Functional Variant & Mutation Proteomics Service

Q: Do I need to provide genomic sequencing (WES / RNA‑seq) data with my samples?

Providing matched WES or RNA‑seq data (in VCF, BAM, or FASTA format) is strongly recommended. This enables our bioinformatics team to construct a sample‑specific customized database containing your exact missense mutations, insertions/deletions, or fusion breakpoints. Without genomic data, we can still perform open‑search or de novo variant algorithms, but a sample‑matched custom database substantially improves identification sensitivity and reduces false discovery rates.

Q: Can you detect oncogenic fusion proteins and chimeric breakpoint peptides?

Yes. For known or suspected gene fusions (e.g., EML4‑ALK, BCR‑ABL1, TMPRSS2‑ERG), we model the in silico translated junction peptide sequences into our search database. LC‑MS/MS identifies tryptic peptides spanning the exact chimeric fusion breakpoint, providing definitive biochemical confirmation of fusion oncoprotein expression and stoichiometry.

Q: What is the difference between testing single clones versus multiple independent mutant clones?

Single‑cell CRISPR cloning can introduce clonal drift, parental heterogeneity, or off‑target edits unrelated to the intended mutation. We strongly recommend a multi‑clone concordance design—profiling wild‑type parental cells alongside 3+ independently derived mutant clones. Proteomic changes that occur consistently across all mutant clones are confident, bona fide consequences of the variant, whereas clone‑specific outliers are filtered out.

Q: What sample submission format is required?

Samples should be submitted as flash‑frozen cell pellets (washed 2× with cold PBS), fresh‑frozen tissue pieces (≥20–50 mg), or non‑denatured cell lysates for AP‑MS/TPP assays. Please provide project metadata including: (1) target gene and mutation annotation (e.g., KRAS p.G12D, EGFR p.T790M), (2) matched genomic VCF/FASTA sequence files if available, (3) cell/tissue model, (4) clone/replicate mapping, and (5) requested analytical layers (proteogenomics, TPP, AP‑MS, 4D‑phosphoproteomics).

Missense Mutations · VUS Validation · Kinase Gatekeeper Resistance · Fusion Oncogenes · TPP Stability

Genomic sequencing identifies thousands of somatic mutations and variants of uncertain significance (VUS), but DNA sequencing alone cannot determine whether a mutant protein is stably expressed, misfolded, degraded, or functionally rewired.

Creative Proteomics provides an integrated Functional Variant & Mutation Proteomics Service, translating genomics into protein-level reality. Using customized sample-matched proteogenomic databases, thermal proteome profiling (TPP/CETSA), AP-MS interactome mapping, and deep DIA quantification, we directly verify mutant peptide expression, conformational stability shifts, and downstream oncogenic signaling networks.

Customized proteogenomic FASTA searching: Integrate matched WES/RNA-seq variant calls to directly identify and quantify single-amino-acid variant (SAAV) peptides
Protein stability & degradation assays: Measure variant melting temperature shifts (ΔT_m) via Thermal Proteome Profiling (TPP-MS) to detect misfolding vs. stabilization
Interactome remodeling (AP-MS / Proximity Labeling): Map loss of tumor suppressor complexes or gain of aberrant oncogenic binding partners
Secondary resistance deconvolution: Benchmark baseline oncogenes against drug-resistant gatekeeper mutants (e.g., EGFR C797S, KRAS G12C/D, BTK C481S)
Rigorous synthetic peptide validation: Heavy isotope-labeled peptide spiking to confirm low-abundance mutant spectral identifications with zero false discovery

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The Genomics-to-Protein Gap in Mutation Analysis

Next-generation sequencing (NGS) has cataloged millions of somatic mutations across human cancers and rare diseases. However, predicting biological causality from genomic coordinates remains a major bottleneck in translational medicine and oncology drug development.

Over 40% of non-synonymous single-nucleotide variants (missense SNVs) destabilize protein tertiary structure, triggering rapid chaperone-mediated ubiquitination and proteasomal degradation. In these cases, high mRNA levels correlate with complete protein-level loss of function. Conversely, oncogenic gain-of-function variants (e.g., KRAS G12D, PIK3CA H1047R) and drug-resistant secondary mutations (e.g., EGFR T790M/C797S) often alter catalytic velocity, rewrite kinase cascades, or remodel protein-protein interactions without changing baseline mRNA abundance.

Because mutant-specific commercial antibodies exist for fewer than 1% of known clinical variants, high-resolution LC-MS/MS mass spectrometry is the only unbiased technology capable of directly detecting mutated peptide sequences, quantifying variant protein stability, and mapping downstream functional rewiring.

Content Guide

Four Analytical Pillars
Variant Classes & Models
Proteogenomics Workflow
Study Design Architectures
Platform Decision Guide
Sample Requirements
Deliverables & Data Outputs

Four Methodological Pillars for Functional Mutation Proteomics

Depending on whether your objective is verifying mutant peptide expression, measuring biophysical stability, mapping interactome remodeling, or profiling downstream signaling networks, we deploy four specialized proteomic modalities:

1. Proteogenomic SAAV Detection

Customized FASTA databases generated from matched WES/RNA-seq identify exact Single Amino Acid Variant (SAAV) peptides, novel splice junctions, and gene fusion breakpoint peptides with rigorous 1% spectral FDR.

2. Thermal Proteome Profiling (TPP-MS)

Cellular Thermal Shift Assay (CETSA) coupled with multiplexed TMT/DIA mass spectrometry determines variant-induced thermal melting shifts (ΔT_m), distinguishing misfolded, destabilized mutants from stabilized active conformations.

3. Interactome Remodeling (AP-MS)

Affinity purification (FLAG/HA/BioID) comparing WT versus mutant proteins identifies loss of physiological tumor suppressor complexes (e.g., p53-MDM2, PTEN) or gain of aberrant oncogenic binding partners.

4. Global Signaling & PTM Rewiring

Deep DIA proteomics paired with 4D-phosphoproteomics quantifies whole-proteome pathway alterations, constitutive kinase phosphorylation (MAPK, PI3K/Akt, STAT), and compensatory survival pathways triggered by the variant.

Variant Classes, Biological Questions, and Analytical Strategies

Variant Category	Representative Biological Models	Primary Analytical Question	Recommended Strategy
Clinical Variants of Uncertain Significance (VUS)	Germline or somatic missense variants in BRCA1/2, TP53, PTEN, mismatch repair genes.	Does the missense change cause protein destabilization, loss of expression, or aberrant turnover?	Deep DIA quantification + TPP stability assay (ΔT_m measurement).
Oncogenic Hotspot Gain-of-Function	KRAS (G12C/D/V, G13D, Q61H), BRAF (V600E), PIK3CA (E545K, H1047R), IDH1 (R132H).	Which downstream kinase cascades and metabolic pathways are constitutively activated?	Paired 4D-Phosphoproteomics + Global DIA pathway enrichment (KSEA).
Secondary Kinase Gatekeeper Resistance	EGFR (T790M, C797S), BTK (C481S), ALK (G1202R), BCR-ABL (T315I).	How does the secondary mutation prevent inhibitor binding or recruit alternative signaling hubs?	CETSA-MS drug-binding competition + AP-MS interactome mapping.
Chromosomal Translocations & Fusion Proteins	EML4-ALK, BCR-ABL1, TMPRSS2-ERG, FGFR3-TACC3, SS18-SSX.	Is the chimeric junction peptide expressed, and what novel multiprotein complexes does it recruit?	Custom fusion breakpoint FASTA searching + Co-IP MS interactome analysis.
Truncating & Frameshift Indels	Premature termination codons (PTCs), alternative translation reinitiation, exon skipping.	Does residual truncated protein escape nonsense-mediated decay (NMD) and persist?	Sequence-mapped peptide-level coverage analysis (N-terminal vs. C-terminal recovery).

Customized Proteogenomics Database Construction & Verification Rules

Detecting mutant peptides from shotgun mass spectrometry data requires rigorous bioinformatic controls to prevent inflated false-discovery rates caused by database inflation:

Proteogenomics variant database construction

Sample-Matched Database Customization: We extract non-synonymous SNVs, insertions/deletions, and RNA-seq junction reads from your matched genomic data, appending variant sequences directly to the canonical UniProt reference proteome.
Two-Pass Search & 1% Spectral FDR: To control the search space, MS/MS spectra are searched using target-decoy approaches with strict 1% false discovery rate applied independently at both peptide-spectrum match (PSM) and variant-peptide levels.
Distinguishing Homologous Isoforms: Bioinformatic filters distinguish true somatic mutant peptides from common single-nucleotide polymorphisms (dbSNP) and homologous pseudogene products.
Synthetic Heavy Peptide (AQUA) Validation: For high-priority biomarker candidates or clinical decisions, we synthesize stable isotope-labeled heavy reference peptides to co-elute and match MS/MS fragmentation patterns exactly, providing 100% conclusive analytical verification.

Study Design Architectures for Mutation Projects

Experimental Design	Core Biological Comparison	What This Design Establishes
Isogenic WT vs. Mutant Knock-In	Parental isogenic cell line compared to CRISPR-engineered single-amino-acid mutant clone(s).	Isolates the phenotypic effect of the single variant from genetic background variations.
Multi-Clone Concordance Design	Wild-type parental vs. 3+ independently derived mutant clones targeting the same codon.	Separates genuine mutation-driven proteomic shifts from clonal drift and culture artifacts.
Inhibitor Sensitivity ± Drug Challenge	WT vs. Gatekeeper Mutant cells treated with escalating doses of targeted kinase inhibitors.	Measures resistance index, persistent downstream phosphorylation, and bypass pathway activation.
Thermal Melting Curve Series (TPP)	Intact cells or lysates heated across a 10-temperature gradient (37°C to 67°C) ± ligand.	Calculates exact melting temperature (ΔT_m) shifts induced by mutation or drug binding.

Functional Variant Proteomics Analytical Platform Decision Guide

Match your variant class, sample type, and biological question with the optimal acquisition strategy and mass spectrometry platform.

Study Objective & Scenario	Recommended Strategy	Primary MS Platform	Technical Rationale & Deliverables
Proteome-Wide Impact & Pathway Rewiring (Isogenic Knock-in / Cancer Cell Lines)	Discovery DIA Quantitative Proteomics	Orbitrap Astral / Exploris 480 / timsTOF Pro 2	Single-shot depth (>6,500–8,500+ proteins), CV < 15%, deep coverage of metabolic pathways, transcription factors, and compensatory proteins.
Conformational Stability & Misfolding (VUS Characterization / Ligand Binding)	Thermal Proteome Profiling (TPP-MS / CETSA)	Orbitrap Exploris 480 (TMT-Multiplexed / DIA-TPP)	10-point thermal melting curves for thousands of proteins; precise melting point (ΔT_m) shifts quantify variant biophysical stability.
Interactome Remodeling & Complex Assembly (AP-MS / Flag / HA / TurboID Proximity)	High-Resolution Affinity Purification MS	Orbitrap Exploris 480 / timsTOF Pro 2	Label-free quantification (LFQ) with SAINTexpress statistical filtering to distinguish true mutant-specific interactors from background contaminants.
Constitutive Kinase & Signaling Cascades (Oncogenic Hotspots / Gatekeeper Mutants)	4D Phosphoproteomics (Ti-IMAC / Fe-NTA Enrichment)	timsTOF Pro 2 (TIMS-DIA) / Orbitrap Exploris 480	Captures >15,000–25,000+ phosphosites; Kinase-Substrate Enrichment Analysis (KSEA) maps constitutive downstream pathway hyperactivation.
Low-Abundance SAAV Peptide Verification (Biomarker Validation / Clinical Cohorts)	Targeted PRM / 4D-PRM with Heavy Standards	Orbitrap PRM / Triple Quadrupole (TSQ Altis / QTRAP 6500+)	Absolute quantification of mutant versus wild-type peptide ratios using synthetic AQUA heavy peptides with zero false-discovery risk.

Sample Submission Requirements

Sample Category	Recommended Input	Minimum Feasibility	Harvesting & Shipping Guidelines
Standard Cell Pellets (Global DIA)	1–5 × 10⁶ cells (20–50 μg protein)	2 × 10⁵ cells (≥2 μg protein)	Wash 2× with ice-cold PBS; aspirate completely; flash-freeze pellet in liquid N₂. Ship on dry ice (-80°C).
Fresh-Frozen Tissues / Tumors	20–50 mg wet weight	5 mg wet weight	Dissect rapidly; snap-freeze immediately in liquid N₂; avoid repeated freeze-thaw cycles. Ship on dry ice.
TPP / CETSA Thermal Assays	1–2 × 10⁷ live intact cells or clarified lysate	5 × 10⁶ cells	Harvest live cells with non-enzymatic dissociation; perform thermal gradient heating per SOP before lysis. Ship on dry ice.
Affinity Purification (AP-MS)	1–2 × 10⁷ cells expressing tagged bait	5 × 10⁶ cells	Lyse in non-denaturing buffer (e.g., 0.5% NP-40/Tris-HCl) to preserve native protein complexes. Ship on dry ice.
Pre-Extracted Lysates	20–50 μL at 1–2 mg/mL	5 μg total protein	SDS/RapiGest buffer; BCA quantified; provide matched genomic VCF or sequence files. Ship on dry ice.

Deliverables and Decision-Ready Outputs

Quantitative matrices, spectral proof, and functional pathway interpretation

PCA visualization of wild-type versus mutant proteomic states

Sample-level PCA/UMAP evaluates whether global proteome profiles cluster strictly by genotype (WT vs. Mutant) across biological replicates.

Thermal melting curve shift showing variant protein stability

Thermal melting curves from TPP-MS quantify exact melting temperature shifts (ΔT_m), establishing biophysical stability or misfolding.

Volcano plot of mutant versus wild-type differential protein abundance

Differential volcano plots prioritize significant downstream effector proteins, compensatory chaperones, and altered metabolic enzymes.

AP-MS interactome network comparing WT and mutant binding partners

Interactome network diagrams highlight lost physiological complexes and newly acquired aberrant protein-protein interactions.

Discuss Your Project

Variant Peptide Evidence Tables

Annotated MS/MS spectra, precursor mass accuracy, retention time alignment, and variant peptide sequence confirmation.

Quality Assessment Summary

Digestion completeness metrics, proteome depth, pooled QC CV distributions, and clone concordance assessment.

Differential Expression & TPP Curves

Statistical testing (limma FDR ≤ 0.05), fold-change ranking, and fitted Boltzmann thermal denaturation melting curves.

Pathway & Interactome Mapping

GSEA functional pathway enrichment, KSEA kinase activity networks, and SAINTexpress filtered interactome tables.

Comprehensive Final Report

Publication-ready figures, auditable methods documentation, and candidate shortlists for targeted PRM validation.

Functional Variant Proteomics Frequently Asked Questions

Do I need to provide genomic sequencing (WES / RNA-seq) data with my samples?

Providing matched WES or RNA-seq data (in VCF, BAM, or FASTA format) is strongly recommended. This enables our bioinformatics team to construct a sample-specific customized database containing your exact missense mutations, insertions/deletions, or fusion breakpoints. Without genomic data, we can still perform open-search or de novo variant algorithms, but a sample-matched custom database substantially improves identification sensitivity and reduces false discovery rates.

Can mass spectrometry distinguish wild-type from single-amino-acid mutant peptides?

Yes, provided the amino acid substitution produces a detectable mass shift (which occurs for all substitutions except isobaric Leucine/Isoleucine swaps) and the mutated tryptic peptide falls within typical mass spectrometry m/z detection windows (7–30 amino acids). The substitution alters both the precursor mass and the b/y fragment ion series, yielding unique tandem MS/MS spectra that definitively distinguish the mutant peptide from the wild-type counterpart.

How does Thermal Proteome Profiling (TPP / CETSA) evaluate variant stability?

Thermal Proteome Profiling leverages the principle that natively folded proteins precipitate upon thermal denaturation at characteristic melting temperatures (T_m). Destabilizing missense mutations cause premature unfolding and precipitation at lower temperatures (ΔT_m < 0), whereas stabilizing mutations or drug binding shift the denaturation curve to higher temperatures (ΔT_m > 0). By measuring soluble protein across a 10-temperature gradient, TPP-MS quantifies biophysical stability shifts for the mutant protein and thousands of background proteins in intact cells.

How do you control for false-positive mutant peptide identifications?

Database inflation from appending thousands of theoretical variants can increase false-positive rates. We enforce strict two-tier quality control: (1) target-decoy searching with 1% FDR applied separately to mutant peptide candidates; (2) manual spectral curation verifying continuous fragment ion series across the substituted residue; and (3) optional validation via parallel reaction monitoring (PRM) spiked with synthetic heavy isotope-labeled AQUA peptide standards.

Can you detect oncogenic fusion proteins and chimeric breakpoint peptides?

Yes. For known or suspected gene fusions (e.g., EML4-ALK, BCR-ABL1, TMPRSS2-ERG), we model the in silico translated junction peptide sequences into our search database. LC-MS/MS identifies tryptic peptides spanning the exact chimeric fusion breakpoint, providing definitive biochemical confirmation of fusion oncoprotein expression and stoichiometry.

What is the difference between testing single clones versus multiple independent mutant clones?

Single-cell CRISPR cloning can introduce clonal drift, parental heterogeneity, or off-target edits unrelated to the intended mutation. We strongly recommend a multi-clone concordance design—profiling wild-type parental cells alongside 3+ independently derived mutant clones. Proteomic changes that occur consistently across all mutant clones are confident, bona fide consequences of the variant, whereas clone-specific outliers are filtered out.

How does AP-MS identify mutant-specific interactome remodeling?

We perform affinity purification (using FLAG, HA, or endogenous antibodies) from cells expressing WT vs. Mutant proteins under non-denaturing lysis conditions. Following LC-MS/MS, we apply the SAINTexpress (Significance Analysis of INTeractome) algorithm to filter non-specific background contaminants and statistically score high-confidence protein-protein interactions that are selectively lost or gained by the mutant.

What sample submission format is required?

Samples should be submitted as flash-frozen cell pellets (washed 2× with cold PBS), fresh-frozen tissue pieces (≥20–50 mg), or non-denatured cell lysates for AP-MS/TPP assays. Please provide project metadata including: (1) target gene and mutation annotation (e.g., KRAS p.G12D, EGFR p.T790M), (2) matched genomic VCF/FASTA sequence files if available, (3) cell/tissue model, (4) clone/replicate mapping, and (5) requested analytical layers (proteogenomics, TPP, AP-MS, 4D-phosphoproteomics).

* For Research Use Only. Not for use in the treatment or diagnosis of disease.

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Please submit a detailed description of your project. We will provide you with a customized study plan to meet your requests. You can also send us an email to for inquiries.