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Table S4 shows the SNPs for colorectal cancer.

Supplementary Methods shows the formulas for calculating F-statistics.

Background:Human gut microbiome has complex relationships with the host, contributing to metabolism, immunity, and carcinogenesis.Methods:Summary-level data for gut microbiota and metabolites were obtained from MiBioGen, FINRISK and human metabolome consortia. Summary-level data for colorectal cancer were derived from a genome-wide association study meta-analysis. In forward Mendelian randomization (MR), we employed genetic instrumental variables (IV) for 24 gut microbiota taxa and six bacterial metabolites to examine their causal relationship with colorectal cancer. We also used a lenient threshold for nine apriori gut microbiota taxa as secondary analyses. In reverse MR, we explored association between genetic liability to colorectal neoplasia and abundance of microbiota studied above using 95, 19, and 7 IVs for colorectal cancer, adenoma, and polyps, respectively.Results:Forward MR did not find evidence indicating causal relationship between any of the gut microbiota taxa or six bacterial metabolites tested and colorectal cancer risk. However, reverse MR supported genetic liability to colorectal adenomas was causally related with increased abundance of two taxa: Gammaproteobacteria (β = 0.027, which represents a 0.027 increase in log-transformed relative abundance values of Gammaproteobacteria for per one-unit increase in log OR of adenoma risk; P = 7.06×10−8), Enterobacteriaceae (β = 0.023, P = 1.29×10−5).Conclusions:We find genetic liability to colorectal neoplasia may be associated with abundance of certain microbiota taxa. It is more likely that subset of colorectal cancer genetic liability variants changes gut biology by influencing both gut microbiota and colorectal cancer risk.Impact:This study highlights the need of future complementary studies to explore causal mechanisms linking both host genetic variation with gut microbiome and colorectal cancer susceptibility.

Figure S1: Experimental design, Figure S2: LyzM-Cre-mediated RBPj cKO suppressed the growth of subcutaneous LLC tumors, Figure S3: LyzM-Cre-mediated RBPj cKO promoted the growth of orthotopic HCC tumors, Figure S4: kclTAMs dominated TAM populations promoting HCC growth, Figure S5: RBPj cKO led to increased proliferation of kclTAMs without influencing apoptosis in hepatic Hepa1-6 tumors, Figure S6: RBPj cKO did not affect the proliferation capacity of monocytes in vitro, Figure S7: RBPj cKO promoted the growth of hepatic Hepa1-6 tumors independent of CCR2,Figure S8: Notch signaling negatively regulated the activation of Wnt/β-catenin signaling and the proliferation of kclTAMs, Figure S9: Blocking Wnt signaling inhibited the growth of hepatic Hepa1-6 tumors, Figure S10: Knockdown of β-catenin repressed the proliferation of RBPj-deficient KCs, Figure S11: RBPj cKO promoted kclTAM proliferation and hepatic tumor growth through β-catenin-dependent Wnt signaling, Figure S12: RBPj cKO promoted the hepatic metastasis but suppressed lung metastasis, Figure S13: A model depicting the role of Notch signaling in TAM subsets regulating hepatic tumor growth and metastasis in liver, Table S1: Clinical data of 44 HCC patients involved in this study, Table S2: Antibodies used in this study, Table S3: Primers and oligonucleotides used in this study

Tumor-associated macrophages (TAM) play pivotal roles in tumor progression and metastasis, but the contribution and regulation of different macrophage populations remain unclear. Here we show that Notch signaling plays distinct roles in regulating different TAM subsets in hepatocellular carcinoma (HCC). Myeloid-specific NOTCH blockade by conditional disruption of recombination signal binding protein Jκ (RBPj cKO) significantly delayed the growth of subcutaneously inoculated Lewis lung carcinoma (LLC), but accelerated orthotopically inoculated hepatic Hepa1-6 tumors in mice. In contrast to subcutaneous LLC, RBPj cKO significantly increased the number of TAMs in hepatic Hepa1-6 tumors despite impeded differentiation of monocyte-derived TAMs (moTAM). The dominating TAMs in orthotopic HCC manifested properties of Kupffer cells (KC) and hence are tentatively named KC-like TAMs (kclTAM). The increased proliferation of RBPj cKO kclTAMs was maintained even in Ccr2−/− mice, in which moTAMs were genetically blocked. NOTCH signaling blockade accelerated proliferation of kclTAMs via enhanced β-catenin–dependent WNT signaling, which also downregulated IL12 and upregulated IL10 expression by kclTAMs likely through c-MYC. In addition, myeloid-specific RBPj cKO facilitated hepatic metastasis of colorectal cancer but suppressed lung metastasis in mice, suggesting that the phenotype of RBPj cKO in promoting tumor growth was liver-specific. In patient-derived HCC biopsies, NOTCH signaling negatively correlated with WNT activation in CD68+ macrophages, which positively correlated with advanced HCC stages. Therefore, NOTCH blockade impedes the differentiation of moTAMs, but upregulates Wnt/β-catenin signaling to promote the proliferation and protumor cytokine production of kclTAMs, facilitating HCC progression and hepatic metastasis of colorectal cancer.Significance:These findings highlight the role of NOTCH and WNT signaling in regulating TAMs in hepatocellular carcinoma.

N6-methyladenosine (m6A) modification has been demonstrated to exhibit a crucial prognostic effect on colorectal cancer (CRC). Nonetheless, potential mechanism of m6A in survival rate and immunotherapeutic response remains unknown. Here we investigated the genes associated with m6A regulators and developed a risk score for predicting the overall survival (OS) of CRC patients. RNA-seq transcriptomic profiling data of COAD/READ samples were obtained from The Cancer Genome Atlas (TCGA) database. Absolute Shrinkage and Selection Operator (LASSO)- Cox regression analysis was conducted to identify the m6A-related gene expression signatures and the selected genes were inputted into stepwise regression to develop a prognostic risk score in TCGA, and its predictive performance of CRC survival was further validated in Gene Expression Omnibus (GEO) datasets. According to our results, the risk score comprising 18 m6A-related mRNAs was significantly associated with CRC survival in both TCGA and GEO datasets. And the stratified analysis also confirmed that high-risk score acted as a poor factor in different age, sex, T stage, and tumour, node, metastasis (TNM) stages. The m6A-related prognostic score in combination with clinical characteristics yielded time-dependent area under the receiver operating characteristic curve (AUCs) of 0.85 (95%CI: 0.79–0.91), 0.84 (95%CI: 0.79–0.90) and 0.80 (95%CI: 0.71–0.88) for the prediction of the 1-, 3-, 5-year OS of CRC in TCGA cohort. Furthermore, mutation of oncogenes occurred more frequently in the high-risk group and the composition of immune cells in tumour microenvironment (TME) was significantly distinct between the low- and high-risk groups. The low-risk group had a lower microsatellite instability (MSI) score, T-cell exclusion score and dysfunction score, implying that low-risk patients may have a better immunotherapy response than high-risk patients. In summary, a prognostic risk score derived from m6A-related gene expression signatures could serve as a potential prognostic predictor for CRC survival and indicator for predicting immunotherapy response in CRC patients.

Cancer is a heterogeneous disease that is driven by the accumulation of both genetic and nongenetic alterations, so integrating multiomics data and extracting effective information from them is expected to be an effective way to predict cancer driver genes. In this paper, we first generate comprehensive instructive features for each gene from genomic, epigenomic, transcriptomic levels together with protein–protein interaction (PPI)-networks-derived attributes and then propose a novel semisupervised deep graph learning framework GGraphSAGE to predict cancer driver genes according to the impact of the alterations on a biological system. When applied to eight tumor types, experimental results suggest that GGraphSAGE outperforms several state-of-the-art computational methods for driver genes identification. Moreover, it broadens our current understanding of cancer driver genes from multiomics level and identifies driver genes specific to the tumor type rather than pan-cancer. We expect GGraphSAGE to open new avenues in precision medicine and even further predict drivers for other complex diseases.

Background Nearly 15% colorectal cancer (CRC) patients received ileostomy, while surgical site infection (SSI) is a common complication after ileostomy wound closure. Purse-string closure was reported to reduce SSI rate in ileostomy wound closure compared with conventional linear closure, but had never been systematically reported in CRC patients. The present study aimed to compare the short-term outcomes between purse-string and conventional closure in Chinese CRC patients. Patients and methods A total of 57 CRC patients underwent ileostomy wounds closure in the Second Affiliated Hospital of Zhejiang University during November, 2015 and October, 2017 were retrospectively reviewed. Twenty-nine received purse-string closure while the others received conventional closure. The short-term outcomes including SSI rate, scar length, pain score and hospital stay were reviewed and analyzed. Results There were no significant differences in the characteristics of the patients between two groups. The SSI rate was similar within two groups (10.3% vs 10.7%, p = 1.000). The purse-string closure group had a significantly short scar length (1.66 cm vs 5.30 cm, p Conclusion The present study did not find superiority of Purse-string closure in SSI rate control. It seemed only had a cosmetic effect according to its shorter scar length.

Primordial germ cells (PGCs) play an important role in sexual fate determination and gonadal development in gonochoristic fish, such as zebrafish and medaka. However, little is known about the function of PGCs in hermaphroditic fish. Rice field eel (Monopterus albus), a protogynous hermaphroditic fish, is an economically valuable aquaculture species. We eliminated PGCs in rice field eels during embryogenesis via morpholino-mediated knockdown dead end (dnd). The PGCs-depleted gonads developed into testis-like structures with Sertoli cells and Leydig cells. The gene expression pattern of 15-month-old PGCs-depleted gonads showed that male-biased genes, dmrt1, sox9a, gsdf, and amh, were significantly higher than that of the WT, whereas female-biased genes, foxl2 and cyp19a1a, were significantly decreased. These results indicate that PGCs are essential for ovarian differentiation in rice field eel, and PGCs-depleted gonads develop into sterile males without undergoing the female and intersex stages. Our study is the first to identify the role of PGCs in sex differentiation in rice field eel, a protogynous hermaphrodite teleost. And it is of great significance in rice field eel for discovering the underlying mechanism of sex differentiation and establishing sex control technology.

The chicken is rich in various proteins, fatty acids, polysaccharides, trace elements, and other human essential nutrients that contribute to its high nutritional value. In this study, the expression levels of nutrition-related genes (acetyl-CoA acyltransferase, ACAA) of native chicken breeds were investigated. The level of GgalACAA1-2 transcripts expression in the liver of chicken was significantly higher than that of muscle and heart. Moreover, three protein extracts were isolated from the muscle, heart, and liver tissues from the chicken, and their nutritional function was evaluated in the present study. These protein extracts had excellent DPPH and hydroxyl radical scavenging capacities and exhibited significant superoxide anion scavenging ability. Moreover, the protein extracts of muscle tissue showed an important mouse splenocyte proliferation activity and could be used as an immunomodulator of natural origin. In addition, this report presented an automatic visual inspection of chicken viscera using the active contour algorithms and the image processing method for eviscerating by the parallel robot. The recognition and positioning rate of chicken viscera obtained by the proposed method could reach 96.45%. These methods provided basic data for automated poultry slaughter and segmentation, avoiding unnecessary health risks by a pathogenic microorganism, such as avian influenza, Newcastle disease virus, and coronavirus. Moreover, the internal organs of the chicken could be fully harvested by the image segmentation of automatic evisceration, which also facilitated the processing value of these internal organs as by-products of poultry.