Whole Genome Analysis Identifies Homologous Recombination Deficiency in Cancers with BRCA1/2 Wild-Type and BRCA1/2 Structural Variants

Whole Genome Analysis Identifies Homologous Recombination Deficiency in Cancers with BRCA1/2 Wild-Type and BRCA1/2 Structural Variants | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Whole Genome Analysis Identifies Homologous Recombination Deficiency in Cancers with BRCA1/2 Wild-Type and BRCA1/2 Structural Variants Juan Miguel Mosquera, Majd Assaad, Kevin Hadi, Max Levine, Daniela Guevara, and 22 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4978638/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Jan, 2026 Read the published version in Communications Medicine → Version 1 posted You are reading this latest preprint version Abstract Purpose Homologous recombination deficiency (HRD) impacts cancer treatment strategies, particularly effective utilization of PARP inhibitors. However, the variability of different HRD assays has hampered the selection of oncology patients who may benefit from these therapies. Our study aims to use the whole genome landscape to better define HRD in a pan-cancer cohort. Methods We employed a novel whole genome sequencing (WGS) HRD classifier that includes genome-wide signatures associated with HRD to analyze 580 tumor/normal paired samples. The HRD phenotype was correlated with genomic variants in BRCA1/2 and other homologous recombination repair genes. The results were compared to other assays and, in a subset, with commercial HRD tests, correlating them with treatment responses. Results HRD phenotype was identified in various cancers including breast (21%), pancreaticobiliary (20%), gynecological (17%), prostate (9%), upper gastrointestinal (GI) (2%), and other cancers (1%). HRD cases were not confined to BRCA1/2 mutations; 24% of HRD cases were BRCA1/2 wild-type. A diverse range of gene alterations involved in HRD were elucidated, including biallelic mutations in FANCF, XRCC2 , and FANCC , and deleterious structural variants. In a subset of 15 cases, the WGS-based classifier offered more insights and a better correlation to treatment response when compared to other assays. Conclusion HRD is a biomarker used to determine which cancer patients would benefit from PARP inhibitors. However, a lack of harmonization of tests to determine HRD status makes it challenging to interpret their results. Our study highlights the use of comprehensive WGS analysis to better predict HRD and elucidates new genomic mechanisms associated with this phenotype. Biological sciences/Cancer/Cancer genomics Biological sciences/Cancer/Cancer therapy/Targeted therapies Figures Figure 1 Figure 2 Figure 3 Introduction BRCA1 and BRCA2 ( BRCA1/2 ) play a significant role in an error-free DNA damage repair pathway known as homologous recombination repair (HRR) 1 . This pathway corrects DNA double-strand breaks (DSBs) and interstrand cross-links 1 , 2 . Somatic or germline mutations in BRCA1/2 (BRCA mut ) lead to homologous recombination deficiency (HRD) and have long been associated with breast, ovarian, pancreatic, and prostate cancers 3 , 4 . Poly (ADP-ribose) polymerase inhibitors (PARPi) have been developed to treat cancers associated with mutations in BRCA1/2 and other HRR genes based on the synthetically lethal relationship with HRD 5 . Furthermore, the use of alkylating-like agents, especially platinum-based chemotherapy (PBCT), has shown increased effectiveness for cancers with HRD 6 , 7 . Loss of function in HRR genes, such as RAD51B, ATM, FANC genes, CHEK2, PALB2 , among others, can result from small mutations, structural variants, or epigenetic changes 8 – 10 . Therefore, evaluation of different deleterious mechanisms would require several assays and advanced analysis. Due to the broad range of HRR-inactivating genes, it is necessary to not only survey the full genetic landscape of HRR genes, but also detect DNA damage signatures associated with HRD for selective treatment with PARPi and PBCT 10 . HRD is associated with DNA damage signatures, including single base substitution (SBS), structural variant (SV) signatures, in addition to loss of heterozygosity (LOH), large scale transition (LST), and telomeric allelic imbalance (TAI) 11 – 13 . Assays that report HRD, such as MyChoice® CDx and FoundationOne CDx, among others, are based on targeted next-generation sequencing (NGS) and only employ a subset (LOH, LST, and TAI) of the available signals to detect HRD. Their use in PARPi treatment of ovarian cancer has been approved based on the results of multiple clinical trials 14 – 17 . It is worth noting that in some trials several patients with BRCAness (HRD phenotype) have experienced shorter survival under first-line maintenance PARPi and numerous cases lacking BRCAness have shown extended survival (16, 20). In contrast to the current commercially available companion diagnostics (CDx) for HRD testing, algorithms using whole genome sequencing (WGS) such as HRDetect and CHORD, employ all mutation classes. However, these have yet to be tested in clinical settings. The clinical and research assays have shown a variable association between BRCAness and the presence of HRR genes mutations 3 , 18 , 19 . This variability indicates that not every deleterious mutation in these genes results in BRCAness. Conversely, BRCAness can also be associated with BRCA1/2 wild type ( BRCA wt) and variants of unknown significance (VUS) 18 . This highlights the necessity of focusing on the BRCAness phenotype rather than solely relying on the known pathogenicity of mutations. WGS offers a comprehensive assessment of the genome, covering simple and complex SVs, copy number alterations (CNA), and mutational patterns associated with HRD 20 , 21 . It achieves superior precision and sensitivity in identifying BRCAness. Consequently, WGS-based HRD biomarkers may more effectively stratify cancer patients for therapeutic interventions 22 . In this study, we analyzed WGS data from pan-cancer samples and investigated the prevalence and characteristics of HRD employing a novel WGS-based classifier. We compared our HRD results with scores from other WGS-based algorithms and, in a subset, with commercial HRD tests, correlating them with treatment responses. Methods I. Patient enrollment, tissue samples and clinical data acquisition Participants were prospectively enrolled at Weill Cornell Medicine in the Institutional Review Board (IRB)-approved protocols WCM IRB #1305013903 and #1007011157. Tumor DNA for WGS was extracted from frozen tumor samples, formalin-fixed, paraffin-embedded (FFPE) archival tissue, or fluid from malignant ascites. Histopathology review was performed before DNA extraction. Germline DNA was primarily extracted from blood. When unavailable, saliva or benign tissue (frozen or FFPE) was used. We collected comprehensive clinical data, which encompassed age, sex, ethnicity, treatment-related information, radiologic findings, and pathologic data. II. DNA Extraction and WGS: For DNA extraction from FFPE blocks, we used 5-micrometer-thick unstained slides macro-dissected for at least 80% tumor content. For DNA extraction from frozen specimens, we employed 3mm core punches from the frozen OCT-embedded tissue. The Maxwell® 16 FFPE Plus DNA kit (Promega, Cat# AS1135) was employed, in combination with the Maxwell® 16 instrument (Promega, Madison, WI). DNA quality and quantity was assessed by using the Agilent Tapestation 4200 (Agilent Technologies) and the Qubit Fluorometer (ThermoFisher), respectively. Whole genome sequencing (WGS) was carried out at the New York Genome Center on an Illumina Novaseq6000 sequencer using 2x150 bp cycles. Libraries were generated using the KAPA Hyper Library Preparation Kit (KAPABiosystems KK8502, KK8504), targeting 500 bp fragments, in compliance with the manufacturer's instructions. DNA fragments underwent a series of preparation steps including shearing, end-repair, adenylation, and ligation to Illumina sequencing adapters. The prepared DNA fragments were size-selected using bead-based methods and amplified 23 . Quality and quantity of the final libraries were assessed prior to sequencing. III. WGS data processing pipeline and HRD curation We employed Isabl GxT analytics 24 , a comprehensive data management, processing, and visualization platform, to analyze cancer whole genome and transcriptome sequencing data. This platform was used to process all WGS and RNA sequencing data and generate comprehensive reports 25 , 26 . Within the Isabl pipeline deployed in Amazon Web Services (AWS) cloud high performance computing (HPC) environments, DNA and RNA alignment with Burrows-Wheeler Aligner (BWAMem) and Spliced Transcripts Alignment to a Reference (STAR), quality control, somatic and germline variant calling, and annotation were performed as previously described 25 , 27 – 30 . Briefly, ensemble calling was done for both somatic and germline single nucleotide variants (SNV), insertions deletions (InDels), and somatic SVs. These variant classes were then annotated and those in which at least 2 of 3 callers of each class were included for reporting. Purity, ploidy, and genome-wide copy number states were estimated with Battenberg, followed by annotation of CNA events at the gene level. Driver alterations for all variant classes and their potential treatment targets were assessed by cross-referencing protein-coding variants with Catalogue Of Somatic Mutations In Cancer (COSMIC) 31 and Oncology Knowledge Base (OncoKB) 32 . WGS-HRD scores were assigned with Isabl HRD 33 , a random forest classifier trained on a subset of the data to detect HRD by incorporating evidence from genome-wide SNV, indels, SV, and copy number variant (CNV) signals ( Figure S1 ). A subset of the whole cohort was used as the training cohort consisting of 381 matched tumor/normal (T/N) WGS pairs from 321 patients, representing 62 tumor types. All WGS samples were sequenced to a median Tumor/Normal sequencing depth of 92X/48X. The training cohort consisted of 195 fresh frozen and 98 FFPE tumors. SNV, InDels, SV, and allele-specific copy number alteration (aCNA) events were detected across all samples using ensemble pipelines for filtering and annotation 25 . Patients with high-confidence HRD (hcHRD, N = 37) were determined through analysis of genome-wide mutation patterns, and selecting cases that were top quartile outliers for each feature associated with HRD (COSMIC SBS 3, deletions with microhomology, and small SV duplications and deletions). Further visual curation of cases that harbored at least two outlier signatures was performed to select patients with hcHRD. A random forest classifier (Isabl HRD) was then trained using the 37 hcHRD and 268 HRR proficient (HRP) patients from the training cohort with > 20% tumor purity. The following WGS features were used to train the classifier: 96 trinucleotide SNV contexts, 45 InDel types, 38 SV types, and LST, LOH, and TAI scores. Classifier performance to predict bi-allelic BRCA1/2 status was evaluated on a validation cohort of 556 breast, ovarian, prostate, and pancreas cases with mutation calls obtained from the International Cancer Genome Consortium using the area under receiver operating characteristic (AUROC = 0.99) and precision-recall (AUPRC = 0.96) curves. We applied the classifier on our entire cohort, which assigned a probability of presence of the HRD phenotype. The resulting score ranged from 0 to 1, with a score equal to or greater than 0.5 indicating HRD (≥ 0.5) and a score less than 0.5 labeled HRP ( 20% is required to accurately assess HRD. IV. Fluorescence in situ Hybridization Four-µm-thick formalin-fixed paraffin-embedded tissue sections were used for fluorescence in situ hybridization (FISH) analysis, as described in our protocols 34 – 36 . Bacterial artificial chromosomes were designed against loci of interest to prepare break-part dual-color FISH probes 37 . For BRCA2 RP11-110O22 BAC clone was labeled red and RP11-11K16 clone was labeled green, and for ATM RP11- 144G7 BAC clone was labeled red and RP11-589O5 clone was labeled green. All clones were validated on normal metaphase spreads before any application on FFPE tissue. A positive break-apart was determined by one red, one green, and one yellow signal (combination of red and green signal indicating the normal chromosome homologue). At least 200 nuclei were analyzed per case using a fluorescent microscope (Olympus BX51; Olympus Optical). Cytovision 7.3.1 software was used for imaging and analysis. Results Sample Characteristics and Frequency of HRD We performed WGS analysis on 580 tumor samples and the matching germline samples from 453 patients. Figure 1 summarizes the types of tumor samples (FFPE, frozen, or fluid) and type of lesion (primary and metastatic). These encompass 77 unique histology types ( Figure S2 ), classified according to the MSKCC Oncotree 38 , and obtained from 33 unique primary sites. Sites were divided into six cancer subgroups: prostate (29%), gynecological (20%), pancreaticobiliary (15%), breast (11%), upper gastrointestinal (GI) (10%), and “others” (12%), which included smaller cancer cohorts and rare tumors (Fig. 1, Figure S2 , Supplementary Data 1 ). HRD analysis was conducted on 521 of the 580 tumor samples, with 59 cases excluded due to low purity (< 20%). The median purity was 71.5%, and the median coverage was 90x. Sixty-two samples across 53 patients exhibited HRD by WGS. The highest percentage of HRD cases was found in breast cancer (21%), followed by pancreaticobiliary (20%), gynecological (17%), and prostate cancers (9%). Upper GI cancers had the lowest percentage of HRD, with only one case harboring this phenotype. Additionally, one case of carcinoma of unknown primary in the "others" cohort demonstrated HRD. Mutational landscape of HRD While BRCAness is most commonly explained and clinically tested by alterations in BRCA1/2 , dysfunction in other HRR pathway genes can also result in phenocopy. We investigated events in BRCA1, BRCA2 , and other HRR pathway genes in HRD phenotype cases, accounting for loss of heterozygosity and compound hits that could result in biallelic loss of function and focusing on SVs and somatic mutations with unknown effects on HRD (Fig. 2). Out of 62 HRD samples across 53 patients, 76% (47) harbored alterations in BRCA1 and/or BRCA2 ( BRCA1/2mut ). In 55% (34) of samples, BRCA1/2mut had biallelic pathogenic small mutations (SNVs and InDels) and 6% (4) had homozygous deletions. Another 3% (2) harbored SVs with LOH in BRCA1/2 with predicted impact on coding sequence. Interestingly, none of those two samples with BRCA1/2 biallelic SVs had deleterious mutations in other HRR pathway-related genes (Fig. 2). In addition, 11% (7) harbored BRCA1/2 small mutation VUS or SV VUS. An example of BRCA1/2 SV is a case of advanced prostatic carcinoma with neuroendocrine histology where WGS revealed BRCA2::TMPRSS2 fusion and HRD. BRCA2 rearrangement was validated with FISH break-apart assay (Fig. 3. a ). Ultimately, the remaining 15 HRD cases (24%) were BRCAwt (Fig. 2). For those samples with BRCA wt we investigated other gene mutations that might have caused the HRD phenotype, and we found that one prostate cancer had a pathogenic small mutation in FANCF (p.W193*), another prostate cancer had biallelic FANCC deletion, and one endometrial carcinoma had biallelic XRCC2 deletion. The remaining BRCA wt HRD cases (n = 12) either had no mutations in any of the known HRR genes (n = 5; 33% of the BRCA wt HRD cases) or had a VUS small mutation or SV in one or multiple HRR pathway genes including RAD51B, PALB2, ATM, CHEK2, FANCD2 and RAD51 (n = 7; 47% of the BRCA wt HRD cases, Supplementary Fig. 2 ). Examples of these cases include one sample of high-grade serous carcinoma of the ovary (HGSOC) with a HIF1A::UIMC1 fusion involving intron 13 of UIMC1 with LOH. UIMC1 encodes a nuclear protein that functions with BRCA1 in recognizing and repairing DNA lesions. The fusion was validated by RNA sequencing (Fig. 3. b ). Another case involved a high-grade serous carcinoma of the fallopian tube (HGSFC) with a biallelic VUS ATM mutation (p.P2842S). In both cases, MyChoice CDx predicted HRD. The first case showed a response to PBCT (RECIST 1.1, Supplementary Data 1 ), and the second case had 20 months of PFS on PARPi without progression at the time of writing this manuscript. Features frequently enriched in the HRD cohort consisted of genome wide small microhomology deletions (MH-dels), COSMIC signatures (V3) SBS3 or SBS40, SV deletions from 1-10kb, and SV duplications from 1-10kb (Fig. 2). SV duplications were largely enriched in BRCA1 mutated tumors. While MH-dels were the most frequently enriched feature among HRD samples, 3 BRCA wt, RAD51B mutated samples harbored intermediate MH-dels with enrichment of SV deletions or duplications and SBS3/40 indicating a potentially distinct HRD feature profile. HRP cases with BRCA1/2mut In the HRP tumor cohort, 12.4% (57 of 459) samples had at least one mutated BRCA1/2 allele. Among these, 10% (5 of 57) had biallelic pathogenic mutations and 23% (13 of 57) had monoallelic pathogenic mutations. The remaining monoallelic and biallelic mutations were VUS small mutations or SV with germline pathogenic mutations. For the 5 samples with biallelic pathogenic BRCA1/2 mutations and HRP, one was from a patient with mixed ovarian carcinoma with a POLE pathogenic mutation (c.857C > G, p.P286R) that led to a hypermutator state with a TMB of 897.9/mb and no HRD signatures. This suggests the possibility of the BRCA2 mutation being a result of the hypermutator phenotype. The other 4 samples were from a prostate adenocarcinoma patient where no HRD signatures were found in any of the samples. HRD concordance in cases with multiple samples Our cohort included 54 patients with two or more samples, totaling 169 samples. Among these patients, 85% (46 of 54) did not have any samples with HRD, and 13% (7 of 54) had all their samples consistently showing HRD. Only 1 of 54 (2%) had a discrepant HRD status between samples. The patient had histologically and molecularly different synchronous ovarian and endometrial serous carcinomas. The sample from the brain metastatic lesion originated from the endometrial cancer, which displayed HRD associated with BRCA1, RAD51B , and RAD54B deleterious rearrangements. This sample also had drivers including TP53 (p.G244R), RB1 (p.R579fs29), and SMARCA2 (p.A7fs15), among others. In contrast, the ovarian cancer sample displayed only a FANCM rearrangement, with wild-type BRCA1, RAD51B , and RAD54B . The drivers for this sample included TP53 (p.G244R) and RRAS2 (p.G23V), with wild-type RB1 and SMARCA2 . Comparison of Isabl WGS HRD with other assays Current commercial tests for HRD employ only GIS or LOH scores based on allele-specific copy number segmentation, a subset of genome-wide features predictive of HRD and captured by WGS. To explore the potential clinical significance of WGS-based HRD testing, we retrospectively assessed cases with WGS, commercial HRD scores, and clinical history that included treatment response. From the 39 serous carcinoma cases in the gynecological cancer cohort, where an HRD score can inform treatment decisions, we identified 15 cases that had undergone a commercial assay that included an HRD score. This group comprised 9 cases evaluated with MyChoice CDx GIS and 6 cases with FoundationOne HRD score. The results of both commercial assays and WGS testing are summarized in Table 1 . Of these cases, 3 out of 5 identified as HRD-positive by WGS were deemed HRP by commercial assays; these included 1 case tested by FoundationOne (negative) and 2 cases by MyChoice CDx, one negative and the other inconclusive for HRD. All 3 cases had confident HRD phenotype features, including enrichment for MH-dels, SV deletions, or duplications. Two of the 3 patients were maintained on PARPi after showing a response to PBCT (RECIST 1.1) and experienced prolonged periods of non-progression, lasting 10 months and 5 years, respectively. The third patient did not receive PARPi. Table 1 Comparison of WGS HRD with commercially available assays. HRD, Homologous Recombination Deficiency; HRP, Homologous Recombination Proficiency; PARPi, PARP inhibitor; PFS, Progression Free Survival. WCMID Isabl Commercial Assay Result Clinical response to Maintenance PARPi WCM231 HRD FoundationOne HRP Progression 10 months after maintenance thearpy (PFS = 10months) WCM209 HRD MyChoice CDx HRD No available PARPi response data WCM414 HRD MyChoice CDx HRD No disease recurrence to date (PFS = 20 months) WCM205 HRD MyChoice CDx HRP Did not receive PARPi WCM228 HRD MyChoice CDx Inconclusive No disease recurrence to date (PFS = 60 months) WCM425 HRP FoundationOne CDx HRD Progression 2 months after maintenance thearpy (PFS = 2 months) WCM295 HRP MyChoice CDx HRP Did not receive PARPi WCM436 HRP FoundationOne CDx HRD Did not receive PARPi WCM236 HRP FoundationOne CDx HRD Progression 3 months after maintenance thearpy (PFS = 3 months) WCM435 HRP MyChoice CDx HRP Did not receive PARPi WCM442 HRP FoundationOne CDx HRP Did not receive PARPi WCM272 HRP FoundationOne CDx Inconclusive Progression 3 months after maintenance thearpy (PFS = 3 months) WCM284 HRP MyChoice CDx HRP Did not receive PARPi WCM331 HRP MyChoice CDx HRP Did not receive PARPi WCM419 HRP MyChoice CDx HRP Did not receive PARPi Among cases determined as HRP by WGS (N = 10), 1 was found to be inconclusive and 3 were found to be positive according to FoundationOne. All 4 cases had an enrichment in MH-dels, SV deletions, duplications, and SBS3/40. Our assessment using RECIST 1.1 ( Supplementary Data 2 ) confirmed disease progression on PARPi after 3 months for the case deemed inconclusive by FoundationOne, and after 2 and 3 months, respectively, for 2 of the 3 cases with HRD by FoundationOne but HRP by WGS. The third case was not treated with PARPi. We also investigated HRD positivity using two other HRD algorithms, CHORD and HRDetect (Fig. 2. a ) 3 , 19 . Overall, 15% (9 of 62) of our WGS HRD samples were negative by CHORD, which included 3 cases that are simultaneously negative by HRDetect. Interestingly, 2 of those cases were BRCA wt with RAD51 structural variants, and one with BRCA2 monoallelic VUS somatic small mutation and BRCA1 biallelic pathogenic somatic small mutation. Discussion The significance of HRD in precision oncology has grown because of the development of PARPi and the correlation with response to PBCT in solid tumors 20 , 39 – 42 . Targeted NGS panels are limited in detecting the full range of BRCA1/2 mutational events and mainly focus on exonic regions 43 – 45 . Targeted panels may also overlook alterations in other genes of the HRR pathway that may cause HRD 43 – 45 . Consequently, recent research has focused on scoring the genomic signatures of the disruption in the HRR pathway like LOH, TAI, LST, SBS3, small deletions, and tandem duplications 1 , 21 , 45 . However, these HRD 'footprints' are not fully revealed by common targeted panels and exome sequencing 1 , 46 . To address these limitations, we employed a WGS approach to better determine the HRD status in a pan-cancer cohort. Epithelial carcinomas of the ovary and fallopian tube are the only cancer types approved for PARPi treatment based on clinical HRD signature testing, according to the most recent NCCN guidelines 47 . In our cohort, we compared WGS HRD phenotype testing results to MyChoice CDx and FoundationOne CDx when available. We identified several discrepant cases: patients with HRD on WGS but HRP by clinical panels showed treatment response to PARPi and/or PBCT, whereas those patients with HRP tumors by our WGS classifier but HRD on other panels exhibited treatment resistance to PARPi or PBCT. While preliminary and limited by the number of cases, our study provides evidence that WGS would improve prediction of HRD with subsequent treatment response, beyond current FDA approved CDx for HRD. As reported in other studies, a WGS classifier of HRD might reduce false negatives and increase the inclusion of appropriate patients in relevant clinical trials 48 . In an effort to assess concordance across commercial and research tests that employ GIS or LOH scores, recent analysis of 13 GIS-based assays revealed challenges in unifying a definition of HRD and reported a wide range of percent positive HRD cases (> 50% differences) in the cohorts studied 49 . More fundamentally, comparative studies that continue to be designed around performance metrics other than treatment or other clinical response limit objective assessment of the use of such assays. PARPi are progressively becoming a part of the therapeutic arsenal against tumors with HRD. However, treatment of non-ovarian cancers with PARPi depends on specific conditions, according to NCCN guidelines. These include the presence of a pathogenic BRCA1/2 mutation for breast and pancreatic cancers, or the presence of pathogenic mutations in BRCA1/2 and/or other HRR genes in prostate cancer 47 . Our results reveal that the HRD phenotype was not only identified across a variety of cancer types, but also associated with pathogenic variants, VUS, and wild-type status of BRCA1/2 or other HRR genes. Our study further expands the spectrum of molecular events that cause HRD and includes biallelic structural variants in BRCA1/2 and other HRR pathway genes. Our results in this area confirm the data reported by Ewing et al. , on BRCA1/2 SVs in ovarian serous carcinomas, prostatic carcinoma, and breast carcinoma and expand our knowledge of SVs impacting other HRR genes like RAD51B, FANCC , and CHEK2 among others 50 . We also report that cases with structural or small mutation VUS in BRCA1/2 or other HRR genes were the most probable drivers in cases with HRD phenotype, not coinciding with other known pathogenic mutations in the HRR pathway. This suggests that those VUS are possibly related to HRD and might be considered pathogenic, supporting a previous study that reported a correlation between BRCA1/2 VUS and the HRD phenotype 51 . We also interrogated those BRCA wt cases with HRD phenotype. These patients, identified as having HRD tumors through clinically approved testing assays like MyChoice CDx and Foundation CDx, as well as other WGS-based assays, have been reported in the literature to constitute approximately 20–30% of cases 20 , 52 , 53 . This range aligns with the data observed in our study. Based on WGS, some of our patients had biallelic mutations in other HRD genes, like PALB2 and RAD51B , known to be associated with HRD. In other cases, we identified variants in genes reported to be linked to HRR pathway dysfunction without previously known clinical impact. One example is a case with a UIMC1 fusion in which the deletion of the AIR domain, essential for binding to the BRCA1-A complex, could have caused HRD 54 . In some BRCA wt HRD cases, the genomic cause could not be uncovered by WGS, which may be due to epigenetic changes like BRCA1/2 promoter methylation 55 – 57 . One of the main conclusions of our study is that, compared to commercial assays, WGS-based HRD assessment could clarify inconclusive or misleading results from NGS-based assays that rely on fewer signatures. On a routine basis, we discuss such cases during a research molecular tumor board (MTB) format, a Continuing Medical Education (CME) accredited conference 27 , 58 – 62 . Examples include 2 patients (detailed above), both of which showed a WGS HRD phenotype but were HRP and inconclusive by MyChoice CDx respectively. For the first patient, following a recent disease recurrence of HGSOC, the consensus was to consider PARPi as a valid treatment option, especially in light of a previous response to PBCT. For the second patient, who had HGSOC with a WGS-determined HRD phenotype, the commercial HRD assay results were inconclusive. However, WGS identified a biallelic structural variant in RAD51B as the likely cause of the HRD phenotype, rather than the monoallelic BRCA2 VUS found through clinical targeted sequencing. The consensus was to continue the patient on maintenance PARPi treatment started earlier, and to which the patient was responding. In summary, we illustrate how a WGS HRD classifier could be universally applicable in precision oncology, unearthing the HRD phenotype that may be invisible by other methods. Future functional studies will help elucidate the role of structural variants in causing HRD. We acknowledge that larger clinical response data is required to definitively assess accuracy of HRD predictions against treatment response. This study provides major impetus to evaluate WGS as a potential clinical diagnostic tool to target PARPi and PBCT responses and paves the way for both clinical validity studies and drug trial designs that include WGS methodology in their endpoints. Declarations Acknowledgements This work was supported by the Englander Institute for Precision Medicine. Whole-genome sequencing was performed at the New York Genome Center, supported by an agreement with Illumina, Inc., and Weill Cornell Medicine. Project support for this research was also provided in part by the Center for Translational Pathology from the Department of Pathology and Laboratory Medicine at Weill Cornell Medicine. The authors thank Ahmed G Elsaeed for project support with data extraction. Ethics approval and informed consent The use of the clinical data and samples for this study was approved by Weill Cornell Medicine institutional review board (IRB) protocols # 1305013903 (Research for Precision Medicine) and # 1007011157 (Comprehensive Cancer Characterization by Genomic and Transcriptomic Profiling). Author contributions M.A., K.H. and JM.M. performed study concept and design, and wrote the manuscript. JM.M, M.A., M.S., and J.M. generated the patient cohort. K.H.performed statistical analysis and interpretation of data. K.H., M.L., G.G., J.S.M, and E.P. performed genomic analyses. JM.M and M.A. performed the histopathological assessment. A.S. performed the FISH experiments. M.A, A.S., and K.H. prepared the figures. All authors read and approved the final paper. Funding statement The authors received no specific funding for this work. Data availability The analyzed molecular data is available in the supplementary documents. Raw data are available upon reasonable request from the corresponding authors. Competing interests Kevin Hadi, Max F. Levine, Gunes Gundem, Juan S. Medina-Martinez, and Elli Papaemmanuil are Isabl, Inc. employees. References Stewart MD, Merino Vega D, Arend RC, et al: Homologous Recombination Deficiency: Concepts, Definitions, and Assays. Oncologist 27:167–174, 2022 Miller RE, Leary A, Scott CL, et al: ESMO recommendations on predictive biomarker testing for homologous recombination deficiency and PARP inhibitor benefit in ovarian cancer. Ann Oncol 31:1606–1622, 2020 Nguyen L, J WMM, Van Hoeck A, et al: Pan-cancer landscape of homologous recombination deficiency. Nat Commun 11:5584, 2020 Vollebergh MA, Lips EH, Nederlof PM, et al: Genomic patterns resembling BRCA1- and BRCA2-mutated breast cancers predict benefit of intensified carboplatin-based chemotherapy. Breast Cancer Res 16:R47, 2014 DrÊan A, Lord CJ, Ashworth A: PARP inhibitor combination therapy. Crit Rev Oncol Hematol 108:73–85, 2016 Chai Y, Chen Y, Zhang D, et al: Homologous Recombination Deficiency (HRD) and BRCA 1/2 Gene Mutation for Predicting the Effect of Platinum-Based Neoadjuvant Chemotherapy of Early-Stage Triple-Negative Breast Cancer (TNBC): A Systematic Review and Meta-Analysis. J Pers Med 12, 2022 Pokataev I, Fedyanin M, Polyanskaya E, et al: Efficacy of platinum-based chemotherapy and prognosis of patients with pancreatic cancer with homologous recombination deficiency: comparative analysis of published clinical studies. ESMO Open 5:e000578, 2020 Moschetta M, George A, Kaye SB, et al: BRCA somatic mutations and epigenetic BRCA modifications in serous ovarian cancer. Ann Oncol 27:1449–55, 2016 Varol U, Kucukzeybek Y, Alacacioglu A, et al: BRCA genes: BRCA 1 and BRCA 2. J buon 23:862–866, 2018 Seol JH, Shim EY, Lee SE: Microhomology-mediated end joining: Good, bad and ugly. Mutat Res 809:81–87, 2018 PÃŗti Ã, GyergyÃĄk H, NÊmeth E, et al: Correlation of homologous recombination deficiency induced mutational signatures with sensitivity to PARP inhibitors and cytotoxic agents. Genome Biol 20:240, 2019 Coleman RL, Oza AM, Lorusso D, et al: Rucaparib maintenance treatment for recurrent ovarian carcinoma after response to platinum therapy (ARIEL3): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet 390:1949–1961, 2017 Setton J, Reis-Filho JS, Powell SN: Homologous recombination deficiency: how genomic signatures are generated. Curr Opin Genet Dev 66:93–100, 2021 Akinjiyan FA, Morecroft R, Phillipps J, et al: Homologous Recombination Deficiency (HRD) in Cutaneous Oncology. Int J Mol Sci 24, 2023 Milbury CA, Creeden J, Yip WK, et al: Clinical and analytical validation of FoundationOneÂŽCDx, a comprehensive genomic profiling assay for solid tumors. PLoS One 17:e0264138, 2022 Ray-Coquard I, Pautier P, Pignata S, et al: Olaparib plus Bevacizumab as First-Line Maintenance in Ovarian Cancer. N Engl J Med 381:2416–2428, 2019 Coleman RL, Fleming GF, Brady MF, et al: Veliparib with First-Line Chemotherapy and as Maintenance Therapy in Ovarian Cancer. New England Journal of Medicine 381:2403–2415, 2019 Hodgson D, Lai Z, Dearden S, et al: Analysis of mutation status and homologous recombination deficiency in tumors of patients with germline BRCA1 or BRCA2 mutations and metastatic breast cancer: OlympiAD. Ann Oncol 32:1582–1589, 2021 Davies H, Glodzik D, Morganella S, et al: HRDetect is a predictor of BRCA1 and BRCA2 deficiency based on mutational signatures. Nat Med 23:517–525, 2017 Ter Brugge P, Moser SC, Bièche I, et al: Homologous recombination deficiency derived from whole-genome sequencing predicts platinum response in triple-negative breast cancers. Nat Commun 14:1958, 2023 de Luca XM, Newell F, Kazakoff SH, et al: Using whole-genome sequencing data to derive the homologous recombination deficiency scores. NPJ Breast Cancer 6:33, 2020 Lord CJ, Ashworth A: PARP inhibitors: Synthetic lethality in the clinic. Science 355:1152–1158, 2017 Bruinsma S, Burgess J, Schlingman D, et al: Bead-linked transposomes enable a normalization-free workflow for NGS library preparation. BMC Genomics 19:722, 2018 Nauseef JT, Elsaeed A, Al Assaad M, et al: Use of a navigable interface for integrated whole genome and transcriptome sequencing as a platform for pursuit of therapeutic targets in advanced prostate cancers. Journal of Clinical Oncology 41:225–225, 2023 Shukla N, Levine MF, Gundem G, et al: Feasibility of whole genome and transcriptome profiling in pediatric and young adult cancers. Nat Commun 13:2485, 2022 Medina-Martínez JS, Arango-Ossa JE, Levine MF, et al: Isabl Platform, a digital biobank for processing multimodal patient data. BMC Bioinformatics 21:549, 2020 Al Assaad M, Gundem G, Liechty B, et al: The importance of escalating molecular diagnostics in patients with low-grade pediatric brain cancer. Cold Spring Harb Mol Case Stud 9, 2023 Assaad MA, Kuo H-H, Nauseef J, et al: Abstract 3437: Whole genome and transcriptome sequencing of a pan cancer cohort unearths novel therapeutic avenues. Cancer Research 83:3437–3437, 2023 Hissong E, Al Assaad M, Bal M, et al: NIPBL::NACC1 Fusion Hepatic Carcinoma. The American Journal of Surgical Pathology 48, 2024 Mendelson NL, Al Assaad M, Hadi K, et al: Whole-genome Analysis Elucidates Complex Genomic Events in GLI1-rearranged Enteric Tumor. The American Journal of Surgical Pathology 47, 2023 Tate JG, Bamford S, Jubb HC, et al: COSMIC: the Catalogue Of Somatic Mutations In Cancer. Nucleic Acids Res 47:D941-d947, 2019 Chakravarty D, Gao J, Phillips SM, et al: OncoKB: A Precision Oncology Knowledge Base. JCO Precis Oncol 2017, 2017 Hadi K, Gundem G, Levine M, et al: Abstract 2149: A whole genome sequencing classifier of homologous recombination deficiency. Cancer Research 83:2149–2149, 2023 Al Assaad M, Michaud O, Semaan A, et al: Whole-Genome Sequencing Analysis of Male Breast Cancer Unveils Novel Structural Events and Potential Therapeutic Targets. Mod Pathol 37:100452, 2024 Hissong E, Al Assaad M, Bal M, et al: NIPBL::NACC1 Fusion Hepatic Carcinoma. Am J Surg Pathol 48:183–193, 2024 Mendelson NL, Al Assaad M, Hadi K, et al: Whole-genome Analysis Elucidates Complex Genomic Events in GLI1 -rearranged Enteric Tumor. Am J Surg Pathol 47:1192–1193, 2023 Genomics B: Kundra R, Zhang H, Sheridan R, et al: OncoTree: A Cancer Classification System for Precision Oncology. JCO Clin Cancer Inform 5:221–230, 2021 D'Andrea AD: Mechanisms of PARP inhibitor sensitivity and resistance. DNA Repair (Amst) 71:172–176, 2018 Feng Z, Shao D, Cai Y, et al: Homologous recombination deficiency status predicts response to platinum-based chemotherapy in Chinese patients with high-grade serous ovarian carcinoma. J Ovarian Res 16:53, 2023 O'Malley DM, Krivak TC, Kabil N, et al: PARP Inhibitors in Ovarian Cancer: A Review. Target Oncol 18:471–503, 2023 Tsang ES, Csizmok V, Williamson LM, et al: Homologous recombination deficiency signatures in gastrointestinal and thoracic cancers correlate with platinum therapy duration. NPJ Precis Oncol 7:31, 2023 Fountzilas E, Papadopoulou K, Chatzikonstantinou T, et al: Concordance between Three Homologous Recombination Deficiency (HRD) Assays in Patients with High-Grade Epithelial Ovarian Cancer. Cancers (Basel) 15, 2023 Sztupinszki Z, Diossy M, Krzystanek M, et al: Detection of Molecular Signatures of Homologous Recombination Deficiency in Prostate Cancer with or without BRCA1/2 Mutations. Clin Cancer Res 26:2673–2680, 2020 Doig KD, Fellowes AP, Fox SB: Homologous Recombination Repair Deficiency: An Overview for Pathologists. Mod Pathol 36:100049, 2023 Vogel A, Haupts A, Kloth M, et al: A novel targeted NGS panel identifies numerous homologous recombination deficiency (HRD)-associated gene mutations in addition to known BRCA mutations. Diagn Pathol 19:9, 2024 Network NCC: NCCN Guidelines, 2024 Lheureux S, Lai Z, Dougherty BA, et al: Long-Term Responders on Olaparib Maintenance in High-Grade Serous Ovarian Cancer: Clinical and Molecular Characterization. Clin Cancer Res 23:4086–4094, 2017 , Friends of Cancer Research, 2022 Ewing A, Meynert A, Churchman M, et al: Structural Variants at the BRCA1/2 Loci are a Common Source of Homologous Repair Deficiency in High-grade Serous Ovarian Carcinoma. Clin Cancer Res 27:3201–3214, 2021 Bouwman P, van der Heijden I, van der Gulden H, et al: Functional Categorization of BRCA1 Variants of Uncertain Clinical Significance in Homologous Recombination Repair Complementation Assays. Clin Cancer Res 26:4559–4568, 2020 Matsumoto K, Nishimura M, Onoe T, et al: PARP inhibitors for BRCA wild type ovarian cancer; gene alterations, homologous recombination deficiency and combination therapy. Jpn J Clin Oncol 49:703–707, 2019 Gruber JJ, Afghahi A, Timms K, et al: A phase II study of talazoparib monotherapy in patients with wild-type BRCA1 and BRCA2 with a mutation in other homologous recombination genes. Nat Cancer 3:1181–1191, 2022 . National Library of Medicine, 2024 Chiang JW, Karlan BY, Cass L, et al: BRCA1 promoter methylation predicts adverse ovarian cancer prognosis. Gynecol Oncol 101:403–10, 2006 Frey MK, Pothuri B: Homologous recombination deficiency (HRD) testing in ovarian cancer clinical practice: a review of the literature. Gynecol Oncol Res Pract 4:4, 2017 Shi Z, Chen B, Han X, et al: Genomic and molecular landscape of homologous recombination deficiency across multiple cancer types. Sci Rep 13:8899, 2023 , International Cancer Genome Consortium Armstrong AJ, Li X, Tucker M, et al: Molecular medicine tumor board: whole-genome sequencing to inform on personalized medicine for a man with advanced prostate cancer. Prostate Cancer Prostatic Dis 24:786–793, 2021 Sailer V, Eng KW, Zhang T, et al: Integrative Molecular Analysis of Patients With Advanced and Metastatic Cancer. JCO Precis Oncol 3, 2019 Beltran H, Eng K, Mosquera JM, et al: Whole-Exome Sequencing of Metastatic Cancer and Biomarkers of Treatment Response. JAMA Oncol 1:466–74, 2015 Al Assaad M, Shin N, Sigouros M, et al: Deciphering the origin and therapeutic targets of cancer of unknown primary: a case report that illustrates the power of integrative whole-exome and transcriptome sequencing analysis. Front Oncol 13:1274163, 2023 Additional Declarations Yes there is potential Competing Interest. Kevin Hadi, Max F. Levine, Gunes Gundem, Juan S. Medina-Martinez, and Elli Papaemmanuil are Isabl, Inc. employees. Supplementary Files FigureS1.pdf FigureS2.pdf Cite Share Download PDF Status: Published Journal Publication published 12 Jan, 2026 Read the published version in Communications Medicine → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4978638","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":357855560,"identity":"70a3f943-f044-4ec5-a630-f7276ec6d6c9","order_by":0,"name":"Juan Miguel 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(B) Breakdown of the Isabl HRD score and HRD status (cutoff \u0026gt; 0.5) across the cohort. FFPE, formalin-fixed, paraffin-embedded; GI, gastrointestinal; HRD, homologous recombination deficiency.\u003c/p\u003e","description":"","filename":"11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4978638/v1/dc4d02d4e7587f45a85368ed.jpg"},{"id":70209144,"identity":"eab639fa-bf1b-4a2a-89e5-f182ee4a5bb7","added_by":"auto","created_at":"2024-11-29 14:13:49","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":409278,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGenomic alterations and features of HRD. \u003c/strong\u003e(A) Landscape of BRCA1/2 and other HR-associated genes in HRD cases. (B) Top, \u003cem\u003eBRCA1/2 \u003c/em\u003ealteration status in the HRD cohort by variant class. Bottom, further delineating alterations in genes outside of \u003cem\u003eBRCA1/2 \u003c/em\u003ein cases that have BRCA1/2 events not considered in standard clinical practice (SSV or VUS) or are \u003cem\u003eBRCAwt\u003c/em\u003e. (C) Genomic feature enrichment (Z-score calculated across the full HRD \u0026amp; HRP cohort) in HRD. Notably, the features of HRD are not distinguished by gene target or variant type. Del, deletion; Dup, duplication; GI, gastrointestinal; Hom, homozygous; HRD, homologous recombination deficiency; HRR, homologous recombination repair; MH, microhomology; Mut, mutation; SBS, single base substitution; SV, structural variant; VUS, variant of unknown significance; WGS, whole genome sequencing; WT, wild-type.\u003c/p\u003e","description":"","filename":"12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4978638/v1/4337a90fa07f17afe09e176c.jpg"},{"id":70209143,"identity":"1b2f8129-6596-46d1-8c16-7de3758fccaf","added_by":"auto","created_at":"2024-11-29 14:13:49","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":742861,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eValidation of alterations in 2 WGS HRD positive cases.\u003c/strong\u003e (A) HGSOC (H\u0026amp;E, 20x) tumor harboring HRD signals as shown in the circos plot with high rate of microhomology deletions, SBS3, SV tandem duplications, and SV deletions. \u0026nbsp;WGS detected an in-frame \u003cem\u003eHIF1A::UIMC1 \u003c/em\u003efusion that leads to a truncated, non-functional chimeric transcript that is missing exon 6, necessary for binding to \u003cem\u003eBRCA1\u003c/em\u003e. (B) PRNE (H\u0026amp;E, 20x) tumor with HRD that harbored a \u003cem\u003eBRCA2::TMPRSS2\u003c/em\u003e fusion validated by FISH. H\u0026amp;E, hematoxylin and eosin; HGSOC, high grade serous ovarian carcinoma; HRD, homologous recombination deficiency; Indel, insertion deletion; LOH, loss of heterozygosity; PRNE, prostate neuroendocrine carcinoma; SBS, single base substitution; SV, structural variant.\u003c/p\u003e","description":"","filename":"13.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4978638/v1/e407d6b56b189c1597d13f74.jpg"},{"id":100117712,"identity":"7b5841b1-42b1-477f-b213-d86a9998f4e1","added_by":"auto","created_at":"2026-01-13 08:10:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2396790,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4978638/v1/16abdb51-3cb1-4ac0-9482-0fef0227c8ea.pdf"},{"id":70209142,"identity":"10688a55-06a2-48e6-bbfe-435b74c6f0be","added_by":"auto","created_at":"2024-11-29 14:13:49","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":108014,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"FigureS1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4978638/v1/8489c9be5c6a4487dbf120d9.pdf"},{"id":70209420,"identity":"bc7eabbc-84c7-47bc-9256-1ac36e04f48f","added_by":"auto","created_at":"2024-11-29 14:21:49","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":218665,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4978638/v1/4ddf6aa818fc693546169f7a.pdf"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nKevin Hadi, Max F. Levine, Gunes Gundem, Juan S. Medina-Martinez, and Elli Papaemmanuil are Isabl, Inc. employees.","formattedTitle":"Whole Genome Analysis Identifies Homologous Recombination Deficiency in Cancers with BRCA1/2 Wild-Type and BRCA1/2 Structural Variants","fulltext":[{"header":"Introduction","content":"\u003cp\u003e \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e (\u003cem\u003eBRCA1/2\u003c/em\u003e) play a significant role in an error-free DNA damage repair pathway known as homologous recombination repair (HRR) \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. This pathway corrects DNA double-strand breaks (DSBs) and interstrand cross-links \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Somatic or germline mutations in \u003cem\u003eBRCA1/2 (BRCA\u003c/em\u003emut\u003cem\u003e)\u003c/em\u003e lead to homologous recombination deficiency (HRD) and have long been associated with breast, ovarian, pancreatic, and prostate cancers \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Poly (ADP-ribose) polymerase inhibitors (PARPi) have been developed to treat cancers associated with mutations in \u003cem\u003eBRCA1/2\u003c/em\u003e and other HRR genes based on the synthetically lethal relationship with HRD \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Furthermore, the use of alkylating-like agents, especially platinum-based chemotherapy (PBCT), has shown increased effectiveness for cancers with HRD \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eLoss of function in HRR genes, such as \u003cem\u003eRAD51B, ATM, FANC\u003c/em\u003e genes, \u003cem\u003eCHEK2, PALB2\u003c/em\u003e, among others, can result from small mutations, structural variants, or epigenetic changes \u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Therefore, evaluation of different deleterious mechanisms would require several assays and advanced analysis. Due to the broad range of HRR-inactivating genes, it is necessary to not only survey the full genetic landscape of HRR genes, but also detect DNA damage signatures associated with HRD for selective treatment with PARPi and PBCT \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHRD is associated with DNA damage signatures, including single base substitution (SBS), structural variant (SV) signatures, in addition to loss of heterozygosity (LOH), large scale transition (LST), and telomeric allelic imbalance (TAI) \u003csup\u003e\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Assays that report HRD, such as MyChoice\u0026reg; CDx and FoundationOne CDx, among others, are based on targeted next-generation sequencing (NGS) and only employ a subset (LOH, LST, and TAI) of the available signals to detect HRD. Their use in PARPi treatment of ovarian cancer has been approved based on the results of multiple clinical trials \u003csup\u003e\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. It is worth noting that in some trials several patients with BRCAness (HRD phenotype) have experienced shorter survival under first-line maintenance PARPi and numerous cases lacking BRCAness have shown extended survival (16, 20). In contrast to the current commercially available companion diagnostics (CDx) for HRD testing, algorithms using whole genome sequencing (WGS) such as HRDetect and CHORD, employ all mutation classes. However, these have yet to be tested in clinical settings.\u003c/p\u003e \u003cp\u003eThe clinical and research assays have shown a variable association between BRCAness and the presence of HRR genes mutations \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. This variability indicates that not every deleterious mutation in these genes results in BRCAness. Conversely, BRCAness can also be associated with \u003cem\u003eBRCA1/2\u003c/em\u003e wild type (\u003cem\u003eBRCA\u003c/em\u003ewt) and variants of unknown significance (VUS) \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. This highlights the necessity of focusing on the BRCAness phenotype rather than solely relying on the known pathogenicity of mutations.\u003c/p\u003e \u003cp\u003eWGS offers a comprehensive assessment of the genome, covering simple and complex SVs, copy number alterations (CNA), and mutational patterns associated with HRD \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. It achieves superior precision and sensitivity in identifying BRCAness. Consequently, WGS-based HRD biomarkers may more effectively stratify cancer patients for therapeutic interventions \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, we analyzed WGS data from pan-cancer samples and investigated the prevalence and characteristics of HRD employing a novel WGS-based classifier. We compared our HRD results with scores from other WGS-based algorithms and, in a subset, with commercial HRD tests, correlating them with treatment responses.\u003c/p\u003e "},{"header":"Methods","content":"\n\u003ch3\u003eI. Patient enrollment, tissue samples and clinical data acquisition\u003c/h3\u003e\n\u003cp\u003e Participants were prospectively enrolled at Weill Cornell Medicine in the Institutional Review Board (IRB)-approved protocols WCM IRB #1305013903 and #1007011157. Tumor DNA for WGS was extracted from frozen tumor samples, formalin-fixed, paraffin-embedded (FFPE) archival tissue, or fluid from malignant ascites. Histopathology review was performed before DNA extraction. Germline DNA was primarily extracted from blood. When unavailable, saliva or benign tissue (frozen or FFPE) was used. We collected comprehensive clinical data, which encompassed age, sex, ethnicity, treatment-related information, radiologic findings, and pathologic data.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eII. DNA Extraction and WGS:\u003c/h2\u003e \u003cp\u003eFor DNA extraction from FFPE blocks, we used 5-micrometer-thick unstained slides macro-dissected for at least 80% tumor content. For DNA extraction from frozen specimens, we employed 3mm core punches from the frozen OCT-embedded tissue. The Maxwell\u0026reg; 16 FFPE Plus DNA kit (Promega, Cat# AS1135) was employed, in combination with the Maxwell\u0026reg; 16 instrument (Promega, Madison, WI). DNA quality and quantity was assessed by using the Agilent Tapestation 4200 (Agilent Technologies) and the Qubit Fluorometer (ThermoFisher), respectively. Whole genome sequencing (WGS) was carried out at the New York Genome Center on an Illumina Novaseq6000 sequencer using 2x150 bp cycles. Libraries were generated using the KAPA Hyper Library Preparation Kit (KAPABiosystems KK8502, KK8504), targeting 500 bp fragments, in compliance with the manufacturer's instructions. DNA fragments underwent a series of preparation steps including shearing, end-repair, adenylation, and ligation to Illumina sequencing adapters. The prepared DNA fragments were size-selected using bead-based methods and amplified \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Quality and quantity of the final libraries were assessed prior to sequencing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eIII. WGS data processing pipeline and HRD curation\u003c/h2\u003e \u003cp\u003eWe employed Isabl GxT analytics \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, a comprehensive data management, processing, and visualization platform, to analyze cancer whole genome and transcriptome sequencing data. This platform was used to process all WGS and RNA sequencing data and generate comprehensive reports \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Within the Isabl pipeline deployed in Amazon Web Services (AWS) cloud high performance computing (HPC) environments, DNA and RNA alignment with Burrows-Wheeler Aligner (BWAMem) and Spliced Transcripts Alignment to a Reference (STAR), quality control, somatic and germline variant calling, and annotation were performed as previously described \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Briefly, ensemble calling was done for both somatic and germline single nucleotide variants (SNV), insertions deletions (InDels), and somatic SVs. These variant classes were then annotated and those in which at least 2 of 3 callers of each class were included for reporting. Purity, ploidy, and genome-wide copy number states were estimated with Battenberg, followed by annotation of CNA events at the gene level. Driver alterations for all variant classes and their potential treatment targets were assessed by cross-referencing protein-coding variants with Catalogue Of Somatic Mutations In Cancer (COSMIC)\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e and Oncology Knowledge Base (OncoKB)\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWGS-HRD scores were assigned with Isabl HRD\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, a random forest classifier trained on a subset of the data to detect HRD by incorporating evidence from genome-wide SNV, indels, SV, and copy number variant (CNV) signals (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). A subset of the whole cohort was used as the training cohort consisting of 381 matched tumor/normal (T/N) WGS pairs from 321 patients, representing 62 tumor types. All WGS samples were sequenced to a median Tumor/Normal sequencing depth of 92X/48X. The training cohort consisted of 195 fresh frozen and 98 FFPE tumors. SNV, InDels, SV, and allele-specific copy number alteration (aCNA) events were detected across all samples using ensemble pipelines for filtering and annotation\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Patients with high-confidence HRD (hcHRD, N\u0026thinsp;=\u0026thinsp;37) were determined through analysis of genome-wide mutation patterns, and selecting cases that were top quartile outliers for each feature associated with HRD (COSMIC SBS 3, deletions with microhomology, and small SV duplications and deletions). Further visual curation of cases that harbored at least two outlier signatures was performed to select patients with hcHRD. A random forest classifier (Isabl HRD) was then trained using the 37 hcHRD and 268 HRR proficient (HRP) patients from the training cohort with \u0026gt;\u0026thinsp;20% tumor purity. The following WGS features were used to train the classifier: 96 trinucleotide SNV contexts, 45 InDel types, 38 SV types, and LST, LOH, and TAI scores. Classifier performance to predict bi-allelic \u003cem\u003eBRCA1/2\u003c/em\u003e status was evaluated on a validation cohort of 556 breast, ovarian, prostate, and pancreas cases with mutation calls obtained from the International Cancer Genome Consortium using the area under receiver operating characteristic (AUROC\u0026thinsp;=\u0026thinsp;0.99) and precision-recall (AUPRC\u0026thinsp;=\u0026thinsp;0.96) curves.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe applied the classifier on our entire cohort, which assigned a probability of presence of the HRD phenotype. The resulting score ranged from 0 to 1, with a score equal to or greater than 0.5 indicating HRD (\u0026ge;\u0026thinsp;0.5) and a score less than 0.5 labeled HRP (\u0026lt;\u0026thinsp;0.5). Tumor purity\u0026thinsp;\u0026gt;\u0026thinsp;20% is required to accurately assess HRD.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIV. Fluorescence\u003c/b\u003e \u003cb\u003ein situ\u003c/b\u003e \u003cb\u003eHybridization\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFour-\u0026micro;m-thick formalin-fixed paraffin-embedded tissue sections were used for fluorescence \u003cem\u003ein situ\u003c/em\u003e hybridization (FISH) analysis, as described in our protocols \u003csup\u003e\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Bacterial artificial chromosomes were designed against loci of interest to prepare break-part dual-color FISH probes \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. For \u003cem\u003eBRCA2\u003c/em\u003e RP11-110O22 BAC clone was labeled red and RP11-11K16 clone was labeled green, and for \u003cem\u003eATM\u003c/em\u003e RP11- 144G7 BAC clone was labeled red and RP11-589O5 clone was labeled green. All clones were validated on normal metaphase spreads before any application on FFPE tissue. A positive break-apart was determined by one red, one green, and one yellow signal (combination of red and green signal indicating the normal chromosome homologue). At least 200 nuclei were analyzed per case using a fluorescent microscope (Olympus BX51; Olympus Optical). Cytovision 7.3.1 software was used for imaging and analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSample Characteristics and Frequency of HRD\u003c/h2\u003e \u003cp\u003eWe performed WGS analysis on 580 tumor samples and the matching germline samples from 453 patients. Figure\u0026nbsp;1 summarizes the types of tumor samples (FFPE, frozen, or fluid) and type of lesion (primary and metastatic). These encompass 77 unique histology types (\u003cb\u003eFigure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e), classified according to the MSKCC Oncotree \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, and obtained from 33 unique primary sites. Sites were divided into six cancer subgroups: prostate (29%), gynecological (20%), pancreaticobiliary (15%), breast (11%), upper gastrointestinal (GI) (10%), and \u0026ldquo;others\u0026rdquo; (12%), which included smaller cancer cohorts and rare tumors (Fig.\u0026nbsp;1, \u003cb\u003eFigure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e, Supplementary Data 1\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eHRD analysis was conducted on 521 of the 580 tumor samples, with 59 cases excluded due to low purity (\u0026lt;\u0026thinsp;20%). The median purity was 71.5%, and the median coverage was 90x. Sixty-two samples across 53 patients exhibited HRD by WGS. The highest percentage of HRD cases was found in breast cancer (21%), followed by pancreaticobiliary (20%), gynecological (17%), and prostate cancers (9%). Upper GI cancers had the lowest percentage of HRD, with only one case harboring this phenotype. Additionally, one case of carcinoma of unknown primary in the \"others\" cohort demonstrated HRD.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eMutational landscape of HRD\u003c/h2\u003e \u003cp\u003eWhile BRCAness is most commonly explained and clinically tested by alterations in \u003cem\u003eBRCA1/2\u003c/em\u003e, dysfunction in other HRR pathway genes can also result in phenocopy. We investigated events in \u003cem\u003eBRCA1, BRCA2\u003c/em\u003e, and other HRR pathway genes in HRD phenotype cases, accounting for loss of heterozygosity and compound hits that could result in biallelic loss of function and focusing on SVs and somatic mutations with unknown effects on HRD (Fig.\u0026nbsp;2). Out of 62 HRD samples across 53 patients, 76% (47) harbored alterations in \u003cem\u003eBRCA1\u003c/em\u003e and/or \u003cem\u003eBRCA2\u003c/em\u003e (\u003cem\u003eBRCA1/2mut\u003c/em\u003e). In 55% (34) of samples, \u003cem\u003eBRCA1/2mut\u003c/em\u003e had biallelic pathogenic small mutations (SNVs and InDels) and 6% (4) had homozygous deletions. Another 3% (2) harbored SVs with LOH in \u003cem\u003eBRCA1/2\u003c/em\u003e with predicted impact on coding sequence. Interestingly, none of those two samples with \u003cem\u003eBRCA1/2\u003c/em\u003e biallelic SVs had deleterious mutations in other HRR pathway-related genes (Fig.\u0026nbsp;2). In addition, 11% (7) harbored \u003cem\u003eBRCA1/2\u003c/em\u003e small mutation VUS or SV VUS. An example of \u003cem\u003eBRCA1/2\u003c/em\u003e SV is a case of advanced prostatic carcinoma with neuroendocrine histology where WGS revealed \u003cem\u003eBRCA2::TMPRSS2\u003c/em\u003e fusion and HRD. \u003cem\u003eBRCA2\u003c/em\u003e rearrangement was validated with FISH break-apart assay (Fig.\u0026nbsp;3.\u003cb\u003ea\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eUltimately, the remaining 15 HRD cases (24%) were BRCAwt (Fig.\u0026nbsp;2). For those samples with \u003cem\u003eBRCA\u003c/em\u003ewt we investigated other gene mutations that might have caused the HRD phenotype, and we found that one prostate cancer had a pathogenic small mutation in \u003cem\u003eFANCF\u003c/em\u003e (p.W193*), another prostate cancer had biallelic \u003cem\u003eFANCC\u003c/em\u003e deletion, and one endometrial carcinoma had biallelic \u003cem\u003eXRCC2\u003c/em\u003e deletion. The remaining \u003cem\u003eBRCA\u003c/em\u003ewt HRD cases (n\u0026thinsp;=\u0026thinsp;12) either had no mutations in any of the known HRR genes (n\u0026thinsp;=\u0026thinsp;5; 33% of the \u003cem\u003eBRCA\u003c/em\u003ewt HRD cases) or had a VUS small mutation or SV in one or multiple HRR pathway genes including \u003cem\u003eRAD51B, PALB2, ATM, CHEK2, FANCD2\u003c/em\u003e and \u003cem\u003eRAD51\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;7; 47% of the \u003cem\u003eBRCA\u003c/em\u003ewt HRD cases, \u003cb\u003eSupplementary Fig.\u0026nbsp;2\u003c/b\u003e). Examples of these cases include one sample of high-grade serous carcinoma of the ovary (HGSOC) with a \u003cem\u003eHIF1A::UIMC1\u003c/em\u003e fusion involving intron 13 of \u003cem\u003eUIMC1\u003c/em\u003e with LOH. \u003cem\u003eUIMC1\u003c/em\u003e encodes a nuclear protein that functions with \u003cem\u003eBRCA1\u003c/em\u003e in recognizing and repairing DNA lesions. The fusion was validated by RNA sequencing (Fig.\u0026nbsp;3.\u003cb\u003eb\u003c/b\u003e). Another case involved a high-grade serous carcinoma of the fallopian tube (HGSFC) with a biallelic VUS \u003cem\u003eATM\u003c/em\u003e mutation (p.P2842S). In both cases, MyChoice CDx predicted HRD. The first case showed a response to PBCT (RECIST 1.1, \u003cb\u003eSupplementary Data 1\u003c/b\u003e), and the second case had 20 months of PFS on PARPi without progression at the time of writing this manuscript.\u003c/p\u003e \u003cp\u003eFeatures frequently enriched in the HRD cohort consisted of genome wide small microhomology deletions (MH-dels), COSMIC signatures (V3) SBS3 or SBS40, SV deletions from 1-10kb, and SV duplications from 1-10kb (Fig.\u0026nbsp;2). SV duplications were largely enriched in \u003cem\u003eBRCA1\u003c/em\u003e mutated tumors. While MH-dels were the most frequently enriched feature among HRD samples, 3 \u003cem\u003eBRCA\u003c/em\u003ewt, \u003cem\u003eRAD51B\u003c/em\u003e mutated samples harbored intermediate MH-dels with enrichment of SV deletions or duplications and SBS3/40 indicating a potentially distinct HRD feature profile.\u003c/p\u003e \u003cp\u003e \u003cb\u003eHRP cases with\u003c/b\u003e \u003cb\u003eBRCA1/2mut\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn the HRP tumor cohort, 12.4% (57 of 459) samples had at least one mutated \u003cem\u003eBRCA1/2\u003c/em\u003e allele. Among these, 10% (5 of 57) had biallelic pathogenic mutations and 23% (13 of 57) had monoallelic pathogenic mutations. The remaining monoallelic and biallelic mutations were VUS small mutations or SV with germline pathogenic mutations.\u003c/p\u003e \u003cp\u003eFor the 5 samples with biallelic pathogenic \u003cem\u003eBRCA1/2\u003c/em\u003e mutations and HRP, one was from a patient with mixed ovarian carcinoma with a \u003cem\u003ePOLE\u003c/em\u003e pathogenic mutation (c.857C\u0026thinsp;\u0026gt;\u0026thinsp;G, p.P286R) that led to a hypermutator state with a TMB of 897.9/mb and no HRD signatures. This suggests the possibility of the \u003cem\u003eBRCA2\u003c/em\u003e mutation being a result of the hypermutator phenotype. The other 4 samples were from a prostate adenocarcinoma patient where no HRD signatures were found in any of the samples.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eHRD concordance in cases with multiple samples\u003c/h2\u003e \u003cp\u003eOur cohort included 54 patients with two or more samples, totaling 169 samples. Among these patients, 85% (46 of 54) did not have any samples with HRD, and 13% (7 of 54) had all their samples consistently showing HRD. Only 1 of 54 (2%) had a discrepant HRD status between samples. The patient had histologically and molecularly different synchronous ovarian and endometrial serous carcinomas. The sample from the brain metastatic lesion originated from the endometrial cancer, which displayed HRD associated with \u003cem\u003eBRCA1, RAD51B\u003c/em\u003e, and \u003cem\u003eRAD54B\u003c/em\u003e deleterious rearrangements. This sample also had drivers including \u003cem\u003eTP53\u003c/em\u003e (p.G244R), \u003cem\u003eRB1\u003c/em\u003e (p.R579fs29), and \u003cem\u003eSMARCA2\u003c/em\u003e (p.A7fs15), among others. In contrast, the ovarian cancer sample displayed only a \u003cem\u003eFANCM\u003c/em\u003e rearrangement, with wild-type \u003cem\u003eBRCA1, RAD51B\u003c/em\u003e, and \u003cem\u003eRAD54B\u003c/em\u003e. The drivers for this sample included \u003cem\u003eTP53\u003c/em\u003e (p.G244R) and \u003cem\u003eRRAS2\u003c/em\u003e (p.G23V), with wild-type \u003cem\u003eRB1\u003c/em\u003e and \u003cem\u003eSMARCA2\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eComparison of Isabl WGS HRD with other assays\u003c/h2\u003e \u003cp\u003eCurrent commercial tests for HRD employ only GIS or LOH scores based on allele-specific copy number segmentation, a subset of genome-wide features predictive of HRD and captured by WGS. To explore the potential clinical significance of WGS-based HRD testing, we retrospectively assessed cases with WGS, commercial HRD scores, and clinical history that included treatment response. From the 39 serous carcinoma cases in the gynecological cancer cohort, where an HRD score can inform treatment decisions, we identified 15 cases that had undergone a commercial assay that included an HRD score. This group comprised 9 cases evaluated with MyChoice CDx GIS and 6 cases with FoundationOne HRD score. The results of both commercial assays and WGS testing are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Of these cases, 3 out of 5 identified as HRD-positive by WGS were deemed HRP by commercial assays; these included 1 case tested by FoundationOne (negative) and 2 cases by MyChoice CDx, one negative and the other inconclusive for HRD. All 3 cases had confident HRD phenotype features, including enrichment for MH-dels, SV deletions, or duplications. Two of the 3 patients were maintained on PARPi after showing a response to PBCT (RECIST 1.1) and experienced prolonged periods of non-progression, lasting 10 months and 5 years, respectively. The third patient did not receive PARPi.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of WGS HRD with commercially available assays. HRD, Homologous Recombination Deficiency; HRP, Homologous Recombination Proficiency; PARPi, PARP inhibitor; PFS, Progression Free Survival.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCMID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIsabl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCommercial Assay\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eResult\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eClinical response to Maintenance PARPi\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCM231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHRD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFoundationOne\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProgression 10 months after maintenance thearpy (PFS\u0026thinsp;=\u0026thinsp;10months)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCM209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHRD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMyChoice CDx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHRD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo available PARPi response data\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCM414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHRD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMyChoice CDx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHRD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo disease recurrence to date (PFS\u0026thinsp;=\u0026thinsp;20 months)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCM205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHRD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMyChoice CDx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDid not receive PARPi\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCM228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHRD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMyChoice CDx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInconclusive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo disease recurrence to date (PFS\u0026thinsp;=\u0026thinsp;60 months)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCM425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFoundationOne CDx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHRD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProgression 2 months after maintenance thearpy (PFS\u0026thinsp;=\u0026thinsp;2 months)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCM295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMyChoice CDx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDid not receive PARPi\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCM436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFoundationOne CDx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHRD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDid not receive PARPi\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCM236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFoundationOne CDx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHRD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProgression 3 months after maintenance thearpy (PFS\u0026thinsp;=\u0026thinsp;3 months)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCM435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMyChoice CDx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDid not receive PARPi\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCM442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFoundationOne CDx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDid not receive PARPi\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCM272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFoundationOne CDx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInconclusive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProgression 3 months after maintenance thearpy (PFS\u0026thinsp;=\u0026thinsp;3 months)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCM284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMyChoice CDx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDid not receive PARPi\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCM331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMyChoice CDx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDid not receive PARPi\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWCM419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMyChoice CDx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDid not receive PARPi\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmong cases determined as HRP by WGS (N\u0026thinsp;=\u0026thinsp;10), 1 was found to be inconclusive and 3 were found to be positive according to FoundationOne. All 4 cases had an enrichment in MH-dels, SV deletions, duplications, and SBS3/40. Our assessment using RECIST 1.1 (\u003cb\u003eSupplementary Data 2\u003c/b\u003e) confirmed disease progression on PARPi after 3 months for the case deemed inconclusive by FoundationOne, and after 2 and 3 months, respectively, for 2 of the 3 cases with HRD by FoundationOne but HRP by WGS. The third case was not treated with PARPi.\u003c/p\u003e \u003cp\u003eWe also investigated HRD positivity using two other HRD algorithms, CHORD and HRDetect (Fig.\u0026nbsp;2.\u003cb\u003ea\u003c/b\u003e) \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Overall, 15% (9 of 62) of our WGS HRD samples were negative by CHORD, which included 3 cases that are simultaneously negative by HRDetect. Interestingly, 2 of those cases were \u003cem\u003eBRCA\u003c/em\u003ewt with \u003cem\u003eRAD51\u003c/em\u003e structural variants, and one with \u003cem\u003eBRCA2\u003c/em\u003e monoallelic VUS somatic small mutation and \u003cem\u003eBRCA1\u003c/em\u003e biallelic pathogenic somatic small mutation.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe significance of HRD in precision oncology has grown because of the development of PARPi and the correlation with response to PBCT in solid tumors \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan additionalcitationids=\"CR40 CR41\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Targeted NGS panels are limited in detecting the full range of \u003cem\u003eBRCA1/2\u003c/em\u003e mutational events and mainly focus on exonic regions \u003csup\u003e\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Targeted panels may also overlook alterations in other genes of the HRR pathway that may cause HRD \u003csup\u003e\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Consequently, recent research has focused on scoring the genomic signatures of the disruption in the HRR pathway like LOH, TAI, LST, SBS3, small deletions, and tandem duplications \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. However, these HRD 'footprints' are not fully revealed by common targeted panels and exome sequencing \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. To address these limitations, we employed a WGS approach to better determine the HRD status in a pan-cancer cohort.\u003c/p\u003e \u003cp\u003eEpithelial carcinomas of the ovary and fallopian tube are the only cancer types approved for PARPi treatment based on clinical HRD signature testing, according to the most recent NCCN guidelines \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. In our cohort, we compared WGS HRD phenotype testing results to MyChoice CDx and FoundationOne CDx when available. We identified several discrepant cases: patients with HRD on WGS but HRP by clinical panels showed treatment response to PARPi and/or PBCT, whereas those patients with HRP tumors by our WGS classifier but HRD on other panels exhibited treatment resistance to PARPi or PBCT. While preliminary and limited by the number of cases, our study provides evidence that WGS would improve prediction of HRD with subsequent treatment response, beyond current FDA approved CDx for HRD. As reported in other studies, a WGS classifier of HRD might reduce false negatives and increase the inclusion of appropriate patients in relevant clinical trials \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn an effort to assess concordance across commercial and research tests that employ GIS or LOH scores, recent analysis of 13 GIS-based assays revealed challenges in unifying a definition of HRD and reported a wide range of percent positive HRD cases (\u0026gt;\u0026thinsp;50% differences) in the cohorts studied \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. More fundamentally, comparative studies that continue to be designed around performance metrics other than treatment or other clinical response limit objective assessment of the use of such assays.\u003c/p\u003e \u003cp\u003ePARPi are progressively becoming a part of the therapeutic arsenal against tumors with HRD. However, treatment of non-ovarian cancers with PARPi depends on specific conditions, according to NCCN guidelines. These include the presence of a pathogenic \u003cem\u003eBRCA1/2\u003c/em\u003e mutation for breast and pancreatic cancers, or the presence of pathogenic mutations in \u003cem\u003eBRCA1/2\u003c/em\u003e and/or other HRR genes in prostate cancer \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Our results reveal that the HRD phenotype was not only identified across a variety of cancer types, but also associated with pathogenic variants, VUS, and wild-type status of \u003cem\u003eBRCA1/2\u003c/em\u003e or other HRR genes.\u003c/p\u003e \u003cp\u003eOur study further expands the spectrum of molecular events that cause HRD and includes biallelic structural variants in \u003cem\u003eBRCA1/2\u003c/em\u003e and other HRR pathway genes. Our results in this area confirm the data reported by Ewing \u003cem\u003eet al.\u003c/em\u003e, on \u003cem\u003eBRCA1/2\u003c/em\u003e SVs in ovarian serous carcinomas, prostatic carcinoma, and breast carcinoma and expand our knowledge of SVs impacting other HRR genes like \u003cem\u003eRAD51B, FANCC\u003c/em\u003e, and \u003cem\u003eCHEK2\u003c/em\u003e among others\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. We also report that cases with structural or small mutation VUS in \u003cem\u003eBRCA1/2\u003c/em\u003e or other HRR genes were the most probable drivers in cases with HRD phenotype, not coinciding with other known pathogenic mutations in the HRR pathway. This suggests that those VUS are possibly related to HRD and might be considered pathogenic, supporting a previous study that reported a correlation between \u003cem\u003eBRCA1/2\u003c/em\u003e VUS and the HRD phenotype \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe also interrogated those \u003cem\u003eBRCA\u003c/em\u003ewt cases with HRD phenotype. These patients, identified as having HRD tumors through clinically approved testing assays like MyChoice CDx and Foundation CDx, as well as other WGS-based assays, have been reported in the literature to constitute approximately 20\u0026ndash;30% of cases \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. This range aligns with the data observed in our study. Based on WGS, some of our patients had biallelic mutations in other HRD genes, like \u003cem\u003ePALB2\u003c/em\u003e and \u003cem\u003eRAD51B\u003c/em\u003e, known to be associated with HRD. In other cases, we identified variants in genes reported to be linked to HRR pathway dysfunction without previously known clinical impact. One example is a case with a \u003cem\u003eUIMC1\u003c/em\u003e fusion in which the deletion of the AIR domain, essential for binding to the BRCA1-A complex, could have caused HRD \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. In some \u003cem\u003eBRCA\u003c/em\u003ewt HRD cases, the genomic cause could not be uncovered by WGS, which may be due to epigenetic changes like \u003cem\u003eBRCA1/2\u003c/em\u003e promoter methylation \u003csup\u003e\u003cspan additionalcitationids=\"CR56\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOne of the main conclusions of our study is that, compared to commercial assays, WGS-based HRD assessment could clarify inconclusive or misleading results from NGS-based assays that rely on fewer signatures. On a routine basis, we discuss such cases during a research molecular tumor board (MTB) format, a Continuing Medical Education (CME) accredited conference \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan additionalcitationids=\"CR59 CR60 CR61\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. Examples include 2 patients (detailed above), both of which showed a WGS HRD phenotype but were HRP and inconclusive by MyChoice CDx respectively. For the first patient, following a recent disease recurrence of HGSOC, the consensus was to consider PARPi as a valid treatment option, especially in light of a previous response to PBCT. For the second patient, who had HGSOC with a WGS-determined HRD phenotype, the commercial HRD assay results were inconclusive. However, WGS identified a biallelic structural variant in \u003cem\u003eRAD51B\u003c/em\u003e as the likely cause of the HRD phenotype, rather than the monoallelic \u003cem\u003eBRCA2\u003c/em\u003e VUS found through clinical targeted sequencing. The consensus was to continue the patient on maintenance PARPi treatment started earlier, and to which the patient was responding.\u003c/p\u003e \u003cp\u003eIn summary, we illustrate how a WGS HRD classifier could be universally applicable in precision oncology, unearthing the HRD phenotype that may be invisible by other methods. Future functional studies will help elucidate the role of structural variants in causing HRD. We acknowledge that larger clinical response data is required to definitively assess accuracy of HRD predictions against treatment response. This study provides major impetus to evaluate WGS as a potential clinical diagnostic tool to target PARPi and PBCT responses and paves the way for both clinical validity studies and drug trial designs that include WGS methodology in their endpoints.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Englander Institute for Precision Medicine. Whole-genome sequencing was performed at the New York Genome Center, supported by an agreement with Illumina, Inc., and Weill Cornell Medicine. Project support for this research was also provided in part by the Center for Translational Pathology from the Department of Pathology and Laboratory Medicine at Weill Cornell Medicine. The authors thank Ahmed G Elsaeed for project support with data extraction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and informed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe use of the clinical data and samples for this study was approved by Weill Cornell Medicine institutional review board (IRB) protocols # 1305013903 (Research for Precision Medicine) and # 1007011157 (Comprehensive Cancer Characterization by Genomic and Transcriptomic Profiling).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.A., K.H. and JM.M. performed study concept and design, and wrote the manuscript. JM.M, M.A., M.S., and J.M. generated the patient cohort. K.H.performed statistical analysis and interpretation of data. K.H., M.L., G.G., J.S.M, and E.P. performed genomic analyses. JM.M and M.A. performed the histopathological assessment. A.S. performed the FISH experiments. M.A, A.S., and K.H. prepared the figures. All authors read and approved the final paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors received no specific funding for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analyzed molecular data is available in the supplementary documents. Raw data are available upon reasonable request from the corresponding authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKevin Hadi, Max F. Levine, Gunes Gundem, Juan S. Medina-Martinez, and Elli Papaemmanuil are Isabl, Inc. employees.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eStewart MD, Merino Vega D, Arend RC, et al: Homologous Recombination Deficiency: Concepts, Definitions, and Assays. Oncologist 27:167\u0026ndash;174, 2022\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller RE, Leary A, Scott CL, et al: ESMO recommendations on predictive biomarker testing for homologous recombination deficiency and PARP inhibitor benefit in ovarian cancer. Ann Oncol 31:1606\u0026ndash;1622, 2020\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNguyen L, J WMM, Van Hoeck A, et al: Pan-cancer landscape of homologous recombination deficiency. Nat Commun 11:5584, 2020\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVollebergh MA, Lips EH, Nederlof PM, et al: Genomic patterns resembling BRCA1- and BRCA2-mutated breast cancers predict benefit of intensified carboplatin-based chemotherapy. Breast Cancer Res 16:R47, 2014\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDr\u0026Atilde;Šan A, Lord CJ, Ashworth A: PARP inhibitor combination therapy. Crit Rev Oncol Hematol 108:73\u0026ndash;85, 2016\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChai Y, Chen Y, Zhang D, et al: Homologous Recombination Deficiency (HRD) and BRCA 1/2 Gene Mutation for Predicting the Effect of Platinum-Based Neoadjuvant Chemotherapy of Early-Stage Triple-Negative Breast Cancer (TNBC): A Systematic Review and Meta-Analysis. J Pers Med 12, 2022\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePokataev I, Fedyanin M, Polyanskaya E, et al: Efficacy of platinum-based chemotherapy and prognosis of patients with pancreatic cancer with homologous recombination deficiency: comparative analysis of published clinical studies. ESMO Open 5:e000578, 2020\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoschetta M, George A, Kaye SB, et al: BRCA somatic mutations and epigenetic BRCA modifications in serous ovarian cancer. Ann Oncol 27:1449\u0026ndash;55, 2016\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVarol U, Kucukzeybek Y, Alacacioglu A, et al: BRCA genes: BRCA 1 and BRCA 2. J buon 23:862\u0026ndash;866, 2018\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeol JH, Shim EY, Lee SE: Microhomology-mediated end joining: Good, bad and ugly. Mutat Res 809:81\u0026ndash;87, 2018\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eP\u0026Atilde;ŗti \u0026Atilde;, Gyergy\u0026Atilde;Ąk H, N\u0026Atilde;Šmeth E, et al: Correlation of homologous recombination deficiency induced mutational signatures with sensitivity to PARP inhibitors and cytotoxic agents. Genome Biol 20:240, 2019\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eColeman RL, Oza AM, Lorusso D, et al: Rucaparib maintenance treatment for recurrent ovarian carcinoma after response to platinum therapy (ARIEL3): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet 390:1949\u0026ndash;1961, 2017\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSetton J, Reis-Filho JS, Powell SN: Homologous recombination deficiency: how genomic signatures are generated. Curr Opin Genet Dev 66:93\u0026ndash;100, 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkinjiyan FA, Morecroft R, Phillipps J, et al: Homologous Recombination Deficiency (HRD) in Cutaneous Oncology. Int J Mol Sci 24, 2023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMilbury CA, Creeden J, Yip WK, et al: Clinical and analytical validation of FoundationOne\u0026Acirc;ŽCDx, a comprehensive genomic profiling assay for solid tumors. PLoS One 17:e0264138, 2022\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRay-Coquard I, Pautier P, Pignata S, et al: Olaparib plus Bevacizumab as First-Line Maintenance in Ovarian Cancer. N Engl J Med 381:2416\u0026ndash;2428, 2019\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eColeman RL, Fleming GF, Brady MF, et al: Veliparib with First-Line Chemotherapy and as Maintenance Therapy in Ovarian Cancer. New England Journal of Medicine 381:2403\u0026ndash;2415, 2019\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHodgson D, Lai Z, Dearden S, et al: Analysis of mutation status and homologous recombination deficiency in tumors of patients with germline BRCA1 or BRCA2 mutations and metastatic breast cancer: OlympiAD. Ann Oncol 32:1582\u0026ndash;1589, 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavies H, Glodzik D, Morganella S, et al: HRDetect is a predictor of BRCA1 and BRCA2 deficiency based on mutational signatures. Nat Med 23:517\u0026ndash;525, 2017\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTer Brugge P, Moser SC, Bi\u0026Atilde;\u0026uml;che I, et al: Homologous recombination deficiency derived from whole-genome sequencing predicts platinum response in triple-negative breast cancers. Nat Commun 14:1958, 2023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Luca XM, Newell F, Kazakoff SH, et al: Using whole-genome sequencing data to derive the homologous recombination deficiency scores. NPJ Breast Cancer 6:33, 2020\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLord CJ, Ashworth A: PARP inhibitors: Synthetic lethality in the clinic. Science 355:1152\u0026ndash;1158, 2017\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBruinsma S, Burgess J, Schlingman D, et al: Bead-linked transposomes enable a normalization-free workflow for NGS library preparation. BMC Genomics 19:722, 2018\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNauseef JT, Elsaeed A, Al Assaad M, et al: Use of a navigable interface for integrated whole genome and transcriptome sequencing as a platform for pursuit of therapeutic targets in advanced prostate cancers. Journal of Clinical Oncology 41:225\u0026ndash;225, 2023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShukla N, Levine MF, Gundem G, et al: Feasibility of whole genome and transcriptome profiling in pediatric and young adult cancers. Nat Commun 13:2485, 2022\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMedina-Mart\u0026iacute;nez JS, Arango-Ossa JE, Levine MF, et al: Isabl Platform, a digital biobank for processing multimodal patient data. BMC Bioinformatics 21:549, 2020\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl Assaad M, Gundem G, Liechty B, et al: The importance of escalating molecular diagnostics in patients with low-grade pediatric brain cancer. Cold Spring Harb Mol Case Stud 9, 2023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAssaad MA, Kuo H-H, Nauseef J, et al: Abstract 3437: Whole genome and transcriptome sequencing of a pan cancer cohort unearths novel therapeutic avenues. Cancer Research 83:3437\u0026ndash;3437, 2023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHissong E, Al Assaad M, Bal M, et al: NIPBL::NACC1 Fusion Hepatic Carcinoma. The American Journal of Surgical Pathology 48, 2024\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMendelson NL, Al Assaad M, Hadi K, et al: Whole-genome Analysis Elucidates Complex Genomic Events in GLI1-rearranged Enteric Tumor. The American Journal of Surgical Pathology 47, 2023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTate JG, Bamford S, Jubb HC, et al: COSMIC: the Catalogue Of Somatic Mutations In Cancer. Nucleic Acids Res 47:D941-d947, 2019\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChakravarty D, Gao J, Phillips SM, et al: OncoKB: A Precision Oncology Knowledge Base. JCO Precis Oncol 2017, 2017\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHadi K, Gundem G, Levine M, et al: Abstract 2149: A whole genome sequencing classifier of homologous recombination deficiency. Cancer Research 83:2149\u0026ndash;2149, 2023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl Assaad M, Michaud O, Semaan A, et al: Whole-Genome Sequencing Analysis of Male Breast Cancer Unveils Novel Structural Events and Potential Therapeutic Targets. Mod Pathol 37:100452, 2024\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHissong E, Al Assaad M, Bal M, et al: NIPBL::NACC1 Fusion Hepatic Carcinoma. Am J Surg Pathol 48:183\u0026ndash;193, 2024\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMendelson NL, Al Assaad M, Hadi K, et al: Whole-genome Analysis Elucidates Complex Genomic Events in GLI1 -rearranged Enteric Tumor. Am J Surg Pathol 47:1192\u0026ndash;1193, 2023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGenomics B:\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKundra R, Zhang H, Sheridan R, et al: OncoTree: A Cancer Classification System for Precision Oncology. JCO Clin Cancer Inform 5:221\u0026ndash;230, 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eD'Andrea AD: Mechanisms of PARP inhibitor sensitivity and resistance. DNA Repair (Amst) 71:172\u0026ndash;176, 2018\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeng Z, Shao D, Cai Y, et al: Homologous recombination deficiency status predicts response to platinum-based chemotherapy in Chinese patients with high-grade serous ovarian carcinoma. J Ovarian Res 16:53, 2023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO'Malley DM, Krivak TC, Kabil N, et al: PARP Inhibitors in Ovarian Cancer: A Review. Target Oncol 18:471\u0026ndash;503, 2023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsang ES, Csizmok V, Williamson LM, et al: Homologous recombination deficiency signatures in gastrointestinal and thoracic cancers correlate with platinum therapy duration. NPJ Precis Oncol 7:31, 2023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFountzilas E, Papadopoulou K, Chatzikonstantinou T, et al: Concordance between Three Homologous Recombination Deficiency (HRD) Assays in Patients with High-Grade Epithelial Ovarian Cancer. Cancers (Basel) 15, 2023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSztupinszki Z, Diossy M, Krzystanek M, et al: Detection of Molecular Signatures of Homologous Recombination Deficiency in Prostate Cancer with or without BRCA1/2 Mutations. Clin Cancer Res 26:2673\u0026ndash;2680, 2020\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDoig KD, Fellowes AP, Fox SB: Homologous Recombination Repair Deficiency: An Overview for Pathologists. Mod Pathol 36:100049, 2023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVogel A, Haupts A, Kloth M, et al: A novel targeted NGS panel identifies numerous homologous recombination deficiency (HRD)-associated gene mutations in addition to known BRCA mutations. Diagn Pathol 19:9, 2024\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNetwork NCC: NCCN Guidelines, 2024\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLheureux S, Lai Z, Dougherty BA, et al: Long-Term Responders on Olaparib Maintenance in High-Grade Serous Ovarian Cancer: Clinical and Molecular Characterization. Clin Cancer Res 23:4086\u0026ndash;4094, 2017\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e, Friends of Cancer Research, 2022\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEwing A, Meynert A, Churchman M, et al: Structural Variants at the BRCA1/2 Loci are a Common Source of Homologous Repair Deficiency in High-grade Serous Ovarian Carcinoma. Clin Cancer Res 27:3201\u0026ndash;3214, 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBouwman P, van der Heijden I, van der Gulden H, et al: Functional Categorization of BRCA1 Variants of Uncertain Clinical Significance in Homologous Recombination Repair Complementation Assays. Clin Cancer Res 26:4559\u0026ndash;4568, 2020\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatsumoto K, Nishimura M, Onoe T, et al: PARP inhibitors for BRCA wild type ovarian cancer; gene alterations, homologous recombination deficiency and combination therapy. Jpn J Clin Oncol 49:703\u0026ndash;707, 2019\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGruber JJ, Afghahi A, Timms K, et al: A phase II study of talazoparib monotherapy in patients with wild-type BRCA1 and BRCA2 with a mutation in other homologous recombination genes. Nat Cancer 3:1181\u0026ndash;1191, 2022\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e. National Library of Medicine, 2024\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChiang JW, Karlan BY, Cass L, et al: BRCA1 promoter methylation predicts adverse ovarian cancer prognosis. Gynecol Oncol 101:403\u0026ndash;10, 2006\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrey MK, Pothuri B: Homologous recombination deficiency (HRD) testing in ovarian cancer clinical practice: a review of the literature. Gynecol Oncol Res Pract 4:4, 2017\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi Z, Chen B, Han X, et al: Genomic and molecular landscape of homologous recombination deficiency across multiple cancer types. Sci Rep 13:8899, 2023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e, International Cancer Genome Consortium\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArmstrong AJ, Li X, Tucker M, et al: Molecular medicine tumor board: whole-genome sequencing to inform on personalized medicine for a man with advanced prostate cancer. Prostate Cancer Prostatic Dis 24:786\u0026ndash;793, 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSailer V, Eng KW, Zhang T, et al: Integrative Molecular Analysis of Patients With Advanced and Metastatic Cancer. JCO Precis Oncol 3, 2019\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeltran H, Eng K, Mosquera JM, et al: Whole-Exome Sequencing of Metastatic Cancer and Biomarkers of Treatment Response. JAMA Oncol 1:466\u0026ndash;74, 2015\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl Assaad M, Shin N, Sigouros M, et al: Deciphering the origin and therapeutic targets of cancer of unknown primary: a case report that illustrates the power of integrative whole-exome and transcriptome sequencing analysis. Front Oncol 13:1274163, 2023\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4978638/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4978638/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eHomologous recombination deficiency (HRD) impacts cancer treatment strategies, particularly effective utilization of PARP inhibitors. However, the variability of different HRD assays has hampered the selection of oncology patients who may benefit from these therapies. Our study aims to use the whole genome landscape to better define HRD in a pan-cancer cohort.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe employed a novel whole genome sequencing (WGS) HRD classifier that includes genome-wide signatures associated with HRD to analyze 580 tumor/normal paired samples. The HRD phenotype was correlated with genomic variants in \u003cem\u003eBRCA1/2\u003c/em\u003e and other homologous recombination repair genes. The results were compared to other assays and, in a subset, with commercial HRD tests, correlating them with treatment responses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eHRD phenotype was identified in various cancers including breast (21%), pancreaticobiliary (20%), gynecological (17%), prostate (9%), upper gastrointestinal (GI) (2%), and other cancers (1%). HRD cases were not confined to \u003cem\u003eBRCA1/2\u003c/em\u003e mutations; 24% of HRD cases were \u003cem\u003eBRCA1/2\u003c/em\u003e wild-type. A diverse range of gene alterations involved in HRD were elucidated, including biallelic mutations in \u003cem\u003eFANCF, XRCC2\u003c/em\u003e, and \u003cem\u003eFANCC\u003c/em\u003e, and deleterious structural variants. In a subset of 15 cases, the WGS-based classifier offered more insights and a better correlation to treatment response when compared to other assays.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eHRD is a biomarker used to determine which cancer patients would benefit from PARP inhibitors. However, a lack of harmonization of tests to determine HRD status makes it challenging to interpret their results. Our study highlights the use of comprehensive WGS analysis to better predict HRD and elucidates new genomic mechanisms associated with this phenotype.\u003c/p\u003e","manuscriptTitle":"Whole Genome Analysis Identifies Homologous Recombination Deficiency in Cancers with BRCA1/2 Wild-Type and BRCA1/2 Structural Variants","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-29 14:13:44","doi":"10.21203/rs.3.rs-4978638/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-medicine","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsmed","sideBox":"Learn more about [Communications Medicine](http://www.nature.com/commsmed)","snPcode":"43856","submissionUrl":"https://mts-commsmed.nature.com/cgi-bin/main.plex","title":"Communications Medicine","twitterHandle":"@commsmedicine","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"76e862df-a9e3-4a2f-8990-c091cac12619","owner":[],"postedDate":"November 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":38067754,"name":"Biological sciences/Cancer/Cancer genomics"},{"id":38067755,"name":"Biological sciences/Cancer/Cancer therapy/Targeted therapies"}],"tags":[],"updatedAt":"2026-01-13T08:10:10+00:00","versionOfRecord":{"articleIdentity":"rs-4978638","link":"https://doi.org/10.1038/s43856-025-01308-5","journal":{"identity":"communications-medicine","isVorOnly":false,"title":"Communications Medicine"},"publishedOn":"2026-01-12 05:00:00","publishedOnDateReadable":"January 12th, 2026"},"versionCreatedAt":"2024-11-29 14:13:44","video":"","vorDoi":"10.1038/s43856-025-01308-5","vorDoiUrl":"https://doi.org/10.1038/s43856-025-01308-5","workflowStages":[]},"version":"v1","identity":"rs-4978638","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4978638","identity":"rs-4978638","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}