Proteo-genomic characterization of cirrhosis-associated liver cancers reveals potential subtypes and therapeutic targets.

BACKGROUND: This study aimed to identify potential subtypes of hepatocellular carcinoma (HCC) associated with cirrhosis and to investigate key markers using bioinformatic analysis of gene expression datasets-0. METHODS: Three data sets (GSE17548, GSE56140, and GSE87630) were extracted from the Gene Expression Omnibus (GEO) database and normalized using the Limma package in R. Principal component analysis (PCA) and cluster analysis was performed to examine data distribution and identify subtypes. Differential gene expression analysis was performed using the Limma software package. Protein-protein interaction analysis and functional annotation were performed using the STRING database and Cytoscape software. Important signaling pathways and processes were identified using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Analysis. RESULTS: The analysis revealed different subtypes of HCC associated with cirrhosis and identified several key genes, including CCNB2, MCM4, and CDC20, with strong binding power and prognostic value. Functional annotation indicated involvement in cell cycle regulation and metabolic pathways. ROC analysis showed high sensitivity and specificity of these genes in predicting HCC prognosis. CONCLUSION: These results suggest that CCNB2, MCM4, and CDC20 may serve as potential biomarkers for predicting HCC prognosis in patients with cirrhosis and provide insights into the molecular mechanisms of HCC progression.

Nodule-CLIP: Lung nodule classification based on multi-modal contrastive learning.

The latest developments in deep learning have demonstrated the importance of CT medical imaging for the classification of pulmonary nodules. However, challenges remain in fully leveraging the relevant medical annotations of pulmonary nodules and distinguishing between the benign and malignant labels of adjacent nodules. Therefore, this paper proposes the Nodule-CLIP model, which deeply mines the potential relationship between CT images, complex attributes of lung nodules, and benign and malignant attributes of lung nodules through a comparative learning method, and optimizes the model in the image feature extraction network by using its similarities and differences to improve its ability to distinguish similar lung nodules. Firstly, we segment the 3D lung nodule information by U-Net to reduce the interference caused by the background of lung nodules and focus on the lung nodule images. Secondly, the image features, class features, and complex attribute features are aligned by contrastive learning and loss function in Nodule-CLIP to achieve lung nodule image optimization and improve classification ability. A series of testing and ablation experiments were conducted on the public dataset LIDC-IDRI, and the final benign and malignant classification rate was 90.6%, and the recall rate was 92.81%. The experimental results show the advantages of this method in terms of lung nodule classification as well as interpretability.

A gene signature linked to fibroblast differentiation for prognostic prediction of mesothelioma.

BACKGROUND: Malignant mesothelioma is a type of infrequent tumor that is substantially related to asbestos exposure and has a terrible prognosis. We tried to produce a fibroblast differentiation-related gene set for creating a novel classification and prognostic prediction model of MESO. METHOD: Three databases, including NCBI-GEO, TCGA, and MET-500, separately provide single-cell RNA sequencing data, bulk RNA sequencing profiles of MESO, and RNA sequencing information on bone metastatic tumors. Dimensionality reduction and clustering analysis were leveraged to acquire fibroblast subtypes in the MESO microenvironment. The fibroblast differentiation-related genes (FDGs), which were associated with survival and subsequently utilized to generate the MESO categorization and prognostic prediction model, were selected in combination with pseudotime analysis and survival information from the TCGA database. Then, regulatory network was constructed for each MESO subtype, and candidate inhibitors were predicted. Clinical specimens were collected for further validation. RESULT: A total of six fibroblast subtypes, three differentiation states, and 39 FDGs were identified. Based on the expression level of FDGs, three MESO subtypes were distinguished in the fibroblast differentiation-based classification (FDBC). In the multivariate prognostic prediction model, the risk score that was dependent on the expression level of several important FDGs, was verified to be an independently effective prognostic factor and worked well in internal cohorts. Finally, we predicted 24 potential drugs for the treatment of MESO. Moreover, immunohistochemical staining and statistical analysis provided further validation. CONCLUSION: Fibroblast differentiation-related genes (FDGs), especially those in low-differentiation states, might participate in the proliferation and invasion of MESO. Hopefully, the raised clinical subtyping of MESO would provide references for clinical practitioners.

An overview of Twist1 in glioma progression and recurrence.

Glioma cells are characterized by high migration ability, resulting in the aggressive growth of the tumors and poor prognosis of patients. Epithelial-to-mesenchymal transition (EMT) is one of the most important steps for tumor migration and metastasis and be elevated during glioma progression and recurrence. Twist1 is a basic helix-loop-helix transcription factor and a key transcription factor involved in the process of EMT. Twist1 is related to glioma mesenchymal change, invasion, heterogeneity, self-renewal of tumor stem cells, angiogenesis, etc., and may be used as a prognostic indicator and therapeutic target for glioma patients. This paper mainly reviews the structural characteristics, regulatory mechanisms, and apparent regulation of Twist1, as well as the roles of Twist1 during glioma progression and recurrence, providing new revelations for its use as a potential drug target and glioma treatment research.

Gender-specific lncRNA-miRNA-mRNA regulatory network to reveal potential genes for primary open-angle glaucoma.

BACKGROUND: Investigation of biomarkers may facilitate understanding the mechanisms of primary open-angle glaucoma (POAG) and developing therapeutic targets. This study aimed to identify potential genes based on competing endogenous RNA (ceRNA) network for POAG. METHODS: Based on long noncoding RNAs (lncRNAs), microRNAs (miRNAs) and messenger RNAs (mRNAs) from the Gene Expression Omnibus (GEO) database, we identified differential expressed lncRNAs (DELs), differential expressed miRNAs (DEMis) and differential expressed mRNAs (DEMs) and then constructed a ceRNA network. Through weighted gene co-expression network analysis (WGCNA), we identified gender-specific genes for gender-associated ceRNA network construction, followed by the protein-protein interaction (PPI) network and functional enrichment analysis to screen hub genes and reveal their functions. The expression levels of hub genes were measured in steroid-induced ocular hypertension (SIOH) mice. RESULTS: A total of 175 DELs, 727 DEMs and 45 DEMis were screened between control and POAG samples. Seven modules were identified through WGCNA and one module was associated with gender of POAG patients. We discovered 41 gender-specific genes for gender-associated ceRNA construction and then identified 8 genes (NAV3, C1QB, RXRB, P2RY4, ADAM15, VAV3, ZNF207 and TOP1), which were enriched in cell cycle-related pathways and immune-related pathways. C1QB, RXRB, Top1 and ZNF207 were highly interacted with other proteins. The expression levels of NAV3 and C1QB were downregulated in SIOH, while the levels of RXRB, P2RY4, ADAM15, VAV3, ZNF207 and TOP1 were upregulated in SIOH. CONCLUSION: This study identifies hub genes associated with the pathogenesis of gender-specific POAG and provides potential biomarkers for POAG.

RBP7 Regulated by EBF1 Affects Th2 Cells and the Oocyte Meiosis Pathway in Bone Metastases of Bladder Urothelial Carcinoma.

BACKGROUND: Bladder urothelial carcinoma (BLCA) is a malignancy with a high incidence worldwide. One-third of patients may experience aggressive progression later on, and 70% of patients who have undergone surgical intervention will still suffer from metastasis. MATERIALS AND METHODS: RNA sequencing profiles of BLCA samples were obtained from The Cancer Genome Atlas (TCGA) database. Differential expression and univariate Cox regression analyses were performed to identify prognosis-related differentially expressed immune genes (DEIGs). Subsequently, a proportional hazards model of DEIGs was then constructed by univariate regression analysis. Differential expression and correlation analyses, CIBERSORT, Single Sample Gene Set Enrichment Analysis (ssGSEA), GSVA were conducted on transcription factors (TFs), immune cells/pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The regulation network was then constructed. Eventually, ATAC-seq, ChIP-seq, scRNA-seq, and multiple online databases were employed for further validation. RESULTS: A proportional hazards model of 31 DEIGs was constructed and risk score was calculated and proven to be a independent prognostic factor. Then 5 immune genes were characterized to be significantly correlated with bone metastasis, stage and TF expression simultaneously. 4 TFs were identified to be significantly correlated with prognosis and RBP7 expression. 5 immune cells/pathways were revealed to be significantly correlated with RBP7 expression. Only 1 KEGG pathway was identified to be significant in Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) analyses. The regulatory relationship was then constructed, in which the correlation between EBF1 and RBP7 (R = 0.677, p < 0.001), Th2 cells and RBP7 (R = 0.23, p < 0.001), the oocyte meiosis pathway and RBP7 (R = 0.14, p = 0.042) were the most statistically significant. The results were further confirmed by Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq), Chromatin Immunoprecipitation sequencing (ChIP-seq), single-cell RNA sequencing (scRNA-seq), and multiple online databases validation. CONCLUSIONS: This study revealed that the EBF1-RBP7 regulatory relationship had potential importance in the bone metastasis in BLCA through Th2 cells and the oocyte meiosis pathway.

Allelic variations of ClACO gene improve nitrogen uptake via ethylene-mediated root architecture in watermelon.

KEY MESSAGE: The ClACO gene encoding 1-aminocyclopropane-1-carboxylate oxidase enabled highly efficient 15N uptake in watermelon. Nitrogen is one of the most essential nutrient elements that play a pivotal role in regulating plant growth and development for crop productivity. Elucidating the genetic basis of high nitrogen uptake is the key to improve nitrogen use efficiency for sustainable agricultural productivity. Whereas previous researches on nitrogen absorption process are mainly focused on a few model plants or crops. To date, the causal genes that determine the efficient nitrogen uptake of watermelon have not been mapped and remains largely unknown. Here, we fine-mapped the 1-aminocyclopropane-1-carboxylate oxidase (ClACO) gene associated with nitrogen uptake efficiency in watermelon via bulked segregant analysis (BSA). The variations in the ClACO gene led to the changes of gene expression levels between two watermelon accessions with different nitrogen uptake efficiencies. Intriguingly, in terms of the transcript abundance of ClACO, it was concomitant with significant differences in ethylene evolutions in roots and root architectures between the two accessions and among the different genotypic offsprings of the recombinant BC2F1(ZJU132)-18. These findings suggest that ethylene as a negative regulator altered nitrogen uptake efficiency in watermelon by controlling root development. In conclusion, our current study will provide valuable target gene for precise breeding of 'green' watermelon varieties with high-nitrogen uptake efficiencies.

A rapid and highly sensitive multiple detection of human adenovirus type 3, type 7 and respiratory syncytial virus by recombinase-aided reverse transcription PCR.

BACKGROUND: Polymerase chain reaction (PCR) has been widely used for many pathogen detection. However, PCR technology still suffers from long detection time and insufficient sensitivity. Recombinase-aided amplification (RAA) is a powerful nucleic acid detection tool with high sensitivity and amplification efficiency, but its complex probes and inability of multiplex detection hinder the further application of this technology. METHODS: In this study, we developed and validated the multiplex reverse transcription recombinase-aided PCR (multiplex RT-RAP) assay for human adenovirus 3 (HADV3), human adenovirus 7 (HADV7), and human respiratory syncytial virus (HRSV) within 1 h with Human RNaseP protein as a reference gene to monitor the whole process. RESULTS: Using recombinant plasmids, the sensitivity of multiplex RT-RAP for the detection of HADV3, HADV7, and HRSV was 18, 3, and 18 copies per reaction, respectively. The multiplex RT-RAP showed no cross-reactivity with other respiratory viruses, demonstrating its good specificity. A total of 252 clinical specimens were tested by multiplex RT-RAP and the results were found to be consistent with those of corresponding RT-qPCR assays. After testing serial dilutions of selected positive specimens, the detection sensitivity of multiplex RT-RAP was two to eightfold higher than that of corresponding RT-qPCR. CONCLUSION: We conclude the multiplex RT-RAP is a robust, rapid, highly sensitive, and specific assay with the potential to be used in the screening of clinical samples with low viral load.

Pan-cancer analysis reveals signal transducer and activator of transcription (STAT) gene family as biomarkers for prognostic prediction and therapeutic guidance.

Background: The signal transducer and activator of transcription (STAT) gene family have been widely found to regulate cell proliferation, differentiation, apoptosis, and angiogenesis through complex signaling pathways, and thus impacting tumor formation and development in different types of tumor. However, the roles of STATs on prognostic prediction and therapeutic guidance in pan-cancer remain unexplored. Materials and Methods: The dataset of 33 types of TCGA tumor, para-carcinoma and normal tissues, was obtained from the UCSC Xena database, including the gene expression profiles in the formats of FPKM value, demographic characteristics, clinical information, and survival data of STATs. Differential expression and co-expression analyses, WGCNA, clinical relevance analysis, immune subtype analysis, tumor stemness analysis, tumor purity analysis, immune infiltration analysis, immunotherapy related analysis, tumor mutation related analysis, and drug sensitivity analysis were performed by R software. Results: Differential expression of STAT1 was found between normal and BRCA tissues (p < 0.001, log2FC = 0.895). Additionally, the strongest correlation among STATs lied between STAT1 and STAT2 (correlation coefficient = 0.6). Moreover, high expression levels of STAT1 (p = 0.031) were revealed to be notably correlated with poor prognosis in KIRP. In addition, STAT1 expressed the highest value in immune subtypes C1, C2, C3, and C6 in LUAD. What's more, strong negative correlations were demonstrated between expression of STAT6 and mDNAss and mRNAss of TGCT. Additionally, STAT4 expression was characterized to be significantly negatively correlated with tumor purity of the majority of cancer types. Moreover, STAT1 and STAT3 were shown to be generally high-expressed in pan-cancer myeloid cells, and STATs all had positive correlation with the infiltration of the majority of immune cells. In addition, STATs were revealed to be closely linked with immunotherapy response. What's more, STAT4 expression was identified to have a strong negative correlation with TMB value in DLBC. Last but not least, positive correlations were accessed between STAT5 and sensitivity of Nelarabine (cor = 0.600, p < 0.001). Conclusion: In the present study, we identified STATs as biomarkers for prognostic prediction and therapeutic guidance in pan-cancer. Hopefully our findings could provide a valuable reference for future STATs research and clinical applications.

Development of field-applicable endogenous internally controlled recombinase-aided amplification (EIC-RAA) assays for the detection of human papillomavirus genotypes 6 and 11 using sample releasing agent.

Objective: Human papillomavirus (HPV) 6 and 11 are the two most common low-risk HPV subtypes, accounting for more than 90% of condyloma acuminatum. A simple, accurate and rapid screening method to be applied in community-level hospitals is in high demand. Methods: Endogenous internally controlled recombinase-assisted amplification (EIC-RAA) assays for HPV6 and 11 were performed in a single closed-tube at 39 °C within 30 min. The sensitivity and specificity of EIC-RAA were examined using recombinant plasmids and pre-tested HPV DNA. A total of 233 clinical samples were collected, and the DNA was extracted by traditional multi-step extraction, or sample releasing agent, before analysis by EIC-RAA. For comparison, HPV detection via Quantitative real-time PCR (qPCR) was also performed. Results: The sensitivity of EIC-RAA analysis was 10 copies/reaction for HPV6, 100 copies/reaction for HPV11, and 100 copies/reaction for the human ß-globin gene. No cross-reaction was observed with other HPV subtypes. Clinical performance of the EIC-RAA assay achieved a 100% of concordance rate with the commercial HPV qPCR kit. Further, the EIC-RAA assay achieved a 100% of concordance rate when using multi-step extracted DNA and sample releasing agent-processed DNA. Summary: The EIC-RAA assay for HPV6 and 11 detection possesses the advantages of accuracy, simplicity and rapidity, and demonstrates great potential to be used in community-level hospitals for field investigation.

A rational foundation for micheliolide-based combination strategy by targeting redox and metabolic circuit in cancer cells.

Accumulating evidence has supported that targeting oxidative stress and metabolic alterations of cancer is an effective strategy to combat cancer. We previously reported that Dimethylaminomicheliolide (DMAMCL) and its active metabolite micheliolide (MCL) can cause oxidative stress and cell death in leukemia and glioblastoma. However, the detailed mechanism underlying MCL or DMAMCL triggered oxidative stress remains elusive. Herein, using leukemia HL60 cells and glioblastoma U118MG cells as models, we found that MCL-induced oxidative stress is mainly mediated by reduced glutathione (GSH). Overproduced reactive oxygen species (ROS) can lead to oxidative damage to mitochondrial, impairing the ability of the tricarboxylic acid (TCA) cycle and causing dysfunction of mitochondrial respiratory chain. On the other hand, the depletion of GSH activates GSH biosynthesis pathway and has possibility to give rise to more GSH to scavenge ROS in cancer cells. Targeting this redox and metabolic circuit, we identified L-buthionine sulfoximine (BSO), an inhibitor in GSH biosynthesis, as an agent that can enhance MCL regimen to inhibit GSH compensatory event and thereby further facilitate cancer cell oxidative stress. Together, these results illustrate that targeting redox and metabolic pathway by MCL/DMAMCL combination with BSO is a potent therapeutic intervention for the treatments of glioblastoma and acute-myelocytic leukemia.

The Added Value of a Computer-Aided Diagnosis System in Differential Diagnosis of Breast Lesions by Radiologists With Different Experience.

OBJECTIVES: To evaluate the value of the computer-aided diagnosis system, S-Detect (based on deep learning algorithm), in distinguishing benign and malignant breast masses and reducing unnecessary biopsy based on the experience of radiologists. METHODS: From February 2018 to March 2019, 266 breast masses in 192 women were included in our study. Ultrasound (US) examination, including S-Detect technique, was performed by the radiologist with about 10 years of clinical experience in breast US imaging. US images were analyzed by four other radiologists with different experience in breast imaging (radiologists 1, 2, 3, and 4 with 1, 4, 9, and 20 years, respectively) according to their clinical experience (with and without the results of S-Detect). Diagnostic capabilities and unnecessary biopsy of radiologists and radiologists combined with S-Detect were compared and analyzed. RESULTS: After referring to the results of S-Detect, the changes made by less experienced radiologists were greater than experienced radiologists (benign or malignant, 44 vs 22 vs 14 vs 2; unnecessary biopsy, 34 vs 25 vs 10 vs 5). When combined with S-Detect, less experienced radiologists showed significant improvement in accuracy, specificity, positive predictive value, negative predictive value, and area under curve (P < .05), but not for experienced radiologists (P > .05). Similarly, the unnecessary biopsy rate of less experienced radiologists decreased significantly (44.4% vs 32.7%, P = .006; 36.8% vs 28.2%, P = .033), but not for experienced radiologists (P > .05). CONCLUSIONS: Less experienced radiologists rely more on S-Detect software. And S-Detect can be an effective decision-making tool for breast US, especially for less experienced radiologists.

Antibody-dependent cellular cytotoxicity response to SARS-CoV-2 in COVID-19 patients.

Antibody-dependent cellular cytotoxicity (ADCC) responses to viral infection are a form of antibody regulated immune responses mediated through the Fc fragment. Whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) triggered ADCC responses contributes to COVID-19 disease development is currently not well understood. To understand the potential correlation between ADCC responses and COVID-19 disease development, we analyzed the ADCC activity and neutralizing antibody response in 255 individuals ranging from asymptomatic to fatal infections over 1 year post disease. ADCC was elicited by 10 days post-infection, peaked by 11-20 days, and remained detectable until 400 days post-infection. In general, patients with severe disease had higher ADCC activities. Notably, patients who had severe disease and recovered had higher ADCC activities than patients who had severe disease and deceased. Importantly, ADCC activities were mediated by a diversity of epitopes in SARS-COV-2-infected mice and induced to comparable levels against SARS-CoV-2 variants of concern (VOCs) (B.1.1.7, B.1.351, and P.1) as that against the D614G mutant in human patients and vaccinated mice. Our study indicates anti-SARS-CoV-2 ADCC as a major trait of COVID-19 patients with various conditions, which can be applied to estimate the extra-neutralization level against COVID-19, especially lethal COVID-19.

SARS-CoV-2 501Y.V2 variants lack higher infectivity but do have immune escape.

The 501Y.V2 variants of SARS-CoV-2 containing multiple mutations in spike are now dominant in South Africa and are rapidly spreading to other countries. Here, experiments with 18 pseudotyped viruses showed that the 501Y.V2 variants do not confer increased infectivity in multiple cell types except for murine ACE2-overexpressing cells, where a substantial increase in infectivity was observed. Notably, the susceptibility of the 501Y.V2 variants to 12 of 17 neutralizing monoclonal antibodies was substantially diminished, and the neutralization ability of the sera from convalescent patients and immunized mice was also reduced for these variants. The neutralization resistance was mainly caused by E484K and N501Y mutations in the receptor-binding domain of spike. The enhanced infectivity in murine ACE2-overexpressing cells suggests the possibility of spillover of the 501Y.V2 variants to mice. Moreover, the neutralization resistance we detected for the 501Y.V2 variants suggests the potential for compromised efficacy of monoclonal antibodies and vaccines.

Pharmacological Inhibition of BAD Ser99 Phosphorylation Enhances the Efficacy of Cisplatin in Ovarian Cancer by Inhibition of Cancer Stem Cell-like Behavior.

Platinum-based chemotherapy has been the standard treatment for ovarian cancer patients for approximately four decades. However, the prognosis of patients with advanced ovarian carcinoma remains dismal, mainly attributed to both dose-limiting toxicities of cisplatin and the high rate of chemo-resistant disease recurrence. Herein, both patient-derived and experimentally generated cisplatin-sensitive and -resistant ovarian cancer cell line models were used to delineate BADSer99 phosphorylation as an actionable target in ovarian cancer. BADSer99 phosphorylation was negatively associated with cisplatin sensitivity in ovarian cancer, and the inhibition of BADSer99 phosphorylation by point mutation induced apoptosis and reduced cisplatin IC50. In addition, BAD phosphorylation was also shown to be associated with cancer stem cell-like properties. Henceforth, a novel small molecule which inhibits BAD phosphorylation specifically at Ser99 (NPB) was utilized. NPB promoted apoptosis and reduced 3D growth of bulk cancer cells and inhibited cancer stem cell-like properties in both cisplatin-sensitive and -resistant ovarian cancer cells. The combination of cisplatin with NPB exhibited synergistic effects in vitro. NPB in combination with cisplatin also achieved an improved outcome compared to either monotreatment in vivo, including suppression of the cancer stem cell population, an effect not observed with cisplatin treatment. Furthermore, NPB exhibited strong synergistic effects with the AKT inhibitor AZD5363, and significantly reduced its IC50 in cells resistant to cisplatin treatment. These findings identify BADSer99 phosphorylation as an actionable and pharmacologically relevant target to improve outcomes of cisplatin treated ovarian cancer.

The value of S-Detect in improving the diagnostic performance of radiologists for the differential diagnosis of thyroid nodules.

AIMS: To compare the diagnostic value of S-Detect (a computer aided diagnosis system using deep learning) in differentiating thyroid nodules in radiologists with different experience and to assess if S-Detect can improve the diagnostic performance of radiologists. MATERIALS AND METHODS: Between February 2018 and October 2019, 204 thyroid nodules in 181 patients were included. An experienced radiologist performed ultrasound for thyroid nodules and obtained the result of S-Detect. Four radiologists with different experience on thyroid ultrasound (Radiologist 1, 2, 3, 4 with 1, 4, 9, 20 years, respectively) analyzed the conventional ultrasound images of each thyroid nodule and made a diagnosis of "benign" or "malignant" based on the TI-RADS category. After referring to S-Detect results, they re-evaluated the diagnoses. The diagnostic performance of radiologists was analyzed before and after referring to the results of S-Detect. RESULTS: The accuracy, sensitivity, specificity, positive predictive value and negative predictive value of S-Detect were 77.0, 91.3, 65.2, 68.3 and 90.1%, respectively. In comparison with the less experienced radiologists (radiologist 1 and 2), S-Detect had a higher area under receiver operating characteristic curve (AUC), accuracy and specificity (p <0.05). In comparison with the most experienced radiologist, the diagnostic accuracy and AUC were lower (p<0.05). In the less experienced radiologists, the diagnostic accuracy, specificity and AUC were significantly improved when combined with S-Detect (p<0.05), but not for experienced radiologists (radiologist 3 and 4) (p>0.05). CONCLUSIONS: S-Detect may become an additional diagnostic method for the diagnosis of thyroid nodules and improve the diagnostic performance of less experienced radiologists.

Selective and sensitive detection of chronic myeloid leukemia using fluorogenic DNAzyme probes.

One of the major challenges facing the early diagnosis of chronic myelogenous leukemia (CML) patients today is enhancing the simplicity, rapidness, sensitivity and specificity of detection assay for easy clinical implementation. RNA-cleaving fluorogenic DNAzymes (RFDs) are single-stranded DNA molecules with catalytic activity and can produce fluorescent signals when combined with specific targets. As K562 cells were the first established human immortalized myelogenous leukemia line, we try to screen several RFDs using the crude extracellular mixture of K562 cells through the SELEX process. We obtained an RFD probe A1-3 that is able to distinguish K562 cells from other tumor cell lines. 10 nM of A1-3 can induce an increase of detectable fluorescence signal. Moreover, the RFD assay system can work well for target detection in complex serum matrix. The optimized RFD assay system with low cost also has a desirable ability to exactly distinguish K562 cells after truncation of 20 bases in the 5'end of A1-3. This study is the first report to investigate the RFD system for detection of K562 cells using cell culture supernatants as the complex target. This RFD assay system could potentially be applied for the diagnosis of CML.

Bromodomains and Extra-Terminal (BET) Inhibitor JQ1 Suppresses Proliferation of Acute Lymphocytic Leukemia by Inhibiting c-Myc-Mediated Glycolysis.

BACKGROUND Acute lymphocytic leukemia (ALL) is a common blood cancer which induces high mortality in children. Bromodomains and extra-terminal (BET) protein inhibitors, such as JQ1 and ARV-825, are promising cancer therapeutic agents that can be used by targeting c-Myc. A recent work reported that JQ1 effectively attenuates ALL in vitro by suppressing cell proliferation and accelerating apoptosis. The purpose of this research was to probe into the potential mechanism of how JQ1 inhibits ALL cell proliferation in vitro. MATERIAL AND METHODS Cell viability of ALL cells were measured by CTG after treatment by JQ1. Cell cycle analysis was done by EdU and PI staining. Cell apoptosis was assessed by Annexin V/PI staining. Glycolysis was detected using Seahorse and LC-MS kits. The expression of glycolytic rate-limiting enzymes was assessed by RNA-seq, qRT-PCR, and Western blot. RESULTS JQ1 suppressed cell proliferation by arresting the cell cycle and inducing the apoptosis of acute lymphocytic leukemia cells. JQ1 inhibited cell proliferation of B-ALL cells by restraining glycolysis. Conversely, the cell cycle block of B-ALL cells induced by JQ1 was partially abolished after pretreatment with 2-Deoxy-D-glucose (2-DG), an inhibitor of glycolysis. Furthermore, JQ1 restrained the glycolysis of B-ALL cell lines by remarkably downregulating the rate-limiting enzymes of glycolysis, such as hexokinase 2, phosphofructokinase, and lactate dehydrogenase A. Moreover, the cell cycle arrest was reversed in B-ALL cells with overexpressed c-Myc treated by JQ1, which is involved in the enhancement of glycolysis. CONCLUSIONS The BET inhibitor JQ1 suppresses the proliferation of ALL by inhibiting c-Myc-mediated glycolysis, thus providing a new strategy for the treatment of ALL.

Comprehensive analysis of competitive endogenous RNA network in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. Growing evidence supports a role for noncoding RNAs (ncRNAs) in CRC. In particular, they form competitive endogenous RNA (ceRNA) networks involved in the regulation of mRNA expression. However, the role of these networks in the pathogenesis of CRC is not fully understood. The aim of this study was to elucidate the role of circRNA/lncRNA-miRNA-mRNA systems in CRC pathogenesis based on the construction of a ceRNA network. METHODS: RNA expression profiles were obtained from public datasets in the Gene Expression Omnibus (GEO) database and used for further analysis by online databases and tools. RESULTS: In total, 245 circRNAs, 1,666 lncRNAs, 5 miRNAs, and 934 mRNAs were differentially expressed in CRC samples. Functional enrichment analysis identified altered biological functions related to the mRNAs in the ceRNA network, and it was found that the oxytocin signaling pathway was significantly enriched (P<0.05) in genes with differential expression in CRC. Additionally, we established a protein-protein interaction (PPI) network and identified 10 hub genes for the construction of circRNA/lncRNA-miRNA-hub gene regulatory modules. CONCLUSIONS: We identified several ncRNAs with a possible pathogenetic role in CRC and built a CRC-specific ceRNA network. The results of our study provide novel insights into the molecular events implicated in CRC.

Pharmacological Inhibition of TFF3 Enhances Sensitivity of CMS4 Colorectal Carcinoma to 5-Fluorouracil through Inhibition of p44/42 MAPK.

Increased expression of trefoil factor 3 (TFF3) has been reported in colorectal carcinoma (CRC), being correlated with distant metastasis and poor clinical outcomes. Amongst the CRC subtypes, mesenchymal (CMS4) CRC is associated with the worst survival outcome. Herein, the functional roles of TFF3 and the pharmacological inhibition of TFF3 by a novel specific small molecule TFF3 inhibitor-2-amino-4-(4-(6-fluoro-5-methylpyridin-3-yl)phenyl)-5-oxo-4H,5H-pyrano[3,2-c]chromene-3-carbonitrile (AMPC) in CMS4 CRC was explored. Forced expression of TFF3 in CMS4 CRC cells promoted cell proliferation, cell survival, foci formation, invasion, migration, cancer stem cell like behaviour and growth in 3D Matrigel. In contrast, siRNA-mediated depletion of TFF3 or AMPC inhibition of TFF3 in CMS4 CRC cells decreased oncogenic behaviour as indicated by the above cell function assays. AMPC also inhibited tumour growth in vivo. The TFF3-stimulated oncogenic behaviour of CMS4 CRC cells was dependent on TFF3 activation of the p44/42 MAPK (ERK1/2) pathway. Furthermore, the forced expression of TFF3 decreased the sensitivity of CMS4 CRC cells to 5-fluorouracil (5-FU); while depleted TFF3 expression enhanced 5-FU sensitivity in CMS4 CRC cells. 5-FU treatment induced TFF3 expression in CMS4 CRC cells. AMPC, when used in combination with 5-FU in CMS4 CRC cells exhibited a synergistic inhibitory effect. In summary, this study provides functional evidence for TFF3 as a therapeutic target in CMS4 CRC.