Development of an immune-related prognostic index associated with osteosarcoma

Single-Cell RNA Sequencing Pro-angiogenic Macrophage Profiles Reveal Novel Prognostic Biomarkers and Therapeutic Targets for Osteosarcoma

Osteosarcoma (OS) is a malignant bone tumor that most commonly occurs in children and adolescents. OS patients have a poor prognosis, and 5-year survival rates have rarely improved significantly over the past few decades. OS prognosis may be related to the infiltration of tumor-associated macrophages (TAMs). However, the role of proangiogenic macrophages, a subtype of TAMs, in OS prognosis has not been reported. In this study, seven subtypes of TAMs were identified from single-cell RNA sequencing (scRNA-seq) data that we propose defining as proangiogenic TAMs (Angio-TAMs), interferon-primed TAMs (IFN-TAMs), inflammatory cytokine-enriched TAMs (Inflam-TAMs), immune regulatory TAMs (Reg-TAMs), lipid-associated TAMs (LA-TAMs), and resident-tissue macrophages like TAMs (RTM-TAMs) (containing two subcellular types). In the survival analysis of each macrophage subtype, it was found that patients with Angio-TAMs had the most significant difference in survival. Eight genes associated with Angio-TAMs were obtained by differential expression analysis, and these genes were built into a prognostic model using the LASSO algorithm. Clinical OS case samples were categorized into high-risk and low-risk subgroups using median risk scores. In comparison to the low-risk subgroup, the survival time of the high-risk subgroup was much shorter. Additional studies on immune cell infiltration and immune checkpoint molecule expression in the two risk subgroups were carried out. In immunotherapy response prediction, the Angio-TAM-associated gene risk signature was found to be negatively correlated with immune checkpoint responses. In addition, the associated enriched GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways were mainly involved in the malignant progression of tumors. As suggested by these findings, the Angio-TAM gene risk signature may be an underlying prognostic biomarker and novel therapeutic target for OS patients.Kindly check and confirm whether the ESM file is correctly identifiedWe have checked this file and confirmed that it can be correctly identified.

Targeted Regulation of Osteoblasts and Osteoclasts in Osteosarcoma Patients by CSF3R Receptor Inhibition of Osteolysis Caused by Tumor Inflammation Based on Transcriptional Spectrum Analysis and Drug Library Screening

BACKGROUND

Osteosarcoma (OS) is a common primary malignant bone tumor that mainly occurs in children and adolescents. The use of IL-8 inhibitor compounds has been reported in patents, which can be used to treat and/or prevent osteosarcoma, but the pathogenesis of osteosarcoma remains to be investigated. At present, osteoblasts and osteoclasts play an important role in the occurrence and development of OS. However, the relationship between osteoblasts and osteoclasts in the specific participation mechanism and inflammatory response of OS patients has not been further studied.

METHODS

The transcriptome, clinical data, and other data related to OS were downloaded from the GEO database to analyze them with 200 known inflammatory response genes. We set the screening conditions as p < 0.05 and | log2FC| > 0.50, screened the differentially expressed genes (DEGs) related to OS, tested the correlation coefficient between the OS INF gene and clinical risk, and analyzed the survival prognosis. We further enriched and analyzed the DEGs and inflammatory response genes of OS with GO/KEGG to explore the potential biological function and signal pathway mechanism of OS inflammatory response genes. Moreover, the virtual screening of drug sensitivity of OS based on the FDA drug library was also carried out to explore potential therapeutic drugs targeted to regulate OS osteogenesis and osteoclast inflammation, and finally, the molecular dynamics simulation verification of OS core protein and potential drugs was carried out to explore the binding stability and mechanism between potential drugs and core protein.

RESULTS

Through differential analysis of GSE39058, GSE36001, GSE87624, and three other data sets closely related to OS osteoblasts and osteoclasts, we found that there was one upregulated gene (CADM1) and one down-regulated gene (PHF15) related to OS. In addition, GSEA enrichment analysis of the DEGs of OS showed that it was mainly involved in the progress of OS through biological functions, such as oxidative photosynthesis, acute junction, and epithelial-mesenchymal transition. The enrichment analysis of OS DEGs revealed that they mainly affect the occurrence and progress of OS by participating in the regulation of the actin skeleton, PI3K Akt signal pathway, complement and coagulation cascade. According to the expression of CSF3R in OS patients, a risk coefficient model and a diagnostic model were established. It was found that the more significant the difference in the CSF3R gene in OS patients, the greater the risk coefficient of disease (p < 0.05). The AUC under the curve of the CSF3R gene was greater than 0.65, which had a good diagnostic significance for OS. The above results showed that the prognosis risk gene CSF3R related to OS inflammation was closely related to the survival status of OS patients. Finally, through the virtual screening of the ZINC drug library and molecular dynamics simulation, it was found that the docking model formed by the core protein CSF3R and the compounds, Leucovorin and Methotrexate, were the most stable, which revealed that the compounds Leucovorin and Methotrexate might play a role in the treatment of OS by combining with the inflammatory response related factor CSF3R of OS.

CONCLUSION

CSF3R participates in the occurrence and development of OS bone destruction by regulating the inflammatory response of osteoblasts and osteoclasts and can affect the survival prognosis of OS patients.

Establishment of a new prognostic risk model of GNG7 pathway-related molecules in clear cell renal cell carcinoma based on immunomodulators

Clear cell renal cell carcinoma (CCRCC) is a common tumor of the urological system for which surgery is the preferred treatment, but there is a lack of therapeutic options after surgery. This study aims to explore the biological role of GNG7 on CCRCC from a genetic perspective. Differences in mRNA expression and patient survival of GNG7 in patients with CCRCC and healthy patients were analyzed using the TCGA database. It was observed that GNG7 gene expression was downregulated in CCRCC tissue compared with healthy tissue, and high GNG7 predicted better prognosis for patients, and GNG7 also showed strong variability in clinical and TMN staging. The immune relevance of GNG7 and related genes was explored using renal cancer data from CCLE and TISIDB database. It was verified that the risk score constructed by 7 GNG7-related regulators might be used as an independent prognostic risk factor for CCRCC. A CCRCC prognostic model that involved 7 immune genes was further established to predict the survival probabilities of patients. At last, the GEO database and immunochemical tissue staining were used to validate GNG7 expression in CCRCC. Our study proposed a novel panel of genes to predict CCRCC OS based on GNG7-related immune genes, which may help to accurately predict the prognosis of CCRCC patients and make better clinical decisions for individual treatment.

The fibrinogen-albumin ratio as a novel prognostic factor for elderly patients with osteosarcoma

To analyze the prognostic value of fibrinogen-albumin ratio (FAR) in predicting the overall survival in elderly osteosarcoma patients. One hundred nineteen elderly osteosarcoma patients (> 40 years old) from 2 centers were retrospectively reviewed and analyzed. The cutoff values of the biomarker were calculated via receiver operating characteristic curves, and the cohort was divided into high FAR group and low FAR group. The association between the FAR and clinical-pathological parameters was analyzed. And the prognosis of elderly osteosarcoma patients and the potential risk factors were analyzed using Kaplan-Meier method and Cox proportional hazards model. Finally, a clinical nomogram was constructed, and its predictive capacity was verified. According to receiver operating characteristic results, the cutoff value for FAR was 0.098, and the enrolled patients were divided into the low FAR group and high FAR group. The FAR was significantly correlated with several clinical-pathological characteristics, including age, tumor size, tumor stage, recurrence, and metastasis. Moreover, the multivariate Cox analyses results showed that the FAR, pathological fracture, and metastasis were independent risk factors for overall survival in elderly osteosarcoma patients. The predictive nomogram was subsequently constructed, representing satisfactory predictive performance for prognosis in elderly patients with osteosarcoma. The FAR value is a promising indicator for elderly osteosarcoma patients, which is correlated with the various clinical characteristics and prognosis. A clinical nomogram integrating FAR and other clinical indicators is a convenient and available tool to assess the prognosis and manage the individualized and precise treatment of elderly patients with osteosarcoma.

Construction and validation of a novel cuproptosis-mitochondrion prognostic model related with tumor immunity in osteosarcoma

BACKGROUND

The purpose of this study was to develop a new prognostic model for osteosarcoma based on cuproptosis-mitochondrion genes.

MATERIALS AND METHODS

The data of osteosarcoma were obtained from TARGET database. By using Cox regression and LASSO regression analysis, a novel risk score was constructed based on cuproptosis-mitochondrion genes. Kaplan-Meier, ROC curve and independent prognostic analyses were performed to validate the risk score in GSE21257 dataset. Then, a predictive nomogram was constructed and further validated by calibration plot, C-index and ROC curve. Based on the risk score, all patients were divided into high-risk and low-risk group. GO and KEGG enrichment, immune correlation and drug sensitivity analyses were performed between groups. Real-time quantitative PCR verified the expression of cuproptosis-mitochondrion prognostic model genes in osteosarcoma. And we explored the function of FDX1 in osteosarcoma by western blotting, CCK8, colony formation assay, wound healing assay and transwell assays.

RESULTS

A total of six cuproptosis-mitochondrion genes (FDX1, COX11, MFN2, TOMM20, NDUFB9 and ATP6V1E1) were identified. A novel risk score and associated prognostic nomogram were constructed with high clinical application value. Strong differences in function enrichment and tumor immune microenvironment were shown between groups. Besides, the correlation of cuproptosis-mitochondrion genes and drug sensitivity were revealed to search for potential therapeutic target. The expression of FDX1, COX11, MFN2, TOMM20 and NDUFB9 at mRNA level was elevated in osteosarcoma cells compared with normal osteoblast hFOB1.19. The mRNA expression level of ATP6V1E1 was decreased in osteosarcoma. Compared with hFOB1.19, western blotting revealed that the expression of FDX1 was significantly elevated in osteosarcoma cells. Functional experiments indicated that FDX1 mainly promoted the migration of osteosarcoma rather than proliferation.

CONCLUSIONS

We developed a novel prognostic model of osteosarcoma based on cuproptosis-mitochondrion genes, which provided great guidance in survival prediction and individualized treatment decision making for patients with osteosarcoma.

A four-lncRNA risk signature for prognostic prediction of osteosarcoma

Aim: Osteosarcoma is the most common primary malignant tumor of bone. However, our understanding of the prognostic indicators and the genetic mechanisms of the disease progression are still incomplete. The aim of this study was to identify a long noncoding RNA (lncRNA) risk signature for osteosarcoma survival prediction. Methods: RNA sequencing data and relevant clinical information of osteosarcoma patients were downloaded from the database of Therapeutically Applicable Research to Generate Effective Treatments (TARGET). We analyzed the differentially expressed lncRNAs between deceased and living patients by univariate and multivariate Cox regression analysis to identify a risk signature. We calculated a prognostic risk score for each sample according to this prognosis signature, and divided patients into high-risk and low-risk groups according to the median value of the risk score (0.975). Kaplan-Meier analysis and receiver operating characteristic (ROC) curve statistics were used to evaluate the performance of the signature. Next, we analyzed the signature's potential function through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene-set enrichment analysis (GSEA). Lastly, qRT-PCR was used to validate the expression levels of the four lncRNAs in clinical samples. Results: Twenty-six differentially expressed lncRNAs were identified between deceased and living patients. Four of these lncRNAs (CTB-4E7.1, RP11-553A10.1, RP11-24N18.1, and PVRL3-AS1) were identified as independent prognostic factors, and a risk signature of these four lncRNAs for osteosarcoma survival prediction was constructed. Kaplan-Meier analysis showed that the five-year survival time in high-risk and low-risk groups was 33.1% and 82.5%, and the area under the curve (AUC) of the ROC was 0.784, which demonstrated that the prognostic signature was reliable and had the potential to predict the survival of patients with osteosarcoma. The expression level of the four lncRNAs in osteosarcoma tissues and cells was determined by qRT-PCR. Functional enrichment analysis suggested that the signature might be related to osteosarcoma through regulation of the MAPK signaling pathway, the PI3K-Akt signaling pathway, and the extracellular matrix and also provided new insights into the study of osteosarcoma, including the role of papillomavirus infection, olfactory receptor activity, and olfactory transduction in osteosarcoma. Conclusion: We constructed a novel lncRNA risk signature that served as an independent biomarker for predicting the prognosis of osteosarcoma patients.

Identification of a novel immune-related gene signature for prognosis and the tumor microenvironment in patients with uveal melanoma combining single-cell and bulk sequencing data

Introduction

Uveal melanoma (UVM) is the most invasive intraocular malignancy in adults with a poor prognosis. Growing evidence revealed that immune-related gene is related to tumorigenesis and prognosis. This study aimed to construct an immune-related prognostic signature for UVM and clarify the molecular and immune classification.

Methods

Based on The Cancer Genome Atlas (TCGA) database, single-sample gene set enrichment (ssGSEA) and hierarchical clustering analysis were performed to identify the immune infiltration pattern of UVM and classify patients into two immunity clusters. Then, we proposed univariate and multivariate Cox regression analysis to identify immune-related genes that related to overall survival (OS) and validated in the Gene Expression Omnibus (GEO) external validation cohort. The molecular and immune classification in the immune-related gene prognostic signature defined subgroups were analyzed.

Results

The immune-related gene prognostic signature was constructed based on S100A13, MMP9, and SEMA3B genes. The prognostic value of this risk model was validated in three bulk RNA sequencing datasets and one single-cell sequencing dataset. Patients in the low-risk group had better OS than those in the high-risk group. The receiver-operating characteristic (ROC) analysis revealed its strong predictive ability for UVM patients. Lower expression of immune checkpoint genes was presented in the low-risk group. Functional studies showed that S100A13 knockdown via siRNA inhibited UVM cell proliferation, migration, and invasion in vitro, with the increased expression of reactive oxygen species (ROS) related markers in UVM cell lines.

Discussion

The immune-related gene prognostic signature is an independent predictive factor for the survival of patients with UVM and provides new information about cancer immunotherapy in UVM.

CKB affects human osteosarcoma progression by regulating the p53 pathway

This study aimed to explore the role of the creatine kinase B (CKB) gene in the development of human osteosarcoma (OS). Western blotting and qRT-PCR were performed to detect CKB expression in tissues and cells. CCK-8, colony formation, flow cytometry, Transwell, and cell scratch assays were performed to detect OS cell viability, proliferation, apoptosis, invasion, and migration. Gene set enrichment analysis (GSEA) was used to conduct signal pathway enrichment. CKB expression was higher in OS tissues and cells than that in normal tissues and cells. Silencing CKB expression reduced cell proliferation, migration, and invasion, and improved cell apoptosis in HOS cells, while overexpressing CKB increased cell proliferation, migration, and invasion, and decreased apoptosis in U2-OS cells. GSEA showed that CKB affected the p53 signaling pathway. Overexpression of CKB inhibited the protein expression of p53, p21, and Bax and promoted the expression of Bcl-2 and MDM2 in U2-OS cells. Conversely, silencing CKB promoted the protein expression of p53, p21, and Bax, and inhibited the expression of Bcl-2 and MDM2 in HOS cells. Silencing p53 could reverse the effect of the silencing CKB in HOS cells, and overexpressing p53 could reverse the effect of overexpressing CKB in U2-OS cells. Taken together, CKB affects the development of OS by regulating the activity of the p53 signaling pathway.

Expression of immune-related genes as prognostic biomarkers for the assessment of osteosarcoma clinical outcomes

Cancer immunotherapy is a promising therapeutic approach, but the prognostic value of immune-related genes in osteosarcoma (OS) is unknown. Here, Target-OS RNA-seq data were analyzed to detect differentially expressed genes (DEGs) between OS subgroups, followed by functional enrichment analysis. Cox proportional risk regression was performed for each immune-related gene, and a risk score model to predict the prognosis of patients with OS was constructed. The risk scores were calculated using the risk signature to divide the training set into high-risk and low-risk groups, and validation was performed with GSE21257. We identified two immune-associated clusters, C1 and C2. C1 was closely related to immunity, and the immune score was significantly higher in C1 than in C2. Furthermore, we validated 6 immune cell hub genes related to the prognosis of OS: CD8A, KIR2DL1, CD79A, APBB1IP, GAL, and PLD3. Survival analysis revealed that the prognosis of the high-risk group was significantly worse than that of the low-risk group. We also explored whether the 6-gene prognostic risk model was effective for survival prediction. In conclusion, the constructed a risk score model based on immune-related genes and the survival of patients with OS could be a potential tool for targeted therapy.

Identification and preliminary validation of a four-gene signature to predict metastasis and survival in osteosarcoma

Osteosarcoma is a primary malignant bone tumor that occurs frequently in children and adolescents and has a propensity for drug resistance, recurrence, and metastasis. The purpose of this study was to identify potential target genes to predict metastasis and survival in patients with osteosarcoma. We analyzed gene expression profiles and corresponding clinical data of patients with osteosarcoma in the Gene Expression Omnibus database and identified 202 genes that were differentially expressed between osteosarcoma cells and normal osteoblasts. Univariate and multivariable Cox regression analyses identified four risk genes that affected osteosarcoma prognosis: MCAM, ENPEP, LRRC1, and CPE. Independent prognostic analyses and clinical correlation studies showed that the four risk genes constituted an independent prognostic signature that correlated with survival and clinical parameters including age and distant metastasis. In a single-sample Gene Set Enrichment Analysis, risk scores based on the prognostic signature correlated with tumor infiltration by immune cells and immune functions in osteosarcoma. A subsequent analysis showed that the expression levels of the four genes in the prognostic signature were predictive of overall survival and metastasis-free survival of patients with osteosarcoma. Furthermore, Human Cancer Metastasis Database and qRT-PCR analyses demonstrated that the four risk genes are overexpressed in osteosarcoma tissues and cell lines. In summary, we developed and validated a four-gene prognostic signature that may be useful in osteosarcoma diagnosis and metastasis prediction.

DNA Damage Response Genes in Osteosarcoma

BACKGROUND

Improving the osteosarcoma (OS) patients' survival has long been a challenge, even though the disease's treatment is on the verge of progress. DNA damage response (DDR) has traditionally been associated with carcinogenesis, tumor growth, and genomic instability. No study has used DDR genes as a signature to identify the prognosis of OS. The goal of this work was to find an effective possible DDR gene biomarker for predicting OS prognosis, which may be useful in clinical diagnosis and therapy.

METHODS

To assess gene methylation, univariate and multivariate cox regression analyses were performed on data from OS patients. The data were retrieved from public databases, including the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and the Gene Expression Omnibus (GEO).

RESULTS

The DDR gene signature was chosen, which included seven genes (NHEJ1, RMI2, SWI5, ERCC2, CLK2, POLG, and MLH1). In the TARGET dataset, patients were categorized into two groups: high-risk and low-risk. Patients with a high-risk score revealed a shorter OS rate (hazard ratio (HR): 3.15, 95% confidence interval (CI): 1.38-4.34, P < 0.001) in comparison with the patients with a low-risk score in the TARGET as a training group. The validation of the prognostic signature accuracy was carried out in relapse and validation cohorts (TARGET, n = 75; GSE21257, n = 53). The signature was found to be an independent predictive factor for OS in multivariate cox regression analysis, and a nomogram model was developed to predict an individual's risk of OS. DDR gene signature involved in Fanconi anemia pathway, nonhomologous end-joining pathway, mismatch repair, and nucleotide excision repair pathway.

CONCLUSIONS

Our study suggests that the identified novel DDR genes could be a powerful prognostic tool for prognosis evaluation and a valuable tool in predicting the risk factors in OS patients.

Analysis of microRNA expression in CD133 positive cancer stem‑like cells of human osteosarcoma cell line MG-63

Osteosarcoma (OS) is a primary malignant tumor of bone occurring in young adults. OS stem cells (OSCs) play an important role in the occurrence, growth, metastasis, drug resistance and recurrence of OS. CD133 is an integral membrane glycoprotein, which has been identified as an OSC marker. However, the mechanisms of metastasis, chemoresistance, and progression in CD133(+) OSCs need to be further explored. In this study, we aim to explore differences in miRNA levels between CD133(+) and CD133(-) cells from the MG-63 cell line. We found 20 differentially expressed miRNAs (DEmiRNAs) (16 upregulated and 4 downregulated) in CD133(+) cells compared with CD133(-) cells. Hsa-miR-4485-3p, hsa-miR-4284 and hsa-miR-3656 were the top three upregulated DEmiRNAs, while hsa-miR-487b-3p, hsa-miR-493-5p and hsa-miR-431-5p were the top three downregulated DEmiRNAs. In addition, RT-PCR analysis confirmed that the expression levels of hsa-miR-4284, hsa-miR-4485-3p and hsa-miR-3656 were significantly increased, while the expression levels of hsa-miR-487b-3p, hsa-miR-493-5p, and hsa-miR-431-5p were significantly decreased in CD133(+) cells compared with CD133(-) cells. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that predicted or validated target genes for all 20 DEmiRNAs or the selected 6 DEmiRNAs participated in the "PI3K-Akt signaling pathway," "Wnt signaling pathway," "Rap1 signaling pathway," "Cell cycle" and "MAPK signaling pathway". Among the selected six DEmiRNAs, miR-4284 was especially interesting. MiR-4284 knockdown significantly reduced the sphere forming capacity of CD133(+) OS cells. The number of invasive CD133(+) OS cells was markedly decreased after miR-4284 knockdown. In addition, miR-4284 knockdown increased the p-β-catenin levels in CD133(+) OS cells. In conclusion, RNA-seq analysis revealed DEmiRNAs between CD133(+) and CD133(-) cells. MiRNAs might play significant roles in the function of OSCs and could serve as targets for OS treatment. MiR-4284 prompted the self-renewal and invasion of OSCs. The function of miR-4284 might be associated with the Wnt signaling pathway.

Immune-associated molecular occurrence and prognosis predictor of hepatocellular carcinoma: an integrated analysis of GEO datasets

Hepatocellular carcinoma (HCC) is the fifth most common cancer and the second most common cause of cancer-related deaths worldwide. As immune response failure is the main factor in the occurrence and poor prognosis of HCC, our study aimed to develop an immune-associated molecular occurrence and prognosis predictor (IMOPP) of HCC. To that end, we discovered a 4-gene immune-associated gene signature: C-C motif chemokine ligand 14 (CCL14), kallikrein B1 (KLKB1), vasoactive intestinal peptide receptor 1 (VIPR1), and cluster of differentiation 4 (CD4). When tested on three cohorts as an immune-associated molecular occurrence predictor (IMOP), it had high sensitivity, specificity, and area under the receiver operating characteristics curve. When tested as an immune-associated molecular prognosis predictor (IMPP), it stratified the HCC prognosis for overall survival (Kaplan-Meier analysis, log rank P = 0.0016; Cox regression, HR = 1.832, 95% CI = 1.173-2.859, P = 0.008) and disease-free survival (Kaplan-Meier analysis, log rank P = 0.0227). IMPP also significantly correlated with the clinicopathological characteristics of HCC; integrating it with clinicopathological characteristics improved the accuracy of a nomogram for overall survival prediction (C-index: 0.7097 vs. 0.6631). In HCC tumor microenviroments, the proportion of CD8⁺ T cells significantly differed between IMOP-stratified groups. We conclude that IMOPP can potentially predict the occurrence of HCC in high-risk populations and improve prognostic accuracy by providing new biomarkers for risk stratification. In addition, we believe that the IMOP mechanism may be related to its effect on the proportion of CD8⁺ T cells in tumor-infiltrating lymphocytes.

Prediction of clinical prognosis in cutaneous melanoma using an immune-related gene pair signature

Cutaneous melanoma (CM) is a malignant and aggressive skin cancer that is the leading cause of skin cancer-related deaths. Increasing evidence shows that immunity plays a vital role in the prognosis of CM. In this study, we developed an immune-related gene pair (IRGP) signature to predict the clinical prognosis of patients with CM. Immune-related genes from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were selected to construct the IRGPs, and patients with CM in these two cohorts were assigned to low- and high-risk subgroups. Moreover, we investigated the IRGPs and their individualized prognostic signatures using Kaplan-Meier survival analysis, univariate and multivariate Cox analyses, and analysis of immune cell infiltration in CM. A 41-IRGP signature was constructed from 2498 immune genes that could significantly predict the overall survival of patients with CM in both the TCGA and GEO cohorts. Immune infiltration analysis indicated that several immune cells, especially M1 macrophages and activated CD4 T cells, were significantly associated with the prognostic effect of the IRGP signature in patients with CM. Overall, the IRGP signature constructed in this study was useful for determining the prognosis of patients with CM and for providing further understanding of CM immunotherapy.