Q-omics provides the consensus-scored HEPHL1 profile across patient tissues and cancer cell-line models. HEPHL1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, HEPHL1 is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, HEPHL1 RNA expression shows 16,118 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UCEC, KICH, and UVM as cancer lineages where HEPHL1 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for HEPHL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HEPHL1 survival associations across molecular data types. HEPHL1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (8) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HEPHL1 RNA expression–survival associations across cancer types. High HEPHL1 expression shows unfavorable associations in UCEC, MESO, COAD, SKCM and UVM, but favorable associations in SCLC. The UCEC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify UCEC as the clearest survival context for HEPHL1 RNA expression.
This table summarizes HEPHL1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for HEPHL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HEPHL1 shows lower tumor expression in KICH, KIRC and THCA and higher tumor expression in LUSC, LUAD and LIHC. The KICH box plot shows higher HEPHL1 RNA expression in normal versus tumor tissue (log2 FC = −0.561, t-test p < 0.001).
This table shows molecular features associated with HEPHL1 in patient tissues and cancer cell lines. In patient samples, HEPHL1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, HEPHL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and UPPER_AERODIGESTIVE_TRACT.
