Q-omics provides the consensus-scored SMG6 profile across patient tissues and cancer cell-line models. SMG6 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SMG6 is differentially expressed in 13, with the highest sampling consensus in KICH. Additionally, SMG6 RNA expression shows 21,011 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, KICH, and ACC as cancer lineages where SMG6 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 SMG6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SMG6 survival associations across molecular data types. SMG6 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (7) 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 SMG6 RNA expression–survival associations across cancer types. High SMG6 expression shows unfavorable associations in MESO and LUSC, but favorable associations in KIRC, SCLC, BRCA and HNSC. 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 SMG6 RNA expression.
This table summarizes SMG6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 3. The strongest signals are observed in KICH for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SMG6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SMG6 shows lower tumor expression in KICH, COAD, BRCA and BLCA and higher tumor expression in CHOL and LIHC. The KICH box plot shows higher SMG6 RNA expression in normal versus tumor tissue (log2 FC = −0.941, t-test p < 0.001).
This table shows molecular features associated with SMG6 in patient tissues and cancer cell lines. In patient samples, SMG6 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, SMG6 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 LARGE_INTESTINE.
