scholarly journals Role of tumor mutation burden-related signatures in the prognosis and immune microenvironment of pancreatic ductal adenocarcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rong Tang ◽  
Xiaomeng Liu ◽  
Wei Wang ◽  
Jie Hua ◽  
Jin Xu ◽  
...  

Abstract Background High tumor mutation burden (TMB) has gradually become a sensitive biomarker for predicting the response to immunotherapy in many cancers, including lung, bladder and head and neck cancers. However, whether high TMB predicts the response to immunotherapy and prognosis in pancreatic ductal adenocarcinoma (PDAC) remained obscure. Hence, it is significant to investigate the role of genes related to TMB (TRGs) in PDAC. Methods The transcriptome and mutation data of PDAC was downloaded from The Cancer Genome Atlas-Pancreatic Adenocarcinoma (TCGA). Five independent external datasets of PDAC were chosen to validate parts of our results. qRT-PCR and immunohistochemical staining were also performed to promote the reliability of this study. Results The median overall survival (OS) was significantly increased in TMB_low group compared with the counterpart with higher TMB score after tumor purity adjusted (P = 0.03). 718 differentially expressed TRGs were identified and functionally enriched in some oncogenic pathways. 67 TRGs were associated with OS in PDAC. A prognostic model for the OS was constructed and showed a high predictive accuracy (AUC = 0.849). We also found TMB score was associated with multiple immune components and signatures in tumor microenvironment. In addition, we identified a PDAC subgroup featured with TMBlowMicrosatellite instabilityhigh (MSIhigh) was associated with prolonged OS and a key molecule, ANKRD55, potentially mediating the survival benefits. Conclusion This study analyzed the biological function, prognosis value, implications for mutation landscape and potential influence on immune microenvironment of TRGs in PDAC, which contributed to get aware of the role of TMB in PDAC. Future studies are expected to investigate how these TRGs regulate the initiation, development or repression of PDAC.

2021 ◽  
Author(s):  
Rong Tang ◽  
Xiaomeng Liu ◽  
Wei Wang ◽  
Jie Hua ◽  
Jin Xu ◽  
...  

Abstract Background High tumor mutation burden (TMB) has gradually become a sensitive biomarker for predicting the response to immunotherapy in many cancers, including lung, bladder and head and neck cancers. Nonetheless, whether high TMB could predict the response to immunotherapy and prognosis in pancreatic ductal adenocarcinoma (PDAC), a classic “cold” tumor, remained obscure. Hence, it is significant to investigate the role of genes related to TMB (TRGs) in PDAC.Methods The transcriptome and mutation data of PDAC was downloaded from The Cancer Genome Atlas-Pancreatic Adenocarcinoma (TCGA). Five independent external datasets of PDAC were chosen to validate parts of our results. qRT-PCR and immunohistochemical staining were also performed to promote the reliability of this study. Results The median overall survival (OS) was significantly increased in TMB_low group compared with the counterpart with higher TMB score after tumor purity adjusted (P = 0.03). 718 differentially expressed TRGs were identified and functionally enriched in some oncogenic pathways. 67 TRGs were associated with OS in PDAC. A prognostic model for the OS was constructed and showed a high predictive accuracy (AUC = 0.849). We also found TMB score was associated with multiple immune components and signatures in tumor microenvironment. In addition, we identified a PDAC subgroup featured with TMBlowMSIhigh was associated with prolonged OS and a key molecule, ANKRD55, potentially mediating the survival benefits.Conclusion This study analyzed the biological function, prognosis value, implications for mutation landscape and potential influence on immune microenvironment of TRGs in PDAC, which contributed to get aware of the role of TMB in PDAC. Future studies are expected to investigate how these TRGs regulate the initiation, development or repression of PDAC.


Epigenomics ◽  
2020 ◽  
Author(s):  
Qijie Zhao ◽  
Jinan Guo ◽  
Yueshui Zhao ◽  
Jing Shen ◽  
Parham Jabbarzadeh Kaboli ◽  
...  

Background: PD-L1 and PD-L2 are ligands of PD-1. Their overexpression has been reported in different cancers. However, the underlying mechanism of PD-L1 and PD-L2 dysregulation and their related signaling pathways are still unclear in gastrointestinal cancers. Materials & methods: The expression of PD-L1 and PD-L2 were studied in The Cancer Genome Atlas and Genotype-Tissue Expression databases. The gene and protein alteration of PD-L1 and PD-L2 were analyzed in cBioportal. The direct transcription factor regulating PD-L1/ PD-L2 was determined with ChIP-seq data. The association of PD-L1/PD-L2 expression with clinicopathological parameters, survival, immune infiltration and tumor mutation burden were investigated with data from The Cancer Genome Atlas. Potential targets and pathways of PD-L1 and PD-L2 were determined by protein enrichment, WebGestalt and gene ontology. Results: Comprehensive analysis revealed that PD-L1 and PD-L2 were significantly upregulated in most types of gastrointestinal cancers and their expressions were positively correlated. SP1 was a key transcription factor regulating the expression of PD-L1. Conclusion: Higher PD-L1 or PD-L2 expression was significantly associated with poor overall survival, higher tumor mutation burden and more immune and stromal cell populations. Finally, HIF-1, ERBB and mTOR signaling pathways were most significantly affected by PD-L1 and PD-L2 dysregulation. Altogether, this study provided comprehensive analysis of the dysregulation of PD-L1 and PD-L2, its underlying mechanism and downstream pathways, which add to the knowledge of manipulating PD-L1/PD-L2 for cancer immunotherapy.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ritu Pandey ◽  
Muhan Zhou ◽  
Shariful Islam ◽  
Baowei Chen ◽  
Natalie K Barker ◽  
...  

AbstractWe investigated biomarker CEACAM6, a highly abundant cell surface adhesion receptor that modulates the extracellular matrix (ECM) in pancreatic ductal adenocarcinoma (PDA). The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) RNA-Seq data from PDA patients were analyzed for CEACAM6 expression and evaluated for overall survival, association, enrichment and correlations. A CRISPR/Cas9 Knockout (KO) of CEACAM6 in PDA cell line for quantitative proteomics, mitochondrial bioenergetics and tumor growth in mice were conducted. We found CEACAM6 is over-expressed in primary and metastatic basal and classical PDA subtypes. Highest levels are in classical activated stroma subtype. CEACAM6 over-expression is universally a poor prognostic marker in KRAS mutant and wild type PDA. High CEACAM6 expression is associated with low cytolytic T-cell activity in both basal and classical PDA subtypes and correlates with low levels of T-REG markers. In HPAF-II cells knockout of CEACAM6 alters ECM-cell adhesion, catabolism, immune environment, transmembrane transport and autophagy. CEACAM6 loss increases mitochondrial basal and maximal respiratory capacity. HPAF-II CEACAM6−/− cells are growth suppressed by >65% vs. wild type in mice bearing tumors. CEACAM6, a key regulator affects several hallmarks of PDA including the fibrotic reaction, immune regulation, energy metabolism and is a novel therapeutic target in PDA.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Deyu Zhang ◽  
Meiqi Wang ◽  
Lisi Peng ◽  
Xiaoli Yang ◽  
Keliang Li ◽  
...  

Background. With the progress of precision medicine treatment in pancreatic ductal adenocarcinoma (PDAC), individualized cancer-related medical examination and prediction are of great importance in this high malignant tumor and tumor-immune microenvironment with changed pathways highly enrolled in the carcinogenesis of PDAC. Methods. High-throughput data of pancreatic ductal adenocarcinoma were downloaded from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database. After batch normalization, the enrichment pathway and relevant scores were identified by the enrichment of immune-related pathway signature using gene set variation analysis (GSVA). Then, cancerous subtype in TCGA and GEO samples was defined through the NMF methods by cancertypes packages in R software, respectively. Subsequently, the significance between the characteristics of each TCGA sample and cancer type and the significant prognosis-related pathway with risk score formula is calculated through t-test and univariate Cox analysis. Next, the prognostic value of gained risk score formula and each significant prognosis-related pathway were validated in TCGA and GEO samples by survival analysis. The pivotal hub genes in the enriched significant prognosis-related pathway are identified and validated, and the TIMER database was used to identify the potential role of hub genes in the PDAC immune environment. The potential role of hub genes is promoting the transdifferentiation of cancer-associated fibroblasts. Results. The enrichment pathway and relevant scores were identified by GSVA, and 3 subtypes of pancreatic ductal adenocarcinoma were defined in TCGA and GEO samples. The clinical stage, tumor node metastasis classification, and tumor grade are strongly relative to the subtype above in TCGA samples. A risk formula about GSVA significant pathway “GSE45365_WT_VS_IFNAR_KO_CD11B_DC_MCMV_INFECTION_DN ∗ 0.80 + HALLMARK_GLYCOLYSIS ∗ 16.8 + GSE19888_CTRL_VS_T_CELL_MEMBRANES_ACT_MAST_CELL_DN ∗ 14.4” was identified and validated in TCGA and GEO samples through survival analysis with significance. DCN, VCAN, B4GALT7, SDC1, SDC2, B3GALT6, B3GAT3, SDC3, GPC1, and XYLT2 were identified as hub genes in these GSVA significant pathways and validated in silico. Conclusions. Three pancreatic ductal adenocarcinoma subtypes are identified, and an individualized GSVA immune pathway score-related prognostic risk score formula with 10 hub genes is identified and validated. The predicted function of the 10 upregulated hub genes in tumor-immune microenvironment was promoting the infiltration of cancer-associated fibroblasts. These findings will contribute to the precision medicine of pancreatic ductal adenocarcinoma treatment and tumor immune-related basic research.


2020 ◽  
Vol 8 (1) ◽  
pp. e000613
Author(s):  
Nicholas Bevins ◽  
Shulei Sun ◽  
Zied Gaieb ◽  
John A Thorson ◽  
Sarah S Murray

BackgroundTumor mutation burden (TMB) is a biomarker frequently reported by clinical laboratories, which is derived by quantifying of the number of single nucleotide or indel variants (mutations) identified by next-generation sequencing of tumors. TMB values can inform prognosis or predict the response of a patient’s tumor to immune checkpoint inhibitor therapy. Methods for the calculation of TMB are not standardized between laboratories, with significant variables being the gene content of the panels sequenced and the inclusion or exclusion of synonymous variants in the calculations. The impact of these methodological differences has not been investigated and the concordance of reported TMB values between laboratories is unknown.MethodsSequence variant lists from more than 9000 tumors of various types were downloaded from The Cancer Genome Atlas. Variant lists were filtered to include only appropriate variant types (ie, non-synonymous only or synonymous and non-synonymous variants) within the genes found in five commonly used targeted solid tumor gene panels as well as an in-house gene panel. Calculated TMB was paired with corresponding overall survival (OS) data of each patient.ResultsRegression analysis indicates high concordance of TMB as derived from the examined panels. TMB derived from panels was consistently and significantly lower than that derived from a whole exome. TMB, as derived from whole exome or the examined panels, showed a significant correlation with OS in the examined data.ConclusionsTMB derived from the examined gene panels was analytically equivalent between panels, but not between panels and whole-exome sequencing. Correlation between TMB and OS is significant if TMB method-specific cut-offs are used. These results suggest that TMB values, as derived from the gene panels examined, are analytically and prognostically equivalent.


2021 ◽  
Author(s):  
Zaoqu Liu ◽  
Long Liu ◽  
Chunguang Guo ◽  
Libo Wang ◽  
Zhaonan Li ◽  
...  

Abstract BackgroundEsophageal adenocarcinoma (EAC) remains a leading cause of cancer-related deaths worldwide, and demonstrates a predominant rising incidence in Western countries. Recently, immunotherapy has dramatically changed the landscape of treatment for many advanced cancers, the benefit in EAC thus far been limited to a small fraction of patients. MethodsUsing somatic mutations data of The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), we delineated somatic mutation landscape of EAC patients from US and England. Bioinformatics algorithms were utilized to perform function annotation, immune cell infiltration analysis, and immunotherapy response assessment.ResultsWe found that RYR2 was a common frequently mutated gene (FMG) in both cohorts, and patients with RYR2 mutation suggested higher tumor mutation burden (TMB), better prognosis, and superior expression of immune checkpoints. Moreover, RYR2 mutation upregulated the signaling pathways implicated in immune response and enhanced antitumor immunity in EAC. Multiple bioinformatics algorithms for assessing immunotherapy response demonstrated that patients with RYR2 mutation might benefit more from immunotherapy. In order to provide additional reference for antitumor therapy of different RYR2 status, we identified nine latent antitumor drugs associated with RYR2 status in EAC. ConclusionsThis study reveals a novel gene whose mutation could be served as a potential biomarker for prognosis, TMB, and immunotherapy of EAC patients.


Author(s):  
Chunyu Zhang ◽  
Lirui Guo ◽  
Zhongzhou Su ◽  
Na Luo ◽  
Yinqiu Tan ◽  
...  

The tumor immune microenvironment (TIME) has been recognized to be associated with sensitivity to immunotherapy and patient prognosis. Recent research demonstrates that assessing the TIME patterns on large-scale samples will expand insights into TIME and will provide guidance to formulate immunotherapy strategies for tumors. However, until now, thorough research has not yet been reported on the immune infiltration landscape of glioma. Herein, the CIBERSORT algorithm was used to unveil the TIME landscape of 1,975 glioma observations. Three TIME subtypes were established, and the TIMEscore was calculated by least absolute shrinkage and selection operator (LASSO)–Cox analysis. The high TIMEscore was distinguished by an elevated tumor mutation burden (TMB) and activation of immune-related biological process, such as IL6-JAK-STAT3 signaling and interferon gamma (IFN-γ) response, which may demonstrate that the patients with high TIMEscore were more sensitive to immunotherapy. Multivariate analysis revealed that the TIMEscore could strongly and independently predict the prognosis of gliomas [Chinese Glioma Genome Atlas (CGGA) cohort: hazard ratio (HR): 2.134, p < 0.001; Gravendeel cohort: HR: 1.872, p < 0.001; Kamoun cohort: HR: 1.705, p < 0.001; The Cancer Genome Atlas (TCGA) cohort: HR: 2.033, p < 0.001; the combined cohort: HR: 1.626, p < 0.001], and survival advantage was evident among those who received chemotherapy. Finally, we validated the performance of the signature in human tissues from Wuhan University (WHU) dataset (HR: 15.090, p = 0.008). Our research suggested that the TIMEscore could be applied as an effective predictor for adjuvant therapy and prognosis assessment.


2021 ◽  
Vol 19 (3) ◽  
pp. 247-252
Author(s):  
Robert J. Besaw ◽  
Adrienne R. Terra ◽  
Grace L. Malvar ◽  
Tobias R. Chapman ◽  
Lauren M. Hertan ◽  
...  

Undifferentiated carcinoma with osteoclast-like giant cells (UCOGC) of the pancreas is a rare and potentially aggressive variant of pancreatic ductal adenocarcinoma. Data on this disease are sparse, and despite genetic similarities to pancreatic ductal adenocarcinoma, UCOGC clinical outcomes can be markedly different. We report on a female patient aged 62 years who presented with UCOGC with pulmonary metastases initially treated with 2 lines of cytotoxic chemotherapy. After rapid disease progression with both cytotoxic treatments, the patient’s tissue was sent for next-generation sequencing, which revealed a high tumor mutation burden (32 mutations per megabase), as well as somatic mutations in BRAF, NF1, PIK3CA, CDKN2A, TERT, and TP53. Pancreatic cancers have previously demonstrated suboptimal responses to immunotherapeutic approaches. However, given the high tumor mutation burden and distinctiveness of the tumor class, the patient began third-line pembrolizumab monotherapy after palliative radiation to the rapidly progressing and painful abdominal mass from her primary tumor. She had a marked response in her primary UCOGC tumor and metastatic sites, and she remains on pembrolizumab monotherapy with ongoing response after 32 months of therapy. Recent evidence showing significant PD-L1 enrichment on neoplastic cells of undifferentiated carcinomas (including UCOGC) may indicate a role for immunotherapeutic approaches in these patients. Rare cancers such as UCOGC and other undifferentiated carcinomas may benefit from next-generation sequencing to inform treatment decisions when standards of care are absent, as in this report.


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