Multilocus Inherited Neoplasia Alleles Syndrome: A Retrospective Review from a Canadian Single Institution

Multilocus Inherited Neoplasia Alleles Syndrome: A Retrospective Review from a Canadian Single Institution | 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 Multilocus Inherited Neoplasia Alleles Syndrome: A Retrospective Review from a Canadian Single Institution Raymond Kim, Kathleen Orrell, Malek Horani, María Sanabria-Salas, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8149436/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Genetic testing in hereditary cancer is evolving from single-gene focused approaches on affected individuals to multi-gene panel testing in affected individuals and unaffected relatives. The widespread use of multi-gene panel testing has led to the identification of individuals with two or more pathogenic or likely pathogenic variants in hereditary cancer susceptibility genes (CSGs), termed Multilocus Inherited Neoplasia Allele Syndrome (MINAS) carriers. It remains unclear whether MINAS carriers are at increased risk of multiple, atypical or more severe cancer phenotypes, and currently, there is no consensus on how best to identify and manage cancer risk. In this retrospective study, we identified 54 MINAS carriers at Princess Margaret Cancer Centre in Toronto, Canada. The majority of affected MINAS carriers had a cancer consistent with expression of at least one pathogenic variant, although nearly 40% were diagnosed with at least one cancer outside of the typical spectrum of their CSGs. The most frequent gene pair combinations included hereditary breast cancer genes, with some carriers exhibiting earlier age of breast cancer onset than single CSG variants reported in the literature. Overall, our study indicates that the cancer spectrum associated with certain CSGs is expanding and suggests more intensive cancer surveillance for subgroups of MINAS carriers with hereditary breast cancer CSGs. Health sciences/Medical research/Genetics research Health sciences/Diseases/Cancer MINAS hereditary cancer cancer susceptibility genes Figures Figure 1 Figure 2 Introduction Hereditary cancer syndromes account for approximately 5–10% of all cancers and describe a spectrum of cancers that are caused by inherited pathogenic or likely pathogenic variants in cancer susceptibility genes (CSGs) ( 1 ). Hereditary cancer syndromes include the well-known and relatively common BRCA1 and BRCA2 associated breast, ovarian and prostate cancers, and lesser-known and comparatively more rare cancer syndromes, including EGFR associated lung cancer. Traditionally, hereditary cancers have been identified by recognizing clusters of related individuals with a high burden of cancer, followed by targeted testing of individual genes. With the advent of next generation sequence, there is a paradigm shift toward multi-gene panel testing that allows for simultaneous detection of multiple CSGs, which have increasingly detected pathogenic variants not predicted by phenotype or family history. Further, multi-gene panel testing has led to the detection of carriers of two or more pathogenic or likely pathogenic variants in CSGs, termed M ultilocus I nherited N eoplasia A llele S yndrome, or MINAS ( 2 ), with an estimated prevalence between 0.2–2.4% ( 3 – 5 ). Although early MINAS studies included both autosomal dominant (AD) and recessive (AR) gene pair combinations ( 3 ), more recent studies have analyzed AD-AD and AD-AR gene pair combinations separately, citing higher penetrance and higher frequency of malignancies in AD-AD gene pair combinations ( 4 , 5 ). Hereditary cancer syndromes have been associated with an elevated lifetime risk for specific cancers and more severe cancer phenotypes ( 6 ). Carriers of single pathogenic variants in CSGs undergo lifelong specialized cancer surveillance, and these genetic test results provide information on cancer risks and implications for other family members, such as the potential need for cascade testing ( 7 ). The results of surveillance are actionable, guiding decision making around preventive or risk-reducing measures and the use of certain therapeutic agents in cancer treatments. Compared to single CSG variants, it has long been hypothesized that MINAS carriers are at elevated risk of multiple, atypical and more severe cancers because of synergistic interaction CSGs in related tumorigenic pathways or in chromosomal proximity ( 2 ). Research into this area has yielded conflicting results, with reports supporting that CSGs can act both independently (each variant contributes independently to overall cancer risk and characteristics) and synergistically (variants interact in such a way that enhances their impact on cancer risk and characteristics) ( 3 , 4 , 8 – 14 ). As present, the recommended screening guidelines for MINAS carriers is to follow the established protocols for each CSG independently. In this retrospective cohort study, we identify and characterize MINAS carriers (defined here as AD-AD gene pair combinations) who were diagnosed at Princess Margaret Cancer Centre from January 1, 2017, to September 30, 2024. We provide information about the age of onset, clinical characteristics and spectrum of associated cancers, and compare to carriers with AD-AR gene pair combinations in our cohort. Materials and Methods Study Cohort and Ethics Committee Approval We conducted a retrospective cohort study of individuals referred for genetic counseling and testing between January 1, 2017, and September 30, 2024, to identify and characterize AD-AD and AD-AR carriers, defined as those harboring germline pathogenic variants in two or more different CSGs. A total of 65 eligible cases from 60 families were identified through the Progeny database of the Bhalwani Familial Cancer Clinic at the Princess Margaret (PM) Cancer Centre, University Health Network (UHN), Toronto, Canada. Ethics approval for this retrospective chart-review study was granted by the UHN Research Ethics Board (ID: 24-5884). The study was classified as no-risk and exempt from written informed consent. Data Collection We collected detailed information across four domains by reviewing data from the Progeny database and the Electronic Medical Records (EMR): i) Demographic data, including sex and self-reported ancestry from maternal and paternal lineages; ii) Clinical data, including affected/unaffected status, cancer type(s), number of primary cancers, age at each diagnosis, and breast cancer receptor status when applicable; iii) Genetic data, including HUGO gene symbols, HGVS nomenclature for each pathogenic variant, pathogenicity interpretation, inheritance pattern, and cancer risk category per gene (high risk (HR), moderate risk (MR), or low-risk (LR)) based on the National Comprehensive Cancer Network Guidelines ( 15 , 16 ) (Supplemental Table 1) (all APC carriers have the p.I1301K allele and are classified as LR) and iv) Family history among first- and second-degree relatives. The clinical team assessed, for each individual, whether none (0), one ( 1 ) or both ( 2 ) variants were phenotypically expressed in the proband or family members, based on their established association with diagnosed cancer types, reported family history and known inheritance patterns (autosomal dominant (AD) or autosomal recessive (AR)) (Supplemental Table 2) . The presence of an atypical phenotype was determined if there was one or more cancers expressed that were not associated with pathogenic variant expression. A dominant inheritance mode was assigned to genes with both AD and AR implications if the heterozygous state was linked to cancer susceptibility (e.g., ATM ). To safeguard confidentiality, all records were de-identified using unique Study IDs. Genetic Counseling and Test Results All patients were referred to the Princess Margaret Genetics Clinic or had their charts reviewed by certified genetic counsellors, the medical genetics team or an oncologist to determine the most appropriate genetic test(s) based on each patient's personal and family history. Decisions were guided by institutional protocols and provincial guidelines, such as the updated Cancer Care Ontario Hereditary Cancer Testing Eligibility Criteria ( 17 ). Genetic testing was performed at Clinical Laboratory Improvement Amendments (CLIA)-certified laboratories. Following result disclosure, all individuals received post-test counseling and were referred to appropriate multidisciplinary teams for personalized risk management and clinical follow-up. Individuals with two or more germline variants in different genes, classified as pathogenic, likely pathogenic, or risk alleles (for example, APC c.3920T > A (p.Ile1307Lys), which is risk factor for colorectal cancer in individuals of Ashkenazi Jewish ancestry and carries specific screening recommendations), were included in this study. Variant classification followed the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines ( 18 ). All variant nomenclature was standardized according to Human Genome Variation Society (HGVS) conventions using the VariantValidator tool ( https://variantvalidator.org ). Statistical Analysis Descriptive statistics were used to summarize demographic, clinical, and genetic characteristics of the study cohort. Categorical variables were described using frequencies and percentages. Age at first cancer diagnosis was the only continuous variable analyzed, and it was described using measures of central tendency or categorized into age ranges. Normality and homogeneity of variance for age were assessed using the Shapiro-Wilk and Levene’s tests, respectively. Implicated genes were assigned a cancer risk level (high risk (HR), moderate risk (MR), or low risk (LR)) and an inheritance pattern (AD or AR) (Supplemental Table 1) . Based on the inheritance pattern of the implicated genes per individual (Supplemental Table 2) , two groups were formed: AD-AD combinations and AD-AR combinations. Group comparisons for categorical variables, which often included small cell counts (< 5), were performed using Fisher’s exact test; otherwise, chi-square tests were applied. Differences in age at diagnosis between groups were assessed using independent t-tests. Besides gene combination category, cases were also stratified by clinical status (affected vs. unaffected), and the number of phenotypically expressed variants (0, 1, or 2) in the individual and family based on their cancer history. Statistical significance was set at p ≤ 0.05. Cancer co-occurrence, as well as gene co-occurrence patterns, were visualized using circular chord diagrams (circlize package), and other data visualizations were generated with ggplot2. All analyses were conducted in R (version 4.4.2). Results Clinical characteristics of MINAS carriers and relatives We identified 65 individuals based on the search criteria (Supplemental Table 3) . Of the 65 cases, a total of 54 individuals from 49 families were categorized as MINAS (AD-AD gene combinations), while 11 individuals were AD-AR gene combinations. Most MINAS carriers were female (57%; 31/54). Self-reported ancestry across both lineages was primarily White (63%), followed by Ashkenazi Jewish (17%) and South Asian (7.5%) ( Table 1 ). Table 1 Comparison of AD-AD and AD-AR gene combinations across demographic, clinical and genetic variables. Variable Overall N = 65 1 AD-AD N = 54 1 AD-AR N = 11 1 p-value 2 Sex 0.181 Female 40 (62%) 31 (57%) 9 (82%) Male 25 (38%) 23 (43%) 2 (18%) Age of first cancer 0.522 N Non-missing 46 38 8 Mean (SD) 47 ( 18 ) 48 ( 19 ) 44 ( 10 ) Median (Q1, Q3) 49 (33, 59) 52 (31, 62) 40 (36, 54) Min, Max 4, 83 4, 83 31, 59 Self-reported ancestry (both lineages) 0.755 White 76 (62%) 67 (63%) 9 (56%) Ashkenazi Jewish 22 (18%) 18 (17%) 4 (25%) South Asian 10 (8.2%) 8 (7.5%) 2 (13%) Southeast Asian 4 (3.3%) 4 (3.8%) 0 (0%) Latino 3 (2.5%) 2 (1.9%) 1 (6.3%) Middle Eastern 3 (2.5%) 3 (2.8%) 0 (0%) Black or African descent 2 (1.6%) 2 (1.9%) 0 (0%) East Asian 2 (1.6%) 2 (1.9%) 0 (0%) Number of cancers 0.807 0 19 (29%) 16 (30%) 3 (27%) 1 32 (49%) 25 (46%) 7 (64%) 2 9 (14%) 8 (15%) 1 (9.1%) 3 5 (7.7%) 5 (9.3%) 0 (0%) Cancer type 0.338 Breast 22 (34%) 18 (32%) 4 (44%) Prostate 7 (11%) 7 (13%) 0 (0%) Hematologic Disorders 6 (9.2%) 5 (8.9%) 1 (11%) Melanoma 5 (7.7%) 5 (8.9%) 0 (0%) Ovarian 5 (7.7%) 4 (7.1%) 1 (11%) Renal 5 (7.7%) 5 (8.9%) 0 (0%) Endometrial 2 (3.1%) 2 (3.6%) 0 (0%) Neuroendocrine 2 (3.1%) 1 (1.8%) 1 (11%) Sarcoma 2 (3.1%) 2 (3.6%) 0 (0%) Thyroid (Papillary) 2 (3.1%) 2 (3.6%) 0 (0%) Adenoid Cystic 1 (1.5%) 1 (1.8%) 0 (0%) Pancreatic 1 (1.5%) 0 (0%) 1 (11%) PGL/PCC 1 (1.5%) 1 (1.8%) 0 (0%) Testicular 1 (1.5%) 0 (0%) 1 (11%) Small Bowel 1 (1.5%) 1 (1.8%) 0 (0%) Thyroid (Medullary) 1 (1.5%) 1 (1.8%) 0 (0%) Bladder 1 (1.5%) 1 (1.8%) 0 (0%) Breast cancer receptors 0.071 ER/PR positive 9 (50%) 8 (57%) 1 (25%) Triple negative 4 (22%) 4 (29%) 0 (0%) HER2-enriched 3 (17%) 1 (7.1%) 2 (50%) Triple positive 1 (5.6%) 1 (7.1%) 0 (0%) ND 1 (5.6%) 0 (0%) 1 (25%) Number of CSGs expressed 0.083 0 29 (45%) 22 (7A + 15U) (41%) 7 (4A + 3 U) (64%) 1 20 (31%) 16 (15A + 1U) (30%) 4 (4A) (36%) 2 16 (25%) 16 (16A) (30%) 0 (0%) Family history indicative of CSG expression 0.000 0 17 (26%) 10 (19%) 7 (64%) 1 18 (28%) 14 (26%) 4 (36%) 2 30 (46%) 30 (56%) 0 (0%) 1 n (%) 2 Fisher's exact test; Two Sample t-test; AD, autosomal dominant; AR, autosomal recessive; A, affected; U, unaffected. Seventy percent of MINAS carriers were affected with at least one cancer at the time of data collection. Forty-six percent (25/54) had one cancer, 15% (8/54) had two cancers and 9.3% (5/54) had three or more cancers. The most common cancer types were breast (32%, 18/54) and prostate (13%, 7/54), followed by hematologic disorders, melanoma and renal cancers at 8.9% each, and ovarian cancers with 7.1%. In individuals with two or more primary cancers, nearly 20 distinct cancer pairings were observed. Age of first cancer diagnosis ranged widely among MINAS carriers, with nearly 40% (15/38) of affected individuals diagnosed before age 41 ( Table 1 ) . We compared MINAS carriers to those with AD–AR gene combinations across demographic, clinical, and genetic variables ( Table 1 ) . No significant differences were observed between groups in sex distribution (p = 0.181), age at first cancer diagnosis (mean 48 vs. 44 years; p = 0.522), self-reported ancestry (p = 0.755), number of cancers (p = 0.807), or cancer type (p = 0.338). Although not statistically significant, three or more primary cancers were only observed in MINAS carriers, suggesting potentially higher cancer burden in AD-AD compared to AD-AR gene pair combinations. We also compared breast cancer receptor expression in MINAS and AD-AR carriers. Breast cancer receptor subtypes did not differ significantly between groups (p = 0.071) ( Table 1 ) . In MINAS carriers, most breast cancers were ER/ PR-positive/ HER-2 negative (57%). HER2-enriched tumours were more frequent in AD-AR than MINAS carriers (50% vs. 7.1%, respectively). Triple negative breast cancers were the second most frequent subtype among the MINAS group (29%). There were zero occurrences of triple negative breast cancers in the AD-AR group. Genes and gene combinations in MINAS carriers and correlation with clinical characteristics In MINAS carriers, we identified pathogenic variants in 26 CSGs (Supplemental Table 3) . In MINAS carriers with cancer (herein referred to as “affected”) (n = 38), the most frequently identified genes were CHEK2 (n = 19), BRCA1 (n = 12) and BRCA2 (n = 12), followed by ATM (n = 6), PALB2 (n = 3) and RAD51C (n = 3). In MINAS carriers unaffected by cancer (herein referred to as “unaffected”) (n = 16), the most frequently identified genes were CHEK2 (n = 8), BRCA2 (n = 5), APC (n = 3, all of which corresponds to the risk allele c.3920T > A (p.Ile1307Lys)) and SDHB (n = 3, all of which are healthy relatives from the affected proband). In AD-AR carriers, the most frequently identified genes included MUTYH (n = 5), CHEK2 (n = 3) and BRCA1 (n = 3), with varying gene combinations observed across affected and unaffected patients. In MINAS carriers, a total of 58 gene pair combinations were identified (Supplemental Table 3 , Fig. 1 ) . Nearly all carriers (52/54) had two pathogenic variants, leading to one possible gene pair combination, while two carriers had three pathogenic variants, leading to three gene pair combinations per carrier. Of these 58 gene pair combinations in MINAS carriers, the most frequently identified gene pairs were BRCA1 + BRCA2 (n = 5, 100% affected), followed by BRCA2 + CHEK2 (n = 5, 80% affected), CHEK2 + SDHB (n = 4, 25% affected), APC + CHEK2 (n = 3, 33% affected). Of the 11 gene pair combinations in AD-AR carriers, nine were unique gene pair combinations. The most frequent gene pair combinations were BRCA1 + FANCC (n = 2, 50% affected) and CHEK2 + MUTYH (n = 2, 100% affected). A small portion of both MINAS (13/54) and AD-AR (1/11) gene pair combinations were associated with two or more cancers (Fig. 2 , Supplemental Table 3 ). We next analyzed the correlation of the gene and gene combination with clinical presentation. In this analysis, we defined a pathogenic variant as being expressed if a CSG was known to have an association with the cancer or a key trait diagnosed in the individual (i.e. café au lait macules in individual in NF1 variant). Conversely, a pathogenic variant was not expressed if the diagnosed cancer had no known associations with the CSG. The majority of MINAS carriers (60%; 32/54) had a cancer (31/32) or a key trait (i.e. café au lait macules in individual in NF1 variant, 1/32) consistent with expression of at least one of the CSGs (Table 1 ). Of the MINAS carriers with no CSG expression, the majority (68%, 15/22) were unaffected at time of data collection. Notably, 39% (15/38) of MINAS carriers with cancer were diagnosed with at least one atypical cancer with no known strong association to the CSGs (Supplemental Table 4) . Of the 15 MINAS carriers with atypical cancers, the only gene pair present more than once was CHEK2 + SEC23B , which was present in two members of the same family who were diagnosed with essential thrombocythemia. Comparing MINAS to AD-AR carriers, significantly fewer AD-AR individuals had a cancer consistent with expression of at least one of the CSGs, while the majority (64%) had no CSG expression (p = 0.083) ( Table 1 ). Notably, a significantly greater proportion of AD–AR carriers compared to MINAS carriers lacked a family history indicative of pathogenic variant expression (64% vs. 19%, p < 0.001), highlighting family history as a key differentiating feature of MINAS carriers ( Table 1 ). We then classified genes as high (HR), moderate (MR), or low-risk (LR) based on the National Comprehensive Cancer Network Guidelines and analyzed gene-pair combinations with respect to pathogenic variant expression ( Table 2 , Fig. 2 ) . The distribution of gene risk combinations differed across CSGs expressed (p = 0.026). Combinations involving HR genes, either paired with other HR or MR genes, were the most frequent in individuals with two CSGs expressed (45% and 40%, respectively). In individuals with one CSG expressed, the most common combinations included MR genes paired with either other MR or HR genes (31% and 44%, respectively). Interestingly, in cases with no pathogenic variant expression, the most common gene risk combination was HR + MR (64%). The HR-MR group mostly includes unaffected individuals, including healthy relatives of probands identified through cascade testing as MINAS carriers, but who have not developed cancer. In line with this, the median age at last data capture for unaffected carriers was relatively young (48 years, range 31–73) compared to affected individuals (58 years, range 30–84) (p = 0.037) ( Table 3 ). These findings highlight the importance of ongoing surveillance, as many unaffected carriers may still be within the age range of risk for developing related cancers. Table 2 Gene risk combination counts and CSG expression among MINAS carriers. CSG expression Variable Overall N = 58 1 0 N = 22 1 1 N = 16 1 2 N = 20 1 p-value 2 Clinical status 0.000 Affected 42 (72%) 7 (32%) 15 (94%) 20 (100%) Unaffected 16 (28%) 15 (68%) 1 (6.3%) 0 (0%) Gene risk combination 0.026 HR + HR 11 (19%) 1 (4.5%) 1 (6.3%) 9 (45%) HR + MR 29 (50%) 14 (64%) 7 (44%) 8 (40%) HR + LR 2 (3.4%) 1 (4.5%) 1 (6.3%) 0 (0%) MR + MR 10 (17%) 3 (14%) 5 (31%) 2 (10%) LR + MR 6 (10%) 3 (14%) 2 (13%) 1 (5.0%) Family history indicative of CSG expression 0.028 0 12 (21%) 1 (4.5%) 5 (31%) 6 (30%) 1 14 (24%) 6 (27%) 6 (38%) 2 (10%) 2 32 (55%) 15 (68%) 5 (31%) 12 (60%) 1 n (%); Includes all gene pair combinations identified in MINAS cases (n = 54) 2 Fisher's exact test N, Number of gene pairs among MINAS cases; HR, High-risk; MR, Moderate-risk; LR, Low-risk. Table 3 Age at last data-entry (years) by clinical status of MINAS carriers. Variable Overall N = 54 1 Affected N = 38 1 Unaffected N = 16 1 p-value 2 Age at last data-entry (years) 0.037 N Non-missing 54 38 16 Mean (SD) 55 ( 16 ) 58 ( 16 ) 48 ( 13 ) Median (Q1, Q3) 54 (41, 69) 58 (43, 72) 48 (37, 54) Min, Max 30, 84 30, 84 31, 73 1 n (%) 2 Two Sample t-test Correlation with clinical characteristics in hereditary breast cancer gene pair combinations The most frequent gene pair combinations in our MINAS dataset were BRCA1 + BRCA2 (n = 5) and BRCA2 + CHEK2 (n = 5). Notably, all BRCA1 + BRCA2 MINAS carriers were affected by breast or prostate cancer. In BRCA1 + BRCA2 carriers with breast cancer, 75% (3/4) had receptor expression profiles consistent with BRCA1 breast cancers (triple negative), while 25% (1/4) had an expression profile consistent with BRCA2 breast cancers (ER/PR +). All four carriers with BRCA1 + BRCA2 gene pair combinations who developed cancer were diagnosed before age 39, with a median age of onset of 33.5 years, which is earlier than reported for single BRCA1 or BRCA2 variant carriers in the literature (40 and 42 years, respectively) ( 9 ). MINAS carriers with BRCA2 + CHEK2 had variable phenotypes. Sixty percent (3/5) were affected by one primary cancer (sarcoma, melanoma or breast cancer, n = 1), while the remaining remained unaffected. Age of onset of breast cancer was 61 years in the BRCA2 + CHEK2 carrier, which is not significantly earlier than breast cancer onset in the general population. Thirty six percent (5/14) of MINAS carriers with breast cancer had two variants in other hereditary breast cancer genes. These gene pair combinations included BRCA1 + TP53, BRCA2 + PALB2, BRCA2 + RAD51D, PALB2 + CHEK2 and ATM + CHEK2 (one of each, respectively). Pathogenic variants in TP53 are associated with Li-Fraumeni syndrome, a hereditary cancer predisposition syndrome associated with multiple cancers, including breast cancer onset at a median age of 34 ( 19 ). The BRCA1 + TP53 carrier in our cohort developed bilateral invasive ductal carcinoma breast cancer at age 33. Carriers with BRCA2 + PALB2, BRCA2 + RAD51D, ATM + CHEK2, PALB2 + CHEK2 had breast cancer (or bilateral breast cancer, in the case of the ATM + CHEK2 and PALB2 + CHEK2 carriers) diagnosed at age 28, 28, 42 and 51, respectively. Notably, median age of breast cancer diagnosis in single variants of PALB2, RAD51C, ATM and CHEK2 is reported as 52, 43, 47 and 47, respectively, in the literature ( 20 – 22 ). Although our data set is small, our results suggest that most carriers affected by breast cancer and with two or more variants in hereditary breast cancer genes have an earlier onset of breast cancer. Discussion In this retrospective cohort study, we identified 54 MINAS carriers. To our knowledge, this is the largest cohort of MINAS carriers at a single center identified to date. In line with previous studies, a significant proportion of MINAS carriers (77%) had at least one hereditary breast cancer gene, most commonly BRCA1 (n = 14) or BRCA2 (n = 17). The high frequency of hereditary breast CSGs in our cohort is reflective of several factors, including the high proportion of patients with personal or family history of breast cancer referred to Princess Margaret Cancer Centre and offered genetic testing (i.e. ascertainment bias), and more generally, the high penetrance, well-established screening protocols and genetic panels for hereditary breast cancers compared to other hereditary cancers, such as colorectal and pancreatic cancer. Interestingly, compared to MINAS carriers, AD-AR carriers are less likely to have a family history of cancer but are otherwise similar in terms of demographic features, cancer type and age of first cancer diagnosis. Our results are similar to work done by Yuen et. al. , who found that AD-AD carriers have a higher burden of cancer than AD-AR carriers, and suggest that cancer risk management should be guided by the AD gene ( 4 ). Notably, our AD-AR cohort is small (n = 11) and clinically heterogeneous, with nine unique gene pair combinations. Further work is required to clarify the role of AR CSGs in cancer risk management. Approximately 40% (15/39) of MINAS carriers affected by cancer in our study presented with at least one atypical cancer with no known strong association to the CSGs. In previous studies of MINAS carriers, atypical tumors have been found in 14.5–15.8% of cohorts ( 3 , 4 ). Given how rare these CSG combinations are present, it is not possible to say whether the resulting cancer is coincidental or a reflection of novel CSG synergistic interaction. Unfortunately, rare gene pair combinations are an inherent challenge with MINAS cases. Open access MINAS databases, such as the Global Variome LOVD created by Whitworth et. al., are essential in continuing to document rare gene pair combinations and investigate atypical tumor presentations ( 2 ). There is great interest in determining whether MINAS carriers exhibit more severe disease due to synergistic interactions of CSGs. The most well studied gene pair combinations include BRCA1 and BRCA2 . In our study, the median age of breast cancer diagnosis in BRCA1 and BRCA2 carriers was 33.5 years, which is nearly a decade younger than single BRCA1 and BRCA2 variants cited in the literature ( 9 ). The largest study of BRCA1 + BRCA2 carriers and cancer risk was done by the Consortium of Investigators of Modifiers of BRCA1 and BRCA2 (CIMBA) in 2012 ( 9 ). In their study of 93 BRCA1 + BRCA2 carriers, Rebbeck et. al. found that BRCA1 + BRCA2 carriers were more likely to be diagnosed with breast cancer than either BRCA1 or BRCA2 single variants, but that mean age of breast cancer diagnosis was not statistically different than carriers of a single BRCA1 variant (40.4 vs. 41.9 years) ( 9 ). Further loss of heterozygosity studies supported an additive vs. synergistic effect in BRCA1 + BRCA2 carriers ( 9 ). A more recent study by Yuen et. al . analyzed 89 BRCA1 + BRCA2 carriers and found that BRCA1 + BRCA2 carriers had a higher percentage of multiple malignancies and an earlier onset of cancer than single CSG variants (but did not specifically compare to single BRCA1 or BRCA2 variants) ( 4 ). In addition to these studies, there are multiple case reports of small cohorts of BRCA1 + BRCA2 carriers that have yielded conflicting results ( 11 , 12 , 14 ). Beyond BRCA1 + BRCA2 gene pair combinations, there is limited information on cancer risk management in other gene pair combinations. In their recent study, Yuen et. al. commented that MINAS carriers with hereditary breast cancer genes beyond BRCA1 + BRCA2 are also more likely to be associated with multiple malignancies and earlier onset of cancer ( 4 ). Consistent with this, we found several hereditary breast gene pair combinations with an earlier onset of breast cancer than either of the single variants. Importantly, there are no large-scale prospective cohort studies or case series that provide robust, quantitative estimates of cancer incidence, age of onset or outcomes. Based on our results, we believe a closer examination of gene pair combinations with two or hereditary breast CSGs is warranted, as initial results suggest enhanced surveillance and possible benefit of prophylactic surgeries at an earlier age. In addition to small cohort sizes and rare gene pair combinations, there are several limitations to MINAS studies. Primarily, there is significant clinical heterogeneity. For example, studies such as Rebbeck et. al. have a large Ashkenazi Jewish population and subsequently higher rates of particular founder variants (i.e. c.68_69delAG; p.Glu23Valfs17*) in their BRCA1 + BRCA2 cohort compared to studies with predominantly Asian cohorts ( 4 , 9 , 12 , 14 ). Additionally, guidelines for genetic testing vary between countries, testing centers and even individual providers, leading to variability in what gene panels are selected for genetic testing. Individuals with more severe presentations (i.e. multiple cancers) are more likely to be referred for genetic testing and undergo multi-gene panel testing, therefore reflecting selection bias in MINAS cohorts. Inclusion of unaffected individuals (usually identified through cascade testing of affected relatives) may confound the analysis, as they are likely to be captured at a younger age and have not yet developed cancer. Last, as discussed by McGuigan et. al. , most MINAS papers lack tumor studies, and thus it is not clear if one or more of the MINAS CSGs are contributing to tumor occurrence. Detailed analysis, in the form of loss of heterozygosity or other tumor profiling strategies including immunohistochemistry of CSG gene products and microsatellite instability, would help clarify the role of MINAS CSGs in tumorigenesis ( 3 ). Conclusions Here, we provide information on the largest single center cohort of MINAS carriers. In our study, a significant proportion of MINAS carriers are associated with atypical cancer presentations that cannot be explained by the single CSG alone, which may point to novel synergistic interactions of CSGs and expand the spectrum of cancers associated with CSGs. Further, we find that MINAS carriers with two or more hereditary breast CSGs developed earlier onset of breast cancer than single variants reported in the literature, therefore, warranting earlier surveillance and intervention. Importantly, further research is needed to interrogate novel cancer associations and disease severity in MINAS carriers with hereditary breast CSGs, in the form of larger, prospective cohort studies and case series and tumor profiling studies. Declarations Data availability statement: data generated or analyzed during this study can be found within the published article and its supplementary file. Code availability: not applicable Acknowledgements: The authors thank the medical geneticists at the Bhalwani Familial Cancer Clinic for their assistance with genetic analysis. Author contributions: KO analyzed data and wrote the manuscript. MS performed statistical analysis and helped to write the manuscript. MH, KA, RM, LP contributed to study design and data extraction. RHK conceived the study. All authors read and approved the final version of the manuscript before submission. Funding: This work was supported in part by the Bhalwani Family Charitable Foundation, Goldie R. Feldman, Karen Green and George Fischer Genomics and Genetics Fund, Lindy Green Family Foundation, FDC Foundation, Shar Foundation, The Devine/Sucharda Charitable Foundation, Leslie E. Born, Hal Jackman Foundation, Nicol Family Foundation, James and Christine Nicol, Janice Fukakusa and Greg Belbeck, Jack and Buschie Kamin Foundation, Marcus Tzaferis, Paul Bronfman Family Foundation, The Honey and Leonard Wolfe Family Charitable Foundation, Arman Alie and Margarette Nory, The Princess Margaret Cancer Foundation. Ethical approval: Ethics approval for this retrospective chart-review study was granted by the UHN Research Ethics Board (ID: 24-5884). The study was classified as no-risk and exempt from written informed consent. Competing interests: the authors declare no competing financial interests. Disclosures: the authors have no disclosures. References Foulkes WD. Inherited Susceptibility to Common Cancers. N Engl J Med. 2008;359(20):2143–53. Whitworth J, Skytte AB, Sunde L, Lim DH, Arends MJ, Happerfield L, et al. Multilocus Inherited Neoplasia Alleles Syndrome: A Case Series and Review. JAMA Oncol. 2016;2(3):373–9. McGuigan A, Whitworth J, Andreou A, Hearn T, Tischkowitz M, Maher ER. Multilocus Inherited Neoplasia Allele Syndrome (MINAS): an update. Eur J Hum Genet. 2022;30(3):265–70. Yuen J, Zhou S, Caeser R, Venkatramani M, Bte Ishak DN, Li ST, et al. Multi-locus inherited neoplasia alleles syndromes in cancer: implications for clinical practice. Eur J Hum Genet. 2025;33(3):289–96. Narayanan DL, Udyawar D, Kaur P, Sharma S, Suresh N, Nampoothiri S, et al. Multilocus disease-causing genomic variations for Mendelian disorders: role of systematic phenotyping and implications on genetic counselling. Eur J Hum Genet. 2021;29(12):1774–80. Imyanitov EN, Kuligina ES, Sokolenko AP, Suspitsin EN, Yanus GA, Iyevleva AG, et al. Hereditary cancer syndromes. World J Clin Oncol. 2023;14(2):40–68. Bokkers K, Vlaming M, Engelhardt EG, Zweemer RP, van Oort IM, Kiemeney LALM, et al. The Feasibility of Implementing Mainstream Germline Genetic Testing in Routine Cancer Care—A Systematic Review. Cancers. 2022;14(4):1059. Heidemann S, Fischer C, Engel C, Fischer B, Harder L, Schlegelberger B, et al. Double heterozygosity for mutations in BRCA1 and BRCA2 in German breast cancer patients: implications on test strategies and clinical management. Breast Cancer Res Treat. 2012;134(3):1229–39. Rebbeck TR, Mitra N, Wan F, Sinilnikova OM, Healey S, McGuffog L, et al. Association of Type and Location of BRCA1 and BRCA2 Mutations With Risk of Breast and Ovarian Cancer. JAMA. 2015;313(13):1347–61. Stradella A, Del Valle J, Rofes P, Feliubadaló L, Grau Garces È, Velasco À, et al. Does multilocus inherited neoplasia alleles syndrome have severe clinical expression? J Med Genet. 2019;56(8):521–5. Leegte B, Hout AH van der, Deffenbaugh AM, Bakker MK, Mulder IM, Berge A ten, et al. Phenotypic expression of double heterozygosity for BRCA1 and BRCA2 germline mutations. J Med Genet. 2005;42(3):e20–e20. Bang YJ, Kwon WK, Nam SJ, Kim SW, Chae BJ, Lee SK, et al. Clinicopathological Characterization of Double Heterozygosity for BRCA1 and BRCA2 Variants in Korean Breast Cancer Patients. Cancer Res Treat. 2021;54(3):827–33. Pócza T, Papp J, Bozsik A, Grolmusz VK, Nagy P, Patócs A, et al. Double Pathogenic or Likely Pathogenic Variants in Cancer Predisposition Genes in Hungarian Cancer Patients. Int J Mol Sci. 2025;26(17):8390. Hur JY, Kim JY, Ahn JS, Im YH, Lee J, Kwon M, et al. Clinical Characteristics of Korean Breast Cancer Patients Who Carry Pathogenic Germline Mutations in Both BRCA1 and BRCA2: A Single-Center Experience. Cancers. 2020;12(5):1306. Hodan R, Gupta S, Weiss JM, Axell L, Burke CA, Chen LM, et al. Genetic/Familial High-Risk Assessment: Colorectal, Endometrial, and Gastric, Version 3.2024, NCCN Clinical Practice Guidelines In Oncology. J Natl Compr Cancer Netw JNCCN. 2024;22(10):695–711. Daly MB, Pal T, Maxwell KN, Churpek J, Kohlmann W, AlHilli Z, et al. NCCN Guidelines® Insights: Genetic/Familial High-Risk Assessment: Breast, Ovarian, and Pancreatic, Version 2.2024. J Natl Compr Cancer Netw JNCCN. 2023;21(10):1000–10. Hereditary Cancer Testing Eligibility Criteria: Version 3.1. Ontario Health Cancer Care Ontario; 2024. Richards 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. Genet Med. 2015;17(5):405–24. Achatz MI, Villani A, Bertuch AA, Bougeard G, Chang VY, Doria AS, et al. Update on Cancer Screening Recommendations for Individuals with Li–Fraumeni Syndrome. Clin Cancer Res. 2025;31(10):1831–40. Tischkowitz M, Balmaña J, Foulkes WD, James P, Ngeow J, Schmutzler R, et al. Management of individuals with germline variants in PALB2: a clinical practice resource of the American College of Medical Genetics and Genomics (ACMG). Genet Med. 2021;23(8):1416–23. Torres-Esquius S, Llop-Guevara A, Gutiérrez-Enríquez S, Romey M, Teulé À, Llort G, et al. Prevalence of Homologous Recombination Deficiency Among Patients With Germline RAD51C/D Breast or Ovarian Cancer. JAMA Netw Open. 2024;7(4):e247811. Double heterozygous pathogenic variants prevalence in a cohort of patients with hereditary breast cancer. - Abstract - Europe PMC [Internet]. [cited 2025 Sept 27]. Available from: https://europepmc.org/article/MED/36003761 Additional Declarations There is no duality of interest Supplementary Files EJHGSupplemental.docx Supplemental Table 1: Risk category assigned to CSGs. Supplemental Table 2: Inheritance mode assigned to CSGs. Supplemental Table 3: AD-AD and AD-AR carriers included in this study. Supplemental Table 4: Atypical cancers in affected AD-AD carriers, with the atypical cancer(s) bolded. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: revise 12 Feb, 2026 Review # 3 received at journal 10 Feb, 2026 Reviewer # 3 agreed at journal 06 Feb, 2026 Review # 2 received at journal 14 Dec, 2025 Reviewer # 2 agreed at journal 12 Dec, 2025 Reviewer # 1 agreed at journal 11 Dec, 2025 Reviewers invited by journal 02 Dec, 2025 Submission checks completed at journal 25 Nov, 2025 First submitted to journal 18 Nov, 2025 Editor assigned by journal 18 Nov, 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8149436","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":554149760,"identity":"f79f0d9c-d7a9-460f-8930-ef5c124b0ceb","order_by":0,"name":"Raymond 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1","display":"","copyAsset":false,"role":"figure","size":259829,"visible":true,"origin":"","legend":"\u003cp\u003eChord diagrams showing combinations of CSGs in AD-AD carriers (n = 54). A Gene pairs found in affected individuals B. The Gene pairs found in unaffected individuals. The width of each chord reflects the frequency of co-occurrence of gene pairs. Gene colors represent their associated cancer risk category (high, moderate, or low).\u003c/p\u003e","description":"","filename":"EJHGMINASFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8149436/v1/b1c6e971e269cd88466b3a6b.png"},{"id":97667306,"identity":"67145790-5afd-4ec5-8101-ebfab60123ec","added_by":"auto","created_at":"2025-12-08 09:23:13","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":127988,"visible":true,"origin":"","legend":"\u003cp\u003eChord diagram depicting the cancer gene pair combinations in AD-AD carriers affected by two and three cancers (n = 13). Multiple combinations may apply to the same individual. Abbreviations: Breast(1) refers (primary breast cancer), breast(2) (secondary primary breast cancer), PGL/ PCC (pheochromocytoma/ paraganglioma).\u003c/p\u003e","description":"","filename":"EJHGMINASFigure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8149436/v1/27445d5e5179ca093f261993.jpg"},{"id":97677355,"identity":"b42d7469-4b89-4cca-889d-94f7f4bc81b3","added_by":"auto","created_at":"2025-12-08 09:53:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1521863,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8149436/v1/af9031b9-4228-4f09-84cf-2e1114749559.pdf"},{"id":97427376,"identity":"5e7239e1-0b72-4581-9ccb-27b27cccff3a","added_by":"auto","created_at":"2025-12-04 09:27:07","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":36088,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental Table 1: \u003c/strong\u003eRisk category assigned to CSGs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplemental Table 2: \u003c/strong\u003eInheritance mode assigned to CSGs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplemental Table 3: \u003c/strong\u003eAD-AD and AD-AR carriers included in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplemental Table 4: \u003c/strong\u003eAtypical cancers in affected AD-AD carriers, with the atypical cancer(s) bolded.\u003c/p\u003e","description":"","filename":"EJHGSupplemental.docx","url":"https://assets-eu.researchsquare.com/files/rs-8149436/v1/2da5dab08ab8e91a94d5ba67.docx"}],"financialInterests":"There is no duality of interest","formattedTitle":"Multilocus Inherited Neoplasia Alleles Syndrome: A Retrospective Review from a Canadian Single Institution","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHereditary cancer syndromes account for approximately 5\u0026ndash;10% of all cancers and describe a spectrum of cancers that are caused by inherited pathogenic or likely pathogenic variants in cancer susceptibility genes (CSGs) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Hereditary cancer syndromes include the well-known and relatively common \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e associated breast, ovarian and prostate cancers, and lesser-known and comparatively more rare cancer syndromes, including \u003cem\u003eEGFR\u003c/em\u003e associated lung cancer. Traditionally, hereditary cancers have been identified by recognizing clusters of related individuals with a high burden of cancer, followed by targeted testing of individual genes. With the advent of next generation sequence, there is a paradigm shift toward multi-gene panel testing that allows for simultaneous detection of multiple CSGs, which have increasingly detected pathogenic variants not predicted by phenotype or family history. Further, multi-gene panel testing has led to the detection of carriers of two or more pathogenic or likely pathogenic variants in CSGs, termed \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eM\u003c/span\u003eultilocus \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eI\u003c/span\u003enherited \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eN\u003c/span\u003eeoplasia \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eA\u003c/span\u003ellele \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eS\u003c/span\u003eyndrome, or MINAS (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), with an estimated prevalence between 0.2\u0026ndash;2.4% (\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Although early MINAS studies included both autosomal dominant (AD) and recessive (AR) gene pair combinations (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), more recent studies have analyzed AD-AD and AD-AR gene pair combinations separately, citing higher penetrance and higher frequency of malignancies in AD-AD gene pair combinations (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHereditary cancer syndromes have been associated with an elevated lifetime risk for specific cancers and more severe cancer phenotypes (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Carriers of single pathogenic variants in CSGs undergo lifelong specialized cancer surveillance, and these genetic test results provide information on cancer risks and implications for other family members, such as the potential need for cascade testing (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The results of surveillance are actionable, guiding decision making around preventive or risk-reducing measures and the use of certain therapeutic agents in cancer treatments. Compared to single CSG variants, it has long been hypothesized that MINAS carriers are at elevated risk of multiple, atypical and more severe cancers because of synergistic interaction CSGs in related tumorigenic pathways or in chromosomal proximity (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Research into this area has yielded conflicting results, with reports supporting that CSGs can act both independently (each variant contributes independently to overall cancer risk and characteristics) and synergistically (variants interact in such a way that enhances their impact on cancer risk and characteristics) (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR9 CR10 CR11 CR12 CR13\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). As present, the recommended screening guidelines for MINAS carriers is to follow the established protocols for each CSG independently.\u003c/p\u003e\u003cp\u003eIn this retrospective cohort study, we identify and characterize MINAS carriers (defined here as AD-AD gene pair combinations) who were diagnosed at Princess Margaret Cancer Centre from January 1, 2017, to September 30, 2024. We provide information about the age of onset, clinical characteristics and spectrum of associated cancers, and compare to carriers with AD-AR gene pair combinations in our cohort.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Cohort and Ethics Committee Approval\u003c/h2\u003e\u003cp\u003eWe conducted a retrospective cohort study of individuals referred for genetic counseling and testing between January 1, 2017, and September 30, 2024, to identify and characterize AD-AD and AD-AR carriers, defined as those harboring germline pathogenic variants in two or more different CSGs. A total of 65 eligible cases from 60 families were identified through the Progeny database of the Bhalwani Familial Cancer Clinic at the Princess Margaret (PM) Cancer Centre, University Health Network (UHN), Toronto, Canada. Ethics approval for this retrospective chart-review study was granted by the UHN Research Ethics Board (ID: 24-5884). The study was classified as no-risk and exempt from written informed consent.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eWe collected detailed information across four domains by reviewing data from the Progeny database and the Electronic Medical Records (EMR): i) Demographic data, including sex and self-reported ancestry from maternal and paternal lineages; ii) Clinical data, including affected/unaffected status, cancer type(s), number of primary cancers, age at each diagnosis, and breast cancer receptor status when applicable; iii) Genetic data, including HUGO gene symbols, HGVS nomenclature for each pathogenic variant, pathogenicity interpretation, inheritance pattern, and cancer risk category per gene (high risk (HR), moderate risk (MR), or low-risk (LR)) based on the National Comprehensive Cancer Network Guidelines (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) \u003cb\u003e(Supplemental Table\u0026nbsp;1)\u003c/b\u003e (all APC carriers have the p.I1301K allele and are classified as LR) and iv) Family history among first- and second-degree relatives. The clinical team assessed, for each individual, whether none (0), one (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) or both (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) variants were phenotypically expressed in the proband or family members, based on their established association with diagnosed cancer types, reported family history and known inheritance patterns (autosomal dominant (AD) or autosomal recessive (AR)) \u003cb\u003e(Supplemental Table\u0026nbsp;2)\u003c/b\u003e. The presence of an atypical phenotype was determined if there was one or more cancers expressed that were not associated with pathogenic variant expression. A dominant inheritance mode was assigned to genes with both AD and AR implications if the heterozygous state was linked to cancer susceptibility (e.g., \u003cem\u003eATM\u003c/em\u003e). To safeguard confidentiality, all records were de-identified using unique Study IDs.\u003c/p\u003e\n\u003ch3\u003eGenetic Counseling and Test Results\u003c/h3\u003e\n\u003cp\u003eAll patients were referred to the Princess Margaret Genetics Clinic or had their charts reviewed by certified genetic counsellors, the medical genetics team or an oncologist to determine the\u003c/p\u003e\u003cp\u003emost appropriate genetic test(s) based on each patient's personal and family history. Decisions were guided by institutional protocols and provincial guidelines, such as the updated Cancer Care Ontario Hereditary Cancer Testing Eligibility Criteria (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Genetic testing was performed at Clinical Laboratory Improvement Amendments (CLIA)-certified laboratories. Following result disclosure, all individuals received post-test counseling and were referred to appropriate multidisciplinary teams for personalized risk management and clinical follow-up.\u003c/p\u003e\u003cp\u003eIndividuals with two or more germline variants in different genes, classified as pathogenic, likely pathogenic, or risk alleles (for example, \u003cem\u003eAPC\u003c/em\u003e c.3920T\u0026thinsp;\u0026gt;\u0026thinsp;A (p.Ile1307Lys), which is risk factor for colorectal cancer in individuals of Ashkenazi Jewish ancestry and carries specific screening recommendations), were included in this study. Variant classification followed the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). All variant nomenclature was standardized according to Human Genome Variation Society (HGVS) conventions using the VariantValidator tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://variantvalidator.org\u003c/span\u003e\u003cspan address=\"https://variantvalidator.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eDescriptive statistics were used to summarize demographic, clinical, and genetic characteristics of the study cohort. Categorical variables were described using frequencies and percentages. Age at first cancer diagnosis was the only continuous variable analyzed, and it was described using measures of central tendency or categorized into age ranges. Normality and homogeneity of variance for age were assessed using the Shapiro-Wilk and Levene\u0026rsquo;s tests, respectively. Implicated genes were assigned a cancer risk level (high risk (HR), moderate risk (MR), or low risk (LR)) and an inheritance pattern (AD or AR) \u003cb\u003e(Supplemental Table\u0026nbsp;1)\u003c/b\u003e. Based on the inheritance pattern of the implicated genes per individual \u003cb\u003e(Supplemental Table\u0026nbsp;2)\u003c/b\u003e, two groups were formed: AD-AD combinations and AD-AR combinations. Group comparisons for categorical variables, which often included small cell counts (\u0026lt;\u0026thinsp;5), were performed using Fisher\u0026rsquo;s exact test; otherwise, chi-square tests were applied. Differences in age at diagnosis between groups were assessed using independent t-tests. Besides gene combination category, cases were also stratified by clinical status (affected vs. unaffected), and the number of phenotypically expressed variants (0, 1, or 2) in the individual and family based on their cancer history. Statistical significance was set at p\u0026thinsp;\u0026le;\u0026thinsp;0.05. Cancer co-occurrence, as well as gene co-occurrence patterns, were visualized using circular chord diagrams (circlize package), and other data visualizations were generated with ggplot2. All analyses were conducted in R (version 4.4.2).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eClinical characteristics of MINAS carriers and relatives\u003c/h2\u003e\u003cp\u003eWe identified 65 individuals based on the search criteria \u003cb\u003e(Supplemental Table\u0026nbsp;3)\u003c/b\u003e. Of the 65 cases, a total of 54 individuals from 49 families were categorized as MINAS (AD-AD gene combinations), while 11 individuals were AD-AR gene combinations. Most MINAS carriers were female (57%; 31/54). Self-reported ancestry across both lineages was primarily White (63%), followed by Ashkenazi Jewish (17%) and South Asian (7.5%) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of AD-AD and AD-AR gene combinations across demographic, clinical and genetic variables.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;65\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAD-AD \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;54\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAD-AR \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;11\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.181\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40 (62%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31 (57%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (82%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (38%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (43%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (18%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge of first cancer\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.522\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN Non-missing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47 (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48 (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44 (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedian (Q1, Q3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e49 (33, 59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 (31, 62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40 (36, 54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMin, Max\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4, 83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4, 83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31, 59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSelf-reported ancestry (both lineages)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.755\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhite\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e76 (62%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e67 (63%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (56%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAshkenazi Jewish\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (18%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (17%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (25%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSouth Asian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10 (8.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (7.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (13%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSoutheast Asian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (3.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (3.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLatino\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (2.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMiddle Eastern\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (2.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (2.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlack or African descent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEast Asian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of cancers\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.807\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19 (29%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (30%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (27%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32 (49%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25 (46%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (64%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (9.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (7.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (9.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCancer type\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.338\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBreast\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (34%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (32%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (44%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProstate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (11%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (13%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHematologic Disorders\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (9.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (8.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (11%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMelanoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (7.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (8.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOvarian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (7.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (7.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (11%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRenal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (7.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (8.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEndometrial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (3.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (3.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeuroendocrine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (3.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (11%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSarcoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (3.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (3.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThyroid (Papillary)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (3.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (3.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdenoid Cystic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePancreatic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (11%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePGL/PCC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTesticular\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (11%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmall Bowel\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThyroid (Medullary)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBladder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBreast cancer receptors\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.071\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eER/PR positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (50%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (57%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (25%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriple negative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (22%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (29%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHER2-enriched\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (17%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (7.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (50%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriple positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (5.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (7.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eND\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (5.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (25%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of CSGs expressed\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.083\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29 (45%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 (7A\u0026thinsp;+\u0026thinsp;15U) (41%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (4A\u0026thinsp;+\u0026thinsp;3 U)\u003c/p\u003e\u003cp\u003e(64%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20 (31%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (15A\u0026thinsp;+\u0026thinsp;1U) (30%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (4A) (36%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16 (25%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (16A)\u003c/p\u003e\u003cp\u003e(30%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFamily history indicative of CSG expression\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (26%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (19%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (64%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (28%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (26%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (36%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30 (46%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30 (56%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003csup\u003e1\u003c/sup\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e2\u003c/sup\u003eFisher's exact test; Two Sample t-test; AD, autosomal dominant; AR, autosomal recessive; A, affected; U, unaffected.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eSeventy percent of MINAS carriers were affected with at least one cancer at the time of data collection. Forty-six percent (25/54) had one cancer, 15% (8/54) had two cancers and 9.3% (5/54) had three or more cancers. The most common cancer types were breast (32%, 18/54) and prostate (13%, 7/54), followed by hematologic disorders, melanoma and renal cancers at 8.9% each, and ovarian cancers with 7.1%. In individuals with two or more primary cancers, nearly 20 distinct cancer pairings were observed. Age of first cancer diagnosis ranged widely among MINAS carriers, with nearly 40% (15/38) of affected individuals diagnosed before age 41 \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eWe compared MINAS carriers to those with AD\u0026ndash;AR gene combinations across demographic, clinical, and genetic variables \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. No significant differences were observed between groups in sex distribution (p\u0026thinsp;=\u0026thinsp;0.181), age at first cancer diagnosis (mean 48 vs. 44 years; p\u0026thinsp;=\u0026thinsp;0.522), self-reported ancestry (p\u0026thinsp;=\u0026thinsp;0.755), number of cancers (p\u0026thinsp;=\u0026thinsp;0.807), or cancer type (p\u0026thinsp;=\u0026thinsp;0.338). Although not statistically significant, three or more primary cancers were only observed in MINAS carriers, suggesting potentially higher cancer burden in AD-AD compared to AD-AR gene pair combinations.\u003c/p\u003e\u003cp\u003eWe also compared breast cancer receptor expression in MINAS and AD-AR carriers. Breast cancer receptor subtypes did not differ significantly between groups (p\u0026thinsp;=\u0026thinsp;0.071) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. In MINAS carriers, most breast cancers were ER/ PR-positive/ HER-2 negative (57%). HER2-enriched tumours were more frequent in AD-AR than MINAS carriers (50% vs. 7.1%, respectively). Triple negative breast cancers were the second most frequent subtype among the MINAS group (29%). There were zero occurrences of triple negative breast cancers in the AD-AR group.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eGenes and gene combinations in MINAS carriers and correlation with clinical characteristics\u003c/h3\u003e\n\u003cp\u003eIn MINAS carriers, we identified pathogenic variants in 26 CSGs \u003cb\u003e(Supplemental Table\u0026nbsp;3)\u003c/b\u003e. In MINAS carriers with cancer (herein referred to as \u0026ldquo;affected\u0026rdquo;) (n\u0026thinsp;=\u0026thinsp;38), the most frequently identified genes were \u003cem\u003eCHEK2\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;19), \u003cem\u003eBRCA1\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;12) and \u003cem\u003eBRCA2\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;12), followed by \u003cem\u003eATM\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;6), \u003cem\u003ePALB2\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;3) and \u003cem\u003eRAD51C\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;3). In MINAS carriers unaffected by cancer (herein referred to as \u0026ldquo;unaffected\u0026rdquo;) (n\u0026thinsp;=\u0026thinsp;16), the most frequently identified genes were \u003cem\u003eCHEK2\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;8), \u003cem\u003eBRCA2\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;5), \u003cem\u003eAPC\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;3, all of which corresponds to the risk allele c.3920T\u0026thinsp;\u0026gt;\u0026thinsp;A (p.Ile1307Lys)) and \u003cem\u003eSDHB\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;3, all of which are healthy relatives from the affected proband). In AD-AR carriers, the most frequently identified genes included \u003cem\u003eMUTYH\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;5), \u003cem\u003eCHEK2\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;3) and \u003cem\u003eBRCA1\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;3), with varying gene combinations observed across affected and unaffected patients.\u003c/p\u003e\u003cp\u003eIn MINAS carriers, a total of 58 gene pair combinations were identified \u003cb\u003e(Supplemental Table\u0026nbsp;3\u003c/b\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Nearly all carriers (52/54) had two pathogenic variants, leading to one possible gene pair combination, while two carriers had three pathogenic variants, leading to three gene pair combinations per carrier. Of these 58 gene pair combinations in MINAS carriers, the most frequently identified gene pairs were \u003cem\u003eBRCA1\u0026thinsp;+\u0026thinsp;BRCA2\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;5, 100% affected), followed by \u003cem\u003eBRCA2\u0026thinsp;+\u0026thinsp;CHEK2\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;5, 80% affected), \u003cem\u003eCHEK2\u0026thinsp;+\u0026thinsp;SDHB\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;4, 25% affected), \u003cem\u003eAPC\u0026thinsp;+\u0026thinsp;CHEK2\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;3, 33% affected). Of the 11 gene pair combinations in AD-AR carriers, nine were unique gene pair combinations. The most frequent gene pair combinations were \u003cem\u003eBRCA1\u0026thinsp;+\u0026thinsp;FANCC\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;2, 50% affected) and \u003cem\u003eCHEK2\u0026thinsp;+\u0026thinsp;MUTYH\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;2, 100% affected). A small portion of both MINAS (13/54) and AD-AR (1/11) gene pair combinations were associated with two or more cancers (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cb\u003eSupplemental Table\u0026nbsp;3\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe next analyzed the correlation of the gene and gene combination with clinical presentation. In this analysis, we defined a pathogenic variant as being expressed if a CSG was known to have an association with the cancer or a key trait diagnosed in the individual (i.e. caf\u0026eacute; au lait macules in individual in \u003cem\u003eNF1\u003c/em\u003e variant). Conversely, a pathogenic variant was not expressed if the diagnosed cancer had no known associations with the CSG.\u003c/p\u003e\u003cp\u003eThe majority of MINAS carriers (60%; 32/54) had a cancer (31/32) or a key trait (i.e. caf\u0026eacute; au lait macules in individual in \u003cem\u003eNF1\u003c/em\u003e variant, 1/32) consistent with expression of at least one of the CSGs (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Of the MINAS carriers with no CSG expression, the majority (68%, 15/22) were unaffected at time of data collection. Notably, 39% (15/38) of MINAS carriers with cancer were diagnosed with at least one atypical cancer with no known strong association to the CSGs \u003cb\u003e(Supplemental Table\u0026nbsp;4)\u003c/b\u003e. Of the 15 MINAS carriers with atypical cancers, the only gene pair present more than once was \u003cem\u003eCHEK2\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eSEC23B\u003c/em\u003e, which was present in two members of the same family who were diagnosed with essential thrombocythemia.\u003c/p\u003e\u003cp\u003eComparing MINAS to AD-AR carriers, significantly fewer AD-AR individuals had a cancer consistent with expression of at least one of the CSGs, while the majority (64%) had no CSG expression (p\u0026thinsp;=\u0026thinsp;0.083) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e Notably, a significantly greater proportion of AD\u0026ndash;AR carriers compared to MINAS carriers lacked a family history indicative of pathogenic variant expression (64% vs. 19%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), highlighting family history as a key differentiating feature of MINAS carriers \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe then classified genes as high (HR), moderate (MR), or low-risk (LR) based on the National Comprehensive Cancer Network Guidelines and analyzed gene-pair combinations with respect to pathogenic variant expression \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The distribution of gene risk combinations differed across CSGs expressed (p\u0026thinsp;=\u0026thinsp;0.026). Combinations involving HR genes, either paired with other HR or MR genes, were the most frequent in individuals with two CSGs expressed (45% and 40%, respectively). In individuals with one CSG expressed, the most common combinations included MR genes paired with either other MR or HR genes (31% and 44%, respectively). Interestingly, in cases with no pathogenic variant expression, the most common gene risk combination was HR\u0026thinsp;+\u0026thinsp;MR (64%). The HR-MR group mostly includes unaffected individuals, including healthy relatives of probands identified through cascade testing as MINAS carriers, but who have not developed cancer. In line with this, the median age at last data capture for unaffected carriers was relatively young (48 years, range 31\u0026ndash;73) compared to affected individuals (58 years, range 30\u0026ndash;84) (p\u0026thinsp;=\u0026thinsp;0.037) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e These findings highlight the importance of ongoing surveillance, as many unaffected carriers may still be within the age range of risk for developing related cancers.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGene risk combination counts and CSG expression among MINAS carriers.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eCSG expression\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVariable\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eOverall\u003c/b\u003e \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;58\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0\u003c/b\u003e \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;22\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e1\u003c/b\u003e \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;16\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e2\u003c/b\u003e \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;20\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eClinical status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAffected\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42 (72%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (32%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15 (94%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnaffected\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16 (28%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (68%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGene risk combination\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHR\u0026thinsp;+\u0026thinsp;HR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (19%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (4.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9 (45%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHR\u0026thinsp;+\u0026thinsp;MR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29 (50%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (64%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (44%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8 (40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHR\u0026thinsp;+\u0026thinsp;LR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (3.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (4.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMR\u0026thinsp;+\u0026thinsp;MR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10 (17%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (31%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLR\u0026thinsp;+\u0026thinsp;MR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (13%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (5.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFamily history indicative of CSG expression\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.028\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (21%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (4.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (31%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6 (30%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (24%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (27%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (38%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32 (55%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (68%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (31%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12 (60%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e1\u003c/sup\u003en (%); Includes all gene pair combinations identified in MINAS cases (n\u0026thinsp;=\u0026thinsp;54)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e2\u003c/sup\u003eFisher's exact test\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eN, Number of gene pairs among MINAS cases; HR, High-risk; MR, Moderate-risk; LR, Low-risk.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAge at last data-entry (years) by clinical status of MINAS carriers.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;54\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAffected \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;38\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnaffected \u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;16\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge at last data-entry (years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.037\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN Non-missing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e55 (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58 (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48 (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedian (Q1, Q3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e54 (41, 69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58 (43, 72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48 (37, 54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMin, Max\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30, 84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30, 84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31, 73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003csup\u003e1\u003c/sup\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e2\u003c/sup\u003eTwo Sample t-test\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eCorrelation with clinical characteristics in hereditary breast cancer gene pair combinations\u003c/h3\u003e\n\u003cp\u003eThe most frequent gene pair combinations in our MINAS dataset were \u003cem\u003eBRCA1\u0026thinsp;+\u0026thinsp;BRCA2\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;5) and \u003cem\u003eBRCA2\u0026thinsp;+\u0026thinsp;CHEK2\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;5). Notably, all \u003cem\u003eBRCA1\u0026thinsp;+\u0026thinsp;BRCA2\u003c/em\u003e MINAS carriers were affected by breast or prostate cancer. In \u003cem\u003eBRCA1\u0026thinsp;+\u0026thinsp;BRCA2\u003c/em\u003e carriers with breast cancer, 75% (3/4) had receptor expression profiles consistent with \u003cem\u003eBRCA1\u003c/em\u003e breast cancers (triple negative), while 25% (1/4) had an expression profile consistent with \u003cem\u003eBRCA2\u003c/em\u003e breast cancers (ER/PR +). All four carriers with \u003cem\u003eBRCA1\u0026thinsp;+\u0026thinsp;BRCA2\u003c/em\u003e gene pair combinations who developed cancer were diagnosed before age 39, with a median age of onset of 33.5 years, which is earlier than reported for single \u003cem\u003eBRCA1\u003c/em\u003e or \u003cem\u003eBRCA2\u003c/em\u003e variant carriers in the literature (40 and 42 years, respectively) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). MINAS carriers with \u003cem\u003eBRCA2\u0026thinsp;+\u0026thinsp;CHEK2\u003c/em\u003e had variable phenotypes. Sixty percent (3/5) were affected by one primary cancer (sarcoma, melanoma or breast cancer, n\u0026thinsp;=\u0026thinsp;1), while the remaining remained unaffected. Age of onset of breast cancer was 61 years in the \u003cem\u003eBRCA2\u0026thinsp;+\u0026thinsp;CHEK2\u003c/em\u003e carrier, which is not significantly earlier than breast cancer onset in the general population.\u003c/p\u003e\u003cp\u003eThirty six percent (5/14) of MINAS carriers with breast cancer had two variants in other hereditary breast cancer genes. These gene pair combinations included \u003cem\u003eBRCA1\u0026thinsp;+\u0026thinsp;TP53, BRCA2\u0026thinsp;+\u0026thinsp;PALB2, BRCA2\u0026thinsp;+\u0026thinsp;RAD51D, PALB2\u0026thinsp;+\u0026thinsp;CHEK2\u003c/em\u003e and \u003cem\u003eATM\u0026thinsp;+\u0026thinsp;CHEK2\u003c/em\u003e (one of each, respectively). Pathogenic variants in \u003cem\u003eTP53\u003c/em\u003e are associated with Li-Fraumeni syndrome, a hereditary cancer predisposition syndrome associated with multiple cancers, including breast cancer onset at a median age of 34 (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). The \u003cem\u003eBRCA1\u0026thinsp;+\u0026thinsp;TP53\u003c/em\u003e carrier in our cohort developed bilateral invasive ductal carcinoma breast cancer at age 33. Carriers with \u003cem\u003eBRCA2\u0026thinsp;+\u0026thinsp;PALB2, BRCA2\u0026thinsp;+\u0026thinsp;RAD51D, ATM\u0026thinsp;+\u0026thinsp;CHEK2, PALB2\u0026thinsp;+\u0026thinsp;CHEK2\u003c/em\u003e had breast cancer (or bilateral breast cancer, in the case of the \u003cem\u003eATM\u0026thinsp;+\u0026thinsp;CHEK2\u003c/em\u003e and \u003cem\u003ePALB2\u0026thinsp;+\u0026thinsp;CHEK2\u003c/em\u003e carriers) diagnosed at age 28, 28, 42 and 51, respectively. Notably, median age of breast cancer diagnosis in single variants of \u003cem\u003ePALB2, RAD51C, ATM\u003c/em\u003e and \u003cem\u003eCHEK2\u003c/em\u003e is reported as 52, 43, 47 and 47, respectively, in the literature (\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Although our data set is small, our results suggest that most carriers affected by breast cancer and with two or more variants in hereditary breast cancer genes have an earlier onset of breast cancer.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this retrospective cohort study, we identified 54 MINAS carriers. To our knowledge, this is the largest cohort of MINAS carriers at a single center identified to date. In line with previous studies, a significant proportion of MINAS carriers (77%) had at least one hereditary breast cancer gene, most commonly \u003cem\u003eBRCA1\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;14) or \u003cem\u003eBRCA2\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;17). The high frequency of hereditary breast CSGs in our cohort is reflective of several factors, including the high proportion of patients with personal or family history of breast cancer referred to Princess Margaret Cancer Centre and offered genetic testing (i.e. ascertainment bias), and more generally, the high penetrance, well-established screening protocols and genetic panels for hereditary breast cancers compared to other hereditary cancers, such as colorectal and pancreatic cancer.\u003c/p\u003e\u003cp\u003eInterestingly, compared to MINAS carriers, AD-AR carriers are less likely to have a family history of cancer but are otherwise similar in terms of demographic features, cancer type and age of first cancer diagnosis. Our results are similar to work done by Yuen \u003cem\u003eet. al.\u003c/em\u003e, who found that AD-AD carriers have a higher burden of cancer than AD-AR carriers, and suggest that cancer risk management should be guided by the AD gene (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Notably, our AD-AR cohort is small (n\u0026thinsp;=\u0026thinsp;11) and clinically heterogeneous, with nine unique gene pair combinations. Further work is required to clarify the role of AR CSGs in cancer risk management.\u003c/p\u003e\u003cp\u003eApproximately 40% (15/39) of MINAS carriers affected by cancer in our study presented with at least one atypical cancer with no known strong association to the CSGs. In previous studies of MINAS carriers, atypical tumors have been found in 14.5\u0026ndash;15.8% of cohorts (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Given how rare these CSG combinations are present, it is not possible to say whether the resulting cancer is coincidental or a reflection of novel CSG synergistic interaction. Unfortunately, rare gene pair combinations are an inherent challenge with MINAS cases. Open access MINAS databases, such as the Global Variome LOVD created by Whitworth et. al., are essential in continuing to document rare gene pair combinations and investigate atypical tumor presentations (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThere is great interest in determining whether MINAS carriers exhibit more severe disease due to synergistic interactions of CSGs. The most well studied gene pair combinations include \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e. In our study, the median age of breast cancer diagnosis in \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e carriers was 33.5 years, which is nearly a decade younger than single \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e variants cited in the literature (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The largest study of \u003cem\u003eBRCA1\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eBRCA2\u003c/em\u003e carriers and cancer risk was done by the Consortium of Investigators of Modifiers of BRCA1 and BRCA2 (CIMBA) in 2012 (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). In their study of 93 \u003cem\u003eBRCA1\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eBRCA2\u003c/em\u003e carriers, Rebbeck \u003cem\u003eet. al.\u003c/em\u003e found that \u003cem\u003eBRCA1\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eBRCA2\u003c/em\u003e carriers were more likely to be diagnosed with breast cancer than either \u003cem\u003eBRCA1\u003c/em\u003e or \u003cem\u003eBRCA2\u003c/em\u003e single variants, but that mean age of breast cancer diagnosis was not statistically different than carriers of a single \u003cem\u003eBRCA1\u003c/em\u003e variant (40.4 vs. 41.9 years) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Further loss of heterozygosity studies supported an additive vs. synergistic effect in \u003cem\u003eBRCA1\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eBRCA2\u003c/em\u003e carriers (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). A more recent study by Yuen \u003cem\u003eet. al\u003c/em\u003e. analyzed 89 \u003cem\u003eBRCA1\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eBRCA2\u003c/em\u003e carriers and found that \u003cem\u003eBRCA1\u0026thinsp;+\u0026thinsp;BRCA2\u003c/em\u003e carriers had a higher percentage of multiple malignancies and an earlier onset of cancer than single CSG variants (but did not specifically compare to single \u003cem\u003eBRCA1\u003c/em\u003e or \u003cem\u003eBRCA2\u003c/em\u003e variants) (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). In addition to these studies, there are multiple case reports of small cohorts of \u003cem\u003eBRCA1\u0026thinsp;+\u0026thinsp;BRCA2\u003c/em\u003e carriers that have yielded conflicting results (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBeyond \u003cem\u003eBRCA1\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eBRCA2\u003c/em\u003e gene pair combinations, there is limited information on cancer risk management in other gene pair combinations. In their recent study, Yuen \u003cem\u003eet. al.\u003c/em\u003e commented that MINAS carriers with hereditary breast cancer genes beyond \u003cem\u003eBRCA1\u0026thinsp;+\u0026thinsp;BRCA2\u003c/em\u003e are also more likely to be associated with multiple malignancies and earlier onset of cancer (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Consistent with this, we found several hereditary breast gene pair combinations with an earlier onset of breast cancer than either of the single variants. Importantly, there are no large-scale prospective cohort studies or case series that provide robust, quantitative estimates of cancer incidence, age of onset or outcomes. Based on our results, we believe a closer examination of gene pair combinations with two or hereditary breast CSGs is warranted, as initial results suggest enhanced surveillance and possible benefit of prophylactic surgeries at an earlier age.\u003c/p\u003e\u003cp\u003eIn addition to small cohort sizes and rare gene pair combinations, there are several limitations to MINAS studies. Primarily, there is significant clinical heterogeneity. For example, studies such as Rebbeck \u003cem\u003eet. al.\u003c/em\u003e have a large Ashkenazi Jewish population and subsequently higher rates of particular founder variants (i.e. c.68_69delAG; p.Glu23Valfs17*) in their \u003cem\u003eBRCA1\u0026thinsp;+\u0026thinsp;BRCA2\u003c/em\u003e cohort compared to studies with predominantly Asian cohorts (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Additionally, guidelines for genetic testing vary between countries, testing centers and even individual providers, leading to variability in what gene panels are selected for genetic testing. Individuals with more severe presentations (i.e. multiple cancers) are more likely to be referred for genetic testing and undergo multi-gene panel testing, therefore reflecting selection bias in MINAS cohorts. Inclusion of unaffected individuals (usually identified through cascade testing of affected relatives) may confound the analysis, as they are likely to be captured at a younger age and have not yet developed cancer. Last, as discussed by McGuigan \u003cem\u003eet. al.\u003c/em\u003e, most MINAS papers lack tumor studies, and thus it is not clear if one or more of the MINAS CSGs are contributing to tumor occurrence. Detailed analysis, in the form of loss of heterozygosity or other tumor profiling strategies including immunohistochemistry of CSG gene products and microsatellite instability, would help clarify the role of MINAS CSGs in tumorigenesis (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eHere, we provide information on the largest single center cohort of MINAS carriers. In our study, a significant proportion of MINAS carriers are associated with atypical cancer presentations that cannot be explained by the single CSG alone, which may point to novel synergistic interactions of CSGs and expand the spectrum of cancers associated with CSGs. Further, we find that MINAS carriers with two or more hereditary breast CSGs developed earlier onset of breast cancer than single variants reported in the literature, therefore, warranting earlier surveillance and intervention. Importantly, further research is needed to interrogate novel cancer associations and disease severity in MINAS carriers with hereditary breast CSGs, in the form of larger, prospective cohort studies and case series and tumor profiling studies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement:\u0026nbsp;\u003c/strong\u003edata generated or analyzed during this study can be found within the published article and its supplementary file.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability:\u0026nbsp;\u003c/strong\u003enot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eThe authors thank the medical geneticists at\u0026nbsp;the Bhalwani Familial Cancer Clinic for their assistance with genetic analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eKO analyzed data and wrote the manuscript. MS performed statistical analysis and helped to write the manuscript. MH, KA, RM, LP contributed to study design and data extraction. RHK conceived the study. All authors read and approved the final version of the manuscript before submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis work was supported in part by the Bhalwani Family Charitable Foundation, Goldie R. Feldman, Karen Green and George Fischer Genomics and Genetics Fund, Lindy Green Family Foundation, FDC Foundation, Shar Foundation, The Devine/Sucharda Charitable Foundation, Leslie E. Born, Hal Jackman Foundation, Nicol Family Foundation, James and Christine Nicol, Janice Fukakusa and Greg Belbeck, Jack and Buschie Kamin Foundation, Marcus Tzaferis, Paul Bronfman Family Foundation, The Honey and Leonard Wolfe Family Charitable Foundation, Arman Alie and Margarette Nory, The Princess Margaret Cancer Foundation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval:\u0026nbsp;\u003c/strong\u003eEthics approval for this retrospective chart-review study was granted by the UHN Research Ethics\u0026nbsp;Board (ID:\u0026nbsp;24-5884).\u0026nbsp;The study was classified as no-risk and exempt from written informed consent.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003ethe authors declare no competing financial interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosures:\u0026nbsp;\u003c/strong\u003ethe authors have no disclosures.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFoulkes WD. Inherited Susceptibility to Common Cancers. N Engl J Med. 2008;359(20):2143\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWhitworth J, Skytte AB, Sunde L, Lim DH, Arends MJ, Happerfield L, et al. Multilocus Inherited Neoplasia Alleles Syndrome: A Case Series and Review. JAMA Oncol. 2016;2(3):373\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcGuigan A, Whitworth J, Andreou A, Hearn T, Tischkowitz M, Maher ER. Multilocus Inherited Neoplasia Allele Syndrome (MINAS): an update. Eur J Hum Genet. 2022;30(3):265\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYuen J, Zhou S, Caeser R, Venkatramani M, Bte Ishak DN, Li ST, et al. Multi-locus inherited neoplasia alleles syndromes in cancer: implications for clinical practice. Eur J Hum Genet. 2025;33(3):289\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNarayanan DL, Udyawar D, Kaur P, Sharma S, Suresh N, Nampoothiri S, et al. Multilocus disease-causing genomic variations for Mendelian disorders: role of systematic phenotyping and implications on genetic counselling. Eur J Hum Genet. 2021;29(12):1774\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eImyanitov EN, Kuligina ES, Sokolenko AP, Suspitsin EN, Yanus GA, Iyevleva AG, et al. Hereditary cancer syndromes. World J Clin Oncol. 2023;14(2):40\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBokkers K, Vlaming M, Engelhardt EG, Zweemer RP, van Oort IM, Kiemeney LALM, et al. The Feasibility of Implementing Mainstream Germline Genetic Testing in Routine Cancer Care\u0026mdash;A Systematic Review. Cancers. 2022;14(4):1059.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHeidemann S, Fischer C, Engel C, Fischer B, Harder L, Schlegelberger B, et al. Double heterozygosity for mutations in BRCA1 and BRCA2 in German breast cancer patients: implications on test strategies and clinical management. Breast Cancer Res Treat. 2012;134(3):1229\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRebbeck TR, Mitra N, Wan F, Sinilnikova OM, Healey S, McGuffog L, et al. Association of Type and Location of BRCA1 and BRCA2 Mutations With Risk of Breast and Ovarian Cancer. JAMA. 2015;313(13):1347\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStradella A, Del Valle J, Rofes P, Feliubadal\u0026oacute; L, Grau Garces \u0026Egrave;, Velasco \u0026Agrave;, et al. Does multilocus inherited neoplasia alleles syndrome have severe clinical expression? J Med Genet. 2019;56(8):521\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLeegte B, Hout AH van der, Deffenbaugh AM, Bakker MK, Mulder IM, Berge A ten, et al. Phenotypic expression of double heterozygosity for BRCA1 and BRCA2 germline mutations. J Med Genet. 2005;42(3):e20\u0026ndash;e20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBang YJ, Kwon WK, Nam SJ, Kim SW, Chae BJ, Lee SK, et al. Clinicopathological Characterization of Double Heterozygosity for BRCA1 and BRCA2 Variants in Korean Breast Cancer Patients. Cancer Res Treat. 2021;54(3):827\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eP\u0026oacute;cza T, Papp J, Bozsik A, Grolmusz VK, Nagy P, Pat\u0026oacute;cs A, et al. Double Pathogenic or Likely Pathogenic Variants in Cancer Predisposition Genes in Hungarian Cancer Patients. Int J Mol Sci. 2025;26(17):8390.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHur JY, Kim JY, Ahn JS, Im YH, Lee J, Kwon M, et al. Clinical Characteristics of Korean Breast Cancer Patients Who Carry Pathogenic Germline Mutations in Both BRCA1 and BRCA2: A Single-Center Experience. Cancers. 2020;12(5):1306.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHodan R, Gupta S, Weiss JM, Axell L, Burke CA, Chen LM, et al. Genetic/Familial High-Risk Assessment: Colorectal, Endometrial, and Gastric, Version 3.2024, NCCN Clinical Practice Guidelines In Oncology. J Natl Compr Cancer Netw JNCCN. 2024;22(10):695\u0026ndash;711.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDaly MB, Pal T, Maxwell KN, Churpek J, Kohlmann W, AlHilli Z, et al. NCCN Guidelines\u0026reg; Insights: Genetic/Familial High-Risk Assessment: Breast, Ovarian, and Pancreatic, Version 2.2024. J Natl Compr Cancer Netw JNCCN. 2023;21(10):1000\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHereditary Cancer Testing Eligibility Criteria: Version 3.1. Ontario Health Cancer Care Ontario; 2024.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\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. Genet Med. 2015;17(5):405\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAchatz MI, Villani A, Bertuch AA, Bougeard G, Chang VY, Doria AS, et al. Update on Cancer Screening Recommendations for Individuals with Li\u0026ndash;Fraumeni Syndrome. Clin Cancer Res. 2025;31(10):1831\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTischkowitz M, Balma\u0026ntilde;a J, Foulkes WD, James P, Ngeow J, Schmutzler R, et al. Management of individuals with germline variants in PALB2: a clinical practice resource of the American College of Medical Genetics and Genomics (ACMG). Genet Med. 2021;23(8):1416\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTorres-Esquius S, Llop-Guevara A, Guti\u0026eacute;rrez-Enr\u0026iacute;quez S, Romey M, Teul\u0026eacute; \u0026Agrave;, Llort G, et al. Prevalence of Homologous Recombination Deficiency Among Patients With Germline RAD51C/D Breast or Ovarian Cancer. JAMA Netw Open. 2024;7(4):e247811.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDouble heterozygous pathogenic variants prevalence in a cohort of patients with hereditary breast cancer. - Abstract - Europe PMC [Internet]. [cited 2025 Sept 27]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://europepmc.org/article/MED/36003761\u003c/span\u003e\u003cspan address=\"https://europepmc.org/article/MED/36003761\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\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":"european-journal-of-human-genetics","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"ejhg","sideBox":"Learn more about [European Journal of Human Genetics](http://www.nature.com/ejhg/)","snPcode":"41431","submissionUrl":"https://mts-ejhg.nature.com/cgi-bin/main.plex","title":"European Journal of Human Genetics","twitterHandle":"@ejhg_journal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"MINAS, hereditary cancer, cancer susceptibility genes","lastPublishedDoi":"10.21203/rs.3.rs-8149436/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8149436/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGenetic testing in hereditary cancer is evolving from single-gene focused approaches on affected individuals to multi-gene panel testing in affected individuals and unaffected relatives. The widespread use of multi-gene panel testing has led to the identification of individuals with two or more pathogenic or likely pathogenic variants in hereditary cancer susceptibility genes (CSGs), termed Multilocus Inherited Neoplasia Allele Syndrome (MINAS) carriers. It remains unclear whether MINAS carriers are at increased risk of multiple, atypical or more severe cancer phenotypes, and currently, there is no consensus on how best to identify and manage cancer risk. In this retrospective study, we identified 54 MINAS carriers at Princess Margaret Cancer Centre in Toronto, Canada. The majority of affected MINAS carriers had a cancer consistent with expression of at least one pathogenic variant, although nearly 40% were diagnosed with at least one cancer outside of the typical spectrum of their CSGs. The most frequent gene pair combinations included hereditary breast cancer genes, with some carriers exhibiting earlier age of breast cancer onset than single CSG variants reported in the literature. Overall, our study indicates that the cancer spectrum associated with certain CSGs is expanding and suggests more intensive cancer surveillance for subgroups of MINAS carriers with hereditary breast cancer CSGs.\u003c/p\u003e","manuscriptTitle":"Multilocus Inherited Neoplasia Alleles Syndrome: A Retrospective Review from a Canadian Single Institution","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-04 09:27:03","doi":"10.21203/rs.3.rs-8149436/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2026-02-12T10:59:28+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-02-10T05:11:04+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-02-06T07:39:40+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-12-14T16:55:12+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-12-12T15:10:55+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-12-11T09:26:19+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-12-02T14:57:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-25T16:45:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Human Genetics","date":"2025-11-18T23:50:33+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-18T23:50:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-human-genetics","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"ejhg","sideBox":"Learn more about [European Journal of Human Genetics](http://www.nature.com/ejhg/)","snPcode":"41431","submissionUrl":"https://mts-ejhg.nature.com/cgi-bin/main.plex","title":"European Journal of Human Genetics","twitterHandle":"@ejhg_journal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"cbd70c91-6cbd-46b0-8d1a-fb53517a93c8","owner":[],"postedDate":"December 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":58970479,"name":"Health sciences/Medical research/Genetics research"},{"id":58970480,"name":"Health sciences/Diseases/Cancer"}],"tags":[],"updatedAt":"2026-05-05T00:10:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-04 09:27:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8149436","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8149436","identity":"rs-8149436","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}