The C17orf64 antibody targets the C17orf64 protein, a 562-amino-acid protein with unknown function. Key properties include:
Immunogen: Recombinant human protein (e.g., residues 111–236) or synthetic peptides conjugated to keyhole limpet hemocyanin (KLH) .
Reactivity: Primarily human; some cross-reactivity with mouse and rat .
Conjugation: Unconjugated for most applications, though biotinylated variants exist .
C17orf64 antibodies are validated for multiple techniques:
C17orf64 antibodies undergo rigorous validation to ensure specificity:
Prestige Antibodies (Sigma-Aldrich): Tested on 44 normal tissues and 20 cancer types to confirm cross-reactivity and signal reproducibility .
Human Protein Atlas: Immunohistochemistry data for tissue-specific expression, including testis and prostate cancer .
Orthogonal RNAseq and Recombinant Protein Arrays: Confirmed absence of off-target binding via protein array validation .
A landmark study identified a novel MSI2-C17orf64 fusion in a refractory gastroesophageal tumor. This fusion implicates C17orf64 in tumor progression, drug resistance, and metastasis, suggesting its potential as a therapeutic target .
C17orf64 is an uncharacterized protein encoded by a gene mapping to human chromosome 17. While its specific function remains largely unknown, its location on chromosome 17 is notable as this chromosome contains crucial tumor suppressor genes including p53 and BRCA1 . Chromosome 17 makes up over 2.5% of the human genome with approximately 81 million bases encoding over 1,200 genes . Research interest in C17orf64 stems partly from its genomic neighborhood, which is associated with multiple diseases including various cancers, neurofibromatosis, Alexander disease, Birt-Hogg-Dube syndrome, and Canavan disease . Recent methylomic studies have identified C17orf64 as one of the top-performing loci in ovarian cancer analyses, suggesting potential roles in cancer development or progression .
Multiple types of validated C17orf64 antibodies are available for research applications:
Most commercially available C17orf64 antibodies are produced in rabbit as polyclonal antibodies, which provide good sensitivity for detecting this relatively uncharacterized protein across multiple applications . Researchers should note that antibody validation levels vary between suppliers, with some products like the Prestige Antibodies® line undergoing enhanced validation through recombinant expression and orthogonal RNAseq verification .
C17orf64 antibodies are typically generated using synthetic peptide fragments derived from the human C17orf64 sequence. For example, some antibodies utilize KLH conjugated synthetic peptides derived from the human C17orf64 sequence , while others target specific epitopes such as the sequence "LHSNISGMKERLSNMQTPGQGSPLPGQPRSQDHVKKDSLRELSQKPKLKRKRIKEAPETPETE" . The choice of immunogen significantly impacts the specificity and applications of the resulting antibody, with carefully selected regions producing antibodies with lower cross-reactivity to other proteins .
High-quality C17orf64 antibodies undergo multiple validation steps:
Protein Array Screening: Testing against large panels (e.g., 364 human recombinant protein fragments) to confirm specificity
Tissue Microarray Analysis: Validation through IHC using arrays of multiple normal human tissues (typically 44) and cancer tissues (approximately 20 common types)
Enhanced Validation: Advanced verification through:
When selecting a C17orf64 antibody, researchers should review available validation data and prioritize antibodies validated through multiple methodologies. The Human Protein Atlas project provides extensive validation data for some C17orf64 antibodies, allowing researchers to examine actual immunostaining patterns across tissues and subcellular compartments .
Selection criteria should include:
Application compatibility: Verify the antibody has been validated for your specific application (WB, IHC, IF, etc.) with documented dilution ranges
Species reactivity: Confirm cross-reactivity with your model organism (human, mouse, rat)
Epitope location: Consider whether the recognized epitope might be masked in your experimental system
Validation depth: Prioritize antibodies with comprehensive validation data, especially those tested across numerous tissues
Buffer compatibility: Ensure the antibody formulation is compatible with your experimental buffers and fixation methods
For specific applications, recommended antibody dilutions typically range from 1:300-5000 for Western blotting, 1:200-400 for immunohistochemistry on paraffin sections, and 1:50-200 for immunofluorescence on paraffin sections .
For Immunohistochemistry (Paraffin Sections):
Fix samples with paraformaldehyde
Embed in paraffin
Perform antigen retrieval by boiling in sodium citrate buffer (pH 6.0) for 15 minutes
Block endogenous peroxidase activity with 3% hydrogen peroxide for 30 minutes
Apply blocking buffer (normal goat serum) at 37°C for 20 minutes
Incubate with primary antibody overnight at 4°C (typical dilution 1:200-1:1000)
Apply conjugated secondary antibody followed by DAB staining
For Western Blotting:
Use standard protein extraction methods appropriate for your tissue/cell type
Determine optimal antibody concentration (typically 0.04-0.4 μg/mL or dilutions of 1:300-1:5000)
Include appropriate blocking reagents to minimize background
Optimize incubation time and temperature based on signal strength and specificity
Issue | Possible Cause | Recommended Solution |
---|---|---|
Weak or no signal | Insufficient antigen retrieval | Optimize antigen retrieval methods (time, buffer composition, pH) |
Low antibody concentration | Increase antibody concentration or incubation time | |
Protein degradation | Use fresh samples and add protease inhibitors | |
High background | Insufficient blocking | Extend blocking step or use alternative blocking reagent |
Excessive antibody concentration | Further dilute primary antibody | |
Non-specific binding | Try alternative buffer conditions or add blocking proteins | |
Unexpected bands/staining | Cross-reactivity | Validate with additional antibodies targeting different epitopes |
Post-translational modifications | Consider using modification-specific antibodies if relevant |
When optimizing protocols, remember that storage conditions significantly impact antibody performance. Most C17orf64 antibodies should be stored at -20°C, and repeated freeze/thaw cycles should be avoided .
C17orf64 has emerged as a significant locus in methylomic analyses of ovarian cancers . Researchers combine C17orf64 antibodies with methylation-specific techniques to:
Correlate protein expression with methylation status: By comparing immunohistochemical staining patterns with methylation results obtained through bisulfite sequencing or methylation arrays
Identify potential biomarkers: C17orf64 was identified among eight top-performing loci (along with c6orf174, IRX2, TUBB6, PTPRN, OTX2, LOC200726, and NEUROD1) in ovarian cancer studies
Develop diagnostic assays: Researchers have developed SMART-MSP (Sensitive Melting Analysis after Real Time-Methylation Specific PCR) assays for C17orf64 methylation with clinical diagnostic potential
The integration of protein-level detection via antibodies with epigenetic analyses provides a comprehensive understanding of C17orf64's potential role in cancer development and progression.
For comprehensive methylomic analysis involving C17orf64:
Bisulfite Treatment: DNA samples undergo bisulfite conversion before analysis
Illumina's Infinium Human MethylationEPIC BeadChip Analysis: Processed through functional normalization algorithms implemented in packages like minfi from Bioconductor
SMART-MSP Assays: Performed using:
Bisulfite-treated DNA
Evagreen dye
Specific primers (300 nM forward and reverse)
Fluorescein reference dye
Platinum Taq® DNA Polymerase
Thermocycling conditions: 5 minutes at 95°C, followed by 50 cycles of 95°C for 30 seconds, assay-specific annealing temperature for 30 seconds, and 72°C for 30 seconds
While C17orf64's specific role remains to be fully characterized, its location on chromosome 17 places it in proximity to genes associated with multiple diseases:
Cancer connections: Chromosome 17 contains tumor suppressors p53 and BRCA1, both directly involved in DNA repair. Malfunction or loss of p53 expression is associated with malignant cell growth and Li-Fraumeni syndrome, while BRCA1 is linked to early-onset breast cancer and predisposition to cancers of the ovary, colon, prostate, and fallopian tubes
Neurological disorders: Chromosome 17 is linked to neurofibromatosis (characterized by neural and epidermal lesions with dysregulated Schwann cell growth), Alexander disease, and Canavan disease
Other genetic conditions: Associations with Birt-Hogg-Dube syndrome have been reported
Research utilizing C17orf64 antibodies in these disease contexts helps establish whether this uncharacterized protein has functional relationships with these better-characterized disease pathways.
For SMART-MSP (methylation) analysis:
Analyze results using software like CFX Manager v3.1
Use regression to obtain the mean Cq for each sample
Calculate Percent Methylated Reference (PMR) values using the formula:
PMR = [# methylated copies marker] / [# copies β-Actin = 1000] × 100%
Generate receiver-operating characteristic (ROC) analysis and area under the curve (AUC) values
Perform statistical analyses using R statistical software suite with linear regression models
For Immunohistochemistry quantification:
Score staining intensity (typically on a 0-3 scale)
Assess percentage of positive cells
Calculate H-score or other composite metrics depending on research question
Compare across tissues or conditions using appropriate statistical tests
When interpreting combined antibody and methylation data for C17orf64:
Establish baseline expression: Use normal tissue controls to establish baseline expression patterns across different cell types and tissues
Correlate with methylation status: Determine whether protein expression inversely correlates with promoter methylation (the typical pattern for gene silencing)
Consider context-specific factors: Evaluate whether expression patterns differ between tissue types or disease states
Validate findings with multiple methods: Confirm key results using orthogonal techniques (e.g., immunohistochemistry, Western blotting, qRT-PCR)
Interpret based on minimum detection thresholds: Consider assay sensitivity limitations, such as the established minimum specificity/sensitivity for assay development (e.g., EAF of 0.2% or 1 in 500 as determined using linear regression of the standard curve)
The integration of protein-level detection with methylation analysis provides insights into the regulatory mechanisms potentially affecting C17orf64 expression in normal and disease states.