F-box and leucine rich repeat protein 16Genealiases: C16orf22 · Fbl16 · c380A1.1
Q-omics provides the consensus-scored FBXL16 profile across patient tissues and cancer cell-line models. FBXL16 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, FBXL16 is differentially expressed in 11, with the highest sampling consensus in COAD. Additionally, FBXL16 RNA expression shows 18,640 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UCEC, COAD, and GBM as cancer lineages where FBXL16 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 FBXL16 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FBXL16 survival associations across molecular data types. FBXL16 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (2) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FBXL16 RNA expression–survival associations across cancer types. High FBXL16 expression shows unfavorable associations in UCEC and UCS, but favorable associations in KIRC, PAAD, MESO and KICH. The UCEC 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 UCEC as the clearest survival context for FBXL16 RNA expression.
This table summarizes FBXL16 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 2. The strongest signals are observed in COAD for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for FBXL16. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FBXL16 shows lower tumor expression in HNSC, THCA and KICH and higher tumor expression in COAD, KIRC and BRCA. The COAD box plot shows higher FBXL16 RNA expression in tumor versus normal tissue (log2 FC = +1.892, t-test p < 0.001).
This table shows molecular features associated with FBXL16 in patient tissues and cancer cell lines. In patient samples, FBXL16 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, FBXL16 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Leukemia.
