Progress In Precision Medicine Research Articles

Discrimination Based on Genetic Information in South Asia: An Exploratory Study of Constitutions and Relevant Laws

Abstract The progress in precision medicine has resulted in genomic technology spreading worldwide. This has raised concerns about the ethics of genetic data sharing and privacy. This article focuses on South Asia and first aims to identify, analyze, and understand the laws, regulations, and policies related to genetic data privacy and discrimination in that region. This is accomplished through a qualitative examination of existing laws and policies on privacy rights and a doctrinal analysis of legislation gathered from seven jurisdictions, viz. Bangladesh, Bhutan, India, the Maldives, Nepal, Pakistan, and Sri Lanka. Following the presentation of the country-specific study, the article turns to discussing the study's results, which suggest that the area lacks both national norms and a regional policy specific to the protection of personal genetic data. The article then offers possible reasons for this outcome and suggests that the countries must formulate culturally sensitive regulations and universally applicable legal principles for genetic privacy notwithstanding the existing challenges of poverty, non-uniform demographics, and an absence of political will.

Potential of extracellular space for tissue regeneration in dentistry.

With the proven relationship between oral and general health and the growing aging population, it is pivotal to provide accessible therapeutic approaches to regenerate oral tissues and restore clinical function. However, despite sharing many core concepts with medicine, dentistry has fallen behind the progress in precision medicine and regenerative treatments. Stem cell therapies are a promising avenue for tissue regeneration, however, ethical, safety and cost issues may limit their clinical use. With the significance of paracrine signalling in stem cell and tissue regeneration, extracellular space comprising of the cell secretome, and the extracellular matrix can serve as a potent source for tissue regeneration. Extravesicles are secreted and naturally occurring vesicles with biologically active cargo that can be harvested from the extracellular space. These vesicles have shown great potential as disease biomarkers and can be used in regenerative medicine. As a cell free therapy, secretome and extracellular vesicles can be stored and transferred easily and pose less ethical and safety risks in clinical application. Since there are currently many reviews on the secretome and the biogenesis, characterization and function of extracellular vesicles, here we look at the therapeutic potential of extracellular space to drive oral tissue regeneration and the current state of the field in comparison to regenerative medicine.

Relationship of Methylenetetrahydrofolate Reductase (MTHFR) C677T Variation With Susceptibility of Patients With Ischemic Stroke: A Meta-Analysis.

Discovery and validation of genetic factors for multifactorial and polygenic disorders like stroke are needed to make progress in precision medicine. Although some traditional risk factors for stroke have been identified, they do not fully explain the pathophysiological mechanism of ischemic stroke. The research of genetic risk factors is becoming increasingly relevant in the understanding of stroke mechanisms and the finding of population-specific therapeutic targets. The methylenetetrahydrofolate reductase (MTHFR) gene is involved in homocysteine metabolism, and a high homocysteine level is a risk factor for stroke. Using a meta-analysis technique, we investigated the link between the MTHFR C677T gene polymorphism and the risk of ischemic stroke.We used the electronic databases PubMed, Medline, Embase, and Google Scholar to find articles in the Journal of Stroke. If heterogeneity was more than 50%, pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using a random-effects model; otherwise, a fixed-effects model was used.A total of 67 case-control studies with 17,704 cases and 21,981 controls met our inclusion criteria. The Asian population was represented by 41 studies, whereas the Caucasian population was represented by 26. Under the recessive model, a gene polymorphism at the 677 location of the MTHFR gene is related to an elevated risk of ischemic stroke (OR: 1.29, 95% CI: 1.22-1.37, P < 0.001).People who have the MTHFR C677T gene polymorphism have a greater risk of stroke than people who do not.

AACR Cancer Disparities Progress Report 2022.

AACR Cancer Disparities Progress Report 2022.

Genetic Evaluation for Hereditary Cancer Syndromes Among African Americans: A Critical Review.

While hereditary cancer syndromes have been described and studied for centuries, the completion of the human genome project fueled accelerated progress in precision medicine due to the introduction of genetic testing in the 1990s, creating avenues for tailored treatments and medical management options. However, genetic testing has not benefited everyone equitably, with nearly all of the published work based on individuals of non-Hispanic White/European ancestry. There remains a gap in knowledge regarding the prevalence, penetrance, and manifestations of common hereditary cancer syndromes in the African-American population due to significant disparities in access and uptake of genetic testing. This review summarizes the available literature on genetic testing for breast, colon, and prostate cancers in the African-American population and explores the disparities in access to genetic testing between non-Hispanic White and African-American patients. This article also addresses the barriers to genetic testing and discrepancies in the uptake of recommendations for hereditary cancer syndromes in the African-American population when compared with non-Hispanic Whites. The review offers practice implications for many healthcare providers and demonstrates gaps in the existing knowledge to be addressed in future studies to help eliminate the persisting health disparities faced by the African-American population.

Communicating Precision Medicine Research: Multidisciplinary Teams and Diverse Communities

Introduction: Precision medicine research investigates the differences in individuals’ genetics, environment, and lifestyle to tailor health prevention and treatment options as part of an emerging model of health care delivery. Advancing precision medicine research will require effective communication across a wide range of scientific and health care disciplines and with research participants who represent diverse segments of the population. Methods: A multidisciplinary group convened over the course of a year and developed precision medicine research case examples to facilitate precision medicine research discussions with communities. Results: A shared definition of precision medicine research as well as six case examples of precision medicine research involving genetic risk, pharmacogenetics, epigenetics, the microbiome, mobile health, and electronic health records were developed. Discussion/Conclusion: The precision medicine research definition and case examples can be used as planning tools to establish a shared understanding of the scope of precision medicine research across multidisciplinary teams and with the diverse communities in which precision medicine research will take place. This shared understanding is vital for successful and equitable progress in precision medicine.

Targeting Oncogenic KRAS in Non-Small-Cell Lung Cancer.

Simple Summaryv-Ki-ras2 Kirsten rat sarcoma viral oncogene (KRAS) is the most common driver in NSCLC, and targeting oncogenic KRAS is a major challenge in the treatment of non-small-cell lung cancer (NSCLC). While several covalent KRAS G12C inhibitors have emerged as a novel anti-KRAS therapy, the development of combined therapies involving the targeting of oncogenic KRAS plus other targeted drugs is still required given the vast heterogeneity of KRAS-mutated tumors. In this review, we summarize the biological and immunological characteristics of oncogenic KRAS-driven NSCLC and the preclinical and clinical evidence for mutant KRAS-targeted therapies. We also discuss the mechanisms of resistance to KRAS G12C inhibitors and possible therapeutic strategies to overcome this drug resistance.Recent advances in molecular biology and the resultant identification of driver oncogenes have achieved major progress in precision medicine for non-small-cell lung cancer (NSCLC). v-Ki-ras2 Kirsten rat sarcoma viral oncogene (KRAS) is the most common driver in NSCLC, and targeting KRAS is considerably important. The recent discovery of covalent KRAS G12C inhibitors offers hope for improving the prognosis of NSCLC patients, but the development of combination therapies corresponding to tumor characteristics is still required given the vast heterogeneity of KRAS-mutated NSCLC. In this review, we summarize the current understanding of KRAS mutations regarding the involvement of malignant transformation and describe the preclinical and clinical evidence for targeting KRAS-mutated NSCLC. We also discuss the mechanisms of resistance to KRAS G12C inhibitors and possible combination treatment strategies to overcome this drug resistance.

Assessment of [Ru(bpy)2]3+and [Os(diars)2(bthp)]2+ for the electrochemiluminescence detection of gemcitabine and leucovorin toward diagnostic point-of-care sensors within precision medicine

With advances in medical understanding and pharmaceutical drug development a shift away from the traditional “one size fits all” approaches common place in today's treatment plans have been witnessed. Instead greater emphasis has been placed upon the development of personalised precision medicine, tailored to the individual and their disease characteristics. Although the fundamental knowledge is currently present for such a development, current health care practices do not possess the required resources to see such treatment plans implemented. As such the progress and implementation of precision medicine has stalled. Monitoring of the ADMET properties of a therapeutic species will ultimately aid in the progression of precision medicine in addition to drug development timelines. Within this contribution the development of an electrochemiluminescence (ECL) sensor to this end is discussed. Utilising cancer therapies gemcitabine hydrochloride (GMB) and leucovorin calcium (LV) as model compounds, the ability to use ECL for their detection down to a relevant therapeutic range (6.25–100 µM) via a portable sensing system is shown both within ideal and complex biological matrices. For the first time, GMB and LV are detected via ECL utilising both traditional and non-traditional luminophores, and demonstrated how the employment of alternative luminophores can circumvent competing side reactions preventing detection via the traditional ruthenium luminophores, previously rendering the species as unsuited for ECL monitoring. This approach successfully represents an initial concept proof for the utilisation of ECL sensors for monitoring of therapeutics within complex matrices and lays the initial foundations for wider employment of ECL sensors for medical diagnostics and precision medicine.

Aptamer-Based Detection of Circulating Targets for Precision Medicine.

The past decade has witnessed ongoing progress in precision medicine to improve human health. As an emerging diagnostic technique, liquid biopsy can provide real-time, comprehensive, dynamic physiological and pathological information in a noninvasive manner, opening a new window for precision medicine. Liquid biopsy depends on the sensitive and reliable detection of circulating targets (e.g., cells, extracellular vesicles, proteins, microRNAs) from body fluids, the performance of which is largely governed by recognition ligands. Aptamers are single-stranded functional oligonucleotides, capable of folding into unique tertiary structures to bind to their targets with superior specificity and affinity. Their mature evolution procedure, facile modification, and affinity regulation, as well as versatile structural design and engineering, make aptamers ideal recognition ligands for liquid biopsy. In this review, we present a broad overview of aptamer-based liquid biopsy techniques for precision medicine. We begin with recent advances in aptamer selection, followed by a summary of state-of-the-art strategies for multivalent aptamer assembly and aptamer interface modification. We will further describe aptamer-based micro-/nanoisolation platforms, aptamer-enabled release methods, and aptamer-assisted signal amplification and detection strategies. Finally, we present our perspectives regarding the opportunities and challenges of aptamer-based liquid biopsy for precision medicine.

Imaging features of breast cancer molecular subtypes: state of the art.

Characterization of breast cancer molecular subtypes has been the standard of care for breast cancer management. We aimed to provide a review of imaging features of breast cancer molecular subtypes for the field of precision medicine. We also provide an update on the recent progress in precision medicine for breast cancer, implications for imaging, and recent observations in longitudinal functional imaging with radiomics.

Insights on the Interplay between Cells Metabolism and Signaling: A Therapeutic Perspective in Pediatric Acute Leukemias.

Nowadays, thanks to extensive studies and progress in precision medicine, pediatric leukemia has reached an extremely high overall survival rate. Nonetheless, a fraction of relapses and refractory cases is still present, which are frequently correlated with poor prognosis. Although several molecular features of these diseases are known, still the field of energy metabolism, which is widely studied in adult, has not been frequently explored in childhood leukemias. Metabolic reprogramming is a hallmark of cancer and is deeply connected with other genetic and signaling aberrations generally known to be key features of both acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). This review aims to clear the current knowledge on metabolic rewiring in pediatric ALL and AML, also highlighting the influence of the main signaling pathways and suggesting potential ideas to further exploit this field to discover new prognostic biomarkers and, above all, beneficial therapeutic options.

Abstract LB-242: Proteomic Data Commons: A resource for proteogenomic analysis

Abstract The objective of the National Cancer Institutes' Proteomic Data Commons (PDC) is to make cancer-related proteomic datasets accessible to the public. The PDC provides the cancer research community with a unified data repository that enables data sharing across cancer proteomic studies and also enables multi-omic integration in support of precision medicine. As a domain-specific repository within the Cancer Research Data Commons (CRDC), the vision for the PDC is to provide researchers the ability to find and analyze proteomic data across a wide variety of tumor types. Currently, the PDC houses data, supported by a large collection of metadata attributes, for nearly 40 datasets from over 12 cancer types produced by several large-scale cancer research programs, each with cohort sizes greater than 100 patients. The PDC facilitates the analysis of proteomic, genomic, and imaging data derived from the same tumor. Most of the datasets in the PDC also have corresponding genomic and imaging data available in the Genomic Data Commons and The Cancer Imaging Archive respectively. Researchers can discover which genomic variants are detectable at the protein-level or better understand associations between gene expression, copy number variation, and protein abundance. The resource is currently available to the public in beta phase (https://pdc.esacinc.com) and will be officially launched on the cancer.gov domain in March 2020. The PDC data portal is supported by a robust and extensible data model and provides user-friendly exploration, visualization and data analysis. This allows researchers to search for and visualize expression of proteins (through their mapped genes) across all studies, analyze protein abundance for all cases in a study through heatmaps, build and explore pan-cancer cohorts using highly curated, clinical metadata, and comprehensively view a study without needing to download the data. The PDC provides quick access to mapping of peptide identities and quantities on the human genome as well as protein databases containing patient/tumor-specific variants and novel splicing events. It also enables fast, accurate, and convenient proteomic validation of novel genomic alterations through the PepQuery algorithm. Through a highly versatile application programming interface (API), PDC allows users to interact with data programmatically and facilitates integration with data from other resources in their scripts for multi-omic analysis. Big data interoperability is critical for progress in precision medicine. PDC is designed to interoperate with other resources including the CRDC nodes, allowing users to analyze PDC data with the tools and pipelines available on the NCI cloud resources. It further allows users to use their own tools to co-analyze genomic and proteomic data available from a common sample on Amazon Web Services (AWS) platform or on a local system. The presentation will provide an overview of the PDC and it's available datasets, as well as a discussion of how it facilitates multi-omic data analyses. Citation Format: Ratna Rajesh Thangudu, Paul A. Rudnick, Michael Holck, Deepak Singhal, Michael J. MacCoss, Nathan J. Edwards, Karen A. Ketchum, Christopher R. Kinsinger, Erika Kim, Anand Basu. Proteomic Data Commons: A resource for proteogenomic analysis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-242.

Abstract 6587: Proteogenomic characterization of colorectal cancer using the IndivuType multiomics database

Abstract Cancer is a highly heterogeneous disease, both intra- and inter-individually consisting of complex phenotypes and systems biology. Although genomic data has contributed greatly towards the identification of cancer-specific mutations and the progress of precision medicine, genomic alterations are only one of several important biological drivers of cancer. Furthermore, single-layer omics represent only a small piece of the cancer biology puzzle and provide only partial clues to connecting genotype with phenotype. A more integrated approach is urgently needed to unravel the underpinnings of molecular signatures and the phenotypic manifestation of cancer hallmarks. We have developed IndivuType, a knowledge and discovery platform that combines genomics, transcriptomics, and proteomics datasets to identify putative therapeutic targets in a colorectal cancer (CRC) cohort of 500 patients. We identified hundreds of proteins dysregulated in CRC that are dependent on the genetic background of the patient. Further, we characterized these proteins using clinical parameters from the IndivuType database to prioritize targets for precision medicine approaches. This project highlights the utility of moving beyond solely genomics approaches to better understand the molecular mechanisms underpinning cancer. Citation Format: Margarita Krawczyk, Jonathan Woodsmith, Marcel Nutsoa, Thomas Corwin, Silvia von der Heyde, Vincent Piras, Mark Whittaker, Alex Hergovich, Peter Frommolt, Hartmut Juhl. Proteogenomic characterization of colorectal cancer using the IndivuType multiomics database [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6587.

Abstract A084: The forgotten race: Under-representation of Asians in clinical research

Abstract The United States (US) is racially and culturally diverse. Still, white women disproportionately comprise clinical trial participants, stemming largely from the fact that minorities often decline participation. Clinical trial findings, therefore, have not been representative of the diverse patient population, and have stymied progress in precision medicine and cancer prevention. According to the CDC, among Asian/Pacific Islander females, the leading cause of death is cancer. Moreover, they have more total cancer-related deaths than any other racial group. Per the 2017 US Census, Asians are the third largest minority group of the population (6.6%). Despite the grave health disparities faced by a sizable proportion of the population, the literature is sparse with regards to their research engagement. For example, several studies have focused on Black and Hispanic consenting rates, including one study that demonstrated no significant differences between the two groups (Wendler, Kington, Madans, Wye, Christ-Schmidt, Pratt et al., 2005) and another that indicated relatively lower enrollment rates among Hispanics and Blacks (Murthy, Krumholz, Gross, 2004). This gap in research is largely due to the marked heterogeneity with respect to language, nationality, and acculturation status. We examined Asian participation in three therapeutic, noninterventional trials that aim to develop early detection methods and accurate prognosis in women at high risk for breast cancer. Primarily, we collect leftover tissue and/or cells from fine needle aspirations (FNA) to better understand the cellular microenvironment that correlates with breast cancer development. We analyzed demographic data across these studies to investigate refusal rates among Asian women. Across the three trials, 3,119 participants were screened. Of the total number screened, 426 participants were eligible, 368 consented, and 58 declined. Of those who declined, 23.5% were Asians, 13.9% Hispanic, 8.3% Blacks, 5.6% Native Americans, and 11.4% White/non-Hispanic. Notably, Asians had the highest refusal rate. Fisher's exact test (two-tailed) was conducted to examine refusal rates for Asians compared to Whites, Blacks, and Hispanics. Results suggest that Asians had significantly higher rates of compared to Whites (p = .02, observed odds ratio = .42, 95% CI [.20, .86]), but were not significantly different than Blacks or Hispanics. The under-representation of Asians in research may exacerbate health disparities. Thus, further studies should examine ways, such as increasing racial and cultural competency, for increasing Asian representation in clinical research studies. Ultimately, we believe that illuminating under-representation of the “forgotten” Asian population in clinical research can inform future interventions that promote chemoprevention and treatment of this high-risk population. Citation Format: Stacey N. Doan, Christine Thai, Angela K. Wong, Tanya A. Chavez, Angelica Sanchez, Laura L. Kruper, Veronica C. Jones, Sharon Clancy, Amy C. Polverini, Lisa D. Yee, Courtney Vito, Alan Nunez, Ellen J. Rippberger, Noe R. Chavez, Karen Herold, Chidimma M.K. Kalu, Jackelyn A. Alva-Ornelas, Jerneja Tomsic, Krista M. Round, Margarita Robles, Ombeni M. Idassi, Kendall J. Kennedy, Christopher Sistrunk, Victoria L. Seewaldt. The forgotten race: Under-representation of Asians in clinical research [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr A084.

Clinically relevant multi-omic analysis of colorectal cancer.

e16063 Background: Cancer is a highly heterogeneous disease, both intra- and inter-individually consisting of complex phenotypes and systems biology. Although genomic data has contributed greatly towards the identification of cancer-specific mutations and the progress of precision medicine, genomic alterations are only one of several important biological drivers of cancer. Furthermore, single-layer omics represent only a small piece of the cancer biology puzzle and provide only partial clues to connecting genotype with clinically relevant phenotypic data. A more integrated approach is urgently needed to unravel the underpinnings of molecular signatures and the phenotypic manifestation of cancer hallmarks. Methods: Here we characterize a colorectal cancer (CRC) cohort of 500 patients across multiple distinct omic data types. Across this CRC cohort, we defined clinically relevant whole genome sequencing based metrics such as micro-satellite-instability (MSI) status, and furthermore investigate gene expression at the transcript level using RNA-Seq, as well as at the proteomic level using tandem mass spectrometry. We further characterized a subgroup of 100 of these patients through 16s rRNA sequencing to identify associated microbiome profiles. Results: We combined these analyses with comprehensive clinical data to observe the impact of ascertained molecular signatures on the CRC patient cohort. Here, we report how patient survival correlates both with specific molecular events across individual omic data types, as well as with combined multi-omic analyses. Conclusions: This project highlights the utility of integrating multiple distinct data types to obtain a more comprehensive overview of the molecular mechanisms underpinning colo-rectal cancer. Furthermore, through combining identified aberrant molecular mechanisms with clinical reports, multi-omic data can be prioritized through their impact on patient cohort survival.

Points to consider: is there evidence to support BRCA1/2 and other inherited breast cancer genetic testing for all breast cancer patients? A statement of the American College of Medical Genetics and Genomics (ACMG)

Points to consider: is there evidence to support BRCA1/2 and other inherited breast cancer genetic testing for all breast cancer patients? A statement of the American College of Medical Genetics and Genomics (ACMG)

Gut microbiome interventions in human health and diseases.

Ongoing studies have determined that the gut microbiota is a major factor influencing both health and disease. Host genetic factors and environmental factors contribute to differences in gut microbiota composition and function. Intestinal dysbiosis is a cause or a contributory cause for diseases in multiple body systems, ranging from the digestive system to the immune, cardiovascular, respiratory, and even nervous system. Investigation of pathogenesis has identified specific species or strains, bacterial genes, and metabolites that play roles in certain diseases and represent potential drug targets. As research progresses, gut microbiome-based diagnosis and therapy are proposed and applied, which might lead to considerable progress in precision medicine. We further discuss the limitations of current studies and potential solutions.

Simultaneous Interrogation of Cancer Omics to Identify Subtypes With Significant Clinical Differences.

Recent advances in high-throughput sequencing have accelerated the accumulation of omics data on the same tumor tissue from multiple sources. Intensive study of multi-omics integration on tumor samples can stimulate progress in precision medicine and is promising in detecting potential biomarkers. However, current methods are restricted owing to highly unbalanced dimensions of omics data or difficulty in assigning weights between different data sources. Therefore, the appropriate approximation and constraints of integrated targets remain a major challenge. In this paper, we proposed an omics data integration method, named high-order path elucidated similarity (HOPES). HOPES fuses the similarities derived from various omics data sources to solve the dimensional discrepancy, and progressively elucidate the similarities from each type of omics data into an integrated similarity with various high-order connected paths. Through a series of incremental constraints for commonality, HOPES can take both specificity of single data and consistency between different data types into consideration. The fused similarity matrix gives global insight into patients' correlation and efficiently distinguishes subgroups. We tested the performance of HOPES on both a simulated dataset and several empirical tumor datasets. The test datasets contain three omics types including gene expression, DNA methylation, and microRNA data for five different TCGA cancer projects. Our method was shown to achieve superior accuracy and high robustness compared with several benchmark methods on simulated data. Further experiments on five cancer datasets demonstrated that HOPES achieved superior performances in cancer classification. The stratified subgroups were shown to have statistically significant differences in survival. We further located and identified the key genes, methylation sites, and microRNAs within each subgroup. They were shown to achieve high potential prognostic value and were enriched in many cancer-related biological processes or pathways.

Guest Editorial on the Special Issue on Integrating Informatics and Technology for Precision Medicine

The seven papers in this special section examine the latest advances in the field of integrated precision medicine technologies. In the majority of medical conditions common therapeutic approaches are usually effective in only a small percentage of the patient population. Recent scientific discoveries implicate as possible causes of this lack of effect the multifactorial nature of most diseases and the patient variability in disease expression, genetic disposition, and environmental exposures. It has become apparent that in order to improve the response to therapy and long term prognosis, treatment must be specifically tailored to the disease and the patient. Precision medicine is an attempt to maximize effectiveness by taking into account individual variability in clinical presentation, medical history, genes, environment, and lifestyle. It is a leap beyond the promise of “personalization” empowered by recent technological advances. However, progress in precision medicine has been slow due to the lack of “precision” in the traditional research, translation, and clinical practice. Current approaches are largely empirical, fragmented, lack integration, and rely on population statistics, with inadequate feedback between disciplines. In addition, most of the information required for personalization is either missing or unutilized. New technological developments can help overcome these hurdles of imprecision to achieve the full promise of precision medicine.

Abstract IA19: Homologous recombination repair deficiency and breast cancer progression in high-risk populations

Abstract Analysis of cancer genomes has rapidly become an integral part of the practice of clinical oncology, with implications for diagnosis, prognosis, treatment, and prevention. Inherited and sporadic cancers often share common mutational events. When inherited mutations are identified, genetic counseling is an essential component of care. Pathogenic BRCA1 and BRCA2 mutations are the strongest predictors of breast cancer risk and may be the strongest predictors of other inherited forms of solid tumors and hematologic malignancies as well. Waiting to treat advanced breast cancer with targeted therapies is a failure of primary prevention, and population-based strategies for risk management in high-risk populations will be needed. Understanding breast cancer progression in genetic defined subgroups has the potential to accelerate progress in precision medicine. I will discuss ongoing research in our group, our recent findings in defining the genomic landscape of early-onset breast cancer, and future directions for the early detection, treatment, and prevention of breast cancer in high-risk populations. Citation Format: Olufunmilayo I. Olopade. Homologous recombination repair deficiency and breast cancer progression in high-risk populations [abstract]. In: Proceedings of the AACR Special Conference: Advances in Breast Cancer Research; 2017 Oct 7-10; Hollywood, CA. Philadelphia (PA): AACR; Mol Cancer Res 2018;16(8_Suppl):Abstract nr IA19.