Pharma's Bio-AI revolution.

Drug development has become unbearably slow and expensive. A key underlying problem is the clinical prediction challenge: the inability to predict which drug candidates will be safe in the human body and for whom. Recently, a dramatic regulatory change has removed FDA's mandated reliance on antiquated, ineffective animal studies. A new frontier is an integration of several disruptive technologies [machine learning (ML), patient-on-chip, real-time sensing, and stem cells], which when integrated, have the potential to address this challenge, drastically cutting the time and cost of developing drugs, and tailoring them to individual patients.

MicroRNAs accurately identify cancer tissue origin.

MicroRNAs (miRNAs) belong to a class of noncoding, regulatory RNAs that is involved in oncogenesis and shows remarkable tissue specificity. Their potential for tumor classification suggests they may be used in identifying the tissue in which cancers of unknown primary origin arose, a major clinical problem. We measured miRNA expression levels in 400 paraffin-embedded and fresh-frozen samples from 22 different tumor tissues and metastases. We used miRNA microarray data of 253 samples to construct a transparent classifier based on 48 miRNAs. Two-thirds of samples were classified with high confidence, with accuracy >90%. In an independent blinded test-set of 83 samples, overall high-confidence accuracy reached 89%. Classification accuracy reached 100% for most tissue classes, including 131 metastatic samples. We further validated the utility of the miRNA biomarkers by quantitative RT-PCR using 65 additional blinded test samples. Our findings demonstrate the effectiveness of miRNAs as biomarkers for tracing the tissue of origin of cancers of unknown primary origin.

Identifying human microRNAs.

MicroRNAs are a recently discovered group of short, non-coding RNA regulatory genes found in many species including humans. Originally viewed as a rare curiosity, over a thousand peer-reviewed publications have now established their major role in health and disease. MicroRNA discovery approaches, both biological and computational, have played an important role in this enfolding drama, and have led to the discovery of many hundreds of novel microRNAs. These different discovery and validation approaches are briefly reviewed here, as are the challenges and questions that lie ahead.

Prediction and validation of microRNAs and their targets.

MicroRNAs are short non-coding RNAs that inhibit translation of target genes by binding to their mRNAs, and have been shown to play a central role in gene regulation in health and disease. Sophisticated computer-based prediction approaches of microRNAs and of their targets, and effective biological validation techniques for validating these predictions, now play a central role in discovery of microRNAs and elucidating their functions.

Identification of hundreds of conserved and nonconserved human microRNAs.

MicroRNAs are noncoding RNAs of approximately 22 nucleotides that suppress translation of target genes by binding to their mRNA and thus have a central role in gene regulation in health and disease. To date, 222 human microRNAs have been identified, 86 by random cloning and sequencing, 43 by computational approaches and the rest as putative microRNAs homologous to microRNAs in other species. To prove our hypothesis that the total number of microRNAs may be much larger and that several have emerged only in primates, we developed an integrative approach combining bioinformatic predictions with microarray analysis and sequence-directed cloning. Here we report the use of this approach to clone and sequence 89 new human microRNAs (nearly doubling the current number of sequenced human microRNAs), 53 of which are not conserved beyond primates. These findings suggest that the total number of human microRNAs is at least 800.

A postulated role for microRNA in cellular differentiation.

Over the past two decades a variety of mechanisms regulating cellular differentiation have been uncovered. These include signaling by morphogens or membrane-associated ligands and asymmetric segregation of cytoplasmic components. Most of these processes are driven by protein coding genes. Here I describe another possible cellular differentiation mechanism that involves asymmetric segregation of microRNAs, a group of recently discovered non-protein coding genes that have been shown to be involved in differentiation.

MicroRNA expression detected by oligonucleotide microarrays: system establishment and expression profiling in human tissues.

MicroRNAs (MIRs) are a novel group of conserved short approximately 22 nucleotide-long RNAs with important roles in regulating gene expression. We have established a MIR-specific oligonucleotide microarray system that enables efficient analysis of the expression of the human MIRs identified so far. We show that the 60-mer oligonucleotide probes on the microarrays hybridize with labeled cRNA of MIRs, but not with their precursor hairpin RNAs, derived from amplified, size-fractionated, total RNA of human origin. Signal intensity is related to the location of the MIR sequences within the 60-mer probes, with location at the 5' region giving the highest signals, and at the 3' end, giving the lowest signals. Accordingly, 60-mer probes harboring one MIR copy at the 5' end gave signals of similar intensity to probes containing two or three MIR copies. Mismatch analysis shows that mutations within the MIR sequence significantly reduce or eliminate the signal, suggesting that the observed signals faithfully reflect the abundance of matching MIRs in the labeled cRNA. Expression profiling of 150 MIRs in five human tissues and in HeLa cells revealed a good overall concordance with previously published results, but also with some differences. We present novel data on MIR expression in thymus, testes, and placenta, and have identified MIRs highly enriched in these tissues. Taken together, these results highlight the increased sensitivity of the DNA microarray over other methods for the detection and study of MIRs, and the immense potential in applying such microarrays for the study of MIRs in health and disease.