- Research article
- Open Access
Detailed characterization of tumor infiltrating lymphocytes in two distinct human solid malignancies show phenotypic similarities
© Kovacsovics-Bankowski et al.; licensee BioMed Central Ltd. 2014
Received: 27 May 2014
Accepted: 22 September 2014
Published: 18 November 2014
We examined the phenotype and function of lymphocytes collected from the peripheral blood (PBL) and tumor (TIL) of patients with two different solid malignancies: colorectal cancer liver metastases (CRLM) and ovarian cancer (OVC).
Tumor and corresponding peripheral blood were collected from 16 CRLM and 22 OVC patients; immediately following resection they were processed and analyzed using a multi-color flow cytometry panel. Cytokine mRNA from purified PBL and TIL CD4+ T cells were also analyzed by qPCR.
Overall, we found similar changes in the phenotypic and cytokine profiles when the TIL were compared to PBL from patients with two different malignancies. The percentage of Treg (CD4+/CD25+/FoxP3+) in PBL and TIL was similar: 8.1% versus 10.2%, respectively in CRLM patients. However, the frequency of Treg in primary OVC TIL was higher than PBL: 19.2% versus 4.5% (p <0.0001). A subpopulation of Treg expressing HLA-DR was markedly increased in TIL compared to PBL in both tumor types, CRLM: 69.0% versus 31.7% (p = 0.0002) and OVC 74.6% versus 37.0% (p <0.0001), which suggested preferential Treg activation within the tumor. The cytokine mRNA profile showed that IL-6, a cytokine known for its immunosuppressive properties through STAT3 upregulation, was increased in TIL samples in patients with OVC and CRLM. Both TIL populations also contained a significantly higher proportion of activated CD8+ T cells (HLA-DR+/CD38+) compared to PBL (CRLM: 30.2% vs 7.7%, (p = 0.0012), OVC: 57.1% vs 12.0%, (p <0.0001)).
This study demonstrates that multi-color flow cytometry of freshly digested tumor samples reveals phenotypic differences in TIL vs PBL T cell sub-populations. The TIL composition in primary and metastatic tumors from two distinct histologies were remarkably similar, showing a greater proportion of activated/suppressive Treg (HLA-DR+, CD39+, CTLA-4+ and Helios+) and activated cytotoxic T cells (CD8+/HLA-DR+/CD38+) when compared to PBL and an increase in IL-6 mRNA from CD4 TIL.
Tumor immunotherapy has emerged as an important treatment modality for cancer patients. Historically, melanoma and renal cell carcinoma have been described as tumors that respond to immunotherapy. However, recent clinical trials have shown that a variety of other tumor types are also responding to immunotherapy -.
The mechanism(s) of tumor rejection following immunotherapy treatment have been difficult to define. Until recently, most immunologic analyses in cancer patients have been conducted on PBL or tissue sections, where samples are more easily obtained. However, it is the composition of the immune cells at the tumor site that is likely to be most important; and the tumor infiltrating lymphocytes (TIL) may be quite different from the PBL. Furthermore it is extremely hard to perform immune subset analyses by immunohistochemistry. Therefore to gain a deeper understanding of how immunotherapy could potentially affect the tumor microenvironment, it would be important to first characterize the subset distribution and phenotype of the immune cells in progressively growing tumors.
The purpose of this study was to compare the phenotype and function of freshly isolated TIL to PBL in patients with progressively growing tumors by flow cytometry. Several studies, using primarily immunohistochemistry, have shown that greater frequencies of Treg cells within the tumor environment leads to a decrease in patient survival ,. Increased Treg inhibitory function has been associated with increases in several surface and/or intra-cellular markers. Treg cells with the greatest suppressive capacity express high levels of HLA-DR and CD39 on their surface and a decline in this population has been associated with renal graft rejection or premature delivery ,. In contrast to Treg frequency and phenotype, increased levels of CD8+ T cells in TIL has been associated with a positive clinical outcome in patients with CRC . However, these studies did not examine the activation status of CD8+ T cells. We have used the co-expression of HLA-DR and CD38 as well as the proliferation marker Ki-67 to determine the activation status of CD8+ T cells isolated from TIL vs blood.
In this study, we analyzed fresh tumor and paired peripheral blood samples from patients with CRC and OVC; we compared the function and phenotype of lymphocytes from TIL to those in peripheral blood. The first group was composed of patients undergoing resection of colorectal cancer liver metastases (CRLM), while the second enrolled women undergoing cytoreductive surgery for ovarian cancer.
CRC is the third most common cause of cancer-related deaths worldwide and liver is the most common site of this metastatic disease. Fifteen percent of patients with CRC, are diagnosed with liver metastasis at the same time as their primary tumor and another 15% will develop liver metastases after resection of the primary tumor . Surgical resection is the primary treatment option for operable metastases but is associated with a recurrence rate of 50-90% -. The medical treatment after surgical resection has traditionally been cytotoxic chemotherapy and recent studies have suggested that the immune response has important prognostic implications for CRC patients ,.
Ovarian Cancer represents only 3% of female cancers, but it is the fifth leading cause of cancer-related death in women. Most patients are diagnosed in advanced stage (spread beyond the pelvis, 75%) due to lack of effective early detection strategies. Surgical debulking is the standard of care followed by chemotherapy with paclitaxel and carboplatin. Unfortunately, the relapse rate after treatment is high, up to 75%. Many different strategies have been attempted to reduce relapse rates with little success. Several studies summarized in a meta-analysis by Hwang et al. , have suggested that the composition of TIL also has prognostic significance.
The results of this study demonstrate that the composition of T lymphocytes within CRLM and ovarian tumors is significantly different than peripheral blood T lymphocytes from the same patient. Within the tumor microenvironment, there was a significant increase in both activated Treg and activated CD8+ T cells. Moreover, we found that regardless of the tumor type, tumor location, or whether the tumor was a primary or metastatic deposit, the composition of lymphocytes within the tumors were very similar.
Age at liver procedure
Primary tumor T stage
Primary tumor N stage
Primary tumor M stage
Post primary resection chemotx
Adjuvant chemo before liver resection
Time between resection and chemotx (Days)
Bevacizumab, Oxaliplatin, Capecitabine
5FU + Leukovorin
FOLFOX + avastin
FOLFOX + avastin
FOLFOX + avastin
FOLFOX + avastin
FOLFOX + avastin
FOLFOX + avastin
FOLFIRI + avastin
T cell composition: PBL versus TIL
T cell distribution in CRLM
CRC liver metastasis
Median (25th-75th percentile) percentages
Blood (n = 16)
TIL (n = 16)
CD3+ T cells
CD4+ T cells
CD8 + T cells
T cell distribution in OVC tumor specimens
Median (25th-75th percentile) percentages
Blood (n = 21)
Ascites (n = 16)
TIL (n = 21)
Met (n = 17)
CD3+ T cells
28.2 (17.8- 52.3)
CD4+ T cells
CD8+ T cells
1.3 ( 0.8-2.5)
Characterization of CD4+ T cell
The phenotype of CD4+ CD25+ FoxP3+ T cells: TIL versus PBMC
Percentage distribution of CD4 + T cell phenotypes: summary of CD4 + T cells phenotypes in CRLM patients
Mean% cell population (+/- SD)
CD25+ Foxp3+ CD4+ T cells
8.1 (+/− 3.0)
10.2 (+/− 8.0)
Ki-67+ Treg cells
17.9 (+/− 7.6)
13.5 (+/− 9.4)
HLA-DR + Treg cells
31.7 (+/− 13.5)
69.4 (+/− 13.5)
Percentage distribution of CD4 + T cell phenotypes: summary of CD4 + T cells phenotypes in OVC patients
Mean% cell population (+/- SD)
CD25+ Foxp3+ CD4+ T cells
4.6 (+/− 3.4)
10.31 (+/− 4.4)
19.8 (+/− 11.4)
Ki-67+ Treg cells
13.9 (+/− 8.2)
18.2 (+/− 12)
HLA-DR + Treg cells
37.4 (+/− 17.4)
47.0 (+/− 14.1)
74.6 (+/− 12.1)
75.1 (+/− 8.3)
HLA-DR + CD4+ T cells
7.6 (+/− 7.7)
25.5 (+/− 17.3)
48 (+/− 20.6)
Helios + Treg cells
50.7 (+/− 19.8)
58.7 (+/− 27.1)
77.2 (+/− 12.6)
76.3 (+/− 11.0)
HLA-DR + Helios + Treg cells
24.1 (+/− 7.7)
59.2 (+/− 14.2)
62 (+/− 8.7)
CD39+ Treg cells
29.1 (+/− 16.7)
43.1 (+/− 20.9)
72.2 (+/− 21.1)
67.5 (+/− 23.7)
HLA-DR + CD39+ Treg cells
21.1 (+/− 15)
28.8 (+/− 15)
54.4 (+/− 19.3)
53.4 (+/− 18.1)
CTLA-4 Treg cells
50.6 (+/− 27.8)
63.8 (+/− 28)
81.6 (+/− 14.9)
77.1 (+/− 20.2)
CD39+ CTLA-4+ Treg cells
18.5 (+/− 17.8)
27.2 (+/− 14.2)
61.7 (+/− 20.3)
53.6 (+/− 23)
HLA-DR+ Treg isolated from tumors have greater suppressive function
Characterization of CD8+ TIL
Cytokine mRNA levels in CDT Cells from TIL versus PBL
This work demonstrates the utility of using a 10 color flow-cytometry panel for analyzing TIL from freshly isolated tumor samples and shows that extensive information can be obtained using this approach. 10-color flow cytometry allows for a more detailed phenotypic characterization of T cell subsets when compared to standard IHC techniques, which have been used in previous TIL studies . These analyses show several significant phenotypic differences in the composition of TIL when compared to PBL. Our results also suggest, that regardless of the tumor type (CRC and OVC), the site of the disease (primary or metastatic lesions), or treatment status, the composition of TIL was surprisingly similar in these progressively growing tumors. We will began exploring other human malignancies in the future to ascertain whether this phenotypic pattern holds true across several different tumor types.
When comparing the TIL immune phenotype to PBL, we found several significant differences. OVC TIL contained a higher percentage of Treg compared to PBL (4.6% PBL compared to 19.7%), while there was no difference in Treg percentage in the CRC tumors compared to PBL. In both tumor types, Treg infiltrating the tumor were qualitatively different expressing higher levels of activation markers when compared to blood. These data show that proteins associated with a highly suppressive Treg phenotype ,,, were more abundant in T cells that infiltrate tumors when compared to peripheral blood. These results also suggest that there is a selective accumulation of activated Treg within the tumor microenvironment regardless of the tumor type or location; primary or secondary site. These findings may lend credence to the hypothesis that the immune system fails to immunologically reject tumors because highly activated Treg are suppressing effector responses within the tumor microenvironment. Others have shown that the some of proteins studied within this manuscript mark Treg with a greater suppressive capacity ,. This is an observation we confirmed by showing that sorted HLA-DR+ Treg were more suppressive when compared to HLA-DR- Treg in two OVC patient tumor samples. Recent studies have shown that Treg isolated from CRLM have potent immune suppressive properties ,. These studies did not analyze the phenotype of the Treg population, but they clearly demonstrated that Treg isolated from CRLM were more suppressive than Treg from PBL or tumor non-invaded tissue. We also found that infiltrating lymphocytes from both tumor types had a higher CD8/CD4 T cell ratio compared to PBL (see Table 1). Moreover, the CD8+ T cells within the tumor showed a greater propensity towards activation as measured by increased co-expression of CD38/HLA-DR. There was also an increased frequency of Ki-67+ CD8+ T cells in the TIL compared to PBL. While there is an increase in CD8 T cell activation and proliferation among patients’ TIL, it is clearly not sufficient to eradicate the tumor. There may be several explanations as to why these activated CD8 T cells are incapable of eradicating tumors. The CD8+ T cells within these tumors were found among suppressive cells including Treg (Tables 4 and 5), as well as MDSC  (not analyzed here), which could help to explain their failure to eradicate the tumor. These CD8 T cells could also express a host of exhaustive markers, such as PD-1 or Tim-3 (not assessed in this study), which could also limit their functional activity as shown by others ,. Another possibility is that the cytokine milieu created by cells within the tumor microenvironment could have suppressive effects on T cell function. Hence, we also investigated levels of cytokine transcripts produced by CD4+ TIL isolated from progressively growing tumors. While we have found an increase in activated Treg, we also found that the CD4+ TIL express higher levels of IL-6 mRNA compared to CD4+ PBL. The increased expression of IL-6 mRNA observed within the tumor, if translated to protein, could also contribute to an immune-suppressed environment potentially through increased pSTAT3 upregulation within immune cells found in the tumor -.
The two patient populations in this study had different clinical treatment histories. The CRLM patients typically had a preexisting history of cancer prior to the metastatic cancer resection, and in most cases had undergone previous resection of their primary tumor followed by chemotherapy (Table 1). In contrast, the patients with ovarian cancer typically had no treatment prior to their cytoreductive surgery. The tumor types analyzed also varied by stage of tumor development; liver metastatic tissue for CRC and primary tumors, omental metastases, and/or ascites for OVC patients. However, despite these differences, we observed many similarities in the TIL composition that were noted across different tumor types and sites of tumor growth.
Using a 10-color flow panel we provide a detailed analysis of the TIL composition from two different tumor types and found as expected that the TIL phenotype is much different than that of PBL. We can use these analyses as a phenotypic template of TIL isolated from progressively growing tumors and in the future compare these results to the phenotype of TIL isolated from patients treated with immunotherapy (e.g. anti-CTLA-4, anti-PD-1 and anti-OX40). Understanding how immunotherapies work by potentially changing the TIL composition and phenotype could lead to a more mechanistic approach to tumor immunotherapy, as most of the analyses in immunotherapy trials to date have analyzed PBL. This work also serve as a detailed platform for understanding the T cell phenotypes within progressively growing tumors and future studies will investigate the T cell phenotypes from other human malignancies in order determine similarities and differences to the results shown in this study. Ultimately, a greater understanding of the frequency and function of T cell infiltrates within progressively growing human tumors will allow us to better understand how to treat patients with immunotherapy to elicit T cell responses with greater clinical efficacy.
The results presented in this study show that the composition of immune infiltrates isolated from patients harboring different tumor types is very similar. We found that both colorectal liver metastases and ovarian cancer have a greater percentage of activated T regulatory cells as well as a higher percentage of activated CD8+ T cells when compared to peripheral blood of the same patients. We also found that CD4 T cells isolated from both tumor types have an increase in mRNA for IL-6 compared to peripheral blood CD4 T cells. This manuscript provides a foundation for the activation profile of tumor infiltrating T cells in two different progressively growing tumor types and could be used as baseline when assessing immunologic changes in patients treated with immunotherapy.
Collection and isolation of lymphocytes from peripheral blood and ascites
Peripheral blood was collected in heparinized tubes just prior to or during surgery. Ascites cells were centrifuged and the pellet was resuspended in XVivo media (Lonza) and mononuclear leukocytes were separated from red blood cells and or tumor cells by Ficoll-Paque Plus (GE Healthcare, 17-1440-02) density gradient centrifugation for both ascites and peripheral blood. The leukocyte fraction was harvested, washed in PBS and counted prior to being stained or enriched.
Isolation of tumor-infiltrating lymphocytes
Specimens were obtained at the time of surgery. Single cell suspension were obtained under sterile conditions in PBS, solid tumors were cut into 1-3 mm3 pieces and digested at room temperature for 1 hour on a magnetic stirring apparatus in a solution containing DNAse (Roche, 4536282001), collagenase (Sigma, C5138), halyuronidase (Sigma, H-6254) as well as human albumin (CSL Behring, 0053-7680-32) in RPMI (Lonza, 12-702Q). Enzymatically dissociated tumor was filtered through a 70 μm filter. Filtered samples were then diluted 1:2 with RPMI and ficolled as described above to obtain a leukocyte-enriched fraction. Cells were then washed three times in PBS (1st wash @ 1,000 rpm for 10 minutes to remove debris, then 2x @1,250 for 5 minutes) and counted. Leukocytes were resuspended at 10 × 106 cells/ml in PBS prior to staining or enrichment.
Flow cytometry analysis
Single cell suspensions of leukocytes from blood, ascites, tumor or omental metastases were stained with the following monoclonal antibodies: anti-CD3 APC-H7 (BD Pharmingen, 560176), anti-CD4 eFlour 450 (eBioscience, 48-0048-42), anti-CD8 Pacific Orange (Invitrogen, MHCD0830), anti-CD25 APC (BD Pharmingen, 555434), or anti-CTLA-4 APC (BD Pharmingen, 555855), anti-CD28 PerCpCy5.5 (eBioscience, 45-0289-42), anti-CD38 PE-TR (Invitrogen, MHCD3817), anti-HLA-DR PE-Cy7 (BD Biosciences, 335795), anti-FoxP3 PE (eBioscience, 12-4777-42), anti-ki67 FITC (BD Pharmingen, 556026) or CD39 FITC (BD Pharmingen, 561444) or anti-Helios (Biolegend, 137214). Cells were stained in FACs buffer (1%FBS in PBS with 0.01%NaN3) and fixed according to the ebioscience FoxP3 Fix-Perm kit protocol (eBioscience, 00-5521-00). All samples were run on a BD LSRII Flow cytometer and analysed by FACSDiva BD. Briefly, for every single flow cytometric antibody, we have used Fluorescent Minus One (FMO), to discriminate between positive and negative cells .
Lymphocytes from ascites, prepared as described above, were stained with anti-CD3, anti-CD4, anti-CD25, anti CD127 and anti-HLA-DR and sorted for T effector cells (CD3+, CD4+, CD25low and CD127high) and Treg: CD3+, CD4+, CD25high, CD127low and HLA-DR+ and CD3+, CD4+, CD25high, CD127low and HLA-DR-. Cells were sorted on an Aria sorter (BD).
Treg suppressive assay
Effector (30-50,000/well) and Treg were plated at ratio described in Figure 4, and stimulated with soluble anti-CD3 (1 μg/ml) and CD28 (2 μg/ml) as previously described . Supernatents were harvested at Day 3 and 5 and IFNγ was measured by ELISA (eBioscience).
Enrichment of CD4+ T cells from blood and tumor samples was achieved using the EasySep Human CD4 Negative Enrichment kit (StemCell Technologies, 19052). The CD4 population was further purified, using the EasySep Human CD4 Positive Selection kit (StemCell Technologies, 18052).
The RNA from CD4+ lymphocyte populations was isolated using the QIAshredder (QIAGEN, 79654) and RNeasy Mini kits (QIAGEN, 74104). The isolated RNA was treated with Turbo DNase (Ambion, AM1907) and quantified by optical density. 1 μg of treated RNA was used to prepare cDNA using the RevertAid First Strand cDNA Synthesis kit (Fermentas, K1621). Samples were then analyzed by qPCR on the Applied Biosystems Step One Plus using 250 ng of cDNA per reaction with reactions set up in triplicate. The reactions utilized the Maxima Probe/ROX qPCR Master Mix (Fermentas, K0232). Samples were analyzed using FAM/TAMRA probes for IL-6 expression (Invitrogen, Hs00985639_m1), IL-17 expression (Invitrogen, Hs00174383_m1) and IFNγ expression (Invitrogen, Hs00989291_m1). GAPDH was used as the endogenous mRNA control (Invitrogen, Hs02758991_g1). cDNA from normal donor PBMCs stimulated with PMA/ionomycin for 11 hours was used as the calibrator sample. The results were then analyzed using the Comparative Ct Method of relative quantification.
MKB designed the study, analyzed and interpreted data and wrote the manuscript. LC, JV CGT, RM and DH performed the experiments. PN, JM, PT, RW, JTV, CH, and PH were involved in patients care and performed the surgical procedures. ADW designed the study interpreted data and wrote the manuscript. All authors read and approved the final manuscript.
The authors thank Dr. Walter Urba for critical reading of the manuscript and Helena Hoen for her help with the statistical analyses.
- Topalian SL, Hodi FS, Brahmer JR, Gettinger SN, Smith DC, McDermott DF, Powderly JD, Carvajal RD, Sosman JA, Atkins MB, Leming PD, Spigel DR, Antonia SJ, Horn L, Drake CG, Pardoll DM, Chen L, Sharfman WH, Anders RA, Taube JM, McMiller TL, Xu H, Korman AJ, Jure-Kunkel M, Agrawal S, McDonald D, Kollia GD, Gupta A, Wigginton JM, Sznol M: Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med. 2012, 366 (26): 2443-2454. 10.1056/NEJMoa1200690.View ArticlePubMedPubMed CentralGoogle Scholar
- Brahmer JR, Tykodi SS, Chow LQ, Hwu WJ, Topalian SL, Hwu P, Drake CG, Camacho LH, Kauh J, Odunsi K, Pitot HC, Hamid O, Bhatia S, Martins R, Eaton K, Chen S, Salay TM, Alaparthy S, Grosso JF, Korman AJ, Parker SM, Agrawal S, Goldberg SM, Pardoll DM, Gupta A, Wigginton JM: Safety and activity of anti-PD-L1 antibody in patients with advanced cancer. N Engl J Med. 2012, 366 (26): 2455-2465. 10.1056/NEJMoa1200694.View ArticlePubMedPubMed CentralGoogle Scholar
- Beatty GL, Chiorean EG, Fishman MP, Saboury B, Teitelbaum UR, Sun W, Huhn RD, Song W, Li D, Sharp LL, Torigian DA, O'Dwyer PJ, Vonderheide RH: CD40 agonists alter tumor stroma and show efficacy against pancreatic carcinoma in mice and humans. Science. 2011, 331 (6024): 1612-1616. 10.1126/science.1198443.View ArticlePubMedPubMed CentralGoogle Scholar
- Pages F, Galon J, Dieu-Nosjean MC, Tartour E, Sautes-Fridman C, Fridman WH: Immune infiltration in human tumors: a prognostic factor that should not be ignored. Oncogene. 2010, 29 (8): 1093-1102. 10.1038/onc.2009.416.View ArticlePubMedGoogle Scholar
- Tosolini M, Kirilovsky A, Mlecnik B, Fredriksen T, Mauger S, Bindea G, Berger A, Bruneval P, Fridman WH, Pages F, Galon J: Clinical impact of different classes of infiltrating T cytotoxic and helper cells (Th1, th2, treg, th17) in patients with colorectal cancer. Cancer Res. 2011, 71 (4): 1263-1271. 10.1158/0008-5472.CAN-10-2907.View ArticlePubMedGoogle Scholar
- Kisielewicz A, Schaier M, Schmitt E, Hug F, Haensch GM, Meuer S, Zeier M, Sohn C, Steinborn A: A distinct subset of HLA-DR + -regulatory T cells is involved in the induction of preterm labor during pregnancy and in the induction of organ rejection after transplantation. Clin Immunol. 2010, 137 (2): 209-220. 10.1016/j.clim.2010.07.008.View ArticlePubMedGoogle Scholar
- Schober L, Radnai D, Schmitt E, Mahnke K, Sohn C, Steinborn A: Term and preterm labor: decreased suppressive activity and changes in composition of the regulatory T-cell pool. Immunol Cell Biol. 2012, 90 (10): 935-944. 10.1038/icb.2012.33.View ArticlePubMedGoogle Scholar
- Manfredi S, Lepage C, Hatem C, Coatmeur O, Faivre J, Bouvier AM: Epidemiology and management of liver metastases from colorectal cancer. Ann Surg. 2006, 244 (2): 254-259. 10.1097/01.sla.0000217629.94941.cf.View ArticlePubMedPubMed CentralGoogle Scholar
- Abdalla EK, Vauthey JN, Ellis LM, Ellis V, Pollock R, Broglio KR, Hess K, Curley SA: Recurrence and outcomes following hepatic resection, radiofrequency ablation, and combined resection/ablation for colorectal liver metastases. Ann Surg. 2004, 239 (6): 818-825. 10.1097/01.sla.0000128305.90650.71. discussion 825-7View ArticlePubMedPubMed CentralGoogle Scholar
- Adam R, Wicherts DA, de Haas RJ, Ciacio O, Levi F, Paule B, Ducreux M, Azoulay D, Bismuth H, Castaing D: Patients with initially unresectable colorectal liver metastases: is there a possibility of cure?. J Clin Oncol. 2009, 27 (11): 1829-1835. 10.1200/JCO.2008.19.9273.View ArticlePubMedGoogle Scholar
- Wagner P, Koch M, Nummer D, Palm S, Galindo L, Autenrieth D, Rahbari N, Schmitz-Winnenthal FH, Schirrmacher V, Buchler MW, Beckhove P, Weitz J: Detection and functional analysis of tumor infiltrating T-lymphocytes (TIL) in liver metastases from colorectal cancer. Ann Surg Oncol. 2008, 15 (8): 2310-2317. 10.1245/s10434-008-9971-5.View ArticlePubMedGoogle Scholar
- Mlecnik B, Tosolini M, Kirilovsky A, Berger A, Bindea G, Meatchi T, Bruneval P, Trajanoski Z, Fridman WH, Pages F, Galon J: Histopathologic-based prognostic factors of colorectal cancers are associated with the state of the local immune reaction. J Clin Oncol. 2011, 29 (6): 610-618. 10.1200/JCO.2010.30.5425.View ArticlePubMedGoogle Scholar
- Hwang WT, Adams SF, Tahirovic E, Hagemann IS, Coukos G: Prognostic significance of tumor-infiltrating T cells in ovarian cancer: a meta-analysis. Gynecol Oncol. 2012, 124 (2): 192-198. 10.1016/j.ygyno.2011.09.039.View ArticlePubMedPubMed CentralGoogle Scholar
- Thompson JM, Gralow JR, Levy R, Miller RA: The optimal application of forward and ninety-degree light scatter in flow cytometry for the gating of mononuclear cells. Cytometry. 1985, 6 (5): 401-406. 10.1002/cyto.990060503.View ArticlePubMedGoogle Scholar
- Jenabian MA, Seddiki N, Yatim A, Carriere M, Hulin A, Younas M, Kok E, Ghadimi A, Routy JP, Tremblay A, Sevigny J, Lelievre JD, Levy Y: Regulatory T cells negatively affect IL-2 production of effector T cells through CD39/adenosine pathway in HIV infection.PLoS Pathog 2013, 9(4):e1003319.,Google Scholar
- Mandapathil M, Lang S, Gorelik E, Whiteside TL: Increased ectonucleotidase expression and activity in regulatory T cells of patients with head and neck cancer. Clin Cancer Res. 2009, 15 (20): 6348-6357. 10.1158/1078-0432.CCR-09-1143.View ArticlePubMedPubMed CentralGoogle Scholar
- Zabransky DJ, Nirschl CJ, Durham NM, Park BV, Ceccato CM, Bruno TC, Tam AJ, Getnet D, Drake CG: Phenotypic and functional properties of Helios + regulatory T cells.PLoS One 2012, 7(3):e34547.,Google Scholar
- Krummel MF, Allison JP: CD28 and CTLA-4 have opposing effects on the response of T cells to stimulation. J Exp Med. 1995, 182: 459-466. 10.1084/jem.182.2.459.View ArticlePubMedGoogle Scholar
- Seddiki N, Santner-Nanan B, Martinson J, Zaunders J, Sasson S, Landay A, Solomon M, Selby W, Alexander SI, Nanan R, Kelleher A, Fazekas de St Groth B: Expression of interleukin (IL)-2 and IL-7 receptors discriminates between human regulatory and activated T cells. J Exp Med. 2006, 203 (7): 1693-1700. 10.1084/jem.20060468.View ArticlePubMedPubMed CentralGoogle Scholar
- Liu W, Putnam AL, Xu-Yu Z, Szot GL, Lee MR, Zhu S, Gottlieb PA, Kapranov P, Gingeras TR, Fazekas de St Groth B, Clayberger C, Soper DM, Ziegler SF, Bluestone JA: CD127 expression inversely correlates with FoxP3 and suppressive function of human CD4+ T reg cells. J Exp Med. 2006, 203 (7): 1701-1711. 10.1084/jem.20060772.View ArticlePubMedPubMed CentralGoogle Scholar
- Jie HB, Gildener-Leapman N, Li J, Srivastava RM, Gibson SP, Whiteside TL, Ferris RL: Intratumoral regulatory T cells upregulate immunosuppressive molecules in head and neck cancer patients. Br J Cancer. 2013, 109 (10): 2629-2635. 10.1038/bjc.2013.645.View ArticlePubMedPubMed CentralGoogle Scholar
- Schuler PJ, Schilling B, Harasymczuk M, Hoffmann TK, Johnson J, Lang S, Whiteside TL: Phenotypic and functional characteristics of CD4+ CD39+ FOXP3+ and CD4+ CD39+ FOXP3neg T-cell subsets in cancer patients. Eur J Immunol. 2012, 42 (7): 1876-1885. 10.1002/eji.201142347.View ArticlePubMedPubMed CentralGoogle Scholar
- Camus M, Tosolini M, Mlecnik B, Pages F, Kirilovsky A, Berger A, Costes A, Bindea G, Charoentong P, Bruneval P, Trajanoski Z, Fridman WH, Galon J: Coordination of intratumoral immune reaction and human colorectal cancer recurrence. Cancer Res. 2009, 69 (6): 2685-2693. 10.1158/0008-5472.CAN-08-2654.View ArticlePubMedGoogle Scholar
- 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 epithelial ovarian cancer. N Engl J Med. 2003, 348 (3): 203-213. 10.1056/NEJMoa020177.View ArticlePubMedGoogle Scholar
- Miller JD, van der Most RG, Akondy RS, Glidewell JT, Albott S, Masopust D, Murali-Krishna K, Mahar PL, Edupuganti S, Lalor S, Germon S, Del Rio C, Mulligan MJ, Staprans SI, Altman JD, Feinberg MB, Ahmed R: Human effector and memory CD8+ T cell responses to smallpox and yellow fever vaccines. Immunity. 2008, 28 (5): 710-722. 10.1016/j.immuni.2008.02.020.View ArticlePubMedGoogle Scholar
- Hagemann AR, Cadungog M, Hagemann IS, Hammond R, Adams SF, Chu CS, Rubin SC, Zhang L, Addya K, Birrer MJ, Gimotty PA, Coukos G: Tissue-based immune monitoring II: multiple tumor sites reveal immunologic homogeneity in serous ovarian carcinoma. Cancer Biol Ther. 2011, 12 (4): 367-377. 10.4161/cbt.12.4.16908.View ArticlePubMedPubMed CentralGoogle Scholar
- Pedroza-Gonzalez A, Verhoef C, Ijzermans JN, Peppelenbosch MP, Kwekkeboom J, Verheij J, Janssen HL, Sprengers D: Activated tumor-infiltrating CD4+ regulatory T cells restrain antitumor immunity in patients with primary or metastatic liver cancer. Hepatology. 2013, 57 (1): 183-194. 10.1002/hep.26013.View ArticlePubMedGoogle Scholar
- Ma C, Dong X: Colorectal cancer-derived Foxp3(+) IL-17(+) T cells suppress tumour-specific CD8+ T cells. Scand J Immunol. 2011, 74 (1): 47-51. 10.1111/j.1365-3083.2011.02539.x.View ArticlePubMedGoogle Scholar
- Lindau D, Gielen P, Kroesen M, Wesseling P, Adema GJ: The immunosuppressive tumour network: myeloid-derived suppressor cells, regulatory T cells and natural killer T cells. Immunology. 2013, 138 (2): 105-115. 10.1111/imm.12036.View ArticlePubMedPubMed CentralGoogle Scholar
- Ahmadzadeh M, Johnson LA, Heemskerk B, Wunderlich JR, Dudley ME, White DE, Rosenberg SA: Tumor antigen-specific CD8 T cells infiltrating the tumor express high levels of PD-1 and are functionally impaired. Blood. 2009, 114 (8): 1537-1544. 10.1182/blood-2008-12-195792.View ArticlePubMedPubMed CentralGoogle Scholar
- Anderson AC: Tim-3, a negative regulator of anti-tumor immunity. Curr Opin Immunol. 2012, 24 (2): 213-216. 10.1016/j.coi.2011.12.005.View ArticlePubMedGoogle Scholar
- Fisher DT, Appenheimer MM, Evans SS: The two faces of IL-6 in the tumor microenvironment. Semin Immunol. 2014, 26 (1): 38-47. 10.1016/j.smim.2014.01.008.View ArticlePubMedPubMed CentralGoogle Scholar
- Yu H, Kortylewski M, Pardoll D: Crosstalk between cancer and immune cells: role of STAT3 in the tumour microenvironment. Nat Rev Immunol. 2007, 7 (1): 41-51. 10.1038/nri1995.View ArticlePubMedGoogle Scholar
- Yu H, Pardoll D, Jove R: STATs in cancer inflammation and immunity: a leading role for STAT3. Nat Rev Cancer. 2009, 9 (11): 798-809. 10.1038/nrc2734.View ArticlePubMedGoogle Scholar
- Roederer M: Spectral compensation for flow cytometry: visualization artifacts, limitations, and caveats. Cytometry. 2001, 45 (3): 194-205. 10.1002/1097-0320(20011101)45:3<194::AID-CYTO1163>3.0.CO;2-C.View ArticlePubMedGoogle Scholar
- Baecher-Allan C, Brown JA, Freeman GJ, Hafler DA: Cd4(+)cd25(high) regulatory cells in human peripheral blood. J Immunol. 2001, 167 (3): 1245-1253. 10.4049/jimmunol.167.3.1245.View ArticlePubMedGoogle Scholar
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