Q-omics provides the consensus-scored HBE1 profile across patient tissues and cancer cell-line models. HBE1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, HBE1 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, HBE1 protein abundance shows 8,983 significant protein co-abundance associations, with the highest sampling consensus in CCRCC. Together, these results highlight STAD, KICH, and CCRCC as cancer lineages where HBE1 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 HBE1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HBE1 survival associations across molecular data types. HBE1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (8) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HBE1 RNA expression–survival associations across cancer types. High HBE1 expression shows unfavorable associations in STAD, UVM and DLBC, but favorable associations in ESCA, UCS and SKCM. The STAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify STAD as the clearest survival context for HBE1 RNA expression.
This table summarizes HBE1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 3. The strongest signals are observed in KICH for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for HBE1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HBE1 shows lower tumor expression in KICH, UCEC and BRCA and higher tumor expression in HNSC, COAD and LIHC. The KICH box plot shows higher HBE1 RNA expression in normal versus tumor tissue (log2 FC = −0.480, t-test p < 0.001).
This table shows molecular features associated with HBE1 in patient tissues and cancer cell lines. In patient samples, HBE1 shows the broadest associations at the RNA and protein expression levels, with CCRCC recurring as the lineage with the largest associated feature set. In cancer cell lines, HBE1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LUNG_NSCLC_LUAD.
