Yip1 domain family member 3Genealiases: C6orf109 · FinGER3 · KLIP1 · YIPFbeta2 · Yip5b · dJ337H4.3
Q-omics provides the consensus-scored YIPF3 profile across patient tissues and cancer cell-line models. YIPF3 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, YIPF3 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, YIPF3 RNA expression shows 19,648 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight SCLC, HNSC, and ACC as cancer lineages where YIPF3 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 YIPF3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes YIPF3 survival associations across molecular data types. YIPF3 RNA expression shows survival associations in the most cancer types (21), 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 YIPF3 RNA expression–survival associations across cancer types. High YIPF3 expression shows unfavorable associations in ACC, COAD, SARC and HNSC, but favorable associations in SCLC and OV. The SCLC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .002). Together, the overview and detailed table identify SCLC as the clearest survival context for YIPF3 RNA expression.
This table summarizes YIPF3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for YIPF3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. YIPF3 shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, KIRC, LUAD and BRCA. The HNSC box plot shows higher YIPF3 RNA expression in tumor versus normal tissue (log2 FC = +0.527, t-test p < 0.001).
This table shows molecular features associated with YIPF3 in patient tissues and cancer cell lines. In patient samples, YIPF3 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, YIPF3 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 SKIN and UPPER_AERODIGESTIVE_TRACT.
