Q-omics provides the consensus-scored SSTR1 profile across patient tissues and cancer cell-line models. SSTR1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SSTR1 is differentially expressed in 16, with the highest sampling consensus in BLCA. Additionally, SSTR1 RNA expression shows 16,789 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, BLCA, and GBM as cancer lineages where SSTR1 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 SSTR1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SSTR1 survival associations across molecular data types. SSTR1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (8) 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 SSTR1 RNA expression–survival associations across cancer types. High SSTR1 expression shows unfavorable associations in LUSC and LUAD, but favorable associations in KIRC, ACC, MESO and LGG. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for SSTR1 RNA expression.
This table summarizes SSTR1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 6. The strongest signals are observed in BLCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SSTR1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SSTR1 shows lower tumor expression in BLCA, LUAD, COAD, KICH, LUSC and THCA. The BLCA box plot shows higher SSTR1 RNA expression in normal versus tumor tissue (log2 FC = −2.457, t-test p < 0.001).
This table shows molecular features associated with SSTR1 in patient tissues and cancer cell lines. In patient samples, SSTR1 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, SSTR1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and BLOOD_Leukemia.
