The availability of blood-based diagnostic testing using a non-invasive technique holds promise for real-time monitoring of disease progression and treatment selection. Circulating tumor cells (CTCs) have been used as a prognostic biomarker for the metastatic breast cancer (MBC). The molecular characterization of CTCs is fundamental to the phenotypic identification of malignant cells and description of the relevant genetic alterations that may change according to disease progression and therapy resistance. However, the molecular characterization of CTCs remains a challenge because of the rarity and heterogeneity of CTCs and technological difficulties in the enrichment, isolation and molecular characterization of CTCs. In this pilot study, we evaluated circulating tumor associated cells in one blood draw by size exclusion technology and cytological analysis. Among 30 prospectively enrolled MBC patients, CTCs, circulating tumor cell clusters (CTC clusters), CTCs of epithelial–mesenchymal transition (EMT) and cancer associated macrophage-like cells (CAMLs) were detected and analyzed. For molecular characterization of CTCs, size-exclusion method for CTC enrichment was tested in combination with DEPArray™ technology, which allows the recovery of single CTCs or pools of CTCs as a pure CTC sample for mutation analysis. Genomic mutations of TP53 and ESR1 were analyzed by targeted sequencing on isolated 7 CTCs from a patient with MBC. The results of genomic analysis showed heterozygous TP53 R248W mutation from one single CTC and pools of three CTCs, and homozygous TP53 R248W mutation from one single CTC and pools of two CTCs. Wild-type ESR1 was detected in the same isolated CTCs. The results of this study reveal that size-exclusion method can be used to enrich and identify circulating tumor associated cells, and enriched CTCs were characterized for genetic alterations in MBC patients, respectively.

Background: The neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and circulating tumor cells (CTCs) have been associated with survival in castration-resistant prostate cancer (CRPC). However, no study has examined the prognostic value of NLR and PLR in the context of CTCs. Methods: Baseline CTCs from mCRPC patients were enumerated using the CellSearch System. Baseline NLR and PLR values were calculated using the data from routine complete blood counts. The associations of CTC, NLR, and PLR values, individually and jointly, with progression-free survival (PFS) and overall survival (OS), were evaluated using Kaplan-Meier analysis, as well as univariate and multivariate Cox models. Results: CTCs were detected in 37 (58.7%) of 63 mCRPC patients, and among them, 16 (25.4%) had ≥5 CTCs. The presence of CTCs was significantly associated with a 4.02-fold increased risk for progression and a 3.72-fold increased risk of death during a median follow-up of 17.6 months. OS was shorter among patients with high levels of NLR or PLR than those with low levels (log-rank P = 0.023 and 0.077). Neither NLR nor PLR was individually associated with PFS. Among the 37 patients with detectable CTCs, those with a high NLR had significantly shorter OS (log-rank P = 0.024); however, among the 26 patients without CTCs, the OS difference between high- and low-NLR groups was not statistically significant. Compared to the patients with CTCs and low NLR, those with CTCs and high levels of NLR had a 3.79-fold risk of death (P = 0.036). This association remained significant after adjusting for covariates (P = 0.031). Combination analyses of CTC and PLR did not yield significant results. Conclusion: Among patients with detectable CTCs, the use of NLR could further classify patients into different risk groups, suggesting a complementary role for NLR in CTC-based prognostic stratification in mCRPC.

The prognostic value of routine laboratory variables in breast cancer has been largely overlooked. Based on laboratory tests commonly performed in clinical practice, we aimed to develop a new model to predict disease free survival (DFS) after surgical removal of primary breast cancer. In a cohort of 1,596 breast cancer patients, we analyzed the associations of 33 laboratory variables with patient DFS. Based on 3 significant laboratory variables (hemoglobin, alkaline phosphatase, and international normalized ratio), together with important demographic and clinical variables, we developed a prognostic model, achieving the area under the curve of 0.79. We categorized patients into 3 risk groups according to the prognostic index developed from the final model. Compared with the patients in the low-risk group, those in the medium- and high-risk group had a significantly increased risk of recurrence with a hazard ratio (HR) of 1.75 (95% confidence interval [CI] 1.30–2.38) and 4.66 (95% CI 3.54–6.14), respectively. The results from the training set were validated in the testing set. Overall, our prognostic model incorporating readily available routine laboratory tests is powerful in identifying breast cancer patients who are at high risk of recurrence. Further study is warranted to validate its clinical application.

Liquid biopsy-based biomarkers have advantages in monitoring the dynamics of metastatic castration-resistant prostate cancer (mCRPC), a bone-predominant metastatic disease. Previous studies have demonstrated associations between circulating tumor cells (CTCs) and clinical outcomes of mCRPC patients, but little is known about the prognostic value of CTC-clusters. In 227 longitudinally collected blood samples from 64 mCRPC patients, CTCs and CTC-clusters were enumerated using the CellSearch platform. The associations of CTC and CTC-cluster counts with progression-free survival (PFS) and overall survival (OS), individually and jointly, were evaluated by Cox models. CTCs and CTC-clusters were detected in 24 (37.5%) and 8 (12.5%) of 64 baseline samples, and in 119 (52.4%) and 27 (11.9%) of 227 longitudinal samples, respectively. CTC counts were associated with both PFS and OS, but CTC-clusters were only independently associated with an increased risk of death. Among patients with unfavorable CTCs (≥5), the presence of CTC-clusters signified a worse survival (log-rank p = 0.0185). mCRPC patients with both unfavorable CTCs and CTC-clusters had the highest risk for death (adjusted hazard ratio 19.84, p = 0.0072), as compared to those with <5 CTCs. Analyses using longitudinal data yielded similar results. In conclusion, CTC-clusters provided additional prognostic information for further stratifying death risk among patients with unfavorable CTCs.

Previous studies have detected a higher level of ferritin in patients with hepatocellular carcinoma (HCC), but a potential causal association between serum ferritin level and hepatocarcinogenesis remains to be clarified. Using a well‑established prospective cohort and longitudinally collected serial blood samples, the association between baseline ferritin levels and HCC risk were evaluated in 1,152 patients infected with hepatitis B virus (HBV), a major risk factor for HCC. The association was assessed by Cox proportional hazards regression model using univariate and multivariate analyses and longitudinal analysis. It was demonstrated that HBV patients who developed HCC had a significantly higher baseline ferritin level than those who remained cancer‑free (188.00 vs. 108.00 ng/ml, P<0.0001). The patients with a high ferritin level (≥200 ng/ml) had 2.43‑fold increased risk of HCC compared to those with lower ferritin levels [hazard ratio (HR), 2.43; 95% confidence interval, 1.63‑3.63]. A significant trend of increasing HRs along with elevated ferritin levels was observed (P for trend <0.0001). The association was still significant after multivariate adjustment. Incorporating ferritin into the α‑fetoprotein (AFP) model significantly improved the performance of HCC prediction (the area under the curve from 0.74 to 0.77, P=0.003). Longitudinal analysis showed that the average ferritin level in HBV patients who developed HCC was persistently higher than in those who were cancer‑free during follow‑up. HCC risk reached a peak at approximately the fifth year after baseline ferritin detection. Moreover, stratified analyses showed that the association was noted in both males and females, and was prominent in patients with a low AFP value. In short, serum ferritin level could independently predict the risk of HBV‑related HCC and may have a complementary role in AFP‑based HCC diagnosis. Future studies are warranted to validate these findings and test its clinical applicability in HCC prevention and management.

Objectives. AQP7 and AQP9 represent glycerol channel in adipose tissue and liver and have been associated with metabolic diseases. We aimed to investigate the associations between genetic variants in AQP7 and AQP9 genes and the risk of type 2 diabetes (T2DM) in Chinese population. Methods. Blood samples were drawn from 400 T2DM patients and 400 age- and gender-matched controls. Genomic DNA was extracted by proteinase K digestion and phenol–chloroform extraction. Genotyping of 5 single nucleotide polymorphisms (SNPs) in AQP7 (rs2989924, rs3758269, and rs62542743) and AQP9 (rs57139208, rs16939881) was performed by the polymerase chain reaction assay with TaqMan probes. Results. The subjects with rs2989924 GA+AA genotypes had 1.47-fold increased risk of T2DM (odds ratio [OR] 1.47, 95% confidence interval [CI] 1.06-2.04), compared to those with GG genotype, and this association remained significant after adjustment for covariates (OR 1.66, 95% CI 1.07-2.57). When compared with rs3758269 CC genotype, the subjects with CT+TT genotypes had 45% decreased T2DM risk after multivariate adjustment (OR 0.55, 95% CI 0.35-0.85). The associations were evident in elder and overweight subjects and those with central obesity. No association was observed between AQP9 SNPs and T2DM risk. Conclusions. AQP7 SNP rs2989924 and rs3758269 were associated with T2DM risk in Chinese Han population.