Development of a Chemoresistant Risk Scoring Model for Prechemotherapy Osteosarcoma Using Single-Cell Sequencing

Single-cell transcriptional profiling in osteosarcoma and the effect of neoadjuvant chemotherapy on the tumor microenvironment

Osteosarcoma (OS), a malignant tumor, originates from the bone marrow. Currently, treatment for OS remains limited, making it urgent to understand the immune response in the tumor microenvironment of patients with OS. A comprehensive bioinformatics analysis was performed, including cell clustering subgroups, differential expression genes screening, proposed temporal order, and genomic variant analysis on single-cell RNA-sequencing data, from ten pre-chemotherapy patients and eleven post-chemotherapy patients. Subsequently, we analyzed the differentiation trajectories of osteoblasts, osteoclasts, fibroblasts, myeloid cells, and tumor-infiltrating lymphocytes (TILs) in detail to compare the changes in cell proportions and differential genes pre- and post-chemotherapy. The nine cell types were identified, including fibroblasts, myeloid cells, osteoblasts, TILs, osteoclasts, proliferative osteoblasts, pericytes, endothelial cells, and B cells. Post-chemotherapy treatment, the proportions of myeloid cells and TILs in OS were declined, while the number of osteoblasts was elevated. Besides, a decrease was observed in CD74, FTL, FTH1, MT1X and MT2A, and an increase in PTN, COL3A1, COL1A1, IGFBP7 and FN1. Meanwhile, EMT, DNA repair, G2M checkpoint, and E2F targets were highly enriched post-chemotherapy. Furthermore, there was a down-regulation in the proportions of CD14 monocytes, Tregs, NK cells and CD1C-/CD141-DCs, while an up-regulation was observed in the proportions of SELENOP macrophages, IL7R macrophages, COL1A1 macrophages, CD1C DCs, CD4+ T cells and CD8+ T cells. Overall, these findings revealed changes in the tumor microenvironment of OS post-chemotherapy treatment, providing a new direction for investigating OS treatment.

Single-cell RNA sequencing in osteoarthritis

Osteoarthritis is a progressive and heterogeneous joint disease with complex pathogenesis. The various phenotypes associated with each patient suggest that better subgrouping of tissues associated with genotypes in different phases of osteoarthritis may provide new insights into the onset and progression of the disease. Recently, single-cell RNA sequencing was used to describe osteoarthritis pathogenesis on a high-resolution view surpassing traditional technologies. Herein, this review summarizes the microstructural changes in articular cartilage, meniscus, synovium and subchondral bone that are mainly due to crosstalk amongst chondrocytes, osteoblasts, fibroblasts and endothelial cells during osteoarthritis progression. Next, we focus on the promising targets discovered by single-cell RNA sequencing and its potential applications in target drugs and tissue engineering. Additionally, the limited amount of research on the evaluation of bone-related biomaterials is reviewed. Based on the pre-clinical findings, we elaborate on the potential clinical values of single-cell RNA sequencing for the therapeutic strategies of osteoarthritis. Finally, a perspective on the future development of patient-centred medicine for osteoarthritis therapy combining other single-cell multi-omics technologies is discussed. This review will provide new insights into osteoarthritis pathogenesis on a cellular level and the field of applications of single-cell RNA sequencing in personalized therapeutics for osteoarthritis in the future.

Genomic and transcriptomic characterization of pre-operative chemotherapy response in patients with osteosarcoma

Osteosarcoma is a heterogeneous disease with regard to its chemotherapy response and clinical outcomes. This study aims to investigate the genomic and transcriptomic characteristics related to pre-operative chemotherapy response. Samples from 25 osteosarcoma patients were collected to perform both whole exome and transcriptome sequencing. Osteosarcoma had significant amount of chromosomal copy number variants (CNVs). Chemotherapy responders showed the higher chromosomal CNV burden than non-responders (p = 0.0775), but the difference was not significant. The percentage of COSMIC signature 3, associated with homologous recombination repair deficiency, was higher in responders (56%) than in non-responders (45%). Transcriptomic analysis suggested that 11 genes were significantly up-regulated in responders and 18 genes were up-regulated in non-responders. Both GSEA and KEGG enrichment analysis indicted that four pathways related to cardiomyopathy were up-regulated in responders, while neuroactive ligand - receptor interaction was up-regulated in non-responders. Finally, a previously published chemoresistant model was validated using our dataset, with the area under the curve of 0.796 (95% CI, 0.583-1.000). Osteosarcoma had the heterogeneous mutational profile with frequent occurrence of CNVs. Transcriptomic analysis identified several signaling pathways associated with chemotherapy responsiveness to osteosarcoma. Transcriptomic signatures provides a potential research direction for predicting the chemotherapy response.

Ferroptosis and WDFY4 as novel targets for immunotherapy of lung adenocarcinoma

BACKGROUND

Lung cancer exhibits the world's highest mortality rate among malignant cancers worldwide, thereby presenting a significant global challenge in terms of reducing patient mortality. In the field of oncology, targeted immunotherapy has emerged as a novel therapeutic approach for lung cancer. This study aims to explore potential targets for immunotherapy in lung adenocarcinoma (LUAD) through the analysis of Ferroptosis Index (FPI) and Single Cell RNA-Sequencing (scRNA-seq) data. The findings of this research can potentially offer valuable insights for improving LUAD immunotherapy strategies and informing clinical decision-making.

METHODS

Firstly, the relationship between survival and ferroptosis in LUAD patients was analyzed by FPI. Subsequently, the association between ferroptosis and infiltration and regulation of immune cells was explored by immune infiltration analysis and correlation statistics. Lastly, the relationship between major infiltrating immune cell populations and related pathways and prognosis of LUAD patients was analyzed by GSEA and GSVA. To screen out core genes regulating infiltration of immune cell populations, scRNA-seq data of cancer and para-cancerous tissues of LUAD patients were downloaded, followed by cell clustering analysis, cell identification of core subpopulations, pseudotime analysis, single-cell GSVA and pathway enrichment analysis, and identification and functional analysis of core regulatory genes. Moreover, the expression levels of core functional genes in LUAD tissue microarray were detected by immunohistochemistry, and its relationship with the prognosis of LUAD patients was verified. Finally, we used lentivirus with WDFY4 to transfect LUAD A549 cells. CCK-8, flow cytometry apoptosis detection, Scratch wound healing assay, Transwell migration assay, Xenograft nude mice model, immunohistochemical analysis and other experimental methods were used to explore the biological effects of WDFY4 on LUAD in vitro and in vivo.

RESULTS

Survival analysis of FPI values in LUAD patients revealed a positive correlation between smaller FPI values and longer overall survival. Immuno-infiltration analysis and its correlation with FPI values revealed that B cells were most strongly associated with ferroptosis. Ferroptosis of cancer cells could promote infiltration and activation of B cell populations, and LUAD patients with more infiltration of B cell populations had longer long-term survival. scRNA-seq data analysis indicated that the B cell population is one of the major cell populations infiltrated by immune cells in LUAD. During the later phases of B cell differentiation in LUAD, there was a decrease in the expression levels of ACAP1, LINC00926, TLR10, MS4A1, WDFY4, and TRIM22 genes, whereas the expression levels of TMEM59, TP53INP1, and METTL7A genes were elevated. The protein-protein interaction (PPI) network analysis indicated that WDFY4 plays a crucial role in regulating B cell differentiation in LUAD. Immunohistochemical analysis of LUAD tissue microarray revealed a significant downregulation of WDFY4 expression, which was closely related to the occurrence sites of LUAD. Moreover, LUAD patients with a low WDFY4 expression exhibited a poorer prognosis. Additionally, experimental findings demonstrated that the overexpression of WDFY4 could inhibit the proliferation and metastasis of A549 cells while promoting apoptosis. It was also confirmed that WDFY4 could inhibit cancer growth in vivo.

CONCLUSIONS

The results indicate that promoting infiltration and activation of B cell populations could improve the long-term survival of LUAD patients, thereby offering a potential novel immunotherapeutic approach for LUAD. Besides, the promotion of cancer cell ferroptosis and upregulation of WDFY4 expression have been shown to induce the infiltration and activation of B cell populations. Furthermore, the overexpression of WDFY4 can significantly inhibit the growth of lung adenocarcinoma in vitro and in vivo, highlighting its potential as a target for immunotherapy in LUAD.

How single-cell techniques help us look into lung cancer heterogeneity and immunotherapy

Lung cancer patients tend to have strong intratumoral and intertumoral heterogeneity and complex tumor microenvironment, which are major contributors to the efficacy of and drug resistance to immunotherapy. From a new perspective, single-cell techniques offer an innovative way to look at the intricate cellular interactions between tumors and the immune system and help us gain insights into lung cancer and its response to immunotherapy. This article reviews the application of single-cell techniques in lung cancer, with focuses directed on the heterogeneity of lung cancer and the efficacy of immunotherapy. This review provides both theoretical and experimental information for the future development of immunotherapy and personalized treatment for the management of lung cancer.

Complement C1QC as a potential prognostic marker and therapeutic target in colon carcinoma based on single-cell RNA sequencing and immunohistochemical analysis

Immune cell infiltration plays an essential role in the occurrence and development of colon cancer. However, the main tumor-associated immune cell infiltration and its gene regulation in colon cancer still need to be further clarified in order to provide a new perspective for diagnosing and treating this disease. For this study, single-cell RNA sequencing (scRNA-seq) expression profiles and TCGA colon cancer data sets were first acquired from the GEO database. Then, Seurat, Monocle, LIMMA, Clusterprofile, GSVA and GSEABase algorithms were used to systematically examine the data. Potential target drugs corresponding to target genes were analyzed in the Drugbank database and detected by molecular docking. Immunohistochemistry was used to assess the level of C1QC expression in the tissue microarray. Single cell analysis suggested that neutrophil activation might be the critical regulatory pathway in colon cancer and that macrophages were the main cell population involved. Subsequent functional enrichment analysis on differential genes in macrophages suggested that C1QC may be a critical regulatory factor in the occurrence and progression of colon cancer, and was closely related to the survival of patients. According to the drug target prediction, palivizumab is a targeted drug for C1QC, and molecular docking demonstrated that palivizumab binds to C1QC. Additionally, tissue-microarray based immunohistochemical analysis showed that C1QC was highly expressed in colon cancer tissue, and the prognosis of colon cancer patients with high C1QC expression was worse, closely related to age, lymphatic metastasis and the TNM stage (Tumor, Nodes and Metastases). Our findings suggest that C1QC may regulate the macrophages in colon cancer immune infiltration, which is expected to be a potential immunotherapy target for colon cancer, and beneficial for the diagnosis and prognosis of colon cancer patients.

Comprehensive analysis of potential cellular communication networks in advanced osteosarcoma using single-cell RNA sequencing data

Osteosarcoma (OS) is a common bone cancer in children and adolescents, and metastasis and recurrence are the major causes of poor treatment outcomes. A better understanding of the tumor microenvironment is required to develop an effective treatment for OS. In this paper, a single-cell RNA sequencing dataset was taken to a systematic genetic analysis, and potential signaling pathways linked with osteosarcoma development were explored. Our findings revealed 25 clusters across 11 osteosarcoma tissues, with 11 cell types including “Chondroblastic cells”, “Osteoblastic cells”, “Myeloid cells”, “Pericytes”, “Fibroblasts”, “Proliferating osteoblastic cells”, “Osteoclasts”, “TILs”, “Endothelial cells”, “Mesenchymal stem cells”, and “Myoblasts”. The results of Cell communication analysis showed 17 potential cellular communication networks including “COLLAGEN signaling pathway network”, “CD99 signaling pathway network”, “PTN signaling pathway network”, “MIF signaling pathway network”, “SPP1 signaling pathway network”, “FN1 signaling pathway network”, “LAMININ signaling pathway network”, “FGF signaling pathway network”, “VEGF signaling pathway network”, “GALECTIN signaling pathway network”, “PERIOSTIN signaling pathway network”, “VISFATIN signaling pathway network”, “ITGB2 signaling pathway network”, “NOTCH signaling pathway network”, “IGF signaling pathway network”, “VWF signaling pathway network”, “PDGF signaling pathway network”. This research may provide novel insights into the pathophysiology of OS’s molecular processes.

Identification of novel prognostic biomarkers for osteosarcoma: a bioinformatics analysis of differentially expressed genes in the mesenchymal stem cells from single-cell sequencing data set

BACKGROUND

Mesenchymal stem cells (MSCs) play a crucial role in osteosarcoma (OS) growth and progression. This study conducted a bioinformatics analysis of a single-cell ribonucleic acid sequencing data set and explored the MSC-specific differentially expressed genes (DEGs) in advanced OS.

METHODS

MSC-specific DEGs from GSE152048 was extracted using Seurat R package. These DEGs were then subjected to the functional analysis, and several key genes were further identified and underwent a prognosis analysis.

RESULTS

A total of 234 upregulated and 280 downregulated DEGs were identified between the MSCs and other cells, and a total of 188 upregulated and 158 downregulated DEGs were identified between the MSCs and osteoblastic cells. The Gene Ontology (GO) functional analysis showed that the specific DEGs between the MSCs and osteoblastic cells were enriched in GO terms such as "collagen catabolic process", "positive regulation of pathway-restricted SMAD protein phosphorylation", "osteoblast differentiation", "regulation of release of cytochrome c from mitochondria" and "interleukin-1 production". The specific DEGs between the MSCs and osteoblastic cells were subjected to a protein-protein interaction network analysis. Further, a survival analysis of 20 genes with combined scores >0.94 revealed that the low expression of ANXA1 (annexin A1) and TPM1 (tropomyosin 1) was associated with the shorter overall survival of OS patients, while the high expression of FDPS (farnesyl pyrophosphate synthase), IFITM5 (interferon-induced transmembrane protein 5), FKBP11 (FKBP prolyl isomerase 11), SP7, and SQLE (squalene epoxidase) was associated with the shorter overall survival of OS patients. In a further analysis, we compared the expression of ANXA1, FDPS, IFITM5, FKBP11, SP7, SQLE, and TPM1 between the MSCs and high-grade OS cells. Further validation studies using the GSE42352 data set revealed that ANXA1, FKBP11, SP7, and TPM1 were more upregulated in the MSCs than the high-grade OS cells, while FDPS, IFITM5, and SQLE were more downregulated in the MSCs than the high-grade OS cells.

CONCLUSIONS

Our bioinformatics analysis revealed 7 hub genes derived from the specific DEGs between the MSCs and osteoblastic cells. The 7 hub genes may serve as potential prognostic biomarkers for patients with OS.

Integrated single-cell RNA-seq analysis identifies immune heterogeneity associated with KRAS/TP53 mutation status and tumor-sideness in colorectal cancers

Background

The main objective of this study was to analyze the effects of KRAS/TP53 mutation status and tumor sideness on the immune microenvironment of colorectal cancer using integrated scRNA-seq data.

Methods

A total of 78 scRNA-seq datasets, comprising 42 treatment-naive colorectal tumors, 13 tumor adjacent tissues and 23 normal mucosa tissues were included. Standardized Seurat procedures were applied to identify cellular components with canonical cell marks. The batch-effect was assessed and corrected using harmony algorithm. The scMetabolism algorithm was used for single-cell metabolic analysis. The results and clinical significance were further validated using immunofluorescent-staining and TCGA-COAD datasets. Immune-infiltration scores of bulk-RNA-seq data were estimated using ssGSEA. The presto-wilcoxauc algorithm was used to identify differentially enriched genes or pathways across different subgroups. Two-sided p-value less than 0.05 was considered statistically significant.

Results

We refined the landscape of functional immune cell subtypes, especially T cells and myeloid cells, across normal mucosa, tumor adjacent and tumor tissue. The existence and function of two states of exhausted CD8+ T (Tex) subtypes in colorectal cancer, and FOLR2+ LYVE1+ macrophages indicating unfavorable prognosis in colorectal cancer were identified and validated. The diverse tumor mutation status reshaped the immune cell function and immune checkpoint ligands/receptors (ICLs/ICRs) expression pattern. Importantly, the KRAS/TP53 dual mutations significantly reduced the major energy metabolic functions in immune cells, and promoted the cell-to-cell communications towards immunosuppression in colorectal cancers. The results revealed LAG3, CD24-SIGLEC10 and HBEGF-CD9 pathways as potential therapeutic targets for dual mutant colorectal cancers.

Conclusions

We revealed that the immune microenvironment underwent a gradual remodeling with an enrichment of immunosuppressive myeloid cells from normal mucosa to tumor regions in colorectal cancers. Moreover, we revealed the metabolic heterogeneity of tumor-infiltrating immune cells and suggested that the KRAS/TP53 dual mutation may impair antitumor immunity by reducing T and myeloid cell energy metabolism and reshaping cellular interactions toward immunosuppression.

Integrated Single-Cell RNA-Sequencing Analysis of Gastric Cancer Identifies FABP1 as a Novel Prognostic Biomarker

Gastric cancer (GC) is usually diagnosed in an advanced stage at the first visit due to the atypical clinical symptoms. The low surgical resection rate and chemotherapy sensitivity result in dismal survival. Therefore, it is urgent to develop novel biomarkers with high sensitivity and specificity to accurately assess the prognosis of GC patients. In the present study, 3385 differentially expressed genes (DEGs) were obtained from the single-cell RNA sequencing data of GC specimens. Using the unsupervised dimensionality reduction, we further found 3 subsets of cells including gastric cells, plasmacytoid dendritic cells, and memory T cells. Based on the cell clustering, we explored the key regulatory genes for GC progression by pseudo-time analysis and functional enrichment analysis. According to the results, the significant differentially expressed fatty acid-binding protein 1 (FABP1) verified by pseudo-time analysis was identified as the hub gene of GC progression. FABP1 was shown to be closely related to the long-term survival and the age at diagnosis of patients with GC in analysis based on the TCGA (The Cancer Genome Atlas) database. To further verify the role of FABP1 in GC, we performed immunohistochemical (IHC) analysis using the GC tissue microarray and found that the expression level of FABP1 was higher in GC tissues than in the adjacent tissues. Moreover, GC patients with higher expression of FABP1 had a worse clinical outcome. In summary, our study revealed that FABP1 is a potential effective biomarker for the prognosis of GC, and high expression of FABP1 predicts unsatisfactory survival.