Exposure to green spaces, cardiovascular risk biomarkers and incident cardiovascular disease in older adults: The Seniors-Enrica II cohort.

INTRODUCTION: The impact of residential green spaces on cardiovascular health in older adults remains uncertain. METHODS: Cohort study involving 2114 adults aged ≥ 65 years without cardiovascular disease (CVD), residing in five dense municipalities (Prince et al., 2015) of the Madrid region and with detailed characterization of their socioeconomic background, health behaviors, CVD biological risk factors, and mental, physical, and cognitive health. Greenness exposure was measured using the Normalized Difference Vegetation Index (NDVI) at varying distances from participants' homes. Traffic exposure, neighborhood environment, neighborhood walkability, and socioeconomic deprivation at the census level were also assessed. Serum N-terminal pro-B-type natriuretic peptide (NT-ProBNP), high-sensitivity troponin T (hs-TnT), interleukin 6 (IL-6), and Growth Differentiation Factor 15 (GDF-15) were measured at baseline, and incident CVD events identified through electronic medical records (International Classification of Primary Care-2 codes K74, K75, K77, K90, and K92). RESULTS: After adjusting for sex, age, educational attainment, financial hardship and socioeconomic deprivation at the census level, an interquartile range (IQR) increase in NDVI at 250, 500, 750, and 1000 m around participants' homes was associated with mean differences in ProBNP of -5.56 % (95 %CI: -9.77; -1.35), -5.05 % (-9.58; -0.53), -4.24 % (-8.19, -0.19), and -4.16 % (-7.59; -0.74), respectively; and mean differences in hs-TnT among diabetic participants of -8.03 % (95 %CI: -13.30; -2.77), -9.52 % (-16.08; -2.96), -8.05 % (-13.94, -2.16) and -5.56 % (-10.75; -0.54), respectively. Of similar magnitude, although only statistically significant at 250 and 500 m, were the observed lower IL-6 levels with increasing greenness. GDF-15 levels were independent of NDVI. In prospective analyses (median follow-up 6.29 years), an IQR increase in residential greenness at 500, 750, and 1000 m was associated with a lower risk of incident CVD. The variables that contributed most to the apparent beneficial effects of greenness on CVD were lower exposure to traffic, improved cardiovascular risk factors, and enhanced physical performance. Additionally, neighborhood walkability and increased physical activity were notable contributors among individuals with diabetes. CONCLUSION: Increased exposure to residential green space was associated with a moderate reduction in CVD risk in older adults residing in densely populated areas.

Socio-economic inequalities in lung cancer mortality in Spain: a nation-wide study using area-based deprivation.

BACKGROUND: Lung cancer is the main cause of cancer mortality worldwide and in Spain. Several previous studies have documented socio-economic inequalities in lung cancer mortality but these have focused on specific provinces or cities. The goal of this study was to describe lung cancer mortality in Spain by sex as a function of socio-economic deprivation. METHODS: We analysed all registered deaths from lung cancer during the period 2011-2017 in Spain. Mortality data was obtained from the National Institute of Statistics, and socio-economic level was measured with the small-area deprivation index developed by the Spanish Society of Epidemiology, with the census tract of residence at the time of death as the unit of analysis. We computed crude and age-standardized rates per 100,000 inhabitants by sex, deprivation quintile, and type of municipality (rural, semi-rural, urban) considering the 2013 European standard population (ASR-E). We further calculated ASR-E ratios between the most deprived (Q5) and the least deprived (Q1) areas and mapped census tract smoothed standardized lung cancer mortality ratios by sex. RESULTS: We observed 148,425 lung cancer deaths (80.7% in men), with 73.5 deaths per 100,000 men and 17.1 deaths per 100,000 women. Deaths from lung cancer in men were five times more frequent than in women (ASR-E ratio = 5.3). Women residing in the least deprived areas had higher mortality from lung cancer (ASR-E = 22.2), compared to women residing in the most deprived areas (ASR-E = 13.2), with a clear gradient among the quintiles of deprivation. For men, this pattern was reversed, with the highest mortality occurring in areas of lower socio-economic level (ASR-E = 99.0 in Q5 vs. ASR-E = 86.6 in Q1). These socio-economic inequalities remained fairly stable over time and across urban and rural areas. CONCLUSIONS: Socio-economic status is strongly related to lung cancer mortality, showing opposite patterns in men and women, such that mortality is highest in women residing in the least deprived areas and men residing in the most deprived areas. Systematic surveillance of lung cancer mortality by socio-economic status may facilitate the assessment of public health interventions aimed at mitigating cancer inequalities in Spain.

Identification of NRF2 Activation as a Prognostic Biomarker in T-Cell Acute Lymphoblastic Leukaemia.

The standard-of-care treatment of T-cell acute lymphoblastic leukaemia (T-ALL) with chemotherapy usually achieves reasonable rates of initial complete response. However, patients who relapse or do not respond to conventional therapy show dismal outcomes, with cure rates below 10% and limited therapeutic options. To ameliorate the clinical management of these patients, it is urgent to identify biomarkers able to predict their outcomes. In this work, we investigate whether NRF2 activation constitutes a biomarker with prognostic value in T-ALL. Using transcriptomic, genomic, and clinical data, we found that T-ALL patients with high NFE2L2 levels had shorter overall survival. Our results demonstrate that the PI3K-AKT-mTOR pathway is involved in the oncogenic signalling induced by NRF2 in T-ALL. Furthermore, T-ALL patients with high NFE2L2 levels displayed genetic programs of drug resistance that may be provided by NRF2-induced biosynthesis of glutathione. Altogether, our results indicate that high levels of NFE2L2 may be a predictive biomarker of poor treatment response in T-ALL patients, which would explain the poor prognosis associated with these patients. This enhanced understanding of NRF2 biology in T-ALL may allow a more refined stratification of patients and the proposal of targeted therapies, with the ultimate goal of improving the outcome of relapsed/refractory T-ALL patients.

SOCS3 deregulation contributes to aberrant activation of the JAK/STAT pathway in precursor T-cell neoplasms.

Despite the Janus kinase/signal transducers and activators of transcription (JAK/STAT) pathway being frequently altered in T-ALL/LBL, no specific therapy has been approved for T-ALL/LBL patients with constitutive signalling by JAK/STAT, so there is an urgent need to identify pathway members that may be potential therapeutic targets. In the present study, we searched for JAK/STAT pathway members potentially modulated through aberrant methylation and identified SOCS3 hypermethylation as a recurrent event in T-ALL/LBL. Additionally, we explored the implications of SOCS3 deregulation in T-ALL/LBL and demonstrated that SOCS3 counteracts the constitutive activation of the JAK/STAT pathway through different molecular mechanisms. Therefore, SOCS3 emerges as a potential therapeutic target in T-ALL/LBL.

Rural-urban gradients and all-cause, cardiovascular and cancer mortality in Spain using individual data.

•The literature reporting on rural-urban health status disparities remains inconclusive.•We analyzed data from a longitudinal population-based study using individual observations.•Our results show that the risks of all-cause and cancer mortality are greater in large cities than in other municipalities, with no clear urban-rural gradient.•Not differences were found among territories in cardiovascular mortality.

Toenail zinc as a biomarker: Relationship with sources of environmental exposure and with genetic variability in MCC-Spain study.

BACKGROUND: Toenails are commonly used as biomarkers of exposure to zinc (Zn), but there is scarce information about their relationship with sources of exposure to Zn. OBJECTIVES: To investigate the main determinants of toenail Zn, including selected sources of environmental exposure to Zn and individual genetic variability in Zn metabolism. METHODS: We determined toenail Zn by inductively coupled plasma mass spectrometry in 3,448 general population controls from the MultiCase-Control study MCC-Spain. We assessed dietary and supplement Zn intake using food frequency questionnaires, residential proximity to Zn-emitting industries and residential topsoil Zn levels through interpolation methods. We constructed a polygenic score of genetic variability based on 81 single nucleotide polymorphisms in genes involved in Zn metabolism. Geometric mean ratios of toenail Zn across categories of each determinant were estimated from multivariate linear regression models on log-transformed toenail Zn. RESULTS: Geometric mean toenail Zn was 104.1 µg/g in men and 100.3 µg/g in women. Geometric mean toenail Zn levels were 7 % lower (95 % confidence interval 1-13 %) in men older than 69 years and those in the upper tertile of fibre intake, and 9 % higher (3-16 %) in smoking men. Women residing within 3 km from Zn-emitting industries had 4 % higher geometric mean toenail Zn levels (0-9 %). Dietary Zn intake and polygenic score were unrelated to toenail Zn. Overall, the available determinants only explained 9.3 % of toenail Zn variability in men and 4.8 % in women. DISCUSSION: Sociodemographic factors, lifestyle, diet, and environmental exposure explained little of the individual variability of toenail Zn in the study population. The available genetic variants related to Zn metabolism were not associated with toenail Zn.

Association of socioeconomic deprivation with life expectancy and all-cause mortality in Spain, 2011-2013.

Life tables summarise a population's mortality experience during a time period. Sex- and age-specific life tables are needed to compute various cancer survival measures. However, mortality rates vary according to socioeconomic status. We present sex- and age-specific life tables based on socioeconomic status at the census tract level in Spain during 2011-2013 that will allow estimating cancer relative survival estimates and life expectancy measures by socioeconomic status. Population and mortality data were obtained from the Spanish Statistical Office. Socioeconomic level was measured using the Spanish Deprivation Index by census tract. We produced sex- and age-specific life expectancies at birth by quintiles of deprivation, and life tables by census tract and province. Life expectancy at birth was higher among women than among men. Women and men in the most deprived census tracts in Spain lived 3.2 and 3.8 years less than their counterparts in the least deprived areas. A higher life expectancy in the northern regions of Spain was discovered. Life expectancy was higher in provincial capitals than in rural areas. We found a significant life expectancy gap and geographical variation by sex and socioeconomic status in Spain. The gap was more pronounced among men than among women. Understanding the association between life expectancy and socioeconomic status could help in developing appropriate public health programs. Furthermore, the life tables we produced are needed to estimate cancer specific survival measures by socioeconomic status. Therefore, they are important for cancer control in Spain.

Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci.

BACKGROUND: Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants. METHODS: We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia. RESULTS: We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p < 0.05. TWAS further identified two novel genes (SHOX2 and CRISPLD2) whose genetically predicted expression was significantly associated with MD phenotypes. CONCLUSIONS: Our findings provided novel insight into the genetic background of MD phenotypes, and further demonstrated their shared genetic basis with breast cancer.

Socio-Economic Inequalities in Lung Cancer Outcomes: An Overview of Systematic Reviews.

In the past decade, evidence has accumulated about socio-economic inequalities in very diverse lung cancer outcomes. To better understand the global effects of socio-economic factors in lung cancer, we conducted an overview of systematic reviews. Four databases were searched for systematic reviews reporting on the relationship between measures of socio-economic status (SES) (individual or area-based) and diverse lung cancer outcomes, including epidemiological indicators and diagnosis- and treatment-related variables. AMSTAR-2 was used to assess the quality of the selected systematic reviews. Eight systematic reviews based on 220 original studies and 8 different indicators were identified. Compared to people with a high SES, people with a lower SES appear to be more likely to develop and die from lung cancer. People with lower SES also have lower cancer survival, most likely due to the lower likelihood of receiving both traditional and next-generation treatments, higher rates of comorbidities, and the higher likelihood of being admitted as emergency. People with a lower SES are generally not diagnosed at later stages, but this may change after broader implementation of lung cancer screening, as early evidence suggests that there may be socio-economic inequalities in its use.

Prostate cancer genetic propensity risk score may modify the association between this tumour and type 2 diabetes mellitus (MCC-Spain study).

BACKGROUND: Some studies have reported an inverse association between type 2 diabetes mellitus (T2DM) and prostate cancer (PCa), but results on this issue are still inconsistent. In this study, we evaluate whether this heterogeneity might be related to differences in this relationship by tumour or by individual genetic susceptibility to PCa. METHODS: We studied 1047 incident PCa cases and 1379 randomly selected controls, recruited in 7 Spanish provinces for the population-based MCC-Spain case-control. Tumour were classified by aggressiveness according to the International Society of Urological Pathology (ISUP), and we constructed a PCa polygenic risk score (PRS) as proxy for genetic susceptibility. The epidemiological questionnaire collected detailed self-reported data on T2DM diagnosis and treatment. The association between T2DM status and PCa was studied by fitting mixed logistic regression models, and, for its association by aggressiveness of PCa, with multinomial logistic regression models. To evaluate the possible modulator role of PRS in this relationship, we included the corresponding interaction term in the model, and repeated the analysis stratified by PRS tertiles. RESULTS: Globally, our results showed an inverse association between T2DM and overall PCa limited to grade 1 tumours (ORISUP = 1: 0.72; 95% CI: 0.53-0.98), which could be compatible with a detection bias. However, PCa risk also varied with duration of diabetes treatment -inversely to metformin and positively with insulin-, without differences by aggressiveness. When we considered genetic susceptibility, T2DM was more strongly associated with lower PCa risk in those with lower PRS (ORtertile 1: 0.31; 95% CI: 0.11-0.87), independently of ISUP grade. CONCLUSIONS: Our findings reinforce the need to include aggressiveness and susceptibility of PCa, and T2DM treatments in the study of the relationship between both diseases.

Evaluation of Feature Selection Techniques for Breast Cancer Risk Prediction.

This study evaluates several feature ranking techniques together with some classifiers based on machine learning to identify relevant factors regarding the probability of contracting breast cancer and improve the performance of risk prediction models for breast cancer in a healthy population. The dataset with 919 cases and 946 controls comes from the MCC-Spain study and includes only environmental and genetic features. Breast cancer is a major public health problem. Our aim is to analyze which factors in the cancer risk prediction model are the most important for breast cancer prediction. Likewise, quantifying the stability of feature selection methods becomes essential before trying to gain insight into the data. This paper assesses several feature selection algorithms in terms of performance for a set of predictive models. Furthermore, their robustness is quantified to analyze both the similarity between the feature selection rankings and their own stability. The ranking provided by the SVM-RFE approach leads to the best performance in terms of the area under the ROC curve (AUC) metric. Top-47 ranked features obtained with this approach fed to the Logistic Regression classifier achieve an AUC = 0.616. This means an improvement of 5.8% in comparison with the full feature set. Furthermore, the SVM-RFE ranking technique turned out to be highly stable (as well as Random Forest), whereas relief and the wrapper approaches are quite unstable. This study demonstrates that the stability and performance of the model should be studied together as Random Forest and SVM-RFE turned out to be the most stable algorithms, but in terms of model performance SVM-RFE outperforms Random Forest.

Lung, Breast and Colorectal Cancer Incidence by Socioeconomic Status in Spain: A Population-Based Multilevel Study.

Socioeconomic inequalities in cancer incidence are not well documented in southern Europe. We aim to study the association between socioeconomic status (SES) and colorectal, lung, and breast cancer incidence in Spain. We conducted a multilevel study using data from Spanish population-based cancer registries, including incident cases diagnosed for the period 2010-2013 in nine Spanish provinces. We used Poisson mixed-effects models, including the census tract as a random intercept, to derive cancer incidence rate ratios by SES, adjusted for age and calendar year. Male adults with the lowest SES, compared to those with the highest SES, showed weak evidence of being at increased risk of lung cancer (risk ratio (RR): 1.18, 95% CI: 0.94-1.46) but showed moderate evidence of being at reduced risk of colorectal cancer (RR: 0.84, 95% CI: 0.74-0.97). Female adults with the lowest SES, compared to those with the highest SES, showed strong evidence of lower breast cancer incidence with 24% decreased risk (RR: 0.76, 95% CI: 0.68-0.85). Among females, we did not find evidence of an association between SES and lung or colorectal cancer. The associations found between SES and cancer incidence in Spain are consistent with those obtained in other European countries.

Cancer incidence estimation from mortality data: a validation study within a population-based cancer registry.

BACKGROUND: Population-based cancer registries are required to calculate cancer incidence in a geographical area, and several methods have been developed to obtain estimations of cancer incidence in areas not covered by a cancer registry. However, an extended analysis of those methods in order to confirm their validity is still needed. METHODS: We assessed the validity of one of the most frequently used methods to estimate cancer incidence, on the basis of cancer mortality data and the incidence-to-mortality ratio (IMR), the IMR method. Using the previous 15-year cancer mortality time series, we derived the expected yearly number of cancer cases in the period 2004-2013 for six cancer sites for each sex. Generalized linear mixed models, including a polynomial function for the year of death and smoothing splines for age, were adjusted. Models were fitted under a Bayesian framework based on Markov chain Monte Carlo methods. The IMR method was applied to five scenarios reflecting different assumptions regarding the behavior of the IMR. We compared incident cases estimated with the IMR method to observed cases diagnosed in 2004-2013 in Granada. A goodness-of-fit (GOF) indicator was formulated to determine the best estimation scenario. RESULTS: A total of 39,848 cancer incidence cases and 43,884 deaths due to cancer were included. The relative differences between the observed and predicted numbers of cancer cases were less than 10% for most cancer sites. The constant assumption for the IMR trend provided the best GOF for colon, rectal, lung, bladder, and stomach cancers in men and colon, rectum, breast, and corpus uteri in women. The linear assumption was better for lung and ovarian cancers in women and prostate cancer in men. In the best scenario, the mean absolute percentage error was 6% in men and 4% in women for overall cancer. Female breast cancer and prostate cancer obtained the worst GOF results in all scenarios. CONCLUSION: A comparison with a historical time series of real data in a population-based cancer registry indicated that the IMR method is a valid tool for the estimation of cancer incidence. The goodness-of-fit indicator proposed can help select the best assumption for the IMR based on a statistical argument.

Approximate Bayesian inference for multivariate point pattern analysis in disease mapping.

We present a novel approach for analysing multivariate case-control georeferenced data in a Bayesian disease mapping context using stochastic partial differential equations (SPDEs) and the integrated nested Laplace approximation (INLA) for model fitting. In particular, we propose smooth terms based on SPDE models to estimate the underlying spatial variation as well as risk associated to pollution sources. Log-Gaussian Cox processes are used to estimate the intensity of the cases and controls, to account for risk factors and include a term to measure spatial residual variation. Each intensity is modelled on a baseline spatial effect (estimated from both controls and cases), a disease-specific spatial term and the effects of some covariates. By fitting these models, the residual spatial terms can be easily compared to detect high-risk areas not explained by the covariates. Three different types of effects to model exposure to pollution sources are considered on the distance to the source: a fixed effect, a smooth term to model non-linear effects by means of a discrete random walk of order one and a Gaussian process in one dimension with a Matérn covariance function. Spatial terms are modelled using a Gaussian process in two dimensions with a Matérn covariance function and are approximated using an approach based on solving an SPDE through INLA. Finally, this new framework is applied to a dataset of three different types of cancer and a set of controls from Alcalá de Henares (Madrid, Spain). Covariates available include the distance to several polluting industries and socioeconomic indicators. Our findings point to a possible risk increase due to the proximity to some of these industries.

Socioeconomic Inequalities in Colorectal Cancer Survival in Southern Spain: A Multilevel Population-Based Cohort Study.

BACKGROUND: Colorectal cancer (CRC) is the most frequently diagnosed cancer in Spain. Socioeconomic inequalities in cancer survival are not documented in Spain. We aim to study the association of socioeconomic inequalities with overall mortality and survival among CRC patients in southern Spain. METHODS: We conducted a multilevel population-based cohort study, including CRC cases for the period 2011-2013. The study time-to-event outcome was death, and the primary exposure was CRC patients' socioeconomic status assessed by the Spanish deprivation index at the census tract level. We used a mixed-effects flexible hazard model, including census tract as a random intercept, to derive overall survival estimates by deprivation. RESULTS: Among 3589 CRC patients and 12,148 person-years at risk (pyr), 964 patients died before the end of the follow-up. Mortality by deprivation showed the highest mortality rate for the most deprived group (96.2 per 1000 pyr, 95% CI: 84.0-110.2). After adjusting for sex, age, cancer stage, and the area of residence, the most deprived had a 60% higher excess mortality risk than the less deprived group (excess mortality risk ratio: 1.6, 95% CI: 1.1-2.3). CONCLUSIONS: We found a consistent association between deprivation and CRC excess mortality and survival. The reasons behind these inequalities need further investigation in order to improve equality cancer outcomes in all social groups.

Deprivation gap in colorectal cancer survival attributable to stage at diagnosis: A population-based study in Spain.

OBJECTIVE: Socioeconomic inequalities in colorectal cancer (CRC) survival are a major concern of the Spanish public health system. If these inequalities were mainly due to differences in stage at diagnosis, population-based screening programs might reduce them substantially. We aimed to determine to what extent adverse stage distribution contributed to survival inequalities in a Spanish region before the implementation of a CRC screening program. METHODS: We analyzed data from a population-based cohort study that included all patients living in a region of southern Spain with CRC diagnosed between 2004 and 2013. The European Deprivation Index was used to assign each patient a socioeconomic level based on their area of residence. The role of tumor stage in survival disparities between socioeconomic groups was assessed using a causal mediation analysis. RESULTS: A total of 2802 men and 1957 women were included in the study. For men, the adjusted difference in deaths between the most deprived and the most affluent areas was 131 deaths per 1000 person-years by the first year after diagnosis. Of these deaths, 42 (per 1000 person-years) were attributable to differences in stage at diagnosis. No socioeconomic disparities in survival were detected among female patients. CONCLUSIONS: In this study, we mainly detected socioeconomic disparities in short term survival of male patients. More than two thirds of these inequalities could not be attributed to differences in stage at diagnosis. Our results suggest that in addition to a screening program, other public health interventions are necessary to reduce the deprivation gap in survival.

Author Correction: Validating a breast cancer score in Spanish women. The MCC-Spain study.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Association between proximity to industrial chemical installations and cancer mortality in Spain.

It is likely that pollution from chemical facilities will affect the health of any exposed population; however, the majority of scientific evidence available has focused on occupational exposure rather than environmental. Consequently, this study assessed whether there could have been an excess of cancer-related mortality associated with environmental exposure to pollution from chemical installations - for populations residing in municipalities in the vicinity of chemical industries. To this end, we designed an ecological study which assessed municipal mortality due to 32 types of cancer in the period from 1999 to 2008. The exposure to pollution was estimated using distance from the facilities to the centroid of the municipality as a proxy for exposure. In order to assess any increased cancer mortality risk in municipalities potentially exposed to chemical facilities pollution (situated at a distance of ≤5 km from a chemical installation), we employed Bayesian Hierarchical Poisson Regression Models. This included two Bayesian inference methods: Integrated Nested Laplace Approximations (INLA) and Markov Chain Monte Carlo (MCMC, for validation). The reference category consisted of municipalities beyond the 5 km limit. We found higher mortality risk (relative risk, RR; estimated by INLA, 95% credible interval, 95%CrI) for both sexes for colorectal (RR, 1.09; 95%CrI, 1.05-1.15), gallbladder (1.14; 1.03-1.27), and ovarian cancers (1.10; 1.02-1.20) associated with organic chemical installations. Notably, pleural cancer (2.27; 1.49-3.41) in both sexes was related to fertilizer facilities. Associations were found for women, specifically for ovarian (1.11; 1.01-1.22) and breast cancers (1.06; 1.00-1.13) in the proximity of explosives/pyrotechnics installations; increased breast cancer mortality risk (1.10; 1.03-1.18) was associated with proximity to inorganic chemical installations. The results suggest that environmental exposure to pollutants from some types of chemical facilities may be associated with increased mortality from several different types of cancer.

The use of PanDrugs to prioritize anticancer drug treatments in a case of T-ALL based on individual genomic data.

BACKGROUND: Acute T-cell lymphoblastic leukaemia (T-ALL) is an aggressive disorder derived from immature thymocytes. The variability observed in clinical responses on this type of tumours to treatments, the high toxicity of current protocols and the poor prognosis of patients with relapse or refractory make it urgent to find less toxic and more effective therapies in the context of a personalized medicine of precision. METHODS: Whole exome sequencing and RNAseq were performed on DNA and RNA respectively, extracted of a bone marrow sample from a patient diagnosed with tumour primary T-ALL and double negative thymocytes from thymus control samples. We used PanDrugs, a computational resource to propose pharmacological therapies based on our experimental results, including lists of variants and genes. We extend the possible therapeutic options for the patient by taking into account multiple genomic events potentially sensitive to a treatment, the context of the pathway and the pharmacological evidence already known by large-scale experiments. RESULTS: As a proof-of-principle we used next-generation-sequencing technologies (Whole Exome Sequencing and RNA-Sequencing) in a case of diagnosed Pro-T acute lymphoblastic leukaemia. We identified 689 disease-causing mutations involving 308 genes, as well as multiple fusion transcript variants, alternative splicing, and 6652 genes with at least one principal isoform significantly deregulated. Only 12 genes, with 27 pathogenic gene variants, were among the most frequently mutated ones in this type of lymphoproliferative disorder. Among them, 5 variants detected in CTCF, FBXW7, JAK1, NOTCH1 and WT1 genes have not yet been reported in T-ALL pathogenesis. CONCLUSIONS: Personalized genomic medicine is a therapeutic approach involving the use of an individual's information data to tailor drug therapy. Implementing bioinformatics platform PanDrugs enables us to propose a prioritized list of anticancer drugs as the best theoretical therapeutic candidates to treat this patient has been the goal of this article. Of note, most of the proposed drugs are not being yet considered in the clinical practice of this type of cancer opening up the approach of new treatment possibilities.