Background:　Liquid　biopsy　based　on　5-hydroxymethylcytosine　(5hmC)　signatures　of　plasma　cell-free　DNA　(cfDNA)　originating　from　tumor　cells　provides　a　novel　approach　for　early　diagnosis　in　hepatocellular　carcinoma　(HCC).　Here,　we　sought　to　develop　a　reliable　model　using　cfDNA　ShmC　signatures　and　protein　biomarkers　for　diagnosis　and　prognosis　of　HCC.　Patients　and　methods:　We　carried　out　genome-wide　5hmC　sequencing　of　cfDNA　samples　collected　from　165　healthy　volunteers,　62　liver　cirrhosis　(LC)　patients　and　135　HCC　patients.　A　sensitive　5hmC　diagnostic　model　was　developed　based　on　ShmC　signatures　selected　by　sparse　Partial　Least　Squares　Discriminant　Analysis　and　cross-validation　to　define　the　weighted　diagnostic　score　(wd-score).　Then,　we　combined　protein　biomarkers　with　the　wd-score　to　build　a　more　robust　score　(HCC　score)　by　logistic　regression.　Results:　The　distribution　pattern　of　differential　5hmC　regions　could　dearly　distinguish　HCC　patients,　LC　patients　and　healthy　volunteers.　The　wd-score　based　on　64　5hmC　signatures　in　cfDNA　achieves　93.24%　of　area　under　the　curve　(AUC)　to　distinguish　HCC　patients　from　non-HCC　patients,　and　the　HCC　score　by　combing　protein　biomarkers　achieves　92.75%　of　AUC　to　distinguish　HCC　patients　from　LC　patients.　Meanwhile,　the　HCC　score　showed　high　capacity　for　screening　high　recurrence　risk　patients　after　receiving　surgical　resection,　and　appeared　to　be　an　independent　indicator　for　both　relapse-free　survival　(P　=　0.00865)　and　overall　survival　(P　=　0.000739).　Furthermore,　the　values　of　the　HCC　score　in　patients＇　longitudinal　plasma　samples　were　positively　associated　with　tumor　burden　dynamics　during　follow-up.　Conclusion:　We　have　developed　and　validated　a　novel　non-invasive　liquid　biopsy　strategy　for　HCC　diagnosis,　prognosis　and　surveillance　during　HCC　progression.