Plasma Metabolite Profiling in the Search for Early-Stage Biomarkers for Lung Cancer: Some Important Breakthroughs.

Lung cancer is the leading cause of cancer-related mortality worldwide. In order to improve its overall survival, early diagnosis is required. Since current screening methods still face some pitfalls, such as high false positive rates for low-dose computed tomography, researchers are still looking for early biomarkers to complement existing screening techniques in order to provide a safe, faster, and more accurate diagnosis. Biomarkers are biological molecules found in body fluids, such as plasma, that can be used to diagnose a condition or disease. Metabolomics has already been shown to be a powerful tool in the search for cancer biomarkers since cancer cells are characterized by impaired metabolism, resulting in an adapted plasma metabolite profile. The metabolite profile can be determined using nuclear magnetic resonance, or NMR. Although metabolomics and NMR metabolite profiling of blood plasma are still under investigation, there is already evidence for its potential for early-stage lung cancer diagnosis, therapy response, and follow-up monitoring. This review highlights some key breakthroughs in this research field, where the most significant biomarkers will be discussed in relation to their metabolic pathways and in light of the altered cancer metabolism.

Unraveling the Rewired Metabolism in Lung Cancer Using Quantitative NMR Metabolomics.

Lung cancer cells are well documented to rewire their metabolism and energy production networks to enable proliferation and survival in a nutrient-poor and hypoxic environment. Although metabolite profiling of blood plasma and tissue is still emerging in omics approaches, several techniques have shown potential in cancer diagnosis. In this paper, the authors describe the alterations in the metabolic phenotype of lung cancer patients. In addition, we focus on the metabolic cooperation between tumor cells and healthy tissue. Furthermore, the authors discuss how metabolomics could improve the management of lung cancer patients.

Glutamine Addiction and Therapeutic Strategies in Lung Cancer.

Lung cancer cells are well-documented to rewire their metabolism and energy production networks to support rapid survival and proliferation. This metabolic reorganization has been recognized as a hallmark of cancer. The increased uptake of glucose and the increased activity of the glycolytic pathway have been extensively described. However, over the past years, increasing evidence has shown that lung cancer cells also require glutamine to fulfill their metabolic needs. As a nitrogen source, glutamine contributes directly (or indirectly upon conversion to glutamate) to many anabolic processes in cancer, such as the biosynthesis of amino acids, nucleobases, and hexosamines. It plays also an important role in the redox homeostasis, and last but not least, upon conversion to α-ketoglutarate, glutamine is an energy and anaplerotic carbon source that replenishes tricarboxylic acid cycle intermediates. The latter is generally indicated as glutaminolysis. In this review, we explore the role of glutamine metabolism in lung cancer. Because lung cancer is the leading cause of cancer death with limited curative treatment options, we focus on the potential therapeutic approaches targeting the glutamine metabolism in cancer.

Metabolic phenotyping of human plasma by 1 H-NMR at high and medium magnetic field strengths: a case study for lung cancer.

Accurate identification and quantification of human plasma metabolites can be challenging in crowded regions of the NMR spectrum with severe signal overlap. Therefore, this study describes metabolite spiking experiments on the basis of which the NMR spectrum can be rationally segmented into well-defined integration regions, and this for spectrometers having magnetic field strengths corresponding to 1 H resonance frequencies of 400 MHz and 900 MHz. Subsequently, the integration data of a case-control dataset of 69 lung cancer patients and 74 controls were used to train a multivariate statistical classification model for both field strengths. In this way, the advantages/disadvantages of high versus medium magnetic field strength were evaluated. The discriminative power obtained from the data collected at the two magnetic field strengths is rather similar, i.e. a sensitivity and specificity of respectively 90 and 97% for the 400 MHz data versus 88 and 96% for the 900 MHz data. This shows that a medium-field NMR spectrometer (400-600 MHz) is already sufficient to perform clinical metabolomics. However, the improved spectral resolution (reduced signal overlap) and signal-to-noise ratio of 900 MHz spectra yield more integration regions that represent a single metabolite. This will simplify the unraveling and understanding of the related, disease disturbed, biochemical pathways. Copyright © 2017 John Wiley & Sons, Ltd.

Are Randomized Controlled Trials the (G)old Standard? From Clinical Intelligence to Prescriptive Analytics.

Despite the accelerating pace of scientific discovery, the current clinical research enterprise does not sufficiently address pressing clinical questions. Given the constraints on clinical trials, for a majority of clinical questions, the only relevant data available to aid in decision making are based on observation and experience. Our purpose here is 3-fold. First, we describe the classic context of medical research guided by Poppers' scientific epistemology of "falsificationism." Second, we discuss challenges and shortcomings of randomized controlled trials and present the potential of observational studies based on big data. Third, we cover several obstacles related to the use of observational (retrospective) data in clinical studies. We conclude that randomized controlled trials are not at risk for extinction, but innovations in statistics, machine learning, and big data analytics may generate a completely new ecosystem for exploration and validation.

Prognostic value of the 1-min sit-to-stand test to predict post-operative complications in patients with lung cancer elected for lung resection.

Patients with nonsmall cell lung cancer achieving ≤22 repetitions during a 1-min sit-to-stand test are at increased risk of post-operative complications https://bit.ly/3T7pnS9.

Physical status, symptoms and health-related quality of life during a severe exacerbation of COPD: Recovery and discriminative capacity for future events.

OBJECTIVE: Severe acute exacerbations of chronic obstructive pulmonary disease (AECOPD) can have a negative impact on functional capacity, symptoms and health-related quality of life (HRQOL). This study aimed to i) investigate the recovery of muscle strength, functional capacity, symptoms, and HRQOL in patients after a severe AECOPD; ii) compare with matched patients with stable COPD (SCOPD); and iii) assess whether these assessments at hospital discharge could discriminate patients' risk for future events. METHODS: This observational study assessed patients with AECOPD during hospital discharge (T1) and one month after discharge (T2). Patients with SCOPD were assessed once. Quadriceps force, handgrip strength, short physical performance battery (SPPB), 6-min walk distance (6 MWD), COPD assessment test (CAT), London chest activity of daily living (LCADL), modified medical research council, checklist individual strength-fatigue, patient health questionnaire, and physical activity (Actigraph) were measured. Exacerbation-related readmission and mortality within six months and 1-year were collected. RESULTS: Forty-four patients with AECOPD were matched with 44 patients with SCOPD. At T2, a significant improvement was found for the SPPB total score, 6 MWD, CAT score, and LCADL score. Compared to patients with SCOPD, a worse LCADL score was found at T2 in patients with AECOPD. Patients with AECOPD that were readmitted or died had a worse SPPB classification and five-repetition sit-to-stand test at T1. CONCLUSION: Patients after severe AECOPD improved in functional capacity and HRQOL one month after hospital discharge, but ADL performance was still worse compared to SCOPD. Patients who were readmitted or died had significantly worse scores on functional tests at hospital discharge.

Randomised, controlled, open-label pragmatic trial evaluating changes in functional exercise capacity after primary care PUlmonary REhabilitation in patients with long COVID: protocol of the PuRe-COVID trial in Belgium.

INTRODUCTION: Long COVID is a prevalent condition with many multisystemic symptoms, such as fatigue, dyspnoea, muscle weakness, anxiety, depression and sleep difficulties, impacting daily life and (social and physical) functioning. Pulmonary rehabilitation (PR) may improve physical status and symptoms of patients with long COVID, yet the evidence is limited. Therefore, this trial aims to study the effect of primary care PR on exercise capacity, symptoms, physical activity and sleep in patients with long COVID. METHODS AND ANALYSIS: PuRe-COVID is a prospective, pragmatic, open-label, randomised controlled trial. A sample of 134 adult patients with long COVID will be randomised to a 12 week PR programme in primary care, supervised by a physiotherapist or to a control group, following no PR. A 3 month and 6 month follow-up period is foreseen. The primary endpoint will be the change in exercise capacity measured by 6-minute walk distance (6MWD) at 12 weeks, hypothesising a more significant improvement in the PR group. Other parameters, such as pulmonary function tests (including maximal inspiratory pressure/maximal expiratory pressure), patient-reported outcomes (COPD Assessment Test, modified Medical Research Council Dyspnoea Scale, Checklist Individual Strength, post-COVID-19 Functional Status, Nijmegen questionnaire, Hospital Anxiety and Depression Scale, Work Productivity and Activity Impairment Questionnaire and EuroQol-5D-5L), physical activity measured by an activity tracker, hand grip strength and sleep efficiency, are secondary and exploratory outcomes.The recruitment started on 19 April 2022, and 52 patients were included as of 14 December 2022. ETHICS AND DISSEMINATION: Ethical approval was obtained in Belgium from the relevant institutional review boards on 21 February 2022 (Antwerp University Hospital, approval number 2022-3067) and on 1 April 2022 (Ziekenhuis Oost-Limburg in Genk, approval number Z-2022-01). Findings from this randomised controlled trial will be disseminated in peer-reviewed publications and presentations at international scientific meetings. TRIAL REGISTRATION NUMBER: NCT05244044.

NMR-Metabolomics Reveals a Metabolic Shift after Surgical Resection of Non-Small Cell Lung Cancer.

BACKGROUND: Lung cancer can be detected by measuring the patient's plasma metabolomic profile using nuclear magnetic resonance (NMR) spectroscopy. This NMR-based plasma metabolomic profile is patient-specific and represents a snapshot of the patient's metabolite concentrations. The onset of non-small cell lung cancer (NSCLC) causes a change in the metabolite profile. However, the level of metabolic changes after complete NSCLC removal is currently unknown. PATIENTS AND METHODS: Fasted pre- and postoperative plasma samples of 74 patients diagnosed with resectable stage I-IIIA NSCLC were analyzed using 1H-NMR spectroscopy. NMR spectra (s = 222) representing two preoperative and one postoperative plasma metabolite profile at three months after surgical resection were obtained for all patients. In total, 228 predictors, i.e., 228 variables representing plasma metabolite concentrations, were extracted from each NMR spectrum. Two types of supervised multivariate discriminant analyses were used to train classifiers presenting a strong differentiation between the pre- and postoperative plasma metabolite profiles. The validation of these trained classification models was obtained by using an independent dataset. RESULTS: A trained multivariate discriminant classification model shows a strong differentiation between the pre- and postoperative NSCLC profiles with a specificity of 96% (95% CI [86-100]) and a sensitivity of 92% (95% CI [81-98]). Validation of this model results in an excellent predictive accuracy of 90% (95% CI [77-97]) and an AUC value of 0.97 (95% CI [0.93-1]). The validation of a second trained model using an additional preoperative control sample dataset confirms the separation of the pre- and postoperative profiles with a predictive accuracy of 93% (95% CI [82-99]) and an AUC value of 0.97 (95% CI [0.93-1]). Metabolite analysis reveals significantly increased lactate, cysteine, asparagine and decreased acetate levels in the postoperative plasma metabolite profile. CONCLUSIONS: The results of this paper demonstrate that surgical removal of NSCLC generates a detectable metabolic shift in blood plasma. The observed metabolic shift indicates that the NSCLC metabolite profile is determined by the tumor's presence rather than donor-specific features. Furthermore, the ability to detect the metabolic difference before and after surgical tumor resection strongly supports the prospect that NMR-generated metabolite profiles via blood samples advance towards early detection of NSCLC recurrence.

Ascertainment of individual risk of mortality for patients with idiopathic pulmonary fibrosis.

RATIONALE: Several predictors of mortality in patients with idiopathic pulmonary fibrosis have been described; however, there is a need for a practical and accurate method of quantifying the prognosis of individual patients. OBJECTIVES: Develop a practical mortality risk scoring system for patients with idiopathic pulmonary fibrosis. METHODS: We used a Cox proportional hazards model and data from two clinical trials (n = 1,099) to identify independent predictors of 1-year mortality among patients with idiopathic pulmonary fibrosis. From the comprehensive model, an abbreviated clinical model comprised of only those predictors that are readily and reliably ascertained by clinicians was derived. Beta coefficients for each predictor were then used to develop a practical mortality risk scoring system. MEASUREMENTS AND MAIN RESULTS: Independent predictors of mortality included age, respiratory hospitalization, percent predicted FVC, 24-week change in FVC, percent predicted carbon monoxide diffusing capacity, 24-week change in percent predicted carbon monoxide diffusing capacity, and 24-week change in health-related quality of life. An abbreviated clinical model comprising only four predictors (age, respiratory hospitalization, percent predicted FVC, and 24-wk change in FVC), and the corresponding risk scoring system produced estimates of 1-year mortality risk consistent with observed data (9.9% vs. 9.7%; C statistic = 0.75; 95% confidence interval, 0.71­0.79). CONCLUSIONS: The prognosis for patients with idiopathic pulmonary fibrosis may be accurately determined using four readily ascertainable predictors. Our simplified scoring system may be a valuable tool for determining prognosis and guiding clinical management. Additional research is needed to validate the applicability and accuracy of the scoring system.

Forced vital capacity in patients with idiopathic pulmonary fibrosis: test properties and minimal clinically important difference.

RATIONALE: Forced vital capacity (FVC) is an established measure of pulmonary function in idiopathic pulmonary fibrosis (IPF). Evidence regarding its measurement properties and minimal clinically important difference (MCID) in this population is limited. OBJECTIVES: To assess the reliability, validity, and responsiveness of FVC and estimate the MCID in patients with IPF. METHODS: The study population included all 1,156 randomized patients in two clinical trials of IFN-γ1b. FVC and other measures of functional status were measured at screening or baseline and 24-week intervals thereafter. Reliability was assessed based on two proximal measures of FVC, validity was assessed based on correlations between FVC and other measures of functional status, and responsiveness was assessed based on the relationship between 24-week changes in FVC and other measures of functional status. Distribution-based and anchor-based methods were used to estimate the MCID. MEASUREMENTS AND MAIN RESULTS: Correlation of percent-predicted FVC between measurements (mean interval, 18 d) was high (r = 0.93; P < 0.001). Correlations between FVC and other parameters were generally weak, with the strongest observed correlation between FVC and carbon monoxide diffusing capacity (r = 0.38; P < 0.001). Correlations between change in FVC and changes in other parameters were slightly stronger (range, r = 0.16-0.37; P < 0.001). Importantly, 1-year risk of death was more than twofold higher (P < 0.001) in patients with a 24-week decline in FVC between 5% and 10%. The estimated MCID was 2-6%. CONCLUSIONS: FVC is a reliable, valid, and responsive measure of clinical status in patients with IPF, and a decline of 2-6%, although small, represents a clinically important difference.

Six-minute-walk test in idiopathic pulmonary fibrosis: test validation and minimal clinically important difference.

RATIONALE: The 6-minute-walk test (6MWT) is a practical and clinically meaningful measure of exercise tolerance with favorable performance characteristics in various cardiac and pulmonary diseases. Performance characteristics in patients with idiopathic pulmonary fibrosis (IPF) have not been systematically evaluated. OBJECTIVES: To assess the reliability, validity, and responsiveness of the 6MWT and estimate the minimal clinically important difference (MCID) in patients with IPF. METHODS: The study population included all subjects completing a 6MWT in a clinical trial evaluating interferon gamma-1b (n = 822). Six-minute walk distance (6MWD) and other parameters were measured at baseline and at 24-week intervals using a standardized protocol. Parametric and distribution-independent correlation coefficients were used to assess the strength of the relationships between 6MWD and measures of pulmonary function, dyspnea, and health-related quality of life. Both distribution-based and anchor-based methods were used to estimate the MCID. MEASUREMENTS AND MAIN RESULTS: Comparison of two proximal measures of 6MWD (mean interval, 24 d) demonstrated good reliability (coefficient = 0.83; P < 0.001). 6MWD was weakly correlated with measures of physiologic function and health-related quality of life; however, values were consistently and significantly lower for patients with the poorest functional status, suggesting good construct validity. Importantly, change in 6MWD was highly predictive of mortality; a 24-week decline of greater than 50 m was associated with a fourfold increase in risk of death at 1 year (hazard ratio, 4.27; 95% confidence interval, 2.57- 7.10; P < 0.001). The estimated MCID was 24-45 m. CONCLUSIONS: The 6MWT is a reliable, valid, and responsive measure of disease status and a valid endpoint for clinical trials in IPF.

HLA-I diversity and tumor mutational burden by comprehensive next-generation sequencing as predictive biomarkers for the treatment of non-small cell lung cancer with PD-(L)1 inhibitors.

OBJECTIVES: Immune checkpoint inhibitors (ICIs) improved outcomes in non-small cell lung cancer (NSCLC) patients. We report the predictive utility of human leukocyte antigen class I (HLA-I) diversity and tumor mutational burden (TMB) by comprehensive next-generation sequencing. METHODS: 126 patients were included. TMB high was defined as ≥ 10 nonsynonymous mutations/Mb. Patients exhibit high HLA-I diversity if at least one locus was in the upper 15th percentile for DNA alignment scores. RESULTS: No difference in response rate (RR; 44.4% versus 30.9%; p = 0.1741) or 6-month survival rate (SR; 75.6% versus 77.8%; p = 0.7765) was noted between HLA-I high diversity and low diversity patients. HLA-I high diversity patients did significantly more often exhibit durable clinical benefit (DCB), defined as response or stable disease lasting minimally 6 months (64.4% [29/45] versus 43.2% [35/81]; p = 0.0223). TMB high patients exhibited higher RR (49.1% versus 25.4%; p = 0.0084) and SR 6 months after start ICI (85.5% versus 70.4%; p = 0.0468) than TMB low patients. The proportion of patients with DCB, did not differ significantly between TMB high and low subgroups (60.0% [33/55] versus 42.3% [30/71]; p = 0.0755). Patients with combined dual high TMB and HLA-I diversity had higher RR (63.2% versus 22.2%; p = 0.0033), but SR at 6 months did not differ significantly (84.2% versus 64,4%; p = 0.1536). A significantly higher rate of patients experienced DCB in dual high compared to the dual low group (73.7% [14/19] versus 35.6% [16/45]; p = 0.0052). Triple positive patients (high TMB and HLA-I diversity and PD-L1 positive) had higher RR (63.6% versus 0.0%; p = 0.0047) and SR at 6 months (100% versus 66.7%; p = 0.0378) compared to triple-negative patients. CONCLUSION: HLA-I diversity was able to predict durable clinical benefit in ICI treated NSCLC patients, but failed to confirm as a predictor of response or survival. TMB confirmed as a predictive biomarker.

Changes in Metabolism as a Diagnostic Tool for Lung Cancer: Systematic Review.

Lung cancer is the leading cause of cancer-related mortality worldwide, with five-year survival rates varying from 3-62%. Screening aims at early detection, but half of the patients are diagnosed in advanced stages, limiting therapeutic possibilities. Positron emission tomography-computed tomography (PET-CT) is an essential technique in lung cancer detection and staging, with a sensitivity reaching 96%. However, since elevated 18F-fluorodeoxyglucose (18F-FDG) uptake is not cancer-specific, PET-CT often fails to discriminate between malignant and non-malignant PET-positive hypermetabolic lesions, with a specificity of only 23%. Furthermore, discrimination between lung cancer types is still impossible without invasive procedures. High mortality and morbidity, low survival rates, and difficulties in early detection, staging, and typing of lung cancer motivate the search for biomarkers to improve the diagnostic process and life expectancy. Metabolomics has emerged as a valuable technique for these pitfalls. Over 150 metabolites have been associated with lung cancer, and several are consistent in their findings of alterations in specific metabolite concentrations. However, there is still more variability than consistency due to the lack of standardized patient cohorts and measurement protocols. This review summarizes the identified metabolic biomarkers for early diagnosis, staging, and typing and reinforces the need for biomarkers to predict disease progression and survival and to support treatment follow-up.

Modulation of thromboinflammation in hospitalized COVID-19 patients with aprotinin, low molecular weight heparin, and anakinra: The DAWn-Antico study.

Background: Thromboinflammation plays a central role in severe COVID-19. The kallikrein pathway activates both inflammatory pathways and contact-mediated coagulation. We investigated if modulation of the thromboinflammatory response improves outcomes in hospitalized COVID-19 patients. Methods: In this multicenter open-label randomized clinical trial (EudraCT 2020-001739-28), patients hospitalized with COVID-19 were 1:2 randomized to receive standard of care (SOC) or SOC plus study intervention. The intervention consisted of aprotinin (2,000,000 IE IV four times daily) combined with low molecular weight heparin (LMWH; SC 50 IU/kg twice daily on the ward, 75 IU/kg twice daily in intensive care). Additionally, patients with predefined hyperinflammation received the interleukin-1 receptor antagonist anakinra (100 mg IV four times daily). The primary outcome was time to a sustained 2-point improvement on the 7-point World Health Organization ordinal scale for clinical status, or discharge. Findings: Between 24 June 2020 and 1 February 2021, 105 patients were randomized, and 102 patients were included in the full analysis set (intervention N = 67 vs. SOC N = 35). Twenty-five patients from the intervention group (37%) received anakinra. The intervention did not affect the primary outcome (HR 0.77 [CI 0.50-1.19], p = 0.24) or mortality (intervention n = 3 [4.6%] vs. SOC n = 2 [5.7%], HR 0.82 [CI 0.14-4.94], p = 0.83). There was one treatment-related adverse event in the intervention group (hematuria, 1.49%). There was one thrombotic event in the intervention group (1.49%) and one in the SOC group (2.86%), but no major bleeding. Conclusions: In hospitalized COVID-19 patients, modulation of thromboinflammation with high-dose aprotinin and LMWH with or without anakinra did not improve outcome in patients with moderate to severe COVID-19.

Newer modes of treating interstitial lung disease.

PURPOSE OF REVIEW: This review critically discusses recent advances in the treatment of idiopathic pulmonary fibrosis (IPF). Moreover, it also focuses on the practical approach of a patient diagnosed with IPF and uncovers challenges for the future. RECENT FINDINGS: Treatment can be divided into three major parts. Firstly, many new agents have been tested, but only the combination of N-acetylcysteine with corticosteroids, azathioprine and pirfenidone was able to show some significant effects. In the mean time, many second-generation agents are under development. Lung transplantation has made some major progress by introducing an appropriate allocation system. Finally, as part of best supportive care, several studies show that pulmonary rehabilitation might induce some important effects on quality of life. SUMMARY: So, it is clear that major progress has been made in the treatment of IPF, but we are convinced that an orchestrated effort will lead to a better understanding and treatment of this devastating condition.

Detection of Lung Cancer via Blood Plasma and 1H-NMR Metabolomics: Validation by a Semi-Targeted and Quantitative Approach Using a Protein-Binding Competitor.

Metabolite profiling of blood plasma, by proton nuclear magnetic resonance (1H-NMR) spectroscopy, offers great potential for early cancer diagnosis and unraveling disruptions in cancer metabolism. Despite the essential attempts to standardize pre-analytical and external conditions, such as pH or temperature, the donor-intrinsic plasma protein concentration is highly overlooked. However, this is of utmost importance, since several metabolites bind to these proteins, resulting in an underestimation of signal intensities. This paper describes a novel 1H-NMR approach to avoid metabolite binding by adding 4 mM trimethylsilyl-2,2,3,3-tetradeuteropropionic acid (TSP) as a strong binding competitor. In addition, it is demonstrated, for the first time, that maleic acid is a reliable internal standard to quantify the human plasma metabolites without the need for protein precipitation. Metabolite spiking is further used to identify the peaks of 62 plasma metabolites and to divide the 1H-NMR spectrum into 237 well-defined integration regions, representing these 62 metabolites. A supervised multivariate classification model, trained using the intensities of these integration regions (areas under the peaks), was able to differentiate between lung cancer patients and healthy controls in a large patient cohort (n = 160), with a specificity, sensitivity, and area under the curve of 93%, 85%, and 0.95, respectively. The robustness of the classification model is shown by validation in an independent patient cohort (n = 72).