Life Sciences Commons^™

Selected Fermented Indigenous Vegetables And Fruits From Malaysia As Potential Sources Of Natural Probiotics For Improving Gut Health, Olaide Olawunmi Ajibola, Raymond Thomas, Babatunde Femi Bakare

Biochemistry Publications

In the Peninsular Malaysia and Northern Borneo island of Malaysia, various rich indigenous leafy vegetables and fruits grow and contribute to the nutritional and dietary values of the population. They have high water contents, thus, naturally vulnerable to rapid food spoilage. Food preservation and processing play a vital role in the inhibition of food pathogens in fruits and vegetables that are prevalent in Malaysia. Lactic acid fermentation is generally a local-based bioprocess, among the oldest form and well-known for food-processing techniques among indigenous people there. The long shelf life of fermented vegetables and fruits improves their nutritional values and antioxidant …

Radiation Exposure Determination In A Secure, Cloud-Based Online Environment, Ben C. Shirley, Eliseos J. Mucaki, Peter Rogan

Biochemistry Publications

Rapid sample processing and interpretation of estimated exposures will be critical for triaging exposed individuals after a major radiation incident. The dicentric chromosome (DC) assay assesses absorbed radiation using metaphase cells from blood. The Automated Dicentric Chromosome Identifier and Dose Estimator System (ADCI) identifies DCs and determines radiation doses. This study aimed to broaden accessibility and speed of this system, while protecting data and software integrity. ADCI Online is a secure web-streaming platform accessible worldwide from local servers. Cloud-based systems containing data and software are separated until they are linked for radiation exposure estimation. Dose estimates are identical to ADCI …

Radiation Exposure Determination In A Secure, Cloudbased Online Environment, Ben C. Shirley, Eliseos J. Mucaki, Joan H.M. Knoll, Peter Rogan

Biochemistry Publications

Rapid sample processing and interpretation of estimated exposures will be critical for triaging exposed individuals after a major radiation incident. The dicentric chromosome (DC) assay assesses absorbed radiation using metaphase cells from blood. The Automated Dicentric Chromosome Identifier and Dose Estimator System (ADCI) identifies DCs and determines radiation doses. This study aimed to broaden accessibility and speed of this system, while protecting data and software integrity. ADCI Online is a secure web-streaming platform accessible worldwide from local servers. Cloud-based systems containing data and software are separated until they are linked for radiation exposure estimation. Dose estimates are identical to ADCI …

Likely Community Transmission Of Covid-19 Infections Between Neighboring, Persistent Hotspots In Ontario, Canada, Ben C. Shirley, Eliseos J. Mucaki, Peter Rogan

Biochemistry Publications

Introduction: This study aimed to produce community-level geo-spatial mapping of confirmed COVID-19 cases in Ontario Canada in near real-time to support decision-making. This was accomplished by area-to-area geostatistical analysis, space-time integration, and spatial interpolation of COVID-19 positive individuals.
Methods: COVID-19 cases and locations were curated for geostatistical analyses from March 2020 through June 2021, corresponding to the first, second, and third waves of infections. Daily cases were aggregated according to designated forward sortation area (FSA), and postal codes (PC) in municipal regions Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, and Windsor/Essex county. Hotspots were identified with area-to-area tests including Getis-Ord Gi*, Global …

Improved Radiation Expression Profiling In Blood By Sequential Application Of Sensitive And Specific Gene Signatures, Eliseos J. Mucaki, Ben C. Shirley, Peter K. Rogan

Biochemistry Publications

Purpose. Combinations of expressed genes can discriminate radiation-exposed from normal control blood samples by machine learning based signatures (with 8 to 20% misclassification rates). These signatures can quantify therapeutically-relevant as well as accidental radiation exposures. The prodromal symptoms of Acute Radiation Syndrome (ARS) overlap those present in Influenza and Dengue Fever infections. Surprisingly, these human radiation signatures misclassified gene expression profiles of virally infected samples as false positive exposures. The present study investigates these and other confounders, and then mitigates their impact on signature accuracy.

Methods. This study investigated recall by previous and novel radiation signatures independently derived …

Pathway‐Extended Gene Expression Signatures Integrate Novel Biomarkers That Improve Predictions Of Patient Responses To Kinase Inhibitors, Ashis Bagchee‐Clark, Eliseos J. Mucaki, Tyson Whitehead, Peter Rogan

Biochemistry Publications

Cancer chemotherapy responses have been related to multiple pharmacogenetic biomarkers, often for the same drug. This study utilizes machine learning to derive multi‐gene expression signatures that predict individual patient responses to specific tyrosine kinase inhibitors, including erlotinib, gefitinib, sorafenib, sunitinib, lapatinib and imatinib. Support vector machine (SVM) learning was used to train mathematical models that distinguished sensitivity from resistance to these drugs using a novel systems biology‐based approach. This began with expression of genes previously implicated in specific drug responses, then expanded to evaluate genes whose products were related through biochemical pathways and interactions. Optimal pathway‐extended SVMs predicted responses in …

Pathway-Extended Gene Expression Signatures Integrate Novel Biomarkers That Improve Predictions Of Patient Responses To Kinase Inhibitors, Ashis Jem Bagchee-Clark, Eliseos J. Mucaki, Tyson Whitehead, Peter Rogan

Biochemistry Publications

No abstract provided.

Pathway-Extended Gene Expression Signatures Integrate Novel Biomarkers That Improve Predictions Of Patient Responses To Kinase Inhibitors, Jem Bagchee-Clark, Eliseos J. Mucaki, Tyson Whitehead, Peter Rogan

Biochemistry Publications

Cancer chemotherapy responses have been related to multiple pharmacogenetic biomarkers, often for the same drug. This study utilizes machine learning to derive multi-gene expression signatures that predict individual patient responses to specific tyrosine kinase inhibitors, including erlotinib, gefitinib, sorafenib, sunitinib, lapatinib and imatinib. Support Vector Machine learning was used to train mathematical models that distinguished sensitivity from resistance to these drugs using a novel systems biology-based approach. This began with expression of genes previously implicated in specific drug responses, then expanded to evaluate genes whose products were related through biochemical pathways and interactions. Optimal pathway-extended support vector machines predicted responses …

Estimating Partial Body Ionizing Radiation Exposure By Automated Cytogenetic Biodosimetry, Ben Shirley, Peter Rogan

Biochemistry Publications

Purpose: Inhomogeneous exposures to ionizing radiation can be detected and quantified with the dicentric chromosome assay (DCA) of metaphase cells. Complete automation of interpretation of the DCA for whole-body irradiation has significantly improved throughput without compromising accuracy, however, low levels of residual false positive dicentric chromosomes (DCs) have confounded its application for partial-body exposure determination.

Materials and methods: We describe a method of estimating and correcting for false positive DCs in digitally processed images of metaphase cells. Nearly all DCs detected in unirradiated calibration samples are introduced by digital image processing. DC frequencies of irradiated calibration samples and those exposed …

Estimating Partial Body Ionizing Radiation Exposure By Automated Cytogenetic Biodosimetry, Peter Rogan

Biochemistry Publications

Purpose: Inhomogeneous exposures to ionizing radiation can be detected and quantified with the Dicentric Chromosome Assay (DCA) of metaphase cells. Complete automation of interpretation of the DCA for whole body irradiation has significantly improved throughput without compromising accuracy, however low levels of residual false positive dicentric chromosomes (DCs) have confounded its application for partial body exposure determination.

Materials and Methods: We describe a method of estimating and correcting for false positive DCs in digitally processed images of metaphase cells. Nearly all DCs detected in unirradiated calibration samples are introduced by digital image processing. DC frequencies of irradiated calibration …

Collaborative, Multidisciplinary Evaluation Of Cancer Variants Through Virtual Molecular Tumor Boards Informs Local Clinical Practices., Shruti Rao, Beth Pitel, Alex H Wagner, Simina M Boca, Matthew Mccoy, Ian King, Samir Gupta, Ben Ho Park, Jeremy L Warner, James Chen, Peter Rogan, Debyani Chakravarty, Malachi Griffith, Obi L Griffith, Subha Madhavan

Biochemistry Publications

PURPOSE: The cancer research community is constantly evolving to better understand tumor biology, disease etiology, risk stratification, and pathways to novel treatments. Yet the clinical cancer genomics field has been hindered by redundant efforts to meaningfully collect and interpret disparate data types from multiple high-throughput modalities and integrate into clinical care processes. Bespoke data models, knowledgebases, and one-off customized resources for data analysis often lack adequate governance and quality control needed for these resources to be clinical grade. Many informatics efforts focused on genomic interpretation resources for neoplasms are underway to support data collection, deposition, curation, harmonization, integration, and analytics …

Meeting Radiation Dosimetry Capacity Requirements Of Population-Scale Exposures By Geostatistical Sampling., Peter K Rogan, Eliseos J Mucaki, Ruipeng Lu, Ben C Shirley, Edward Waller, Joan H M Knoll

Biochemistry Publications

BACKGROUND: Accurate radiation dose estimates are critical for determining eligibility for therapies by timely triaging of exposed individuals after large-scale radiation events. However, the universal assessment of a large population subjected to a nuclear spill incident or detonation is not feasible. Even with high-throughput dosimetry analysis, test volumes far exceed the capacities of first responders to measure radiation exposures directly, or to acquire and process samples for follow-on biodosimetry testing.

AIM: To significantly reduce data acquisition and processing requirements for triaging of treatment-eligible exposures in population-scale radiation incidents.

METHODS: Physical radiation plumes modelled nuclear detonation scenarios of simulated exposures at …

Expression Changes Confirm Genomic Variants Predicted To Result In Allele-Specific, Alternative Mrna Splicing, Peter Rogan

Biochemistry Publications

Splice isoform structure and abundance can be affected by either noncoding or masquerading coding variants that alter the structure or abundance of transcripts. When these variants are common in the population, these nonconstitutive transcripts are sufficiently frequent so as to resemble naturally occurring, alternative mRNA splicing. Prediction of the effects of such variants has been shown to be accurate using information theory-based methods. Single nucleotide polymorphisms (SNPs) predicted to significantly alter natural and/or cryptic splice site strength were shown to affect gene expression. Splicing changes for known SNP genotypes were confirmed in HapMap lymphoblastoid cell lines with gene expression microarrays …

Multigene Signatures Of Responses To Chemotherapy Derived By Biochemically-Inspired Machine Learning., Peter K. Rogan

Biochemistry Publications

Pharmacogenomic responses to chemotherapy drugs can be modeled by supervised machine learning of expression and copy number of relevant gene combinations. Such biochemical evidence can form the basis of derived gene signatures using cell line data, which can subsequently be examined in patients that have been treated with the same drugs. These gene signatures typically contain elements of multiple biochemical pathways which together comprise multiple origins of drug resistance or sensitivity. The signatures can capture variation in these responses to the same drug among different patients.

Radiation Dose Estimation By Completely Automated Interpretation Of The Dicentric Chromosome Assay, Peter Rogan, Yanxin Li, Ben Shirley, Ruth Wilkins, Farrah Norton, Joan Knoll

Biochemistry Publications

Accuracy of the automated dicentric chromosome (DC) assay relies on metaphase image selection. This study validates a software framework to find the best image selection models that mitigate inter-sample variability. Evaluation methods to determine model quality include the Poisson goodness-of-fit of DC distributions for each sample, residuals after calibration curve fitting and leave-one-out dose estimation errors. The process iteratively searches a pool of selection model candidates by modifying statistical and filter cut-offs to rank the best candidates according to their respective evaluation scores. Evaluation scores minimize the sum of squared errors relative to the actual radiation dose of the calibration …

Transcription Factor Binding Site Clusters Identify Target Genes With Similar Tissue-Wide Expression And Buffer Against Mutations., Peter Rogan, Ruipeng Lu

Biochemistry Publications

Background: The distribution and composition of cis-regulatory modules composed of transcription factor (TF) binding site (TFBS) clusters in promoters substantially determine gene expression patterns and TF targets. TF knockdown experiments have revealed that TF binding profiles and gene expression levels are correlated. We use TFBS features within accessible promoter intervals to predict genes with similar tissue-wide expression patterns and TF targets using Machine Learning (ML). Methods: Bray-Curtis Similarity was used to identify genes with correlated expression patterns across 53 tissues. TF targets from knockdown experiments were also analyzed by this approach to set up the ML framework. TFBSs were …

Brca1 And Brca2 5′ Noncoding Region Variants Identified In Breast Cancer Patients Alter Promoter Activity And Protein Binding, Leslie J. Burke, Jan Sevcik, Gaetana Gambino, Emma Tudini, Eliseos J. Mucaki, Ben C. Shirley, Phillip Whiley, Michael T. Parsons, Kim De Leeneer, Sara Gutiérrez-Enríquez, Marta Santamariña, Sandrine M. Caputo, Elizabeth Santana Dos Santos, Jana Soukupova, Marketa Janatova, Petra Zemankova, Klara Lhotova, Lenka Stolarova, Mariana Borecka, Alejandro Moles-Fernández, Siranoush Manoukian, Bernardo Bonanni, Stacey L. Edwards, Marinus J. Blok, Thomas Van Overeem Hansen, Maria Rossing, Orland Diez, Ana Vega, Kathleen B.M. Claes, David E. Goldgar, Etienne Rouleau

Biochemistry Publications

© 2018 The Authors. Human Mutation published by Wiley Periodicals, Inc. The widespread use of next generation sequencing for clinical testing is detecting an escalating number of variants in noncoding regions of the genome. The clinical significance of the majority of these variants is currently unknown, which presents a significant clinical challenge. We have screened over 6,000 early-onset and/or familial breast cancer (BC) cases collected by the ENIGMA consortium for sequence variants in the 5′ noncoding regions of BC susceptibility genes BRCA1 and BRCA2, and identified 141 rare variants with global minor allele frequency < 0.01, 76 of which have not been reported previously. Bioinformatic analysis identified a set of 21 variants most likely to impact transcriptional regulation, and luciferase reporter assays detected altered promoter activity for four of these variants. Electrophoretic mobility shift assays demonstrated that three of these altered the binding of proteins to the respective BRCA1 or BRCA2 promoter regions, including NFYA binding to BRCA1:c.-287C>T and PAX5 binding to BRCA2:c.-296C …

Predicting Response To Platin Chemotherapy Agents With Biochemically-Inspired Machine Learning, Peter Rogan, Eliseos J. Mucaki, Dan Lizotte

Biochemistry Publications

Selection of effective genes that accurately predict chemotherapy response could improve cancer outcomes. We compare optimized gene signatures for cisplatin, carboplatin, and oxaliplatin response in the same cell lines, and respectively validate each with cancer patient data. Supervised support vector machine learning was used to derive gene sets whose expression was related to cell line GI₅₀ values by backwards feature selection with cross-validation. Specific genes and functional pathways distinguishing sensitive from resistant cell lines are identified by contrasting signatures obtained at extreme vs. median GI₅₀ thresholds. Ensembles of gene signatures at different thresholds are combined to reduce dependence …

The Clinical Significance Of Occult Gastrointestinal Primary Tumours In Metastatic Cancer: A Population Retrospective Cohort Study, Malek B. Hannouf, Eric Winquist, Salaheddin M. Mahmud, Muriel Brackstone, Sisira Sarma, George Rodrigues, Peter K. Rogan, Jeffrey S. Hoch, Gregory S. Zaric

Biochemistry Publications

© 2018 by the Korean Cancer Association. Purpose The purpose of this study was to estimate the incidence of occult gastrointestinal (GI) primary tumours in patients with metastatic cancer of uncertain primary origin and evaluate their influence on treatments and overall survival (OS). Materials and Methods We used population heath data from Manitoba, Canada to identify all patients initially diagnosed with metastatic cancer between 2002 and 2011. We defined patients to have "occult" primary tumour if the primary was found at least 6 months after initial diagnosis. Otherwise, we considered primary tumours as "obvious." We used propensity-score methods to match …

Expedited Radiation Biodosimetry By Automated Dicentric Chromosome Identification (Adci) And Dose Estimation, Peter Rogan, Ben Shirley, Yanxin Li, Joan Knoll

Biochemistry Publications

Biological radiation dose can be estimated from dicentric chromosome frequencies in metaphase cells. Performing these cytogenetic dicentric chromosome assays is traditionally a manual, labor-intensive process not well suited to handle the volume of samples which may require examination in the wake of a mass casualty event. Automated Dicentric Chromosome Identifier and Dose Estimator (ADCI) software automates this process by examining sets of metaphase images using machine learning-based image processing techniques. The software selects appropriate images for analysis by removing unsuitable images, classifies each object as either a centromere-containing chromosome or non-chromosome, further distinguishes chromosomes as monocentric chromosomes (MCs) or dicentric …

Accurate Cytogenetic Biodosimetry Through Automated Dicentric Chromosome Curation And Metaphase Cell Selection, Jin Liu, Yanxin Li, Ruth Wilkins, Canadian Nuclear Laboratories, Joan H. Knoll, Peter Rogan

Biochemistry Publications

Accurate digital image analysis of abnormal microscopic structures relies on high quality images and on minimizing the rates of false positive (FP) and negative objects in images. Cytogenetic biodosimetry detects dicentric chromosomes (DCs) that arise from exposure to ionizing radiation, and determines radiation dose received based on DC frequency. Improvements in automated DC recognition increase the accuracy of dose estimates by reclassifying FP DCs as monocentric chromosomes or chromosome fragments. We also present image segmentation methods to rank high quality digital metaphase images and eliminate suboptimal metaphase cells. A set of chromosome morphology segmentation methods selectively filtered out FP DCs …

Predicting Outcomes Of Hormone And Chemotherapy In The Molecular Taxonomy Of Breast Cancer International Consortium (Metabric) Study By Biochemically-Inspired Machine Learning, Peter Rogan, Eliseos J. Mucaki, Katherina Baranova, Huy Q. Pham, Iman Rezaeian, Dimo Angelov, Alioune Ngom, Luis Rueda

Biochemistry Publications

Genomic aberrations and gene expression-defined subtypes in the large METABRIC patient cohort have been used to stratify and predict survival. The present study used normalized gene expression signatures of paclitaxel drug response to predict outcome for different survival times in METABRIC patients receiving hormone (HT) and, in some cases, chemotherapy (CT) agents. This machine learning method, which distinguishes sensitivity vs. resistance in breast cancer cell lines and validates predictions in patients; was also used to derive gene signatures of other HT (tamoxifen) and CT agents (methotrexate, epirubicin, doxorubicin, and 5-fluorouracil) used in METABRIC. Paclitaxel gene signatures exhibited the best performance, …

Birc6 Mediates Imatinib Resistance Independently Of Mcl-1, Denis O. Okumu, Michael P. East, Merlin Levine, Laura E. Herring, Raymond Zhang, Thomas S.K. Gilbert, David Litchfield, Yanping Zhang, Lee M. Graves

Biochemistry Publications

© 2017 Okumu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Baculoviral IAP repeat containing 6 (BIRC6) is a member of the inhibitors of apoptosis proteins (IAPs), a family of functionally and structurally related proteins that inhibit apoptosis. BIRC6 has been implicated in drug resistance in several different human cancers, however mechanisms regulating BIRC6 have not been extensively explored. Our phosphoproteomic analysis of an imatinib-resistant chronic myelogenous leukemia (CML) cell line (MYL-R) …

Discovery And Validation Of Information Theory-Based Transcription Factor And Cofactor Binding Site Motifs., Ruipeng Lu, Eliseos J Mucaki, Peter K Rogan

Biochemistry Publications

Data from ChIP-seq experiments can derive the genome-wide binding specificities of transcription factors (TFs) and other regulatory proteins. We analyzed 765 ENCODE ChIP-seq peak datasets of 207 human TFs with a novel motif discovery pipeline based on recursive, thresholded entropy minimization. This approach, while obviating the need to compensate for skewed nucleotide composition, distinguishes true binding motifs from noise, quantifies the strengths of individual binding sites based on computed affinity and detects adjacent cofactor binding sites that coordinate with the targets of primary, immunoprecipitated TFs. We obtained contiguous and bipartite information theory-based position weight matrices (iPWMs) for 93 sequence-specific TFs, …

Domains Of Stip1 Responsible For Regulating Prpc-Dependent Amyloid-Β Oligomer Toxicity., Andrzej Maciejewski, Valeriy G Ostapchenko, Flavio H Beraldo, Vania F Prado, Marco A M Prado, Wing-Yiu Choy

Biochemistry Publications

Soluble oligomers of amyloid-beta peptide (AβO) transmit neurotoxic signals through the cellular prion protein (PrP(C)) in Alzheimer's disease (AD). Secreted stress-inducible phosphoprotein 1 (STIP1), an Hsp70 and Hsp90 cochaperone, inhibits AβO binding to PrP(C) and protects neurons from AβO-induced cell death. Here, we investigated the molecular interactions between AβO and STIP1 binding to PrP(C) and their effect on neuronal cell death. We showed that residues located in a short region of PrP (90-110) mediate AβO binding and we narrowed the major interaction in this site to amino acids 91-100. In contrast, multiple binding sites on STIP1 (DP1, TPR1 and TPR2A) …

A Unified Analytic Framework For Prioritization Of Non-Coding Variants Of Uncertain Significance In Heritable Breast And Ovarian Cancer, Eliseos J. Mucaki, Natasha G. Caminsky, Ami M. Perri, Ruipeng Lu, Alain Laederach, Matthew Halvorsen, Joan H. M. Knoll, Peter K. Rogan

Biochemistry Publications

Background

Sequencing of both healthy and disease singletons yields many novel and low frequency variants of uncertain significance (VUS). Complete gene and genome sequencing by next generation sequencing (NGS) significantly increases the number of VUS detected. While prior studies have emphasized protein coding variants, non-coding sequence variants have also been proven to significantly contribute to high penetrance disorders, such as hereditary breast and ovarian cancer (HBOC). We present a strategy for analyzing different functional classes of non-coding variants based on information theory (IT) and prioritizing patients with large intragenic deletions.

Methods

We captured and enriched for coding and non-coding variants …

Cost-Effectiveness Of Using A Gene Expression Profiling Test To Aid In Identifying The Primary Tumour In Patients With Cancer Of Unknown Primary., M B Hannouf, E Winquist, S M Mahmud, M Brackstone, S Sarma, G Rodrigues, P Rogan, J S Hoch, G S Zaric

Biochemistry Publications

We aimed to investigate the cost-effectiveness of a 2000-gene-expression profiling (GEP) test to help identify the primary tumor site when clinicopathological diagnostic evaluation was inconclusive in patients with cancer of unknown primary (CUP). We built a decision-analytic-model to project the lifetime clinical and economic consequences of different clinical management strategies for CUP. The model was parameterized using follow-up data from the Manitoba Cancer Registry, cost data from Manitoba Health administrative databases and secondary sources. The 2000-GEP-based strategy compared to current clinical practice resulted in an incremental cost-effectiveness ratio (ICER) of $44,151 per quality-adjusted life years (QALY) gained. The total annual-budget …

Automated Discrimination Of Dicentric And Monocentric Chromosomes By Machine Learning-Based Image Processing., Yanxin Li, Joan H Knoll, Ruth C Wilkins, Farrah N Flegal, Peter K Rogan

Biochemistry Publications

Dose from radiation exposure can be estimated from dicentric chromosome (DC) frequencies in metaphase cells of peripheral blood lymphocytes. We automated DC detection by extracting features in Giemsa-stained metaphase chromosome images and classifying objects by machine learning (ML). DC detection involves (i) intensity thresholded segmentation of metaphase objects, (ii) chromosome separation by watershed transformation and elimination of inseparable chromosome clusters, fragments and staining debris using a morphological decision tree filter, (iii) determination of chromosome width and centreline, (iv) derivation of centromere candidates, and (v) distinction of DCs from monocentric chromosomes (MC) by ML. Centromere candidates are inferred from 14 image …

Prioritizing Variants In Complete Hereditary Breast And Ovarian Cancer (Hboc) Genes In Patients Lacking Known Brca Mutations., Natasha G Caminsky, Eliseos J Mucaki, Ami M Perri, Ruipeng Lu, Joan H M Knoll, Peter K Rogan

Biochemistry Publications

BRCA1 and BRCA2 testing for Hereditary breast and ovarian cancer (HBOC) does not identify all pathogenic variants. Sequencing of 20 complete genes in HBOC patients with uninformative test results (N = 287), including non-coding and flanking sequences of ATM, BARD1, BRCA1, BRCA2, CDH1, CHEK2, EPCAM, MLH1, MRE11A, MSH2, MSH6, MUTYH, NBN, PALB2, PMS2, PTEN, RAD51B, STK11, TP53, and XRCC2, identified 38,372 unique variants. We apply information theory (IT) to predict and prioritize non-coding variants of uncertain significance (VUS) in regulatory, coding, and intronic regions based on changes in binding sites in these genes. Besides mRNA splicing, IT provides a common …

Genomic Signatures For Paclitaxel And Gemcitabine Resistance In Breast Cancer Derived By Machine Learning., Stephanie N Dorman, Katherina Baranova, Joan H M Knoll, Brad L Urquhart, Gabriella Mariani, Maria Luisa Carcangiu, Peter K Rogan

Biochemistry Publications

Increasingly, the effectiveness of adjuvant chemotherapy agents for breast cancer has been related to changes in the genomic profile of tumors. We investigated correspondence between growth inhibitory concentrations of paclitaxel and gemcitabine (GI50) and gene copy number, mutation, and expression first in breast cancer cell lines and then in patients. Genes encoding direct targets of these drugs, metabolizing enzymes, transporters, and those previously associated with chemoresistance to paclitaxel (n = 31 genes) or gemcitabine (n = 18) were analyzed. A multi-factorial, principal component analysis (MFA) indicated expression was the strongest indicator of sensitivity for paclitaxel, and copy number and expression …