Skip to main content
SpringerLink
Log in

Quantitative digital image analysis of tumor-infiltrating lymphocytes in HER2-positive breast cancer

Virchows Archiv volume 476, pages 701–709 (2020)Cite this article

Abstract

As visual quantification of the density of tumor-infiltrating lymphocytes (TILs) lacks in precision, digital image analysis (DIA) approach has been applied in order to improve. In several studies, TIL density has been examined on hematoxylin and eosin (HE)-stained sections using DIA. The aim of the present study was to quantify TIL density on HE sections of core needle biopsies using DIA and investigate its association with clinicopathological parameters and pathological response to neoadjuvant chemotherapy in human epidermal growth factor receptor 2 (HER2)-positive breast cancer. The study cohort comprised of patients with HER2-positive breast cancer, all treated with neoadjuvant anti-HER2 therapy. DIA software applying machine learning-based classification of epithelial and stromal elements was used to count TILs. TIL density was determined as the number of TILs per square millimeter of stromal tissue. Median TIL density was 1287/mm2 (range, 123–8101/mm2). A high TIL density was associated with higher histological grade (P = 0.02), estrogen receptor negativity (P = 0.036), and pathological complete response (pCR) (P < 0.0001). In analyses using receiver operating characteristic curves, a threshold TIL density of 2420/mm2 best discriminated pCR from non-pCR. In multivariate analysis, high TIL density (> 2420/mm2) was significantly associated with pCR (P < 0.0001). Our results indicate that DIA can assess TIL density quantitatively, machine learning-based classification algorithm allowing determination of TIL density as the number of TILs per unit area, and TIL density established by this method appears to be an independent predictor of pCR in HER2-positive breast cancer.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3

References

  1. Stanton SE, Adams S, Disis ML (2016) Variation in the incidence and magnitude of tumor-infiltrating lymphocytes in breast cancer subtypes: a systematic review. JAMA Oncol 2:1354–1360. https://doi.org/10.1001/jamaoncol.2016.1061

    Article  PubMed  Google Scholar 

  2. Loi S, Sirtaine N, Piette F, Salgado R, Viale G, Van Eenoo F, Rouas G, Francis P, Crown JP, Hitre E, de Azambuja E, Quinaux E, Di Leo A, Michiels S, Piccart MJ, Sotiriou C (2013) Prognostic and predictive value of tumor-infiltrating lymphocytes in a phase III randomized adjuvant breast cancer trial in node-positive breast cancer comparing the addition of docetaxel to doxorubicin with doxorubicin-based chemotherapy: BIG 02-98. J Clin Oncol 31:860–867. https://doi.org/10.1200/JCO.2011.41.0902

    Article  CAS  PubMed  Google Scholar 

  3. Loi S, Michiels S, Salgado R, Sirtaine N, Jose V, Fumagalli D, Kellokumpu-Lehtinen PL, Bono P, Kataja V, Desmedt C, Piccart MJ, Loibl S, Denkert C, Smyth MJ, Joensuu H, Sotiriou C (2014) Tumor infiltrating lymphocytes are prognostic in triple negative breast cancer and predictive for trastuzumab benefit in early breast cancer: results from the FinHER trial. Ann Oncol 25:1544–1550. https://doi.org/10.1093/annonc/mdu112

    Article  CAS  PubMed  Google Scholar 

  4. Adams S, Gray RJ, Demaria S, Goldstein L, Perez EA, Shulman LN, Martino S, Wang M, Jones VE, Saphner TJ, Wolff AC, Wood WC, Davidson NE, Sledge GW, Sparano JA, Badve SS (2014) Prognostic value of tumor-infiltrating lymphocytes in triple-negative breast cancers from two phase III randomized adjuvant breast cancer trials: ECOG 2197 and ECOG 1199. J Clin Oncol 32:2959–2966

    Article  PubMed  PubMed Central  Google Scholar 

  5. Pruneri G, Gray KP, Vingiani A, Viale G, Curigliano G, Criscitiello C, Láng I, Ruhstaller T, Gianni L, Goldhirsch A, Kammler R, Price KN, Cancello G, Munzone E, Gelber RD, Regan MM, Colleoni M (2016) Tumor-infiltrating lymphocytes (TILs) are a powerful prognostic marker in patients with triple-negative breast cancer enrolled in the IBCSG phase III randomized clinical trial 22-00. Breast Cancer Res Treat 158:323–331. https://doi.org/10.1007/s10549-016-3863-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Pruneri G, Vingiani A, Bagnardi V, Rotmensz N, De Rose A, Palazzo A, Colleoni AM, Goldhirsch A, Viale G (2016) Clinical validity of tumor-infiltrating lymphocytes analysis in patients with triple-negative breast cancer. Ann Oncol 27:249–256. https://doi.org/10.1093/annonc/mdv571

    Article  CAS  PubMed  Google Scholar 

  7. Luen SJ, Salgado R, Fox S, Savas P, Eng-Wong J, Clark E, Kiermaier A, Swain SM, Baselga J, Michiels S, Loi S (2017) Tumour-infiltrating lymphocytes in advanced HER2-positive breast cancer treated with pertuzumab or placebo in addition to trastuzumab and docetaxel: a retrospective analysis of the CLEOPATRA study. Lancet Oncol 18:52–62. https://doi.org/10.1016/S1470-2045(16)30631-3

    Article  CAS  PubMed  Google Scholar 

  8. Denkert C, Loibl S, Noske A, Roller M, Müller BM, Komor M, Budczies J, Darb-Esfahani S, Kronenwett R, Hanusch C, von Törne C, Weichert W, Engels K, Solbach C, Schrader I, Dietel M, von Minckwitz G (2010) Tumor-associated lymphocytes as an independent predictor of response to neoadjuvant chemotherapy in breast cancer. J Clin Oncol 28:105–113. https://doi.org/10.1200/JCO.2009.23.7370

    Article  CAS  PubMed  Google Scholar 

  9. Salgado R, Denkert C, Campbell C, Savas P, Nuciforo P, Aura C, de Azambuja E, Eidtmann H, Ellis CE, Baselga J, Piccart-Gebhart MJ, Michiels S, Bradbury I, Sotiriou C, Loi S (2015) Tumor-infiltrating lymphocytes and associations with pathological complete response and event-free survival in HER2-positive early-stage breast cancer treated with lapatinib and trastuzumab: a secondary analysis of the NeoALTTO Trial. JAMA Oncol 1:448–454. https://doi.org/10.1001/jamaoncol.2015.0830

    Article  PubMed  PubMed Central  Google Scholar 

  10. Denkert C, von Minckwitz G, Brase JC, Sinn BV, Gade S, Kronenwett R, Pfitzner BM, Salat C, Loi S, Schmitt WD, Schem C, Fisch K, Darb-Esfahani S, Mehta K, Sotiriou C, Wienert S, Klare P, André F, Klauschen F, Blohmer JU, Krappmann K, Schmidt M, Tesch H, Kümmel S, Sinn P, Jackisch C, Dietel M, Reimer T, Untch M, Loibl S (2015) Tumor-infiltrating lymphocytes and response to neoadjuvant chemotherapy with or without carboplatin in human epidermal growth factor receptor 2-positive and triple-negative primary breast cancers. J Clin Oncol 33:983–991. https://doi.org/10.1200/JCO.2014.58.1967

    Article  CAS  PubMed  Google Scholar 

  11. West NR, Milne K, Truong PT, Macpherson N, Nelson BH, Watson PH (2011) Tumor-infiltrating lymphocytes predict response to anthracycline-based chemotherapy in estrogen receptor-negative breast cancer. Breast Cancer Res 13:R126. https://doi.org/10.1186/bcr3072

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Mahmoud SM, Paish EC, Powe DG, Macmillan RD, Grainge MJ, Lee AH, Ellis IO, Green AR (2011) Tumor-infiltrating CD8+ lymphocytes predict clinical outcome in breast cancer. J Clin Oncol 29:1949–1955. https://doi.org/10.1200/JCO.2010.30.5037

    Article  PubMed  Google Scholar 

  13. Mohammed ZM, Going JJ, Edwards J, Elsberger B, McMillan DC (2013) The relationship between lymphocyte subsets and clinico-pathological determinants of survival in patients with primary operable invasive ductal breast cancer. Br J Cancer 109:1676-1684. doi:0.1038/bjc.2013.493

  14. Baker K, Lachapelle J, Zlobec I, Bismar TA, Terracciano L, Foulkes WD (2011) Prognostic significance of CD8+ T lymphocytes in breast cancer depends upon both oestrogen receptor status and histological grade. Histopathology 58:1107–1116. https://doi.org/10.1111/j.1365-2559.2011.03846.x

    Article  PubMed  Google Scholar 

  15. Matsumoto H, Thike AA, Li H, Yeong J, Koo SL, Dent RA, Tan PH, Iqbal J (2016) Increased CD4 and CD8-positive T cell infiltrate signifies good prognosis in a subset of triple-negative breast cancer. Breast Cancer Res Treat 156:237–247. https://doi.org/10.1007/s10549-016-3743-x

    Article  CAS  PubMed  Google Scholar 

  16. Salgado R, Denkert C, Demaria S et al (2015) The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: recommendations by an International TILs Working Group 2014. Ann Oncol 26:259–271. https://doi.org/10.1093/annonc/mdu450

    Article  CAS  PubMed  Google Scholar 

  17. Symmans WF, Peintinger F, Hatzis C, Rajan R, Kuerer H, Valero V, Assad L, Poniecka A, Hennessy B, Green M, Buzdar AU, Singletary SE, Hortobagyi GN, Pusztai L (2007) Measurement of residual breast cancer burden to predict survival after neoadjuvant chemotherapy. J Clin Oncol 25:4414–4422

    Article  PubMed  Google Scholar 

  18. Denkert C, Wienert S, Poterie A et al (2016) Standardized evaluation of tumor-infiltrating lymphocytes in breast cancer: results of the ring studies of the international immuno-oncology biomarker working group. Mod Pathol 29:1155–1164. https://doi.org/10.1038/modpathol.2016.109

    Article  CAS  PubMed  Google Scholar 

  19. Vasaturo A, Di Blasio S, Verweij D, Blokx WA, van Krieken JH, de Vries IJ, Figdor CG (2017) Multispectral imaging for highly accurate analysis of tumour-infiltrating lymphocytes in primary melanoma. Histopathology 70:643–649. https://doi.org/10.1111/his.13070

    Article  PubMed  Google Scholar 

  20. Eriksen AC, Andersen JB, Kristensson M, dePont CR, Hansen TF, Kjær-Frifeldt S, Sørensen FB (2017) Computer-assisted stereology and automated image analysis for quantification of tumor infiltrating lymphocytes in colon cancer. Diagn Pathol 12:65. https://doi.org/10.1186/s13000-017-0653-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Sirinukunwattana K, Ahmed Raza SE, Tsang Y-W, Snead DR, Cree IA, Rajpoot NM (2016) Locality sensitive deep learning for detection and classification of nuclei in routine colon cancer histology images. IEEE Trans Med Imaging 35:1196–1206. https://doi.org/10.1109/TMI.2016.2525803

    Article  PubMed  Google Scholar 

  22. Ingold Heppner B, Untch M, Denkert C, Pfitzner BM, Lederer B, Schmitt W, Eidtmann H, Fasching PA, Tesch H, Solbach C, Rezai M, Zahm DM, Holms F, Glados M, Krabisch P, Heck E, Ober A, Lorenz P, Diebold K, Habeck JO, Loibl S (2016) Tumor-infiltrating lymphocytes: a predictive and prognostic biomarker in neoadjuvant-treated HER2-positive breast cancer. Clin Cancer Res 22:5747–5754

    Article  CAS  PubMed  Google Scholar 

  23. Kurozumi S, Inoue K, Matsumoto H, Fujii T, Horiguchi J, Oyama T, Kurosumi M, Shirabe K (2019) Prognostic utility of tumor-infiltrating lymphocytes in residual tumor after neoadjuvant chemotherapy with trastuzumab for HER2-positive breast cancer. Sci Rep 9:1583. https://doi.org/10.1038/s41598-018-38272-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Liu S, Duan X, Xu L, Xin L, Cheng Y, Liu Q, Ye J, Zhang S, Zhang H, Zhu S, Li T, Liu Y (2015) Optimal threshold for stromal tumor-infiltrating lymphocytes: its predictive and prognostic value in HER2-positive breast cancer treated with trastuzumab-based neoadjuvant chemotherapy. Breast Cancer Res Treat 154:239–249. https://doi.org/10.1007/s10549-015-3617-7

    Article  CAS  PubMed  Google Scholar 

  25. Yang X, Rao J, Yang W, Shui R (2018) Evaluation of the predictive and prognostic values of stromal tumor-infiltrating lymphocytes in HER2-positive breast cancers treated with neoadjuvant chemotherapy. Target Oncology 13:757–767. https://doi.org/10.1007/s11523-018-0602-1

    Article  CAS  Google Scholar 

  26. Cortazar P, Zhang L, Untch M et al (2014) Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet 384:164–172. https://doi.org/10.1016/S0140-6736(13)62422-8

    Article  PubMed  Google Scholar 

  27. Carey LA, Berry DA, Cirrincione CT, Barry WT, Pitcher BN, Harris LN, Ollila DW, Krop IE, Henry NL, Weckstein DJ, Anders CK, Singh B, Hoadley KA, Iglesia M, Cheang MC, Perou CM, Winer EP, Hudis CA (2016) Molecular heterogeneity and response to neoadjuvant human epidermal growth factor receptor 2 targeting in CALGB 40601, a randomized phase III trial of paclitaxel plus trastuzumab with or without lapatinib. J Clin Oncol 34:542–549. https://doi.org/10.1200/JCO.2015.62.1268

    Article  CAS  PubMed  Google Scholar 

  28. Llombart-Cussac A, Cortés J, Paré L, Galván P, Bermejo B, Martínez N, Vidal M, Pernas S, López R, Muñoz M, Nuciforo P, Morales S, Oliveira M, de la Peña L, Peláez A, Prat A (2017) HER2-enriched subtype as a predictor of pathological complete response following trastuzumab and lapatinib without chemotherapy in early-stage HER2-positive breast cancer (PAMELA): an open-label, single-group, multicentre, phase 2 trial. Lancet Oncol 18:545–554. https://doi.org/10.1016/S1470-2045(17)30021-9

    Article  CAS  PubMed  Google Scholar 

  29. Fumagalli D, Venet D, Ignatiadis M et al (2017) RNA sequencing to predict response to neoadjuvant anti-HER2 therapy: a secondary analysis of the NeoALTTO randomized clinical trial. JAMA Oncol. https://doi.org/10.1001/jamaoncol.2016.3824

  30. Chumsri S, Sperinde J, Liu H, Gligorov J, Spano JP, Antoine M, Moreno Aspitia A, Tan W, Winslow J, Petropoulos CJ, Chenna A, Bates M, Weidler JM, Huang W, Dueck A, Perez EA (2018) High p95HER2/HER2 ratio associated with poor outcome in trastuzumab-treated HER2-positive metastatic breast cancer NCCTG N0337 and NCCTG 98-32-52 (Alliance). Clin Cancer Res 24:3053–3058. https://doi.org/10.1158/1078-0432.CCR-17-1864

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Scaltriti M, Nuciforo P, Bradbury I, Sperinde J, Agbor-Tarh D, Campbell C, Chenna A, Winslow J, Serra V, Parra JL, Prudkin L, Jimenez J, Aura C, Harbeck N, Pusztai L, Ellis C, Eidtmann H, Arribas J, Cortes J, de Azambuja E, Piccart M, Baselga J (2015) High HER2 expression correlates with response to the combination of lapatinib and trastuzumab. Clin Cancer Res 21:569–576. https://doi.org/10.1158/1078-0432.CCR-14-1824

    Article  CAS  PubMed  Google Scholar 

  32. Gallardo A, Lerma E, Escuin D, Tibau A, Muñoz J, Ojeda B, Barnadas A, Adrover E, Sánchez-Tejada L, Giner D, Ortiz-Martínez F, Peiró G (2012) Increased signalling of EGFR and IGF1R, and deregulation of PTEN/PI3K/Akt pathway are related with trastuzumab resistance in HER2 breast carcinomas. Br J Cancer 106:1367–1373. https://doi.org/10.1038/bjc.2012.85

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Shattuck DL, Miller JK, Carraway KL 3rd, Sweeney C Met receptor contributes to trastuzumab resistance of Her2-overexpressing breast cancer cells. (2008) Cancer Res 68(5):1471-1477. doi:https://doi.org/10.1158/0008-5472.CAN-07-5962

  34. Majewski IJ, Nuciforo P, Mittempergher L, Bosma AJ, Eidtmann H, Holmes E, Sotiriou C, Fumagalli D, Jimenez J, Aura C, Prudkin L, Díaz-Delgado MC, de la Peña L, Loi S, Ellis C, Schultz N, de Azambuja E, Harbeck N, Piccart-Gebhart M, Bernards R, Baselga J (2015) PIK3CA mutations are associated with decreased benefit to neoadjuvant human epidermal growth factor receptor 2-targeted therapies in breast cancer. J Clin Oncol 33:1334–1339. https://doi.org/10.1200/JCO.2014.55.2158

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Breast Surgery, Nakagami Hospital, Okinawa, Japan

    Norie Abe, Tokiwa Motonari, Mikiko Unesoko & Hisamitsu Zaha

  2. Department of Pathology and Oncology, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan

    Norie Abe, Reika Takamatsu & Naoki Yoshimi

  3. Department of Pathology, Ryukyu University Hospital, 207 Uehara, Nishihara, Okinawa, 903-0215, Japan

    Hirofumi Matsumoto

  4. Department of Breast Surgical Oncology, Nahanishi Clinic, Okinawa, Japan

    Kentaro Tamaki, Naoko Takigami, Kano Uehara, Yoshihiko Kamada & Nobumitsu Tamaki

  5. Department of Pathology, Nakagami Hospital, Okinawa, Japan

    Norihiro Nakada

Authors
  1. Norie Abe
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hirofumi Matsumoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Reika Takamatsu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kentaro Tamaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Naoko Takigami
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Kano Uehara
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yoshihiko Kamada
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Nobumitsu Tamaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Tokiwa Motonari
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Mikiko Unesoko
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Norihiro Nakada
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Hisamitsu Zaha
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Naoki Yoshimi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

NA designed and write the study, analyzed the data, and collected clinical data and sample. HM and NY designed the study and assisted with data analysis. RT analyzed HER2 fluorescence in situ hybridization. All authors have substantial contributions to the conception, design, and drafting the work.

Corresponding author

Correspondence to Hirofumi Matsumoto.

Ethics declarations

Conflict of interest

The authors declared that they have no conflict of interest.

Ethical approval

This study was part of a research project approved by the ethics committees at Nakagami Hospital (2016029-2) and Nahanishi Clinic (NNCEC2018005). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from each individual participant included in the study.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection on Quality in Pathology

Electronic supplementary material

Supplementary Fig. 1

The area of TIL assessment on CNB slide. TILs were evaluated on the stromal compartment within the border of the invasive foci (encircled in yellow). TILs around ductal carcinoma in situ elements and area of tertiary lymphoid structures were excluded from TIL assessment (encircled in black) (PNG 8163 kb)

High Resolution Image (TIF 8071 kb)

Supplementary Fig. 2

Concordance in stromal area derived from machine learning-based classification and manual assessment (PNG 149 kb)

High Resolution Image (TIF 502 kb)

Supplementary Fig. 3

Concordance in the number of stromal TILs derived from DIA and manual assessment (PNG 147 kb)

High Resolution Image (TIF 491 kb)

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abe, N., Matsumoto, H., Takamatsu, R. et al. Quantitative digital image analysis of tumor-infiltrating lymphocytes in HER2-positive breast cancer. Virchows Arch 476, 701–709 (2020). https://doi.org/10.1007/s00428-019-02730-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00428-019-02730-6

Keywords

search

Navigation