Cancer Research, Drug Discovery, Biochemistry, Pharmaceutical Science
80
Scopus Publications
4576
Scholar Citations
34
Scholar h-index
63
Scholar i10-index
Scopus Publications
Klebsiella pneumoniae LPS drives stromal-mediated repression of p53 and colorectal cancer chemoresistance Konstantinos Fragkoulis, Barbara Łasut-Szyszka, Ákos Végvári, Diyoly Ayona, Amir Ata Saei, Marie-Stéphanie Aschtgen, Sylvain Peuget Cell Death and Disease, 2026 The gut bacterial microbiota is increasingly recognized as a key modulator of colorectal cancer (CRC) initiation, progression and response to therapy. However, the mechanisms by which bacteria influence the response to anticancer drugs remain poorly understood. Here, we investigate the effects of microbiota-driven signaling on the tumor suppressor p53 and its impact on chemotherapy. We uncover a mechanism by which lipopolysaccharide (LPS) from Klebsiella pneumoniae and other Enterobacteria impairs p53 activity and promotes chemoresistance via paracrine signaling from the tumor microenvironment. While direct exposure to LPS did not alter the drug response of CRC cells, conditioned media from LPS-stimulated macrophages or fibroblasts suppressed p53 accumulation and attenuated the response to chemotherapeutic agents. Deep quantitative proteomics further revealed selective inhibition of a subset of p53 targets by inflammation. This same subset negatively correlated with inflammatory signature and immune infiltration in patients and was associated with improved survival following chemotherapy. Mechanistically, our data suggest that macrophage-derived extracellular vesicles contribute to p53 degradation in cancer cells. Overall, our findings reveal a microbiota-driven mechanism of p53 suppression via the microenvironment that contributes to chemoresistance, highlighting the impact of bacteria on tumor cell fate and therapeutic efficacy in CRC.
Solubility based mechanistic profiling of combinatorial drug therapy Elham Gholizadeh, Ehsan Zangene, Uladzislau Vadadokhau, Danilo Ritz, Juho J. Miettinen, Rabah Soliymani, Marc Baumann, Mathias Wilhelm, Esko Kankuri, Paul A. Haynes, Caroline A. Heckman, Amir A. Saei, Mohieddin Jafari Nature Communications, 2026 Acute myeloid leukemia (AML) remains challenging to treat due to extensive genetic heterogeneity, high relapse rates, and treatment-related toxicity. Although drug combinations offer therapeutic promise, their selection is often empirical. Here, we introduce Combinatorial Proteome Integral Solubility/Stability Alteration analysis (CoPISA), a high-throughput proteomics workflow that captures protein solubility/stability alterations uniquely induced by drug combinations. We applied CoPISA to two rationally designed AML drug pairs, LY3009120-sapanisertib (LS) and ruxolitinib-ulixertinib (RU), previously identified as the most effective and least toxic combinations among many candidates and validated in AML cell lines, patient-derived samples and zebrafish xenograft models. We uncovered an emergent mechanism termed "conjunctional targeting", in which combinatorial drug action induces combination-exclusive protein targets consistent with an AND-gate logic model. LS-specific converged on SUMOylation, chromatin condensation, and VEGF-linked adhesion, while RU-specific targets disrupted DNA-damage checkpoints, mitochondrial bioenergetics, and RNA-splicing. Post-translational modification analysis revealed combination-induced acetylation, methylation, and phosphorylation of key AML proteins, including NPM1. Network analysis demonstrated that a substantial fraction of AML-associated proteins targeted by CoPISA are unique to combinations, including DNMT3A, NPM1, and TP53. By uncovering a mechanistic layer beyond classical synergy, CoPISA provides a robust framework for the precision-guided design of combinatorial therapies in heterogeneous cancers.
Preventing Proteomics Data Tombs Through Collective Responsibility and Community Engagement Uladzislau Vadadokhau, Mai Soliman, Leticia Castillon, Paula Pastor Muñoz, Linda Id, Swethaa Natraj Gayathri, Ankita Srivastava, Tyko Runeberg, Tamara González-Armijos, Karina Šapovalovaitė, Milda Sakalauskaite, Sadiksha Adhikari, Oluwatosin Abe, Tiialotta Tohmola, Hao Li, Srividhya Sundaresan, Hanna Vesikukka, Jannica Roininen, Ehsan Zangene, Rabah Soliymani, Sami T. Tuomivaara, Veit Schwämmle, Amir A. Saei, Markku Varjosalo, Mohieddin Jafari Scientific Data, 2026 Public proteomics repositories now host vast amounts of mass spectrometry data, yet much of it remains difficult to reuse, risking "data tombs" that are open access but not practically re-analyzable. In spring 2025, a graduate-level course at the University of Helsinki tasked six student teams with reanalyzing six projects from the Proteomics Identification Database (label-free quantification only) using a common R-based workflow (rpx, mzR, QFeatures, DEP/MSqRob2/limma/OmicsQ packages) that was shared across all teams. The teams reproduced identification, optional quantification, normalization, imputation, and differential expression analyses, and compared the outcomes to the original studies. As expected, systemic barriers recurred across cases: (i) no sample and data relationship format for proteomics metadata in any of the cases; (ii) missing details regarding decoy sets for false discovery rate assessment; (iii) proprietary-only outputs or software (e.g., Thermo.msf, Progenesis) that impeded open reanalysis in interoperable, community-standard formats; (iv) missing data-independent acquisition spectral libraries or protein sequences database files (FASTA); (v) absent or vague normalization/imputation/statistical parameters; (vi) inconsistent file naming; and (vii) insufficient biological/technical replication in at least one project. These shortcomings yielded large discrepancies in the analysis results (e.g., 13,068 vs. 4,923 proteins; 108 vs. 11 differentially expressed proteins), and, in one instance, a highlighted protein lacked robust support in the deposited identifications. We observed that reproducibility in mass spectrometry-based proteomics hinges less on instruments than on transparent metadata, open formats, and executable analysis provenance. We propose that data creators provide a minimum re-analysis package, including raw data and open formats, community standards, basic quality control summaries, data-independent acquisition spectral libraries, and complete parameter/code sets with pinned versions or containers. Moreover, we recommend repository-level nudges toward making such packages mandatory. This educational exercise simultaneously trains the students as well as stress-tests the community data practices to prevent proteomics "data tombs".
Small molecule inhibition of voltage dependent anion channel 1 reroutes mitochondrial metabolite flux Seyed Majed Modaresi, Leilei Zhang, Amir Ata Saei, Morris Degen, Mohammad Khavani, Hassan Gharibi, Ákos Végvári, Zhiwei Ye, Jie Zhang, Evgeny Pavlov, Elizabeth A. Jonas, Kenneth D. Tew, Sebastian Hiller, Danyelle M. Townsend, Eduardo N. Maldonado Molecules and Cells, 2026 Voltage dependent anion channels (VDACs 1, 2 and 3) in the outer mitochondrial membrane control the flux of anions and oxidizable substrates that sustain mitochondrial metabolism. Nicotinamide adenine dinucleotide (NADH) closes VDAC by binding to a pocket, conserved in all isoforms, located in the inner wall of the channel. Previously, we identified the small molecule SC18 that targets the NADH-binding pocket of VDAC1 employing computational analysis. Here, we explored the interaction between SC18 and VDAC1 using high-resolution nuclear magnetic resonance spectroscopy and molecular dynamics simulations. Atomically resolved data precisely confirmed the computational results, showing that SC18 binds to a site on VDAC1 that partially overlaps with the NADH binding pocket. SC18, in the presence of NADH blocked the conductance of VDAC1 reconstituted in lipid bilayers. To determine the metabolic effect of SC18, we combined readouts of mitochondrial metabolism and glycolysis with functional metabolomics and proteomics. Short-term treatment with SC18 inhibited mitochondrial metabolism and adenosine triphosphate production. Treatment over 24 h and 48 h further reduced mitochondrial uptake of pyruvate and glutamine, utilization of tricarboxylic acid cycle intermediates, as well as lipid, DNA and amino acid synthesis. Concomitant with the inhibition of mitochondrial metabolism, cellular uptake of glucose and glutamine increased in parallel with augmented lactate release. These results indicate that compensatory enhanced glycolysis sustains adenosine triphosphate production after impaired mitochondrial function induced by SC18 blockage of VDAC1. Our work sets a mechanistic foundation for VDAC1 inhibition as a novel strategy to target and reprogram cancer metabolism through modulation of the biosynthetic ability of mitochondria.
A ginsenoside metabolite and its derivative target PRELID3B against lung cancer cells Jilin He, Chun-Nam Lok, Guanya Yang, Ying He, Yungen Liu, Amir Ata Saei, Yiwei Zhang, Chunlei Zhang, Yanting Zhu, Zhiwen Fu, Christian Michel Beusch, Pierre Sabatier, Roman A. Zubarev, Chi-Ming Che Proceedings of the National Academy of Sciences of the United States of America, 2026 Ginseng is widely praised for its benefits on cancer patients, often attributed to its metabolite compound K ( CK ). Here, we synthesized a derivative ( CKD-4 ) that, compared with CK , exhibited enhanced cellular uptake, threefold greater cytotoxicity, and improved pharmacokinetics. CKD-4 induced significant growth inhibition on lung cancer patient-derived organoids, and on cell line-derived xenografts with minimal systemic toxicity. CKD-4 also suppressed orthotopic lung tumor growth in immunocompetent mice with enhanced antitumor immune infiltration. Using proteome integral solubility alteration and ProTargetMiner analyses, the mitochondrial phospholipid transfer protein PRELID3B was unbiasedly identified as a shared anticancer target of CK and CKD-4 . PRELID3B is a potential pancancer therapeutic target and prognostic biomarker supported by cancer genetics and transcriptomics evidence. Both CK and CKD-4 stabilize PRELID3B in cellular thermal shift assay and bind PRELID3B with K d of 23 µM and 5 µM, respectively, measured by biolayer interferometry. Multiomics analyses revealed that CK and CKD-4 share similar anticancer mechanisms, involving mitochondrial phospholipid depletion, integrated stress response activation, and immunomodulatory pathways induction associated with PRELID3B inhibition. This study provides the basis for the immunomodulatory and anticancer effects of ginseng metabolites through targeting PRELID3B, and illustrates the application of orthogonal proteomics in target identification of natural compounds.
Above-Filter Digestion Proteomics Reveals Drug Targets and Localizes Ligand Binding Site Bohdana Sokolova, Hassan Gharibi, Maryam Jafari, Hezheng Lyu, Silvia Lovera, Massimiliano Gaetani, Amir Ata Saei, Roman A. Zubarev Journal of Proteome Research, 2026 Identifying how drugs interact with proteins is fundamental to understanding their therapeutic effects and side effects. While numerous chemical proteomics methods exist for determining protein targets of drugs, each exhibits "blind spots," necessitating complementary approaches. We introduce Above-Filter Digestion Proteomics (AFDIP), which monitors trypsin digestion rates that decrease at ligand-binding sites, while potentially increasing elsewhere. Molecular dynamics simulations showed that these changes relate to backbone flexibility. Using AFDIP, we identified targets of various drugs and metabolites, allowing two-dimensional analysis with the drug concentration as the second dimension. The method identifies binding sites within ≤10 Å of crystallography-determined locations with improved resolution (≤5 Å) for larger proteins. Compared with existing proteolysis approaches, AFDIP offers simpler sample preparation, deeper proteome analysis, and broader sequence coverage. AFDIP addresses the blind spots of current techniques and provides structural insights, enhancing the chemical proteomics toolkit.
Toward a Species Search Engine: KISSE Offers a Rigorous Statistical Framework for Bone Collagen Tandem Mass Spectrometry Data Hassan Gharibi, Amir Ata Saei, Alexey L. Chernobrovkin, Susanna L. Lundstrom, Hezheng Lyu, Zhaowei Meng, Akos Vegvari, Massimilliano Gaetani, Roman A. Zubarev Advanced Science, 2025 DNA and bone collagen are two key sources of resilient molecular markers used to identify species from their remains. Collagen is more stable than DNA, and thus it is preferred for ancient and degraded samples. Current mass spectrometry‐based collagen sequencing approaches are empirical and lack a rigorous statistical framework. Based on the well‐developed approaches to protein identification in shotgun proteomics, a first approximation of the species search engine (SSE) is introduced. SSE named KISSE is based on a species‐specific library of collagenous peptides that uses both peptide sequences and their relative abundances. The developed statistical model can identify the species and the probability of correct identification, as well as determine the likelihood of the analyzed species not being in the library. The advantages and limitations of the proposed approach, and the possibility of extending it to other tissues is discussed.
A generative deep learning approach to de novo antibiotic design Aarti Krishnan, Melis N. Anahtar, Jacqueline A. Valeri, Wengong Jin, Nina M. Donghia, Leif Sieben, Andreas Luttens, Yu Zhang, Seyed Majed Modaresi, Andrew Hennes, Jenna Fromer, Parijat Bandyopadhyay, Jonathan C. Chen, Danyal Rehman, Ronak Desai, Paige Edwards, Ryan S. Lach, Marie-Stéphanie Aschtgen, Margaux Gaborieau, Massimiliano Gaetani, Samantha G. Palace, Satotaka Omori, Lutete Khonde, Yurii S. Moroz, Bruce Blough, Chunyang Jin, Edmund Loh, Yonatan H. Grad, Amir Ata Saei, Connor W. Coley, Felix Wong, James J. Collins Cell, 2025
Beyond the known cuts: trypsin specificity in native proteins Marcelo Gaspar, Bohdana Sokolova, Amir Ata Saei, José C. Marques, Roman A. Zubarev Chemical Communications, 2025 Peptides from trypsin digestion of native proteomes reveal that size, charge and local sequence motifs influence cleavage speed.
Small molecule modulation of protein corona for deep plasma proteome profiling Ali Akbar Ashkarran, Hassan Gharibi, Seyed Amirhossein Sadeghi, Seyed Majed Modaresi, Qianyi Wang, Teng-Jui Lin, Ghafar Yerima, Ali Tamadon, Maryam Sayadi, Maryam Jafari, Zijin Lin, Danilo Ritz, David Kakhniashvili, Avirup Guha, Mohammad R. K. Mofrad, Liangliang Sun, Markita P. Landry, Amir Ata Saei, Morteza Mahmoudi Nature Communications, 2024
Ultralight Ultrafast Enzymes** Xuepei Zhang, Zhaowei Meng, Christian M. Beusch, Hassan Gharibi, Qing Cheng, Hezheng Lyu, Luciano Di Stefano, Jijing Wang, Amir A. Saei, Ákos Végvári, Massimiliano Gaetani, Roman A. Zubarev Angewandte Chemie International Edition, 2024
Multi-omics analysis of magnetically levitated plasma biomolecules Ali Akbar Ashkarran, Hassan Gharibi, Dalia Abou Zeki, Irina Radu, Farnaz Khalighinejad, Kiandokht Keyhanian, Christoffer K. Abrahamsson, Carolina Ionete, Amir Ata Saei, Morteza Mahmoudi Biosensors and Bioelectronics, 2023
Abnormal (Hydroxy)proline Deuterium Content Redefines Hydrogen Chemical Mass Hassan Gharibi, Alexey L. Chernobrovkin, Gunilla Eriksson, Amir Ata Saei, Zena Timmons, Andrew C. Kitchener, Daniela C. Kalthoff, Kerstin Lidén, Alexander A. Makarov, Roman A. Zubarev Journal of the American Chemical Society, 2022
System-wide identification and prioritization of enzyme substrates by thermal analysis Amir Ata Saei, Christian M. Beusch, Pierre Sabatier, Juan Astorga Wells, Hassan Gharibi, Zhaowei Meng, Alexey Chernobrovkin, Sergey Rodin, Katja Näreoja, Ann-Gerd Thorsell, Tobias Karlberg, Qing Cheng, Susanna L. Lundström, Massimiliano Gaetani, Ákos Végvári, Elias S. J. Arnér, Herwig Schüler, Roman A. Zubarev Nature Communications, 2021
An integrative proteomics method identifies a regulator of translation during stem cell maintenance and differentiation Pierre Sabatier, Christian M. Beusch, Amir A. Saei, Mike Aoun, Noah Moruzzi, Ana Coelho, Niels Leijten, Magnus Nordenskjöld, Patrick Micke, Diana Maltseva, Alexander G. Tonevitsky, Vincent Millischer, J. Carlos Villaescusa, Sandeep Kadekar, Massimiliano Gaetani, Kamilya Altynbekova, Alexander Kel, Per-Olof Berggren, Oscar Simonson, Karl-Henrik Grinnemo, Rikard Holmdahl, Sergey Rodin, Roman A. Zubarev Nature Communications, 2021
Crosstalk between P53 and DNA damage response in ageing Amir Mohammadzadeh, Mohammad Mirza-Aghazadeh-Attari, Shahin Hallaj, Amir Ata Saei, Mohammad Reza Alivand, Amir Valizadeh, Bahman Yousefi, Maryam Majidinia DNA Repair, 2019
Possibilities in Germ Cell Research: An Engineering Insight Fereshteh Esfandiari, Omid Mashinchian, Mohammad Kazemi Ashtiani, Mohammad Hossein Ghanian, Katsuhiko Hayashi, Amir Ata Saei, Morteza Mahmoudi, Hossein Baharvand Trends in Biotechnology, 2015
Nanotoxicology: Advances and pitfalls in research methodology Morteza Azhdarzadeh, Amir Ata Saei, Shahriar Sharifi, Mohammad J Hajipour, Alaaldin M Alkilany, Mohammad Sharifzadeh, Fatemeh Ramazani, Sophie Laurent, Alireza Mashaghi, Morteza Mahmoudi Nanomedicine, 2015
Small Molecule Inhibition of VDAC1 Reroutes Mitochondrial Metabolite Flux SM Modaresi, L Zhang, AA Saei, M Degen, M Khavani, H Gharibi, ... Molecules and Cells, 100369 , 2026 2026
A ginsenoside metabolite and its derivative target PRELID3B against lung cancer cells J He, CN Lok, G Yang, Y He, Y Liu, AA Saei, Y Zhang, C Zhang, Y Zhu, ... Proceedings of the National Academy of Sciences 123 (19), e2533505123 , 2026 2026
Ligand-Mediated Proteome Remodeling Shapes Nanoparticle Protein Corona Composition for Deep Plasma Profiling M Mahmoudi, B Ghaffari, L Han, A Alpaydin, N Wills, S Grumelot, ... 2026
Klebsiella pneumoniae LPS drives stromal-mediated repression of p53 and colorectal cancer chemoresistance K Fragkoulis, B Łasut-Szyszka, Á Végvári, D Ayona, AA Saei, ... Cell Death & Disease 17 (1), 395 , 2026 2026
Solubility based mechanistic profiling of combinatorial drug therapy E Gholizadeh, E Zangene, U Vadadokhau, D Ritz, JJ Miettinen, ... Nature Communications 17 (1), 2744 , 2026 2026 Citations: 5
CoPISA: Combinatorial Proteome Integral Solubility/Stability Alteration analysis E Zangene, E Gholizadeh, U Vadadokhau, D Ritz, AA Saei, M Jafari bioRxiv, 2026.03. 20.713131 , 2026 2026
A systemic circadian nicotinic acid riboside (NaR) signal engages the unfolded protein response and adipogenesis via the prefoldin complex I Vlassakev, C Savva, L Zhou, D Ritz, A Schmidt, C Jang, AA Saei, ... bioRxiv, 2026.03. 04.709493 , 2026 2026
Mass spectrometry-based top-down proteomics for proteoform profiling of protein coronas SA Sadeghi, F Fang, R Tabatabaeian Nimavard, Q Wang, G Zhu, AA Saei, ... Nature protocols 21 (3), 1092-1125 , 2026 2026 Citations: 16
Recalibrating Nanoparticle Protein Corona Analysis for Accurate Biological Identity and Soluble Plasma Proteome Profiling B Ghaffari, S Grumelot, SA Sadeghi, A Alpaydin, K Hilsen, B Shango, ... bioRxiv, 2026.02. 19.706828 , 2026 2026
Above-Filter Digestion Proteomics reveals drug targets and localizes ligand binding site B Sokolova, H Gharibi, M Jafari, H Lyu, S Lovera, M Gaetani, AA Saei, ... Journal of Proteome Research 25 (3), 1556-1570 , 2026 2026 Citations: 2
Preventing Proteomics Data Tombs Through Collective Responsibility and Community Engagement U Vadadokhau, M Soliman, L Castillon, P Pastor Muñoz, L Id, ... Scientific data , 2026 2026 Citations: 2
Multi-omics uncovers interaction in the vaginal microbiome and a type II secretion/Tad pilus system in Gardnerella vaginalis F Romero Garcia, V Dovhalyuk, SL Kuilboer, KJ van Dijk, C Forsstrom, ... bioRxiv, 2026.05. 09.724037 , 2026 2026
Multi-omics uncovers interaction in the vaginal microbiome and a type II secretion/Tad pilus system in Gardnerella vaginalis FR García, V Dovhalyuk, S Kuilboer, KJ van Dijk, C Forsström, H Gharibi, ... 2026
Lipid nanoparticle protein coronas form via lipoprotein fusion rather than shell-like adsorption S Grumelot, N Mohammed, J Colonrosado, SA Sadeghi, F Fang, K Hilsen, ... bioRxiv, 2025.12. 21.695162 , 2025 2025 Citations: 2
A generative deep learning approach to de novo antibiotic design A Krishnan, JA Valeri, W Jin, NM Donghia, L Sieben, A Luttens, Y Zhang, ... Cell 188 (21), 5962-5979. e22 , 2025 2025 Citations: 53
Toward a Species Search Engine: KISSE Offers a Rigorous Statistical Framework for Bone Collagen Tandem Mass Spectrometry Data H Gharibi, AA Saei, AL Chernobrovkin, SL Lundstrom, H Lyu, Z Meng, ... Advanced Science 12 (40), e03963 , 2025 2025
Integrated top-down and bottom-up mass spectrometry enables precise characterization of proteoforms and their post-translational modifications within the protein corona M Mahmoudi, S Sadeghi, K Li, Y Yue, RT Nimavard, S Grumelot, A Saei, ... Research Square, rs. 3. rs-7593385 , 2025 2025 Citations: 2
HigH-ratiO partiaL proteolysiS with carriER proteome (HOLSER) Enables Global Structure Profiling and Site-resolved Elucidation of Ligand-Protein Interactions X Zhang, B Sokolova, Z Meng, H Gharibi, H Lyu, A Ata Saei, M Gaetani, ... bioRxiv, 2025.07. 11.664381 , 2025 2025 Citations: 1
Deciphering the complexity of combinatorial therapies through advanced target engagement deconvolution assays in acute myeloid leukemia E Gholizadeh, E Zangene, U Vadadokhau, D Ritz, JJ Miettinen, ... EUROPEAN JOURNAL OF CLINICAL PHARMACOLOGY 81 (1), S21-S21 , 2025 2025
Beyond correlation: establishing causality in protein corona formation for nanomedicine A Rafieioskouei, K Rogale, AA Saei, M Mahmoudi, B Bonakdarpour Molecular Pharmaceutics 22 (5), 2723-2730 , 2025 2025 Citations: 6
MOST CITED SCHOLAR PUBLICATIONS
Superparamagnetic iron oxide nanoparticles for delivery of therapeutic agents: opportunities and challenges S Laurent, AA Saei, S Behzadi, A Panahifar, M Mahmoudi Expert opinion on drug delivery 11 (9), 1449-1470 , 2014 2014 Citations: 558
Proteome integral solubility alteration: a high-throughput proteomics assay for target deconvolution M Gaetani, P Sabatier, AA Saei, CM Beusch, Z Yang, SL Lundstrom, ... Journal of proteome research 18 (11), 4027-4037 , 2019 2019 Citations: 324
Targeted superparamagnetic iron oxide nanoparticles for early detection of cancer: Possibilities and challenges Z Bakhtiary, AA Saei, MJ Hajipour, M Raoufi, O Vermesh, M Mahmoudi Nanomedicine: Nanotechnology, Biology and Medicine 12 (2), 287-307 , 2016 2016 Citations: 249
Electrochemical biosensors for glucose based on metal nanoparticles AA Saei, JE NazhadDolatabadi, P Najafi-Marandi, A Abhari, M Guardia TrAC Trends in Analytical Chemistry , 2013 2013 Citations: 223
Repurposing of auranofin: Thioredoxin reductase remains a primary target of the drug X Zhang, K Selvaraju, AA Saei, P D'Arcy, RA Zubarev, ESJ Arnér, ... Biochimie 162, 46-54 , 2019 2019 Citations: 196
Theranostic MUC-1 aptamer targeted gold coated superparamagnetic iron oxide nanoparticles for magnetic resonance imaging and photothermal therapy of colon cancer M Azhdarzadeh, F Atyabi, AA Saei, BS Varnamkhasti, Y Omidi, M Fateh, ... Colloids and Surfaces B: Biointerfaces 143, 224-232 , 2016 2016 Citations: 183
Superparamagnetic iron oxide nanoparticles for in vivo molecular and cellular imaging S Sharifi, H Seyednejad, S Laurent, F Atyabi, AA Saei, M Mahmoudi Contrast media & molecular imaging 10 (5), 329-355 , 2015 2015 Citations: 155
Microparticles containing erlotinib-loaded solid lipid nanoparticles for treatment of non-small cell lung cancer Z Bakhtiary, J Barar, A Aghanejad, AA Saei, E Nemati, ... Drug development and industrial pharmacy 43 (8), 1244-1253 , 2017 2017 Citations: 153
Nanoparticle surface functionality dictates cellular and systemic toxicity AA Saei, M Yazdani, SE Lohse, Z Bakhtiary, V Serpooshan, M Ghavami, ... Chemistry of Materials 29 (16), 6578-6595 , 2017 2017 Citations: 125
Cellular toxicity of nanogenomedicine in MCF-7 cell line: MTT assay S Ahmadian, J Barar, AA Saei, MAA Fakhree, Y Omidi Journal of visualized experiments: JoVE, 1191 , 2009 2009 Citations: 113
Nanotechnology for targeted detection and removal of bacteria: opportunities and challenges MJ Hajipour, AA Saei, ED Walker, B Conley, Y Omidi, KB Lee, ... Advanced Science 8 (21), 2100556 , 2021 2021 Citations: 111
Nanotoxicology: advances and pitfalls in research methodology M Azhdarzadeh, AA Saei, S Sharifi, MJ Hajipour, AM Alkilany, ... Nanomedicine 10 (18), 2931-2952 , 2015 2015 Citations: 108
Comprehensive chemical proteomics for target deconvolution of the redox active drug auranofin AA Saei, H Gullberg, P Sabatier, CM Beusch, K Johansson, B Lundgren, ... Redox biology 32, 101491 , 2020 2020 Citations: 107
Measurements of heterogeneity in proteomics analysis of the nanoparticle protein corona across core facilities AA Ashkarran, H Gharibi, E Voke, MP Landry, AA Saei, M Mahmoudi Nature Communications 13 (1), 6610 , 2022 2022 Citations: 96
An update to space biomedical research: tissue engineering in microgravity bioreactors A Barzegari, AA Saei BioImpacts: BI 2 (1), 23 , 2012 2012 Citations: 92
ProTargetMiner as a proteome signature library of anticancer molecules for functional discovery AA Saei, CM Beusch, A Chernobrovkin, P Sabatier, B Zhang, ÜG Tokat, ... Nature communications 10 (1), 5715 , 2019 2019 Citations: 90
Breathomics: review of sample collection and analysis, data modeling and clinical applications M Khoubnasabjafari, MRA Mogaddam, E Rahimpour, J Soleymani, ... Critical Reviews in Analytical Chemistry 52 (7), 1461-1487 , 2022 2022 Citations: 85
System-wide identification and prioritization of enzyme substrates by thermal analysis AA Saei, CM Beusch, P Sabatier, JA Wells, H Gharibi, Z Meng, ... Nature communications 12 (1), 1296 , 2021 2021 Citations: 77
The Microbiome: The Forgotten Organ of the Astronaut‘s Body–Probiotics beyond Terrestrial Limits AA Saei, A Barzegari Future microbiology 7 (9), 1037-1046 , 2012 2012 Citations: 76
DNA damage response and repair in ovarian cancer: Potential targets for therapeutic strategies M Mirza-Aghazadeh-Attari, C Ostadian, AA Saei, A Mihanfar, SG Darband, ... DNA repair 80, 59-84 , 2019 2019 Citations: 66