Genetics risk assessment of PALB2 polymorphism (rs249954 and rs152451) with breast cancer susceptibility among the Pashtun population of Khyber Pakhtunkhwa, Pakistan

Genetics risk assessment of PALB2 polymorphism (rs249954 and rs152451) with breast cancer susceptibility among the Pashtun population of Khyber Pakhtunkhwa, Pakistan | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Genetics risk assessment of PALB2 polymorphism (rs249954 and rs152451) with breast cancer susceptibility among the Pashtun population of Khyber Pakhtunkhwa, Pakistan Sohni Gul, Najeeb Ullah Khan, Hamza Khan, Mikhlid H. Almutairi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4160569/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The partner and localizer of BRCA2 ( PALB2 ) gene play an important role in DNA damage repair and control of many biological processes. The occurrence of specific genetic variations, known as single nucleotide polymorphisms (SNPs), in the PALB2 gene has been identified as a factor contributing to an increased susceptibility to breast cancer. The SNPs in PALB2 (rs249954 and rs152451) are identified and associated with breast cancer risk, however its role remains unknown in the Pashtun ethnic group, making it necessary to explore in this population. This case-controls study included 100 breast cancer patients and 100 healthy controls. The SNPs genotyping was performed using amplification-refractory mutation system-polymerase chain reaction (ARMS-PCR). The statistical analysis revealed a significant association between the risk allele of rs249954 and an elevated breast cancer risk (P = 0.0001), while rs152451 did not exhibit a significant association (P = 0.07). Heterozygous genotype of rs249954 was linked to increased breast cancer risk (P = 0.0001), whereas rs152451 did not show a significant association (P = 0.08). Mutant genotypes of both the SNPs correlated positively with breast cancer risk (P = 0.002, P = 0.042). Additionally, rs249954 exhibited significant association with Nodal status (P=0.01), Metastasis (P=0.01) and PR status (P=0.01). While PALB2 (rs142451) failed to exhibit significant association with any of the selected demographic and clinical parameters. In conclusion, the risk allele and both the heterozygous and homozygous genotypes of rs249954 were associated with an increased risk of breast cancer, whereas only homozygous mutant genotype of rs152451 exhibited significant association. However, further studies with larger datasets and comprehensive genomic analysis are necessary to validate these findings and explore associations with other relevant SNPs. PALB2 gene single nucleotide polymorphism breast cancer risk Figures Figure 1 Figure 2 Introduction Breast cancer, a globally pervasive disease, is characterized by abnormal cell growth in the breast [ 1 ]. This complex disease manifests in various types, each with unique characteristics. The two primary categories are non-invasive, such as ductal carcinoma in situ (DCIS), and invasive, exemplified by invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) [ 2 ]. Recognizing the symptoms of breast cancer is crucial for early detection. These may encompass a palpable lump, changes in breast size or shape, nipple abnormalities, and skin alterations [ 3 ]. Globally, breast cancer stands as the second-leading cause of cancer-related mortality, constituting approximately 30% of all newly diagnosed cancer cases [ 4 , 5 ]. Detailed statistics from GLOBOCAN in 2020 reported 2.3 million diagnosed cases, representing an additional 11.7% of all newly identified cancer cases [ 6 , 7 ]. These figures underscore the significant impact of breast cancer on global health and emphasize the ongoing importance of research, prevention, and treatment efforts in addressing this prevalent and life-threatening disease [ 8 ]. The values for high-income countries in Asia, such as Japan, Singapore, South Korea, and Taiwan, have perceptibly improved in reducing this disease [ 9 , 10 ]. However, in Pakistan, the breast cancer ratio is increasing, most probably in younger ages [ 11 – 13 ]. Numerous risk factors contribute to the development of breast cancer, including age, gender, family history, genetic mutations and other different non-genetics factors [ 14 ]. Genetic mutations in breast cancer involve several genes, including BRCA1 , BRCA2 , HER1 , HER2 , CHEK2 , PALB2 , RAD51 and TP53 . PALB2 , the partner and localizing protein of BRCA2 , is particularly noteworthy [ 15 ]. PALB2 is an 1186 amino acid protein located on chromosome 16p12 and with a molecular weight of approximately 130 kilo Daltons, consisting of 12 intron and 13 exons [ 16 ]. PALB2 contains several proteins including N-terminal coiled-coil domain that interacts with BRCA1 at its C terminus and the WD40 domain that interacts with BRCA2 at the Chromatin organization Motif to promote chromatin organization [ 17 – 19 ]. PALB2 provides an association between BRCA1 and BRCA2 in the DNA damage repair [ 20 ]. The PALB2 protein completes homologous recombination repair (HRR) of DNA double-strand breaks (DSBs) while binding the BRCA1 and BRCA2 proteins. The combined BRCA1-PALB2-BRCA2 actively then recruits RAD51 and promote RAD51-mediated HR, ultimately affecting the resolution of DSBs10 repair [ 21 ]. In addition to playing an important role in HR regulation, PALB2 also play a role in the regulation of biological processes, including control of cell-cycle at the S-phase, cellular redox, homeostasis regulation, protection of actively transcribed genes, and recovery of stalled DNA replication forks [ 22 ]. The genetic variant rs249954 C > T exhibits functional effects, including altered enhancer histone marks, changed motifs, and significant associations with phenotypes as observed in NHGRI/EBI GWAS hits and GRASP QTL hits [ 23 ]. Moreover, the rs152451 A > G single nucleotide polymorphism (SNP) in the PALB2 gene is positioned proximal to the exon 4 splice donor site. Although not residing within a recognized protein domain, computational analyses, including the Human Splicing Finder (v3), suggest a potential influence on an exonic splicing enhancer motif. This proximity to a splice site raises the hypothesis that rs152451 could alter the splicing pattern of PALB2 mRNA, introducing a mechanism through which this genetic variant may impact PALB2 function. It is noteworthy that while various algorithms predict a benign effect on protein function, confirmation through RNA-based assays is essential for a comprehensive understanding of the SNP's functional implications in the context of breast cancer susceptibility [ 24 ]. Numerous studies have identified the association of PALB2 (rs249954 and rs152451) with the risk of breast cancer [ 25 – 28 ]. However, in Pakistan, especially in Khyber Pakhtunkhwa (KP) Population, the associations of these polymorphisms to breast cancer risk are largely unknown. Therefore, this case–controls study aimed to assess the susceptibility of selected SNPs in PALB2 with breast cancer risk in KP population. Materials and methods Inclusion, exclusion criteria and ethical approval A case-controls study was carried out in the Institute of Biotechnology and Genetic Engineering (IBGE) with a total of 200 participants, which include clinically, confirmed 100 breast cancer patients over a period of (2023–2024) from Institute of Radiotherapy and nuclear medicine (IRNUM) hospital Peshawar (under the license No- IBGE/2023/003). All the procedures from data collection to disposal were conducted under strict departmental guidelines. A gender (women only) and age matched 100 healthy controls were also recruited. Patients primarily diagnosed with breast cancer were enrolled while patients with other chronic diseases were excluded from the study. The research study was approved by the ethical committee of IBGE and IRNUM hospital Peshawar. Blood sampling and DNA extraction Approval (written consent) from all the enrolled subjects was taken after clearly describe the aim and objectives of the study in local language. A total of 3mL blood was collected in ethylene diamine tetra acetic acid (EDTA) tube and DNA isolation was carried out using salting out method already adopted at our lab and stored at -20°C for further analysis. Concentration and purity of DNA was confirmed using Nano-drop spectrophotometry machine. Demographic and comprehensive clinical data were collected using structured proforma. SNPs genotyping and gel electrophoresis Genotyping of PALB2 polymorphisms (rs152451 and rs249954) were carried out using specifically designed primers (Table 1 ). In each PCR reaction, 25 ng of extracted DNA was added to 10 µL reaction comprising of 5 µL Master Mix (2X), 0.5 µL each of forward and reverse primers, and 3 µL of RNase-free ddH2O water. Genotyping was done using ARMS-PCR followed by Gel Electrophoresis. Table 1 Allele specific primer sequences designed for SNPs genotyping Primer Primer Sequence (5 − 3) PALB2 (rs249954) Forward Outer TGCTTCTGATAGCATAAACCCAG Reverse Outer TCAAACAGAATGCCTGTAAAGCT Forward Inner CTACATATGAAAACTTTAATGAAT Reverse Inner GCTATATGACTGATTCTTTTCAG PALB2 (rs152451) Forward Outer GAAATCAGCCTGCCC Reverse Outer GTCTCACTCTGTTCCTGGTCAG Forward Inner TCAGCACGAAAAATTATTTATTCG Reverse Inner CATCTTGATTTACCTTTCACTT Statistical analysis Statistical Package for Social Science (SPSS) version 23 was used to analyze PALB2 selected alleles in breast cancer patient and healthy controls. An association between the mutational gene and the outcome components was determined using fisher exact test, and a derived odd ratio with 95% confidence level was also employed. Results Risk association of PALB2 (rs249954 and rs152451) polymorphism with breast cancer patients Both the selected SNPs were genotyped using ARMS-PCR protocol (Fig. 1 ). The analysis revealed significant association of PALB2 (rs249954) risk allele T (OR = 2.67, 95% CI = 1.78 to 4.00, P = 0.001) and both heterozygous (OR = 3.77, 95% CI = 1.70 to 8.34, P = 0.001) and homozygous mutant genotypes (OR = 6.40, 95% CI = 2.37 to 17.26, P = 0.0002) with breast cancer risk. Furthermore, statistical analysis for PALB2 (rs152451) revealed non-significant association of risk allele G (OR = 0.69, 95% CI = 0.47 to 1.03, P = 0.07) and heterozygous mutant genotype (OR = 0.52, 95% CI = 0.24 to 1.10, P = 0.08) with breast cancer risk. However, homozygous mutant genotype (OR = 0.38, 95% CI = 0.15 to 0.96, P = 0.042) exhibited significant association with breast cancer risk (Table 2 ). Table 2 The frequency distribution of PALB2 (rs249954 and rs152451) polymorphism in breast cancer patients and healthy controls PALB2 (rs249954) Allele Patients N = 100 Control N = 100 Odd ratio 95% CI P- value C(W) 82(41%) 130(65%) Reference T(M) 118(59%) 70(35%) 2.67 1.78 to 4.00 0.001 Genotype CC 10(10%) 32(32%) Reference CT 66(66%) 56(56%) 3.77 1.70 to 8.34 0.001 TT 24(24%) 12(12%) 6.40 2.37 to 17.26 0.0002 PALB2 (rs152451) Allele Patients N = 100 Control N = 100 Odd ratio 95% CI P-value A(W) 110(55%) 92(45%) Reference G(M) 90(46%) 108(54%) 0.69 0.4708 to 1.033 0.07 Genotype AA 25(25%) 14(14%) Reference AG 60(60%) 64(64%) 0.52 0.24 to 1.10 0.08 GG 15(15%) 22(22%) 0.38 0.15 to 0.96 0.042 Association of PALB2 (rs249954 and rs152451) variant with demographic and clinicopathological parameters of breast cancer patients The association between different demographic and clinical parameters of breast cancer patients and genotypic distribution of selected SNPs was determined. Both the PALB2 variants exhibited non-significant association with family history (P = 0.76, P = 0.60), Nulliparity (P = 0.06, P = 0.76) and menstrual status (P = 0.10, P = 0.81). Furthermore, both variant failed to exhibit significant association with clinicopathological parameters including Luminal A (P = 0.10, P = 0.15), Luminal B (P = 0.16, P = 0.40), HER2 status (P = 0.10, P = 0.15), TNBC (P = 0.51, P = 0.17) and ER status (P = 0.10, P = 1.0). Moreover, PALB2 (rs249954) exhibited significant association with Nodal status (P = 0.01), Metastasis (P = 0.01) and PR status (P = 0.01), while PALB2 (rs152451) didn’t showed any significant association (Table 3 ). Table 3 The association between demographic and clinical parameters of breast cancer patients and genotype distribution of selected SNPs Parameters PALB2 (rs249954) PALB2 (rs152451) Menstrual status CC (%) CG (%) GG (%) OR P value AA (%) AG (%) GG (%) OR P value Pre-menopausal 8(14.81) 36(66.6) 10(11.49) 0.26 13(24.07) 31(57.40) 10(18.51) 1.11 Post-menopausal 2(4.34) 30(65.21) 14(30.43) 3.82 0.10 12(26.08) 29(63.04) 5(10.86) 0.89 0.81 Nulliparity Positive 6(7.31) 56(68.29) 20(24.39) 3.61 20(24.3) 51(62.1) 11(13.4) 1.19 Negative 4(22.2) 10(55.5) 4(22.2) 0.27 0.06 5(27.7) 9(50) 4(22.2) 0.83 0.76 Nodal status Positive 3(4.54) 44(66.6) 19(28.7) 5.54 17(25.7) 37(56.1) 12(18.8) 0.88 Negative 7(20.5) 22(64.7) 5(14.7) 0.18 0.01 8(23.5) 23(67.6) 3(8.82) 1.12 0.80 Stages 2 4(12.5) 20(62.5) 8(25.0) 6(18.7) 24(75.0) 2(6.25) 3 2(8.88) 31(70.4) 11(26.0) 11(25) 23(54.5) 10(22.7) 4 4(16.6) 15(62.5) 5(20.8) 0.98 8(33.3) 13(54.1) 3(12.5) 0.28 Metastasis Positive 6(25) 14(58.3) 4(16.6) 0.16 8(33.3) 13(54.1) 3(12.5) 0.57 Negative 4(5.26) 52(68.4) 20(26.3) 6.0 0.01 17(22.3) 47(61.8) 12(15.7) 1.73 0.28 Family history Positive 1(7.69) 10(76.9) 2(15.3) 0.72 4(30.7) 6(46.1) 3(23.1) 1.39 Negative 9(10.3) 56(64.3) 22(25.2) 1.38 0.76 21(24.1) 54(62.1) 12(26.4) 0.71 0.60 HER2 Status Positive 1(2.77) 25(69.4) 10(27.7) 5.72 13(20.31) 42(65.6) 9(14.1) 1.96 Negative 9(14.1) 41(64.1) 14(21.8) 0.17 0.10 12(33.3) 18(50.0) 6(16.6) 0.50 0.15 Luminal A Positive 6(16.6) 20(55.5) 10(27.7) 0.33 12(35.2) 18(52.9) 6(17.6) 1.96 Negative 4(6.25) 46(71.8) 14(21.8) 3.00 0.10 13(19.6) 42(63.6) 9(13.6) 0.50 0.15 Luminal B Positive 2(25.0) 5(62.5) 1(12.5) 0.28 1(12.5) 6(75.0) 1(12.5) 2.47 Negative 8(8.69) 61(66.3) 23(25.0) 3.50 0.16 24(15.21) 54(58.6) 14(15.2) 0.40 0.40 Basal Type Positive 6(8.69) 44(63.7) 19(27.5) 1.55 20(28.9) 38(55.1) 11(15.9) 0.47 Negative 4(12.9) 22(70.9) 5(16.1) 0.64 0.51 5(16.1) 22(70.9) 4(12.9) 2.12 0.17 PR Status Positive 7(20.5) 21(61.7) 6(17.6) 0.18 8(23.5) 21(61.7) 5(14.7) 1.12 Negative 3(4.45) 45(68.1) 18(27.2) 2.03 0.01 17(25.7) 39(59.1) 10(15.1) 0.88 0.80 ER Status Positive 4(6.2) 46(71.8) 14(21.8) 3.0 16(25) 37(57.8) 11(17.1) 1.0 Negative 6(16.6) 20(55.5) 10(27.7) 0.33 0.10 9(25.0) 23(63.8) 4(11.1) 1.0 1.0 Discussion Breast cancer has emerged as the most prevalent form of cancer affecting women globally, with its incidence steadily increasing on a worldwide scale [ 29 ]. Globally, breast cancer stands as the second-leading cause of cancer-related mortality, constituting approximately 30% of all newly diagnosed cancer cases [ 4 , 30 ]. According to comprehensive data from GLOBOCAN in 2020, there were 2.3 million reported cases, signifying an additional 11.7% of all recently identified cancer instances [ 31 ]. Several established risk factors are linked to the development of breast cancer, including age, family history, weight, physical activity, oral contraceptive use, and alcohol consumption [ 32 ]. Genetic mutations in breast cancer involve several genes, including BRCA1 , BRCA2 , HER1 , HER2 , CHEK2 , PALB2 , RAD51 and TP53 . PALB2 , the partner and localizing protein of BRCA2 , is particularly noteworthy [ 15 ]. The PALB2 is located on chromosome 16p12.1, and has been identified as a third clinically significant medium-to-high penetrance breast cancer gene after BRCA1 and BRCA2 [ 33 ]. This gene plays a crucial role in co-localizing with BRCA2 proteins within nuclear foci. It also contributes to the stabilization of chromatin and the nuclear matrix, thereby enhancing the tumor-suppressing effects associated with BRCA2 [ 34 ]. Over the past decades, numerous studies have disclosed associations between PALB2 polymorphisms in various regions and cancer risk; however, the findings have displayed inconsistency [ 35 – 38 ]. In Pakistan, especially in KP Population, the associations of these polymorphisms to breast cancer risk are largely unknown. Therefore, this case–controls study aimed to assess the susceptibility of these two single nucleotide polymorphisms in PALB2 (rs249954 and rs 152451) to breast cancer risk in a KP female population. In this study, we enrolled 100 breast cancer patients and 100 healthy controls to examine the frequencies of polymorphism rs249954 and rs152451 within the Pashtun population. DNA extraction was carried out using salting out method while genotyping was done using ARMS-PCR previously used in our lab [ 39 , 40 ]. The analysis revealed significant association of PALB2 (rs249954) risk allele T (P = 0.001) and both heterozygous (P = 0.001) and homozygous mutant genotypes (P = 0.0002) with Breast cancer risk. Additionally, PALB2 (rs249954) exhibited significant association with Nodal status (P = 0.01), Metastasis (P = 0.01) and PR status (P = 0.01). Our findings align with research study conducted in two different Chinese populations, Asian and Turkey populations [ 25 – 28 ]. While study performed in Canadian population showed contradictory results indicating non-significant association of rs249954 with breast cancer risk [ 41 ]. Moreover, PALB2 (rs152451) risk allele G (P = 0.07) and heterozygous AG genotype (P = 0.08) indicated non-significant association with breast cancer risk. However, the homozygous mutant GG genotype was associated with an increased risk of breast cancer (P = 0.042). However, rs152451 failed to exhibit significant association with any of the selected demographic and clinical parameter. Our results align with research study conducted in South American and Turkey population [ 26 , 42 ]. Furthermore a meta-analysis study also supported our result indicating non-significant association of rs152451 with breast cancer risk [ 43 ]. Moreover, family based study performed in Australian population signifies the potential role of (rs152451) in familial breast cancer [ 24 ]. In conclusion our study highlighted the role of both PALB2 selected SNPs (rs249954 and rs152451) with the risk of breast cancer in KP population. PALB2 (rs249954) indicated significant association with breast cancer risk while rs152451 failed to exhibit significant association. However, different studies have identified the role of rs152451 highly significant with breast cancer cases of highly family history positive [ 24 , 42 ]. Therefore, future endeavors should consider identifying the role of PALB2 (rs152451) in separate cohort of highly positive familial breast cancer cases. Furthermore, while considering certain positive impact of study, there are certain limitations which also need to be discussed. The study was conducted with limited number of samples which may not fully cover this diverse population. Additionally, participants’ recruitment was done based on hospital settings which may introduce selection bias. Declarations Competing interests The authors declared no competing interests Consent to publish All the authors have read and approved the article for publication Availability of data and materials All the necessary data are included in manuscript, related data will be provided on request from corresponding author Funding There is no funding received to conduct the study, the authors contributed for the study Authors' Contributions SG did the experimental work and wrote the first draft under the supervision of NUK. HK help in data collection, analysis and write the article. NUK, MHA and IA critically review the final manuscript. Acknowledgements Not applicable References Muñoz, J.P., et al., The Role of MicroRNAs in Breast Cancer and the Challenges of Their Clinical Application. 2023. 13 (19): p. 3072. Ali, R., et al., Non-coding RNA’s prevalence as biomarkers for prognostic, diagnostic, and clinical utility in breast cancer. 2023. 23 (2): p. 195. 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Khan, Y., et al., Significant association of BRCA1 (rs1799950), BRCA2 (rs144848) and TP53 (rs1042522) polymorphism with breast cancer risk in Pashtun population of Khyber Pakhtunkhwa, Pakistan. 2023: p. 1-10. Shahzad, S., et al., Estrogen receptor alpha (ESR1) gene polymorphism (rs2234693 and rs2046210) with breast cancer risk in pashtun population of Khyber Pakhtunkhwa. 2023. 50 (3): p. 2445-2451. Guenard, F., et al., Evaluation of the contribution of the three breast cancer susceptibility genes CHEK2, STK11, and PALB2 in non-BRCA1/2 French Canadian families with high risk of breast cancer. 2010. 14 (4): p. 515-526. Leyton, Y., et al., Association of PALB2 sequence variants with the risk of familial and early-onset breast cancer in a South-American population. 2015. 15 (1): p. 1-10. Wu, Y., et al., Association between rs120963, rs152451, rs249935, rs447529, rs8053188, and rs16940342 polymorphisms in the PALB2 gene and breast cancer susceptibility: a meta-analysis. 2018. 41 (12): p. 780-786. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4160569","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":283455542,"identity":"4f2023c7-c618-4c5c-8ac7-9505c98d4bc5","order_by":0,"name":"Sohni Gul","email":"","orcid":"","institution":"The University of Agriculture Peshawar","correspondingAuthor":false,"prefix":"","firstName":"Sohni","middleName":"","lastName":"Gul","suffix":""},{"id":283455543,"identity":"fc8fe8dc-7e2e-4051-8dbf-bf40d155128e","order_by":1,"name":"Najeeb Ullah Khan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYHCCBAbGhoQEBgbmAxA+kGJsIE4LWwLRWhigWngMiNNizn7g4YOPO9Ly+Gf3fPzMu4NBju9GAtvDGXi0WPYkJBvOPJNTLHHn7GZp3jMMxpI3EtgNN+DRYnAgIU2at60iseFG7gYggyFxA9AWyQf4tJx/kP77L1DL/Bs5j38DtdQT1nIjIY2ZsS0HaHgOG8iWBAOQFrwOu/EgWbL3TFrixhtpZpZzz0gAPfaw3RCf9w3O5yR++LkjOXHejeTHN97usJHnO5587GEPHi3A6EhAsBkbJEBkG14NDAzsB5C1gCk2AlpGwSgYBaNghAEAP2BcEhNUy8IAAAAASUVORK5CYII=","orcid":"","institution":"The University of Agriculture Peshawar","correspondingAuthor":true,"prefix":"","firstName":"Najeeb","middleName":"Ullah","lastName":"Khan","suffix":""},{"id":283455544,"identity":"aff1c71f-ad01-4e62-b708-ee9118067209","order_by":2,"name":"Hamza Khan","email":"","orcid":"","institution":"The University of Agriculture Peshawar","correspondingAuthor":false,"prefix":"","firstName":"Hamza","middleName":"","lastName":"Khan","suffix":""},{"id":283455545,"identity":"c4333a50-e7d9-4757-b6dd-df39b288d949","order_by":3,"name":"Mikhlid H. Almutairi","email":"","orcid":"","institution":"King Saud University","correspondingAuthor":false,"prefix":"","firstName":"Mikhlid","middleName":"H.","lastName":"Almutairi","suffix":""},{"id":283455546,"identity":"53f6b0b7-ff69-4e2c-9999-5d09045f1378","order_by":4,"name":"Ijaz Ali","email":"","orcid":"","institution":"Gulf University for Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Ijaz","middleName":"","lastName":"Ali","suffix":""}],"badges":[],"createdAt":"2024-03-25 04:02:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4160569/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4160569/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53680324,"identity":"5c8172ae-b354-4782-af17-82e9558ee147","added_by":"auto","created_at":"2024-03-28 20:23:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":247829,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative gel picture of \u003cem\u003ePALB2\u003c/em\u003epolymorphism (rs249954 and rs152451): Representative gel picture of \u003cem\u003ePALB2\u003c/em\u003eselected SNPs, run on 2% gel and matches with 100 bp DNA Ladder (Thermo Fisher Scientific), L indicates ladder, M indicates mutant and W denotes wild allele.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4160569/v1/ef0e9a79260c5d4571794443.png"},{"id":53680323,"identity":"8645151a-d60a-4189-a213-367d2b570697","added_by":"auto","created_at":"2024-03-28 20:23:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":34336,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFrequency Distribution of PALB2 (rs249954) and (rs152551) Alleles and Genotypes among Healthy Controls and Patients\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4160569/v1/6de524cff5fff6274d8d2d71.png"},{"id":56419205,"identity":"dd2cfae1-d0a3-48e5-b11b-7587deae33a2","added_by":"auto","created_at":"2024-05-14 02:03:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1146600,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4160569/v1/dad317e2-4fae-47c8-ac4d-ca222cad8237.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Genetics risk assessment of PALB2 polymorphism (rs249954 and rs152451) with breast cancer susceptibility among the Pashtun population of Khyber Pakhtunkhwa, Pakistan","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBreast cancer, a globally pervasive disease, is characterized by abnormal cell growth in the breast [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This complex disease manifests in various types, each with unique characteristics. The two primary categories are non-invasive, such as ductal carcinoma in situ (DCIS), and invasive, exemplified by invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Recognizing the symptoms of breast cancer is crucial for early detection. These may encompass a palpable lump, changes in breast size or shape, nipple abnormalities, and skin alterations [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGlobally, breast cancer stands as the second-leading cause of cancer-related mortality, constituting approximately 30% of all newly diagnosed cancer cases [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Detailed statistics from GLOBOCAN in 2020 reported 2.3\u0026nbsp;million diagnosed cases, representing an additional 11.7% of all newly identified cancer cases [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These figures underscore the significant impact of breast cancer on global health and emphasize the ongoing importance of research, prevention, and treatment efforts in addressing this prevalent and life-threatening disease [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The values for high-income countries in Asia, such as Japan, Singapore, South Korea, and Taiwan, have perceptibly improved in reducing this disease [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, in Pakistan, the breast cancer ratio is increasing, most probably in younger ages [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNumerous risk factors contribute to the development of breast cancer, including age, gender, family history, genetic mutations and other different non-genetics factors [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Genetic mutations in breast cancer involve several genes, including \u003cem\u003eBRCA1\u003c/em\u003e, \u003cem\u003eBRCA2\u003c/em\u003e, \u003cem\u003eHER1\u003c/em\u003e, \u003cem\u003eHER2\u003c/em\u003e, \u003cem\u003eCHEK2\u003c/em\u003e, \u003cem\u003ePALB2\u003c/em\u003e, \u003cem\u003eRAD51\u003c/em\u003e and \u003cem\u003eTP53\u003c/em\u003e. \u003cem\u003ePALB2\u003c/em\u003e, the partner and localizing protein of \u003cem\u003eBRCA2\u003c/em\u003e, is particularly noteworthy [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. \u003cem\u003ePALB2\u003c/em\u003e is an 1186 amino acid protein located on chromosome 16p12 and with a molecular weight of approximately 130 kilo Daltons, consisting of 12 intron and 13 exons [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. \u003cem\u003ePALB2\u003c/em\u003e contains several proteins including N-terminal coiled-coil domain that interacts with BRCA1 at its C terminus and the WD40 domain that interacts with \u003cem\u003eBRCA2\u003c/em\u003e at the Chromatin organization Motif to promote chromatin organization [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. \u003cem\u003ePALB2\u003c/em\u003e provides an association between \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e in the DNA damage repair [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The PALB2 protein completes homologous recombination repair (HRR) of DNA double-strand breaks (DSBs) while binding the \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e proteins. The combined BRCA1-PALB2-BRCA2 actively then recruits RAD51 and promote RAD51-mediated HR, ultimately affecting the resolution of DSBs10 repair [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In addition to playing an important role in HR regulation, PALB2 also play a role in the regulation of biological processes, including control of cell-cycle at the S-phase, cellular redox, homeostasis regulation, protection of actively transcribed genes, and recovery of stalled DNA replication forks [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe genetic variant rs249954 C\u0026thinsp;\u0026gt;\u0026thinsp;T exhibits functional effects, including altered enhancer histone marks, changed motifs, and significant associations with phenotypes as observed in NHGRI/EBI GWAS hits and GRASP QTL hits [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Moreover, the rs152451 A\u0026thinsp;\u0026gt;\u0026thinsp;G single nucleotide polymorphism (SNP) in the \u003cem\u003ePALB2\u003c/em\u003e gene is positioned proximal to the exon 4 splice donor site. Although not residing within a recognized protein domain, computational analyses, including the Human Splicing Finder (v3), suggest a potential influence on an exonic splicing enhancer motif. This proximity to a splice site raises the hypothesis that rs152451 could alter the splicing pattern of \u003cem\u003ePALB2\u003c/em\u003e mRNA, introducing a mechanism through which this genetic variant may impact \u003cem\u003ePALB2\u003c/em\u003e function. It is noteworthy that while various algorithms predict a benign effect on protein function, confirmation through RNA-based assays is essential for a comprehensive understanding of the SNP's functional implications in the context of breast cancer susceptibility [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNumerous studies have identified the association of \u003cem\u003ePALB2\u003c/em\u003e (rs249954 and rs152451) with the risk of breast cancer [\u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, in Pakistan, especially in Khyber Pakhtunkhwa (KP) Population, the associations of these polymorphisms to breast cancer risk are largely unknown. Therefore, this case\u0026ndash;controls study aimed to assess the susceptibility of selected SNPs in \u003cem\u003ePALB2\u003c/em\u003e with breast cancer risk in KP population.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eInclusion, exclusion criteria and ethical approval\u003c/h2\u003e \u003cp\u003e A case-controls study was carried out in the Institute of Biotechnology and Genetic Engineering (IBGE) with a total of 200 participants, which include clinically, confirmed 100 breast cancer patients over a period of (2023\u0026ndash;2024) from Institute of Radiotherapy and nuclear medicine (IRNUM) hospital Peshawar (under the license No- IBGE/2023/003). All the procedures from data collection to disposal were conducted under strict departmental guidelines. A gender (women only) and age matched 100 healthy controls were also recruited. Patients primarily diagnosed with breast cancer were enrolled while patients with other chronic diseases were excluded from the study. The research study was approved by the ethical committee of IBGE and IRNUM hospital Peshawar.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eBlood sampling and DNA extraction\u003c/h2\u003e \u003cp\u003eApproval (written consent) from all the enrolled subjects was taken after clearly describe the aim and objectives of the study in local language. A total of 3mL blood was collected in ethylene diamine tetra acetic acid (EDTA) tube and DNA isolation was carried out using salting out method already adopted at our lab and stored at -20\u0026deg;C for further analysis. Concentration and purity of DNA was confirmed using Nano-drop spectrophotometry machine. Demographic and comprehensive clinical data were collected using structured proforma.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSNPs genotyping and gel electrophoresis\u003c/h2\u003e \u003cp\u003eGenotyping of \u003cem\u003ePALB2\u003c/em\u003e polymorphisms (rs152451 and rs249954) were carried out using specifically designed primers (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In each PCR reaction, 25 ng of extracted DNA was added to 10 \u0026micro;L reaction comprising of 5 \u0026micro;L Master Mix (2X), 0.5 \u0026micro;L each of forward and reverse primers, and 3 \u0026micro;L of RNase-free ddH2O water. Genotyping was done using ARMS-PCR followed by Gel Electrophoresis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAllele specific primer sequences designed for SNPs genotyping\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSequence (5\u0026thinsp;\u0026minus;\u0026thinsp;3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePALB2\u003c/p\u003e \u003cp\u003e(rs249954)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward Outer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTGCTTCTGATAGCATAAACCCAG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse Outer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTCAAACAGAATGCCTGTAAAGCT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward Inner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTACATATGAAAACTTTAATGAAT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse Inner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGCTATATGACTGATTCTTTTCAG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePALB2 (rs152451)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward Outer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGAAATCAGCCTGCCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse Outer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGTCTCACTCTGTTCCTGGTCAG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward Inner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTCAGCACGAAAAATTATTTATTCG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse Inner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCATCTTGATTTACCTTTCACTT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical Package for Social Science (SPSS) version 23 was used to analyze PALB2 selected alleles in breast cancer patient and healthy controls. An association between the mutational gene and the outcome components was determined using fisher exact test, and a derived odd ratio with 95% confidence level was also employed.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eRisk association of\u003c/b\u003e \u003cb\u003ePALB2\u003c/b\u003e \u003cb\u003e(rs249954 and rs152451) polymorphism with breast cancer patients\u003c/b\u003e\u003c/p\u003e \u003cp\u003eBoth the selected SNPs were genotyped using ARMS-PCR protocol (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The analysis revealed significant association of \u003cem\u003ePALB2\u003c/em\u003e (rs249954) risk allele T (OR\u0026thinsp;=\u0026thinsp;2.67, 95% CI\u0026thinsp;=\u0026thinsp;1.78 to 4.00, P\u0026thinsp;=\u0026thinsp;0.001) and both heterozygous (OR\u0026thinsp;=\u0026thinsp;3.77, 95% CI\u0026thinsp;=\u0026thinsp;1.70 to 8.34, P\u0026thinsp;=\u0026thinsp;0.001) and homozygous mutant genotypes (OR\u0026thinsp;=\u0026thinsp;6.40, 95% CI\u0026thinsp;=\u0026thinsp;2.37 to 17.26, P\u0026thinsp;=\u0026thinsp;0.0002) with breast cancer risk. Furthermore, statistical analysis for \u003cem\u003ePALB2\u003c/em\u003e (rs152451) revealed non-significant association of risk allele G (OR\u0026thinsp;=\u0026thinsp;0.69, 95% CI\u0026thinsp;=\u0026thinsp;0.47 to 1.03, P\u0026thinsp;=\u0026thinsp;0.07) and heterozygous mutant genotype (OR\u0026thinsp;=\u0026thinsp;0.52, 95% CI\u0026thinsp;=\u0026thinsp;0.24 to 1.10, P\u0026thinsp;=\u0026thinsp;0.08) with breast cancer risk. However, homozygous mutant genotype (OR\u0026thinsp;=\u0026thinsp;0.38, 95% CI\u0026thinsp;=\u0026thinsp;0.15 to 0.96, P\u0026thinsp;=\u0026thinsp;0.042) exhibited significant association with breast cancer risk (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe frequency distribution of \u003cem\u003ePALB2\u003c/em\u003e (rs249954 and rs152451) polymorphism in breast cancer patients and healthy controls\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePALB2\u003c/em\u003e (rs249954)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAllele\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePatients\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;100\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;100\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOdd ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP- value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC(W)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82(41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130(65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eT(M)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118(59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70(35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.78 to 4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGenotype\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10(10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66(66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56(56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.70 to 8.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24(24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.37 to 17.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePALB2\u003c/b\u003e \u003cb\u003e(rs152451)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAllele\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePatients\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eN\u0026thinsp;=\u0026thinsp;100\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eN\u0026thinsp;=\u0026thinsp;100\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eOdd ratio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eP-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eA(W)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110(55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92(45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eG(M)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90(46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108(54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4708 to 1.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGenotype\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25(25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAG\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60(60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64(64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24 to 1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGG\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15(15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.15 to 0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAssociation of\u003c/b\u003e \u003cb\u003ePALB2\u003c/b\u003e \u003cb\u003e(rs249954 and rs152451) variant with demographic and clinicopathological parameters of breast cancer patients\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe association between different demographic and clinical parameters of breast cancer patients and genotypic distribution of selected SNPs was determined. Both the \u003cem\u003ePALB2\u003c/em\u003e variants exhibited non-significant association with family history (P\u0026thinsp;=\u0026thinsp;0.76, P\u0026thinsp;=\u0026thinsp;0.60), Nulliparity (P\u0026thinsp;=\u0026thinsp;0.06, P\u0026thinsp;=\u0026thinsp;0.76) and menstrual status (P\u0026thinsp;=\u0026thinsp;0.10, P\u0026thinsp;=\u0026thinsp;0.81). Furthermore, both variant failed to exhibit significant association with clinicopathological parameters including Luminal A (P\u0026thinsp;=\u0026thinsp;0.10, P\u0026thinsp;=\u0026thinsp;0.15), Luminal B (P\u0026thinsp;=\u0026thinsp;0.16, P\u0026thinsp;=\u0026thinsp;0.40), HER2 status (P\u0026thinsp;=\u0026thinsp;0.10, P\u0026thinsp;=\u0026thinsp;0.15), TNBC (P\u0026thinsp;=\u0026thinsp;0.51, P\u0026thinsp;=\u0026thinsp;0.17) and ER status (P\u0026thinsp;=\u0026thinsp;0.10, P\u0026thinsp;=\u0026thinsp;1.0). Moreover, \u003cem\u003ePALB2\u003c/em\u003e (rs249954) exhibited significant association with Nodal status (P\u0026thinsp;=\u0026thinsp;0.01), Metastasis (P\u0026thinsp;=\u0026thinsp;0.01) and PR status (P\u0026thinsp;=\u0026thinsp;0.01), while \u003cem\u003ePALB2\u003c/em\u003e (rs152451) didn\u0026rsquo;t showed any significant association (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe association between demographic and clinical parameters of breast cancer patients and genotype distribution of selected SNPs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePALB2\u003c/em\u003e (rs249954)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c11\" namest=\"c7\"\u003e \u003cp\u003e\u003cem\u003ePALB2\u003c/em\u003e (rs152451)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMenstrual status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCC (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCG (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGG (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAA (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAG (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eGG (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePre-menopausal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(14.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36(66.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(11.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13(24.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31(57.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10(18.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePost-menopausal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(4.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30(65.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(30.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12(26.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29(63.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5(10.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNulliparity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(7.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56(68.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20(24.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20(24.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e51(62.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11(13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(55.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5(27.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9(50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4(22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNodal status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(4.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44(66.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(28.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17(25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e37(56.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12(18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7(20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(64.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8(23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23(67.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3(8.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStages\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6(18.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24(75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2(6.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(8.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31(70.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(26.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11(25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23(54.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10(22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8(33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13(54.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3(12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMetastasis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(58.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8(33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13(54.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3(12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(5.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52(68.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20(26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17(22.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e47(61.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12(15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily history\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(7.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(76.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4(30.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6(46.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3(23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9(10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56(64.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22(25.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21(24.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54(62.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12(26.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHER2 Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(2.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(69.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(27.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13(20.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e42(65.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9(14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9(14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41(64.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(21.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12(33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18(50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6(16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLuminal A\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(55.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(27.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12(35.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18(52.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6(17.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(6.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46(71.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(21.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13(19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e42(63.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9(13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLuminal B\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1(12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6(75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1(12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(8.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61(66.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23(25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24(15.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54(58.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e14(15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBasal Type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(8.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44(63.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(27.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20(28.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38(55.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11(15.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(12.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(70.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5(16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22(70.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4(12.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePR Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7(20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21(61.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(17.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8(23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21(61.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5(14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(4.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45(68.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18(27.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17(25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e39(59.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10(15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eER Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46(71.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(21.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16(25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e37(57.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11(17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(55.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(27.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9(25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23(63.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4(11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eBreast cancer has emerged as the most prevalent form of cancer affecting women globally, with its incidence steadily increasing on a worldwide scale [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Globally, breast cancer stands as the second-leading cause of cancer-related mortality, constituting approximately 30% of all newly diagnosed cancer cases [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. According to comprehensive data from GLOBOCAN in 2020, there were 2.3\u0026nbsp;million reported cases, signifying an additional 11.7% of all recently identified cancer instances [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Several established risk factors are linked to the development of breast cancer, including age, family history, weight, physical activity, oral contraceptive use, and alcohol consumption [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Genetic mutations in breast cancer involve several genes, including \u003cem\u003eBRCA1\u003c/em\u003e, \u003cem\u003eBRCA2\u003c/em\u003e, \u003cem\u003eHER1\u003c/em\u003e, \u003cem\u003eHER2\u003c/em\u003e, \u003cem\u003eCHEK2\u003c/em\u003e, \u003cem\u003ePALB2\u003c/em\u003e, \u003cem\u003eRAD51\u003c/em\u003e and \u003cem\u003eTP53\u003c/em\u003e. \u003cem\u003ePALB2\u003c/em\u003e, the partner and localizing protein of \u003cem\u003eBRCA2\u003c/em\u003e, is particularly noteworthy [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The \u003cem\u003ePALB2\u003c/em\u003e is located on chromosome 16p12.1, and has been identified as a third clinically significant medium-to-high penetrance breast cancer gene after \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This gene plays a crucial role in co-localizing with \u003cem\u003eBRCA2\u003c/em\u003e proteins within nuclear foci. It also contributes to the stabilization of chromatin and the nuclear matrix, thereby enhancing the tumor-suppressing effects associated with \u003cem\u003eBRCA2\u003c/em\u003e [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Over the past decades, numerous studies have disclosed associations between \u003cem\u003ePALB2\u003c/em\u003e polymorphisms in various regions and cancer risk; however, the findings have displayed inconsistency [\u003cspan additionalcitationids=\"CR36 CR37\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In Pakistan, especially in KP Population, the associations of these polymorphisms to breast cancer risk are largely unknown. Therefore, this case\u0026ndash;controls study aimed to assess the susceptibility of these two single nucleotide polymorphisms in \u003cem\u003ePALB2\u003c/em\u003e (rs249954 and rs 152451) to breast cancer risk in a KP female population.\u003c/p\u003e \u003cp\u003eIn this study, we enrolled 100 breast cancer patients and 100 healthy controls to examine the frequencies of polymorphism rs249954 and rs152451 within the Pashtun population. DNA extraction was carried out using salting out method while genotyping was done using ARMS-PCR previously used in our lab [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The analysis revealed significant association of \u003cem\u003ePALB2\u003c/em\u003e (rs249954) risk allele T (P\u0026thinsp;=\u0026thinsp;0.001) and both heterozygous (P\u0026thinsp;=\u0026thinsp;0.001) and homozygous mutant genotypes (P\u0026thinsp;=\u0026thinsp;0.0002) with Breast cancer risk. Additionally, \u003cem\u003ePALB2\u003c/em\u003e (rs249954) exhibited significant association with Nodal status (P\u0026thinsp;=\u0026thinsp;0.01), Metastasis (P\u0026thinsp;=\u0026thinsp;0.01) and PR status (P\u0026thinsp;=\u0026thinsp;0.01). Our findings align with research study conducted in two different Chinese populations, Asian and Turkey populations [\u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. While study performed in Canadian population showed contradictory results indicating non-significant association of rs249954 with breast cancer risk [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Moreover, \u003cem\u003ePALB2\u003c/em\u003e (rs152451) risk allele G (P\u0026thinsp;=\u0026thinsp;0.07) and heterozygous AG genotype (P\u0026thinsp;=\u0026thinsp;0.08) indicated non-significant association with breast cancer risk. However, the homozygous mutant GG genotype was associated with an increased risk of breast cancer (P\u0026thinsp;=\u0026thinsp;0.042). However, rs152451 failed to exhibit significant association with any of the selected demographic and clinical parameter. Our results align with research study conducted in South American and Turkey population [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Furthermore a meta-analysis study also supported our result indicating non-significant association of rs152451 with breast cancer risk [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Moreover, family based study performed in Australian population signifies the potential role of (rs152451) in familial breast cancer [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn conclusion our study highlighted the role of both \u003cem\u003ePALB2\u003c/em\u003e selected SNPs (rs249954 and rs152451) with the risk of breast cancer in KP population. \u003cem\u003ePALB2\u003c/em\u003e (rs249954) indicated significant association with breast cancer risk while rs152451 failed to exhibit significant association. However, different studies have identified the role of rs152451 highly significant with breast cancer cases of highly family history positive [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Therefore, future endeavors should consider identifying the role of \u003cem\u003ePALB2\u003c/em\u003e (rs152451) in separate cohort of highly positive familial breast cancer cases. Furthermore, while considering certain positive impact of study, there are certain limitations which also need to be discussed. The study was conducted with limited number of samples which may not fully cover this diverse population. Additionally, participants\u0026rsquo; recruitment was done based on hospital settings which may introduce selection bias.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declared no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors have read and approved the article for publication\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the necessary data are included in manuscript, related data will be provided on request from corresponding author\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no funding received to conduct the study, the authors contributed for the study \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' Contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSG did the experimental work and wrote the first draft under the supervision of NUK. HK help in data collection, analysis and write the article. NUK, MHA and IA critically review the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eMu\u0026ntilde;oz, J.P., et al., The Role of MicroRNAs in Breast Cancer and the Challenges of Their Clinical Application. 2023. \u003cstrong\u003e13\u003c/strong\u003e(19): p. 3072.\u003c/li\u003e\n \u003cli\u003eAli, R., et al., Non-coding RNA\u0026rsquo;s prevalence as biomarkers for prognostic, diagnostic, and clinical utility in breast cancer. 2023. \u003cstrong\u003e23\u003c/strong\u003e(2): p. 195.\u003c/li\u003e\n \u003cli\u003eGl\u0026uuml;ck, S., et al., TP53 genomics predict higher clinical and pathologic tumor response in operable early-stage breast cancer treated with docetaxel-capecitabine\u0026plusmn;trastuzumab. 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The occurrence of specific genetic variations, known as single nucleotide polymorphisms (SNPs), in the \u003cem\u003ePALB2\u003c/em\u003e gene has been identified as a factor contributing to an increased susceptibility to breast cancer. The SNPs in \u003cem\u003ePALB2\u003c/em\u003e (rs249954 and rs152451) are identified and associated with breast cancer risk, however its role remains unknown in the Pashtun ethnic group, making it necessary to explore in this population. This case-controls study included 100 breast cancer patients and 100 healthy controls. The SNPs genotyping was performed using amplification-refractory mutation system-polymerase chain reaction (ARMS-PCR). The statistical analysis revealed a significant association between the risk allele of rs249954 and an elevated breast cancer risk (P = 0.0001), while rs152451 did not exhibit a significant association (P = 0.07). Heterozygous genotype of rs249954 was linked to increased breast cancer risk (P = 0.0001), whereas rs152451 did not show a significant association (P = 0.08). Mutant genotypes of both the SNPs correlated positively with breast cancer risk (P = 0.002, P = 0.042). Additionally, rs249954 exhibited significant association with Nodal status (P=0.01), Metastasis (P=0.01) and PR status (P=0.01). While \u003cem\u003ePALB2\u003c/em\u003e (rs142451) failed to exhibit significant association with any of the selected demographic and clinical parameters. In conclusion, the risk allele and both the heterozygous and homozygous genotypes of rs249954 were associated with an increased risk of breast cancer, whereas only homozygous mutant genotype of rs152451 exhibited significant association. However, further studies with larger datasets and comprehensive genomic analysis are necessary to validate these findings and explore associations with other relevant SNPs.\u003c/p\u003e","manuscriptTitle":"Genetics risk assessment of PALB2 polymorphism (rs249954 and rs152451) with breast cancer susceptibility among the Pashtun population of Khyber Pakhtunkhwa, Pakistan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-28 20:23:54","doi":"10.21203/rs.3.rs-4160569/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3d21721b-3197-4f93-847e-7080c75da00b","owner":[],"postedDate":"March 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-14T01:55:08+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-28 20:23:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4160569","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4160569","identity":"rs-4160569","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}