Mathematical Model of Intrinsic Drug Resistance in Lung Cancer.

Drug resistance is a bottleneck in cancer treatment. Commonly, a molecular treatment for cancer leads to the emergence of drug resistance in the long term. Thus, some drugs, despite their initial excellent response, are withdrawn from the market. Lung cancer is one of the most mutated cancers, leading to dozens of targeted therapeutics available against it. Here, we have developed a mechanistic mathematical model describing sensitization to nine groups of targeted therapeutics and the emergence of intrinsic drug resistance. As we focus only on intrinsic drug resistance, we perform the computer simulations of the model only until clinical diagnosis. We have utilized, for model calibration, the whole-exome sequencing data combined with clinical information from over 1000 non-small-cell lung cancer patients. Next, the model has been applied to find an answer to the following questions: When does intrinsic drug resistance emerge? And how long does it take for early-stage lung cancer to grow to an advanced stage? The results show that drug resistance is inevitable at diagnosis but not always detectable and that the time interval between early and advanced-stage tumors depends on the selection advantage of cancer cells.

Radiomic signature accurately predicts the risk of metastatic dissemination in late-stage non-small cell lung cancer.

Background: Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, and the median overall survival (OS) is approximately 2-3 years among patients with stage III disease. Furthermore, it is one of the deadliest types of cancer globally due to non-specific symptoms and the lack of a biomarker for early detection. The most important decision that clinicians need to make after a lung cancer diagnosis is the selection of a treatment schedule. This decision is based on, among others factors, the risk of developing metastasis. Methods: A cohort of 115 NSCLC patients treated using chemotherapy and radiotherapy (RT) with curative intent was retrospectively collated and included patients for whom positron emission tomography/computed tomography (PET/CT) images, acquired before RT, were available. The PET/CT images were used to compute radiomic features extracted from a region of interest (ROI), the primary tumor. Radiomic and clinical features were then classified to stratify the patients into short and long time to metastasis, and regression analysis was used to predict the risk of metastasis. Results: Classification based on binarized metastasis-free survival (MFS) was applied with moderate success. Indeed, an accuracy of 0.73 was obtained for the selection of features based on the Wilcoxon test and logistic regression model. However, the Cox regression model for metastasis risk prediction performed very well, with a concordance index (C-index) score equal to 0.84. Conclusions: It is possible to accurately predict the risk of metastasis in NSCLC patients based on radiomic features. The results demonstrate the potential use of features extracted from cancer imaging in predicting the risk of metastasis.

Allele-specific quantitation of ATXN3 and HTT transcripts in polyQ disease models.

BACKGROUND: The majority of genes in the human genome is present in two copies but the expression levels of both alleles is not equal. Allelic imbalance is an aspect of gene expression relevant not only in the context of genetic variation, but also to understand the pathophysiology of genes implicated in genetic disorders, in particular, dominant genetic diseases where patients possess one normal and one mutant allele. Polyglutamine (polyQ) diseases are caused by the expansion of CAG trinucleotide tracts within specific genes. Spinocerebellar ataxia type 3 (SCA3) and Huntington's disease (HD) patients harbor one normal and one mutant allele that differ in the length of CAG tracts. However, assessing the expression level of individual alleles is challenging due to the presence of abundant CAG repeats in the human transcriptome, which make difficult the design of allele-specific methods, as well as of therapeutic strategies to selectively engage CAG sequences in mutant transcripts. RESULTS: To precisely quantify expression in an allele-specific manner, we used SNP variants that are linked to either normal or CAG expanded alleles of the ataxin-3 (ATXN3) and huntingtin (HTT) genes in selected patient-derived cell lines. We applied a SNP-based quantitative droplet digital PCR (ddPCR) protocol for precise determination of the levels of transcripts in cellular and mouse models. For HD, we showed that the process of cell differentiation can affect the ratio between endogenous alleles of HTT mRNA. Additionally, we reported changes in the absolute number of the ATXN3 and HTT transcripts per cell during neuronal differentiation. We also implemented our assay to reliably monitor, in an allele-specific manner, the silencing efficiency of mRNA-targeting therapeutic approaches for HD. Finally, using the humanized Hu128/21 HD mouse model, we showed that the ratio of normal and mutant HTT transgene expression in brain slightly changes with the age of mice. CONCLUSIONS: Using allele-specific ddPCR assays, we observed differences in allele expression levels in the context of SCA3 and HD. Our allele-selective approach is a reliable and quantitative method to analyze low abundant transcripts and is performed with high accuracy and reproducibility. Therefore, the use of this approach can significantly improve understanding of allele-related mechanisms, e.g., related with mRNA processing that may be affected in polyQ diseases.

Atrophin-1 Function and Dysfunction in Dentatorubral-Pallidoluysian Atrophy.

Dentatorubral-pallidoluysian atrophy (DRPLA) is a rare, incurable genetic disease that belongs to the group of polyglutamine (polyQ) diseases. DRPLA is the most common in the Japanese population; however, its global prevalence is also increasing due to better clinical recognition. It is characterized by cerebellar ataxia, myoclonus, epilepsy, dementia, and chorea. DRPLA is caused by dynamic mutation of CAG repeat expansion in ATN1 gene encoding the atrophin-1 protein. In the cascade of molecular disturbances, the pathological form of atrophin-1 is the initial factor, which has not been precisely characterized so far. Reports indicate that DRPLA is associated with disrupted protein-protein interactions (in which an expanded polyQ tract plays a crucial role), as well as gene expression deregulation. There is a great need to design efficient therapy that would address the underlying neurodegenerative process and thus prevent or alleviate DRPLA symptoms. An in-depth understanding of the normal atrophin-1 function and mutant atrophin-1 dysfunction is crucial for this purpose. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Regulatory Potential of Competing Endogenous RNAs in Myotonic Dystrophies.

Non-coding RNAs (ncRNAs) have been reported to be implicated in cell fate determination and various human diseases. All ncRNA molecules are emerging as key regulators of diverse cellular processes; however, little is known about the regulatory interaction among these various classes of RNAs. It has been proposed that the large-scale regulatory network across the whole transcriptome is mediated by competing endogenous RNA (ceRNA) activity attributed to both protein-coding and ncRNAs. ceRNAs are considered to be natural sponges of miRNAs that can influence the expression and availability of multiple miRNAs and, consequently, the global mRNA and protein levels. In this review, we summarize the current understanding of the role of ncRNAs in two neuromuscular diseases, myotonic dystrophy type 1 and 2 (DM1 and DM2), and the involvement of expanded CUG and CCUG repeat-containing transcripts in miRNA-mediated RNA crosstalk. More specifically, we discuss the possibility that long repeat tracts present in mutant transcripts can be potent miRNA sponges and may affect ceRNA crosstalk in these diseases. Moreover, we highlight practical information related to innovative disease modelling and studying RNA regulatory networks in cells. Extending knowledge of gene regulation by ncRNAs, and of complex regulatory ceRNA networks in DM1 and DM2, will help to address many questions pertinent to pathogenesis and treatment of these disorders; it may also help to better understand general rules of gene expression and to discover new rules of gene control.

What, When and How to Measure-Peripheral Biomarkers in Therapy of Huntington's Disease.

Among the main challenges in further advancing therapeutic strategies for Huntington's disease (HD) is the development of biomarkers which must be applied to assess the efficiency of the treatment. HD is a dreadful neurodegenerative disorder which has its source of pathogenesis in the central nervous system (CNS) but is reflected by symptoms in the periphery. Visible symptoms include motor deficits and slight changes in peripheral tissues, which can be used as hallmarks for prognosis of the course of HD, e.g., the onset of the disease symptoms. Knowing how the pathology develops in the context of whole organisms is crucial for the development of therapy which would be the most beneficial for patients, as well as for proposing appropriate biomarkers to monitor disease progression and/or efficiency of treatment. We focus here on molecular peripheral biomarkers which could be used as a measurable outcome of potential therapy. We present and discuss a list of wet biomarkers which have been proposed in recent years to measure pre- and postsymptomatic HD. Interestingly, investigation of peripheral biomarkers in HD can unravel new aspects of the disease pathogenesis. This especially refers to inflammatory proteins or specific immune cells which attract scientific attention in neurodegenerative disorders.

Artificial miRNAs targeting CAG repeat expansion in ORFs cause rapid deadenylation and translation inhibition of mutant transcripts.

Polyglutamine (polyQ) diseases are incurable neurological disorders caused by CAG repeat expansion in the open reading frames (ORFs) of specific genes. This type of mutation in the HTT gene is responsible for Huntington's disease (HD). CAG repeat-targeting artificial miRNAs (art-miRNAs) were shown as attractive therapeutic approach for polyQ disorders as they caused allele-selective decrease in the level of mutant proteins. Here, using polyQ disease models, we aimed to demonstrate how miRNA-based gene expression regulation is dependent on target sequence features. We show that the silencing efficiency and selectivity of art-miRNAs is influenced by the localization of the CAG repeat tract within transcript and the specific sequence context. Furthermore, we aimed to reveal the events leading to downregulation of mutant polyQ proteins and found very rapid activation of translational repression and HTT transcript deadenylation. Slicer-activity of AGO2 was dispensable in this process, as determined in AGO2 knockout cells generated with CRISPR-Cas9 technology. We also showed highly allele-selective downregulation of huntingtin in human HD neural progenitors (NPs). Taken together, art-miRNA activity may serve as a model of the cooperative activity and targeting of ORF regions by endogenous miRNAs.

Mathematical model predicts response to chemotherapy in advanced non-resectable non-small cell lung cancer patients treated with platinum-based doublet.

We developed a computational platform including machine learning and a mechanistic mathematical model to find the optimal protocol for administration of platinum-doublet chemotherapy in a palliative setting. The platform has been applied to advanced metastatic non-small cell lung cancer (NSCLC). The 42 NSCLC patients treated with palliative intent at Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, were collected from a retrospective cohort of patients diagnosed in 2004-2014. Patients were followed-up, for three years. Clinical data collected include complete information about the clinical course of the patients including treatment schedule, response according to RECIST classification, and survival. The core of the platform is the mathematical model, in the form of a system of ordinary differential equations, describing dynamics of platinum-sensitive and platinum-resistant cancer cells and interactions reflecting competition for space and resources. The model is simulated stochastically by sampling the parameter values from a joint probability distribution function. The machine learning model is applied to calibrate the mathematical model and to fit it to the overall survival curve. The model simulations faithfully reproduce the clinical cohort at three levels long-term response (OS), the initial response (according to RECIST criteria), and the relationship between the number of chemotherapy cycles and time between two consecutive chemotherapy cycles. In addition, we investigated the relationship between initial and long-term response. We showed that those two variables do not correlate which means that we cannot predict patient survival solely based on the initial response. We also tested several chemotherapy schedules to find the best one for patients treated with palliative intent. We found that the optimal treatment schedule depends, among others, on the strength of competition among various subclones in a tumor. The computational platform developed allows optimizing chemotherapy protocols, within admissible limits of toxicity, for palliative treatment of metastatic NSCLC. The simplicity of the method allows its application to chemotherapy optimization in different cancers.

Author Correction: Virtual clinical trials identify effective combination therapies in ovarian cancer.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Generation of human iPS cell line IBCHi002-A from spinocerebellar ataxia type 3/Machado-Joseph disease patient's fibroblasts.

Spinocerebellar ataxia type 3 (SCA3), also known as Machado-Joseph disease (MJD), is autosomal-dominant neurodegenerative disease caused by an expansion of polyglutamine-encoding CAG repeats in the ATXN3 gene. Here we established IBCHi002-A induced pluripotent stem cells (iPSCs) line generated from SCA3 patient fibroblasts by using non-integrative Sendai-virus delivery system of four reprogramming factors. This cellular model provides a valid platform for study SCA3 pathogenesis and potential therapies for this so far incurable disease.

Generation of New Isogenic Models of Huntington's Disease Using CRISPR-Cas9 Technology.

Huntington's disease (HD) is a fatal neurodegenerative disorder caused by the expansion of CAG repeats in exon 1 of the huntingtin gene (HTT). Despite its monogenic nature, HD pathogenesis is still not fully understood, and no effective therapy is available to patients. The development of new techniques such as genome engineering has generated new opportunities in the field of disease modeling and enabled the generation of isogenic models with the same genetic background. These models are very valuable for studying the pathogenesis of a disease and for drug screening. Here, we report the generation of a series of homozygous HEK 293T cell lines with different numbers of CAG repeats at the HTT locus and demonstrate their usefulness for testing therapeutic reagents. In addition, using the CRISPR-Cas9 system, we corrected the mutation in HD human induced pluripotent stem cells and generated a knock-out of the HTT gene, thus providing a comprehensive set of isogenic cell lines for HD investigation.

Virtual clinical trials identify effective combination therapies in ovarian cancer.

A major issue in oncology is the high failure rate of translating preclinical results in successful clinical trials. Using a virtual clinical trial simulations approach, we present a mathematical framework to estimate the added value of combinatorial treatments in ovarian cancer. This approach was applied to identify effective targeted therapies that can be combined with the platinum-taxane regimen and overcome platinum resistance in high-grade serous ovarian cancer. We modeled and evaluated the effectiveness of three drugs that target the main platinum resistance mechanisms, which have shown promising efficacy in vitro, in vivo, and early clinical trials. Our results show that drugs resensitizing chemoresistant cells are superior to those aimed at triggering apoptosis or increasing the bioavailability of platinum. Our results further show that the benefit of using biomarker stratification in clinical trials is dependent on the efficacy of the drug and tumor composition. The mathematical framework presented herein is suitable for systematically testing various drug combinations and clinical trial designs in solid cancers.

Generation of human iPS cell line IBCHi001-A from dentatorubral-pallidoluysian atrophy patient's fibroblasts.

Dentatorubral-pallidoluysian atrophy (DRPLA) is an incurable autosomal dominant disease caused by an expansion of a CAG repeats in ATN1 gene encoding atrophin 1 protein. Here we report the generation of IBCHi001-A, an induced pluripotent stem cell (iPSC) line derived from DRPLA patient fibroblasts using non-integrative reprogramming technology with OCT4, SOX2, cMYC and KLF4 reprogramming factors. The pluripotency of iPSC was confirmed by immunocytochemistry and PCR for pluripotency markers and by the ability to form three germ layers in vitro. The established iPSC line offers a useful resource to study the pathogenesis of DPRLA.

MicroRNA Profiling During Neural Differentiation of Induced Pluripotent Stem Cells.

MicroRNAs (miRNA) play an essential role in the regulation of gene expression and influence signaling networks responsible for several cellular processes like differentiation of pluripotent stem cells. Despite several studies on the neurogenesis process, no global analysis of microRNA expression during differentiation of induced pluripotent stem cells (iPSC) to neuronal stem cells (NSC) has been done. Therefore, we compared the profile of microRNA expression in iPSC lines and in NSC lines derived from them, using microarray-based analysis. Two different protocols for NSC formation were used: Direct and two-step via neural rosette formation. We confirmed the new associations of previously described miRNAs in regulation of NSC differentiation from iPSC. We discovered upregulation of miR-10 family, miR-30 family and miR-9 family and downregulation of miR-302 and miR-515 family expression. Moreover, we showed that miR-10 family play a crucial role in the negative regulation of genes expression belonging to signaling pathways involved in neural differentiation: WNT signaling pathway, focal adhesion, and signaling pathways regulating pluripotency of stem cells.

Changes in the quality of meat (Longissimus thoracis et lumborum) from Kamieniec lambs during long-term freezer storage.

The aim of this study was to determine changes in the quality of lamb meat (Longissimus thoracis et lumborum), which was vacuum-packaged and freezer-stored (-26°C) for 6 and 12 months. The experiment was performed on 12 male lambs of the Kamieniec Longwool breed, raised to 106 days of age. In comparison with fresh meat, thawed meat was characterized by lower ash content, higher pH, greater natural drip loss and cooking loss, and lower scores for taste intensity. Vacuum packaging and low-temperature storage protected lamb meat against oxidative changes, and alleviated the adverse effects of oxidation on the color, aroma and taste of meat. It can be concluded that freezer storage (-26°C) of vacuum-packaged meat can help meet consumer demand for lamb meat products in periods when fresh meat is unavailable. However, it should be noted that long-term frozen storage induces undesirable changes in meat quality, including a decrease in water-holding capacity and taste intensity.

Mathematical Modeling Predicts Response to Chemotherapy and Drug Combinations in Ovarian Cancer.

Platinum-based chemotherapy constitutes the backbone of clinical care in advanced solid cancers such as high-grade serous ovarian cancer (HGSOC) and has prolonged survival of millions of patients with cancer. Most of these patients, however, become resistant to chemotherapy, which generally leads to a fatal refractory disease. We present a comprehensive stochastic mathematical model and simulator approach to describe platinum resistance and standard-of-care (SOC) therapy in HGSOC. We used pre- and posttreatment clinical data, including 18F-FDG-PET/CT images, to reliably estimate the model parameters and simulate "virtual patients with HGSOC." Treatment responses of the virtual patients generated by our mathematical model were indistinguishable from real-life patients with HGSOC. We demonstrated the utility of our approach by evaluating the survival benefit of combination therapies that contain up to six drugs targeting platinum resistance mechanisms. Several resistance mechanisms were already active at diagnosis, but combining SOC with a drug that targets the most dominant resistance subpopulation resulted in a significant survival benefit. This work provides a theoretical basis for a cancer treatment paradigm in which maximizing platinum's killing effect on cancer cells requires overcoming resistance mechanisms with targeted drugs. This freely available mathematical model and simulation framework enable rapid and rigorous evaluation of the benefit of a targeted drug or combination therapy in virtual patients before clinical trials, which facilitates translating preclinical findings into clinical practice.Significance: These findings present a comprehensive mathematical model for platinum resistance and standard-of-care therapy in a solid cancer, allowing virtual evaluation of novel therapy regimens. Cancer Res; 78(14); 4036-44. ©2018 AACR.

Relaxation oscillations and hierarchy of feedbacks in MAPK signaling.

We formulated a computational model for a MAPK signaling cascade downstream of the EGF receptor to investigate how interlinked positive and negative feedback loops process EGF signals into ERK pulses of constant amplitude but dose-dependent duration and frequency. A positive feedback loop involving RAS and SOS, which leads to bistability and allows for switch-like responses to inputs, is nested within a negative feedback loop that encompasses RAS and RAF, MEK, and ERK that inhibits SOS via phosphorylation. This negative feedback, operating on a longer time scale, changes switch-like behavior into oscillations having a period of 1 hour or longer. Two auxiliary negative feedback loops, from ERK to MEK and RAF, placed downstream of the positive feedback, shape the temporal ERK activity profile but are dispensable for oscillations. Thus, the positive feedback introduces a hierarchy among negative feedback loops, such that the effect of a negative feedback depends on its position with respect to the positive feedback loop. Furthermore, a combination of the fast positive feedback involving slow-diffusing membrane components with slower negative feedbacks involving faster diffusing cytoplasmic components leads to local excitation/global inhibition dynamics, which allows the MAPK cascade to transmit paracrine EGF signals into spatially non-uniform ERK activity pulses.

Application of bifurcation theory and siRNA-based control signal to restore the proper response of cancer cells to DNA damage.

Many diseases with a genetic background such as some types of cancer are caused by damage in the p53 signaling pathway. The damage changes the system dynamics providing cancer cells with resistance to therapy such as radiation therapy. The change can be observed as the difference in bifurcation diagrams and equilibria type and location between normal and damaged cells, and summarized as the changes of the mathematical model parameters and following changes of the eigenvalues of Jacobian matrix. Therefore a change in other model parameters, such as mRNA degradation rates, may restore the proper eigenvalues and by that proper system dynamics. From the biological point of view, the change of mRNA degradation rate can be achieved by application of the small interfering RNA (siRNA). Here, we propose a general mathematical framework based on the bifurcation theory and siRNA-based control signal in order to study how to restore the proper response of cells with damaged p53 signaling pathway to therapy by using ionizing radiation (IR) therapy as an example. We show the difference between the cells with normal p53 signaling pathway and cells with abnormalities in the negative (as observed in SJSA-1 cell line) or positive (as observed in MCF-7 or PNT1a cell lines) feedback loop. Then we show how the dynamics of these cells can be restored to normal cell dynamics by using selected siRNA.

Modeling simple repeat expansion diseases with iPSC technology.

A number of human genetic disorders, including Huntington's disease, myotonic dystrophy type 1, C9ORF72 form of amyotrophic lateral sclerosis and several spinocerebellar ataxias, are caused by the expansion of various microsatellite sequences in single implicated genes. The neurodegenerative and neuromuscular nature of the repeat expansion disorders considerably limits the access of researchers to appropriate cellular models of these diseases. This limitation, however, can be overcome by the application of induced pluripotent stem cell (iPSC) technology. In this paper, we review the current knowledge on the modeling of repeat expansion diseases with human iPSCs and iPSC-derived cells, focusing on the disease phenotypes recapitulated in these models. In subsequent sections, we provide basic practical knowledge regarding iPSC generation, characterization and differentiation into neurons. We also cover disease modeling in iPSCs, neuronal stem cells and specialized neuronal cultures. Furthermore, we also summarize the therapeutic potential of iPSC technology in repeat expansion diseases.

Cooperation meets competition in microRNA-mediated DMPK transcript regulation.

The fundamental role of microRNAs (miRNAs) in the regulation of gene expression has been well-established, but many miRNA-driven regulatory mechanisms remain elusive. In the present study, we demonstrate that miRNAs regulate the expression of DMPK, the gene mutated in myotonic dystrophy type 1 (DM1), and we provide insight regarding the concerted effect of the miRNAs on the DMPK target. Specifically, we examined the binding of several miRNAs to the DMPK 3' UTR using luciferase assays. We validated the interactions between the DMPK transcript and the conserved miR-206 and miR-148a. We suggest a possible cooperativity between these two miRNAs and discuss gene targeting by miRNA pairs that vary in distance between their binding sites and expression profiles. In the same luciferase reporter system, we showed miR-15b/16 binding to the non-conserved CUG repeat tract present in the DMPK transcript and that the CUG-repeat-binding miRNAs might also act cooperatively. Moreover, we detected miR-16 in cytoplasmic foci formed by exogenously expressed RNAs with expanded CUG repeats. Therefore, we propose that the expanded CUGs may serve as a target for concerted regulation by miRNAs and may also act as molecular sponges for natural miRNAs with CAG repeats in their seed regions, thereby affecting their physiological functions.