Q-omics provides the consensus-scored YJU2 profile across patient tissues and cancer cell-line models. YJU2 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, YJU2 is differentially expressed in 13, with the highest sampling consensus in LIHC. Additionally, YJU2 protein abundance shows 26,605 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SCLC, LIHC, and GBM as cancer lineages where YJU2 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 YJU2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes YJU2 survival associations across molecular data types. YJU2 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (5) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible YJU2 RNA expression–survival associations across cancer types. High YJU2 expression shows unfavorable associations in ACC and UCS, but favorable associations in SCLC, CESC, HNSC and KIRC. The SCLC 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 SCLC as the clearest survival context for YJU2 RNA expression.
This table summarizes YJU2 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 9. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for YJU2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. YJU2 shows lower tumor expression in LUAD, THCA and UCEC and higher tumor expression in LIHC, COAD and HNSC. The LIHC box plot shows higher YJU2 RNA expression in tumor versus normal tissue (log2 FC = +1.037, t-test p < 0.001).
This table shows molecular features associated with YJU2 in patient tissues and cancer cell lines. In patient samples, YJU2 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, YJU2 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 LARGE_INTESTINE and UPPER_AERODIGESTIVE_TRACT.
