Digitally quantified CD8+ cells: the best candidate marker for an immune cell score in non-small cell lung cancer?. (9th October 2020)
- Record Type:
- Journal Article
- Title:
- Digitally quantified CD8+ cells: the best candidate marker for an immune cell score in non-small cell lung cancer?. (9th October 2020)
- Main Title:
- Digitally quantified CD8+ cells: the best candidate marker for an immune cell score in non-small cell lung cancer?
- Authors:
- Kilvaer, Thomas K
Paulsen, Erna-Elise
Andersen, Sigve
Rakaee, Mehrdad
Bremnes, Roy M
Busund, Lill-Tove Rasmussen
Donnem, Tom - Abstract:
- Abstract: The TNM classification is well established as a state-of-the-art prognostic and treatment-decision-making tool for non-small cell lung cancer (NSCLC) patients. However, incorporation of biological data may hone the TNM system. This article focuses on choosing and incorporating subsets of tissue-infiltrating lymphocyte (TIL), detected by specific immunohistochemistry and automatically quantified by open source software, into a TNM-Immune cell score (TNM-I) for NSCLC. We use common markers (CD3, CD4, CD8, CD20 and CD45RO) of TILs to identify TIL subsets in tissue micro-arrays comprising tumor tissue from 553 patients resected for primary NSCLC. The number of TILs is automatically quantified using open source software (QuPath). Their prognostic efficacy, alone and within a TNM-I model, is evaluated in all patients and histological subgroups. Compared with previous manual semi-quantitative scoring of TILs in the same cohort, the present digital quantification proved superior. As a proof-of-concept, we construct a TNM-I, using TNM categories and the CD8 + TIL density. The TNM-I is an independent prognosticator of favorable diagnosis in both the overall cohort and in the main histological subgroups. In conclusion, CD8 + TIL density is the most promising candidate marker for a TNM-I in NSCLC. The prognostic efficacy of the CD8 + TIL density is strongest in lung squamous cell carcinomas, whereas both CD8 + TILs and CD20 + TILs, or a combination of these, may be candidatesAbstract: The TNM classification is well established as a state-of-the-art prognostic and treatment-decision-making tool for non-small cell lung cancer (NSCLC) patients. However, incorporation of biological data may hone the TNM system. This article focuses on choosing and incorporating subsets of tissue-infiltrating lymphocyte (TIL), detected by specific immunohistochemistry and automatically quantified by open source software, into a TNM-Immune cell score (TNM-I) for NSCLC. We use common markers (CD3, CD4, CD8, CD20 and CD45RO) of TILs to identify TIL subsets in tissue micro-arrays comprising tumor tissue from 553 patients resected for primary NSCLC. The number of TILs is automatically quantified using open source software (QuPath). Their prognostic efficacy, alone and within a TNM-I model, is evaluated in all patients and histological subgroups. Compared with previous manual semi-quantitative scoring of TILs in the same cohort, the present digital quantification proved superior. As a proof-of-concept, we construct a TNM-I, using TNM categories and the CD8 + TIL density. The TNM-I is an independent prognosticator of favorable diagnosis in both the overall cohort and in the main histological subgroups. In conclusion, CD8 + TIL density is the most promising candidate marker for a TNM-I in NSCLC. The prognostic efficacy of the CD8 + TIL density is strongest in lung squamous cell carcinomas, whereas both CD8 + TILs and CD20 + TILs, or a combination of these, may be candidates for a TNM-I in lung adenocarcinoma. Furthermore, based on the presented results, digital quantification is the preferred method for scoring TILs in the future. Abstract : Digitally quantified CD8 + TIL density is a positive prognosticator for NSCLC, which combines with pStage into a TNM-Immune cell score (TNM-I). The combined score provides superior prognostication versus TNM alone. Moreover, histological adaptation of the TNM-I is likely further to increase its prognostic efficacy. … (more)
- Is Part Of:
- Carcinogenesis. Volume 41:Number 12(2020)
- Journal:
- Carcinogenesis
- Issue:
- Volume 41:Number 12(2020)
- Issue Display:
- Volume 41, Issue 12 (2020)
- Year:
- 2020
- Volume:
- 41
- Issue:
- 12
- Issue Sort Value:
- 2020-0041-0012-0000
- Page Start:
- 1671
- Page End:
- 1681
- Publication Date:
- 2020-10-09
- Subjects:
- Carcinogenesis -- Periodicals
Cancer -- Genetic aspects -- Periodicals
Cancer -- Prevention -- Periodicals
Cancer -- Periodicals
616.994071 - Journal URLs:
- http://carcin.oupjournals.org ↗
http://carcin.oxfordjournals.org ↗
http://www.ingenta.com/journals/browse/oup/carcin?mode=direct ↗
http://ukcatalogue.oup.com/ ↗
http://firstsearch.oclc.org ↗ - DOI:
- 10.1093/carcin/bgaa105 ↗
- Languages:
- English
- ISSNs:
- 0143-3334
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3051.007000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 15728.xml