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Biomedical subjects

Isaac Kohane

Publications and source records attributed to Isaac Kohane.

9 recordsLinked to original sources

Comprehensive Genomic Analysis of Normal and Cancer Cells Elucidates the Elevated Mutation Burden in Cancer.

Self-renewing normal tissues generate several somatic mutations at each division. Previous studies have reported that cancer cells have more mutations than their normal counterparts. It is not obvious why dramatic differences in mutation burdens between normal tissues and cancers should exist. To fully understand human tumorigenesis, the increase of mutation burden in cancers will have to be understood. Here, we provided a systematic comparison of mutational burdens in normal and cancer cells from five different organs, revealing a four-fold increase of mutation burdens in cancerous vs. non-cancerous cells. Three proposed hypotheses that could account for the increased mutation burdens in cancer are: the classical hypothesis, where driver gene mutations explain the higher mutational burden; the catastrophic hypothesis, where extreme mutational events lead to large-scale genomic alterations; and the tail hypothesis, where differences in baseline mutation rates among individuals account for the differences. Testing through orthogonal observations showed that the observed medians and distributions of mutation burdens in cancers could be explained by the hypotheses to various degrees of significance, and only the tail hypothesis could easily explain the increase in median mutation burdens in the normal tissues of cancer patients compared to the normal tissues of non-cancer patients. Overall, this study characterizes an increased mutation burden across multiple types of cancer compared to normal tissue and provides insights into the contributing factors. A tenable hypothesis proposed in this study involving fundamental differences in baseline mutation rates among individuals could have implications for cancer prevention strategies.

Journal Article↗

Differences in gene expression profiles of diabetic and nondiabetic patients undergoing cardiopulmonary bypass and cardioplegic arrest.

BACKGROUND: Diabetes mellitus is an independent risk factor for early postoperative mortality and complications after coronary artery bypass grafting (CABG). We sought to compare the cardiac gene expression responses to cardiopulmonary bypass (CPB) and cardioplegic arrest (C) in patients with and without diabetes. METHODS AND RESULTS: Twenty atrial myocardium samples were harvested from 5 type II insulin-dependent diabetic and 5 matched nondiabetic patients undergoing CABG, before and after CPB/C. Oligonucleotide microarray analyses of 12625 genes were performed on the 10 sample pairs using matched pre-CPB tissues as controls. Array results were validated with Northern blotting and immunoblotting. Compared with pre-CPB/C, post-CPB/C myocardial tissues revealed 851 upregulated and 480 downregulated genes with a threshold P< or =0.025 (signal-to-noise ratio, 4.04) in the diabetic group, compared with 480 upregulated and 626 downregulated genes (signal-to-noise ratio, 3.04) in the nondiabetic group (P<0.001). There were 18 genes that were upregulated >4-fold in diabetic and nondiabetic patients (including inflammatory/transcription activators FOS, CYR 61, and IL-6, apoptotic gene NR4A1, stress gene DUSP1, and glucose-transporter gene SLC2A3). However, 28 genes showed such marked upregulation in the diabetic group exclusively (including inflammatory/transcription activators MYC, IL8, IL-1beta, growth factor vascular endothelial growth factor, amphiregulin, and glucose metabolism-involved gene insulin receptor substrate 1), and 27 genes in the nondiabetic group only, including glycogen-binding subunit PPP1R3C. CONCLUSIONS: Gene expression profile after CPB/C is quantitatively and qualitatively different in patients with diabetes. These results have important implications for the design of tailored myocardial protection and operative strategies for diabetic patients undergoing CPB/C.

Actins↗

Increased measurement accuracy for sequence-verified microarray probes.

Microarrays have been extensively used to investigate genome-wide expression patterns. Although this technology has been tremendously successful, it has suffered from suboptimal individual measurement precision. Significant improvements in this respect have been recently made. In an effort to further explore the underlying variability, we have attempted to globally assess the accuracy of individual probe sequences used to query gene expression. For mammalian Affymetrix microarrays, we identify an unexpectedly large number of probes (greater than 19% of the probes on each platform) that do not correspond to their appropriate mRNA reference sequence (RefSeq). Compared with data derived from inaccurate probes, we find that data derived from sequence-verified probes show 1) increased precision in technical replicates, 2) increased accuracy translating data from one generation microarray to another, 3) increased accuracy translating data from oligonucleotide to cDNA microarrays, and 4) improved capture of biological information in human clinical specimens. The logical conclusion of this work is that probes containing the most reliable sequence information provide the most accurate results. Our data reveal that the identification and removal of inaccurate probes can significantly improve this technology.

Breast↗

Gene regulation and DNA damage in the ageing human brain.

The ageing of the human brain is a cause of cognitive decline in the elderly and the major risk factor for Alzheimer's disease. The time in life when brain ageing begins is undefined. Here we show that transcriptional profiling of the human frontal cortex from individuals ranging from 26 to 106 years of age defines a set of genes with reduced expression after age 40. These genes play central roles in synaptic plasticity, vesicular transport and mitochondrial function. This is followed by induction of stress response, antioxidant and DNA repair genes. DNA damage is markedly increased in the promoters of genes with reduced expression in the aged cortex. Moreover, these gene promoters are selectively damaged by oxidative stress in cultured human neurons, and show reduced base-excision DNA repair. Thus, DNA damage may reduce the expression of selectively vulnerable genes involved in learning, memory and neuronal survival, initiating a programme of brain ageing that starts early in adult life.

Adult↗

Prediction of mortality in an Indian intensive care unit. Comparison between APACHE II and artificial neural networks.

OBJECTIVE: To compare hospital outcome prediction using an artificial neural network model, built on an Indian data set, with the APACHE II (Acute Physiology and Chronic Health Evaluation II) logistic regression model. DESIGN: Analysis of a database containing prospectively collected data. SETTING: Medical-neurological ICU of a university hospital in Mumbai, India. SUBJECTS: Two thousand sixty-two consecutive admissions between 1996 and 1998. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: The 22 variables used to obtain day-1 APACHE II score and risk of death were recorded. Data from 1,962 patients were used to train the neural network using a back-propagation algorithm. Data from the remaining 1,000 patients were used for testing this model and comparing it with APACHE II. There were 337 deaths in these 1,000 patients; APACHE II predicted 246 deaths while the neural network predicted 336 deaths. Calibration, assessed by the Hosmer-Lemeshow statistic, was better with the neural network (H=22.4) than with APACHE II (H=123.5) and so was discrimination (area under receiver operating characteristic curve =0.87 versus 0.77, p=0.002). Analysis of information gain due to each of the 22 variables revealed that the neural network could predict outcome using only 15 variables. A new model using these 15 variables predicted 335 deaths, had calibration (H=27.7) and discrimination (area under receiver operating characteristic curve =0.88) which was comparable to the 22-variable model (p=0.87) and superior to the APACHE II equation (p<0.001). CONCLUSION: Artificial neural networks, trained on Indian patient data, used fewer variables and yet outperformed the APACHE II system in predicting hospital outcome.

APACHE↗

Coordinated reduction of genes of oxidative metabolism in humans with insulin resistance and diabetes: Potential role of PGC1 and NRF1.

Type 2 diabetes mellitus (DM) is characterized by insulin resistance and pancreatic beta cell dysfunction. In high-risk subjects, the earliest detectable abnormality is insulin resistance in skeletal muscle. Impaired insulin-mediated signaling, gene expression, glycogen synthesis, and accumulation of intramyocellular triglycerides have all been linked with insulin resistance, but no specific defect responsible for insulin resistance and DM has been identified in humans. To identify genes potentially important in the pathogenesis of DM, we analyzed gene expression in skeletal muscle from healthy metabolically characterized nondiabetic (family history negative and positive for DM) and diabetic Mexican-American subjects. We demonstrate that insulin resistance and DM associate with reduced expression of multiple nuclear respiratory factor-1 (NRF-1)-dependent genes encoding key enzymes in oxidative metabolism and mitochondrial function. Although NRF-1 expression is decreased only in diabetic subjects, expression of both PPAR gamma coactivator 1-alpha and-beta (PGC1-alpha/PPARGC1 and PGC1-beta/PERC), coactivators of NRF-1 and PPAR gamma-dependent transcription, is decreased in both diabetic subjects and family history-positive nondiabetic subjects. Decreased PGC1 expression may be responsible for decreased expression of NRF-dependent genes, leading to the metabolic disturbances characteristic of insulin resistance and DM.

Adult↗

Localization and characterization of mouse-human alignments within the human genome. Does evolutionary conservation suggest functional importance?

In an attempt to validate the use of evolutionary conservation as a method to identify putative regulatory elements, we have quantified the frequency of Single Nucleotide Polymorphisms (SNPs) within the most tightly conserved regions across the entire Human Genome. Our results show that conserved non-coding sequences have a significantly lower SNP frequency than their exonic counterparts, which suggests that these regions are functionally important.

Animals↗

Identification of genes expressed with temporal-spatial restriction to developing cerebellar neuron precursors by a functional genomic approach.

Hedgehog pathway activation is required for proliferation of cerebellar granule cell neuron precursors during development and is etiologic in certain cerebellar tumors. To identify genes expressed specifically in granule cell neuron precursors, we used oligonucleotide microarrays to analyze regulation of 13,179 genes/expressed sequence tags in heterogeneous primary cultures of neonatal mouse cerebellum that respond to the mitogen Sonic hedgehog. In conjunction, we applied experiment-specific noise models to render a gene-by-gene robust indication of up-regulation in Sonic hedgehog-treated cultures. Twelve genes so identified were tested, and 10 (83%) showed appropriate expression in the external granular layer (EGL) of the postnatal day (PN) 7 cerebellum and down-regulation by PN 15, as verified by in situ hybridization. Whole-organ profiling of the developing cerebellum was carried out from PN 1 to 30 to generate a database of temporal gene regulation profiles (TRPs). From the database an algorithm was developed to capture the TRP typical of EGL-specific genes. The "TRP-EGL" accurately predicted expression in vivo of an additional 18 genes/expressed sequence tags with a sensitivity of 80% and a specificity of 88%. We then compared the positive predictive value of our analytical procedure with other widely used methods, as verified by the TRP-EGL in silico. These findings suggest that replicate experiments and incorporation of noise models increase analytical specificity. They further show that genome-wide methods are an effective means to identify stage-specific gene expression in the developing granule cell lineage.

Algorithms↗

Computerized reminders to physicians in the emergency department: a web-based system to report late-arriving abnormal laboratory results.

Inadequate follow-up for abnormal laboratory results is a frequent cause of medical errors, especially for those that arrive after the patient is discharged in an Emergency Department (ED) setting. We have developed and implemented a computerized reminder system called the Automated Late-Arriving Results Monitoring System (ALARMS) for the Emergency Department at Children's Hospital, Boston. ALARMS scans the hospital's laboratory and ED registration databases to generate an electronic daily log of all late-arriving abnormal results for ED patients, which can be obtained by authorized physicians through a web-based user interface inside the hospital's intranet. We believe, by using this automated data-driven rule-based reminder system, we can minimize the risk of errors resulting from late-arriving laboratory data without requiring substantial additional efforts from clinicians.

Boston↗