Whole exome sequencing for determination of tumor mutation load in liquid biopsy from advanced cancer patients.

Tumor mutation load (TML) has been proposed as a biomarker of patient response to immunotherapy in several studies. TML is usually determined by tumor biopsy DNA (tDNA) whole exome sequencing (WES), therefore TML evaluation is limited by informative biopsy availability. Circulating cell free DNA (cfDNA) provided by liquid biopsy is a surrogate specimen to biopsy for molecular profiling. Nevertheless performing WES on DNA from plasma is technically challenging and the ability to determine tumor mutation load from liquid biopsies remains to be demonstrated. In the current study, WES was performed on cfDNA from 32 metastatic patients of various cancer types included into MOSCATO 01 (NCT01566019) and/or MATCHR (NCT02517892) molecular triage trials. Results from targeted gene sequencing (TGS) and WES performed on cfDNA were compared to results from tumor tissue biopsy. In cfDNA samples, WES mutation detection sensitivity was 92% compared to targeted sequencing (TGS). When comparing cfDNA-WES to tDNA-WES, mutation detection sensitivity was 53%, consistent with previously published prospective study comparing cfDNA-TGS to tDNA-TGS. For samples in which presence of tumor DNA was confirmed in cfDNA, tumor mutation load from liquid biopsy was correlated with tumor biopsy. Taken together, this study demonstrated that liquid biopsy may be applied to determine tumor mutation load. Qualification of liquid biopsy for interpretation is a crucial point to use cfDNA for mutational load estimation.

Hsa-miR-31-3p expression is linked to progression-free survival in patients with KRAS wild-type metastatic colorectal cancer treated with anti-EGFR therapy.

PURPOSE: To identify microRNAs (miRNA) that predict response to anti-EGFR antibodies in patients with wild-type KRAS metastatic colorectal cancer (mCRC). EXPERIMENTAL DESIGN: miRNA profiling was performed in a training set of 87 patients with mCRC refractory to chemotherapy treated with anti-EGFR antibodies. This included 33 fresh-frozen (FF) and 35 formalin-fixed paraffin-embedded (FFPE) samples retrospectively collected and 19 prospectively collected FF samples. An independent validation cohort consisting of 19 FF and 26 FFPE prospectively collected samples from patients with mCRC treated with anti-EGFR antibodies was used to confirm our findings. RESULTS: After screening the expression of 1,145 miRNAs in FF samples from the training set, we identified that hsa-miR-31-3p expression level was significantly associated with progression-free survival (PFS). Statistical models based on miRNA expression discriminated between high and low risk of progression for both FF and FFPE samples. These models were confirmed in the validation cohort for both FF [HR, 4.1; 95% confidence interval (CI), 1.1-15.3; P < 0.04] and FFPE samples (HR, 2.44; 95% CI, 1.1-5.4; P = 0.028). The percentage of variation of RECIST criteria in the validation series was significantly associated with the expression level of hsa-miR-31-3p (r(2) = 0.49; P = 0.0035) and risk status determined by hsa-miR-31-3p expression level (P = 0.02, Kruskal-Wallis rank test). Nomograms were built and validated to predict PFS-depending on hsa-miR-31-3p expression level. Following in vitro studies, we identified 47 genes regulated by hsa-miR-31-3p. CONCLUSION: Hsa-miR-31-3p seems to be a new mCRC biomarker whose expression level allows for the identification of patients with wild-type KRAS mCRC who are more likely to respond to anti-EGFR therapy.

A scoring strategy combining statistics and functional genomics supports a possible role for common polygenic variation in autism.

Autism spectrum disorders (ASD) are highly heritable complex neurodevelopmental disorders with a 4:1 male: female ratio. Common genetic variation could explain 40-60% of the variance in liability to autism. Because of their small effect, genome-wide association studies (GWASs) have only identified a small number of individual single-nucleotide polymorphisms (SNPs). To increase the power of GWASs in complex disorders, methods like convergent functional genomics (CFG) have emerged to extract true association signals from noise and to identify and prioritize genes from SNPs using a scoring strategy combining statistics and functional genomics. We adapted and applied this approach to analyze data from a GWAS performed on families with multiple children affected with autism from Autism Speaks Autism Genetic Resource Exchange (AGRE). We identified a set of 133 candidate markers that were localized in or close to genes with functional relevance in ASD from a discovery population (545 multiplex families); a gender specific genetic score (GS) based on these common variants explained 1% (P = 0.01 in males) and 5% (P = 8.7 × 10(-7) in females) of genetic variance in an independent sample of multiplex families. Overall, our work demonstrates that prioritization of GWAS data based on functional genomics identified common variants associated with autism and provided additional support for a common polygenic background in autism.

Does epilepsy in multiplex autism pedigrees define a different subgroup in terms of clinical characteristics and genetic risk?

BACKGROUND: Autism spectrum disorders (ASD) and epilepsy frequently occur together. Prevalence rates are variable, and have been attributed to age, gender, comorbidity, subtype of pervasive developmental disorder (PDD) and risk factors. Recent studies have suggested disparate clinical and genetic settings depending on simplex or multiplex autism. The aim of this study was to assess: 1) the prevalence of epilepsy in multiplex autism and its association with genetic and non-genetic risk factors of major effect, intellectual disability and gender; and 2) whether autism and epilepsy cosegregate within multiplex autism families. METHODS: We extracted from the Autism Genetic Resource Exchange (AGRE) database (n = 3,818 children from 1,264 families) all families with relevant medical data (n = 664 children from 290 families). The sample included 478 children with ASD and 186 siblings without ASD. We analyzed the following variables: seizures, genetic and non-genetic risk factors, gender, and cognitive functioning as assessed by Raven's Colored Progressive Matrices (RCPM) and Vineland Adaptive Behavior Scales (VABS). RESULTS: The prevalence of epilepsy was 12.8% in cases with ASD and 2.2% in siblings without ASD (P <10-5). With each RCPM or VABS measure, the risk of epilepsy in multiplex autism was significantly associated with intellectual disability, but not with gender. Identified risk factors (genetic or non-genetic) of autism tended to be significantly associated with epilepsy (P = 0.052). When children with prematurity, pre- or perinatal insult, or cerebral palsy were excluded, a genetic risk factor was reported for 6/59 (10.2%) of children with epilepsy and 12/395 (3.0%) of children without epilepsy (P = 0.002). Finally, using a permutation test, there was significant evidence that the epilepsy phenotype co-segregated within families (P <10-4). CONCLUSIONS: Epilepsy in multiplex autism may define a different subgroup in terms of clinical characteristics and genetic risk.

ABCA2 is a strong genetic risk factor for early-onset Alzheimer's disease.

Recent epidemiological, biological and genetic data indicate a relationship between cholesterol and Alzheimer's disease (AD) including the association of polymorphisms of ABCA1 (a gene that is known to participate in cholesterol and phospholipid transport) with AD prevalence. Based on these data, we postulated that genetic variation in the related and brain-specific ABCA2 gene leads to increase risk of AD. A large case-control study was conducted where the sample was randomly divided into a hypothesis-testing sample (230 cases/286 controls) and a validation sample (210 cases/233 controls). Among the 45 SNPs we tested, one synonymous SNP (rs908832) was found significantly associated with AD in both samples. Additional analyses performed on the whole sample showed a very strong association between this marker and early-onset AD (OR = 3.82, 95% C.I. = [2.00 - 7.30], P = 5 x 10(-5)). Further research is needed to understand the functional role of this polymorphism. However, together with the reported associations of AD with APOE, CYP46A1 and ABCA1, the present result adds a very significant support for the role of cholesterol and phospholipid homeostasis in AD and a rationale for testing novel cholesterol homeostasis-related therapeutic strategies in AD.