Biological and clinical perspectives of the actionable gene fusions and amplifications involving tyrosine kinase receptors in lung cancer

MS is supported by a Juan-Rodés contract from the Instituto de Salud Carlos III (JR20/00015).This work was supported by Spanish grant from ICAPEM (ICAPEM becas 2021), to EP, and by Spanish grant form Asociación Española Contra el Cancer (AECC) (grant number GCB14142170MONT) to MSC. We thank M Rey providing language help and O Romero for data analysis support.Identifying molecular oncogenic drivers is crucial for precision oncology. Genetic rearrangements, including gene fusions and gene amplification, involving and activating receptor tyrosine kinases (RTKs) are recurrent in solid tumors, particularly in non-small cell lung cancer. Advances in the tools to detect these alterations have deepened our understanding of the underlying biology and tumor characteristics and have prompted the development of novel inhibitors targeting activated RTKs. Nowadays, druggable oncogenic rearrangements are found in around 15% of lung adenocarcinomas. However, taken separately, each of these alterations has a low prevalence, which poses a challenge to their diagnosis. The identification and characterization of novel targetable oncogenic rearrangements in lung cancer continue to expand, as shown by the recent discovery of the CLIP1-LTK fusion found in 0.4% of lung adenocarcinomas. While tyrosine kinase inhibitors that block the activity of RTKs have represented a breakthrough in the therapeutic landscape by improving the prognosis of this disease, prolonged treatment inevitably leads to the development of acquired resistance. Here, we review the oncogenic fusions and gene amplifications involving RTK in lung cancer. We address the genetic and molecular structure of oncogenic RTKs and the methods to diagnose them, emphasizing the role of next-generation sequencing technologies. Furthermore, we discuss the therapeutic implications of the different tyrosine kinase inhibitors, including the current clinical trials and the mechanisms responsible for acquired resistance. Finally, we provide an overview of the use of liquid biopsies to monitor the course of the disease

Modeling of celiac disease immune response and the therapeutic effect of potential drugs

BACKGROUND: Celiac disease (CD) is an autoimmune disorder that occurs in genetically predisposed people and is caused by a reaction to the gluten protein found in wheat, which leads to intestinal villous atrophy. Currently there is no drug for treatment of CD. The only known treatment is lifelong gluten-free diet. The main aim of this work is to develop a mathematical model of the immune response in CD patients and to predict the efficacy of a transglutaminase-2 (TG-2) inhibitor as a potential drug for treatment of CD. RESULTS: A thorough analysis of the developed model provided the following results: 1. TG-2 inhibitor treatment leads to insignificant decrease in antibody levels, and hence remains higher than in healthy individuals. 2. TG-2 inhibitor treatment does not lead to any significant increase in villous area. 3. The model predicts that the most effective treatment of CD would be the use of gluten peptide analogs that antagonize the binding of immunogenic gluten peptides to APC. The model predicts that the treatment of CD by such gluten peptide analogs can lead to a decrease in antibody levels to those of normal healthy people, and to a significant increase in villous area. CONCLUSIONS: The developed mathematical model of immune response in CD allows prediction of the efficacy of TG-2 inhibitors and other possible drugs for the treatment of CD: their influence on the intestinal villous area and on the antibody levels. The model also allows to understand what processes in the immune response have the strongest influence on the efficacy of different drugs. This model could be applied in the pharmaceutical R&D arena for the design of drugs against autoimmune small intestine disorders and on the design of their corresponding clinical trials

Best practices to maximize the use and reuse of quantitative and systems pharmacology models: recommendations from the United Kingdom quantitative and systems pharmacology network

The lack of standardization in the way that quantitative and systems pharmacology (QSP) models are developed, tested, and documented hinders their reproducibility, reusability, and expansion or reduction to alternative contexts. This in turn undermines the potential impact of QSP in academic, industrial, and regulatory frameworks. This article presents a minimum set of recommendations from the UK Quantitative and Systems Pharmacology Network (UK QSP Network) to guide QSP practitioners seeking to maximize their impact, and stakeholders considering the use of QSP models in their environment

ASPASIA: A toolkit for evaluating the effects of biological interventions on SBML model behavior

<div><p>A calibrated computational model reflects behaviours that are expected or observed in a complex system, providing a baseline upon which sensitivity analysis techniques can be used to analyse pathways that may impact model responses. However, calibration of a model where a behaviour depends on an intervention introduced after a defined time point is difficult, as model responses may be dependent on the conditions at the time the intervention is applied. We present ASPASIA (Automated Simulation Parameter Alteration and SensItivity Analysis), a cross-platform, open-source Java toolkit that addresses a key deficiency in software tools for understanding the impact an intervention has on system behaviour for models specified in Systems Biology Markup Language (SBML). ASPASIA can generate and modify models using SBML solver output as an initial parameter set, allowing interventions to be applied once a steady state has been reached. Additionally, multiple SBML models can be generated where a subset of parameter values are perturbed using local and global sensitivity analysis techniques, revealing the model’s sensitivity to the intervention. To illustrate the capabilities of ASPASIA, we demonstrate how this tool has generated novel hypotheses regarding the mechanisms by which Th17-cell plasticity may be controlled <i>in vivo</i>. By using ASPASIA in conjunction with an SBML model of Th17-cell polarisation, we predict that promotion of the Th1-associated transcription factor T-bet, rather than inhibition of the Th17-associated transcription factor ROR<i>γ</i>t, is sufficient to drive switching of Th17 cells towards an IFN-<i>γ</i>-producing phenotype. Our approach can be applied to all SBML-encoded models to predict the effect that intervention strategies have on system behaviour. ASPASIA, released under the Artistic License (2.0), can be downloaded from <a href="http://www.york.ac.uk/ycil/software" target="_blank">http://www.york.ac.uk/ycil/software</a>.</p></div

SARS-CoV-2 omicron (B.1.1.529)-related COVID-19 sequelae in vaccinated and unvaccinated patients with cancer: results from the OnCovid registry

Background COVID-19 sequelae can affect about 15% of patients with cancer who survive the acute phase of SARS-CoV-2 infection and can substantially impair their survival and continuity of oncological care. We aimed to investigate whether previous immunisation affects long-term sequelae in the context of evolving variants of concern of SARS-CoV-2. Methods OnCovid is an active registry that includes patients aged 18 years or older from 37 institutions across Belgium, France, Germany, Italy, Spain, and the UK with a laboratory-confirmed diagnosis of COVID-19 and a history of solid or haematological malignancy, either active or in remission, followed up from COVID-19 diagnosis until death. We evaluated the prevalence of COVID-19 sequelae in patients who survived COVID-19 and underwent a formal clinical reassessment, categorising infection according to the date of diagnosis as the omicron (B.1.1.529) phase from Dec 15, 2021, to Jan 31, 2022; the alpha (B.1.1.7)-delta (B.1.617.2) phase from Dec 1, 2020, to Dec 14, 2021; and the pre-vaccination phase from Feb 27 to Nov 30, 2020. The prevalence of overall COVID-19 sequelae was compared according to SARS-CoV-2 immunisation status and in relation to post-COVID-19 survival and resumption of systemic anticancer therapy. This study is registered with ClinicalTrials.gov, NCT04393974. Findings At the follow-up update on June 20, 2022, 1909 eligible patients, evaluated after a median of 39 days (IQR 24-68) from COVID-19 diagnosis, were included (964 [ 50 center dot 7%] of 1902 patients with sex data were female and 938 [49 center dot 3%] were male). Overall, 317 (16 center dot 6%; 95% CI 14 center dot 8-18 center dot 5) of 1909 patients had at least one sequela from COVID-19 at the first oncological reassessment. The prevalence of COVID-19 sequelae was highest in the prevaccination phase (191 [19 center dot 1%; 95% CI 16 center dot 4-22 center dot 0] of 1000 patients). The prevalence was similar in the alpha-delta phase (110 [16 center dot 8%; 13 center dot 8- 20 center dot 3] of 653 patients, p=0 center dot 24), but significantly lower in the omicron phase (16 [6 center dot 2%; 3 center dot 5-10 center dot 2] of 256 patients, p<0 center dot 0001). In the alpha- delta phase, 84 (18 center dot 3%; 95% CI 14 center dot 6-22 center dot 7) of 458 unvaccinated patients and three (9 center dot 4%; 1 center dot 9- 27 center dot 3) of 32 unvaccinated patients in the omicron phase had sequelae. Patients who received a booster and those who received two vaccine doses had a significantly lower prevalence of overall COVID-19 sequelae than unvaccinated or partially vaccinated patients (ten [7 center dot 4%; 95% CI 3 center dot 5-13 center dot 5] of 136 boosted patients, 18 [9 center dot 8%; 5 center dot 8-15 center dot 5] of 183 patients who had two vaccine doses vs 277 [ 18 center dot 5%; 16 center dot 5-20 center dot 9] of 1489 unvaccinated patients, p=0 center dot 0001), respiratory sequelae (six [4 center dot 4%; 1 center dot 6-9 center dot 6], 11 [6 center dot 0%; 3 center dot 0-10 center dot 7] vs 148 [9 center dot 9%; 8 center dot 4- 11 center dot 6], p= 0 center dot 030), and prolonged fatigue (three [2 center dot 2%; 0 center dot 1-6 center dot 4], ten [5 center dot 4%; 2 center dot 6-10 center dot 0] vs 115 [7 center dot 7%; 6 center dot 3-9 center dot 3], p=0 center dot 037)

SARS-CoV-2 omicron (B.1.1.529)-related COVID-19 sequelae in vaccinated and unvaccinated patients with cancer: results from the OnCovid registry

Background COVID-19 sequelae can affect about 15% of patients with cancer who survive the acute phase of SARS-CoV-2 infection and can substantially impair their survival and continuity of oncological care. We aimed to investigate whether previous immunisation affects long-term sequelae in the context of evolving variants of concern of SARS-CoV-2. Methods OnCovid is an active registry that includes patients aged 18 years or older from 37 institutions across Belgium, France, Germany, Italy, Spain, and the UK with a laboratory-confirmed diagnosis of COVID-19 and a history of solid or haematological malignancy, either active or in remission, followed up from COVID-19 diagnosis until death. We evaluated the prevalence of COVID-19 sequelae in patients who survived COVID-19 and underwent a formal clinical reassessment, categorising infection according to the date of diagnosis as the omicron (B.1.1.529) phase from Dec 15, 2021, to Jan 31, 2022; the alpha (B.1.1.7)-delta (B.1.617.2) phase from Dec 1, 2020, to Dec 14, 2021; and the pre-vaccination phase from Feb 27 to Nov 30, 2020. The prevalence of overall COVID-19 sequelae was compared according to SARS-CoV-2 immunisation status and in relation to post-COVID-19 survival and resumption of systemic anticancer therapy. This study is registered with ClinicalTrials.gov, NCT04393974. Findings At the follow-up update on June 20, 2022, 1909 eligible patients, evaluated after a median of 39 days (IQR 24-68) from COVID-19 diagnosis, were included (964 [ 50 center dot 7%] of 1902 patients with sex data were female and 938 [49 center dot 3%] were male). Overall, 317 (16 center dot 6%; 95% CI 14 center dot 8-18 center dot 5) of 1909 patients had at least one sequela from COVID-19 at the first oncological reassessment. The prevalence of COVID-19 sequelae was highest in the prevaccination phase (191 [19 center dot 1%; 95% CI 16 center dot 4-22 center dot 0] of 1000 patients). The prevalence was similar in the alpha-delta phase (110 [16 center dot 8%; 13 center dot 8- 20 center dot 3] of 653 patients, p=0 center dot 24), but significantly lower in the omicron phase (16 [6 center dot 2%; 3 center dot 5-10 center dot 2] of 256 patients, p<0 center dot 0001). In the alpha- delta phase, 84 (18 center dot 3%; 95% CI 14 center dot 6-22 center dot 7) of 458 unvaccinated patients and three (9 center dot 4%; 1 center dot 9- 27 center dot 3) of 32 unvaccinated patients in the omicron phase had sequelae. Patients who received a booster and those who received two vaccine doses had a significantly lower prevalence of overall COVID-19 sequelae than unvaccinated or partially vaccinated patients (ten [7 center dot 4%; 95% CI 3 center dot 5-13 center dot 5] of 136 boosted patients, 18 [9 center dot 8%; 5 center dot 8-15 center dot 5] of 183 patients who had two vaccine doses vs 277 [ 18 center dot 5%; 16 center dot 5-20 center dot 9] of 1489 unvaccinated patients, p=0 center dot 0001), respiratory sequelae (six [4 center dot 4%; 1 center dot 6-9 center dot 6], 11 [6 center dot 0%; 3 center dot 0-10 center dot 7] vs 148 [9 center dot 9%; 8 center dot 4- 11 center dot 6], p= 0 center dot 030), and prolonged fatigue (three [2 center dot 2%; 0 center dot 1-6 center dot 4], ten [5 center dot 4%; 2 center dot 6-10 center dot 0] vs 115 [7 center dot 7%; 6 center dot 3-9 center dot 3], p=0 center dot 037)

Extracellular vesicles and their nucleic acids for biomarker discovery

Extracellular vesicles (EVs) are a heterogenous population of vesicles originate from cells. EVs are found in different biofluids and carry different macromolecules, including proteins, lipids, and nucleic acids, providing a snap shot of the parental cells at the time of release. EVs have the ability to transfer molecular cargoes to other cells and can initiate different physiological and pathological processes. Mounting lines of evidence demonstrated that EVs' cargo and machinery is affected in disease states, positioning EVs as potential sources for the discovery of novel biomarkers. In this review, we demonstrate a conceptual overview of the EV field with particular focus on their nucleic acid cargoes. Current knowledge of EV subtypes, nucleic acid cargo and pathophysiological roles are outlined, with emphasis placed on advantages against competing analytes. We review the utility of EVs and their nucleic acid cargoes as biomarkers and critically assess the newly available advances in the field of EV biomarkers and high throughput technologies. Challenges to achieving the diagnostic potential of EVs, including sample handling, EV isolation, methodological considerations, and bioassay reproducibility are discussed. Future implementation of ‘omics-based technologies and integration of systems biology approaches for the development of EV-based biomarkers and personalized medicine are also considered

Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19

Background: We previously reported that impaired type I IFN activity, due to inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity or to autoantibodies against type I IFN, account for 15–20% of cases of life-threatening COVID-19 in unvaccinated patients. Therefore, the determinants of life-threatening COVID-19 remain to be identified in ~ 80% of cases. Methods: We report here a genome-wide rare variant burden association analysis in 3269 unvaccinated patients with life-threatening COVID-19, and 1373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. Among the 928 patients tested for autoantibodies against type I IFN, a quarter (234) were positive and were excluded. Results: No gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7, with an OR of 27.68 (95%CI 1.5–528.7, P = 1.1 × 10−4) for biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR = 3.70[95%CI 1.3–8.2], P = 2.1 × 10−4). This enrichment was further strengthened by (1) adding the recently reported TYK2 and TLR7 COVID-19 loci, particularly under a recessive model (OR = 19.65[95%CI 2.1–2635.4], P = 3.4 × 10−3), and (2) considering as pLOF branchpoint variants with potentially strong impacts on splicing among the 15 loci (OR = 4.40[9%CI 2.3–8.4], P = 7.7 × 10−8). Finally, the patients with pLOF/bLOF variants at these 15 loci were significantly younger (mean age [SD] = 43.3 [20.3] years) than the other patients (56.0 [17.3] years; P = 1.68 × 10−5). Conclusions: Rare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60&nbsp;years old