Oxidatively modified proteins as plasma biomarkers in breast cancer

Isotypes of autoantibodies against novel differential 4-hydroxy-2-nonenal-modified peptide adducts in serum is associated with rheumatoid arthritis in Taiwanese women

Background

Rheumatoid arthritis (RA) is an autoimmune disorder with systemic inflammation and may be induced by oxidative stress that affects an inflamed joint. Our objectives were to examine isotypes of autoantibodies against 4-hydroxy-2-nonenal (HNE) modifications in RA and associate them with increased levels of autoantibodies in RA patients.

Methods

Serum samples from 155 female patients [60 with RA, 35 with osteoarthritis (OA), and 60 healthy controls (HCs)] were obtained. Four novel differential HNE-modified peptide adducts, complement factor H (CFAH)^1211–1230, haptoglobin (HPT)^78–108, immunoglobulin (Ig) kappa chain C region (IGKC)^2–19, and prothrombin (THRB)^328–345, were re-analyzed using tandem mass spectrometric (MS/MS) spectra (ProteomeXchange: PXD004546) from RA patients vs. HCs. Further, we determined serum protein levels of CFAH, HPT, IGKC and THRB, HNE-protein adducts, and autoantibodies against unmodified and HNE-modified peptides. Significant correlations and odds ratios (ORs) were calculated.

Results

Levels of HPT in RA patients were greatly higher than the levels in HCs. Levels of HNE-protein adducts and autoantibodies in RA patients were significantly greater than those of HCs. IgM anti-HPT⁷⁸⁻¹⁰⁸ HNE, IgM anti-IGKC²⁻¹⁹, and IgM anti-IGKC²⁻¹⁹ HNE may be considered as diagnostic biomarkers for RA. Importantly, elevated levels of IgM anti-HPT⁷⁸⁻¹⁰⁸ HNE, IgM anti-IGKC²⁻¹⁹, and IgG anti-THRB^328−345 were positively correlated with the disease activity score in 28 joints for C-reactive protein (DAS28-CRP). Further, the ORs of RA development through IgM anti-HPT⁷⁸⁻¹⁰⁸ HNE (OR 5.235, p < 0.001), IgM anti-IGKC²⁻¹⁹ (OR 12.655, p < 0.001), and IgG anti-THRB^328−345 (OR 5.761, p < 0.001) showed an increased risk. Lastly, we incorporated three machine learning models to differentiate RA from HC and OA, and performed feature selection to determine discriminative features. Experimental results showed that our proposed method achieved an area under the receiver operating characteristic curve of 0.92, which demonstrated that our selected autoantibodies combined with machine learning can efficiently detect RA.

Conclusions

This study discovered that some IgG- and IgM-NAAs and anti-HNE M-NAAs may be correlated with inflammation and disease activity in RA. Moreover, our findings suggested that IgM anti-HPT⁷⁸⁻¹⁰⁸ HNE, IgM anti-IGKC²⁻¹⁹, and IgG anti-THRB^328−345 may play heavy roles in RA development.

Cumulative receiver operating characteristics for analyzing interaction between tissue visfatin and clinicopathologic factors in breast cancer progression

Background

Visfatin has been reported to be associated with breast cancer progression, but the interaction between the visfatin and clinicopathologic factors in breast cancer progression status requires further investigation. To address this problem, it is better to simultaneously consider multiple factors in sensitivity and specificity assays.

Methods

In this study, a dataset for 105 breast cancer patients (84 disease-free and 21 progressing) were chosen. Individual and cumulative receiver operating characteristics (ROC) were used to analyze the impact of each factor along with interaction effects.

Results

In individual ROC analysis, only 3 of 13 factors showed better performance for area under curve (AUC), i.e., AUC > 7 for hormone therapy (HT), tissue visfatin, and lymph node (LN) metastasis. Under our proposed scoring system, the cumulative ROC analysis provides higher AUC performance (0.746–0.886) than individual ROC analysis in predicting breast cancer progression. Considering the interaction between these factors, a minimum of six factors, including HT, tissue visfatin, LN metastasis, tumor stage, age, and tumor size, were identified as being highly interactive and associated with breast cancer progression, providing potential and optimal discriminators for predicting breast cancer progression.

Conclusion

Taken together, the cumulative ROC analysis provides better prediction for breast cancer progression than individual ROC analysis.

Electronic supplementary material

The online version of this article (10.1186/s12935-018-0517-z) contains supplementary material, which is available to authorized users.

Interaction of MRE11 and Clinicopathologic Characteristics in Recurrence of Breast Cancer: Individual and Cumulated Receiver Operating Characteristic Analyses

The interaction between the meiotic recombination 11 homolog A (MRE11) oncoprotein and breast cancer recurrence status remains unclear. The aim of this study was to assess the interaction between MRE11 and clinicopathologic variables in breast cancer. A dataset for 254 subjects with breast cancer (220 nonrecurrent and 34 recurrent) was used in individual and cumulated receiver operating characteristic (ROC) analyses of MRE11 and 12 clinicopathologic variables for predicting breast cancer recurrence. In individual ROC analysis, the area under curve (AUC) for each predictor of breast cancer recurrence was smaller than 0.7. In cumulated ROC analysis, however, the AUC value for each predictor improved. Ten relevant variables in breast cancer recurrence were used to find the optimal prognostic indicators. The presence of any six of the following ten variables had a high (79%) sensitivity and a high (70%) specificity for predicting breast cancer recurrence: tumor size ≥ 2.4 cm, tumor stage II/III, therapy other than hormone therapy, age ≥ 52 years, MRE11 positive cells > 50%, body mass index ≥ 24, lymph node metastasis, positivity for progesterone receptor, positivity for epidermal growth factor receptor, and negativity for estrogen receptor. In conclusion, this study revealed that these 10 clinicopathologic variables are the minimum discriminators needed for optimal discriminant effectiveness in predicting breast cancer recurrence.

Crucial considerations for pipelines to validate circulating biomarkers for breast cancer

Despite decades of progress in breast imaging, breast cancer remains the second most common cause of cancer mortality in women. The rapidly proliferative breast cancers that are associated with high relapse rates and mortality frequently present in younger women, in unscreened individuals, or in the intervals between screening mammography. Biomarkers exist for monitoring metastatic disease, such as CEA, CA27.29 and CA15-3, but there are no circulating biomarkers clinically available for early detection, prognosis, or monitoring for clinical relapse. There has been significant progress in the discovery of potential circulating biomarkers, including proteins, autoantibodies, nucleic acids, exosomes, and circulating tumor cells, but the vast majority of these biomarkers have not progressed beyond initial research discovery, and none have yet been approved for clinical use in early stage disease. Here, the authors review the crucial considerations of developing pipelines for the rapid evaluation of circulating biomarkers for breast cancer.

4-Hydroxy-nonenal-A Bioactive Lipid Peroxidation Product

This review on recent research advances of the lipid peroxidation product 4-hydroxy-nonenal (HNE) has four major topics: I. the formation of HNE in various organs and tissues, II. the diverse biochemical reactions with Michael adduct formation as the most prominent one, III. the endogenous targets of HNE, primarily peptides and proteins (here the mechanisms of covalent adduct formation are described and the (patho-) physiological consequences discussed), and IV. the metabolism of HNE leading to a great number of degradation products, some of which are excreted in urine and may serve as non-invasive biomarkers of oxidative stress.