Q-omics provides the consensus-scored SMG1P2 profile across patient tissues and cancer cell-line models. SMG1P2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SMG1P2 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, SMG1P2 RNA expression shows 19,437 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where SMG1P2 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 SMG1P2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SMG1P2 survival associations across molecular data types. SMG1P2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SMG1P2 RNA expression–survival associations across cancer types. High SMG1P2 expression shows unfavorable associations in ACC, KICH, MESO and KIRP, but favorable associations in DLBC and UCS. 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 SMG1P2 RNA expression.
This table summarizes SMG1P2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for SMG1P2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SMG1P2 shows lower tumor expression in KICH and UCEC and higher tumor expression in HNSC, KIRC, LIHC and CHOL. The HNSC box plot shows higher SMG1P2 RNA expression in tumor versus normal tissue (log2 FC = +0.308, t-test p < 0.001).
This table shows molecular features associated with SMG1P2 in patient tissues and cancer cell lines. In patient samples, SMG1P2 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, SMG1P2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in OVARY.
