The role of SPP1 as a prognostic biomarker and therapeutic target in head and neck squamous cell carcinoma

A single-cell atlas deconstructs heterogeneity across multiple models in murine traumatic brain injury and identifies novel cell-specific targets

Traumatic brain injury (TBI) heterogeneity remains a critical barrier to translating therapies. Identifying final common pathways/molecular signatures that integrate this heterogeneity informs biomarker and therapeutic-target development. We present the first large-scale murine single-cell atlas of the transcriptomic response to TBI (334,376 cells) across clinically relevant models, sex, brain region, and time as a foundational step in molecularly deconstructing TBI heterogeneity. Results were unique to cell populations, injury models, sex, brain regions, and time, highlighting the importance of cell-level resolution. We identify cell-specific targets and previously unrecognized roles for microglial and ependymal subtypes. Ependymal-4 was a hub of neuroinflammatory signaling. A distinct microglial lineage shared features with disease-associated microglia at 24 h, with persistent gene-expression changes in microglia-4 even 6 months after contusional TBI, contrasting all other cell types that mostly returned to naive levels. Regional and sexual dimorphism were noted. CEREBRI, our searchable atlas (https://shiny.crc.pitt.edu/cerebri/), identifies previously unrecognized cell subtypes/molecular targets and is a leverageable platform for future efforts in TBI and other diseases with overlapping pathophysiology.

Open-ST: High-resolution spatial transcriptomics in 3D

Spatial transcriptomics (ST) methods unlock molecular mechanisms underlying tissue development, homeostasis, or disease. However, there is a need for easy-to-use, high-resolution, cost-efficient, and 3D-scalable methods. Here, we report Open-ST, a sequencing-based, open-source experimental and computational resource to address these challenges and to study the molecular organization of tissues in 2D and 3D. In mouse brain, Open-ST captured transcripts at subcellular resolution and reconstructed cell types. In primary head-and-neck tumors and patient-matched healthy/metastatic lymph nodes, Open-ST captured the diversity of immune, stromal, and tumor populations in space, validated by imaging-based ST. Distinct cell states were organized around cell-cell communication hotspots in the tumor but not the metastasis. Strikingly, the 3D reconstruction and multimodal analysis of the metastatic lymph node revealed spatially contiguous structures not visible in 2D and potential biomarkers precisely at the 3D tumor/lymph node boundary. All protocols and software are available at https://rajewsky-lab.github.io/openst.

Diagnostic role of SPP1 and collagen IV in a rat model of type 2 diabetes mellitus with MASLD

Type 2 diabetes mellitus combined with metabolic dysfunction-associated steatotic liver disease (MASLD) leads to an increasing incidence of liver injury year by year, and patients are at a significantly higher risk of developing cirrhosis or even liver failure. No drugs have emerged to specifically treat this disease. The aim of this study is to investigate the mechanisms and causative hub genes of type 2 diabetes combined with MASLD. The data were obtained through the GEO platform for bioinformatics analysis and validated by in vitro experiments to find the causative targets of type 2 diabetes mellitus combined with MASLD, which will provide some theoretical basis for the development of future therapeutic drugs. GSE23343 and GSE49541 were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) in type 2 diabetes mellitus combined with MASLD for functional enrichment analysis. And STRING database and Cytoscape software were used to construct Protein-Protein Interaction (PPI) and hub gene networks. And GO (gene ontology, GO) analysis and KEGG (Kyoto encyclopedia of genes and genomes, KEGG) enrichment analysis were performed on target genes. A total of 185 co-expressed DEGs were obtained by differential analysis, and 20 key genes involved in the development and progression of type 2 diabetes were finally screened. These 20 key genes were involved in 529 GO enrichment results and 20 KEGG enrichment results, and were mainly associated with ECM-receptor interaction, Focal adhesion, Human papillomavirus infection, PI3K-Akt signaling pathway, and the Toll-like receptor signaling pathway. A total of two target genes (SPP1, collagen IV) were found to be highly correlated with type 2 diabetes mellitus combined with MASLD. Real time PCR results showed that there was a significant difference in SPP1 and collagen IV mRNA expression among the three groups (P < 0.05). SPP1 and Collagen IV may be candidate biomarkers for type 2 diabetes mellitus combined with MASLD, as verified by bioinformatics screening and in vitro experiments. Our findings provide new targets for the treatment of type 2 diabetes combined with MASLD.

Novel tumor-associated macrophage populations and subpopulations by single cell RNA sequencing

Tumor-associated macrophages (TAMs) are present in almost all solid tumor tissues. 16They play critical roles in immune regulation, tumor angiogenesis, tumor stem cell activation, tumor invasion and metastasis, and resistance to therapy. However, it is unclear how TAMs perform these functions. With the application of single-cell RNA sequencing (scRNA-seq), it has become possible to identify TAM subpopulations associated with distinct functions. In this review, we discuss four novel TAM subpopulations in distinct solid tumors based on core gene signatures by scRNA-seq, including FCN1 +, SPP1 +, C1Q + and CCL18 + TAMs. Functional enrichment and gene expression in scRNA-seq data from different solid tumor tissues found that FCN1 + TAMs may induce inflammation; SPP1 + TAMs are potentially involved in metastasis, angiogenesis, and cancer cell stem cell activation, whereas C1Q + TAMs participate in immune regulation and suppression; And CCL18 + cells are terminal immunosuppressive macrophages that not only have a stronger immunosuppressive function but also enhance tumor metastasis. SPP1 + and C1Q + TAM subpopulations can be further divided into distinct populations with different functions. Meanwhile, we will also present emerging evidence highlighting the separating macrophage subpopulations associated with distinct functions. However, there exist the potential disconnects between cell types and subpopulations identified by scRNA-seq and their actual function.

Immunosuppressive role of SPP1-CD44 in the tumor microenvironment of intrahepatic cholangiocarcinoma assessed by single-cell RNA sequencing

PURPOSE

To demonstrate the biological function of Secreted Phosphoprotein 1(SPP1) and its immune suppressive role in the progression intrahepatic cholangiocarcinoma (ICC).

METHODS

We collected 62,770 cells' published transcriptome data of nine patients whose paired adjacent liver and tumor tissues were both available. We applied differential gene expression analysis to screen potential ICC marker genes, survival analysis to verify the prognostic value of SPP1, and correlation analysis to decipher factors that are related to SPP1 expression. The CellChat was used to distinguish interactions between cancer and T cells. CytoSig was applied to query cytokines that modulate CD44. Further, we established a proliferation score and correlated the score with inhibitory signals to determine the proliferation-suppressive function of SPP1-CD44.

RESULTS

SPP1 expression is significantly upregulated in tumoral epitheliums, and patients with higher SPP1 expression have worse survival (P < 0.05). Tumor cells communicate with T cells via SPP1-CD44 interactions. The average expression of SPP1 in malignant cells (SPP1m) and CD44 in T cells (CD44t) is moderately negatively correlated with T cell proliferation score. Immunosuppressive cytokine TGFβ-3 identified as an inducer of CD44 and was significantly negatively correlated with proliferation score (R = - 0.88, P < 0.01), and the negative correlation was aggravated in samples with high CD44 expression.

CONCLUSION

SPP1 is a prognostic marker of ICC and is associated with the genome heterogeneity. SPP1-CD44 hinders sustained proliferation of T cells, but immunosuppressive T cells in the tumor microenvironment may evade this inhibition by reducing CD44 expression.

A Four-Gene Signature Associated with Radioresistance in Head and Neck Squamous Cell Carcinoma Identified by Text Mining and Data Analysis

Purpose

Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer globally, and radiotherapy plays a crucial part in its treatment. This study was designed to identify potential genes related to radiation resistance in HNSCC.

Method

We first used text mining to obtain common genes related to radiotherapy resistance and HNSCC in published articles. Functional enrichment analyses were conducted to identify the significantly enriched pathways and genes. Protein and protein interactions were performed, and the most significant gene modules were determined; then, genes in the gene modules were validated at transcriptional levels and overall survival. Gene set variation analysis (GSVA) score was calculated, and the association between GSVA score and survival/pathway was estimated. Immune cell infiltration, methylation, and genetic alteration analysis of these genes was conducted in HNSCC patients. Finally, potential sensitive anticancer drugs related to target genes were obtained.

Result

We identified 583 common genes through text mining. After further validation, a four-gene signature (EPHB2, SPP1, SERPINE1, and VEGFC) was constructed. The patients with higher GSVA scores have a worse prognosis than those with lower GSVA scores. Differences in methylation of these four genes in HNSCC tumor tissue and normal tissue were compared, with higher methylation levels of EBPH2 and SPP1 in normal tissue and higher methylation levels of SERPINE1 in the tumor. Immune cell infiltration revealed that the increased expression of these genes was closely related to the infiltration level of CD4+ T cell, neutrophil, macrophage, and dendritic cell. Thirty drugs, including 22 positively and eight negatively correlated drugs that most correlated with related genes, were available for treating HNSCC.

Conclusion

In this study, we identified four potential genes as well as corresponding drugs that might be related to radioresistance in HNSCC patients. These candidate genes may provide a promising avenue to further elevate radiotherapy efficacy.

Identification of Biomarkers Associated with Cancerous Change in Oral Leukoplakia Based on Integrated Transcriptome Analysis

Objective

Oral leukoplakia (OLK) is the most common precancerous lesion in the oral cavity. This study aimed to explore key biomarkers for monitoring OLK for early diagnosis of oral squamous cell carcinoma (OSCC) and screen small-molecule drugs for the prevention of OSCC.

Method

The Gene Expression Omnibus (GEO) database was explored to extract two microarray datasets, namely, GSE85195 and GSE25099. The data of the normal group, OLK group, and OSCC group were analyzed by weighted gene coexpression network analysis (WGCNA) to identify the most significant gene module and differentially expressed genes (DEGs). The intersection genes were extracted as the key genes of OLK carcinogenesis. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed in the module. Connectivity Map and molecular docking were used to screen small-molecule drugs. The diagnostic values of four key genes were identified and verified in the GSE26549 dataset.

Results

WGCNA obtained the red module (r = −0.91, p < 0.05) with the strongest correlation with cancerous phenotype. GO enrichment analysis showed 60 pathways, including 28 biological processes, 11 cell components, and 21 molecular functions, and KEGG enrichment analysis showed 4 pathways (p < 0.05). In the differential expression analysis, there was no intersection between the upregulated genes and the red module genes. However, the intersection of the downregulated genes and the red module genes yielded 4 key genes: dopachrome tautomerase (DCT), keratin 3 (KRT3), keratin 76 (KRT76), and FAM3 metabolic regulation signal molecule B (FAM3B). The area under the curve of the diagnostic model constructed by these four genes was 0.963 (CI = 0.913–1.000). The sensitivity was 0.933, and the specificity was 0.923. The diagnostic model was successfully verified in GSE26549 (AUC = 0.745, CI = 0.638–0.851). Compared with the diagnostic models of the previous studies, the diagnostic efficiency of this model was the highest. The small-molecule drugs, selumetinib and benidipine, were selected according to the gene expression profile and showed binding activity when docking with the above molecules.

Conclusions

This study provides new targets and drugs for OLK. These targets could be used as the key diagnostic molecules for long-term follow-up of OLK. The small-molecule drugs selumetinib and benidipine could be used for the prevention and treatment of OSCC.