PURPOSE: Advances in biological measurement technologies are enabling large-scale studies of patient cohorts across multiple omics platforms. Holistic analysis of these data can generate actionable insights for translational research and necessitate new approaches for data integration and mining. METHODS: We present a novel approach for integrating data across platforms on the basis of the shared nearest neighbors algorithm and use it to create a network of multiplatform data from the immunogenomic profiling of non-small-cell lung cancer project. RESULTS: Benchmarking demonstrates that the shared nearest neighbors-based network approach outperforms a traditional gene-gene network in capturing established interactions while providing new ones on the basis of the interplay between measurements from different platforms. When used to examine patient characteristics of interest, our approach provided signatures associated with and new leads related to recurrence and TP53 oncogenotype. CONCLUSION: The network developed offers an unprecedented, holistic view into immunogenomic profiling of non-small-cell lung cancer, which can be explored through the accompanying interactive browser that we built.
PURPOSE: Advances in biological measurement technologies are enabling large-scale studies of patient cohorts across multiple omics platforms. Holistic analysis of these data can generate actionable insights for translational research and necessitate new approaches for data integration and mining. METHODS: We present a novel approach for integrating data across platforms on the basis of the shared nearest neighbors algorithm and use it to create a network of multiplatform data from the immunogenomic profiling of non-small-cell lung cancer project. RESULTS: Benchmarking demonstrates that the shared nearest neighbors-based network approach outperforms a traditional gene-gene network in capturing established interactions while providing new ones on the basis of the interplay between measurements from different platforms. When used to examine patient characteristics of interest, our approach provided signatures associated with and new leads related to recurrence and TP53 oncogenotype. CONCLUSION: The network developed offers an unprecedented, holistic view into immunogenomic profiling of non-small-cell lung cancer, which can be explored through the accompanying interactive browser that we built.
Authors: L Federico; D J McGrail; S-E Bentebibel; C Haymaker; A Ravelli; M-A Forget; T Karpinets; P Jiang; A Reuben; M V Negrao; J Li; R Khairullah; J Zhang; A Weissferdt; A A Vaporciyan; M B Antonoff; G Walsh; S-Y Lin; A Futreal; I Wistuba; J Roth; L A Byers; P-O Gaudreau; N Uraoka; A F Cruz; H Dejima; R N Lazcano; L M Solis; E R Parra; J J Lee; S Swisher; T Cascone; J V Heymach; J Zhang; B Sepesi; D L Gibbons; C Bernatchez Journal: Ann Oncol Date: 2021-10-13 Impact factor: 32.976
Authors: Alexandre Reuben; Jiexin Zhang; Shin-Heng Chiou; Rachel M Gittelman; Jun Li; Won-Chul Lee; Junya Fujimoto; Carmen Behrens; Xiaoke Liu; Feng Wang; Kelly Quek; Chunlin Wang; Farrah Kheradmand; Runzhe Chen; Chi-Wan Chow; Heather Lin; Chantale Bernatchez; Ali Jalali; Xin Hu; Chang-Jiun Wu; Agda Karina Eterovic; Edwin Roger Parra; Erik Yusko; Ryan Emerson; Sharon Benzeno; Marissa Vignali; Xifeng Wu; Yuanqing Ye; Latasha D Little; Curtis Gumbs; Xizeng Mao; Xingzhi Song; Samantha Tippen; Rebecca L Thornton; Tina Cascone; Alexandra Snyder; Jennifer A Wargo; Roy Herbst; Stephen Swisher; Humam Kadara; Cesar Moran; Neda Kalhor; Jianhua Zhang; Paul Scheet; Ara A Vaporciyan; Boris Sepesi; Don L Gibbons; Harlan Robins; Patrick Hwu; John V Heymach; Padmanee Sharma; James P Allison; Veera Baladandayuthapani; Jack J Lee; Mark M Davis; Ignacio I Wistuba; P Andrew Futreal; Jianjun Zhang Journal: Nat Commun Date: 2020-01-30 Impact factor: 14.919