Biomarkers For Precision Medicine Research Articles

Epitranscriptome: A Novel Regulatory Layer during Atherosclerosis Progression.

RNA modifications have recently gained great attention due to their extensive regulatory effects in a wide range of cellular networks and signaling pathways. In cardiovascular diseases (CVDs), several RNA changes, called "epitranscriptome" alterations, are found in all RNA molecules (tRNA, rRNA, mRNA, and ncRNAs). Unlike the epigenetic process, which influences the progression of atherosclerosis (AS), its transcriptional and post-transcriptional regulatory mechanisms are still unknown. Here, we described the main epitranscriptome signs to provide new insights into AS, including m6A, m5C, m1A, m7G, Ψ, and A-to-I editing. Moreover, we also included all current known RNA-- modifier-targeting, including small molecular inhibitors or activators, mainly designed against m6A- and m5A-related enzymes, such as METTL3, FTO, and ALKBH5. Finally, since only a few drugs, such as azacitidine and tazemetostat, targeting the DNA epigenome, have been approved by the FDA, the next challenge would be to identify molecules for targeting the RNA epitranscriptome. To date, total Panax notoginseng total saponin could reduce vascular hyperplasia via Wilms' tumor-associated protein-1 m6A-dependent. Indeed, a virtual screening allowed us to individuate a phytomolecule, the rhein, which acts as an FTO inhibitor by increasing mRNA m6A levels. In this review, we highlighted the RNA epitranscriptome pathways implicated in AS, describing their biological functions and their connections to the disease. The identification of epitranscriptome- sensitive pathways could provide novel opportunities to find predictive, diagnostic, and prognostic biomarkers for precision medicine.

Reliability of brain metrics derived from a Time-Domain Functional Near-Infrared Spectroscopy System

With the growing interest in establishing brain-based biomarkers for precision medicine, there is a need for noninvasive, scalable neuroimaging devices that yield valid and reliable metrics. Kernel’s second-generation Flow2 Time-Domain Functional Near-Infrared Spectroscopy (TD-fNIRS) system meets the requirements of noninvasive and scalable neuroimaging, and uses a validated modality to measure brain function. In this work, we investigate the test-retest reliability (TRR) of a set of metrics derived from the Flow2 recordings. We adopted a repeated-measures design with 49 healthy participants, and quantified TRR over multiple time points and different headsets—in different experimental conditions including a resting state, a sensory, and a cognitive task. Results demonstrated high reliability in resting state features including hemoglobin concentrations, head tissue light attenuation, amplitude of low frequency fluctuations, and functional connectivity. Additionally, passive auditory and Go/No-Go inhibitory control tasks each exhibited similar activation patterns across days. Notably, areas with the highest reliability were in auditory regions during the auditory task, and right prefrontal regions during the Go/No-Go task, consistent with prior literature. This study underscores the reliability of Flow2-derived metrics, supporting its potential to actualize the vision of using brain-based biomarkers for diagnosis, treatment selection and treatment monitoring of neuropsychiatric and neurocognitive disorders.

The Diversity of CYP2C19 Polymorphisms in the Thai Population: Implications for Precision Medicine.

CYP2C19 plays a major role in the metabolism of various drugs. The most common genetic variants were the CYP2C19*2 and *3 alleles (rs4244285 and rs4986893, non-functional variants). In previous studies, we found that genetic polymorphisms in CYP2C19 variants influenced the active metabolites of clopidogrel and caused major adverse cardiovascular and cerebrovascular effects. However, the distribution of CYP2C19 varies among ethnic groups and according to adverse drug reactions. This study aimed to investigate the frequency of CYP2C19 genetic polymorphisms in the Thai population and analyze the differences in the frequency of CYP2C19 genetic polymorphisms between Thai and other populations. This study enrolled 211 unrelated healthy Thai individuals in total. We performed a real-time polymerase chain reaction to genotype CYP2C19*2 (681G > A) and CYP2C19*3 (636G > A). In the Thai population, the CYP2C19*1 allele was the most prevalent at 70.14%, while the CYP2C19*2 and *3 alleles were found at frequencies of 25.36% and 4.50%, respectively. Conversely, the CYP2C19*3 allele was not detected in Caucasian, Hispanic, African, Italian, Macedonian, Tanzanian, or North Indian populations. The phenotypic profile of this gene revealed that the frequency of intermediate metabolizers (IMs) is nearly equal to that of extensive metabolizers (EMs), at 42.65% and 48.82% respectively, with genotypes *1/*2 (36.02%) and *1/*3 (6.63%). Likewise, poor metabolizers (PMs) with genotypes *2/*2 (6.16%), *2/*3 (2.37%), and *3/*3 (<1%) are more prevalent in our population as well. The distribution of CYP2C19 genotype and phenotype influenced by non-functional alleles has potential as a pharmacogenomics biomarker for precision medicine and is dependent on an ethnic-specific genetic variation database.

Twin Scholarships of Glycomedicine and Precision Medicine in Times of Single-Cell Multiomics.

Systems biology and multiomics research expand the prospects of planetary health innovations. In this context, this mini-review unpacks the twin scholarships of glycomedicine and precision medicine in the current era of single-cell multiomics. A significant growth in glycan research has been observed over the past decade, unveiling and establishing co- and post-translational modifications as dynamic indicators of both pathological and physiological conditions. Systems biology technologies have enabled large-scale and high-throughput glycoprofiling and access to data-intensive biological repositories for global research. These advancements have established glycans as a pivotal third code of life, alongside nucleic acids and amino acids. However, challenges persist, particularly in the simultaneous analysis of the glycome and transcriptome in single cells owing to technical limitations. In addition, holistic views of the complex molecular interactions between glycomics and other omics types remain elusive. We underscore and call for a paradigm shift toward the exploration of integrative glycan platforms and analysis methods for single-cell multiomics research and precision medicine biomarker discovery. The integration of multiple datasets from various single-cell omics levels represents a crucial application of systems biology in understanding complex cellular processes and is essential for advancing the twin scholarships of glycomedicine and precision medicine.

Tumor Size Is Not Everything: Advancing Radiomics as a Precision Medicine Biomarker in Oncology Drug Development and Clinical Care. A Report of a Multidisciplinary Workshop Coordinated by the RECIST Working Group.

Radiomics, the science of extracting quantifiable data from routine medical images, is a powerful tool that has many potential applications in oncology. The Response Evaluation Criteria in Solid Tumors Working Group (RWG) held a workshop in May 2022, which brought together various stakeholders to discuss the potential role of radiomics in oncology drug development and clinical trials, particularly with respect to response assessment. This article summarizes the results of that workshop, reviewing radiomics for the practicing oncologist and highlighting the work that needs to be done to move forward the incorporation of radiomics into clinical trials.

Pulmonologists’ Attitudes and Role in Precision Medicine Biomarker Testing for Non-Small Cell Lung Cancer

Despite advances in precision medicine for non-small cell lung cancer (NSCLC), biomarker testing for these therapies remain frequently underused, delayed, and inequitable. Pulmonologists often play a critical role in the initial diagnostic steps for patients with lung cancer, and previous data show variability in their knowledge and practices regarding biomarker testing. The purpose of this study is to better understand how pulmonologists view their role in lung cancer care. With the increasing importance of biomarker testing and precision medicine, how do pulmonologists view their role in lung cancer care? An electronic survey consisting of 31 items focused on attitudes and practices regarding diagnostic steps for NSCLC was randomly distributed to a sample of practicing pulmonologists in the American College of Chest Physicians (CHEST) analytics database. Inferential statistics were performed using χ2 tests and multivariable logistic regression models. A total of 401 pulmonologists responded to the survey. Most (92%) were general pulmonologists, and more than half (62%) indicate they order biomarker testing. Longer practice tenure, higher case volumes, and participation in a multidisciplinary tumor board were associated with ordering biomarkers (P< .05). Pulmonology was identified to have the leading responsibility for the initial diagnostic biopsy by most respondents (83%) and less often for staging (45%), leading discussions about biomarker testing with patients (28%), and for ordering biomarkers (22%). The most common reasons for not ordering biomarkers included the following: oncology was responsible (84%), it was not within their scope of practice (46%), or lack of the necessary knowledge (51%). Pulmonologists vary in their practices for ordering biomarkers, and many defer this responsibility to oncology. Despite the role of bronchoscopy and pulmonology societal guidelines for staging, many defer leadership of this process. Many pulmonologists lack the necessary resources and multidisciplinary infrastructure likely required to efficiently accomplish biomarker testing.

Integrating disulfidptosis-related long noncoding RNAs in colorectal cancer prognosis: A path to precision medicine.

This commentary explores the burgeoning field of disulfidptosis-related long noncoding RNAs (lncRNAs) in the prognosis and therapeutic targeting of colorectal cancer (CRC). By evaluating recent research, including the pivotal study "Predicting colorectal cancer prognosis based on long noncoding RNAs of disulfidptosis genes" by Wang et al, this analysis underscores the critical role of lncRNAs in deciphering the molecular complexities of CRC. Highlighting the innovative methodologies and significant findings, I discuss the implications for patient survival, therapeutic response, and the potential of lncRNAs as biomarkers for precision medicine. The integration of bioinformatics, clinical databases, and molecular biology in these studies offers a promising avenue for advancing CRC treatment strategies and improving patient outcomes.

Abstract PO4-05-03: Cell-free tumor DNA analysis in advanced or metastatic breast cancer patients enrolled in the German registry study PRAEGNANT

Abstract Background Accurate molecular profiling is crucial for optimal treatment decisions in advanced or metastatic breast cancer. Liquid biopsies, such as circulating cell-free tumor DNA (cfDNA, cftDNA or ctDNA), provide a non-invasive approach to monitor molecular alterations in the tumor. The German PRAEGNANT registry study aims to investigate such molecular biomarkers for precision medicine and their practical integration into clinical practice. In this context, cftDNA testing was performed as part of a PRAEGNANT research subproject, with the objectives of understanding the physician's rationale for initiating cftDNA testing, identifying detected alterations, and assessing the clinical impact of the associated findings Methods Patients with advanced or metastatic breast cancer were prospectively enrolled in the PRAEGNANT registry study (NCT02338167). The decision to undergo cftDNA testing was based on the physician's discretion. Blood samples were collected using Streck cfDNA BCT tubes and sent to the GUARDANT Health central laboratory for cftDNA extraction and subsequent next-generation sequencing analysis, employing the FDA-approved GUARDANT360 CDx test, a 74 gene panel including all guideline-recommended biomarkers, including single nucleotide variants (SNVs), indels, fusions and amplifications. Recruitment of patients occurred at four PRAEGNANT study centers between April 2022 and July 2023. The GUARDANT360 CDx report, along with a questionnaire regarding the testing intent and clinical impact of the results, was provided to the treating physician. Results 46 patients were eligible for analysis as per clinical characteristics. CftDNA analysis was successfully performed for all 46 cases. 38 (83%) harbored at least one somatic alteration in the analyzed genes. Fifteen patients (33%) harbored alterations in TP53, thirteen (28%) in PIK3CA. Five patients (11%) harbored mutations in ESR1. Somatic mutations in BRCA1 or BRCA2 were detected for five (11%) and six (13%) patients, respectively. One BRCA2 mutation was categorized as synonymous and one BRCA2 and three BRCA1 alterations as variants of uncertain significance. Eight patients (17%) harbored mutations in ATM. Most patients included were HR+HER2- (N=27, 58%). In this subgroup, eight (30%) patients had a PIK3CA alteration, five (19%) with an indication for treatment with alpelisib, eight (30%) a mutation in ATM, BRCA1 or BRCA2 and four (15%) in ESR1. Questionnaires regarding intention of testing and clinical impact were completed by 43 treating physicians (93%). Among them, 33% of patients had current indications for PARP inhibitor treatment, and 61% would consider it at the next change of therapy if a BRCA1 or BRCA2 mutation was detected. Additionally, 21% of patients had a current indication for alpelisib treatment if a relevant PIK3CA mutation was found, and 58% would consider it in the next line of treatment. Overall, cfDNA testing influenced the current or future treatment decisions in 35% of patients. Discussion The high prevalence of somatic alterations in TP53, PIK3CA, ESR1, and BRCA1/2 genes, identified through cftDNA testing with GUARDANT360 CDx, highlights their potential as biomarkers for targeted therapies in advanced/metastatic breast cancer. Detection of specific mutations influenced treatment decisions, such as eligibility for alpelisib or PARP inhibitors and might further facilitate treatment with elacestrant in future treatment lines after its approval in Germany. These findings demonstrate the clinical impact of cftDNA testing in guiding personalized treatment selection. Additionally, the identification of such somatic alterations within a registry study like PRAEGNANT presents a unique opportunity to consider enrolling these patients into biomarker-guided clinical trials. Citation Format: Hanna Hübner, Pauline Wimberger, Elena Laakmann, Eugen Ruckhäberle, Matthias Ruebner, Theresa Link, Erik Belleville, Iris Faull, Marcus Hausch, Diethelm Wallwiener, Andreas Schneeweiss, Hans Tesch, Sara Brucker, Peter A. Fasching, Volkmar Müller, Tanja Fehm. Cell-free tumor DNA analysis in advanced or metastatic breast cancer patients enrolled in the German registry study PRAEGNANT [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-05-03.

Abstract 4912: Unsupervised detection of stromal phenotypes with distinct fibrogenic and inflamed properties in NSCLC

Abstract Background: Understanding the composition of cancer-associated stroma (CAS) is vital, as the number and location of immune cells and fibroblasts, as well as the degree of extracellular matrix deposition, have implications for cancer progression and response to treatment, including in non-small cell lung cancer (NSCLC). Manual analysis of CAS does not fully describe the stromal milieu, especially from a spatial perspective, and is highly subjective. To this end, we have developed an unsupervised machine learning (ML) model to characterize the CAS in NSCLC from hematoxylin and eosin (H&amp;E) stained whole slide images (WSI) at scale. Methods: PathExploreTM models were deployed to predict stromal tissue and cell types, while another ML model was used to detect collagen fibers from H&amp;E stained WSIs from the TCGA LUAD (N=536) and LUSC (N=464) datasets. Stroma was divided into small regions (median = 0.02 mm2), and 88 features characterizing cell distribution, tissue composition and fiber density were extracted from each region. Graphs were generated connecting neighboring regions (nodes), and an unsupervised variational graph auto-encoder (VGAE) model was trained to learn 8 latent features through dimensionality reduction. Stromal phenotypes were then derived from the latent features using k-means clustering. The fraction of each phenotype in the stroma was correlated against immune- and stroma-related gene expression signatures (GES) and overall survival (OS). Results: Deployment of VGAE on LUAD and LUSC WSIs revealed three distinct stromal phenotypes - P0, P1 and P2. Fibroblast density was elevated in P0 and P1 regions (p&amp;lt;0.001), immune cell density was elevated in P2 regions (p&amp;lt;0.001), and collagen fiber intensity was highest in P1 regions (p&amp;lt;0.001). P2 enrichment was correlated with elevated expression of the T cell-inflamed gene expression profile (TGEP; Spearman ρ = 0.43 in LUAD; ρ = 0.27 in LUSC) and with improved OS (HR = 0.696; 95% CIs: 0.571-0.847 in LUSC). Conversely, P1 enrichment was positively associated with a transforming growth factor-β-induced cancer associated fibroblast GES (TGFβ-CAF: ρ = 0.19 in LUAD and ρ = 0.12 in LUSC) and poor OS (HR = 1.358; 95% CIs: 1.149-1.603 in LUSC). These phenotypes are consistent with fibroblast-enriched, collagen-depleted stroma (P0), collagen-rich, fibroblast-enriched tumor-promoting stroma (P1), and immune cell-enriched, tumor-suppressive stroma (P2). Conclusions: We describe an unsupervised, data-driven method of predicting stromal regions with discrete patterns of cell composition and collagen deposition in NSCLC. This approach identified three phenotypes of NSCLC stroma. These results highlight the ability of ML models to characterize and find meaningful patterns within the cell, tissue, and matrix components of a tumor. This work provides further evidence of the potential of ML to discover novel precision medicine biomarkers in NSCLC. Citation Format: Neel Patel, Nhat Le, Tan Nguyen, Fedaa Najdawi, Sandhya Srinivasan, Adam Stanford-Moore, Deeksha Kartik, Jun Zhang, Jacqueline Brosnan-Cashman, Robert Egger, Justin Lee, Matthew Bronnimann. Unsupervised detection of stromal phenotypes with distinct fibrogenic and inflamed properties in NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4912.

Microfluidic isolation of extrachromosomal circular DNA through selective digestion of plasmids and linear DNA using immobilized nucleases.

Extrachromosomal circular DNA (eccDNA) refers to small circular DNA molecules that are distinct from chromosomal DNA and play diverse roles in various biological processes. They are also explored as potential biomarkers for disease diagnosis and precision medicine. However, isolating eccDNA from tissues and plasma is challenging due to low abundance and the presence of interfering linear DNA, requiring time-consuming processes and expert handling. Our study addresses this by utilizing a microfluidic chip tailored for eccDNA isolation, leveraging microfluidic principles for enzymatic removal of non-circular DNA. Our approach involves integrating restriction enzymes into the microfluidic chip, enabling selective digestion of mitochondrial and linear DNA fragments while preserving eccDNA integrity. This integration is facilitated by an in situ photo-polymerized emulsion inside microchannels, creating a porous monolithic structure suitable for immobilizing restriction and exonuclease enzymes (restriction enzyme MssI and exonuclease ExoV). Evaluation using control DNA mixtures and plasma samples with artificially introduced eccDNA demonstrated that our microfluidic chips reduce linear DNA by over 99%, performing comparable to conventional off-chip methods but with substantially faster digestion times, allowing for a remarkable 76-fold acceleration in overall sample preparation time. This technological advancement holds great promise for enhancing the isolation and analysis of eccDNA from tissue and plasma and the potential for increasing the speed of other molecular methods with multiple enzymatic steps.

Immunomodulatory roles of metalloproteinases in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic, autoimmune pathology characterized by persistent synovial inflammation and gradually advancing bone destruction. Matrix metalloproteinases (MMPs), as a family of zinc-containing enzymes, have been found to play an important role in degradation and remodeling of extracellular matrix (ECM). MMPs participate in processes of cell proliferation, migration, inflammation, and cell metabolism. A growing number of persons have paid attention to their function in inflammatory and immune diseases. In this review, the details of regulation of MMPs expression and its expression in RA are summarized. The role of MMPs in ECM remodeling, angiogenesis, oxidative and nitrosative stress, cell migration and invasion, cytokine and chemokine production, PANoptosis and bone destruction in RA disease are discussed. Additionally, the review summarizes clinical trials targeting MMPs in inflammatory disease and discusses the potential of MMP inhibition in the therapeutic context of RA. MMPs may serve as biomarkers for drug response, pathology stratification, and precision medicine to improve clinical management of rheumatoid arthritis.

Machine learning-derived identification of tumor-infiltrating immune cell-related signature for improving prognosis and immunotherapy responses in patients with skin cutaneous melanoma

BackgroundImmunoblockade therapy based on the PD-1 checkpoint has greatly improved the survival rate of patients with skin cutaneous melanoma (SKCM). However, existing anti-PD-1 therapeutic efficacy prediction markers often exhibit a poor situation of poor reliability in identifying potential beneficiary patients in clinical applications, and an ideal biomarker for precision medicine is urgently needed.Methods10 multicenter cohorts including 4 SKCM cohorts and 6 immunotherapy cohorts were selected. Through the analysis of WGCNA, survival analysis, consensus clustering, we screened 36 prognostic genes. Then, ten machine learning algorithms were used to construct a machine learning-derived immune signature (MLDIS). Finally, the independent data sets (GSE22153, GSE54467, GSE59455, and in-house cohort) were used as the verification set, and the ROC index standard was used to evaluate the model.ResultsBased on computing framework, we found that patients with high MLDIS had poor overall survival and has good prediction performance in all cohorts and in-house cohort. It is worth noting that MLDIS performs better in each data set than almost all models which from 51 prognostic signatures for SKCM. Meanwhile, high MLDIS have a positive prognostic impact on patients treated with anti-PD-1 immunotherapy by driving changes in the level of infiltration of immune cells in the tumor microenvironment. Additionally, patients suffering from SKCM with high MLDIS were more sensitive to immunotherapy.ConclusionsOur study identified that MLDIS could provide new insights into the prognosis of SKCM and predict the immunotherapy response in patients with SKCM.

Clonal Hematopoiesis as a Molecular Risk Factor for Doxorubicin-Induced Cardiotoxicity: A Proof-of-Concept Study.

The main dose-limiting toxicity of anthracyclines is cardiotoxicity. Clonal hematopoiesis (CH), somatic mutations in hematopoietic stem or progenitor cells in patients without hematologic malignancy, is also associated with risk for adverse cardiovascular events and worse outcomes overall. We hypothesize that CH increases risk for doxorubicin-induced cardiotoxicity (DIC). We conducted a retrospective cohort study in patients treated with doxorubicin for cancer (N = 100). Patients (n = 25) had incident symptomatic heart failure, decline in left ventricular ejection fraction, or arrhythmia. CH was identified using paired peripheral blood and tumor DNA. After adjusting for age at doxorubicin initiation, diabetes, dyslipidemia, and chest radiation, high cumulative dose of doxorubicin (>240 mg/m2; odds ratio [OR], 7.00; 95% CI, 1.77 to 27.74; P = .0056), CH (OR, 8.58; 95% CI, 2.05 to 35.99; P = .0033), and history of smoking (OR, 3.15; 95% CI, 1.00 to 9.93; P = .0495) were associated with DIC. This study provides preliminary evidence for CH as a predictive risk factor for DIC, which, with further investigation, could serve as an important precision medicine biomarker for the large number of patients with cancer who have CH.

A novel RBBP8(p.E281*) germline mutation is a predisposing mutation in familial hereditary cancer syndrome.

Screening tumor susceptibility genes helps in identifying powerful biomarkers for hereditary cancer monitoring, prevention, and diagnosis, providing opportunities for understanding potential molecular mechanisms and biomarkers for the precise treatment of hereditary cancer syndromes. Whole-exome sequencing of blood and bioinformatics analysis uncovered a novel RBBP8(p.E281*) germline mutation in a family with hereditary cancer syndrome, which was verified by Sanger sequencing. Cell proliferation, colony formation, cell migration, and in vivo tumorigenesis were investigated by CCK8, colony formation, Transwell, and in vivo xenograft assays. Protein localization and interaction were detected by immunofluorescence, nuclear and cytoplasmic protein extraction kits, and Co-IP. A new heterozygous germline mutation of the RBBP8(p.E281*) gene was found to be associated with familial hereditary cancer syndrome. RBBP8-WT was mainly detected in the nucleus and interacts with BRCA1. In contrast, RBBP8(p.E281*) is mainly located in the cytoplasm, with no interaction with BRCA1. RBBP8(p.E281*) variant plays an oncogenic role in the cytoplasm in addition to its loss of function in the nucleus, which promotes breast cancer proliferation, in vivo tumorigenesis, and migration. Compared with the control group, RBBP8(p.E281*) showed elevated cell death in response to cisplatin and olaparib treatment. A novel RBBP8(p.E281*) germline mutation was identified from familial hereditary cancer syndrome. RBBP8(p.E281*) is not able to enter the nucleus or interact with BRCA1 through the lost binding motif, and RBBP8(p.E281*) variant appears to promote tumorigenesis in the cytoplasm in addition to its loss of function in the nucleus. RBBP8(p.E281*) variant may promote tumor susceptibility and serve as a precision medicine biomarker in familial hereditary cancer syndrome. KEY MESSAGES: RBBP8(p.E281*) is a susceptibility gene in this familial hereditary cancer syndrome RBBP8(p.E281*) lost its ability to enter the nucleus and the BRCA1 binding motif A novel RBBP8(p.E281*) germline mutation promotes breast cancer tumorigenesis Patients with RBBP8(p.E281*) germline mutation may benefit from Olaparib, Cisplatin.

CT radiomics analysis of primary colon cancer patients with or without liver metastases: a correlative study with [18F]FDG PET uptake values.

Utilizing [18F]Fluoro-2-deoxy-D-glucose Positron Emission Tomography/Computed Tomography ([18F]FDG PET/CT) scans on primary colon cancer (CC) patients including with liver metastases (LM), we aimed to determine the relationship between structural CT radiomic features and metabolic PET standard uptake value (SUV) in these patients. A retrospective analysis was performed on 60 patients with primary CC, of which 40 had liver metastases that were more than 2 cm in diameter. [18F]FDG PET/CT was used to calculate SUVmax, and 42 CT radiomic characteristics were extracted from non-enhanced CT images. Tumors were manually segmented on fused PET/CT scans by two experienced nuclear medicine physicians. Sixty primary CC and forty LM lesions were segmented accordingly. In the cases of multiple LM lesions, the lesion with the largest diameter was chosen for segmentation. In a univariate analysis approach, we used Spearman correlation with multiple testing correction (Benjamini-Hutchberg false discovery rate (FDR), α=0.05) to ascertain the relationship between SUVmax and CT radiomic features. Twenty-two (52.3%) and twenty-six (61.9%) CT radiomic features were found to be significantly correlated with SUVmax values of primary CC (n=60) and LM (n=40) lesions, respectively (FDR-corrected p value <0.05 and 0.6 < |ρ| < 1). GLCM_homogeneity (ρ = 0.839), GLCM_dissimilarity (ρ = -0.832), GLZLM_ZLNU (ρ = 0.827), and GLCM_contrast (ρ = -0.815) were the 4 features most correlated with SUVmax in CC. On the other hand, in LM, the 4 features most correlated with SUVmax were GLRLM_LRHGE (ρ = 0.859), GLRLM_LRE (ρ = 0.859), GLRLM_LRLGE (ρ = 0.857), and GLRLM_RP (ρ = -0.820). We investigated the relationship between SUVmax of preoperative primary CC lesions and their LM with CT radiomic features. We found some CT radiomic features having relationships with the metabolic characteristics of lesions. This work suggests that non-invasive predictive imaging biomarkers for precision medicine can be derived from CT radiomic.

Epigenetics of Early Cardiometabolic Disease: Mechanisms and Precision Medicine.

Epigenetics has transformed our understanding of the molecular basis of complex diseases, including cardiovascular and metabolic disorders. This review offers a comprehensive overview of the current state of knowledge on epigenetic processes implicated in cardiovascular and metabolic diseases, highlighting the potential of DNA methylation as a precision medicine biomarker and examining the impact of social determinants of health, gut bacterial epigenomics, noncoding RNA, and epitranscriptomics on disease development and progression. We discuss challenges and barriers to advancing cardiometabolic epigenetics research, along with the opportunities for novel preventive strategies, targeted therapies, and personalized medicine approaches that may arise from a better understanding of epigenetic processes. Emerging technologies, such as single-cell sequencing and epigenetic editing, hold the potential to further enhance our ability to dissect the complex interplay between genetic, environmental, and lifestyle factors. To translate research findings into clinical practice, interdisciplinary collaborations, technical and ethical considerations, and accessibility of resources and knowledge are crucial. Ultimately, the field of epigenetics has the potential to revolutionize the way we approach cardiovascular and metabolic diseases, paving the way for precision medicine and personalized health care, and improving the lives of millions of individuals worldwide affected by these conditions.

Immune Phenotype as a Biomarker for Systemic Lupus Erythematosus.

The treatment of rheumatoid arthritis was revolutionized with the use of molecular-targeted drugs that target immunoregulatory molecules. The success of treatment with these drugs prompted the development of molecular-targeted drugs for systemic lupus erythematosus. However, systemic lupus erythematosus is a disease with high heterogeneous immune abnormalities, and diverse cells or molecules can be treatment targets. Thus, the identification of subpopulations based on immune abnormalities is essential for the development of effective treatment. One analytical method used to identify subpopulations is the immunophenotyping of peripheral blood samples of patients. This analysis evaluates the validity of target molecules for peripheral blood immune cell subsets, which are expected to be developed as biomarkers for precision medicine in which appropriate treatment targets are set for each subpopulation.

Treatment response prediction with circulating tumor cell-derived organoids for soft tissue sarcoma.

e23521 Background: Pharmacologic treatment for soft tissue sarcoma (STS) remains challenging. There is a lack to predict treatment responses to chemotherapy or targeted therapy to oncologic drivers. We hypothesize that circulating tumor cells may enrich cancer initiating cells and represent a window to probe personalized drug treatment response. In this study, we test if drug sensitivity profile of short-term culture of tumor organoids derived from circulating tumor cells (CTCs) correlates to clinical treatment response. Methods: From April 2019 to December 2020, 50 patients with biopsy-confirmed STS, who had either recurrent or metastatic tumors, were enrolled in a prospective observational study in Taipei Medical University Hospital. The median age of the patients was 47, and the top 3 diagnoses were leiomyosarcoma, aggressive fibromatosis and rhabdomyosarcoma. 74% of patients had metastatic diseases at the time of blood collection. Fifty-five blood samples were collected and processed for CTC organoid culture and drug sensitivity analysis (EVASelect, CancerFree Biotech, Taipei, Taiwan), which involves culturing nucleated blood cells on a binary colloid crystal-coated surface. Clinical response was evaluated using RECIST criteria 3 months after blood collection. The relationship between CTC viability and clinical response was analyzed using a contingency table and Chi-square analysis. Results: The success rate of CTC expansion was 87.2% (48/55), as defined by ATP abundance higher than 3000 U2OS cells after 18 days of culture. Clinical information from 32 of the 50 cases was eligible for analysis, and the results showed that CTC viability at a 70% cutoff correlated with clinical disease control at 3 months after blood collection. The odds ratio, sensitivity, specificity, and diagnostic accuracy were 12 (p = 0.036), 92.3%, 50%, and 79%, respectively. A demonstration of the interaction between this research and the Molecular Tumor Board (MTB) in the Taipei Medical University Healthcare System is presented through a case study of metastatic angiosarcoma and its correlation. Conclusions: The study highlights the potential of using CTC drug sensitivity as a biomarker for precision medicine in STS, despite limitations such as small sample size, short follow-up, and disease and treatment heterogeneity. Advancements in gene-based precision medicine have been made in the past decade, but only a small number of STS patients have seen benefits from it. This emphasizes the need for further research to thoroughly evaluate the potential of CTC drug sensitivity as a predictive biomarker in clinical practice. Key words: soft tissue sarcoma; circulating tumor cells; liquid biopsy; predictive biomarker; precision medicine.

Glucocorticoid mediated inhibition of LKB1 mutant non-small cell lung cancers.

The glucocorticoid receptor (GR) is an important anti-cancer target in lymphoid cancers but has been understudied in solid tumors like lung cancer, although glucocorticoids are often given with chemotherapy regimens to mitigate side effects. Here, we identify a dexamethasone-GR mediated anti-cancer response in a subset of aggressive non-small cell lung cancers (NSCLCs) that harbor Serine/Threonine Kinase 11 (STK11/LKB1) mutations. High tumor expression of carbamoyl phosphate synthase 1 (CPS1) was strongly linked to the presence of LKB1 mutations, was the best predictor of NSCLC dexamethasone (DEX) sensitivity (p < 10-16) but was not mechanistically involved in DEX sensitivity. Subcutaneous, orthotopic and metastatic NSCLC xenografts, biomarker-selected, STK11/LKB1 mutant patient derived xenografts, and genetically engineered mouse models with KRAS/LKB1 mutant lung adenocarcinomas all showed marked in vivo anti-tumor responses with the glucocorticoid dexamethasone as a single agent or in combination with cisplatin. Mechanistically, GR activation triggers G1/S cell cycle arrest in LKB1 mutant NSCLCs by inducing the expression of the cyclin-dependent kinase inhibitor, CDKN1C/p57(Kip2). All findings were confirmed with functional genomic experiments including CRISPR knockouts and exogenous expression. Importantly, DEX-GR mediated cell cycle arrest did not interfere with NSCLC radiotherapy, or platinum response in vitro or with platinum response in vivo. While DEX induced LKB1 mutant NSCLCs in vitro exhibit markers of cellular senescence and demonstrate impaired migration, in vivo DEX treatment of a patient derived xenograft (PDX) STK11/LKB1 mutant model resulted in expression of apoptosis markers. These findings identify a previously unknown GR mediated therapeutic vulnerability in STK11/LKB1 mutant NSCLCs caused by induction of p57(Kip2) expression with both STK11 mutation and high expression of CPS1 as precision medicine biomarkers of this vulnerability.

TSLP and HMGB1: Inflammatory Targets and Potential Biomarkers for Precision Medicine in Asthma and COPD

The airway epithelium, through pattern recognition receptors expressed transmembrane or intracellularly, acts as a first line of defense for the lungs against many environmental triggers. It is involved in the release of alarmin cytokines, which are important mediators of inflammation, with receptors widely expressed in structural cells as well as innate and adaptive immune cells. Knowledge of the role of epithelial cells in orchestrating the immune response and mediating the clearance of invading pathogens and dead/damaged cells to facilitate resolution of inflammation is necessary to understand how, in many chronic lung diseases, there is a persistent inflammatory response that becomes the basis of underlying pathogenesis. This review will focus on the role of pulmonary epithelial cells and of airway epithelial cell alarmins, in particular thymic stromal lymphopoietin (TSLP) and high mobility group box 1 (HMGB1), as key mediators in driving the inflammation of chronic lung diseases, such as asthma and chronic obstructive pulmonary disease (COPD), evaluating the similarities and differences. Moreover, emerging concepts regarding the therapeutic role of molecules that act on airway epithelial cell alarmins will be explored for a precision medicine approach in the context of pulmonary diseases, thus allowing the use of these molecules as possible predictive biomarkers of clinical and biological response.