Additional file 3 of Development of a novel immune-related lncRNA prognostic signature for patients with hepatocellular carcinoma

Additional file 3: Supplementary Figure 1. (A) The best-fit OS-related lncRNAs were chosen by Lasso regression analysis. (B) The Lasso regression was performed with the optimal value of λ. (C-D) Distribution of risk scores, survival status. Supplementary Figure 2. (A-D) PCA among all genes, immune genes, immune LncRNA, and risk immune LncRNA

DataSheet1_Identification and Validation of a Novel Tumor Microenvironment-Related Prognostic Signature of Patients With Hepatocellular Carcinoma.ZIP

Background: In recent years, immunotherapy has changed the therapeutic landscape of hepatocellular carcinoma (HCC). Since the efficacy of immunotherapy is closely related to the tumor microenvironment (TME), in this study, we constructed a prognostic model based on TME to predict the prognosis and immunotherapy effect of HCC patients.Methods: Transcriptome and follow-up data of 374 HCC patients were acquired from the TCGA Cancer Genome Atlas (TCGA) database. The immune/stromal/estimate scores (TME scores) and tumor purity were calculated using the ESTIMATE algorithm and the module most associated with TME scores were screened by the weighted gene co-expression network analysis (WGCNA). A TME score-related prognostic model was constructed and patients were divided into a high-risk group and a low-risk group. Kaplan-Meier survival curves and receiver operator characteristic curve (ROC) were used to evaluate the performance of the TME risk prognostic model and validated with the external database International Cancer Genome Consortium (ICGC) cohort. Combined with clinicopathologic factors, a prognostic nomogram was established. The nomogram’s ability to predict prognosis was assessed by ROC, calibration curve, and the decision curve analysis (DCA). Gene Set Enrichment Analyses (GSEA) were conducted to explore the underlying biological functions and pathways of this risk signature. Moreover, the possible correlation of risk signature with TME immune cell infiltration, immune checkpoint inhibitor (ICI) treatment response, single-nucleotide polymorphisms (SNPs), and drug sensitivity were assessed. Finally, real-time PCR was used to verify the gene expression levels in normal liver cells and cancer cells.Results: KM survival analysis results indicated that high immune/stromal/estimate score groups were closely associated with a better prognosis, while the tumor purity showed a reverse trend (p Conclusion: It provided a theoretical basis for predicting the prognosis and personalized treatment of patients with HCC.</p

Image2_Identification and Validation of a Novel Tumor Microenvironment-Related Prognostic Signature of Patients With Hepatocellular Carcinoma.TIF

Background: In recent years, immunotherapy has changed the therapeutic landscape of hepatocellular carcinoma (HCC). Since the efficacy of immunotherapy is closely related to the tumor microenvironment (TME), in this study, we constructed a prognostic model based on TME to predict the prognosis and immunotherapy effect of HCC patients.Methods: Transcriptome and follow-up data of 374 HCC patients were acquired from the TCGA Cancer Genome Atlas (TCGA) database. The immune/stromal/estimate scores (TME scores) and tumor purity were calculated using the ESTIMATE algorithm and the module most associated with TME scores were screened by the weighted gene co-expression network analysis (WGCNA). A TME score-related prognostic model was constructed and patients were divided into a high-risk group and a low-risk group. Kaplan-Meier survival curves and receiver operator characteristic curve (ROC) were used to evaluate the performance of the TME risk prognostic model and validated with the external database International Cancer Genome Consortium (ICGC) cohort. Combined with clinicopathologic factors, a prognostic nomogram was established. The nomogram’s ability to predict prognosis was assessed by ROC, calibration curve, and the decision curve analysis (DCA). Gene Set Enrichment Analyses (GSEA) were conducted to explore the underlying biological functions and pathways of this risk signature. Moreover, the possible correlation of risk signature with TME immune cell infiltration, immune checkpoint inhibitor (ICI) treatment response, single-nucleotide polymorphisms (SNPs), and drug sensitivity were assessed. Finally, real-time PCR was used to verify the gene expression levels in normal liver cells and cancer cells.Results: KM survival analysis results indicated that high immune/stromal/estimate score groups were closely associated with a better prognosis, while the tumor purity showed a reverse trend (p Conclusion: It provided a theoretical basis for predicting the prognosis and personalized treatment of patients with HCC.</p

Additional file 4 of Development of a novel immune-related lncRNA prognostic signature for patients with hepatocellular carcinoma

Additional file 4: Supplementary Table 3. All the primer sequences

Additional file 1 of Development of a novel immune-related lncRNA prognostic signature for patients with hepatocellular carcinoma

Additional file 1: Table 1. Clinical characteristics of hepatocellular carcinoma in train and validation cohort

Image1_Identification and Validation of a Novel Tumor Microenvironment-Related Prognostic Signature of Patients With Hepatocellular Carcinoma.TIF

Background: In recent years, immunotherapy has changed the therapeutic landscape of hepatocellular carcinoma (HCC). Since the efficacy of immunotherapy is closely related to the tumor microenvironment (TME), in this study, we constructed a prognostic model based on TME to predict the prognosis and immunotherapy effect of HCC patients.Methods: Transcriptome and follow-up data of 374 HCC patients were acquired from the TCGA Cancer Genome Atlas (TCGA) database. The immune/stromal/estimate scores (TME scores) and tumor purity were calculated using the ESTIMATE algorithm and the module most associated with TME scores were screened by the weighted gene co-expression network analysis (WGCNA). A TME score-related prognostic model was constructed and patients were divided into a high-risk group and a low-risk group. Kaplan-Meier survival curves and receiver operator characteristic curve (ROC) were used to evaluate the performance of the TME risk prognostic model and validated with the external database International Cancer Genome Consortium (ICGC) cohort. Combined with clinicopathologic factors, a prognostic nomogram was established. The nomogram’s ability to predict prognosis was assessed by ROC, calibration curve, and the decision curve analysis (DCA). Gene Set Enrichment Analyses (GSEA) were conducted to explore the underlying biological functions and pathways of this risk signature. Moreover, the possible correlation of risk signature with TME immune cell infiltration, immune checkpoint inhibitor (ICI) treatment response, single-nucleotide polymorphisms (SNPs), and drug sensitivity were assessed. Finally, real-time PCR was used to verify the gene expression levels in normal liver cells and cancer cells.Results: KM survival analysis results indicated that high immune/stromal/estimate score groups were closely associated with a better prognosis, while the tumor purity showed a reverse trend (p Conclusion: It provided a theoretical basis for predicting the prognosis and personalized treatment of patients with HCC.</p

Additional file 2 of Development of a novel immune-related lncRNA prognostic signature for patients with hepatocellular carcinoma

Additional file 2: Supplementary Table 2. 76 prognostic associated lncRNAs

Table_3_Identification of MTHFD2 as a prognostic biomarker and ferroptosis regulator in triple-negative breast cancer.docx

BackgroundMethylenetetrahydrofolate dehydrogenase 2 (MTHFD2) is a mitochondrial bifunctional enzyme encoded in the nucleus. It plays a significant role in the regulation of glucose, nucleic acid, and folate metabolism, and maintains redox balance in the cells. The present study aimed at elucidating the potential function and mechanisms of MTHFD2 and explored the correlation between ferroptosis and MTHFD2 in triple-negative breast cancer.MethodsMTHFD2 expression, survival analysis, and clinical correlation were performed using data from various online databases including TCGA, GEO, HPA, GTEX, Kaplan–Meier Plotter, PrognoScan, and UALCAN databases. Genomic alterations and CNV analysis were performed using the cBioPortal and GSCA databases. Potential functions and mechanisms were explored by enrichment analysis. The tumor microenvironment was identified by the TIMER database. In vitro, RT-qPCR and western blot assays were utilized to identify the MTHFD2 expression and the knockdown effects in breast cancer. CCK8, cell wound healing, transwell, and flow cytometry assays were used to identify the potential function of MTHFD2 in TNBC cells. MDA, GSH detection, and flow cytometry assays were performed to identify ferroptosis. Western blot assays were performed to measure the protein expression of all target genes.ResultsMTHFD2 expression levels were up-regulated in the majority of cancers and particularly in TNBC, in which higher expression levels indicated a poorer prognosis. Enrichment analyses showed that MTHFD2 is involved in various tumor-related biological processes. MTHFD2 expression was found to strongly correlate with multiple immune cell infiltration. In vitro, the knockdown of MTHFD2 suppresses the proliferation, apoptosis, migration, and invasion in TNBC cells. In addition, the MTHFD2 knockdown significantly enhanced intracellular ROS and lipid peroxidation and decreased intracellular GSH. The expressions of SLC7A11, GPX4, and NRF2 were down-regulated by the MTHFD2 knockdown.ConclusionMTHFD2 could be a crucial molecular biomarker for predicting patient prognosis and a novel therapeutic target in TNBC. In addition, MTHFD2 is a potential ferroptosis regulatory gene in TNBC.</p

Table_1_Identification of MTHFD2 as a prognostic biomarker and ferroptosis regulator in triple-negative breast cancer.docx

BackgroundMethylenetetrahydrofolate dehydrogenase 2 (MTHFD2) is a mitochondrial bifunctional enzyme encoded in the nucleus. It plays a significant role in the regulation of glucose, nucleic acid, and folate metabolism, and maintains redox balance in the cells. The present study aimed at elucidating the potential function and mechanisms of MTHFD2 and explored the correlation between ferroptosis and MTHFD2 in triple-negative breast cancer.MethodsMTHFD2 expression, survival analysis, and clinical correlation were performed using data from various online databases including TCGA, GEO, HPA, GTEX, Kaplan–Meier Plotter, PrognoScan, and UALCAN databases. Genomic alterations and CNV analysis were performed using the cBioPortal and GSCA databases. Potential functions and mechanisms were explored by enrichment analysis. The tumor microenvironment was identified by the TIMER database. In vitro, RT-qPCR and western blot assays were utilized to identify the MTHFD2 expression and the knockdown effects in breast cancer. CCK8, cell wound healing, transwell, and flow cytometry assays were used to identify the potential function of MTHFD2 in TNBC cells. MDA, GSH detection, and flow cytometry assays were performed to identify ferroptosis. Western blot assays were performed to measure the protein expression of all target genes.ResultsMTHFD2 expression levels were up-regulated in the majority of cancers and particularly in TNBC, in which higher expression levels indicated a poorer prognosis. Enrichment analyses showed that MTHFD2 is involved in various tumor-related biological processes. MTHFD2 expression was found to strongly correlate with multiple immune cell infiltration. In vitro, the knockdown of MTHFD2 suppresses the proliferation, apoptosis, migration, and invasion in TNBC cells. In addition, the MTHFD2 knockdown significantly enhanced intracellular ROS and lipid peroxidation and decreased intracellular GSH. The expressions of SLC7A11, GPX4, and NRF2 were down-regulated by the MTHFD2 knockdown.ConclusionMTHFD2 could be a crucial molecular biomarker for predicting patient prognosis and a novel therapeutic target in TNBC. In addition, MTHFD2 is a potential ferroptosis regulatory gene in TNBC.</p

Table_2_Identification of MTHFD2 as a prognostic biomarker and ferroptosis regulator in triple-negative breast cancer.docx

BackgroundMethylenetetrahydrofolate dehydrogenase 2 (MTHFD2) is a mitochondrial bifunctional enzyme encoded in the nucleus. It plays a significant role in the regulation of glucose, nucleic acid, and folate metabolism, and maintains redox balance in the cells. The present study aimed at elucidating the potential function and mechanisms of MTHFD2 and explored the correlation between ferroptosis and MTHFD2 in triple-negative breast cancer.MethodsMTHFD2 expression, survival analysis, and clinical correlation were performed using data from various online databases including TCGA, GEO, HPA, GTEX, Kaplan–Meier Plotter, PrognoScan, and UALCAN databases. Genomic alterations and CNV analysis were performed using the cBioPortal and GSCA databases. Potential functions and mechanisms were explored by enrichment analysis. The tumor microenvironment was identified by the TIMER database. In vitro, RT-qPCR and western blot assays were utilized to identify the MTHFD2 expression and the knockdown effects in breast cancer. CCK8, cell wound healing, transwell, and flow cytometry assays were used to identify the potential function of MTHFD2 in TNBC cells. MDA, GSH detection, and flow cytometry assays were performed to identify ferroptosis. Western blot assays were performed to measure the protein expression of all target genes.ResultsMTHFD2 expression levels were up-regulated in the majority of cancers and particularly in TNBC, in which higher expression levels indicated a poorer prognosis. Enrichment analyses showed that MTHFD2 is involved in various tumor-related biological processes. MTHFD2 expression was found to strongly correlate with multiple immune cell infiltration. In vitro, the knockdown of MTHFD2 suppresses the proliferation, apoptosis, migration, and invasion in TNBC cells. In addition, the MTHFD2 knockdown significantly enhanced intracellular ROS and lipid peroxidation and decreased intracellular GSH. The expressions of SLC7A11, GPX4, and NRF2 were down-regulated by the MTHFD2 knockdown.ConclusionMTHFD2 could be a crucial molecular biomarker for predicting patient prognosis and a novel therapeutic target in TNBC. In addition, MTHFD2 is a potential ferroptosis regulatory gene in TNBC.</p