BAY61-3606 affects the viability of colon cancer cells in a genotype-directed manner

Background

K-RAS mutation poses a particularly difficult problem for cancer therapy. Activating mutations in K-RAS are common in cancers of the lung, pancreas, and colon and are associated with poor response to therapy. As such, targeted therapies that abrogate K-RAS-induced oncogenicity would be of tremendous value.

Methods

We searched for small molecule kinase inhibitors that preferentially affect the growth of colorectal cancer cells expressing mutant K-RAS. The mechanism of action of one inhibitor was explored using chemical and genetic approaches.

Results

We identified BAY61-3606 as an inhibitor of proliferation in colorectal cancer cells expressing mutant forms of K-RAS, but not in isogenic cells expressing wild-type K-RAS. In addition to its anti-proliferative effects in mutant cells, BAY61-3606 exhibited a distinct biological property in wild-type cells in that it conferred sensitivity to inhibition of RAF. In this context, BAY61-3606 acted by inhibiting MAP4K2 (GCK), which normally activates NFκβ signaling in wild-type cells in response to inhibition of RAF. As a result of MAP4K2 inhibition, wild-type cells became sensitive to AZ-628, a RAF inhibitor, when also treated with BAY61-3606.

Conclusions

These studies indicate that BAY61-3606 exerts distinct biological activities in different genetic contexts.     

Activin Signaling in Microsatellite Stable Colon Cancers Is Disrupted by a Combination of Genetic and Epigenetic Mechanisms

Background

Activin receptor 2 (ACVR2) is commonly mutated in microsatellite unstable (MSI) colon cancers, leading to protein loss, signaling disruption, and larger tumors. Here, we examined activin signaling disruption in microsatellite stable (MSS) colon cancers.

Methods

Fifty-one population-based MSS colon cancers were assessed for ACVR1, ACVR2 and pSMAD2 protein. Consensus mutation-prone portions of ACVR2 were sequenced in primary cancers and all exons in colon cancer cell lines. Loss of heterozygosity (LOH) was evaluated for ACVR2 and ACVR1, and ACVR2 promoter methylation by methylation-specific PCR and bisulfite sequencing and chromosomal instability (CIN) phenotype via fluorescent LOH analysis of 3 duplicate markers. ACVR2 promoter methylation and ACVR2 expression were assessed in colon cancer cell lines via qPCR and IP-Western blots. Re-expression of ACVR2 after demethylation with 5-aza-2′-deoxycytidine (5-Aza) was determined. An additional 26 MSS colon cancers were assessed for ACVR2 loss and its mechanism, and ACVR2 loss in all tested cancers correlated with clinicopathological criteria.

Results

Of 51 MSS colon tumors, 7(14%) lost ACVR2, 2 (4%) ACVR1, and 5(10%) pSMAD2 expression. No somatic ACVR2 mutations were detected. Loss of ACVR2 expression was associated with LOH at ACVR2 (p<0.001) and ACVR2 promoter hypermethylation (p<0.05). ACVR2 LOH, but not promoter hypermethylation, correlated with CIN status. In colon cancer cell lines with fully methylated ACVR2 promoter, loss of ACVR2 mRNA and protein expression was restored with 5-Aza treatment. Loss of ACVR2 was associated with an increase in primary colon cancer volume (p<0.05).

Conclusions

Only a small percentage of MSS colon cancers lose expression of activin signaling members. ACVR2 loss occurs through LOH and ACVR2 promoter hypermethylation, revealing distinct mechanisms for ACVR2 inactivation in both MSI and MSS subtypes of colon cancer.     

Mirna expression profiles identify drivers in colorectal and pancreatic cancers

Background and Aim

Altered expression of microRNAs (miRNAs) hallmarks many cancer types. The study of the associations of miRNA expression profile and cancer phenotype could help identify the links between deregulation of miRNA expression and oncogenic pathways.

Methods

Expression profiling of 866 human miRNAs in 19 colorectal and 17 pancreatic cancers and in matched adjacent normal tissues was investigated. Classical paired t-test and random forest analyses were applied to identify miRNAs associated with tissue-specific tumors. Network analysis based on a computational approach to mine associations between cancer types and miRNAs was performed.

Results

The merge between the two statistical methods used to intersect the miRNAs differentially expressed in colon and pancreatic cancers allowed the identification of cancer-specific miRNA alterations. By miRNA-network analysis, tissue-specific patterns of miRNA deregulation were traced: the driving miRNAs were miR-195, miR-1280, miR-140-3p and miR-1246 in colorectal tumors, and miR-103, miR-23a and miR-15b in pancreatic cancers.

Conclusion

MiRNA expression profiles may identify cancer-specific signatures and potentially useful biomarkers for the diagnosis of tissue specific cancers. miRNA-network analysis help identify altered miRNA regulatory networks that could play a role in tumor pathogenesis.     

Somatic mutation profiles of MSI and MSS colorectal cancer identified by whole exome next generation sequencing and bioinformatics analysis

Background

Colorectal cancer (CRC) is with approximately 1 million cases the third most common cancer worldwide. Extensive research is ongoing to decipher the underlying genetic patterns with the hope to improve early cancer diagnosis and treatment. In this direction, the recent progress in next generation sequencing technologies has revolutionized the field of cancer genomics. However, one caveat of these studies remains the large amount of genetic variations identified and their interpretation.

Methodology/Principal Findings

Here we present the first work on whole exome NGS of primary colon cancers. We performed 454 whole exome pyrosequencing of tumor as well as adjacent not affected normal colonic tissue from microsatellite stable (MSS) and microsatellite instable (MSI) colon cancer patients and identified more than 50,000 small nucleotide variations for each tissue. According to predictions based on MSS and MSI pathomechanisms we identified eight times more somatic non-synonymous variations in MSI cancers than in MSS and we were able to reproduce the result in four additional CRCs. Our bioinformatics filtering approach narrowed down the rate of most significant mutations to 359 for MSI and 45 for MSS CRCs with predicted altered protein functions. In both CRCs, MSI and MSS, we found somatic mutations in the intracellular kinase domain of bone morphogenetic protein receptor 1A, BMPR1A, a gene where so far germline mutations are associated with juvenile polyposis syndrome, and show that the mutations functionally impair the protein function.

Conclusions/Significance

We conclude that with deep sequencing of tumor exomes one may be able to predict the microsatellite status of CRC and in addition identify potentially clinically relevant mutations.     

HotSpotter: efficient visualization of driver mutations

Background

Driver mutations are positively selected during the evolution of cancers. The relative frequency of a particular mutation within a gene is typically used as a criterion for identifying a driver mutation. However, driver mutations may occur with relative infrequency at a particular site, but cluster within a region of the gene. When analyzing across different cancers, particular mutation sites or mutations within a particular region of the gene may be of relatively low frequency in some cancers, but still provide selective growth advantage.

Results

This paper presents a method that allows rapid and easy visualization of mutation data sets and identification of potential gene mutation hotspot sites and/or regions. As an example, we identified hotspot regions in the NFE2L2 gene that are potentially functionally relevant in endometrial cancer, but would be missed using other analyses.

Conclusions

HotSpotter is a quick, easy-to-use visualization tool that delivers gene identities with associated mutation locations and frequencies overlaid upon a large cancer mutation reference set. This allows the user to identify potential driver mutations that are less frequent in a cancer or are localized in a hotspot region of relatively infrequent mutations.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1044) contains supplementary material, which is available to authorized users.     

Transcriptional Regulation and Biological Functions of Selenium-Binding Protein 1 in Colorectal Cancer In Vitro and in Nude Mouse Xenografts

Background

It has been shown that selenium-binding protein 1 (SBP1) is significantly downregulated in different human cancers. Its regulation and function have not yet been established.

Methodology and Principal Findings

We show that the SBP1 promoter is hypermethylated in colon cancer tissues and human colon cancer cells. Treatment with 5′-Aza-2′-deoxycytidine leads to demethylation of the SBP1 promoter and to an increase of SBP1 promoter activity, rescues SBP1 mRNA and protein expression in human colon cancer cells. Additionally, overexpression of SBP1 sensitizes colon cancer cells to H₂O₂-induced apoptosis, inhibits cancer cell migration in vitro and inhibits tumor growth in nude mice.

Conclusion and Significance

These data demonstrate that SBP1 has tumor suppressor functions that are inhibited in colorectal cancer through epigenetic silencing.     

A Systematic Proteomic Study of Irradiated DNA Repair Deficient Nbn-Mice

Background

The NBN gene codes for the protein nibrin, which is involved in the detection and repair of DNA double strand breaks (DSBs). The NBN gene is essential in mammals.

Methodology/Principal Findings

We have used a conditional null mutant mouse model in a proteomics approach to identify proteins with modified expression levels after 4 Gy ionizing irradiation in the absence of nibrin in vivo. Altogether, amongst ∼8,000 resolved proteins, 209 were differentially expressed in homozygous null mutant mice in comparison to control animals. One group of proteins significantly altered in null mutant mice were those involved in oxidative stress and cellular redox homeostasis (p<0.0001). In substantiation of this finding, analysis of Nbn null mutant fibroblasts indicated an increased production of reactive oxygen species following induction of DSBs.

Conclusions/Significance

In humans, biallelic hypomorphic mutations in NBN lead to Nijmegen breakage syndrome (NBS), an autosomal recessive genetic disease characterised by extreme radiosensitivity coupled with growth retardation, immunoinsufficiency and a very high risk of malignancy. This particularly high cancer risk in NBS may be attributable to the compound effect of a DSB repair defect and oxidative stress.     

Assessing the activity of nonsense-mediated mRNA decay in lung cancer

Background

Inhibition of nonsense-mediated mRNA decay (NMD) in tumor cells can suppress tumor growth through expressing new antigens whose mRNAs otherwise are degraded by NMD. Thus NMD inhibition is a promising approach for developing cancer therapies. Apparently, the success of this approach relies on the basal NMD activity in cancer cells. If NMD is already strongly inhibited in tumors, the approach would not work. Therefore, it is crucial to assess NMD activity in cancers to forecast the efficacy of NMD-inhibition based therapy.

Methods

Here we develop three metrics using RNA-seq data to measure NMD activity, and apply them to a dataset consisting of 72 lung cancer (adenocarcinoma) patients.

Results

We show that these metrics have good correlations, and that the NMD activities in adenocarcinoma samples vary among patients: some cancerous samples show significantly stronger NMD activities than the normal tissues while some others show the opposite pattern. The variation of NMD activities among these samples may be partly explained by the varying expression of NMD effectors.

Conclusions

In sum, NMD activity varies among lung cancerous samples, which forecasts varying efficacies of NMD-inhibition based therapy. The developed metrics can be further used in other cancer types to assess NMD activity.

     

ENCAPP: elastic-net-based prognosis prediction and biomarker discovery for human cancers

Background

With the explosion of genomic data over the last decade, there has been a tremendous amount of effort to understand the molecular basis of cancer using informatics approaches. However, this has proven to be extremely difficult primarily because of the varied etiology and vast genetic heterogeneity of different cancers and even within the same cancer. One particularly challenging problem is to predict prognostic outcome of the disease for different patients.

Results

Here, we present ENCAPP, an elastic-net-based approach that combines the reference human protein interactome network with gene expression data to accurately predict prognosis for different human cancers. Our method identifies functional modules that are differentially expressed between patients with good and bad prognosis and uses these to fit a regression model that can be used to predict prognosis for breast, colon, rectal, and ovarian cancers. Using this model, ENCAPP can also identify prognostic biomarkers with a high degree of confidence, which can be used to generate downstream mechanistic and therapeutic insights.

Conclusion

ENCAPP is a robust method that can accurately predict prognostic outcome and identify biomarkers for different human cancers.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1465-9) contains supplementary material, which is available to authorized users.     

Differences in Survival between Colon and Rectal Cancer from SEER Data

Background

Little is known about colorectal cancer or colon and rectal cancer. Are they the same disease or different diseases?

Objectives

The aim of this epidemiology study was to compare the features of colon and rectal cancer by using recent national cancer surveillance data.

Design and setting

Data included colorectal cancer (1995–2008) from the Surveillance, Epidemiology, and End Results Program (SEER) database. Only adenocarcinoma was included for analysis.

Patients

A total of 372,130 patients with a median follow-up of 32 months were analyzed.

Main outcome measures

Mean survival of patients with the same stage of colon and rectal cancer was evaluated.

Results

Around 35% of patients had stage information. Among them, colon cancer patients had better survival than those with rectal cancer, by a margin of 4 months in stage IIB. In stage IIIC and stage IV, rectal cancer patients had better survival than colon cancer patients, by about 3 months. Stage IIB colorectal cancer patients had a poorer prognosis than those with stage IIIA and IIIB colorectal cancer. After adjustment of age, sex and race, colon cancer patients had better survival than rectal cancer of stage IIB, but in stage IIIC and IV, rectal cancer patients had better survival than colon cancer.

Limitations

The study is limited by its retrospective nature.

Conclusion

This was a population-based study. The prognosis of rectal cancer was not worse than that of colon cancer. Local advanced colorectal cancer had a poorer prognosis than local regional lymph node metastasis. Stage IIB might require more aggressive chemotherapy, and no less than that for stage III.