Implications For Precision Medicine Research Articles

Clinicopathologic and Molecular Characteristics of HER2 (ERBB2)-Altered Non–Small Cell Lung Cancer: Implications for Precision Medicine

The heterogeneous relationship between protein expression, amplification, and mutations in human epidermal growth factor receptor 2 (HER2) in non–small cell lung cancer (NSCLC) and the optimal methods for detecting these alterations remain unclear. We aimed to elucidate the clinicopathological and molecular characteristics of HER2-altered NSCLC and investigate practical approaches for identifying patients who might benefit from HER2-targeted therapies. Using next-generation sequencing data from 1680 individuals, we searched for patients with HER2-altered NSCLCs, including amplifications and mutations. Clinicopathological data and tissue slides were reviewed. Immunohistochemistry (IHC) and silver in situ hybridization were performed according to the American Society of Clinical Oncology/College of American Pathologists guidelines. Our analysis identified 89 (5.3%) patients with HER2-altered NSCLCs, comprising 30 (1.8%) with amplification and 59 (3.6%) mutations, and they were compared with 165 control patients. Of the 59 HER2-mutated cases, 52 harbored tyrosine kinase domain (TKD) mutations, primarily HER2 exon 20 insertions. HER2 TKD alterations were associated with younger age, female sex, nonsmoking status, adenocarcinoma with a micropapillary pattern, lung-to-lung metastasis, and poor overall survival. The 33 patients with TKD mutations and 3 with non-TKD point mutations showed incomplete or complete membranous HER2 immunoreactivity (1+ and 2+, 61.07%). Six patients exhibiting amplifications had an IHC score of ≤2+ despite their high copy numbers and concomitantly displayed other actionable EGFR, KRAS, SMARCA4, and other HER2 mutations. These HER2-altered NSCLCs with molecular coalterations showed heterogeneous patterns through HER2 IHC and silver in situ hybridization. Therefore, next-generation sequencing should be used to identify HER2 mutations in patients with NSCLC who present with concomitant alterations. In addition, the above clinicopathological characteristics and HER2 IHC results can be valuable determinants for identifying patients with HER2-altered NSCLC. These insights hold promise for the development of more effective diagnostic and therapeutic strategies for this complex subset of NSCLC patients.

Temporal trends and regional variability in BRAF and KRAS genetic testing in Denmark (2010-2022): Implications for precision medicine.

This study aims to evaluate the developments in the testing of Kirsten Rat Sarcoma viral oncogene homolog (KRAS) and v-Raf murine sarcoma viral oncogene homolog B1 (BRAF) mutations across different cancer types and regions in Denmark from 2010 to 2022. Using comprehensive data from the Danish health registries, we linked molecular test results from the Danish Pathology Registry with cancer diagnoses from the Danish National Patient Registry between 2010 and 2022. We assessed the frequency and distribution of KRAS and BRAF mutations across all cancer types, years of testing, and the five Danish regions. The study included records of KRAS testing for 30 671 patients and BRAF testing for 30 860 patients. Most KRAS testing was performed in colorectal (78%) and lung cancer (18%), and BRAF testing in malignant melanoma (13%), colorectal cancer (67%), and lung cancer (12%). Testing rates and documentation mutational subtypes increased over time. Reporting of wildtype results varied between lung and colorectal cancer, with underreporting in lung cancer. Regional variations in testing and reporting were observed. Our study highlights substantial progress in KRAS and BRAF testing in Denmark from 2010 to 2022, evidenced by increased and more specific reporting of mutational test results, thereby improving the precision of cancer diagnosis and treatment. However, persistent regional variations and limited testing for cancer types beyond melanoma, colorectal, and lung cancer highlight the necessity for a nationwide assessment of the optimal testing approach.

A comprehensive review of data analytics in healthcare management: Leveraging big data for decision-making

This research paper presents a comprehensive review of data analytics in healthcare management, focusing on leveraging big data for decision-making. The literature review explores the historical evolution of data analytics, emphasizing its growing importance in clinical support, resource allocation, and operational efficiency within the healthcare sector. The paper discusses fundamental concepts, methodologies, and emerging trends, including integrating artificial intelligence, real-time analytics, and the impact of wearable technologies. Challenges such as data quality, privacy, and interoperability are identified, along with recommendations for future research. The findings underscore the pivotal role of data analytics in transforming healthcare decision-making processes, with implications for precision medicine, preventive healthcare, and enhanced patient outcomes.

Temporal Interactions between Maintenance of Cerebral Cortex Thickness and Physical Activity from an Individual Person Micro-Longitudinal Perspective and Implications for Precision Medicine.

Maintenance of brain structure is essential for neurocognitive health. Precision medicine has interests in understanding how maintenance of an individual person's brain, including cerebral cortical structure, interacts with lifestyle factors like physical activity. Cortical structure, including cortical thickness, has recognized relationships with physical activity, but concepts of these relationships come from group, not individual, focused findings. Whether or how group-focused concepts apply to an individual person is fundamental to precision medicine interests but remains unclear. This issue was studied in a healthy man using concurrent micro-longitudinal tracking of magnetic resonance imaging-defined cortical thickness and accelerometer-defined steps/day over six months. These data permitted detailed examination of temporal relationships between thickness maintenance and physical activity at an individual level. Regression analyses revealed graded significant and trend-level temporal interactions between preceding activity vs. subsequent thickness maintenance and between preceding thickness maintenance vs. subsequent activity. Interactions were bidirectional, delayed/prolonged over days/weeks, positive, bilateral, directionally asymmetric, and limited in strength. These novel individual-focused findings in some ways are predicted, but in other ways remain unaddressed or undetected, by group-focused work. We suggest that individual-focused concepts of temporal interactions between maintenance of cortical structure and activity can provide needed new insight for personalized tailoring of physical activity, cortical, and neurocognitive health.

Significance of RNA Processing Factors in Prognosis and Treatment of Hepatocellular Carcinoma: Implications for Precision Medicine

Hepatocellular carcinoma (HCC) is a malignant tumor with heterogenous nature and high mortality worldwide. RNA processing has been implicated in tumorigenesis, progression, and prognosis to develop early diagnosis and targeted therapy for cancer, including HCC. This study aimed to identify and validate a novel RNA processing gene signature for predicting HCC prognosis. Transcriptome and clinical data of HCC samples were obtained from Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), Gene Expression Omnibus databases, and RNA processing factors from the AmiGO database. The least absolute shrinkage and selection operator and multivariate Cox regression analysis were performed to examine prognostic gene signatures. Correlation analysis of prognostic models with clinical features and HallMark pathway-based Genomic Variation Analysis enrichment analysis were performed. We identified seven distinguished RNA processing factors to build the prognostic model for HCC patients. ROC curve analysis of the TCGA-HCC, ICGC-HCC, and GSE76427 cohorts determined the ability to predict prognosis through a sevengene-based model (AUC > 0.7). A nomogram to forecast the overall survival among HCC patients was established. In addition, 7 cell types (CD3+ cells, CD8+ T cells, macrophage/monocyte, monocyte, myeloid dendritic cells, neutrophils and cancer-associated fibroblast) significantly differed between the two risk groups. Furthermore, enrichment analysis showed significant enrichment in fatty acid metabolism, lipogenesis, pancreatic beta cells, and bile acid metabolism in the low-risk group, while in the high-risk group, DNA repair, protein secretion, and mitotic pathways were significantly enriched. Analyzing the Tumor Immune Dysfunction and Exclusion results demonstrated that immune checkpoint blockade therapy was poorly efficacious in the high-risk group. This study constructed and validated a novel prognostic signature related to RNA processing factors in HCC, improving therapeutic strategies for HCC. Building such prognostic signatures could pave the way for developing targeted therapy and precision medicine in HCC.

Neuronal-type-specific epigenome editing to decrease SNCA expression: Implications for precision medicine in synucleinopathies

Overexpression of SNCA has been implicated in the pathogenesis of synucleinopathies, particularly Parkinson's disease (PD) and dementia with Lewy bodies (DLB). While PD and DLB share some clinical and pathological similarities, each disease presents distinct characteristics, including the primary affected brain region and neuronal type. We aimed to develop neuronal-type-specific SNCA-targeted epigenome therapies for synucleinopathies. The system is based on an all-in-one lentiviral vector comprised of CRISPR-dSaCas9 and guide RNA (gRNA) targeted at SNCA intron 1 fused with a synthetic repressor molecule of Krüppel-associated box (KRAB)/ methyl CpG binding protein 2 (MeCp2) transcription repression domain (TRD). To achieve neuronal-type specificity for dopaminergic and cholinergic neurons, the system was driven by tyrosine hydroxylase (TH) and choline acetyltransferase (ChAT) promoters, respectively. Delivering the system into human induced pluripotent stem cell (hiPSC)-derived dopaminergic and cholinergic neurons from a patient with the SNCA triplication resulted in efficient and neuronal-type-specific downregulation of SNCA-mRNA and protein. Furthermore, the reduction in SNCA levels by the gRNA-dSaCas9-repressor system rescued disease-related cellular phenotypes including Ser129-phophorylated α-synuclein, neuronal viability, and mitochondrial dysfunction. We established a novel neuronal-type-specific SNCA-targeted epigenome therapy and provided invitro proof of concept using human-based disease models. Our results support the therapeutic potential of our system for PD and DLB and provide the foundation for further preclinical studies in animal models toward investigational new drug (IND) enablement and clinical trials.

Wearable Devices: Implications for Precision Medicine and the Future of Health Care.

Wearable devices are integrated analytical units equipped with sensitive physical, chemical, and biological sensors capable of noninvasive and continuous monitoring of vital physiological parameters. Recent advances in disciplines including electronics, computation, and material science have resulted in affordable and highly sensitive wearable devices that are routinely used for tracking and managing health and well-being. Combined with longitudinal monitoring of physiological parameters, wearables are poised to transform the early detection, diagnosis, and treatment/management of a range of clinical conditions. Smartwatches are the most commonly used wearable devices and have already demonstrated valuable biomedical potential in detecting clinical conditions such as arrhythmias, Lyme disease, inflammation, and, more recently, COVID-19 infection. Despite significant clinical promise shown in research settings, there remain major hurdles in translating the medical uses of wearables to the clinic. There is a clear need for more effective collaboration among stakeholders, including users, data scientists, clinicians, payers, and governments, to improve device security, user privacy, data standardization, regulatory approval, and clinical validity. This review examines the potential of wearables to offer affordable and reliable measures of physiological status that are on par with FDA-approved specialized medical devices. We briefly examine studies where wearables proved critical for the early detection of acute and chronic clinical conditions with a particular focus on cardiovascular disease, viral infections, and mental health. Finally, we discuss current obstacles to the clinical implementation of wearables and provide perspectives on their potential to deliver increasingly personalized proactive health care across a wide variety of conditions.

Deciphering the Biology of Circulating Tumor Cells through Single-Cell RNA Sequencing: Implications for Precision Medicine in Cancer.

Circulating tumor cells (CTCs) hold unique biological characteristics that directly involve them in hematogenous dissemination. Studying CTCs systematically is technically challenging due to their extreme rarity and heterogeneity and the lack of specific markers to specify metastasis-initiating CTCs. With cutting-edge technology, single-cell RNA sequencing (scRNA-seq) provides insights into the biology of metastatic processes driven by CTCs. Transcriptomics analysis of single CTCs can decipher tumor heterogeneity and phenotypic plasticity for exploring promising novel therapeutic targets. The integrated approach provides a perspective on the mechanisms underlying tumor development and interrogates CTCs interactions with other blood cell types, particularly those of the immune system. This review aims to comprehensively describe the current study on CTC transcriptomic analysis through scRNA-seq technology. We emphasize the workflow for scRNA-seq analysis of CTCs, including enrichment, single cell isolation, and bioinformatic tools applied for this purpose. Furthermore, we elucidated the translational knowledge from the transcriptomic profile of individual CTCs and the biology of cancer metastasis for developing effective therapeutics through targeting key pathways in CTCs.

Phenome-wide association study and precision medicine of cardiovascular diseases in the post-COVID-19 era.

SARS-CoV-2 infection causes injuries of not only the lungs but also the heart and endothelial cells in vasculature of multiple organs, and induces systemic inflammation and immune over-reactions, which makes COVID-19 a disease phenome that simultaneously affects multiple systems. Cardiovascular diseases (CVD) are intrinsic risk and causative factors for severe COVID-19 comorbidities and death. The wide-spread infection and reinfection of SARS-CoV-2 variants and the long-COVID may become a new common threat to human health and propose unprecedented impact on the risk factors, pathophysiology, and pharmacology of many diseases including CVD for a long time. COVID-19 has highlighted the urgent demand for precision medicine which needs new knowledge network to innovate disease taxonomy for more precise diagnosis, therapy, and prevention of disease. A deeper understanding of CVD in the setting of COVID-19 phenome requires a paradigm shift from the current phenotypic study that focuses on the virus or individual symptoms to phenomics of COVID-19 that addresses the inter-connectedness of clinical phenotypes, i.e., clinical phenome. Here, we summarize the CVD manifestations in the full clinical spectrum of COVID-19, and the phenome-wide association study of CVD interrelated to COVID-19. We discuss the underlying biology for CVD in the COVID-19 phenome and the concept of precision medicine with new phenomic taxonomy that addresses the overall pathophysiological responses of the body to the SARS-CoV-2 infection. We also briefly discuss the unique taxonomy of disease as Zheng-hou patterns in traditional Chinese medicine, and their potential implications in precision medicine of CVD in the post-COVID-19 era.

Abstract A072: Unique mouse models of high-risk prostate cancer adequate for targeted interception

Abstract Metastasis-associate protein 1 (MTA1), a master transcriptional co-regulator and chromatin modifier, is strongly associated with clinically aggressive prostate cancer. The loss of MTA1 reduces the aggressiveness and metastatic potential of prostate cancer cells. Preclinical studies with subcutaneous and orthotopic MTA1 knockdown xenograft models have shown the tumor promoting role of MTA1 and associated survival pathways in prostate cancer. However, the exact role of MTA1 in the pathobiology of prostate cancer is unknown. We first generated a conditional mouse with human MTA1 transgene knocked into the mouse Rosa26 locus (R26MTA1; Cre+ ). By crossing a R26MTA1 mouse with a Pten “floxed” mouse, we have created unique high-risk high-grade PIN-prone R26MTA1; Ptenf/+; Cre+ mice and a high-risk R26MTA1; Ptenf/f; Cre+ cohort of mice with characteristics of a castrate-resistant neuroendocrine subtype suitable for early chemoprevention/interception and novel effective therapies, respectively. I will discuss the potent MTA1-targeted anticancer effects of natural stilbenes (resveratrol, pterostilbene, and Gnetin C) observed in the preclinical R26MTA1; Ptenf/+; Cre+ model mimicking high-risk premalignant tumors with overexpressed MTA1. Further, evidence will be provided on the role of MTA1 in castrate resistance and on the neuroendocrine features defining the potential of the R26MTA1; Ptenf/f; Cre+ model in discovering novel chemoimmunotherapies. Our studies demonstrate progress towards successful targeted interception strategies for prostate cancer with an implication for precision medicine. Supported by the NCI/NIH R15CA216070 Award. Citation Format: Anait S. Levenson. Unique mouse models of high-risk prostate cancer adequate for targeted interception [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr A072.

A hotspot for posttranslational modifications on the androgen receptor dimer interface drives pathology and anti-androgen resistance

Mutations of the androgen receptor (AR) associated with prostate cancer and androgen insensitivity syndrome may profoundly influence its structure, protein interaction network, and binding to chromatin, resulting in altered transcription signatures and drug responses. Current structural information fails to explain the effect of pathological mutations on AR structure-function relationship. Here, we have thoroughly studied the effects of selected mutations that span the complete dimer interface of AR ligand-binding domain (AR-LBD) using x-ray crystallography in combination with in vitro, in silico, and cell-based assays. We show that these variants alter AR-dependent transcription and responses to anti-androgens by inducing a previously undescribed allosteric switch in the AR-LBD that increases exposure of a major methylation target, Arg761. We also corroborate the relevance of residues Arg761 and Tyr764 for AR dimerization and function. Together, our results reveal allosteric coupling of AR dimerization and posttranslational modifications as a disease mechanism with implications for precision medicine.

A novel endothelial-related prognostic index by integrating single-cell and bulk RNA sequencing data for patients with kidney renal clear cell carcinoma.

Background: Endothelial cells in the tumor microenvironment play an important role in the development of kidney renal clear cell carcinoma (KIRC). We wanted to further identify the function of endothelial cells in KIRC patients by integrating single-cell and bulk RNA sequencing data. Methods: Online databases provide the original data of this study. An endothelial-related prognostic index (ERPI) was constructed and validated by R version 3.6.3 and relative packages. Results: The ERPI consisted of three genes (CCND1, MALL, and VWF). Patients with high ERPI scores were significantly correlated with worse prognosis than those with low ERPI scores in the TCGA training group, TCGA test group, and GSE29609 group. A positive correlation was identified between the ERPI score and poor clinical features. The results of functional analysis indicated that ERPI was significantly associated with immune-related activities. We suggested that patients with high ERPI scores were more likely to benefit from immunotherapy based on the results of immune checkpoints, tumor microenvironment, stemness index, and TCIA, while patients with low ERPI scores were sensitive to gemcitabine, docetaxel, paclitaxel, axitinib, pazopanib, sorafenib, and temsirolimus according to the results of the "pRRophetic" algorithm. Therefore, this ERPI may help doctors choose the optimal treatment for patients with KIRC. Conclusion: By integrating single-cell and bulk RNA sequencing data from KIRC patients, we successfully identified the key genes from the perspective of endothelial cells in the tumor microenvironment and constructed ERPIs that had positive implications in precision medicine.

Characterization of bone marrow heterogeneity in NK-AML (M4/M5) based on single-cell RNA sequencing

Normal karyotype acute myeloid leukemia (NK-AML) is a heterogeneous hematological malignancy that contains a minor population of self-renewing leukemia stem cells (LSCs), which complicate efforts to achieve long-term survival. We performed single-cell RNA sequencing to profile 39,288 cells from 6 bone marrow (BM) aspirates including 5 NK-AML (M4/M5) patients and 1 healthy donor. The single-cell transcriptome atlas and gene expression characteristics of each cell population in NK-AML (M4/M5) and healthy BM were obtained. In addition, we identified a distinct LSC-like cluster with possible biomarkers in NK-AML (M4/M5) and verified 6 genes using qRT‒PCR and bioinformatic analyses. In conclusion, we utilized single-cell technologies to provide an atlas of NK-AML (M4/M5) cell heterogeneity, composition, and biomarkers with implications for precision medicine and targeted therapies.

Contribution of heterozygous PCSK1 variants to obesity and implications for precision medicine: a case-control study.

Rare biallelic pathogenic mutations in PCSK1 (encoding proprotein convertase subtilisin/kexin type 1 [PC1/3]) cause early-onset obesity associated with various endocrinopathies. Setmelanotide has been approved for carriers of these biallelic mutations in the past 3 years. We aimed to perform a large-scale functional genomic study focusing on rare heterozygous variants of PCSK1 to decipher their putative impact on obesity risk. This case-control study included all participants with overweight and obesity (ie, cases) or healthy weight (ie, controls) from the RaDiO study of three community-based and one hospital-based cohort in France recruited between Jan 1, 1995, and Dec 31, 2000. In adults older than 18 years, healthy weight was defined as BMI of less than 25·0 kg/m2, overweight as 25·0-29·9 kg/m2, and obesity as 30·0 kg/m2 or higher. Participants with type 2 diabetes had fasting glucose of 7·0 mmol/L or higher or used treatment for hyperglycaemia (or both) and were negative for islet or insulin autoantibodies. Functional assessment of rare missense variants of PCSK1 was performed. Pathogenicity clusters of variants were determined with machine learning. The effect of each cluster of PCSK1 variants on obesity was assessed using the adjusted mixed-effects score test. All 13 coding exons of PCSK1 were sequenced in 9320 participants (including 7260 adults and 2060 children and adolescents) recruited from the RaDiO study. We detected 65 rare heterozygous PCSK1 variants, including four null variants and 61 missense variants that were analysed in vitro and clustered into five groups (A-E), according to enzymatic activity. Compared with the wild-type, 15 missense variants led to complete PC1/3 loss of function (group A; reference) and rare exome variant ensemble learner (REVEL) led to 15 (25%) false positives and four (7%) false negatives. Carrying complete loss-of-function or null PCSK1 variants was significantly associated with obesity (six [86%] of seven carriers vs 1518 [35%] of 4395 non-carriers; OR 9·3 [95% CI 1·5-177·4]; p=0·014) and higher BMI (32·0 kg/m2 [SD 9·3] in carriers vs 27·3 kg/m2 [6·5] in non-carriers; mean effect π 6·94 [SE 1·95]; p=0·00029). Clusters of PCSK1 variants with partial or neutral effect on PC1/3 activity did not have an effect on obesity or overweight and on BMI. Only carriers of heterozygous, null, or complete loss-of-function PCSK1 variants cause monogenic obesity and, therefore, might be eligible for setmelanotide. In silico tests were unable to accurately detect these variants, which suggests that in vitro assays are necessary to determine the variant pathogenicity for genetic diagnosis and precision medicine purposes. Agence Nationale de la Recherche, European Research Council, National Center for Precision Diabetic Medicine, European Regional Development Fund, Hauts-de-France Regional Council, and the European Metropolis of Lille.

Sequencing of genes of drug response in tumor DNA and implications for precision medicine in cancer patients.

Tumor DNA sequencing is becoming standard-of-care for patient treatment decisions. We evaluated genotype concordance between tumor DNAand genomic DNA from blood and catalogued functional effects of somatic mutations in 21 drug response genes in 752 solid tumor patients. Using a threshold of 10% difference between tumor and blood DNA variant allele fraction (VAF), concordance for heterogenous genotype calls was 78%and increased to 97.5% using a 30% VAFthreshold. Somatic mutations were observed in all 21 drug response genes, and 44% of patients had at least one somatic mutation in these genes. In tumor DNA, eight patients had a frameshift mutation in CYP2C8, which metabolizes taxanes. Overall, somatic copy number losses were more frequent than gains, including for CYP2C19 and CYP2D6 which had the most frequent copy number losses. However, copy number gains in TPMT were more than four times as common as losses. Seven % of patients had copy number gains in ABCB1, a multidrug resistance transporter of anti-cancer agents. These results demonstrate tumor-only DNA sequencing might not be reliable to call germline genotypes of drug response variants.

Cell and Tissue Specific Metabolism of Nucleoside and Nucleotide Drugs: Case Studies and Implications for Precision Medicine.

Many clinically used antiviral drugs are nucleoside or nucleotide analog drugs, which have a unique mechanism of action that requires intracellular phosphorylation. This dependence on intracellular activation presents novel challenges for the discovery and development of nucleoside/nucleotide analog drugs. Contrary to many small molecule drug development programs that rely on plasma pharmacokinetics and systemic exposures, the precise mechanisms that result in efficacious intracellular nucleoside triphosphate concentrations must be understood in the process of nucleoside/nucleotide drug development. The importance is highlighted here, using the following as case studies: the herpes treatment acyclovir, the cytomegalovirus therapy ganciclovir, and human immunodeficiency virus (HIV) treatments based on tenofovir, which are also in use for HIV prophylaxis. For each drug, the specificity of metabolism that results in its activation in different cells or tissues is discussed, and the implications explored. Acyclovir's dependence on a viral enzyme for activation provides selective pressure for resistance mutations. Ganciclovir is also dependent on a viral enzyme for activation, and suicide gene therapy capitalizes on that for a novel oncology treatment. The tissue of most relevance for tenofovir activation depends on its use as treatment or as prophylaxis, and the pharmacogenomics and drug-drug interactions in those tissues must be considered. Finally, differential metabolism of different tenofovir prodrugs and its effects on toxicity risk are explored. Taken together, these examples highlight the importance of understanding tissue specific metabolism for optimal use of nucleoside/nucleotide drugs in the clinic. SIGNIFICANCE STATEMENT: Nucleoside and nucleotide analogue drugs are cornerstones in current antiviral therapy and prevention efforts that require intracellular phosphorylation for activity. Understanding their cell and tissue specific metabolism enables their rational, precision use for maximum efficacy.

Central role of the sentinel acute pancreatitis event (SAPE) model in understanding recurrent acute pancreatitis (RAP): Implications for precision medicine.

Traditional approaches to understanding the origins of chronic pancreatitis (CP) and find treatments led to abysmal failure. Thus, no drugs now exists to meet this need. Outdated concepts of the etiopathogenesis of CP have been replaced with new insights and disease models that provide the framework for early detection of the pathogenic pancreatitis process. Application of these principals require a new paradigm in disease definition and management, i.e. personalized / precision medicine. The key is acute pancreatitis (AP) starting with the first (sentinel) acute pancreatitis (AP) event (SAPE). This event sensitizes the pancreas to recurrent acute pancreatitis (RAP) as ongoing stressors drive various inflammatory responses to cause CP. The problem is the complex etiologies of AP and the additional genetic and environmental factors that promote progression to RAP and CP. This paper provides a background on the key conceptual changes that facilitate new approaches and the rationale for using mechanism-specific therapies to prevent RAP and CP.

Abstract 5928: MTA1-targeted interception by natural stilbenes in high-risk prostate cancer

Abstract Active surveillance subpopulation of patients with prostate cancer includes men with varying cancer risk categories of precancerous disease due to prostatic intraepithelial neoplasia (PIN) heterogeneity. Identifying molecular alterations associated with PIN can provide preventable measures through finding novel targets for cancer interception, specifically by active dietary polyphenols with potent biological properties including anti-inflammatory, anti-oxidant, and anticancer effects. A large volume of preclinical evidence shows that natural stilbenes produce anticancer responses in a variety of cell lines and animal models of different types of cancer, including solid tumors as well as hematological malignancies. However, identification of a particular target with clinical relevance is rare. I will discuss the potent MTA1-targeted anticancer effects of natural stilbenes (resveratrol, pterostilbene, and Gnetin C) observed in unique preclinical models of prostate cancer mimicking high-risk premalignant tumors with overexpressed MTA1. We have shown that MTA1 cooperates with PTEN deficiency to accelerate high-grade PIN development through MTA1-associated signaling. We further demonstrated that stilbene supplemented diets lead to more favorable histopathology with decreased severity and number of PIN foci accompanied with reduced proliferation, inflammation, and angiogenesis concomitant to reduction of MTA1-associated signaling, including specific miRNAs. Together, our preclinical data provide strong evidence for the potential of stilbenes as promising natural agents for MTA1-targeted interceptive strategy. Human cancer prevention trials for protecting select patients with high MTA1 from developing into full-fledged disease are urgently needed. This can be one extra forward step towards viable and successful interception/chemoprevention potential for prostate cancer with an implication for precision medicine. Supported by NCI/NIH R15CA216070 to ASL. Citation Format: Anait S. Levenson. MTA1-targeted interception by natural stilbenes in high-risk prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5928.

Abstract 2735: An information theoretic approach to investigate AML development using time-series-omics

Abstract Introductory Statement: Using our previously published state-transition model applied to times-series micro-RNA (miRNA) expression samples, we construct a miRNA-based transcriptomic landscape of AML development to discover how miRNA dynamics contribute to leukemogenesis. Experimental Procedures: We used a genetic mouse model that mimics development of inv(16) AML through the induction of a leukemogenic fusion gene CBFB-MYH11 (CM). From monthly blood draws on both CM and control mice, we produced time-series messenger RNA (mRNA) and micro-RNA (miRNA) transcriptomic data. We have recently reported a state-transition model using the mRNA transcriptome data. We model the development of AML as a particle undergoing Brownian motion in a potential well with three critical points. Here, investigate whether the miRNA transcriptome can also be used to model AML development. Our current work is to extend the state-transition model using information theoretic approach to explore both the regulatory relationship between mRNA and miRNA and how a biological system transitions to a disease state. Summary of Results: Our state-transition model detects early perturbations of the system before it can be detected using cKit expression, the marker of AML blasts in this model. Since individual mice develop AML stochastically in time, we used the state-transition model to align the mice based on the phenotypic disease state rather than chronological time. Four distinct expression dynamics of miRNAs were identified with hierarchical clustering: persistent increase or decrease in expression; and two nonlinear patterns of expression. The nonlinear dynamic groups showed changes in expression at the critical transition point between health and AML. Additionally, the nonlinear expression dynamic patterns occurred at the boundary between the health and AML states was associated with cytokines and systemic inflammation signaling pathways, suggesting an anti-leukemic restorative miRNA program. Using regulatory dynamics in the state-transition model, we observed unique mRNA-miRNA regulatory interactions which may suggest miRNA gene targets at critical transition points in leukemia progression. Conclusions: Our information theoretic approach combined with our state-transition model is a promising approach to study AML development. This framework provides a method to integrate different -omic data without prior knowledge of the relationship between a gene and its regulatory features. Additionally, our approach can investigate the inter-individual heterogeneity of disease progression which has important implications for precision medicine. The state-transition analysis framework is a promising approach to explore the underlying principles that govern biological systems. Citation Format: David E. Frankhouser, Sergio Branciamore, Denis O'Meally, Lisa Uechi, Guido Marcucci, Ya-Huei Kuo, Russell Rockne. An information theoretic approach to investigate AML development using time-series-omics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2735.

Immune Cell Networks Uncover Candidate Biomarkers of Melanoma Immunotherapy Response.

The therapeutic activation of antitumour immunity by immune checkpoint inhibitors (ICIs) is a significant advance in cancer medicine, not least due to the prospect of long-term remission. However, many patients are unresponsive to ICI therapy and may experience serious side effects; companion biomarkers are urgently needed to help inform ICI prescribing decisions. We present the IMMUNETS networks of gene coregulation in five key immune cell types and their application to interrogate control of nivolumab response in advanced melanoma cohorts. The results evidence a role for each of the IMMUNETS cell types in ICI response and in driving tumour clearance with independent cohorts from TCGA. As expected, ‘immune hot’ status, including T cell proliferation, correlates with response to first-line ICI therapy. Genes regulated in NK, dendritic, and B cells are the most prominent discriminators of nivolumab response in patients that had previously progressed on another ICI. Multivariate analysis controlling for tumour stage and age highlights CIITA and IKZF3 as candidate prognostic biomarkers. IMMUNETS provide a resource for network biology, enabling context-specific analysis of immune components in orthogonal datasets. Overall, our results illuminate the relationship between the tumour microenvironment and clinical trajectories, with potential implications for precision medicine.