Circulating Tumor Cells as a Predictive Biomarker in Resectable Lung Cancer: A Systematic Review and Meta-Analysis

The impact of vascular division sequence and epithelial-mesenchymal transition status on postoperative recurrence in lung adenocarcinoma

BACKGROUND

The vascular division sequence in video-assisted thoracic surgery (VATS) lung resection is usually determined by the handling difficulty due to the limited surgical view through the scope. However, upfront pulmonary vein division is theoretically desirable to avoid tumor cells spreading by surgical manipulation. Epithelial-mesenchymal transition (EMT) is associated with poor prognosis and an increased number of circulating tumor cells. The purpose of this study is to evaluate the effect of vascular division sequence and EMT on postoperative recurrence.

METHODS

We retrospectively investigated tissue microarrays of 282 lung adenocarcinomas surgically resected between 2001 and 2007. We excluded the cases with segmentectomy, wedge resection, dissemination, insufficient material for staining, or lack of medical records. The effect of vascular division sequence and clinicopathologic factors on recurrence was evaluated in 195 cases.

RESULTS

The upfront pulmonary vein division (V-first) was performed in 60 patients, and the upfront pulmonary artery division (A-first) was performed in 135 patients. The recurrence was observed in 67 patients (13 in V-first and 54 in A-first). Epithelial-mesenchymal transition activation was observed in 104 patients. Multivariable analysis with 195 patients revealed that lymph node metastasis and pleural invasion were risk factors for the recurrence. The stratified multivariable analysis showed that vascular division sequence (A-first) was a risk factor only in the EMT-negative group (91 patients). In the EMT-negative subset, the 5-year relapse-free survival rate was significantly lower in the A-first group than the V-first group (72.6% vs. 92.2%, p  =  0.0136).

CONCLUSIONS

The upfront pulmonary artery division might be a risk factor in patients without EMT activation.

A real-world clinicopathological model for predicting pathological complete response to neoadjuvant chemotherapy in breast cancer

Purpose

This study aimed to develop and validate a clinicopathological model to predict pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer patients and identify key prognostic factors.

Methods

This retrospective study analyzed data from 279 breast cancer patients who received NAC at Zhejiang Provincial People's Hospital from 2011 to 2021. Additionally, an external validation dataset, comprising 50 patients from Lanxi People's Hospital and Second Affiliated Hospital, Zhejiang University School of Medicine from 2022 to 2023 was utilized for model verification. A multivariate logistic regression model was established incorporating clinical, ultrasound features, circulating tumor cells (CTCs), and pathology variables at baseline and post-NAC. Model performance for predicting pCR was evaluated. Prognostic factors were identified using survival analysis.

Results

In the 279 patients enrolled, a pathologic complete response (pCR) rate of 27.96% (78 out of 279) was achieved. The predictive model incorporated independent predictors such as stromal tumor-infiltrating lymphocyte (sTIL) levels, Ki-67 expression, molecular subtype, and ultrasound echo features. The model demonstrated strong predictive accuracy for pCR (C-statistics/AUC 0.874), especially in human epidermal growth factor receptor 2 (HER2)-enriched (C-statistics/AUC 0.878) and triple-negative (C-statistics/AUC 0.870) subtypes, and the model performed well in external validation data set (C-statistics/AUC 0.836). Incorporating circulating tumor cell (CTC) changes post-NAC and tumor size changes further improved predictive performance (C-statistics/AUC 0.945) in the CTC detection subgroup. Key prognostic factors included tumor size >5cm, lymph node metastasis, sTIL levels, estrogen receptor (ER) status and pCR. Despite varied pCR rates, overall prognosis after standard systemic therapy was consistent across molecular subtypes.

Conclusion

The developed predictive model showcases robust performance in forecasting pCR in NAC-treated breast cancer patients, marking a step toward more personalized therapeutic strategies in breast cancer.

The use of minimal residual disease in thoracic oncology: Gaps between promises and the on-the-ground reality of daily practice

The assessment of minimal residual disease (MRD) from blood samples of patients with resected non-small cell lung carcinoma (NSCLC) is promising and opens up many opportunities for the optimisation of patient care in daily practice. Notably, this includes the potential for escalation or de-escalation of adjuvant therapies. Thus, the evaluation of MRD status can directly contribute to an increase in the overall survival of early stage NSCLC patients and/or limit therapeutic but also "financial" toxicity. Therefore, several clinical trials recently evaluated MRD in early stage NSCLC by integrating and retrospectively comparing the results of MRD assessments. In this context, there is an urgent need to close the gap between clinical research and the use of the evaluation of MRD in routine daily practice. Further action needs to be taken, particularly in evaluating the pertinence of the detection of MRD in prospective interventional clinical studies. This may be done in part by comparing different parameters, such as the techniques used, the different time points and the cutoffs of MRD assessments. This article investigates the assessment of MRD in non-small cell lung cancers, with a special focus on the issues associated with the various assays and the limitations of using circulating free DNA analyses for MRD assessment in early stage lung cancer. Recommendations and tips for the optimisation of MRD evaluation in non-small cell lung cancers are provided.

Biological function, regulatory mechanism, and clinical application of mannose in cancer

Studies examining the regulatory roles and clinical applications of monosaccharides other than glucose in cancer have been neglected. Mannose, a common type of monosaccharide found in human body fluids and tissues, primarily functions in protein glycosylation rather than carbohydrate metabolism. Recent research has demonstrated direct anticancer effects of mannose in vitro and in vivo. Simply supplementing cell culture medium or drinking water with mannose achieved these effects. Moreover, mannose enhances the effectiveness of current cancer treatments including chemotherapy, radiotherapy, targeted therapy, and immune therapy. Besides the advancements in basic research on the anticancer effects of mannose, recent studies have reported its application as a biomarker for cancer or in the delivery of anticancer drugs using mannose-modified drug delivery systems. This review discusses the progress made in understanding the regulatory roles of mannose in cancer progression, the mechanisms underlying its anticancer effects, and its current application in cancer diagnosis and treatment.

Single-cell analysis technologies for cancer research: from tumor-specific single cell discovery to cancer therapy

Single-cell sequencing (SCS) technology is changing our understanding of cellular components, functions, and interactions across organisms, because of its inherent advantage of avoiding noise resulting from genotypic and phenotypic heterogeneity across numerous samples. By directly and individually measuring multiple molecular characteristics of thousands to millions of single cells, SCS technology can characterize multiple cell types and uncover the mechanisms of gene regulatory networks, the dynamics of transcription, and the functional state of proteomic profiling. In this context, we conducted systematic research on SCS techniques, including the fundamental concepts, procedural steps, and applications of scDNA, scRNA, scATAC, scCITE, and scSNARE methods, focusing on the unique clinical advantages of SCS, particularly in cancer therapy. We have explored challenging but critical areas such as circulating tumor cells (CTCs), lineage tracing, tumor heterogeneity, drug resistance, and tumor immunotherapy. Despite challenges in managing and analyzing the large amounts of data that result from SCS, this technique is expected to reveal new horizons in cancer research. This review aims to emphasize the key role of SCS in cancer research and promote the application of single-cell technologies to cancer therapy.

A Review of Biomarkers and Their Clinical Impact in Resected Early-Stage Non-Small-Cell Lung Cancer

The postoperative survival of early-stage non-small-cell lung cancer (NSCLC) patients remains unsatisfactory. In this review, we examined the relevant literature to ascertain the prognostic effect of related indicators on early-stage NSCLC. The prognostic effects of the epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), mesenchymal-epithelial transition (MET), C-ros oncogene 1 (ROS1), or tumour protein p53 (TP53) alterations in resected NSCLC remains debatable. Kirsten rat sarcoma viral oncogene homologue (KRAS) alterations indicate unfavourable outcomes in early-stage NSCLC. Meanwhile, adjuvant or neoadjuvant EGFR-targeted agents can substantially improve prognosis in early-stage NSCLC with EGFR alterations. Based on the summary of current studies, resected NSCLC patients with overexpression of programmed death-ligand 1 (PD-L1) had worsening survival. Conversely, PD-L1 or PD-1 inhibitors can substantially improve patient survival. Considering blood biomarkers, perioperative peripheral venous circulating tumour cells (CTCs) and pulmonary venous CTCs predicted unfavourable prognoses and led to distant metastases. Similarly, patients with detectable perioperative circulating tumour DNA (ctDNA) also had reduced survival. Moreover, patients with perioperatively elevated carcinoembryonic antigen (CEA) in the circulation predicted significantly worse survival outcomes. In the future, we will incorporate mutated genes, immune checkpoints, and blood-based biomarkers by applying artificial intelligence (AI) to construct prognostic models that predict patient survival accurately and guide individualised treatment.

Circulating tumour cells for early detection of clinically relevant cancer

Given that cancer mortality is usually a result of late diagnosis, efforts in the field of early detection are paramount to reducing cancer-related deaths and improving patient outcomes. Increasing evidence indicates that metastasis is an early event in patients with aggressive cancers, often occurring even before primary lesions are clinically detectable. Metastases are usually formed from cancer cells that spread to distant non-malignant tissues via the blood circulation, termed circulating tumour cells (CTCs). CTCs have been detected in patients with early stage cancers and, owing to their association with metastasis, might indicate the presence of aggressive disease, thus providing a possible means to expedite diagnosis and treatment initiation for such patients while avoiding overdiagnosis and overtreatment of those with slow-growing, indolent tumours. The utility of CTCs as an early diagnostic tool has been investigated, although further improvements in the efficiency of CTC detection are required. In this Perspective, we discuss the clinical significance of early haematogenous dissemination of cancer cells, the potential of CTCs to facilitate early detection of clinically relevant cancers, and the technological advances that might improve CTC capture and, thus, diagnostic performance in this setting.

Soluble biomarkers to predict clinical outcomes in non-small cell lung cancer treated by immune checkpoints inhibitors

Lung cancer remains the first cause of cancer-related death despite many therapeutic innovations, including immune checkpoint inhibitors (ICI). ICI are now well used in daily practice at late metastatic stages and locally advanced stages after a chemo-radiation. ICI are also emerging in the peri-operative context. However, all patients do not benefit from ICI and even suffer from additional immune side effects. A current challenge remains to identify patients eligible for ICI and benefiting from these drugs. Currently, the prediction of ICI response is only supported by Programmed death-ligand 1 (PD-L1) tumor expression with perfectible results and limitations inherent to tumor-biopsy specimen analysis. Here, we reviewed alternative markers based on liquid biopsy and focused on the most promising biomarkers to modify clinical practice, including non-tumoral blood cell count such as absolute neutrophil counts, platelet to lymphocyte ratio, neutrophil to lymphocyte ratio, and derived neutrophil to lymphocyte ratio. We also discussed soluble-derived immune checkpoint-related products such as sPD-L1, circulating tumor cells (detection, count, and marker expression), and circulating tumor DNA-related products. Finally, we explored perspectives for liquid biopsies in the immune landscape and discussed how they could be implemented into lung cancer management with a potential biological-driven decision.

Proliferative ability of circulating tumor cells is a prognostic factor in Early-Stage lung adenocarcinoma

INTRODUCTION

Circulating tumor cells (CTCs) and their proliferative ability in lung adenocarcinoma (LUAD) were not well-investigated. We developed a protocol combining an efficient viable CTC isolation and in-vitro cultivation for the CTC enumeration and proliferation to evaluate their clinical significance.

METHOD

The peripheral blood of 124 treatment-naïve LUAD patients were processed by a CTC isolation microfluidics, DS platform, followed by in-vitro cultivation. LUAD-specific CTCs were defined by immunostaining of DAPI+/CD45-/(TTF1/CK7)+ and were enumerated upon isolation and after 7-day cultivation. The CTC proliferative ability was evaluated by both the cultured number and the culture index, a ratio of cultured CTC number to the initial CTC number in 2 mL of blood.

RESULT

All but two LUAD patients (98.4%) were detected with at least one CTC per 2 mL of blood. Initial CTC numbers did not correlate with metastasis (75 ± 126 for non-metastatic, 87 ± 113 for metastatic groups; P = 0.203). In contrast, both the cultured CTC number (mean: 28, 104, and 185 in stage 0/I, II/III, and IV; P < 0.001), and the culture index (mean: 1.1, 1.7 and 9.3 in stage 0/I, II/III, and IV; P = 0.043) were significantly correlated with the stages. Overall survival analysis within the non-metastatic group (N = 53) showed poor prognosis for patients with elevated cultured counts (cutoff ≥ 30; P = 0.027).

CONCLUSION

We implemented a CTC assay in clinical LUAD patients with a high detection rate and cultivation capability. Cultured CTC count and proliferative ability, rather than the crude CTC numbers, highly associated with cancer prognosis.

Circulating tumor cells dynamics during chemotherapy predict survival and response in advanced non-small-cell lung cancer patients

Background

Circulating tumor cells (CTCs) are prognostic biomarker in non-small-cell lung cancer (NSCLC). CTCs could also be used as predictor of efficacy of systemic treatments in advanced NSCLC.

Objectives

We described the dynamic changes of CTCs during first-line platinum-based chemotherapy in advanced NSCLC and clarified the correlation between CTC counts and efficacy of chemotherapy.

Design

Chemotherapy is administered and blood specimens are collected at four time points from baseline to disease progression for CTC detection.

Methods

This multicenter prospective study enrolled patients with previously untreated stage III or IV NSCLC fit for standard platinum-based chemotherapy. Bloods were sampled as per standard operating procedures at baseline, cycle 1 and cycle 4 of chemotherapy, and at disease progression for CTC analysis using the CellSearch system.

Results

Among 150 patients enrolled, median overall survival (OS) was 13.8, 8.4, and 7.9 months in patients with CTC^-, KIT^-CTC, and KIT⁺CTC at baseline (p = 0.002). Patients with persistent negative CTC (46.0%) had longer progression-free survival [5.7 months, 95% confidence interval (CI): 5.0-6.5 versus 3.0 months, 0.6-5.4; hazard ratio (HR): 0.34, 95% CI: 0.18-0.67) and OS (13.1 months, 10.9-15.3 versus 5.6 months, 4.1-7.1; HR: 0.17, 0.08-0.36) compared with patients with persistent positive CTC (10.7%), which was not impacted by chemotherapy. Chemotherapy decreased CTC from 36.0% (54/150) to 13.7% (13/95).

Conclusions

CTC persistent presence during treatment represents poor prognosis and resistance to chemotherapy in advanced NSCLC. Chemotherapy could effectively eliminate CTCs. Molecular characterization and the functionalization of CTC will be warranted for further intensive investigation.

Trial registration

NCT01740804.