Table_1_Relationships Between Cardinal Features of Obstructive Sleep Apnea and Blood Pressure: A Retrospective Study.DOC

BackgroundObstructive sleep apnea (OSA) is associated with hypertension; however, the associations between cardinal features of OSA, such as intermittent hypoxia (IH) and sleep fragmentation (SF), and blood pressure remain unclear. We performed this study to address this issue.MethodWe investigated 335 subjects with the polysomnography (PSG) tests. Data, including basic characteristics, PSG parameters, and blood pressure, were collected. We calculated p-values for linear trends of blood pressure across oxygen-desaturation index (ODI)/microarousal index (MAI) quartiles. Logistic regressions were used to determine the risk factors for abnormal blood pressure and to detect the multiplicative interaction between ODI and MAI with blood pressure.ResultsAfter adjusting for multiple variables, compared with subjects with lower ODI quartiles, those with higher ODI quartiles had significant higher systolic blood pressure (SBP) and diastolic blood pressure (DBP) (p for trend = 0.010 and 0.018, respectively). And compared with subjects with lower ODI quartiles, those with higher ODI quartiles were also more likely to have abnormal DBP and hypertension after adjusting for multiple variables. Similarly, compared with subjects with lower MAI quartiles, those with higher MAI quartiles had significant higher SBP and DBP, and were more likely to have abnormal DBP and hypertension. No significant multiplicative interactions between ODI and MAI with blood pressure were detected.ConclusionSubjects with more severe IH/SF had significant higher blood pressure and were more likely to have abnormal DBP and hypertension than those with less severe IH/SF. No interaction between IH and SF on the relationship with blood pressure was shown.</p

MOESM4 of Simultaneously inactivating Src and AKT by saracatinib/capivasertib co-delivery nanoparticles to improve the efficacy of anti-Src therapy in head and neck squamous cell carcinoma

Additional file 4: Figure S4. The average weight of tongue and body in HN8- (A) and HN12-derived orthotopic xenograft mice (B) during different treatments. *p<0.05; **p<0.01

Image6_Prognostic Analysis of Differentially Expressed DNA Damage Repair Genes in Bladder Cancer.TIF

Bladder cancer (BCa) is the tenth most common tumor in humans. DNA damage repair genes (DDRGs) play important roles in many malignant tumors; thus, their functions in BCa should also be explored. We performed a comprehensive analysis of the expression profiles of DDRGs in 410 BCa tumors and 19 normal tissues from The Cancer Genome Atlas database. We identified 123 DDRGs differentially expressed between BCa tumors and normal tissues, including 95 upregulated and 28 downregulated genes. We detected 22 DDRGs associated with overall survival (OS) of patients with BCa by performing univariate Cox regression analysis. To explore the interactions between OS-associated DDRGs, we constructed a PPI network, which showed that the top six DDRGs (CDCA2, FOXM1, PBK, RRM2, ORC1, and HDAC4) with the highest scores in the PPI network might play significant roles in OS of BCa. Moreover, to investigate the latent regulatory mechanism of these OS-associated DDRGs, we analyzed the transcription factors (TFs)-DDRGs regulatory network. The core seven TFs (NCAPG, DNMT1, LMNB1, BRCA1, E2H2, CENPA, and E2F7) were shown to be critical regulators of the OS-related DDRGs. The 22 DDRGs were incorporated into a stepwise multivariable Cox analysis. Then, we built the index of risk score based on the expression of 8 DDRGs (CAD, HDAC10, JDP2, LDLR, PDGFRA, POLA2, SREBF1, and STAT1). The p-value < 0.0001 in the Kaplan–Meier survival plot and an area under the ROC curve (AUC) of 0.771 in TCGA-BLCA training dataset suggested the high specificity and sensitivity of the prognostic index. Furthermore, we validated the risk score in the internal TCGA-BLCA and an independent GSE32894 dataset, with AUC of 0.743 and 0.827, respectively. More importantly, the multivariate Cox regression and stratification analysis demonstrated that the predictor was independent of various clinical parameters, including age, tumor stage, grade, and number of positive tumor lymph nodes. In summary, a panel of 8 DNA damage repair genes associated with overall survival in bladder cancer may be a useful prognostic tool.</p

MOESM3 of Simultaneously inactivating Src and AKT by saracatinib/capivasertib co-delivery nanoparticles to improve the efficacy of anti-Src therapy in head and neck squamous cell carcinoma

Additional file 3: Figure S3. The effect of indicated treatment on other Src-related proteins (including STAT3, FAK and EGFR) in HNSCC cells

Image2_Novel Immune-Related Ferroptosis Signature in Esophageal Cancer: An Informatics Exploration of Biological Processes Related to the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 Regulatory Network.JPEG

Background: Considering the role of immunity and ferroptosis in the invasion, proliferation and treatment of cancer, it is of interest to construct a model of prognostic-related differential expressed immune-related ferroptosis genes (PR-DE-IRFeGs), and explore the ferroptosis-related biological processes in esophageal cancer (ESCA).Methods: Four ESCA datasets were used to identify three PR-DE-IRFeGs for constructing the prognostic model. Validation of our model was based on analyses of internal and external data sets, and comparisons with past models. With the biological-based enrichment analysis as a guide, exploration for ESCA-related biological processes was undertaken with respect to the immune microenvironment, mutations, competing endogenous RNAs (ceRNA), and copy number variation (CNV). The model’s clinical applicability was measured by nomogram and correlation analysis between risk score and gene expression, and also immune-based and chemotherapeutic sensitivity.Results: Three PR-DE-IRFeGs (DDIT3, SLC2A3, and GCH1), risk factors for prognosis of ESCA patients, were the basis for constructing the prognostic model. Validation of our model shows a meaningful capability for prognosis prediction. Furthermore, many biological functions and pathways related to immunity and ferroptosis were enriched in the high-risk group, and the role of the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 network in ESCA is supported. Also, the KMT2D mutation is associated with our risk score and SLC2A3 expression. Overall, the prognostic model was associated with treatment sensitivity and levels of gene expression.Conclusion: A novel, prognostic model was shown to have high predictive value. Biological processes related to immune functions, KMT2D mutation, CNV and the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 network were involved in ESCA progression.</p

Image8_Prognostic Analysis of Differentially Expressed DNA Damage Repair Genes in Bladder Cancer.TIF

Bladder cancer (BCa) is the tenth most common tumor in humans. DNA damage repair genes (DDRGs) play important roles in many malignant tumors; thus, their functions in BCa should also be explored. We performed a comprehensive analysis of the expression profiles of DDRGs in 410 BCa tumors and 19 normal tissues from The Cancer Genome Atlas database. We identified 123 DDRGs differentially expressed between BCa tumors and normal tissues, including 95 upregulated and 28 downregulated genes. We detected 22 DDRGs associated with overall survival (OS) of patients with BCa by performing univariate Cox regression analysis. To explore the interactions between OS-associated DDRGs, we constructed a PPI network, which showed that the top six DDRGs (CDCA2, FOXM1, PBK, RRM2, ORC1, and HDAC4) with the highest scores in the PPI network might play significant roles in OS of BCa. Moreover, to investigate the latent regulatory mechanism of these OS-associated DDRGs, we analyzed the transcription factors (TFs)-DDRGs regulatory network. The core seven TFs (NCAPG, DNMT1, LMNB1, BRCA1, E2H2, CENPA, and E2F7) were shown to be critical regulators of the OS-related DDRGs. The 22 DDRGs were incorporated into a stepwise multivariable Cox analysis. Then, we built the index of risk score based on the expression of 8 DDRGs (CAD, HDAC10, JDP2, LDLR, PDGFRA, POLA2, SREBF1, and STAT1). The p-value < 0.0001 in the Kaplan–Meier survival plot and an area under the ROC curve (AUC) of 0.771 in TCGA-BLCA training dataset suggested the high specificity and sensitivity of the prognostic index. Furthermore, we validated the risk score in the internal TCGA-BLCA and an independent GSE32894 dataset, with AUC of 0.743 and 0.827, respectively. More importantly, the multivariate Cox regression and stratification analysis demonstrated that the predictor was independent of various clinical parameters, including age, tumor stage, grade, and number of positive tumor lymph nodes. In summary, a panel of 8 DNA damage repair genes associated with overall survival in bladder cancer may be a useful prognostic tool.</p

Image5_Novel Immune-Related Ferroptosis Signature in Esophageal Cancer: An Informatics Exploration of Biological Processes Related to the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 Regulatory Network.JPEG

Background: Considering the role of immunity and ferroptosis in the invasion, proliferation and treatment of cancer, it is of interest to construct a model of prognostic-related differential expressed immune-related ferroptosis genes (PR-DE-IRFeGs), and explore the ferroptosis-related biological processes in esophageal cancer (ESCA).Methods: Four ESCA datasets were used to identify three PR-DE-IRFeGs for constructing the prognostic model. Validation of our model was based on analyses of internal and external data sets, and comparisons with past models. With the biological-based enrichment analysis as a guide, exploration for ESCA-related biological processes was undertaken with respect to the immune microenvironment, mutations, competing endogenous RNAs (ceRNA), and copy number variation (CNV). The model’s clinical applicability was measured by nomogram and correlation analysis between risk score and gene expression, and also immune-based and chemotherapeutic sensitivity.Results: Three PR-DE-IRFeGs (DDIT3, SLC2A3, and GCH1), risk factors for prognosis of ESCA patients, were the basis for constructing the prognostic model. Validation of our model shows a meaningful capability for prognosis prediction. Furthermore, many biological functions and pathways related to immunity and ferroptosis were enriched in the high-risk group, and the role of the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 network in ESCA is supported. Also, the KMT2D mutation is associated with our risk score and SLC2A3 expression. Overall, the prognostic model was associated with treatment sensitivity and levels of gene expression.Conclusion: A novel, prognostic model was shown to have high predictive value. Biological processes related to immune functions, KMT2D mutation, CNV and the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 network were involved in ESCA progression.</p

Image10_Novel Immune-Related Ferroptosis Signature in Esophageal Cancer: An Informatics Exploration of Biological Processes Related to the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 Regulatory Network.JPEG

Background: Considering the role of immunity and ferroptosis in the invasion, proliferation and treatment of cancer, it is of interest to construct a model of prognostic-related differential expressed immune-related ferroptosis genes (PR-DE-IRFeGs), and explore the ferroptosis-related biological processes in esophageal cancer (ESCA).Methods: Four ESCA datasets were used to identify three PR-DE-IRFeGs for constructing the prognostic model. Validation of our model was based on analyses of internal and external data sets, and comparisons with past models. With the biological-based enrichment analysis as a guide, exploration for ESCA-related biological processes was undertaken with respect to the immune microenvironment, mutations, competing endogenous RNAs (ceRNA), and copy number variation (CNV). The model’s clinical applicability was measured by nomogram and correlation analysis between risk score and gene expression, and also immune-based and chemotherapeutic sensitivity.Results: Three PR-DE-IRFeGs (DDIT3, SLC2A3, and GCH1), risk factors for prognosis of ESCA patients, were the basis for constructing the prognostic model. Validation of our model shows a meaningful capability for prognosis prediction. Furthermore, many biological functions and pathways related to immunity and ferroptosis were enriched in the high-risk group, and the role of the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 network in ESCA is supported. Also, the KMT2D mutation is associated with our risk score and SLC2A3 expression. Overall, the prognostic model was associated with treatment sensitivity and levels of gene expression.Conclusion: A novel, prognostic model was shown to have high predictive value. Biological processes related to immune functions, KMT2D mutation, CNV and the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 network were involved in ESCA progression.</p

Image9_Novel Immune-Related Ferroptosis Signature in Esophageal Cancer: An Informatics Exploration of Biological Processes Related to the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 Regulatory Network.JPEG

Background: Considering the role of immunity and ferroptosis in the invasion, proliferation and treatment of cancer, it is of interest to construct a model of prognostic-related differential expressed immune-related ferroptosis genes (PR-DE-IRFeGs), and explore the ferroptosis-related biological processes in esophageal cancer (ESCA).Methods: Four ESCA datasets were used to identify three PR-DE-IRFeGs for constructing the prognostic model. Validation of our model was based on analyses of internal and external data sets, and comparisons with past models. With the biological-based enrichment analysis as a guide, exploration for ESCA-related biological processes was undertaken with respect to the immune microenvironment, mutations, competing endogenous RNAs (ceRNA), and copy number variation (CNV). The model’s clinical applicability was measured by nomogram and correlation analysis between risk score and gene expression, and also immune-based and chemotherapeutic sensitivity.Results: Three PR-DE-IRFeGs (DDIT3, SLC2A3, and GCH1), risk factors for prognosis of ESCA patients, were the basis for constructing the prognostic model. Validation of our model shows a meaningful capability for prognosis prediction. Furthermore, many biological functions and pathways related to immunity and ferroptosis were enriched in the high-risk group, and the role of the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 network in ESCA is supported. Also, the KMT2D mutation is associated with our risk score and SLC2A3 expression. Overall, the prognostic model was associated with treatment sensitivity and levels of gene expression.Conclusion: A novel, prognostic model was shown to have high predictive value. Biological processes related to immune functions, KMT2D mutation, CNV and the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 network were involved in ESCA progression.</p

Image4_Novel Immune-Related Ferroptosis Signature in Esophageal Cancer: An Informatics Exploration of Biological Processes Related to the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 Regulatory Network.JPEG

Background: Considering the role of immunity and ferroptosis in the invasion, proliferation and treatment of cancer, it is of interest to construct a model of prognostic-related differential expressed immune-related ferroptosis genes (PR-DE-IRFeGs), and explore the ferroptosis-related biological processes in esophageal cancer (ESCA).Methods: Four ESCA datasets were used to identify three PR-DE-IRFeGs for constructing the prognostic model. Validation of our model was based on analyses of internal and external data sets, and comparisons with past models. With the biological-based enrichment analysis as a guide, exploration for ESCA-related biological processes was undertaken with respect to the immune microenvironment, mutations, competing endogenous RNAs (ceRNA), and copy number variation (CNV). The model’s clinical applicability was measured by nomogram and correlation analysis between risk score and gene expression, and also immune-based and chemotherapeutic sensitivity.Results: Three PR-DE-IRFeGs (DDIT3, SLC2A3, and GCH1), risk factors for prognosis of ESCA patients, were the basis for constructing the prognostic model. Validation of our model shows a meaningful capability for prognosis prediction. Furthermore, many biological functions and pathways related to immunity and ferroptosis were enriched in the high-risk group, and the role of the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 network in ESCA is supported. Also, the KMT2D mutation is associated with our risk score and SLC2A3 expression. Overall, the prognostic model was associated with treatment sensitivity and levels of gene expression.Conclusion: A novel, prognostic model was shown to have high predictive value. Biological processes related to immune functions, KMT2D mutation, CNV and the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 network were involved in ESCA progression.</p