SCY1 like pseudokinase 2Genealiases: AMC4 · AMCNACC · CVAK104
Q-omics provides the consensus-scored SCYL2 profile across patient tissues and cancer cell-line models. SCYL2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, SCYL2 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, SCYL2 protein abundance shows 22,551 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight LGG, HNSC, and LSCC as cancer lineages where SCYL2 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 SCYL2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SCYL2 survival associations across molecular data types. SCYL2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SCYL2 RNA expression–survival associations across cancer types. High SCYL2 expression shows unfavorable associations in LGG, MESO, ACC, BLCA and LIHC, but favorable associations in KIRC. The LGG 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 LGG as the clearest survival context for SCYL2 RNA expression.
This table summarizes SCYL2 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 8. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SCYL2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SCYL2 shows lower tumor expression in KIRC and higher tumor expression in HNSC, BLCA, LIHC, BRCA and LUSC. The HNSC box plot shows higher SCYL2 RNA expression in tumor versus normal tissue (log2 FC = +0.728, t-test p < 0.001).
This table shows molecular features associated with SCYL2 in patient tissues and cancer cell lines. In patient samples, SCYL2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, SCYL2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in LIVER and UPPER_AERODIGESTIVE_TRACT.
