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Background NCAPD3 is one of the three non-SMC subunits of condensin II complex, which plays an important role in the chromosome condensation and segregation during mitosis. Notably, elevated levels of NCAPD3 are found in many somatic cancers. However, the clinical role, biological functions of NCAPD3 in cancers especially in colorectal cancer (CRC) and the underlying molecular mechanisms remain poorly elucidated. Methods Clinical CRC and adjacent normal tissues were used to confirm the expression of NCAPD3. The association of NCAPD3 expression with clinicopathological characteristics and patient outcomes were analyzed by using online database. In vivo subcutaneous tumor xenograft model, NCAPD3 gene knockout following azoxymethane (AOM)/dextran sodium sulfate (DSS)-induced tumor mouse model, Co-IP, western blot, qRT-PCR, IHC, ChIP assays and cell functional assays were used to investigate the biological functions of NCAPD3 in CRC and the underlying molecular mechanisms. Results NCAPD3 was overexpressed in CRC tissues and positively correlated with poor prognosis of CRC patients. NCAPD3 knockout suppressed CRC development in AOM/DSS induced and xenograft mice models. Moreover, we found that NCAPD3 promoted aerobic glycolysis in CRC. Mechanistically, NCAPD3 up-regulated the level of c-Myc and interacted with c-Myc to recruit more c-Myc to the gene promoter of its downstream glycolytic regulators GLUT1, HK2, ENO1, PKM2 and LDHA, and finally enhanced cellular aerobic glycolysis. Also, NCAPD3 increased the level of E2F1 and interacted with E2F1 to recruit more E2F1 to the promoter regions of PDK1 and PDK3 genes, which resulted in the inhibition of PDH activity and TCA cycle. Conclusions Our data demonstrated that NCAPD3 promoted glucose metabolism reprogramming and enhanced Warburg effect in colorectal tumorigenesis and CRC progression. These findings reveal a novel mechanism underlying NCAPD3 mediated CRC cell growth and provide new targets for CRC treatment.

Phloretin is a flavonoid existed in various plants and has been reported to possess anticarcinogenic activity. However, the anticancer mechanism of phloretin in prostate cancer (PCa) remains unclear. Here, our in vitro and in vivo experimental data demonstrate that phloretin inhibits the phosphorylation and the activation of EGFR and then inhibits its downstream PI3K/AKT and MEK/ERK1/2 pathways in PCa cells. Inhibition of these two pathways further decreases expression of Sp1 by inhibiting Sp1 gene transcription, induces degradation of Sp1 protein by inhibiting GSK3β phosphorylation, suppresses nucleolin-enhanced translation of Sp1 mRNA by inhibiting nucleolin phosphorylation, and directly inactivates transcription activity of Sp1. Inhibition of Sp1 subsequently decreases the expression of Sp3/4, VEGF, and Survivin and then upregulates apoptosis-related proteins and downregulates cell cycle-related proteins in PCa cells. Finally, phloretin treatment in PCa cells induces cell growth inhibition and apoptosis, suggesting that phloretin may be an effective therapy compound in the treatment of prostate cancer.

A deep understanding of the effect of seasonal dietary changes on the nutrition and health of Père David’s deer in Dafeng Reserve will contribute greatly to Père David’s deer’s protection. In this reserve, there were three seasonal dietary regimes: feeding on naturally occurring plants (PLANT diet), silage (SILAGE diet), and a combination of natural plants and silage (COMB diet). To some extent, the COMB diet reflects the seasonal transition from silage to the all-natural plant diet, especially in early spring. However, little is known regarding the gut microbiota changes and metabolic consequences under the COMB diet. Based on 16S rRNA sequencing and ultra-high performance liquid chromatography combined with tandem mass spectrometry, the gut microbiota and fecal metabolites of Père David’s deer under these three diets were compared. Results showed the alpha diversity of the gut microbiota was significantly lower under the COMB diet compared to either the SILAGE or PLANT diets. Although no significant changes were observed in the core phyla, Firmicutes and Bacteroidetes, among the three dietary regimes, a significant lower abundance of several other phyla (Spirochaetes, Melainabacteria, Proteobacteria, and Verrucobacteria) was observed in the COMB diet compared to the SILAGE diet. A greater number of fecal metabolite differences was identified between the COMB and SILAGE or COMB and PLANT diets than between the SILAGE and PLANT diets, suggesting that the COMB diet had more of an effect on the metabolism of Père David’s deer. The integrated pathway analysis showed that several metabolic pathways were significantly affected by the different dietary regimes, such as tryptophan metabolism, vitamin metabolism, and the platelet activation pathways. These metabolic changes reflect the responses and adaptations of Père David’s deer to different diets. Taken overall, our data reveal the difference in the gut microbiota and metabolic pathways of Père David’s deer under three dietary regimes in Dafeng Reserve, which provides important information for Père David’s deer conservation.

Background Tumor metastasis is the main cause of death of cancer patients, and cancer stem cells (CSCs) is the basis of tumor metastasis. However, systematic analysis of the stemness of prostate cancer cells is still not abundant. In this study, we explore the effective factors related to the stemness of prostate cancer cells by comprehensively mining the multi-omics data from TCGA database. Methods Based on the prostate cancer transcriptome data in TCGA, gene expression modules that strongly relate to the stemness of prostate cancer cells are obtained with WGCNA and stemness scores. Copy number variation of stemness genes of prostate cancer is calculated and the difference of transcription factors between prostate cancer and normal tissues is evaluated by using CNV (copy number variation) data and ATAC-seq data. The protein interaction network of stemness genes in prostate cancer is constructed using the STRING database. Meanwhile, the correlation between stemness genes of prostate cancer and immune cells is analyzed. Results Prostate cancer with higher Gleason grade possesses higher cell stemness. The gene set highly related to prostate cancer stemness has higher CNV in prostate cancer samples than that in normal samples. Although the transcription factors of stemness genes have similar expressions, they have different contributions between normal and prostate cancer tissues; and particular transcription factors enhance the stemness of prostate cancer, such as PUM1, CLOCK, SP1, TCF12, and so on. In addition, the lower tumor immune microenvironment is conducive to the stemness of prostate cancer. CD8 + T cells and M1 macrophages may play more important role in the stemness of prostate cancer than other immune cells in the tumor microenvironment. Finally, EZH2 is found to play a central role in stemness genes and is negatively correlated with resting mast cells and positively correlated with activated memory CD4 + T cells. Conclusions Based on the systematic and combined analysis of multi-omics data, we find that high copy number variation, specific transcription factors, and low immune microenvironment jointly contribute to the stemness of prostate cancer cells. These findings may provide us new clues and directions for the future research on stemness of prostate cancer.

Maize (Zea mays L.), an important industrial material and food source, shows an astonishing environmental adaptation. A remarkable feature of its post-domestication adaptation from tropical to temperate environments is adaptation to a long photoperiod (LP). Many photoperiod-related genes have been identified in previous transcriptomics analysis, but proteomics shows less evidence for this mechanism of photoperiod response. In this study, we sampled newly expanded leaves of maize at the three- and six-leaf stages from an LP-sensitive introgression line H496, the donor CML288, LP-insensitive inbred line, and recurrent parent Huangzao4 (HZ4) grown under long days (15 h light and 9 h dark). To characterize the proteomic changes in response to LP, the iTRAQ-labeling method was used to determine the proteome profiles of plants exposed to LP. A total of 943 proteins differentially expressed at the three- and six-leaf stages in HZ4 and H496 were identified. Functional analysis was performed by which the proteins were classified into stress defense, signal transduction, carbohydrate metabolism, protein metabolism, energy production, and transport functional groups using the WEGO online tool. The enriched gene ontology categories among the identified proteins were identified statistically with the Cytoscape plugin ClueGO + Cluepedia. Twenty Gene Ontology terms showed the highest significance, including those associated with protein processing in the endoplasmic reticulum, splicesome, ribosome, glyoxylate, dicarboxylate metabolism, L-malate dehydrogenase activity, and RNA transport. In addition, for subcellular location, all proteins showed significant enrichment of the mitochondrial outer membrane. The sugars producted by photosynthesis in plants are also a pivotal metabolic output in the circadian regulation. The results permit the prediction of several crucial proteins to photoperiod response and provide a foundation for further study of the influence of LP treatments on the circadian response in short-day plants.

Background: Tumor metastasis is the main cause of death of cancer patients, and the existence of cancer stem cells is the basis of tumor metastasis. However, the systematic analysis of the stemness of prostate cancer cells is still not abundant. This article explores the effective factors that lead to the stemness of prostate cancer cells with multi-omics data mining.Methods: Gene expression modules that were strongly related to the stemness of prostate cancer cells were obtained with WGCNA and stemness scores, based on the prostate cancer transcriptome data in TCGA. Calculated the copy number variation of stemness genes of prostate cancer and evaluated the difference of transcription factors in prostate cancer and normal tissues, based on CNV (copy number variation) data and ATAC-seq data. The protein interaction network of stemness genes of prostate cancer was constructed with the STRING database. At the same time, the correlation between stemness genes of prostate cancer and immune cells was analyzed.Results: Prostate cancer with high Gleason grade was more stemness. The gene set highly related to prostate cancer stemness had higher CNV in prostate cancer samples than normal samples. The transcription factors of stemness genes had similar expressions but had different contributions in normal and prostate cancer tissues. And particular transcription factors enhanced the stemness of prostate cancer, such as PUM1, CLOCK, SP1, TCF12, and so on. The lower tumor immune microenvironment was conducive to the stemness of prostate cancer, and CD8+ T cells and M1 macrophages might play an important role than other immune cells in the tumor microenvironment. We also found that EZH2 played a central role in stemness genes and was negatively correlated with resting mast cells and positively correlated with activated memory CD4+ T cells.Conclusions: This study found that high copy number variation, specific transcription factors, and low immune microenvironment contributed to the stemness of prostate cancer cells through systematic multi-omics analysis. These findings would provide new clues and directions for future research of prostate cancer stem cells.

Background: Prostate cancer stem cells (pCSC) play an important role in tumor metastasis through multiple pathways. From gene, protein to microenvironment, there are many factors affecting the cell stemness of prostate cancer (PCa). However, the effective factors affecting the stemness of prostate cancer cells are still unclear.Methods: Based on the transcription data of prostate cancer in the TCGA database, WGCNA (Weighted Gene Co-expression Network Analysis) and stemness scores were used to find important stemness gene module. According to ATAC-seq and genomic data, analyze their relationship with stemness. The interaction of stemness genes was analyzed with STRING (functional protein association networks) database. Furthermore, based on the immune microenvironment score, the relationship between immune and stemness was analyzed.Results: The most important stemness gene module in prostate cancer was obtained with WGCNA method; then a positive correlation between the gene CNVs (Copy Number Variants) of the most important stemness gene module and PCa stemness was found, as well as a positive correlation between the gene CNVs and Gleason score of PCa was also drug out. Further, the key transcriptional regulators of the most important stemness genes in PCa were obtained. In addition, it's found that immune cells, especially CD8+T cells and M1 macrophages, suppressed the stemness of PCa cells. Finally, by analyzing the protein interactions and the relationship between genes and immune cells, we found that interaction of the proteins of the most important stemness genes module and the relationship between these genes and immune cells of microenvironment of PCa were all important in affecting the stemness of PCa cells.Conclusions: By analyzing multi-omics data of clinical specimen, we got the most important stemness genes and their important transcriptional regulators in PCa; and further mining analysis showed that the stemness of PCa cells is positive regulated by the CNVs and the interaction of the proteins of the most important stemness genes, and negatively regulated by the immune cells of the microenvironment of prostate cancer.