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.

Aspartate Transaminase-to-Albumin Ratio (ATAR), a Novel Prognostic Index, Predicts Outcomes in Patients with Small-Cell Lung Cancer.

BACKGROUND: Small cell lung cancer (SCLC) is characterized by high invasion rates, rapid progression, and poor prognoses. Thus, identifying SCLC patients at high risk of progression and death is critical to improve long-term survival. In this study, the aspartate transaminase-to-albumin ratio (ATAR) was examined as a prognostic factor for SCLC patients. METHODS: We screened 196 SCLC patients from December 2013 to September 2022 at the Sichuan Cancer Hospital. The data was collected from patients' medical information as well as from their blood results during diagnosis. Using the Youden index as a cutoff value, patients were divided into high-risk（> 0.54) and low-risk (≤ 0.54) ATAR groups. We analyzed the prognostic factors for overall survival (OS) using the Kaplan-Meier method, univariate and multivariate analyses, Cox regression, and the C-index. RESULTS: There were 109 (55.6%) smokers among the patients, and the median OS was 17.55 months. The Kaplan-Meier analysis indicated that patients with high-risk ATAR had significantly lower OS (p < 0.0001). A multivariate analysis demonstrated that elevated ATAR is an independent adverse predictor of OS (p < 0.001, HR = 1.907). Our study found that ATAR is an independent predictor of survival outcomes in SCLC, which was superior to ALB, PNI, and SII in predicting outcomes in low-risk and high-risk groups (all p < 0.05). Models combining ATAR with ALB, PNI, and SII showed more powerful prognostic value than their corresponding original models. Moreover, the prognostic indicator ATAR can significantly stratify stage I - II and III - IV SCLC patients (p ＜ 0.05). CONCLUSIONS: Peripheral blood ATAR prognostic index can be used as an independent predictor of SCLC patients before treatment.

Exosome-transported circ_0061407 and circ_0008103 play a tumour-repressive role and show diagnostic value in non-small-cell lung cancer.

BACKGROUND: Circular RNAs (circRNAs), one of the major contents of exosomes, have been shown to participate in the occurrence and progression of cancers. The role and the diagnostic potential of exosome-transported circRNAs in non-small-cell lung cancer (NSCLC) remain largely unknown. METHODS: The NSCLC-associated exosomal circ_0061407 and circ_0008103 were screened by circRNA microarray. The role of circ_0061407 and circ_0008103 in NSCLC was examined in vitro and in vivo. The encapsulation of the two circRNAs into exosomes and the transport to recipient cells were observed by confocal microscopy. The effects of exosome-transported circ_0061407 and circ_0008103 on recipient cells were investigated using a co-culture device. Bioinformatics analyses were performed to predict the mechanisms by which circ_0061407 and circ_0008103 affected NSCLC. The quantitative polymerase chain reaction was used to quantify the exosome-containing circ_0061407 and circ_0008103 in the serum samples of healthy, pneumonia, benign lung tumours, and NSCLC. The diagnostic efficacy was evaluated using receiver operating characteristic curves. RESULTS: The levels of circ_0061407 and circ_0008103 within exosomes were down-regulated in the serum of patients with NSCLC. The up-regulation of circ_0061407 and circ_0008103 inhibited the proliferation, migration/invasion, cloning formation of NSCLC cells in vitro and inhibited lung tumour growth in vivo. Circ_0061407 and circ_0008103 were observed to be packaged in exosomes and transported to recipient cells, where they inhibited the proliferation, migration/invasion, and cloning formation abilities of the recipient cells. Moreover, circ_0061407 and circ_0008103 might be involved in the progression of NSCLC by interacting with microRNAs and proteins. Additionally, lower serum exosomal circ_0061407 and circ_0008103 levels were associated with advanced pathological staging and distant metastasis. CONCLUSIONS: This study identified two novel exosome-transported circRNAs (circ_0061407 and circ_0008103) associated with NSCLC. These findings may provide additional insights into the development of NSCLC and potential diagnostic biomarkers for NSCLC.

[Earlier detection of lung cancer through analysis of circulating tumor DNA from blood]. / Tidigare upptäckt av lungcancer med analys av tumör-DNA i blod.

To investigate the  clinical use of analyzing circulating tumor DNA in a clinical setting we present a pilot study comprising 93 patients from individuals with suspected lung cancer. The study aimed to evaluate the capability of analyzing circulating tumor DNA at the initial medical visit in order to detect genetic changes and mutations associated with lung cancer in plasma samples. Tumor DNA from plasma was extracted and analyzed with Next Generation Sequencing (NGS) and the result was compared with a matched tumor tissue collected in close connection from the same individual. Cancer-associated genetic mutations could be confirmed in about 60 percent of the plasma samples, and we observed a higher degree of conformance in patients with a more advanced disease. The results from the study provide valuable insights for an early clinical use of analyzing circulating tumor DNA in cases of suspected lung cancer, which could contribute to improving early diagnosis and treatment strategies for patients with lung cancer.

Integration of clinical phenoms and metabolomics facilitates precision medicine for lung cancer.

Lung cancer is a common malignancy that is frequently associated with systemic metabolic disorders. Early detection is pivotal to survival improvement. Although blood biomarkers have been used in its early diagnosis, missed diagnosis and misdiagnosis still exist due to the heterogeneity of lung cancer. Integration of multiple biomarkers or trans-omics results can improve the accuracy and reliability for lung cancer diagnosis. As metabolic reprogramming is a hallmark of lung cancer, metabolites, specifically lipids might be useful for lung cancer detection, yet systematic characterizations of metabolites in lung cancer are still incipient. The present study profiled the polar metabolome and lipidome in the plasma of lung cancer patients to construct an inclusive metabolomic atlas of lung cancer. A comprehensive analysis of lung cancer was also conducted combining metabolomics with clinical phenotypes. Furthermore, the differences in plasma lipid metabolites were compared and analyzed among different lung cancer subtypes. Alcohols, amides, and peptide metabolites were significantly increased in lung cancer, while carboxylic acids, hydrocarbons, and fatty acids were remarkably decreased. Lipid profiling revealed a significant increase in plasma levels of CER, PE, SM, and TAG in individuals with lung cancer as compared to those in healthy controls. Correlation analysis confirmed the association between a panel of metabolites and TAGs. Clinical trans-omics studies elucidated the complex correlations between lipidomic data and clinical phenotypes. The present study emphasized the clinical importance of lipidomics in lung cancer, which involves the correlation between metabolites and the expressions of other omics, ultimately influencing clinical phenotypes. This novel trans-omics network approach would facilitate the development of precision therapy for lung cancer.

[Effect of peripheral blood inflammatory indicators on the efficacy of immunotherapy in patients with advanced non-small cell lung cancer and chronic obstructive pulmonary disease].

Objective: To investigate the impact of peripheral blood inflammatory indicators on the efficacy of immunotherapy in patients with advanced non-small cell lung cancer (NSCLC) complicated with chronic obstructive pulmonary disease (COPD). Methods: A retrospective cohort study was performed to include 178 patients with Ⅲ-Ⅳ NSCLC complicated with COPD who received at least 2 times of immunotherapy in Xinqiao Hospital of the Army Medical University from January 2019 to August 2021. Baseline peripheral blood inflammatory indicators such as interleukin-6 (IL-6), interleukin-8 (IL-8), tumor necrosis factor-α (TNF-α) were collected within 2 weeks before the first treatment, with the last one being on or before February 7, 2022. X-tile software was used to determine the optimal cut-off value of peripheral blood inflammatory indicators. The Cox multivariate regression models were used to analyze the factors affecting progression free survival (PFS) and overall survival (OS). Results: Among the 178 patients, there were 174 males (97.8%) and 4 females (2.2%); the age ranged from 42 to 86 (64.3±8.3) years old.There were 30 cases (16.9%) of immunotherapy monotherapy, 114 cases (64.0%) of immunotherapy combined with chemotherapy, 21 cases (11.8%) of immunotherapy combined with antivascular therapy, and 13 cases (7.3%) of immunotherapy combined with radiotherapy. The median follow-up period was 14.5 months (95%CI: 13.6-15.3 months). The objective response rate (ORR) and disease control rate (DCR) were 44.9% (80/178) and 90.4% (161/178) for the whole group, the median PFS was 14.6 months (95%CI: 11.6-17.6 months), and the median OS was 25.7 months (95%CI: 18.0-33.4 months). The results of Cox multivariate analysis showed that IL-6>9.9 ng/L (HR=5.885, 95%CI: 2.558-13.543, P<0.01), TNF-α>8.8 ng/L (HR=3.213, 95%CI: 1.468-7.032, P=0.003), IL-8>202 ng/L (HR=2.614, 95%CI: 1.054-6.482, P=0.038), systemic immune inflammatory index (SII)>2 003.95 (HR=2.976, 95%CI: 1.647-5.379, P<0.001) were risk factors for PFS, and advanced lung cancer inflammation index (ALI)>171.15 was protective factor for PFS (HR=0.545, 95%CI: 0.344-0.863, P=0.010). IL-6>9.9 ng/L(HR=6.124, 95%CI: 1.950-19.228, P<0.002), lactate dehydrogenase (LDH)>190.7 U/L (HR=2.776, 95%CI: 1.020-7.556, P=0.046), SII>2 003.95 (HR=4.521, 95%CI: 2.241-9.120, P<0.001) were risk factors for OS, and ALI>171.15 was a protective factor for OS (HR=0.434, 95%CI: 0.243-0.778, P=0.005). Conclusion: Baseline high levels of IL-6, TNF-α, IL-8, SII, LDH, and low levels of ALI are risk factors for poor prognosis in patients with advanced NSCLC-COPD receiving immunotherapy.

Human epididymal protein 4 and its combined detection show good diagnostic value in lung cancer: A retrospective study.

OBJECTIVES: This study aimed to assess the diagnostic value of human epididymal protein 4 (HE4), a potential novel biomarker for lung cancer, and its combined detection with five other conventional biomarkers in lung cancer diagnosis and subtyping. METHODS: In this retrospective study, 115 lung cancer patients, 50 patients with benign pulmonary disease, and 50 healthy controls were included. Serum HE4, progastrin-releasing peptide (ProGRP), squamous cell carcinoma (SCC) antigen, cytokeratin-19 fragment (CYFRA21-1), neuron-specific enolase (NSE), and carcinoembryonic antigen (CEA) were analyzed using the electrochemiluminescence immunoassay and chemiluminescence immunoassay. The receiver operating characteristic curve was performed to analyze the diagnostic efficacy of individual biomarkers in identifying both lung cancer and its histologic subtypes. RESULTS: All six biomarkers showed significantly elevated levels in the lung cancer group compared to both benign pulmonary disease and control groups (P < 0.05). Among the biomarkers evaluated, HE4 exhibited the highest diagnostic performance for lung cancer, lung adenocarcinoma, and lung squamous cell carcinoma with area under the curve (AUC) values of 0.921, 0.891, and 0.937, respectively. ProGRP was the optimal biomarker for small cell lung cancer with an AUC of 0.973. The combination of all six biomarkers yielded the largest AUCs in the diagnosis of lung cancer subtypes (0.937 for lung adenocarcinoma, 0.998 for lung squamous cell carcinoma, and 0.985 for small cell lung cancer). Furthermore, specific combinations, such as HE4 + CEA, HE4 + SCC, and ProGRP + HE4 + NSE, showed strong diagnostic performance in lung cancer. CONCLUSIONS: HE4 and its combined detection held substantial clinical significance in the diagnosis of lung cancer and its histologic subtyping, especially for lung adenocarcinoma and lung squamous cell carcinoma.

Genetic and phenotypic profiling of single living circulating tumor cells from patients with microfluidics.

Accurate prediction of the efficacy of immunotherapy for cancer patients through the characterization of both genetic and phenotypic heterogeneity in individual patient cells holds great promise in informing targeted treatments, and ultimately in improving care pathways and clinical outcomes. Here, we describe the nanoplatform for interrogating living cell host-gene and (micro-)environment (NICHE) relationships, that integrates micro- and nanofluidics to enable highly efficient capture of circulating tumor cells (CTCs) from blood samples. The platform uses a unique nanopore-enhanced electrodelivery system that efficiently and rapidly integrates stable multichannel fluorescence probes into living CTCs for in situ quantification of target gene expression, while on-chip coculturing of CTCs with immune cells allows for the real-time correlative quantification of their phenotypic heterogeneities in response to immune checkpoint inhibitors (ICI). The NICHE microfluidic device provides a unique ability to perform both gene expression and phenotypic analysis on the same single cells in situ, allowing us to generate a predictive index for screening patients who could benefit from ICI. This index, which simultaneously integrates the heterogeneity of single cellular responses for both gene expression and phenotype, was validated by clinically tracing 80 non-small cell lung cancer patients, demonstrating significantly higher AUC (area under the curve) (0.906) than current clinical reference for immunotherapy prediction.

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.

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.

Label-Free Multiplex Profiling of Exosomal Proteins with a Deep Learning-Driven 3D Surround-Enhancing SERS Platform for Early Cancer Diagnosis.

Identification of protein profiling on plasma exosomes by SERS can be a promising strategy for early cancer diagnosis. However, it is still challenging to detect multiple exosomal proteins simultaneously by SERS since the Raman signals of exosomes detected by conventional colloidal nanocrystals or two-dimensional SERS substrates are incomplete and complex. Herein, we develop a novel three-dimensional (3D) surround-enhancing SERS platform, named 3D se-SERS, for the multiplex detection of exosomal proteins. In this 3D se-SERS, proteins and exosomes are covered with "hotspots" generated by the gold nanoparticles, which surround the analytes densely and three-dimensionally, providing sensitive and comprehensive SERS signals. Combining this 3D se-SERS with a deep learning model, we successfully quantitatively profiled seven proteins including CD63, CD81, CD9, CD151, CD171, TSPAN8, and PD-L1 on the surface of plasma exosomes from patients, which can predict the occurrence and advancement of lung cancer. This 3D se-SERS integrating deep learning technique benefits from high sensitivity and significant multiplexing ability for comprehensive analysis of proteins and exosomes, demonstrating the potential of deep learning-driven 3D se-SERS technology for plasma exosome-based early cancer diagnosis.

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.

Personalized, tumor-informed, circulating tumor DNA assay for detecting minimal residual disease in non-small cell lung cancer patients receiving curative treatments.

BACKGROUND: Circulating tumor DNA (ctDNA) has emerged as a prognostic and predictive biomarker for detection of minimal residual disease (MRD), monitoring treatment response, and early detection of recurrence in cancer patients. In this study, we explored the utility of ctDNA-based MRD detection to predict recurrence in a real-world cohort of primarily early-stage non-small cell lung cancer (NSCLC) patients treated with curative intent. METHODS: Longitudinal plasma samples were collected post curative-intent treatment from 36 patients with stage I-IV NSCLC. A personalized, tumor-informed assay was used to detect and quantify ctDNA in plasma samples. RESULTS: Of the 24 patients with plasma samples available during the MRD window (within 6 months of curative surgery and before adjuvant therapy), ctDNA was detectable in two patients. Patients with ctDNA-positivity during the MRD window were 15 times more likely to recur compared to ctDNA-negative patients (HR: 15.0, 95% CI: 1.0-253.0, p = 0.010). At any time post-curative intent treatment, ctDNA-positivity was associated with significantly poorer recurrence-free survival compared to persistently ctDNA-negative patients (p < 0.0001). CONCLUSION: Our real-world data indicate that longitudinal, personalized, tumor-informed ctDNA monitoring is a valuable tool in patients with NSCLC receiving curative treatment to identify patients at high risk for recurrence.

Digital Circulating Tumor Cells Quantification.

Circulating tumor cells (CTCs) are an emerging but vital biomarker for cancer management. An efficient methodology for accurately quantifying CTCs remains challenging due to their rareness. Here, we develop a digital CTC detection strategy using partitioning instead of enrichment to quantify CTCs. By utilizing the characteristics of droplet microfluidics that can rapidly generate a large number of parallel independent reactors, combined with Poisson distribution, we realize the quantification of CTCs in the blood directly. The limit of detection of our digital CTCs quantification assay is five cells per 5 mL of whole blood. By simultaneously detecting multiple genetic mutations, our approach achieves highly sensitive and specific detection of CTCs in peripheral blood from NSCLC patients (AUC = 1). Our digital platform offers a potential approach and strategy for the quantification of CTCs, which could contribute to the advancement of cancer medical management.

Prognostic utility of blood inflammation biomarkers before and after treatment on the survival of patients with locally advanced non-small cell lung cancer undergoing stereotactic body radiotherapy.

BACKGROUND AND OBJECTIVE: The neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) were significant and succinct indicators of systemic inflammation. We assessed the influence of stereotactic body radiotherapy (SBRT) on NLR and PLR in patients with locally advanced non-small cell lung cancer (LA-NSCLC). METHODS: We reviewed the medical data of patients with LA-NSCLC who underwent SBRT between 1 January 2013 and 31 December 2018. NLR and PLR values recorded at pre- and post-SBRT were examined. We assessed the correlation between pre/post-SBRT NLR and PLR and survival outcomes. The decision tree evaluation was conducted using Chi-square automatic detection. RESULTS: In total, 213 patients were included in the study with a median follow-up duration of 40.00 (ranging from 5.28 to 100.70) months. Upon dichotomization by a median, we identified that post-SBRT NLR > 5.5 and post-SBRT PLR > 382.0 were negatively associated with shorter overall survival (OS). In the multivariate assessment, post-SBRT PLR > 382.0 was the only factor. Based on post-SBRT PLR, tumor locations, and tumor stage, we categorized patients into low, medium, or high-risk groups. CONCLUSIONS: Post-SBRT PLR > 382.0 correlated with survival in patients undergoing SBRT. The decision tree model might play a role in future risk stratification to guide the clinical practice of individualized SBRT for LA-NSCLC.

Circulating biomarkers as predictors of response to immune checkpoint inhibitors in NSCLC: Are we on the right path?

Immune checkpoints inhibitors (ICIs) have markedly improved the therapeutic management of advanced NSCLC and, more recently, they have demonstrated efficacy also in the early-stage disease. Despite better survival outcomes with ICIs compared to standard chemotherapy, a large proportion of patients can derive limited clinical benefit from these agents. So far, few predictive biomarkers, including the programmed death-ligand 1 (PD-L1), have been introduced in clinical practice. Therefore, there is an urgent need to identify novel biomarkers to select patients for immunotherapy, to improve efficacy and avoid unnecessary toxicity. A deeper understanding of the mechanisms involved in antitumor immunity and advances in the field of liquid biopsy have led to the identification of a wide range of circulating biomarkers that could potentially predict response to immunotherapy. Herein, we provide an updated overview of these circulating biomarkers, focusing on emerging data from clinical studies and describing modern technologies used for their detection.

Novel Blood Biomarkers for Response Prediction and Monitoring of Stereotactic Ablative Radiotherapy and Immunotherapy in Metastatic Oligoprogressive Lung Cancer.

Up to 80% of patients under immune checkpoint inhibitors (ICI) face resistance. In this context, stereotactic ablative radiotherapy (SABR) can induce an immune or abscopal response. However, its molecular determinants remain unknown. We present early results of a translational study assessing biomarkers of response to combined ICI and SABR (I-SABR) in liquid biopsy from oligoprogressive patients in a prospective observational multicenter study. Cohort A includes metastatic patients in oligoprogression to ICI maintaining the same ICI due to clinical benefit and who receive concomitant SABR. B is a comparative group of oligometastatic patients receiving only SABR. Blood samples are extracted at baseline (T1), after the first (T2) and last (T3) fraction, two months post-SABR (T4) and at further progression (TP). Response is evaluated by iRECIST and defined by the objective response rate (ORR)-complete and partial responses. We assess peripheral blood mononuclear cells (PBMCs), circulating cell-free DNA (cfDNA) and small RNA from extracellular vesicles. Twenty-seven patients could be analyzed (cohort A: n = 19; B: n = 8). Most were males with non-small cell lung cancer and one progressing lesion. With a median follow-up of 6 months, the last ORR was 63% (26% complete and 37% partial response). A decrease in cfDNA from T2 to T3 correlated with a good response. At T2, CD8+PD1+ and CD8+PDL1+ cells were increased in non-responders and responders, respectively. At T2, 27 microRNAs were differentially expressed. These are potential biomarkers of response to I-SABR in oligoprogressive disease.

Red blood cells function as reservoirs of tumor DNA.

Novel screening techniques for early detection of lung cancer are urgently needed. Profiling circulating tumor cell-free DNA (ctDNA) has emerged as a promising tool for biopsy-free tumor genotyping. However, both the scarcity and short half-life of ctDNA substantially limit the sensitivity and clinical utility of ctDNA detection methodologies. Our discovery that red blood cells (RBCs) sequester mitochondrial DNA opens a new avenue for detecting circulating nucleic acids, as RBCs represent an unrecognized reservoir of circulating nucleic acid. Here, we show that RBCs acquire tumor DNA following coculture with lung cancer cell lines harboring Kirsten rat sarcoma viral oncogene homolog (KRAS) and epidermal growth factor receptor (EGFR) mutations. RBC-bound tumor DNA is detectable in patients with early-stage non-small cell lung cancer (NSCLC) but not in healthy controls by qPCR. Our results collectively uncover a previously unrecognized yet easily accessible reservoir of tumor DNA, offering a promising foundation for future RBC-based tumor diagnostics.NEW & NOTEWORTHY We present a novel method for lung cancer detection by revealing RBCs as a reservoir for tumor DNA, overcoming the limitations of current circulating tumor ctDNA methodologies. By demonstrating that RBCs can capture tumor DNA, including critical mutations found in lung cancer, we provide a promising, biopsy-free avenue for early cancer diagnostics. This discovery opens up exciting possibilities for developing RBC-based diagnostic tools, significantly enhancing the sensitivity and clinical utility of noninvasive cancer detection.

Application of a nomogram from coagulation-related biomarkers and C1q and total bile acids in distinguishing advanced and early-stage lung cancer.

BACKGROUND: This study aimed to establish a nomogram to distinguish advanced- and early-stage lung cancer based on coagulation-related biomarkers and liver-related biomarkers. METHODS: A total of 306 patients with lung cancer and 172 patients with benign pulmonary disease were enrolled. Subgroup analyses based on histologic type, clinical stage, and neoplasm metastasis status were carried out and multivariable logistic regression analysis was applied. Furthermore, a nomogram model was developed and validated with bootstrap resampling. RESULTS: The concentrations of complement C1q, fibrinogen, and D-dimers, fibronectin, inorganic phosphate, and prealbumin were significantly changed in lung cancer patients compared to benign pulmonary disease patients. Multiple regression analysis based on subgroup analysis of clinical stage showed that compared with early-stage lung cancer, female (P < 0.001), asymptomatic admission (P = 0.001), and total bile acids (P = 0.011) were negatively related to advanced lung cancer, while C1q (P = 0.038), fibrinogen (P < 0.001), and D-dimers (P = 0.001) were positively related. A nomogram model based on gender, symptom, and the levels of total bile acids, C1q, fibrinogen, and D-dimers was constructed for distinguishing advanced lung cancer and early-stage lung cancer, with an area under the receiver operating characteristic curve of 0.919. The calibration curve for this nomogram revealed good predictive accuracy (P-Hosmer-Lemeshow = 0.697) between the predicted probability and the actual probability. CONCLUSIONS: We developed a nomogram based on gender, symptom, and the levels of fibrinogen, D-dimers, total bile acids, and C1q that can individually distinguish early- and advanced-stage lung cancer.

Detection of circulating tumor DNA with ultradeep sequencing of plasma cell-free DNA for monitoring minimal residual disease and early detection of recurrence in early-stage lung cancer.

BACKGROUND: In early-stage non-small cell lung cancer (NSCLC), recurrence is frequently observed. Circulating tumor DNA (ctDNA) has emerged as a noninvasive tool to risk stratify patients for recurrence after curative intent therapy. This study aimed to risk stratify patients with early-stage NSCLC via a personalized, tumor-informed multiplex polymerase chain reaction (mPCR) next-generation sequencing assay. METHODS: This retrospective cohort study included patients with stage I-III NSCLC. Recruited patients received standard-of-care management (surgical resection with or without adjuvant chemotherapy, followed by surveillance). Whole-exome sequencing of NSCLC resected tissue and matched germline DNA was used to design patient-specific mPCR assays (Signatera, Natera, Inc) to track up to 16 single-nucleotide variants in plasma samples. RESULTS: The overall cohort with analyzed plasma samples consisted of 57 patients. Stage distribution was 68% for stage I and 16% each for stages II and III. Presurgery (i.e., at baseline), ctDNA was detected in 15 of 57 patients (26%). ctDNA detection presurgery was significantly associated with shorter recurrence-free survival (RFS; hazard ratio [HR], 3.54; 95% confidence interval [CI], 1.00-12.62; p = .009). In the postsurgery setting, ctDNA was detected in seven patients, of whom 100% experienced radiological recurrence. ctDNA positivity preceded radiological findings by a median lead time of 2.8 months (range, 0-12.9 months). Longitudinally, ctDNA detection at any time point was associated with shorter RFS (HR, 16.1; 95% CI, 1.63-158.9; p < .0001). CONCLUSIONS: ctDNA detection before surgical resection was strongly associated with a high risk of relapse in early-stage NSCLC in a large unique Asian cohort. Prospective studies are needed to assess the clinical utility of ctDNA status in this setting.