Biology subjects

Kurowski, K.

Publications and source records attributed to Kurowski, K..

4 recordsLinked to original sources

bioRxiv2026

Hybrid quantum-classical de novo design of MHC-binding peptides

Deep generative models have become a leading approach for designing therapeutic molecules, yet efficiently exploring vast biomolecular sequence spaces remains difficult, particularly for targets with limited training data. The prior distribution that seeds a generative model shapes which regions of sequence space it explores, and recent work suggests that non-classical distributions sampled from quantum processors can serve as a structured alternative to the factorised Gaussian priors used by default. Whether such priors help on complex biological design tasks has been largely untested. Here we present what is, to our knowledge, the first end-to-end hybrid quantum-classical pipeline for de novo design of MHC class I-binding peptides, coupling a generative adversarial network (GAN) to latent vectors sampled from a real photonic quantum processor. Tested in silico across 131 HLA alleles, quantum-derived priors increased the yield of predicted strong binders, with the largest relative gains for understudied alleles where classical baselines perform worst. We selected three understudied alleles for further evaluation, finding that large gains coincided with broader sequence exploration at non-anchor positions while anchor specificity was preserved. On these three alleles, we validated the designs in vitro using peptide-MHC stability ELISAs, confirming that quantum-designed peptides are potent stabilisers of peptide-MHC class I complexes. These results establish structured, hardware-realisable non-classical priors as a useful inductive bias for generative peptide design, with direct relevance to personalised immunotherapies and vaccines.

biochemistry↗

bioRxiv2025

In Situ, Antibody-Independent, and Multiplexed Characterization of Amyloid Plaques by MALDI MS/MS Imaging Using iprm-PASEF

BackgroundAmyloidosis collectively describes a heterogeneous group of protein aggregation-based diseases involving the misfolding and extracellular accumulation of fibril-forming amyloid proteins. The tissue deposition of these fibrils occurs either localized (limited to one organ) or systemically, impairing organ function and, in severe cases, leading to organ failure. Identification of the amyloidogenic protein leading to the correct subtyping is challenging but crucial for treatment decisions. Imaging parallel reaction monitoring (iprm)-parallel accumulation-serial fragmentation (PASEF) is a novel method for matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry imaging (MSI) that enables the fast, spatially resolved, multiplexed, and antibody-independent identification of peptides and proteins in situ. In this proof-of-concept study, we demonstrate the applicability of iprm-PASEF for the in situ characterization of amyloidosis. MethodsA multiplexed iprm-PASEF panel (comprising trapped ion mobility spectrometry (TIMS) and m/z values) for characterizing amyloid plaques by MALDI-MSI was compiled. The panel included nine peptide entries of amyloidosis-associated proteins (vitronectin, apolipoprotein E, serum amyloid P component) and the prevalent amyloidosis-subtype proteins serum amyloid A, transthyretin, and immunoglobulin light chain 2. The multiplexed iprm-PASEF panel was applied to a tissue microarray (TMA) assembled from formalin-fixed, paraffin-embedded (FFPE) specimens, comprising biopsies of amyloidosis-positive tissues from 18 patients, including six different tissue types, and representing the following amyloidosis subtypes: ATTR (transthyretin amyloidosis), AL (immunoglobulin light chain amyloidosis), and AA (secondary amyloidosis). For comparison and co-localization, congo red staining was performed on adjacent slides. ResultsMALDI TIMS MS1 imaging was acquired from the amyloidosis TMA, providing an m/z feature list containing 1390 entries that was subsequently refined to only include m/z features likely stemming from amyloidosis-related peptides. Further, we focused on optimal usage of the m/z and ion mobility range to increase the number of targeted peptides. The final iprm-PASEF panel comprised 10 entries ranging from m/z 887.51 - 1,986.85 and 1/K0 1.4 - 2.1 V{middle dot}s/cm2; targeting nine peptides from six different amyloidosis-related proteins. Apolipoprotein E, serum amyloid P component, and immunoglobulin light chain 1/2 were included with two entries. Transthyretin, vitronectin, and serum amyloid A were covered by one peptide. One entry was included as a positive control targeting actin A. We applied the iprm-PASEF (MS2 mode) panel to the amyloidosis TMA and fragment (MS2) spectra were analyzed by the search engine MASCOT. Eight out of ten peptides derived from vitronectin, apolipoprotein E, serum amyloid A, serum amyloid P component, and transthyretin were successfully identified with MASCOT scores above 18. Comparison to Congo red staining indicated a more localized and heterogeneous pattern of amyloid-associated proteins (vitronectin, apolipoprotein E, serum amyloid P component) by iprm-PASEF. Compared to the clinical annotation, transthyretin and serum amyloid A were only found in their respective subtypes. In total, it was possible to describe the spatial distribution of five different amyloid-associated proteins, thereby further characterizing Congo red-positive amyloid plaques in one single iprm-PASEF measurement. Conclusion and perspectiveThis proof-of-concept study demonstrates feasibility for in situ, antibody-independent, and multiplexed proteomic typing of amyloidosis plaques. Future enlargement of the multiplex panel is likely to increase the number of targetable amyloid proteins and to probe for the presence of post-translational modifications. The present study highlights the value of iprm-PASEF for MALDI imaging strategies.

molecular biology↗

bioRxiv2024

Serum Proteome Profiling Identifies N-Cadherin and C-Met as Early Marker Candidates of Therapeutic Response to Neoadjuvant Chemotherapy in Breast Cancer

Breast cancer remains the most common cancer in women worldwide. Neoadjuvant chemotherapy (NACT) is often preferred to adjuvant chemotherapy to achieve tumour shrinkage, monitor response to therapy and facilitate surgical removal in the absence of metastases. In addition, there is strong evidence that pathological complete remission (pCR) is associated with prolonged survival. In this study, we sought to identify candidate markers that signal response or resistance to therapy. We present a retrospective longitudinal serum proteomic study of 22 breast cancer patients (11 with pCR and 11 with non-pCR) matched with 21 healthy controls. Serum was analysed by LC-MS/MS after depletion of abundant proteins by immunoaffinity, trypsinisation, isobaric labelling and fractionation by reversed-phase HPLC. We observed an inverse behaviour of the serum proteins c-Met and N-cadherin after the second cycle of chemotherapy with a high predictive value (AUC 0.93). More pronounced changes were observed after the 6th cycle of NACT, with significant changes in the intensity of the proteins contactin-1, centrosomal protein, sex hormone-binding globuline and cholinesterase. Our study highlights the possibility of monitoring response to NACT using serum as a liquid biopsy.

cancer biology↗

bioRxiv2024

Proteomic Characterization of Intrahepatic Cholangiocarcinoma Identifies Distinct Subgroups and Proteins Associated with Time-To-Recurrence

Background & AimsIntrahepatic cholangiocarcinoma (ICC) is a poorly understood cancer with dismal survival and high recurrence rates. ICCs are often detected in advanced stages. Surgical resection is the most important first-line treatment but limited to non-advanced cases, whereas chemotherapy provides only a moderate benefit. The proteome biology of ICC has only been scarcely studied and the prognostic value of initial ICCs proteomic features for the time-to-recurrence (TTR) remains unclear. MethodsWe dissected formalin-fixed, paraffin-embedded samples from 80 tumor- and 77 matching adjacent non-malignant (TANM) tissues. All samples were measured via liquid-chromatography mass-spectrometry (LC-MS/MS) in data independent acquisition mode (DIA). ResultsTumor- and TANM tissue showed strongly different biologies and DNA-repair, translation, and matrisomal processes were upregulated in ICC. In a hierarchical clustering analysis, we determined two proteomic subgroups of ICC, which showed significantly diverging TTRs. Cluster 1, which is associated with a beneficial prognosis, was enriched for matrisomal processes and proteolytic processing, while cluster 2 showed increased RNA and protein turnover. In a second, independent Cox proportional hazards model analysis, we identified individual proteins whose expression correlates with TTR distribution. Proteins with a positive hazard ratio were mainly involved in carbon/glucose metabolism and protein turnover. Conversely, proteins associated with a low hazard ratio were mostly linked to the extracellular matrix. Additional proteome profiling of patient-derived xenograft tumor models of ICC successfully distinguished tumor and stromal proteins and provided insights into cell-matrix interactions. ConclusionsWe successfully determine the proteome biology of ICC and present two proteome clusters in ICC patients with significantly different TTR rates and distinct biological motifs. A xenograft model confirmed the importance of tumor-stroma interactions for this cancer.

cancer biology↗