Serum Lipidomic Profiling in Breast Cancer to Identify Screening, Diagnostic, and Prognostic Biomarkers

The impact of circulating protein levels identified by affinity proteomics on short-term, overall breast cancer risk

OBJECTIVE

Current breast cancer risk prediction scores and algorithms can potentially be further improved by including molecular markers. To this end, we studied the association of circulating plasma proteins using Proximity Extension Assay (PEA) with incident breast cancer risk.

SUBJECTS

In this study, we included 1577 women participating in the prospective KARMA mammographic screening cohort.

RESULTS

In a targeted panel of 164 proteins, we found 8 candidates nominally significantly associated with short-term breast cancer risk (P < 0.05). Similarly, in an exploratory panel consisting of 2204 proteins, 115 were found nominally significantly associated (P < 0.05). However, none of the identified protein levels remained significant after adjustment for multiple testing. This lack of statistically significant findings was not due to limited power, but attributable to the small effect sizes observed even for nominally significant proteins. Similarly, adding plasma protein levels to established risk factors did not improve breast cancer risk prediction accuracy.

CONCLUSIONS

Our results indicate that the levels of the studied plasma proteins captured by the PEA method are unlikely to offer additional benefits for risk prediction of short-term overall breast cancer risk but could provide interesting insights into the biological basis of breast cancer in the future.

Effect of Serum Lipid Profile on the Risk of Breast Cancer: Systematic Review and Meta-Analysis of 1,628,871 Women

Dyslipidemia has been linked to breast cancer incidence. The aim of the present meta-analysis was to further investigate the relationship between the serum lipid profile and breast cancer risk. Databases such as PubMed, EMBASE, and Web of Sciences were searched up to the end of January 2021 using certain MeSH and non-MeSH keywords and combinations to extract related published articles. Twenty-six prospective studies involving 1,628,871 women, of whom 36,590 were diagnosed with breast cancer during the follow-up period met the inclusion criteria. A negative and significant association was found between the HDL-C level and the risk of breast cancer (relative risk (RR): 0.85, 95% CI: 0.72–0.99, I²: 67.6%, p = 0.04). In contrast, TG (RR: 1.02, 95% CI: 0.91–1.13, I²: 54.2%, p = 0.79), total cholesterol (TC) (RR: 0.98, 95% CI: 0.90–1.06, I²: 67.2%, p = 0.57), apolipoprotein A (ApoA) (RR: 0.96, 95% CI: 0.70–1.30, I²: 83.5%, p = 0.78) and LDL-C (RR: 0.93, 95% CI: 0.79–1.09, I²: 0%, p = 0.386) were not associated with breast cancer development. In studies adjusting for hormone use and physical activity, breast cancer risk was positively correlated with TC (RR: 1.05, 95% CI: 1.01–1.10). Similarly, TG was significantly related to breast cancer development after adjustment for baseline lipids (RR: 0.92, 95% CI: 0.85–0.99) and race (any races mentioned in each study) (RR: 1.80, 95% CI: 1.22–2.65). In the present meta-analysis, HDL-C was inversely related to breast cancer risk. Overall, data on the links between lipids and breast cancer are conflicting. However, there is increasing evidence that low HDL-C is related to an increased risk for this type of malignancy.

Integration Profiling Between Plasma Lipidomics, Epstein–Barr Virus and Clinical Phenomes in Nasopharyngeal Carcinoma Patients

Plasma lipidomics has been commonly used for biomarker discovery. Studies in cancer have suggested a significant alteration of circulating metabolite profiles which is correlated with cancer characteristics and treatment outcome. However, the lipidomics characteristics of nasopharyngeal carcinoma (NPC) have rarely been studied. We previously described the phenomenon of lipid droplet accumulation in NPC cells and showed that such accumulation could be regulated by latent infection of Epstein–Barr virus (EBV). Here, we compared the plasma lipidome of NPC patients to that of healthy controls by liquid chromatography-tandem mass spectrometry (LC–MS/MS). We found 19 lipids (e.g., phosphatidylinositols 18:0/20:4 and 18:0/18:2 and free fatty acid 22:6) to be remarkably decreased, whereas 2 lipids (i.e., diacylglycerols 16:0/16:1 and 16:0/20:3) to be increased, in the plasma of NPC patients, compared with controls. Different lipid profiles were also observed between patients with different titers of EBV antibodies (e.g., EA-IgA and VCA-IgA) as well as between patients with and without lymph node or distant organ metastasis. In conclusion, plasma lipidomics might help to differentiate NPC cases from controls, whereas EBV infection might influence the risk and prognosis of NPC through modulating lipid metabolism in both tumor cells and peripheral blood.

Bilayer Forming Phospholipids as Targets for Cancer Therapy

Phospholipids represent a crucial component for the structure of cell membranes. Phosphatidylcholine and phosphatidylethanolamine are two phospholipids that comprise the majority of cell membranes. De novo biosynthesis of phosphatidylcholine and phosphatidylethanolamine occurs via the Kennedy pathway, and perturbations in the regulation of this pathway are linked to a variety of human diseases, including cancer. Altered phosphatidylcholine and phosphatidylethanolamine membrane content, phospholipid metabolite levels, and fatty acid profiles are frequently identified as hallmarks of cancer development and progression. This review summarizes the research on how phospholipid metabolism changes over oncogenic transformation, and how phospholipid profiling can differentiate between human cancer and healthy tissues, with a focus on colorectal cancer, breast cancer, and non-small cell lung cancer. The potential for phospholipids to serve as biomarkers for diagnostics, or as anticancer therapy targets, is also discussed.

Beneficial Effects of Oral Nutritional Supplements on Body Composition and Biochemical Parameters in Women with Breast Cancer Undergoing Postoperative Chemotherapy: A Propensity Score Matching Analysis

Aim: Recently, more attention has been paid to the role of nutritional intervention in preventing the side effects of chemotherapy in oncology patients. Therefore, the aim of the present study was to analyze the effects of oral nutritional supplements on the body composition and biochemical parameters in women with breast cancer receiving postoperative adjuvant chemotherapy. Patients and Methods: The study involved women diagnosed with breast cancer who underwent surgical treatment and were qualified for chemotherapy (doxorubicin and cyclophosphamide). Women were divided into two groups, depending on whether oral nutritional supplements were used during chemotherapy. Anthropometric and biochemical parameters were analyzed twice in all patients: before and after six weeks of chemotherapy. Propensity score (PS) matching was performed to select patients balanced in terms of age, BMI, and clinicopathological features of the tumor. Statistical comparisons were conducted in a propensity-matched cohort of patients. Results: The value of BMI was maintained constant in the supplemented women older than 56 years after six weeks of chemotherapy. Regardless of age in the supplemented women, a significant increase in muscle mass, fat free mass (FFM), and fat free mass index (FFMI) was demonstrated. An increase in fat mass (FM) including visceral fat was observed only in the non-supplemented control. Regardless of age or initial FM, supplemented women exhibited a constant level of albumin. Moreover, in the supplemented women with normal initial FM, the stable values of triglycerides and HDL cholesterol were maintained after six weeks of chemotherapy. Conclusion: The present study demonstrated that oral nutritional supplements could improve body composition and prevent hypoalbuminemia and lipid abnormalities in women with breast cancer undergoing chemotherapy.

Proteomics and its applications in breast cancer

Breast cancer is an individually unique, multi-faceted and chameleonic disease, an eternal challenge for the new era of high-integrated precision diagnostic and personalized oncomedicine. Besides traditional single-omics fields (such as genomics, epigenomics, transcriptomics and metabolomics) and multi-omics contributions (proteogenomics, proteotranscriptomics or reproductomics), several new "-omics" approaches and exciting proteomics subfields are contributing to basic and advanced understanding of these "multiple diseases termed breast cancer": phenomics/cellomics, connectomics and interactomics, secretomics, matrisomics, exosomics, angiomics, chaperomics and epichaperomics, phosphoproteomics, ubiquitinomics, metalloproteomics, terminomics, degradomics and metadegradomics, adhesomics, stressomics, microbiomics, immunomics, salivaomics, materiomics and other biomics. Throughout the extremely complex neoplastic process, a Breast Cancer Cell Continuum Concept (BCCCC) has been modeled in this review as a spatio-temporal and holistic approach, as long as the breast cancer represents a complex cascade comprising successively integrated populations of heterogeneous tumor and cancer-associated cells, that reflect the carcinoma's progression from a "driving mutation" and formation of the breast primary tumor, toward the distant secondary tumors in different tissues and organs, via circulating tumor cell populations. This BCCCC is widely sustained by a Breast Cancer Proteomic Continuum Concept (BCPCC), where each phenotype of neoplastic and tumor-associated cells is characterized by a changing and adaptive proteomic profile detected in solid and liquid minimal invasive biopsies by complex proteomics approaches. Such a profile is created, beginning with the proteomic landscape of different neoplastic cell populations and cancer-associated cells, followed by subsequent analysis of protein biomarkers involved in epithelial-mesenchymal transition and intravasation, circulating tumor cell proteomics, and, finally, by protein biomarkers that highlight the extravasation and distant metastatic invasion. Proteomics technologies are producing important data in breast cancer diagnostic, prognostic, and predictive biomarkers discovery and validation, are detecting genetic aberrations at the proteome level, describing functional and regulatory pathways and emphasizing specific protein and peptide profiles in human tissues, biological fluids, cell lines and animal models. Also, proteomics can identify different breast cancer subtypes and specific protein and proteoform expression, can assess the efficacy of cancer therapies at cellular and tissular level and can even identify new therapeutic target proteins in clinical studies.

Dynamic Changes of Blood Lipids in Breast Cancer Patients After (Neo)adjuvant Chemotherapy: A Retrospective Observational Study

Background

Previous studies indicated that the (neo)adjuvant chemotherapy for breast cancer can cause significant dyslipidemia in patients, but how long this abnormality can persist is unclear so far. The purpose of this study is to investigate whether (neo)adjuvant chemotherapy has a long-term effect on blood lipids in breast cancer patients.

Methods

A total of 159 newly diagnosed female breast cancer patients receiving the (neo)adjuvant chemotherapy subsequently and 159 female healthy controls were enrolled into the observational study. All participants' blood lipid profiles which included TC, TG, HDL-C, and LDL-C before and at the end of the 1st and 12th month after chemotherapy were retrieved from the electronic medical record system. The blood lipid profiles and the percentage of dyslipidemia before and after chemotherapy in breast cancer patients and controls were compared.

Results

Compared with the baseline before chemotherapy, TC, LDL-C, and TG increased significantly at the end of the 1st month after chemotherapy, but only the abnormal increase in TG (2.98±0.71 mmol/L vs 2.82±0.63 mmol/L, P<0.05) and LDL-C (1.82±0.42 mmol/L vs 1.59±0.42 mmol/L, P<0.05) continued until the 12th month after chemotherapy. Levels of HDL-C in breast cancer patients and all the blood lipid parameters in controls remained stable during the observation period. The percentage of dyslipidemia in breast cancer patients rose from 41.5% at baseline to 54.1% at the 12th month after chemotherapy. Subgroup analysis demonstrated that the increase in dyslipidemia percentage was more pronounced in patients with low body mass index and aged over 50 years.

Conclusion

The (neo)adjuvant chemotherapy used for treating breast cancers can cause significant abnormalities in blood lipid profiles, and the abnormal increase in LDL-C and TG can last at least 12 months after chemotherapy, which indicates long-term management of blood lipid is necessary for those patients.