Table_2_StTCP15 regulates potato tuber sprouting by modulating the dynamic balance between abscisic acid and gibberellic acid.DOCX

The major stages of the potato life cycle are tuber dormancy and sprouting, however, there is still known very little of the mechanisms that control these processes. TCP (Theosinte branch I, Cycloidea, proliferationcell factors 1 and 2) transcription factors play a key role in plant growth and dormancy related developmental processes. Previous researches demonstrated that TCP transcription factor StTCP15 had a function in the promotion of dormancy. To elucidate the function of StTCP15 gene, it was cloned from potato cultivar “Desiree,” which encodes a polypeptide consisting of 414 amino acids and is mainly found in the nucleus. The potato tubers of StTCP15 overexpression lines sprouted in advance, while the potato tubers of StTCP15 down-regulated expression lines showed delayed sprouting. In addition, it was also found that overexpression lines of StTCP15 extremely significantly reduced the ratio of abscisic acid (ABA)/gibberellic acid (GA3), while the superoxide dismutase activity decreased, and the activity of peroxidase and catalase increased compared with the wild type. The opposite result was found in the down-regulated expression lines of StTCP15 gene. Three interacting proteins, StSnRK1, StF-Box and StGID1, were screened by Yeast two-hybrid, and verified by Bimolecular Fluorescence Complementation and Split-luciferase, indicating that StTCP15 could affect ABA and GA3 signaling pathways to regulate potato tuber dormancy and sprouting. Together, these results demonstrated that StTCP15 regulated potato tuber dormancy and sprouting by affecting the dynamic balance between ABA and GA3. The result could provide some information on the molecular mechanism of StTCP15 regulating potato tuber dormancy and sprouting.</p

Data_Sheet_1_StTCP15 regulates potato tuber sprouting by modulating the dynamic balance between abscisic acid and gibberellic acid.docx

The major stages of the potato life cycle are tuber dormancy and sprouting, however, there is still known very little of the mechanisms that control these processes. TCP (Theosinte branch I, Cycloidea, proliferationcell factors 1 and 2) transcription factors play a key role in plant growth and dormancy related developmental processes. Previous researches demonstrated that TCP transcription factor StTCP15 had a function in the promotion of dormancy. To elucidate the function of StTCP15 gene, it was cloned from potato cultivar “Desiree,” which encodes a polypeptide consisting of 414 amino acids and is mainly found in the nucleus. The potato tubers of StTCP15 overexpression lines sprouted in advance, while the potato tubers of StTCP15 down-regulated expression lines showed delayed sprouting. In addition, it was also found that overexpression lines of StTCP15 extremely significantly reduced the ratio of abscisic acid (ABA)/gibberellic acid (GA3), while the superoxide dismutase activity decreased, and the activity of peroxidase and catalase increased compared with the wild type. The opposite result was found in the down-regulated expression lines of StTCP15 gene. Three interacting proteins, StSnRK1, StF-Box and StGID1, were screened by Yeast two-hybrid, and verified by Bimolecular Fluorescence Complementation and Split-luciferase, indicating that StTCP15 could affect ABA and GA3 signaling pathways to regulate potato tuber dormancy and sprouting. Together, these results demonstrated that StTCP15 regulated potato tuber dormancy and sprouting by affecting the dynamic balance between ABA and GA3. The result could provide some information on the molecular mechanism of StTCP15 regulating potato tuber dormancy and sprouting.</p

Image_1_Prognostic prediction and immune infiltration analysis based on ferroptosis and EMT state in hepatocellular carcinoma.tif

BackgroundFerroptosis is one of the main mechanisms of sorafenib against hepatocellular carcinoma (HCC). Epithelial-mesenchymal transition (EMT) plays an important role in the heterogeneity, tumor metastasis, immunosuppressive microenvironment, and drug resistance of HCC. However, there are few studies looking into the relationship between ferroptosis and EMT and how they may affect the prognosis of HCC collectively.MethodsWe downloaded gene expression and clinical data of HCC patients from the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases for prognostic model construction and validation respectively. The Least absolute shrinkage and selection operator (LASSO) Cox regression was used for model construction. The predictive ability of the model was assessed by Kaplan–Meier survival analysis and receiver operating characteristic (ROC) curve. We performed the expression profiles analysis to evaluate the ferroptosis and EMT state. CIBERSORT and single-sample Gene Set Enrichment Analysis (ssGSEA) methods were used for immune infiltration analysis.ResultsA total of thirteen crucial genes were identified for ferroptosis-related and EMT-related prognostic model (FEPM) stratifying patients into two risk groups. The high-FEPM group had shorter overall survivals than the low-FEPM group (p1, pConclusionIn conclusion, we developed a ferroptosis-related and EMT-related prognostic model, which could help predict overall survival for HCC patients. It might provide a new idea for predicting the response to targeted therapies and immunotherapies in HCC patients.</p

Table_5_Prognostic prediction and immune infiltration analysis based on ferroptosis and EMT state in hepatocellular carcinoma.docx

BackgroundFerroptosis is one of the main mechanisms of sorafenib against hepatocellular carcinoma (HCC). Epithelial-mesenchymal transition (EMT) plays an important role in the heterogeneity, tumor metastasis, immunosuppressive microenvironment, and drug resistance of HCC. However, there are few studies looking into the relationship between ferroptosis and EMT and how they may affect the prognosis of HCC collectively.MethodsWe downloaded gene expression and clinical data of HCC patients from the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases for prognostic model construction and validation respectively. The Least absolute shrinkage and selection operator (LASSO) Cox regression was used for model construction. The predictive ability of the model was assessed by Kaplan–Meier survival analysis and receiver operating characteristic (ROC) curve. We performed the expression profiles analysis to evaluate the ferroptosis and EMT state. CIBERSORT and single-sample Gene Set Enrichment Analysis (ssGSEA) methods were used for immune infiltration analysis.ResultsA total of thirteen crucial genes were identified for ferroptosis-related and EMT-related prognostic model (FEPM) stratifying patients into two risk groups. The high-FEPM group had shorter overall survivals than the low-FEPM group (p1, pConclusionIn conclusion, we developed a ferroptosis-related and EMT-related prognostic model, which could help predict overall survival for HCC patients. It might provide a new idea for predicting the response to targeted therapies and immunotherapies in HCC patients.</p

Table_2_Prognostic prediction and immune infiltration analysis based on ferroptosis and EMT state in hepatocellular carcinoma.docx

BackgroundFerroptosis is one of the main mechanisms of sorafenib against hepatocellular carcinoma (HCC). Epithelial-mesenchymal transition (EMT) plays an important role in the heterogeneity, tumor metastasis, immunosuppressive microenvironment, and drug resistance of HCC. However, there are few studies looking into the relationship between ferroptosis and EMT and how they may affect the prognosis of HCC collectively.MethodsWe downloaded gene expression and clinical data of HCC patients from the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases for prognostic model construction and validation respectively. The Least absolute shrinkage and selection operator (LASSO) Cox regression was used for model construction. The predictive ability of the model was assessed by Kaplan–Meier survival analysis and receiver operating characteristic (ROC) curve. We performed the expression profiles analysis to evaluate the ferroptosis and EMT state. CIBERSORT and single-sample Gene Set Enrichment Analysis (ssGSEA) methods were used for immune infiltration analysis.ResultsA total of thirteen crucial genes were identified for ferroptosis-related and EMT-related prognostic model (FEPM) stratifying patients into two risk groups. The high-FEPM group had shorter overall survivals than the low-FEPM group (p1, pConclusionIn conclusion, we developed a ferroptosis-related and EMT-related prognostic model, which could help predict overall survival for HCC patients. It might provide a new idea for predicting the response to targeted therapies and immunotherapies in HCC patients.</p

Table_4_Prognostic prediction and immune infiltration analysis based on ferroptosis and EMT state in hepatocellular carcinoma.docx

BackgroundFerroptosis is one of the main mechanisms of sorafenib against hepatocellular carcinoma (HCC). Epithelial-mesenchymal transition (EMT) plays an important role in the heterogeneity, tumor metastasis, immunosuppressive microenvironment, and drug resistance of HCC. However, there are few studies looking into the relationship between ferroptosis and EMT and how they may affect the prognosis of HCC collectively.MethodsWe downloaded gene expression and clinical data of HCC patients from the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases for prognostic model construction and validation respectively. The Least absolute shrinkage and selection operator (LASSO) Cox regression was used for model construction. The predictive ability of the model was assessed by Kaplan–Meier survival analysis and receiver operating characteristic (ROC) curve. We performed the expression profiles analysis to evaluate the ferroptosis and EMT state. CIBERSORT and single-sample Gene Set Enrichment Analysis (ssGSEA) methods were used for immune infiltration analysis.ResultsA total of thirteen crucial genes were identified for ferroptosis-related and EMT-related prognostic model (FEPM) stratifying patients into two risk groups. The high-FEPM group had shorter overall survivals than the low-FEPM group (p1, pConclusionIn conclusion, we developed a ferroptosis-related and EMT-related prognostic model, which could help predict overall survival for HCC patients. It might provide a new idea for predicting the response to targeted therapies and immunotherapies in HCC patients.</p

Table_3_Prognostic prediction and immune infiltration analysis based on ferroptosis and EMT state in hepatocellular carcinoma.docx

BackgroundFerroptosis is one of the main mechanisms of sorafenib against hepatocellular carcinoma (HCC). Epithelial-mesenchymal transition (EMT) plays an important role in the heterogeneity, tumor metastasis, immunosuppressive microenvironment, and drug resistance of HCC. However, there are few studies looking into the relationship between ferroptosis and EMT and how they may affect the prognosis of HCC collectively.MethodsWe downloaded gene expression and clinical data of HCC patients from the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases for prognostic model construction and validation respectively. The Least absolute shrinkage and selection operator (LASSO) Cox regression was used for model construction. The predictive ability of the model was assessed by Kaplan–Meier survival analysis and receiver operating characteristic (ROC) curve. We performed the expression profiles analysis to evaluate the ferroptosis and EMT state. CIBERSORT and single-sample Gene Set Enrichment Analysis (ssGSEA) methods were used for immune infiltration analysis.ResultsA total of thirteen crucial genes were identified for ferroptosis-related and EMT-related prognostic model (FEPM) stratifying patients into two risk groups. The high-FEPM group had shorter overall survivals than the low-FEPM group (p1, pConclusionIn conclusion, we developed a ferroptosis-related and EMT-related prognostic model, which could help predict overall survival for HCC patients. It might provide a new idea for predicting the response to targeted therapies and immunotherapies in HCC patients.</p

Table_1_Prognostic prediction and immune infiltration analysis based on ferroptosis and EMT state in hepatocellular carcinoma.docx

BackgroundFerroptosis is one of the main mechanisms of sorafenib against hepatocellular carcinoma (HCC). Epithelial-mesenchymal transition (EMT) plays an important role in the heterogeneity, tumor metastasis, immunosuppressive microenvironment, and drug resistance of HCC. However, there are few studies looking into the relationship between ferroptosis and EMT and how they may affect the prognosis of HCC collectively.MethodsWe downloaded gene expression and clinical data of HCC patients from the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases for prognostic model construction and validation respectively. The Least absolute shrinkage and selection operator (LASSO) Cox regression was used for model construction. The predictive ability of the model was assessed by Kaplan–Meier survival analysis and receiver operating characteristic (ROC) curve. We performed the expression profiles analysis to evaluate the ferroptosis and EMT state. CIBERSORT and single-sample Gene Set Enrichment Analysis (ssGSEA) methods were used for immune infiltration analysis.ResultsA total of thirteen crucial genes were identified for ferroptosis-related and EMT-related prognostic model (FEPM) stratifying patients into two risk groups. The high-FEPM group had shorter overall survivals than the low-FEPM group (p1, pConclusionIn conclusion, we developed a ferroptosis-related and EMT-related prognostic model, which could help predict overall survival for HCC patients. It might provide a new idea for predicting the response to targeted therapies and immunotherapies in HCC patients.</p