Epigenetic Signatures of Asthma: A Comprehensive Study of DNA Methylation and Clinical Markers.

Background: Asthma, a complex respiratory disease, presents with inflammatory symptoms in the lungs, blood, and other tissues. We investigated the relationship between DNA methylation and 35 clinical markers of asthma. The Illumina Infinium EPIC v1 methylation array was used to evaluate 742,442 CpGs in whole blood samples from 319 participants. They were part of the Netherlands Twin Register from families with at least one member suffering from severe asthma. Repeat blood samples were taken after 10 years from 182 of these individuals. Principal component analysis (PCA) on the clinical markers yielded ten principal components (PCs) that explained 92.8% of the total variance. We performed epigenome-wide association studies (EWAS) for each of the ten PCs correcting for familial structure and other covariates. Results: 221 unique CpGs reached genome-wide significance at timepoint 1 (T1) after Bonferroni correction. PC7 accounted for the majority of associations (204), which correlated with loadings of eosinophil counts and immunoglobulin levels. Enrichment analysis via the EWAS Atlas identified 190 of these CpGs to be previously identified in EWASs of asthma and asthma-related traits. Proximity assessment to previously identified SNPs associated with asthma identified 17 unique SNPs within 1 MB of two of the 221 CpGs. EWAS in 182 individuals with epigenetic data at a second timepoint (T2) identified 49 significant CpGs. EWAS Atlas enrichment analysis indicated that 4 of the 49 were previously associated with asthma or asthma-related traits. Comparing the estimates of all the significant associations identified across the two time points (271 in total) yielded a correlation of 0.81. Conclusion: We identified 270 unique CpGs that were associated with PC scores generated from 35 clinical markers of asthma, either cross-sectionally or 10 years later. A strong correlation was present between effect sizes at the 2 timepoints. Most associations were identified for PC7, which captured blood eosinophil counts and immunoglobulin levels and many of these CpGs have previous associations in earlier studies of asthma and asthma-related traits. The results point to using this robust DNA methylation profile as a new, stable biomarker for asthma.

More Than Results: The Clinical and Research Relationship in the Evolving Detection and Surveillance of SARS-CoV-2.

INTRODUCTION: During the coronavirus disease 2019 (COVID-19) pandemic, real-time reverse transcription polymerase chain reaction (RT-PCR) became an essential tool for laboratories to provide high-sensitivity qualitative diagnostic testing for patients and real-time data to public health officials. Here we explore the predictive value of quantitative data from RT-PCR cycle threshold (Ct) values in epidemiological measures, symptom presentation, and variant transition. METHODS: To examine the association with hospitalizations and deaths, data from 74,479 patients referred to the Avera Institute for Human Genetics (AIHG) for COVID-19 testing in 2020 were matched by calendar week to epidemiological data reported by the South Dakota Department of Health. We explored the association between symptom data, patient age, and Ct values for 101 patients. We also explored changes in Ct values during variant transition detected by genomic surveillance sequencing of the AIHG testing population during 2021. RESULTS: Measures from AIHG diagnostic testing strongly explain variance in the South Dakota state positivity percentage (R2 = 0.758), a two-week delay in hospitalizations (R2 = 0.856), and a four-week delay in deaths (R2 = 0.854). Based on factor analysis of patient symptoms, three groups could be distinguished which had different presentations of age, Ct value, and time from collection. Additionally, conflicting Ct value results among SARSCoV- 2 variants during variant transition may reflect the community transmission dynamics. CONCLUSIONS: Measures of Ct value in RT-PCR diagnostic assays combined with routine screening have valuable applications in monitoring the dynamics of SARS-CoV-2 within communities.

B cell-dependent subtypes and treatment-based immune correlates to survival in stage 3 and 4 lung adenocarcinomas.

Lung cancer is the leading cause of cancer-related deaths worldwide. Surgery and chemoradiation are the standard of care in early stages of non-small cell lung cancer (NSCLC), while immunotherapy is the standard of care in late-stage NSCLC. The immune composition of the tumor microenvironment (TME) is recognized as an indicator for responsiveness to immunotherapy, although much remains unknown about its role in responsiveness to surgery or chemoradiation. In this pilot study, we characterized the NSCLC TME using mass cytometry (CyTOF) and bulk RNA sequencing (RNA-Seq) with deconvolution of RNA-Seq being performed by Kassandra, a recently published deconvolution tool. Stratification of patients based on the intratumoral abundance of B cells identified that the B-cell rich patient group had increased expression of CXCL13 and greater abundance of PD1+ CD8 T cells. The presence of B cells and PD1+ CD8 T cells correlated positively with the presence of intratumoral tertiary lymphoid structures (TLS). We then assessed the predictive and prognostic utility of these cell types and TLS within publicly available stage 3 and 4 lung adenocarcinoma (LUAD) RNA-Seq datasets. As previously described by others, pre-treatment expression of intratumoral 12-chemokine TLS gene signature is associated with progression free survival (PFS) in patients who receive treatment with immune checkpoint inhibitors (ICI). Notably and unexpectedly pre-treatment percentages of intratumoral B cells are associated with PFS in patients who receive surgery, chemotherapy, or radiation. Further studies to confirm these findings would allow for more effective patient selection for both ICI and non-ICI treatments.

Pathogenesis of Tobacco-Associated Lung Adenocarcinoma Is Closely Coupled with Changes in the Gut and Lung Microbiomes.

Microbial dysbiosis has emerged as a modulator of oncogenesis and response to therapy, particularly in lung cancer. Here, we investigate the evolution of the gut and lung microbiomes following exposure to a tobacco carcinogen. We performed 16S rRNA-Seq of fecal and lung samples collected prior to and at several timepoints following (nicotine-specific nitrosamine ketone/NNK) exposure in Gprc5a-/- mice that were previously shown to exhibit accelerated lung adenocarcinoma (LUAD) development following NNK exposure. We found significant progressive changes in human-relevant gut and lung microbiome members (e.g., Odoribacter, Alistipes, Akkermansia, and Ruminococus) that are closely associated with the phenotypic development of LUAD and immunotherapeutic response in human lung cancer patients. These changes were associated with decreased short-chain fatty acids (propionic acid and butyric acid) following exposure to NNK. We next sought to study the impact of Lcn2 expression, a bacterial growth inhibitor, given our previous findings on its protective role in LUAD development. Indeed, we found that the loss of Lcn2 was associated with widespread gut and lung microbiome changes at all timepoints, distinct from those observed in our Gprc5a-/- mouse model, including a decrease in abundance and diversity. Our overall findings apprise novel cues implicating microbial phenotypes in the development of tobacco-associated LUAD.

Case report: 16-yr life history and genomic evolution of an ER+ HER2- breast cancer.

Metastatic breast cancer is one of the leading causes of cancer-related death in women. Limited studies have been done on the genomic evolution between primary and metastatic breast cancer. We reconstructed the genomic evolution through the 16-yr history of an ER+ HER2- breast cancer patient to investigate molecular mechanisms of disease relapse and treatment resistance after long-term exposure to hormonal therapy. Genomic and transcriptome profiling was performed on primary breast tumor (2002), initial recurrence (2012), and liver metastasis (2015) samples. Cell-free DNA analysis was performed at 11 time points (2015-2017). Mutational analysis revealed a low mutational burden in the primary tumor that doubled at the time of progression, with driver mutations in PI3K-Akt and RAS-RAF signaling pathways. Phylogenetic analysis showed an early branching off between primary tumor and metastasis. Liquid biopsies, although initially negative, started to detect an ESR1 E380Q mutation in 2016 with increasing allele frequency until the end of 2017. Transcriptome analysis revealed 721 (193 up, 528 down) genes to be differentially expressed between primary tumor and first relapse. The most significantly down-regulated genes were TFF1 and PGR, indicating resistance to aromatase inhibitor (AI) therapy. The most up-regulated genes included PTHLH, S100P, and SOX2, promoting tumor growth and metastasis. This phylogenetic reconstruction of the life history of a single patient's cancer as well as monitoring tumor progression through liquid biopsies allowed for uncovering the molecular mechanisms leading to initial relapse, metastatic spread, and treatment resistance.

Deep targeted sequencing analysis of hot spot mutations in non-small cell lung cancer patients from the Middle Eastern population.

BACKGROUND: The overall 5-year survival of lung cancer remains dismal despite the current treatment regimens. Testing for driver mutations has become routine practice for oncologists due to the presence of targeted therapy readily available for patients. Deep targeted sequencing through next generation sequencing (NGS) is an adequate methodology to detect mutations at multi-genetic levels. The molecular pathology of non-small cell lung cancer (NSCLC) is poorly understood in the Middle East and, to date, no other reports have been published on deep targeted sequencing of lung adenocarcinoma (LUAD) tissues. METHODS: Deep targeted sequencing using TruSeq Amplicon Cancer panel of 48 genes was performed on 85 formalin-fixed paraffin-embedded tissues from patients with LUAD who were treatment-naive at the time of the collection. Variants with an allele frequency higher than 10% were retained. RESULTS: Variant calling identified a total of 2,455 variants of which missense mutations were the most frequent (75.6%). All of our samples showed at least one mutation in one of the 10 most commonly mutated genes with FLT3 being the gene with the highest mutation rate (67%). TP53, KRAS and STK11 were the second, third and fourth most commonly mutated genes, respectively while EGFR mutation rate reached 22.4%. CONCLUSIONS: To the best of our knowledge, this is the first hot spot profiling study on patients from this area. The frequencies of mutated genes presented in our study showed similarity to other reported outcomes. At least one mutation was detected in our cohort of LUAD.