Evidence map›Paper›PMID 35022192›Full record

ReviewJournal for immunotherapy of cancer2022

Immuno-oncology trends: preclinical models, biomarkers, and clinical development.

Maryland Rosenfeld Franklin, Suso Platero, Kamal S Saini, Giuseppe Curigliano, Steven Anderson

Abstract readReview
In one paragraph

Review in Journal for immunotherapy of cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
–field-weighted citation impact
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

37 citing papers in PubMed.

  1. Article
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  7. Translational 3DFrontiers in immunology · 2026
    Article
  8. Immunocompetent Murine Models Recapitulate the Heterogeneous Tumor-Immune Microenvironment of Human Liposarcoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
    Article
  9. Review
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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

5 authors.

Maryland Rosenfeld FranklinLabcorp Drug Development Inc, Princeton, New Jersey, USA.
Suso PlateroLabcorp Drug Development Inc, Princeton, New Jersey, USA.
Kamal S SainiLabcorp Drug Development Inc, Princeton, New Jersey, USA.ORCID 0000-0001-6301-3309
Giuseppe CuriglianoIstituto Europeo di Oncologia, IRCCS, Milan, Italy giuseppe.curigliano@ieo.it.
Steven AndersonLabcorp Drug Development Inc, Princeton, New Jersey, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The landscape in immuno-oncology (I-O) has undergone profound changes since its early beginnings up through the rapid advances happening today. The current drug development pipeline consists of thousands of potential I-O therapies and therapy combinations, many of which are being evaluated in clinical trials. The efficient and successful development of these assets requires the investment in and utilization of appropriate tools and technologies that can facilitate the rapid transitions from preclinical evaluation through clinical development. These tools include (i) appropriate preclinical models, (ii) biomarkers of pharmacodynamic, predictive and monitoring utility, and (iii) evolving clinical trial designs that allow rapid and efficient evaluation during the development process. This article provides an overview of how novel discoveries and insights into each of these three areas have the potential to further address the clinical management needs for patients with cancer.

Indexed as

Biomarkers, TumorHumansImmunotherapyMedical OncologyNeoplasmsBiomarkers, Tumorantigenic modulationbiomarkersclinical trials as topicimmune toleranceimmunotherapytumor

Identifiers

PMID35022192
PMCPMC8756278

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.