The University of Southampton
University of Southampton Institutional Repository

Immunoglobulin Kappa C Predicts Overall Survival in Node-Negative Breast Cancer

Immunoglobulin Kappa C Predicts Overall Survival in Node-Negative Breast Cancer
Immunoglobulin Kappa C Predicts Overall Survival in Node-Negative Breast Cancer
Background: Biomarkers of the immune system are currently not used as prognostic factors in breast cancer. We analyzed
the association of the B cell/plasma cell marker immunoglobulin kappa C (IGKC) and survival of untreated node-negative breast cancer patients.
Material and Methods: IGKC expression was evaluated by immunostaining in a cohort of 335 node-negative breast cancer patients with a median follow-up of 152 months. The prognostic significance of IGKC for disease-free survival (DFS) and breast cancer-specific overall survival (OS) was evaluated with Kaplan-Meier survival analysis as well as univariate and multivariate Cox analysis adjusted for age at diagnosis, pT stage, histological grade, estrogen receptor (ER) status, progesterone receptor (PR) status, Ki-67 and human epidermal growth factor receptor 2 (HER-2) status.
Results: 160 patients (47.7%) showed strong expression of IGKC. Univariate analysis showed that IGKC was significantly
associated with DFS (P = 0.017, hazard ratio [HR] = 0.570, 95% confidence interval [CI] = 0.360–0.903) and OS (P = 0.011, HR = 0.438, 95% CI = 0.233–0.822) in the entire cohort. The significance of IGKC was especially strong in ER negative and in luminal B carcinomas. In multivariate analysis IGKC retained its significance independent of established clinical factors for DFS (P = 0.004, HR = 0.504, 95% CI = 0.315–0.804) as well as for OS (P = 0.002, HR = 0.371, 95% CI = 0.196–0.705).
Conclusion: Expression of IGKC has an independent protective impact on DFS and OS in node-negative breast cancer.
1932-6203
e44741
Chen, Zonglin
9a644bbd-31d5-4431-87e1-0ceb073e1e9e
Gerhold-Ay, Aslihan
35383108-4244-484b-afb3-df552709514c
Gebhard, Susanne
4018b17c-0f6c-4b09-8d96-a7337dd71f7e
Boehm, Daniel
82042fc7-342a-41c4-bb4b-e17fdaf02262
Solbach, Christine
089776b9-b68f-40d8-89d2-be38bb54bd7d
Lebrecht, Antje
d490a5ee-c769-432e-8735-b7a412fa10aa
Battista, Marco
a0a22944-93cb-425c-8191-491525005e50
Sicking, Isabel
4e39f360-1b65-41b8-bf9c-fe7932b18db9
Cotarelo, Christina
dbab1dc4-370d-4084-ba50-0e11951b2b05
Cadenas, Cristina
28c017c5-5bb8-4845-8d18-2867dc3a78aa
Marchan, Rosemarie
961c89f4-38bc-4a93-910c-530cd2791809
Stewart, Joanna D
e1ec9784-39cc-48ed-9f4f-2a05d25f2106
Gehrmann, Mathias
382bb683-d2d1-4cc3-a7f5-4603775d877d
Koelbl, Heinz
81a239d2-e474-471d-bc6d-329b04be4951
Hengstler, Jan G
20cdc036-fae1-4201-9c52-efcef242a955
Schmidt, Marcus
08f1cc75-7b64-45e1-b165-a499da121849
Chen, Zonglin
9a644bbd-31d5-4431-87e1-0ceb073e1e9e
Gerhold-Ay, Aslihan
35383108-4244-484b-afb3-df552709514c
Gebhard, Susanne
4018b17c-0f6c-4b09-8d96-a7337dd71f7e
Boehm, Daniel
82042fc7-342a-41c4-bb4b-e17fdaf02262
Solbach, Christine
089776b9-b68f-40d8-89d2-be38bb54bd7d
Lebrecht, Antje
d490a5ee-c769-432e-8735-b7a412fa10aa
Battista, Marco
a0a22944-93cb-425c-8191-491525005e50
Sicking, Isabel
4e39f360-1b65-41b8-bf9c-fe7932b18db9
Cotarelo, Christina
dbab1dc4-370d-4084-ba50-0e11951b2b05
Cadenas, Cristina
28c017c5-5bb8-4845-8d18-2867dc3a78aa
Marchan, Rosemarie
961c89f4-38bc-4a93-910c-530cd2791809
Stewart, Joanna D
e1ec9784-39cc-48ed-9f4f-2a05d25f2106
Gehrmann, Mathias
382bb683-d2d1-4cc3-a7f5-4603775d877d
Koelbl, Heinz
81a239d2-e474-471d-bc6d-329b04be4951
Hengstler, Jan G
20cdc036-fae1-4201-9c52-efcef242a955
Schmidt, Marcus
08f1cc75-7b64-45e1-b165-a499da121849

Chen, Zonglin, Gerhold-Ay, Aslihan, Gebhard, Susanne, Boehm, Daniel, Solbach, Christine, Lebrecht, Antje, Battista, Marco, Sicking, Isabel, Cotarelo, Christina, Cadenas, Cristina, Marchan, Rosemarie, Stewart, Joanna D, Gehrmann, Mathias, Koelbl, Heinz, Hengstler, Jan G and Schmidt, Marcus (2012) Immunoglobulin Kappa C Predicts Overall Survival in Node-Negative Breast Cancer. PLoS ONE, 7 (9), e44741. (doi:10.1371/journal.pone.0044741). (PMID:23028600)

Record type: Article

Abstract

Background: Biomarkers of the immune system are currently not used as prognostic factors in breast cancer. We analyzed
the association of the B cell/plasma cell marker immunoglobulin kappa C (IGKC) and survival of untreated node-negative breast cancer patients.
Material and Methods: IGKC expression was evaluated by immunostaining in a cohort of 335 node-negative breast cancer patients with a median follow-up of 152 months. The prognostic significance of IGKC for disease-free survival (DFS) and breast cancer-specific overall survival (OS) was evaluated with Kaplan-Meier survival analysis as well as univariate and multivariate Cox analysis adjusted for age at diagnosis, pT stage, histological grade, estrogen receptor (ER) status, progesterone receptor (PR) status, Ki-67 and human epidermal growth factor receptor 2 (HER-2) status.
Results: 160 patients (47.7%) showed strong expression of IGKC. Univariate analysis showed that IGKC was significantly
associated with DFS (P = 0.017, hazard ratio [HR] = 0.570, 95% confidence interval [CI] = 0.360–0.903) and OS (P = 0.011, HR = 0.438, 95% CI = 0.233–0.822) in the entire cohort. The significance of IGKC was especially strong in ER negative and in luminal B carcinomas. In multivariate analysis IGKC retained its significance independent of established clinical factors for DFS (P = 0.004, HR = 0.504, 95% CI = 0.315–0.804) as well as for OS (P = 0.002, HR = 0.371, 95% CI = 0.196–0.705).
Conclusion: Expression of IGKC has an independent protective impact on DFS and OS in node-negative breast cancer.

Text
Chen et al, 2012.pdf - Other
Download (2MB)

More information

Published date: 2012
Organisations: Centre for Biological Sciences

Identifiers

Local EPrints ID: 355896
URI: http://eprints.soton.ac.uk/id/eprint/355896
ISSN: 1932-6203
PURE UUID: e439478d-7953-4527-ab15-be67a15d5e00
ORCID for Joanna D Stewart: ORCID iD orcid.org/0000-0002-2608-1967

Catalogue record

Date deposited: 04 Sep 2013 16:40
Last modified: 14 Mar 2024 14:40

Export record

Altmetrics

Contributors

Author: Zonglin Chen
Author: Aslihan Gerhold-Ay
Author: Susanne Gebhard
Author: Daniel Boehm
Author: Christine Solbach
Author: Antje Lebrecht
Author: Marco Battista
Author: Isabel Sicking
Author: Christina Cotarelo
Author: Cristina Cadenas
Author: Rosemarie Marchan
Author: Joanna D Stewart ORCID iD
Author: Mathias Gehrmann
Author: Heinz Koelbl
Author: Jan G Hengstler
Author: Marcus Schmidt

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×