Recently, the Breast Cancer Center of Sun Yat-sen Memorial Hospital of Sun Yat-sen University, together with the Tianjin Key Laboratory of Clinical Multi-Omics, published an article in Cancer Science entitled "Effect of 1H-NMR serum lipoproteins on immunotherapy response in advanced triple-negative breast cancer patients". Based on NMR (nuclear magnetic resonance) spectroscopy, the study measured blood lipids and dynamic changes in metabolites and explored biomarkers, building a model composed of six blood lipid and metabolic indicators to identify patients who benefit more from triple-drug combination therapy, and concluding that asparagine and sarcosine may be associated with treatment resistance.

Triple-negative breast cancer (TNBC) is characterised by high malignancy and short median overall survival (OS). Immune checkpoint inhibitor (ICI) combined with chemotherapy can significantly prolong survival in patients with PD-L1-positive advanced TNBC, but for patients with PD-L1-negative TNBC or advanced disease there are few effective immunotherapy-based options. Recently, a multicentre phase II clinical study explored the triple combination of camrelizumab plus apatinib and eribulin in patients with advanced TNBC; despite good therapeutic effect, more than half of the enrolled patients derived little benefit. Identifying patients who are sensitive to treatment will help clinicians deliver individualised therapy, so biomarkers that can effectively predict the efficacy of immunotherapy-based triple therapy remain to be explored.

In this study, 1H-NMR was used to measure changes in blood lipid composition in patients with advanced TNBC before and after treatment with an anti-PD-1 antibody plus apatinib and eribulin (NCT04303741), and to compare them with the serum lipoproteins of healthy individuals. An efficacy prediction model based on blood lipid and metabolic indicators was constructed from HDA2, N,N-dimethylglycine, formic acid, VLFC, H4A2 and V4CH, with an AUC of 0.88. The model predicting 6-month progression-free survival (PFS) achieved an AUC of 0.87. Further analysis examined the correlation between baseline lipid indicators and patient PFS and explored nine indicators with statistically significant differences relative to PFS. High expression of these indicators was associated with treatment sensitivity, among which high H4A2 expression correlated with the objective response rate (ORR) and PFS, suggesting that this indicator can be used for efficacy prediction. Analysis of serum levels before and after treatment in patients with different efficacy showed that very-low-density lipoprotein (VLDL) levels after treatment were higher than before treatment, and that serum asparagine and sarcosine levels rose significantly after treatment. The results indicate that asparagine and sarcosine may be responsible for treatment resistance. To further explore serum indicators in advanced TNBC, baseline serum metabolites of the patients and of 17 age- and sex-matched healthy individuals were analysed. The results showed that TNBC patients are characterised by low H4-class lipoproteins, suggesting that a recent history of chemotherapy affects lipid metabolism in these patients.

NMR indicators associated with progression-free survival (PFS) in baseline serum

Treating with this triple therapy, combined with measures that lower asparagine levels, may improve efficacy and reduce the proportion of individuals who develop resistance. The efficacy prediction model based on six serum lipids and metabolites described here may be a good screening tool for identifying patients with advanced TNBC who are sensitive to anti-PD-1 antibody combined with apatinib and eribulin. The model will be tested in a subsequently planned randomised phase III trial to verify its accuracy.

Precision NMR blood lipid testing service

Nuclear magnetic resonance (NMR) spectroscopy is an ideal analytical technique, allowing non-invasive, non-destructive and quantitative analysis of molecular structure, dynamic processes and chemical reactions. A large body of literature confirms that NMR is an irreplaceable tool for measuring low-density lipoprotein particle (LDL-P) subfractions, and the role of LDL-P in the early warning and treatment monitoring of atherosclerotic cardiovascular disease (ASCVD) has been widely reported: the smaller and more numerous the lipoprotein particles, the higher the risk of atherosclerosis. The 2022 Chinese Expert Consensus on Non-Traditional Lipid Indicators and Risk Management of Atherosclerotic Cardiovascular Disease already recommends NMR as a new technology, and a growing number of non-traditional lipid indicators have since been written into domestic expert consensus documents.

ProteinT has therefore been among the first to introduce internationally leading NMR spectroscopy technology into China and apply it in clinical practice, addressing the pain point that conventional lipid indicators lack precision. Thanks to its stable performance, a fully automated standard platform has been established featuring simple sample preparation, automatic data acquisition and processing, automatic generation of quantitative reports and no need for professional NMR experience.

ProteinT NMR testing items and clinical applications

Tianjin Key Laboratory of Clinical Multi-Omics

The laboratory focuses on the development of early screening and early diagnosis technologies for high-incidence tumours based on liquid biopsy, and on multi-omics-based tumour recurrence monitoring and companion diagnostics. Established under the leadership of ProteinT and approved by the Tianjin Science and Technology Bureau, it covers an area of 1,700 m2. Drawing on the technological strengths of the enterprise, it supports research institutes, hospitals and research organisations in related fields in work on the mechanisms of tumour and cardiovascular disease, the screening of diagnostic and therapeutic biomarkers and the establishment of databases, with a view to bringing the advantages of multi-omics technology more fully into clinical diagnosis, treatment and drug development.

► Key research directions

● Tumour biomarker development  

● Precision medication guidance 

● Drug target development  

● Early tumour diagnosis  

● Treatment monitoring and prognosis assessment    

● Early screening of cardiovascular disease