a series of in vitro experimental investigations. Employing unsupervised consensus clustering analysis, we established the NETosis clusters and respective NETosis subtypes. By analyzing DEGs between NETosis clusters, an NETosis scoring system was developed. Results: By comparing the outcomes obtained from LASSO regression analysis and SVM-RFE, 17 common NRGs were identified. The expression levels of the majority of NRGs exhibited notable dissimilarities between STS and normal tissues. The correlation with immune cell infiltration were demonstrated by the network comprising 17 NRGs. Patients within various NETosis clusters and subtypes exhibited different clinical and biological features. The prognostic and immune cell infiltration predictive capabilities of the scoring system were deemed efficient. Furthermore, the scoring system demonstrated potential for predicting immunotherapy response. Conclusion: The current study presents a systematic analysis of NETosis-related gene patterns in STS. The results of our study highlight the critical role NRGs play in tumor biology and the potential for personalized therapeutic approaches through the application of the NETosis score model in STS patients.
| S-EPMC10318157 | biostudies-literature
Project description:BackgroundImmune-related genes (IRGs) have been confirmed to have an important role in tumorigenesis and tumor microenvironment formation. Nevertheless, a systematic analysis of IRGs and their clinical significance in soft tissue sarcoma (STS) patients is lacking.MethodsGene expression files from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx) were used to select differentially expressed genes (DEGs). Differentially expressed immune-related genes (DEIRGs) were determined by matching the DEG and ImmPort gene sets, which were evaluated by functional enrichment analysis. Unsupervised clustering of the identified DEIRGs was conducted, and associations with prognosis, the tumor microenvironment (TME), immune checkpoints, and immune cells were analyzed simultaneously. Two prognostic signatures, one for overall survival (OS) and one for progression free survival (PFS), were established and validated in an independent set. Finally, two transcription factor (TF)-IRG regulatory networks were constructed, and a crucial regulatory axis was validated.ResultsIn total, 364 DEIRGs and four clusters were identified. OS, TME scores, five immune checkpoints, and 12 types of immune cells were found to be significantly different among the four clusters. The two prognostic signatures incorporating 20 DEIRGs showed favorable discrimination and were successfully validated. Two nomograms combining signature and clinical variables were generated. The C-indexes were 0.879 (95%CI 0.832 ~ 0.926) and 0.825 (95%CI 0.776 ~ 0.874) for the OS and PFS signatures, respectively. Finally, TF-IRG regulatory networks were established, and the MYH11-ADM regulatory axis was verified in three independent datasets.ConclusionThis comprehensive analysis of the IRG landscape in soft tissue sarcoma revealed novel IRGs related to carcinogenesis and the immune microenvironment. These findings have implications for prognosis and therapeutic responses, which reveal novel potential prognostic biomarkers, promote precision medicine, and provide potential novel targets for immunotherapy.
| S-EPMC7465445 | biostudies-literature
Project description:Background: Soft-tissue sarcoma (STS) is a massive threat to human health due to its high morbidity and malignancy. STS also represents more than 100 histologic and molecular subtypes, with different prognosis. There is growing evidence that anoikis play a key role in the proliferation and invasion of tumors. However, the effects of anoikis in the immune landscape and the prognosis of STS remain unclear. Methods: We analyzed the genomic and transcriptomic profiling of 34 anoikis-related genes (ARGs) in patient cohort of pan-cancer and STS from The Cancer Genome Atlas (TCGA) database. Single-cell transcriptome was used to disclose the expression patterns of ARGs in specific cell types. Gene expression was further validated by real-time PCR and our own sequencing data. We established the Anoikis cluster and Anoikis subtypes by using unsupervised consensus clustering analysis. An anoikis scoring system was further built based on the differentially expressed genes (DEGs) between Anoikis clusters. The clinical and biological characteristics of different groups were evaluated. Results: The expressions of most ARGs were significantly different between STS and normal tissues. We found some common ARGs profiles across the pan-cancers. Network of 34 ARGs demonstrated the regulatory pattern and the association with immune cell infiltration. Patients from different Anoikis clusters or Anoikis subtypes displayed distinct clinical and biological characteristics. The scoring system was efficient in prediction of prognosis and immune cell infiltration. In addition, the scoring system could be used to predict immunotherapy response. Conclusion: Overall, our study thoroughly depicted the anoikis-related molecular and biological profiling and interactions of ARGs in STS. The Anoikis score model could guide the individualized management.
| S-EPMC10014785 | biostudies-literature
Project description:Tumor stemness has been reported to play important roles in cancers. However, a comprehensive analysis of tumor stemness remains to be performed to investigate the specific mechanisms and practical values of stemness in soft tissue sarcomas (STS). Here, we applied machine learning to muti-omic data of patients from TCGA-SARC and GSE21050 cohorts to reveal important roles of stemness in STS. We demonstrated limited roles of existing mRNAsi in clinical application. Therefore, based on stemness-related signatures (SRSs), we identified three stemness subtypes with distinct stemness, immune, and metabolic characteristics using consensus clustering. The low-stemness subtype had better prognosis, activated innate and adaptive immunity (e.g., infiltrating B, DC, Th1, CD8+ T, activated NK, gamma delta T cells, and M1 macrophages), more enrichment of metabolic pathways, more sites with higher methylation level, higher gene mutations, CNA burdens, and immunogenicity indicators. Furthermore, the 16 SRS-based stemness prognostic index (SPi) was developed, and we found that low-SPi patients with low stemness had better prognosis and other characteristics similar to those in the low-stemness subtype. Besides, low-stemness subtype and low-SPi patients could benefit from immunotherapy. The predictive value of SPi in immunotherapy was more accurate after the addition of MSI into SPi. MSIlowSPilow patients might be more sensitive to immunotherapy. In conclusion, we highlighted mechanisms and practical values of the stemness in STS. We also recommended the combination of MSI and SPi which is a promising tool to predict prognosis and achieve precise treatments of immunotherapy in STS.
| S-EPMC9022121 | biostudies-literature
Project description:(1) Background: PRAME, NY-ESO-1, and SSX2 are cancer testis antigens (CTAs), which are expressed in testicular germ cells with re-expression in numerous cancer types. Their ability to elicit humoral and cellular immune responses have rendered them promising targets for cancer immunotherapy, but they have never been studied in a large and well-characterised cohort of soft tissue sarcomas (STS). (2) Methods: On a protein level, we examined PRAME, NY-ESO-1, and SSX2 expression in tumour tissues of 249 high-risk STS using immunohistochemistry. We correlated expression levels with clinicopathological parameters including tumour-infiltrating lymphocyte (TIL) counts, grading, and long-term survival. (3) Results: Expression of PRAME, NY-ESO-1, and SSX2 was observed in 25 (10%), 19 (8%), and 11 (4%) of 249 specimens with distinct patterns for histo-subtypes. Expression of PRAME was associated with shorter patient survival (p = 0.005) and higher grade (G2 vs. G3, p = 0.001), while NY-ESO-1 expression was correlated with more favourable survival (p = 0.037) and lower grade (G2 vs. G3, p = 0.029). Both PRAME and NY-ESO-1 expression were more frequent in STS with low TIL counts. In multivariate analysis, high PRAME and low SSX2 expression levels as well as metastatic disease and non-radical resections were independent predictors of shorter overall survival. (4) Conclusions: CTAs PRAME, NY-ESO-1, and SSX2 show distinct expression patterns in different STS subtypes. These results demonstrate their prognostic relevance and may guide future immunotherapeutic approaches in STS.
| S-EPMC7761656 | biostudies-literature