Q-omics provides the consensus-scored SRP14 profile across patient tissues and cancer cell-line models. SRP14 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, SRP14 is differentially expressed in 11, with the highest sampling consensus in LIHC. Additionally, SRP14 protein abundance shows 21,788 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, LIHC, and GBM as cancer lineages where SRP14 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 SRP14 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SRP14 survival associations across molecular data types. SRP14 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (3) 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 SRP14 RNA expression–survival associations across cancer types. High SRP14 expression shows unfavorable associations in HNSC, UVM and LAML, but favorable associations in KIRC, THCA and MESO. The HNSC 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 HNSC as the clearest survival context for SRP14 RNA expression.
This table summarizes SRP14 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 6. The strongest signals are observed in LIHC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SRP14. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SRP14 shows lower tumor expression in KICH, THCA and UCEC and higher tumor expression in LIHC, HNSC and CHOL. The LIHC box plot shows higher SRP14 RNA expression in tumor versus normal tissue (log2 FC = +1.131, t-test p < 0.001).
This table shows molecular features associated with SRP14 in patient tissues and cancer cell lines. In patient samples, SRP14 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, SRP14 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 BLOOD_Leukemia and BREAST.
