Quantitative Gene Expression Analysis of Surrogate Markers for Genetic Risk Groups and Survival in CLL

Abstract In CLL, a variety of surrogate markers for individual genetic features, mostly the VH mutation status, were proposed from gene expression analyses. However, their detailed relation to specific genetic subsets such as V3-21 usage, del11q22-q23 (11q−), and del17p13 (17p−), and their prognostic value in relation to established factors is not elucidated yet. Gene expression markers (ADAM29, ATM, CLLU1, DMD, GLO1, HS1, KIAA0977, LPL, MGC9913, PCDH9, PEG10, SEPT10, TCF7, TP53, Vimentin, ZAP-70, ZNF2) were evaluated using real-time quantitative RT-PCR (RQ-PCR) in purified samples of 151 patients. VH sequencing and FISH screening for genomic aberrations were carried out for all cases, survival information was available for 133 cases. Logistic regression was performed to test the predictive value of gene expression for genetic risk groups, Cox proportional hazards statistics for survival analysis. VH mutation status was best assigned by LPL and ZAP70, followed by TCF7, a marker with a characteristic overexpression in VH mutated CLL patients (correct VH prediction in 83%, 83%, and 75% of the patients, respectively). A similar rate of correct VH assignments was achieved in the subgroup of patients with 11q− or 17p− when using these markers (88%, 86%, and 79%, respectively). In contrast to LPL and TCF7, most of the patients with V3-21 usage were recognized as risk patients by ZAP70 independently of the VH status. Therefore, ZAP70 yielded the best results for the overall recognition of patients with a genetic risk constellation (VH unmutated or V3-21 usage or 11q− or 17p−). Comparison of ZAP-70 determination by RQPCR and flow cytometry was performed for 72 patients and revealed 30% of discordant cases. Thereof, the majority was VH unmutated (including several cases with 11q− or 17p−) showing ZAP-70 negativity by FACS and positivity by RQ-PCR. In multivariate analysis of time to first treatment (TFT), ADAM29 was an independent prognostic factor besides the VH status and Binet stage. In overall survival analysis including the gene expression variables only, LPL was the strongest predictor for overall survival. When genetic and clinical factors were added to this analysis, V3-21 usage, 17p−, age, binet stage, and expression of ATM, ADAM29, SEPT10, and TCL1 were identified as significant prognostic factors. In conclusion, novel gene expression markers allow screening for patients at risk but can not fully substitute for the genetic factors, which should therefore at present remain the basis for risk stratification approaches. Some of the novel markers appear to have a prognostic relevance independently of the established factors, which points to relevant biologic and clinical implications demanding further investigation.

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A novel nomogram to predict the overall survival in esthesinoeroblastoma

10.21203/rs.3.rs-22163/v2 ◽

2020 ◽

Author(s):

Lijie Jiang ◽

Tengjiao Lin ◽

Yu Zhang ◽

Wenxiang Gao ◽

Jie Deng ◽

...

Keyword(s):

Overall Survival ◽

Proportional Hazards ◽

Proportional Hazards Model ◽

Validation Cohort ◽

Risk Groups ◽

Cox Proportional Hazards ◽

Cox Proportional Hazards Model ◽

Cancer Center ◽

P Value ◽

Training Cohort

Abstract Background Increasing evidence indicates that the pathology and the modified Kadish system have some influence on the prognosis of esthesioneuroblastoma (ENB). However, an accurate system to combine pathology with a modified Kadish system has not been established. Methods This study aimed to set up and evaluate a model to predict overall survival (OS) accurately in ENB, including clinical characteristics, treatment and pathological variables. We screened the information of patients with ENB between January 1, 1976, and December 30, 2016 from the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) program as a training cohort. The validation cohort consisted of patients with ENB at Sun Yat-sen University Cancer Center and The First Affiliated Hospital of Sun Yat-sen University in the same period, and 87 patients were identified. The Pearson’s chi-squared test was used to assess significance of clinicopathological and demographic characteristics. We used the Cox proportional hazards model to examine univariate and multivariate analyses. The model coefficients were used to calculate the Hazard ratios (HR) with 95% confidence intervals (CI). Prognostic factors with a p- value < 0.05 in multivariate analysis were included in the nomogram. The concordance index (c-index) and calibration curve were used to evaluate the predictive power of the nomogram. Results The c-index of training cohort and validation cohort are 0.737 (95% CI, 0.709 to 0.765) and 0.791 (95% CI, 0.767 to 0.815) respectively. The calibration curves revealed a good agreement between the nomogram prediction and actual observation regarding the probability of 3-year and 5-year survival. We used a nomogram to calculate the 3-year and 5-year growth probability and stratified patients into three risk groups. Conclusions The nomogram provided the risk group information and identified mortality risk and can serve as a reference for designing a reasonable follow-up plan.

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A novel nomogram to predict the overall survival in esthesinoeroblastoma

10.21203/rs.3.rs-22163/v3 ◽

2020 ◽

Author(s):

Lijie Jiang ◽

Tengjiao Lin ◽

Yu Zhang ◽

Wenxiang Gao ◽

Jie Deng ◽

...

Keyword(s):

Overall Survival ◽

Proportional Hazards ◽

Proportional Hazards Model ◽

Validation Cohort ◽

Risk Groups ◽

Cox Proportional Hazards ◽

Cox Proportional Hazards Model ◽

Cancer Center ◽

Training Cohort ◽

Chi Squared

Abstract Background Increasing evidence indicates that the pathology and the modified Kadish system have some influence on the prognosis of esthesioneuroblastoma (ENB). However, an accurate system to combine pathology with a modified Kadish system has not been established. MethodsThis study aimed to set up and evaluate a model to predict overall survival (OS) accurately in ENB, including clinical characteristics, treatment and pathological variables. We screened the information of patients with ENB between January 1, 1976, and December 30, 2016 from the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) program as a training cohort. The validation cohort consisted of patients with ENB at Sun Yat-sen University Cancer Center and The First Affiliated Hospital of Sun Yat-sen University in the same period, and 87 patients were included. The Pearson’s chi-squared test was used to assess significance of clinicopathological and demographic characteristics. We used the Cox proportional hazards model to examine univariate and multivariate analyses. The model coefficients were used to calculate the Hazard ratios (HR) with 95% confidence intervals (CI). Prognostic factors with a p-value < 0.05 in multivariate analysis were included in the nomogram. The concordance index (c-index) and calibration curve were used to evaluate the predictive power of the nomogram.ResultsThe c-index of training cohort and validation cohort are 0.737 (95% CI, 0.709 to 0.765) and 0.791 (95% CI, 0.767 to 0.815) respectively. The calibration curves revealed a good agreement between the nomogram prediction and actual observation regarding the probability of 3-year and 5-year survival. We used a nomogram to calculate the 3-year and 5-year growth probability and stratified patients into three risk groups.ConclusionsThe nomogram provided the risk group information and identified mortality risk and can serve as a reference for designing a reasonable follow-up plan.

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A novel nomogram to predict the overall survival in esthesinoeroblastoma

10.21203/rs.3.rs-22163/v4 ◽

2020 ◽

Author(s):

Lijie Jiang ◽

Tengjiao Lin ◽

Yu Zhang ◽

Wenxiang Gao ◽

Jie Deng ◽

...

Keyword(s):

Overall Survival ◽

Proportional Hazards ◽

Proportional Hazards Model ◽

Validation Cohort ◽

Risk Groups ◽

Cox Proportional Hazards ◽

Cox Proportional Hazards Model ◽

Cancer Center ◽

P Value ◽

Training Cohort

Abstract Background: Increasing evidence indicates that the pathology and the modified Kadish system have some influence on the prognosis of esthesioneuroblastoma (ENB). However, an accurate system to combine pathology with a modified Kadish system has not been established. Methods: This study aimed to set up and evaluate a model to predict overall survival (OS) accurately in ENB, including clinical characteristics, treatment and pathological variables. We screened the information of patients with ENB between January 1, 1976, and December 30, 2016 from the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) program as a training cohort. The validation cohort consisted of patients with ENB at Sun Yat-sen University Cancer Center and The First Affiliated Hospital of Sun Yat-sen University in the same period, and 87 patients were identified. The Pearson’s chi-squared test was used to assess significance of clinicopathological and demographic characteristics. We used the Cox proportional hazards model to examine univariate and multivariate analyses. The model coefficients were used to calculate the Hazard ratios (HR) with 95% confidence intervals (CI). Prognostic factors with a p- value < 0.05 in multivariate analysis were included in the nomogram. The concordance index (c-index) and calibration curve were used to evaluate the predictive power of the nomogram. Results: The c-index of training cohort and validation cohort are 0.737 (95% CI, 0.709 to 0.765) and 0.791 (95% CI, 0.767 to 0.815) respectively. The calibration curves revealed a good agreement between the nomogram prediction and actual observation regarding the probability of 3-year and 5-year survival. We used a nomogram to calculate the 3-year and 5-year growth probability and stratified patients into three risk groups. Conclusions: The nomogram provided the risk group information and identified mortality risk and can serve as a reference for designing a reasonable follow-up plan.

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A novel nomogram to predict the overall survival in esthesinoeroblastoma

BMC Cancer ◽

10.1186/s12885-020-07435-7 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Lijie Jiang ◽

Tengjiao Lin ◽

Yu Zhang ◽

Wenxiang Gao ◽

Jie Deng ◽

...

Keyword(s):

Overall Survival ◽

Proportional Hazards ◽

Proportional Hazards Model ◽

Validation Cohort ◽

Risk Groups ◽

Cox Proportional Hazards ◽

Cox Proportional Hazards Model ◽

Cancer Center ◽

Training Cohort ◽

Chi Squared

Abstract Background Increasing evidence indicates that the pathology and the modified Kadish system have some influence on the prognosis of esthesioneuroblastoma (ENB). However, an accurate system to combine pathology with a modified Kadish system has not been established. Methods This study aimed to set up and evaluate a model to predict overall survival (OS) accurately in ENB, including clinical characteristics, treatment and pathological variables. We screened the information of patients with ENB between January 1, 1976, and December 30, 2016 from the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) program as a training cohort. The validation cohort consisted of patients with ENB at Sun Yat-sen University Cancer Center and The First Affiliated Hospital of Sun Yat-sen University in the same period, and 87 patients were included. The Pearson’s chi-squared test was used to assess significance of clinicopathological and demographic characteristics. We used the Cox proportional hazards model to examine univariate and multivariate analyses. The model coefficients were used to calculate the Hazard ratios (HR) with 95% confidence intervals (CI). Prognostic factors with a p-value < 0.05 in multivariate analysis were included in the nomogram. The concordance index (c-index) and calibration curve were used to evaluate the predictive power of the nomogram. Results The c-index of training cohort and validation cohort are 0.737 (95% CI, 0.709 to 0.765) and 0.791 (95% CI, 0.767 to 0.815) respectively. The calibration curves revealed a good agreement between the nomogram prediction and actual observation regarding the probability of 3-year and 5-year survival. We used a nomogram to calculate the 3-year and 5-year growth probability and stratified patients into three risk groups. Conclusions The nomogram provided the risk group information and identified mortality risk and can serve as a reference for designing a reasonable follow-up plan.

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Association of variably methylated tumour DNA regions with overall survival for invasive lobular breast cancer

Clinical Epigenetics ◽

10.1186/s13148-020-00975-6 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Medha Suman ◽

Pierre-Antoine Dugué ◽

Ee Ming Wong ◽

JiHoon Eric Joo ◽

John L. Hopper ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Dna Methylation ◽

Overall Survival ◽

Proportional Hazards ◽

Cox Proportional Hazards ◽

The Cancer Genome Atlas ◽

Lobular Breast Cancer ◽

Genome Wide ◽

Invasive Lobular Breast Cancer

Abstract Background Tumour DNA methylation profiling has shown potential to refine disease subtyping and improve the diagnosis and prognosis prediction of breast cancer. However, limited data exist regarding invasive lobular breast cancer (ILBC). Here, we investigated the genome-wide variability of DNA methylation levels across ILBC tumours and assessed the association between methylation levels at the variably methylated regions and overall survival in women with ILBC. Methods Tumour-enriched DNA was prepared by macrodissecting formalin-fixed paraffin embedded (FFPE) tumour tissue from 130 ILBCs diagnosed in the participants of the Melbourne Collaborative Cohort Study (MCCS). Genome-wide tumour DNA methylation was measured using the HumanMethylation 450K (HM450K) BeadChip array. Variably methylated regions (VMRs) were identified using the DMRcate package in R. Cox proportional hazards regression models were used to assess the association between methylation levels at the ten most significant VMRs and overall survival. Gene set enrichment analyses were undertaken using the web-based tool Metaspace. Replication of the VMR and survival analysis findings was examined using data retrieved from The Cancer Genome Atlas (TCGA) for 168 ILBC cases. We also examined the correlation between methylation and gene expression for the ten VMRs of interest using TCGA data. Results We identified 2771 VMRs (P < 10−8) in ILBC tumours. The ten most variably methylated clusters were predominantly located in the promoter region of the genes: ISM1, APC, TMEM101, ASCL2, NKX6, HIST3H2A/HIST3H2BB, HCG4P3, HES5, CELF2 and EFCAB4B. Higher methylation level at several of these VMRs showed an association with reduced overall survival in the MCCS. In TCGA, all associations were in the same direction, however stronger than in the MCCS. The pooled analysis of the MCCS and TCGA data showed that methylation at four of the ten genes was associated with reduced overall survival, independently of age and tumour stage; APC: Hazard Ratio (95% Confidence interval) per one-unit M-value increase: 1.18 (1.02–1.36), TMEM101: 1.23 (1.02–1.48), HCG4P3: 1.37 (1.05–1.79) and CELF2: 1.21 (1.02–1.43). A negative correlation was observed between methylation and gene expression for CELF2 (R = − 0.25, P = 0.001), but not for TMEM101 and APC. Conclusions Our study identified regions showing greatest variability across the ILBC tumour genome and found methylation at several genes to potentially serve as a biomarker of survival for women with ILBC.

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Integrative transcriptome analysis of malignant pleural mesothelioma reveals a clinically relevant immune-based classification

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2020-001601 ◽

2021 ◽

Vol 9 (2) ◽

pp. e001601

Author(s):

Ania Alay ◽

David Cordero ◽

Sara Hijazo-Pechero ◽

Elisabet Aliagas ◽

Adriana Lopez-Doriga ◽

...

Keyword(s):

Gene Expression ◽

Overall Survival ◽

Malignant Pleural Mesothelioma ◽

Drug Response ◽

Proportional Hazards ◽

Immune Cell ◽

Checkpoint Inhibitors ◽

Cox Proportional Hazards ◽

Transcriptional Level ◽

Pleural Mesothelioma

BackgroundMalignant pleural mesothelioma (MPM) is a rare and aggressive neoplasia affecting the lung mesothelium. Immune checkpoint inhibitors (ICI) in MPM have not been extremely successful, likely due to poor identification of suitable candidate patients for the therapy. We aimed to identify cellular immune fractions associated with clinical outcome and classify patients with MPM based on their immune contexture. For each defined group, we sought for molecular specificities that could help further define our MPM classification at the genomic and transcriptomic level, as well as identify differential therapeutic strategies based on transcriptional signatures predictive of drug response.MethodsThe abundance of 20 immune cell fractions in 516 MPM samples from 7 gene expression datasets was inferred using gene set variation analysis. Identification of clinically relevant fractions was performed with Cox proportional-hazards models adjusted for age, stage, sex, and tumor histology. Immune-based groups were defined based on the identified fractions.ResultsT-helper 2 (TH2) and cytotoxic T (TC) cells were found to be consistently associated with overall survival. Three immune clusters (IG) were subsequently defined based on TH2 and TC immune infiltration levels: IG1 (54.5%) was characterized by high TH2 and low TC levels, IG2 (37%) had either low or high levels of both fractions, and IG3 (8.5%) was defined by low TH2 and high TC levels. IG1 and IG3 groups were associated with worse and better overall survival, respectively. While no differential genomic alterations were identified among immune groups, at the transcriptional level, IG1 samples showed upregulation of proliferation signatures, while IG3 samples presented upregulation of immune and inflammation-related pathways. Finally, the integration of gene expression with functional signatures of drug response showed that IG3 patients might be more likely to respond to ICI.ConclusionsThis study identifies a novel immune-based signature with potential clinical relevance based on TH2 and TC levels, unveiling a fraction of patients with MPM with better prognosis and who might benefit from immune-based therapies. Molecular specificities of the different groups might be used to tailor specific potential therapies in the future.

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Plasma thrombopoietin compared with immunoglobulin heavy-chain mutation status as a predictor of survival in chronic lymphocytic leukemia

Blood ◽

10.1182/blood-2005-05-2110 ◽

2006 ◽

Vol 108 (3) ◽

pp. 1001-1006 ◽

Cited By ~ 16

Author(s):

Charles Koller ◽

B. Nebiyou Bekele ◽

Xian Zhou ◽

Charles Park ◽

Zeev Estrov ◽

...

Keyword(s):

Overall Survival ◽

Chronic Lymphocytic Leukemia ◽

Heavy Chain ◽

Proportional Hazards ◽

Variable Region ◽

Immunoglobulin Heavy Chain ◽

Cox Proportional Hazards ◽

Lymphocytic Leukemia ◽

Mutation Status ◽

Previously Treated

Abstract We investigated the association of plasma thrombopoietin (TPO) and overall survival in 127 patients with previously treated and previously untreated chronic lymphocytic leukemia (CLL). Higher levels of TPO were associated with advanced Rai stage (P < .001), higher levels of β2-microglobulin (β2-M) (P < .001), and the absence of mutation in the immunoglobulin heavy chain variable region (IgVH) (P < .001), and were inversely correlated with platelet count (P = .002). We found that TPO correlated strongly in a continuous manner with overall survival in both previously treated and untreated patients. The univariate Cox proportional hazard model demonstrated that high TPO levels were associated with shorter survival (P < .001), and multiple variable Cox proportional hazards regression analysis demonstrated that this was independent of the IgVH mutation status, β2-M, and Rai stage. Recursive partitioning showed that a cutoff point of 639 pg/mL separated the CLL patients into 2 major survival groups (P < .001). The effects of β2-M were masked by the effects of TPO in the patients with TPO levels higher than 639 pg/mL, but in the remainder, patients with β2-M level higher than 4.95 mg/L had significantly shorter survival than those with lower values. Plasma TPO and β2-M may be useful for the prediction of clinical behavior in CLL and may replace the need for the determination of IgVH mutation status.

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A Clinicogenetic Prognostic Classifier for Prediction of Recurrence and Survival in Asian Breast Cancer Patients

Frontiers in Oncology ◽

10.3389/fonc.2021.645853 ◽

2021 ◽

Vol 11 ◽

Author(s):

Ting-Hao Chen ◽

Jun-Ru Wei ◽

Jason Lei ◽

Jian-Ying Chiu ◽

Kuan-Hui Shih

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Cancer Patients ◽

Proportional Hazards ◽

Genetic Model ◽

Expression Profiles ◽

Risk Groups ◽

Cox Proportional Hazards ◽

Luminal Breast Cancer ◽

Breast Cancer Patients

BackgroundSeveral prognostic factors affect the recurrence of breast cancer in patients who undergo mastectomy. Assays of the expression profiles of multiple genes increase the probability of overexpression of certain genes and thus can potentially characterize the risk of metastasis.MethodsWe propose a 20-gene classifier for predicting patients with high/low risk of recurrence within 5 years. Gene expression levels from a quantitative PCR assay were used to screen 473 luminal breast cancer patients treated at Taiwan Hospital (positive for estrogen and progesterone receptors, negative for human epidermal growth factor receptor 2). Gene expression scores, along with clinical information (age, tumor stage, and nodal stage), were evaluated for risk prediction. The classifier could correctly predict patients with and without relapse (logistic regression, P<0.05).ResultsA Cox proportional hazards regression analysis showed that the 20-gene panel was prognostic with hazard ratios of 5.63 (95% confidence interval 2.77-11.5, univariate) and 5.56 (2.62-11.8, multivariate) for the “genetic” model, and of 8.02 (3.52-18.3, univariate) and 19.8 (5.96-65.87, multivariate) for the “clinicogenetic” model during a 5-year follow-up.ConclusionsThe proposed 20-gene classifier can successfully separate the patients into two risk groups, and the two risk group had significantly different relapse rate and prognosis. This 20-gene classifier can provide better estimation of prognosis, which can help physicians to make better personalized treatment plans.

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Immunogenomic determinants of tumor microenvironment correlate with superior survival in high-risk neuroblastoma

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2021-002417 ◽

2021 ◽

Vol 9 (7) ◽

pp. e002417

Author(s):

Riyue Bao ◽

Stefani Spranger ◽

Kyle Hernandez ◽

Yuanyuan Zha ◽

Peter Pytel ◽

...

Keyword(s):

Gene Expression ◽

Overall Survival ◽

T Cell ◽

High Risk ◽

Proportional Hazards ◽

Checkpoint Inhibitors ◽

Gene Expression Signature ◽

Cox Proportional Hazards ◽

Cox Proportional Hazards Models ◽

Immune Exclusion

BackgroundTumor-infiltrating CD8+ T cells and neoantigens are predictors of a favorable prognosis and response to immunotherapy with checkpoint inhibitors in many types of adult cancer, but little is known about their role in pediatric malignancies. Here, we analyzed the prognostic strength of T cell-inflamed gene expression and neoantigen load in high-risk neuroblastoma. We also compared transcriptional programs in T cell-inflamed and non-T cell-inflamed high-risk neuroblastomas to investigate possible mechanisms of immune exclusion.MethodsA defined T cell-inflamed gene expression signature was used to categorize high-risk neuroblastomas in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) program (n=123), and the Gabriella Miller Kids First (GMKF) program (n=48) into T cell-inflamed, non-T cell-inflamed, and intermediate groups. Associations between the T cell-inflamed and non-T cell-inflamed group, MYCN amplification, and survival were analyzed by Cox proportional hazards models. Additional survival analysis was conducted after integrating neoantigen load predicted from somatic mutations. Pathways activated in non-T cell-inflamed relative to T cell-inflamed tumors were analyzed using causal network analysis.ResultsPatients with T cell-inflamed high-risk tumors showed improved overall survival compared with those with non-T cell-inflamed tumors (p<0.05), independent of MYCN amplification status, in both TARGET and GMKF cohorts. Higher neoantigen load was also associated with better event-free and overall survival (p<0.005) and was independent of the T cell-inflamed signature. Activation of MYCN, ASCL1, SOX11, and KMT2A transcriptional programs was inversely correlated with the T cell-inflamed signature in both cohorts.ConclusionsOur results indicate that tumors from children with high-risk neuroblastoma harboring a strong T cell-inflamed signature have a more favorable clinical outcome, and neoantigen load is a prognosis predictor, independent of T cell inflammation. Strategies to target SOX11 and other signaling pathways associated with non-T cell-inflamed tumors should be pursued as potential immune-potentiating interventions.

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Combining Expression of Hypervariably Expressed Genes with IGHV Mutation Status Is a More Robust Prognostic Indicator Than Mutation Status Alone in Chronic Lymphocytic Leukemia

Blood ◽

10.1182/blood.v118.21.1774.1774 ◽

2011 ◽

Vol 118 (21) ◽

pp. 1774-1774

Author(s):

Xiao J. Yan ◽

Igor Dozmorov ◽

Ivanovic Ivana ◽

Sophia Yancopoulos ◽

Daniel Kalenscher ◽

...

Keyword(s):

Gene Expression ◽

Chronic Lymphocytic Leukemia ◽

Regression Model ◽

Proportional Hazards ◽

Cox Proportional Hazards ◽

Lymphocytic Leukemia ◽

Mutation Status ◽

Cox Proportional Hazards Regression ◽

Proportional Hazards Regression ◽

Low Levels

Abstract Abstract 1774 Introduction: Chronic Lymphocytic Leukemia (CLL) follows a variable, difficult to predict course. Biomarkers (IGHV mutations, CD38 and ZAP-70) have improved prognostication but accuracy is only ∼80%, not sufficient to initiate preemptive therapy. To address this, we have incorporated another molecular biological parameter, hypervariably expressed genes (HVEGs) from global gene expression profiles (GEPs) [Dozmorov, 2011], along with IGHV mutation status to develop a more robust method of prognostication. Methods: RNA was purified from B cells of 65 CLL patients and 25 normal subjects. GEPs were defined with Illumina HumanHT12 beadchips and analyzed to identify HVEGs fluctuating coordinately in CLL patients but not expressed in normal circulating human B cells. A Cox proportional hazards regression model was used to compare expression levels with clinical outcome. Results: Unmutated CLL (U-CLL) and mutated CLL (M-CLL) samples were sorted based on the averaged normalized gene expression level in the largest HVEG cluster consisting of 45 genes. Samples were split into subgroups based on high and low expression of these genes. Four subgroups were identified: U-CLL with high (U-HVEhi), U-CLL with low (U-HVElo), M-CLL with high (M-HVEhi), and M-CLL with low (M-HVElo) expression of HVEGs. When these subgroups were analyzed for time-to-first treatment (TTFT), the findings were remarkably different. Using a Cox proportional hazards regression model we found that for M-CLL the presence of low levels of HVEGs denoted a subgroup with a prolonged median TTFT compared to M-CLL patients with high levels of HVEGs (23.46 yrs in M-HVElo versus 9.05 yrs in M-HVEhi; P=0.0075). This association was reversed in U-CLL, where low levels of HVEGs pinpointed a subgroup with a shortened median TTFT compared to U-CLL patients with high levels of HVEGs: median TTFT was 8.01 yrs in U-HVEhi and decreased by 50% to 3.12 yrs in U-HVElo (P=0.0151). Compared to the TTFT for M-HVElo, the TTFT for U-HVElo was dramatically shorter (3.12 vs. 23.46 years; P<0.0001). Discussion: Combining the HVEG approach with IGHV mutation status enabled us to define intra-group heterogeneity, and thereby improve prognostication for apparently homogeneous subgroups of U-CLL and M-CLL patients. This combination was superior to IGHV mutations alone in that it pinpointed a subset of M-CLL patients with shorter TTFTs and a subset of U-CLL patients with longer TTFTs, indicating that the combined approach selects those patients that IGHV mutation analysis misclassified. Therefore, combining IGHV mutation status and HVEG expression provides a more precise indicator with potentially valuable clinical implications. The data suggest that the HVEGs are responsible for the different outcomes in the two groups and could provide mechanistic insights into key aspects of CLL B-cell biology as well as therapeutic targets. Disclosures: No relevant conflicts of interest to declare.

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