Q-omics provides the consensus-scored HBQ1 profile across patient tissues and cancer cell-line models. HBQ1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, HBQ1 is differentially expressed in 8, with the highest sampling consensus in KIRP. Additionally, HBQ1 protein abundance shows 16,497 significant protein co-abundance associations, with the highest sampling consensus in CCRCC. Together, these results highlight ACC, KIRP, and CCRCC as cancer lineages where HBQ1 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 HBQ1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HBQ1 survival associations across molecular data types. HBQ1 RNA expression shows survival associations in the most cancer types (23), followed by mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HBQ1 RNA expression–survival associations across cancer types. High HBQ1 expression shows unfavorable associations in ACC, LUAD, KIRP and KIRC, but favorable associations in LGG and OV. The ACC 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 ACC as the clearest survival context for HBQ1 RNA expression.
This table summarizes HBQ1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRP for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for HBQ1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HBQ1 shows higher tumor expression in KIRP, UCEC, COAD, HNSC, LUAD and PRAD. The KIRP box plot shows higher HBQ1 RNA expression in tumor versus normal tissue (log2 FC = +1.448, t-test p = .002).
This table shows molecular features associated with HBQ1 in patient tissues and cancer cell lines. In patient samples, HBQ1 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, HBQ1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BONE.
