MMP1, IL-1ß, sTNFR-1, and IL-6 are prognostic factors for patients with unresectable or metastatic renal cell carcinoma treated with immune checkpoint inhibitors.

BACKGROUND: Few studies have reported reliable prognostic factors for immune checkpoint inhibitors (ICIs) in renal cell carcinoma (RCC). Therefore, we investigated prognostic factors in patients treated with ICIs for unresectable or metastatic RCC. METHODS: We included 43 patients who received ICI treatment for RCC between January 2018 and October 2021. Blood samples were drawn before treatment, and 73 soluble factors in the plasma were analyzed using a bead-based multiplex assay. We examined factors associated with progression-free survival (PFS), overall survival (OS), and immune-related adverse events (irAE) using the Chi-squared test, Kaplan-Meier method, and the COX proportional hazards model. RESULTS: Patients exhibited a median PFS and OS of 212 and 783 days, respectively. Significant differences in both PFS and OS were observed for MMP1 (PFS, p < 0.001; OS, p = 0.003), IL-1ß (PFS, p = 0.021; OS, p = 0.008), sTNFR-1 (PFS, p = 0.017; OS, p = 0.005), and IL-6 (PFS, p = 0.004; OS, p < 0.001). Multivariate analysis revealed significant differences in PFS for MMP1 (hazard ratio [HR] 5.305, 95% confidence interval [CI], 1.648-17.082; p = 0.005) and OS for IL-6 (HR 23.876, 95% CI, 3.426-166.386; p = 0.001). Moreover, 26 patients experienced irAE, leading to ICI discontinuation or withdrawal. MMP1 was significantly associated with irAE (p = 0.039). CONCLUSION: MMP1 may be associated with severe irAE, and MMP1, IL-1ß, sTNFR-1, and IL-6 could serve as prognostic factors in unresectable or metastatic RCC treated with ICIs. MMP1 and IL-6 were independent predictors of PFS and OS, respectively. Thus, inhibiting these soluble factors may be promising for enhancing antitumor responses in patients with RCC treated with ICIs.

Regioselective Deacetylation of Peracetylated Deoxy-C-glycopyranosides by Boron Trichloride (BCl3).

A general approach for regioselective deacetylation at sugar 3-OH of peracetylated 6-deoxy-C-glucopyranosides mediated by BCl3 was developed. The approach could be extended to other sugar-derived 6-deoxy-C-glycopyranosides, such as those derived from mannose, galactose, and rhamnose, with deacetylation occurring at varied sugar hydroxyl groups, and further extended to 4-deoxy-C-glucopyranosides with deacetylation occurring at sugar 3-OH. The approach would enable access to synthetically challenging carbohydrate derivatives. A possible mechanism of the regioselectivity was proposed.

Enhancing Mass spectrometry-based tumor immunopeptide identification: machine learning filter leveraging HLA binding affinity, aliphatic index and retention time deviation.

Accurately identifying neoantigens is crucial for developing effective cancer vaccines and improving tumor immunotherapy. Mass spectrometry-based immunopeptidomics has emerged as a promising approach to identifying human leukocyte antigen (HLA) peptides presented on the surface of cancer cells, but false-positive identifications remain a significant challenge. In this study, liquid chromatography-tandem mass spectrometry-based proteomics and next-generation sequencing were utilized to identify HLA-presenting neoantigenic peptides resulting from non-synonymous single nucleotide variations in tumor tissues from 18 patients with renal cell carcinoma or pancreatic cancer. Machine learning was utilized to evaluate Mascot identifications through the prediction of MS/MS spectral consistency, and four descriptors for each candidate sequence: the max Mascot ion score, predicted HLA binding affinity, aliphatic index and retention time deviation, were selected as important features in filtering out identifications with inadequate fragmentation consistency. This suggests that incorporating rescoring filters based on peptide physicochemical characteristics could enhance the identification rate of MS-based immunopeptidomics compared to the traditional Mascot approach predominantly used for proteomics, indicating the potential for optimizing neoantigen identification pipelines as well as clinical applications.

Serum MYCN as a predictive biomarker of prognosis and therapeutic response in the prevention of hepatocellular carcinoma recurrence.

The proto-oncogene MYCN expression marked a cancer stem-like cell population in hepatocellular carcinoma (HCC) and served as a therapeutic target of acyclic retinoid (ACR), an orally administered vitamin A derivative that has demonstrated promising efficacy and safety in reducing HCC recurrence. This study investigated the role of MYCN as a predictive biomarker for therapeutic response to ACR and prognosis of HCC. MYCN gene expression in HCC was analyzed in the Cancer Genome Atlas and a Taiwanese cohort (N = 118). Serum MYCN protein levels were assessed in healthy controls (N = 15), patients with HCC (N = 116), pre- and post-surgical patients with HCC (N = 20), and a subset of patients from a phase 3 clinical trial of ACR (N = 68, NCT01640808). The results showed increased MYCN gene expression in HCC tumors, which positively correlated with HCC recurrence in non-cirrhotic or single-tumor patients. Serum MYCN protein levels were higher in patients with HCC, decreased after surgical resection of HCC, and were associated with liver functional reserve and fibrosis markers, as well as long-term HCC prognosis (>4 years). Subgroup analysis of a phase 3 clinical trial of ACR identified serum MYCN as the risk factor most strongly associated with HCC recurrence. Patients with HCC with higher serum MYCN levels after a 4-week treatment of ACR exhibited a significantly higher risk of recurrence (hazard ratio 3.27; p = .022). In conclusion, serum MYCN holds promise for biomarker-based precision medicine for the prevention of HCC, long-term prognosis of early-stage HCC, and identification of high-response subgroups for ACR-based treatment.

Immune mediators as predictive biomarkers for anti-PD-1 antibody therapy in urothelial carcinoma.

Introduction: This study aimed to identify immune mediators, including cytokines, chemokines, and growth factors, in the plasma for predicting treatment efficacy and immune-related adverse events (irAEs) in advanced urothelial carcinoma (aUC) treated with immune checkpoint inhibitors (ICIs). Methods: We enrolled 57 patients with aUC who were treated with the anti-programmed cell death protein 1 (PD-1) antibody pembrolizumab after the failure of platinum-based chemotherapy between February 2018 and December 2020. Plasma levels of 73 soluble immune mediators were measured before and 6 weeks after initiating pembrolizumab therapy. The association of estimated soluble immune mediators with clinical outcomes, including overall survival (OS), progression-free survival (PFS), anti-tumor responses, and irAEs, were statistically evaluated. Results: In the multivariate analysis, levels of 18 factors at baseline and 12 factors during treatment were significantly associated with OS. Regarding PFS, baseline levels of 17 factors were significantly associated with PFS. Higher levels of interleukin (IL)-6, IL-8, soluble tumor necrosis factor receptor 1 (sTNF-R1), and IL-12 (p40), both at baseline and post-treatment, were significantly associated with worse OS. Conversely, low IL-6 and high TWEAK levels at baseline were associated with irAEs. Among identified factors, interferon (IFN) γ and IL-12 (p40) were repeatedly identified; high baseline levels of these factors were risk factors for worse OS and PFS, as well as progressive disease. Notably, using correlation and principal component analysis, factors significantly associated with clinical outcomes were broadly classified into three groups exhibiting similar expression patterns. Discussion: Measuring plasma levels of soluble immune mediators, such as IL-6, IL-8, sTNF-R1, IFNγ, and IL-12 (p40), could be recommended for predicting prognosis and irAEs in ICI-treated patients with aUC.

Machine learning for prediction of immunotherapeutic outcome in non-small-cell lung cancer based on circulating cytokine signatures.

BACKGROUND: Immune checkpoint inhibitor (ICI) therapy has substantially improved the overall survival (OS) in patients with non-small-cell lung cancer (NSCLC); however, its response rate is still modest. In this study, we developed a machine learning-based platform, namely the Cytokine-based ICI Response Index (CIRI), to predict the ICI response of patients with NSCLC based on the peripheral blood cytokine profiles. METHODS: We enrolled 123 and 99 patients with NSCLC who received anti-PD-1/PD-L1 monotherapy or combined chemotherapy in the training and validation cohorts, respectively. The plasma concentrations of 93 cytokines were examined in the peripheral blood obtained from patients at baseline (pre) and 6 weeks after treatment (early during treatment: edt). Ensemble learning random survival forest classifiers were developed to select feature cytokines and predict the OS of patients undergoing ICI therapy. RESULTS: Fourteen and 19 cytokines at baseline and on treatment, respectively, were selected to generate CIRI models (namely preCIRI14 and edtCIRI19), both of which successfully identified patients with worse OS in two completely independent cohorts. At the population level, the prediction accuracies of preCIRI14 and edtCIRI19, as indicated by the concordance indices (C-indices), were 0.700 and 0.751 in the validation cohort, respectively. At the individual level, patients with higher CIRI scores demonstrated worse OS [hazard ratio (HR): 0.274 and 0.163, and p<0.0001 and p=0.0044 in preCIRI14 and edtCIRI19, respectively]. By including other circulating and clinical features, improved prediction efficacy was observed in advanced models (preCIRI21 and edtCIRI27). The C-indices in the validation cohort were 0.764 and 0.757, respectively, whereas the HRs of preCIRI21 and edtCIRI27 were 0.141 (p<0.0001) and 0.158 (p=0.038), respectively. CONCLUSIONS: The CIRI model is highly accurate and reproducible in determining the patients with NSCLC who would benefit from anti-PD-1/PD-L1 therapy with prolonged OS and may aid in clinical decision-making before and/or at the early stage of treatment.

CircRNA CircABCB1 Diminishes the Sensitivity of Breast Cancer Cells to Docetaxel by Sponging MiR-153-3p.

Resistance to docetaxel is a major problem to the success of docetaxel-based therapies for breast cancer. The present study was to identify the role of circABCB1 in altering the docetaxel resistance properties. Reverse transcription-quantitative PCR (qRT-PCR) was performed to quantify circABCB1 and miR-153-3p. The effects of circABCB1 on the viability, apoptosis and migration/invasion of docetaxel-resistant and -sensitive cells were investigated by cell function experiments, including Cell Counting Kit-8 and Transwell assays. Correlation between circABCB1 and the docetaxel-treated outcome was analyzed by multivariate Cox regression analysis, in addition to Kaplan-Meier analysis of time to treatment failure (TTF). The targeting relationship between circABCB1 and miR-153-3p was predicted and verified by dual-luciferase reporter assay and RNA immunoprecipitation. CircABCB1 was highly expressed in cancerous tissues, as well as the docetaxel-sensitive group and cells. The overexpression of circABCB1 contributed to cell viability, docetaxel-resistance and migration/invasion, but inhibited apoptosis. CircABCB1 can sponge miR-153-3p. CircABCB1 contributed to the docetaxel resistance of breast cancer, maybe via the miR-153-3p.

Clinical roles of soluble PD-1 and PD-L1 in plasma of NSCLC patients treated with immune checkpoint inhibitors.

INTRODUCTION: Immune checkpoint inhibitors (ICIs) have significantly improved the prognosis of non-small cell lung cancer (NSCLC). However, only a limited proportion of patients can benefit from this therapy, and clinically useful predictive biomarkers remain to be elucidated. METHODS: Blood was collected from 189 patients with NSCLC before and six weeks after the initiation of ICI treatment (anti-PD-1 or anti-PD-L1 antibody). Soluble PD-1 (sPD-1) and PD-L1 (sPD-L1) in plasma before and after treatment were analyzed to evaluate their clinical significance. RESULTS: Cox regression analysis demonstrated that higher sPD-L1 levels before treatment significantly predicted unfavorable progression-free survival (PFS; HR 15.4, 95% CI 1.10-86.7, P = 0.009) and overall survival (OS; HR 11.4, 95% CI 1.19-52.3, P = 0.007) in NSCLC patients treated with ICI monotherapy (n = 122) but not in those treated with ICIs combined with chemotherapy (n = 67: P = 0.729 and P = 0.155, respectively). In addition, higher sPD-1 levels after treatment were significantly associated with better OS (HR 0.24, 95% CI 0.06-0.91, P = 0.037) in patients treated with anti-PD-1 monotherapy, whereas higher sPD-L1 levels after treatment were significantly associated with worse PFS (HR 6.09, 95% CI 1.42-21.0, P = 0.008) and OS (HR 42.6, 95% CI 6.83-226, P < 0.001). The levels of sPD-L1 at baseline closely correlated with those of other soluble factors, such as sCD30, IL-2Ra, sTNF-R1, and sTNF-R2, which are known to be released from the cell surface by zinc-binding proteases ADAM10/17. CONCLUSIONS: These findings suggest the clinical significance of pretreatment sPD-L1 as well as posttreatment sPD-1 and sPD-L1 in NSCLC patients treated with ICI monotherapy.

circRNA_0001006 predicts prognosis and regulates cellular processes of triple-negative breast cancer via miR-424-5p.

BACKGROUND: circular RNAs (circRNAs) have been considered novel biomarker candidates for human cancers, such as triple-negative breast cancer (TNBC). circ_0001006 was identified as a differentially expressed circRNA in metastatic breast cancer, but its significance and function in TNBC were unclear. The significance of circ_0001006 in TNBC was assessed and exploring its potential molecular mechanism to provide a therapeutic target for TNBC. RESULTS: circ_0001006 showed significant upregulation in TNBC and close association with patients' histological grade, Ki67 level, and TNM stage. Upregulated circ_0001006 could predict a worse prognosis and high risk of TNBC patients. In TNBC cells, silencing circ_0001006 suppressed cell proliferation, migration, and invasion. In mechanism, circ_0001006 could negatively regulate miR-424-5p, which mediated the inhibition of cellular processes by circ_0001006 knockdown. CONCLUSIONS: Upregulated circ_0001006 in TNBC served as a poor prognosis predictor and tumor promoter via negatively regulating miR-424-5p.

LncRNA-NEAT1 inhibits the occurrence and development of pancreatic cancer through spongy miR-146b-5p/traf6.

To investigate the inhibitory effect of LNCNA-NEA1 on pancreatic cancer development and progression via spongiosa miR-146b-5p/TRAF6, 60 pancreatic cancer patients diagnosed from December 2017 to December 2019 were selected as a general source of information. Real-time fluorescence quantitative polymerase chain reaction (RTFQ-PCR) was used to detect the expression level of NEAT1 in cancerous and adjacent non-cancerous tissues. Cell counting kit-8 (CCK-8) and transwell were used to determine the effect of LNCNA-NEA1 on the proliferation and migration of pancreatic cancer cells (Panc-1). The results of dual luciferase reporter gene assay showed that nea 1 could target and regulate the expression of spongy miR-146b-5p/TRAF6, and reducing the expression of spongy miR-146b-5p/TRAF6 could reverse the inhibitory effects of nea 1-siRNA on proliferation, migration and invasion of pancreatic cancer cells. Therefore, it was concluded that knockdown of nea 1 could inhibit the proliferation, migration and invasion of pancreatic cancer cells by upregulating the level of miR-146b-5p/TRAF6, and the expression of lnc RNA-nea 1 could be used as an indicator for preoperative diagnosis and postoperative prognosis of pancreatic cancer patients. .

Iodine-Modified Ag NPs for Highly Sensitive SERS Detection of Deltamethrin Residues on Surfaces.

It is essential to estimate the indoor pesticides/insecticides exposure risk since reports show that 80% of human exposure to pesticides occurs indoors. As one of the three major contamination sources, surface collected pesticides contributed significantly to this risk. Here, a highly sensitive liquid freestanding membrane (FSM) SERS method based on iodide modified silver nanoparticles (Ag NPs) was developed for quantitative detection of insecticide deltamethrin (DM) residues in solution phase samples and on surfaces with good accuracy and high sensitivity. The DM SERS spectrum from 500 to 2500 cm-1 resembled the normal Raman counterpart of solid DM. Similar bands at 563, 1000, 1165, 1207, 1735, and 2253 cm-1 were observed as in the literature. For the quantitative analysis, the strongest peak at 1000 cm-1 that was assigned to the stretching mode of the benzene ring and the deformation mode of C-C was selected. The peak intensity at 1000 cm-1 and the concentration of DM showed excellent linearity from 39 to 5000 ppb with a regression equation I = 649.428 + 1.327 C (correlation coefficient R2 = 0.991). The limit of detection (LOD) of the DM was found to be as low as 11 ppb. Statistical comparison between the proposed and the HPLC methods for the analysis of insecticide deltamethrin (DM) residues in solution phase samples showed no significant difference. DM residue analysis on the surface was mimicked by dropping DM pesticide on the glass surface. It is found that DM exhibited high residue levels up to one week after exposure. This proposed SERS method could find application in the household pesticide residues analysis.

Circulating IL-6 and not its circulating signaling components sIL-6R and sgp130 demonstrate clinical significance in NSCLC patients treated with immune checkpoint inhibitors.

Introduction: Clinical roles of plasma IL-6 levels have been reported in patients with various cancers, including non-small cell lung cancer (NSCLC), treated with immune checkpoint inhibitors (ICIs). However, the roles of other IL-6 signaling components, soluble IL-6 receptor (sIL-6R) and soluble gp130 (sgp130), in the plasma have not been elucidated. Methods: Blood was collected from 106 patients with NSCLC before initiation of ICI treatment (anti-PD-1 or anti-PD-L1 antibody). Plasma levels of IL-6, sIL-6R, sgp130, and their complexes were assessed by Cox regression hazard model to evaluate their clinical significance. The clinical role of IL-6 or IL-6R genetic polymorphisms was also analyzed. Results: Cox regression analysis showed that higher plasma IL-6 levels significantly predicted unfavorable overall survival (OS; hazard ratio [HR] 1.34, 95% confidence interval [CI] 1.05-1.68, p = 0.012) in NSCLC patients treated with ICIs. However, plasma sIL-6R and sgp130 levels showed no prognostic significance (p = 0.882 and p = 0.934, respectively). In addition, the estimated concentrations of binary IL-6:sIL-6R and ternary IL-6:sIL-6R:sgp130 complexes and their ratios (binary/ternary complex) were not significantly associated with OS (p = 0.647, p = 0.727, and p = 0.273, respectively). Furthermore, the genetic polymorphisms of IL-6 (-634G>C) and IL-6R (48892A>C) showed no clinical role by Kaplan-Meier survival analysis (p = 0.908 and p = 0.639, respectively). Discussion: These findings demonstrated the clinical significance of plasma levels of IL-6, but not of other IL-6 signaling components, sIL-6R and sgp130, suggesting that classical IL-6 signaling, but not trans-signaling, may be related to anti-tumor immune responses in cancer patients treated with ICIs.

Proliferation, Metastasis, and Radiosensitivity of Nasopharyngeal Carcinoma Cells in the Expression and Effect of Kiwifruit Extract through the Regulation of miR-205-5p.

Background: Radix Actinidiae extract (RAE) has been shown to inhibit cancer in many studies, but its potential mechanism in nasopharyngeal cancer (NPC) progression remains unclear. Methods: NPC cells (SUNE1) were treated with different doses of RAE. For transfection, SUNE1 cells were transfected with the microRNA (miR)-205-5p inhibitor (anti-miR-205-5p) or mimic followed by treatment with 200 µg/mL RAE for 24 h. The MTT assay and colony formation assay were used to detect cell proliferation and radiosensitivity. The transwell assay was used to detect cell migration and invasion. The expression of miR-205-5p was detected by quantitative real-time PCR. The protein expression levels of matrix metalloproteinase-2 (MMP2) and matrix metalloproteinase-9 (MMP9) were detected by western blot analysis. Results: RAE inhibited NPC cell proliferation, migration, and invasion, while it enhanced radiosensitivity (P < 0.05). Also, RAE treatment decreased miR-205-5p expression, as well as MMP2 and MMP9 protein levels (P < 0.05). Anti-miR-205-5p transfection enhanced the effects of RAE on NPC cell proliferation, migration, invasion, and radiosensitivity (P < 0.05), while miR-205-5p mimic transfection had an opposite effect (P < 0.05). Conclusion: RAE might decrease miR-205-5p, thereby it inhibited NPC cell proliferation and metastasis and enhanced radiosensitivity.

lncRNA LINC000466 Predicts the Prognosis and Promotes the Progression of Triple-negative Breast Cancer via Modulating miR-539-5p.

BACKGROUND: Triple-negative breast cancer (TNBC) is one of the most malignant subtypes of breast cancer with an unsatisfied prognosis. Effective biomarkers could predict the risk and improve patients' survival. Whether LINC00466 possesses the potential to serve as a biomarker of the progression and prognosis of TNBC was evaluated. MATERIALS AND METHODS: A total of 122 TNBC patients were included in this study and provided paired clinical tissues. The expression of LINC00466 in TNBC was evaluated by RT-qPCR and evaluated the clinical significance with a series of statistical analyses. The biological effects and the mechanism were investigated in TNBC cells with CCK8, Transwell, and luciferase reporter assays. RESULTS: LINC00466 was significantly upregulated in TNBC and showed close association with the clinical features of patients, which indicates the development, and severity of patients. LINC00466 functioned as a prognostic biomarker predicting the survival of patients and a tumor promoter improving the proliferation, migration, and invasion of TNBC cells through sponging miR-539-5p. CONCLUSION: LINC00466 promotes the progression of TNBC via regulating miR-539-5p. The inhibition of LINC00466 might be a novel therapeutic strategy for TNBC.

The value of miR-510 in the prognosis and development of colon cancer.

PURPOSE: Colon cancer is one of the malignant tumors that threatens human health. miR-510 was demonstrated to play roles in the progression of various cancers; its dysregulation was speculated to be associated with the development of colon cancer. METHODS: One hundred and thirteen colon cancer patients participated in this research. With the help of RT-qPCR, the expression of miR-510 in collected tissues and cultured cells was analyzed. The association between miR-510 expression level and clinical features and prognosis of patients was evaluated. Moreover, the effects of miR-510 on cell proliferation, migration, and invasion of colon cancer were assessed by CCK8 and Transwell assay. RESULTS: miR-510 significantly upregulated in colon cancer tissues and cell lines relative to the adjacent normal tissues and colonic cells. The expression of miR-510 was significantly associated with the TNM stage and poor prognosis of patients, indicating miR-510 was involved in the disease progression and clinical prognosis of colon cancer. Additionally, the upregulation of miR-510 significantly promoted cell proliferation, migration, and invasion of colon cancer, while its knockdown significantly inhibited these cellular processes. SRCIN 1 was the direct target of miR-510 during its promoted effect on the development of colon cancer. CONCLUSION: The upregulation of miR-510 acts as an independent prognostic indicator and a tumor promoter by targeting SRCIN 1 in colon cancer, which provides novel therapeutic strategies for colon cancer.

Inhibition of Ganglioside Synthesis Suppressed Liver Cancer Cell Proliferation through Targeting Kinetochore Metaphase Signaling.

The incidence and mortality of liver cancer, mostly hepatocellular carcinoma (HCC), have increased during the last two decades, partly due to persistent inflammation in the lipid-rich microenvironment associated with lifestyle diseases, such as obesity. Gangliosides are sialic acid-containing glycosphingolipids known to be important in the organization of the membrane and membrane protein-mediated signal transduction. Ganglioside synthesis is increased in several types of cancers and has been proposed as a promising target for cancer therapy. Here, we provide evidence that ganglioside synthesis was increased in the livers of an animal model recapitulating the features of activation and expansion of liver progenitor-like cells and liver cancer (stem) cells. Chemical inhibition of ganglioside synthesis functionally suppressed proliferation and sphere growth of liver cancer cells, but had no impact on apoptotic and necrotic cell death. Proteome-based mechanistic analysis revealed that inhibition of ganglioside synthesis downregulated the expression of AURKA, AURKB, TTK, and NDC80 involved in the regulation of kinetochore metaphase signaling, which is essential for chromosome segregation and mitotic progression and probably under the control of activation of TP53-dependent cell cycle arrest. These data suggest that targeting ganglioside synthesis holds promise for the development of novel preventive/therapeutic strategies for HCC treatment.

Relaxometric learning: a pattern recognition method for T2 relaxation curves based on machine learning supported by an analytical framework.

Nuclear magnetic resonance (NMR)-based relaxometry is widely used in various fields of research because of its advantages such as simple sample preparation, easy handling, and relatively low cost compared with metabolomics approaches. However, there have been no reports on the application of the T2 relaxation curves in metabolomics studies involving the evaluation of metabolic mixtures, such as geographical origin determination and feature extraction by pattern recognition and data mining. In this study, we describe a data mining method for relaxometric data (i.e., relaxometric learning). This method is based on a machine learning algorithm supported by the analytical framework optimized for the relaxation curve analyses. In the analytical framework, we incorporated a variable optimization approach and bootstrap resampling-based matrixing to enhance the classification performance and balance the sample size between groups, respectively. The relaxometric learning enabled the extraction of features related to the physical properties of fish muscle and the determination of the geographical origin of the fish by improving the classification performance. Our results suggest that relaxometric learning is a powerful and versatile alternative to conventional metabolomics approaches for evaluating fleshiness of chemical mixtures in food and for other biological and chemical research requiring a nondestructive, cost-effective, and time-saving method.

Fish ecotyping based on machine learning and inferred network analysis of chemical and physical properties.

Functional diversity rather than species richness is critical for the understanding of ecological patterns and processes. This study aimed to develop novel integrated analytical strategies for the functional characterization of fish diversity based on the quantification, prediction and integration of the chemical and physical features in fish muscles. Machine learning models with an improved random forest algorithm applied on 1867 muscle nuclear magnetic resonance spectra belonging to 249 fish species successfully predicted the mobility patterns of fishes into four categories (migratory, territorial, rockfish, and demersal) with accuracies of 90.3-95.4%. Markov blanket-based feature selection method with an ecological-chemical-physical integrated network based on the Bayesian network inference algorithm highlighted the importance of nitrogen metabolism, which is critical for environmental adaptability of fishes in nutrient-rich environments, in the functional characterization of fish biodiversity. Our study provides valuable information and analytical strategies for fish home-range assessment on the basis of the chemical and physical characterization of fish muscle, which can serve as an ecological indicator for fish ecotyping and human impact monitoring.

MiR-106b-5p regulates the migration and invasion of colorectal cancer cells by targeting FAT4.

MicroRNA-106b-5p (miR-106b-5p) is involved in the development of many cancers including colorectal cancer (CRC), and FAT4 is correlated with regulation of growth and apoptosis of cancer cells. The present study aimed to investigate the relation between FAT4 and miR-106b-5p and the underlying mechanism of the two on the development of CRC. Quantitative real-time PCR (qRT-PCR) assay and Western blot (WB) analysis were performed to detect the expressions of messenger RNAs (mRNAs), microRNAs (miRNAs) and proteins. The viability of CRC cells was detected by cell counting kit-8 (CCK-8). Scratch test and transwell assay were performed to measure the migration and invasion of CRC cell. Tumor angiogenesis was simulated by in vitro angiogenesis experiment. Dual-luciferase reporter assay was performed to verify the targeting relation between miR-106b-5p and FAT4. The study found that the expression of FAT4 was down-regulated and that of miR-106b-5p was up-regulated in CRC tissues. Overexpression of FAT4 resulted in decreased proliferation, migration, invasion and angiogenesis of CRC cells, whereas silencing of FAT4 led to the opposite results. In rescue experiment, miR-106b-5p partially reversed the function of FAT4 in CRC cells, thus playing a carcinogenic role by targeting FAT4 in the CRC cells.