grofit: Fitting Biological Growth Curves with R

The grofit package was developed to fit many growth curves obtained under different conditions in order to derive a conclusive dose-response curve, for instance for a compound that potentially affects growth. grofit fits data to different parametric models and in addition provides a model free spline method to circumvent systematic errors that might occur within application of parametric methods. This amendment increases the reliability of the characteristic parameters (e.g.,lag phase, maximal growth rate, stationary phase) derived from a single growth curve. By relating obtained parameters to the respective condition (e.g.,concentration of a compound) a dose response curve can be derived that enables the calculation of descriptive pharma-/toxicological values like half maximum effective concentration (EC50). Bootstrap and cross-validation techniques are used for estimating confidence intervals of all derived parameters.

Germline ancestry influences the evolutionary disease course in lung adenocarcinomas

Evolutionary Applications published by John Wiley & Sons Ltd Precision medicine relies on targeting specific somatic alterations present in a patient's tumor. However, the extent to which germline ancestry may influence the somatic burden of disease has received little attention. We estimated the genetic ancestry of non-small-cell lung cancer (NSCLC) patients and performed an in-depth analysis of the influence of genetic ancestry on the evolutionary disease course. Compared with European Americans (EA), African Americans (AA) with lung adenocarcinoma (LUAD) were found to be significantly younger and smoke significantly less. However, LUADs from AAs exhibited a significantly higher somatic mutation burden, with a more pronounced tobacco carcinogen footprint and increased frequencies of alterations affecting cancer genes. Conversely, no significant differences were observed between lung squamous cell carcinomas (LUSC) from EAs and AAs. Our results suggest germline ancestry influences the somatic evolution of LUAD but not LUSC

A Breast Cancer Meta-Analysis of Two Expression Measures of Chromosomal Instability Reveals a Relationship with Younger Age at Diagnosis and High Risk Histopathological Variables

Breast cancer in younger patients often presents with adverse histopathological features, including increased frequency of estrogen receptor negative and lymph node positive disease status. Chromosomal instability (CIN) is increasingly recognised as an important prognostic variable in solid tumours. In a breast cancer meta-analysis of 2423 patients we examine the relationship between clinicopathological parameters and two distinct chromosomal instability gene expression signatures in order to address whether younger age at diagnosis is associated with increased tumour genome instability. We find that CIN, assessed by the two independently derived CIN expression signatures, is significantly associated with increased tumour size, ER negative or HER2 positive disease, higher tumour grade and younger age at diagnosis in ER negative breast cancer. These data support the hypothesis that chromosomal instability may be a defining feature of breast cancer biology and clinical outcome

A breast cancer meta-analysis of two expression measures of chromosomal instability reveals a relationship with younger age at diagnosis and high risk histopathological variables

Breast cancer in younger patients often presents with adverse histopathological features, including increased frequency of estrogen receptor negative and lymph node positive disease status. Chromosomal instability (CIN) is increasingly recognised as an important prognostic variable in solid tumours. In a breast cancer meta-analysis of 2423 patients we examine the relationship between clinicopathological parameters and two distinct chromosomal instability gene expression signatures in order to address whether younger age at diagnosis is associated with increased tumour genome instability. We find that CIN, assessed by the two independently derived CIN expression signatures, is significantly associated with increased tumour size, ER negative or HER2 positive disease, higher tumour grade and younger age at diagnosis in ER negative breast cancer. These data support the hypothesis that chromosomal instability may be a defining feature of breast cancer biology and clinical outcome

Loss of USP28 and SPINT2 expression promotes cancer cell survival after whole genome doubling

Background Whole genome doubling is a frequent event during cancer evolution and shapes the cancer genome due to the occurrence of chromosomal instability. Yet, erroneously arising human tetraploid cells usually do not proliferate due to p53 activation that leads to CDKN1A expression, cell cycle arrest, senescence and/or apoptosis. Methods To uncover the barriers that block the proliferation of tetraploids, we performed a RNAi mediated genome-wide screen in a human colorectal cancer cell line (HCT116). Results We identified 140 genes whose depletion improved the survival of tetraploid cells and characterized in depth two of them: SPINT2 and USP28. We found that SPINT2 is a general regulator of CDKN1A transcription via histone acetylation. Using mass spectrometry and immunoprecipitation, we found that USP28 interacts with NuMA1 and affects centrosome clustering. Tetraploid cells accumulate DNA damage and loss of USP28 reduces checkpoint activation, thus facilitating their proliferation. Conclusions Our results indicate three aspects that contribute to the survival of tetraploid cells: (i) increased mitogenic signaling and reduced expression of cell cycle inhibitors, (ii) the ability to establish functional bipolar spindles and (iii) reduced DNA damage signaling

DNA replication stress mediates APOBEC3 family mutagenesis in breast cancer

BACKGROUND: The APOBEC3 family of cytidine deaminases mutate the cancer genome in a range of cancer types. Although many studies have documented the downstream effects of APOBEC3 activity through next-generation sequencing, less is known about their upstream regulation. In this study, we sought to identify a molecular basis for APOBEC3 expression and activation. RESULTS: HER2 amplification and PTEN loss promote DNA replication stress and APOBEC3B activity in vitro and correlate with APOBEC3 mutagenesis in vivo. HER2-enriched breast carcinomas display evidence of elevated levels of replication stress-associated DNA damage in vivo. Chemical and cytotoxic induction of replication stress, through aphidicolin, gemcitabine, camptothecin or hydroxyurea exposure, activates transcription of APOBEC3B via an ATR/Chk1-dependent pathway in vitro. APOBEC3B activation can be attenuated through repression of oncogenic signalling, small molecule inhibition of receptor tyrosine kinase signalling and alleviation of replication stress through nucleoside supplementation. CONCLUSION: These data link oncogene, loss of tumour suppressor gene and drug-induced replication stress with APOBEC3B activity, providing new insights into how cytidine deaminase-induced mutagenesis might be activated in tumourigenesis and limited therapeutically

Acute MUS81 depletion leads to replication fork slowing and a constitutive DNA damage response

The MUS81 protein belongs to a conserved family of DNA structure-specific nucleases that play important roles in DNA replication and repair. Inactivation of the Mus81 gene in mice has no major deleterious consequences for embryonic development, although cancer susceptibility has been reported. We have investigated the role of MUS81 in human cells by acutely depleting the protein using shRNAs. We found that MUS81 depletion from human fibroblasts leads to accumulation of ssDNA and a constitutive DNA damage response that ultimately activates cellular senescence. Moreover, we show that MUS81 is required for efficient replication fork progression during an unperturbed S-phase, and for recovery of productive replication following replication stalling. These results demonstrate essential roles for the MUS81 nuclease in maintenance of replication fork integrity

GibbsST: a Gibbs sampling method for motif discovery with enhanced resistance to local optima

BACKGROUND: Computational discovery of transcription factor binding sites (TFBS) is a challenging but important problem of bioinformatics. In this study, improvement of a Gibbs sampling based technique for TFBS discovery is attempted through an approach that is widely known, but which has never been investigated before: reduction of the effect of local optima. RESULTS: To alleviate the vulnerability of Gibbs sampling to local optima trapping, we propose to combine a thermodynamic method, called simulated tempering, with Gibbs sampling. The resultant algorithm, GibbsST, is then validated using synthetic data and actual promoter sequences extracted from Saccharomyces cerevisiae. It is noteworthy that the marked improvement of the efficiency presented in this paper is attributable solely to the improvement of the search method. CONCLUSION: Simulated tempering is a powerful solution for local optima problems found in pattern discovery. Extended application of simulated tempering for various bioinformatic problems is promising as a robust solution against local optima problems

Pairwise statistical significance of local sequence alignment using multiple parameter sets and empirical justification of parameter set change penalty

Background: Accurate estimation of statistical significance of a pairwise alignment is an important problem in sequence comparison. Recently, a comparative study of pairwise statistical significance with database statistical significance was conducted. In this paper, we extend the earlier work on pairwise statistical significance by incorporating with it the use of multiple parameter sets. Results: Results for a knowledge discovery application of homology detection reveal that using multiple parameter sets for pairwise statistical significance estimates gives better coverage than using a single parameter set, at least at some error levels. Further, the results of pairwise statistical significance using multiple parameter sets are shown to be significantly better than database statistical significance estimates reported by BLAST and PSI-BLAST, and comparable and at times significantly better than SSEARCH. Using non-zero parameter set change penalty values give better performance than zero penalty. Conclusion: The fact that the homology detection performance does not degrade when using multiple parameter sets is a strong evidence for the validity of the assumption that the alignment score distribution follows an extreme value distribution even when using multiple parameter sets. Parameter set change penalty is a useful parameter for alignment using multiple parameter sets. Pairwise statistical significance using multiple parameter sets can be effectively used to determine the relatedness of a (or a few) pair(s) of sequences without performing a time-consuming database search