Regulatory microRNAs and phasiRNAs of paclitaxel biosynthesis in Taxus chinensis.

Paclitaxel (trade name Taxol) is a rare diterpenoid with anticancer activity isolated from Taxus. At present, paclitaxel is mainly produced by the semi-synthetic method using extract of Taxus tissues as raw materials. The studies of regulatory mechanisms in paclitaxel biosynthesis would promote the production of paclitaxel through tissue/cell culture approaches. Here, we systematically identified 990 transcription factors (TFs), 460 microRNAs (miRNAs), and 160 phased small interfering RNAs (phasiRNAs) in Taxus chinensis to explore their interactions and potential roles in regulation of paclitaxel synthesis. The expression levels of enzyme genes in cone and root were higher than those in leaf and bark. Nearly all enzyme genes in the paclitaxel synthesis pathway were significantly up-regulated after jasmonate treatment, except for GGPPS and CoA Ligase. The expression level of enzyme genes located in the latter steps of the synthesis pathway was significantly higher in female barks than in male. Regulatory TFs were inferred through co-expression network analysis, resulting in the identification of TFs from diverse families including MYB and AP2. Genes with ADP binding and copper ion binding functions were overrepresented in targets of miRNA genes. The miRNA targets were mainly enriched with genes in plant hormone signal transduction, mRNA surveillance pathway, cell cycle and DNA replication. Genes in oxidoreductase activity, protein-disulfide reductase activity were enriched in targets of phasiRNAs. Regulatory networks were further constructed including components of enzyme genes, TFs, miRNAs, and phasiRNAs. The hierarchical regulation of paclitaxel production by miRNAs and phasiRNAs indicates a robust regulation at post-transcriptional level. Our study on transcriptional and posttranscriptional regulation of paclitaxel synthesis provides clues for enhancing paclitaxel production using synthetic biology technology.

Artificial intelligence-based computer-aided diagnosis system supports diagnosis of lymph node metastasis in esophageal squamous cell carcinoma: A multicenter study.

Background: This study aimed to develop an artificial intelligence-based computer-aided diagnosis system (AI-CAD) emulating the diagnostic logic of radiologists for lymph node metastasis (LNM) in esophageal squamous cell carcinoma (ESCC) patients, which contributed to clinical treatment decision-making. Methods: A total of 689 ESCC patients with PET/CT images were enrolled from three hospitals and divided into a training cohort and two external validation cohorts. 452 CT images from three publicly available datasets were also included for pretraining the model. Anatomic information from CT images was first obtained automatically using a U-Net-based multi-organ segmentation model, and metabolic information from PET images was subsequently extracted using a gradient-based approach. AI-CAD was developed in the training cohort and externally validated in two validation cohorts. Results: The AI-CAD achieved an accuracy of 0.744 for predicting pathological LNM in the external cohort and a good agreement with a human expert in two external validation cohorts (kappa = 0.674 and 0.587, p < 0.001). With the aid of AI-CAD, the human expert's diagnostic performance for LNM was significantly improved (accuracy [95% confidence interval]: 0.712 [0.669-0.758] vs. 0.833 [0.797-0.865], specificity [95% confidence interval]: 0.697 [0.636-0.753] vs. 0.891 [0.851-0.928]; p < 0.001) among patients underwent lymphadenectomy in the external validation cohorts. Conclusions: The AI-CAD could aid in preoperative diagnosis of LNM in ESCC patients and thereby support clinical treatment decision-making.

Large scale preparation of midkine antisense oligonucleotides nanoliposomes by a cross-flow injection technique combined with ultrafiltration and high-pressure extrusion procedures.

The midkine antisense oligonucleotide (MK-ASODN, 5'-CCC CGG GCC GCC CTT CTT CA-3') nanoliposomes have been identified to suppress hepatocellular carcinoma (HCC) growth effectively, and have a great potential to be an effective target drug for HCC. In this study, a facile and reproducible method for large-scale preparation of MK-ASODN nanoliposomes followed by lyophilization has been developed successfully. Meanwhile, the MK-ASODN nanoliposomes characteristics, storage stability and their antitumor efficiency were studied. The mean particle size of MK-ASODN nanoliposomes were 229.43±15.11 nm, and the zeta potential were 29.7±1.1 mV. High entrapment efficiency values were achieved around 90%. Transmission electron microscopy images revealed spherical shaped nanoliposomes. Nanoliposomes allowed sustained MK-ASODN release for as long as 14 days. During 180 days of storage, freeze-dried nanoliposomes showed no significant change in the mean size, zeta potential, entrapment efficiency and drug release ratio. Regarding their antitumor efficiency, the in vitro proliferation of human liver cancer cells were significantly inhibited by the MK-ASODN nanoliposomes. Furthermore, the MK-ASOND nanoliposomes also significantly inhibited the growth of HCC in the mouse model. In summary, the results confirmed that this large-scale preparation of MK-ASOND nanoliposomes was facile and reproducible, and potentially, could speed up the application process of our MK-ASOND nanoliposomes for HCC therapy.

Molecular biomarkers of colorectal cancer: prognostic and predictive tools for clinical practice.

Colorectal cancer remains one of the most common types of cancer and leading causes of cancer death worldwide. Although we have made steady progress in chemotherapy and targeted therapy, evidence suggests that the majority of patients undergoing drug therapy experience severe, debilitating, and even lethal adverse drug events which considerably outweigh the benefits. The identification of suitable biomarkers will allow clinicians to deliver the most appropriate drugs to specific patients and spare them ineffective and expensive treatments. Prognostic and predictive biomarkers have been the subjects of many published papers, but few have been widely incorporated into clinical practice. Here, we want to review recent biomarker data related to colorectal cancer, which may have been ready for clinical use.

In vitro and in vivo suppression of hepatocellular carcinoma growth by midkine-antisense oligonucleotide-loaded nanoparticles.

AIM: To synthesize antisense oligonucleotides (ASODNs) of midkine (MK), package the ASODNs with nanoparticles, and to inhibit hepatocellular carcinoma (HCC) growth using these nanoparticles. METHODS: HepG2 cell proliferation was analyzed in vitro using the 3-(4,5-dimethythiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2Htetrazolium, inner salt assay. The in vivo activity of nanoparticles delivering the MK-ASODNs was analyzed by histopathological and immunohistochemical staining and quantitative real time polymerase chain reaction (PCR). RESULTS: The in vitro proliferation of HepG2 cells was significantly inhibited by the nanoparticles packaged with MK-ASODNs (NANO-ASODNs). Furthermore, the NANO-ASODNs significantly inhibited the growth of HCC in the mouse model. CONCLUSION: NANO-ASODNs can significantly suppress the growth of HCC in vitro and in vivo.

[Knockdown of PLK1 mRNA by special siRNA].

To study knockdown effect of small interfering RNA (siRNA) to PLK1 (Polo-like kinase 1) mRNA in colorectal cancer cell line SW480 and its mitosis and growth was changed. Ten special siRNA molecules were designed targeting different sites of PLK1 mRNA sequence and chemically synthesized. The siRNA molecules were transfected into SW480 by Oligofectamine. The gene mRNA level was assayed by Real-Time PCR. The changes of PLK1 protein, SW480 cell cycle and survival percentage was checked by Western-blot, Flow cytometry and Cell counter assays respectively. All 10 siRNA molecules knocked PLK1 mRNA down in different level. Of them P1, P4 and P9 showed over 80% knockdown efficiency and the others had more than 20% knockdown efficiency to PLK1 mRNA. The best knockdown effect over 95% of all groups was at 25 nmol/L of a mixture with P1, P4 and P9 siRNA equally. In this situation the protein was very less and the cells were blocked at G2 phase of cell cycle. After 72 h cell survival percentages were consistent with PKL1 mRNA level change by siRNA gradient concentration. The results showed that siRNA targeting PLK1 mRNA had effectively knocked PLK1 mRNA down in SW480 cell line. And a blended siRNAs held the best knockdown effect. The cell was blocked on the mitosis and growth.