The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Baseline Biomarkers for Outcome of Melanoma Patients Treated with Pembrolizumab
Open accessPublished version of a preprint
Abstract
Purpose: Biomarkers for outcome after immune-checkpoint blockade are strongly needed as these may influence individual treatment selection or sequence. We aimed to identify baseline factors associated with overall survival (OS) after pembrolizumab treatment in melanoma patients. Experimental Design: Serum lactate dehydrogenase (LDH), routine blood count parameters, and clinical characteristics were investigated in 616 patients. Endpoints were OS and best overall response following pembrolizumab treatment. Kaplan–Meier analysis and Cox regression were applied for survival analysis. Results: Relative eosinophil count (REC) ≥1.5%, relative lymphocyte count (RLC) ≥17.5%, ≤2.5-fold elevation of LDH, and the absence of metastasis other than soft-tissue/lung were associated with favorable OS in the discovery (n = 177) and the confirmation (n = 182) cohort and had independent positive impact (all P < 0.001). Their independent role was subsequently confirmed in the validation cohort (n = 257; all P < 0.01). The number of favorable factors was strongly associated with prognosis. One-year OS probabilities of 83.9% versus 14.7% and response rates of 58.3% versus 3.3% were observed in patients with four of four compared to those with none of four favorable baseline factors present, respectively. Conclusions: High REC and RLC, low LDH, and absence of metastasis other than soft-tissue/lung are independent baseline characteristics associated with favorable OS of patients with melanoma treated with pembrolizumab. Presence of four favorable factors in combination identifies a subgroup with excellent prognosis. In contrast, patients with no favorable factors present have a poor prognosis, despite pembrolizumab, and additional treatment advances are still needed. A potential predictive impact needs to be further investigated. Clin Cancer Res; 22(22); 5487–96. ©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
“Other pre-treatment immunological factors associated with improved treatment responses include high eosinophil and lymphocyte blood counts, an abundance of CD8+ T cells infiltrating the tumor or present at the tumor margin, and increased serum TGF-β levels in melanoma patients treated with anti-PD-1 (88, 91, 92, 109).”
From Anti-PD-1 and Anti-CTLA-4 Therapies in Cancer: Mechanisms of Action, Efficacy, and Limitations (2018) · cites this paper as [109]
In the citing paper
“Importantly, it has been shown that investigating several biomarkers in combination can improve treatment predictions (109).”
From Anti-PD-1 and Anti-CTLA-4 Therapies in Cancer: Mechanisms of Action, Efficacy, and Limitations (2018) · cites this paper as [109]
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
New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1)
Eisenhauer, E. A., Therasse, P., Bogaerts, J., Schwartz, L. H., Sargent, D., Ford, R., Dancey, J., Arbuck, S., Gwyther, S., Mooney, M., et al. (2009) · European Journal of Cancer · doi:10.1016/j.ejca.2008.10.026 · Cited by 29,534
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
The blockade of immune checkpoints in cancer immunotherapy
Pardoll, D. M. (2012) · Nature Reviews Cancer · doi:10.1038/nrc3239 · Cited by 13,838
Safety, 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
Combined Nivolumab and Ipilimumab or Monotherapy in Untreated Melanoma
Larkin, J., Chiarion-Sileni, V., Gonzalez, R., Grob, J. J., Cowey, C. L., Lao, C. D., Schadendorf, D., Dummer, R., Smylie, M., Rutkowski, P., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1504030 · Cited by 8,157
Self-citationSafety 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×
“Blocking antibodies targeting PD-1 or its counterpart PD-L1 can prevent this form of T cell inactivation (1, 10, 18, 34) ensuring sustained antitumor activity.”
BackgroundMutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer
Rizvi, N. A., Hellmann, M. D., Snyder, A., Kvistborg, P., Makarov, V., Havel, J. J., Lee, W., Yuan, J., Wong, P., Ho, T. S., et al. (2015) · Science · doi:10.1126/science.aaa1348 · Cited by 7,802
Self-citationPD-1 blockade induces responses by inhibiting adaptive immune resistance
Tumeh, P. C., Harview, C. L., Yearley, J. H., Shintaku, I. P., Taylor, E. J. M., Robert, L., Chmielowski, B., Spasic, M., Henry, G., Ciobanu, V., et al. (2014) · Nature · doi:10.1038/nature13954 · Cited by 6,609
Pembrolizumab for the Treatment of Non–Small-Cell Lung Cancer
Garon, E. B., Rizvi, N. A., Hui, R., Leighl, N., Balmanoukian, A. S., Eder, J. P., Patnaik, A., Aggarwal, C., Gubens, M., Horn, L., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1501824 · Cited by 6,198
Cited by
Sorted by citations
Inflammation and tumor progression: signaling pathways and targeted intervention
Zhao, H., Wu, L., Yan, G., Chen, Y., Zhou, M., Wu, Y., & Li, Y. (2021) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-021-00658-5 · Cited by 3,058
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
Predictive biomarkers for checkpoint inhibitor-based immunotherapy
Gibney, G. T., Weiner, L. M., & Atkins, M. B. (2016) · The Lancet Oncology · doi:10.1016/s1470-2045(16)30406-5 · Cited by 1,635
Hiam-Galvez, K. J., Allen, B. M., & Spitzer, M. H. (2021) · Nature Reviews Cancer · doi:10.1038/s41568-021-00347-z · Cited by 1,400
Anti-PD-1 and Anti-CTLA-4 Therapies in Cancer: Mechanisms of Action, Efficacy, and Limitations
Seidel, J. A., Otsuka, A., & Kabashima, K. (2018) · Frontiers in Oncology · doi:10.3389/fonc.2018.00086 · Cited by 1,360
Liu, D., Schilling, B., Liu, D., Sucker, A., Livingstone, E., Jerby-Arnon, L., Zimmer, L., Gutzmer, R., Satzger, I., Loquai, C., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0654-5 · Cited by 1,039
Self-citationMonitoring immune-checkpoint blockade: response evaluation and biomarker development
Nishino, M., Ramaiya, N. H., Hatabu, H., & Hodi, F. S. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2017.88 · Cited by 1,023
Mezquita, L., Auclin, E., Ferrara, R., Charrier, M., Remon, J., Planchard, D., Ponce, S., Ares, L. P., Leroy, L., Audigier-Valette, C., et al. (2018) · JAMA Oncology · doi:10.1001/jamaoncol.2017.4771 · Cited by 913
Emens, L. A., Cruz, C., Eder, J. P., Braiteh, F., Chung, C. T., Tolaney, S. M., Kuter, I., Nanda, R., Cassier, P. A., Delord, J., et al. (2018) · JAMA Oncology · doi:10.1001/jamaoncol.2018.4224 · Cited by 797
Biomarkers for predicting efficacy of PD-1/PD-L1 inhibitors
Yi, M., Jiao, D., Xu, H., Liu, Q., Zhao, W., Han, X., & Wu, K. (2018) · Molecular Cancer · doi:10.1186/s12943-018-0864-3 · Cited by 764
Navigating metabolic pathways to enhance antitumour immunity and immunotherapy
Li, X., Wenes, M., Romero, P. J., Huang, S. C., Fendt, S., & Ho, P. (2019) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-019-0203-7 · Cited by 750
De-novo and acquired resistance to immune checkpoint targeting
Syn, N. L., Teng, M. W. L., Mok, T. S. K., & Soo, R. A. (2017) · The Lancet Oncology · doi:10.1016/s1470-2045(17)30607-1 · Cited by 662
Cutaneous melanoma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up
Michielin, O. A., van Akkooi, A. C. J., Ascierto, P. A., Dummer, R., & Keilholz, U. (2019) · Annals of Oncology · doi:10.1093/annonc/mdz411 · Cited by 659
Self-citationKeung, E. Z.-Y., & Gershenwald, J. E. (2018) · Expert Review of Anticancer Therapy · doi:10.1080/14737140.2018.1489246 · Cited by 647
Bagley, S. J., Kothari, S., Aggarwal, C., Bauml, J. M., Alley, E. W., Evans, T. L., Kosteva, J. A., Ciunci, C. A., Gabriel, P. E., Thompson, J. C., et al. (2017) · Lung Cancer · doi:10.1016/j.lungcan.2017.01.013 · Cited by 523
PD‐1/PD‐L1 immune checkpoint: Potential target for cancer therapy
Dermani, F. K., Samadi, P., Rahmani, G., Kohlan, A. K., & Najafi, R. (2018) · Journal of Cellular Physiology · doi:10.1002/jcp.27172 · Cited by 524
Capone, M., Giannarelli, D., Mallardo, D., Madonna, G., Festino, L., Grimaldi, A. M., Vanella, V., Simeone, E., Paone, M., Palmieri, G., et al. (2018) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-018-0383-1 · Cited by 497
Self-citationPredictive biomarkers for cancer immunotherapy with immune checkpoint inhibitors
Bai, R., Lv, Z., Xu, D., & Cui, J. (2020) · Biomarker Research · doi:10.1186/s40364-020-00209-0 · Cited by 486
Tumor immunoevasion via acidosis-dependent induction of regulatory tumor-associated macrophages
Bohn, T., Rapp, S., Luther, N., Klein, M., Brühl, T.-J., Kojima, N., Lopez, P. A., Hahlbrock, J., Muth, S., Endo, S., et al. (2018) · Nature Immunology · doi:10.1038/s41590-018-0226-8 · Cited by 444
Tumor-draining lymph nodes are pivotal in PD-1/PD-L1 checkpoint therapy
Fransen, M. F., Schoonderwoerd, M. J. A., Knopf, P., Camps, M. G. M., Hawinkels, L. J. A. C., Kneilling, M., van Hall, T., & OSSENDORP, F. A. (2018) · JCI Insight · doi:10.1172/jci.insight.124507 · Cited by 436
Adaptive immune resistance at the tumour site: mechanisms and therapeutic opportunities
Kim, T. K., Vandsemb, E. N., Herbst, R. S., & Chen, L. (2022) · Nature Reviews Drug Discovery · doi:10.1038/s41573-022-00493-5 · Cited by 361
Ménétrier‐Caux, C., Ray-Coquard, I. L., Blay, J., & Caux, C. (2019) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-019-0549-5 · Cited by 359
Zhong, X., He, X., Wang, Y., Hu, Z., Huang, H., Zhao, S., Wei, P., & Li, D. (2022) · Journal of Hematology & Oncology · doi:10.1186/s13045-022-01358-5 · Cited by 356
Circulating tumour DNA predicts response to anti-PD1 antibodies in metastatic melanoma
Lee, J. H., Long, G. V., Boyd, S., Lo, S., Menzies, A. M., Tembe, V., Guminski, A., Jakrot, V., Scolyer, R. A., Mann, G. J., et al. (2017) · Annals of Oncology · doi:10.1093/annonc/mdx026 · Cited by 333
Dabrafenib, trametinib and pembrolizumab or placebo in BRAF-mutant melanoma
Ascierto, P. A., Ferrucci, P. F., Fisher, R. A., Vecchio, M. D., Atkinson, V. G., Schmidt, H., Schachter, J., Queirolo, P., Long, G. V., Giacomo, A. M. D., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0448-9 · Cited by 331
Self-citationProteomics of Melanoma Response to Immunotherapy Reveals Mitochondrial Dependence
Harel, M., Ortenberg, R., Varanasi, S. K., Mangalhara, K. C., Mardamshina, M., Markovits, E., Baruch, E. N., Tripple, V., Arama-Chayoth, M., Greenberg, E., et al. (2019) · Cell · doi:10.1016/j.cell.2019.08.012 · Cited by 328
Biomarkers of response to PD-1/PD-L1 inhibition
Vareki, S. M., Garrigós, C., & Durán, I. (2017) · Critical Reviews in Oncology/Hematology · doi:10.1016/j.critrevonc.2017.06.001 · Cited by 325
Long, G. V., Grob, J., Nathan, P., Ribas, A., Robert, C., Schadendorf, D., Lane, S. R., Mak, C., Legenne, P., Flaherty, K. T., et al. (2016) · The Lancet Oncology · doi:10.1016/s1470-2045(16)30578-2 · Cited by 321
Self-citationOvercoming resistance to tumor-targeted and immune-targeted therapies
Aldea, M., Andre, F., Marabelle, A., Dogan, S., Barlesi, F., & Soria, J.-C. (2021) · Cancer Discovery · doi:10.1158/2159-8290.cd-20-1638 · Cited by 311
A new dawn for eosinophils in the tumour microenvironment
Grisaru‐Tal, S., Itan, M., Klion, A. D., & Munitz, A. (2020) · Nature reviews. Cancer · doi:10.1038/s41568-020-0283-9 · Cited by 315
PD-1/PD-L1 Blockade: Have We Found the Key to Unleash the Antitumor Immune Response?
Xu-Monette, Z. Y., Zhang, M., Li, J., & Young, K. H. (2017) · Frontiers in Immunology · doi:10.3389/fimmu.2017.01597 · Cited by 297
Eosinophils: The unsung heroes in cancer?
Varricchi, G., Galdiero, M. R., Loffredo, S., Lucarini, V., Marone, G., Mattei, F., Marone, G., & Schiavoni, G. (2017) · OncoImmunology · doi:10.1080/2162402x.2017.1393134 · Cited by 288
Parihar, R., Rivas, C. H., Huynh, M., Omer, B. A., Lapteva, N., Metelitsa, L. S., Gottschalk, S. M., & Rooney, C. M. (2019) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-18-0572 · Cited by 254
Diehl, A., Yarchoan, M. M., Hopkins, A., Jaffee, E. M., & Grossman, S. A. (2017) · Oncotarget · doi:10.18632/oncotarget.23217 · Cited by 249
Teng, F., Meng, X., Kong, L., & Yu, J. (2017) · Cancer Letters · doi:10.1016/j.canlet.2017.11.014 · Cited by 249
Exploiting innate immunity for cancer immunotherapy
Yi, M., Li, T., Niu, M., Mei, Q., Zhao, B., Chu, Q., Dai, Z., & Wu, K. (2023) · Molecular Cancer · doi:10.1186/s12943-023-01885-w · Cited by 250
Overcoming Immune Evasion in Melanoma
Eddy, K., & Chen, S. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21238984 · Cited by 243
Tanizaki, J., Haratani, K., Hayashi, H., Chiba, Y., Nakamura, Y., Yonesaka, K., Kudo, K., Kaneda, H., Hasegawa, Y., Tanaka, K., et al. (2017) · Journal of Thoracic Oncology · doi:10.1016/j.jtho.2017.10.030 · Cited by 227
Buder‐Bakhaya, K., & Hassel, J. C. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.01474 · Cited by 219
Self-citationCancer immunotherapy: it’s time to better predict patients’ response
Pilard, C., Ancion, M., Delvenne, P., Jérusalem, G., Hubert, P., & Herfs, M. F. (2021) · British Journal of Cancer · doi:10.1038/s41416-021-01413-x · Cited by 224
Fucà, G., Galli, G., Poggi, M., Lo Russo, G., Proto, C., Imbimbo, M., Ferrara, R., Zilembo, N., Ganzinelli, M., Sica, A., et al. (2019) · ESMO Open · doi:10.1136/esmoopen-2018-000457 · Cited by 209
Kim, K. H., Cho, J., Ku, B. M., Koh, J., Sun, J., Lee, S., Ahn, J. S., Cheon, J., Min, Y. J., Park, S., et al. (2019) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-18-1449 · Cited by 211
The Use of Immune Checkpoint Inhibitors in Oncology and the Occurrence of AKI: Where Do We Stand?
Franzin, R., Netti, G. S., Spadaccino, F., Porta, C., Gesualdo, L., Stallone, G., Castellano, G., & Ranieri, E. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.574271 · Cited by 208
Indini, A., Di Guardo, L., Cimminiello, C., Prisciandaro, M., Randon, G., De Braud, F., & Del Vecchio, M. (2019) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-018-2819-x · Cited by 202
Limagne, E., Richard, C., Thibaudin, M., Fumet, J.-D., Truntzer, C., Lagrange, A., Favier, L., Coudert, B. P., & Ghiringhelli, F. (2019) · OncoImmunology · doi:10.1080/2162402x.2018.1564505 · Cited by 211
Ferrucci, P. F., Giacomo, A. M. D., Vecchio, M. D., Atkinson, V. G., Schmidt, H., Schachter, J., Queirolo, P., Long, G. V., Stephens, R., Svane, I. M., et al. (2020) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2020-001806 · Cited by 200
Self-citationHeppt, M. V., Heinzerling, L., Kähler, K. C., Forschner, A., Kirchberger, M. C., Loquai, C., Meißner, M., Meier, F. E., Terheyden, P. A. M., Schell, B., et al. (2017) · European Journal of Cancer · doi:10.1016/j.ejca.2017.05.038 · Cited by 202
Self-citationExisting and Emerging Biomarkers for Immune Checkpoint Immunotherapy in Solid Tumors
Arora, S., Velichinskii, R. A., Lesh, R. W., Ali, U., Kubiak, M. J., Bansal, P., Borghaei, H., Edelman, M. J., & Boumber, Y. (2019) · Advances in Therapy · doi:10.1007/s12325-019-01051-z · Cited by 202
Predictors of responses to immune checkpoint blockade in advanced melanoma
Jacquelot, N., Roberti, M. P., Enot, D. P., Rusakiewicz, S., Ternès, N., Jegou, S., Woods, D. M., Sodré, A. L., Hansen, M., Meirow, Y., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00608-2 · Cited by 200
Self-citationZimmer, L., Apuri, S., Eroglu, Z., Kottschade, L. A., Forschner, A., Gutzmer, R., Schlaak, M. S., Heinzerling, L., Krackhardt, A. M., Loquai, C., et al. (2017) · European Journal of Cancer · doi:10.1016/j.ejca.2017.01.009 · Cited by 193
Self-citationPredictive biomarkers of response for immune checkpoint inhibitors in non–small-cell lung cancer
Prelaj, A., Tay, R. Y., Ferrara, R., Chaput, N., Besse, B., & Califano, R. (2018) · European Journal of Cancer · doi:10.1016/j.ejca.2018.11.002 · Cited by 197
Subrahmanyam, P. B., Dong, Z., Gusenleitner, D., Giobbie-Hurder, A., Severgnini, M., Zhou, J., Manos, M., Eastman, L. M., Maecker, H. T., & Hodi, F. S. (2018) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-018-0328-8 · Cited by 190
Biochemistry, Lactate Dehydrogenase
Farhana, A., & Lappin, S. L. (2021) · StatPearls · Cited by 185
Biomarkers for Immune Checkpoint Inhibitor-Mediated Tumor Response and Adverse Events
Nakamura, Y. (2019) · Frontiers in Medicine · doi:10.3389/fmed.2019.00119 · Cited by 185
Hopkins, A. M., Rowland, A., Kichenadasse, G., Wiese, M. D., Gurney, H., McKinnon, R. A., Karapetis, C. S., & Sorich, M. J. (2017) · British Journal of Cancer · doi:10.1038/bjc.2017.274 · Cited by 183
Schadendorf, D., Long, G. V., Stroyakovskiy, D., Karaszewska, B., Hauschild, A., Levchenko, E., Chiarion‐Sileni, V., Schachter, J., Garbe, C., Dutriaux, C., et al. (2017) · European Journal of Cancer · doi:10.1016/j.ejca.2017.05.033 · Cited by 179
Self-citationTissue-Dependent Tumor Microenvironments and Their Impact on Immunotherapy Responses
Oliver, A. J., Lau, P. K. H., Unsworth, A., Loi, S., Darcy, P. K., Kershaw, M. H., & Slaney, C. Y. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.00070 · Cited by 169
Hogan, S. A., Courtier, A., Cheng, P. F., Jaberg-Bentele, N. F., Goldinger, S. M., Manuel, M., Perez, S., Plantier, N., Mouret, J.-F., Nguyen‐Kim, T. D. L., et al. (2018) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-18-0136 · Cited by 155
Self-citationTargeting immune checkpoints in breast cancer: an update of early results
Solinas, C., Gombos, A., Latifyan, S., Piccart, M. J., Kok, M., & Buisseret, L. (2017) · ESMO Open · doi:10.1136/esmoopen-2017-000255 · Cited by 157
Moreira, A., Leisgang, W., Schuler, G., & Heinzerling, L. (2017) · Immunotherapy · doi:10.2217/imt-2016-0138 · Cited by 147
Self-citationForget, M., Haymaker, C., Hess, K. R., Meng, Y. J., Creasy, C. A., Karpinets, T. V., Fulbright, O. J., Roszik, J., Woodman, S. E., Kim, Y. U., et al. (2018) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-17-3649 · Cited by 143
Heppt, M. V., Amaral, T. M. S., Kähler, K. C., Heinzerling, L., Hassel, J. C., Meißner, M., Kreuzberg, N., Loquai, C., Reinhardt, L., Utikal, J. S., et al. (2019) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-019-0800-0 · Cited by 141
Self-citationPawelec, G. (2017) · Biogerontology · doi:10.1007/s10522-017-9682-z · Cited by 140
Soyano, A. E., Dholaria, B., Marin-Acevedo, J. A., Diehl, N. N., Hodge, D. O., Luo, Y., Manochakian, R., Chumsri, S., Adjei, A. A., Knutson, K. L., et al. (2018) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-018-0447-2 · Cited by 142
Immune checkpoint blockade therapy
Wieder, T., Eigentler, T., Brenner, E., & Röcken, M. (2018) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2018.02.042 · Cited by 134
Beyond the Barrier: Unraveling the Mechanisms of Immunotherapy Resistance
Bell, H. N., & Zou, W. (2024) · Annual Review of Immunology · doi:10.1146/annurev-immunol-101819-024752 · Cited by 143
Eosinophil–lymphocyte interactions in the tumor microenvironment and cancer immunotherapy
Grisaru‐Tal, S., Rothenberg, M. E., & Munitz, A. (2022) · Nature Immunology · doi:10.1038/s41590-022-01291-2 · Cited by 131
Ho, W. J., Yarchoan, M. M., Hopkins, A., Mehra, R., Grossman, S. A., & Kang, H. (2018) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-018-0395-x · Cited by 129
Opposing roles of eosinophils in cancer
Simon, S. C. S., Utikal, J., & Umansky, V. (2019) · Cancer Immunology, Immunotherapy · doi:10.1007/s00262-018-2255-4 · Cited by 128
Nosrati, A., Tsai, K. K., Goldinger, S. M., Tumeh, P. C., Grimes, B. A., Loo, K. L., Algazi, A. P., Nguyen‐Kim, T. D. L., Levesque, M. P., Dummer, R., et al. (2017) · British Journal of Cancer · doi:10.1038/bjc.2017.70 · Cited by 126
Self-citationRosner, S., Kwong, E., Shoushtari, A. N., Friedman, C. F., Warner, A. B., Brady, M. S., Coit, D. G., Callahan, M. K., Wolchok, J. D., Chapman, P. B., et al. (2018) · Cancer Medicine · doi:10.1002/cam4.1356 · Cited by 127
Self-citationMazzaschi, G., Facchinetti, F., Missale, G., Canetti, D., Madeddu, D., Zecca, A., Veneziani, M., Gelsomino, F., Goldoni, M., Buti, S., et al. (2018) · Lung Cancer · doi:10.1016/j.lungcan.2018.11.038 · Cited by 124
The Cancer Immunogram as a Framework for Personalized Immunotherapy in Urothelial Cancer
van Dijk, N., Funt, S. A., Blank, C. U., Powles, T. B., Rosenberg, J. E., & van der Heijden, M. S. (2018) · European Urology · doi:10.1016/j.eururo.2018.09.022 · Cited by 121
Self-citationJílková, Z. M., Aspord, C., & Decaens, T. (2019) · Cancers · doi:10.3390/cancers11101554 · Cited by 123
Barta, S. K., Zain, J. M., Macfarlane, A. W., Smith, S. M., Ruan, J., Fung, H. C. H., Tan, C. R. C., Yang, Y., Alpaugh, R. K., Dulaimi, E., et al. (2019) · Clinical Lymphoma Myeloma & Leukemia · doi:10.1016/j.clml.2019.03.022 · Cited by 119
Basler, L., Gabryś, H. S., Hogan, S. A., Pavic, M., Bogowicz, M., Vuong, D., Tanadini‐Lang, S., Forster, R. E., Kudura, K., Huellner, M. W., et al. (2020) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-20-0020 · Cited by 119
Self-citationPredictive biomarkers for response to immune checkpoint inhibition
Shum, B., Larkin, J., & Turajlic, S. (2021) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2021.03.036 · Cited by 118
Haake, M., Haack, B., Schäfer, T., Harter, P. N., Mattavelli, G., Eiring, P., Vashist, N., Wedekink, F., Genßler, S., Fischer, B., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-39817-3 · Cited by 116
Self-citationNakamura, Y., Tanaka, R., Maruyama, H., Ishitsuka, Y., Okiyama, N., Watanabe, R., Fujimoto, M., & Fujisawa, Y. (2018) · Japanese Journal of Clinical Oncology · doi:10.1093/jjco/hyy201 · Cited by 114
Tumor location impacts immune response in mouse models of colon cancer
Zhao, X., Li, L., Starr, T. K., & Subramanian, S. (2017) · Oncotarget · doi:10.18632/oncotarget.18423 · Cited by 111
Ugurel, S., Schadendorf, D., Horny, K., Sucker, A., Schramm, S., Utikal, J. S., Pföhler, C., Herbst, R. A., Schilling, B., Blank, C. U., et al. (2020) · Annals of Oncology · doi:10.1016/j.annonc.2019.09.005 · Cited by 110
Self-citationPeripheral Blood-Based Biomarkers for Immune Checkpoint Inhibitors
An, H. J., Chon, H. J., & Kim, C. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22179414 · Cited by 107
Bladder cancer, a unique model to understand cancer immunity and develop immunotherapy approaches
Song, D., Powles, T. B., Shi, L., Zhang, L., Ingersoll, M. A., & Lu, Y. (2019) · The Journal of Pathology · doi:10.1002/path.5306 · Cited by 108
Metabolic flexibility in melanoma: A potential therapeutic target
Ruocco, M. R., Avagliano, A., Granato, G., Vigliar, E., Masone, S., Montagnani, S., & Arcucci, A. (2019) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2019.07.016 · Cited by 106
Alessi, J. V., Ricciuti, B., Alden, S. L., Bertram, A. A., Lin, J. J., Sakhi, M., Nishino, M., Vaz, V. R., Lindsay, J. R., Turner, M. M., et al. (2021) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2021-003536 · Cited by 105
Fujisawa, Y., Yoshino, K., Otsuka, A., Funakoshi, T., Fujimura, T., Yamamoto, Y., Hata, H., Gosho, M., Tanaka, R., Yamaguchi, K., et al. (2017) · Journal of Dermatological Science · doi:10.1016/j.jdermsci.2017.07.007 · Cited by 101
Advanced Melanoma: Current Treatment Options, Biomarkers, and Future Perspectives
Rozeman, E. A., Dekker, T. J. A., Haanen, J. B. A. G., & Blank, C. U. (2017) · American Journal of Clinical Dermatology · doi:10.1007/s40257-017-0325-6 · Cited by 99
Self-citationImmunotherapies for the Treatment of Uveal Melanoma—History and Future
Schank, T. E., & Hassel, J. C. (2019) · Cancers · doi:10.3390/cancers11081048 · Cited by 97
Self-citationLiquid biomarkers in melanoma: detection and discovery
Lim, S. Y., Lee, J., Diefenbach, R. J., Kefford, R. F., & Rizos, H. (2018) · Molecular Cancer · doi:10.1186/s12943-018-0757-5 · Cited by 99
C-reactive protein as an early marker of immune-related adverse events
Abolhassani, A.-R., Schuler, G., Kirchberger, M. C., & Heinzerling, L. (2019) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-019-03002-1 · Cited by 97
Self-citationAndreone, S., Spadaro, F., Buccione, C., Mancini, J., Tinari, A., Sestili, P., Gambardella, A. R., Lucarini, V., Ziccheddu, G., Parolini, I., et al. (2019) · Cancers · doi:10.3390/cancers11111664 · Cited by 91
Progress and Challenges of Predictive Biomarkers for Immune Checkpoint Blockade
Lei, Y., Li, X., Huang, Q., Zheng, X., & Liu, M. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.617335 · Cited by 94
(IMI), O. B. O. T. I. M. I., Pistillo, M. P., Fontana, V., Morabito, A., Dozin, B., Laurent, S., Carosio, R., Banelli, B., Ferrero, F., Spano, L., et al. (2018) · Cancer Immunology Immunotherapy · doi:10.1007/s00262-018-2258-1 · Cited by 91
Self-citationEosinophil accumulation predicts response to melanoma treatment with immune checkpoint inhibitors
Simon, S. C. S., Hu, X., Panten, J., Grees, M., Renders, S., Thomas, D., Weber, R., Schulze, T. J., Utikal, J. S., & Umansky, V. (2020) · OncoImmunology · doi:10.1080/2162402x.2020.1727116 · Cited by 88
Morita, M., Nishida, N., Sakai, K., Aoki, T., Chishina, H., Takita, M., Ida, H., Hagiwara, S., Minami, Y., Ueshima, K., et al. (2021) · Liver Cancer · doi:10.1159/000516899 · Cited by 90
Metastasis-Entrained Eosinophils Enhance Lymphocyte-Mediated Antitumor Immunity
Grisaru‐Tal, S., Dulberg, S., Beck, L., Zhang, C., Itan, M., Hediyeh-zadeh, S., Caldwell, J. M., Rozenberg, P., Dolitzky, A., Avlas, S., et al. (2021) · Cancer Research · doi:10.1158/0008-5472.can-21-0839 · Cited by 91
Petrelli, F., Ardito, R., Merelli, B., Lonati, V., Cabiddu, M., Seghezzi, S., Barni, S., & Ghidini, A. (2018) · Melanoma Research · doi:10.1097/cmr.0000000000000520 · Cited by 89
Bridge, J. A., Lee, J., DAUD, A. I., Wells, J. W., & Bluestone, J. A. (2018) · Frontiers in Medicine · doi:10.3389/fmed.2018.00351 · Cited by 86
da Silva, I. P., Ahmed, T., McQuade, J. L., Nebhan, C. A., Park, J., Versluis, J. M., Serra-Bellver, P., Khan, Y., Slattery, T., Oberoi, H. K., et al. (2022) · Journal of Clinical Oncology · doi:10.1200/jco.21.01701 · Cited by 88
Self-citationGuo, L., Wei, R., Lin, Y., & Kwok, H. F. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.01508 · Cited by 85
Metadata
- Authors
- Weide, B., Martens, A., Hassel, J. C., Berking, C., Postow, M. A., Bisschop, K., Simeone, E., Mangana, J., Schilling, B., Di Giacomo, A. M., Brenner, N., Kähler, K., Heinzerling, L., Gutzmer, R., Bender, A., Gebhardt, C., Romano, E., Meier, F., Martus, P., Maio, M., Blank, C., Schadendorf, D., Dummer, R., Ascierto, P. A., Hospers, G., Garbe, C., & Wolchok, J. D.
- Affiliations
- Universitätsklinikum Tübingen (DE)
- Heidelberg University (DE)
- Deutsches Konsortium für Translationale Krebsforschung (DE)
- Memorial Sloan Kettering Cancer Center (US)
- University Medical Center Groningen (NL)
- Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale" (IT)
- 10Department of Dermatology, University of Zürich, Zürich, Switzerland.
- 12Division of Medical Oncology and Immunotherapy, University Hospital of Siena, Siena, Italy.
- University Hospital Cologne (DE)
- University Hospital Schleswig-Holstein (DE)
- Universitätsklinikum Erlangen (DE)
- Medizinische Hochschule Hannover (DE)
- Universitätsklinikum Gießen und Marburg (DE)
- German Cancer Research Center (DE)
- Institut Curie (FR)
- University of Tübingen (DE)
- University of Siena (IT)
- The Netherlands Cancer Institute (NL)
- University of Zurich (CH)
- Corresponding author
- Weide, Benjamin
- ORCID
- Weide, Benjamin
- Hassel, Jessica C.
- Berking, Carola
- Postow, Michael A.
- Bisschop, Kees
- Simeone, Ester
- Schilling, Bastian
- Brenner, Nicole
- Kähler, Katharina
- Heinzerling, Lucie
- Gutzmer, Ralf
- Gebhardt, Christoffer
- Romano, Emanuela
- Meier, Friedegund
- Martus, Peter
- Maio, Michele
- Blank, Christian
- Schadendorf, Dirk
- Dummer, Reinhard
- Ascierto, Paolo A.
- Hospers, Geke
- Garbe, Claus
- Wolchok, Jedd D.
- Venue
- Clinical Cancer Research
- Published
- 2016-11-14
- Volume
- 22
- Issue
- 22
- Pages
- 5487-5496
- ISSN
- 1078-0432 (ISSN-L)
- 1557-3265
- PMC
- PMC5572569
- OpenAlex
- W2397854274
- Semantic Scholar
- b5a9c4e2d6333e54d55ec140895bb53cebb851f9
- Cited by
- 589
- References
- 44
- Citations by year
- 2026: 17 · 2025: 38 · 2024: 31 · 2023: 46 · 2022: 57 · 2021: 91 · 2020: 86 · 2019: 77 · 2018: 72 · 2017: 59 · 2016: 14
- FWCI
- 39.91
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Clinical Cancer Research (publishedVersion)
- PubMed (publishedVersion)
- Kölner Universitäts PublikationsServer (Universität zu Köln) (publishedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Use Siena air (University of Siena) (submittedVersion)
- Universitätsbibliographie, Universität Duisburg-Essen (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
- Funders
- National Cancer Institute (P30CA008748)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Health Sciences › Medicine › Oncology › Cutaneous Melanoma Detection and Management
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Melanoma and MAPK Pathways
- Keywords
- melanoma, pembrolizumab, immune checkpoint blockade, prognostic factors, overall survival, lactate dehydrogenase, eosinophil count, lymphocyte count, metastasis, best overall response, predictive biomarkers
- MeSH terms
- Aged, Antibodies, Monoclonal, Female, Humans, L-Lactate Dehydrogenase, Male, Melanoma, Middle Aged, Prognosis, Skin Neoplasms, Biomarkers, Tumor, Cohort Studies, Survival Analysis, Treatment Outcome, Kaplan-Meier Estimate, Antibodies, Monoclonal, Humanized
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