Investigating geographic and temporal genetic variation in the black grouse (Lyrurus tetrix) in the Italian Alps

The black grouse (Lyrurus tetrix) is a Galliform distributed across northern Eurasia, and is a game bird in most EU countries. Although the species is listed as ‘Least Concern’ by the IUCN, populations at the western and southern edges of its range are considered ‘Vulnerable’ due to increasing habitat fragmentation and human disturbance. Between 1995 and 2017, in collaboration with several hunting associations, we collected more than 600 black grouse samples across seven regions of the Italian Alps. Ten microsatellite markers (STRs) and 2442 Single Nucleotide Polymorphisms (SNPs) were analysed in large subsets of the collected data, with the aim of identifying environmental, temporal and anthropic factors that affect the distribution and level of genomic variation. The main factor shaping the genetic distances between populations based on STRs is the geographic distance between them (i.e. isolation-bydistance), but even the populations on the two extremes of our sampling area are very similar (Fst between the two regions = 0.053). SNP data supports the STR analysis. However, isolation-by-resistance methods for the larger STR data set show that both higher altitudes and urban areas inhibit movement of grouse between populations. While temporal analysis of STRs for the Trentino-Alto Adige region showed no significant change in the mean number of alleles and allelic size range between the two time frames studied (e.g. mean number of alleles 1995-1999: 8.8, 2009-2010: 8.2), and the expected heterozygosity was high in both time frames (1995-1999: 0.740, 2009-2010: 0.722). While black grouse population size is reportedly decreasing, our results suggest there is no measurable genetic impact from this trend. Hence this dataset provides a basis for future monitoring of genetic diversity in this charismatic alpine species

The predictive and prognostic potential of plasma telomerase reverse transcriptase (TERT) RNA in rectal cancer patients

Background: Preoperative chemoradiotherapy (CRT) followed by surgery is the standard care for locally advanced rectal cancer, but tumour response to CRT and disease outcome are variable. The current study aimed to investigate the effectiveness of plasma telomerase reverse transcriptase (TERT) levels in predicting tumour response and clinical outcome. Methods: 176 rectal cancer patients were included. Plasma samples were collected at baseline (before CRT\ubcT0), 2 weeks after CRT was initiated (T1), post-CRT and before surgery (T2), and 4\u20138 months after surgery (T3) time points. Plasma TERT mRNA levels and total cell-free RNA were determined using real-time PCR. Results: Plasma levels of TERT were significantly lower at T2 (Po0.0001) in responders than in non-responders. Post-CRT TERT levels and the differences between pre- and post-CRT TERT levels independently predicted tumour response, and the prediction model had an area under curve of 0.80 (95% confidence interval (CI) 0.73\u20130.87). Multiple analysis demonstrated that patients with detectable TERT levels at T2 and T3 time points had a risk of disease progression 2.13 (95% CI 1.10\u20134.11)-fold and 4.55 (95% CI 1.48\u201313.95)-fold higher, respectively, than those with undetectable plasma TERT levels. Conclusions: Plasma TERT levels are independent markers of tumour response and are prognostic of disease progression in rectal cancer patients who undergo neoadjuvant therapy

mismatch repair deficiency mmrd in glioma patients pts frequency and correlation with clinical histological and molecular characteristics

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Altered tumor formation and evolutionary selection of genetic variants in the human MDM4 oncogene

A large body of evidence strongly suggests that the p53 tumor suppressor pathway is central in reducing cancer frequency in vertebrates. The protein product of the haploinsufficient mouse double minute 2 (MDM2) oncogene binds to and inhibits the p53 protein. Recent studies of human genetic variants in p53 and MDM2 have shown that single nucleotide polymorphisms (SNPs) can affect p53 signaling, confer cancer risk, and suggest that the pathway is under evolutionary selective pressure (1–4). In this report, we analyze the haplotype structure of MDM4, a structural homolog of MDM2, in several different human populations. Unusual patterns of linkage disequilibrium (LD) in the haplotype distribution of MDM4 indicate the presence of candidate SNPs that may also modify the efficacy of the p53 pathway. Association studies in 5 different patient populations reveal that these SNPs in MDM4 confer an increased risk for, or early onset of, human breast and ovarian cancers in Ashkenazi Jewish and European cohorts, respectively. This report not only implicates MDM4 as a key regulator of tumorigenesis in the human breast and ovary, but also exploits for the first time evolutionary driven linkage disequilibrium as a means to select SNPs of p53 pathway genes that might be clinically relevant

Altered tumor formation and evolutionary selection of genetic variants in the human MDM4 oncogene

A large body of evidence strongly suggests that the p53 tumor suppressor pathway is central in reducing cancer frequency in vertebrates. The protein product of the haploinsufficient mouse double minute 2 (MDM2) oncogene binds to and inhibits the p53 protein. Recent studies of human genetic variants in p53 and MDM2 have shown that single nucleotide polymorphisms (SNPs) can affect p53 signaling, confer cancer risk, and suggest that the pathway is under evolutionary selective pressure (1–4). In this report, we analyze the haplotype structure of MDM4, a structural homolog of MDM2, in several different human populations. Unusual patterns of linkage disequilibrium (LD) in the haplotype distribution of MDM4 indicate the presence of candidate SNPs that may also modify the efficacy of the p53 pathway. Association studies in 5 different patient populations reveal that these SNPs in MDM4 confer an increased risk for, or early onset of, human breast and ovarian cancers in Ashkenazi Jewish and European cohorts, respectively. This report not only implicates MDM4 as a key regulator of tumorigenesis in the human breast and ovary, but also exploits for the first time evolutionary driven linkage disequilibrium as a means to select SNPs of p53 pathway genes that might be clinically relevant

BCR::ABL1 levels at first month after TKI discontinuation predict subsequent maintenance of treatment-free remission: A study from the “GRUPPO TRIVENETO LMC”

We analyzed BCR::ABL1 expression at stop and in the first month after discontinuation in 168 chronic myeloid leukemia patients who stopped imatinib or 2nd generation tyrosine kinase inhibitors (2G-TKIs) while in sustained deep molecular response. Patients were divided among those who maintained response (group 1, n = 123) and those who lost major molecular response (group 2, n = 45). Mean BCR::ABL1 RNA levels 1 month after discontinuation were higher in group 2 than in group 1 (p = 0.0005) and the difference was more evident 2 months after stop (p < 0.0001). The same trend was found both for imatinib and 2G-TKIs. A receiver operating characteristic (ROC) analysis to determine a threshold value of BCR::ABL1 at 1 month after discontinuation identified a cut-off value of 0.0051%, with 92.2% specificity, 31.7% sensitivity and a likelihood ratio of 4.087

Morphological variation in a secondary contact between divergent lineages of brown trout (Salmo trutta) from the Iberian Peninsula

The aim of this study was to analyze the morphological variation of brown trout (Salmo trutta) in the Duero basin, an Atlantic river basin in the Iberian Peninsula, where a spatial segregation of two divergent lineages was previously reported, based on isozyme, microsatellite and mtDNA data. In these studies, two divergent pure regions (Pisuerga and Lower-course) and several hybrid populations between them were identified. Morphological variation was evaluated in 11 populations representative of the genetic differentiation previously observed in the Duero basin, using multivariate analysis on 12 morphometric and 4 meristic traits. A large differentiation between populations was observed (interpopulation component of variance: 41.8%), similar to that previously detected with allozymes and microsatellites. Morphometric differentiation was also reflected by the high classification success of pure and hybrid individuals to their respective populations, using multivariate discriminant functions (94.1% and 79.0%, respectively). All multivariate and clustering analyses performed demonstrated a strong differentiation between the pure regions. The hybrid populations, though showing large differentiation among them, evidenced an intermediate position between the pure samples. Head and body shape traits were the most discriminant among the morphometric characters, while pectoral rays and gillrakers were the most discriminant among the meristic traits. These results confirmed the high divergence of the brown trout from the Duero basin and suggest some traits on which selection could be acting to explain the spatial segregation observed

Temozolomide 3 weeks on and 1 week off as first-line therapy for recurrent glioblastoma: phase II study from gruppo italiano cooperativo di neuro-oncologia (GICNO)

The efficacy of temozolomide strongly depends on O6-alkylguanine DNA-alkyl transferase (AGAT), which repairs DNA damage caused by the drug itself. Low-dose protracted temozolomide administration can decrease AGAT activity. The main end point of the present study was therefore to test progression-free survival at 6 months (PFS-6) in glioblastoma patients following a prolonged temozolomide schedule. Chemonaïve glioblastoma patients with disease recurrence or progression after surgery and standard radiotherapy were considered eligible. Chemotherapy cycles consisted of temozolomide 75 mg/m2/daily for 21 days every 28 days until disease progression. O6-methyl-guanine-DNA-methyl-tranferase (MGMT) was determined in 22 patients (66.7%). A total of 33 patients (median age 57 years, range 31–71) with a median KPS of 90 (range 60–100) were accrued. The overall response rate was 9%, and PFS-6 30.3% (95% CI:18–51%). No correlation was found between the MGMT promoter methylation status of the tumours and the overall response rate, time to progression and survival. In 153 treatment cycles delivered, the most common grade 3/4 event was lymphopoenia. The prolonged temozolomide schedule considered in the present study is followed by a high PFS-6 rate; toxicity is acceptable. Further randomised trials should therefore be conducted to confirm the efficacy of this regimen

A Model-Based Bayesian Estimation of the Rate of Evolution of VNTR Loci in Mycobacterium tuberculosis

Variable numbers of tandem repeats (VNTR) typing is widely used for studying the bacterial cause of tuberculosis. Knowledge of the rate of mutation of VNTR loci facilitates the study of the evolution and epidemiology of Mycobacterium tuberculosis. Previous studies have applied population genetic models to estimate the mutation rate, leading to estimates varying widely from around to per locus per year. Resolving this issue using more detailed models and statistical methods would lead to improved inference in the molecular epidemiology of tuberculosis. Here, we use a model-based approach that incorporates two alternative forms of a stepwise mutation process for VNTR evolution within an epidemiological model of disease transmission. Using this model in a Bayesian framework we estimate the mutation rate of VNTR in M. tuberculosis from four published data sets of VNTR profiles from Albania, Iran, Morocco and Venezuela. In the first variant, the mutation rate increases linearly with respect to repeat numbers (linear model); in the second, the mutation rate is constant across repeat numbers (constant model). We find that under the constant model, the mean mutation rate per locus is (95% CI: ,)and under the linear model, the mean mutation rate per locus per repeat unit is (95% CI: ,). These new estimates represent a high rate of mutation at VNTR loci compared to previous estimates. To compare the two models we use posterior predictive checks to ascertain which of the two models is better able to reproduce the observed data. From this procedure we find that the linear model performs better than the constant model. The general framework we use allows the possibility of extending the analysis to more complex models in the future