Evidence map›Paper›PMID 42307267›Full record

ArticleClinical cancer research : an official journal of the American Association for Cancer Research2026

Piggybacking toward Progress for CAR T-Cell Therapy in Prostate Cancer.

Patrick C Lee, Michael T Schweizer, Rosa Nadal

Abstract read
In one paragraph

Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Patrick C LeeDivision of Hematology and Oncology, Department of Medicine, University of Washington, Seattle, Washington.ORCID 0000-0001-9291-6179
Michael T SchweizerDivision of Hematology and Oncology, Department of Medicine, University of Washington, Seattle, Washington.ORCID 0000-0002-5510-0661
Rosa NadalDivision of Hematology and Oncology, Department of Medicine, University of Washington, Seattle, Washington.ORCID 0000-0002-6836-9731

Funding

TRANSCRIPTOME AND PROTEOME STRATIFICATION OF PROSTATE ADENOCARCINOMA PHENOTYPESP50CA097186 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI PETER S NELSON · 2002 to 2026
$58.1M
TRAINING IN CANCER BIOLOGY &TRANSPLANTATIONT32CA009515 · NCI · UNIVERSITY OF WASHINGTON · PI NANCY ELLEN DAVIDSON, Effie W Petersdorf · 1985 to 2026
$16.2M
Augmenting PSMA expression to enhance PSMA directed therapeutic efficacyR37CA286450 · NCI · FRED HUTCHINSON CANCER CENTER · PI Michael C Haffner, Michael T Schweizer · 2024 to 2026
$2.1M
National Cancer Institute (NCI) P50CA097186-21National Cancer Institute (NCI) R37CA268450National Cancer Institute (NCI) T32CA009515NCI NIH HHS P50 CA097186NCI NIH HHS R37 CA286450NCI NIH HHS T32 CA009515U.S. Department of Defense (DOD) W81XWH-17-2-0043
6 · The paper itself

Abstract

P-PSMA-101 is a first-in-class, stem cell memory T cell-enriched, prostate-specific membrane antigen (PSMA)-targeting chimeric antigen receptor (CAR) T therapy. This cellular therapy showed notable clinical activity in two patients; however, PSA50 responses were generally modest. Although severe immune effector-related toxicities were observed in some patients, a novel inducible caspase 9 (iCasp9) safety switch was largely effective in mitigating toxicity. See related article by Slovin et al., p. 3540.

Indexed as

Immunotherapy, AdoptiveProstatic NeoplasmsReceptors, Antigen, T-CellReceptors, Chimeric AntigenT-LymphocytesHumansMaleTreatment OutcomeReceptors, Antigen, T-CellReceptors, Chimeric Antigen

Identifiers

PMID42307267
PMCPMC13431268

What OpenQuestion holds

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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.