Increased CYFRA 21-1, CEA and NSE are Prognostic of Poor Outcome for Locally Advanced Squamous Cell Carcinoma in Lung: A Nomogram and Recursive Partitioning Risk Stratification Analysis

Identification of biomarkers for the early detection of non-small cell lung cancer: a systematic review and meta-analysis

Lung cancer (LC) causes few symptoms in the earliest stages, leading to one of the highest mortality rates among cancers. Low-dose computerised tomography (LDCT) is used to screen high-risk individuals, reducing the mortality rate by 20%. However, LDCT results in a high number of false positives and is associated with unnecessary follow-up and cost. Biomarkers with high sensitivities and specificities could assist in the early detection of LC, especially in patients with high-risk features. Carcinoembryonic antigen (CEA), cytokeratin 19 fragments and cancer antigen 125 have been found to be highly expressed during the later stages of LC but have low sensitivity in the earliest stages. We determined the best biomarkers for the early diagnosis of LC, using a systematic review of eight databases. We identified 98 articles that focussed on the identification and assessment of diagnostic biomarkers and achieved a pooled area under curve of 0.85 (95% CI 0.82-0.088), indicating that the diagnostic performance of these biomarkers when combined was excellent. Of the studies, 30 focussed on single/antigen panels, 22 on autoantibodies, 31 on miRNA and RNA panels, and 15 suggested the use of circulating DNA combined with CEA or neuron-specific enolase (NSE) for early LC detection. Verification of blood biomarkers with high sensitivities (Ciz1, exoGCC2, ITGA2B), high specificities (CYFR21-1, antiHE4, OPNV) or both (HSP90α, CEA) along with miR-15b and miR-27b/miR-21 from sputum may improve early LC detection. Further assessment is needed using appropriate sample sizes, control groups that include patients with non-malignant conditions, and standardised cut-off levels for each biomarker.

The Diagnostic and Prognostic Value of the Combination of Tumor M2-Pyruvate Kinase, Carcinoembryonic Antigen, and Cytokeratin 19 Fragment in Non-Small Cell Lung Cancer

Objective: Finding biomarkers related to non-small cell lung cancer (NSCLC) is helpful for the diagnosis and precise treatment of lung cancer. The relationship between serum tumor M2-pyruvate kinase (TuM2-PK), carcinoembryonic antigen (CEA), and cytokeratin 19 fragment (CYFRA21-1) and NSCLC was analyzed. Methods: The serum levels of TuM2-PK, CEA, and CYFRA21-1 in 184 patients with the NSCLC group, 60 patients with the benign lung disease (BLD) group, and 90 healthy controls (HC) group were detected. The levels of TuM2-PK were measured by using an enzyme-linked immunosorbent assay. The detection methods of CEA and CYFRA21-1 were electrochemiluminescence. The receiver operating characteristic (ROC) curve was drawn to evaluate the diagnostic value of TuM2-PK, CEA, and CYFRA21-1 on NSCLC. The Kaplan-Meier survival curve was drawn to evaluate the survival status in NSCLC patients with different serum levels of TuM2-PK, CEA, and CYFRA21-1. Results: Serum levels of TuM2-PK, CEA, and CYFRA21-1 in the NSCLC group were significantly higher than those in the BLD group and the HC group (P < .01). Serum levels of TuM2-PK, CEA, and CYFRA21-1 in NSCLC patients were associated with the tumor lymph node metastasis stage (P < .05), lymph node metastasis (P < .05), and distant metastasis (P < .05). The ROC curve showed that the area under the curve of serum levels of TuM2-PK, CEA, and CYFRA21-1 was 0.814, 0.638, and 0.719, respectively, and that the combination of the above 3 was 0.918. The Kaplan-Meier survival curve showed that the 1-, 3- and 5-year survival rate in NSCLC patients with positive TuM2-PK, CEA, and CYFRA21-1 was significantly lower than that in NSCLC patients with negative TuM2-PK, CEA, and CYFRA21-1, respectively (P < .05). Conclusions: Serum TuM2-PK, CEA, and CYFRA21-1 levels have high clinical values in the diagnosis of NSCLC, and can effectively judge the prognosis of patients.

Biosensors for the detection of lung cancer biomarkers: A review on biomarkers, transducing techniques and recent graphene-based implementations

Lung cancer remains the leading cause of cancer-related death. In addition to chest X-rays and computerised tomography, the detection of cancer biomarkers serves as an emerging diagnostic tool for lung cancer. This review explores biomarkers including the rat sarcoma gene, the tumour protein 53 gene, the epidermal growth factor receptor, the neuron-specific enolase, the cytokeratin-19 fragment 21-1 and carcinoembryonic antigen as potential indicators of lung cancer. Biosensors, which utilise various transduction techniques, present a promising solution for the detection of lung cancer biomarkers. Therefore, this review also explores the working principles and recent implementations of transducers in the detection of lung cancer biomarkers. The transducing techniques explored include optical techniques, electrochemical techniques and mass-based techniques for detecting biomarkers and cancer-related volatile organic compounds. Graphene has outstanding properties in terms of charge transfer, surface area, thermal conductivity and optical characteristics, on top of allowing easy incorporation of other nanomaterials. Exploiting the collective merits of both graphene and biosensor is an emerging trend, as evidenced by the growing number of studies on graphene-based biosensors for the detection of lung cancer biomarkers. This work provides a comprehensive review of these studies, including information on modification schemes, nanomaterials, amplification strategies, real sample applications, and sensor performance. The paper concludes with a discussion of the challenges and future outlook of lung cancer biosensors, including scalable graphene synthesis, multi-biomarker detection, portability, miniaturisation, financial support, and commercialisation.

Improved Cancer-Specific Risk Stratification by the Lymph Node Ratio-Based Nomogram: A Potential Role in Guiding Postoperative Management Decisions for Oral Cavity Carcinoma

PURPOSE

To develop and validate a nomogram integrating lymph node ratio (LNR) to predict cancer-specific survival (CSS) and assist decision making for postoperative management in nonmetastatic oral cavity squamous cell carcinoma (OCSCC).

MATERIALS AND METHODS

We retrospectively retrieved 6,760 patients with OCSCC primarily treated with surgery from surveillance, epidemiology, and end results database between 2010 and 2015. They were randomly divided into training and validation cohorts. Performance of the nomogram was evaluated by calibration curve, consistency index, area under the curve, and decision curve analysis and was compared with that of the LNR, positive lymph nodes (PLN) and tumor node metastasis (TNM) staging. According to the individualized nomogram score, patients were classified into three risk cohorts. The therapeutic efficacy of postoperative radiotherapy and chemotherapy was evaluated in each cohort.

RESULTS

The nomogram incorporated six independent variables, including race, tumor site, grade, T stage, PLN, and LNR. Calibration plots demonstrated a good match between the predicted and observed CSS. C-indices for training and validation cohorts were 0.746 (95% CI, 0.740 to 0.752) and 0.726 (95% CI, 0.713 to 0.739), compared with 0.687, 0.695, and 0.669 for LNR, PLN, and TNM staging, respectively (P < .001). Decision curve analyses confirmed that nomogram showed the best performance in clinical utility. Postoperative radiotherapy presented survival benefit in medium-and high-risk groups but showed a negative effect in the low-risk group. Chemotherapy was only beneficial in the high-risk group.

CONCLUSION

The LN status-incorporated nomogram demonstrated good discrimination and predictive accuracy of CSS for patients with OCSCC and could identify those most likely to benefit from adjuvant therapy.

Preoperative blood markers for prediction of recurrence-free survival after surgical treatment of patients with stage III lung adenocarcinoma

The possibility of the preoperative level of 42 indicators characterizing the cellular composition and metabolism in blood of patients with stage III lung adenocarcinoma (AC) to predict their relapse-free survival was studied. Blood samples of 451 patients with newly diagnosed AK stage III after their surgical treatment (resection volume - R0) have been investigated. The duration of the relapse-free period (period of observation - 1 year), cellular composition of the blood, concentration of C-RP, albumin, Cyfra 21-1 antigens, SCC, TPA, chemokines CXCL5, CXCL8, pyruvate kinase TuM2 PK isoenzyme, HIF-1α and hyaluronic acid in blood serum so as the proportion of blood cells with CXCR1 and CXCR2, CD44V6 receptors in blood serum were measured. To determine the dependence of the duration of the relapse-free period after the treatment on the observation time, Kaplan-Meier graphs were built. The relationship between the determined parameters and survival was judged using single- and multi-factor Cox proportional hazard models. Comparison of groups with different risk of AK recurrence was performed using the Log Rank test and χ2. The assessment of the predictive information content of laboratory tests was carried out using ROC analysis. It was shown that the concentration of monocytes, eosinophilic leukocytes, the relative quantity of lymphocytes with CXCR1 receptor, the level of Cyfra 21-1 before surgical treatment were associated with the duration of the relapse-free period. A regression equation was compiled, which included the level of Cyfra 21-1, relative content of lymphocytes with CXCR1, and the eosinophilic leukocytes / monocytes ratio. Based on the threshold value Y=0,597, a Kaplan-Meier plot of patient survival was built and the results of it correspond to the TNM stratification. The prognostic sensitivity of the results of the equation - 85,7%, the specificity - 94,7%.

Simple diagnosis of cancer by detecting CEA and CYFRA 21-1 in saliva using electronic sensors

One way of early diagnosis of cancer is by detecting the biomarkers that get introduced into easily accessible body fluids. We report the development of portable and rapid electronic biosensors for quantitative detection of two secretive cancer biomarkers-Carcinoembryonic antigen (CEA) and Cytokeratin fragment 19 (CYFRA 21-1). The reduced graphene oxide (rGO)/ melamine (MEL)/antibodies/ bovine serum albumin (BSA) based devices were tested for 1 pg/mL to 800 ng/mL of CEA and CYFRA 21-1. The responses of the sensors ranged from 7.14 to 59.1% and from 6.18 to 64% for 1 pg/mL to 800 ng/mL CEA and CYFRA 21-1 respectively. A read-out circuit was assembled to develop a portable prototype which was used to assess the concentrations of the two antigens present in saliva samples of 14 subjects. The prototype could accurately discriminate between 9 oral squamous cell carcinoma patients and 5 healthy controls.

Lymph node ratio-based nomogram for prognosis evaluation and treatment optimization of non-metastatic oral cavity squamous cell carcinoma

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LNR is an independent prognostic factor over N stage in OCSCC.

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LNR-based nomogram surpasses AJCC TNM staging in predicting outcome of OCSCC.

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LNR-based nomogram is valid in guiding post-operative radiotherapy in OCSCC.

Background

Lymph node ratio (LNR) has been increasingly reported as a prognostic factor in oral cavity squamous cell carcinoma (OCSCC). This study aimed to develop and validate a prognostic nomogram integrating LNR and to further assess its role in guiding adjuvant therapy for OCSCC.

Methods

A total of 8703 OCSCC patients treated primarily with surgery in the Surveillance, Epidemiology and End Results (SEER) database were retrieved and randomly divided into training and validation cohorts. The nomogram was created based on the factors identified by Cox model. The value of PORT and chemotherapy was respectively evaluated in each prognostic group according to nomogram-deduced individualized score.

Results

The final nomogram included tumor site, grade, T stage, number of positive lymph nodes and LNR. Calibration plots demonstrated a good match between predicted and observed rates of overall survival (OS). The concordance indexes for training and validation cohorts were 0.720 (95% confidence interval (CI): 0.708, 0.732) and 0.711 (95% CI: 0.687, 0.735), both significantly higher than did TNM stage (p< 0.001). According to individualized nomogram score, patients were stratified into three subgroups with significantly distinct outcome. PORT presented survival benefit among medium- and high-risk groups whereas a near-detrimental effect in low-risk group. Chemotherapy was found to be beneficial only in high-risk group.

Conclusion

This LNR-incorporated nomogram surpassed the conventional TNM stage in predicting prognosis of patients with non-metastatic OCSCC and identified sub-settings that could gain survival benefit from adjuvant thearpy.

Establishment of a Lung Cancer Discriminative Model Based on an Optimized Support Vector Machine Algorithm and Study of Key Targets of Wogonin in Lung Cancer

An optimized support vector machine model was used to construct a lung cancer diagnosis model based on serological indicators, and a molecular regulation model of Wogonin, a component of Scutellaria baicalensis, was established. Serological indexes of patients were collected, the grid search method was used to identify the optimal penalty coefficient C and parameter g of the support vector machine model, and the benign and malignant auxiliary diagnosis model of isolated pulmonary nodules based on serological indicators was established. The regulatory network and key targets of Wogonin in lung cancer were analyzed by network pharmacology, and key targets were detected by western blot. The relationship between serological susceptibility genes and key targets of Wogonin was established, and the signaling pathway of Wogonin regulating lung cancer was constructed. After support vector machine parameter optimization (C = 90.597, g = 32), the accuracy of the model was 90.8333%, with nine false positives and two false negative cases. Ontology functional analysis of 67 common genes between Wogonin targets and lung cancer–related genes showed that the targets were associated with biological processes involved in peptidye-serine modification and regulation of protein kinase B signaling; cell components in the membrane raft and chromosomal region; and molecular function in protein serine/threonine kinase activity and heme binding. Kyoto Encyclopedia of Genes and Genomes analysis showed that the regulation pathways involved the PI3K-Akt signaling pathway, ERBB signaling pathway, and EGFR tyrosine kinase inhibitor resistance. In vitro analyses using lung cancer cells showed that Wogonin led to significantly increased levels of cleaved caspase-3 and Bad and significantly decreased Bcl-2 expression in a concentration-dependent manner. ErbB4 expression also significantly decreased in lung cancer cells after treatment with Wogonin. A regulatory network of Wogonin regulating lung cancer cell apoptosis was constructed, including the participation of serological susceptibility genes. There is a certain regulatory effect between the serological indexes that can be used in the diagnosis of lung cancer and the key targets of Chinese herbal medicine treatment of lung cancer, which provides a new idea for the diagnosis, treatment and prognosis of clinical lung cancer.

Discovering Panel of Autoantibodies for Early Detection of Lung Cancer Based on Focused Protein Array

Substantial studies indicate that autoantibodies to tumor-associated antigens (TAAbs) arise in early stage of lung cancer (LC). However, since single TAAbs as non-invasive biomarkers reveal low diagnostic performances, a panel approach is needed to provide more clues for early detection of LC. In the present research, potential TAAbs were screened in 150 serum samples by focused protein array based on 154 proteins encoded by cancer driver genes. Indirect enzyme-linked immunosorbent assay (ELISA) was used to verify and validate TAAbs in two independent datasets with 1,054 participants (310 in verification cohort, 744 in validation cohort). In both verification and validation cohorts, eight TAAbs were higher in serum of LC patients compared with normal controls. Moreover, diagnostic models were built and evaluated in the training set and the test set of validation cohort by six data mining methods. In contrast to the other five models, the decision tree (DT) model containing seven TAAbs (TP53, NPM1, FGFR2, PIK3CA, GNA11, HIST1H3B, and TSC1), built in the training set, yielded the highest diagnostic value with the area under the receiver operating characteristic curve (AUC) of 0.897, the sensitivity of 94.4% and the specificity of 84.9%. The model was further assessed in the test set and exhibited an AUC of 0.838 with the sensitivity of 89.4% and the specificity of 78.2%. Interestingly, the accuracies of this model in both early and advanced stage were close to 90%, much more effective than that of single TAAbs. Protein array based on cancer driver genes is effective in screening and discovering potential TAAbs of LC. The TAAbs panel with TP53, NPM1, FGFR2, PIK3CA, GNA11, HIST1H3B, and TSC1 is excellent in early detection of LC, and they might be new target in LC immunotherapy.

A nomogram-based immune-serum scoring system predicts overall survival in patients with lung adenocarcinoma

OBJECTIVE

The immunoscore, which is used to quantify immune infiltrates, has greater relative prognostic value than tumor, node, and metastasis (TNM) stage and might serve as a new system for classification of colorectal cancer. However, a comparable immunoscore for predicting lung adenocarcinoma (LUAD) prognosis is currently lacking.

METHODS

We analyzed the expression of 18 immune features by immunohistochemistry in 171 specimens. The relationship of immune marker expression and clinicopathologic factors to the overall survival (OS) was analyzed with the Kaplan-Meier method. A nomogram was developed by using the optimal features selected by least absolute shrinkage and selection operator (LASSO) regression in the training cohort (n = 111) and evaluated in the validation cohort (n = 60).

RESULTS

The indicators integrated in the nomogram were TNM stage, neuron-specific enolase, carcino-embryonic antigen, CD8center of tumor (CT), CD8invasive margin (IM), FoxP3CT, and CD45ROCT. The calibration curve showed prominent agreement between the observed 2- and 5-year OS and that predicted by the nomogram. To simplify the nomogram, we developed a new immune-serum scoring system (I-SSS) based on the points awarded for each factor in the nomogram. Our I-SSS was able to stratify same-stage patients into different risk subgroups. The combination of I-SSS and TNM stage had better prognostic value than the TNM stage alone.

CONCLUSIONS

Our new I-SSS can accurately and individually predict LUAD prognosis and may be used to supplement prognostication based on the TNM stage.

Downregulation of circ-RANBP9 in laryngeal cancer and its clinical significance

Background

Laryngeal cancer (LC) is a common malignant tumor of the head and neck. As circular RNAs (circRNAs) and other non-coding RNAs are involved in various malignant processes, we analyzed circRNAs to better understand LC and explored specific tumor markers.

Methods

High-throughput sequence was performed to analyze the differential circular RNAs in four coupled laryngeal cancers and para-cancerous tissues. The differential expression of selected circ-RANBP9 in laryngeal cancer tissues and cells was verified by RT-qPCR assay. CCK8, EDU, Transwell and wound healing assays were used to confirm the biological function of circ-RANBP9 in laryngeal cancer. Western blot assay was performed to identify the effects of circ-RANBP9 having on the epithelial to mesenchymal transition process. One-way AN0VA was used to analyze the correlation between the expression of circ-RANBP9 and clinicopathological parameters of the included patients. Kaplan-Meier analysis was used to investigate whether the expression level of circ-RANBP9 correlated with survival in LC patients. Bioinformatic analyses were also conducted to predict the functions and possible signaling pathways of the targeted mRNAs of circ-RANBP9 via co-expression and competing endogenous RNA network.

Results

We found a transcript from RNA sequence data, termed hsa_circ_0001578, which is a circRNA spliced from RANBP9. Circ-RANBP9 was downregulated in the LC cell lines tissues, relating to a better prognosis. Circ-RANBP9 was found to inhibit the proliferation, migration, and invasion ability of LC, exerting a suppressive role in the epithelial to mesenchymal transition process as well. For the diagnostic value of circ-RANBP9, the sensitivity and the specificity were 0.979 and 0.553, respectively. Circ-RANBP9 downregulation was significantly correlated with differentiation (P=0.031), T-stage (P=0.018), lymphatic metastasis (P=0.046), and clinical stage (P=0.003). Circ-RANBP9 was involved in insulin-like growth factor receptor binding, cell polarity, focal adhesion, and MAPK signaling pathways. CeRNA analysis identified the possible involvement of circ-RANBP9 in the ECM-receptor interaction, cAMP, calcium, and Wnt signaling pathways by harboring miRNA genes.

Conclusions

Circ-RANBP9 was confirmed to play important roles in inhibiting laryngeal cancers. Circ-RANBP9 was also validated to be associated with the clinicopathological parameters and diagnostic value, suggesting that circ-RANBP9 is a promising biomarker for LC prognosis and early diagnosis.

Liposome encapsulated electron donor strategy for signal-on CYFRA 21-1 photoelectrochemical analysis

A novel electron donor controlled-release system is proposed based on liposome encapsulated L-cysteine for the sensitive determination of cytokeratin 19 fragment 21-1 (CYFRA 21-1). On the one hand, a defective TiO₂ modified with methylene blue was employed as a photoactive platform which exhibited a high photoelectrochemical (PEC) response owing to the introduction of oxygen vacancies and the high  photosensitivity of the dye. On the other hand, L-cysteine as the sacrificial electron donor was encapsulated in the vesicles of liposomes, and this composite was used as the signal amplification factor, which is labeled on the secondary antibody of CYFRA 21-1 to further improve the photocurrent sensitivity. The excellent electron transfer path in photoactive materials coupled with the skilful electron donor controlled-release system, contributed to the sensitive  PEC analysis of CYFRA 21-1 underoptimum conditions. The PEC immunoassay showed a linear current response in the range 0.0001-100 ng/mL with a detection limitof 37 fg/mL. Enhanced stability and satisfactory reproducibility were also achieved. The proposed concept  provides a novel signal-on strategy for the sensitive detection of other cancer markers in the electrochemical sensing field.

Analysis of the Clinical Diagnostic Value of GMFB in Cerebral Infarction

BACKGROUND

Glial Maturation Factor Beta (GMFB) is a highly conserved brain-enriched protein implicated in immunoregulation, neuroplasticity and apoptosis, processes central to neural injury and repair following cerebral ischaemia. Therefore, we examined if changes in neurocellular GMFB expression and release can be used to assess brain injury following ischaemia.

METHODS AND RESULTS

Immunofluorescence staining, Western blotting, immunohistochemistry and ELISA were used to measure GMFB in cultured neurons and astrocytes, rat brain tissues and plasma samples from stroke model rats and stroke patients, while cell viability assays, TTC staining and micro- PET were used to assess neural cell death and infarct severity. Immunofluorescence and immunohistochemistry revealed GMFB expression mainly in astrocyte and neuronal nuclei but also in neuronal axons and dendrites. Free GMFB concentration increased progressively in the culture medium during hypoxia-hypoglycaemia treatment. Plasma GMFB concentration increased in rats subjected to middle cerebral artery occlusion (MCAO, a model of stroke-reperfusion) and in stroke patients. Plasma GMFB in MCAO model rats was strongly correlated with infarct size (R2=0.9582). Plasma GMFB concentration was also markedly elevated in stroke patients within 24 h of onset and remained elevated for more than one week. Conversely, plasma GMFB elevations were not significant in myocardial infarct patients and stroke patients without infarction.

CONCLUSION

GMFB has the prerequisite stability, expression specificity and response dynamics to serve as a reliable indicator of ischaemic injury in animal models and stroke patients. Plasma GMFB may be a convenient non-invasive adjunct to neuroimaging for stroke diagnosis and prognosis.

Multifunctional neuron-specific enolase: its role in lung diseases

Neuron-specific enolase (NSE), also known as gamma (γ) enolase or enolase-2 (Eno2), is a form of glycolytic enolase isozyme and is considered a multifunctional protein. NSE is mainly expressed in the cytoplasm of neurons and neuroendocrine cells, especially in those of the amine precursor uptake and decarboxylation (APUD) lineage such as pituitary, thyroid, pancreas, intestine and lung. In addition to its well-established glycolysis function in the cytoplasm, changes in cell localization and differential expression of NSE are also associated with several pathologies such as infection, inflammation, autoimmune diseases and cancer. This article mainly discusses the role and diagnostic potential of NSE in some lung diseases.

Nomograms to Predict Survival in Patients with Lung Squamous Cell Cancer: A Population-Based Study

BACKGROUND

This study aimed to identify risk factors affecting cancer-specific survival (CSS) and overall survival (OS) in patients with lung squamous cell carcinoma (LSCC) and to develop nomograms for prognostic prediction in these patients.

METHODS

Patients who received an LSCC diagnosis between 2007 and 2013 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. The prognostic effect of each variable on survival was evaluated with Cox regression and Kaplan-Meier analysis, and nomograms were developed to predict 3-, 5-, and 7-year CSS and OS rates.

RESULTS

Data from 23,004 patients with LSCC were analyzed. Nomograms were first developed by using variables that were significantly associated with CSS and OS and then validated by using an internal bootstrap resampling approach, which showed that they had a sufficient level of discrimination, according to the C-index.

CONCLUSIONS

The nomograms satisfactorily predicted 3-, 5-, and 7-year CSS and OS rates for patients with LSCC.

Applications and strategies in nanodiagnosis and nanotherapy in lung cancer

Lung cancer is the second most common cancer and the leading cause of death in both men and women in the world. Lung cancer is heterogeneous in nature and diagnosis is often at an advanced stage as it develops silently in the lung and is frequently associated with high mortality rates. Despite the advances made in understanding the biology of lung cancer, progress in early diagnosis, cancer therapy modalities and considering the mechanisms of drug resistance, the prognosis and outcome still remains low for many patients. Nanotechnology is one of the fastest growing areas of research that can solve many biological problems such as cancer. A growing number of therapies based on using nanoparticles (NPs) have successfully entered the clinic to treat pain, cancer, and infectious diseases. Recent progress in nanotechnology has been encouraging and directed to developing novel nanoparticles that can be one step ahead of the cancer reducing the possibility of multi-drug resistance. Nanomedicine using NPs is continuingly impacting cancer diagnosis and treatment. Chemotherapy is often associated with limited targeting to the tumor, side effects and low solubility that leads to insufficient drug reaching the tumor. Overcoming these drawbacks of chemotherapy by equipping NPs with theranostic capability which is leading to the development of novel strategies. This review provides a synopsis of current progress in theranostic applications for lung cancer diagnosis and therapy using NPs including liposome, polymeric NPs, quantum dots, gold NPs, dendrimers, carbon nanotubes and magnetic NPs.

Prognostic model based on circular RNA circPDK1 for resected lung squamous cell carcinoma

Background

Circular RNA has been revealed as a potential biomarker in multiple malignancies. However, few studies have focused on its potential to be prognostic markers in lung squamous cell carcinoma (LSCC). In this work, we aimed to build a prognostic model of resected LSCC based on circular RNA pyruvate dehydrogenase kinase 1 (circPDK1) and other clinicopathological factors.

Methods

circPDK1 was identified via next-generation sequencing. Three hundred two cases of LSCC tissue and their adjacent normal lung tissues were obtained from multiple medical centers and divided into study cohort (n=232) and validation cohort (n=70). The expression of circPDK1 was detected for analyzing its potential prognostic value for recurrence-free survival (RFS) and overall survival (OS) in LSCC. Finally, combined with circPDK1, T staging, lymph nodes (LN) metastasis status, age, and serum squamous cell Carcinoma Antigen (SCCAg), we built a prognostic model by nomograms method and confirmed it in the validation cohort.

Results

CircPDK1 was identified to be overexpressed (P<0.01) in LSCC. Through analysis in study cohort, circPDK1^low patients (less than the mean expression, n=124) showed more lymph nodes metastasis (P=0.025), more vascular invasion (VI) (P=0.047), more visceral pleural invasion (VPI) (P=0.015) and poorer prognosis (P=0.003) than circPDK1^high ones (n=108). Univariate and multivariate analysis showed that circPDK1, T staging, LN status, age, and SCCAg were significant prognostic factors for RFS and OS. The prognostic model based on these factors showed the concordance index (C-index) of 0.8214 and 0.8359 for predicting 5-year RFS and OS, respectively. Finally, the calibration curves were performed in the study cohort and a validation cohort to evaluate the model's efficiency.

Conclusions

circPDK1 was identified as a potential biomarker of resected LSCC. The prognostic model including circPDK1, T staging, LN status, age, and SCCAg could effectively predict prognosis of resected LSCC.

A Prediction Rule for Overall Survival in Non-Small-Cell Lung Cancer Patients with a Pathological Tumor Size Less Than 30 mm

We sought to develop and validate a clinical nomogram model for predicting overall survival (OS) in non-small-cell lung cancer (NSCLC) patients with resected tumors that were 30 mm or smaller, using clinical data and molecular marker findings. We retrospectively analyzed 786 NSCLC patients with a pathological tumor size less than 30 mm who underwent surgery between 2007 and 2017 at our institution. We identified and integrated significant prognostic factors to build the nomogram model using the training set, which was subjected to the internal data validation. The prognostic performance was calibrated and evaluated by the concordance index (C-index) and risk group stratification. Multivariable analysis identified the pathological tumor size, lymph node metastasis, and Ki-67 expression as independent prognostic factors, which were entered into the nomogram model. The nomogram-predicted probabilities of OS at 1 year, 3 years, and 5 years posttreatment represented optimal concordance with the actual observations. Harrell's C-index of the constructed nomogram with the training set was 0.856 (95% CI: 0.804-0.908), whereas TNM staging was 0.814 (95% CI: 0.742-0.886, P = 5.280221e − 13). Survival analysis demonstrated that NSCLC subgroups showed significant differences in the training and validation sets (P < 0.001). A nomogram model was established for predicting survival in NSCLC patients with a pathological tumor size less than 30 mm, which would be further validated using demographic and clinicopathological data. In the future, this prognostic model may assist clinicians during treatment planning and clinical studies.

A combination of tumor and molecular markers predicts a poor prognosis in lung adenocarcinoma

PURPOSE

Whether patients with stage IA-IIA lung adenocarcinoma require conventional chemotherapy is still a controversy. An ideal metastasis risk prediction model in lung adenocarcinoma is valuable for determining the prognosis and giving timely, individualized treatment.

RESULTS

Analyzing the clinical cases of 153 lung adenocarcinoma patients using an χ² test, Kaplan-Meier survival curves, and a multivariate logistic regression analysis, we selected the most valuable factors for determining metastasis and constructed metastasis prediction models. We confirmed the importance of the tumor markers (CEA, NSE) and a molecular marker (CAMKII) as independent prognostic factors in lung adenocarcinoma. The result of a five-year survival status was significantly associated with CAMKII and CEA (P < 0.05). A nomogram was created using CEA, NSE, CYFRA 21-1, and CAMKII to estimate the metastasis probability for individuals, specifically, 78 stage I lung adenocarcinoma patients were used to verify the effectiveness of the nomogram. Using machine learning, LASSO selected the subset of variables that minimized the predictive error of the outcome, including CEA, NSE, CYFRA 21-1, CAMKII, tumor size, histologic type, lymph node status, smoking, and age. A ten-fold cross-validation showed the average accuracy of this model was 86.208%, with an area under the curve of 0.857, a sensitivity value of 0.840, and a specificity value of 0.873.

CONCLUSION

Using both complementary methods, the predictive models illustrated that the combination of tumor markers and a key molecule to predict the prognosis of lung adenocarcinoma patients in early stages is valuable. The postoperative transfer rate of stage I patients can be effectively predicted by these complementary methods.