Discovery of a Novel Immune Gene Signature with Profound Prognostic Value in Colorectal Cancer: A Model of Cooperativity Disorientation Created in the Process from Development to Cancer

Identification and analysis of key genes related to efferocytosis in colorectal cancer

The impact of efferocytosis-related genes (ERGs) on the diagnosis of colorectal cancer (CRC) remains unclear. In this study, efferocytosis-associated biomarkers for the diagnosis of CRC were identified by integrating data from transcriptome sequencing and public databases. Finally, the expression of biomarkers was validated by real-time quantitative polymerase chain reaction (RT-qPCR). Our study may provide a reference for CRC diagnosis.

BACKGROUND

It has been shown that some efferocytosis related genes (ERGs) are associated with the development of cancer. However, it is still uncertain how ERGs may influence the diagnosis of colorectal cancer (CRC).

METHODS

In our study, the CRC cohorts were gained from transcriptome sequencing and the gene expression omnibus (GEO) database (GSE71187). Efferocytosis related biomarkers with diagnostic utility for CRC were identified through combining differentially expressed analysis, machine learning algorithms, and receiver operating characteristic (ROC) analysis. Then, infiltration abundance of immune cells between CRC and control was evaluated. The regulatory networks (including mRNA-miRNA-lncRNA and miRNA/transcription factors (TF)-mRNA networks) were created. Finally, the expression of biomarkers was validated via real-time quantitative polymerase chain reaction (RT-qPCR).

RESULTS

There were 3 biomarkers (ELMO3, P2RY12, and PDK4) related diagnosis for CRC patients gained. ELMO3 was highly expressed in CRC group, while P2RY12 and PDK4 was lowly expressed. Besides, the infiltrating abundance of 3 immune cells between CRC and control groups was significantly differential, namely activated CD4 memory T cells, macrophages M0, and resting mast cells. We then constructed a mRNA-miRNA-lncRNA network containing 3 mRNAs, 33 miRNAs, and 22 lncRNAs, and a miRNA/TF-mRNA network including 3 mRNAs, 33 miRNAs, and 7 TFs. Additionally, RT-qPCR results revealed that the expression trends of all biomarkers were consistent with the transcriptome sequencing data and GSE71187.

CONCLUSION

Taken together, this study provides three efferocytosis related biomarkers (ELMO3, P2RY12, and PDK4) for diagnosis of CRC, providing a scientific reference for further studies of CRC.

High expression of NXPH4 correlates with poor prognosis, metabolic reprogramming, and immune infiltration in colon adenocarcinoma

Background

Colon adenocarcinoma (COAD) is a prevalent gastrointestinal malignant disease with high mortality rate, and identification of novel prognostic biomarkers and therapeutic targets is urgently needed. Although neurexophilin 4 (NXPH4) has been investigated in several tumors, its role in COAD remains unclear. The aim of this study was to explore the prognostic value and potential functions of NXPH4 in COAD.

Methods

The expression of NXPH4 in COAD were analyzed using The Cancer Genome Atlas (TCGA) and datasets from the Gene Expression Omnibus (GEO) database. The prognostic value of NXPH4 was determined using Kaplan-Meier analysis and Cox regression analysis. To investigate the possible mechanism underlying the role of NXPH4 in COAD, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were employed. The correlation between NXPH4 expression and immune cell infiltration levels was examined thorough single-sample gene set enrichment analysis (ssGSEA). Furthermore, the competing endogenous RNA (ceRNA) regulatory network that may be involved in NXPH4 in COAD was predicted and constructed through a variety of databases.

Results

NXPH4 expression was significantly higher in COAD tissue compared with normal colon tissues. Meanwhile, high expression of NXPH4 was associated with poor prognosis in COAD patients. GO-KEGG and GSEA analyses indicated that NXPH4 was associated with glycolysis and hypoxia pathway, and may promote COAD progression and metastasis by modulating metabolic reprogramming. ssGSEA analysis demonstrated that NXPH4 expression also associated with immune infiltration. Furthermore, we identified various microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) as upstream regulators of NXPH4 in COAD.

Conclusions

The present study revealed that high expression of NXPH4 is associated with tumor progression, metabolic reprogramming, and immune infiltration. These findings suggest that NXPH4 could serve as a reliable prognostic biomarker and a promising therapeutic target in COAD.

High Expression of ATP6V1C2 Predicts Unfavorable Overall Survival in Patients With Colon Adenocarcinoma

Aims: Colon adenocarcinoma (COAD) is responsible for 90% of all colorectal cancer cases and is one of the most common causes of cancer-related deaths worldwide. ATP6V1s (cytosolic V1 domain of vacuolar adenosine triphosphatase) participate in the biological process of transporting hydrogen ions and are implicated in tumor growth and metastasis. ATP6V1C2 as a family member has been documented to associate with esophageal carcinoma and renal clear cell carcinoma, while its roles in COAD remain elusive.

Methods: The expression status, potential molecular mechanism, and prognostic value of ATP6V1C2 in COAD were investigated using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. In addition, its biological roles in COAD were explored through in vitro studies.

Results: ATP6V1C2 showed a significantly higher expression level in COAD compared with matched non-cancerous tissues. High expression of ATP6V1C2 predicted a shorter overall survival both in TCGA and GEO COAD datasets, and ATP6V1C2 was identified as an independent factor associated with overall survival in COAD. Bioinformatic analyses showed that high expression of ATP6V1C2 was associated with high epithelial–mesenchymal transition (EMT) score and Wnt signaling pathway was significantly enriched from differentially expressed genes between ATP6V1C2-high and -low group. We also found that high expression of ATP6V1C2 could decrease pathway activity of CD8 T effector implicated in tumor microenvironment (TME). In vitro study revealed that ATP6V1C2 knockdown resulted in aberrant expression of Wnt- and EMT-related genes and inhibited COAD cell proliferation and growth.

Conclusion: This is the first study to reveal the molecular functions of ATP6V1C2 in COAD. Our study suggests that overexpressed ATP6V1C2 might promote EMT by activating Wnt signaling pathway, resulting in cancer metastasis and poor prognosis. This study paves the way for understanding potential molecular mechanisms and therapeutic perspectives in COAD.

Construction of a Novel MYC-Associated ceRNA Regulatory Network to Identify Prognostic Biomarkers in Colon Adenocarcinoma

Colorectal cancer (CRC) includes colon adenocarcinoma (COAD) and rectal adenocarcinoma (READ). Competitive endogenous RNA (ceRNA) is crucial for cancer pathogenesis. Abnormal expression of MYC is generally associated with a poor colon adenocarcinoma prognosis. The present study aimed to identify a novel MYC-associated ceRNA regulatory network and identify potential prognostic markers associated with COAD. We obtained the transcriptome sequencing profiles of 462 COAD cases from the TCGA database and analyzed differentially expressed genes (DEGs) in MYC high expression (MYChigh) and MYC low expression (Myclow) tumors. We identified an important lncRNA, LINC00114, which effectively predicts overall survival and plays a protective role in COAD. Moreover, the LINC00114/miR-216a-5p axis was identified as a clinical prognostic model. The predicted target genes of the LINC00114/miR-216a-5p axis include uromodulin Like 1 (UMODL1) and oncoprotein induced transcript 3 (OIT3), which are closely related to the survival and prognosis of COAD patients. In summary, we constructed a novel ceRNA regulatory network and identified potential biomarkers for the targeted therapy and prognosis of COAD.

Combined Efficacy of CXCL5, STC2, and CHI3L1 in the Diagnosis of Colorectal Cancer

Objective

To improve the diagnostic capacity of serum biomarkers for colorectal cancer (CRC), we introduced three novel indicators, namely, the C-X-C motif chemokine ligand 5 (CXCL5), stanniocalcin 2 (STC2), and chitinase 3 like 1 (CHI3L1) and assessed their performances in the detection of CRC.

Methods

A total of 887 serum samples (153 health, 342 polyps, and 392 CRCs) were collected. Concentrations of CXCL5, STC2, and CHI3L1 were measured by the ELISA. CEA and CA199 were determined by electrochemiluminescence. Binary logistic regression was used to build the combination model. ROC analysis was used to evaluate the performance of biomarkers alone or in combination.

Results

Model_2 that based on CXCL5, STC2, and CHI3L1 was the best approach in discriminating CRC from non-CRC controls (AUC, 0.943 (0.922–0.960); sensitivity, 0.848; specificity, 0.917; and accuracy, 0.887 in the training cohort and 0.959 (95% CI 0.927–0.980), 0.878, 0.917, and 0.900 in the testing cohort, respectively). In the detection of early CRC, Model_2 revealed AUC, sensitivity, specificity, and accuracy of 0.925 (0.897–0.947), 0.793, 0.917, and 0.886 in the training cohort and those of 0.926 (0.979–0.959), 0.786, 0.931, and 0.898 in the testing cohort. Furthermore, Model_2 exhibited an excellent diagnostic performance in CEA-negative cases (0.938 (0.913–0.957), 0.826, 0.917, and 0.888 in the training cohort and 0.961 (0.925–0.983), 0.887, 0.931, and 0.918 in the testing cohort). As used alone, STC2 achieved the capacities that is second only to that of Model_2 (0.866 (0.837–0.892), 0.859, 0.842, and 0.853 in the training cohort and 0.887 (0.842–0.923), 0.922, 0.799, and 0.853 in the testing cohort). STC2 alone also yielded acceptable results for early CRC detection (0.815 (0.776–0.849), 0.767, 0.849, and 0.829 in the training cohort and 0.870 (0.812–0.914), 0.952, 0.799, and 0.833 in the testing cohort). Moreover, STC2 maintained diagnostic accuracy for CRC patients with negative CEA (0.874 (0.842–0.901), 0.862, 0.849, and 0.853 in the training cohort and 0.898 (0.848–0.936), 0.930, 0.801, and 0.842 in the testing cohort). In comparison, the performances of the CEA and CA199 based Model_1 were far from satisfactory, especially in early cases (0.767 (0.726–0.805), 0.491, 0.863, and 0.771 in the training cohort and 0.817 (0.754–0.870), 0.476, 0.889, and 0.796 in the testing cohort).

Conclusions

STC2 was a promising serum biomarker for CRC diagnosis either used alone or in combination with CXCL5 and CHI3L1.

A Gene-Based Machine Learning Classifier Associated to the Colorectal Adenoma-Carcinoma Sequence

Colorectal cancer (CRC) carcinogenesis is generally the result of the sequential mutation and deletion of various genes; this is known as the normal mucosa–adenoma–carcinoma sequence. The aim of this study was to develop a predictor-classifier during the “adenoma-carcinoma” sequence using microarray gene expression profiles of primary CRC, adenoma, and normal colon epithelial tissues. Four gene expression profiles from the Gene Expression Omnibus database, containing 465 samples (105 normal, 155 adenoma, and 205 CRC), were preprocessed to identify differentially expressed genes (DEGs) between adenoma tissue and primary CRC. The feature selection procedure, using the sequential Boruta algorithm and Stepwise Regression, determined 56 highly important genes. K-Means methods showed that, using the selected 56 DEGs, the three groups were clearly separate. The classification was performed with machine learning algorithms such as Linear Model (LM), Random Forest (RF), k-Nearest Neighbors (k-NN), and Artificial Neural Network (ANN). The best classification method in terms of accuracy (88.06 ± 0.70) and AUC (92.04 ± 0.47) was k-NN. To confirm the relevance of the predictive models, we applied the four models on a validation cohort: the k-NN model remained the best model in terms of performance, with 91.11% accuracy. Among the 56 DEGs, we identified 17 genes with an ascending or descending trend through the normal mucosa–adenoma–carcinoma sequence. Moreover, using the survival information of the TCGA database, we selected six DEGs related to patient prognosis (SCARA5, PKIB, CWH43, TEX11, METTL7A, and VEGFA). The six-gene-based classifier described in the current study could be used as a potential biomarker for the early diagnosis of CRC.

Colon Cancer Progression Is Reflected to Monotonic Differentiation in Gene Expression and Pathway Deregulation Facilitating Stage-specific Drug Repurposing

BACKGROUND/AIM

Colon cancer is one of the most common cancer types and the second leading cause of death due to cancer. Many efforts have been performed towards the investigation of molecular alterations during colon cancer progression. However, the identification of stage-specific molecular markers remains a challenge. The aim of this study was to develop a novel computational methodology for the analysis of alterations in differential gene expression and pathway deregulation across colon cancer stages in order to reveal stage-specific biomarkers and reinforce drug repurposing investigation.

MATERIALS AND METHODS

Transcriptomic datasets of colon cancer were used to identify (a) differentially expressed genes with monotonicity in their fold changes (MEGs) and (b) perturbed pathways with ascending monotonic enrichment (MEPs) related to the number of the participating differentially expressed genes (DEGs), across the four colon cancer stages. Through an in silico drug repurposing pipeline we identified drugs that regulate the expression of MEGs and also target the resulting MEPs.

RESULTS

Our methodology highlighted 15 MEGs and 32 candidate repurposed drugs that affect their expression. We also found 51 MEPs divided into two groups according to their rate of DEG content alteration across colon cancer stages. Focusing on the target MEPs of the highlighted repurposed drugs, we found that one of them, the neuroactive ligand-receptor interaction, was targeted by the majority of the candidate drugs. Moreover, we observed that two of the drugs (PIK-75 and troglitazone) target the majority of the resulting MEPs.

CONCLUSION

These findings highlight significant genes and pathways that can be used as stage-specific biomarkers and facilitate the discovery of new potential repurposed drugs for colon cancer. We expect that the computational methodology presented can be applied in a similar way to the analysis of any progressive disease.

Immune infiltration and prognostic and diagnostic use of LGALS4 in colon adenocarcinoma and bladder urothelial carcinoma

Colon adenocarcinoma (COAD) is a common tumor of the gastrointestinal tract with a high mortality rate. Current research has identified many genes associated with immune infiltration that play a vital role in the development of COAD. In this study, we analysed the prognostic and diagnostic features of such immune-related genes in the context of colonic adenocarcinoma (COAD). We analysed 17 overlapping gene expression profiles of COAD and healthy samples obtained from TCGA-COAD and public single-cell sequencing resources, to identify potential therapeutic COAD targets. We evaluated the abundance of immune infiltration with those genes using the TIMER (Tumor Immune Estimation Resource) deconvolution method. Subsequently, we developed predictive and survival models to assess the prognostic value of these genes. The LGALS4 (Galectin-4) gene was found to be significantly (P<0.05) downregulated in COAD and bladder urothelial carcinoma (BLCA) compared to healthy samples. We identified LGALS4 as a prognostic and diagnostic marker for multiple cancer types, including COAD and BLCA. Our analysis reveals a series of novel candidate drug targets, as well as candidate molecular markers, that may explain the pathogenesis of COAD and BLCA. LGALS4 gene is associated with multiple cancer types and is a possible prognostic, as well as diagnostic, marker of COAD and BLCA.

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.

Identification of Prognostic Biomarkers for Multiple Solid Tumors Using a Human Villi Development Model

The processes of embryonic development that rely on epithelial-mesenchymal transition (EMT) for the implantation of trophoblast cells are co-opted by tumors, reflecting their inherent uncontrolled characteristics and leading to invasion and metastasis. Although tumorigenesis and embryogenesis have similar EMT characteristics, trophoblasts have been shown to exhibit "physiological metastasis" or be "pseudo-malignant," resulting in different outcomes. The gene co-expression network is the basis of embryonic development and tumorigenesis. We hypothesize that if the gene co-expression network in tumors is "off-track" from that in villi, it is more likely to develop into malignant tumors and have a worse prognosis, and we proposed the "off-track theory" for the first time. In this study, we examined gene co-expression networks in villi and multiple solid tumors. Through network functional enrichment analyses, we found that most tumors and villi exhibited a significantly enriched EMT, but the genes that performed this function were not identical. Then, we identified the "off-track genes" in the EMT-related gene interaction network using the "off-track theory," and through survival analysis, we discovered that the risk score of "off-track genes" was associated with poor survival of cancer patients. Our study indicated that villi development is a reliable and strictly regulated model that can illuminate the trajectory of human cancer development and that the gene co-expression networks in tumor development are "off-track" from those in villi. These "off-track genes" may have a substantial impact on tumor development and could reveal novel prognostic biomarkers.

IRF1 association with tumor immune microenvironment and use as a diagnostic biomarker for colorectal cancer recurrence

Colorectal cancer (CRC) is considered to be one of the most lethal cancer types globally, and its recurrence is a major treatment challenge. Identifying the factors involved when determining the risk of CRC recurrence is required to improve personalized therapy for patients with CRC. Based on the GSE39582 dataset, the present study demonstrated that a higher ratio of M1 macrophages and activated memory CD4+ T cells indicated a better recurrence-free survival (RFS) time for CRC, using CIBERSORT and Pearson's correlation analysis. Through weighted correlation network analysis (WGCNA), an immune-associated module was identified that was significantly positively correlated with the ratio of M1 macrophages and activated memory CD4+ T cells. In this module, using WGCNA and a protein-protein interaction network, interferon regulatory factor 1 (IRF1), chemokine ligand 5, ubiquitin/ISG15-conjugating enzyme E2 L6, guanylate binding protein 1 and interleukin 2 receptor subunit beta were identified as hub genes. Among these genes, univariate Cox and multivariate Cox analysis revealed that IRF1 may be a potential diagnostic biomarker for RFS in patients with CRC. This was further validated using The Cancer Genome Atlas data. Gene set enrichment analysis demonstrated that IRF1 influenced the genes and pathways that are associated with immune cell recruitment and activation. Additionally, the DNA methylation of cg27587780 and cg15375424 CpG sites in the IRF1 gene region was indicated to be negatively correlated with IRF1 mRNA expression and positively correlated with the recurrence of CRC. Collectively, the results of the present study demonstrated that IRF1 may be a potential diagnostic biomarker for RFS in patients with CRC.

Prognostic and predictive values of CXCL10 in colorectal cancer

BACKGROUND

The role of CXCL10 in progression and prognosis of colorectal cancer (CRC) has been studied for years, yet results remain controversial.

AIM

This study aims to explore the relationship between CXCL10 and CRC progression and prognosis.

METHODS

We evaluated plasma CXCL10 in CRC patients using ELISA. We also performed a meta-analysis of the associations between CXCL10 and overall survival (OS), disease-free survival (DFS), disease-specific survival (DSS), relapse-free survival (RFS), and clinicopathological features. Finally, correlations between CXCL10 and methylation or immune infiltration were performed using TCGA data.

RESULTS

ELISA analysis showed that CXCL10 was associated with age, red blood cells, blood platelets, and blood urea nitrogen. A separate analysis of 3,763 patients from 24 studies revealed that there were significant associations between low CXCL10 expression and OS (HR 1.25, 95% CI 1.01-1.53), DFS (HR 1.65, 95% CI 1.17-2.34), and RFS (HR 1.43, 95% CI 1.20-1.71) in CRC. Additionally, downregulated CXCL10 expression was significantly correlated with age [odds ratio (OR) 1.31, 95% CI 1.13-1.52], metastasis (OR 1.34, 95% CI 1.11-1.63), recurrence (OR 1.46, 95% CI 1.16-1.83), tumor location (OR 1.88, 95% CI 1.58-2.24), differentiation (OR 0.57, 95% CI 0.35-0.93), microsatellite instability (OR 0.23, 95% CI 0.15-0.35), BRAF mutation (OR 1.62, 95% CI 1.25-2.08), p53 mutation (OR 0.28, 95% CI 0.16-0.47), and CIMP (OR 0.27, 95% CI 0.17-0.43). Furthermore, significant associations were observed between CXCL10 and methylation and immune infiltration.

CONCLUSIONS

The study suggests that CXCL10 might be a potential target for the treatment of CRC.

TRIAL REGISTRATION

NCT03189992. Registered 4 June 2017, https://www.clinicaltrials.gov/ct2/show/study/NCT03189992?term=NCT03189992&rank=1 .

Integrated analysis of competing endogenous RNA networks revealing five prognostic biomarkers associated with colorectal cancer

Colorectal cancer (CRC) is a common malignant tumor with high morbidity and mortality around the world. The aim of this study was to determine the genes significantly associated with the overall survival (OS) of CRC patients and predict their function in the competing endogenous RNA (ceRNA) regulation networks. We constructed the lncRNA-miRNA-mRNA networks according to the differentially expressed RNAs from the The Cancer Genome Atlas data sets of 561 CRC patients. Twelve differentially expressed messenger RNAs from the ceRNA networks were selected through a univariate Cox proportional hazards regression. Then, these genes were analyzed by using multivariate Cox proportional hazards stepwise regression to construct a prognostic model in which five genes (tensin 1, clusterin, proteolipid protein 1, epiregulin, and transcription factor Spi-B) were included. The Kaplan-Meier risk survival analysis showed that this five-gene signature independently predicted a 5-year overall survival in CRC patients (P < 0.001). Furthermore, significance was verified according to two irrelevant Gene Expression Omnibus (GEO) data sets (GSE38832 and GSE39582). The verified five-gene model of CRC can be used to predict patient prognosis and will inform postoperational evaluation and follow-up strategies.

Identification of prognostic genes in colorectal cancer through transcription profiling of multi-stage carcinogenesis

Colorectal cancer is a complex multistage process following the adenoma-carcinoma sequence. Additional research on the basis of molecular dysregulations, particularly in the precancerous stage, may provide insight into the realization of potential biomarkers and therapeutic targets for the disease. In the present study, the expression profile of human multistage colorectal mucosa tissues, including healthy, adenoma and adenocarcinoma samples, was downloaded. Genes that were consistently differentially expressed in precancerous tissues and cancer samples were collected. Based on a merged biological network, the biggest connected component composed of these identified genes and their one-step neighbors were retrieved to conduct random walk with restart algorithm, in order to identify genes significantly affected during carcinogenesis. Therefore, 35 genes significantly affected by carcinogenic dysregulation were successfully identified. Survival and Cox analysis indicated that the expression of these genes was an independent prognostic factor confirmed by six cohorts. In summary, based on the transcription profile of multi-stage carcinogenesis and bioinformatics analysis, 35 genes significantly associated with patient survival were successfully identified, which may serve as promising therapeutic targets for the disease.

Identification of Critical Genes and Five Prognostic Biomarkers Associated with Colorectal Cancer

BACKGROUND Colorectal cancer (CRC) is a common malignant tumor with high incidence and mortality worldwide. The aim of this study was to evaluate the association between differentially expressed genes (DEGs), which may function as biomarkers for CRC prognosis and therapies, and the clinical outcome in patients with CRC. MATERIAL AND METHODS A total of 116 normal mucous tissue and 930 CRC tissue datasets were downloaded from the Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA). After screening DEGs based on limma package in R. Gene Ontology (GO) and KEGG enrichment analysis as well as the protein-protein interaction (PPI) networks were performed to predict the function of these DEGs. Meanwhile, Cox proportional hazards regression was used to build a prognostic model of these DEGs. Then, Kaplan-Meier risk analysis was used to test the model in TCGA datasets and validation datasets. RESULTS In the present study, 300 DEGs with 100 upregulated genes and 200 downregulated genes were identified. The PPI networks including 162 DEGs and 256 nodes were constructed and 2 modules with high degree were selected. Moreover, 5 genes (MMP1, ACSL6, SMPD1, PPARGC1A, and HEPACAM2) were identified using the Cox proportional hazards stepwise regression. Kaplan-Meier risk curve in the TCGA and validation cohorts showed that high-risk group had significantly poor overall survival than the low-risk group. CONCLUSIONS Our study provided insights into the mechanisms of CRC formation and found 5 prognostic genes, which could potentially inform further studies and clinical therapies.

Immune Prophets of Lung Cancer: The Prognostic and Predictive Landscape of Cellular and Molecular Immune Markers

Lung cancer is the leading cause of cancer deaths throughout the world. The majority of patients are diagnosed with locally advanced or metastatic disease when surgery, the best curative option, is no longer feasible. Thus, the prognosis of lung cancer remains poor and heterogeneous and new biomarkers are needed. As the immune system plays a pivotal role in cancer, the study of tumor microenvironment, with regard to the immune component, may provide valuable information for a better comprehension of the pathogenesis and progression of the disease. Through a detailed and critical evaluation of the most recent publications on this topic, we provide evidences of the prognostic and predictive significance of immune markers in tumor and in peripheral blood of lung cancer patients: from the landscape of immune cells (macrophages, neutrophils, lymphocytes and natural killer) and their cytokines, to the analysis of immune-checkpoints (PD-L1 and CTLA4), up to the genetic and epigenetic regulation of the immune response (immune gene signatures and miRNA). We also argue about the lights and shadows related to immune marker use in clinical practice, emphasizing on one hand the importance of their assessment in the choice of therapeutic treatment, on the other, the difficulty in their determination and reproducibility of literature data. The following review gives a foundation and a suggestion for future studies investigating tumor immunology in lung cancer.

The clinical implications of immunogenomics in colorectal cancer: A path for precision medicine

Colorectal cancer (CRC) remains the third most common malignancy and the second-leading cause of cancer-related deaths in the United States. Large multi-omic databases, such as The Cancer Genome Atlas and the International Colorectal Cancer Subtyping Consortium, have identified distinct molecular subtypes related to anatomy. The identification of genomic alterations in CRC is now critical because of the recent success and US Food and Drug Administration approval of pembrolizumab and nivolumab for microsatellite-instable tumors. In parallel, landmark studies have established the prognostic significance of the CRC tumor-infiltrating lymphocyte and the clinical impact of the tumor immune microenvironment. As a result, there is a growing appreciation for immunogenomics, the interconnected relation between tumor genomics and the immune microenvironment. The clinical implications of CRC immunogenomics continue to expand, and it will likely serve as a guide for next-generation immunotherapy strategies for improving outcomes for this disease. Cancer 2018;124:1650-9. © 2018 American Cancer Society.

Prognostic impact of a novel gene expression profile classifier for the discrimination between metastatic and non-metastatic primary colorectal cancer tumors

Despite significant advances have been achieved in the genetic characterization of sporadic colorectal cancer (sCRC), the precise genetic events leading to the development of distant metastasis remain poorly understood. Thus, accurate prediction of metastatic disease in newly-diagnosed sCRC patients remains a challenge. Here, we evaluated the specific genes and molecular pathways associated with the invasive potential of colorectal tumor cells, through the assessment of the gene expression profile (GEP) of coding and non-coding genes in metastatic (MTX) vs. non-metastatic (non-MTX) primary sCRC tumors followed for >5 years. Overall, MTX tumors showed up-regulation of genes associated with tumor progression and metastatic potential while non-MTX cases displayed GEP associated with higher cell proliferation, activation of DNA repair and anti-tumoral immune/inflammatory responses. Based on only 19 genes a specific GEP that classifies sCRC tumors into two MTX-like and non-MTX-like molecular subgroups was defined which shows an independent prognostic impact on patient overall survival, particularly when it is combined with the lymph node status at diagnosis. In summary, we show an association between the global GEP of primary sCRC cells and their metastatic potential and defined a GEP-based classifier that provides the basis for further prognostic stratification of sCRC patients who are at risk of distant metastases.

A 16-gene signature predicting prognosis of patients with oral tongue squamous cell carcinoma

Background

Oral tongue squamous cell carcinoma (OTSCC) is the most common subtype of oral cancer. A predictive gene signature is necessary for prognosis of OTSCC.

Methods

Five microarray data sets of OTSCC from the Gene Expression Omnibus (GEO) and one data set from The Cancer Genome Atlas (TCGA) were obtained. Differentially expressed genes (DEGs) of GEO data sets were identified by integrated analysis. The DEGs associated with prognosis were screened in the TCGA data set by univariate survival analysis to obtain a gene signature. A risk score was calculated as the summation of weighted expression levels with coefficients by Cox analysis. The signature was used to distinguish carcinoma, estimated by receiver operator characteristic curves and the area under the curve (AUC). All were validated in the GEO and TCGA data sets.

Results

Integrated analysis of GEO data sets revealed 300 DEGs. A 16-gene signature and a risk score were developed after survival analysis. The risk score was effective to stratify patients into high-risk and low-risk groups in the TCGA data set (P < 0.001). The 16-gene signature was valid to distinguish the carcinoma from normal samples (AUC 0.872, P < 0.001).

Discussion

We identified a useful 16-gene signature for prognosis of OTSCC patients, which could be applied to clinical practice. Further studies were needed to prove the findings.

Molecular signatures reflecting microenvironmental metabolism and chemotherapy-induced immunogenic cell death in colorectal liver metastases

Background

Metastatic colorectal cancer (CRC) is associated with highly variable clinical outcome and response to therapy. The recently identified consensus molecular subtypes (CMS1-4) have prognostic and therapeutic implications in primary CRC, but whether these subtypes are valid for metastatic disease is unclear. We performed multi-level analyses of resectable CRC liver metastases (CLM) to identify molecular characteristics of metastatic disease and evaluate the clinical relevance.

Methods

In this ancillary study to the Oslo-CoMet trial, CLM and tumor-adjacent liver tissue from 46 patients were analyzed by profiling mutations (targeted sequencing), genome-wide copy number alteration (CNAs), and gene expression.

Results

Somatic mutations and CNAs detected in CLM were similar to reported primary CRC profiles, while CNA profiles of eight metastatic pairs suggested intra-patient divergence. A CMS classifier tool applied to gene expression data, revealed the cohort to be highly enriched for CMS2. Hierarchical clustering of genes with highly variable expression identified two subgroups separated by high or low expression of 55 genes with immune-related and metabolic functions. Importantly, induction of genes and pathways associated with immunogenic cell death (ICD) was identified in metastases exposed to neoadjuvant chemotherapy (NACT).

Conclusions

The uniform classification of CLM by CMS subtyping may indicate that novel class discovery approaches need to be explored to uncover clinically useful stratification of CLM. Detected gene expression signatures support the role of metabolism and chemotherapy in shaping the immune microenvironment of CLM. Furthermore, the results point to rational exploration of immune modulating strategies in CLM, particularly by exploiting NACT-induced ICD.

Integrated analysis of the potential roles of miRNA‑mRNA networks in triple negative breast cancer

Triple negative breast cancer (TNBC) is a type of breast cancer where the tumor cells are negative for the estrogen, progesterone and human epidermal growth factor 2 receptors. To date, expression profiling of microRNA (miRNA/miR) and mRNA sequences have been widely applied for the diagnosis of TNBC. In the present study, an integrated analysis of miRNA‑mRNA profiling arrays was performed. A total of five dysregulated miRNAs in patients with TNBC were identified, including upregulated miR‑558 expression and downregulated miR‑320d‑1, miR‑548v, miR‑99a and miR‑21 expression. In addition, 49 potential target mRNA sequences were identified. Bioinformatics analyses were performed on the identified miRNAs and mRNAs, including gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes pathway and miRNA‑mRNA network analyses. A total of 31 GO terms and three signaling pathways were identified. The results indicated that the differentially expressed miRNAs and their potential target mRNAs may affect the pathogenesis of TNBC, and may therefore be considered as promising biomarkers for the early diagnosis and targeted therapy of patients with TNBC.

Cell cycle related genes up-regulated in human colorectal development predict the overall survival of late-stage colorectal cancer patients

A tumor can be perceived as a special "organ" that undergoes aberrant and poorly regulated organogenesis. Embryonic development and carcinogenesis share striking similarities in their cellular behavior and underlying molecular mechanisms. This intimate association makes embryonic development a viable reference model for studying cancer thereby circumventing the potentially misleading complexity of tumor heterogeneity. Therefore, on the basis of global expression profile, the genes simultaneously activated (up-regulated in terms of expression profile) or suppressed (down-regulated) in both the embryonic development and cancer stage, probably contain profound information on the molecular mechanism of cancer. In this study, the Affymetrix expression profile of 1593 colorectal cancer samples was downloaded from Gene Expression Omnibus. The 1396 differentially expressed probes were robustly obtained using 660 colorectal normal and cancer samples, the expression pattern of which was analyzed using our human colorectal developmental data. All of these 1396 probes were classified into 27 distinct patterns based on their expression patterns during the developmental process. By means of gene set enrichment analysis, we collected 393 V probes simultaneously up-regulated in both development and carcinogenesis and 207 A probes down-regulated in both. Functional enrichment analysis indicated that the V probes were significantly related to cell cycle regulation. Notably, 28 cell-cycle related probes within the V probe group were found to be significantly associated with an overall survival of Stage III/IV patients (GSE17536 cross validation, n = 96, p = 5.70 × 10(-3); GSE29621, n = 36, p = 1.70 × 10(-3); GSE39084, n = 38, p = 0.05; GSE39582, n = 264, p = 0.047; GSE17537, n = 36, p = 5.90 × 10(-3)).

The significance of tumor-associated immune response in molecular taxonomy, prognosis and therapy of colorectal cancer patients

The importance of host immune response in colorectal cancer (CRC) has been constantly revealed through the last 10 years. A number of relevant immune markers have been introduced as prognostic and are now been used alone or in combination with each other in clinical practice. Efforts establishing a worldwide consensus on the implications of immune-profiles in conjunction to other factors are designed in the right direction in order to more effectively categorize patients with CRC in groups that might benefit from currently used or future applied therapies. On the other hand, a number of clinical trials have evolved the application of immunotherapies in patients with CRC both in the adjuvant and palliative setting.

A network-based method for identifying prognostic gene modules in lung squamous carcinoma

Similarities in gene expression between both developing embryonic and precancerous tissues and cancer tissues may help identify much-needed biomarkers and therapeutic targets in lung squamous carcinoma. In this study, human lung samples representing ten successive time points, from embryonic development to carcinogenesis, were used to construct global gene expression profiles. Differentially expressed genes with similar expression in precancerous and cancer samples were identified. Using a network-based greedy searching algorithm to analyze the training cohort (n = 69) and three independent testing cohorts, we successfully identified a significant 22-gene module in which expression levels were correlated with overall survival in lung squamous carcinoma patients.