NqA: An R-based algorithm for the normalization and analysis of microRNA quantitative real-time polymerase chain reaction data

Verderio, Paolo; Bottelli, Stefano; Ciniselli, Chiara Maura; Gariboldi, Manuela; Pizzamiglio, Sara

doi:10.1016/j.ab.2014.05.020

Cited by 16 publications

(11 citation statements)

References 10 publications

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“…Within each treatment arm (i.e., trastuzumab, lapatinib, and their combination) and timing of blood collection (i.e., T0 and T1), the following workflow was applied: the relative quantity (RQ) of each miRNA was calculated using the comparative threshold cycle method following the formula 2^-DCq where DCq ¼ Cq miRNA -Cq reference (38). The Cq reference was computed by averaging the Cq values of the reference miRNAs identified by an updated version of the NqA algorithm (39). The RQ of each miRNA, expressed in logarithmic scale (log 2 RQ ¼ ÀDCq), was then analyzed in univariate manner to identify those miRNAs statistically associated with pCR.…”

Section: Ct-mirna Profiling Data Processingmentioning

confidence: 99%

Plasma miRNA Levels for Predicting Therapeutic Response to Neoadjuvant Treatment in HER2-positive Breast Cancer: Results from the NeoALTTO Trial

Cosimo

Appierto

Pizzamiglio

et al. 2019

Clinical Cancer Research

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Purpose: To investigate the potential of circulating-miRNAs (ct-miRNA) as noninvasive biomarkers to predict the efficacy of single/dual HER2-targeted therapy in the NeoALTTO study. Experimental Design: Patients with plasma samples at baseline (T0) and/or after 2 weeks (T1) of treatment were randomized into training (n ¼ 183) and testing (n ¼ 246) sets. RT-PCR-based high-throughput miRNA profiling was employed in the training set. After normalization, ct-miRNAs associated with pathologic complete response (pCR) were identified by univariate analysis. Multivariate logistic regression models were implemented to generate treatment-specific signatures at T0 and T1, which were evaluated by RT-PCR in the testing set. Event-free survival (EFS) according to ct-miRNA signatures was estimated by Kaplan-Meier method and Cox regression model. Results: In the training set, starting from 51 ct-miRNAs associated with pCR, six signatures with statistically significant predictive capability in terms of area under the ROC curve (AUC) were identified. Four signatures were confirmed in the testing set: lapatinib at T0 and T1 [AUC 0.86; 95% confidence interval (CI), 0.73-0.98 and 0.71 (0.55-0.86)], respectively; trastuzumab at T1 (0.81; 0.70-0.92); lapatinib þ trastuzumab at T1 (0.67; 0.51-0.83). These signatures were confirmed predictive after adjusting for known variables, including estrogen receptor status. ct-miRNA signatures failed to correlate with EFS. However, the levels of ct-miR-140-5p, included in the trastuzumab signature, were associated with EFS (HR 0.43; 95% CI, 0.22-0.84). Conclusions: ct-miRNAs discriminate patients with and without pCR after neoadjuvant lapatinib-and/or trastuzumab-based therapy. ct-miRNAs at week two could be valuable to identify patients responsive to trastuzumab, to avoid unnecessary combination with other anti-HER2 agents, and finally to assist deescalating treatment strategies.

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Section: Ct-mirna Profiling Data Processingmentioning

confidence: 99%

Plasma miRNA Levels for Predicting Therapeutic Response to Neoadjuvant Treatment in HER2-positive Breast Cancer: Results from the NeoALTTO Trial

Cosimo

Appierto

Pizzamiglio

et al. 2019

Clinical Cancer Research

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“…Each subject was classified as: no lesion (NL, including negative or no neoplastic lesions), LgA, HgA and cancerous lesion (CL, including cancerized adenoma and carcinomas), according to the worst endoscopic lesion recorded in the LHA register. By running an updated version of the normalization quantitative polymerase chain reaction array R‐function developed in the study, the data were normalized according to the overall mean and a subset of reference miRNAs that best resembled the results with the overall mean was identified. The nonparametric Kruskal‐Wallis test, adopting a nominal α value of 5%, was applied to the log 2 (RQ) distributions (where relative quantity [RQ] = 2 −ΔCt ) to identify miRNAs that showed significantly different expression in subjects with proliferative lesions compared to those without lesions (NL) and then within each specific proliferative lesion (LgA, HgA or CL) compared to NL.…”

Section: Methodsmentioning

confidence: 99%

Plasma miRNA‐based signatures in CRC screening programs

Zanutto

Ciniselli

Belfiore

et al. 2019

Intl Journal of Cancer

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Colorectal cancer (CRC) screening programs help diagnose cancer precursors and early cancers and help reduce CRC mortality. However, currently recommended tests, the fecal immunochemical test (FIT) and colonoscopy, have low uptake. There is therefore a pressing need for screening strategies that are minimally invasive and consequently more acceptable to patients, most likely blood based, to increase early CRC identification. MicroRNAs (miRNAs) released from cancer cells are detectable in plasma in a remarkably stable form, making them ideal cancer biomarkers. Using plasma samples from FIT‐positive (FIT+) subjects in an Italian CRC screening program, we aimed to identify plasma circulating miRNAs that detect early CRC. miRNAs were initially investigated by quantitative real‐time PCR in plasma from 60 FIT+ subjects undergoing colonoscopy at Fondazione IRCCS Istituto Nazionale dei Tumori, then tested on an internal validation cohort (IVC, 201 cases) and finally in a large multicenter prospective series (external validation cohort [EVC], 1121 cases). For each endoscopic lesion (low‐grade adenoma [LgA], high‐grade adenoma [HgA], cancer lesion [CL]), specific signatures were identified in the IVC and confirmed on the EVC. A two‐miRNA‐based signature for CL and six‐miRNA signatures for LgA and HgA were selected. In a multivariate analysis including sex and age at blood collection, the areas under the receiver operating characteristic curve (95% confidence interval) of the signatures were 0.644 (0.607–0.682), 0.670 (0.626–0.714) and 0.682 (0.580–0.785) for LgA, HgA and CL, respectively. A miRNA‐based test could be introduced into the FIT+ workflow of CRC screening programs so as to schedule colonoscopies only for subjects likely to benefit most.

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“…The amplification curves were analyzed using the Roche LC software for determination of quantification cycle (Cq) values. The relative quantity (RQ) of each ct-miRNA was calculated using the comparative threshold cycle method following the formula 2ˆ-DCq where DCq = (Cq miRNA − Cq reference) [35], where the Cq reference was computed by considering the Cq average of all the detected miRNAs (global mean approach) [36,37]. The RQ of each miRNA, expressed in logarithmic scale (log2 RQ), was then used for the statistical analysis.…”

Section: Ct-mirna Profiling Data Processingmentioning

confidence: 99%

Early Modulation of Circulating MicroRNAs Levels in HER2-Positive Breast Cancer Patients Treated with Trastuzumab-Based Neoadjuvant Therapy

Cosimo

Appierto

Pizzamiglio

et al. 2020

IJMS

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Circulating microRNA (ct-miRNAs) are able to identify patients with differential response to HER2-targeted therapy. However, their dynamics are largely unknown. We assessed 752 miRNAs from 52 NeoALTTO patients with plasma pairs prior and two weeks after trastuzumab. Increased levels of ct-miR-148a-3p and ct-miR-374a-5p were significantly associated with pathological complete response (pCR) (p = 0.008 and 0.048, respectively). At a threshold ≥ the upper limit of the 95%CI of the mean difference, pCR resulted 45% (95%CI 24%–68%), and 44% (95%CI 22%–69%) for ct-miR-148a-3p and ct-miR-374a-5p, respectively. Notably, ct-miR-148a-3p retained its predictive value (OR 3.42, 95%CI 1.23–9.46, p = 0.018) in bivariate analysis along with estrogen receptor status. Combined information from ct-miR-148a-3p and ct-miR140-5p, which we previously reported to identify trastuzumab-responsive patients, resulted in greater predictive capability over each other, with pCR of 54% (95%CI 25%–81%) and 0% (95%CI 0%–31%) in ct-miR-148a/ct-miR-140-5p high/present and low/absent, respectively. GO and KEGG analyses showed common enriched terms between the targets of these ct-miRNAs, including cell metabolism regulation, AMPK and MAPK signaling, and HCC progression. In conclusion, early modulated ct-miR-148-3p may inform on the functional processes underlying treatment response, integrate the information from already available predictive biomarkers, and identify patients likely to respond to single agent trastuzumab-based neoadjuvant therapy.

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NqA: An R-based algorithm for the normalization and analysis of microRNA quantitative real-time polymerase chain reaction data

Cited by 16 publications

References 10 publications

Plasma miRNA Levels for Predicting Therapeutic Response to Neoadjuvant Treatment in HER2-positive Breast Cancer: Results from the NeoALTTO Trial

Plasma miRNA Levels for Predicting Therapeutic Response to Neoadjuvant Treatment in HER2-positive Breast Cancer: Results from the NeoALTTO Trial

Plasma miRNA‐based signatures in CRC screening programs

Early Modulation of Circulating MicroRNAs Levels in HER2-Positive Breast Cancer Patients Treated with Trastuzumab-Based Neoadjuvant Therapy

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