drexml: A command line tool and Python package for drug repurposing

We introduce drexml, a command line tool and Python package for rational data-driven drug repurposing. The package employs machine learning and mechanistic signal transduction modeling to identify drug targets capable of regulating a particular disease. In addition, it employs explainability tools to contextualize potential drug targets within the functional landscape of the disease. The methodology is validated in Fanconi Anemia and Familial Melanoma, two distinct rare diseases where there is a pressing need for solutions. In the Fanconi Anemia case, the model successfully predicts previously validated repurposed drugs, while in the Familial Melanoma case, it identifies a promising set of drugs for further investigation.

Characterization of the Common Genetic Variation in the Spanish Population of Navarre

Large-scale genomic studies have significantly increased our knowledge of genetic variability across populations. Regional genetic profiling is essential for distinguishing common benign variants from disease-causing ones. To this end, we conducted a comprehensive characterization of exonic variants in the population of Navarre (Spain), utilizing whole genome sequencing data from 358 unrelated individuals of Spanish origin. Our analysis revealed 61,410 biallelic single nucleotide variants (SNV) within the Navarrese cohort, with 35% classified as common (MAF > 1%). By comparing allele frequency data from 1000 Genome Project (excluding the Iberian cohort of Spain, IBS), Genome Aggregation Database, and a Spanish cohort (including IBS individuals and data from Medical Genome Project), we identified 1069 SNVs common in Navarre but rare (MAF ≤ 1%) in all other populations. We further corroborated this observation with a second regional cohort of 239 unrelated exomes, which confirmed 676 of the 1069 SNVs as common in Navarre. In conclusion, this study highlights the importance of population-specific characterization of genetic variation to improve allele frequency filtering in sequencing data analysis to identify disease-causing variants.

Real-world evidence with a retrospective cohort of 15,968 COVID-19 hospitalized patients suggests 21 new effective treatments

PURPOSE

Despite the extensive vaccination campaigns in many countries, COVID-19 is still a major worldwide health problem because of its associated morbidity and mortality. Therefore, finding efficient treatments as fast as possible is a pressing need. Drug repurposing constitutes a convenient alternative when the need for new drugs in an unexpected medical scenario is urgent, as is the case with COVID-19.

METHODS

Using data from a central registry of electronic health records (the Andalusian Population Health Database), the effect of prior consumption of drugs for other indications previous to the hospitalization with respect to patient outcomes, including survival and lymphocyte progression, was studied on a retrospective cohort of 15,968 individuals, comprising all COVID-19 patients hospitalized in Andalusia between January and November 2020.

RESULTS

Covariate-adjusted hazard ratios and analysis of lymphocyte progression curves support a significant association between consumption of 21 different drugs and better patient survival. Contrarily, one drug, furosemide, displayed a significant increase in patient mortality.

CONCLUSIONS

In this study we have taken advantage of the availability of a regional clinical database to study the effect of drugs, which patients were taking for other indications, on their survival. The large size of the database allowed us to control covariates effectively.

Functional Profiling of Soft Tissue Sarcoma Using Mechanistic Models

Soft tissue sarcoma is an umbrella term for a group of rare cancers that are difficult to treat. In addition to surgery, neoadjuvant chemotherapy has shown the potential to downstage tumors and prevent micrometastases. However, finding effective therapeutic targets remains a research challenge. Here, a previously developed computational approach called mechanistic models of signaling pathways has been employed to unravel the impact of observed changes at the gene expression level on the ultimate functional behavior of cells. In the context of such a mechanistic model, RNA-Seq counts sourced from the Recount3 resource, from The Cancer Genome Atlas (TCGA) Sarcoma project, and non-diseased sarcomagenic tissues from the Genotype-Tissue Expression (GTEx) project were utilized to investigate signal transduction activity through signaling pathways. This approach provides a precise view of the relationship between sarcoma patient survival and the signaling landscape in tumors and their environment. Despite the distinct regulatory alterations observed in each sarcoma subtype, this study identified 13 signaling circuits, or elementary sub-pathways triggering specific cell functions, present across all subtypes, belonging to eight signaling pathways, which served as predictors for patient survival. Additionally, nine signaling circuits from five signaling pathways that highlighted the modifications tumor samples underwent in comparison to normal tissues were found. These results describe the protective role of the immune system, suggesting an anti-tumorigenic effect in the tumor microenvironment, in the process of tumor cell detachment and migration, or the dysregulation of ion homeostasis. Also, the analysis of signaling circuit intermediary proteins suggests multiple strategies for therapy.

A Comprehensive Analysis of 21 Actionable Pharmacogenes in the Spanish Population: From Genetic Characterisation to Clinical Impact

The implementation of pharmacogenetics (PGx) is a main milestones of precision medicine nowadays in order to achieve safer and more effective therapies. Nevertheless, the implementation of PGx diagnostics is extremely slow and unequal worldwide, in part due to a lack of ethnic PGx information. We analysed genetic data from 3006 Spanish individuals obtained by different high-throughput (HT) techniques. Allele frequencies were determined in our population for the main 21 actionable PGx genes associated with therapeutical changes. We found that 98% of the Spanish population harbours at least one allele associated with a therapeutical change and, thus, there would be a need for a therapeutical change in a mean of 3.31 of the 64 associated drugs. We also identified 326 putative deleterious variants that were not previously related with PGx in 18 out of the 21 main PGx genes evaluated and a total of 7122 putative deleterious variants for the 1045 PGx genes described. Additionally, we performed a comparison of the main HT diagnostic techniques, revealing that after whole genome sequencing, genotyping with the PGx HT array is the most suitable solution for PGx diagnostics. Finally, all this information was integrated in the Collaborative Spanish Variant Server to be available to and updated by the scientific community.

Crosstalk between Metabolite Production and Signaling Activity in Breast Cancer

The reprogramming of metabolism is a recognized cancer hallmark. It is well known that different signaling pathways regulate and orchestrate this reprogramming that contributes to cancer initiation and development. However, recent evidence is accumulating, suggesting that several metabolites could play a relevant role in regulating signaling pathways. To assess the potential role of metabolites in the regulation of signaling pathways, both metabolic and signaling pathway activities of Breast invasive Carcinoma (BRCA) have been modeled using mechanistic models. Gaussian Processes, powerful machine learning methods, were used in combination with SHapley Additive exPlanations (SHAP), a recent methodology that conveys causality, to obtain potential causal relationships between the production of metabolites and the regulation of signaling pathways. A total of 317 metabolites were found to have a strong impact on signaling circuits. The results presented here point to the existence of a complex crosstalk between signaling and metabolic pathways more complex than previously was thought.

A crowdsourcing database for the copy-number variation of the Spanish population

BACKGROUND

Despite being a very common type of genetic variation, the distribution of copy-number variations (CNVs) in the population is still poorly understood. The knowledge of the genetic variability, especially at the level of the local population, is a critical factor for distinguishing pathogenic from non-pathogenic variation in the discovery of new disease variants.

RESULTS

Here, we present the SPAnish Copy Number Alterations Collaborative Server (SPACNACS), which currently contains copy number variation profiles obtained from more than 400 genomes and exomes of unrelated Spanish individuals. By means of a collaborative crowdsourcing effort whole genome and whole exome sequencing data, produced by local genomic projects and for other purposes, is continuously collected. Once checked both, the Spanish ancestry and the lack of kinship with other individuals in the SPACNACS, the CNVs are inferred for these sequences and they are used to populate the database. A web interface allows querying the database with different filters that include ICD10 upper categories. This allows discarding samples from the disease under study and obtaining pseudo-control CNV profiles from the local population. We also show here additional studies on the local impact of CNVs in some phenotypes and on pharmacogenomic variants. SPACNACS can be accessed at: http://csvs.clinbioinfosspa.es/spacnacs/ .

CONCLUSION

SPACNACS facilitates disease gene discovery by providing detailed information of the local variability of the population and exemplifies how to reuse genomic data produced for other purposes to build a local reference database.

An SPM-Enriched Marine Oil Supplement Shifted Microglia Polarization toward M2, Ameliorating Retinal Degeneration in rd10 Mice

Retinitis pigmentosa (RP) is the most common inherited retinal dystrophy causing progressive vision loss. It is accompanied by chronic and sustained inflammation, including M1 microglia activation. This study evaluated the effect of an essential fatty acid (EFA) supplement containing specialized pro-resolving mediators (SPMs), on retinal degeneration and microglia activation in rd10 mice, a model of RP, as well as on LPS-stimulated BV2 cells. The EFA supplement was orally administered to mice from postnatal day (P)9 to P18. At P18, the electrical activity of the retina was examined by electroretinography (ERG) and innate behavior in response to light were measured. Retinal degeneration was studied via histology including the TUNEL assay and microglia immunolabeling. Microglia polarization (M1/M2) was assessed by flow cytometry, qPCR, ELISA and histology. Redox status was analyzed by measuring antioxidant enzymes and markers of oxidative damage. Interestingly, the EFA supplement ameliorated retinal dysfunction and degeneration by improving ERG recording and sensitivity to light, and reducing photoreceptor cell loss. The EFA supplement reduced inflammation and microglia activation attenuating M1 markers as well as inducing a shift to the M2 phenotype in rd10 mouse retinas and LPS-stimulated BV2 cells. It also reduced oxidative stress markers of lipid peroxidation and carbonylation. These findings could open up new therapeutic opportunities based on resolving inflammation with oral supplementation with SPMs such as the EFA supplement.

Discovering potential interactions between rare diseases and COVID-19 by combining mechanistic models of viral infection with statistical modeling

Recent studies have demonstrated a relevant role of the host genetics in the coronavirus disease 2019 (COVID-19) prognosis. Most of the 7000 rare diseases described to date have a genetic component, typically highly penetrant. However, this vast spectrum of genetic variability remains yet unexplored with respect to possible interactions with COVID-19. Here, a mathematical mechanistic model of the COVID-19 molecular disease mechanism has been used to detect potential interactions between rare disease genes and the COVID-19 infection process and downstream consequences. Out of the 2518 disease genes analyzed, causative of 3854 rare diseases, a total of 254 genes have a direct effect on the COVID-19 molecular disease mechanism and 207 have an indirect effect revealed by a significant strong correlation. This remarkable potential of interaction occurs for >300 rare diseases. Mechanistic modeling of COVID-19 disease map has allowed a holistic systematic analysis of the potential interactions between the loss of function in known rare disease genes and the pathological consequences of COVID-19 infection. The results identify links between disease genes and COVID-19 hallmarks and demonstrate the usefulness of the proposed approach for future preventive measures in some rare diseases.

Real world evidence of calcifediol or vitamin D prescription and mortality rate of COVID-19 in a retrospective cohort of hospitalized Andalusian patients

COVID-19 is a major worldwide health problem because of acute respiratory distress syndrome, and mortality. Several lines of evidence have suggested a relationship between the vitamin D endocrine system and severity of COVID-19. We present a survival study on a retrospective cohort of 15,968 patients, comprising all COVID-19 patients hospitalized in Andalusia between January and November 2020. Based on a central registry of electronic health records (the Andalusian Population Health Database, BPS), prescription of vitamin D or its metabolites within 15–30 days before hospitalization were recorded. The effect of prescription of vitamin D (metabolites) for other indication previous to the hospitalization was studied with respect to patient survival. Kaplan–Meier survival curves and hazard ratios support an association between prescription of these metabolites and patient survival. Such association was stronger for calcifediol (Hazard Ratio, HR = 0.67, with 95% confidence interval, CI, of [0.50–0.91]) than for cholecalciferol (HR = 0.75, with 95% CI of [0.61–0.91]), when prescribed 15 days prior hospitalization. Although the relation is maintained, there is a general decrease of this effect when a longer period of 30 days prior hospitalization is considered (calcifediol HR = 0.73, with 95% CI [0.57–0.95] and cholecalciferol HR = 0.88, with 95% CI [0.75, 1.03]), suggesting that association was stronger when the prescription was closer to the hospitalization.

Mutational Characterization of Cutaneous Melanoma Supports Divergent Pathways Model for Melanoma Development

According to the divergent pathway model, cutaneous melanoma comprises a nevogenic group with a propensity to melanocyte proliferation and another one associated with cumulative solar damage (CSD). While characterized clinically and epidemiologically, the differences in the molecular profiles between the groups have remained primarily uninvestigated. This study has used a custom gene panel and bioinformatics tools to investigate the potential molecular differences in a thoroughly characterized cohort of 119 melanoma patients belonging to nevogenic and CSD groups. We found that the nevogenic melanomas had a restricted set of mutations, with the prominently mutated gene being BRAF. The CSD melanomas, in contrast, showed mutations in a diverse group of genes that included NF1, ROS1, GNA11, and RAC1. We thus provide evidence that nevogenic and CSD melanomas constitute different biological entities and highlight the need to explore new targeted therapies.

A comprehensive database for integrated analysis of omics data in autoimmune diseases

BACKGROUND

Autoimmune diseases are heterogeneous pathologies with difficult diagnosis and few therapeutic options. In the last decade, several omics studies have provided significant insights into the molecular mechanisms of these diseases. Nevertheless, data from different cohorts and pathologies are stored independently in public repositories and a unified resource is imperative to assist researchers in this field.

RESULTS

Here, we present Autoimmune Diseases Explorer ( https://adex.genyo.es ), a database that integrates 82 curated transcriptomics and methylation studies covering 5609 samples for some of the most common autoimmune diseases. The database provides, in an easy-to-use environment, advanced data analysis and statistical methods for exploring omics datasets, including meta-analysis, differential expression or pathway analysis.

CONCLUSIONS

This is the first omics database focused on autoimmune diseases. This resource incorporates homogeneously processed data to facilitate integrative analyses among studies.

Genome-scale mechanistic modeling of signaling pathways made easy: A bioconductor/cytoscape/web server framework for the analysis of omic data

Genome-scale mechanistic models of pathways are gaining importance for genomic data interpretation because they provide a natural link between genotype measurements (transcriptomics or genomics data) and the phenotype of the cell (its functional behavior). Moreover, mechanistic models can be used to predict the potential effect of interventions, including drug inhibitions. Here, we present the implementation of a mechanistic model of cell signaling for the interpretation of transcriptomic data as an R/Bioconductor package, a Cytoscape plugin and a web tool with enhanced functionality which includes building interpretable predictors, estimation of the effect of perturbations and assessment of the effect of mutations in complex scenarios.

A versatile workflow to integrate RNA-seq genomic and transcriptomic data into mechanistic models of signaling pathways

MIGNON is a workflow for the analysis of RNA-Seq experiments, which not only efficiently manages the estimation of gene expression levels from raw sequencing reads, but also calls genomic variants present in the transcripts analyzed. Moreover, this is the first workflow that provides a framework for the integration of transcriptomic and genomic data based on a mechanistic model of signaling pathway activities that allows a detailed biological interpretation of the results, including a comprehensive functional profiling of cell activity. MIGNON covers the whole process, from reads to signaling circuit activity estimations, using state-of-the-art tools, it is easy to use and it is deployable in different computational environments, allowing an optimized use of the resources available.

Mechanistic modeling of the SARS-CoV-2 disease map

Here we present a web interface that implements a comprehensive mechanistic model of the SARS-CoV-2 disease map. In this framework, the detailed activity of the human signaling circuits related to the viral infection, covering from the entry and replication mechanisms to the downstream consequences as inflammation and antigenic response, can be inferred from gene expression experiments. Moreover, the effect of potential interventions, such as knock-downs, or drug effects (currently the system models the effect of more than 8000 DrugBank drugs) can be studied. This freely available tool not only provides an unprecedentedly detailed view of the mechanisms of viral invasion and the consequences in the cell but has also the potential of becoming an invaluable asset in the search for efficient antiviral treatments.

CSVS, a crowdsourcing database of the Spanish population genetic variability

The knowledge of the genetic variability of the local population is of utmost importance in personalized medicine and has been revealed as a critical factor for the discovery of new disease variants. Here, we present the Collaborative Spanish Variability Server (CSVS), which currently contains more than 2000 genomes and exomes of unrelated Spanish individuals. This database has been generated in a collaborative crowdsourcing effort collecting sequencing data produced by local genomic projects and for other purposes. Sequences have been grouped by ICD10 upper categories. A web interface allows querying the database removing one or more ICD10 categories. In this way, aggregated counts of allele frequencies of the pseudo-control Spanish population can be obtained for diseases belonging to the category removed. Interestingly, in addition to pseudo-control studies, some population studies can be made, as, for example, prevalence of pharmacogenomic variants, etc. In addition, this genomic data has been used to define the first Spanish Genome Reference Panel (SGRP1.0) for imputation. This is the first local repository of variability entirely produced by a crowdsourcing effort and constitutes an example for future initiatives to characterize local variability worldwide. CSVS is also part of the GA4GH Beacon network. CSVS can be accessed at: http://csvs.babelomics.org/.

Immune Cell Associations with Cancer Risk

Proper immune system function hinders cancer development, but little is known about whether genetic variants linked to cancer risk alter immune cells. Here, we report 57 cancer risk loci associated with differences in immune and/or stromal cell contents in the corresponding tissue. Predicted target genes show expression and regulatory associations with immune features. Polygenic risk scores also reveal associations with immune and/or stromal cell contents, and breast cancer scores show consistent results in normal and tumor tissue. SH2B3 links peripheral alterations of several immune cell types to the risk of this malignancy. Pleiotropic SH2B3 variants are associated with breast cancer risk in BRCA1/2 mutation carriers. A retrospective case-cohort study indicates a positive association between blood counts of basophils, leukocytes, and monocytes and age at breast cancer diagnosis. These findings broaden our knowledge of the role of the immune system in cancer and highlight promising prevention strategies for individuals at high risk.

Mechanistic Models of Signaling Pathways Reveal the Drug Action Mechanisms behind Gender-Specific Gene Expression for Cancer Treatments

Despite the existence of differences in gene expression across numerous genes between males and females having been known for a long time, these have been mostly ignored in many studies, including drug development and its therapeutic use. In fact, the consequences of such differences over the disease mechanisms or the drug action mechanisms are completely unknown. Here we applied mechanistic mathematical models of signaling activity to reveal the ultimate functional consequences that gender-specific gene expression activities have over cell functionality and fate. Moreover, we also used the mechanistic modeling framework to simulate the drug interventions and unravel how drug action mechanisms are affected by gender-specific differential gene expression. Interestingly, some cancers have many biological processes significantly affected by these gender-specific differences (e.g., bladder or head and neck carcinomas), while others (e.g., glioblastoma or rectum cancer) are almost insensitive to them. We found that many of these gender-specific differences affect cancer-specific pathways or in physiological signaling pathways, also involved in cancer origin and development. Finally, mechanistic models have the potential to be used for finding alternative therapeutic interventions on the pathways targeted by the drug, which lead to similar results compensating the downstream consequences of gender-specific differences in gene expression.

Mechanistic models of signaling pathways deconvolute the glioblastoma single-cell functional landscape

Single-cell RNA sequencing is revealing an unexpectedly large degree of heterogeneity in gene expression levels across cell populations. However, little is known on the functional consequences of this heterogeneity and the contribution of individual cell fate decisions to the collective behavior of the tissues these cells are part of. Here, we use mechanistic modeling of signaling circuits, which reveals a complex functional landscape at single-cell level. Different clusters of neoplastic glioblastoma cells have been defined according to their differences in signaling circuit activity profiles triggering specific cancer hallmarks, which suggest different functional strategies with distinct degrees of aggressiveness. Moreover, mechanistic modeling of effects of targeted drug inhibitions at single-cell level revealed, how in some cells, the substitution of VEGFA, the target of bevacizumab, by other expressed proteins, like PDGFD, KITLG and FGF2, keeps the VEGF pathway active, insensitive to the VEGFA inhibition by the drug. Here, we describe for the first time mechanisms that individual cells use to avoid the effect of a targeted therapy, providing an explanation for the innate resistance to the treatment displayed by some cells. Our results suggest that mechanistic modeling could become an important asset for the definition of personalized therapeutic interventions.

Exploring the druggable space around the Fanconi anemia pathway using machine learning and mechanistic models

BACKGROUND

In spite of the abundance of genomic data, predictive models that describe phenotypes as a function of gene expression or mutations are difficult to obtain because they are affected by the curse of dimensionality, given the disbalance between samples and candidate genes. And this is especially dramatic in scenarios in which the availability of samples is difficult, such as the case of rare diseases.

RESULTS

The application of multi-output regression machine learning methodologies to predict the potential effect of external proteins over the signaling circuits that trigger Fanconi anemia related cell functionalities, inferred with a mechanistic model, allowed us to detect over 20 potential therapeutic targets.

CONCLUSIONS

The use of artificial intelligence methods for the prediction of potentially causal relationships between proteins of interest and cell activities related with disease-related phenotypes opens promising avenues for the systematic search of new targets in rare diseases.

Breast Cancer in Very Young Patients in a Spanish Cohort: Age as an Independent Bad Prognostic Indicator

Purpose:

Breast cancer (BC) in very young women (BCVY) is more aggressive than in older women. The purpose of this study was to evaluate the relevance of a range of clinico-pathological factors in the prognosis of BCVY patients.

Methods:

We retrospectively analyzed 258 patients diagnosed with BCVY at our hospital from 1998 to 2014; the control group comprised 101 older patients with BC. We correlated clinicopathological factors, treatments, relapse and exitus with age and with previously published miRNA expression data.

Results:

We identified some significant differences in risk factors between BCVY and older patients. The age at menarche, number of pregnancies, and age at first pregnancy were lower in the BCVY group and had a greater probability of recurrence and death in all cases. Lymph node-positive patients in the BCVY group are associated with a worse prognosis (P = .02), an immunohistochemical HER2⁺ subtype, and disease relapse (P = .03). Moreover, there was a shorter time between diagnosis and first relapse in BCVY patients compared with controls, and they were more likely to die from the disease (P = .002). Finally, from our panel of miRNAs deregulated in BC, reduced miR-30c expression was associated with more aggressive BC in very young patients, lower overall survival, and with axillary lymph node metastases.

Conclusions:

Patient age and axillary lymph node status post-surgery are independent and significant predictors of distant disease-free survival, local recurrence-free survival, and overall survival. The HER2⁺ subtype and lower miR-30c expression are related to poor prognosis in lymph node-positive young BC patients.

Epigenetic changes in localized gastric cancer: the role of RUNX3 in tumor progression and the immune microenvironment

Gastric cancer (GC) pathogenesis involves genetic, epigenetic and environmental factors. Epigenetic alterations, such as DNA methylation are considered pivotal in the inactivation of tumor-related genes. We assessed a methylation panel of 5 genes to study their association to GC progression and microsatellite instability (MSI), and studied the role of RUNX3 in GC pathogenesis and the tumor immune microenvironment.The methylation status of 47 promoter-CpG islands was studied through MALDI-TOF mass spectrometry analysis in 35 Microsatellite stable (MSS) GC, 26 MSI, and 18 cancer-free samples (CFS), and 6 MSS GC and 4 MSI GC cell lines. We also studied RUNX3 expression by immunohistochemistry (IHC) in 40 samples, and validated differences in methylation levels between tumor, normal, and immune tissue in 14 additional samples.Unsupervised hierarchical clustering of methylation levels revealed no distinct subgroups between MSI and MSS samples or cell lines. CFSs clustered together showing higher levels of RUNX3 methylation compared to GC samples. RUNX3 showed protein silencing in cancer and normal mucosa, compared to inflammatory peritumoural infiltrate in almost all cases, showing a non-lymphocytic predominant pattern and being correlated with epigenetic silencing.Our results show aberrant promoter's methylation in APC, CDH1, CDKN2A, MLH1 and RUNX3 associated with GC, as well as a non-lymphocytic predominant infiltrate with high expression of RUNX3. Deep study of RUNX3 inflammation signaling could help in understanding inflammation and immune activation in the tumor microenvironment.

Involvement of ANXA5 and ILKAP in susceptibility to malignant melanoma

Single nucleotide-polymorphisms (SNPs) are a source of diversity among human population, which may be responsible for the different individual susceptibility to diseases and/or response to drugs, among other phenotypic traits. Several low penetrance susceptibility genes associated with malignant melanoma (MM) have been described, including genes related to pigmentation, DNA damage repair and oxidative stress pathways. In the present work, we conducted a candidate gene association study based on proteins and genes whose expression we had detected altered in melanoma cell lines as compared to normal melanocytes. The result was the selection of 88 loci and 384 SNPs, of which 314 fulfilled our quality criteria for a case-control association study. The SNP rs6854854 in ANXA5 was statistically significant after conservative Bonferroni correction when 464 melanoma patients and 400 controls were analyzed in a discovery Phase I. However, this finding could not be replicated in the validation phase, perhaps because the minor allele frequency of SNP rs6854854 varies depending on the geographical region considered. Additionally, a second SNP (rs6431588) located on ILKAP was found to be associated with melanoma after considering a combined set of 1,883 MM cases and 1,358 disease-free controls. The OR was 1.29 (95% CI 1.12–1.48; p-value = 4×10⁻⁴). Both SNPs, rs6854854 in ANXA5 and rs6431588 in ILKAP, show population structure, which, assuming that the Spanish population is not significantly structured, suggests a role of these loci on a specific genetic adaptation to different environmental conditions. Furthermore, the biological relevance of these genes in MM is supported by in vitro experiments, which show a decrease in the transcription levels of ANXA5 and ILKAP in melanoma cells compared to normal melanocytes.

Abstract P5-13-14: Breast cancer in very young patient is a more aggressive entity independent from breast cancer subtype

BACKGROUND AND OBJECTIVES: Breast cancer in very young patients (< 35 years) (BCVY) is an uncommon disease and when it occurs it usually has aggressive biological characteristics. Whether this effect is due to an overrepresentation of aggressive breast cancer subtypes in younger patients or not remains an issue of controversial. The objective of this study was to identify potential differences in the molecular and clinical features of breast carcinomas from patients < = 35 years versus a cohort of older counterparts previously matched by breast cancer subtype.

METHODS: We performed a retrospective analysis of a prospectively maintained database that included 424 patients diagnosed with an invasive breast carcinoma from 1995 to 2012 at Hospital Clinico of Valencia. We selected 89 patients separated in two groups, the study group with very young women ≤ 35 years old and with no BRCA mutation or unknown and a second group with women older than 50 years. Data related to clinical and pathological features from both groups such as tumor size, nodal status, histological grade, Ki 67 labeling oestrogen and progesterone receptor and HER2 overexpression were obtained from medical records and we used the statistic model of chi-squared to compare the two groups.

RESULTS: Of the 89 patients, 43 patients ≤ 35 year were included in the study group (median age 31.4 years, standard deviation (SD): 3.82) and 46 patients >50 years were included in the control group (median age 66.4 years, SD: 10.00). Ductal carcinoma was the most common histological subtype in both groups (88.4% of BCVY and 78.3% of the old woman). The majority of tumors were ER and PR positive in both groups, but younger women had a higher proportion of HER2 positive tumors, although the result was not significant. By subtype 57.4% of BCVY presented an immunohistochemical luminal subtype, compared to 71.7% in older patients. Triple negative and HER2 profiles were 11.6% and 34.8% in youngest versus 15.2% and 13.04% in older women respectively. No statistically significant differences were found in terms of breast cancer subtype (p = 0.279)). However, BCVY had a higher pathological grade (56% younger patients had grade IIII vs 26% in oldest, p = 0.002), higher proportion of Ki67 >30% (32.5% of youngest versus 17.4% in older women, p = 0.008), larger tumors (16.3% of BCVY had size tumor > 5 cm, versus 2.2% in controls, p<0.0001) and more frequent nodal involvement (39.5% in young women vs 28.2% in oldest, p = 0.0264).

CONCLUSIONS: Patients diagnosed with breast cancer at ≤ 35 years present more aggressive tumors compared to older patients. These data suggest that BCVY is a distinct entity, further studies to confirm these findings are needed.

Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P5-13-14.

Abstract P4-07-04: A distinctive miRNA profile highlights breast cancer in very young women (BCVY) as a new molecular subgroup

Background: Although less frequent (1% of all breast cancer) than in older women, breast cancer (BC) in very young women (BCVY),(≤35 years old) often exhibits larger tumor sizes, high pathological grade, high proliferation percentage, nodal involvement, and greater HER2+ percentage, usually associated with a poorer prognosis. BC and BCVY might arise as different disease entities derived from different underlying mechanisms.

MicroRNAs (miRNAs) are short RNA molecules with post-transcriptional regulatory function, usually silencing targeted mRNAs. Recently, miRNA profiling has arisen as major approaching study technique, demonstrating a widespread miRNA deregulation in various tumor types.

In this study we offer a miRNA profile of a subset of BCVY patients and evaluate whether there are any miRNA deregulated pointing out some pathway to better understand the ongoing mechanism and characterize BCVY as a new molecular entity.

Material and methods: We performed a comprehensive study of miRNA expression using miRNA Affymetrix 2.0 array. We extracted RNA from FFPE tumor tissue of both 44 BC patients ≤35years (BCVY) and 46 older than 45years in two age groups (45-65 and >65), we used normal breast tissue as control and evaluated the differences in expression of each age group. We tried to validate most interesting miRNA by qRT-PCR. We performed enrichment analysis of multiple miRNA target genes (DIANA mirpath) to search for putative pathways that could be deregulated by the miRNAs.

Results: We obtained a differential and unique miRNA expression profile of 121 miRNAs (p-value<0.05), 96 of those with FDR<0.05. After hierarchical clustering, samples were unsupervised grouped according to their age, neither by subtype nor by tumor characteristics. Of the 11 miRNA selected for validation, we were able to validate differences in the expression of 6 miRNAs: miR-1228*, miR-3196, miR-1275, miR-92b, miR-139, miR-1207, moreover, all of the miRNAs maintained the expression's trend. The validated miRNAs pointed out pathways related with cell motility and invasion (adherens junction, chondroitin sulfate biosynthesis, cell adhesion molecules) and cell proliferation (calcium signaling, wnt signaling).

Conclusion: We performed a comprehensive study of the miRNA expression on a total of 89 BC patients, detecting a differential molecular profile in BCVY patients, suggesting that there might be a different underlying mechanism and that BCVY could be identified as a different entity.

Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P4-07-04.

High stability of microRNAs in tissue samples of compromised quality

Degradation of tissue samples limits performing RNA-based molecular studies, but little is known about the potential usefulness of samples of compromised quality for studies focused on miRNAs. In this work we analyze a series of cryopreserved tissue samples (n = 14), frozen samples that underwent a severe thawing process (n = 10), and their paired formalin-fixed paraffin-embedded (FFPE) tissue samples (n = 24) from patients with breast cancer obtained during primary surgical resection and collected in 2011. Quality and integrity analyses of the total and small fraction of RNA were carried out. Recovery of specific RNA molecules (miRNAs hsa-miR-21, hsa-miR-125b, and hsa-miR-191; snoRNA RNU6B; and mRNAs GAPDH and HPRT1) was also analyzed by quantitative RT-PCR. Our results suggest that visualisation of the small RNA electrophoretic profiles obtained using the Agilent 2100 bioanalyzer makes it possible to differentiate between the three groups of samples (optimally frozen, thawed, and FFPE). We demonstrate that specific miRNA molecules can be similarly recovered from different tissue sample sources, which supports their high degree of stability. We conclude that miRNAs are robustly detected irrespective of the quality of the tissue sample. In this regard, a word of caution should be raised before degraded samples are discarded: although prior quality assessment of the biological material to be analyzed is recommended, our work demonstrates that degraded tissue samples are also suitable for miRNA studies.