Elisa Dama

Optimization and Standardization of Circulating MicroRNA Detection for Clinical Application: The miR-Test Case.

BACKGROUND The identification of circulating microRNAs (miRNAs) in the blood has been recently exploited for the development of minimally invasive tests for the early detection of cancer. Nevertheless, the clinical transferability of such tests is uncertain due to still-insufficient standardization and optimization of methods to detect circulating miRNAs in the clinical setting. METHODS We performed a series of tests to optimize the quantification of serum miRNAs that compose the miR-Test, a signature for lung cancer early detection, and systematically analyzed variables that could affect the performance of the test. We took advantage of a large-scale (>1000 samples) validation study of the miR-Test that we recently published, to evaluate, in clinical samples, the effects of analytical and preanalytical variables on the quantification of circulating miRNAs and the clinical output of the signature (risk score). RESULTS We developed a streamlined and standardized pipeline for the processing of clinical serum samples that allows the isolation and analysis of circulating miRNAs by quantitative reverse-transcription PCR, with a throughput compatible with screening trials. The major source of analytical variation came from RNA isolation from serum, which could be corrected by use of external (spike-in) or endogenous miRNAs as a reference for normalization. We also introduced standard operating procedures and QC steps to check for unspecific fluctuations that arise from the lack of standardized criteria in the collection or handling of the samples (preanalytical factors). CONCLUSIONS We propose our methodology as a reference for the development of clinical-grade blood tests on the basis of miRNA detection.

An aggressive subtype of stage I lung adenocarcinoma with molecular and prognostic characteristics typical of advanced lung cancers

Purpose: The National Lung Cancer Screening Trial has confirmed that lung cancer mortality can be reduced if tumors are diagnosed early, that is, at stage I. However, a substantial fraction of stage I lung cancer patients still develop metastatic disease within 5 years from surgery. Prognostic biomarkers are therefore needed to identify patients at risk of an adverse outcome, who might benefit from multimodality treatment. Experimental Design: We extensively validated a 10-gene prognostic signature in a cohort of 507 lung adenocarcinoma patients using formalin-fixed paraffin-embedded samples. Furthermore, we performed an integrated analysis of gene expression, methylation, somatic mutations, copy number variations, and proteomic profiles on an independent cohort of 468 patients from The Cancer Genome Atlas (TCGA). Results: Stage I lung cancer patients (N = 351) identified as high-risk by the 10-gene signature displayed a 4-fold increased risk of death [HR = 3.98; 95% confidence interval (CI), 1.73–9.14], with a 3-year overall survival of 84.2% (95% CI, 78.7–89.7) compared with 95.6% (92.4–98.8) in low-risk patients. The analysis of TCGA cohort revealed that the 10-gene signature identifies a subgroup of stage I lung adenocarcinomas displaying distinct molecular characteristics and associated with aggressive behavior and poor outcome. Conclusions: We validated a 10-gene prognostic signature capable of identifying a molecular subtype of stage I lung adenocarcinoma with characteristics remarkably similar to those of advanced lung cancer. We propose that our signature might aid the identification of stage I patients who would benefit from multimodality treatment. Clin Cancer Res; 23(1); 62–72. ©2016 AACR.

Most high-grade neuroendocrine tumours of the lung are likely to secondarily develop from pre-existing carcinoids: innovative findings skipping the current pathogenesis paradigm

Among lung neuroendocrine tumours (Lung-NETs), typical carcinoid (TC) and atypical carcinoid (AC) are considered separate entities as opposed to large cell neuroendocrine carcinoma (LCNEC) and small cell lung carcinoma (SCLC). By means of two-way clustering analysis of previously reported next-generation sequencing data on 148 surgically resected Lung-NETs, six histology-independent clusters (C1 → C6) accounting for 68% of tumours were identified. Low-grade Lung-NETs were likely to evolve into high-grade tumours following two smoke-related paths. Tumour composition of the first path (C5 → C1 → C6) was coherent with the hypothesis of an evolution of TC to LCNEC, even with a conversion of SCLC-featuring tumours to LCNEC. The second path (C4 → C2–C3) had a tumour composition supporting the evolution of AC to SCLC-featuring tumours. The relevant Ki-67 labelling index varied accordingly, with median values being 5%, 9% and 50% in the cluster sequence C5 → C1 → C6, 12% in cluster C4 and 50–60% in cluster C2–C3. This proof-of-concept study suggests an innovative view on the progression of pre-existing TC or AC to high-grade NE carcinomas in most Lung-NET instances.

Sensitive and affordable diagnostic assay for the quantitative detection of anaplastic lymphoma kinase ( ALK ) alterations in patients with non-small cell lung cancer

Accurate detection of altered anaplastic lymphoma kinase (ALK) expression is critical for the selection of lung cancer patients eligible for ALK-targeted therapies. To overcome intrinsic limitations and discrepancies of currently available companion diagnostics for ALK, we developed a simple, affordable and objective PCR-based predictive model for the quantitative measurement of any ALK fusion as well as wild-type ALK upregulation. This method, optimized for low-quantity/−quality RNA from FFPE samples, combines cDNA pre-amplification with ad hoc generated calibration curves. All the models we derived yielded concordant predictions when applied to a cohort of 51 lung tumors, and correctly identified all 17 ALK FISH-positive and 33 of the 34 ALK FISH-negative samples. The one discrepant case was confirmed as positive by IHC, thus raising the accuracy of our test to 100%. Importantly, our method was accurate when using low amounts of input RNA (10 ng), also in FFPE samples with limited tumor cellularity (5–10%) and in FFPE cytology specimens. Thus, our test is an easily implementable diagnostic tool for the rapid, efficacious and cost-effective screening of ALK status in patients with lung cancer.

Mining cancer gene expression databases for latent information on intronic microRNAs

Around 50% of all human microRNAs reside within introns of coding genes and are usually co‐transcribed. Gene expression datasets, therefore, should contain a wealth of miRNA‐relevant latent information, exploitable for many basic and translational research aims. The present study was undertaken to investigate this possibility. We developed an in silico approach to identify intronic‐miRNAs relevant to breast cancer, using public gene expression datasets. This led to the identification of a miRNA signature for aggressive breast cancer, and to the characterization of novel roles of selected miRNAs in cancer‐related biological phenotypes. Unexpectedly, in a number of cases, expression regulation of the intronic‐miRNA was more relevant than the expression of their host gene. These results provide a proof of principle for the validity of our intronic miRNA mining strategy, which we envision can be applied not only to cancer research, but also to other biological and biomedical fields.

Abstract 1573: miR-Test: a blood test for lung cancer early detection

Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PA Background: Lung cancer is the leading cause of cancer death worldwide. As lung cancer is asymptomatic in its early stages, the majority of patients are diagnosed with advanced disease, when the tumor is unresectable. Consequently, the survival rate is very low: 15% at 5 years. It is vital, therefore, that screening programs and novel diagnostic tools are developed, which will increase the detection of lung cancer in its early stages (stage I-II), when the tumor is still curable, to reduce lung cancer mortality. Recently, we described a serum microRNA signature diagnostic for asymptomatic, early stage, lung cancer. The availability of reliable biomarkers to identify high-risk individuals might help to reduce the size of the target population for LDCT-based programs, thereby reducing costs and probably increasing compliance Methods: We performed a large-scale validation study of a miRNA blood test based on our signature (the miR-Test) in a population of high-risk individuals (N = 1115) enrolled in the lung cancer screening program COSMOS (Continuous Observation of SMOking Subjects), and other 74 lung cancer patients diagnosed outside of screening. Results: The miR-Test showed overall accuracy, specificity and sensitivity of 75%, 78%, and 75%, respectively, with an AUC of 0.85. The test appears to have a dual origin: the first from epithelial cells (the epithelial-like component); the second from cells of hematopoietic origin (the inflammatory-like component). Of note, we found that both components are needed to maintain a good performance of the miR-Test. Conclusions: The relatively high sensitivity of the miR-Test in detecting asymptomatic lung cancer and its high negative predictive value (NPV > 99%), confirm the effectiveness of the test, both interms of its ability to identify asymptomatic lung cancer patients and to reduce significantly unnecessary CTs on healthy individuals. Citation Format: Francesca Montani, Matteo Jacopo Marzi, Fabio Dezi, Elisa Dama, Rose Mary Carletti, Giuseppina Bonizzi, Raffaella Bertolotti, Massimo Bellomi, Cristiano Rampinelli, Patrick Maisonneuve, Lorenzo Spaggiari, Giulia Veronesi, Francesco Nicassio, Pier Paolo Di Fiore, Fabrizio Bianchi. miR-Test: a blood test for lung cancer early detection. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1573. doi:10.1158/1538-7445.AM2015-1573

Abstract 4441: Unveil the role of cell-free circulating microRNA in lung cancer

We previously reported the identification of a signature composed by 34 serum circulating cell-free microRNAs (cf-miRNA) diagnostic for lung cancer. Using this signature, we developed a blood test (miR-test) which was capable of detecting asymptomatic lung cancer in a large cohort (N>1000) of high-risk individuals (>50years and smokers). Interestingly, we now found that a fraction (~30%) of these cf-miRNAs were preferentially expressed in cells of epithelial origin, while another ~30% were more expressed in hematopoietic cells. We reasoned that this cf-miRNA signature could result from the extracellular release of miRNAs from cancer epithelial cells as well as from immune/stromal cells composing the tumor microenvironment. We developed an integrated strategy for the identification of the origin of cf-miRNAs through combined analysis of published circulating and intracellular miRNAs expression datasets (microarray and qRT-PCR based) and of NGS analysis of cf-miRNAs in lung tumors. Our approach will contribute elucidating the biological role of cf-miRNAs in lung cancer and explore eventual therapeutic implications. Citation Format: Fabrizio Bianchi, Valentina Melocchi, Tommaso Colangelo, Roberto Cuttano, Lucia Anna Muscarella, Elisa Dama. Unveil the role of cell-free circulating microRNA in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4441. doi:10.1158/1538-7445.AM2017-4441

Abstract 1575: Serum circulating miR–Test application: Standardized protocol for miR–Test clinical application

Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PA Lung cancer is leading cause of cancer death worldwide. Being lung cancer asymptomatic in its early stages, the majority of patients are diagnosed with advanced disease. Therefore, it is vital that screening programs and novel diagnostic tools are developed to increase lung cancer early detection. The development of a minimally invasive blood-based diagnostic tool would be ideal as a first-line screening procedure. An increasing number of studies are demonstrating that fluctuations of circulating miRNAs are associated to lung cancer. Recently, we described a serum circulating miRNA signature (miR-Test) diagnostic for asymptomatic, early stage, lung cancer, that was validated in a large cohort of individuals (N = 1115) enrolled in the lung cancer screening program COSMOS (Continuous Observation of SMOking Subjects). However, the transfer to the clinic of a blood test based on circ-miRNAs requires the establishment of standardized operating procedures (SOPs), working instructions and guidelines for all pre-analytical and analytical procedures. We identified possible sources of variability affecting circulating miRNAs, analyzed their impact on the miR-Test performance, and defined a standardized protocol to optimize miR-Test application. Analysis of all possible technical and biological variation affecting circ-miRNAs level, revealed two main sources of variability: one related to analytical procedures for miRNAs extraction and quantification, and the other due to pre-analytical conditions, on how samples are prepared. The extraction causes the main source of analytical imprecision. In conclusion, we identified an optimal protocol for the application of miR-Test for lung cancer early diagnosis. Citation Format: Francesca Montani, Matteo Marzi, Fabio Dezi, Elisa Dama, Rose Mary Carletti, Giulia Veronesi, Francesco Nicassio, Pier Paolo Di Fiore, Fabrizio Bianchi. Serum circulating miR–Test application: Standardized protocol for miR–Test clinical application. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1575. doi:10.1158/1538-7445.AM2015-1575

Abstract 233: Mining cancer gene expression databases for latent information on intronic microRNAs

In recent years, enormous effort has been dedicated to transcriptomic profiling of various physiological and pathological conditions, in particular in cancer biology field. Microarray gene expression (mRNA) datasets of thousands of human tumors are now publicly available and can be used to get insights of cancer processes by systems-based analysis and to identify biomarkers for improvement of cancer therapy. However, the high complexity of human transcriptome may be difficult to handle. In this regard, shifting the attention to the miRNome could be an advantage, since its complexity is at least 20-fold lower than that of a reference transcriptome (∼1000 miRNAs vs. ∼20,000 genes). Importantly, patterns of distinct miRNA expression profiles were observed in tumors and there is a growing interest in miRNAs, behaving as potential cancer determinants and biomarkers. Knowing that almost 50% of human miRNA genes are located within introns of coding genes and that they usually share transcriptional regulation, those publicly available datasets are likely to contain “latent” information on intronic-miRNA expression. In other words, it could be possible to predict the regulation of intronic-miRNA expression by simply analyzing their host genes profile (miR-HG). The aim of our work is to take advantage of cancer datasets, focusing mainly on breast cancer datasets, to provide proof of principle evidences that meta-analysis of miR-HG expression profiles can pinpoint intronic-miRNAs with a role in breast cancer cell biology, and a potential utility as cancer biomarkers. Using this approach, we successfully discovered a diagnostic microRNA signature enabling the identification of breast cancer molecular subtypes. Importantly, qRT-PCR analysis of just three intronic-miRNAs, using FFPE samples, was sufficient to identify more aggressive breast tumor subtypes (i.e. basal, HER2 and luminal B subtypes), with a ∼80% of accuracy, in patients with moderately differentiated breast cancer. Unexpectedly, in a number of cases, the regulation of expression of intronic-miRNAs was more relevant to cancer phenotypes than the expression of their host genes. In line with these encouraging results, we propose our data mining strategy as a valid tool for cancer research and other biomedical fields. Citation Format: Simona Monterisi, Giovanni D9Ario, Elisa Dama, Nicole Rotmensz, Stefano Confalonieri, Chiara Tordonato, Flavia Troglio, Giovanni Bertalot, Patrick Maisonneuve, Giuseppe Viale, Francesco Nicassio, Pier Paolo Di Fiore, Fabrizio Bianchi. Mining cancer gene expression databases for latent information on intronic microRNAs. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 233. doi:10.1158/1538-7445.AM2015-233