| Title |
Targeting tumor-associated acidity in cancer immunotherapy
|
|---|---|
| Published in |
Cancer Immunology, Immunotherapy, July 2018
|
| DOI | 10.1007/s00262-018-2195-z |
| Pubmed ID | |
| Authors |
Ruben Lacroix, Elisa A. Rozeman, Marina Kreutz, Kathrin Renner, Christian U. Blank |
| Abstract |
Checkpoint inhibitors, such as cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) and programmed cell death-1 (PD-1) monoclonal antibodies have changed profoundly the treatment of melanoma, renal cell carcinoma, non-small cell lung cancer, Hodgkin lymphoma, and bladder cancer. Currently, they are tested in various tumor entities as monotherapy or in combination with chemotherapies or targeted therapies. However, only a subgroup of patients benefit from checkpoint blockade (combinations). This raises the question, which all mechanisms inhibit T cell function in the tumor environment, restricting the efficacy of these immunotherapeutic approaches. Serum activity of lactate dehydrogenase, likely reflecting the glycolytic activity of the tumor cells and thus acidity within the tumor microenvironment, turned out to be one of the strongest markers predicting response to checkpoint inhibition. In this review, we discuss the impact of tumor-associated acidity on the efficacy of T cell-mediated cancer immunotherapy and possible approaches to break this barrier. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 67% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 74 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 19% |
| Researcher | 13 | 18% |
| Student > Master | 7 | 9% |
| Student > Doctoral Student | 7 | 9% |
| Other | 6 | 8% |
| Other | 15 | 20% |
| Unknown | 12 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 23 | 31% |
| Biochemistry, Genetics and Molecular Biology | 9 | 12% |
| Immunology and Microbiology | 8 | 11% |
| Agricultural and Biological Sciences | 7 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 7% |
| Other | 8 | 11% |
| Unknown | 14 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 July 2018.
All research outputs
#14,951,052
of 23,923,788 outputs
Outputs from Cancer Immunology, Immunotherapy
#2,060
of 2,897 outputs
Outputs of similar age
#189,219
of 330,471 outputs
Outputs of similar age from Cancer Immunology, Immunotherapy
#25
of 44 outputs
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We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.