ReviewAdvances in experimental medicine and biology2017
Adaptive Resistance to Cancer Immunotherapy.
Review in Advances in experimental medicine and biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Immune evasion in cancer: mechanisms and cutting-edge therapeutic approaches.Signal transduction and targeted therapy · 2025Review
- Article
- Resistance to immune checkpoint inhibitors in advanced lung cancer: Clinical characteristics, potential prognostic factors and next strategy.Frontiers in immunology · 2023Article
- Signal pathways and precision therapy of small-cell lung cancer.Signal transduction and targeted therapy · 2022Review
- A prime/boost vaccine platform efficiently identifies CD27 agonism and depletion of myeloid-derived suppressor cells as therapies that rationally combine with checkpoint blockade in ovarian cancer.Cancer immunology, immunotherapy : CII · 2021Article
- Single-cell Analysis Technologies for Immuno-oncology Research: from Mechanistic Delineation to Biomarker Discovery.Genomics, proteomics & bioinformatics · 2021Review
- AFP-Inhibiting Fragments for Drug Delivery: The Promise and Challenges of Targeting Therapeutics to Cancers.Frontiers in cell and developmental biology · 2021Review
- Review
- Immunotherapy for Ovarian Cancer: Adjuvant, Combination, and Neoadjuvant.Frontiers in immunology · 2020Review
- Genetics and biology of prostate cancer.Genes & development · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Immunosuppressive mechanisms within the tumor microenvironment have emerged as a major impediment to cancer immunotherapy. While a broad range of secreted factors, receptors/ligands, and cell populations have been described that contribute to the immunosuppression, the involvement of these processes in immune evasion by tumors is typically considered to be an intrinsic property of the tumor. Evidence is now emerging that the processes underlying immune suppression within the tumor are, in fact, triggered by immune attack and reflect a dynamic interplay between the tumor and the host's immune system. The term adaptive resistance has been coined to describe the induction of immune suppressive pathways in the tumor following active attack on the tumor. Adaptive resistance is a scalable process where the magnitude of immune suppression matches the magnitude of the immune attack; the net balance between suppression and attack determines the durability of the anti-tumor response and tumor outcome. In this chapter, we will examine the data supporting adaptive resistance and the opposing roles of T cells in simultaneously promoting both anti-tumor immunity and immune suppression within the tumor microenvironment. The clinical implications of adaptive resistance in the design and application of immunotherapeutic strategies is also discussed.
Indexed as
Identifiers
29275474What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.