Lung cancer screening in the randomized Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial

Potentially functional variants of PARK7 and DDR2 in ferroptosis-related genes predict survival of non-small cell lung cancer patients

Ferroptosis, a form of regulated cell death, is characterized by iron-dependent lipid peroxidation. It is recognized increasingly for its pivotal role in both cancer development and the response to cancer treatments. We assessed associations between 370,027 single-nucleotide polymorphisms (SNPs) within 467 ferroptosis-related genes and survival of non-small cell lung cancer (NSCLC) patients. Data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial served as our discovery dataset, while the Harvard Lung Cancer Susceptibility Study used as our validation dataset. For SNPs that remained statistically significantly associated with overall survival (OS) in both datasets, we employed a multivariable stepwise Cox proportional hazards regression model with the PLCO dataset. Ultimately, two independent SNPs, PARK7 rs225120 C>T and DDR2 rs881127 T>C, were identified with adjusted hazard ratios of 1.32 (95% confidence interval = 1.15-1.52, p = .0001) and 1.34 (95% confidence interval = 1.09-1.64, p = .006) for OS, respectively. We aggregated these two SNPs into a genetic score reflecting the number of unfavorable genotypes (NUG) in further multivariable analysis, revealing a noteworthy association between increased NUG and diminished OS (ptrend = .001). Additionally, an expression quantitative trait loci analysis indicated that PARK7 rs225120T genotypes were significantly associated with higher PARK7 mRNA expression levels in both whole blood and normal lung tissue. Conversely, DDR2 rs881127C genotypes were significantly associated with lower DDR2 mRNA expression levels in normal lung tissue. Our findings suggest that genetic variants in the ferroptosis-related genes PARK7 and DDR2 are associated with NSCLC survival, potentially through their influence on gene expression levels.

Potentially functional variants of ERRFI1 in hypoxia-related genes predict survival of non-small cell lung cancer patients

BACKGROUND

Hypoxia is often involved in tumor microenvironment, and the hypoxia-induced signaling pathways play a key role in aggressive cancer phenotypes, including angiogenesis, immune evasion, and therapy resistance. However, it is unknown what role genetic variants in the hypoxia-related genes play in survival of patients with non-small cell lung cancer (NSCLC).

METHODS

We evaluated the associations between 16,092 single-nucleotide polymorphisms (SNPs) in 182 hypoxia-related genes and survival outcomes of NSCLC patients. Data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial were used as the discovery dataset, and the Harvard Lung Cancer Susceptibility (HLCS) Study served as the replication dataset. We also performed additional linkage disequilibrium analysis and a stepwise multivariable Cox proportional hazards regression analysis in the PLCO dataset.

RESULTS

An independent SNP, ERRFI1 rs28624 A > C, was identified with an adjusted hazards ratio (HR) of 1.31 (95% CI = 1.14-1.51, p = 0.0001) for overall survival (OS). In further analyses, unfavorable genotypes AC and CC, compared with the AA genotype, were associated a worse OS (HR = 1.20, 95% CI = 1.03-1.39, p = 0.014) and disease-specific survival (HR = 1.21, 95% CI = 1.04-1.42, p = 0.016). Further expression quantitative trait loci analysis indicated that ERRFI1 rs28624C genotypes were significantly associated with higher ERRFI1 mRNA expression levels in the whole blood. Additional analysis showed that high ERRFI1 mRNA expression levels were associated with a worse OS in patients with lung adenocarcinoma.

CONCLUSION

Our findings suggest that genetic variants in the hypoxia-related gene ERRFI1 may modulate NSCLC survival, potentially through their effect on the gene expression.

Associations of chest X-ray trajectories, smoking, and the risk of lung cancer in two population-based cohort studies

Objectives

Despite the increasing use of computed tomography (CT), chest X-ray (CXR) remains the first-line investigation for suspected lung cancer (LC) in primary care. However, the associations of CXR trajectories, smoking and LC risk remain unknown.

Methods

A total of 52,486 participants from the PLCO and 22,194 participants from the NLST were included. The associations of CXR trajectories with LC risk were evaluated with multivariable COX regression models and pooled with meta-analyses. Further analyses were conducted to explore the stratified associations by smoking status and the factors associated with progression and regression in CXR.

Results

Compared to stable negative CXR (CXRSN), HRs (95%CIs) of LC incidence were 2.88(1.50-5.52), 3.86(2.03-7.35), and 1.08(0.80-1.46) for gain of positive CXR (CXRGP), stable positive CXR (CXRSP), and loss of positive CXR (CXRLP), while the risk of LC mortality were 1.58(1.33-1.87), 2.56(1.53-4.29), and 1.05(0.89-1.25). Similar trends were observed across different smoking status. However, LC risk with CXRGP overweighed that with CXRSP among ever smokers [2.95(2.25-3.88) vs. 2.59(1.33-5.02)] and current smokers [2.33(1.70-3.18) vs. 2.26(1.06-4.83)]. Moreover, compared to CXRSN among never smokers, even no progression in CXR, the HRs(95%CIs) of LC incidence were 7.39(5.60-9.75) and 31.45(23.58-41.95) for ever and current smokers, while risks of LC mortality were 6.30(5.07-7.81) and 27.17(21.65-34.11). If participants gained positive CXR, LC incidence risk significantly climbed to 22.04(15.37-31.60) and 71.97(48.82-106.09) for ever and current smokers, while LC mortality risk climbed to 11.90(8.58-16.50) and 38.92(27.04-56.02). CXRLP was associated with decreased LC risk. However, even smokers lost their positive CXR, and the increased risks of LC incidence and mortality did not decrease to non-significant level. Additionally, smoking was significantly associated with increased risk of CXRGP but not CXRLP.

Conclusion

LC risk differed across CXR trajectories and would be modified by smoking status. Comprehensive intervention incorporating CXR trajectories and smoking status should be recommended to reduce LC risk.

Cancer overdiagnosis: a challenge in the era of screening

"Screening" is a search for preclinical, asymptomatic disease, including cancer. Widespread cancer screening has led to large increases in early-stage cancers and pre-cancers. Ubiquitous public messages emphasize the potential benefits to screening for these lesions based on the underlying assumption that treating cancer at early stages before spread to other organs should make it easier to treat and cure, using more tolerable interventions. The intuition is so strong that public campaigns are sometimes launched without conducting definitive trials directly comparing screening to usual care. An effective cancer screening test should not only increase the incidence of early-stage preclinical disease but should also decrease the incidence of advanced and metastatic cancer, as well as a subsequent decrease in cancer-related mortality. Otherwise, screening efforts may be uncovering a reservoir of non-progressive and very slowly progressive lesions that were not destined to cause symptoms or suffering during the person's remaining natural lifespan: a phenomenon known as "overdiagnosis." We provide here a qualitative review of cancer overdiagnosis and discuss specific examples due to extensive population-based screening, including neuroblastoma, prostate cancer, thyroid cancer, lung cancer, melanoma, and breast cancer. The harms of unnecessary diagnosis and cancer therapy call for a balanced presentation to people considering undergoing screening, even with a test of accepted benefit, with a goal of informed decision-making. We also discuss proposed strategies to mitigate the adverse sequelae of overdiagnosis.

Early Diagnosis and Lung Cancer Screening

Lung cancer remains the most significant cause of cancer death, accounting for about 20% of all cancer-related mortality. A significant reason for this is delayed diagnosis, either due to lack of symptoms in early-stage disease or presentation with non-specific symptoms common with a broad range of alternative diagnoses. More is needed in terms of increasing public awareness, providing adequate healthcare professional education and implementing clinical pathways that improve the earlier diagnosis of symptomatic lung cancer. Low-dose computed tomography screening of high-risk, asymptomatic populations has been shown to reduce lung cancer mortality, with focus now shifting towards how best to implement lung cancer screening on a wider scale in a safe, efficient and cost-effective manner. For maximum benefit, efforts must be made to optimise uptake, especially among high-risk populations with significant socioeconomic deprivation, as well as successfully incorporate tobacco-dependency treatment. Quality assured programme management will be critical to minimising screening-related harms and adequately managing incidental findings. By undertaking the above, there can be optimism that lung cancer outcomes can be improved significantly in the near future.

CD133 as a Biomarker for an Autoantibody-to-ImmunoPET Paradigm for the Early Detection of Small Cell Lung Cancer

Small cell lung cancer (SCLC) is a deadly neuroendocrine tumor for which there are no screening methods sensitive enough to facilitate early, effective intervention. We propose targeting the neuroendocrine tumor neoantigen CD133 via antibody-based early detection and PET (immunoPET) to facilitate earlier and more accurate detection of SCLC. Methods: RNA sequencing datasets, immunohistochemistry, flow cytometry, and Western blots were used to quantify CD133 expression in healthy and SCLC patients. CD133 was imaged in vivo using near-infrared fluorescence (NIRF) immunoimaging, and 89Zr immunoPET. Anti(α)-CD133 autoantibody levels were measured in SCLC patient plasma using antibody microarrays. Results: Across 6 publicly available datasets, CD133 messenger RNA was found to be higher in SCLC tumors than in other tissues, including healthy or normal adjacent lung and non-SCLC samples. Critically, the upregulation of CD133 messenger RNA in SCLC was associated with a significant increase (hazard ratio, 2.62) in death. CD133 protein was expressed in primary human SCLC, in SCLC patient-derived xenografts, and in both SCLC cell lines tested (H82 and H69). Using an H82 xenograft mouse model, we first imaged CD133 expression with NIRF. Both in vivo and ex vivo NIRF clearly showed that a fluorophore-tagged αCD133 homed to lung tumors. Next, we validated the noninvasive visualization of subcutaneous and orthotopic H82 xenografts via immunoPET. An αCD133 antibody labeled with the positron-emitting radiometal 89Zr demonstrated significant accumulation in tumor tissue while producing minimal uptake in healthy organs. Finally, plasma αCD133 autoantibodies were found in subjects from cohort studies up to 1 year before SCLC diagnosis. Conclusion: In light of these findings, we conclude that the presence of αCD133 autoantibodies in a blood sample followed by CD133-targeted 89Zr-immunoPET could be an effective early detection screening strategy for SCLC.

Application of Artificial Intelligence in Lung Cancer

Lung cancer is the leading cause of malignancy-related mortality worldwide due to its heterogeneous features and diagnosis at a late stage. Artificial intelligence (AI) is good at handling a large volume of computational and repeated labor work and is suitable for assisting doctors in analyzing image-dominant diseases like lung cancer. Scientists have shown long-standing efforts to apply AI in lung cancer screening via CXR and chest CT since the 1960s. Several grand challenges were held to find the best AI model. Currently, the FDA have approved several AI programs in CXR and chest CT reading, which enables AI systems to take part in lung cancer detection. Following the success of AI application in the radiology field, AI was applied to digitalized whole slide imaging (WSI) annotation. Integrating with more information, like demographics and clinical data, the AI systems could play a role in decision-making by classifying EGFR mutations and PD-L1 expression. AI systems also help clinicians to estimate the patient's prognosis by predicting drug response, the tumor recurrence rate after surgery, radiotherapy response, and side effects. Though there are still some obstacles, deploying AI systems in the clinical workflow is vital for the foreseeable future.

Artificial intelligence: opportunities in lung cancer

PURPOSE OF REVIEW

In this article, we focus on the role of artificial intelligence in the management of lung cancer. We summarized commonly used algorithms, current applications and challenges of artificial intelligence in lung cancer.

RECENT FINDINGS

Feature engineering for tabular data and computer vision for image data are commonly used algorithms in lung cancer research. Furthermore, the use of artificial intelligence in lung cancer has extended to the entire clinical pathway including screening, diagnosis and treatment. Lung cancer screening mainly focuses on two aspects: identifying high-risk populations and the automatic detection of lung nodules. Artificial intelligence diagnosis of lung cancer covers imaging diagnosis, pathological diagnosis and genetic diagnosis. The artificial intelligence clinical decision-support system is the main application of artificial intelligence in lung cancer treatment. Currently, the challenges of artificial intelligence applications in lung cancer mainly focus on the interpretability of artificial intelligence models and limited annotated datasets; and recent advances in explainable machine learning, transfer learning and federated learning might solve these problems.

SUMMARY

Artificial intelligence shows great potential in many aspects of the management of lung cancer, especially in screening and diagnosis. Future studies on interpretability and privacy are needed for further application of artificial intelligence in lung cancer.

Genetic Variants of CLEC4E and BIRC3 in Damage-Associated Molecular Patterns-Related Pathway Genes Predict Non-Small Cell Lung Cancer Survival

Accumulating evidence supports a role of various damage-associated molecular patterns (DAMPs) in progression of lung cancer, but roles of genetic variants of the DAMPs-related pathway genes in lung cancer survival remain unknown. We investigated associations of 18,588 single-nucleotide polymorphisms (SNPs) in 195 DAMPs-related pathway genes with non-small cell lung cancer (NSCLC) survival in a subset of genotyping data for 1,185 patients from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial and validated the findings in another independent subset of genotyping data for 984 patients from Harvard Lung Cancer Susceptibility Study. We performed multivariate Cox proportional hazards regression analysis, followed by expression quantitative trait loci (eQTL) analysis, Kaplan-Meier survival analysis and bioinformatics functional prediction. We identified that two SNPs (i.e., CLEC4E rs10841847 G>A and BIRC3 rs11225211 G>A) were independently associated with NSCLC overall survival, with adjusted allelic hazards ratios of 0.89 (95% confidence interval=0.82-0.95 and P=0.001) and 0.82 (0.73-0.91 and P=0.0003), respectively; so were their combined predictive alleles from discovery and replication datasets (P_trend=0.0002 for overall survival). We also found that the CLEC4E rs10841847 A allele was associated with elevated mRNA expression levels in normal lymphoblastoid cells and whole blood cells, while the BIRC3 rs11225211 A allele was associated with increased mRNA expression levels in normal lung tissues. Collectively, these findings indicated that genetic variants of CLEC4E and BIRC3 in the DAMPs-related pathway genes were associated with NSCLC survival, likely by regulating the mRNA expression of the corresponding genes.

Intravoxel Incoherent Motion Diffusion-Weighted Imaging for Predicting and Monitoring the Response of Anti-Angiogenic Treatment in the Orthotopic Nude Mouse Model of Lung Adenocarcinoma

BACKGROUND

The treatment efficacy of angiogenesis inhibitor could be underestimated at an early stage based on tumor volume changes. Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) can quantitatively assess tumors at the cellular level, but it is unclear whether it can provide useful information for assessing treatment response of anti-angiogenic treatment for lung adenocarcinoma.

PURPOSE

To determine the use of IVIM-DWI for non-invasive monitoring of the early response to anti-angiogenic treatment in the orthotopic transplantation of lung adenocarcinoma model.

STUDY TYPE

Prospective.

POPULATION

Thirty-seven nude mice were randomized into two groups: treatment group (received bevacizumab + cisplatin, N = 20) and control group (received saline, N = 17).

FIELD STRENGTH/SEQUENCE

Single-shot turbo spin-echo (TSE) IVIM-DWI, TSE T2-weighted imaging at 3.0 T.

ASSESSMENT

Tumor volume, IVIM parameters (apparent diffusion coefficient [ADC], diffusivity [D], perfusion fraction [f], and pseudo-diffusion coefficient [D*]) were measured before and 2 hours, 3, 7, 10 and 14 days after treatment. Regions of interest were manually drawn along the inner edge of the tumor by two radiologists with 5 and 10-year experience in magnetic resonance imaging. Pathological examinations (hematoxylin and eosin stain, cluster of differentiation 34) were performed.

STATISTICAL TESTS

Kolmogorov-Smirnov test, repeated-measure two-way analysis of variance test, Mann-Whitney U test, Pearson correlation analysis, receiver operating characteristic curve. P < 0.05 was considered statistically significant.

RESULTS

The tumor volume of the two groups was significantly different only on day 14 (control group vs. treatment group, 43.15 ± 18.28 mm³ vs. 28.41 ± 1.71 mm³ ). ADC_2h , ADC_10d , D_2h , D_7d , D_10d , and D_14d were significantly higher, while f_10d and f_14d were significantly lower in the treatment group compared to those of the control group. Both the △ADC_2h (r = -0.631) and △D_2h (r = -0.700) showed moderate correlations with the relative tumor volume on day 14.

DATA CONCLUSION

IVIM has the potential to predict and monitor the early response to anti-angiogenic treatment, earlier than size changes, for lung adenocarcinoma.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 4.

Potentially functional variants of HBEGF and ITPR3 in GnRH signaling pathway genes predict survival of non-small cell lung cancer patients

The gonadotropin-releasing hormone (GnRH) signaling pathway controls reproductive functions and cancer growth and progression. However, few studies investigated roles of genetic variants of GnRH pathway genes in survival of patients with non-small cell lung cancer (NSCLC). Therefore, we first evaluated associations between 22,528 single-nucleotide polymorphisms (SNPs) in 101 GnRH pathway genes and survival of 1185 NSCLC patients using a dataset from Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. We found 572 SNPs to be significantly associated with overall survival (OS) of NSCLC (P ≤ 0.05, Bayesian false discovery probability ≤0.80). We then validated these SNPs in another dataset with 984 NSCLC patients from the Harvard Lung Cancer Susceptibility Study. Finally, two independent SNPs (HBEGF rs4150236G>A and ITPR3 rs116454384C>T) remained significantly associated with NSCLC OS in the combined analysis with hazards ratios of 0.84 (95% confidence interval = 0.76-0.92, P = 0.0003) and 0.85 (0.78-0.94, 0.0012), respectively; their genetic score (the number of protective genotypes) was associated with a better OS and disease-specific survival (P_trend = 0.0002 and 0.0001, respectively). Further expression quantitative trail loci analysis showed a significant correlation between ITPR3 rs116454384 T allele and an increased mRNA expression level in both whole blood and normal lung tissue, and high ITPR3 mRNA expression levels in tumors were associated with a better survival of NSCLC patients. Because ITPR3 mutations were rare in tumors, ITPR3 rs116454384C>T likely had an effect on cancer progression by regulating the gene expression. Therefore, genetic variants of HBEGF rs4150236G>A and ITPR3 rs116454384C>T may be predictors for NSCLC survival, but HBEGF rs4150236G>A functional relevance remains to be determined.

Modeling the mean time to interval cancer after negative results of periodic cancer screening

Interval cancers are cancers detected symptomatically between screens or after the last screen. A mathematical model for the development of interval cancers can provide useful information for evaluating cancer screening. In this regard a useful quantity is MIC, the mean duration in years of progressive preclinical cancer (PPC) that leads to interval cancers. Estimation of MIC involved extending a previous model to include three negative screens, invoking the multinomial-Poisson transformation to avoid estimating background cancer trends, and varying screening test sensitivity. Simulations show that when the true MIC is 0.5, the method yields a reasonably narrow range of estimated MICs over the range of screening test sensitivities from 0.5 to 1.0. If the lower bound on the screening test sensitivity is 0.7, the method performs considerably better even for larger MICs. The application of the method involved annual lung cancer screening in the Prostate, Lung, Colorectal, and Ovarian trial. Assuming a normal distribution for PPC duration, the estimated MIC (95% confidence interval) ranged from 0.00 (0.00 to 0.34) at a screening test sensitivity of 1.0 to 0.54 (0.03, 1.00) at a screening test sensitivity of 0.5 Assuming an exponential distribution for PPC duration, which did not fit as well, the estimated MIC ranged from 0.27 (0.08, 0.49) at a screening test sensitivity of 0.5 to 0.73 (0.32, 1.26) at a screen test sensitivity of 1.0 Based on these results, investigators may wish to investigate more frequent lung cancer screening.

Potentially functional variants of ERAP1, PSMF1 and NCF2 in the MHC-I-related pathway predict non-small cell lung cancer survival

BACKGROUND

Cellular immunity against tumor cells is highly dependent on antigen presentation by major histocompatibility complex class I (MHC-I) molecules. However, few published studies have investigated associations between functional variants of MHC-I-related genes and clinical outcomes of lung cancer patients.

METHODS

We performed a two-phase Cox proportional hazards regression analysis by using two previously published genome-wide association studies to evaluate associations between genetic variants in the MHC-I-related gene set and the survival of non-small cell lung cancer (NSCLC) patients, followed by expression quantitative trait loci analysis.

RESULTS

Of the 7811 single-nucleotide polymorphisms (SNPs) in 89 genes of 1185 NSCLC patients in the discovery dataset of the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial, 24 SNPs remained statistically significant after validation in additional 984 NSCLC patients from the Harvard Lung Cancer Susceptibility Study. In a multivariate stepwise Cox model, three independent functional SNPs (ERAP1 rs469783 T > C, PSMF1 rs13040574 C > A and NCF2 rs36071574 G > A) remained significant with an adjusted hazards ratio (HR) of 0.83 [95% confidence interval (CI) = 0.77-0.89, P = 8.0 × 10^-7], 0.86 (0.80-0.93, P = 9.4 × 10^-5) and 1.31 (1.11-1.54, P = 0.001) for overall survival (OS), respectively. Further combined genotypes revealed a poor survival in a dose-response manner in association with the number of unfavorable genotypes (P_trend < 0.0001 and 0.0002 for OS and disease-specific survival, respectively). Also, ERAP1 rs469783C and PSMF1 rs13040574A alleles were associated with higher mRNA expression levels of their genes.

CONCLUSION

These potentially functional SNPs of the MHC-I-related genes may be biomarkers for NSCLC survival, possibly through modulating the expression of corresponding genes.

UKCTOCS update: applying insights of delayed effects in cancer screening trials to the long-term follow-up mortality analysis

BACKGROUND

During trials that span decades, new evidence including progress in statistical methodology, may require revision of original assumptions. An example is the continued use of a constant-effect approach to analyse the mortality reduction which is often delayed in cancer-screening trials. The latter led us to re-examine our approach for the upcoming primary mortality analysis (2020) of long-term follow-up of the United Kingdom Collaborative Trial of Ovarian Cancer Screening (LTFU UKCTOCS), having initially (2014) used the proportional hazards (PH) Cox model.

METHODS

We wrote to 12 experts in statistics/epidemiology/screening trials, setting out current evidence, the importance of pre-specification, our previous mortality analysis (2014) and three possible choices for the follow-up analysis (2020) of the mortality outcome: (A) all data (2001-2020) using the Cox model (2014), (B) new data (2015-2020) only and (C) all data (2001-2020) using a test that allows for delayed effects.

RESULTS

Of 11 respondents, eight supported changing the 2014 approach to allow for a potential delayed effect (option C), suggesting various tests while three favoured retaining the Cox model (option A). Consequently, we opted for the Versatile test introduced in 2016 which maintains good power for early, constant or delayed effects. We retained the Royston-Parmar model to estimate absolute differences in disease-specific mortality at 5, 10, 15 and 18 years.

CONCLUSIONS

The decision to alter the follow-up analysis for the primary outcome on the basis of new evidence and using new statistical methodology for long-term follow-up is novel and has implications beyond UKCTOCS. There is an urgent need for consensus building on how best to design, test, estimate and report mortality outcomes from long-term randomised cancer screening trials.

TRIAL REGISTRATION

ISRCTN22488978 . Registered on 6 April 2000.

Artificial Intelligence Tools for Refining Lung Cancer Screening

Nearly one-quarter of all cancer deaths worldwide are due to lung cancer, making this disease the leading cause of cancer death among both men and women. The most important determinant of survival in lung cancer is the disease stage at diagnosis, thus developing an effective screening method for early diagnosis has been a long-term goal in lung cancer care. In the last decade, and based on the results of large clinical trials, lung cancer screening programs using low-dose computer tomography (LDCT) in high-risk individuals have been implemented in some clinical settings, however, this method has various limitations, especially a high false-positive rate which eventually results in a number of unnecessary diagnostic and therapeutic interventions among the screened subjects. By using complex algorithms and software, artificial intelligence (AI) is capable to emulate human cognition in the analysis, interpretation, and comprehension of complicated data and currently, it is being successfully applied in various healthcare settings. Taking advantage of the ability of AI to quantify information from images, and its superior capability in recognizing complex patterns in images compared to humans, AI has the potential to aid clinicians in the interpretation of LDCT images obtained in the setting of lung cancer screening. In the last decade, several AI models aimed to improve lung cancer detection have been reported. Some algorithms performed equal or even outperformed experienced radiologists in distinguishing benign from malign lung nodules and some of those models improved diagnostic accuracy and decreased the false-positive rate. Here, we discuss recent publications in which AI algorithms are utilized to assess chest computer tomography (CT) scans imaging obtaining in the setting of lung cancer screening.

Performance of a Deep Learning Algorithm Compared with Radiologic Interpretation for Lung Cancer Detection on Chest Radiographs in a Health Screening Population

Background The performance of a deep learning algorithm for lung cancer detection on chest radiographs in a health screening population is unknown. Purpose To validate a commercially available deep learning algorithm for lung cancer detection on chest radiographs in a health screening population. Materials and Methods Out-of-sample testing of a deep learning algorithm was retrospectively performed using chest radiographs from individuals undergoing a comprehensive medical check-up between July 2008 and December 2008 (validation test). To evaluate the algorithm performance for visible lung cancer detection, the area under the receiver operating characteristic curve (AUC) and diagnostic measures, including sensitivity and false-positive rate (FPR), were calculated. The algorithm performance was compared with that of radiologists using the McNemar test and the Moskowitz method. Additionally, the deep learning algorithm was applied to a screening cohort undergoing chest radiography between January 2008 and December 2012, and its performances were calculated. Results In a validation test comprising 10 285 radiographs from 10 202 individuals (mean age, 54 years ± 11 [standard deviation]; 5857 men) with 10 radiographs of visible lung cancers, the algorithm's AUC was 0.99 (95% confidence interval: 0.97, 1), and it showed comparable sensitivity (90% [nine of 10 radiographs]) to that of the radiologists (60% [six of 10 radiographs]; P = .25) with a higher FPR (3.1% [319 of 10 275 radiographs] vs 0.3% [26 of 10 275 radiographs]; P < .001). In the screening cohort of 100 525 chest radiographs from 50 070 individuals (mean age, 53 years ± 11; 28 090 men) with 47 radiographs of visible lung cancers, the algorithm's AUC was 0.97 (95% confidence interval: 0.95, 0.99), and its sensitivity and FPR were 83% (39 of 47 radiographs) and 3% (2999 of 100 478 radiographs), respectively. Conclusion A deep learning algorithm detected lung cancers on chest radiographs with a performance comparable to that of radiologists, which will be helpful for radiologists in healthy populations with a low prevalence of lung cancer. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Armato in this issue.

Novel genetic variants of SYK and ITGA1 related lymphangiogenesis signaling pathway predict non-small cell lung cancer survival

Although lymphangiogenesis is a vital step in lung cancer metastasis, the association between lymphangiogenesis and non-small cell lung cancer (NSCLC) survival remains unclear. Since single-nucleotide polymorphisms (SNPs) have been reported to predict NSCLC survival, we investigated associations between SNPs in lymphangiogenesis-related pathway genes and NSCLC survival in a discovery genotyping dataset of 1,185 patients from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial and validated the findings in another genotyping dataset of 984 patients from the Harvard Lung Cancer Susceptibility Study. We evaluated associations between 34,509 genetic variants (3252 genotyped and 31,257 imputed) in 247 genes involved in lymphangiogenesis-related pathway and NSCLC survival. After validation, we finally identified two independent SNPs (SYK rs11787670 A>G and ITGA1 rs67715745 T>C) to be significantly associated with NSCLC overall survival (OS), with adjusted hazards ratios of 0.77 and 0.83 (95% confidence interval =0.66-0.90, P=7.20×10^-4) and 0.84 (95% confidence interval =0.75-0.92, P=3.50×10^-4), respectively. Moreover, an increasing number of combined protective alleles of these two SNPs was significantly associated with an improved NSCLC OS and disease-specific survival (DSS) in the PLCO dataset (P _trend=0.011 and 0.006, respectively). Furthermore, the addition of these protective alleles to the prediction model for the 5-year survival increased the time-dependent area under the curve both from 87% to 87.67% for OS (P=0.029) and from 88.54% to 89.06% for DSS (P=0.022). Subsequent expression quantitative trait loci (eQTL) functional analysis revealed that the rs11787670 G allele was significantly associated with an elevated SYK mRNA expression in normal tissues. Additional analyses suggested a suppressor role for both SYK and ITGA1 in NSCLC survival. Collectively, these findings indicated that SYK rs11787670 A>G and ITGA1 rs67715745 T>C may be independent prognostic factors for NSCLC survival once further validated.

Novel genetic variants in KIF16B and NEDD4L in the endosome-related genes are associated with nonsmall cell lung cancer survival

The endosome is a membrane-bound organ inside most eukaryotic cells, playing an important role in adaptive immunity by delivering endocytosed antigens to both MHC class I and II pathways. Here, by analyzing genotyping data from two published genome-wide association studies (GWASs), we evaluated associations between genetic variants in the endosome-related gene-set and survival of patients with nonsmall cell lung cancer (NSCLC). The discovery included 44,112 (3,478 genotyped and 40,634 imputed) single-nucleotide polymorphisms (SNPs) in 220 genes in a singlelocus analysis for their associations with survival of 1,185 NSCLC patients from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. After validation of the 821 survival-associated significant SNPs in additional 984 NSCLC patients from the Harvard Lung Cancer Susceptibility Study, 14 SNPs remained significant. The final multivariate stepwise Cox proportional hazards regression modeling of the PLCO dataset identified three potentially functional and independent SNPs (i.e., KIF16B rs1555195 C>T, NEDD4L rs11660748 A>G and rs73440898 A>G) with an adjusted hazards ratio (HR) of 0.86 (95% confidence interval [CI] = 0.79-0.94, p = 0.0007), 1.31 (1.16-1.47, p = 6.0 × 10-5 ) and 1.27 (1.12-1.44, p = 0.0001) for overall survival (OS), respectively. Combined analysis of the adverse genotypes of these three SNPs revealed a trend in the genotype-survival association (ptrend < 0.0001 for OS and ptrend < 0.0001 for disease-specific survival). Furthermore, the survival-associated KIF16B rs1555195T allele was significantly associated with decreased mRNA expression levels of KIF16B in both lung tissues and blood cells. Therefore, genetic variants of the endosome-related genes may be biomarker for NSCLC survival, possibly through modulating the expression of corresponding genes.

Novel Variants of ELP2 and PIAS1 in the Interferon Gamma Signaling Pathway Are Associated with Non-Small Cell Lung Cancer Survival

BACKGROUND

IFNγ is a pleiotropic cytokine that plays critical immunomodulatory roles in intercellular communication in innate and adaptive immune responses. Despite recognition of IFNγ signaling effects on host defense against viral infection and its utility in immunotherapy and tumor progression, the roles of genetic variants of the IFNγ signaling pathway genes in survival of patients with cancer remain unknown.

METHODS

We used a discovery genotyping dataset from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (n = 1,185) and a replication genotyping dataset from the Harvard Lung Cancer Susceptibility Study (n = 984) to evaluate associations between 14,553 genetic variants in 150 IFNγ pathway genes and survival of non-small cell lung cancer (NSCLC).

RESULTS

The combined analysis identified two independent potentially functional SNPs, ELP2 rs7242481G>A and PIAS1 rs1049493T>C, to be significantly associated with NSCLC survival, with a combined HR of 0.85 (95% confidence interval, 0.78-0.92; P < 0.0001) and 0.87 (0.81-0.93; P < 0.0001), respectively. Expression quantitative trait loci analyses showed that the survival-associated ELP2 rs7242481A allele was significantly associated with increased mRNA expression levels of elongator acetyltransferase complex subunit 2 (ELP2) in 373 lymphoblastoid cell lines and 369 whole-blood samples. The PIAS1 rs1049493C allele was significantly associated with decreased mRNA expression levels of PIAS1 in 383 normal lung tissues and 369 whole-blood samples.

CONCLUSIONS

Genetic variants of IFNγ signaling genes are potential prognostic markers for NSCLC survival, likely through modulating the expression of key genes involved in host immune response.

IMPACT

Once validated, these variants could be useful predictors of NSCLC survival.

APOB Genotypes and CDH13 Haplotypes in the Cholesterol-Related Pathway Genes Predict Non-Small Cell Lung Cancer Survival

BACKGROUND

Several oncogenic signals are involved in the synthesis, metabolism, transportation, and modulation of cholesterol. However, the roles of genetic variants of the cholesterol pathway genes in cancer survival remain unclear.

METHODS

We investigated associations between 26,781 common SNPs in 209 genes of the cholesterol pathway and non-small cell lung cancer (NSCLC) survival by utilizing genotyping data from two published genome-wide association studies. We used multivariate Cox proportional hazards regression and expression quantitative trait loci analyses to identify survival-associated SNPs and their correlations with the corresponding mRNA expression, respectively. We also used the Kaplan-Meier survival analysis and bioinformatics functional prediction to further evaluate the identified independent SNPs.

RESULTS

We found five independent SNPs (APOB rs1801701C>T; CDH13 rs35859010 C>T, rs1833970 T>A, rs254315 T>C, and rs425904 T>C) to be significantly associated with NSCLC survival in both discovery and replication datasets. When the unfavorable genotype (APOB rs1801701CC) and haplotypes (CDH13 rs35859010-rs1833970-rs254315-rs425904 C-A-T-C and T-T-T-T) were combined into a genetic score as the number of unfavorable genotypes/haplotypes (NUGH) in the multivariate analysis, an increased NUGH was associated with worse survival (P trend < 0.0001). In addition, both APOB rs1801701T

CONCLUSIONS

Genetic variants of APOB and CDH13 in the cholesterol pathway were associated with NSCLC survival, possibly by affecting their gene expression.

IMPACT

Genetic variants of APOB and CDH13 in the cholesterol pathway may provide new scientific insights into NSCLC prognosis.

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Key Words Collapse

MESH Headings

• Aged
• Apolipoprotein B-100/genetics
• Cadherins/genetics
• Carcinoma, Non-Small-Cell Lung/genetics
• Carcinoma, Non-Small-Cell Lung/pathology
• Cholesterol/genetics
• Female
• Genotype
• Haplotypes
• Humans
• Lung Neoplasms/genetics
• Lung Neoplasms/pathology
• Male

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Grants

• R01 NS091307 NINDS NIH HHS
• U19 CA203654 NCI NIH HHS
• R01 CA074386 NCI NIH HHS
• P30 CA014236 NCI NIH HHS
• R01 CA092824 NCI NIH HHS
• R35 CA197449 NCI NIH HHS

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Affiliation(s)

Wei Deng Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China Duke Cancer Institute, Duke University Medical Center, Durham, North Carolina Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina
Hongliang Liu Duke Cancer Institute, Duke University Medical Center, Durham, North Carolina Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina
Sheng Luo Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina
Jeffrey Clarke Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China Department of Medicine, Duke University School of Medicine, Durham, North Carolina
Carolyn Glass Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China Department of Pathology, Duke University School of Medicine, Durham, North Carolina
Li Su Departments of Environmental Health and Epidemiology, Harvard School of Public Health, Boston, Massachusetts
Lijuan Lin Departments of Environmental Health and Epidemiology, Harvard School of Public Health, Boston, Massachusetts
David C Christiani Departments of Environmental Health and Epidemiology, Harvard School of Public Health, Boston, Massachusetts Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
Qingyi Wei Duke Cancer Institute, Duke University Medical Center, Durham, North Carolina. Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina Department of Medicine, Duke University School of Medicine, Durham, North Carolina

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Novel genetic variants of KIR3DL2 and PVR involved in immunoregulatory interactions are associated with non-small cell lung cancer survival

Immunoregulatory interactions play a pivotal role in immune surveillance, recognition, and killing, particularly its internal pathway, likely playing an important role in immune escape. By using two genotyping datasets, one from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer screening trial (n = 1,185) as the discovery, and the other from Harvard Lung Cancer Susceptibility (HLCS) study (n = 984) as the validation, we evaluated associations between 4,713 genetic variants (338 genotyped and 4,375 imputed) in 60 genes involved in immunoregulatory interactions and survival of non-small cell lung cancer (NSCLC). We found that 115 SNPs were significantly associated with NSCLC overall survival in the discovery, of which four remained significant after validation by the HLCS dataset after multiple test correction by Bayesian false discovery probability. Final combined analysis identified two independent SNPs (KIR3DL2 rs4487030 A>G and PVR rs35385129 C>A) that predicted NSCLC survival with a combined hazards ratio of 0.84 (95% confidence interval = 0.76-0.93, P = 0.001) and 0.84 (95% confidence interval = 0.73-0.97, P = 0.021), respectively. Besides, expression quantitative trait loci analyses showed that these two survival-associated SNPs of KRI3DL2 and PVR were significantly associated with their mRNA expression levels in both normal lung tissues and whole blood cells. Additional analyses suggested an oncogenic role for KRI3DL2 and a suppressor role for PVR on the survival. Once further validated, genetic variants of KIR3DL2 and PVR may be potential prognostic markers for NSCLC survival.

Genetic variants in RUNX3, AMD1 and MSRA in the methionine metabolic pathway and survival in nonsmall cell lung cancer patients

Abnormal methionine dependence in cancer cells has led to methionine restriction as a potential therapeutic strategy. We hypothesized that genetic variants involved in methionine-metabolic genes are associated with survival in nonsmall cell lung cancer (NSCLC) patients. Therefore, we investigated associations of 16,378 common single-nucleotide polymorphisms (SNPs) in 97 methionine-metabolic pathway genes with overall survival (OS) in NSCLC patients using genotyping data from two published genome-wide association study (GWAS) datasets. In the single-locus analysis, 1,005 SNPs were significantly associated with NSCLC OS (p < 0.05 and false-positive report probability < 0.2) in the discovery dataset. Three SNPs (RUNX3 rs7553295 G > T, AMD1 rs1279590 G > A and MSRA rs73534533 C > A) were replicated in the validation dataset, and their meta-analysis showed an adjusted hazards ratio [HR] of 0.82 [95% confidence interval (CI) =0.75-0.89] and pmeta  = 2.86 × 10-6 , 0.81 (0.73-0.91) and pmeta  = 4.63 × 10-4 , and 0.77 (0.68-0.89) and pmeta  = 2.07 × 10-4 , respectively). A genetic score of protective genotypes of these three SNPs revealed an increased OS in a dose-response manner (ptrend  < 0.0001). Further expression quantitative trait loci (eQTL) analysis showed significant associations between these genotypes and mRNA expression levels. Moreover, differential expression analysis further supported a tumor-suppressive effect of MSRA, with lower mRNA levels in both lung squamous carcinoma and adenocarcinoma (p < 0.0001 and < 0.0001, respectively) than in adjacent normal tissues. Additionally, low mutation rates of these three genes indicated the critical roles of these functional SNPs in cancer progression. Taken together, these genetic variants of methionine-metabolic pathway genes may be promising predictors of survival in NSCLC patients.

ACR Appropriateness Criteria® Lung Cancer Screening

Lung cancer remains the leading cause of cancer death in both men and women. Smoking is the single greatest risk factor for the development of lung cancer. For patients between the age of 55 and 80 with 30 or more pack years smoking history who currently smoke or who have quit within the last 15 years should undergo lung cancer screening with low-dose CT. In patients who do not meet these criteria but who have additional risk factors for lung cancer, lung cancer screening with low-dose CT is controversial but may be appropriate. Imaging is not recommended for lung cancer screening of patient younger than 50 years of age or patients older than 80 years of age or patients of any age with less than 20 packs per year history of smoking and no additional risk factor (ie, radon exposure, occupational exposure, cancer history, family history of lung cancer, history of COPD, or history of pulmonary fibrosis). The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Potentially functional genetic variants in the complement-related immunity gene-set are associated with non-small cell lung cancer survival

The complement system plays an important role in the innate and adaptive immunity, complement components mediate tumor cytolysis of antibody-based immunotherapy, and complement activation in the tumor microenvironment may promote tumor progression or inhibition, depending on the mechanism of action. In the present study, we conducted a two-phase analysis of two independently published genome-wide association studies (GWASs) for associations between genetic variants in a complement-related immunity gene-set and overall survival of non-small cell lung cancer (NSCLC). The GWAS dataset from Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial was used as the discovery, and multivariate Cox proportional hazards regression with false-positive report probability for multiple test corrections were performed to evaluate associations between 14,699 single-nucleotide polymorphisms (SNPs) in 111 genes and survival of 1,185 NSCLC patients. The identified significant SNPs in a single-locus analysis were further validated with 984 NSCLC patients in the GWAS dataset from the Harvard Lung Cancer Susceptibility (HLCS) Study. The results showed that two independent, potentially functional SNPs in two genes (VWF rs73049469 and ITGB2 rs3788142) were significantly associated with NSCLC survival, with a combined hazards ratio (HR) of 1.22 [95% confidence interval (CI) = 1.07-1.40, P = 0.002] and 1.16 (1.07-1.27, 6.45 × 10-4 ), respectively. Finally, we performed expression quantitative trait loci (eQTL) analysis and found that survival-associated genotypes of VWF rs73049469 were also significantly associated with mRNA expression levels of the gene. These results indicated that genetic variants of the complement-related immunity genes might be predictors of NSCLC survival, particularly for the short-term survival, possibly by modulating the expression of genes involved in the host immunity.

Clinical validation of a blood-based classifier for diagnostic evaluation of asymptomatic individuals with pulmonary nodules

BACKGROUND

The number of pulmonary nodules detected in the US is expected to increase substantially following recent recommendations for nationwide CT-based lung cancer screening. Given the low specificity of CT screening, non-invasive adjuvant methods are needed to differentiate cancerous lesions from benign nodules to help avoid unnecessary invasive procedures in the asymptomatic population. We have constructed a serum-based multi-biomarker panel and assessed its clinical accuracy in a retrospective analysis of samples collected from participants with suspicious radiographic findings in the Prostate, Lung, Chest and Ovarian (PLCO) cancer screening trial.

METHODS

Starting with a set of 9 candidate biomarkers, we identified 8 that exhibited limited pre-analytical variability with increasing clotting time, a key pre-analytical variable associated with the collection of serum. These 8 biomarkers were evaluated in a training study consisting of 95 stage I NSCLC patients and 186 smoker controls where a 5-biomarker pulmonary nodule classifier (PNC) was selected. The clinical accuracy of the PNC was determined in a blinded study of asymptomatic individuals comprising 119 confirmed malignant nodule cases and 119 benign nodule controls selected from the PLCO screening trial.

RESULTS

A PNC comprising 5 biomarkers: CEA, CYFRA 21-1, OPN, SCC, and TFPI, was selected in the training study. In an independent validation study, the PNC resolved lung cancer cases from benign nodule controls with an AUC of 0.653 (p < 0.0001). CEA and CYFRA 21-1, two of the markers included in the PNC, also accurately distinguished malignant lesions from benign controls.

CONCLUSIONS

A 5-biomarker blood test has been developed for the diagnostic evaluation of asymptomatic individuals with solitary pulmonary nodules.

Cigarette smoking and the oral microbiome in a large study of American adults

Oral microbiome dysbiosis is associated with oral disease and potentially with systemic diseases; however, the determinants of these microbial imbalances are largely unknown. In a study of 1204 US adults, we assessed the relationship of cigarette smoking with the oral microbiome. 16S rRNA gene sequencing was performed on DNA from oral wash samples, sequences were clustered into operational taxonomic units (OTUs) using QIIME and metagenomic content was inferred using PICRUSt. Overall oral microbiome composition differed between current and non-current (former and never) smokers (P<0.001). Current smokers had lower relative abundance of the phylum Proteobacteria (4.6%) compared with never smokers (11.7%) (false discovery rate q=5.2 × 10(-7)), with no difference between former and never smokers; the depletion of Proteobacteria in current smokers was also observed at class, genus and OTU levels. Taxa not belonging to Proteobacteria were also associated with smoking: the genera Capnocytophaga, Peptostreptococcus and Leptotrichia were depleted, while Atopobium and Streptococcus were enriched, in current compared with never smokers. Functional analysis from inferred metagenomes showed that bacterial genera depleted by smoking were related to carbohydrate and energy metabolism, and to xenobiotic metabolism. Our findings demonstrate that smoking alters the oral microbiome, potentially leading to shifts in functional pathways with implications for smoking-related diseases.

Genetic variants in ABCG1 are associated with survival of nonsmall-cell lung cancer patients

Cell membrane transporters and metabolic enzymes play a crucial role in the transportation of a wide variety of substrates that maintain homeostasis in biological processes. We explored associations between genetic variants in these genes and survival of nonsmall-cell lung cancer (NSCLC) patients by reanalyzing two datasets from published genome-wide association studies (GWASs). In the discovery by using the GWAS dataset of the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial, we evaluated associations of 1,245 single-nucleotide polymorphisms (SNPs) in genes of four transporter families and two metabolic enzyme families with survival of 1,185 NSCLC patients. We then performed a replication analysis in the Harvard University Lung Cancer study (LCS) with 984 NSCLC patients. Multivariate Cox proportional hazards regression and false discovery rate (FDR) corrections were performed to evaluate the associations. We identified that 21 genotyped SNPs in eight gene regions were significantly associated with survival with FDR ≤ 0.1 in the discovery dataset. Subsequently, we confirmed six SNPs, which were putative functional, in ABCG1 of the ATP-binding cassette transporter family in the replication dataset. In the pooled analysis, two tagging (at r(2)  > 0.8 for linkage disequilibrium with other replicated SNPs)/functional SNPs were independently associated with survival: rs225388 G > A [adjusted hazards ratio (HR) = 1.12, 95% confidence interval (CI) = 1.03-1.20, Ptrend  = 4.6 × 10(-3)] and rs225390 A > G (adjusted HR = 1.16, 95% CI = 1.07-1.25, Ptrend  = 3.8 × 10(-4) ). Our results indicated that genetic variants of ABCG1 may be predictors of survival of NSCLC patients.

Implementing lung cancer screening in the real world: opportunity, challenges and solutions

The World Health Organization estimates that, in 2012, there were 1,589,925 deaths from lung cancer worldwide. Screening for lung cancer with low-dose computed tomography (LDCT) has the potential to significantly alter this statistic, by identifying lung cancers in earlier stages, enabling curative treatment. Challenges remain, however, in replicating the 20% mortality benefit demonstrated by the National Lung Screening Trial (NLST), in populations outside the confines of a research trial, not only in the US but around the world. We review the history of lung cancer screening, the current evidence for LDCT screening, and the key elements needed for a successful screening program.

Health screening for older people-what are the current recommendations?

The world population of older people is on the rise with improved health services. With longevity, older people are at increased risk of chronic non-communicable diseases (NCDs), which are also leading causes of death among older people. Screening through case finding in primary care would allow early identification of NCDs and its risk factors, which could lead to the reduction of related complications as well as mortality. However, direct evidence for screening older people is lacking and the decision to screen for diseases should be made based on comorbidity, functional status and life expectancy, and has to be individualised.

Long-term outcomes of wedge resection for pulmonary ground-glass opacity nodules

BACKGROUND

We aimed to characterize ground-glass opacity (GGO) nodules and evaluate the prognosis of clinical stage IA lung adenocarcinoma with GGO nodules after wedge resection.

METHODS

Patients who underwent wedge resection for early stage lung cancer and proven adenocarcinoma on postoperative pathologic report were enrolled in the study between 2004 and 2010. Radiologic findings of the main tumor were evaluated for ground-glass opacities with chest computed tomography (CT). We divided patients into two groups based on the consolidation-to-tumor ratio (C/T ratio ≤ 0.25, pure GGO group; C/T ratio > 0.25, mixed GGO group). Overall survival and recurrence-free survival were analyzed for all patients.

RESULTS

A total of 97 patients were included in our study. Among these, 71 patients were categorized into the pure GGO group and 26 patients into the mixed GGO group. The 5-year overall survival rate was 98.6% in the pure GGO group and 95.5% in the mixed GGO group (p = 0.663). Five patients (5.1%) experienced recurrences; only 1 patient (1/71, 1.4%) in the pure GGO group and 4 patients (4/26, 15.3%) in the mixed GGO group had recurrence.

CONCLUSIONS

GGO-dominant clinical stage IA lung adenocarcinoma (pure GGO group) showed an excellent prognosis. Wedge resection should be carefully considered for patients with mixed GGO nodules (C/T ratio >0.25) because of the high recurrence rate. Radiologic noninvasiveness (C/T ratio ≤ 0.25) might be a good indicator for candidates for sublobar resection in cases of early stage lung adenocarcinoma.

Evolution and immediate future of US screening guidelines

Although observational studies and simulation models have shed some interesting light on many of the uncertainties surrounding prostate cancer screening, well-done clinical trials provide the best evidence on screening among the extremes of age, the most appropriate interval to screen, and the best complement of tests to use. Enthusiasm for screening is temporized by the acknowledgment that overdetection leads to frequent overtreatment despite evidence supporting the safety of active surveillance in many men with low-risk disease.

Current status of circulating protein biomarkers to aid the early detection of lung cancer

ABSTRACT: 

Considerable efforts have been undertaken to produce an effective screening method to reduce lung cancer mortality. Imaging tools such as low-dose computed tomography has shown an increase in the detection of early disease and a reduction in the rate of death. This screening modality has, however, several limitations, such as overdiagnosis and a high rate of false positives. Therefore, new screening methods, such as the use of circulating protein biomarkers, have emerged as an option that could complement imaging studies. In this review, current imaging techniques applied to lung cancer screening protocols are presented, as well as up-to-date status of circulating protein biomarker panels that may improve lung cancer diagnosis. Additionally, diverse statistical and artificial intelligence tools applied to the design and optimization of these panels are discussed along with the presentation of two commercially available blood tests recently developed to help detect lung cancer early.

Preoperative consolidation-to-tumor ratio and SUVmax stratify the risk of recurrence in patients undergoing limited resection for lung adenocarcinoma ≤2 cm

PURPOSE

Limited resection is an increasingly utilized option for treatment of clinical stage IA lung adenocarcinoma (ADC) ≤2 cm (T1aN0M0), yet there are no validated predictive factors for postoperative recurrence. We investigated the prognostic value of preoperative consolidation/tumor (C/T) ratio [on computed tomography (CT) scan] and maximum standardized uptake value (SUVmax) on (18)F-fluorodeoxyglucose-positron emission tomography (PET) scan.

METHODS

We retrospectively reviewed 962 consecutive patients who underwent limited resection for lung cancer at Memorial Sloan-Kettering between 2000 and 2008. Patients with available CT and PET scans were included in the analysis. C/T ratio of 25 % (in accordance with the Japan Clinical Oncology Group 0201) and SUVmax of 2.2 (cohort median) were used as cutoffs. Cumulative incidence of recurrence (CIR) was assessed.

RESULTS

A total of 181 patients met the study inclusion criteria. Patients with a low C/T ratio (n = 15) had a significantly lower 5-year recurrence rate compared with patients with a high C/T ratio (n = 166) (5-year CIR, 0 vs. 33 %; p = 0.015), as did patients with low SUVmax (n = 86) compared with patients with high SUVmax (n = 95; 5-year CIR, 18 vs. 40 %; p = 0.002). Furthermore, within the high C/T ratio group, SUVmax further stratified risk of recurrence [5-year CIR, 22 % (low) vs. 40 % (high); p = 0.018].

CONCLUSIONS

With the expected increase in diagnoses of small lung ADC as a result of more widespread use of CT screening, C/T ratio and SUVmax are widely available markers that can be used to stratify the risk of recurrence among cT1aN0M0 patients after limited resection.

Diagnostic evaluation following a positive lung screening chest radiograph in the Prostate, Lung, Colorectal, Ovarian (PLCO) Cancer Screening Trial

Lung cancer is the major cause of cancer mortality. One of the aims of the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) was to determine if annual screening chest radiographs reduce lung cancer mortality. We enrolled 154,900 individuals, aged 55-74 years; 77,445 were randomized to the intervention arm and received an annual chest radiograph for 3 or 4 years. Participants with a positive screen underwent diagnostic evaluation under guidance of their primary physician. Methods of diagnosis or exclusion of cancer, interval from screen to diagnosis, and factors predicting diagnostic testing were evaluated. One or more positive screens occurred in 17% of participants. Positive screens resulted in biopsy in 3%, with 54% positive for cancer. Biopsy likelihood was associated with a mass, smoking, age, and family history of lung cancer. Diagnostic testing stopped after a chest radiograph or computed tomography/magnetic resonance imaging in over half. After a second or subsequent positive screen, evaluation stopped after comparison to prior radiographs in over half. Of 308 screen-detected cancers, the diagnosis was established by thoracotomy/thoracoscopy in 47.7%, needle biopsy in 27.6%, bronchoscopy in 20.1% and mediastinoscopy in 2.9%. Eighty-four percent of screen-detected lung cancers were diagnosed within 6 months. Diagnostic evaluations following a positive screen were conducted in a timely fashion. Lung cancer was diagnosed by tissue biopsy or cytology in all cases. Lung cancer was excluded during evaluation of positive screening examinations by clinical or radiographic evaluation in all but 1.4% who required a tissue biopsy.

Screening for lung cancer: Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines

BACKGROUND

Lung cancer is by far the major cause of cancer deaths largely because in the majority of patients it is at an advanced stage at the time it is discovered, when curative treatment is no longer feasible. This article examines the data regarding the ability of screening to decrease the number of lung cancer deaths.

METHODS

A systematic review was conducted of controlled studies that address the effectiveness of methods of screening for lung cancer.

RESULTS

Several large randomized controlled trials (RCTs), including a recent one, have demonstrated that screening for lung cancer using a chest radiograph does not reduce the number of deaths from lung cancer. One large RCT involving low-dose CT (LDCT) screening demonstrated a significant reduction in lung cancer deaths, with few harms to individuals at elevated risk when done in the context of a structured program of selection, screening, evaluation, and management of the relatively high number of benign abnormalities. Whether other RCTs involving LDCT screening are consistent is unclear because data are limited or not yet mature.

CONCLUSIONS

Screening is a complex interplay of selection (a population with sufficient risk and few serious comorbidities), the value of the screening test, the interval between screening tests, the availability of effective treatment, the risk of complications or harms as a result of screening, and the degree with which the screened individuals comply with screening and treatment recommendations. Screening with LDCT of appropriate individuals in the context of a structured process is associated with a significant reduction in the number of lung cancer deaths in the screened population. Given the complex interplay of factors inherent in screening, many questions remain on how to effectively implement screening on a broader scale.

Moving beyond the national lung screening trial: discussing strategies for implementation of lung cancer screening programs

The National Lung Screening Trial (NLST) has sparked new interest in the adoption of lung cancer screening using low-dose computed tomography (LDCT). If adopted at a national level, LDCT screening may prevent approximately 18,000 lung cancer deaths per year, potentially constituting a high-value public health intervention. Before incorporating LDCT screening into practice, health care institutions need to consider the risks associated with LDCT screening and the impact of LDCT screening on health care costs, as well as other remaining areas of uncertainty, including the unknown cost-effectiveness of LDCT screening. This article will review the benefits and risks of LDCT screening in light of the results of the NLST and other randomized trials, it will discuss the additional health care costs associated with LDCT screening from the perspective of health care payers, and it will examine the published cost-effectiveness analyses of LDCT screening. A subsequent discussion highlights guideline recommendations for implementation strategies, the goals of which are to ensure that those eligible for LDCT screening derive the benefits while minimizing the risks of screening and avoiding an unnecessary escalation in screening-related costs. The article concludes by endorsing the use of LDCT screening in institutions capable of responsible implementation of screening in both medical and economic terms. The key elements of responsible implementation include the development of standardized screening practices, careful selection of screening candidates, and the creation of prospective registries that will mitigate current areas of uncertainty regarding LDCT screening.

Palliative care in patients with lung cancer

Lung cancer accounts for 12% of all cancers and has the highest annual rate of mortality in men and women. The overall aim is cure or prolongation of life without evidence of disease. Almost 60% of patients at the moment of diagnosis are not eligible for radical treatment. Therefore soothing and supportive treatment is the only treatment of choice. Patients with lung cancer who have symptoms of dyspnea, chronic cough, severe pain, exhaustion and cachexia syndrome, fear and depression and significantly reduced physical and intellectual activities are qualified for inpatient or home palliative care. Knowledge about various methods used in palliative treatment allows one to alleviate symptoms that occur in an advanced stage of disease with an expected short survival period. Methods of oncological treatment that are often used in patients with advanced lung cancer include radiotherapy and chemotherapy. Drawing attention to the earlier implementation of palliative care is an objective of research carried out during recent years. Advances in surgical and conservative treatment of these patients have contributed to better outcomes and longer survival time.

Screening for lung cancer

BACKGROUND

This is an updated version of the original review published in The Cochrane Library in 1999 and updated in 2004 and 2010. Population-based screening for lung cancer has not been adopted in the majority of countries. However it is not clear whether sputum examinations, chest radiography or newer methods such as computed tomography (CT) are effective in reducing mortality from lung cancer.

OBJECTIVES

To determine whether screening for lung cancer, using regular sputum examinations, chest radiography or CT scanning of the chest, reduces lung cancer mortality.

SEARCH METHODS

We searched electronic databases: the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2012, Issue 5), MEDLINE (1966 to 2012), PREMEDLINE and EMBASE (to 2012) and bibliographies. We handsearched the journal Lung Cancer (to 2000) and contacted experts in the field to identify published and unpublished trials.

SELECTION CRITERIA

Controlled trials of screening for lung cancer using sputum examinations, chest radiography or chest CT.

DATA COLLECTION AND ANALYSIS

We performed an intention-to-screen analysis. Where there was significant statistical heterogeneity, we reported risk ratios (RRs) using the random-effects model. For other outcomes we used the fixed-effect model.

MAIN RESULTS

We included nine trials in the review (eight randomised controlled studies and one controlled trial) with a total of 453,965 subjects. In one large study that included both smokers and non-smokers comparing annual chest x-ray screening with usual care there was no reduction in lung cancer mortality (RR 0.99, 95% CI 0.91 to 1.07). In a meta-analysis of studies comparing different frequencies of chest x-ray screening, frequent screening with chest x-rays was associated with an 11% relative increase in mortality from lung cancer compared with less frequent screening (RR 1.11, 95% CI 1.00 to 1.23); however several of the trials included in this meta-analysis had potential methodological weaknesses. We observed a non-statistically significant trend to reduced mortality from lung cancer when screening with chest x-ray and sputum cytology was compared with chest x-ray alone (RR 0.88, 95% CI 0.74 to 1.03). There was one large methodologically rigorous trial in high-risk smokers and ex-smokers (those aged 55 to 74 years with ≥ 30 pack-years of smoking and who quit ≤ 15 years prior to entry if ex-smokers) comparing annual low-dose CT screening with annual chest x-ray screening; in this study the relative risk of death from lung cancer was significantly reduced in the low-dose CT group (RR 0.80, 95% CI 0.70 to 0.92).

AUTHORS' CONCLUSIONS

The current evidence does not support screening for lung cancer with chest radiography or sputum cytology. Annual low-dose CT screening is associated with a reduction in lung cancer mortality in high-risk smokers but further data are required on the cost effectiveness of screening and the relative harms and benefits of screening across a range of different risk groups and settings.

Selection criteria for lung-cancer screening

BACKGROUND

The National Lung Screening Trial (NLST) used risk factors for lung cancer (e.g., ≥30 pack-years of smoking and <15 years since quitting) as selection criteria for lung-cancer screening. Use of an accurate model that incorporates additional risk factors to select persons for screening may identify more persons who have lung cancer or in whom lung cancer will develop.

METHODS

We modified the 2011 lung-cancer risk-prediction model from our Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial to ensure applicability to NLST data; risk was the probability of a diagnosis of lung cancer during the 6-year study period. We developed and validated the model (PLCO(M2012)) with data from the 80,375 persons in the PLCO control and intervention groups who had ever smoked. Discrimination (area under the receiver-operating-characteristic curve [AUC]) and calibration were assessed. In the validation data set, 14,144 of 37,332 persons (37.9%) met NLST criteria. For comparison, 14,144 highest-risk persons were considered positive (eligible for screening) according to PLCO(M2012) criteria. We compared the accuracy of PLCO(M2012) criteria with NLST criteria to detect lung cancer. Cox models were used to evaluate whether the reduction in mortality among 53,202 persons undergoing low-dose computed tomographic screening in the NLST differed according to risk.

RESULTS

The AUC was 0.803 in the development data set and 0.797 in the validation data set. As compared with NLST criteria, PLCO(M2012) criteria had improved sensitivity (83.0% vs. 71.1%, P<0.001) and positive predictive value (4.0% vs. 3.4%, P=0.01), without loss of specificity (62.9% and. 62.7%, respectively; P=0.54); 41.3% fewer lung cancers were missed. The NLST screening effect did not vary according to PLCO(M2012) risk (P=0.61 for interaction).

CONCLUSIONS

The use of the PLCO(M2012) model was more sensitive than the NLST criteria for lung-cancer detection.

From randomized trials to the clinic: is it time to implement individual lung-cancer screening in clinical practice? A multidisciplinary statement from French experts on behalf of the French intergroup (IFCT) and the groupe d'Oncologie de langue francaise (GOLF)

Background

Despite advances in cancer therapy, mortality is still high except in early-stage tumors, and screening remains a challenge. The randomized National Lung Screening Trial (NLST), comparing annual low-dose computed tomography (LDCT) and chest X-rays, revealed a 20% decrease in lung-cancer-specific mortality. These results raised numerous questions. The French intergroup for thoracic oncology and the French-speaking oncology group convened an expert group to provide a coherent outlook on screening modalities in France.

Methods

A literature review was carried out and transmitted to the expert group, which was divided into three workshops to tackle specific questions, with responses presented in a plenary session. A writing committee drafted this article.

Results

The multidisciplinary group favored individual screening in France, when carried out as outlined in this article and after informing subjects of the benefits and risks. The target population involves subjects aged 55–74 years, who are smokers or have a 30 pack-year smoking history. Subjects should be informed about the benefits of quitting. Screening should involve LDCT scanning with specific modalities. Criteria for CT positivity and management algorithms for positive examinations are given.

Conclusions

Individual screening requires rigorous assessment and precise research in order to potentially develop a lung-cancer screening policy.

Current status of lung cancer screening

Recent results have demonstrated a major reduction in lung cancer mortality through computed tomography screening and no benefit from chest radiograph (CXR) screening. This presents a huge potential for benefit but also poses challenges regarding management of details to minimize harm. Many unresolved questions remain that must be addressed to implement computed tomography screening for lung cancer in a thoughtful and responsible way.

A gated-7T MRI technique for tracking lung tumor development and progression in mice after exposure to low doses of ionizing radiation

A gated-7T magnetic resonance imaging (MRI) application is described that can accurately and efficiently measure the size of in vivo mouse lung tumors from ∼0.1 mm(3) to >4 mm(3). This MRI approach fills a void in radiation research because the technique can be used to noninvasively measure the growth rate of lung tumors in large numbers of mice that have been irradiated with low doses (<50 mGy) without the additional radiation exposure associated with planar X ray, CT or PET imaging. High quality, high resolution, reproducible images of the mouse thorax were obtained in ∼20 min using: (1) a Bruker 7T micro-MRI scanner equipped with a 60 mm inner diameter gradient insert capable of generating a maximum gradient of 1000 mT/m; (2) a 35 mm inner diameter quadrature radiofrequency volume coil; and (3) an electrocardiogram and respiratory gated Fast Low Angle Shot (FLASH) pulse sequence. The images had an in-plane image resolution of 98 μm and a 0.5 mm slice thickness. Tumor diameter measured by MRI was highly correlated (R(2) = 0.97) with the tumor diameter measured by electronic calipers. Data generated with an initiation/promotion mouse model of lung carcinogenesis and this MRI technique demonstrated that mice exposed to 4 weekly fractions of 10, 30 or 50 mGy of CT radiation had the same lung tumor growth rate as that measured in sham-irradiated mice. In summary, this high-field, double-gated MRI approach is an efficient way of quantitatively tracking lung tumor development and progression after exposure to low doses of ionizing radiation.