22 research outputs found
The role of PI3K/AKT pathway in miR-27a induced apoptosis.
<p>(A) Western blot analysis of total PI3KCD, p-AKT, NF-κB, Bcl-2 and cleaved caspase 3 protein levels inhuman NP cells with up-regulation and knockdown of miR-27a. (B) Quantification of band intensity in (A). Results are shown as mean ± SEM. Data are representative of three independent experiments (*P<0.05 vs control).</p
Image3_Identification of molecular subtypes and diagnostic model in clear cell renal cell carcinoma based on collagen-related genes may predict the response of immunotherapy.tif
Background: Collagen represents a prominent constituent of the tumor’s extracellular matrix (ECM). Nonetheless, its correlation with the molecular subtype attributes of clear cell renal cell carcinoma (ccRCC) remains elusive. Our objective is to delineate collagen-associated molecular subtypes and further construct diagnostic model, offering insights conducive to the precise selection of ccRCC patients for immunotherapeutic interventions.Methods: We performed unsupervised non-negative matrix factorization (NMF) analysis on TCGA-KIRC samples, utilizing a set of 33 collagen-related differentially expressed genes (33CRDs) for clustering. Our analysis encompassed evaluations of subtype-associated differences in pathways, immune profiles, and somatic mutations. Through weighted gene co-expression network analysis (WGCNA) and four machine learning algorithms, two core genes were found and a diagnostic model was constructed. This was subsequently validated in a clinical immunotherapy cohort. Single cell sequencing analysis and experiments demonstrated the role of core genes in ccRCC. Finally, we also analyzed the roles of MMP9 and SCGN in pan-cancer.Results: We described two novel collagen related molecular subtypes in ccRCC, designated subtype 1 and subtype 2. Compared with subtype 1, subtype 2 showed more infiltration of immune components, but had a higher TIDE (tumor immunedysfunctionandexclusion) score and increased levels of immune checkpoint molecules. Furthermore, reduced prognosis for subtype 2 was a consistent finding in both high and low mutation load subgroups. MMP9 and SCGN were identified as key genes for distinguishing subtype 1 and subtype 2. The diagnostic model based on them could better distinguish the subtype of patients, and the differentiated patients had different progression free survival (PFS) in the clinical immunotherapy cohort. MMP9 was predominantly expressed in macrophages and has been extensively documented in the literature. Meanwhile, SCGN, which was overexpressed in tumor cells, underwent experimental validation, emphasizing its role in ccRCC. In various cancers, MMP9 and SCGN were associated with immune-related molecules and immune cells.Conclusion: Our study identifies two collagen-related molecular subtypes of ccRCC and constructs a diagnostic model to help select appropriate patients for immunotherapy.</p
Overexpression of miR-27a in nucleus pulposus cells, and its function in the regulation of target proteins
<p>(A) Comparison of cell proliferation in various NP cell groups (*P<0.05). Data are representative of three experiments; error bars represent SEM. (B) Increased expression of cleaved caspase 3 and decreased expression of PIK3CD in the group overexpressing miR-27a compared to the control group (magnification ×200), respectively. Black arrows indicate positive-stained cells. (C) Contour diagram of FITC-Annexin V/PI FCM of human NP cells. The graphs represent typical results of cellular apoptosis; values represent the means of three experiments. Error bars represent SEM. (D) Results of cellular apoptosis was expressed as a fold change. Results are shown as mean ± SEM. Data are representative of three independent experiments (*P<0.05, ***P<0.001). (E) Increased numbers of nucleus pulposus cells were observed to undergo apoptosis in the group overexpressing miR-27a compared to the control group (magnification ×200). (F) (G) After 36 h, cellular protein lysates were prepared and PIK3CD expression was assessed by Western blot. GAPDH was used as an internal loading standard. Results are shown as mean ± SEM. Data are representative of three independent experiments (*P<0.05, **P<0.01).</p
MiR-27a can inhibit PIK3CD by targeting the 3’-UTRs of PIK3CD.
<p>(A) Complementarity between miR-27a and the putative PIK3CD 3’-UTR target site. PIK3CD 3’-mut indicates the PIK3CD 3’-UTRs with three mutation sites (underlined) in miR-27a binding sites. (B) The relative luciferase activities of three independent experiments are shown. Error bars represent SEM; (**P<0.01).</p
The expression levels of miR-27a were analyzed in human degenerative NP compared with control NP by real-time RT-PCR.
<p>The relative expression of miR-27a was normalized to the endogenous control U6. Each sample was analyzed in triplicate (**<i>P</i> <0.01, ***<i>P</i><0.001). (A) miR-27a is up-regulated in damaged NP <i>in </i><i>vitro</i>. (B) miR-27a is up-regulated in damaged NP cells <i>in </i><i>vivo</i>. Data are representative of six independent experiments. Error bars represent SEM; *<i>P</i><0.05.</p
Apoptosis was increased in the injury model.
<p>(A) Assessment of cell viability by MTT. The cell viability was compared in the different NP cell groups (∗P <0.05). Data are representative of three experiments; error bars represent SEM. (B) Contour diagram of FITC-Annexin V/PI FCM of human NP cells. The graphs represent typical results of cell apoptosis; values represent the means of two experiments. (C) Results of cellular apoptosis was expressed as a fold change. Results are shown as mean ± SEM. Data are representative of three independent experiments (*P<0.05, **P<0.01).</p
Image5_Identification of molecular subtypes and diagnostic model in clear cell renal cell carcinoma based on collagen-related genes may predict the response of immunotherapy.tif
Background: Collagen represents a prominent constituent of the tumor’s extracellular matrix (ECM). Nonetheless, its correlation with the molecular subtype attributes of clear cell renal cell carcinoma (ccRCC) remains elusive. Our objective is to delineate collagen-associated molecular subtypes and further construct diagnostic model, offering insights conducive to the precise selection of ccRCC patients for immunotherapeutic interventions.Methods: We performed unsupervised non-negative matrix factorization (NMF) analysis on TCGA-KIRC samples, utilizing a set of 33 collagen-related differentially expressed genes (33CRDs) for clustering. Our analysis encompassed evaluations of subtype-associated differences in pathways, immune profiles, and somatic mutations. Through weighted gene co-expression network analysis (WGCNA) and four machine learning algorithms, two core genes were found and a diagnostic model was constructed. This was subsequently validated in a clinical immunotherapy cohort. Single cell sequencing analysis and experiments demonstrated the role of core genes in ccRCC. Finally, we also analyzed the roles of MMP9 and SCGN in pan-cancer.Results: We described two novel collagen related molecular subtypes in ccRCC, designated subtype 1 and subtype 2. Compared with subtype 1, subtype 2 showed more infiltration of immune components, but had a higher TIDE (tumor immunedysfunctionandexclusion) score and increased levels of immune checkpoint molecules. Furthermore, reduced prognosis for subtype 2 was a consistent finding in both high and low mutation load subgroups. MMP9 and SCGN were identified as key genes for distinguishing subtype 1 and subtype 2. The diagnostic model based on them could better distinguish the subtype of patients, and the differentiated patients had different progression free survival (PFS) in the clinical immunotherapy cohort. MMP9 was predominantly expressed in macrophages and has been extensively documented in the literature. Meanwhile, SCGN, which was overexpressed in tumor cells, underwent experimental validation, emphasizing its role in ccRCC. In various cancers, MMP9 and SCGN were associated with immune-related molecules and immune cells.Conclusion: Our study identifies two collagen-related molecular subtypes of ccRCC and constructs a diagnostic model to help select appropriate patients for immunotherapy.</p
DataSheet4_Identification of molecular subtypes and diagnostic model in clear cell renal cell carcinoma based on collagen-related genes may predict the response of immunotherapy.zip
Background: Collagen represents a prominent constituent of the tumor’s extracellular matrix (ECM). Nonetheless, its correlation with the molecular subtype attributes of clear cell renal cell carcinoma (ccRCC) remains elusive. Our objective is to delineate collagen-associated molecular subtypes and further construct diagnostic model, offering insights conducive to the precise selection of ccRCC patients for immunotherapeutic interventions.Methods: We performed unsupervised non-negative matrix factorization (NMF) analysis on TCGA-KIRC samples, utilizing a set of 33 collagen-related differentially expressed genes (33CRDs) for clustering. Our analysis encompassed evaluations of subtype-associated differences in pathways, immune profiles, and somatic mutations. Through weighted gene co-expression network analysis (WGCNA) and four machine learning algorithms, two core genes were found and a diagnostic model was constructed. This was subsequently validated in a clinical immunotherapy cohort. Single cell sequencing analysis and experiments demonstrated the role of core genes in ccRCC. Finally, we also analyzed the roles of MMP9 and SCGN in pan-cancer.Results: We described two novel collagen related molecular subtypes in ccRCC, designated subtype 1 and subtype 2. Compared with subtype 1, subtype 2 showed more infiltration of immune components, but had a higher TIDE (tumor immunedysfunctionandexclusion) score and increased levels of immune checkpoint molecules. Furthermore, reduced prognosis for subtype 2 was a consistent finding in both high and low mutation load subgroups. MMP9 and SCGN were identified as key genes for distinguishing subtype 1 and subtype 2. The diagnostic model based on them could better distinguish the subtype of patients, and the differentiated patients had different progression free survival (PFS) in the clinical immunotherapy cohort. MMP9 was predominantly expressed in macrophages and has been extensively documented in the literature. Meanwhile, SCGN, which was overexpressed in tumor cells, underwent experimental validation, emphasizing its role in ccRCC. In various cancers, MMP9 and SCGN were associated with immune-related molecules and immune cells.Conclusion: Our study identifies two collagen-related molecular subtypes of ccRCC and constructs a diagnostic model to help select appropriate patients for immunotherapy.</p
Image8_Identification of molecular subtypes and diagnostic model in clear cell renal cell carcinoma based on collagen-related genes may predict the response of immunotherapy.png
Background: Collagen represents a prominent constituent of the tumor’s extracellular matrix (ECM). Nonetheless, its correlation with the molecular subtype attributes of clear cell renal cell carcinoma (ccRCC) remains elusive. Our objective is to delineate collagen-associated molecular subtypes and further construct diagnostic model, offering insights conducive to the precise selection of ccRCC patients for immunotherapeutic interventions.Methods: We performed unsupervised non-negative matrix factorization (NMF) analysis on TCGA-KIRC samples, utilizing a set of 33 collagen-related differentially expressed genes (33CRDs) for clustering. Our analysis encompassed evaluations of subtype-associated differences in pathways, immune profiles, and somatic mutations. Through weighted gene co-expression network analysis (WGCNA) and four machine learning algorithms, two core genes were found and a diagnostic model was constructed. This was subsequently validated in a clinical immunotherapy cohort. Single cell sequencing analysis and experiments demonstrated the role of core genes in ccRCC. Finally, we also analyzed the roles of MMP9 and SCGN in pan-cancer.Results: We described two novel collagen related molecular subtypes in ccRCC, designated subtype 1 and subtype 2. Compared with subtype 1, subtype 2 showed more infiltration of immune components, but had a higher TIDE (tumor immunedysfunctionandexclusion) score and increased levels of immune checkpoint molecules. Furthermore, reduced prognosis for subtype 2 was a consistent finding in both high and low mutation load subgroups. MMP9 and SCGN were identified as key genes for distinguishing subtype 1 and subtype 2. The diagnostic model based on them could better distinguish the subtype of patients, and the differentiated patients had different progression free survival (PFS) in the clinical immunotherapy cohort. MMP9 was predominantly expressed in macrophages and has been extensively documented in the literature. Meanwhile, SCGN, which was overexpressed in tumor cells, underwent experimental validation, emphasizing its role in ccRCC. In various cancers, MMP9 and SCGN were associated with immune-related molecules and immune cells.Conclusion: Our study identifies two collagen-related molecular subtypes of ccRCC and constructs a diagnostic model to help select appropriate patients for immunotherapy.</p
Image10_Identification of molecular subtypes and diagnostic model in clear cell renal cell carcinoma based on collagen-related genes may predict the response of immunotherapy.tif
Background: Collagen represents a prominent constituent of the tumor’s extracellular matrix (ECM). Nonetheless, its correlation with the molecular subtype attributes of clear cell renal cell carcinoma (ccRCC) remains elusive. Our objective is to delineate collagen-associated molecular subtypes and further construct diagnostic model, offering insights conducive to the precise selection of ccRCC patients for immunotherapeutic interventions.Methods: We performed unsupervised non-negative matrix factorization (NMF) analysis on TCGA-KIRC samples, utilizing a set of 33 collagen-related differentially expressed genes (33CRDs) for clustering. Our analysis encompassed evaluations of subtype-associated differences in pathways, immune profiles, and somatic mutations. Through weighted gene co-expression network analysis (WGCNA) and four machine learning algorithms, two core genes were found and a diagnostic model was constructed. This was subsequently validated in a clinical immunotherapy cohort. Single cell sequencing analysis and experiments demonstrated the role of core genes in ccRCC. Finally, we also analyzed the roles of MMP9 and SCGN in pan-cancer.Results: We described two novel collagen related molecular subtypes in ccRCC, designated subtype 1 and subtype 2. Compared with subtype 1, subtype 2 showed more infiltration of immune components, but had a higher TIDE (tumor immunedysfunctionandexclusion) score and increased levels of immune checkpoint molecules. Furthermore, reduced prognosis for subtype 2 was a consistent finding in both high and low mutation load subgroups. MMP9 and SCGN were identified as key genes for distinguishing subtype 1 and subtype 2. The diagnostic model based on them could better distinguish the subtype of patients, and the differentiated patients had different progression free survival (PFS) in the clinical immunotherapy cohort. MMP9 was predominantly expressed in macrophages and has been extensively documented in the literature. Meanwhile, SCGN, which was overexpressed in tumor cells, underwent experimental validation, emphasizing its role in ccRCC. In various cancers, MMP9 and SCGN were associated with immune-related molecules and immune cells.Conclusion: Our study identifies two collagen-related molecular subtypes of ccRCC and constructs a diagnostic model to help select appropriate patients for immunotherapy.</p