Whole genome profiling of 400 patients at risk for hereditary cancer in a Brazilian cohort

Whole genome profiling of 400 patients at risk for hereditary cancer in a Brazilian cohort | 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 Article Whole genome profiling of 400 patients at risk for hereditary cancer in a Brazilian cohort Ana Camila Mendes Andrade, Angelina Xavier Acosta, Taisa Manuela Bonfim Machado Lopes, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7104192/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Hereditary cancer syndromes, caused by inherited genetic alterations, account for 5–10% of all cancers, posing substantial diagnostic and management challenges. Despite advances in next-generation sequencing technologies, access to genetic testing remains limited, particularly in low- and middle-income countries (LMICs), such as Brazil. Genetic heterogeneity and complex etiopathogenic patterns further complicate case resolution. This study enrolled genetically underrepresented admixed individuals at risk for hereditary cancer at a Reference Center for Rare Diseases in Salvador, Bahia, Brazil. A total of 400 individuals meeting hereditary cancer risk criteria underwent whole genome sequencing from whole blood as part of the Brazilian Rare Genomes Project. Clinical, demographic, and genetic data were jointly analyzed to investigate cancer predisposition. Most participants were female (95%), self-identified as brown/admixed (74.3%), and reported a personal history of breast cancer (74%). Pathogenic or likely pathogenic (P/LP) variants in hereditary cancer-related genes were identified in 23% of individuals, most frequently in BRCA1 (17.7%), BRCA2 (17.7%), MUTYH (6.3%), NF1 (5.2%), ATM (4.2%), and TP53 (4.2%) genes. Diagnostic conclusions were reached in 19% of cases with 7.8% of these harboring P/LP variants in two different genes. Inconclusive cases accounted for 26% of the cohort and included those with P/LP findings in genes with an unclear association to the patient’s cancer type, variants in heterozygous states for recessive conditions or variants of uncertain significance. The remaining 55% of cases were negative. Additionally, ACMG-recommended secondary findings were identified in 3.8% of patients. Notably, one patient carried a deep intronic variant that would have been missed by panel or exome sequencing. These findings highlight the genetic diversity in hereditary cancer syndromes and emphasize the need for expanded access to genetic testing and research to improve diagnostic outcomes. Biological sciences/Cancer Biological sciences/Genetics Health sciences/Oncology hereditary cancer syndromes whole genome sequencing genetic diagnosis germline pathogenic variant variant of uncertain significance Figures Figure 1 Figure 2 Figure 3 Introduction Although most cancers occur sporadically, 5 to 10% result from inherited genetic alterations associated with hereditary cancer predisposition syndromes ( 1 ). Individuals with these syndromes have an increased risk of developing specific tumor types, due to variants in genes that typically play regulatory roles in either the cell cycle or DNA repair pathways ( 2 ). Patients are commonly affected at an early age, have a higher risk of developing multiple primary tumors, and exhibit a familial pattern of a spectrum of cancers ( 3 ). Advances in next-generation sequencing (NGS) techniques have enhanced the identification of new susceptibility genes and cancer-related variants, contributing to personalized care ( 3 – 6 ). However, significant challenges persist in classifying and interpreting the thousands of variants detected through comprehensive DNA sequencing, requiring advanced computational processing, clinical correlation, analytical expertise, and high-quality reference databases ( 5 , 7 ). The Brazilian population, shaped by 500 years of admixture among Amerindians, Africans, and Europeans, is one of the most heterogeneous in the world ( 8 , 9 ). The contribution of these three major ancestral components varies by geographic region, with the highest proportions of Afro-descendants (self-identified as Black or mixed-race [ pardo , in Portuguese]) found in the North (76%) and Northeast (72.6%) regions ( 10 ). Moreover, when analyzing the relative proportion of the Black population, Bahia has the highest share among all Federation Units, with 22.4% ( 10 ). Yet, individuals of African and Indigenous ancestry remain underrepresented in genomic studies, which still rely largely on data from European populations ( 11 ). In Brazil, oncogenetic services currently reach less than 5% of the population, and public policies to assist patients and their families are limited ( 12 ). The recently instituted Law 14.758 (2023), which established the National Policy for Cancer Prevention and Control, aimed at improving access and quality of cancer care across the country, though it lacks specific guidelines for genetic testing. Enhancing accessibility to testing would significantly improve risk assessment and genetic counseling, providing insights into the impact of familial cancer in Brazil ( 12 , 13 ). The Brazilian Rare Genomes Project (BRGP), a collaborative initiative between Brazil's Ministry of Health and the Hospital Israelita Albert Einstein (HIAE), along with the Support Program for the Institutional Development of the Unified Health System (PROADI-SUS), aims to conduct whole genome sequencing (WGS) on germline cells derived from whole blood for individuals with rare diseases or those with clinical and family histories consistent with hereditary cancer. As part of the Genomas Brasil national genomics initiative, this project seeks to enhance the diagnostic potential for those conditions, providing early preventive and treatment strategies while incorporating genetic tools for future use in the Brazilian Unified Health System (SUS) ( 14 – 16 ). Despite investigations into the heritability of cancer risk in Brazil, data on hereditary cancer in the Northeast region, home to over 54.6 million people, remain limited ( 17 ). Given Brazil's admixed background and genetic heterogeneity, studies covering all regions are essential. Epidemiological and genetic data could substantially inform the identification of needs and opportunities for effective interventions and resource allocation ( 18 – 20 ). Therefore, this study aims to provide a comprehensive socio-demographic, clinical, and genetic characterization of underrepresented individuals at risk for hereditary cancer, recruited from a Reference Service for Rare Diseases (RDRS) in Salvador, Bahia, Brazil, and enrolled in the BRGP. METHODS Ethical approval This study was performed in line with the principles of the Declaration of Helsinki concerning research involving human subjects. Approval was granted by the Research Ethics Committee (REC) of Hospital Israelita Albert Einstein, São Paulo, Brazil (Protocol number: CAAE 29567220.4.1001.0071) and by the REC of University Hospital Edgard Santos (HUPES/UFBA) Salvador, Brazil, under protocol number: CAAE 29567220.4.2015.00494. All subjects, or their legal guardians, provided written informed consent for the collection of samples and subsequent analysis. Study population and inclusion criteria A total of 400 patients were recruited from the Oncogenetics Ambulatory at HUPES/UFBA and the Institute of Health Sciences (ICS/UFBA) between December 2020 and June 2023. Probands were referred for inclusion in the BRGP based on the project’s inclusion criteria (Supplementary document 1). Clinical and demographic data, including sex assigned at birth, age, place of birth, race/ethnicity, personal and familial history of cancer, and age at diagnosis were obtained from the patients’ electronic medical records. Sample collection Individuals attended the Medical Genetics Laboratory of HUPES/UFBA for sample collection, after providing written informed consent. Peripheral blood samples (at least 3 mL) were collected in EDTA tubes and sent to the BRGP sequencing centers at HIAE in São Paulo or Recife, where WGS and bioinformatic analysis were performed. Whole genome sequencing and variant classification WGS from whole blood was performed using an Illumina NovaSeq 6000® platform, following a protocol validated by the BRGP (14). The data were processed to detect single nucleotide variants (SNVs), copy number variants (CNVs), and structural variants (SVs) using Illumina's DRAGEN pipeline for alignment and variant call, as detailed in the protocol (14) Quality control metrics were assessed during each DRAGEN run, with target alignment quality metrics including: a Q30 score >90% for base quality, a minimum 20X coverage, coverage uniformity ≥80%, median insert size >300 bp, mapped reads >98%, chimeric (supplementary) reads <5%, DNA contamination ≤2%, and duplicate mapped reads <10% (14). Variant numbering was based on the reference transcript, using the A of the ATG initiation codon, aligned to the GRCh38/hg38 reference genome. Genomic coordinates for CNVs and SVs were determined based on variant calling; however, due to the inherent complexity of these variants and potential methodological constraints, precise breakpoints could not be guaranteed for all events. Variants located in low coverage regions, repeat-rich regions, or areas with pseudogenes might not have been reported. Variant classification adhered to guidelines from the American College of Medical Genetics (ACMG) and the Association for Molecular Pathology (AMP) (21). Recently, the BRGP incorporated HIAE’s own “Standards for Constitutional Sequence Variants Classification ” , which integrates updates from major genetics societies and the ClinGen framework (22). Secondary findings were reported to patients who provided written consent, in accordance with ACMG guidelines recommending the communication of pathogenic or likely pathogenic variants in genes associated with actionable medical conditions (23). Eight patients did not provide consent for secondary findings. Analysis of diagnostic reports The overall detection rate of WGS was determined by identifying pathogenic (P) or likely pathogenic (LP) variants in hereditary cancer predisposition genes. However, the WGS test result was only considered positive if it identified P/LP variants in genes with a current definitive association with the syndrome under investigation, thereby providing a conclusive diagnosis. Inconclusive cases included those with variants of uncertain significance (VUS), P/LP variants in genes with limited or unclear association to the patient’s phenotype, or isolated monoallelic variants for recessive disorders. Cases without clinically relevant variants for cancer predisposition were classified as negative. RESULTS Clinical and demographic characteristics of the study population In total, 400 individuals were enrolled in the study, with the majority being female (95%; Table 1). Most participants were aged between 30 and 49 years (63.3%). Race and ethnicity were self-reported, with 74.3% identifying as Brown/admixed, 15% as Black, 9% as White, 0.8% as Yellow/Asian and 1% not providing information on racial identity. The majority of probands were from the state of Bahia (92.8%), with a small percentage (7.2%) born in other states. Table 1 Baseline sociodemographic characteristics of the study population Gender Number of patients (%) Female 379 (95) Male 21 (5) Age group (years) 0-9 2 (0.5) 10-19 6 (1.5) 20-29 22 (5.5) 30-39 103 (25.8) 40-49 150 (37.5) 50-59 67 (16.8) 60-69 30 (7.5) 70-79 16 (4) 80+ 4 (1) Race/ethnicity White 36 (9) Black 60 (15) Brown/Admixed 297 (74.3) Yellow/Asian 3 (0.8) No information provided 4 (1) Place of birth Bahia state 371 (92.8) Salvador (state capital ) 127 (31.8) Countryside cities 244 (61) Other states a 29 (7.2) a Sergipe (n=6 probands), São Paulo (n=6), Pernambuco (n=5), Ceará (n=2), Piauí (n=2), Rio de Janeiro (n=2), Alagoas (n=1), Distrito-Federal (n=1), Minas Gerais (n=1), Mato Grosso do Sul (n=1), Pará (n=1), Paraná (n=1). A personal history of breast cancer was reported by most participants (74%; Table 2). Patients typically received their first cancer diagnosis between the ages of 30 and 49 (65.3%; median age: 40) and most had a single primary tumor (84%). The individuals were referred for investigation of various hereditary cancer syndromes, with hereditary breast, ovarian and pancreatic cancer being the most frequently suspected (62.5% of cases). Other syndromes included hereditary lobular breast cancer (18.5%), Lynch syndrome (5.3%), familial gastrointestinal stromal tumor (GIST) (3%) and hereditary polyposis (2.3%). Family history of cancer was reported by 89% of patients, with the most common cancers being breast (28.5%), prostate (13.7%), colorectal (8.5%), uterine (7%) and stomach (5%). A minority of probands (9%) reported no family history of cancer, and 1.8% did not provide information regarding familial cancer cases. Table 2 Clinical characteristics of individuals undergoing WGS for hereditary cancer investigation Personal history of cancer Number (%) Overall cancer occurrences a 442 Breast 328 (74) Ovarian 23 (5.2) Colorectal 22 (5) Thyroid 13 (2.9) Stomach 9 (2) Kidney 8 (1.8) Neurofibromatosis 4 (0.9) Intestinal polyps 4 (0.9) Endometrium 4 (0.9) Prostate 3 (0.7) Lung 3 (0.7) Skin non-melanoma 3 (0.7) Sarcomas 3 (0.7) Uterus 2 (0.5) Pancreas 2 (0.5) Other b 12 (2.7) Age at first diagnosis (years) 0-9 2 (0.5) 10-19 7 (1.8) 20-29 42 (10.5) 30-39 159 (39.8) 40-49 102 (25.5) 50-59 24 (6) 60-69 54 (13.5) 70-79 0 80 + 10 (2.5) Number of primary tumors 1 336 (84) 2 52 (13) ≥ 3 12 (3) Syndrome under investigation Number (%) Hereditary breast, ovarian and pancreatic cancer 249 (62.5) Hereditary lobular breast cancer 74 (18.5) Lynch syndrome 22 (5.3) Familial gastrointestinal stromal tumor (GIST) 12 (3) Hereditary polyposis 9 (2.3) Hereditary kidney cancer 6 (1.5) Neurofibromatosis 6 (1.5) Hereditary prostate cancer 5 (1.3) Familial thyroid cancer 5 (1.3) Li Fraumeni syndrome 3 (0.8) Cowden syndrome 3 (0.8) Hereditary paraganglioma-pheochromocytoma 2 (0.5) Multiple endocrine neoplasia syndromes (MEN) 2 (0.5) Peutz Jeghers syndrome 1 (0.3) Hereditary cancer syndrome 1 (0.3) Family history of cancer Number (% [when applicable]) Probands with family history of cancer 357 (89) Overall cancer occurrences 1458 Breast 416 (28.5) Prostate 200 (13.7) Colorectal 125 (8.5) Uterus 102 (7) Stomach 73 (5) Skin 74 (5) Melanoma 8 (0.5) Non-melanoma 66 (4.5) Lung 55 (3.8) Leukemia 53 (3.6) Thyroid 50 (3.4) Liver 47 (3.2) Ovarian 39 (2.7) Central nervous system (CNS) 34 (2.3) Pancreas 30 (2.1) Throat 29 (2) Other c 131 (8.9) No family history 36 (9) No information 7 (1.8) a The total exceeds 400 individuals because some individuals were diagnosed with multiple types of cancer. b Paraganglioma (n=2 probands), bladder (n=2), liver (n=2), xeroderma pigmentosum (n=1), lymphoma (n=1), bone (n=1), adrenocortical (n=1), melanoma (n=1) and esophageal (n=1). c Esophageal (n=14 cases), lymphoma (n=14), intestinal polyps (n=12), kidney (n=12), sarcomas (n=10), mouth (n=9), bone (n=7), gallbladder (n=6), bladder (n=5), laryngeal (n=5), neurofibromatosis (n=5), myeloma (n=5), head or neck (n=5), testicular (n=4), tracheal (n=4), penile (n=3), endometrium (n=2), mediastinal (n=2), eye (n=2), spinal cord (n=1), neuroendocrine (n=1), leg (n=1), peritoneal (n=1), abdominal (n=1). Diagnostic yield and genetic findings Among all individuals recruited, 77 (19%) received a positive WGS result, leading to a conclusive diagnosis (Fig. 1A; Supplementary Table 1). Additionally, 103 probands (26%) had inconclusive results, while 220 cases (55%) showed no clinically relevant variants, resulting in negative findings. Considering the variant distribution, P/LP variants were identified in 23% of individuals (92/400), covering 32 genes. The most frequently affected genes were BRCA1 (17.7%), BRCA2 (17.7%), MUTYH (6.3%), NF1 (5.2%), ATM (4.2%), and TP53 (4.2%) (Fig. 1B). Among the detected variants, 79 were unique (Supplementary Table 2), with frameshift deletions being the most common (32.9%), followed by stop-gain mutations (21.5%), nonsynonymous SNVs (13.9%), and splice site SNVs (11.4%) (Fig. 1C). There were two LP intronic SNVs detected (2.5%), one of which was a deep intronic variant in NF1 (c.1642-449A>G), that would have been missed through panel or exome sequencing. Additionally, 13 recurrent variants (found in at least two unrelated individuals) were identified in seven genes, including BRCA1 , BRCA2 , and MUTYH (Supplementary Table 2). Almost all individuals with a positive test result harbored a single P/LP variant defining their diagnosis. However, 7.8% of these probands were found to be double heterozygotes, carrying two P/LP variants, typically in different genes. Specific cases exhibiting these genetic profiles were (Supplementary Table 2): one patient diagnosed with breast cancer exhibiting variants in BRCA2 and a heterozygous variant in MUTYH ; another patient with thyroid cancer also presenting with variants in BRCA2 and a heterozygous variant in MUTYH . Further, among breast cancer probands, one carried variants in ATM and BRCA2 ; another, in BRCA1 and BRCA2 ; and a third had a BRCA1 SNV concurrently with a CNV. Additionally, one patient presenting with multiple subcutaneous nodules and facial dysmorphisms harbored two variants in ANTXR2 (phase undefined). Beyond these primary findings, 3.8% of consented patients (15/392) exhibited secondary findings in ACMG-recommended genes, predominantly TTR and TPM1 (Supplementary Table 2). There were 14 probands (3.5% of all cases) carrying P/LP variants but still presenting inconclusive WGS results. Most of these patients carried variants in genes with limited association with their diagnosed cancer type or had isolated monoallelic variants in genes associated with recessive disorders. For example, 10 patients had a personal history of breast cancer and presented P/LP variants in MUTYH , XRCC2 , POLH , FANCA , MSH3 , RAD50 , SDHB , or NTHL1 (Supplementary Table 2). One patient had adrenocortical carcinoma and an LP variant in XRCC2, and the remaining patients had ovarian cancer and variants in MUTYH and LZTR1 . A total of 120 VUS were reported, with at least one identified in 24.2% of the patients (97/400). Among these, 22 patients harbored two or more VUS. Additionally, five VUS were found in at least two unrelated patients (Supplementary Table 2). Overall, these VUS were distributed across 49 distinct genes, with the highest frequencies observed in BRCA2 (10.9%), ATM (6.7%), PALB2 (6.7%), CHEK2 (5.9%), MSH2 (5%), POLE (5%), APC (4.2%), MSH6 (3.4%), ATR (2.5%), BRCA1 (2.5%), BRIP1 (2.5%) and POLD1 (2.5%) (Fig. 2; Supplementary Table 2). The distribution of cancer types according to variant classification showed that breast cancer, the most frequent diagnosis in the cohort, contributed to the largest number of cases without identified variants, followed by those with VUS, and then P and LP variants. Colorectal, ovarian, and thyroid cancers were also among the more represented cancer types and exhibited varying distributions across classification categories. Other conditions, including kidney, stomach, endometrial, and adrenal cancers, as well as cancer-predisposing genetic disorders such as neurofibromatosis and paraganglioma, were less common but appeared in multiple variant categories. Overall, VUS represented a considerable proportion of the variants observed, and P/LP variants were distributed across different cancer types, most notably in breast, colorectal, and ovarian cancers, as well as in neurofibromatosis and paraganglioma. DISCUSSION Our study in a genetically underrepresented admixed population found an overall positivity rate of 23% for pathogenic or likely pathogenic variants in hereditary cancer predisposition genes. Specifically, our diagnostic yield, representing cases where a P/LP variant provided a clear genetic justification for the cancer diagnosis, was 19%. This aligns with reported rates ranging from 5.1% to 27% in global studies and 16.4% to 27% in Brazilian cohorts (18,19,24–34). Variability in positivity rates across studies is influenced by differences in inclusion criteria, cancer distribution among participants, sequencing methods, analysis pipelines, gene panel selection, and CNV evaluation (19,25,35). WGS has demonstrated a 5.1% increase in diagnostic yield for undiagnosed familial cancer cases previously tested with single or multigene panels, offering advantages by detecting a broader range of genetic alterations, including those in non-coding regions, and enabling cost-effective reanalysis to improve diagnostic accuracy (31). Indeed, one patient, undergoing investigation for a clinical suspicion of neurofibromatosis type 1, had a deep intronic variant identified in NF1 , that would not have been detected by exome sequencing or panel testing. Functional studies have shown that this variant induces a damaging effect, causing abnormal splicing (36). While this variant has been functionally assessed, other deep intronic variants may also be present, whose pathogenic effects remain to be fully understood. The study enrolled 400 individuals, predominantly female, most of whom were aged 30–49 years and were first diagnosed within a similar age range. The high proportion of individuals with a single primary tumor may reflect the recent nature of their cancer diagnoses, as indicated by their current age. The predominance of breast cancer in both personal and family histories aligns with the prevalence of female patients investigated for hereditary breast cancer syndromes. The observed diversity of other suspected hereditary cancer syndromes highlights the challenges in genetic counseling for this population, emphasizing the need for further studies to explore how specific genetic profiles and demographic factors interact to influence hereditary cancer risks. Key genes identified among P/LP carriers included BRCA1, BRCA2, MUTYH, NF1, ATM, and TP53 , consistent with findings from Oliveira et al. (32) and Leite et al. (18), who also identified high frequencies of BRCA1/2 , MUTYH , and TP53 variants in Brazilian cohorts. The prevalence of BRCA1/2 variants reflects the enrichment of breast cancer cases in our study, while MUTYH , TP53 , and ATM were significant among non-BRCA genes. Recurrent variants were observed in seven genes, notably the BRCA1 c.3331_3334del and the c.211A>G, which have been documented in other Brazilian studies (17,37–39). The absence of the Ashkenazi-associated BRCA1 c.5266dupC variant in our cohort, a variant that accounts for approximately 20% of BRCA1 pathogenic variants in South Brazil, suggests its low prevalence in Northeast Brazil compared to other regions (17,37,39,40), likely reflecting the distinct genetic background of the studied population and the diversity of Brazilian genetics. In BRCA2 , the variant c.2808_2811del identified in two patients, was recurrent in other studies (37,38), while the c.7124T>G variant, identified in three patients, was rare in both other Brazilian and global datasets (41). The MUTYH c.1103G>A, identified in three patients in our cohort, also recurred in Brazilian patients with colorectal cancer predisposition (42). Double heterozygosity was observed in 7.8% of the positive cases, representing 1.5% of all recruited participants, consistent with findings by Megid et al. (43) and Agaoglu & Doganay (44). Research on the combined impact of double heterozygosity on cancer risk is limited, and the diversity of variant combinations complicates comparisons across studies, highlighting the need for larger investigations and functional analyses to better understand digenic variant effects for improved genetic surveillance and disease management (32,43,44). Inconclusive cases accounted for 26% of participants and included those with VUS, P or LP variants in genes not strongly linked to the suspected syndrome, or isolated monoallelic variants for recessive disorders. For example, monoallelic MUTYH variants were identified in individuals with breast cancer. Although MUTYH is typically associated with colorectal cancer risk, previous reports have suggested broader cancer associations for MUTYH , though such links remain debated (28,33,45–48). Similarly, rare findings in XRCC2 , POLH and SDHB in breast cancer patients (genes typically associated with Fanconi Anemia, Xeroderma Pigmentosum and Pheochromocytomas/Paragangliomas, respectively), are consistent with studies suggesting potential links of those genes to breast cancer, although a definitive association remains uncertain (49–59). Such results require further investigation to determine whether they represent novel associations or spurious links. Additionally, our study identified heterozygous P/LP variants in genes related to autosomal recessive conditions, such as FANCA , MSH3 , RAD50 and NTHL1 . Del Valle et al. (60) found a significant association between FANCA mutations and an increased risk of breast and/or ovarian cancer but recommended larger studies to better comprehend their role in cancer risk. These findings reinforce the need for careful interpretation of variants in genes linked to autosomal recessive disorders, where compound heterozygosity or homozygosity is necessary for full phenotypic expression. VUS were reported in 24.2% of cases, lower than rates observed in panel-based or smaller-scale sequencing studies, which ranged up to 82.7% depending on the number of genes analyzed (18,19,24,25,28,30,32–35). Rehm et al. (61) note that broader sequencing approaches like exome sequencing (ES) and WGS may yield fewer reported VUS due to selective reporting practices, focusing on clinically significant variants and opting not to report VUS with limited clinical correlation or weak pathogenic evidence. This highlights the importance of thorough variant assessment to minimize uncertainty in clinical contexts. Advances in genetic testing, particularly with NGS, have enhanced our ability to identify complex genetic alterations, identifying new risk genes and variant patterns across populations (30). Despite these advances, challenges remain, including addressing the high proportion of inconclusive cases (which are often due to the increased occurrence of VUS complicating clinical decision-making) and improving access to testing, especially in public healthcare systems of LMIC countries like Brazil (62–65). The growing accessibility of genomic sequencing has also led to an increased identification of secondary findings, and healthcare professionals should now be prepared to manage individuals with these discoveries, as they are becoming an increasingly common aspect of clinical practice (66). A small percentage of individuals in our cohort carried secondary findings in ACMG-recommended genes, including MYBPC3 , TTN , and TTR , which could have clinical implications beyond cancer risk, such as predisposition to cardiomyopathies or arrhythmias (67).These findings may affect cancer treatment protocols, as cardiotoxicity from certain chemotherapeutic agents could require modified plans or closer cardiac monitoring (67). This illustrates a gap in current cancer gene panels, which often exclude ACMG-recommended genes. Integrating ACMG findings into cancer genomic testing could improve patient care with a more comprehensive risk assessment. Further studies are needed to evaluate the clinical utility of incorporating these findings into hereditary cancer testing and prompt the development of broader gene panels. Our study, conducted as part of the Brazilian Rare Genomes Project, reinforces the importance of integrating genomic medicine into Brazil's public healthcare system to ensure equitable access to cancer diagnosis and care. However, our findings should be interpreted considering certain limitations. While the analytical pipeline demonstrated high sensitivity (>99%) for detecting SNVs and small insertions/deletions (up to 20 bp) and >90% for CNVs affecting one or more exons, its sensitivity was reduced for variants larger than 20 bp and smaller than an exon. Furthermore, limitations include the use of a convenience sample predominantly consisting of female breast cancer patients, potential inaccuracies in medical records, and a sample size that, while representative of Bahia's population, may not fully capture the state's entire genetic diversity. CONCLUSION This study provides the first comprehensive whole-genome characterization of hereditary cancer predisposition in an admixed Northeast Brazilian cohort, revealing a distinct genetic architecture marked by recurrent variants (e.g., BRCA1 c.3331_3334del), low prevalence of Ashkenazi-associated alleles (e.g., BRCA1 c.5266dupC), and novel deep intronic findings. We observed a 23% detection rate of pathogenic or likely pathogenic variants in cancer predisposition genes, emphasizing the critical role of comprehensive genetic testing in hereditary cancer risk assessment. Whole-genome sequencing provided diagnostic conclusions in 19% of cases and showed that broader techniques, despite potential for higher VUS rates, may ultimately yield fewer inconclusive findings. Diagnostic challenges persisted, as over half of the enrolled cases had no definitive findings, while others, even with P/LP findings, remained inconclusive. Our results offer insights into the genetic landscape of cancer predisposition in Bahia, Brazil, a population with a highly diverse genetic background. The findings highlight the need for improved access to genetic testing in public healthcare systems and the challenges of VUS interpretation in populations currently underrepresented in genomic studies and reference databases. This illustrates the need for tailored genetic testing panels. Further research on the clinical impact of novel and recurrent variants, alongside efforts to address genetic heterogeneity and complex etiologies, will be key to refining cancer risk assessments and guiding patient management. Declarations DATA AVAILABILITY The data supporting the findings of this study are not publicly available to protect participant privacy. A de-identified version of the dataset can be obtained from the corresponding author upon reasonable request. ACKNOWLEDGMENTS This research was made possible through access to the data and findings generated by the Brazilian Rare Genomes Project. P.I.P.R. and R.K. are research fellows for Brazil’s National Council for Scientific and Technological Development (CNPq). The Brazilian Rare Genomes Project Consortium is composed of the following members: Antonio Victor Campos Coelho; Rafael Sales de Albuquerque; Catarina dos Santos Gomes; José Bandeira do Nascimento Junior; Gustavo Santos de Oliveira; Livia Maria Silva Moura; Luciana Souto Mofatto; Rafael Lucas Muniz Guedes; Rodrigo Araújo Sequeira Barreiro; Marcel Pinheiro Caraciolo; Ana Paula de Andrade Oliveira; Anne Caroline Barbosa Teixeira; Bruna Mascaro Cordeiro de Azevedo; Carolina Dias Carlos; Lucas Santos de Santana; Marina Cadena da Matta; Matheus Martinelli Lima; Nuria Bengala Zurro; Renata Yoshiko Yamada; Vivian Pedigone Cintra; Gabriela Pereira Campilongo; Gabriela Borges Cherulli Colichio; Renata Martins Ribeiro da Silva; Caio Robledo D’Angioli Costa Quaio; Carolina Araújo Moreno; Eduardo Perrone; Jéssica Grasiela Araújo Espolaor; Joana Rosa Marques Prota; José Ricardo Magliocco Ceroni; Kelin Chen; Luiza do Amaral Virmond; Marina de Franca Basto Silva; Michele Patricia Migliavacca; Renata Moldenhauer Minillo; Thiago Yoshinaga Tonholo Silva; Karla de Oliveira Pelegrino; Tatiana Ferreira de Almeida; João Bosco Oliveira. AUTHOR CONTRIBUTIONS All authors contributed to the study conception and design. Material preparation, data collection and analysis, as well as pre-test and post-test counseling and the completion of digital forms/electronic medical records with the construction of pedigrees and family histories, were performed by T.M.B.M.L., L.S.M.B., T.C.M.F., A.C.M.A., I.L.O.N., M.B.P.T., A.V.C.C., E.P and the B.R.G.P.C. team. The first draft of the manuscript was written by A.C.M.A., and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. FUNDING The Brazilian Rare Genomes Project was funded by Hospital Israelita Albert Einstein in partnership with the Support Program for the Institutional Development of the Unified Health System (PROADI-SUS), from the Brazilian Ministry of Health (Law 12.101/2009). COMPETING INTERESTS The authors declare no competing interests. ADDITIONAL INFORMATION Supplementary information The online version contains supplementary material available at: Correspondence and requests for materials should be addressed to Ana Camila Mendes Andrade. References Lu KH, Wood ME, Daniels M, Burke C, Ford J, Kauff ND, et al. American society of clinical oncology expert statement: Collection and use of a cancer family history for oncology providers. Journal of Clinical Oncology. 2014 Mar 10;32(8):833–40. Rahner N, Steinke V. Hereditary Cancer Syndromes. Dtsch Arztebl. 2008 Oct 10;105(41):706–14. Okur V, Chung WK. The impact of hereditary cancer gene panels on clinical care and lessons learned. Vol. 3, Cold Spring Harbor molecular case studies. 2017. Rahman N. Realizing the promise of cancer predisposition genes. Vol. 505, Nature. Nature Publishing Group; 2014. p. 302–8. Federici G, Soddu S. Variants of uncertain significance in the era of high-throughput genome sequencing: A lesson from breast and ovary cancers. 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Hum Mol Genet. 2012 Jan;21(2):300–10. del Valle J, Rofes P, Moreno-Cabrera JM, López-Dóriga A, Belhadj S, Vargas-Parra G, et al. Exploring the role of mutations in fanconi anemia genes in hereditary cancer patients. Cancers (Basel). 2020 Apr 1;12(4). Rehm HL, Alaimo JT, Aradhya S, Bayrak-Toydemir P, Best H, Brandon R, et al. The landscape of reported VUS in multi-gene panel and genomic testing: Time for a change. Genetics in Medicine. 2023 Dec 1;25(12). Wright M, Menon V, Taylor L, Shashidharan M, Westercamp T, Ternent CA. Factors predicting reclassification of variants of unknown significance. Am J Surg. 2018 Dec 1;216(6):1148–54. Chiang J, Tze ;, Chia H, Yuen J, Shaw T, Li ST, et al. Impact of Variant Reclassification in Cancer Predisposition Genes on Clinical Care [Internet]. 2021. Available from: https://doi.org/10. Stanislaw C, Xue Y, Wilcox WR. Genetic evaluation and testing for hereditary forms of cancer in the era of next-generation sequencing. Vol. 13, Cancer Biology and Medicine. Cancer Biology and Medicine; 2016. p. 55–67. Francies FZ, Hull R, Khanyile R, Dlamini Z. Breast cancer in low-middle income countries: abnormality in splicing and lack of targeted treatment options [Internet]. Vol. 10, Am J Cancer Res. 2020 May. Available from: www.ajcr.us/ Perrone E, Virmond L, Coelho AVC, De França M, Moreno CA, Prota JRM, et al. ACMG secondary findings in the Brazilian rare genomes project: insights from 5402 genome sequencing. J Hum Genet. 2025; Kim Y, Seidman JG, Seidman CE. Genetics of cancer therapy-associated cardiotoxicity. J Mol Cell Cardiol. 2022 Jun 1;167:85 Additional Declarations No competing interests reported. Supplementary Files Suplementarytable1Summaryofgeneticfindingspersonalandfamilyhistoryofprobands.xlsx Supplementarytable2SummaryofvariantsPLPVUSdoubleheterozygotesandACMGsecondaryfindings.xlsx BRGPInclusioncriteriaandConsortiaauthorship.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 26 Sep, 2025 Reviews received at journal 21 Sep, 2025 Reviews received at journal 10 Sep, 2025 Reviewers agreed at journal 08 Sep, 2025 Reviewers agreed at journal 05 Sep, 2025 Reviewers agreed at journal 04 Sep, 2025 Reviewers invited by journal 14 Aug, 2025 Editor assigned by journal 11 Aug, 2025 Submission checks completed at journal 16 Jul, 2025 First submitted to journal 11 Jul, 2025 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. 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highlighting the prevalence of significant genetic alterations according to circle size; \u003cstrong\u003e(C)\u003c/strong\u003e Distribution of the unique P/LP variants according to their functional annotation\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7104192/v1/d1a5ed859f4c17619aa193bf.jpeg"},{"id":89658648,"identity":"c7bf03e0-7f53-4b69-af61-cbd7d3afc09b","added_by":"auto","created_at":"2025-08-22 10:44:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":438006,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of VUS amongst the most frequently mutated genes. Genes with lower frequencies were grouped as “Other” and comprised the following: \u003cem\u003eABRAXAS1\u003c/em\u003e, \u003cem\u003eAXIN2\u003c/em\u003e, \u003cem\u003eBAP1\u003c/em\u003e, \u003cem\u003eBARD1\u003c/em\u003e, \u003cem\u003eCDH1\u003c/em\u003e, \u003cem\u003eCDKN2A\u003c/em\u003e, \u003cem\u003eEPCAM\u003c/em\u003e, \u003cem\u003eFANCA\u003c/em\u003e, \u003cem\u003eFLCN\u003c/em\u003e, \u003cem\u003eGNAS\u003c/em\u003e, \u003cem\u003eHABP2\u003c/em\u003e, \u003cem\u003eHMMR\u003c/em\u003e, \u003cem\u003eLZTR1\u003c/em\u003e, \u003cem\u003eMLH1\u003c/em\u003e, \u003cem\u003eMLH3\u003c/em\u003e, \u003cem\u003eMSH3\u003c/em\u003e, \u003cem\u003eMSR1\u003c/em\u003e, \u003cem\u003eMUTYH\u003c/em\u003e, \u003cem\u003eNBN\u003c/em\u003e, \u003cem\u003eNF1\u003c/em\u003e, \u003cem\u003eNTHL1\u003c/em\u003e, \u003cem\u003ePOT1\u003c/em\u003e, \u003cem\u003ePTCH2\u003c/em\u003e, \u003cem\u003eRAD50\u003c/em\u003e, \u003cem\u003eRAD51C\u003c/em\u003e, \u003cem\u003eRAD51D\u003c/em\u003e, \u003cem\u003eRAD54L\u003c/em\u003e, \u003cem\u003eRECQL\u003c/em\u003e, \u003cem\u003eRECQL4\u003c/em\u003e, \u003cem\u003eRET\u003c/em\u003e, \u003cem\u003eRNF43\u003c/em\u003e, \u003cem\u003eSDHA\u003c/em\u003e, \u003cem\u003eSMAD4\u003c/em\u003e, \u003cem\u003eSTK11\u003c/em\u003e, \u003cem\u003eTP53\u003c/em\u003e, \u003cem\u003eVHL\u003c/em\u003e, and \u003cem\u003eXRCC3\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7104192/v1/9437af188860389238e4c357.png"},{"id":89656317,"identity":"eb3da7d6-9379-4aa2-b3d3-660e93140042","added_by":"auto","created_at":"2025-08-22 10:28:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":515913,"visible":true,"origin":"","legend":"\u003cp\u003eSankey diagram showing the distribution of proband's cancer types according to variant classification. Cancer types are listed on the left, and variant classifications (VUS, P, LP, and no variants identified) are shown on the right. The width of the flows is proportional to the number of cases in each category\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7104192/v1/b4ba81a9c5dad6c9970c0ba7.png"},{"id":89659059,"identity":"84f637bf-67a8-4d88-b759-db296bd184fd","added_by":"auto","created_at":"2025-08-22 10:52:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2413591,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7104192/v1/646b6933-4a41-48f2-9195-09bd5e9e94c0.pdf"},{"id":89656307,"identity":"14f9ccf4-4d0e-4294-9a4d-93bb0fc124c5","added_by":"auto","created_at":"2025-08-22 10:28:34","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":40609,"visible":true,"origin":"","legend":"","description":"","filename":"Suplementarytable1Summaryofgeneticfindingspersonalandfamilyhistoryofprobands.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7104192/v1/de0a1f421720e1dfd173fdf3.xlsx"},{"id":89657709,"identity":"6c9907fe-ac3a-4ce3-9a17-dfcb583cb18a","added_by":"auto","created_at":"2025-08-22 10:36:34","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":36625,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable2SummaryofvariantsPLPVUSdoubleheterozygotesandACMGsecondaryfindings.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7104192/v1/78a01875926200568f366bc2.xlsx"},{"id":89656309,"identity":"8c0895a1-cd09-4415-ae1d-0dd91ca3e66c","added_by":"auto","created_at":"2025-08-22 10:28:34","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":143427,"visible":true,"origin":"","legend":"","description":"","filename":"BRGPInclusioncriteriaandConsortiaauthorship.docx","url":"https://assets-eu.researchsquare.com/files/rs-7104192/v1/31d2325f161c2e9da7b179af.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Whole genome profiling of 400 patients at risk for hereditary cancer in a Brazilian cohort","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAlthough most cancers occur sporadically, 5 to 10% result from inherited genetic alterations associated with hereditary cancer predisposition syndromes (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Individuals with these syndromes have an increased risk of developing specific tumor types, due to variants in genes that typically play regulatory roles in either the cell cycle or DNA repair pathways (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Patients are commonly affected at an early age, have a higher risk of developing multiple primary tumors, and exhibit a familial pattern of a spectrum of cancers (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Advances in next-generation sequencing (NGS) techniques have enhanced the identification of new susceptibility genes and cancer-related variants, contributing to personalized care (\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). However, significant challenges persist in classifying and interpreting the thousands of variants detected through comprehensive DNA sequencing, requiring advanced computational processing, clinical correlation, analytical expertise, and high-quality reference databases (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe Brazilian population, shaped by 500 years of admixture among Amerindians, Africans, and Europeans, is one of the most heterogeneous in the world (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The contribution of these three major ancestral components varies by geographic region, with the highest proportions of Afro-descendants (self-identified as Black or mixed-race [\u003cem\u003epardo\u003c/em\u003e, in Portuguese]) found in the North (76%) and Northeast (72.6%) regions (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Moreover, when analyzing the relative proportion of the Black population, Bahia has the highest share among all Federation Units, with 22.4% (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Yet, individuals of African and Indigenous ancestry remain underrepresented in genomic studies, which still rely largely on data from European populations (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn Brazil, oncogenetic services currently reach less than 5% of the population, and public policies to assist patients and their families are limited (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). The recently instituted Law 14.758 (2023), which established the National Policy for Cancer Prevention and Control, aimed at improving access and quality of cancer care across the country, though it lacks specific guidelines for genetic testing. Enhancing accessibility to testing would significantly improve risk assessment and genetic counseling, providing insights into the impact of familial cancer in Brazil (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe Brazilian Rare Genomes Project (BRGP), a collaborative initiative between Brazil's Ministry of Health and the Hospital Israelita Albert Einstein (HIAE), along with the Support Program for the Institutional Development of the Unified Health System (PROADI-SUS), aims to conduct whole genome sequencing (WGS) on germline cells derived from whole blood for individuals with rare diseases or those with clinical and family histories consistent with hereditary cancer. As part of the \u003cem\u003eGenomas Brasil\u003c/em\u003e national genomics initiative, this project seeks to enhance the diagnostic potential for those conditions, providing early preventive and treatment strategies while incorporating genetic tools for future use in the Brazilian Unified Health System (SUS) (\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite investigations into the heritability of cancer risk in Brazil, data on hereditary cancer in the Northeast region, home to over 54.6\u0026nbsp;million people, remain limited (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Given Brazil's admixed background and genetic heterogeneity, studies covering all regions are essential. Epidemiological and genetic data could substantially inform the identification of needs and opportunities for effective interventions and resource allocation (\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Therefore, this study aims to provide a comprehensive socio-demographic, clinical, and genetic characterization of underrepresented individuals at risk for hereditary cancer, recruited from a Reference Service for Rare Diseases (RDRS) in Salvador, Bahia, Brazil, and enrolled in the BRGP.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki concerning research involving human subjects. Approval was granted by the Research Ethics Committee (REC) of Hospital Israelita Albert Einstein, S\u0026atilde;o Paulo, Brazil (Protocol number: CAAE 29567220.4.1001.0071) and by the REC of University Hospital Edgard Santos (HUPES/UFBA) Salvador, Brazil, under protocol number: CAAE 29567220.4.2015.00494. All subjects, or their legal guardians, provided written informed consent for the collection of samples and subsequent analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy population and inclusion criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 400 patients were recruited from the Oncogenetics Ambulatory at HUPES/UFBA and the Institute of Health Sciences (ICS/UFBA) between December 2020 and June 2023. Probands were referred for inclusion in the BRGP based on the project\u0026rsquo;s inclusion criteria (Supplementary document 1). Clinical and demographic data, including sex assigned at birth, age, place of birth, race/ethnicity, personal and familial history of cancer, and age at diagnosis were obtained from the patients\u0026rsquo; electronic medical records.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eSample collection\u0026nbsp;\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eIndividuals attended the Medical Genetics Laboratory of HUPES/UFBA for sample collection, after providing written informed consent. Peripheral blood samples (at least 3 mL) were collected in EDTA tubes and sent to the BRGP sequencing centers at HIAE in S\u0026atilde;o Paulo or Recife, where WGS and bioinformatic analysis were performed.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eWhole genome sequencing and variant classification\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eWGS from whole blood was performed using an Illumina NovaSeq 6000\u0026reg; platform, following a protocol validated by the BRGP (14). The data were processed to detect single nucleotide variants (SNVs), copy number variants (CNVs), and structural variants (SVs) using Illumina\u0026apos;s DRAGEN pipeline for alignment and variant call, as detailed in the protocol (14)\u0026nbsp;Quality control metrics were assessed during each DRAGEN run, with target alignment quality metrics including: a Q30 score \u0026gt;90% for base quality, a minimum 20X coverage, coverage uniformity \u0026ge;80%, median insert size \u0026gt;300 bp, mapped reads \u0026gt;98%, chimeric (supplementary) reads \u0026lt;5%, DNA contamination \u0026le;2%, and duplicate mapped reads \u0026lt;10%\u0026nbsp;(14). Variant numbering was based on the reference transcript, using the A of the ATG initiation codon, aligned to the GRCh38/hg38 reference genome.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Genomic coordinates for CNVs and SVs were determined based on variant calling; however, due to the inherent complexity of these variants and potential methodological constraints, precise breakpoints could not be guaranteed for all events. Variants located in low coverage regions, repeat-rich regions, or areas with pseudogenes might not have been reported. Variant classification adhered to guidelines from the American College of Medical Genetics (ACMG) and the Association for Molecular Pathology (AMP) (21). Recently, the BRGP incorporated HIAE\u0026rsquo;s own \u0026ldquo;Standards for Constitutional Sequence Variants Classification\u003cem\u003e\u0026rdquo;\u003c/em\u003e, which integrates updates from major genetics societies and the ClinGen framework (22). Secondary findings were reported to patients who provided written consent, in accordance with ACMG guidelines recommending the communication of pathogenic or likely pathogenic variants in genes associated with actionable medical conditions (23). Eight patients did not provide consent for secondary findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of diagnostic reports\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overall detection rate of WGS was determined by identifying pathogenic (P) or likely pathogenic (LP) variants in hereditary cancer predisposition genes. However, the WGS test result was only considered positive if it identified P/LP variants in genes with a current definitive association with the syndrome under investigation, thereby providing a conclusive diagnosis. Inconclusive cases included those with variants of uncertain significance (VUS), P/LP variants in genes with limited or unclear association to the patient\u0026rsquo;s phenotype, or isolated monoallelic variants for recessive disorders. Cases without clinically relevant variants for cancer predisposition were classified as negative.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003ch3\u003e\u003cstrong\u003eClinical and demographic characteristics of the study population\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eIn total, 400 individuals were enrolled in the study, with the majority being female (95%; Table 1). Most participants were aged between 30 and 49 years (63.3%). Race and ethnicity were self-reported, with 74.3% identifying as Brown/admixed, 15% as Black, 9% as White, 0.8% as Yellow/Asian and 1% not providing information on racial identity. The majority of probands were from the state of Bahia (92.8%), with a small percentage (7.2%) born in other states.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Baseline sociodemographic characteristics of the study population\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"643\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of patients (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e379 (95)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e21 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e0-9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e2 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e10-19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e6 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e20-29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e22 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e30-39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e103 (25.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e40-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e150 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e50-59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e67 (16.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e60-69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e30 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e70-79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e16 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e80+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e4 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace/ethnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e36 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e60 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003eBrown/Admixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e297 (74.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003eYellow/Asian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e3 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003eNo information provided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e4 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of birth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003eBahia state\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e371 (92.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e\u003cem\u003eSalvador (state capital\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e127 (31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003e\u003cem\u003eCountryside cities\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e244 (61)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 74.9221%;\"\u003e\n \u003cp\u003eOther states\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.0779%;\"\u003e\n \u003cp\u003e29 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u0026nbsp;\u003c/sup\u003eSergipe (n=6 probands), S\u0026atilde;o Paulo (n=6), Pernambuco (n=5), Cear\u0026aacute; (n=2), Piau\u0026iacute; (n=2), Rio de Janeiro (n=2), Alagoas (n=1), Distrito-Federal (n=1), Minas Gerais (n=1), Mato Grosso do Sul (n=1), Par\u0026aacute; (n=1), Paran\u0026aacute; (n=1).\u003c/p\u003e\n\u003ch3\u003e\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eA personal history of breast cancer was reported by most participants (74%; Table 2). Patients typically received their first cancer diagnosis between the ages of 30 and 49 (65.3%; median age: 40) and most had a single primary tumor (84%). The individuals were referred for investigation of various hereditary cancer syndromes, with hereditary breast, ovarian and pancreatic cancer being the most frequently suspected (62.5% of cases). Other syndromes included hereditary lobular breast cancer (18.5%), Lynch syndrome (5.3%), familial gastrointestinal stromal tumor (GIST) (3%) and hereditary polyposis (2.3%). Family history of cancer was reported by 89% of patients, with the most common cancers being breast (28.5%), prostate (13.7%), colorectal (8.5%), uterine (7%) and stomach (5%). A minority of probands (9%) reported no family history of cancer, and 1.8% did not provide information regarding familial cancer cases.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Clinical characteristics of individuals undergoing WGS for hereditary cancer investigation\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"651\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePersonal history of cancer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eOverall cancer occurrences\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e442\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eBreast\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e328 (74)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eOvarian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e23 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eColorectal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e22 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eThyroid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e13 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eStomach\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e9 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eKidney\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e8 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eNeurofibromatosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e4 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eIntestinal polyps\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e4 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eEndometrium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e4 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eProstate\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e3 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eLung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e3 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eSkin non-melanoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e3 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eSarcomas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e3 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eUterus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e2 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003ePancreas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e2 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eOther\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e12 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at first diagnosis (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e0-9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; 2 (0.5)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e10-19\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;7 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e20-29\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e42 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e30-39\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e159 (39.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e40-49\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e102 (25.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e50-59\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e24 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e60-69\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e54 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e70-79\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e80 +\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e10 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of primary tumors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e336 (84)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e52 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e\u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e12 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSyndrome under investigation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eHereditary breast, ovarian and pancreatic cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e249 (62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eHereditary lobular breast cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e74 (18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eLynch syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e22 (5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eFamilial gastrointestinal stromal tumor (GIST)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e12 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eHereditary polyposis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e9 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eHereditary kidney cancer\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e6 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eNeurofibromatosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e6 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eHereditary prostate cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e5 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eFamilial thyroid cancer\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e5 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eLi Fraumeni syndrome\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e3 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eCowden syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e3 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eHereditary paraganglioma-pheochromocytoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e2 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eMultiple endocrine neoplasia syndromes (MEN)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e2 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003ePeutz Jeghers syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eHereditary cancer syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily history of cancer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber (% [when applicable])\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eProbands with family history of cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e357 (89)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eOverall cancer occurrences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e1458\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eBreast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e416 (28.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eProstate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e200 (13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eColorectal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e125 (8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eUterus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e102 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eStomach\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e73 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eSkin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e74 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e\u003cem\u003eMelanoma\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e8 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003e\u003cem\u003eNon-melanoma\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e66 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eLung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e55 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eLeukemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e53 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eThyroid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e50 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e47 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eOvarian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e39 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eCentral nervous system (CNS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e34 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003ePancreas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e30 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eThroat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e29 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eOther\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e131 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eNo family history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e36 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.1551%;\"\u003e\n \u003cp\u003eNo information\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50.8449%;\"\u003e\n \u003cp\u003e7 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea \u0026nbsp;\u003c/sup\u003eThe total exceeds 400 individuals because some individuals\u0026nbsp;were diagnosed with multiple types of cancer.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u0026nbsp;\u003c/sup\u003eParaganglioma (n=2\u0026nbsp;probands), bladder (n=2), liver (n=2), xeroderma pigmentosum (n=1), lymphoma (n=1), bone (n=1), adrenocortical (n=1), melanoma (n=1) and esophageal (n=1).\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec \u0026nbsp;\u003c/sup\u003eEsophageal (n=14 cases), lymphoma (n=14), intestinal polyps (n=12), kidney (n=12), sarcomas (n=10), mouth (n=9), bone (n=7), gallbladder (n=6), bladder (n=5), laryngeal (n=5), neurofibromatosis (n=5), myeloma (n=5), \u0026nbsp;head or neck (n=5), testicular (n=4), tracheal (n=4), penile (n=3), endometrium (n=2), mediastinal (n=2), eye (n=2), spinal cord (n=1), neuroendocrine (n=1), leg (n=1), peritoneal (n=1), abdominal (n=1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiagnostic yield and genetic findings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong all individuals recruited, 77 (19%) received a positive WGS result, leading to a conclusive diagnosis (Fig. 1A; Supplementary Table 1). Additionally, 103 probands (26%) had inconclusive results, while 220 cases (55%) showed no clinically relevant variants, resulting in negative findings.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsidering the variant distribution, P/LP variants were identified in 23% of individuals (92/400), covering 32 genes. The most frequently affected genes were \u003cem\u003eBRCA1\u003c/em\u003e (17.7%), \u003cem\u003eBRCA2\u003c/em\u003e (17.7%), \u003cem\u003eMUTYH\u003c/em\u003e (6.3%), \u003cem\u003eNF1\u003c/em\u003e (5.2%), \u003cem\u003eATM\u003c/em\u003e (4.2%), and \u003cem\u003eTP53\u003c/em\u003e (4.2%) (Fig. 1B). Among the detected variants, 79 were unique (Supplementary Table 2), with frameshift deletions being the most common (32.9%), followed by stop-gain mutations (21.5%), nonsynonymous SNVs (13.9%), and splice site SNVs (11.4%) (Fig. 1C). There were two LP intronic SNVs detected (2.5%), one of which was a deep intronic variant in \u003cem\u003eNF1\u003c/em\u003e (c.1642-449A\u0026gt;G), that would have been missed through panel or exome sequencing. Additionally, 13 recurrent variants (found in at least two unrelated individuals) were identified in seven genes, including \u003cem\u003eBRCA1\u003c/em\u003e, \u003cem\u003eBRCA2\u003c/em\u003e, and \u003cem\u003eMUTYH\u003c/em\u003e (Supplementary Table 2).\u003c/p\u003e\n\u003cp\u003eAlmost all individuals with a positive test result harbored a single P/LP variant defining their diagnosis. However, 7.8% of these probands were found to be double heterozygotes, carrying two P/LP variants, typically in different genes. Specific cases exhibiting these genetic profiles were (Supplementary Table 2): one patient diagnosed with breast cancer exhibiting variants in\u0026nbsp;\u003cem\u003eBRCA2\u003c/em\u003e and a heterozygous variant in\u0026nbsp;\u003cem\u003eMUTYH\u003c/em\u003e; another patient with thyroid cancer also presenting with variants in\u0026nbsp;\u003cem\u003eBRCA2\u003c/em\u003e and a heterozygous variant in\u0026nbsp;\u003cem\u003eMUTYH\u003c/em\u003e. Further, among breast cancer probands, one carried variants in\u0026nbsp;\u003cem\u003eATM\u003c/em\u003e and\u0026nbsp;\u003cem\u003eBRCA2\u003c/em\u003e; another, in\u0026nbsp;\u003cem\u003eBRCA1\u003c/em\u003e and\u0026nbsp;\u003cem\u003eBRCA2\u003c/em\u003e; and a third had a\u0026nbsp;\u003cem\u003eBRCA1\u003c/em\u003e SNV concurrently with a CNV. Additionally, one patient presenting with multiple subcutaneous nodules and facial dysmorphisms harbored two variants in\u0026nbsp;\u003cem\u003eANTXR2\u003c/em\u003e (phase undefined). Beyond these primary findings, 3.8% of consented patients (15/392) exhibited secondary findings in ACMG-recommended genes, predominantly\u0026nbsp;\u003cem\u003eTTR\u003c/em\u003e and\u0026nbsp;\u003cem\u003eTPM1\u003c/em\u003e (Supplementary Table 2).\u003c/p\u003e\n\u003cp\u003eThere were 14 probands (3.5% of all cases) carrying P/LP variants but still presenting inconclusive WGS results. Most of these patients carried variants in genes with limited association with their diagnosed cancer type or had isolated monoallelic variants in genes associated with recessive disorders. For example, 10 patients had a personal history of breast cancer and presented P/LP variants in \u003cem\u003eMUTYH\u003c/em\u003e, \u003cem\u003eXRCC2\u003c/em\u003e, \u003cem\u003ePOLH\u003c/em\u003e, \u003cem\u003eFANCA\u003c/em\u003e, \u003cem\u003eMSH3\u003c/em\u003e, \u003cem\u003eRAD50\u003c/em\u003e, \u003cem\u003eSDHB\u003c/em\u003e, or \u003cem\u003eNTHL1\u003c/em\u003e (Supplementary Table 2). One patient had adrenocortical carcinoma and an LP variant in \u003cem\u003eXRCC2,\u003c/em\u003e and the remaining patients had ovarian cancer and variants in \u003cem\u003eMUTYH\u003c/em\u003e and \u003cem\u003eLZTR1\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eA total of 120 VUS were reported, with at least one identified in 24.2% of the patients (97/400). Among these, 22 patients harbored two or more VUS. Additionally, five VUS were found in at least two unrelated patients (Supplementary Table 2). Overall, these VUS were distributed across 49 distinct genes, with the highest frequencies observed in \u003cem\u003eBRCA2\u003c/em\u003e (10.9%), \u003cem\u003eATM\u003c/em\u003e (6.7%), \u003cem\u003ePALB2\u003c/em\u003e (6.7%), \u003cem\u003eCHEK2\u0026nbsp;\u003c/em\u003e(5.9%), \u003cem\u003eMSH2\u0026nbsp;\u003c/em\u003e(5%), \u003cem\u003ePOLE\u0026nbsp;\u003c/em\u003e(5%), \u003cem\u003eAPC\u003c/em\u003e (4.2%), \u003cem\u003eMSH6\u003c/em\u003e (3.4%), \u003cem\u003eATR\u003c/em\u003e (2.5%), \u003cem\u003eBRCA1\u003c/em\u003e (2.5%), \u003cem\u003eBRIP1\u003c/em\u003e (2.5%) and \u003cem\u003ePOLD1\u003c/em\u003e (2.5%) (Fig. 2; Supplementary Table 2).\u003c/p\u003e\n\u003cp\u003eThe distribution of cancer types according to variant classification showed that breast cancer, the most frequent diagnosis in the cohort, contributed to the largest number of cases without identified variants, followed by those with VUS, and then P and LP variants. Colorectal, ovarian, and thyroid cancers were also among the more represented cancer types and exhibited varying distributions across classification categories. Other conditions, including kidney, stomach, endometrial, and adrenal cancers, as well as cancer-predisposing genetic disorders such as neurofibromatosis and paraganglioma, were less common but appeared in multiple variant categories. Overall, VUS represented a considerable proportion of the variants observed, and P/LP variants were distributed across different cancer types, most notably in breast, colorectal, and ovarian cancers, as well as in neurofibromatosis and paraganglioma.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur study in a genetically underrepresented admixed population found an overall positivity rate of 23% for pathogenic or likely pathogenic variants in hereditary cancer predisposition genes. Specifically, our diagnostic yield, representing cases where a P/LP variant provided a clear genetic justification for the cancer diagnosis, was 19%. This aligns with reported rates ranging from 5.1% to 27% in global studies and 16.4% to 27% in Brazilian cohorts (18,19,24\u0026ndash;34). Variability in positivity rates across studies is influenced by differences in inclusion criteria, cancer distribution among participants, sequencing methods, analysis pipelines, gene panel selection, and CNV evaluation (19,25,35). WGS has demonstrated a 5.1% increase in diagnostic yield for undiagnosed familial cancer cases previously tested with single or multigene panels, offering advantages by detecting a broader range of genetic alterations, including those in non-coding regions, and enabling cost-effective reanalysis to improve diagnostic accuracy (31). Indeed, one patient, undergoing investigation for a clinical suspicion of neurofibromatosis type 1, had a deep intronic variant identified in \u003cem\u003eNF1\u003c/em\u003e, that would not have been detected by exome sequencing or panel testing. Functional studies have shown that this variant induces a damaging effect, causing abnormal splicing (36).\u0026nbsp;While this variant has been functionally assessed, other deep intronic variants may also be present, whose pathogenic effects remain to be fully understood.\u003c/p\u003e\n\u003cp\u003eThe study enrolled 400 individuals, predominantly female, most of whom were aged 30\u0026ndash;49 years and were first diagnosed within a similar age range. The high proportion of individuals with a single primary tumor may reflect the recent nature of their cancer diagnoses, as indicated by their current age. The predominance of breast cancer in both personal and family histories aligns with the prevalence of female patients investigated for hereditary breast cancer syndromes. The observed diversity of other suspected hereditary cancer syndromes highlights the challenges in genetic counseling for this population, emphasizing the need for further studies to explore how specific genetic profiles and demographic factors interact to influence hereditary cancer risks.\u003c/p\u003e\n\u003cp\u003eKey genes identified among P/LP carriers included \u003cem\u003eBRCA1, BRCA2, MUTYH, NF1, ATM,\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;TP53\u003c/em\u003e, consistent with findings from Oliveira et al. (32) and Leite et al. (18), who also identified high frequencies of \u003cem\u003eBRCA1/2\u003c/em\u003e, \u003cem\u003eMUTYH\u003c/em\u003e, and \u003cem\u003eTP53\u003c/em\u003e variants in Brazilian cohorts. The prevalence of \u003cem\u003eBRCA1/2\u003c/em\u003e variants reflects the enrichment of breast cancer cases in our study, while \u003cem\u003eMUTYH\u003c/em\u003e, \u003cem\u003eTP53\u003c/em\u003e, and \u003cem\u003eATM\u003c/em\u003e were significant among non-BRCA genes. Recurrent variants were observed in seven genes, notably the \u003cem\u003eBRCA1\u003c/em\u003e c.3331_3334del and the c.211A\u0026gt;G, which have been documented in other Brazilian studies (17,37\u0026ndash;39). The absence of the Ashkenazi-associated \u003cem\u003eBRCA1\u003c/em\u003e c.5266dupC variant in our cohort, a variant that accounts for approximately 20% of \u003cem\u003eBRCA1\u003c/em\u003e pathogenic variants in South Brazil, suggests its low prevalence in Northeast Brazil compared to other regions (17,37,39,40),\u0026nbsp;likely reflecting the distinct genetic background of the studied population and the diversity of Brazilian genetics. In \u003cem\u003eBRCA2\u003c/em\u003e, the variant c.2808_2811del identified in two patients, was recurrent in other studies (37,38), while the c.7124T\u0026gt;G variant, identified in three patients, was rare in both other Brazilian and global datasets (41). The \u003cem\u003eMUTYH\u003c/em\u003e c.1103G\u0026gt;A, identified in three patients in our cohort, also recurred in Brazilian patients with colorectal cancer predisposition (42).\u003c/p\u003e\n\u003cp\u003eDouble heterozygosity was observed in 7.8% of the positive cases, representing 1.5% of all recruited participants, consistent with findings by Megid et al. (43) and Agaoglu \u0026amp; Doganay (44). Research on the combined impact of double heterozygosity on cancer risk is limited, and the diversity of variant combinations complicates comparisons across studies, highlighting the need for larger investigations and functional analyses to better understand digenic variant effects for improved genetic surveillance and disease management (32,43,44).\u003c/p\u003e\n\u003cp\u003eInconclusive cases accounted for 26% of participants and included those with VUS, P or LP variants in genes not strongly linked to the suspected syndrome, or isolated monoallelic variants for recessive disorders. For example, monoallelic \u003cem\u003eMUTYH\u003c/em\u003e variants were identified in individuals with breast cancer. Although \u003cem\u003eMUTYH\u003c/em\u003e is typically associated with colorectal cancer risk, previous reports have suggested broader cancer associations for \u003cem\u003eMUTYH\u003c/em\u003e, though such links remain debated (28,33,45\u0026ndash;48). Similarly, rare findings in \u003cem\u003eXRCC2\u003c/em\u003e, \u003cem\u003ePOLH\u003c/em\u003e and \u003cem\u003eSDHB\u003c/em\u003e in breast cancer patients (genes typically associated with Fanconi Anemia, Xeroderma Pigmentosum and Pheochromocytomas/Paragangliomas, respectively), are consistent with studies suggesting potential links of those genes to breast cancer, although a definitive association remains uncertain (49\u0026ndash;59). Such results require further investigation to determine whether they represent novel associations or spurious links. Additionally, our study identified heterozygous P/LP variants in genes related to autosomal recessive conditions, such as \u003cem\u003eFANCA\u003c/em\u003e, \u003cem\u003eMSH3\u003c/em\u003e, \u003cem\u003eRAD50\u003c/em\u003e and \u003cem\u003eNTHL1\u003c/em\u003e. Del Valle et al. (60) found a significant association between \u003cem\u003eFANCA\u003c/em\u003e mutations and an increased risk of breast and/or ovarian cancer but recommended larger studies to better comprehend their role in cancer risk. These findings reinforce the need for careful interpretation of variants in genes linked to autosomal recessive disorders, where compound heterozygosity or homozygosity is necessary for full phenotypic expression.\u003c/p\u003e\n\u003cp\u003eVUS were reported in 24.2% of cases, lower than rates observed in panel-based or smaller-scale sequencing studies, which ranged up to 82.7% depending on the number of genes analyzed (18,19,24,25,28,30,32\u0026ndash;35). Rehm et al. (61) note that broader sequencing approaches like exome sequencing (ES) and WGS may yield fewer reported VUS due to selective reporting practices, focusing on clinically significant variants and opting not to report VUS with limited clinical correlation or weak pathogenic evidence. This highlights the importance of thorough variant assessment to minimize uncertainty in clinical contexts. Advances in genetic testing, particularly with NGS, have enhanced our ability to identify complex genetic alterations, identifying new risk genes and variant patterns across populations (30). Despite these advances, challenges remain, including addressing the high proportion of inconclusive cases (which are often due to the increased occurrence of VUS complicating clinical decision-making) and improving access to testing, especially in public healthcare systems of\u0026nbsp;LMIC countries like Brazil (62\u0026ndash;65).\u003c/p\u003e\n\u003cp\u003eThe growing accessibility of genomic sequencing has also led to an increased identification of secondary findings, and healthcare professionals should now be prepared to manage individuals with these discoveries, as they are becoming an increasingly common aspect of clinical practice (66). A small percentage of individuals in our cohort carried secondary findings in ACMG-recommended genes, including \u003cem\u003eMYBPC3\u003c/em\u003e, \u003cem\u003eTTN\u003c/em\u003e, and \u003cem\u003eTTR\u003c/em\u003e, which could have clinical implications beyond cancer risk, such as predisposition to cardiomyopathies or arrhythmias (67).These findings may affect cancer treatment protocols, as cardiotoxicity from certain chemotherapeutic agents could require modified plans or closer cardiac monitoring (67). This illustrates a gap in current cancer gene panels, which often exclude ACMG-recommended genes. Integrating ACMG findings into cancer genomic testing could improve patient care with a more comprehensive risk assessment. Further studies are needed to evaluate the clinical utility of incorporating these findings into hereditary cancer testing and prompt the development of broader gene panels.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur study, conducted as part of the Brazilian Rare Genomes Project, reinforces the importance of integrating genomic medicine into Brazil\u0026apos;s public healthcare system to ensure equitable access to cancer diagnosis and care. However, our findings should be interpreted considering certain limitations. While the analytical pipeline demonstrated high sensitivity (\u0026gt;99%) for detecting SNVs and small insertions/deletions (up to 20 bp) and \u0026gt;90% for CNVs affecting one or more exons, its sensitivity was reduced for variants larger than 20 bp and smaller than an exon. Furthermore, limitations include the use of a convenience sample predominantly consisting of female breast cancer patients, potential inaccuracies in medical records, and a sample size that, while representative of Bahia\u0026apos;s population, may not fully capture the state\u0026apos;s entire genetic diversity.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study provides the first comprehensive whole-genome characterization of hereditary cancer predisposition in an admixed Northeast Brazilian cohort, revealing a distinct genetic architecture marked by recurrent variants (e.g., \u003cem\u003eBRCA1\u003c/em\u003e c.3331_3334del), low prevalence of Ashkenazi-associated alleles (e.g., \u003cem\u003eBRCA1\u003c/em\u003e c.5266dupC), and novel deep intronic findings. We observed a 23% detection rate of pathogenic or likely pathogenic variants in cancer predisposition genes, emphasizing the critical role of comprehensive genetic testing in hereditary cancer risk assessment. Whole-genome sequencing provided diagnostic conclusions in 19% of cases and showed that broader techniques, despite potential for higher VUS rates, may ultimately yield fewer inconclusive findings. Diagnostic challenges persisted, as over half of the enrolled cases had no definitive findings, while others, even with P/LP findings, remained inconclusive. Our results offer insights into the genetic landscape of cancer predisposition in Bahia, Brazil, a population with a highly diverse genetic background. The findings highlight the need for improved access to genetic testing in public healthcare systems and the challenges of VUS interpretation in populations currently underrepresented in genomic studies and reference databases. This illustrates the need for tailored genetic testing panels. Further research on the clinical impact of novel and recurrent variants, alongside efforts to address genetic heterogeneity and complex etiologies, will be key to refining cancer risk assessments and guiding patient management.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The data supporting the findings of this study are not publicly available to protect participant privacy. A de-identified version of the dataset can be obtained from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eACKNOWLEDGMENTS\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research was made possible through access to the data and findings generated by the Brazilian Rare Genomes Project. P.I.P.R. and R.K. are research fellows for Brazil’s National Council for Scientific and Technological Development (CNPq). The Brazilian Rare Genomes Project Consortium is composed of the following members:\u0026nbsp;Antonio Victor Campos Coelho; Rafael Sales de Albuquerque; Catarina dos Santos Gomes; José Bandeira do Nascimento Junior; Gustavo Santos de Oliveira; Livia Maria Silva Moura; Luciana Souto Mofatto; Rafael Lucas Muniz Guedes; Rodrigo Araújo Sequeira Barreiro; Marcel Pinheiro Caraciolo; Ana Paula de Andrade Oliveira; Anne Caroline Barbosa Teixeira; Bruna Mascaro Cordeiro de Azevedo; Carolina Dias Carlos; Lucas Santos de Santana; Marina Cadena da Matta; Matheus Martinelli Lima; Nuria Bengala Zurro; Renata Yoshiko Yamada; Vivian Pedigone Cintra; Gabriela Pereira Campilongo; Gabriela Borges Cherulli Colichio; Renata Martins Ribeiro da Silva; Caio Robledo D’Angioli Costa Quaio; Carolina Araújo Moreno; Eduardo Perrone; Jéssica Grasiela Araújo Espolaor; Joana Rosa Marques Prota; José Ricardo Magliocco Ceroni; Kelin Chen; Luiza do Amaral Virmond; Marina de Franca Basto Silva; Michele Patricia Migliavacca; Renata Moldenhauer Minillo; Thiago Yoshinaga Tonholo Silva; Karla de Oliveira Pelegrino; Tatiana Ferreira de Almeida; João Bosco Oliveira.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTIONS\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis, as well as pre-test and post-test counseling and the completion of digital forms/electronic medical records with the construction of pedigrees and family histories, were performed by T.M.B.M.L., L.S.M.B., T.C.M.F., A.C.M.A., I.L.O.N., M.B.P.T., A.V.C.C., E.P and the B.R.G.P.C. team. The first draft of the manuscript was written by A.C.M.A., and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Brazilian Rare Genomes Project was funded by Hospital Israelita Albert Einstein in partnership with the Support Program for the Institutional Development of the Unified Health System (PROADI-SUS), from the Brazilian Ministry of Health (Law 12.101/2009).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCOMPETING INTERESTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eADDITIONAL INFORMATION\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary information\u003c/strong\u003e The online version contains supplementary material available at:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrespondence\u003c/strong\u003e and requests for materials should be addressed to Ana Camila Mendes Andrade.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLu KH, Wood ME, Daniels M, Burke C, Ford J, Kauff ND, et al. 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Front Oncol. 2022 Sep 5;12. \u003c/li\u003e\n\u003cli\u003eSandoval RL, Leite ACR, Barbalho DM, Assad DX, Barroso R, Polidorio N, et al. Germline molecular data in hereditary breast cancer in Brazil: Lessons from a large single-center analysis. PLoS One. 2021 Feb 1;16(2 February 2021). \u003c/li\u003e\n\u003cli\u003eFelix GES, Guindalini RSC, Zheng Y, Walsh T, Sveen E, Lopes TMM, et al. Mutational spectrum of breast cancer susceptibility genes among women ascertained in a cancer risk clinic in Northeast Brazil. Breast Cancer Res Treat. 2022 Jun 1;193(2):485\u0026ndash;94. \u003c/li\u003e\n\u003cli\u003eRichards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: A joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. 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Spectrum of germline pathogenic variants in Brazilian hereditary breast/ovarian cancer cases. Breast Cancer Res Treat. 2024 Oct 1; \u003c/li\u003e\n\u003cli\u003e\u0026Ouml;zdemir Z, \u0026Ccedil;evik E, \u0026Ouml;ks\u0026uuml;zoğlu \u0026Ouml;B\u0026Ccedil;, Doğan M, Ateş \u0026Ouml;, Esin E, et al. Uncommon variants detected via hereditary cancer panel and suggestions for genetic counseling. Mutation Research - Fundamental and Molecular Mechanisms of Mutagenesis. 2023 Jul 1;827. \u003c/li\u003e\n\u003cli\u003eDouben HCW, Nellist M, van Unen L, Elfferich P, Kasteleijn E, Hoogeveen-Westerveld M, et al. High-yield identification of pathogenic NF1 variants by skin fibroblast transcriptome screening after apparently normal diagnostic DNA testing. Hum Mutat. 2022 Dec 1;43(12):2130\u0026ndash;40. \u003c/li\u003e\n\u003cli\u003ede Freitas Ribeiro AA, Junior NMC, dos Santos LL. Systematic review of the molecular basis of hereditary breast and ovarian cancer syndrome in Brazil: the current scenario. Vol. 29, European Journal of Medical Research. BioMed Central Ltd; 2024. \u003c/li\u003e\n\u003cli\u003eCotrim DP, Ribeiro ARG, Paix\u0026atilde;o D, De Queiroz Soares DC, Jbili R, Pandolfi NC, et al. Prevalence of BRCA1 and BRCA2 pathogenic and likely pathogenic variants in non-selected ovarian carcinoma patients in Brazil. BMC Cancer. 2019 Jan 3;19(1). \u003c/li\u003e\n\u003cli\u003ePalmero EI, Carraro DM, Alemar B, Moreira MAM, Ribeiro-Dos-Santos \u0026Acirc;, Abe-Sandes K, et al. The germline mutational landscape of BRCA1 and BRCA2 in Brazil. Sci Rep. 2018 Dec 1;8(1). \u003c/li\u003e\n\u003cli\u003eGomes R, Soares BL, Felicio PS, Michelli R, Netto CBO, Alemar B, et al. Haplotypic characterization of BRCA1 c.5266dupC, the prevailing mutation in Brazilian hereditary breast/ovarian cancer. Genet Mol Biol. 2020;43(2). \u003c/li\u003e\n\u003cli\u003eRebbeck TR, Friebel TM, Friedman E, Hamann U, Huo D, Kwong A, et al. Mutational spectrum in a worldwide study of 29,700 families with BRCA1 or BRCA2 mutations. Hum Mutat. 2018 May 1;39(5):593\u0026ndash;620. \u003c/li\u003e\n\u003cli\u003ePitroski CE, Cossio SL, Koehler-Santos P, Graudenz M, Prolla JC, Ashton-Prolla P. Frequency of the common germline MUTYH mutations p.G396D and p.Y179C in patients diagnosed with colorectal cancer in Southern Brazil. Int J Colorectal Dis. 2011 Jul;26(7):841\u0026ndash;6. \u003c/li\u003e\n\u003cli\u003eMegid TBC, Barros-Filho MC, Pisani JP, Achatz MI. Double heterozygous pathogenic variants prevalence in a cohort of patients with hereditary breast cancer. Front Oncol. 2022 Aug 8;12. \u003c/li\u003e\n\u003cli\u003eAgaoglu NB, Doganay L. Concurrent pathogenic variations in patients with hereditary cancer syndromes. Eur J Med Genet. 2021 Dec 1;64(12). \u003c/li\u003e\n\u003cli\u003eVenesio T, Balsamo A, D\u0026rsquo;Agostino VG, Ranzani GN. MUTYH-associated polyposis (MAP), the syndrome implicating base excision repair in inherited predisposition to colorectal tumors. Vol. 2 AUG, Frontiers in Oncology. Frontiers Research Foundation; 2012. \u003c/li\u003e\n\u003cli\u003eRizzolo P, Zelli V, Silvestri V, Valentini V, Zanna I, Bianchi S, et al. Insight into genetic susceptibility to male breast cancer by multigene panel testing: Results from a multicenter study in Italy. Int J Cancer. 2019 Jul 15;145(2):390\u0026ndash;400. \u003c/li\u003e\n\u003cli\u003eOut AA, Wasielewski M, Huijts PEA, Van Minderhout IJHM, Houwing-Duistermaat JJ, Tops CMJ, et al. MUTYH gene variants and breast cancer in a Dutch case-control study. Breast Cancer Res Treat. 2012;134(1):219\u0026ndash;27. \u003c/li\u003e\n\u003cli\u003eBeiner ME, Zhang WW, Zhang S, Gallinger S, Sun P, Narod SA. Mutations of the MYH gene do not substantially contribute to the risk of breast cancer. Breast Cancer Res Treat. 2009 Apr;114(3):575\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eGratchev A, Strein P, Utikal J, Goerdt S. Molecular genetics of Xeroderma pigmentosum variant. 2003. \u003c/li\u003e\n\u003cli\u003eGirard E, Eon-Marchais S, Olaso R, Renault AL, Damiola F, Dondon MG, et al. Familial breast cancer and DNA repair genes: Insights into known and novel susceptibility genes from the GENESIS study, and implications for multigene panel testing. Int J Cancer. 2019 Apr 15;144(8):1962\u0026ndash;74. \u003c/li\u003e\n\u003cli\u003eJalkh N, Chouery E, Haidar Z, Khater C, Atallah D, Ali H, et al. Next-generation sequencing in familial breast cancer patients from Lebanon. BMC Med Genomics. 2017 Feb 15;10(1):1\u0026ndash;12. \u003c/li\u003e\n\u003cli\u003ePelttari LM, Kiiski JI, Ranta S, Vilske S, Blomqvist C, Aittom\u0026auml;ki K, et al. RAD51, XRCC3, and XRCC2 mutation screening in Finnish breast cancer families. Springerplus. 2015 Dec 1;4(1). \u003c/li\u003e\n\u003cli\u003eHilbers FS, Wijnen JT, Hoogerbrugge N, Oosterwijk JC, Collee MJ, Peterlongo P, et al. Rare variants in XRCC2 as breast cancer susceptibility alleles. J Med Genet. 2012 Oct;49(10):618\u0026ndash;20. \u003c/li\u003e\n\u003cli\u003eCouch FJ, Hart SN, Sharma P, Toland AE, Wang X, Miron P, et al. Inherited mutations in 17 breast cancer susceptibility genes among a large triple-negative breast cancer cohort unselected for family history of breast cancer. Journal of Clinical Oncology. 2015 Feb 1;33(4):304\u0026ndash;11. \u003c/li\u003e\n\u003cli\u003eGolmard L, Cast\u0026eacute;ra L, Krieger S, Moncoutier V, Abidallah K, Tenreiro H, et al. Contribution of germline deleterious variants in the RAD51 paralogs to breast and ovarian cancers /631/208/68 /631/67/1347 article. 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Am J Surg. 2018 Dec 1;216(6):1148\u0026ndash;54. \u003c/li\u003e\n\u003cli\u003eChiang J, Tze ;, Chia H, Yuen J, Shaw T, Li ST, et al. Impact of Variant Reclassification in Cancer Predisposition Genes on Clinical Care [Internet]. 2021. Available from: https://doi.org/10.\u003c/li\u003e\n\u003cli\u003eStanislaw C, Xue Y, Wilcox WR. Genetic evaluation and testing for hereditary forms of cancer in the era of next-generation sequencing. Vol. 13, Cancer Biology and Medicine. Cancer Biology and Medicine; 2016. p. 55\u0026ndash;67. \u003c/li\u003e\n\u003cli\u003eFrancies FZ, Hull R, Khanyile R, Dlamini Z. Breast cancer in low-middle income countries: abnormality in splicing and lack of targeted treatment options [Internet]. Vol. 10, Am J Cancer Res. 2020 May. Available from: www.ajcr.us/\u003c/li\u003e\n\u003cli\u003ePerrone E, Virmond L, Coelho AVC, De Fran\u0026ccedil;a M, Moreno CA, Prota JRM, et al. ACMG secondary findings in the Brazilian rare genomes project: insights from 5402 genome sequencing. J Hum Genet. 2025; \u003c/li\u003e\n\u003cli\u003eKim Y, Seidman JG, Seidman CE. Genetics of cancer therapy-associated cardiotoxicity. J Mol Cell Cardiol. 2022 Jun 1;167:85\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"npj-genomic-medicine","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjgenmed","sideBox":"Learn more about [npj Genomic Medicine](http://www.nature.com/npjgenmed/)","snPcode":"41525","submissionUrl":"https://mts-npjgenmed.nature.com/","title":"npj Genomic Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"hereditary cancer syndromes, whole genome sequencing, genetic diagnosis, germline pathogenic variant, variant of uncertain significance","lastPublishedDoi":"10.21203/rs.3.rs-7104192/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7104192/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHereditary cancer syndromes, caused by inherited genetic alterations, account for 5\u0026ndash;10% of all cancers, posing substantial diagnostic and management challenges. Despite advances in next-generation sequencing technologies, access to genetic testing remains limited, particularly in low- and middle-income countries (LMICs), such as Brazil. Genetic heterogeneity and complex etiopathogenic patterns further complicate case resolution. This study enrolled genetically underrepresented admixed individuals at risk for hereditary cancer at a Reference Center for Rare Diseases in Salvador, Bahia, Brazil. A total of 400 individuals meeting hereditary cancer risk criteria underwent whole genome sequencing from whole blood as part of the Brazilian Rare Genomes Project. Clinical, demographic, and genetic data were jointly analyzed to investigate cancer predisposition. Most participants were female (95%), self-identified as brown/admixed (74.3%), and reported a personal history of breast cancer (74%). Pathogenic or likely pathogenic (P/LP) variants in hereditary cancer-related genes were identified in 23% of individuals, most frequently in \u003cem\u003eBRCA1\u003c/em\u003e (17.7%), \u003cem\u003eBRCA2\u003c/em\u003e (17.7%), \u003cem\u003eMUTYH\u003c/em\u003e (6.3%), \u003cem\u003eNF1\u003c/em\u003e (5.2%), \u003cem\u003eATM\u003c/em\u003e (4.2%), and \u003cem\u003eTP53\u003c/em\u003e (4.2%) genes. Diagnostic conclusions were reached in 19% of cases with 7.8% of these harboring P/LP variants in two different genes. Inconclusive cases accounted for 26% of the cohort and included those with P/LP findings in genes with an unclear association to the patient\u0026rsquo;s cancer type, variants in heterozygous states for recessive conditions or variants of uncertain significance. The remaining 55% of cases were negative. Additionally, ACMG-recommended secondary findings were identified in 3.8% of patients. Notably, one patient carried a deep intronic variant that would have been missed by panel or exome sequencing. These findings highlight the genetic diversity in hereditary cancer syndromes and emphasize the need for expanded access to genetic testing and research to improve diagnostic outcomes.\u003c/p\u003e","manuscriptTitle":"Whole genome profiling of 400 patients at risk for hereditary cancer in a Brazilian cohort","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-22 10:28:29","doi":"10.21203/rs.3.rs-7104192/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-26T14:03:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-21T19:57:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-10T14:17:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"7096459443694330370490300561679183114","date":"2025-09-08T14:06:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"318249958020199050550156350208946381244","date":"2025-09-05T14:10:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"52776914187687604465622588921525421077","date":"2025-09-04T19:33:18+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-14T15:03:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-11T19:38:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-16T07:04:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Genomic Medicine","date":"2025-07-11T19:19:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-genomic-medicine","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjgenmed","sideBox":"Learn more about [npj Genomic Medicine](http://www.nature.com/npjgenmed/)","snPcode":"41525","submissionUrl":"https://mts-npjgenmed.nature.com/","title":"npj Genomic Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"87ca7a9f-77ce-4958-8131-c2df64eb2e7d","owner":[],"postedDate":"August 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":53400391,"name":"Biological sciences/Cancer"},{"id":53400392,"name":"Biological sciences/Genetics"},{"id":53400393,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2025-09-26T14:08:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-22 10:28:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7104192","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7104192","identity":"rs-7104192","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}