signal regulatory protein alphaGenealiases: BIT · CD172A · MFR · MYD-1 · MYD1 · P84
Q-omics provides the consensus-scored SIRPA profile across patient tissues and cancer cell-line models. SIRPA expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, SIRPA is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, SIRPA protein abundance shows 26,972 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight MESO, HNSC, and GBM as cancer lineages where SIRPA 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 SIRPA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SIRPA survival associations across molecular data types. SIRPA RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SIRPA RNA expression–survival associations across cancer types. High SIRPA expression shows unfavorable associations in LUSC, SKCM, BLCA, LIHC and OV, but favorable associations in MESO. The MESO Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify MESO as the clearest survival context for SIRPA RNA expression.
This table summarizes SIRPA 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 CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SIRPA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SIRPA shows lower tumor expression in KICH, LUAD and BRCA and higher tumor expression in HNSC, KIRC and KIRP. The HNSC box plot shows higher SIRPA RNA expression in tumor versus normal tissue (log2 FC = +2.086, t-test p < 0.001).
This table shows molecular features associated with SIRPA in patient tissues and cancer cell lines. In patient samples, SIRPA shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, SIRPA 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 SOFT_TISSUE and BLOOD_Leukemia.
