Ex vivo discovery of synergistic drug combinations for hematologic malignancies.

Combination therapies have improved outcomes for patients with acute myeloid leukemia (AML). However, these patients still have poor overall survival. Although many combination therapies are identified with high-throughput screening (HTS), these approaches are constrained to disease models that can be grown in large volumes (e.

Predicting moderate drinking behaviors in National Health and Nutrition Examination Survey participants using biochemical and demographical factors with machine learning.

Recent studies revealed that any amount of alcohol consumption is an overall health detriment to multiple populations, contrary to popular beliefs. In addition, very few alcohol use studies utilized machine learning methods to compare the biological health of moderate drinkers compared to those that abstain from alcohol consumption, opting instead to focus on binge drinking and heavy drinking. Using participant data of multiple factor types from the National Health and Nutrition Examination Survey, we created prediction models with stacked ensembles and gradient boosting models.

Development of a Machine Learning Model to Predict Recurrence of Oral Tongue Squamous Cell Carcinoma.

Despite diagnostic advancements, the development of reliable prognostic systems for assessing the risk of cancer recurrence still remains a challenge. In this study, we developed a novel framework to generate highly representative machine-learning prediction models for oral tongue squamous cell carcinoma (OTSCC) cancer recurrence. We identified cases of 5- and 10-year OTSCC recurrence from the SEER database.

Evaluation of a genetic risk score computed using human chromosomal-scale length variation to predict breast cancer.

Introduction: The ability to accurately predict whether a woman will develop breast cancer later in her life, should reduce the number of breast cancer deaths. Different predictive models exist for breast cancer based on family history, BRCA status, and SNP analysis. The best of these models has an accuracy (area under the receiver operating characteristic curve, AUC) of about 0.

Genetic Risk Scores and Missing Heritability in Ovarian Cancer.

Ovarian cancers are curable by surgical resection when discovered early. Unfortunately, most ovarian cancers are diagnosed in the later stages. One strategy to identify early ovarian tumors is to screen women who have the highest risk.

A genetic risk score using human chromosomal-scale length variation can predict schizophrenia.

Studies indicate that schizophrenia has a genetic component, however it cannot be isolated to a single gene. We aimed to determine how well one could predict that a person will develop schizophrenia based on their germ line genetics. We compared 1129 people from the UK Biobank dataset who had a diagnosis of schizophrenia to an equal number of age matched people drawn from the general UK Biobank population.

Comment on "comparative analysis of triple-negative breast cancer transcriptomics of Kenyan, African American and Caucasian women" by Saleh et al.

• Alterations to the somatic genome lead to a tumor. • Different germ line genomes influence the formation of the tumor and its response to therapeutics. • Germ line genetics can play a role in breast cancer.

A genetic risk score for glioblastoma multiforme based on copy number variations.

Glioblastoma multiforme is the most common form of brain cancer. Several lines of evidence suggest that glioblastoma multiforme has a genetic basis. A genetic test that could identify people who are at high risk of developing glioblastoma multiforme could improve our understanding of this form of brain cancer.

Genetic risk score for ovarian cancer based on chromosomal-scale length variation.

Introduction: Twin studies indicate that a substantial fraction of ovarian cancers should be predictable from genetic testing. Genetic risk scores can stratify women into different classes of risk. Higher risk women can be treated or screened for ovarian cancer, which should reduce ovarian cancer death rates.

Evaluation of a genetic risk score for severity of COVID-19 using human chromosomal-scale length variation.

Introduction: The course of COVID-19 varies from asymptomatic to severe in patients. The basis for this range in symptoms is unknown. One possibility is that genetic variation is partly responsible for the highly variable response.

Laboratory tests as short-term correlates of stroke.

Background: The widespread adoption of electronic health records provides new opportunities to better predict which patients are likely to suffer a stroke. Using electronic health records, we assessed the correlation of different laboratory tests to future occurrences of a stroke.

Methods: We examined the electronic health records of 2.

Breast tumor laterality in the United States depends upon the country of birth, but not race.

More breast cancers are diagnosed in the left breast than the right. The ratio (l/r) is called the laterality ratio. We analyzed 1.

Similarities in the Age-Specific Incidence of Colon and Testicular Cancers.

Colon cancers are thought to be an inevitable result of aging, while testicular cancers are thought to develop in only a small fraction of men, beginning in utero. These models of carcinogenesis are, in part, based upon age-specific incidence data. The specific incidence for colon cancer appears to monotonically increase with age, while that of testicular cancer increases to a maximum value at about 35 years of age, then declines to nearly zero by the age of 80.

Age-specific incidence data indicate four mutations are required for human testicular cancers.

Normal human cells require a series of genetic alterations to undergo malignant transformation. Direct sequencing of human tumors has identified hundreds of mutations in tumors, but many of these are thought to be unnecessary and a result of, rather than a cause of, the tumor. The exact number of mutations to transform a normal human cell into a tumor cell is unknown.

Reverse engineering the yeast RNR1 transcriptional control system.

Transcription is controlled by multi-protein complexes binding to short non-coding regions of genomic DNA. These complexes interact combinatorially. A major goal of modern biology is to provide simple models that predict this complex behavior.

Parallel routes of human carcinoma development: implications of the age-specific incidence data.

Background: The multi-stage hypothesis suggests that cancers develop through a single defined series of genetic alterations. This hypothesis was first suggested over 50 years ago based upon age-specific incidence data. However, recent molecular studies of tumors indicate that multiple routes exist to the formation of cancer, not a single route.

Microfabricated arrays of cylindrical wells facilitate single-molecule enzymology of alpha-chymotrypsin.

Single-molecule enzymology allows scientists to examine the distributions of kinetic rates among members of a population. We describe a simple method for the analysis of single-molecule enzymatic kinetics and provide comparisons to ensemble-averaged kinetics. To isolate our model enzyme, alpha-chymotrypsin, into single molecules, we use an array of cylindrical poly(dimethylsiloxane) wells 2 microm in diameter and 1.

Dynamic SPR monitoring of yeast nuclear protein binding to a cis-regulatory element.

Gene expression is controlled by protein complexes binding to short specific sequences of DNA, called cis-regulatory elements. Expression of most eukaryotic genes is controlled by dozens of these elements. Comprehensive identification and monitoring of these elements is a major goal of genomics.

Diversity in the activity of individual enzymes.

Although the structure of an enzyme is often depicted as static, it is dynamic. Hence, a population of chemically identical enzymes has not one, but a distribution of structures at any moment in time. Does this have an effect on the activity of the enzyme? This article reviews experiments designed to test the hypothesis that this distribution of structures results in a distribution of enzyme activities.

Single-molecule enzymology of chymotrypsin using water-in-oil emulsion.

Single-molecule studies allow the study of subtle activity differences due to local folding in proteins, but are time consuming and difficult because only a few molecules are observed in one experiment. We developed an assay where we can simultaneously measure the activity of hundreds of individual molecules. The assay utilizes a synthetic chymotrypsin substrate that is nonfluorescent before cleavage by chymotrypsin, but is intensely fluorescent afterward.

Surface plasmon resonance-based sensors to identify cis-regulatory elements.

In eukaryotes, transcription is regulated by multiprotein complexes binding to specific regions of genomic DNA, called cis-regulatory elements. Comprehensive identification of these elements is an important goal of functional genomics. Hence, it is of practical interest to develop a high-throughput assay to identify cis-regulatory elements.

Electronic manipulation of DNA, proteins, and nanoparticles for potential circuit assembly.

Using gold electrodes lithographically fabricated onto microscope cover slips, DNA and proteins are interrogated both optically (through fluorescence) and electronically (through conductance measurements). Dielectrophoresis is used to position the DNA and proteins at well-defined positions on a chip. Quadrupole electrode geometries are investigated with gaps ranging from 3 to 100 microm; field strengths are typically 10(6) V/m.

Manipulating nanoparticles in solution with electrically contacted nanotubes using dielectrophoresis.

Dielectrophoresis is an electronic analogue1,2 of optical tweezers3 based on the same physical principle: an ac electric field induces a dipole moment on an object in solution, which then experiences a force proportional to the gradient of the field intensity. For both types of tweezers, this force must compete with thermal Brownian4 motion to be effective, which becomes increasingly difficult as the particle size approaches the nanometer scale. Here we show that this restriction can be overcome by using the large electric field gradient in the vicinity of a carbon nanotube to electronically manipulate nanoparticles down to 2 nm in diameter.

Post-translationally modified S12, absent in transformed breast epithelial cells, is not associated with the 26S proteasome and is induced by proteasome inhibitor.

The 26S proteasome, consisting of the 20S core and 19S regulatory complexes, regulates intracellular protein concentration through proteolytic degradation of targeted substrates. Composition of the 19S regulatory complex as well as posttranslational modifications of the 19S subunits can effectively regulate the activity of the 26S proteasome. Aberrant activity of the 26S proteasome affects the cell cycle, apoptosis and other cellular processes related to cancer.

Identification of the protein Zibra, its genomic organization, regulation, and expression in breast cancer cells.

The mRNA that encodes zibra (zinc, in-between-ring finger, ubiquitin-associated domain), previously known as hypothetical protein FLJ10111, or RNF31 is expressed in several distinct cancers. Little is known about the genomic organization, expression, or regulation of zibra. Using RNA ligase-mediated rapid amplification of cDNA ends (RLM-RACE), we cloned the full-length zibra cDNA from a transformed breast cell line.