Intravoxel Incoherent Motion and Dynamic Contrast-Enhanced Magnetic Resonance Imaging Can Differentiate Between Atypical Cartilaginous Tumors and High-Grade Chondrosarcoma: Correlation With Histological Vessel Characteristics.

OBJECTIVE: To differentiate between atypical cartilaginous tumors and high-grade chondrosarcoma of the major long bones using intravoxel incoherent motion (IVIM) and Dynamic Contrast-Enhanced magnetic resonance imaging (DCE-MRI), and explore the correlation of quantitative parameters with hypoxia inducible factor-1α (HIF-1α), vascular endothelial growth factor (VEGF) and microvessel density (MVD). METHOD: Between September 2016 and March 2022, 35 patients (17 atypical cartilaginous tumors, 18 high-grade chondrosarcoma) underwent MRI examination and pathological confirmation at our hospital. First, IVIM-derived parameters ( D , D* , and f ), and DCE-MRI parameters ( Ktrans , Kep , and V e ) were measured, and intraclass correlation efficient (ICC) and Mann-Whitney U test were performed. Second, receiver-operating characteristic curve analysis was performed to evaluate the diagnostic performance. Finally, Spearman's correlation analysis was performed between the quantitative parameters of IVIM-DWI and DCE-MRI and the immunohistochemical factors HIF-1α, VEGF, and MVD in chondrosarcoma tissue. RESULTS: D in atypical cartilaginous tumors was significantly higher than that in high-grade chondrosarcoma ( P = 0.003), whereas D* , Ktrans , and K ep in atypical cartilaginous tumors were significantly lower than those in high-grade chondrosarcoma (all P < 0.001). Ktrans demonstrated the highest area under the curve (AUC) of 0.979. The D* , Ktrans , and K ep were positively correlated with HIF-1α, VEGF, and MVD (all P < 0.001), whereas D had no correlation with HIF-1α, VEGF, and MVD ( P = 0.113, 0.077, 0.058, respectively). CONCLUSION: The IVIM-DWI quantitative parameters ( D , D* ) and DCE-MRI quantitative parameters ( Ktrans , Kep ) are helpful to differentiate between atypical cartilaginous tumors and high-grade chondrosarcoma and could be imaging biomarkers to reflect the expressions of HIF-1α, VEGF, and angiogenesis of chondrosarcoma.

Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression.

BACKGROUND: Osteosarcoma has been the most common primary bone malignant tumor in children and adolescents. Despite the considerable improvement in the understanding of genetic events attributing to the rapid development of molecular pathology, the current information is still lacking, partly due to the comprehensive and highly heterogeneous nature of osteosarcoma. The study is to identify more potential responsible genes during the development of osteosarcoma, thus identifying promising gene indicators and aiding more precise interpretation of the disease. METHODS: Firstly, from GEO database, osteosarcoma transcriptome microarrays were used to screen the differential expression genes (DEGS) in cancer comparing to normal bone samples, followed by GO/KEGG interpretation, risk score assessment and survival analysis of the genes, for the purpose of selecting a credible key gene. Further, the basic physicochemical properties, predicted cellular location, gene expression in human cancers, the association with clinical pathological features and potential signaling pathways involved in the key gene's regulation on osteosarcoma development were in succession explored. RESULTS: Based on the selected GEO osteosarcoma expression profiles, we identified the differential expression genes in osteosarcoma versus normal bone samples, and the genes were classified into four groups based on the difference level, further genes interpretation indicated that the high differently level (> 8 fold) genes were mainly located extracellular and related to matrix structural constituent regulation. Meanwhile, module function analysis of the 67 high differential level (> 8 fold) DEGS revealed a 22-gene containing extracellular matrix regulation associated hub gene cluster. Further survival analysis of the 22 genes revealed that STC2 was an independent prognosis indicator in osteosarcoma. Moreover, after validating the differential expression of STC2 in cancer vs. normal tissues using local hospital osteosarcoma samples by IHC and qRT-PCR experiment, the gene's physicochemical property revealed STC2 as a cellular stable and hydrophilic protein, and the gene's association with osteosarcoma clinical pathological parameters, expression in pan-cancers and the probable biological functions and signaling pathways it involved were explored. CONCLUSION: Using multiple bioinformatic analysis and local hospital samples validation, we revealed the gain of expression of STC2 in osteosarcoma, which associated statistical significantly with patients survival, and the gene's clinical features and potential biological functions were also explored. Although the results shall provide inspiring insights into further understanding of the disease, further experiments and detailed rigorous clinical trials are needed to reveal its potential drug-target role in clinical medical use.

Multiple metastases of clear cell sarcoma at diagnosis presented in bone marrow aspirate: A case report.

Clear cell sarcoma (CCS) is a rare and aggressive soft-tissue sarcoma that arises most commonly in adolescents and young adults of both sexes. CCS presents a diagnostic challenge due to its morphological and immunohistochemical similarity to malignant melanoma. We present a rare and severe case of CCS simultaneously with multiple bone and lymph node metastases at the time of initial diagnosis in a previously healthy 15-year-old Chinese man. Detailed information on clinical manifestations, laboratory profiles, histopathological findings and poor outcome were described. The cytomorphology of bone marrow aspirate in CCS in Wright-Giemsa staining smear was first depicted in this case. The diagnostic difficulties of the rare case was also discussed.

Molecular profiling of gene fusions in soft tissue sarcomas by Ion AmpliSeqTM: a study of 35 cases.

Background: The accurate diagnosis of sarcoma can be difficult as there are over 70 different subtypes. While molecular profiling in soft tissue sarcoma (STS) has gradually been incorporated into routine diagnostics, conventional methods such as fluorescence in situ hybridization (FISH), reverse transcriptase-PCR (RT-PCR), and Sanger sequencing have several drawbacks. By allowing simultaneous analysis of multiple targets and increasing sequencing depth to achieve ultra-sensitivity, next-generation sequencing (NGS) can not only detect common genetic abnormalities without prior assumptions but also identify uncommon or even new variants. Methods: In this study, the applicability of NGS in assessing STS using the Ion Torrent Proton was evaluated and compared with other methods. A cohort of 35 tissue specimens from STS patients, including alveolar soft-part sarcoma (ASPS), Ewing's sarcoma (ES), synovial sarcoma (SS), dermatofibrosarcoma protuberans (DFSP), and myxoid liposarcoma (MLPS) patients, were subjected to NGS by an Ion AmpliSeqTM Custom panel. Results: A proportion of 97.14% (34/35) were successfully conducted to detect gene fusion positive events and met all criteria for good quality. The concordance between NGS and conventional techniques was 94.12% (32/34). NGS also showed superior results, as Sanger sequencing and FISH in two cases were false negatives, demonstrating the excellent diagnostic utility of NGS for translocation detection in STS. Conclusions: The results in this study show the potential for NGS to aid in diagnosis and clinical monitoring of STS and warrant additional studies in larger cohorts.

Bioinformatic analysis revealing mitotic spindle assembly regulated NDC80 and MAD2L1 as prognostic biomarkers in non-small cell lung cancer development.

BACKGROUND: Lung cancer has been the leading cause of tumor related death, and 80% ~ 85% of it is non-small cell lung cancer (NSCLC). Even with the rising molecular targeted therapies, for example EGFR, ROS1 and ALK, the treatment is still challenging. The study is to identify credible responsible genes during the development of NSCLC using bioinformatic analysis, developing new prognostic biomarkers and potential gene targets to the disease. METHODS: Firstly, three genes expression profiles GSE44077, GSE18842 and GSE33532 were picked from Gene Expression Omnibus (GEO) to analyze the genes with different expression level (GDEs) between NSCLC and normal lung samples, and the cellular location, molecular function and the biology pathways the GDEs enriched in were analyzed. Then, gene function modules of GDEs were explored based on the protein-protein interaction network (PPI), and the top module which contains most genes was identified, followed by containing genes annotation and survival analysis. Moreover, multivariate cox regression analysis was performed in addition to the Kaplan meier survival to narrow down the key genes scale. Further, the clinical pathological features of the picked key genes were explored using TCGA data. RESULTS: Three GEO profiles shared a total of 664 GDEs, including 232 up-regulated and 432 down-regulated genes. Based on the GDEs PPI network, the top function module containing a total of 69 genes was identified, and 31 of 69 genes were mitotic cell cycle regulation related. And survival analysis of the 31 genes revealed that 17/31 genes statistical significantly related to NSCLC overall survival, including 4 spindle assembly checkpoints, namely NDC80, BUB1B, MAD2L1 and AURKA. Further, multivariate cox regression analysis identified NDC80 and MAD2L1 as independent prognostic indicators in lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) respectively. Interestingly, pearson correlation analysis indicated strong connection between the four genes NDC80, BUB1B, MAD2L1 and AURKA, and their clinical pathological features were addressed. CONCLUSIONS: Using bioinformatic analysis of GEO combined with TCGA data, we revealed two independent prognostic indicators in LUAD and LUSC respectively and analyzed their clinical features. However, more detailed experiments and clinical trials are needed to verify their drug targets role in clinical medical use.