Gene Expression Profiles and Molecular Markers To Predict Recurrence of Dukes' B Colon Cancer

The Spectrum of Clinical Utilities in Molecular Pathology Testing Procedures for Inherited Conditions and Cancer: A Report of the Association for Molecular Pathology

Clinical utility describes the benefits of each laboratory test for that patient. Many stakeholders have adopted narrow definitions for the clinical utility of molecular testing as applied to targeted pharmacotherapy in oncology, regardless of the population tested or the purpose of the testing. This definition does not address all of the important applications of molecular diagnostic testing. Definitions consistent with a patient-centered approach emphasize and recognize that a clinical test result's utility depends on the context in which it is used and are particularly relevant to molecular diagnostic testing because of the nature of the information they provide. Debates surrounding levels and types of evidence needed to properly evaluate the clinical value of molecular diagnostics are increasingly important because the growing body of knowledge, stemming from the increase of genomic medicine, provides many new opportunities for molecular testing to improve health care. We address the challenges in defining the clinical utility of molecular diagnostics for inherited diseases or cancer and provide assessment recommendations. Starting with a modified analytic validity, clinical validity, clinical utility, and ethical, legal, and social implications model for addressing clinical utility of molecular diagnostics with a variety of testing purposes, we recommend promotion of patient-centered definitions of clinical utility that appropriately recognize the valuable contribution of molecular diagnostic testing to improve patient care.

New trends in molecular and cellular biomarker discovery for colorectal cancer

Colorectal cancer (CRC) is the third leading cause of cancer death worldwide, which is consequence of multistep tumorigenesis of several genetic and epigenetic events. Since CRC is mostly asymptomatic until it progresses to advanced stages, the early detection using effective screening approaches, selection of appropriate therapeutic strategies and efficient follow-up programs are essential to reduce CRC mortalities. Biomarker discovery for CRC based on the personalized genotype and clinical information could facilitate the classification of patients with certain types and stages of cancer to tailor preventive and therapeutic approaches. These cancer-related biomarkers should be highly sensitive and specific in a wide range of specimen(s) (including tumor tissues, patients’ fluids or stool). Reliable biomarkers which enable the early detection of CRC, can improve early diagnosis, prognosis, treatment response prediction, and recurrence risk. Advances in our understanding of the natural history of CRC have led to the development of different CRC associated molecular and cellular biomarkers. This review highlights the new trends and approaches in CRC biomarker discovery, which could be potentially used for early diagnosis, development of new therapeutic approaches and follow-up of patients.

Comparison of Nanostring nCounter® Data on FFPE Colon Cancer Samples and Affymetrix Microarray Data on Matched Frozen Tissues

The prognosis of colorectal cancer (CRC) stage II and III patients remains a challenge due to the difficulties of finding robust biomarkers suitable for testing clinical samples. The majority of published gene signatures of CRC have been generated on fresh frozen colorectal tissues. Because collection of frozen tissue is not practical for routine surgical pathology practice, a clinical test that improves prognostic capabilities beyond standard pathological staging of colon cancer will need to be designed for formalin-fixed paraffin-embedded (FFPE) tissues. The NanoString nCounter^® platform is a gene expression analysis tool developed for use with FFPE-derived samples. We designed a custom nCounter^® codeset based on elements from multiple published fresh frozen tissue microarray-based prognostic gene signatures for colon cancer, and we used this platform to systematically compare gene expression data from FFPE with matched microarray array data from frozen tissues. Our results show moderate correlation of gene expression between two platforms and discovery of a small subset of genes as candidate biomarkers for colon cancer prognosis that are detectable and quantifiable in FFPE tissue sections.

IGFBP-3 Gene Methylation in Primary Tumor Predicts Recurrence of Stage II Colorectal Cancers

OBJECTIVES

To evaluate the influence of IGFBP-3 methylation on recurrence in patients with stage II colorectal cancer (CRC) from 2 independent cohorts.

BACKGROUND

The relationship between IGFBP-3 methylation in primary tumors (PTs) or lymph nodes (LNs) and risk of recurrence in patients with stage II CRC treated with surgery alone is unknown.

METHODS

IGFBP-3 methylation of DNA from 115 PTs and 1641 LNs in patients with stage II CRC from 2 independent cohorts was analyzed. Forty patients developed recurrence, whereas 75 matched patients remained recurrence free for more than 2 years after surgery. Cox proportional hazard models were used to calculate hazard ratios (HRs) of recurrence, adjusted for patient and tumor characteristics.

RESULTS

Methylation of IGFBP-3 in PTs was identified to be significantly associated with risk of recurrence in the training set. The signature was tested in a validation set and classified 40.7% of patients as high risk. Five-year recurrence-free survival rates were 76.4% and 58.3% for low- and high-risk patients, respectively, with an HR of 2.21 (95% confidence interval, 1.04-4.68; P = 0.039). In multivariate analysis, the signature remained the most significant prognostic factor, with an HR of 2.40 (95% confidence interval, 1.10-5.25; P = 0.029). A combined analysis of 1641 LNs from the 2 sets identified IGFBP-3 methylation in LNs was not associated with risk of recurrence.

CONCLUSIONS

Detection of IGFBP-3 methylation in PTs, but not in LNs, provides a powerful tool for the identification of patients with stage II CRC at high risk of recurrence.

Gene expression profile predictive of response to chemotherapy in metastatic colorectal cancer

Fluoropyrimidine-based chemotherapy (CT) has been the mainstay of care of metastatic colorectal cancer (mCRC) for years. Response rates are only observed, however, in about half of treated patients, and there are no reliable tools to prospectively identify patients more likely to benefit from therapy. The purpose of our study was to identify a gene expression profile predictive of CT response in mCRC. Whole genome expression analyses (Affymetrix GeneChip^® HG-U133 Plus 2.0) were performed in fresh frozen tumor samples of 37 mCRC patients (training cohort). Differential gene expression profiles among the two study conditions (responders versus non-responders) were assessed using supervised class prediction algorithms. A set of 161 differentially expressed genes in responders (23 patients; 62%) versus non-responders (14 patients; 38%) was selected for further assessment and validation by RT-qPCR (TaqMan^®Low Density Arrays (TLDA) 7900 HT Micro Fluidic Cards) in an independent multi-institutional cohort (53 mCRC patients). Seven of these genes were confirmed as significant predictors of response. Patients with a favorable predictive signature had significantly greater response rate (58% vs 13%, p = 0.024), progression-free survival (61% vs 13% at 1 year, HR = 0.32, p = 0.009) and overall survival (32 vs 16 months, HR = 0.21, p = 0.003) than patients with an unfavorable gene signature. This is the first study to validate a gene-expression profile predictive of response to CT in mCRC patients. Larger and prospective confirmatory studies are required, however, in order to successfully provide oncologists with adequate tools to optimize treatment selection in routine clinical practice.

CDX2 as a Prognostic Biomarker in Stage II and Stage III Colon Cancer

Background The identification of high-risk stage II colon cancers is key to the selection of patients who require adjuvant treatment after surgery. Microarray-based multigene-expression signatures derived from stem cells and progenitor cells hold promise, but they are difficult to use in clinical practice. Methods We used a new bioinformatics approach to search for biomarkers of colon epithelial differentiation across gene-expression arrays and then ranked candidate genes according to the availability of clinical-grade diagnostic assays. With the use of subgroup analysis involving independent and retrospective cohorts of patients with stage II or stage III colon cancer, the top candidate gene was tested for its association with disease-free survival and a benefit from adjuvant chemotherapy. Results The transcription factor CDX2 ranked first in our screening test. A group of 87 of 2115 tumor samples (4.1%) lacked CDX2 expression. In the discovery data set, which included 466 patients, the rate of 5-year disease-free survival was lower among the 32 patients (6.9%) with CDX2-negative colon cancers than among the 434 (93.1%) with CDX2-positive colon cancers (hazard ratio for disease recurrence, 3.44; 95% confidence interval [CI], 1.60 to 7.38; P=0.002). In the validation data set, which included 314 patients, the rate of 5-year disease-free survival was lower among the 38 patients (12.1%) with CDX2 protein-negative colon cancers than among the 276 (87.9%) with CDX2 protein-positive colon cancers (hazard ratio, 2.42; 95% CI, 1.36 to 4.29; P=0.003). In both these groups, these findings were independent of the patient's age, sex, and tumor stage and grade. Among patients with stage II cancer, the difference in 5-year disease-free survival was significant both in the discovery data set (49% among 15 patients with CDX2-negative tumors vs. 87% among 191 patients with CDX2-positive tumors, P=0.003) and in the validation data set (51% among 15 patients with CDX2-negative tumors vs. 80% among 106 patients with CDX2-positive tumors, P=0.004). In a pooled database of all patient cohorts, the rate of 5-year disease-free survival was higher among 23 patients with stage II CDX2-negative tumors who were treated with adjuvant chemotherapy than among 25 who were not treated with adjuvant chemotherapy (91% vs. 56%, P=0.006). Conclusions Lack of CDX2 expression identified a subgroup of patients with high-risk stage II colon cancer who appeared to benefit from adjuvant chemotherapy. (Funded by the National Comprehensive Cancer Network, the National Institutes of Health, and others.).

ColoLipidGene: signature of lipid metabolism-related genes to predict prognosis in stage-II colon cancer patients

Lipid metabolism plays an essential role in carcinogenesis due to the requirements of tumoral cells to sustain increased structural, energetic and biosynthetic precursor demands for cell proliferation. We investigated the association between expression of lipid metabolism-related genes and clinical outcome in intermediate-stage colon cancer patients with the aim of identifying a metabolic profile associated with greater malignancy and increased risk of relapse. Expression profile of 70 lipid metabolism-related genes was determined in 77 patients with stage II colon cancer. Cox regression analyses using c-index methodology was applied to identify a metabolic-related signature associated to prognosis. The metabolic signature was further confirmed in two independent validation sets of 120 patients and additionally, in a group of 264 patients from a public database. The combined analysis of these 4 genes, ABCA1, ACSL1, AGPAT1 and SCD, constitutes a metabolic-signature (ColoLipidGene) able to accurately stratify stage II colon cancer patients with 5-fold higher risk of relapse with strong statistical power in the four independent groups of patients. The identification of a group of 4 genes that predict survival in intermediate-stage colon cancer patients allows delineation of a high-risk group that may benefit from adjuvant therapy, and avoids the toxic and unnecessary chemotherapy in patients classified as low-risk group.

Overexpression of the S100A2 protein as a prognostic marker for patients with stage II and III colorectal cancer

We aimed to identify a novel prognostic biomarker related to recurrence in stage II and III colorectal cancer (CRC) patients. Stage II and III CRC tissue mRNA expression was profiled using an Affymetrix Gene Chip, and copy number profiles of 125 patients were generated using an Affymetrix 250K Sty array. Genes showing both upregulated expression and copy number gains in cases involving recurrence were extracted as candidate biomarkers. The protein expression of the candidate gene was assessed using immunohistochemical staining of tissue from 161 patients. The relationship between protein expression and clinicopathological features was also examined. We identified 9 candidate genes related to recurrence of stage II and III CRC, whose mRNA expression was significantly higher in CRC than in normal tissue. Of these proteins, the S100 calcium-binding protein A2 (S100A2) has been observed in several human cancers. S100A2 protein overexpression in CRC cells was associated with significantly worse overall survival and relapse-free survival, indicating that S100A2 is an independent risk factor for stage II and III CRC recurrence. S100A2 overexpression in cancer cells could be a biomarker of poor prognosis in stage II and III CRC recurrence and a target for treatment of this disease.

Identifying molecular subtypes in human colon cancer using gene expression and DNA methylation microarray data

Identifying colon cancer subtypes based on molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications using gene expression data have been attempted before with little concordance between the different studies carried out. In this study we aimed to uncover subtypes of colon cancer that have distinct biological characteristics and identify a set of novel biomarkers which could best reflect the clinical and/or biological characteristics of each subtype. Clustering analysis and discriminant analysis were utilized to discover the subtypes in two different molecular levels on 153 colon cancer samples from The Cancer Genome Atlas (TCGA) Data Portal. At gene expression level, we identified two major subtypes, ECL1 (expression cluster 1) and ECL2 (expression cluster 2) and a list of signature genes. Due to the heterogeneity of colon cancer, the subtype ECL1 can be further subdivided into three nested subclasses, and HOTAIR were found upregulated in subclass 2. At DNA methylation level, we uncovered three major subtypes, MCL1 (methylation cluster 1), MCL2 (methylation cluster 2) and MCL3 (methylation cluster 3). We found only three subtypes of CpG island methylator phenotype (CIMP) in colon cancer instead of the four subtypes in the previous reports, and we found no sufficient evidence to subdivide MCL3 into two distinct subgroups.

Prognostic significance of Traf2- and Nck- interacting kinase (TNIK) in colorectal cancer

BACKGROUND

The potential of expression profiling using microarray analysis as a tool to predict the prognosis for different types of cancer has been realized. This study aimed to identify a novel biomarker for colorectal cancer (CRC).

METHODS

The expression profiles of cancer cells in 152 patients with stage I-III CRC were examined using microarray analysis. High expression in CRC cells, especially in patients with distant recurrences, was a prerequisite to select candidate genes. Thus, we identified seventeen candidate genes, and selected Traf2- and Nck-interacting kinase (TNIK), which was known to be associated with progression in CRC through Wnt signaling pathways. We analyzed the protein expression of TNIK using immunohistochemistry (IHC) and investigated the relationship between protein expression and patient characteristics in 220 stage I-III CRC patients.

RESULTS

Relapse-free survival was significantly worse in the TNIK high expression group than in the TNIK low expression group in stage II (p = 0.028) and stage III (p = 0.006) patients. In multivariate analysis, high TNIK expression was identified as a significant independent risk factor of distant recurrence in stage III patients.

CONCLUSION

This study is the first to demonstrate the prognostic significance of intratumoral TNIK protein expression in clinical tissue samples of CRC, in that high expression of TNIK protein in primary tumors was associated with distant recurrence in stage II and III CRC patients. This TNIK IHC study might contribute to practical decision-making in the treatment of these patients.

Gene-expression analysis of a colorectal cancer-specific discriminatory transcript set on formalin-fixed, paraffin-embedded (FFPE) tissue samples

BACKGROUND

A recently published transcript set is suitable for gene expression-based discrimination of normal colonic and colorectal cancer (CRC) biopsy samples. Our aim was to test the discriminatory power of the CRC-specific transcript set on independent biopsies and on formalin-fixed, paraffin-embedded (FFPE) tissue samples.

METHODS

Total RNA isolations were performed with the automated MagNA Pure 96 Cellular RNA Large Volume Kit (Roche) from fresh frozen biopsies stored in RNALater (CRC (n = 15) and healthy colonic (n = 15)), furthermore from FFPE specimens including CRC (n = 15) and normal adjacent tissue (NAT) (n = 15) specimens next to the tumor. After quality and quantity measurements, gene expression analysis of a colorectal cancer-specific marker set with 11 genes (CA7, COL12A1, CXCL1, CXCL2, CHI3L1, GREM1, IL1B, IL1RN, IL8, MMP3, SLC5A7) was performed with array real-time PCR using Transcriptor First Strand cDNA Synthesis Kit (Roche) and RealTime ready assays on LightCycler480 System (Roche). In situ hybridization for two selected transcripts (CA7, CXCL1) was performed on NAT (n = 3), adenoma (n = 3) and CRC (n = 3) FFPE samples.

RESULTS

Although analytical parameters of automatically isolated RNA samples showed differences between fresh frozen biopsy and FFPE samples, both quantity and the quality enabled their application in gene expression analyses. CRC and normal fresh frozen biopsy samples could be distinguished with 93.3% sensitivity and 86.7% specificity and FFPE samples with 96.7 and 70.0%, respectively. In situ hybridization could confirm the upregulation of CXCL1 and downregulation of CA7 in colorectal adenomas and tumors compared to healthy controls.

CONCLUSION

According to our results, gene expression analysis of the analyzed colorectal cancer-specific marker set can also be performed from FFPE tissue material. With the addition of an automated workflow, this marker set may enhance the objective classification of colorectal neoplasias in the routine procedure in the future.

Colorectal Cancer Biomarkers: Where Are We Now?

Colorectal cancer is one of the major causes of cancer-related death in the Western world. Patient survival is highly dependent on the tumor stage at the time of diagnosis. Reduced sensitivity to chemotherapy is still a major obstacle in effective treatment of advanced disease. Due to the fact that colorectal cancer is mostly asymptomatic until it progresses to advanced stages, the implementation of screening programs aimed at early detection is essential to reduce incidence and mortality rates. Current screening and diagnostic methods range from semi-invasive procedures such as colonoscopy to noninvasive stool-based tests. The combination of the absence of symptoms, the semi-invasive nature of currently used methods, and the suboptimal accuracy of fecal blood tests results in colorectal cancer diagnosis at advanced stages in a significant number of individuals. Alterations in gene expression leading to colorectal carcinogenesis are reflected in dysregulated levels of nucleic acids and proteins, which can be used for the development of novel, minimally invasive molecular biomarkers. The purpose of this review is to discuss the commercially available colorectal cancer molecular diagnostic methods as well as to highlight some of the new candidate predictive and prognostic molecular markers for tumor, stool, and blood samples.

The prognostic value of the stem-like group in colorectal cancer using a panel of immunohistochemistry markers

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the Western world. It is becoming increasingly clear that CRC is a diverse disease, as exemplified by the identification of subgroups of CRC tumours that are driven by distinct biology. Recently, a number of studies have begun to define panels of diagnostically relevant markers to align patients into individual subgroups in an attempt to give information on prognosis and treatment response. We examined the immunohistochemical expression profile of 18 markers, each representing a putative role in cancer development, in 493 primary colorectal carcinomas using tissue microarrays. Through unsupervised clustering in stage II cancers, we identified two cluster groups that are broadly defined by inflammatory or immune-related factors (CD3, CD8, COX-2 and FOXP3) and stem-like factors (CD44, LGR5, SOX2, OCT4). The expression of the stem-like group markers was associated with a significantly worse prognosis compared to cases with lower expression. In addition, patients classified in the stem-like subgroup displayed a trend towards a benefit from adjuvant treatment. The biologically relevant and poor prognostic stem-like group could also be identified in early stage I cancers, suggesting a potential opportunity for the identification of aggressive tumors at a very early stage of the disease.

Long non-coding RNA LINC01296 is a potential prognostic biomarker in patients with colorectal cancer

Colorectal cancer (CRC), one of the most malignant cancers, is currently the fourth leading cause of cancer deaths worldwide. Recent studies indicated that long non-coding RNAs (lncRNAs) could be robust molecular prognostic biomarkers that can refine the conventional tumor-node-metastasis staging system to predict the outcomes of CRC patients. In this study, the lncRNA expression profiles were analyzed in five datasets (GSE24549, GSE24550, GSE35834, GSE50421, and GSE31737) by probe set reannotation and an lncRNA classification pipeline. Twenty-five lncRNAs were differentially expressed between CRC tissue and tumor-adjacent normal tissue samples. In these 25 lncRNAs, patients with higher expression of LINC01296, LINC00152, and FIRRE showed significantly better overall survival than those with lower expression (P < 0.05), suggesting that these lncRNAs might be associated with prognosis. Multivariate analysis indicated that LINC01296 overexpression was an independent predictor for patients' prognosis in the test datasets (GSE24549, GSE24550) (P = 0.001) and an independent validation series (GSE39582) (P = 0.027). Our results suggest that LINC01296 could be a novel prognosis biomarker for the diagnosis of CRC.

mRNA expression profiles in circulating tumor cells of metastatic colorectal cancer patients

INTRODUCTION

The molecular characterization of circulating tumor cells (CTCs) is a promising tool for the repeated and non-invasive evaluation of predictive and prognostic factors. Challenges associated with CTC characterization using the only FDA approved method for CTC enumeration, the CellSearch technique, include the presence of an excess of leukocytes in CTC-enriched blood fractions. Here we aimed to identify colorectal tumor-specific gene expression levels in the blood of patients with and without detectable CTCs according to CellSearch criteria.

MATERIALS AND METHODS

Blood of 30 healthy donors (HDs) and 142 metastatic colorectal cancer (mCRC) patients was subjected to CellSearch CTC enumeration and isolation. In all samples, 95 mRNAs were measured by reverse transcriptase quantitative PCR (RT-qPCR). HD blood samples and patient samples with three or more CTCs were compared to identify CTC-specific mRNAs. Patient samples without detectable CTCs were separately analyzed.

RESULTS

Thirty-four CTC-specific mRNAs were higher expressed in patients with ≥3 CTCs compared with HDs (Mann-Whitney U-test P < 0.05). Among patients without detectable CTCs, a HD-unlike subgroup was identified which could be distinguished from HDs by the expression of epithelial genes such as KRT19, KRT20 and AGR2. Also, in an independent patient set, a similar HD-unlike group could be identified among the patients without detectable CTCs according to the CellSearch system.

CONCLUSION

Extensive molecular characterization of colorectal CTCs is feasible and a subgroup of patients without detectable CTCs according to CellSearch criteria bears circulating tumor load, which may have clinical consequences. This CTC-specific gene panel for mCRC patients may enable the exploration of CTC characterization as a novel means to further individualize cancer treatment.

Personalized identification of altered pathways in cancer using accumulated normal tissue data

MOTIVATION

Identifying altered pathways in an individual is important for understanding disease mechanisms and for the future application of custom therapeutic decisions. Existing pathway analysis techniques are mainly focused on discovering altered pathways between normal and cancer groups and are not suitable for identifying the pathway aberrance that may occur in an individual sample. A simple way to identify individual's pathway aberrance is to compare normal and tumor data from the same individual. However, the matched normal data from the same individual are often unavailable in clinical situation. Therefore, we suggest a new approach for the personalized identification of altered pathways, making special use of accumulated normal data in cases when a patient's matched normal data are unavailable. The philosophy behind our method is to quantify the aberrance of an individual sample's pathway by comparing it with accumulated normal samples. We propose and examine personalized extensions of pathway statistics, overrepresentation analysis and functional class scoring, to generate individualized pathway aberrance score.

RESULTS

Collected microarray data of normal tissue of lung and colon mucosa are served as reference to investigate a number of cancer individuals of lung adenocarcinoma (LUAD) and colon cancer, respectively. Our method concurrently captures known facts of cancer survival pathways and identifies the pathway aberrances that represent cancer differentiation status and survival. It also provides more improved validation rate of survival-related pathways than when a single cancer sample is interpreted in the context of cancer-only cohort. In addition, our method is useful in classifying unknown samples into cancer or normal groups. Particularly, we identified 'amino acid synthesis and interconversion' pathway is a good indicator of LUAD (Area Under the Curve (AUC) 0.982 at independent validation). Clinical importance of the method is providing pathway interpretation of single cancer, even though its matched normal data are unavailable.

AVAILABILITY AND IMPLEMENTATION

The method was implemented using the R software, available at our Web site: http://bibs.snu.ac.kr/ipas.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genomic classifier ColoPrint predicts recurrence in stage II colorectal cancer patients more accurately than clinical factors

BACKGROUND

Approximately 20% of patients with stage II colorectal cancer will experience a relapse. Current clinical-pathologic stratification factors do not allow clear identification of these high-risk patients. ColoPrint (Agendia, Amsterdam, The Netherlands, http://www.agendia.com) is a gene expression classifier that distinguishes patients with low or high risk of disease relapse.

METHODS

ColoPrint was developed using whole-genome expression data and validated in several independent validation cohorts. Stage II patients from these studies were pooled (n = 416), and ColoPrint was compared with clinical risk factors described in the National Comprehensive Cancer Network (NCCN) 2013 Guidelines for Colon Cancer. Median follow-up was 81 months. Most patients (70%) did not receive adjuvant chemotherapy. Risk of relapse (ROR) was defined as survival until first event of recurrence or death from cancer.

RESULTS

In the pooled stage II data set, ColoPrint identified 63% of patients as low risk with a 5-year ROR of 10%, whereas high-risk patients (37%) had a 5-year ROR of 21%, with a hazard ratio (HR) of 2.16 (p = .004). This remained significant in a multivariate model that included number of lymph nodes retrieved and microsatellite instability. In the T3 microsatellite-stable subgroup (n = 301), ColoPrint classified 59% of patients as low risk with a 5-year ROR of 9.9%. High-risk patients (31%) had a 22.4% ROR (HR: 2.41; p = .005). In contrast, the NCCN clinical high-risk factors were unable to distinguish high- and low-risk patients (15% vs. 13% ROR; p = .55).

CONCLUSION

ColoPrint significantly improved prognostic accuracy independent of microsatellite status or clinical variables, facilitating the identification of patients at higher risk who might be considered for additional treatment.

A long non-coding RNA signature to improve prognosis prediction of colorectal cancer

Increasing evidence suggests long non-coding RNAs (lncRNAs) are frequently aberrantly expressed in cancers, however, few related lncRNA signatures have been established for prediction of cancer prognosis. We aimed to develop a lncRNA signature to improve prognosis prediction of colorectal cancer (CRC). Using a lncRNA-mining approach, we performed lncRNA expression profiling in large CRC cohorts from Gene Expression Ominus (GEO), including GSE39582 test series(N=436), internal validation series (N=117); and two independent validation series GSE14333 (N=197) and GSE17536(N=145). We established a set of six lncRNAs that were significantly correlated with the disease free survival (DFS) in the test series. Based on this six-lncRNA signature, the test series patients could be classified into high-risk and low-risk subgroups with significantly different DFS (HR=2.670; P<0.0001). The prognostic value of this six-lncRNA signature was confirmed in the internal validation series and another two independent CRC sets. Gene set enrichment analysis (GSEA) analysis suggested that risk score positively correlated with several cancer metastasis related pathways. Functional experiments demonstrated three dysregulated lncRNAs, AK123657, BX648207 and BX649059 were required for efficient invasion and proliferation suppression in CRC cell lines. Our results might provide an efficient classification tool for clinical prognosis evaluation of CRC.

Bcl-2 stabilization by paxillin confers 5-fluorouracil resistance in colorectal cancer

5-Fluorouracil (5-FU) is chemotherapeutic agent widely used for the treatment of colorectal cancer. Unfortunately, advanced colorectal cancer is often resistance to such chemotherapy and poor outcome. An adaptor protein paxillin (PXN) is phosphorylated at Y31/Y118 (pPXN-Y31/Y118) by Src contributes to cell mobility and Ser (S)272 of PXN in LD4 domain is important to the interaction between PXN and Bcl-2. We thus hypothesized that pPXN-Y31/Y118 may be required for Bcl-2 protein stability via PXN interacting with Bcl-2 to confer 5-FU resistance in colorectal cancer. Mechanistically, pPXN-S272 is phosphorylated through pPXN-Y31/Y118-mediated p21 protein-activated kinase 1 (PAK1) activation and pPXN-S272 is required for PXN to interact with Bcl-2. The interaction between PXN and Bcl-2 is essential for Bcl-2 protein stability through phosphorylation of Bcl-2 at S87 (pBcl-2-S87) by pPXN-Y31/Y118-mediated ERK activation. An increase in Bcl-2 expression by PXN is responsible for resistance to 5-FU. The resistance to 5-FU can be abolished by inhibitor of Src and PAK1 or Bcl-2 antagonist in cell and animal models. Among patients, Bcl-2 expression is positively correlated with expression of PXN and pPXN-S272, respectively. Patients with high PXN/high Bcl-2 or high pPXN-S272/high Bcl-2 tumors are commonly to have an unfavorable response to 5-FU-based chemotherapy, compared with patients who have high PXN, high pPXN-S272 or high Bcl-2 tumors alone. Therefore, we suggest that Src, PAK1 or Bcl-2 inhibitor may potentially overcome the resistance of 5-FU-based chemotherapy and consequently to improve outcomes in patients with PXN/Bcl-2 and pPXN-S272/Bcl-2-positive tumors.

MicroRNA dysregulation as a prognostic biomarker in colorectal cancer

Colorectal cancer (CRC) is one of the most potentially curable cancers, yet it remains the fourth most common overall cause of cancer death worldwide. The identification of robust molecular prognostic biomarkers can refine the conventional tumor–node–metastasis staging system, avoid understaging of tumor, and help pinpoint patients with early-stage CRC who may benefit from aggressive treatments. Recently, epigenetic studies have provided new molecular evidence to better categorize the CRC subtypes and predict clinical outcomes. In this review, we summarize recent findings concerning the prognostic potential of microRNAs (miRNAs) in CRC. We first discuss the prognostic value of three tissue miRNAs (miR-21-5p, miR-29-3p, miR-148-3p) that have been examined in multiple studies. We also summarize the dysregulation of miRNA processing machinery DICER in CRC and its association with risk for mortality. We also reviewe the potential application of miRNA-associated single-nucleotide polymorphisms as prognostic biomarkers for CRC, especially the miRNA-associated polymorphism in the KRAS gene. Last but not least, we discuss the microsatellite instability-related miRNA candidates. Among all these candidates, miR-21-5p is the most promising prognostic marker, yet further prospective validation studies are required before it can go into clinical usage.

Anomalies in network bridges involved in bile Acid metabolism predict outcomes of colorectal cancer patients

Biomarkers prognostic for colorectal cancer (CRC) would be highly desirable in clinical practice. Proteins that regulate bile acid (BA) homeostasis, by linking metabolic sensors and metabolic enzymes, also called bridge proteins, may be reliable prognostic biomarkers for CRC. Based on a devised metric, "bridgeness," we identified bridge proteins involved in the regulation of BA homeostasis and identified their prognostic potentials. The expression patterns of these bridge proteins could distinguish between normal and diseased tissues, suggesting that these proteins are associated with CRC pathogenesis. Using a supervised classification system, we found that these bridge proteins were reproducibly prognostic, with high prognostic ability compared to other known markers.

Gene expression profiling-derived immunohistochemistry signature with high prognostic value in colorectal carcinoma

OBJECTIVE

Gene expression profiling provides an opportunity to develop robust prognostic markers of colorectal carcinoma (CRC). However, the markers have not been applied for clinical decision making. We aimed to develop an immunohistochemistry signature using microarray data for predicting CRC prognosis.

DESIGN

We evaluated 25 CRC gene signatures in independent microarray datasets with prognosis information and constructed a subnetwork using signatures with high concordance and repeatable prognostic values. Tumours were examined immunohistochemically for the expression of network-centric and the top overlapping molecules. Prognostic values were assessed in 682 patients from Shanghai, China (training cohort) and validated in 343 patients from Guangzhou, China (validation cohort). Median follow-up duration was 58 months. All p values are two-sided.

RESULTS

Five signatures were selected to construct a subnetwork. The expression of GRB2, PTPN11, ITGB1 and POSTN in cancer cells, each significantly associated with disease-free survival, were selected to construct an immunohistochemistry signature. Patients were dichotomised into high-risk and low-risk subgroups with an optimal risk score (1.55). Compared with low-risk patients, high-risk patients had shorter disease-specific survival (DSS) in the training (HR=6.62; 95% CI 3.70 to 11.85) and validation cohorts (HR=3.53; 95% CI 2.13 to 5.84) in multivariate Cox analyses. The signature better predicted DSS than did tumour-node-metastasis staging in both cohorts. In those who received postoperative chemotherapy, high-risk score predicted shorter DSS in the training (HR=6.35; 95% CI 3.55 to 11.36) and validation cohorts (HR=5.56; 95% CI 2.25 to 13.71).

CONCLUSIONS

Our immunohistochemistry signature may be clinically practical for personalised prediction of CRC prognosis.

Differential survival trends of stage II colorectal cancer patients relate to promoter methylation status of PCDH10, SPARC, and UCHL1

Surgical excision of colorectal cancer at early clinical stages is highly effective, but 20-30% of patients relapse. Therefore, it is of clinical relevance to identify patients at high risk for recurrence, who would benefit from adjuvant chemotherapy. The objective of this study was to identify prognostic and/or predictive methylation markers in stage II colorectal cancer patients. Therefore, we selected six gene promoters (FZD9, PCDH10 (protocadherin 10), SFRP2, SPARC (secreted protein acidic and rich in cysteine), UCHL1 (ubiquitin carboxyl-terminal hydrolase 1), and WIF1) for methylation analysis in formalin-fixed, paraffin-embedded primary tumor samples of colorectal cancer patients (n=143) who were enrolled in a prospective randomized phase III trial of the Austrian Breast and Colorectal cancer Study Group. Patients were randomized to adjuvant chemotherapy with 5-fluorouracil and leucovorin or surveillance only. Survival analyses revealed that combined evaluation of three promoters (PCDH10, SPARC, and UCHL1) showed differential effects with regard to disease-free survival and overall survival in the two treatment groups (significance level 0.007). In the chemotherapy arm, a statistically insignificant trend for patients without methylation toward longer survival was observed (P=0.069 for disease-free survival and P=0.139 for overall survival). Contrary, patients in the surveillance arm without methylation in their gene promoters had shorter disease-free survival and overall survival (P=0.031 for disease-free survival and P=0.003 for overall survival), indicating a prognostic effect of methylation in this group (test for interaction, P=0.006 for disease-free survival and P=0.018 for overall survival). These results indicate that promoter methylation status of PCDH10, SPARC, and UCHL1 may be used both as prognostic and predictive molecular marker for colorectal cancer patients and, therefore, may facilitate treatment decisions for stage II colorectal cancer.

Concerted down-regulation of immune-system related genes predicts metastasis in colorectal carcinoma

Background

This study aimed at the identification of prognostic gene expression markers in early primary colorectal carcinomas without metastasis at the time point of surgery by analyzing genome-wide gene expression profiles using oligonucleotide microarrays.

Methods

Cryo-conserved tumor specimens from 45 patients with early colorectal cancers were examined, with the majority of them being UICC stage II or earlier and with a follow-up time of 41–115 months. Gene expression profiling was performed using Whole Human Genome 4x44K Oligonucleotide Microarrays. Validation of microarray data was performed on five of the genes in a smaller cohort.

Results

Using a novel algorithm based on the recursive application of support vector machines (SVMs), we selected a signature of 44 probes that discriminated between patients developing later metastasis and patients with a good prognosis. Interestingly, almost half of the genes was related to the patients’ immune response and showed reduced expression in the metastatic cases.

Conclusions

Whereas up to now gene signatures containing genes with various biological functions have been described for prediction of metastasis in CRC, in this study metastasis could be well predicted by a set of gene expression markers consisting exclusively of genes related to the MHC class II complex involved in immune response. Thus, our data emphasize that the proper function of a comprehensive network of immune response genes is of vital importance for the survival of colorectal cancer patients.

Genome-wide analysis of esophageal adenocarcinoma yields specific copy number aberrations that correlate with prognosis

The incidence of esophageal adenocarcinoma (EAC) has been increasing rapidly for the past 3 decades in Western (Caucasian) populations. Curative treatment is based around esophagectomy, which has a major impact on quality of life. For those suitable for treatment with curative intent, 5-year survival is ∼30%. More accurate prognostic tools are therefore needed, and copy number aberrations (CNAs) may offer the ability to act as prospective biomarkers in this regard. We performed a genome-wide examination of CNAs in 54 samples of EAC using single-nucleotide polymorphism (SNP) arrays. Our aims were to describe frequent regions of CNA, to define driver CNAs, and to identify CNAs that correlated with survival. Regions of frequent amplification included oncogenes such as EGFR, MYC, KLF12, and ERBB2, while frequently deleted regions included tumor suppressor genes such as CDKN2A/B, PTPRD, FHIT, and SMAD4. The genomic identification of significant targets in cancer (GISTIC) algorithm identified 24 regions of gain and 28 regions of loss that were likely to contain driver changes. We discovered 61 genes in five regions that, when stratified by CNA type (gain or loss), correlated with a statistically significant difference in survival. Pathway analysis of the genes residing in both the GISTIC and prognostic regions showed they were significantly enriched for cancer-related networks. Finally, we discovered that copy-neutral loss of heterozygosity is a frequent mechanism of CNA in genes currently targetable by chemotherapy, potentially leading to under-reporting of cases suitable for such treatment.

Current stage-specific chemotherapeutic options in colon cancer

Colorectal cancer is one of the most common cancers worldwide. Until recently, chemotherapeutic treatment options were limited to various 5-fluorouracil-leucovorin combinations. However, the last 10 years have seen rapid developments in the treatment of colon cancer. These include the introduction of two additional chemotherapeutic agents, irinotecan and oxaliplatin. Additional agents have been developed, namely the targeted therapies in the form of the monoclonal antibodies bevacizumab and cetuximab. The oral forms of chemotherapy (i.e., capecitabine and uracil-tegafur) have been demonstrated to be as efficacious as traditional intravenously administered 5-fluorouracil. As a result, the number of possible treatment options available to patients has increased dramatically. The aim of this review is to report the currently accepted stage-specific chemotherapeutic treatment options for colon cancer, the evidence for these regimens and future developments.

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

Gene expression studies are informative about changes in colon cancer, increase understanding of the biology of tumorigenesis and aid in developing diagnostic and prognostic markers. In this review, expression techniques used to examine the multistage process of colon cancer are discussed. Many genes have been found to differ in expression between normal and tumorigenic states, as early as the seemingly normal colonic crypts. The clinical usefulness of markers varies with stage, ethnicity and anatomic location of colon cancer. Thus, combinations of markers can be used to develop an approach to molecularly screen and follow the progression of this prevalent cancer.

Network cluster analysis of protein-protein interaction network identified biomarker for early onset colorectal cancer

Colorectal cancer (CRC) is a major cause of morbidity and mortality throughout the world. However, the genetic alterations and molecular mechanism of the early onset CRCs are not fully investigated. The present study aimed to characterize early onset CRC by analyzing its gene expression compared with normal controls and to identify network-based biomarkers of early onset CRC. The gene expression profiles of early onset CRC were downloaded from Gene Expression Omnibus and the differentially expressed genes (DEGs) in CRC patients were identified. Then, a protein-protein interaction (PPI) network was constructed and the clusters in PPI were analyzed by ClusterONE. Furthermore, the gene ontology functional analysis and pathway enrichment analysis were conducted to the modules in PPI network. A systems biology approach integrating microarray data and PPI was further applied to construct a PPI network in CRC. Total 631 DEGs were identified from the early onset CRC compared to healthy controls. These genes were found to be involved in several biological processes, including cell communication, cell proliferation, cell shape and apoptosis. Five functional modules which may play important roles in the initiation of early onset CRC were identified from the PPI network. Functional annotation revealed that these five modules were involved in the pathways of signal transduction, carcinogenesis and metastasis. The hub nodes of these five modules, CDC42, TEX11, QKI, CAV1 and FN1, may serve as the biomarkers of early onset CRC and have the potential to be targets for therapeutic intervention. However, further investigations are still needed to confirm our findings.

Anticipating the clinical use of prognostic gene expression-based tests for colon cancer stage II and III: is Godot finally arriving?

PURPOSE

According to current recommendations for adjuvant treatment, patients with colon cancer stage II are not routinely offered chemotherapy, unless considered to have a high risk of relapse based on specific clinicopathological parameters. Following these criteria, it is challenging to identify the subgroup of patients that will benefit the most from adjuvant treatment. Contrarily, patients with colon cancer stage III are routinely offered chemotherapy, but due to expected adverse effects and frailty, elderly patients are often excluded from standard protocols. Colon cancer is a disease of the elderly and accordingly, there is a large subgroup of patients for which guidelines for adjuvant treatment remain less clear. In these two clinical settings, improved risk stratification has great potential impact on patient care, anticipating that high-risk patients will benefit from chemotherapy. However, microsatellite instability is the only molecular prognostic marker recommended for clinical use.

EXPERIMENTAL DESIGN

In this perspective, we provide an updated view on the status and clinical potential of the many proposed prognostic gene expression-based tests for colon cancer stage II and III.

RESULTS

The main limitation for clinical implementation is lack of prospective validation. For patients with stage II, highly promising tests have been identified and clinical trials are ongoing. For elderly patients with stage III, the value of such tests has received less focus, but promising early results have been shown.

CONCLUSION

Although awaiting results from prospective trials, improved risk assessment for patients with stage II and III is likely to be achieved in the foreseeable future.

Eastern Canadian Colorectal Cancer Consensus Conference: standards of care for the treatment of patients with rectal, pancreatic, and gastrointestinal stromal tumours and pancreatic neuroendocrine tumours

The annual Eastern Canadian Colorectal Cancer Consensus Conference was held in Halifax, Nova Scotia, October 20-22, 2011. Health care professionals involved in the care of patients with colorectal cancer participated in presentation and discussion sessions for the purposes of developing the recommendations presented here. This consensus statement addresses current issues in the management of rectal cancer, including pathology reporting, neoadjuvant systemic and radiation therapy, surgical techniques, and palliative care of rectal cancer patients. Other topics discussed include multidisciplinary cancer conferences, treatment of gastrointestinal stromal tumours and pancreatic neuroendocrine tumours, the use of folfirinox in pancreatic cancer, and treatment of stage ii colon cancer.

Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics

Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper, we present an extension of the BHC algorithm. Our Gaussian BHC (GBHC) algorithm represents data as a mixture of Gaussian distributions. It uses normal-gamma distribution as a conjugate prior on the mean and precision of each of the Gaussian components. We tested GBHC over 11 cancer and 3 synthetic datasets. The results on cancer datasets show that in sample clustering, GBHC on average produces a clustering partition that is more concordant with the ground truth than those obtained from other commonly used algorithms. Furthermore, GBHC frequently infers the number of clusters that is often close to the ground truth. In gene clustering, GBHC also produces a clustering partition that is more biologically plausible than several other state-of-the-art methods. This suggests GBHC as an alternative tool for studying gene expression data.

The implementation of GBHC is available at https://sites.google.com/site/gaussianbhc/

The NOD2insC polymorphism is associated with worse outcome following ileal pouch-anal anastomosis for ulcerative colitis

BACKGROUND

Inflammatory complications after ileal pouch-anal anastomosis (IPAA) for ulcerative colitis (UC) are common.

OBJECTIVE

To investigate whether genetic factors are associated with adverse pouch outcomes such as chronic pouchitis (CP) and a Crohn's disease-like (CDL) phenotype.

DESIGN

866 patients were recruited from three centres in North America: Mount Sinai Hospital (Toronto, Ontario, Canada), the Cleveland Clinic (Cleveland, Ohio, USA) and Penn State Milton S Hershey Medical Center (Hershey, Pennsylvania, USA). DNA and clinical and demographic information were collected. Subjects were classified into post-surgical outcome groups: no chronic pouchitis (NCP), CP and CDL phenotype.

RESULTS

Clinical and genetic data were available on 714 individuals. 487 (68.2%) were classified as NCP, 118 (16.5%) CP and 109 (15.3%) CDL. The presence of arthritis or arthropathy (p=0.02), primary sclerosing cholangitis (p=0.009) and duration of time from ileostomy closure to recruitment (p=0.001) were significantly associated with outcome. The NOD2insC (rs2066847) risk variant was the single nucleotide polymorphism (SNP) most significantly associated with pouch outcome (p=7.4×10(-5)). Specifically, it was associated with both CP and CDL in comparison with NCP (OR=3.2 and 4.3, respectively). Additionally, SNPs in NOX3 (rs6557421, rs12661812), DAGLB (rs836518) and NCF4 (rs8137602) were shown to be associated with pouch outcome with slightly weaker effects. A multivariable risk model combining previously identified clinical (smoking status, family history of inflammatory bowel disease), serological (anti-Saccharomyces cerevisiae antibody IgG, perinuclear antineutrophil cytoplasmic antibody and anti-CBir1) and genetic markers was constructed and resulted in an OR of 2.72 (p=8.89×10(-7)) for NCP versus CP/CDL and 3.22 (p=4.11×10(-8)) for NCP versus CDL, respectively.

CONCLUSION

Genetic polymorphisms, in particular, the NOD2insC risk allele, are associated with chronic inflammatory pouch outcomes among patients with UC and IPAA.

Cancer markers: integratively annotated classification

Translational cancer genomics research aims to ensure that experimental knowledge is subject to computational analysis, and integrated with a variety of records from omics and clinical sources. The data retrieval from such sources is not trivial, due to their redundancy and heterogeneity, and the presence of false evidence. In silico marker identification, therefore, remains a complex task that is mainly motivated by the impact that target identification from the elucidation of gene co-expression dynamics and regulation mechanisms, combined with the discovery of genotype-phenotype associations, may have for clinical validation. Based on the reuse of publicly available gene expression data, our aim is to propose cancer marker classification by integrating the prediction power of multiple annotation sources. In particular, with reference to the functional annotation for colorectal markers, we indicate a classification of markers into diagnostic and prognostic classes combined with susceptibility and risk factors.

Independent validation of a prognostic genomic signature (ColoPrint) for patients with stage II colon cancer

OBJECTIVES

The aim of this study was to independently validate a genomic signature developed both to assess recurrence risk in stage II patients and to assist in treatment decisions.

BACKGROUND

Adjuvant therapy is recommended for high-risk patients with stage II colon cancer, but better tools to assess the patients' prognosis accurately are still required.

METHODS

Previously, an 18-gene signature had been developed and validated on an independent cohort, using full genome microarrays. In this study, the gene signature was translated and validated as a robust diagnostic test (ColoPrint), using customized 8-pack arrays. In addition, clinical validation of the diagnostic ColoPrint assay was performed on 135 patients who underwent curative resection (R0) for colon cancer stage II in Munich. Fresh-frozen tissue, microsatellite instability status, clinical parameters, and follow-up data for all patients were available. The diagnostic ColoPrint readout was determined blindly from the clinical data.

RESULTS

ColoPrint identified most stage II patients (73.3%) as at low risk. The 5-year distant-metastasis free survival was 94.9% for low-risk patients and 80.6% for high-risk patients. In multivariable analysis, ColoPrint was the only significant parameter to predict the development of distant metastasis with a hazard ratio of 4.28 (95% confidence interval, 1.36-13.50; P = 0.013). Clinical risk parameters from the American Society of Clinical Oncology (ASCO) recommendation did not add power to the ColoPrint classification. Technical validation of ColoPrint confirmed stability and reproducibility of the diagnostic platform.

CONCLUSIONS

ColoPrint is able to predict the development of distant metastasis of patients with stage II colon cancer and facilitates the identification of patients who may be safely managed without chemotherapy.

Role of MUC20 overexpression as a predictor of recurrence and poor outcome in colorectal cancer

Background

Colorectal cancer (CRC) remains one of the most common cancers worldwide. We observed that MUC20 was significantly up-regulated in CRC patients with poor prognosis based on the microarray analysis. However, little is known about the role of MUC20 in CRC.

Methods

Microarray experiments were performed on the Affymetrix U133 plus 2.0 GeneChip Array. The protein and mRNA levels of MUC20 were examined by immunohistochemistry (IHC) and Real-Time quantitative PCR (RT-qPCR) in CRC tissues and adjacent noncancerous tissues (ANCT). ShRNA and overexpression plasmids were used to regulate MUC20 expression in CRC cell lines in vitro; wound healing, Transwell migration assays, and Western blotting were used to detect migration and invasion changes.

Results

MUC20 was one of the up-regulated genes in CRC patients with poor prognosis by microarray. Using IHC and RT-qPCR, we showed that MUC20 expression was significantly higher in CRC tissues than in ANCT (P < 0.05). We further showed that MUC20 overexpression was correlated with recurrence and poor outcome (P < 0.05). The Kaplan-Meier survival curves indicated that disease-free survival (DFS) and overall survival (OS) were significantly worse in CRC patients with MUC20 overexpression. The Cox multivariate analysis revealed that MUC20 overexpression and TNM stage were independent prognostic factors. Elevated expression of MUC20 in cells promoted migration and invasion, whereas ShRNA-mediated knockdown inhibited these processes. In addition, Western blotting demonstrated that MUC20-induced invasion was associated with MMP-2, MMP-3, and E-cadherin.

Conclusions

Cumulatively, MUC20 may serve as an important predictor of recurrence and poor outcome for CRC patients. MUC20 overexpression could enhance migration and invasion abilities of CRC cells. Translation of its roles into clinical practice will need further investigation and additional test validation.

Clinical applications of gene expression in colorectal cancer

BACKGROUND

Despite developments in diagnosis and treatment, 20% of colorectal cancer (CRC) patients present with metastatic disease and 30% of cases recur after curative surgery. Furthermore, the molecular factors involved in prognosis and response to therapy in CRC is poorly understood. The aims of this study were to quantitatively examine the expression of target genes in colorectal cancer and to correlate their expression levels with clinico-pathological variables.

METHODS

A detailed analysis of published CRC microarray data was performed to identify the most prominent genes. The selected genes were validated in fifty-two pairs of fresh colorectal tumour and associated normal tissue specimens by RQ-PCR using TaqMan(®) assays. Statistical analysis and correlation with clinicopathological data was performed using SPSS software.

RESULTS

Expression levels of CXCL12 (P=0.000), CDH17 (P=0.026), MUC2 (P=0.000), L-FABP (P=0.000) and PDCD4 (P=0.000) were down regulated and IL8 (P=0.000) was upregulated in tumours compared to normal colorectal tissues. No significant differences were noted in expression of CEACAM5, CXCR4, CXCR7, TGFB1, TGFBR1 and TGFBR2. Furthermore, we found significant associations of gene expression levels and clinicopathological variables such as tumour size, grade, invasion and lymph node status.

CONCLUSIONS

We identified a comprehensive list of genes with highly differential expression patterns in colorectal cancer that could serve as molecular markers to complement existing histopathological factors in diagnosis, follow up and therapeutic strategies for individualised care of patients.

Association between a multi-locus genetic risk score and inflammatory bowel disease

To date, the utility of single genetic markers to improve disease risk assessment still explains only a small proportion of genetic variance for many complex diseases. This missing heritability may be explained by additional variants with weak effects. To discover and incorporate these additional genetic factors, statistical and computational methods must be evaluated and developed. We develop a multi-locus genetic risk score (GRS) based approach to analyze genes in NADPH oxidase complex which may result in susceptibility to development of inflammatory bowel disease (IBD). We find the complex is highly associated with IBD (P = 7.86 × 10⁻¹⁴) using the GRS-based association method. Similar results are also shown in permutation analysis (P = 6.65 × 10⁻¹¹). Likelihood ratio test shows that the single nucleotide polymorphisms (SNPs) in the complex without nominal signals have significant contribution to the overall genetic effect within the complex (P = 0.015). Our results show that the multi-locus GRS association model can improve the genetic risk assessment on IBD by taking into account both confirmed and as yet unconfirmed disease susceptibility variants.