Noncoding RNome as Enabling Biomarkers for Precision Health.

Noncoding RNAs (ncRNAs), in the form of structural, catalytic or regulatory RNAs, have emerged to be critical effectors of many biological processes. With the advent of new technologies, we have begun to appreciate how intracellular and circulatory ncRNAs elegantly choreograph the regulation of gene expression and protein function(s) in the cell. Armed with this knowledge, the clinical utility of ncRNAs as biomarkers has been recently tested in a wide range of human diseases. In this review, we examine how critical factors govern the success of interrogating ncRNA biomarker expression in liquid biopsies and tissues to enhance our current clinical management of human diseases, particularly in the context of cancer. We also discuss strategies to overcome key challenges that preclude ncRNAs from becoming standard-of-care clinical biomarkers, including sample pre-analytics standardization, data cross-validation with closer attention to discordant findings, as well as correlation with clinical outcomes. Although harnessing multi-modal information from disease-associated noncoding RNome (ncRNome) in biofluids or in tissues using artificial intelligence or machine learning is at the nascent stage, it will undoubtedly fuel the community adoption of precision population health.

MicroRNAs as Potential Biomarkers in the Differential Diagnosis of Lipomatous Tumors and Their Mimics.

Adipocytic tumors are the most common subtype of soft tissue tumors. In current clinical practice, distinguishing benign lipomas from well-differentiated liposarcomas (WDLPS), as well as dedifferentiated liposarcomas (DDLPS) from their morphologic mimics, remains a significant diagnostic challenge. This is especially so when examining small biopsy samples and without the aid of additional ancillary tests. Recognizing the important role that microRNAs (miRNAs) play in tumorigenesis and their potential utility in tumor classification, we analyzed routine clinical tissue samples of benign and malignant lipomatous tumors, as well as other sarcoma mimics, to identify distinguishing miRNA-based signatures that can aid in the differential diagnosis of these entities. We discovered a 6-miRNA signature that separated lipomas from WDLPS with high confidence (AUC of 0.963), as well as a separate 6-miRNA signature that distinguished DDLPS from their more aggressive histologic mimics (AUC of 0.740). Functional enrichment analysis unveiled possible mechanistic involvement of these predictive miRNAs in adipocytic cancer-related biological processes and pathways such as PI3K/AKT/mTOR and MAPK signaling, further supporting the relevance of these miRNAs as biomarkers for adipocytic tumors. Our results demonstrate that miRNA expression profiling may potentially be used as an adjunctive tool for the diagnosis of benign and malignant adipocytic tumors. Further validation studies are warranted.

Advances in quantifying circulatory microRNA for early disease detection.

Precision preventive healthcare aims to improve patient health by integrating preventive measures with early disease detection for timely intervention with precision medicine. Key to the delivery of preventive healthcare is the clinical adoption of novel assays that enable early disease detection. Such assays, typically based on biomarkers such as microRNAs (miRNAs) from liquid biopsy or excreta, are entering clinical practice after years of clinical development and validation. In this review, we discuss the clinical utility and validation of miRNA-based molecular diagnostics for early disease detection through large-cohort studies and key considerations for developing multi-analyte clinical assays. We also highlight recent advances in the ongoing development of integrated PCR-free miRNA detection systems for point-of-care testing.

Development and validation of a circulating microRNA panel for the early detection of breast cancer.

BACKGROUND: Mammography is widely used for breast cancer screening but suffers from a high false-positive rate. Here, we perform the largest comprehensive, multi-center study to date involving diverse ethnic groups, for the identification of circulating miRNAs for breast cancer screening. METHODS: This study had a discovery phase (n = 289) and two validation phases (n = 374 and n = 379). Quantitative PCR profiling of 324 miRNAs was performed on serum samples from breast cancer (all stages) and healthy subjects to identify miRNA biomarkers. Two-fold cross-validation was used for building and optimising breast cancer-associated miRNA panels. An optimal panel was validated in cohorts with Caucasian and Asian samples. Diagnostic ability was evaluated using area under the curve (AUC) analysis. RESULTS: The study identified and validated 30 miRNAs dysregulated in breast cancer. An optimised eight-miRNA panel showed consistent performance in all cohorts and was successfully validated with AUC, accuracy, sensitivity, and specificity of 0.915, 82.3%, 72.2% and 91.5%, respectively. The prediction model detected breast cancer in both Caucasian and Asian populations with AUCs ranging from 0.880 to 0.973, including pre-malignant lesions (stage 0; AUC of 0.831) and early-stage (stages I-II) cancers (AUC of 0.916). CONCLUSIONS: Our panel can potentially be used for breast cancer screening, in conjunction with mammography.

Development of a microRNA Panel for Classification of Abnormal Mammograms for Breast Cancer.

Mammography is extensively used for breast cancer screening but has high false-positive rates. Here, prospectively collected blood samples were used to identify circulating microRNA (miRNA) biomarkers to discriminate between malignant and benign breast lesions among women with abnormal mammograms. The Discovery cohort comprised 72 patients with breast cancer and 197 patients with benign breast lesions, while the Validation cohort had 73 and 196 cancer and benign cases, respectively. Absolute expression levels of 324 miRNAs were determined using RT-qPCR. miRNA biomarker panels were identified by: (1) determining differential expression between malignant and benign breast lesions, (2) focusing on top differentially expressed miRNAs, and (3) building panels from an unbiased search among all expressed miRNAs. Two-fold cross-validation incorporating a feature selection algorithm and logistic regression was performed. A six-miRNA biomarker panel identified by the third strategy, had an area under the curve (AUC) of 0.785 and 0.774 in the Discovery and Validation cohorts, respectively, and an AUC of 0.881 when differentiating between cases versus those with benign lesions or healthy individuals with normal mammograms. Biomarker panel scores increased with tumor size, stage and number of lymph nodes involved. Our work demonstrates that circulating miRNA signatures can potentially be used with mammography to differentiate between patients with malignant and benign breast lesions.

Development and validation of a serum microRNA biomarker panel for detecting gastric cancer in a high-risk population.

OBJECTIVE: An unmet need exists for a non-invasive biomarker assay to aid gastric cancer diagnosis. We aimed to develop a serum microRNA (miRNA) panel for identifying patients with all stages of gastric cancer from a high-risk population. DESIGN: We conducted a three-phase, multicentre study comprising 5248 subjects from Singapore and Korea. Biomarker discovery and verification phases were done through comprehensive serum miRNA profiling and multivariant analysis of 578 miRNA candidates in retrospective cohorts of 682 subjects. A clinical assay was developed and validated in a prospective cohort of 4566 symptomatic subjects who underwent endoscopy. Assay performance was confirmed with histological diagnosis and compared with Helicobacter pylori (HP) serology, serum pepsinogens (PGs), 'ABC' method, carcinoembryonic antigen (CEA) and cancer antigen 19-9 (CA19-9). Cost-effectiveness was analysed using a Markov decision model. RESULTS: We developed a clinical assay for detection of gastric cancer based on a 12-miRNA biomarker panel. The 12-miRNA panel had area under the curve (AUC)=0.93 (95% CI 0.90 to 0.95) and AUC=0.92 (95% CI 0.88 to 0.96) in the discovery and verification cohorts, respectively. In the prospective study, overall sensitivity was 87.0% (95% CI 79.4% to 92.5%) at specificity of 68.4% (95% CI 67.0% to 69.8%). AUC was 0.848 (95% CI 0.81 to 0.88), higher than HP serology (0.635), PG 1/2 ratio (0.641), PG index (0.576), ABC method (0.647), CEA (0.576) and CA19-9 (0.595). The number needed to screen is 489 annually. It is cost-effective for mass screening relative to current practice (incremental cost-effectiveness ratio=US$44 531/quality-of-life year). CONCLUSION: We developed and validated a serum 12-miRNA biomarker assay, which may be a cost-effective risk assessment for gastric cancer. TRIAL REGISTRATION NUMBER: This study is registered with ClinicalTrials.gov (Registration number: NCT04329299).

Functional genomics identifies specific vulnerabilities in PTEN-deficient breast cancer.

BACKGROUND: Phosphatase and tensin homolog (PTEN) is one of the most frequently inactivated tumor suppressors in breast cancer. While PTEN itself is not considered a druggable target, PTEN synthetic-sick or synthetic-lethal (PTEN-SSL) genes are potential drug targets in PTEN-deficient breast cancers. Therefore, with the aim of identifying potential targets for precision breast cancer therapy, we sought to discover PTEN-SSL genes present in a broad spectrum of breast cancers. METHODS: To discover broad-spectrum PTEN-SSL genes in breast cancer, we used a multi-step approach that started with (1) a genome-wide short interfering RNA (siRNA) screen of ~ 21,000 genes in a pair of isogenic human mammary epithelial cell lines, followed by (2) a short hairpin RNA (shRNA) screen of ~ 1200 genes focused on hits from the first screen in a panel of 11 breast cancer cell lines; we then determined reproducibility of hits by (3) identification of overlaps between our results and reanalyzed data from 3 independent gene-essentiality screens, and finally, for selected candidate PTEN-SSL genes we (4) confirmed PTEN-SSL activity using either drug sensitivity experiments in a panel of 19 cell lines or mutual exclusivity analysis of publicly available pan-cancer somatic mutation data. RESULTS: The screens (steps 1 and 2) and the reproducibility analysis (step 3) identified six candidate broad-spectrum PTEN-SSL genes (PIK3CB, ADAMTS20, AP1M2, HMMR, STK11, and NUAK1). PIK3CB was previously identified as PTEN-SSL, while the other five genes represent novel PTEN-SSL candidates. Confirmation studies (step 4) provided additional evidence that NUAK1 and STK11 have PTEN-SSL patterns of activity. Consistent with PTEN-SSL status, inhibition of the NUAK1 protein kinase by the small molecule drug HTH-01-015 selectively impaired viability in multiple PTEN-deficient breast cancer cell lines, while mutations affecting STK11 and PTEN were largely mutually exclusive across large pan-cancer data sets. CONCLUSIONS: Six genes showed PTEN-SSL patterns of activity in a large proportion of PTEN-deficient breast cancer cell lines and are potential specific vulnerabilities in PTEN-deficient breast cancer. Furthermore, the NUAK1 PTEN-SSL vulnerability identified by RNA interference techniques can be recapitulated and exploited using the small molecule kinase inhibitor HTH-01-015. Thus, NUAK1 inhibition may be an effective strategy for precision treatment of PTEN-deficient breast tumors.

Genetic and bioinformatic analyses of the expression and function of PI3K regulatory subunit PIK3R3 in an Asian patient gastric cancer library.

BACKGROUND: While there is strong evidence for phosphatidylinositol 3-kinase (PI3K) involvement in cancer development, there is limited information about the role of PI3K regulatory subunits. PIK3R3, the gene that encodes the PI3K regulatory subunit p55γ, is over-expressed in glioblastoma and ovarian cancers, but its expression in gastric cancer (GC) is not known. We thus used genetic and bioinformatic approaches to examine PIK3R3 expression and function in GC, the second leading cause of cancer mortality world-wide and highly prevalent among Asians. METHODS: Primary GC and matched non-neoplastic mucosa tissue specimens from a unique Asian patient gastric cancer library were comprehensively profiled with platforms that measured genome-wide mRNA expression, DNA copy number variation, and DNA methylation status. Function of PIK3R3 was predicted by IPA pathway analysis of co-regulated genes with PIK3R3, and further investigated by siRNA knockdown studies. Cell proliferation was estimated by crystal violet dye elution and BrdU incorporation assay. Cell cycle distribution was analysed by FACS. RESULTS: PIK3R3 was significantly up-regulated in GC specimens (n = 126, p < 0.05), and 9.5 to 15% tumors showed more than 2 fold increase compare to the paired mucosa tissues. IPA pathway analysis showed that PIK3R3 promoted cellular growth and proliferation. Knockdown of PIK3R3 decreased the growth of GC cells, induced G0/G1 cell cycle arrest, decreased retinoblastoma protein (Rb) phosphorylation, cyclin D1, and PCNA expression. CONCLUSION: Using a combination of genetic, bioinformatic, and molecular biological approaches, we showed that PIK3R3 was up-regulated in GC and promoted cell cycle progression and proliferation; and thus may be a potential new therapeutic target for GC.

DNA-directed assembly of protein microarrays.

Microarray technology has made it possible to simultaneously study the abundance, interactions, and functions of potentially tens of thousands of biological molecules. From its earliest use in DNA microarrays, where only nucleic acids were captured and detected on the arrays, applications of microarrays now extend to those involving biomolecules such as antibodies, proteins, peptides, and carbohydrates. In contrast to the relative robustness of DNA microarrays, the use of such chemically diverse biomolecules on microarray formats presents many challenges in their fabrication as well as application. Among the many methods that have been proposed to overcome these challenges, DNA-directed assembly (DDA) has emerged as a promising strategy for the high sensitivity and multiplexed capture and detection of various analytes. In this review, we explore the challenges faced during the design, fabrication, and utilization of protein microarrays and highlight how DDA strategies, together with other recent advances in the field, are accelerating the development of platforms available for protein microarray applications.

Spatially addressable protein array: ssDNA-directed assembly for antibody microarray.

Protein microarray offers a means for high-throughput profiling of cellular proteins to provide insights into the mechanisms of biological processes. This study describes the design and fabrication of a robust platform, spatially addressable protein array (SAPA), by exploring the specificity of ssDNA hybridization for self-assembly of semi-synthetic ssDNA-antibody conjugates which capture antigens from complex biological samples. This approach does not involve the direct immobilization of antibodies nor antigen, but instead captures the target antigens in the solution phase followed by self-directed assembly of the complex onto the surface. In an effort to optimize the platform, the effects of surface chemistry, nonspecific protein adsorption, facile preparation, and purification of ssDNA-conjugated antibody and capture of the antigen from a complex biological sample such as cell lysate were examined. This platform allowed antigen detection in cell lysate with high sensitivity (1 pM). The method described herein can be extended to the high-throughput detection of other interacting molecules in solution phase and their subsequent assembly onto any substrate.

Carboxyl-terminated dendrimer-coated bioactive interface for protein microarray: high-sensitivity detection of antigen in complex biological samples.

Protein microarrays are promising tools that can potentially enable high throughput proteomic screening in areas such as disease diagnosis and drug discovery. A critical aspect in the development of protein microarrays is the optimization of the array's surface chemistry to achieve the high sensitivity required for detection of proteins in cell lysate and other complex biological mixtures. In the present study, a high-density antibody array with minimal nonspecific cellular protein adsorption was prepared using a glass surface coated with a poly(propyleneimine) dendrimer terminated with carboxyl group (PAMAM-COOH). The carboxyl-terminated dendrimer-modified surface has almost similar nonspecific cellular protein adsorption when compared to an inert PEG-modified surface. In addition, the multiple functional sites available for reaction on the dendrimer surface facilitated high-density immobilization of antibodies and efficient capture of bioanalytes. Various molecules were tested for their ability to block or deactivate the reactive carboxyl surface after antibody immobilization to further reduce the nonspecific binding. A short oligoethylene glycol (NH2-d4-PEG-COOH), was found to significantly improve the signal-to-noise ratio of the assay, resulting in higher sensitivity. The properties and functional qualities of the various surfaces were characterized by contact angle and AFM measurements. Nonspecific protein adsorption and protein immobilization as a function of dendrimer generations and sensitivity of antigen capturing from a buffer (1 pM) as well as from the complex cell lysate (10 pM) system were examined. Our detailed experimental studies demonstrated a facile method of preparing surfaces with high protein loading and low nonspecific protein binding for the development of high sensitivity protein microarrays.