scholarly journals Prediction of Outcome in Patients With Chronic Lymphocytic Leukemia Treated With Ibrutinib: Development and Validation of a Four-Factor Prognostic Model

2020 ◽  
pp. JCO.20.00979 ◽  
Author(s):  
Inhye E. Ahn ◽  
Xin Tian ◽  
David Ipe ◽  
Mei Cheng ◽  
Maher Albitar ◽  
...  
Keyword(s):  
High Risk ◽  
Chronic Lymphocytic Leukemia ◽  
Phase Ii ◽  
Prognostic Model ◽  
Risk Group ◽  
Machine Learning Algorithms ◽  
Lymphocytic Leukemia ◽  
Low Risk ◽  
Data Set ◽  
Increased Risk

PURPOSE Randomized trials established the superiority of ibrutinib-based therapy over chemoimmunotherapy in chronic lymphocytic leukemia. Durability of progression-free survival (PFS) with ibrutinib can vary by patient subgroup. Clinical tools for prognostication and risk-stratification are needed. PATIENTS AND METHODS Patients treated with ibrutinib in phase II and III trials provided the discovery data set and were subdivided into discovery and internal validation cohorts. An external validation cohort included 84 patients enrolled in our investigator-initiated phase II trial. Univariable analysis of 18 pretreatment parameters was performed using PFS and overall survival (OS) end-points. Multivariable analysis and machine-learning algorithms identified four factors for a prognostic model that was validated in internal and external cohorts. RESULTS Factors independently associated with inferior PFS and OS were as follows: TP53 aberration, prior treatment, β-2 microglobulin ≥ 5 mg/L, and lactate dehydrogenase > 250 U/L. Each of these four factors contributed one point to a prognostic model that stratified patients into three risk groups: three to four points, high risk; two points, intermediate risk; zero to one point, low risk. The 3-year PFS rates for all 804 patients combined were 47%, 74%, and 87% for the high-, the intermediate-, and the low-risk group, respectively ( P < .0001). The 3-year OS rates were 63%, 83%, and 93%, respectively ( P < .0001). The model remained significant when applied to treatment-naïve and relapsed/refractory cohorts individually. For 84 patients in the external cohort, BTK and PLCG2 mutations were tested cross-sectionally and at progression. The cumulative incidences of mutations were strongly correlated with the model. In the external cohort, Richter’s transformation occurred in 17% of the high-risk group, and in no patient in the low-risk group. CONCLUSION Patients at increased risk of ibrutinib failure can be identified at treatment initiation and considered for clinical trials.

scholarly journals Detection Rate of Integrated Molecular and Cytogenetic Biomarker Testing for Chronic Lymphocytic Leukemia

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 4691-4691
Author(s):  
Ramadevi Prathapam ◽  
Najuma Maharjan ◽  
Sheila B Powers ◽  
Tracey Allen K Freitas ◽  
Guoli Sun ◽  
...  
Keyword(s):  
High Risk ◽  
Chronic Lymphocytic Leukemia ◽  
Prognostic Model ◽  
Lymphocytic Leukemia ◽  
Low Risk ◽  
Intermediate Risk ◽  
Clinical Value ◽  
Trisomy 12 ◽  
Biomarker Testing ◽  
Testing Approach

Abstract Chronic lymphocytic leukemia (CLL) is the most common type of leukemia in western countries and typically occurs in elderly individuals. There will be an estimated 21,250 newly diagnosed cases in the United States this year and 4,320 deaths. Due to the highly variable clinical course of this disease, prognostication and risk stratification methods are necessary for guiding decisions on clinical management. Integrated prognostic models incorporating laboratory testing for multiple molecular, cytogenetic, and other biomarkers have recently been proposed by major clinical guidelines to classify patients into risk subgroups. The current NCCN Guidelines for Chronic Lymphocytic Leukemia/Small Lymphocytic Leukemia describe such an integrated prognostic model known as the Rossi model that includes TP53, NOTCH1, SF3B1, and BIRC3 mutations along with the cytogenetic abnormalities detected by fluorescence in situ hybridization (FISH) to classify CLL patients into 4 distinct prognostic subgroups: high-risk (TP53 and/or BIRC3 abnormalities), intermediate-risk (NOTCH1 and/or SF3B1 mutations and/or deletion 11q), low-risk (trisomy 12 and wild-type for all genetic lesions), and very low-risk (deletion 13q only). The 10-year survival rates for these subgroups are 29%, 37%, 57%, and 69%, respectively. To assess the clinical value of an integrated biomarker testing approach, we analyzed results of 651 consecutive cases submitted to our clinical diagnostic laboratory for testing on our integrated panel of molecular and cytogenetic biomarkers for CLL. Our panel includes detection of genomic alterations by FISH (deletion 6q, 13q, 11q, 17p, trisomy 12, IGH rearrangement, and IGH/CCND1 translocation) and detection of sequence variants in BIRC3, BTK, MYD88, NOTCH1, PCLG2, SF3B1, and TP53 by next-generation sequencing (NGS). In total, 472 cases had positive findings by either FISH (90%) or NGS (46%) for a detection rate of 72.5%. Using the Rossi integrated prognostic model, 17.5% of cases fell into the high-risk subgroup, 20% of cases fell into the intermediate-risk subgroup, 43.5% of cases fell into the low-risk subgroup, and 19% of cases fell into the very low-risk subgroup. Importantly, among cases with positive FISH findings, 40.1% of cases also had positive molecular findings. In approximately 84% of cases belonging to the low-risk cytogenetic subgroups by FISH assessment alone, the incorporation of molecular findings resulted in reclassification into a higher-risk subgroup. Among the FISH-negative cases, 17% were classified as high-risk or intermediate-risk based on the molecular findings. Together, these findings support the clinical value of an integrative biomarker testing approach that includes both molecular and cytogenetic biomarkers to stratify CLL patients into risk subgroups to help guide decisions on clinical management. Disclosures Prathapam: Quest Diagnostics: Current Employment. Maharjan: Quest Diagnostics: Current Employment. Powers: Quest Diagnostics: Current Employment. Freitas: Quest Diagnostics: Current Employment. Sun: Quest Diagnostics: Current Employment. Tan: Quest Diagnostics: Current Employment. Gupta: Quest Diagnostics: Current Employment. Hucthagowder: Quest Diagnostics: Current Employment. Graham: Quest Diagnostics: Current Employment. Whitman: Quest Diagnostics: Current Employment. Khadgi: Quest Diagnostics: Current Employment. Daniel: Quest Diagnostics: Current Employment. Racke: Quest Diagnostics: Current Employment. Champion: Quest Diagnostics: Current Employment.

scholarly journals Polygenic risk scores predict diabetic complications and their response to therapy

2019 ◽  
Author(s):  
J. Tremblay ◽  
M. Haloui ◽  
F. Harvey ◽  
R. Tahir ◽  
F.-C. Marois-Blanchet ◽  
...  
Keyword(s):  
High Risk ◽  
Prediction Model ◽  
Risk Group ◽  
Intensive Therapy ◽  
Cardiovascular Death ◽  
Response To Therapy ◽  
Low Risk ◽  
Number Needed To Treat ◽  
Genome Wide Association Studies ◽  
Increased Risk

AbstractType 2 diabetes increases the risk of cardiovascular and renal complications, but early risk prediction can lead to timely intervention and better outcomes. Through summary statistics of meta-analyses of published genome-wide association studies performed in over 1.2 million of individuals, we combined 9 PRS gathering genomic variants associated to cardiovascular and renal diseases and their key risk factors into one logistic regression model, to predict micro- and macrovascular endpoints of diabetes. Its clinical utility in predicting complications of diabetes was tested in 4098 participants with diabetes of the ADVANCE trial followed during a period of 10 years and replicated it in three independent non-trial cohorts. The prediction model adjusted for ethnicity, sex, age at onset and diabetes duration, identified the top 30% of ADVANCE participants at 3.1-fold increased risk of major micro- and macrovascular events (p=6.3×10−21 and p=9.6×10−31, respectively) and at 4.4-fold (p=6.8×10−33) increased risk of cardiovascular death compared to the remainder of T2D subjects. While in ADVANCE overall, combined intensive therapy of blood pressure and glycaemia decreased cardiovascular mortality by 24%, the prediction model identified a high-risk group in whom this therapy decreased mortality by 47%, and a low risk group in whom the therapy had no discernable effect. Patients with high PRS had the greatest absolute risk reduction with a number needed to treat of 12 to prevent one cardiovascular death over 5 years. This novel polygenic prediction model identified people with diabetes at low and high risk of complications and improved targeting those at greater benefit from intensive therapy while avoiding unnecessary intensification in low-risk subjects.

scholarly journals Identification of prognostic gene signature associated with microenvironment of lung adenocarcinoma

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8128 ◽  
Author(s):  
Cheng Yue ◽  
Hongtao Ma ◽  
Yubai Zhou
Keyword(s):  
High Risk ◽  
Lung Adenocarcinoma ◽  
Prognostic Model ◽  
Cox Regression ◽  
Risk Group ◽  
Expression Profiles ◽  
Gene Signature ◽  
Low Risk ◽  
Differentially Expressed ◽  
Lasso Regression

Background Lung cancer has the highest morbidity and mortality worldwide, and lung adenocarcinoma (LADC) is the most common pathological subtype. Accumulating evidence suggests the tumor microenvironment (TME) is correlated with the tumor progress and the patient’s outcome. As the major components of TME, the tumor-infiltrated immune cells and stromal cells have attracted more and more attention. In this study, differentially expressed immune and stromal signature genes were used to construct a TME-related prognostic model for predicting the outcomes of LADC patients. Methods The expression profiles of LADC samples with clinical information were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) related to the TME of LADC were identified using TCGA dataset by Wilcoxon rank sum test. The prognostic effects of TME-related DEGs were analyzed using univariate Cox regression. Then, the least absolute shrinkage and selection operator (LASSO) regression was performed to reduce the overfit and the number of genes for further analysis. Next, the prognostic model was constructed by step multivariate Cox regression and risk score of each sample was calculated. Then, survival and Receiver Operating Characteristic (ROC) analyses were conducted to validate the model using TCGA and GEO datasets, respectively. The Kyoto Encyclopedia of Genes and Genomes analysis of gene signature was performed using Gene Set Enrichment Analysis (GSEA). Finally, the overall immune status, tumor purity and the expression profiles of HLA genes of high- and low-risk samples was further analyzed to reveal the potential mechanisms of prognostic effects of the model. Results A total of 93 TME-related DEGs were identified, of which 23 DEGs were up-regulated and 70 DEGs were down-regulated. The univariate cox analysis indicated that 23 DEGs has the prognostic effects, the hazard ratio ranged from 0.65 to 1.25 (p < 0.05). Then, seven genes were screened out from the 23 DEGs by LASSO regression method and were further analyzed by step multivariate Cox regression. Finally, a three-gene (ADAM12, Bruton Tyrosine Kinase (BTK), ERG) signature was constructed, and ADAM12, BTK can be used as independent prognostic factors. The three-gene signature well stratified the LADC patients in both training (TCGA) and testing (GEO) datasets as high-risk and low-risk groups, the 3-year area under curve (AUC) of ROC curves of three GEO sets were 0.718 (GSE3141), 0.646 (GSE30219) and 0.643 (GSE50081). The GSEA analysis indicated that highly expressed ADAM12, BTK, ERG mainly correlated with the activation of pathways involving in focal adhesion, immune regulation. The immune analysis indicated that the low-risk group has more immune activities and higher expression of HLA genes than that of the high-risk group. In sum, we identified and constructed a three TME-related DEGs signature, which could be used to predict the prognosis of LADC patients.

Chronic Lymphocytic Leukemia: Evaluation of Cytogenetic Markers as Prognostic Factors

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 4860-4860
Author(s):  
Jose Carda ◽  
Patricia Sousa ◽  
Patricia Olim ◽  
Emília Magalhães ◽  
Luis Rito ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Retrospective Study ◽  
High Risk ◽  
Chronic Lymphocytic Leukemia ◽  
Progressive Disease ◽  
Risk Group ◽  
Staging System ◽  
Lymphocytic Leukemia ◽  
Intermediate Risk

Abstract Abstract 4860 Backgroud: Chronic lymphocytic leukemia (CLL) is one of the most frequent chronic lymphoproliferative disorders in Europe. It is characterized by persistent monoclonal lymphocitosis with localized or generalized lymphadenopathy. Despite the initial clinical presentation, it has a heterogeneous natural history, with the majority of patients living 10–12 years, but with some patients dying rapidly, within 2–3 years of diagnosis. Beside clinical prognostic factors, novel cytogenetic markers are recognized to be useful in predicting disease free and overall survival in CLL. AIMS: In a retrospective study throughout 10 years (1999-2009), we analyzed the clinical and biological presentation and compared the evolution and survival of patients with B-CLL using different cytogenetic markers. METHODS: We identified 112 cases (63 males and 49 females) of B-CLL with cytogenetic study by fluorescence in situ hybridization (FISH). RESULTS: Amongst 112 patients, the male to female (M/F) ratio was 1.3:1 and the median age was 70 (43-96) years. At diagnosis, the median lymphocyte count was 15.5 G/L (5.4-173). Fifty five patients (49%) had lymphadenopathies and seventeen (15%) had splenomegaly and/or hepatomegaly at presentation. By the revised Rai staging system seventy (63%) patients were included in low risk group, thirty (27%) in intermediate risk group and twelve (10%) in high risk group. The expression of ZAP-70 and CD38 by flow citometry was performed in 75 patients and revealed 13 (17%) patients CD38+ and 12 (16%) ZAP70+. The study of chromosomal aberrations with FISH showed thirty six patients (32%) with no abnormality, thirty six (32%) with isolated 13q deletion, fifteen (14%) with 12 trisomy, twelve (11%) with 11q deletion and thirteen (11%) with 17p deletion. Forty (36%) patients showed progressive disease in a median time of sixteen months (0-120), thirteen with 13qdel, seven with 17pdel and five with 12 trisomy. After treatment two patients showed progressive disease, six maintain a stable disease and thirty two obtain a remission, nine in complete remission. The Overall Survival (OS) at ten years was 70%. By the revised Rai staging system the OS at ten years was 80% for low risk, 70% for intermediate risk and all the high risk patients died during follow up. The OS at five years for the del13q-, 12 trisomy, del11q- and del17p- was 90%, 88%, 58% and 60%, respectively. SUMMARY: Chronic lymphocytic leukemia is currently considered a chronic disorder with a favourable outcome, but with a variable evolution to progressive disease. This retrospective study allowed the characterization of patient with CLL in our department and the acknowledgement that our results are quite similar to the published data. Disclosures: No relevant conflicts of interest to declare.

The Glasgow whipple risk score to predict pancreas-specific complications after pancreaticoduodenectomy.

2015 ◽  
Vol 33 (3_suppl) ◽  
pp. 394-394
Author(s):  
Lavanniya Kumar Palani Velu ◽  
Vishnuvardhan Chandrabalan ◽  
Ross Carter ◽  
Colin McKay ◽  
Donald McMillan ◽  
...  
Keyword(s):  
High Risk ◽  
Serum Amylase ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Low Risk ◽  
Prolonged Stay ◽  
Increased Risk ◽  
Clinically Significant ◽  
Serum Crp

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.

Statistical Validation of the EORTC Prognostic Model for Malignant Pleural Mesothelioma Based on Three Consecutive Phase II Trials

2005 ◽  
Vol 23 (1) ◽  
pp. 184-189 ◽  
Author(s):  
Dean A. Fennell ◽  
Amit Parmar ◽  
Jonathan Shamash ◽  
Marie T. Evans ◽  
Michael T. Sheaff ◽  
...  
Keyword(s):  
High Risk ◽  
Phase Ii ◽  
Malignant Pleural Mesothelioma ◽  
Prognostic Model ◽  
Group Performance ◽  
Leukocyte Count ◽  
Low Risk ◽  
Pleural Mesothelioma ◽  
Phase Ii Trials ◽  
Three Phase

Purpose Malignant pleural mesothelioma (MPM) carries a poor prognosis due to chemoresistance. The European Organisation for Research and Treatment of Cancer (EORTC) prognostic model was reported to predict survival in MPM. Our retrospective analysis set out to test the validity of the model as a prognostic tool in patients treated in three phase II trials at St Bartholomew’s Hospital (London, United Kingdom) between 1999 and 2003. Patients and Methods A total of 145 patients were treated in three phase II trials; vinorelbine (VIN; 70 patients), vinorelbine/oxaliplatin (VO; 26 patients), and irinotecan/cisplatin/mitomycin C (IPM; 49 patients). Two subgroups, high-risk and low-risk, were defined by EORTC prognostic score (EPS). EPS was determined by a five-parameter model incorporating age, sex, histology, probability of diagnosis, and leukocyte count. An EPS cutoff of less than 1.27 (low risk) or more than 1.27 (high risk) was used to stratify Kaplan-Meier survival curves. Each of the EPS variables exhibited either trends or significant stratification of overall survival (OS). Results Multivariate analysis confirmed leukocyte count, Eastern Cooperative Oncology Group performance status, and sarcomatous histology as independent prognostic variables. EPS stratified OS in both individual and pooled trial datasets. No association between objective tumor response and EPS classification was identified by multinomial logistic regression. EPS stratified progression-free survival for the VO and IPM cohorts, but not for VIN. Conclusion This study validates the EPS system as a robust tool for stratifying small trials into low- and high-risk subgroups. EPS should facilitate patient selection and analysis in randomized clinical trials.

scholarly journals Prognostic Modeling of Patients with Metastatic Melanoma Based on Tumor Immune Microenvironment Characteristics

2021 ◽  
Author(s):  
Jing Liu ◽  
Ting Ye ◽  
Xue fang Zhang ◽  
Yong jian Dong ◽  
Wen feng Zhang ◽  
...  
Keyword(s):  
High Risk ◽  
Metastatic Melanoma ◽  
Prognostic Model ◽  
Cox Regression ◽  
Risk Group ◽  
Low Risk ◽  
Risk Scores ◽  
Immune Microenvironment ◽  
Immune Infiltration ◽  
Tumor Immune Microenvironment

Abstract Most of the malignant melanomas are already in the middle and advanced stages when they are diagnosed, which is often accompanied by the metastasis and spread of other organs.Besides, the prognosis of patients is bleak. The characteristics of the local immune microenvironment in metastatic melanoma have important implications for both tumor progression and tumor treatment. In this study, data on patients with metastatic melanoma from the TCGA and GEO datasets were selected for immune, stromal, and estimate scores, and overlapping differentially expressed genes (DEGs) were screened. A nine-IRGs prognostic model (ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22) was established by univariate COX regression, LASSO and multivariate COX regression. Receiver operating characteristic (ROC) curves were used to test the predictive accuracy of the model. Immune infiltration was analyzed by using CIBERSORT, Xcell and ssGSEA in high-risk and low-risk groups. The immune infiltration of the high-risk group was significantly lower than that of the low-risk group. Immune checkpoint analysis revealed that the expression of PDCD1, CTLA4, TIGIT, CD274, HAVR2 and LAG3 were significantly different in groups with different levels of risk scores. WGCNA analysis found that the yellow-green module contained seven genes (ALOX5AP, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22) from the nine-IRG prognostic model, of which the yellow-green module had the highest correlation with risk scores. The results of GO and KEGG suggested that the genes in the yellow-green module were mainly enriched in immune-related biological processes. Finally, we analyzed the prognostic ability and expression characteristics of ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22 in metastatic melanoma. Overall, a prognostic model for metastatic melanoma based on the characteristics of the tumor immune microenvironment was established, which was helpful for further studies.It could function well in helping people to understand the characteristics of the immune microenvironment in metastatic melanoma and to find possible therapeutic targets.

scholarly journals Assessment of the Progression Risk of Chronic Lymphocytic Leukemia

2019 ◽  
pp. 38-43
Author(s):  
D. V. Kravchenko ◽  
Yu. I. Yarets ◽  
V. N. Martinkov ◽  
A. E. Silin ◽  
A. I. Svirnovsky
Keyword(s):  
Risk Assessment ◽  
Chronic Lymphocytic Leukemia ◽  
Disease Progression ◽  
Risk Group ◽  
Lymphocytic Leukemia ◽  
Low Risk ◽  
Assessment Model ◽  
Laboratory Parameters ◽  
Β2 Microglobulin ◽  
Progression Risk

Objective: to identify the interconnection of laboratory parameters with different courses of chronic lymphocytic leukemia (CLL) and to develop a comprehensive model for the assessment of the risk of the disease progression. Material and methods. The study included 127 patients with CLL whose laboratory parameters were evaluated (general and biochemical blood tests, β2-microglobulin, thymidinekinase, tissue polypeptide antigen (TPA), immunophenotypic markers, and also NOTCH1 gene mutations). Results. For the prediction of the course of the disease the most informative were such markers as β2-microglobulin, thymidinekinase, ZAP-70, CD38, and TPA. Based on the obtained data, a model of the risk assessment for CLL progression with high sensitivity and specificity was developed. The progressive-free survival (PFS) was evaluated in two groups of the patients of different risk (low and high) assigned to them according to the prognostic model. In the patients from the low-risk group PFS was determined to be 60 months, and in the high-risk group it was equal to 29.4 months. And it was found out that the patients without progression at the time of inclusion in the study with the presence of mutations of the NOTCH1 gene had a shorter PFS in comparison with the patients without mutations, which may indicate a link between the mutations of the NOTCH1 gene and the unfavorable prognosis for the disease progression. Conclusion . The integrated application of the prognostic factors in the form of a CLL progression risk assessment model allows to stratify CLL patients into high and low risk groups and to predict the probability and progression rate at the time of the diagnosis and during the treatment.

scholarly journals Development and Validation of a Novel Hypoxia-Related Long Noncoding RNA Model With Regard to Prognosis and Immune Features in Breast Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Peng Gu ◽  
Lei Zhang ◽  
Ruitao Wang ◽  
Wentao Ding ◽  
Wei Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Prognostic Model ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Cox Regression Analysis

Background: Female breast cancer is currently the most frequently diagnosed cancer in the world. This study aimed to develop and validate a novel hypoxia-related long noncoding RNA (HRL) prognostic model for predicting the overall survival (OS) of patients with breast cancer.Methods: The gene expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. A total of 200 hypoxia-related mRNAs were obtained from the Molecular Signatures Database. The co-expression analysis between differentially expressed hypoxia-related mRNAs and lncRNAs based on Spearman’s rank correlation was performed to screen out 166 HRLs. Based on univariate Cox regression and least absolute shrinkage and selection operator Cox regression analysis in the training set, we filtered out 12 optimal prognostic hypoxia-related lncRNAs (PHRLs) to develop a prognostic model. Kaplan–Meier survival analysis, receiver operating characteristic curves, area under the curve, and univariate and multivariate Cox regression analyses were used to test the predictive ability of the risk model in the training, testing, and total sets.Results: A 12-HRL prognostic model was developed to predict the survival outcome of patients with breast cancer. Patients in the high-risk group had significantly shorter median OS, DFS (disease-free survival), and predicted lower chemosensitivity (paclitaxel, docetaxel) compared with those in the low-risk group. Also, the risk score based on the expression of the 12 HRLs acted as an independent prognostic factor. The immune cell infiltration analysis revealed that the immune scores of patients in the high-risk group were lower than those of the patients in the low-risk group. RT-qPCR assays were conducted to verify the expression of the 12 PHRLs in breast cancer tissues and cell lines.Conclusion: Our study uncovered dozens of potential prognostic biomarkers and therapeutic targets related to the hypoxia signaling pathway in breast cancer.

scholarly journals Development and validation of a ferroptosis-related prognostic model in pancreatic cancer

2021 ◽  
Author(s):  
Chen-jie Qiu ◽  
Xue-bing Wang ◽  
Zi-ruo Zheng ◽  
Chao-zhi Yang ◽  
Kai Lin ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
T Cell ◽  
High Risk ◽  
Risk Score ◽  
Prognostic Model ◽  
Immune Cell ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Immune Cell Infiltration

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.

Sign in / Sign up

Export Citation Format

Share Document