UBC Faculty Research and Publications

CD8+ lymphocyte infiltration is an independent favorable prognostic indicator in basal-like breast cancer Liu, Shuzhen; Lachapelle, Jonathan; Leung, Samuel; Gao, Dongxia; Foulkes, William D; Nielsen, Torsten O Mar 15, 2012

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Item Metadata


52383-13058_2011_Article_2941.pdf [ 408.54kB ]
JSON: 52383-1.0223456.json
JSON-LD: 52383-1.0223456-ld.json
RDF/XML (Pretty): 52383-1.0223456-rdf.xml
RDF/JSON: 52383-1.0223456-rdf.json
Turtle: 52383-1.0223456-turtle.txt
N-Triples: 52383-1.0223456-rdf-ntriples.txt
Original Record: 52383-1.0223456-source.json
Full Text

Full Text

RESEARCH ARTICLE Open AccessCD8+ lymphocyte infiltration is an independentfavorable prognostic indicator in basal-likebreast cancerShuzhen Liu1, Jonathan Lachapelle2, Samuel Leung1, Dongxia Gao1, William D Foulkes3,4,5 and Torsten O Nielsen1*AbstractIntroduction: Tumor infiltrating lymphocytes may indicate an immune response to cancer development, but theirsignificance remains controversial in breast cancer. We conducted this study to assess CD8+ (cytotoxic T)lymphocyte infiltration in a large cohort of invasive early stage breast cancers, and to evaluate its prognostic effectin different breast cancer intrinsic subtypes.Methods: Immunohistochemistry for CD8 staining was performed on tissue microarrays from 3992 breast cancerpatients. CD8+ tumor infiltrating lymphocytes were counted as intratumoral when in direct contact with tumorcells, and as stromal in adjacent locations. Kaplan-Meier functions and Cox proportional hazards regression modelswere applied to examine the associations between tumor infiltrating lymphocytes and breast cancer specificsurvival.Results: Among 3403 cases for which immunohistochemical results were obtained, CD8+ tumor infiltratinglymphocytes were identified in an intratumoral pattern in 32% and stromal pattern in 61% of the cases. In thewhole cohort, the presence of intratumoral tumor-infiltrating lymphocytes was significantly correlated with youngage, high grade, estrogen receptor negativity, human epidermal growth factor receptor-2 positivity and core basalintrinsic subtype, and was associated with superior breast cancer specific survival. Multivariate analysis indicatedthat the favorable prognostic effect of CD8+ tumor infiltrating lymphocytes was significant only in the core basalintrinsic subgroup (Hazard ratio, HR = 0.35, 95% CI = 0.23-0.54). No association with improved survival was presentin those triple negative breast cancers that lack expression of basal markers (HR = 0.99, 95% CI = 0.48-2.04) nor inthe other intrinsic subtypes.Conclusions: CD8+ tumor infiltrating lymphocytes are an independent prognostic factor associated with betterpatient survival in basal-like breast cancer, but not in non-basal triple negative breast cancers nor in other intrinsicmolecular subtypes.IntroductionImmune response may play an important role in cancerprogression. Tumor-infiltrating lymphocytes (TILs)reflect a local immune response and could be a keymechanism in controlling tumor progression [1,2]. Anumber of studies demonstrate that TILs are associatedwith clinical outcome in patients with carcinoma andmelanoma [3-8]. TILs have been found to be mainly Tlymphocytes, and the majority express a cytotoxic effec-tor phenotype (CD8+) [9-11]. CD8+ T cell-mediatedtype 1 immune responses can enhance the accumulationof distinct endogenous CD8+ and CD4+ T cells andfacilitate their antitumor function within the tumormicroenvironment [12,13]. Studies in ovarian carcino-mas and colon cancer show that high levels of CD8+lymphocyte infiltration are associated with better prog-nosis in these diseases [3,14]. In breast cancer, somestudies have reported that inflammation and cytotoxiclymphocyte infiltration are associated with better survi-val [15-17]. In contrast, other groups have reported thathigh numbers of TILs are related to worse overall* Correspondence: torsten@mail.ubc.ca1Genetic Pathology Evaluation Centre, Department of Pathology andLaboratory Medicine, University of British Columbia, 2660 Oak Street,Vancouver, BC, V6H 3Z6, CanadaFull list of author information is available at the end of the articleLiu et al. Breast Cancer Research 2012, 14:R48http://breast-cancer-research.com/content/14/2/R48© 2011 Liu et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative CommonsAttribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction inany medium, provided the original work is properly cited.survival [18,19], whereas still other studies did not findany significant association of TILs with patient outcome[20,21]. A recent publication reported that a high ratioof CD8+ TILs to FOXP3+ regulatory T cells had a signif-icant relationship to improved patient survival in breastcancer [22]. Two other studies have tested larger series:one study used a retrospective cohort of 1,334 patientswith primary breast cancer diagnosed from 1987 to1998 in the UK and showed that total CD8+ TILs wereindependently associated with better survival in breastcancer [23], whereas another study with 1,953 breastcancer cases treated in the University Hospital Basel inSwitzerland between 1985 and 1996 demonstrated thatthe independent favorable prognostic effect of total CD8+ TILs was observed only in those with estrogen recep-tor-negative (ER-) tumors (whereas, in univariate ana-lyses, CD8+ TILs had an unfavorable effect on outcomein ER-positive (ER+) breast cancers) [24]. Thus, theextent to which TILs contribute to tumor progressionand clinical outcome in breast cancer has remained con-troversial, possibly because the effect is limited to cer-tain subgroups of patients.Breast cancer is a heterogeneous disease composed ofdifferent intrinsic subtypes, each with distinctive biologi-cal and prognostic behaviors and responses to therapy.Although the introduction of adjuvant systemic therapy(AST) has led to a significant reduction in breast cancermortality, many patients do not benefit. Gene expressionstudies suggest that predictive indicators should bedeveloped for different breast cancer subtypes [25,26].The interaction between immune response, intrinsicsubtype, and treatment strategy all likely contribute tothe outcome of the disease. The development of mole-cular diagnostic techniques has facilitated a betterunderstanding of the heterogeneity of breast cancer andopened up the possibility of more personalized therapy[27,28]. Hormone receptor status and human epidermalgrowth factor receptor-2 (HER2) molecular status arecurrently used to guide AST strategies for the luminaland HER2+ intrinsic subgroups, but no targeted therapyfor the basal-like subgroup is currently available. Basal-like breast cancer comprises about 15% of all invasivebreast cancers and is likely to be high-grade, occur inyoung women, and have an aggressive clinical course[29]. Although a majority of basal-like tumors carry aclinical triple-negative phenotype (TNP) (ER-, progester-one receptor-negative (PR-), and HER2-), they are notsynonymous [30], and triple-negative breast cancersinclude many cases that lack the expression of basalmarkers - the so-called ‘five-marker negative phenotype’(5NP): ER-, PR-, HER2-, epidermal growth factor recep-tor-negative (EGFR-), and cytokeratin (CK) 5/6- - whichhave been shown to have significantly better outcomesthan core basal cases [31,32]. Gene expression profilingdata suggest that medullary breast tumors (a rare histo-logical subtype with a prominent lymphocytic reactionand a good prognosis) are a specific subgroup withinthe basal-like class, indicating that the overall poor sur-vival of basal-like breast cancer might be mitigated incases in which there is a strong immune response[33-35]. On the other hand, a separate body of researchhas highlighted that recruitment of chronic inflamma-tory cells, including macrophages, can actually promotecancer progression [36]. Different types of immuneresponse in different subtypes of breast cancer mightexplain apparently contradictory results. However, todate, no large immunohistochemistry study has exploredthe prognostic effect of an immune response in breastcancer stratified by breast cancer intrinsic subtype.Therefore, there is a clear need for studies with suffi-cient power for subgroup analysis, employing validatedmeasurements of immune response, to evaluate the sig-nificance of TILs in breast tumors. The aim of thisstudy was to examine the prognostic significance ofCD8+ TILs in different breast cancer intrinsic subtypesin a large population-based cohort with long-term fol-low-up. Our hypothesis was that CD8+ lymphocyte infil-tration has distinct prognostic effects in differentintrinsic molecular subtypes of breast cancer.Materials and methodsStudy populationThe study population consists of 3,992 female patientswith invasive breast cancer diagnosed between 1986 and1992 in the province of British Columbia. This cohortwas collected from the Breast Cancer Outcomes Unitdatabase maintained by the British Columbia CancerAgency (BCCA). During the study period, 75% ofpatients with breast cancer in the province were referredto the BCCA; non-referred patients were generally olderor had no indications for adjuvant therapy [37,38]. Ofthe patients referred to the BCCA, approximately 25%had available formalin-fixed paraffin-embedded blockswith sufficient tumor tissues for tissue microarray(TMA) construction. Thus, the study cohort representsabout 20% of all of the patients with breast cancer diag-nosed in the province during the study period. Themean age of the cohort at diagnosis was 58.9 years (23to 95 years), and the median follow-up was 12.6 years.Baseline clinical information of the study populationincludes age at diagnosis, histology, grade, tumor size,number of involved axillary nodes, lymphovascular inva-sion (LVI), and dates of diagnosis, recurrence, death,and cause of death (breast cancer versus other). Asshown in Table 1 among the study cases, approximatelyhalf (51.1%, 2,040/3,992) were poorly differentiatedtumors (grade 3), 47.3% (1,888/3,992) had breast tumorsover 2 cm, 43.1% (1,719/3,992) were node-positive, andLiu et al. Breast Cancer Research 2012, 14:R48http://breast-cancer-research.com/content/14/2/R48Page 2 of 1442.8% (1,710/3,992) had LVI. Histological categorizationon these cases, including assignment to the medullarysubtype, was determined by a central review of full sec-tions which was performed at the time of referral to theBCCA. During the time period of this study cohort,most patients with breast cancer were treated accordingto the provincial guidelines developed by the BCCA onthe basis of patient age, tumor size, nodal status, andLVI. Patients were defined as high-risk if their lymphnodes were positive, if there was evidence of LVI, or ifthe tumor was both greater than 2 cm and ER- at thetime of diagnosis. High-risk patients were treated withAST according to their age and menopausal status.Low-risk patients were not given any AST. This studyand the use of de-identified data were approved by theClinical Research Ethics Board of the BCCA and theUniversity of British Columbia. We were permittedaccess to the de-identified patient outcome informationfrom the Breast Cancer Outcomes Unit database, main-tained by the BCCA. In compliance with the CanadianTri-Council Policy Statement for ethical research invol-ving human subjects, the requirement for informed con-sent was waived as this study was limited to anonymousarchival specimens.Table 1 Clinicopathologic characteristics and distributionof CD8+ intratumoral lymphocytes in the studypopulationCharacteristics Patients,number(percentage)iTILs (≥ 1)Prevalence,percentage(proportion)PvalueAge at diagnosis,years< 0.001< 40 294 (7.4) 38.9 (98/252)40-49 844 (21.1) 37.5 (273/728)50-65 1,425 (35.7) 31.3 (377/1,203)> 65 1,429 (35.8) 29.2 (356/1,220)Grade < 0.0011: well differentiated 209 (5.2) 24.4 (40/164)2: moderately well orpartially differentiated1,563 (39.2) 26.9 (361/1,342)3: poorlydifferentiated2,040 (51.1) 37.2 (652/1,754)Unknown 180 (4.5)Tumor size,centimeters0.076≤ 2 2,078 (52.1) 30.5 (540/1,768)> 2-5 1,667 (41.8) 34.1 (494/1,449)> 5 221 (5.5) 34.9 (59/169)Unknown 26 (0.6)Nodal status 0.051Negative 2,265 (56.7) 31.0 (593/1,911)Positive 1,719 (43.1) 34.3 (509/1,484)Unknown 8 (0.2)Lymphovascularinvasion0.638Negative 2,106 (52.8) 32.5 (576/1,770)Positive 1,710 (42.8) 31.8 (474/1,492)Unknown 176 (4.4)Histology < 0.001Medullary 66 (1.7) 78.4 (40/51)Not medullary 3926 (98.3) 31.7 (1,064/3,352)AJCC stage 0.004I 1,393 (34.9) 28.8 (337/1,172)II 2,255 (56.5) 34.6 (677/1,959)III 317 (7.9) 32.9 (83/252)Unknown/missing 27 (0.7)Adjuvant systemictherapy0.012No adjuvant systemictherapy1,676 (42.0) 21.2 (302/1,427)Tamoxifen only 1,276 (32.0) 18.6 (206/1,105)Chemotherapy only 727 (18.2) 27.2 (169/622)Tamoxifen +chemotherapy297 (7.4) 29.4 (73/148)Other 16 (0.4) 21.4 (3/14)ER < 0.001Negative 1,200 (30.1) 39.9 (370/927)Table 1 Clinicopathologic characteristics and distributionof CD8+ intratumoral lymphocytes in the study popula-tion (Continued)Positive (≥ 1% nucleistained)2,761 (69.1) 29.6 (728/2,456)Uninterpretable/missing31 (0.8)HER2 < 0.001Negative 3,316 (83.1) 31.3 (907/2,902)Positive 498 (12.5) 39.6 (176/444)Uninterpretable/missing178 (4.4)Subtype < 0.001Luminal A 1,518 (38.0) 25.4 (353/1,392)Luminal B 829 (20.8) 36.9 (285/773)Luminal/HER2 224 (5.6) 39.8 (82/206)Luminal not furtherassigned244 (6.1) 21.5 (37/172)HER2+/ER- 250 (6.3) 39.6 (90/227)TNP 630 (15.8) 42.2 (226/535)Core basal 330 (8.3) 49.2 (151/307)5NP 162 (4.1) 35.2 (50/142)TNP not assignable 138 (3.4) 29.1 (25/86)Unassignable 297 (7.4) 31.6 (31/98)Total 3,992 (100) 32.4 (1,104/3,403)5NP, five negative phenotype; AJCC, American Joint Committee on Cancer; ER,estrogen receptor; HER2, human epidermal growth factor receptor-2; iTIL,intratumoral tumor-infiltrating lymphocyte; TNP, triple-negative phenotype.Liu et al. Breast Cancer Research 2012, 14:R48http://breast-cancer-research.com/content/14/2/R48Page 3 of 14Tissue microarray and immunohistochemistryThe centralized provincial laboratory of Vancouver Gen-eral Hospital retained single archival blocks for each ofthe 3,992 patients. One 0.6-mm core per patient wasused, 17 TMAs representing these samples were con-structed, and immunohistochemistry and scoring for ER,PR, HER2, the Ki67 proliferation marker, EGFR, andCK5/6 were performed as previously described[31,37,39-42]. Immunohistochemistry for CD8+ TILswas performed by using the antibody against humanCD8 (clone C8/144B, dilution 1:100) in accordance withthe protocol of the manufacturer (DakoCytomation,Glostrup, Denmark). Intrinsic breast cancer subtypeswere determined by the immunohistochemical expres-sions of ER, PR, HER2, Ki67, EGFR, and CK5/6. Lumi-nal A was defined as ER+ or PR+, HER2-, and low Ki67(< 14%); luminal B was defined as ER+ (or PR+) andHER2- with high Ki67 (≥ 14%); luminal/HER2 subgroupwas defined as ER+ (or PR+) and HER2+; HER2+/ER-was defined as HER2+ with ER- and PR- [42]; and triple-negative subgroup (TNP) was defined as ER-, PR-, andHER2-. The core basal subgroup was defined as triple-negative with either EGFR+ or CK5/6+, and the fivenegative phenotype (5NP) was defined as triple-negativeas well as EGFR- and CK5/6- [31]. The 3,992 patientswith breast cancer were thereby categorized as follows:38.0% (1,518/3,992) luminal A, 20.8% (829/3,992) lumi-nal B, 5.6% (223/3,992) luminal/HER2, 6.3% (250/3,992)HER2+/ER-, and 15.8% (630/3,992) triple-negative, ofwhich 8.3% (330/3,992) could be categorized as corebasal and 4.1% (162/3,992) as 5NP; the remainder had apartial or unassignable subtype because of missing orambiguous biomarker data (Table 1).CD8+ tumor-infiltrating lymphocytes: scoring andquantificationStained TMA slides were digitally scanned and CD8+TILs were visually scored by a pathologist who wasblinded to the clinical characteristics and outcomes ofthe patients. Scoring and quantification of CD8+ TILswere carried out as described in a recent study [24]. Inbrief, intratumoral CD8+ TILs (iTILs) were defined asCD8+ lymphocytes located within tumor cell nests or indirect contact with the breast carcinoma malignantepithelial cells, whereas stromal CD8+ TILs (sTILs) weredefined as CD8+ lymphocytes in the adjacent peritu-moral stroma without direct contact with the carcinomacells. Total CD8+ TILs (tTILs) were measured by com-bining the counts of iTILs and sTILs for each tissuecore. To assess the reproducibility and reliability of thescoring, 490 cases were repeatedly scored by the samepathologist after a period of time (4 weeks), and 200cases were randomly selected from the whole cohortand iTILs were re-scored by a second pathologist.Pearson correlation analysis was used to check the relia-bility of the repeated scoring by the same scorer, andthe intraclass correlation coefficient (ICC) was used toassess the reliability of re-scoring by the two scorers.High correlation coefficients were obtained (Pearson rwas at least 0.94, and ICC was 0.74).Statistical analysisThe outcome variable in this study was breast cancer-specific survival (BCSS). Optimal cutoff points for TILscounts against BCSS were chosen on the basis ofrecently published findings from an independent series[24] and checked by receiver operating characteristiccurve analysis by using 10-year BCSS as the endpoints,as described in the Supplemental method section (Addi-tional file 1). The optimal cutoff points for iTIL, sTIL,and tTIL used in this study were 1, 3, and 2, respec-tively. To specify, CD8+ iTIL expression was categorizedas low when iTIL was 0 (no CD8+ iTIL counted) andhigh when iTIL was at least 1 (1 or more CD8+ iTILs inthe assessed tissue core); sTIL low means fewer than 3CD8+ sTILs per core, and tTIL low means fewer than 2CD8+ tTILs were identified in a core.Analysis of the association between TILs and clinico-pathologic variables was performed by using SPSS ver-sion 19.0 and R 2.11.1. Because the distributions of theoutcome variable (BCSS) were not normal in the studycohort, non-parametric Wilcoxon testing was used tocheck the bivariate relationship between BCSS and TILsand other potential confounding variables, including ageat diagnosis, grade, tumor size, involvement of lymphnodes, LVI, and intrinsic subtypes. Chi-squared testingwas used to check the relationship between TILs andthose potential confounding variables. For survival ana-lysis, the event under study was death from breast can-cer. BCSS time was defined as the number of yearsbetween the date of diagnosis of breast cancer and thedate of death attributable to breast cancer. Survival timewas censored at the time a patient died from anothercause or when the follow-up period ended. For univari-ate survival analyses, the Kaplan-Meier function analysiswas performed to estimate probabilities of BCSS. Log-rank testing was used to assess differences in BCSSamong different subgroups. For multivariate survivalanalyses, Cox proportional hazards regression modelswere built to estimate the TIL hazard ratio (HR), whichwas adjusted by the potential confounding variables onthe basis of the partial maximum likelihood estimation.Smoothed, rescaled Schoenfeld residual plots were per-formed to test proportional hazards assumptions. Onlycases with sufficient information for all covariates wereincluded in the multivariate analysis. Wald statisticswere used to test the significance of individual coeffi-cients. Interactions between TILs and some covariablesLiu et al. Breast Cancer Research 2012, 14:R48http://breast-cancer-research.com/content/14/2/R48Page 4 of 14were checked by building Cox regression models for dif-ferent levels of those variables and comparing HRs ofTILs. All of the tests were two-sided at a significancelevel of 0.05. Supplementary analyses were also per-formed by using relapse-free survival as an outcomevariable; relapse-free survival time was defined as thenumber of years between the date of diagnosis of breastcancer and the date of any type of relapse, includinglocal, regional, and distant relapses of the disease.ResultsCD8+ tumor-infiltrating lymphocyte counts anddistributions in breast cancerAmong the 3,992 breast tumor cases, intact cores bear-ing infiltrating breast carcinoma sufficient for interpreta-tion of immunohistochemical data for CD8 stainingwere available from 3,403 (85.2%) tumors. Mediancounts of CD8+ TILs per 0.6-mm TMA core were 0 foriTIL (interquartile range, or IQR, of 0 to 1), 2 for sTIL(IQR of 0 to 10), and 3 for tTIL (IQR of 0 to 12). Ofthe 3,403 interpretable cases, 32.4% had tumor infil-trated with at least one CD8+ iTIL and 60.6% by at leastone CD8+ sTIL (Figure S1 of Additional file 2). The dis-tributions of CD8+ iTILs and sTILs were both signifi-cantly and positively skewed (Figure S2 of Additionalfile 3). Because analytical results from all types of TILsinterpretation were broadly similar, results presented inthis paper are based primarily on iTILs analysis, whichis the fastest and simplest to perform. As shown inTable 1 the presence of iTIL is significantly associatedwith young age, high grade, medullary histology, ERnegativity, HER2 positivity, and the core basal intrinsicsubgroup, the category that has the highest prevalenceof cases displaying intratumoral lymphocytes.Prognosis of CD8+ iTILs in patients with breast cancer(whole cohort)To examine the prognosis of CD8+ TILs in the studypopulation, we first applied univariate Kaplan-Meierfunction survival analysis in the whole cohort. Theresults did not show a significant difference in BCSSbetween breast cancer patients with an iTIL count of atleast 1 and an iTIL of 0 (P = 0.761). Since the distribu-tion of iTILs was associated with patient age at diagno-sis, tumor grade, and ER and HER2 status, we nextassessed the survival functions of iTIL associated withBCSS in groups with different age, tumor grade, and ERand HER2 status. Figure 1 showed that, in youngerpatients (< 50 years) and in those with ER- tumors,cases with iTILs had significantly better BCSS thanthose without. Reversed associations were observed inpatients who were at least 50 years old or who had ER+breast cancer. No significant associations were detectedin cases stratified by grade (grade 1 + 2 versus grade 3)or HER2 status (HER2+ versus HER2-). These resultsindicated that age and ER status could have an interac-tion with the association between iTILs and patient sur-vival in breast cancer.We built Cox proportional hazards regression modelsto estimate the HR for iTILs. Smoothed, rescaledSchoenfeld residual plots showed that iTILs and mostother covariables satisfied the proportional hazardsassumptions well during the period of follow-up. OnlyiTILs in the luminal A subgroup varied slightly duringlonger follow-up.Results from the univariate Cox regression model ana-lysis showed that iTILs was not a significant prognosticfactor associated with BCSS in the cohort as a whole:HR = 1.02, 95% confidence interval (CI) = 0.89 to 1.17.To take into consideration potential confounders, a mul-tivariate Cox regression model was built to assess theassociation between iTILs and BCSS, including the cov-ariates of age at diagnosis, tumor grade and size, lymphnode status, LVI, and intrinsic subtype. Table 2 showedthat the adjusted HR of iTIL was 0.79 (95% CI = 0.68 to0.91), meaning that, in the whole cohort, the probabilityof BCSS among patients with an iTIL count of at least 1was 21% (1 to 0.79) higher than among those with aniTIL count of 0 after adjustment for age, grade, tumorsize, lymph node status, LVI, and intrinsic subtypes.Besides iTIL, tumor grade and size, nodal status, LVI,and intrinsic subtype, each had significant effects onBCSS. To examine the effect of interaction between age,ER status, and iTIL, we built multivariate Cox regressionmodels for iTILs at different levels of age and ER status.These analyses showed that the adjusted HRs for iTILswere 0.65 (95% CI = 0.51 to 0.84) for those youngerthan 50 years old and 0.89 (95% CI = 0.74 to 1.06) forthose at least 50 years old; the adjusted HRs were 0.61(95% CI = 0.47 to 0.77) for those with ER- tumors but0.91 (95% CI = 0.77 to 1.11) for those with ER+ tumors.Therefore, interactions between iTIL and age and ERstatus might modify the effect size for iTILs in theunstratified whole cohort of patients with breast cancer.Association of CD8+ iTILs with breast cancer-specificsurvival in different breast cancer intrinsic subgroupsWe further assessed the association of CD8+ TILs withpatient survival in different breast cancer intrinsic sub-types, first using univariate Kaplan-Meier function survi-val analysis. No difference in BCSS was detectedbetween those with an iTIL count of at least 1 and aniTIL count of 0 within the luminal A and luminal Bsubgroups (Figure 2a, b). Although we observed anapparent difference between the two groups amongHER2+/ER- cases, this was not statistically significant (P= 0.064) (Figure 2c). However, as shown in Figure 2d, alarge and significant difference in BCSS was foundLiu et al. Breast Cancer Research 2012, 14:R48http://breast-cancer-research.com/content/14/2/R48Page 5 of 14between cases with an iTIL count of at least 1 and thosewith an iTIL count of 0 among triple-negative breastcancers. By stratifying triple-negatives into core basaland 5NP subgroups, we observed a much larger differ-ence in BCSS between cases with an iTIL count of atleast 1 and those with an iTIL count of 0 in the corebasal intrinsic subgroup. Patients with an iTIL count ofat least 1 basal-like tumor had significantly better survi-val than those with an iTIL count of 0 (mean survivaltime of 14.5 vears versus 11.0 years, P < 0.001) (Figure2e). No such association was found among triple-nega-tive, non-basal (5NP) cases (Figure 2f). We also per-formed survival analysis in all patients with ER- breastcancer, excluding the core basal cases, and found no sig-nificant difference in BCSS between cases with an iTILcount of at least 1 and those with an iTIL count of 0 (P= 0.434).To confirm the association between iTIL and BCSSand to assess the independent prognostic effect size indifferent breast cancer intrinsic subgroups, multivariateCox proportional hazards regression models were builtto estimate the iTIL HRs, which were adjusted by thepotential confounders. Results in Table 3 showed thatthe HRs of iTIL were not significant in the luminal A,luminal B, and HER2+/ER- intrinsic subgroups. How-ever, iTIL was demonstrated to be a significantlya                                                                     b20.0015.0010. of follow-up                                                          Years of follow-upCumulative BCSSiTIL ≥ 1  n = 371  event = 107 iTIL = 0  n = 609  event = 22720.0015.0010. ≥ 1  n = 370  event = 113 iTIL = 0  n = 557  event = 225c                                                                     d20.0015.0010. = 0  n = 1690 event = 431 iTIL ≥ 1  n = 733  event = 21720.0015.0010. = 0  n = 1728 event = 432 iTIL ≥ 1  n = 728  event = 211iTIL = 0  15-year BCSS 61% (95% CI, 57-65)                                      iTIL = 0  15-year BCSS 70% (95% CI, 68-72)iTIL ≥ 1  15-year BCSS 70% (95% CI, 66-74)                                      iTIL ≥ 1  15-year BCSS 68% (95% CI, 64-72)Age < 50; p = 0.008                                                                              Age ≥ 50; p = 0.034  iTIL = 0  15-year BCSS 58% (95% CI, 54-62)                                      iTIL = 0  15-year BCSS 70% (95% CI, 68-72)iTIL ≥ 1  15-year BCSS 68% (95% CI, 64-72)                                      iTIL ≥ 1  15-year BCSS 68% (95% CI, 64-72)ER-; p = 0.003                                                                                      ER+; p = 0.046  Years of follow-up                                                          Years of follow-upCumulative BCSSCumulative BCSSCumulative BCSSFigure 1 Breast cancer-specific survival (BCSS) by intratumoral tumor-infiltrating lymphocytes (iTILs) among groups with different ageand estrogen receptor (ER) status. (a) Age of less than 50 years, (b) age of at least 50 years, (c) ER-, and (d) ER+. CI, confidence interval.Liu et al. Breast Cancer Research 2012, 14:R48http://breast-cancer-research.com/content/14/2/R48Page 6 of 14independent favorable factor for BCSS in triple-negativecases because of a strong effect in the core basal sub-group (Table 4). Among core basal cases, the presenceof any intratumoral CD8+ lymphocytes (iTILs of at least1) was associated with a 65% higher probability of BCSSthan among those tumors lacking intratumoral CD8+lymphocytes (iTIL of 0) and this was statistically signifi-cant even after adjusting for age at diagnosis, grade,tumor size, lymph node status, and LVI. Consideringthat medullary breast carcinoma, a histologically evidentsubtype known to carry a good prognosis, usually has acore basal immunophenotype and could be responsiblefor some of the observed effect, we repeated the multi-variate Cox regression analysis for core basal cases byexcluding those with medullary carcinoma (27 cases).The results still showed a similar and significant HR(HR = 0.38, 95% CI = 0.24 to 0.59), which thereforecould not be attributed to medullary histology. In con-trast, the multivariate analysis did not show any associa-tion between iTILs and BCSS in the 5NP subgroup (thatis, triple-negative breast cancers that do not expressbasal markers). These results demonstrated that theprognostic effect of iTILs was significantly different inthese two subgroups of triple-negative cases, indicatingthat the association of iTIL with BCSS exists primarilyin only the core basal intrinsic subgroup.Association of CD8+ sTILs and tTILs with clinical outcomeTo confirm the prognostic value of CD8+ TILs in breastcancer, we also evaluated the distributions of sTILs andtTILs in relation to patient and tumor characteristicsand the associations of sTILs and tTILs with survival.Results similar to those from the analysis with iTILswere obtained. In brief, high expressions of sTILs andtTILs were significantly correlated with young age, highgrade, larger tumor size, medullary histology, ER nega-tivity, HER2 positivity, and the core basal phenotype(Table S1 of Additional file 4) and again were signifi-cantly associated with better BCSS in only the corebasal intrinsic subgroup (Figure S3 of Additional file 5and Tables S2 and S3 of Additional file 4).DiscussionThe prognostic significance of TILs in breast cancer hasbeen debated, but no consistent conclusion has yet beendrawn. We implemented this study, using a particularlylarge, well-annotated cohort comprising nearly 4,000patients, in an attempt to definitively assess the clinicalimplication of TILs in breast cancer. In addition toaddressing the question of whether immune response(as measured by CD8+ TILs) has a prognostic role inbreast cancer in general, we examined the effect of TILsin the major breast cancer intrinsic biological subtypes.To our knowledge, this is the first study sufficientlypowered for multivariate analysis to investigate the asso-ciation of CD8+ TILs with patient survival within thebreast cancer intrinsic subtypes. Our results demon-strate that the presence of iTILs is independently asso-ciated with a significantly superior outcome in womenwith diagnosed core basal tumors. Although theTable 2 Hazards for breast cancer-specific survival in the whole cohort with univariate and multivariate analysesVariable Univariate analysis Multivariate analysisn = 3,144HR (95% CI) P value HR (95% CI) P valueAge≥ 50 vs. < 50 years 0.85 (0.75-0.96) 0.011 1.01 (0.88-1.16) 0.884Grade3 vs. 1 and 2 2.12 (1.87-2.41) < 0.001 1.57 (1.35-1.82) < 0.001Tumor size> 2 vs. ≤ 2 cm 2.17 (1.92-2.45) < 0.001 1.59 (1.36-1.83) < 0.001Nodal statusPositive vs. negative 2.79 (2.48-3.15) < 0.001 2.05 (1.76-2.39) < 0.001Lymphovascular invasionPositive vs. negative 2.25 (1.99-2.54) < 0.001 1.29 (1.10-1.51) 0.001SubtypeLuminal B vs. luminal A 2.08 (1.78-2.45) < 0.001 1.75 (1.46-2.09) < 0.001HER2+/ER- vs. luminal A 2.98 (2.40-3.70) < 0.001 2.51 (2.99-3.19) < 0.001Core basal vs. luminal A 2.30 (1.87-2.84) < 0.001 2.02 (1.58-2.58) < 0.0015NP vs. luminal A 1.65 (1.30-2.10) 0.002 1.49 (1.12-1.97) 0.011iTIL≥ 1 vs. 0 1.02 (0.89-1.17) 0.761 0.79 (0.68-0.91) < 0.0015NP, five negative phenotype; CI, confidence interval; ER, estrogen receptor; HER2, human epidermal growth factor receptor-2; HR, hazard ratio; iTIL, intratumoraltumor-infiltrating lymphocyte.Liu et al. Breast Cancer Research 2012, 14:R48http://breast-cancer-research.com/content/14/2/R48Page 7 of 14a                                                                      b                                     20.0015.0010.                                                                      d            20.0015.0010.                                                         e                                                                      f                        20.0015.0010. ≥ 1  n = 226  event = 57 iTIL = 0  n = 309  event = 121iTIL ≥ 1  n = 90  event = 35 iTIL = 0  n = 137  event = 70iTIL = 0  n = 50  event = 14iTIL ≥ 1  n = 92  event = 24iTIL ≥ 1  n = 151  event = 38 iTIL = 0  n = 156  event = 74iTIL = 0  n = 1039 event = 197 iTIL ≥ 1  n = 353  event = 79Years of follow-up                                                          Years of follow-upiTIL ≥ 1  n = 285  event = 102 iTIL = 0  n = 488  event = 175Years of follow-up                                                          Years of follow-upYears of follow-up                                                          Years of follow-upiTIL = 0  15-year BCSS 77% (95% CI, 73-81)                                      iTIL = 0  15-year BCSS 57% (95% CI, 51-63)iTIL ≥ 1  15-year BCSS 77% (95% CI, 73-81)                                      iTIL ≥ 1  15-year BCSS 60% (95% CI, 54-66)Luminal A; p = 0.104                                                                            Luminal B; p = 0.506  iTIL = 0  15-year BCSS 48% (95% CI, 40-56)                                      iTIL = 0  15-year BCSS 60% (95% CI, 54-66)iTIL ≥ 1  15-year BCSS 61% (95% CI, 51-71)                                      iTIL ≥ 1  15-year BCSS 74% (95% CI, 68-80)HER2+/ER-; p = 0.064                                                                           TNP; p = 0.001  iTIL = 0  15-year BCSS 52% (95% CI, 44-60)                                      iTIL = 0  15-year BCSS 72% (95% CI, 62-82)iTIL ≥ 1  15-year BCSS 74% (95% CI, 66-82)                                      iTIL ≥ 1  15-year BCSS 71% (95% CI, 59-83)CBP; p < 0.001                                                                                     5NP; p = 0.675  Cumulative BCSSCumulative BCSSCumulative BCSSCumulative BCSSCumulative BCSSCumulative BCSSFigure 2 Breast cancer-specific survival (BCSS) by intratumoral tumor-infiltrating lymphocytes (iTILs) in different breast cancer intrinsicsubgroups. (a) Luminal A, (b) luminal B, (c) HER2+/ER-, (d) triple-negative phenotype, (e) core basal phenotype, and (f) five negative phenotypesubgroups. CI, confidence interval; ER, estrogen receptor; HER2, human epidermal growth factor receptor-2.Liu et al. Breast Cancer Research 2012, 14:R48http://breast-cancer-research.com/content/14/2/R48Page 8 of 14presence of CD8+ iTILs is also an independent prognos-tic indicator for improved patient survival in triple-nega-tive breast cancers, this favorable prognostic effectcannot be detected among those lacking expression ofbasal biomarkers (5NP). In the core basal subgroup,patients having tumors with CD8+ iTILs survived anaverage of 3.5 years longer than did patients with basaltumors lacking evidence of a CD8+ iTIL immuneresponse.Breast cancer is both clinically and molecularly het-erogeneous and is, in practice, stratified by hormonalreceptors (ER and PR), by HER2 status, and, increas-ingly, by expression of other biomarkers such as Ki67 orby gene expression profiling methodologies. Dissectingthe heterogeneity of breast cancer is critically importantfor understanding the underlying mechanisms of thedisease and for identifying subpopulations that are mostlikely to respond to particular therapies [43]. In general,ER- breast cancers have a worse prognosis than thosethat are ER+, but not all patients with ER- breast cancerhave poor survival. Teschendorf and colleagues [44]applied an integrative analysis of three gene expressiondatasets to assess the prognostic value of molecular sig-natures and found that most prognostic markers of bet-ter prognosis in ER- breast cancer are associated withthe activation of immune response pathways. Further-more, a seven-gene immune response classifier was con-structed and showed significant good prognostic valuein patients with ER- breast cancer [45]. Meta-analyticstudies of clinical and gene expression data havedemonstrated that immune response is significantlyassociated with prognosis in breast cancer [46], primar-ily in rapidly proliferating [47] and ER- [48,49] sub-groups. Results from some studies indicate that TILscould be a protective factor reducing the likelihood ofdistant metastasis in patients with triple-negative breastTable 3 Hazards for breast cancer-specific survival with multivariate analysis in the luminal A, luminal B, and HER2+/ER- intrinsic subgroupsVariable Luminal A (n = 1,276) Luminal B (n = 709) HER2+/ER- (n = 216)HR P HR P HR PAge 1.38 1.04 1.13≥ 50 vs. < 50 years (1.02-1.86) 0.037 (0.81-1.35) 0.750 (0.75-1.70) 0.564Grade 1.75 1.28 2.133 vs. 1 and 2 (1.36-2.25) < 0.001 (0.99-1.67) 0.062 (1.21-3.76) 0.009Tumor size 1.64 1.49 1.73> 2 vs. ≤ 2 cm (1.28-2.11) < 0.001 (1.14-1.95) 0.004 (1.11-2.68) 0.015Nodal status 2.20 1.75 1.75Positive vs. negative (1.65-2.95) < 0.001 (1.31-2.32) < 0.001 (1.07-2.83) 0.025Lymphovascular invasion 1.12 1.33 1.36Positive vs. negative (0.84-1.49) 0.444 (0.99-1.77) 0.056 (0.84-2.18) 0.211iTIL 1.14 0.85 0.76≥ 1 vs. 0 (0.86-1.50) 0.357 (0.66-1.11) 0.235 (0.50-1.15) 0.194ER, estrogen receptor; HER2, human epidermal growth factor receptor-2; HR, hazard ratio; iTIL, intratumoral tumor-infiltrating lymphocyte.Table 4 Hazards for breast cancer-specific survival with multivariate analysis in TNP, core basal, and 5NP groupsVariable TNP (n = 496) Core basal (n = 287) 5NP (n = 130)HR P HR P HR PAge 0.90 0.91 1.07≥ 50 vs. < 50 years (0.66-1.22) 0.488 (0.62-1.35) 0.648 (0.54-2.14) 0.830Grade 1.74 1.54 1.813 vs. 1 and 2 (1.11-2.70) 0.015 (0.80-2.97) 0.201 (0.74-4.41) 0.191Tumor size 1.66 1.85 1.49> 2 vs. ≤ 2 cm (1.19-2.30) 0.003 (1.23-2.79) 0.003 (0.71-3.12) 0.293Nodal status 2.00 2.16 1.58Positive vs. negative (1.42-2.83) < 0.001 (1.39-3.35) 0.001 (0.73-3.42) 0.244Lymphovascular invasion 1.55 1.52 3.13Positive vs. negative (1.08-2.21) 0.017 (0.97-2.36) 0.065 (1.27-7.77) 0.013iTIL 0.48 0.35 0.99≥ 1 vs. 0 (0.34-0.67) < 0.001 (0.23-0.54) < 0.001 (0.48-2.04) 0.9865NP, five negative phenotype; HR, hazard ratio; iTIL, intratumoral tumor-infiltrating lymphocyte; TNP, triple-negative phenotype.Liu et al. Breast Cancer Research 2012, 14:R48http://breast-cancer-research.com/content/14/2/R48Page 9 of 14tumors [50] and among those with medullary carcinoma[17]. Moreover, two recently published gene expressionprofiling studies demonstrated that effective immune(particularly cytotoxic T-cell) response plays a favorableprognostic role in basal breast cancer subgroups [51,52].In our study, the multivariate analysis clearly demon-strates that the presence of CD8+ iTILs has a differentprognostic value in breast cancer with different intrinsicbiological subtypes. Even among the triple-negativecases, immune response has different meanings in corebasal versus ‘five negative’ phenotypes. Evidence fromprevious studies has shown that core basal-like tumorsare associated with a poorer prognosis and appear biolo-gically different from 5NP tumors [31,32]. Our resultssuggest that local immune response characterized byCD8+ lymphocyte infiltration might be considered animportant factor differentiating the core basal from 5NPbreast tumors within the class of triple-negative breastcancers.Tumor-infiltrating lymphocytes and macrophages arethought to be molecular determinants of clinical out-come in breast cancer. Although cytotoxic T lympho-cytes and natural killer cells have been found to haveantitumor activity, some lymphocytes such as B cellsexhibit bipolar roles in breast cancer development. Dis-tinct cell-mediated immune responses also play antago-nistic roles in disease prognosis. T helper cell 1 (Th1)-mediated immune response pathways are considered tohave an inhibitory effect, whereas Th2 immune responsepathways may promote development and metastasis ofbreast cancer. It has been found that CD4+ T lympho-cytes can promote metastasis by activating the EGFRsignaling pathway in a Th2-type tumor microenviron-ment [53]. Identification of interactions betweenimmune response and other molecular pathways maydefine novel prognostic subtypes. In ER- breast cancer,those characterized with high expression of EGFR andlow expression of Th1-mediated pathway-related mar-kers such as interleukin-12 and interferon-gamma werefound to have a poor prognosis [54]. TILs in the tumormicroenvironment are predominantly CD8+ T cells[55,56], which are considered to be the effector cells inTh1 antitumor immune responses. CD8+ T cells pro-duce interferon-gamma through interaction with tumor-related antigens, potential leading to tumoricidal activityby induction of apoptosis or macrophage tumor killingactivity or both [57]. Studies indicate that tumor-specificor even non-cancer-specific antigens such as p53 and b-actin are common targets of cytotoxic T lymphocytesand can induce immunological and clinical effects inpatients with breast cancer [58-60]. Findings from ourstudy suggest that core basal-like breast cancer is moreimmunogenic than other intrinsic subgroups, as mea-sured by CD8+ T-cell infiltration. Tumors of thissubtype have a high expression of basal markers, someof which (such as EGFR) may interact with T cell-mediated immune response to affect clinical outcome inbreast cancer. We would suggest a hypothesis that cer-tain ‘basal proteins’ expressed on the cell surface can berecognized as tumor antigens and that the consequentinduction of adaptive basal marker-specific immunitycan enhance the local Th1-mediated antitumor immuneresponse in these breast cancers. The absence of thesesurface markers in 5NP breast cancers could underpinthe observed difference in prognostic significance ofTILs in core basal compared with 5NP breast cancers.Recent studies have suggested that a pre-existingimmune response can strengthen the effect of conven-tional chemotherapy [61,62], enhancing destruction oftumor cells [63], and this favorable effect could becomestronger in patients with highly immunogenic tumors,perhaps including the core basal group. Basal-like breastcancers have distinctive survival patterns, many relapsesand deaths during the first 5 years after diagnosis, butfewer events after this period [32], indicating that basal-like breast cancers encompass both poor and good prog-nostic subgroups responding variably to conventionaltherapies. In our cohort, systemic treatment decisionswere not randomized, making outcomes stratified bytreatment difficult to interpret; nevertheless, an explora-tory analysis suggests that pre-treatment CD8+ lympho-cyte infiltration is an independent favorable predictiveindicator of good outcomes in basal-like cases treatedwith chemotherapy (HR = 0.29, 95% CI = 0.16 to 0.55, P< 0.001, n = 107) (Table S4 of Additional file 4). Ourresults indicate that efforts toward developing immuno-stimulative therapies might be best directed to the corebasal group. The recognition of tumor-associated anti-gens by CD8+ cells is a significant contributor to thedetection and ultimate destruction of tumor cells [64].Basal-like breast cancer could be particularly suitable fortargeted immunotherapy. The lack of success of priorattempts at immunotherapy for breast cancer may beattributable, in part, to the lack of focus on appropriatebreast cancer subtypes. A better understanding of theinteraction between immune response, intrinsic subtype,AST, and patient outcome is critical to more effectiveand targeted clinical management for patients with breastcancer, especially those with basal-like breast tumors.Studies on TILs in breast cancer have come to incon-sistent conclusions. We believe that one of the underly-ing reasons could be inconsistency in defining andmeasuring TILs. Some research considered only the pre-sence of peritumoral stromal lymphocytes [65,66], andmany considered all T lymphocytes (which mightinclude larger numbers of regulatory T cells that couldin some cases reflect immune suppression instead ofactivation). In our study, specific immunohistochemistryLiu et al. Breast Cancer Research 2012, 14:R48http://breast-cancer-research.com/content/14/2/R48Page 10 of 14was used with a mouse monoclonal anti-human CD8antibody to detect cytotoxic effector CD8+ TILs in intra-tumoral and stromal locations for each tumor tissuecore. We evaluated the reliability of repeated scoring bythe same scorer and between different scorers, and itwas demonstrated that our visual CD8+ TILs scoringwas highly reliable (Figure S4 of Additional file 6). Ana-lyses with intratumoral, stromal, and total CD8+ TILswere conducted, and consistent results were obtained.We also did analyses using relapse-free survival as anoutcome and obtained results similar to those usingBCSS as the outcome (Figures S5 and S6 of Additionalfiles 7 and 8 and Tables S5 to S7 of Additional file 4).Thus, we are confident that the identification and quan-tification of TILs and the assessment of the associationof TILs with clinical outcome in breast cancer are reli-able and valid in this study. One potential limitation ofour methods is that TMAs may not adequately repre-sent breast tumor heterogeneity. Several studies never-theless have shown that findings from TMAs areconsistent with those from full-face tissue sections[67,68]. Although we observed a trend to a favorableprognostic effect of CD8 TILs in the HER2+/ER- sub-group (and this trend is consistent with a gene expres-sion study [69]), the effect was not statisticallysignificant in our univariate or multivariate analyses.Research with more power particularly for this subgroupneeds to be done to draw a more definitive conclusionamong HER2+ cases. We were not able to measurechanges in immune response induced by chemotherapy,as all of the tissue samples were collected beforepatients received systemic therapy. Further studieswould need to be conducted to assess the interaction ofTILs with chemotherapy, ideally in randomized trials.ConclusionsThis study provides strong evidence that CD8+ lympho-cyte infiltration is an independent factor associated withimproved survival in patients with breast cancer. Thefavorable prognostic effects of TILs occur mostly in thebasal-like intrinsic subgroup.Additional materialAdditional file 1: Validation of the cutoff points of TILs. TheSupplemental method section explained how the receiver operatingcharacteristic (ROC) analysis was used to validate the optimal cutoffs ofTILs chosen from an independent study. To take into consideration thatoutcome variable, breast cancer specific survival, is a time to eventendpoint, X-tile software was also used to validate the optimal cut-offs,and the same cutoff points of iTIL and sTIL were obtained as those fromthe ROC method.Additional file 2: CD8+ TILs in breast cancer. This image showedsome examples of CD8+ iTIL and sTIL in a breast tumor sample (scalebar: 50 μm). Information with respect to availability of all of our CD8staining images were provided in the figure legend.Additional file 3: Distributions of CD8+ iTIL and sTIL in the wholecohort. Histograms were used to show the distributions of CD8+ iTILand sTIL in the whole study population. Values on the X-axis representabsolute counts of CD8+ iTIL (A) or sTIL (B) per tissue microarry core.Additional file 4: Supplemental tables. Table S1 showed thedistributions of CD8+ sTIL and tTIL in relation to patient and tumorcharacteristics. Table S2 showed the hazard ratios (HRs) of sTIL and tTILin the whole cohort with multivariate Cox regression analysis, adjustedby age at diagnosis, tumor grade and size, lymph node status,lymphovascular invasion, and intrinsic subtype. Table S3 showed the HRsof sTIL and tTIL in triple negative (TNP), core basal (CBP), and fivenegative (5NP) breast cancer intrinsic subgroups in multivariate analysis.Table S4 showed the HRs of iTIL, sTIL and tTIL in patients withoutadjuvant systemic therapy (AST) and with chemotherapy in multivariateanalysis. Table S5 showed HRs of iTIL in the whole cohort with univariateand mulvariate analysis, using relapse-free survival (RFS) as the outcomevariable. Tables S6 and S7 showed the HRs of iTIL in different intrinsicsubgroups with multivariate Cox regression analysis using RFS as theoutcome variable.Additional file 5: Breast cancer specific survival (BCSS) by sTIL andtTIL in different breast cancer intrinsic subgroups. Kaplan-Meierfunction survival analysis of association of TILs with BCSS: (A) sTIL in triplenegative (TNP), (B) tTIL in TNP, (C) sTIL in core basal (CBP), (D) tTIL in CBP,(E) sTIL in five negative (5NP), and (F) tTIL in 5NP.Additional file 6: Correlation of re-scoring of CD8+ TILs by thesame and different pathologists. The scatter plots demonstratedcorrelations of repeated scoring for 490 cases by the same pathologistfor CD8+ iTIL (A) and sTIL (B), and re-scoring of CD8+ iTIL for 200 casesby two pathologists (C).Additional file 7: Relapse-free survival (RFS) by iTIL among groupswith different age and ER status. Kaplan-Meier function survivalanalysis of association between iTIL and RFS in: (A) age < 50 year, (B) age≥ 50 year; (C) ER-, and (D) ER+.Additional file 8: Relapse-free survival (RFS) by iTIL in differentbreast cancer intrinsic subgroups. Kaplan-Meier function survivalanalysis of association between iTIL and RFS in: (A) luminal A, (B) luminalB, (C) HER2+/ER-, (D) Triple negative, (E) core basal, and (F) five negativesubgroups.Abbreviations5NP: five negative phenotype; AST: adjuvant systemic therapy; BCCA: BritishColumbia Cancer Agency; BCSS: breast cancer-specific survival; CI: confidenceinterval; CK: cytokeratin; EGFR: epidermal growth factor receptor; ER:estrogen receptor; HER2: human epidermal growth factor receptor-2; HR:hazard ratio; ICC: intraclass correlation coefficient; IQR: interquartile range;iTIL: intratumoral tumor-infiltrating lymphocyte; LVI: lymphovascular invasion;PR: progesterone receptor; sTIL: stromal tumor-infiltrating lymphocyte; Th: Thelper; TIL: tumor-infiltrating lymphocyte; TMA: tissue microarray; TNP: triple-negative phenotype; tTIL: total CD8+ tumor-infiltrating lymphocyte.AcknowledgementsWe thank present and former members of the Breast Cancer Outcomes Unitand Genetic Pathology Evaluation Centre for assembly of the tissuemicroarray series and clinical database. We thank Inti Zlobec for statisticalanalysis assistance. This study was supported by a Canadian Breast CancerResearch Alliance Translation Acceleration Grant and the National CancerInstitute Strategic Partnering to Evaluate Cancer Signatures program (UO1-CA114722) (TON) and Susan G Komen for the Cure (WDF). TON is a MichaelSmith Foundation for Health Research Senior Scholar. WDF is a ChercheurNational of the Fonds de Recherche en Santé du Québec. The GeneticPathology Evaluation Centre is supported by an unrestricted educationalgrant from Sanofi (Montreal, Canada).Author details1Genetic Pathology Evaluation Centre, Department of Pathology andLaboratory Medicine, University of British Columbia, 2660 Oak Street,Vancouver, BC, V6H 3Z6, Canada. 2Department of Pathology, McGillLiu et al. Breast Cancer Research 2012, 14:R48http://breast-cancer-research.com/content/14/2/R48Page 11 of 14University, 3775 University Street, Montreal, QC, H3A 2B2, Canada. 3Programin Cancer Genetics, Department of Oncology and Human Genetics, McGillUniversity, 546 Pine Avenue West, Montreal, QC, H2W 1S6, Canada.4Department of Medical Genetics, Lady Davis Institute, Segal Cancer Centre,Jewish General Hospital, 3755 Chemin de la Côte-Sainte-Catherine, Montreal,QC, H3T 1E2, Canada. 5Medical Genetics and Genomics Axis, ResearchInstitute of the McGill University Health Centre, 1650 Cedar Avenue,Montreal, QC, H3G 1A4, Canada.Authors’ contributionsSLi coordinated the study, analyzed data, and drafted the manuscript. JLadvised on scoring and edited the manuscript. SLe assisted with statisticalanalyses. DG generated primary data. WDF provided the idea for the study,helped with data analysis, and edited the manuscript. TON organized thestudy, directed data generation and analysis, and edited the manuscript. Allauthors read and approved the final manuscript.Competing interestsThe authors declare that they have no competing interests.Received: 23 September 2011 Revised: 14 February 2012Accepted: 15 March 2012 Published: 15 March 2012References1. Tsuta K, Ishii G, Kim E, Shiono S, Nishiwaki Y, Endoh Y, Kodama T, Nagai K,Nagai K: Primary lung adenocarcinoma with massive lymphocyteinfiltration. Am J Clin Pathol 2005, 123:547-552.2. Canna K, McArdle PA, McMillan DC, McNicol AM, Smith GW, McKee RF,McArdle CS: The relationship between tumour T-lymphocyte infiltration,the systemic inflammatory response and survival in patients undergoingcurative resection for colorectal cancer. Br J Cancer 2005, 92:651-654.3. Zhang L, Conejo-Garcia JR, Katsaros D, Gimotty PA, Massobrio M,Regnani G, Makrigiannakis A, Gray H, Schlienger K, Liebman MN, Rubin SC,Coukos G: Intratumoral T cells, recurrence, and survival in epithelialovarian cancer. N Engl J Med 2003, 348:203-213.4. Clemente CG, Mihm MC Jr, Bufalino R, Zurrida S, Collini P, Cascinelli N:Prognostic value of tumor infiltrating lymphocytes in the vertical growthphase of primary cutaneous melanoma. Cancer 1996, 77:1303-1310.5. Furihata M, Ohtsuki Y, Sonobe H, Araki K, Ogata T, Toki T, Ogoshi S,Tamiya T: Prognostic significance of simultaneous infiltration of HLA-DR-positive dendritic cells and tumor infiltrating lymphocytes into humanesophageal carcinoma. Tohoku J Exp Med 1993, 169:187-195.6. Jass JR: Lymphocytic infiltration and survival in rectal cancer. J Clin Pathol1986, 39:585-589.7. Menard S, Tomasic G, Casalini P, Balsari A, Pilotti S, Cascinelli N, Salvadori B,Colnaghi MI, Rilke F: Lymphoid infiltration as a prognostic variable forearly-onset breast carcinomas. Clin Cancer Res 1997, 3:817-819.8. Nakano O, Sato M, Naito Y, Suzuki K, Orikasa S, Aizawa M, Suzuki Y,Shintaku I, Nagura H, Ohtani H: Proliferative activity of intratumoral CD8(+) T-lymphocytes as a prognostic factor in human renal cell carcinoma:clinicopathologic demonstration of antitumor immunity. Cancer Res 2001,61:5132-5136.9. Schondorf T, Engel H, Lindemann C, Kolhagen H, von Rucker AA,Mallmann P: Cellular characteristics of peripheral blood lymphocytes andtumour-infiltrating lymphocytes in patients with gynaecologicaltumours. Cancer Immunol Immunother 1997, 44:88-96.10. Ben-Hur H, Cohen O, Schneider D, Gurevich P, Halperin R, Bala U, Mozes M,Zusman I: The role of lymphocytes and macrophages in human breasttumorigenesis: an immunohistochemical and morphometric study.Anticancer Res 2002, 22:1231-1238.11. Leong PP, Mohammad R, Ibrahim N, Ithnin H, Abdullah M, Davis WC,Seow HF: Phenotyping of lymphocytes expressing regulatory andeffector markers in infiltrating ductal carcinoma of the breast. ImmunolLett 2006, 102:229-236.12. Schillaci R, Salatino M, Cassataro J, Proietti CJ, Giambartolomei GH,Rivas MA, Carnevale RP, Charreau EH, Elizalde PV: Immunization withmurine breast cancer cells treated with antisense oligodeoxynucleotidesto type I insulin-like growth factor receptor induced an antitumoraleffect mediated by a CD8+ response involving Fas/Fas ligand cytotoxicpathway. J Immunol 2006, 176:3426-3437.13. Dobrzanski MJ, Reome JB, Hylind JC, Rewers-Felkins KA: CD8-mediatedtype 1 antitumor responses selectively modulate endogenousdifferentiated and nondifferentiated T cell localization, activation, andfunction in progressive breast cancer. J Immunol 2006, 177:8191-8201.14. Pages F, Berger A, Camus M, Sanchez-Cabo F, Costes A, Molidor R,Mlecnik B, Kirilovsky A, Nilsson M, Damotte D, Meatchi T, Bruneval P,Cugnenc PH, Trajanoski Z, Fridman WH, Galon J: Effector memory T cells,early metastasis, and survival in colorectal cancer. N Engl J Med 2005,353:2654-2666.15. Lee AH, Gillett CE, Ryder K, Fentiman IS, Miles DW, Millis RR: Differentpatterns of inflammation and prognosis in invasive carcinoma of thebreast. Histopathology 2006, 48:692-701.16. Yakirevich E, Izhak OB, Rennert G, Kovacs ZG, Resnick MB: Cytotoxicphenotype of tumor infiltrating lymphocytes in medullary carcinoma ofthe breast. Mod Pathol 1999, 12:1050-1056.17. Rakha EA, Aleskandarany M, El-Sayed ME, Blamey RW, Elston CW, Ellis IO,Lee AH: The prognostic significance of inflammation and medullaryhistological type in invasive carcinoma of the breast. Eur J Cancer 2009,45:1780-1787.18. Matkowski R, Gisterek I, Halon A, Lacko A, Szewczyk K, Staszek U,Pudelko M, Szynglarewicz B, Szelachowska J, Zolnierek A, Kornafel J: Theprognostic role of tumor-infiltrating CD4 and CD8 T lymphocytes inbreast cancer. Anticancer Res 2009, 29:2445-2451.19. Carlomagno C, Perrone F, Lauria R, de Laurentiis M, Gallo C, Morabito A,Pettinato G, Panico L, Bellelli T, Apicella A: Prognostic significance ofnecrosis, elastosis, fibrosis and inflammatory cell reaction in operablebreast cancer. Oncology 1995, 52:272-277.20. Aaltomaa S, Lipponen P, Eskelinen M, Kosma VM, Marin S, Alhava E,Syrjanen K: Lymphocyte infiltrates as a prognostic variable in femalebreast cancer. Eur J Cancer 1992, 28A:859-864.21. Camp BJ, Dyhrman ST, Memoli VA, Mott LA, Barth RJ Jr: In situ cytokineproduction by breast cancer tumor-infiltrating lymphocytes. Ann SurgOncol 1996, 3:176-184.22. Liu F, Lang R, Zhao J, Zhang X, Pringle GA, Fan Y, Yin D, Gu F, Yao Z, Fu L:CD8(+) cytotoxic T cell and FOXP3(+) regulatory T cell infiltration inrelation to breast cancer survival and molecular subtypes. Breast CancerRes Treat 2011, 130:645-655.23. Mahmoud SM, Paish EC, Powe DG, Macmillan RD, Grainge MJ, Lee AH,Ellis IO, Green AR: Tumor-infiltrating CD8+ lymphocytes predict clinicaloutcome in breast cancer. J Clin Oncol 2011, 29:1949-1955.24. Baker K, Lachapelle J, Zlobec I, Bismar TA, Terracciano L, Foulkes WD:Prognostic significance of CD8(+) T lymphocytes in breast cancerdepends upon both oestrogen receptor status and histological grade.Histopathology 2011, 58:1107-1116.25. Eden P, Ritz C, Rose C, Ferno M, Peterson C: ’Good Old’ clinical markershave similar power in breast cancer prognosis as microarray geneexpression profilers. Eur J Cancer 2004, 40:1837-1841.26. Nimeus-Malmstrom E, Ritz C, Eden P, Johnsson A, Ohlsson M, Strand C,Ostberg G, Ferno M, Peterson C: Gene expression profilers andconventional clinical markers to predict distant recurrences forpremenopausal breast cancer patients after adjuvant chemotherapy. EurJ Cancer 2006, 42:2729-2737.27. Cleator S, Ashworth A: Molecular profiling of breast cancer: clinicalimplications. Br J Cancer 2004, 90:1120-1124.28. Early Breast Cancer Trialists’ Collaborative Group (EBCTCG): Effects ofchemotherapy and hormonal therapy for early breast cancer onrecurrence and 15-year survival: an overview of the randomised trials.Lancet 2005, 365:1687-1717.29. Carey L, Winer E, Viale G, Cameron D, Gianni L: Triple-negative breastcancer: disease entity or title of convenience? Nat Rev Clin Oncol 2010,7:683-692.30. Bertucci F, Finetti P, Cervera N, Esterni B, Hermitte F, Viens P, Birnbaum D:How basal are triple-negative breast cancers? Int J Cancer 2008,123:236-240.31. Cheang MC, Voduc D, Bajdik C, Leung S, McKinney S, Chia SK, Perou CM,Nielsen TO: Basal-like breast cancer defined by five biomarkers hassuperior prognostic value than triple-negative phenotype. Clin Cancer Res2008, 14:1368-1376.32. Blows FM, Driver KE, Schmidt MK, Broeks A, van Leeuwen FE, Wesseling J,Cheang MC, Gelmon K, Nielsen TO, Blomqvist C, Heikkila P, Heikkinen T,Nevanlinna H, Akslen LA, Begin LR, Foulkes WD, Couch FJ, Wang X,Liu et al. Breast Cancer Research 2012, 14:R48http://breast-cancer-research.com/content/14/2/R48Page 12 of 14Cafourek V, Olson JE, Baglietto L, Giles GG, Severi G, McLean CA,Southey MC, Rakha E, Green AR, Ellis IO, Sherman ME, Lissowska J, et al:Subtyping of breast cancer by immunohistochemistry to investigate arelationship between subtype and short and long term survival: acollaborative analysis of data for 10,159 cases from 12 studies. PLoS Med2010, 7:e1000279.33. Bertucci F, Finetti P, Rougemont J, Charafe-Jauffret E, Cervera N, Tarpin C,Nguyen C, Xerri L, Houlgatte R, Jacquemier J, Viens P, Birnbaum D: Geneexpression profiling identifies molecular subtypes of inflammatorybreast cancer. Cancer Res 2005, 65:2170-2178.34. Bertucci F, Finetti P, Cervera N, Charafe-Jauffret E, Mamessier E, Adelaide J,Debono S, Houvenaeghel G, Maraninchi D, Viens P, Charpin C,Jacquemier J, Birnbaum D: Gene expression profiling shows medullarybreast cancer is a subgroup of basal breast cancers. Cancer Res 2006,66:4636-4644.35. Mouawad R, Spano JP, Khayat D: Lymphocyte infiltration in breast cancer:a key prognostic factor that should not be ignored. J Clin Oncol 2011,29:1935-1936.36. Qian BZ, Pollard JW: Macrophage diversity enhances tumor progressionand metastasis. Cell 2010, 141:39-51.37. Cheang MC, Treaba DO, Speers CH, Olivotto IA, Bajdik CD, Chia SK,Goldstein LC, Gelmon KA, Huntsman D, Gilks CB, Nielsen TO, Gown AM:Immunohistochemical detection using the new rabbit monoclonalantibody SP1 of estrogen receptor in breast cancer is superior to mousemonoclonal antibody 1D5 in predicting survival. J Clin Oncol 2006,24:5637-5644.38. Lohrisch C, Jackson J, Jones A, Mates D, Olivotto IA: Relationship betweentumor location and relapse in 6,781 women with early invasive breastcancer. J Clin Oncol 2000, 18:2828-2835.39. Liu S, Chia SK, Mehl E, Leung S, Rajput A, Cheang MC, Nielsen TO:Progesterone receptor is a significant factor associated with clinicaloutcomes and effect of adjuvant tamoxifen therapy in breast cancerpatients. Breast Cancer Res Treat 2010, 119:53-61.40. Chia S, Norris B, Speers C, Cheang M, Gilks B, Gown AM, Huntsman D,Olivotto IA, Nielsen TO, Gelmon K: Human epidermal growth factorreceptor 2 overexpression as a prognostic factor in a large tissuemicroarray series of node-negative breast cancers. J Clin Oncol 2008,26:5697-5704.41. Nielsen TO, Hsu FD, Jensen K, Cheang M, Karaca G, Hu Z, Hernandez-Boussard T, Livasy C, Cowan D, Dressler L, Akslen LA, Ragaz J, Gown AM,Gilks CB, van de Rijn M, Perou CM: Immunohistochemical and clinicalcharacterization of the basal-like subtype of invasive breast carcinoma.Clin Cancer Res 2004, 10:5367-5374.42. Cheang MC, Chia SK, Voduc D, Gao D, Leung S, Snider J, Watson M,Davies S, Bernard PS, Parker JS, Perou CM, Ellis MJ, Nielsen TO: Ki67 index,HER2 status, and prognosis of patients with luminal B breast cancer. JNatl Cancer Inst 2009, 101:736-750.43. Gatza ML, Lucas JE, Barry WT, Kim JW, Wang Q, Crawford MD, Datto MB,Kelley M, Mathey-Prevot B, Potti A, Nevins JR: A pathway-basedclassification of human breast cancer. Proc Natl Acad Sci USA 2010,107:6994-6999.44. Teschendorff AE, Miremadi A, Pinder SE, Ellis IO, Caldas C: An immuneresponse gene expression module identifies a good prognosis subtypein estrogen receptor negative breast cancer. Genome Biol 2007, 8:R157.45. Teschendorff AE, Caldas C: A robust classifier of high predictive value toidentify good prognosis patients in ER-negative breast cancer. BreastCancer Res 2008, 10:R73.46. Reyal F, van Vliet MH, Armstrong NJ, Horlings HM, de Visser KE, Kok M,Teschendorff AE, Mook S, van’t Veer L, Caldas C, Salmon RJ, van deVijver MJ, Wessels LF: A comprehensive analysis of prognostic signaturesreveals the high predictive capacity of the proliferation, immuneresponse and RNA splicing modules in breast cancer. Breast Cancer Res2008, 10:R93.47. Schmidt M, Bohm D, von Torne C, Steiner E, Puhl A, Pilch H, Lehr HA,Hengstler JG, Kolbl H, Gehrmann M: The humoral immune system has akey prognostic impact in node-negative breast cancer. Cancer Res 2008,68:5405-5413.48. Desmedt C, Haibe-Kains B, Wirapati P, Buyse M, Larsimont D, Bontempi G,Delorenzi M, Piccart M, Sotiriou C: Biological processes associated withbreast cancer clinical outcome depend on the molecular subtypes. ClinCancer Res 2008, 14:5158-5165.49. Calabro A, Beissbarth T, Kuner R, Stojanov M, Benner A, Asslaber M,Ploner F, Zatloukal K, Samonigg H, Poustka A, Sultmann H: Effects ofinfiltrating lymphocytes and estrogen receptor on gene expression andprognosis in breast cancer. Breast Cancer Res Treat 2009, 116:69-77.50. Kreike B, van Kouwenhove M, Horlings H, Weigelt B, Peterse H, Bartelink H,van de Vijver MJ: Gene expression profiling and histopathologicalcharacterization of triple-negative/basal-like breast carcinomas. BreastCancer Res 2007, 9:R65.51. Sabatier R, Finetti P, Cervera N, Lambaudie E, Esterni B, Mamessier E,Tallet A, Chabannon C, Extra JM, Jacquemier J, Viens P, Birnbaum D,Bertucci F: A gene expression signature identifies two prognosticsubgroups of basal breast cancer. Breast Cancer Res Treat 2011,126:407-420.52. Sabatier R, Finetti P, Mamessier E, Raynaud S, Cervera N, Lambaudie E,Jacquemier J, Viens P, Birnbaum D, Bertucci F: Kinome expression profilingand prognosis of basal breast cancers. Mol Cancer 2011, 10:86.53. DeNardo DG, Barreto JB, Andreu P, Vasquez L, Tawfik D, Kolhatkar N,Coussens LM: CD4(+) T cells regulate pulmonary metastasis of mammarycarcinomas by enhancing protumor properties of macrophages. CancerCell 2009, 16:91-102.54. Teschendorff AE, Gomez S, Arenas A, El-Ashry D, Schmidt M, Gehrmann M,Caldas C: Improved prognostic classification of breast cancer defined byantagonistic activation patterns of immune response pathway modules.BMC Cancer 2010, 10:604.55. Whitford P, Mallon EA, George WD, Campbell AM: Flow cytometric analysisof tumour infiltrating lymphocytes in breast cancer. Br J Cancer 1990,62:971-975.56. Georgiannos SN, Renaut A, Goode AW, Sheaff M: The immunophenotypeand activation status of the lymphocytic infiltrate in human breastcancers, the role of the major histocompatibility complex in cell-mediated immune mechanisms, and their association with prognosticindicators. Surgery 2003, 134:827-834.57. Smyth MJ, Dunn GP, Schreiber RD: Cancer immunosurveillance andimmunoediting: the roles of immunity in suppressing tumordevelopment and shaping tumor immunogenicity. Adv Immunol 2006,90:1-50.58. Pedersen AE, Stryhn A, Justesen S, Harndahl M, Rasmussen S, Donskov F,Claesson MH, Pedersen JW, Wandall HH, Svane IM, Buus S: Wildtype p53-specific antibody and T-cell responses in cancer patients. J Immunother2011, 34:629-640.59. Svane IM, Pedersen AE, Johansen JS, Johnsen HE, Nielsen D, Kamby C,Ottesen S, Balslev E, Gaarsdal E, Nikolajsen K, Claesson MH: Vaccinationwith p53 peptide-pulsed dendritic cells is associated with diseasestabilization in patients with p53 expressing advanced breast cancer;monitoring of serum YKL-40 and IL-6 as response biomarkers. CancerImmunol Immunother 2007, 56:1485-1499.60. Hansen MH, Nielsen H, Ditzel HJ: The tumor-infiltrating B cell response inmedullary breast cancer is oligoclonal and directed against theautoantigen actin exposed on the surface of apoptotic cancer cells. ProcNatl Acad Sci USA 2001, 98:12659-12664.61. Apetoh L, Tesniere A, Ghiringhelli F, Kroemer G, Zitvogel L: Molecularinteractions between dying tumor cells and the innate immune systemdetermine the efficacy of conventional anticancer therapies. Cancer Res2008, 68:4026-4030.62. Zitvogel L, Apetoh L, Ghiringhelli F, Kroemer G: Immunological aspects ofcancer chemotherapy. Nat Rev Immunol 2008, 8:59-73.63. Zitvogel L, Apetoh L, Ghiringhelli F, Andre F, Tesniere A, Kroemer G: Theanticancer immune response: indispensable for therapeutic success?J Clin Invest 2008, 118:1991-2001.64. Del Campo AB, Carretero J, Aptsiauri N, Garrido F: Targeting HLA class Iexpression to increase tumor immunogenicity. Tissue Antigens 2012,79:147-154.65. Putti TC, El-Rehim DM, Rakha EA, Paish CE, Lee AH, Pinder SE, Ellis IO:Estrogen receptor-negative breast carcinomas: a review of morphologyand immunophenotypical analysis. Mod Pathol 2005, 18:26-35.66. Wernicke M, Roitman P, Manfre D, Stern R: Breast cancer and the stromalfactor. The ‘prometastatic healing process’ hypothesis. Medicina (B Aires)2011, 71:15-21.67. Schraml P, Kononen J, Bubendorf L, Moch H, Bissig H, Nocito A,Mihatsch MJ, Kallioniemi OP, Sauter G: Tissue microarrays for geneLiu et al. Breast Cancer Research 2012, 14:R48http://breast-cancer-research.com/content/14/2/R48Page 13 of 14amplification surveys in many different tumor types. Clin Cancer Res1999, 5:1966-1975.68. Torhorst J, Bucher C, Kononen J, Haas P, Zuber M, Kochli OR, Mross F,Dieterich H, Moch H, Mihatsch M, Kallioniemi OP, Sauter G: Tissuemicroarrays for rapid linking of molecular changes to clinical endpoints.Am J Pathol 2001, 159:2249-2256.69. Alexe G, Dalgin GS, Scanfeld D, Tamayo P, Mesirov JP, DeLisi C, Harris L,Barnard N, Martel M, Levine AJ, Ganesan S, Bhanot G: High expression oflymphocyte-associated genes in node-negative HER2+ breast cancerscorrelates with lower recurrence rates. Cancer Res 2007, 67:10669-10676.doi:10.1186/bcr3148Cite this article as: Liu et al.: CD8+ lymphocyte infiltration is anindependent favorable prognostic indicator in basal-like breast cancer.Breast Cancer Research 2012 14:R48.Submit your next manuscript to BioMed Centraland take full advantage of: • Convenient online submission• Thorough peer review• No space constraints or color figure charges• Immediate publication on acceptance• Inclusion in PubMed, CAS, Scopus and Google Scholar• Research which is freely available for redistributionSubmit your manuscript at www.biomedcentral.com/submitLiu et al. Breast Cancer Research 2012, 14:R48http://breast-cancer-research.com/content/14/2/R48Page 14 of 14


Citation Scheme:


Citations by CSL (citeproc-js)

Usage Statistics



Customize your widget with the following options, then copy and paste the code below into the HTML of your page to embed this item in your website.
                            <div id="ubcOpenCollectionsWidgetDisplay">
                            <script id="ubcOpenCollectionsWidget"
                            async >
IIIF logo Our image viewer uses the IIIF 2.0 standard. To load this item in other compatible viewers, use this url:


Related Items