Lingual Alveolar Soft Part Sarcoma in a 78-Year-Old Woman: A Case Report and Comprehensive Review of the Literature from 1952 to 2022

Aksionau, Aliaksandr; Cruz, Nestor Enriquez Dela; Meram, Andrew T.; Cuellar‐Saenz, Hugo; Aveni, Jillian R.; Takei, Hiroyuki

doi:10.1007/s12105-022-01505-x

Cited by 2 publications

(3 citation statements)

References 55 publications

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“…There is a slight female predominance in patients under the age of 30 years, whereas the opposite phenomenon has been found in patients above 30 ( 13 ). ASPS can occur in all body parts, mostly in the deep soft tissues of the thighs and buttocks in adults, whereas it is mainly found in the head and neck in infants and children, especially in the orbit and tongue ( 14 , 15 ). In agreement with previous observations, our study showed that the median patient age at diagnosis was 23.50±6.36 years (9–49 years), and a majority (21/34) of the patients were aged less than 30 years.…”

Section: Discussionmentioning

confidence: 99%

The dynamic contrast enhanced-magnetic resonance imaging and diffusion-weighted imaging features of alveolar soft part sarcoma

Lv,

Xue,

Huang

et al. 2023

Quant Imaging Med Surg

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Background Alveolar soft part sarcoma (ASPS) is a rare type of soft tissue sarcoma that predominantly affects adolescents and young adults. Early diagnosis of ASPS is crucial for optimal therapeutic planning and improving prognosis, but its diagnostic features are not well delineated. This study aimed to retrospectively analyze the imaging features of ASPS with an emphasis on the dynamic contrast-enhanced-magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) findings to identify imaging findings that might suggest the diagnosis to radiologists. Methods The imaging features of 34 patients with pathologically proven limb ASPS were retrospectively analyzed. A total of 23 underwent DCE-MRI, and 12 underwent DWI. Results Among the 34 cases of ASPS, 31 tumors were in the lower extremities, and 3 were in the upper extremities. The maximum tumor diameters ranged from 3.0 to 19.4 cm (mean, 8.7±3.96 cm). A total of 28 cases had well-defined borders. The masses demonstrated heterogeneous high signal intensity on T2-weighted imaging (T2WI) and the fat-suppressed (FS) T2WI sequence and slight hyperintensity on T1-weighted imaging (T1WI). A total of 25 lesions had thin hypointense bands on T1WI and T2WI. Intra- and peri-tumoral tubular areas of flow void were exhibited on both T1WI and T2WI in all cases. A total of 12 cases showed a high signal on DWI, and the mean apparent diffusion coefficient (ADC) value was (0.86±0.07)×10 –3 mm 2 /s [range, (0.6–1.4)×10 –3 mm 2 /s]. Persistent remarkable enhancement of the lesion was displayed on contrast-enhanced scans. The time-intensity curves (TICs) of 23 masses showed early arterial enhancement and slow washout of contrast. Conclusions ASPS most commonly presents in the lower extremities of adolescents or young adults. Hyperintense T1WI, T2WI, and DWI signals, low ADC, flow voids, early arterial enhancement are frequent MRI features.

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Section: Discussionmentioning

confidence: 99%

The dynamic contrast enhanced-magnetic resonance imaging and diffusion-weighted imaging features of alveolar soft part sarcoma

Lv,

Xue,

Huang

et al. 2023

Quant Imaging Med Surg

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

“…The study concludes that ASPS should be considered in the differential diagnoses for slow-growing lingual masses, particularly those with vascular characteristics and nonspecific clinical presentations, irrespective of the patient's age. 14,15 In a different publication, a case report is presented concerning a patient diagnosed with oral squamous cell carcinoma carrying a CDKN2A c.301G>T mutation. The authors explore the heightened susceptibility to head and neck squamous cell carcinoma (HNSCC), specifically oral squamous cell carcinoma (OSCC), in individuals with inherited CDKN2A mutations.…”

Section: Introductionmentioning

confidence: 99%

Emerging Drug Combinations for Targeting Tongue Neoplasms Associated Proteins/Genes: Employing Graph Neural Networks within the RAIN Protocol

Askari,

Kiaei,

Boush

et al. 2024

Preprint

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BackgroundTongue Neoplasms is a common form of malignancy, with squamous cell carcinoma of the tongue being the most frequently diagnosed type due to regular mechanical stimulation. Its prevalence remains on the rise among neoplastic cancer cases. Finding effective combinations of drugs to target the genetic and protein elements contributing to the development of Managing Tongue Neoplasms poses a difficulty owing to the intricate and varied nature of the ailment.MethodIn this research, we introduce a novel approach using Deep Modularity Networks (DMoN) to identify potential synergistic drug combinations for the condition, following the RAIN protocol. This procedure comprises three primary phases: First, employing Graph Neural Network (GNN) to propose drug combinations for treating the ailment by extracting embedding vectors of drugs and proteins from an extensive knowledge graph containing various biomedical data types, such as drug-protein interactions, gene expression, and drug-target interactions. Second, utilizing natural language processing to gather pertinent articles from clinical trials involving the previously recommended drugs. Finally, conducting network meta-analysis to evaluate the comparative efficacy of these drug combinations.ResultWe utilized our approach on a dataset containing drugs and genes as nodes, connected by edges indicating their associated p-values. Our DMoN model identified Cisplatin, Bleomycin, and Fluorouracil as the optimal drug combination for targeting the human genes/proteins associated with this cancer. Subsequent scrutiny of clinical trials and literature confirmed the validity of our findings. Additionally, network meta-analysis substantiated the efficacy of these medications concerning the pertinent genes.ConclusionThrough the utilization of DMoN as part of the RAIN protocol, our method introduces a fresh and effective way to suggest notable drug combinations for addressing proteins/genes linked to Tongue Neoplasms. This approach holds promise in assisting healthcare practitioners and researchers in pinpointing the best treatments for patients, as well as uncovering the fundamental mechanisms of the disease.HighlightsA new method using Deep Modularity Networks and the RAIN protocol can find the best drug combinations for treating Tongue Neoplasms, a common and deadly form of cancer.The method uses a Graph Neural Network to suggest drug pairings from a large knowledge graph of biomedical data, then searches for clinical trials and performs network meta-analysis to compare their effectiveness.The method discovered that Cisplatin, Bleomycin, and Fluorouracil are suitable drugs for targeting the genes/proteins involved in this cancer, and confirmed this finding with literature review and statistical analysis.The method offers a novel and powerful way to assist doctors and researchers in finding the optimal treatments for patients with Tongue Neoplasms, and to understand the underlying causes of the disease.Abstract Figure

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Lingual Alveolar Soft Part Sarcoma in a 78-Year-Old Woman: A Case Report and Comprehensive Review of the Literature from 1952 to 2022

Cited by 2 publications

References 55 publications

The dynamic contrast enhanced-magnetic resonance imaging and diffusion-weighted imaging features of alveolar soft part sarcoma

The dynamic contrast enhanced-magnetic resonance imaging and diffusion-weighted imaging features of alveolar soft part sarcoma

Emerging Drug Combinations for Targeting Tongue Neoplasms Associated Proteins/Genes: Employing Graph Neural Networks within the RAIN Protocol

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