Evidence map›Paper›PMID 42472879›Full record

ArticleCell death and differentiation2026

Pan-cancer proteogenomic interrogation of the ubiquitin-proteasome system.

Tania J González-Robles, Maha Khan, Paul Sastourné, Marisa Triola, Hua Zhou, Yuki Kito, Sharon Kaisari, David Fenyö, Gergely Rona, Yadira M Soto-Feliciano and 3 more

Abstract read
PubMed Publisher
In one paragraph

Article in Cell death and differentiation, 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

5 · Who and what money

Authors and funding

13 authors.

Tania J González-RoblesDivision of Precision Medicine, Department of Medicine, NYU Grossman School of Medicine, New York, NY, USA.ORCID http://orcid.org/0000-0001-9292-382X
Maha KhanDivision of Precision Medicine, Department of Medicine, NYU Grossman School of Medicine, New York, NY, USA.
Paul SastournéDivision of Precision Medicine, Department of Medicine, NYU Grossman School of Medicine, New York, NY, USA.
Marisa TriolaDivision of Precision Medicine, Department of Medicine, NYU Grossman School of Medicine, New York, NY, USA.
Hua ZhouApplied Bioinformatics Laboratories, NYU Grossman School of Medicine, New York, NY, USA.
Yuki KitoLaura and Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA.
Sharon KaisariDepartment of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY, USA.ORCID http://orcid.org/0000-0002-6884-3886
David FenyöInstitute for System Genetics, NYU Grossman School of Medicine, New York, NY, USA.
Gergely RonaDepartment of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY, USA.
Yadira M Soto-FelicianoDepartment of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-8523-7917
Benjamin G NeelDivision of Precision Medicine, Department of Medicine, NYU Grossman School of Medicine, New York, NY, USA.ORCID http://orcid.org/0000-0002-9589-585X
Kelly V RugglesDivision of Precision Medicine, Department of Medicine, NYU Grossman School of Medicine, New York, NY, USA. Kelly.Ruggles@nyulangone.org.
Michele PaganoLaura and Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA. Michele.Pagano@nyulangone.org.ORCID http://orcid.org/0000-0003-3210-2442

Funding

Training Program in Cell BiologyT32GM136542 · NIGMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI SMITH, SUSAN · 2020 to 2024
$3.0M
Elucidating the role of cyclin D1-CDK4/6 in protein homeostasis.K99GM155613 · NIGMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Sharon Kaisari · 2025 to 2026
$250k
Howard Hughes Medical Institute (HHMI) GT15758U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) K99GM155613U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) T32GM136542U.S. Department of Health & Human Services | NIH | NCI | Division of Cancer Epidemiology and Genetics, National Cancer Institute (National Cancer Institute Division of Cancer Epidemiology and Genetics) 1U54CA263001-01A1
6 · The paper itself

Abstract

Somatic mutations rewire the ubiquitin-proteasome system (UPS) to support tumor growth, but the proteome-wide consequences of cancer-driver alterations on UPS composition remain incompletely understood. Using harmonized proteogenomic data from up to 11 CPTAC cohorts, we performed an integrated pan-cancer analysis of UPS protein dysregulation, prognostic associations, and mutation-driven remodeling. We show that mRNA poorly predicts UPS protein abundance, that a defined set of E3 ligases is recurrently dysregulated across cancers, and that somatic mutations (most strikingly TP53 loss) produce coherent UPS protein-quantitative trait locus (pQTL) signatures. Two case studies (UBR5 and TRIM28) illustrate orthogonal modes of UPS rewiring: a mutation-driven axis in which TP53-mutant tumors elevate UBR5 to support replication stress tolerance, and a lineage-driven axis in which TRIM28 engages tissue-restricted regulatory networks with opposing prognostic effects in glioblastoma versus head and neck cancer. Each axis exposes context-specific therapeutic vulnerabilities, including sensitivity to DNA damage response inhibitors (UBR5-high) and lineage-specific drug responses (TRIM28-high). Together, these analyses define a mechanistic framework for how cancer-driver mutations reshape proteostasis through the UPS and nominate mutation- and lineage-defined dependencies for precision degrader therapy. The harmonized pan-tissue atlas and the UbiDash interactive resource that underpin parts of this analysis are reported in our companion paper [1].

Identifiers

PMID42472879

What Socratic holds

Textmetadata
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 Socratic graph.