Q-omics provides the consensus-scored SCP2D1 profile across patient tissues and cancer cell-line models. SCP2D1 expression is associated with patient survival in 10 of 34 cancer types, with the highest sampling consensus in KIRC. Additionally, SCP2D1 protein abundance shows 9,159 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight KIRC, and BRCA as cancer lineages where SCP2D1 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 SCP2D1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SCP2D1 survival associations across molecular data types. SCP2D1 RNA expression shows survival associations in the most cancer types (10), followed by mutation status (7) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SCP2D1 RNA expression–survival associations across cancer types. High SCP2D1 expression shows unfavorable associations in KIRC, SKCM, MESO, UCEC, THYM and UCS. The KIRC 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 KIRC as the clearest survival context for SCP2D1 RNA expression.
This table shows molecular features associated with SCP2D1 in patient tissues and cancer cell lines. In patient samples, SCP2D1 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, SCP2D1 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 LIVER and OESOPHAGUS.
