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Fig. S1. RNF6 genomic amplification is prevalent in colorectal cancer and correlated with shortened patient survival. Fig. S2. RNF6 is clinically relevant in colorectal cancer. Fig. S3. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) in RNF6-higher/lower expression CRC cells and patients, and RNF6 is an oncogenic gene. FigureS4. RNF6 upregulates pSTAT3 via downregulating SHP-1 expression. Figure S5. RNF6 Interacts with SHP-1 and enhances ubiquitylation and degradation of SHP-1. Figure S6. Effectiveness of pSTAT3 inhibitors in treating RNF6-amplified tumors.

Supplementary Material and Methods clean

Fig. S1. RNF6 genomic amplification is prevalent in colorectal cancer and correlated with shortened patient survival. Fig. S2. RNF6 is clinically relevant in colorectal cancer. Fig. S3. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) in RNF6-higher/lower expression CRC cells and patients, and RNF6 is an oncogenic gene. FigureS4. RNF6 upregulates pSTAT3 via downregulating SHP-1 expression. Figure S5. RNF6 Interacts with SHP-1 and enhances ubiquitylation and degradation of SHP-1. Figure S6. Effectiveness of pSTAT3 inhibitors in treating RNF6-amplified tumors.

Table S1.Expression of human ubiquitin ligase genes in 246 CRC patients of TCGAdatabase.TableS2.Clinial information of 62 cases CRC patients (fresh tissues).Table S3.Clinial information of 78 cases CRC patients (paraffin tissues).Table S4.Clinial information of 97 cases CRC patients (paraffin tissues).Table S5.RNA sequence data. TableS 6. Primer sequences

Objective: The E3 ubiquitin ligase RNF6 (RING-finger protein 6) plays a crucial role in carcinogenesis. However, the copy number and expression of RNF6 were rarely reported in colorectal cancer. We aimed to explore the mechanical, biological, and clinical role of RNF6 in colorectal cancer initiation and progression.Design: The copy number and expression of RNF6 were analyzed from Tumorscape and The Cancer Genome Atlas (TCGA) datasets. Gene expressions were examined by real-time PCR, Western blot, and immunohistochemical staining. Gene expression profiling studies were performed to identify pivotal genes regulated by RNF6. Biological function of RNF6 on tumor growth and metastasis was detected in vivo and in vitro. Role of RNF6 in modulating SHP-1 expression was examined by coimmunoprecipitation and confocal microscopy, respectively.Results: The copy number of RNF6 was significantly amplified in colorectal cancer, and the amplification was associated with RNF6 expression level. Amplification and overexpression of RNF6 positively correlated with patients with colorectal cancer with poor prognosis. The gene set enrichment analysis (GSEA) revealed cell proliferation, and invasion-related genes were enriched in RNF6 high-expressed colorectal cancer cells as well as in patients from TCGA dataset. Downregulation of RNF6 impaired the colorectal cancer cell proliferation and invasion in vitro and in vivo. RNF6 may activate the JAK/STAT3 pathway and increase pSTAT3 levels by inducing the ubiquitination and degradation of SHP-1.Conclusions: Genomic amplification drives RNF6 overexpression in colorectal cancer. RNF6 may be a novel biomarker in colorectal carcinogenesis, and RNF6 may increase pSTAT3 level via promoting SHP-1 ubiquitylation and degradation. Targeting the RNF6/SHP-1/STAT3 axis provides a potential therapeutic option for RNF6-amplified tumors. Clin Cancer Res; 24(6); 1473–85. ©2017 AACR.

Genome-wide association studies (GWASs) implicate 16q22.1 locus in risk for colorectal cancer (CRC). However, the underlying oncogenic mechanisms remain unknown. Here, through comprehensive filtration, we prioritized rs7198799, a common SNP in the second intron of the CDH1, as the putative causal variant. In addition, we found an association of CRC-risk allele C of rs7198799 with elevated transcript level of biological plausible candidate gene ZFP90 via expression quantitative trait loci analysis. Mechanistically, causal variant rs7198799 resides in an enhancer element and remotely regulate ZFP90 expression by targeting the transcription factor NFATC2. Remarkably, CRISPR/Cas9-guided single-nucleotide editing demonstrated the direct effect of rs7198799 on ZFP90 expression and CRC cellular malignant phenotype. Furthermore, ZFP90 affects several oncogenic pathways, including BMP4, and promotes carcinogenesis in patients and in animal models with ZFP90 specific genetic manipulation. Taken together, these findings reveal a risk SNP-mediated long-range regulation on the NFATC2-ZFP90-BMP4 pathway underlying the initiation of CRC.

Long non-coding RNAs (lncRNAs) contribute to colorectal cancer (CRC). However, the role of lncRNAs in CRC metabolism, especially glucose metabolism remains largely unknown. In this study, we identify a lncRNA, GLCC1, which is significantly upregulated under glucose starvation in CRC cells, supporting cell survival and proliferation by enhancing glycolysis. Mechanistically, GLCC1 stabilizes c-Myc transcriptional factor from ubiquitination by direct interaction with HSP90 chaperon and further specifies the transcriptional modification pattern on c-Myc target genes, such as LDHA, consequently reprogram glycolytic metabolism for CRC proliferation. Clinically, GLCC1 is associated with tumorigenesis, tumor size and predicts poor prognosis. Thus, GLCC1 is mechanistically, functionally, and clinically oncogenic in colorectal cancer. Targeting GLCC1 and its pathway may be meaningful for treating patients with colorectal cancer., lncRNA and cellular metabolism are frequently dysregulated in cancer. In this study, the authors discover the lncGLCC1 is increased in colorectal cancer cells under glucose starvation conditions and correlates with poor prognosis in this cancer.

Long non-coding RNAs (lncRNAs) play key roles in colorectal carcinogenesis. Here, we aimed to identify the risk SNP-induced lncRNAs and to investigate their roles in colorectal carcinogenesis. First, we identified rs6695584 as the causative SNP in 1q41 locus. The A>G mutation of rs6695584 created a protein-binding motif of BATF, altered the enhancer activity, and subsequently activated lncSLCC1 expression. Further validation in two independent CRC cohorts confirmed the upregulation of lncSLCC1 in CRC tissues, and revealed that increased lncSLCC1 expression was associated with poor survival in CRC patients. Mechanistically, lncRNA-SLCC1 interacted with AHR and transcriptionally activated HK2 expression, the crucial enzyme in glucose metabolism, thereby driving the glycolysis pathway and accelerating CRC tumor growth. The functional assays revealed that lncSLCC1 induced glycolysis activation and tumor growth in CRC mediated by HK2. In addition, HK2 was upregulated in colorectal cancer tissues and positively correlated with lncSLCC1 expression and patient survival. Taken together, our findings reveal a risk SNP-mediated oncogene lncRNA-SLCC1 promotes CRC through activating the glycolysis pathway.

Additional file 3 Figure S1. METTL3 is closely correlated with glycolytic metabolism in CRC. (a) The relative expression of METTL3 was measured by real-time PCR in normal colonic epithelial cell line FHC and CRC cell lines, n = 3, nonparametric Mann–Whitney test. (b) Schematic diagram of METTL3 genomic sequence in HCT116 wild-type (WT) and METTL3-knockout (METTL3-KO) cells. Red label, target sgRNA sequence; Yellow label, A 161 bp DNA fragment was inserted in the cutting site; Red circle, a premature stop site was generated after insertion of 161 bp DNA fragment. (c) The knockout efficiency of METTL3 was confirmed by Western blot. (d) GSEA analysis was conducted to identify the differential gene profiles between HCT116 METTL3-KO and WT cells. (WT, wild type; METTL3-KO, METTL3-knockout). Figure S2. METTL3 drives glycolytic metabolism in CRC. (a-b) The knockdown efficiency of METTL3 siRNA1/2 was evaluated in HCT116 (a) and SW480 (b) cells, n = 3, nonparametric Mann–Whitney test. (c-e) Lactate production (c), glucose uptake (d) and ECAR (e) were measured after transfection of control siRNA and METTL3 siRNA1/2 in SW480 cells, n = 3, nonparametric Mann–Whitney test. (f) OCR was measured in HCT116 WT and METTL3-KO cells (left). OCR was measured in SW480 cells transfected with control siRNA and METTL3 siRNA1/2 (right). (g) Schematic domain structures of METTL3. METTL3 MTase (AA residues 369–580). (h-i) Real-time PCR (h) and Western blot assay (i) were performed to detect METTL3 expression after transfection with pcDNA3.1-METTL3 and pcDNA3.1-METTL3-mut in DLD1 cells. (WT, wild type; METTL3-KO, METTL3-knockout). Figure S3. METTL3 is an oncogenic gene in colorectal cancer. (a-b) GSEA analysis was conducted to identify the differential gene profiles between HCT116 METTL3-KO and WT cells. (c) The expression of CDK1, PCNA and CDCA7 were detected in HCT116 WT and METTL3-KO cells, n = 3, nonparametric Mann–Whitney test. (d-e) The expression of CDK1, PCNA and CDCA7 were detected after transfection with control siRNA and METTL3-siRNA1/2 in HCT116 (d) and SW480 cells (e), n = 3, nonparametric Mann–Whitney test. (f) Cell proliferation of HCT116 cells was measured by CCK8 assay after transfected with control siRNA or METTL3 siRNA, n = 6, nonparametric Mann–Whitney test. (g) Colony formation assay was performed in HCT116 cells after transfection with control siRNA or METTL3 siRNA1/2, n = 3, nonparametric Mann–Whitney test. (h) Cell proliferation assay was performed by CCK8 assay in SW480 cells with METTL3 knockdown, n = 6, nonparametric Mann–Whitney test. (i) Colony formation assay was performed after transfection with control siRNA or METTL3 siRNA1/2 in SW480 cells, n = 3, nonparametric Mann–Whitney test. (j) Representative images of tumors in nude mice bearing DLD1 cells treated with PBS, control adenovirus and shControl adenovirus, n = 8. (k-l) Tumor volumes and (k) tumor weights (l) were measured in mice bearing DLD1 cells treated with PBS, control adenovirus and shControl adenovirus, n = 8, nonparametric Mann–Whitney test. (WT, wild type; METTL3-KO, METTL3-knockout). Figure S4. Transcriptome-wide m6A-seq and RNA-seq assays identified potential targets of METTL3 in colorectal cancer. (a) The distribution of m6A IP signal across the mRNA transcripts. m6A IP signal was enriched around the stop codon of mRNAs. (b) Comparison of the abundance of m6A peaks between HCT116 WT and METTL3-KO cells. A total of 2632 (hypo-methylated) and 584 (hyper-methylated) m6A peaks showed a significant decrease and increase in abundance in HCT116 METTL3-KO cells compared with WT cells. (c) Gene ontology analysis of genes with a significant decrease in m6A modification as well as a significant decrease in mRNA expression level (Hypo-down, p

Additional file 1. Supplementary Methods

Although several prognostic signatures have been developed for gastric cancer (GC), the utility of these tools is limited in clinical practice due to lack of validation with large and multiple independent cohorts, or lack of a statistical test to determine the robustness of the predictive models. Here, a prognostic signature was constructed using a least absolute shrinkage and selection operator (LASSO) Cox regression model and a training dataset with 300 GC patients. The signature was verified in three independent datasets with a total of 658 tumors across multiplatforms. A nomogram based on the signature was built to predict disease-free survival (DFS). Based on the LASSO model, we created a GeneExpressScore signature (GESGC ) classifier comprised of eight mRNA. With this classifier patients could be divided into two subgroups with distinctive prognoses [hazard ratio (HR) = 4.00, 95% confidence interval (CI) = 2.41-6.66, P

Objective: The E3 ubiquitin ligase RNF6 (RING-finger protein 6) plays a crucial role in carcinogenesis. However, the copy number and expression of RNF6 were rarely reported in colorectal cancer. We aimed to explore the mechanical, biological, and clinical role of RNF6 in colorectal cancer initiation and progression. Design: The copy number and expression of RNF6 were analyzed from Tumorscape and The Cancer Genome Atlas (TCGA) datasets. Gene expressions were examined by real-time PCR, Western blot, and immunohistochemical staining. Gene expression profiling studies were performed to identify pivotal genes regulated by RNF6. Biological function of RNF6 on tumor growth and metastasis was detected in vivo and in vitro. Role of RNF6 in modulating SHP-1 expression was examined by coimmunoprecipitation and confocal microscopy, respectively. Results: The copy number of RNF6 was significantly amplified in colorectal cancer, and the amplification was associated with RNF6 expression level. Amplification and overexpression of RNF6 positively correlated with patients with colorectal cancer with poor prognosis. The gene set enrichment analysis (GSEA) revealed cell proliferation, and invasion-related genes were enriched in RNF6 high-expressed colorectal cancer cells as well as in patients from TCGA dataset. Downregulation of RNF6 impaired the colorectal cancer cell proliferation and invasion in vitro and in vivo. RNF6 may activate the JAK/STAT3 pathway and increase pSTAT3 levels by inducing the ubiquitination and degradation of SHP-1. Conclusions: Genomic amplification drives RNF6 overexpression in colorectal cancer. RNF6 may be a novel biomarker in colorectal carcinogenesis, and RNF6 may increase pSTAT3 level via promoting SHP-1 ubiquitylation and degradation. Targeting the RNF6/SHP-1/STAT3 axis provides a potential therapeutic option for RNF6-amplified tumors. Clin Cancer Res; 24(6); 1473–85. ©2017 AACR.

High throughput gene expression profiling has showed great promise in providing insight into molecular mechanisms. Metastasis‐related mRNAs may potentially enrich genes with the ability to predict cancer recurrence, therefore we attempted to build a recurrence‐associated gene signature to improve prognostic prediction of colorectal cancer (CRC). We identified 2848 differentially expressed mRNAs by analyzing CRC tissues with or without metastasis. For the selection of prognostic genes, a LASSO Cox regression model (least absolute shrinkage and selection operator method) was employed. Using this method, a 13‐mRNA signature was identified and then validated in two independent Gene Expression Omnibus cohorts. This classifier could successfully discriminate the high‐risk patients in discovery cohort [hazard ratio (HR) = 5.27, 95% confidence interval (CI) 2.30–12.08, P

FAM83B (family with sequence similarity 83, member B) seems to emerge as a new class of players involved in the development of a variety of malignant tumors. Yet the molecular mechanisms are not well understood. The present study is intended to investigate the expression and function of FAM83B in pancreatic ductal adenocarcinoma (PDAC). In this study, we found that the expression of FAM83B was significantly increased both in PDAC cell lines and PDAC tumor tissues. FAM83B expression was positively related with advanced clinical stage and poor vital status. Higher FAM83B expression predicted shorter overall survival in PDAC patients, regardless of lymphatic metastasis status and histological differentiation. Actually, FAM83B may act as an independent prognostic indicator as well. What's more, down-regulation of FAM83B in PDAC cells contributed to G0/G1 phase arrest and inhibition of cell proliferation. Finally, a subcutaneous xenograft model indicated that knockdown of FAM83B significantly reduced the tumor volume in vivo. Our findings have provided supporting evidence for the potential molecular biomarker role of FAM83B in PDAC. It's of great interest and broad significance to target FAM83B in PDAC, which may conduce to develop a meaningful and effective strategy in the diagnosis and treatment of PDAC.

Current studies indicate that long non-coding RNAs (lncRNAs) are frequently aberrantly expressed in cancers and implicated with prognosis in gastric cancer (GC). We intended to generate a multi-lncRNA signature to improve prognostic prediction of GC. By analyzing ten paired GC and adjacent normal mucosa tissues, 339 differentially expressed lncRNAs were identified as the candidate prognostic biomarkers in GC. Then we used LASSO Cox regression method to build a 12-lncRNA signature and validated it in another independent GEO dataset. An innovative 12-lncRNA signature was established, and it was significantly associated with the disease free survival (DFS) in the training dataset. By applying the 12-lncRNA signature, the training cohort patients could be categorized into high-risk or low-risk subgroup with significantly different DFS (HR = 4.52, 95%CI= 2.49-8.20, P < 0.0001). Similar results were obtained in another independent GEO dataset (HR=1.58, 95%CI=1.05 - 2.38, P=0.0270). Further analysis showed that the prognostic value of this 12-lncRNA signature was independent of AJCC stage and postoperative chemotherapy. Receiver operating characteristic (ROC) analysis showed that the area under receiver operating characteristic curve (AUC) of combined model reached 0.869. Additionally, a well-performed nomogram was constructed for clinicians. Moreover, single-sample gene-set enrichment analysis (ssGSEA) showed that a group of pathways related to drug resistance and cancer metastasis significantly enriched in the high risk patients. A useful innovative 12-lncRNA signature was established for prognostic evaluation of GC. It might complement clinicopathological features and facilitate personalized management of GC.

Genome-wide association studies (GWAS) have identified several loci harboring variants that affected the risk of colorectal cancer; however, the specific mechanisms by which germline variation influenced the tumorigenesis of colorectal cancer (CRC) remains unrevealed. We found the T>C variant of rs1317082, locating at the exon 1 of lncRNA RP11-362K14.5 (CCSlnc362), was predicted to be a protective locus for cancer. However, the specific role of CCSlnc362 and the interaction between CCSlnc362 and rs1317082 variation in colorectal cancer and its mechanisms remain unclear. Here we explored the expression and function of CCSlnc362 in CRC cells and tissues. We found lncRNA CCSlnc362 expression was significantly increased in CRC samples. Follow-up functional experiments elucidated that downregulation of CCSlnc362 inhibited cell proliferation, arrested cell cycle, and promoted apoptosis in CRC cells. The T>C variant of rs1317082 at CCSlnc362 exon 1 created a binding site for miR-4658 to reduce the expression of CCSlnc362 and thus decreased the susceptibility to CRC. Our findings have provided supporting evidence for the protective role of rs1317082 variation and the potential oncogenic role of lncRNA CCSlnc362 in CRC. The data shed new light on the relationship between germline variation, miRNAs, and lncRNAs and opened a new avenue for targeted therapy in CRC.

Background Gene expression profiling has been used to classify molecular subtypes in colorectal cancer (CRC). Given that tumour transcriptome signals not only derive from cancer cells but also from tumour microenvironment. Recent studies have shown that noncancerous components might affect the classification of CRC subtypes. We hypothesised that using stroma-specific gene signature would be more effective to identify CRC subtypes with clinical relevance. Methods To this end, we analysed gene expression profiles from 1821 CRCs. We firstly constructed a signature where genes were both stroma-specifically expressed and associated with drug response. Further, we identified CRC stroma-specific subtypes (CRSS) using K-means clustering based on the signature and verified the classification in two datasets. We also used the nearest template prediction algorithm to predict drug response. Results The CRSS subtypes were associated with distinct clinicopathological, molecular and phenotypic characteristics and specific enrichments of gene signatures and signalling pathways (table 1): (i) CRSS-A: non-serrated adenomas, colon crypt top derived, glycolytic, epithelial, KRAS-mutant, sensitive to Cetuximab, enriched with NK cells; (ii) CRSS-B: non-serrated adenomas, colon crypt base derived, DNA replication activity, epithelial, BRAF wild-type, TP53 mutant, chromosomal stability, distal CRC, sensitive to Cetuximab; (iii) CRSS-C: serrated adenomas, colon crypt top derived, interleukin-6 pathway activity, epithelial, microsatellite instability (MSI), BRAF mutant, hypermutation, chromosomal instability, CpG island methylator phenotype, proximal CRC, sensitive to Gefitinib, good prognosis, enriched with cytotoxic lymphocytes and monocytic lineage; (iv) CRSS-D: non-serrated adenomas, colon crypt top derived, interleukin-2 pathway activity, epithelial-mesenchymal transition (EMT), chromosomal stability, sensitive to FOLFIRI and FOLFOX chemotherapy regimens; (v) CRSS-E: serrated adenomas, colon crypt base derived, EMT, immune pathways activation, poor prognosis, sensitive to FOLFIRI and FOLFOX, enriched with endothelial cells and fibroblasts; (vi) CRSS-F: serrated adenomas, colon crypt base derived, EMT, IGF1 pathway activity, poor prognosis, sensitive to FOLFIRI and FOLFOX, enriched with endothelial cells, fibroblasts and monocytic lineage. Conclusions We classified CRC into six molecular subtypes (CRSS). The identification of CRSS subtypes is critical, as it provides possibilities to identify robust prognostic models and provide more precise therapeutic options for each CRC subtype.

Clinical characteristics of 492 gastric cancer patients involved in the study. (DOCX 15Â kb)

Supplemental Digital Content is available in the text, Background: As an important antivascular endothelial growth factor monoclonal antibody, bevacizumab has been administrated for the treatment of cancer patients. Hemorrhage, one of the common adverse events of angiogenesis inhibitors, sometimes is also fatal and life-threatening. We aimed at determining the incidence and risk of hemorrhage associated with bevacizumab in patients with metastatic colorectal cancer (mCRC). Methods: We searched PubMed, EMBASE, and the Web of Science databases for relevant randomized controlled trials (RCTs). The overall incidence, overall relative risk (RR), and 95% confidence interval (CI) were calculated by using a random-effects or fixed-effects model based on the heterogeneity of selected trials. Results: A total of 10,555 mCRC patients from 12 RCTs were included in our study. The overall incidence of hemorrhage was 5.8% (95% CI 3.9%–7.8%). Bevacizumab significantly increased the overall risk of hemorrhage with an RR of 1.96 (95% CI 1.27–3.02). The RR of all-grade hemorrhage was 2.39 (95% CI 1.09–5.24) and 1.41 (95% CI 1.01–1.97) for high-grade hemorrhage. The risk of hemorrhage associated with bevacizumab was dose-dependent with an RR of 1.73 (95% CI 1.15–2.61) for 2.5 mg/kg/wk and 4.67 (95% CI 2.36–9.23) for 5 mg/kg/wk. More importantly, the RR of hemorrhage for treatment duration ( 6 months) based on subgroup analysis was 4.13 (95% CI 2.58–6.61) and 1.43 (95% CI 0.96–2.14), respectively. Conclusion: The addition of bevacizumab to concurrent antineoplastic in patients with mCRC significantly increased the risk of hemorrhage. The dose of bevacizumab may contribute to the risk of hemorrhage. And the 1st 6 months of treatment may be a crucial period when hemorrhagic events occur.

Background Increasing evidence suggests long non-coding RNAs (lncRNAs) are frequently aberrantly expressed in cancers, however, few related lncRNA signatures have been established for prediction of cancer prognosis. We aimed at developing alncRNA signature to improve prognosis prediction of gastric cancer (GC). Methods Using a lncRNA-mining approach, we performed lncRNA expression profiling in large GC cohorts from Gene Expression Ominus (GEO), including GSE62254 data set (N = 300) and GSE15459 data set (N = 192). We established a set of 24-lncRNAs that were significantly associated with the disease free survival (DFS) in the test series. Results Based on this 24-lncRNA signature, the test series patients could be classified into high-risk or low-risk subgroup with significantly different DFS (HR = 1.19, 95 % CI = 1.13–1.25, P