Number of mass spectrometry runs for each cohort and the number of identified peptides and proteins.

PURPOSE:Despite advances in colon cancer management, stage III disease lacks robust, clinically applicable prognostic biomarkers. We aimed to use proteomic profiling to provide a quantitative, tissue-based approach to improve recurrence risk stratification. EXPERIMENTAL DESIGN:We performed data-independent acquisition mass spectrometric proteomic analysis of tumor samples from three independent stage III colon cancer cohorts (n = 759). Differential protein expression between tumor and matched normal adjacent tissue was analyzed in the training cohort (cohort 1) using the limma package, and a univariate Cox model identified candidate biomarker proteins. A risk score based on the levels of six proteins (ITIH1, PPIE, LTBP1, KPNA2, IGFBP7, and CKAP4) was developed using multivariate Cox regression in the training cohort (n = 175) and validated in two external cohorts (cohort 2, n = 386; cohort 3, n = 198). Kaplan-Meier and multivariate Cox regression analyses assessed the prognostic value of the score for recurrence. RESULTS:The six-protein risk score categorized patients in the training cohort as high- or low-risk for recurrence [hazard ratio (HR) 5.7, P < 0.001], and this was validated in the two separate cohorts (cohort 2: HR 1.8, P < 0.001; cohort 3: HR 1.8, P = 0.02). Integrating the proteomic score with clinical risk factors further enhanced prognostic accuracy (P < 0.001 in all three cohorts). The combined proteomic-clinical risk score consistently identified a subgroup of patients with very low recurrence risk across cohorts. CONCLUSIONS:The validated six-protein risk score improves prognostic stratification beyond standard clinical factors in stage III colon cancer, providing a robust framework for risk-adapted clinical investigation. Prospective, treatment-stratified clinical trials are warranted to determine whether this prognostic information can inform adjuvant therapy decision-making.

List of the differentially abundant proteins across the High-risk vs Low-risk proteomic groups based on the “limma” analysis.

Missingness rate of the six proteins included in the risk score across the three cohorts.

Supplementary Figure 1: CONSORT diagram. Supplementary Figure 2: Summary of the workflow to develop the proteomic-based risk score. Supplementary Figure 3: Evaluation of different cut-off points for the risk score in the training cohort. Supplementary Figure 4: The intensities of the six proteins included in the risk score among the normal (n = 67) and tumor (n = 175) tissue samples in the Training cohort. Supplementary Figure 5: The intensities of the six proteins included in the risk score among the relapse and non-relapse groups in the A) Training cohort (Cohort 1), B) The first validation cohort (Cohort 2), and C) The second validation cohort (Cohort 3). Supplementary Figure 6: The intensities of the six proteins included in the risk score in the three cohorts among (A-C) Tumor (T)-stage; (D-F) Nodal (N)-stage; (G-I) Tumor side and (J-L) Tumor grade. Supplementary Figure 7: Association of the proteomic risk score and clinical variables with recurrence risk in Cohort 1. Supplementary Figure 8: A receiver operating characteristic curve (ROC) showing the Area Under the Curve (AUC) of different models including clinical variables with and without the risk score in the training cohort (Cohort 1). Supplementary Figure 9: Kaplan-Meier analyses showing the association of proteomic risk score in Cohort 1 with the risk of recurrence among subgroup of patients with A) MSI High, B) MSI Stable, C) Left-sided tumor, D) Right-sided tumor, E) Adjuvant Chemotherapy, F) No Adjuvant Chemotherapy, G) Mucinous subtype, H) Non-mucinous subtype. MSI: Microsatellite Instability. Supplementary Figure 10: Kaplan-Meier analyses showing the association of adjuvant chemotherapy with risk of recurrence in A) Whole training cohort (Cohort 1), B) Among patients in the high proteomic risk group and C) Among patients in the low proteomic risk group. D) A nomogram including the proteomic risk score and clinical variables. Supplementary Figure 11: Pathway enrichment analysis related to the proteins differentially abundant in high- vs low-risk proteomic group. Supplementary Figure 12: Association of the proteomic risk score and clinical variables with recurrence risk in Cohort 2. Supplementary Figure 13: A receiver operating characteristic curve (ROC) showing the area under the curve (AUC) of different models including clinical variables with and without the risk score in the first validation cohort (Cohort 2). Supplementary Figure 14: Kaplan-Meier analyses showing the association of the proteomic risk score with risk of recurrence within subgroups of patients with A) High clinical risk (T4 and/or N2) or B) Low clinical risk (T1-3/N0-1) in Cohort. 2 Supplementary Figure 15: Risk of recurrence within Cohort 2 including the subgroups. Supplementary Figure 16: Risk of recurrence in Cohort 2 by adjuvant treatment regimen and duration. Supplementary Figure 17: Kaplan-Meier analyses showing the association of adjuvant chemotherapy regimens in Cohort 2 with risk of recurrence among the different subgroups of patients . Supplementary Figure 18: Prognostic value of the proteomic risk score in Cohort 3. Supplementary Figure 19: Association of the proteomic risk score and clinical variables with recurrence risk in Cohort 3. Supplementary Figure 20: A receiver operating characteristic curve (ROC) showing the Area under the curve (AUC) of different models, including clinical variables with and without the risk score in the second validation cohort (Cohort 3). Supplementary Figure 21: Risk of recurrence among different subgroups within Cohort 3. Supplementary Figure 22: Kaplan-Meier analyses of Cohort 3 showing the association of adjuvant chemotherapy with risk of recurrence.

Esophageal adenocarcinoma (EAC) is an aggressive malignancy with poor survival rates. Current management relies on tumor stage and grade, with neoadjuvant therapy (NT) showing improved outcomes over surgery alone. However, robust biomarkers are still required to improve staging and patient selection for therapy, including NT. A training cohort of fresh frozen samples from 64 patients with EAC, not treated with NT, was analyzed by data-independent acquisition mass spectrometry. Formalin-fixed paraffin-embedded samples from an independent cohort of 188 patients with EAC treated with NT were used as validation. Unsupervised consensus clustering (CC) was performed followed by differential abundance (DA) analyses (DAA) and pathway enrichment analyses (PEA) to identify the DA proteins and enriched pathways in each cluster. Survival analyses using Cox regression were performed to assess the prognostic power of the proteomic clusters for overall survival (OS). Finally, a prognostic signature for OS was built on the training cohort using multivariable Cox regression analyses with LASSO regularization followed by StepAIC to select the most prognostic proteomic combination. The predictive power of the proteomic signature was tested using the Area Under the Receiver Operating Characteristic (AUROC) analysis and via inclusion in a nomogram with other prognostic variables. Proteomic analyses identified 8,730 and 5,214 proteins in the training and validation cohorts, respectively. The CC analyses revealed five clusters in the training cohort. Clusters 2 and 3 showed shorter OS compared to the other clusters (p=0.0025). Independent DAA and PEA revealed upregulation in extracellular matrix-related pathways in the poor prognostic clusters within both cohorts. A five-protein signature was developed in the training cohort and was associated with OS (p<0.001). This signature was independent of other prognostic variables, including N stage, T stage, grade, and age. The five-protein signature was also associated with higher odds of having positive nodes at the time of resection (Odd Ratio 6.3, p=0.009). The proteomic signature demonstrated an AUROC of 0.81 and was the most prognostic variable in a nomogram for survival risk. Finally, the proteomic signature maintained its prognostic power in the validation cohort (p=0.016) and was independent of other clinical variables, showing the highest prognostic value in the nomogram. Using two independent cohorts of EAC surgical samples, we were able to identify a prognostic proteomic-based classification and develop a proteomic-based signature that was prognostic for OS and independent of other clinical variables. This signature may be investigated further as a criterion to tailor treatment and select patients who can benefit from treatment de-escalation. AuAdel T. Aref, Daniel Bucio-Noble, Ahilya Singh, Jerresa Jabson, Myra Cheung, George Craft, Daniella Jaber, Rebecca Poulos, Erin K. Sykes, Jennifer M. Koh, Erin M. Humphries, Dylan Xavier, Peter G. Hains,V Phillip J. Robinson, Thejaani Udumanne, Sarah J. Lord, Yi Jin Liew, Jason Ross, Dan Falkenback, Jan Johansson, Duncan McLeod, David Whiteman, Reginald V. Lord, Roger R. Reddelthors. Proteomic profiling identifies and validates a prognostic survival biomarker and pathways associated with novel subtypes of esophogeal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1892.

Formalin-fixed paraffin-embedded (FFPE) tissues are suitable for proteomic and phosphoproteomic biomarker studies by data-independent acquisition mass spectrometry. The choice of the sample preparation method influences the number, intensity, and reproducibility of identifications. By comparing four deparaffinization and rehydration methods, including heptane, histolene, SubX, and xylene, we found that heptane and methanol produced the lowest coefficients of variation (CVs). Using this, five extraction methods from the literature were modified and evaluated for their performance using kidney, leg muscle, lung, and testicular rat organs. All methods performed well, except for SP3 due to insufficient tissue lysis. Heat n' Beat was the fastest and most reproducible method with the highest digestion efficiency and lowest CVs. S-Trap produced the highest peptide yield, while TFE produced the best phosphopeptide enrichment efficiency. The quantitation of FFPE-derived peptides remains an ongoing challenge with bias in UV and fluorescence assays across methods, most notably in SPEED. Functional enrichment analysis demonstrated that each method favored extracting some gene ontology cellular components over others including chromosome, cytoplasmic, cytoskeleton, endoplasmic reticulum, membrane, mitochondrion, and nucleoplasm protein groups. The outcome is a set of recommendations for choosing the most appropriate method for different settings.

Dynamin 1 mediates fission of endocytic synaptic vesicles in the brain and has two major splice variants, Dyn1xA and Dyn1xB, which are nearly identical apart from the extended C-terminal region of Dyn1xA. Despite a similar set of binding partners, only Dyn1xA is enriched at endocytic zones and accelerates vesicle fission during ultrafast endocytosis. Here, we report that Dyn1xA achieves this localization by preferentially binding to Endophilin A1 through a newly defined binding site within its long C-terminal tail extension. Endophilin A1 binds this site at higher affinity than the previously reported site, and the affinity is determined by amino acids within the Dyn1xA tail but outside the binding site. This interaction is regulated by the phosphorylation state of two serine residues specific to the Dyn1xA variant. Dyn1xA and Endophilin A1 colocalize in patches near the active zone, and mutations disrupting Endophilin A binding to the long tail cause Dyn1xA mislocalization and stalled endocytic pits on the plasma membrane during ultrafast endocytosis. Together, these data suggest that the specificity for ultrafast endocytosis is defined by the phosphorylation-regulated interaction of Endophilin A1 with the C-terminal extension of Dyn1xA.

Dynamin 1 (Dyn1) has two major splice variants, xA and xB, with unique C-terminal extensions of 20 and 7 amino acids, respectively. Of these, only Dyn1xA is enriched at endocytic zones and accelerates vesicle fission during ultrafast endocytosis. Here, we report that the long tail variant, Dyn1xA, achieves this localization by preferentially binding to Endophilin A through a newly defined Class II binding site overlapping with its extension, at a site spanning the splice boundary. Endophilin binds this site at higher affinity than the previously reported site, and this affinity is determined by amino acids outside the binding sites acting as long distance elements within the xA tail. Their interaction is regulated by the phosphorylation state of two serine residues specific to the xA variant. Dyn1xA and Endophilin colocalize in patches near the active zone of synapses. Mutations selectively disrupting Endophilin binding to the long extension cause Dyn1xA mislocalization along axons. In these mutants, endocytic pits are stalled on the plasma membrane during ultrafast endocytosis. These data suggest that the specificity for ultrafast endocytosis is defined by the phospho-regulated interaction of Endophilin A through a newly identified site of Dyn1xA's long tail.

[PDF] [Full Text] [Abstract] , October 12, 1999; 96 (21): 12068-12072. PNAS E. Korkotian and M. Segal hippocampal neurons Release of calcium from stores alters the morphology of dendritic spines in cultured [Full Text] [Abstract] , January 1, 2001; 21 (1): 186-193. J. Neurosci. M. Goldin, M. Segal and E. Avignone Hippocampal Networks Functional Plasticity Triggers Formation and Pruning of Dendritic Spines in Cultured [PDF] [Full Text] [Abstract] , August 15, 2001; 21 (16): 6115-6124. J. Neurosci. E. Korkotian and M. Segal Regulation of Dendritic Spine Motility in Cultured Hippocampal Neurons [PDF] [Full Text] [Abstract] , July 1, 2004; 87 (1): 81-91. Biophys. J. D. Holcman, Z. Schuss and E. Korkotian Calcium Dynamics in Dendritic Spines and Spine Motility [PDF] [Full Text] [Abstract] , August 30, 2006; 26 (35): 8881-8891. J. Neurosci. M. Haber, L. Zhou and K. K. Murai Cooperative astrocyte and dendritic spine dynamics at hippocampal excitatory synapses.

The pattern of neurodegeneration in Alzheimer's disease (AD) is very distinctive: neurofibrillary tangles (NFTs) composed of hyper-phosphorylated tau selectively affect pyramidal neurons of the aging association cortex that interconnect extensively through glutamate synapses on dendritic spines. In contrast, primary sensory cortices have few NFTs, even in late-stage disease. Understanding this selective vulnerability, and why advancing age is such a high risk factor for the degenerative process, may help to reveal disease etiology and provide targets for intervention. Our study has revealed age-related increase in cAMP-dependent protein kinase (PKA) phosphorylation of tau at serine 214 (pS214-tau) in monkey dorsolateral prefrontal association cortex (dlPFC), which specifically targets spine synapses and the Ca2+-storing spine apparatus. This increase is mirrored by loss of phosphodiesterase 4A from the spine apparatus, consistent with increase in cAMP-Ca2+ signaling in aging spines. Phosphorylated tau was not detected in primary visual cortex, similar to the pattern observed in AD. We also report electron microscopic evidence of previously unidentified vesicular trafficking of phosphorylated tau in normal association cortex-in axons in young dlPFC vs. in spines in aged dlPFC-consistent with the transneuronal lesion spread reported in genetic rodent models. pS214-Tau was not observed in normal aged mice, suggesting that it arises with the evolutionary expansion of corticocortical connections in primates, crossing the threshold into NFTs and degeneration in humans. Thus, the cAMP-Ca2+ signaling mechanisms, needed for flexibly modulating network strength in young association cortex, confer vulnerability to degeneration when dysregulated with advancing age.

The field of proteomics is undergoing rapid development in a number of different areas including improvements in mass spectrometric platforms, peptide identification algorithms and bioinformatics. In particular, new and/or improved approaches have established robust methods that not only allow for in-depth and accurate peptide and protein identification and modification, but also allow for sensitive measurement of relative or absolute quantitation. These methods are beginning to be applied to the area of neuroproteomics, but the central nervous system poses many specific challenges in terms of quantitative proteomics, given the large number of different neuronal cell types that are intermixed and that exhibit distinct patterns of gene and protein expression. This review highlights the recent advances that have been made in quantitative neuroproteomics, with a focus on work published over the last five years that applies emerging methods to normal brain function as well as to various neuropsychiatric disorders including schizophrenia and drug addiction as well as of neurodegenerative diseases including Parkinson's disease and Alzheimer's disease. While older methods such as two-dimensional polyacrylamide electrophoresis continued to be used, a variety of more in-depth MS-based approaches including both label (ICAT, iTRAQ, TMT, SILAC, SILAM), label-free (label-free, MRM, SWATH) and absolute quantification methods, are rapidly being applied to neurobiological investigations of normal and diseased brain tissue as well as of cerebrospinal fluid (CSF). While the biological implications of many of these studies remain to be clearly established, that there is a clear need for standardization of experimental design and data analysis, and that the analysis of protein changes in specific neuronal cell types in the central nervous system remains a serious challenge, it appears that the quality and depth of the more recent quantitative proteomics studies is beginning to shed light on a number of aspects of neuroscience that relates to normal brain function as well as of the changes in protein expression and regulation that occurs in neuropsychiatric and neurodegenerative disorders.

Protein phosphorylation and glycosylation are the most common post-translational modifications observed in biology, frequently on the same protein. Assembly protein AP180 is a synapse-specific phosphoprotein and O-linked beta-N-acetylglucosamine (O-GlcNAc) modified glycoprotein. AP180 is involved in the assembly of clathrin coated vesicles in synaptic vesicle endocytosis. Unlike other types of O-glycosylation, O-GlcNAc is nucleocytoplasmic and reversible. It was thought to be a terminal modification, that is, the O-GlcNAc was not found to be additionally modified in any way. We now show that AP180 purified from rat brain contains a phosphorylated O-GlcNAc (O-GlcNAc-P) within a highly conserved sequence. O-GlcNAc or O-GlcNAc-P, but not phosphorylation alone, was found at Thr-310. Analysis of synthetic GlcNAc-6-P produced identical fragmentation products to GlcNAc-P from AP180. Direct O-linkage of GlcNAc-P to a Thr residue was confirmed by electron transfer dissociation MS. A second AP180 tryptic peptide was also glycosyl phosphorylated, but the site of modification was not assigned. Sequence similarities suggest there may be a common motif within AP180 involving glycosyl phosphorylation and dual flanking phosphorylation sites within 4 amino acid residues. This novel type of protein glycosyl phosphorylation adds a new signaling mechanism to the regulation of neurotransmission and more complexity to the study of O-GlcNAc modification.

Amphiphysin I (amphI) is dephosphorylated by calcineurin during nerve terminal depolarization and synaptic vesicle endocytosis (SVE). Some amphI phosphorylation sites (phosphosites) have been identified with in vitro studies or phosphoproteomics screens. We used a multifaceted strategy including 32P tracking to identify all in vivo amphI phosphosites and determine their relative abundance and potential relevance to SVE. AmphI was extracted from 32P-labeled synaptosomes, phosphopeptides were isolated from proteolytic digests using TiO2 chromatography, and mass spectrometry revealed 13 sites: serines 250, 252, 262, 268, 272, 276, 285, 293, 496, 514, 539, and 626 and Thr-310. These were distributed into two clusters around the proline-rich domain and the C-terminal Src homology 3 domain. Hierarchical phosphorylation of Ser-262 preceded phosphorylation of Ser-268, -272, -276, and -285. Off-line HPLC separation and two-dimensional tryptic mapping of 32P-labeled amphI revealed that Thr-310, Ser-293, Ser-285, Ser-272, Ser-276, and Ser-268 contained the highest 32P incorporation and were the most stimulus-sensitive. Individually Thr-310 and Ser-293 were the most abundant phosphosites, incorporating 16 and 23% of the 32P. The multiple phosphopeptides containing Ser-268, Ser-276, Ser-272, and Ser-285 had 27% of the 32P. Evidence for a role for at least one proline-directed protein kinase and one non-proline-directed kinase was obtained. Four phosphosites predicted for non-proline-directed kinases, Ser-626, -250, -252, and -539, contained low amounts of 32P and were not depolarization-responsive. At least one alternatively spliced amphI isoform was identified in synaptosomes as being constitutively phosphorylated because it did not incorporate 32P during the 1-h labeling period. Multiple phosphosites from amphI-co-migrating synaptosomal proteins were also identified, including SGIP (Src homology 3 domain growth factor receptor-bound 2 (Grb2)-like (endophilin)-interacting protein 1), AAK1, eps15R, MAP6, alpha/beta-adducin, and HCN1. The results reveal two sets of amphI phosphosites that are either dynamically turning over or constitutively phosphorylated in nerve terminals and improve understanding of the role of individual amphI sites or phosphosite clusters in synaptic SVE.

Dynamin I (dynI) is phosphorylated in synaptosomes at Ser774 and Ser778 by cyclin-dependent kinase 5 to regulate recruitment of syndapin I for synaptic vesicle endocytosis, and in PC12 cells on Ser857. Hierarchical phosphorylation of Ser774 precedes phosphorylation of Ser778. In contrast, Thr780 phosphorylation by cdk5 has been reported as the sole site (Tomizawa, K., Sunada, S., Lu, Y. F., Oda, Y., Kinuta, M., Ohshima, T., Saito, T., Wei, F. Y., Matsushita, M., Li, S. T., Tsutsui, K., Hisanaga, S. I., Mikoshiba, K., Takei, K., and Matsui, H. (2003) J. Cell Biol. 163, 813–824). To resolve the discrepancy and to better understand the biological roles of dynI phosphorylation, we undertook a systematic identification of all phosphorylation sites in rat brain nerve terminal dynI. Using phosphoamino acid analysis, exclusively phospho-serine residues were found. Thr780 phosphorylation was not detectable. Mutation of Ser774, Ser778, and Thr780 confirmed that Thr780 phosphorylation is restricted to in vitro conditions. Mass spectrometry of 32P-labeled phosphopeptides separated by two-dimensional mapping revealed seven in vivo phosphorylation sites: Ser774, Ser778, Ser822, Ser851, Ser857, Ser512, and Ser347. Quantification of 32P radiation in each phosphopeptide showed that Ser774 and Ser778 were the major sites (up to 69% of the total), followed by Ser851 and Ser857 (12%), and Ser853 (2%). Phosphorylation of Ser851 and Ser857 was restricted to the long tail splice variant dynIxa and was not hierarchical. Co-purified, 32P-labeled dynIII was phosphorylated at Ser759, Ser763, and Ser853. Ser853 is homologous to Ser851 in dynIxa. The results identify all major and several minor phosphorylation sites in dynI and provide the first measure of their relative abundance and relative responses to depolarization. The multiple phospho-sites suggest subtle regulation of synaptic vesicle endocytosis by new protein kinases and new protein-protein interactions. The homologous dynI and dynIII phosphorylation indicates a high mechanistic similarity. The results suggest a unique role for the long splice variants of dynI and dynIII in nerve terminals.

Proteomics is the analysis of the protein complement of the genome. The technique involves extracting proteins from the tissue being examined; separating the proteins using methods such as two-dimensional gel electrophoresis and then identifying the proteins by mass spectrometry. This paper describes the application of proteomics to incised wounds of the rat to determine if this technology could be applied to the important forensic issue of determining the age of wounds. Experimental incised skin wounds were inflicted on rats 5, 15, 30 and 60 minutes, 3, 6, 12 and 24 hours and 2, 5, 7 and 12 days before euthanasia. Each wound was excised and frozen at - 80°C; protein extracts were prepared and subjected to two-dimensional polyacrylamide gel electrophoresis over the range pH 3 to pH 10. Protein spots were identified using Matrix-assisted Laser Desorption/Ionisation Time-of-Flight (MALDI-TOF) mass spectrometry. A number of proteins were identified in skin wounds. After wounding the most prominent change was in the level of haemoglobin, which was elevated in wounds five minutes old and remained elevated for three hours, falling to near control levels after 12 hours. This pilot study has illustrated the feasibility for proteomics to be applied to determining wound age.

Brief periods of myocardial ischemia prior to timely reperfusion result in prolonged, yet reversible, contractile dysfunction of the myocardium, or "myocardial stunning". It has been hypothesized that the delayed recovery of contractile function in stunned myocardium reflects damage to one or a few key sarcomeric proteins. However, damage to such proteins does not explain observed physiological alterations to myocardial oxygen consumption and ATP requirements observed following myocardial stunning, and therefore the impact of alterations to additional functional groups is unresolved. We utilized two-dimensional gel electrophoresis and mass spectrometry to identify changes to the protein profiles in whole cell, cytosolic- and myofilament-enriched subcellular fractions from isolated, perfused rabbit hearts following 15 min or 60 min low-flow (1 mL/min) ischemia. Comparative gel analysis revealed 53 protein spot differences (> 1.5-fold difference in visible abundance) in reperfused myocardium. The majority of changes were observed to proteins from four functional groups: (i) the sarcomere and cytoskeleton, notably myosin light chain-2 and troponin C; (ii) redox regulation, in particular several components of the NADH ubiquinone oxidoreductase complex; (iii) energy metabolism, encompassing creatine kinase; and (iv) the stress response. Protein differences appeared to be the result of isoelectric point shifts most probably resulting from chemical modifications, and molecular mass shifts resulting from proteolytic or physical fragmentation. This is consistent with our hypothesis that the time course for the onset of injury associated with myocardial stunning is too brief to be mediated by large changes to gene/protein expression, but rather that more subtle, rapid and potentially transient changes are occurring to the proteome. The physical manifestation of stunned myocardium is therefore the likely result of the summed functional impairment resulting from these multiple changes, rather than a result of damage to a single key protein.

Proteome analysis was conducted on the grain of 2 closely related soft biscuit-making wheats (Bowie and Rosella cultivars) differing in processing quality. Comparisons between these wheat cultivars were carried out on total wholemeal proteins, extracts with enriched starch granule proteins, and extracts enriched with gliadin storage proteins, with the intention of characterising, identifying, and cataloguing cultivar-specific proteins that could be used for segregation purposes. Initially, 2-dimensional gel electrophoresis was carried out on total wholemeal proteins using a broad range pH 3–10 immobilised pH gradient for the first dimension. Further screening was carried out using a combination of mid to narrow range immobilised pH gradients, including pH 4–7, 5.5–6.7, 5–8, 6–9, and 6–11. Best cultivar-specific protein fractionation was provided by the pH 5–8 range. Altogether, 4 unique cultivar-specific protein spots were excised from the pH 5–8 gels and identified by means of peptide mass fingerprinting, tandem mass spectrometry, or N-terminal sequencing. Starch granule protein extracts were prepared and fractionated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. A western blot was performed and probed with an anti-puroindoline-a antibody. Further to this, extracts enriched in gliadin storage proteins were isolated using 70% ethanol and analysed by 2-dimensional gel electrophoresis. The resulting gliadin protein maps showed 18 unique cultivar-specific gliadins. They were excised from the pH 6–9 gels and submitted for N-terminal amino acid sequencing. Overall, this study identified 23 proteins that could be used to distinguish between these closely related cultivars and may provide information on the molecular basis for the differences in processing exhibited by these wheats. The findings reported also contribute to a longer term objective of developing a broad and comprehensive knowledge base of commercial wheats, in regard to protein composition and their inherent processing qualities.