Analysis and Visualization of Longitudinal Genomic and Clinical Data from the AACR Project GENIE Biopharma Collaborative in cBioPortal.
Ino De BruijnRitika KundraBrooke MastrogiacomoThinh Ngoc TranLuke SikinaTali MazorXiang LiAngelica OchoaGaofei ZhaoBryan LaiAdam AbeshouseDiana BaiceanuErsin CiftciUgur DogrusozAndrew DufilieZiya ErkocElena G LaraZhaoyuan FuBenjamin E GrossCharles D HaynesAllison P HeathDavid M HigginsPrasanna JagannathanKarthik KalletlaPriti KumariJames R LindsayAaron LismanBas LeenknegtPieter LukasseDivya MadalaRamyasree MadupuriPim van NieropOleguer PlantalechJoyce QuachAdam C ResnickSander Y A RodenburgBaby A SatravadaFedde SchaefferRobert SheridanJessica SinghRajat SirohiSelcuk Onur SumerSjoerd van HagenAvery WangManda WilsonHongxin ZhangKelsey ZhuNicole RuskSamantha BrownJessica A LaveryKatherine S PanageasJulia E RudolphMichele L LeNoue-NewtonJeremy L WarnerXindi GuoHaley Hunter-ZinckThomas V YuShirin PillaiChelsea NicholsStuart M GardosJohn PhilipGenie Bpc Core TeamAacr Project Genie ConsortiumKenneth L KehlGregory J RielyDeborah SchragJocelyn LeeMichael V FiandaloShawn M SweeneyTrevor J PughChris SanderEthan CeramiJianjiong GaoNikolaus SchultzPublished in: Cancer research (2023)
International cancer registries make real-world genomic and clinical data available, but their joint analysis remains a challenge. AACR Project GENIE, an international cancer registry collecting data from 19 cancer centers, makes data from >130,000 patients publicly available through the cBioPortal for Cancer Genomics (https://genie.cbioportal.org). For 25,000 patients, additional real-world longitudinal clinical data, including treatment and outcome data, are being collected by the AACR Project GENIE Biopharma Collaborative using the PRISSMM data curation model. Several thousand of these cases are now also available in cBioPortal. We have significantly enhanced the functionalities of cBioPortal to support the visualization and analysis of this rich clinico-genomic linked dataset, as well as datasets generated by other centers and consortia. Examples of these enhancements include 1) visualization of the longitudinal clinical and genomic data at the patient level, including timelines for diagnoses, treatments, and outcomes, 2) the ability to select samples based on treatment status, facilitating a comparison of molecular and clinical attributes between samples before and after a specific treatment, and 3) survival analysis estimates based on individual treatment regimens received. Together, these features provide cBioPortal users with a toolkit to interactively investigate complex clinico-genomic data in order to generate hypotheses and make discoveries about the impact of specific genomic variants on prognosis and therapeutic sensitivities in cancer.
Keyphrases
- electronic health record
- papillary thyroid
- big data
- copy number
- end stage renal disease
- quality improvement
- squamous cell
- chronic kidney disease
- newly diagnosed
- machine learning
- young adults
- data analysis
- gene expression
- adipose tissue
- cross sectional
- case report
- artificial intelligence
- peritoneal dialysis
- genome wide
- deep learning
- patient reported outcomes
- weight loss
- single cell