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The EarlyCDT-Lung test is a blood-based autoantibody assay intended to identify high-risk individuals for low-dose computed tomography lung cancer screening. However, there is a paucity of evidence on the performance of the EarlyCDT-Lung test in ever-smokers. We conducted a nested case-control study within two prospective cohorts to evaluate the risk-discriminatory performance of the EarlyCDT-Lung test using prediagnostic blood samples from 154 future lung cancer cases and 154 matched controls. Cases were selected from those who had ever smoked and had a prediagnostic blood sample <3 years prior to diagnosis. Conditional logistic regression was used to estimate the association between EarlyCDT-Lung test results and lung cancer risk. Sensitivity and specificity of the EarlyCDT-Lung test were calculated in all subjects and subgroups based on age, smoking history, lung cancer stage, sample collection time before diagnosis and year of sample collection. The overall lung cancer odds ratios were 0.89 (95% CI: 0.34-2.30) for a moderate risk EarlyCDT-Lung test result and 1.09 (95% CI: 0.48-2.47) for a high-risk test result compared to no significant test result. The overall sensitivity was 8.4% (95% CI: 4.6-14) and overall specificity was 92% (95% CI: 87-96) when considering a high-risk result as positive. Stratified analysis indicated higher sensitivity (17%, 95% CI: 7.2-32.1) in subjects with blood drawn up to 1 year prior to diagnosis. In conclusion, our study does not support a role of the EarlyCDT-Lung test in identifying the high-risk subjects in ever-smokers for lung cancer screening in the EPIC and NSHDS cohorts.

BACKGROUND: We sought to develop a proteomics-based risk model for lung cancer and evaluate its risk-discriminatory performance in comparison with a smoking-based risk model (PLCOm2012) and a commercially available autoantibody biomarker test.

METHODS: We designed a case-control study nested in 6 prospective cohorts, including 624 lung cancer participants who donated blood samples at most 3 years prior to lung cancer diagnosis and 624 smoking-matched cancer free participants who were assayed for 302 proteins. We used 470 case-control pairs from 4 cohorts to select proteins and train a protein-based risk model. We subsequently used 154 case-control pairs from 2 cohorts to compare the risk-discriminatory performance of the protein-based model with that of the Early Cancer Detection Test (EarlyCDT)-Lung and the PLCOm2012 model using receiver operating characteristics analysis and by estimating models' sensitivity. All tests were 2-sided.

RESULTS: The area under the curve for the protein-based risk model in the validation sample was 0.75 (95% confidence interval [CI] = 0.70 to 0.81) compared with 0.64 (95% CI = 0.57 to 0.70) for the PLCOm2012 model (Pdifference = .001). The EarlyCDT-Lung had a sensitivity of 14% (95% CI = 8.2% to 19%) and a specificity of 86% (95% CI = 81% to 92%) for incident lung cancer. At the same specificity of 86%, the sensitivity for the protein-based risk model was estimated at 49% (95% CI = 41% to 57%) and 30% (95% CI = 23% to 37%) for the PLCOm2012 model.

CONCLUSION: Circulating proteins showed promise in predicting incident lung cancer and outperformed a standard risk prediction model and the commercialized EarlyCDT-Lung.

Despite having common overlapping immunophenotypic and morphological features, T-cell lymphoblastic leukemia (T-ALL) and lymphoma (T-LBL) have distinct clinical manifestations, which may represent separate diseases. We investigated and compared the epigenetic and genetic landscape of adult and pediatric T-ALL (n = 77) and T-LBL (n = 15) patient samples by high-resolution genome-wide DNA methylation and Copy Number Variation (CNV) BeadChip arrays. DNA methylation profiling identified the presence of CpG island methylator phenotype (CIMP) subgroups within both pediatric and adult T-LBL and T-ALL. An epigenetic signature of 128 differentially methylated CpG sites was identified, that clustered T-LBL and T-ALL separately. The most significant differentially methylated gene loci included the SGCE/PEG10 shared promoter region, previously implicated in lymphoid malignancies. CNV analysis confirmed overlapping recurrent aberrations between T-ALL and T-LBL, including 9p21.3 (CDKN2A/CDKN2B) deletions. A significantly higher frequency of chromosome 13q14.2 deletions was identified in T-LBL samples (36% in T-LBL vs. 0% in T-ALL). This deletion, encompassing the RB1, MIR15A and MIR16-1 gene loci, has been reported as a recurrent deletion in B-cell malignancies. Our study reveals epigenetic and genetic markers that can distinguish between T-LBL and T-ALL, and deepen the understanding of the biology underlying the diverse disease localization.

Background: Prematurity in itself and exposure to neonatal intensive care triggers inflammatory processes and oxidative stress, leading to risk for disease later in life. The effects on cellular aging processes are incompletely understood.

Methods: Relative telomere length (RTL) was measured by qPCR in this longitudinal cohort study with blood samples taken at birth and at 2 years of age from 60 children (16 preterm and 44 term). Viral respiratory infections the first year were evaluated. Epigenetic biological DNA methylation (DNAm) age was predicted based on methylation array data in 23 children (11 preterm and 12 term). RTL change/year and DNAm age change/year was compared in preterm and term during the 2 first years of life.

Results: Preterm infants had longer telomeres than term born at birth and at 2 years of age, but no difference in telomere attrition rate could be detected. Predicted epigenetic DNAm age was younger in preterm infants, but rate of DNAm aging was similar in both groups.

Conclusions: Despite early exposure to risk factors for accelerated cellular aging, children born preterm exhibited preserved telomeres. Stress during the neonatal intensive care period did not reflect accelerated epigenetic DNAm aging. Early-life aging was not explained by preterm birth.

Impact: Preterm birth is associated with elevated disease risk later in life. Preterm children often suffer from inflammation early in life. Stress-related telomere erosion during neonatal intensive care has been proposed. Inflammation-accelerated biological aging in preterm is unknown. We find no accelerated aging due to prematurity or infections during the first 2 years of life.

Classification of pediatric T‐cell acute lymphoblastic leukemia (T‐ALL) patients into CIMP (CpG Island Methylator Phenotype) subgroups has the potential to improve current risk stratification. To investigate the biology behind these CIMP subgroups, diagnostic samples from Nordic pediatric T‐ALL patients were characterized by genome‐wide methylation arrays, followed by targeted exome sequencing, telomere length measurement, and RNA sequencing. The CIMP subgroups did not correlate significantly with variations in epigenetic regulators. However, the CIMP+ subgroup, associated with better prognosis, showed indicators of longer replicative history, including shorter telomere length (P = 0.015) and older epigenetic (P < 0.001) and mitotic age (P < 0.001). Moreover, the CIMP+ subgroup had significantly higher expression of ANTP homeobox oncogenes, namely TLX3, HOXA9, HOXA10, and NKX2‐1, and novel genes in T‐ALL biology including PLCB4, PLXND1, and MYO18B. The CIMP− subgroup, with worse prognosis, was associated with higher expression of TAL1 along with frequent STIL‐TAL1 fusions (2/40 in CIMP+ vs 11/24 in CIMP−), as well as stronger expression of BEX1. Altogether, our findings suggest different routes for leukemogenic transformation in the T‐ALL CIMP subgroups, indicated by different replicative histories and distinct methylomic and transcriptomic profiles. These novel findings can lead to new therapeutic strategies.

Background: Clear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cancer and is associated with poor prognosis if metastasized. Up to one third of patients with local disease at diagnosis will develop metastasis after nephrectomy, and there is a need for new molecular markers to identify patients with high risk of tumor progression. In the present study, we performed genome-wide promoter DNA methylation analysis at diagnosis to identify DNA methylation profiles associated with risk for progress.

Method: Diagnostic tissue samples from 115 ccRCC patients were analysed by Illumina HumanMethylation450K arrays and methylation status of 155,931 promoter associated CpGs were related to genetic aberrations, gene expression and clinicopathological parameters.

Results: The ccRCC samples separated into two clusters (cluster A/B) based on genome-wide promoter methylation status. The samples in these clusters differed in tumor diameter (p < 0.001), TNM stage (p < 0.001), morphological grade (p < 0.001), and patients outcome (5 year cancer specific survival (pCSS5yr) p < 0.001 and cumulative incidence of progress (pCIP5yr) p < 0.001. An integrated genomic and epigenomic analysis in the ccRCCs, revealed significant correlations between the total number of genetic aberrations and total number of hypermethylated CpGs (R = 0.435, p < 0.001), and predicted mitotic age (R = 0.407, p < 0.001). We identified a promoter methylation classifier (PMC) panel consisting of 172 differently methylated CpGs accompanying progress of disease. Classifying non-metastatic patients using the PMC panel showed that PMC high tumors had a worse prognosis compared with the PMC low tumors (pCIP5yr 38% vs. 8%, p = 0.001), which was confirmed in non-metastatic ccRCCs in the publically available TCGA-KIRC dataset (pCIP5yr 39% vs. 16%, p < 0.001).

Conclusion: DNA methylation analysis at diagnosis in ccRCC has the potential to improve outcome-prediction in non-metastatic patients at diagnosis.

Precursor lymphoid neoplasms, namely acute lymphoblastic leukemias (ALL) and lymphoblastic lymphomas (LBL), are characterized by an aggressive proliferation of malignant progenitor B- or T-cells. To improve risk classification at diagnosis, better prognostic and treatment stratifying biomarkers are needed. Altered DNA methylation pattern is a hallmark of neoplastic transformation, and has been employed as a molecular prognostic and predictive marker in various cancers, including hematological malignancies. Our research group previously identified a CpG island methylator phenotype (CIMP) panel that classified pediatric T-ALL patients into prognostic subgroups.

The aim of this thesis was to evaluate distinct DNA methylation signatures in precursor lymphoid neoplasms, and to validate the prognostic value of CIMP classification in separate patient cohorts. Additionally, the biological mechanisms underlying the distinct CIMP methylation signatures in these malignancies were investigated.

The prognostic relevance of CIMP classification was validated in an independent Nordic cohort of pediatric T-ALL patients. Combination of CIMP status with minimal residual disease (MRD) status, could further dissect the high-risk MRD positive T-ALL patients into two CIMP subgroups with significantly distinct outcomes. Furthermore, CIMP classification at diagnosis was shown to predict overall survival in relapsed BCP-ALL patients. CIMP methylation signatures were also identified in T-LBL patients, indicating a broader relevance of CIMP based classification in lymphoid malignancies. Investigating the biology behind CIMP methylation signatures showed the association of CIMP status with the proliferative history of the leukemic cells. A differential transcriptomic analysis revealed a correlation of CIMP subgroups with known T-ALL drivers, as well as with novel genes in T-ALL biology. Finally, we identified distinct DNA methylation patterns and genetic aberrations in T-ALL and T-LBL that might contribute to the different clinical presentation of these two diseases. In conclusion, we validated the prognostic significance of CIMP methylation signature in precursor lymphoid malignancies and identified transcriptomic profiles that associated with the subgroups. DNA methylation is a strong candidate for further risk classification in lymphoid neoplasms and our findings can contribute to the identification of new potential targets for treatment.

Background: Few biological markers are associated with survival after relapse of B-cell precursor acute lymphoblastic leukemia (BCP-ALL). In pediatric T-cell ALL, we have identified promoter-associated methylation alterations that correlate with prognosis. Here, the prognostic relevance of CpG island methylation phenotype (CIMP) classification was investigated in pediatric BCP-ALL patients.

Methods: Six hundred and one BCP-ALL samples from Nordic pediatric patients (age 1-18) were CIMP classified at initial diagnosis and analyzed in relation to clinical data.

Results: Among the 137 patients that later relapsed, patients with a CIMP-profile (n = 42) at initial diagnosis had an inferior overall survival (pOS(5years) 33%) compared to CIMP+ patients (n = 95, pOS(5years) 65%) (p = 0.001), which remained significant in a Cox proportional hazards model including previously defined risk factors.

Conclusion: CIMP classification is a strong candidate for improved risk stratification of relapsed BCP-ALL.

Epigenetic alterations during aging have been proposed to contribute to decline in physical and cognitive functions, and accelerated epigenetic aging has been associated with disease and all-cause mortality later in life. In this study, we estimated epigenetic age dynamics in groups with different memory trajectories (maintained high performance, average decline, and accelerated decline) over a 15-year period. Epigenetic (DNA-methylation [DNAm]) age was assessed, and delta age (DNAm age - chronological age) was calculated in blood samples at baseline (age: 55-65 years) and 15 years later in 52 age- and gender-matched individuals from the Betula study in Sweden. A lower delta DNAm age was observed for those with maintained memory functions compared with those with average (p = 0.035) or accelerated decline (p = 0.037). Moreover, separate analyses revealed that DNAm age at follow-up, but not chronologic age, was a significant predictor of dementia (p = 0.019). Our findings suggest that young epigenetic age contributes to maintained memory in aging.

Background. Despite increased knowledge about genetic aberrations in pediatric T-cell acute lymphoblastic leukemia (T-ALL), no clinically feasible treatment-stratifying marker exists at diagnosis. Instead patients are enrolled in intensive induction therapies with substantial side effects. In modern protocols, therapy response is monitored by minimal residual disease (MRD) analysis and used for postinduction risk group stratification. DNA methylation profiling is a candidate for subtype discrimination at diagnosis and we investigated its role as a prognostic marker in pediatric T-ALL. Procedure. Sixty-five diagnostic T-ALL samples from Nordic pediatric patients treated according to the Nordic Society of Pediatric Hematology and Oncology ALL 2008 (NOPHO ALL 2008) protocol were analyzed by HumMeth450K genome wide DNA methylation arrays. Methylation status was analyzed in relation to clinical data and early T-cell precursor (ETP) phenotype. Results. Two distinct CpG island methylator phenotype (CIMP) groups were identified. Patients with a CIMP-negative profile had an inferior response to treatment compared to CIMP-positive patients (3-year cumulative incidence of relapse (CIR3y) rate: 29% vs. 6%, P = 0.01). Most importantly, CIMP classification at diagnosis allowed subgrouping of high-risk T-ALL patients (MRD >= 0.1% at day 29) into two groups with significant differences in outcome (CIR3y rates: CIMP negative 50% vs. CIMP positive 12%; P = 0.02). These groups did not differ regarding ETP phenotype, but the CIMP-negative group was younger (P = 0.02) and had higher white blood cell count at diagnosis (P = 0.004) compared with the CIMP-positive group. Conclusions. CIMP classification at diagnosis in combination with MRD during induction therapy is a strong candidate for further risk classification and could confer important information in treatment decision making.