Serum lipid profiles: novel biomarkers predicting advanced prostate cancer in patients receiving radical prostatectomy

Carbohydrate antigen 125, carbohydrate antigen 15-3 and low-density lipoprotein as risk factors for intraocular metastases in postmenopausal breast cancer

The prognosis of patients with postmenopausal breast cancer (PBC) could be improved by the early detection of intraocular metastases (IOMs). However, serum biomarkers for IOMs in PBC remain elusive. In the current study, we investigated patients with PBC, and compared serum parameters in an IOM and a non-IOM group, and then differentiated the risk factors related to IOMs. A comparison between an IOM and a non-IOM (NIOM) group was performed using Student t-test and a Chi-Squared test. After constructing a Poisson regression model to identify risk factors, we plotted receiver operating characteristic curves to evaluate the predictive value of significant risk factors in detecting IOMs. The incidence of IOMs in PBC was 1.16%. The histopathology results were not significantly different between the 2 groups. The levels of serum carbohydrate antigen 125 (CA-125), carbohydrate antigen 15-3 (CA15-3) and alkaline phosphatase were significantly elevated in IOMs compared with NIOMs (P = .082, P < .001, and P < .001, respectively). Compared with NIOMs, age, carbohydrate antigen 19 to 9, hemoglobin, calcium, total cholesterol, low-density lipoprotein (LDL) and apolipoprotein A1 were remarkably lower in IOMs (P = .038, P < .001, P < .001, P = .032, P = .041, P < .001, and P = .001, respectively). Poisson regression suggested that CA-125, CA15-3 and LDL were contributing to IOMs in PBC as risk factors (OR = 1.003, 95% CI: 1.001-1.005; OR = 1.025, 95% CI: 1.019-1.033; OR = 0.238, 95% CI: 0.112-0.505, respectively). A receiver operating characteristic curve revealed that the cut-off values for CA-125, CA15-3 and LDL were 16.78 0 U/mL, 63.175 U/mL, and 2.415 mmol/L, respectively. The combination of CA-125 and CA15-3 showed significant diagnostic value (area under the curve [AUC] = 0.982, P < .001). Our investigation suggests that CA-125, CA15-3 and LDL remarkably predict IOMs in PBC as risk factors, and the combination of CA-125 and CA15-3 shows considerable diagnostic value.

Metabolically Abnormal Obesity Increases the Risk of Advanced Prostate Cancer in Chinese Patients Undergoing Radical Prostatectomy

Background

To investigate the pathological risk of prostate cancer (PCa) according to the obesity and metabolic status of Chinese patients undergoing radical prostatectomy.

Materials and Methods

We performed a retrospective cross-sectional study of 1016 patients with PCa who underwent radical prostatectomy and whose metabolic status and body mass index were examined. Multivariate logistic regression analysis was performed to examine the relationship between different metabolic obesity phenotypes and the pathological outcomes of PCa.

Results

Among 1016 men, 551 (54.2%), 106 (10.4%), 238 (23.4%), and 121 (11.9%) were assigned to the metabolically healthy and normal weight (MHNW) group, metabolically abnormal but normal weight (MANW) group, metabolically healthy but overweight or obese (MHO) group, and metabolically abnormal and overweight or obese (MAO) group, respectively. Compared with the MHNW group, the MAO group had a significantly greater risk of a higher prostatectomy Gleason score [odds ratio (OR), 1.907; 95% confidence interval (95% CI), 1.144–3.182], pathological stage (OR, 1.606; 95% CI, 1.035–2.493), and seminal vesicle invasion (OR, 1.673; 95% CI, 1.041–2.687). In contrast, the ORs were not increased in the MHO or MANW group. In the context of normal weight, metabolic disorders were associated with lymph node involvement. The metabolic status and body mass index were not associated with extracapsular extension or surgical margins in any of the four groups.

Conclusion

The MAO phenotype is associated with aggressive PCa, including a higher prostatectomy Gleason score, pathological stage, and seminal vesicle invasion and might also be associated with disease progression. Obesity and metabolic disorders act synergistically to increase the pathological risk of PCa.

The Adverse Effects of Androgen Deprivation Therapy in Prostate Cancer and the Benefits and Potential Anti-oncogenic Mechanisms of Progressive Resistance Training

Prostate cancer has the second highest incidence of all cancers amongst men worldwide. Androgen deprivation therapy (ADT) remains a common form of treatment. However, in reducing serum testosterone to castrate levels and rendering men hypogonadal, ADT contributes to a myriad of adverse effects which can affect prostate cancer prognosis. Physical activity is currently recommended as synergistic medicine in prostate cancer patients to alleviate the adverse effects of treatment. Progressive resistance training (PRT) is an anabolic exercise modality which may be of benefit in prostate cancer patients given its potency in maintaining and positively adapting skeletal muscle. However, currently, there is a scarcity of RCTs which have evaluated the use of isolated PRT in counteracting the adverse effects of prostate cancer treatment. Moreover, although physical activity in general has been found to reduce relapse rates and improve survival in prostate cancer, the precise anti-oncogenic effects of specific exercise modalities, including PRT, have not been fully established. Thus, the overall objective of this article is to provide a rationale for the in-depth investigation of PRT and its biological effects in men with prostate cancer on ADT. This will be achieved by (1) summarising the metabolic effects of ADT in patients with prostate cancer and its effect on prostate cancer progression and prognosis, (2) reviewing the existing evidence regarding the metabolic benefits of PRT in this cohort, (3) exploring the possible oncological pathways by which PRT can affect prostate cancer prognosis and progression and (4) outlining avenues for future research.

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

Breast cancer is the major mortality cause of women worldwide. In the course of management of breast cancer, the identification of a biomarker is important in enhancing our knowledge on cancer pathology, predicting the response to treatment, and selecting the patients who are more favorable to receive certain treatments. These biomarkers have a prognostic value. In addition to traditional breast cancer prognosis factors such as the tumor size and grade, the axillary lymph node micrometastasis, and biomarkers such as HER2/neu, newly discovered biomarkers have been discovered. Some of these factors are genetic signature in tissue or in peripheral blood. Lipid profil, a simple and accessible biological examination, has been a novel path on the prediction of breast cancer risk of occurrence and recurrence in many studies. The main goal of our review is to evaluate lipid profile and breast cancer risk with an emphasis on the prognosis value of lipid profiles in breast cancer patient management.

Serum lipids might improve prostate-specific antigen sensitivity in patients undergoing transrectal ultrasonography-guided biopsy for suspected prostate cancer: A pilot study

Objectives: To investigate the potential use of body mass index (BMI) and serum lipids in improving prostate-specific antigen (PSA) sensitivity in patients undergoing biopsy for suspicion of prostate cancer, as there is an established relationship between metabolic syndrome, obesity and serum lipids with prostate cancer.

Patients and methods: A pilot study was conducted in a tertiary referral centre between June 2016 and August 2017 of patients undergoing transrectal ultrasonography (TRUS)-guided biopsy. After the result of TRUS-biopsy, the first 50 patients diagnosed with prostate cancer (study group) and those with no prostate cancer (control group) were enrolled. BMI, serum PSA level, fasting blood sugar and lipid profile (e.g. cholesterol, triglycerides, low-density lipoprotein [LDL] and high-density lipoprotein [HDL]), were compared between the groups.

Results: Higher BMI, cholesterol, LDL and lower HDL together with PSA were significantly associated with a positive biopsy. On multivariate analysis, LDL (odds ratio [OR] 5.3, 95% confidence interval [CI] 1.2–24.9; P = 0.03) and total PSA level (OR 12.9, 95% CI 4.7–35; P < 0.001) were independent predictors of a positive biopsy. A combination of LDL <80 mg/dL and PSA level <26 ng/mL threshold values determined by receiver operating characteristic curve analysis, had a sensitivity and specificity of 94% and 28%, respectively; whilst, the negative (NPV) and positive predictive values were 82.4% and 56.6%, respectively. The sensitivity and NPV of the combination was significantly higher than that of PSA level alone (94% vs 72% and 82.4% vs 75%, respectively; P < 0.001).

Conclusions: Serum lipids might have a role in the diagnosis of prostate cancer and could be used as an adjunct to PSA measurement to improve sensitivity and avoid unnecessary biopsies.

Abbreviations: AUC: area under the curve; BMI: body mass index; FBS: fasting blood sugar; HDL: high-density lipoprotein; LDL: low-density lipoprotein; LOX-1: lectin-like oxidised LDL receptor-1; OR: odds ratio; ROC: receiver operating characteristic; RP: radical prostatectomy; TG: triglyceride

Obesity is a predictor in prostate cancer patients receiving prostatectomy after neoadjuvant hormonal therapy

OBJECTIVE

This study aimed to investigate the relationship between obesity and pathologic features and biochemical recurrence in patients with prostate cancer (PCa) undergoing radical prostatectomy (RP) after neoadjuvant hormonal therapy (NHT).

METHODS

A total of 422 consecutive patients with clinically localized PCa who received NHT before RP were retrospectively analyzed. Unconditional multiple logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) regarding probability. A receiver operating characteristic (ROC) curve was used to assess the efficacy of the predictive variables. Castration resistance free survival curves were obtained using the Kaplan-Meier method, and were compared using the log-rank test.

RESULTS

Being overweight was associated with an increased risk of positive margins (OR 2.281; 95% CI 1.292-4.028) after adjusting for potential confounders. The area under the ROC curve for overweight patients was larger than that for patients in the normal weight range. There was no significant difference between the overweight and normal weight groups regarding castration resistance free survival.

CONCLUSIONS

Being overweight was associated with positive margins in patients with PCa undergoing RP after NHT.

Prostate Cancer Development Is Not Affected by Statin Use in Patients with Elevated PSA Levels

Background: The role of statins in prostate cancer (PCa) remains unclear. Conflicting evidence has been found concerning risk reduction with the use of statins on biochemical recurrence (BCR). In this study, we evaluated whether statin use decreases the incidence of advanced PCa in males with elevated prostate-specific antigen (PSA; ≥4.0 ng/mL) levels and determined whether statin use reduces the risk of BCR after radical prostatectomy (RP). Methods: Patients visiting the outpatient urology clinic of the VU Medical Center between 2006 and 2018 with elevated PSA were retrospectively analyzed. Biochemical recurrence after RP was defined as a PSA level of ≥0.2 ng/mL (measured twice). Results: A total of 1566 patients were included, of which 1122 (72%) were diagnosed with PCa. At the time of diagnosis, 252 patients (23%) used statins compared to 83 patients (19%) in the non-malignancy group (p = 0.10). No differences were found in the use of statins between the different risk groups. No correlation was found between the risk of BCR after RP and the use of statins in the total (p = 0.20), the intermediate-risk group (p = 0.63) or the high-risk group (p = 0.14). Conclusion: The use of statins does not affect PCa development/progression in patients with elevated PSA levels, nor the development of BCR after RP.

Prognostic value of lipid profiles after radical prostatectomy: a systematic review and meta-analysis

Background

Lipid profiles are believed to play an important role in the tumorigenesis and progression of prostate cancer (PCa), but research combining those data is lacking. Therefore, this meta-analysis aims to assess the prognostic role of lipid profiles after RP.

Method

We systematically searched PubMed, Embase, and Cochrane Library Central Register of Controlled Trials for articles evaluating association between lipid profiles and prognosis after RP. Odds ratio (OR) and hazard ratio (HR) of lipid profiles for advanced pathological tumor features and biochemical recurrence (BCR) were extracted and pooled OR and HR were calculated. Newcastle-Ottawa scale was used for study quality assessment and funnel plot was used for evaluating publication bias.

Results

Twelve articles involving 11,108 patients were eventually selected. We found low HDL was associated with more frequent occurrence of pathological T stage (pT) ≥ T3 (pooled OR = 1.29, 95% CI 1.07–1.56) and Gleason score (GS) ≥8 (pooled OR = 1.32, 95% CI 1.02–1.72) after RP. Hypertriglyceridemia was also linked with higher risk of pT ≥ T3 (pooled OR = 1.20, 95% CI 1.01–1.42) and positive surgical margin (PSM) (pooled OR = 1.36, 95% CI 1.11–1.65). However, no significant association was observed between BCR and abnormal lipid profile levels.

Conclusion

Low HDL level was associated with more common occurrence of pT ≥ T3 and GS ≥8, and elevated triglycerides level was linked higher risk of pT ≥ T3 and PSM, but none of the lipid subfractions was correlated with biochemical recurrence after RP.

Electronic supplementary material

The online version of this article (10.1186/s12944-019-1068-6) contains supplementary material, which is available to authorized users.

Influence of serum cholesterol level and statin treatment on prostate cancer aggressiveness

Both cholesterol levels and the use of statins have been described to influence the development and prognosis of prostate cancer (PC). In this retrospective, cross-sectional analysis of consecutive cases from a tertiary referral center we evaluated an association between hypercholesterolemia (≥5.0mmol/l), the use of statins, and advanced/aggressive PC in 767 men with histologically confirmed, clinically localized PC awaiting radical prostatectomy. We found that patients with HCE (n=287, 37.4%) had a significantly higher incidence of poorly differentiated PC (Gleason score ≥7b, 81.1% vs. 4.9%), advanced local tumor stage (≥pT3, 57.7% vs. 22.2%), and nodal involvement (19.8% vs. 1.6%). Multivariate logistic regression analysis identified hypercholesterolemia as a risk factor for aggressive and/or advanced PC (OR 2.01, p<0.001) whereas statin intake showed an odds ratio of 0.49 (p=0.005) indicating a negative association with high-risk PC. Despite a limited number of patients using statins (~9.5%), adjusted and weighed multivariate logistic regression models revealed that preoperative hypercholesterolemia is associated with a diagnosis of high-risk PC which is negatively influenced by statin intake.

Plasma lipidomics profiling identified lipid biomarkers in distinguishing early-stage breast cancer from benign lesions

BACKGROUND

Breast cancer is very common and highly fatal in women. Current non-invasive detection methods like mammograms are unsatisfactory. Lipidomics, a promising detection method, may serve as a novel prognostic approach for breast cancer in high-risk patients.

RESULTS

According the predictive model, the combination of 15 lipid species had high diagnostic value. In the training set, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the combination of these 15 lipid species were 83.3%, 92.7%, 89.7%, and 87.9%, respectively. The AUC in the training set was 0.926 (95% CI 0.869-0.982). Similar results were found in the validation set, with the sensitivity, specificity, PPV and NPV at 81.0%, 94.5%, 91.9%, and 86.7%, respectively. The AUC was 0.938 (95% CI 0.889-0.986) in the validation set.

METHODS

Using triple quadrupole liquid chromatography electrospray ionization tandem mass spectrometry, this study was to detect global lipid profiling of a total of 194 plasma samples from 84 patients with early-stage breast cancer (stage 0-II) and 110 patients with benign breast disease included in a training set and a validation set. A binary logistic regression was used to build a predictive model for evaluating the lipid species as potential biomarkers in the diagnosis of breast cancer.

CONCLUSIONS

The combination of these 15 lipid species as a panel could be used as plasma biomarkers for the diagnosis of breast cancer.

Potential plasma lipid biomarkers in early-stage breast cancer

OBJECTIVE

To find new biomarkers for early diagnosis of breast cancer.

RESULTS

847 lipid species were identified from 78 plasma samples (37 breast cancer samples and 41 healthy controls) by ultra HPLC coupled with quadrupole time-of-flight tandem mass spectrometry. These include 321 glycerophospholipids (GPs), 265 glycerolipids (GLs), 91 sphingolipids (SPs), 77 fatty acyls (FAs), 68 sterol lipids (STs), 18 prenol lipids (PRs), 6 polyketides (PKs), and 1 saccharolipid (SL). Separation was observed from an orthogonal signal correction Partial Least Square Discrimination Analysis model. Based on this analysis, six differentiating lipids were identified: PC (20:2/20:5), PC (22:0/24:1), TG (12:0/14:1), and DG (18:1/18:2) had high levels, whereas PE (15:0/19:1) and N-palmitoyl proline had low levels in the breast cancer samples compared with the healthy controls. Furthermore, significant differences in metabolites were found among some clinical characteristics.

CONCLUSIONS

Our results reveal that six specific lipids could serve as potential biomarkers for early diagnosis of breast cancer.