BackgroundMicrovascular　invasion　(MVI)　is　the　main　factor　affecting　the　prognosis　of　patients　with　hepatocellular　carcinoma　(HCC).　The　aim　of　this　study　was　to　identify　accurate　diagnostic　biomarkers　from　urinary　protein　signatures　for　preoperative　prediction.MethodsWe　conducted　label-free　quantitative　proteomic　studies　on　urine　samples　of　91　HCC　patients　and　22　healthy　controls.　We　identified　candidate　biomarkers　capable　of　predicting　MVI　status　and　combined　them　with　patient　clinical　information　to　perform　a　preoperative　nomogram　for　predicting　MVI　status　in　the　training　cohort.　Then,　the　nomogram　was　validated　in　the　testing　cohort　(n　=　23).　Expression　levels　of　biomarkers　were　further　confirmed　by　enzyme-linked　immunosorbent　assay　(ELISA)　in　an　independent　validation　HCC　cohort　(n　=　57).ResultsUrinary　proteomic　features　of　healthy　controls　are　mainly　characterized　by　active　metabolic　processes.　Cell　adhesion　and　cell　proliferation-related　pathways　were　highly　defined　in　the　HCC　group,　such　as　extracellular　matrix　organization,　cell-cell　adhesion,　and　cell-cell　junction　organization,　which　confirms　the　malignant　phenotype　of　HCC　patients.　Based　on　the　expression　levels　of　four　proteins:　CETP,　HGFL,　L1CAM,　and　LAIR2,　combined　with　tumor　diameter,　serum　AFP,　and　GGT　concentrations　to　establish　a　preoperative　MVI　status　prediction　model　for　HCC　patients.　The　nomogram　achieved　good　concordance　indexes　of　0.809　and　0.783　in　predicting　MVI　in　the　training　and　testing　cohorts.ConclusionsThe　four-protein-related　nomogram　in　urine　samples　is　a　promising　preoperative　prediction　model　for　the　MVI　status　of　HCC　patients.　Using　the　model,　the　risk　for　an　individual　patient　to　harbor　MVI　can　be　determined.