Heterogeneity of Soft Tissue Sarcomas and Its Implications in Targeted Therapy

Du, Xuehui; Wei, Hua; Zhang, Peng; Yao, Weitao; Cai, Qianqian

doi:10.3389/fonc.2020.564852

Cited by 17 publications

(18 citation statements)

References 26 publications

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“…Soft-tissue sarcomas (STS) are rare tumors of the connective tissues and account for 1% of all cancers (1). While the radiological assessment of STS typically includes size-based criteria, such as those defined by the Response Evaluation Criteria in Solid Tumors guidelines (RECIST 1.1) (2), intralesion heterogeneity is commonly seen in the clinic, both in tumor appearance and treatment response (3). Furthermore, several studies have reported that changes in tumor size have a poor correlation with histopathological tumor response (4)(5)(6)(7)(8).…”

Section: Introductionmentioning

confidence: 99%

Radiomic Features From Diffusion-Weighted MRI of Retroperitoneal Soft-Tissue Sarcomas Are Repeatable and Exhibit Change After Radiotherapy

et al. 2022

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BackgroundSize-based assessments are inaccurate indicators of tumor response in soft-tissue sarcoma (STS), motivating the requirement for new response imaging biomarkers for this rare and heterogeneous disease. In this study, we assess the test–retest repeatability of radiomic features from MR diffusion-weighted imaging (DWI) and derived maps of apparent diffusion coefficient (ADC) in retroperitoneal STS and compare baseline repeatability with changes in radiomic features following radiotherapy (RT).Materials and MethodsThirty patients with retroperitoneal STS received an MR examination prior to treatment, of whom 23/30 were investigated in our repeatability analysis having received repeat baseline examinations and 14/30 patients were investigated in our post-treatment analysis having received an MR examination after completing pre-operative RT. One hundred and seven radiomic features were extracted from the full manually delineated tumor region using PyRadiomics. Test–retest repeatability was assessed using an intraclass correlation coefficient (baseline ICC), and post-radiotherapy variance analysis (post-RT-IMS) was used to compare the change in radiomic feature value to baseline repeatability.ResultsFor the ADC maps and DWI images, 101 and 102 features demonstrated good baseline repeatability (baseline ICC > 0.85), respectively. Forty-three and 2 features demonstrated both good baseline repeatability and a high post-RT-IMS (>0.85), respectively. Pearson correlation between the baseline ICC and post-RT-IMS was weak (0.432 and 0.133, respectively).ConclusionsThe ADC-based radiomic analysis shows better test–retest repeatability compared with features derived from DWI images in STS, and some of these features are sensitive to post-treatment change. However, good repeatability at baseline does not imply sensitivity to post-treatment change.

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Section: Introductionmentioning

confidence: 99%

Radiomic Features From Diffusion-Weighted MRI of Retroperitoneal Soft-Tissue Sarcomas Are Repeatable and Exhibit Change After Radiotherapy

et al. 2022

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“…Although surgery is considered the standard of care therapy, LMS tumors recur in over 80% of persons with LMS even after adequate resection. Persons with unresectable or recurrent LMS have limited systemic therapeutic options and display widely varying responses to therapy 1 – 3 . To date, there are no approved biomarkers of response in LMS that can be used to guide clinical treatment.…”

Section: Introductionmentioning

confidence: 99%

Drivers of genomic loss of heterozygosity in leiomyosarcoma are distinct from carcinomas

Seligson

Tang

Jin³

et al. 2022

npj Precis. Onc.

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Leiomyosarcoma (LMS) is a rare, aggressive, mesenchymal tumor. Subsets of LMS have been identified to harbor genomic alterations associated with homologous recombination deficiency (HRD); particularly alterations in BRCA2. Whereas genomic loss of heterozygosity (gLOH) has been used as a surrogate marker of HRD in other solid tumors, the prognostic or clinical value of gLOH in LMS (gLOH-LMS) remains poorly defined. We explore the genomic drivers associated with gLOH-LMS and their clinical import. Although the distribution of gLOH-LMS scores are similar to that of carcinomas, outside of BRCA2, there was no overlap with previously published gLOH-associated genes from studies in carcinomas. We note that early stage tumors with elevated gLOH demonstrated a longer disease-free interval following resection in LMS patients. Taken together, and despite similarities to carcinomas in gLOH distribution and clinical import, gLOH-LMS are driven by different genomic signals. Additional studies will be required to isolate and confirm the unique differences in biological factors driving these differences.

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“…The prognosis of patients with advanced STS is not ideal, and the median overall survival (OS) is less than 2 years. 9 And due to the heterogeneity of STSs, 2 patients who differ only in histological subtype may have very different prognoses. In addition, although the widely used American Joint Committee on Cancer (AJCC) TNM staging system represents the gold standard for classification system of STSs, criticisms of its limitations are still emerging.…”

Section: Introductionmentioning

confidence: 99%

Development and Validation of Novel Nomograms for Predicting Specific Distant Metastatic Sites and Overall Survival of Patients With Soft Tissue Sarcoma

Zhang

et al. 2021

Technol Cancer Res Treat

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Purpose: The goal of this study is to construct nomograms to effectively predict the distant metastatic sites and overall survival (OS) of soft tissue sarcoma (STS) patients. Methods: STS case data between 2010 and 2015 for retrospective study were gathered from public databases. According to the chi-square and multivariate logistic regression analysis determined independent predictive factors of specific metastatic sites, the nomograms based on these factors were consturced. Subsequently, combined metastatic information a nomogram to predict 1-, 2-, and 3-year OS of STS patients was developed. The performance of models was validated by the area under the curve (AUC), calibration plots, and decision curve analyses (DCA). Results: A total of 7001 STS patients were included in this retrospective study, including 4901 cases in the training group and the remaining 2,100 patients in the validation group. Three nomograms were established to predict lung, liver and bone metastasis, and satisfactory results have been obtained by internal and external validation. The AUCs for predicting lung, liver, and bone metastases in the training cohort were 0.796, 0.799, and 0.766, respectively, and in the validation cohort were 0.807, 0.787, and 0.775, respectively, which means that the nomograms have good discrimination. The calibration curves showed that the models have high precision, and the DCA manifested that the nomograms have great clinical application prospects. Through univariate and multivariate COX regression analyses, 8 independent prognosis factors of age, grade, histological type, tumor size, surgery, chemotherapy, radiatiotherapy and lung metastasis were determined. A nomogram was then constructed to predict the 1-, 2-, and 3-years OS, which has a good performance in both internal and external validations. Conclusion: The nomograms for predicting specific metastatic sites and OS have good discrimination, accuracy and clinical applicability. The models could accurately predict the metastatic risk and survival information, and help clinical decision-making.

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Heterogeneity of Soft Tissue Sarcomas and Its Implications in Targeted Therapy

Cited by 17 publications

References 26 publications

Radiomic Features From Diffusion-Weighted MRI of Retroperitoneal Soft-Tissue Sarcomas Are Repeatable and Exhibit Change After Radiotherapy

Radiomic Features From Diffusion-Weighted MRI of Retroperitoneal Soft-Tissue Sarcomas Are Repeatable and Exhibit Change After Radiotherapy

Drivers of genomic loss of heterozygosity in leiomyosarcoma are distinct from carcinomas

Development and Validation of Novel Nomograms for Predicting Specific Distant Metastatic Sites and Overall Survival of Patients With Soft Tissue Sarcoma

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