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  • 1
    In: Revista Portuguesa de Pneumologia, Elsevier BV, Vol. 12, No. 2 ( 2006-03), p. S9-S36
    Type of Medium: Online Resource
    ISSN: 0873-2159
    Language: Portuguese
    Publisher: Elsevier BV
    Publication Date: 2006
    detail.hit.zdb_id: 2086283-0
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  • 2
    In: Revista Portuguesa de Pneumologia, Elsevier BV, Vol. 15 ( 2009-03), p. S33-S91
    Type of Medium: Online Resource
    ISSN: 0873-2159
    Language: Portuguese
    Publisher: Elsevier BV
    Publication Date: 2009
    detail.hit.zdb_id: 2086283-0
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  • 3
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 10, No. 1 ( 2020-02-27)
    Abstract: EGFR and KRAS are the most frequently mutated genes in lung cancer, being active research topics in targeted therapy. The biopsy is the traditional method to genetically characterise a tumour. However, it is a risky procedure, painful for the patient, and, occasionally, the tumour might be inaccessible. This work aims to study and debate the nature of the relationships between imaging phenotypes and lung cancer-related mutation status. Until now, the literature has failed to point to new research directions, mainly consisting of results-oriented works in a field where there is still not enough available data to train clinically viable models. We intend to open a discussion about critical points and to present new possibilities for future radiogenomics studies. We conducted high-dimensional data visualisation and developed classifiers, which allowed us to analyse the results for EGFR and KRAS biological markers according to different combinations of input features. We show that EGFR mutation status might be correlated to CT scans imaging phenotypes; however, the same does not seem to hold for KRAS mutation status. Also, the experiments suggest that the best way to approach this problem is by combining nodule-related features with features from other lung structures.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
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  • 4
    Online Resource
    Online Resource
    Elsevier BV ; 2010
    In:  Revista Portuguesa de Pneumologia Vol. 16, No. 2 ( 2010-03), p. 321-329
    In: Revista Portuguesa de Pneumologia, Elsevier BV, Vol. 16, No. 2 ( 2010-03), p. 321-329
    Type of Medium: Online Resource
    ISSN: 0873-2159
    Language: Portuguese
    Publisher: Elsevier BV
    Publication Date: 2010
    detail.hit.zdb_id: 2086283-0
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  • 5
    In: Revista Portuguesa de Pneumologia, Elsevier BV, Vol. 2, No. 2 ( 1996-03), p. 107-117
    Type of Medium: Online Resource
    ISSN: 0873-2159
    Language: Portuguese
    Publisher: Elsevier BV
    Publication Date: 1996
    detail.hit.zdb_id: 2086283-0
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  • 6
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 11 ( 2021-4-16)
    Abstract: Liquid biopsy is an emerging technology with a potential role in the screening and early detection of lung cancer. Several liquid biopsy-derived biomarkers have been identified and are currently under ongoing investigation. In this article, we review the available data on the use of circulating biomarkers for the early detection of lung cancer, focusing on the circulating tumor cells, circulating cell-free DNA, circulating micro-RNAs, tumor-derived exosomes, and tumor-educated platelets, providing an overview of future potential applicability in the clinical practice. While several biomarkers have shown exciting results, diagnostic performance and clinical applicability is still limited. The combination of different biomarkers, as well as their combination with other diagnostic tools show great promise, although further research is still required to define and validate the role of liquid biopsies in clinical practice.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
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  • 7
    In: Applied Sciences, MDPI AG, Vol. 11, No. 7 ( 2021-04-06), p. 3273-
    Abstract: The evolution of personalized medicine has changed the therapeutic strategy from classical chemotherapy and radiotherapy to a genetic modification targeted therapy, and although biopsy is the traditional method to genetically characterize lung cancer tumor, it is an invasive and painful procedure for the patient. Nodule image features extracted from computed tomography (CT) scans have been used to create machine learning models that predict gene mutation status in a noninvasive, fast, and easy-to-use manner. However, recent studies have shown that radiomic features extracted from an extended region of interest (ROI) beyond the tumor, might be more relevant to predict the mutation status in lung cancer, and consequently may be used to significantly decrease the mortality rate of patients battling this condition. In this work, we investigated the relation between image phenotypes and the mutation status of Epidermal Growth Factor Receptor (EGFR), the most frequently mutated gene in lung cancer with several approved targeted-therapies, using radiomic features extracted from the lung containing the nodule. A variety of linear, nonlinear, and ensemble predictive classification models, along with several feature selection methods, were used to classify the binary outcome of wild-type or mutant EGFR mutation status. The results show that a comprehensive approach using a ROI that included the lung with nodule can capture relevant information and successfully predict the EGFR mutation status with increased performance compared to local nodule analyses. Linear Support Vector Machine, Elastic Net, and Logistic Regression, combined with the Principal Component Analysis feature selection method implemented with 70% of variance in the feature set, were the best-performing classifiers, reaching Area Under the Curve (AUC) values ranging from 0.725 to 0.737. This approach that exploits a holistic analysis indicates that information from more extensive regions of the lung containing the nodule allows a more complete lung cancer characterization and should be considered in future radiogenomic studies.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
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  • 8
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2016
    In:  Cancer Research Vol. 76, No. 14_Supplement ( 2016-07-15), p. 488-488
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 76, No. 14_Supplement ( 2016-07-15), p. 488-488
    Abstract: Tumor-specific (somatic) mutations in plasma can serve as biomarkers for tumor detection, monitor tumor response to specific therapies, detect residual disease after surgery, and long-term follow-up. The intrinsic low abundance of circulating cell-free tumor DNA (cfDNA) makes the detection and quantification of such mutations in plasma a challenging task. This study aimed to establish a comprehensive strategy to be used in the detection of clinically relevant somatic mutations in plasma of lung cancer patients both at diagnosis and during follow-up of disease. Plasma samples from healthy controls were used to isolate cfDNA and to optimize the experimental approach. A custom multiplex PCR panel was designed to target 420 unique genetic variants. To cover a broad range (0.0 -100%) of variant allele fractions (VAF), as expected for somatic mutations in the plasma of cancer patients, the cfDNA samples from the controls were mixed at five different ratios and sequenced using five different levels of coverage. In order to evaluate our strategy, plasma samples obtained at different stages of disease were collected from a group of 100 lung cancer patients and used to isolate cfDNA. The mean treatment follow up time was 6 months with a minimum of 1 and a maximum of 23 months. Different enrichment strategies where tested. All amplified products were used to prepare libraries and sequenced using the Ion PGM system. The QuantStudio 3D Digital PCR System was used to confirm selected results. Our controlled data set enabled us to define VAF, allele depth and allele quality score cutoffs for a reliable detection of low VAF in cfDNA. For variants present at VAF ≥5%, a sensitivity of 100% was achieved at ≥500x coverage. At ≥1000x coverage, more than 94% of the variants present at VAF & lt;5% were successfully detected with an average sequencing quality score & gt;Q30. In the plasma isolated from lung cancer patients, tumor derived genetic mutations could be identified in as little as 10ng of cfDNA. Mutations identified in cfDNA mirrored the mutations identified in tumor biopsies. Mutations with VAF as low as 0.1% could be detected in cfDNA and confirmed using Digital PCR. The changes in tumor-specific mutations in cfDNA was then correlated with the clinical follow up of the patients. Response to therapy, including resistance, could be observed by tracking specific mutations in cfDNA and the detection of tumor relapse could be anticipated up to two months using cfDNA when compared to standard methodologies. In conclusion, the comprehensiveness and speed of the NGS methodology, combined with the high sensitivity of detection, delivered an experimental protocol for the detection of somatic mutations in cfDNA for non-invasive real time therapy response monitoring of cancer patients. This strategy can be implemented in any molecular pathology laboratory with clear benefits for the management of cancer patients. Citation Format: Jose L. Costa, Gabriela Fernandes, Joana Reis, Miguel Silva, Venceslau Hespanhol, José C. Machado. Detection of somatic mutations in plasma allows for non-invasive real-time therapy response monitoring of lung cancer patients. [abstract] . In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 488.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2016
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  • 9
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2015
    In:  Cancer Research Vol. 75, No. 15_Supplement ( 2015-08-01), p. 4930-4930
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 75, No. 15_Supplement ( 2015-08-01), p. 4930-4930
    Abstract: The identification of mutations in circulating tumor DNA (ctDNA) can serve as a biomarker for non-invasive diagnosis and real time therapeutic monitoring. Although next generation sequencing (NGS) is a promising technology, the intrinsic low abundance of ctDNA in the high background of wild-type cell free DNA (cfDNA) makes the detection and quantification of such mutations in plasma a challenging task. This study aims to measure the performance of NGS analysis when applied to the identification of somatic mutations in plasma samples. Plasma samples from two healthy controls were used to isolate cfDNA. Constitutional genomic DNA from these controls was previously genotyped using the Human OmniExpress BeadChip. A custom multiplex PCR panel was designed to target 420 unique variants. To cover a broad range (0.5%-100%) of minor allele frequencies (MAF), as expected for somatic mutations in the plasma of cancer patients, the cfDNA samples from the two controls were mixed at five different rations (7:25, 1:6, 1:8, 1:20 and 1:100). Because sequence coverage is a key driver of accuracy, 5 different coverage profiles (100x, 500x, 1000x, 2000x and 5000x) were established for each of the cfDNA pools. On total 25 libraries were generated, pooled and sequenced with the Ion PGM system. Ion Reporter software was used for data analysis. The observed MAFs were compared with expected results for all the variants of each cfDNA pool. Median exon sequencing coverage of 133x, 650x, 1312x, 2628x and 5466x was obtained for each of the 5 cfDNA pools, with & gt;99% of the amplicons covered. Overall base substitution and indel detection performance was high ( & gt;95% of the variants were detected across the different coverage levels). A direct correlation between expected and observed MAFs for the known variants was observed. For variants present at MAF ≥5%, a sensitivity of 91.4% and 100% was achieved at 100x and ≥500x coverage levels, respectively. For variants with 5% ≤ MAF ≤ 10% at 100x of coverage, the average quality score was & lt;Q20. For variants occurring at low MAF ( & lt;5%) the detection sensitivity and the quality score dropped as coverage decreased. At 1000x coverage and above, more than 94% of the variants present at MAF & lt;5% were successfully detected with an average quality score & gt;Q30. Overall, positive predictive value remained high ( & gt;98%), with an average of 5 false-positive calls across the full coverage range. To validate our approach we analyzed 10 pairs of primary tumour/plasma samples. All cases carried known mutations of the EGFR gene detected during routine analysis. We were able to detect the corresponding mutation in the plasma samples in all cases. MAF in plasma samples ranged from 3% to 85%. Here we demonstrate that NGS can be used to detect mutations in cfDNA. Our approach with controlled data sets also enabled us to define allele frequency, allele depth, and allele quality score cutoffs for a reliable detection of low MAF variants in ctDNA. Citation Format: Ana Justino, Gabriela Fernandes, Ana Barroso, Barbara Parente, Venceslau Hespanhol, Jose C. Machado, Jose L. Costa. Next generation sequencing performance for the detection of mutations in plasma cell free DNA. [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 4930. doi:10.1158/1538-7445.AM2015-4930
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2015
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    detail.hit.zdb_id: 410466-3
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  • 10
    Online Resource
    Online Resource
    Elsevier BV ; 2017
    In:  Archivos de Bronconeumología (English Edition) Vol. 53, No. 9 ( 2017-09), p. 530-531
    In: Archivos de Bronconeumología (English Edition), Elsevier BV, Vol. 53, No. 9 ( 2017-09), p. 530-531
    Type of Medium: Online Resource
    ISSN: 1579-2129
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2017
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    detail.hit.zdb_id: 2084843-2
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