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Background: Angiogenesis is associated with tumour growth, infiltration, and metastasis. This study aimed to detect the mechanisms of angiogenesis-related genes (ARGs) in multiple myeloma (MM) and to construct a new prognostic model. Methods: MM research foundation (MMRF)-CoMMpass cohort, GSE47552, GSE57317, and ARGs were sourced from public databases. Differentially expressed genes (DEGs) in the tumour and control cohorts in GSE47552 were determined through differential expression analysis and were enriched with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Weighted gene coexpression network analysis (WGCNA) was applied to derive modules linked to the ARG scores and obtain module genes in GSE47552. Differentially expressed ARGs (DE-ARGs) were selected for subsequent analyses by overlapping DEGs and module genes. Furthermore, prognostic genes were selected using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. Depending on the prognostic genes, a risk model was constructed, and risk scores were determined. Moreover, MM samples from MMRF-CoMMpass were sorted into high- and low-risk teams on account of the median risk score. Additionally, correlations among clinical characteristics, gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), immune analysis, immunotherapy predictions and the mRNA‒miRNA‒lncRNA network were carried out. Results: A total of 898 DEGs, 211 module genes, 24 DE-ARGs and three prognostic genes (AKAP12, C11orf80 and EMP1) were selected for this study. Enrichment analysis revealed that the DEGs were related to 86 GO terms, such as 'cytoplasmic translation', and 41 KEGG pathways, such as 'small cell lung cancer'. A prognostic gene-based risk model was created in MMRF-CoMMpass and confirmed with the GSE57317 dataset. Moreover, a nomogram was established on the basis of independent prognostic factors that have proven to be good predictors. In addition, the immune cell infiltration results suggested that memory B cells were enriched in the high-risk group and that immature B cells were enriched in the low-risk group. Finally, the mRNA‒miRNA‒lncRNA network demonstrated that hsa-miR-508-5p was tightly associated with EMP1 and AKAP12. RT‒qPCR was used to validate the expression of the genes associated with prognosis. Conclusion: A new prognostic model of MM associated with ARGs was created and validated, providing a new perspective for exploring the connection between ARGs and MM. [ABSTRACT FROM AUTHOR]

Abstract Background Angiogenesis is associated with tumour growth, infiltration, and metastasis. This study aimed to detect the mechanisms of angiogenesis-related genes (ARGs) in multiple myeloma (MM) and to construct a new prognostic model. Methods MM research foundation (MMRF)-CoMMpass cohort, GSE47552, GSE57317, and ARGs were sourced from public databases. Differentially expressed genes (DEGs) in the tumour and control cohorts in GSE47552 were determined through differential expression analysis and were enriched with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Weighted gene coexpression network analysis (WGCNA) was applied to derive modules linked to the ARG scores and obtain module genes in GSE47552. Differentially expressed ARGs (DE-ARGs) were selected for subsequent analyses by overlapping DEGs and module genes. Furthermore, prognostic genes were selected using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. Depending on the prognostic genes, a risk model was constructed, and risk scores were determined. Moreover, MM samples from MMRF-CoMMpass were sorted into high- and low-risk teams on account of the median risk score. Additionally, correlations among clinical characteristics, gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), immune analysis, immunotherapy predictions and the mRNA‒miRNA‒lncRNA network were carried out. Results A total of 898 DEGs, 211 module genes, 24 DE-ARGs and three prognostic genes (AKAP12, C11orf80 and EMP1) were selected for this study. Enrichment analysis revealed that the DEGs were related to 86 GO terms, such as ‘cytoplasmic translation’, and 41 KEGG pathways, such as ‘small cell lung cancer’. A prognostic gene-based risk model was created in MMRF-CoMMpass and confirmed with the GSE57317 dataset. Moreover, a nomogram was established on the basis of independent prognostic factors that have proven to be good predictors. In addition, the immune cell infiltration results suggested that memory B cells were enriched in the high-risk group and that immature B cells were enriched in the low-risk group. Finally, the mRNA‒miRNA‒lncRNA network demonstrated that hsa-miR-508-5p was tightly associated with EMP1 and AKAP12. RT‒qPCR was used to validate the expression of the genes associated with prognosis. Conclusion A new prognostic model of MM associated with ARGs was created and validated, providing a new perspective for exploring the connection between ARGs and MM.

Diffuse large B cell lymphoma (DLBCL) is a highly heterogeneous disease with varying therapeutic responses and prognoses. Angiogenesis is a crucial factor in lymphoma growth and progression, but no scoring model based on angiogenesis-related genes (ARGs) has been developed for prognostic evaluation of DLBCL patients. In this study, we used univariate Cox regression to identify prognostic ARGs and found two distinct clusters of DLBCL patients in the GSE10846 dataset based on the expression of these prognostic ARGs. These two clusters had different prognoses and immune cell infiltration. Using LASSO regression analysis, we constructed a novel seven-ARG-based scoring model in GSE10846 dataset, and it was further validated in the GSE87371 dataset. The DLBCL patients were divided into high- and low-score groups based on the median risk score as a cut-off. The high-score group had a worse prognosis and showed higher expression of immune checkpoints, M2 macrophages, myeloid-derived suppressor cells, and regulatory T cells, indicating a stronger immunosuppressive environment. DLBCL patients in high-score group were resistant to doxorubicin and cisplatin, which are components of frequently used chemotherapy regimens, but more sensitive to gemcitabine and temozolomide. Using RT-qPCR, we found that two candidate risk genes, RAPGEF2 and PTGER2, were over-expressed in DLBCL tissues compared with control tissues. Taken together, the ARG-based scoring model provides a promising direction for the prognosis and immune status of DLBCL patients, and benefits the development of personalized treatment for DLBCL patients. [ABSTRACT FROM AUTHOR]

Lung adenocarcinoma (LUAD) is an essential pathological subtype of non-small cell lung cancer and offers a severe problem for worldwide public health. There is mounting proof that angiogenesis is a crucial player in LUAD progression. Consequently, the purpose of this research was to construct a novel LUAD risk assessment model based on genetic markers related to angiogenesis. We accessed The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases for LUAD mRNA sequencing data and clinical information. Based on machine algorithms and bioinformatics, angiogenic gene-related risk scores (RS) were calculated. Patients in the high-risk category had a worse prognosis (p < 0.001) in the discovery TCGA cohort, and the results were confirmed by these three cohorts (validation TCGA cohort, total TCGA cohort, and GSE68465 cohort). Moreover, risk scores for genes involved in angiogenesis were independent risk factors for lung cancer in all four cohorts. The low-risk group was associated with better immune status and lower tumor mutational load. In addition, the somatic mutation study revealed that the low-risk group had a lower mutation frequency than the high-risk group. According to an analysis of tumor stem cell infiltration, HLA expression, and TIDE scores, the low-risk group had higher TIDE scores and HLA expression levels than the high-risk group, and the amount of tumor stem cell infiltration correlated with the risk score. In addition, high-risk groups may benefit from immune checkpoint inhibitors and targeted therapies. In conclusion, we developed an angiogenesis-related gene risk model to predict the prognosis of LUAD patients, which may aid in the classification of patients with LUAD and select medications for LUAD patients.

Cervical cancer ranks first in female reproductive tract tumors in terms of morbidity and mortality. Yet the curative effect of patients with persistent, recurrent or metastatic cervical cancer remains unsatisfactory. Although antitumor angiogenic drugs have been recommended as the first-line treatment options for cervical cancer, there are no comprehensive prognostic indicators for cervical cancer based on angiogenic signature genes. In this study, we aimed to develop a model to assess the prognosis of cervical cancer based on angiogenesis-related (AG) signature genes, and to provide some reference for the comprehensive treatment of cervical cancer in the clinical setting. First we screened the AG gene set from GeneCard website, and then performed angiogenesis-related scores (AGS) per cell from single cell sequencing dataset GSE168652, followed by performing weighted gene co-expression network analysis (WGCNA) for cervical cancer patients according to angiogenesis phenotype. Thus, we established a prognostic model based on AGS by taking the intersection of WGCNA angiogenic module gene and differential gene (DEGs) of GSE168652. The GSE44001 was selected as an external validation set, followed by performing ROC curve analysis to assess its accuracy. The results showed that we successfully constructed a prognostic model related to the AG genes. Patients in the high-AGS group in both the train, test and the validation sets had a worse prognosis than those in the low-AGS group, had lower expression of most immune checkpoint-associated genes and lower tumor mutational burden as well. Patients in the low-AGS group were more sensitive to AMG.706, Bosutinib, and Lenalidomide while Imatinib, Pazopanib, and Sorafenib were more recommended to patients in the high-AGS group. Finally, TXNDC12 and ZC3H13, which have high hazard ratio and poor prognosis in the model, were highly expressed in cervical cancer cell lines and tissue. Meanwhile, the results showed that TXNDC12 promoted the migration of cervical cancer cells and the tubule-forming ability of endothelial cells. In conclusion, our model based on genes with AG features can effectively assess the prognosis of cervical cancer, and can also provide reference for clinicians to choose immune-related treatments.

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world with high morbidity and mortality. Identifying an effective marker for predicting the prognosis and therapeutic response is extremely meaningful. Angiogenesis-related genes (ARGs) play important roles in the tumor progression and immune-suppressive microenvironment formation. Methods: The differential expressed ARGs associated with the prognosis of HCC were identified in the TCGA dataset. Univariate Cox and least absolute shrinkage selection operator (LASSO) regression were applied to construct a ARGs Scoring model. The prognostic value of the ARGs Scoring model was assessed by Cox regression, Kaplan-Meier (KM) and ROC curve analyses. Then the model was further validated in an external dataset, ICGC dataset. The patients were split into two groups based on the ARGs Score and the clinical features were compared. TIMER, CIBERSORT and xCell algorithms were utilized to analyze the correlation between the ARGs Score and tumor immune microenvironment (TIME). Furthermore, we analyzed the efficacy of the model in predicting the therapeutic response for immunotherapy, targeted therapy and TACE treatment in different cohorts. Results: A total of 97 differential expressed ARGs were identified relating to the prognosis of HCC patients from the TCGA dataset. Then the ARGs Scoring model based on a 9-gene signature was constructed using the Cox and LASSO regression analyses. Higher ARGs Score had a poor clinical outcome and was considered to be an independent prognostic predictor for HCC in the multivariate Cox analysis. The ARGs Score was related to the enrichment of various immune cells, such as CD4+ T cells, Treg, macrophage, neutrophil and dendritic cells, exhibiting a more immunosuppressive phenotype. Higher ARGs Score was correlated with higher expression of immune checkpoint genes and poor response to immunotherapy. Furthermore, higher ARGs Score indicated poor therapeutic response in the sorafenib and TACE treatment cohorts, individually. Conclusions: The ARGs Scoring model exhibited robust predictive value for the prognosis and TIME for HCC patients. Higher ARGs Score indicated poor therapeutic response of the immunotherapy, sorafenib and TACE treatment. The ARGs Scoring model could be used as a biomarker to help physicians to develop more individualized treatment for HCC patients. [ABSTRACT FROM AUTHOR]

Hashimoto's thyroiditis (HT) can cause angiogenesis in the thyroid gland. However, the molecular mechanism of endothelial cells and angiogenesis related genes (ARGs) has not been extensively studied in HT. The HRA001684, GSE29315 and GSE163203 datasets were included in this study. Using single-cell analysis, weighted gene co-expression network analysis (WGCNA), functional enrichment analysis, machine learning algorithms and expression analysis for exploration. And receiver operator characteristic (ROC) curves was draw. Gene set enrichment analysis (GSEA) was utilized to investigate the biological function of the biomarkers. Meanwhile, we investigated into the relationship between biomarkers and different types of immune cells. Additionally, the expression of biomarkers in the TCGA-TC dataset was examined and the mRNA-drug interaction network was constructed. We found 14 cell subtypes were obtained in HT samples after single-cell analysis. A total of 5 biomarkers (CD52, CD74, CD79A, HLA-B and RGS1) were derived, and they had excellent diagnostic performance. Then, 27 drugs targeting biomarkers were predicted. The expression analysis showed that CD74 and HLA-B were significantly up-regulated in HT samples. In this study, 5 biomarkers (CD52, CD74, CD79A, HLA-B and RGS1) were screened and their expressions in endothelial cells was compared to offer a new reference for the recognition and management of HT. [Display omitted] • We identified 14 cell subtypes in Hashimoto's thyroiditis (HT) samples through single-cell analysis. • We identified a set of 5 biomarkers (CD52, CD74, CD79A, HLA-B, and RGS1) and predicted 27 drugs targeting these biomarkers. • Our expression analysis revealed significant up-regulation of CD74 and HLA-B in HT samples giving a new insights into the diagnosis and treatment of HT. [ABSTRACT FROM AUTHOR]

Background: The function of angiogenesis-related genes (ARGs) in lung adenocarcinoma (LUAD) remains poorly documented. This study was designed to reveal ARGs in LUAD and related networks. Methods: We worked with sequencing data and clinical information pertaining to LUAD from public databases. ARGs were retrieved from the HALLMARK_ANGIOGENESIS gene set. Differential analysis and Kaplan–Meier (K–M) analysis were performed to authenticate the ARGs associated with LUAD. Weighted gene correlation network analysis was performed on the mining hub genes linked to the abovementioned genes, and functional enrichment analysis was done. Subsequently, Cox regression analyses were used to construct the prognostic gene. POSTN and microvessel density were detected using immunohistochemistry. Results: POSTN , an ARG that was highly expressed in patients with LUAD and was closely associated with their weak overall survival was identified. Differentially expressed genes associated with POSTN were mainly enriched in entries related to the tubulointerstitial system, immune response, and epithelial cells. A positive correlation was demonstrated between POSTN expression and tumor microvessel density in LUAD. Subsequently, a prognostic gene signature was constructed and revealed that 4 genes may predict the survival of LUAD patients. Furthermore, the ESTIMATE and CIBERSORT analyses suggested that our risk scoring system may be implicated in altering the immune microenvironment of patients with LUAD. Finally, a ceRNA network was constructed based on the prognostic genes, and the regulatory networks were examined. Conclusion: POSTN , a novel prognostic gene signature associated with ARGs, was constructed for the prognosis of patients with LUAD. This signature may alter the immune microenvironment by modulating the activation of the tubulointerstitial system, epithelial cells, and immune cells, ultimately affecting patient survival. [ABSTRACT FROM AUTHOR]

BackgroundThe function of angiogenesis-related genes (ARGs) in lung adenocarcinoma (LUAD) remains poorly documented. This study was designed to reveal ARGs in LUAD and related networks.MethodsWe worked with sequencing data and clinical information pertaining to LUAD from public databases. ARGs were retrieved from the HALLMARK_ANGIOGENESIS gene set. Differential analysis and Kaplan–Meier (K–M) analysis were performed to authenticate the ARGs associated with LUAD. Weighted gene correlation network analysis was performed on the mining hub genes linked to the abovementioned genes, and functional enrichment analysis was done. Subsequently, Cox regression analyses were used to construct the prognostic gene. POSTN and microvessel density were detected using immunohistochemistry.ResultsPOSTN, an ARG that was highly expressed in patients with LUAD and was closely associated with their weak overall survival was identified. Differentially expressed genes associated with POSTN were mainly enriched in entries related to the tubulointerstitial system, immune response, and epithelial cells. A positive correlation was demonstrated between POSTN expression and tumor microvessel density in LUAD. Subsequently, a prognostic gene signature was constructed and revealed that 4 genes may predict the survival of LUAD patients. Furthermore, the ESTIMATE and CIBERSORT analyses suggested that our risk scoring system may be implicated in altering the immune microenvironment of patients with LUAD. Finally, a ceRNA network was constructed based on the prognostic genes, and the regulatory networks were examined.ConclusionPOSTN, a novel prognostic gene signature associated with ARGs, was constructed for the prognosis of patients with LUAD. This signature may alter the immune microenvironment by modulating the activation of the tubulointerstitial system, epithelial cells, and immune cells, ultimately affecting patient survival.

In a view to explore blood vessels neo formation as a possible adaptive response to hypobaric hypoxia in the chicken lung, mRNA expression of the following genes was examined: hypoxia inducible factor-1α (HIF-1α) and -2α (HIF-2α), vascular endothelial growth factor (VEGF), receptors for VEGF (Flk-1 and Flt-1), hepatocyte growth factor (HGF) and its receptor (HGFR), epidermal growth factor (EGF) and its receptor (EGFR). The molecular regulation of these genes remains completely unknown in these conditions. One group of birds was exposed to relative normoxia and the other group, to hypobaric hypoxia. Comparisons were made among non-pulmonary hypertensive chickens under relative normoxic conditions (NHCN) and non-pulmonary hypertensive chickens (NHCH) and pulmonary hypertensive chickens (PHCH) under hypobaric hypoxic conditions, respectively. For HIF-2α, VEGF, Flk-1, HGF and HGFR genes, no statistical differences were found in the relative mRNA expression between PHCH and NHCH, but those were lower when compared to NHCN (P

Lung adenocarcinoma (LUAD) is an essential pathological subtype of non-small cell lung cancer and offers a severe problem for worldwide public health. There is mounting proof that angiogenesis is a crucial player in LUAD progression. Consequently, the purpose of this research was to construct a novel LUAD risk assessment model based on genetic markers related to angiogenesis. We accessed The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases for LUAD mRNA sequencing data and clinical information. Based on machine algorithms and bioinformatics, angiogenic gene-related risk scores (RS) were calculated. Patients in the high-risk category had a worse prognosis ( p < 0.001) in the discovery TCGA cohort, and the results were confirmed by these three cohorts (validation TCGA cohort, total TCGA cohort, and GSE68465 cohort). Moreover, risk scores for genes involved in angiogenesis were independent risk factors for lung cancer in all four cohorts. The low-risk group was associated with better immune status and lower tumor mutational load. In addition, the somatic mutation study revealed that the low-risk group had a lower mutation frequency than the high-risk group. According to an analysis of tumor stem cell infiltration, HLA expression, and TIDE scores, the low-risk group had higher TIDE scores and HLA expression levels than the high-risk group, and the amount of tumor stem cell infiltration correlated with the risk score. In addition, high-risk groups may benefit from immune checkpoint inhibitors and targeted therapies. In conclusion, we developed an angiogenesis-related gene risk model to predict the prognosis of LUAD patients, which may aid in the classification of patients with LUAD and select medications for LUAD patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Wang, Cui, Weng, Wei, Chen, Wang, Wang, Qin and Peng.)

Cervical cancer ranks first in female reproductive tract tumors in terms of morbidity and mortality. Yet the curative effect of patients with persistent, recurrent or metastatic cervical cancer remains unsatisfactory. Although antitumor angiogenic drugs have been recommended as the first-line treatment options for cervical cancer, there are no comprehensive prognostic indicators for cervical cancer based on angiogenic signature genes. In this study, we aimed to develop a model to assess the prognosis of cervical cancer based on angiogenesis-related (AG) signature genes, and to provide some reference for the comprehensive treatment of cervical cancer in the clinical setting. First we screened the AG gene set from GeneCard website, and then performed angiogenesis-related scores (AGS) per cell from single cell sequencing dataset GSE168652, followed by performing weighted gene co-expression network analysis (WGCNA) for cervical cancer patients according to angiogenesis phenotype. Thus, we established a prognostic model based on AGS by taking the intersection of WGCNA angiogenic module gene and differential gene (DEGs) of GSE168652. The GSE44001 was selected as an external validation set, followed by performing ROC curve analysis to assess its accuracy. The results showed that we successfully constructed a prognostic model related to the AG genes. Patients in the high-AGS group in both the train, test and the validation sets had a worse prognosis than those in the low-AGS group, had lower expression of most immune checkpoint-associated genes and lower tumor mutational burden as well. Patients in the low-AGS group were more sensitive to AMG.706, Bosutinib, and Lenalidomide while Imatinib, Pazopanib, and Sorafenib were more recommended to patients in the high-AGS group. Finally, TXNDC12 and ZC3H13 , which have high hazard ratio and poor prognosis in the model, were highly expressed in cervical cancer cell lines and tissue. Meanwhile, the results showed that TXNDC12 promoted the migration of cervical cancer cells and the tubule-forming ability of endothelial cells. In conclusion, our model based on genes with AG features can effectively assess the prognosis of cervical cancer, and can also provide reference for clinicians to choose immune-related treatments., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Kang, Xiang, Chen, Jiang, Zhang, Li and Tang.)

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world with high morbidity and mortality. Identifying an effective marker for predicting the prognosis and therapeutic response is extremely meaningful. Angiogenesis-related genes (ARGs) play important roles in the tumor progression and immune-suppressive microenvironment formation., Methods: The differential expressed ARGs associated with the prognosis of HCC were identified in the TCGA dataset. Univariate Cox and least absolute shrinkage selection operator (LASSO) regression were applied to construct a ARGs Scoring model. The prognostic value of the ARGs Scoring model was assessed by Cox regression, Kaplan-Meier (KM) and ROC curve analyses. Then the model was further validated in an external dataset, ICGC dataset. The patients were split into two groups based on the ARGs Score and the clinical features were compared. TIMER, CIBERSORT and xCell algorithms were utilized to analyze the correlation between the ARGs Score and tumor immune microenvironment (TIME). Furthermore, we analyzed the efficacy of the model in predicting the therapeutic response for immunotherapy, targeted therapy and TACE treatment in different cohorts., Results: A total of 97 differential expressed ARGs were identified relating to the prognosis of HCC patients from the TCGA dataset. Then the ARGs Scoring model based on a 9-gene signature was constructed using the Cox and LASSO regression analyses. Higher ARGs Score had a poor clinical outcome and was considered to be an independent prognostic predictor for HCC in the multivariate Cox analysis. The ARGs Score was related to the enrichment of various immune cells, such as CD4+ T cells, Treg, macrophage, neutrophil and dendritic cells, exhibiting a more immunosuppressive phenotype. Higher ARGs Score was correlated with higher expression of immune checkpoint genes and poor response to immunotherapy. Furthermore, higher ARGs Score indicated poor therapeutic response in the sorafenib and TACE treatment cohorts, individually., Conclusions: The ARGs Scoring model exhibited robust predictive value for the prognosis and TIME for HCC patients. Higher ARGs Score indicated poor therapeutic response of the immunotherapy, sorafenib and TACE treatment. The ARGs Scoring model could be used as a biomarker to help physicians to develop more individualized treatment for HCC patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Tang, Zhang, Yang, Wang, Li and Liu.)

Objectives To investigate the potential mechanism of development of resistance to tyrosine kinase inhibitor in renal cell carcinoma. Methods A primary culture of renal cell carcinoma cells ( KMRM- S2) was established from an advanced renal cell carcinoma patient with cutaneous metastasis, who had not responded to sorafenib. A total of 84 human angiogenesis-related genes were compared between cutaneous metastasis and the primary tumor by real time polymerase chain reaction. Spectral karyotyping and cell proliferation assay were carried out to determine the biological features of the cells. Results Primary tumor was histopathologically diagnosed as high-grade clear cell carcinoma with sarcomatoid change and rhabdoid features. The cutaneous metastasis also consisted of sarcomatoid components. Expression levels of many angiogenesis-related genes in the cutaneous metastasis were relatively higher than those of primary tumor. Chromosomal analysis of the KMRM- S2 showed cytogenetic abnormalities with hypertriploidy and translocation. In vitro proliferation assay showed the relatively higher resistance of KMRM- S2 against sorafenib. Conclusions The sarcomatoid change and rhabdoid features of renal cell carcinoma with cytogenetic hyperploidy might be associated with elevated expression of angiogenesis-related genes, which leads to resistance against tyrosine kinase inhibitor. The present study might contribute to discovering novel therapeutic targets for the treatment of patients with advanced renal cell carcinoma resistant to tyrosine kinase inhibitor. [ABSTRACT FROM AUTHOR]

In a view to explore blood vessels neo formation as a possible adaptive response to hypobaric hypoxia in the chicken lung, mRNA expression of the following genes was examined: hypoxia inducible factor-1α (HIF-1α) and -2α (HIF-2α), vascular endothelial growth factor (VEGF), receptors for VEGF (Flk- 1 and Flt-1), hepatocyte growth factor (HGF) and its receptor (HGFR), epidermal growth factor (EGF) and its receptor (EGFR). The molecular regulation of these genes remains completely unknown in these conditions. One group of birds was exposed to relative normoxia and the other group, to hypobaric hypoxia. Comparisons were made among non-pulmonary hypertensive chickens under relative normoxic conditions (NHCN) and non-pulmonary hypertensive chickens (NHCH) and pulmonary hypertensive chickens (PHCH) under hypobaric hypoxic conditions, respectively. For HIF-2α, VEGF, Flk-1, HGF and HGFR genes, no statistical differences were found in the relative mRINA expression between PHCH and NHCH, but those were lower when compared to NHCN (P<0,05). For Flt-1 mRNA expression, a significant difference between NHCH and NHCN was noted (P<0.05), but relative mRNA expression in the lungs of PHCH did not show differences with findings in the lungs of NHCN or NHCH. HIF-1α and EGFR mRNA expression analysis indicated significant differences between NHCN and PHCH, but not between NHCH and PHCH. There was a general trend towards a lower mRNA expression of genes involved in the response to hypoxia and vascular proliferation in the lungs of chickens exposed to chronic hypoxia in PHCH and NHCH when compared with NHCN. These results show consistency with those registered in a parallel study which indicated a lower number of blood vessels with a diameter range ≥50-100μm in the lungs of PHCH and NHCH when compared with observations obtained in NHCN. [ABSTRACT FROM AUTHOR]

For better understanding cancer pathogenesis and searching a potential target for antineoplastic therapy, the authors have studied mRNA expression profile in tissues from 39 children with histological confirmed malignant sarcomas and from 23 patients with bone and soft tissue nonmalignant lesions. mRNA levels of Angiogenesis-related genes VEGFA (including isoforms of 121, 165, 189), VEGFC, VEGFR-1, VEGFR-2, VEGFR-3, HIF-1α, TF, TFPI-1, TFPI-2, uPA, PAI-1 in pediatric specimens were examined using quantitative reverse transcriptase–polymerase chain reaction (qRT-PCR). uPA, HIF-1α, VEGFR-1, VEGFR-2, VEGFR-3, and VEGFC mRNA levels from nonmalignant tissue were significantly higher than those from cancer tissue. On the other hand, isoform VEGFA121 and VEGFA165 and ratio VEGFA165/189 mRNA levels in cancer were higher in comparison with nonmalignant tissue. There was a strong correlation between VEGFA165 and VEGFA189 mRNA expression levels both in cancer tissue and in nonmalignant tissue. In grade 4 tumors in comparison with grade 2 tumors, there was a reduced VEGFA165/189 ratio. Moreover, TFPI-1 and TFPI-2 mRNA levels were significantly lower in sarcomas than in nonmalignant lesions and TFPI-2 was significantly lower in grade 4 tumors than in grade 2. The present data suggested that mRNA overexpression of angiogenesis-related genes is not a prerogative of malignant tissues. The authors supposed that in pediatric bone and soft tissue pathology, high expression of mRNAs of some angiogenesis-related genes may be associated with inflammation and physiological angiogenesis rather than with the development of a malignant tumor. The authors showed the importance of VEGFA121 and/or VEGFA165 and VEGFA165/189 isoform ratio in pediatric sarcomas neoangiogenesis and TFPI-2 for tumors grade 4. [ABSTRACT FROM AUTHOR]