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CD68 and CD83 immune populations in non-metastatic axillary lymph nodes are of prognostic value for the survival and relapse of breast cancer patients

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Abstract

Background

The foremost cause of death of breast cancer (BC) patients is metastasis, and the first site to which BC predominantly metastasizes is the axillary lymph node (ALN). Thus, ALN status is a key prognostic indicator at diagnosis. The immune system has an essential role in cancer progression and dissemination, so its evaluation in ALNs could have significant applications. In the present study we aimed to investigate the association of clinical-pathological and immune variables in the primary tumour and non-metastatic ALNs (ALNs–) of a cohort of luminal A and triple-negative BC (TNBC) patients with cancer-specific survival (CSS) and time to progression (TTP).

Methods

We analysed the differences in the variables between patients with different outcomes, created univariate and multivariate Cox regression models, validated them by bootstrapping and multiple imputation of missing data techniques, and used Kaplan–Meier survival curves for a 10-years follow-up.

Results

We found some clinical-pathological variables at diagnosis (tumour diameter, TNBC molecular profile and presence of ALN metastasis), and the levels of several immune markers in the two studied sites, to be associated with worse CSS and TTP. Nevertheless, only CD68 and CD83 in ALNs– were confirmed as independent prognostic factors for TTP.

Conclusions

The study identified the importance of macrophage and dendritic cell markers as prognostic factors of relapse for BC. We highlight the importance of studying the immune response in ALNs–, which could be relevant to the prediction of BC patients’ outcome.

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Availability of data and material

Datasets generated and analysed during this study are available from the corresponding authors upon reasonable request.

Abbreviations

ALN:

Axillary lymph node

ALN– :

Non-metastatic axillary lymph node

ALN+ :

Metastatic axillary lymph node

AUC:

Area under the curve

BC:

Breast cancer

CI:

Confidence interval

CSS:

Cancer-specific survival

DAB:

Diaminobenzidine

DC:

Dendritic cell

ER:

Oestrogen receptor

HER2:

Human epidermal growth factor receptor 2

HR:

Hazard ratio

HTVC:

Hospital de Tortosa Verge de la Cinta

Ki67:

Proliferation index

NK:

Natural killer

PR:

Progesterone receptor

ROC:

Receiver-operating characteristic

STROBE:

Strengthening the Reporting of Observational Studies in Epidemiology

TMA:

Tissue microarray

TNBC:

Triple-negative breast cancer

TTP:

Time to progression

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Acknowledgements

We thank Barbara Tomàs, María del Mar Barbera, Noelia Burgues, Ainhoa Montserrat, Almudena Nagera, Montse Salvadó, Ana Suñé, Beatriu Domenech, Anna Guasch, Marita Curto, and Marc Iniesta for their skilful technical assistance.

Funding

Carlos López is the guarantor of this work and, as such, had full access to all the data in the study. He takes responsibility for the integrity of the data and the accuracy of the data analysis. This work was funded by projects PI11/0488 (Principal Investigator: C.L.) and PI13/02501 (Principal investigator: M.L.) of the Institute of Health Carlos III, which is the main public research body that funds, manages and carries out biomedical research in Spain. It was co-funded by the European Union European Regional Development Fund. It was also supported by the Project AIDPATH FP7-PEOPLE Project ID: 612471 (Principal Investigator: G.B.). The biopsies were selected from the Banc de Tumors of the HTVC, member of the Xarxa de Bancs de Tumors de Catalunya (XBTC), sponsored by the Oncology Master Plan for Catalonia (Pla Director d’Oncologia de Catalunya).

Author information

Authors and Affiliations

  1. Department of Pathology, Oncological Pathology and Bioinformatics Research Group, Hospital de Tortosa Verge de la Cinta, ICS, IISPV, C/Esplanetes no 14, 43500, Tortosa, Spain

    Carlos López, Ramón Bosch, Andrea Gras Navarro, Esther Sauras Colón, Júlia Casanova Ribes, Daniel Mata & Marylène Lejeune

  2. Universitat Rovira i Virgili (URV) - Campus Terres de l’Ebre, Avinguda Remolins no 13-15, 43500, Tortosa, Spain

    Carlos López, Andrea Gras Navarro, Silvia Reverté-Villarroya & Marylène Lejeune

  3. Laboratory of Processing and Analysis of Microscopic Images, Polish Academy of Sciences (IBIB PAN), Nalęcz Institute of Biocybernetics and Biomedical Engineering, Ks. Trojdena 4 St., 02-109, Warsaw, Poland

    Anna Korzynska & Lukasz Roszkowiak

  4. Department of Pathology, Hospital Universitario Puerta del Mar, Avda. Ana de Viya, 21, 11009, Cádiz, Spain

    Marcial García-Rojo

  5. VISILAB, Universidad de Castilla-La Mancha, Av. Camilo José Cela, s/n, 13071, Ciudad Real, Spain

    Gloria Bueno

  6. Department of Pathology, Hospital Universitari Joan XXIII, C/Dr. Mallafrè Guasch, 4, 43005, Tarragona, Spain

    Joan Francesc García-Fontgivell & Salomé Martínez González

  7. Institut d’Investigació Sanitària Pere Virgili, Radiation Oncology Department, Universitat Rovira i Virgili, Hospital Universitari Sant Joan de Reus, Reus, Spain

    Meritxell Arenas & Junior Gómez

  8. Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol), Gran Via Corts Catalanes, 587, 08007, Barcelona, Spain

    Albert Roso

  9. Knowledge Management Department, Hospital de Tortosa Verge de la Cinta, ICS, IISPV, C/Esplanetes no 14, 43500, Tortosa, Spain

    Marta Berenguer & Silvia Reverté-Villarroya

  10. Department of Oncology, Hospital de Tortosa Verge de la Cinta, ICS, IISPV, C/Esplanetes no 14, 43500, Tortosa, Spain

    Montserrat Llobera

  11. Informatics Department, Hospital de Tortosa Verge de la Cinta, ICS, IISPV, C/Esplanetes no 14, 43500, Tortosa, Spain

    Jordi Baucells

Authors
  1. Carlos López
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  2. Ramón Bosch
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  3. Anna Korzynska
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  4. Marcial García-Rojo
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  5. Gloria Bueno
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  6. Joan Francesc García-Fontgivell
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  7. Salomé Martínez González
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  8. Andrea Gras Navarro
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  9. Esther Sauras Colón
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  10. Júlia Casanova Ribes
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  11. Lukasz Roszkowiak
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  12. Daniel Mata
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  13. Meritxell Arenas
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  14. Junior Gómez
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  15. Albert Roso
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  16. Marta Berenguer
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  17. Silvia Reverté-Villarroya
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  18. Montserrat Llobera
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  19. Jordi Baucells
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  20. Marylène Lejeune
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Contributions

CL, RB, DM and ML designed the study and selected the sample. CL, JFGF, SMG, JCR, MA, JG, MB, SRV, MLL and ML collected data and reviewed the clinical records. CL, ESC, JCR and ML processed the samples. CL, AK, MGR, GB, LR and JB digitized the samples and developed image analysis procedures. CL, AGN, ESC, AR and ML did the statistical analysis. CL, AGN, ESC and ML designed the figures. All the authors have read and reviewed the article and made significant contributions to the interpretation of the data.

Corresponding authors

Correspondence to Carlos López or Esther Sauras Colón.

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The authors have no conflicts of interest to declare.

Ethics approval and consent to participate

This study was approved by the Ethics Committee of Hospital Joan XXIII de Tarragona (Reference number: 24p/2012) and by the Research Committee of the HTVC. All patients provided their written informed consent to participate in the study and for the use of their biopsy tissues and clinical data, in accordance with Spanish law. We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.

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López, C., Bosch, R., Korzynska, A. et al. CD68 and CD83 immune populations in non-metastatic axillary lymph nodes are of prognostic value for the survival and relapse of breast cancer patients. Breast Cancer 29, 618–635 (2022). https://doi.org/10.1007/s12282-022-01336-2

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