Proteomic Stratification of Prognosis and Treatment Options for Small Cell Lung Cancer.

Small cell lung cancer (SCLC) is a highly malignant and heterogeneous cancer with limited therapeutic options and prognosis prediction models. Here, we analyzed formalin-fixed, paraffin-embedded (FFPE) samples of surgical resections by proteomic profiling, and stratified SCLC into three proteomic subtypes (S-I, S-II, and S-III) with distinct clinical outcomes and chemotherapy responses. The proteomic subtyping was an independent prognostic factor and performed better than current tumor-node-metastasis or Veterans Administration Lung Study Group staging methods. The subtyping results could be further validated using FFPE biopsy samples from an independent cohort, extending the analysis to both surgical and biopsy samples. The signatures of the S-II subtype in particular suggested potential benefits from immunotherapy. Differentially overexpressed proteins in S-III, the worst prognostic subtype, allowed us to nominate potential therapeutic targets, indicating that patient selection may bring new hope for previously failed clinical trials. Finally, analysis of an independent cohort of SCLC patients who had received immunotherapy validated the prediction that the S-II patients had better progression-free survival and overall survival after first-line immunotherapy. Collectively, our study provides the rationale for future clinical investigations to validate the current findings for more accurate prognosis prediction and precise treatments.

Itaconate alleviates diet-induced obesity via activation of brown adipocyte thermogenesis.

Despite medical advances, there remains an unmet need for better treatment of obesity. Itaconate, a product of the decarboxylation of the tricarboxylic acid cycle intermediate cis-aconitate, plays a regulatory role in both metabolism and immunity. Here, we show that itaconate, as an endogenous compound, counteracts high-fat-diet (HFD)-induced obesity through leptin-independent mechanisms in three mouse models. Specifically, itaconate reduces weight gain, reverses hyperlipidemia, and improves glucose tolerance in HFD-fed mice. Additionally, itaconate enhances energy expenditure and the thermogenic capacity of brown adipose tissue (BAT). Unbiased proteomic analysis reveals that itaconate upregulates key proteins involved in fatty acid oxidation and represses the expression of lipogenic genes. Itaconate may provoke a major metabolic reprogramming by inducing fatty acid oxidation and suppression of fatty acid synthesis in BAT. These findings highlight itaconate as a potential activator of BAT-mediated thermogenesis and a promising candidate for anti-obesity therapy.

Dynamic Proteomic Changes in Tumor and Immune Organs Reveal Systemic Immune Response to Tumor Development.

In orthotopic mouse tumor models, tumor progression is a complex process, involving interactions among tumor cells, host cell-derived stromal cells, and immune cells. Much attention has been focused on the tumor and its tumor microenvironment, while the host's macroenvironment including immune organs in response to tumorigenesis is poorly understood. Here, we report a temporal proteomic analysis on a subcutaneous tumor and three immune organs (LN, MLN, and spleen) collected on Days 0, 3, 7, 10, 14, and 21 after inoculation of mouse forestomach cancer cells in a syngeneic mouse model. Bioinformatics analysis identified key biological processes during distinct tumor development phases, including an initial acute immune response, the attack by the host immune system, followed by the adaptive immune activation, and the build-up of extracellular matrix. Proteomic changes in LN and spleen largely recapitulated the dynamics of the immune response in the tumor, consistent with an acute defense response on D3, adaptive immune response on D10, and immune evasion by D21. In contrast, the immune response in MLN showed a gradual and sustained activation, suggesting a delayed response from a distal immune organ. Combined analyses of tumors and host immune organs allowed the identification of potential therapeutic targets. A proof-of-concept experiment demonstrated that significant growth reduction can be achieved by dual inhibition of MEK and DDR2. Together, our temporal proteomic dataset of tumors and immune organs provides a useful resource for understanding the interaction between tumors and the immune system and has the potential for identifying new therapeutic targets for cancer treatment.

Expanding individualized therapeutic options via genoproteomics.

Clinical next-generation sequencing (NGS) tests have enabled treatment recommendations for cancer patients with driver gene mutations. Targeted therapy options for patients without driver gene mutations are currently unavailable. Herein, we performed NGS and proteomics tests on 169 formalin-fixed paraffin-embedded (FFPE) samples of non-small cell lung cancers (NSCLC, 65), colorectal cancers (CRC, 61), thyroid carcinomas (THCA, 14), gastric cancers (GC, 2), gastrointestinal stromal tumors (GIST, 11), and malignant melanomas (MM, 6). Of the 169 samples, NGS detected 14 actionable mutated genes in 73 samples, providing treatment options for 43% of the patients. Proteomics identified 61 actionable clinical drug targets approved by the FDA or undergoing clinical trials in 122 samples, providing treatment options for 72% of the patients. In vivo experiments demonstrated that the Mitogen-Activated Protein Kinase (MEK) inhibitor could block lung tumor growth in mice with overexpression of Map2k1 protein. Therefore, protein overexpression is a potentially feasible indicator for guiding targeted therapies. Collectively, our analysis suggests that combining NGS and proteomics (genoproteomics) could expand the targeted treatment options to 85% of cancer patients.

Multilevel proteomic analyses reveal molecular diversity between diffuse-type and intestinal-type gastric cancer.

Diffuse-type gastric cancer (DGC) and intestinal-type gastric cancer (IGC) are the major histological types of gastric cancer (GC). The molecular mechanism underlying DGC and IGC differences are poorly understood. In this research, we carry out multilevel proteomic analyses, including proteome, phospho-proteome, and transcription factor (TF) activity profiles, of 196 cases covering DGC and IGC in Chinese patients. Integrative proteogenomic analysis reveals ARIDIA mutation associated with opposite prognostic effects between DGC and IGC, via diverse influences on their corresponding proteomes. Systematical comparison and consensus clustering analysis identify three subtypes of DGC and IGC, respectively, based on distinct patterns of the cell cycle, extracellular matrix organization, and immune response-related proteins expression. TF activity-based subtypes demonstrate that the disease progressions of DGC and IGC were regulated by SWI/SNF and NFKB complexes. Furthermore, inferred immune cell infiltration and immune clustering show Th1/Th2 ratio is an indicator for immunotherapeutic effectiveness, which is validated in an independent GC anti-PD1 therapeutic patient group. Our multilevel proteomic analyses enable a more comprehensive understanding of GC and can further advance the precision medicine.

Urine proteomic signatures predicting the progression from premalignancy to malignant gastric cancer.

BACKGROUND: Early detection of gastric cancer (GC) remains challenging. We aimed to examine urine proteomic signatures and identify protein biomarkers that predict the progression of gastric lesions and risk of GC. METHODS: A case-control study was initially designed, covering subjects with GC and gastric lesions of different stages. Subjects were aged 40-69 years, without prior diagnosis of renal or urological diseases. We enrolled a total of 255 subjects, with 123 in the discovery stage from Linqu, China, a high-risk area for GC and 132 in the validation stage from Linqu and Beijing. A prospective study was further designed for a subset of 60 subjects with gastric lesions, which were followed for 297-857 days. FINDINGS: We identified 43 differentially expressed urine proteins in subjects with GC vs. mild or advanced gastric lesions. Baseline urinary levels of ANXA11, CDC42, NAPA and SLC25A4 were further positively associated with risk of gastric lesion progression. Three of them, except for SLC25A4, also had higher expression in GC than non-GC tissues. Integrating these four proteins showed outstanding performance in predicting the progression of gastric lesions (AUC (95% CI): 0.92 (0.83-1.00)) and risk of GC (AUC (95% CI): 0.81 (0.73-0.89) and 0.84 (0.77-0.92) for GC vs. mild or advanced gastric lesions respectively). INTERPRETATION: This study revealed distinct urine proteomic profiles and a panel of proteins that may predict the progression of gastric lesions and risk of GC. These biomarkers in a non-invasive approach may have translational significance for defining high-risk populations of GC and its early detection. FUNDING: Funders are listed in the Acknowledgement.

Liver cancer heterogeneity modeled by in situ genome editing of hepatocytes.

Mechanistic study and precision treatment of primary liver cancer (PLC) are hindered by marked heterogeneity, which is challenging to recapitulate in any given liver cancer mouse model. Here, we report the generation of 25 mouse models of PLC by in situ genome editing of hepatocytes recapitulating 25 single or combinations of human cancer driver genes. These mouse tumors represent major histopathological types of human PLCs and could be divided into three human-matched molecular subtypes based on transcriptomic and proteomic profiles. Phenotypical characterization identified subtype- or genotype-specific alterations in immune microenvironment, metabolic reprogramming, cell proliferation, and expression of drug targets. Furthermore, single-cell analysis and expression tracing revealed spatial and temporal dynamics in expression of pyruvate kinase M2 (Pkm2). Tumor-specific knockdown of Pkm2 by multiplexed genome editing reversed the Warburg effect and suppressed tumorigenesis in a genotype-specific manner. Our study provides mouse PLC models with defined genetic drivers and characterized phenotypical heterogeneity suitable for mechanistic investigation and preclinical testing.

A urinary proteomic landscape of COVID-19 progression identifies signaling pathways and therapeutic options.

Signaling pathway alterations in COVID-19 of living humans as well as therapeutic targets of the host proteins are not clear. We analyzed 317 urine proteomes, including 86 COVID-19, 55 pneumonia and 176 healthy controls, and identified specific RNA virus detector protein DDX58/RIG-I only in COVID-19 samples. Comparison of the COVID-19 urinary proteomes with controls revealed major pathway alterations in immunity, metabolism and protein localization. Biomarkers that may stratify severe symptoms from moderate ones suggested that macrophage induced inflammation and thrombolysis may play a critical role in worsening the disease. Hyper activation of the TCA cycle is evident and a macrophage enriched enzyme CLYBL is up regulated in COVID-19 patients. As CLYBL converts the immune modulatory TCA cycle metabolite itaconate through the citramalyl-CoA intermediate to acetyl-CoA, an increase in CLYBL may lead to the depletion of itaconate, limiting its anti-inflammatory function. These observations suggest that supplementation of itaconate and inhibition of CLYBL are possible therapeutic options for treating COVID-19, opening an avenue of modulating host defense as a means of combating SARS-CoV-2 viruses.

Proteomic profiling identifies signatures associated with progression of precancerous gastric lesions and risk of early gastric cancer.

BACKGROUND: Molecular features underlining the multistage progression of gastric lesions and development of early gastric cancer (GC) are poorly understood, restricting the ability to GC prevention and management. METHODS: We portrayed proteomic landscape and explored proteomic signatures associated with progression of gastric lesions and risk of early GC. Tissue proteomic profiling was conducted for a total of 324 subjects. A case-control study was performed in the discovery stage (n=169) based on populations from Linqu, a known high-risk area for GC in China. We then conducted two-stage validation, including a cohort study from Linqu (n = 56), with prospective follow-up for progression of gastric lesions (280-473 days), and an independent case-control study from Beijing (n = 99). FINDINGS: There was a clear distinction in proteomic features for precancerous gastric lesions and GC. We derived four molecular subtypes of gastric lesions and identified subtype-S4 with the highest progression risk. We found 104 positively-associated and 113 inversely-associated proteins for early GC, with APOA1BP, PGC, HPX and DDT associated with the risk of gastric lesion progression. Integrating these proteomic signatures, the ability to predict progression of gastric lesions was significantly strengthened (areas-under-the-curve=0.88 (95%CI: 0.78-0.99) vs. 0.56 (0.36-0.76), Delong's P = 0.002). Immunohistochemistry assays and examination at mRNA level validated the findings for four proteins. INTERPRETATION: We defined proteomic signatures for progression of gastric lesions and risk of early GC, which may have translational significance for identifying particularly high-risk population and detecting GC at an early stage, improving potential for targeted GC prevention. FUNDING: The funders are listed in the Acknowledgement.

Proteomics provides individualized options of precision medicine for patients with gastric cancer.

While precision medicine driven by genome sequencing has revolutionized cancer care, such as lung cancer, its impact on gastric cancer (GC) has been minimal. GC patients are routinely treated with chemotherapy, but only a fraction of them receive the clinical benefit. There is an urgent need to develop biomarkers or algorithms to select chemo-sensitive patients or apply targeted therapy. Here, we carried out retrospective analyses of 1,020 formalin-fixed, paraffin-embedded GC surgical resection samples from 5 hospitals and developed a mass spectrometry-based workflow for proteomic subtyping of GC. We identified two proteomic subtypes: the chemo-sensitive group (CSG) and the chemo-insensitive group (CIG) in the discovery set. The 5-year overall survival of CSG was significantly improved in patients who had received adjuvant chemotherapy after surgery compared with those who received surgery only (64.2% vs. 49.6%; Cox P-value=0.002), whereas no such improvement was observed in CIG (50.0% vs. 58.6%; Cox P-value=0.495). We validated these results in an independent validation set. Further, differential proteome analysis uncovered 9 FDA-approved drugs that may be applicable for targeted therapy of GC. A prospective study is warranted to test these findings for future GC patient care.