ReviewJournal for immunotherapy of cancer2026
Priorities for local immunotherapy research and drug development.
Review in Journal for immunotherapy of cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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
Local immunotherapy comprises broad classes of therapeutics that aim to trigger a robust "in situ" immune response that can ultimately generate systemic antitumor immunity. These agents are appealing as resistance to standard immune checkpoint inhibitors has been linked to a lack of baseline immune activity or immune suppressive elements in the tumor microenvironment. By administering agents directly to the tumor microenvironment, local immune therapies can both stimulate immune response and attempt to "reprogram" or subvert the effects of immune suppressive cell populations. Proof of concept for the benefit of local immune therapy has been demonstrated by several Food and Drug Administration-approved therapies.A "Summit on Intralesional Immunotherapy" was held in September 2024, which comprised lectures and discussion from an international panel of experts on local immune therapy. In this consensus paper, we will discuss unique considerations for local immunotherapy development across the continuum from pre-clinical and early-stage investigation through registration intent clinical trials.Early phase trials offer an opportunity to gain understanding of the biologic activity of candidate therapies and determine optimal dosing schedules. For local immunotherapies, it is most informative to measure the direct effect of the therapy in the tumor microenvironment at both injected and non-injected tumor sites. Carefully planned pharmacodynamic endpoints using on-treatment biopsies and novel imaging strategies to track immune cell activity will maximize the insights from early phase trials. For promising local therapies, selecting the proper patient population and treatment setting are critical. In order to intervene before the tumor microenvironment has reached a fixed immune suppressive state, local immunotherapies may best be suited as part of neoadjuvant or frontline metastatic therapy regimens. We also highlight several specific classes of local immunotherapy under investigation including oncolytic viruses, radiation, messenger RNA, Toll-like receptor agonists, stimulator of interferon gene agonists, CD40 agonists and cytokines.Novel local therapies currently being investigated are poised to expand the field and show promising activity in generating systemic antitumor immunity. Thoughtful trial design in both early stage as well as registration intent settings will accelerate the advancement of this field.
Indexed as
Identifiers
What 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.