suppressor of cancer cell invasionGenealiases: C9orf126 · NET40
Q-omics provides the consensus-scored SCAI profile across patient tissues and cancer cell-line models. SCAI expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, SCAI is differentially expressed in 11, with the highest sampling consensus in LUAD. Additionally, SCAI protein abundance shows 22,521 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, LUAD, and GBM as cancer lineages where SCAI 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 SCAI — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SCAI survival associations across molecular data types. SCAI RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6) 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 SCAI RNA expression–survival associations across cancer types. High SCAI expression shows unfavorable associations in UVM, but favorable associations in HNSC, KIRC, READ, LGG and THYM. The HNSC 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 HNSC as the clearest survival context for SCAI RNA expression.
This table summarizes SCAI 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 4. The strongest signals are observed in LUAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SCAI. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SCAI shows lower tumor expression in LUAD, LUSC, KIRC and KICH and higher tumor expression in LIHC and CHOL. The LUAD box plot shows higher SCAI RNA expression in normal versus tumor tissue (log2 FC = −1.430, t-test p < 0.001).
This table shows molecular features associated with SCAI in patient tissues and cancer cell lines. In patient samples, SCAI 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, SCAI RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and BLOOD_Leukemia.
