Rare germline structural variants increase risk for pediatric solid tumors.

Pediatric solid tumors are rare malignancies that represent a leading cause of death by disease among children in developed countries. The early age-of-onset of these tumors suggests that germline genetic factors are involved, yet conventional germline testing for short coding variants in established predisposition genes only identifies pathogenic events in 10-15% of patients. Here, we examined the role of germline structural variants (SVs)-an underexplored form of germline variation-in pediatric extracranial solid tumors using germline genome sequencing of 1,766 affected children, their 943 unaffected relatives, and 6,665 adult controls. We discovered a sex-biased association between very large (>1 megabase) germline chromosomal abnormalities and a four-fold increased risk of solid tumors in male children. The overall impact of germline SVs was greatest in neuroblastoma, where we revealed burdens of ultra-rare SVs that cause loss-of-function of highly expressed, mutationally intolerant, neurodevelopmental genes, as well as noncoding SVs predicted to disrupt three-dimensional chromatin domains in neural crest-derived tissues. Collectively, our results implicate rare germline SVs as a predisposing factor to pediatric solid tumors that may guide future studies and clinical practice.

Integrative Analysis of Germline Rare Variants in Clear and Non-clear Cell Renal Cell Carcinoma.

Background and objective: Previous germline studies on renal cell carcinoma (RCC) have usually pooled clear and non-clear cell RCCs and have not adequately accounted for population stratification, which might have led to an inaccurate estimation of genetic risk. Here, we aim to analyze the major germline drivers of RCC risk and clinically relevant but underexplored germline variant types. Methods: We first characterized germline pathogenic variants (PVs), cryptic splice variants, and copy number variants (CNVs) in 1436 unselected RCC patients. To evaluate the enrichment of PVs in RCC, we conducted a case-control study of 1356 RCC patients ancestry matched with 16 512 cancer-free controls using approaches accounting for population stratification and histological subtypes, followed by characterization of secondary somatic events. Key findings and limitations: Clear cell RCC patients (n = 976) exhibited a significant burden of PVs in VHL compared with controls (odds ratio [OR]: 39.1, p = 4.95e-05). Non-clear cell RCC patients (n = 380) carried enrichment of PVs in FH (OR: 77.9, p = 1.55e-08) and MET (OR: 1.98e11, p = 2.07e-05). In a CHEK2-focused analysis with European participants, clear cell RCC (n = 906) harbored nominal enrichment of low-penetrance CHEK2 variants-p.Ile157Thr (OR: 1.84, p = 0.049) and p.Ser428Phe (OR: 5.20, p = 0.045), while non-clear cell RCC (n = 295) exhibited nominal enrichment of CHEK2 loss of function PVs (OR: 3.51, p = 0.033). Patients with germline PVs in FH, MET, and VHL exhibited significantly earlier age of cancer onset than patients without germline PVs (mean: 46.0 vs 60.2 yr, p < 0.0001), and more than half had secondary somatic events affecting the same gene (n = 10/15, 66.7%). Conversely, CHEK2 PV carriers exhibited a similar age of onset to patients without germline PVs (mean: 60.1 vs 60.2 yr, p = 0.99), and only 30.4% carried somatic events in CHEK2 (n = 7/23). Finally, pathogenic germline cryptic splice variants were identified in SDHA and TSC1, and pathogenic germline CNVs were found in 18 patients, including CNVs in FH, SDHA, and VHL. Conclusions and clinical implications: This analysis supports the existing link between several RCC risk genes and RCC risk manifesting in earlier age of onset. It calls for caution when assessing the role of CHEK2 due to the burden of founder variants with varying population frequency. It also broadens the definition of the RCC germline landscape of pathogenicity to incorporate previously understudied types of germline variants. Patient summary: In this study, we carefully compared the frequency of rare inherited mutations with a focus on patients' genetic ancestry. We discovered that subtle variations in genetic background may confound a case-control analysis, especially in evaluating the cancer risk associated with specific genes, such as CHEK2. We also identified previously less explored forms of rare inherited mutations, which could potentially increase the risk of kidney cancer.

Accelerated Aging and Microsatellite Instability in Recessive Dystrophic Epidermolysis Bullosa-Associated Cutaneous Squamous Cell Carcinoma.

Recessive dystrophic epidermolysis bullosa (RDEB) is a severely debilitating disorder caused by pathogenic variants in COL7A1 and is characterized by extreme skin fragility, chronic inflammation, and fibrosis. A majority of patients with RDEB develop squamous cell carcinoma, a highly aggressive skin cancer with limited treatment options currently available. In this study, we utilized an approach leveraging whole-genome sequencing and RNA sequencing across 3 different tissues in a single patient with RDEB to gain insight into possible mechanisms of RDEB-associated squamous cell carcinoma progression and to identify potential therapeutic options. As a result, we identified PLK-1 as a possible candidate for targeted therapy and discovered microsatellite instability and accelerated aging as factors potentially contributing to the aggressive nature and early onset of RDEB squamous cell carcinoma. By integrating multitissue genomic and transcriptomic analyses in a single patient, we demonstrate the promise of bridging the gap between genomic research and clinical applications for developing tailored therapies for patients with rare genetic disorders such as RDEB.

Interplay of Mendelian and polygenic risk factors in Arab breast cancer patients.

BACKGROUND: Breast cancer patients from the indigenous Arab population present much earlier than patients from Western countries and have traditionally been underrepresented in cancer genomics studies. The contribution of polygenic and Mendelian risk toward the earlier onset of breast cancer in the population remains elusive. METHODS: We performed low-pass whole genome sequencing (lpWGS) and whole-exome sequencing (WES) from 220 female breast cancer patients unselected for positive family history from the indigenous Arab population. Using publicly available resources, we imputed population-specific variants and calculated breast cancer burden-sensitive polygenic risk scores (PRS). Variant pathogenicity was also evaluated on exome variants with high coverage. RESULTS: Variants imputed from lpWGS showed high concordance with paired exome (median dosage correlation: 0.9459, Interquartile range: 0.9410-0.9490). After adjusting the PRS to the Arab population, we found significant associations between PRS performance in risk prediction and first-degree relative breast cancer history prediction (Spearman rho=0.43, p = 0.03), where breast cancer patients in the top PRS decile are 5.53 (95% CI 1.76-17.97, p = 0.003) times more likely also to have a first-degree relative diagnosed with breast cancer compared to those in the middle deciles. In addition, we found evidence for the genetic liability threshold model of breast cancer where among patients with a family history of breast cancer, pathogenic rare variant carriers had significantly lower PRS than non-carriers (p = 0.0205, Mann-Whitney U test) while for non-carriers every standard deviation increase in PRS corresponded to 4.52 years (95% CI 8.88-0.17, p = 0.042) earlier age of presentation. CONCLUSIONS: Overall, our study provides a framework to assess polygenic risk in an understudied population using lpWGS and identifies common variant risk as a factor independent of pathogenic variant carrier status for earlier age of onset of breast cancer among indigenous Arab breast cancer patients.

Profiling of pharmacogenomic variants in CYP2D6 and DPYD in indigenous Arab breast cancer patients.

Aim: The indigenous Arab population is underrepresented in genomic studies and the landscape of actionable pharmacogenomic variants among Arab breast cancer patients remains unclear. Materials & methods: Exome sequencing was performed on 220 unselected Arab female breast cancer patients and germline variants in CYP2D6 and DPYD were profiled using a deep learning method. Results: In total, 13 (5.9%) patients had clinically actionable results and 56 (25.5%) carried an allele in DYPD or CYP2D6 with unknown impact on drug metabolism. In addition, four unique novel missense variants were discovered, including one in CYP2D6 (p.Arg64Leu) with high predicted pathogenicity. Conclusion: A nontrivial subset of Arab breast cancer patients can potentially benefit from pretreatment molecular profiling, and further study is needed to improve characterization of the pharmacogenomic landscape.

Overcoming Barriers to Tumor Genomic Profiling through Direct-to-Patient Outreach.

PURPOSE: To overcome barriers to genomic testing for patients with rare cancers, we initiated a program to offer free clinical tumor genomic testing worldwide to patients with select rare cancer subtypes. EXPERIMENTAL DESIGN: Patients were recruited through social media outreach and engagement with disease-specific advocacy groups, with a focus on patients with histiocytosis, germ cell tumors (GCT), and pediatric cancers. Tumors were analyzed using the MSK-IMPACT next-generation sequencing assay with the return of results to patients and their local physicians. Whole-exome recapture was performed for female patients with GCTs to define the genomic landscape of this rare cancer subtype. RESULTS: A total of 333 patients were enrolled, and tumor tissue was received for 288 (86.4%), with 250 (86.8%) having tumor DNA of sufficient quality for MSK-IMPACT testing. Eighteen patients with histiocytosis have received genomically guided therapy to date, of whom 17 (94%) have had clinical benefit with a mean treatment duration of 21.7 months (range, 6-40+). Whole-exome sequencing of ovarian GCTs identified a subset with haploid genotypes, a phenotype rarely observed in other cancer types. Actionable genomic alterations were rare in ovarian GCT (28%); however, 2 patients with ovarian GCTs with squamous transformation had high tumor mutational burden, one of whom had a complete response to pembrolizumab. CONCLUSIONS: Direct-to-patient outreach can facilitate the assembly of cohorts of rare cancers of sufficient size to define their genomic landscape. By profiling tumors in a clinical laboratory, results could be reported to patients and their local physicians to guide treatment. See related commentary by Desai and Subbiah, p. 2339.

Analysis of evolutionary dynamics and clonal architecture in prostate cancer.

The extent to which clinical and genomic characteristics associate with prostate cancer clonal architecture, tumor evolution, and therapeutic response remains unclear. Here, we reconstructed the clonal architecture and evolutionary trajectories of 845 prostate cancer tumors with harmonized clinical and molecular data. We observed that tumors from patients who self-reported as Black had more linear and monoclonal architectures, despite these men having higher rates of biochemical recurrence. This finding contrasts with prior observations relating polyclonal architecture to adverse clinical outcomes. Additionally, we utilized a novel approach to mutational signature analysis that leverages clonal architecture to uncover additional cases of homologous recombination and mismatch repair deficiency in primary and metastatic tumors and link the origin of mutational signatures to specific subclones. Broadly, prostate cancer clonal architecture analysis reveals novel biological insights that may be immediately clinically actionable and provide multiple opportunities for subsequent investigation. Statement of significance: Tumors from patients who self-reported as Black demonstrate linear and monoclonal evolutionary trajectories yet experience higher rates of biochemical recurrence. In addition, analysis of clonal and subclonal mutational signatures identifies additional tumors with potentially actionable alterations such as deficiencies in mismatch repair and homologous recombination.

Integrative Analysis of Germline Rare Variants in Clear and Non-Clear Cell Renal Cell Carcinoma.

IMPORTANCE: RCC encompasses a set of histologically distinct cancers with a high estimated genetic heritability, of which only a portion is currently explained. Previous rare germline variant studies in RCC have usually pooled clear and non-clear cell RCCs and have not adequately accounted for population stratification that may significantly impact the interpretation and discovery of certain candidate risk genes. OBJECTIVE: To evaluate the enrichment of germline PVs in established cancer-predisposing genes (CPGs) in clear cell and non-clear cell RCC patients compared to cancer-free controls using approaches that account for population stratification and to identify unconventional types of germline RCC risk variants that confer an increased risk of developing RCC. DESIGN SETTING AND PARTICIPANTS: In 1,436 unselected RCC patients with sufficient data quality, we systematically identified rare germline PVs, cryptic splice variants, and copy number variants (CNVs). From this unselected cohort, 1,356 patients were ancestry-matched with 16,512 cancer-free controls, and gene-level enrichment of rare germline PVs were assessed in 143 CPGs, followed by an investigation of somatic events in matching tumor samples. MAIN OUTCOMES AND MEASURES: Gene-level burden of rare germline PVs, identification of secondary somatic events accompanying the germline PVs, and characterization of less-explored types of rare germline PVs in RCC patients. RESULTS: In clear cell RCC (n = 976 patients), patients exhibited significantly higher prevalence of PVs in VHL compared to controls (OR: 39.1, 95% CI: 7.01-218.07, p-value:4.95e-05, q-value:0.00584). In non-clear cell RCC (n = 380 patients), patients carried enriched burden of PVs in FH (OR: 77.9, 95% CI: 18.68-324.97, p-value:1.55e-08, q-value: 1.83e-06) and MET (OR: 1.98e11, 95% CI: 0-inf, p-value: 2.07e-05, q-value: 3.50e-07). In a CHEK2-focused analysis with European cases and controls, clear cell RCC patients (n=906 European patients) harbored nominal enrichment of the previously reported low-penetrance CHEK2 variants, p.Ile157Thr (OR:1.84, 95% CI: 1.00-3.36, p-value:0.049) and p.Ser428Phe (OR:5.20, 95% CI: 1.00-26.40, p-value:0.045) while non-clear cell RCC patients (n=295 European patients) exhibited nominal enrichment of CHEK2 LOF germline PVs (OR: 3.51, 95% CI: 1.10-11.10, p-value: 0.033). RCC patients with germline PVs in FH, MET, and VHL exhibited significantly earlier age of cancer onset compared to patients without any germline PVs in CPGs (Mean: 46.0 vs 60.2 years old, Tukey adjusted p-value < 0.0001), and more than half had secondary somatic events affecting the same gene (n=10/15, 66.7%, 95% CI: 38.7-87.0%). Conversely, patients with rare germline PVs in CHEK2 exhibited a similar age of disease onset to patients without any identified germline PVs in CPGs (Mean: 60.1 vs 60.2 years old, Tukey adjusted p-value: 0.99), and only 30.4% of the patients carried secondary somatic events in CHEK2 (n=7/23, 95% CI: 14.1-53.0%). Finally, rare pathogenic germline cryptic splice variants underexplored in RCC were identified in SDHA and TSC1, and rare pathogenic germline CNVs were found in 18 patients, including CNVs in FH, SDHA, and VHL. CONCLUSIONS AND RELEVANCE: This systematic analysis supports the existing link between several RCC risk genes and elevated RCC risk manifesting in earlier age of RCC onset. Our analysis calls for caution when assessing the role of germline PVs in CHEK2 due to the burden of founder variants with varying population frequency in different ancestry groups. It also broadens the definition of the RCC germline landscape of pathogenicity to incorporate previously understudied types of germline variants, such as cryptic splice variants and CNVs.

miRNA Expression Associated with HbF in Saudi Sickle Cell Anemia.

Background and Objectives: Sickle cell anemia (SCA) is a hereditary monogenic disease due to a single ß-globin gene mutation that codes for the production of sickle hemoglobin. Its phenotype is modulated by fetal hemoglobin (HbF), a product of γ-globin genes. Exploring the molecules that regulate γ-globin genes at both transcriptional and translational levels, including microRNA (miRNA), might help identify alternative therapeutic targets. Materials and Methods: Using next-generation sequencing we identified pre-miRNAs and mature miRNA expression signatures associated with different HbF levels in patients homozygous for the sickle hemoglobin gene. The involvement of identified miRNAs in potential SCD-related pathways was investigated with the DIANA TOOL and miRWalk 2.0 database. Results: miR-184 were most highly upregulated in reticulocytes. miR-3609 and miR-483-5p were most highly downregulated in sickle cell anemia with high HbF. miR-370-3p that regulates LIN28A, and miR-451a which is effective in modulating α- and ß- globin levels were also significantly upregulated. miRNA targeted gene pathway interaction identified BCL7A, BCL2L1, LIN28A, KLF6, GATA6, solute carrier family genes and ZNF genes associated with erythropoiesis, cell cycle regulation, glycosphingolipid biosynthesis, cAMP, cGMP-PKG, mTOR, MAPK and PI3K-AKT signaling pathways and cancer pathways. Conclusions: miRNA signatures and their target genes identified novel miRNAs that could regulate fetal hemoglobin production and might be exploited therapeutically.

A patient-driven clinicogenomic partnership for metastatic prostate cancer.

Molecular profiling studies have enabled discoveries for metastatic prostate cancer (MPC) but have predominantly occurred in academic medical institutions and involved non-representative patient populations. We established the Metastatic Prostate Cancer Project (MPCproject, mpcproject.org), a patient-partnered initiative to involve patients with MPC living anywhere in the US and Canada in molecular research. Here, we present results from our partnership with the first 706 MPCproject participants. While 41% of patient partners live in rural, physician-shortage, or medically underserved areas, the MPCproject has not yet achieved racial diversity, a disparity that demands new initiatives detailed herein. Among molecular data from 333 patient partners (572 samples), exome sequencing of 63 tumor and 19 cell-free DNA (cfDNA) samples recapitulated known findings in MPC, while inexpensive ultra-low-coverage sequencing of 318 cfDNA samples revealed clinically relevant AR amplifications. This study illustrates the power of a growing, longitudinal partnership with patients to generate a more representative understanding of MPC.

Germline predisposition to pediatric Ewing sarcoma is characterized by inherited pathogenic variants in DNA damage repair genes.

More knowledge is needed regarding germline predisposition to Ewing sarcoma to inform biological investigation and clinical practice. Here, we evaluated the enrichment of pathogenic germline variants in Ewing sarcoma relative to other pediatric sarcoma subtypes, as well as patterns of inheritance of these variants. We carried out European-focused and pan-ancestry case-control analyses to screen for enrichment of pathogenic germline variants in 141 established cancer predisposition genes in 1,147 individuals with pediatric sarcoma diagnoses (226 Ewing sarcoma, 438 osteosarcoma, 180 rhabdomyosarcoma, and 303 other sarcoma) relative to identically processed cancer-free control individuals. Findings in Ewing sarcoma were validated with an additional cohort of 430 individuals, and a subset of 301 Ewing sarcoma parent-proband trios was analyzed for inheritance patterns of identified pathogenic variants. A distinct pattern of pathogenic germline variants was seen in Ewing sarcoma relative to other sarcoma subtypes. FANCC was the only gene with an enrichment signal for heterozygous pathogenic variants in the European Ewing sarcoma discovery cohort (three individuals, OR 12.6, 95% CI 3.0-43.2, p = 0.003, FDR = 0.40). This enrichment in FANCC heterozygous pathogenic variants was again observed in the European Ewing sarcoma validation cohort (three individuals, OR 7.0, 95% CI 1.7-23.6, p = 0.014), representing a broader importance of genes involved in DNA damage repair, which were also nominally enriched in individuals with Ewing sarcoma. Pathogenic variants in DNA damage repair genes were acquired through autosomal inheritance. Our study provides new insight into germline risk factors contributing to Ewing sarcoma pathogenesis.

Inherited TP53 Variants and Risk of Prostate Cancer.

BACKGROUND: Inherited germline TP53 pathogenic and likely pathogenic variants (gTP53) cause autosomal dominant multicancer predisposition including Li-Fraumeni syndrome (LFS). However, there is no known association of prostate cancer with gTP53. OBJECTIVE: To determine whether gTP53 predisposes to prostate cancer. DESIGN, SETTING, AND PARTICIPANTS: This multi-institutional retrospective study characterizes prostate cancer incidence in a cohort of LFS males and gTP53 prevalence in a prostate cancer cohort. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We evaluated the spectrum of gTP53 variants and clinical features associated with prostate cancer. RESULTS AND LIMITATIONS: We identified 31 prostate cancer cases among 163 adult LFS males, including 26 of 54 aged ≥50 yr. Among 117 LFS males without prostate cancer at the time of genetic testing, six were diagnosed with prostate cancer over a median (interquartile range [IQR]) of 3.0 (1.3-7.2) yr of follow-up, a 25-fold increased risk (95% confidence interval [CI] 9.2-55; p < 0.0001). We identified gTP53 in 38 of 6850 males (0.6%) in the prostate cancer cohort, a relative risk 9.1-fold higher than that of population controls (95% CI 6.2-14; p < 0.0001; gnomAD). We observed hotspots at the sites of attenuated variants not associated with classic LFS. Two-thirds of available gTP53 prostate tumors had somatic inactivation of the second TP53 allele. Among gTP53 prostate cancer cases in this study, the median age at diagnosis was 56 (IQR: 51-62) yr, 44% had Gleason ≥8 tumors, and 29% had advanced disease at diagnosis. CONCLUSIONS: Complementary analyses of prostate cancer incidence in LFS males and gTP53 prevalence in prostate cancer cohorts suggest that gTP53 predisposes to aggressive prostate cancer. Prostate cancer should be considered as part of LFS screening protocols and TP53 considered in germline prostate cancer susceptibility testing. PATIENT SUMMARY: Inherited pathogenic variants in the TP53 gene are likely to predispose men to aggressive prostate cancer.

Biologically informed deep neural network for prostate cancer discovery.

The determination of molecular features that mediate clinically aggressive phenotypes in prostate cancer remains a major biological and clinical challenge1,2. Recent advances in interpretability of machine learning models as applied to biomedical problems may enable discovery and prediction in clinical cancer genomics3-5. Here we developed P-NET-a biologically informed deep learning model-to stratify patients with prostate cancer by treatment-resistance state and evaluate molecular drivers of treatment resistance for therapeutic targeting through complete model interpretability. We demonstrate that P-NET can predict cancer state using molecular data with a performance that is superior to other modelling approaches. Moreover, the biological interpretability within P-NET revealed established and novel molecularly altered candidates, such as MDM4 and FGFR1, which were implicated in predicting advanced disease and validated in vitro. Broadly, biologically informed fully interpretable neural networks enable preclinical discovery and clinical prediction in prostate cancer and may have general applicability across cancer types.

Molecular features of exceptional response to neoadjuvant anti-androgen therapy in high-risk localized prostate cancer.

High-risk localized prostate cancer (HRLPC) is associated with a substantial risk of recurrence and disease mortality. Recent clinical trials have shown that intensifying anti-androgen therapies administered before prostatectomy can induce pathologic complete responses or minimal residual disease, called exceptional response, although the molecular determinants of these clinical outcomes are largely unknown. Here, we perform whole-exome and transcriptome sequencing on pre-treatment multi-regional tumor biopsies from exceptional responders (ERs) and non-responders (NRs, pathologic T3 or lymph node-positive disease) to intensive neoadjuvant anti-androgen therapies. Clonal SPOP mutation and SPOPL copy-number loss are exclusively observed in ERs, while clonal TP53 mutation and PTEN copy-number loss are exclusively observed in NRs. Transcriptional programs involving androgen signaling and TGF-ß signaling are enriched in ERs and NRs, respectively. These findings may guide prospective validation studies of these molecular features in large HRLPC clinical cohorts treated with neoadjuvant anti-androgens to improve patient stratification.

Clinical Multigene Testing for Prostate Cancer.

Germline genetic testing for prostate cancer (PC) is increasingly important as the clinical utility of germline variants in this patient population is understood better. To better characterize the clinical landscape of germline testing in PC, published clinical cohorts of PC who underwent clinical germline genetic analysis at point of care are reviewed. Limitations and heterogeneity of these cohorts are highlighted and pathogenic results with established or potential clinical utility in PC noted. The need for additional germline genetic studies is underscored, because the number of PC patients studied lags greatly behind the high prevalence of the disease.

Evaluating the molecular diagnostic yield of joint genotyping-based approach for detecting rare germline pathogenic and putative loss-of-function variants.

PURPOSE: Cohort-based germline variant characterization is the standard approach for pathogenic variant discovery in clinical and research samples. However, the impact of cohort size on the molecular diagnostic yield of joint genotyping is largely unknown. METHODS: Head-to-head comparison of the molecular diagnostic yield of joint genotyping in two cohorts of 239 cancer patients in the absence and then in the presence of 100 additional germline exomes. RESULTS: In 239 testicular cancer patients, 4 (7.4%, 95% confidence interval [CI]: 2.1-17.9) of 54 pathogenic variants in the cancer predisposition and American College of Medical Genetics and Genomics (ACMG) genes were missed by one or both computational runs of joint genotyping. Similarly, 8 (12.1%, 95% CI: 5.4-22.5) of 66 pathogenic variants in these genes were undetected by joint genotyping in another independent cohort of 239 breast cancer patients. An exome-wide analysis of putative loss-of-function (pLOF) variants in the testicular cancer cohort showed that 162 (8.2%, 95% CI: 7.1-9.6) pLOF variants were only detected in one analysis run but not the other, while 433 (22.0%, 95% CI: 20.2-23.9%) pLOF variants were filtered out by both analyses despite having sufficient sequencing coverage. CONCLUSION: Our analysis of the standard germline variant detection method highlighted a substantial impact of concurrently analyzing additional genomic data sets on the ability to detect clinically relevant germline pathogenic variants.

Integrating molecular profiles into clinical frameworks through the Molecular Oncology Almanac to prospectively guide precision oncology.

Tumor molecular profiling of single gene-variant ('first-order') genomic alterations informs potential therapeutic approaches. Interactions between such first-order events and global molecular features (for example, mutational signatures) are increasingly associated with clinical outcomes, but these 'second-order' alterations are not yet accounted for in clinical interpretation algorithms and knowledge bases. We introduce the Molecular Oncology Almanac (MOAlmanac), a paired clinical interpretation algorithm and knowledge base to enable integrative interpretation of multimodal genomic data for point-of-care decision making and translational-hypothesis generation. We benchmarked MOAlmanac to a first-order interpretation method across multiple retrospective cohorts and observed an increased number of clinical hypotheses from evaluation of molecular features and profile-to-cell line matchmaking. When applied to a prospective precision oncology trial cohort, MOAlmanac nominated a median of two therapies per patient and identified therapeutic strategies administered in 47% of patients. Overall, we present an open-source computational method for integrative clinical interpretation of individualized molecular profiles.

Detection of Pathogenic Variants With Germline Genetic Testing Using Deep Learning vs Standard Methods in Patients With Prostate Cancer and Melanoma.

Importance: Less than 10% of patients with cancer have detectable pathogenic germline alterations, which may be partially due to incomplete pathogenic variant detection. Objective: To evaluate if deep learning approaches identify more germline pathogenic variants in patients with cancer. Design, Setting, and Participants: A cross-sectional study of a standard germline detection method and a deep learning method in 2 convenience cohorts with prostate cancer and melanoma enrolled in the US and Europe between 2010 and 2017. The final date of clinical data collection was December 2017. Exposures: Germline variant detection using standard or deep learning methods. Main Outcomes and Measures: The primary outcomes included pathogenic variant detection performance in 118 cancer-predisposition genes estimated as sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The secondary outcomes were pathogenic variant detection performance in 59 genes deemed actionable by the American College of Medical Genetics and Genomics (ACMG) and 5197 clinically relevant mendelian genes. True sensitivity and true specificity could not be calculated due to lack of a criterion reference standard, but were estimated as the proportion of true-positive variants and true-negative variants, respectively, identified by each method in a reference variant set that consisted of all variants judged to be valid from either approach. Results: The prostate cancer cohort included 1072 men (mean [SD] age at diagnosis, 63.7 [7.9] years; 857 [79.9%] with European ancestry) and the melanoma cohort included 1295 patients (mean [SD] age at diagnosis, 59.8 [15.6] years; 488 [37.7%] women; 1060 [81.9%] with European ancestry). The deep learning method identified more patients with pathogenic variants in cancer-predisposition genes than the standard method (prostate cancer: 198 vs 182; melanoma: 93 vs 74); sensitivity (prostate cancer: 94.7% vs 87.1% [difference, 7.6%; 95% CI, 2.2% to 13.1%]; melanoma: 74.4% vs 59.2% [difference, 15.2%; 95% CI, 3.7% to 26.7%]), specificity (prostate cancer: 64.0% vs 36.0% [difference, 28.0%; 95% CI, 1.4% to 54.6%]; melanoma: 63.4% vs 36.6% [difference, 26.8%; 95% CI, 17.6% to 35.9%]), PPV (prostate cancer: 95.7% vs 91.9% [difference, 3.8%; 95% CI, -1.0% to 8.4%]; melanoma: 54.4% vs 35.4% [difference, 19.0%; 95% CI, 9.1% to 28.9%]), and NPV (prostate cancer: 59.3% vs 25.0% [difference, 34.3%; 95% CI, 10.9% to 57.6%]; melanoma: 80.8% vs 60.5% [difference, 20.3%; 95% CI, 10.0% to 30.7%]). For the ACMG genes, the sensitivity of the 2 methods was not significantly different in the prostate cancer cohort (94.9% vs 90.6% [difference, 4.3%; 95% CI, -2.3% to 10.9%]), but the deep learning method had a higher sensitivity in the melanoma cohort (71.6% vs 53.7% [difference, 17.9%; 95% CI, 1.82% to 34.0%]). The deep learning method had higher sensitivity in the mendelian genes (prostate cancer: 99.7% vs 95.1% [difference, 4.6%; 95% CI, 3.0% to 6.3%]; melanoma: 91.7% vs 86.2% [difference, 5.5%; 95% CI, 2.2% to 8.8%]). Conclusions and Relevance: Among a convenience sample of 2 independent cohorts of patients with prostate cancer and melanoma, germline genetic testing using deep learning, compared with the current standard genetic testing method, was associated with higher sensitivity and specificity for detection of pathogenic variants. Further research is needed to understand the relevance of these findings with regard to clinical outcomes.

Clonal hematopoiesis is associated with adverse outcomes in multiple myeloma patients undergoing transplant.

Multiple myeloma (MM) is a plasma-cell neoplasm that is treated with high-dose chemotherapy, autologous stem cell transplant (ASCT) and long-term immunomodulatory drug (IMiD) maintenance. The presence of somatic mutations in the peripheral blood is termed clonal hematopoiesis of indeterminate potential (CHIP) and is associated with adverse outcomes. Targeted sequencing of the stem cell product from 629 MM patients treated by ASCT at the Dana-Farber Cancer Institute (2003-2011) detects CHIP in 136/629 patients (21.6%). The most commonly mutated genes are DNMT3A, TET2, TP53, ASXL1 and PPM1D. Twenty-one from fifty-six patients (3.3%) receiving first-line IMiD maintenance develop a therapy-related myeloid neoplasm (TMN). However, regardless of CHIP status, the use of IMiD maintenance associates with improved PFS and OS. In those not receiving IMiD maintenance, CHIP is associated with decreased overall survival (OS) (HR:1.34, p = 0.02) and progression free survival (PFS) (HR:1.45, p < 0.001) due to an increase in MM progression.

Implementation of Germline Testing for Prostate Cancer: Philadelphia Prostate Cancer Consensus Conference 2019.

PURPOSE: Germline testing (GT) is a central feature of prostate cancer (PCA) treatment, management, and hereditary cancer assessment. Critical needs include optimized multigene testing strategies that incorporate evolving genetic data, consistency in GT indications and management, and alternate genetic evaluation models that address the rising demand for genetic services. METHODS: A multidisciplinary consensus conference that included experts, stakeholders, and national organization leaders was convened in response to current practice challenges and to develop a genetic implementation framework. Evidence review informed questions using the modified Delphi model. The final framework included criteria with strong (> 75%) agreement (Recommend) or moderate (50% to 74%) agreement (Consider). RESULTS: Large germline panels and somatic testing were recommended for metastatic PCA. Reflex testing-initial testing of priority genes followed by expanded testing-was suggested for multiple scenarios. Metastatic disease or family history suggestive of hereditary PCA was recommended for GT. Additional family history and pathologic criteria garnered moderate consensus. Priority genes to test for metastatic disease treatment included BRCA2, BRCA1, and mismatch repair genes, with broader testing, such as ATM, for clinical trial eligibility. BRCA2 was recommended for active surveillance discussions. Screening starting at age 40 years or 10 years before the youngest PCA diagnosis in a family was recommended for BRCA2 carriers, with consideration in HOXB13, BRCA1, ATM, and mismatch repair carriers. Collaborative (point-of-care) evaluation models between health care and genetic providers was endorsed to address the genetic counseling shortage. The genetic evaluation framework included optimal pretest informed consent, post-test discussion, cascade testing, and technology-based approaches. CONCLUSION: This multidisciplinary, consensus-driven PCA genetic implementation framework provides novel guidance to clinicians and patients tailored to the precision era. Multiple research, education, and policy needs remain of importance.