Development of novel diagnostic and prognostic molecular markers for sporadic colon cancer

Novel biomarkers for the diagnosis and prognosis of colorectal cancer

Colorectal cancer (CRC) is among the most common malignancies and remains a major cause of cancer-related death worldwide. Despite recent advances in surgical and multimodal therapies, the overall survival of advanced CRC patients remains very low. Cancer progression, including invasion and metastasis, is a major cause of death among CRC patients. The underlying mechanisms of action resulting in cancer progression are beginning to unravel. The reported molecular and biochemical mechanisms that might contribute to the phenotypic changes in favor of carcinogenesis include apoptosis inhibition, enhanced tumor cell proliferation, increased invasiveness, cell adhesion perturbations, angiogenesis promotion, and immune surveillance inhibition. These events may contribute to the development and progression of cancer. A biomarker is a molecule that can be detected in tissue, blood, or stool samples to allow the identification of pathological conditions such as cancer. Thus, it would be beneficial to identify reliable and practical molecular biomarkers that aid in the diagnostic and therapeutic processes of CRC. Recent research has targeted the development of biomarkers that aid in the early diagnosis and prognostic stratification of CRC. Despite that, the identification of diagnostic, prognostic, and/or predictive biomarkers remains challenging, and previously identified biomarkers might be insufficient to be clinically applicable or offer high patient acceptability. Here, we discuss recent advances in the development of molecular biomarkers for their potential usefulness in early and less-invasive diagnosis, treatment, and follow-up of CRC.

Forkhead‑box A1 regulates tumor cell growth and predicts prognosis in colorectal cancer

Forkhead box A1 (FOXA1) functions as a tumor suppressor gene or an oncogene in various types of cancer; however, the distinct function of FOXA1 in colorectal cancer is unclear. The present study aimed to evaluate whether FOXA1 affects the oncogenic behavior of colorectal cancer cells, and to investigate its prognostic value in colorectal cancer. The impact of FOXA1 on tumor cell behavior was investigated using small interfering RNA and the pcDNA6‑myc vector in human colorectal cancer cell lines. To investigate the role of FOXA1 in the progression of human colorectal cancer, an immunohistochemical technique was used to localize FOXA1 protein in paraffin‑embedded tissue blocks obtained from 403 patients with colorectal cancer. Tumor cell apoptosis and proliferation were evaluated using a terminal deoxynucleotidyl transferase‑mediated dUTP nick‑end labeling assay and Ki‑67 immunohistochemical staining, respectively. FOXA1 knockdown inhibited tumor cell invasion in colorectal cancer cells, and induced apoptosis and cell cycle arrest. FOXA1 knockdown activated cleaved caspase‑poly (ADP‑ribose) polymerase, upregulated the expression of p53 upregulated modulator of apoptosis, and downregulated BH3 interacting domain death agonist and myeloid cell leukemia‑1, leading to the induction of apoptosis. FOXA1 knockdown increased the phosphorylation level of signal transducer and activator of tran-scription‑3. By contrast, these results were reversed following the overexpression of FOXA1. The overexpression of FOXA1 was associated with differentiation, lymphovascular invasion, advanced tumor stage, depth of invasion, lymph node metastasis and poor survival rate. The mean Ki‑67 labeling index value of FOXA1‑positive tumors was significantly higher than that of FOXA1‑negative tumors. However, no significant association was observed between the expression of FOXA1 and the mean apoptotic index value. These results indicate that FOXA1 is associated with tumor progression via the modulation of tumor cell survival in human colorectal cancer.

Expression of Livin in colorectal cancer and its relationship to tumor cell behavior and prognosis

BACKGROUNDS

Expression of Livin, a member of the inhibitors of apoptosis protein family, is associated with tumor development and progression. The aims of this study were to evaluate whether Livin affects oncogenic biological behavior of colorectal cancer cells, and to document the relationship between its expression and various clinicopathological parameters in colorectal cancer.

METHODS

We investigated the impact of Livin on tumor cell behavior by using the small interfering RNA and pcDNA3.1 vector in SW480 and DKO1 colorectal cancer cell lines. The expression of Livin was investigated by RT-PCR and immunohistochemistry in coloretcal cancer tissues. The apoptotic cells were visualized by TUNEL assay, and proliferative cells were visualized by Ki-67 antibody staining.

RESULTS

Knockdown of Livin suppressed tumor cell migration and invasion in colorectal cancer cells. Knockdown of Livin induced the apoptosis by up-regulating of caspase-3, -7 and PARP activities and the cell cycle arrest by decreasing cyclin D1, cyclin D3, cyclin-dependent kinase 4 and 6, and by inducing p27 expression. The MAPK signaling cascades were significantly blocked by knockdown of Livin. In contrast, overexpression of Livin enhanced tumor cell migration and invasion, and inhibited the apoptosis and cell cycle arrest. The mean apoptotic index (AI) value of Livin positive tumors was significantly lower than AI of Livin negative tumors. However, there was no significant difference between Livin expression and Ki-67 labeling index (KI). Livin expression was significantly increased in colorectal cancer and metastatic lymph node tissues compared to normal colorectal mucosa and non-metastatic lymph node tissues and was associated with tumor stage, lymphovascular invasion, lymph node metastasis and poor survival.

CONCLUSIONS

These results indicate that Livin is associated with tumor progression by increasing tumor cell motility and inhibiting apoptosis in colorectal cancer.

Sample preparation and fractionation for proteome analysis and cancer biomarker discovery by mass spectrometry

Sample preparation and fractionation technologies are one of the most crucial processes in proteomic analysis and biomarker discovery in solubilized samples. Chromatographic or electrophoretic proteomic technologies are also available for separation of cellular protein components. There are, however, considerable limitations in currently available proteomic technologies as none of them allows for the analysis of the entire proteome in a simple step because of the large number of peptides, and because of the wide concentration dynamic range of the proteome in clinical blood samples. The results of any undertaken experiment depend on the condition of the starting material. Therefore, proper experimental design and pertinent sample preparation is essential to obtain meaningful results, particularly in comparative clinical proteomics in which one is looking for minor differences between experimental (diseased) and control (nondiseased) samples. This review discusses problems associated with general and specialized strategies of sample preparation and fractionation, dealing with samples that are solution or suspension, in a frozen tissue state, or formalin-preserved tissue archival samples, and illustrates how sample processing might influence detection with mass spectrometric techniques. Strategies that dramatically improve the potential for cancer biomarker discovery in minimally invasive, blood-collected human samples are also presented.

Role of miRNA in carcinogenesis and biomarker selection: a methodological view

miRNAs, their involvement in cancer development and their potential to be robust biomarkers of diagnosis, staging, prognosis and response to therapy are reviewed. In small RNA animal biogenesis, miRNA genes in the nucleus are transcribed to generate long primary transcripts (pri-miRNAs), which are first cropped by RNase-III-type enzyme Drosha to release hairpin intermediates (pre-miRNAs) in the nucleus. Pre-miRNA is then exported to the cytoplasm by exportin-5. Following arrival in the cytoplasm, pre-miRNAs are subjected to the second processing step (dicing) to release the mature miRNA duplex, which is then separated: one strand becomes the mature miRNA and the other is degraded. These tiny miRNAs induce messenger degradation, translational repression or both. However, there is no evidence to demonstrate that these two mechanisms exist in the regulation of the same gene. Since a miRNA can target numerous mRNAs, often in combination with other miRNAs, these miRNAs operate a highly complex regulatory network. The specific function in most mammalian miRNAs is unknown. However, data suggest that miRNA genes, approximately 1% of all human genes, regulate protein production for 20-30% or more of all genes. miRNA expression profiles are effective for classifying solid and hematologic human cancers, and have shown great promise for early cancer detection. This is of great importance for effective treatment before the cells metastasize; therefore, tumors can be surgically resected. Computer-based prediction approaches of miRNAs and their targets, and biological validation techniques for ascertaining these predictions, currently play a central role in the discovery of miRNAs and in elucidating their function. Guidelines have been established for the identification and annotation of new miRNAs to distinguish them from other RNAs, especially siRNAs. These guidelines take into account factors such as transcript structure, conservation and processing, and a centralized, searchable database of all possible miRNA sequence information and annotation for humans and of more than 38 other species. Two approaches are used to characterize miRNAs: studying expression of known miRNAs by hybridization-based techniques (e.g., northern blots, RNase protection, primer extension, real-time, quantitative PCR and microarrays) or discovery of novel miRNAs molecules by cloning and sequencing. Owing to their adaptability and high throughput, microarrays may prove to be the preferred platform for whole-genome miRNA expression analysis.

Molecular markers that predict response to colon cancer therapy

Progress in the treatment of colon cancer depends on the development of target-based molecules built on an improved understanding of the molecular biology of the disease. Defining end points for chemotherapy resistance is needed as drug resistance develops quickly and patients demonstrate variation in response to chemotherapy. Many techniques that measure a marker's preponderance have been developed including biochemical, immunohistochemical, genomics, proteomics or a combination thereof. However, standardization of these techniques that measure either genes or their protein products is urgently needed. This article reviews several markers (TS,TP, DPD, FT, EGFR, VEGF, CD44v6, TRAIL, microsatellite instability, allelic deletions, oncogenes and suppressor genes [c-myc, Ki-Ras, p53, p21, Topo I, Topo IIalpha, Fos, hMLH1, Bcl-2/Bax and MDR1], MDR-related proteins [Pgp, MRP and LRP], genomic polymorphisms [XPD, ERCC1, GSTP1 and TS 3 -UTR] and COX-;2) that influence DNA metabolism, DNA damage, programmed cell death, the immune or vascular system, or lead to mutations. When combined together and tested by newly developed genomic and proteomic approaches, many of these markers provide a more sensitive indicative predictor of response than when evaluated separately or by older biochemical, immunohistologic or morphologic methods. A global approach involving the simultaneous testing of several predictive multimarkers will provide critical information for improving chemotherapy to alleviate suffering from this disease.

Microarray RNA transcriptional profiling: part II. Analytical considerations and annotation

This review summarizes the various data filtration, transformation and normalization processes for different array platforms (cDNA, oligos, one- and two-color), data analysis methods and their validation, and databases and annotation for RNA transcriptional profiling microarrays. This review is intended to introduce the beginner to the analyses and interpretation of gene expression studies using a nonmathematical approach for easier comprehension. Microarray analysis is not a trivial undertaking as there is no single method that works well for all, and results obtained from these analyses should be considered as a complement to other approaches.

Nucleic acid quantification and disease outcome prediction in colorectal cancer

Histopathological stage at diagnosis remains the most important prognostic determinant for colorectal cancer. However, conventional staging is unable to predict disease outcome accurately for each individual patient. This results in considerable prognostic heterogeneity within a given tumor stage and is of particular relevance for a subgroup of patients with stage II disease that would benefit from adjuvant therapy. The recent advances in functional genomics are beginning to have a significant impact on clinical oncology, and there is widespread interest in using molecular techniques for clinical applications. These have focused on two approaches: the use of polymerase chain reaction (PCR)-based methods for the detection of occult disease in lymph nodes, bone marrow and blood and the use of microarrays for the expression profiling of primary tumors. The aim is to develop molecular classifiers that will allow the prediction of disease outcome, thus matching patients with individualized treatment. Despite the obvious attractions of these approaches, there have been significant technical, biological and analytical problems in their translation into clinically relevant practice. This is particularly true for colorectal cancer, the second most common cancer in the western world. Nevertheless, progress is being made and the improved awareness and appreciation of those difficulties is beginning to generate results that should prove useful for clinical oncology.

Gene-gene, gene-environment & multiple interactions in colorectal cancer

This review comprehensively evaluates the influence of gene-gene, gene-environment and multiple interactions on the risk of colorectal cancer (CRC). Methods of studying these interactions and their limitations have been discussed herein. There is a need to develop biomarkers of exposure and of risk that are sensitive, specific, present in the pathway of the disease, and that have been clinically tested for routine use. The influence of inherited variation (polymorphism) in several genes has been discussed in this review; however, due to study limitations and confounders, it is difficult to conclude which ones are associated with the highest risk (either individually or in combination with environmental factors) to CRC. The majority of the sporadic cancer is believed to be due to modification of mutation risk by other genetic and/or environmental factors. Micronutrient deficiency may explain the association between low consumption of fruit/vegetables and CRC in human studies. Mitochondrial modulation by dietary factors influences the balance between cell renewal and death critical in colon mucosal homeostasis. Both genetic and epigenetic interactions are intricately dependent on each other, and collectively influence the process of colorectal tumorigenesis. The genetic and environmental interactions present a good prospect and a challenge for prevention strategies for CRC because they support the view that this highly prevalent cancer is preventable.