Research of histological characteristics and single nucleotide polymorphisms in hereditary genes among Pakistani breast cancer patients

Research of histological characteristics and single nucleotide polymorphisms in hereditary genes among Pakistani breast cancer patients | 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 Research of histological characteristics and single nucleotide polymorphisms in hereditary genes among Pakistani breast cancer patients Yasir Nawaz, Ali Zaib Khan, Fouzia Tanvir, Sadaf Ambreen, Javaria Zafar, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2411036/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 Cancer is a type which involves irregular progression of cells with the capacity to enter and move to other portions of body. Breast cancer starts from breast tissues, mostly from inner coating of milk ducts. It is categorized into various methods by, grade, stage and receptors status. It is very common in females worldwide. Whole-exome sequencing (WES) was done in DNA removed from tumors of six breast cancer patients from Jinnah hospital Lahore, Pakistan. There were 19 patients from age 27 to 73 from which tissue sample were collected from 6 patients. The age distribution shows non-significant differences. The ER/PR status shows non-significant differences and odds ratio equals to 1. Somatic mutations were detected in three targeted genes ATM, TP53 and CDH (CDH5, CDH8, CDH10, CDH12, CDH16, CDH20, CDH23 and CDH24) in sample 1. Two genes with exonic variants were found in sample 2 containing TP53 and CDH (CDH5, CDH16, CDH19, and CDH23). Amino acid change and deletions were observed in different exonic sites of these genes. To conclude, more number of patients was observed having invasive ductal breast carcinoma. A number of novel somatic mutations for breast cancer were recognized. More studies are needed to define the functions of these mutated genes in breast cancer. Whole exome sequencing shows different type of mutations in different exonic regions of genes including TP53, ATM and CDH. Breast cancer Single nucleotide polymorphisms Somatic mutations Whole exome sequencing Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Cancer is a type which involves irregular progression of cells with the capacity to enter and move to other portions of body (Dwivedi; Fleisch, Franz, & Herrmann, 2021 ). On contrary, benign tumors do not move to other parts. In male, most common types of cancers are lung cancer, prostate cancer, colorectal cancer, and oesophageal cancer (Baenziger et al., 2020 ). In women, BC, colorectal cancer, lung cancer, and cervical cancer is significant (Regitha, Parthasarathy, & Balakrishnan, 2021 ). 40% cases will be expected if skin cancer added (Cakir, Adamson, & Cingi, 2012 ; Dubas & Ingraffea, 2013 ). Cancer threat rises considerably with age, and various occurs more frequently in developing countries (Regitha et al., 2021 ). It is 2nd important reason of death in U.S and most common in Pakistani females (Cokkinides, Albano, Samuels, Ward, & Thum, 2005 ; Gilani, Kamal, & Akhter, 2003 ). The age related cancer mortality increases in U.S. people. Cancer is characterized into 4 stages (I, II, III, and IV). Stage I specifies the initial infection and stage IV is progressive stage of infection (Gilani et al., 2003 ). TNM method is used to grade BC. It shows the mass of tumors (T), tumors might spreads to lymph nodes (N) in armpits, and the tumors has metastasized (M) (i.e., spreads to other parts of body) (Saslow et al., 2004 ). In 2015, about 90.5 million patients had cancer (Lipton, Schwedt, & Friedman, 2016 ). In 2019, about 18 million fresh patients were diagnosed (Sciacovelli, Schmidt, Maher, & Frezza, 2020 ). Yearly, it causes 8.8 million cancer mortality (15.7%) (H. Wang et al., 2016 ). BRCA1, BRCA2, p53, and PTEN/MMAC1 are the highly penetrant genes that are firstly found in those people who have large family history of breast cancer. Some other genes which are less mutated and cause low risk of breast cancer also find out. Low penetrant genes are the ataxia telangiectasia gene ATM and the HRAS1 (Ellisen & Haber, 1998 ). About 5–10% of BC are supposed to be inherited that are affected by irregular genes. Studies shows that females with a family history of BC have more threat of developing BC. The alterations responsible for increasing BC threat in families are documented. These include alterations in ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, MLH1, MRE11, MSH2, MSH6, MUTYH, NBN, PALB2, PMS1, PMS2, PTEN, RAD50, RAD51C, STK11 and TP53 genes. These infrequent alterations are perhaps dispersed to a small percentage (2–5%) of BC cases (Cybulski et al., 2011 ). Germline alterations of high penetrance BC susceptibility genes like BRCA1, BRCA2, TP53, CHEK2, ATM, PTEN and PPM1D deliberate a high threat of developing HBC (Cybulski et al., 2011 ). In recent times, it was found that alterations in PPM1D gene are related with an increased threat of BC and females with PPM1D alterations have 20% chances of developing BC. In many BC causing genes one copy of alteration is hereditary and occurs in every part and the second copy of altered gene occurs in the tumors itself, but interestingly PPM1D alterations were not hereditary, and found only in red blood cells. SNPs are one of the majority frequent types of genetic changes in the human genome. Single nucleotide polymorphisms in the genes which normalize DNA variance mend, cell cycle regulation, immunity and metabolism are connected with genetic defenselessness to cancer. From an experimental perspective, Single nucleotide polymorphisms are possible diagnostic and therapeutic biomarkers in most of the cancer types (Zhang et al., 2012 ). The purpose of this study was to characterize how rare histological characteristics vary in their stages, size, lymph node status, estrogen and progesterone receptors (ER)/PR status, and grade of BC patients from Pakistan and to analyze the somatic mutations in the breast tissues. Materials And Methods Ethics Statement and consent to participate The study was conducted in according to the Declaration of Helsinki. The written consent form was signed from all patients under study. This study was permitted by the Institutional Review Board of the Jinnah Hospital Lahore/ Allama Iqbal Medical College Lahore. Site And Population Selection Breast tissue samples were collected from Jinnah hospital Lahore, Pakistan. The study duration was from March 2021 to March 2022. The population under study includes breast cancer patients having characteristics of hereditary breast cancer which includes: (i) analysed with BC and another primary cancer, (ii) with family history which includes at least 2 cases of BC in 1st and 2nd degree relatives (iii) bilateral breast cancer and (iv) breast cancer identification earlier the age of 40 years (Sun et al., 2017 ). Familial breast cancer includes those people who had history of BC. Early onset breast cancer (EBC) included those patients who do not have any history of BC and were identified at or earlier the age of 40 years, sporadic breast cancer (SBC) included those patients who do not have a family history of BC and were identified above the age of 40 years (Sun et al., 2017 ). Tumor size is the maximum tumor diameter which is measured by ultrasound during analysis. The tumors were classified in accordance to the modified Bloom–Richardson system. Estrogen receptors (ER), progesterone receptors (PR), and human epidermal growth factor receptors 2 (HER2) status were obtained by using the breast tumor tissue acquired from a core needle biopsy and from surgery (C. Wang et al., 2015 ). Immunohistochemistry (Ihc) Histopathological investigation was done by pathologists. To regulate the expressions of hormone receptors comprising of estrogen receptors ER and progesterone receptors PR, and the epidermal growth factor receptor 2 (HER2) in a 5µm formalin- embeded, paraffin- fixed tumor section. IHC test was achieved the standard protocol (Engstrøm et al., 2013 ; Lipponen, Aaltomaa, Kosma, & Syrjänen, 1994 ). The IHC grouping offers both helpful and predictive evidence. In this study BC was classified into four groups on the basis of immunohistochemistry profile ER, PR and Her2/neu expression, positive (+) or negative (-). The groups include: ER/PR+,Her2 + = ER+/PR+,Her2+; ER-/PR+,Her2+; ER+/PR-,Her2+ ER/PR+,Her2- = ER+/PR+,Her2-; ER-/PR+,Her2-; ER+/PR-,Her2 ER/PR-,Her2 + = ER-/PR-,Her2+ ER/PR-,Her2- = ER-/PR-,Her2- These are classified as: ER/PR+,Her2 + called Luminal B, ER/PR+,Her2- called Luminal A and ER/PR-,Her2 + and ER/PR-, Her2- called triple negative/basal-like tumor.1 in the absence of tissue sample, it was difficult to identify the classification by IHC (Onitilo, Engel, Greenlee, Mukesh, & research, 2009). Dna Extraction Phenol chloroform or Organic technique was used to extract DNA. 20 mg of Breast tissue sample was chosen from each sample and regulated in 500µl of lysis solution and incubate it for 20 to 30min at room temperature. Samples were mixed moderately to confirm the suitable homogenization. Centrifugation was done on samples for 3 minute at 13000 rpm for phase separation. The supernatant was cast-off while the pellet holding DNA was further treated with multiple washings by lysis solution were completed to avoid impurity. Pellet was again treated by 400 µl lysis solution, 13 µl of 20% SDS and 25 µl proteinase K. Samples were incubated at 37 ◦ C whole night. The samples were then treating for the complete cell digestion. Then processed with 500 µl of phenol, chloroform and isoamyl alcohol (i.e. P:CI solution). The suspended solution was centrifuged at 13000 rpm for 10 minutes for moderate and through mixing. Aqueous phase was transported to another tube to purify and separate the DNA. The aqueous layer was processed with 500 µl of chloroform and isoamyl alcohol (C:I, 24:1) and centrifuged for 10 minutes at 13000 rpm. The aqueous layer was trsnported into 1.5 ml centrifuge tube, 55 µl of sodium acetate and 500 µl of chilled isopropanol were added. Samples were incubated for 45 minutes at -20 ° C. Then the samples were centrifuged at 13000 rpm for 10 minutes. Supernatant was removed and pellet was processed with 500 µl of 70% ethanol and centrifuged at 7500 rpm for 5 minutes for the purpose to remove impurities, pellet was reserved while supernatant was removed and then dry in air. DNA pellet was resuspended in TE Buffer (Tris EDTA) and stored at 4 ◦ C (Köchl, Niederstätter, & Parson, 2005 ; Sambrook & Russell, 2006 ). Agarose Gel Electrophoresis: This was done by using 1% agarose gel which contains 1 gram of agarose mixed in 100 ml of 1X TAE buffer (Tris Acetic acid EDTA). Clear solution was obtained after heating. 7 µl Ethidium Bromide mixed in gel solution. Gel was transferred into the gel casting tray with injecting combs. After solidification, gel caster was transported to gel tank having 1X TAE buffer and combs were detached carefully. 7 µl of obtained DNA was mixed with 3 µl of 6X bromophenol blue dye (called loading dye) loaded in wells. The gel was run in exact constraints included 500 mA of current with 75 volts for 1 hour. Gel was pictured under UV Trans-Illuminator bio Doc Analyzer (Ghatak, Muthukumaran, & Nachimuthu, 2013; Joshi & Deshpande, 2010). Dna Quantification The quantity of DNA was calculated by using Thermo scientific Multi Skan Go Apparatus. 260/280 ratio showed the quality whereas concentration is shown in ng/ul (Waye, Presley, Budowle, Shutler, & Fourney, 1989 ). Whole Exome Sequencing (Wes) WES is an inexpensive alternate method to whole genome sequencing, as it marks only the protein coding regions of the human genome answerable for many known disease associated variants. It is helpful whether in directing trainings in infrequent mendelian disorders, complex diseases, cancer research, or human population studies, human whole exome sequencing gives a good quality, reasonable, and suitable solution. The results of WES include: Identify variants across a widespread range of submissions Attains complete exposure of coding regions Delivers an inexpensive alternate to WES containing less data of 4 to 5 GB than 90 GB Creates a small, more convenient data set for quicker, informal data investigation associated to whole-genome methods Statistical analysis Statistical analysis was performed in Microsoft excel 2010. Results This study was conducted from Jinnah hospital to collect breast tissue samples during surgery. The informed consent was signed by the patient. Six samples were collected from patients. Data was collected related to the study which includes histopathological reports of all patients. Out of these seven samples WES was performed on two patients. The hereditary genes TP53, ATM and CDH were selected to find the somatic mutation sites by whole exome sequencing. Immunohistochemistry The data was collected from Jinnah hospital Lahore. This study includes 19 patients in which 1 was male and remaining 18 were female. The data collected during the interview session includes cancer type and subtype, age, gender, number of tumors, location of tumors, TNM_stage, ER, PR, and (HER2) status of patients. The age of all patients varies from 27 to 73 years. There were different number of tumors which includes 1, 2, 3, 11 and sometimes 15 in patients under study. The metastatic site includes the location of tumor which shows that the tumor was collected from either left side of breast or right side of breast. Tumor was collected from left side of breast in some patients and in some from right side of breast. The detailed study is shown in Table 1 in supplementary data. The TNM_Stage varies from patients to patients. Some patients have grade II, III, IV and IV. Some patient’s shows triple negative breast cancer type and some shows HER2 overexpressed. The cancer type includes the patients with Invasive ductal carcinoma and very rarely shows Hidradenocarcinoma and Hodgkin lymphoma. Two patients in this study do not have complete information. This is shown in Table 1 in supplementary data. The status of ER, PR and HER-2 varies among patients. In some patients all shows negative which indicates the subtype is triple negative. In patients with both negative ER, PR and positive HER-2 and also if both ER, PR positive and HER-2 negative indicates HER-2 overexpressed. If both the ER, PR positive and HER-2 negative then it is called luminal A type of BC. Table 1 Shows the characteristics of breast cancer patients ID Age in years Gender Number of tumors Tumor location TNM_Stage ER PR HER2 Subtypes Cancer type Patient 1 58 F 1 Tumor Right side III - - - Triple Negative Invasive ductal carcinoma Patient 2 70 F 1 Tumor_Left side II - - + HER2-overexpressed Invasive ductal carcinoma Patient 3 50 F 1 Tumor_Left side II - - - Triple Negative Invasive ductal carcinoma Patient 4 30 F 1 Tumor_Left side III - - - Triple Negative Invasive ductal carcinoma Patient 5 65 F 1 Tumor Right side III - - - Triple Negative Invasive ductal carcinoma Patient 6 36 F 1 Tumor_Left side III - - - Triple Negative Invasive ductal carcinoma Patient 7 45 F 1 Tumor Right side III - - + HER2-overexpressed Invasive ductal carcinoma Patient 8 60 F 2 Tumor_Left side III + + - HER2-overexpressed Hodgkin lymphoma Patient 9 58 F 1 Tumor_Left side III - - - Triple Negative Invasive ductal carcinoma Patient 10 56 F 11 Tumor_Left side III + + - HER2-overexpressed Invasive ductal carcinoma Patient 11 27 F 1 Tumor Right side III - - - Triple Negative Invasive ductal carcinoma Patient 12 38 F 1 Tumor_Left side II + + - HER2-overexpressed Invasive ductal carcinoma Patient 13 35 F 1 Tumor_Left side II + + - HER2-overexpressed Invasive ductal carcinoma Patient 14 43 F 15 Tumor Right side IV nill nill nill nill Mallignant phyllodes tumor Patient 15 45 F 1 Tumor Right side II - - - Triple Negative Invasive ductal carcinoma Patient 16 42 M nill Tumor Right side V nill nill nill nill Hodgkin lymphoma Patient 17 73 F 1 Tumor_Left side III - - - Triple Negative Invasive ductal carcinoma Patient 18 45 F 3 Tumor_Left side III - - + HER2-overexpressed Invasive ductal carcinoma Patient 19 45 F 1 Tumor_Left side II - - + HER2-overexpressed Invasive ductal carcinoma Age Distribution In this study, the data collected from patients includes 1 male and 18 female with two age groups below 50 and above 50 years of age. The p-value shows 0.45 i.e > 0.05 which indicates the difference was non-significant. This is shown in Table 2 . Table 2 Shows the age distribution of Breast cancer patients Gender 50 and below 50 % Above 50 % Total P-value Male 1 5.26 0 0.00 1 0.43 Female 11 57.89 7 36.84 18 Total 12 63.16 7 36.84 19 Descriptive analysis Descriptive analysis includes different values on the basis of age. The mean of age was 48.2, standard error was 2.86, median and mode was 45. The standard deviation of the age shows 12.79, sample variance was 163.64. The range, minimum and maximum values were 46, 27 and 73 respectively. The total samples were 19 patients in this study. ER/PR status of breast cancer patients The table shows the odds ratio and p-value of collected data. The ER/PR shows equal number of patients with positive and equal number with negative. This shows the non-significant difference and odds ratio equal to 1. 2 patients do not have this data. This is shown in Table 3 . Table 3 Shows the ER/PR status of patients Status ER PR OR P-value Positive 4 4 1 1 Negative 14 14 DNA Extraction and Agarose gel electrophoresis DNA was extracted from 6 tissue samples. Two of these were lost during the research and the DNA from remaining four samples including sample 3, 4, 5 and 6 extracted were run into gel is shown in Fig. 1 . Phenol chloroform (Organic) technique was employed to extract DNA. This was done by 1% agarose gel and configuration includes 1 gram of agarose mixed in 100 ml of 1X TAE buffer (Tris Acetic acid EDTA). For gel electrophoresis 1KB ladder was laden in 1st well with DNA sample in next well. DNA is of highly complete and of more than 20kb size. This is shown in Fig. 1 . DNA quantification The DNA quantity was measured by using Thermo scientific Multi Skan Go Instrument. 260/280 ratio showed the quality whereas concentration is shown in ng/ul. (i.e., 1.81–1.88). Whole exome sequencing (WES) and Exonic variant analysis The 3 genes were targeted in sample 1 including ATM, TP53 and CDH (CDH5, CDH8, CDH10, CDH12, CDH16, CDH20, CDH23 and CDH24). The mutation types includes synonymous SNV, non-synonymous SNV, stopgain, non-frameshift deletion, frameshift deletion and non-framesghift substitution in sample 1 It was found that ATM gene is located on chromosome no 11. This shows two types of DNA mutations including stopgain mutations at Ref C and Alt T with exonic variants on exons 10 and 11 and nonsynonymous SNV mutations at Ref A and Alt G with exonic variants with 10 and 11 exons and also at Alt T and Alt C with exonic mutations having 10 and 11 exons. All these shows amino acid change and deletions shown in the table. Tp53 gene is located on chromosome no 17. It also shows two types of DNA mutations including stopgain mutations at Ref. ACG and Alt nill, with exonic variants on exons 6 and 10 and nonsynonymous SNV mutations at Alt G and Alt A with exonic variants with 4,7and 8 exons. All these shows amino acid change and deletions shown in the table. CDH5 gene is located on chromosome no 16. It shows DNA mutations including frameshift deletion at Ref. CT and Alt. nill, with exonic variants on exon7. CDH8 gene is located on chromosome no 14 and shows nonsynonymous SNV mutations at Ref. C and Alt. A and Ref. T and Alt. A with exonic variants on exon 23 and 2. This also shows frameshift deletion at Ref. C and Alt. nill with exonic variants on exon 2. CDH10 gene is located on chromosome no 5 and shows nonframeshift deletion at Ref. GACGATGGAGAA and Alt. nill, and also frameshift deletion at Ref. GCCA and Alt. nill with exonic variants on exon 2. This also shows nonsynonymous SNV at Ref. G and Alt. T with exonic variants on exon 2. CDH12 gene is located on chromosome no 5 and shows nonsynonymous SNV at Ref. C and Alt. T, with exonic variants on exon 10, 12, 13, 14, 15, and 16. This also shows frameshift deletion at Ref. TC and nills. T with exonic variants on exon 7, 9, 10, 11, 12 and 13. CDH16 gene is located on chromosome no 16 and shows nonsynonymous SNV at Ref. A and Alt. C, with exonic variants on exon 3. CDH20 gene is located on chromosome no 18 and shows nonsynonymous SNV at Ref. C and Alt. A with exonic variants on exon 3. CDH23 gene is located on chromosome no 10 and shows synonymous SNV at Ref. T and Alt. C, with exonic variants on exon 6 and at Ref. C and Alt. R, with exonic variants on exon 10. This also shows frameshift deletion at Ref. CCACAGG and Alt. nill with exonic variants on exon 37. Synonymous SNV at Ref. C and Alt. T, with exonic variants on exon 14 and nonframeshift deletion at Ref. TTC and Alt. nill, with exonic variants on exon 9 and 54 were also observed. CDH24 gene is located on chromosome no 14 and shows synonymous SNV at Ref. A and Alt. G, with exonic variants on exon 3. The accession number of nucleotide sequences and amino acid change and deletion is also shown in the Table 2 in supplementary data. The observed mutation type is shown in Table 4 . Table 4 Shows detail of mutations in hereditary genes in both samples Sr. no Gene name Chromosome no. Mutation type Patient 1 Patient 2 1. ATM 11 Stopgain nonsynonymous SNV 2. TP53 17 Stopgain nonsynonymous SNV nonsynonymous SNV 3. CDH5 16 frameshift deletion nonsynonymous SNV nonframeshift substitution 4. CDH8 14 nonsynonymous SNV frameshift deletion 5. CDH10 5 nonframeshift deletion frameshift deletion nonsynonymous SNV 6. CDH12 5 nonsynonymous SNV frameshift deletion 7. CDH16 16 nonsynonymous SNV nonsynonymous SNV 8. CDH19 18 nonsynonymous SNV 9. CDH20 18 nonsynonymous SNV 10. CDH23 10 synonymous SNV synonymous SNV frameshift deletion frameshift deletion synonymous SNV nonframeshift deletion 11. CDH24 4 nonsynonymous SNV Graphically the exonic variants in sample 1 are shown in Fig. 2 . Further two genes with exonic variants were found in sample 2 containing TP53 and CDH (CDH5, CDH16, CDH19, and CDH23). The mutations type includes non-synonymous SNV, synonymous SNV, frameshift deletion and non-framesghift substitution in both samples TP53 gene is located on chromosome no 17 and shows nonsynonymous SNV at Ref. C and Alt. T, with exonic variants on exon 4, 7 and 8. CDH5 gene is located on chromosome no 16 and shows nonsynonymous SNV at Ref. T and Alt. C, with exonic variants on exon 10 and nonframeshift substitution at Ref. TC and Alt. CT, with exonic variants on exon 10. CDH16 gene is located on chromosome no 16 and shows nonsynonymous SNV at Ref. C and Alt. T, with exonic variants on exon 12 and 13. CDH19 gene is located on chromosome no 18 and shows nonsynonymous SNV at Ref. C and Alt. T, with exonic variants on exon 12. CDH23 gene is located on chromosome no 10 and shows frameshift deletion at Ref. CC and Alt. nill, with exonic variants on exon 6 and synonymous SNV at Ref. T and Alt. C, with exonic variants on exon 6. The accession number of nucleotide sequences and amino acid change and deletion is shown in the Table 3 in supplementary data. Graphically the exonic variants in sample 2 are shown in Fig. 3 . Exonic variants graph Whole exome sequencing (WES) was done to know the exonic variants in sample 1 and sample 2. The graph shows the mutations type which includes synonymous SNV, non-synonymous SNV, stopgain, stoploss, frameshift insertion, non-frameshift deletion, non frameshift insertion, frameshift deletion and non-framesghift substitution in both samples. This is shown in Fig. 4 . Nucleotide Sequences The nucleotide sequences of the obtained data are submitted in the online website ( https://www.ncbi.nlm.nih.gov/ ) and is available to public. Discussion This cohort was conducted in Jinnah Hospital Lahore, Pakistan to assess the histological characteristics and SNPs in the targeted genes which includes TP53, ATM and CDH. Indians and Pakistanis from Asian are the rising ethnic groups in US and have a greater rate of BC than Caucasians (Goggins, Wong, & Control, 2009 ; Rastogi et al., 2008 ). Their study on BC diagnoses by the SEER record for patients analyzed from 1988–2006 found higher frequency of BC in young females than 40 years of age related to Caucasians. It is likely the whole age dispersal of Asian females were young related to the other ethnic groups in the US, results in a unequal analysis by age (Kakarala, Rozek, Cote, Liyanage, & Brenner, 2010 ). This study was conducted in Pakistan during the time of 1 year from 2021 to 2022. During this study the age distribution of patients was compared below 50 years and above 50 years of age. This shows non-significant difference. During previous studies, the ecology of BC redefined into sets of different subtypes. Each shows details related with different usual histories, therapeutic consequences and diagnoses (Bauer, Brown, Cress, Parise, & Caggiano, 2007 ; Bertolo et al., 2008 ; Carey et al., 2006 ; Del Casar et al., 2008 ). Published study on BC in Indians of Asia did not study the occurrence of histological characteristics of BC invasive ductal, lobular and inflammatory carcinoma of the breast. Each type has diverse biological behavior and diagnosis (Ivshina et al., 2006 ; Rosenberg et al., 2006 ; Sims, Howell, Howell, & Clarke, 2007 ). Inflammatory BC, e.g., is the most violent subtype with poorer threat ratio for 5 years existence in their multivariate analysis and occurs more commonly among Indians belong to Asia than to Caucasians in their investigation. Lobular invasive carcinoma may found with bilateral diseases. The invasive ductal carcinoma is generally unilateral and threat of reappearance declines as time passes from primary analysis (Kakarala et al., 2010 ) In this study, during clinical investigation there was 1 patient with stage V and 1 with stage IV. There were 11 patients who were on stage III, and there were 7 patients who were at stage II. This shows that more number of people affected witht stgage III. In this study 16 patients were affected from invasive ductal carcinoma except 2 patients with Hodgkin lymphoma, 1 with Mallignant phyllodes tumor and 1 with Hidradenocarcinoma. This shows that more number of people affected with invasive breast carcinoma. Their SEER study demonstrate that invasive ductal carcinoma is more often diagnosed in Indians and Pakistani belongs to Asia females than to Caucasian females while analysis of lobular carcinoma is consistently lower (Kakarala et al., 2010 ). This study shows that more number of patients with invasive ductal carcinoma were found in Pakistan during 2021 to 2022. High proportion of BC in females of Asia than to Caucasians (30.6% vs. 21.8%, p < 0.0095) in their study was ER and PR negative (Kakarala et al., 2010 ). In this study, equal number of patients with ER/PR positive and ER/PR negative. This shows the odds ratio 1 and p value < 0.05 (i.e p-value equals to 1). This also shows non-significant differences. HER2 status was also observed. In this study 13 patients with HER2 negative and 5 patients with HER2 positive while 2 patients do not have this data. During their study they found the occurrence of deleterious BRCA1 and BRCA2 mutations of inherited BC ovarian cancer was 9.4% in Southern Chinese high-threat relatives (n Z 1427) through the combination of PCR-based Sanger sequencing, Next generation sequencing, and MLPA (Kwong et al., 2016). This study was conducted to know the amino acid change and deletions in the targeted genes including TP53, ATM and CDH in the breast cancer patients of Pakistan. This was performed by whole exome sequencing. They detect mutations by Next generation sequencing that was before missed by high resolution melting. According to them, this is the biggest study of genetic predisposition screening of BC described in population of China. Generally, 126 pathogenic variations were recognized in BRCA1, BRCA2 genes, furthermore, variations in TP53 and PTEN were noticed in 5 and 2 families, respectively. Comprehensive study of the mutational pattern exposed that 17 varieties of hotspot mutation were observed in their study, contributing 48.8% of all identified variations. This recommended about one-half of the Southern Chinese variations. They revealed that 9 population-specific single nucleotide polymorphisms from the normal study, which includes 8 in BRCA2 and 1 in BRCA1, found and beneficial in the classification of VUS (Kwong et al., 2016). Whole genome sequencing was done to identify the mutations or single nucleotide polymorphysims in TP53, ATM and CDH gene. In this study, amino acid change and deletions were observed in ATM gene on exone 10 and 11 in sample 1 shows stopgain and nonsynonymous SNV mutation type. Mutations in TP53 gene on exon 4, 6, 7, 8 and 10 in sample 1 shows shows stopgain and nonsynonymous SNV mutation type and on exon 4, 7 and 8 in sample 2 shows nonsynonymous SNV mutation type. In this study the variations were also observed in CDH gene including (CDH5, CDH8, CDH10, CDH12, CDH16, CDH20, CDH23 and CDH24) shows frameshift deletion, nonsynonymous SNV, nonframeshift deletion on exon 2, 3, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 23, 37 and 54 in sample 1. Mutations in CDH gene (CDH5, CDH16, CDH19 and CDH23) shows mutations like nonsynonymous SNV, nonframeshift substitution and frameshift deletion on exon 6, 10, 12 and 13 in sample 2. The most common used technique to show muutations of the TP53 gene is immunohistochemistry identifies only alterations that induce protein growth, frameshift deletion, nonsense and splice mutations. The TTGE/sequencing study noticed 15% of the TP53 alterations outside exons 5 to 8; associate the significance of examining the whole gene and not only exons 5 to 8 as reported in old studies (Langerød et al., 2007). During this study, mutations on exon 4, 6, 7, 8, and 10 of tp53 gene was observed in sample 1 and on exon 4, 7 and 8 in sample 2. Conclusion It is concluded that in Pakistani population more number of patients were observed having invasive ductal breast carcinoma. The people with ER/PR positive and negative were equal in number of total 19 patients. People with HER2 positive and negative were observed. This shows the triple negative breast cancer and HER2 overexpressed in patients. Whole exome sequencing shows that there were different type of mutations includes synonymous SNV, non-synonymous SNV, stopgain, non-frameshift deletion, frameshift deletion and non-frameshift substitution in different exonic regions of genes including TP53, ATM and CDH. The accession numbers and amino acid change and deletions were also observed in patients. For exome study on breast cancer alterations there is a need of more data and vast investigation. Declarations Acknowledgment Authors are thankful to Mr. Asad Nawaz and hospital management for helping during the whole work. Funding Not applicable Competing interests Authors share no competing interests Author contributions All authors participated to the study conception and design. Material preparation, data collection and analysis were performed by Yasir Nawaz, Ali Zaib Khan and Fouzia Tanvir. The first draft of the manuscript was written by Yasir Nawaz and all authors commented on previous file of manuscript. All authors read and approved the final manuscript. Data Availability Data will be available on the demand of authors. The data including accession numbers will be available on the website https://www.ncbi.nlm.nih.gov/ . Ethics approval This study was performed in accordance to the Declaration of Helsinki. Approval was obtained by the Ethical review board of Allama Iqbal Medical College/Jinnah Hospital Lahore, Punjab, Pakistan on dated: 17/02/2022 with reference no. 194/23/12/2021/S2 ERB. Consent to participate Informed consent was signed from patients during data collection. Consent to publish Informed consent was signed from patients to publish data in journals. References Baenziger, M., Baierl, M., Devanathan, K., Eswaran, S., Fu, P., Gschwend, B., . . . Langlois, A. (2020). 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Ö., Adamson, P., & Cingi, C. (2012). Epidemiology and economic burden of nonmelanoma skin cancer. Facial plastic surgery clinics of North America, 20 (4), 419-422. Carey, L. A., Perou, C. M., Livasy, C. A., Dressler, L. G., Cowan, D., Conway, K., . . . Edmiston, S. J. J. (2006). Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA, 295 (21), 2492-2502. doi:doi:10.1001/jama.295.21.2492 Cokkinides, V., Albano, J., Samuels, A., Ward, M., & Thum, J. (2005). American cancer society: Cancer facts and figures. Atlanta: American Cancer Society . Cybulski, C., Wokołorczyk, D., Jakubowska, A., Huzarski, T., Byrski, T., Gronwald, J., . . . Blecharz, P. (2011). Risk of breast cancer in women with a CHEK2 mutation with and without a family history of breast cancer. Journal of Clinical Oncology, 29 (28), 3747-3752. doi:DOI: 10.1200/JCO.2010.34.0778 Del Casar, J., Martin, A., Garcia, C., Corte, M., Alvarez, A., Junquera, S., . . . Biology, R. (2008). Characterization of breast cancer subtypes by quantitative assessment of biological parameters: relationship with clinicopathological characteristics, biological features and prognosis. European Journal of Obstetrics & Gynecology and Reproductive Biology, 141 (2), 147-152. doi:https://doi.org/10.1016/j.ejogrb.2008.07.021 Dubas, L. E., & Ingraffea, A. (2013). Nonmelanoma skin cancer. Facial Plastic Surgery Clinics, 21 (1), 43-53. doi:https://doi.org/10.1016/S0140-6736(09)61196-X Dwivedi, M. A Perspective Review on Cancer–The Deadliest Disease. International Journal of Cancer, 1 (1). Ellisen, L. W., & Haber, D. A. (1998). Hereditary breast cancer. Annual review of medicine, 49 (1), 425-436. Engstrøm, M. J., Opdahl, S., Hagen, A. I., Romundstad, P. R., Akslen, L. A., Haugen, O. A., . . . treatment. (2013). Molecular subtypes, histopathological grade and survival in a historic cohort of breast cancer patients. 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V., George, J., Senko, O., Mow, B., Putti, T. C., Smeds, J., . . . Nordgren, H. J. C. r. (2006). Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer. Cancer Res, 66 (21), 10292-10301. doi:https://doi.org/10.1158/0008-5472.CAN-05-4414 Joshi, M., & Deshpande, J. J. I. J. o. B. R. (2010). Polymerase chain reaction: methods, principles and application. International Journal of Biomedical Research, 2 (1), 81-97. Kakarala, M., Rozek, L., Cote, M., Liyanage, S., & Brenner, D. E. J. B. c. (2010). Breast cancer histology and receptor status characterization in Asian Indian and Pakistani women in the US-a SEER analysis. BMC Cancer volume, 10 (1), 1-8. doi:https://doi.org/10.1186/1471-2407-10-191 Köchl, S., Niederstätter, H., & Parson, W. (2005). DNA extraction and quantitation of forensic samples using the phenol-chloroform method and real-time PCR. In Forensic DNA typing protocols (pp. 13-29): Springer. Kwong, A., Shin, V. Y., Au, C. H., Law, F. B., Ho, D. N., Ip, B. K., . . . Choy, G. J. T. J. o. M. D. (2016). Detection of germline mutation in hereditary breast and/or ovarian cancers by next-generation sequencing on a four-gene panel. The Journal of Molecular Diagnostics, 18 (4), 580-594. doi:https://doi.org/10.1016/j.jmoldx.2016.03.005 Langerød, A., Zhao, H., Borgan, Ø., Nesland, J. M., Bukholm, I. R., Ikdahl, T., . . . Jeffrey, S. S. J. B. c. r. (2007). TP53mutation status and gene expression profiles are powerful prognostic markers of breast cancer. Breast Cancer Research volume, 9 (3), 1-16. doi:https://doi.org/10.1186/bcr1675 Lipponen, P., Aaltomaa, S., Kosma, V.-M., & Syrjänen, K. J. E. J. o. C. (1994). Apoptosis in breast cancer as related to histopathological characteristics and prognosis. European Journal of Cancer, 30 (14), 2068-2073. doi:https://doi.org/10.1016/0959-8049(94)00342-3 Lipton, R., Schwedt, T., & Friedman, B. (2016). GBD 2015 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2017 Jan 5; 388 (10053): 1545–602. doi:. PMID: 27733282.[PubMed: 27733282][Cross Ref]. Onitilo, A. A., Engel, J. M., Greenlee, R. T., Mukesh, B. N. J. C. m., & research. (2009). Breast cancer subtypes based on ER/PR and Her2 expression: comparison of clinicopathologic features and survival. Clinical medicine and research, 7 (1-2), 4-13. doi:doi: 10.3121/cmr.2008.825 Rastogi, T., Devesa, S., Mangtani, P., Mathew, A., Cooper, N., Kao, R., & Sinha, R. J. I. J. o. E. (2008). Cancer incidence rates among South Asians in four geographic regions: India, Singapore, UK and US. International Journal of Epidemiology, 37 (1), 147-160. doi:https://doi.org/10.1093/ije/dym219 Regitha, R., Parthasarathy, V., & Balakrishnan, N. (2021). Cancer Protective effect of Brassicca nigra and Role of its Chemical Constituents. Research Journal of Pharmacy and Technology, 14 (2), 1115-1121. Rosenberg, L. U., Magnusson, C., Lindström, E., Wedrén, S., Hall, P., & Dickman, P. W. J. B. C. R. (2006). Menopausal hormone therapy and other breast cancer risk factors in relation to the risk of different histological subtypes of breast cancer: a case-control study. Breast Cancer Research, 8 (1), 1-13. doi:https://doi.org/10.1186/bcr1378 Sambrook, J., & Russell, D. W. J. C. S. H. P. (2006). Purification of nucleic acids by extraction with phenol: chloroform. Cold Spring Harb Protoc, 2006 (1), pdb. prot4455. doi:doi:10.1101/pdb.prot4455 Saslow, D., Hannan, J., Osuch, J., Alciati, M. H., Baines, C., Barton, M., . . . Gaumer, G. (2004). Clinical breast examination: practical recommendations for optimizing performance and reporting. CA: a cancer journal for clinicians, 54 (6), 327-344. doi:https://doi.org/10.3322/canjclin.54.6.327 Sciacovelli, M., Schmidt, C., Maher, E. R., & Frezza, C. (2020). Metabolic drivers in hereditary cancer syndromes. Annual Review of Cancer Biology, 4 , 77-97. doi:https://doi.org/10.1146/annurev-cancerbio-030419-033612 Sims, A. H., Howell, A., Howell, S. J., & Clarke, R. B. J. N. C. P. O. (2007). Origins of breast cancer subtypes and therapeutic implications. Nature Clinical Practice Oncology volume, 4 (9), 516-525. doi:https://doi.org/10.1038/ncponc0908 Sun, J., Meng, H., Yao, L., Lv, M., Bai, J., Zhang, J., . . . Wang, T. J. C. C. R. (2017). Germline Mutations in Cancer Susceptibility Genes in a Large Series of Unselected Breast Cancer PatientsMutations in Cancer Susceptibility Genes in Breast Cancer. Clinical Cancer Res, 23 (20), 6113-6119. doi:https://doi.org/10.1158/1078-0432.CCR-16-3227 Wang, C., Zhang, J., Wang, Y., Ouyang, T., Li, J., Wang, T., . . . Xie, Y. J. A. o. O. (2015). Prevalence of BRCA1 mutations and responses to neoadjuvant chemotherapy among BRCA1 carriers and non-carriers with triple-negative breast cancer. Annals of Oncology, 26 (3), 523-528. doi:https://doi.org/10.1093/annonc/mdu559 Wang, H., Naghavi, M., Allen, C., Barber, R. M., Bhutta, Z. A., Carter, A., . . . Coates, M. M. (2016). Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. The lancet, 388 (10053), 1459-1544. doi:https://doi.org/10.1016/S0140-6736(16)31012-1 Waye, J., Presley, L., Budowle, B., Shutler, G., & Fourney, R. J. B. (1989). A simple and sensitive method for quantifying human genomic DNA in forensic specimen extracts. Europe PMC, 7 (8), 852-855. Zhang, Y., Sun, L.-P., Xing, C.-Z., Xu, Q., He, C.-Y., Li, P., . . . Yuan, Y. (2012). Interaction between GSTP1 Val allele and H. pylori infection, smoking and alcohol consumption and risk of gastric cancer among the Chinese population. PLOS one . doi:https://doi.org/10.1371/journal.pone.0047178 Additional Declarations No competing interests reported. Supplementary Files SUPPLEMENTARYDATA2.docx 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-2411036","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":162755532,"identity":"2c374833-298d-44d2-acda-614794253e81","order_by":0,"name":"Yasir 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electrophoresis of extracted DNA\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-2411036/v1/56083a87c4ef91c63ac2d742.png"},{"id":31028540,"identity":"cbb1d6fd-9043-4135-acbf-bb55d7ca3acf","added_by":"auto","created_at":"2023-01-03 14:49:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":36506,"visible":true,"origin":"","legend":"\u003cp\u003eShows exonic variants in sample 1\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-2411036/v1/bf1934c9903f136245f9c380.png"},{"id":31026817,"identity":"26f5356f-1259-40c0-adf3-379951579754","added_by":"auto","created_at":"2023-01-03 14:41:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":25841,"visible":true,"origin":"","legend":"\u003cp\u003eShows the exonic variant in sample 2\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-2411036/v1/0526a69ab806c042ac07a869.png"},{"id":31026815,"identity":"a87b0b38-a933-47f6-94b4-e33ccd0fa310","added_by":"auto","created_at":"2023-01-03 14:41:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":39053,"visible":true,"origin":"","legend":"\u003cp\u003eShows the summary of Exonic variants across samples\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-2411036/v1/7dcc963f8d2f94f8026b9da9.png"},{"id":32993863,"identity":"bf5c7a48-ad24-492d-a165-f8493c89c96b","added_by":"auto","created_at":"2023-02-15 17:44:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":537378,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2411036/v1/2de0a7eb-d3e5-4dee-890c-fd867c7b96f1.pdf"},{"id":31026816,"identity":"b2f115c8-bcba-4557-828e-b4b7db8b3065","added_by":"auto","created_at":"2023-01-03 14:41:22","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":23480,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPLEMENTARYDATA2.docx","url":"https://assets-eu.researchsquare.com/files/rs-2411036/v1/4014e6a681710ba4a5b36237.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Research of histological characteristics and single nucleotide polymorphisms in hereditary genes among Pakistani breast cancer patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCancer is a type which involves irregular progression of cells with the capacity to enter and move to other portions of body (Dwivedi; Fleisch, Franz, \u0026amp; Herrmann, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). On contrary, benign tumors do not move to other parts. In male, most common types of cancers are lung cancer, prostate cancer, colorectal cancer, and oesophageal cancer (Baenziger et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In women, BC, colorectal cancer, lung cancer, and cervical cancer is significant (Regitha, Parthasarathy, \u0026amp; Balakrishnan, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). 40% cases will be expected if skin cancer added (Cakir, Adamson, \u0026amp; Cingi, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Dubas \u0026amp; Ingraffea, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Cancer threat rises considerably with age, and various occurs more frequently in developing countries (Regitha et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt is 2nd important reason of death in U.S and most common in Pakistani females (Cokkinides, Albano, Samuels, Ward, \u0026amp; Thum, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Gilani, Kamal, \u0026amp; Akhter, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). The age related cancer mortality increases in U.S. people. Cancer is characterized into 4 stages (I, II, III, and IV). Stage I specifies the initial infection and stage IV is progressive stage of infection (Gilani et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). TNM method is used to grade BC. It shows the mass of tumors (T), tumors might spreads to lymph nodes (N) in armpits, and the tumors has metastasized (M) (i.e., spreads to other parts of body) (Saslow et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). In 2015, about 90.5\u0026nbsp;million patients had cancer (Lipton, Schwedt, \u0026amp; Friedman, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In 2019, about 18\u0026nbsp;million fresh patients were diagnosed (Sciacovelli, Schmidt, Maher, \u0026amp; Frezza, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Yearly, it causes 8.8\u0026nbsp;million cancer mortality (15.7%) (H. Wang et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBRCA1, BRCA2, p53, and PTEN/MMAC1 are the highly penetrant genes that are firstly found in those people who have large family history of breast cancer. Some other genes which are less mutated and cause low risk of breast cancer also find out. Low penetrant genes are the ataxia telangiectasia gene ATM and the HRAS1 (Ellisen \u0026amp; Haber, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). About 5\u0026ndash;10% of BC are supposed to be inherited that are affected by irregular genes. Studies shows that females with a family history of BC have more threat of developing BC. The alterations responsible for increasing BC threat in families are documented. These include alterations in ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, MLH1, MRE11, MSH2, MSH6, MUTYH, NBN, PALB2, PMS1, PMS2, PTEN, RAD50, RAD51C, STK11 and TP53 genes. These infrequent alterations are perhaps dispersed to a small percentage (2\u0026ndash;5%) of BC cases (Cybulski et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Germline alterations of high penetrance BC susceptibility genes like BRCA1, BRCA2, TP53, CHEK2, ATM, PTEN and PPM1D deliberate a high threat of developing HBC (Cybulski et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In recent times, it was found that alterations in PPM1D gene are related with an increased threat of BC and females with PPM1D alterations have 20% chances of developing BC. In many BC causing genes one copy of alteration is hereditary and occurs in every part and the second copy of altered gene occurs in the tumors itself, but interestingly PPM1D alterations were not hereditary, and found only in red blood cells.\u003c/p\u003e \u003cp\u003eSNPs are one of the majority frequent types of genetic changes in the human genome. Single nucleotide polymorphisms in the genes which normalize DNA variance mend, cell cycle regulation, immunity and metabolism are connected with genetic defenselessness to cancer. From an experimental perspective, Single nucleotide polymorphisms are possible diagnostic and therapeutic biomarkers in most of the cancer types (Zhang et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The purpose of this study was to characterize how rare histological characteristics vary in their stages, size, lymph node status, estrogen and progesterone receptors (ER)/PR status, and grade of BC patients from Pakistan and to analyze the somatic mutations in the breast tissues.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEthics Statement and consent to participate\u003c/h2\u003e \u003cp\u003e The study was conducted in according to the Declaration of Helsinki. The written consent form was signed from all patients under study. This study was permitted by the Institutional Review Board of the Jinnah Hospital Lahore/ Allama Iqbal Medical College Lahore.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSite And Population Selection\u003c/h3\u003e\n\u003cp\u003eBreast tissue samples were collected from Jinnah hospital Lahore, Pakistan. The study duration was from March 2021 to March 2022.\u003c/p\u003e \u003cp\u003eThe population under study includes breast cancer patients having characteristics of hereditary breast cancer which includes: (i) analysed with BC and another primary cancer, (ii) with family history which includes at least 2 cases of BC in 1st and 2nd degree relatives (iii) bilateral breast cancer and (iv) breast cancer identification earlier the age of 40 years (Sun et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFamilial breast cancer includes those people who had history of BC. Early onset breast cancer (EBC) included those patients who do not have any history of BC and were identified at or earlier the age of 40 years, sporadic breast cancer (SBC) included those patients who do not have a family history of BC and were identified above the age of 40 years (Sun et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTumor size is the maximum tumor diameter which is measured by ultrasound during analysis. The tumors were classified in accordance to the modified Bloom\u0026ndash;Richardson system. Estrogen receptors (ER), progesterone receptors (PR), and human epidermal growth factor receptors 2 (HER2) status were obtained by using the breast tumor tissue acquired from a core needle biopsy and from surgery (C. Wang et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eImmunohistochemistry (Ihc)\u003c/h3\u003e\n\u003cp\u003eHistopathological investigation was done by pathologists. To regulate the expressions of hormone receptors comprising of estrogen receptors ER and progesterone receptors PR, and the epidermal growth factor receptor 2 (HER2) in a 5\u0026micro;m formalin- embeded, paraffin- fixed tumor section. IHC test was achieved the standard protocol (Engstr\u0026oslash;m et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Lipponen, Aaltomaa, Kosma, \u0026amp; Syrj\u0026auml;nen, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1994\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe IHC grouping offers both helpful and predictive evidence. In this study BC was classified into four groups on the basis of immunohistochemistry profile ER, PR and Her2/neu expression, positive (+) or negative (-). The groups include:\u003c/p\u003e \u003cp\u003eER/PR+,Her2\u0026thinsp;+\u0026thinsp;=\u0026thinsp;ER+/PR+,Her2+; ER-/PR+,Her2+; ER+/PR-,Her2+\u003c/p\u003e \u003cp\u003eER/PR+,Her2- = ER+/PR+,Her2-; ER-/PR+,Her2-; ER+/PR-,Her2\u003c/p\u003e \u003cp\u003eER/PR-,Her2\u0026thinsp;+\u0026thinsp;=\u0026thinsp;ER-/PR-,Her2+\u003c/p\u003e \u003cp\u003eER/PR-,Her2- = ER-/PR-,Her2-\u003c/p\u003e \u003cp\u003eThese are classified as: ER/PR+,Her2\u0026thinsp;+\u0026thinsp;called Luminal B, ER/PR+,Her2- called Luminal A and ER/PR-,Her2\u0026thinsp;+\u0026thinsp;and ER/PR-, Her2- called triple negative/basal-like tumor.1 in the absence of tissue sample, it was difficult to identify the classification by IHC (Onitilo, Engel, Greenlee, Mukesh, \u0026amp; research, 2009).\u003c/p\u003e\n\u003ch3\u003eDna Extraction\u003c/h3\u003e\n\u003cp\u003ePhenol chloroform or Organic technique was used to extract DNA. 20 mg of Breast tissue sample was chosen from each sample and regulated in 500\u0026micro;l of lysis solution and incubate it for 20 to 30min at room temperature. Samples were mixed moderately to confirm the suitable homogenization. Centrifugation was done on samples for 3 minute at 13000 rpm for phase separation. The supernatant was cast-off while the pellet holding DNA was further treated with multiple washings by lysis solution were completed to avoid impurity. Pellet was again treated by 400 \u0026micro;l lysis solution, 13 \u0026micro;l of 20% SDS and 25 \u0026micro;l proteinase K. Samples were incubated at 37\u003csup\u003e◦\u003c/sup\u003e C whole night.\u003c/p\u003e \u003cp\u003eThe samples were then treating for the complete cell digestion. Then processed with 500 \u0026micro;l of phenol, chloroform and isoamyl alcohol (i.e. P:CI solution). The suspended solution was centrifuged at 13000 rpm for 10 minutes for moderate and through mixing. Aqueous phase was transported to another tube to purify and separate the DNA. The aqueous layer was processed with 500 \u0026micro;l of chloroform and isoamyl alcohol (C:I, 24:1) and centrifuged for 10 minutes at 13000 rpm. The aqueous layer was trsnported into 1.5 ml centrifuge tube, 55 \u0026micro;l of sodium acetate and 500 \u0026micro;l of chilled isopropanol were added. Samples were incubated for 45 minutes at -20\u003csup\u003e\u0026deg;\u003c/sup\u003e C. Then the samples were centrifuged at 13000 rpm for 10 minutes. Supernatant was removed and pellet was processed with 500 \u0026micro;l of 70% ethanol and centrifuged at 7500 rpm for 5 minutes for the purpose to remove impurities, pellet was reserved while supernatant was removed and then dry in air. DNA pellet was resuspended in TE Buffer (Tris EDTA) and stored at 4\u003csup\u003e◦\u003c/sup\u003eC (K\u0026ouml;chl, Niederst\u0026auml;tter, \u0026amp; Parson, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Sambrook \u0026amp; Russell, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eAgarose Gel Electrophoresis:\u003c/h2\u003e \u003cp\u003eThis was done by using 1% agarose gel which contains 1 gram of agarose mixed in 100 ml of 1X TAE buffer (Tris Acetic acid EDTA). Clear solution was obtained after heating. 7 \u0026micro;l Ethidium Bromide mixed in gel solution. Gel was transferred into the gel casting tray with injecting combs. After solidification, gel caster was transported to gel tank having 1X TAE buffer and combs were detached carefully. 7 \u0026micro;l of obtained DNA was mixed with 3 \u0026micro;l of 6X bromophenol blue dye (called loading dye) loaded in wells. The gel was run in exact constraints included 500 mA of current with 75 volts for 1 hour. Gel was pictured under UV Trans-Illuminator bio Doc Analyzer (Ghatak, Muthukumaran, \u0026amp; Nachimuthu, 2013; Joshi \u0026amp; Deshpande, 2010).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDna Quantification\u003c/h3\u003e\n\u003cp\u003eThe quantity of DNA was calculated by using Thermo scientific Multi Skan Go Apparatus. 260/280 ratio showed the quality whereas concentration is shown in ng/ul (Waye, Presley, Budowle, Shutler, \u0026amp; Fourney, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1989\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eWhole Exome Sequencing (Wes)\u003c/h3\u003e\n\u003cp\u003eWES is an inexpensive alternate method to whole genome sequencing, as it marks only the protein coding regions of the human genome answerable for many known disease associated variants. It is helpful whether in directing trainings in infrequent mendelian disorders, complex diseases, cancer research, or human population studies, human whole exome sequencing gives a good quality, reasonable, and suitable solution. The results of WES include:\u003c/p\u003e \u003cp\u003eIdentify variants across a widespread range of submissions\u003c/p\u003e \u003cp\u003eAttains complete exposure of coding regions\u003c/p\u003e \u003cp\u003eDelivers an inexpensive alternate to WES containing less data of 4 to 5 GB than 90 GB\u003c/p\u003e \u003cp\u003eCreates a small, more convenient data set for quicker, informal data investigation associated to whole-genome methods\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed in Microsoft excel 2010.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThis study was conducted from Jinnah hospital to collect breast tissue samples during surgery. The informed consent was signed by the patient. Six samples were collected from patients. Data was collected related to the study which includes histopathological reports of all patients. Out of these seven samples WES was performed on two patients. The hereditary genes TP53, ATM and CDH were selected to find the somatic mutation sites by whole exome sequencing.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemistry\u003c/h2\u003e \u003cp\u003eThe data was collected from Jinnah hospital Lahore. This study includes 19 patients in which 1 was male and remaining 18 were female. The data collected during the interview session includes cancer type and subtype, age, gender, number of tumors, location of tumors, TNM_stage, ER, PR, and (HER2) status of patients. The age of all patients varies from 27 to 73 years. There were different number of tumors which includes 1, 2, 3, 11 and sometimes 15 in patients under study. The metastatic site includes the location of tumor which shows that the tumor was collected from either left side of breast or right side of breast. Tumor was collected from left side of breast in some patients and in some from right side of breast. The detailed study is shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e in supplementary data.\u003c/p\u003e \u003cp\u003eThe TNM_Stage varies from patients to patients. Some patients have grade II, III, IV and IV. Some patient\u0026rsquo;s shows triple negative breast cancer type and some shows HER2 overexpressed. The cancer type includes the patients with Invasive ductal carcinoma and very rarely shows Hidradenocarcinoma and Hodgkin lymphoma. Two patients in this study do not have complete information. This is shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e in supplementary data.\u003c/p\u003e \u003cp\u003eThe status of ER, PR and HER-2 varies among patients. In some patients all shows negative which indicates the subtype is triple negative. In patients with both negative ER, PR and positive HER-2 and also if both ER, PR positive and HER-2 negative indicates HER-2 overexpressed. If both the ER, PR positive and HER-2 negative then it is called luminal A type of BC.\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\u003eShows the characteristics of breast cancer patients\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=\"char\" char=\".\" 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\u003eID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge in years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNumber of tumors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor location\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTNM_Stage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eER\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eHER2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSubtypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eCancer type\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor Right side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTriple Negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor_Left side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHER2-overexpressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor_Left side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTriple Negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor_Left side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTriple Negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor Right side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTriple Negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor_Left side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTriple Negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor Right side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHER2-overexpressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor_Left side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHER2-overexpressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eHodgkin lymphoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor_Left side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTriple Negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor_Left side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHER2-overexpressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor Right side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTriple Negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor_Left side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHER2-overexpressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor_Left side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHER2-overexpressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor Right side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003enill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003enill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003enill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eMallignant phyllodes tumor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor Right side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTriple Negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003enill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor Right side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003enill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003enill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003enill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003enill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eHodgkin lymphoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor_Left side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTriple Negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor_Left side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHER2-overexpressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient 19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTumor_Left side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHER2-overexpressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvasive ductal carcinoma\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\n\u003ch3\u003eAge Distribution\u003c/h3\u003e\n\u003cp\u003eIn this study, the data collected from patients includes 1 male and 18 female with two age groups below 50 and above 50 years of age. The p-value shows 0.45 i.e\u0026thinsp;\u0026gt;\u0026thinsp;0.05 which indicates the difference was non-significant. This is shown in Table \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\u003eShows the age distribution of Breast cancer patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 and below 50\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAbove 50\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\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\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eDescriptive analysis\u003c/h2\u003e \u003cp\u003eDescriptive analysis includes different values on the basis of age. The mean of age was 48.2, standard error was 2.86, median and mode was 45. The standard deviation of the age shows 12.79, sample variance was 163.64. The range, minimum and maximum values were 46, 27 and 73 respectively. The total samples were 19 patients in this study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eER/PR status of breast cancer patients\u003c/h2\u003e \u003cp\u003eThe table shows the odds ratio and p-value of collected data. The ER/PR shows equal number of patients with positive and equal number with negative. This shows the non-significant difference and odds ratio equal to 1. 2 patients do not have this data. This is shown in Table \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\u003eShows the ER/PR status of patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eER\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\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\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\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=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eDNA Extraction and Agarose gel electrophoresis\u003c/h2\u003e \u003cp\u003eDNA was extracted from 6 tissue samples. Two of these were lost during the research and the DNA from remaining four samples including sample 3, 4, 5 and 6 extracted were run into gel is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Phenol chloroform (Organic) technique was employed to extract DNA. This was done by 1% agarose gel and configuration includes 1 gram of agarose mixed in 100 ml of 1X TAE buffer (Tris Acetic acid EDTA). For gel electrophoresis 1KB ladder was laden in 1st well with DNA sample in next well. DNA is of highly complete and of more than 20kb size. This is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eDNA quantification\u003c/h2\u003e \u003cp\u003eThe DNA quantity was measured by using Thermo scientific Multi Skan Go Instrument. 260/280 ratio showed the quality whereas concentration is shown in ng/ul. (i.e., 1.81\u0026ndash;1.88).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eWhole exome sequencing (WES) and Exonic variant analysis\u003c/h2\u003e \u003cp\u003eThe 3 genes were targeted in sample 1 including ATM, TP53 and CDH (CDH5, CDH8, CDH10, CDH12, CDH16, CDH20, CDH23 and CDH24). The mutation types includes synonymous SNV, non-synonymous SNV, stopgain, non-frameshift deletion, frameshift deletion and non-framesghift substitution in sample 1\u003c/p\u003e \u003cp\u003eIt was found that ATM gene is located on chromosome no 11. This shows two types of DNA mutations including stopgain mutations at Ref C and Alt T with exonic variants on exons 10 and 11 and nonsynonymous SNV mutations at Ref A and Alt G with exonic variants with 10 and 11 exons and also at Alt T and Alt C with exonic mutations having 10 and 11 exons. All these shows amino acid change and deletions shown in the table.\u003c/p\u003e \u003cp\u003eTp53 gene is located on chromosome no 17. It also shows two types of DNA mutations including stopgain mutations at Ref. ACG and Alt nill, with exonic variants on exons 6 and 10 and nonsynonymous SNV mutations at Alt G and Alt A with exonic variants with 4,7and 8 exons. All these shows amino acid change and deletions shown in the table.\u003c/p\u003e \u003cp\u003eCDH5 gene is located on chromosome no 16. It shows DNA mutations including frameshift deletion at Ref. CT and Alt. nill, with exonic variants on exon7. CDH8 gene is located on chromosome no 14 and shows nonsynonymous SNV mutations at Ref. C and Alt. A and Ref. T and Alt. A with exonic variants on exon 23 and 2. This also shows frameshift deletion at Ref. C and Alt. nill with exonic variants on exon 2.\u003c/p\u003e \u003cp\u003eCDH10 gene is located on chromosome no 5 and shows nonframeshift deletion at Ref. GACGATGGAGAA and Alt. nill, and also frameshift deletion at Ref. GCCA and Alt. nill with exonic variants on exon 2. This also shows nonsynonymous SNV at Ref. G and Alt. T with exonic variants on exon 2. CDH12 gene is located on chromosome no 5 and shows nonsynonymous SNV at Ref. C and Alt. T, with exonic variants on exon 10, 12, 13, 14, 15, and 16. This also shows frameshift deletion at Ref. TC and nills. T with exonic variants on exon 7, 9, 10, 11, 12 and 13.\u003c/p\u003e \u003cp\u003eCDH16 gene is located on chromosome no 16 and shows nonsynonymous SNV at Ref. A and Alt. C, with exonic variants on exon 3. CDH20 gene is located on chromosome no 18 and shows nonsynonymous SNV at Ref. C and Alt. A with exonic variants on exon 3.\u003c/p\u003e \u003cp\u003eCDH23 gene is located on chromosome no 10 and shows synonymous SNV at Ref. T and Alt. C, with exonic variants on exon 6 and at Ref. C and Alt. R, with exonic variants on exon 10. This also shows frameshift deletion at Ref. CCACAGG and Alt. nill with exonic variants on exon 37. Synonymous SNV at Ref. C and Alt. T, with exonic variants on exon 14 and nonframeshift deletion at Ref. TTC and Alt. nill, with exonic variants on exon 9 and 54 were also observed. CDH24 gene is located on chromosome no 14 and shows synonymous SNV at Ref. A and Alt. G, with exonic variants on exon 3. The accession number of nucleotide sequences and amino acid change and deletion is also shown in the Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e in supplementary data. The observed mutation type is shown in Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eShows detail of mutations in hereditary genes in both samples\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSr. no\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGene name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChromosome no.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMutation type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003ePatient 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePatient 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStopgain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003enonsynonymous SNV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTP53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStopgain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003enonsynonymous SNV\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003enonsynonymous SNV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCDH5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eframeshift deletion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003enonsynonymous SNV\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\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 \u003cp\u003enonframeshift substitution\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCDH8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003enonsynonymous SNV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003eframeshift deletion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCDH10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003enonframeshift deletion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003eframeshift deletion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003enonsynonymous SNV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCDH12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003enonsynonymous SNV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003eframeshift deletion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCDH16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003enonsynonymous SNV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003enonsynonymous SNV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCDH19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003enonsynonymous SNV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCDH20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003enonsynonymous SNV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCDH23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003esynonymous SNV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003esynonymous SNV\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eframeshift deletion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eframeshift deletion\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003esynonymous SNV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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 \u003cp\u003enonframeshift deletion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCDH24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003enonsynonymous SNV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eGraphically the exonic variants in sample 1 are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurther two genes with exonic variants were found in sample 2 containing TP53 and CDH (CDH5, CDH16, CDH19, and CDH23). The mutations type includes non-synonymous SNV, synonymous SNV, frameshift deletion and non-framesghift substitution in both samples\u003c/p\u003e \u003cp\u003eTP53 gene is located on chromosome no 17 and shows nonsynonymous SNV at Ref. C and Alt. T, with exonic variants on exon 4, 7 and 8.\u003c/p\u003e \u003cp\u003eCDH5 gene is located on chromosome no 16 and shows nonsynonymous SNV at Ref. T and Alt. C, with exonic variants on exon 10 and nonframeshift substitution at Ref. TC and Alt. CT, with exonic variants on exon 10. CDH16 gene is located on chromosome no 16 and shows nonsynonymous SNV at Ref. C and Alt. T, with exonic variants on exon 12 and 13. CDH19 gene is located on chromosome no 18 and shows nonsynonymous SNV at Ref. C and Alt. T, with exonic variants on exon 12. CDH23 gene is located on chromosome no 10 and shows frameshift deletion at Ref. CC and Alt. nill, with exonic variants on exon 6 and synonymous SNV at Ref. T and Alt. C, with exonic variants on exon 6. The accession number of nucleotide sequences and amino acid change and deletion is shown in the Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e in supplementary data.\u003c/p\u003e \u003cp\u003eGraphically the exonic variants in sample 2 are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eExonic variants graph\u003c/h2\u003e \u003cp\u003eWhole exome sequencing (WES) was done to know the exonic variants in sample 1 and sample 2. The graph shows the mutations type which includes synonymous SNV, non-synonymous SNV, stopgain, stoploss, frameshift insertion, non-frameshift deletion, non frameshift insertion, frameshift deletion and non-framesghift substitution in both samples. This is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eNucleotide Sequences\u003c/h3\u003e\n\u003cp\u003eThe nucleotide sequences of the obtained data are submitted in the online website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and is available to public.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis cohort was conducted in Jinnah Hospital Lahore, Pakistan to assess the histological characteristics and SNPs in the targeted genes which includes TP53, ATM and CDH.\u003c/p\u003e \u003cp\u003eIndians and Pakistanis from Asian are the rising ethnic groups in US and have a greater rate of BC than Caucasians (Goggins, Wong, \u0026amp; Control, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Rastogi et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Their study on BC diagnoses by the SEER record for patients analyzed from 1988\u0026ndash;2006 found higher frequency of BC in young females than 40 years of age related to Caucasians. It is likely the whole age dispersal of Asian females were young related to the other ethnic groups in the US, results in a unequal analysis by age (Kakarala, Rozek, Cote, Liyanage, \u0026amp; Brenner, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). This study was conducted in Pakistan during the time of 1 year from 2021 to 2022. During this study the age distribution of patients was compared below 50 years and above 50 years of age. This shows non-significant difference.\u003c/p\u003e \u003cp\u003eDuring previous studies, the ecology of BC redefined into sets of different subtypes. Each shows details related with different usual histories, therapeutic consequences and diagnoses (Bauer, Brown, Cress, Parise, \u0026amp; Caggiano, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Bertolo et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Carey et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Del Casar et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Published study on BC in Indians of Asia did not study the occurrence of histological characteristics of BC invasive ductal, lobular and inflammatory carcinoma of the breast. Each type has diverse biological behavior and diagnosis (Ivshina et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Rosenberg et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Sims, Howell, Howell, \u0026amp; Clarke, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Inflammatory BC, e.g., is the most violent subtype with poorer threat ratio for 5 years existence in their multivariate analysis and occurs more commonly among Indians belong to Asia than to Caucasians in their investigation. Lobular invasive carcinoma may found with bilateral diseases. The invasive ductal carcinoma is generally unilateral and threat of reappearance declines as time passes from primary analysis (Kakarala et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2010\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eIn this study, during clinical investigation there was 1 patient with stage V and 1 with stage IV. There were 11 patients who were on stage III, and there were 7 patients who were at stage II. This shows that more number of people affected witht stgage III. In this study 16 patients were affected from invasive ductal carcinoma except 2 patients with Hodgkin lymphoma, 1 with Mallignant phyllodes tumor and 1 with Hidradenocarcinoma. This shows that more number of people affected with invasive breast carcinoma.\u003c/p\u003e \u003cp\u003eTheir SEER study demonstrate that invasive ductal carcinoma is more often diagnosed in Indians and Pakistani belongs to Asia females than to Caucasian females while analysis of lobular carcinoma is consistently lower (Kakarala et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). This study shows that more number of patients with invasive ductal carcinoma were found in Pakistan during 2021 to 2022.\u003c/p\u003e \u003cp\u003eHigh proportion of BC in females of Asia than to Caucasians (30.6% vs. 21.8%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0095) in their study was ER and PR negative (Kakarala et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, equal number of patients with ER/PR positive and ER/PR negative. This shows the odds ratio 1 and p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (i.e p-value equals to 1). This also shows non-significant differences. HER2 status was also observed. In this study 13 patients with HER2 negative and 5 patients with HER2 positive while 2 patients do not have this data.\u003c/p\u003e \u003cp\u003eDuring their study they found the occurrence of deleterious BRCA1 and BRCA2 mutations of inherited BC ovarian cancer was 9.4% in Southern Chinese high-threat relatives (n Z 1427) through the combination of PCR-based Sanger sequencing, Next generation sequencing, and MLPA (Kwong et al., 2016). This study was conducted to know the amino acid change and deletions in the targeted genes including TP53, ATM and CDH in the breast cancer patients of Pakistan. This was performed by whole exome sequencing.\u003c/p\u003e \u003cp\u003eThey detect mutations by Next generation sequencing that was before missed by high resolution melting. According to them, this is the biggest study of genetic predisposition screening of BC described in population of China. Generally, 126 pathogenic variations were recognized in BRCA1, BRCA2 genes, furthermore, variations in TP53 and PTEN were noticed in 5 and 2 families, respectively. Comprehensive study of the mutational pattern exposed that 17 varieties of hotspot mutation were observed in their study, contributing 48.8% of all identified variations. This recommended about one-half of the Southern Chinese variations. They revealed that 9 population-specific single nucleotide polymorphisms from the normal study, which includes 8 in BRCA2 and 1 in BRCA1, found and beneficial in the classification of VUS (Kwong et al., 2016).\u003c/p\u003e \u003cp\u003eWhole genome sequencing was done to identify the mutations or single nucleotide polymorphysims in TP53, ATM and CDH gene. In this study, amino acid change and deletions were observed in ATM gene on exone 10 and 11 in sample 1 shows stopgain and nonsynonymous SNV mutation type. Mutations in TP53 gene on exon 4, 6, 7, 8 and 10 in sample 1 shows shows stopgain and nonsynonymous SNV mutation type and on exon 4, 7 and 8 in sample 2 shows nonsynonymous SNV mutation type. In this study the variations were also observed in CDH gene including (CDH5, CDH8, CDH10, CDH12, CDH16, CDH20, CDH23 and CDH24) shows frameshift deletion, nonsynonymous SNV, nonframeshift deletion on exon 2, 3, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 23, 37 and 54 in sample 1. Mutations in CDH gene (CDH5, CDH16, CDH19 and CDH23) shows mutations like nonsynonymous SNV, nonframeshift substitution and frameshift deletion on exon 6, 10, 12 and 13 in sample 2. The most common used technique to show muutations of the TP53 gene is immunohistochemistry identifies only alterations that induce protein growth, frameshift deletion, nonsense and splice mutations. The TTGE/sequencing study noticed 15% of the TP53 alterations outside exons 5 to 8; associate the significance of examining the whole gene and not only exons 5 to 8 as reported in old studies (Langer\u0026oslash;d et al., 2007). During this study, mutations on exon 4, 6, 7, 8, and 10 of tp53 gene was observed in sample 1 and on exon 4, 7 and 8 in sample 2.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIt is concluded that in Pakistani population more number of patients were observed having invasive ductal breast carcinoma. The people with ER/PR positive and negative were equal in number of total 19 patients. People with HER2 positive and negative were observed. This shows the triple negative breast cancer and HER2 overexpressed in patients. Whole exome sequencing shows that there were different type of mutations includes synonymous SNV, non-synonymous SNV, stopgain, non-frameshift deletion, frameshift deletion and non-frameshift substitution in different exonic regions of genes including TP53, ATM and CDH. The accession numbers and amino acid change and deletions were also observed in patients. For exome study on breast cancer alterations there is a need of more data and vast investigation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors are thankful to Mr. Asad Nawaz and hospital management for helping during the whole work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors share no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAll authors participated to the study conception and design. Material preparation, data collection and analysis were performed by Yasir Nawaz, Ali Zaib Khan and Fouzia Tanvir. The first draft of the manuscript was written by Yasir Nawaz and all authors commented on previous file of manuscript. All authors read and approved the final manuscript.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData will be available on the demand of authors. The data including accession numbers will be available on the website\u0026nbsp;\u003c/em\u003ehttps://www.ncbi.nlm.nih.gov/\u003cem\u003e.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThis study was performed in accordance to the Declaration of Helsinki. Approval was obtained by the Ethical review board of Allama Iqbal Medical College/Jinnah Hospital Lahore, Punjab, Pakistan on dated: 17/02/2022 with reference no. 194/23/12/2021/S2 ERB.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eInformed consent was signed from patients during data collection.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eInformed consent was signed from patients to publish data in journals.\u003c/em\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBaenziger, M., Baierl, M., Devanathan, K., Eswaran, S., Fu, P., Gschwend, B., . . . Langlois, A. (2020). 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Interaction between GSTP1 Val allele and H. pylori infection, smoking and alcohol consumption and risk of gastric cancer among the Chinese population. \u003cem\u003ePLOS one\u003c/em\u003e. doi:https://doi.org/10.1371/journal.pone.0047178\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"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},"keywords":"Breast cancer, Single nucleotide polymorphisms, Somatic mutations, Whole exome sequencing","lastPublishedDoi":"10.21203/rs.3.rs-2411036/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2411036/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCancer is a type which involves irregular progression of cells with the capacity to enter and move to other portions of body. Breast cancer starts from breast tissues, mostly from inner coating of milk ducts. It is categorized into various methods by, grade, stage and receptors status. It is very common in females worldwide. Whole-exome sequencing (WES) was done in DNA removed from tumors of six breast cancer patients from Jinnah hospital Lahore, Pakistan. There were 19 patients from age 27 to 73 from which tissue sample were collected from 6 patients. The age distribution shows non-significant differences. The ER/PR status shows non-significant differences and odds ratio equals to 1. Somatic mutations were detected in three targeted genes ATM, TP53 and CDH (CDH5, CDH8, CDH10, CDH12, CDH16, CDH20, CDH23 and CDH24) in sample 1. Two genes with exonic variants were found in sample 2 containing TP53 and CDH (CDH5, CDH16, CDH19, and CDH23). Amino acid change and deletions were observed in different exonic sites of these genes. To conclude, more number of patients was observed having invasive ductal breast carcinoma. A number of novel somatic mutations for breast cancer were recognized. More studies are needed to define the functions of these mutated genes in breast cancer. Whole exome sequencing shows different type of mutations in different exonic regions of genes including TP53, ATM and CDH.\u003c/p\u003e","manuscriptTitle":"Research of histological characteristics and single nucleotide polymorphisms in hereditary genes among Pakistani breast cancer patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-01-03 14:41:16","doi":"10.21203/rs.3.rs-2411036/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":"5db2b8a1-c287-47c2-a81d-728b1dea4672","owner":[],"postedDate":"January 3rd, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-02-15T17:44:28+00:00","versionOfRecord":[],"versionCreatedAt":"2023-01-03 14:41:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2411036","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2411036","identity":"rs-2411036","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}