Q-omics provides the consensus-scored SST profile across patient tissues and cancer cell-line models. SST expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, SST is differentially expressed in 5, with the highest sampling consensus in COAD. Additionally, SST protein abundance shows 15,046 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, COAD, and GBM as cancer lineages where SST 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 SST — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SST survival associations across molecular data types. SST RNA expression shows survival associations in the most cancer types (18), followed by mutation status (1) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SST RNA expression–survival associations across cancer types. High SST expression shows unfavorable associations in SKCM, UCEC and UVM, but favorable associations in HNSC, KICH and KIRC. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .002). Together, the overview and detailed table identify HNSC as the clearest survival context for SST RNA expression.
This table summarizes SST tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5, while mass-spec protein shows differences in 2. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SST. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SST shows lower tumor expression in COAD, STAD, READ, KICH and PRAD. The COAD box plot shows higher SST RNA expression in normal versus tumor tissue (log2 FC = −5.368, t-test p < 0.001).
This table shows molecular features associated with SST in patient tissues and cancer cell lines. In patient samples, SST 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, SST RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
