Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

TP53 mutation predicts the poor prognosis of non-Hodgkin lymphomas: Evidence from a meta-analysis

  • Peipei Xu ,

    Contributed equally to this work with: Peipei Xu, Xu Liu

    Affiliation Department of Hematology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu Province, People’s Republic of China

  • Xu Liu ,

    Contributed equally to this work with: Peipei Xu, Xu Liu

    Affiliation Department of Hematology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu Province, People’s Republic of China

  • Jian Ouyang ,

    chenb211@163.com (BC); ouyangj211@163.com (JO)

    Affiliation Department of Hematology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu Province, People’s Republic of China

  • Bing Chen

    chenb211@163.com (BC); ouyangj211@163.com (JO)

    Affiliation Department of Hematology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu Province, People’s Republic of China

Abstract

Non-Hodgkin lymphoma (NHL) is a group of malignant hematologic disorders with high heterogeneity. The diagnosis, clinical manifestations, classification, and prognosis of this condition differ among numerous NHL subgroups. The prognostic significance of the mutation of TP53, a tumor suppressor gene involved in cell cycle regulation, should be confirmed in NHL. In this study, our searching strategy and inclusion criteria were implemented, and the pooled hazard ratios (HRs) of the included studies were calculated directly or indirectly. A total of 1,851 patients were enrolled in 22 studies. A meta-analysis was then performed using STATA version 12.0 to confirm the correlation between the status of TP53 mutation and the survival time of patients with NHL. Statistical heterogeneity was assessed with a chi-square-based Q statistical test and Inconsistency index (I2) statistic. Sensitivity analysis and publication bias were also evaluated. A total of 22 studies were included in our meta-analysis. The pooled HR of the overall survival from 20 studies was 2.30 (95% CI: 1.92–2.76, p = 0.001) with heterogeneity (I2 30.2% p = 0.099). The pooled HR of the progression free survival provided in 5 articles was 2.28 (95% CI: 1.78–2.93, p = 0.001) with heterogeneity (I2 39.8% p = 0.156). No publication bias was found among the included studies, and sensitivity analysis suggested that the combined HRs were stable after any of the studies was excluded from our meta-analysis. This study identified the prognostic significance of TP53 mutation that varied in different NHL subgroups. The group with a mutated TP53 was significantly associated with poor prognosis in patients with NHL. This parameter is a valuable basis for accurate individual therapeutic regimens.

Introduction

Lymphoma has been commonly detected in developed countries [1], and this condition ranks sixth among cancer diseases affecting males and females in the USA [2]. Although the improvement of the diagnosis, classification, and treatment for NHL results in a decreased death rate, non-Hodgkin lymphoma (NHL) remains the ninth leading cause of cancer-related deaths in the USA [2]. With the heterogeneity and epidemiology of NHL, prognostic factors are necessary to achieve accurate classification and individual treatment regimens.

International prognostic index (IPI) is a widely used clinical prognostic indicator for aggressive NHL [3] and is based on patients treated with combination chemotherapy; however, NHL has been widely treated with a regimen comprising rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). Therefore, the accuracy of IPI may require improvement. Adjusted IPI has been extensively investigated, but an adjusted standard has yet to be established.

Molecular markers have been applied to clinical studies on the evaluation of survival time, pesticide effect, and individualized treatment. For instance, Heselmeyer-Haddad [4] indicated that the amplification of TERC is a necessary condition in cervical cancer development, and its detection can help diagnose low-grade lesions with high progression risks. CYP2C19 mutation is related to a weak response to clopidogre, and Food and Drug Administration (FDA) recommends the detection of CYP2C19 gene type in patients before they are treated with clopidogre [5]. With the deletion of TP53, the short survival time of patients with plasma cell myeloma can be predicted [6]. However, relevant prognostic indicators based on molecular markers for NHL remain insufficient.

An important tumor suppressor gene localized in chromosome 17P13.1, TP53 is considered as the gatekeeper for cellular growth and division [7]. TP53 tumor suppressor is involved in cell cycle processes, including DNA repair, apoptosis, senescence, and autophagy under cellular stress [8, 9]. TP53 mutation significantly affects cancer development because of its function, that is, TP53 regulates cell cycle and transcription to prevent excessive cellular activation.

The significance of TP53 mutation for NHL prognosis is inconsistent in several studies [10] [11]. TP53 mutation is a secondary genetic event in different types of B-cell and T-cell lymphomas [11]. The sample quantity in some reports is also insufficient to confirm the importance of TP53 mutation in NHL prognosis. Thus, further studies should be performed to reveal the relationship between the survival time of patients with NHL and the status of TP53 mutation.

In this research, a meta-analysis was performed to estimate the correlation of TP53 mutation and the survival time of patients with various NHLs and to confirm the value of TP53 mutation as a prognostic indicator for NHL.

Methods

Literature search

To ensure retrieval of all relevant studies, we used a broad search strategy with several key words in two electronic databases, including “PubMed” and Web of Science”. The following items were searched: “p53,”“prognosis,” and”lymphoma.” An upper date limit of February 2016 was applied, and no earlier data limitation. After the titles and abstracts were examined to include the studies that may meet the criteria, the full-text reading of the included articles was performed. The references of the included studies were also assessed to obtain additional experimental data.

Inclusion and exclusion criteria

The inclusion and exclusion criteria were strictly implemented, and the studies meeting the following requirements were included in this document. (1) The study investigated the relationship between TP53 mutation in tumor samples and the overall survival (OS) and progression free survival (PFS) of the NHL. (2) The study provided adequate data to calculate the hazard ratio (HR) of the OS and the PFS along with the corresponding 95% confidence interval (CI). (3) The study used reliable gene mutation technology such as DNA sequencing, polymerase chain reaction-single stranded conformation polymorphism. (4) The study results were written in English.

Only the studies meeting all the above mentioned inclusion criteria would be included in our meta-analysis. In addition, the following articles were excluded in our study. (1)The study did not give a clear pathological diagnosis on NHL. (2) The study did not give a specific number of TP53 mutation in detected cases. (3) The study did not offer the OS or PFS of detected cases, either the K-M curves. The case reports, reviews, meeting abstracts, editorials, or letters to the editor without the original data were not included, and the non-English studies and duplicate articles were excluded.

Data extraction and assessment of the study

We extracted the following information from the literature: first author, year, country, age of patients, disease subtype, number of total cases and TP53 mutation and wildtype cases, TP53 mutation threshold, study design, and HR (95% CI) of OS or PFS. We evaluated the quality of each study included in our research according to the Newcastle-Ottawa quality assessment scale [12].

Statistical analysis

We calculated the pooled HR of the studies included in our meta-analysis to explain the correlation between the TP53 mutation status and the prognosis of lymphoma. HRs were extracted for each study directly or indirectly. Five studies provided HRs and corresponding 95% CI of OS or PFS directly. For the studies providing Kaplan-Meier survival curves, data were extracted from the curve through the Enguage Digitizer version 4.1. Thereafter, the HRs and their 95% CI were estimated through the method described in Parmar’s study [13]. The rest of the studies provided the complete patient information on the TP53 mutation status and survival time. Thus, the calculation of HRs was performed with SPSS Version 22.0 software for Windows using the Cox proportional hazards regression model. A calculated HR > 1 suggested a poor prognosis for the group with mutated TP53. The 95% CI of HRs crossing 1 suggested that the correlation between TP53 mutation and prognosis was not statistically significant.

The statistical heterogeneity between the studies included in our document was evaluated through the Chi-square-based Q statistical test based on Peto’s method [14]. A p-value less than 0.10 for the Q-test means that heterogeneity exists among the studies. The Inconsistency index (I2) statistic was used to evaluate the level of heterogeneity. A high heterogeneity was related to a large I2 statistic. According to the Cochrane systematic reviews, I2 ranged from 0%–40%, indicating little or no heterogeneity; 30%–60% indicated rate heterogeneity; 50%–90% indicated substantial heterogeneity; and 75%–100% suggested considerable heterogeneity.

Random-effects or fixed-effects models were selected depending on the heterogeneity among the included studies. The pooled HR was calculated by the fixed-effects model on the condition of mild heterogeneity. Otherwise, the random-effects model was used. Begg’s test and Egger’s test were applied to detect the presence of publication bias. A p-value of less than 0.05 for Egger’s test indicated asymmetry of the funnel plot, whereas a Z-value of less than 1.96 and a p-value of more than 0.05 indicated no publication bias according to Begg’s test. All calculations were performed through STATA version 12.0 software (Stata Corporation, Collage Station, Texas, USA).

Results

Literature search and characteristics of studies

We checked 688 possibly related studies using the searching strategy presented in Fig 1. Finally, 22 studies were identified in our meta-analysis [10,11,1535]. The details of the 22 studies are listed in Table 1. A total of 1,851 patients were enrolled in these studies. Among the 22 studies, 20 provided the HR of the OS, and 5 provided the HR of the PFS.

thumbnail
Fig 1. Flow diagram of the relevant studies selection procedure.

https://doi.org/10.1371/journal.pone.0174809.g001

thumbnail
Table 1. Characteristics of studies included in the meta-analysis.

https://doi.org/10.1371/journal.pone.0174809.t001

Among the 22 studies published from 1995–2016, 16 studies were performed in the 21st century, whereas six were conducted in the 20th century. The areas carried out the trails including Europe, North America, and Asia. Three of the studies are multiple-center researches. Four studies were conducted in Japan; three in Italy; two in France, Denmark, and the USA; and one each in China, Czechoslovakia, UK, Sweden, and Norway. The subtypes of lymphoma involved in the studies were various, namely, DLBCL, MCL, Burkitt lymphoma, and others. 1 study investigated the Ritcher syndrome cases, but the RS cases in the study were all classified as DLBCL according to the pathological diagnosis [17]. The detection method of gene mutation in the trails was mainly PCR-SSCP and sequencing. Three studies used DGGE, whereas one study each used FASSAY, CDGE, or DHPLC to detect TP53 mutation. The exons detected mostly ranged from 5 to 8.

The quality score for the selected studies ranged from 6 to 9 through the NOS scoring system, with a median score of 8. A total of eight studies were prospective, whereas 12 were retrospective.

Pooled HR of OS and PFS

The pooled HR of the OS from the 20 studies was 2.30 (95% CI: 1.92–2.76, p = 0.001; Fig 2) with heterogeneity (I2 30.2% p = 0.099). The pooled HR of the PFS provided in five articles was 2.28 (95% CI: 1.78–2.93, p = 0.001; Fig 3) with heterogeneity (I2 39.8% p = 0.156). Both results indicate that the mutations of TP53 predict a poor prognosis on NHL.

thumbnail
Fig 2. The Hazard Ratio (HR) of TP53 mutation with the Overall Survival (OS).

HR > 1 implied worse OS for the TP53 mutated group.

https://doi.org/10.1371/journal.pone.0174809.g002

thumbnail
Fig 3. The Hazard Ratio (HR) of TP53 mutation with the Progression Free Survival (PFS).

HR > 1 implied worse PFS for the TP53 mutated group.

https://doi.org/10.1371/journal.pone.0174809.g003

Sensitivity analysis of OS was performed (Fig 4), and the outcome demonstrated that the removal of any of the studies would not have an important effect on the combined HR. Thus, a negative correlation between mutated TP53 and the prognosis of NHL existed after any study was excluded from our meta-analysis.

thumbnail
Fig 4. The sensitivity analysis of the Overall Survival (OS).

https://doi.org/10.1371/journal.pone.0174809.g004

Analysis on the pooled HR of OS in the subtypes of NHL

An analysis on the subtypes of NHL was performed. The pooled HR of the OS provided in three articles concerned with DLBCL was 1.94 (95% CI: 1.48–2.55, p = 0.001; Fig 5). The pooled HRs for MCL and BL were 4.51 (95% CI: 2.05–9.95, p = 0.001) and 1.58 (95% CI: 0.63–3.95, p = 0.329), respectively (Fig 5).

thumbnail
Fig 5. The Hazard Ratio (HR) of TP53 mutation with the Overall Survival (OS) of different subtypes.

HR > 1 implied worse OS for the TP53 mutated group.

https://doi.org/10.1371/journal.pone.0174809.g005

Subgroup analysis for OS

We performed subgroup analysis of OS on the publication year, areas, quality score, study design and number of total patients (Table 2). The findings suggest that the negative association between TP53 mutation and the survival time of NHL existed in all subgroups that we listed.

thumbnail
Table 2. Subgroup analysis of the pooled HRs with Overall Survival (OS).

https://doi.org/10.1371/journal.pone.0174809.t002

Publication bias

Egger’s test indicated that the funnel plot was symmetrical (p = 0.422), and the p-value of Begg’s test was greater than 0.5 (p = 0.604, Z = 0.52). Both outcomes suggested no publication bias for the studies included in our meta-analysis. The funnel plot of Begg’s test was presented (Fig 6).

thumbnail
Fig 6. The funnel plot of the Overall Survival (OS) of NHL.

https://doi.org/10.1371/journal.pone.0174809.g006

Discussion

According to our statistical data, 1,851 patients were examined, and the mutation frequency among the studies ranged from 11.43% to 66.67%, which was approximately distributed across the disease subtypes and influenced by the statistical significance of patients. The combined HR of OS in the 22 studies included in our meta-analysis was 2.30 (95% CI: 1.92–2.76, p = 0.001) with heterogeneity (I2 30.2% p = 0.099). The Q test and I2 test revealed low heterogeneity of the study. The results indicated that TP53 mutation negatively affected the survival time of patients with NHL.

The aberration of chromosome 17 in patients with lymphomas is related to drug resistance, therapeutic failure, and high tumor-related mortality rate [36]. Thus, the status of TP53 localized in chromosome 17 may influence the progression and survival of lymphomas. TP53 mutations have been detected in various human organs and in more than 50% of human cancers [37]. The most important domain of TP53 is the DNA-binding domain (DBD), and most TP53 mutations are missense mutations occurring in the DBD encoded by exons 4 to 8 of TP53 [22], [37]. In our meta-analysis, the trials for the detection of TP53 mutation mostly involved these exons. The high frequency of these mutations can disrupt the TP53 structure and then deactivate the TP53 pathway [38]; as a consequence, disruptions in cell cycle, DNA repair, apoptosis signaling, and apoptosis and autophagy in the cytoplasm occur, and these processes are related to tumor development and progression [9]. The dominantly negative effect exhibited in mutant TP53 can cause adverse therapeutic outcomes and early cancer recurrence [39]. Several studies included in our research also confirmed that TP53 mutations in the DBD are significantly correlated with poor OS in patients with NHLs [15,16,22]. In 2014, the American Association for Cancer Research (AACR) recommended two categories of precision medicine: Umbrella Trails and Basket Trails. Basket trails aim to investigate the therapeutic value of the same target genes in different types of cancers or human organs. Our results indicated that TP53 could be a potential target gene for precise individual therapeutic regimen.

Disease subtype analysis implied that the prognostic value of TP53 mutation was distinguished in the different subtypes of NHL. The pooled HR of DLBCL was 1.94 (95% CI: 1.48–2.55, p = 0.001), and a total of 894 patients were included in three studies. DLBCL was the most common type of NHL that is highly heterogeneous. The pooled HR confirmed the prognostic significance of TP53 mutation in DLBCL and indicated the clinical value of this phenomenon. By comparison, the pooled HR of MCL was 4.51 (95% CI: 2.05–9.95, p = 0.001). Several studies have confirmed that TP53 mutation is closely involved in advanced MCL, and the frequency of TP53 mutation reaches 27.3%, as revealed by a FASAY method [18]. Our result showed that TP53 mutation was strongly correlated with poor MCL prognosis, although the total cases were small in the two investigated articles. This result could be influenced by different sensitivities of the testing methods and the small sample size. Thus, the gap between the pooled HRs of DLBCL and MCL should be further investigated.

The combined HR showed the prognostic significance of TP53 mutation in NHL, but some inconsistent results were found in our investigation. The correlation between TP53 mutation and prognosis was not statistically significant in eight studies because of the 95% CI of HRs crossing 1. A study implied that TP53 mutation does not exhibit an intergroup difference in T/NK cell lymphomas [11]. The combined HR of Burkitt lymphoma in subtype analysis was also not significant probably because of the insufficient number of samples and unified therapies. Different treatment regimens could significantly affect the prognosis of NHL, which showed remarkable heterogeneity among different subtypes. However, the studies included in our meta-analysis did not strictly treat patients with the unified therapy strategy, and the lymphoma subgroups were analyzed on the basis of few articles because of the clinical characteristics of the included studies. Thus, the investigation based on separate subgroup analyses and R-CHOP-treated NHLs should be improved.

In conclusion, this meta-analysis supports the prognostic value of TP53 mutation despite the limitations of our study. TP53 mutation is considered a prognostic indicator for NHL. Further studies on the prognostic value of single NHL subtypes and therapeutic effects should be conducted to verify our findings.

Supporting information

Acknowledgments

We would like to thank two reviewers for their constructive criticisms which have led to substantial improvements to the manuscript.

Author Contributions

  1. Conceptualization: JO.
  2. Data curation: PX XL.
  3. Formal analysis: PX.
  4. Funding acquisition: JO BC.
  5. Investigation: XL.
  6. Methodology: PX.
  7. Project administration: JO BC.
  8. Resources: PX XL.
  9. Software: XL.
  10. Supervision: JO BC.
  11. Validation: BC.
  12. Visualization: JO BC.
  13. Writing – original draft: PX XL.
  14. Writing – review & editing: JO BC.

References

  1. 1. Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2011;61(2):69–90. pmid:21296855
  2. 2. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin. 2016;66(1):7–30. pmid:26742998
  3. 3. A predictive model for aggressive non-Hodgkin's lymphoma. The International Non-Hodgkin's Lymphoma Prognostic Factors Project. The New England journal of medicine. 1993;329(14):987–94. pmid:8141877
  4. 4. Heselmeyer-Haddad K, Sommerfeld K, White NM, Chaudhri N, Morrison LE, Palanisamy N, et al. Genomic amplification of the human telomerase gene (TERC) in pap smears predicts the development of cervical cancer. The American journal of pathology. 2005;166(4):1229–38. pmid:15793301
  5. 5. Mega JL, Close SL, Wiviott SD, Shen L, Hockett RD, Brandt JT, et al. Cytochrome p-450 polymorphisms and response to clopidogrel. The New England journal of medicine. 2009;360(4):354–62. pmid:19106084
  6. 6. Fonseca R, Bergsagel PL, Drach J, Shaughnessy J, Gutierrez N, Stewart AK, et al. International Myeloma Working Group molecular classification of multiple myeloma: spotlight review. Leukemia. 2009;23(12):2210–21. pmid:19798094
  7. 7. Levine AJ. p53, the cellular gatekeeper for growth and division. Cell. 1997;88(3):323–31. pmid:9039259
  8. 8. Mihara M, Erster S, Zaika A, Petrenko O, Chittenden T, Pancoska P, et al. p53 has a direct apoptogenic role at the mitochondria. Mol Cell. 2003;11(3):577–90. pmid:12667443
  9. 9. Xu-Monette ZY, Medeiros LJ, Li Y, Orlowski RZ, Andreeff M, Bueso-Ramos CE, et al. Dysfunction of the TP53 tumor suppressor gene in lymphoid malignancies. Blood. 2012;119(16):3668–83. pmid:22275381
  10. 10. Dong HJ, Zhou LT, Fang C, Fan L, Zhu DX, Wang YH, et al. TP53 mutation is not an independent prognostic factor in patients with mantle cell lymphoma at advanced stage. Med Oncol. 2012;29(3):2166–73. pmid:22057359
  11. 11. Petit B, Leroy K, Kanavaros P, Boulland ML, Druet-Cabanac M, Haioun C, et al. Expression of p53 protein in T- and natural killer-cell lymphomas is associated with some clinicopathologic entities but rarely related to p53 mutations. Hum Pathol. 2001;32(2):196–204. pmid:11230707
  12. 12. Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25(9):603–5. pmid:20652370
  13. 13. Parmar MK, Torri V, Stewart L. Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Stat Med. 1998;17(24):2815–34. pmid:9921604
  14. 14. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557–60. pmid:12958120
  15. 15. Munch-Petersen HD, Asmar F, Dimopoulos K, Areskeviciute A, Brown P, Girkov MS, et al. TP53 hotspot mutations are predictive of survival in primary central nervous system lymphoma patients treated with combination chemotherapy. Acta Neuropathologica Communications. 2016;4.
  16. 16. Xu-Monette ZY, Wu L, Visco C, Tai YC, Tzankov A, Liu W-m, et al. Mutational profile and prognostic significance of TP53 in diffuse large B-cell lymphoma patients treated with R-CHOP: report from an International DLBCL Rituximab-CHOP Consortium Program Study. Blood. 2012;120(19):3986–96. pmid:22955915
  17. 17. Rossi D, Spina V, Deambrogi C, Rasi S, Laurenti L, Stamatopoulos K, et al. The genetics of Richter syndrome reveals disease heterogeneity and predicts survival after transformation. Blood. 2011;117(12):3391–401. pmid:21266718
  18. 18. Stefancikova L, Moulis M, Fabian P, Ravcukova B, Vasova I, Muzik J, et al. Loss of the p53 tumor suppressor activity is associated with negative prognosis of mantle cell lymphoma. International Journal of Oncology. 2010;36(3):699–706. pmid:20126990
  19. 19. O'Shea D, O'Riain C, Taylor C, Waters R, Carlotti E, Macdougall F, et al. The presence of TP53 mutation at diagnosis of follicular lymphoma identifies a high-risk group of patients with shortened time to disease progression and poorer overall survival. Blood. 2008;112(8):3126–9. pmid:18628487
  20. 20. Young KH, Leroy K, Moller MB, Colleoni GWB, Sanchez-Beato M, Kerbauy FR, et al. Structural profiles of TP53 gene mutations predict clinical outcome in diffuse large B-cell lymphoma: an international collaborative study. Blood. 2008;112(8):3088–98. pmid:18559976
  21. 21. Zainuddin N, Berglund M, Wanders A, Ren Z-P, Amini R-M, Lindell M, et al. TP53 mutations predict for poor survival in de novo diffuse large B-cell lymphoma of germinal center subtype. Leukemia Research. 2009;33(1):60–6. pmid:18706692
  22. 22. Young KH, Weisenburger DD, Dave BJ, Smith L, Sanger W, Iqbal J, et al. Mutations in the DNA-binding codons of TP53, which are associated with decreased expression of TRAILreceptor-2, predict for poor survival in diffuse large B-cell lymphoma. Blood. 2007;110(13):4396–405. pmid:17881637
  23. 23. Hiraga J, Kinoshita T, Ohno T, Mori N, Ohashi H, Fukami S, et al. Promoter hypermethylation of the DNA-repair gene O-6-Methylguanine-DNA methyltransferase and p53 mutation in diffuse large B-cell lymphoma. International Journal of Hematology. 2006;84(3):248–55. pmid:17050200
  24. 24. Hoshida Y, Hongyo T, Xu JX, Sasaki T, Tomita Y, Nomura T, et al. TP53 gene mutation, an unfavorable prognostic factor for malignant lymphomas in autoimmune diseases. Oncology. 2005;69(2):175–83. pmid:16131817
  25. 25. Namiki T, Sakashita A, Kobayashi H, Maseki N, Izumo T, Komada Y, et al. Clinical and genetic characteristics of Japanese Burkitt lymphomas with or without leukemic presentation. International Journal of Hematology. 2003;77(5):490–8. pmid:12841388
  26. 26. Bellido M, Capello D, Altes A, Estivill C, Gaidano G, Pujol R, et al. Bcl-6 and p53 mutations in lymphomas carrying the bcl-2/Jh rearrangement. Haematologica. 2002;87(9):908–17. pmid:12217802
  27. 27. Nakatsuka S, Hongyo T, Syaifudin M, Nomura T, Shingu N, Aozasa K. Mutations of p53, c-kit, K-ras, and beta-catenin gene in non-Hodgkin's lymphoma of adrenal gland. Japanese Journal of Cancer Research. 2002;93(3):267–74. pmid:11927008
  28. 28. Stokke T, Galteland E, Holte H, Smedshammer L, Suo ZH, Smeland EB, et al. Oncogenic aberrations in the p53 pathway are associated with a high S phase fraction and poor patient survival in B-cell non-Hodgkin's lymphoma. International Journal of Cancer. 2000;89(4):313–24. pmid:10956404
  29. 29. Gronbaek K, Moller PH, Nedergaard T, Thomsen K, Baadsgaard O, Hou-Jensen K, et al. Primary cutaneous B-cell lymphoma: a clinical, histological, phenotypic and genotypic study of 21 cases. British Journal of Dermatology. 2000;142(5):913–23. pmid:10809848
  30. 30. Marrogi AJ, Khan MA, Vonderheid EC, Wood GS, McBurney E. p53 tumor suppressor gene mutations in transformed cutaneous T-cell lymphoma: A study of 12 cases. Journal of Cutaneous Pathology. 1999;26(8):369–78. pmid:10551408
  31. 31. Baldini L, Guffanti A, Cro L, Fracchiolla NS, Colombi M, Motta M, et al. Poor prognosis in non-villous splenic marginal zone cell lymphoma is associated with p53 mutations. British Journal of Haematology. 1997;99(2):375–8. pmid:9375758
  32. 32. Baldini L, Fracchiolla NS, Cro LM, Trecca D, Romitti L, Polli E, et al. Frequent p53 gene involvement in splenic B-cell leukemia/lymphomas of possible marginal zone origin. Blood. 1994;84(1):270–8. pmid:8018922
  33. 33. Ichikawa A, Kinoshita T, Watanabe T, Kato H, Nagai H, Tsushita K, et al. Mutations of the p53 gene as a prognostic factor in aggressive B-cell lymphoma. New England Journal of Medicine. 1997;337(8):529–34. pmid:9262496
  34. 34. Marks DI, Vonderheid EC, Kurz BW, Bigler RD, Sinha K, Morgan DA, et al. Analysis of p53 and mdm-2 expression in 18 patients with Sezary syndrome. British Journal of Haematology. 1996;92(4):890–9. pmid:8616082
  35. 35. Preudhomme C, Dervite I, Wattel E, Vanrumbeke M, Flactif M, Lai JL, et al. Clinical significance of p53 mutations in newly diagnosed Burkitt's lymphoma and acute lymphoblastic leukemia: a report of 48 cases. J Clin Oncol. 1995;13(4):812–20. pmid:7707106
  36. 36. Cabanillas F, Pathak S, Grant G, Hagemeister FB, McLaughlin P, Swan F, et al. Refractoriness to chemotherapy and poor survival related to abnormalities of chromosomes 17 and 7 in lymphoma. Am J Med. 1989;87(2):167–72. pmid:2757057
  37. 37. Petitjean A, Mathe E, Kato S, Ishioka C, Tavtigian SV, Hainaut P, et al. Impact of mutant p53 functional properties on TP53 mutation patterns and tumor phenotype: lessons from recent developments in the IARC TP53 database. Hum Mutat. 2007;28(6):622–9. pmid:17311302
  38. 38. Joerger AC, Fersht AR. Structural biology of the tumor suppressor p53. Annu Rev Biochem. 2008;77:557–82. pmid:18410249
  39. 39. Lee MK, Teoh WW, Phang BH, Tong WM, Wang ZQ, Sabapathy K. Cell-type, dose, and mutation-type specificity dictate mutant p53 functions in vivo. Cancer Cell. 2012;22(6):751–64. pmid:23238012