The DOI matches its Crossref record; 54 of the 55 references it cites were found in a registry or an index.
Baseline Peripheral Blood Biomarkers Associated with Clinical Outcome of Advanced Melanoma Patients Treated with Ipilimumab
Open accessPublished version of a preprint
Abstract
Purpose: To identify baseline peripheral blood biomarkers associated with clinical outcome following ipilimumab treatment in advanced melanoma patients. Experimental Design: Frequencies of myeloid-derived suppressor cells (MDSC) and regulatory T cells (Treg), serum lactate dehydrogenase (LDH), routine blood counts, and clinical characteristics were assessed in 209 patients. Endpoints were overall survival (OS) and best overall response. Statistical calculations were done by Kaplan–Meier and Cox regression analysis, including calibration and discrimination by C-statistics. Results: Low baseline LDH, absolute monocyte counts (AMC), Lin−CD14+HLA-DR−/low-MDSC frequencies, and high absolute eosinophil counts (AEC), relative lymphocyte counts (RLC), and CD4+CD25+FoxP3+-Treg frequencies were significantly associated with better survival, and were considered in a combination model. Patients (43.5%) presenting with the best biomarker signature had a 30% response rate and median survival of 16 months. In contrast, patients with the worst biomarkers (27.5%) had only a 3% response rate and median survival of 4 months. The occurrence of adverse events correlated with neither baseline biomarker signatures nor the clinical benefit of ipilimumab. In another model, limited to the routine parameters LDH, AMC, AEC, and RLC, the number of favorable factors (4 vs. 3 vs. 2–0) was also associated with OS (P < 0.001 for all pairwise comparisons) in the main study and additionally in an independent validation cohort. Conclusions: A baseline signature of low LDH, AMC, and MDSCs as well as high AEC, Tregs, and RLC is associated with favorable outcome following ipilimumab. Prospective investigation of the predictive impact of these markers following ipilimumab and other treatments, e.g., PD-1 antibodies, is warranted. Clin Cancer Res; 22(12); 2908–18. ©2016 AACR.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Furthermore, an elevated eosinophil count prior to treatment was associated with longer overall survival in several studies.8–12”
In the citing paper
“increased lymphocyte counts in the blood are associated not only with favorable treatment outcome but also with increased overall survival in patients with melanoma treated with ICIs (132-135).”
From Immune Checkpoint Inhibitors for the Treatment of Cancer: Clinical Impact and Mechanisms of Response and Resistance (2021) · cites this paper as [134]
In the citing paper
“numerous studies of patients with cancer have indeed found that these myeloid cell subsets, whether in the tumor or in peripheral tissues, were negatively correlated with effective ICI therapy (134, 161, 168-171).”
From Immune Checkpoint Inhibitors for the Treatment of Cancer: Clinical Impact and Mechanisms of Response and Resistance (2021) · cites this paper as [134]
In the citing paper
“both a low baseline frequency of MDSCs and a low frequency of MDSCs in the blood of patients with melanoma following ipilimumab treatment were associated with favorable therapy outcome (134, 169-171).”
From Immune Checkpoint Inhibitors for the Treatment of Cancer: Clinical Impact and Mechanisms of Response and Resistance (2021) · cites this paper as [134]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,989
Adverse Renal Effects of Immune Checkpoint Inhibitors: A Narrative Review
Wanchoo, R., Karam, S., Uppal, N. N., Barta, V. S., Deray, G., Devoe, C., Launay‐Vacher, V., Jhaveri, K. D., & on behalf of Cancer and Kidney International Network Workgroup on Immune Checkpoint Inhibitors (2017) · American Journal of Nephrology · doi:10.1159/000455014 · Cited by 15,320
Improved Survival with Ipilimumab in Patients with Metastatic Melanoma
Hodi, F. S., O'Day, S. J., McDermott, D. F., Weber, R. W., Sosman, J. A., Haanen, J. B., Gonzalez, R., Robert, C., Schadendorf, D., Hassel, J. C., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa1003466 · Cited by 15,155
Self-citationSafety, activity, and immune correlates of anti–PD-1 antibody in cancer
Topalian, S. L., Hodi, F. S., Brahmer, J. R., Gettinger, S. N., Smith, D. C., McDermott, D. F., Powderly, J. D., Carvajal, R. D., Sosman, J. A., Atkins, M. B., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1200690 · Cited by 12,628 · cited 1×
“Moreover, recent breakthroughs in immunotherapy, especially anti-PD-1 (5, 21) and anti-programmed cell death ligand-1 (PD-L1) antibodies (22), impressively demonstrate the capacity of a modulated immune system to reject cancer.”
BackgroundSafety and activity of anti-PD-L1 antibody in patients with advanced cancer
Brahmer, J. R., Tykodi, S. S., Chow, L. Q. M., Hwu, W.-J., Topalian, S. L., Hwu, P., Drake, C. G., Camacho, L. H., Kauh, J., Odunsi, K., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1200694 · Cited by 7,945 · cited 1×
“Moreover, recent breakthroughs in immunotherapy, especially anti-PD-1 (5, 21) and anti-programmed cell death ligand-1 (PD-L1) antibodies (22), impressively demonstrate the capacity of a modulated immune system to reject cancer.”
BackgroundMyeloid-derived-suppressor cells as regulators of the immune system
Gabrilovich, D. I., & Nagaraj, S. (2009) · Nature Reviews Immunology · doi:10.1038/nri2506 · Cited by 6,753 · cited 1×
“MDSCs and Tregs have been shown to exert suppressive function on T cells, thereby possibly counteracting the beneficial effect of ipilimumab (28, 45).”
BackgroundFinal Version of 2009 AJCC Melanoma Staging and Classification
Balch, C. M., Gershenwald, J. E., Soong, S.-J., Thompson, J. F., Atkins, M. B., Byrd, D. R., Buzaid, A. C., Cochran, A. J., Coit, D. G., Ding, S., et al. (2009) · Journal of Clinical Oncology · doi:10.1200/jco.2009.23.4799 · Cited by 4,653 · cited 1×
“The aim of the present studywas to identify baseline peripheral blood biomarkers associated with overall survival (OS) and tumor response of melanoma patients treated with ipilimumab, by a comprehensive analysis of routine blood counts, frequencies of immune cell subsets analyzed by flow cytometry, and established pro…”
BackgroundIpilimumab plus Dacarbazine for Previously Untreated Metastatic Melanoma
Robert, C., Thomas, L., Bondarenko, I., O'Day, S., Weber, J., Garbe, C., Lebbe, C., Baurain, J.-F., Testori, A., Grob, J.-J., et al. (2011) · New England Journal of Medicine · doi:10.1056/nejmoa1104621 · Cited by 4,496 · cited 1×
“Ipilimumab was the first agent to prolong survival of melanoma patients in randomized phase III studies (1, 2).”
BackgroundSelf-citationGenetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma
Snyder, A., Makarov, V., Merghoub, T., Yuan, J., Zaretsky, J. M., Desrichard, A., Walsh, L. A., Postow, M. A., Wong, P., Ho, T. S., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1406498 · Cited by 4,286 · cited 3×
“CD4þ T helper cells (15), CD8þ cytotoxic T cells (16, 17), and those targeting melanoma-associated- (18) or neoantigens (19, 20) are in principle able to attack cancer cells and are most likely responsible for the beneficial effects of ipilimumab.”
BackgroundSelf-citationCamp, R. L., Dolled-Filhart, M. P., & Rimm, D. L. (2004) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-04-0713 · Cited by 3,748 · cited 1×
“Candidates and respective cutoff points for continuous variables were defined by applying an optimization algorithm similar to those published earlier (10, 33).”
Method
Cited by
Sorted by citations
The immune contexture in cancer prognosis and treatment
Fridman, W. H., Zitvogel, L., Sautès–Fridman, C., & Kroemer, G. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2017.101 · Cited by 2,263
Bagchi, S., Yuan, R., & Engleman, E. G. (2021) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathol-042020-042741 · Cited by 2,189
The evolving landscape of biomarkers for checkpoint inhibitor immunotherapy
Havel, J. J., Chowell, D., & Chan, T. A. (2019) · Nature Reviews Cancer · doi:10.1038/s41568-019-0116-x · Cited by 2,286
Immune checkpoint inhibitors: recent progress and potential biomarkers
Darvin, P., Toor, S. M., Sasidharan Nair, V., & Elkord, E. (2018) · Experimental & Molecular Medicine · doi:10.1038/s12276-018-0191-1 · Cited by 2,035
Myeloid-derived suppressor cells coming of age
Veglia, F., Perego, M., & Gabrilovich, D. I. (2018) · Nature Immunology · doi:10.1038/s41590-017-0022-x · Cited by 1,818
Metadata
- Authors
- Martens, A., Wistuba-Hamprecht, K., Foppen, M. G., Yuan, J., Postow, M. A., Wong, P., Romano, E., Khammari, A., Dreno, B., Capone, M., Ascierto, P. A., Di Giacomo, A. M., Maio, M., Schilling, B., Sucker, A., Schadendorf, D., Hassel, J. C., Eigentler, T. K., Martus, P., Wolchok, J. D., Blank, C., Pawelec, G., Garbe, C., & Weide, B.
- Affiliations
- Universitätsklinikum Tübingen (DE)
- 1Department of Dermatology, University Medical Center, Tübingen, Germany.
- The Netherlands Cancer Institute (NL)
- Memorial Sloan Kettering Cancer Center (US)
- Institut Curie (FR)
- Inserm (FR)
- 7Department of Oncodermatology, INSERM Research Unit 892, University Hospital, Nantes, France.
- Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale" (IT)
- 9Division of Medical Oncology and Immunotherapy, University Hospital of Siena, Italy.
- University of Siena (IT)
- Essen University Hospital (DE)
- Heidelberg University (DE)
- University of Tübingen (DE)
- Corresponding author
- Weide, Benjamin
- ORCID
- Venue
- Clinical Cancer Research
- Published
- 2016-06-14
- Volume
- 22
- Issue
- 12
- Pages
- 2908-2918
- ISSN
- 1078-0432 (ISSN-L)
- 1557-3265
- PMC
- PMC5770142
- OpenAlex
- W2282962877
- Semantic Scholar
- 687f623ec6cd13653346165ccad52a8570919d07
- Cited by
- 541
- References
- 55
- Citations by year
- 2026: 10 · 2025: 29 · 2024: 21 · 2023: 42 · 2022: 50 · 2021: 75 · 2020: 85 · 2019: 61 · 2018: 70 · 2017: 63 · 2016: 33
- FWCI
- 40.81
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Clinical Cancer Research (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Use Siena air (University of Siena) (submittedVersion, other-oa)
- HAL (submittedVersion)
- Universitätsbibliographie, Universität Duisburg-Essen (submittedVersion)
- Funders
- Bristol-Myers-Squibb (Munich, Germany) and EU Seventh Framework Program "PRIAT" (305309 and DFG PA 361-22/1)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Health Sciences › Medicine › Oncology › Cutaneous Melanoma Detection and Management
- Health Sciences › Medicine › Oncology › Inflammatory Biomarkers in Disease Prognosis
- Keywords
- advanced melanoma, ipilimumab, predictive biomarkers, myeloid-derived suppressor cells, regulatory T cells, lactate dehydrogenase, absolute monocyte count, absolute eosinophil count, overall survival, best overall response, immune checkpoint inhibitors, anti-PD-1
- MeSH terms
- Myeloid-Derived Suppressor Cells, Antineoplastic Agents, Immunological, Ipilimumab, Aged, Erythrocyte Count, Female, Humans, L-Lactate Dehydrogenase, Male, Melanoma, Skin Neoplasms, Biomarkers, Tumor, Treatment Outcome, Lymphocyte Count, T-Lymphocytes, Regulatory
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
