Mangalaparthi, Kiran K.

Tumor-associated antigens (TAAs) are non-mutated antigenic peptides expressed in cancer tissue at abnormally high levels but in normal tissue either at negligible levels, during only particular developmental stages, or in a tissue-restricted manner. The shared nature of TAAs across patients makes them attractive targets for off-the-shelf immunotherapies. However, no studies have comprehensively surveyed the TAA potential of all possible wild-type peptides originating from cancer-associated genes. In this study of 16 cancer tissue types and 39 normal tissue types, we analyzed the expression profiles of protein-coding genes to identify those with aberrantly high RNA levels across multiple solid tumor types and low RNA levels across all normal tissue types examined. We then developed a score to quantify tumor specificity of gene expression. Compared to previously reported TAA genes, those we identified exhibited substantially greater tumor specificity. Seven of these genes demonstrated consistently elevated expression in at least five tumor types and minimal expression across all non-immune-privileged normal tissues. To assess Human Leukocyte Antigen (HLA) class I presentation potential of the multi-cancer-associated genes, we computationally predicted the binding affinities between the most common class I HLA alleles and all possible wild-type TAA epitopes of 8–11 amino acids arising from those genes. We then applied rigorous filtering criteria to prioritize the most promising multi-cancer TAA peptide candidates and evaluated their HLA binding and cell-surface presentation using T2 and immunopeptidome analysis. Our results highlight new potential targets for multi-cancer immunotherapies.

ABSTRACT Interferon-γ (IFNγ) signaling is prominent in inflammatory CNS microenvironments across many neurological disorders, but the neuronal peptides presented on HLA class I under these conditions and their functional consequences for CD8 + T cells remain incompletely defined. Here we combine human iPSC-derived human neural aggregates (HNAs), HLA class I immunoprecipitation coupled to LC-MS/MS immunopeptidomics, and microfluidic co-culture assays to map IFNγ-induced neuronal antigen presentation and test antigen-specific cytotoxicity. IFNγ stimulation induced robust HLA class I expression in HNAs and enabled recovery of a canonical 8-12-mer class I ligandome enriched for 9-mers. Neuron-restricted expression of a synapsin-driven polyepitope cassette yielded presentation of defined neoantigen 9-mer peptides on donor HLA class I molecules and, in the presence of IFNγ, elicited activation of autologous antigen-specific CD8 + T cells and consequent antigen-dependent neurite injury. Across four donors, comparative immunopeptidomics identified large IFNγ-unique neural peptide repertoires distinct from matched fibroblasts and revealed a consistent enrichment of predicted high-affinity binders on HLA-B allotypes. Finally, β2-microglobulin deletion ablated peptide recovery, and neuron-restricted β2-microglobulin reconstitution enabled identification of neuron-derived peptides, including peptides derived from neurofilament light (NEFL) that were shared across donors and presented on multiple HLA allotypes. Together, these data provide an integrated platform for neuronal autoantigen discovery and functional validation and support a model in which IFNγ-driven neuronal HLA class I presentation creates an HLA-B-weighted epitope landscape that can be recognized by autoreactive cytotoxic CD8 + T cells.

Abstract Introduction: The intricate cellular structure is a constantly evolving environment where cells interact, communicate, and adapt to their surroundings. The fate, role, and actions of each cell are shaped by its specific location within the tissue. Therefore, studying the spatial proteome is crucial for gaining a deeper understanding of physiological or pathological processes. With significant advancements in microscopy and mass spectrometry, it has become feasible to explore the cellular proteome at low or even single cell numbers. However, spatial proteomics is an evolving field with scope for newer sample preparation and data analysis techniques. Our objective was to develop a sample preparation workflow for analyzing proteome from limited cells extracted from formalin fixed paraffin embedded (FFPE) tissue using laser capture microdissection (LCM). Methods: One hundred cells from the FFPE normal colon tissue were extracted by LCM and collected into an AFA-compatible 96-well plate. Decrosslinking was performed at 900C for 50 minutes followed by lysis in a buffer composed of 100 mM triethylammonium bicarbonate and 0.1% n-dodecyl-β-D-maltoside using adaptive focused acoustic (AFA) energetics in scanning mode for 5 minutes. After lysis, the proteins were digested using Trypsin/Lys-C mix using AFA energetics for 1 hour. The resulting peptides were acidified with trifluoroacetic acid and analyzed on a timsTOF Ultra 2 mass spectrometer coupled to a nanoElute 2 liquid chromatography system using a 15 cm (75 μm) IonOpticks column, in DDA-PASEF mode for a total run time of 34 minutes. The data were searched against the UniProt Human Reviewed protein database using MSFragger. Results: We utilized AFA energetics to extract and digest proteins from a limited number of cells isolated from FFPE tissue using LCM. This experiment was conducted with technical replicates to ensure accuracy and reliability. A total of 3,723 proteins were identified across the three replicates, with replicate 1 identifying 3,895 proteins, replicate 2 identifying 3,754 proteins, and replicate 3 identifying 3,519 proteins. In total, we identified 21,005 peptides, with replicate 1 identifying 22,896 peptides, replicate 2 identifying 22,377 peptides, and replicate 3 identifying 17,741 peptides from 100 colon cells. Notably, we observed a 70% overlap in the proteins identified across the three replicates, which highlights the reproducibility of the approach. Conclusion: The entire sample preparation process, after cell collection, was completed within a concise four-hour timeframe, demonstrating the efficiency of this methodology for analyzing protein profiles from small cell populations. Further, this approach is highly adaptable to automation and high-throughput applications. Its adaptability and scalability make it a promising strategy for spatial proteomics applications. Citation Format: Dong-Gi Mun, Kiran Mangalaparthi, Daigo Gunji, Amy J. French, Raghavendra Pasupuleti, Cristine Charlesworth, Sameer Vasantgadkar, DEB BHATTACHARYYA, Akhilesh Pandey. An AFA assisted workflow for mass-spectrometry based proteomics of FFPE samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7657.

Abstract Multiple myeloma (MM) is an incurable plasma cell neoplasm characterized by diverse and complex genetic abnormalities, including translocations of immunoglobulin (Ig) genes and a hyperdiploid (HRD) karyotype. Much of our current understanding of MM genetics, epigenetics, pathogenesis and response/resistance to myeloma directed therapies originated from studies on human MM-derived cell lines (HMCL). In this study, we conducted an integrated multi-omics analysis in five hyperdiploid cell lines established from serial samples from a single relapsed/refractory hyperdiploid MM patient, enabling detailed characterization of the genetic landscape and molecular alterations through disease progression.

ABSTRACT Imaging mass spectrometry has made significant advancements in recent years owing to its ability to study the spatial localization and abundance of proteins, peptides, lipids, glycans, metabolites, and drugs. In this study, we employed an imaging mass spectrometry‐based workflow called MALDI‐IHC, which uses antibodies conjugated with photocleavable mass‐tags, to investigate the detection of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) along with pan‐cytokeratin in formalin‐fixed paraffin‐embedded (FFPE) sections from cases with breast cancer. The expression of ER, PR, and HER2 was consistent with the clinical diagnosis based on conventional immunohistochemistry, lacking signal in triple‐negative cases and concordant signals in the cases that were classified as ER+/PR+/HER2+, ER+/PR+/HER2−, and ER−/PR−/HER2+ groups, respectively. In addition, the potential utility of a seconday antibody‐based MALDI‐IHC approach for HER2 expression was evaluated. In agreement with immunohistochemistry results, HER2 expression co‐localized within tumor regions in a HER2+ breast cancer case, while no expression was observed in a HER2− case. Collectively, these results highlight the potential of imaging mass spectrometry‐based MALDI‐IHC workflow for multiplexed detection of proteins in clinically relevant tissue sections.

Key Points Increased protein expression of tissue inhibitor of metalloproteinase-3, glypican 6, synuclein γ , apolipoprotein A-4, and Ecto-5′-nucleotidase was observed in old adults compared with young adults. In old adults, overexpressed proteins were enriched in mitochondrial processes while under expressed proteins enriched in RNA metabolism. Validated differentially expressed proteins were not significantly correlated with kidney pathology after adjusting for age. Background Kidney aging is characterized by a loss of glomeruli, predominantly in the superficial cortex, with a resultant decline in GFR and an increased risk of various kidney-related diseases. The early molecular alterations in glomeruli associated with the aging process are not well studied. Methods We combined laser capture microdissection and mass spectrometry–based unbiased proteomic analysis of nonsclerosed, nonischemic glomeruli in the superficial cortex from young and old adults who underwent a radical nephrectomy for a tumor to understand the age-related molecular changes in glomeruli. Twenty-four young and 30 old adults were used for the discovery dataset, and the significant differentially expressed proteins were further validated using an independent set comprising six young and eight old adults. Results Kidneys from old adults had lower eGFR, less kidney parenchyma on computed tomography imaging, and more glomerulosclerosis and arteriosclerosis on histology. Quantitative proteomic analysis of nonsclerosed, nonischemic glomeruli identified increased expression of tissue inhibitor of metalloproteinase-3, glypican 6, synuclein γ , apolipoprotein A-4, and Ecto-5′-nucleotidase in old adults that were further validated in an independent set. Pathway analysis indicated that proteins with increased expression in old adults were enriched in mitochondrial translational processes, aerobic respiration, and TCA cycle, whereas proteins with decreased expression in old adults were enriched in mRNA splicing, mRNA processing, and nonsense mediated decay. Furthermore, validated differentially expressed proteins did not show any significant correlation with the kidney pathology independent of age group. Conclusions Overall, this study identified proteins that are specifically associated with the aging process in otherwise normal-appearing glomeruli.

ABSTRACT Periprosthetic joint infection (PJI) is the most common and difficult to treat form of arthroplasty failure. While treatment with debridement, antibiotics, and implant retention (DAIR) is preferable to one- or two-stage implant exchange based on morbidity and cost, outcomes are not successful in all cases selected for this management strategy. DAIR is currently recommended when infection is perceived to be in an “acute” phase, based on symptom duration; despite this selection strategy, DAIR failure rates are high. A more objective means of predicting DAIR success could improve patient outcomes by limiting DAIR failures. To explore this possibility, advanced proteomic analysis of sonicate fluid samples from 95 subjects with PJI was performed using proximity extension assay (PEA), with 77 samples additionally undergoing complementary proteomics analysis with liquid chromatography with tandem mass spectrometry (LC-MS/MS). Sparse partial least squares differentiation analysis (sPLS-DA) separated samples from patients who underwent DAIR with known outcomes ( n = 19) into successful or unsuccessful groups, predicting DAIR surgical outcome (area under the curve [AUC]: 1; mean “leave one out” AUC: 0.6). Proteins predictive of DAIR surgical outcome were significantly enriched for the “protein repair” Gene Ontology (GO) pathway ( P -adj = 0.02). Additionally, proteomic signatures associated with symptom duration in PJI categorized samples into short and long symptom duration PJI. In summary, an investigation of 7,261 unique human proteins separated PJI-associated samples based on symptom duration and identified a proteomic profile predictive of DAIR success. IMPORTANCE Chronic infections are generally understood to last months to years, with acute infections lasting days to weeks. The transition from acute to chronic infection is, however, poorly understood. Periprosthetic joint infection (PJI) has been considered more challenging to treat when “chronic” than when “acute.” A surgery preferred for its recovery time and cost—debridement, antibiotics, and implant retention (DAIR)—is recommended for PJI management when symptom duration is short; yet, even in this select patient group, DAIR is associated with a high treatment failure rate. A means to better identify those predicted to have a successful outcome if they undergo DAIR is needed. Here, over 7,000 proteins from human clinical PJI samples were measured and shown to be able to separate samples based on symptom duration. Importantly, a proteomic profile predictive of DAIR success was identified.

The quinoxaline core is found in several biologically active compounds, with Erdafitinib being the first FDA-approved quinoxaline derivative that targets a kinase and exhibits anti-cancer properties. We previously reported a quinoxaline analog (84) that displayed anti-cancer effects by inhibiting IKKβ, a key kinase in the NFκB pathway. Here, we present the synthesis of a regioisomer (51-106) and its characterization as a selective MAP3K1 inhibitor with improved metabolic stability and oral bioavailability. We used the small molecule MAP3K1 inhibitor in a proteomics study that identified NPM1 as a member of the MAP3K1 network.

Increased infiltration of CD3 + and CD8 + T cells into ovarian cancer (OC) is linked to better prognosis, but the specific antigens involved are unclear. Recent reports suggest that HLA class I can present peptides from noncoding genomic regions, known as noncanonical or cryptic peptides, but their immunogenicity is underexplored. To address this, we used immunopeptidomic analysis and RNA sequencing on five metastatic OC samples, which identified 311 cryptic peptides (40 to 83 per patient). Despite comprising less than 1% of total peptides, cryptic peptides from noncoding transcripts emerged as the predominant antigen class when compared to the other major classes of known tumor-specific and tumor-associated antigens in OC samples. Notably, nearly 70% of the prioritized cryptic peptides elicited T cell activation, as evidenced by increased 4-1BB and IFN-γ expression in autologous CD8 + T cells. This study reveals noncoding cryptic peptides as an important class of immunogenic antigens in OC.

Introduction: Extracranial carotid artery pathology accounts for 15-20% of ischemic strokes. Advancements in magnetic resonance angiography (MRA) with vessel wall imaging (VWI) have enabled the identification of vulnerable plaques, aiding in risk stratification for neurovascular events. This pilot study aimed to identify proteins in plaques with and without vulnerable features on MRA with VWI. Hypothesis: There is a differential proteomic profile of vulnerable and non-vulnerable, thus, these can serve as potential biomarkers for disease progression, stroke prevention, and therapeutic targets. Methods: Consecutive patients undergoing carotid endarterectomy (CEA) were included in the study cohort with pre-operative MRA with VWI. A retrospective chart review was conducted to extract pertinent clinical data including cardiovascular risk factors and medications. The proteomic analysis involved Tandem Mass Tag (TMTpro) labeling of peptides, basic pH HPLC fractionation, and NanoLC-tandem mass spectrometry. Results: A total of sixteen plaques were retrieved from fifteen patients. There were 73.3% male patients. The most common comorbidities were hyperlipidemia (93.3%) and hypertension (80%). 31.2% of patients had symptomatic disease. Eleven plaques were vulnerable in preoperative MRI with VWI. From those, intraplaque hemorrhage was the most common feature (81.1%) . Proteomic analysis revealed 23 relevant proteins significantly elevated in vulnerable plaques, including Proteinase 3 (PRTN3), Phospholipid Transfer Protein (PLTP), and S100 Calcium-Binding Protein A12 (S100A12), with increased abundance exceeding two-fold changes or above (P<0.001). Conversely, three proteins exhibited reduced abundance in vulnerable plaques including Dynamin-3 (DNM3), Transmembrane Protein 181 (TMEM181), and Adducin-3 (ADD3) (P<0.05). All results are summarized in Figure 1A-C and Table I and II. Conclusion: This study contributes to the understanding of protein biomarkers associated with carotid plaque vulnerability, offering insights into disease progression, stroke prevention, and identification of potential therapeutic targets (Figure 1D) . Furthermore, these patients could benefit from early surgical intervention if these biomarkers were to be detected. We present a comprehensive study of multiple proteins with significant bioavailability in explanted plaque specimens that can serve as a foundation for identifying blood biomarkers for future validation studies.