small G protein signaling modulator 3Genealiases: CIP85 · MAP · MRT84 · RABGAP5 · RUSC3 · RUTBC3
Q-omics provides the consensus-scored SGSM3 profile across patient tissues and cancer cell-line models. SGSM3 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SGSM3 is differentially expressed in 6, with the highest sampling consensus in THCA. Additionally, SGSM3 protein abundance shows 21,698 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight ACC, THCA, and BRCA as cancer lineages where SGSM3 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 SGSM3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SGSM3 survival associations across molecular data types. SGSM3 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (9) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SGSM3 RNA expression–survival associations across cancer types. High SGSM3 expression shows unfavorable associations in ACC, KIRC and LIHC, but favorable associations in READ, BLCA and UCEC. 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 SGSM3 RNA expression.
This table summarizes SGSM3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6, while mass-spec protein shows differences in 7. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SGSM3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SGSM3 shows lower tumor expression in THCA and KIRP and higher tumor expression in LIHC, CHOL, UCEC and PRAD. The THCA box plot shows higher SGSM3 RNA expression in normal versus tumor tissue (log2 FC = −0.691, t-test p < 0.001).
This table shows molecular features associated with SGSM3 in patient tissues and cancer cell lines. In patient samples, SGSM3 shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, SGSM3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
