SKA2

associated omics data
Gene

Q-omics provides the consensus-scored SKA2 profile across patient tissues and cancer cell-line models. SKA2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, SKA2 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, SKA2 RNA expression shows 19,394 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRP, HNSC, and ACC as cancer lineages where SKA2 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.

Survival associations

This table summarizes SKA2 survival associations across molecular data types. SKA2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
SKA2 data typeSurvival analysisLineage consensusLineage of highest sampling consensus
RNAKaplan–Meier25KIRP (133)view →
Protein (mass-spec)Kaplan–Meier5PDAC (51)view →
MutationKaplan–Meier2LIHC (6)view →
This table ranks reproducible SKA2 RNA expression–survival associations across cancer types. High SKA2 expression shows unfavorable associations in KIRP, ACC, KICH, HNSC and LIHC, but favorable associations in UCS. The KIRP 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 KIRP as the clearest survival context for SKA2 RNA expression.
LineageMeasureSplitStageAUC1
high
AUC2
low
pSampling consensus
KIRPOSMedianAll0.8150.942<.001133view →
ACCOSMedianAll0.4460.765<.001132view →
KICHOSQuartileII,III,IV0.4461.000<.00158view →
HNSCOSTertileIII,IV0.5280.700.00456view →
LIHCDFSQuartileAll0.4400.674<.00142view →
UCSDFSMedianAll0.5540.300.01424view →
Pink = unfavorable, green = favorable. all 25 lineages →

SKA2-KIRP (OS)

Kaplan–Meier survival curve for SKA2 RNA expression in KIRP: high vs low expression groups.

Explore this curve interactively →

Tumor vs Normal expression

This table summarizes SKA2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and LSCC for protein.
SKA2 data typeExpression analysisLineage consensusLineage of highest sampling consensus
RNABox plot14HNSC (12)view →
Protein (mass-spec)Box plot3LSCC (7)view →
This table ranks reproducible tumor–normal expression differences for SKA2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SKA2 shows lower tumor expression in KICH and THCA and higher tumor expression in HNSC, LIHC, LUAD and BRCA. The HNSC box plot shows higher SKA2 RNA expression in tumor versus normal tissue (log2 FC = +1.218, t-test p < 0.001).
LineageGenderStageFold-changepSampling consensus
HNSCMaleIII,IV+1.218<.00112view →
KICHFemaleAll−1.413<.00110view →
LIHCFemaleII,III,IV+1.045<.0019view →
LUADMaleAll+0.646<.0019view →
THCAAllAll−0.335<.0019view →
BRCAAllIII,IV+1.071<.0016view →
Green = repressed in tumor. all 14 lineages →

SKA2-HNSC

Tumor-vs-normal expression box plot for SKA2 in HNSC.

Explore this plot interactively →

Cross-omics associations

This table shows molecular features associated with SKA2 in patient tissues and cancer cell lines. In patient samples, SKA2 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, SKA2 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 SOFT_TISSUE and BLOOD_Leukemia.
Associated data typeStrength (# associated data)Lineage of highest associated data
RNA
RNA19,394ACC (9517)view →
Protein (mass-spec)18,048LSCC (6787)view →
Protein (mass-spec)
Protein (mass-spec)11,946LSCC (5383)view →
RNA7,350LSCC (5699)view →
Mutation
RNA882UCEC (876)view →
Protein (RPPA)6UCEC (6)view →
Associated data typeStrength (# associated data)Lineage of highest associated data
CRISPR
CRISPR1,721PANCREAS (193)view →
shRNA1,112SOFT_TISSUE (116)view →
RNA
RNA8,929BLOOD_Leukemia (3843)view →
Function (RNA)4,071BLOOD_Leukemia (1389)view →
shRNA
shRNA1,509BREAST (152)view →
RNA1,467PANCREAS (168)view →
Protein (mass-spec)
RNA181BLOOD_Leukemia (95)view →
Function (RNA)127BLOOD_Leukemia (64)view →