Prognostic Significance of Percentage and Size of Dedifferentiation in Dedifferentiated Chondrosarcoma

Hung, Yin P.; Chebib, Ivan; Bredella, Miriam A.; Berner, Emily; Taylor-Black, Quinn; Choy, Edwin; Coté, Gregory M.; Chen, Yen‐Lin; MacDonald, Shannon M.; Schwab, Joseph H.; Raskin, Kevin A.; Newman, Erik T.; Selig, Martin K.; Hornick, Jason L.; Lozano-Calderón, Santiago; Nielsen, G. Petur

doi:10.1016/j.modpat.2022.100069

Cited by 5 publications

(6 citation statements)

References 20 publications

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“…This distinction is clinically critical, as sarcomas can be treated with chemotherapy, depending on their histologic diagnosis. Furthermore, it has been reported that the clinical prognosis of DDCS is defined by the proportion of dedifferentiated components 9 . Therefore, our WES analysis proved the association between both tumors.…”

Section: Discussionsupporting

confidence: 68%

“…Furthermore, it has been reported that the clinical prognosis of DDCS is defined by the proportion of dedifferentiated components. 9 Therefore, our WES analysis proved the association between both tumors. It is well known that two components of DDCS share the same gene alterations and are derived from the same clone.…”

Section: Discussionmentioning

confidence: 57%

“…It is a rare lesion that occurs in less than 10%–15% of central chondrosarcomas 8 . It is reported that dedifferentiated component may metastasize in the setting of very small volumes of dedifferentiation in the primary tumor 9 . DDCS has an extremely poor prognosis and few effective treatment options, so further elucidation of its pathogenesis is desirable 10 …”

Section: Introductionmentioning

confidence: 99%

“…8 It is reported that dedifferentiated component may metastasize in the setting of very small volumes of dedifferentiation in the primary tumor. 9 DDCS has an extremely poor prognosis and few effective treatment options, so further elucidation of its pathogenesis is desirable. 10 Recent genomic studies have revealed a correlation between the histologic grade of chondrosarcoma and the number of somatic mutations.…”

mentioning

confidence: 99%

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IDH‐negative chondrosarcoma with metachronous dedifferentiation only in the metastatic site—A diagnostic pitfall

Sekita,

Yoshida,

Kawai

et al. 2023

Genes Chromosomes & Cancer

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Dedifferentiated chondrosarcoma is a subtype of chondrosarcoma with a biphasic histological appearance of a chondrosarcoma component transitioning to a high‐grade, noncartilaginous sarcoma. It is particularly difficult to confirm the diagnosis when a sarcoma lacking cartilaginous component occurs at a distant location from the primary lesion. The patient was a 72‐year‐old woman with multiple lesions in the pelvis, lungs, and liver, 18 months after resection of grade 2 central chondrosarcoma of the sternum. Imaging showed no cartilage component in any location. Although a needle biopsy from the pelvic region confirmed the diagnosis as high‐grade sarcoma without a cartilage component, it was difficult to distinguish between a new primary sarcoma and metachronous metastatic lesions from patient's known prior dedifferentiated chondrosarcoma. We therefore performed a comparative molecular analysis by whole‐exome sequencing of the biopsy sample and the resected sternal central chondrosarcoma. Both lesions had no IDH1/2 mutations but shared 19 somatic mutations and wide‐range chromosomal losses, indicating similar origin. This case illustrates the challenge is coupling a diagnosis of metastatic dedifferentiated chondrosarcoma when no chondroid component is evident. Our study also highlights the benefit of genomic analysis in this differential diagnosis, especially in the context of dedifferentiated chondrosarcoma lacking IDH1/2 mutations.

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Section: Discussionsupporting

confidence: 68%

Section: Discussionmentioning

confidence: 57%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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IDH‐negative chondrosarcoma with metachronous dedifferentiation only in the metastatic site—A diagnostic pitfall

Sekita,

Yoshida,

Kawai

et al. 2023

Genes Chromosomes & Cancer

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“…In DDCS, the mass of the tumour is usually much greater than in conventional chondrosarcoma due to the second, non-cartilaginous component. The size of the tumour mass varies from 5 mm to 36 mm [18] or even to 460 mm [31]. The size of its constitutive components is also diverse and difficult to predict, especially in terms of the high-grade component, which is increasing with the progress of the disease [32].…”

Section: Sizementioning

confidence: 99%

Dedifferentiated Chondrosarcoma from Molecular Pathology to Current Treatment and Clinical Trials

Zając,

Dróżdż,

Kisielewska

et al. 2023

Cancers

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Dedifferentiated chondrosarcoma (DDCS) is a rare subtype of chondrosarcoma, a primary cartilaginous malignant neoplasm. It accounts for up to 1–2% of all chondrosarcomas and is generally associated with one of the poorest prognoses among all chondrosarcomas with the highest risk of metastasis. The 5-year survival rates range from 7% to 24%. DDCS may develop at any age, but the average presentation age is over 50. The most common locations are the femur, pelvis humerus, scapula, rib, and tibia. The standard treatment for localised disease is surgical resection. Most patients are diagnosed in unresectable and advanced stages, and chemotherapy for localised and metastatic dedifferentiated DDCS follows protocols used for osteosarcoma.

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Novel machine‐learning prediction tools for overall survival of patients with chondrosarcoma: Based on recursive partitioning analysis

Yang,

Bao

et al. 2024

Cancer Medicine

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BackgroundChondrosarcoma (CHS), a bone malignancy, poses a significant challenge due to its heterogeneous nature and resistance to conventional treatments. There is a clear need for advanced prognostic instruments that can integrate multiple prognostic factors to deliver personalized survival predictions for individual patients. This study aimed to develop a novel prediction tool based on recursive partitioning analysis (RPA) to improve the estimation of overall survival for patients with CHS.MethodsData from the Surveillance, Epidemiology, and End Results (SEER) database were analyzed, including demographic, clinical, and treatment details of patients diagnosed between 2000 and 2018. Using C5.0 algorithm, decision trees were created to predict survival probabilities at 12, 24, 60, and 120 months. The performance of the models was assessed through confusion scatter plot, accuracy rate, receiver operator characteristic (ROC) curve, and area under ROC curve (AUC).ResultsThe study identified tumor histology, surgery, age, visceral (brain/liver/lung) metastasis, chemotherapy, tumor grade, and sex as critical predictors. Decision trees revealed distinct patterns for survival prediction at each time point. The models showed high accuracy (82.40%–89.09% in training group, and 82.16%–88.74% in test group) and discriminatory power (AUC: 0.806–0.894 in training group, and 0.808–0.882 in test group) in both training and testing datasets. An interactive web‐based shiny APP (URL: https://yangxg1209.shinyapps.io/chondrosarcoma_survival_prediction/) was developed, simplifying the survival prediction process for clinicians.ConclusionsThis study successfully employed RPA to develop a user‐friendly tool for personalized survival predictions in CHS. The decision tree models demonstrated robust predictive capabilities, with the interactive application facilitating clinical decision‐making. Future prospective studies are recommended to validate these findings and further refine the predictive model.

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Prognostic Significance of Percentage and Size of Dedifferentiation in Dedifferentiated Chondrosarcoma

Cited by 5 publications

References 20 publications

IDH‐negative chondrosarcoma with metachronous dedifferentiation only in the metastatic site—A diagnostic pitfall

IDH‐negative chondrosarcoma with metachronous dedifferentiation only in the metastatic site—A diagnostic pitfall

Dedifferentiated Chondrosarcoma from Molecular Pathology to Current Treatment and Clinical Trials

Novel machine‐learning prediction tools for overall survival of patients with chondrosarcoma: Based on recursive partitioning analysis

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