Statins are an essential medication class in the treatment of lipid diseases because they inhibit 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase. They reduce cholesterol levels and reduce the risk of cardiovascular disease in both primary and secondary prevention. In addition to their powerful pharmacologic suppression of cholesterol production, statins appear to have pleitropic effects in a wide variety of other diseases by modulating signaling pathways. In recent years, statins have seen a large increase in interest due to their putative anticancer effects. Statins appear to cause upregulation or inhibition in key pathways involved in cancer such as inhibition of proliferation, angiogenesis, and metastasis as well as reducing cancer stemness. Further, statins have been found to induce oxidative stress, cell cycle arrest, autophagy, and apoptosis of cancer cells. Interestingly, clinical studies have shown that statin use is associated with a decreased risk of cancer formation, lower cancer grade at diagnosis, reduction in the risk of local reoccurrence, and increasing survival in patients. Therefore, our objective in the present review is to summarize the findings of the publications on the underlying mechanisms of statins’ anticancer effects and their clinical implications.

Fibroblasts and myofibroblasts are major mesenchymal cells in the lamina propria of colon mucosa and in colon cancer tissues. Detailed insight into the highly specific populations of fibroblasts and myofibroblasts is required to understand the integrity and homeostasis of human colon mucosa and colon cancer. Based on gene expression profiles of single cells, we identified fibroblast populations that produce extracellular matrix components, Wnt ligand- and BMP-secreting fibroblasts, chemokine- and chemokine ligand-generating fibroblasts, highly activated fibroblasts, immune-modulating fibroblasts, epithelial cell-modulating myofibroblasts, stimuli-responsive myofibroblasts, proliferating myofibroblasts, fibroblast-like myofibroblasts, matrix producing myofibroblasts, and contractile myofibroblasts in human colon mucosa. In colon cancer tissue, the compositions of fibroblasts and myofibroblasts were highly altered, as were the expressing patterns of genes including BMPs, Wnt ligands, chemokines, chemokine ligands, growth factors and extracellular matrix components in fibroblasts and myofibroblasts. Our work expands the working atlas of fibroblasts and myofibroblasts and provides a framework for interrogating the complexity of stromal cells in human healthy colon mucosa and colon cancer tissues.

Aim: To investigate the association and prognostic value of ANKZF1 gene for survival in colorectal cancer, the mechanism of ANKZF1 level alteration and correlated signaling pathways ANKZF1 is invol...

P53 mutation is common and highly related to radiotherapy resistance in rectal cancer. APR-246, as a small molecule, can restore the tumor-suppressor function to mutant p53. As there is currently no existing study on combining APR-246 with radiation in rectal cancer, our objective was to investigate whether APR-246 could enhance the sensitivity of colorectal cancer cells, regardless of their p53 status, to radiation treatment. The combination treatment had synergistic effects on HCT116p53-R248W/− (p53Mut) cells, followed by HCT116p53+/+ [wild-type p53 (p53WT)] cells, and exhibited an additive effect on HCT116p53−/− (p53Null) cells through inhibiting proliferation, enhancing reactive oxygen species, and apoptosis. The results were confirmed in zebrafish xenografts. Mechanistically, p53Mut and p53WT cells shared more activated pathways and differentially expressed genes following the combination treatment, compared with p53Null cells, although the combination treatment regulated individual pathways in the different cell lines. APR-246 mediated radiosensitization effects through p53-dependent and -independent ways. The results may provide evidence for a clinical trial of the combination in patients with rectal cancer.

Background. The incidence of colorectal cancers has been constantly increasing. Although the mortality has slightly decreased, it is far from satisfaction. Precise early diagnosis for colorectal cancer has been a great challenge in order to improve patient survival. Patients and Methods. We started with searching for protein biomarkers based on our colorectal cancer biomarker database (CBD), finding differential expressed genes (GEGs) and non-DEGs from RNA sequencing (RNA-seq) data, and further predicted new biomarkers of protein–protein interaction (PPI) networks by machine learning (ML) methods. The best-selected biomarker was further verified by a receiver operating characteristic (ROC) test from microarray and RNA-seq data, biological network, and functional analysis, and immunohistochemistry in the tissue arrays from 198 specimens. Results. There were twelve proteins (MYO5A, CHGA, MAPK13, VDAC1, CCNA2, YWHAZ, CDK5, GNB3, CAMK2G, MAPK10, SDC2, and ADCY5) which were predicted by ML as colon cancer candidate diagnosis biomarkers. These predicted biomarkers showed close relationships with reported biomarkers of the PPI network and shared some pathways. An ROC test showed the CHGA protein with the best diagnostic accuracy (AUC = 0.9 in microarray data and 0.995 in RNA-seq data) among these candidate protein biomarkers. Furthermore, immunohistochemistry examination on our colon cancer tissue microarray samples further confirmed our bioinformatical prediction, indicating that CHGA may be used as a potential biomarker for early diagnosis of colon cancer patients. Conclusions. CHGA could be a potential candidate biomarker for diagnosing earlier colon cancer in the patients.

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