Gene expression profiles in stages II and III colon cancers: application of a 128-gene signature

Hidden patterns of gene expression provide prognostic insight for colorectal cancer

Cancer tissue samples contain cancer cells and non-cancer cells with each biopsied site containing distinct proportions of these populations. Consequently, assigning useful tumor subtypes based on gene expression measurements from clinical samples is challenging. We applied a blind source separation approach to extract cancer cell-intrinsic gene expression patterns within clinical tumor samples of colorectal cancer. After a blind source separation, we found that a cancer cell-intrinsic gene expression program unique to each patient exists in the "residual" expression profile remaining after separation of the gene expression data. We performed a consensus clustering analysis of the extracted gene expression profiles to identify novel and robust cancer cell-intrinsic subtypes. We validated the identified subtypes using an independent clinical gene expression dataset. The cancer cell-intrinsic subtypes are independent of biopsy site and provided prognostic information in addition to currently available clinical and molecular variables. After validating this approach in colorectal cancer, we further identified novel tumor subtypes with unique clinical information across multiple types of cancer. These cancer cell-intrinsic molecular subtypes provide novel prognostic value for clinical assessment of cancer.

Identification of Prognostic Gene Signatures by Developing a scRNA-Seq-Based Integration Approach to Predict Recurrence and Chemotherapy Benefit in Stage II–III Colorectal Cancer

Prospective identification of robust biomarkers related to prognosis and adjuvant chemotherapy has become a necessary and critical step to predict the benefits of adjuvant therapy for patients with stage II–III colorectal cancer (CRC) before clinical treatment. We proposed a single-cell-based prognostic biomarker recognition approach to identify and construct CRC up- and down-regulated prognostic signatures (CUPsig and CDPsig) by integrating scRNA-seq and bulk datasets. We found that most genes in CUPsig and CDPsig were known disease genes, and they had good prognostic abilities in CRC validation datasets. Multivariate analysis confirmed that they were two independent prognostic factors of disease-free survival (DFS). Significantly, CUPsig and CDPsig could effectively predict adjuvant chemotherapy benefits in drug-treated validation datasets. Additionally, they also performed well in patients with CMS4 subtype. Subsequent analysis of drug sensitivity showed that expressions of these two signatures were significantly associated with the sensitivities of CRC cell lines to multiple drugs. In summary, we proposed a novel prognostic biomarker identification approach, which could be used to identify novel prognostic markers for stage II–III CRC patients who will undergo adjuvant chemotherapy and facilitate their further personalized treatments.

KCNJ14 knockdown significantly inhibited the proliferation and migration of colorectal cells

Background

This study attempted to verify the potential of KCNJ14 as a biomarker in colorectal cancer (CRC).

Methods

Data on transcriptomics and DNA methylation and the clinical information of CRC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Biological information analysis methods were conducted to determine the role of KCNJ14 in the prognosis, diagnosis, immune cell infiltration, and regulation mechanism of CRC patients. The effect of KCNJ14 on the proliferation and migration of HCT116 and SW480 CRC cell lines was verified by in vitro experiments (MTT, colony-forming, wound healing, and transwell assays). Western blotting was performed to detect the effect of KCNJ14 on the levels of mTOR signalling pathway-related proteins.

Results

KCNJ14 expression was remarkably increased in CRC tissues and cell lines, which reduced the overall survival time of patients. KCNJ14 mRNA was negatively regulated by its methylation site cg17660703, which can also endanger the prognosis of patients with CRC. Functional enrichment analysis suggested that KCNJ14 is involved in the mTOR, NOD-like receptor, and VEGF signalling pathways. KCNJ14 expression was positively correlated with the number of CD4 + T cells and negatively correlated with that of CD8 + T cells in the immune microenvironment. KCNJ14 knockdown significantly reduced not only the proliferation and migration of CRC cell lines but also the levels of mTOR signalling pathway-related proteins.

Conclusions

This study not only increases the molecular understanding of KCNJ14 but also provides a potentially valuable biological target for the treatment of colorectal cancer.

Long Noncoding RNA MALAT1 and Colorectal Cancer: A Propensity Score Analysis of Two Prospective Cohorts

Background

Previous researches have shown that the aberrant expression of Metastasis associated in lung adenocarcinoma transcript 1 (MALAT1) in tumour tissues may serve as a biomarker for colorectal cancer (CRC) prognosis. However, these previous studies have small sample sizes and lacked validation from independent external populations. We therefore aimed to clarify the prognostic value of MALAT1 expression status in CRC patients using a large cohort and validate the findings with another large external cohort.

Methods

The prognostic association between MALAT1 expression status and CRC outcomes was evaluated initially in a prospective cohort in China (n=164) and then validated in an external TCGA population (n=596). In the initial cohort, MALAT1 expression levels were quantified by quantitative reverse transcriptase polymerase chain reaction. Propensity score (PS) adjustment method was used to control potential confounding biases. The prognostic significance was reported as PS-adjusted hazard ratio (HR) and corresponding 95% confidence interval (CI).

Results

There was no statistically significant association between MALAT1 expression status and CRC patient overall survival (OS) or disease free survival (DFS) in both initial cohort and external validation cohort populations. When combining these populations together, the results did not change materially. The summarized HR_PS-adjusted were 1.010 (95% CI, 0.752-1.355, P=0.950) and 1.170 (95% CI, 0.910-1.502, P=0.220) for OS and DFS, respectively.

Conclusions

MALAT1 expression status is not associated with prognostic outcomes of CRC patients. However, additional larger population studies are needed to further validate these findings.

Assessment of the targeted effect of Sijunzi decoction on the colorectal cancer microenvironment via the ESTIMATE algorithm

Objective

Sijunzi decoction (SJZD) was used to treat patients with colorectal cancer (CRC) as an adjuvant method. The aim of the study was to investigate the therapeutic targets and pathways of SJZD towards the tumor microenvironment of CRC via network pharmacology and the ESTIMATE algorithm.

Methods

The ESTIMATE algorithm was used to calculate immune and stromal scores to predict the level of infiltrating immune and stromal cells. The active targets of SJZD were searched in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and UniProt database. The core targets were obtained by matching the differentially expressed genes in CRC tissues and the targets of SJZD. Then, GO, KEGG and validation in TCGA were carried out.

Results

According to the ESTIMATE algorithm and survival analysis, the median survival time of the low stromal score group was significantly higher than that of the high stromal score group (P = 0.018), while the patients showed no significant difference of OS between different immune groups (P = 0.19). A total of 929 genes were upregulated and 115 genes were downregulated between the stromal score groups (|logFC| > 2, adjusted P < 0.05); 357 genes were upregulated and 472 genes were downregulated between the immune score groups. The component-target network included 139 active components and 52 related targets. The core targets were HSPB1, SPP1, IGFBP3, and TGFB1, which were significantly associated with poor prognosis in TCGA validation. GO terms included the response to hypoxia, the extracellular space, protein binding and the TNF signaling pathway. Immunoreaction was the main enriched pathway identified by KEGG analysis.

Conclusion

The core genes (HSPB1, SPP1, IGFBP3 and TGFB1) affected CRC development and prognosis by regulating hypoxia, protein binding and epithelial-mesenchymal transition in the extracellular matrix.

A SMAD4-modulated gene profile predicts disease-free survival in stage II and III colorectal cancer

Background

Colorectal cancer is the second‐leading cause of cancer‐related mortality in the United States and a leading cause of cancer‐related mortality worldwide. Loss of SMAD4, a critical tumor suppressor and the central node of the transforming growth factor‐beta superfamily, is associated with worse outcomes for colorectal cancer patients; however, it is unknown whether an RNA‐based profile associated with SMAD4 expression could be used to better identify high‐risk colorectal cancer patients.

Aim

Identify a gene expression‐based SMAD4‐modulated profile and test its association with patient outcome.

Methods and results

Using a discovery dataset of 250 colorectal cancer patients, we analyzed expression of BMP/Wnt target genes for association with SMAD4 expression. Promoters of the BMP/Wnt genes were interrogated for SMAD‐binding elements. Fifteen genes were implicated and three tested for modulation by SMAD4 in patient‐derived colorectal cancer tumoroids. Expression of the 15 genes was used for unsupervised hierarchical clustering of a training dataset and two resulting clusters modeled in a centroid model. This model was applied to an independent validation dataset of stage II and III patients. Disease‐free survival was analyzed by the Kaplan‐Meier method. In vitro analysis of three genes identified in the SMAD4‐modulated profile (JAG1, TCF7, and MYC) revealed modulation by SMAD4 consistent with the trend observed in the profile. In the training dataset (n = 553), the profile was not associated with outcome. However, among stage II and III patients (n = 461), distinct clusters were identified by unsupervised hierarchical clustering that were associated with disease‐free survival (p = .02, log‐rank test). The main model was applied to a validation dataset of stage II/III CRC patients (n = 257) which confirmed the association of clustering with disease‐free survival (p = .013, log‐rank test).

Conclusions

A SMAD4‐modulated gene expression profile identified high‐risk stage II and III colorectal cancer patients, can predict disease‐free survival, and has prognostic potential for stage II and III colorectal cancer patients.

Tumor-infiltrating plasmacytoid dendritic cells are associated with survival in human colon cancer

Background

Plasmacytoid dendritic cells (pDCs) play a key role in the induction and maintenance of antitumor immunity. Conversely, they can act as tolerogenic DCs by inhibiting tumor-directed immune responses. Therefore, pDCs may profoundly influence tumor progression. To gain novel insights into the role of pDCs in colon cancer, we investigated the frequency and clinical relevance of pDCs in primary tumor tissues from patients with colon cancer with different clinicopathological characteristics.

Methods

Immunohistochemical stainings were performed to explore the frequency of tumor-infiltrating BDCA-2⁺ pDCs in patients with colon cancer. Statistical analyses were conducted to determine an association between the pDC density and clinicopathological characteristics of the patients. Furthermore, we used multiplex immunofluorescence stainings to evaluate the localization and phenotype of pDCs in stroma and tertiary lymphoid structures (TLS) of colon cancer tissues.

Results

An increased density of infiltrating pDCs was associated with lower Union for International Cancer Control (UICC) stages. Furthermore, a higher pDC frequency was significantly correlated with increased progression-free and overall survival of patients with colon cancer. Moreover, a lower number of coloncancer-infiltrating pDCs was significantly and independently linked to worse prognosis. In addition, we found that a proportion of pDCs shows a nuclear expression of the transcription factor interferon regulatory factor 7 (IRF7), which is characteristic for an activated phenotype. In various tumor stroma regions, IRF7⁺ pDCs were located in the neighborhood of granzyme B-expressing CD8⁺ T cells. Moreover, pDCs were identified as a novel component of the T cell zone of colon cancer-associated TLS, which are major regulators of adaptive antitumor immunity. A proportion of TLS-associated pDCs displayed a nuclear IRF7 expression and was preferentially located close to CD4⁺ T cells.

Conclusions

These results indicate that higher densities of tumor-infiltrating pDCs are associated with prolonged survival of patients with colon cancer. Moreover, colon cancer-infiltrating pDCs may represent a novel prognostic factor. The colocalization of activated pDCs and T cells in tumor stroma and within TLS may contribute to the correlation between higher pDC densities and better prognosis. In addition, our findings may have implications for the design of novel immunotherapeutic strategies that are based on targeting colon cancer-infiltrating pDCs.

Development of a Gene-Based Prediction Model for Recurrence of Colorectal Cancer Using an Ensemble Learning Algorithm

It is difficult to determine which patients with stage I and II colorectal cancer are at high risk of recurrence, qualifying them to undergo adjuvant chemotherapy. In this study, we aimed to determine a gene signature using gene expression data that could successfully identify high risk of recurrence among stage I and II colorectal cancer patients. First, a synthetic minority oversampling technique was used to address the problem of imbalanced data due to rare recurrence events. We then applied a sequential workflow of three methods (significance analysis of microarrays, logistic regression, and recursive feature elimination) to identify genes differentially expressed between patients with and without recurrence. To stabilize the prediction algorithm, we repeated the above processes on 10 subsets by bagging the training data set and then used support vector machine methods to construct the prediction models. The final predictions were determined by majority voting. The 10 models, using 51 differentially expressed genes, successfully predicted a high risk of recurrence within 3 years in the training data set, with a sensitivity of 91.18%. For the validation data sets, the sensitivity of the prediction with samples from two other countries was 80.00% and 91.67%. These prediction models can potentially function as a tool to decide if adjuvant chemotherapy should be administered after surgery for patients with stage I and II colorectal cancer.

Overexpression of sortilin is associated with 5-FU resistance and poor prognosis in colorectal cancer

Colorectal cancer (CRC) is the third most common cancer worldwide. Even if 5-fluorouracil (5-FU) is used as the first-line chemotherapeutic drug, responsiveness is only 20-30%. Acquired resistance to 5-FU contributes to both poor patient prognosis and relapse, emphasizing the need to identify biomarkers. Sortilin, a vacuolar protein sorting 10 protein (Vps10p), implicated in protein trafficking, is over expressed in CRC cell lines cultured 72 hours in presence of 5-FU. This overexpression was also observed in 5-FU-resistant cells derived from these cell lines as well as in CRC primary cultures (or patients derived cell lines). A significantly higher expression of sortilin was observed in vivo, in 5-FU-treated tumours engrafted in Nude mice, as compared with non-treated tumour. A study of transcriptional regulation allowed identifying a decrease in ATF3 expression, as an explanation of sortilin overexpression following 5-FU treatment. In silico analysis revealed SORT1 expression correlation with poor prognosis. Moreover, sortilin expression was found to be positively correlated with CRC tumour grades. Collectively, our findings identify sortilin as a potential biomarker of 5-FU resistance associated with poor clinical outcomes and aggressiveness in CRC. As a new prognostic factor, sortilin expression could be used to fight against CRC.

KRT17 as a prognostic biomarker for stage II colorectal cancer

Adjuvant chemotherapy is considered for patients with stage II colorectal cancer (CRC) characterized by poor prognostic clinicopathological features; however, current stratification algorithms remain inadequate for identifying high-risk patients. To develop prognostic assays, we conducted a step-wise screening and validation strategy using nine cohorts of stage II patients based on multiple platforms, including microarray, RNA-sequencing (RNA-seq) and immunohistochemistry (IHC) on formalin-fixed paraffin-embedded (FFPE) tissues. Four microarray datasets (total n = 458) were used as the discovery set to screen for single genes associated with postoperative recurrence. Prognostic values of candidate genes were evaluated in three independent microarray/RNA-seq validation cohorts (n = 89, n = 93 and n = 183, respectively), and then IHC for KRT17 was conducted in two independent FFPE series (n = 110 and n = 44, respectively). We found that high levels of KRT17 transcript expression were significantly associated with poor relapse-free survival (RFS) not only in the discovery set, but also in three validation cohorts, and its prognostic impact was independent of conventional factors by multivariate analyses. Positive staining of KRT17 protein was significantly associated with poor RFS in two independent FFPE cohorts. KRT17 protein expression had independent prognostic impact on RFS in a multivariate model adjusted for conventional variables, including high-risk clinicopathological features. In conclusion, using nine independent cohorts consisting of 997 stage II patients, we identified and validated the expression of KRT17 transcript and KRT17 protein as a robust prognostic biomarker that can discriminate postoperative stage II patients who are at high probability of disease recurrence, providing additional prognostic stratification beyond the currently available high-risk factors.

Microarray‑based analysis of COL11A1 and TWIST1 as important differentially‑expressed pathogenic genes between left and right‑sided colon cancer

Colonic cancer has become a main reason of mortality associated with cancer; however, left and right-sided colonic cancer have diverse outcomes in terms of epidemiological, histological, clinical parameters and prognosis. We aimed to examine the discrepancies between these two types of colon cancers to identify potential therapeutic targets. In the present study, three gene expression profiles (GSE44076, GSE31595, GSE26906) from Gene Expression Omnibus (GEO) database were downloaded and further analyzed. A PPI (protein-protein interaction) network of the differentially-expressed genes (DEGs) of GSE44076 between tumor and normal was established with the Search Tool for the Retrieval of Interacting Genes database. Then, the DEGs of these two colon cancers (left, right) samples were identified. Subsequently, the intersection of DEGs of left and right-sided colon cancer samples obtained from three databases, and DEGs of tumor and normal samples were analyzed. Collagen type XI α1 chain (COL11A1), Twist family bHLH transcription factor 1 (TWIST1), insulin-like 5 and chromogranin A were upregulated proteins, while 3β-hydroxysteroid dehydrogenase was downregulated protein in right colon cancer than in left-sided tumor samples. Through further experimental verification, we revealed that COL11A1 and TWIST1 were significantly upregulated at the mRNA and protein levels within right-sided colon cancer compared with in left-sided colon cancer samples (P<0.05), consistent with bioinformatical analysis. Furthermore, a positive correlation between COL11A1 and TWIST1 protein expression was observed (P<0.0276). Collectively, our data showed that COL11A1 and TWIST1 may be potential prognostic indicators and molecular targets for the treatment of right-sided colon cancer.

Identification of β-catenin target genes in colorectal cancer by interrogating gene fitness screening data

β-catenin regulates its target genes which are associated with proliferation, differentiation, migration and angiogenesis, and the dysregulation of Wnt/β-catenin signaling facilitates hallmarks of colorectal cancer (CRC). Identification of β-catenin targets and their potential roles in tumorigenesis has gained increased interest. However, the number of identified targets remains limited. The present study implemented a novel strategy, interrogating gene fitness profiles derived from large-scale RNA interference and CRISPR-CRISPR associated protein 9 screening data to identify β-catenin target genes in CRC cell lines. Using these data sets, pair wise gene fitness similarities were determined which highlighted a total of 13 genes whose functions were highly correlated with β-catenin. It was further demonstrated that the expression of these genes were altered in CRC, illustrating their potential roles in the progression of CRC. The present study further demonstrated that these targets could be used to predict disease-free survival in CRC. In conclusion, the findings provided novel approaches for the identification of β-catenin targets, which may become prognostic biomarkers or drug targets for the management of CRC.

A predictive computational model reveals that GIV/girdin serves as a tunable valve for EGFR-stimulated cyclic AMP signals

Cellular levels of the versatile second messenger cyclic (c)AMP are regulated by the antagonistic actions of the canonical G protein → adenylyl cyclase pathway that is initiated by G-protein–coupled receptors (GPCRs) and attenuated by phosphodiesterases (PDEs). Dysregulated cAMP signaling drives many diseases; for example, its low levels facilitate numerous sinister properties of cancer cells. Recently, an alternative paradigm for cAMP signaling has emerged in which growth factor–receptor tyrosine kinases (RTKs; e.g., EGFR) access and modulate G proteins via a cytosolic guanine-nucleotide exchange modulator (GEM), GIV/girdin; dysregulation of this pathway is frequently encountered in cancers. In this study, we present a network-based compartmental model for the paradigm of GEM-facilitated cross-talk between RTKs and G proteins and how that impacts cellular cAMP. Our model predicts that cross-talk between GIV, Gα_s, and Gα_i proteins dampens ligand-stimulated cAMP dynamics. This prediction was experimentally verified by measuring cAMP levels in cells under different conditions. We further predict that the direct proportionality of cAMP concentration as a function of receptor number and the inverse proportionality of cAMP concentration as a function of PDE concentration are both altered by GIV levels. Taking these results together, our model reveals that GIV acts as a tunable control valve that regulates cAMP flux after growth factor stimulation. For a given stimulus, when GIV levels are high, cAMP levels are low, and vice versa. In doing so, GIV modulates cAMP via mechanisms distinct from the two most often targeted classes of cAMP modulators, GPCRs and PDEs.

Convergence of Wnt, growth factor, and heterotrimeric G protein signals on the guanine nucleotide exchange factor Daple

Cellular proliferation, differentiation, and morphogenesis are shaped by multiple signaling cascades, and their dysregulation plays an integral role in cancer progression. Three cascades that contribute to oncogenic potential are those mediated by Wnt proteins and the receptor Frizzled (FZD), growth factor receptor tyrosine kinases (RTKs), and heterotrimeric G proteins and associated GPCRs. Daple is a guanine nucleotide exchange factor (GEF) for the G protein G_αi Daple also binds to FZD and the Wnt/FZD mediator Dishevelled (Dvl), and it enhances β-catenin-independent Wnt signaling in response to Wnt5a-FZD7 signaling. We identified Daple as a substrate of multiple RTKs and non-RTKs and, hence, as a point of convergence for the three cascades. We found that phosphorylation near the Dvl-binding motif in Daple by both RTKs and non-RTKs caused Daple/Dvl complex dissociation and augmented the ability of Daple to bind to and activate G_αi, which potentiated β-catenin-independent Wnt signals and stimulated epithelial-mesenchymal transition (EMT) similarly to Wnt5a/FZD7 signaling. Although Daple acts as a tumor suppressor in the healthy colon, the concurrent increased abundance of Daple and epidermal growth factor receptor (EGFR) in colorectal tumors was associated with poor patient prognosis. Thus, the Daple-dependent activation of G_αi and the Daple-dependent enhancement of β-catenin-independent Wnt signals are not only stimulated by Wnt5a/FZD7 to suppress tumorigenesis but also hijacked by growth factor-activated RTKs to enhance tumor progression. These findings identify a cross-talk paradigm among growth factor RTKs, heterotrimeric G proteins, and the Wnt/FZD pathway in cancer.

Building personalized treatment plans for early-stage colorectal cancer patients

We developed a series of models to predict the likelihood of recurrence and the response to chemotherapy for the personalized treatment of stage I and II colorectal cancer patients. A recurrence prediction model was developed from 235 stage I/II patients. The model successfully distinguished between high-risk and low-risk groups, with a hazard ratio of recurrence of 4.66 (p < 0.0001). More importantly, the model was accurate for both stage I (hazard ratio = 5.87, p = 0.0006) and stage II (hazard ratio = 4.30, p < 0.0001) disease. This model performed much better than the Oncotype and ColoPrint commercial services in identifying patients at high risk for stage II recurrence. And unlike the commercial services, the robust model included recurrence prediction for stage I patients. As stage I/II CRC patients usually do not receive chemotherapy, we generated chemotherapy efficacy prediction models with data from 358 stage III patients. The predictions were highly accurate: the hazard ratio of recurrence for responders vs. non-responders was 4.13 for those treated with FOLFOX (p < 0.0001), and 3.16 (p = 0.0012) for those treated with fluorouracil. We have thus created a prognostic model that accurately identifies patients at high risk for recurrence, and the first accurate chemotherapy efficacy prediction model for individual patients. In the future, complete personalized treatment plans for stage I/II patients may be developed if the drug prediction models generated from stage III patients are verified to be effective for stage I and II patients in prospective studies.

Standardising RNA profiling based biomarker application in cancer-The need for robust control of technical variables

Histopathology-based staging of colorectal cancer (CRC) has utility in assessing the prognosis of patient subtypes, but as yet cannot accurately predict individual patient's treatment response. Transcriptomics approaches, using array based or next generation sequencing (NGS) platforms, of formalin fixed paraffin embedded tissue can be harnessed to develop multi-gene biomarkers for predicting both prognosis and treatment response, leading to stratification of treatment. While transcriptomics can shape future biomarker development, currently <1% of published biomarkers become clinically validated tests, often due to poor study design or lack of independent validation. In this review of a large number of CRC transcriptional studies, we identify recurrent sources of technical variability that encompass collection, preservation and storage of malignant tissue, nucleic acid extraction, methods to quantitate RNA transcripts and data analysis pipelines. We propose a series of defined steps for removal of these confounding issues, to ultimately aid in the development of more robust clinical biomarkers.

A 19-Gene expression signature as a predictor of survival in colorectal cancer

Background

Histopathological assessment has a low potential to predict clinical outcome in patients with the same stage of colorectal cancer. More specific and sensitive biomarkers to determine patients’ survival are needed. We aimed to determine gene expression signatures as reliable prognostic marker that could predict survival of colorectal cancer patients with Dukes’ B and C.

Methods

We examined microarray gene expression profiles of 78 archived tissues of patients with Dukes’ B and C using the Illumina DASL assay. The gene expression data were analyzed using the GeneSpring software and R programming.

Results

The outliers were detected and replaced with randomly chosen genes from the 90 % confidence interval of the robust mean for each group. We performed three statistical methods (SAM, LIMMA and t-test) to identify significant genes. There were 19 significant common genes identified from microarray data that have been permutated 100 times namely NOTCH2, ITPRIP, FRMD6, GFRA4, OSBPL9, CPXCR1, SORCS2, PDC, C12orf66, SLC38A9, OR10H5, TRIP13, MRPL52, DUSP21, BRCA1, ELTD1, SPG7, LASS6 and DUOX2. This 19-gene signature was able to significantly predict the survival of patients with colorectal cancer compared to the conventional Dukes’ classification in both training and test sets (p < 0.05). The performance of this signature was further validated as a significant independent predictor of survival using patient cohorts from Australia (n = 185), USA (n = 114), Denmark (n = 37) and Norway (n = 95) (p < 0.05). Validation using quantitative PCR confirmed similar expression pattern for the six selected genes.

Conclusion

Profiling of these 19 genes may provide a more accurate method to predict survival of patients with colorectal cancer and assist in identifying patients who require more intensive treatment.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-016-0218-1) contains supplementary material, which is available to authorized users.

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.).

In silico and Ex vivo approaches identify a role for toll-like receptor 4 in colorectal cancer

BACKGROUND

Inflammation increases the risk of colorectal cancer (CRC). We and others have described a role for TLR4, the receptor for LPS, in colon cancer. To explore the relationships between TLR4 expression and CRC, we combined the strength of transcriptome array data and immunohistochemical (IHC) staining.

METHODS

TLR4 signal intensity was scored in the stromal and epithelial compartments. Detection of differential expression between conditions of interest was performed using linear models, Cox proportional hazards models, and empirical Bayes methods.

RESULTS

A strong association between TLR4 expression and survival was noted, though a dichotomous relationship between survival and specific TLR4 transcripts was observed. Increasing TLR4 expression was seen with advancing tumor stage and was also over-expressed in some adenomas. IHC staining confirmed the positive relationship between TLR4 staining score in the CRC tumor stroma and epithelium with tumor stage, with up to 47% of colon cancer stroma positive for TLR4 staining. Increased TLR4 expression by IHC was also marginally associated with decreased survival. We now also describe that pericryptal myofibroblasts are responsible for a portion of the TLR4 stromal staining.

CONCLUSIONS

Increased TLR4 expression occurs early in colonic neoplasia. TLR4 is associated with the important cancer-related outcomes of survival and stage.

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.

General aspects of colorectal cancer

Colorectal cancer (CRC) is one of the main causes of death. Cancer is initiated by several DNA damages, affecting proto-oncogenes, tumour suppressor genes, and DNA repairing genes. The molecular origins of CRC are chromosome instability (CIN), microsatellite instability (MSI), and CpG island methylator phenotype (CIMP). A brief description of types of CRC cancer is presented, including sporadic CRC, hereditary nonpolyposis colorectal cancer (HNPCC) or Lynch syndromes, familiar adenomatous polyposis (FAP), MYH-associated polyposis (MAP), Peutz-Jeghers syndrome (PJS), and juvenile polyposis syndrome (JPS). Some signalling systems for CRC are also described, including Wnt-β-catenin pathway, tyrosine kinase receptors pathway, TGF-β pathway, and Hedgehog pathway. Finally, this paper describes also some CRC treatments.