The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Primary resistance to osimertinib due to SCLC transformation: Issue of T790M determination on liquid re-biopsy
Abstract
Objectives EGFR T790M mutation is the most common mechanism of resistance to first-/second-generation EGFR tyrosine kinase inhibitors (TKIs) in non-small cell lung cancer (NSCLC) and could be overcome by third-generation EGFR-TKIs, such as osimertinib. Liquid biopsy, a non-invasive technique used to test the presence of the resistant mutation, may help avoiding tissue re-biopsy. However, analysing only circulating-free DNA, information about other less frequent and coexisting resistance mechanisms may remain unrevealed.Materials and methods All patients reported in this series participated in the ASTRIS trial, a real world treatment study testing the efficacy of osimertinib (80mg os die) in advanced T790M-positive NSCLC progressed to prior EGFR-TKI. Patients were considered eligible to osimertinib if T790M positive on tissue or plasma samples. In our patients, EGFR molecular testing on blood sample was conducted with digital droplet PCR (ddPCR).Results We report our experience of five patients treated with osimertinib after T790M detection on liquid biopsy that presented a disease progression at first tumor assessment mediated by SCLC transformation, as evidenced at tissue re-biopsies. All patients showed low ratio T790M/activating mutation in the blood before osimertinib (lower than 0.03). For three patients, EGFR mutational analysis was T790M-negative when re-assessed by using a less sensitive method (therascreen®) on the same liquid biopsy sample analysed by ddPCR before osimertinib therapy.Conclusion Although liquid biopsy is a relevant tool to diagnose T790M presence in NSCLC patients resistant to EGFR-TKI, in case of a low ratio T790M/activating mutation, tissue biopsy should be considered to exclude the presence of SCLC transformation and/or other concomitant resistance mechanisms.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“However, these noninvasive liquid biopsies cannot identify the full spectrum of mutations possibly affecting clinical outcomes due to the limited number of genes analyzed (typically 68 to 70 genes) or other concomitant resistant mechanisms.9,27,30”
From Concurrent Genetic Alterations Predict the Progression to Target Therapy in EGFR-Mutated Advanced NSCLC (2019) · cites this paper as [30]
Citations
Cites
Genotypic and Histological Evolution of Lung Cancers Acquiring Resistance to EGFR Inhibitors
Sequist, L. V., Waltman, B. A., Dias-Santagata, D., Digumarthy, S., Turke, A. B., Fidias, P., Bergethon, K., Shaw, A. T., Gettinger, S., Cosper, A. K., et al. (2011) · Science Translational Medicine · doi:10.1126/scitranslmed.3002003 · Cited by 3,499
Osimertinib or Platinum–Pemetrexed in EGFR T790M–Positive Lung Cancer
Mok, T. S., Wu, Y.-L., Ahn, M.-J., Garassino, M. C., Kim, H. R., Ramalingam, S. S., Shepherd, F. A., He, Y., Akamatsu, H., Theelen, W. S. M. E., et al. (2017) · New England Journal of Medicine · doi:10.1056/nejmoa1612674 · Cited by 3,379
Novello, S., Barlesi, F., Califano, R., Cufer, T., Ekman, S., Levra, M. G., Kerr, K., Popat, S., Reck, M., Senan, S., et al. (2016) · Annals of Oncology · doi:10.1093/annonc/mdw326 · Cited by 2,631
Yu, H. A., Arcila, M. E., Rekhtman, N., Sima, C. S., Zakowski, M. F., Pao, W., Kris, M. G., Miller, V. A., Ladanyi, M., & Riely, G. J. (2013) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-12-2246 · Cited by 2,454
AZD9291 in EGFR Inhibitor–Resistant Non–Small-Cell Lung Cancer
Jänne, P. A., Yang, J. C.-H., Kim, D.-W., Planchard, D., Ohe, Y., Ramalingam, S. S., Ahn, M.-J., Kim, S.-W., Su, W.-C., Horn, L., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1411817 · Cited by 2,116
Oser, M. G., Niederst, M. J., Sequist, L. V. D., & Engelman, J. A. (2015) · The Lancet Oncology · doi:10.1016/s1470-2045(14)71180-5 · Cited by 974
Oxnard, G. R., Thress, K. S., Alden, R. S., Lawrance, R., Paweletz, C. P., Cantarini, M., Yang, J. C.-H., Barrett, J. C., & Jänne, P. A. (2016) · Journal of Clinical Oncology · doi:10.1200/jco.2016.66.7162 · Cited by 850
Oxnard, G. R., Paweletz, C. P., Kuang, Y., Mach, S. L., O'Connell, A., Messineo, M. M., Luke, J. J., Butaney, M., Kirschmeier, P., Jackman, D. M., et al. (2014) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-13-2482 · Cited by 786
Chabon, J. J., Simmons, A. D., Lovejoy, A. F., Esfahani, M. S., Newman, A. M., Haringsma, H. J., Kurtz, D. M., Stehr, H., Scherer, F., Karlovich, C., et al. (2016) · Nature Communications · doi:10.1038/ncomms11815 · Cited by 657
Goss, G. D., Tsai, C., Shepherd, F. A., Bazhenova, L. A., Lee, J. S., Chang, G., Crinò, L., Satouchi, M., Chu, Q. S.-C., Hida, T., et al. (2016) · The Lancet Oncology · doi:10.1016/s1470-2045(16)30508-3 · Cited by 654
Flagged first, then by citations
Cited by
Sorted by citations
Items 101–106 of 106
Biomarkers for response to immune checkpoint inhibitors in metastatic melanoma
Wind, T. T. (2024) · University of Groningen research database (University of Groningen / Centre for Information Technology) · doi:10.33612/diss.1065420649
Li, W., Zhang, K., Raúl, M. L., Rotter-Maskowitz, A., Nejman, D., Potempa, J., Straussman, R., & Raz, D. J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.08.681060
Chitneni, E., Venugopal, A., Okorie, C. O., George, A. T., Arya, A., Arias, D., Yasin, O., de Souza, L. C. P., Afshan, R., & Dave, V. A. (2026) · Cureus · doi:10.7759/cureus.108302
Winardi, W., Mitsuishi, Y., Matsuda, H., Takahashi, F., Hayakawa, D., Kanamori, K., Nakamura, I., Wirawan, A., Hidayat, M., Wibowo, A., et al. (2026) · Thoracic Cancer · doi:10.1111/1759-7714.70360
Metadata
- Authors
- Minari, R., Bordi, P., Del Re, M., Facchinetti, F., Mazzoni, F., Barbieri, F., Camerini, A., Comin, C. E., Gnetti, L., Azzoni, C., Nizzoli, R., Bortesi, B., Rofi, E., Petreni, P., Campanini, N., Rossi, G., Danesi, R., & Tiseo, M.
- Affiliations
- University of Parma (IT)
- Azienda Ospedaliero-Universitaria Careggi (IT)
- Azienda Ospedaliero-Universitaria di Modena (IT)
- Ospedale Versilia (IT)
- University of Florence (IT)
- Ospedale di Parma (IT)
- University of Pisa (IT)
- Azienda USL della Valle d’Aosta (IT)
- Corresponding author
- Tiseo, M.
- ORCID
- Venue
- Lung Cancer
- Publisher
- Elsevier BV
- Published
- 2018-01
- Volume
- 115
- Pages
- 21-27
- ISSN
- 0169-5002 (ISSN-L)
- OpenAlex
- W2769241338
- Cited by
- 105
- References
- 25
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 10 · 2023: 8 · 2022: 11 · 2021: 18 · 2020: 16 · 2019: 18 · 2018: 14
- FWCI
- 10.86
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Lung Cancer (publishedVersion)
- PubMed (publishedVersion)
- CINECA IRIS Institutial research information system (University of Pisa) (submittedVersion)
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Health Sciences › Medicine › Oncology › HER2/EGFR in Cancer Research
- Keywords
- osimertinib, T790M mutation, small cell lung cancer transformation, liquid biopsy, circulating tumor DNA, EGFR tyrosine kinase inhibitors, treatment resistance, droplet digital PCR, non-small cell lung cancer
- MeSH terms
- Acrylamides, Aged, Aniline Compounds, Antineoplastic Agents, Biopsy, Carcinoma, Non-Small-Cell Lung, Cell Transformation, Neoplastic, DNA Mutational Analysis, Female, Humans, Indoles, Lung Neoplasms, Male, Middle Aged, Mutation, Neoplasm Staging, Piperazines, Pyrimidines, Drug Resistance, Neoplasm, Protein Kinase Inhibitors, ErbB Receptors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review