A formalin-fixed paraffin-embedded (FFPE)-based prognostic signature to predict metastasis in clinically low risk stage I/II microsatellite stable colorectal cancer

Functional annotation with expression validation identifies novel metastasis-relevant genes from post-GWAS risk loci in sporadic colorectal carcinomas

BACKGROUND

Colorectal cancer (CRC) is the third highest incidence cancer and is the leading cause of cancer mortality worldwide. Metastasis to distal organ is the major cause of cancer mortality. However, the underlying genetic factors are unclear. This study aimed to identify metastasis-relevant genes and pathways for better management of metastasis-prone patients.

METHODS

A case-case genome-wide association study comprising 2677 sporadic Chinese CRC cases (1282 metastasis-positive vs 1395 metastasis-negative) was performed using the Human SNP6 microarray platform and analysed with the correlation/trend test based on the additive model. SNP variants with association testing -log10 p value ≥5 were imported into Functional Mapping and Annotation (FUMA) for functional annotation.

RESULTS

Glycolysis was uncovered as the top hallmark gene set. Transcripts from two of the five genes profiled, hematopoietic substrate 1 associated protein X 1 (HAX1) and hyaluronan-mediatedmotility receptor (HMMR), were significantly upregulated in the metastasis-positive tumours. In contrast to disease-risk variants, HAX1 appeared to act synergistically with HMMR in significantly impacting metastasis-free survival. Examining the subtype datasets with FUMA and Ingenuity Pathway Analysis (IPA) identified distinct pathways demonstrating sexual dimorphism in CRC metastasis.

CONCLUSIONS

Combining genome-wide association testing with in silico functional annotation and wet-bench validation identified metastasis-relevant genes that could serve as features to develop subtype-specific metastasis-risk signatures for tailored management of patients with stage I-III CRC.

Integrated analysis of Helicobacter pylori-related prognostic gene modification patterns in the tumour microenvironment of gastric cancer

Background

Helicobacter pylori (HP) infection is one of the leading causes of gastric cancer (GC). However, the interaction between HP and the TME, and its carcinogenic mechanism remains unknown.

Methods

The HP-related prognostic genes were identified based on HP infection-related gene markers and HP infection sample datasets by risk method and NMF algorithm. Principal component analysis (PCA) algorithm was used to constructed the HPscore system. The “limma” R package was employed to determine differentially expressed genes. In addition, the R packages, such as “xCell” and “GSVA”, was used to analyze the relationship between the HPscore and tumor microenvironment. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to verify the expression levels of 28 HP-related prognostic genes in tissues.

Results

We successfully identified 28 HP-related prognostic genes that accurately classified the GC population. There are significant differences in survival between different subgroups (high-, low-risk and cluster_1,2). Thereafter, the HPscore system was constructed to evaluate the signatures of the 28 HP-related prognostic genes. The overall survival rate in the high-HPscore group was poor and immunological surveillance was reduced, whereas the low-HPscore group had a survival advantage and was related to the inflammatory response. HPscore was also strongly correlated with the tumour stage, TME cell infiltration and stemness. The qRT-PCR results showed that DOCK4 expression level of 28 HP-related prognostic genes was higher in gastric cancer tissues than in adjacent tissues.

Conclusions

HP signatures play a crucial role in the TME and tumourigenesis. HPscore evaluation of a single tumour sample can help identify the TME characteristics and the carcinogenic mechanism of GC patients infected with HP, based on which personalized treatment can be administered.

SELENBP1 inhibits progression of colorectal cancer by suppressing epithelial–mesenchymal transition

Selenium-binding protein 1 (SELENBP1) is frequently dysregulated in various malignancies including colorectal cancer (CRC); however, its roles in progression of CRCs and the underlying mechanism remain to be elucidated. In this study, we compared the expression of SELENBP1 between CRCs and colorectal normal tissues (NTs), as well as between primary and metastatic CRCs; we determined the association between SELENBP1 expression and CRC patient prognoses; we conducted both in vitro and in vivo experiments to explore the functional roles of SELENBP1 in CRC progression; and we characterized the potential underlying mechanisms associated with SELENBP1 activities. We found that the expression of SELENBP1 was significantly and consistently decreased in CRCs than that in adjacent NTs, while significantly and frequently decreased in metastatic than primary CRCs. High expression of SELENBP1 was an independent predictor of favorable prognoses in CRC patients. Overexpression of SELENBP1 suppressed, while silencing of SELENBP1 promoted cell proliferation, migration and invasion, and in vivo tumorigenesis of CRC. Mechanically, SELENBP1 may suppress CRC progression by inhibiting the epithelial–mesenchymal transition.

RCRdiff: A fully integrated Bayesian method for differential expression analysis using raw NanoString nCounter data

The medium-throughput mRNA abundance platform NanoString nCounter has gained great popularity in the past decade, due to its high sensitivity and technical reproducibility as well as remarkable applicability to ubiquitous formalin fixed paraffin embedded (FFPE) tissue samples. Based on RCRnorm developed for normalizing NanoString nCounter data and Bayesian LASSO for variable selection, we propose a fully integrated Bayesian method, called RCRdiff, to detect differentially expressed (DE) genes between different groups of tissue samples (eg, normal and cancer). Unlike existing methods that often require normalization performed beforehand, RCRdiff directly handles raw read counts and jointly models the behaviors of different types of internal controls along with DE and non-DE gene patterns. Doing so would avoid efficiency loss caused by ignoring estimation uncertainty from the normalization step in a sequential approach and thus can offer more reliable statistical inference. We also propose clustering-based strategies for DE gene selection, which do not require any external dataset and are free of any arbitrary cutoff. Empirical evidence of the attractiveness of RCRdiff is demonstrated via extensive simulation and data examples.

LncRNAs Associated with Chemoradiotherapy Response and Prognosis in Locally Advanced Rectal Cancer

BACKGROUND

There are only limited studies on the long non-coding RNAs (lncRNAs) associated with neoadjuvant chemoradiotherapy (NCRT) response and prognosis of locally advanced rectal cancer (LARC) patients. This study identified lncRNAs associated with NCRT response and prognosis in CRC patients and explored their potential predictive mechanisms.

METHODS

The study subjected the LncRNA expression profiles from our previous gene chip data to LASSO and identified a four-lncRNA signature that predicted NCRT response and prognosis. A Cox regression model was subsequently performed to identify the prognostic risk factors. The function of LINC00909, the lncRNA with the most powerful predictive ability, was finally identified in vivo and in vitro using CRC cell lines.

RESULTS

A comparison of the relative lncRNA expression of NCRT-responsive and non-responsive patients revealed four hub lncRNAs: DBET, LINC00909, FLJ33534, and HSD52 with AUC = 0.68, 0.73, 0.73, and 0.70, respectively (all p < 0.05). COX regression analysis further demonstrated that DBET, LINC00909 and FLJ33534 were associated with the DFS in CRC patients. The expression of the four lncRNAs was also significant in LARC patients who had not undergone NCRT (all p < 0.05). A risk score model was subsequently constructed based on the results of the multivariate COX analysis and used to predict NCRT response and prognosis in the CRC and LARC patients. The expression and prognosis of DBET, LINC00909 and FLJ33534 in the CRC tissues were further validated in the R2 platform and Oncomine database. Notably, overexpression of the LINC00909 increased the cell line resistance to the 5-FU and radiotherapy in vivo and in vitro.

CONCLUSION

DBET, LINC00909, and FLJ33534 are potential novel biomarkers for predicting NCRT response and prognosis in CRC patients. In particular, LINC00909 is an effective oncogene in CRC that could be used as a novel therapeutic target to enhance NCRT response.

Advances in colorectal cancer genomics and transcriptomics drive early detection and prevention

Colorectal carcinoma (CRC) is a high incidence cancer and leading cause of cancer mortality worldwide. The advances in genomics and transcriptomics in the past decades have improved the detection and prevention of CRC in familial CRC syndromes. Nevertheless, the ultimate goal of personalized medicine for sporadic CRC is still not within reach due no less to the difficulty in integrating population disparity and clinical data to combat what essentially is a very heterogenous disease. This minireview highlights the achievement of the past decades and present possible direction in the hope of early detection and metastasis prevention for reducing CRC-associated morbidity and mortality.

miRNA Profile and Bioinformatic Analysis for Diagnosis in Patients with Stage IIIA Colon Cancer

Early diagnosis is a critical factor in deciding the outcome of colon cancer, as is the case with other types of cancers. Recent scientific developments have enabled the use of biomarkers for diagnosis and for designing treatment strategies for various cancer types. Further, identification of potential targets of these biomarkers will facilitate a better understanding of molecular processes. The aim of this study is to analyze microRNA expression profile, and through bioinformatic analyses determine the cellular processes of potential target genes and understand their molecular mechanism in stage IIIA colon cancer patients. The microRNA expression profiles of both normal and tumor tissues of seven patients were analyzed using the Affymetrix microarray system. The target genes were identified by performing a KEGG pathway analysis on eight miRNAs (hsa-miR-362-3p, hsa-miR-34c-5p, hsa-miR-34c-3p, hsa-miR-34a-3p, hsa-miR-19b-1-3p, hsa-miR-371a-5p, hsa-miR-941 ad hsa-miR-7-5p), which were selected through an array scan by using DIANA-miRPath v.3 bioinformatic analysis tool. Biological pathway and cellular component analyses were performed on 30 genes targeted by miRNAs using FunRich Gene Enrichment tool. These analyses indicated that the genes targeted by these eight miRNAs played a role in either cell communication (53%), signal transduction (60%) or apoptosis (20%) in stage IIIA colon cancer. Taken together, these data suggest that these miRNAs can be used as biomarkers in Stage IIIA colon cancer.

The clinical relevance of gene expression based prognostic signatures in colorectal cancer

Colorectal cancer (CRC) is one of the most prevalent cancers, with more than one million new cases every year. In the last few decades, several advancements in therapeutic and preventative levels have reduced the mortality rate, but new biomarkers are required for improved prognosis. The alterations at the genetic and epigenetic level have been recognized as major players in tumorigenesis. The products of gene expression in the form of mRNA, microRNA, and long-noncoding RNA, have started to emerge as important regulatory molecules, playing an important role in cancer. Gene-expression based prognostic risk scores, which quantify and compare their expression, have emerged as promising biomarkers with enormous clinical value. These composite multi-gene models in which more than one gene is used to predict prognosis have been shown to be significantly effective in identifying patients with multiple clinico-pathological risks like overall mortality, response to chemotherapy, risk of metastasis, etc. The advent of microarray and advanced sequencing technologies have led to the generation of large datasets like TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus), which have fueled the search for new biomarkers. Continuous evaluation of these candidate biomarkers in clinical settings is promising to improve the management of CRC. These composite gene signatures provide potential in identifying high-risk patients, which might help clinicians to better manage these patients and design appropriate personalized therapeutic interventions. In this review, we emphasize on composite prognostic scores from diverse resources with clinical utility in CRC.

Enhancer-derived long non-coding RNAs CCAT1 and CCAT2 at rs6983267 has limited predictability for early stage colorectal carcinoma metastasis

Up-regulation of long non-coding RNAs (lncRNAs), colon-cancer associated transcript (CCAT) 1 and 2, was associated with worse prognosis in colorectal cancer (CRC). Nevertheless, their role in predicting metastasis in early-stage CRC is unclear. We measured the expression of CCAT1, CCAT2 and their oncotarget, c-Myc, in 150 matched mucosa-tumour samples of early-stage microsatellite-stable Chinese CRC patients with definitive metastasis status by multiplex real-time RT-PCR assay. Expression of CCAT1, CCAT2 and c-Myc were significantly up-regulated in the tumours compared to matched mucosa (p < 0.0001). The expression of c-Myc in the tumours was significantly correlated to time to metastasis [hazard ratio = 1.47 (1.10–1.97)] and the risk genotype (GG) of rs6983267, located within CCAT2. Expression of c-Myc and CCAT2 in the tumour were also significantly up-regulated in metastasis-positive compared to metastasis-negative patients (p = 0.009 and p = 0.04 respectively). Nevertheless, integrating the expression of CCAT1 and CCAT2 by the Random Forest classifier did not improve the predictive values of ColoMet19, the mRNA-based predictor for metastasis previously developed on the same series of tumours. The role of these two lncRNAs is probably mitigated via their oncotarget, c-Myc, which was not ranked high enough previously to be included in ColoMet19.

GABRD promotes progression and predicts poor prognosis in colorectal cancer

Little is known about the functional roles of gamma-aminobutyric acid type A receptor subunit delta (GABRD) in colorectal cancer (CRC). The expression of GABRD between CRCs and adjacent normal tissues (NTs), metastasis and primary tumors was compared using public transcriptomic datasets. A tissue microarray and immunohistochemical staining (IHC) were used to determine the clinical and prognostic significance of the GABRD in CRC. We used gain-of-function and loss-of-function experiments to investigate the in vitro roles of GABRD in cultured CRC cells. We characterized the potential mechanism of GABRD’s activities in CRC using a Gene Set Enrichment Analysis (GSEA) with The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) dataset. We found that the GABRD expression was significantly increased in CRCs compared to that in NTs, but was similar between metastasis and primary tumors. Overexpression of GABRD was significantly associated with later pTNM stages and unfavorable patient survival. Overexpression of GABRD accelerated while knock-down of GABRD inhibited cell growth and migration. Mechanistically, the function of GABRD might be ascribed to its influence on major oncogenic events such as epithelial–mesenchymal transition (EMT), angiogenesis, and hedgehog signaling. Collectively, GABRD could be a novel prognostic predictor for CRC that deserves further investigation.

Hypomethylation of GDNF family receptor alpha 1 promotes epithelial-mesenchymal transition and predicts metastasis of colorectal cancer

Tumor metastasis is the major cause of poor prognosis and mortality in colorectal cancer (CRC). However, early diagnosis of highly metastatic CRC is currently difficult. In the present study, we screened for a novel biomarker, GDNF family receptor alpha 1 (GFRA1) based on the expression and methylation data in CRC patients from The Cancer Genome Altlas (TCGA), followed by further analysis of the correlation between the GFRA1 expression, methylation, and prognosis of patients. Our results show DNA hypomethylation-mediated upregulation of GFRA1 in invasive CRC, and it was found to be correlated with poor prognosis of CRC patients. Furthermore, GFRA1 methylation-modified sequences were found to have potential as methylation diagnostic markers of highly metastatic CRC. The targeted demethylation of GFRA1 by dCas9-TET1CD and gRNA promoted CRC metastasis in vivo and in vitro. Mechanistically, demethylation of GFRA1 induces epithelial-mesenchymal transition (EMT) by promoting AKT phosphorylation and increasing c-Jun expression in CRC cells. Collectively, our findings indicate that GFRA1 hypomethylation can promote CRC invasion via inducing EMT, and thus, GFRA1 methylation can be used as a biomarker for the early diagnosis of highly metastasis CRC.

Abnormal DNA methylation, one of important characteristics in tumor cells, is exploited as biomarkers for cancer diagnosis and prognosis prediction. Early diagnosis of highly metastatic CRC will be helpful for the clinical management, thus prolongs patient survival. However, it is currently difficult to make early diagnosis of highly metastatic CRC in clinical practice. Currently, we screened a novel biomarker gene, GFRA1, which associated with the invasion and poor prognosis of CRC. The targeted demethylation of GFRA1 exerted a significant promoting effect on CRC metastasis, and GFRA1 methylation-modified sequences are valuable diagnostic biomarker for CRC metastasis risk assessment. Mechanically, demethylation of GFRA1 induced epithelial-mesenchymal transition (EMT) by upregulating AKT phosphorylation and c-Jun expression in CRC cells. Our results demonstrate the promoting effect of GFRA1 demethylation on CRC invasion and GFRA1 methylation may be a potential prognostic marker for predicting metastasis of CRC.

miRNA-148a-3p Regulates Immunosuppression in DNA Mismatch Repair-Deficient Colorectal Cancer by Targeting PD-L1

Immunotherapy against the interaction between programmed cell death 1/programmed cell death ligand 1 (PD-L1) has emerged as a promising strategy for colorectal cancer with mismatch repair deficiency (dMMR) or microsatellite instability-high (MSI-H). The study aimed to identify miRNAs that posttranscriptionally control PD-L1 expression on tumor cells and also regulate immune evasion. A comprehensive miRNA screening using The Cancer Genome Atlas (TCGA) dataset (n = 260) combined with eight different miRNA target prediction programs resulted in the identification of a tumor suppressive miRNA, miR-148a-3p, as a potential negative regulator of PD-L1 expression, particularly in dMMR/MSI-H colorectal cancer. Using multiple cohorts of colorectal cancer, including TCGA data, a microarray dataset (n = 148), and formalin-fixed, paraffin-embedded samples (n = 395), we found that the expression of miR-148a-3p was decreased in dMMR/MSI-H tumors, correlating inversely with PD-L1 levels. We demonstrate that miR-148a-3p directly binds to the 3'-untranslated region of PD-L1, thereby reducing whole-cell and cell surface PD-L1 levels in HCT116 and SW837 cell lines. Overexpression of miR-148a-3p repressed IFNγ-induced PD-L1 expression on tumor cells and consequently diminished T-cell apoptosis in a coculture model of IL2-activated T cells and IFNγ-treated tumor cells. In conclusion, our data support a regulatory mechanism of PD-L1 expression on tumor cells and immune suppression via miR-148a-3p downregulation in colorectal cancer. IMPLICATIONS: This study provides novel evidence that miR-148a-3p negatively regulates tumor cell PD-L1 expression and decreased levels of miR-148a-3p contributes to the immunosuppressive tumor microenvironment.