Q-omics provides the consensus-scored ARPP19 profile across patient tissues and cancer cell-line models. ARPP19 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ARPP19 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, ARPP19 protein abundance shows 23,406 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where ARPP19 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 ARPP19 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARPP19 survival associations across molecular data types. ARPP19 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (2) 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 ARPP19 RNA expression–survival associations across cancer types. High ARPP19 expression shows unfavorable associations in UVM, ACC, HNSC, PAAD and ESCA, but favorable associations in KIRC. The KIRC 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 KIRC as the clearest survival context for ARPP19 RNA expression.
This table summarizes ARPP19 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 10. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ARPP19. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARPP19 shows lower tumor expression in THCA, KICH and LUAD and higher tumor expression in HNSC, LIHC and CHOL. The HNSC box plot shows higher ARPP19 RNA expression in tumor versus normal tissue (log2 FC = +0.933, t-test p < 0.001).
This table shows molecular features associated with ARPP19 in patient tissues and cancer cell lines. In patient samples, ARPP19 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, ARPP19 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
