Association of a novel seven-gene expression signature with the disease prognosis in colon cancer patients

METTL3-mediated SMPDL3A promotes cell growth, metastasis and immune process of hepatocellular carcinoma by regulating LRPPRC

BACKGROUND

Methyltransferase-like protein 3 (METTL3) has been confirmed to act as a tumor promoter to regulate hepatocellular carcinoma (HCC) progression. Therefore, more roles and mechanisms of METTL3 in HCC progression deserve to be further revealed.

METHODS

The mRNA and protein levels of METTL3, sphingomyelin phodiesterase acid-like 3 A (SMPDL3A), and leucine rich pentatricopeptide repeat containing (LRPPRC) were determined by qRT-PCR and western blot. Cell proliferation, apoptosis, invasion and migration were detected by CCK8 assay, EdU assay, flow cytometry, transwell assay and wound healing assay. HCC cells were co-cultured with phytohemagglutinin-stimulated peripheral blood mononuclear cells, cytokine-induced killer cells, or CD8 + T-cells. IFN-γ, TNF-α levels, HCC cell survival rate and CD8 + T-cell apoptosis were determined to assess cell immune process. The interaction between METTL3, SMPDL3A and LRPPRC was assessed by MeRIP assay, RIP assay, dual-luciferase reporter assay or Co-IP assay. Animal experiments were performed to evaluate the effect of METTL3 knockdown on HCC tumorigenesis and lung metastasis.

RESULTS

METTL3 was upregulated in HCC tissues and cells, and its knockdown repressed HCC cell proliferation, invasion, migration, immune process and promoted apoptosis. METTL3 increased SMPDL3A mRNA stability by m6A methylation modification, and this modification could be recognized by IGF2BP1. SMPDL3A overexpression reversed the inhibitory effect of METTL3 knockdown on HCC cell growth, metastasis and immune process. SMPDL3A interacted with LRPPRC to positively regulate its expression, and LRPPRC overexpression also eliminated the regulation of SMPDL3A silencing on HCC progression. In addition, downregulation of METTL3 repressed HCC tumorigenesis and lung metastasis via mediating SMPDL3A/LRPPRC axis.

CONCLUSION

METTL3 accelerated HCC cell growth, metastasis and immune process by regulating SMPDL3A/LRPPRC axis, providing a potential target for HCC treatment.

The proton channel OTOP1 is a sensor for the taste of ammonium chloride

Ammonium (NH4+), a breakdown product of amino acids that can be toxic at high levels, is detected by taste systems of organisms ranging from C. elegans to humans and has been used for decades in vertebrate taste research. Here we report that OTOP1, a proton-selective ion channel expressed in sour (Type III) taste receptor cells (TRCs), functions as sensor for ammonium chloride (NH4Cl). Extracellular NH4Cl evoked large dose-dependent inward currents in HEK-293 cells expressing murine OTOP1 (mOTOP1), human OTOP1 and other species variants of OTOP1, that correlated with its ability to alkalinize the cell cytosol. Mutation of a conserved intracellular arginine residue (R292) in the mOTOP1 tm 6-tm 7 linker specifically decreased responses to NH4Cl relative to acid stimuli. Taste responses to NH4Cl measured from isolated Type III TRCs, or gustatory nerves were strongly attenuated or eliminated in an Otop1-/- mouse strain. Behavioral aversion of mice to NH4Cl, reduced in Skn-1a-/- mice lacking Type II TRCs, was entirely abolished in a double knockout with Otop1. These data together reveal an unexpected role for the proton channel OTOP1 in mediating a major component of the taste of NH4Cl and a previously undescribed channel activation mechanism.

Identification of key claudin genes associated with survival prognosis and diagnosis in colon cancer through integrated bioinformatic analysis

The claudin multigene family is associated with various aberrant physiological and cellular signaling pathways. However, the association of claudins with survival prognosis, signaling pathways, and diagnostic efficacy in colon cancer remains poorly understood. Methods: Through the effective utilization of various bioinformatics methods, including differential gene expression analysis, gene set enrichment analysis protein-protein interaction (PPI) network analysis, survival analysis, single sample gene set enrichment analysis (ssGSEA), mutational variance analysis, and identifying receiver operating characteristic curve of claudins in The Cancer Genome Atlas colon adenocarcinoma (COAD). Results: We found that: CLDN2, CLDN1, CLDN14, CLDN16, CLDN18, CLDN9, CLDN12, and CLDN6 are elevated in COAD. In contrast, the CLDN8, CLDN23, CLDN5, CLDN11, CLDN7, and CLDN15 are downregulated in COAD. By analyzing the public datasets GSE15781 and GSE50760 from NCBI-GEO (https://www.ncbi.nlm.nih.gov/geo/), we have confirmed that CLDN1, CLDN2, and CLDN14 are significantly upregulated and CLDN8 and CLDN23 are significantly downregulated in normal colon, colon adenocarcinoma tumor, and liver metastasis of colon adenocarcinoma tissues from human samples. Various claudins are mutated and found to be associated with diagnostic efficacy in COAD. Conclusion: The claudin gene family is associated with prognosis, immune regulation, signaling pathway regulations, and diagnosis of COAD. These findings may provide new molecular insight into claudins in the treatment of colon cancer.

Regulatory network and targeted interventions for CCDC family in tumor pathogenesis

CCDC (coiled-coil domain-containing) is a coiled helix domain that exists in natural proteins. There are about 180 CCDC family genes, encoding proteins that are involved in intercellular transmembrane signal transduction and genetic signal transcription, among other functions. Alterations in expression, mutation, and DNA promoter methylation of CCDC family genes have been shown to be associated with the pathogenesis of many diseases, including primary ciliary dyskinesia, infertility, and tumors. In recent studies, CCDC family genes have been found to be involved in regulation of growth, invasion, metastasis, chemosensitivity, and other biological behaviors of malignant tumor cells in various cancer types, including nasopharyngeal carcinoma, lung cancer, colorectal cancer, and thyroid cancer. In this review, we summarize the involvement of CCDC family genes in tumor pathogenesis and the relevant upstream and downstream molecular mechanisms. In addition, we summarize the potential of CCDC family genes as tumor therapy targets. The findings discussed here help us to further understand the role and the therapeutic applications of CCDC family genes in tumors.

Zinc activation of OTOP proton channels identifies structural elements of the gating apparatus

Otopetrin proteins (OTOPs) form proton-selective ion channels that are expressed in diverse cell types where they mediate detection of acids or regulation of pH. In vertebrates there are three family members: OTOP1 is required for formation of otoconia in the vestibular system and it forms the receptor for sour taste, while the functions of OTOP2 and OTOP3 are not yet known. Importantly, the gating mechanisms of any of the OTOP channels are not well understood. Here, we show that zinc (Zn2+), as well as other transition metals including copper (Cu2+), potently activates murine OTOP3 (mOTOP3). Zn2+ pre-exposure increases the magnitude of mOTOP3 currents to a subsequent acid stimulus by as much as 10-fold. In contrast, mOTOP2 currents are insensitive to activation by Zn2+. Swapping the extracellular tm 11-12 linker between mOTOP3 and mOTOP2 was sufficient to eliminate Zn2+ activation of mOTOP3 and confer Zn2+ activation on mOTOP2. Mutation to alanine of H531 and E535 within the tm 11-12 linker and H234 and E238 within the 5-6 linker reduced or eliminated activation of mOTOP3 by Zn2+, indicating that these residues likely contribute to the Zn2+ activating site. Kinetic modeling of the data is consistent with Zn2+ stabilizing the opn2+en state of the channel, competing with H+ for activation of the channels. These results establish the tm 11-12 and tm 5-6 linkers as part of the gating apparatus of OTOP channels and a target for drug discovery. Zn2+ is an essential micronutrient and its activation of OTOP channels will undoubtedly have important physiological sequelae.

Alterations in Gene Pair Correlations as Potential Diagnostic Markers for Colon Cancer

Colorectal cancer (CRC) is a leading cause of death from cancer in Canada. Early detection of CRC remains crucial in managing disease prognosis and improving patient survival. It can also facilitate prevention, screening, and treatment before the disease progresses to a chronic stage. In this study, we developed a strategy for identifying colon cancer biomarkers from both gene expression and gene pair correlation. Using the RNA-Seq dataset TCGA-COAD, a panel of 71 genes, including the 20 most upregulated genes, 20 most downregulated genes and 31 genes involved in the most significantly altered gene pairs, were selected as potential biomarkers for colon cancer. This signature set of genes could be used for early diagnosis. Furthermore, this strategy could be applied to other types of cancer.

Sphingomyelin Phodiesterase Acid-Like 3A Promotes Hepatocellular Carcinoma Growth Through the Enhancer of Rudimentary Homolog

Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, with unclear pathogenesis. Sphingomyelin phodiesterase acid-like 3A (SMPDL3A) affects cell differentiation and participates in immune regulation. However, its molecular biological function in HCC has not yet been elucidated.

Methods

Data from 180 HCC patients were analyzed the relationship between the expression of SMPDL3A in liver cancer tissues and the prognosis of liver cancer patients. Crispr-Cas9 dual vector lentivirus was used to knock out SMPDL3A in HCC cell lines. The effects of SMPDL3A on cell viability were determined by CCK8 assay, clone formation experiment, cell cycle assay, cell scratch, TUNEL experiment and flow cytometry. Xenograft tumor assays in BALB/c nude mice confirmed that SMPDL3A promoted tumor growth and in vivo. Preliminary exploration of SMPDL3A interacting protein by mass spectrometry analysis and co-immunoprecipitation.

Results

This study showed that the expression of SMPDL3A in HCC tissue differed from that in tumor-adjacent tissues. Moreover, the overall survival rate and tumor-free survival rate of patients with high-SMPDL3A expression were significantly lower than those with low-SMPDL3A expression. SMPDL3A expression was closely related to the level of protein induced by PIVKA-II, liver cirrhosis, tumor diameter, microvascular invasion, and Barcelona clinic liver cancer staging. Thus, SMPDL3A is an independent risk factor that affects the tumor-free survival rate and overall survival rate of HCC patients. In vitro study using Crispr-Cas9 genome editing technology revealed the knockout effect of SMPDL3A on cell proliferation, apoptosis, and migration. Cell counting kit-8 assay and clone formation experiment showed that sgSMPDL3A inhibited tumor cell proliferation and migration. Flow cytometry and TUNEL assay showed that sgSMPDL3A promoted apoptosis in tumors. Moreover, sgSMPDL3A inhibited tumor growth during subcutaneous tumor formation in nude mice. Immunohistochemistry of Ki67 and PNCA also indicated that sgSMPDL3A inhibited subcutaneous tumor proliferation in tumor-bearing nude mice. Further experiments showed that SMPDL3A interacts with the enhancer of rudimentary homolog (ERH).

Conclusions

High-SMPDL3A expression was related to poor prognosis of patients with HCC. Knockout of SMPDL3A inhibited the proliferation and migration and accelerated the migration of HCC cells. SMPDL3A interacted with ERH to affect the tumorigenesis and progression of HCC.

Effect and Prognosis Factors of Combining Laparoscopic Radical Resection of Colon Adenocarcinoma with Docetaxel Therapy in Treating Middle and Advanced Colon Adenocarcinoma

Objective. The aim of the study is to explore the clinical efficacy and prognosis factors of joint application of laparoscopic radical resection of colon adenocarcinoma (COAD) and docetaxel therapy in treating COAD of middle and advanced stages. Methods. The clinical data of 103 COAD patients of middle and advanced stages treated in our hospital from July 2016 to July 2018 were selected for the retrospective analysis, all patients received the treatment scheme of combining laparoscopic radical resection of COAD with docetaxel therapy for the observation of short-term efficacy, follow-up was conducted to record their 3-year survival, and relevant factors affecting patient prognosis were analyzed by the logistic regression model. Results. After treatment, the total remission rate of patients was 75.73% (78/103), the total incidence rate of adverse reactions was 16.50% (17/103); patients’ level values of various serum tumor markers after treatment were significantly lower than those before treatment ( $P<0.001$ ); according to the univariate analysis results, for COAD patients with different tumor diameters, differentiated degrees, TNM stages, perineural invasion degrees, pathological types, and depths of invasion, their modality rates were statistically different ( $P<0.05$ ); and the logistic regression analysis showed that tumor diameter ≥5 cm, poor differentiation, TNM stage IV, perineural invasion, pathologically signet-ring cell carcinoma, and T3-invasion were the independent risk factors affecting patient prognosis ( $P<0.05$ ). Conclusion. Combining laparoscopic radical resection of COAD with docetaxel therapy in treating COAD of middle and advanced stages achieves affirmed short-term efficacy, which can reduce patients’ level of serum tumor markers and ensure high safety and good survival prognosis. Tumor diameter, differentiated degree, TNM stage, perineural invasion, pathological type, and T3-invasion are the relevant factors affecting the prognosis of middle and advanced COAD.

SLC4A4 promotes prostate cancer progression in vivo and in vitro via AKT-mediated signalling pathway

Background

Prostate cancer (PCa) is the second leading cause of cancer-related male deaths worldwide. The purpose of this study was to investigate the effects of homo sapiens solute carrier family 4 member 4 (SLC4A4), which encodes the electrogenic Na+/HCO3− cotransporter isoform 1 (NBCe1), in the development and progression of PCa.

Methods

The expression levels of SLC4A4 in PCa and normal prostate tissues were evaluated by immunohistochemistry. The SLC4A4 knockdown cell model was structured by lentiviral infection, and the knockdown efficiency was validated by RT-qPCR and Western blotting. The effects of SLC4A4 knockdown on cell proliferation, apoptosis and cycle, migration, and invasion were detected by Celigo cell counting assay and CCK-8 assay, flow cytometry analysis, wound-healing, and Transwell assay, respectively. Tumor growth in nude mice was surveyed by in vivo imaging and Ki-67 staining. Furthermore, underlying mechanism of SLC4A4 silence induced inhibition of PCa progression was explored by human phospho-kinase array.

Results

Our results revealed that SLC4A4 expression was up-regulated in PCa tissues and human PCa cell lines. High expression of SLC4A4 in tumor specimens was significantly correlated with disease progression. SLC4A4 knockdown inhibited cell proliferation, migration and invasion, while facilitated apoptosis, which was also confirmed in vivo. Moreover, SLC4A4 promoted PCa progression through the AKT-mediated signalling pathway.

Conclusion

The results of this study indicated that SLC4A4 overexpression was closely associated with the progression of PCa; SLC4A4 knockdown suppressed PCa development in vitro and in vivo. SLC4A4 acts as a tumor promotor in PCa by regulating key components of the AKT pathway and may therefore act as a potential therapeutic target for PCa treatment.

Inferences of carboplatin response-related signature by integrating multiomics data in ovarian serous cystadenocarcinoma

Platinum-based chemotherapy, especially carboplatin, is the primary measure to treat patients with ovarian cancer (OC). However, OC patients still have an adverse prognosis due to emergency of chemotherapy resistance. Ovarian serous cystadenocarcinoma (OSC) is the most common histological subtype of OC. Therefore, identifying the key factors that affect chemotherapy resistance and searching novel treatments had become a top priority. In this study, we analyzed carboplatin response-related mRNA, miRNA, DNA methylation, and alternative splicing (AS) and established a drug-resistant signature for carboplatin in OSC. This drug-resistant signature was obviously higher in resistant group than in non-resistant group and had accuracy predictive performance, which demonstrated that this signature could be considered as a superior indicator for OSC patients with carboplatin resistance. Furthermore, we selected three potential small molecule drugs including liranaftate, siguazodan, and tramiprostate to inhibit carboplatin resistance of OSC. In addition, we also identified ZINC00000205417, ZINC00000140928, and ZINC00021908260 were potential small molecule compounds for SLC17A7 based on Molecular Operating Environment (MOE) virtual screening. Finally, we confirmed the drug-like properties of these small molecule drugs via evaluating absorption, distribution, metabolism, elimination, and toxicity (ADMET) property. In summary, the signature could be used as biomarker for carboplatin resistance and small molecule drugs targeting these genes could improve clinical treatment for OSC in the future.

Machine Learning-Based Identification of Colon Cancer Candidate Diagnostics Genes

Simple Summary

We developed a predictive approach using different machine learning methods to identify a number of genes that can potentially serve as novel diagnostic colon cancer biomarkers.

Abstract

Background: Colorectal cancer (CRC) is the third leading cause of cancer-related death and the fourth most commonly diagnosed cancer worldwide. Due to a lack of diagnostic biomarkers and understanding of the underlying molecular mechanisms, CRC’s mortality rate continues to grow. CRC occurrence and progression are dynamic processes. The expression levels of specific molecules vary at various stages of CRC, rendering its early detection and diagnosis challenging and the need for identifying accurate and meaningful CRC biomarkers more pressing. The advances in high-throughput sequencing technologies have been used to explore novel gene expression, targeted treatments, and colon cancer pathogenesis. Such approaches are routinely being applied and result in large datasets whose analysis is increasingly becoming dependent on machine learning (ML) algorithms that have been demonstrated to be computationally efficient platforms for the identification of variables across such high-dimensional datasets. Methods: We developed a novel ML-based experimental design to study CRC gene associations. Six different machine learning methods were employed as classifiers to identify genes that can be used as diagnostics for CRC using gene expression and clinical datasets. The accuracy, sensitivity, specificity, F1 score, and area under receiver operating characteristic (AUROC) curve were derived to explore the differentially expressed genes (DEGs) for CRC diagnosis. Gene ontology enrichment analyses of these DEGs were performed and predicted gene signatures were linked with miRNAs. Results: We evaluated six machine learning classification methods (Adaboost, ExtraTrees, logistic regression, naïve Bayes classifier, random forest, and XGBoost) across different combinations of training and test datasets over GEO datasets. The accuracy and the AUROC of each combination of training and test data with different algorithms were used as comparison metrics. Random forest (RF) models consistently performed better than other models. In total, 34 genes were identified and used for pathway and gene set enrichment analysis. Further mapping of the 34 genes with miRNA identified interesting miRNA hubs genes. Conclusions: We identified 34 genes with high accuracy that can be used as a diagnostics panel for CRC.

Structural motifs for subtype-specific pH-sensitive gating of vertebrate otopetrin proton channels

Otopetrin (OTOP) channels are proton-selective ion channels conserved among vertebrates and invertebrates, with no structural similarity to other ion channels. There are three vertebrate OTOP channels (OTOP1, OTOP2, and OTOP3), of which one (OTOP1) functions as a sour taste receptor. Whether extracellular protons gate OTOP channels, in addition to permeating them, was not known. Here, we compare the functional properties of the three murine OTOP channels using patch-clamp recording and cytosolic pH microfluorimetry. We find that OTOP1 and OTOP3 are both steeply activated by extracellular protons, with thresholds of pH_o <6.0 and 5.5, respectively, and kinetics that are pH-dependent. In contrast, OTOP2 channels are broadly active over a large pH range (pH 5 pH 10) and carry outward currents in response to extracellular alkalinization (>pH 9.0). Strikingly, we could change the pH-sensitive gating of OTOP2 and OTOP3 channels by swapping extracellular linkers that connect transmembrane domains. Swaps of extracellular linkers in the N domain, comprising transmembrane domains 1-6, tended to change the relative conductance at alkaline pH of chimeric channels, while swaps within the C domain, containing transmembrane domains 7-12, tended to change the rates of OTOP3 current activation. We conclude that members of the OTOP channel family are proton-gated (acid-sensitive) proton channels and that the gating apparatus is distributed across multiple extracellular regions within both the N and C domains of the channels. In addition to the taste system, OTOP channels are expressed in the vertebrate vestibular and digestive systems. The distinct gating properties we describe may allow them to subserve varying cell-type specific functions in these and other biological systems.

Integrative Analysis of Histopathological Images and Genomic Data in Colon Adenocarcinoma

Background

Colon adenocarcinoma (COAD) is one of the most common malignant tumors in the world. The histopathological features are crucial for the diagnosis, prognosis, and therapy of COAD.

Methods

We downloaded 719 whole-slide histopathological images from TCIA, and 459 corresponding HTSeq-counts mRNA expression and clinical data were obtained from TCGA. Histopathological image features were extracted by CellProfiler. Prognostic image features were selected by the least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM) algorithms. The co-expression gene module correlated with prognostic image features was identified by weighted gene co-expression network analysis (WGCNA). Random forest was employed to construct an integrative prognostic model and calculate the histopathological-genomic prognosis factor (HGPF).

Results

There were five prognostic image features and one co-expression gene module involved in the model construction. The time-dependent receiver operating curve showed that the prognostic model had a significant prognostic value. Patients were divided into high-risk group and low-risk group based on the HGPF. Kaplan-Meier analysis indicated that the overall survival of the low-risk group was significantly better than the high-risk group.

Conclusions

These results suggested that the histopathological image features had a certain ability to predict the survival of COAD patients. The integrative prognostic model based on the histopathological images and genomic features could further improve the prognosis prediction in COAD, which may assist the clinical decision in the future.

Prognostic Score Model Based on Ten Differentially Methylated Genes for Predicting Clinical Outcomes in Patients with Adenocarcinoma of the Colon

Purpose

We aimed to screen novel genetic biomarkers for use in a prognostic score (PS) model for the accurate prediction of survival outcomes for patients with colon adenocarcinoma (COAD).

Methods

Gene expression and methylation data were downloaded from The Cancer Genome Atlas database, and the samples were randomly divided into training and validation sets for the screening of differentially methylated genes (DMGs) and differentially expressed genes (DEGs). Co-methylated genes were screened using weighted gene co-expression network analysis. Functional enrichment analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery. Univariate and multivariate Cox regression analyses were performed to identify prognosis-related genes and clinical factors. Receiver operating characteristic curve analysis was carried out to evaluate the predictive performance of the PS model.

Results

In total, 1434 DEGs and 1038 DMGs were screened in the training set, among which 284 were found to be overlapping genes. For 127 of these overlapping genes, the methylation and expression levels were significantly negatively correlated. An optimal signature from 10 DMGs was identified to construct the PS model. Patients with a high PS seemed to have worse outcomes than those with a low PS. Moreover, cancer recurrence and the PS model status were independent prognostic factors.

Conclusion

This PS model based on an optimal 10-gene signature would help in the stratification of patients with COAD and improve the assessment of their clinical outcomes.

Development and Validation of a Random Forest Diagnostic Model of Acute Myocardial Infarction Based on Ferroptosis-Related Genes in Circulating Endothelial Cells

The high incidence and mortality of acute myocardial infarction (MI) drastically threaten human life and health. In the past few decades, the rise of reperfusion therapy has significantly reduced the mortality rate, but the MI diagnosis is still by means of the identification of myocardial injury markers without highly specific biomarkers of microcirculation disorders. Ferroptosis is a novel reported type of programmed cell death, which plays an important role in cancer development. Maintaining iron homeostasis in cells is essential for heart function, and its role in the pathological process of ischemic organ damages remains unclear. Being quickly detected through blood tests, circulating endothelial cells (CECs) have the potential for early judgment of early microcirculation disorders. In order to explore the role of ferroptosis-related genes in the early diagnosis of acute MI, we relied on two data sets from the GEO database to first detect eight ferroptosis-related genes differentially expressed in CECs between the MI and healthy groups in this study. After comparing different supervised learning algorithms, we constructed a random forest diagnosis model for acute MI based on these ferroptosis-related genes with a compelling diagnostic performance in both the validation (AUC = 0.8550) and test set (AUC = 0.7308), respectively. These results suggest that the ferroptosis-related genes might play an important role in the early stage of MI and have the potential as specific diagnostic biomarkers for MI.

A New Oxaliplatin Resistance-Related Gene Signature With Strong Predicting Ability in Colon Cancer Identified by Comprehensive Profiling

Numerous colon cancer cases are resistant to chemotherapy based on oxaliplatin and suffer from relapse. A number of survival- and prognosis-related biomarkers have been identified based on database mining for patients who develop drug resistance, but the single individual gene biomarker cannot attain high specificity and sensitivity in prognosis prediction. This work was conducted aiming to establish a new gene signature using oxaliplatin resistance-related genes to predict the prognosis for colon cancer. To this end, we downloaded gene expression profile data of cell lines that are resistant and not resistant to oxaliplatin from the Gene Expression Omnibus (GEO) database. Altogether, 495 oxaliplatin resistance-related genes were searched by weighted gene co-expression network analysis (WGCNA) and differential expression analysis. As suggested by functional analysis, the above genes were mostly enriched into cell adhesion and immune processes. Besides, a signature was built based on four oxaliplatin resistance-related genes selected from the training set to predict the overall survival (OS) by stepwise regression and least absolute shrinkage and selection operator (LASSO) Cox analysis. Relative to the low risk score group, the high risk score group had dismal OS (P < 0.0001). Moreover, the area under the curve (AUC) value regarding the 5-year OS was 0.72, indicating that the risk score was accurate in the prediction of OS for colon cancer patients (AUC >0.7). Additionally, multivariate Cox regression suggested that the signature constructed based on four oxaliplatin resistance-related genes predicted the prognosis for colon cancer cases [hazard ratio (HR), 2.77; 95% CI, 2.03–3.78; P < 0.001]. Finally, external test sets were utilized to further validate the stability and accuracy of oxaliplatin resistance-related gene signature for prognosis of colon cancer patients. To sum up, this study establishes a signature based on four oxaliplatin resistance-related genes for predicting the survival of colon cancer patients, which sheds more light on the mechanisms of oxaliplatin resistance and helps identify colon cancer cases with a dismal prognostic outcome.

Profiles of alternative splicing events in the diagnosis and prognosis of Gastric Cancer

Background: Gastric cancer (GC) is a heterogeneous disease, and alternative splicing (AS) is a powerful universal transcriptional regulatory mechanism that contributes to the occurrence and development of cancer. However, the systematic analysis of AS events in GC is lacking; therefore, further studies are needed. Methods: Genome-wide analysis of AS events was performed using RNA-Seq data to evaluate the difference between GC and adjacent tissues at the AS level. Prognostic signatures based on differentially expressed alternative splicing (DEAS) events and a correlation network between DEAS and genes were built. Results: We identified 48,141 AS events, of which 2325 showed differential expression patterns. The parental genes before DEAS events play an essential role in regulating GC-related processes such as ribosome (FDR < 0.0001) and thermogenesis (FDR = 0.0002). There were 76 survival-associated DEAS cases. Stratifying patients according to the percent spliced in index value of six types of splicing patterns formed significant Kaplan-Meier curves in the overall survival analysis. A prognostic feature based on DEAS performed well for stratification in patients with GC. Conclusion: The present study will enrich our understanding regarding the distinction of GC and provide a generous amount of biomarkers and potential targets for the treatment of GC.

MMP7 as a potential biomarker of colon cancer and its prognostic value by bioinformatics analysis

ABSTRACT

Colon cancer is one of the most common cancers in the world. To identify the candidate genes in the carcinogenesis and progression of colon cancer, the microarray datasets GSE10950, GSE44861 and GSE74602 were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and functional enrichment analyses were performed. A total of 176 DEGs were identified, consisting of 55 genes upregulated and 121 genes downregulated in colon cancer tissues compared to non-cancerous tissues. The DEGs were mainly enriched in mineral absorption, nitrogen metabolism and complement and coagulation cascades. By using STRING database analysis, we constructed a coexpression network composed of 140 nodes and 280 edges for the DEGs with a combined score >0.4 and a significant interaction relation. Thirteen hub genes were identified, and poor OS of patients was only associated with high expression of Matrix Metallopeptidase 7 (MMP7), which may be involved in the carcinogenesis, invasion or recurrence of colon cancer. In conclusion, we propose that the DEGs and hub genes identified in the present study may be regarded as diagnostic biomarkers for colon cancer. Moreover, the overexpression of MMP7 may correlate with poor prognosis.

Identification of 9-Gene Epithelial-Mesenchymal Transition Related Signature of Osteosarcoma by Integrating Multi Cohorts

BACKGROUND

The prognosis of patients with osteosarcoma is still poor due to the lack of effective prognostic markers. The EMT (epithelial-mesenchymal transition) serves as a promoter in the progression of osteosarcoma. This study systematically analyzed EMT-related genes to explore new markers for predicting the prognosis of osteosarcoma.

METHODS

RNA-Seq data and clinical information were obtained from the GEO database; GSVA and GSEA analysis were used to enrich pathways related to osteosarcoma progression; LASSO method analysis was used to construct the prognosis risk signature. The "Nomogram" package generated the risk prediction nomogram, and its clinical applicability was evaluated by decision curve analysis (DCA).

RESULTS

GSVA and GSEA analysis showed that the EMT signaling pathway was closely related to osteosarcoma progression. A 9-genes signature (LAMA3, LGALS1, SGCG, VEGFA, WNT5A, MATN3, ANPEP, FUCA1, and FLNA) was constructed. The overall survival (OS) of the high-risk scores group was significantly lower than the low-risk scores group. The 9-gene signature demonstrated good predictive accuracy. Cox regression analysis showed that the 9-gene signature provided independent prognostic factors for osteosarcoma patients. In addition, the predictive nomogram model could effectively predict the prognosis of osteosarcoma patients.

CONCLUSION

This study constructed a 9-gene signature as a new prognostic marker to predict osteosarcoma patients' survival.

An Eight-CircRNA Assessment Model for Predicting Biochemical Recurrence in Prostate Cancer

Prostate cancer (PCa) is a high morbidity malignancy in males, and biochemical recurrence (BCR) may appear after the surgery. Our study is designed to build up a risk score model using circular RNA sequencing data for PCa. The dataset is from the GEO database, using a cohort of 144 patients in Canada. We removed the low abundance circRNAs (FPKM < 1) and obtained 546 circRNAs for the next step. BCR-related circRNAs were selected by Logistic regression using the “survival” and “survminer” R package. Least absolute shrinkage and selector operation (LASSO) regression with 10-fold cross-validation and penalty was used to construct a risk score model by “glmnet” R software package. In total, eight circRNAs (including circ_30029, circ_117300, circ_176436, circ_112897, circ_112897, circ_178252, circ_115617, circ_14736, and circ_17720) were involved in our risk score model. Further, we employed differentially expressed mRNAs between high and low risk score groups. The following Gene Ontology (GO) analysis were visualized by Omicshare Online tools. As per the GO analysis results, tumor immune microenvironment related pathways are significantly enriched. “CIBERSORT” and “ESTIMATE” R package were used to detect tumor-infiltrating immune cells and compare the level of microenvironment scores between high and low risk score groups. What’s more, we verified two of eight circRNA’s (circ_14736 and circ_17720) circular characteristics and tested their biological function with qPCR and CCK8 in vitro. circ_14736 and circ_17720 were detected in exosomes of PCa patients’ plasma. This is the first bioinformatics study to establish a prognosis model for prostate cancer using circRNA. These circRNAs were associated with CD8⁺ T cell activities and may serve as a circRNA-based liquid biopsy panel for disease prognosis.

A genomic-clinicopathologic nomogram for predicting overall survival of hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a common digestive tumor with great heterogeneity and different overall survival (OS) time, causing stern problems for selecting optimal treatment. Here we aim to establish a nomogram to predict the OS in HCC patients.

Methods

International Cancer Genome Consortium (ICGC) database was searched for the target information in our study. Lasso regression, univariate and multivariate cox analysis were applied during the analysis process. And a nomogram integrating model scoring and clinical characteristic was drawn.

Results

Six mRNAs were screened out by Lasso regression to make a model for predicting the OS of HCC patients. And this model was proved to be an independent prognostic model predicting OS in HCC patients. The area under the ROC curve (AUC) of this model was 0.803. TCGA database validated the significant value of this 6-mRNA model. Eventually a nomogram including 6-mRNA risk score, gender, age, tumor stage and prior malignancy was set up to predict the OS in HCC patients.

Conclusions

We established an independent prognostic model of predicting OS for 1–3 years in HCC patients, which is available to all populations. And we developed a nomogram on the basis of this model, which could be of great help to precisely individual treatment measures.

Prognostic Value of SLC4A4 and its Correlation with Immune Infiltration in Colon Adenocarcinoma

BACKGROUND SLC4A4 is differentially expressed in a variety of tumors, but its significance in colon adenocarcinoma has not been determined. MATERIAL AND METHODS Transcriptomes of two cohorts, GSE41258 and GSE32323, contained in The Cancer Genome Atlas (TCGA) were analysed to determine differences in SLC4A4 expression between tumor and normal tissue and their correlations with overall survival. The relationships between SLC4A4 expression and clinical characteristics were determined by COX regression analysis and logistic regression analysis, and correlations of SLC4A4 levels with tumor infiltrating immune cells (TIICs) and genes with high mutation frequency were evaluated by Pearson correlation analysis. Molecular functions and signaling pathways that might be affected by changes in SLC4A4 expression were determined by gene set enrichment analysis (GSEA). The overall distribution of TIICs was determined by two web servers: tumor immune estimation resource (TIMER) and CIBERSORT. RESULTS SLC4A4 expression was lower in colon adenocarcinoma than in normal colon tissue, suggesting that SLC4A4 was associated with poor prognosis. Reduced SLC4A4 expression was also associated with lymph node invasion and distant metastasis and was moderately correlated with increased expression of MUC4 and SMAD4, two genes with high mutation frequency in colon adenocarcinoma. GSEA indicated that changes in SLC4A4 expression affects several biological processes, including mismatch repair, base excision repair, and DNA replication. Eight TIICs in the tumor microenvironment differed significantly in groups with low and high expression of SLC4A4. CONCLUSIONS SLC4A4 may be a novel biomarker predicting prognosis in patients with colon adenocarcinoma. TIICs differed significantly in samples with higher and lower expression of SLC4A4.