Standardization of sequencing coverage depth in NGS: Recommendation for detection of clonal and subclonal mutations in cancer diagnostics

The insufficient standardization of diagnostic next-generation sequencing (NGS) still limits its implementation in clinical practice, with the correct detection of mutations at low variant allele frequencies (VAF) facing particular challenges. We address here the standardization of sequencing coverage depth in order to minimize the probability of false positive and false negative results, the latter being underestimated in clinical NGS. There is currently no consensus on the minimum coverage depth, and so each laboratory has to set its own parameters. To assist laboratories with the determination of the minimum coverage parameters, we provide here a user-friendly coverage calculator. Using the sequencing error only, we recommend a minimum depth of coverage of 1,650 together with a threshold of at least 30 mutated reads for a targeted NGS mutation analysis of >= 3% VAF, based on the binomial probability distribution. Moreover, our calculator also allows adding assay-specific errors occurring during DNA processing and library preparation, thus calculating with an overall error of a specific NGS assay. The estimation of correct coverage depth is recommended as a starting point when assessing thresholds of NGS assay. Our study also points to the need for guidance regarding the minimum technical requirements, which based on our experience should include the limit of detection (LOD), overall NGS assay error, input, source and quality of DNA, coverage depth, number of variant supporting reads, and total number of target reads covering variant region. Further studies are needed to define the minimum technical requirements and its reporting in diagnostic NGS.Web of Science9art. no. 85

Inflammation time-axis in aseptic loosening of total knee arthroplasty: A preliminary study

Objective Aseptic loosening (AL) is the most frequent long-term reason for revision of total knee arthroplasty (TKA) affecting about 15–20% patients within 20 years after the surgery. Although there is a solid body of evidence about the crucial role of inflammation in the AL pathogenesis, scared information on inflammation signature and its time-axis in tissues around TKA exists. Design The inflammation protein signatures in pseudosynovial tissues collected at revision surgery from patients with AL (AL, n = 12) and those with no clinical/radiographic signs of AL (non-AL, n = 9) were investigated by Proximity Extension Assay (PEA)-Immunoassay and immunohistochemistry. Results AL tissues had elevated levels of TNF-family members sTNFR2, TNFSF14, sFasL, sBAFF, cytokines/chemokines IL8, CCL2, IL1RA/IL36, sIL6R, and growth factors sAREG, CSF1, comparing to non-AL. High interindividual variability in protein levels was evident particularly in non-AL. Levels of sTNFR2, sBAFF, IL8, sIL6R, and MPO discriminated between AL and non-AL and were associated with the time from index surgery, suggesting the cumulative character of inflammatory osteolytic response to prosthetic byproducts. The source of elevated inflammatory molecules was macrophages and multinucleated osteoclast-like cells in AL and histiocytes and osteoclast-like cells in non-AL tissues, respectively. All proteins were present in higher levels in osteoclast-like cells than in macrophages. Conclusions Our study revealed a differential inflammation signature between AL and non-AL stages of TKA. It also highlighted the unique patient’s response to TKA in non-AL stages. Further confirmation of our preliminary results on a larger cohort is needed. Analysis of the time-axis of processes ongoing around TKA implantation may help to understand the mechanisms driving periprosthetic bone resorption needed for diagnostic/preventative strategies.Web of Science148art. no. E022105