Q-omics provides the consensus-scored SRP9 profile across patient tissues and cancer cell-line models. SRP9 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SRP9 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, SRP9 protein abundance shows 23,678 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight ACC, and HNSC as cancer lineages where SRP9 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 SRP9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SRP9 survival associations across molecular data types. SRP9 RNA expression shows survival associations in the most cancer types (24), 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 SRP9 RNA expression–survival associations across cancer types. High SRP9 expression shows unfavorable associations in ACC, UVM, LIHC, LUAD, KIRP and HNSC. 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 SRP9 RNA expression.
This table summarizes SRP9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SRP9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SRP9 shows lower tumor expression in KICH and higher tumor expression in HNSC, BLCA, LIHC, LUAD and BRCA. The HNSC box plot shows higher SRP9 RNA expression in tumor versus normal tissue (log2 FC = +0.775, t-test p < 0.001).
This table shows molecular features associated with SRP9 in patient tissues and cancer cell lines. In patient samples, SRP9 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, SRP9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and BLOOD_Leukemia.
