miRquad: first-in-class dPCR multiplex TaqMan™ Advanced RUO assay for microRNA detection in head and neck cancer

miRquad: first-in-class dPCR multiplex TaqMan™ Advanced RUO assay for microRNA detection in head and neck cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article miRquad: first-in-class dPCR multiplex TaqMan™ Advanced RUO assay for microRNA detection in head and neck cancer Matteo Allegretti, David J. Joun, Giulia Urbani, Valentina Pascale, and 21 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7623968/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Dec, 2025 Read the published version in Journal of Experimental & Clinical Cancer Research → Version 1 posted 8 You are reading this latest preprint version Abstract Background: Despite remarkable therapeutic progress, cancer resistance remains one of the major challenges in oncology, often resulting in disease relapse and poor patient outcomes. Resistance arises from multiple genetic and non-genetic mechanisms, ultimately limiting the effectiveness of chemo- and targeted therapies. Within the RNA family, microRNAs (miRNAs) regulate core biological processes and have been recognized also as critical contributors of tumor resistance and therapy failure. Being pivotal, they have been increasingly exploited as biomarkers in various settings. Although in silico analyses facilitate miRNAs identification, PCR-based approaches remain essential to validate their expression. Currently, a plethora of well-established methods exist but multiplex detection from the same input have been only rarely explored. Methods: We present miRquad, the first-in-class digital PCR (dPCR) TaqMan™ multiplex RUO assay for miRNA detection in head and neck (HNC) cancers. Based on a patented prognostic signature including miR-21-5p, miR-96-5p, miR-21-3p and miR-429, the assay enables simultaneous miRNA analysis via qPCR and dPCR across multiple clinically relevant sample types. Results: We designed and optimized miRquad using both synthetic controls and retrospective patient-derived tissues, sera and saliva. A multicentre ring study was conducted to evaluate assay reliability across different platforms, demonstrating strong correlation with commercial singleplexes, broad applicability, and cost-effectiveness. Finally, we provide evidence for its potential clinical application in different HNC settings, testing miRquad on tumoral and peritumoral tissues, sera and saliva samples collected throughout patient follow up. Conclusions : The assay overcomes common challenges associated with multiple miRNAs detection, particularly in liquid biopsy samples, and provides robust and accurate detection, demonstrating potential for real-time patient monitoring and prognostication in HNC. digital PCR multiplex assay microRNA head and neck cancers liquid biopsy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 BACKGROUND Despite remarkable therapeutic achievements, cancer resistance remains a key hurdle in oncology, often causing poor drug responses, disease relapse and, ultimately, patient death ( 1 ). Tumors escape treatment pressure through multiple mechanisms including genetic alterations, rewired signaling pathways, or the adaptation to both immune system and the surrounding microenvironment ( 2 ). Recently, the long-standing view of sequential genetic evolution as the driving force of resistance has been questioned shedding lights on other, non-genetic, adaptive mechanisms ( 3 ). Although our understanding has considerably expanded over the years, tools to anticipate tumor evolution or predict therapy failure remain limited, leaving cancer resistance a pressing challenge in the era of precision medicine. Addressing this limitation is of utmost importance to achieve durable and more effective patient responses. MicroRNAs (miRNAs) are a class of single-stranded, small non-coding RNA molecules that post-transcriptionally modulate gene expression ( 4 , 5 ). Due to their pivotal role in various physiological and pathological processes, including cancer, miRNAs have attracted increasing attention as diagnostic and prognostic biomarkers, being also investigated for therapeutic purposes both in tissues and liquid biopsies (e.g., circulating miRNAs) ( 6 – 8 ). Moreover, their function as key determinants of cancer resistance and drug metabolism has been elucidated ( 9 ). For example, overexpression of miR-21 can promote tumorigenesis and therapy resistance by targeting tumor suppressor genes and signalling pathways ( 10 ). Similarly, miR-34a modulates DNA repair mechanisms, influencing the sensitivity of cancer cells to chemotherapy ( 11 ), while miR-506 acts as a crucial regulator within the competing endogenous RNA (ceRNA) network, affecting cancer cell proliferation and migration ( 12 ). Understanding these miRNA-mediated mechanisms is essential for developing strategies to overcome drug resistance in cancer therapy. However, intrinsic features such as their size, variable abundance in body fluids, sequence homology within different families combined with technical hurdles (e.g., inconsistencies across extraction methods, multiplexing requirements, lack of standardized strategies for normalization of target expression) still pose challenges for miRNA identification and clinical exploitation, limiting their stable implementation as cancer biomarkers ( 13 , 14 ). So far, numerous approaches to evaluate miRNA expression levels, alone or as components of broader signatures, have been proposed ( 14 , 15 ). Among them, reverse transcription quantitative PCR (RT-qPCR) is widely recognized as the gold standard, showing enough sensitivity, specificity and a broad dynamic range while performing at relatively low costs in different settings ( 16 , 17 ). However, the investigation of single deregulated miRNAs, typical of standard RT-qPCR workflows, is often inadequate for cancer profiling, which requires quantitative and multiplex analyses ( 18 ). RT-qPCR also faces limitations when applied to challenging sample types, like those characterized by a limited number of analytes (e.g., liquid biopsies) or by the presence of polymerase inhibitors. Additionally, screening large collections of samples looking for even moderate numbers of targets is prohibitive with qRT-PCR and singleplex assays, requiring multiple individual reactions per biomarker. This, in turn, may result in an error-prone and inefficient process due to sample splitting and wasting ( 17 , 19 ). Over the years, alternative methods as microarray or NGS sequencing have been introduced providing larger amounts of data but in a relatively slow and expensive fashion ( 20 , 21 ). Drawbacks have emerged also for other techniques as rolling circle amplification, duplex-specific nuclease signal amplification, isothermal amplification, all demanding for reaction optimization, improvements in signal readouts, reproducibility and accuracy ( 22 – 24 ). Besides, the introduction and constant update of novel digital PCR (dPCR) systems, either in droplet or array-based format, are expanding the possibilities for accurate miRNAs profiling, particularly in liquid biopsy applications, paving the way for transforming these analytes in powerful, non-invasive tools for cancer detection and monitoring ( 25 , 26 ). dPCR offers absolute quantification of targets by partitioning reactions into thousands of droplets or wells and applying Poisson statistics ( 27 ). This approach eliminates the need for external calibrators or normalization controls, enhances analytical sensitivity, and reduces hands-on time compared to conventional methods. Moreover, advanced platforms support multiplexing as compared to 1st -gen dPCRs ( 28 ) enabling cancer-related miRNA signatures to be explored with reduced workload and at sustainable costs. Nonetheless, challenges related to probe cross-reactivity and assay design may arise, requiring efforts before introducing multiplexed miRNA-based liquid biopsy analyses in clinical practice. Here, we present miRquad, the first-in-class dPCR TaqMan™ Advanced clinical research assay for multiplex miRNA detection in head and neck (HNC) cancers. Based on our previous works demonstrating the prognostic value of miR-21-5p, miR-96-5p, miR-21-3p and miR-429 signature in predicting HNC local recurrence ( 29 – 31 ), we designed and validated a custom research assay relying on TaqMan™ Advanced chemistry, benchmarking its performance on different cohort of clinical samples (e.g., FFPEs, sera and saliva) and lab settings (i.e., through a dedicated ring study). Our efforts result in reproducible, accurate, and affordable quantification of target miRNAs, comparable to that of TaqMan™ commercial single research assays, but with significant advantages over conventional investigation in terms of multiplexing capacity, efficiency, and scalability. Overall, these findings support the potential translation of miRquad into routine clinical practice for the management and monitoring of HNC. METHODS Custom miRNA mimics and spike-ins development To mimic the presence of target miRNAs in solution and dispose of soluble ‘standards’ for a flexible investigation, both in terms of concentration (relative abundance) and analytical composition (numbers of miRNAs simultaneously present), without facing with the biological complexity of clinical samples, 4 different custom BLOCK-IT™ RNA (Thermo Fisher Scientific™, Carlsbad, CA, USA) oligonucleotides were designed using the online tool BLOCK-iT™ RNAi Designer ( https://rnaidesigner.thermofisher.com/rnaiexpress , Thermo Fisher Scientific™) based on the reported sequences in the miRBase database (release 22, https://www.mirbase.org ) (Supplementary Table 1). These products were chemically modified at 5’ with the addition of a phosphate group, and at 3’ to show protruding ends. Both modifications were necessary to allow reverse transcription as for endogenous miRNAs. Custom BLOCK-IT™ RNAs were resuspended in nuclease-free water at a fixed concentration (100 µM) and subsequently diluted at scalar doses (dilution factor 1:10) to generate (a) different single spike-ins hosting known concentrations of a single miRNA of interest and (b) a multiple spike-in that simultaneously included all 4 different miRNAs at 4 different concentrations, which were chosen based on our previous studies ( 29 , 30 ). Synthetic spike-ins were then stored at -80°C until RNA extraction. Biological materials Formalin-fixed paraffin-embedded tissue samples (FFPE, n = 60), including matched tumors and peritumoral area, were obtained from Policlinico of Milan based on an ongoing collaboration within a national grant (PNRR-POC-2022-12376580, EC authorization #105/IRE/24) and used as a validation cohort. Additional FFPE samples (n = 24), belonging to HNCs with different clinical outcome, were obtained from the Regina Elena National Cancer Institute biobank (BB-IRE) and applied for the preliminary benchmark of miRquad and the ring study (see below). FFPE sections (5 µm) were initially assessed with immunohistochemistry for tumor content by a dedicated pathologist and further used for nucleic acid extraction as described below. Serial liquid biopsy samples including sera (n = 48) and saliva (n = 16), collected at specific time intervals (i.e., pre-surgery, 1 day post-surgery, 15 days post-surgery, and at follow-up visits), were retrospectively obtained from the BB-IRE. These were part of a prospective study underway at IRE (EC authorization #RS868/16) which involves patients affected by HPV-negative, resectable HNC of the oral cavity, pharynx or larynx undergoing surgery with curative intent and chemo/radio-treatments or in follow-up as per clinical practice. Study cohort was selected based on the availability of the clinical outcome (i.e., patients with favourable or unfavourable prognosis) and a minimum follow-up of 36 months. A written informed consent was collected from all subjects involved in the study. With respect to sample nature, biological fluids have been subjected to single centrifugation at 3500 g for 20 minutes (sera) or at 2000 g for 10 minutes (cleared saliva), both at 4°C. The former were stored at -80°C while the latter were kept at room temperature by adding 10 ml of ThinPrep solution (Hologic BV, Zaventem, Belgium) to allow long-term stabilization. miRNAs extraction from synthetic and biological specimens Extraction of total RNAs, including miRNAs of interest, from synthetic materials, tissues and liquid biopsies was carried out by the MagMAX™ mirVana™ Total RNA isolation kit and the KingFisher™ Apex purification system (both from Thermo Fisher Scientific™), according to the manufacturer instructions, in a final volume of 50 µl (tissues) or 30 µl (spike-ins, liquid biopsies), respectively. Ten nanograms of Qubit™ BR (Thermo Fisher Scientific™) quantified RNAs from tissues or 2 µl of eluate from liquid biopsies were then reverse transcribed using the TaqMan™ Advanced miRNA cDNA synthesis kit (Thermo Fisher Scientific™), as per protocol. This supports optimal conversion of all miRNAs in the corresponding cDNA, avoiding the need for specific oligonucleotides and targeted amplification, thus providing a single product including all targets at the original ratios. Resulting cDNAs were stored at -20°C until downstream amplification by qPCR or dPCR. qPCR and dPCR analyses Analysis of miRNA expression (i.e., miR-21-5p, miR-96-5p, miR-21-3p and miR-429) was carried out by using either commercially available singleplex TaqMan™ Advanced research assays, single custom assays (those composing the miRquad) or the miRquad as a whole on the QuantStudio™ 5 real-time PCR and QuantStudio™ Absolute Q digital PCR systems (both from Thermo Fisher Scientific™). Experimental design aimed at providing (a) pre-validated commercial references, (b) evaluating the performance of the multiplex assay and (c) investigating any quantitative issue or fluorescence interference due to the simultaneous amplification and detection of different molecular targets into the same reaction. As for qPCR, reactions were setup in triplicates in a final volume of 20 µl containing 10 µl of 2x TaqMan™ Advanced master mix, 1 µl of 20x TaqMan™ research assays (both from Thermo Fisher Scientific™), 5 µl of a 1:10 diluted sample and nuclease-free water. Thermocycling conditions were as follows: 95°C for 20 seconds, 40 cycles at 95°C for 1 second and 60°C for 20 seconds. miRNAs levels, as assessed by commercial assays, were evaluated through automatic thresholding and the average Ct mean, and internally compared with those of custom assays, either in single or multiplex (miRquad) format. dPCR reactions were prepared in a final volume of 10 µl containing 2 µl of 5x Absolute Q™ universal DNA master mix, 0.5 µl of 20x TaqMan™ research assays (both from Thermo Fisher Scientific™), 5 µl of 1:10 diluted sample and nuclease-free water. Thermocycling protocol was as follows: 96°C for 10 minutes, 40 cycles at 96°C for 5 seconds and 60°C for 15 seconds. Automatic thresholding was applied by the software (QuantStudio™ Absolute Q dPCR software, v. 6.3.5, Thermo Fisher Scientific™), manually reviewed by the operator to enhance discrimination between negative from positive dots, and miRNA levels expressed as copies/µl of reaction. dPCR results were compared across various assay conditions and correlated with qPCR data. INNOVA Consortium ring study To extend the analytical evaluation of miRquad on different qPCR/dPCR platforms and clinical environments, the INNOVA Consortium, a multidisciplinary diagnostic network operating within the Italian NHS and translational research which promotes the development and dissemination of novel, standardized, advanced molecular tools, was considered. A ring study involving various (n = 6) Italian Cancer Centres belonging to the WP4 – Liquid Biopsy & Biomarkers group (Supplementary Fig. 1a) was designed and executed as follows: synthetic materials (e.g., single and multiple spike-ins) and representative FFPE, sera and saliva samples (n = 7, 4 and 4, respectively) available at IRE, were extracted, reverse transcribed, splitted in single use aliquots and shipped to all participants; receiving lab personnel were invited to analyse them in a blinded manner according to their own laboratory practice, simultaneously applying both the commercial TaqMan™ Advanced miRNA research assays, custom singleplexes composing the miRquad and the miRquad in the same qPCR or dPCR reaction (depending on instrument availability); raw data were analysed as per laboratory routine using on board software, afterwards sent to IRE for a more broader and cumulative evaluation. Statistical analyses Evaluation of miRquad performance as compared to commercial assays was performed using Student’s t-test and linear regression. The non-parametric Mann-Whitney test was applied to investigate statistical significance of miRNA changes in patient-derived materials. Wilcoxon matched-pairs signed-rank test was applied for comparisons between paired measures. P values ​​< 0.05 were considered statistically significant. All data were reported using GraphPAD® Prism v. 10.5 software application (GraphPAD® software, Dotmatics). RESULTS Custom TaqMan™ Advanced singleplexes specifically amplify their targets mirroring the performance of commercial research assays The formulation of a multiplex assay requires switching from FAM™-conjugated TaqMan™ probes to other fluorescent molecules (e.g., VIC™, ABY™ and Cy5™) to allow simultaneous discrimination of several miRNAs across different channels. To verify whether these modifications may affect the ability of each assay, as singleplex, to properly interact with its target and/or generate false positive spillover-dependent signals (i.e., non-specific signal in neighbouring fluorescence channels), preliminary experiments were performed in qPCR (data not shown) and dPCR using spike-ins containing a discrete concentration (⁓100 copies/µl) of each miRNA of interest as input (Fig. 1 ). Our results clearly showed the ability of all custom assays, with respect to their own fluorescence channel, to successfully amplify target sequences with elevated selectivity, as demonstrated by the nearly complete absence of spillover signals in the non-target fluorescence channels (Fig. 1 a). Next, since the different brightness of custom fluorophores as compared to FAM™ may also affect instrument thresholding impairing the ability to properly discriminate positive/negative signals, we assessed whether our custom singleplexes incorrectly quantified the concentration of target miRNAs and if their detection was allowed within a dynamic range sufficiently wide to consider different biological sources. Initially, we generated series of single spike-ins by sequentially diluting each specific BLOCK-IT™ RNAs at a fixed ratio (1:10) and tested them on qPCR by using commercial assays (Fig. 1 b). A good intra- and inter-assay correlation in terms of scalar concentration was found. Based on the expected expression of each miRNA in clinical samples, specific dilutions from each spike-in series were selected as follows: miR-21-5p > miR-21-3p > miR-96-5p > miR-429. dPCR experiments were then performed investigating miRNA expression with commercial assays or by applying our custom singleplexes. The analysis of copies/µl ​​demonstrated a significant (p < 0.001) concordance ​​between the two detection methods (Fig. 1 c-d). Furthermore, no lack of performance was noted with respect to the different concentrations of the BLOCK-IT™ RNA used as input, demonstrating the high sensitivity of the custom products. miRquad multiplex shows comparable performance to those of custom TaqMan™ Advanced single research assays Having demonstrated the ability of custom assays, as singleplexes, to mirror the behaviour of FAM™-conjugated counterparts, we moved to assess the performance of miRquad as a whole (i.e., in the multiplex format) (Fig. 2 ). Firstly, a side-by-side comparison was carried out in dPCR on newly-generated single spike-ins by alternatively applying either individual custom assays or the miRquad, aiming at unveiling possible technical issues related to the simultaneous presence of multiple primers and probes in samples including only the target sequence (i.e., the specific miRNA of interest at relatively low abundance instead of a mixture of different miRNAs). We observed that, even in the multiplex configuration, our custom assays retained the ability to discriminate each target. More broader extensions of the positive clusters along the fluorescence axis and a global reduction in fluorescence intensity were noted in almost all of fluorescence channels (Fig. 2 a) and, consequently, adjustments of thresholds to ensure correct targets quantification were applied. This effect, partly expected, was supposed to result from the interactions between various primers, their relative concentrations, and multi-probe interferences in the assay. Nevertheless, it did not preclude the use of miRquad nor an accurate quantitation of miRNAs even in the range of low copies/µl (Fig. 2 b). To better investigate whether the fluorescence smear was dependent to the formulation of miRquad itself and could increase in samples simultaneously hosting, among different circulating analytes, multiple miRNAs at higher concentrations, becoming detrimental for an accurate quantification, a multiplex spike-in was generated. Different BLOCK-iT RNAs were spiked at decreasing scalar concentrations in nuclease-free water, total RNA extracted, reverse transcribed and cDNAs were used as input for dPCR (Fig. 2 c-d). Overall, our data demonstrated that, despite fluorescence smears in all other than FAM™ channel, miRquad supports a consistent and absolute quantitation relative to each specific target of interest, also in the presence of multiple analytes, requiring only minimal adjustments of fluorescence thresholds. miRquad is applicable on different biological matrices and grant reproducible results over different platforms and clinical contexts To assess whether miRquad may serve as a valuable molecular tool, particularly in the context of HNC where we previously demonstrated a prognostic role of the signature to predict disease local recurrence ( 29 – 31 ), different biological matrices (i.e., FFPE tissues and sera) were retrospectively collected from the BB-IRE and subjected to dPCR analysis with either the multiplex and commercial assays, the latter being used as a reference. This representative cohort was defined by selecting samples collected over a period of ⁓7 years (range: 3–10 years ago) aiming at mimicking technical and biological variability which generally occurs in real-world clinical settings. Analytical comparisons of assay performances in FFPEs and sera are presented in Fig. 3 a-b and Suppl. Table 2, respectively. As shown, even where RNAs can be notoriously degraded due to sample processing or quantities of circulating miRNA are expected to be intrinsically variable, miRquad maintained the ability to properly identify each target of interest, as the validated commercial assays, showing a significant (p < 0.0001) correlation in terms of copies/µl of reaction across all different sources, for all miRNAs (Fig. 3 c-d). To corroborate preliminary findings, and technically benchmark assay performances on different qPCR/dPCR platforms and in contexts featured by variable technical expertise, evaluation of miRquad was extended by performing a ring study involving 6 Italian institutes belonging to the INNOVA Consortium (Supplementary Fig. 1). Briefly, cDNAs resulting from synthetic material (i.e., spike-ins, both as single or multiplex) and the above-cited biological specimens were shipped in ready-to-use aliquots, blinded to the final users who were asked to provide a final data report according to their laboratory practice. All the results were then collected by IRE, revised to exclude technical and biological issues, and subjected to comparative analysis. As shown in Fig. 4 , the application of commercial assays or the miRquad for qPCR (Fig. 4 a) or dPCR (Fig. 4 b) analyses resulted in a minimal (mean qPCR CV = 6.2%; mean dPCR CV = 3.5%) variability in terms of mean Ct outputs or copies/µl of reaction, respectively, across the different Centers in both single and multiplex spike ins. Highest CVs were recorded on Cy5 fluorescence (i.e. the expression of miR429). This effect was partially expected due to the lower brightness of the fluorophore which renders signal quantification less efficient as compared to the other dyes. Then, representative patient-derived materials, either FFPEs or liquid biopsies (i.e., sera and saliva), were addressed in dPCR with miRquad (Fig. 4 c). Again, no significant differences in miRNA expression levels were noted between different Centers (Fig. 4 e-f). Overall, no technical hurdles were recorded by running miRquad on qPCR/dPCR platforms provided by different vendors, thus supporting its applicability as a molecular tool for biological investigation. miRquad as a non-invasive tool for predicting local recurrence risk in HNC Translational feasibility of miRquad for the clinical management of HNC cancers was finally explored by qPCR and dPCR on an independent cohort of FFPE samples (n = 60), including matched tumoral and peritumoral tissues, additional HNC sera (n = 48) and a selection of saliva (n = 16). As previously observed (Fig. 3 a), also in these additional tissue specimens no significant differences in the expression levels of miR-21-5p, miR-96-5p and miR-21-3p were observed between the miRquad and commercial assays in qPCR (Fig. 5 a). Higher deviations were noted for miR-429 (R 2 = 0.4496) probably due to the relatively low expression (mean Ct > 30) in these samples and the reduced brightness of Cy5. They were partially mitigated by manual thresholding but, as expected, they completely disappeared in dPCR, which offered a more reliable analysis of miRNA expression, rescuing also those samples originally missed/discordant by qPCR. An extended representation of dPCR analysis in low-abundance samples is shown in Fig. 5 b. Notably, when samples were stratified according to sampling site (i.e., core or peritumoral area), miRquad-based analysis recapitulated our previous findings ( 29 , 30 ), with tumor tissues expressing higher levels of the miRNA signature as compared to the peritumoral area. No significant differences were noted between relapsing and not relapsing patients (Fig. 5 c). As to liquid biopsies, performances of miRquad were confirmed also in these sera, where dynamic changes occurring during clinical follow-up were easily detected by dPCR (Fig. 5 d). Particularly, we demonstrated that HNC patients with unfavourable prognosis were characterized by an increase, easily detectable already 15 days after surgery, of the various miRNAs, particularly those belonging to the miR-21 family, while subjects showing a favourable outcome did not, except for miR-429 (Fig. 5 e), whose upregulated levels may depend from the dual role as tumor suppressor/oncomiR ( 32 ). However, when signature changes were considered and compared to miRNA baseline levels, the two groups of patients were stratified with higher accuracy (Fig. 5 f). Finally, since saliva is recognized as the most suitable source for conducting liquid biopsy analyses in HNC ( 33 , 34 ), selected samples collected at baseline and before relapse were tested with miRquad. Representative results are shown in Fig. 5 g. Also in this context, miRquad-based detection resulted in a clear evaluation of each miRNA of interest, reinforcing the observation of higher signature expression in patients with poor prognosis as compared to those displaying good outcome (Fig. 5 h), thus suggesting a potential use of miRquad for real-time monitoring and patient prognostication in HNC by miRNA analysis. DISCUSSION Over the last few years, growing evidence have highlighted miRNAs as promising tools in precision medicine, particularly in oncology. As master regulators of gene expression, miRNA offer several advantages: (a) broad expression enabling detection from different sources; (b) high stability in body fluids allowing non-invasive testing; (c) functionally links to key cellular processes underlying disease onset and evolution ( 4 , 5 ). Furthermore, as components of broader, non-genetic, adaptive mechanisms, they have been recently recognized as critical contributors to cancer resistance and therapy failure ( 9 ). Therefore, miRNAs appear as ideal surrogate biomarkers for early diagnosis, outcome prognostication, treatment monitoring or anticipation of disease progression ( 15 , 35 ). Several clinical trials are currently underway to further validate their important clinical utility (clinicaltrials.gov). Although promising, clinical translation of miRNAs, either as individual biomarkers or as part of multi-miRNA signatures, often face important technical and biological challenges ( 36 ). Paramount among these are the limitations related to the extraction kits, detection methods and assay biases which frequently lead to an altered target representation, ultimately contributing to low inter-laboratory consistency and inaccurate interpretation. While pre-processing guidelines have been recently released ( 37 ) supporting reproducibility and facilitating comparisons, analytical and post-analytical issues remain less standardized ( 38 – 40 ). Proof-of-concept studies have demonstrated that selection of appropriate extraction kits may severely influence RNA yields, particularly with liquid biopsy samples ( 40 – 42 ). Also, kits used for the RT may have an impact on measured miRNA expression levels ( 43 ). Others have advocated that technologies like traditional RT-qPCR are not well suited for clinical routine, due to either the higher sensitivity or target multiplexing needed for cancer profiling ( 41 ). Indeed, clinical scenarios such as early detection or anticipation of disease progression often demand multiple miRNAs analyses to achieve sufficient sensitivity and specificity. This typically results in running parallel reactions for each specific target, increasing complexity and limiting scalability. Moreover, when input quantities are limited, samples cannot be split across multiple reactions, resulting in missed information and the inability to produce meaningful biological insights. At the same time, single biomarker assessment may reduce the overall throughput, increase the turnaround time, and introduce run-to-run variability, all factors that collectively compromise the reliability of the results. Recently, the introduction of 2nd -gen dPCR has offered solutions to several of these issues, providing higher sensitivity, better signal-to-noise ratios, reduced inhibitor susceptibility, and compatibility with small sample volumes ( 25 , 28 , 44 – 46 ). Nevertheless, dPCR is not routinely used for miRNA analysis and its multiplexing capabilities, critical for oncology applications, are still limited with only a few reports of multiplex assays to date ( 47 – 50 ). We present miRquad, the first-in-class dPCR TaqMan™ Advanced clinical research assay for multiplex miRNA detection in HNCs. The prognostic impact of miR-21-5p, miR-96-5p, miR-21-3p and miR-429 as a signature in predicting local recurrence, a frequent and often unexpected problem of HNCs, has been previously demonstrated and patented by our group ( 29 – 31 ). Herein, we aimed at highlighting the advantages of simultaneous multiplex miRNA analysis (i.e., from the same input and at the same time) over conventional, one-by-one, investigations for clinical application, providing rationale for assay translation and paving the way for future developments of miRNA diagnostics using dPCR. To this goal, successive rounds of testing and optimization of miRquad design, first as singleplexes and later in multiplex format, were extensively conducted using single or multiple miRNA spike-ins to minimize potential interference promoted by the complexity of human matrices, both solid (tissues) or liquid (serum, saliva). According to a previous report discussing the importance, in a clinical context, of selecting miRNAs expressed at a sufficient level to be reliably detected (⁓100 cp/µL) ( 49 ), we showed that, in these conditions, our custom assays specifically amplify all synthetic targets, reflecting the performance of commercially available TaqMan™ RUO assays. A negligible-to-zero background for all miRNAs, linear performances as demonstrated by the correlation coefficients over a wide dynamic range, and limits of detection comparable to state-of-art methodologies or previously published targeted assays employing similar designs ( 49 , 51 – 53 ) were observed. Although side-by-side comparison portrayed a global reduction of the fluorescence intensity when individual assays were combined in a multiplex assay, a predictable and addressable issue deserving further optimization or fluorophore switch, miRquad performance were not impaired. These results clearly demonstrated that fluorophore multiplexing is a feasible approach also for dPCR-based miRNA analysis. Besides, all tested combinatorial strategies, even those rejected for the final design, exhibited limited influence on assay sensitivity but pointed out the importance of collaborative development with global research partners to rigorously evaluate rational designs in detail (e.g., perform fine adjustments of primers/probes concentrations or introduce modification into the RT reaction, both covered by patented technologies). The additional benchmarking performed on patient-derived samples collected under real-world conditions, i.e. characterized by variability in pre-analytical handling and sample age, further reinforced the robustness of the assay, underscoring its potential to serve as a valuable molecular tool. Notably, miRquad testing was characterized by high reproducibility between independent dPCR runs and multiple RT reactions. Particularly, the ring study promoted within the INNOVA Consortium showed that different platforms (i.e., qPCR/dPCR instruments able to detect up to 4 different fluorophores) may easily accommodate miRquad with minimal variability, supporting its wide applicability. Moreover, laboratories with different expertise and throughputs were perfectly able to implement the assay in their routine without requiring specialized training. Translational feasibility of miRquad for the clinical management of HNC was also explored by assessing an independent cohort of FFPE samples, sera and saliva longitudinally collected from patients with different clinical outcome. In this context, miRquad approach emerged as a natural and effective solution for all types of biological specimens, offering improved performance (e.g., reduced turnaround time, costs, sample inputs, and minimizing handling steps) while recapitulating our previous findings ( 29 – 31 ), with HNC with unfavorable prognosis exhibiting increased levels of the targeted miRNAs, readily detectable at 15 days post-surgery, as compared to those with better outcomes. Besides the confirmatory results, miRquad enabled longitudinal assessment of circulating miRNAs across multiple timepoints, one of the most common practices in precision medicine, highlighting a superior sensitivity and specificity when applied into dPCR in detecting low-abundance analytes and their fluctuation over time. Although alternative approaches have been described ( 54 – 56 ), to the best of our knowledge, this is the first report presenting a TaqMan™ Advanced multiplex assay for miRNA detection in HNCs with prognostic value. Despite promising technical qualities and potential for accurate miRNA quantification, our work has a few limitations. Firstly, the real clinical impact of the assay could not be thoroughly evaluated due to the relatively small size of the sample cohort. While this was beyond the scope of the present study, integrating miRquad into clinical practice will likely require validation in larger, prospective cohorts to fully establish its translational impact. Secondly, the limited number of miRNAs analyzed per sample precludes the possibility to apply normalization strategies based on the global mean, which are considered the most accurate for microRNA data analysis ( 20 , 57 ). Nevertheless, our assay was designed to be expandable, accommodating additional miRNAs or spike-in controls, such as cel-39-3p or cel-54-3p, which would grant improved quantification and provide more controlled measurements, especially for liquid biopsy samples. Finally, we had chances to test only a model of dPCR and a selection of qPCR instruments, while broader comparative studies across a variety of dPCR platforms would be more beneficial for establishing robustness and versatility. CONCLUSION Herein, we have presented miRquad, the first-in-class dPCR TaqMan™ Advanced clinical research assay for multiplex miRNA detection in HNCs. Developed on a patented prognostic signature capable of predicting the risk for local recurrence ( 29 – 31 ), this assay overcomes most of the common limitations encountered when multiple miRNAs are under investigation, particularly in liquid biopsy samples. By enabling robust and accurate detection, miRquad demonstrates potential for real-time monitoring and patient prognostication in HNC through dPCR-based miRNA analysis. Furthermore, our work lays the groundwork for future efforts aimed at enhancing the clinical applicability and attractiveness of circulating miRNAs for routine diagnostic use. Abbreviations ceRNA competing endogenous RNA dPCR digital PCR FFPE Formalin-fixed paraffin-embedded HNC head and neck miRNAs microRNAs RT-qPCR reverse transcription quantitative PCR Declarations Ethics approval and consent to participate FFPE samples including matched tumors and peritumoral area were obtained from Policlinico of Milan (EC authorization #105/IRE/24). Additional tumor specimens, sera and saliva were also collected from the IRCCS Regina Elena National Cancer Institute biobank (EC authorization #RS868/16). A written informed consent was collected from all human subjects involved in this study. Consent for publication Not applicable Availability of data and materials Raw data and related analyses supporting paper findings are available upon reasonable request to the corresponding author (GB). Competiting interests MA, GU, VDP, FG, RP, GB, SF, SF, TM, CC, EDG, AB, LS, RM, MU, EA, SDS, AA, SG, AP, GC and GB declare no potential conflicts of interest with the present work. DJJ and JFS are employees of Thermo Fisher Scientific™. miRquad assay content is based on a previously patented set of miRNA targets registered by GB, FG, and RP (#102020000019024). Fundings This work received support from the Italian Ministry of Health (PNC E3-2022-23683266, PNRR-POC-2022–12376580), Associazione Italiana per la Ricerca sul Cancro (AIRC, IG 29040), and in-kind support from Thermo Fisher Scientific™. Authors’ contributions MA supervised miRNAs extraction from synthetic and patient-derived material, designed and performed qPCR/dPCR experiments, analysed molecular data, and wrote the paper; DJJ designed miRquad assay, performed preliminary assessment, analysed molecular data, and revised the paper; GU performed dPCR experiments on patient sera and saliva; VDP extracted miRNAs from tissues, sera and saliva; FG collected and processed patient samples; RP recruited HNC patients and elaborated clinical data; GB, SF and SF recruited patient and collected tissue samples included in the validation cohort; TM, CC, EDG, AB, LS, MR, MU, EA, SDS, AA, SG, AP performed qPCR/dPCR experiments for the ring study; GC provided fundings for WP4 activities; JFS coordinated miRquad design, supervised benchmarking activities, and critically revised the paper; BG designed and supervised the study, provided fundings, and critically revised the paper. All authors read and approved the final manuscript. Acknowledgements Drs. Gianluca Fascioli and Francesco Lulli from Thermo Fisher Scientific™ are kindly acknowledge for their extraordinary support in bridging together administrative, economic and scientific parts below the present study. References Vasan N, Baselga J, Hyman DM. A view on drug resistance in cancer. Nature. 2019;575(7782):299–309. França GS, Baron M, King BR, Bossowski JP, Bjornberg A, Pour M, et al. Cellular adaptation to cancer therapy along a resistance continuum. Nature. 2024;631(8022):876–83. Marine JC, Dawson SJ, Dawson MA. Non-genetic mechanisms of therapeutic resistance in cancer. Nat Rev Cancer. 2020;20(12):743–56. Lu J, Getz G, Miska EA, Alvarez-Saavedra E, Lamb J, Peck D, et al. MicroRNA expression profiles classify human cancers. Nature. 2005;435(7043):834–8. Macfarlane LA, Murphy PR. MicroRNA: Biogenesis, Function and Role in Cancer. Curr Genom. 2010;11(7):537–61. Vishnoi A, Rani S. miRNA Biogenesis and Regulation of Diseases: An Updated Overview. 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Laprovitera N, Riefolo M, Porcellini E, Durante G, Garajova I, Vasuri F, et al. MicroRNA expression profiling with a droplet digital PCR assay enables molecular diagnosis and prognosis of cancers of unknown primary. Mol Oncol. 2021;15(10):2732–51. Wu C, Tong L, Wu C, Chen D, Chen J, Li Q, et al. Two miRNA prognostic signatures of head and neck squamous cell carcinoma: A bioinformatic analysis based on the TCGA dataset. Cancer Med. 2020;9(8):2631–42. Krsek A, Baticic L, Sotosek V, Braut T. The Role of Biomarkers in HPV-Positive Head and Neck Squamous Cell Carcinoma. Towards Precision Med. 2024;14(13):1448. Schwarzenbach H, da Silva AM, Calin G, Pantel K. Data Normalization Strategies for MicroRNA Quantification. Clin Chem. 2015;61(11):1333–42. Additional Declarations Competing interest reported. MA, GU, VDP, FG, RP, GB, SF, SF, TM, CC, EDG, AB, LS, RM, MU, EA, SDS, AA, SG, AP, GC and GB declare no potential conflicts of interest with the present work. DJJ and JFS are employees of Thermo Fisher Scientific™. miRquad assay content is based on a previously patented set of miRNA targets registered by GB, FG, and RP (#102020000019024). Supplementary Files SupplFig1.tif SUPPLEMENTARY FIGURES Suppl. Fig. 1. Footprint of Centers participating in the ring study. Centers and platform availability (qPCR or dPCR) involved into the ring study are indicated. SupplTab1.tif Suppl. Tab. 1. miRNA sequences used for custom BLOCK-IT™ RNAs design. SupplTab2.tif Suppl. Tab. 2. miRNA expression levels by commercial assays and the miRquad. Copies/µl for each miRNA target as detected by dPCR and commercial assays (indicated as cmiR) or the miRquad in (a) tissues and (b) sera samples. 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15:27:41","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":345935,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/87dd28c074d157917230d0ed.png"},{"id":92274863,"identity":"7cf1e579-f1a4-4567-b00f-89982266bc88","added_by":"auto","created_at":"2025-09-26 15:27:42","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":247469,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/9b0a8985e327d252df657110.png"},{"id":92274871,"identity":"50129a43-55b0-47ee-9493-b07c1bbcc6ed","added_by":"auto","created_at":"2025-09-26 15:27:43","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":349416,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig3.png","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/b43c127dc2d086e89cf7fe71.png"},{"id":92274792,"identity":"efff52af-83ce-4ec9-b26d-2979946f19e7","added_by":"auto","created_at":"2025-09-26 15:27:39","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":607632,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig4.png","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/68239179dab036f981a9d7b0.png"},{"id":92274786,"identity":"0a51cb58-3364-4b4b-b289-ab83fe3b62b4","added_by":"auto","created_at":"2025-09-26 15:27:38","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":658545,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig5.png","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/cbb5af60d2dea0f7653a71e8.png"},{"id":92274790,"identity":"26b72bdc-772c-43b3-811e-00ee1dd1e4ae","added_by":"auto","created_at":"2025-09-26 15:27:39","extension":"xml","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":135833,"visible":true,"origin":"","legend":"","description":"","filename":"4b7d2402b89a453ea375be499ce9ca1f1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/4e3842abccadaaa7cda43ee5.xml"},{"id":92274832,"identity":"7d358e1e-b671-4c46-8cdd-39f4feadfffe","added_by":"auto","created_at":"2025-09-26 15:27:40","extension":"html","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":143507,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/c3c8575931f6584e725ae7c3.html"},{"id":92274911,"identity":"8412f1ac-c14b-4c3e-aabf-bec4dd4ae62a","added_by":"auto","created_at":"2025-09-26 15:27:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":11143221,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePreliminary analysis of custom assays performances as singleplex.\u003c/strong\u003e Single spike-ins containing a discrete concentration (⁓100 copies/µL) of each miRNA of interest were used to preliminarily assess amplification, specificity and selectivity of the corresponding custom TaqMan™ Advanced research assay. (a) 2D plots describing the resulting signals obtained from each singleplex, in duplicates, when tested in dPCR. None to negligible spillovers were detected in surrounding channels (indicated). (b) Dilution series of single spike-ins containing scalar concentrations of each BLOCK-iT™ RNA mimicking the miRNA of interest (miR-21-5p, blue; miR-96-5p, green; miR-21-3p, yellow; miR-429, red) were generated and further tested in qPCR using commercial TaqMan™ Advanced assays to evaluate the presence of each target over a wide dynamic range. (c-d) Side-by-side comparison of miRNA expression in selected single spike-ins by either commercial assays (left) or custom singleplexes (right). Detection channels are color-coded. Resulting signals appear equivalent in terms of copies/µl of reaction, demonstrating robustness in amplification and quantification of the molecular targets.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/12fe4a8a7731005645fac020.png"},{"id":92274927,"identity":"c40a9f47-95e1-4b09-98a0-16479c233caf","added_by":"auto","created_at":"2025-09-26 15:27:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":7291782,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003edPCR analysis of miRquad as compared to custom singleplexes on synthetic spike-ins. \u003c/strong\u003eSingle spike-ins containing scalar concentration for each miRNA of interest, previously analysed by qPCR, were used as input to assess the detection capabilities of miRquad. (a) Representative 2D plots depicting miRNA analysis carried out by using either the custom TaqMan™ Advanced research assays as singleplex (left) or the miRquad (right). (b) Absolute quantification of copies/µl of reaction resulting from side-by-side comparison of custom TaqMan™ advanced (left) and miRquad (right) with respect to each miRNA. Detection channel are color-coded. (c) miRquad dPCR testing on the multiplex spike-in, including each single miRNA of interest at decreasing scalar concentrations. (d) Side-by-side comparison of commercial TaqMan™ assays (left) and the miRquad (right) in the multiplex spike-in. Absolute quantification of copies/µl of reaction with respect to each miRNA is shown and color-coded.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/efba1965cbb06a208bce7ebd.png"},{"id":92277062,"identity":"2b32866d-6ad8-4cec-946b-b205ca8495c9","added_by":"auto","created_at":"2025-09-26 15:35:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":7450189,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvaluation of miRquad performances on clinical specimens. \u003c/strong\u003eDifferent biological matrices, including FFPE tissues (n=24) and sera (n=18), belonging to HNC patients retrospectively collected at IRE were simultaneously assessed by commercial assays and the miRquad in dPCR. (a-b) Analytical comparison of miRNA expression levels in tissue (a) and sera (b) as detected by commercial assays (blue bars) or miRquad (red bars). Copies/µl of reaction are indicated. (c-d) Linear regression analyses for each specific miRNA of interest in tissue (c) or sera (d). R and \u003cem\u003ep\u003c/em\u003e values are shown.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/4cf8fecb2cbf28dbddf88902.png"},{"id":92274860,"identity":"70974aad-b6f4-4831-b4b0-fec0fa5cf010","added_by":"auto","created_at":"2025-09-26 15:27:42","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":19372302,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExtended analysis of miRquad across different Italian cancer Centers. \u003c/strong\u003eA ring study involving 6 Italian Institutes belonging to the INNOVA Consortium and the WP4 – Liquid Biopsy group was executed to benchmark miRquad robustness on different qPCR/dPCR platforms and in the context of variable technical expertise. (a-b) Analysis of miRNA expression levels detected by commercial assays (left) or the miRquad (right) in single and multiplex spike-in products by qPCR (a) or dPCR (b). Values obtained in each specific Center are indicated by color-coded dots. (c) Representative 2D plots showing miRNA abundance in patient-derived materials included into the ring study as analyzed at IRE by dPCR. (d) Multicenter comparison of miRNA expression levels in tissues and liquid biopsies by dPCR. Copies/µl of reaction are shown (tissue: left axis; sera and saliva: right axis). NTC: no template control (nuclease-free water).\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/a9c14f32042555709bae8431.png"},{"id":92274926,"identity":"7ad229f5-e060-4b75-b168-c92477df0a06","added_by":"auto","created_at":"2025-09-26 15:27:45","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":15453751,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eValidation of miRquad on independent cohorts of patient-derived samples. \u003c/strong\u003eTranslational potential of miRquad for HNCs was investigated by qPCR and dPCR on a cohort of independent FFPE samples (n=60), sera (n=48) and saliva (n=16). (a) Linear regression analyses of mean Ct values obtained by commercial assays or the miRquad in tissue samples for each specific miRNA. R and \u003cem\u003ep\u003c/em\u003e values are shown. (b) Representative 1D plots of miR-429 expression (Cy5 fluorescence) in low-abundance FFPEs analyzed by miRquad in dPCR. Samples previously missed by qPCR or showing discrepancies between standard (i.e., with commercial assays) and miRquad-based analyses are indicated by the arrows. (c) miRNA expression assessed by dPCR and the miRquad assay in tumor tissues and matched peritumoral area as related to the clinical outcome. (d) Longitudinal evaluation of circulating (sera) miRNA levels in patients with good (left panels) and poor outcome (right panels). Representative 2D plots are shown. T\u003csub\u003e0\u003c/sub\u003e: before surgery; T\u003csub\u003e+1\u003c/sub\u003e: 1 day after surgery; T\u003csub\u003e+15\u003c/sub\u003e: 15 days after surgery. (e) miRNA expression levels, as quantified by dPCR and the miRquad assay, in sera samples of good and poor responders at baseline (T\u003csub\u003e0\u003c/sub\u003e) and 15 days after surgery (T\u003csub\u003e+15\u003c/sub\u003e). (f) Heatmap summarizing signature modulations occurring in good (up) and poor (down) outcome patients in the immediate post-surgery follow up. Values are expressed as percentages of mean changes \u003cem\u003evs\u003c/em\u003e baseline. (g) Representative 2D plots of miRNA expression in saliva samples of good (left) and poor (right) outcome patients obtained at baseline (T\u003csub\u003e0\u003c/sub\u003e) and before relapse (T\u003csub\u003erec\u003c/sub\u003e). (h) Comparative analysis of miRNA expression levels in saliva samples of good (left) and poor (right) outcome patients. * p = 0.05; ** p \u0026lt; 0.01; *** p \u0026lt; 0.001. NTC: no template control (nuclease-free water).\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/bfaeb79b93d106e8a760b4f3.png"},{"id":98813999,"identity":"92833d0f-d11c-47a7-bf0b-d67aa8eb6937","added_by":"auto","created_at":"2025-12-22 16:09:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":99479026,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/3df295a9-6e4f-440d-8fee-911089f67c0d.pdf"},{"id":92274845,"identity":"fbb97145-e967-459e-9018-f3d6c0eebcde","added_by":"auto","created_at":"2025-09-26 15:27:41","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":806608,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSUPPLEMENTARY FIGURES\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSuppl. Fig. 1. Footprint of Centers participating in the ring study. \u003c/strong\u003eCenters and platform availability (qPCR or dPCR) involved into the ring study are indicated.\u003c/p\u003e","description":"","filename":"SupplFig1.tif","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/054f18c0c7107dd68b1ce435.tif"},{"id":92274773,"identity":"dc346a4a-7876-4381-a4ad-ba5ca8c8a89c","added_by":"auto","created_at":"2025-09-26 15:27:37","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":389344,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSuppl. Tab. 1. miRNA sequences used for custom BLOCK-IT™ RNAs design.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplTab1.tif","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/d506563e5685d8248f2d520f.tif"},{"id":92274736,"identity":"67d78daf-6bad-41d1-883e-a80ee15e6f69","added_by":"auto","created_at":"2025-09-26 15:27:36","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":3361776,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSuppl. Tab. 2. miRNA expression levels by commercial assays and the miRquad. \u003c/strong\u003eCopies/µl for each miRNA target as detected by dPCR and commercial assays (indicated as cmiR) or the miRquad in (a) tissues and (b) sera samples.\u003c/p\u003e","description":"","filename":"SupplTab2.tif","url":"https://assets-eu.researchsquare.com/files/rs-7623968/v1/02d6303efed94439555112a2.tif"}],"financialInterests":"Competing interest reported. MA, GU, VDP, FG, RP, GB, SF, SF, TM, CC, EDG, AB, LS, RM, MU, EA, SDS, AA, SG, AP, GC and GB declare no potential conflicts of interest with the present work. DJJ and JFS are employees of Thermo Fisher Scientific™. miRquad assay content is based on a previously patented set of miRNA targets registered by GB, FG, and RP (#102020000019024).","formattedTitle":"miRquad: first-in-class dPCR multiplex TaqMan™ Advanced RUO assay for microRNA detection in head and neck cancer","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eDespite remarkable therapeutic achievements, cancer resistance remains a key hurdle in oncology, often causing poor drug responses, disease relapse and, ultimately, patient death (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Tumors escape treatment pressure through multiple mechanisms including genetic alterations, rewired signaling pathways, or the adaptation to both immune system and the surrounding microenvironment (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Recently, the long-standing view of sequential genetic evolution as the driving force of resistance has been questioned shedding lights on other, non-genetic, adaptive mechanisms (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Although our understanding has considerably expanded over the years, tools to anticipate tumor evolution or predict therapy failure remain limited, leaving cancer resistance a pressing challenge in the era of precision medicine. Addressing this limitation is of utmost importance to achieve durable and more effective patient responses.\u003c/p\u003e\u003cp\u003eMicroRNAs (miRNAs) are a class of single-stranded, small non-coding RNA molecules that post-transcriptionally modulate gene expression (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Due to their pivotal role in various physiological and pathological processes, including cancer, miRNAs have attracted increasing attention as diagnostic and prognostic biomarkers, being also investigated for therapeutic purposes both in tissues and liquid biopsies (e.g., circulating miRNAs) (\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Moreover, their function as key determinants of cancer resistance and drug metabolism has been elucidated (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). For example, overexpression of miR-21 can promote tumorigenesis and therapy resistance by targeting tumor suppressor genes and signalling pathways (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Similarly, miR-34a modulates DNA repair mechanisms, influencing the sensitivity of cancer cells to chemotherapy (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), while miR-506 acts as a crucial regulator within the competing endogenous RNA (ceRNA) network, affecting cancer cell proliferation and migration (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Understanding these miRNA-mediated mechanisms is essential for developing strategies to overcome drug resistance in cancer therapy. However, intrinsic features such as their size, variable abundance in body fluids, sequence homology within different families combined with technical hurdles (e.g., inconsistencies across extraction methods, multiplexing requirements, lack of standardized strategies for normalization of target expression) still pose challenges for miRNA identification and clinical exploitation, limiting their stable implementation as cancer biomarkers (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSo far, numerous approaches to evaluate miRNA expression levels, alone or as components of broader signatures, have been proposed (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Among them, reverse transcription quantitative PCR (RT-qPCR) is widely recognized as the gold standard, showing enough sensitivity, specificity and a broad dynamic range while performing at relatively low costs in different settings (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). However, the investigation of single deregulated miRNAs, typical of standard RT-qPCR workflows, is often inadequate for cancer profiling, which requires quantitative and multiplex analyses (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). RT-qPCR also faces limitations when applied to challenging sample types, like those characterized by a limited number of analytes (e.g., liquid biopsies) or by the presence of polymerase inhibitors. Additionally, screening large collections of samples looking for even moderate numbers of targets is prohibitive with qRT-PCR and singleplex assays, requiring multiple individual reactions per biomarker. This, in turn, may result in an error-prone and inefficient process due to sample splitting and wasting (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Over the years, alternative methods as microarray or NGS sequencing have been introduced providing larger amounts of data but in a relatively slow and expensive fashion (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Drawbacks have emerged also for other techniques as rolling circle amplification, duplex-specific nuclease signal amplification, isothermal amplification, all demanding for reaction optimization, improvements in signal readouts, reproducibility and accuracy (\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Besides, the introduction and constant update of novel digital PCR (dPCR) systems, either in droplet or array-based format, are expanding the possibilities for accurate miRNAs profiling, particularly in liquid biopsy applications, paving the way for transforming these analytes in powerful, non-invasive tools for cancer detection and monitoring (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). dPCR offers absolute quantification of targets by partitioning reactions into thousands of droplets or wells and applying Poisson statistics (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). This approach eliminates the need for external calibrators or normalization controls, enhances analytical sensitivity, and reduces hands-on time compared to conventional methods. Moreover, advanced platforms support multiplexing as compared to 1st -gen dPCRs (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) enabling cancer-related miRNA signatures to be explored with reduced workload and at sustainable costs. Nonetheless, challenges related to probe cross-reactivity and assay design may arise, requiring efforts before introducing multiplexed miRNA-based liquid biopsy analyses in clinical practice.\u003c/p\u003e\u003cp\u003eHere, we present miRquad, the first-in-class dPCR TaqMan\u0026trade; Advanced clinical research assay for multiplex miRNA detection in head and neck (HNC) cancers. Based on our previous works demonstrating the prognostic value of miR-21-5p, miR-96-5p, miR-21-3p and miR-429 signature in predicting HNC local recurrence (\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), we designed and validated a custom research assay relying on TaqMan\u0026trade; Advanced chemistry, benchmarking its performance on different cohort of clinical samples (e.g., FFPEs, sera and saliva) and lab settings (i.e., through a dedicated ring study). Our efforts result in reproducible, accurate, and affordable quantification of target miRNAs, comparable to that of TaqMan\u0026trade; commercial single research assays, but with significant advantages over conventional investigation in terms of multiplexing capacity, efficiency, and scalability. Overall, these findings support the potential translation of miRquad into routine clinical practice for the management and monitoring of HNC.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eCustom miRNA mimics and spike-ins development\u003c/h2\u003e\u003cp\u003eTo mimic the presence of target miRNAs in solution and dispose of soluble \u0026lsquo;standards\u0026rsquo; for a flexible investigation, both in terms of concentration (relative abundance) and analytical composition (numbers of miRNAs simultaneously present), without facing with the biological complexity of clinical samples, 4 different custom BLOCK-IT\u0026trade; RNA (Thermo Fisher Scientific\u0026trade;, Carlsbad, CA, USA) oligonucleotides were designed using the online tool BLOCK-iT\u0026trade; RNAi Designer (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://rnaidesigner.thermofisher.com/rnaiexpress\u003c/span\u003e\u003cspan address=\"https://rnaidesigner.thermofisher.com/rnaiexpress\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, Thermo Fisher Scientific\u0026trade;) based on the reported sequences in the miRBase database (release 22, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mirbase.org\u003c/span\u003e\u003cspan address=\"https://www.mirbase.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Supplementary Table\u0026nbsp;1). These products were chemically modified at 5\u0026rsquo; with the addition of a phosphate group, and at 3\u0026rsquo; to show protruding ends. Both modifications were necessary to allow reverse transcription as for endogenous miRNAs. Custom BLOCK-IT\u0026trade; RNAs were resuspended in nuclease-free water at a fixed concentration (100 \u0026micro;M) and subsequently diluted at scalar doses (dilution factor 1:10) to generate (a) different single spike-ins hosting known concentrations of a single miRNA of interest and (b) a multiple spike-in that simultaneously included all 4 different miRNAs at 4 different concentrations, which were chosen based on our previous studies (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Synthetic spike-ins were then stored at -80\u0026deg;C until RNA extraction.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eBiological materials\u003c/h3\u003e\n\u003cp\u003eFormalin-fixed paraffin-embedded tissue samples (FFPE, n\u0026thinsp;=\u0026thinsp;60), including matched tumors and peritumoral area, were obtained from Policlinico of Milan based on an ongoing collaboration within a national grant (PNRR-POC-2022-12376580, EC authorization #105/IRE/24) and used as a validation cohort. Additional FFPE samples (n\u0026thinsp;=\u0026thinsp;24), belonging to HNCs with different clinical outcome, were obtained from the Regina Elena National Cancer Institute biobank (BB-IRE) and applied for the preliminary benchmark of miRquad and the ring study (see below). FFPE sections (5 \u0026micro;m) were initially assessed with immunohistochemistry for tumor content by a dedicated pathologist and further used for nucleic acid extraction as described below. Serial liquid biopsy samples including sera (n\u0026thinsp;=\u0026thinsp;48) and saliva (n\u0026thinsp;=\u0026thinsp;16), collected at specific time intervals (i.e., pre-surgery, 1 day post-surgery, 15 days post-surgery, and at follow-up visits), were retrospectively obtained from the BB-IRE. These were part of a prospective study underway at IRE (EC authorization #RS868/16) which involves patients affected by HPV-negative, resectable HNC of the oral cavity, pharynx or larynx undergoing surgery with curative intent and chemo/radio-treatments or in follow-up as per clinical practice. Study cohort was selected based on the availability of the clinical outcome (i.e., patients with favourable or unfavourable prognosis) and a minimum follow-up of 36 months. A written informed consent was collected from all subjects involved in the study. With respect to sample nature, biological fluids have been subjected to single centrifugation at 3500 g for 20 minutes (sera) or at 2000 g for 10 minutes (cleared saliva), both at 4\u0026deg;C. The former were stored at -80\u0026deg;C while the latter were kept at room temperature by adding 10 ml of ThinPrep solution (Hologic BV, Zaventem, Belgium) to allow long-term stabilization.\u003c/p\u003e\n\u003ch3\u003emiRNAs extraction from synthetic and biological specimens\u003c/h3\u003e\n\u003cp\u003eExtraction of total RNAs, including miRNAs of interest, from synthetic materials, tissues and liquid biopsies was carried out by the MagMAX\u0026trade; mirVana\u0026trade; Total RNA isolation kit and the KingFisher\u0026trade; Apex purification system (both from Thermo Fisher Scientific\u0026trade;), according to the manufacturer instructions, in a final volume of 50 \u0026micro;l (tissues) or 30 \u0026micro;l (spike-ins, liquid biopsies), respectively. Ten nanograms of Qubit\u0026trade; BR (Thermo Fisher Scientific\u0026trade;) quantified RNAs from tissues or 2 \u0026micro;l of eluate from liquid biopsies were then reverse transcribed using the TaqMan\u0026trade; Advanced miRNA cDNA synthesis kit (Thermo Fisher Scientific\u0026trade;), as per protocol. This supports optimal conversion of all miRNAs in the corresponding cDNA, avoiding the need for specific oligonucleotides and targeted amplification, thus providing a single product including all targets at the original ratios. Resulting cDNAs were stored at -20\u0026deg;C until downstream amplification by qPCR or dPCR.\u003c/p\u003e\n\u003ch3\u003eqPCR and dPCR analyses\u003c/h3\u003e\n\u003cp\u003eAnalysis of miRNA expression (i.e., miR-21-5p, miR-96-5p, miR-21-3p and miR-429) was carried out by using either commercially available singleplex TaqMan\u0026trade; Advanced research assays, single custom assays (those composing the miRquad) or the miRquad as a whole on the QuantStudio\u0026trade; 5 real-time PCR and QuantStudio\u0026trade; Absolute Q digital PCR systems (both from Thermo Fisher Scientific\u0026trade;). Experimental design aimed at providing (a) pre-validated commercial references, (b) evaluating the performance of the multiplex assay and (c) investigating any quantitative issue or fluorescence interference due to the simultaneous amplification and detection of different molecular targets into the same reaction. As for qPCR, reactions were setup in triplicates in a final volume of 20 \u0026micro;l containing 10 \u0026micro;l of 2x TaqMan\u0026trade; Advanced master mix, 1 \u0026micro;l of 20x TaqMan\u0026trade; research assays (both from Thermo Fisher Scientific\u0026trade;), 5 \u0026micro;l of a 1:10 diluted sample and nuclease-free water. Thermocycling conditions were as follows: 95\u0026deg;C for 20 seconds, 40 cycles at 95\u0026deg;C for 1 second and 60\u0026deg;C for 20 seconds. miRNAs levels, as assessed by commercial assays, were evaluated through automatic thresholding and the average Ct mean, and internally compared with those of custom assays, either in single or multiplex (miRquad) format. dPCR reactions were prepared in a final volume of 10 \u0026micro;l containing 2 \u0026micro;l of 5x Absolute Q\u0026trade; universal DNA master mix, 0.5 \u0026micro;l of 20x TaqMan\u0026trade; research assays (both from Thermo Fisher Scientific\u0026trade;), 5 \u0026micro;l of 1:10 diluted sample and nuclease-free water. Thermocycling protocol was as follows: 96\u0026deg;C for 10 minutes, 40 cycles at 96\u0026deg;C for 5 seconds and 60\u0026deg;C for 15 seconds. Automatic thresholding was applied by the software (QuantStudio\u0026trade; Absolute Q dPCR software, v. 6.3.5, Thermo Fisher Scientific\u0026trade;), manually reviewed by the operator to enhance discrimination between negative from positive dots, and miRNA levels expressed as copies/\u0026micro;l of reaction. dPCR results were compared across various assay conditions and correlated with qPCR data.\u003c/p\u003e\n\u003ch3\u003eINNOVA Consortium ring study\u003c/h3\u003e\n\u003cp\u003eTo extend the analytical evaluation of miRquad on different qPCR/dPCR platforms and clinical environments, the INNOVA Consortium, a multidisciplinary diagnostic network operating within the Italian NHS and translational research which promotes the development and dissemination of novel, standardized, advanced molecular tools, was considered. A ring study involving various (n\u0026thinsp;=\u0026thinsp;6) Italian Cancer Centres belonging to the WP4 \u0026ndash; Liquid Biopsy \u0026amp; Biomarkers group (Supplementary Fig.\u0026nbsp;1a) was designed and executed as follows: synthetic materials (e.g., single and multiple spike-ins) and representative FFPE, sera and saliva samples (n\u0026thinsp;=\u0026thinsp;7, 4 and 4, respectively) available at IRE, were extracted, reverse transcribed, splitted in single use aliquots and shipped to all participants; receiving lab personnel were invited to analyse them in a blinded manner according to their own laboratory practice, simultaneously applying both the commercial TaqMan\u0026trade; Advanced miRNA research assays, custom singleplexes composing the miRquad and the miRquad in the same qPCR or dPCR reaction (depending on instrument availability); raw data were analysed as per laboratory routine using on board software, afterwards sent to IRE for a more broader and cumulative evaluation.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analyses\u003c/h2\u003e\u003cp\u003eEvaluation of miRquad performance as compared to commercial assays was performed using Student\u0026rsquo;s t-test and linear regression. The non-parametric Mann-Whitney test was applied to investigate statistical significance of miRNA changes in patient-derived materials. Wilcoxon matched-pairs signed-rank test was applied for comparisons between paired measures. \u003cem\u003eP\u003c/em\u003e values ​​\u0026lt; 0.05 were considered statistically significant. All data were reported using GraphPAD\u0026reg; Prism v. 10.5 software application (GraphPAD\u0026reg; software, Dotmatics).\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eCustom TaqMan\u0026trade; Advanced singleplexes specifically amplify their targets mirroring the performance of commercial research assays\u003c/h2\u003e\u003cp\u003eThe formulation of a multiplex assay requires switching from FAM\u0026trade;-conjugated TaqMan\u0026trade; probes to other fluorescent molecules (e.g., VIC\u0026trade;, ABY\u0026trade; and Cy5\u0026trade;) to allow simultaneous discrimination of several miRNAs across different channels. To verify whether these modifications may affect the ability of each assay, as singleplex, to properly interact with its target and/or generate false positive spillover-dependent signals (i.e., non-specific signal in neighbouring fluorescence channels), preliminary experiments were performed in qPCR (data not shown) and dPCR using spike-ins containing a discrete concentration (⁓100 copies/\u0026micro;l) of each miRNA of interest as input (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Our results clearly showed the ability of all custom assays, with respect to their own fluorescence channel, to successfully amplify target sequences with elevated selectivity, as demonstrated by the nearly complete absence of spillover signals in the non-target fluorescence channels (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Next, since the different brightness of custom fluorophores as compared to FAM\u0026trade; may also affect instrument thresholding impairing the ability to properly discriminate positive/negative signals, we assessed whether our custom singleplexes incorrectly quantified the concentration of target miRNAs and if their detection was allowed within a dynamic range sufficiently wide to consider different biological sources. Initially, we generated series of single spike-ins by sequentially diluting each specific BLOCK-IT\u0026trade; RNAs at a fixed ratio (1:10) and tested them on qPCR by using commercial assays (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). A good intra- and inter-assay correlation in terms of scalar concentration was found. Based on the expected expression of each miRNA in clinical samples, specific dilutions from each spike-in series were selected as follows: miR-21-5p\u0026thinsp;\u0026gt;\u0026thinsp;miR-21-3p\u0026thinsp;\u0026gt;\u0026thinsp;miR-96-5p\u0026thinsp;\u0026gt;\u0026thinsp;miR-429. dPCR experiments were then performed investigating miRNA expression with commercial assays or by applying our custom singleplexes. The analysis of copies/\u0026micro;l ​​demonstrated a significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) concordance ​​between the two detection methods (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec-d). Furthermore, no lack of performance was noted with respect to the different concentrations of the BLOCK-IT\u0026trade; RNA used as input, demonstrating the high sensitivity of the custom products.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003emiRquad multiplex shows comparable performance to those of custom TaqMan\u0026trade; Advanced single research assays\u003c/h2\u003e\u003cp\u003eHaving demonstrated the ability of custom assays, as singleplexes, to mirror the behaviour of FAM\u0026trade;-conjugated counterparts, we moved to assess the performance of miRquad as a whole (i.e., in the multiplex format) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Firstly, a side-by-side comparison was carried out in dPCR on newly-generated single spike-ins by alternatively applying either individual custom assays or the miRquad, aiming at unveiling possible technical issues related to the simultaneous presence of multiple primers and probes in samples including only the target sequence (i.e., the specific miRNA of interest at relatively low abundance instead of a mixture of different miRNAs). We observed that, even in the multiplex configuration, our custom assays retained the ability to discriminate each target. More broader extensions of the positive clusters along the fluorescence axis and a global reduction in fluorescence intensity were noted in almost all of fluorescence channels (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea) and, consequently, adjustments of thresholds to ensure correct targets quantification were applied. This effect, partly expected, was supposed to result from the interactions between various primers, their relative concentrations, and multi-probe interferences in the assay. Nevertheless, it did not preclude the use of miRquad nor an accurate quantitation of miRNAs even in the range of low copies/\u0026micro;l (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). To better investigate whether the fluorescence smear was dependent to the formulation of miRquad itself and could increase in samples simultaneously hosting, among different circulating analytes, multiple miRNAs at higher concentrations, becoming detrimental for an accurate quantification, a multiplex spike-in was generated. Different BLOCK-iT RNAs were spiked at decreasing scalar concentrations in nuclease-free water, total RNA extracted, reverse transcribed and cDNAs were used as input for dPCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec-d). Overall, our data demonstrated that, despite fluorescence smears in all other than FAM\u0026trade; channel, miRquad supports a consistent and absolute quantitation relative to each specific target of interest, also in the presence of multiple analytes, requiring only minimal adjustments of fluorescence thresholds.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003emiRquad is applicable on different biological matrices and grant reproducible results over different platforms and clinical contexts\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTo assess whether miRquad may serve as a valuable molecular tool, particularly in the context of HNC where we previously demonstrated a prognostic role of the signature to predict disease local recurrence (\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), different biological matrices (i.e., FFPE tissues and sera) were retrospectively collected from the BB-IRE and subjected to dPCR analysis with either the multiplex and commercial assays, the latter being used as a reference. This representative cohort was defined by selecting samples collected over a period of ⁓7 years (range: 3\u0026ndash;10 years ago) aiming at mimicking technical and biological variability which generally occurs in real-world clinical settings. Analytical comparisons of assay performances in FFPEs and sera are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-b and Suppl. Table\u0026nbsp;2, respectively. As shown, even where RNAs can be notoriously degraded due to sample processing or quantities of circulating miRNA are expected to be intrinsically variable, miRquad maintained the ability to properly identify each target of interest, as the validated commercial assays, showing a significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) correlation in terms of copies/\u0026micro;l of reaction across all different sources, for all miRNAs (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec-d). To corroborate preliminary findings, and technically benchmark assay performances on different qPCR/dPCR platforms and in contexts featured by variable technical expertise, evaluation of miRquad was extended by performing a ring study involving 6 Italian institutes belonging to the INNOVA Consortium (Supplementary Fig.\u0026nbsp;1). Briefly, cDNAs resulting from synthetic material (i.e., spike-ins, both as single or multiplex) and the above-cited biological specimens were shipped in ready-to-use aliquots, blinded to the final users who were asked to provide a final data report according to their laboratory practice. All the results were then collected by IRE, revised to exclude technical and biological issues, and subjected to comparative analysis. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the application of commercial assays or the miRquad for qPCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea) or dPCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb) analyses resulted in a minimal (mean qPCR CV\u0026thinsp;=\u0026thinsp;6.2%; mean dPCR CV\u0026thinsp;=\u0026thinsp;3.5%) variability in terms of mean Ct outputs or copies/\u0026micro;l of reaction, respectively, across the different Centers in both single and multiplex spike ins. Highest CVs were recorded on Cy5 fluorescence (i.e. the expression of miR429). This effect was partially expected due to the lower brightness of the fluorophore which renders signal quantification less efficient as compared to the other dyes. Then, representative patient-derived materials, either FFPEs or liquid biopsies (i.e., sera and saliva), were addressed in dPCR with miRquad (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). Again, no significant differences in miRNA expression levels were noted between different Centers (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee-f). Overall, no technical hurdles were recorded by running miRquad on qPCR/dPCR platforms provided by different vendors, thus supporting its applicability as a molecular tool for biological investigation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003emiRquad as a non-invasive tool for predicting local recurrence risk in HNC\u003c/h2\u003e\u003cp\u003eTranslational feasibility of miRquad for the clinical management of HNC cancers was finally explored by qPCR and dPCR on an independent cohort of FFPE samples (n\u0026thinsp;=\u0026thinsp;60), including matched tumoral and peritumoral tissues, additional HNC sera (n\u0026thinsp;=\u0026thinsp;48) and a selection of saliva (n\u0026thinsp;=\u0026thinsp;16). As previously observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea), also in these additional tissue specimens no significant differences in the expression levels of miR-21-5p, miR-96-5p and miR-21-3p were observed between the miRquad and commercial assays in qPCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Higher deviations were noted for miR-429 (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.4496) probably due to the relatively low expression (mean Ct\u0026thinsp;\u0026gt;\u0026thinsp;30) in these samples and the reduced brightness of Cy5. They were partially mitigated by manual thresholding but, as expected, they completely disappeared in dPCR, which offered a more reliable analysis of miRNA expression, rescuing also those samples originally missed/discordant by qPCR. An extended representation of dPCR analysis in low-abundance samples is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb. Notably, when samples were stratified according to sampling site (i.e., core or peritumoral area), miRquad-based analysis recapitulated our previous findings (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), with tumor tissues expressing higher levels of the miRNA signature as compared to the peritumoral area. No significant differences were noted between relapsing and not relapsing patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). As to liquid biopsies, performances of miRquad were confirmed also in these sera, where dynamic changes occurring during clinical follow-up were easily detected by dPCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed). Particularly, we demonstrated that HNC patients with unfavourable prognosis were characterized by an increase, easily detectable already 15 days after surgery, of the various miRNAs, particularly those belonging to the miR-21 family, while subjects showing a favourable outcome did not, except for miR-429 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee), whose upregulated levels may depend from the dual role as tumor suppressor/oncomiR (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). However, when signature changes were considered and compared to miRNA baseline levels, the two groups of patients were stratified with higher accuracy (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ef). Finally, since saliva is recognized as the most suitable source for conducting liquid biopsy analyses in HNC (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), selected samples collected at baseline and before relapse were tested with miRquad. Representative results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eg. Also in this context, miRquad-based detection resulted in a clear evaluation of each miRNA of interest, reinforcing the observation of higher signature expression in patients with poor prognosis as compared to those displaying good outcome (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eh), thus suggesting a potential use of miRquad for real-time monitoring and patient prognostication in HNC by miRNA analysis.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOver the last few years, growing evidence have highlighted miRNAs as promising tools in precision medicine, particularly in oncology. As master regulators of gene expression, miRNA offer several advantages: (a) broad expression enabling detection from different sources; (b) high stability in body fluids allowing non-invasive testing; (c) functionally links to key cellular processes underlying disease onset and evolution (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Furthermore, as components of broader, non-genetic, adaptive mechanisms, they have been recently recognized as critical contributors to cancer resistance and therapy failure (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Therefore, miRNAs appear as ideal surrogate biomarkers for early diagnosis, outcome prognostication, treatment monitoring or anticipation of disease progression (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Several clinical trials are currently underway to further validate their important clinical utility (clinicaltrials.gov).\u003c/p\u003e\u003cp\u003eAlthough promising, clinical translation of miRNAs, either as individual biomarkers or as part of multi-miRNA signatures, often face important technical and biological challenges (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Paramount among these are the limitations related to the extraction kits, detection methods and assay biases which frequently lead to an altered target representation, ultimately contributing to low inter-laboratory consistency and inaccurate interpretation. While pre-processing guidelines have been recently released (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) supporting reproducibility and facilitating comparisons, analytical and post-analytical issues remain less standardized (\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Proof-of-concept studies have demonstrated that selection of appropriate extraction kits may severely influence RNA yields, particularly with liquid biopsy samples (\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Also, kits used for the RT may have an impact on measured miRNA expression levels (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Others have advocated that technologies like traditional RT-qPCR are not well suited for clinical routine, due to either the higher sensitivity or target multiplexing needed for cancer profiling (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Indeed, clinical scenarios such as early detection or anticipation of disease progression often demand multiple miRNAs analyses to achieve sufficient sensitivity and specificity. This typically results in running parallel reactions for each specific target, increasing complexity and limiting scalability. Moreover, when input quantities are limited, samples cannot be split across multiple reactions, resulting in missed information and the inability to produce meaningful biological insights. At the same time, single biomarker assessment may reduce the overall throughput, increase the turnaround time, and introduce run-to-run variability, all factors that collectively compromise the reliability of the results. Recently, the introduction of 2nd -gen dPCR has offered solutions to several of these issues, providing higher sensitivity, better signal-to-noise ratios, reduced inhibitor susceptibility, and compatibility with small sample volumes (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Nevertheless, dPCR is not routinely used for miRNA analysis and its multiplexing capabilities, critical for oncology applications, are still limited with only a few reports of multiplex assays to date (\u003cspan additionalcitationids=\"CR48 CR49\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWe present miRquad, the first-in-class dPCR TaqMan\u0026trade; Advanced clinical research assay for multiplex miRNA detection in HNCs. The prognostic impact of miR-21-5p, miR-96-5p, miR-21-3p and miR-429 as a signature in predicting local recurrence, a frequent and often unexpected problem of HNCs, has been previously demonstrated and patented by our group (\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Herein, we aimed at highlighting the advantages of simultaneous multiplex miRNA analysis (i.e., from the same input and at the same time) over conventional, one-by-one, investigations for clinical application, providing rationale for assay translation and paving the way for future developments of miRNA diagnostics using dPCR. To this goal, successive rounds of testing and optimization of miRquad design, first as singleplexes and later in multiplex format, were extensively conducted using single or multiple miRNA spike-ins to minimize potential interference promoted by the complexity of human matrices, both solid (tissues) or liquid (serum, saliva). According to a previous report discussing the importance, in a clinical context, of selecting miRNAs expressed at a sufficient level to be reliably detected (⁓100 cp/\u0026micro;L) (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e), we showed that, in these conditions, our custom assays specifically amplify all synthetic targets, reflecting the performance of commercially available TaqMan\u0026trade; RUO assays. A negligible-to-zero background for all miRNAs, linear performances as demonstrated by the correlation coefficients over a wide dynamic range, and limits of detection comparable to state-of-art methodologies or previously published targeted assays employing similar designs (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan additionalcitationids=\"CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e) were observed. Although side-by-side comparison portrayed a global reduction of the fluorescence intensity when individual assays were combined in a multiplex assay, a predictable and addressable issue deserving further optimization or fluorophore switch, miRquad performance were not impaired. These results clearly demonstrated that fluorophore multiplexing is a feasible approach also for dPCR-based miRNA analysis. Besides, all tested combinatorial strategies, even those rejected for the final design, exhibited limited influence on assay sensitivity but pointed out the importance of collaborative development with global research partners to rigorously evaluate rational designs in detail (e.g., perform fine adjustments of primers/probes concentrations or introduce modification into the RT reaction, both covered by patented technologies). The additional benchmarking performed on patient-derived samples collected under real-world conditions, i.e. characterized by variability in pre-analytical handling and sample age, further reinforced the robustness of the assay, underscoring its potential to serve as a valuable molecular tool. Notably, miRquad testing was characterized by high reproducibility between independent dPCR runs and multiple RT reactions. Particularly, the ring study promoted within the INNOVA Consortium showed that different platforms (i.e., qPCR/dPCR instruments able to detect up to 4 different fluorophores) may easily accommodate miRquad with minimal variability, supporting its wide applicability. Moreover, laboratories with different expertise and throughputs were perfectly able to implement the assay in their routine without requiring specialized training. Translational feasibility of miRquad for the clinical management of HNC was also explored by assessing an independent cohort of FFPE samples, sera and saliva longitudinally collected from patients with different clinical outcome. In this context, miRquad approach emerged as a natural and effective solution for all types of biological specimens, offering improved performance (e.g., reduced turnaround time, costs, sample inputs, and minimizing handling steps) while recapitulating our previous findings (\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), with HNC with unfavorable prognosis exhibiting increased levels of the targeted miRNAs, readily detectable at 15 days post-surgery, as compared to those with better outcomes. Besides the confirmatory results, miRquad enabled longitudinal assessment of circulating miRNAs across multiple timepoints, one of the most common practices in precision medicine, highlighting a superior sensitivity and specificity when applied into dPCR in detecting low-abundance analytes and their fluctuation over time. Although alternative approaches have been described (\u003cspan additionalcitationids=\"CR55\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e), to the best of our knowledge, this is the first report presenting a TaqMan\u0026trade; Advanced multiplex assay for miRNA detection in HNCs with prognostic value.\u003c/p\u003e\u003cp\u003eDespite promising technical qualities and potential for accurate miRNA quantification, our work has a few limitations. Firstly, the real clinical impact of the assay could not be thoroughly evaluated due to the relatively small size of the sample cohort. While this was beyond the scope of the present study, integrating miRquad into clinical practice will likely require validation in larger, prospective cohorts to fully establish its translational impact. Secondly, the limited number of miRNAs analyzed per sample precludes the possibility to apply normalization strategies based on the global mean, which are considered the most accurate for microRNA data analysis (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Nevertheless, our assay was designed to be expandable, accommodating additional miRNAs or spike-in controls, such as cel-39-3p or cel-54-3p, which would grant improved quantification and provide more controlled measurements, especially for liquid biopsy samples. Finally, we had chances to test only a model of dPCR and a selection of qPCR instruments, while broader comparative studies across a variety of dPCR platforms would be more beneficial for establishing robustness and versatility.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eHerein, we have presented miRquad, the first-in-class dPCR TaqMan\u0026trade; Advanced clinical research assay for multiplex miRNA detection in HNCs. Developed on a patented prognostic signature capable of predicting the risk for local recurrence (\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), this assay overcomes most of the common limitations encountered when multiple miRNAs are under investigation, particularly in liquid biopsy samples. By enabling robust and accurate detection, miRquad demonstrates potential for real-time monitoring and patient prognostication in HNC through dPCR-based miRNA analysis. Furthermore, our work lays the groundwork for future efforts aimed at enhancing the clinical applicability and attractiveness of circulating miRNAs for routine diagnostic use.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eceRNA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;competing endogenous RNA\u003c/p\u003e\n\u003cp\u003edPCR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;digital PCR\u003c/p\u003e\n\u003cp\u003eFFPE\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Formalin-fixed paraffin-embedded\u003c/p\u003e\n\u003cp\u003eHNC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;head and neck\u003c/p\u003e\n\u003cp\u003emiRNAs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;microRNAs\u003c/p\u003e\n\u003cp\u003eRT-qPCR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; reverse transcription quantitative PCR\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFFPE samples including matched tumors and peritumoral area were obtained from Policlinico of Milan (EC authorization #105/IRE/24). Additional tumor specimens, sera and saliva were also collected\u0026nbsp;from the IRCCS Regina Elena National Cancer Institute biobank (EC authorization #RS868/16). A written informed consent was collected from all human subjects involved in this study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRaw data and related analyses supporting paper findings are available upon reasonable request to the corresponding author (GB).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompetiting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMA, GU, VDP, FG, RP, GB, SF, SF, TM, CC, EDG, AB, LS, RM, MU, EA, SDS, AA, SG, AP, GC and GB declare no potential conflicts of interest with the present work. DJJ and JFS are employees of Thermo Fisher Scientific™. miRquad assay content is based on a previously patented set of miRNA targets registered by GB, FG, and RP (#102020000019024).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFundings\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis work received support from the Italian Ministry of Health (PNC E3-2022-23683266, PNRR-POC-2022–12376580), Associazione Italiana per la Ricerca sul Cancro (AIRC, IG 29040), and in-kind support from Thermo Fisher Scientific™.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthors’ contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMA supervised miRNAs extraction from synthetic and patient-derived material, designed and performed qPCR/dPCR experiments, analysed molecular data, and wrote the paper; DJJ designed miRquad assay, performed preliminary assessment, analysed molecular data, and revised the paper; GU performed dPCR experiments on patient sera and saliva; VDP extracted miRNAs from tissues, sera and saliva; FG collected and processed patient samples; RP recruited HNC patients and elaborated clinical data; GB, SF and SF recruited patient and collected tissue samples included in the validation cohort; TM, CC, EDG, AB, LS, MR, MU, EA, SDS, AA, SG, AP performed qPCR/dPCR experiments for the ring study; GC provided fundings for WP4 activities; JFS coordinated miRquad design, supervised benchmarking activities, and critically revised the paper; BG designed and supervised the study, provided fundings, and critically revised the paper. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDrs. Gianluca Fascioli and Francesco Lulli from Thermo Fisher Scientific™ are kindly acknowledge for their extraordinary support in bridging together administrative, economic and scientific parts below the present study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eVasan N, Baselga J, Hyman DM. A view on drug resistance in cancer. Nature. 2019;575(7782):299\u0026ndash;309.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFran\u0026ccedil;a GS, Baron M, King BR, Bossowski JP, Bjornberg A, Pour M, et al. Cellular adaptation to cancer therapy along a resistance continuum. Nature. 2024;631(8022):876\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMarine JC, Dawson SJ, Dawson MA. Non-genetic mechanisms of therapeutic resistance in cancer. 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BMC Biotechnol. 2018;18(1):16.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRedshaw N, Wilkes T, Whale A, Cowen S, Huggett J, Foy CA. A comparison of miRNA isolation and RT-qPCR technologies and their effects on quantification accuracy and repeatability. Biotechniques. 2013;54(3):155\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrunet-Vega A, Pericay C, Qu\u0026iacute;lez ME, Ram\u0026iacute;rez-L\u0026aacute;zaro MJ, Calvet X, Lario S. Variability in microRNA recovery from plasma: Comparison of five commercial kits. Anal Biochem. 2015;488:28\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTan GW, Khoo AS, Tan LP. Evaluation of extraction kits and RT-qPCR systems adapted to high-throughput platform for circulating miRNAs. Sci Rep. 2015;5:9430.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDay E, Dear PH, McCaughan F. 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Two miRNA prognostic signatures of head and neck squamous cell carcinoma: A bioinformatic analysis based on the TCGA dataset. Cancer Med. 2020;9(8):2631\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKrsek A, Baticic L, Sotosek V, Braut T. The Role of Biomarkers in HPV-Positive Head and Neck Squamous Cell Carcinoma. Towards Precision Med. 2024;14(13):1448.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchwarzenbach H, da Silva AM, Calin G, Pantel K. Data Normalization Strategies for MicroRNA Quantification. Clin Chem. 2015;61(11):1333\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-experimental-and-clinical-cancer-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jecc","sideBox":"Learn more about [Journal of Experimental \u0026 Clinical Cancer Research](http://jeccr.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jecc/default.aspx","title":"Journal of Experimental \u0026 Clinical Cancer Research","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"digital PCR, multiplex assay, microRNA, head and neck cancers, liquid biopsy","lastPublishedDoi":"10.21203/rs.3.rs-7623968/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7623968/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003c/em\u003e Despite remarkable therapeutic progress, cancer resistance remains one of the major challenges in oncology, often resulting in disease relapse and poor patient outcomes. Resistance arises from multiple genetic and non-genetic mechanisms, ultimately limiting the effectiveness of chemo- and targeted therapies. Within the RNA family, microRNAs (miRNAs) regulate core biological processes and have been recognized also as critical contributors of tumor resistance and therapy failure. Being pivotal, they have been increasingly exploited as biomarkers in various settings. Although in silico analyses facilitate miRNAs identification, PCR-based approaches remain essential to validate their expression. Currently, a plethora of well-established methods exist but multiplex detection from the same input have been only rarely explored.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/em\u003e We present miRquad, the first-in-class digital PCR (dPCR) TaqMan™ multiplex RUO assay for miRNA detection in head and neck (HNC) cancers. Based on a patented prognostic signature including miR-21-5p, miR-96-5p, miR-21-3p and miR-429, the assay enables simultaneous miRNA analysis via qPCR and dPCR across multiple clinically relevant sample types.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/em\u003e We designed and optimized miRquad using both synthetic controls and retrospective patient-derived tissues, sera and saliva. A multicentre ring study was conducted to evaluate assay reliability across different platforms, demonstrating strong correlation with commercial singleplexes, broad applicability, and cost-effectiveness. Finally, we provide evidence for its potential clinical application in different HNC settings, testing miRquad on tumoral and peritumoral tissues, sera and saliva samples collected throughout patient follow up.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e: \u003c/strong\u003eThe assay overcomes common challenges associated with multiple miRNAs detection, particularly in liquid biopsy samples, and provides robust and accurate detection, demonstrating potential for real-time patient monitoring and prognostication in HNC.\u003c/p\u003e","manuscriptTitle":"miRquad: first-in-class dPCR multiplex TaqMan™ Advanced RUO assay for microRNA detection in head and neck cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-26 15:06:04","doi":"10.21203/rs.3.rs-7623968/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-17T07:02:33+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-26T14:22:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"216628048632763468137344270172055699615","date":"2025-09-23T10:43:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"59396485555728890996860292304308119947","date":"2025-09-22T03:47:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-17T17:36:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-17T17:34:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-17T17:31:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Experimental \u0026 Clinical Cancer Research","date":"2025-09-15T20:48:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-experimental-and-clinical-cancer-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jecc","sideBox":"Learn more about [Journal of Experimental \u0026 Clinical Cancer Research](http://jeccr.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jecc/default.aspx","title":"Journal of Experimental \u0026 Clinical Cancer Research","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"de74b64c-fc1a-4b8e-97d1-052137cfa13e","owner":[],"postedDate":"September 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-22T16:01:59+00:00","versionOfRecord":{"articleIdentity":"rs-7623968","link":"https://doi.org/10.1186/s13046-025-03590-6","journal":{"identity":"journal-of-experimental-and-clinical-cancer-research","isVorOnly":false,"title":"Journal of Experimental \u0026 Clinical Cancer Research"},"publishedOn":"2025-12-20 15:57:58","publishedOnDateReadable":"December 20th, 2025"},"versionCreatedAt":"2025-09-26 15:06:04","video":"","vorDoi":"10.1186/s13046-025-03590-6","vorDoiUrl":"https://doi.org/10.1186/s13046-025-03590-6","workflowStages":[]},"version":"v1","identity":"rs-7623968","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7623968","identity":"rs-7623968","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}