Screening for early stage lung cancer and its correlation with lung nodule detection

USP32 facilitates non-small cell lung cancer progression via deubiquitinating BAG3 and activating RAF-MEK-ERK signaling pathway

The regulatory significance of ubiquitin-specific peptidase 32 (USP32) in tumor is significant, nevertheless, the biological roles and regulatory mechanisms of USP32 in non-small cell lung cancer (NSCLC) remain unclear. According to our research, USP32 was strongly expressed in NSCLC cell lines and tissues and was linked to a bad prognosis for NSCLC patients. Interference with USP32 resulted in a significant inhibition of NSCLC cell proliferation, migration potential, and EMT development; on the other hand, USP32 overexpression had the opposite effect. To further elucidate the mechanism of action of USP32 in NSCLC, we screened H1299 cells for interacting proteins and found that USP32 interacts with BAG3 (Bcl2-associated athanogene 3) and deubiquitinates and stabilizes BAG3 in a deubiquitinating activity-dependent manner. Functionally, restoration of BAG3 expression abrogated the antitumor effects of USP32 silencing. Furthermore, USP32 increased the phosphorylation level of the RAF/MEK/ERK signaling pathway in NSCLC cells by stabilizing BAG3. In summary, these findings imply that USP32 is critical to the development of NSCLC and could offer a theoretical framework for the clinical diagnosis and management of NSCLC patients in the future.

Identification and Application of Emerging Biomarkers in Treatment of Non-Small-Cell Lung Cancer: Systematic Review

Non-small-cell lung cancer (NSCLC) comprises approximately 85% of all lung cancer cases, often diagnosed at advanced stages, which diminishes the effective treatment options and survival rates. This systematic review assesses the utility of emerging biomarkers-circulating tumor DNA (ctDNA), microRNAs (miRNAs), and the blood tumor mutational burden (bTMB)-enhanced by next-generation sequencing (NGS) to improve the diagnostic accuracy, prognostic evaluation, and treatment strategies in NSCLC. Analyzing data from 37 studies involving 10,332 patients from 2020 to 2024, the review highlights how biomarkers like ctDNA and PD-L1 expression critically inform the selection of personalized therapies, particularly beneficial in the advanced stages of NSCLC. These biomarkers are critical for prognostic assessments and in dynamically adapting treatment plans, where high PD-L1 expression and specific genetic mutations (e.g., ALK fusions, EGFR mutations) significantly guide the use of targeted therapies and immunotherapies. The findings recommend integrating these biomarkers into standardized clinical pathways to maximize their potential in enhancing the treatment precision, ultimately fostering significant advancements in oncology and improving patient outcomes and quality of life. This review substantiates the prognostic and predictive value of these biomarkers and emphasizes the need for ongoing innovation in biomarker research.

Gut microbes as medical signature for the effectiveness of immunotherapy in patients with advanced non-small cell lung cancer

Lung cancer (LC) is the most common cause of cancer-related death worldwide and poses a severe threat to public health. Immunotherapy with checkpoint blockers has improved the outlook for advanced non-small cell lung cancer (NSCLC) therapy. For the treatment of patients with advanced NSCLC, antibodies such as anti-programmed death 1 (anti-PD1), anti-programmed death ligand 1 (anti-PD-L1), and anti-cytotoxic T lymphocyte-associated antigen 4 (anti-CTLA-4) are of paramount importance. Anti-PD-1 and anti-PD-L1 monoclonal antibody therapies are used to block the PD-1/PD-L1 pathway and identify cancerous cells to the body's defenses. Antibodies directed against CTLA-4 (anti-CTLA-4) have also been shown to improve survival rates in patients with NSCLC. Currently, other immunotherapy approaches like neoadjuvant immune checkpoint inhibitors (NAICIs) and chimeric antigen receptor T-cell (CAR-T) therapies are applied in NSCLC patients. NAICIs are used for resectable and early stage NSCLC and CAR-T is used to find more useful epitope sites for lung tumors and destroy cancer cells. A patient's gut microbiota might influence how their immune system reacts to NSCLC immunotherapy. The majority of intestinal microbes stimulate helper/cytotoxic T cells, induce natural killer (NK) cells, activate various toll-like receptors (TLR), build up cluster of differentiation 8 (CD8), increase PD-1 production, and attract chemokine receptors towards cancer cells. Thus, they serve as immune inducers in NSCLC immunotherapy. Nonetheless, certain bacteria can function as immune suppressors by inhibiting DC proliferation, stopping CD28 trafficking, restoring CD80/CD86, increasing immunological tolerance, and upsetting Th17 cells. Therefore, they are prevalent in non-responders with NSCLC immunotherapy.

Classification of Pulmonary Nodules in 2-[18F]FDG PET/CT Images with a 3D Convolutional Neural Network

Purpose

2-[18F]FDG PET/CT plays an important role in the management of pulmonary nodules. Convolutional neural networks (CNNs) automatically learn features from images and have the potential to improve the discrimination between malignant and benign pulmonary nodules. The purpose of this study was to develop and validate a CNN model for classification of pulmonary nodules from 2-[18F]FDG PET images.

Methods

One hundred thirteen participants were retrospectively selected. One nodule per participant. The 2-[18F]FDG PET images were preprocessed and annotated with the reference standard. The deep learning experiment entailed random data splitting in five sets. A test set was held out for evaluation of the final model. Four-fold cross-validation was performed from the remaining sets for training and evaluating a set of candidate models and for selecting the final model. Models of three types of 3D CNNs architectures were trained from random weight initialization (Stacked 3D CNN, VGG-like and Inception-v2-like models) both in original and augmented datasets. Transfer learning, from ImageNet with ResNet-50, was also used.

Results

The final model (Stacked 3D CNN model) obtained an area under the ROC curve of 0.8385 (95% CI: 0.6455-1.0000) in the test set. The model had a sensibility of 80.00%, a specificity of 69.23% and an accuracy of 73.91%, in the test set, for an optimised decision threshold that assigns a higher cost to false negatives.

Conclusion

A 3D CNN model was effective at distinguishing benign from malignant pulmonary nodules in 2-[18F]FDG PET images.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13139-023-00821-6.

Diagnostic Yield of Cone-beam-Derived Augmented Fluoroscopy and Ultrathin Bronchoscopy Versus Conventional Navigational Bronchoscopy Techniques

BACKGROUND

Pulmonary nodules suspicious for lung cancer are frequently diagnosed. Evaluating and optimizing the diagnostic yield of lung nodule biopsy is critical as innovation in bronchoscopy continues to progress.

METHODS

This is a retrospective cohort study. Consecutive patients undergoing guided bronchoscopy for suspicious pulmonary nodule(s) between February 2020 and July 2021 were included. The cone-beam computed tomography (CBCT)+ radial endobronchial ultrasound (r-EBUS) group had their procedure using CBCT-derived augmented fluoroscopy along with r-EBUS. The CBCT+ ultrathin bronchoscope (UTB)+r-EBUS group had the same procedure but with the use of an ultrathin bronchoscope. The r-EBUS group underwent r-EBUS guidance without CBCT or augmented fluoroscopy. We used multivariable logistic regression to compare diagnostic yield, adjusting for confounding variables.

RESULTS

A total of 116 patients were included. The median pulmonary lesion diameter was 19.5 mm (interquartile range, 15.0 to 27.5 mm), and 91 (78.4%) were in the peripheral half of the lung. Thirty patients (25.9%) underwent CBCT+UTB, 27 (23.3%) CBCT, and 59 (50.9%) r-EBUS alone with unadjusted diagnostic yields of 86.7%, 70.4%, and 42.4%, respectively ( P <0.001). The adjusted diagnostic yields were 85.0% (95% CI, 68.6% to 100%), 68.3% (95% CI, 50.1% to 86.6%), and 44.5% (95% CI, 31.0% to 58.0%), respectively. There was significantly more virtual navigational bronchoscopy use in the r-EBUS group (45.8%) compared with the CBCT+UTB (13.3%) and CBCT (18.5%) groups, respectively. CBCT procedures required dose area product radiation doses of 7602.5 µGym 2 .

CONCLUSION

Compared with the r-EBUS group, CBCT + UTB + r-EBUS was associated with higher navigational success, fewer nondiagnostic biopsy results, and a higher diagnostic yield. CBCT procedures are associated with a considerable radiation dose.

Qualitative (and Quantitative) Values of the Lung-RADS and Computed Tomography in Diagnosing Solitary Pulmonary Nodules

Background: Lung-RADS classification and CT signs can both help in the differential diagnosis of SPNs. The purpose of this study was to investigate the diagnostic value of these two methods and the combination of the two methods for solitary pulmonary nodules (SPNs). Methods: A total of 296 cases of SPNs were retrospectively analyzed. All the SPNs were classified according to the Lung-RADS grading version 1.1. The scores of each lesion were calculated according to their CT signs. Imaging features, such as the size and margin of the lesions, pleural traction, spiculation, lobulation, bronchial cutoff, air bronchogram, vacuoles, tumor vasculature, and cavity signs, were analyzed. The imaging results were compared with the pathology examination findings. Receiver operating characteristic (ROC) curves were applied to compare the values of the different methods in differentially diagnosing benign and malignant SPNs. Results: The sensitivity, specificity, and accuracy of Lung-RADS grading for diagnosing SPNs were 34.0%, 94.4%, and 47.6%, respectively. The area under the ROC curve (AUC) was 0.600 (p < 0.001). The sensitivity, specificity, and accuracy of the CT sign scores were 56.3%, 70.0%, and 60.5%, respectively, and the AUC was 0.657 (p < 0.001). The sensitivity, specificity, and accuracy of the combination of the two methods for diagnosing SPNs were 93.2%, 61.1%, and 83.5%, and the AUC was 0.777 (p < 0.001). Conclusion: The combination of Lung-RADS classification and CT signs significantly improved the differential diagnosis of SPNs.

Chemokines and NSCLC: Emerging role in prognosis, heterogeneity, and therapeutics

Lung cancer persists to contribute to one-quarter of cancer-associated deaths. Among the different histologies, non-small cell lung cancer (NSCLC) alone accounts for 85% of the cases. The development of therapies involving immune checkpoint inhibitors and angiogenesis inhibitors has increased patients' survival probability and reduced mortality rates. Developing targeted therapies against essential genetic alterations also translates to better treatment strategies. But the benefits still seem farfetched due to the development of drug resistance and refractory tumors. In this review, we have highlighted the interplay of different tumor microenvironment components, essentially discussing the chemokine families (CC, CXC, C, and CX3C) that regulate the tumor biology in NSCLC and promote tumor growth, metastasis, and associated heterogeneity. The development of therapeutics and prognostic markers is a complex and multipronged approach. However, some essential chemokines can act as critical players for being considered potential prognostic markers and therapeutic targets.

MS-ResNet: disease-specific survival prediction using longitudinal CT images and clinical data

PURPOSE

Medical imaging data of lung cancer in different stages contain a large amount of time information related to its evolution (emergence, development, or extinction). We try to explore the evolution process of lung images in time dimension to improve the prediction of lung cancer survival by using longitudinal CT images and clinical data jointly.

METHODS

In this paper, we propose an innovative multi-branch spatiotemporal residual network (MS-ResNet) for disease-specific survival (DSS) prediction by integrating the longitudinal computed tomography (CT) images at different times and clinical data. Specifically, we first extract the deep features from the multi-period CT images by an improved residual network. Then, the feature selection algorithm is used to select the most relevant feature subset from the clinical data. Finally, we integrate the deep features and feature subsets to take full advantage of the complementarity between the two types of data to generate the final prediction results.

RESULTS

The experimental results demonstrate that our MS-ResNet model is superior to other methods, achieving a promising 86.78% accuracy in the classification of short-survivor, med-survivor, and long-survivor.

CONCLUSION

In computer-aided prognostic analysis of cancer, the time dimension features of the course of disease and the integration of patient clinical data and CT data can effectively improve the prediction accuracy.

Role of Cytokines and Chemokines in NSCLC Immune Navigation and Proliferation

With over a million deaths every year around the world, lung cancer is found to be the most recurrent cancer among all types. Nonsmall cell lung carcinoma (NSCLC) amounts to about 85% of the entire cases. The other 15% owes it to small cell lung carcinoma (SCLC). Despite decades of research, the prognosis for NSCLC patients is poorly understood with treatment options limited. First, this article emphasises on the part that tumour microenvironment (TME) and its constituents play in lung cancer progression. This review also highlights the inflammatory (pro- or anti-) roles of different cytokines (ILs, TGF-β, and TNF-α) and chemokine (CC, CXC, C, and CX3C) families in the lung TME, provoking tumour growth and subsequent metastasis. The write-up also pinpoints recent developments in the field of chemokine biology. Additionally, it covers the role of extracellular vesicles (EVs), as alternate carriers of cytokines and chemokines. This allows the cytokines/chemokines to modulate the EVs for their secretion, trafficking, and aid in cancer proliferation. In the end, this review also stresses on the role of these factors as prognostic biomarkers for lung immunotherapy, apart from focusing on inflammatory actions of these chemoattractants.

Breaking potentially bad news of cancer workup to well-informed patients by telephone versus in-person: A randomised controlled trial on psychosocial consequences

BACKGROUND

The use of telephone in delivering cancer care increases, but not in cancer workup. Current protocols for breaking bad news assume a single in-person meeting. Cancer workup involves multiple opportunities for patient information. We investigated the psychosocial consequences in gradually informed patients of receiving lung cancer workup results by telephone versus in-person.

METHODS

A randomised, controlled, open-label, assessor-blinded, single-centre trial including patients referred for invasive workup for suspected malignancy (clinical trials no. NCT04315207). Patients were informed on probable cancer at referral, after imaging, and on the day of invasive workup (Baseline visit). Primary endpoint: change (Δ) from baseline to follow-up (4 weeks after receiving workup results) in scores of a validated, sensitive, condition-specific questionnaire (COS-LC) assessing consequences on anxiety, behaviour, dejection and sleep.

RESULTS

Of 492 eligible patients, we randomised 255 patients (mean age: 68 years; female: 38%; malignancy diagnosed: 68%) to the telephone (n = 129) or in-person (n = 126) group. Groups were comparable at baseline and follow-up, and no between-groups difference in ΔCOS-LC was observed in the intention-to-treat population, or in subgroups diagnosed with or without malignancy.

CONCLUSION

Breaking final result of cancer workup by telephone is not associated with adverse psychosocial consequences compared to in-person conversation in well-informed patients.

Reduced expression of circRNA novel_circ_0005280 and its clinical value in the diagnosis of non-small cell lung cancer

Background

Circular RNAs (circRNAs) are a class of novel RNAs with important biologic functions. The aberrant expression of circRNAs has been implicated in human diseases; however, the clinical significance of circRNAs in non-small cell lung cancer (NSCLC) is still unclear. The aim of the present study was to evaluate the expression and clinical implications of novel_circ_0005280 in patients with NSCLC.

Methods

We evaluated differential circRNA expression in cancer and adjacent normal tissues from 3 patients with NSCLC via RNA sequencing. Among these circRNAs, 17 and 64 circRNAs showed higher and lower expressions, respectively. Novel_circ_0005280 expression in cancer tissues (n=41) was examined using quantitative real-time polymerase chain reaction, and the results are presented in the form of paired graph and scatter graph and its correlation with clinicopathological features and patient prognosis was analyzed by drawing receiver-operating characteristic (ROC) curve and Kaplan-Meier survival analysis.

Results

Novel_circ_0005280 expression was significantly decreased in NSCLC tumor tissues (n=41, obtained via biopsies), compared with adjacent normal tissues (n=27). Novel_circ_0005280 expression was correlated with tumor diameter and age. The area under the receiver-operating characteristic curve, cutoff, sensitivity, and specificity of novel_circ_0005280 were 0.944, 10.23, 85.2%, and 95.1%, respectively. Low novel_circ_0005280 expression was associated with a worse prognosis.

Conclusions

Novel_circ_0005280 may be a useful biomarker for the diagnosis and prognosis of NSCLC.

Comparison of the outcomes of sublobar resection and stereotactic body radiotherapy for stage T1-2N0M0 non-small cell lung cancer with tumor size ≤ 5 cm: a propensity score matching analysis

Background

Surgery and stereotactic body radiotherapy (SBRT) are both suitable treatment options for early stage Non-small cell lung cancer (NSCLC), which accounts for the majority of lung cancer. This study compared the outcomes of sublobar resection (SLR) and SBRT in patients with stage T1-2N0M0 NSCLC with tumor size ≤5 cm.

Methods

Patients with T1-2N0M0 lung cancer who underwent SLR or SBRT between January, 2012 and December, 2016 were included in this retrospective study. The survival outcomes and toxicity of the SLR and SBRT cohorts were compared using Kaplan-Meier survival plots. In a second exploratory analysis, propensity score matching (PSM) was applied to reduce selection bias between the two groups of patients.

Results

A total of 121 SLR and 109 SBRT cases were included. The average follow-up was 49.4 months. Prior to PSM, the 5-year overall survival (OS) and cancer-specific survival (CSS) rates in the SLR group (82.8% and 89.0%, respectively) were superior to those in the SBRT group (67.0% and 75.3%; P=0.001 and P=0.013, respectively). There were no statistically significant differences in the five-year locoregional control and disease-free survival (DFS) rates between the groups. PSM identified 40 patients from each treatment group who shared similar characteristics. At 5 years, the OS rates in the SLR and SBRT groups were comparable (79.9% vs. 66.5%, respectively; P=0.154). After PSM, the rates of CSS, locoregional control, and DFS were also similar between the groups (P=0.458, 0.369, and 0.698, respectively). In the SBRT group, one patient developed grade 3 radioactive pneumonitis. No grade >3 toxicities or treatment-related deaths occurred in either group.

Conclusions

SBRT may be an alternative option to SLR for patients who cannot tolerate lobectomy because of medical comorbidities and has a similar level of effectiveness.

A Task-dependent Investigation on Dose and Texture in CT Image Reconstruction

Localizing and characterizing clinically-significant lung nodules, a potential precursor to lung cancer, at the lowest achievable radiation dose is demanded to minimize the stochastic radiation effects from x-ray computed tomography (CT). A minimal dose level is heavily dependent on the image reconstruction algorithms and clinical task, in which the tissue texture always plays an important role. This study aims to investigate the dependence through a task-based evaluation at multiple dose levels and variable textures in reconstructions with prospective patient studies. 133 patients with a suspicious pulmonary nodule scheduled for biopsy were recruited and the data was acquired at120kVp with three different dose levels of 100, 40 and 20mAs. Three reconstruction algorithms were implemented: analytical filtered back-projection (FBP) with optimal noise filtering; statistical Markov random field (MRF) model with optimal Huber weighting (MRF-H) for piecewise smooth reconstruction; and tissue-specific texture model (MRF-T) for texture preserved statistical reconstruction. Experienced thoracic radiologists reviewed and scored all images at random, blind to the CT dose and reconstruction algorithms. The radiologists identified the nodules in each image including the 133 biopsy target nodules and 66 other non-target nodules. For target nodule characterization, only MRF-T at 40mAs showed no statistically significant difference from FBP at 100mAs. For localizing both the target nodules and the non-target nodules, some as small as 3mm, MRF-T at 40 and 20mAs levels showed no statistically significant difference from FBP at 100mAs, respectively. MRF-H and FBP at 40 and 20mAs levels performed statistically differently from FBP at 100mAs. This investigation concluded that (1) the textures in the MRF-T reconstructions improves both the tasks of localizing and characterizing nodules at low dose CT and (2) the task of characterizing nodules is more challenging than the task of localizing nodules and needs more dose or enhanced textures from reconstruction.

Evaluating the efficacy of bronchoscopy for the diagnosis of early stage lung cancer

Novel diagnostic techniques for lung cancer are rapidly evolving. Specifically, several novel changes to bronchoscopy are reaching clinical evaluation. It is critical to think about historical standards for evaluating new diagnostic testing, and put those concepts into the framework of lung cancer. Often a thorough evaluation of new technology is not performed as a part of regulatory marketing clearance. Therefore, we must consider how to best study novel testing beyond these regulatory minimums. There are several methodological principles that can achieve this goal such as using a control arm, more thorough reporting of enrolled patients, consecutive patient enrollment, and adequate sample size. We hope clinicians, particularly those performing bronchoscopy for lung nodules, will feel empowered to critically appraise the evaluation of new diagnostic testing for lung cancer moving forward.

hsa_circRNA_012515 Is Highly Expressed in NSCLC Patients and Affects Its Prognosis

Background

NSCLC is one of the most common and most lethal malignancies throughout the world, and there is still a lack of sensitive diagnostic biomarkers. Identifying novel NSCLC biomarkers can help with the diagnosis and clinical decision-making.

Methods

Identifying the differentially expressed circRNAs in three cases of NSCLC tissues by high-throughput circRNA microarray sequencing. qRT-PCR was employed to detect the expression levels of hsa_circRNA_012515 in 80 cases of NSCLC tissues (tumor resection patients) and 60 cases of peripheral blood samples (chemotherapy patients), NSCLC cells and gefitinib-resistant NSCLC cell lines. Then combining with clinical data, we discussed whether it was feasible to use hsa_circRNA_012515 as the diagnostic and prognostic biomarker for NSCLC.

Results

In the cancerous tissues from NSCLC patients, NSCLC cells and gefitinib-resistant cell lines, the average expressions of hsa_circRNA_012515 increased significantly (P<0.01). Patients of stage III–IV, with lymph node metastases, had an overexpression of hsa_circRNA_012515. High expression of hsa_circRNA_012515 was associated with lower OS and shorter PFS, and it is closely related to the prognosis of the patients. Bioinformatic analysis indicated that hsa_circRNA_012515 interacted with 5 miRNAs. This finding may shed new light on the subsequent studies on the working mechanism and functions.

Conclusion

Our study showed that hsa_circRNA_012515 may be a novel biomarker candidate for NSCLC. However, further studies are needed to ascertain the working mechanism of hsa_circRNA_012515 in the occurrence and development of NSCLC.

Spiral wire localization of lung nodules: procedure effectiveness and oncological usefulness

Background

In the last years, a large number of techniques and devices for localizing small pulmonary nodules prior to resection have been developed with the aim of facilitating minimally invasive surgery (VATS). However, each device presents pros and cons and there is no unanimous consensus. We report our experience with an uncommon wire system with spiral shape for percutaneous marking.

Methods

We recorded 102 consecutive CT-guided spiral wire localizations in our Institution, and we evaluated the efficacy of the method according to 4 success rates (SR): (I) successful targeting rate (SR-1): number of successful targeting procedures/number of all localizations; (II) successful localization in operative field (SR-2): (number of successful targeting procedures -number of dislodgements in operative field)/number of all localizations; (III) successful VATS rate (SR-3): number of successful VATS procedures/(number of localizations-number of thoracotomies not due to wire dislocation); (IV) successful curative rate (SR-4): number of neoplastic nodules resected with curative intent with free margins (R0) on definitive tissue diagnosis/number of neoplastic nodules resected with curative intent. Complications rate was recorded as well.

Results

SR-1: 100%, SR-2: 97.1%, SR-3: 100%, SR-4: 100%. Asymptomatic pneumothorax and minimal parenchymal hemorrhage were observed in 5 (4.9%) and 19 (18.6%) cases, respectively.

Conclusions

Spiral wire localization showed very good results in terms of feasibility, stability in operative field and contributed to effective use of VATS during wedge resection performed for malignant nodules. In the era of widespread radiological investigations (as it is happening in lung cancer screening) and evolutions in cancer treatments, this appears to be clinically relevant.

Volumetric assessment of solid pulmonary nodules on ultralow-dose CT: a phantom study

Background

To reduce the radiation exposure from chest computed tomography (CT), ultralow-dose CT (ULDCT) protocols performed at sub-millisievert levels were previously tested for the evaluation of pulmonary nodules (PNs). The purpose of our study was to investigate the effect of ULDCT and iterative image reconstruction on volumetric measurements of solid PNs.

Methods

CT datasets of an anthropomorphic chest phantom containing solid microspheres were obtained with a third-generation dual-source CT at standard dose, 1/8th, 1/20th and 1/70th of standard dose [CT volume dose index (CTDI_vol): 0.03-2.03 mGy]. Semi-automated volumetric measurements were performed on CT datasets reconstructed with filtered back projection (FBP) and advanced modelled iterative reconstruction (ADMIRE), at strength level 3 and 5. Absolute percentage error (APE) evaluated measurement accuracy related to the effective volume. Scan repetition differences were evaluated using Bland-Altman analysis. Two-way analysis of variance (ANOVA) assessed influence of different scan parameters on APE. Proportional differences (PDs) tested the effect of dose settings and reconstruction algorithms on volumetric measurements, as compared to the standard protocol (standard dose-FBP).

Results

Bland-Altman analysis revealed small mean interscan differences of APE with narrow limits of agreement (-0.1%±4.3% to -0.3%±3.8%). Dose settings (P<0.001), reconstruction algorithms (P<0.001), nodule diameters (P<0.001) and nodule density (P=0.011) had statistically significant influence on APE. Post-hoc Bonferroni tests showed slightly higher APE when scanning with 1/70th of standard dose [mean difference: 3.4%, 95% confidence interval (CI): 2.5-4.3%; P<0.001], and for image reconstruction with ADMIRE5 (mean difference: 1.8%, 95% CI: 1.0-2.5%; P<0.001). No significant differences for scanning with 1/20th of standard dose (P=0.42), and image reconstruction with ADMIRE3 (P=0.19) were found. Scanning with 1/70th of standard dose and image reconstruction with FBP showed the widest range of PDs (-16.8% to 23.4%) compared to standard dose-FBP.

Conclusions

Our phantom study showed no significant difference between nodule volume measurements on standard dose CT (CTDI_vol: 2 mGy) and ULDCT with 1/20th of standard dose (CTDI_vol: 0.10 mGy).

A promising role of interferon regulatory factor 5 as an early warning biomarker for the development of human non-small cell lung cancer

OBJECTIVES

Non-small cell lung cancer (NSCLC) accounts for 85%-90% of lung cancer cases and is a covert disease lacking early symptoms. Since cancer is recognised as an inflammation-associated condition, we analysed the relationship between the expression of interferon regulatory factor 5 (IRF5), a key transcription factor controlling inflammatory responses, and NSCLC development with the aim of identifying a warning biomarker for early diagnosis of the disease.

MATERIALS AND METHODS

The expression of IRF5 and its associated inflammatory factors IL-6, IL-10, IP-10, and TNF-α in the peripheral blood of NSCLC patients (n = 66) and healthy controls (n = 42) was analysed by quantitative RT-PCR, flow cytometry, and a cytometric bead array. IRF5 protein expression in NSCLC tissues (n = 102) was detected by Western blotting. The diagnostic value of IRF5 expression was determined by a receiver-operating characteristic (ROC) curve analysis.

RESULTS

The protein levels of IRF5, IL-6, and IP-10 were significantly higher in the peripheral blood of NSCLC patients than in that of healthy controls. IP-10 levels in plasma and IL-10 mRNA expression in white blood cells (WBCs) were significantly upregulated in early-stage NSCLC, whereas plasma IL-6 and IL-10 were elevated in the progressive stage. IRF5 protein levels in WBCs were positively correlated with plasma IP-10 but negatively correlated with plasma IL-10. Furthermore, the mRNA and protein levels of IRF5 in WBCs were significantly elevated in patients with early stage NSCLC compared to those in the progressive stage. Additionally, IRF5 protein levels were significantly lower in NSCLC tumour tissues than those in normal lung tissues.

CONCLUSIONS

IRF5 levels in WBCs can be significantly upregulated in early stage NSCLC and were shown to have diagnostic value as an early warning biomarker of NSCLC development.