Finite mixture clustering of human tissues with different levels of IGF-1 splice variants mRNA transcripts

BACKGROUND: This study addresses a recurrent biological problem, that is to define a formal clustering structure for a set of tissues on the basis of the relative abundance of multiple alternatively spliced isoforms mRNAs generated by the same gene. To this aim, we have used a model-based clustering approach, based on a finite mixture of multivariate Gaussian densities. However, given we had more technical replicates from the same tissue for each quantitative measurement, we also employed a finite mixture of linear mixed models, with tissue-specific random effects. RESULTS: A panel of human tissues was analysed through quantitative real-time PCR methods, to quantify the relative amount of mRNA encoding different IGF-1 alternative splicing variants. After an appropriate, preliminary, equalization of the quantitative data, we provided an estimate of the distribution of the observed concentrations for the different IGF-1 mRNA splice variants in the cohort of tissues by employing suitable kernel density estimators. We observed that the analysed IGF-1 mRNA splice variants were characterized by multimodal distributions, which could be interpreted as describing the presence of several sub-population, i.e. potential tissue clusters. In this context, a formal clustering approach based on a finite mixture model (FMM) with Gaussian components is proposed. Due to the presence of potential dependence between the technical replicates (originated by repeated quantitative measurements of the same mRNA splice isoform in the same tissue) we have also employed the finite mixture of linear mixed models (FMLMM), which allowed to take into account this kind of within-tissue dependence. CONCLUSIONS: The FMM and the FMLMM provided a convenient yet formal setting for a model-based clustering of the human tissues in sub-populations, characterized by homogeneous values of concentrations of the mRNAs for one or multiple IGF-1 alternative splicing isoforms. The proposed approaches can be applied to any cohort of tissues expressing several alternatively spliced mRNAs generated by the same gene, and can overcome the limitations of clustering methods based on simple comparisons between splice isoform expression levels

Finite mixtures of quantile and M-quantile regression models

In this paper we define a finite mixture of quan- tile and M-quantile regression models for heterogeneous and /or for dependent/clustered data. Components of the finite mixture represent clusters of individuals with homogeneous values of model parameters. For its flexibility and ease of estimation, the proposed approaches can be extended to ran- dom coefficients with a higher dimension than the simple random intercept case. Estimation of model parameters is obtained through maximum likelihood, by implementing an EM-type algorithm. The standard error estimates for model parameters are obtained using the inverse of the observed information matrix, derived through the Oakes (J R Stat Soc Ser B 61:479–482, 1999) formula in the M-quantile setting, and through nonparametric bootstrap in the quantile case. We present a large scale simulation study to analyse the practical behaviour of the proposed model and to evaluate the empiri- cal performance of the proposed standard error estimates for model parameters. We considered a variety of empirical set- tings in both the random intercept and the random coefficient case. The proposed modelling approaches are also applied to two well-known datasets which give further insights on their empirical behaviour

Quality of life and sexual functioning among endometrial cancer patients treated with one week adjuvant high-dose-rate vaginal brachytherapy schedule

Purpose: To examine quality of life (QOL) and sexual functioning in a series of patients with intermediate- and high-intermediate risk endometrial cancer, treated with exclusive adjuvant one week high-dose-rate (HDR) vaginal brachytherapy (VBT) schedule. Material and methods: Between July 2008 and October 2013, 55 patients with diagnosis of endometrial cancer were treated with adjuvant exclusive VBT. All patients had undergone surgical treatment with a laparotomy approach before VBT. Post-operative VBT was administered 6-8 weeks after surgery. Treatment was delivered to vaginal vault using Nucletron HDR unit with iridium-192 source at a dose of 21 Gy/3 fractions of 7 Gy each, three times a week, every other day, prescribed at 0.5 cm depth of vaginal wall, and 3 cm in length from the apex. QOL was assessed using European Organization for Research and Treatment of Cancer (EORTC) quality of life questionnaire Core-30 (QLQ-C30), and EORTC cancer-specific quality of life questionnaire (QLQ-CX24). Results: Median follow-up time was 92 months (range, 42-162 months). Questionnaires were carried out respectively at 1, 3, 6, 12, 24, 36, 48, and 60 months after the end of BT. Response rate to questionnaires was 100% (n = 55). Nineteen patients (35%) answered all the questions of surveys, while 36 patients (65%) completed the surveys, except for questions on sex activity, vaginal function, and sex enjoyment. Longitudinal analysis during 5-year follow-up period showed a statistically significant trend towards worsening of fatigue, constipation, and diarrhea. Overall physical functioning and role functioning was not impaired after VBT. Over the time, sex enjoyment improved, except for elderly patients. For emotional functioning, sex worry and social functioning presented no significant time-related effect. Conclusions: One week brachytherapy schedule to vaginal cuff is generally well-tolerated. QOL does not worsen after applying vaginal brachytherapy. brachytherapy; endometrial carcinoma; fatigue; quality of life; sexual disfunction

Inactive Atm abrogates DSB repair in mouse cerebellum more than does Atm loss, without causing a neurological phenotype

The genome instability syndrome, ataxia-telangiectasia (A-T) is caused by null mutations in the ATM gene, that lead to complete loss or inactivation of the gene's product, the ATM protein kinase. ATM is the primary mobilizer of the cellular response to DNA double-strand breaks (DSBs) – a broad signaling network in which many components are ATM targets. The major clinical feature of A-T is cerebellar atrophy, characterized by relentless loss of Purkinje and granule cells. In Atm-knockout (Atm-KO) mice, complete loss of Atm leads to a very mild neurological phenotype, suggesting that Atm loss is not sufficient to markedly abrogate cerebellar structure and function in this organism. Expression of inactive (“kinase-dead”) Atm (AtmKD) in mice leads to embryonic lethality, raising the question of whether conditional expression of AtmKD in the murine nervous system would lead to a more pronounced neurological phenotype than Atm loss. We generated two mouse strains in which AtmKD was conditionally expressed as the sole Atm species: one in the CNS and one specifically in Purkinje cells. Focusing our analysis on Purkinje cells, the dynamics of DSB readouts indicated that DSB repair was delayed longer in the presence of AtmKD compared to Atm loss. However, both strains exhibited normal life span and displayed no gross cerebellar histological abnormalities or significant neurological phenotype. We conclude that the presence of AtmKD is indeed more harmful to DSB repair than Atm loss, but the murine central nervous system can reasonably tolerate the extent of this DSB repair impairment. Greater pressure needs to be exerted on genome stability to obtain a mouse model that recapitulates the severe A-T neurological phenotype

Minimal Extrathyroidal Extension in Predicting 1-Year Outcomes: A Longitudinal Multicenter Study of Low-to-Intermediate-Risk Papillary Thyroid Carcinoma (ITCO#4)

Background: The role of minimal extrathyroidal extension (mETE) as a risk factor for persistent papillary thyroid carcinoma (PTC) is still debated. The aims of this study were to assess the clinical impact of mETE as a predictor of worse initial treatment response in PTC patients and to verify the impact of radioiodine therapy after surgery in patients with mETE. Methods: We reviewed all records in the Italian Thyroid Cancer Observatory database and selected 2237 consecutive patients with PTC who satisfied the inclusion criteria (PTC with no lymph node metastases and at least 1 year of follow-up). For each case, we considered initial surgery, histological variant of PTC, tumor diameter, recurrence risk class according to the American Thyroid Association (ATA) risk stratification system, use of radioiodine therapy, and initial therapy response, as suggested by ATA guidelines. Results: At 1-year follow-up, 1831 patients (81.8%) had an excellent response, 296 (13.2%) had an indeterminate response, 55 (2.5%) had a biochemical incomplete response, and 55 (2.5%) had a structural incomplete response. Statistical analysis suggested that mETE (odds ratio [OR] 1.16, p = 0.65), tumor size >2 cm (OR 1.45, p = 0.34), aggressive PTC histology (OR 0.55, p = 0.15), and age at diagnosis (OR 0.90, p = 0.32) were not significant risk factors for a worse initial therapy response. When evaluating the combination of mETE, tumor size, and aggressive PTC histology, the presence of mETE with a >2 cm tumor was significantly associated with a worse outcome (OR 5.27 [95% confidence interval], p = 0.014). The role of radioiodine ablation in patients with mETE was also evaluated. When considering radioiodine treatment, propensity score-based matching was performed, and no significant differences were found between treated and nontreated patients (p = 0.24). Conclusions: This study failed to show the prognostic value of mETE in predicting initial therapy response in a large cohort of PTC patients without lymph node metastases. The study suggests that the combination of tumor diameter and mETE can be used as a reliable prognostic factor for persistence and could be easily applied in clinical practice to manage PTC patients with low-to-intermediate risk of recurrent/persistent disease

The relationship between woody vegetation and environmental factors: A spatial discriminant analysis

A detailed analysis of the relationship between woody types and environmental variables (pedological and topographical) was carried out inside the city of Rome. Twenty-three sample sites 100 m 2 each were selected according to the principle that they were inside woody vegetation patches greater than 2.3 ha. Presence-absence data were analysed through hierarchical classification and principal coordinates analysis in order to detect woody vegetation types. The six groups identified were then analysed according to thirty-four variables: a spatial discriminant analysis was performed using soil physical and chemical variables measured in the A1 and A2 horizons, topographical variables (altitude, slope and aspect), and annual potential irradiation. This procedure was able to quantify the contribution of the spatial distribution of the samples with respect to that of the environmental variables, thus improving the discriminant model. The combination of three variables: Aspect, organic matter A2 and exchangeable cations A2 is the most effective in discriminating the woody types allowing a hypothesis for the planning and management of these communities

Random effect models for multivariate mixed data: A Parafac-based finite mixture approach

We discuss a flexible regression model for multivariate mixed responses. Dependence between outcomes is introduced via the joint distribution of discrete outcome- and individual-specific random effects that represent potential unobserved heterogeneity in each outcome profile. A different number of locations can be used for each margin, and the association structure is described by a tensor that can be further simplified by using the Parafac model. A case study illustrates the proposal