Q-omics provides the consensus-scored ZFYVE19 profile across patient tissues and cancer cell-line models. ZFYVE19 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, ZFYVE19 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, ZFYVE19 RNA expression shows 19,337 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KICH, KIRC, and ACC as cancer lineages where ZFYVE19 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 ZFYVE19 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZFYVE19 survival associations across molecular data types. ZFYVE19 RNA expression shows survival associations in the most cancer types (24), 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 ZFYVE19 RNA expression–survival associations across cancer types. High ZFYVE19 expression shows unfavorable associations in KICH, COAD, UCS, ACC and LIHC, but favorable associations in KIRC. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify KICH as the clearest survival context for ZFYVE19 RNA expression.
This table summarizes ZFYVE19 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for ZFYVE19. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZFYVE19 shows higher tumor expression in KIRC, THCA, BLCA, LUAD, LIHC and HNSC. The KIRC box plot shows higher ZFYVE19 RNA expression in tumor versus normal tissue (log2 FC = +0.680, t-test p < 0.001).
This table shows molecular features associated with ZFYVE19 in patient tissues and cancer cell lines. In patient samples, ZFYVE19 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, ZFYVE19 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and UPPER_AERODIGESTIVE_TRACT.
