Germline pathogenic variants identification through Comprehensive Cancer Genome Profiling

Germline pathogenic variants identification through Comprehensive Cancer Genome Profiling | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Germline pathogenic variants identification through Comprehensive Cancer Genome Profiling Simona Duranti, Arianna Panfili, Camilla Nero, Ilenia Marino, and 23 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8088663/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Background: Comprehensive cancer genome profiling (CGP) is recommended for the identification of actionable somatic mutations in a selected subgroup of cancer patients. Some variants detected by CGP can be constitutional. The aim of this study is to evaluate the rate of potential and confirmed constitutional pathogenic/likely pathogenic variants (overall defined as PVs) identified through CGP according to the recommendations of the European Society of Medical Oncology Methods: This is a prospective interventional trial enrolling solid cancer patients in whom molecular assessment was clinically indicated based on national guidelines, referring them for CGP. Patients with suspected constitutional variants were subsequently referred for germline testing. The present analysis focuses on the first two years of the program, from January 2022 to December 2023. Results: Of 2688 samples (2674 patients) with a CGP report, more than half were represented by female reproductive system cancers. 16% of the patients were addressed to genetic evaluation for 527 suspected constitutional PVs, with a compliance to genetic counselling of 80%. 331 patients underwent germline testing, of whom 73% harbored at least one PV, with 66% of tested variants confirmed to be germline. Interestingly, 16% of germline variants were secondary findings and 20% of the confirmed “on-tumor” germline PVs were in moderate-risk genes. Eighteen additional constitutional PVs were identified in 17 patients based on the results of other somatic tests or through additional tests requested following genetic counselling (0.6% of the entire cohort). Conclusions: Constitutional PVs were detected in about 10% of an unselected solid tumor cohort through CGP. A relevant fraction of the constitutional PVs were secondary findings or constitutional variants in moderate penetrance genes, that would not have been detected based on current guidelines. The integration of CGP with systematic genetic counseling provides a comprehensive approach that optimizes both therapeutic decision-making and hereditary cancer prevention. Trial Registration: Protocol ID: FPG500, ID number: 3837, ClinicalTrials.gov Identifier: NCT06020625. Comprehensive cancer genome profiling Germline pathogenic variants Hereditary cancer syndrome Oncogenetics Figures Figure 1 Figure 2 INTRODUCTION The widespread adoption of comprehensive genomic profiling (CGP) in routine cancer care has introduced significant challenges, particularly in managing constitutional variants [ 1 ][ 2 ][ 3 ] To address this, the ESMO Precision Medicine Working Group has updated its recommendations for when to proceed with germline analysis based on tumor-only sequencing results. A reflex testing approach was advised for 40 cancer predisposition genes based on an observed per-gene germline confirmation rate (GCR) ≥ 5%. This testing is advised when the tumor variant allele frequency (VAF) exceeds 30% for single nucleotide variants (SNVs) and 20% for small insertions/deletions (indels). The list includes BRCA1, BRCA2, PALB2, MLH1, MSH2, MSH6 , and RET , alongside actionable intermediate-penetrance genes such as ATM and CHEK2 . For six genes ( APC, PTEN, RB1, TP53, CDKN2A, SMARCA4 ), germline analysis was recommended only for tumors arising in patients under the age of 30 [ 4 ]. Constitutional alterations in cancer susceptibility genes drive hereditary cancer predisposing syndromes (HCS) accounting for 10–13% of cancers [ 5 ][ 6 ][ 7 ][ 8 ]. Identifying these inherited variants is critical for defining surveillance, prophylactic, and therapeutic strategies. Currently, guidelines for germline testing are primarily based on a patient's personal and family medical history and focus on specific cancers (e.g., ovarian, breast, colorectal, prostate, endometrial), whereas comprehensive recommendations for other cancer types (ie, lung, bladder, brain) are not available. Large series suggest that suspected germline likely pathogenic/pathogenic variants (collectively defined “PVs”) in selected cancer predisposing genes are found in 10–23% of patients tested by CGP, with 3–18% confirmed to be constitutional [ 9 ][ 10 ][ 11 ][ 12 ]. Higher PV rates are observed in tumors with established guidelines (14% for ovarian cancer) compared to those without (5.4%). However, current screening methods may miss up to 50% of patients with rare or reduced-penetrance HCS [ 6 ]. The present study aims at evaluating the genetic implications of a monocentric CGP program across 11 different solid cancer types (ovary, endometrium, lung, colorectal, pancreas, biliary tract, prostate, thyroid, GIST, melanoma, breast). Specifically, we report the frequency of somatic variants for which germline analysis was recommended based on ESMO recommendations and the prevalence of identified constitutional PVs. The ultimate goal is to assess whether CGP can improve the detection of HCS, including moderate penetrance conditions and cancers not routinely considered for germline evaluation. Additionally, we aim to evaluate germline opportunistic findings, namely variants not typically associated with the tumor type. METHODS At Fondazione Policlinico Universitario Agostino Gemelli IRCCS (FPG), cancer patients ≥ 18 years old with clinical indication for somatic molecular test according to ESMO guidelines [ 1 ][ 2 ] were evaluated for enrollment in a CGP program using a tumor-only targeted NGS panel. This study follows the Declaration of Helsinki guidelines and received approval from the local ethical committee. All patients provided informed consent before participation. DNA was extracted from FFPE specimens with at least 20% tumor cells. All samples were profiled using TruSight Oncology 500 (TSO500) solution which identifies SNVs, indels, copy number alterations (CNA) in coding and exon/intron junction regions (+/-2 bp) of 523 genes, as well as fusions and splicing variants in 55 genes. Each report was reviewed by a medical geneticist to identify suspected germline variants and selected subjects were invited to the genetics clinic for confirmation on blood leukocyte DNA. Follow-up constitutional testing was advised based on ESMO recommendations [ 4 ]. In August 2023 a protocol amendment consented to collect blood at the time of enrollment, to allow quick testing without participant recall. Due to the sensitivity limits of TSO500 for CNVs and splice site variant identification, some patients were referred to genetic consultation based on other tests results [ BRCA Devyser, HRD status (Sophiagenetics) for ovarian cancer and mismatch repair (MMR) immunohistochemistry for endometrial or colorectal cancer] or based on clinical or pathological characteristics (multiple tumors, young age at cancer diagnosis, specific histotype, family history). Constitutional testing of the somatic variant(s) was performed by Sanger sequencing to detect a single variant or with a multi-gene panel (SOPHiA Hereditary Cancer Solution, Custom Panel Ion Ampliseq On-Demand IAD197864) or Multiplex Ligation-dependent Probe Amplification (MLPA) when clinically indicated. Demographic, clinical and molecular data of enrolled patients were collected through disease- and molecular-related electronic Case Report Forms (eCRFs) by reviewing medical records. The eCRFs were developed using REDCap hosted at https://redcap-irccs.policlinicogemelli.it/redcap/ . This web application is fully compliant with EU guidelines for data protection and management (General Data Protection Regulation - GDPR − 2016/679). STATISTICAL ANALYSIS Statistical analyses were mainly descriptive. Categorical variables were summarized by absolute frequencies and percentages while continuous variables were reported as means with standard deviations. Associations between categorical variables were evaluated using the chi-square test, and differences in mean values were assessed with the Student's t-test. A two-sided p value < 0.05 was considered statistically significant. All analyses were performed using STATA software (STATA/BE 17.0 for Windows, StataCorp LP, College Station, TX). RESULTS From January 2022 to December 2023, a total of 3124 cases were enrolled in the program. CGP analysis was feasible for 2674 patients (2688 samples, accounting for 86% of the entire cohort) (Suppl. Figure 1). For fourteen patients with multiple synchronous primary tumors one sample for each tumor was tested. Mean age at the time of cancer diagnosis was 61.8 years. Most individuals were female (77.3%) (Table 1). Table 1 Characteristics of the study population referred to genetic counseling and testing according to ESMO Recommendations Characteristics All subjects Subjects referred to genetic counseling Subjects not meeting criteria for germline testing Subjects tested for variant origin in leukocyte DNA All tested subjects Confirmed Not confirmed P value n = 2674 n = 437 n = 17 n = 331 n = 240 n = 91 Mean (SD) age at diagnosis, years 61.8 58.3 62.3 56.6 (11.9) 56.1 (11.2) 57.9 (13.6) 0.25^ Gender 0.20* Male 607 (22.7) 52 (11.9) 5 (29.4) 20 (6) 12 (5) 8 (8.8) Female 2067 (77.3) 385 (88.1) 12 (70.6) 311 (94) 228 (95) 83 (91.2) Familiy history of cancer 0.016* Unknown 631 (23.6) 93 (21.3) 3 (17.6) 63 (19) 42 (17.5) 21 (23.1) No 1090 (40.8) 138 (31.6) 7 (41.2) 88 (26.6) 56 (23.3) 32 (35.2) Yes 953 (35.6) 206 (47.1) 7 (41.2) 180 (54.4) 142 (59.2) 38 (41.8) Results are presented as n (%) except where indicated. ^Student t-test for independent group *chi-square test 57% of the tumors originated from the female reproductive system, followed by lung (18.2%), colorectal (11.4%) and pancreatic cancers (6.2%). Around 33% of the tumors were diagnosed at stage IV (Table 2). Table 2 Clinical characteristics of the cases referred to genetic counseling and testing according to ESMO Recommendations* Characteristics All cases Cases who underwent genetic counseling Cases with no clinical indication to perform constitutional test Cases who underwent constitutional testing All cases Confirmed* Not confirmed* P value n = 2688 n = 444 n = 18 n = 336 n = 244 n = 92 Neoplasm 0.08^ Ovary 860 (32) 241 (54.3) 6 (33.3) 221 (65.8) 169 (76.5) 52 (23.5) Endometrium 665 (24.7) 101 (22.7) 3 (16.7) 74 (22) 46 (62.2) 28 (37.8) Lung 490 (18.2) 37 (8.3) 5 (27.8) 10 (3) 6 (60) 4 (40) Colorectum 307 (11.4) 23 (5.2) 3 (16.7) 8 (2.4) 5 (62.5) 3 (37.5) Pancreas 166 (6.2) 14 (3.2) 0 (0) 10 (3) 9 (90) 1 (10) Prostate 65 (2.4) 7 (1.6) 0 (0) 3 (0.9) 3 (100) 0 (0) Melanoma 61 (2.3) 6 (1.4) 0 (0) 2 (0.6) 1 (50) 1 (50) Cholangiocarcinoma 40 (1.5) 7 (1.6) 0 (0) 3 (0.9) 1 (33.3) 2 (66.7) Thyroid 12 (0.4) 4 (0.9) 0 (0) 3 (0.9) 2 (66.7) 1 (33.3) GIST 10 (0.4) 2 (0.5) 0 (0) 2 (0.6) 2 (100) 0 (0) Breast 12 (0.4) 2 (0.5) 1 (5.6) 0 (0) - - Stage 0.08§ I 562 (20.9) 90 (20.3) 4 (22.2) 63 (18.8) 39 (61.9) 24 (38.1) II 146 (5.4) 26 (5.9) 2 (11.1) 23 (6.8) 17 (73.9) 6 (26.1) III 528 (19.6) 119 (26.8) 2 (11.1) 111 (33) 85 (76.6) 26 (23.4) IV 891 (33.1) 124 (27.9) 6 (33.3) 81 (24.1) 65 (80.2) 16 (19.8) Unknown 561 (20.9) 85 (19.1) 4 (22.2) 58 (17.3) 38 (65.5) 20 (34.5) Results are presented as n (%) except where indicated. *Patients with more than one primary cancer (resulting in multiple samples) were counted more than once and defined as cases ^chi-square calculated considering Neoplasm with an overall frequency > 3 § chi-square test 437 patients out of 2674 (16%) were referred to genetic counselling. The distribution of 444 cases by tumor type was as follows: ovarian cancer (54.3%), endometrial cancer (22.7%), lung cancer (8.3%), colorectal cancer (5.2%), pancreatic cancer (3.2%), prostate cancer (1.6%), melanoma (1.4%), cholangiocarcinoma (1.6%), thyroid cancer (0.9%), GIST (0.5%), and breast cancer (0.5%). Overall, 527 suspected constitutional PVs were identified across 30 genes. Of the patients with an indication for genetic counseling, 348 (80.0%) were evaluated by a geneticist. Adherence to genetic consultation varied by tumor types: individuals with ovarian, endometrial, pancreatic, thyroid cancer and GIST complied in more than 70% of cases, with ovarian cancer patients reaching 94.0% adherence. In contrast, less than 50% of the participants with lung, colorectal, and prostate cancer, melanoma, and cholangiocarcinoma, underwent genetic evaluation. 17 patients (4.9%) out of 348 did not receive indication to proceed with constitutional testing due to the absence of expected clinical features upon examination (i.e., NF1, PTCH1, TSC2 ). A total of 380 suspected PVs identified in 336 samples from 331 subjects were submitted to blood testing. 240 patients (72.5%) were diagnosed with at least one germline PV and 249 (65.5%) of the tested variants were confirmed to be constitutional (Table 1, Table 3 , Suppl Fig. 2). Table 3 Potential relevance of somatic pathogenic variants for cancer predisposition according to tumor type and gene involved Variants with indication to genetic counseling Variants with no clinical indication to perform germline test Variants tested in leukocyte DNA All variants Confirmed Not confirmed n = 527 n = 33 n = 380 n = 249 n = 131 Neoplasm Ovary 265 15 233 172 61 Endometrium 147 8 99 48 51 Lung 45 5 14 6 8 Colorectum 26 4 10 5 5 Cholangiocarcinoma 7 0 3 1 2 Pancreas 14 0 10 9 1 Prostate 8 0 4 3 1 Melanoma 7 0 2 1 1 Thyroid 4 0 3 2 1 GIST 2 0 2 2 0 Breast 2 1 0 0 0 Gene ATM 61 2 28 16 12 BAP1 4 0 2 0 2 BARD1 9 2 3 2 1 BRCA1 128 0 122 89 33 BRCA2 96 1 76 52 24 BRIP1 12 0 8 5 3 CHEK2 18 2 11 4 7 DICER1 10 4 4 0 4 FH 1 0 1 1 0 FLCN 1 0 1 0 1 MLH1 21 0 21 11 10 MSH2 29 0 27 14 13 MSH6 31 0 23 15 8 MUTYH 6 0 6 6 0 NF1 21 13 1 1 0 PALB2 13 0 8 8 0 PMS2 2 0 2 2 0 POLD1 3 0 0 0 0 POLE 5 1 4 1 3 PTCH1 13 6 4 0 4 PTEN 2 0 2 0 2 RAD51C 15 0 10 9 1 RAD51D 6 0 6 5 1 RET 5 1 4 3 1 SDHA 3 0 3 3 0 SDHB 3 0 2 1 1 SDHC 2 0 1 1 0 SMAD3 4 0 0 0 0 SMARCB1 2 0 0 0 0 TSC2 1 1 0 0 0 Results are presented as n (%) except where indicated. Among the 336 samples, the confirmation rate by tumor type was 100% for both GIST (2/2) and prostate cancer (3/3), 90.0% (9/10) for pancreatic cancer, 76.5% (169/221) for ovarian cancer, 66.7% (2/3) for thyroid cancer, around 60% for colon (5/8), endometrial (46/74) and lung cancer (6/10), 50% (1/2) for melanoma, and 33.3% (1/3) for cholangiocarcinoma (Table 2, Fig. 1 ). The mean age of individuals with confirmed PVs was significantly younger compared to the whole study population (56.1 vs. 61.8 years, p < 0.0001) (Table 1). 23.3% of the individuals with constitutional variants had no significant family history of malignancy based on medical history collected by oncologists. Among the 14 patients with synchronous cancers, 4 harbored at least one germline PV. Overall, more than 50% of suspected germline PVs were in BRCA1 / 2 and 19.2% in MMR genes, with a confirmation rate of 71.2% and 57.5% respectively (Table 3 ). Figure 2 shows the distribution of constitutional variants across the top five neoplasms, while Suppl. Figure 3 shows the distribution of all constitutional variants by gene and variant type. In ovarian cancer, 72.7% of germline variants were in BRCA1/2 , while a quarter were non- BRCA . MMR genes and RAD51C/RAD51D accounted for 5.8% and 7.0%, respectively (Suppl Table 1a). In endometrial cancers, 58.3% of germline variants were in MMR genes, 14.6% in BRCA1/2 , and 8.3% in ATM (Suppl. Table 1b). Among lung cancer, the 6 confirmed germline variants were in ATM (3) or BRCA1/2 (3) (Suppl Table 1c). Among colorectal cancer confirmed germline variants, 4 were in Lynch syndrome genes ( MLH1 ) and 1 in BRCA2 (Suppl Table 1d). In pancreatic cancers, 7/9 of the constitutional variants were in ATM, BRCA1/2 and PALB2 genes (Suppl Table 1e). Both the cholangiocarcinoma and melanoma cohorts, had only one germline BRCA1 variant (Suppl Table 1f and Suppl Table 1g). Among individuals with prostate cancer, the three confirmed variants were in HRR genes other than BRCA1/2 ( ATM, CHEK2, RAD51C ) (Suppl Table 1h). In the thyroid cohort, two germline PVs in the RET gene were documented (Suppl. Table 1i), while one PV in NF1 and one PV in SDHC were found in the GIST cohort (Suppl table 1j). Due to the inclusion criteria, only a small cohort of breast cancer patients was profiled and no germline PV was identified (Suppl table 1k). Two patients with MUTYH -associated polyposis (MAP) with biallelic PVs were identified, both with endometrial cancer, consistent with previous literature associating this syndrome with a moderately increased risk (3–9%) of this cancer type [ 13 ][ 14 ]. We also detected 27 MUTYH constitutional monoallelic PVs, but there were not included in the overall variant counting. Interestingly, 16% of germline variants were opportunistic findings. In particular, considering the tumors most represented in our cohort, 33% of PVs found in endometrial cancers and 6% of those identified in ovarian cancer were “off-tumor”. In contrast, only “on-tumor” variants were found in thyroid cancer and GIST. Moreover, among the “on-tumor” variants, 20% were associated to moderate-risk penetrance genes. Eighteen additional constitutional PVs, not detected by CGP due to technical limitations, because they were CNVs, or were located in flanking intronic regions or homopolymeric traits, were identified in 17 patients. These were tested due to a suspicion raised by the results of other somatic tests or by clinical characteristics. Two of them were opportunistic findings. It is worth noting that a CHEK2 PV, with a VAF below the threshold indicated by ESMO for reflex genetic testing, was confirmed to be constitutional following referral to genetic consultation for clinical suspicion of a HCS. Moreover, one PV in MSH2 , initially classified as VUS, has been reclassified as class 4, based on geneticist’s evaluation (suppl. Table 2). Overall, we identified three patients with a Multilocus Inherited Neoplasia Allele Syndrome (MINAS)[ 15 ]. All of them were affected by ovarian cancer: one with BRCA2 and BRIP1 PVs, the second with ATM and BRCA2 PVs and the third one with BRCA1 and CDKN2A PVs. Of note, in this last patient both PVs were identified with alternative techniques ( BRCA1 ) and after genetic evaluation, since the ESMO age criteria were not fulfilled ( CDKN2A ). DISCUSSION In this study we evaluated the germline predisposition potential of somatic variants identified through a large NGS panel in patients with 11 different solid tumors. In line with recently published trials [ 9 ][ 10 ][ 11 ][ 12 ], among 11 different cancer types, 16% of the patients were addressed to genetic counseling. High compliance with genetic evaluation was observed, with an attendance of 80% to the genetics clinic. Among tested patients, 73% showed a positive result, corresponding to approximately 10% of the overall cohort. However, the percentage varies from 1% to 20%, depending on cancer types. Of note, a high prevalence of opportunistic findings was registered, with 16% of constitutional variants found in an "off-tumor" context. Additionally, 20% of PVs identified “on-tumor” were associated with moderate risk penetrance genes. Interestingly, 23% of cases with confirmed constitutional variants had no reported family history of cancer. Identifying HCS is crucial for defining therapeutic, surveillance, and risk reduction strategies, such as prophylactic surgery and screening of at-risk family members. In this context, the widespread use of NGS panels for molecular cancer characterization, rather than the evaluation of individual biomarkers, enables at the same time the identification of molecular alterations useful for therapeutic purposes, as well as somatic variants with potential germline implications [ 16 ]. This includes not only variants routinely evaluated in clinical practice but also those in moderate-penetrance cancer genes not typically screened based on current guidelines, tumor type or family history [ 17 ]. CGP may improve the identification of constitutional PVs in unselected cancer patients, particularly when no test on normal tissue is indicated based on available guidelines. It may also detect variants not usually associated with the tested tumor type ("off-tumor" or opportunistic findings). A large study from Memorial Sloan Kettering Cancer Center, involving 10,336 patients with available tumor DNA sequencing, identified 1,040 patients with potential PVs; 17.5% of these patients were confirmed to have constitutional PVs, and more than half would have not been detected based on the available guidelines [ 11 ]. Recently, ESMO proposed recommendations concerning follow-up germline evaluation of somatic variants, based on factors such as the type of gene, patient’s age and variant characteristics (i.e. variant allele frequency). The authors reported that only 3% of true germline pathogenic variants were absent from the filtered tumor-detected variants [ 4 ]. In our study, after genetic evaluation, we found two cases in which somatic variants were later confirmed as constitutional in the absence of ESMO-recommended characteristics (VAF lower than the established threshold and patient’s age). Moreover, somatic testing may have limitations in identifying constitutional variants due to inherent technical issues. Lincoln et al. reported that approximately 8% of PVs were missed by tumor-only sequencing and 11% were identified only after a second primary cancer was diagnosed [ 16 ]. The Illumina TSO500 panel has limitations in CNV detection and can only identify variants located within ± 2 base pairs of exon/intron junctions. Consequently, further analyses were performed when another somatic test identified potential CNVs or in cases with suspected personal or family history. This approach led to the identification of additional 18 PVs, many of which were BRCA1/2 exon deletions. This finding aligns with literature data reporting a high prevalence of CNVs in these genes (11–13% in BRCA1 and 2–3% in BRCA2 ) [ 18 ]. Regarding the strengths of this study, we highlight a high adherence rate to genetic testing compared with clinical practice. This high compliance was achieved through the involvement of trained healthcare professionals, particularly dedicated clinical geneticists and molecular care managers. However, lower compliance to genetic counselling was reported for some tumors, probably due to the metastatic setting and high mortality rate, to the fact that some of these patients were lost to follow up, or for lack of therapeutic implications of the genetic variant identified. LIMITATIONS This study has several limitations. First, the major limitation concerns reproducibility, constrained by restricted access to extensive somatic NGS panels. This constraint arises from the limited availability and elevated costs of such technologies, which restrict their use to a select number of specialized centers. Furthermore, to ensure correct data interpretation, dedicated resources, multidisciplinary meetings, and a well-defined workflow are essential. In particular, genetic counseling with constitutional sampling should be promptly arranged for patients suspected of carrying germline variants. This will ensure the establishment of appropriate surveillance pathways, risk reduction strategies, and identification of carriers among family members. Second, somatic panels analyzing only the tumor may have limitations in identifying germline PVs. As a result, additional analyses were performed for the first 2 years of program when other somatic tests suggested potential CNVs or when patients had a suggestive personal or family history. A new secondary analysis pipeline optimized for BRCA1/2 CNV detection was implemented in 2024, improving sensitivity for these alterations. However, this limitation could also be addressed by performing paired tumor-normal sequencing, which improves both in terms of compliance and technical limitations the detection rate [ 4 ]. Third, for confirmed carriers of variants associated with HCS, data on the uptake of available risk-reducing procedures, surveillance strategies, and cascade testing among relatives were not available. This gap limits the ability to perform a comprehensive cost-effectiveness analysis to inform healthcare policy and decision-making. Finally, the cohort is unbalanced in terms of tumor types, with a predominance of gynecological cancers and tumors characterized by hypermutated or ultramutated phenotypes. This may have led to an overrepresentation of suspected PVs and could limit the generalizability of the findings. CONCLUSIONS Italian national guidelines currently control access to germline genetic testing, with clinical and familial criteria determining eligibility. These guidelines align with international recommendations, particularly for BRCA1/2 and Lynch syndrome-associated cancers but also consider specific aspects of the Italian healthcare system, such as the public reimbursement framework. Notably, recent publications [ 10 ] have emphasized the importance of extending genetic testing beyond traditional clinical indications, particularly in light of the increasing availability of somatic NGS-based testing in oncology. The growing availability of these assays offers the opportunity to simultaneously identify variants potentially of germline origin associated with HCS. Our analysis represents a single-center study in one of the largest academic hospitals in Italy. We confirmed that approximately 10% of cancer patients have a HCS identifiable through somatic testing. In particular, through CGP, we identified a significant proportion of germline variants as opportunistic findings and a substantial number of PVs in moderate-penetrance genes in patients without a known family history of cancer. These probably would not have been identified through standard diagnostic pathways. This data reinforce the suggestion to establish integrated workflows for identifying potential germline variants in centers adopting CGP for enabling preventive strategies and facilitating cascade testing in at-risk families. Abbreviations CGP: comprehensive genomic profiling VAF : variant allele frequency SNVs : single nucleotide variants INDELS : insertions/deletions HCS : hereditary cancer predisposing syndromes PVs : pathogenic/likely pathogenic variants TSO500 : TruSight Oncology 500 CNA : copy number alterations MMR : mismatch repair MLPA : Multiplex Ligation-dependent Probe Amplification eCRFs : electronic Case Report Forms MAP : MUTYH-associated polyposis MINAS : Multilocus Inherited Neoplasia Allele Syndrome Declarations Additional Information Acknowledgements We acknowledge the support of AIRC under MFAG 2022 – ID. 27367 - PI Lisa Salvatore; Ministero della Salute (Ricerca Corrente 2022), the AIRC (Investigator Grant number IG26330), Ministero dell’Università e della Ricerca (PRIN 2022 PNRR Prot P2022LN3KS and PRIN 2022 Prot 2022P79F9N), and Agenzia Italiana del Farmaco, Ministero della Salute (J38D19000690001 FIMP,and RF CO-2019-12369662) to Giampaolo Tortora. We thank Chiara Parrillo (Bioinformatics Research Core Facility), Giulia Pugliese (Data Collection Core Facility), and Gabriella Ciotti (Immunohistochemistry Core Facility), all part of the Gemelli Science and Technology Park (GSTeP), for their valuable support and technical assistance. Author contributions SD, AP, CN, MG, GS contributed to study design, data interpretation, literature search, and writing of the manuscript; TP, IM, IM, contributed to data curation; LG, SR, TP, DG contributed to data analysis and generation of figures; AM, GM contributed in genomic analysis; AP, contributed in pathological analysis; EB, LS, MAC, RI, KP,RT, VI, AV, AP, AF, FF, ELC, GT contributed in revision of the manuscript. All authors read and approved the final paper. Ethics approval and consent to participate The study has been conducted following the Declaration of Helsinki and has received approval from the Fondazione Policlinico Universitario “A. Gemelli” IRCCS ethical committee. Prior to participation, all patients provided informed consent. Data Availability Statement The datasets generated and analyzed during the current study are not publicly available due to Ethical reasons, but are available from the corresponding author on reasonable request. Financial & competing interests disclosure This study was partially supported by the Italian Ministry of Health (Ricerca Corrente; no grant number provided). C.N. declares travel support from MSD, Illumina, Menarini, AZand honoraria from Veeva, GSK, MSD, AZ, Altems, Illumina and Guardant Health. F.F. reports research funding from Clovis, GSK, MSD and PharmaMar, personal and financial interests with GSK, MSD, SYSMEX, STRYKER ,G.S. reports research support from MSD and honoraria from Clovis Oncology, consultant for Tesaro and Johnson&Johnson. LS reports consulting or advisory role for Pierre-Fabre, AstraZeneca, Bayer, SERVIER, Merck, Amgen, GSK, Incyte, Leopharma, MSD, Takeda. 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Mutation Detection in Patients With Advanced Cancer by Universal Sequencing of Cancer-Related Genes in Tumor and Normal DNA vs Guideline-Based Germline Testing. JAMA. 2017;318(9):825-835. doi:10.1001/jama.2017.11137 Huang KL, Mashl RJ, Wu Y, et al. Pathogenic Germline Variants in 10,389 Adult Cancers. Cell. 2018;173(2):355-370.e14. doi:10.1016/j.cell.2018.03.039 Sutcliffe EG, Bartenbaker Thompson A, Stettner AR, et al. Multi-gene panel testing confirms phenotypic variability in MUTYH-Associated Polyposis. Fam Cancer . 2019;18(2):203-209. doi:10.1007/s10689-018-00116-2 Tricarico R, Bet P, Ciambotti B, et al. Endometrial cancer and somatic G>T KRAS transversion in patients with constitutional MUTYH biallelic mutations. Cancer Lett . 2009;274(2):266-270. doi:10.1016/j.canlet.2008.09.022 McGuigan A, Whitworth J, Andreou A, et al. Multilocus Inherited Neoplasia Allele Syndrome (MINAS): an update. Eur J Hum Genet. 2022;30(3):265-270. doi:10.1038/s41431-021-01013-6 Lincoln SE, Nussbaum RL, Kurian AW, et al. Yield and Utility of Germline Testing Following Tumor Sequencing in Patients With Cancer. JAMA Netw Open . 2020;3(10):e2019452. Published 2020 Oct 1. doi:10.1001/jamanetworkopen.2020.19452 Tung N, Ricker C, Messersmith H, et al. Selection of germline genetic testing panels in patients with cancer: ASCO guideline. J Clin Oncol. 2024;42(21). doi:10.1200/JCO.24.00662 LaDuca H, Polley EC, Yussuf A, et al. A clinical guide to hereditary cancer panel testing: evaluation of gene-specific cancer associations and sensitivity of genetic testing criteria in a cohort of 165,000 high-risk patients. Genet Med . 2020;22(2):407-415. doi:10.1038/s41436-019-0633-8 Additional Declarations Competing interest reported. This study was partially supported by the Italian Ministry of Health (Ricerca Corrente; no grant number provided). C.N. declares travel support from MSD, Illumina, Menarini, AZand honoraria from Veeva, GSK, MSD, AZ, Altems, Illumina and Guardant Health. F.F. reports research funding from Clovis, GSK, MSD and PharmaMar, personal and financial interests with GSK, MSD, SYSMEX, STRYKER ,G.S. reports research support from MSD and honoraria from Clovis Oncology, consultant for Tesaro and Johnson&Johnson. LS reports consulting or advisory role for Pierre-Fabre, AstraZeneca, Bayer, SERVIER, Merck, Amgen, GSK, Incyte, Leopharma, MSD, Takeda. MAC reports consulting or advisory role for Amgen, Bayer, Merck, Pierre-Fabre, SERVIER, Takeda GT reports consulting or advisory role for BMS, AstraZeneca, MSD, Merck, and Servier. All other authors have declared no conflicts of interest. Supplementary Files Supplementaryfigure1.pdf Supplementaryfigure2.pdf Supplementaryfigure3.pdf SupplementaryTables.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 28 Jan, 2026 Reviews received at journal 28 Jan, 2026 Reviews received at journal 05 Jan, 2026 Reviews received at journal 31 Dec, 2025 Reviews received at journal 30 Dec, 2025 Reviewers agreed at journal 08 Dec, 2025 Reviewers agreed at journal 04 Dec, 2025 Reviewers agreed at journal 04 Dec, 2025 Reviewers agreed at journal 04 Dec, 2025 Reviewers invited by journal 03 Dec, 2025 Editor assigned by journal 26 Nov, 2025 Submission checks completed at journal 12 Nov, 2025 First submitted to journal 11 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. 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bars, scaled 0%–100%). Patients with more than one primary cancer (resulting in multiple samples) were counted more than once. In addition, a heatmap illustrates constitutional findings by gene and cancer type. Blue cells indicate cancer/gene combinations in which a germline variant was confirmed, with the shading reflecting the percentage of findings of constitutional origin. Cancer/gene combinations in which no variants were present are represented as blank cells\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8088663/v1/6c964d03c37c6e1b775503ac.png"},{"id":97691442,"identity":"6bb4c7f2-0510-4762-82d4-445a095ba727","added_by":"auto","created_at":"2025-12-08 10:59:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":118879,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of Constitutional Variants by Gene and Cancer Type\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThis figure illustrates the distribution of the constitutional variants across the top 5 neoplasms. Each bar represents a specific gene, with colors consistently assigned to each gene, as indicated by the legend on the right. The percentage at the top of each bar reflects the proportion of variants for that gene relative to the total number of constitutional variants for the corresponding neoplasm.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8088663/v1/f44b3b065a7b28af30baeb02.png"},{"id":97902542,"identity":"f03ec938-5f41-4d58-8daf-24a20a7efc75","added_by":"auto","created_at":"2025-12-10 15:52:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1509060,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8088663/v1/52a08ebe-4653-497e-b217-ab39810828dd.pdf"},{"id":97893704,"identity":"f9b0df01-242f-441a-a084-50d21cd768ed","added_by":"auto","created_at":"2025-12-10 15:30:53","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":287516,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfigure1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8088663/v1/11e4152b8a32ee3bb936e977.pdf"},{"id":97892681,"identity":"e4de55f2-d30a-44c4-aff8-2b36f7f0924b","added_by":"auto","created_at":"2025-12-10 15:18:27","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":479156,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfigure2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8088663/v1/34e29212b8e52c4b348bc0eb.pdf"},{"id":97894234,"identity":"545e8617-2711-413f-8f5e-682adc60d9b1","added_by":"auto","created_at":"2025-12-10 15:32:04","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":417847,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfigure3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8088663/v1/75b525cfae7d33f81b2ffaaf.pdf"},{"id":97691450,"identity":"81bd99aa-9948-423e-94c4-ca912d85f36f","added_by":"auto","created_at":"2025-12-08 10:59:20","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":623814,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8088663/v1/81297847d5828b400c802c79.pdf"}],"financialInterests":"Competing interest reported. This study was partially supported by the Italian Ministry of Health (Ricerca Corrente; no grant number provided). \nC.N. declares travel support from MSD, Illumina, Menarini, AZand honoraria from Veeva, GSK, MSD, AZ, Altems, Illumina and Guardant Health. \nF.F. reports research funding from Clovis, GSK, MSD and PharmaMar, personal and financial interests with GSK, MSD, SYSMEX, STRYKER ,G.S. reports research support from MSD and honoraria from Clovis Oncology, consultant for Tesaro and Johnson\u0026Johnson.\nLS reports consulting or advisory role for Pierre-Fabre, AstraZeneca, Bayer, SERVIER, Merck, Amgen, GSK, Incyte, Leopharma, MSD, Takeda.\nMAC reports consulting or advisory role for Amgen, Bayer, Merck, Pierre-Fabre, SERVIER, Takeda\nGT reports consulting or advisory role for BMS, AstraZeneca, MSD, Merck, and Servier.\nAll other authors have declared no conflicts of interest.","formattedTitle":"Germline pathogenic variants identification through Comprehensive Cancer Genome Profiling","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe widespread adoption of comprehensive genomic profiling (CGP) in routine cancer care has introduced significant challenges, particularly in managing constitutional variants [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e][\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e][\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eTo address this, the ESMO Precision Medicine Working Group has updated its recommendations for when to proceed with germline analysis based on tumor-only sequencing results. A reflex testing approach was advised for 40 cancer predisposition genes based on an observed per-gene germline confirmation rate (GCR)\u0026thinsp;\u0026ge;\u0026thinsp;5%. This testing is advised when the tumor variant allele frequency (VAF) exceeds 30% for single nucleotide variants (SNVs) and 20% for small insertions/deletions (indels). The list includes \u003cem\u003eBRCA1, BRCA2, PALB2, MLH1, MSH2, MSH6\u003c/em\u003e, and \u003cem\u003eRET\u003c/em\u003e, alongside actionable intermediate-penetrance genes such as \u003cem\u003eATM\u003c/em\u003e and \u003cem\u003eCHEK2\u003c/em\u003e. For six genes (\u003cem\u003eAPC, PTEN, RB1, TP53, CDKN2A, SMARCA4\u003c/em\u003e), germline analysis was recommended only for tumors arising in patients under the age of 30 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConstitutional alterations in cancer susceptibility genes drive hereditary cancer predisposing syndromes (HCS) accounting for 10\u0026ndash;13% of cancers [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e][\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e][\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e][\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Identifying these inherited variants is critical for defining surveillance, prophylactic, and therapeutic strategies. Currently, guidelines for germline testing are primarily based on a patient's personal and family medical history and focus on specific cancers (e.g., ovarian, breast, colorectal, prostate, endometrial), whereas comprehensive recommendations for other cancer types (ie, lung, bladder, brain) are not available.\u003c/p\u003e\u003cp\u003eLarge series suggest that suspected germline likely pathogenic/pathogenic variants (collectively defined \u0026ldquo;PVs\u0026rdquo;) in selected cancer predisposing genes are found in 10\u0026ndash;23% of patients tested by CGP, with 3\u0026ndash;18% confirmed to be constitutional [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e][\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e][\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e][\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Higher PV rates are observed in tumors with established guidelines (14% for ovarian cancer) compared to those without (5.4%). However, current screening methods may miss up to 50% of patients with rare or reduced-penetrance HCS [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe present study aims at evaluating the genetic implications of a monocentric CGP program across 11 different solid cancer types (ovary, endometrium, lung, colorectal, pancreas, biliary tract, prostate, thyroid, GIST, melanoma, breast). Specifically, we report the frequency of somatic variants for which germline analysis was recommended based on ESMO recommendations and the prevalence of identified constitutional PVs. The ultimate goal is to assess whether CGP can improve the detection of HCS, including moderate penetrance conditions and cancers not routinely considered for germline evaluation. Additionally, we aim to evaluate germline opportunistic findings, namely variants not typically associated with the tumor type.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eAt Fondazione Policlinico Universitario Agostino Gemelli IRCCS (FPG), cancer patients\u0026thinsp;\u0026ge;\u0026thinsp;18 years old with clinical indication for somatic molecular test according to ESMO guidelines [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e][\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] were evaluated for enrollment in a CGP program using a tumor-only targeted NGS panel. This study follows the Declaration of Helsinki guidelines and received approval from the local ethical committee. All patients provided informed consent before participation.\u003c/p\u003e\u003cp\u003eDNA was extracted from FFPE specimens with at least 20% tumor cells. All samples were profiled using TruSight Oncology 500 (TSO500) solution which identifies SNVs, indels, copy number alterations (CNA) in coding and exon/intron junction regions (+/-2 bp) of 523 genes, as well as fusions and splicing variants in 55 genes.\u003c/p\u003e\u003cp\u003eEach report was reviewed by a medical geneticist to identify suspected germline variants and selected subjects were invited to the genetics clinic for confirmation on blood leukocyte DNA. Follow-up constitutional testing was advised based on ESMO recommendations [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In August 2023 a protocol amendment consented to collect blood at the time of enrollment, to allow quick testing without participant recall.\u003c/p\u003e\u003cp\u003eDue to the sensitivity limits of TSO500 for CNVs and splice site variant identification, some patients were referred to genetic consultation based on other tests results [\u003cem\u003eBRCA\u003c/em\u003e Devyser, HRD status (Sophiagenetics) for ovarian cancer and mismatch repair (MMR) immunohistochemistry for endometrial or colorectal cancer] or based on clinical or pathological characteristics (multiple tumors, young age at cancer diagnosis, specific histotype, family history).\u003c/p\u003e\u003cp\u003eConstitutional testing of the somatic variant(s) was performed by Sanger sequencing to detect a single variant or with a multi-gene panel (SOPHiA Hereditary Cancer Solution, Custom Panel Ion Ampliseq On-Demand IAD197864) or Multiplex Ligation-dependent Probe Amplification (MLPA) when clinically indicated.\u003c/p\u003e\u003cp\u003e Demographic, clinical and molecular data of enrolled patients were collected through disease- and molecular-related electronic Case Report Forms (eCRFs) by reviewing medical records. The eCRFs were developed using REDCap hosted at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://redcap-irccs.policlinicogemelli.it/redcap/\u003c/span\u003e\u003cspan address=\"https://redcap-irccs.policlinicogemelli.it/redcap/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. This web application is fully compliant with EU guidelines for data protection and management (General Data Protection Regulation - GDPR \u0026minus;\u0026thinsp;2016/679).\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eSTATISTICAL ANALYSIS\u003c/h2\u003e\u003cp\u003eStatistical analyses were mainly descriptive. Categorical variables were summarized by absolute frequencies and percentages while continuous variables were reported as means with standard deviations. Associations between categorical variables were evaluated using the chi-square test, and differences in mean values were assessed with the Student's t-test. A two-sided p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All analyses were performed using STATA software (STATA/BE 17.0 for Windows, StataCorp LP, College Station, TX).\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eFrom January 2022 to December 2023, a total of 3124 cases were enrolled in the program. CGP analysis was feasible for 2674 patients (2688 samples, accounting for 86% of the entire cohort) (Suppl. Figure\u0026nbsp;1).\u003c/p\u003e\n\u003cp\u003eFor fourteen patients with multiple synchronous primary tumors one sample for each tumor was tested. Mean age at the time of cancer diagnosis was 61.8 years. Most individuals were female (77.3%) (Table 1).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"10\"\u003e\n \u003cp\u003eTable\u0026nbsp;1 Characteristics of the study population referred to genetic counseling and testing according to ESMO Recommendations\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAll subjects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSubjects referred to genetic counseling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSubjects not meeting criteria for germline testing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eSubjects tested for variant origin in leukocyte DNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAll tested subjects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConfirmed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot confirmed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;2674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD) age at diagnosis, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.6 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.1 (11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.9 (13.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.25^\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.20*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e607 (22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (29.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2067 (77.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e385 (88.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (70.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e311 (94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e228 (95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83 (91.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFamiliy history of cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.016*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e631 (23.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93 (21.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42 (17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1090 (40.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e138 (31.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (41.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88 (26.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56 (23.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (35.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e953 (35.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e206 (47.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (41.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e180 (54.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e142 (59.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (41.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003eResults are presented as n (%) except where indicated.\u003c/p\u003e\n \u003cp\u003e^Student t-test for independent group *chi-square test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e57% of the tumors originated from the female reproductive system, followed by lung (18.2%), colorectal (11.4%) and pancreatic cancers (6.2%). Around 33% of the tumors were diagnosed at stage IV (Table 2).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tabb\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"10\"\u003e\n \u003cp\u003eTable\u0026nbsp;2 Clinical characteristics of the cases referred to genetic counseling and testing according to ESMO Recommendations*\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAll cases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCases who underwent genetic counseling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCases with no clinical indication to perform constitutional test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eCases who underwent constitutional testing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAll cases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConfirmed*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot confirmed*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;2688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeoplasm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.08^\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOvary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e860 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e241 (54.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e221 (65.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e169 (76.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52 (23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEndometrium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e665 (24.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e101 (22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 (62.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (37.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e490 (18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (27.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eColorectum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e307 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePancreas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e166 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProstate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMelanoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCholangiocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGIST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBreast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.08\u0026sect;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e562 (20.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90 (20.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63 (18.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (61.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (38.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e146 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (73.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (26.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e528 (19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e119 (26.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e111 (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85 (76.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (23.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e891 (33.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e124 (27.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81 (24.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65 (80.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e561 (20.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85 (19.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 (17.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (65.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (34.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003eResults are presented as n (%) except where indicated.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"10\"\u003e\n \u003cp\u003e*Patients with more than one primary cancer (resulting in multiple samples) were counted more than once and defined as cases\u003c/p\u003e\n \u003cp\u003e^chi-square calculated considering Neoplasm with an overall frequency\u0026thinsp;\u0026gt;\u0026thinsp;3\u003c/p\u003e\n \u003cp\u003e\u0026sect; chi-square test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e437 patients out of 2674 (16%) were referred to genetic counselling. The distribution of 444 cases by tumor type was as follows: ovarian cancer (54.3%), endometrial cancer (22.7%), lung cancer (8.3%), colorectal cancer (5.2%), pancreatic cancer (3.2%), prostate cancer (1.6%), melanoma (1.4%), cholangiocarcinoma (1.6%), thyroid cancer (0.9%), GIST (0.5%), and breast cancer (0.5%). Overall, 527 suspected constitutional PVs were identified across 30 genes.\u003c/p\u003e\n\u003cp\u003eOf the patients with an indication for genetic counseling, 348 (80.0%) were evaluated by a geneticist. Adherence to genetic consultation varied by tumor types: individuals with ovarian, endometrial, pancreatic, thyroid cancer and GIST complied in more than 70% of cases, with ovarian cancer patients reaching 94.0% adherence. In contrast, less than 50% of the participants with lung, colorectal, and prostate cancer, melanoma, and cholangiocarcinoma, underwent genetic evaluation. 17 patients (4.9%) out of 348 did not receive indication to proceed with constitutional testing due to the absence of expected clinical features upon examination (i.e., \u003cem\u003eNF1, PTCH1, TSC2\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eA total of 380 suspected PVs identified in 336 samples from 331 subjects were submitted to blood testing. 240 patients (72.5%) were diagnosed with at least one germline PV and 249 (65.5%) of the tested variants were confirmed to be constitutional (Table 1, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, Suppl Fig. 2).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePotential relevance of somatic pathogenic variants for cancer predisposition according to tumor type and gene involved\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariants with indication to genetic counseling\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariants with no clinical indication to perform germline test\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eVariants tested in leukocyte DNA\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAll variants\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConfirmed\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNot confirmed\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;527\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeoplasm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOvary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEndometrium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eColorectum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCholangiocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePancreas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProstate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMelanoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGIST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBreast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eATM\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBAP1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBARD1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRIP1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCHEK2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eDICER1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eFH\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eFLCN\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMLH1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMSH2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMSH6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMUTYH\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNF1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePALB2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePMS2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePOLD1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePOLE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePTCH1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePTEN\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRAD51C\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRAD51D\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRET\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSDHA\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSDHB\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSDHC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSMAD3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSMARCB1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTSC2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eResults are presented as n (%) except where indicated.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAmong the 336 samples, the confirmation rate by tumor type was 100% for both GIST (2/2) and prostate cancer (3/3), 90.0% (9/10) for pancreatic cancer, 76.5% (169/221) for ovarian cancer, 66.7% (2/3) for thyroid cancer, around 60% for colon (5/8), endometrial (46/74) and lung cancer (6/10), 50% (1/2) for melanoma, and 33.3% (1/3) for cholangiocarcinoma (Table 2, Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe mean age of individuals with confirmed PVs was significantly younger compared to the whole study population (56.1 vs. 61.8 years, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Table\u0026nbsp;1). 23.3% of the individuals with constitutional variants had no significant family history of malignancy based on medical history collected by oncologists. Among the 14 patients with synchronous cancers, 4 harbored at least one germline PV.\u003c/p\u003e\n\u003cp\u003eOverall, more than 50% of suspected germline PVs were in \u003cem\u003eBRCA1\u003c/em\u003e/\u003cem\u003e2\u003c/em\u003e and 19.2% in MMR genes, with a confirmation rate of 71.2% and 57.5% respectively (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e shows the distribution of constitutional variants across the top five neoplasms, while Suppl. Figure 3 shows the distribution of all constitutional variants by gene and variant type.\u003c/p\u003e\n\u003cp\u003eIn ovarian cancer, 72.7% of germline variants were in \u003cem\u003eBRCA1/2\u003c/em\u003e, while a quarter were non-\u003cem\u003eBRCA\u003c/em\u003e. MMR genes and \u003cem\u003eRAD51C/RAD51D\u003c/em\u003e accounted for 5.8% and 7.0%, respectively (Suppl Table 1a). In endometrial cancers, 58.3% of germline variants were in MMR genes, 14.6% in \u003cem\u003eBRCA1/2\u003c/em\u003e, and 8.3% in \u003cem\u003eATM\u003c/em\u003e (Suppl. Table 1b). Among lung cancer, the 6 confirmed germline variants were in \u003cem\u003eATM\u003c/em\u003e (3) or \u003cem\u003eBRCA1/2\u003c/em\u003e (3) (Suppl Table 1c). Among colorectal cancer confirmed germline variants, 4 were in Lynch syndrome genes (\u003cem\u003eMLH1\u003c/em\u003e) and 1 in \u003cem\u003eBRCA2\u003c/em\u003e (Suppl Table 1d). In pancreatic cancers, 7/9 of the constitutional variants were in \u003cem\u003eATM, BRCA1/2\u003c/em\u003e and \u003cem\u003ePALB2\u003c/em\u003e genes (Suppl Table 1e). Both the cholangiocarcinoma and melanoma cohorts, had only one germline \u003cem\u003eBRCA1\u003c/em\u003e variant (Suppl Table 1f and Suppl Table 1g). Among individuals with prostate cancer, the three confirmed variants were in HRR genes other than \u003cem\u003eBRCA1/2\u003c/em\u003e (\u003cem\u003eATM, CHEK2, RAD51C\u003c/em\u003e) (Suppl Table 1h). In the thyroid cohort, two germline PVs in the \u003cem\u003eRET\u003c/em\u003e gene were documented (Suppl. Table 1i), while one PV in \u003cem\u003eNF1\u003c/em\u003e and one PV in \u003cem\u003eSDHC\u003c/em\u003e were found in the GIST cohort (Suppl table 1j). Due to the inclusion criteria, only a small cohort of breast cancer patients was profiled and no germline PV was identified (Suppl table 1k).\u003c/p\u003e\n\u003cp\u003eTwo patients with \u003cem\u003eMUTYH\u003c/em\u003e-associated polyposis (MAP) with biallelic PVs were identified, both with endometrial cancer, consistent with previous literature associating this syndrome with a moderately increased risk (3\u0026ndash;9%) of this cancer type [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e][\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e]. We also detected 27 \u003cem\u003eMUTYH\u003c/em\u003e constitutional monoallelic PVs, but there were not included in the overall variant counting.\u003c/p\u003e\n\u003cp\u003eInterestingly, 16% of germline variants were opportunistic findings. In particular, considering the tumors most represented in our cohort, 33% of PVs found in endometrial cancers and 6% of those identified in ovarian cancer were \u0026ldquo;off-tumor\u0026rdquo;. In contrast, only \u0026ldquo;on-tumor\u0026rdquo; variants were found in thyroid cancer and GIST. Moreover, among the \u0026ldquo;on-tumor\u0026rdquo; variants, 20% were associated to moderate-risk penetrance genes.\u003c/p\u003e\n\u003cp\u003eEighteen additional constitutional PVs, not detected by CGP due to technical limitations, because they were CNVs, or were located in flanking intronic regions or homopolymeric traits, were identified in 17 patients. These were tested due to a suspicion raised by the results of other somatic tests or by clinical characteristics. Two of them were opportunistic findings. It is worth noting that a \u003cem\u003eCHEK2\u003c/em\u003e PV, with a VAF below the threshold indicated by ESMO for reflex genetic testing, was confirmed to be constitutional following referral to genetic consultation for clinical suspicion of a HCS. Moreover, one PV in \u003cem\u003eMSH2\u003c/em\u003e, initially classified as VUS, has been reclassified as class 4, based on geneticist\u0026rsquo;s evaluation (suppl. Table\u0026nbsp;2).\u003c/p\u003e\n\u003cp\u003eOverall, we identified three patients with a Multilocus Inherited Neoplasia Allele Syndrome (MINAS)[\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]. All of them were affected by ovarian cancer: one with \u003cem\u003eBRCA2\u003c/em\u003e and \u003cem\u003eBRIP1\u003c/em\u003e PVs, the second with \u003cem\u003eATM\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e PVs and the third one with \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eCDKN2A\u003c/em\u003e PVs. Of note, in this last patient both PVs were identified with alternative techniques (\u003cem\u003eBRCA1\u003c/em\u003e) and after genetic evaluation, since the ESMO age criteria were not fulfilled (\u003cem\u003eCDKN2A\u003c/em\u003e).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this study we evaluated the germline predisposition potential of somatic variants identified through a large NGS panel in patients with 11 different solid tumors. In line with recently published trials [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e][\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e][\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e][\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], among 11 different cancer types, 16% of the patients were addressed to genetic counseling.\u003c/p\u003e\u003cp\u003e High compliance with genetic evaluation was observed, with an attendance of 80% to the genetics clinic. Among tested patients, 73% showed a positive result, corresponding to approximately 10% of the overall cohort. However, the percentage varies from 1% to 20%, depending on cancer types. Of note, a high prevalence of opportunistic findings was registered, with 16% of constitutional variants found in an \"off-tumor\" context. Additionally, 20% of PVs identified \u0026ldquo;on-tumor\u0026rdquo; were associated with moderate risk penetrance genes. Interestingly, 23% of cases with confirmed constitutional variants had no reported family history of cancer.\u003c/p\u003e\u003cp\u003eIdentifying HCS is crucial for defining therapeutic, surveillance, and risk reduction strategies, such as prophylactic surgery and screening of at-risk family members. In this context, the widespread use of NGS panels for molecular cancer characterization, rather than the evaluation of individual biomarkers, enables at the same time the identification of molecular alterations useful for therapeutic purposes, as well as somatic variants with potential germline implications [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This includes not only variants routinely evaluated in clinical practice but also those in moderate-penetrance cancer genes not typically screened based on current guidelines, tumor type or family history [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. CGP may improve the identification of constitutional PVs in unselected cancer patients, particularly when no test on normal tissue is indicated based on available guidelines. It may also detect variants not usually associated with the tested tumor type (\"off-tumor\" or opportunistic findings). A large study from Memorial Sloan Kettering Cancer Center, involving 10,336 patients with available tumor DNA sequencing, identified 1,040 patients with potential PVs; 17.5% of these patients were confirmed to have constitutional PVs, and more than half would have not been detected based on the available guidelines [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRecently, ESMO proposed recommendations concerning follow-up germline evaluation of somatic variants, based on factors such as the type of gene, patient\u0026rsquo;s age and variant characteristics (i.e. variant allele frequency). The authors reported that only 3% of true germline pathogenic variants were absent from the filtered tumor-detected variants [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In our study, after genetic evaluation, we found two cases in which somatic variants were later confirmed as constitutional in the absence of ESMO-recommended characteristics (VAF lower than the established threshold and patient\u0026rsquo;s age).\u003c/p\u003e\u003cp\u003eMoreover, somatic testing may have limitations in identifying constitutional variants due to inherent technical issues. Lincoln et al. reported that approximately 8% of PVs were missed by tumor-only sequencing and 11% were identified only after a second primary cancer was diagnosed [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The Illumina TSO500 panel has limitations in CNV detection and can only identify variants located within \u0026plusmn;\u0026thinsp;2 base pairs of exon/intron junctions. Consequently, further analyses were performed when another somatic test identified potential CNVs or in cases with suspected personal or family history. This approach led to the identification of additional 18 PVs, many of which were \u003cem\u003eBRCA1/2\u003c/em\u003e exon deletions. This finding aligns with literature data reporting a high prevalence of CNVs in these genes (11\u0026ndash;13% in \u003cem\u003eBRCA1\u003c/em\u003e and 2\u0026ndash;3% in \u003cem\u003eBRCA2\u003c/em\u003e) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRegarding the strengths of this study, we highlight a high adherence rate to genetic testing compared with clinical practice. This high compliance was achieved through the involvement of trained healthcare professionals, particularly dedicated clinical geneticists and molecular care managers. However, lower compliance to genetic counselling was reported for some tumors, probably due to the metastatic setting and high mortality rate, to the fact that some of these patients were lost to follow up, or for lack of therapeutic implications of the genetic variant identified.\u003c/p\u003e"},{"header":"LIMITATIONS","content":"\u003cp\u003eThis study has several limitations. First, the major limitation concerns reproducibility, constrained by restricted access to extensive somatic NGS panels. This constraint arises from the limited availability and elevated costs of such technologies, which restrict their use to a select number of specialized centers.\u003c/p\u003e\u003cp\u003eFurthermore, to ensure correct data interpretation, dedicated resources, multidisciplinary meetings, and a well-defined workflow are essential. In particular, genetic counseling with constitutional sampling should be promptly arranged for patients suspected of carrying germline variants. This will ensure the establishment of appropriate surveillance pathways, risk reduction strategies, and identification of carriers among family members.\u003c/p\u003e\u003cp\u003eSecond, somatic panels analyzing only the tumor may have limitations in identifying germline PVs. As a result, additional analyses were performed for the first 2 years of program when other somatic tests suggested potential CNVs or when patients had a suggestive personal or family history. A new secondary analysis pipeline optimized for \u003cem\u003eBRCA1/2\u003c/em\u003e CNV detection was implemented in 2024, improving sensitivity for these alterations. However, this limitation could also be addressed by performing paired tumor-normal sequencing, which improves both in terms of compliance and technical limitations the detection rate [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThird, for confirmed carriers of variants associated with HCS, data on the uptake of available risk-reducing procedures, surveillance strategies, and cascade testing among relatives were not available. This gap limits the ability to perform a comprehensive cost-effectiveness analysis to inform healthcare policy and decision-making.\u003c/p\u003e\u003cp\u003eFinally, the cohort is unbalanced in terms of tumor types, with a predominance of gynecological cancers and tumors characterized by hypermutated or ultramutated phenotypes. This may have led to an overrepresentation of suspected PVs and could limit the generalizability of the findings.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003e Italian national guidelines currently control access to germline genetic testing, with clinical and familial criteria determining eligibility. These guidelines align with international recommendations, particularly for \u003cem\u003eBRCA1/2\u003c/em\u003e and Lynch syndrome-associated cancers but also consider specific aspects of the Italian healthcare system, such as the public reimbursement framework. Notably, recent publications [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] have emphasized the importance of extending genetic testing beyond traditional clinical indications, particularly in light of the increasing availability of somatic NGS-based testing in oncology. The growing availability of these assays offers the opportunity to simultaneously identify variants potentially of germline origin associated with HCS.\u003c/p\u003e\u003cp\u003eOur analysis represents a single-center study in one of the largest academic hospitals in Italy. We confirmed that approximately 10% of cancer patients have a HCS identifiable through somatic testing. In particular, through CGP, we identified a significant proportion of germline variants as opportunistic findings and a substantial number of PVs in moderate-penetrance genes in patients without a known family history of cancer. These probably would not have been identified through standard diagnostic pathways.\u003c/p\u003e\u003cp\u003eThis data reinforce the suggestion to establish integrated workflows for identifying potential germline variants in centers adopting CGP for enabling preventive strategies and facilitating cascade testing in at-risk families.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eCGP:\u0026nbsp;\u003c/strong\u003ecomprehensive genomic profiling\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVAF\u003c/strong\u003e: variant allele frequency\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSNVs\u003c/strong\u003e: single nucleotide variants\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eINDELS\u003c/strong\u003e: insertions/deletions\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHCS\u003c/strong\u003e: hereditary cancer predisposing syndromes\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePVs\u003c/strong\u003e: pathogenic/likely pathogenic variants\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTSO500\u003c/strong\u003e: TruSight Oncology 500\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCNA\u003c/strong\u003e: copy number alterations\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMMR\u003c/strong\u003e: mismatch repair\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMLPA\u003c/strong\u003e: Multiplex Ligation-dependent Probe Amplification\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eeCRFs\u003c/strong\u003e: electronic Case Report Forms\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMAP\u003c/strong\u003e: MUTYH-associated polyposis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMINAS\u003c/strong\u003e: Multilocus Inherited Neoplasia Allele Syndrome\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAdditional Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the support of AIRC under MFAG 2022 \u0026ndash; ID. 27367 - PI Lisa Salvatore; Ministero della Salute (Ricerca Corrente 2022), the AIRC (Investigator Grant number IG26330), Ministero dell\u0026rsquo;Università e della Ricerca (PRIN 2022 PNRR Prot P2022LN3KS and PRIN 2022 Prot 2022P79F9N), and Agenzia Italiana del Farmaco, Ministero della Salute (J38D19000690001 FIMP,and RF CO-2019-12369662) to Giampaolo Tortora.\u003c/p\u003e\n\u003cp\u003eWe thank Chiara Parrillo (Bioinformatics Research Core Facility), Giulia Pugliese (Data Collection Core Facility), and Gabriella Ciotti (Immunohistochemistry Core Facility), all part of the Gemelli Science and Technology Park (GSTeP), for their valuable support and technical assistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSD, AP, CN, MG, GS contributed to study design, data interpretation, literature search, and writing of the manuscript; TP, IM, IM, contributed to data curation; LG, SR, TP, DG contributed to data analysis and generation of figures; AM, GM contributed in genomic analysis; AP, \u0026nbsp; contributed in pathological analysis; EB, LS, MAC, RI, KP,RT, VI, AV, AP, AF, FF, ELC, GT contributed in revision of the manuscript. All authors read and approved the final paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study has been conducted following the Declaration of Helsinki and has received approval from the Fondazione Policlinico Universitario \u0026ldquo;A. Gemelli\u0026rdquo; IRCCS ethical committee. Prior to participation, all patients provided informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are not publicly available due to Ethical reasons, but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial \u0026amp; competing interests disclosure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was partially supported by the Italian Ministry of Health (Ricerca Corrente; no grant number provided).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eC.N. declares travel support from MSD, Illumina, Menarini, AZand honoraria from Veeva, GSK, MSD, AZ, Altems, Illumina and Guardant Health.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eF.F. reports research funding from Clovis, GSK, MSD and PharmaMar, personal and financial interests with GSK, MSD, SYSMEX, STRYKER ,G.S. reports research support from MSD and honoraria from Clovis Oncology, consultant for Tesaro and Johnson\u0026amp;Johnson.\u003c/p\u003e\n\u003cp\u003eLS reports consulting or advisory role for Pierre-Fabre, AstraZeneca, Bayer, SERVIER, Merck, Amgen, GSK, Incyte, Leopharma, MSD, Takeda.\u003c/p\u003e\n\u003cp\u003eMAC reports consulting or advisory role for Amgen, Bayer, Merck, Pierre-Fabre, SERVIER, Takeda\u003c/p\u003e\n\u003cp\u003eGT reports consulting or advisory role for BMS, AstraZeneca, MSD, Merck, and Servier.\u003c/p\u003e\n\u003cp\u003eAll other authors have declared no conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMosele F, Remon J, Mateo J, et al. Recommendations for the use of next-generation sequencing (NGS) for patients with metastatic cancers: a report from the ESMO Precision Medicine Working Group. Ann Oncol. 2020;31(11):1491-1505. doi:10.1016/j.annonc.2020.07.014\u003c/li\u003e\n\u003cli\u003eMosele MF, Westphalen CB, Stenzinger A, et al. Recommendations for the use of next-generation sequencing (NGS) for patients with advanced cancer in 2024: a report from the ESMO Precision Medicine Working Group. Ann Oncol. 2024;35(7):588-606. doi:10.1016/j.annonc.2024.04.005\u003c/li\u003e\n\u003cli\u003eNero C, Duranti S, Giacomini F, et al. Integrating a comprehensive cancer genome profiling into clinical practice: a blueprint in an Italian referral center. J Pers Med. 2022;12(10):1746. doi:10.3390/jpm12101746\u003c/li\u003e\n\u003cli\u003eKuzbari Z, Bandlamudi C, Loveday C, et al. Germline-focused analysis of tumour-detected variants in 49,264 cancer patients: ESMO Precision Medicine Working Group recommendations. Ann Oncol. 2023;34(3):215-227. doi:10.1016/j.annonc.2022.12.003\u003c/li\u003e\n\u003cli\u003eLindor NM, McMaster ML, Lindor CJ, Greene MH; National Cancer Institute, Division of Cancer Prevention, Community Oncology and Prevention Trials Research Group. Concise handbook of familial cancer susceptibility syndromes - second edition. J Natl Cancer Inst Monogr. 2008;(38):1-93. doi:10.1093/jncimonographs/lgn001\u003c/li\u003e\n\u003cli\u003eSamadder NJ, Riegert-Johnson D, Boardman L, et al. Comparison of Universal Genetic Testing vs Guideline-Directed Targeted Testing for Patients With Hereditary Cancer Syndrome. JAMA Oncol. 2021;7(2):230-237. doi:10.1001/jamaoncol.2020.6252\u003c/li\u003e\n\u003cli\u003eIdos GE, Kurian AW, Ricker C, et al. Multicenter Prospective Cohort Study of the Diagnostic Yield and Patient Experience of Multiplex Gene Panel Testing For Hereditary Cancer Risk. JCO Precis Oncol. 2019;3:PO.18.00217. Published 2019 Mar 28. doi:10.1200/PO.18.00217\u003c/li\u003e\n\u003cli\u003eOrsi G, Carconi C, Ghiorzo P, et al. Germline pathogenic variants of cancer predisposition genes in a multicentre Italian cohort of pancreatic cancer patients. Eur J Cancer. 2024;208:114226. doi:10.1016/j.ejca.2024.114226\u003c/li\u003e\n\u003cli\u003eYap TA, Ashok A, Stoll J, et al. Prevalence of Germline Findings Among Tumors From Cancer Types Lacking Hereditary Testing Guidelines. JAMA Netw Open. 2022;5(5):e2213070. Published 2022 May 2. doi:10.1001/jamanetworkopen.2022.13070\u003c/li\u003e\n\u003cli\u003eTung N, Dougherty KC, Gatof ES, et al. Potential pathogenic germline variant reporting from tumor comprehensive genomic profiling complements classic approaches to germline testing. NPJ Precis Oncol. 2023;7(1):76. Published 2023 Aug 11. doi:10.1038/s41698-023-00429-1\u003c/li\u003e\n\u003cli\u003eMandelker D, Zhang L, Kemel Y, et al. Mutation Detection in Patients With Advanced Cancer by Universal Sequencing of Cancer-Related Genes in Tumor and Normal DNA vs Guideline-Based Germline Testing. JAMA. 2017;318(9):825-835. doi:10.1001/jama.2017.11137\u003c/li\u003e\n\u003cli\u003eHuang KL, Mashl RJ, Wu Y, et al. Pathogenic Germline Variants in 10,389 Adult Cancers. Cell. 2018;173(2):355-370.e14. doi:10.1016/j.cell.2018.03.039\u003c/li\u003e\n\u003cli\u003eSutcliffe EG, Bartenbaker Thompson A, Stettner AR, et al. Multi-gene panel testing confirms phenotypic variability in MUTYH-Associated Polyposis. \u003cem\u003eFam Cancer\u003c/em\u003e. 2019;18(2):203-209. doi:10.1007/s10689-018-00116-2\u003c/li\u003e\n\u003cli\u003eTricarico R, Bet P, Ciambotti B, et al. Endometrial cancer and somatic G\u0026gt;T KRAS transversion in patients with constitutional MUTYH biallelic mutations. \u003cem\u003eCancer Lett\u003c/em\u003e. 2009;274(2):266-270. doi:10.1016/j.canlet.2008.09.022\u003c/li\u003e\n\u003cli\u003eMcGuigan A, Whitworth J, Andreou A, et al. Multilocus Inherited Neoplasia Allele Syndrome (MINAS): an update. Eur J Hum Genet. 2022;30(3):265-270. doi:10.1038/s41431-021-01013-6\u003c/li\u003e\n\u003cli\u003eLincoln SE, Nussbaum RL, Kurian AW, et al. Yield and Utility of Germline Testing Following Tumor Sequencing in Patients With Cancer. \u003cem\u003eJAMA Netw Open\u003c/em\u003e. 2020;3(10):e2019452. Published 2020 Oct 1. doi:10.1001/jamanetworkopen.2020.19452\u003c/li\u003e\n\u003cli\u003eTung N, Ricker C, Messersmith H, et al. Selection of germline genetic testing panels in patients with cancer: ASCO guideline. J Clin Oncol. 2024;42(21). doi:10.1200/JCO.24.00662\u003c/li\u003e\n\u003cli\u003eLaDuca H, Polley EC, Yussuf A, et al. A clinical guide to hereditary cancer panel testing: evaluation of gene-specific cancer associations and sensitivity of genetic testing criteria in a cohort of 165,000 high-risk patients. \u003cem\u003eGenet Med\u003c/em\u003e. 2020;22(2):407-415. doi:10.1038/s41436-019-0633-8\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"genome-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Genome Medicine](https://genomemedicine.biomedcentral.com/)","snPcode":"13073","submissionUrl":"https://submission.springernature.com/new-submission/13073/3","title":"Genome Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Comprehensive cancer genome profiling, Germline pathogenic variants, Hereditary cancer syndrome, Oncogenetics ","lastPublishedDoi":"10.21203/rs.3.rs-8088663/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8088663/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eComprehensive cancer genome profiling (CGP) is recommended for the identification of actionable somatic mutations in a selected subgroup of cancer patients. Some variants detected by CGP can be constitutional. The aim of this study is to evaluate the rate of potential and confirmed constitutional pathogenic/likely pathogenic variants (overall defined as PVs) identified through CGP according to the recommendations of the European Society of Medical Oncology\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods:\u003c/b\u003e\u003c/p\u003e\u003cp\u003e This is a prospective interventional trial enrolling solid cancer patients in whom molecular assessment was clinically indicated based on national guidelines, referring them for CGP. Patients with suspected constitutional variants were subsequently referred for germline testing. The present analysis focuses on the first two years of the program, from January 2022 to December 2023.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOf 2688 samples (2674 patients) with a CGP report, more than half were represented by female reproductive system cancers. 16% of the patients were addressed to genetic evaluation for 527 suspected constitutional PVs, with a compliance to genetic counselling of 80%. 331 patients underwent germline testing, of whom 73% harbored at least one PV, with 66% of tested variants confirmed to be germline. Interestingly, 16% of germline variants were secondary findings and 20% of the confirmed \u0026ldquo;on-tumor\u0026rdquo; germline PVs were in moderate-risk genes. Eighteen additional constitutional PVs were identified in 17 patients based on the results of other somatic tests or through additional tests requested following genetic counselling (0.6% of the entire cohort).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eConstitutional PVs were detected in about 10% of an unselected solid tumor cohort through CGP. A relevant fraction of the constitutional PVs were secondary findings or constitutional variants in moderate penetrance genes, that would not have been detected based on current guidelines. The integration of CGP with systematic genetic counseling provides a comprehensive approach that optimizes both therapeutic decision-making and hereditary cancer prevention.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTrial Registration:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eProtocol ID: FPG500, ID number: 3837, ClinicalTrials.gov Identifier: NCT06020625.\u003c/p\u003e","manuscriptTitle":"Germline pathogenic variants identification through Comprehensive Cancer Genome Profiling","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-08 10:59:15","doi":"10.21203/rs.3.rs-8088663/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-28T11:58:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-28T11:31:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-05T06:23:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-31T14:23:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-30T16:56:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"225651119987531476322238664516364999258","date":"2025-12-09T04:43:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"157545448920636339635804042967899882969","date":"2025-12-04T17:41:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"234167769669874323504814756866085217124","date":"2025-12-04T16:45:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"279214445329526204824797734379214119970","date":"2025-12-04T08:35:01+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-04T00:50:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-26T15:11:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-12T05:42:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"Genome Medicine","date":"2025-11-11T16:00:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"genome-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Genome Medicine](https://genomemedicine.biomedcentral.com/)","snPcode":"13073","submissionUrl":"https://submission.springernature.com/new-submission/13073/3","title":"Genome Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ba7e07d4-9de9-436d-bbaf-84aeb4759b7e","owner":[],"postedDate":"December 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-18T20:23:20+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-08 10:59:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8088663","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8088663","identity":"rs-8088663","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}