Evidence map›Paper›PMID 36745048›Full record

ArticleCancer discovery2023

Discovery of Targets for Immune-Metabolic Antitumor Drugs Identifies Estrogen-Related Receptor Alpha.

Avinash Sahu, Xiaoman Wang, Phillip Munson, Jan P G Klomp, Xiaoqing Wang, Shengqing Stan Gu, Ya Han, Gege Qian, Phillip Nicol, Zexian Zeng and 22 more

Open access · hybridAbstract read
In one paragraph

Article in Cancer discovery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
7.1field-weighted citation impact, top 2% 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

22 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Facts and Hopes: Toward the Next Quantum Leap in Melanoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
    Review
  7. Spatially resolved C1QCCell discovery · 2025
    Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Editorial: Multi-omics studies on aging and age-related diseases.Frontiers in cell and developmental biology · 2024
    Article
  19. Article
  20. Review
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

32 authors at 8 institutions in 3 countries.

Avinash Sahu *Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0002-2193-6276
Xiaoman Wang *Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0002-7833-6108
Phillip Munson *Department of Medicine and Harvard Medical School, Massachusetts General Hospital Cancer Center, Boston, Massachusetts.ORCID 0000-0003-1635-3313
Jan P G KlompLead Pharma, Kloosterstraat, Oss, the Netherlands.ORCID 0000-0002-1313-2614
Xiaoqing WangDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0001-7476-8889
Shengqing Stan GuDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0002-4200-0864
Ya HanSchool of Life Sciences and Technology, Tongji University, Shanghai, China.ORCID 0000-0003-1892-4239
Gege QianDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0001-5068-0399
Phillip NicolDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0002-8526-5889
Zexian ZengDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0002-3905-3244
Chenfei WangDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0001-7573-3768
Collin TokheimDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0003-1395-5378
Wubing ZhangDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0003-2233-299X
Jingxin FuDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0002-4028-3661
Jin WangDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0002-4785-0403
Nishanth Ulhas NairCancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0002-8832-0329
Joost A P RensLead Pharma, Kloosterstraat, Oss, the Netherlands.ORCID 0000-0002-5737-9088
Meriem BourajjajLead Pharma, Kloosterstraat, Oss, the Netherlands.ORCID 0000-0002-6029-1028
Bas JansenLead Pharma, Kloosterstraat, Oss, the Netherlands.ORCID 0000-0001-5985-7656
Inge LeendersLead Pharma, Kloosterstraat, Oss, the Netherlands.ORCID 0000-0002-6030-0641
Jaap LemmersLead Pharma, Kloosterstraat, Oss, the Netherlands.ORCID 0000-0003-1760-3329
Mark MustersLead Pharma, Kloosterstraat, Oss, the Netherlands.ORCID 0000-0001-9801-7334
Sanne van ZantenLead Pharma, Kloosterstraat, Oss, the Netherlands.ORCID 0000-0002-9819-5218
Laura van ZelstLead Pharma, Kloosterstraat, Oss, the Netherlands.ORCID 0000-0002-0094-8892
Jenny WorthingtonAxis Bioservices, Coleraine, United Kingdom.ORCID 0000-0003-0442-0371
Jun S LiuDepartment of Statistics, Harvard University, Cambridge, Massachusetts.ORCID 0000-0002-4450-7239
Dejan JuricDepartment of Medicine and Harvard Medical School, Massachusetts General Hospital Cancer Center, Boston, Massachusetts.ORCID 0000-0003-2983-7704
Clifford A MeyerDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0002-8321-2839
Arthur OubrieLead Pharma, Kloosterstraat, Oss, the Netherlands.ORCID 0000-0001-6765-9246
X Shirley LiuDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0003-4736-7339
David E FisherDepartment of Medicine and Harvard Medical School, Massachusetts General Hospital Cancer Center, Boston, Massachusetts.ORCID 0000-0002-5506-0575
Keith T FlahertyDepartment of Medicine and Harvard Medical School, Massachusetts General Hospital Cancer Center, Boston, Massachusetts.ORCID 0000-0002-3402-0478
Dana-Farber Cancer Institute · USPharmaleads (France) · FRMassachusetts General Hospital · USChinese Academy of Medical Sciences & Peking Union Medical College · CNFisher Bioservices (United States) · USHarvard University Press · USNational Institutes of Health · USTongji University · CN

Funding

Transcriptional mechanisms and melanomaP01CA163222 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI David Liu · 2013 to 2026
$25.3M
Training Grant in Quantitative Sciences for Cancer ResearchT32CA009337 · NCI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI QUACKENBUSH, JOHN, TRIPPA, LORENZO · 1986 to 2025
$12.3M
The MITF transcriptional network: melanoma risk and carcinogenesisR01AR043369 · NIAMS · MASSACHUSETTS GENERAL HOSPITAL · PI DAVID E FISHER · 1996 to 2026
$9.4M
Therapeutic strategies for treatment of giant congenital melanocytic neviR01AR072304 · NIAMS · MASSACHUSETTS GENERAL HOSPITAL · PI DAVID E FISHER · 2017 to 2026
$3.9M
A druggable dependency in low-MITF/high-AXL melanoma: preclinical efficacy and mechanism of action in a key treatment-resistant subclass.R01CA222871 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI FISHER, DAVID E · 2018 to 2022
$1.8M
Identifying drug synergistic with cancer immunotherapyR00CA248953 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI SAHU, AVINASH DAS · 2023 to 2025
$716k
Identifying drug synergistic with cancer immunotherapyK99CA248953 · NCI · DANA-FARBER CANCER INST · PI SAHU, AVINASH DAS · 2020 to 2021
$240k
NCI NIH HHS K99 CA248953NCI NIH HHS P01 CA163222NCI NIH HHS R00 CA248953NCI NIH HHS R01 CA222871NCI NIH HHS T32 CA009337NIAMS NIH HHS R01 AR043369NIAMS NIH HHS R01 AR072304
6 · The paper itself

Abstract

Drugs that kill tumors through multiple mechanisms have the potential for broad clinical benefits. Here, we first developed an in silico multiomics approach (BipotentR) to find cancer cell-specific regulators that simultaneously modulate tumor immunity and another oncogenic pathway and then used it to identify 38 candidate immune-metabolic regulators. We show the tumor activities of these regulators stratify patients with melanoma by their response to anti-PD-1 using machine learning and deep neural approaches, which improve the predictive power of current biomarkers. The topmost identified regulator, ESRRA, is activated in immunotherapy-resistant tumors. Its inhibition killed tumors by suppressing energy metabolism and activating two immune mechanisms: (i) cytokine induction, causing proinflammatory macrophage polarization, and (ii) antigen-presentation stimulation, recruiting CD8+ T cells into tumors. We also demonstrate a wide utility of BipotentR by applying it to angiogenesis and growth suppressor evasion pathways. BipotentR (http://bipotentr.dfci.harvard.edu/) provides a resource for evaluating patient response and discovering drug targets that act simultaneously through multiple mechanisms. SIGNIFICANCE: BipotentR presents resources for evaluating patient response and identifying targets for drugs that can kill tumors through multiple mechanisms concurrently. Inhibition of the topmost candidate target killed tumors by suppressing energy metabolism and effects on two immune mechanisms. This article is highlighted in the In This Issue feature, p. 517.

Indexed as

Antineoplastic AgentsMelanomaCD8-Positive T-LymphocytesCell Line, TumorERRalpha Estrogen-Related ReceptorHumansImmunotherapyReceptors, EstrogenTumor MicroenvironmentAntineoplastic AgentsERRalpha Estrogen-Related ReceptorReceptors, Estrogen

Identifiers

PMID36745048
PMCPMC9975674
OpenAlexW4319294239

What Socratic holds

Textmetadata
LicenceTDM
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.