Integrative analysis of blood transcriptome profiles in small-cell lung cancer patients for identification of novel chemotherapy resistance-related biomarkers.

Introduction: Chemoresistance constitutes a prevalent factor that significantly impacts thesurvival of patients undergoing treatment for smal-cell lung cancer (SCLC). Chemotherapy resistance in SCLC patients is generally classified as primary or acquired resistance, each governedby distinct mechanisms that remain inadequately researched. Methods: In this study, we performed transcriptome screening of peripheral blood plasma obtainedfrom 17 patients before and after receiving combined etoposide and platinum treatment. We firs testimated pseudo-single-cell analysis using xCell and ESTIMATE and identified differentially expressed genes (DEGs), then performed network analysis to discover key hub genes involved in chemotherapy resistance. Results: Our analysis showed a significant increase in class-switched memory B cell scores acrossboth chemotherapy resistance patterns, indicating their potential crucial role in mediatingresistance. Moreover, network analysis identifed PRICKLE3, TNFSFI0, ACSLl and EP300 as potential contributors to primary resistance, with SNWl, SENP2 and SMNDCl emerging assignificant factors in acquired resistance, providing valuable insights into chemotherapy resistancein SCLC. Discussion: These findings offer valuable insights for understanding chemotherapy resistance and related gene signatures in SCLC, which could help further biological validation studies.

Rapid detection of lung cancer based on serum Raman spectroscopy and a support vector machine: a case-control study.

BACKGROUND: Early screening and detection of lung cancer is essential for the diagnosis and prognosis of the disease. In this paper, we investigated the feasibility of serum Raman spectroscopy for rapid lung cancer screening. METHODS: Raman spectra were collected from 45 patients with lung cancer, 45 with benign lung lesions, and 45 healthy volunteers. And then the support vector machine (SVM) algorithm was applied to build a diagnostic model for lung cancer. Furthermore, 15 independent individuals were sampled for external validation, including 5 lung cancer patients, 5 benign lung lesion patients, and 5 healthy controls. RESULTS: The diagnostic sensitivity, specificity, and accuracy were 91.67%, 92.22%, 90.56% (lung cancer vs. healthy control), 92.22%,95.56%,93.33% (benign lung lesion vs. healthy) and 80.00%, 83.33%, 80.83% (lung cancer vs. benign lung lesion), repectively. In the independent validation cohort, our model showed that all the samples were classified correctly. CONCLUSION: Therefore, this study demonstrates that the serum Raman spectroscopy analysis technique combined with the SVM algorithm has great potential for the noninvasive detection of lung cancer.

Metabolomics-based search for lung cancer markers among patients with different smoking status.

Tobacco smoking is the main etiological factor of lung cancer (LC), which can also cause metabolome disruption. This study aimed to investigate whether the observed metabolic shift in LC patients was also associated with their smoking status. Untargeted metabolomics profiling was applied for the initial screening of changes in serum metabolic profile between LC and chronic obstructive pulmonary disease (COPD) patients, selected as a non-cancer group. Differences in metabolite profiles between current and former smokers were also tested. Then, targeted metabolomics methods were applied to verify and validate the proposed LC biomarkers. For untargeted metabolomics, a single extraction-dual separation workflow was applied. The samples were analyzed using a liquid chromatograph-high resolution quadrupole time-of-flight mass spectrometer. Next, the selected metabolites were quantified using liquid chromatography-triple-quadrupole mass spectrometry. The acquired data confirmed that patients' stratification based on smoking status impacted the discriminating ability of the identified LC marker candidates. Analyzing a validation set of samples enabled us to determine if the putative LC markers were truly robust. It demonstrated significant differences in the case of four metabolites: allantoin, glutamic acid, succinic acid, and sphingosine-1-phosphate. Our research showed that studying the influence of strong environmental factors, such as tobacco smoking, should be considered in cancer marker research since it reduces the risk of false positives and improves understanding of the metabolite shifts in cancer patients.

Exploring the causal association between uric acid and lung cancer in east Asian and European populations: a mendelian randomization study.

BACKGROUND: Lung cancer still ranks first in the mortality rate of cancer. Uric acid is a product of purine metabolism in humans. Its presence in the serum is controversial; some say that its high levels have a protective effect against tumors, others say the opposite, that is, high levels increase the risk of cancer. Therefore, the aim of this study was to investigate the potential causal association between serum uric acid levels and lung cancer. METHODS: Mendelian randomization was used to achieve our aim. Sensitivity analyses was performed to validate the reliability of the results, followed by reverse Mendelian analyses to determine a potential reverse causal association. RESULTS: A significant causal association was found between serum uric acid levels and lung cancer in East Asian and European populations. Further sublayer analysis revealed a significant causal association between uric acid and small cell lung cancer, while no potential association was observed between uric acid and non-small cell lung cancer, squamous lung cancer, and lung adenocarcinoma. The sensitivity analyses confirmed the reliability of the results. Reverse Mendelian analysis showed no reverse causal association between uric acid and lung cancer. CONCLUSIONS: The results of this study suggested that serum uric acid levels were negatively associated with lung cancer, with uric acid being a potential protective factor for lung cancer. In addition, uric acid level monitoring was simple and inexpensive. Therefore, it might be used as a biomarker for lung cancer, promoting its wide use clinical practice.

Deep learning model integrating cfDNA methylation and fragment size profiles for lung cancer diagnosis.

Detecting aberrant cell-free DNA (cfDNA) methylation is a promising strategy for lung cancer diagnosis. In this study, our aim is to identify methylation markers to distinguish patients with lung cancer from healthy individuals. Additionally, we sought to develop a deep learning model incorporating cfDNA methylation and fragment size profiles. To achieve this, we utilized methylation data collected from The Cancer Genome Atlas and Gene Expression Omnibus databases. Then we generated methylated DNA immunoprecipitation sequencing and genome-wide Enzymatic Methyl-seq (EM-seq) form lung cancer tissue and plasma. Using these data, we selected 366 methylation markers. A targeted EM-seq panel was designed using the selected markers, and 142 lung cancer and 56 healthy samples were produced with the panel. Additionally, cfDNA samples from healthy individuals and lung cancer patients were diluted to evaluate sensitivity. Its lung cancer detection performance reached an accuracy of 81.5% and an area under the receiver operating characteristic curve of 0.87. In the serial dilution experiment, we achieved tumor fraction detection of 1% at 98% specificity and 0.1% at 80% specificity. In conclusion, we successfully developed and validated a combination of methylation panel and a deep learning model that can distinguish between patients with lung cancer and healthy individuals.

Accurate Early Detection and EGFR Mutation Status Prediction of Lung Cancer Using Plasma cfDNA Coverage Patterns: A Proof-of-Concept Study.

Lung cancer is a major global health concern with a low survival rate, often due to late-stage diagnosis. Liquid biopsy offers a non-invasive approach to cancer detection and monitoring, utilizing various features of circulating cell-free DNA (cfDNA). In this study, we established two models based on cfDNA coverage patterns at the transcription start sites (TSSs) from 6X whole-genome sequencing: an Early Cancer Screening Model and an EGFR mutation status prediction model. The Early Cancer Screening Model showed encouraging prediction ability, especially for early-stage lung cancer. The EGFR mutation status prediction model exhibited high accuracy in distinguishing between EGFR-positive and wild-type cases. Additionally, cfDNA coverage patterns at TSSs also reflect gene expression patterns at the pathway level in lung cancer patients. These findings demonstrate the potential applications of cfDNA coverage patterns at TSSs in early cancer screening and in cancer subtyping.

Blood Neurofilament Light Chain and Glial Fibrillary Acidic Protein as Promising Screening Biomarkers for Brain Metastases in Patients with Lung Cancer.

The diagnosis of brain metastases (BMs) in patients with lung cancer (LC) predominantly relies on magnetic resonance imaging (MRI), a method that is constrained by high costs and limited accessibility. This study explores the potential of serum neurofilament light chain (sNfL) and serum glial fibrillary acidic protein (sGFAP) as screening biomarkers for BMs in LC patients. We conducted a retrospective analysis of 700 LC cases at the National Cancer Center, Korea, from July 2020 to June 2022, measuring sNfL and sGFAP levels at initial LC diagnosis. The likelihood of BM was evaluated using multivariate analysis and a predictive nomogram. Additionally, we prospectively monitored 177 samples from 46 LC patients initially without BM. Patients with BMs (n= 135) had significantly higher median sNfL (52.5 pg/mL) and sGFAP (239.2 pg/mL) levels compared to those without BMs (n = 565), with medians of 17.8 pg/mL and 141.1 pg/mL, respectively (p < 0.001 for both). The nomogram, incorporating age, sNfL, and sGFAP, predicted BM with an area under the curve (AUC) of 0.877 (95% CI 0.84-0.914), showing 74.8% sensitivity and 83.5% specificity. Over nine months, 93% of samples from patients without BM remained below the cutoff, while all patients developing BMs showed increased levels at detection. A nomogram incorporating age, sNfL, and sGFAP provides a valuable tool for identifying LC patients at high risk for BM, thereby enabling targeted MRI screenings and enhancing diagnostic efficiency.

C-reactive protein as robust laboratory value associated with prognosis in patients with stage III non-small cell lung cancer (NSCLC) treated with definitive radiochemotherapy.

To evaluate the prognostic value of biomarkers from peripheral blood obtained as routine laboratory assessment for overall survival in a cohort of stage III non-small cell lung cancer (NSCLC) patients treated with definitive radiochemotherapy at a high-volume cancer center. Seven blood biomarkers from 160 patients treated with definitive radiochemotherapy for stage III NSCLC were analyzed throughout the course treatment. Parameters were preselected using univariable and multivariable proportional hazards analysis and were assessed for internal validity using leave-one-out cross validation. Cross validated classifiers including biomarkers in addition to important clinical parameters were compared with classifiers containing the clinical parameters alone. An increased C-reactive protein (CRP) value in the final week of radiotherapy was found as a prognostic factor for overall survival, both as a continuous (HR 1.099 (1.038-1.164), p < 0.0012) as well as categorical variable splitting data at the median value of 1.2 mg/dl (HR 2.214 (1.388-3.531), p < 0.0008). In the multivariable analysis, the CRP value-maintained significance with an HR of 1.105 (1.040-1.173) and p-value of 0.0012. The cross validated classifier using CRP at the end of radiotherapy in addition to clinical parameters separated equally sized high and low risk groups more distinctly than a classifier containing the clinical parameters alone (HR = 2.786 (95% CI 1.686-4.605) vs. HR = 2.287 (95% CI 1.407-3.718)). Thus, the CRP value at the end of radiation therapy has successfully passed the crucial cross-validation test. The presented data on CRP levels suggests that inflammatory markers may become increasingly important during definitive radiochemotherapy, particularly with the growing utilization of immunotherapy as a consolidation therapy for stage III NSCLC.

Serum albumin and derived neutrophil-to-lymphocyte ratio are potential predictive biomarkers for immune checkpoint inhibitors in small cell lung cancer.

Background: Immune checkpoint inhibitors (ICIs) have reshaped the treatment landscape of small cell lung cancer (SCLC), but only a minority of patients benefit from this therapy. Therefore, it is critical to identify potential risk factors that could predict the efficacy of ICI treatment in SCLC patients and identify patient subgroups who may benefit the most from ICI therapy. Methods: Our study included a total of 183 SCLC patients who had received at least one dose of ICI treatment. We utilized both logistic regression and Cox proportional hazard regression to evaluate whether various patient clinical factors and serum biomarkers could serve as predictors of patient response to treatment and overall survival (OS) during ICI therapy. Results: Logistic regression showed that patients with a history of surgery (p=0.003, OR 9.06, 95% CI: (2.17, 37.9)) and no metastasis (p=0.008, OR 7.82, 95% CI: (1.73, 35.4)) exhibited a higher odds of response to ICI treatment. Cox regression analyses demonstrated that pretreatment blood albumin (p=0.003, HR 1.72, 95% CI: (1.21, 2.45)) and derived neutrophil to lymphocyte ratio (dNLR) (p=0.003, HR 1.71, 95% CI: (1.20-2.44)) were independent predictors for OS in SCLC patients. By establishing a pre-treatment prognostic scoring system based on baseline albumin and dNLR, we found that patients with high albumin and low dNLR exhibited a significantly better prognosis than those with low albumin and high dNLR in both the full (P<.0001, HR 0.33, 95% CI: 0.20-0.55) and the metastatic cohort (P<.0001, HR 0.28, 95% CI: 0.15-0.51). The better prognostic group also had younger age, higher BMI and lower systemic inflammatory biomarker values than the unfavorable group (P<.0001). Conclusion: Our data reveals the significant role of metastasis status and treatment history in predicting the initial response of SCLC patients to ICI treatment. However, baseline serum albumin and dNLR provide a more precise prognostic prediction for patient OS. The scoring system based on albumin and dNLR enhances the ability to stratify patient prognosis and holds the potential to guide clinical decision-making for SCLC patients undergoing ICI therapy.

Tumor Educated Platelets as a Biomarker for Diagnosis of Lung cancer: A Systematic Review.

INTRODUCTION: Lung cancer is one of the commonest cause of cancer associated mortality worldwide. Platelets have emerged as key players in cancer development and progression by supporting tumor growth, and dissemination. In the present systematic review, we analyzed RNA transfer between cancer cells and platelets and explored potential role of different platelet RNA profiles as onco-signature in diagnosis, subtyping, disease progression and treatment monitoring in carcinoma lung carcinoma. MATERIALS AND METHODS: The study followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and Cochrane Manual of Systematic Reviews and Meta-analysis that included seven studies on patients with lung cancer, with data on tumor-educated platelets, and control group. The outcome measured was based on sensitivity, specificity, and ROC. PUBMED, SCOPUS, Central Cochrane Registry of Controlled Trials and Science Direct databases were searched using specific search terms until October 2023. QUADAS - 2 tool was used to assess quality, risk of bias and applicability concerns. RESULTS: The analysis revealed AUC > 70% for different platelet mRNAs, with sensitivity and specificity of more than 60 %. AUC and sensitivity were highest for ITGA2B (AUC 0.922; sensitivity 92.8%). lncRNA GTF2H2-1 was the most specific platelet RNA. On QUADAS-2 tool, 3/7 articles were unclear in reference standards, patient flow timing, and 1/7 had high bias in both aspects. For applicability, 1/7 studies were unclear in reference standards, and 2/7 in index tests. CONCLUSION: TEP RNA can aid in early diagnosis of lung cancer and of proven utility in its early-stage detection. TEP RNA can also monitor disease progression and treatment response.

Lung cancer metabolomics: a pooled analysis in the Cancer Prevention Studies.

BACKGROUND: A better understanding of lung cancer etiology and the development of screening biomarkers have important implications for lung cancer prevention. METHODS: We included 623 matched case-control pairs from the Cancer Prevention Study (CPS) cohorts. Pre-diagnosis blood samples were collected between 1998 and 2001 in the CPS-II Nutrition cohort and 2006 and 2013 in the CPS-3 cohort and were sent for metabolomics profiling simultaneously. Cancer-free controls at the time of case diagnosis were 1:1 matched to cases on date of birth, blood draw date, sex, and race/ethnicity. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using conditional logistic regression, controlling for confounders. The Benjamini-Hochberg method was used to correct for multiple comparisons. RESULTS: Sphingomyelin (d18:0/22:0) (OR: 1.32; 95% CI: 1.15, 1.53, FDR = 0.15) and taurodeoxycholic acid 3-sulfate (OR: 1.33; 95% CI: 1.14, 1.55, FDR = 0.15) were positively associated with lung cancer risk. Participants diagnosed within 3 years of blood draw had a 55% and 48% higher risk of lung cancer per standard deviation increase in natural log-transformed sphingomyelin (d18:0/22:0) and taurodeoxycholic acid 3-sulfate level, while 26% and 28% higher risk for those diagnosed beyond 3 years, compared to matched controls. Lipid and amino acid metabolism accounted for 47% to 80% of lung cancer-associated metabolites at P < 0.05 across all participants and subgroups. Notably, ever-smokers exhibited a higher proportion of lung cancer-associated metabolites (P < 0.05) in xenobiotic- and lipid-associated pathways, whereas never-smokers showed a more pronounced involvement of amino acid- and lipid-associated metabolic pathways. CONCLUSIONS: This is the largest prospective study examining untargeted metabolic profiles regarding lung cancer risk. Sphingomyelin (d18:0/22:0), a sphingolipid, and taurodeoxycholic acid 3-sulfate, a bile salt, may be risk factors and potential screening biomarkers for lung cancer. Lipid and amino acid metabolism may contribute significantly to lung cancer etiology which varied by smoking status.

Assessment of serum tumor markers CEA, CA-125, and CA19-9 as adjuncts in non-small cell lung cancer management.

Conventional tumor markers may serve as adjuncts in non-small cell lung cancer (NSCLC) management. This study analyzed whether three tumor markers (CEA, CA19-9, and CA-125) held associations with radiographic and clinical outcomes in NSCLC. It constituted a single-center study of NSCLC patients treated with systemic therapy at the London Regional Cancer Program. Serum tumor markers were analyzed for differences in radiographic responses (RECIST v1.1 or iRECIST), associations with clinical characteristics, and all-cause mortality. A total of 533 NSCLC patients were screened, of which 165 met inclusion criteria. A subset of 92 patients had paired tumor markers and radiographic scans. From the latter population, median (IQR) fold-change from nadir to progression was 2.13 (IQR 1.24-3.02; p < 0.001) for CEA, 1.46 (IQR 1.13-2.18; p < 0.001) for CA19-9, and 1.53 (IQR 0.96-2.12; p < 0.001) for CA-125. Median (IQR) fold-change from baseline to radiographic response was 0.50 (IQR 0.27, 0.95; p < 0.001) for CEA, 1.08 (IQR 0.74, 1.61; p = 0.99) for CA19-9, and 0.47 (IQR 0.18, 1.26; p = 0.008) for CA-125. In conclusion, tumor markers are positioned to be used as adjunct tools in clinical decision making, especially for their associations with radiographic response (CEA/CA-125) or progression (CEA/CA-125/CA-19-9).

Risk Factors of Severe Postoperative Complication in Lung Cancer Patients with Diabetes Mellitus.

PURPOSE: Clinically, postoperative complications are occasionally observed in lung cancer patients with diabetes mellitus (DM). The increased risk of postoperative complications in DM patients has been reported in other fields. This study aims to identify risk factors for severe postoperative complications in lung cancer patients with DM. METHODS: Of 2756 consecutive patients who underwent complete resection for lung cancer between 2008 and 2018 in our hospital, 475 patients (20%) were complicated by DM. Clinical factors and diabetic factors (HbA1c, preoperative fasting blood glucose [FBG], postoperative mean FBG on 1, 3 postoperative days [PODs], and use of insulin) were evaluated by univariable and multivariable analyses to identify independent risk factors of severe complication. RESULTS: The 349 (73%) patients were male. Their median age was 71 years. Severe perioperative complications occurred in 128 (27%) patients. In the multivariable analysis, male (p <0.01), age (≥75 years) (p = 0.04), preoperative FBG (≥140 mg/dL) (p = 0.03), and increased mean FBG on 1, 3 PODs (≥180 mg/dL) (p <0.01) were significantly associated with severe perioperative complications. CONCLUSION: Increased FBG on 1, 3 PODs (≥180 mg/dL) was an independent risk factor for severe perioperative complications in lung cancer with DM. Postoperative hyperglycemia may be correlated to severe perioperative complications.

Prognostic significance of programmed cell death ligand 1 blood markers in non-small cell lung cancer treated with immune checkpoint inhibitors: a systematic review and meta-analysis.

Background: Immune checkpoint inhibitors (ICIs) are effective for non-small cell lung cancer (NSCLC) treatment, but the response rate remains low. Programmed cell death ligand 1 (PD-L1) in peripheral blood, including soluble form (sPD-L1), expression on circulating tumor cells (CTCs PD-L1) and exosomes (exoPD-L1), are minimally invasive and promising markers for patient selection and management, but their prognostic significance remains inconclusive. Here, we performed a meta-analysis for the prognostic value of PD-L1 blood markers in NSCLC patients treated with ICIs. Methods: Eligible studies were obtained by searching PubMed, EMBAS, Web of Science, and Cochrane Library prior to November 30, 2023. The associations between pre-treatment, post-treatment and dynamic changes of blood PD-L1 levels and progression-free survival (PFS)/over survival (OS) were analyzed by estimating hazard ratio (HR) and 95% confidence interval (CI). Results: A total of 26 studies comprising 1606 patients were included. High pre- or post-treatment sPD-L1 levels were significantly associated with worse PFS (pre-treatment: HR=1.49, 95%CI 1.13-1.95; post-treatment: HR=2.09, 95%CI 1.40-3.12) and OS (pre-treatment: HR=1.83, 95%CI 1.25-2.67; post-treatment: HR=2.60, 95%CI 1.09-6.20, P=0.032). High pre-treatment exoPD-L1 levels predicted a worse PFS (HR=4.24, 95%CI 2.82-6.38, P<0.001). Pre-treatment PD-L1+ CTCs tended to be correlated with prolonged PFS (HR=0.63, 95%CI 0.39-1.02) and OS (HR=0.58, 95%CI 0.36-0.93). Patients with up-regulated exoPD-L1 levels, but not sPD-L1, after ICIs treatment had significantly favorable PFS (HR=0.36, 95%CI 0.23-0.55) and OS (HR=0.24, 95%CI 0.08-0.68). Conclusion: PD-L1 blood markers, including sPD-L1, CTCs PD-L1 and exoPD-L1, can effectively predict prognosis, and may be potentially utilized for patient selection and treatment management for NSCLC patients receiving ICIs.

Influence of higher body mass index on postoperative nausea and vomiting in patients following thoracic surgery for lung cancer: a propensity score-matched cohort study.

This study aimed to quantify the association between body mass index (BMI) and postoperative nausea and vomiting (PONV) within the initial 48 h following thoracic surgery for lung cancer. We then explored whether changes in serum inflammatory factor concentrations were related to BMI during the early postoperative period. We conducted a propensity score-matched (PSM), retrospective cohort study at a specialized tertiary medical center. A total of 194 patients aged 18-80 years who underwent thoracic surgery for lung cancer at Shanghai Pulmonary Hospital between January and June 2021 were enrolled. The primary outcome was the incidence of PONV during the first 48 h after surgery. Nausea, vomiting or retching at different time periods, severe pain, and concentrations of perioperative serum inflammatory factors including CRP, IL-6, IL-12, and IFN-γ were also assessed. Patients in the high BMI group (BMI ≥ 25 kg/m2) had a lower incidence of PONV than those in the normal BMI group (18.5-25 kg/m2) within the first 48 h after surgery (22 vs. 50%, p = 0.004). The incidence of nausea was lower at 0-12 h (14.5 vs. 37.1%, p = 0.004) and 12-24 h (8.1 vs. 22.6%, p = 0.025) in the high BMI group after surgery, and the incidence of vomiting was lower at 0-12 h (12.9 vs. 30.6%, p = 0.017) in higher BMI after surgery. We found no significant difference in the incidence of severe pain [severe static pain (p = 0.697) and severe dynamic pain (p = 0.158)]. Moreover, higher concentrations of IL-12 (2.24 ± 2.67 pg/ml vs. 1.48 ± 1.14 pg/ml, p = 0.048) and IFN-γ [1.55 (1.00) pg/ml vs. 1.30 (0.89) pg/ml, p = 0.041] were observed in patients with normal BMI on the first day after surgery. Given this finding, patients with a normal BMI should receive more attention for the prevention of PONV than those with a high BMI following thoracic surgery for lung cancer.Trial registration: http://www.chictr.org.cn and ChiCTR2100052380 (24/10/2021).

Tumor mutational burden adjusted by neutrophil-to-lymphocyte ratio serves as a potential biomarker for atezolizumab-treated patients with extensive stage small cell lung cancer.

BACKGROUND: There is a desperate for the identification of more accurate and efficient biomarkers for ICI responses in patients with SCLC. METHODS: The data of our study was obtained from IMpower133 study. A total of 202 patients with SCLC received the treatment of placebo plus carboplatin plus etoposide (EC) while a total of 201 patients with SCLC received the treatment of atezolizumab plus EC. Overall survival (OS) was compared using Kaplan Meier analyses. Univariate and multivariate Cox regression analysis were used to determine independent prognostic variables affecting OS in patients with SCLC. RESULTS: We have demonstrated that a higher TMB adjusted by a lower neutrophil-to-lymphocyte ratio (NLR) is significantly correlated with improved OS, in patients with SCLC subject to either atezolizumab or placebo (P = 0.001 for atezolizumab and P = 0.034 for placebo). Moreover, Cox model showed that TMB < 10 mut/Mb adjusted by NLR ≥ median was an independent factor of OS for atezolizumab-treated SCLC patients (hazard ratio [HR], 2.82; 95% confidence interval; 1.52-5.24; P = 0.001). Both univariate and multivariate cox regression analysis showed that for patients with SCLC harboring low NLR and high TMB, survival is significantly longer in those treated with atezolizumab than those treated with placebo. Survival benefit is significantly higher in atezolizumab-treated patients with SCLC than those treated with placebo (P = 0.018 for TMB cutoff = 10 mut/Mb, P = 0.034 for TMB cutoff = 16 mut/Mb). CONCLUSION: Our findings provide a promising insight into the utility of NLR-adjusted TMB in the prognosis and immune responses in patients with SCLC.

Circulating receptor activator of nuclear factor kappa-B ligand (RANKL) levels predict response to immune checkpoint inhibitors in advanced non-small cell lung cancer (NSCLC).

BACKGROUND: Receptor activator of nuclear factor kappa-B ligand (RANKL) can directly promote tumor growth and indirectly support tumor immune evasion by altering the tumor microenvironment and immune cell responses. This study aimed to assess the prognostic significance of soluble RANKL in patients with advanced non-small cell lung cancer (NSCLC) receiving programmed cell death 1 (PD1)/programmed death-ligand 1 (PDL1) checkpoint inhibitor therapy. METHODS: Plasma RANKL levels were measured in 100 patients with advanced NSCLC without bone metastases undergoing monotherapy with PD1/PDL1 checkpoint inhibitors. To establish the optimal cut-off value, we used the Cutoff Finder package in R. Survival curves for four distinct patient groups, according to their RANKL and PDL1 levels (high or low), were generated using the Kaplan-Meier method and compared with the log-rank test. The Cox regression model calculated HRs and 95% CIs for overall survival (OS) and progression-free survival (PFS). RESULTS: The optimal RANKL cut-off was established at 280.4 pg/mL, categorizing patients into groups with high or low RANKL levels. A significant association was observed between increased RANKL concentrations and decreased survival rates at 24 months, only within the subgroup expressing high levels of PDL1 (p=0.002). Additionally, low RANKL levels in conjunction with elevated PDL1 expression correlated with improved PFS (median 22 months, 95% CI 6.70 to 50 vs median 4 months, 95% CI 3.0 to 7.30, p=0.009) and OS (median 26 months, 95% CI 20 to not reached vs median 7 months, 95% CI 6 to 13, p=0.003), indicating RANKL's potential as an indicator of adverse prognosis in these patients. Multivariate analysis identified RANKL as an independent negative prognostic factor for both PFS and OS, regardless of other clinicopathological features. CONCLUSION: These results highlight the prognostic and predictive value of RANKL specifically in patients with high PDL1 expression.

The predictive value of delta-like3 and serum NSE in evaluating chemotherapy response and prognosis in patients with advanced small cell lung carcinoma: An observational study.

Lung cancer is one of the most malignant tumors with fastest morbidity and mortality. Small cell lung cancer (SCLC) is the most malignant pathological type of lung cancer with early metastasis and poor prognosis. At present, there is a lack of effective indicators to predict prognosis of SCLC patients. Delta-like 3 protein (DLL3) is selectively expressed on the surface of SCLC and is involved in proliferation and invasion. Neuron-specific enolase (NSE) is an enolase isoenzyme that is generally regarded as a biomarker for SCLC and may correlate with stage of SCLC, prognosis and chemotherapy response. NSE can be influenced by different types of factors. To explore the associations between expression levels of DLL3 in tumor tissues with platinum/etoposide chemotherapy response, and assess the prognostic values of DLL3, NSE and other potential prognostic factors in advanced SCLC patients were herein studied. Ninety-seven patients diagnosed with SCLC in Zhongda Hospital from 2014 to 2020 were enrolled in the study. Serum NSE levels were tested using ELISA methods before any treatment. The expression of DLL3 in tumor tissue was detected by Immunohistochemistry (IHC). We investigated the relationship of DLL3 expression with chemotherapy and survival. Progression free survival (PFS) and overall survival (OS) were estimated by the Kaplan-Meier method. Multivariate Cox-proportional hazard regression was used to identify predictors of PFS and OS. DLL3 was detected in 84.5% (82/97) of all patients' tumor samples by IHC, mainly located on the surface of SCLC cells. Lower DLL3 expression was associated with longer PFS and better chemotherapy response. OS had no significant differences. Multivariate analysis by Cox Hazard model showed that, high DLL3 expression and maximum tumor size >5 cm were independent risk factors for PFS, where NSE < 35 ng/mL and age < 70 were independent prognostic factors for OS. Early stage was independent prognostic factors for PFS and OS (P < .05 log-rank). DLL3 was expressed in the most of SCLCs. DLL3 expression level in the tumor and NSE level in the serum may be useful biomarkers to predict the prognosis of SCLC. DLL3 may be a potential therapeutic target for SCLC in the future.

Identifying MiR-140-3p as a stable internal reference to normalize MicroRNA qRT-PCR levels of plasma small extracellular vesicles in lung cancer patients.

Exploration of a stably expressed gene as a reference is critical for the accurate evaluation of miRNAs isolated from small extracellular vesicles (sEVs). In this study, we analyzed small RNA sequencing on plasma sEV miRNAs in the training dataset (n = 104) and found that miR-140-3p was the most stably expressed candidate reference for sEV miRNAs. We further demonstrated that miR-140-3p expressed most stably in the validation cohort (n = 46) when compared to two other reference miRNAs, miR-451a and miR-1228-3p, and the commonly-used miRNA reference U6. Finally, we compared the capability of miR-140-3p and U6 as the internal reference for sEV miRNA expression by evaluating key miRNAs expression in lung cancer patients and found that miR-140-3p was more suitable as a sEV miRNA reference gene. Taken together, our data indicated miR-140-3p as a stable internal reference miRNA of plasma sEVs to evaluate miRNA expression profiles in lung cancer patients.

Prognostic Outcome of Pulmonary Resection for Pulmonary Metastases from Gastric Cancer.

PURPOSE: Regardless of the devastating outcomes of pulmonary resection for metastases from gastric cancer, a handful of patients survive long after pulmonary metastasectomy. This study aimed to identify a good candidate for pulmonary resection for metastases from gastric cancer. METHODS: Between 2005 and 2023, 564 patients underwent pulmonary metastasectomy in our department, of which 12 patients underwent pulmonary resection for metastases from gastric cancer. Variables evaluated were the number and size of metastatic lesions, surgical procedure, disease-free interval (DFI), and the serum carcinoembryonic antigen at pulmonary metastasectomy. RESULTS: The DFI following gastrectomy ≤12.5 months group had a significantly worse overall survival (OS) than the other group (p = 0.005). A comparison between DFI following gastrectomy ≤12.5 months group and DFI following gastrectomy >12.5 months group showed a significant difference in serum carcinoembryonic antigen (CEA) value at pulmonary metastasectomy (p = 0.048). The serum CEA value at pulmonary metastasectomy >5.8 ng/ml group had a significantly worse OS than the other group (p = 0.001). CONCLUSION: Pulmonary metastasectomy can be indicated in some patients with metastasis from gastric cancer who have longer DFI from gastrectomy and lower serum CEA at pulmonary metastasectomy.