Q-omics provides the consensus-scored PLAC9 profile across patient tissues and cancer cell-line models. PLAC9 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in OV. Among the 18 cancer types available for tumor–normal comparison, PLAC9 is differentially expressed in 16, with the highest sampling consensus in BLCA. Additionally, PLAC9 protein abundance shows 30,131 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight OV, BLCA, and LUAD as cancer lineages where PLAC9 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 PLAC9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PLAC9 survival associations across molecular data types. PLAC9 RNA expression shows survival associations in the most cancer types (25), 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 PLAC9 RNA expression–survival associations across cancer types. High PLAC9 expression shows unfavorable associations in OV, UVM, BLCA, ACC and SCLC, but favorable associations in KIRC. The OV Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify OV as the clearest survival context for PLAC9 RNA expression.
This table summarizes PLAC9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 7. The strongest signals are observed in BLCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PLAC9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PLAC9 shows lower tumor expression in BLCA, COAD, LUAD, KICH, THCA and HNSC. The BLCA box plot shows higher PLAC9 RNA expression in normal versus tumor tissue (log2 FC = −4.200, t-test p < 0.001).
This table shows molecular features associated with PLAC9 in patient tissues and cancer cell lines. In patient samples, PLAC9 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, PLAC9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
