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Wu M, Yuan H, Zou W, Xu S, Liu S, Gao Q, Guo Q, Han Y, An X. Circular RNAs: characteristics, functions, mechanisms, and potential applications in thyroid cancer. Clin Transl Oncol 2024; 26:808-824. [PMID: 37864677 DOI: 10.1007/s12094-023-03324-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 09/08/2023] [Indexed: 10/23/2023]
Abstract
Thyroid cancer (TC) is one of the most common endocrine malignancies, and its incidence has increased globally. Despite extensive research, the underlying molecular mechanisms of TC remain partially understood, warranting continued exploration of molecular markers for diagnostic and prognostic applications. Circular RNAs (circRNAs) have recently garnered significant attention owing to their distinct roles in cancers. This review article introduced the classification and biological functions of circRNAs and summarized their potential as diagnostic and prognostic markers in TC. Further, the interplay of circRNAs with PI3K/Akt/mTOR, Wnt/β-catenin, MAPK/ERK, Notch, JAK/STAT, and AMPK pathways is elaborated upon. The article culminates with an examination of circRNA's role in drug resistance of TC and highlights the challenges in circRNA research in TC.
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Affiliation(s)
- Mengmeng Wu
- Department of Thyroid Surgery, Binzhou Medical University Hospital, Binzhou, 256603, Shandong, People's Republic of China
| | - Haibin Yuan
- Department of Health Management, Binzhou Medical University Hospital, Binzhou, 256603, Shandong, People's Republic of China
| | - Weiwei Zou
- Department of Thyroid Surgery, Binzhou Medical University Hospital, Binzhou, 256603, Shandong, People's Republic of China
| | - Shujian Xu
- Department of Thyroid Surgery, Binzhou Medical University Hospital, Binzhou, 256603, Shandong, People's Republic of China
| | - Song Liu
- Department of Thyroid Surgery, Binzhou Medical University Hospital, Binzhou, 256603, Shandong, People's Republic of China
| | - Qiang Gao
- Department of Thyroid Surgery, Binzhou Medical University Hospital, Binzhou, 256603, Shandong, People's Republic of China
| | - Qingqun Guo
- Department of Thyroid Surgery, Binzhou Medical University Hospital, Binzhou, 256603, Shandong, People's Republic of China
| | - Yong Han
- Department of Thyroid Surgery, Binzhou Medical University Hospital, Binzhou, 256603, Shandong, People's Republic of China.
| | - Xingguo An
- Department of Thyroid Surgery, Binzhou Medical University Hospital, Binzhou, 256603, Shandong, People's Republic of China.
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Çalışkan M, Tazaki K. AI/ML advances in non-small cell lung cancer biomarker discovery. Front Oncol 2023; 13:1260374. [PMID: 38148837 PMCID: PMC10750392 DOI: 10.3389/fonc.2023.1260374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 11/16/2023] [Indexed: 12/28/2023] Open
Abstract
Lung cancer is the leading cause of cancer deaths among both men and women, representing approximately 25% of cancer fatalities each year. The treatment landscape for non-small cell lung cancer (NSCLC) is rapidly evolving due to the progress made in biomarker-driven targeted therapies. While advancements in targeted treatments have improved survival rates for NSCLC patients with actionable biomarkers, long-term survival remains low, with an overall 5-year relative survival rate below 20%. Artificial intelligence/machine learning (AI/ML) algorithms have shown promise in biomarker discovery, yet NSCLC-specific studies capturing the clinical challenges targeted and emerging patterns identified using AI/ML approaches are lacking. Here, we employed a text-mining approach and identified 215 studies that reported potential biomarkers of NSCLC using AI/ML algorithms. We catalogued these studies with respect to BEST (Biomarkers, EndpointS, and other Tools) biomarker sub-types and summarized emerging patterns and trends in AI/ML-driven NSCLC biomarker discovery. We anticipate that our comprehensive review will contribute to the current understanding of AI/ML advances in NSCLC biomarker research and provide an important catalogue that may facilitate clinical adoption of AI/ML-derived biomarkers.
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Affiliation(s)
- Minal Çalışkan
- Translational Science Department, Precision Medicine Function, Daiichi Sankyo, Inc., Basking Ridge, NJ, United States
| | - Koichi Tazaki
- Translational Science Department I, Precision Medicine Function, Daiichi Sankyo, Tokyo, Japan
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Pedraz-Valdunciel C, Ito M, Giannoukakos S, Giménez-Capitán A, Molina-Vila MÁ, Rosell R. Brief Report: circRUNX1 as Potential Biomarker for Cancer Recurrence in EGFR Mutation-Positive Surgically Resected NSCLC. JTO Clin Res Rep 2023; 4:100604. [PMID: 38162176 PMCID: PMC10757026 DOI: 10.1016/j.jtocrr.2023.100604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 11/07/2023] [Accepted: 11/10/2023] [Indexed: 01/03/2024] Open
Abstract
Introduction As recently evidenced by the ADAURA trial, most patients with stages IB to IIIA of resected EGFR-mutant lung adenocarcinoma benefit from osimertinib as adjuvant therapy. Nevertheless, predictive markers of response and recurrence are still an unmet need for more than 10% of these patients. Some circular RNAs (circRNAs) have been reported to play a role in tumor growth and proliferation. In this project, we studied circRNA expression levels in formalin-fixed, paraffin-embedded lung tumor samples to explore their biomarker potential and develop a machine learning (ML)-based signature that could predict the benefit of adjuvant EGFR tyrosine kinase inhibitors in patients with EGFR-mutant NSCLC. Methods Patients with surgically resected EGFR mutant-positive, stages I to IIIB NSCLC were recruited from February 2007 to December 2015. Formalin-fixed, paraffin-embedded tumor samples were retrospectively collected from those patients with a follow-up period of more than or equal to 36 months (N = 76). Clinicopathologic features were annotated. Total RNA was purified and quantified prior nCounter processing with our circRNA custom panel. Data analysis and ML were performed taking into consideration circRNA expression levels and recurrence-free survival (RFS). RFS was defined from the day of surgery to the day when recurrence was detected radiologically or the death owing to any cause. Results Of the 76 patients with EGFR mutation-positive NSCLC included in the study, 34 relapsed within 3 years after resection. The median age of the relapsing cohort was 71.5 (range: 49-89) years. Most patients were nonsmokers (n = 21; 61.8%) and of female sex (n = 21; 61.8%). Most cases (n = 17; 50%) presented an exon 21 mutation, whereas 15 and four patients had an exon 19 and exon 18 mutation, respectively. Differential expression analysis revealed that circRUNX1, along with circFUT8 and circAASDH, was up-regulated in relapsing patients (p < 0.05 and >2 fold-change). A ML-based circRNA signature predictive of recurrence in patients with EGFR mutation-positive NSCLC, comprising circRUNX1, was developed. Our final model including selected 6-circRNA signature with random forest algorithm was able to classify relapsing patients with an accuracy of 83% and an area under the receiver operating characteristic curve of 0.91.RFS was significantly shorter not only for the subgroup of patients with high versus low circRUNX1 expression but also for the group classified as recurrent by the ML circRNA signature when compared with those classified as nonrecurrent. Conclusions Our findings suggest that circRUNX1 and the presented ML-developed signature could be novel tools to predict the benefit of adjuvant EGFR tyrosine kinase inhibitors with regard to RFS in patients with EGFR-mutant NSCLC. The training and validation phases of our ML signature will be conducted including bigger independent cohorts.
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Affiliation(s)
| | - Masaoki Ito
- Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan
| | | | | | | | - Rafael Rosell
- Pangaea Oncology, Dexeus University Hospital, Barcelona, Spain
- Germans Trias i Pujol Health Sciences Institute and Hospital (IGTP), Badalona, Spain
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Ito M, Miyata Y, Okada M. Current clinical trials with non-coding RNA-based therapeutics in malignant diseases: A systematic review. Transl Oncol 2023; 31:101634. [PMID: 36841158 PMCID: PMC9969060 DOI: 10.1016/j.tranon.2023.101634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 12/01/2022] [Accepted: 01/25/2023] [Indexed: 02/25/2023] Open
Abstract
This systematic review aimed to shed light on the trend of current clinical trials of non-coding RNA (ncRNA)-based therapeutics for malignant diseases. We conducted a database search for published literature and ongoing clinical trials using PubMed, clinicaltrials.gov, and University Medical Information Network (UMIN) clinical trial registry. To ensure that our review was based on up-to-date clinical trials, we limited our search to literature published within the last five years (January 2017-September 2022). Furthermore, due to the "clinical" nature of our review, we focused only on studies involving human participants. Among ncRNAs, microRNAs have been extensively explored in observational studies of malignant diseases as potential diagnostic markers and prognostic predictors, as well as for their therapeutic monitoring and profiling capabilities. As therapeutic agents, microRNA or siRNA were estimated in interventional human clinical trials and showed promising outcomes; however, the number of trials was small. Evidence and ongoing clinical trials in which ncRNAs other than microRNA or siRNA have been evaluated for their potential as therapeutic agents are limited. Here, we summarized microRNA as a potential therapeutic agent in malignant diseases, but most of the current evidence suggests that it is useful as a potential biomarker. siRNA is also a promising ncRNA technique in cancer, however more data from clinical trials are warranted for clinical use.
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Affiliation(s)
- Masaoki Ito
- Department of Surgical Oncology, Research Institute for Radiation, Biology and Medicine, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
| | - Yoshihiro Miyata
- Department of Surgical Oncology, Research Institute for Radiation, Biology and Medicine, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Morihito Okada
- Department of Surgical Oncology, Research Institute for Radiation, Biology and Medicine, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
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5
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Crudele F, Bianchi N, Terrazzan A, Ancona P, Frassoldati A, Gasparini P, D'Adamo AP, Papaioannou D, Garzon R, Wójcicka A, Gaj P, Jażdżewski K, Palatini J, Volinia S. Circular RNAs Could Encode Unique Proteins and Affect Cancer Pathways. BIOLOGY 2023; 12:biology12040493. [PMID: 37106694 PMCID: PMC10135897 DOI: 10.3390/biology12040493] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 03/10/2023] [Accepted: 03/21/2023] [Indexed: 04/29/2023]
Abstract
circRNAs constitute a novel class of RNA, generally considered as non-coding RNAs; nonetheless, their coding potential has been under scrutiny. In this work, we systematically explored the predicted proteins of more than 160,000 circRNAs detected by exome capture RNA-sequencing and collected in the MiOncoCirc pan-cancer compendium, including normal and cancer samples from different types of tissues. For the functional evaluation, we compared their primary structure and domain composition with those derived from the same linear mRNAs. Among the 4362 circRNAs potentially encoding proteins with a unique primary structure and 1179 encoding proteins with a novel domain composition, 183 were differentially expressed in cancer. In particular, eight were associated with prognosis in acute myeloid leukemia. The functional classification of the dysregulated circRNA-encoded polypeptides showed an enrichment in the heme and cancer signaling, DNA-binding, and phosphorylation processes, and disclosed the roles of some circRNA-based effectors in cancer.
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Affiliation(s)
- Francesca Crudele
- Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy
- Genetics Unit, Institute for Maternal and Child Health, Scientific Institute for Research, Hospitalization and Healthcare (IRCCS) Burlo Garofolo, 34137 Trieste, Italy
| | - Nicoletta Bianchi
- Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy
| | - Anna Terrazzan
- Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy
- Laboratory for Advanced Therapy Technologies (LTTA), University of Ferrara, 44121 Ferrara, Italy
| | - Pietro Ancona
- Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy
| | - Antonio Frassoldati
- Department of Oncology, Azienda Ospedaliero-Universitaria St. Anna di Ferrara, 44124 Ferrara, Italy
| | - Paolo Gasparini
- Genetics Unit, Institute for Maternal and Child Health, Scientific Institute for Research, Hospitalization and Healthcare (IRCCS) Burlo Garofolo, 34137 Trieste, Italy
| | - Adamo P D'Adamo
- Genetics Unit, Institute for Maternal and Child Health, Scientific Institute for Research, Hospitalization and Healthcare (IRCCS) Burlo Garofolo, 34137 Trieste, Italy
| | - Dimitrios Papaioannou
- Laura and Isaac Perlmutter Cancer Center, New York University School of Medicine, NYU Langone Health, New York, NY 10016, USA
| | - Ramiro Garzon
- Division of Hematology and Hematological Malignancies, University of Utah, Salt Lake City, UT 84112, USA
| | | | - Paweł Gaj
- Warsaw Genomics INC, 01-682 Warszawa, Poland
| | - Krystian Jażdżewski
- Human Cancer Genetics, Biological and Chemical Research Centre, University of Warsaw, 02-089 Warsaw, Poland
| | - Jeffrey Palatini
- Genomics Core Facility, Centre of New Technologies, University of Warsaw, 02-097 Warsaw, Poland
| | - Stefano Volinia
- Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy
- Laboratory for Advanced Therapy Technologies (LTTA), University of Ferrara, 44121 Ferrara, Italy
- CNBCh, Biological and Chemical Research Centre, University of Warsaw, 02-089 Warsaw, Poland
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Combinatorial Blood Platelets-Derived circRNA and mRNA Signature for Early-Stage Lung Cancer Detection. Int J Mol Sci 2023; 24:ijms24054881. [PMID: 36902312 PMCID: PMC10003255 DOI: 10.3390/ijms24054881] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 02/21/2023] [Accepted: 02/21/2023] [Indexed: 03/06/2023] Open
Abstract
Despite the diversity of liquid biopsy transcriptomic repertoire, numerous studies often exploit only a single RNA type signature for diagnostic biomarker potential. This frequently results in insufficient sensitivity and specificity necessary to reach diagnostic utility. Combinatorial biomarker approaches may offer a more reliable diagnosis. Here, we investigated the synergistic contributions of circRNA and mRNA signatures derived from blood platelets as biomarkers for lung cancer detection. We developed a comprehensive bioinformatics pipeline permitting an analysis of platelet-circRNA and mRNA derived from non-cancer individuals and lung cancer patients. An optimal selected signature is then used to generate the predictive classification model using machine learning algorithm. Using an individual signature of 21 circRNA and 28 mRNA, the predictive models reached an area under the curve (AUC) of 0.88 and 0.81, respectively. Importantly, combinatorial analysis including both types of RNAs resulted in an 8-target signature (6 mRNA and 2 circRNA), enhancing the differentiation of lung cancer from controls (AUC of 0.92). Additionally, we identified five biomarkers potentially specific for early-stage detection of lung cancer. Our proof-of-concept study presents the first multi-analyte-based approach for the analysis of platelets-derived biomarkers, providing a potential combinatorial diagnostic signature for lung cancer detection.
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Liquid Biopsy for Lung Cancer: Up-to-Date and Perspectives for Screening Programs. Int J Mol Sci 2023; 24:ijms24032505. [PMID: 36768828 PMCID: PMC9917347 DOI: 10.3390/ijms24032505] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 12/09/2022] [Accepted: 12/19/2022] [Indexed: 01/31/2023] Open
Abstract
Lung cancer is the deadliest cancer worldwide. Tissue biopsy is currently employed for the diagnosis and molecular stratification of lung cancer. Liquid biopsy is a minimally invasive approach to determine biomarkers from body fluids, such as blood, urine, sputum, and saliva. Tumor cells release cfDNA, ctDNA, exosomes, miRNAs, circRNAs, CTCs, and DNA methylated fragments, among others, which can be successfully used as biomarkers for diagnosis, prognosis, and prediction of treatment response. Predictive biomarkers are well-established for managing lung cancer, and liquid biopsy options have emerged in the last few years. Currently, detecting EGFR p.(Tyr790Met) mutation in plasma samples from lung cancer patients has been used for predicting response and monitoring tyrosine kinase inhibitors (TKi)-treated patients with lung cancer. In addition, many efforts continue to bring more sensitive technologies to improve the detection of clinically relevant biomarkers for lung cancer. Moreover, liquid biopsy can dramatically decrease the turnaround time for laboratory reports, accelerating the beginning of treatment and improving the overall survival of lung cancer patients. Herein, we summarized all available and emerging approaches of liquid biopsy-techniques, molecules, and sample type-for lung cancer.
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Ren L, Jiang Q, Mo L, Tan L, Dong Q, Meng L, Yang N, Li G. Mechanisms of circular RNA degradation. Commun Biol 2022; 5:1355. [PMID: 36494488 PMCID: PMC9734648 DOI: 10.1038/s42003-022-04262-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 11/15/2022] [Indexed: 12/13/2022] Open
Abstract
Circular RNAs (CircRNAs) are a class of noncoding RNAs formed by backsplicing during cotranscriptional and posttranscriptional processes, and they widely exist in various organisms. CircRNAs have multiple biological functions and are associated with the occurrence and development of many diseases. While the biogenesis and biological function of circRNAs have been extensively studied, there are few studies on circRNA degradation and only a few pathways for specific circRNA degradation have been identified. Here we outline basic information about circRNAs, summarize the research on the circRNA degradation mechanisms and discusses where this field might head, hoping to provide some inspiration and guidance for scholars who aim to study the degradation of circRNAs.
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Affiliation(s)
- Longxin Ren
- grid.412017.10000 0001 0266 8918The Hengyang Key Laboratory of Cellular Stress Biology, Institute of Cytology and Genetics, Hengyang Medical School, University of South China, Hengyang, 421001 Hunan China
| | - Qingshan Jiang
- grid.412017.10000 0001 0266 8918Department of Otolaryngology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan 421001 China
| | - Liyi Mo
- grid.412017.10000 0001 0266 8918The Hengyang Key Laboratory of Cellular Stress Biology, Institute of Cytology and Genetics, Hengyang Medical School, University of South China, Hengyang, 421001 Hunan China
| | - Lijie Tan
- grid.412017.10000 0001 0266 8918The Hengyang Key Laboratory of Cellular Stress Biology, Institute of Cytology and Genetics, Hengyang Medical School, University of South China, Hengyang, 421001 Hunan China
| | - Qifei Dong
- grid.412017.10000 0001 0266 8918The Hengyang Key Laboratory of Cellular Stress Biology, Institute of Cytology and Genetics, Hengyang Medical School, University of South China, Hengyang, 421001 Hunan China
| | - Lijuan Meng
- grid.412017.10000 0001 0266 8918Department of Ultrasonography, Second Affiliated Hospital, University of South China, Hengyang Hunan, 421001 China
| | - Nanyang Yang
- grid.412017.10000 0001 0266 8918The Hengyang Key Laboratory of Cellular Stress Biology, Institute of Cytology and Genetics, Hengyang Medical School, University of South China, Hengyang, 421001 Hunan China
| | - Guoqing Li
- grid.412017.10000 0001 0266 8918The Hengyang Key Laboratory of Cellular Stress Biology, Institute of Cytology and Genetics, Hengyang Medical School, University of South China, Hengyang, 421001 Hunan China
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Pedraz-Valdunciel C, Giannoukakos S, Giménez-Capitán A, Fortunato D, Filipska M, Bertran-Alamillo J, Bracht JWP, Drozdowskyj A, Valarezo J, Zarovni N, Fernández-Hilario A, Hackenberg M, Aguilar-Hernández A, Molina-Vila MÁ, Rosell R. Multiplex Analysis of CircRNAs from Plasma Extracellular Vesicle-Enriched Samples for the Detection of Early-Stage Non-Small Cell Lung Cancer. Pharmaceutics 2022; 14:2034. [PMID: 36297470 PMCID: PMC9610636 DOI: 10.3390/pharmaceutics14102034] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 09/15/2022] [Accepted: 09/15/2022] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND The analysis of liquid biopsies brings new opportunities in the precision oncology field. Under this context, extracellular vesicle circular RNAs (EV-circRNAs) have gained interest as biomarkers for lung cancer (LC) detection. However, standardized and robust protocols need to be developed to boost their potential in the clinical setting. Although nCounter has been used for the analysis of other liquid biopsy substrates and biomarkers, it has never been employed for EV-circRNA analysis of LC patients. METHODS EVs were isolated from early-stage LC patients (n = 36) and controls (n = 30). Different volumes of plasma, together with different number of pre-amplification cycles, were tested to reach the best nCounter outcome. Differential expression analysis of circRNAs was performed, along with the testing of different machine learning (ML) methods for the development of a prognostic signature for LC. RESULTS A combination of 500 μL of plasma input with 10 cycles of pre-amplification was selected for the rest of the study. Eight circRNAs were found upregulated in LC. Further ML analysis selected a 10-circRNA signature able to discriminate LC from controls with AUC ROC of 0.86. CONCLUSIONS This study validates the use of the nCounter platform for multiplexed EV-circRNA expression studies in LC patient samples, allowing the development of prognostic signatures.
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Affiliation(s)
- Carlos Pedraz-Valdunciel
- Department of Cancer Biology and Precision Medicine, Germans Trias I Pujol Research Institute (IGTP), Campus Can Ruti, 08916 Badalona, Spain
- Department of Biochemistry, Molecular Biology and Biomedicine, Autonomous University of Barcelona, Campus de Bellaterra, 08193 Barcelona, Spain
- Laboratory of Oncology, Pangaea Oncology, Dexeus University Hospital, 08028 Barcelona, Spain
| | - Stavros Giannoukakos
- Department of Genetics, Facultad de Ciencias, Campus Fuentenueva s/n, Universidad de Granada, 18071 Granada, Spain
| | - Ana Giménez-Capitán
- Laboratory of Oncology, Pangaea Oncology, Dexeus University Hospital, 08028 Barcelona, Spain
| | | | - Martyna Filipska
- Department of Cancer Biology and Precision Medicine, Germans Trias I Pujol Research Institute (IGTP), Campus Can Ruti, 08916 Badalona, Spain
- B Cell Biology Group, Hospital del Mar Biomedical Research Park (IMIM), Barcelona Biomedical Research Park (PRBB), 08003 Barcelona, Spain
| | - Jordi Bertran-Alamillo
- Laboratory of Oncology, Pangaea Oncology, Dexeus University Hospital, 08028 Barcelona, Spain
| | - Jillian W. P. Bracht
- Vesicle Observation Centre, Laboratory of Experimental Clinical Chemistry, Department of Clinical Chemistry, Amsterdam UMC location University of Amsterdam, 1105AZ Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, 1105AZ Amsterdam, The Netherlands
| | - Ana Drozdowskyj
- Oncology Institute Dr. Rosell (IOR), Dexeus University Institute, 08028 Barcelona, Spain
| | - Joselyn Valarezo
- Laboratory of Oncology, Pangaea Oncology, Dexeus University Hospital, 08028 Barcelona, Spain
| | | | - Alberto Fernández-Hilario
- Department of Computer Science and Artificial Intelligence, DaSCI., University of Granada, 18071 Granada, Spain
| | - Michael Hackenberg
- Department of Genetics, Facultad de Ciencias, Campus Fuentenueva s/n, Universidad de Granada, 18071 Granada, Spain
| | | | | | - Rafael Rosell
- Department of Cancer Biology and Precision Medicine, Germans Trias I Pujol Research Institute (IGTP), Campus Can Ruti, 08916 Badalona, Spain
- Oncology Institute Dr. Rosell (IOR), Dexeus University Institute, 08028 Barcelona, Spain
- Catalan Institute of Oncology, Campus Can Ruti, 08916 Badalona, Spain
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