Clinical features of prostate cancer by polygenic risk score.

Genome-wide association studies have identified more than 290 single nucleotide variants (SNVs) associated with prostate cancer. These SNVs can be combined to generate a Polygenic Risk Score (PRS), which estimates an individual's risk to develop prostate cancer. Identifying individuals at higher risk for prostate cancer using PRS could allow for personalized screening recommendations, improve current screening tools, and potentially result in improved survival rates, but more research is needed before incorporating them into clinical use. Our study aimed to investigate associations between PRS and clinical factors in affected individuals, including age of diagnosis, metastases, histology, International Society of Urological Pathology (ISUP) Grade Group (GG) and family history of prostate cancer, while taking into account germline genetic testing in known prostate cancer related genes. To evaluate the relationship between these clinical factors and PRS, a quantitative retrospective chart review of 250 individuals of European ancestry diagnosed with prostate cancer who received genetic counseling services at The Ohio State University's Genitourinary Cancer Genetics Clinic and a 72-SNV PRS through Ambry Genetics, was performed. We found significant associations between higher PRS and younger age of diagnosis (p = 0.002), lower frequency of metastases (p = 0.006), and having a first-degree relative diagnosed with prostate cancer (p = 0.024). We did not observe significant associations between PRS and ISUP GG, histology or a having a second-degree relative with prostate cancer. These findings provide insights into features associated with higher PRS, but larger multi-ancestral studies using PRS that are informative across populations are needed to understand its clinical utility.

Immunotherapy for colorectal cancer: insight from inherited genetics.

Immunotherapy shows efficacy for multiple cancer types and potential for expanded use. However, current immune checkpoint inhibitors (ICIs) are ineffective against microsatellite-stable colorectal cancer (CRC), which is more commonly diagnosed. Immunotherapy strategies for non-responsive CRC, including new targets and new combination therapies, are being tested to address this need. Importantly, a subset of inherited germline genetic variants associated with CRC risk are predicted to regulate genes with immune functions, including genes related to existing ICIs, as well as new potential targets in the major histocompatibility complex (MHC) region and immunoregulatory cytokines. We review discoveries in the inherited genetics of CRC related to the immune system and draw connections with ongoing developments and emerging immunotherapy targets.

Glioblastoma pseudoprogression and true progression reveal spatially variable transcriptional differences.

Post-resection radiologic monitoring to identify areas of new or progressive enhancement concerning for cancer recurrence is critical during patients with glioblastoma follow-up. However, treatment-related pseudoprogression presents with similar imaging features but requires different clinical management. While pathologic diagnosis is the gold standard to differentiate true progression and pseudoprogression, the lack of objective clinical standards and admixed histologic presentation creates the needs to (1) validate the accuracy of current approaches and (2) characterize differences between these entities to objectively differentiate true disease. We demonstrated using an online RNAseq repository of recurrent glioblastoma samples that cancer-immune cell activity levels correlate with heterogenous clinical outcomes in patients. Furthermore, nCounter RNA expression analysis of 48 clinical samples taken from second neurosurgical resection supports that pseudoprogression gene expression pathways are dominated with immune activation, whereas progression is predominated with cell cycle activity. Automated image processing and spatial expression analysis however highlight a failure to apply these broad expressional differences in a subset of cases with clinically challenging admixed histology. Encouragingly, applying unsupervised clustering approaches over our segmented histologic images provides novel understanding of morphologically derived differences between progression and pseudoprogression. Spatially derived data further highlighted polarization of myeloid populations that may underscore the tumorgenicity of novel lesions. These findings not only help provide further clarity of potential targets for pathologists to better assist stratification of progression and pseudoprogression, but also highlight the evolution of tumor-immune microenvironment changes which promote tumor recurrence.

Association of ESR1 germline variants with TP53 somatic variants in breast tumors in a genome-wide study.

Background: In breast tumors, somatic mutation frequencies in TP53 and PIK3CA vary by tumor subtype and ancestry. HER2 positive and triple negative breast cancers (TNBC) have a higher frequency of TP53 somatic mutations than other subtypes. PIK3CA mutations are more frequently observed in hormone receptor positive tumors. Emerging data suggest tumor mutation status is associated with germline variants and genetic ancestry. We aimed to identify germline variants that are associated with somatic TP53 or PIK3CA mutation status in breast tumors. Methods: A genome-wide association study was conducted using breast cancer mutation status of TP53 and PIK3CA and functional mutation categories including TP53 gain of function (GOF) and loss of function mutations and PIK3CA activating/hotspot mutations. The discovery analysis consisted of 2850 European ancestry women from three datasets. Germline variants showing evidence of association with somatic mutations were selected for validation analyses based on predicted function, allele frequency, and proximity to known cancer genes or risk loci. Candidate variants were assessed for association with mutation status in a multi-ancestry validation study, a Malaysian study, and a study of African American/Black women with TNBC. Results: The discovery Germline x Mutation (GxM) association study found five variants associated with one or more TP53 phenotypes with P values <1×10-6, 33 variants associated with one or more TP53 phenotypes with P values <1×10-5, and 44 variants associated with one or more PIK3CA phenotypes with P values <1×10-5. In the multi-ancestry and Malaysian validation studies, germline ESR1 locus variant, rs9383938, was associated with the presence of TP53 mutations overall (P values 6.8×10-5 and 9.8×10-8, respectively) and TP53 GOF mutations (P value 8.4×10-6). Multiple variants showed suggestive evidence of association with PIK3CA mutation status in the validation studies, but none were significant after correction for multiple comparisons. Conclusions: We found evidence that germline variants were associated with TP53 and PIK3CA mutation status in breast cancers. Variants near the estrogen receptor alpha gene, ESR1, were significantly associated with overall TP53 mutations and GOF mutations. Larger multi-ancestry studies are needed to confirm these findings and determine if these variants contribute to ancestry-specific differences in mutation frequency.

Pharmacogenomics: Driving Personalized Medicine.

Personalized medicine tailors therapies, disease prevention, and health maintenance to the individual, with pharmacogenomics serving as a key tool to improve outcomes and prevent adverse effects. Advances in genomics have transformed pharmacogenetics, traditionally focused on single gene-drug pairs, into pharmacogenomics, encompassing all "-omics" fields (e.g., proteomics, transcriptomics, metabolomics, and metagenomics). This review summarizes basic genomics principles relevant to translation into therapies, assessing pharmacogenomics' central role in converging diverse elements of personalized medicine. We discuss genetic variations in pharmacogenes (drug-metabolizing enzymes, drug transporters, and receptors), their clinical relevance as biomarkers, and the legacy of decades of research in pharmacogenetics. All types of therapies, including proteins, nucleic acids, viruses, cells, genes, and irradiation, can benefit from genomics, expanding the role of pharmacogenomics across medicine. Food and Drug Administration approvals of personalized therapeutics involving biomarkers increase rapidly, demonstrating the growing impact of pharmacogenomics. A beacon for all therapeutic approaches, molecularly targeted cancer therapies highlight trends in drug discovery and clinical applications. To account for human complexity, multicomponent biomarker panels encompassing genetic, personal, and environmental factors can guide diagnosis and therapies, increasingly involving artificial intelligence to cope with extreme data complexities. However, clinical application encounters substantial hurdles, such as unknown validity across ethnic groups, underlying bias in health care, and real-world validation. This review address the underlying science and technologies germane to pharmacogenomics and personalized medicine, integrated with economic, ethical, and regulatory issues, providing insights into the current status and future direction of health care. SIGNIFICANCE STATEMENT: Personalized medicine aims to optimize health care for the individual patients with use of predictive biomarkers to improve outcomes and prevent adverse effects. Pharmacogenomics drives biomarker discovery and guides the development of targeted therapeutics. This review addresses basic principles and current trends in pharmacogenomics, with large-scale data repositories accelerating medical advances. The impact of pharmacogenomics is discussed, along with hurdles impeding broad clinical implementation, in the context of clinical care, ethics, economics, and regulatory affairs.

KMT2D loss drives aggressive tumor phenotypes in cutaneous squamous cell carcinoma.

Cutaneous squamous cell carcinoma (cSCC) is the second most lethal skin cancer. Due to ultraviolet light-induced damage, cSCCs have a high mutation rate, but some genes are more frequently mutated in aggressive cSCCs. Lysine-specific histone methyltransferase 2D (KMT2D) has a two-fold higher mutation frequency in metastatic cSCCs relative to primary non-metastatic associated cSCCs. The role of KMT2D in more aggressive phenotypes in cSCC is uncharacterized. Studies of other tumor types suggest that KMT2D acts to suppress tumor development. To determine whether KMT2D loss has an impact on tumor characteristics, we disrupted KMT2D in a cSCC cell line using CRISPR-cas9 and performed phenotypic analyses. KMT2D loss modestly increased cell proliferation and colony formation (1.4- and 1.6-fold respectively). Cells lacking KMT2D showed increased rates of migration and faster cell cycle progression. In xenograft models, tumors with KMT2D loss showed slight increases in mitotic indices. Collectively, these findings suggest that KMT2D loss-of-function mutations may promote more aggressive and invasive behaviors in cSCC, suggesting that KMT2D-related pathways could be targets for cancer therapies. Future studies to determine the downstream genes and mechanism of phenotypic effect are needed.

Differences in somatic TP53 mutation type in breast tumors by race and receptor status.

PURPOSE: Somatic driver mutations in TP53 are associated with triple-negative breast cancer (TNBC) and poorer outcomes. Breast cancers in women of African ancestry (AA) are more likely to be TNBC and have somatic TP53 mutations than cancers in non-Hispanic White (NHW) women. Missense driver mutations in TP53 have varied functional impact including loss-of-function (LOF) or gain-of-function (GOF) activity, and dominant negative (DNE) effects. We aimed to determine if there were differences in somatic TP53 mutation types by patient ancestry or TNBC status. METHODS: We identified breast cancer datasets with somatic TP53 mutation data, ancestry, age, and hormone receptor status. Mutations were classified for functional impact using published data and type of mutation. We assessed differences using Fisher's exact test. RESULTS: From 96 breast cancer studies, we identified 2964 women with somatic TP53 mutations: 715 (24.1%) Asian, 258 (8.7%) AA, 1931 (65.2%) NHW, and 60 (2%) Latina. The distribution of TP53 mutation type was similar by ancestry. However, 35.8% of tumors from NHW individuals had GOF mutations compared to 29% from AA individuals (p = 0.04). Mutations with DNE activity were positively associated with TNBC (OR 1.37, p = 0.03) and estrogen receptor (ER) negative status (OR 1.38; p = 0.005). CONCLUSIONS: Somatic TP53 mutation types did not differ by ancestry overall, but GOF mutations were more common in NHW women than AA women. ER-negative and TNBC tumors are less likely to have DNE+ TP53 mutations which could reflect biological processes. Larger cohorts and functional studies are needed to further elucidate these findings.

Genetic analysis of a malignant meningioma and associated metastases.

To identify genes altered in a highly aggressive metastatic meningioma primary as well as its metastases. Exome sequencing of a primary anaplastic meningioma and metastatic lesions in which DNA could be extracted and compared to germline DNA. Genetic analysis of the metastatic sites found 31 common mutations among the primary tumor and two metastatic sites. Additionally, genetic mutations were identified which were either infrequently (MUC3A, ALDH1A3, HOXA1) or not at all previously described in meningiomas (CASS4, CMKLR1). Exome sequencing of a metastatic meningioma and its distant metastases outside the CNS identified mutations that were not previously well described.

Polygenic Risk Scores in Prostate Cancer Risk Assessment and Screening.

More than 40% of the risk of developing prostate cancer (PCa) is from genetic factors. Genome-wide association studies have led to the discovery of more than 140 variants associated with PCa risk. Polygenic risk scores (PRS) generated using these variants show promise in identifying individuals at much higher (and lower) lifetime risk than the average man. PCa PRS also improve the predictive value of prostate-specific antigen screening, may inform the age for starting PCa screening, and are informative for development of more aggressive tumors. Despite the promise, few clinical trials have evaluated the benefit of PCa PRS for clinical care.

Machine learning approaches reveal subtle differences in breathing and sleep fragmentation in Phox2b-derived astrocytes ablated mice.

Modern neurophysiology research requires the interrogation of high-dimensionality data sets. Machine learning and artificial intelligence (ML/AI) workflows have permeated into nearly all aspects of daily life in the developed world but have not been implemented routinely in neurophysiological analyses. The power of these workflows includes the speed at which they can be deployed, their availability of open-source programming languages, and the objectivity permitted in their data analysis. We used classification-based algorithms, including random forest, gradient boosted machines, support vector machines, and neural networks, to test the hypothesis that the animal genotypes could be separated into their genotype based on interpretation of neurophysiological recordings. We then interrogate the models to identify what were the major features utilized by the algorithms to designate genotype classification. By using raw EEG and respiratory plethysmography data, we were able to predict which recordings came from genotype class with accuracies that were significantly improved relative to the no information rate, although EEG analyses showed more overlap between groups than respiratory plethysmography. In comparison, conventional methods where single features between animal classes were analyzed, differences between the genotypes tested using baseline neurophysiology measurements showed no statistical difference. However, ML/AI workflows successfully were capable of providing successful classification, indicating that interactions between features were different in these genotypes. ML/AI workflows provide new methodologies to interrogate neurophysiology data. However, their implementation must be done with care so as to provide high rigor and reproducibility between laboratories. We provide a series of recommendations on how to report the utilization of ML/AI workflows for the neurophysiology community.NEW & NOTEWORTHY ML/AI classification workflows are capable of providing insight into differences between genotypes for neurophysiology research. Analytical techniques utilized in the neurophysiology community can be augmented by implementing ML/AI workflows. Random forest is a robust classification algorithm for respiratory plethysmography data. Utilization of ML/AI workflows in neurophysiology research requires heightened transparency and improved community research standards.

Impact of Previous Genetic Counseling and Objective Numeracy on Accurate Interpretation of a Pharmacogenetics Test Report.

INTRODUCTION: Pharmacogenetic (PGx) testing can be useful for providing information about a patient's drug response by increasing drug efficacy and decreasing the incidence of adverse drug events. While PGx tests were previously only offered to patients under healthcare provider supervision, they are now available as direct to consumer (DTC) tests. This study aimed to assess how accurately individuals from the general population were able to interpret a sample PGx test report and if accuracy differed based on individuals' numeracy or prior genetic counseling (GC). METHODS: We surveyed 293 individuals from the general population, ascertained through ResearchMatch. The survey included questions about PGx test interpretation, numeracy, and genetic literacy. RESULTS: In our cohort, numeracy level impacted PGx result interpretation, with those of high numeracy performing statistically significantly better on both the table format and graphical format (p value = 0.002 and p value <0.001, respectively) and genetic knowledge questions (p value <0.001) than those with low/average numeracy. In addition, previous GC did not impact test interpretation or genetic knowledge, but the number of individuals with prior GC was small (n = 26). DISCUSSION/CONCLUSION: We found that numeracy had a significant impact on correct interpretation of PGx test reports. Because many individuals in the USA have low numeracy levels, it is extremely important that patients do not make their own medication management decision based on the test results and that they consult with their physicians about their PGx testing. The importance of consultation and discussion with providers about results should be emphasized on the test report.

Polygenic risk scores for prostate cancer: testing considerations.

Genome-wide association studies (GWAS) have identified more than 170 single nucleotide variants (SNVs) associated with prostate cancer risk. Each variant is associated with only small increases in risk and is not predictive of an individuals' overall risk of developing prostate cancer. Polygenic risk scores (PRS) combining these variants are now clinically available and may improve predictive value of other factors such as PSA. This overview reviews the current state of PRS for prostate cancer including testing considerations.

Germline Variants Impact Somatic Events during Tumorigenesis.

Cancer is characterized by diverse genetic alterations in both germline and somatic genomes that disrupt normal biology and provide a selective advantage to cells during tumorigenesis. Germline and somatic genomes have been extensively studied independently, leading to numerous biological insights. Analyses integrating data from both genomes have identified genetic variants impacting somatic events in tumors, including hotspot driver mutations. Interactions among specific germline variants and somatic events influence cancer subtypes, treatment response, and clinical outcomes. Investigation of these complex interactions is increasing our understanding of aberrant pathways in tumors that may uncover novel therapeutic targets. Here, we review the literature describing the role of germline genetic variants in promoting the selection and generation of specific mutations during tumorigenesis.

Genetic Testing to Guide Risk-Stratified Screens for Breast Cancer.

Breast cancer screening modalities and guidelines continue to evolve and are increasingly based on risk factors, including genetic risk and a personal or family history of cancer. Here, we review genetic testing of high-penetrance hereditary breast and ovarian cancer genes, including BRCA1 and BRCA2, for the purpose of identifying high-risk individuals who would benefit from earlier screening and more sensitive methods such as magnetic resonance imaging. We also consider risk-based screening in the general population, including whether every woman should be genetically tested for high-risk genes and the potential use of polygenic risk scores. In addition to enabling early detection, the results of genetic screens of breast cancer susceptibility genes can be utilized to guide decision-making about when to elect prophylactic surgeries that reduce cancer risk and the choice of therapeutic options. Variants of uncertain significance, especially missense variants, are being identified during panel testing for hereditary breast and ovarian cancer. A finding of a variant of uncertain significance does not provide a basis for increased cancer surveillance or prophylactic procedures. Given that variant classification is often challenging, we also consider the role of multifactorial statistical analyses by large consortia and functional tests for this purpose.

Exploring genetic counselors' perceptions of usefulness and intentions to use refined risk models in clinical care based on the Technology Acceptance Model (TAM).

Pathogenic germline mutations in the BRCA1 or BRCA2 genes are associated with an elevated lifetime risk for breast (50%-85% risk) and ovarian cancer (20%-40% risk). Genome-wide association studies have identified over 100 genetic variants associated with modified breast and/or ovarian cancer risk in BRCA1 and BRCA2 carriers. Risk models generated based on these variants have shown that these genetic modifiers strongly influence absolute risk of developing breast or ovarian cancer in BRCA mutation carriers. There is a lack of understanding, however, about the clinical applicability and utility of these risk models. To investigate this gap, we collected survey data from 274 cancer genetic counselors (GCs) through the National Society of Genetic Counselors Cancer Special Interest Group. Questions assessed perceptions of usefulness and intentions of genetic counselors to use these refined risk models in clinical care based on the Technology Acceptance Model (TAM). We found that GCs' reactions to the estimates were largely positive, though they thought the possibility of changing management based on results was unlikely. Additionally, we found that more experienced GCs were more likely to consider refined risk estimates in clinic. Support also was provided for core predictions within the TAM, whereby the perceived usefulness (indirect effect est. = 0.08, 95% CI: [0.04, 0.13]) and perceived ease of use (indirect effect est. = 0.078, 95% CI: [0.04, 0.13]) of refined risk estimates were indirectly associated with intentions to use via attitudes.

F-Box Protein-Mediated Resistance to PARP Inhibitor Therapy.

PARP inhibitor (PARPi) therapy targets BRCA1/2 mutant tumor cells, but acquired resistance limits its effectiveness. In this issue of Molecular Cell, Marzio et al. (2019) identify a novel mechanism of resistance to PARPi through regulation of RAD51 protein stability via an SCF ubiquitin ligase dependent on EMI1.

Keratinocyte Carcinomas: Current Concepts and Future Research Priorities.

Cutaneous squamous cell carcinoma (cSCC) and basal cell carcinoma (BCC) are keratinocyte carcinomas, the most frequently diagnosed cancers in fair-skinned populations. Ultraviolet radiation (UVR) is the main driving carcinogen for these tumors, but immunosuppression, pigmentary factors, and aging are also risk factors. Scientific discoveries have improved the understanding of the role of human papillomaviruses (HPV) in cSCC as well as the skin microbiome and a compromised immune system in the development of both cSCC and BCC. Genomic analyses have uncovered genetic risk variants, high-risk susceptibility genes, and somatic events that underlie common pathways important in keratinocyte carcinoma tumorigenesis and tumor characteristics that have enabled development of prediction models for early identification of high-risk individuals. Advances in chemoprevention in high-risk individuals and progress in targeted and immune-based treatment approaches have the potential to decrease the morbidity and mortality associated with these tumors. As the incidence and prevalence of keratinocyte carcinoma continue to increase, strategies for prevention, including effective sun-protective behavior, educational interventions, and reduction of tanning bed access and usage, are essential. Gaps in our knowledge requiring additional research to reduce the high morbidity and costs associated with keratinocyte carcinoma include better understanding of factors leading to more aggressive tumors, the roles of microbiome and HPV infection, prediction of response to therapies including immune checkpoint blockade, and how to tailor both prevention and treatment to individual risk factors and needs.

Involvement and Influence of Healthcare Providers, Family Members, and Other Mutation Carriers in the Cancer Risk Management Decision-Making Process of BRCA1 and BRCA2 Mutation Carriers.

Deciding between increased cancer screening or prophylactic surgery and the timing of such procedures can be a difficult and complex process for women with BRCA mutations. There are gaps in our understanding of involvement of others in the decision-making process for women with BRCA mutations. This study evaluated the management decision-making process of women with BRCA mutations, focusing on the involvement of others. Grounded theory was used to analyze and code risk management decision-making information from interviews with 20 BRCA mutation carriers. Unaffected at-risk participants with a BRCA mutation, those under age 40, and those with no children described having a difficult time making risk management decisions. Physicians were an integral part of the decision-making process by providing decisional support and management recommendations. Family members and other mutation carriers filled similar yet distinct roles by providing experiential information as well as decisional and emotional support for carriers. Participants described genetic counselors as short-term providers of risk information and management recommendations. The study findings suggest that unaffected at-risk women, women under 40, and those who do not have children may benefit from additional support and information during the decision-making process. Genetic counselors are well trained to help women through this process and connect them with resources, and may be under-utilized in long-term follow-up for women with a BRCA mutation.

Clinical testing of BRCA1 and BRCA2: a worldwide snapshot of technological practices.

Clinical testing of BRCA1 and BRCA2 began over 20 years ago. With the expiration and overturning of the BRCA patents, limitations on which laboratories could offer commercial testing were lifted. These legal changes occurred approximately the same time as the widespread adoption of massively parallel sequencing (MPS) technologies. Little is known about how these changes impacted laboratory practices for detecting genetic alterations in hereditary breast and ovarian cancer genes. Therefore, we sought to examine current laboratory genetic testing practices for BRCA1/BRCA2. We employed an online survey of 65 questions covering four areas: laboratory characteristics, details on technological methods, variant classification, and client-support information. Eight United States (US) laboratories and 78 non-US laboratories completed the survey. Most laboratories (93%; 80/86) used MPS platforms to identify variants. Laboratories differed widely on: (1) technologies used for large rearrangement detection; (2) criteria for minimum read depths; (3) non-coding regions sequenced; (4) variant classification criteria and approaches; (5) testing volume ranging from 2 to 2.5 × 105 tests annually; and (6) deposition of variants into public databases. These data may be useful for national and international agencies to set recommendations for quality standards for BRCA1/BRCA2 clinical testing. These standards could also be applied to testing of other disease genes.