Q-omics provides the consensus-scored AHSP profile across patient tissues and cancer cell-line models. AHSP expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, AHSP is differentially expressed in 8, with the highest sampling consensus in LUAD. Additionally, AHSP protein abundance shows 15,300 significant protein co-abundance associations, with the highest sampling consensus in CCRCC. Together, these results highlight COAD, LUAD, and CCRCC as cancer lineages where AHSP 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 AHSP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AHSP survival associations across molecular data types. AHSP RNA expression shows survival associations in the most cancer types (17), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AHSP RNA expression–survival associations across cancer types. High AHSP expression shows unfavorable associations in COAD, ACC, THCA and READ, but favorable associations in PCPG and KIRC. The COAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .005). Together, the overview and detailed table identify COAD as the clearest survival context for AHSP RNA expression.
This table summarizes AHSP 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 LUAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for AHSP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AHSP shows lower tumor expression in LUAD, BRCA, LUSC, KICH and UCEC and higher tumor expression in KIRC. The LUAD box plot shows higher AHSP RNA expression in normal versus tumor tissue (log2 FC = −0.377, t-test p < 0.001).
This table shows molecular features associated with AHSP in patient tissues and cancer cell lines. In patient samples, AHSP 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, AHSP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
