Assessment of Serum Tumor Markers for Predicting Ocular Metastasis in Lung Adenocarcinoma: A Retrospective Study.

The purpose of this study was to detect clinical variations between lung adenocarcinoma patients with and without ocular metastasis (OM) to identify risk factors for OM and assess the diagnostic values. We included 1153 patients with lung adenocarcinoma in this study. Independent t-tests and chi-square tests were used to compare patients' clinical characteristics. Statistically significant parameters were analyzed by binary logistic regression to detect risk factors of OM. The results showed that the OM group had increased alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), cytokeratin fragment 19 (CYFRA 21-1), carbohydrate antigen- (CA-) 125, CA-153, and total prostate-specific antigen (TPSA) compared with the NOM group. CYFRA21-1 is the most useful biomarker for detecting OM in this population.

Assessment of associations between clinical and immune microenvironmental factors and tumor mutation burden in resected nonsmall cell lung cancer by applying machine learning to whole-slide images.

BACKGROUND: It is unclear whether clinical factors and immune microenvironment (IME) factors are associated with tumor mutation burden (TMB) in patients with nonsmall cell lung cancer (NSCLC). MATERIALS AND METHODS: We assessed TMB in surgical tumor specimens by performing whole exome sequencing. IME profiles, including PD-L1 tumor proportion score (TPS), stromal CD8 tumor-infiltrating lymphocyte (TIL) density, and stromal Foxp3 TIL density, were quantified by digital pathology using a machine learning algorithm. To detect factors associated with TMB, clinical data, and IME factors were assessed by means of a multiple regression model. RESULTS: We analyzed tumors from 200 of the 246 surgically resected NSCLC patients between September 2014 and September 2015. Patient background: median age (range) 70 years (39-87); male 37.5%; smoker 27.5%; pathological stage (p-stage) I/II/III, 63.5/22.5/14.0%; histological type Ad/Sq, 77.0/23.0%; primary tumor location upper/lower, 58.5/41.5%; median PET SUV 7.5 (0.86-29.8); median serum CEA (sCEA) level 3.4 ng/mL (0.5-144.3); median serum CYFRA 21-1 (sCYFRA) level 1.2 ng/mL (1.0-38.0); median TMB 2.19/ Mb (0.12-64.38); median PD-L1 TPS 15.1% (0.09-77.4); median stromal CD8 TIL density 582.1/mm2 (120.0-4967.6);, and median stromal Foxp3 TIL density 183.7/mm2 (6.3-544.0). The multiple regression analysis identified three factors associated with higher TMB: smoking status: smoker, increase PET SUV, and sCEA level: >5 ng/mL (P < .001, P < .001, and P = .006, respectively). CONCLUSIONS: The IME factors assessed were not associated with TMB, but our findings showed that, in addition to smoking, PET SUV and sCEA levels may be independent predictors of TMB. TMB and IME factors are independent factors in resected NSCLC.

Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins.

Importance: There is an urgent need to improve lung cancer risk assessment because current screening criteria miss a large proportion of cases. Objective: To investigate whether a lung cancer risk prediction model based on a panel of selected circulating protein biomarkers can outperform a traditional risk prediction model and current US screening criteria. Design, Setting, and Participants: Prediagnostic samples from 108 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and samples from 216 smoking-matched controls from the Carotene and Retinol Efficacy Trial (CARET) cohort were used to develop a biomarker risk score based on 4 proteins (cancer antigen 125 [CA125], carcinoembryonic antigen [CEA], cytokeratin-19 fragment [CYFRA 21-1], and the precursor form of surfactant protein B [Pro-SFTPB]). The biomarker score was subsequently validated blindly using absolute risk estimates among 63 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and 90 matched controls from 2 large European population-based cohorts, the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Northern Sweden Health and Disease Study (NSHDS). Main Outcomes and Measures: Model validity in discriminating between future lung cancer cases and controls. Discrimination estimates were weighted to reflect the background populations of EPIC and NSHDS validation studies (area under the receiver-operating characteristics curve [AUC], sensitivity, and specificity). Results: In the validation study of 63 ever-smoking patients with lung cancer and 90 matched controls (mean [SD] age, 57.7 [8.7] years; 68.6% men) from EPIC and NSHDS, an integrated risk prediction model that combined smoking exposure with the biomarker score yielded an AUC of 0.83 (95% CI, 0.76-0.90) compared with 0.73 (95% CI, 0.64-0.82) for a model based on smoking exposure alone (P = .003 for difference in AUC). At an overall specificity of 0.83, based on the US Preventive Services Task Force screening criteria, the sensitivity of the integrated risk prediction (biomarker) model was 0.63 compared with 0.43 for the smoking model. Conversely, at an overall sensitivity of 0.42, based on the US Preventive Services Task Force screening criteria, the integrated risk prediction model yielded a specificity of 0.95 compared with 0.86 for the smoking model. Conclusions and Relevance: This study provided a proof of principle in showing that a panel of circulating protein biomarkers may improve lung cancer risk assessment and may be used to define eligibility for computed tomography screening.

Serum cytokeratin 19 fragment 21-1 is a useful tumor marker for the assessment of extramammary Paget's disease.

Cytokeratin 19 fragment 21-1 (CYFRA 21-1) has been used as a tumor marker for several malignancies. However, to date, no studies have assessed whether CYFRA 21-1 could be a useful marker for extramammary Paget's disease (EMPD). The present study aimed to evaluate the significance of CYFRA 21-1 as a serum tumor marker for EMPD progression. Concentrations of serum CYFRA 21-1 and carcinoembryonic antigen (CEA) in 13 cases of EMPD were measured prior to undergoing treatment at Sapporo Medical University Hospital from January 2014 to May 2016. Four of the 13 patients had lymph node metastases at diagnosis, but none had distant metastases. Immunohistochemistry indicated that all 13 primary tumors and four metastatic tumors in lymph nodes were positive for cytokeratin 19. Although none of the 13 patients showed high serum CEA levels, six patients (46.2%) had elevated serum CYFRA 21-1. Furthermore, CYFRA 21-1 was reduced in association with post-treatment tumor reduction in all six patients. Among these six patients, four developed recurrence and metastasis during the follow-up period. CYFRA 21-1 was re-elevated in all four of these patients; however, serum CEA was elevated only in the patient with distant metastasis. These results suggest that CYFRA 21-1 is more sensitive compared with CEA, and can be useful as a tumor marker for evaluating tumor progression and treatment efficacy in patients with EMPD.

Assessment of Relationship Between CT Features and Serum Tumor Marker Index in Early-stage Lung Adenocarcinoma.

RATIONALE AND OBJECTIVES: The study aimed to assess the relationship between tumor marker index (TMI) and high-resolution computed tomography features in early-stage lung adenocarcinoma. MATERIALS AND METHODS: Seventy-four stage IA lung adenocarcinomas confirmed pathologically were retrospectively evaluated. Lung nodules were divided into two types: solid nodule (SN) and subsolid nodule (SSN). The maximum diameters on mediastinal window in axial imaging (Dm) and tumor shadow disappearance rate (TDR) were measured. Meanwhile, other computed tomography features of lung nodules were also recorded. TMI represents the geometric mean of normalized CEA and CYFRA 21-1 values, and the discriminatory value of TMI in this study was set at 1.0. The evaluation of discriminatory values for Dm and the TMI between SNs and SSNs was done with Mann-Whitney U-test. The relationship between TDR and TMI in SSNs was evaluated by Pearson correlation analysis. RESULTS: Of 74 cases, 40 cases (54.05%) showed SNs and 34 cases (45.95%) showed SSNs. Dm and TMI were higher in SNs than in SSNs (z = -4.782, P < 0.001; z = -2.647, P = 0.008). TDR demonstrated negative relationship with TMI in SSNs (r = -0.448, P = 0.008). Spiculation (odds ratio [OR] = 14.685; 95% confidence interval [CI]: 2.739-78.729; P = 0.002), nodule type (OR = 6.215; 95% CI: 1.531-25.228; P = 0.011), and gender (OR = 0.227; 95% CI: 0.062-0.833; P = 0.025) were independent factors associated with TMI. CONCLUSIONS: Early-stage lung adenocarcinoma with lower TDR coexisting with spiculation was associated with higher TMI, especially in patients with solid nodule, which tended to have poor prognosis.

Cancers Screening in an Asymptomatic Population by Using Multiple Tumour Markers.

BACKGROUND: Analytic measurement of serum tumour markers is one of commonly used methods for cancer risk management in certain areas of the world (e.g. Taiwan). Recently, cancer screening based on multiple serum tumour markers has been frequently discussed. However, the risk-benefit outcomes appear to be unfavourable for patients because of the low sensitivity and specificity. In this study, cancer screening models based on multiple serum tumour markers were designed using machine learning methods, namely support vector machine (SVM), k-nearest neighbour (KNN), and logistic regression, to improve the screening performance for multiple cancers in a large asymptomatic population. METHODS: AFP, CEA, CA19-9, CYFRA21-1, and SCC were determined for 20 696 eligible individuals. PSA was measured in men and CA15-3 and CA125 in women. A variable selection process was applied to select robust variables from these serum tumour markers to design cancer detection models. The sensitivity, specificity, positive predictive value (PPV), negative predictive value, area under the curve, and Youden index of the models based on single tumour markers, combined test, and machine learning methods were compared. Moreover, relative risk reduction, absolute risk reduction (ARR), and absolute risk increase (ARI) were evaluated. RESULTS: To design cancer detection models using machine learning methods, CYFRA21-1 and SCC were selected for women, and all tumour markers were selected for men. SVM and KNN models significantly outperformed the single tumour markers and the combined test for men. All 3 studied machine learning methods outperformed single tumour markers and the combined test for women. For either men or women, the ARRs were between 0.003-0.008; the ARIs were between 0.119-0.306. CONCLUSION: Machine learning methods outperformed the combined test in analysing multiple tumour markers for cancer detection. However, cancer screening based solely on the application of multiple tumour markers remains unfavourable because of the inadequate PPV, ARR, and ARI, even when machine learning methods were incorporated into the analysis.

The assessment of the prognostic value of tumor markers and cytokines as SCCAg, CYFRA 21.1, IL-6, VEGF and sTNF receptors in patients with squamous cell cervical cancer, particularly with early stage of the disease.

The aim of this study is to determine the prognostic value of tumor markers, as squamous cell carcinoma antigen (SCCAg) and cytokeratin-19 fragment (CYFRA 21.1) and interleukin 6 (IL-6), vascular endothelial growth factor (VEGF), soluble tumor necrosis factor receptor I (sTNF RI), and sTNF RII in patients with squamous cell carcinoma of the cervix. The subjects of analysis were 138 patients with stage I-IVA according to the International Federation of Gynecology and Obstetrics (FIGO) classification. The collected research material comes from one oncology center. During the 10 years of follow-up, 56 relapses and 53 deaths were observed, and recurrent disease in early stage was confirmed in 45 % of patients. The pretreatment serum levels of SCCAg and CYFRA 21.1, and cytokines IL-6, VEGF, sTNF RI, and sTNF RII were determined in all patients. The probability of disease-free survival (DFS) and overall survival (OS) was evaluated using the log-rank test and the Cox regression model. Based on the ROC curve analysis for patients with recurrence, the largest area under the curve was demonstrated for SCCAg and IL-6 and for patients who died, for SCCAg and VEGF. Cox analysis demonstrated that independent prognostic factor for DFS was only SCCAg and for OS cytokine IL-6 and SCCAg, but in patients with early stage the prognostic value for DFS was VEGF, whereas IL-6 and CYFRA 21.1 for OS. Serum level of VEGF, CYFRA 21.1 and IL-6 before treatment in patients with early stage cervical cancer appears to be an important prognostic factor.

Assessment of a Combined Panel of Six Serum Tumor Markers for Lung Cancer.

RATIONALE: We have previously identified six serum tumor markers (TMs) (carcinoembryonic antigen, carbohydrate antigen 15.3, squamous cell carcinoma-associated antigen, cytokeratin-19 fragment, neuron-specific enolase, and pro-gastrin-releasing peptide) related to the presence of lung cancer (LC). OBJECTIVES: To validate their individual performance in an independent cohort, and to explore if their combined assessment (≥1 abnormal TM value) is a more accurate marker for LC presence. METHODS: We determined these six TMs in 3,144 consecutive individuals referred to our institution by their primary care physician because of the clinical suspicion of LC. MEASUREMENTS AND MAIN RESULTS: LC was excluded in 1,316 individuals and confirmed in 1,828 patients (1,563 with non-small cell LC and 265 with small cell LC). This study validated the previously reported performance of each individual TM. We also showed that their combined assessment (≥1 abnormal TM) had a better sensitivity, specificity, negative predictive value, and positive predictive value (88.5, 82, 83.7, and 87.3%, respectively) than each TM considered individually and that it increased the diagnostic performance (area under the curve) of a clinical model that included tumor size, age, and smoking status. In patients with radiographic nodules less than 3 cm, the negative predictive value of the TM panel was 71.8%, hence providing some support for a more conservative diagnostic approach. Finally we identified two TMs (neuron-specific enolase and pro-gastrin-releasing peptide) that differentiate the risk of non-small cell LC from that of small cell LC. CONCLUSIONS: The combined assessment of a panel of six serum TMs is a more accurate marker for LC presence than these same TMs considered individually. The potential of these TMs in the diagnostic and screening settings deserves further research.

Assessment of circulating tumor cells and serum markers for progression-free survival prediction in metastatic breast cancer: a prospective observational study.

INTRODUCTION: Circulating tumor cells (CTC) have been recently proposed as a new dynamic blood marker whose positivity at baseline is a prognostic factor and whose changes under treatment are correlated with progression-free survival (PFS) in metastatic breast cancer patients. However, serum marker levels are also used for the same purpose, and no clear comparison has been reported to date. METHODS: The IC 2006-04 enrolled prospectively 267 metastatic breast cancer patients treated by first line chemotherapy and confirmed that CTC levels are an independent prognostic factor for PFS and overall survival (OS). A secondary pre-planned endpoint was to compare prospectively the positivity rates and the value of CTC (CellSearch®), of serum tumor markers (carcinoembryonic antigen (CEA), cancer antigen 15.3 (CA 15-3), CYFRA 21-1), and of serum non-tumor markers (lactate deshydrogenase (LDH), alkaline phosphatase (ALP)) at baseline and under treatment for PFS prediction, independently from the other known prognostic factors, using univariate analyses and concordance indexes. RESULTS: A total of 90% of the patients had at least one elevated blood marker. Blood markers were correlated with poor performance status, high number of metastatic sites and with each other. In particular, CYFRA 21-1, a marker usually used in lung cancer, was elevated in 65% of patients. A total of 86% of patients had either CA 15-3 and/or CYFRA 21-1 elevated at baseline. Each serum marker was associated, when elevated at baseline, with a significantly shorter PFS. Serum marker changes during treatment, assessed either between baseline and week 3 or between baseline and weeks 6 to 9, were significantly associated with PFS, as reported for CTC. Concordance indexes comparison showed no clear superiority of any of the serum marker or CTC for PFS prediction. CONCLUSIONS: For the purpose of PFS prediction by measuring blood marker changes during treatment, currently available blood-derived markers (CTC and serum markers) had globally similar performances. Besides CEA and CA 15-3, CYFRA 21-1 is commonly elevated in metastatic breast cancer and has a strong prognostic value.

Assessment of the effect of surgery on the kinetics of circulating tumour cells in patients with operable breast cancer based on cytokeratin-19 mRNA detection.

AIMS: The aim of this study was to evaluate the effect of surgery on the kinetics of CTCs in breast cancer patients. METHODS: The detection of CK-19 mRNA-positive CTCs in the blood by RT-PCR was analysed in 104 stage 0-IIIA patients at 4 time-points: prior to surgery, upon completion, 24 h after surgery and 15 days after surgery. Furthermore, a late sample was assessed prior to initiation of adjuvant chemotherapy in a subgroup of 53 patients. As negative controls, peripheral blood was obtained from 50 female patients undergoing excision of benign breast lesions and from 11 female patients receiving surgery for early-stage colorectal cancer. RESULTS: A significant percentage of blood samples from breast cancer patients (14.4%) were negative for CK-19 preoperatively but turned transiently positive early postoperatively. However, no significant difference in CK-19 mRNA detection was noted among the first 4 examined time-points. There was no significant correlation between CK-19 mRNA-positive cells and classic prognostic factors. A significant increase in CK-19 mRNA-positivity (32.1%) was observed in a late sample of the subgroup of 53 patients before adjuvant chemotherapy after a median of 54 days, postoperatively. CONCLUSIONS: Surgery may result in CTC detection in a small proportion of early breast cancer patients. There is no clear correlation to indicate which patients are expected to have detectable CTCs. Although CTCs are detected in a small proportion of patients during the perioperative period, the detection rate may increase over time and with longer follow-up.

[Clinical value of CEA and CYFRA21-1 as an assessment indicator of therapeutic efficacy in advanced non-small cell lung cancer patients].

OBJECTIVE: To investigate the value of carcinoembryonic antigen (CEA) or cytokeratin 19 fragment (CYFRA21-1) as an assessment indicator of therapeutic efficacy in advanced non-small cell lung cancer (NSCLC) patients. METHODS: 228 cases of advanced NSCLC with chemotherapy were enrolled into this retrospective study. The serum CEA or CYFRA21-1 levels of all patients were above the cut-off limit before treatment. The relationship between changes of tumor markers (TMs) and imaging therapeutic efficacy or progression-free survival (PFS) was analyzed, and the value of TMs in therapeutic efficacy assessment was evaluated. RESULTS: According to RECIST criteria, partial response (PR) occurred in 40 cases, stable disease (SD) in 151 and PD (progressive disease) in 37. The cut-off values of the changes of TMs between pre- and post-treatment were determined according to the above mentioned criteria. The CEA down (D), stable (S), above (A) groups were 90, 49 and 66 cases, respectively. CYFRA21-1 down (D), stable (S), above (A) groups were 84, 26 and 37 cases, respectively. PR groups were 68.4% and 88.9% in CEA and cyfra21-1 down groups, respectively, 7.9% and 5.6% in the above groups, respectively. PD groups were 59.4% and 76.2% in CEA and CYFRA21-1 above groups, respectively. No PD cases were in the down groups. The changes of TMs in SD group were between them. Statistically significant correlations were observed between changes of TMs and imaging therapeutic efficacy (r(CEA) = 0.45, P = 0.00; r(CYFRA21-1) = 0.44, P = 0.00). PFS among different TMs groups were significantly different (all P < 0.05), which can be used to further distinguish the prognosis among SD subgroups. CONCLUSION: Changes of TMs can be used to predict the imaging therapeutic effect and PFS of the patients, and if the SD group is divided into subgroups according to different therapeutic efficacy and prognosis, it may help the patients to receive individualized treatment.