Zusammenfassung
In unterschiedlichen Tumorentitäten, wie beispielsweise dem nicht-kleinzelligen Lungenkarzinom (NSCLC), ist die (wiederholte) Gewinnung von Proben zur Diagnose und zur Untersuchung von prädiktiven Markern aufgrund der anatomischen Verhältnisse in manchen Fällen schwierig. Hier werden häufig sehr kleine oder ausschließlich zytologische Proben gewonnen. Wie bereits gezeigt wurde, lassen sich zytologische Proben exzellent für die prädiktive Markeranalytik mittels Fluoreszenz-in-situ-Hybridisierung und Next Generation Sequencing einsetzen. Auch beim zytologischen Probenmaterial ist wie beim formalinfixierten, paraffineingebetteten Gewebe eine strikte Qualitätskontrolle sowie eine Standardisierung der Laborprozesse von großer Bedeutung. Weitere Vorteile der zytologischen Proben sind die einfache und schnelle Überprüfung der Repräsentativität, zum Beispiel im Rahmen einer Rapid-on-site-Evaluation (ROSE) sowie die Möglichkeit zur Anfertigung von zwei- oder dreidimensionalen präklinischen Zellkulturmodellen. Somit kann das zytologische Probenmaterial in Ergänzung zur prädiktiven Markeranalytik direkt für funktionelle genomische Testungen, z. B. bei unklaren Variantenkonstellationen, expandiert werden. Hieraus können beispielsweise ergänzende Informationen für die Therapieentscheidung gewonnen werden, welche im molekularen Tumorboard in Zukunft hilfreich sein können.
Abstract
Predictive marker (re-)analysis of tumor material can be a real obstacle in several tumor entities, like non-small cell lung cancer (NSCLC), due to difficult anatomic conditions and small biopsy samples. As reported in the literature, cytological samples comprise excellent starting material for predictive marker analysis like fluorescence in situ hybridization and next generation sequencing. As for formalin-fixed paraffin-embedded tissue samples, rigorous quality control and standardized laboratory operating procedures are mandatory. Further advantages of cytological specimens are the rapid and straightforward inspection of representativeness, for example by rapid on-site evaluation (ROSE). Another striking advantage is that the fresh cellular material from smears and serous cavity fluids can be used for the generation of two- and three-dimensional cell culture models. Hereby, in addition to the conventional biomarker testing, complex complementary functional genomic assays can also be applied, for example, to assess the effects of multiple variants in one sample and unknown variants of tumor driver genes and tumor suppressor genes. This information may provide additional vulnerabilities of the tumor to be considered for the therapy decision, for example in the molecular tumor board.
Literatur
Bode-Lesniewska B, Cochand-Priollet B, Straccia P, Fadda G, Bongiovanni M (2019) Management of thyroid cytological material, preanalytical procedures and bio-banking. Cytopathology 30(1):7–16
Junker K, Büttner R, Langer T, Ukena D (2018) Pathological–anatomical diagnosis according to the German lung cancer guideline 2018. Pathologe 39(6):589–603
Wagner BJ, Buettner R (2020) Immunhistochemische und molekularpathologische Diagnostik von Lungenkarzinomen. Pathologe 41(1):3–13. https://doi.org/10.1007/s00292-019-00732-4
Fassunke J, Ball M, Engels M (2020) Schwerpunkt: Lunge Molekularpathologische Diagnostik an zytologischen Präparaten, S 39–45
Jain D, Roy-Chowdhuri S (2018) Molecular pathology of lung cancer cytology specimens. A concise review. Arch Pathol Lab Med 142:1127–1133
Velizheva NP, Rechsteiner MP, Wong CE, Zhong Q, Rössle M, Bode B et al (2017) Cytology smears as excellent starting material for next-generation sequencing-based molecular testing of patients with adenocarcinoma of the lung. Cancer Cytopathol 125(1):30–40
Canberk S, Engels M (2021) Cytology samples and molecular biomarker testing in lung cancer—advantages and challenges. Virchows Archiv 478:45–57
Malapelle U, Pepe F, Pisapia P, Altimari A, Bellevicine C, Brunnström H et al (2021) Reference standards for gene fusion molecular assays on cytological samples: an international validation study. J Clin Pathol. https://doi.org/10.1136/jclinpath-2021-207825
Pisapia P, Malapelle U, Roma G, Saddar S, Zheng Q, Pepe F et al (2019) Consistency and reproducibility of next-generation sequencing in cytopathology: A second worldwide ring trial study on improved cytological molecular reference specimens. Cancer Cytopathol 127(5):285–296
Tate JG, Bamford S, Jubb HC, Sondka Z, Beare DM, Bindal N et al (2019) COSMIC: the catalogue of somatic mutations in cancer. Nucleic Acids Res 47(D1):D941–D947
Landrum MJ, Lee JM, Benson M, Brown GR, Chao C, Chitipiralla S et al (2018) ClinVar: Improving access to variant interpretations and supporting evidence. Nucleic Acids Res 46(D1):D1062–D1067
Chakravarty D, Gao J, Phillips S, Kundra R, Zhang H, Wang J et al (2017) OncoKB: a precision oncology knowledge base. JCO Precis Oncol. https://doi.org/10.1200/PO.17.00011
Wagner AH, Walsh B, Mayfield G, Tamborero D, Sonkin D, Krysiak K et al (2020) A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer. Nat Genet 52(4):448–457. https://doi.org/10.1038/s41588-020-0603-8
Patterson SE, Liu R, Statz CM, Durkin D, Lakshminarayana A, Mockus SM (2016) The clinical trial landscape in oncology and connectivity of somatic mutational profiles to targeted therapies. Hum Genomics 10(1):1–13. https://doi.org/10.1186/s40246-016-0061-7
Griffith M, Spies NC, Krysiak K, McMichael JF, Coffman AC, Danos AM et al (2017) CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer. Nat Genet 49(2):170–174. https://doi.org/10.1038/ng.3774
Leichsenring J, Horak P, Kreutzfeldt S, Heining C, Christopoulos P, Volckmar AL et al (2019) Variant classification in precision oncology. Int J Cancer 145(11):2996–3010
Kato S, Kim KH, Lim HJ, Boichard A, Nikanjam M, Weihe E et al (2020) Real-world data from a molecular tumor board demonstrates improved outcomes with a precision N-of-One strategy. Nat Commun 11(1):4965. https://doi.org/10.1038/s41467-020-18613-3
Horak P, Heining C, Kreutzfeldt S, Hutter B, Mock A, Hüllein J et al (2021) Comprehensive genomic and transcriptomic analysis for guiding therapeutic decisions in patients with rare cancers. Cancer Discov 11(11):2780–2795
Westphalen BC, Bokemeyer C, Büttner R, Fröhling S, Gaidzik VI, Glimm H et al (2020) Conceptual framework for precision cancer medicine in Germany: Consensus statement of the Deutsche Krebshilfe working group ‘Molecular Diagnostics and Therapy. Eur J Cancer 135:1–7
Ootani A, Li X, Sangiorgi E, Ho QT, Ueno H, Toda S et al (2009) Sustained in vitro intestinal epithelial culture within a Wnt-dependent stem cell niche. Nat Med 15(6):701–706
Li X, Nadauld L, Ootani A, Corney DC, Pai RK, Gevaert O et al (2014) Oncogenic transformation of diverse gastrointestinal tissues in primary organoid culture. Nat Med 20(7):769–777. https://doi.org/10.1038/nm.3585
Sato T, Vries RG, Snippert HJ, van de Wetering M, Barker N, Stange DE et al (2009) Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche. Nature 459(7244):262–265. https://doi.org/10.1038/nature07935
Pauli C, Hopkins BD, Prandi D, Shaw R, Fedrizzi T, Sboner A et al (2017) Personalized in vitro and in vivo cancer models to guide precision medicine. Cancer Discov 7(5):462–477
van de Wetering M, Francies HE, Francis JM, Bounova G, Iorio F, Pronk A et al (2015) Prospective derivation of a living organoid biobank of colorectal cancer patients. Cell 161(4):933–945
Weeber F, van de Wetering M, Hoogstraat M, Dijkstra KK, Krijgsman O, Kuilman T et al (2015) Preserved genetic diversity in organoids cultured from biopsies of human colorectal cancer metastases. Proc Natl Acad Sci 112(43):201516689. https://doi.org/10.1073/pnas.1516689112
Pauli C, Puca L, Mosquera JM, Robinson BD, Beltran H, Rubin MA et al (2016) An emerging role for cytopathology in precision oncology. Cancer Cytopathol 124(3):167–173. https://doi.org/10.1002/cncy.21647
Vilgelm AE, Bergdorf K, Wolf M, Bharti V, Shattuck-Brandt R, Blevins A et al (2020) Fine-needle aspiration-based patient-derived cancer organoids. iScience 23(8):101408. https://doi.org/10.1016/j.isci.2020.101408
Pisapia P, Pepe F, Sgariglia R, Nacchio M, Russo G, Conticelli F et al (2021) Next generation sequencing in cytology. Cytopathology 32(5):588–595
Osamura RY, Matsui N, Kawashima M, Saiga H, Ogura M, Kiyuna T (2021) Digital/computational technology for molecular cytology testing: a short technical note with literature review. Acta Cytol 65(4):342–347
Ishii S, Takamatsu M, Ninomiya H, Inamura K, Horai T, Iyoda A, Honma N et al (2022) Machine learning-based gene alteration prediction model for primary lung cancer using cytologic images. Cancer Cytopathol. 130(10):812–823. https://doi.org/10.1002/cncy.22609
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Interessenkonflikt
V. Tischler gibt an, dass kein Interessenkonflikt besteht.
Für diesen Beitrag wurden von den Autor/-innen keine Studien an Menschen oder Tieren durchgeführt. Für die aufgeführten Studien gelten die jeweils dort angegebenen ethischen Richtlinien.
The supplement containing this article is not sponsored by industry.
Additional information
QR-Code scannen & Beitrag online lesen
Rights and permissions
About this article
Cite this article
Tischler, V. Molekulare Zytologie: Chancen und Herausforderungen. Pathologie 43 (Suppl 1), 130–133 (2022). https://doi.org/10.1007/s00292-022-01155-4
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00292-022-01155-4