• Blood lipids
• Cancer biomarkers
• Disease-free survival
• Overall survival

• Humans
• Neoplasms/blood
• Neoplasms/mortality
• Prognosis
• Lipids/blood
• Biomarkers, Tumor/blood
• Apolipoprotein A-I/blood
• Dyslipidemias/blood
• Dyslipidemias/mortality
• Triglycerides/blood
• Cholesterol, HDL/blood
• Biomarkers/blood
• Disease-Free Survival
• Cholesterol, LDL/blood

• Lung squamous cell carcinoma
• concurrent chemoradiotherapy
• mortality
• statin
• unresectable

• ApoA-I
• colorectal cancer
• prognostic
• recurrence
• survival

• Humans
• Apolipoprotein A-I/blood
• Colorectal Neoplasms/blood
• Colorectal Neoplasms/mortality
• Male
• Female
• Middle Aged
• Retrospective Studies
• Aged
• Prognosis
• Biomarkers, Tumor/blood
• Survival Rate
• Adult
• Kaplan-Meier Estimate

• Concurrent chemoradiotherapy
• Dose–response relationship
• Nasopharyngeal cancer
• Radiation induced stroke
• Statin

• Humans
• Nasopharyngeal Carcinoma/pathology
• Cohort Studies
• Hydroxymethylglutaryl-CoA Reductase Inhibitors/therapeutic use
• Atorvastatin/therapeutic use
• Pravastatin/therapeutic use
• Stroke/epidemiology
• Stroke/etiology
• Stroke/prevention & control
• Nasopharyngeal Neoplasms/pathology
• Ischemic Stroke/complications
• Ischemic Stroke/drug therapy

• Apolipoprotein A
• Diffuse large B cell lymphoma
• High-density lipoprotein
• Prognosis
• Rituximab
• Serum lipids

The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways—by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of “classical plasma proteins”. Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.

• Biomarkers, Tumor
• Blood Proteins
• Early Detection of Cancer
• Electrophoresis, Gel, Two-Dimensional/methods
• Humans
• Neoplasms/diagnosis
• Proteome/metabolism

• lipid profile
• metabolism
• multiple myeloma
• prognostic model

• IPSS-R
• Myelodysplastic syndromes
• Prognosis
• Serum ApoA1
• TP53

Metabolic syndrome has been identified as a prognostic predictor in multiple cancers. This study aimed to evaluate the impact of metabolic syndrome on the clinical outcome of patients with nasopharyngeal carcinoma (NPC) and its mechanism.

A cohort of 2003 NPC patients with a median follow-up time of 96.3 months (range: 4.1–120.0 months) were enrolled in this analysis. Kaplan–Meier curves and the Log rank test were used to determine the differences in progression-free survival (PFS), cancer specific survival (CSS) and overall survival (OS). Univariate and multivariable analyses were used to identify independent prognostic predictors. Untargeted metabolomics (LC-HRMS) was used to detect the serum metabolic profiles of 10 well-matched patients with or without metabolic syndrome. Differential metabolite-based enrichment analysis and pathway analysis were performed to identify the potential mechanism of metabolic syndrome in NPC.

A total of 171/2003 (8.5%) patients were diagnosed with metabolic syndrome, and these patients tended to be male (P < 0.001) and older (P = 0.003). Patients with metabolic syndrome had poorer PFS (P = 0.011), CSS (P = 0.003) and OS (P = 0.001) than those without metabolic syndrome. Univariate and multivariable analyses showed that metabolic syndrome was a statistically significant and independent predictor for PFS (HR: 1.34, 95% CI: 1.03–1.75, P = 0.032), CSS (HR: 1.53, 95% CI: 1.12–2.08, P = 0.008), and OS (HR: 1.50, 95% CI: 1.13–2.00, P = 0.006). The serum metabolic profile of patients with metabolic syndrome was distinct from that of patients without metabolic syndrome. A total of 319 differential metabolites [log2(FC)>1 or log2 (FC)<-1] were identified and were significantly involved in D-glutamine and D-glutamate metabolism, and valine, leucine and isoleucine biosynthesis.

Metabolic syndrome can serve as a prognostic predictor and guide a more personalized therapy for NPC patients.

• metabolic syndrome
• metabolite
• nasopharyngeal carcinoma
• prognosis
• survival

• Apolipoprotein
• Liver metastasis
• Rectal cancer
• Survival

• Adolescent
• Adult
• Aged
• Antigens, Tumor-Associated, Carbohydrate/blood
• Apolipoprotein A-I/blood
• Apolipoproteins B/blood
• Biomarkers, Tumor/blood
• Combined Modality Therapy
• Female
• Humans
• Kaplan-Meier Estimate
• Liver Neoplasms/diagnosis
• Liver Neoplasms/secondary
• Male
• Middle Aged
• Neoadjuvant Therapy
• Postoperative Period
• Predictive Value of Tests
• Proctectomy
• Proportional Hazards Models
• Rectal Neoplasms/blood
• Rectal Neoplasms/pathology
• Rectal Neoplasms/therapy
• Reference Values
• Young Adult

• 2020A1515011286 Guangdong Basic and Applied Basic Research Foundation, China
• 2020A1515010037 Guangdong Basic and Applied Basic Research Foundation, China

• apolipoprotein AI
• nasopharyngeal carcinoma
• neutrophil
• prognostic
• ratio

At present, the value of lipid indicators in evaluating the prognosis of colorectal cancer is still relatively limited.

To evaluate the value of a novel parameter for colorectal cancer (CRC) prognosis scoring based on preoperative serum lipid levels.

Four key serum lipid factors, namely, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), and apolipoprotein B (ApoB), were detected. Two representative ratios, HDL-C-LDL-C ratio (HLR) and ApoA1-ApoB ratio (ABR) were calculated. The relationship of these parameters with the prognosis of CRC patients including progression-free survival (PFS) and overall survival (OS) was analyzed by Kaplan-Meier plot and Cox proportional hazards regression. A novel lipoprotein cholesterol-apolipoprotein (LA) score based on HLR and ABR was established and its value in prognosis evaluation for CRC patients was explored.

Multivariate Cox proportional hazards regression analysis of PFS and OS showed that HDL-C, ApoA1, HLR, and ABR were positively associated with the prognosis of CRC patients. LA score was independently associated with a good prognosis in resectable CRC patients. Data processing of a dummy variable showed that the prognosis of patients with higher LA scores is better than that with lower LA scores.

The newly established LA score might serve as a better predictor of the prognosis of resectable CRC patients.

• Colorectal cancer
• High-density lipoprotein cholesterol-low-density lipoprotein cholesterol ratio
• Apolipoprotein A1-apolipoprotein B ratio
• Liptein cholesterol-apolipoprotein score
• Prognosis

• Apolipoprotein A-I
• Lung neoplasms
• Prognosis
• Ratio of apolipoprotein B to apolipoprotein A-I

Serum lipids have been reported as prognosticators for malignancies, including rectal cancer (RC). Yet, their value in predicting the response of RC to neoadjuvant chemoradiotherapy (NACRT) remains unknown. This study aimed to assess the predictive abilities of serum lipids for a bad response, and to build a serum lipid-based prediction model.

In total, 751 patients diagnosed with stage cII–III RC and treated with NACRT plus surgery from January 2007 to August 2018 were retrospectively reviewed and randomly divided into two data sets, in a ratio of 1:1. Receiver operating characteristics (ROC) analysis was conducted in the development set to select possible predictors of bad NACRT response from pathoclinical factors, including serum lipids. Multivariate logistic regression was conducted to further determine independent predictors, which were then used to develop a prediction index (PI). Finally, the PI was verified in the validation set, through ROC analysis and chi-squared test.

Five independent predictors were identified: tumor length ≥4 cm, cT4 stage, carcinoembryonic antigen ≥5.0 ng/mL, irradiation with three-dimensional conformal radiotherapy technique, and apolipoprotein A-I ≤1.20 g/L. Each of them was assigned a number of points. In the validation set, the area under the curve of PI appeared as 0.642 (95% confidence interval 0.586–0.697). The sensitivity, specificity, positive and negative predictive values, and concordance were 72.3%, 52.3%, 63.8%, 61.9%, and 63.0%, respectively.

Serum apolipoprotein A-I was found to correlate negatively with the RC response to NACRT. It could serve as a biomarker for guiding individualized treatment and a potential target for improving sensitivity to chemoradiation.

• apolipoprotein A-I
• prediction model
• radiotherapy
• rectal cancer
• tumor response

• Apolipoproteina
• Cancer
• High-density lipoprotein (HDL)

近年来，肺癌成为导致癌症相关死亡的主要原因。越来越多证据表明，许多脂类和脂类类似物是肿瘤发生的关键调节因子，吸烟、饮食及肥胖等影响血脂水平的因素可能与癌症的风险相关。目前随着脂质与肿瘤发生过程关系的研究逐渐深入，探索血脂与肺癌风险及预后相关性已成为研究的热点。本文就血脂水平与肺癌发病风险、血脂水平与肺癌患者预后相关性及调整血脂药物与防治肺癌方向的研究进展进行综述。

• Lipid
• Lung neoplasms
• Prognosis

Predicting the clinical course of prostate cancer is challenging due to the wide biological spectrum of the disease. The objective of our study was to identify prostate cancer prognostic markers in patients ‘sera using a multi-omics discovery platform.

Pre-surgical serum samples collected from a longitudinal, racially diverse, prostate cancer patient cohort (N = 382) were examined. Linear Regression and Bayesian computational approaches integrated with multi-omics, were used to select markers to predict biochemical recurrence (BCR). BCR-free survival was modeled using unadjusted Kaplan–Meier estimation curves and multivariable Cox proportional hazards analysis, adjusted for key pathologic variables. Receiver operating characteristic (ROC) curve statistics were used to examine the predictive value of markers in discriminating BCR events from non-events. The findings were further validated by creating a training set (N = 267) and testing set (N = 115) from the cohort.

Among 382 patients, 72 (19%) experienced a BCR event in a median follow-up time of 6.9 years. Two proteins—Tenascin C (TNC) and Apolipoprotein A1V (Apo-AIV), one metabolite—1-Methyladenosine (1-MA) and one phospholipid molecular species phosphatidic acid (PA) 18:0-22:0 showed a cumulative predictive performance of AUC = 0.78 [OR (95% CI) = 6.56 (2.98–14.40), P < 0.05], in differentiating patients with and without BCR event. In the validation set all four metabolites consistently reproduced an equivalent performance with high negative predictive value (NPV; > 80%) for BCR. The combination of pTstage and Gleason score with the analytes, further increased the sensitivity [AUC = 0.89, 95% (CI) = 4.45–32.05, P < 0.05], with an increased NPV (0.96) and OR (12.4) for BCR. The panel of markers combined with the pathological parameters demonstrated a more accurate prediction of BCR than the pathological parameters alone in prostate cancer.

In this study, a panel of serum analytes were identified that complemented pathologic patient features in predicting prostate cancer progression. This panel offers a new opportunity to complement current prognostic markers and to monitor the potential impact of primary treatment versus surveillance on patient oncological outcome.

• Bayesian networks
• Biochemical recurrence
• Biomarkers
• Metabolomics
• Prostate cancer

Though radiotherapy is a local therapy, it has systemic effects mainly influencing immune and inflammation processes. This has important consequences in the long-term prognosis and therapy individualization. Our objective was to investigate immune and inflammation-related changes in the peripheral blood of head and neck cancer patients treated with radiotherapy. Peripheral blood cells, plasma and blood cell-derived RNA were isolated from 23 patients before and at two time points after radiotherapy and cellular immune parameters, plasma protein changes and gene expression alterations were studied. Increased regulatory T cells and increased CTLA4 and PD-1 expression on CD4 cells indicated an immune suppression induced by the malignant condition, which was accentuated by radiotherapy. Circulating dendritic cells were strongly elevated before treatment and were not affected by radiotherapy. Decreased endoglin levels in the plasma of patients before treatment were further decreased by radiotherapy. Expression of the FXDR, SESN1, GADD45, DDB2 and MDM2 radiation-response genes were altered in the peripheral blood cells of patients after radiotherapy. All changes were long-lasting, detectable one month after radiotherapy. In conclusion we demonstrated radiotherapy-induced changes in systemic immune parameters of head and neck cancer patients and proposed markers suitable for patient stratification worth investigating in larger patient cohorts.

• PBMC
• dendritic cell
• gene expression
• head and neck cancer
• immune phenotyping
• natural killer cell
• plasma proteins
• radiotherapy
• regulatory T cell

Apolipoprotein A-I (ApoA-I), the major protein component of high-density lipoproteins (HDL) is a multifunctional protein, involved in cholesterol traffic and inflammatory and immune response regulation. Many studies revealing alterations of ApoA-I during the development and progression of various types of cancer suggest that serum ApoA-I levels may represent a useful biomarker contributing to better estimation of cancer risk, early cancer diagnosis, follow up, and prognosis stratification of cancer patients. In addition, recent in vitro and animal studies disclose a more direct, tumor suppressive role of ApoA-I in cancer pathogenesis, which involves anti-inflammatory and immune-modulatory mechanisms. Herein, we review recent epidemiologic, clinicopathologic, and mechanistic studies investigating the role of ApoA-I in cancer biology, which suggest that enhancing the tumor suppressive activity of ApoA-I may contribute to better cancer prevention and treatment.

• HDL
• apolipoprotein A-I
• cancer
• immunity
• inflammation
• review

• Apolipoprotein
• Metastasis, Prognosis
• Renal cell carcinoma