Establishing a Framework for the Clinical Translation of Germline Findings in Precision Oncology

Whole genome and transcriptome integrated analyses guide clinical care of pediatric poor prognosis cancers

The role for routine whole genome and transcriptome analysis (WGTA) for poor prognosis pediatric cancers remains undetermined. Here, we characterize somatic mutations, structural rearrangements, copy number variants, gene expression, immuno-profiles and germline cancer predisposition variants in children and adolescents with relapsed, refractory or poor prognosis malignancies who underwent somatic WGTA and matched germline sequencing. Seventy-nine participants with a median age at enrollment of 8.8 y (range 6 months to 21.2 y) are included. Germline pathogenic/likely pathogenic variants are identified in 12% of participants, of which 60% were not known prior. Therapeutically actionable variants are identified by targeted gene report and whole genome in 32% and 62% of participants, respectively, and increase to 96% after integrating transcriptome analyses. Thirty-two molecularly informed therapies are pursued in 28 participants with 54% achieving a clinical benefit rate; objective response or stable disease ≥6 months. Integrated WGTA identifies therapeutically actionable variants in almost all tumors and are directly translatable to clinical care of children with poor prognosis cancers.

Homologous recombination deficiency signatures in gastrointestinal and thoracic cancers correlate with platinum therapy duration

There is emerging evidence about the predictive role of homologous recombination deficiency (HRD), but this is less defined in gastrointestinal (GI) and thoracic malignancies. We reviewed whole genome (WGS) and transcriptomic (RNA-Seq) data from advanced GI and thoracic cancers in the Personalized OncoGenomics trial (NCT02155621) to evaluate HRD scores and single base substitution (SBS)3, which is associated with BRCA1/2 mutations and potentially predictive of defective HRD. HRD scores were calculated by sum of loss of heterozygosity, telomeric allelic imbalance, and large-scale state transitions scores. Regression analyses examined the association between HRD and time to progression on platinum (TTPp). We included 223 patients with GI (n = 154) or thoracic (n = 69) malignancies. TTPp was associated with SBS3 (p < 0.01) but not HRD score in patients with GI malignancies, whereas neither was associated with TTPp in thoracic malignancies. Tumors with gBRCA1/2 mutations and a somatic second alteration exhibited high SBS3 and HRD scores, but these signatures were also present in several tumors with germline but no somatic second alterations, suggesting silencing of the wild-type allele or BRCA1/2 haploinsufficiency. Biallelic inactivation of an HR gene, including loss of XRCC2 and BARD1, was identified in BRCA1/2 wild-type HRD tumors and these patients had prolonged response to platinum. Thoracic cases with high HRD score were associated with high RECQL5 expression (p ≤ 0.025), indicating another potential mechanism of HRD. SBS3 was more strongly associated with TTPp in patients with GI malignancies and may be complementary to using HRD and BRCA status in identifying patients who benefit from platinum therapy.

Cancer prevention in cancer predisposition syndromes: A protocol for testing the feasibility of building a hereditary cancer research registry and nurse navigator follow up model

Monogenic, high penetrance syndromes, conferring an increased risk of malignancies in multiple organs, are important contributors to the hereditary burden of cancer. Early detection and risk reduction strategies in patients with a cancer predisposition syndrome can save their lives. However, despite evidence supporting the benefits of early detection and risk reduction strategies, most Canadian jurisdictions have not implemented programmatic follow up of these patients. In our study site in the province of Newfoundland and Labrador (NL), Canada, there is no centralized, provincial registry of high-risk individuals. There is no continuity or coordination of care providing cancer genetics expertise and no process to ensure that patients are referred to the appropriate specialists or risk management interventions. This paper describes a study protocol to test the feasibility of obtaining and analyzing patient risk management data, specifically patients affected by hereditary breast ovarian cancer syndrome (HBOC; BRCA 1 and BRCA 2 genes) and Lynch syndrome (LS; MLH1, MSH2, MSH6, and PMS2 genes). Through a retrospective cohort study, we will describe these patients' adherence to risk management guidelines and test its relationship to health outcomes, including cancer incidence and stage. Through a qualitative interviews, we will determine the priorities and preferences of patients with any inherited cancer mutation for a follow up navigation model of risk management. Study data will inform a subsequent funding application focused on creating and evaluating a research registry and follow up nurse navigation model. It is not currently known what proportion of cancer mutation carriers are receiving care according to guidelines. Data collected in this study will provide clinical uptake and health outcome information so gaps in care can be identified. Data will also provide patient preference information to inform ongoing and planned research with cancer mutation carriers.

An integrated somatic and germline approach to aid interpretation of germline variants of uncertain significance in cancer susceptibility genes

Genomic profiles of tumors are often unique and represent characteristic mutational signatures defined by DNA damage or DNA repair response processes. The tumor-derived somatic information has been widely used in therapeutic applications, but it is grossly underutilized in the assessment of germline genetic variants. Here, we present a comprehensive approach for evaluating the pathogenicity of germline variants in cancer using an integrated interpretation of somatic and germline genomic data. We have previously demonstrated the utility of this integrated approach in the reassessment of pathogenic germline variants in selected cancer patients with unexpected or non-syndromic phenotypes. The application of this approach is presented in the assessment of rare variants of uncertain significance (VUS) in Lynch-related colon cancer, hereditary paraganglioma-pheochromocytoma syndrome, and Li-Fraumeni syndrome. Using this integrated method, germline VUS in PMS2, MSH6, SDHC, SHDA, and TP53 were assessed in 16 cancer patients after genetic evaluation. Comprehensive clinical criteria, somatic signature profiles, and tumor immunohistochemistry were used to re-classify VUS by upgrading or downgrading the variants to likely or unlikely actionable categories, respectively. Going forward, collation of such germline variants and creation of cross-institutional knowledgebase datasets that include integrated somatic and germline data will be crucial for the assessment of these variants in a larger cancer cohort.

Whole genome and transcriptome analysis enhances precision cancer treatment options

BACKGROUND

Recent advances are enabling delivery of precision genomic medicine to cancer clinics. While the majority of approaches profile panels of selected genes or hotspot regions, comprehensive data provided by whole genome and transcriptome sequencing and analysis (WGTA) presents an opportunity to align a much larger proportion of patients to therapies.

PATIENTS AND METHODS

Samples from 570 patients with advanced or metastatic cancer of diverse types enrolled in the Personalized OncoGenomics (POG) program underwent WGTA. DNA-based data, including mutations, copy number, and mutation signatures, were combined with RNA-based data, including gene expression and fusions, to generate comprehensive WGTA profiles. A multidisciplinary molecular tumour board used WGTA profiles to identify and prioritize clinically actionable alterations and inform therapy. Patient responses to WGTA-informed therapies were collected.

RESULTS

Clinically actionable targets were identified for 83% of patients, 37% of whom received WGTA-informed treatments. RNA expression data were particularly informative, contributing to 67% of WGTA-informed treatments; 25% of treatments were informed by RNA expression alone. Of a total 248 WGTA-informed treatments, 46% resulted in clinical benefit. RNA expression data were comparable to DNA-based mutation and copy number data in aligning to clinically beneficial treatments. Genome signatures also guided therapeutics including platinum, PARP inhibitors, and immunotherapies. Patients accessed WGTA-informed treatments through clinical trials (19%), off-label use (35%), and as standard therapies (46%) including those which would not otherwise have been the next choice of therapy, demonstrating the utility of genomic information to direct use of chemotherapies as well as targeted therapies.

CONCLUSIONS

Integrating RNA expression and genome data illuminated treatment options that resulted in 46% of treated patients experiencing positive clinical benefit, supporting the use of comprehensive WGTA profiling in clinical cancer care.

CLINICAL TRIAL NUMBER

NCT02155621.

Whole-genome and transcriptome analysis of advanced adrenocortical cancer highlights multiple alterations affecting epigenome and DNA repair pathways

Adrenocortical cancer (ACC) is a rare cancer of the adrenal gland. Several driver mutations have been identified in both primary and metastatic ACCs, but the therapeutic options are still limited. We performed whole-genome and transcriptome sequencing on seven patients with metastatic ACC. Integrative analysis of mutations, RNA expression changes, mutation signature, and homologous recombination deficiency (HRD) analysis was performed. Mutations affecting CTNNB1 and TP53 and frequent loss of heterozygosity (LOH) events were observed in our cohort. Alterations affecting genes involved in cell cycle (RB1, CDKN2A, CDKN2B), DNA repair pathways (MUTYH, BRCA2, ATM, RAD52, MLH1, MSH6), and telomere maintenance (TERF2 and TERT) consisting of somatic and germline mutations, structural variants, and expression outliers were also observed. HRDetect, which aggregates six HRD-associated mutation signatures, identified a subset of cases as HRD. Genomic alterations affecting genes involved in epigenetic regulation were also identified, including structural variants (SWI/SNF genes and histone methyltransferases), and copy gains and concurrent high expression of KDM5A, which may contribute to epigenomic deregulation. Findings from this study highlight HRD and epigenomic pathways as potential therapeutic targets and suggest a subgroup of patients may benefit from a diverse array of molecularly targeted therapies in ACC, a rare disease in urgent need of therapeutic strategies.

Drug repurposing for cancer therapy in the era of precision medicine

Drug repurposing refers to the identification of clinically approved drugs, with the known safety profiles and defined pharmacokinetic properties, to new indications. Despite the advances in oncology research, cancers are still associated with the most unmet medical needs. Drug repurposing has emerged as a useful approach for the search for effective and durable cancer treatment. It may also represent a promising strategy to facilitate precision cancer treatment and to overcome drug resistance. The repurposing of non-cancer drugs for precision oncology effectively extends the inventory of actionable molecular targets and thus increases the number of patients who may benefit from precision cancer treatment. In cancer types where genetic heterogeneity is so high that it is not feasible to identify strong repurposed drug candidates for standard treatment, the precision oncology approach offers individual patients access to novel treatment options. For repurposed candidates with low potency, a combination of multiple repurposed drugs may produce a synergistic therapeutic effect. Precautions should be taken when combining repurposed drugs with anticancer agents to avoid detrimental drug-drug interactions and unwanted side effects. New multifactorial data analysis and artificial intelligence methods are needed to untangle the complex association of molecular signatures influencing specific cancer subtypes to facilitate drug repurposing in precision oncology.