Matching Patients to Accelerate Clinical Trials (MPACT): Enabling Technology for Oncology Clinical Trial Workflow.

Clinical trial enrollment is impeded by the significant time burden placed on research coordinators screening eligible patients. With 50,000 new cancer cases every year, the Veterans Health Administration (VHA) has made increased access for Veterans to high-quality clinical trials a priority. To aid in this effort, we worked with research coordinators to build the MPACT (Matching Patients to Accelerate Clinical Trials) platform with a goal of improving efficiency in the screening process. MPACT supports both a trial prescreening workflow and a screening workflow, employing Natural Language Processing and Data Science methods to produce reliable phenotypes of trial eligibility criteria. MPACT also has a functionality to track a patient's eligibility status over time. Qualitative feedback has been promising with users reporting a reduction in time spent on identifying eligible patients.

Clinical characteristics and prognosis analysis of postoperative patients with stage I-III colon cancer based on SEER database.

PURPOSE: To identify the relevant factors affecting the prognosis and survival time of colon cancer and construct a survival prediction model. METHODS: Data on postoperative stage I-III colon cancer patients were obtained from the Surveillance, Epidemiology, and End Results database. We used R project to analyze the data. Univariate and multivariate Cox regression analyses were performed for independent factors correlated with overall survival from colon cancer. The C-index was used to screen the factors that had the greatest influence in overall survival after surgery in colon cancer patients. Receiver operating characteristic (ROC) curve was made according to the Risk score and calculated to validate the predictive accuracy of the model. In addition, we used decision curve analysis (DCA) to evaluate the clinical benefits and utility of the nomogram. We created a model survival curve to determine the difference in prognosis between patients in the low-risk group and those in the high-risk group. RESULTS: Univariate and multifactor COX analyses showed that the race, Grade, tumor size, N-stage and T-stage were independent risk factors affecting survival time of patients. The analysis of ROC and DCA showed the nomogram prediction model constructed based on the above indicators has good predictive effects. CONCLUSION: Overall, the nomogram constructed in this study has good predictive effects. It can provide a reference for future clinicians to evaluate the prognosis of colon cancer patients.

GEMIN4, a potential therapeutic targets for patients with basal-like subtype breast cancer.

BACKGROUND: Basal-like breast cancer (BLBC) takes up about 10-20% of all breast cancer(BC), what's more, BLBC has the lowest survival rate among all BC subtypes because of lacks of efficient treatment methods. We aimed to explore the molecules that can be used as diagnostic maker for BLBC at early stage and provide optimized treatment strategies for BLBC patients in this study. METHODS: Apply weighted gene co-expression network analysis (WGCNA) to identify gene modules related to BLBC;The functional enrichment of candidate genes related to BLBC in the red module of Go data package and KEGG analysis;Overlapping cross analysis of URGs and WGCNA to identify candidate genes in each BC subtype;Divide BCBL patients into high-risk and low-risk groups, and analyze the two groups of overall survival (OS) and relapse free survival (RFS);Screening of GEMIN4 dependent cell lines; QRT PCR was used to verify the expression of GEMIN4 transfected with siRNA; CCK8 was used to determine the effect of GEMIN4 on cell viability; Positive cell count detected by BrdU staining;GO and KEGG enrichment analysis of GEMIN4. RESULTS: The "red module" has the highest correlation with BLBC, with 913 promising candidate genes identified from the red module;913 red module candidate genes related to BLBC participated in multiple GO terms, and KEGG enrichment analysis results mainly enriched in estrogen signaling pathways and pathways in cancer;There are 386 overlapping candidate genes among the 913 "red module" genes identified by 1893 common URG and WGCNA;In BLBC patients, 9 highly expressed genes are associated with OS. Five highly expressed genes are associated with RFS. Kaplan Meier survival analysis suggests that high GEMIN4 expression levels are associated with poor prognosis in BLBC patients;The GEMIN4 gene dependency score in HCC1143 and CAL120 cell lines is negative and low; Si-GEMIN4-1 can significantly reduce the mRNA expression of GEMIN4; Si-GEMIN4 can inhibit cell viability; Si-GEMIN4 can reduce the number of positive cells;GO enrichment analysis showed that GEMIN4 is associated with DNA metabolism processes and adenylate binding; KEGG pathway enrichment analysis shows that GEMIN4 is related to ribosome biogenesis in eukaryotes. CONCLUSION: We hypothesized that GEMIN4 may be the potential target for the treatment of BLBC.

Gamma-Aminobutyric Acid Type A Receptor Subunit Delta (GABRD) Inhibits Breast Cancer Progression by Regulating the Cell Cycle.

Background: The role of γ-aminobutyric acid receptor (GABR) in breast cancer (BC) is unknown. Methods: The expression of different GABR subunits between BC and adjacent normal tissues was compared using transcriptome data set. The clinical and prognostic importance of the various GABR subunit genes in BC was determined using clinical and survival data (Data downloaded from TCGA, May 2022). Only GABRD was discovered to be substantially expressed and strongly related to the prognosis of BC cases. Results: Compared with normal tissues, GABRD expression was increased in all subgroups of breast cancer tissues. Knockdown of GABRD inhibited the growth of BC cells. Mechanistically, the function of GABRD may be attributed to its effect on major pathways such as oxidative phosphorylation, Parkinson disease, and cell cycle. GABRD deletion significantly blocked the G2/M phase in BC cells. Conclusion: Overall, GABRD might be a novel prognostic predictor of BC, providing clues for further studies on GABRD.

A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories.

Pancreatic cancer is an aggressive disease that typically presents late with poor outcomes, indicating a pronounced need for early detection. In this study, we applied artificial intelligence methods to clinical data from 6 million patients (24,000 pancreatic cancer cases) in Denmark (Danish National Patient Registry (DNPR)) and from 3 million patients (3,900 cases) in the United States (US Veterans Affairs (US-VA)). We trained machine learning models on the sequence of disease codes in clinical histories and tested prediction of cancer occurrence within incremental time windows (CancerRiskNet). For cancer occurrence within 36 months, the performance of the best DNPR model has area under the receiver operating characteristic (AUROC) curve = 0.88 and decreases to AUROC (3m) = 0.83 when disease events within 3 months before cancer diagnosis are excluded from training, with an estimated relative risk of 59 for 1,000 highest-risk patients older than age 50 years. Cross-application of the Danish model to US-VA data had lower performance (AUROC = 0.71), and retraining was needed to improve performance (AUROC = 0.78, AUROC (3m) = 0.76). These results improve the ability to design realistic surveillance programs for patients at elevated risk, potentially benefiting lifespan and quality of life by early detection of this aggressive cancer.

Computational ranking-assisted identification of Plexin-B2 in homotypic and heterotypic clustering of circulating tumor cells in breast cancer metastasis.

Metastasis is the cause of over 90% of all deaths associated with breast cancer, yet the strategies to predict cancer spreading based on primary tumor profiles and therefore prevent metastasis are egregiously limited. As rare precursor cells to metastasis, circulating tumor cells (CTCs) in multicellular clusters in the blood are 20-50 times more likely to produce viable metastasis than single CTCs. However, the molecular mechanisms underlying various CTC clusters, such as homotypic tumor cell clusters and heterotypic tumor-immune cell clusters, are yet to be fully elucidated. Combining machine learning-assisted computational ranking with experimental demonstration to assess cell adhesion candidates, we identified a transmembrane protein Plexin- B2 (PB2) as a new therapeutic target that drives the formation of both homotypic and heterotypic CTC clusters. High PB2 expression in human primary tumors predicts an unfavorable distant metastasis-free survival and is enriched in CTC clusters compared to single CTCs in advanced breast cancers. Loss of PB2 reduces formation of homotypic tumor cell clusters as well as heterotypic tumor-myeloid cell clusters in triple-negative breast cancer. Interactions between PB2 and its ligand Sema4C on tumor cells promote homotypic cluster formation, and PB2 binding with Sema4A on myeloid cells (monocytes) drives heterotypic CTC cluster formation, suggesting that metastasizing tumor cells hijack the PB2/Sema family axis to promote lung metastasis in breast cancer. Additionally, using a global proteomic analysis, we identified novel downstream effectors of the PB2 pathway associated with cancer stemness, cell cycling, and tumor cell clustering in breast cancer. Thus, PB2 is a novel therapeutic target for preventing new metastasis.

lncRNA MALAT1 promotes HCC metastasis through the peripheral vascular infiltration via miRNA-613: a primary study using contrast ultrasound.

BACKGROUND: This study aimed to explore the specific pathogenesis of lncRNA MALAT1 promoting the invasion and metastasis of hepatocellular carcinoma (HCC) through peripheral blood vessels by regulating the expression of miRNA-613 molecule. METHODS: The data of 60 HCC metastatic patients and 60 HCC non-metastatic patients detected by the contrast-enhanced ultrasound (CEUS) in the Second Affiliated Hospital of Qiqihar Medical College from January 2020 to June 2021 were collected, as well as postoperatively retained HCC tissues and paired paracancer tissues (5 cm laterally from the edge of the cancer area), to study the changes of microangiogenesis in HCC tissues with CEUS. The correlation between CEUS grading and lncRNA MALAT1 in patients with HCC was analyzed through Pearson correlation analysis, lncRNA MALAT1 and miRNA-613 in HCC tissues of patients with HCC were detected by qRT-PCR, followed by the bioinformatic analysis for the relationship between lncRNA MALAT1 and miRNA-613. The Log-growing human HCC cell strain, HepG2, was selected for experiments. Adenovirus transfection knocked down lncRNA MALAT1 in HCC cells, which was divided into two groups (inhibitor-NC group and lncR-inhibitor group), followed by knocking down miRNA-613 on the basis of knocking down lncRNA MALAT1, which was divided into three groups (inhibitor-NC group, lncR-inhibitor groups, and lncR/miR613-inhibitor group). The expression of miRNA-613 and lncRNA MALAT1 in each group was detected by qRT-PCR. The migration and invasiveness of cells in each group were detected by Transwell assay. RESULTS: CEUS of HCC and Pearson correlation analysis showed that CEUS grading and lncRNA MALAT1 were positively correlated in patients with HCC. In HCC tissues of patients with HCC, lncRNA MALAT1 expressed high and miRNA-613 expressed low. The results of bioinformatic analysis showed the targeting of lncRNA MALAT1 and miRNA-613. Knocking down lncRNA MALAT1 could increase miRNA-613 expression significantly, and reduce the migration of HCC cells. Inhibiting miRNA-613 based on knocking down lncRNA MALAT1 could increase the survival and migration of HCC cells. CONCLUSIONS: lncRNA MALAT1 can promote HCC metastasis through the peripheral vascular infiltration by inhibiting the level of MiRNA-613, which can, therefore, be used as a potential target for the treatment of HCC.

Platelet Function Is Associated With Dementia Risk in the Framingham Heart Study.

Background Vascular function is compromised in Alzheimer disease (AD) years before amyloid and tau pathology are detected and a substantial body of work shows abnormal platelet activation states in patients with AD. The aim of our study was to investigate whether platelet function in middle age is independently associated with future risk of AD. Methods and Results We examined associations of baseline platelet function with incident dementia risk in the community-based FHS (Framingham Heart Study) longitudinal cohorts. The association between platelet function and risk of dementia was evaluated using the cumulative incidence function and inverse probability weighted Cox proportional cause-specific hazards regression models, with adjustment for demographic and clinical covariates. Platelet aggregation response was measured by light transmission aggregometry. The final study sample included 1847 FHS participants (average age, 53.0 years; 57.5% women). During follow-up (median, 20.5 years), we observed 154 cases of incident dementia, of which 121 were AD cases. Results from weighted models indicated that platelet aggregation response to adenosine diphosphate 1.0 µmol/L was independently and positively associated with dementia risk, and it was preceded in importance only by age and hypertension. Sensitivity analyses showed associations with the same directionality for participants defined as adenosine diphosphate hyper-responders, as well as the platelet response to 0.1 µmol/L epinephrine. Conclusions Our study shows individuals free of antiplatelet therapy with a higher platelet response are at higher risk of dementia in late life during a 20-year follow-up, reinforcing the role of platelet function in AD risk. This suggests that platelet phenotypes may be associated with the rate of dementia and potentially have prognostic value.

Analysis of Long Noncoding RNAs-Related Regulatory Mechanisms in Duchenne Muscular Dystrophy Using a Disease-Related lncRNA-mRNA Pathway Network.

Objective: This study aimed to investigate the molecular regulatory mechanisms underpinning Duchenne muscular dystrophy (DMD). Methods: Using microarray data, differentially expressed long noncoding RNAs (DELs) and DMD-related differentially expressed mRNAs (DEMs) were screened based on the comparative toxicogenomics database, using a cutoff of |log2 fold change| > 1 and false discovery rate (FDR) < 0.05. Then, protein-protein interaction (PPI), coexpression network of lncRNA-mRNA, and DMD-related lncRNA-mRNA pathway networks were constructed, and functional analyses of the genes in the network were performed. Finally, the proportions of immune cells infiltrating the muscle tissues in DMD were analyzed, and the correlation between the immune cells and expression of the DELs/DEMs was studied. Results: A total of 46 DELs and 313 DMD-related DEMs were identified. The PPI network revealed STAT1, VEGFA, and CCL2 to be the top three hub genes. The DMD-related lncRNA-mRNA pathway network comprising two pathways, nine DELs, and nine DMD-related DEMs showed that PYCARD, RIPK2, and CASP1 were significantly enriched in the NOD-like receptor signaling pathway, whereas MAP2K2, LUM, RPS6, PDCD4, TWIST1, and HIF1A were significantly enriched with proteoglycans in cancers. The nine DELs in this network were DBET, MBNL1-AS1, MIR29B2CHG, CCDC18-AS1, FAM111A-DT, GAS5, LINC01290, ATP2B1-AS1, and PSMB8-AS1. Conclusion: The nine DMD-related DEMs and DELs identified in this study may play important roles in the occurrence and progression of DMD through the two pathways of the NOD-like receptor signaling pathway and proteoglycans in cancers.

Kang-Ai Injection Inhibits Gastric Cancer Cells Proliferation through IL-6/STAT3 Pathway.

OBJECTIVE: To explore the mechanisms underlying the proliferative inhibition of Chinese herbal medicine Kang-Ai injection (KAI) in gastric cancer cells. METHODS: Gastric cancer cell lines MGC803 and BGC823 were treated by 0, 0.3%, 1%, 3% and 10% KAI for 24, 48 and 72 h, respectively. The cell proliferation was evaluated by 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) assay. The apoptosis and cell cycle were evaluated by flow cytometry. Interleukin (IL)-6 mRNA and protein expression levels were detected by quantitative real-time polymerase chain reaction (qRT-PCR) and enzyme-linked immune sorbent assay (ELISA), respectively. The protein expression levels of cyclin A, cyclin E, cyclin B1, cyclin D1, p21, retinoblastoma (RB), protein kinase B (AKT), extracellular regulated protein kinases (ERK), signal transducer and activator of transcription (STAT) 1 and STAT3 were detected by Western blot. RESULTS: KAI inhibited the proliferation of MGC803 and BGC823 gastric cancer cells in dose- and time-dependent manner. After treated with KAI for 48 h, the proportion of G1 phase was increased, expression level of cyclin D1 and phosphorylation-RB were down-regulated, whereas the expression of p21 was up-regulated (all P<0.01). Furthermore, 48-h treatment with KAI decreased the phosphorylation level of STAT3, inhibited the mRNA and protein expressions of IL-6 (all P<0.01). IL-6 at dose of 10 ng/mL significantly attenuated the proliferative effect of both 3% and 10% KAI, and recovered KAI-inhibited STAT3 phosphorylation and cyclin D1 expression level (all P<0.01). CONCLUSION: KAI exerted an anti-proliferative function by inhibiting IL-6/STAT3 signaling pathway followed by the induction of G1 phase arrest in gastric cancer cells.

Potential long-term effect of tumor necrosis factor inhibitors on dementia risk: A propensity score matched retrospective cohort study in US veterans.

INTRODUCTION: Tumor necrosis factor (TNF) inhibitors are widely used to treat rheumatoid arthritis (RA) and their potential to retard Alzheimer's disease (AD) progression has been reported. However, their long-term effects on the dementia/AD risk remain unknown. METHODS: A propensity scored matched retrospective cohort study was conducted among 40,207 patients with RA within the US Veterans Affairs health-care system from 2000 to 2020. RESULTS: A total of 2510 patients with RA prescribed TNF inhibitors were 1:2 matched to control patients. TNF inhibitor use was associated with reduced dementia risk (hazard ratio [HR]: 0.64, 95% confidence interval [CI]: 0.52-0.80), which was consistent as the study period increased from 5 to 20 years after RA diagnosis. TNF inhibitor use also showed a long-term effect in reducing the risk of AD (HR: 0.57, 95% CI: 0.39-0.83) during the 20 years of follow-up. CONCLUSION: TNF inhibitor use is associated with lower long-term risk of dementia/AD among US veterans with RA.

The Neutrophil to Lymphocyte Ratio Is Associated With the Risk of Subsequent Dementia in the Framingham Heart Study.

Objective: Active neutrophils are important contributors to Alzheimer's disease (AD) pathology through the formation of capillary stalls that compromise cerebral blood flow (CBF) and through aberrant neutrophil signaling that advances disease progression. The neutrophil to lymphocyte ratio (NLR) is a proxy of neutrophil-mediated inflammation, and higher NLR is found in persons diagnosed with clinical AD. The objective of this study was to investigate whether increased NLR in older adults is independently associated with the risk of subsequent dementia. Methods: We examined associations of baseline NLR with incident dementia risk in the community-based Framingham Heart Study (FHS) longitudinal cohorts. The association between NLR and risk of dementia was evaluated using the cumulative incidence function (CIF) and inverse probability-weighted Cox proportional cause-specific hazards regression models, with adjustment for age, sex, body mass index (BMI), systolic and diastolic blood pressure, diabetes, current smoking status, low-density lipoprotein (LDH), high-density lipoprotein (LDL), total cholesterol, triglycerides, and history of cardiovascular disease (CVD). Random forest survival models were used to evaluate the relative predictive value of the model covariates on dementia risk. Results: The final study sample included 1,648 participants with FHS (average age, 69 years; 56% women). During follow-up (median, 5.9 years), we observed 51 cases of incident dementia, of which 41 were AD cases. Results from weighted models suggested that the NLR was independently associated with incident dementia, and it was preceded in predictive value only by age, history of CVD, and blood pressure at baseline. Conclusion: Our study shows that individuals with higher NLR are at a greater risk of subsequent dementia during a 5.9-year follow-up period. Further evaluating the role of neutrophil-mediated inflammation in AD progression may be warranted.

Evaluation of 3D-CEUS in the Recurrence of Liver Cancer after Radiofrequency Ablation.

Background: Radiofrequency ablation (RFA) has the similar curative effects to surgery, but RFA will lead to higher postoperative local recurrence rate. 3D-CEUS is a minimally invasive examination method, which is used to analyze the sensitivity to postoperative recurrence in this study. Methods: The clinical data of 60 patients with liver cancer admitted to our hospital (February 2018-February 2020) were retrospectively analyzed. All patients were treated with RFA and were followed up with 3D-CEUS, MRI, and enhanced CT examination after surgery. The ROC curve was used to analyze the differences of different examination methods in judging postoperative recurrence. Results: For the 60 patients, 52 patients (86.7%) had a single lesion and 8 patients (13.3%) had multiple lesions, with a total of 72 lesions. After RFA, 56 lesions (77.8%) were completely inactivated and 16 lesions (22.2%) remained. Totally inactivated lesions were detected as follows: 51 (91.1%) by 3D-CEUS, 42 (75.0%) by MRI, and 50 (89.3%) by enhanced CT. During a 2-year follow-up, a total of 26 recurrent lesions were detected, 24 (92.3%) by 3D-CEUS, 12 (46.2%) by MRI, and 25 (96.2%) by enhanced CT, indicating that the sensitivity of 3D-CEUS and enhanced CT was obviously higher than that of MRI (P < 0.001), without conspicuous difference between sensitivity of 3D-CEUS and enhanced CT (P > 0.05). Conclusion: As a new imaging examination method based on artificial intelligence, 3D-CEUS has a high sensitivity in patients with liver cancer who underwent RFA, which can effectively judge the recurrence after surgery and should be widely used in practice.

Integrin α5 promotes migration and invasion through the FAK/STAT3/AKT signaling pathway in icotinib-resistant non-small cell lung cancer cells.

Patients with non-small cell lung cancer (NSCLC) treated with EGFR-tyrosine kinase inhibitors (TKIs) ultimately develop drug resistance and metastasis. Therefore, there is a need to identify the underlying mechanisms of resistance to EGFR-TKIs. In the present study, colony formation and MTT assays were performed to investigate cell viability following treatment with icotinib. Gene Expression Omnibus datasets were used to identify genes associated with resistance. Wound healing and Transwell assays were used to detect cell migration and invasion with icotinib treatment and integrin α5-knockdown. The expression levels of integrin α5 and downstream genes were detected using western blotting. Stable icotinib-resistant (IcoR) cell lines (827/IcoR and PC9/IcoR) were established that showed enhanced malignant properties compared with parental cells (HCC827 and PC9). Furthermore, the resistant cell lines were resistant to icotinib in terms of proliferation, migration and invasion. The enrichment of function and signaling pathways analysis showed that integrin α5-upregulation was associated with the development of icotinib resistance. The knockdown of integrin α5 attenuated the migration and invasion capability of the resistant cells. Moreover, a combination of icotinib and integrin α5 siRNA significantly inhibited migration and partly restored icotinib sensitivity in IcoR cells. The expression levels of phosphorylated (p)-focal adhesion kinase (FAK), p-STAT3 and p-AKT decreased after knockdown of integrin α5, suggesting that FAK/STAT3/AKT signaling had a notable effect on the resistant cells. The present study revealed that the integrin α5/FAK/STAT3/AKT signaling pathway promoted icotinib resistance and malignancy in IcoR NSCLC cells. This signaling pathway may provide promising targets against acquired resistance to EGFR-TKI in patients with NSCLC.

miR-497 targets VEGF signal pathway to regulate proliferation, invasion and migration of hepatocellular carcinoma cells: a primary study using DEC-MRI.

PURPOSE: To quantify the expression of miR-497 and its target gene VEGF-B in patients with hepatocellular carcinoma (HCC), and microvascular invasion (MVI) to identify their relationship with clinicopathological characteristics and prognosis. METHODS: Imaging data of postoperative cancer and adjacent tissues of HCC patients with MVI diagnosed by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) were retrospectively analyzed. The expression of miR-497 in clinical samples and HepG2 and SMMC-7721 cell lines was quantified by quantitative PCR (Q-PCR). Correlations between miR-497 and patient survival and VEGF-B were explored in TCGA database. The invasion and migration of SMMC-7721 cells were tested by transwell assay. The binding sites between miR-497 and its target gene VEGF-B were verified by dual-luciferase reporter (DLR) assay, and VEGF-B levels were analyzed by western blot (WB). RESULTS: miR-497 showed a lower expression in HCC patients with MVI than those without MVI. It was also lowly expressed in HCC cell lines compared to normal liver cell lines. The proliferation and migration in HCC cells were inhibited by overexpression of miR-497, which were enhanced after transfection with miR-497 inhibitor. miR-497 had an effect on VEGF-B levels and there was a regulatory relationship between them. miR-497 was able to target VEGF-B and downregulate the receptor of VEGF-B (FLT-1). CONCLUSION: miR-497 was lowly expressed in HCC tissues, and its overexpression inhibited invasion and metastasis in HCC cells by suppressing VEGF-B levels. MiR-497 and its target gene VEGF-B are closely associated with the biological function and may serve as prognostic factors of MVI in patients with HCC.

Circular RNA circ­CCT3 promotes hepatocellular carcinoma progression by regulating the miR­1287­5p/TEAD1/PTCH1/LOX axis.

Hepatocellular carcinoma (HCC) is characterized by a poor prognosis because of its insensitivity to radiation and chemotherapy. Recently, circular RNAs (circRNAs) have been found to serve important roles in hepatocellular carcinogenesis. circ­CCT3, a novel circRNA, was screened from the differential tissue expression results of a circRNA microarray. Relative expression levels of circ­CCT3 in specimens and cell lines were evaluated by reverse transcription­quantitative PCR and the relationship between circ­CCT3 and prognosis was analyzed by Kaplan­Meier curves. The oncogenic role of circ­CCT3 was confirmed in HCC cells through a cell counting kit­8 (CCK­8) assay, a colony formation assay, acridine orange/ethidium bromide double fluorescence staining, flow cytometry, a wound­healing assay and a Transwell assay. Bioinformatics prediction and luciferase reporter assays validated that circ­CCT3 facilitated HCC progression through the miR­1287­5p/TEA domain transcription factor 1 (TEAD1) axis. TEAD1 could then directly activate patched 1 and lysyl oxidase transcription, as analyzed by chromatin immunoprecipitation and luciferase reporter assays. The present study identified a novel circRNA, circ­CCT3, which may be used as a potential therapeutic target for HCC.

Bioinformatics-Based Identification of HDAC Inhibitors as Potential Drugs to Target EGFR Wild-Type Non-Small-Cell Lung Cancer.

Patients with EGFR-mutant non-small-cell lung cancer (NSCLC) greatly benefit from EGFR-tyrosine kinase inhibitors (EGFR-TKIs) while the prognosis of patients who lack EGFR-sensitive mutations (EGFR wild type, EGFR-WT) remains poor due to a lack of effective therapeutic strategies. There is an urgent need to explore the key genes that affect the prognosis and develop potentially effective drugs in EGFR-WT NSCLC patients. In this study, we clustered functional modules related to the survival traits of EGFR-WT patients using weighted gene co-expression network analysis (WGCNA). We used these data to establish a two-gene prognostic signature based on the expression of CYP11B1 and DNALI1 by combining the least absolute shrinkage and selection operator (LASSO) algorithms and Cox proportional hazards regression analysis. Following the calculation of risk score (RS) based on the two-gene signature, patients with high RSs showed a worse prognosis. We further explored targeted drugs that could be effective in patients with a high RS by the connectivity map (CMap). Surprisingly, multiple HDAC inhibitors (HDACis) such as trichostatin A (TSA) and vorinostat (SAHA) that may have efficacy were identified. Also, we proved that HDACis could inhibit the proliferation and metastasis of NSCLC cells in vitro. Taken together, our study identified prognostic biomarkers for patients with EGFR-WT NSCLC and confirmed a novel potential role for HDACis in the clinical management of EGFR-WT patients.