Publications

For cells the passage from life to death can involve a regulated, programmed transition. In contrast to cell death, the mechanisms of systemic collapse underlying organismal death remain poorly understood. Here we present evidence of a cascade of cell death involving the calpain-cathepsin necrosis pathway that can drive organismal death in Caenorhabditis elegans. We report that organismal death is accompanied by a burst of intense blue fluorescence, generated within intestinal cells by the necrotic cell death pathway. Such death fluorescence marks an anterior to posterior wave of intestinal cell death that is accompanied by cytosolic acidosis. This wave is propagated via the innexin INX-16, likely by calcium influx. Notably, inhibition of systemic necrosis can delay stress-induced death. We also identify the source of the blue fluorescence, initially present in intestinal lysosome-related organelles (gut granules), as anthranilic acid glucosyl esters–not, as previously surmised, the damage product lipofuscin. Anthranilic acid is derived from tryptophan by action of the kynurenine pathway. These findings reveal a central mechanism of organismal death in C. elegans that is related to necrotic propagation in mammals–e.g., in excitotoxicity and ischemia-induced neurodegeneration. Endogenous anthranilate fluorescence renders visible the spatio-temporal dynamics of C. elegans organismal death.

MicroRNAs (miRNAs) have emerged as key genetic regulators of a wide variety of biological processes, including growth, proliferation, and survival. Recent advances have led to the recognition that miRNAs can act as potent oncogenes and tumor suppressors, playing crucial roles in the initiation, maintenance, and progression of the oncogenic state in a variety of cancers. Determining how miRNA expression and function is altered in cancer is an important goal, and a necessary prerequisite to the development and adoption of miRNA-based therapeutics in the clinic. Highly promising clinical applications of miRNAs are the use of miRNA signatures as biomarkers for cancer (for example, for early detection or diagnosis), and therapeutic supplementation or inhibition of specific miRNAs to alter the cancer phenotype. In this review, we discuss the main methods used for miRNA profiling, and examine key miRNAs that are commonly altered in a variety of tumors. Current studies underscore the functional versatility and potency of miRNAs in various aspects of the cancer phenotype, pointing to their potential clinical applications. Consequently, we discuss the application of miRNAs as biomarkers, clinical agents, and therapeutic targets, highlighting both the enormous potential and major challenges in this field.

Targeted therapeutic approaches have seen tremendous advances in the last decade, for good reason. Specifically intervening with a disease-causing gene can revert the deleterious phenotype while eliminating the toxicity often associated with broad-spectrum agents. Unfortunately, because these selective agents hit one target in a single location, acquired resistance is often high. An arguably better treatment approach includes coupling multiple targeted agents or using an agent that hits an individual target in several independent locations and/or alters multiple relevant targets in the disease-causing pathway(s), precisely the approach taken by Nishimura and colleagues in their recent report aimed at identifying a better treatment option for ovarian cancer.

Dysregulation of microRNAs (miRNAs), particularly their downregulation, has been widely shown to be associated with the development of lung cancer. Downregulation of miRNAs leads to the overactivation of their oncogene targets, while upregulation of some miRNAs leads to inhibition of important tumor suppressors. Research has implicated cigarette smoke in miRNA dysregulation, leading to carcinogenesis. Cigarette smoke may lead to genetic or epigenetic damage to miRNAs, many of which map to fragile sites and some of which contain single nucleotide polymorphisms. Cigarette smoke may also cause dysregulation by affecting regulatory mechanisms controlling miRNA expression. Researchers have shown a correlation between smoke-exposure-induced dysregulation of miRNAs and age. Furthermore, dysregulation seems to be associated with intensity and duration of smoke exposure and duration of cessation. Longer exposure at a threshold level is needed for irreversibility of changes in expression. Better understanding of miRNA dysregulation may allow for improved biomonitoring and treatment regimens for lung cancer.

The KRAS-variant is a germline single nucleotide polymorphism (SNP) within the 3'UTR of the KRAS gene predicted to disrupt a complementary binding site (LCS6) for the let-7 microRNA (miRNA). The KRAS-variant is associated with increased risk of various cancers, including lung cancer, ovarian cancer and triple-negative breast cancer, and is associated with altered tumor biology in head and neck cancer, colon cancer and melanoma. To better understand the molecular pathways that may be regulated or affected by the presence of the KRAS-variant allele in cancer cells, we examined its prevalence in the NCI-60 panel of cell lines and sought to identify common features of the cell lines that carry the variant allele. This study provides a step forward towards understanding the molecular and pathological significance of the KRAS-variant.

Comment on: Cirera-Salinas D, et al. Cell Cycle 2012; 11:922–33

MicroRNAs (miRNAs) are a class of short non-coding RNAs that bind mRNAs through partial base-pair complementarity with their target genes, resulting in post-transcriptional repression of gene expression. The role of miRNAs in controlling aging processes has been uncovered recently with the discovery of miRNAs that regulate lifespan in the nematode Caenorhabditis elegans through insulin and insulin-like growth factor-1 signaling and DNA damage checkpoint factors. Furthermore, numerous miRNAs are differentially expressed during aging in C. elegans, but the specific functions of many of these miRNAs are still unknown. Recently, various miRNAs have been identified that are up- or down-regulated during mammalian aging by comparing their tissue-specific expression in younger and older mice. In addition, many miRNAs have been implicated in governing senescence in a variety of human cell lines, and the precise functions of some of these miRNAs in regulating cellular senescence have helped to elucidate mechanisms underlying aging. In this Commentary, we review the various regulatory roles of miRNAs during aging processes. We highlight how certain miRNAs can regulate aging on the level of organism lifespan, tissue aging or cellular senescence. Finally, we discuss future approaches that might be used to investigate the mechanisms by which miRNAs govern aging processes.

It has long been established that cancers can become addicted to particular oncogenes. Despite the genetic complexity that governs tumorigenesis, certain cancers can exhibit a critical dependency on the expression of a single oncogene, which when removed leads to death of the cancer cell. Recent observations on the relationships between regulatory RNAs and cancer have revealed that this concept of oncogene addiction extends to microRNAs (miRNAs) as well. Certain cancers exhibit a dependency on the expression of a single oncogenic miRNA, or oncomiR. The field of miRNA biology and its involvement in diseases such as cancer have seen tremendous advances over the past decade. However, little is known about the phenomenon of oncomiR addiction. In this review, we introduce the concept of proto-oncomiRs, or miRNAs that gain oncogenic activity after an initiating event. Furthermore, by highlighting the role of proto-oncomiRs in generating malignant phenotypes, we glean possible insights into the mechanisms that guide oncomiR addiction. In addition, toward the realization of genetically driven personalized medicine, some of the most clinically successful anticancer strategies have involved targeting addictive oncogenes such as HER2, BCR/ABL, EGFR, and VEGF. Elucidating how addictive miRNAs can perpetuate cancer may reveal additional critical molecular targets to exploit for therapeutic purposes. Therefore, in this review, we also summarize the field of anti-miRNA therapeutics, in which antisense and nanoscale delivery technologies are the driving force. Addictive oncomiRs are a double-edged sword; addicted cancers are dependent on oncomiRs that are highly potent therapeutic targets. Dissection of this phenomenon may reveal the mechanisms through which lynchpin miRNAs can perpetuate cancer and present a new paradigm for miRNA-based cancer therapy.

Next-generation sequencing is widely used to study complex diseases because of its ability to identify both common and rare variants without prior single nucleotide polymorphism (SNP) information. Pooled sequencing of implicated target regions can lower costs and allow more samples to be analyzed, thus improving statistical power for disease-associated variant detection. Several methods for disease association tests of pooled data and for optimal pooling designs have been developed under certain assumptions of the pooling process, for example, equal/unequal contributions to the pool, sequencing depth variation, and error rate. However, these simplified assumptions may not portray the many factors affecting pooled sequencing data quality, such as PCR amplification during target capture and sequencing, reference allele preferential bias, and others. As a result, the properties of the observed data may differ substantially from those expected under the simplified assumptions. Here, we use real datasets from targeted sequencing of pooled samples, together with microarray SNP genotypes of the same subjects, to identify and quantify factors (biases and errors) affecting the observed sequencing data. Through simulations, we find that these factors have a significant impact on the accuracy of allele frequency estimation and the power of association tests. Furthermore, we develop a workflow protocol to incorporate these factors in data analysis to reduce the potential biases and errors in pooled sequencing data and to gain better estimation of allele frequencies. The workflow, Psafe, is available at http://bioinformatics.med.yale.edu/group/.