Mutation Frequencies in Endometrial Cancer Patients of Different Ethnicities and Tumor Grades: An Analytical Study

Mutation Frequencies in Endometrial Cancer Patients of Different Ethnicities and Tumor Grades: An Analytical Study

Originally Published in the Saudi Journal of Medicine and Medical Sciences, 7(1):16-21.


Background: Endometrial carcinoma is a predominant health problem for women worldwide. However, there is a lack of data on genetic mutation frequencies in endometrial cancer patients of different ethnicities and tumor grades.

Objective: The objective of this study is to provide data regarding mutation frequencies in endometrial cancer patients of different ethnic groups and tumor grades by analyzing large-scale cancer genomic datasets of a database.

Materials and Methods: The following databases of cBioPortal were explored for possible mutation frequency variations in endometrial cancer patients: the Uterine Corpus Endometrial Carcinoma (TCGA, PanCancer Atlas) database for ethnicity‑based studies; the Uterine Corpus Endometrial Carcinoma (TCGA, Nature 2013) database for tumor grade‑based study; and GDC Data Portal database for calculating survival rates using the Kaplan–Meier method.

Results: PTEN mutation frequency was almost identical in all ethnic groups studied (White, Black/African American, Asian, Native Hawaiian or other Pacific Islander, and American Indian or Asian Native). PIK3CA and ARID1A mutation frequencies were higher in White and Asian patients compared with other ethnicities; TP53 and FAT1 mutation frequencies were higher in Black/African Americans; and CTNNB1 and RYR2 mutation frequencies were higher Native Hawaiians or Asian Natives. TTN mutation frequency was lower in Asian patients. With regards to mutation frequencies at different tumor stages, in all genes, >50% of the mutations occurred during the first stage, except in TP53 and POLQ. In terms of prognosis in endometrial cancer considering the 10 most frequently mutated genes, PIK3CA and ARID1A mutations were correlated with good prognosis, whereas TP53 and PIK3R1 mutations were correlated with poor prognosis; mutations in all other genes did not show significant differences.

Conclusion: This study revealed a new mutation frequency profile for different ethnicities and tumor grades in endometrial cancer patients. However, because this is a retrospective study, future prospective studies should be conducted including large sample sizes and more controlled measurements.



Endometrial cancer is the most common gynecological cancer in the United States. According to the American Cancer Society, in 2018, there would be 63,230 new cases of  endometrial cancer, and about 11,350 patients will  die from this cancer.[1,2] In fact, endometrial cancer is a predominant health problem for women worldwide.[3] In women from developed countries, endometrial cancer is usually detected after the age of 60 years.[4] Nearly 90% of the diagnosed cases are sporadic, while 10% are attributed to genetic factors.[5]

Endometrial cancer is a multifactorial disease. Obesity and long‑term therapeutic administration of estrogen are the most common risk factors, while pathological production of estrogen has also found to be associated.[6‑9] In addition, nulliparity and infertility are among factors that increase the risk of endometrial cancer.[10]

Endometrial cancer is classified into Type I or Type II, based on clinical and pathological differences. Type I endometrial cancer accounts for 80% of  all cases and    is linked to excess estrogen exposure. It is associated with  low‑grade  tumors  and  has  a  good  prognosis.[11,12] Type II accounts for 20% of all new cases of endometrial cancer and is a highly differentiated papillary serous‑cell carcinoma that is not linked to estrogen exposure. It is commonly detected at later stages and is associated with poor prognosis.[11]

Genetic mutations in cancers have been shown to  be influenced by patients’ ethnicity and grade of tumor.[13‑20] These variations in mutations affect therapeutic regimes.[21‑24]   Conceptually,  precision  medicine  requires knowledge of the exact mutation present in each patient along with the tumor stage. Currently, there is a lack of data regarding genetic mutation frequencies (GMFs) in endometrial cancer patients of different ethnic groups and tumor grades. To obtain significant data regarding any such differences in mutation frequencies, a large‑scale, multicenter study that includes endometrial cancer patients with different ethnicities and tumor stages is required. However, such studies are difficult to conduct and require concerted efforts at several levels. Nonetheless, an analytical study of large‑scale endometrial cancer genomics datasets can provide initial data on GMFs of different ethnic groups and tumor grades. Accordingly, this study was conducted using cBioPortal, an open source database of large‑scale cancer genomics data sets, to search for variability in genetic mutations of endometrial cancer in different ethnic groups and stages.


Data collection

Data were retrieved from cBioPortal (, an open access platform with data distribution under the terms of CC‑BY‑4.0 license, to assess the variability in genetic mutations among endometrial cancer patients. After a preliminary analysis of the database, the author searched for the following genes that displayed differences in mutation frequencies across ethnic groups and tumor grades: PTEN, PIK3CA, TTN, TP53, PIK3R1, KMT2D, CTNNB1, CTNND1, USH2A, DMD, KRAS, MACF1, FAT4, FAT1, MTOR, MUC16, CTCF,  RYR2,  ZFHX3,  CSMD3,  MUC5B, OBSCN,

SYNE1, CHD4, FLG, and ZFHX4. The ethnic groups included in the study were White, Black/African American, Asian, Native Hawaiian or other Pacific Islanders and American Indian or Asian Native. A preliminary search on the database showed that the following genes had significant mutation frequencies at different stages of endometrial cancer: CTNNB1, PTEN, ARID1A, KRAS, PIK3CA, PIK3R1, ZFHX3, FAT4, DMD, FAT1, MUC5B, ERCC6 L2, RYR2, CSMD3, NEB, PPP2R1A, TP53, and POLQ. Stages I–IV of endometrial cancer were compared to determine frequency differences. The author also tested the prognostic potential of 10 most frequently mutated genes, namely, PTEN, KRAS, TNN, CTNNB1, MUC16, CSMD3, PIK3CA, ARID1A, TP53 and PIK3R1, to assess the overall survival rates for patients with endometrial carcinoma.

Data analysis

To assess the GMF of different ethnicities, the Uterine Corpus Endometrial Carcinoma (TCGA, PanCancer Atlas) database was used through cBioPortal.[25] For GMFs of different grades, information was obtained from the Uterine Corpus Endometrial Carcinoma (TCGA, Nature 2013) database.[26] Finally, the Kaplan–Meier method was used to determine the survival rates of endometrial cancer patients in the GDC Data Portal database of cBioPortal.[27] The frequencies of genetic mutations were then normalized to the total patient number in each group using Microsoft Excel for Mac 2011. Using Prism 7 for Mac software (GraphPad Software, La Jolla, CA, USA), a heat plot of the genes most frequently mutated was generated for each ethnic group and grouped for analysis of different tumor stages.

Ethical issues

This work used anonymous, open‑access data, and thus did not involve any personal information of individuals.


Mutation frequency by ethnicity

To explore the variation in the frequency of endometrial cancer‑associated genetic mutations among different ethnicities, a hotspot model was used. As shown in Figure 1, there was a clear variation in the GFM between individual genes. The PTEN gene showed nearly identical mutation frequencies in White, Asian and American Indian or Asian Native endometrial cancer patients, but Black/African American patients possessed a lower mutation frequency. PIK3CA displayed high mutation frequency in Asians compared with other ethnicities. However, mutations were less frequent in Asians compared to other ethnic groups. CTNNB1 and RYR1 mutation were found more frequently in Native Hawaiian or other Pacific Islanders compared with other ethnic groups. FAT1 exhibited a high mutation frequency in Black/African American and Asian populations; FAT4 mutations were more frequent in Asians; MUC5B mutations occurred more frequent in American Indian or Asian Native; while ZFHX4 and FLG were more frequently mutated in Asians. TP53 and RYR2 mutation frequencies were very high in Black/African American and Native Hawaiian or Other Pacific Islander, respectively, compared with other ethnicities. TNN mutation frequencies were high in all ethnicities, except among Asian patients, in whom it was very low.

Figure 1

Figure 1: Genetic mutation frequency of selected genes for each ethnicity (green = low genetic mutation frequency; black = moderate genetic mutation frequency; dark red to light red = high to very high genetic mutation frequency).

Mutation frequency by endometrial carcinoma stage

To study the distinct mutation frequencies in each stage of endometrial cancer, the author compared the GMFs of 18 genes that were found to be most commonly mutated in endometrial cancer patients [Figure 2]. All genes, except TP53 and POLQ, showed high mutation frequencies in the first stage of the cancer. The PTEN, PPP2R1A and ARID1A genes were less frequently mutated in the second stage of cancer than the other genes studied. The third stage of the cancer exhibited the most frequent genetic mutations, with TP53, POLQ, PPP2R1A, NEB, RYR2 and ERCC6 L2 displaying the highest mutation frequencies. In the fourth stage, mutation frequencies were much lower than that in the other stages of endometrial cancer.

figure 2

Figure 2: Genetic mutation frequencies in selected genes according to different stages of endometrial cancer

Survival rates

With regards to the potential prognostic value of the mutated genes in endometrial cancer, it was found that patients with mutations in PIK3CA and ARID1A have  a significantly better prognosis than patients with the wild‑type gene (P < 0.05). Similarly, patients with mutations in PTEN, KRAS, TNN, CTNNB1 and MUC16 had a better prognosis than patients with the wild‑type genes [Figure 3], although this finding is not significant (P > 0.05). However, patients with a mutation in CSMD3 did not have any prognostic difference from patients with its wild‑type counterpart. In contrast, patients with the wild‑type TP53 and PIK3R1 genes displayed a better prognosis relative to patients with mutations in these genes.

figure 3

Figure 3: Kaplan–Meier survival curves demonstrating correlations between mutated (red) and wild‑type (blue) gene expression and survival rates (*indicates significant difference)


Genetic mutations in cancers are likely to be influenced by patients’ ethnicity and grade of tumor.[13‑20] However, there is a lack of knowledge on GMFs in endometrial cancer patients of different ethnic groups. The current analytical study found that GMFs in endometrial cancer patients vary by ethnicity. Variations in GMFs can help understand biological differences between ethnic groups, which in turn could be used for targeted therapy. Further, this study also demonstrates altered activity of certain genes during different cancer stages.

In African Americans with prostate cancer, recurrent loss‑of‑function mutations has been shown in the ERF gene, which is a tumor suppressor gene.[28] Increased mutations in KRAS have been reported in African Americans with colon cancer compared with Caucasians patients.[29] In non‑small cell lung cancer, Black women have been found to be at a higher risk of EGFR mutations than White women.[30] BRCA1 mutations in breast cancer patients have been shown to be more prevalent in Hispanics compared with other ethnicities.[15] Further, BRCA1 exon 2 mutations are more frequent in Ashkenazi Jewish women relative to Caucasians.[31] Such differences in GMFs between women of different ethnicities were also observed in several other studies.[32‑34] These and the current study results collectively show that genetic mutations vary by ethnicity, and thus could potentially be used to determine and administer precise therapy for a subset of patients within an ethnic group. Therefore, a larger study, including more ethnic groups, could potentially aid in improving endometrial cancer diagnosis and therapy.

The current study also demonstrated differences in the mutation frequency between endometrial cancer stages, which could potentially be used to better understand the progression of cancer and to monitor its treatment. The frequent  mutation of PTEN in early‑stage  endometrial cancer has also been suggested previously.[35] However,  in that study, endometrial carcinoma PTEN mutations were compared with that of endometrial hyperplasia, thereby limiting the validity of  the finding. Therefore, a large population study should be conducted to elucidate the genetic mutation patterns in each stage of endometrial cancer. This would further contribute to the implementation of precise therapy. Previously, in studies of other cancers, GMFs have been found to vary in different stages of cancer.[36‑40] However, to the best of the author’s knowledge, this is the first study demonstrating GMF variation in different stages of endometrial carcinoma.

Endometrial carcinoma is characterized by mutations in many genes, with microsatellite instability genes PTEN, KRAS, PIK3CA and β‑catenin most commonly involved.[19,41‑43] The  mechanisms that initiate and drive endometrial cancer have been explored. Mutations in the pro‑survival genes, such as KRAS, Akt, mTOR and β‑catenin, or pro‑apoptotic genes, such as PTEN and p53, have all exhibited a role in the pathological findings of this

cancer.[44‑46] Understanding the molecular background of uterine cancers could help in determining future therapy for endometrial cancer.[44‑46] Small molecules capable of targeting and inhibiting these genes have been found to potentially reduce mortality rates of endometrial cancer patients.[45] Further, inhibitors can be combined with hormonal or cytotoxic agents, thereby focusing on multiple targets.[46] For example, the PI3K/AKT/mTOR pathways have been used for uterine cancer therapy.[12,47] In fact, the effectiveness of mTOR inhibitors such as AZD8055, OSI‑027 and INK128 for treating endometrial cancer are being evaluated in clinical trials.[48] Other inhibitors have also been tested in vivo but have not yet been introduced into trials.[46]

The results of this study’s survival rates of patients could potentially be used as prognostic markers for clinical outcome. This study found that mutations in TP53 and PIK3R1 are correlated with poor prognosis in endometrial cancer. These results conform to the findings of previous study results on other cancers. For example, TP53 has been shown to correlate with poor prognosis in breast cancer,[49,50] lymphoma,[51] colon cancer,[52] lung cancer[53] and leukemia,[54] while PIK3R1 is associated with poor prognosis  in  glioblastoma.[55]   In  patients  with  late‑stage endometrial cancer, poor prognosis may be related to the observed increased frequency of TP53 mutations.

It should be noted that because the current study is a retrospective study that is more exploratory and hypothesis generating in nature, its findings cannot be considered conclusive. Therefore, future work should comprise large sample sizes, including more ethnic groups such as Arabs from different countries, and long‑term follow‑up, including detailed information on patient body weight, morbidity, mortality and treatment regimens administered.


The findings of the current retrospective study illustrate a new GMF profile for endometrial cancer patients of different ethnicities. Further, this study demonstrates the altered activity of certain genes during different cancer stages and that the survival rates of patients with endometrial carcinoma could be predicted using the set of genes investigated. Nonetheless, to validate the findings of this study, future prospective studies should be conducted with large sample sizes, more diverse ethnic groups and long‑term follow‑up.



1. American Cancer Society. Key Statistics for Endometrial Cancer USA; 2017. Available from: endometrial‑cancer/about/key‑statistics.html. [Last accessed on 2018 Jul 14].
2. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin 2018;68:7‑30.
3. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018;68:394‑424.
4. Jemal A, Siegel R, Ward E, Hao Y, Xu J, Murray T, et al. Cancer statistics, 2008. CA Cancer J Clin 2008;58:71‑96.
5. Doll A, Abal M, Rigau M, Monge M, Gonzalez M, Demajo S, et al. Novel molecular profiles of endometrial cancer‑new light through old windows. J Steroid Biochem Mol Biol 2008;108:221‑9.
6. von Gruenigen VE, Tian C, Frasure H, Waggoner S, Keys H, Barakat RR, et al. Treatment effects, disease recurrence, and survival in obese women with early endometrial carcinoma: A gynecologic oncology group study. Cancer 2006;107:2786‑91.
7. Onstad MA, Schmandt RE, Lu KH. Addressing the role of obesity in endometrial cancer risk, prevention, and treatment. J Clin Oncol 2016;34:4225‑30.
8. Leslie KK, Thiel KW, Goodheart MJ, De Geest K, Jia Y, Yang S. Endometrial cancer. Obstet Gynecol Clin North Am 2012;39:255‑68.
9. Ziel HK. Estrogen’s role in endometrial cancer. Obstet Gynecol 1982;60:509‑15.
10. Yang HP, Cook LS, Weiderpass E, Adami HO, Anderson KE, Cai H, et al. Infertility and incident endometrial cancer risk: A pooled analysis from the epidemiology of endometrial cancer consortium (E2C2). Br J Cancer 2015;112:925‑33.
11. Bokhman JV. Two pathogenetic types of endometrial carcinoma. Gynecol Oncol 1983;15:10‑7.
12. Hecht JL, Mutter GL. Molecular and pathologic aspects of endometrial carcinogenesis. J Clin Oncol 2006;24:4783‑91.
13. Tomlinson IP, Webb E, Carvajal‑Carmona L, Broderick P, Howarth K, Pittman AM, et al. A genome‑wide association study identifies colorectal cancer susceptibility loci on chromosomes 10p14 and 8q23.3. Nat Genet 2008;40:623‑30.
14. Tenesa A, Farrington SM, Prendergast JG, Porteous ME, Walker M, Haq N, et al. Genome‑wide association scan identifies a colorectal cancer susceptibility locus on 11q23 and replicates risk loci at 8q24 and 18q21. Nat Genet 2008;40:631‑7.
15. John EM, Miron A, Gong G, Phipps AI, Felberg A, Li FP, et al. Prevalence of pathogenic BRCA1 mutation carriers in 5 US racial/ethnic groups. JAMA 2007;298:2869‑76.
16. Hall MJ, Reid JE, Burbidge LA, Pruss D, Deffenbaugh AM, Frye C, et al. BRCA1 and BRCA2 mutations in women of different ethnicities undergoing testing for hereditary breast‑ovarian cancer. Cancer 2009;115:2222‑33.
17. van ‘t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002;415:530‑6.
18. Gamallo C, Palacios J, Moreno G, Calvo de Mora J, Suárez A, Armas A, et al. Beta‑catenin expression pattern in stage I and II ovarian carcinomas: Relationship with beta‑catenin gene mutations, clinicopathological features, and clinical outcome. Am J Pathol 1999;155:527‑36.
19. Maxwell GL, Risinger JI, Gumbs C, Shaw H, Bentley RC, Barrett JC, et al. Mutation of the PTEN tumor suppressor gene in endometrial hyperplasias. Cancer Res 1998;58:2500‑3.
20. Bookstein R, MacGrogan D, Hilsenbeck SG, Sharkey F, Allred DC. p53 is mutated in a subset of advanced‑stage prostate cancers. Cancer Res 1993;53:3369‑73.
21. Pao W, Girard N. New driver mutations in non‑small‑cell lung cancer. Lancet Oncol 2011;12:175‑80.
22. Aas T, Børresen AL, Geisler S, Smith‑Sørensen B, Johnsen H, Varhaug JE, et al. Specific P53 mutations are associated with de novo resistance to doxorubicin in breast cancer patients. Nat Med 1996;2:811‑4.
23. Burrell RA, McGranahan N, Bartek J, Swanton C. The causes and consequences of genetic heterogeneity in cancer evolution. Nature 2013;501:338‑45.
24. Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA Jr., Kinzler KW, et al. Cancer genome landscapes. Science 2013;339:1546‑58.
25. Cancer Genome Atlas Research Network, Weinstein JN, Collisson EA, Mills GB, Shaw KR, Ozenberger BA, et al. The cancer genome atlas pan‑cancer analysis project. Nat Genet 2013;45:1113‑20.
26. Cancer Genome Atlas Research Network, Kandoth C, Schultz N, Cherniack AD, Akbani R, Liu Y, et al. Integrated genomic characterization of endometrial carcinoma. Nature 2013;497:67‑73.
27. NIH National Cancer Institute. Harmonized Datasets – Genomic Data Commons Genomic Data Commons Data Portal. Available from: [Last accessed on 2018 Jul 20].
28. Huang FW, Mosquera JM, Garofalo A, Oh C, Baco M, Amin‑Mansour A, et al. Exome sequencing of African‑American prostate cancer reveals loss‑of‑function ERF mutations. Cancer Discov 2017;7:973‑83.
29. Staudacher JJ, Yazici C, Bul V, Zeidan J, Khalid A, Xia Y, et al. Increased frequency of KRAS mutations in African Americans compared with caucasians in sporadic colorectal cancer. Clin Transl Gastroenterol 2017;8:e124.
30. Bollig‑Fischer A, Chen W, Gadgeel SM, Wenzlaff AS, Cote ML, Schwartz AG, et al. Racial diversity of actionable mutations in non‑small cell lung cancer. J Thorac Oncol 2015;10:250‑5.
31. Bayraktar S, Jackson M, Gutierrez‑Barrera AM, Liu D, Meric‑Bernstam F, Brandt A, et al. Genotype‑phenotype correlations by ethnicity and mutation location in BRCA mutation carriers. Breast J 2015;21:260‑7.
32. Kytola V, Topaloglu U, Miller LD, Bitting RL, Goodman MM, D Agostino RB Jr., et al. Mutational landscapes of smoking‑related cancers in caucasians and African Americans: Precision oncology perspectives at wake forest baptist comprehensive cancer center. Theranostics 2017;7:2914‑23.
33. Nahar R, Zhai W, Zhang T, Takano A, Khng AJ, Lee YY, et al. Elucidating the genomic architecture of asian EGFR‑mutant lung adenocarcinoma through multi‑region exome sequencing. Nat Commun 2018;9:216.
34. Jia F, Teer JK, Knepper TC, Lee JK, Zhou HH, He YJ, et al. Discordance of somatic mutations between asian and caucasian patient populations with gastric cancer. Mol Diagn Ther 2017;21:179‑85.
35. Sun H, Enomoto T, Fujita M, Wada H, Yoshino K, Ozaki K, et al. Mutational analysis of the PTEN gene in endometrial carcinoma and hyperplasia. Am J Clin Pathol 2001;115:32‑8.
36. Li X. Dynamic changes of driver genes’ mutations across clinical stages in nine cancer types. Cancer Med 2016;5:1556‑65.
37. Cho J, Choi SM, Lee J, Lee CH, Lee SM, Yim JJ, et al. The association of EGFR mutations with stage at diagnosis in lung adenocarcinomas. PLoS One 2016;11:e0166821.
38. Li Y, Wang X, Vural S, Mishra NK, Cowan KH, Guda C, et al. Exome analysis reveals differentially mutated gene signatures of stage, grade and subtype in breast cancers. PLoS One 2015;10:e0119383.
39. Charlton ME, Kahl AR, Greenbaum AA, Karlitz JJ, Lin C, Lynch CF, et al. KRAS testing, tumor location, and survival in patients with stage IV colorectal cancer: SEER 2010‑2013. J Natl Compr Canc Netw 2017;15:1484‑93.
40. Taieb J, Le Malicot K, Shi Q, Penault‑Llorca F, Bouché O, Tabernero J, et al. Prognostic value of BRAF and KRAS Mutations in MSI and MSS stage III colon cancer. J Natl Cancer Inst 2017;109(50):djw272.
41. Basil JB, Goodfellow PJ, Rader JS, Mutch DG, Herzog TJ. Clinical significance of microsatellite instability in endometrial carcinoma. Cancer 2000;89:1758‑64.
42. Lax SF, Kendall B, Tashiro H, Slebos RJ, Hedrick L. The frequency of p53, K‑ras mutations, and microsatellite instability differs in uterine endometrioid and serous carcinoma: Evidence of distinct molecular genetic pathways. Cancer 2000;88:814‑24.
43. O’Hara AJ, Bell DW. The genomics and genetics of endometrial cancer. Adv Genomics Genet 2012;2012:33‑47.
44. Gadducci A, Tana R, Cosio S, Fanucchi A, Genazzani AR. Molecular target therapies in endometrial cancer: From the basic research to the clinic. Gynecol Endocrinol 2008;24:239‑49.
45. Dong P, Kaneuchi M, Konno Y, Watari H, Sudo S, Sakuragi N, et al. Emerging therapeutic biomarkers in endometrial cancer. Biomed Res Int 2013;2013:130362.
46. Westin SN, Broaddus RR. Personalized therapy in endometrial cancer: Challenges and opportunities. Cancer Biol Ther 2012;13:1‑3.
47. Bansal N, Yendluri V, Wenham RM. The molecular biology of endometrial cancers and the implications for pathogenesis, classification, and targeted therapies. Cancer Control 2009;16:8‑13.
48. Slomovitz BM, Coleman RL. The PI3K/AKT/mTOR pathway as a therapeutic target in endometrial cancer. Clin Cancer Res 2012;18:5856‑64.
49. Dobes P, Podhorec J, Coufal O, Jureckova A, Petrakova K, Vojtesek B, et al. Influence of mutation type on prognostic and predictive values of TP53 status in primary breast cancer patients. Oncol Rep 2014;32:1695‑702.
50. Silwal‑Pandit L, Vollan HK, Chin SF, Rueda OM, McKinney S, Osako T, et al. TP53 mutation spectrum in breast cancer is subtype specific and has distinct prognostic relevance. Clin Cancer Res 2014;20:3569‑80.
51. Munch‑Petersen HD, Asmar F, Dimopoulos K, Areškevičiūtė 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 Neuropathol Commun 2016;4:40.
52. Conlin A, Smith G, Carey FA, Wolf CR, Steele RJ. The prognostic significance of K‑ras, p53, and APC mutations in colorectal carcinoma. Gut 2005;54:1283‑6.
53. Mitsudomi T, Hamajima N, Ogawa M, Takahashi T. Prognostic significance of p53 alterations in patients with non‑small cell lung cancer: A meta‑analysis. Clin Cancer Res 2000;6:4055‑63.
54. Drach J, Ackermann J, Fritz E, Krömer E, Schuster R, Gisslinger H, et al. Presence of a p53 gene deletion in patients with multiple myeloma predicts for short survival after conventional‑dose chemotherapy. Blood 1998;92:802‑9.
55. Otani Y, Ishida J, Kurozumi K, Oka T, Shimizu T, Tomita Y, et al. PIK3R1Met326Ile germline mutation correlates with cysteine‑rich protein 61 expression and poor prognosis in glioblastoma. Sci Rep 2017;7:7391.

Original article: Althubiti MA. Mutation frequencies in endometrial cancer patients of different ethnicities and tumor grades: An analytical study. Saudi journal of medicine & medical sciences. 2019 Jan;7(1):16.

Share this post