2024
A Survival Analysis of Patients with Radiation-Induced Cancers after Prior Radiation for Head and Neck Cancer
Laseinde E, Guan L, Hildebrand R, Meurice N, Gensheimer M, Beadle B, Holsinger F, Sunwoo J, Baik F, Sirjani D, Divi V, Kaplan M, Pinto H, Colevas A, Rahman M, Le Q. A Survival Analysis of Patients with Radiation-Induced Cancers after Prior Radiation for Head and Neck Cancer. International Journal Of Radiation Oncology • Biology • Physics 2024, 120: e764. DOI: 10.1016/j.ijrobp.2024.07.1678.Peer-Reviewed Original ResearchHead and neck cancerNonsurgical groupNeck cancerRadiation treatmentTreated with non-surgical therapyIRB-approved retrospective reviewSurvival rateKaplan-Meier survival curvesSurvival rate of patientsNon-surgical therapySurvival analysis of patientsLog-rank testAnalysis of patientsNon-surgical groupNon-surgical treatmentRate of patientsRadiation-induced cancerCompare survival ratesPrior RTPostoperative RTMedian followPrior radiationSquamous histologyOverall survivalMedian ageTert-expressing cells contribute to salivary gland homeostasis and tissue regeneration after radiation therapy
Guan L, Viswanathan V, Jiang Y, Vijayakumar S, Cao H, Zhao J, Colburg D, Neuhöfer P, Zhang Y, Wang J, Xu Y, Laseinde E, Hildebrand R, Rahman M, Frock R, Kong C, Beachy P, Artandi S, Le Q. Tert-expressing cells contribute to salivary gland homeostasis and tissue regeneration after radiation therapy. Genes & Development 2024, 38: 569-582. PMID: 38997156, PMCID: PMC11293384, DOI: 10.1101/gad.351577.124.Peer-Reviewed Original ResearchConceptsSubmandibular glandSalivary gland homeostasisProgenitor cellsGland homeostasisResponse to radiotherapyAdult submandibular glandCell survivalSalivary gland regenerationSelf-renewal capacityEnhanced proliferative activityRadiation therapyDuctal regionsRadiotherapyModulate cell survivalTelomerase-expressingGland regenerationProliferative activityMouse strainsTERT expressionCreERT2 recombinaseSalivary gland biologyRadiation exposureTERT locusIn vitro cultureCell populationsIntegrated longitudinal multiomics study identifies immune programs associated with acute COVID-19 severity and mortality
Gygi J, Maguire C, Patel R, Shinde P, Konstorum A, Shannon C, Xu L, Hoch A, Jayavelu N, Haddad E, Network I, Reed E, Kraft M, McComsey G, Metcalf J, Ozonoff A, Esserman D, Cairns C, Rouphael N, Bosinger S, Kim-Schulze S, Krammer F, Rosen L, van Bakel H, Wilson M, Eckalbar W, Maecker H, Langelier C, Steen H, Altman M, Montgomery R, Levy O, Melamed E, Pulendran B, Diray-Arce J, Smolen K, Fragiadakis G, Becker P, Sekaly R, Ehrlich L, Fourati S, Peters B, Kleinstein S, Guan L. Integrated longitudinal multiomics study identifies immune programs associated with acute COVID-19 severity and mortality. Journal Of Clinical Investigation 2024, 134: e176640. PMID: 38690733, PMCID: PMC11060740, DOI: 10.1172/jci176640.Peer-Reviewed Original ResearchConceptsClinical outcomesImmune cascadeElevated levels of inflammatory cytokinesDisease severityLevels of inflammatory cytokinesFormation of neutrophil extracellular trapsAcute COVID-19 severityCritically ill patientsNeutrophil extracellular trapsDevelopment of therapiesCOVID-19 cohortCOVID-19 severityViral clearanceImmunosuppressive metabolitesDeep immunophenotypingMultiomic modelIFN-stimulated genesImmunophenotypic assessmentB cellsDisease courseEarly upregulationInflammatory cytokinesDisease progressionIFN inhibitorsExtracellular trapsA supervised Bayesian factor model for the identification of multi-omics signatures
Gygi J, Konstorum A, Pawar S, Aron E, Kleinstein S, Guan L. A supervised Bayesian factor model for the identification of multi-omics signatures. Bioinformatics 2024, 40: btae202. PMID: 38603606, PMCID: PMC11078774, DOI: 10.1093/bioinformatics/btae202.Peer-Reviewed Original ResearchConceptsMulti-omics signaturesBayesian factor modelMulti-omics dataMulti-omics integrationSupplementary dataOmics datasetsMulti-omicsProfiling datasetsR packageDiverse assaysImproved biological understandingProfiling assaysSignature discoveryBioinformaticsProfiling studiesBiological understandingDimensionality reductionBiological responsesBiological signaturesCombination of dimensionality reductionAbstract 5442: Terthighcells: key players in salivary gland homeostasis and regeneration after radiation therapy in adult mice
Guan L, Viswanathan V, V S, Cao H, Jiang Y, Zhao J, Colburg D, Neuhoefer P, Xu Y, Laseinde E, Artandi S, Le Q. Abstract 5442: Terthighcells: key players in salivary gland homeostasis and regeneration after radiation therapy in adult mice. Cancer Research 2024, 84: 5442-5442. DOI: 10.1158/1538-7445.am2024-5442.Peer-Reviewed Original ResearchSalivary gland homeostasisSubmandibular glandRadiation therapyGland homeostasisDuctal regionsAdult miceAmerican Association for Cancer Research annual meetingsProgenitor cellsAcinar cellsRadiation cell killingAdult submandibular glandCell survivalSelf-renewal capacityPost-radiotherapyPost-radiationModulate cell survivalStem/progenitor cellsNormal organsMouse strainsTERT expressionCell killingDuctal cellsOxidative stress response pathwayCreERT2 recombinaseTERT locusA multi-omics systems vaccinology resource to develop and test computational models of immunity
Shinde P, Soldevila F, Reyna J, Aoki M, Rasmussen M, Willemsen L, Kojima M, Ha B, Greenbaum J, Overton J, Guzman-Orozco H, Nili S, Orfield S, Gygi J, da Silva Antunes R, Sette A, Grant B, Olsen L, Konstorum A, Guan L, Ay F, Kleinstein S, Peters B. A multi-omics systems vaccinology resource to develop and test computational models of immunity. Cell Reports Methods 2024, 4: 100731. PMID: 38490204, PMCID: PMC10985234, DOI: 10.1016/j.crmeth.2024.100731.Peer-Reviewed Original Research
2023
Smooth and Probabilistic PARAFAC Model with Auxiliary Covariates
Guan L. Smooth and Probabilistic PARAFAC Model with Auxiliary Covariates. Journal Of Computational And Graphical Statistics 2023, 33: 538-550. DOI: 10.1080/10618600.2023.2257783.Peer-Reviewed Original ResearchEarly cellular and molecular signatures correlate with severity of West Nile virus infection
Lee H, Zhao Y, Fleming I, Mehta S, Wang X, Vander Wyk B, Ronca S, Kang H, Chou C, Fatou B, Smolen K, Levy O, Clish C, Xavier R, Steen H, Hafler D, Love J, Shalek A, Guan L, Murray K, Kleinstein S, Montgomery R. Early cellular and molecular signatures correlate with severity of West Nile virus infection. IScience 2023, 26: 108387. PMID: 38047068, PMCID: PMC10692672, DOI: 10.1016/j.isci.2023.108387.Peer-Reviewed Original ResearchWest Nile virusEffective anti-viral responseInnate immune cell typesWest Nile virus infectionPro-inflammatory markersAcute time pointsImmune cell typesAnti-viral responseMolecular signaturesHost cellular activitiesAcute infectionAsymptomatic donorsPeripheral bloodSevere infectionsVirus infectionImmune responseSevere casesCell activityIll individualsSerum proteomicsInfectionInfection severityHigh expressionTime pointsNile virusDistinguishing features of long COVID identified through immune profiling
Klein J, Wood J, Jaycox J, Dhodapkar R, Lu P, Gehlhausen J, Tabachnikova A, Greene K, Tabacof L, Malik A, Silva Monteiro V, Silva J, Kamath K, Zhang M, Dhal A, Ott I, Valle G, Peña-Hernández M, Mao T, Bhattacharjee B, Takahashi T, Lucas C, Song E, McCarthy D, Breyman E, Tosto-Mancuso J, Dai Y, Perotti E, Akduman K, Tzeng T, Xu L, Geraghty A, Monje M, Yildirim I, Shon J, Medzhitov R, Lutchmansingh D, Possick J, Kaminski N, Omer S, Krumholz H, Guan L, Dela Cruz C, van Dijk D, Ring A, Putrino D, Iwasaki A. Distinguishing features of long COVID identified through immune profiling. Nature 2023, 623: 139-148. PMID: 37748514, PMCID: PMC10620090, DOI: 10.1038/s41586-023-06651-y.Peer-Reviewed Original ResearchConceptsLong COVIDSARS-CoV-2Infection syndromeExaggerated humoral responseSoluble immune mediatorsEpstein-Barr virusPost-exertional malaiseCross-sectional studyHigher antibody responseImmune mediatorsImmune phenotypingImmune profilingHumoral responseAntibody responseLymphocyte populationsCOVID statusUnbiased machineCortisol levelsLC statusRelevant biomarkersViral pathogensSyndromeCOVIDFuture studiesBiological featuresPredictive overfitting in immunological applications: Pitfalls and solutions
Gygi J, Kleinstein S, Guan L. Predictive overfitting in immunological applications: Pitfalls and solutions. Human Vaccines & Immunotherapeutics 2023, 19: 2251830. PMID: 37697867, PMCID: PMC10498807, DOI: 10.1080/21645515.2023.2251830.Peer-Reviewed Original ResearchMulti-omic longitudinal study reveals immune correlates of clinical course among hospitalized COVID-19 patients
Diray-Arce J, Fourati S, Jayavelu N, Patel R, Maguire C, Chang A, Dandekar R, Qi J, Lee B, van Zalm P, Schroeder A, Chen E, Konstorum A, Brito A, Gygi J, Kho A, Chen J, Pawar S, Gonzalez-Reiche A, Hoch A, Milliren C, Overton J, Westendorf K, Network I, Abraham J, Adkisson M, Albert M, Torres L, Alvarenga B, Anderson M, Anderson E, Arnett A, Asashima H, Atkinson M, Baden L, Barton B, Beach K, Beagle E, Becker P, Bell M, Bernui M, Bime C, Kumar A, Booth L, Borresen B, Brakenridge S, Bristow L, Bryant R, Calfee C, Manuel J, Carrillo S, Chak S, Chang I, Connors J, Conway M, Corry D, Cowan D, Croen B, Dela Cruz C, Cusimano G, Eaker L, Edwards C, Ehrlich L, Elashoff D, Erickson H, Erle D, Farhadian S, Farrugia K, Fatou B, Fernandes A, Fernandez-Sesma A, Fragiadakis G, Furukawa S, Geltman J, Ghale R, Bermúdez M, Goonewardene M, Sanchez E, Guirgis F, Hafler D, Hamilton S, Harris P, Nemati A, Hendrickson C, Agudelo N, Hodder T, Holland S, Hough C, Huerta C, Hurley K, Hutton S, Iwasaki A, Jauregui A, Jha M, Johnson B, Joyner D, Kangelaris K, Kelly G, Khalil Z, Khan Z, Kheradmand F, Kim J, Kimura H, Ko A, Kohr B, Kraft M, Krummel M, Kutzler M, Lasky-Su J, Lee S, Lee D, Leipold M, Lentucci C, Leroux C, Lin E, Liu S, Love C, Lu Z, Maliskova L, Roth B, Manohar M, Martens M, McComsey G, McEnaney K, McLin R, Melamed E, Melnyk N, Mendez K, Messer W, Metcalf J, Michelotti G, Mick E, Mohanty S, Mosier J, Mulder L, Murphy M, Nadeau K, Nelson E, Nelson A, Nguyen V, Oberhaus J, Panganiban B, Pellegrini K, Pickering H, Powell D, Presnell S, Pulendran B, Rahman A, Sadeed A, Raskin A, Reed E, Pereira S, Rivera A, Rogers J, Rogers A, Rogowski B, Rooks R, Rosenberg-Hasson Y, Rothman J, Rousseau J, Salehi-Rad R, Saluvan M, Samaha H, Schaenman J, Schunk R, Semenza N, Sen S, Sevransky J, Seyfert-Margolis V, Shaheen T, Shaw A, Sieg S, Siegel S, Sigal N, Siles N, Simmons B, Simon V, Singh G, Sinko L, Smith C, Smolen K, Song L, Srivastava K, Sullivan P, Syphurs C, Tcheou J, Tegos G, Tharp G, Ally A, Tsitsiklis A, Ungaro R, Vaysman T, Viode A, Vita R, Wang X, Ward A, Ward D, Willmore A, Woloszczuk K, Wong K, Woodruff P, Xu L, van Haren S, van de Guchte A, Zhao Y, Cairns C, Rouphael N, Bosinger S, Kim-Schulze S, Krammer F, Rosen L, Grubaugh N, van Bakel H, Wilson M, Rajan J, Steen H, Eckalbar W, Cotsapas C, Langelier C, Levy O, Altman M, Maecker H, Montgomery R, Haddad E, Sekaly R, Esserman D, Ozonoff A, Becker P, Augustine A, Guan L, Peters B, Kleinstein S. Multi-omic longitudinal study reveals immune correlates of clinical course among hospitalized COVID-19 patients. Cell Reports Medicine 2023, 4: 101079. PMID: 37327781, PMCID: PMC10203880, DOI: 10.1016/j.xcrm.2023.101079.Peer-Reviewed Original ResearchConceptsDisease courseFatal COVID-19 diseaseHospitalized COVID-19 patientsSevere disease courseCOVID-19 participantsCOVID-19 patientsTrajectory groupsHost immune responseCOVID-19 diseaseImmune correlatesAcute infectionClinical courseHospital admissionClinical outcomesFatal outcomeClinical prognosisImmune responseSevere diseaseLongitudinal bloodNasal samplesBiologic stateLongitudinal studyDistinct assaysCohortMolecular signaturesSmooth and probabilistic PARAFAC model with auxiliary covariates
Leying Guan (2023) Smooth and Probabilistic PARAFAC Model with Auxiliary Covariates, Journal of Computational and Graphical Statistics, DOI: 10.1080/10618600.2023.2257783Peer-Reviewed Original Research
2022
Localized conformal prediction: a generalized inference framework for conformal prediction
Guan L. Localized conformal prediction: a generalized inference framework for conformal prediction. Biometrika 2022, 110: 33-50. DOI: 10.1093/biomet/asac040.Peer-Reviewed Original ResearchPrediction and Outlier Detection in Classification Problems
Guan L, Tibshirani R. Prediction and Outlier Detection in Classification Problems. Journal Of The Royal Statistical Society Series B (Statistical Methodology) 2022, 84: 524-546. PMID: 35910400, PMCID: PMC9305480, DOI: 10.1111/rssb.12443.Peer-Reviewed Original ResearchPost model‐fitting exploration via a “Next‐Door” analysis.
Guan, Leying, and Robert Tibshirani. "Post model‐fitting exploration via a “Next‐Door” analysis." Canadian Journal of Statistics 48, no. 3 (2020): 447-470.Peer-Reviewed Original Research
2020
Post model‐fitting exploration via a “Next‐Door” analysis
Guan L, Tibshirani R. Post model‐fitting exploration via a “Next‐Door” analysis. Canadian Journal Of Statistics 2020, 48: 447-470. PMID: 36092475, PMCID: PMC9454156, DOI: 10.1002/cjs.11542.Peer-Reviewed Original Research
2019
Increased T Cell Differentiation and Cytolytic Function in Bangladeshi Compared to American Children
Wagar LE, Bolen CR, Sigal N, Angel C, Guan L, Kirkpatrick BD, Haque R, Tibshirani RJ, Parsonnet J, Petri WA, Davis MM. Increased T Cell Differentiation and Cytolytic Function in Bangladeshi Compared to American Children. Frontiers In Immunology 2019, 10: 2239. PMID: 31620139, PMCID: PMC6763580, DOI: 10.3389/fimmu.2019.02239.Peer-Reviewed Original ResearchConceptsPeripheral blood mononuclear cellsYears of ageIL-8Immune cellsPMA-ionomycinInfection-related morbidityIncidence of allergyBlood mononuclear cellsCytokine production profileT cell differentiationYears of lifeHygiene hypothesisImmune monitoringCytolytic functionMononuclear cellsHigh-income countriesImmune responseBangladeshi childrenMicrobial exposureAmerican childrenTGFβ expressionInfectious agentsImmune systemClinical healthAltered activationDetecting Strong Signals in Gene Perturbation Experiments: An Adaptive Approach With Power Guarantee and FDR Control
Guan L, Chen X, Wong H. Detecting Strong Signals in Gene Perturbation Experiments: An Adaptive Approach With Power Guarantee and FDR Control. Journal Of The American Statistical Association 2019, 115: 1747-1755. PMID: 33311819, PMCID: PMC7731979, DOI: 10.1080/01621459.2019.1635484.Peer-Reviewed Original Research
2018
Approximate $\ell_{0}$-penalized estimation of piecewise-constant signals on graphs
Fan Z, Guan L. Approximate $\ell_{0}$-penalized estimation of piecewise-constant signals on graphs. The Annals Of Statistics 2018, 46: 3217-3245. DOI: 10.1214/17-aos1656.Peer-Reviewed Original ResearchPiecewise constant signalsAverage vertex degreeInhomogeneous graphsSparsity classesMinimax optimalityApproximate minimizerVertex degreeRisk guaranteesGraph connectivityExact minimizationNoise settingsPolynomial timeEstimatorGraphMinimizationExpansion algorithmGuaranteesHigh signalEffective resistanceMinimizersClassOptimalityEstimationAlgorithmSignalsSupervised learning via the "hubNet" procedure.
Guan L, Fan Z, Tibshirani R. Supervised learning via the "hubNet" procedure. Statistica Sinica 2018, 28: 1225-1243. PMID: 35677806, PMCID: PMC9173714, DOI: 10.5705/ss.202016.0482.Peer-Reviewed Original Research