Single-cell and spatial transcriptomics reveal metastasis mechanism and microenvironment remodeling of lymph node in osteosarcoma.

BACKGROUND: Osteosarcoma (OS) is the most common primary malignant bone tumor and is highly prone to metastasis. OS can metastasize to the lymph node (LN) through the lymphatics, and the metastasis of tumor cells reestablishes the immune landscape of the LN, which is conducive to the growth of tumor cells. However, the mechanism of LN metastasis of osteosarcoma and remodeling of the metastatic lymph node (MLN) microenvironment is not clear. METHODS: Single-cell RNA sequencing of 18 samples from paracancerous, primary tumor, and lymph nodes was performed. Then, new signaling axes closely related to metastasis were identified using bioinformatics, in vitro experiments, and immunohistochemistry. The mechanism of remodeling of the LN microenvironment in tumor cells was investigated by integrating single-cell and spatial transcriptomics. RESULTS: From 18 single-cell sequencing samples, we obtained 117,964 cells. The pseudotime analysis revealed that osteoblast(OB) cells may follow a differentiation path from paracancerous tissue (PC) → primary tumor (PT) → MLN or from PC → PT, during the process of LN metastasis. Next, in combination of bioinformatics, in vitro and in vivo experiments, and immunohistochemistry, we determined that ETS2/IBSP, a new signal axis, might promote LN metastasis. Finally, single-cell and spatial dissection uncovered that OS cells could reshape the microenvironment of LN by interacting with various cell components, such as myeloid, cancer-associated fibroblasts (CAFs), and NK/T cells. CONCLUSIONS: Collectively, our research revealed a new molecular mechanism of LN metastasis and clarified how OS cells influenced the LN microenvironment, which might provide new insight for blocking LN metastasis.

Development and validation of neutrophil extracellular traps-derived signature to predict the prognosis for osteosarcoma patients.

Neutrophil extracellular traps (NETs) have been reported to be crucial in tumorigenesis and malignant progression. However, their prognostic significance, association with tumor immune microenvironment (TIME), and therapeutic response in osteosarcoma (OS) stills remain unclear. Hence, TARGET and GSE21257 cohorts were included for analysis. Single-sample gene set enrichment analysis (ssGSEA) and weighted gene co-expression network analysis (WGCNA) were conducted to extract NETs-derived genes. Subsequently, the NETs score (NETScore) model, consisting of 4 signature genes, was established and validated with the least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. Our results indicated that NETScore has satisfactory predictability of the patient's overall survival, with AUC values at 1-, 3- and 5-year in the training cohort of 0.798, 0.792 and 0.804, respectively; similar prominent prediction performance was obtained in three validation cohorts. Further, real-time quantitative PCR (RT-qPCR) assay was conducted to determine the expression of signature genes in human osteoblasts and OS cells. Besides, NETScore and clinical factors (age, gender, metastatic status) were integrated to construct a nomogram. C-index and AUC values at 1-, 3-, and 5-year were above 0.800, displaying robust predictive performance. Patients with high and low NETScore had different immune statuses and drug sensitivity. Meanwhile, several positive regulatory immune function pathways, including T cell proliferation, activation and migration, were significantly suppressed among patients with high NETScore. Summarily, we established a novel NETScore that can accurately predict OS patients' prognosis, which correlated closely with the immune landscape and therapeutic response and might help to guide clinical decision-making.

Association of survivin positive circulating tumor cell levels with immune escape and prognosis of osteosarcoma.

PURPOSE: Function of survivin protein (encoded by BIRC5) in circulating tumor cells (CTCs) of osteosarcoma (OS) has not been investigated. The goal of this study is to determine whether the expression of survivin protein of CTCs is associated with circulating immune cell infiltration and disease prognosis of OS. METHODS: Blood samples of 20 patients with OS were collected. CanPatrol™ CTC enrichment technology combined with in situ hybridization (ISH) was applied to enrich and test CTCs and survivin protein. Bioinformation analysis combined with data of routine blood test was used to verify the association between survivin and immune cell infiltration in circulatory system. To screen independent prognostic factors, Kaplan-Meier survival curve, univariate and multivariable Cox regression analyses were performed. RESULTS: Bioinformatics analysis showed that BIRC5 was strongly negatively related to lymphocyte, including T cell, NK cell and B cell, which released that BIRC5 played a key role in immune escape via reducing immune cell infiltration in circulatory system. Meanwhile, the number of survivin+ CTCs was significantly negatively connection with lymphocyte count (R = -0.56, p = 0.011), which was consistent with bioinformatics analysis. Kaplan-Meier curve showed that the overall survival rate in high survivin+ CTCs group was significantly lower than low group (88.9% vs 36.4%, p = 0.04). Multivariable Cox regression analyses showed that survivin+ CTCs were an independent prognostic factor (p = 0.019). CONCLUSION: These findings suggested that survivin protein played a key role in immune escape of CTCs and the presence of survivin+ CTCs might be a promising prognostic factor in OS patients.

Long non-coding RNA and circular RNA and coding RNA profiling of plasma exosomes of osteosarcoma by RNA seq.

Osteosarcoma (OS) is a primary bone tumor with high malignancy and the mechanism of hematogenous metastasis in OS is still not clear. The plasma exosomes derived from osteosarcoma play a key role in the process of tumor metastasis. Here, we established RNA-seq dataset for lncRNAs, circRNAs and mRNAs in plasma exosomes from 10 OS patients and 5 healthy donors. A total of 329.52 Gb of clean data was obtained. Besides, 1754 lincRNAs, 7096 known and 1935 new circRNA was identified. Finally, gene expression profiles and differentially expressed genes (DEGs) were analyzed among these 15 samples. There were 331 DEGs of mRNA, 132 of lincRNA and 489 of circRNA was obtained, respectively. This data set provides a significant resource for relevant researchers to excavate potential dysregulated lncRNAs, circRNAs and mRNAs of plasma exosomes in OS versus normal conditions.

Interaction gene set between osteoclasts and regulatory CD4+ T cells can accurately predict the prognosis of patients with osteosarcoma.

Osteoclasts (OCs) and regulatory CD4+ T cells (CD4+ Tregs) are important components in the tumor microenvironment (TME) of osteosarcoma. In this study, we collected six osteosarcoma samples from our previous study (GSE162454). We also integrated a public database (GSE152048), which included single cell sequencing data of 11 osteosarcoma patients. We obtained 138,192 cells and then successfully identified OCs and CD4+ Tregs. Based on the interaction gene set between OCs and CD4+ Tregs, patients from GSE21257 were distinguished into two clusters by consensus clustering analysis. Both the tumor immune microenvironment and survival prognosis between the two clusters were significantly different. Subsequently, five model genes were identified by protein-protein interaction network based on differentially upregulated genes of cluster 2. Quantitative RT-PCR was used to detect their expression in human osteoblast and osteosarcoma cells. A prognostic model was successfully established using these five genes. Kaplan-Meier survival analysis found that patients in the high-risk group had worse survival (p = 0.029). Therefore, our study first found that cell-cell communication between OCs and CD4+ Tregs significantly alters TME and is connected to poor prognosis of OS. The model we constructed can accurately predict prognosis for osteosarcoma patients.

A novel molecular signature for predicting prognosis and immunotherapy response in osteosarcoma based on tumor-infiltrating cell marker genes.

Background: Tumor infiltrating lymphocytes (TILs), the main component in the tumor microenvironment, play a critical role in the antitumor immune response. Few studies have developed a prognostic model based on TILs in osteosarcoma. Methods: ScRNA-seq data was obtained from our previous research and bulk RNA transcriptome data was from TARGET database. WGCNA was used to obtain the immune-related gene modules. Subsequently, we applied LASSO regression analysis and SVM algorithm to construct a prognostic model based on TILs marker genes. What's more, the prognostic model was verified by external datasets and experiment in vitro. Results: Eleven cell clusters and 2044 TILs marker genes were identified. WGCNA results showed that 545 TILs marker genes were the most strongly related with immune. Subsequently, a risk model including 5 genes was developed. We found that the survival rate was higher in the low-risk group and the risk model could be used as an independent prognostic factor. Meanwhile, high-risk patients had a lower abundance of immune cell infiltration and many immune checkpoint genes were highly expressed in the low-risk group. The prognostic model was also demonstrated to be a good predictive capacity in external datasets. The result of RT-qPCR indicated that these 5 genes have differential expression which accorded with the predicting outcomes. Conclusions: This study developed a new molecular signature based on TILs marker genes, which is very effective in predicting OS prognosis and immunotherapy response.

Analysis of scRNA-seq and bulk RNA-seq demonstrates the effects of EVI2B or CD361 on CD8+ T cells in osteosarcoma.

Osteosarcoma (OS) is a common primary malignant tumor of the bone in children and adolescents. The five-year survival rate is estimated to be ~70% based on the currently available treatment modalities. It is well known that tumor-infiltrating immune cells (TIICs) that are the most important components in the tumor microenvironment can exert a killing effect on tumor cells. Therefore, in the present study, 85 RNA-sequencing OS samples were categorized into high- and low-immune score groups with ESTIAMATE. Based on the immune score groups, 474 differentially expressed genes (DEGs) were acquired using the LIMMA package of R language. Subsequently, 86 DEGs were taken through univariate COX regression analysis, of which 14 were screened out by least absolute shrinkage and selection operator regression analysis. Furthermore, multivariate COX regression analysis was performed to obtain 4 DEGs. Finally, ecotropic virus integration site 2B (EVI2B) or CD361 gene was screened out via Kaplan-Meier analysis. In addition, CIBERSORT algorithm was used to evaluate the proportion of 22 kinds of TIICs in OS. Correlation analysis revealed that the high expression level of EVI2B can elevate the infiltrated proportion of CD8+ T cells. Moreover, analysis of single cell RNA-sequencing transcriptome datasets and immunohistochemical staining uncovered that EVI2B was mainly expressed on CD8+ T cells and that EVI2B could promote the expression of granzyme A and K of CD8+ T cells to exhibit a potent killing effect on tumor cells. Therefore, EVI2B was identified as a protective immune-related gene and contributed to good prognosis in OS patients.

Circ_0001060 Upregulates and Encourages Progression in Osteosarcoma.

Circular RNA (circRNA) is involved in the occurrence and development of various cancers. To this day, the expression and mechanism of circRNA in osteosarcoma (OS) remain unclear. We previously found that circ_0001060 was highly expressed in OS tumor tissues. In this work, we identified that high level expression of circ_0001060 was significantly associated with late clinical stage, larger tumor volume, higher frequency of metastasis, and poor prognosis in OS patients. Furthermore, we confirmed that silencing circ_0001060 inhibited the proliferation and migration of OS cell. Using bioinformatics analysis, we built three circRNA-miRNA-mRNA regulatory modules (circ_0001060-miR-203a-5p-TRIM21, circ_0001060-miR-208b-5p-MAP3K5, and circ_0001060-miR-203a-5p-PRKX), suggesting that these signaling axes may be involved in the inhibitory effect of circ_0001060 on OS. To sum up, circ_0001060 is a novel tumor biomarker for OS as well as a potential therapeutic target.

A new model of preoperative systemic inflammatory markers predicting overall survival of osteosarcoma: a multicenter retrospective study.

BACKGROUND: The purpose of this study was to investigate the significance of preoperative C-reactive protein-to-albumin ratio (CAR), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in predicting overall survival (OS) of osteosarcoma, to establish a nomogram of an individualized prognostic prediction model for osteosarcoma. METHODS: Two hundred thirty-five patients with osteosarcoma from multiple centers were included in this study. Receiver operating characteristic (ROC) and Youden index were used to determine the optimal cutoff values ​​for CAR, NLR, and PLR. Univariate analysis using COX proportional hazards model to identify factors associated with OS in osteosarcoma, and multivariate analysis of these factors to identify independent prognostic factors. R software (4.1.3-win) rms package was used to build a nomogram, and the concordance index (C-index) and calibration curve were used to assess model accuracy and discriminability. RESULTS: Univariate analysis revealed that the OS of osteosarcoma is significantly correlated (P < 0.05) with CAR, NLR, PLR, Enneking stage, tumor size, age, neoadjuvant chemotherapy (NACT), and high alkaline phosphatase. Multivariate analysis confirmed that CAR, NLR, Enneking stage, NACT and tumor size are independent prognostic factors for OS of osteosarcoma. The calibration curve shows that the nomogram constructed from these factors has acceptable consistency and calibration capability. CONCLUSION: Preoperative CAR and NLR were independent predictors of osteosarcoma prognosis, and the combination of nomogram model can realize individualized prognosis prediction and guide medical practice.

Polyphyllin VII induces fibroblasts apoptosis via the ERK/JNK pathway.

Hypertrophic scar (HS) is a pathological scar that often occurs in burn patients. Its histology is characterized by the excessive proliferation of fibroblasts (FB) and excessive accumulation of extracellular matrix (ECM). Inhibition of proliferation and activation of FB is essential for the treatment of HS. The crude extracts of traditional Chinese medicines have beneficial therapeutic effects on HS besides possessing fewer side effects and being easily available. Polyphyllin VII (PP7) is an isoprene saponin isolated from Rhizoma paridis. It has a pro-apoptotic effect on cancer cells. In the present study, we demonstrate that PP7 exerts a significant inhibitory effect on hypertrophic scar fibroblasts (HSFs) in vitro. We also demonstrate that PP7 considerably induces the apoptosis of HSFs and inhibits their activity. Our data show that the PP7-induced HSFs cell apoptosis was mainly due to the enhanced expression of apoptotic genes (Bax, Caspase-3, Caspase-9) and decreased expression of Bcl-2. Moreover, PP7 treatment also enhances the expression of JNK, but that of extracellular protein kinases (ERK) was reduced, and induces apoptosis through ERK/JNK pathways. Thus, PP7 can be used as a drug to prevent the formation of HS.

Gö6983 attenuates titanium particle-induced osteolysis and RANKL mediated osteoclastogenesis through the suppression of NFκB/JNK/p38 pathways.

Osteoclast activation by wear particles has caused major difficulties for surgeons. Wear particles are the main causes of aseptic prosthetic loosening. Gö6983, a protein kinase C inhibitor, inhibits five subtypes of protein kinase C family members. Here, we found that Gö6983 had an obviously inhibitory effect on wear-particles-induced osteolysis in vivo. In vitro, Gö6983 inhibited RANKL-stimulated osteoclast formation and function by inhibiting the RANKL-stimulated nuclear factor-κB/JNK/p38 signaling pathway. We also observed that Go6983 had no effect on the differentiation of osteoblasts and osteoblast-associated genes expression. According to our data, Gö6983 has potential therapeutic effects for aseptic prosthetic loosening caused by osteoclast activation.