sperm antigen with calponin homology and coiled-coil domains 1 likeGenealiases: CYTSA · GBBB2 · OBLFC1 · TBHS · TBHS1
Q-omics provides the consensus-scored SPECC1L profile across patient tissues and cancer cell-line models. SPECC1L expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SPECC1L is differentially expressed in 11, with the highest sampling consensus in COAD. Additionally, SPECC1L RNA expression shows 20,070 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and COAD as cancer lineages where SPECC1L 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 SPECC1L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPECC1L survival associations across molecular data types. SPECC1L RNA expression shows survival associations in the most cancer types (26), followed by mutation status (10) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPECC1L RNA expression–survival associations across cancer types. High SPECC1L expression shows unfavorable associations in ACC, HNSC, KICH and LUSC, but favorable associations in THYM and KIRC. The ACC 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 ACC as the clearest survival context for SPECC1L RNA expression.
This table summarizes SPECC1L 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 COAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SPECC1L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPECC1L shows lower tumor expression in COAD, THCA and LUAD and higher tumor expression in HNSC, LIHC and CHOL. The COAD box plot shows higher SPECC1L RNA expression in normal versus tumor tissue (log2 FC = −0.985, t-test p < 0.001).
This table shows molecular features associated with SPECC1L in patient tissues and cancer cell lines. In patient samples, SPECC1L 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, SPECC1L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BLOOD_Leukemia.
