scholarly journals A Combination of CD302 gene Expression and 3-Months BCR-ABL1 Level Predicts Inferior Achievement of Deep Molecular Response in CP-CML Patients Treated with Imatinib

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 663-663
Author(s):  
Chung Hoow Kok ◽  
Liu Liu ◽  
David T Yeung ◽  
Verity A Saunders ◽  
Phuong Dang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Predictive Model ◽  
Research Funding ◽  
Validation Cohort ◽  
Molecular Response ◽  
Discovery Cohort ◽  
Independent Validation ◽  
Poor Risk ◽  
Achievement Rate ◽  
Deep Molecular Response

Introduction and Aim. Achievement of deep molecular response (DMR) is the prerequisite for treatment-free remission in chronic phase CML (CP-CML) patients (pts). Pts who fail to achieve early molecular response (BCR-ABL1 > 10% IS) at 3-months (mths), or have high ELTS score at diagnosis have inferior achievement of DMR. We and others have shown that the levels of NK-cell, T-cell, myeloid-derived suppressor cell, and neutrophils in the blood at diagnosis have an impact on DMR achievement. We hypothesized that Cluster of Differentiation (CD) (cell surface marker) gene expression might provide a surrogate marker to characterize immune cell composition. We aimed to identify pts who had a low probability of achieving DMR by 5 years (yrs) by combining 3-mths BCR-ABL1% and CD gene expression. This may enable clinicians to determine whether an individual patient is on a pathway towards DMR and potentially TFR or should be considered for a different therapeutic approach if TFR is the eventual goal. Methods. 119 blood samples from the imatinib-based TIDEL-II trial were subjected to transcriptomic microarray profiling. A total of 357 CD genes classified by the HUGO Gene Nomenclature Committee CD molecular gene group were assessed. We defined DMR as achieving MR4.5 (BCR-ABL1 < 0.0032%) at two consecutive time points. To construct a predictive model, the samples were randomly assigned to discovery and validation cohorts. Recursive partitioning and construction of a regression tree with tenfold cross-validation based on expression of 357 CD genes and 3-mths BCR-ABL1% were used as inputs in the discovery cohort. The performance was assessed based on accuracy of prediction of DMR by 5 yrs. The final model was validated using the independent validation cohort. All the analysis was performed using R statistical software. Results. Clinical variables (age, gender, ELTS, 3-mths BCR-ABL1%, MMR, and MR4.5) were well matched in the discovery (n=60) and independent validation cohort (n=59). The predictive model was constructed using the discovery cohort to reveal two risk groups: poor-risk (PR, 15% achieving MR4.5 at 5 yrs, n=19), and good-risk (GR, 88% achieving MR4.5 at 5 yrs, n=41) groups (Figure 1A-B). This model classified PR group by BCR-ABL1 ≥ 7.5% at 3 mths OR BCR-ABL1 < 7.5% at 3 months with high CD302 gene expression (≥7.9 log2 gene expression; top 15%) at diagnosis. GR group was defined as having both BCR-ABL1 < 7.5% and low CD302 gene expression (<7.9 log2 gene expression). These variables were chosen by the model based on accuracy performance in predicting DMR. CD302 is a C-type lectin receptor involved in cell adhesion and migration. It is expressed in myeloid populations as well as in blasts and leukemic stem cells (LSC) in AML. High expression of CD302 in PR pts may be a surrogate for increased LSC. The model was validated in the independent validation cohort. Pts identified as PR in the validation cohort had significantly lower 5-yrs MR4.5 achievement rate (14%, n=14) compared to those with GR (82%, n=45, p=0.0002, Figure 1C). We asked whether using the more conventional BCR-ABL1 10% cutoff instead of 7.5% in our model would give similar results, but the performance in predicting long-term DMR achievement was inferior: Pts predicted as PR with this criteria had ~2x higher achievement of DMR (e.g. 26% vs 14% using 3-mths BCR-ABL1 10% vs 7.5% cutoff respectively). ELTS score have been associated with the probability of DMR achievement. We compared the performance of ELTS in combination with 3-mths BCR-ABL1% by replacing CD302 gene expression with ELTS. The predictive accuracy was inferior. Pts with 3-mths BCR-ABL1 ≥7.5% OR BCR-ABL1 <7.5% with high/intermediate ELTS (PR-2) had about 3.3-3.5 fold higher DMR achievement rate than the PR group with CD302 in both discovery and validation cohorts (Figure 1D-E). In contrast, pts with 3-mths BCR-ABL1 <7.5% and low ELTS (GR-2) had approximately 1.1-1.2 fold lower DMR achievement rate than the GR group with CD302 in both discovery and validation cohorts (Figure 1D-E). Conclusion. We have constructed a predictive model for DMR achievement for pts who receive optimised frontline imatinib therapy. This model performs better than combining ELTS and 3-mths BCR-ABL1%. We postulate that this predictive model could enable identification of poor risk pts at 3 mths who would benefit from intensified therapeutic approaches to obtain eligibility for TFR and potentially optimal clinical outcome. Disclosures Yeung: Novartis: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Pfizer: Honoraria; Amgen: Honoraria. Hughes:Novartis: Other: Advisory Board and Symposia, Research Funding; BMS: Research Funding.

Abstract 19: Machine Learning Approach Identifies a Pattern of Gene Expression in Peripheral Blood Which Can Accurately Detect Ischemic Stroke

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Grant C O’Connell ◽  
Ashley B Petrone ◽  
Madison B Treadway ◽  
Connie S Tennant ◽  
Noelle Lucke-Wold ◽  
...  
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Ischemic Stroke ◽  
Whole Blood ◽  
Validation Cohort ◽  
Gene Expression Pattern ◽  
Discovery Cohort ◽  
Stroke Mimics ◽  
Independent Validation ◽  
Diagnostic Potential

Objective: The identification of stroke-associated biomarkers represents a means by which prehospital triage could be expedited to increase the probability of successful intervention. Thus, the objective of this work was to use high-throughput transcriptomics in combination with basic machine learning techniques to identify a pattern of gene expression in peripheral whole blood which could be used to identify acute ischemic stroke (AIS) in the acute care setting. Methods: A two-stage study design was used which included a discovery cohort and an independent validation cohort. In the discovery cohort, peripheral whole blood samples were obtained from 39 AIS patients upon emergency department admission, and from 24 neurologically asymptomatic controls. Microarray was used to measure the expression of over 22,000 genes and a pattern recognition technique known as genetic algorithm k-nearest neighbors (GA/kNN) identified a pattern of gene expression that optimally discriminated between AIS and controls. In an independent validation cohort, the gene expression pattern was tested for its ability to discriminate between 39 AIS patients and each of two different control groups, one consisting of 30 neurologically asymptomatic controls, and the other consisting of 15 stroke mimics, with gene expression levels being assessed by qRT-PCR. Results: In the discovery cohort, GA/kNN identified ten transcripts (ANTXR2, STK3, PDK4, CD163, MAL, GRAP, ID3, CTSZ, KIF1B, and PLXDC2) whose coordinate pattern of expression correctly identified 98.4% of subjects (97.4% sensitive, 100% specific). In the validation cohort, the same 10 transcripts correctly identified 95.6% of subjects when comparing AIS patients to asymptomatic controls (92.3% sensitive, 100% specific), and 96.3% of subjects when comparing AIS patients to stroke mimics (97.4% specific, 93.3% sensitive). Conclusion: These results demonstrate that a highly accurate RNA-based companion diagnostic for AIS is plausible using a relatively small number of markers. The pattern of gene expression identified in this study shows strong diagnostic potential, and warrants further evaluation to determine true clinical efficacy.

scholarly journals Combining Gene Expression Profiling and Artificial Intelligence to Diagnose B-Cell Non-Hodgkin Lymphoma

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 1476-1476
Author(s):  
Victor Bobée ◽  
Fanny Drieux ◽  
Vinciane Marchand ◽  
Vincent Sater ◽  
Liana Veresezan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Artificial Intelligence ◽  
B Cell ◽  
Board Of Directors ◽  
Expression Profiling ◽  
Marginal Zone ◽  
Validation Cohort ◽  
B Cell Lymphomas ◽  
Advisory Committees ◽  
Independent Validation

Introduction Non-Hodgkin B-cell lymphomas (B-NHLs) are a highly heterogeneous group of mature B-cell malignancies associated with very diverse clinical behaviors. They rely on the activation of different signaling pathways for proliferation and survival which might be amenable to targeted therapies, increasing the need for precision diagnosis. Unfortunately, their accurate classification can be challenging, even for expert hemato-pathologists, and secondary reviews recurrently differ from initial diagnosis. To address this issue we have developed a pan-B-NHL classifier based on a middle throughput gene expression assay coupled with a random forest algorithm. Material and Methods Five hundred ten B-NHL diagnosed according to the WHO criteria were studied, with 325 diffuse large B-cell lymphomas (DLBCL), 43 primary mediastinal B-cell lymphomas (PMBL), 55 follicular lymphomas (FL), 31 mantle cell lymphomas (MCL), 17 small lymphocytic lymphomas (SLL), 20 marginal zone lymphomas (MZL), 11 marginal zone lymphomas of mucosa-associated lymphoid tissue (MALT) and 8 lymphoplasmacytic lymphomas (LPL). To train and validate the predictor the samples were randomly split into a training (2/3) and an independent validation cohort (1/3). A panel of 137 genes was designed by purposely selecting the differentiation markers identified in the WHO classification for their capacity to provide diagnostic and prognostic information in NHLs. Gene expression profiles were generated by ligation dependent RT-PCR applied to RNA extracted from frozen or FFPE tissue and analyzed on a MiSeq sequencer. For analysis, the sequencing reads were de-multiplexed, aligned with the sequences of the LD-RTPCR probes and counted. Results were normalized using unique molecular indexes counts to correct PCR amplification biases. Results In DLBCL, unsupervised gene expression analysis retrieved the expected GCB, ABC and PMBL signatures (Fig A). These tumors also showed higher expressions of the KI67 (proliferation), CD68 and CD163 (tumor associated macrophages), and PD-L1/2 (immune response) markers. We also observed that the dual expression of MYC and BCL2 at the mRNA level significantly associates with inferior PFS and OS, independent from the International Prognostic Index and from the GCB/ABC cell-of-origin signature, validating the capacity of the assay to identify these highly aggressive lymphomas (Fig C). Overall, low-grade lymphomas were characterized by a significant T cell component. FLs associated with the GCB (BCL6, MYBL1, CD10 and LMO2) and Tfh (CD3, CD5, CD28, ICOS, CD40L, CXCL13) signatures. Other small B-cell lymphomas tended to overexpress activated B-cell markers (LIMD1, TACI, IRF4,FOXP1...), and the expected CD5, CD10, CD23 and CCND1 differential expressions in SLL, MCL and MZL were correctly retrieved (Fig B). Surprisingly, our analysis revealed that the Ie-Ce sterile transcript, expressed from the IGH locus during IgE isotype switching, is almost exclusively expressed by FLs, constituting one of the most discriminant markers for this pathology. We next trained a random forest classifier to discriminate the 7 principal subtypes of B-NHLs. The training cohort comprised 162 DLBCLs (ABC or GCB), 28 PMBL, 35 FLs (grade 1-3A), 21 MCLs, 12 SLLs, and 25 NHLs grouped into the MZL category (13 MZLs, 8 MALT and 4 LPLs). The independent validation series comprised 90 DLBCLs classified as GCB or ABC DLBCLs by the Lymph2Cx assay, 15 PMBLs, 12 FLs (grade 1-3A), 10 MCLs, 5 SLLs and 14 MZLs (7 MZL, 3 MALT and 4 LPL). The RF algorithm classified all cases of the training series into the expected subtype, as well as 94.5% samples of the independent validation cohort (Fig D). For ABC and GCB DLBCLs, the concordance with the Lymph2Cx assay in the validation cohort was 94.3%. Conclusion We have developed a comprehensive gene expression based solution which allows a systematic evaluation of multiple diagnostic and prognostic markers expressed by the tumor and by the microenvironment in B-NHLs. This assay, which does not require any specific platform, could be implemented in complement to histology in many diagnostic laboratories and, with the current development of targeted therapies, enable a more accurate and standardized B-NHL diagnosis. Together, our data illustrate how the integration of gene expression profiling and artificial intelligence can increase precision diagnosis in cancers. Figure Disclosures Oberic: Takeda: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria; Roche: Membership on an entity's Board of Directors or advisory committees. Haioun:Miltenyi: Honoraria; Takeda: Honoraria; Servier: Honoraria; F. Hoffmann-La Roche Ltd: Honoraria; Novartis: Honoraria; Amgen: Honoraria; Celgene: Honoraria; Gilead: Honoraria; Janssen: Honoraria. Salles:Roche, Janssen, Gilead, Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Amgen: Honoraria, Other: Educational events; BMS: Honoraria; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis, Servier, AbbVie, Karyopharm, Kite, MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Epizyme: Consultancy, Honoraria. Tilly:roche: Membership on an entity's Board of Directors or advisory committees; servier: Honoraria; merck: Honoraria; Roche: Consultancy; Celgene: Consultancy, Research Funding; Astra-Zeneca: Consultancy; Karyopharm: Consultancy; BMS: Honoraria; Janssen: Honoraria; Gilead: Honoraria. Jardin:celgene: Honoraria; roche: Honoraria; amgen: Honoraria; Servier: Honoraria; janssen: Honoraria.

scholarly journals Second Imatinib Discontinuation Outcomes in Patients Regaining Durable Deep Molecular Response in the Korean Imatinib Discontinuation Study; KID Study

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 51-52
Author(s):  
Sung-Eun Lee ◽  
Joon Seong Park ◽  
Young Rok Do ◽  
Sung-Hyun Kim ◽  
Dae Young Zang ◽  
...  
Keyword(s):  
Prospective Study ◽  
Board Of Directors ◽  
Median Duration ◽  
Research Funding ◽  
Kinase Inhibitor ◽  
Molecular Response ◽  
Close Monitoring ◽  
Advisory Committees ◽  
Deep Molecular Response ◽  
Multicenter Prospective Study

Backgroud: Although multiple trials have shown that stopping tyrosine kinase inhibitor (TKI) treatment can be employed in CP CML patients with sustained deep molecular response (DMR) after enough TKI therapy, they emphasized the need for close monitoring because about 50-70% of patients experienced molecular relapse. However, most patients with molecular recurrence regain their initial molecular level after restarting TKI therapy. Aims: In this study, we analyzed second imatinib (IM) discontinuation outcomes in patients regaining durable DMR in the Korean multicenter prospective study (Korean Imatinib Discontinuation Study; KID Study) Methods: CP CML patients who were treated with IM for more than 3 years and maintained DMR for at least 2 years were eligible for the Korean multicenter prospective study and in cases of MMR loss on 2 consecutive assessments, IM treatment was re-introduced. After IM resumption, the molecular response was evaluated every month until re-achievement of MMR and every 3 months thereafter. The second stop was permitted in the patients who were in second DMR for at least 2 years. Results: Among the patients who maintained a second DMR for at least 2 years after IM resumption, 23 patients entered into a second IM stop. Prior to first discontinuation, the median duration of IM therapy was 73.2 months (range, 38.4-133.2 months) and the duration of sustained UMRD was 38.4 months (range, 24-102 months). After first attempt of IM discontinuation, they relapsed after a median duration of 3.7 months (range, 1.8-20.8 months) and re-achieved UMRD at a median of 5.8 months (range, 1.7-12.1 months) after IM resumption. After sustaining a second DMR for a median of 26.3 months, IM therapy discontinued for a second time. With a median follow-up of 29.5 months (range, 9-63 months) since second IM stop, 15/23 patients (65%) lost MMR after a median 2.9 months (range, 1.8-30.7 months), which was similar to those of the first IM discontinuation [median 3.7 (range, 1.8-20.8 months)]. The patients who lost MMR were retreated with IM for a median of 24.5 months (range, 1.2-49.7 months); 14 patients re-achieved MMR and one patient was in therapy for 1.2 months. Conclusion: Our data demonstrated that a second attempt might be possible and the median time to MMR loss after second discontinuation was similar to those of the first discontinuation. Further studies on the predictors to select patients for a trial of second TFR and novel strategies will be warranted. Disclosures Kim: Takeda: Research Funding; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; ILYANG: Consultancy, Honoraria, Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Sun Pharma.: Research Funding.

Identification and validation of a potent multi-mRNA signature for the prediction of early relapse in hepatocellular carcinoma

2019 ◽  
Vol 40 (7) ◽  
pp. 840-852 ◽  
Author(s):  
Jie Cai ◽  
Ying Tong ◽  
Lifeng Huang ◽  
Lei Xia ◽  
Han Guo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Messenger Rna ◽  
Validation Cohort ◽  
Expression Profiles ◽  
External Validation ◽  
Early Recurrence ◽  
Discovery Cohort ◽  
Early Relapse ◽  
Staging Systems

Abstract Early recurrence of hepatocellular carcinoma (HCC) is implicated in poor patient survival and is the major obstacle to improving prognosis. The current staging systems are insufficient for accurate prediction of early recurrence, suggesting that additional indicators for early recurrence are needed. Here, by analyzing the gene expression profiles of 12 Gene Expression Omnibus data sets (n = 1533), we identified 257 differentially expressed genes between HCC and non-tumor tissues. Least absolute shrinkage and selection operator regression model was used to identify a 24-messenger RNA (mRNA)-based signature in discovery cohort GSE14520. With specific risk score formula, patients were divided into high- and low-risk groups. Recurrence-free survival within 2 years (early-RFS) was significantly different between these two groups in discovery cohort [hazard ratio (HR): 7.954, 95% confidence interval (CI): 4.596–13.767, P < 0.001], internal validation cohort (HR: 8.693, 95% CI: 4.029–18.754, P < 0.001) and external validation cohort (HR: 5.982, 95% CI: 3.414–10.480, P < 0.001). Multivariable and subgroup analyses revealed that the 24-mRNA-based classifier was an independent prognostic factor for predicting early relapse of patients with HCC. We further developed a nomogram integrating the 24-mRNA-based signature and clinicopathological risk factors to predict the early-RFS. The 24-mRNA-signature-integrated nomogram showed good discrimination (concordance index: 0.883, 95% CI: 0.836–0.929) and calibration. Decision curve analysis demonstrated that the 24-mRNA-signature-integrated nomogram was clinically useful. In conclusion, our 24-mRNA signature is a powerful tool for early-relapse prediction and will facilitate individual management of HCC patients.

scholarly journals Gene Expression Patterns Distinguish Mortality Risk in Patients with Postsurgical Shock

2020 ◽  
Vol 9 (5) ◽  
pp. 1276
Author(s):  
Pedro Martínez-Paz ◽  
Marta Aragón-Camino ◽  
Esther Gómez-Sánchez ◽  
Mario Lorenzo-López ◽  
Estefanía Gómez-Pesquera ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Mortality Risk ◽  
Validation Cohort ◽  
Expression Patterns ◽  
Gene Expression Signature ◽  
Mrna Levels ◽  
Characteristic Analysis ◽  
Discovery Cohort ◽  
Risk Of Death

Nowadays, mortality rates in intensive care units are the highest of all hospital units. However, there is not a reliable prognostic system to predict the likelihood of death in patients with postsurgical shock. Thus, the aim of the present work is to obtain a gene expression signature to distinguish the low and high risk of death in postsurgical shock patients. In this sense, mRNA levels were evaluated by microarray on a discovery cohort to select the most differentially expressed genes between surviving and non-surviving groups 30 days after the operation. Selected genes were evaluated by quantitative real-time polymerase chain reaction (qPCR) in a validation cohort to validate the reliability of data. A receiver-operating characteristic analysis with the area under the curve was performed to quantify the sensitivity and specificity for gene expression levels, which were compared with predictions by established risk scales, such as acute physiology and chronic health evaluation (APACHE) and sequential organ failure assessment (SOFA). IL1R2, CD177, RETN, and OLFM4 genes were upregulated in the non-surviving group of the discovery cohort, and their predictive power was confirmed in the validation cohort. This work offers new biomarkers based on transcriptional patterns to classify the postsurgical shock patients according to low and high risk of death. The results present more accuracy than other mortality risk scores.

scholarly journals A Prognostic Gene-Expression Signature and Risk Score for Meningioma Recurrence After Resection

Neurosurgery ◽  
2020 ◽  
Vol 88 (1) ◽  
pp. 202-210 ◽  
Author(s):  
William C Chen ◽  
Harish N Vasudevan ◽  
Abrar Choudhury ◽  
Melike Pekmezci ◽  
Calixto-Hope G Lucas ◽  
...  
Keyword(s):  
Gene Expression ◽  
Risk Score ◽  
Gene Expression Analysis ◽  
Validation Cohort ◽  
Gene Expression Signature ◽  
Gene Signature ◽  
Who Grade ◽  
Independent Validation ◽  
Meningioma Recurrence ◽  
Targeted Gene Expression

Abstract BACKGROUND Prognostic markers for meningioma are needed to risk-stratify patients and guide postoperative surveillance and adjuvant therapy. OBJECTIVE To identify a prognostic gene signature for meningioma recurrence and mortality after resection using targeted gene-expression analysis. METHODS Targeted gene-expression analysis was used to interrogate a discovery cohort of 96 meningiomas and an independent validation cohort of 56 meningiomas with comprehensive clinical follow-up data from separate institutions. Bioinformatic analysis was used to identify prognostic genes and generate a gene-signature risk score between 0 and 1 for local recurrence. RESULTS We identified a 36-gene signature of meningioma recurrence after resection that achieved an area under the curve of 0.86 in identifying tumors at risk for adverse clinical outcomes. The gene-signature risk score compared favorably to World Health Organization (WHO) grade in stratifying cases by local freedom from recurrence (LFFR, P &lt; .001 vs .09, log-rank test), shorter time to failure (TTF, F-test, P &lt; .0001), and overall survival (OS, P &lt; .0001 vs .07) and was independently associated with worse LFFR (relative risk [RR] 1.56, 95% CI 1.30-1.90) and OS (RR 1.32, 95% CI 1.07-1.64), after adjusting for clinical covariates. When tested on an independent validation cohort, the gene-signature risk score remained associated with shorter TTF (F-test, P = .002), compared favorably to WHO grade in stratifying cases by OS (P = .003 vs P = .10), and was significantly associated with worse OS (RR 1.86, 95% CI 1.19-2.88) on multivariate analysis. CONCLUSION The prognostic meningioma gene-expression signature and risk score presented may be useful for identifying patients at risk for recurrence.

Prediction for Sustained Deep Molecular Response of BCR-ABL Levels in Patients with Chronic Myeloid Leukemia in Chronic Phase (CML-CP)

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 1224-1224
Author(s):  
Koji Sasaki ◽  
Hagop M. Kantarjian ◽  
Susan O'Brien ◽  
Farhad Ravandi ◽  
Marina Konopleva ◽  
...  
Keyword(s):  
Research Funding ◽  
Chronic Phase ◽  
High Dose ◽  
Molecular Response ◽  
Regression Equations ◽  
Transcript Levels ◽  
Deep Molecular Response ◽  
Best Fit ◽  
Time Point

Abstract Introduction Initial treatment with tyrosine kinase inhibitors (TKI) induces excellent response in the majority of patients with CML-CP. Current guidelines recommend periodic monitoring of BCR-ABL1 levels to monitor response. During the course of treatment, recognizing early predictors of deeper response and longer-term outcomes can help guide treatment. This is relevant not only at the specified fixed time point typically reported (i.e., 3, 6, 12 months) but at any other time point when an assessment is made. Achievement of sustained deep molecular response is a goal of increasing relevance as it opens the possibility of treatment discontinuation. The objective of this study is suggest optimal BCR-ABL transcript levels at any given time, and to suggest a prediction model for sustained molecular response 4.5 (MR4.5) (BCR-ABL ≤0.0032%) for at least 2 years according to BCR-ABL levels achieved within the first 12 months of TKI therapy. Methods Response data for 630 patients with newly diagnosed CML-CP in consecutive prospective clinical trials of frontline imatinib (n=73; NCT00048672), high-dose imatinib (n=208; NCT00038469 and NCT00050531), nilotinib (n=148; NCT00129740), dasatinib (n=150; NCT00254423), and ponatinib (n=51; NCT01570868) were analyzed. Real-time PCR analysis was performed at approximately 3 month intervals during the first year and 6 month intervals thereafter. The "best fit average" molecular response was defined by robust linear regression models, with which the estimated molecular level in patients with complete cytogenetic response (CCyR) within 1 year, major molecular response (MMR) within 1 year, and sustained MR4.5 at any point were defined. The acceptable molecular response was defined by quantile regression for the 95th percentile, with which the worst 5% BCR-ABL levels in patients with CCyR within 1 year, MMR within 1 year, and sustained MR4.5 at any point were identified. Results In 630 patients, 2512 data points of BCR-ABL levels within 1 year of TKI were identified. The median follow-up for the entire cohort was 106 months (range, 0.3-177.8). The regression equations for best fit average PCR for CCyR within 1 year was Log10(PCR) = -0.2159 x (Months) + 0.1957; for MMR within 1 year, Log10(PCR) = -0.2304 x (Months) + 0.1046; for sustained MR4.5 at any point, Log10(PCR) = -0.2154 x Months -0.1161. The regression equations for acceptable PCR for CCyR within 1 year was Log10(PCR) = -0.15796 x (Months) + 1.54839; for MMR within 1 year, Log10(PCR) = -0.20999 x (Months) + 1.54839; for sustained MR4.5, Log10(PCR) = -0.22476 x (Months) + 1.50516 (Figure 1). The best fit average PCR (i.e., estimated levels achieved by the average responder in each category) for CCyR within 1 year was 0.353%, 0.079%, 0.017%, and 0.004% at 3, 6, 9, and 12 months, respectively; for MMR within 1 year was 0.259%, 0.053%, 0.011%, and 0.002% at 3, 6, 9, and 12 months, respectively; for sustained MR4.5 at any point was 0.295%, 0.067%, 0.015%, and 0.003% at 3, 6, 9, and 12 months, respectively (Table 1). To achieve CCyR within 1 year, the acceptable PCR (i.e., levels achieved by 95% of all those who eventually reach the said endpoint) response was 11.872%, 3.987%, 1.339%, and 0.450% at 3, 6, 9, and 12 months, respectively; to achieve MMR within 1 year, 8.287%, 1.943%, 0.455%, and 0.107% at 3, 6, 9, and 12 months, respectively; to achieve sustained MR4.5 at any time, 6.774%, 1.434%, 0.304%, and 0.064% at 3, 6, 9, and 12 months, respectively. Of 289 patients who eventually achieved sustained MR4.5, 288 (99%) achieved CCyR within 1 year; 268 (93%), MMR within 1 year; 201 (70%), MR4 within 1 year; 162 (56%), MR4.5 within 1 year; 72 (25%), CMR within 1 year. Of 359 patients who achieved MMR within 1 year with a minimum follow-up of 48 months, 256 (71%) achieved sustained MR4.5; of 180 patients who achieved MR4.5 within 1 year, 151 (84%); of 72 patients who achieved CMR within 1 year, 65 (90%). Conclusion Proper interpretation of early transcript levels at any time during the course of therapy may help predict later response and outcome. Such models can be built to guide therapy for patients in a continuous basis. To achieve sustained MR4.5 for at least 2 years, deeper responses are required at each time point. Our model proposes optimal values that predict the highest probability of reaching such goal. At a minimum, CCyR within 1 year is required to achieve sustained MR4.5. Disclosures Kantarjian: Bristol-Myers Squibb: Research Funding; ARIAD: Research Funding; Amgen: Research Funding; Pfizer Inc: Research Funding; Delta-Fly Pharma: Research Funding; Novartis: Research Funding. Ravandi:Seattle Genetics: Consultancy, Honoraria, Research Funding; BMS: Research Funding. Konopleva:AbbVie: Research Funding; Genentech: Research Funding. Wierda:Novartis: Research Funding; Abbvie: Research Funding; Acerta: Research Funding; Gilead: Research Funding; Genentech: Research Funding. Daver:Ariad: Research Funding; Karyopharm: Honoraria, Research Funding; Sunesis: Consultancy, Research Funding; BMS: Research Funding; Kiromic: Research Funding; Otsuka: Consultancy, Honoraria; Pfizer: Consultancy, Research Funding. Jabbour:ARIAD: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Research Funding; BMS: Consultancy.

scholarly journals Outcome of 472 Chronic Myeloid Leukemia Patients Treated with Frontline Nilotinib: A Gimema CML WP Analysis

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 458-458 ◽  
Author(s):  
Gabriele Gugliotta ◽  
Fausto Castagnetti ◽  
Massimo Breccia ◽  
Alessandra Iurlo ◽  
Mariella D'Adda ◽  
...  
Keyword(s):  
Board Of Directors ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Age Groups ◽  
Advisory Board ◽  
Molecular Response ◽  
First Line ◽  
Advisory Committees ◽  
Deep Molecular Response ◽  
First Line Treatment

Abstract BACKGROUND: In chronic phase (CP) chronic myeloid leukemia (CML) nilotinib showed better efficacy compared to imatinib. The higher rates of deep molecular response with nilotinib may translate in more patients (pts) eligible for treatment discontinuation. On the other hand, cardiovascular toxicity may limit nilotinib use in selected groups of pts (e.g. elderly pts). AIM: To investigate the efficacy and safety, overall and according to age, of first-line treatment with nilotinib in CML pts. METHODS: We analyzed response rates, events and outcome of 472 pts ≥ 18 y of age with CP CML, enrolled in clinical trials of the GIMEMA CML WP with nilotinib frontline. Pts were treated with: nilotinib 300 mg BID (n=276); nilotinib 400 mg BID (n=73); rotation of nilotinib 400 mg BID / imatinib 400 mg OD (3-month periods for each drug)(n=123). The median follow-up was 36 (3-82) months. Pts were further analyzed considering 3 age groups: 18-39 y (98 pts); 40-59 y (217 pts); and ≥ 60 y (157 pts). Definitions: Major molecular response (MR3): BCR-ABL≤0.1% (IS), with > 10.000 ABL copies; MR4: BCR-ABL≤0.01% (IS), with > 10.000 ABL copies. Events: permanent discontinuation of nilotinib for any reason, including adverse events, progression to accelerated/blast phase (AP/BP), or deaths. Arterial thrombotic events (ATEs): peripheral arterial obstructive disease, acute coronary syndrome, chronic ischemic heart disease, significant carotid stenosis and ischemic stroke, or other significant ischemic events. RESULTS: Overall, the cumulative incidences of MR3 by 12, 24, and 36 months were 75, 88, and 93%, respectively. The cumulative incidences of MR4 by 12, 24, and 36 months were 38, 63, and 76%, respectively. Events leading to permanent nilotinib discontinuation occurred in 132 (27.9%) pts. ATEs occurred in 33 (7% of pts) ATEs, corresponding to 19.7 ATEs/1000 pt-y. Fifteen (3.1%) pts progressed to AP/BP. Overall, 23 (4.9%) pts died, 11 of them after progression to AP/BP. The estimated 5-year OS was 93%. The sub-analysis according to age showed that: MR3 and MR4 rates were similar across the 3 age groups (cumulative incidences of MR4 by 24 months were 55, 62, and 70% in pts 18-39 y, 40-59 y, and ≥ 60 y, respectively; p=0.25). Progressions to AP/BP were: 6.1% in pts 18-39 y, 2.8% in pts 40-59 y, and 1.9% in pts ≥ 60 y. ATEs were: 0 in pts 18-39y, 4.1% (11.7/1000 pt-years) in pts 40-59 y, and 15.3% (41.3/1000 pt-years) in pts ≥ 60 y (no difference in ATEs was found between pts 60-69 y and those ≥ 70 y). The 5-y OS was 91, 97, and 89% in pts 18-39 y, 40-59 y, and ≥ 60 y, respectively (p=0.065). Death was always leukemia-related in pts 18-39 y (100%), while it was mainly leukemia-unrelated (75%) in pts ≥ 60 y. SUMMARY/CONCLUSION: Nilotinib as first-line treatment of newly diagnosed CP CML pts showed high rates of deep molecular responses, few progressions to AP/BP, and a high OS. Deep molecular response were similar in all age groups; as expected, ATEs were more frequent in pts > 60 y. These data suggest that: in pts > 60 y, the high efficacy of nilotinib should be weighed against its potential toxicity; in pts < 60 years, nilotinib may be a very good choice, with high efficacy and low toxicity. Disclosures Gugliotta: Novartis: Honoraria; Pfizer: Honoraria; Incyte: Honoraria; Bristol-Myers Squibb: Honoraria. Castagnetti:Bristol Myers Squibb: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria. Breccia:Novartis: Honoraria; Pfizer: Honoraria; BMS: Honoraria; Incyte: Honoraria. Levato:Novartis: Other: Advisory board. Abruzzese:Pfizer: Consultancy; Ariad: Consultancy; Novartis: Research Funding; BMS: Consultancy. Soverini:Bristol Myers Squibb: Consultancy; Incyte Biosciences: Consultancy; Novartis: Consultancy. Foà:NOVARTIS: Speakers Bureau; JANSSEN: Other: ADVISORY BOARD, Speakers Bureau; CELTRION: Other: ADVISORY BOARD; INCYTE: Other: ADVISORY BOARD; CELGENE: Other: ADVISORY BOARD, Speakers Bureau; ABBVIE: Other: ADVISORY BOARD, Speakers Bureau; ROCHE: Other: ADVISORY BOARD, Speakers Bureau; GILEAD: Speakers Bureau; AMGEN: Other: ADVISORY BOARD. Cavo:AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees. Pane:Novartis: Research Funding, Speakers Bureau; BMS: Speakers Bureau; AMGEN: Speakers Bureau.

scholarly journals Discovery of a simple two-gene expression biomarker in whole blood predictive of the need for treatment escalation in inflammatory bowel disease

2021 ◽  
Author(s):  
Jan K Nowak ◽  
Rahul Kalla ◽  
Alex T Adams ◽  
Jonas Halfvarson ◽  
Jack Satsangi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Inflammatory Bowel Disease ◽  
Bowel Disease ◽  
Validation Cohort ◽  
Inception Cohort ◽  
Treatment Intensification ◽  
Discovery Cohort ◽  
Inflammatory Bowel ◽  
Treatment Escalation ◽  
Risk Of Treatment

Background and aims: The IBD-Character consortium has recruited large internationally based inception cohorts of treatment-naive inflammatory bowel disease (IBD) patients, providing a unique resource to derive a simple transcriptome signature in the field of prognostication. Methods: The discovery cohort (n=160) was recruited in Norway, Sweden and Spain. The replication inception cohort from the United Kingdom (n=97) was followed-up for a mean (SD) of 350 (228) days. Treatment escalation was formally defined as the need for a biologic agent, ciclosporin and/or surgery, instituted for disease flare after initial remission, or colectomy during the index admission for ulcerative colitis. Whole blood RNA was subject to paired-end sequencing. In the discovery cohort a simple procedure was applied, which exploited differences of transcript ratios. The ten top performing ratios were tested using Cox regression models in the validation cohort. Results: Newly diagnosed IBD patients with high CACNA1E/LRRC42 expression ratio had an increased risk of treatment intensification (validation cohort: HR=19.3, 95%CI 2.6-143.9, p=0.000005; AUC 0.76, 95%CI 0.66-0.86). In 51 patients with CRP < 3.5 mg/L, CACNA1E/LRRC42 still predicted escalation (HR=10.4; 95%CI 1.2-86.5, p=0.007). The second best performing transcript ratio was CACNA1E/CEACAM21 yielding a HR of 10.9 (95%CI 2.5-46.7, p=0.00002) and an AUC of 0.76 (95%CI 0.65-0.86) in the validation cohort. Conclusion: Transcriptomic profiling of an IBD inception cohort identified gene expression ratios CACNA1E/LRRC42 and CACNA1E/CEACAM21 as prognostic biomarkers. These were validated in a replication cohort as strongly associated with short- and long-term risk of treatment intensification and may provide valuable information in clinical decision-making.

scholarly journals Identification and Verification of a 17 Immune-Related Gene Pair Prognostic Signature for Colon Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Qianshi Zhang ◽  
Zhen Feng ◽  
Yongnian Zhang ◽  
Shasha Shi ◽  
Yu Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colon Cancer ◽  
Poor Prognosis ◽  
Validation Cohort ◽  
Risk Group ◽  
High Risk Group ◽  
Related Gene ◽  
Prognostic Signature ◽  
Discovery Cohort ◽  
Immune Related Gene

Background. Colon cancer (CC) is a malignant tumor with a high incidence and poor prognosis. Accumulating evidence shows that the immune signature plays an important role in the tumorigenesis, progression, and prognosis of CC. Our study is aimed at establishing a novel robust immune-related gene pair signature for predicting the prognosis of CC. Methods. Gene expression profiles and corresponding clinical information are obtained from two public data sets: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO, GSE39582). We screened out immune-related gene pairs (IRGPs) associated with prognosis in the discovery cohort. Lasso-Cox proportional hazard regression was used to develop the best prognostic signature model. According to this, the patients in the validation cohort were divided into high immune-risk group and low immune-risk group, and the prediction ability of the signature model was verified by survival analysis and independent prognostic analysis. Results. A total of 17 IRGPs composed of 26 IRGs were used to construct a prognostic-related risk scoring model. This model accurately predicted the prognosis of CC patients, and the patients in the high immune-risk group indicated poor prognosis in the discovery cohort and validation cohort. Besides, whether in univariate or multivariate analysis, the IRGP signature was an independent prognostic factor. T cell CD4 memory resting in the low-risk group was significantly higher than that in the high-risk group. Functional analysis showed that the biological processes of the low-risk group included “TCA cycle” and “RNA degradation,” while the high-risk group was enriched in the “CAMs” and “focal adhesion” pathways. Conclusion. We have successfully established a signature model composed of 17 IRGPs, which provides a novel idea to predict the prognosis of CC patients.

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