CoChat
Sign Up
Cited by 24Pancreatic and Hepatic Oncology ResearchCancer Genomics and DiagnosticsBreast Cancer Treatment Studies

A novel tp53-associated nomogram to predict the overall survival in patients with pancreatic cancer

Open access
Liu, Xun, Chen, Bobo, Chen, Jiahui, Sun, Shaolong·2021·BMC Cancer
DOI 10.1186/s12885-021-08066-2PMC PMC8011162
Open this paper in CoChat — free accountOpen PDF

Abstract

BACKGROUND: Gene mutations play critical roles in tumorigenesis and cancer development. Our study aimed to screen survival-related mutations and explore a novel gene signature to predict the overall survival in pancreatic cancer. METHODS: Somatic mutation data from three cohorts were used to identify the common survival-related gene mutation with Kaplan-Meier curves. RNA-sequencing data were used to explore the signature for survival prediction. First, Weighted Gene Co-expression Network Analysis was conducted to identify candidate genes. Then, the ICGC-PACA-CA cohort was applied as the training set and the TCGA-PAAD cohort was used as the external validation set. A TP53-associated signature calculating the risk score of every patient was developed with univariate Cox, least absolute shrinkage and selection operator, and stepwise regression analysis. Kaplan-Meier and receiver operating characteristic curves were plotted to verify the accuracy. The independence of the signature was confirmed by the multivariate Cox regression analysis. Finally, a prognostic nomogram including 359 patients was constructed based on the combined expression data and the risk scores. RESULTS: TP53 mutation was screened to be the robust and survival-related mutation type, and was associated with immune cell infiltration. Two thousand, four hundred fifty-five genes included in the six modules generated in the WGCNA were screened as candidate survival related TP53-associated genes. A seven-gene signature was constructed: Risk score = (0.1254 × ERRFI1) - (0.1365 × IL6R) - (0.4400 × PPP1R10) - (0.3397 × PTOV1-AS2) + (0.1544 × SCEL) - (0.4412 × SSX2IP) - (0.2231 × TXNL4A). Area Under Curves of 1-, 3-, and 5-year ROC curves were 0.731, 0.808, and 0.873 in the training set and 0.703, 0.677, and 0.737 in the validation set. A prognostic nomogram including 359 patients was constructed and well-calibrated, with the Area Under Curves of 1-, 3-, and 5-year ROC curves as 0.713, 0.753, and 0.823. CONCLUSIONS: The TP53-associated signature exhibited good prognostic efficacy in predicting the overall survival of PC patients.

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 · 10.1186/s12885-021-08066-2

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

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?

  • The TP53 mutational status-based genomic signature is a critical factor for disease prognosis and therapeutic responses.

    “The TP53 mutational status-based genomic signature emerges as a critical factor for disease prognosis and therapeutic responses.”

    From Significance of TP53, CDKN2A, SMAD4 and KRAS in Pancreatic Cancer (2024) · cites this paper as [23]

    The Results report that TP53-mutated patients had significantly worse overall survival in three pancreatic cancer cohorts, and the Discussion describes a seven-gene TP53-related signature for prognosis prediction. The cited passages do not establish that the signature predicts therapeutic responses. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • The TP53 mutational status-based genomic signature has independent predictive value for overall survival and good prognostic estimate in pancreatic cancer patients.

    “Studies demonstrate its independent predictive value for overall survival and good prognostic estimate in pancreatic cancer patients.”

    From Significance of TP53, CDKN2A, SMAD4 and KRAS in Pancreatic Cancer (2024) · cites this paper as [23]

  • The accuracy of the TP53 genomic signature is underscored by its association with the immunophenotype of PDAC.

    “The accuracy of this genomic signature is underscored by its association with the immunophenotype of PDAC [21,22,23].”

    From Significance of TP53, CDKN2A, SMAD4 and KRAS in Pancreatic Cancer (2024) · cites this paper as [23]

Self-check

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

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

Cites

Flagged first, then by citations

Research works printed but not linked: 46

  1. [1]Rahib L Smith BD Aizenberg R Rosenzweig AB Fleshman JM Matrisian LM Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States Cancer Res 2014 74 11 2913 2921 10.1158/0008-5472.CAN-14-0155 24840647 · DOI · Paper page
  2. [2]Ilic M Ilic I Epidemiology of pancreatic cancer World J Gastroenterol 2016 22 44 9694 9705 10.3748/wjg.v22.i44.9694 27956793 PMC5124974 · DOI
  3. [3]Ansari D Tingstedt B Andersson B Holmquist F Sturesson C Williamsson C Sasor A Borg D Bauden M Andersson R Pancreatic cancer: yesterday, today and tomorrow Future Oncol (London, England) 2016 12 16 1929 1946 10.2217/fon-2016-0010 27246628 · DOI
  4. [4]Dreyer SB Chang DK Bailey P Biankin AV Pancreatic Cancer genomes: implications for clinical management and therapeutic development Clin Cancer Res 2017 23 7 1638 1646 10.1158/1078-0432.CCR-16-2411 28373362 · DOI
  5. [5]McGuigan A Kelly P Turkington RC Jones C Coleman HG McCain RS Pancreatic cancer: a review of clinical diagnosis, epidemiology, treatment and outcomes World J Gastroenterol 2018 24 43 4846 4861 10.3748/wjg.v24.i43.4846 30487695 PMC6250924 · DOI
  6. [6]Kim JE Lee KT Lee JK Paik SW Rhee JC Choi KW Clinical usefulness of carbohydrate antigen 19-9 as a screening test for pancreatic cancer in an asymptomatic population J Gastroenterol Hepatol 2004 19 2 182 186 10.1111/j.1440-1746.2004.03219.x 14731128 · DOI
  7. [7]Ansari D Torén W Zhou Q Hu D Andersson R Proteomic and genomic profiling of pancreatic cancer Cell Biol Toxicol 2019 35 4 333 343 10.1007/s10565-019-09465-9 30771135 PMC6757097 · DOI
  8. [8]Klein AP Wolpin BM Risch HA Stolzenberg-Solomon RZ Mocci E Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer Nat Commun 2018 9 1 556 10.1038/s41467-018-02942-5 29422604 PMC5805680 · DOI · Paper page
  9. [10]Wu J Li Z Zeng K Wu K Xu D Zhou J Xu L Key genes associated with pancreatic cancer and their association with outcomes: a bioinformatics analysis Mol Med Rep 2019 20 2 1343 1352 10.3892/mmr.2019.10321 31173193 · DOI
  10. [11]Koboldt DC Zhang Q Larson DE Shen D McLellan MD Lin L Miller CA Mardis ER Ding L Wilson RK VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing Genome Res 2012 22 3 568 576 10.1101/gr.129684.111 22300766 PMC3290792 · DOI
  11. [12]Kassahn KS Holmes O Nones K Patch AM Miller DK Christ AN Harliwong I Bruxner TJ Xu Q Anderson M Wood S Leonard C Taylor D Newell F Song S Idrisoglu S Nourse C Nourbakhsh E Manning S Wani S Steptoe A Pajic M Cowley MJ Pinese M Chang DK Gill AJ Johns AL Wu J Wilson PJ Fink L Biankin AV Waddell N Grimmond SM Pearson JV Somatic point mutation calling in low cellularity tumors PLoS One 2013 8 11 e74380 10.1371/journal.pone.0074380 24250782 PMC3826759 · DOI
  12. [13]Cibulskis K Lawrence MS Carter SL Sivachenko A Jaffe D Sougnez C Gabriel S Meyerson M Lander ES Getz G Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples Nat Biotechnol 2013 31 3 213 219 10.1038/nbt.2514 23396013 PMC3833702 · DOI
  13. [14]Skidmore ZL Wagner AH Lesurf R Campbell KM Kunisaki J Griffith OL Griffith M GenVisR: genomic visualizations in R Bioinformatics 2016 32 19 3012 3014 10.1093/bioinformatics/btw325 27288499 PMC5039916 · DOI
  14. [15]Yoshihara K Shahmoradgoli M Martínez E Vegesna R Kim H Torres-Garcia W Treviño V Shen H Laird PW Levine DA Carter SL Getz G Stemke-Hale K Mills GB Verhaak RGW Inferring tumour purity and stromal and immune cell admixture from expression data Nat Commun 2013 4 1 2612 10.1038/ncomms3612 24113773 PMC3826632 · DOI · Paper page
  15. [16]Newman AM Liu CL Green MR Gentles AJ Feng W Xu Y Hoang CD Diehn M Alizadeh AA Robust enumeration of cell subsets from tissue expression profiles Nat Methods 2015 12 5 453 457 10.1038/nmeth.3337 25822800 PMC4739640 · DOI · Paper page
  16. [17]Langfelder P Horvath S WGCNA: an R package for weighted correlation network analysis BMC Bioinformatics 2008 9 1 559 10.1186/1471-2105-9-559 19114008 PMC2631488 · DOI · Paper page
  17. [18]Hou J Wang Z Li H Zhang H Luo L Gene signature and identification of clinical trait-related m (6) a regulators in pancreatic Cancer Front Genet 2020 11 522 10.3389/fgene.2020.00522 32754191 PMC7367043 · DOI
  18. [19]Meng Z Yuan Q Zhao J Wang B Li S Offringa R Jin X Wu H The m (6) A-related mRNA signature predicts the prognosis of pancreatic Cancer patients Mol Ther Oncolytics 2020 17 460 470 10.1016/j.omto.2020.04.011 32490170 PMC7256444 · DOI
  19. [20]Meng Z Ren D Zhang K Zhao J Jin X Wu H Using ESTIMATE algorithm to establish an 8-mRNA signature prognosis prediction system and identify immunocyte infiltration-related genes in pancreatic adenocarcinoma Aging (Albany NY) 2020 12 6 5048 5070 10.18632/aging.102931 32181755 PMC7138590 · DOI
  20. [21]Wu C Wu Z Tian B Five gene signatures were identified in the prediction of overall survival in resectable pancreatic cancer BMC Surg 2020 20 1 207 10.1186/s12893-020-00856-y 32943033 PMC7499920 · DOI
  21. [22]Wu M Li X Liu R Yuan H Liu W Liu Z Development and validation of a metastasis-related gene signature for predicting the overall survival in patients with pancreatic ductal adenocarcinoma J Cancer 2020 11 21 6299 6318 10.7150/jca.47629 33033514 PMC7532518 · DOI
  22. [23]Yue P Zhu C Gao Y Li Y Wang Q Zhang K Gao S Shi Y Wu Y Wang B Xie J Meng X Development of an autophagy-related signature in pancreatic adenocarcinoma Biomed Pharmacother 2020 126 110080 10.1016/j.biopha.2020.110080 32203889 · DOI
  23. [24]Zhou S Yan Y Chen X Zeng S Wei J Wang X Gong Z Xu Z A two-gene-based prognostic signature for pancreatic cancer Aging (Albany NY) 2020 12 18 18322 18342 10.18632/aging.103698 32966237 PMC7585105 · DOI
  24. [25]Deng Z Li X Shi Y Lu Y Yao W Wang J A novel autophagy-related IncRNAs signature for prognostic prediction and clinical value in patients with pancreatic Cancer Front Cell Dev Biol 2020 8 606817 10.3389/fcell.2020.606817 33384999 PMC7769875 · DOI
  25. [26]Charoentong P Finotello F Angelova M Mayer C Efremova M Rieder D Hackl H Trajanoski Z Pan-cancer Immunogenomic analyses reveal genotype-Immunophenotype relationships and predictors of response to checkpoint blockade Cell Rep 2017 18 1 248 262 10.1016/j.celrep.2016.12.019 28052254 · DOI · Paper page
  26. [27]Cicenas J Kvederaviciute K Meskinyte I Meskinyte-Kausiliene E Skeberdyte A Cicenas J KRAS, TP53, CDKN2A, SMAD4, BRCA1, and BRCA2 mutations in pancreatic cancer Cancers 2017 9 5 42 10.3390/cancers9050042 PMC5447952 28452926 · DOI
  27. [28]Levy N Yonish-Rouach E Oren M Kimchi A Complementation by wild-type p53 of interleukin-6 effects on M1 cells: induction of cell cycle exit and cooperativity with c-myc suppression Mol Cell Biol 1993 13 12 7942 7952 10.1128/MCB.13.12.7942 8247009 PMC364866 · DOI
  28. [29]Morton JP Timpson P Karim SA Ridgway RA Athineos D Doyle B Jamieson NB Oien KA Lowy AM Brunton VG Frame MC Evans TRJ Sansom OJ Mutant p53 drives metastasis and overcomes growth arrest/senescence in pancreatic cancer Proc Natl Acad Sci U S A 2010 107 1 246 251 10.1073/pnas.0908428107 20018721 PMC2806749 · DOI · Paper page
  29. [30]Kanda M Sadakari Y Borges M Topazian M Farrell J Syngal S Lee J Kamel I Lennon AM Knight S Mutant TP53 in duodenal samples of pancreatic juice from patients with pancreatic cancer or high-grade dysplasia Clin Gastroenterol Hepatol 2013 11 6 719 730.e715 10.1016/j.cgh.2012.11.016 23200980 PMC3600161 · DOI · Paper page
  30. [31]Ormanns S Siveke JT Heinemann V Haas M Sipos B Schlitter AM Esposito I Jung A Laubender RP Kruger S Vehling-Kaiser U Winkelmann C Fischer von Weikersthal L Clemens MR Gauler TC Märten A Geissler M Greten TF Kirchner T Boeck S pERK, pAKT and p53 as tissue biomarkers in erlotinib-treated patients with advanced pancreatic cancer: a translational subgroup analysis from AIO-PK0104 BMC Cancer 2014 14 1 624 10.1186/1471-2407-14-624 25164437 PMC4152581 · DOI
  31. [32]Kahlert C Melo SA Protopopov A Tang J Seth S Koch M Zhang J Weitz J Chin L Futreal A Kalluri R Identification of double-stranded genomic DNA spanning all chromosomes with mutated KRAS and p53 DNA in the serum exosomes of patients with pancreatic cancer J Biol Chem 2014 289 7 3869 3875 10.1074/jbc.C113.532267 24398677 PMC3924256 · DOI
  32. [33]Lu X Xu T Qian J Wen X Wu D Detecting K-ras and p53 gene mutation from stool and pancreatic juice for diagnosis of early pancreatic cancer Chin Med J 2002 115 11 1632 1636 12609076
  33. [34]Mukherjee I Powell B Parianos M Downs D Ross SB Available technologies and clinical applications of targeted chemotherapy in pancreatic cancer Cancer Genet 2016 209 12 582 591 10.1016/j.cancergen.2016.08.001 27613576 · DOI
  34. [35]Cairns J Fridley BL Jenkins GD Zhuang Y Yu J Wang L Differential roles of ERRFI1 in EGFR and AKT pathway regulation affect cancer proliferation EMBO Rep 2018 19 3 e44767 10.15252/embr.201744767 29335246 PMC5835844 · DOI
  35. [36]Yu Y Chen Q Long noncoding RNA ANRIL promotes the malignant progression of cholangiocarcinoma by epigenetically repressing ERRFI1 expression Cancer Sci 2020 111 7 2297 2309 10.1111/cas.14447 32378752 PMC7385372 · DOI
  36. [37]Migliore C Morando E Ghiso E Anastasi S Leoni VP Apicella M Cora D Sapino A Pietrantonio F De Braud F miR-205 mediates adaptive resistance to MET inhibition via ERRFI1 targeting and raised EGFR signaling EMBO Mol Med 2018 10 9 e8746 10.15252/emmm.201708746 30021798 PMC6127885 · DOI
  37. [38]Heo TH Wahler J Suh N Potential therapeutic implications of IL-6/IL-6R/gp130-targeting agents in breast cancer Oncotarget 2016 7 13 15460 15473 10.18632/oncotarget.7102 26840088 PMC4941253 · DOI
  38. [39]Høgdall D O'Rourke CJ Dehlendorff C Larsen OF Jensen LH Johansen AZ Dang H Factor VM Grunnet M Mau-Sørensen M Serum IL6 as a prognostic biomarker and IL6R as a therapeutic target in biliary tract cancers Clin Cancer Res 2020 26 21 5655 5667 10.1158/1078-0432.CCR-19-2700 32933994 PMC8998158 · DOI
  39. [40]Colomiere M Ward AC Riley C Trenerry MK Cameron-Smith D Findlay J Ackland L Ahmed N Cross talk of signals between EGFR and IL-6R through JAK2/STAT3 mediate epithelial-mesenchymal transition in ovarian carcinomas Br J Cancer 2009 100 1 134 144 10.1038/sj.bjc.6604794 19088723 PMC2634691 · DOI
  40. [41]Zhu X Shen H Yin X Long L Chen X Feng F Liu Y Zhao P Xu Y Li M Xu W Li Y IL-6R/STAT3/miR-204 feedback loop contributes to cisplatin resistance of epithelial ovarian cancer cells Oncotarget 2017 8 24 39154 39166 10.18632/oncotarget.16610 28388577 PMC5503602 · DOI
  41. [42]Nagy A Banyai D Semjen D Beothe T Kovacs G Sciellin is a marker for papillary renal cell tumours Virchows Archiv 2015 467 6 695 700 10.1007/s00428-015-1856-y 26475151 · DOI
  42. [43]Chou CK Fan CC Lin PS Liao PY Tung JC Hsieh CH Hung MC Chen CH Chang WC Sciellin mediates mesenchymal-to-epithelial transition in colorectal cancer hepatic metastasis Oncotarget 2016 7 18 25742 25754 10.18632/oncotarget.8264 27013588 PMC5041940 · DOI
  43. [44]Breslin A Denniss FA Guinn BA SSX2IP: an emerging role in cancer Biochem Biophys Res Commun 2007 363 3 462 465 10.1016/j.bbrc.2007.09.052 17904521 · DOI
  44. [45]Guinn B Greiner J Schmitt M Mills KI Elevated expression of the leukemia-associated antigen SSX2IP predicts survival in acute myeloid leukemia patients who lack detectable cytogenetic rearrangements Blood 2009 113 5 1203 1204 10.1182/blood-2008-09-178848 19179477 · DOI
  45. [46]Li P Lin Y Zhang Y Zhu Z Huo K SSX2IP promotes metastasis and chemotherapeutic resistance of hepatocellular carcinoma J Transl Med 2013 11 1 52 10.1186/1479-5876-11-52 23452395 PMC3599991 · DOI
  46. [47]Chang SL Lee SW Yang SF Chien CC Chan TC Chen TJ Yang CC Li CF Wei YC Expression and prognostic utility of SSX2IP in patients with nasopharyngeal carcinoma APMIS 2020 128 4 287 297 10.1111/apm.13023 31837171 · DOI

Cited by

Sorted by citations

Authors
Liu, X., Chen, B., Chen, J., & Sun, S.
Affiliations
Sheng Jing Hospital (CN)
Corresponding author
Sun, Shaolong
ORCID
Venue
BMC Cancer
Publisher
Springer Science and Business Media LLC
Published
2021-03-31
Volume
21
Issue
1
Pages
335-335
ISSN
1471-2407 (ISSN-L)
DOI
10.1186/s12885-021-08066-2
PMC
PMC8011162
OpenAlex
W3152072428
Cited by
24
References
1
Citations by year
2026: 4 · 2025: 2 · 2024: 2 · 2023: 8 · 2022: 4 · 2021: 4
FWCI
1.64
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Cancer (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Health Sciences › Medicine › Oncology › Pancreatic and Hepatic Oncology Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
Keywords
pancreatic cancer, TP53 mutation, prognostic gene signature, nomogram, overall survival prediction, risk score, immune cell infiltration, gene co-expression network, ERRFI1, IL-6 receptor, somatic mutations, prognostic factors, risk stratification
MeSH terms
Aged, Female, Humans, Male, Mutation, Pancreatic Neoplasms, Prognosis, Cohort Studies, Survival Analysis, Tumor Suppressor Protein p53, Sequence Analysis, RNA, Nomograms

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