scholarly journals Identification of N6-Methyladenosine-Associated Long Non-coding RNAs for Immunotherapeutic Response and Prognosis in Patients With Pancreatic Cancer

Author(s):  
Xinshuang Yu ◽  
Peng Dong ◽  
Yu Yan ◽  
Fengjun Liu ◽  
Hui Wang ◽  
...  

Pancreatic cancer is a highly aggressive disease with poor prognosis. N6-methyladenosine (m6A) is critical for post-transcriptional modification of messenger RNA (mRNA) and long non-coding RNA (lncRNA). However, the m6A-associated lncRNAs (m6A-lncRNA) and their values in predicting clinical outcomes and immune microenvironmental status in pancreatic cancer patients remain largely unexplored. This study aimed to evaluate the importance of m6A-lncRNA and established a m6A-lncRNA signature for predicting immunotherapeutic response and prognosis of pancreatic cancer. The m6A-lncRNA co-expression networks were constructed using data from the TCGA and GTEx database. Based on the least absolute shrinkage and selection operator (LASSO) analysis, we constructed an 8 m6A-lncRNA signature risk model, and selection operator (LASSO) analysis, and stratified patients into the high- and low-risk groups with significant difference in overall survival (OS) (HR = 2.68, 95% CI = 1.74–4.14, P < 0.0001). Patients in the high-risk group showed significantly reduced OS compared to patients in the low-risk group (P < 0.001). The clinical characteristics and m6A-lncRNA risk scores were used to construct a nomogram which accurately predicted the OS in pancreatic cancer. TIMER 2.0 were used to investigate tumor immune infiltrating cells and its relationship with pancreatic cancer. CIBERSORT analysis revealed increased higher infiltration proportions of M0 and M2 macrophages, and lower infiltration of naive B cell, CD8+ T cell and Treg cells in the high-risk group. Compared to the low-risk group, functional annotation using ssGSEA showed that T cell infiltration and the differential immune-related check-point genes are expressed at low level in the high-risk group (P < 0.05). In summary, our study constructed a novel m6A-associated lncRNAs signature to predict immunotherapeutic responses and provided a novel nomogram for the prognosis prediction of pancreatic cancer.

2021 ◽  
Author(s):  
Chen-jie Qiu ◽  
Xue-bing Wang ◽  
Zi-ruo Zheng ◽  
Chao-zhi Yang ◽  
Kai Lin ◽  
...  

Abstract Background: The purpose of this study was to identify ferroptosis-related genes (FRGs) associated with the prognosis of pancreatic cancer and to construct a prognostic model based on FRGs. Methods: Based on pancreatic cancer data obtained from The Cancer Genome Atlas database, we established the prognostic model from 232 FRGs. A nomogram was constructed by combining the prognostic model and clinicopathological features. Gene Expression Omnibus datasets and tissue samples obtained from our center were utilized to validate the model. Relationship between risk score and immune cell infiltration was explored by CIBERSORT and TIMER.Results: The prognostic model was established based on four FRGs (ENPP2, ATG4D, SLC2A1 and MAP3K5) and can be an independent risk factor in pancreatic cancer (HR 1.648, 95% CI 1.335-2.035, p < 0.001). Based on the median risk score, patients were divided into a high-risk group and a low-risk group. The prognosis of the low-risk group was significantly better than that of the high-risk group. In the high-risk group, patients treated with chemotherapy had a better prognosis. The nomogram showed that the model was the most important element. Gene set enrichment analysis identified three key pathways, namely, TGFβ signaling, HIF signaling pathway and adherens junction. The prognostic model can also affect the immune cell infiltration, such as macrophages M0, M1, CD4+T cell and CD8+T cell. Conclusion: A ferroptosis-related prognostic model can be employed to predict the prognosis of pancreatic cancer. Ferroptosis can be an important marker and immunotherapy can be a potential therapeutic target for pancreatic cancer.


2021 ◽  
Author(s):  
Peng-wei Cao ◽  
Lei Liu ◽  
Zi-Han Li ◽  
Feng Cao ◽  
Fu-Bao Liu

Abstract Background: The role of N6-methyladenosine (m6A)-associated long-stranded non-coding RNA (lncRNA) in pancreatic cancer is unclear. Therefore, we analysed the characteristics and tumour microenvironment in pancreatic cancer and determined the value of m6A-related lncRNAs for prognosis and drug target prediction.Methods: An m6A-lncRNA co-expression network was constructed using The Cancer Genome Atlas database to screen m6A-related lncRNAs. Prognosis-related lncRNAs were screened using univariate Cox regression; patients were divided into high- and low-risk groups and randomised into training and test groups. In the training group, least absolute shrinkage and selection operator (LASSO) was used for regression analysis and to construct a prognostic model, which was validated in the test group. Tumour mutational burden (TMB), immune evasion, and immune function of risk genes were analysed using R; drug sensitivity and potential drugs were examined using the Genomics of Drug Sensitivity in Cancer database.Results: We screened 129 m6A-related lncRNAs; 17 prognosis-related m6A-related lncRNAs were obtained using multivariate analysis and three m6A-related lncRNAs (AC092171.5, MEG9, AC002091.1) were screened using LASSO regression. Survival rates were significantly higher (P < 0.05) in the low-risk than in the high-risk group. Risk score was an independent predictor affecting survival (P < 0.001), with the highest risk score being obtained by calculating the c-index. The TMB significantly differed between the high- and low-risk groups (P < 0.05). In the high- and low-risk groups, mutations were detected in 61 of 70 samples and 49 of 71 samples, respectively, with KRAS, TP53, and SMAD4 showing the highest mutation frequencies in both groups. A lower survival rate was observed in patients with a high versus low TMB. Immune function HLA, Cytolytic activity, and Inflammation-promoting, T cell co-inhibition, Check-point, and T cell co-stimulation significantly differed in different subgroups (P < 0.05). Immune evasion scores were significantly higher in the high-risk group than in the low-risk group. Eight sensitive drugs were screened: ABT.888, ATRA, AP.24534, AG.014699, ABT.263, axitinib, A.443654, and A.770041.Conclusions: We screened m6A-related lncRNAs using bioinformatics, constructed a prognosis-related model, explored TMB and immune function differences in pancreatic cancer, and identified potential therapeutic agents, providing a foundation for further studies of pancreatic cancer diagnosis and treatment.


2021 ◽  
Vol 12 ◽  
Author(s):  
Qian Zhang ◽  
Liping Lv ◽  
Ping Ma ◽  
Yangyang Zhang ◽  
Jiang Deng ◽  
...  

BackgroundPancreatic adenocarcinoma (PAAD) spreads quickly and has a poor prognosis. Autophagy research on PAAD could reveal new biomarkers and targets for diagnosis and treatment.MethodsAutophagy-related genes were translated into autophagy-related gene pairs, and univariate Cox regression was performed to obtain overall survival (OS)-related IRGPs (P&lt;0.001). LASSO Cox regression analyses were performed to construct an autophagy-related gene pair (ARGP) model for predicting OS. The Cancer Genome Atlas (TCGA)-PAAD cohort was set as the training group for model construction. The model predictive value was validated in multiple external datasets. Receiver operating characteristic (ROC) curves were used to evaluate model performance. Tumor microenvironments and immune infiltration were compared between low- and high-risk groups with ESTIMATE and CIBERSORT. Differentially expressed genes (DEGs) between the groups were further analyzed by Gene Ontology biological process (GO-BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and used to identify potential small-molecule compounds in L1000FWD.ResultsRisk scores were calculated as follows: ATG4B|CHMP4C×(-0.31) + CHMP2B|MAP1LC3B×(0.30) + CHMP6|RIPK2 ×(-0.33) + LRSAM1|TRIM5×(-0.26) + MAP1LC3A|PAFAH1B2×(-0.15) + MAP1LC3A|TRIM21×(-0.08) + MET|MFN2×(0.38) + MET|MTDH×(0.47) + RASIP1|TRIM5×(-0.23) + RB1CC1|TPCN1×(0.22). OS was significantly shorter in the high-risk group than the low-risk group in each PAAD cohort. The ESTIMATE analysis showed no difference in stromal scores but a significant difference in immune scores (p=0.0045) and ESTIMATE scores (p=0.014) between the groups. CIBERSORT analysis showed higher naive B cell, Treg cell, CD8 T cell, and plasma cell levels in the low-risk group and higher M1 and M2 macrophage levels in the high-risk group. In addition, the results showed that naive B cells (r=-0.32, p&lt;0.001), Treg cells (r=-0.31, p&lt;0.001), CD8 T cells (r=-0.24, p=0.0092), and plasma cells (r=-0.2, p&lt;0.026) were statistically correlated with the ARGP risk score. The top 3 enriched GO-BPs were signal release, regulation of transsynaptic signaling, and modulation of chemical synaptic transmission, and the top 3 enriched KEGG pathways were the insulin secretion, dopaminergic synapse, and NF-kappa B signaling pathways. Several potential small-molecule compounds targeting ARGs were also identified.ConclusionOur results demonstrate that the ARGP-based model may be a promising prognostic indicator for identifying drug targets in patients with PAAD.


2022 ◽  
Vol 12 ◽  
Author(s):  
Xitao Wang ◽  
Xiaolin Dou ◽  
Xinxin Ren ◽  
Zhuoxian Rong ◽  
Lunquan Sun ◽  
...  

Pancreatic ductal adenocarcinoma (PDAC) is a highly heterogeneous malignancy. Single-cell sequencing (scRNA-seq) technology enables quantitative gene expression measurements that underlie the phenotypic diversity of cells within a tumor. By integrating PDAC scRNA-seq and bulk sequencing data, we aim to extract relevant biological insights into the ductal cell features that lead to different prognoses. Firstly, differentially expressed genes (DEGs) of ductal cells between normal and tumor tissues were identified through scRNA-seq data analysis. The effect of DEGs on PDAC survival was then assessed in the bulk sequencing data. Based on these DEGs (LY6D, EPS8, DDIT4, TNFSF10, RBP4, NPY1R, MYADM, SLC12A2, SPCS3, NBPF15) affecting PDAC survival, a risk score model was developed to classify patients into high-risk and low-risk groups. The results showed that the overall survival was significantly longer in the low-risk group (p &lt; 0.05). The model also revealed reliable predictive power in different subgroups of patients. The high-risk group had a higher tumor mutational burden (TMB) (p &lt; 0.05), with significantly higher mutation frequencies in KRAS and ADAMTS12 (p &lt; 0.05). Meanwhile, the high-risk group had a higher tumor stemness score (p &lt; 0.05). However, there was no significant difference in the immune cell infiltration scores between the two groups. Lastly, drug candidates targeting risk model genes were identified, and seven compounds might act against PDAC through different mechanisms. In conclusion, we have developed a validated survival assessment model, which acted as an independent risk factor for PDAC.


2021 ◽  
Author(s):  
Jinlong Huo ◽  
Shuang Shen ◽  
Chen Chen ◽  
Rui Qu ◽  
Youming Guo ◽  
...  

Abstract Background: Breast cancer(BC) is the most common tumour in women. Hypoxia stimulates metastasis in cancer and is linked to poor patient prognosis.Methods: We screened prognostic-related lncRNAs(Long Non-Coding RNAs) from the Cancer Genome Atlas (TCGA) data and constructed a prognostic signature based on hypoxia-related lncRNAs in BC.Results: We identified 21 differentially expressed lncRNAs associated with BC prognosis. Kaplan Meier survival analysis indicated a significantly worse prognosis for the high-risk group(P<0.001). Moreover, the ROC-curve (AUC) of the lncRNAs signature was 0.700, a performance superior to other traditional clinicopathological characteristics. Gene set enrichment analysis (GSEA) showed many immune and cancer-related pathways and in the low-risk group patients. Moreover, TCGA revealed that functions including activated protein C (APC)co-inhibition, Cinnamoyl CoA reductase(CCR),check-point pathways, cytolytic activity, human leukocyte antigen (HLA), inflammation-promotion, major histocompatibility complex(MHC) class1, para-inflammation, T cell co-inhibition, T cell co-stimulation, and Type Ⅰ and Ⅱ Interferons (IFN) responses were significantly different in the low-risk and high-risk groups. Immune checkpoint molecules such as ICOS, IDO1, TIGIT, CD200R1, CD28, PDCD1(PD-1), were also expressed differently between the two risk groups. The expression of m6A-related mRNA indicated that YTHDC1, RBM15, METTL3, and FTO were significantly between the high and low-risk groups.Additionally, immunotherapy in patients with BC from the low-risk group yielded a higher frequency of clinical responses to anti-PD-1/PD-L1 therapy or a combination of anti-PD-1/PD-L1and anti-CTLA4 therapies.Except for lapatinib, the results also show that a high-risk score is related to a higher half-maximal inhibitory concentration (IC50) of chemotherapy drugs.Conclusion: A novel hypoxia-related lncRNAs signature may serve as a prognostic model for BC.


2021 ◽  
Author(s):  
Chen-jie Qiu ◽  
Xue-bing Wang ◽  
Zi-ruo Zheng ◽  
Chao-zhi Yang ◽  
Kai Lin ◽  
...  

Abstract Background: With the development of genomics, ferroptosis has been determined to be highly important in cancer. The purpose of this study was to identify ferroptosis-related genes (FRGs) associated with the prognosis of pancreatic cancer and to construct a prognostic model based on FRGs. Methods: Based on pancreatic cancer data obtained from The Cancer Genome Atlas (TCGA) database, we employed univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) analysis and multivariate Cox analysis to establish the prognostic model from 232 FRGs. A nomogram was constructed by combining the prognostic model and clinicopathological features. Gene Expression Omnibus (GEO) datasets and tissue samples obtained from our center were utilized to validate the prognostic model. Relationship between risk score and immune cell infiltration was explored by CIBERSORT and TIMER.Results: The prognostic model was established based on four FRGs (ENPP2, ATG4D, SLC2A1 and MAP3K5) and can be an independent risk factor in pancreatic cancer (HR 1.648, 95% CI 1.335-2.035, p < 0.001). Based on the median risk score, patients were divided into a high-risk group and a low-risk group. The KM curve indicated that the overall survival (OS) of the low-risk group was significantly better than that of the high-risk group. The nomogram showed that the prognostic model was the most important element. Gene set enrichment analysis (GSEA) identified three key pathways, namely, TGFβ signaling, HIF signaling pathway and adherens junction. GSE57495, GSE62452 and 88 pancreatic cancer tissues from our center were utilized to validate the prognostic model. The prognostic model can also affect the immune cell infiltration, such as macrophages M0, M1, CD4+T cell and CD8+T cell. Conclusion: A ferroptosis-related prognostic model can be employed to predict the prognosis of pancreatic cancer. Ferroptosis can be an important marker and immunotherapy can be a potential therapeutic target for pancreatic cancer.


Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3836-3836
Author(s):  
Matheus Rodrigues Lopes ◽  
Fabiola Traina ◽  
Joao Kleber Novais Pereira ◽  
Paula de Melo Campos ◽  
Joao Machado-Neto ◽  
...  

Abstract Abstract 3836 Low-risk MDS is characterized by increased apoptosis in the bone marrow and autoimmune disease-like profile, whereas advanced MDS is distinguished by immune evasion, lower apoptosis and secondary DNA damage, facilitating progress into acute leukemia. This evidence, together with immunosupressive therapeutics, indicates a role for the immune system in the progression of early MDS to the advanced stage. Thus, new insights related to the immune system are important to better understand the pathogenesis of MDS. The aim of this study was to investigate the absolute lymphocyte count, the frequency of peripheral CD4+ and CD8+ and their ratio in healthy controls and MDS patients, after age-adjusted analysis. These data were correlated with biological parameters, FOXP3, and also with expressions of the anti-inflammatory cytokines IL10, TGFß1, and CTLA4. A total of 29 samples from healthy donors were used as controls (median age=39 years; range 28–60) and 49 patients with a diagnosis of MDS (median age=67 years; range, 27–89; WHO: RCUD=09, RCMD=23, RARS=08, RAEB-1=07, RAEB-2=02) were included in the study. The study was approved by the ethics committee and informed written consent was provided. CD3+CD4+ and CD3+CD8+ cell frequencies were determined by flow-cytometry. FOXP3, IL10, TGFß1 and CTLA4 expression levels from peripheral blood CD3+ cells were determined by q-PCR. Linear regression analysis and 2-tailed Spearman's correlation coefficient were used for statistical analyses. Correlation of CD3+CD4+ and CD3+CD8+ cell frequencies with clinical data (age, sex, hemoglobin, leukocyte, granulocyte, platelet, number cytopenias and dysplasias, percentage of blast in BM, karyotype, and transfusion dependency) was performed by a univariate and multivariate regression model. We observed a significant decrease in absolute lymphocyte counts in the MDS group, when compared to controls, after adjusting for age (P=0.002). On the other hand, the age-adjusted percentages of T cell subsets were significantly higher in high-risk MDS WHO, for CD3+CD4+ frequency (P=0.02), and in low-risk, for CD3+CD8+ frequency (P=0.04), both compared with the control group. The CD4:CD8 ratio was significantly higher in the high-risk group, when compared to the low-risk group (P=0.03). Univariate and multivariate analysis, showed that advanced age correlated with decreased CD3+CD8+ frequency. Transfusion dependency correlated positively with CD3+CD4+ frequency. FOXP3 expression correlated positively with IL10, TGFß1 and CTLA4 expressions. FOXP3 expression was significantly lower in the low-risk MDS group compared to controls, and demonstrated similar levels to those of the control group in the high-risk group. The same expression pattern was observed for IL10 transcripts. Interestingly, IL10 transcripts correlated negatively with the percentage of CD3+CD8+cells (P=0.02; r=-0.35). There were no significant differences in TGFß1 and CTLA4 expressions. Several studies have shown that lymphocytes are generally not involved in the MDS malignant clone. Hence, our results showing alterated absolute lymphocyte count and T cell frequencies support the hypothesis of immune abnormalities in MDS. The higher CD3+CD8+ frequency in low-risk MDS and its correlation with age are in agreement with the literature. Moreover, there was an increased CD3+CD4+ cell frequency in high-risk MDS, followed by a positive correlation of these cells with transfusion dependency. Therefore, the increased CD4:CD8 ratio observed in the high-risk group could be a consequence of CD4+ cell activation due to transfusion dependency, which was present in 44.4% of the high-risk patients. These findings may explain, in part, why studies of T cell subsets in MDS have been so contradictory when transfusion dependency is not taken into account. A profile of autoimmune disease is described during early stage MDS, as illustrated by the low number of Tregs, and confirmed herein by the lower FOXP3 expression. Although Tregs play a role in the immune system deregulation in MDS patients, via interleukin secretion, this has not yet been proven. This is the first report to show an inverse pattern of CD8+ cell frequency with IL10 expression in MDS patients, suggesting the role of Treg in the immune system deregulation in this disease, via IL10 secretion. Disclosures: No relevant conflicts of interest to declare.


2020 ◽  
Vol 10 ◽  
Author(s):  
Ming Li ◽  
Jinbo Yue ◽  
Xiangbo Wan ◽  
Bin Hua ◽  
Qiuan Yang ◽  
...  

PurposeThe aim of this study was to develop a widely accepted prognostic nomogram and establish a risk-adapted PMRT strategy based on locoregional recurrence for pT1-2N1M0 breast cancer.Methods and MaterialsA total of 3,033 patients with pT1-2N1M0 breast cancer treated at 6 participating institutions between 2000 and 2016 were retrospectively reviewed. A nomogram was developed to predicted locoregional recurrence-free survival (LRFS). A propensity score-matched (PSM) analyses was performed in risk-adapted model.ResultsWith the median follow-up of 65.0 months, the 5-year overall survival (OS), disease free survival (DFS) and LRFS were 93.0, 84.8, and 93.6%, respectively. There was no significant difference between patients who received PMRT or not for the entire group. A nomogram was developed and validated to estimate the probability of 5-year LRFS based on five independent factors including age, primary tumor site, positive lymph nodes number, pathological T stage, and molecular subtype that were selected by a multivariate analysis of patients who did not receive PMRT in the primary cohort. According to the total nomogram risk scores, the entire patients were classified into low- (40.0%), moderate- (42.4%), and high-risk group (17.6%). The 5-year outcomes were significantly different among these three groups (P&lt;0.001). In low-risk group, patients who received PMRT or not both achieved a favorable OS, DFS, and LRFS. In moderate-risk group, no differences in OS, DFS, and LRFS were observed between PMRT and no PMRT patients. In high-risk group, compared with no PMRT, PMRT resulted in significantly different OS (86.8 vs 83.9%, P = 0.050), DFS (77.2 vs 70.9%, P = 0.049), and LRFS (90.8 vs. 81.6%, P = 0.003). After PSM adjustment, there were no significant differences in OS, DFS, and LRFS in low-risk and moderate-risk groups. However, in the high-risk group, PMRT still resulted in significantly better OS, DFS and improved LRFS.ConclusionsThe proposed nomogram provides an individualized risk estimate of LRFS in patients with pT1-2N1M0 breast cancer. Risk-adapted PMRT for high-risk patients is a viable effective strategy.


2021 ◽  
Vol 12 ◽  
Author(s):  
Tao Yan ◽  
Guoyuan Ma ◽  
Kai Wang ◽  
Weidong Liu ◽  
Weiqing Zhong ◽  
...  

Adenocarcinoma (AD) and squamous cell carcinoma (SCC) are both classified as major forms of non-small cell lung cancer, but differences in clinical prognoses and molecular mechanisms are remarkable. Recent studies have supported the importance of understanding immune status in that it influences clinical outcomes of cancer, and immunotherapies based on the theory of “immune editing” have had notable clinical success. Our study aimed to identify specific long non-coding (lnc) RNAs that control key immune-related genes and to use them to construct risk models for AD and SCC. Risk scores were used to separate patients into high- and low-risk groups, and we validated the prognostic significance of both risk scores with our own cohorts. A Gene Set Enrichment Analysis suggested that the immune responses of patients in the AD high-risk group and the SCC low-risk group tended to be weakened. Evaluation of immune infiltration revealed that the degree of infiltration of dendritic cells is of particular importance in AD. In addition, prediction of responses to immune checkpoint inhibitor (ICI) treatments, based on the T Cell Immune Dysfunction and Exclusion and immunophenoscore models, indicated that deterioration of the immune microenvironment is due mainly to T cell exclusion in AD patients and T cell dysfunction in SCC patients and that high-risk patients with SCC might benefit from ICI treatment. The prediction of downstream targets via The Cancer Proteome Atlas and RNA-seq analyses of a transfected lung cancer cell line indicated that the lncRNA LINC00996 is a potential therapeutic target in AD.


2020 ◽  
Author(s):  
zhiyong zeng ◽  
Chaohui Wu ◽  
Zhenlv Lin ◽  
Yong Ye ◽  
Shaodan Feng ◽  
...  

Abstract Background No therapeutics have demonstrated specific efficacy for patients with COVID-19. Methods We retrospectively evaluated 351 patients with COVID-19 admitted to the Third People's Hospital of Yichang from 9 January to 25 March, 2020.Univariate logistic regression and least absolute shrinkage and selection operator (LASSO) regression were employed to identify risk factors associated with progression, which were then incorporated into the nomogram. Survival of patients between high-risk and low-risk groups was compared by kaplan-Meier analysis. Moreover, we assessed the effects of existing common drugs on survival of patients with high-risk. Results Based on the LASSO, four variables (white blood cell, C-reactive protein, whether lymphocyte ≥ 0.8 × 109/L, and whether lactate dehydrogenase ≥ 400 U/L) were selected for construction of the nomogram. Patients in the total cohort were stratified into low-risk group (total point < 160) and high-risk group (total point ≥ 160). Kaplan-Meier analysis demonstrated that there was significant difference in survival of patients between high-risk and low-risk groups (8-week survival rate: 71.41% vs 100%, P < 0.0001). Among the common drugs, we found that patients with high-risk received oseltamivir, lopinavir/ritonavir or Reduning injection exhibited better survival. The combination of these three drugs showed the effect of improving survival, although single drug may have no effect in different grouping analysis. Conclusions The combination of oseltamivir, lopinavir/ritonavir and Reduning injection may improve survival of COVID-19 patients with high-risk identified by our simple-to-use nomogram.


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