Expression ratio of CCND1 to CDKN2A mRNA predicts RB1 status of cultured cancer cell lines and clinical tumor samples

<p>Abstract</p> <p>Background</p> <p>The retinoblastoma product (RB1) is frequently deregulated in various types of tumors by mutation, deletion, or inactivation through association with viral oncoproteins. The functional loss of RB1 is recognized to be one of the hallmarks that differentiate cancer cells from normal cells. Many researchers are attempting to develop anti-tumor agents that are preferentially effective against RB1-negative tumors. However, to identify patients with RB1-negative cancers, it is imperative to develop predictive biomarkers to classify RB1-positive and -negative tumors.</p> <p>Results</p> <p>Expression profiling of 30 cancer cell lines composed of 16 RB1-positive and 14 RB1-negative cancers was performed to find genes that are differentially expressed between the two groups, resulting in the identification of an RB1 signature with 194 genes. Among them, critical RB1 pathway components CDKN2A and CCND1 were included. We found that microarray data of the expression ratio of CCND1 and CDKN2A clearly distinguished the RB1 status of 30 cells lines. Measurement of the CCND1/CDKN2A mRNA expression ratio in additional cell lines by RT-PCR accurately predicted RB1 status (12/12 cells lines). The expression of CCND1/CDKN2A also correlated with RB1 status in xenograft tumors <it>in vivo</it>. Lastly, a CCND1/CDKN2A assay with clinical samples showed that uterine cervical and small cell lung cancers known to have a high prevalence of RB1-decifiency were predicted to be 100% RB1-negative, while uterine endometrial or gastric cancers were predicted to be 5-22% negative. All clinically normal tissues were 100% RB1-positive.</p> <p>Conclusions</p> <p>We report here that the CCND1/CDKN2A mRNA expression ratio predicts the RB1 status of cell lines <it>in vitro </it>and xenograft tumors and clinical tumor samples <it>in vivo</it>. Given the high predictive accuracy and quantitative nature of the CCND1/CDKN2A expression assay, the assay could be utilized to stratify patients for anti-tumor agents with preferential effects on either RB1-positive or -negative tumors.</p

Discovery of gene expression-based pharmacodynamic biomarker for a p53 context-specific anti-tumor drug Wee1 inhibitor

<p>Abstract</p> <p>Background</p> <p>Wee1 is a tyrosine kinase regulating S-G2 cell cycle transition through the inactivating phosphorylation of CDC2. The inhibition of Wee1 kinase by a selective small molecule inhibitor significantly enhances the anti-tumor efficacy of DNA damaging agents, specifically in p53 negative tumors by abrogating S-G2 checkpoints, while normal cells with wild-type p53 are not severely damaged due to the intact function of the G1 checkpoint mediated by p53. Since the measurement of mRNA expression requires a very small amount of biopsy tissue and is highly quantitative, the development of a pharmacodynamic (PD) biomarker leveraging mRNA expression is eagerly anticipated in order to estimate target engagement of anti-cancer agents.</p> <p>Results</p> <p>In order to find the Wee1 inhibition signature, mRNA expression profiling was first performed in both p53 positive and negative cancer cell lines treated with gemcitabine and a Wee1 inhibitor, MK-1775. We next carried out mRNA expression profiling of skin samples derived from xenograft models treated with the Wee1 inhibitor to identify a Wee1 inhibitor-regulatory gene set. Then, the genes that were commonly modulated in both cancer cell lines and rat skin samples were extracted as a Wee1 inhibition signature that could potentially be used as a PD biomarker independent of p53 status. The expression of the Wee1 inhibition signature was found to be regulated in a dose-dependent manner by the Wee1 inhibitor, and was significantly correlated with the inhibition level of a direct substrate, phosphorylated-CDC2. Individual genes in this Wee1 inhibition signature are known to regulate S-G2 cell cycle progression or checkpoints, which is consistent with the mode-of-action of the Wee1 inhibitor.</p> <p>Conclusion</p> <p>We report here the identification of an mRNA gene signature that was specifically changed by gemcitabine and Wee1 inhibitor combination treatment by molecular profiling. Given the common regulation of expression in both xenograft tumors and animal skin samples, the data suggest that the Wee1 inhibition gene signature might be utilized as a quantitative PD biomarker in both tumors and surrogate tissues, such as skin and hair follicles, in human clinical trials.</p

Los mecanismos alternativos de solución de conflictos y la querella en el nuevo Código Procesal Penal – 2021

El presente trabajo de investigación lleva por título “Los mecanismos alternativos de solución de conflictos y la Querella en el Nuevo Código Procesal Penal – 2021”, tiene como finalidad buscar que, a través de la conciliación, se evite un proceso penal de acción privada, teniendo en cuenta que los intereses en este tipo de casos son, generalmente, indemnizatorios o reparatorios. Los medios alternativos de solución de conflictos se han convertido en un tema relativamente común en el mundo jurídico peruano. Se constituyen como una visión novedosa y distinta de la tradicional atención de litigios exclusivamente por medio del proceso judicial; y es justamente por tratarse una acción privada de la acción penal donde tiene como objetivo resarcir el daño básicamente, se puede inducir a los querellantes a solucionar el problema pecuniario o indemnizatorio a través de un mecanismo alternativo, ya sea la autotutela, autocomposición o la heterocomposición. El trabajo de investigación, consideró la opinión de diferentes abogados respecto a la propuesta planteada, a través de cuestionarios que han sido llenados, teniendo en cuenta las preguntas, cuyas respuestas iban dirigidas a emitir las conclusiones finales de la investigación. Asimismo, se ha empleado material bibliográfico con la finalidad de señalar las principales figuras relacionadas con el tema principal de la tesis.The purpose of this research work, which is entitled Alternative Conflict Resolution Mechanisms Prior to the Filing of the Complaint in Lima 2021, is to seek to somehow avoid a criminal proceeding of private action prior to the filing of a complaint. , taking into account that the interests in this type of cases are, generally, indemnity or reparation. Alternative means of conflict resolution have become a relatively common theme in the Peruvian legal world. They are constituted as a new vision and different from the traditional litigation attention exclusively through the judicial process; and it is precisely because it is a private action of the criminal action where the objective is to basically compensate the damage, the plaintiffs can be induced to solve the pecuniary or compensation problem through an alternative mechanism, be it self- protection, self-composition or hetero-composition . In this thesis, an alternative dispute resolution mechanism will be proposed prior to filing a complaint in a private action process, taking into account that the interests in this type of case are, generally, compensatory or reparatory. In this research work, the opinion of different lawyers regarding the proposed proposal has been considered, through questionnaires that have been filled out taking into account the questions whose answers were aimed at issuing the final conclusions of the investigation. Likewise, bibliographic material has been used in order to point out the main figures related to the main theme of the thesis

Drug absorption through a cell monolayer: a theoretical work on a non-linear three-compartment model

The subject of analysis is a non-linear three-compartment model, widely used in pharmacological absorption studies. It has been transformed into a general form, thus leading automatically to an appropriate approximation. This made the absorption profile accessible and expressions for absorption times, apparent permeabilities and equilibrium values were given. These findings allowed a profound analysis of results from non-linear curve fits and delivered the dependencies on the systems' parameters over a wide range of values. The results were applied to an absorption experiment with multidrug transporter-affected antibiotic CNV97100 on Caco-2 cell monolayers.Comment: 21 pages, 8 figures (v4: detailed definition of the treated model - additional information about limitations

A practical, bioinformatic workflow system for large data sets generated by next-generation sequencing

Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic workflow system, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This workflow system provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This system is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism

A practical, bioinformatic workflow system for large data sets generated by next-generation sequencing

Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic workflow system, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This workflow system provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This system is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism

Time to Recurrence and Survival in Serous Ovarian Tumors Predicted from Integrated Genomic Profiles

Serous ovarian cancer (SeOvCa) is an aggressive disease with differential and often inadequate therapeutic outcome after standard treatment. The Cancer Genome Atlas (TCGA) has provided rich molecular and genetic profiles from hundreds of primary surgical samples. These profiles confirm mutations of TP53 in ∼100% of patients and an extraordinarily complex profile of DNA copy number changes with considerable patient-to-patient diversity. This raises the joint challenge of exploiting all new available datasets and reducing their confounding complexity for the purpose of predicting clinical outcomes and identifying disease relevant pathway alterations. We therefore set out to use multi-data type genomic profiles (mRNA, DNA methylation, DNA copy-number alteration and microRNA) available from TCGA to identify prognostic signatures for the prediction of progression-free survival (PFS) and overall survival (OS). prediction algorithm and applied it to two datasets integrated from the four genomic data types. We (1) selected features through cross-validation; (2) generated a prognostic index for patient risk stratification; and (3) directly predicted continuous clinical outcome measures, that is, the time to recurrence and survival time. We used Kaplan-Meier p-values, hazard ratios (HR), and concordance probability estimates (CPE) to assess prediction performance, comparing separate and integrated datasets. Data integration resulted in the best PFS signature (withheld data: p-value = 0.008; HR = 2.83; CPE = 0.72).We provide a prediction tool that inputs genomic profiles of primary surgical samples and generates patient-specific predictions for the time to recurrence and survival, along with outcome risk predictions. Using integrated genomic profiles resulted in information gain for prediction of outcomes. Pathway analysis provided potential insights into functional changes affecting disease progression. The prognostic signatures, if prospectively validated, may be useful for interpreting therapeutic outcomes for clinical trials that aim to improve the therapy for SeOvCa patients

Chemical genomics of cancer chemopreventive dithiolethiones

3H-1,2-dithiole-3-thione (D3T) and its analogues 4-methyl-5-pyrazinyl-3H-1,2-dithiole-3-thione (OLT) and 5-tert-butyl-3H-1,2-dithiole-3-thione (TBD) are chemopreventive agents that block or diminish early stages of carcinogenesis by inducing activities of detoxication enzymes. While OLT has been used in clinical trials, TBD has been shown to be more efficacious and possibly less toxic than OLT in animals. Here, we utilize a robust and high-resolution chemical genomics procedure to examine the pharmacological structure–activity relationships of these compounds in livers of male rats by microarray analyses. We identified 226 differentially expressed genes that were common to all treatments. Functional analysis identified the relation of these genes to glutathione metabolism and the nuclear factor, erythroid derived 2-related factor 2 pathway (Nrf2) that is known to regulate many of the protective actions of dithiolethiones. OLT and TBD were shown to have similar efficacies and both were weaker than D3T. In addition, we identified 40 genes whose responses were common to OLT and TBD, yet distinct from D3T. As inhibition of cytochrome P450 (CYP) has been associated with the effects of OLT on CYP expression, we determined the half maximal inhibitory concentration (IC50) values for inhibition of CYP1A2. The rank order of inhibitor potency was OLT ≫ TBD ≫ D3T, with IC50 values estimated as 0.2, 12.8 and >100 μM, respectively. Functional analysis revealed that OLT and TBD, in addition to their effects on CYP, modulate liver lipid metabolism, especially fatty acids. Together, these findings provide new insight into the actions of clinically relevant and lead dithiolethione analogues