Proteomic Portrait of Human Lymphoma Reveals Protein Molecular Fingerprint of Disease Specific Subtypes and Progression

Xin Ku; Jinghan Wang; Haikuo Li; Chen Meng; Fang Yu; Wenjuan Yu; Zhongqi Li; Ziqi Zhou; Can Zhang; Ying Hua; Wei Yan; Jie Jin

doi:10.1007/s43657-022-00075-w

Proteomic Portrait of Human Lymphoma Reveals Protein Molecular Fingerprint of Disease Specific Subtypes and Progression

Phenomics. 2022 Dec 12;3(2):148-166. doi: 10.1007/s43657-022-00075-w. eCollection 2023 Apr.

Authors

Xin Ku^#¹, Jinghan Wang^#^{2

3

4}, Haikuo Li^#^{1

5}, Chen Meng⁶, Fang Yu⁷, Wenjuan Yu², Zhongqi Li⁸, Ziqi Zhou¹, Can Zhang¹, Ying Hua¹, Wei Yan¹, Jie Jin^{2

3

4}

Affiliations

¹ Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200240 China.
² Department of Hematology, The First Affiliated Hospital of Medical School of Zhejiang University, Hangzhou, 310003 China.
³ Cancer Center, Zhejiang University, Hangzhou, 310003 China.
⁴ Key Laboratory of Hematologic Malignancies, Diagnosis and Treatment, Hangzhou, 310003 China.
⁵ Present Address: Division of Biology & Biomedical Sciences, Washington University in St. Louis School of Medicine, St. Louis, 63130 USA.
⁶ Bavarian Center for Biomolecular Mass Spectrometry, Technical University of Munich, 85354 Freising, Germany.
⁷ Department of Pathology, The First Affiliated Hospital of Zhejiang University, Hangzhou, 310003 China.
⁸ Department of Surgical Oncology, College of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, 310003 China.

^# Contributed equally.

Abstract

An altered proteome in lymph nodes often suggests abnormal signaling pathways that may be associated with diverse lymphatic disorders. Current clinical biomarkers for histological classification of lymphomas have encountered many discrepancies, particularly for borderline cases. Therefore, we launched a comprehensive proteomic study aimed to establish a proteomic landscape of patients with various lymphatic disorders and identify proteomic variations associated with different disease subgroups. In this study, 109 fresh-frozen lymph node tissues from patients with various lymphatic disorders (with a focus on Non-Hodgkin's Lymphoma) were analyzed by data-independent acquisition mass spectrometry. A quantitative proteomic landscape was comprehensively characterized, leading to the identification of featured protein profiles for each subgroup. Potential correlations between clinical outcomes and expression profiles of signature proteins were also probed. Two representative signature proteins, phospholipid-binding proteins Annexin A6 (ANXA6) and Phospholipase C Gamma 2 (PLCG2), were successfully validated via immunohistochemistry. We also evaluated the capability of acquired proteomic signatures to segregate multiple lymphatic abnormalities and identified several core signature proteins, such as Sialic Acid Binding Ig Like Lectin 1 (SIGLEC1) and GTPase of immunity-associated protein 5 (GIMAP5). In summary, the established lympho-specific data resource provides a comprehensive map of protein expression in lymph nodes during multiple disease states, thus extending the existing human tissue proteome atlas. Our findings will be of great value in exploring protein expression and regulation underlying lymphatic malignancies, while also providing novel protein candidates to classify various lymphomas for more precise medical practice.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-022-00075-w.

Keywords: Lymphoma; Molecular profiling; Non-Hodgkin’s Lymphoma; Proteomics; Stratification.

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