Comparison of the Modified IHC4 Score and 21-Gene Recurrence Score Assay in Patients with Estrogen Receptor-Positive Breast Cancer

Introduction: Not only the 21-gene recurrence score (RS) assay but also online prognostic tools and immunohistochemical prognostic models predict chemotherapy benefits for women with early breast cancer. Multi-gene assays, including Oncotype DX, are expensive and not covered by insurance in some countries. Methods: In this study, we retrospectively analyzed a series of 155 patients with estrogen receptor-positive primary breast cancer for whom an Oncotype DX assay was performed between January 2016 and August 2021. The patients’ modified immunohistochemical marker (mIHC4) scores were calculated on the basis of their pathological reports. The correlations of the RS with the online tool PREDICT and mIHC4 scores were evaluated. Results: Of the patients, 43.9% were premenopausal, 147 (94.8%) had T1 or T2 tumor, and 55.5% had no positive lymph nodes. Low (0–10), intermediate (11–25), and high RSs (26–100) were obtained in 16.1%, 61.9%, and 21.9% of the patients, respectively. The RS showed no correlation with the PREDICT score (r = 0.2720) but correlated with the mIHC4 score (r = 0.6356). In addition, a stronger correlation was observed in the patients with no node involvement and in the postmenopausal patients (r = 0.6609 and r = 0.7277, respectively). Conclusions: A relatively strong correlation was observed between the RS and the mIHC4 score. The mIHC4 score is a potentially easy and useful tool to guide adjuvant chemotherapy decision making especially for postmenopausal patients with no node involvement if a genomic test could not be performed for some reason.

Genomic health data generation in the UK: a 360 view

In the UK, genomic health data is being generated in three major contexts: the healthcare system (based on clinical indication), in large scale research programmes, and for purchasers of direct-to-consumer genetic tests. The recently delivered hybrid clinical/research programme, 100,000 Genomes Project set the scene for a new Genomic Medicine Service, through which the National Health Service aims to deliver consistent and equitable care informed by genomics, while providing data to inform academic and industry research and development. In parallel, a large scale research study, Our Future Health, has UK Government and Industry investment and aims to recruit 5 million volunteers to support research intended to improve early detection, risk stratification, and early intervention for chronic diseases. To explore how current models of genomic health data generation intersect, and to understand clinical, ethical, legal, policy and social issues arising from this intersection, we conducted a series of five multidisciplinary panel discussions attended by 28 invited stakeholders. Meetings were recorded and transcribed. We present a summary of issues identified: genomic test attributes; reasons for generating genomic health data; individuals’ motivation to seek genomic data; health service impacts; role of genetic counseling; equity; data uses and security; consent; governance and regulation. We conclude with some suggestions for policy consideration.

Primary Ovarian Choriocarcinoma: Rare Entity

Background. Primary pure ovarian choriocarcinoma is a rare aggressive tumor which can be nongestational arising from germ cells or gestational origin. Preoperative diagnosis of extrauterine choriocarcinoma is challenging due to nonspecific clinical presentation. Case Presentation. This article reports primary ovarian choriocarcinoma, likely gestational in a 25-year-old para 2 woman presenting with lower abdominal pain and swelling of two-week duration. Diagnosis was suspected by serum beta-human chorionic gonadotropin and confirmed histologically after surgery. Postoperatively, she was managed with multiple courses of chemotherapy using a bleomycin, etoposide, and cisplatin regimen, and the treatment was effective. Conclusion. In patients with adnexal mass presenting with nonspecific symptoms especially with high Doppler blood flow of the mass on ultrasound evaluation, serum beta-human chorionic gonadotropin determination is recommended before laparotomy. In setups where the genomic test is not available, histological and clinical effort to differentiate gestational versus nongestational choriocarcinoma is useful for specific management decision.

Creation of an Expert Curated Variant List for Clinical Genomic Test Development and Validation: A ClinGen and GeT-RM Collaborative Project

Modern genomic sequencing tests often interrogate large numbers of genes. Identification of appropriate reference materials for development, validation studies, and quality assurance of these tests poses a significant challenge for laboratories. It is difficult to develop and maintain expert knowledge to identify all variants that must be validated to assure analytic and clinical validity. Additionally, it is usually not possible to procure appropriate and characterized genomic DNA reference materials containing the number and scope of variants required. To address these challenges, the Centers for Disease Control and Prevention's Genetic Testing Reference Material Program (GeT-RM) has partnered with the Clinical Genome Resource (ClinGen) to develop a publicly available list of expert curated, clinically important variants. ClinGen Variant Curation Expert Panels nominated 546 variants found in 84 disease associated genes, including common pathogenic and difficult to detect variants. Variant types nominated included 346 SNVs, 104 deletions, 37 CNVs, 25 duplications, 18 deletion-insertions, 5 inversions, 4 insertions, 2 complex rearrangements, 3 in difficult to sequence regions, and 2 fusions. This expert-curated variant list is a resource that provides a foundation for designing comprehensive validation studies and for creating in silico reference materials for clinical genomic test development and validation.

Towards a Responsible Transition to Learning Healthcare Systems in Precision Medicine: Ethical Points to Consider

Learning healthcare systems have recently emerged as a strategy to continuously use experiences and outcomes of clinical care for research purposes in precision medicine. Although it is known that learning healthcare transitions in general raise important ethical challenges, the ethical ramifications of such transitions in the specific context of precision medicine have not extensively been discussed. Here, we describe three levers that institutions can pull to advance learning healthcare systems in precision medicine: (1) changing testing of individual variability (such as genes); (2) changing prescription of treatments on the basis of (genomic) test results; and/or (3) changing the handling of data that link variability and treatment to clinical outcomes. Subsequently, we evaluate how patients can be affected if one of these levers are pulled: (1) patients are tested for different or more factors than before the transformation, (2) patients receive different treatments than before the transformation and/or (3) patients’ data obtained through clinical care are used, or used more extensively, for research purposes. Based on an analysis of the aforementioned mechanisms and how these potentially affect patients, we analyze why learning healthcare systems in precision medicine need a different ethical approach and discuss crucial points to consider regarding this approach.

Gene expression signatures predict response to therapy with growth hormone

Recombinant human growth hormone (r-hGH) is used as a therapeutic agent for disorders of growth including growth hormone deficiency (GHD) and Turner syndrome (TS). Treatment is costly and current methods to model response are inexact. GHD (n = 71) and TS patients (n = 43) were recruited to study response to r-hGH over 5 years. Analysis was performed using 1219 genetic markers and baseline (pre-treatment) blood transcriptome. Random forest was used to determine predictive value of transcriptomic data associated with growth response. No genetic marker passed the stringency criteria for prediction. However, we identified an identical set of genes in both GHD and TS whose expression could be used to classify therapeutic response to r-hGH with a high accuracy (AUC > 0.9). Combining transcriptomic markers with clinical phenotype was shown to significantly reduce predictive error. This work could be translated into a single genomic test linked to a prediction algorithm to improve clinical management. Trial registration numbers: NCT00256126 and NCT00699855.

Identifying Aspects of Public Attitudes Toward Whole Genome Sequencing to Inform the Integration of Genomics into Care

<b><i>Introduction:</i></b> The growth of global sequencing initiatives and commercial genomic test offerings suggests the public will increasingly be confronted with decisions about sequencing. Understanding public attitudes can assist efforts to integrate sequencing into care and inform the development of public education and outreach strategies. <b><i>Methods:</i></b> A 48-item online survey was advertised on Facebook in Eastern Canada and hosted on SurveyMonkey in late 2018. The survey measured public interest in whole genome sequencing and attitudes toward various aspects of sequencing using vignettes, scaled, and open-ended items. <b><i>Results:</i></b> While interest in sequencing was high, critical attitudes were observed. In particular, items measuring features of patient control and choice regarding genomic data were strongly endorsed by respondents. Majority wanted to specify upfront how their data could be used, retain the ability to withdraw their sample at a later date, sign a written consent form, and speak to a genetic counselor prior to sequencing. Concerns about privacy and unauthorized access to data were frequently observed. Education level was the sociodemographic variable most often related to attitude statements such that those with higher levels of education generally displayed more critical attitudes. <b><i>Conclusions:</i></b> Attitudes identified here could be used to inform the development of implementation strategies for genomic medicine. Findings suggest health systems must address patient concerns about privacy, consent practices, and the strong desire to control what happens to their genomic data through public outreach and education. Specific oversight procedures and policies that are clearly communicated to the public will be required.