Role of Epigenetics in the Pathogenesis, Treatment, Prediction, and Cellular Transformation of Asthma

Asthma is a mysterious disease with heterogeneity in etiology, pathogenesis, and clinical phenotypes. Although ongoing studies have provided a better understanding of asthma, its natural history, progression, pathogenesis, diversified phenotypes, and even the exact epigenetic linkage between childhood asthma and adult-onset/old age asthma remain elusive in many aspects. Asthma heritability has been established through genetic studies, but genetics is not the only influencing factor in asthma. The increasing incidence and some unsolved queries suggest that there may be other elements related to asthma heredity. Epigenetic mechanisms link genetic and environmental factors with developmental trajectories in asthma. This review provides an overview of asthma epigenetics and its components, including several epigenetic studies on asthma, and discusses the epigenetic linkage between childhood asthma and adult-onset/old age asthma. Studies involving asthma epigenetics present valuable novel approaches to solve issues related to asthma. Asthma epigenetic research guides us towards gene therapy and personalized T cell therapy, directs the discovery of new therapeutic agents, predicts long-term outcomes in severe cases, and is also involved in the cellular transformation of childhood asthma to adult-onset/old age asthma.

Mycobacteriophage–antibiotic therapy promotes enhanced clearance of drug-resistant Mycobacterium abscessus

ABSTRACT Infection by multidrug-resistant Mycobacterium abscessus is increasingly prevalent in cystic fibrosis (CF) patients, leaving clinicians with few therapeutic options. A compassionate study showed the clinical improvement of a CF patient with a disseminated M. abscessus (GD01) infection, following injection of a phage cocktail, including phage Muddy. Broadening the use of phage therapy in patients as a potential antibacterial alternative necessitates the development of biological models to improve the reliability and successful prediction of phage therapy in the clinic. Herein, we demonstrate that Muddy very efficiently lyses GD01 in vitro, an effect substantially increased with standard drugs. Remarkably, this cooperative activity was retained in an M. abscessus model of infection in CFTR-depleted zebrafish, associated with a striking increase in larval survival and reduction in pathological signs. The activity of Muddy was lost in macrophage-ablated larvae, suggesting that successful phage therapy relies on functional innate immunity. CFTR-depleted zebrafish represent a practical model to rapidly assess phage treatment efficacy against M. abscessus isolates, allowing the identification of drug combinations accompanying phage therapy and treatment prediction in patients. This article has an associated First Person interview with the first author of the paper.

LncRNA SRA gene polymorphisms and risk of gynecological pathology development among Ukrainian women with proliferative type of benign breast disease without atypia

Benign breast disease is a group of all noncancerous mammary lesions with a risk of breast cancer (BC) development. BC is the most common cancer in the world; therefore, it is necessary to find new biomarkers and targets for early diagnosis, treatment, prediction of prognosis and survival. Long non-coding RNA SRA could play this role, thus further studies of its impact on the precancerous lesion pathogenesis are needed. The aim. To analyze the association between SRA1 rs801460 and rs10463297 SNPs and the occurrence of gynecological pathology among Ukrainian women with the proliferative type of benign breast disease without atypia. Materials and methods. This study included 115 patients with proliferative type of benign breast disease without atypia: 55 – with gynecological pathology and 60 – without it. Polymerase chain reaction-restriction fragment length polymorphism analysis (PCR-RFLP) was used for polymorphism genotyping. Hematoxylin and eosin, toluidine blue and van Gieson’s picrofuchsin methods were applied for staining of sections. Statistical analysis was carried out using Statistical Package for the Social Sciences software (SPSS, version 25.0, Chicago, IL, USA). Results. Significant differences were found in the rs10463297 frequency of alleles (P = 0.032), but not in the rs801460 (P > 0.05), in groups with and without gynecological pathology, while the distribution of both single nucleotide polymorphism (SNPs) genotypes was similar between these groups (P > 0.05). Statistically significant association was detected between SRA1 rs10463297 polymorphism and gynecological pathology occurrence in both dominant (Pa = 0.023; ORa = 2.638, 95 % CI = 1.145–6.076) and additive (Pa = 0.034; ORa = 2.489, 95 % CI = 1.069–5.794) models of inheritance. No association was found between SRA1 rs801460 SNP and gynecological pathology development among Ukrainian women with proliferative type of benign breast disease without atypia (P > 0.05). Conclusions. It was revealed that SRA1 rs10463297 TT carriers had 2.6 times higher risk of gynecological pathology development than C allele carriers and 2.48 times than TC carriers.

Radiomics of MRI for the Prediction of the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer Patients: A Single Referral Centre Analysis

Objectives: We aimed to determine whether radiomic features extracted from a highly homogeneous database of breast MRI could non-invasively predict pathological complete responses (pCR) to neoadjuvant chemotherapy (NACT) in patients with breast cancer. Methods: One hundred patients with breast cancer receiving NACT in a single center (01/2017–06/2019) and undergoing breast MRI were retrospectively evaluated. For each patient, radiomic features were extracted within the biopsy-proven tumor on T1-weighted (T1-w) contrast-enhanced MRI performed before NACT. The pCR to NACT was determined based on the final surgical specimen. The association of clinical/biological and radiomic features with response to NACT was evaluated by univariate and multivariable analysis by using random forest and logistic regression. The performances of all models were assessed using the areas under the receiver operating characteristic curves (AUC) with 95% confidence intervals (CI). Results: Eighty-three patients (mean (SD) age, 47.26 (8.6) years) were included. Patients with HER2+, basal-like molecular subtypes and Ki67 ≥ 20% presented a pCR to NACT more frequently; the clinical/biological model’s AUC (95% CI) was 0.81 (0.71–0.90). Using 136 representative radiomics features selected through cluster analysis from the 1037 extracted features, a radiomic score was calculated to predict the response to NACT, with AUC (95% CI): 0.64 (0.51–0.75). After combining the clinical/biological and radiomics models, the AUC (95% CI) was 0.83 (0.73–0.92). Conclusions: MRI-based radiomic features slightly improved the pre-treatment prediction of pCR to NACT, in addiction to biological characteristics. If confirmed on larger cohorts, it could be helpful to identify such patients, to avoid unnecessary treatment.

Biomarkers and cell-based models to predict the outcome of neoadjuvant therapy for rectal cancer patients

Rectal cancer constitutes approximately one-third of all colorectal cancers and contributes to considerable mortality globally. In contrast to colon cancer, the standard treatment for localized rectal cancer often involves neoadjuvant chemoradiotherapy. Tumour response rates to treatment show substantial inter-patient heterogeneity, indicating a need for treatment stratification. Consequently researchers have attempted to establish new means for predicting tumour response in order to assist in treatment decisions. In this review we have summarized published findings regarding potential biomarkers to predict neoadjuvant treatment response for rectal cancer tumours. In addition, we describe cell-based models that can be utilized both for treatment prediction and for studying the complex mechanisms involved.

PD-L1 Testing in Cytological Non-Small Cell Lung Cancer Specimens: A Comparison with Biopsies and Review of the Literature

<b><i>Introduction:</i></b> Programmed death-ligand 1 (PD-L1) expression is used for treatment prediction in non-small cell lung cancer (NSCLC). While cytology may be the only available material in the routine clinical setting, testing in clinical trials has mainly been based on biopsies. <b><i>Methods:</i></b> We included 2 retrospective cohorts of paired, concurrently sampled, cytological specimens and biopsies. Also, the literature on PD-L1 in paired cytological/histological samples was reviewed. Focus was on the cutoff levels ≥1 and ≥50% positive tumor cells. <b><i>Results:</i></b> Using a 3-tier scale, PD-L1 was concordant in 40/47 (85%) and 66/97 (68%) of the paired NSCLC cases in the 2 cohorts, with kappa 0.77 and 0.49, respectively. In the former cohort, all discordant cases had lower score in cytology. In both cohorts, concordance was lower in samples from different sites (e.g., biopsy from primary tumor and cytology from pleural effusion). Based on 25 published studies including about 1,700 paired cytology/histology cases, the median (range) concordance was 81–85% (62–100%) at cutoff 1% for a positive PD-L1 staining and 89% (67–100%) at cutoff 50%. <b><i>Conclusions:</i></b> The overall concordance of PD-L1 between cytology and biopsies is rather good but with significant variation between laboratories, which calls for local quality assurance.

Protocol for a pharmacogenomic study on individualised antipsychotic drug treatment for patients with schizophrenia

Background Schizophrenia is a severe and complex psychiatric disorder that needs treatment based on extensive experience. Antipsychotic drugs have already become the cornerstone of the treatment for schizophrenia; however, the therapeutic effect is of significant variability among patients, and only around a third of patients with schizophrenia show good efficacy. Meanwhile, drug-induced metabolic syndrome and other side-effects significantly affect treatment adherence and prognosis. Therefore, strategies for drug selection are desperately needed. In this study, we will perform pharmacogenomics research and set up an individualised preferred treatment prediction model. Aims We aim to create a standard clinical cohort, with multidimensional index assessment of antipsychotic treatment for patients with schizophrenia. Method This trial is designed as a randomised clinical trial comparing treatment with different kinds of antipsychotics. A total sample of 2000 patients with schizophrenia will be recruited from in-patient units from five clinical research centres. Using a computer-generated program, the participants will be randomly assigned to four treatment groups: aripiprazole, olanzapine, quetiapine and risperidone. The primary outcomes will be measured as changes in the Positive and Negative Syndrome Scale of schizophrenia, which reflects the efficacy. Secondary outcomes include the measure of side-effects, such as metabolic syndromes. The efficacy evaluation and side-effects assessment will be performed at baseline, 2 weeks, 6 weeks and 3 months. Results This trial will assess the efficacy and side effects of antipsychotics and create a standard clinical cohort with a multi-dimensional index assessment of antipsychotic treatment for schizophrenia patients. Conclusion This study aims to set up an individualized preferred treatment prediction model through the genetic analysis of patients using different kinds of antipsychotics.