Tumor progression is closely related to tumor tissue metabolism and reshaping of the microenvironment. Oral squamous cell carcinoma (OSCC), a representative hypoxic tumor, has a heterogeneous internal metabolic environment. To clarify the relationship between different metabolic regions and the tumor immune microenvironment (TME) in OSCC, Single cell (SC) and spatial transcriptomics (ST) sequencing of OSCC tissues were performed. The proportion of TME in the ST data was obtained through SPOTlight deconvolution using SC and GSE103322 data. The metabolic activity of each spot was calculated using scMetabolism, and k-means clustering was used to classify all spots into hyper-, normal-, or hypometabolic regions. CD4T cell infiltration and TGF-β expression is higher in the hypermetabolic regions than in the others. Through CellPhoneDB and NicheNet cell-cell communication analysis, it was found that in the hypermetabolic region, fibroblasts can utilize the lactate produced by glycolysis of epithelial cells to transform into inflammatory cancer-associated fibroblasts (iCAFs), and the increased expression of HIF1A in iCAFs promotes the transcriptional expression of CXCL12. The secretion of CXCL12 recruits regulatory T cells (Tregs), leading to Treg infiltration and increased TGF-β secretion in the microenvironment and promotes the formation of a tumor immunosuppressive microenvironment. This study delineates the coordinate work axis of epithelial cells-iCAFs-Tregs in OSCC using SC, ST and TCGA bulk data, and highlights potential targets for therapy.
Humans ; Carcinoma, Squamous Cell/metabolism* ; Squamous Cell Carcinoma of Head and Neck ; Mouth Neoplasms/metabolism* ; Immunosuppression Therapy ; Transforming Growth Factor beta ; Head and Neck Neoplasms ; Gene Expression Profiling ; Tumor Microenvironment

Objective:To explore the relationship between the expressions of P21,P27 and proliferating cell nuclear antigen(PCNA)in glomerular mesangial tissue and poor renal prognosis in patients with immunoglobulin A(IgA)nephropathy.Methods:A total of 145 patients with IgA nephropathy treated in Xiaogan Central Hospital from April 2017 to August 2019 were selected as the research object.The expressions of P21,P27 and PCNA in glomerular mesangial tissue were detected by immunohistochemistry.All patients were followed up for 24 months,and the prognosis were counted.The expressions of P21,P27 and PCNA in glomerular mesangial tissue of patients with different prognosis were compared and the influencing factors of poor prognosis in patients with IgA nephropathy were analyzed by Logistic regression analysis.Results:The expression rates of P21,P27 and PCNA positive cells in glomerular mesangial tissue of patients with IgA nephropathy were(38.69±6.83)%,(55.94±8.08)%,(33.47±5.72)%,respectively.The incidence rete of poor prognosis in patients with IgA nephropathy was 17.24%,and the expression rates of P21 and PCNA positive cells in glomerular mesangial tissue of patients with poor prognosis were higher than those in good prognosis group(P<0.05),while the expression rate of P27 positive cells was lower than that in good prognosis group(P<0.05).Logistic multiple regression analysis showed that elevated diastolic blood pressure,increased 24 h proteinuria,mesangial cell proliferation,segmental glomerulosclerosis,renal tubular atrophy/interstitial fibrosis,crescentic body,increased expression rates of P21 and PCNA positive cells and decreased expression rate of P27 positive cells were all risk factors affecting the poor prognosis of patients with IgA nephropathy(P<0.05).Conclusion:There are positive expressions of P21,P27 and PCNA in glomerular mesangial tissue of IgA nephropathy.The expression rates of P21 and PCNA positive cells in glomerular mesangial tissue of of patients with poor prognosis of IgA nephropathy are higher than those with good prognosis,while the expression rate of P27 protein positive cells is lower than those with good prognosis,which are risk factors for poor prognosis of patients with IgA nephropathy.

Tumor progression is closely related to tumor tissue metabolism and reshaping of the microenvironment.Oral squamous cell carcinoma(OSCC),a representative hypoxic tumor,has a heterogeneous internal metabolic environment.To clarify the relationship between different metabolic regions and the tumor immune microenvironment(TME)in OSCC,Single cell(SC)and spatial transcriptomics(ST)sequencing of OSCC tissues were performed.The proportion of TME in the ST data was obtained through SPOTlight deconvolution using SC and GSE103322 data.The metabolic activity of each spot was calculated using scMetabolism,and k-means clustering was used to classify all spots into hyper-,normal-,or hypometabolic regions.CD4T cell infiltration and TGF-β expression is higher in the hypermetabolic regions than in the others.Through CellPhoneDB and NicheNet cell-cell communication analysis,it was found that in the hypermetabolic region,fibroblasts can utilize the lactate produced by glycolysis of epithelial cells to transform into inflammatory cancer-associated fibroblasts(iCAFs),and the increased expression of HIF1A in iCAFs promotes the transcriptional expression of CXCL12.The secretion of CXCL12 recruits regulatory T cells(Tregs),leading to Treg infiltration and increased TGF-β secretion in the microenvironment and promotes the formation of a tumor immunosuppressive microenvironment.This study delineates the coordinate work axis of epithelial cells-iCAFs-Tregs in OSCC using SC,ST and TCGA bulk data,and highlights potential targets for therapy.

Tumor progression is closely related to tumor tissue metabolism and reshaping of the microenvironment.Oral squamous cell carcinoma(OSCC),a representative hypoxic tumor,has a heterogeneous internal metabolic environment.To clarify the relationship between different metabolic regions and the tumor immune microenvironment(TME)in OSCC,Single cell(SC)and spatial transcriptomics(ST)sequencing of OSCC tissues were performed.The proportion of TME in the ST data was obtained through SPOTlight deconvolution using SC and GSE103322 data.The metabolic activity of each spot was calculated using scMetabolism,and k-means clustering was used to classify all spots into hyper-,normal-,or hypometabolic regions.CD4T cell infiltration and TGF-β expression is higher in the hypermetabolic regions than in the others.Through CellPhoneDB and NicheNet cell-cell communication analysis,it was found that in the hypermetabolic region,fibroblasts can utilize the lactate produced by glycolysis of epithelial cells to transform into inflammatory cancer-associated fibroblasts(iCAFs),and the increased expression of HIF1A in iCAFs promotes the transcriptional expression of CXCL12.The secretion of CXCL12 recruits regulatory T cells(Tregs),leading to Treg infiltration and increased TGF-β secretion in the microenvironment and promotes the formation of a tumor immunosuppressive microenvironment.This study delineates the coordinate work axis of epithelial cells-iCAFs-Tregs in OSCC using SC,ST and TCGA bulk data,and highlights potential targets for therapy.

Tumor progression is closely related to tumor tissue metabolism and reshaping of the microenvironment.Oral squamous cell carcinoma(OSCC),a representative hypoxic tumor,has a heterogeneous internal metabolic environment.To clarify the relationship between different metabolic regions and the tumor immune microenvironment(TME)in OSCC,Single cell(SC)and spatial transcriptomics(ST)sequencing of OSCC tissues were performed.The proportion of TME in the ST data was obtained through SPOTlight deconvolution using SC and GSE103322 data.The metabolic activity of each spot was calculated using scMetabolism,and k-means clustering was used to classify all spots into hyper-,normal-,or hypometabolic regions.CD4T cell infiltration and TGF-β expression is higher in the hypermetabolic regions than in the others.Through CellPhoneDB and NicheNet cell-cell communication analysis,it was found that in the hypermetabolic region,fibroblasts can utilize the lactate produced by glycolysis of epithelial cells to transform into inflammatory cancer-associated fibroblasts(iCAFs),and the increased expression of HIF1A in iCAFs promotes the transcriptional expression of CXCL12.The secretion of CXCL12 recruits regulatory T cells(Tregs),leading to Treg infiltration and increased TGF-β secretion in the microenvironment and promotes the formation of a tumor immunosuppressive microenvironment.This study delineates the coordinate work axis of epithelial cells-iCAFs-Tregs in OSCC using SC,ST and TCGA bulk data,and highlights potential targets for therapy.

Tumor progression is closely related to tumor tissue metabolism and reshaping of the microenvironment.Oral squamous cell carcinoma(OSCC),a representative hypoxic tumor,has a heterogeneous internal metabolic environment.To clarify the relationship between different metabolic regions and the tumor immune microenvironment(TME)in OSCC,Single cell(SC)and spatial transcriptomics(ST)sequencing of OSCC tissues were performed.The proportion of TME in the ST data was obtained through SPOTlight deconvolution using SC and GSE103322 data.The metabolic activity of each spot was calculated using scMetabolism,and k-means clustering was used to classify all spots into hyper-,normal-,or hypometabolic regions.CD4T cell infiltration and TGF-β expression is higher in the hypermetabolic regions than in the others.Through CellPhoneDB and NicheNet cell-cell communication analysis,it was found that in the hypermetabolic region,fibroblasts can utilize the lactate produced by glycolysis of epithelial cells to transform into inflammatory cancer-associated fibroblasts(iCAFs),and the increased expression of HIF1A in iCAFs promotes the transcriptional expression of CXCL12.The secretion of CXCL12 recruits regulatory T cells(Tregs),leading to Treg infiltration and increased TGF-β secretion in the microenvironment and promotes the formation of a tumor immunosuppressive microenvironment.This study delineates the coordinate work axis of epithelial cells-iCAFs-Tregs in OSCC using SC,ST and TCGA bulk data,and highlights potential targets for therapy.

Tumor progression is closely related to tumor tissue metabolism and reshaping of the microenvironment.Oral squamous cell carcinoma(OSCC),a representative hypoxic tumor,has a heterogeneous internal metabolic environment.To clarify the relationship between different metabolic regions and the tumor immune microenvironment(TME)in OSCC,Single cell(SC)and spatial transcriptomics(ST)sequencing of OSCC tissues were performed.The proportion of TME in the ST data was obtained through SPOTlight deconvolution using SC and GSE103322 data.The metabolic activity of each spot was calculated using scMetabolism,and k-means clustering was used to classify all spots into hyper-,normal-,or hypometabolic regions.CD4T cell infiltration and TGF-β expression is higher in the hypermetabolic regions than in the others.Through CellPhoneDB and NicheNet cell-cell communication analysis,it was found that in the hypermetabolic region,fibroblasts can utilize the lactate produced by glycolysis of epithelial cells to transform into inflammatory cancer-associated fibroblasts(iCAFs),and the increased expression of HIF1A in iCAFs promotes the transcriptional expression of CXCL12.The secretion of CXCL12 recruits regulatory T cells(Tregs),leading to Treg infiltration and increased TGF-β secretion in the microenvironment and promotes the formation of a tumor immunosuppressive microenvironment.This study delineates the coordinate work axis of epithelial cells-iCAFs-Tregs in OSCC using SC,ST and TCGA bulk data,and highlights potential targets for therapy.

Tumor progression is closely related to tumor tissue metabolism and reshaping of the microenvironment.Oral squamous cell carcinoma(OSCC),a representative hypoxic tumor,has a heterogeneous internal metabolic environment.To clarify the relationship between different metabolic regions and the tumor immune microenvironment(TME)in OSCC,Single cell(SC)and spatial transcriptomics(ST)sequencing of OSCC tissues were performed.The proportion of TME in the ST data was obtained through SPOTlight deconvolution using SC and GSE103322 data.The metabolic activity of each spot was calculated using scMetabolism,and k-means clustering was used to classify all spots into hyper-,normal-,or hypometabolic regions.CD4T cell infiltration and TGF-β expression is higher in the hypermetabolic regions than in the others.Through CellPhoneDB and NicheNet cell-cell communication analysis,it was found that in the hypermetabolic region,fibroblasts can utilize the lactate produced by glycolysis of epithelial cells to transform into inflammatory cancer-associated fibroblasts(iCAFs),and the increased expression of HIF1A in iCAFs promotes the transcriptional expression of CXCL12.The secretion of CXCL12 recruits regulatory T cells(Tregs),leading to Treg infiltration and increased TGF-β secretion in the microenvironment and promotes the formation of a tumor immunosuppressive microenvironment.This study delineates the coordinate work axis of epithelial cells-iCAFs-Tregs in OSCC using SC,ST and TCGA bulk data,and highlights potential targets for therapy.

Tumor progression is closely related to tumor tissue metabolism and reshaping of the microenvironment.Oral squamous cell carcinoma(OSCC),a representative hypoxic tumor,has a heterogeneous internal metabolic environment.To clarify the relationship between different metabolic regions and the tumor immune microenvironment(TME)in OSCC,Single cell(SC)and spatial transcriptomics(ST)sequencing of OSCC tissues were performed.The proportion of TME in the ST data was obtained through SPOTlight deconvolution using SC and GSE103322 data.The metabolic activity of each spot was calculated using scMetabolism,and k-means clustering was used to classify all spots into hyper-,normal-,or hypometabolic regions.CD4T cell infiltration and TGF-β expression is higher in the hypermetabolic regions than in the others.Through CellPhoneDB and NicheNet cell-cell communication analysis,it was found that in the hypermetabolic region,fibroblasts can utilize the lactate produced by glycolysis of epithelial cells to transform into inflammatory cancer-associated fibroblasts(iCAFs),and the increased expression of HIF1A in iCAFs promotes the transcriptional expression of CXCL12.The secretion of CXCL12 recruits regulatory T cells(Tregs),leading to Treg infiltration and increased TGF-β secretion in the microenvironment and promotes the formation of a tumor immunosuppressive microenvironment.This study delineates the coordinate work axis of epithelial cells-iCAFs-Tregs in OSCC using SC,ST and TCGA bulk data,and highlights potential targets for therapy.

Tumor progression is closely related to tumor tissue metabolism and reshaping of the microenvironment.Oral squamous cell carcinoma(OSCC),a representative hypoxic tumor,has a heterogeneous internal metabolic environment.To clarify the relationship between different metabolic regions and the tumor immune microenvironment(TME)in OSCC,Single cell(SC)and spatial transcriptomics(ST)sequencing of OSCC tissues were performed.The proportion of TME in the ST data was obtained through SPOTlight deconvolution using SC and GSE103322 data.The metabolic activity of each spot was calculated using scMetabolism,and k-means clustering was used to classify all spots into hyper-,normal-,or hypometabolic regions.CD4T cell infiltration and TGF-β expression is higher in the hypermetabolic regions than in the others.Through CellPhoneDB and NicheNet cell-cell communication analysis,it was found that in the hypermetabolic region,fibroblasts can utilize the lactate produced by glycolysis of epithelial cells to transform into inflammatory cancer-associated fibroblasts(iCAFs),and the increased expression of HIF1A in iCAFs promotes the transcriptional expression of CXCL12.The secretion of CXCL12 recruits regulatory T cells(Tregs),leading to Treg infiltration and increased TGF-β secretion in the microenvironment and promotes the formation of a tumor immunosuppressive microenvironment.This study delineates the coordinate work axis of epithelial cells-iCAFs-Tregs in OSCC using SC,ST and TCGA bulk data,and highlights potential targets for therapy.