Article in JCI insight, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing 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.
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
18 authors.
Serena S KwekDivision of Hematology/Oncology, Department of Medicine.
Hai YangHelen Diller Family Comprehensive Cancer Center Biostatistics and Population Research Core.
Tony LiDivision of Hematology/Oncology, Department of Medicine.
Arielle IlanoDivision of Hematology/Oncology, Department of Medicine.
Eric D ChowCenter for Advanced Technology.
Li ZhangDivision of Hematology/Oncology, Department of Medicine.
Hewitt ChangDivision of Hematology/Oncology, Department of Medicine.
Diamond LuongDivision of Hematology/Oncology, Department of Medicine.
Averey LeaDivision of Hematology/Oncology, Department of Medicine.
Matthew ClarkDivision of Hematology/Oncology, Department of Medicine.
Alec StarzinskiDivision of Hematology/Oncology, Department of Medicine.
Yimin ShiDivision of Hematology/Oncology, Department of Medicine.
Elizabeth McCarthyDivision of Rheumatology.
Sima PortenHelen Diller Family Comprehensive Cancer Center.
Maxwell V MengHelen Diller Family Comprehensive Cancer Center.
Chun Jimmie YeDivision of Rheumatology.
Lawrence FongDivision of Hematology/Oncology, Department of Medicine.
David Y OhDivision of Hematology/Oncology, Department of Medicine.
Funding
Research BaseP30DK063720 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GERMAN, MICHAEL S · 2003 to 2019
$21.8M
Determinants of response to cancer immunotherapyR35CA253175 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Lawrence Fong · 2021 to 2026
$5.8M
Molecular and immune drivers of immunotherapy responsiveness in prostate cancerU01CA233100 · NCI · DANA-FARBER CANCER INST · PI FONG, LAWRENCE, VAN ALLEN, ELIEZER M · 2018 to 2022
$4.2M
Mechanisms of Exosome Driven Immunoregulation of Cancer ProgressionU01CA244452 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BLELLOCH, ROBERT, FONG, LAWRENCE · 2019 to 2022
$4.1M
Immunotherapy of human bladder cancerR01CA194511 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FONG, LAWRENCE · 2015 to 2019
$2.1M
Investigation of the landscape of immunosequencing and its clinical relevance through novel immunoinformatic approachesR01LM013763 · NLM · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ZHANG, LI · 2022 to 2025
$1.4M
Determinants of prostate cancer sensitivity to PD-1 blockadeR01CA223484 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FONG, LAWRENCE · 2018 to 2021
$1.1M
Identification of circulating and tissue-specific autoimmune responses in checkpoint inhibitor-induced immune-related adverse eventsK08AI139375 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI OH, DAVID YOONSUK · 2019 to 2023
$995k
Pacific Biosciences PacBio RS Single Molecule Real Time SequencerS10OD018174 · OD · UNIVERSITY OF CALIFORNIA BERKELEY · PI ROKHSAR, DANIEL SOLEYMAN · 2014 to 2014
$600k
BD FACSAria Fusion Cell SorterS10OD021822 · OD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LEE, MICHAEL R. · 2016 to 2016
$573k
Computational approaches to unravel immune receptor sequencing for cancer immunotherapyR21CA264381 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ZHANG, LI · 2021 to 2022
While cytotoxic CD4+ tumor-infiltrating lymphocytes have anticancer activity in patients, whether these can be noninvasively monitored and how these are regulated remains obscure. By matching single cells with T cell receptors (TCRs) in tumor and blood of patients with bladder cancer, we identified distinct pools of tumor-matching cytotoxic CD4+ T cells in the periphery directly reflecting the predominant antigenic specificities of intratumoral CD4+ tumor-infiltrating lymphocytes. On one hand, the granzyme B-expressing (GZMB-expressing) cytotoxic CD4+ subset proliferated in blood in response to PD-1 blockade but was separately regulated by the killer cell lectin-like receptor G1 (KLRG1), which inhibited their killing by interacting with E-cadherin. Conversely, a clonally related, GZMK-expressing circulating CD4+ population demonstrated basal proliferation and a memory phenotype that may result from activation of GZMB+ cells, but was not directly mobilized by PD-1 blockade. As KLRG1 marked the majority of circulating tumor-TCR-matched cytotoxic CD4+ T cells, this work nominates KLRG1 as a means to isolate them from blood and provide a window into intratumoral CD4+ recognition, as well as a putative regulatory receptor to mobilize the cytolytic GZMB+ subset for therapeutic benefit. Our findings also underscore ontogenic relationships of GZMB- and GZMK-expressing populations and the distinct cues that regulate their activity.
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.
Identification and regulation of circulating tumor-TCR-matched cytotoxic CD4+ lymphocytes by KLRG1 in bladder cancer. · full record | OpenQuestion