The challenge of NSCLC diagnosis and predictive analysis on small samples. Practical approach of a working group
(2012) In Lung Cancer 76(1). p.1-18- Abstract
- Until recently, the division of pulmonary carcinomas into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) was adequate for therapy selection. Due to the emergence of new treatment options subtyping of NSCLC and predictive testing have become mandatory. A practical approach to the new requirements involving interaction between pulmonologist, oncologist and molecular pathology to optimize patient care is described. The diagnosis of lung cancer involves (i) the identification and complete classification of malignancy, (ii) immunohistochemistry is used to predict the likely NSCLC subtype (squamous cell vs. adenocarcinoma), as in small diagnostic samples specific subtyping is frequently on morphological grounds alone not... (More)
- Until recently, the division of pulmonary carcinomas into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) was adequate for therapy selection. Due to the emergence of new treatment options subtyping of NSCLC and predictive testing have become mandatory. A practical approach to the new requirements involving interaction between pulmonologist, oncologist and molecular pathology to optimize patient care is described. The diagnosis of lung cancer involves (i) the identification and complete classification of malignancy, (ii) immunohistochemistry is used to predict the likely NSCLC subtype (squamous cell vs. adenocarcinoma), as in small diagnostic samples specific subtyping is frequently on morphological grounds alone not feasible (NSCLC-NOS), (iii) molecular testing. To allow the extended diagnostic and predictive examination (i) tissue sampling should be maximized whenever feasible and deemed clinically safe, reducing the need for re-biopsy for additional studies and (ii) tissue handling, processing and sectioning should be optimized. Complex diagnostic algorithms are emerging, which will require close dialogue and understanding between pulmonologists and others who are closely involved in tissue acquisition, pathologists and oncologists who will ultimately, with the patient, make treatment decisions. Personalized medicine not only means the choice of treatment tailored to the individual patient, but also reflects the need to consider how investigative and diagnostic strategies must also be planned according to individual tumour characteristics. (C) 2011 Elsevier Ireland Ltd. All rights reserved. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2574871
- author
- organization
- publishing date
- 2012
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Non-small cell lung carcinoma, Biopsy, Diagnosis, Pathology, Prediction, Mutation, Immunohistochemistry, Review
- in
- Lung Cancer
- volume
- 76
- issue
- 1
- pages
- 1 - 18
- publisher
- Elsevier
- external identifiers
-
- wos:000302584600001
- scopus:84858005348
- pmid:22138001
- ISSN
- 1872-8332
- DOI
- 10.1016/j.lungcan.2011.10.017
- language
- English
- LU publication?
- yes
- additional info
- The information about affiliations in this record was updated in December 2015. The record was previously connected to the following departments: Pathology, (Lund) (013030000)
- id
- 5694de64-f7d3-4eb8-a928-d1fc7e38b1aa (old id 2574871)
- date added to LUP
- 2016-04-01 10:52:06
- date last changed
- 2022-04-28 01:56:46
@article{5694de64-f7d3-4eb8-a928-d1fc7e38b1aa, abstract = {{Until recently, the division of pulmonary carcinomas into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) was adequate for therapy selection. Due to the emergence of new treatment options subtyping of NSCLC and predictive testing have become mandatory. A practical approach to the new requirements involving interaction between pulmonologist, oncologist and molecular pathology to optimize patient care is described. The diagnosis of lung cancer involves (i) the identification and complete classification of malignancy, (ii) immunohistochemistry is used to predict the likely NSCLC subtype (squamous cell vs. adenocarcinoma), as in small diagnostic samples specific subtyping is frequently on morphological grounds alone not feasible (NSCLC-NOS), (iii) molecular testing. To allow the extended diagnostic and predictive examination (i) tissue sampling should be maximized whenever feasible and deemed clinically safe, reducing the need for re-biopsy for additional studies and (ii) tissue handling, processing and sectioning should be optimized. Complex diagnostic algorithms are emerging, which will require close dialogue and understanding between pulmonologists and others who are closely involved in tissue acquisition, pathologists and oncologists who will ultimately, with the patient, make treatment decisions. Personalized medicine not only means the choice of treatment tailored to the individual patient, but also reflects the need to consider how investigative and diagnostic strategies must also be planned according to individual tumour characteristics. (C) 2011 Elsevier Ireland Ltd. All rights reserved.}}, author = {{Thunnissen, Erik and Kerr, Keith M. and Herth, Felix J. F. and Lantuejoul, Sylvie and Papotti, Mauro and Rintoul, Robert C. and Rossi, Giulio and Skov, Birgit G. and Weynand, Birgit and Bubendorf, Lukas and Katrien, Grunberg and Johansson, Leif and Lopez-Rios, Fernando and Ninane, Vincent and Olszewski, Wlodzimierz and Popper, Helmut and Jaume, Sauleda and Schnabel, Philipp and Thiberville, Luc and Laenger, Florian}}, issn = {{1872-8332}}, keywords = {{Non-small cell lung carcinoma; Biopsy; Diagnosis; Pathology; Prediction; Mutation; Immunohistochemistry; Review}}, language = {{eng}}, number = {{1}}, pages = {{1--18}}, publisher = {{Elsevier}}, series = {{Lung Cancer}}, title = {{The challenge of NSCLC diagnosis and predictive analysis on small samples. Practical approach of a working group}}, url = {{http://dx.doi.org/10.1016/j.lungcan.2011.10.017}}, doi = {{10.1016/j.lungcan.2011.10.017}}, volume = {{76}}, year = {{2012}}, }