Serum CEA and CYFRA Levels in ALK-rearranged NSCLC Patients: Correlation With Distant Metastasis

Predicting bone metastasis-free survival in non-small cell lung cancer from preoperative CT via deep learning

Accurate prediction of bone metastasis-free survival (BMFS) after complete surgical resection in patients with non-small cell lung cancer (NSCLC) may facilitate appropriate follow-up planning. The aim of this study was to establish and validate a preoperative CT-based deep learning (DL) signature to predict BMFS in NSCLC patients. We performed a retrospective analysis of 1547 NSCLC patients who underwent complete surgical resection, followed by at least 36 months of monitoring at two hospitals. We constructed a DL signature from multiparametric CT images using 3D convolutional neural networks, and we integrated this signature with clinical-imaging factors to establish a deep learning clinical-imaging signature (DLCS). We evaluated performance using Harrell's concordance index (C-index) and the time-dependent receiver operating characteristic. We also assessed the risk of bone metastasis (BM) in NSCLC patients at different clinical stages using DLCS. The DL signature successfully predicted BM, with C-indexes of 0.799 and 0.818 for the validation cohorts. DLCS outperformed the DL signature with corresponding C-indexes of 0.806 and 0.834. Ranges for area under the curve at 1, 2, and 3 years were 0.820-0.865 for internal and 0.860-0.884 for external validation cohorts. Furthermore, DLCS successfully stratified patients with different clinical stages of NSCLC as high- and low-risk groups for BM (p < 0.05). CT-based DL can predict BMFS in NSCLC patients undergoing complete surgical resection, and may assist in the assessment of BM risk for patients at different clinical stages.

Tumor marker-based RecistTM is superior to RECIST as criteria to predict the long-term benefits of targeted therapy in advanced non-small-cell lung cancer with driver gene mutations

BACKGROUND

Tyrosine kinase inhibitors (TKIs) are standard first-line treatments for advanced non-small-cell lung cancer (NSCLC) with driver gene mutations. The Response Evaluation Criteria in Solid Tumors (RECIST) are limited in predicting long-term patient benefits. A tumour marker-based evaluation criteria, RecistTM, was used to investigate the potential for assessing targeted-therapy efficacy in lung cancer treatment.

METHODS

We retrospectively analysed patients with stage IIIA-IV NSCLC and driver gene mutations, whose baseline tumour marker levels exceeded the pre-treatment cut-off value three-fold and who received TKI-targeted therapy as a first-line treatment. We compared efficacy, progression-free survival (PFS), and overall survival (OS) between RecistTM and RECIST.

FINDINGS

The median PFS and OS differed significantly among treatment-response subgroups based on RecistTM but not RECIST. The predicted 1-, 2-, and 3-year disease-progression risk, according to area under the receiver operating characteristic curve, as well as the 1-, 3-, and 5-year mortality risk, differed significantly between RecistTM and RECIST. The median PFS and OS of tmCR according to RecistTM, was significantly longer than (CR+PR) according to RECIST. Imaging analysis revealed that the ΔPFS was 11.27 and 6.17 months in the intervention and non-intervention groups, respectively, suggesting that earlier intervention could extend patients' PFS.

INTERPRETATION

RecistTM can assess targeted-therapy efficacy in patients with advanced NSCLC and driver gene mutations, along with tumour marker abnormalities. RecistTM surpasses RECIST in predicting short- and long-term patient benefits, and allows the early identification of patients resistant to targeted drugs, enabling prompt intervention and extending the imaging-demonstrated time to progression.

Carcinoembryonic antigen in the diagnosis, treatment, and follow-up of focal liver lesions

In this editorial review, we comment on the article published in the recent issue of the World Journal of Gastrointestinal Surgery. Carcinoembryonic antigen (CEA) is a fetal glycoprotein and can be secreted in very small amounts from healthy adults after birth. CEA is widely used not only for diagnostic tumor markers but also importantly for the management of some gastrointestinal tumors. The most common clinical use is surveillance for the monitoring of colorectal carcinoma. However, CEA can become elevated in several malign or benign characterized pathologies. Serum CEA level may vary depending on the location of the lesion, whether it metastasizes or not, and its histopathological characteristics. It has been determined that cases with high preoperative CEA have a more aggressive course and the risk of metastasis to the lymph tissue and liver increases. In this editorial review, we focused on evaluating the role of CEA in clinical practice with a holistic approach, including the diagnostic and prognostic significance of CEA in patients with focal liver lesions, the role of CEA in follow-up after definitive surgery, and also hepatic resection for metastasis, and the management of all patients with raised CEA.

CtDNA based molecular residual disease outcompetes carcinoembryonic antigen in predicting postoperative recurrence of non-small cell lung cancer

Background

Carcinoembryonic antigen (CEA) has been routinely used as a postoperative monitoring biomarker for non-small cell lung cancer (NSCLC). Emergingly, circulating tumor DNA (ctDNA)-molecular residual disease (MRD) detection is a well-established prognostic marker, with better positive predictive value (PPV) and negative predictive value (NPV). However, the actual clinical efficiency of CEA in MRD context remain unknown. Hence, we conducted this study for direct comparison of CEA and MRD.

Methods

Two cohorts were analyzed in this study. To investigate the prognostic and predictive value of CEA, we retrospective enrolled NSCLC patient stage IA2-IIIA (8th tumor-node-metastasis staging system) with longitudinal CEA between 2018 and 2019. We also performed a paired comparison of CEA and MRD in our previous published cohort. Survival data were analyzed using the Kaplan-Meier method, and comparisons were performed using the log-rank test. Sensitivity, specificity, PPV and NPV were calculated using the R package "epiR". McNemar's test was used to analyze the paired data. Statistical differences were set at a P value <0.05.

Results

In the retrospective cohort, the sensitivity of longitudinal CEA was only 0.49 [95% confidence interval (CI): 0.37-0.60]. Even for patients with progressively elevated CEA levels, 32% of them still remained disease-free, with PPV of 0.68 (0.49-0.83) and NPV of 0.81 (0.77-0.85). Furthermore, we then compared CEA and MRD values in a previously described MRD cohort. As expected, CEA levels could not stratify the risk of recurrence in detectable versus undetectable MRD populations.

Conclusions

MRD is superior to CEA in postoperative monitoring. there is insufficient evidence to support its use as postoperative monitoring tumor marker.

Prognostic value of blood-based protein biomarkers in non-small cell lung cancer: A critical review and 2008-2022 update

BACKGROUND

Therapeutic possibilities for non-small cell lung cancer (NSCLC) have considerably increased during recent decades.

OBJECTIVE

To summarize the prognostic relevance of serum tumor markers (STM) for early and late-stage NSCLC patients treated with classical chemotherapies, novel targeted and immune therapies.

METHODS

A PubMed database search was conducted for prognostic studies on carcinoembryonic antigen (CEA), cytokeratin-19 fragment (CYFRA 21-1), neuron-specific enolase, squamous-cell carcinoma antigen, progastrin-releasing-peptide, CA125, CA 19-9 and CA 15-3 STMs in NSCLC patients published from 2008 until June 2022.

RESULTS

Out of 1069 studies, 141 were identified as meeting the inclusion criteria. A considerable heterogeneity regarding design, patient number, analytical and statistical methods was observed. High pretherapeutic CYFRA 21-1 levels and insufficient decreases indicated unfavorable prognosis in many studies on NSCLC patients treated with chemo-, targeted and immunotherapies or their combinations in early and advanced stages. Similar results were seen for CEA in chemotherapy, however, high pretherapeutic levels were sometimes favorable in targeted therapies. CA125 is a promising prognostic marker in patients treated with immunotherapies. Combinations of STMs further increased the prognostic value over single markers.

CONCLUSION

Protein STMs, especially CYFRA 21-1, have prognostic potential in early and advanced stage NSCLC. For future STM investigations, better adherence to comparable study designs, analytical methods, outcome measures and statistical evaluation standards is recommended.

Potential biomarkers for the early detection of bone metastases

The clinical manifestations of bone metastases are diversified while many sites remain asymptomatic at early stage. As the early diagnosis method is not perfect and the early symptoms of tumor bone metastasis are not typical, bone metastasis is not easy to be detected. Therefore, the search for bone metastasis-related markers is effective for timely detection of tumor bone metastases and the development of drugs to inhibit bone metastases. As a result, bone metastases can only be diagnosed when symptoms are found, increasing the risk of developing skeletal-related event (SREs), which significantly impairs the patient's quality of life. Therefore, the early diagnosis of bone metastases is of great importance for the treatment and prognosis of cancer patients. Changes of bone metabolism indexes appear earlier in bone metastases, but the traditional biochemical indexes of bone metabolism lack of specificity and could be interfered by many factors, which limits their application in the study of bone metastases. Some new biomarkers of bone metastases have good diagnostic value, such as proteins, ncRNAs, circulating tumor cells (CTCs). Therefore, this study mainly reviewed the initial diagnostic biomarkers of bone metastases which were expected to provide references for the early detection of bone metastases.

Multiparameter prediction model of immune checkpoint inhibitors combined with chemotherapy for non-small cell lung cancer based on support vector machine learning

The reliable predictive markers to identify which patients with advanced non-small cell lung cancer tumors (NSCLC) will achieve durable clinical benefit (DCB) for chemo-immunotherapy are needed. In this retrospective study, we collected radiomics and clinical signatures from 94 patients with advanced NSCLC treated with anti-PD-1/PD-L1 combined with chemotherapy from January 1, 2018 to May 31, 2022. Radiomics variables were extracted from pretreatment CT and selected by Spearman correlation coefficients and clinical features by Logistics regression analysis. We performed effective diagnostic algorithms principal components analysis (PCA) and support vector machine (SVM) to develop an early classification model among DCB and non-durable benefit (NDB) groups. A total of 26 radiomics features and 6 clinical features were selected, and then principal component analysis was used to obtain 6 principal components for SVM building. RC-SVM achieved prediction accuracy with AUC of 0.91 (95% CI 0.87-0.94) in the training set, 0.73 (95% CI 0.61-0.85) in the cross-validation set, 0.84 (95% CI 0.80-0.89) in the external validation set. The new method of RC-SVM model based on radiomics-clinical signatures provides a significant additive value on response prediction in patients with NSCLC preceding chemo-immunotherapy.

Five-year Disease Control With Alectinib in a Patient With Metastatic ALK-rearranged Lung Adenocarcinoma

BACKGROUND/AIM

Therapy with alectinib could achieve prolonged progression-free and overall survival in patients with anaplastic lymphoma kinase gene (ALK)-rearranged non-small-cell lung cancer (NSCLC). However, a large proportion of the patients discontinue alectinib treatment due to recurrence.

CASE REPORT

A 41-year-old male patient presented with cellulitis of the right upper extremity that had developed in the past 3 weeks. Chest radiograph at the time of admission incidentally revealed a nodule in the right lung. At diagnosis, the patient had spinal bone metastases and thrombosis in the common jugular vein subclavian veins. Therefore, in addition to warfarin therapy and irradiation to the bone metastases, chemotherapy was started. After identifying the presence of the ALK rearranged gene, alectinib therapy was initiated. Since then, alectinib treatment has been continued for more than 5 years.

CONCLUSION

Although very rare, there are patients who might be able to maintain a long-term response to alectinib. It is important for chest physicians to manage such patients so that the effects of alectinib can be maintained for a long time.

Prognostic value of lactate dehydrogenase in non-small cell lung cancer patients with brain metastases: a retrospective cohort study

BACKGROUND

At present, although there are some known molecular markers for the prognosis of non-small cell lung cancer (NSCLC) brain metastases, but there are still shortcomings in sensitivity and specificity. Lactate dehydrogenase (LDH) is one of the key enzymes involved in malignancy vital glycolytic pathway. Elevated serum LDH levels are reported significantly associated with a poor prognosis in various malignancies. However, there is currently no consensus regarding the prognostic value of LDH in NSCLC patients with brain metastases.

METHODS

We retrospectively analyzed 224 patients diagnosed with lung cancer brain metastases between January 2006 and June 2020 after excluding patients meeting combined with other malignancies and inaccurate clinical information. The LDH cutoff values were obtained using a restricted cubic spline (RCS) model, and the patients were divided into two groups according to the optimal cut-off value (180 U/L). 107 patients with LDH ≤180 (47.77%) and 117 patients with LDH >180 (52.23%) were identified. Univariate and multivariate logistic regression analyses were performed to identify the risk factors. The overall survival (OS) time was defined as the time from the first diagnosis of brain metastases to the last follow-up or death. Of the included patients, 147 survived and 77 died. The Kaplan-Meier method was used to illustrate the OS difference between the two groups. Finally, sensitivity analysis was employed to evaluate the robustness of the results.

RESULTS

The OS rate was significantly lower in the high LDH group versus the low LDH group (P=0.009). The median survival times of the high and low LDH groups were approximately 16 and 33 months, respectively. Multivariate analysis showed that high LDH was associated with a significantly worse OS [adjusted hazard ratio (aHR), 1.567; 95% confidence interval (CI): 1.058 to 2.32, P=0.025] with adjustment for covariables that P<0.05 in univariate analysis. Sensitivity analysis indicated that the results of this study are robust, despite potential unmeasured confounders.

CONCLUSIONS

High level of serum LDH indicates poor prognosis for patients with NSCLC brain metastases. This finding may provide useful prognostic information for patients and clinicians to choose more aggressive treatment strategies.

Predictive and Prognostic Biomarkers for Lung Cancer Bone Metastasis and Their Therapeutic Value

Lung cancer is the leading cause of cancer-related death worldwide. Bone metastasis, which usually accompanies severe skeletal-related events, is the most common site for tumor distant dissemination and detected in more than one-third of patients with advanced lung cancer. Biopsy and imaging play critical roles in the diagnosis of bone metastasis; however, these approaches are characterized by evident limitations. Recently, studies regarding potential biomarkers in the serum, urine, and tumor tissue, were performed to predict the bone metastases and prognosis in patients with lung cancer. In this review, we summarize the findings of recent clinical research studies on biomarkers detected in samples obtained from patients with lung cancer bone metastasis. These markers include the following: (1) bone resorption-associated markers, such as N-terminal telopeptide (NTx)/C-terminal telopeptide (CTx), C-terminal telopeptide of type I collagen (CTx-I), tartrate-resistant acid phosphatase isoform 5b (TRACP-5b), pyridinoline (PYD), and parathyroid hormone related peptide (PTHrP); (2) bone formation-associated markers, including total serum alkaline phosphatase (ALP)/bone specific alkaline phosphatase(BAP), osteopontin (OP), osteocalcin (OS), amino-terminal extension propeptide of type I procollagen/carboxy-terminal extension propeptide of type I procollagen (PICP/PINP); (3) signaling markers, including epidermal growth factor receptor/Kirsten rat sarcoma/anaplastic lymphoma kinase (EGFR/KRAS/ALK), receptor activator of nuclear factor κB ligand/receptor activator of nuclear factor κB/osteoprotegerin (RANKL/RANK/OPG), C-X-C motif chemokine ligand 12/C-X-C motif chemokine receptor 4 (CXCL12/CXCR4), complement component 5a receptor (C5AR); and (4) other potential markers, such as calcium sensing receptor (CASR), bone sialoprotein (BSP), bone morphogenetic protein 2 (BMP2), cytokeratin 19 fragment/carcinoembryonic antigen (CYFRA/CEA), tissue factor, cell-free DNA, long non-coding RNA, and microRNA. The prognostic value of these markers is also investigated. Furthermore, we listed some clinical trials targeting hotspot biomarkers in advanced lung cancer referring for their therapeutic effects.