Gene expression profiling improves prognostication by nomogram in patients with soft-tissue sarcomas.
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SUBMITTER: Crombe A
PROVIDER: S-EPMC9198343 | biostudies-literature | 2022 Jun
REPOSITORIES: biostudies-literature
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Gene expression profiling improves prognostication by nomogram in patients with soft-tissue sarcomas.
Crombé Amandine A Spalato-Ceruso Mariella M Michot Audrey A Laizet Yech'an Y Lucchesi Carlo C Toulmonde Maud M Bourcier Kevin K Le Loarer François F Italiano Antoine A
Cancer communications (London, England) 20220207 6
Similar Datasets
Project description:BackgroundHigh-risk soft tissue sarcomas of the extremities and trunk wall (eSTS), as defined by the Sarculator nomogram, are more likely to benefit from (neo)adjuvant anthracycline-based therapy compared to low/intermediate-risk patients. The biology underpinning these differential treatment outcomes remain unknown.MethodsWe analysed proteomic profiles and clinical outcomes of 123 eSTS patients. A Cox model for overall survival including the Sarculator was fitted to individual data to define four risk groups. A DNA replication protein signature-Sarcoma Proteomic Module 6 (SPM6) was evaluated for association with clinicopathological factors and risk groups. SPM6 was added as a covariate together with Sarculator in a multivariable Cox model to assess improvement in prognostic risk stratification.ResultsDNA replication and cell cycle proteins were upregulated in high-risk versus very low-risk patients. Evaluation of the functional effects of CRISPR-Cas9 gene knockdown of proteins enriched in high-risk patients using the cancer cell line encyclopaedia database identified candidate drug targets. SPM6 was significantly associated with tumour malignancy grade (p = 1.6e-06), histology (p = 1.4e-05) and risk groups (p = 2.6e-06). Cox model analysis showed that SPM6 substantially contributed to a better calibration of the Sarculator nomogram (Index of Prediction Accuracy = 0.109 for Sarculator alone versus 0.165 for Sarculator + SPM6).ConclusionsRisk stratification of patient with STS is defined by distinct biological pathways across a range of cancer hallmarks. Incorporation of SPM6 protein signature improves prognostic risk stratification of the Sarculator nomogram. This study highlights the utility of integrating protein signatures for the development of next-generation nomograms.
| S-EPMC11263812 | biostudies-literature
Project description:Opinion statementAdvances in proteomic and metabolomic technologies have accelerated our understanding of multiple aspects of cancer biology across distinct tumour types. Here we review the current state-of-the-art in the use of proteomics and metabolomics in soft tissue sarcomas. We highlight the utility of these Omics-based methodologies to identify new drug targets, synthetic lethal interactions, candidate therapeutics and novel biomarkers to facilitate patient stratification. Due to the unbiased and global nature of these profiling methods to assess the levels of protein expression, post-translational modifications such as phosphorylation and glycosylation as well as key metabolites, many of these findings have broad applications not just in specific histotypes but across multiple STS subtypes. Specific examples of proteomic and metabolomic findings that have led to the development of early phase clinical trials of investigational agents will be discussed. While promising, the use of these technologies in the study of sarcoma is still limited, and there is a need for further research in this area. In particular, it would be important to integrate these approaches with other Omics strategies such as genomics and epigenomics as well as implement these tools alongside clinical trials in order to maximize the impact of these tools on our biological understanding and treatment of this group of rare diseases of unmet need.
| S-EPMC8891095 | biostudies-literature
Project description:For the current study we performed whole genome expression profiling on 69 unique patients with soft-tissue sarcoma who underwent curative-intent surgical resection to identify prognostic gene signatures. Specimens were obtained from the Mayo Clinic Florida STS Biobank and RNA was sequenced using the Tempus xT RNA-seq protocol. This protocol uses transcriptome-capture via more than 415,000 IDT xGen probes spanning greater than 19,000 genes, with at least 50 ng of extracted RNA required before proceeding to library preparation and a minimum depth of 30 million reads a on a NovaSeq 6000. RNA-seq data was analyzed using the MAP-RSeq pipeline developed by Mayo Clinic Bioinformatics Shared Resource.
2023-06-05 | GSE234092 | GEO
Project description:The prognosis given for canine soft tissue sarcomas (STSs) is based primarily on histopathologic grade. The decision to administer adjuvant chemotherapy is difficult since less than half of patients with high-grade STSs develop metastatic disease. We hypothesize that there is a gene signature that will improve our ability to predict development of metastatic disease in STS patients. The objective of this study was to determine the feasibility of using cDNA microarray and quantitative real-time PCR (qRT-PCR) analysis to determine gene expression patterns in metastatic versus nonmetastatic canine STSs, given the inherent heterogeneity of this group of tumors. Five STSs from dogs with metastatic disease were evaluated in comparison to eight STSs from dogs without metastasis. Tumor RNA was extracted, processed, and labeled for application to the Affymetrix Canine Genechip 2.0 Array. Array fluorescence was normalized using D-Chip software and data analysis was performed with JMP/Genomics. Differential gene expression was validated using qRT-PCR. Over 200 genes were differentially expressed at a false discovery rate of 5%. Differential gene expression was validated for five genes upregulated in metastatic tumors. Quantitative RT-PCR confirmed increased relative expression of all five genes of interest in the metastatic STSs. Our results demonstrate that microarray and qRT-PCR are feasible methods for comparing gene signatures in canine STSs. Further evaluation of the differences between gene expression in metastatic STSs and in nonmetastatic STSs is likely to identify genes that are important in the development of metastatic disease and improve our ability to prognosticate for individual patients.
| S-EPMC3810003 | biostudies-literature
Project description:Soft tissue sarcomas (STS) are a group of rare and heterogeneous cancers. While large-scale genomic and epigenomic profiling of STS have been undertaken, proteomic analysis has thus far been limited. Here we utilise sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) for proteomic profiling of formalin fixed paraffin embedded (FFPE) specimens from a cohort of STS patients (n = 36) across four histological subtypes (leiomyosarcoma, synovial sarcoma, undifferentiated pleomorphic sarcoma and dedifferentiated liposarcoma). We quantified 2951 proteins across all cases and show that there is a significant enrichment of gene sets associated with smooth muscle contraction in leiomyosarcoma, RNA splicing regulation in synovial sarcoma and leukocyte activation in undifferentiated pleomorphic sarcoma. We further identified a subgroup of STS cases that have a distinct expression profile in a panel of proteins, with worse survival outcomes when compared to the rest of the cohort. Our study highlights the value of comprehensive proteomic characterisation as a means to identify histotype-specific STS profiles that describe key biological pathways of clinical and therapeutic relevance; as well as for discovering new prognostic biomarkers in this group of rare and difficult-to-treat diseases.
| S-EPMC8135130 | biostudies-literature
Project description:Gene Expression Profiling of Surgically Resectable Soft-Tissue Sarcomas
| PRJNA980093 | ENA
Project description:BACKGROUND: High-grade soft tissue sarcomas are a heterogeneous, complex group of aggressive malignant tumors showing mesenchymal differentiation. Recently, soft tissue sarcomas have increasingly been classified on the basis of underlying genetic alterations; however, the role of aberrant DNA methylation in these tumors is not well understood and, consequently, the usefulness of methylation-based classification is unclear. RESULTS: We used the Infinium HumanMethylation27 platform to profile DNA methylation in 80 primary, untreated high-grade soft tissue sarcomas, representing eight relevant subtypes, two non-neoplastic fat samples and 14 representative sarcoma cell lines. The primary samples were partitioned into seven stable clusters. A classification algorithm identified 216 CpG sites, mapping to 246 genes, showing different degrees of DNA methylation between these seven groups. The differences between the clusters were best represented by a set of eight CpG sites located in the genes SPEG, NNAT, FBLN2, PYROXD2, ZNF217, COL14A1, DMRT2 and CDKN2A. By integrating DNA methylation and mRNA expression data, we identified 27 genes showing negative and three genes showing positive correlation. Compared with non-neoplastic fat, NNAT showed DNA hypomethylation and inverse gene expression in myxoid liposarcomas, and DNA hypermethylation and inverse gene expression in dedifferentiated and pleomorphic liposarcomas. Recovery of NNAT in a hypermethylated myxoid liposarcoma cell line decreased cell migration and viability. CONCLUSIONS: Our analysis represents the first comprehensive integration of DNA methylation and transcriptional data in primary high-grade soft tissue sarcomas. We propose novel biomarkers and genes relevant for pathogenesis, including NNAT as a potential tumor suppressor in myxoid liposarcomas.
| S-EPMC4054884 | biostudies-literature
Project description:BackgroundSoft-tissue sarcomas (STS) represent a heterogeneous group of rare tumors including more than 70 different histological subtypes. High throughput molecular analysis (next generation sequencing exome [NGS]) is a unique opportunity to identify driver mutations that can change the usual one-size-fits-all treatment paradigm to a patient-driven therapeutic strategy. The primary objective of the MULTISARC trial is to assess whether NGS can be conducted for a large proportion of metastatic STS participants within a reasonable time, and, secondarily to determine whether a NGS-guided therapeutic strategy improves participant's outcome.MethodsThis is a randomized, multicentre, phase II/III trial inspired by the design of umbrella and biomarker-driven trials. The setting plans up to 17 investigational centres across France and the recruitment of 960 participants. Participants aged at least 18 years, with unresectable locally advanced and/or metastatic STS confirmed by the French sarcoma pathological reference network, are randomized according to 1:1 allocation ratio between the experimental arm "NGS" and the standard "No NGS". NGS will be considered feasible if (i) NGS results are available and interpretable, and (ii) a report of exome sequencing including a clinical recommendation from a multidisciplinary tumor board is provided to investigators within 7 weeks from reception of the samples on the biopathological platform. A feasibility rate of more than 70% is expected (null hypothesis: 70% versus alternative hypothesis: 80%). In terms of care, participants randomized in "No NGS" arm and who fail treatment will be able to switch to the NGS arm at the request of the investigator.DiscussionThe MULTISARC trial is a prospective study designed to provide high-level evidence to support the implementation of NGS in routine clinical practice for advanced STS participants, on a large scale.Trial registrationclinicaltrial.gov NCT03784014 .
| S-EPMC8570026 | biostudies-literature
Project description:Soft tissue sarcomas are a group of rare mesenchymal tumors with more than 70 subtypes described. Treatment of these subtypes in an advanced setting is mainly according to a one-size-fits-all strategy indicating a high unmet need of new and more targeted therapeutic options in order to optimize survival. The introduction of advanced molecular techniques in cancer has led to better diagnostics and identification of new therapeutic targets, leading to more personalized treatment and improved prognosis for several cancer types. In sarcoma, a likewise evolution is seen, albeit at a slower pace. This manuscript describes how in the past years advanced molecular profiling in soft tissue sarcomas was able to identify specific and often pathognomonic aberrations, deferring standard sarcoma treatment in favor of more targeted treatment from an oncologist's point of view.
| S-EPMC7999686 | biostudies-literature
Project description:BackgroundThe use of nomograms for prognostication of individual cancer patients has been recommended in order to facilitate precision medicine. However, models for patients with soft tissue sarcomas (STSs) are limited because of the rarity and heterogeneity of such cancers. In addition, no model has been developed on the basis of an Asian cohort. Here, we attempted to develop and internally validate nomograms for patients with localized STSs of the trunk and extremity.MethodsThis study retrospectively extracted 2827 patients with primary trunk and extremity STSs after definitive surgery using the Bone and Soft Tissue Tumor Registry, which is a nationwide sarcoma database in Japan. We developed three nomograms predicting the probability of local recurrence-free survival (LRFS), distant metastasis-free survival (DMFS) and disease-specific survival (DSS) at 2 years after surgery, using the Cox multivariate model. The nomograms were internally validated for discrimination and calibration using bootstrap resampling and assessed for their clinical applicability by decision curve analysis (DCA).ResultsLocal recurrence, distant metastasis and disease-specific death occurred in 241 patients (8.5%), 554 patients (19.6%) and 230 patients (8.1%), respectively. Histological diagnosis, grade and tumor size strongly influenced all three endpoints. The nomograms predicted accurately the probability of LRFS, DMFS and DSS (concordance index: 0.73, 0.70 and 0.75, respectively). DCA demonstrated that our nomograms had clinical applicability.ConclusionWe have developed the first nomograms for STSs based on an Asian cohort. These nomograms allowed accurate prediction of LRFS, DMFS and DSS at 2 years after definitive surgery, and can be used as a guide by clinicians for appropriate follow-up and counseling of patients.
| S-EPMC6610844 | biostudies-literature