The preanalytical phase in the era of high-throughput genetic testing. What the future holds

Laboratory Medicine is undergoing one of the most challenging periods of its more than centenarian existence [1]. Many technological innovations, coupled with a deeper understanding of pathophysiological mechanisms of human diseases, have contributed enormously to expanding the armamentarium of diagnostic tests that the modern clinical laboratories have made available to their stakeholders [2]. The ensuing increased volume and complexity of diagnostic testing are counterbalanced by many emerging threats, which are contributing to make our daily activities inside the laboratory environment still more complicated. These new challenges include an increasing contraction of public funding, which is now a hallmark of many national healthcare systems, the increasing demand for high quality and advanced care, the reorganization of laboratory services within a large network of facilities according to the so-called “hub-and-spoke” paradigm, and which is then contributing to alienate patients from the primary site of diagnostic testing [3].

The scenario is then worsened by an increasing shortage of vocations of young laboratory professionals, who would be expected to become the backbone of our future profession, as well as by the alarming underestimation that many policymakers and hospital administrators have on the real added value that laboratory diagnostics can endow to the clinical decision-making and to managed care. Albeit, laboratory diagnostics only uses less than 2% of the total healthcare expenditure, it is now undeniable that laboratory test results contribute to the vast majority of clinical decisions [4].

Several lines of evidence support the notion that the preanalytical phase is the most vulnerable part of the total testing process as slips or lapses occurring in some manually intensive activities (i.e. related to sample collection, handling, transportation and preparation) before sample analysis may contribute to generate the largest number of diagnostic errors [5]. Much progress has been made in the past decades for preventing (or limiting) the burden of preanalytical errors [6], yet new challenges constantly emerge. The ongoing introduction of new genetic techniques in routine diagnostics, previoulsy confined to research settings, is now imposing new paradigms on preanalytical quality, which are often more stringent, or simply different, from those characterizing conventional (i.e. “phenotypic”) laboratory testing (e.g. clinical chemistry, immunochemistry, protein electrophoresis, hemostasis, laboratory hematology).

High-throughput genetic techniques, including next-generation sequencing (NGS), are now increasingly used for diagnosing a vast array of human disorders at affordable costs, thus replacing or surrogating conventional diagnostic techniques [7]. Besides “clerical” errors (i.e. sample mismatch, the presence of interfering substances, drawing samples in incorrect tubes), minimal human-human specimen contamination (i.e. in the order of μL or even nL/mL) usually has a modest impact on conventional phenotypic testing, whilst even a negligible contamination with homologous genetic material that occur during the preanalytical processing of specimens may be a calamity for genetic analyses, especially in laboratories performing large volumes of samples in multiplex, due to the potential of generating false-positive variant results, which will then be permanently attributed to the patients, throughout their lifespan [8].

The so-called “liquid biopsy” is another far-reaching and relatively innovative diagnostic enterprise, which is aimed at detecting circulating neoplastic cells or DNA fragments originating from cancer cells, hence embodying the molecular signatures of tumors [9]. Even in such cases, some preanalytical requirements (i.e. blood tubes, additives, conditions of transportation and storage, separation or precipitation) may differ from conventional phenotypic testing. DNA fragments are approximately 150–200 bp long, and reflect specific genetic targets, which can be reliably used as diagnostic, prognostic or predictive biomarkers. Their characterization not only requires a high degree of analytical quality, but should also fulfill stringent preanalytical requirements aimed at maintaining stability and preventing unwanted degradation of genetic material, which may then erode its potential clinical value [10, 11]. The sample matrix itself is also problematic. Free DNA can be measured in serum, plasma, exosomes and extracellular vesicles [12], but the use of one sample matrix rather than another does not yield overlapping data, thus potentially leading to misinterpretation of results and misdiagnosis. Finally, major efforts should be made for standardizing sample preparation (i.e. centrifuging, filtration and free DNA isolation) as the different techniques may generate heterogeneous DNA yields, especially regarding the recovery of different DNA fractions [13].

Whilst theoretically straightforward, genetic analyses appear even more vulnerable to preanalytical variables than phenotypic testing (Figure 1). Unlike phenotypic testing, however, the identification of preanalytical drawbacks is more challenging and the potential clinical consequences of preanalytical errors are magnified by the risk of misdiagnosing germinal or somatic mutations and polymorphisms, potentially associated with genetic diseases or cancer. Hence, a pervasive and holistic approach will be necessary for improving the preanalytical quality of genetic testing. This will entail planning specific risk minimization strategies by developing specific preanalytical recommendations for specimens used for genetic testing, along with the creation of an enlarged set of quality performance indicators [14], aimed at covering the many and often peculiar preanalytical issues of high-throughput genetic technologies.

Figure 1:

Specific preanalytical issues for genetic testing.