Q-omics provides the consensus-scored SHF profile across patient tissues and cancer cell-line models. SHF expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SHF is differentially expressed in 13, with the highest sampling consensus in BLCA. Additionally, SHF RNA expression shows 19,071 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, BLCA, and GBM as cancer lineages where SHF 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 SHF — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SHF survival associations across molecular data types. SHF RNA expression shows survival associations in the most cancer types (29), followed by mutation status (1) and 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 SHF RNA expression–survival associations across cancer types. High SHF expression shows unfavorable associations in ACC, READ, LUSC and UCS, but favorable associations in LGG and THCA. 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 SHF RNA expression.
This table summarizes SHF tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 7. The strongest signals are observed in BLCA for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for SHF. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SHF shows lower tumor expression in BLCA, BRCA and UCEC and higher tumor expression in THCA, LUAD and COAD. The BLCA box plot shows higher SHF RNA expression in normal versus tumor tissue (log2 FC = −1.121, t-test p < 0.001).
This table shows molecular features associated with SHF in patient tissues and cancer cell lines. In patient samples, SHF 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, SHF 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 OVARY and BLOOD_Leukemia.
