- *Corresponding Author:
- Jiuwei Cui
Department of Oncology, Cancer Center, The First Affiliated Hospital of Jilin University, Changchun, Jilin Province 130021, China
E-mail: cuijw@jlu.edu.cn
This article was originally published in a special issue, “Drug Discovery and Repositioning Studies in Biopharmaceutical Sciences” |
Indian J Pharm Sci 2024:86(4) Spl Issue “326-333” |
This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms
Abstract
Ring finger protein 146, an E3 ubiquitin ligase, regulates breast cancer development, metastasis and drug resistance. E3 ubiquitin ligase is an indispensable class of enzymes in the ubiquitin-proteasome system, which can be divided into HECT E3s, U-box E3s and ring E3s. Genome-wide association analyses have revealed the association between the ring finger protein 146 rs2180341 single nucleotide polymorphism and breast cancer risk in Ashkenazi Jewish people but not in Southern Chinese individuals. Herein, A retrospective case-control study of 828 breast cancer patients and 905 healthy controls was conducted to examine this association in Northern Chinese. Deoxyribonucleic acid from peripheral blood was sequenced to determine genotypes. We analyzed the association of the ring finger protein 146 rs2180341 single nucleotide polymorphism with breast cancer risk using odds ratios with binary logistic regression and between the single nucleotide polymorphism and clinic pathological breast cancer characteristics using Pearson’s chi-square or Fisher’s exact tests. Survival analyses were performed using the Kaplan-Meier method. In the codominant model, the ring finger protein 146 rs2180341 single nucleotide polymorphism and breast cancer risk were correlated. Our results showed that, compared with individuals with the ring finger protein 146 rs2180341 AA genotype, those with the GG genotype had an odds ratio of 1.932 (95 % confidence interval, 1.320-2.829, p=0.001) for developing breast cancer. No significant associations were found between the single nucleotide polymorphism and clinical characteristics or disease-free or overall survival. In conclusion, this single nucleotide polymorphism is related to breast cancer susceptibility but not with breast cancer clinic pathological characteristics or prognosis in Northern Chinese individuals.
Keywords
Ring finger protein 146 rs2180341, single nucleotide polymorphism, breast cancer, metastasis, drug resistance
According to the International Agency for Research on Cancer, Breast Cancer (BC) has now surpassed lung cancer to become the world’s number one cancer[1,2]. In 2030, the incidence of BC in China is expected to reach 234 000 cases[3]. The Ring Finger Protein 146 (RNF146) rs2180341 Single Nucleotide Polymorphism (SNP) is the most common genetic variant and can be used to predict the risk and prognosis of tumors, providing a molecular basis for the occurrence and development of BC[4].
RNF146, also known as dactylidin, is located in 6q22.1-q22.33 and contains five exons[5]. RNF146 encodes an amino terminal ring finger (propyne (C3HC4) ring finger) of a ubiquitin protein ligase (E3) containing WWE and the N-terminal ring finger domain[6-8]. The Wnt/β-catenin signaling pathway is of vital importance in both embryo and organ development; however, it is abnormally activated in cancerous tissues[9-11]. RNF146 is genetically amplified in ovarian, breast and colorectal cancers and is regulated by the Wnt signaling pathway[12-15]. RNF146 binds to the Poly ADP-Ribose (PAR)- ribosylated axin through its PAR-binding domain in the WWE domain and exerts its role as an E3 ubiquitin ligase[16,17]. RNF146 can recruit E2 ubiquitin-conjugating enzymes, degrade axin and the β-catenin degradation complex and accumulate β-catenin in the cytoplasm, thereby activating the Wnt signaling pathway[18-20]. Additionally, RNF146 is predominantly involved in the metastasis, development, drug resistance and invasion of BC[21].
A previous study showed that the RNF146 rs2180341 SNP is related to proliferation, metastasis and drug resistance in BC. The association between RNF146 rs2180341 SNP and BC susceptibility was first observed in Ashkenazi Jews (AJ). The findings of Kirchhoff et al.[22], who performed a follow-up study with 1953 patients with BC and 1467 controls of European ancestry, further supported this. However, no relationship was observed in subsequent Indian[23,24] and Southern Chinese[25] population studies. To further investigate this, we analyzed the relation between the RNF146 rs2180341 SNP and the susceptibility and prognosis of BC in China[26].
Materials and Methods
Study design:
Choice and description of participants: The association of the RNF146 rs2180341 SNP with BC in a Northern Chinese population was investigated using a retrospective case-control study. From April 2013 to September 2016, 828 patients with BC and 905 age-matched healthy controls were enrolled at Jilin University First Affiliated Hospital (Changchun City, Jilin Province, China). A median follow-up time was 6.7 y. The features of patients are obtained from their records. A pathology diagnosis of early cancer in females was the inclusion criteria.
RNF146 rs2180341 SNP genotyping: Peripheral blood samples were extracted to obtain Deoxyribonucleic Acid (DNA), and genotypes were detected using a matrix-assisted laser desorption ionization-time of flight mass spectrometer (Agena, San Diego, California, United States of America (USA)). SNP genotyping without knowing the case status. 15 % of the samples were tested interactively and reproducibility was 99.7 %.
Statistical analysis:
Statistical Package for the Social Sciences (SPSS) and online SNP stats developed by Catala d’Oncologia Institute were used to analyze the risk of BC. Based on Odds Ratio (OR) and 95 % Confidence Interval (CI), RNF146 rs2180341 SNP was associated with BC risk, and was analyzed by binary logistic regression. Kaplan-Meier and univariate Cox models were used to analyze the effects of RNF146 rs2180341 SNP on Disease-Free Survival (DFS) and Overall Survival (OS). Statistical significance was set at p≤0.05 for all statistical tests, and all the tests were assumed to be two-sided.
Results and Discussion
All the controls first underwent a physical examination at our hospital and were confirmed to not have a familial history of cancer. The median age of the control group was 38 y (range of 32 y-53 y). The case group included 398 premenopausal and 430 postmenopausal, with a median age of 51 y (ranging from 44 y to 58 y old), among whom 32 patients had a family history of cancer. Among 828 cases of BC, 793 cases have invasive ductal carcinoma, and 35 cases have other diseases. A detailed description of the patient’s characteristics is provided in Table 1. Genotype distribution of the RNF146 rs2180341 SNP was not significantly different between the case and control groups (Table 2). Three genetic models showed that the SNP rs2180341 in RNF146 was associated with increased BC risk. Codominant genetic models had the lowest Akaike information criterion, which was used to select the optimal genetic model. Compared with AA, the BC of rs2180341 GG is 1.932 (95 % CI, 1.320-2.829, p=0.001). Compared with AA, the genotype of rs2180341 GA also increased the risk of BC (OR, 1.168; 95 % CI, 0.944-1.446, p=0.153). In the implicit model, compared with AA, the OR of rs2180341 GG to BC development is 1.810 (95 % CI, 1.250-2.621, p=0.002). In the dominance model, compared with AA, rs2180341 GG also increases the risk of BC (OR, 1.277; 95 % CI is 1.043-1.563, p=0.018). In the hyper dominant model, RNF146 rs2180341 was not associated with BC risk (Table 3 and fig. 1).
Characteristic | Cases no (%) |
---|---|
Age (years) | |
35 | 52 (6.28) |
>35 | 776 (93.72) |
Menstrual status | |
Premenopause | 398 (48.07) |
Postmenopause | 430 (51.93) |
Family history | |
Negative | 796 (96.14) |
Positive | 32 (3.86) |
Pathological type | |
Infiltrating ductal carcinoma | 793 (95.77) |
Other types | 35 (4.23) |
Histological grade | |
I | 31 (3.74) |
II | 511 (61.71) |
III | 286 (34.54) |
Tumor size | |
T1 | 422 (50.97) |
T2 | 365 (44.08) |
T3 | 27 (3.26) |
T4 | 14 (1.69) |
Lymph node | |
N0 | 396 (47.83) |
N1 | 285 (34.42) |
N2 | 101 (12.20) |
N3 | 46 (5.58) |
Lymphovascular invasion | |
Negative | 471 (56.88) |
Positive | 357 (43.12) |
Perineural invasion | |
Negative | 689 (83.21) |
Positive | 139 (16.79) |
Clinical stage | |
I | 243 (29.35) |
II | 415 (50.12) |
III | 159 (19.20) |
IV | 11 (1.33) |
Total | 828 (100.00) |
Table 1: Clinicopathological Characteristics
SNPs | Cases | Controls | ||||||
---|---|---|---|---|---|---|---|---|
1H0 | 1He | χ2 | p | 1H0 | 1He | χ2 | p | |
rs 2180341 | 0.3804 | 0.4152 | 5.8037 | 0.016 | 0.3856 | 0.3797 | 0.2248 | 0.6354 |
Note: (1H0): Observed heterozygote frequency and (1He): Expected heterozygote frequency
Table 2: Hardy-Weinberg Balance Test
SNP | Genotype | Model | Cases no (%) | Controls no (%) | OR (95 % CI) | p | AIC |
---|---|---|---|---|---|---|---|
rs 2180341 | AA | Codominant | 427 (51.57) | 500 (55.25) | 1.000 | 0.003 | 2183.1 |
GA | 315 (38.04) | 349 (38.56) | 1.168 (0.944-1.446) | 0.153 | |||
GG | 86 (10.39) | 56 (6.19) | 1.932 (1.320-2.829) | 0.001 | |||
AA | Dominant | 427 (51.57) | 500 (55.25) | 1.000 | 0.018 | 2187.5 | |
GA/GG | 401 (48.43) | 405 (44.75) | 1.277 (1.043-1.563) | ||||
AA/GA | Recessive | 742 (89.61) | 849 (93.81) | 1.000 | 0.002 | 2184 | |
GG | 86 (10.39) | 56 (6.19) | 1.810 (1.250-2.621) | ||||
AA/GG | Overdominant | 513 (61.96) | 556 (61.44) | 1.000 | 0.526 | 2193.9 | |
GA | 315 (38.04) | 349 (38.56) | 1.069 (0.869-1.315) | ||||
A | - | 1169 (70.59) | 1349 (74.53) | 1.000 | <0.001 | - | |
G | - | 487 (29.41) | 461 (25.47) | 1.334 (1.138-1.565) |
Table 3: Association between Hotair rs 2180341 Polymorphism and Bc Risk
Genotype distribution of the RNF146 rs2180341 SNP was not significantly different between the case and control groups (Table 4). Three genetic models showed that the SNP rs2180341 in RNF146 was associated with increased BC risk. Codominant genetic models had the lowest Akaike information criterion, which was used to select the optimal genetic model. Compared with AA, the BC of rs2180341 GG is 1.932 (95 % CI, 1.320-2.829, p=0.001). Compared with AA, the genotype of rs2180341 GA also increased the risk of BC (OR, 1.168; 95 % CI, 0.944-1.446, p=0.153). In the implicit model, compared with AA, the OR of rs2180341 GG to BC development is 1.810 (95 % CI, 1.250-2.621, p=0.002). In the dominance model, compared with AA, rs2180341 GG also increases the risk of BC (OR, 1.277; 95 % CI is 1.043-1.563, p=0.018). In the hyper dominant model, RNF146 rs2180341 was not associated with BC risk (Table 5).
Characteristic | Grouping | rs genotype 2180341 | χ2 | p | ||
---|---|---|---|---|---|---|
AA, n (%) | GA, n (%) | GG, n (%) | ||||
ER | Negative | 107 (25.06) | 81 (25.72) | 26 (30.23) | 4.975 | 0.547 |
<30 % | 29 (6.79) | 16 (5.08) | 9 (10.47) | |||
30 %-50 % | 21 (4.92) | 15 (4.76) | 3 (3.49) | |||
>50 % | 270 (63.23) | 203 (64.44) | 48 (55.81) | |||
PR | Negative | 170 (39.81) | 119 (37.78) | 40 (46.51) | 4.105 | 0.663 |
<30 % | 50 (11.71) | 40 (12.70) | 11 (12.79) | |||
30 %-50 % | 41 (9.60) | 33 (10.48) | 4 (4.65) | |||
>50 % | 166 (38.88) | 123 (39.04) | 31 (36.05) | |||
HER-2 | Negative | 286 (66.98) | 218 (69.21) | 59 (68.60) | 0.43 | 0.807 |
Positive | 141 (33.02) | 97 (30.79) | 27 (31.40) | |||
Ki-67 | <14 % | 73 (17.10) | 46 (14.60) | 12 (13.95) | 2.912 | 0.573 |
14 %-30 % | 96 (22.48) | 79 (25.08) | 16 (18.60) | |||
>30 % | 258 (60.42) | 190 (60.32) | 58 (67.45) | |||
Molecular type | Luminal A | 57 (13.35) | 38 (12.06) | 9 (10.47) | 1.925 | 0.926 |
Luminal B | 267 (62.53) | 201 (63.81) | 52 (60.47) | |||
HER2 | 52 (12.18) | 37 (11.75) | 14 (16.28) | |||
Triple negative | 51 (11.94) | 39 (12.38) | 11 (12.78) | |||
Lymphovascular invasion | Negative | 242 (56.67) | 174 (55.24) | 55 (63.95) | 2.108 | 0.349 |
Positive | 185 (43.33) | 141 (44.76) | 31 (36.05) | |||
Lymph node | N0 | 206 (48.24) | 146 (46.35) | 44 (51.16) | 8.503 | 0.204 |
N1 | 143 (33.49) | 114 (36.19) | 28 (32.56) | |||
N2 | 55 (12.88) | 41 (13.02) | 5 (5.81) | |||
N3 | 23 (5.39) | 14 (4.44) | 9 (10.47) | |||
Tumor size | T1 | 222 (51.99) | 159 (50.48) | 41 (47.67) | 7.826 | 0.251 |
T2 | 181 (42.39) | 146 (46.35) | 38 (44.19) | |||
T3 | 14 (3.28) | 9 (2.86) | 4 (4.65) | |||
T4 | 10 (2.34) | 1 (0.31) | 3 (3.49) | |||
Menstrual status | Premenopause | 198 (46.37) | 154 (48.89) | 46 (53.49) | 1.59 | 0.451 |
Postmenopause | 229 (53.63) | 161 (51.11) | 40 (46.51) | |||
Family history | Negative | 411 96.25 | 299 (94.92) | 86 (100.00) | 4.724 | 0.094 |
Positive | 16 (3.75) | 16 (5.08) | 0 (0.00) | |||
Pathological type | Infiltrating ductal carcinoma | 409 (95.78) | 299 (94.92) | 85 (98.84) | 2.56 | 0.278 |
Other types histological grade | 18 (4.22) | 16 (5.08) | 1 (1.16) | |||
Histological grade | I | 17 (3.98) | 13 (4.13) | 1 (1.16) | 3.097 | 0.542 |
II | 260 (60.89) | 200 (63.49) | 51 (59.30) | |||
III | 150 (35.13) | 102 (32.38) | 34 (39.54) | |||
Perineural invasion | Negative | 350 (81.97) | 266 (84.44) | 73 (84.88) | 0.988 | 0.61 |
Positive | 77 (18.03) | 49 (15.56) | 13 (15.12) | |||
Clinical stage | Stage I | 133 (31.15) | 84 (26.67) | 26 (30.23) | 4.254 | 0.642 |
Stage II | 204 (47.78) | 169 (53.65) | 42 (48.84) | |||
Stage III | 86 (20.14) | 57 (18.10) | 16 (18.60) | |||
Stage IV | 4 (0.93) | 5 (1.58) | 2 (2.33) | |||
Total | 427 (100.00) | 315 (100.00) | 86 (100.00) |
Table 4: Association between Rnf146 Rs2180341 Polymorphism and Bc Clinical Characteristics
Indicator | B | SE | Wald | Df | HR (95 % CI) | p | |
---|---|---|---|---|---|---|---|
DFS | AA | 0.691 | 2 | 0.708 | |||
GA | -0.074 | 0.213 | 0.119 | 1 | 0.929 (0.612-1.411) | 0.73 | |
GG | 0.176 | 0.293 | 0.363 | 1 | 1.193 (0.672-2.118) | 0.547 | |
OS | AA | 1.695 | 2 | 0.428 | |||
GA | 0.071 | 0.353 | 0.040 | 1 | 1.073 (0.538-2.143) | 0.841 | |
GG | 0.588 | 0.46 | 1.635 | 1 | 1.801 (0.731-4.436) | 0.201 |
Table 5: The Cox Model Result of Genotype
RNF146 is an E3 ubiquitin ligase that downregulates the expression of axin while also inducing the expression of Beta (β)-catenin and increasing its nuclear accumulation[27,28]. Studies confirm that when β-catenin enters the nucleus, it loses its function as a cell adhesion molecule, positively regulates the Wnt signaling pathway, and activates the proliferation, invasion and metastasis of BC[29]. rs2180341 (A>G) is in the intron region of RNF146 and its expression is increased in the GG genotype.
Previous studies that examined the association of the RNF146 rs2180341 SNP with BC susceptibility produced controversial results. In our study, we found that RNF146 rs2180341 SNP increased the risk of BC, which was consistent with the results of Gold et al.[18] for an AJ population and Kirchhoff et al.[22] for a non-AJ population with predominantly European ancestry. Other studies have found no relationship between ethnicity and birth rate among southern Chinese[25], European[30], Cypriot[31] or Chinese Singaporean[32] populations. Genetic and environmental variations may be responsible for the difference in results. The results of the present study, which focused on the Northern and Southern Chinese populations, indicate that unique genetic backgrounds and living environments with different geographical distributions in the same area may affect the occurrence and development of tumors. The median age of the Northern Chinese population was lower than that of the Southern Chinese population and the environment influenced individual genes. A comparison of the results from this study with previous studies is provided in Table 6.
Author | Date of publication | Ethnicity | Median age of case group | Number of cases | Number of controls | Source of control | Assay methods | OR (p) |
---|---|---|---|---|---|---|---|---|
Gold et al. | 2008 | AJ | 55 | 950 | 979 | Hospital | Taq man SNP genotyping | 1.412.9×10-8 |
Kirchhoff et al. | 2009 | AJ and European American (non-AJ) | _ | 1953 | 1467 | Population | Taq man SNP genotyping | 1.18, p=0.0083 |
Kirchhoff et al. | 2009 | AJ and European American (non-AJ) | _ | 1953 | 1467 | Population | Taq man SNP genotyping | 1.18, p=0.0083 |
Long et al. | 2010 | Southern Chinese | 49.3 and 53.9 | 6498 | 3999 | Population | Mass array system Taq man SNP genotyping | 0.94, p=0.13 |
Campa et al. | 2011 | BPC3 (83 % European descent and Latino) | 62.39 | 8576 | 11 892 | Population | Taq man SNP genotyping | 0.95, p=0.11 |
Loizidou et al. | 2011 | Cypriot population | _ | 1109 | 1177 | Population | Taq man SNP genotyping | 1.07, p=0.34 |
Kirchhoff et al. | 2012 | BCAC (88.9 % European and 9 % Asian) | 53.1 | 31 428 | 34 700 | Population | Taq man SNP genotyping | 1.03, p=0.031 |
Lee et al. | 2014 | Singapore Chinese | 54.9 | 411 | 1212 | Population | Mass array system | 1.09, p=0.365 |
Nagrani et al. | 2017 | Western Indian | 46 | 1204 | 1212 | Hospital | Taq man SNP genotyping | 0.95, p=0.408 |
Present study | 2021 | Northern Chinese | 51 | 828 | 905 | Hospital | Mass array system | 1.932, p=0.001 |
Table 6: Comparison of our Results and those of Previous Studies
Kirchhoff et al.[22] found that the RNF146 rs2180341 SNP increased the risk of ER-positive BC (OR, 1.35; 95 % CI, 1.20-1.51, p=2.2×10-5). In contrast, this study found no evidence of a similar relationship in the Northern Chinese population. Furthermore, no relationship was observed between the RNF146 rs2180341 SNP and other clinicopathological characteristics such as menstrual status, pathological type and family history[33].
BC was the first cancer associated with Wnt signaling, and RNF146-regulated activation of Wnt signaling is recognized as a key factor in metastasis, proliferation, drug resistance, immune microenvironment regulation and stem cell maintenance in BC[34-36]. However, we did not find any significant association between the RNF146 rs2180341 SNP and DFS, and OS of BC in this study. The rs2180341 GG genotype was associated with a relatively poor DFS and OS of BC. This may be owing to the short duration of follow-up and small sample size of individuals with the GG genotype. To address this limitation, a large number of individuals with the GG phenotype should be enrolled and studied in future studies.
The results of this study show that the RNF146 rs2180341 SNP increases the risk of BC in the Northern Chinese population and should be investigated in greater detail in the future. Owing to the differences in the living environments and genetic backgrounds of populations in different regions, indepth studies with large sample sizes are warranted in other regions.
Ethical approval:
The research was approved by the Ethics Committee of the First Affiliated Hospital of Jilin University (Approval No: 2014-031), which was conducted according to relevant guidelines and Helsiniki’s statement. All participants provided written informed consent.
Funding:
This study was financially supported by the Natural Science Foundation of Jilin Province (Grant No: 2020J053).
Conflict of interests:
The authors declared no conflict of interests.
References
- Liu J, Zhang W, Cai W, Chen Y, Cai X, Tang D, et al. Multi-omics analyses revealed GOLT1B as a potential prognostic gene in breast cancer probably regulating the immune microenvironment. Front Oncol 2022;11:805273.
[Crossref] [Google Scholar] [PubMed]
- Loibl S, André F, Bachelot T, Barrios CH, Bergh J, Burstein HJ, et al. Early breast cancer: ESMO clinical practice guideline for diagnosis, treatment and follow-up. Ann Oncol 2024;35(2):159-82.
- Curtit E, Pivot X, Henriques J, Paget-Bailly S, Fumoleau P, Rios M, et al. Assessment of the prognostic role of a 94-single nucleotide polymorphisms risk score in early breast cancer in the SIGNAL/PHARE prospective cohort: No correlation with clinico-pathological characteristics and outcomes. Breast Cancer Res 2017;19:1-9.
[Crossref] [Google Scholar] [PubMed]
- Von Rotz RC, Kins S, Hipfel R, von der Kammer H, Nitsch RM. The novel cytosolic ring finger protein dactylidin is up-regulated in brains of patients with Alzheimer's disease. Eur J Neurosci 2005;21(5):1289-98.
[Crossref] [Google Scholar] [PubMed]
- Gao Y, Song C, Hui L, Li CY, Wang J, Tian Y, et al. Overexpression of RNF146 in non-small cell lung cancer enhances proliferation and invasion of tumors through the Wnt/β-catenin signaling pathway. PloS One 2014;9(1):e85377.
[Crossref] [Google Scholar] [PubMed]
- Sharma A, Trivedi AK. Regulation of apoptosis by E3 ubiquitin ligases in ubiquitin proteasome system. Cell Biol Int 2020;44(3):721-34.
[Crossref] [Google Scholar] [PubMed]
- Chhabra S, Kumar Y, Thacker G, Kapoor I, Lochab S, Sanyal S, et al. E6AP inhibits G-CSFR turnover and functions by promoting its ubiquitin-dependent proteasome degradation. Biochim Biophys Acta Mol Cell Res 2017;1864(10):1545-53.
[Crossref] [Google Scholar] [PubMed]
- Peng K, Anmangandla A, Jana S, Jin Y, Lin H. Iso-ADP-ribose fluorescence polarization probe for the screening of RNF146 WWE domain inhibitors. ACS Chem Biol 2024;19:300-7.
- Thacker G, Mishra M, Sharma A, Singh AK, Sanyal S, Trivedi AK. E3 ligase SCFSKP2 ubiquitinates and degrades tumor suppressor C/EBPα in acute myeloid leukemia. Life Sci 2020;257:118041.
[Crossref] [Google Scholar] [PubMed]
- Wang Y, Dai J, Zeng Y, Guo J, Lan J. E3 ubiquitin ligases in breast cancer metastasis: A systematic review of pathogenic functions and clinical implications. Front Oncol 2021;11:752604.
[Crossref] [Google Scholar] [PubMed]
- Gui L, Ye Q, Yu L, Dou G, Zhou Y, Liu Y, et al. Bone-targeting peptide and RNF146 modified apoptotic extracellular vesicles alleviate osteoporosis. Int J Nanomed 2024;19:471-88.
[Crossref] [Google Scholar] [PubMed]
- Shen J, Yu Z, Li N. The E3 ubiquitin ligase RNF146 promotes colorectal cancer by activating the Wnt/β-catenin pathway via ubiquitination of Axin1. Biochem Biophys Res Commun 2018;503(2):991-7.
[Crossref] [Google Scholar] [PubMed]
- Menachem TD, Laitman Y, Kaufman B, Friedman E. The RNF146 and ECHDC1 genes as candidates for inherited breast and ovarian cancer in Jewish Ashkenazi women. Fam Cancer 2009;8:399-402.
[Crossref] [Google Scholar] [PubMed]
- Zhang Y, Liu S, Mickanin C, Feng Y, Charlat O, Michaud GA, et al. RNF146 is a poly (ADP-ribose)-directed E3 ligase that regulates axin degradation and Wnt signalling. Nat Cell Biol 2011;13(5):623-9.
[Crossref] [Google Scholar] [PubMed]
- Yarden RI, Papa MZ. BRCA1 at the crossroad of multiple cellular pathways: Approaches for therapeutic interventions. Mol Cancer Ther 2006;5(6):1396-404.
[Crossref] [Google Scholar] [PubMed]
- Liu X, Teng Y, Wu X, Li Z, Bao B, Liu Y, et al. The E3 ubiquitin ligase Cbl-b predicts favorable prognosis in breast cancer. Front Oncol 2020;10:695.
- Zhang Z, Samsa WE, Gong Z. NUDT16 regulates CtIP PARylation to dictate homologous recombination repair. Nucl Acids Res 2024;52(7):3761-77.
[Crossref] [Google Scholar] [PubMed]
- Gold B, Kirchhoff T, Stefanov S, Lautenberger J, Viale A, Garber J, et al. Genome-wide association study provides evidence for a breast cancer risk locus at 6q22. 33. Proc Natl Acad Sci 2008;105(11):4340-5.
[Crossref] [Google Scholar] [PubMed]
- Hou S, Zhang J, Jiang X, Yang Y, Shan B, Zhang M, et al. PARP5A and RNF146 phase separation restrains RIPK1-dependent necroptosis. Mol Cell 2024;84(5):938-54.
[Crossref] [Google Scholar] [PubMed]
- Wang Y, Zhu Y, Wang Y, Chang Y, Geng F, Ma M, et al. Proteolytic activation of angiomotin by DDI2 promotes angiogenesis. EMBO J 2023;42(15):e112900.
[Crossref] [Google Scholar] [PubMed]
- Sharma A, Thacker G, Mishra M, Singh AK, Upadhyay V, Sanyal S, et al. SOX4-mediated FBW7 transcriptional upregulation confers Tamoxifen resistance in ER+ breast cancers via GATA3 downregulation. Life Sci 2022;303:120682.
[Crossref] [Google Scholar] [PubMed]
- Kirchhoff T, Chen ZQ, Gold B, Pal P, Gaudet MM, Kosarin K, et al. The 6q22. 33 locus and breast cancer susceptibility. Cancer Epidemiol Biomarkers Prev 2009;18(9):2468-75.
[Crossref] [Google Scholar] [PubMed]
- Nagrani R, Mhatre S, Rajaraman P, Chatterjee N, Akbari MR, Boffetta P, et al. Association of Genome-Wide Association Study (GWAS) identified SNPs and risk of breast cancer in an Indian population. Sci Rep 2017;7(1):40963.
[Crossref] [Google Scholar] [PubMed]
- Long J, Shu XO, Cai Q, Gao YT, Zheng Y, Li G, et al. Evaluation of breast cancer susceptibility loci in Chinese women. Cancer Epidemiol Biomarkers Prev 2010;19(9):2357-65.
[Crossref] [Google Scholar] [PubMed]
- Campa D, Kaaks R, Le Marchand L, Haiman CA, Travis RC, Berg CD, et al. Interactions between genetic variants and breast cancer risk factors in the breast and prostate cancer cohort consortium. J Natl Cancer Inst 2011;103(16):1252-63.
[Crossref] [Google Scholar] [PubMed]
- Multi-omics analyses revealed GOLT1B as a potential prognostic gene in breast cancer probably regulating the immune microenvironment
- Asano Y, Matsumoto Y, Wada J, Rottapel R. E3-ubiquitin ligases and recent progress in osteoimmunology. Front Immunol 2023;14:1120710.
[Crossref] [Google Scholar] [PubMed]
- Ma Y, Huang X, Wang Y, Lei Y, Yu J, Yu S, et al. NNMT/1-MNA promote cell-cycle progression of breast cancer by targeting UBC12/Cullin-1-mediated degradation of P27 proteins. Adv Sci 2024;11(9):2305907.
[Crossref] [Google Scholar] [PubMed]
- Matsumoto Y, Rottapel R. PAR sylation-mediated ubiquitylation: Lessons from rare hereditary disease cherubism. Trends Mol Med 2023;29(5):390-405.
[Crossref] [Google Scholar] [PubMed]
- Loizidou MA, Hadjisavvas A, Ioannidis JP, Kyriacou K. Replication of genome-wide discovered breast cancer risk loci in the Cypriot population. Breast Cancer Res Treat 2011;128:267-72.
[Crossref] [Google Scholar] [PubMed]
- Lee CP, Irwanto A, Salim A, Yuan JM, Liu J, Koh WP, et al. Breast cancer risk assessment using genetic variants and risk factors in a Singapore Chinese population. Breast Cancer Res 2014;16:1-3.
[Crossref] [Google Scholar] [PubMed]
- Ferrer G, Montserrat E. Critical molecular pathways in CLL therapy. Mol Med 2018;24:1-9.
[Crossref] [Google Scholar] [PubMed]
- Zhang Y, Kou C, Jia L, Gao Y, Li X, Wu H, et al. Association between the CASC16 rs4784227 polymorphism and breast cancer risk and prognosis in a northeast Chinese Han population. PeerJ 2022;10:e14462.
[Crossref] [Google Scholar] [PubMed]
- Jerusalem G, Park YH, Yamashita T, Hurvitz SA, Modi S, Andre F, et al. Trastuzumab deruxtecan in HER2-positive metastatic breast cancer patients with brain metastases: A DESTINY-Breast01 subgroup analysis. Cancer Discov 2022;12(12):2754-62.
[Crossref] [Google Scholar] [PubMed]
- Yan L, Wu M, Wang T, Yuan H, Zhang X, Zhang H, et al. Breast cancer stem cells secrete MIF to mediate tumor metabolic reprogramming that drives immune evasion. Cancer Res 2024.
[Crossref] [Google Scholar] [PubMed]
- Xu X, Zhang M, Xu F, Jiang S. Wnt signaling in breast cancer: Biological mechanisms, challenges and opportunities. Mol Cancer 2020;19(1):165.
[Crossref] [Google Scholar] [PubMed]