Optical Nanobiosensor Based on Surface-Enhanced Raman Spectroscopy and Catalytic Hairpin Assembly for Early-Stage Lung Cancer Detection via Blood Circular RNA.

Lung cancer has become the leading cause of cancer-related deaths globally. However, early detection of lung cancer remains challenging, resulting in poor outcomes for the patients. Herein, we developed an optical biosensor integrating surface-enhanced Raman spectroscopy (SERS) with a catalyzed hairpin assembly (CHA) to detect circular RNA (circRNA) associated with tumor formation and progression (circSATB2). The signals of the Raman reporter were considerably enhanced by generating abundant SERS "hot spots" with a core-shell nanoprobe and 2D SERS substrate with calibration capabilities. This approach enabled the sensitive (limit of detection: 0.766 fM) and reliable quantitative detection of the target circRNA. Further, we used the developed biosensor to detect the circRNA in human serum samples, revealing that patients with lung cancer had higher circRNA concentrations than healthy subjects. Moreover, we characterized the unique circRNA concentration profiles of the early stages (IA and IB) and subtypes (IA1, IA2, and IA3) of lung cancer. These results demonstrate the potential of the proposed optical sensing nanoplatform as a liquid biopsy and prognostic tool for the early screening of lung cancer.

Comprehensive genomic profiling of pulmonary spindle cell carcinoma using tissue and plasma samples: insights from a real-world cohort analysis.

Pulmonary spindle cell carcinoma (PSCC) is a rare and aggressive non-small cell lung cancer (NSCLC) subtype with a dismal prognosis. The molecular characteristics of PSCC are largely unknown due to its rarity, which limits the diagnosis and treatment of this historically poorly characterized malignancy. We present comprehensive genomic profiling results of baseline tumor samples from 22 patients histologically diagnosed with PSCC, representing the largest cohort to date. Somatic genetic variant detection was compared between paired plasma samples and primary tumors from 13 patients within our cohort. The associations among genomic features, treatment, and prognosis were also analyzed in representative patient cases. TP53 (54.5%), TERT (36.4%), CDKN2A (27.3%), and MET (22.7%) were most frequently mutated. Notably, 81.8% of patients had actionable targets in their baseline tumors, including MET (22.7%), ERBB2 (13.6%), EGFR (9.1%), KRAS (9.1%), ALK (9.1%), and ROS1 (4.5%). The median tumor mutation burden (TMB) for PSCC tumors was 5.5 mutations per megabase (muts/Mb). TMB-high tumors (>10 muts/Mb) exhibited a significantly higher mutation frequency in genes such as KRAS, ARID2, FOXL2, and LRP1B, as well as within the DNA mismatch repair pathway. The detection rates for single nucleotide variants and structural variants were comparable between matched tumor and plasma samples, with 48.6% of genetic variants being mutually identified in both sample types. Additionally, a patient with a high mutation load and positive PD-L1 expression demonstrated a 7-month survival benefit from chemoimmunotherapy. Furthermore, a patient with an ALK-rearranged tumor achieved a remarkable 3-year progression-free survival following crizotinib treatment. Overall, our findings deepen the understanding of the complex genomic landscape of PSCC, revealing actionable targets amenable to tailored treatment of this poorly characterized malignancy.

Evaluation of the preoperative neutrophil-to-lymphocyte ratio as a predictor of the micropapillary component of stage IA lung adenocarcinoma.

OBJECTIVE: To assess the ability of markers of inflammation to identify the solid or micropapillary components of stage IA lung adenocarcinoma and their effects on prognosis. METHODS: We performed a retrospective study of clinicopathologic data from 654 patients with stage IA lung adenocarcinoma collected between 2013 and 2019. Logistic regression analysis was used to identify independent predictors of these components, and we also evaluated the relationship between markers of inflammation and recurrence. RESULTS: Micropapillary-positive participants had high preoperative neutrophil-to-lymphocyte ratios. There were no significant differences in the levels of markers of systemic inflammation between the participants with or without a solid component. Multivariate analysis showed that preoperative neutrophil-to-lymphocyte ratio (odds ratio [OR] = 2.094; 95% confidence interval [CI], 1.668-2.628), tumor size (OR = 1.386; 95% CI, 1.044-1.842), and carcinoembryonic antigen concentration (OR = 1.067; 95% CI, 1.017-1.119) were independent predictors of a micropapillary component. There were no significant correlations between markers of systemic inflammation and the recurrence of stage IA lung adenocarcinoma. CONCLUSIONS: Preoperative neutrophil-to-lymphocyte ratio independently predicts a micropapillary component of stage IA lung adenocarcinoma. Therefore, the potential use of preoperative neutrophil-to-lymphocyte ratio in the optimization of surgical strategies for the treatment of stage IA lung adenocarcinoma should be further studied.

Relationship between hemoglobin and lung cancer: evidence from Mendelian randomization and National Health and Nutrition Examination Survey

Background Lung cancer is the primary cause of cancer-related mortality worldwide. Hemoglobin (Hb) represents the most widely utilized test parameter in clinical settings. However, few articles have examined the causal relationship between Hb concentration and lung cancer incidence. Methods Mendelian randomization (MR) was first conducted to investigate the potential causality between Hb and lung cancer. Sensitivity analyses were applied to validate the reliability of MR results. Then, the National Health and Nutrition Examination Survey (NHANES) database was used to verify the effect of Hb on the prognosis of lung cancer. Results The MR analysis demonstrated that Hb was casually associated with the decreased risk of lung cancer in the European population (ORIVW 0.84, 95% CI 0.75–0.95, p = 0.006; ORWeighted-median 0.78, 95% CI 0.65–0.94, p = 0.008; ORMR-Egger 0.82, 95% CI 0.64–1.04, p = 0.11). The results from the NHANES database showed that a high value of Hb was associated with better outcomes for patients with lung cancer (HR 0.45, 95% CI 0.26–0.79, p = 1.6E−03). Conclusions Our study provides further evidence for the relationship between Hb levels and lung cancer, highlighting the potential significance of Hb as a biomarker for predicting the risk and prognosis of lung cancer (AU)

Clinical value of serum DJ-1 in lung adenocarcinoma.

Objective: DJ-1 is an oncoprotein secreted by cancer cells. However, the physiological and pathological significance of DJ-1 secretion is not clearly understood. This study investigated the clinical value of serum DJ-1 in lung adenocarcinoma (LUAD). Methods: The study involved 224 LUAD patients, 110 patients with benign pulmonary disease and 100 healthy controls from the First Affiliated Hospital of Nanjing Medical University. We detected the expression of DJ-1 in lung cell lines in vitro. Meanwhile, serum concentrations of DJ-1, carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), and cytokeratin 19 fragment (CYFRA21-1) were measured. The diagnostic performance of LUAD was obtained using receiver operating characteristic (ROC) curves. Kaplan-Meier, univariate and multivariate Cox regression analyses were performed for progression-free survival (PFS). Results: DJ-1 was highly expressed in LUAD cell lines. Serum DJ-1 levels were significantly higher in the LUAD group compared to the benign pulmonary disease group (5.04 vs. 3.66 ng/mL, P < 0.001) and healthy controls (5.04 vs. 3.51 ng/mL, P < 0.001). DJ-1 levels were associated with gender (P = 0.002), smoking history (P = 0.042) and lymph node metastasis (P = 0.040). ROC curve analysis of DJ-1 revealed an area under the curve (AUC) of 0.758 (95% CI [0.714-0.803], P < 0.001) with a sensitivity of 63.8% and specificity of 78.6% at a cutoff value of 4.62 ng/mL for the detection of LUAD. Univariate and multivariate analyses confirmed that the preoperative serum DJ-1 level, tumor stage and smoking history were independent prognostic factors of PFS. Conclusion: Our study is the first to explore the clinical value of serum DJ-1 in LUAD comprehensively. Serum DJ-1 could be a potential diagnostic and prognostic biomarker for LUAD.

HOXA9 gene promotor methylation and copy number variation of SOX2 and HV2 genes in cell free DNA: A potential diagnostic panel for non-small cell lung cancer.

BACKGROUND: Most cases of lung cancer are diagnosed at advanced stage. Detection of genetic and epigenetic markers in cell-free DNA (cfDNA) is a promising tool for the diagnosis of lung cancer at an early stage. The aim of this study was to identify non-invasive diagnostic markers in cell free DNA (cfDNA) for non-small cell lung cancer (NSCLC) as it is the most common type of lung cancer. METHODS: We investigated the cfDNA HOXA9 gene promotor methylation by pyrosequencing. Copy number variation of SOX2 and HV2 genes were detected by real-time PCR in cfDNA extracted from plasma samples of 25 newly diagnosed NSCLC patients and 25 age and sex matched controls. RESULTS: Methylation level of HOXA9 was significantly higher in NSCLC patients than controls (p > 0.001). SOX2 showed significantly higher CNV and HV2 showed lower CNV in patients than controls (p > 0.001, p = 0.001 respectively). Receiver Operating Characteristic (ROC) curve analysis for HOXA9 methylation, SOX2 CNV and HV2 CNV showed a discrimination power of 79.4%, 80% and 77.5% respectively and the area under the curve for the combined analysis of the three genes was 0.958 with 88% sensitivity and 100% specificity. CONCLUSIONS: In this study, we suggest a potentially diagnostic panel that may help in detection of lung cancer with high sensitivity and specificity using cell free DNA. This Panel included HOXA9 gene methylation and the CNV of SOX2 and HV2 genes.

Cytokine profiling identifies circulating IL-6 and IL-15 as prognostic stratifiers in patients with non-small cell lung cancer receiving anti-PD-1/PD-L1 blockade therapy.

Whether circulating levels of specific cytokines at baseline link with treatment efficacy of immune checkpoint blockade (ICB) therapy in patients with non-small cell lung cancer remains unknown. In this study, serum samples were collected in two independent, prospective, multicenter cohorts before the initiation of ICB. Twenty cytokines were quantified, and cutoff values were determined by receiver operating characteristic analyses to predict non-durable benefit. The associations of each dichotomized cytokine status with survival outcomes were assessed. In the discovery cohort (atezolizumab cohort; N = 81), there were significant differences in progression-free survival (PFS) in accordance with the levels of IL-6 (log-rank test, P = 0.0014), IL-15 (P = 0.00011), MCP-1 (P = 0.013), MIP-1ß (P = 0.0035), and PDGF-AB/BB (P = 0.016). Of these, levels of IL-6 and IL-15 were also significantly prognostic in the validation cohort (nivolumab cohort, N = 139) for PFS (log-rank test, P = 0.011 for IL-6 and P = 0.00065 for IL-15) and overall survival (OS; P = 3.3E-6 for IL-6 and P = 0.0022 for IL-15). In the merged cohort, IL-6high and IL-15high were identified as independent unfavorable prognostic factors for PFS and OS. The combined IL-6 and IL-15 status stratified patient survival outcomes into three distinct groups for both PFS and OS. In conclusion, combined assessment of circulating IL-6 and IL-15 levels at baseline provides valuable information to stratify the clinical outcome of patients with non-small cell lung cancer treated with ICB. Further studies are required to decipher the mechanistic basis of this finding.

Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA.

Circulating tumour DNA (ctDNA) can be used to detect and profile residual tumour cells persisting after curative intent therapy1. The study of large patient cohorts incorporating longitudinal plasma sampling and extended follow-up is required to determine the role of ctDNA as a phylogenetic biomarker of relapse in early-stage non-small-cell lung cancer (NSCLC). Here we developed ctDNA methods tracking a median of 200 mutations identified in resected NSCLC tissue across 1,069 plasma samples collected from 197 patients enrolled in the TRACERx study2. A lack of preoperative ctDNA detection distinguished biologically indolent lung adenocarcinoma with good clinical outcome. Postoperative plasma analyses were interpreted within the context of standard-of-care radiological surveillance and administration of cytotoxic adjuvant therapy. Landmark analyses of plasma samples collected within 120 days after surgery revealed ctDNA detection in 25% of patients, including 49% of all patients who experienced clinical relapse; 3 to 6 monthly ctDNA surveillance identified impending disease relapse in an additional 20% of landmark-negative patients. We developed a bioinformatic tool (ECLIPSE) for non-invasive tracking of subclonal architecture at low ctDNA levels. ECLIPSE identified patients with polyclonal metastatic dissemination, which was associated with a poor clinical outcome. By measuring subclone cancer cell fractions in preoperative plasma, we found that subclones seeding future metastases were significantly more expanded compared with non-metastatic subclones. Our findings will support (neo)adjuvant trial advances and provide insights into the process of metastatic dissemination using low-ctDNA-level liquid biopsy.

New insights into the diagnostic characteristics and clinical application of serum biomarkers for lung cancer, and human epididymis protein 4 as a new biomarker?

The value of serum tumor biomarkers used for lung cancer diagnosis is still controversial in clinical practice. This study aimed to further dissect and evaluate the clinical value of serum progastrin-releasing peptide (ProGRP), neuron-specific enolase (NSE), squamous cell carcinoma antigen (SCC-Ag), carcinoembryonic antigen (CEA), cytokeratin-19 fragment (CYFRA21-1) together with a potential new biomarker, the human epididymis protein 4 (HE4) for lung cancer diagnosis, in a large cohort of a Chinese population. Ostensibly healthy individuals, as well as those with benign non-cancerous diseases, benign tumors, lung cancers, and other types of malignancies, were enrolled in the study. Serum ProGRP, NSE, SCC-Ag, CEA, CYFRA21-1, and HE4 were analyzed using the chemiluminescence immunoassay. Data were analyzed utilizing the SPSS and GraphPad Prism software. Detailed dissection of the diagnostic characteristics of serum 6 biomarkers on lung cancer was performed. All 6 biomarkers showed capabilities in characterizing lung cancer from other diseases. ProGRP and NSE were highly specific to small cell lung cancer (SCLC); SCC-Ag was a fair biomarker for NSCLC, specifically SCC histotype; CEA showed specificity to SCLC, followed by NSCLC; CYFRA21-1 was a good biomarker for both SCLC and NSCLC; HE4 showed high specificity to SCLC. For NSCLC characterization, CYFRA21-1+HE4+CEA was the best combinatory pattern in the terms of diagnostic performance (AUC=0.8110). The best combinatory analysis for SCLC was ProGRP+NSE+HE4 (AUC=0.9282). Patients with advanced stage, larger tumor, males, and age 50 or older had higher serum biomarkers levels than those with early stage, smaller tumor, females, and age under 50. Six biomarkers had capabilities in characterizing lung cancer with high or fair diagnostic performance. HE4 is a potential biomarker for both SCLC and NSCLC diagnosis, which merits further investigation.

Differential expression and analysis of extrachromosomal circular DNAs as serum biomarkers in lung adenocarcinoma.

BACKGROUND: Extrachromosomal circular DNAs (eccDNAs) increase the number of proto-oncogenes by enhancing oncogene expression to promote tumorigenesis. However, there are limited reports on differential eccDNA expression and analysis in lung cancer, especially in lung adenocarcinoma (LAD). METHODS: Three LAD and three corresponding NT tissues samples were used for eccDNA next-generation sequencing analysis, and an additional 20 were used for quantitative PCR (qPCR) evaluations. We further performed qPCR amplification using serum samples from LAD patients and healthy medical examiners. RESULTS: eccDNAs from LAD samples were mainly 200-1000 bp in length. Gene annotation analysis revealed that most eccDNAs were derived from chromosomes 1 and 2. The top-ten increased and top-ten decreased eccDNAs in LAD tissues were CircD-ARPC1B, CircD-ARPC1A, CircD-FAM49B, CircD-SDK1, CircD-KCNG1, CircD-POLR2F, CircD-SS18L1, CircD-SLC16A3, CircD-CSNK1D, CircD-KCTD1, and CircD-TMIGD2, CircD-PDIA5, CircD-VAV2, CircD-GATAD2A, CircD-CAB39L, CircD-KHDC1, CircD-FOXN3, CircD-SULT2B1, CircD-DPP9, and CircD-CSNK1D. qPCR demonstrated that the expression of CircD-DZRN3 was higher in LAD tissues than in normal lung tissues, whereas CircD-LGR6 and CircD-UMODL1 expression levels were lower in LAD than in normal lung tissues. Furthermore, the serum CircD-PDZRN3 level increased, while CircD-LGR6 decreased in LAD. Receiver operating characteristic (ROC) analysis showed that area under curve (AUC) of serum CircD-PDZRN3 (0.991), CircD-LGR6 (0.916) was higher than that of serum carcinoembryonic antigen (CEA) (0.825), CY211 (cytokeratin 19 fragment) (0.842), SCCA(squamous cell carcinoma antigen) (0.857) for the diagnosis of LAD. CONCLUSIONS: Our study first showed that several eccDNAs were aberrantly expressed in LAD, among which CircD-PDZRN3 and CircD-LGR6 clearly distinguished LAD patients from healthy controls, indicating their potential as biomarkers.

Serum creatinine and cystatin C-based diagnostic indices for sarcopenia in advanced non-small cell lung cancer.

BACKGROUND: Sarcopenia is an important prognostic factor of lung cancer. The serum creatinine/cystatin C ratio (CCR) and the sarcopenia index (SI, serum creatinine × cystatin C-based glomerular filtration rate) are novel screening tools for sarcopenia; however, the diagnostic accuracy of the CCR and SI for detecting sarcopenia remains unknown. We aimed to explore and validate the diagnostic values of the CCR and SI for determining sarcopenia in non-small cell lung cancer (NSCLC) and to explore their prognostic values for overall survival. METHODS: We conducted a prospective cohort study of adult patients with stage IIIB or IV NSCLC. Levels of serum creatinine and cystatin C were measured to calculate the CCR and SI. Sarcopenia was defined separately using CCR, SI, and the Asian Working Group for Sarcopenia (AWGS) 2019 criteria. Participants were randomly sampled into derivation and validation sets (6:4 ratio). The cutoff values for diagnosing sarcopenia were determined based on the derivation set. Diagnostic accuracy was analysed in the validation set through receiver operating characteristic (ROC) curves. Cox regression models and survival curves were applied to evaluate the impact of different sarcopenia definitions on survival. RESULTS: We included 579 participants (women, 35.4%; mean age, 58.4 ± 8.9 years); AWGS-defined sarcopenia was found in 19.5% of men and 10.7% of women. Both CCR and SI positively correlated with computed tomography-derived and bioimpedance-derived muscle mass and handgrip strength. The optimal cutoff values for CCR and SI were 0.623 and 54.335 in men and 0.600 and 51.742 in women, with areas under the ROC curves of 0.837 [95% confidence interval (CI): 0.770-0.904] and 0.833 (95% CI: 0.765-0.901) in men (P = 0.25), and 0.808 (95% CI: 0.682-0.935) and 0.796 (95% CI: 0.668-0.924) in women (P = 0.11), respectively. The CCR achieved sensitivities and specificities of 73.0% and 93.7% in men and 85.7% and 65.7% in women, respectively; the SI achieved sensitivities and specificities of 75.7% and 86.5% in men and 92.9% and 62.9% in women, respectively. CCR-defined, SI-defined, and AWGS-defined sarcopenia were independently associated with a high mortality risk [hazard ratio (HR) = 1.75, 95% CI: 1.25-2.44; HR = 1.55, 95% CI: 1.11-2.17; and HR = 1.76, 95% CI: 1.22-2.53, respectively]. CONCLUSIONS: CCR and SI have satisfactory and comparable diagnostic accuracy and prognostic values for sarcopenia in patients with advanced NSCLC. Both may serve as surrogate biomarkers for evaluating sarcopenia in these patients. However, further external validations are required.

Using biological information to analyze potential miRNA-mRNA regulatory networks in the plasma of patients with non-small cell lung cancer.

BACKGROUND: Lung cancer is the most common malignant tumor, and it has a high mortality rate. However, the study of miRNA-mRNA regulatory networks in the plasma of patients with non-small cell lung cancer (NSCLC) is insufficient. Therefore, this study explored the differential expression of mRNA and miRNA in the plasma of NSCLC patients. METHODS: The Gene Expression Omnibus (GEO) database was used to download microarray datasets, and the differentially expressed miRNAs (DEMs) were analyzed. We predicted transcription factors and target genes of the DEMs by using FunRich software and the TargetScanHuman database, respectively. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for GO annotation and KEGG enrichment analysis of downstream target genes. We constructed protein-protein interaction (PPI) and DEM-hub gene networks using the STRING database and Cytoscape software. The GSE20189 dataset was used to screen out the key hub gene. Using The Cancer Genome Atlas (TCGA) and UALCAN databases to analyze the expression and prognosis of the key hub gene and DEMs. Then, GSE17681 and GSE137140 datasets were used to validate DEMs expression. Finally, the receiver operating characteristic (ROC) curve was used to verify the ability of the DEMs to distinguish lung cancer patients from healthy patients. RESULTS: Four upregulated candidate DEMs (hsa-miR199a-5p, hsa-miR-186-5p, hsa-miR-328-3p, and hsa-let-7d-3p) were screened from 3 databases, and 6 upstream transcription factors and 2253 downstream target genes were predicted. These genes were mainly enriched in cancer pathways and PI3k-Akt pathways. Among the top 30 hub genes, the expression of KLHL3 was consistent with the GSE20189 dataset. Except for let-7d-3p, the expression of other DEMs and KLHL3 in tissues were consistent with those in plasma. LUSC patients with high let-7d-3p expression had poor overall survival rates (OS). External validation demonstrated that the expression of hsa-miR-199a-5p and hsa-miR-186-5p in peripheral blood of NSCLC patients was higher than the healthy controls. The ROC curve confirmed that the DEMs could better distinguish lung cancer patients from healthy people. CONCLUSION: The results showed that miR-199a-5p and miR-186-5p may be noninvasive diagnostic biomarkers for NSCLC patients. MiR-199a-5p-KLHL3 may be involved in the occurrence and development of NSCLC.

Serum RNAs can predict lung cancer up to 10 years prior to diagnosis.

Lung cancer (LC) prognosis is closely linked to the stage of disease when diagnosed. We investigated the biomarker potential of serum RNAs for the early detection of LC in smokers at different prediagnostic time intervals and histological subtypes. In total, 1061 samples from 925 individuals were analyzed. RNA sequencing with an average of 18 million reads per sample was performed. We generated machine learning models using normalized serum RNA levels and found that smokers later diagnosed with LC in 10 years can be robustly separated from healthy controls regardless of histology with an average area under the ROC curve (AUC) of 0.76 (95% CI, 0.68-0.83). Furthermore, the strongest models that took both time to diagnosis and histology into account successfully predicted non-small cell LC (NSCLC) between 6 and 8 years, with an AUC of 0.82 (95% CI, 0.76-0.88), and SCLC between 2 and 5 years, with an AUC of 0.89 (95% CI, 0.77-1.0), before diagnosis. The most important separators were microRNAs, miscellaneous RNAs, isomiRs, and tRNA-derived fragments. We have shown that LC can be detected years before diagnosis and manifestation of disease symptoms independently of histological subtype. However, the highest AUCs were achieved for specific subtypes and time intervals before diagnosis. The collection of models may therefore also predict the severity of cancer development and its histology. Our study demonstrates that serum RNAs can be promising prediagnostic biomarkers in an LC screening setting, from early detection to risk assessment.

Cathepsin F and Fibulin-1 as novel diagnostic biomarkers for brain metastasis of non-small cell lung cancer.

BACKGROUND: The lack of non-invasive methods for detection of early micro-metastasis is a major cause of the poor prognosis of non-small cell lung cancer (NSCLC) brain metastasis (BM) patients. Herein, we aimed to identify circulating biomarkers based on proteomics for the early diagnosis and monitoring of patients with NSCLC BM. METHODS: Upregulated proteins were detected by secretory proteomics in the animal-derived high brain metastatic lung cancer cell line. A well-designed study composed of three independent cohorts was then performed to verify these blood-based protein biomarkers: the serum discovery and verification cohorts (n = 80; n = 459), and the tissue verification cohort (n = 76). Logistic regression was used to develop a diagnostic biomarker panel. Model validation cohort (n = 160) was used to verify the stability of the constructed predictive model. Changes in serum Cathepsin F (CTSF) levels of patients were tracked to monitor the treatment response. Progression-free survival (PFS) and overall survival (OS) were analysed to assess their prognostic relevance. RESULTS: CTSF and Fibulin-1 (FBLN1) levels were specifically upregulated in sera and tissues of patients with NSCLC BM compared with NSCLC without BM and primary brain tumour. The combined diagnostic performance of CTSF and FBLN1 was superior to their individual ones. CTSF serum changes were found to reflect the therapeutic response of patients with NSCLC BM and the trends of progression were detected earlier than the magnetic resonance imaging changes. Elevated expression of CTSF in NSCLC BM tissues was associated with poor PFS, and was found to be an independent prognostic factor. CONCLUSIONS: We report a novel blood-based biomarker panel for early diagnosis, monitoring of therapeutic response, and prognostic evaluation of patients with NSCLC BM.

On-treatment blood TMB as predictors for camrelizumab plus chemotherapy in advanced lung squamous cell carcinoma: biomarker analysis of a phase III trial.

BACKGROUND: Camrelizumab plus chemotherapy significantly prolonged progression-free survival (PFS) and overall survival (OS) compared to chemotherapy alone as first-line treatment in advanced lung squamous cell carcinoma (LUSC) in the phase III trial (CameL-sq), which has become an option of standard-of-cares for Chinese patients with advanced LUSC. However, the predictive biomarkers remain unknown. METHODS: Tumor tissue samples at baseline, and peripheral blood samples at baseline (pretreatment) and after two cycles of treatment (on-treatment) were prospectively collected from 270 LUSC patients from the CameL-sq study. Blood tumor mutation burden (bTMB) and its dynamics were analyzed to explore their predictive values. RESULTS: Pretreatment bTMB was not associated with objective response, PFS and OS in camrelizumab or placebo plus chemotherapy groups. Low on-treatment bTMB was associated with significantly better objective response (73.8% vs 27.8%, P < 0.001), PFS (median, 9.1 vs 4.1 months; P < 0.001) and OS (median, not reached vs 8.0 months; P < 0.001) in camrelizumab plus chemotherapy group whereas it did not correlate with objective response and PFS in chemotherapy alone group. Importantly, on-treatment bTMB level could discriminate patients of initially radiological stable disease who would long-term benefit from camrelizumab plus chemotherapy (low vs high, median OS, 18.2 vs 7.8 months; P = 0.001). Combing on-treatment bTMB and its dynamics improved the ability for predicting the efficacy of camrelizumab plus chemotherapy. CONCLUSION: On-treatment bTMB together with its dynamics could serve as a predictive biomarker for camrelizumab plus chemotherapy in patients with advanced LUSC. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03668496.

A comprehensive profiling of soluble immune checkpoints from the sera of patients with non-small cell lung cancer.

BACKGROUND: Immunotherapy was widely used for the treatment of non-small cell lung cancer (NSCLC). However, whether inhibition of immune checkpoints individually or simultaneously could improve the therapeutic efficacy of NSCLC remains to be investigated. Here, we explored the aberrant levels of several checkpoints and evaluated their potential diagnostic values for NSCLC. METHODS: Serum samples of 89 NSCLC patients and 57 healthy donors were collected from Nanjing Drum Tower Hospital between November 2019 and July 2020. Fourteen human immune checkpoints were quantified by Procarta-Plex Human Immuno-Oncology Checkpoint Panel. RESULTS: The expression levels of sTIM-3, sCD137, sCD27, sLAG-3, sIDO, sPD-L2, sCD152, sCD80, and sPD-1 were all significantly increased in serum of NSCLC patients. Especially, sLAG-3 was significantly elevated in serum of NSCLC patients at early-stage (stages I and II), TIM-3, CD137, and CD27 were significantly higher in the advanced NSCLC patients (stages III and IV) than in the early-stage groups. Receiver operating characteristics (ROC) results showed that except for PD-1, all the other immune checkpoint proteins had potential diagnostic values for NSCLC. sTIM-3 had the highest diagnostic accuracy, followed by sLAG-3. Combining sTIM-3, sLAG-3, and sCD137 could increase the accuracy to a higher level. Moreover, sCD27 was correlated with NSCLC cancer type, age, sex, and disease stage, while sCD137 was correlated with age and disease stage. sTIM-3 and sIDO were correlated with stage and age, respectively. CONCLUSIONS: TIM-3 and LAG-3 were independent biomarkers for the early diagnosis of NSCLC. The combination of TIM-3, LAG-3, and CD137 could increase the diagnostic accuracy.

Inflammation-scores as prognostic markers of overall survival in lung cancer: a register-based study of 6,210 Danish lung cancer patients.

BACKGROUND: Inflammation-scores based on general inflammation markers are suggested as prognostic markers of overall survival (OS) in lung cancer. However, whether these inflammation-scores improves the prognostication performed by well-established prognostic markers is unsettled. In a large register-based lung cancer patient cohort, nine different inflammation-scores were compared, and their ability to optimize the prognostication of OS was evaluated. METHODS: Lung cancer patients diagnosed from 2009-2018 in The Central Denmark Region were identified in the Danish Lung Cancer Registry. Pre-treatment inflammation markers were extracted from the clinical laboratory information system. Prognostication of OS was evaluated by Cox proportional hazard models. Comparison of the inflammation-scores and their added value to established prognostic markers were assessed by Akaike's information criteria and Harrel's C-index. RESULTS: In total, 5,320 patients with non-small cell lung cancer (NSCLC) and 890 patients with small cell lung cancer (SCLC) were identified. In NSCLC, the Aarhus composite biomarker score (ACBS), including albumin, C-reactive protein, neutrophil count, lymphocyte count and haemoglobin, and the neutrophil-lymphocyte-ratio (NLR) were superior. Furthermore, they improved the prognostication of OS significantly (p <0.0001) (ACBS: HR: 2.24 (95%CI: 1.97-2.54); NLR: HR: 1.58 (95%CI: 1.47 - 1.69)). In SCLC, three scores were equally superior and improved the prognostication of OS p < 0.0001): neutrophil-lymphocyte-ratio (HR:1.62 (95%CI: 1.38-1.90)), modified Glasgow Prognostic Score (mGPS) (HR:1.70 (95%CI: 1.55-1.86) and the Combined NLR and GPS (CNG) (HR:2.10 (95%CI: 1.77-2.49). CONCLUSIONS: The ACBS was the optimal score in NSCLC, whereas neutrophil-lymphocyte-ratio, mGPS and CNG were equally superior in SCLC. Additionally, these inflammation-scores all optimised the prognostication of OS and added value to well-established prognostic markers.

Circulating Tumor DNA Minimal Residual Disease Detection of Non-Small-Cell Lung Cancer Treated With Curative Intent.

Circulating tumor DNA (ctDNA) minimal residual disease (MRD) is a powerful biomarker with the potential to improve survival outcomes for non-small-cell lung cancer (NSCLC). Multiple groups have shown the ability to detect MRD following curative-intent NSCLC treatment using next-generation sequencing-based assays of plasma cell-free DNA. These studies have been modest in size, largely retrospective, and without thorough prospective clinical validation. Still, when restricting measurement to the first post-treatment timepoint to assess the clinical performance of ctDNA MRD detection, they have demonstrated sensitivity for predicting disease relapse ranging between 36% and 100%, and specificity ranging between 71% and 100%. When considering all post-treatment follow-up timepoints (surveillance), including those beyond the initial post-treatment measurement, these assays' performances improve with sensitivity and specificity for identifying relapse ranging from 82% to 100% and 70% to 100%, respectively. In this manuscript, we review the evidence available to date regarding ctDNA MRD detection in patients with NSCLC undergoing curative-intent treatment and the ongoing prospective studies involving ctDNA MRD detection in this patient population.

Deep Learning-Based Chest CT Image Features in Diagnosis of Lung Cancer.

This study was to evaluate the diagnostic value of deep learning-optimized chest CT in the patients with lung cancer. 90 patients who were diagnosed with lung cancer by surgery or puncture in hospital were selected as the research subjects. The Mask Region Convolutional Neural Network (Mask-RCNN) model was a typical end-to-end image segmentation model, and Dual Path Network (DPN) was used in nodule detection. The results showed that the accuracy of DPN algorithm model in detecting lung lesions in lung cancer patients was 88.74%, the accuracy of CT diagnosis of lung cancer was 88.37%, the sensitivity was 82.91%, and the specificity was 87.43%. Deep learning-based CT examination combined with serum tumor detection, factoring into Neurospecific enolase (N S E), cytokeratin 19 fragment (CYFRA21), Carcinoembryonic antigen (CEA), and squamous cell carcinoma (SCC) antigen, improved the accuracy to 97.94%, the sensitivity to 98.12%, and the specificity to 100%, all showing significant differences (P < 0.05). In conclusion, this study provides a scientific basis for improving the diagnostic efficiency of CT imaging in lung cancer and theoretical support for subsequent lung cancer diagnosis and treatment.

Perioperative circulating tumor DNA as a potential prognostic marker for operable stage I to IIIA non-small cell lung cancer.

BACKGROUND: Circulating tumor DNA (ctDNA) has emerged as a noninvasive biomarker for dynamically monitoring tumors. However, published data on perioperative ctDNA in patients with operable non-small cell lung cancer (NSCLC) are currently limited. METHODS: This prospective study recruited 123 patients with resectable stage I to IIIA NSCLC. Preoperative and postoperative plasma samples and tumor tissue samples were subjected to next-generation sequencing with a panel of 425 cancer-related genes. Peripheral blood samples were collected before surgery, postoperatively within 1 month, and every 3 to 6 months for up to 3 years. RESULTS: After 4 exclusions, 119 eligible patients were enrolled from June 2016 to February 2019. Presurgical ctDNA was detectable in 29 of 117 patients (24.8%) and was associated with inferior recurrence-free survival (RFS; hazard ratio [HR], 2.42; 95% CI, 1.11-5.27; P = .022) and inferior overall survival (OS; HR, 5.54; 95% CI, 1.01-30.35; P = .026). Similarly, ctDNA was detected in 12 of 116 first postsurgical samples (10.3%) and was associated with shorter RFS (HR, 3.04; 95% CI, 1.22-7.58; P = .012). During surveillance after surgery, longitudinal ctDNA-positive patients (37 of 119; 31.1%) had significantly shorter RFS (HR, 3.46; 95% CI, 1.59-7.55; P < .001) and significantly shorter OS (HR, 9.99; 95% CI, 1.17-85.78; P = .010) in comparison with longitudinal ctDNA-negative patients. Serial ctDNA detection preceded radiologic disease recurrence by a median lead time of 8.71 months. CONCLUSIONS: These results suggest that perioperative ctDNA analyses can predict recurrence and survival, and serial ctDNA analyses can identify disease recurrence/metastasis earlier than routine radiologic imaging in patients with resectable NSCLC. LAY SUMMARY: The utility of serial circulating tumor DNA (ctDNA) monitoring for predicting disease recurrence and survival for early-stage non-small cell lung cancer (NSCLC) has not been well characterized. The detection of ctDNA before and after surgery is associated with the identification of a high risk of disease recurrence and long-term patient outcomes for resectable NSCLC. Perioperative ctDNA analyses identify disease recurrence earlier than routine radiologic imaging. ctDNA analyses can detect minimal residual disease for resectable NSCLC and thus can facilitate early intervention.