1, 9 PA downregulates HIF-1α independent of its JNK inhibitory function.

<p>(A) Temporal order and correlation of 1, 9 PA-induced HIF-1α downregulation and JNK inhibition, and the treatment-induced compensatory activation of Akt and Erk. A431 cells were treated with 5 µM 1, 9 PA in 0.5% FBS culture medium for the indicated time intervals. Cell lysates were then prepared for Western blotting with the antibodies shown. (B) Dose-dependent effects of 1, 9 PA on downregulating HIF-1α, inhibiting JNK, and activating Erk. A431 cells were exposed to increasing concentrations of 1, 9 PA for 16 h in 0.5% FBS culture medium at 37°C. Cell lysates were then prepared for Western blotting with the antibodies shown. (C) Independence of 1, 9 PA-induced HIF-1α downregulation from its JNK inhibitory function. A431 cells were treated with increasing concentrations of 1, 9 PA or 1-methyl-1, 9 PA for 1 h in 0.5% FBS culture medium. Cell lysates were then prepared for Western blotting with the antibodies shown. (D) No changes in HIF-1α level after activation or inhibition of JNK. A431 cells wert transiently transfected with a control vector or one of the constructs containing a constitutively active SEK1 S220E/T224D mutant (SEK1-CA), a dominant-negative SEK1 K129R mutant (SEK1-DN), or a dominant-negative MEKK1 K432M mutant (MEKK1-DN) overnight. Cell lysates were then prepared for Western blotting with the antibodies shown. (E) Compensatory activation of Erk after HIF-1α silencing in comparison with treatment by 1, 9 PA or 1-methyl-1, 9 PA. A431 cells were subjected to knockdown of HIF-1α with specific or control siRNA, or treated with 10 µM 1, 9 PA or 1-methyl-1, 9 PA for 16 h. Cell lysates were then prepared for Western blotting with the antibodies shown. (F) Downregulation of HIF-1α by 1, 9 PA in various cancer cell lines. Indicated cell lines were exposed to 10 or 40 µM 1, 9 PA for 1 h in 0.5% FBS culture medium. Cell lysates were then prepared for Western blotting with the antibodies shown.</p

1, 9 PA enhances responses of cancer cells expressing an oncogenic Ras mutant to cetuximab.

<p>(A) Effect of 1, 9 PA and cetuximab, either alone or in combination, on the HIF-1α level and induction of apoptosis. A431neo and A431/RasG12V cells were untreated or treated with cetuximab (10 nM for 16 h), 10 µM 1, 9 PA (added the last hour before cell lysis), or both in 0.5% FBS culture medium. Cell lysates were prepared and analyzed by Western blotting with the antibodies shown. (B) 1, 9 PA-mediated sensitization to cetuximab-induced growth inhibition. A431neo and A431/RasG12V cells were treated with increasing concentrations of cetuximab ±5 µM 1, 9 PA in 0.5% FBS culture medium for 5 days. After treatment, the cells were subjected to an MTT assay. The optical density values of the treated groups were normalized to the values of the control groups (with or without 1, 9 PA treatment) and expressed as a percentage of respective control. The percentage of surviving cells was plotted as a function of treatment with increasing concentrations of cetuximab. The differences in cell survival between the two groups were statistically significant (<i>p</i><0.01) when the concentrations of cetuximab were greater than 0.625 nM in A431neo cells and 1.25 nM in A431/RasG12V cells. (C) 1, 9 PA-mediated sensitization to cetuximab-induced inhibition of VEGF production. A431neo and A431/RasG12V cells were untreated or treated with 10 nM cetuximab, 10 µM 1, 9 PA, or both in 0.5% FBS culture medium for 16 h. The VEGF secreted into the conditioned media by the cells was measured by ELISA. The <i>p</i>-values for indicated comparisons were shown. (D) Comparison of A431 and GEO cells to treatment with 1, 9 PA and cetuximab, either alone or in combination. A431 and GEO cells were treated as described in (A). Cell lysates were prepared and analyzed by Western blotting with the antibodies shown. (E). 1, 9 PA-mediated sensitization GEO cells to cetuximab-induced growth inhibition. GEO cells were treated with increasing concentrations of cetuximab ±5 µM 1, 9 PA in 0.5% FBS culture medium for 5 days. After treatment, the cells were subjected to an MTT assay. The data were processed as described in (B). The differences in cell survival between the two groups were statistically significant (<i>p</i><0.01) at all concentrations of cetuximab tested.</p

1, 9 PA enhances HIF-1α ubiquitination.

<p>(A). A431 cells were treated with 10 µM 1, 9 PA for indicated time period. Cell lysates were prepared for HIF-1α immunoprecipitation, followed by Western blotting of the immunoprecipitates with antibodies directed against ubiquitin (top), HIF-1α, and β-actin. (B) A431 cells were untreated or treated with 10 µM 1, 9 PA in the presence of 10 µM MG132 for 1 h in 0.5% FBS medium. HIF-1α was immunoprecipitated followed by Western blot analysis with an anti-HIF-1α antibody.</p

Combination of 1, 9 PA and cetuximab induces apoptosis through downregulation of HIF-1α.

<p>(A) Induction of PARP cleavage by the combination of 1, 9 PA and cetuximab. A431, HN5, and DiFi cells were untreated or treated with cetuximab (10 nM for A431 and HN5 cells and 2 nM for DiFi cells for 16 h), 1, 9 PA (10 µM or 40 µM added the last hour before cell lysis), or both in 0.5% FBS culture medium. Cell lysates were prepared and analyzed by Western blotting with the antibodies shown. (B) Increased induction of apoptosis by the combination of 1, 9 PA and cetuximab. A431 cells were treated as described in (A). Cell lysates were prepared and analyzed by apoptosis ELISA. The relative absorbance values are plotted. The <i>p</i> value was <0.01 when comparing the level of apoptosis by 1, 9 PA alone (10 or 40 µM) or cetuximab alone with that of apoptosis by combination of the 2 agents (note: only the <i>p</i> values comparing 10 µM 1, 9 PA alone and in combination with cetuximab are shown). (C) Dependence of induction of apoptosis by the combination of 1, 9 PA and cetuximab on HIF-1α downregulation. A431neo and A431/HIF-1α-ΔODD cells were treated as indicated, and the cell lysates were prepared and analyzed as described in (A).</p

Differential effect of constitutively active Akt on cetuximab and 1, 9 PA-induced downregulation of HIF-1α.

<p>A431 cells were transiently transfected with a control vector or a myristoylated Akt (Myr-Akt) for 24 h in 0.5% FBS medium. The vector- or Myr-Akt–transfected cells were then treated with either 20 nM cetuximab or PBS overnight (A), or with 10 µM 1, 9 PA or DMSO vehicle control for 1 h (B). After treatment, cell lysates were prepared for Western blotting with the antibodies shown.</p

1, 9 PA downregulates HIF-1α in a PHD- and HIF-1α ODD-dependent manner.

<p>(A) Requirement of O₂ and Fe²⁺ in the 1, 9 PA-induced downregulation of HIF-1α. A431 cells were untreated or treated with 10 µM 1, 9 PA in 0.5% FBS culture medium under normoxic conditions in the absence or presence of DFO (100 µM) or MG132 (10 µM), and under hypoxic conditions for 16 h at 37°C. Cell lysates were then prepared for Western blotting with the antibodies shown. (B) Role of the ODD of HIF-1α in the 1, 9 PA-induced downregulation of HIF-1α. A431 cells were transiently transfected with the HIF-1α-ΔODD construct or a control vector for 48 h and were then either untreated or treated with the indicated concentrations of 1, 9 PA for 1 h at 37°C. Cell lysates were then prepared for Western blotting with the antibodies shown. (C) Resistance of A431/HIF-1α-ΔODD cells to the 1, 9 PA-induced downregulation of HIF-1α. A431 cells stably expressing the HIF-1α-ΔODD construct were treated as described in (A). Cell lysates were then prepared for Western blotting with the antibodies shown.</p

DataSheet1_Comprehensive analysis of FRAS1/FREM family as potential biomarkers and therapeutic targets in renal clear cell carcinoma.PDF

Background: FRAS1 (Fraser syndrome protein 1), together with FREM1 (the Fras1-related extracellular matrix proteins 1) and FREM2, belonging to the FRAS1/FREM extracellular matrix protein family, are considered to play essential roles in renal organogenesis and cancer progression. However, their roles in kidney renal clear cell carcinoma (KIRC) remain to be elucidated.Methods: FRAS1/FREM RNA expression analysis was performed using TCGA/GTEx databases, and valided using GEO databases and real-time PCR. Protein expression was peformed using CPTAC databases. Herein, we employed an array of bioinformatics methods and online databases to explore the potential oncogenic roles of FRAS1/FREM in KIRC.Results: We found that FRAS1, FREM1 and FREM2 genes and proteins expression levels were significantly decreased in KIRC tissues than in normal tissues. Decreased FRAS1/FREM expression levels were significantly associated with advanced clinicopathological parameters (pathological stage, grade and tumor metastasis status). Notably, the patients with decreased FRAS1/FREM2 expression showed a high propensity for metastasis and poor prognosis. FRAS1/FREM were correlated with various immune infiltrating cells, especially CD4+ T cells and its corresponding subsets (Th1, Th2, Tfh and Tregs). FRAS1 and FREM2 had association with DNA methylation and their single CpG methylation levels were associated with prognosis. Moreover, FRAS1/FREM might exert antitumor effects by functioning in key oncogenic signalling pathways and metabolic pathways. Drug sensitivity analysis indicated that high FRAS1 and FREM2 expression can be a reliable predictor of targeted therapeutic drug response, highlighting the potential as anticancer drug targets.Conclusion: Together, our results indicated that FRAS1/FREM family members could be potential therapeutic targets and valuable prognostic biomarkers of KIRC.</p

Table_1_Establishment and validation of a carbohydrate metabolism-related gene signature for prognostic model and immune response in acute myeloid leukemia.xlsx

IntroductionThe heterogeneity of treatment response in acute myeloid leukemia (AML) patients poses great challenges for risk scoring and treatment stratification. Carbohydrate metabolism plays a crucial role in response to therapy in AML. In this multicohort study, we investigated whether carbohydrate metabolism related genes (CRGs) could improve prognostic classification and predict response of immunity and treatment in AML patients.MethodsUsing univariate regression and LASSO-Cox stepwise regression analysis, we developed a CRG prognostic signature that consists of 10 genes. Stratified by the median risk score, patients were divided into high-risk group and low-risk group. Using TCGA and GEO public data cohorts and our cohort (1031 non-M3 patients in total), we demonstrated the consistency and accuracy of the CRG score on the predictive performance of AML survival.ResultsThe overall survival (OS) was significantly shorter in high-risk group. Differentially expressed genes (DEGs) were identified in the high-risk group compared to the low-risk group. GO and GSEA analysis showed that the DEGs were mainly involved in immune response signaling pathways. Analysis of tumor-infiltrating immune cells confirmed that the immune microenvironment was strongly suppressed in high-risk group. The results of potential drugs for risk groups showed that inhibitors of carbohydrate metabolism were effective.DiscussionThe CRG signature was involved in immune response in AML. A novel risk model based on CRGs proposed in our study is promising prognostic classifications in AML, which may provide novel insights for developing accurate targeted cancer therapies.</p

Image_1_Establishment and validation of a carbohydrate metabolism-related gene signature for prognostic model and immune response in acute myeloid leukemia.pdf

IntroductionThe heterogeneity of treatment response in acute myeloid leukemia (AML) patients poses great challenges for risk scoring and treatment stratification. Carbohydrate metabolism plays a crucial role in response to therapy in AML. In this multicohort study, we investigated whether carbohydrate metabolism related genes (CRGs) could improve prognostic classification and predict response of immunity and treatment in AML patients.MethodsUsing univariate regression and LASSO-Cox stepwise regression analysis, we developed a CRG prognostic signature that consists of 10 genes. Stratified by the median risk score, patients were divided into high-risk group and low-risk group. Using TCGA and GEO public data cohorts and our cohort (1031 non-M3 patients in total), we demonstrated the consistency and accuracy of the CRG score on the predictive performance of AML survival.ResultsThe overall survival (OS) was significantly shorter in high-risk group. Differentially expressed genes (DEGs) were identified in the high-risk group compared to the low-risk group. GO and GSEA analysis showed that the DEGs were mainly involved in immune response signaling pathways. Analysis of tumor-infiltrating immune cells confirmed that the immune microenvironment was strongly suppressed in high-risk group. The results of potential drugs for risk groups showed that inhibitors of carbohydrate metabolism were effective.DiscussionThe CRG signature was involved in immune response in AML. A novel risk model based on CRGs proposed in our study is promising prognostic classifications in AML, which may provide novel insights for developing accurate targeted cancer therapies.</p