Q-omics provides the consensus-scored HBG1 profile across patient tissues and cancer cell-line models. HBG1 expression is associated with patient survival in 16 of 34 cancer types, with the highest sampling consensus in OV. Among the 18 cancer types available for tumor–normal comparison, HBG1 is differentially expressed in 5, with the highest sampling consensus in BRCA. Additionally, HBG1 protein abundance shows 6,634 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight OV, BRCA, and GBM as cancer lineages where HBG1 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 HBG1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HBG1 survival associations across molecular data types. HBG1 RNA expression shows survival associations in the most cancer types (16), followed by mutation status (5) 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 HBG1 RNA expression–survival associations across cancer types. High HBG1 expression shows unfavorable associations in OV, STAD, BLCA, DLBC, KIRP and UVM. The OV Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .008). Together, the overview and detailed table identify OV as the clearest survival context for HBG1 RNA expression.
This table summarizes HBG1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5, while mass-spec protein shows differences in 3. The strongest signals are observed in BRCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for HBG1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HBG1 shows lower tumor expression in BRCA, LUSC, LUAD and LIHC and higher tumor expression in KIRC. The BRCA box plot shows higher HBG1 RNA expression in normal versus tumor tissue (log2 FC = −0.042, t-test p < 0.001).
This table shows molecular features associated with HBG1 in patient tissues and cancer cell lines. In patient samples, HBG1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, HBG1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and KIDNEY.
