Q-omics provides the consensus-scored SSTR2 profile across patient tissues and cancer cell-line models. SSTR2 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, SSTR2 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, SSTR2 RNA expression shows 17,952 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRP, KICH, and UVM as cancer lineages where SSTR2 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 SSTR2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SSTR2 survival associations across molecular data types. SSTR2 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SSTR2 RNA expression–survival associations across cancer types. High SSTR2 expression shows unfavorable associations in KIRP, UVM, MESO and THCA, but favorable associations in SKCM and LGG. The KIRP 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 KIRP as the clearest survival context for SSTR2 RNA expression.
This table summarizes SSTR2 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 1. The strongest signals are observed in KIRP for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SSTR2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SSTR2 shows lower tumor expression in KICH, KIRP and COAD and higher tumor expression in HNSC, BRCA and LUAD. The KICH box plot shows higher SSTR2 RNA expression in normal versus tumor tissue (log2 FC = −2.255, t-test p < 0.001).
This table shows molecular features associated with SSTR2 in patient tissues and cancer cell lines. In patient samples, SSTR2 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, SSTR2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
