{"id":"https://openalex.org/W7137950905","doi":"https://doi.org/10.48550/arxiv.2603.13787","title":"Advancing Cancer Prognosis with Hierarchical Fusion of Genomic, Proteomic and Pathology Imaging Data from a Systems Biology Perspective","display_name":"Advancing Cancer Prognosis with Hierarchical Fusion of Genomic, Proteomic and Pathology Imaging Data from a Systems Biology Perspective","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7137950905","doi":"https://doi.org/10.48550/arxiv.2603.13787"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.13787","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13787","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.13787","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zhou, Junjie","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhou, Junjie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129700837","display_name":"Bao Xue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xue, Bao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126080795","display_name":"Meiling Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Meiling","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129705460","display_name":"Wei Shao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shao, Wei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129704395","display_name":"Daoqiang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Daoqiang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.5162000060081482,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.5162000060081482,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.30790001153945923,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.05090000107884407,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/systems-biology","display_name":"Systems biology","score":0.6948000192642212},{"id":"https://openalex.org/keywords/data-integration","display_name":"Data integration","score":0.5733000040054321},{"id":"https://openalex.org/keywords/proteome","display_name":"Proteome","score":0.5084999799728394},{"id":"https://openalex.org/keywords/hypergraph","display_name":"Hypergraph","score":0.4334000051021576},{"id":"https://openalex.org/keywords/proteogenomics","display_name":"Proteogenomics","score":0.42989999055862427},{"id":"https://openalex.org/keywords/biological-data","display_name":"Biological data","score":0.42809998989105225},{"id":"https://openalex.org/keywords/genomics","display_name":"Genomics","score":0.39739999175071716},{"id":"https://openalex.org/keywords/fusion-gene","display_name":"Fusion gene","score":0.39149999618530273},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.3871000111103058}],"concepts":[{"id":"https://openalex.org/C152662350","wikidata":"https://www.wikidata.org/wiki/Q815297","display_name":"Systems biology","level":2,"score":0.6948000192642212},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.6169000267982483},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.5733000040054321},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5478000044822693},{"id":"https://openalex.org/C104397665","wikidata":"https://www.wikidata.org/wiki/Q860947","display_name":"Proteome","level":2,"score":0.5084999799728394},{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.4334000051021576},{"id":"https://openalex.org/C145741570","wikidata":"https://www.wikidata.org/wiki/Q7251534","display_name":"Proteogenomics","level":5,"score":0.42989999055862427},{"id":"https://openalex.org/C201797286","wikidata":"https://www.wikidata.org/wiki/Q4914986","display_name":"Biological data","level":2,"score":0.42809998989105225},{"id":"https://openalex.org/C189206191","wikidata":"https://www.wikidata.org/wiki/Q222046","display_name":"Genomics","level":4,"score":0.39739999175071716},{"id":"https://openalex.org/C111829193","wikidata":"https://www.wikidata.org/wiki/Q1108970","display_name":"Fusion gene","level":3,"score":0.39149999618530273},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3871000111103058},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.3869999945163727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38609999418258667},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.3749000132083893},{"id":"https://openalex.org/C28225019","wikidata":"https://www.wikidata.org/wiki/Q4915005","display_name":"Biological network","level":2,"score":0.35830000042915344},{"id":"https://openalex.org/C163763905","wikidata":"https://www.wikidata.org/wiki/Q17075943","display_name":"Precision medicine","level":2,"score":0.35030001401901245},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.34549999237060547},{"id":"https://openalex.org/C2777002142","wikidata":"https://www.wikidata.org/wiki/Q5031432","display_name":"Cancer biomarkers","level":3,"score":0.3440999984741211},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.3400000035762787},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.3328000009059906},{"id":"https://openalex.org/C123894998","wikidata":"https://www.wikidata.org/wiki/Q425158","display_name":"Fusion protein","level":4,"score":0.32429999113082886},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C137866125","wikidata":"https://www.wikidata.org/wiki/Q4299308","display_name":"Modelling biological systems","level":3,"score":0.3073999881744385},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27459999918937683},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C136339569","wikidata":"https://www.wikidata.org/wiki/Q1142297","display_name":"Molecular imaging","level":3,"score":0.2718000113964081},{"id":"https://openalex.org/C2778559731","wikidata":"https://www.wikidata.org/wiki/Q23808793","display_name":"Radiomics","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C94795543","wikidata":"https://www.wikidata.org/wiki/Q3813754","display_name":"Human proteome project","level":4,"score":0.2630000114440918},{"id":"https://openalex.org/C32220436","wikidata":"https://www.wikidata.org/wiki/Q2072214","display_name":"Personalized medicine","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.13787","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13787","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.13787","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13787","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"To":[0,80],"enhance":[1],"the":[2,27,30,93,203],"precision":[3],"of":[4,205],"cancer":[5],"prognosis,":[6],"recent":[7],"research":[8],"has":[9],"increasingly":[10],"focused":[11],"on":[12,198],"multimodal":[13],"survival":[14,50,193],"methods":[15],"by":[16],"integrating":[17],"genomic":[18,38],"data":[19,66],"and":[20,40,131,153,170],"histology":[21,101],"images.":[22],"However,":[23],"current":[24],"approaches":[25],"overlook":[26],"fact":[28],"that":[29,72,91,117],"proteome":[31],"serves":[32],"as":[33],"an":[34],"intermediate":[35],"layer":[36],"bridging":[37],"alterations":[39],"histopathological":[41],"features":[42,183],"while":[43],"providing":[44],"complementary":[45],"biological":[46,53,78,94],"information":[47],"essential":[48],"for":[49,129],"prediction.":[51,195],"This":[52],"reality":[54],"exposes":[55],"another":[56],"architectural":[57],"limitation:":[58],"existing":[59],"integrative":[60],"analysis":[61],"studies":[62],"fuse":[63],"these":[64,82],"heterogeneous":[65],"sources":[67],"in":[68],"a":[69,87,104,113],"flat":[70],"manner":[71],"fails":[73],"to":[74,98,100,124,147,176,190],"capture":[75,177],"their":[76],"inherent":[77],"hierarchy.":[79],"address":[81],"limitations,":[83],"we":[84,109,159],"propose":[85,160],"HFGPI,":[86],"hierarchical":[88,188],"fusion":[89],"framework":[90],"models":[92],"progression":[95],"from":[96,103],"genes":[97,130],"proteins":[99,169],"images":[102],"systems":[105],"biology":[106],"perspective.":[107],"Specifically,":[108],"introduce":[110],"Molecular":[111],"Tokenizer,":[112],"molecular":[114],"encoding":[115],"strategy":[116],"integrates":[118],"identity":[119],"embeddings":[120],"with":[121,144],"expression":[122],"profiles":[123],"construct":[125],"biologically":[126],"informed":[127],"representations":[128],"proteins.":[132],"We":[133],"then":[134],"develop":[135],"Gene-Regulated":[136],"Protein":[137],"Fusion":[138],"(GRPF),":[139],"which":[140,165],"employs":[141],"graph-aware":[142],"cross-attention":[143],"structure-preserving":[145],"alignment":[146],"explicitly":[148],"model":[149],"gene-protein":[150],"regulatory":[151],"relationships":[152],"generate":[154],"gene-regulated":[155],"protein":[156],"representations.":[157],"Additionally,":[158],"Protein-Guided":[161],"Hypergraph":[162],"Learning":[163],"(PGHL),":[164],"establishes":[166],"associations":[167],"between":[168],"image":[171],"patches,":[172],"leveraging":[173],"hypergraph":[174],"convolution":[175],"higher-order":[178],"protein-morphology":[179],"relationships.":[180],"The":[181],"final":[182],"are":[184],"progressively":[185],"fused":[186],"across":[187],"layers":[189],"achieve":[191],"precise":[192],"outcome":[194],"Extensive":[196],"experiments":[197],"five":[199],"benchmark":[200],"datasets":[201],"demonstrate":[202],"superiority":[204],"HFGPI":[206],"over":[207],"state-of-the-art":[208],"methods.":[209]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2026-03-18T00:00:00"}