Cited by 17Prostate Cancer Treatment and ResearchAdvanced Proteomics Techniques and ApplicationsUbiquitin and proteasome pathways

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Single-Cell Proteomic Characterization of Drug-Resistant Prostate Cancer Cells Reveals Molecular Signatures Associated with Morphological Changes

Open access
Woo, Jongmin, Loycano, Michael, Amanullah, Md, Qian, Jiang, Amend, Sarah R., Pienta, Kenneth J., Zhang, Hui·2025·Molecular & Cellular Proteomics

Published version of a preprint

Abstract

This study delves into the proteomic intricacies of drug-resistant cells (DRCs) within prostate cancer, which are known for their pivotal roles in therapeutic resistance, relapse, and metastasis. Utilizing single-cell proteomics (SCP) with an optimized high-throughput data-independent acquisition (DIA) approach with the throughput of 60 sample per day, we characterized the proteomic landscape of DRCs in comparison to parental PC3 cells. This DIA method allowed for robust and reproducible protein quantification at the single-cell level, enabling the identification and quantification of over 1300 proteins per cell on average. Distinct proteomic sub-clusters within the DRC population were identified, closely linked to variations in cell size. The study uncovered novel protein signatures, including the regulation of proteins critical for cell adhesion and metabolic processes, as well as the upregulation of surface proteins and transcription factors pivotal for cancer progression. Furthermore, by conducting single-cell RNA-seq (scRNA-seq) analysis, we identified six upregulated and 10 downregulated genes consistently altered in drug-treated cells across both SCP and scRNA-seq platforms. These findings underscore the heterogeneity of DRCs and their unique molecular signatures, providing valuable insights into their biological behavior and potential therapeutic targets.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.mcpro.2025.100949

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 48

  1. Hanahan, 2011, Hallmarks of cancer: the next generation, Cell, 144, 646, 10.1016/j.cell.2011.02.013 · DOI · Paper page
  2. Marusyk, 2010, Tumor heterogeneity: causes and consequences, Biochim. Biophys. Acta, 1805, 105
  3. Pienta, 2021, Cancer recurrence and lethality are enabled by enhanced survival and reversible cell cycle arrest of polyaneuploid cells, Proc. Natl. Acad. Sci. U. S. A., 118, 10.1073/pnas.2020838118 · DOI
  4. Pienta, 2020, Poly-aneuploid cancer cells promote evolvability, generating lethal cancer, Evol. Appl., 13, 1626, 10.1111/eva.12929 · DOI
  5. Mallin, 2023, Cells in the polyaneuploid cancer cell (PACC) state have increased metastatic potential, Clin. Exp. Metastasis, 40, 321, 10.1007/s10585-023-10216-8 · DOI
  6. Lakhani, 2023, Aneuploidy in human cancer: new tools and perspectives, Trends Genet., 39, 968, 10.1016/j.tig.2023.09.002 · DOI
  7. Trabzonlu, 2023, Presence of cells in the polyaneuploid cancer cell (PACC) state predicts the risk of recurrence in prostate cancer, Prostate, 83, 277, 10.1002/pros.24459 · DOI
  8. Bukkuri, 2022, Stochastic models of Mendelian and reverse transcriptional inheritance in state-structured cancer populations, Sci. Rep., 12, 10.1038/s41598-022-17456-w · DOI
  9. Lin, 2019, The role of heterogeneous environment and docetaxel gradient in the emergence of polyploid, mesenchymal and resistant prostate cancer cells, Clin. Exp. Metastasis, 36, 97, 10.1007/s10585-019-09958-1 · DOI
  10. Fei, 2019, Syncytin 1, CD9, and CD47 regulating cell fusion to form PGCCs associated with cAMP/PKA and JNK signaling pathway, Cancer Med., 8, 3047, 10.1002/cam4.2173 · DOI
  11. Zhou, 2023, Single-cell morphological and transcriptome analysis unveil inhibitors of polyploid giant breast cancer cells in vitro, Commun. Biol., 6, 1301, 10.1038/s42003-023-05674-5 · DOI
  12. Tagal, 2021, Loss of Aurora Kinase signaling allows lung cancer cells to Adopt Endoreplication and form polyploid giant cancer cells that resist Antimitotic drugs, Cancer Res., 81, 400, 10.1158/0008-5472.CAN-20-1693 · DOI
  13. Ganem, 2012, Linking abnormal mitosis to the acquisition of DNA damage, J. Cell Biol, 199, 871, 10.1083/jcb.201210040 · DOI
  14. Vitale, 2011, Illicit survival of cancer cells during polyploidization and depolyploidization, Cell. Death. Differ., 18, 1403, 10.1038/cdd.2010.145 · DOI · Paper page
  15. Woo, 2021, High-throughput and high-efficiency sample preparation for single-cell proteomics using a nested nanowell chip, Nat. Commun., 12, 6246, 10.1038/s41467-021-26514-2 · DOI
  16. Khan, 2024, Dynamics of single-cell protein Covariation during epithelial-mesenchymal Transition, J. Proteome Res., 25, 10
  17. Wang, 2022, Optimized data-independent acquisition approach for proteomic analysis at single-cell level, Clin. Proteomics, 19, 24, 10.1186/s12014-022-09359-9 · DOI
  18. Woo, 2022, Three-dimensional feature matching improves coverage for single-cell proteomics based on ion mobility filtering, Cell. Syst., 13, 426, 10.1016/j.cels.2022.02.003 · DOI
  19. Nehme, 2021, Polyploid giant cancer cells, stemness and epithelial-mesenchymal plasticity elicited by human cytomegalovirus, Oncogene, 40, 3030, 10.1038/s41388-021-01715-7 · DOI
  20. Amend, 2019, Polyploid giant cancer cells: Unrecognized actuators of tumorigenesis, metastasis, and resistance, Prostate, 79, 1489, 10.1002/pros.23877 · DOI
  21. Mallin, 2025, Cells in the polyaneuploid cancer cell state are Pro-metastatic, Mol. Cancer Res., 23, 219, 10.1158/1541-7786.MCR-24-0689 · DOI
  22. Kim, 2023, Nuclear morphology predicts cell survival to cisplatin chemotherapy, Neoplasia, 42, 10.1016/j.neo.2023.100906 · DOI
  23. Kostecka, 2024, Cancer cells employ lipid droplets to survive toxic stress, Prostate, 84, 644, 10.1002/pros.24680 · DOI
  24. Schmidt, 2024, Polyploid cancer cells reveal signatures of chemotherapy resistance, Oncogene, 44, 439, 10.1038/s41388-024-03212-z · DOI
  25. Konno, 2024, Universal Pretreatment development for low-input proteomics using Lauryl Maltose Neopentyl Glycol, Mol. Cell. Proteomics, 23, 10.1016/j.mcpro.2024.100745 · DOI
  26. Clark, 2018, Evaluation of NCI-7 cell line panel as a reference material for clinical proteomics, J. Proteome Res., 17, 2205, 10.1021/acs.jproteome.8b00165 · DOI
  27. Specht, 2021, Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2, Genome Biol., 22, 50, 10.1186/s13059-021-02267-5 · DOI · Paper page
  28. Tyanova, 2016, The Perseus computational platform for comprehensive analysis of (prote)omics data, Nat. Methods, 13, 731, 10.1038/nmeth.3901 · DOI · Paper page
  29. Taverna, 2020, BIOMEX: an interactive workflow for (single cell) omics data interpretation and visualization, Nucleic Acids Res., 48, W385, 10.1093/nar/gkaa332 · DOI
  30. Szklarczyk, 2023, The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest, Nucleic Acids Res., 51, D638, 10.1093/nar/gkac1000 · DOI · Paper page
  31. Dobin, 2013, STAR: ultrafast universal RNA-seq aligner, Bioinformatics, 29, 15, 10.1093/bioinformatics/bts635 · DOI · Paper page
  32. Liao, 2019, The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads, Nucleic Acids Res., 47, e47, 10.1093/nar/gkz114 · DOI
  33. Meier, 2020, diaPASEF: parallel accumulation-serial fragmentation combined with data-independent acquisition, Nat. Methods, 17, 1229, 10.1038/s41592-020-00998-0 · DOI
  34. Munoz-Bernart, 2023, S-adenosylhomocysteine hydrolase-like protein 1 (AHCYL1) inhibits lung cancer tumorigenesis by regulating cell plasticity, Biol. Direct, 18, 8, 10.1186/s13062-023-00364-y · DOI
  35. Ristori, 2020, Amyloid-beta precursor protein APP down-regulation Alters actin cytoskeleton-Interacting proteins in Endothelial cells, Cells, 9, 2506, 10.3390/cells9112506 · DOI
  36. Kievit, 2018, Variants in members of the cadherin-catenin complex, CDH1 and CTNND1, cause blepharocheilodontic syndrome, Eur. J. Hum. Genet., 26, 210, 10.1038/s41431-017-0010-5 · DOI
  37. Jackson, 2010, The mechanism of eukaryotic translation initiation and principles of its regulation, Nat. Rev. Mol. Cell Biol, 11, 113, 10.1038/nrm2838 · DOI · Paper page
  38. Sundblad, 2017, Galectin-1: a Jack-of-all-Trades in the resolution of Acute and Chronic Inflammation, J. Immunol., 199, 3721, 10.4049/jimmunol.1701172 · DOI
  39. Engel, 2018, First evidence of SGPL1 expression in the cell membrane silencing the extracellular S1P siren in mammary epithelial cells, PLoS One, 13, 10.1371/journal.pone.0196854 · DOI
  40. Ribeiro Ede, 2014, The structure and regulation of human muscle alpha-actinin, Cell, 159, 1447, 10.1016/j.cell.2014.10.056 · DOI
  41. Takimoto, 2019, The Macrophage 'Do not eat me' signal, CD47, is a clinically validated cancer immunotherapy target, Ann. Oncol., 30, 486, 10.1093/annonc/mdz006 · DOI
  42. Hou, 2006, The Fat1 cadherin integrates vascular smooth muscle cell growth and migration signals, J. Cell Biol, 173, 417, 10.1083/jcb.200508121 · DOI
  43. Peng, 2021, Role of FAT1 in health and disease, Oncol. Lett., 21, 398, 10.3892/ol.2021.12659 · DOI
  44. Legrand, 2019, DDX5 plays essential transcriptional and post-transcriptional roles in the maintenance and function of spermatogonia, Nat. Commun., 10, 2278, 10.1038/s41467-019-09972-7 · DOI
  45. Jorgensen, 2018, DNA methylation, through DNMT1, has an essential role in the development of gastrointestinal smooth muscle cells and disease, Cell. Death. Dis., 9, 474, 10.1038/s41419-018-0495-z · DOI
  46. Brunner, 2022, Ultra-high sensitivity mass spectrometry quantifies single-cell proteome changes upon perturbation, Mol. Syst. Biol., 18, 10.15252/msb.202110798 · DOI · Paper page
  47. Fulcher, 2024, Parallel measurement of transcriptomes and proteomes from same single cells using nanodroplet splitting, Nat. Commun., 15, 10.1038/s41467-024-54099-z · DOI
  48. Deutsch, 2023, The ProteomeXchange consortium at 10 years: 2023 update, Nucleic Acids Res., 51, D1539, 10.1093/nar/gkac1040 · DOI

Metadata

Authors
Woo, J., Loycano, M., Amanullah, M., Qian, J., Amend, S. R., Pienta, K. J., & Zhang, H.
Affiliations
Johns Hopkins University (US)
Corresponding author
Zhang, Hui
Venue
Molecular & Cellular Proteomics
Publisher
Elsevier BV
Published
2025-04
Volume
24
Issue
4
Pages
100949
ISSN
1535-9476 (ISSN-L)
OpenAlex
W4408432679
Cited by
17
References
2
Citations by year
2026: 11 · 2025: 6
FWCI
11.18
Type
journal article
Language
en
Open access
Locations
  • Molecular & Cellular Proteomics (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (submittedVersion)
Funders
  • National Institutes of Health National Cancer Institute (CA093900)
  • DOD Prostate Cancer Research Program (W81XWH-20-10353, W81XWH-22-1-0680)
  • U.S. Department of Defense
  • Patrick C. Walsh Prostate Cancer Research Fund
  • Congressionally Directed Medical Research Programs
  • National Institutes of Health
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Prostate Cancer Treatment and Research
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Ubiquitin and proteasome pathways
Keywords
single-cell proteomics, data-independent acquisition, proteomic heterogeneity, cell size variation, cell adhesion proteins, cancer metabolism, surface proteins, transcription factors, drug resistance, PC-3 cells, single-cell RNA sequencing, therapeutic target

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review