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Molecular tests predicting the risk of distant recurrence (DR) can be used to assist therapy decision-making in oestrogen receptor-positive (ER+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancer patients after considerations of standard clinical markers. The Oncotype DX Recurrence Score (RS) is a widespread tool used for this purpose. Here, we compared the RS with the StemPrintER Risk Score (SPRS), a novel genomic predictor with a unique biological basis in its ability to measure the expression of cancer stemness genes.We benchmarked the SPRS vs. RS, alone or in combination with clinicopathological variables expressed by the Clinical Treatment Score (CTS), for the prognostication of DR in a retrospective cohort of 776 postmenopausal patients with ER+/HER2-breast cancer enrolled in the translational arm of the randomised Arimidex, Tamoxifen, Alone or in Combination (ATAC) trial. Likelihood ratio (LR) with χIn all patients, the SPRS provided significantly more prognostic information than the RS for ten-year DR prognostication (C-index = 0.688, LR-χIn postmenopausal ER+/HER2- breast cancer patients, SPRS provided more prognostic information than RS for DR when used alone or in combination with the CTS. The SPRS could therefore potentially identify high-risk patients, who might benefit from aggressive treatments, from low-risk patients who might safely avoid adjuvant chemotherapy or prolongation of endocrine therapy.

Motivation Breast cancer is the most commonly diagnosed malignancy in women and the second cause of cancer death in developed countries. While advancements in early detection and therapeutic options have led to a significant decrease in mortality, response to treatment is affected by the genetic heterogeneity of the disease. Recent genome-wide DNA mutation analyses revealed the existence of hundreds of low-frequency mutated genes, in addition to known cancer drivers: a finding that is prompting research into the impact of these genes on the pathogenesis of the disease. Results Herein, we describe a strategy towards the characterization of the role of low-frequency mutated genes in breast cancer. Through the combined analyses of publicly available gene expression and mutational datasets, we identified several Cancer Gene Modules (CMs) that we re-organized in Gene Regulatory Networks (GRN) enriched in low-frequency mutated genes. Importantly, these low-frequency mutated genes were mutually exclusive with known cancer drivers. Finally, we provide evidence that gene expression analysis of these mutated GRNs can predict resistance/sensitivity to chemotherapeutic drugs for breast cancer treatment. Availability and implementation Datasets are available at https://www.ncbi.nlm.nih.gov/geo/ and at https://www.ebi.ac.uk/ega/datasets/. Molecular signatures and GSEA software are available at http://www.gsea-msigdb.org/gsea/index.jsp. Source codes are available at https://github.com/EleonoraLusito/Reverse_Engineering_BC_GRNs. Supplementary information Supplementary data are available at Bioinformatics online.

1020 Background: Accurate prediction of distant metastasis (DM) in early stage ER+/HER2- breast cancer (BC) patients is vital to avoid over/under-treatment with adjuvant chemotherapy (CT). The OncotypeDX Recurrence Score (RS) is a widely used tool to assist clinical decision-making for CT. The StemPrintER Risk Score (SPRS) is an alternative genomic predictor based on the biology of cancer stem cells that predicts recurrence risk in ER+/HER2- BCs (Pece S. et al., EBioMedicine 2019). Here, we analyze the prognostic value of SPRS in the TransATAC cohort of post-menopausal ER+/HER2- BC patients, and compare the prognostic information provided by SPRS and RS for 10-year risk of DM. Methods: The likelihood χ2 (LRχ2) and Kaplan-Meier survival analyses were used to assess prognostic information provided by SPRS, RS and the clinical treatment score (CTS) in 818 TransATAC patients treated with anastrozole or tamoxifen for 5 years. Comparative analyses were made for DM risk over the 10-year follow-up, as well as in the early (0-5 years) or late (5-10 years) interval, according to nodal status. Results: Used as a continuous variable, SPRS was an independent predictor of DM in years 0-10 among all patients when adjusted for clinical parameters as expressed by the CTS [HR=1.43 (1.18-1.73), PHIGH vs. LOW=2.96 (1.85-4.73); P2=33.4; RS: HR=1.52, P2=22.1), with even greater differences in late DM prediction in N0 patients. SPRS also provided more prognostic information than RS to CTS (ΔLRχ2: SPRS+CTS vs. CTS= 14.9; RS+CTS vs. CTS= 9.7). Conclusions: In ER+/HER2- TransATAC BC patients, SPRS was highly prognostic for DM and was superior to RS in providing additional prognostic information to conventional clinicopathological parameters.

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.

Lung cancer is the leading cause of cancer death worldwide. Low-dose computed tomography screening (LDCT) was recently shown to anticipate the time of diagnosis, thus reducing lung cancer mortality. However, concerns persist about the feasibility and costs of large-scale LDCT programs. Such concerns may be addressed by clearly defining the target "high-risk" population that needs to be screened by LDCT. We recently identified a serum microRNA signature (the miR-Test) that could identify the optimal target population. Here, we performed a large-scale validation study of the miR-Test in high-risk individuals (n = 1115) enrolled in the Continuous Observation of Smoking Subjects (COSMOS) lung cancer screening program. The overall accuracy, sensitivity, and specificity of the miR-Test are 74.9% (95% confidence interval [CI] = 72.2% to 77.6%), 77.8% (95% CI = 64.2% to 91.4%), and 74.8% (95% CI = 72.1% to 77.5%), respectively; the area under the curve is 0.85 (95% CI = 0.78 to 0.92). These results argue that the miR-Test might represent a useful tool for lung cancer screening in high-risk individuals.

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

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