Allocating colorectal cancer patients to different risk categories by using a five-biomarker mRNA combination in lymph node analysis
(2020) In PLoS ONE 15(2).- Abstract
Background and aims Curative surgery saves ≈50% of all patients with colorectal cancer (CRC) while remaining patients have synchronous or will develop metachronous metastases. Presently, the single most important prognostic factor is histopathological detection of disseminated tumor cells in regional lymph nodes. However, the routine method has several limitations. The aim was to identify biomarker mRNAs that could be combined in a formula that would allow better prediction of patients’ survival after surgery. Methods Screening for biomarker mRNAs overexpressed in CRC was performed by genome-wide hybridization bead array, with verification by qRT-PCR. Specific qRT-PCR assays with copy standards were developed for 5 selected genes and... (More)
Background and aims Curative surgery saves ≈50% of all patients with colorectal cancer (CRC) while remaining patients have synchronous or will develop metachronous metastases. Presently, the single most important prognostic factor is histopathological detection of disseminated tumor cells in regional lymph nodes. However, the routine method has several limitations. The aim was to identify biomarker mRNAs that could be combined in a formula that would allow better prediction of patients’ survival after surgery. Methods Screening for biomarker mRNAs overexpressed in CRC was performed by genome-wide hybridization bead array, with verification by qRT-PCR. Specific qRT-PCR assays with copy standards were developed for 5 selected genes and mRNA expression levels determined in lymph nodes from 174 CRC patients (517 nodes) and 24 control patients (118 nodes). Prognostic value of biomarker mRNAs was estimated. A cut-off was set using univariate Cox regression analysis and used for calculation of differences between patient groups in disease-free survival 12 years after surgery (Kaplan-Meier survival model) and risk for recurrent disease (Cox’s regression analysis). A formula was constructed for evaluation of the prognostic value of the biomarkers in combination. Results Two new biomarkers, SLC35D3 and POSTN with prognostic value were identified. SLC35D3 was expressed in the epithelium derived tumor cells and POSTN in fibroblasts. Combined with CEACAM5, KLK6 and MUC2 they could be used to identify risk groups. A formula was constructed using CEACAM5 as denominator for KLK6, SLC35D3 and MUC2 and 18S rRNA as denominator for POSTN. The formula yielded 5 categories (-1, 0, 1, 2, 3). Categories (-1 and 0) had good prognosis, categories (1 and 2) relatively poor prognosis and category (3) very poor prognosis. Conclusion Lymph node analysis using 5 selected biomarker mRNAs and 18S rRNA in combination allowed allocation of CRC patients to different risk categories with respect to recurrent disease.
(Less)
- author
- Olsson, Lina ; Hammarström, Marie Louise ; Israelsson, Anne ; Lindmark, Gudrun LU and Hammarström, Sten
- organization
- publishing date
- 2020
- type
- Contribution to journal
- publication status
- published
- subject
- in
- PLoS ONE
- volume
- 15
- issue
- 2
- article number
- e0229007
- publisher
- Public Library of Science (PLoS)
- external identifiers
-
- pmid:32049988
- scopus:85079339087
- ISSN
- 1932-6203
- DOI
- 10.1371/journal.pone.0229007
- language
- English
- LU publication?
- yes
- id
- 58bc1fe3-9fe4-4223-abfe-ba16233258e0
- date added to LUP
- 2021-01-13 11:35:39
- date last changed
- 2024-03-05 18:58:29
@article{58bc1fe3-9fe4-4223-abfe-ba16233258e0,
abstract = {{<p>Background and aims Curative surgery saves ≈50% of all patients with colorectal cancer (CRC) while remaining patients have synchronous or will develop metachronous metastases. Presently, the single most important prognostic factor is histopathological detection of disseminated tumor cells in regional lymph nodes. However, the routine method has several limitations. The aim was to identify biomarker mRNAs that could be combined in a formula that would allow better prediction of patients’ survival after surgery. Methods Screening for biomarker mRNAs overexpressed in CRC was performed by genome-wide hybridization bead array, with verification by qRT-PCR. Specific qRT-PCR assays with copy standards were developed for 5 selected genes and mRNA expression levels determined in lymph nodes from 174 CRC patients (517 nodes) and 24 control patients (118 nodes). Prognostic value of biomarker mRNAs was estimated. A cut-off was set using univariate Cox regression analysis and used for calculation of differences between patient groups in disease-free survival 12 years after surgery (Kaplan-Meier survival model) and risk for recurrent disease (Cox’s regression analysis). A formula was constructed for evaluation of the prognostic value of the biomarkers in combination. Results Two new biomarkers, SLC35D3 and POSTN with prognostic value were identified. SLC35D3 was expressed in the epithelium derived tumor cells and POSTN in fibroblasts. Combined with CEACAM5, KLK6 and MUC2 they could be used to identify risk groups. A formula was constructed using CEACAM5 as denominator for KLK6, SLC35D3 and MUC2 and 18S rRNA as denominator for POSTN. The formula yielded 5 categories (-1, 0, 1, 2, 3). Categories (-1 and 0) had good prognosis, categories (1 and 2) relatively poor prognosis and category (3) very poor prognosis. Conclusion Lymph node analysis using 5 selected biomarker mRNAs and 18S rRNA in combination allowed allocation of CRC patients to different risk categories with respect to recurrent disease.</p>}},
author = {{Olsson, Lina and Hammarström, Marie Louise and Israelsson, Anne and Lindmark, Gudrun and Hammarström, Sten}},
issn = {{1932-6203}},
language = {{eng}},
number = {{2}},
publisher = {{Public Library of Science (PLoS)}},
series = {{PLoS ONE}},
title = {{Allocating colorectal cancer patients to different risk categories by using a five-biomarker mRNA combination in lymph node analysis}},
url = {{http://dx.doi.org/10.1371/journal.pone.0229007}},
doi = {{10.1371/journal.pone.0229007}},
volume = {{15}},
year = {{2020}},
}