RAS signaling pathways, mutations and their role in colorectal cancer

Oxygen and viruses: a breathing story

The effect of oxygen on virus replication is complex, and the role of hypoxia-inducible factor 1α (HIF-1α) in the metabolism of virus-infected cells remains uncertain. Solid tumours are hypoxic, and some viruses use this low oxygen tension level to facilitate their replication in tumour cells, thereby causing cell lysis. In addition, the interactions between viruses and HIF-1α may stimulate a trained immunity. However, the evolutionary basis for the oxygen regulatory mechanism of virus replication is ill-defined and requires further investigation.

Phospholipase Cδ1 induces E-cadherin expression and suppresses malignancy in colorectal cancer cells

Colorectal cancer (CRC) is one of the most common causes of cancer-related deaths worldwide, and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations in CRC predict the ineffectiveness of EGF receptor-targeted therapy. Previous transcriptional microarray analysis suggests the association between phospholipase Cδ1 (PLCδ1) expression and KRAS mutation status in CRC. However, both the roles and the regulatory mechanisms of PLCδ1 in CRC are not known. Here, we found that the expression of PLCδ1, one of the most basal PLCs, is down-regulated in CRC specimens compared with normal colon epithelium by immunohistochemistry. Furthermore, we examined the roles of PLCδ1 in CRC cell lines that harbor an activating KRAS mutation. Ectopic expression of PLCδ1 in CRC cells induced the expression of E-cadherin, whereas knockdown of PLCδ1 repressed the expression of E-cadherin. Moreover, the overexpression of PLCδ1 suppressed the expression of several mesenchymal genes and reduced cell motility, invasiveness, and in vivo tumorigenicity of SW620 CRC cells. We also showed that PLCδ1 expression is repressed by the KRAS/mitogen-activated protein kinase kinase (MEK) pathway. Furthermore, PLCδ1 suppressed the phosphorylation of extracellular signal-regulated kinase (ERK)1/2 through E-cadherin induction in CRC cells, suggesting the presence of a negative regulatory loop between KRAS/MEK/ERK signaling and PLCδ1. These data indicate that PLCδ1 has tumor-suppressive functions in CRC through E-cadherin induction and KRAS/MEK/ERK signal attenuation.

Diterpenoid C of Radix Curcumae: an inhibitor of proliferation and inducer of apoptosis in human colon adenocarcinoma cells acting via inhibiting MAPK signaling pathway

CONTEXT

Radix Curcumae is a traditional Chinese medicine that possesses antitumor properties, from which a new compound, diterpenoid C, was previously isolated and characterized.

OBJECTIVE

In this study, using human colon adenocarcinoma SW620 cells, we further investigated the antitumor effects of diterpenoid C and the underlying mechanisms.

MATERIALS AND METHODS

Cell proliferation was assessed with the MTT assay. Cell apoptosis and cell-cycle progression were analyzed with flow cytometry. The expression of extracellular signal-regulated kinase (ERK), c-Jun N-terminal kinase (JNK), p38 mitogen-activated protein kinase (p38 MAPK), and their phosphorylated forms, as well as caspase-3 protein levels were examined with Western blots.

RESULTS

Diterpenoid C could inhibit the proliferation of SW620 cells in a dose- and time-dependent manner. The median inhibitory concentration (IC50) at 24, 48, and 72 h were 28.31, 15.58, and 6.14 μg/ml, respectively. The inhibition of proliferation was found to be statistically significant as compared with the well-established drugs 5-fluorouracil (5-Fu) and oxaliplatin (L-OHP) (p < 0.01). Diterpenoid C also induced apoptosis and arrested cell cycle. It showed the highest apoptosis rate (98.20 ± 0.91%) at 70 μg/ml, at 72 h. Meanwhile, diterpenoid C suppressed the phosphorylation of ERK, JNK, and p38 MAPK proteins, and markedly induced the cleavage of caspase 3.

DISCUSSION AND CONCLUSION

Diterpenoid C inhibits proliferation and induces apoptosis of cancer cells by suppressing the MAPK signaling pathway and inducing apoptotic factor caspase-3. Our results suggest that this novel compound might become a potent chemotherapeutic agent for the treatment of colon cancer and further studies are warranted.

Relevance of different prior knowledge sources for inferring gene interaction networks

When inferring networks from high-throughput genomic data, one of the main challenges is the subsequent validation of these networks. In the best case scenario, the true network is partially known from previous research results published in structured databases or research articles. Traditionally, inferred networks are validated against these known interactions. Whenever the recovery rate is gauged to be high enough, subsequent high scoring but unknown inferred interactions are deemed good candidates for further experimental validation. Therefore such validation framework strongly depends on the quantity and quality of published interactions and presents serious pitfalls: (1) availability of these known interactions for the studied problem might be sparse; (2) quantitatively comparing different inference algorithms is not trivial; and (3) the use of these known interactions for validation prevents their integration in the inference procedure. The latter is particularly relevant as it has recently been showed that integration of priors during network inference significantly improves the quality of inferred networks. To overcome these problems when validating inferred networks, we recently proposed a data-driven validation framework based on single gene knock-down experiments. Using this framework, we were able to demonstrate the benefits of integrating prior knowledge and expression data. In this paper we used this framework to assess the quality of different sources of prior knowledge on their own and in combination with different genomic data sets in colorectal cancer. We observed that most prior sources lead to significant F-scores. Furthermore, their integration with genomic data leads to a significant increase in F-scores, especially for priors extracted from full text PubMed articles, known co-expression modules and genetic interactions. Lastly, we observed that the results are consistent for three different data sets: experimental knock-down data and two human tumor data sets.