Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 71

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Loss of p53 and mutational heterogeneity drives immune resistance in an autochthonous mouse lung cancer model with high tumor mutational burden

Zhu, Mingrui, Kim, Jiwoong, Deng, Qing, Ricciuti, Biagio, Alessi, Joao V., Eglenen-Polat, Buse, Bender, Matthew E., Huang, Hai-Cheng, Kowash, Ryan R., Cuevas, Ileana, Bennett, Zachary T., Gao, Jinming, Minna, John D., Castrillon, Diego H., Awad, Mark M., Xu, Lin, Akbay, Esra A.·2023·Cancer Cell

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.ccell.2023.09.006

Cites

12 of 12 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

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

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

Show all 12 references

Research works printed but not linked: 58

  1. Siegel, 2022, Cancer statistics, 2022, CA A Cancer J. Clin., 72, 7
  2. Chae, 2018, Current landscape and future of dual anti-CTLA4 and PD-1/PD-L1 blockade immunotherapy in cancer; lessons learned from clinical trials with melanoma and non-small cell lung cancer (NSCLC), J. Immunother. Cancer, 6, 39, 10.1186/s40425-018-0349-3 · DOI · Paper page
  3. Lee, 2022, Efficacy and safety of atezolizumab, in combination with etoposide and carboplatin regimen, in the first-line treatment of extensive-stage small-cell lung cancer: a single-center experience, Cancer Immunol. Immunother., 71, 1093, 10.1007/s00262-021-03052-w · DOI
  4. Puri, 2020, Combination checkpoint inhibitors for treatment of non-small-cell lung cancer: an update on dual anti-CTLA-4 and anti-PD-1/PD-L1 therapies, Drugs Context, 9, 1, 10.7573/dic.2019-9-2 · DOI
  5. Reck, 2021, Five-Year Outcomes With Pembrolizumab Versus Chemotherapy for Metastatic Non-Small-Cell Lung Cancer With PD-L1 Tumor Proportion Score >/= 50, J. Clin. Oncol., 39, 2339, 10.1200/JCO.21.00174 · DOI · Paper page
  6. de Castro, 2023, Five-Year Outcomes With Pembrolizumab Versus Chemotherapy as First-Line Therapy in Patients With Non-Small-Cell Lung Cancer and Programmed Death Ligand-1 Tumor Proportion Score >/= 1% in the KEYNOTE-042 Study, J. Clin. Oncol., 41, 1986, 10.1200/JCO.21.02885 · DOI · Paper page
  7. Wang, 2021, FDA-Approved and Emerging Next Generation Predictive Biomarkers for Immune Checkpoint Inhibitors in Cancer Patients, Front. Oncol., 11, 683419, 10.3389/fonc.2021.683419 · DOI · Paper page
  8. Bonneville, 2017, Landscape of Microsatellite Instability Across 39 Cancer Types, JCO Precis. Oncol., 2017, 1, 10.1200/PO.17.00073 · DOI · Paper page
  9. Zhang, 2020, Role of DNA repair defects in predicting immunotherapy response, Biomark. Res., 8, 23, 10.1186/s40364-020-00202-7 · DOI
  10. Kane, 2014, A common cancer-associated DNA polymerase epsilon mutation causes an exceptionally strong mutator phenotype, indicating fidelity defects distinct from loss of proofreading, Cancer Res., 74, 1895, 10.1158/0008-5472.CAN-13-2892 · DOI
  11. Fu, 2022, Immunotherapy for a POLE Mutation Advanced Non-Small-Cell Lung Cancer Patient, Front. Pharmacol., 13, 817265, 10.3389/fphar.2022.817265 · DOI
  12. Liu, 2018, Favorable outcome of patients with lung adenocarcinoma harboring POLE mutations and expressing high PD-L1, Mol. Cancer, 17, 81, 10.1186/s12943-018-0832-y · DOI
  13. Ma, 2022, POLE/POLD1 mutation and tumor immunotherapy, J. Exp. Clin. Cancer Res., 41, 216, 10.1186/s13046-022-02422-1 · DOI
  14. Schumacher, 2015, Neoantigens in cancer immunotherapy, Science, 348, 69, 10.1126/science.aaa4971 · DOI · Paper page
  15. Hellmann, 2018, Genomic Features of Response to Combination Immunotherapy in Patients with Advanced Non-Small-Cell Lung Cancer, Cancer Cell, 33, 843, 10.1016/j.ccell.2018.03.018 · DOI · Paper page
  16. McGrail, 2021, High tumor mutation burden fails to predict immune checkpoint blockade response across all cancer types, Ann. Oncol., 32, 661, 10.1016/j.annonc.2021.02.006 · DOI · Paper page
  17. Rizvi, 2015, Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer, Science, 348, 124, 10.1126/science.aaa1348 · DOI · Paper page
  18. Aggarwal, 2020, Baseline Plasma Tumor Mutation Burden Predicts Response to Pembrolizumab-based Therapy in Patients with Metastatic Non-Small Cell Lung Cancer, Clin. Cancer Res., 26, 2354, 10.1158/1078-0432.CCR-19-3663 · DOI
  19. Adeegbe, 2018, BET Bromodomain Inhibition Cooperates with PD-1 Blockade to Facilitate Antitumor Response in Kras-Mutant Non-Small Cell Lung Cancer, Cancer Immunol. Res., 6, 1234, 10.1158/2326-6066.CIR-18-0077 · DOI
  20. Pfirschke, 2016, Immunogenic Chemotherapy Sensitizes Tumors to Checkpoint Blockade Therapy, Immunity, 44, 343, 10.1016/j.immuni.2015.11.024 · DOI · Paper page
  21. Akbay, 2017, Interleukin-17A Promotes Lung Tumor Progression Through Neutrophil Attraction to Tumor Sites and Mediating Resistance to PD-1 Blockade, J. Thorac. Oncol., 12, 1268, 10.1016/j.jtho.2017.04.017 · DOI · Paper page
  22. Li, 2018, Polymerase-mediated ultramutagenesis in mice produces diverse cancers with high mutational load, J. Clin. Invest., 128, 4179, 10.1172/JCI122095 · DOI
  23. Li, 2009, Fast and accurate short read alignment with Burrows-Wheeler transform, Bioinformatics, 25, 1754, 10.1093/bioinformatics/btp324 · DOI · Paper page
  24. McKenna, 2010, The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data, Genome Res., 20, 1297, 10.1101/gr.107524.110 · DOI · Paper page
  25. DePristo, 2011, A framework for variation discovery and genotyping using next-generation DNA sequencing data, Nat. Genet., 43, 491, 10.1038/ng.806 · DOI · Paper page
  26. Sherry, 1999, dbSNP - Database for single nucleotide polymorphisms and other classes of minor genetic variation, Genome Res., 9, 677, 10.1101/gr.9.8.677 · DOI · Paper page
  27. Li, 2009, The Sequence Alignment/Map format and SAMtools, Bioinformatics, 25, 2078, 10.1093/bioinformatics/btp352 · DOI · Paper page
  28. Mroz, 2015, Intra-tumor genetic heterogeneity and mortality in head and neck cancer: analysis of data from the Cancer Genome Atlas, PLoS Med., 12, e1001786, 10.1371/journal.pmed.1001786 · DOI · Paper page
  29. Ravi, 2023, Genomic and transcriptomic analysis of checkpoint blockade response in advanced non-small cell lung cancer, Nat. Genet., 55, 807, 10.1038/s41588-023-01355-5 · DOI · Paper page
  30. Li, 2021, Prolonged activation of innate immune pathways by a polyvalent STING agonist, Nat. Biomed. Eng., 5, 455, 10.1038/s41551-020-00675-9 · DOI · Paper page
  31. DuPage, 2009, Conditional mouse lung cancer models using adenoviral or lentiviral delivery of Cre recombinase, Nat. Protoc., 4, 1064, 10.1038/nprot.2009.95 · DOI · Paper page
  32. Jackson, 2001, Analysis of lung tumor initiation and progression using conditional expression of oncogenic K-ras, Genes Dev., 15, 3243, 10.1101/gad.943001 · DOI · Paper page
  33. Koboldt, 2020, Best practices for variant calling in clinical sequencing, Genome Med., 12, 91, 10.1186/s13073-020-00791-w · DOI · Paper page
  34. Fei, 2021, Targeting the CCL2/CCR2 Axis in Cancer Immunotherapy: One Stone, Three Birds?, Front. Immunol., 12, 771210, 10.3389/fimmu.2021.771210 · DOI · Paper page
  35. Shinbrot, 2014, Exonuclease mutations in DNA polymerase epsilon reveal replication strand specific mutation patterns and human origins of replication, Genome Res., 24, 1740, 10.1101/gr.174789.114 · DOI · Paper page
  36. Haradhvala, 2018, Distinct mutational signatures characterize concurrent loss of polymerase proofreading and mismatch repair, Nat. Commun., 9, 1746, 10.1038/s41467-018-04002-4 · DOI · Paper page
  37. Alexandrov, 2013, Signatures of mutational processes in human cancer, Nature, 500, 415, 10.1038/nature12477 · DOI · Paper page
  38. Zhu, 1999, p53 induces TAP1 and enhances the transport of MHC class I peptides, Oncogene, 18, 7740, 10.1038/sj.onc.1203235 · DOI
  39. Wang, 2013, p53 increases MHC class I expression by upregulating the endoplasmic reticulum aminopeptidase ERAP1, Nat. Commun., 4, 2359, 10.1038/ncomms3359 · DOI
  40. Stieger, 2009, In vivo gene regulation using tetracycline-regulatable systems, Adv. Drug Deliv. Rev., 61, 527, 10.1016/j.addr.2008.12.016 · DOI
  41. Chen, 2016, TRIM14 Inhibits cGAS Degradation Mediated by Selective Autophagy Receptor p62 to Promote Innate Immune Responses, Mol. Cell, 64, 105, 10.1016/j.molcel.2016.08.025 · DOI · Paper page
  42. Prabakaran, 2018, Attenuation of cGAS-STING signaling is mediated by a p62/SQSTM1-dependent autophagy pathway activated by TBK1, EMBO J., 37, e97858, 10.15252/embj.201797858 · DOI · Paper page
  43. Li, 2020, A PoleP286R mouse model of endometrial cancer recapitulates high mutational burden and immunotherapy response, JCI Insight, 5, e138829, 10.1172/jci.insight.138829 · DOI
  44. Kucherlapati, 2010, An Msh2 conditional knockout mouse for studying intestinal cancer and testing anticancer agents, Gastroenterology, 138, 993, 10.1053/j.gastro.2009.11.009 · DOI
  45. Cousins, 2021, The Elusive Endometrial Epithelial Stem/Progenitor Cells, Front. Cell Dev. Biol., 9, 640319, 10.3389/fcell.2021.640319 · DOI
  46. Martinez-Usatorre, 2021, Overcoming microenvironmental resistance to PD-1 blockade in genetically engineered lung cancer models, Sci. Transl. Med., 13, eabd1616, 10.1126/scitranslmed.abd1616 · DOI
  47. Ma, 2022, Functional landscapes of POLE and POLD1 mutations in checkpoint blockade-dependent antitumor immunity, Nat. Genet., 54, 996, 10.1038/s41588-022-01108-w · DOI
  48. Martin, 2021, The adaptive immune system is a major driver of selection for tumor suppressor gene inactivation, Science, 373, 1327, 10.1126/science.abg5784 · DOI
  49. Ghosh, 2021, Mutant p53 suppresses innate immune signaling to promote tumorigenesis, Cancer Cell, 39, 494, 10.1016/j.ccell.2021.01.003 · DOI · Paper page
  50. Wang, 2022, Immune Subtypes in LUAD Identify Novel Tumor Microenvironment Profiles With Prognostic and Therapeutic Implications, Front. Immunol., 13, 877896, 10.3389/fimmu.2022.877896 · doi:10.3389/fimmu.2022.877896
  51. Sun, 2020, Specific TP53 subtype as biomarker for immune checkpoint inhibitors in lung adenocarcinoma, EBioMedicine, 60, 102990, 10.1016/j.ebiom.2020.102990 · DOI · Paper page
  52. Assoun, 2019, Association of TP53 mutations with response and longer survival under immune checkpoint inhibitors in advanced non-small-cell lung cancer, Lung Cancer, 132, 65, 10.1016/j.lungcan.2019.04.005 · DOI · Paper page
  53. Murnyák, 2016, Immunohistochemical correlates of TP53 somatic mutations in cancer, Oncotarget, 7, 64910, 10.18632/oncotarget.11912 · DOI
  54. Ahrendt, 2003, p53 mutations and survival in stage I non-small-cell lung cancer: results of a prospective study, J. Natl. Cancer Inst., 95, 961, 10.1093/jnci/95.13.961 · DOI · Paper page
  55. Chinnam, 2022, MDM2 E3 ligase activity is essential for p53 regulation and cell cycle integrity, PLoS Genet., 18, e1010171, 10.1371/journal.pgen.1010171 · DOI
  56. Girish, 2023, Oncogene-like addiction to aneuploidy in human cancers, bioRxiv
  57. Hüllein, 2019, MDM4 Is Targeted by 1q Gain and Drives Disease in Burkitt Lymphoma, Cancer Res., 79, 3125, 10.1158/0008-5472.CAN-18-3438 · DOI
  58. Wolf, 2019, UVB-Induced Tumor Heterogeneity Diminishes Immune Response in Melanoma, Cell, 179, 219, 10.1016/j.cell.2019.08.032 · DOI · Paper page

Cited by

See all 71

Metadata

Authors
Zhu, M., Kim, J., Deng, Q., Ricciuti, B., Alessi, J. V., Eglenen-Polat, B., Bender, M. E., Huang, H.-C., Kowash, R. R., Cuevas, I., Bennett, Z. T., Gao, J., Minna, J. D., Castrillon, D. H., Awad, M. M., Xu, L., & Akbay, E. A.
Venue
Cancer Cell
Publisher
Elsevier BV
Published
2023-10
Volume
41
Issue
10
Pages
1731-1748.e8
ISSN
1535-6108
Cited by
71
References
12
Language
en
Funders
  • Welch Foundation (1975-20190330)
  • Mary Kay Ash Foundation
  • National Institutes of Health (R01CA237405, R01CA265884, RP180770, RP210099)
  • AstraZeneca
  • U.S. Department of Defense (W81XWH-21-1-0856)
  • Cancer Prevention and Research Institute of Texas (RR160080)
  • American Cancer Society (RSG-22-051-01-IBCD)
  • A Breath of Hope Lung Foundation
  • National Cancer Institute (5P50CA070907, R01CA276058)
  • National Comprehensive Cancer Network Foundation (NCCN 2021)

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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Loss of p53 and mutational heterogeneity drives immune resistance in an autochthonous mouse lung cancer model with high tumor mutational burden. https://app.cochat.ai/papers/10.1016/j.ccell.2023.09.006
The paper
Zhu, M., Kim, J., Deng, Q., Ricciuti, B., Alessi, J. V., Eglenen-Polat, B., Bender, M. E., Huang, H.-C., Kowash, R. R., Cuevas, I., Bennett, Z. T., Gao, J., Minna, J. D., Castrillon, D. H., Awad, M. M., Xu, L., & Akbay, E. A. (2023). Loss of p53 and mutational heterogeneity drives immune resistance in an autochthonous mouse lung cancer model with high tumor mutational burden. Cancer Cell. https://doi.org/10.1016/j.ccell.2023.09.006

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.