Gene expression profiles in the diagnosis and prognosis of cancer

DNA-microarray technology can be used to assess the expression of several thousands of genes at the same time. The identification of the gene expression profiles may help to better characterize human cancer. These studies may reveal subclasses of tumor types with similar histopathologic profile but different clinical courses.Furthermore,such studies could help to define therapeutic sensitivity and to estimate prognosis of various cancers. Identification of gene expression profiles of cancer can identify new therapeutic targets or cancer susceptibility genes. The DNA-microarray technology may write a new chapter in molecular oncology.     

High expression of growth factor receptor-bound protein 14 predicts poor prognosis for colorectal cancer patients

Objects

To explore the roles of growth factor receptor-bound protein 14 (GRB14) in colorectal cancer (CRC) and its correlation with clinicopathological characteristics and prognosis of CRC patients.

Results

GRB14 was localized in the cytoplasm of CRC and benign glandular epithelium cells, showing higher levels in CRC tissues compared with normal colon samples (P < 0.001). High GRB14 was associated with a high pathological grade (P = 0.045), advanced clinical stage (P = 0.018), enhanced tumor invasion (P < 0.001) and lymph node metastasis (P = 0.028). The cancer genome atlas (TCGA) mRNA sequence data showed that GRB14 was upregulated in CRC at an advanced clinical stage (P = 0.011) with enhanced tumor invasion (P < 0.001) and lymph node metastasis (P = 0.014). Kaplan–Meier survival curves revealed that CRC patients with high GRB14 levels had a shorter survival compared with those showing low GRB14 expression (P = 0.007). High GRB14 expression was an independent prognostic factor for CRC patients (HR 2.847, 95 %CI 1.058–7.659; P = 0.038).

Conclusions

GRB14 may be an important cancer promoter that enhances CRC progression. Upregulated GRB14 levels may predict a poor clinical outcome in CRC patients.

     

Robust prediction of gene regulation in colorectal cancer tissues from DNA methylation profiles

DNA methylation is recognized as one of several epigenetic regulators of gene expression and as potential driver of carcinogenesis through gene-silencing of tumor suppressors and activation of oncogenes. However, abnormal methylation, even of promoter regions, does not necessarily alter gene expression levels, especially if the gene is already silenced, leaving the exact mechanisms of methylation unanswered. Using a large cohort of matching DNA methylation and gene expression samples of colorectal cancer (CRC; n = 77) and normal adjacent mucosa tissues (n = 108), we investigated the regulatory role of methylation on gene expression. We show that on a subset of genes enriched in common cancer pathways, methylation is significantly associated with gene regulation through gene-specific mechanisms. We built two classification models to infer gene regulation in CRC from methylation differences of tumor and normal tissues, taking into account both gene-silencing and gene-activation effects through hyper- and hypo-methylation of CpGs. The classification models result in high prediction performances in both training and independent CRC testing cohorts (0.92<AUC<0.97) as well as in individual patient data (average AUC = 0.82), suggesting a robust interplay between methylation and gene regulation. Validation analysis in other cancerous tissues resulted in lower prediction performances (0.69<AUC<0.90); however, it identified genes that share robust dependencies across cancerous tissues. In conclusion, we present a robust classification approach that predicts the gene-specific regulation through DNA methylation in CRC tissues with possible transition to different cancer entities. Furthermore, we present HMGA1 as consistently associated with methylation across cancers, suggesting a potential candidate for DNA methylation targeting cancer therapy.     

High expression of Rab3D predicts poor prognosis and associates with tumor progression in colorectal cancer

Rab3D belongs to Rab protein family. Previous reports showed that the expression of Rab3D was dysregulated in various types of cancer. Rab3D belongsRab3D belongs. However, little is known about the role of Rab3D in carcinogenesis and progression of colorectal cancer (CRC). Here, we first evaluated the expression of Rab3D in 32 fresh CRC and matched normal tissues and found Rab3D was dramatically increased in CRC tissues compared to normal tissues (p < 0.001). Furthermore, immunochemistry was used to investigate Rab3D expression in 300CRC tissue specimens. The expression of Rab3D significantly positively correlated with the tumor size (p = 0.041), CEA level (p = 0.007), tumor classification (p = 0.030), lymphatic metastasis (p < 0.001), distant metastasis (p = 0.013) and clinical stage (p = 0.003). We also demonstrated that overall survival is poor in CRC patients with high expression of Rab3D (p < 0.001). Finally, we showed that Rab3D activated Akt/GSK3β/Snail pathway and induced EMT process in colorectal cancer cells. In conclusion, this study establishes increased Rab3D expression is associated with invasiveness of CRC cells, and Rab3D expression status may serve as a reliable prognostic biomarker in CRC patients.     

A panel of differentially methylated regions enable prognosis prediction for colorectal cancer

We aim to identify a panel of differentially methylated regions (DMRs) for predicting survival outcomes for patients with CRC from the TCGA (n = 393). Four DMRs (MUC12, TBX20, CHN2, and B3GNT7) were selected as candidate prognostic markers for CRC. The prediction potential of selected DMRs was validated by the targeted bisulfite sequencing method in an independent cohort with 251 Chinese CRC patients. DMR methylation scores (DMSs) were constructed to evaluate the prognosis of CRC. Results of the validation cohort confirmed that higher DMSs were associated with poor overall survival (OS) of CRC, with hazard ratio (HR) value ranged from 1.445 to 2.698 in multivariable Cox models. Patients in the high prognostic index (high-PI) group showed a markedly unfavorable prognosis compared to the low-PI group in both TCGA discovery cohort (HR = 3.508, 95%CI: 2.196–5.604, P < 0.001) and independent validation cohort (HR = 1.912, 95%CI: 1.258–2.907, P = 0.002).     

Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

Background

One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively.

Methods and Findings

Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER− patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome.

Conclusions

The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic value for both ER-positive and ER-negative breast cancer. The signature was selected using a novel biological approach and hence holds promise to represent the key biological processes of breast cancer.     

Low NLRP3 expression predicts a better prognosis of colorectal cancer

Background: NOD-like receptor pyrin domain-3 (NLRP3) inflammasome activation is a double-edged sword in tumorigenesis. Whether NLRP3 is involved in the progression and prognosis of colorectal cancer (CRC) remains elucidated and is the focus of the present study.Methods: Immunohistochemistry (IHC) was applied on tissue microarray (TMA) to determine the expression of NLRP3 in CRC patients. All 100 patients were divided into the low NLRP3 group and the high NLRP3 group according to their NLRP3 IHC scoring. Additionally, CRC xenografts were established by injecting HCT116 or RKO cells subcutaneously into nude mice. Cell proliferation and apoptosis were determined in HCT116 cells after treatment with NLRP3 inhibitor MCC950.Results: NLRP3 expression was up-regulated in colon adenocarcinoma tissues compared with that in paracancerous tissues in CRC patients, HCT116 xenograft, and RKO xenograft. High NLRP3 level correlated with the advanced TNM classification of malignant tumors, the occurrence of distant metastasis, vascular invasion, and positive lymph nodes. Furthermore, Kaplan–Meier survival analysis revealed that a high NLRP3 level was associated with a low 5-year survival rate and even a low 10-year survival rate. Moreover, the multivariable Cox proportional hazards regression model implied that NLRP3 expression level was an independent risk factor for CRC prognosis. Inhibition of NLRP3 by MCC950 suppressed cell proliferation, induced cell apoptosis, and decreased mRNA levels of interleukin 1β (IL1β) and interleukin 18 (IL18) in HCT116 cells.Conclusions: High level of NLRP3 predicts poor survival in CRC patients. NLRP3 is a putative prognostic biomarker and a potential therapeutic target in CRC treatments.     

Mismatch repair protein MSH2 expression and prognosis of colorectal cancer patients

INTRODUCTION AND AIMS: The role of genetic factors in the etiology and prognosis of patients with sporadic colorectal cancer is controversial. We have therefore investigated the biological and clinicopathological influence of immunohistochemical MSH2 expression in colorectal cancer. PATIENTS AND METHODS: A total of 49 consecutive patients with unselected colorectal cancer operated on in our unit were included in the study. All tumors were resected and tumor specimens were evaluated for MSH2 expression. Clinicopathological data and patient survival were correlated with MSH2 staining. Uni- and multivariate analyses were performed. The minimum follow-up period was five years. RESULTS: Curative resection was performed in 34 patients (64.9%), 14 of whom subsequently relapsed. At the end of the overall follow-up 25 (51%) patients had died, 21 of cancer-related causes. Twenty-eight patients (57.1%) were negative for MSH2 staining. Only vascular invasion was significantly correlated with MSH2 expression (lower median values; p=0.04). The overall median survival was 47.9 months (95% CI=27-86.6%). Multivariate analysis of variables in relation to survival showed that T stage (p=0.001), N stage (p<0.001) and MSH2 expression (p=0.01) were independent factors for survival. CONCLUSIONS: Reduced MSH2 expression is frequent in unselected colorectal cancer patients. Only vascular invasion was correlated with MSH2 expression in this study. Survival was related to TN stage and MSH2 staining.     

Loss of EphB6 protein expression in human colorectal cancer correlates with poor prognosis

Erythropoietin-producing hepatocyte (Eph) receptor family constitutes the largest family of tyrosine kinase receptors in the human genome. Loss of EphB6, a kinase-deficient receptor, correlated with a negative outcome in several carcinomas. This study aimed to investigate the expression of EphB6 protein and mRNA levels in colorectal cancers (CRCs) and possible correlations with clinicopathological variables and prognosis. To assess protein expression level, 124 CRCs and 57 colorectal adenomas samples were examined by immunostaining, the mRNA level of 43 paired CRC and the adjacent normal tissues were detected by using SYBR Green real-time PCR method. Decreased expression of EphB6 protein was found in CRC as compared with adenoma and normal tissues (χ² = 10.146, P = 0.001 and χ² = 45.333, P < 0.001, respectively). Low EphB6 mRNA expression was detected in 83.8 % of cancers with negative or low EphB6 protein expression. The loss of EphB6 protein in CRC was positively associated with poorly differentiation (P < 0.001), lymph node metastasis (P = 0.006), Dukes stage (P = 0.002) and depth of invasion (P = 0.016). The patients with lymph node metastasis had a worse prognosis independently of gender, age, tumor site, stage and differentiation (RR = 0.404, CI 0.267–0.213, P < 0.001). Low levels of EphB6 protein expression are associated with a shorter mean duration of survival in colorectal cancer. Our results demonstrated that EphB6 may represent a novel, useful tissue biomarker for the prediction of survival rate in CRC.     

Augmented CD133 expression in distal margin correlates with poor prognosis in colorectal cancer

Pathological assessment of excised tumour and surgical margins in colorectal cancer (CRC) play crucial role in prognosis after surgery. Molecular assessment of margins could be more sensitive and informative than conventional histopathological analysis. Considering this view, we evaluated the distal surgical margins for expression of cancer stem cell (CSC) markers. Cellular and molecular assessment of normal, tumour and distal margin tissues were performed by flow cytometry, real‐time q‐PCR and immuno‐histochemical analysis for CRC patients after tumour excision. CRC patients were evaluated for expression of CSC markers in their normal, tumour and distal tissues. Flow cytometry assay revealed CD133 and CD44 enriched cells in distal margin and tumour compared to normal colorectal tissues, which was further confirmed by immunohistochemistry. Most importantly, immunohistochemistry also revealed the enrichment of CSC markers expression in pathologically negative distal margins. Patients with distal margin enriched for CD133 expression showed an increased recurrence rate and decreased disease‐free survival. This study proposes that although distal margin seems to be tumour free in conventional histopathological analysis, it could harbour cells enriched for CSC markers. Further CD133 could be a promising molecule to be used in molecular pathology for disease prognosis after surgery in CRC patients.     

Gene expression profiles of inflammatory breast cancer reveal high heterogeneity across the epithelial-hybrid-mesenchymal spectrum

Inflammatory breast cancer (IBC) is a highly aggressive breast cancer that metastasizes largely via tumor emboli, and has a 5-year survival rate of less than 30%. No unique genomic signature has yet been identified for IBC nor has any specific molecular therapeutic been developed to manage the disease. Thus, identifying gene expression signatures specific to IBC remains crucial. Here, we compare various gene lists that have been proposed as molecular footprints of IBC using different clinical samples as training and validation sets and using independent training algorithms, and determine their accuracy in identifying IBC samples in three independent datasets. We show that these gene lists have little to no mutual overlap, and have limited predictive accuracy in identifying IBC samples. Despite this inconsistency, single-sample gene set enrichment analysis (ssGSEA) of IBC samples correlate with their position on the epithelial-hybrid-mesenchymal spectrum. This positioning, together with ssGSEA scores, improves the accuracy of IBC identification across the three independent datasets. Finally, we observed that IBC samples robustly displayed a higher coefficient of variation in terms of EMT scores, as compared to non-IBC samples. Pending verification that this patient-to-patient variability extends to intratumor heterogeneity within a single patient, these results suggest that higher heterogeneity along the epithelial-hybrid-mesenchymal spectrum can be regarded to be a hallmark of IBC and a possibly useful biomarker.     

sLea and sLex expression in colorectal cancer: implications for tumourigenesis and disease prognosis

The glycoconjugates expressed by cancer cells frequently contain sialylated oligosaccharide chains. Among these oligosaccharides the sialyl Lewis a (sLe(a)) and sialyl Lewis x (sLe(x)) antigens are found to be overexpressed in tumours of different origin. The current study assesses sLe(a) and sLe(x) expression in different colorectal specimens in order to establish the correlation of these biomarkers with both malignant transformation of colorectal mucosa and the progression of colorectal cancer (CRC). Healthy disease-free and inflammatory mucosa specimens showed no presence of the antigens. sLe(a) was expressed in 6.7% of the healthy tissue from CRC patients, in 20.8% of the adenomas, and in 33.3% and 42.6% of the transitional tissue and tumour tissue, respectively. sLe(x) expression was observed in 6.7% of the healthy tissue from CRC patients, in 27.0% of the adenomas, and in 25.6% and 74.8% of the transitional and the tumour tissue, respectively. The expression of the sLe(a) and sLe(x) antigens was correlated in adenomas, as well as in healthy and tumour tissue from CRC. Moreover, the high expression of sLe(x) in adenomas was correlated with a high degree of dysplasia (p=0.042). Finally, the survival analysis suggested that sLe(a) expression may be a prognostic factor for predicting disease-free survival in colorectal cancer (p=0.012).     

A network-based gene expression signature informs prognosis and treatment for colorectal cancer patients

Background

Several studies have reported gene expression signatures that predict recurrence risk in stage II and III colorectal cancer (CRC) patients with minimal gene membership overlap and undefined biological relevance. The goal of this study was to investigate biological themes underlying these signatures, to infer genes of potential mechanistic importance to the CRC recurrence phenotype and to test whether accurate prognostic models can be developed using mechanistically important genes.

Methods and Findings

We investigated eight published CRC gene expression signatures and found no functional convergence in Gene Ontology enrichment analysis. Using a random walk-based approach, we integrated these signatures and publicly available somatic mutation data on a protein-protein interaction network and inferred 487 genes that were plausible candidate molecular underpinnings for the CRC recurrence phenotype. We named the list of 487 genes a NEM signature because it integrated information from Network, Expression, and Mutation. The signature showed significant enrichment in four biological processes closely related to cancer pathophysiology and provided good coverage of known oncogenes, tumor suppressors, and CRC-related signaling pathways. A NEM signature-based Survival Support Vector Machine prognostic model was trained using a microarray gene expression dataset and tested on an independent dataset. The model-based scores showed a 75.7% concordance with the real survival data and separated patients into two groups with significantly different relapse-free survival (p = 0.002). Similar results were obtained with reversed training and testing datasets (p = 0.007). Furthermore, adjuvant chemotherapy was significantly associated with prolonged survival of the high-risk patients (p = 0.006), but not beneficial to the low-risk patients (p = 0.491).

Conclusions

The NEM signature not only reflects CRC biology but also informs patient prognosis and treatment response. Thus, the network-based data integration method provides a convergence between biological relevance and clinical usefulness in gene signature development.     

Case-based prediction of survival in colorectal cancer patients

OBJECTIVE: To develop an approach to the prediction of survival in patients with colorectal cancer using nearest neighbor analysis and case-based reasoning. STUDY DESIGN: A total of 216 patients with full clinicopathologic records and five-year follow-up were the subjects of this study. They were divided into a core database of 162 cases and a test group of 54 cases, with follow-up on all patients. When the patient was still alive at the end of the follow-up period, censored survival time was used. For each of the test cases, the four closest neighbors from the database were retrieved and their median survival time recorded and used as the predicted estimate of survival. Case matching was based on a Euclidean multivariate distance measure for the three best predictor variables: patient age, Dukes stage and tubule configuration. Cases with the smallest distance from the test case were considered to be the most similar. The predicted survival times for the test cases were compared with the actual, observed survival in the test cases to determine the success of this approach. RESULTS: The results showed reasonable concordance between observed and predicted survival figures, although there was a large degree of spread. Classification of cases into < or = 60 and > 60 months' survival showed a correct classification rate of 63%. For the prediction of survival time, the distribution of differences between observed and predicted survival times for the uncensored test cases had a median value of--5 months but also showed a wide dispersion of values. Correlation of observed and predicted survival times, while not reaching statistical significance at P < .05, did show a strong positive association. CONCLUSION: Case-based approaches to the prediction of survival times in cancer patients are important. The results of the current study illustrate the difficulties in applying this approach to survival data and highlight the complexity of patient information and the inability to accurately predict patient outcome on a small subset of clinicopathologic features. While extensive work needs to be carried out to improve prediction power, this study illustrates the potential for case-based analyses. The ability to retrieve feature-matched cases from hospital patient databases has clear, independent advantages in patient management, but the ability to provide reliable, targeted prognostic estimates on individual cases should be a common goal in medical research.     

An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer

Background  

Estrogen receptor (ER)-negative breast cancer specimens are predominantly of high grade, have frequent p53 mutations, and are broadly divided into HER2-positive and basal subtypes. Although ER-negative disease has overall worse prognosis than does ER-positive breast cancer, not all ER-negative breast cancer patients have poor clinical outcome. Reliable identification of ER-negative tumors that have a good prognosis is not yet possible.     

Validation of CSN1S1 transcriptional expression,promoter methylation,and prognostic power in breast cancer using independent datasets

Breast cancer ranked second among most frequent cancer in the world playing a significant role in mortality rate. Having prior knowledge on differentially expressed genes in breast cell carcinoma elucidated important indications to understand the molecular mechanism underneath breast carcinogenesis. In this study we have investigated the distinguished CSN1S1 expression in human breast cancer. We have analyzed CSN1S1 mRNA expression between cancer and normal tissues using TCGA datasets. Moreover, analysis including promoter methylation, mutations, prognosis, co-expression, gene ontology, and pathways of CSN1S1 were performed by the TCGA Wanderer, UCSC Xena, cBioPortal, PrognoScan, UALCAN, and Enricher server. We have observed low mRNA expression and high promoter methylation of CSN1S1 in cancer tissues compared to normal tissues. Furthermore, we have also identified low mRNA expression in clinicopathological patients, as well as 9 deleterious mutations with highly co-expressed protein MRC1, and significantly related signaling pathways. We have found a positive correlation between the lower expression of CSN1S1 and patients surviving with breast cancer. Here we have concluded that CSN1S1 acts as a biomarker for the surveillance and prognosis of breast cancer, and also works as a novel therapeutic target at the molecular and pathway levels.     

Preoperative mannan-binding lectin pathway and prognosis in colorectal cancer

Purpose: Deficiency of the mannan-binding lectin (MBL) pathway of innate immunity is associated with increased susceptibility to infections. In patients with colorectal cancer (CRC), postoperative infection is associated with poor prognosis. The aim of the present study was to evaluate (1) the relation between the MBL pathway and postoperative infectious complications and survival of patients resected for CRC, and (2) the role of MBL in acute phase response compared to C-reactive protein (CRP). Methods: Preoperative MBL concentration, MBL-associated serine protease (MBL/MASP) activity and CRP were determined in serum from 611 patients and 150 healthy controls. The patients were observed for 8 years. Postoperative infections, recurrence and survival were recorded. Results: The MBL pathway components were increased in the patients compared with the healthy controls (p<0.0001). Low MBL levels were predictive of pneumonia (p=0.01), and pneumonia (n=87) was associated with poor survival (p=0.003; HR=1.5; 95% CI, 1.1 to 1.9). MBL and MBL/MASP activity showed no correlation with CRP (Spearmans =0.02; 95% CI, –0.06 to 0.10). Conclusion: Low preoperative MBL levels are predictive of pneumonia, which is associated with poorer survival. MBL concentration and MBL/MASP activity was not predictive of other postoperative infections or long-term prognosis, and showed no correlation with CRP.