Bioinformatics and Machine Learning for Cancer Biology

1222 Pages·2022·12.458 MB·English

by  Yiping Fan, Shibiao Wan, Chungie Jiang, Shengli Li

Bioinformatics and
Machine Learning
for Cancer Biology
Edited by
Shibiao Wan, Yiping Fan, Chunjie Jiang and Shengli Li
Printed Edition of the Special Issue Published in Biology
www.mdpi.com/journal/biology
Bioinformatics and Machine Learning
for Cancer Biology

Bioinformatics and Machine Learning
for Cancer Biology
Editors
Shibiao Wan
Yiping Fan
Chunjie Jiang
Shengli Li
MDPI(cid:13)Basel(cid:13)Beijing(cid:13)Wuhan(cid:13)Barcelona(cid:13)Belgrade(cid:13)Manchester(cid:13)Tokyo(cid:13)Cluj(cid:13)Tianjin
Editors
ShibiaoWan YipingFan ChunjieJiang
CenterforApplied CenterforApplied DepartmentofMedicine
Bioinformatics Bioinformatics DivisionofDiabetes,
St. JudeChildren’sResearch St. JudeChildren’sResearch Endocrinologyand
Hospital Hospital Metabolism
Memphis Memphis BaylorCollegeofMedicine
UnitedStates UnitedStates Houston
UnitedStates
ShengliLi
PrecisionResearchCenterfor
RefractoryDisease
ShanghaiJiaoTong
University
Shanghai
China
EditorialOffice
MDPI
St. Alban-Anlage66
4052Basel,Switzerland
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Contents
AbouttheEditors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
Prefaceto”BioinformaticsandMachineLearningforCancerBiology” . . . . . . . . . . . . . . ix
ShibiaoWan,ChunjieJiang,ShengliLiandYipingFan
SpecialIssueonBioinformaticsandMachineLearningforCancerBiology
Reprintedfrom: Biology2022,11,361,doi:10.3390/biology11030361 . . . . . . . . . . . . . . . . . 1
Saraswati Koppad, Annappa Basava, Katrina Nash, Georgios V. Gkoutos and Animesh
Acharjee
MachineLearning-BasedIdentificationofColonCancerCandidateDiagnosticsGenes
Reprintedfrom: Biology2022,11,365,doi:10.3390/biology11030365 . . . . . . . . . . . . . . . . . 3
CristianaTudor
ANovelApproachtoModelingandForecastingCancerIncidenceandMortalityRatesthrough
WebQueriesandAutomatedForecastingAlgorithms: EvidencefromRomania
Reprintedfrom: Biology2022,11,857,doi:10.3390/biology11060857 . . . . . . . . . . . . . . . . . 19
LiminJiang,JijunTang,FeiGuoandYanGuo
PredictionofMajorHistocompatibilityComplexBindingwithBilateralandVariableLongShort
TermMemoryNetworks
Reprintedfrom: Biology2022,11,848,doi:10.3390/biology11060848 . . . . . . . . . . . . . . . . . 37
Sheng-Yao Cheng, Alexander T. H. Wu, Gaber El-Saber Batiha, Ching-Liang Ho, Jih-Chin
LeeandHalimatYusufLukmanetal.
Identification of DPP4/CTNNB1/MET as a Theranostic Signature of Thyroid Cancer and
EvaluationoftheTherapeuticPotentialofSitagliptin
Reprintedfrom: Biology2022,11,324,doi:10.3390/biology11020324 . . . . . . . . . . . . . . . . . 47
Alyssa Obermayer, Li Dong, Qianqian Hu, Michael Golden, Jerald D. Noble and Paulo
Rodriguezetal.
DRPPM-EASY: A Web-Based Framework for Integrative Analysis of Multi-Omics Cancer
Datasets
Reprintedfrom: Biology2022,11,260,doi:10.3390/biology11020260 . . . . . . . . . . . . . . . . . 65
XitongYao,XinleiQi,YaoWang,BaokunZhang,TianshuaiHeandTaoningYanetal.
Identification and Validation of an Annexin-Related Prognostic Signature and Therapeutic
TargetsforBladderCancer: IntegrativeAnalysis
Reprintedfrom: Biology2022,11,259,doi:10.3390/biology11020259 . . . . . . . . . . . . . . . . . 79
KhalilurRehman,JianqiangLi,YanPei,AnaaYasin,SaqibAliandYousafSaeed
Architectural Distortion-Based Digital Mammograms Classification Using Depth Wise
ConvolutionalNeuralNetwork
Reprintedfrom: Biology2021,11,15,doi:10.3390/biology11010015 . . . . . . . . . . . . . . . . . . 97
ChengchengWei,YuanchengZhou,QiXiong,MingXiong,YaxinHouandXiongYangetal.
Comprehensive Analysis of CPA4 as a Poor Prognostic Biomarker Correlated with Immune
CellsInfiltrationinBladderCancer
Reprintedfrom: Biology2021,10,1143,doi:10.3390/biology10111143 . . . . . . . . . . . . . . . . 127
HuiminLi,LinChen,YunsongHan,FangfangZhang,YanyanWangandYaliHanetal.
TheIdentificationofRNAModificationGenePUS7asaPotentialBiomarkerofOvarianCancer
Reprintedfrom: Biology2021,10,1130,doi:10.3390/biology10111130 . . . . . . . . . . . . . . . . 145
v
Roberto Serna-Blasco, Estela Sa´nchez-Herrero, Mar´ıa Berrocal Renedo, Silvia
Calabuig-Farin˜as,MiguelA´ngelMolina-VilaandMarianoProvencioetal.
R-Score: A New Parameter to Assess the Quality of Variants’ Calls Assessed by NGS Using
LiquidBiopsies
Reprintedfrom: Biology2021,10,954,doi:10.3390/biology10100954 . . . . . . . . . . . . . . . . . 159
BibiZainab,ZainabAyaz,UmerRashid,DuniaA.AlFarraj,RouaM.AlkufeidyandFatmah
S.AlQahtanyetal.
Role of Persistent Organic Pollutants in Breast Cancer Progression and Identification of
EstrogenReceptorAlphaInhibitorsUsingIn-SilicoMiningandDrug-DrugInteractionNetwork
Approaches
Reprintedfrom: Biology2021,10,681,doi:10.3390/biology10070681 . . . . . . . . . . . . . . . . . 169
vi
About the Editors
ShibiaoWan
Dr. ShibiaoWaniscurrentlyaBioinformaticsResearchScientistatSt. JudeChildren’sResearch
Hospital,oneofthetoppediatriccancerhospitalsintheUS.Withmorethan12yearsofexperiencein
machinelearning,bioinformatics,andcomputationalbiology,Dr. Wanhaspublished>40articlesin
prestigiousjournalssuchasGenomeResearch(impactfactor: 11.093), NatureCommunications(impact
factor: 14.919), Science Advances (impact factor: 14.136), Circulation Research (impact factor: 15.862),
Briefings in Bioinformatics (impact factor: 11.622), and Bioinformatics (impact factor: 6.937). Dr. Wan
is an academic editor for BioMed Research International (impact factor: 3.411) and a guest associate
editorforaseriesofhigh-impactjournalsincludingFrontiersinCellandDevelopmentalBiology(impact
factor: 6.684), Frontiers in Pharmacology (impact factor: 5.810), Biology (impact factor: 5.079), and
Frontiers in Genetics (impact factor: 4.599). He is a TPC member for >20 machine learning-related
international conferences including IEEE ICTAI, IEEE IAICT, IEEE IoTaIS, and IEEE SOFTT. Dr.
Wan is also a reviewer for >50 prestigious journals including IEEE TNNLS (impact factor: 10.451),
NucleicAcidsResearch(impactfactor: 16.971),GenomicMedicine(impactfactor: 11.117)andBriefingsin
Bioinformatics(impactfactor: 11.622). Hewasarecipientoftheglobalpeerreviewawards(top1%)in
“Cross-Field”and“BiologyandBiochemistry”in2019,awardedbyClarivate. Dr. Wanwasalsoan
OutstandingYoungAlumniAwardeein2021–2022. Dr. WanisamemberofIEEE,ACMandISCB.
YipingFan
Dr. Yiping Fan is currently the Associated Director of Center for Applied Bioinformatics at St.
JudeChildren’sResearchHospital. HeobtainedhisBioengineeringPhDin2002attheUniversityof
CaliforniaatSanDiegoandMSdegreeinBiophysicsatUniversityofIllinoisUrbanaChampaignin
1999. His research interests include the development and optimization of bioinformatics methods,
biomedicalapplicationsofmachinelearning,theepigeneticregulationofT-cellfunctionsandcancer
immunotherapy.
ChunjieJiang
Dr. Chunjie Jiang’s research focuses on the integrative analysis of multi-omics next-generation
sequencing data to reveal the underlying molecular mechanism, identify clinical biomarkers for
diagnosis and treatment, and make contributions to precision medicine in the fields of metabolism
andcancerbiology.
Untilnow,Dr.Jianghaspublished 30papersinScience,Cell,NatureNeuroscience,CellMetabolism,
CellStemCell,etc.,includingtwocoverstories(HuandJiangetal.,CellStemCell,2019;HuandJiang
et al., Genes & Development, 2022) as co-first author. The study Precision Medicine Approach to
GlucocorticoidTherapy(HuandJiangetal.,CellMetabolism,2021,co-firstauthor)hasbeenselected
asthe2022Top10ClinicalResearchFinalists.
Additionally,Dr. JiangservesasaGuest/Associate/YouthEditorfor8journalsandareviewer
formorethan20journals.
vii
ShengliLi
Dr. Shengli Li received his Ph.D. in Medical Systems Biology from Fudan University in
2018 and Postdoctoral training from the University of Texas Health Science center in Houston
in 2018–2020. He is a Principal Investigator with the Precision Research Center for Refractory
DiseaseatShanghaiGeneralHospitalaffiliatedtoShanghaiJiaoTongUniversitySchoolofMedicine.
Shengli is a computational biologist with expertise in human disease genetics, including cancer
and cardiovascular diseases. His research focuses on the integrative utilization of cutting-edge
computational biology algorithms and molecular experimental technologies to reveal systematical
changes and functional factors in human disease progression, disease microenvironment and
responsetodrugtreatment.
viii
Preface to ”Bioinformatics and Machine Learning for
Cancer Biology”
Cancer is a leading cause of death worldwide, claiming millions of lives each year. Cancer
biology is an essential research field to understand how cancer develops, evolves, and responds to
therapy.Bytakingadvantageofaseriesof“omics”technologies(e.g.,genomics,transcriptomics,and
epigenomics), computational methods in bioinformatics and machine learning can help scientists
and researchers to decipher the complexity of cancer heterogeneity, tumorigenesis, and anticancer
drug discovery. Particularly, bioinformatics enables the systematic interrogation and analysis
of cancer from various perspectives, including genetics, epigenetics, signaling networks, cellular
behavior,clinicalmanifestation,andepidemiology. Moreover,thankstotheinfluxofnext-generation
sequencing(NGS)datainthepostgenomiceraandmultiplelandmarkcancer-focusedprojects,such
asTheCancerGenomeAtlas(TCGA)andClinicalProteomicTumorAnalysisConsortium(CPTAC),
machine learning has a uniquely advantageous role in boosting data-driven cancer research and
unravelingnovelmethodsfortheprognosis,prediction,andtreatmentofcancer.
This book presents some of the latest progresses on leveraging bioinformatics and machine
learning for cancer biology, which is particularly useful and attractive for cancer biologists,
bioinformaticians, machine learning experts, computational biologists and other scientists or
researchers in life sciences and biology. We would like to thank all the authors contributing to this
book who made significant contributions to the better understanding of various cancers as well as
cancer-relatedanalysismethodimprovements.Weareeagertoseemoreexcitingdiscoveriesincancer
biologywiththehelpofbioinformaticsanalysisandmachinelearninginthenearfuture.
ShibiaoWan,YipingFan,ChunjieJiang,andShengliLi
Editors
ix