Abstract (1) Background tumor profiling enables patient survival prediction. The two essential parameters to be calibrated when designing a study based on tumor profiles from a cohort are the sequencing depth of RNA-seq technology and the number of patients. This calibration is carried out under cost constraints, and a compromise has to be found. In the context of survival data, the goal of this work is to benchmark the impact of the number of patients and of the sequencing depth of miRNA-seq and mRNA-seq on the predictive capabilities for both the Cox model with elastic net penalty and random survival forest. (2) Results we first show that the Cox model and random survival forest provide comparable prediction capabilities, with significant differences for some cancers. Second, we demonstrate that miRNA and/or mRNA data improve prediction over clinical data alone. mRNA-seq data leads to slightly better prediction than miRNA-seq, with the notable exception of lung adenocarcinoma for which the tumor miRNA profile shows higher predictive power. Third, we demonstrate that the sequencing depth of RNA-seq data can be reduced for most of the investigated cancers without degrading the prediction abilities, allowing the creation of independent validation sets at lower cost. Finally, we show that the number of patients in the training dataset can be reduced for the Cox model and random survival forest, allowing the use of different models on different patient subgroups. (3) Availability R script is available at https://github.com/remyJardillier/Survival_seq_depth
Abstract Clear cell renal cell carcinoma (ccRCC) accounts for 75% of kidney cancers. Due to the high recurrence rate, and treatment options that come with high costs and potential side effects correct prognosis of patient survival is essential for the successful and effective treatment of patients. Novel biomarkers could play an important role in the assessment of the overall survival of patients. COL7A1 encodes for collagen type VII, a constituent of the basal membrane. COL7A1 is associated with survival in many cancers; however, the prognostic value of COL7A1 expression as a standalone biomarker in ccRCC has not been investigated. We used Kaplan-Meier curves and Cox proportional hazards model to investigate the prognostic value of COL7A1, as well as Gene Set Enrichment Analysis to investigate genes that are co-expressed with COL7A1. COL7A1 expression was used to stratify patients into four groups of expression, where the 5-year survival probability of each group was 72.4%, 59.1%, 34.15%, and 8.6% in order of increasing expression. Additionally, COL7A1 expression was successfully used to further divide patients of each stage and histological grade into groups of high and low risk. Similar results were obtained in independent cohorts. In-vitro knockdown of COL7A1 expression significantly impacted ccRCC cells’ ability to migrate and proliferate. To conclude, we identified COL7A1 as a new prognosis marker that can stratify ccRCC patients.
Abstract Primary cilia are sensory organelles located at the cell surface. Their assembly is primed by centrosome migration to the apical surface. Yet surprisingly little is known about this initiating step. To gain insight into the mechanisms driving centrosome migration, we exploited the reproducibility of cell architecture on adhesive micropatterns to investigate the cytoskeletal remodeling supporting it. Microtubule network densification and bundling, with the transient formation of an array of cold-stable microtubules, and actin cytoskeleton asymmetric contraction participated in concert to destabilize basal centrosome position and drive apical centrosome migration. The distal appendage protein Cep164 appeared to be a key actor involved in the cytoskeleton remodeling and centrosome migration, whereas IFT88's role seemed to be restricted to axoneme elongation. Together our data elucidate the hitherto unexplored mechanism of centrosome migration and show that it is driven by the increase and clustering of mechanical forces to push the centrosome toward the cell apical pole.
La genetique de population, la demographie historique et le calcul electronique ont parcouru au debut des chemins differents. Ils peuvent neanmoins se rencontrer, la meme matiere servant aux deux sciences lesquelles utilisent la technique nouvelle. M. Jacques Gomila et Mlle Louise Guyon, du departement d'anthropologie de l'Universite de Montreal, ont realise cette jonction en etudiant, sur quelques communautes rurales du Canada, les caracteristiques demographiques et la consanguinite, au moyen des documents de base que constituent les registres paroissiaux. Cette presentation vaut plus encore par la methode que par les resultats, ceux-ci ne pouvant que s'etendre, grâce a la surete de celle-la.
Bacterial samples (Escherichia coli and Bacillus subtilis) have been analyzed by laser-induced breakdown spectroscopy (LIBS) using femtosecond pulses. We compare the obtained spectra with those resulting from the classical nanosecond LIBS. Specific features of femtosecond LIBS have been demonstrated, very attractive for analyzing biological sample: (i) a lower plasma temperature leading to negligible nitrogen and oxygen emissions from excited ambient air and a better contrast in detection of trace mineral species; and (ii) a specific ablation regime that favors intramolecular bonds emission with respect to atomic emission. A precise kinetic study of molecular band head intensities allows distinguishing the contribution of native CN bonds released by the sample from that due to carbon recombination with atmospheric nitrogen. Furthermore a sensitive detection of trace mineral elements provide specific spectral signature of different bacteria. An example is given for the Gram test provided by different magnesium emissions from Escherichia coli and Bacillus subtilis. An entire spectrum consists of hundred resolved lines belonging to 13 atomic or molecular species, which provides an ensemble of valuable data to identify different bacteria.
