Receiver operating characteristic (ROC) to determine cut-off points of biomarkers in lung cancer patients

The role of biomarkers in disease prognosis continues to be an important investigation in many cancer studies. In order for these biomarkers to have practical application in clinical decision making regarding patient treatment and follow-up, it is common to dichotomize patients into those with low vs. high expression levels. In this study, receiver operating characteristic (ROC) curves, area under the curve (AUC) of the ROC, sensitivity, specificity, as well as likelihood ratios were calculated to determine levels of growth factor biomarkers that best differentiate lung cancer cases versus control subjects. Selected cut-off points for p185(erbB-2) and EGFR membrane appear to have good discriminating power to differentiate control tissues versus uninvolved tissues from patients with lung cancer (AUC = 89% and 90%, respectively); while AUC increased to at least 90% for selected cut-off points for p185(erbB-2) membrane, EGFR membrane, and FASE when comparing between control versus carcinoma tissues from lung cancer cases. Using data from control subjects compared to patients with lung cancer, we presented a simple and intuitive approach to determine dichotomized levels of biomarkers and validated the value of these biomarkers as surrogate endpoints for cancer outcome.     

p53 and erbB-2 are not associated in matched cases of primary and metastatic ovarian carcinomas

Ovarian cancer has a high mortality rate largely due to the limited number of ovarian carcinomas detected at an early stage. Understanding the molecular changes occurring during the progression of ovarian carcinoma would aid in the development of therapies that may inhibit or target metastasis. Primary and metastatic lesions from 54 and 40 patients with advanced ovarian carcinoma, respectively (including matched primary and metastatic lesions from 30 patients) were evaluated for nuclear accumulation of p53 (clone BP53-12-1) and cytoplasmic and membranous immunostaining of p185 erbB-2 (clone 3B5) by immunohistochemistry. No differences in the immunostaining of p53 and p185erbB-2 (cytoplasm or membrane) were observed between primary and metastatic lesions of the matched cases. Similarly, no differences in the proportion of positive cases of p53 between primary and metastatic lesions of the matched cases was observed. Thus, novel therapies that target p53 or p185erbB-2 can utilize specimens from either primary or metastatic lesions to characterize these targets prior to therapy. Spearman correlations between p53 and p185erbB-2 (cytoplasm or membrane) immunohistochemistry scores were insignificant for the matched cases, all primary lesions, and all metastatic lesions. Also, no significant associations occurred between nuclear accumulation of p53 (positive versus negative) and phenotypic expression of p185erbB-2 (cytoplasm or membrane) immunostaining scores for the matched cases, all primary lesions, and all metastatic lesions. Thus, the nuclear accumulation of p53 and immunostaining of p185erbB-2 in the cytoplasm or on the cellular membranes are independent.     

Monoisotopic silver nanoparticles-based mass spectrometry imaging of human bladder cancer tissue: Biomarker discovery

PurposeBladder cancer (BC) is the 10th most common form of cancer worldwide and the 2nd most common cancer of the urinary tract after prostate cancer, taking into account both incidence and prevalence.Materials/methodsTissues from patients with BC and also tissue extracts were analyzed by laser desorption/ionization mass spectrometry imaging (LDI-MSI) with monoisotopic silver-109 nanoparticles-enhanced target (¹⁰⁹AgNPET).ResultsUnivariate and multivariate statistical analyses revealed 10 metabolites that differentiated between tumor and normal tissues from six patients with diagnosed BC. Selected metabolites are discussed in detail in relation to their mass spectrometry (MS) imaging results. The pathway analysis enabled us to link these compounds with 17 metabolic pathways.ConclusionsAccording to receiver operating characteristic (ROC) analysis of biomarkers, 10 known metabolites were identified as the new potential biomarkers with areas under the curve (AUC) higher than >0.99. In both univariate and multivariate analysis, it was predicted that these compounds could serve as useful discriminators of cancerous versus normal tissue in patients diagnosed with BC.     

Humoral immune response to epidermal growth factor receptor in lung cancer

The aim of this study was to explore the potential value of autoantibody to epidermal growth factor receptor (EGFR) in the diagnosis of lung cancer (LC) and its relation with EGFR mutations. Enzyme-linked immunosorbent assay (ELISA) was performed to detect the level of autoantibody to EGFR in sera from 254 LC patients and 222 normal controls (NCs). Besides, the mRNA and protein levels of EGFR were investigated in Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) database, respectively. The level of autoantibody to EGFR (anti-EGFR) in LC even different types of LC was obviously higher than that in NC (P < 0.05). The area under the curve (AUC) of anti-EGFR was 0.695 (95% CI 0.645–0.742) when comparing LC patients with NC, while the AUC of carcinoembryonic antigen (CEA) was 0.681 (95% CI 0.629–0.730). Moreover, by integrating anti-EGFR with CEA to diagnose LC, the AUC was up to 0.784 (95% CI 0.737–0.826). However, the expression level of autoantibody to EGFR had no difference between LC patients with and without EGFR gene mutation (P > 0.05). EGFR mRNA expression level was obviously upregulated in squamous cell carcinoma (SCC) tissues compared with normal tissues (P < 0.05), but not in adenocarcinoma (ADC) (P > 0.05). The study confirmed that anti-EGFR could be a potential biomarker for LC diagnosis; additionally, it could improve the diagnostic value of CEA in clinical work.

     

Application of artificial neural network model combined with four biomarkers in auxiliary diagnosis of lung cancer

The purpose of the study was to explore the application of artificial neural network model in the auxiliary diagnosis of lung cancer and compare the effects of back-propagation (BP) neural network with Fisher discrimination model for lung cancer screening by the combined detections of four biomarkers of p16, RASSF1A and FHIT gene promoter methylation levels and the relative telomere length. Real-time quantitative methylation-specific PCR was used to detect the levels of three-gene promoter methylation, and real-time PCR method was applied to determine the relative telomere length. BP neural network and Fisher discrimination analysis were used to establish the discrimination diagnosis model. The levels of three-gene promoter methylation in patients with lung cancer were significantly higher than those of the normal controls. The values of Z(P) in two groups were 2.641 (0.008), 2.075 (0.038) and 3.044 (0.002), respectively. The relative telomere lengths of patients with lung cancer (0.93 ± 0.32) were significantly lower than those of the normal controls (1.16 ± 0.57), t = 4.072, P < 0.001. The areas under the ROC curve (AUC) and 95 % CI of prediction set from Fisher discrimination analysis and BP neural network were 0.670 (0.569–0.761) and 0.760 (0.664–0.840). The AUC of BP neural network was higher than that of Fisher discrimination analysis, and Z(P) was 0.76. Four biomarkers are associated with lung cancer. BP neural network model for the prediction of lung cancer is better than Fisher discrimination analysis, and it can provide an excellent and intelligent diagnosis tool for lung cancer.     

Serum lemur tyrosine kinase-3: a novel biomarker for screening primary non-small cell lung cancer and predicting cancer progression

Purpose: We aimed to determine the expression level of serum soluble lemur tyrosine kinase-3 (sLMTK3) in human non-small cell lung cancer (NSCLC), and to examine whether the s sLMTK3 level could be used as a biomarker to screen primary NSCLC and to predict lung cancer progression. Methods: Serum levels of sLMTK3 in 67 patients with primary NSCLC, 28 patients with lung benign lesion, and 53 healthy volunteers were measured by sandwich ELISA. LMTK3 protein expression in NSCLC tissues and normal lung tissues was also detected by using immunohistochemical staining. Receiver operating characteristic (ROC) curve was selected to evaluate the sensitivity and the specificity of serum sLMTK3 level. Results: The mean concentration of sLMTK3 in NSCLC group was significantly higher than in the lung benign lesion group (P < 0.001) and the healthy control group (P < 0.001). Higher sLMTK3 level was correlated with age (P = 0.013), tumor-node-metastasis (TNM) stage (P < 0.001), and lymph node metastasis (P < 0.001) of NSCLC. In contrast to the normal lung tissues, increased LMTK3 expression was found in the NSCLC tissues, and was mainly located on the cytoplasm and the nuclei of cancer cells. For separating NSCLC from control group, the corresponding areas under the ROC curve (AUC) were 0.947 for sLMTK3 and 0.804 for CEA. With cutoffs of 10.05 ng/ml for sLMTK3 and 5.0 ng/ml for CEA respectively, the sensitivity and the specificity of sLMTK3 and CEA were, 80.60% and 97.53%, 35.82% and 96.30%, respectively, indicating better diagnostic value of sLMTK3. Conclusions: The sLMTK3 level was significantly increased in human NSCLC, and could be used as a potential and valuable biomarker for screening primary NSCLC and for predicting the progression of patients with this malignancy.     

Circulating microRNA-339-5p and -21 in plasma as an early detection predictors of lung adenocarcinoma

Background

Many studies have shown that differentially expressed miRs in body fluids can serve as biomarkers in non-invasive detection of the cancers. However, the clinical significance of plasma miRs in the diagnosis of lung adenocarcinoma (LA) is still not clear. Therefore, we examined the LA-specific miRs in plasma, which could be utilized to diagnosis and monitor LA in routine clinical practice.

neu oncogene protein and epidermal growth factor receptor are independently expressed in benign and malignant breast tissues

The neu oncogene protein, p185, and epidermal growth factor receptor (EGFR) were localized immunohistochemically in benign and malignant human breast tissues using monoclonal antibodies. Both benign and malignant epithelial cells were positive for these oncogene proteins in acetone-postfixed frozen sections. Stromal cells were negative for p185, but occasionally positive for EGFR. Myoepithelial cells were consistently positive for EGFR, and p185 was localized predominantly in duct-lining cells, where the basolateral plasma membrane was the normal expression site of both substances. Paraformaldehyde-prefixed frozen sections were less sensitive for antigen demonstration. Based on the intensity of immunoreactivity, 11 of 37 acetone-postfixed breast carcinomas (30%) were judged neu overexpressors, while none of 24 benign tissues overexpressed neu. Epidermal growth factor receptor was demonstrated in 18 of 36 acetone-postfixed cancer tissues (50%) and was overexpressed in three (8%). At the cellular level, heterogenous expression of p185 and EGFR was occasionally observed in both benign and malignant tissues, and a single case of cancer overexpressing both neu and EGFR showed reciprocal patterns of staining, indicating their independent expression. In some carcinomas, EGFR was localized only in stromal cells. Our findings confirmed mutually independent expression of the two closely related protooncogenes in benign and malignant breast tissues.     

Erratum to: Mutations in epidermal growth factor receptor and K-ras in Chinese patients with colorectal cancer

Background  

Mutations of EGFR and K-ras are biomarkers for predicting the efficacy of targeting agents in non-small-cell lung cancer (NSCLC) and colorectal cancer (CRC). Data on the gene mutation status of EGFR and K-ras in Chinese patients with CRC are limited.     

Hemopexin: A Novel Anti-inflammatory Marker for Distinguishing COPD From Asthma

PurposeSystemic inflammatory biomarkers can improve diagnosis and assessment of chronic obstructive pulmonary disease (COPD) and asthma. We aimed to validate an airway disease biomarker panel of 4 systemic inflammatory biomarkers, α2-macroglobulin, ceruloplasmin, haptoglobin and hemopexin, to establish their relationship to airway disease diagnosis and inflammatory phenotypes and to identify an optimized biomarker panel for disease differentiation.MethodsParticipants with COPD or asthma were classified by inflammatory phenotypes. Immunoassay methods were used to measure levels of validation biomarkers in the sera of participants with disease and non-respiratory disease controls. Markers were analyzed individually and in combination for disease differentiation and compared to established biomarkers (C-reactive protein, interleukin-6, and white blood cell/blood eosinophil count).ResultsThe study population comprised of 141 COPD, 127 severe asthma, 54 mild-moderate asthma and 71 control participants. Significant differences in ceruloplasmin, haptoglobin and hemopexin levels between disease groups and between systemic inflammatory phenotypes were observed. However, no differences were found between airway inflammatory phenotypes. Hemopexin was the best performing individual biomarker and could diagnose COPD versus control participants (area under the curve [AUC], 98.3%; 95% confidence interval [CI], 96.7%–99.9%) and differentiate COPD from asthmatic participants (AUC, 97.0%; 95% CI, 95.4%–98.6%), outperforming established biomarkers. A biomarker panel, including hemopexin, haptoglobin and other established biomarkers, could diagnose asthma versus control participants (AUC, 87.5%; 95% CI, 82.8%–92.2%).ConclusionsHemopexin can be a novel biomarker with superior diagnostic ability in differentiating COPD and asthma. We propose an anti-inflammatory axis between the airways and systemic circulation, in which hemopexin is a protective component in airway disease.     

Utility of two biomarkers for directing care among patients with non-severe community-acquired pneumonia

The aim of the present study is to evaluate the usefulness of two biomarkers—procalcitonin (PCT) and C-reactive protein (CRP)—in addition to the CURB-65 score for assessing the site of care and the etiology of non-severe community-acquired pneumonia (CAP). We conducted a prospective observational study from April 1, 2006, to June 30, 2007, in a single teaching hospital in northern Spain among patients with non-severe CAP. In addition to collecting data needed to determine the CURB-65 score, microbial cultures were taken and levels of PCT and CRP were measured. We compared the prognostic accuracy of these biomarkers with the CURB-65 score to predict hospitalization and microbial etiology using receiver operating characteristic (ROC) curves. A total of 344 patients with non-severe CAP were enrolled; 73 were admitted to the hospital and 271 were treated on an outpatient basis. An etiologic diagnostic was made for 44?%, with atypical pathogens predominating. Levels of PCT and CRP increased with increasing CURB-65 scores. Patients admitted to the hospital had higher PCT and CRP levels than outpatients (p?<?0.001). For predicting hospitalization, PCT had a better area under the ROC curve (AUC) (0.81) than the CURB-65 score alone (0.77). For PCT plus the CURB-65 score, the AUC increased significantly from 0.77 to 0.83. In patients with bacterial CAP, the biomarker levels were significantly higher than among patients with atypical or viral etiology (p?<?0.001). PCT with a cut-off point of 0.15?ng/mL was the best predictor for bacterial etiology and for select patients eligible for outpatient care. In conclusion, levels of PCT and CRP positively correlate with increasing severity of CAP and may have a role in predicting both patients who can safely receive outpatient care and the microbial etiology in patients with low CURB-65 scores.     

Combined CT score,blood mononuclear cell count,LDH, and plasma D-dimer for viral pneumonia diagnosis: a retrospective study

Objective: Due to a continued increase in viral pneumonia incidence and resulting high mortality, fast and accurate diagnosis is important for effective management. This investigation examined the significance of blood biomarkers and the CT score in the early diagnosis of viral pneumonia. Methods: Patients who were hospitalized due to radiologically-confirmed pneumonia and underwent virus antigen rapid test were enrolled. Their clinical information was compared. Blood mononuclear cell count, LDH, and plasma D-dimer were obtained. To evaluate the utility of biomarker levels in differentiating viral pneumonia from other pneumonia, ROC curves were developed to analyze the AUC. The optimal cut-off thresholds, specificity, sensitivity, and predictive values were assessed using the Youden index. The added value of the multi-marker approach was delineated using IDI and Reclassification analyses using NRI; IDI and NRI values were examined with 95% CI. Results: Overall, 1163 inpatients were recruited between January 2017 and January 2021. They were sub-divided into the viral pneumonia (n = 563) and non-viral pneumonia (n = 600) categories. We found that the CT score, blood mononuclear cell count, LDH, and plasma D-dimer were markedly elevated in viral pneumonia patients. At an LDH threshold of 693.595 U/L, an AUC of ROC was 0.805 in differentiating viral pneumonia. The combination of CT score and blood biomarkers had an ROC AUC value of 0.908. Conclusions: Combining elevated biomarkers with CT assessments outperformed the CT score alone in identifying viral pneumonia. It is crucial to better characterize the significance of biomarkers in combination with CT assessments in the diagnosis of viral pneumonia.     

基于影像组学的肺癌分型预测

目的 基于影像组学特征对肺癌中的两大亚型分类（小细胞肺癌与非小细胞肺癌）进行分型预测。 方法 在131名小细胞肺癌与非小细胞肺癌患者中(其中训练集包含119人,测试集中包含12人),从手动分割的病灶区域提取107维组学特征,使用R统计学软件中的FSelector包对影像组学特征进行关键特征筛选,构建支持向量机模型和k折交叉验证模型对肺癌患者的病理进行表型分类和验证,通过绘制受试者工作特征曲线（ROC曲线）图和计算曲线下面积（AUC）数值来对训练集和测试集中的肺癌分型预测效果进行评估。 结果 挑选出20个主要的影像组学特征用于小细胞肺癌与非小细胞肺癌的分型鉴别,这些特征对于训练集和测试集中的小细胞肺癌与非小细胞肺癌均有较好的区分能力。在测试集中,预肺癌亚型分类的准确率为75%,组学特征的AUC结果为0.69。 结论 通过构建独特的影像组学特征,以用作区分小细胞肺癌与非小细胞肺癌的诊断因素。这对实现非侵入性的肺癌病理有效分型预测,指导肺癌患者后续治疗方案的选择具有重要指导意义。     

Correlated expression of erbB-3 with hormone receptor expression and favorable clinical outcome in invasive ductal carcinomas of the breast

The prognostic impact of epidermal growth factor receptor (EGFR) family members in breast carcinoma was evaluated through the analysis of 378 cases of invasive ductal carcinoma to determine the relationship between EGFR family members and clinical outcome.It was found that 13.8% of the cases were positive for erbB-3. Expression of erbB-3 was inversely correlated with EGFR and erbB-4 expression (P = .012 and P = .046). Expression of erbB-3 was correlated with positive estrogen and progesterone receptor status and inversely correlated with histologic grade. Expression of erbB-3 was correlated with longer disease-free survival (DFS; P = .028). Within the erbB-3-expressing group, there was a tendency for the coexpressing group to have shorter DFS compared with the single-expressing group.This study revealed that erbB-3 expression was associated with better prognosis. In an era of personalized targeted therapy, erbB-3 expression and its coexpressive pattern with other EGFR family members could be an important determinant for therapeutic plans for breast cancer treatment.     

Macrophage Activation Syndrome-Associated Markers in Severe Dengue

Hemophagocytosis, a phenomenon of which activated macrophages phagocytosed hematopoietic elements was reportedly observed in severe dengue patients. In the present study, we investigated whether markers of macrophage activation syndrome (MAS) can be used as differential diagnostic markers of severe dengue. Two hundred and eight confirmed dengue patients were recruited for the study. Sandwich ELISA was used to determine serum ferritin, soluble CD163 (sCD163), and soluble CD25 (sCD25) levels. The population of circulating CD163 (mCD163) monocytes was determined using flow cytometry. Receiver operating characteristic (ROC) analysis was plotted to determine the predictive validity of the biomarkers. Serum ferritin and sCD163 were found significantly increased in severe dengue patients compared to dengue fever patients (P = 0.003). A fair area under ROC curves (AUC) at 0.72 with a significant P value of 0.004 was observed for sCD163. sCD25 and mCD163 levels were not significantly different between severe dengue and dengue fever patients. Our findings suggest that in addition to serum ferritin, sCD163 can differentiate severe dengue from that of dengue fever patients. Hence, sCD163 level can be considered for use as a predictive marker for impending severe dengue.     

Role of E-selectin for diagnosis of myocardial injury in children of age up to 14 years

Background: Effects of myocardial injury on E-selectin remain unclear. Thus, we investigated the diagnostic value of E-selectin for myocardial injury in children of no more than 14 years of age, which determined the scoring method of myocardial injury. Methods: In this prospective study, plasma E-selectin, cardiac troponin I (cTnI) and creatine kinase isoenzyme MB (CK-MB) concentrations in pediatric patients with myocardial injury (myocardial injury group, n=85) were measured. The control group comprised 80 patients without myocardial injury, and the case-control study method was selected at the same time. The definition of cardiac injury was based on cTnI and CK-MB (with or possibly without abnormal ECG evidence). Diagnostic value of E-selectin for myocardial injury was determined by analyzing receiver operating characteristic (ROC) curves. Results: The differences between the two groups were of statistical significance (P<0.001). For the 85 patients with myocardial injury, the area under the ROC curve (AUC) value for plasma E-selectin levels was 0.945 with a 95% CI of 0.899-0.991 and the optimal diagnostic cut-off value 29.67 ng/ml (positive likelihood ratio (positive LR=72.5); AUC value for plasma cTnI level was 0.848 with a 95% CI: 0.737-0.960 and the optimal diagnostic cut-off value was 0.155 µg/L (positive LR=12.3); AUC value for plasma CK-MB levels was 0.946 with a 95% CI: 0.903-0.989 and the optimal diagnostic cut-off value 24.26 IU/L (positive LR=72.5). Conclusions: E-selectin is more effective than cTnI in diagnosing myocardial injury as an important biological marker of myocardial injury- an important index of pediatric cardiac injury score.     

Combined identification of long non-coding RNA XIST and HIF1A-AS1 in serum as an effective screening for non-small cell lung cancer

Objective: Long non-coding RNAs (lncRNAs) XIST and HIF1A-AS1 have been shown to play important regulatory roles in cancer biology, and lncRNA-XIST and HIF1A-AS1 are upregulated in several cancers such as glioblastoma, breast cancer and thoracoabdominal aorta aneurysm, however, its value in the diagnosis of non-small cell lung cancer (NSCLC) is unclear. The aim of this study is to evaluate the clinical significance of serum XIST and HIF1A-AS1 as a biomarker in the screening of NSCLC. Methods: Expression levels of lncRNA-XIST and HIF1A-AS1 in tumor tissues and serum from NSCLC patients were evaluated by quantitative real-time PCR, and its association with overall survival of patients was analyzed by statistical analysis. Moreover, the XIST and lncRNA-XIST expression correlation between tumor tissues and plasma was demonstrated by linear regression analysis. Results: The levels of XIST (P < 0.05) and HIF1A-AS1 (P < 0.05) were significantly increased in tumor tissues or serum from NSCLC patients as compared to those of control group. Correlation of lncRNA-XIST or HIF1A-AS1 expression between tumor tissues and serum from the same individuals was confirmed in NSCLC patients. Moreover, serum levels of XIST and HIF1A-AS1 were significantly decreased after surgical treatment as compared to pre-operative. The ROC curves illustrated strong separation between the NSCLC patients and control group, with an AUC of 0.834 (95% CI: 0.726-0.935; P < 0.001) for XIST and 0.876 (95% CI: 0.793-0.965; P < 0.001) for HIF1A-AS1, however, the combination of XIST and HIF1A-AS1 yielded an AUC of 0.931 (95% CI: 0.869-0.990; P < 0.001), which was significantly improved as compared to XIST or HIF1A-AS1 alone. Conclusion: Our results demonstrated that increased serum XIST and HIF1A-AS1 could be used as a predictive biomarker for NSCLC screening, and that combination of XIST and HIF1A-AS1 had a higher positive diagnostic efficiency of NSCLC than XIST or HIF1A-AS1 alone.     

Chemokine receptor CXCR4 expression in breast cancer as a potential predictive marker of isolated tumor cells in bone marrow

Interactions between the CXCR4 chemokine receptor in breast cancer cells and the ligand CXCL12/SDF-1α are thought to play an important role in breast cancer metastases. In this pilot study, CXCR4 expression along with other biomarkers including HER2-neu and EGFR, were measured in primary tumor samples of patients with operable breast cancer to test whether any of these biomarkers alone and in combination could indicate breast cancer with high likelihood of metastasizing to bone marrow. Cytokeratin (CK) positive cells in bone marrow were identified by flow-cytometry following enrichment with CK 7/8 antibody-coupled magnetic beads. Primary tumors (n = 18) were stained with specific antibodies for CXCR4, HER2-neu, EGFR, and PCNA using an indirect avidin–biotin horseradish peroxidase method. The majority of the patients had T2/T3 tumors (72%), or lymph node involvement (67%) as pathologic characteristics that were more indicative of high-risk breast cancer. High CXCR4 cytoplasmic expression was found in 7 of 18 patients (39%), whereas 6 of 18 patients (33%) were found to have CK positivity in bone marrow. The median number of CK⁺ cells was 236 (range, 20–847) per 5 × 10⁴ enriched BM cells. The presence of CK⁺ cells in bone marrow was found to be associated with increased expression of CXCR4 alone or in addition to EGFR and/or HER2-neu expression (P = 0.013, P = 0.005, and P = 0.025, respectively) in primary tumors. Furthermore, three patients with high CK positivity (>236 CK⁺ per 5 × 10⁴ enriched bone marrow cells) in bone marrow exclusively expressed high levels of CXCR4 with EGFR/HER2-neu (P = 0.001). Our data suggest that high CXCR4 expression in breast cancer may be a potential marker in predicting isolated tumor cells in bone marrow. CXCR4 coexpression with EGFR/HER2-neu might further predict a particular subset of patients with high CK positivity in bone marrow.