Immune evasion in lung metastasis of leiomyosarcoma: upregulation of EPCAM inhibits CD8+ T cell infiltration.

BACKGROUND: Leiomyosarcomas are among the most common histological types of soft tissue sarcoma (STS), with no effective treatment available for advanced patients. Lung metastasis, the most common site of distant metastasis, is the primary prognostic factor. We analysed the immune environment targeting lung metastasis of STS to explore new targets for immunotherapy. METHODS: We analysed the immune environment of primary and lung metastases in 38 patients with STS using immunohistochemistry. Next, we performed gene expression analyses on primary and lung metastatic tissues from six patients with leiomyosarcoma. Using human leiomyosarcoma cell lines, the effects of the identified genes on immune cells were assessed in vitro. RESULTS: Immunohistochemistry showed a significant decrease in CD8+ cells in the lung metastases of leiomyosarcoma. Among the genes upregulated in lung metastases, epithelial cellular adhesion molecule (EPCAM) showed the strongest negative correlation with the number of CD8+ cells. Transwell assay results showed that the migration of CD8+ T cells was significantly increased in the conditioned media obtained after inhibition or knock down of EPCAM. CONCLUSIONS: EPCAM was upregulated in lung metastases of leiomyosarcoma, suggesting inhibition of CD8+ T cell migration. Our findings suggest that EPCAM could serve as a potential novel therapeutic target for leiomyosarcoma.

Extensive analysis of 59 sarcoma-related fusion genes identified pazopanib as a potential inhibitor to COL1A1-PDGFB fusion gene.

Sarcomas are malignant mesenchymal tumors that are extremely rare and divergent. Fusion genes are involved in approximately 30% of sarcomas as driver oncogenes; however, their detailed functions are not fully understood. In this study, we determined the functional significance of 59 sarcoma-related fusion genes. The transforming potential and drug sensitivities of these fusion genes were evaluated using a focus formation assay (FFA) and the mixed-all-nominated-in-one (MANO) method, respectively. The transcriptome was also examined using RNA sequencing of 3T3 cells transduced with each fusion gene. Approximately half (28/59, 47%) of the fusion genes exhibited transformation in the FFA assay, which was classified into five types based on the resulting phenotype. The sensitivity to 12 drugs including multityrosine kinase inhibitors was assessed using the MANO method and pazopanib was found to be more effective against cells expressing the COL1A1-PDGFB fusion gene compared with the others. The downstream MAPK/AKT pathway was suppressed at the protein level following pazopanib treatment. The fusion genes were classified into four subgroups by cluster analysis of the gene expression data and gene set enrichment analysis. In summary, the oncogenicity and drug sensitivity of 59 fusion genes were simultaneously evaluated using a high-throughput strategy. Pazopanib was selected as a candidate drug for sarcomas harboring the COL1A1-PDGFB fusion gene. This assessment could be useful as a screening platform and provides a database to evaluate customized therapy for fusion gene-associated sarcomas.

Deep learning-based automatic-bone-destruction-evaluation system using contextual information from other joints.

BACKGROUND: X-ray images are commonly used to assess the bone destruction of rheumatoid arthritis. The purpose of this study is to propose an automatic-bone-destruction-evaluation system fully utilizing deep neural networks (DNN). This system detects all target joints of the modified Sharp/van der Heijde score (SHS) from a hand X-ray image. It then classifies every target joint as intact (SHS = 0) or non-intact (SHS ≥ 1). METHODS: We used 226 hand X-ray images of 40 rheumatoid arthritis patients. As for detection, we used a DNN model called DeepLabCut. As for classification, we built four classification models that classify the detected joint as intact or non-intact. The first model classifies each joint independently, whereas the second model does it while comparing the same contralateral joint. The third model compares the same joint group (e.g., the proximal interphalangeal joints) of one hand and the fourth model compares the same joint group of both hands. We evaluated DeepLabCut's detection performance and classification models' performances. The classification models' performances were compared to three orthopedic surgeons. RESULTS: Detection rates for all the target joints were 98.0% and 97.3% for erosion and joint space narrowing (JSN). Among the four classification models, the model that compares the same contralateral joint showed the best F-measure (0.70, 0.81) and area under the curve of the precision-recall curve (PR-AUC) (0.73, 0.85) regarding erosion and JSN. As for erosion, the F-measure and PR-AUC of this model were better than the best of the orthopedic surgeons. CONCLUSIONS: The proposed system was useful. All the target joints were detected with high accuracy. The classification model that compared the same contralateral joint showed better performance than the orthopedic surgeons regarding erosion.

Nuclear ß-catenin translocation plays a key role in osteoblast differentiation of giant cell tumor of bone.

Denosumab is a game-changing drug for giant cell tumor of bone (GCTB); however, its clinical biomarker regarding tumor ossification of GCTB has not been elucidated. In this study, we investigated the relationship between Wnt/ß-catenin signaling and the ossification of GCTB and evaluated whether endogenous nuclear ß-catenin expression predicted denosumab-induced bone formation in GCTB. Genuine patient-derived primary GCTB tumor stromal cells exhibited osteoblastic characteristics. Identified osteoblastic markers and nuclear ß-catenin translocation were significantly upregulated via differentiation induction and were inhibited by treating with Wnt signaling inhibitor, GGTI-286, or selective Rac1-LEF inhibitor, NSC23766. Furthermore, we reviewed the endogenous ossification and nuclear ß-catenin translocation of 86 GCTB clinical samples and elucidated that intra-tumoral ossification was significantly associated with the nuclear translocation. Three-dimensional quantitative analyses (n = 13) of tumoral CT images have revealed that the nuclear ß-catenin translocation of naïve GCTB samples was significantly involved with the denosumab-induced tumor ossification. Our findings suggest a close relationship between the nuclear ß-catenin translocation and the osteoblastic differentiation of GCTB. Investigations of the nuclear ß-catenin in naïve GCTB samples may provide a promising biomarker for predicting the ossification of GCTB following denosumab treatment.

Methylation-mediated silencing of protein kinase C zeta induces apoptosis avoidance through ATM/CHK2 inactivation in dedifferentiated chondrosarcoma.

BACKGROUND: Dedifferentiated chondrosarcoma (DDCS) is an aggressive bone tumour with a poor prognosis and no effective treatment. Because changes in DNA methylation play critical roles in DDCS, we explored the roles that DNA methylation plays in oncogenesis to potentially identify an effective epigenetic treatment. METHODS: We identified genes downregulated in DDCS vs. conventional chondrosarcoma (CCS) due to DNA methylation using in silico analysis. The results were validated in DDCS clinical samples, and the molecular functions of the genes of interest were investigated in multiple chondrosarcoma cell lines (NDCS-1, SW1353, and OUMS-27). The therapeutic effect of decitabine, a DNA methyltransferase inhibitor, was evaluated in vitro and in vivo. RESULTS: PRKCZ was specifically downregulated by DNA methylation in DDCS. Overexpression of PRKCZ decreased the proliferation of NDCS-1 and SW1353 cells. PRKCZ directly bound to and activated ATM, which was followed by phosphorylation of CHK2 and subsequent apoptosis. Decitabine increased PRKCZ expression through de-methylating the promoter region of PRKCZ, which activated the ATM/CHK2 pathway and inhibited cell proliferation by inducing apoptosis. CONCLUSIONS: Increased DNA methylation and reduced expression of PRKCZ prevents apoptosis via inactivation of the ATM/CHK2 pathway in DDCS. Decitabine-induced expression of PRKCZ represents a promising therapy for DDCS.

Does the Use of Peripheral Immune-Related Markers Indicate Whether to Administer Pazopanib, Trabectedin, or Eribulin to Advanced Soft Tissue Sarcoma Patients?

Pazopanib, trabectedin, and eribulin are administered for the treatment of soft tissue sarcomas (STSs); however, there is little consensus on which agent should be preferentially used in a clinical setting. This study assessed whether peripheral immune-related markers served as a useful reference when selecting pazopanib, trabectedin, or eribulin. This study included 63 patients who were administered pazopanib, trabectedin, or eribulin for advanced STSs between March 2015 and December 2020. Patients were divided into three groups based on the first drug administered among these three drugs. Differences in overall survival (OS) or progression-free survival (PFS) among the three groups were analyzed. OS showed no significant differences among the drugs administered first. For patients with low neutrophil-to-lymphocyte ratio (NLR), the OS of patients administered pazopanib as the first choice was shorter than the others (hazard ratio [HR] = 9.53, 95% confidence interval [CI] = 1.94-18.13, p = 0.0018). In the low platelet-to-lymphocyte ratio (PLR) subgroup, the OS of the patients administered eribulin for the first choice was longer than that of the others (HR = 0.32, 95%CI = 0.10-0.98, p = 0.046). Therefore, NLR and PLR might be used as prognostic indicators to dictate whether STS patients receive pazopanib, trabectedin, or eribulin.

Predictive factors of non-treatment and non-persistence to osteoporosis medication after fragility hip fractures at 3 years after discharge: a multicentre, prospective cohort study in the northern Kyushu district of Japan.

We examined osteoporosis medication use and factors affecting persistence in 497 patients with fragility hip fractures. Only 25.5% of patients received continuous medication for 3 years, and 44.1% of patients received no treatment. Low Barthel index at discharge was a risk factor for both non-treatment and non-persistence to osteoporosis medication. PURPOSE: Fragility hip fractures (FHF) caused by osteoporosis decrease the quality of life and worsen life expectancy. Use of osteoporosis medication may be an efficient method in the prevention of secondary FHF. However, previous studies have reported low rates of osteoporosis medication and persistence after FHF. This study aimed to evaluate osteoporosis medication use and factors affecting persistence in patients with FHF in the northern Kyushu area of Japan. METHODS: A total of 497 FHF patients aged ≥ 60 years with a 3-year follow-up were included. We prospectively collected data from questionnaires sent every 6 months regarding compliance with osteoporosis medication. We compared baseline characteristics among three groups: no treatment (NT), no persistence (NP), and persistence (P), and conducted multivariable regression models to determine covariates associated with non-treatment (NT vs. NP/P) and non-persistence (NP vs. P). RESULTS: There were 219 (44.1%), 151 (30.4%), and 127 (25.5%) patients in the NT, NP, and P groups, respectively. Factors associated with non-treatment were male sex, chronic kidney disease, no previous osteoporosis treatment, and low Barthel index (BI) at discharge. The only factor associated with non-persistence was a low BI at discharge. Factors associated with a low BI at discharge were male sex, older age, trochanteric fracture, and surgical delay. CONCLUSION: Low BI at discharge is a risk factor for both non-treatment and non-persistence to osteoporosis medication. Therefore, appropriate interventions to improve BI may result in persistence to osteoporosis medication.