Figure - available from: OncoTargets and Therapy
This content is subject to copyright. Terms and conditions apply.
Evaluation of liver function, weight, and overall survival. (A) AST and ALT, (B) weight, (C) direct bilirubin (Dbil) and total bilirubin (Tbil) measurements. (D) Albumin measurements. (E) Overall survival. After 6 Gy low-dose irradiation, liver function indicators of total and direct bilirubin and AST of C57/BL6 mice increased but not significantly. ALT significantly increased whereas the weight of the mice and albumin levels significantly decreased. *P < 0.05, **P < 0.01. Abbreviation: n.s., not significant.
Source publication
Background
The liver is the most common target for metastatic colorectal cancer. Changes of the local hepatic niche due to hepatic diseases such as cirrhosis decrease the incidence of colorectal cancer liver metastasis. Hepatic niche heterogeneity could influence the risk of hepatic metastasis.
Materials and Methods
We simulated changes of the hep...
Citations
... TIMP1 was found to be a sensitive biomarker in patients with metastatic colon cancer, and higher TIMP1 levels were linked to lymph node metastases, vascular invasion and distant metastasis in CRC patients (31,32). Low expression of TIMP1 decreased the invasion and migration of SW480 and HCT116 colon cancer cells (33). ...
Both tumour-infiltrating immune cells and inflammation-related genes that can mediate immune infiltration contribute to the initiation and prognosis of patients with colon cancer. In this study, we developed a method to predict the survival outcomes among colon cancer patients and direct immunotherapy and chemotherapy. We obtained patient data from The Cancer Genome Atlas (TCGA) and captured inflammation-related genes from the GeneCards database. The package “ConsensusClusterPlus” was used to generate molecular subtypes based on inflammation-related genes obtained by differential expression analysis and univariate Cox analysis. A prognostic signature including four genes (PLCG2, TIMP1, BDNF and IL13) was also constructed and was an independent prognostic factor. Cluster 2 and higher risk scores meant worse overall survival and higher expression of human leukocyte antigen and immune checkpoints. Immune cell infiltration calculated by the estimate, CIBERSORT, TIMER, ssGSEA algorithms, tumour immune dysfunction and exclusion (TIDE), and tumour stemness indices (TSIs) were also compared on the basis of inflammation-related molecular subtypes and the risk signature. In addition, analyses of stratification, somatic mutation, nomogram construction, chemotherapeutic response prediction and small-molecule drug prediction were performed based on the risk signature. We finally used qRT–PCR to detect the expression levels of four genes in colon cancer cell lines and obtained results consistent with the prediction. Our findings demonstrated a four-gene prognostic signature that could be useful for prognostication in colon cancer patients and designing personalized treatments, which could provide new versions of personalized management for these patients.
Colorectal cancer (CRC) is the second leading cause of cancer‐related death worldwide. Many molecular classification strategies are proposed for CRC but few studies include survival data in their models. Herein a prognosis‐oriented CRC classifier is constructed by adapting the natural partially labeled censored survival data into a customized semi‐supervised learning algorithm, which is called Monte‐Carlo K‐nearest neighbor voting (MC‐KV) classifier. Three CRC subtypes with distinct prognoses are identified by this classifier using the data from the cancer genome atlas. Furthermore, a six‐gene risk model is constructed by combining weighted gene coexpression network analysis and least absolute selection and shrinkage operator for variable selection and four algorithms (random survival forest, support vector machine, Adaboost, and logistic regression) for optimization. The optimized model shows great performance in distinguishing high‐risk from low‐risk patients with a maximum area under curve of 0.869, 0.906, and 0.921 in 1‐, 3‐, and 5‐year survival, respectively. Additionally, the six‐gene signature identified by MC‐KV exhibits great predictive efficiency for other cancer types. Overall, a tool, Monte‐Carlo K‐nearest neighbor voting (MC‐KV), is provided to identify molecular subtyping of CRC, which suggests the potential contribution of semi‐supervised algorithms and the inclusion of patient‐level survival data in cancer classification.
ZIC2 is involved in the tumor progression of many types of cancers. The role of ZIC2 in the metastasis of colorectal cancer and its mechanism are not yet clear. In this study, we found that high ZIC2 expression was not only associated with poor prognosis, relapse-free survival and advanced metastasis but was also an independent prognostic factor in colorectal cancer patients. Moreover, ZIC2 knockdown inhibited cell proliferation, migration and invasion, while the upregulation of ZIC2 had the opposite effect in vitro. ZIC2 overexpression induced TGF-β1 expression and increased Smad3 phosphorylation. The carcinogenic effects of elevated ZIC2 expression can be eliminated by interfering with the TGF-β1 receptor with inhibitors. This further verified the promoting effect of ZIC2 on the TGF-β signaling pathway. In vivo experiments have also confirmed that ZIC2 can promote liver metastases of colorectal cancer. The results suggest that ZIC2 is associated with poor prognosis and relapse-free survival in colorectal cancer patients. Moreover, ZIC2 promoted colorectal cancer progression and metastasis by activating the TGF-β signaling pathway. Hence, ZIC2 is expected to be a new therapeutic and prognostic target for colorectal cancer in the future.
