Q-omics provides the consensus-scored SIPA1 profile across patient tissues and cancer cell-line models. SIPA1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SIPA1 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, SIPA1 protein abundance shows 28,960 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, KIRC, and LSCC as cancer lineages where SIPA1 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 SIPA1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SIPA1 survival associations across molecular data types. SIPA1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) 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 SIPA1 RNA expression–survival associations across cancer types. High SIPA1 expression shows unfavorable associations in ACC, UVM, LGG and LAML, but favorable associations in HNSC and SKCM. The ACC 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 ACC as the clearest survival context for SIPA1 RNA expression.
This table summarizes SIPA1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SIPA1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SIPA1 shows higher tumor expression in KIRC, HNSC, THCA, LIHC, BLCA and STAD. The KIRC box plot shows higher SIPA1 RNA expression in tumor versus normal tissue (log2 FC = +1.160, t-test p < 0.001).
This table shows molecular features associated with SIPA1 in patient tissues and cancer cell lines. In patient samples, SIPA1 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, SIPA1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
