Development of a prediction model with serum tumor markers to assess tumor metastasis in lung cancer

A pilot study of precision treatment for patients with lung cancer pain by Longteng Tongluo recipe using serum genomics

OBJECTIVE

To investigate the efficacy of Longteng Tongluo recipe (, LTTL) combined with three-step analgesia for the treatment of lung cancer pain, and the changes in serum miRNA expressions before- and after treatment with LTTL and its correlation with lung cancer pain. The possible mechanism underlying LTTL effects on the treatment of lung cancer pain was conducted.

METHODS

The pilot study was conducted at the oncology ward of the Yueyang Hospital and the Longhua Hospital between March 2018 and October 2019. A prospective, single-blind, placebo controlled, randomized clinical trial of LTTL or placebo combined with three-step analgesia treatments were administered to 24 cancer pain patients diagnosed with lung cancer. Analgesic efficacy was investigated as the primary outcome. Equivalent morphine consumption and numerical rating scale (NRS) scores were used as the secondary outcome. In the present study, we utilized deep sequencing techniques to compare the differential miRNA expressions in serum samples obtained from two groups: the lung cancer pain treatment group (LTTL + three-step analgesia) and the control group (placebo + three-step analgesia). Next, we employed the target prediction database to investigate the target genes for differential miRNA expressions and Gene Ontology (GO) analysis along with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to examine the roles and the major biochemical and signaling pathways related to the differentially expressed target genes, respectively.

RESULTS

LTTL treatment significantly reduces the NRS score (P = 0.021) as compared to those before treatment, along with significant reductions in the total morphine equivalent consumption (P = 0.007) and the average daily equivalent morphine consumption (P = 0.003) as opposed to the control group. The expressions of 31 miRNAs differed considerably between the two groups of patients (≥ 2 times up-modulated or down-regulated between these groups, P<0.05). For instance, the miRNAs expression levels for patients before treatment (has-miR-2110 and has-miR-7d-3p) were significantly enhanced as compared to the healthy people, after LTTL treatment, the expressions of miR-2110 and miR-7d-3p in patients with lung cancer pain reduced significantly. Studies show that the above two miRNAs were significantly associated with lung cancer pain, which could mediate lung cancer pain. Furthermore, we identified 355 genes as potential targets of the 31 differentially expressed miRNAs. Pathway enrichment analyses using KEGG and GO analysis indicated that these target genes may play a crucial role in the development and modulation of lung cancer pain.

CONCLUSION

LTTL demonstrated a discernible impact on alleviating lung cancer pain and its mechanism of action may be related to the downregulation of has-miR-2110 and has-miR-7d-3p expressions. This pilot study provides support for further exploration of LTTL in patients with lung cancer pain.

The ratio of lymph node eluate/serum cytokeratin 21-1 is a potential predictor of lymph node metastasis in lung adenocarcinoma

Background

Lymph node metastasis (LNM) plays an important role in prognosis of lung cancer, either in preoperative TNM staging or postoperative disease recurrence or progress. This study aimed to explore the diagnostic performances of biomarkers from lymph node eluate for LNM in lung adenocarcinoma (LUAD).

Methods

A prospective analysis was conducted based on lymph node eluate specimens collected via ultrasound-guided lymph node biopsy from 48 LUAD patients with suspected LNM in the neck. According to cytopathological results, the patients were categorized into two groups: one with LNM and the other with non-LNM (NLNM). Carcinoembryonic antigen (CEA), cytokeratin 21-1 fragment (CYFRA21-1), neuron-specific enolase (NSE) and gastrin precursor releasing peptide (ProGRP) in lymph node eluate were detected by immunoassay analyzers, and tumor marker was simultaneously collected in serum of patients.

Results

The serum levels of CEA, CYFRA21-1, NSE, and the ratios of CYFRA21-1 and NSE in the lymph node eluate to serum were significantly higher in the LNM group, compared to NLNM group. The areas under curves (AUCs) for CEA, CYFRA21-1, NSE, and ratios of CYFRA21-1 and NSE were 0.79, 0.91, 0.85, 0.93, and 0.89, respectively. The ratio of CYFRA21-1 in lymph node eluate to serum (rCYFRA21-1) performed best in diagnosing, with a sensitivity of 92.3%, a specificity of 92.9%, and an AUC of 0.93.

Conclusions

The rCYFRA21-1 to that in the serum might serve as a potential predictor for LNM in LUAD.

Preoperative evaluation and a nomogram prediction model for pelvic lymph node metastasis in endometrial cancer

OBJECTIVE

The primary objective of this study is to explore the preoperative risk factors of pelvic lymph node metastasis (PLNM) in endometrial cancer patients, and construct a nomogram prediction model.

MATERIALS AND METHODS

We retrospectively collected various preoperative clinical characteristics of patients and analyzed their relationship with PLNM. Logistic regression analysis was used to screen for independent risk factors for PLNM of endometrial cancer. A nomogram prediction model was constructed, the receiver operating characteristic (ROC), calibration curve and decision curve analysis (DCA) were constructed and used to assess discrimination, calibration, and net benefit.

RESULTS

Out of the 276 patients, 74 (26.81%) with postoperative pathological confirmation of PLNM. Multivariate logistic regressive analysis demonstrated that preoperative depth of myometrial invasion (DIM) ≥50% determined by Magnetic Resonance Imaging (MRI) (p = 0.003), carbohydrate antigen 125 (CA125) (p = 0.030), carbohydrate antigen 19-9 (CA 19-9) (p = 0.044), and platelet/lymphocyte ratio (PLR) (p = 0.025) could serve as independent risk factors for PLNM. A risk factors-based nomogram prediction model was constructed, which showed good discrimination (AUC = 0.841, p < 0.001) and good efficacy (C-index = 0.842) and good calibration (mean absolute error = 0.046). DCA showed that the model can provide clinical benefits.

CONCLUSIONS

Preoperative DIM ≥50% determined by MRI, serum CA 19-9, CA125 and PLR could be utilized to predict PLNM in endometrial cancer patients. This nomogram prediction model can provide preoperative help for evaluation and identification of patients with endometrial cancer, and provide a theoretical basis for clinical intervention.

Diastole/Body Mass Index Ratio Can Predict Post-Thoracoscopic Surgery Metastasis in Stage I Lung Adenocarcinoma

Background: According to recent animal models for lung adenocarcinoma metastasis, cardiac function may be related to the clinical outcome. The aim of this study is to identify a predictable index for postoperative metastasis (POM) that is associated with cardiac function. Methods. Two hundred and seven consecutive patients who underwent thoracoscopic resection for stage I lung adenocarcinoma were included. Disease-free survival (DFS), overall survival (OS), and patients’ clinical and pathological characteristics were analyzed. Results. Among the 207 patients, 17 cases demonstrated metastasis, 110 cases received a preoperative echocardiogram, and six cases had POM. Mitral valve peak A velocity, which is one of the left ventricular diastolic function parameters affected by BMI (MVPABMI), was associated with a negative factor for POM (hazard ratio (HR): 2.139, p = 0.019) and a poor 5-year DFS in the above median (100% vs. 87%, p = 0.014). The predictable rate increased from 30.7% to 75% when the MVPABMI was above the median = 3.15 in the solid subtype). Conclusions. MVPABMI is a novel index for POM prediction in early-stage lung adenocarcinoma. This is a pilot study and the first attempt at research to verify that the diastole and the BMI may be associated with POM in early-stage lung adenocarcinoma.

Prognostic evaluation of preoperative serum tumor marker-negative cases in non-small cell lung cancer: A retrospective study

BACKGROUND

The role of various serum tumor markers (TMs) has been reported in non-small cell lung cancer (NSCLC). However, the prognosis of patients with multiple TM-negative NSCLC remain unclear.

AIMS

This study aimed to describe the characteristics and outcomes of patients with NSCLC undergoing surgery and to investigate their prognostic association with preoperative serum TM-negative cases.

METHODS AND RESULTS

We retrospectively evaluated 442 patients who underwent complete resection of stage I NSCLC between January 2004 and December 2019. These 442 patients were classified into a group whose preoperative serum levels of carcinoembryonic antigen (CEA), cytokeratin-19 fragment (CYFRA21-1), carbohydrate antigen 19-9 (CA19-9), and squamous cell carcinoma antigen (SCC Ag) were all negative (TM-negative group; n = 249, 56%) and a group with at least one positive marker (TM-positive group; n = 193, 44%). Among all patients, the TM-negative group showed higher 5-year recurrence-free survival (RFS) (92.6% vs. 79.1%; p < .01), and overall survival (OS) rates (86.3% vs. 68.6%; p < .01). After propensity score matching, patients in the TM-negative group still exhibited good 5-year RFS (92.1% vs. 81.4%; p = .01) and OS rates (87.6% vs. 72.6%; p < .01).

CONCLUSION

Our study suggests that NSCLC patients who are preoperatively negative for all serum TMs, such as CEA, CYFRA21-1, CA19-9, and SCC Ag, represent a subgroup with a particularly good prognosis.

Assessment of circulating biomarkers for detection of lung cancer in a high-risk cohort

BACKGROUND

There is an urgent need for early detection of lung cancer. Screening with low-dose computed tomography (LDCT) is now implemented in the US. Supplementary use of a lung cancer biomarker with high specificity is desirable.

OBJECTIVE

To assess the diagnostic properties of a biomarker panel consisting of cytokeratin 19 fragment (CYFRA 21-1), carcinoembryonic antigen (CEA) and cancer antigen 125 (CA125).

METHODS

A cohort of 250 high-risk patients was investigated on suspicion of lung cancer. Ahead of diagnostic work-up, blood samples taken. Cross-validated prediction models were computed to assess lung cancer detection properties.

RESULTS

In total 32% (79/250) of patients were diagnosed with lung cancer. Area under the curve (AUC) for the three biomarkers was of 0.795, with sensitivity/specificity of 57%/93% and negative predictive value of 83%. When combining the biomarkers with US screening criteria, the AUC was 0.809, while applying only US screening criteria on the cohort, yielded an AUC of 0.62. The ability of the biomarkers to detect stage I-II lung cancer was substantially lower; AUC 0.54.

CONCLUSIONS

In a high-risk cohort, the detection properties of the three biomarkers were acceptable compared to current LDCT screening criteria. However, the ability to detect early stage lung cancer was low.

The Potential Role of MUC16 (CA125) Biomarker in Lung Cancer: A Magic Biomarker but with Adversity

Lung cancer is the second most commonly diagnosed cancer in the world. In terms of the diagnosis of lung cancer, combination carcinoembryonic antigen (CEA) and cancer antigen 125 (CA125) detection had higher sensitivity, specificity, and diagnostic odds ratios than CEA detection alone. Most individuals with elevated serum CA125 levels had lung cancer that was either in stage 3 or stage 4. Serum CA125 levels were similarly elevated in lung cancer patients who also had pleural effusions or ascites. Furthermore, there is strong evidence that human lung cancer produces CA125 in vitro, which suggests that other clinical illnesses outside of ovarian cancer could also be responsible for the rise of CA125. MUC16 (CA125) is a natural killer cell inhibitor. As a screening test for lung and ovarian cancer diagnosis and prognosis in the early stages, CA125 has been widely used as a marker in three different clinical settings. MUC16 mRNA levels in lung cancer are increased regardless of gender. As well, increased expression of mutated MUC16 enhances lung cancer cells proliferation and growth. Additionally, the CA125 serum level is thought to be a key indicator for lung cancer metastasis to the liver. Further, CA125 could be a useful biomarker in other cancer types diagnoses like ovarian, breast, and pancreatic cancers. One of the important limitations of CA125 as a first step in such a screening technique is that up to 20% of ovarian tumors lack antigen expression. Each of the 10 possible serum markers was expressed in 29-100% of ovarian tumors with minimal or no CA125 expression. Therefore, there is a controversy regarding CA125 in the diagnosis and prognosis of lung cancer and other cancer types. In this state, preclinical and clinical studies are warranted to elucidate the clinical benefit of CA125 in the diagnosis and prognosis of lung cancer.

Role of circular RNAs in the diagnosis, regulation of drug resistance and prognosis of lung cancer (Review)

Lung cancer is one of the most common malignant tumors in China and is the highest cause of mortality among male and female patients, both in urban and rural areas. A subset of patients with lung cancer only display chest tightness without any other obvious symptoms. This is because most symptoms do not manifest during the early stages of disease development. Consequently, most patients with lung cancer are diagnosed when the disease is in the advanced stages, when they are already unfit for surgical treatment. Furthermore, the prognosis of patients with lung cancer is poor. The 5-year survival rate of patients with stage IA lung cancer is 85%, compared with 6% in those with stage IV. This requires the development of strategies for early diagnosis, treatment and prognosis to improve the management of lung cancer. Circular RNAs (circRNAs) belong to a class of closed circular non-coding RNAs formed by reverse splicing of a precursor mRNA. These RNAs are highly stable, ubiquitously expressed, conserved, and show high specificity. CircRNAs regulate biological processes, such as the proliferation, differentiation and invasion of lung cancer cells. Therefore, they can be used as biomarkers for the early diagnosis and prognosis prediction of lung cancer, as well as novel targets for therapy design. In the present review, the biological characteristics and functions of circRNAs, as well as their application in the diagnosis, control of drug resistance and effect on the prognosis of patients with lung cancer, will be discussed.

Detection of cancer biomarkers CA125 and CA199 via terahertz metasurface immunosensor

The cancer biomarkers including AFP, CEA, CA199 and CA125, are of great importance in the diagnosis, prognostic prediction and recurrence monitoring of malignancies. However, in clinical practical applications, most tumor cancer biomarkers are lack of sensitivity and specificity. In this study, we propose a terahertz (THz) metasurface (MS) immunosensor coupled with gold nanoparticles (AuNPs), which have good biocompatibility and high specific surface area for biomarkers. Firstly, we added AuNPs to the surface of the sensor. And then, the surface is modified with Anti-CA125 or Anti-CA199 to improve the sensitivity and specificity to the target antigen. The biosensor was fabricated using a surface micromachining process and characterized by a THz-time-domain spectroscopy (TDS) system. The sensitivity of the resonance frequency of the sensor to the refractive index was 65 GHz/RIU (refractive index unit). The detection performance of the THz immunosensor was also verified with different concentrations of CA125 and CA199. The experimental results showed that the frequency shift of the resonance peak was linearly related to the concentration of CA125 and CA199. The detection limits for both CA125 and CA199 are 0.01 U/ml, which is better than that of other common methods. Finally, serum samples were collected and detected to explore whether this method is suitable for clinical detection. The results are consistent with the results of antigen recognition. This study proves that the practicability of the THz immunosensor, which potentially provides important techniques and equipment for improving the sensitivity and specificity of cancer biomarkers.

Identification of a novel DNA aptamer that selectively targets lung cancer serum

Lung cancer is the leading cause of cancer-related deaths worldwide. Early diagnosis and treatment is critical to improving the 5 year survival rate of lung cancer. The identification of new options for early-stage diagnosis and therapy of lung cancer still represents a crucial challenge. Therefore, a new diagnostic method is urgently needed. In this study, we used a new modified SELEX, called serum-SELEX, to isolate aptamers that can specifically bind lung cancer serum, without any prior knowledge of their target. Among the obtained candidate aptamer sequences, Ap-LC-19 was identified as the optimal aptamer probe with the lowest dissociation constant (K d) value of 15 ± 8.6 nM and higher affinity assessed by qPCR. Furthermore, this molecule could be a suitable aptamer for lung cancer serum and could be used as a recognition element in aptamer-based biosensors for efficient early diagnosis of lung cancer or as an innovative tool for targeted therapy. In addition, we performed MALDI-TOF MS followed by secondary peptide sequencing MS analysis for the identification of the aptamer targeted proteins. CLEC3B could be useful biomarkers for early detection of lung cancer and in monitoring its evolution.

Collagen type 1 alpha 1 chain is a novel predictive biomarker of poor progression-free survival and chemoresistance in metastatic lung cancer

Background: Collagen type 1 alpha 1 chain (COL1A1) is an extracellular matrix protein comprising two alpha 1 chains and one alpha 2 chain. Our previous study identified that COL1A1 is the key gene during the development and progression of lung adenocarcinoma by multi-omics analysis. However, the clinical significance of COL1A1 expression in lung cancer samples remains largely unknown. Here, we aimed to evaluate the level of COL1A1 in lung cancer samples and correlate its level with the clinical outcome.

Methods:COL1A1 gene expression in lung cancer samples was analyzed using the Oncomine database (www.oncomine.org). A total of 308 lung cancer samples (208 formalin-fixed paraffin-embedded tissues and 100 blood samples) were assessed for protein expression of COL1A1. Immunohistochemistry staining and enzyme-linked immunosorbent assay were used to detect COL1A1 expression in tissues and serum, respectively.

Results: We identified an elevation of COL1A1 in mRNA level and gene amplification in lung cancer tissues compared with normal lung tissues. High COL1A1 expression was observed in lung cancer tissues and serum (P < 0.05), it was significantly correlated with the peripheral type tumor, the larger diameter of the tumor, the occurrence of lymph node metastases and distant metastases, a higher TNM stage, and smoking (P < 0.05). High COL1A1 expression was associated with poor progression-free survival (PFS) and chemoresistance in lung cancer patients (P < 0.05). Multivariable Cox-regression analysis showed that COL1A1 expression was an independent prognostic factor (P < 0.05). Furthermore, the area under the receiver operating characteristic (AUC) curve was 0.909 for the combined COL1A1 and carcinoembryonic antigen (CEA) measurement.

Conclusion: Our findings revealed that COL1A1 could be used as a novel diagnostic, prognostic, and chemoresistance biomarker of human lung cancer, and these results provide a potential therapeutic strategy for lung cancer patients.

Identification of prognostic factors and construction of a nomogram for patients with relapse/refractory adult-onset Still's disease

OBJECTIVES

This study aimed to identify the risk factors for relapse/refractory adult-onset Still's disease (AOSD) and to construct and validate a prognostic nomogram for predicting the individual risk of relapse/refractory disease.

METHOD

A total of 174 patients were included in our study. Univariate and multivariate logistic regression analyses were used to identify relapse/refractory-associated factors, which were used to construct nomograms. Receiver operating characteristic (ROC) curve analysis, calibration curves, and decision curve analysis (DCA) were used to assess the predictive ability of the nomograms.

RESULTS

Univariate and multivariate logistic analyses showed that age, fever, disease duration, platelet count, serum ferritin level, and erythrocyte sedimentation rate were independent unfavourable factors for relapse/refractory AOSD (p < 0.05). We constructed a 6-factor nomogram based on univariate and multivariate logistic analyses. ROC analysis indicated that the area under the curve of the 6-factor nomogram in the training set and test set was 0.765 and 0.714, respectively. In addition, the calibration curves showed excellent prediction accuracy, and DCA showed superior net benefit in the 6-factor nomograms. Moreover, we evaluated the predictive effectiveness of our nomogram in females and young adults. The results showed that our 6-factor nomogram has the same predictive ability in both subgroups.

CONCLUSIONS

Novel nomograms based on clinical characteristics were developed and may be applied to help predict the individual risk of poor prognosis of patients. Key Points • Logistic regression was used to identify risk factors for relapse/refractory adult-onset Still's disease. • We then constructed a nomogram for predicting disease risk. • ROC analysis, calibration curves, and DCA all showed that the nomogram exerted good prediction ability in both the training set and test set. • The nomogram has the same predictive ability in both female and young adult subgroups.

A novel model for extrapleural cavity metastasis assessment in patients with lung cancer

Aim: To investigate the clinical value of tumor markers in extrapleural tumor metastasis assessment of newly diagnosed lung cancer patients. Materials & methods: This study retrospectively analyzed 306 patients diagnosed with lung cancer accompanied by tumor metastasis. Patients were grouped into extrapleural tumor metastasis and intrapleural tumor metastasis. Seven serum tumor markers were included for analysis. Results: The area under curves of receiver operating characteristic curve based on binning decision tree algorithm were above 0.8 in both training and validation sets. A scorecard with a score below 3 suggested extrapleural tumor metastasis in newly diagnosed lung cancer patients. Conclusion: The serum tumor marker-derived model is a convenient and fast approach for extrapleural cavity metastasis assessment, which may provide positive implications in newly diagnosed lung cancer patients.

Development of a prediction model with serum tumor markers to assess tumor metastasis in lung cancer

BACKGROUND

This study aimed to explore the possibility of serum tumor markers (TMs) combinations in assessing tumor metastasis in patients with lung cancer.

METHODS

We performed a retrospective analysis of 541 patients diagnosed with lung cancer between January 2016 and December 2017 at the Pneumology Department of Dazhou Central Hospital. Serum carcinoembryonic antigen (CEA), carbohydrate antigen (CA)125, CA153, CA199, CA724, cytokeratin 19 fragment (CYFRA), and neuron-specific enolase (NSE) levels were quantified in each patient at the time of lung cancer diagnosis. Metastasis was confirmed by computed tomography, and/or positron emission tomography, and/or surgery or other necessary methods. Receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the performance of the model.

RESULTS

Of the 541 patients eligible for final analysis, 253 were detected with metastasis and 288 were detected without metastasis. Compared with those in nonmetastatic patients, the serum CEA, CA125, CA199, CA153, CYFRA, and NSE levels were notably higher in metastatic patients (P < .05). The ROC curve demonstrated that the CEA-CA125-CA199-CA153-CYFRA-NSE-CA724 combination based on the cut-off value had an optimal area under the curve and specificity in assessing tumor metastasis. The decision tree model is a convenient and valuable tool for guiding the appropriate application of our model to assess metastasis in lung cancer patients.

CONCLUSIONS

Our study suggested that the nomogram of the regression model is valuable for assessing tumor metastasis in newly diagnosed lung cancer patients before traditional standard methods are used. These findings could aid in the evaluation of metastasis in the clinic.