scholarly journals MicroRNAs Expression Patterns Predict Tumor Mutational Burden in Colorectal Cancer

2021 ◽  
Vol 10 ◽  
Author(s):  
Jiahao Huang ◽  
Haizhou Liu ◽  
Yang Zhao ◽  
Tao Luo ◽  
Jungang Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Mirna Expression ◽  
Checkpoint Inhibitors ◽  
Expression Patterns ◽  
The Cancer Genome Atlas ◽  
Training Set ◽  
Test Set ◽  
Internal Validation ◽  
Mutational Burden ◽  
Tumor Mutational Burden

BackgroundTumor mutational burden (TMB) could be a measure of response to immune checkpoint inhibitors therapy for patients with colorectal cancer (CRC). MicroRNAs (miRNAs) participate in anticancer immune responses. In the present study, we determined miRNA expression patterns in patients with CRC and built a signature that predicts TMB.MethodsNext generation sequencing (NGS) on formalin-fixed paraffin-embedded samples from CRC patients was performed to measure TMB levels. We used datasets from The Cancer Genome Atlas to compare miRNA expression patterns in samples with high and low TMB from patients with CRC. We created an miRNA-based signature index using the selection operator (LASSO) and least absolute shrinkage method from the training set. We used an independent test set as internal validation. We used real-time polymerase chain reaction (RT-PCR) to validate the miRNA-based signature classifier.ResultsTwenty-seven samples from CRC patients underwent NGS to determine the TMB level. We identified four miRNA candidates in the training set for predicting TMB (N = 311). We used the test set (N = 204) for internal validation. The four-miRNA-based signature classifier was an accurate predictor of TMB, with accuracy 0.963 in the training set. In the test set, it was 0.902; and it was 0.946 in the total set. The classifier was superior to microsatellite instability (MSI) for predicting TMB in TCGA dataset. In the validation cohort, MSI status more positively correlated with TMB levels than did the classifier. Validation from RT-qPCR showed good target discrimination of the classifier for TMB prediction.ConclusionTo our knowledge, this is the first miRNA-based signature classifier validated using high quality clinical data to accurately predict TMB level in patients with CRC.

scholarly journals A next-generation sequencing-based strategy combining microsatellite instability and tumor mutation burden for comprehensive molecular diagnosis of advanced colorectal cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jian Xiao ◽  
Wenyun Li ◽  
Yan Huang ◽  
Mengli Huang ◽  
Shanshan Li ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Microsatellite Instability ◽  
Molecular Diagnosis ◽  
Checkpoint Inhibitors ◽  
The Cancer Genome Atlas ◽  
Immune Microenvironment ◽  
Mutational Burden ◽  
Immune Signatures ◽  
Mutation Burden ◽  
Tumor Mutational Burden

Abstract Background Mismatch repair (MMR)/microsatellite instability (MSI) and tumor mutational burden (TMB) are independent biomarkers that complement each other for predicting immune checkpoint inhibitors (ICIs) efficacy. Here we aim to establish a strategy that integrates MSI and TMB determination for colorectal cancer (CRC) in one single assay. Methods Surgical or biopsy specimens retrospectively collected from CRC patients were subjected to NGS analysis. Immunohistochemistry (IHC) and polymerase chain reaction (PCR) were also used to determine MMR/MSI for those having enough tissues. The NGS-MSI method was validated against IHC and PCR. The MSI-high (MSI-H) or microsatellite stable (MSS) groups were further stratified based on tumor mutational burden, followed by validation using the The Cancer Genome Atlas (TCGA) CRC dataset. Immune microenvironment was evaluated for each subgroup be profiling the expression of immune signatures. Results Tissues from 430 CRC patients were analyzed using a 381-gene NGS panel. Alterations in KRAS, NRAS, BRAF, and HER2 occurred at a significantly higher incidence among MSI-H tumors than in MSS patients (83.6% vs. 58.4%, p = 0.0003). A subset comprising 98 tumors were tested for MSI/MMR using all three techniques, where NGS proved to be 99.0 and 93.9% concordant with PCR and IHC, respectively. Four of the 7 IHC-PCR discordant cases had low TMB (1.1–8.1 muts/Mb) and were confirmed to have been misdiagnosed by IHC. Intriguingly, 4 of the 66 MSS tumors (as determined by NGS) were defined as TMB-high (TMB-H) using a cut-off of 29 mut/Mb. Likewise, 15 of the 456 MSS tumors in the TCGA CRC cohort were also TMB-H with a cut-off of 9 muts/Mb. Expression of immune signatures across subgroups (MSS-TMB-H, MSI-H-TMB-H, and MSS-TMB-L) confirmed that the microenvironment of the MSS-TMB-H tumors was similar to that of the MSI-H-TMB-H tumors, but significantly more immune-responsive than that of the MSS-TMB-L tumors, indicating that MSI combined with TMB may be more precise than MSI alone for immune microenvironment prediction. Conclusion This study demonstrated that NGS panel-based method is both robust and tissue-efficient for comprehensive molecular diagnosis of CRC. It also underscores the importance of combining MSI and TMB information for discerning patients with different microenvironment.

scholarly journals MiRNA expression patterns are associated with tumor mutational burden in lung adenocarcinoma

2019 ◽  
Vol 8 (10) ◽  
pp. e1629260
Author(s):  
Yufeng Lv ◽  
Zhong Huang ◽  
Yan Lin ◽  
Yuan Fang ◽  
Zhichao Chen ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Mirna Expression ◽  
Expression Patterns ◽  
Mutational Burden ◽  
Tumor Mutational Burden

scholarly journals miRNA-Based Feature Classifier Is Associated with Tumor Mutational Burden in Head and Neck Squamous Cell Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Yu Xia ◽  
Qi Wang ◽  
Xiaolin Huang ◽  
Xinhai Yin ◽  
Jukun Song ◽  
...  
Keyword(s):  
Mirna Expression ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Immune Checkpoints ◽  
Training Set ◽  
Test Set ◽  
Tumor Mutation Burden ◽  
Mutation Burden

Tumor mutation burden (TMB) is considered to be an independent genetic biomarker that can predict the tumor patient’s response to immune checkpoint inhibitors (ICIs). Meanwhile, microRNA (miRNA) plays a key role in regulating the anticancer immune response. However, the correlation between miRNA expression patterns and TMB is not elucidated in HNSCC. In the HNSCC cohort of the TCGA dataset, miRNAs that were differentially expressed in high TMB and low TMB samples were screened. The least absolute contraction and selection operator (LASSO) method is used to construct a miRNA-based feature classifier to predict the TMB level in the training set. The test set is used to verify the classifier. The correlation between the miRNA-based classifier index and the expression of three immune checkpoints (PD1, PDL1, and CTLA4) was explored. We further perform functional enrichment analysis on the miRNA contained in the miRNA-based feature classifier. Twenty-five differentially expressed miRNAs are used to build miRNA-based feature classifiers to predict TMB levels. The accuracy of the 25-miRNA-based signature classifier is 0.822 in the training set, 0.702 in the test set, and 0.774 in the total set. The miRNA-based feature classifier index showed a low correlation with PD1 and PDL1, but no correlation with CTLA4. The enrichment analysis of these 25 miRNAs shows that they are involved in many immune-related biological processes and cancer-related pathways. The miRNA expression patterns are related to tumor mutation burden, and miRNA-based feature classifiers can be used as biomarkers to predict TMB levels in HNSCC.

scholarly journals Identification and validation of a miRNA-related expression signature for tumor mutational burden in colorectal cancer

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Lijun Xu ◽  
Qing Zheng
Keyword(s):  
Colorectal Cancer ◽  
Immune Response ◽  
Validation Cohort ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Immune Checkpoints ◽  
Positive Correlation ◽  
Expression Signature ◽  
Mutational Burden ◽  
Tumor Mutational Burden

Abstract Background Tumor mutational burden (TMB) is a promising predictor, which could stratify colorectal cancer (CRC) patients based on the response to immune checkpoint inhibitors (ICIs). MicroRNAs (miRNAs) act as the key regulators of anti-cancer immune response. However, the relationship between TMB and miRNA expression profiles is not elucidated in CRC. Methods Differentially expressed miRNAs (DE miRNAs) between the TMBhigh group and the TMBlow group were identified for the CRC cohort of the TCGA database. In the training cohort, a miRNA-related expression signature for predicting TMB level was developed by the least absolute shrinkage and selection operator (LASSO) method and tested with reference to its discrimination, calibration, and decision curve analysis (DCA) in the validation cohort. Functional enrichment analysis of these TMB-related miRNAs was performed. The correlation between this miRNA-related expression signature and three immune checkpoints was analyzed. Results Twenty-one out of 43 DE miRNAs were identified as TMB-related miRNAs, which were used to develop a miRNA-related expression signature. This TMB-related miRNA signature demonstrated great discrimination (AUCtest set = 0.970), satisfactory calibration (P > 0.05), and clinical utility in the validation cohort. Functional enrichment results revealed that these TMB-related miRNAs were mainly involved in biological processes associated with immune response and signaling pathways related with cancer. This miRNA-related expression signature showed a median positive correlation with PD-L1 (R = 0.47, P < 0.05) and CTLA4 (R = 0.39, P < 0.05) and a low positive correlation with PD-1 (R = 0.16, P < 0.05). Conclusion This study presents a miRNA-related expression signature which could stratify CRC patients with different TMB levels.

scholarly journals Left-Sided Colorectal Cancer Distinct in Indigenous African Patients Compared to Other Ethnic Groups in South Africa.

2021 ◽  
Author(s):  
M. McCabe ◽  
C. Penny ◽  
P. Magangane ◽  
S. Mirza ◽  
Y. Perner
Keyword(s):  
Colorectal Cancer ◽  
South Africa ◽  
Ethnic Groups ◽  
Mirna Expression ◽  
Expression Profiling ◽  
Expression Patterns ◽  
Molecular Characteristics ◽  
Anatomical Site ◽  
Molecular Features ◽  
Mirna Expression Profiling

Abstract Introduction: A large proportion of indigenous African (IA) colorectal cancer (CRC) patients in South Africa are young (<50years), with no unique histopathological or molecular characteristics. Anatomical site as well as microsatellite instability (MSI) status have shown to be associated with different clinicopathological and molecular features. This study aimed to ascertain key histopathological and miRNA expression patterns in microsatellite stable (MSS) and low-frequency MSI (MSI-L) patients, to provide insight into the mechanism of the disease. Methods: A retrospective cohort (2011-2015) of MSS/MSI-L CRC patient samples diagnosed at Charlotte Maxeke Johannesburg Academic Hospital was analyzed. Samples were categorized by site [Right colon cancer (RCC) versus left (LCC)], ethnicity [IA versus other ethnic groups (OEG)] and MSI status (MSI-L vs MSS). T-test, Fischer’s exact and Chi-square tests were conducted. Additional miRNA expression profiling was performed on IA patient samples. Results: IA patients with LCC demonstrated an increased prevalence in males, sigmoid colon, signet-ring-cell morphology, MSI-L with BAT25/26 marker instability and advanced disease association. MiRNA expression profiling revealed unique clustering, with dysregulation of let-7 and miRNA-125. Conclusion: This study revealed distinct histopathological features for LCC, and suggests BAT25/26, miRNAs let-7a-5p and miRNA-125a/b-5p as negative prognostic markers in African CRC patients. Larger confirmatory studies are recommended.

scholarly journals Visual Display of 5p-arm and 3p-arm miRNA Expression with a Mobile Application

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Chao-Yu Pan ◽  
Wei-Ting Kuo ◽  
Chien-Yuan Chiu ◽  
Wen-chang Lin
Keyword(s):  
Mirna Expression ◽  
Expression Patterns ◽  
Mirna Gene ◽  
Visual Display ◽  
Mature Mirnas ◽  
Mobile App ◽  
The Cancer Genome Atlas ◽  
Rna Seq ◽  
Cancer Genome Atlas ◽  
User Friendly

MicroRNAs (miRNAs) play important roles in human cancers. In previous studies, we have demonstrated that both 5p-arm and 3p-arm of mature miRNAs could be expressed from the same precursor and we further interrogated the 5p-arm and 3p-arm miRNA expression with a comprehensive arm feature annotation list. To assist biologists to visualize the differential 5p-arm and 3p-arm miRNA expression patterns, we utilized a user-friendly mobile App to display. The Cancer Genome Atlas (TCGA) miRNA-Seq expression information. We have collected over 4,500 miRNA-Seq datasets from 15 TCGA cancer types and further processed them with the 5p-arm and 3p-arm annotation analysis pipeline. In order to be displayed with the RNA-Seq Viewer App, annotated 5p-arm and 3p-arm miRNA expression information and miRNA gene loci information were converted into SQLite tables. In this distinct application, for any given miRNA gene, 5p-arm miRNA is illustrated on the top of chromosome ideogram and 3p-arm miRNA is illustrated on the bottom of chromosome ideogram. Users can then easily interrogate the differentially 5p-arm/3p-arm expressed miRNAs with their mobile devices. This study demonstrates the feasibility and utility of RNA-Seq Viewer App in addition to mRNA-Seq data visualization.

scholarly journals The Resistance Mechanisms of Checkpoint Inhibitors in Solid Tumors

Biomolecules ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 666 ◽  
Author(s):  
Evangelos Koustas ◽  
Panagiotis Sarantis ◽  
Athanasios G. Papavassiliou ◽  
Michalis V. Karamouzis
Keyword(s):  
Solid Tumors ◽  
Checkpoint Inhibitors ◽  
Resistance Mechanisms ◽  
Epigenetic Alterations ◽  
Primary Resistance ◽  
Cellular Processes ◽  
Mutational Burden ◽  
Number Of Patients ◽  
Tumor Mutational Burden

The emergence of cancer immunotherapy has already shown some remarkable results, having changed the treatment strategy in clinical practice for solid tumors. Despite these promising long-term responses, patients seem to lack the ability to respond to immune checkpoint inhibitors, thus demonstrating a primary resistance to immunotherapy. Moreover, a significant number of patients who initially respond to treatment eventually acquire resistance to immunotherapy. Both resistance mechanisms are a result of a complex interaction among different molecules, pathways, and cellular processes. Several resistance mechanisms, such as tumor microenvironment modification, autophagy, genetic and epigenetic alterations, tumor mutational burden, neo-antigens, and modulation of gut microbiota have already been identified, while more continue to be uncovered. In this review, we discuss the latest milestones in the field of immunotherapy, resistance mechanisms against this type of therapy as well as putative therapeutic strategies to overcome resistance in solid tumors.

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