Q-omics provides the consensus-scored SRPX2 profile across patient tissues and cancer cell-line models. SRPX2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, SRPX2 is differentially expressed in 11, with the highest sampling consensus in COAD. Additionally, SRPX2 protein abundance shows 22,235 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRP, COAD, and PDAC as cancer lineages where SRPX2 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 SRPX2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SRPX2 survival associations across molecular data types. SRPX2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SRPX2 RNA expression–survival associations across cancer types. High SRPX2 expression shows unfavorable associations in KIRP, KIRC, STAD, LGG and ACC, but favorable associations in DLBC. The KIRP 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 KIRP as the clearest survival context for SRPX2 RNA expression.
This table summarizes SRPX2 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 7. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SRPX2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SRPX2 shows lower tumor expression in KICH and higher tumor expression in COAD, LUAD, READ, LUSC and CHOL. The COAD box plot shows higher SRPX2 RNA expression in tumor versus normal tissue (log2 FC = +4.810, t-test p < 0.001).
This table shows molecular features associated with SRPX2 in patient tissues and cancer cell lines. In patient samples, SRPX2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, SRPX2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BONE and LARGE_INTESTINE.
