Evidence map›Paper›PMID 38275827›Full record

ReviewCurrent oncology (Toronto, Ont.)2023

Overcoming Resistance Mechanisms to Immune Checkpoint Inhibitors: Leveraging the Anti-Tumor Immune Response.

Courtney H Coschi, Rosalyn A Juergens

Open access · goldAbstract readReview
In one paragraph

Review in Current oncology (Toronto, Ont.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 15 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Courtney H CoschiDepartment of Oncology, McMaster University, 699 Concession Street, Hamilton, ON L8V 5C2, Canada.
Rosalyn A JuergensDepartment of Oncology, McMaster University, 699 Concession Street, Hamilton, ON L8V 5C2, Canada.ORCID 0000-0001-8627-4704
McMaster University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As far back as 3000 years ago, the immune system was observed to play a role in mediating tumor regression. Since then, many strategies have been developed to leverage the anti-tumor immune response. However, while many patients respond to ICIs up front some do not, and many of those that do eventually experience tumor progression. Currently, there are several predictive biomarkers of the immune checkpoint inhibitor response; however, no one test appears to be universally predictive and their application varies by disease site. There are many ways in which cancer cells develop primary or acquired resistance to immune checkpoint inhibitors. Efforts to reverse resistance include ways to combat T cell exhaustion, reprogram the tumor microenvironment, increase the availability of tumor neo-antigens, target alternative immune checkpoints, restore a normal/healthy patient gut microbiome, oncolytic viruses and tumor vaccines. The most studied and most promising methods include combining ICIs with therapies targeting alternative immune checkpoints and restoring a normal/healthy patient gut microbiome. This review will discuss T cell-mediated immunity, how this is leveraged by modern immunotherapy to treat cancer and mechanisms of immune checkpoint inhibitor resistance, while highlighting strategies to overcome primary and secondary resistance mechanisms.

Indexed as

Immune Checkpoint InhibitorsNeoplasmsBiomarkersHumansImmunityTumor MicroenvironmentBiomarkersImmune Checkpoint Inhibitorsanti-tumor immune responseimmune checkpoint inhibitorlung cancerresistanceT cells

Identifiers

PMID38275827
PMCPMC10814017
OpenAlexW4390005679

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.