Plasma-based longitudinal mutation monitoring as a potential predictor of disease progression in subjects with adenocarcinoma in advanced non-small cell lung cancer.

BACKGROUND: Identifying and tracking somatic mutations in cell-free DNA (cfDNA) by next-generation sequencing (NGS) has the potential to transform the clinical management of subjects with advanced non-small cell lung cancer (NSCLC). METHODS: Baseline tumor tissue (n = 47) and longitudinal plasma (n = 445) were collected from 71 NSCLC subjects treated with chemotherapy. cfDNA was enriched using a targeted-capture NGS kit containing 197 genes. Clinical responses to treatment were determined using RECIST v1.1 and correlations between changes in plasma somatic variant allele frequencies and disease progression were assessed. RESULTS: Somatic variants were detected in 89.4% (42/47) of tissue and 91.5% (407/445) of plasma samples. The most commonly mutated genes in tissue were TP53 (42.6%), KRAS (25.5%), and KEAP1 (19.1%). In some subjects, the allele frequencies of mutations detected in plasma increased 3-5 months prior to disease progression. In other cases, the allele frequencies of detected mutations declined or decreased to undetectable levels, indicating clinical response. Subjects with circulating tumor DNA (ctDNA) levels above background had significantly shorter progression-free survival (median: 5.6 vs 8.9 months, respectively; log-rank p = 0.0183). CONCLUSION: Longitudinal monitoring of mutational changes in plasma has the potential to predict disease progression early. The presence of ctDNA mutations during first-line treatment is a risk factor for earlier disease progression in advanced NSCLC.

Highly multiplexed immune repertoire sequencing links multiple lymphocyte classes with severity of response to COVID-19.

Background: Disease progression of subjects with coronavirus disease 2019 (COVID-19) varies dramatically. Understanding the various types of immune response to SARS-CoV-2 is critical for better clinical management of coronavirus outbreaks and to potentially improve future therapies. Disease dynamics can be characterized by deciphering the adaptive immune response. Methods: In this cross-sectional study we analyzed 117 peripheral blood immune repertoires from healthy controls and subjects with mild to severe COVID-19 disease to elucidate the interplay between B and T cells. We used an immune repertoire Primer Extension Target Enrichment method (immunoPETE) to sequence simultaneously human leukocyte antigen (HLA) restricted T cell receptor beta chain (TRB) and unrestricted T cell receptor delta chain (TRD) and immunoglobulin heavy chain (IgH) immune receptor repertoires. The distribution was analyzed of TRB, TRD and IgH clones between healthy and COVID-19 infected subjects. Using McFadden's Adjusted R2 variables were examined for a predictive model. The aim of this study is to analyze the influence of the adaptive immune repertoire on the severity of the disease (value on the World Health Organization Clinical Progression Scale) in COVID-19. Findings: Combining clinical metadata with clonotypes of three immune receptor heavy chains (TRB, TRD, and IgH), we found significant associations between COVID-19 disease severity groups and immune receptor sequences of B and T cell compartments. Logistic regression showed an increase in shared IgH clonal types and decrease of TRD in subjects with severe COVID-19. The probability of finding shared clones of TRD clonal types was highest in healthy subjects (controls). Some specific TRB clones seems to be present in severe COVID-19 (Figure S7b). The most informative models (McFadden´s Adjusted R2=0.141) linked disease severity with immune repertoire measures across all three cell types, as well as receptor-specific cell counts, highlighting the importance of multiple lymphocyte classes in disease progression. Interpretation: Adaptive immune receptor peripheral blood repertoire measures are associated with COVID-19 disease severity. Funding: The study was funded with grants from the Berlin Institute of Health (BIH).

Innovative Tumor Tissue Dissection Tool for Molecular Oncology Diagnostics.

Formalin-fixed, paraffin-embedded (FFPE) tissue is the most commonly used material for tumor molecular profiling, therapy selection, and prognostication. Tumor tissue enrichment by tissue dissection is highly recommended to generate quality data reproducibly for use in downstream assays, such as real-time PCR and next-generation sequencing. The aim of this study was to evaluate the performance of the automated tissue dissection tool AVENIO Millisect System compared with a manual dissection method using 18 FFPE tissue specimens. The study assessed performance of these two methods with paraffinized and deparaffinized sections at 5- and 10-µm thickness as well as at low (5% to 10%) and high (>50%) tumor content. In addition, compatibility with various nucleic acid and protein extraction methods was assessed. Overall, dissection by Millisect resulted in statistically significantly higher yields of nucleic acids and protein compared with manual dissection (P = 0.00524). In downstream analysis on a statistically nonpowered sample set, EGFR mutation testing by PCR led to highly concordant results, and next-generation sequencing testing yielded significantly higher allelic frequencies when tissue was dissected by Millisect compared with manual scraping, demonstrating noninferiority of the automated method. In summary, the AVENIO Millisect System may replace manual labor and support automation of FFPE tumor tissue workflows in clinical molecular laboratories with high testing volumes with adequate validation.

Increased risk of severe clinical course of COVID-19 in carriers of HLA-C*04:01.

BACKGROUND: Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic, there has been increasing urgency to identify pathophysiological characteristics leading to severe clinical course in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Human leukocyte antigen alleles (HLA) have been suggested as potential genetic host factors that affect individual immune response to SARS-CoV-2. We sought to evaluate this hypothesis by conducting a multicenter study using HLA sequencing. METHODS: We analyzed the association between COVID-19 severity and HLAs in 435 individuals from Germany (n = 135), Spain (n = 133), Switzerland (n = 20) and the United States (n = 147), who had been enrolled from March 2020 to August 2020. This study included patients older than 18 years, diagnosed with COVID-19 and representing the full spectrum of the disease. Finally, we tested our results by meta-analysing data from prior genome-wide association studies (GWAS). FINDINGS: We describe a potential association of HLA-C*04:01 with severe clinical course of COVID-19. Carriers of HLA-C*04:01 had twice the risk of intubation when infected with SARS-CoV-2 (risk ratio 1.5 [95% CI 1.1-2.1], odds ratio 3.5 [95% CI 1.9-6.6], adjusted p-value = 0.0074). These findings are based on data from four countries and corroborated by independent results from GWAS. Our findings are biologically plausible, as HLA-C*04:01 has fewer predicted bindings sites for relevant SARS-CoV-2 peptides compared to other HLA alleles. INTERPRETATION: HLA-C*04:01 carrier state is associated with severe clinical course in SARS-CoV-2. Our findings suggest that HLA class I alleles have a relevant role in immune defense against SARS-CoV-2. FUNDING: Funded by Roche Sequencing Solutions, Inc.