Clinicopathological and histopathological review of dedifferentiated liposarcoma: a comprehensive study of 123 primary tumours

Mori, Taro; Yamada, Yuichi; Kinoshita, Izumi; Kohashi, Kenichi; Yamamoto, Hidetaka; Ito, Yoshihiro; Susuki, Yosuke; Kawaguchi, Ken Ichi; Nakashima, Yasuharu

doi:10.1111/his.14588

Cited by 5 publications

(6 citation statements)

References 19 publications

(57 reference statements)

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“…No signs of infiltrative growth, necrosis, or mitotic activity are found [ 6–8 ]. The presence of lipoblasts is not uncommon in PLs, being present in around 66% of the cases; therefore, it is not considered a distinguishable clinical feature of liposarcoma [ 9 , 11 ].…”

Section: Discussionmentioning

confidence: 99%

“…Typical immunochemistry results present negative desmin values, positive CD34, and negative S100 (positive S100 in the presence of mature adipocytes). Molecular genetic testing is considered the most reliable diagnostic tool [ 11 ], showing a lack of amplification of MDM2 or CDK4 in PLs, which helps differentiate them from other soft tissue tumours such as atypical lipomatous tumours or dedifferentiated liposarcomas (DDLS), which have positive nuclear expression for MDM2 or/and CDK4 in most cases [ 9 , 12 , 13 ].…”

Section: Discussionmentioning

confidence: 99%

“…Pathological analyses showcases floret-like multinucleated giant cells (CD34+ and S100−), lipoblasts, and mature adipocytes (S100+) in a myxoid stroma with no signs of necrosis or mitotic activity suggesting malignancy [ 6–8 ]. Genetic molecular studies for MDMD2 and CDK4 in PLs are negative [ 2 , 8 , 9 ].…”

Section: Introductionmentioning

confidence: 99%

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Giant pleomorphic lipoma in patient with multiple osteochondromatosis

Thorpe,

Lage,

Beiras

et al. 2024

Journal of Surgical Case Reports

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Pleomorphic lipomas are infrequent soft tissue tumours with pseudosarcomatous behaviour. Their polymorphism provides them certain characteristics that may resemble malignancy, which may mislead the initial diagnosis. The presented case report is a 45-year-old man with a giant growing tumour on the left cervicoscapular region initially categorised as a liposarcoma by magnetic resonance with a final confirmed diagnosis of pleomorphic lipoma after the surgical resection and the examination of the pathologist. The patient presented important functional restriction of the upper left extremity, which decreased after surgical resection, improving the quality of life.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Giant pleomorphic lipoma in patient with multiple osteochondromatosis

Thorpe,

Lage,

Beiras

et al. 2024

Journal of Surgical Case Reports

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“…These histological types of sarcomas tend to be highly aggressive and can be Regional lymph node invasion and distant metastasis occur within a short period. [29,30] The TNM staging system contains too few variables to analyze, making it di cult to accurately predict the occurrence of this complex tumor. The clinical guidance ability is also lacking.…”

Section: Discussionmentioning

confidence: 99%

Comparison of nomogram with machine learning techniques for prediction of overall survival in patients with retroperitoneal liposarcoma

Wang

Xie

Wang

et al. 2022

Preprint

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Background Retroperitoneal liposarcoma (RP-LPS) is a rare and overlooked tumor type. Because of the rarity and diversity RP-LPS histological subtypes, the diagnosis, treatment and prediction of survival, pose great challenges. This study compared the performance of the 8th edition TNM model, nomogram, and machine learning algorithms in predicting overall survival in patients with RP-LPS to establish a more effective predictive model for clinical use. Establishing relatively reliable survival prediction models has important implications for planning personalized care and patient counseling. Methods The dataset used included clinical data of 2,147 patients with RP-LPS. The machine learning algorithms evaluated included support vector machine, adaptive boosting, decision tree and random forest. These algorithms were evaluated in terms of the area under the receiver-operating characteristic (ROC) curve (AUC) and accuracy values. The performance of the algorithm that produced the optimal results was compared with the 8th edition TNM model and nomogram to better predict overall survival in patients with RP-LPS. Results Comparison of prediction performance indicators of each machine learning algorithm, including accuracy, AUC, F1 score, etc., revealed that the adaptive boosting (AdaBoost) algorithm produced the best prediction effect (accuracy = 69.1%, AUC = 0.70). The performance indicators of AdaBoost were further compared with the traditional TNM model and the nomogram model, and the machine learning algorithm performance was considerably better than other types of models. Conclusions The machine learning algorithm AdaBoost provides more personalized and reliable prognostic information of RP-LPS than the nomogram. However, the level of transparency offered by the nomogram in estimating patient outcomes is higher, which strengthened the principle of shared decision making between the patient and clinician. Therefore, a combination of a nomogram–machine learning (NomoML) predictive model may help to improve care, provide information to patients, and facilitate clinicians in making RP-LPS management-related decisions.

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“…A varying number of monovacuolated or multivacuolated lipoblasts may be seen. The dedifferentiated component exhibits a wide morphological spectrum but most frequently resemble myxofibrosarcoma or undifferentiated pleomorphic sarcoma (71). Immunohistochemically, diffuse nuclear expression of MDM2 and/or CDK4 is seen in the vast majority of DDLSs.…”

Section: Histological Features Of Spindle Cell Lipoma (A) the Tumor I...mentioning

confidence: 99%

Spindle Cell Lipoma and Pleomorphic Lipoma: An Update and Review

OHSHIMA¹,

Nishio²,

Nakayama³

et al. 2023

CDP

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Spindle cell lipoma (SCL) is a benign adipocytic tumor that primarily occurs in the subcutis of the posterior neck, upper back, and shoulder, particularly of middle-aged males. SCL and pleomorphic lipoma (PL) represent a morphological spectrum of one disease process. The lesion typically presents as a relatively small (<5 cm), mobile, slow-growing, painless mass. Magnetic resonance imaging reveals the lesion to be a well-defined subcutaneous mass with a mixture of adipose and non-adipose components. Intense enhancement of the non-adipose component is seen after contrast administration. Histologically, SCL is composed of variable distributions of mature adipocytes, bland spindle cells and ropey collagen bundles and PL also contains pleomorphic and multinucleated floret-like giant cells. By immunohistochemistry, the spindle and pleomorphic/floret-like giant cells of SCL/PL are diffusely positive for CD34 and show loss of nuclear RB transcriptional corepressor 1 (RB1) expression. Recent cytogenetic and molecular genetic studies have shown heterozygous deletions of 13q14, including the RB1 gene. SCL/PL can be successfully treated with simple excision, with a very low recurrence rate. Knowledge of these peculiar tumors is important because it can mimic a variety of benign and malignant soft-tissue tumors. This review provides an updated overview of the clinical, radiological, histopathological, cytogenetic, and molecular genetic features of SCL/PL.

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Clinicopathological and histopathological review of dedifferentiated liposarcoma: a comprehensive study of 123 primary tumours

Cited by 5 publications

References 19 publications

Giant pleomorphic lipoma in patient with multiple osteochondromatosis

Giant pleomorphic lipoma in patient with multiple osteochondromatosis

Comparison of nomogram with machine learning techniques for prediction of overall survival in patients with retroperitoneal liposarcoma

Spindle Cell Lipoma and Pleomorphic Lipoma: An Update and Review

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