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Establishment of A Nomogram for Predicting the Prognosis of Soft Tissue Sarcoma Based on Seven Glycolysis-Related Gene Risk Score.

ABSTRACT: Background: Soft tissue sarcoma (STS) is a group of tumors with a low incidence and a complex type. Therefore, it is an arduous task to accurately diagnose and treat them. Glycolysis-related genes are closely related to tumor progression and metastasis. Hence, our study is dedicated to the development of risk characteristics and nomograms based on glycolysis-related genes to assess the survival possibility of patients with STS. Methods: All data sets used in our research include gene expression data and clinical medical characteristics in the Genomic Data Commons Data Portal (National Cancer Institute) Soft Tissue Sarcoma (TCGA SARC) and GEO database, gene sequence data of corresponding non-diseased human tissues in the Genotype Tissue Expression (GTEx).Next, transcriptome data in TCGA SARC was analyzed as the training set to construct a glycolysis-related gene risk signature and nomogram, which were confirmed in external test set. Results: We identified and verified the 7 glycolysis-related gene signature that is highly correlated with the overall survival (OS) of STS patients, which performed excellently in the evaluation of the size of AUC, and calibration curve. As well as, the results of the analysis of univariate and multivariate Cox regression demonstrated that this 7 glycolysis-related gene characteristic acts independently as an influence predictor for STS patients. Therefore, a prognostic-related nomogram combing 7 gene signature with clinical influencing features was constructed to predict OS of patients with STS in the training set that demonstrated strong predictive values for survival. Conclusion: These results demonstrate that both glycolysis-related gene risk signature and nomogram were efficient prognostic indicators for patients with STS. These findings may contribute to make individualize clinical decisions on prognosis and treatment.

SUBMITTER: Liu Y

PROVIDER: S-EPMC8674658 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Soft tissue sarcoma (STS) is a heterogeneous family of rare mesenchymal tumors, characterized by histopathological and molecular diversity. Tissue microarray (TMA) is a tool that allows performing research in orphan diseases in a more efficient and cost-effective way. TMAs are paraffin blocks consisting of multiple small representative tissue cores from biological samples, for example, from multiple donors, diverse sites of disease, or multiple different diseases. In 2015, we began constructing TMAs using archival tumor material from STS patients. Specimens were well annotated in terms of histopathological diagnosis, treatment, and clinical follow-up of the tissue donors. Each TMA block contains duplicate or triplicate 1.0-1.5 mm tissue cores from representative tumor areas selected by sarcoma pathologists. The construction of TMAs was performed with TMA Grand Master (3DHistech). So far, we have established disease-specific TMAs from 7 STS subtypes: gastrointestinal stromal tumor (72 cases included in the array), alveolar soft part sarcoma (n = 12 + 47), clear cell sarcoma (n = 22 + 32), leiomyosarcoma (n = 55), liposarcoma (n = 42), inflammatory myofibroblastic tumor (n = 12 + 21), and alveolar rhabdomyosarcoma (n = 24). We also constructed a multisarcoma TMA covering a representative number of important histopathological subtypes on arrays for screening purposes, namely, angiosarcoma, dedifferentiated liposarcoma, pleomorphic liposarcoma, and myxoid liposarcoma, leiomyosarcoma, malignant peripheral nerve sheath tumor, myxofibrosarcoma, rhabdomyosarcoma, synovial sarcoma, and undifferentiated pleomorphic sarcoma, with 7-11 individual cases per subtype. We are currently expanding the list of TMAs with additional sarcoma entities, considering the heterogeneity of this family of tumors. Our extensive STS TMA platform is suitable for rapid and cost-effective morphological, immunohistochemical, and molecular characterization of the tumor as well as for the identification of potential novel diagnostic markers and drug targets. It is readily available for collaborative projects with research partners.

Project description:BACKGROUND:Dysfunction 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 METHODS:We 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. RESULTS:Six 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). CONCLUSIONS:Genetic 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.

Project description:BackgroundPrognostic nomograms for patients with extremity soft tissue sarcoma (eSTS) typically predict survival or the occurrence of local recurrence or distant metastasis at time of surgery. Our aim was to develop and externally validate a dynamic prognostic nomogram for overall survival in eSTS survivors for use during follow-up.MethodsAll primary eSTS patients operated with curative intent between 1994 and 2013 at three European and one Canadian sarcoma centers formed the development cohort. Patients with Fédération Française des Centres de Lutte Contre le Cancer (FNCLCC) grade II and grade III eSTS operated between 2000 and 2016 at seven other European reference centers formed the external validation cohort. We used a landmark analysis approach and a multivariable Cox model to create a dynamic nomogram; the prediction window was fixed at five years. A backward procedure based on the Akaike Information Criterion was adopted for variable selection. We tested the nomogram performance in terms of calibration and discrimination.FindingsThe development and validation cohorts included 3740 and 893 patients, respectively. The variables selected applying the backward procedure were patient's age, tumor size and its interaction with landmark time, tumor FNCLCC grade and its interaction with landmark time, histology, and both local recurrence and distant metastasis (as first event) indicator variables. The nomogram showed good calibration and discrimination. Harrell C indexes at different landmark times were between 0.776 (0.761-0.790) and 0.845 (0.823-0.862) in the development series and between 0.675 (0.643-0.704) and 0.810 (0.775-0.844) in the validation series.InterpretationA new dynamic nomogram is available to predict 5-year overall survival at different times during the first three years of follow-up in patients operated for primary eSTS. This nomogram allows physicians to update the individual survival prediction during follow-up on the basis of baseline variables, time elapsed from surgery and first-event history.

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Establishment of A Nomogram for Predicting the Prognosis of Soft Tissue Sarcoma Based on Seven Glycolysis-Related Gene Risk Score.

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