Identification of a Genome Instability-Associated LncRNA Signature for Prognosis Prediction in Colon Cancer

Long non-coding RNAs (lncRNAs) were reported to have the potential in maintaining genome instability, but the identification of lncRNAs related to genome instability and their prognostic value have not been largely explored in colon cancer. In this study, we obtained 155 genome instability-associated lncRNAs based on somatic mutation profiles in colon cancer from The Cancer Genome Atlas (TCGA) database. Functional enrichment analysis revealed the possible roles of genes co-expressed with those lncRNAs involved in some cancer, genome instability and immune related biological processes. Combined with overall survival data, a seven-lncRNA signature was established for prognosis prediction. According to the risk score calculated by this signature, high-risk patients characterized by high somatic mutation count, high microsatellite instability, significantly poorer clinical outcomes and specific tumor immune infiltration status compared with low-risk patients. The lncRNA signature was validated to be an independent prognostic indicator with good predictive performance in TCGA cohort. Furthermore, the prognostic value of the ZNF503-AS1 in lncRNA signature was confirmed in another independent dataset from Gene Expression Omnibus database. In summary, the genome instability-associated lncRNA signature in this study could be a promising tool for effectively predicting survival outcomes in colon cancer.

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Identification of a Four-lncRNA Prognostic Signature for Colon Cancer Based on Genome Instability

Journal of Oncology ◽

10.1155/2021/7408893 ◽

2021 ◽

Vol 2021 ◽

pp. 1-18

Author(s):

Duo Yun ◽

Zhirong Yang

Keyword(s):

Colon Cancer ◽

Somatic Mutation ◽

Genome Instability ◽

Noncoding Rnas ◽

Cancer Biomarkers ◽

Risk Groups ◽

Mutation Rates ◽

Risk Scores ◽

Prognostic Signature ◽

A Genome

LncRNAs (long noncoding RNAs) are closely associated with genome instability. However, the identification of lncRNAs related to the genome instability and their relationship with the prognosis and clinical signature of cancer remains to be explored. In this paper, we analyzed differential lncRNA expression based on the somatic mutation profiles of colon cancer patients from TCGA database and finally identified 153 lncRNAs that are associated with genome instability in colon cancer. Taking four lncRNAs from these 153, we established a genome-instability-related prognostic signature (GIRlncPSig). By applying the GIRlncPSig, we calculated a risk score for each patient, and using their risk scores, we divided them into low- and high-risk groups. We found that the prognosis between the two risk groups was significantly different, and the results were further verified in different independent patient cohorts. Moreover, we observed that the GIRlncPSig was related to somatic mutation rates in colon cancer, indicating that it may be a potential means of measuring genome instability levels in colon cancer. We also revealed that the GIRlncPSig was correlated with BRAF and DPYD mutation rates and that it may be a potential mutation marker for the BRAF and DPYD gene. In summary, we constructed a genome-instability-related lncRNA prognostic signature (GIRlncPSig), which has a significant effect on prognosis prediction and may allow for the discovery of new colon cancer biomarkers.

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Long Noncoding RNA Expression Signatures of Colon Cancer Based on the ceRNA Network and Their Prognostic Value

Disease Markers ◽

10.1155/2019/7636757 ◽

2019 ◽

Vol 2019 ◽

pp. 1-13 ◽

Cited By ~ 4

Author(s):

Yang Cheng ◽

Lanlan Geng ◽

Kunyuan Wang ◽

Jingjing Sun ◽

Wanfu Xu ◽

...

Keyword(s):

Colon Cancer ◽

Survival Analysis ◽

Noncoding Rna ◽

Prognostic Value ◽

Expression Profiles ◽

Computational Method ◽

Functional Enrichment ◽

Gene Knockdown ◽

Cerna Network ◽

A Genome

Background. The specific functional roles of long noncoding RNAs (lncRNAs) as ceRNAs in colon cancer and their potential implications for colon cancer prognosis remain unclear. In the present study, a genome-wide analysis was performed to investigate the potential lncRNA-mediated ceRNA interplay in colon cancer based on the “ceRNA hypothesis.” The prognostic value of the lncRNAs was evaluated. Methods. A dysregulated lncRNA-associated ceRNA network was constructed based on the miRNA, lncRNA, and mRNA expression profiles in combination with the miRNA regulatory network by using an integrative computational method. Molecular biological techniques, including qPCR and gene knockdown techniques, were used to verify candidate targets in colon cancer. Survival analysis was performed to identify the candidate lncRNAs with prognostic value. Results. Our network analysis uncovered several novel lncRNAs as functional ceRNAs through crosstalk with miRNAs. The QRT-PCR assays of patient tissues as well as gene knockdown colon cancer cells confirmed the expression of top lncRNAs and their correlation with target genes in the ceRNA network. Functional enrichment analysis predicted that differentially expressed lncRNAs might participate in broad biological functions associated with tumor progression. Moreover, these lncRNAs may be involved in a range of cellular pathways, including the apoptosis, PI3K-AKT, and EGFR signaling pathways. The survival analysis showed that the expression level of several lncRNAs in the network was correlated with the prognosis of patients with colon cancer. Conclusions. This study uncovered a dysregulated lncRNA-associated ceRNA network in colon cancer. The function of the identified lncRNAs in colon cancer was preliminarily explored, and their potential prognostic value was evaluated. Our study demonstrated that lncRNAs could potentially serve as important regulators in the development and progression of colon cancer. Candidate prognostic lncRNA biomarkers in colon cancer were identified.

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Exceptional Chemotherapy Response in Metastatic Colorectal Cancer Associated With Hyper-Indel–Hypermutated Cancer Genome and Comutation of POLD1 and MLH1

JCO Precision Oncology ◽

10.1200/po.16.00015 ◽

2017 ◽

pp. 1-12

Author(s):

Manish R. Sharma ◽

James T. Auman ◽

Nirali M. Patel ◽

Juneko E. Grilley-Olson ◽

Xiaobei Zhao ◽

...

Keyword(s):

Colorectal Cancer ◽

Colon Cancer ◽

Somatic Mutation ◽

Mutation Rate ◽

Germ Line ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Response To Chemotherapy ◽

Cancer Genome Atlas ◽

Genome Atlas

Purpose A 73-year-old woman with metastatic colon cancer experienced a complete response to chemotherapy with dose-intensified irinotecan that has been durable for 5 years. We sequenced her tumor and germ line DNA and looked for similar patterns in publicly available genomic data from patients with colorectal cancer. Patients and Methods Tumor DNA was obtained from a biopsy before therapy, and germ line DNA was obtained from blood. Tumor and germline DNA were sequenced using a commercial panel with approximately 250 genes. Whole-genome amplification and exome sequencing were performed for POLE and POLD1. A POLD1 mutation was confirmed by Sanger sequencing. The somatic mutation and clinical annotation data files from the colon (n = 461) and rectal (n = 171) adenocarcinoma data sets were downloaded from The Cancer Genome Atlas data portal and analyzed for patterns of mutations and clinical outcomes in patients with POLE- and/or POLD1-mutated tumors. Results The pattern of alterations included APC biallelic inactivation and microsatellite instability high (MSI-H) phenotype, with somatic inactivation of MLH1 and hypermutation (estimated mutation rate > 200 per megabase). The extremely high mutation rate led us to investigate additional mechanisms for hypermutation, including loss of function of POLE. POLE was unaltered, but a related gene not typically associated with somatic mutation in colon cancer, POLD1, had a somatic mutation c.2171G>A [p.Gly724Glu]. Additionally, we noted that the high mutation rate was largely composed of dinucleotide deletions. A similar pattern of hypermutation (dinucleotide deletions, POLD1 mutations, MSI-H) was found in tumors from The Cancer Genome Atlas. Conclusion POLD1 mutation with associated MSI-H and hyper-indel–hypermutated cancer genome characterizes a previously unrecognized variant of colon cancer that was found in this patient with an exceptional response to chemotherapy.

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Construction of a long noncoding RNA-based competing endogenous RNA network and prognostic signatures of left- and right-side colon cancer

Cancer Cell International ◽

10.1186/s12935-021-01901-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Ke-zhi Li ◽

Yi-xin Yin ◽

Yan-ping Tang ◽

Long Long ◽

Ming-zhi Xie ◽

...

Keyword(s):

Colon Cancer ◽

Prognostic Value ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Molecular Characteristics ◽

Prognostic Signature ◽

Cerna Network ◽

Colon Cancers ◽

Cancer Tissues

Abstract Background Cancers located on the right and left sides of the colon have distinct clinical and molecular characteristics. This study aimed to explore the regulatory mechanisms of location-specific long noncoding RNAs (lncRNAs) as competing endogenous RNAs (ceRNAs) in colon cancer and identify potential prognostic biomarkers. Method Differentially expressed lncRNAs (DELs), miRNAs (DEMs), and genes (DEGs) between right- and left-side colon cancers were identified by comparing RNA sequencing profiles. Functional enrichment analysis was performed for the DEGs, and a ceRNA network was constructed. Associations between DELs and patient survival were examined, and a DEL-based signature was constructed to examine the prognostic value of these differences. Clinical colon cancer tissues and Gene Expression Omnibus (GEO) datasets were used to validate the results. Results We identified 376 DELs, 35 DEMs, and 805 DEGs between right- and left-side colon cancers. The functional enrichment analysis revealed the functions and pathway involvement of DEGs. A ceRNA network was constructed based on 95 DEL–DEM–DEG interactions. Three DELs (LINC01555, AC015712, and FZD10-AS1) were associated with the overall survival of patients with colon cancer, and a prognostic signature was established based on these three DELs. High risk scores for this signature indicated poor survival, suggesting that the signature has prognostic value for colon cancer. Examination of clinical colon cancer tissues and GEO dataset analysis confirmed the results. Conclusion The ceRNA regulatory network suggests roles for location-specific lncRNAs in colon cancer and allowed the development of an lncRNA-based prognostic signature, which could be used to assess prognosis and determine treatment strategies in patients with colon cancer.

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Identification of the Prognostic Significance of Somatic Mutation-Derived LncRNA Signatures of Genomic Instability in Lung Adenocarcinoma

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.657667 ◽

2021 ◽

Vol 9 ◽

Author(s):

Wei Geng ◽

Zhilei Lv ◽

Jinshuo Fan ◽

Juanjuan Xu ◽

Kaimin Mao ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Genomic Instability ◽

Somatic Mutation ◽

Cox Regression ◽

Genome Instability ◽

External Validation ◽

Prognostic Significance ◽

Tumor Stage ◽

Lasso Regression ◽

A Genome

Background: Lung adenocarcinoma (LUAD) is a highly heterogeneous tumor with substantial somatic mutations and genome instability, which are emerging hallmarks of cancer. Long non-coding RNAs (lncRNAs) are promising cancer biomarkers that are reportedly involved in genomic instability. However, the identification of genome instability-related lncRNAs (GInLncRNAs) and their clinical significance has not been investigated in LUAD.Methods: We determined GInLncRNAs by combining somatic mutation and transcriptome data of 457 patients with LUAD and probed their potential function using co-expression network and Gene Ontology (GO) enrichment analyses. We then filtered GInLncRNAs by Cox regression and LASSO regression to construct a genome instability-related lncRNA signature (GInLncSig). We subsequently evaluated GInLncSig using correlation analyses with mutations, external validation, model comparisons, independent prognostic significance analyses, and clinical stratification analyses. Finally, we established a nomogram for prognosis prediction in patients with LUAD and validated it in the testing set and the entire TCGA dataset.Results: We identified 161 GInLncRNAs, of which seven were screened to develop a prognostic GInLncSig model (LINC01133, LINC01116, LINC01671, FAM83A-AS1, PLAC4, MIR223HG, and AL590226.1). GInLncSig independently predicted the overall survival of patients with LUAD and displayed an improved performance compared to other similar signatures. Furthermore, GInLncSig was related to somatic mutation patterns, suggesting its ability to reflect genome instability in LUAD. Finally, a nomogram comprising the GInLncSig and tumor stage exhibited improved robustness and clinical practicability for predicting patient prognosis.Conclusion: Our study identified a signature for prognostic prediction in LUAD comprising seven lncRNAs associated with genome instability, which may provide a useful indicator for clinical stratification management and treatment decisions for patients with LUAD.

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KPNA4 Serves as A Biomarker For Pancreatic Adnenocarcinoma KPNA4 Serves as A Promising Diagnostic and Prognostic Biomarker For Human Pancreatic Adenocarcinoma

10.21203/rs.3.rs-151398/v1 ◽

2021 ◽

Author(s):

Yuqian Zhou ◽

HongYi Zhu ◽

Yi Chu ◽

Min Luo ◽

WenYu Li ◽

...

Keyword(s):

Pancreatic Adenocarcinoma ◽

Survival Data ◽

Prognostic Value ◽

Expression Patterns ◽

Adherens Junction ◽

Tumor Stage ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Aberrant Expression ◽

Value Analysis

Abstract Objectives: Growing evidence suggests that aberrant expression of Karyopherin alpha (KPNA) has been involved in the tumor progression of various cancer types. However, the differential expression patterns and prognostic value of the seven KPNA subtypes remain to be investigated. Hence the transcriptional and survival data of KPNAs in patients with pancreatic adenocarcinoma (PAAD) were analyzed.Methods: Transcriptional and survival data related to KPNA expression in patients with PAAD were derived through ONCOMINE, Gene Expression Profiling Interactive Analysis 2, and Human protein atlas databases. The DNA alteration for KPNAs came from The Cancer Genome Atlas and c-BioPortal. The prognostic value analysis was performed with Kaplan–Meier Plotter. Gene functional enrichment analyses were conducted in database LinkedOmics and Metascape.Results: The mRNA expression levels of KPNA1-4, 6,7 were found significantly upregulated in pancreatic cancer tissues than in normal pancreas tissues, whereas the aberrant expression level of KPNA5 was no more significant in the former than in the latter. KPNA1, 4, and 7 were associated with tumor stage or grade of PAAD. Nevertheless, the obvious association with clinical outcomes was identified only in the aberrant expression of KPNA4. Further gene functional exploration about KPNA4 displayed KPNA4 strongly associated with adherens junction and tumor metastasis in PAAD. Conclusion: Our findings suggested that KPNA4 might be a potential diagnostic and a new biomarker of prognosis for patients with pancreatic adenocarcinoma.

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Comprehensive analysis of metastasis-related genes reveals a gene signature predicting the survival of colon cancer patients

PeerJ ◽

10.7717/peerj.5433 ◽

2018 ◽

Vol 6 ◽

pp. e5433 ◽

Cited By ~ 2

Author(s):

Haotang Wei ◽

Jilin Li ◽

Minzhi Xie ◽

Ronger Lei ◽

Bangli Hu

Keyword(s):

Colon Cancer ◽

Cancer Patients ◽

Prognostic Value ◽

Validation Cohort ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Gene Signature ◽

Functional Enrichment ◽

Training Cohort ◽

Six Genes

Objective The mechanism underlying colon cancer metastasis remain unclear. This study aimed to elucidate the genes alteration during the metastasis of colon cancer and identify genes that crucial to the metastasis and survival of colon cancer patients. Methods The dataset of primary and metastasis tissue of colon cancer, and dataset of high and low metastasis capability of colon cancer cells were selected as training cohort, and the overlapped differentially expressed genes (DEGs) were screened from the training cohort. The functional enrichment analysis for the overlapped DEGs was performed. The prognostic value of overlapped DEGs were analyzed in The Cancer Genome Atlas dataset, and a gene signature was developed using genes that related to the overall survival (OS). The prognostic value of the gene signature was further confirmed in a validation cohort. Results A total of 184 overlapped DEGs were screened from the training cohort. Functional enrichment analysis revealed the significant gene functions and pathways of the overlapped DEGs. Four hub genes (3-oxoacid CoA-transferase 1, actinin alpha 4, interleukin 8, integrin subunit alpha 3) were identified using protein–protein network analysis. Six genes (aldehyde dehydrogenase 2, neural precursor cell expressed, developmentally down-regulated 9, filamin A, lamin B receptor, twinfilin actin binding protein 1, serine and arginine rich splicing factor 1) were closely related to the OS of colon cancer patients. A gene signature was developed using these six genes based on their risk score, and the validation cohort indicated that the prognostic value of this gene signature was high in the prediction of colon cancer patients. Conclusions Our study demonstrates a gene profiles related to the metastasis of colon cancer, and identify a six-gene signature that acts as an independent biomarker on the prognosis of colon cancer.

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Comprehensive analysis of the expression of SLC30A family genes and prognosis in human gastric cancer

Scientific Reports ◽

10.1038/s41598-020-75012-w ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Yongdong Guo ◽

Yutong He

Keyword(s):

Gastric Cancer ◽

Immune Cells ◽

Survival Data ◽

Prognostic Value ◽

Expression Patterns ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Human Gastric Cancer ◽

Advanced Tumor Stage ◽

Advanced Tumor

Abstract The solute carrier 30 (SLC30) family genes play a fundamental role in various cancers. However, the diverse expression patterns, prognostic value, and potential mechanism of SLC30A family genes in gastric cancer (GC) remain unknown. Herein, we analyzed the expression and survival data of SLC30A family genes in GC patients using multiple bioinformatic approaches. Expression data of SLC30A family genes for GC patients were extracted from the Cancer Genome Atlas (TCGA) and genetic alteration frequency assessed by using cBioportal database. And validated the expression of SLC30A family genes in GC tissues and corresponding normal tissues. The prognostic value of SLC30A family genes in gastric cancer patients were explored using Kaplan–Meier plotter database. Functional enrichment analysis performed using DAVID database and clusterProfiler package. And ssGSEA algorithm was performed to explore the relationship between the SLC30A family genes and the infiltration of immune cells. We found that the median expression levels of SLC30A1-3, 5–7, and 9 were significantly upregulated in gastric cancer tissues compared to non-cancerous tissues, while SLC30A4 was downregulated. Meanwhile, SLC30A1-7, and 9 were significantly correlated with advanced tumor stage and nodal metastasis status, SLC30A5-7, and 9–10 were significantly related to the Helicobacter pylori infection status of GC patients. High expression of five genes (SLC30A1, 5–7, and 9) was significantly correlated with better overall survival (OS), first progression survival (FPS), and post progression survival (PPS). Conversely, upregulated SLC30A2-4, 8, and 10 expression was markedly associated with poor OS, FP and PPS. And SLC30A family genes were closely associated with the infiltration of immune cells. The present study implied that SLC30A5 and 7 may be potential biomarkers for predicting prognosis in GC patients, SLC30A2 and 3 play an oncogenic role in GC patients and could provide a new strategy for GC patients treatment.

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Sampling strategies to evaluate the prognostic value of a new biomarker on a time-to-event end-point

BMC Medical Research Methodology ◽

10.1186/s12874-021-01283-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Francesca Graziano ◽

Maria Grazia Valsecchi ◽

Paola Rebora

Keyword(s):

Survival Data ◽

Prognostic Value ◽

Cox Model ◽

Lymphoblastic Leukemia ◽

Fixed Ratio ◽

Case Control ◽

Time To Event ◽

Full Cohort ◽

Number Of Patients ◽

Nested Case Control

Abstract Background The availability of large epidemiological or clinical data storing biological samples allow to study the prognostic value of novel biomarkers, but efficient designs are needed to select a subsample on which to measure them, for parsimony and economical reasons. Two-phase stratified sampling is a flexible approach to perform such sub-sampling, but literature on stratification variables to be used in the sampling and power evaluation is lacking especially for survival data. Methods We compared the performance of different sampling designs to assess the prognostic value of a new biomarker on a time-to-event endpoint, applying a Cox model weighted by the inverse of the empirical inclusion probability. Results Our simulation results suggest that case-control stratified (or post stratified) by a surrogate variable of the marker can yield higher performances than simple random, probability proportional to size, and case-control sampling. In the presence of high censoring rate, results showed an advantage of nested case-control and counter-matching designs in term of design effect, although the use of a fixed ratio between cases and controls might be disadvantageous. On real data on childhood acute lymphoblastic leukemia, we found that optimal sampling using pilot data is greatly efficient. Conclusions Our study suggests that, in our sample, case-control stratified by surrogate and nested case-control yield estimates and power comparable to estimates obtained in the full cohort while strongly decreasing the number of patients required. We recommend to plan the sample size and using sampling designs for exploration of novel biomarker in clinical cohort data.

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CCTs as new biomarkers for the prognosis of head and neck squamous cancer

Open Medicine ◽

10.1515/med-2020-0114 ◽

2020 ◽

Vol 15 (1) ◽

pp. 672-688

Author(s):

Yanbo Dong ◽

Siyu Lu ◽

Zhenxiao Wang ◽

Liangfa Liu

Keyword(s):

Head And Neck ◽

Survival Data ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Advanced Tumor Stage ◽

Expression Levels ◽

T Complex ◽

Advanced Tumor ◽

Squamous Cancer

AbstractThe chaperonin-containing T-complex protein 1 (CCT) subunits participate in diverse diseases. However, little is known about their expression and prognostic values in human head and neck squamous cancer (HNSC). This article aims to evaluate the effects of CCT subunits regarding their prognostic values for HNSC. We mined the transcriptional and survival data of CCTs in HNSC patients from online databases. A protein–protein interaction network was constructed and a functional enrichment analysis of target genes was performed. We observed that the mRNA expression levels of CCT1/2/3/4/5/6/7/8 were higher in HNSC tissues than in normal tissues. Survival analysis revealed that the high mRNA transcriptional levels of CCT3/4/5/6/7/8 were associated with a low overall survival. The expression levels of CCT4/7 were correlated with advanced tumor stage. And the overexpression of CCT4 was associated with higher N stage of patients. Validation of CCTs’ differential expression and prognostic values was achieved by the Human Protein Atlas and GEO datasets. Mechanistic exploration of CCT subunits by the functional enrichment analysis suggests that these genes may influence the HNSC prognosis by regulating PI3K-Akt and other pathways. This study implies that CCT3/4/6/7/8 are promising biomarkers for the prognosis of HNSC.

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