scholarly journals A Novel Inflammatory lncRNAs Prognostic Signature for Predicting the Prognosis of Low-Grade Glioma Patients

2021 ◽  
Vol 12 ◽  
Author(s):  
Zijin Xiang ◽  
Xueru Chen ◽  
Qiaoli Lv ◽  
Xiangdong Peng

BackgroundAs immunotherapy has received attention as new treatments for brain cancer, the role of inflammation in the process of glioma is of particular importance. Increasing studies have further shown that long non-coding RNAs (lncRNAs) are important factors that promote the development of glioma. However, the relationship between inflammation-related lncRNAs and the prognosis of glioma patients remains unclear. The purpose of this study is to construct and validate an inflammation-related lncRNA prognostic signature to predict the prognosis of low-grade glioma patients.MethodsBy downloading and analyzing the gene expression data and clinical information of the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) patients with low-grade gliomas, we could screen for inflammatory gene-related lncRNAs. Furthermore, through Cox and the Least Absolute Shrinkage and Selection Operator regression analyses, we established a risk model and divided patients into high- and low-risk groups based on the median value of the risk score to analyze the prognosis. In addition, we analyzed the tumor mutation burden (TMB) between the two groups based on somatic mutation data, and explored the difference in copy number variations (CNVs) based on the GISTIC algorithm. Finally, we used the MCPCounter algorithm to study the relationship between the risk model and immune cell infiltration, and used gene set enrichment analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to explore the enrichment pathways and biological processes of differentially expressed genes between the high- and low-risk groups.ResultsA novel prognostic signature was constructed including 11 inflammatory lncRNAs. This risk model could be an independent prognostic predictor. The patients in the high-risk group had a poor prognosis. There were significant differences in TMB and CNVs for patients in the high- and low-risk groups. In the high-risk group, the immune system was activated more significantly, and the expression of immune checkpoint-related genes was also higher. The GSEA, GO, and KEGG analyses showed that highly expressed genes in the high-risk group were enriched in immune-related processes, while lowly expressed genes were enriched in neuromodulation processes.ConclusionThe risk model of 11 inflammation-related lncRNAs can serve as a promising prognostic biomarker for low-grade gliomas patients.

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Zhicheng Zhuang ◽  
Huajun Cai ◽  
Hexin Lin ◽  
Bingjie Guan ◽  
Yong Wu ◽  
...  

Background. Pyroptosis has been confirmed as a type of inflammatory programmed cell death in recent years. However, the prognostic role of pyroptosis in colon cancer (CC) remains unclear. Methods. Dataset TCGA-COAD which came from the TCGA portal was taken as the training cohort. GSE17538 from the GEO database was treated as validation cohorts. Differential expression genes (DEGs) between normal and tumor tissues were confirmed. Patients were classified into two subgroups according to the expression characteristics of pyroptosis-related DEGs. The LASSO regression analysis was used to build the best prognostic signature, and its reliability was validated using Kaplan–Meier, ROC, PCA, and t-SNE analyses. And a nomogram based on the multivariate Cox analysis was developed. The enrichment analysis was performed in the GO and KEGG to investigate the potential mechanism. In addition, we explored the difference in the abundance of infiltrating immune cells and immune microenvironment between high- and low-risk groups. And we also predicted the association of common immune checkpoints with risk scores. Finally, we verified the expression of the pyroptosis-related hub gene at the protein level by immunohistochemistry. Results. A total of 23 pyroptosis-related DEGs were identified in the TCGA cohort. Patients were classified into two molecular clusters (MC) based on DEGs. Kaplan–Meier survival analysis indicated that patients with MC1 represented significantly poorer OS than patients with MC2. 13 overall survival- (OS-) related DEGs in MCs were used to construct the prognostic signature. Patients in the high-risk group exhibited poorer OS compared to those in the low-risk group. Combined with the clinical features, the risk score was found to be an independent prognostic factor of CC patients. The above results are verified in the external dataset GSE17538. A nomogram was established and showed excellent performance. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that the varied prognostic performance between high- and low-risk groups may be related to the immune response mediated by local inflammation. Further analysis showed that the high-risk group has stronger immune cell infiltration and lower tumor purity than the low-risk group. Through the correlation between risk score and immune checkpoint expression, T-cell immunoglobulin and mucin domain-containing protein 3 (TIM-3) was predicted as a potential therapeutic target for the high-risk group. Conclusion. The 13-gene signature was associated with OS, immune cells, tumor purity, and immune checkpoints in CC patients, and it could provide the basis for immunotherapy and predicting prognosis and help clinicians make decisions for individualized treatment.


2021 ◽  
Author(s):  
Fang Wen ◽  
Xiaoxue Chen ◽  
Wenjie Huang ◽  
Shuai Ruan ◽  
Suping Gu ◽  
...  

Abstract Background: The diagnosis rate and mortality of gastric cancer (GC) are among the highest in the global, so it is of great significance to predict the survival time of GC patients. Ferroptosis and iron-metabolism make a critical impact on tumor development and are closely linked to the treatment of cancer and the prognosis of patients. However, the predictive value of the genes involved in ferroptosis and iron-metabolism in GC and their effects on immune microenvironment remain to be further clarified.Methods: In this study, the RNA sequence information and general clinical indicators of GC patients were acquired from the public databases. We first systematically screen out 134 DEGs and 13 PRGs related to ferroptosis and iron-metabolism. Then, we identified six PRDEGs (GLS2, MTF1, SLC1A5, SP1, NOX4, and ZFP36) based on the LASSO-penalized Cox regression analysis. The 6-gene prognostic risk model was established in the TCGA cohort and the GC patients were separated into the high- and the low-risk groups through the risk score median value. GEO cohort was used for verification. The expression of PRDEGs was verified by quantitative QPCR.Results: Our study demonstrated that patients in the low-risk group had a higher survival probability compared with those in high-risk group. In addition, univariate and multivariate Cox regression analyses confirmed that the risk score was an independent prediction parameter. The ROC curve analysis and nomogram manifested that the risk model had the high predictive ability and was more sensitive than general clinical features. Furthermore, compared with the high-risk group, the low-risk group had higher TMB and a longer 5-year survival period. In the immune microenvironment of GC, there were also differences in immune function and highly infiltrated immune cells between the two risk groups.Conclusions: The prognostic risk model based on the six genes associated with ferroptosis and iron-metabolism has a good performance for predicting the prognosis of patients with GC. The treatment of cancer by inducing tumor ferroptosis or mediating tumor iron-metabolism, especially combined with immunotherapy, provides a new possibility for individualized treatment of GC patients.


PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11074
Author(s):  
Jin Duan ◽  
Youming Lei ◽  
Guoli Lv ◽  
Yinqiang Liu ◽  
Wei Zhao ◽  
...  

Background Lung adenocarcinoma (LUAD) is the most commonhistological lung cancer subtype, with an overall five-year survivalrate of only 17%. In this study, we aimed to identify autophagy-related genes (ARGs) and develop an LUAD prognostic signature. Methods In this study, we obtained ARGs from three databases and downloaded gene expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We used TCGA-LUAD (n = 490) for a training and testing dataset, and GSE50081 (n = 127) as the external validation dataset.The least absolute shrinkage and selection operator (LASSO) Cox and multivariate Cox regression models were used to generate an autophagy-related signature. We performed gene set enrichment analysis (GSEA) and immune cell analysis between the high- and low-risk groups. A nomogram was built to guide the individual treatment for LUAD patients. Results We identified a total of 83 differentially expressed ARGs (DEARGs) from the TCGA-LUAD dataset, including 33 upregulated DEARGs and 50 downregulated DEARGs, both with thresholds of adjusted P < 0.05 and |Fold change| > 1.5. Using LASSO and multivariate Cox regression analyses, we identified 10 ARGs that we used to build a prognostic signature with areas under the curve (AUCs) of 0.705, 0.715, and 0.778 at 1, 3, and 5 years, respectively. Using the risk score formula, the LUAD patients were divided into low- or high-risk groups. Our GSEA results suggested that the low-risk group were enriched in metabolism and immune-related pathways, while the high-risk group was involved in tumorigenesis and tumor progression pathways. Immune cell analysis revealed that, when compared to the high-risk group, the low-risk group had a lower cell fraction of M0- and M1- macrophages, and higher CD4 and PD-L1 expression levels. Conclusion Our identified robust signature may provide novel insight into underlying autophagy mechanisms as well as therapeutic strategies for LUAD treatment.


2021 ◽  
Vol 12 ◽  
Author(s):  
Pengjun Qiu ◽  
Qiaonan Guo ◽  
Qingzhi Yao ◽  
Jianpeng Chen ◽  
Jianqing Lin

BackgroundAs a kind of small membrane vesicles, exosomes are secreted by most cell types from multivesicular endosomes, including tumor cells. The relationship between exosomes and immune response plays a vital role in the occurrence and development of tumors. Nevertheless, the interaction between exosomes and the microenvironment of tumors remains unclear. Therefore, we set out to study the influence of exosomes on the triple-negative breast cancer (TNBC) microenvironment.MethodOne hundred twenty-one exosome-related genes were downloaded from ExoBCD database, and IVL, CXCL13, and AP2S1 were final selected because of the association with TNBC prognosis. Based on the sum of the expression levels of these three genes, provided by The Cancer Genome Atlas (TCGA), and the regression coefficients, an exosome risk score model was established. With the median risk score value, the patients in the two databases were divided into high- and low-risk groups. R clusterProfiler package was employed to compare the different enrichment ways between the two groups. The ESTIMATE and CIBERSORT methods were employed to analyze ESTIMATE Score and immune cell infiltration. Finally, the correlation between the immune checkpoint-related gene expression levels and exosome-related risk was analyzed. The relationship between selected gene expression and drug sensitivity was also detected.ResultsDifferent risk groups exhibited distinct result of TNBC prognosis, with a higher survival rate in the low-risk group than in the high-risk group. The two groups were enriched by immune response and biological process pathways. A better overall survival (OS) was demonstrated in patients with high scores of immune and ESTIMATE rather than ones with low scores. Subsequently, we found that CD4+-activated memory T cells and M1 macrophages were both upregulated in the low-risk group, whereas M2 macrophages and activated mast cell were downregulated in the low-risk group in patients from the TCGA and GEO databases, respectively. Eventually, four genes previously proposed to be targets of immune checkpoint inhibitors were evaluated, resulting in the expression levels of CD274, CTLA4, LAG3, and TIM3 being higher in the low-risk group than high-risk group.ConclusionThe results of our study suggest that exosome-related risk model was related to the prognosis and ratio of immune cell infiltration in patients with TNBC. This discovery may make contributions to improve immunotherapy for TNBC.


BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Moxuan Zhang ◽  
Yanhao Cheng ◽  
Zhengchun Xue ◽  
Qiang Sun ◽  
Jian Zhang

Abstract Background Glioma is the most common primary intracranial tumour and has a very poor prognosis. Pyroptosis, also known as inflammatory necrosis, is a type of programmed cell death that was discovered in recent years. The expression and role of pyroptosis-related genes in gliomas are still unclear. Methods In this study, we analysed the RNA-seq and clinical information of glioma patients from The Cancer Genome Atlas (TCGA) database and Chinese Glioma Genome Atlas (CGGA) database. To investigate the prognosis and immune microenvironment of pyroptosis-related genes in gliomas, we constructed a risk model based on the TCGA cohort. The patients in the CGGA cohort were used as the validation cohort. Results In this study, we identified 34 pyroptosis-related differentially expressed genes (DEGs) in glioma. By clustering these DEGs, all glioma cases can be divided into two clusters. Survival analysis showed that the overall survival time of Cluster 1 was significantly higher than that of Cluster 2. Using the TCGA cohort as the training set, a 10-gene risk model was constructed through univariate Cox regression analysis and LASSO Cox regression analysis. According to the risk score, gliomas were divided into high-risk and low-risk groups. Survival analysis showed that the low-risk group had a longer survival time than the high-risk group. The above results were verified in the CGGA validation cohort. To verify that the risk model was independent of other clinical features, the distribution and the Kaplan-Meier survival curves associated with risk scores were performed. Combined with the characteristics of the clinical cases, the risk score was found to be an independent factor predicting the overall survival of patients with glioma. The analysis of single sample Gene Set Enrichment Analysis (ssGSEA) showed that compared with the low-risk group, the high-risk group had immune cell and immune pathway activities that were significantly upregulated. Conclusion We established 10 pyroptosis-related gene markers that can be used as independent clinical predictors and provide a potential mechanism for the treatment of glioma.


2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Morten Lindhardt ◽  
Nete Tofte ◽  
Gemma Currie ◽  
Marie Frimodt-Moeller ◽  
Heiko Von der Leyen ◽  
...  

Abstract Background and Aims In the PRIORITY study, it was recently demonstrated that the urinary peptidome-based classifier CKD273 was associated with increased risk for progression to microalbuminuria. As a prespecified secondary outcome, we aim to evaluate the classifier CKD273 as a determinant of relative reductions in eGFR (CKD-EPI) of 30% and 40% from baseline, at one timepoint without requirements of confirmation. Method The ‘Proteomic prediction and Renin angiotensin aldosterone system Inhibition prevention Of early diabetic nephRopathy In TYpe 2 diabetic patients with normoalbuminuria trial’ (PRIORITY) is the first prospective observational study to evaluate the early detection of diabetic kidney disease in subjects with type 2 diabetes (T2D) and normoalbuminuria using the CKD273 classifier. Setting 1775 subjects from 15 European sites with a mean follow-up time of 2.6 years (minimum of 7 days and a maximum of 4.3 years). Patients Subjects with T2D, normoalbuminuria and estimated glomerular filtration rate (eGFR) ≥ 45 ml/min/1.73m2. Participants were stratified into high- or low-risk groups based on their CKD273 score in a urine sample at screening (high-risk defined as score &gt; 0.154). Results In total, 12 % (n = 216) of the subjects had a high-risk proteomic pattern. Mean (SD) baseline eGFR was 88 (15) ml/min/1.73m2 in the low-risk group and 81 (17) ml/min/1.73m2 in the high-risk group (p &lt; 0.01). Baseline median (interquartile range) urinary albumin to creatinine ratio (UACR) was 5 (3-8) mg/g and 7 (4-12) mg/g in the low-risk and high-risk groups, respectively (p &lt; 0.01). A 30 % reduction in eGFR from baseline was seen in 42 (19.4 %) subjects in the high-risk group as compared to 62 (3.9 %) in the low-risk group (p &lt; 0.0001). In an unadjusted Cox-model the hazard ratio (HR) for the high-risk group was 5.7, 95 % confidence interval (CI) (3.9 to 8.5; p&lt;0.0001). After adjustment for baseline eGFR and UACR, the HR was 5.2, 95 % CI (3.4 to 7.8; p&lt;0.0001). A 40 % reduction in eGFR was seen in 15 (6.9 %) subjects in the high-risk group whereas 22 (1.4 %) in the low-risk group developed this endpoint (p&lt;0.0001). In an unadjusted Cox-model the HR for the high-risk group was 5.0, 95 % CI (2.6 to 9.6; p&lt;0.0001). After adjustment for baseline eGFR and UACR, the HR was 4.8, 95 % CI (2.4 to 9.7; p&lt;0.0001). Conclusion In normoalbuminuric subjects with T2D, the urinary proteomic classifier CKD273 predicts renal function decline of 30 % and 40 %, independent of baseline eGFR and albuminuria.


2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Jianfeng Zheng ◽  
Benben Cao ◽  
Xia Zhang ◽  
Zheng Niu ◽  
Jinyi Tong

Cervical cancer (CC) is a common gynecological malignancy for which prognostic and therapeutic biomarkers are urgently needed. The signature based on immune-related lncRNAs (IRLs) of CC has never been reported. This study is aimed at establishing an IRL signature for patients with CC. A cohort of 326 CC and 21 normal tissue samples with corresponding clinical information was included in this study. Twenty-eight IRLs were collected according to the Pearson correlation analysis between the immune score and lncRNA expression ( p < 0.01 ). Four IRLs (BZRAP1-AS1, EMX2OS, ZNF667-AS1, and CTC-429P9.1) with the most significant prognostic values ( p < 0.05 ) were identified which demonstrated an ability to stratify patients into the low-risk and high-risk groups by developing a risk score model. It was observed that patients in the low-risk group showed longer overall survival (OS) than those in the high-risk group in the training set, valid set, and total set. The area under the curve (AUC) of the receiver operating characteristic curve (ROC curve) for the four-IRL signature in predicting the one-, two-, and three-year survival rates was larger than 0.65. In addition, the low-risk and high-risk groups displayed different immune statuses in GSEA. These IRLs were also significantly correlated with immune cell infiltration. Our results showed that the IRL signature had a prognostic value for CC. Meanwhile, the specific mechanisms of the four IRLs in the development of CC were ascertained preliminarily.


2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Yinglian Pan ◽  
Li Ping Jia ◽  
Yuzhu Liu ◽  
Yiyu Han ◽  
Qian Li ◽  
...  

Abstract Background In this study we aimed to identify a prognostic signature in BRCA1/2 mutations to predict disease progression and the efficiency of chemotherapy ovarian cancer (OV), the second most common cause of death from gynecologic cancer in women worldwide. Methods Univariate Cox proportional-hazards and multivariate Cox regression analyses were used to identifying prognostic factors from data obtained from The Cancer Genome Atlas (TCGA) database. The area under the curve of the receiver operating characteristic curve was assessed, and the sensitivity and specificity of the prediction model were determined. Results A signature consisting of two long noncoding RNAs(lncRNAs), Z98885.2 and AC011601.1, was selected as the basis for classifying patients into high and low-risk groups (median survival: 7.2 years vs. 2.3 years). The three-year overall survival (OS) rates for the high- and low-risk group were approximately 38 and 100%, respectively. Chemotherapy treatment survival rates indicated that the high-risk group had significantly lower OS rates with adjuvant chemotherapy than the low-risk group. The one-, three-, and five-year OS were 100, 40, and 15% respectively in the high-risk group. The survival rate of the high-risk group declined rapidly after 2 years of OV chemotherapy treatment. Multivariate Cox regression associated with other traditional clinical factors showed that the 2-lncRNA model could be used as an independent OV prognostic factor. Analyses of data from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) indicated that these signatures are pivotal to cancer development. Conclusion In conclusion, Z98885.2 and AC011601.1 comprise a novel prognostic signature for OV patients with BRCA1/2 mutations, and can be used to predict prognosis and the efficiency of chemotherapy.


2015 ◽  
Vol 33 (3_suppl) ◽  
pp. 394-394
Author(s):  
Lavanniya Kumar Palani Velu ◽  
Vishnuvardhan Chandrabalan ◽  
Ross Carter ◽  
Colin McKay ◽  
Donald McMillan ◽  
...  

394 Background: Pancreas-specific complications (PSC), comprising postoperative pancreatic fistula, post-pancreatectomy haemorrhage, and intra-abdominal collections, are drivers of morbidity following pancreaticoduodenectomy (PD). Intra-operatively derived pancreatic gland texture is a major determinant of postoperative PSC. We have previously demonstrated that a postoperative day 0 (PoD0) serum amylase ≥ 130 IU/L is an objective surrogate of pancreatic texture, and is associated with PSC. We sought to refine the PSC risk prediction model by including serial measurements of serum C-reactive protein (CRP). Methods: 230 consecutive patients undergoing PD between 2008 and 2014 were included in the study. Routine serum investigations, including amylase and CRP were performed from the pre-operative day. Receiver operating characteristic (ROC) curve analysis was used to identify a threshold value of serum CRP associated with clinically significant PSC. Results: 95 (41.3%) patients experienced a clinically significant PSC. ROC analysis identified post-operative day 2 (PoD2) serum CRP of 180 mg/L as the optimal threshold (P=0.005) associated with clinically significant PSC, a prolonged stay in critical care (P =0.032), and a relaparotomy (P = 0.045). Patients with a PoD0 serum amylase ≥ 130 IU/L who then developed a PoD2 serum CRP ≥ 180 mg/L had a higher incidence of postoperative complications. Patients were categorised into high, intermediate and low risk groups based on PoD0 serum amylase and PoD2 serum CRP. Patients in the high risk group (PoD0 serum amylase ≥ 130 IU/L and PoD2 serum CRP ≥ 180 mg/l) had significantly higher incidence of PSC, a return to theatre, prolonged lengths stay (all P≤ 0.05) and a four-fold increase in perioperative mortality compared patients in the intermediate and low risk groups (7 deaths in the high risk group versus 2 and nil in the intermediate and low risk groups respectively). Conclusions: A high risk profile, defined as PoD0 serum amylase ≥ 130 IU/L and PoD2 serum CRP ≥ 180 mg/l, should raise the clinician’s awareness of the increased risk of clinically significant PSC and a complicated postoperative course following pancreaticoduodenectomy.


Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 186-186 ◽  
Author(s):  
Inhye E. Ahn ◽  
Xin Tian ◽  
Maher Albitar ◽  
Sarah E. M. Herman ◽  
Erika M. Cook ◽  
...  

Abstract Introduction: We previously reported a prognostic scoring system in CLL using pre-treatment factors in patients treated with ibrutinib [Ahn et al, 2016 ASH Annual Meeting]. Here we present long-term follow-up results and validation of the prognostic models in a large independent cohort of patients. We also determine the incidence of resistance-conferring mutations in BTK and PLCG2 genes in different clinical risk groups. Methods and Patients: The discovery cohort comprised 84 CLL patients on a phase II study with either TP53 aberration (deletion 17p or TP53 mutation) or age ≥65 years (NCT01500733). The validation cohort comprised 607 patients pooled from four phase II and III studies for ibrutinib in treatment-naïve or relapsed/refractory CLL (NCT01105247; NCT01578707; NCT01722487; NCT01744691). All patients received single-agent ibrutinib 420mg once daily. We used Cox regression models to identify independent predictors of PFS, Kaplan-Meier method to estimate probabilities of PFS, log-rank test to compare PFS, and Cochran-Armitage trend test to compare the incidence of mutation among subgroups. We used R version 3.5.0 or SAS® version 9.3 for statistical analyses. For biomarker correlation, we tested cellular DNA or cell-free DNA collected from patients in the discovery cohort with the targeted sequencing of BTK and PLCG2 genes. Result: At a median follow-up of 5.2 years, 28 (33.3%) of 84 patients in the discovery cohort progressed or died. 52 (61.9%) patients had treatment-naïve CLL. Independent factors of PFS on univariate analysis were; TP53 aberration, prior treatment, and β-2 microglobulin (B2M) >4mg/L (P<0.05 for all tests). Unmutated IGHV and advanced Rai stage (III/IV) showed a trend toward inferior outcome without reaching statistical significance. Because higher levels of B2M were associated with relapsed/refractory CLL, we performed two multivariate Cox regression models to assess B2M and prior treatment status separately. Risk groups were determined by the presence of TP53 aberration, advanced Rai stage, and B2M >4mg/L for Model 1, and TP53 aberration, advanced Rai stage, and relapsed/refractory CLL for Model 2 (Table 1). The high-risk group had all three adverse risk factors; the intermediate-risk group had two risk factors; and the low-risk group, none or one. The median PFS of the high-risk group was 38.9 months for Model 1 and 38.4 months for Model 2, and was significantly shorter than those of intermediate and low-risk groups. In the validation cohort, 254 (41.8%) of 607 patients progressed or died at a median follow-up of 4.2 years. 167 (27.5%) patients had treatment-naïve CLL. Both models showed statistically significant differences in PFS by risk groups (Table 1). For the high-risk group, 4-year PFS was 30.2% in Model 1 and 30.5% in Model 2, which were inferior to those of intermediate (53.4 and 52.4%) and low-risk groups (68.7 and 73.7%). Model 1 classified 20% of patients and Model 2 classified 28% of patients to the high-risk group. BTK and PLCG2 mutations are common genetic drivers of ibrutinib resistance in CLL. To determine whether the incidence of these mutations correlates with prognostic risk groups, we performed targeted sequencing of BTK and PLCG2 of samples collected from patients in the discovery cohort. We used cell-free DNA for patients who received long-term ibrutinib (≥3 years) and had low circulating tumor burden, and cellular DNA, for samples collected within 3 years on ibrutinib or at progression. Of 84 patients, 69 (82.1%) were tested at least once, and 37 (44.0%) were tested at least twice. The frequency of testing was similar across the risk groups by two models (P>0.05). The cumulative incidences of mutations at 5 years in the low-, intermediate-, and high-risk groups were: 21.4%, 44.8% and 50%, respectively, by Model 1 (P=0.02); and 22.6%, 41.4% and 66.7%, respectively, by Model 2 (P=0.01). Conclusion: We developed and validated prognostic models to predict the risk of disease progression or death in CLL patients treated with ibrutinib. Risk groups classified by three commonly available pre-treatment factors showed statistically significant differences in PFS. The clinically-defined high-risk disease was linked to higher propensity to develop clonal evolution with BTK and/or PLCG2 mutations, which heralded ibrutinib resistance. Disclosures Albitar: Neogenomics Laboratories: Employment. Ma:Neogenomics Laboratories: Employment. Ipe:Pharmacyclics, an AbbVie Company: Employment, Other: Travel; AbbVie: Equity Ownership. Tsao:Pharmacyclics LLC, an AbbVie Company: Employment. Cheng:Pharmacyclics LLC, an AbbVie Company: Employment. Dean:CTI BioPharma Corp.: Employment, Equity Ownership; Pharmacyclics LLC, an AbbVie Company: Employment, Equity Ownership. Wiestner:Pharmacyclics LLC, an AbbVie Company: Research Funding.


Sign in / Sign up

Export Citation Format

Share Document