small proline rich protein 2C (pseudogene)Genealiases: []
Q-omics provides the consensus-scored SPRR2C profile across patient tissues and cancer cell-line models. SPRR2C expression is associated with patient survival in 12 of 34 cancer types, with the highest sampling consensus in READ. Among the 18 cancer types available for tumor–normal comparison, SPRR2C is differentially expressed in 1, with the highest sampling consensus in LUSC. Additionally, SPRR2C RNA expression shows 7,987 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight READ, LUSC, and ESCA as cancer lineages where SPRR2C 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 SPRR2C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPRR2C survival associations across molecular data types. SPRR2C RNA expression shows survival associations in the most cancer types (12), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPRR2C RNA expression–survival associations across cancer types. High SPRR2C expression shows unfavorable associations in READ, THCA, PAAD, SKCM and KIRC, but favorable associations in CESC. The READ 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 READ as the clearest survival context for SPRR2C RNA expression.
This table summarizes SPRR2C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 1. The strongest signals are observed in LUSC for RNA.
This table ranks reproducible tumor–normal expression differences for SPRR2C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPRR2C shows higher tumor expression in LUSC. The LUSC box plot shows higher SPRR2C RNA expression in tumor versus normal tissue (log2 FC = +2.878, t-test p < 0.001).
This table shows molecular features associated with SPRR2C in patient tissues and cancer cell lines. In patient samples, SPRR2C shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, SPRR2C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and NCI60_ALL.
