Clinical Associations of Preoperative and Postoperative Serum CEA and Lung Cancer Outcome

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

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

Trajectory patterns and cumulative burden of CEA during follow-up with non-small cell lung cancer outcomes: A retrospective longitudinal cohort study

BACKGROUND

Previous studies of non-small cell lung cancer (NSCLC) focused on CEA measured at a single time point, ignoring serial CEA measurements.

METHODS

This retrospective cohort included 2959 patients underwent surgery for stage I-III NSCLC. CEA trajectory patterns and long-term cumulative CEA burden were evaluated using the latent class growth mixture model.

RESULTS

Four CEA trajectory groups were identified, named as low-stable, decreasing, early-rising and later-rising. Compared with the low-stable group, the adjusted hazard ratios associated with death were 1.27, 4.50, and 3.68 for the other groups. Cumulative CEA burden were positively associated with the risk of death in patients not belonging to the low-stable group. The 5-year overall survival (OS) rates decreased from 62.3% to 33.0% for the first and fourth quantile groups of cumulative CEA burden. Jointly, patients with decreasing CEA trajectory could be further divided into the decreasing & low and decreasing & high group, with 5-year OS rates to be 77.9% and 47.1%. Patients with rising CEA trajectory and high cumulative CEA were found to be more likely to develop bone metastasis.

CONCLUSIONS

Longitudinal trajectory patterns and long-term cumulative burden of CEA were independent prognostic factors of NSCLC. We recommend CEA in postoperative surveillance of NSCLC.

Prognostic value of normal levels of preoperative tumor markers in colorectal cancer

Carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 125 (CA125), and alpha-fetoprotein (AFP) are widely used tumor markers for colorectal cancer (CRC), but their clinical significance is unknown when the levels of these tumor markers were within the normal range. This retrospective study included 2145 CRC patients. The entire cohort was randomly divided into training and validation datasets. The optimal cut-off values of tumor markers were calculated using X-tile software, and univariate and multivariate analyses were performed to assess its association with overall survival (OS). The nomogram model was constructed and validated. The entire cohort was randomly divided into a training dataset (1502 cases, 70%) and a validation dataset (643 cases,30%). Calculated from the training dataset, the optimal cut-off value was 2.9 ng/mL for CEA, 10.1 ng/mL for CA19-9, 13.4 U/mL for CA125, and 1.8 ng/mL for AFP, respectively. Multivariate analysis revealed that age, tumor location, T stage, N stage, preoperative CA19-9, and CA125 levels were independent prognostic predictors. Even within the normal range, CRC patients with relatively high levels of CA19-9 or CA125 worse OS compared to those with relatively low levels. Then, based on the independent prognostic predictors from multivariate analysis, two models with/without (model I/II) CA19-9 and CA125 were built, model I showed better prediction and reliability than model II. Within the normal range, relatively high levels of preoperative CA19-9 and CA125 were significantly associated with poor OS in CRC patients. The nomogram based on CA19-9 and CA125 levels showed improved predictive accuracy ability for CRC.

LncRNAs in non-small cell lung cancer: novel diagnostic and prognostic biomarkers

Non-small cell lung cancer (NSCLC) is one of the main causes of cancer-related death worldwide, with a serious impact on human health and life. The identification of NSCLC at an early stage is a formidable task that frequently culminates in a belated diagnosis. LncRNA is a kind of noncoding RNA with limited protein-coding capacity, and its expression is out of balance in many cancers, especially NSCLC. A large number of studies have reported that lncRNA acts a vital role in regulating angiogenesis, invasion, metastasis, and the proliferation and apoptosis of tumor cells, affecting the occurrence and development of NSCLC. Abundant evidence demonstrates that lncRNAs may serve as potential biomarkers for NSCLC diagnosis and prognosis. In this review, we summarize the latest progress in characterizing the functional mechanism of lncRNAs involved in the development of NSCLC and further discuss the role of lncRNAs in NSCLC therapy and chemotherapy resistance. We also discuss the advantages, limitations, and challenges of using lncRNAs as diagnostic or prognostic biomarkers in the management of NSCLC.

Development and validation of a nomogram based on preoperative variables for predicting recurrence-free survival in stage IA lung adenocarcinoma

BACKGROUND

This study aimed to establish a nomogram for predicting risk of recurrence and provide a model for decision-making between lobectomy and sublobar resection in patients with stage IA lung adenocarcinoma.

METHODS

Patients diagnosed with stage IA lung adenocarcinoma (LUAD) between December 2010 and October 2018 from Cancer Hospital Chinese Academy of Medical Sciences were included. Patients were randomly assigned to training and validation cohorts, accounting for 70% and 30% of the total cases, respectively. We collected laboratory variables before surgery. Univariate and multivariate analyses were performed in the training cohort to identify variables significantly associated with recurrence-free survival (RFS) which were subsequently used to construct a nomogram. Validation was conducted in both cohorts. A receiver operating characteristic curve was used to determine the optional cutoff values of the scores calculated from the nomogram. Patients were then divided into low- and high-risk groups. Survival was performed to determine if the nomogram could guide the operation method.

RESULTS

A total of 543 patients were included in this study. Gender, albumin level, carcinoembryonic antigen level and cytokeratin-19-fragment level were included in the nomogram. In both cohorts, the nomogram stratified the patients into high- and low-risk groups in terms of RFS. In particular, there was a significant difference in RFS between lobectomy and sublobar resection in the high-risk group.

CONCLUSIONS

Gender, albumin level, carcinoembryonic antigen level and cytokeratin-19-fragment level are valuable markers in predicting recurrence and can guide surgical practice in patients with stage IA LUAD.

Prognostic factors affecting survival in patients with non-small cell lung cancer treated with salvage surgery after drug therapy: a multi-institutional retrospective study

BACKGROUND

The prevalence of salvage surgeries after drug therapy for non-small cell lung cancer (NSCLC) has risen, mainly due to recent progress in molecular-targeted drugs and immune checkpoint inhibitors for NSCLC. While the safety and effectiveness of salvage surgery after drug therapy for NSCLC have been studied, its indications remain unclear. We aimed to identify the prognostic factors affecting survival in patients with advanced-stage (stages III-IV) NSCLC treated with salvage surgery after drug therapy.

METHODS

A retrospective investigation was conducted on patients who received salvage surgery after drug therapy at four hospitals between 2007 and 2020. Salvage surgery was defined as surgery after drug therapy for local progression, tumor conversion to resectable status, and discontinuation of prior drug therapy owing to serious complications.

RESULTS

Thirty-two patients received cytotoxic agents alone (n = 12 [38%]), tyrosine kinase inhibitors (TKIs; n = 16 [50%]), or immune checkpoint inhibitors (n = 4 [13%]) as prior drug therapy. In 11 (34%) and 21 (66%) patients, the clinical stage before treatment was III or IV, respectively. The median initial and preoperative serum carcinoembryonic antigen (CEA) levels were 10.2 (range, 0.5-1024) ng/mL and 4.2 (range, 0.6-92.5) ng/mL, respectively. Among the patients, 28 (88%) underwent lobectomy, 2 (6%) underwent segmentectomy, and 2 (6%) underwent wedge resection. Complete resection of the primary lesion was accomplished in 28 (88%) patients. Postoperative complications were documented in six (19%) patients. Mortality rates were 0% at 30 days and 3% at 90 days post-operation. The 5-year overall survival rate stood at 66%, while the 5-year progression-free survival rate was 21%. Multivariate analyses showed that prior TKI therapy and preoperative serum CEA level < 5 ng/mL were prognostic factors influencing overall survival (hazard ratio [95% confidence interval]: 0.06 [0.006-0.68] and 0.03 [0.002-0.41], respectively). The 5-year overall survival in the 11 patients with both favorable prognosticators was 100%.

CONCLUSIONS

In this study, prior TKI therapy and preoperative serum CEA level < 5 ng/mL were favorable prognostic factors for overall survival in patients with NSCLC treated with salvage surgery. Patients with these prognostic factors are considered good candidates for salvage surgery after drug therapy.

Carbon Nanotube Field-Effect Transistor Biosensor with an Enlarged Gate Area for Ultra-Sensitive Detection of a Lung Cancer Biomarker

Carcinoembryonic antigen (CEA) is a recognized biomarker for lung cancer and can be used for early detection. However, the clinical value of CEA is not fully realized due to the rigorous requirement for high-sensitivity and wide-range detection methods. Field-effect transistor (FET) biosensors, as one of the potentially powerful platforms, may detect CEA with a significantly higher sensitivity than conventional clinical testing equipment, while their sensitivity and detection range for CEA are far below the requirement for early detection. Here, we construct a floating gate FET biosensor to detect CEA based on a semiconducting carbon nanotube (CNT) film combined with an undulating yttrium oxide (Y₂O₃) dielectric layer as the biosensing interface. Utilizing an undulating biosensing interface, the proposed device showed a wider detection range and optimized sensitivity and detection limit, which benefited from an increase of probe-binding sites on the sensing interface and an increase of electric double-layer capacitance, respectively. The outcomes of analytical studies confirm that the undulating Y₂O₃ provided the desired biosensing surface for probe immobilization and performance optimization of a CNT-FET biosensor toward CEA including a wide detection range from 1 fg/mL to 1 ng/mL, good linearity, and high sensitivity of 72 ag/mL. More crucially, the sensing platform can function normally in the complicated environment of fetal bovine serum, indicating its great promise for early lung cancer screening.

Current Methods for Identifying Plasma Membrane Proteins as Cancer Biomarkers

Plasma membrane proteins are a special class of biomolecules present on the cellular membrane. They provide the transport of ions, small molecules, and water in response to internal and external signals, define a cell's immunological identity, and facilitate intra- and intercellular communication. Since they are vital to almost all cellular functions, their mutants, or aberrant expression is linked to many diseases, including cancer, where they are a part of cancer cell-specific molecular signatures and phenotypes. In addition, their surface-exposed domains make them exciting biomarkers for targeting by imaging agents and drugs. This review looks at the challenges in identifying cancer-related cell membrane proteins and the current methodologies that solve most of the challenges. We classified the methodologies as biased, i.e., search cells for the presence of already known membrane proteins. Second, we discuss the unbiased methods that can identify proteins without prior knowledge of what they are. Finally, we discuss the potential impact of membrane proteins on the early detection and treatment of cancer.

Development and validation of a deep learning signature for predicting lymph node metastasis in lung adenocarcinoma: comparison with radiomics signature and clinical-semantic model

OBJECTIVE

To develop and validate a deep learning (DL) signature for predicting lymph node (LN) metastasis in patients with lung adenocarcinoma.

METHODS

A total of 612 patients with pathologically-confirmed lung adenocarcinoma were retrospectively enrolled and were randomly divided into training cohort (n = 489) and internal validation cohort (n = 123). Besides, 108 patients were enrolled and constituted an independent test cohort (n = 108). Patients' clinical characteristics and CT semantic features were collected. The radiomics features were derived from contrast-enhanced CT images. The clinical-semantic model and radiomics signature were built to predict LN metastasis. Furthermore, Swin Transformer was adopted to develop a DL signature predictive of LN metastasis. Model performance was evaluated by area under the receiver operating characteristic curve (AUC), sensitivity, specificity, calibration curve, and decision curve analysis. The comparisons of AUC were conducted by the DeLong test.

RESULTS

The proposed DL signature yielded an AUC of 0.948-0.961 across all three cohorts, significantly superior to both clinical-semantic model and radiomics signature (all p < 0.05). The calibration curves show that DL signature predicted probabilities fit well the actual observed probabilities of LN metastasis. DL signature gained a higher net benefit than both clinical-semantic model and radiomics signature. The incorporation of radiomics signature or clinical-semantic risk predictors failed to reveal an incremental value over the DL signature.

CONCLUSIONS

The proposed DL signature based on Swin Transformer achieved a promising performance in predicting LN metastasis and could confer important information in noninvasive mediastinal LN staging and individualized therapeutic options.

KEY POINTS

• Accurate prediction for lymph node metastasis is crucial to formulate individualized therapeutic options for patients with lung adenocarcinoma. • The deep learning signature yielded an AUC of 0.948-0.961 across all three cohorts in predicting lymph node metastasis, superior to both radiomics signature and clinical-semantic model. • The incorporation of radiomics signature or clinical-semantic risk predictors into deep learning signature failed to reveal an incremental value over deep learning signature.

A combined preoperative red cell distribution width and carcinoembryonic antigen score contribute to prognosis prediction in stage I lung adenocarcinoma

AIMS

Hematological markers that can be used for prognosis prediction for stage I lung adenocarcinoma (LUAD) are still lacking. Here, we examined the prognostic value of a combination of the red cell distribution width (RDW) and carcinoembryonic antigen (CEA), namely, the RDW-CEA score (RCS), in stage I LUAD.

MATERIALS AND METHODS

A retrospective study with 154 patients with stage I LUAD was conducted. Patients were divided into RCS 1 (decreased RDW and CEA), RCS 2 (decreased RDW and increased CEA, increased RDW and decreased CEA), and RCS 3 (increased RDW and CEA) subgroups based on the best optimal cutoff points of RDW and CEA for overall survival (OS). The differences in other clinicopathological parameters among RCS subgroups were calculated. Disease-free survival (DFS) and OS among these groups were determined by Kaplan-Meier analysis, and risk factors for outcome were calculated by a Cox proportional hazards model.

RESULTS

Seventy, 65, and 19 patients were assigned to the RCS 1, 2, and 3 subgroups, respectively. Patients ≥ 60 years (P < 0.001), male sex (P = 0.004), T₂ stage (P = 0.004), and IB stage (P = 0.006) were more significant in the RCS 2 or 3 subgroups. The RCS had a good area under the curve (AUC) for predicting DFS (AUC = 0.81, P < 0.001) and OS (AUC = 0.93, P < 0.001). The DFS (log-rank = 33.26, P < 0.001) and OS (log-rank = 42.05, P < 0.001) were significantly different among RCS subgroups, with RCS 3 patients displaying the worst survival compared to RCS 1 or 2 patients. RCS 3 was also an independent risk factor for both DFS and OS.

CONCLUSIONS

RCS is a useful prognostic indicator in stage I LUAD patients, and RCS 3 patients have poorer survival. However, randomized controlled trials are needed to validate our findings in the future.

Blood protein biomarkers in lung cancer

Lung cancer has consistently ranked first as the cause of cancer-associated mortality. The 5-year survival rate has risen slowly, and the main obstacle to improving the prognosis of patients has been that lung cancer is usually diagnosed at an advanced or incurable stage. Thus, early detection and timely intervention are the most effective ways to reduce lung cancer mortality. Tumor-specific molecules and cellular elements are abundant in circulation, providing real-time information in a noninvasive and cost-effective manner during lung cancer development. These circulating biomarkers are emerging as promising tools for early detection of lung cancer and can be used to supplement computed tomography screening, as well as for prognosis prediction and treatment response monitoring. Serum and plasma are the main sources of circulating biomarkers, and protein biomarkers have been most extensively studied. In this review, we summarize the research progress on three most common types of blood protein biomarkers (tumor-associated antigens, autoantibodies, and exosomal proteins) in lung cancer. This review will potentially guide researchers toward a more comprehensive understanding of candidate lung cancer protein biomarkers in the blood to facilitate their translation to the clinic.

Clinical significance of the combination of preoperative SUVmax and CEA in patients with clinical stage IA lung adenocarcinoma

BACKGROUND

Preoperative maximum standardized uptake value (SUVmax) of 2-[18F]-fluoro-2-deoxy-D-glucose positron emission tomography and serum carcinoembryonic antigen (CEA) have been reported as prognostic factors for lung adenocarcinoma. However, the significance of combined SUVmax and CEA in early-stage lung adenocarcinoma is not well known.

METHODS

We retrospectively evaluated the relationship between the combination of SUVmax and CEA and the prognosis of 410 patients with clinical stage IA lung adenocarcinoma who underwent resection. The cutoff values for SUVmax and CEA were determined by receiver operating characteristic curve analysis, and patients were categorized into high SC (SUVmax and CEA) group (SUVmax ≥2.96 and CEA ≥5.3), moderate SC group (either SUVmax <2.96 and CEA ≥5.3 or SUVmax ≥2.96 and CEA <5.3) and low SC group (SUVmax <2.96 and CEA <5.3).

RESULTS

Kaplan-Meier curve analysis showed that patients with clinical stage IA lung adenocarcinoma in the high SC group had significantly shorter overall survival (OS) and recurrence-free survival (RFS) than the other groups (p = 0.011 and p < 0.0001, respectively). Multivariate analysis showed that high SC was an independent prognostic factor of OS (p = 0.029) and RFS (p < 0.0001).

CONCLUSIONS

High values of SUVmax and CEA were associated with poor OS and RFS in patients with stage IA lung adenocarcinoma. Simultaneous evaluation of SUVmax and CEA may be an effective prognostic marker to determine the optimal treatment strategy of early-stage lung adenocarcinoma.

High Expression of lncRNA HEIH is Helpful in the Diagnosis of Non-Small Cell Lung Cancer and Predicts Poor Prognosis

Background

This study aims to investigate the expression and clinical value of long non-coding RNA (lncRNA) HEIH in peripheral blood of patients with non-small cell lung cancer (NSCLC).

Methods

Healthy subjects (N=70), patients with lung squamous cell carcinoma (LUSC, N=70) and patients with lung adenocarcinoma (LUAD, N=80) were included. LncRNA HEIH expression in peripheral blood of included subjects was detected using RT-qPCR. According to the median expression of lncRNA HEIH, LUSC and LUAD patients were allocated into lncRNA HEIH high/low expression groups. The correlation between lncRNA HEIH and clinical indicators of patients was analyzed; Logistic multifactor regression was used to analyze the independent risk factors influencing lncRNA HEIH level. Receiver-operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of lncRNA HEIH and carcinoembryonic antigen (CEA) in LUSC/LUAD patients. MedCalc-Comparison of ROC curves was used to compare the area under ROC curve. The cumulative survival rates of lncRNA HEIH high/low expression group were analyzed by Kaplan–Meier curve. COX multivariate analysis was used to assess the independent factors affecting prognosis of NSCLC.

Results

LncRNA HEIH in peripheral blood of LUSC/LUAD patients was higher than that in healthy controls, with no evident difference between LUSC and LUAD groups. In LUSC/LUAD patients, TNM stage, lymph node metastasis, distal metastasis, and CEA were independent risk factors affecting lncRNA HEIH; patients with high lncRNA HEIH expression had larger pack-years and tumor size, higher CEA level and tumor stage, and higher risk of lymph node metastasis and distal metastasis. LncRNA HEIH had higher diagnostic efficiency than CEA in NSCLC patients. High expression of lncRNA HEIH predicted poor prognosis in patients with NSCLC and was an independent risk factor for prognosis of NSCLC.

Conclusion

High expression of lncRNA HEIH is helpful in the diagnosis of NSCLC and predicts poor prognosis.

High Prevalence of Abnormal Carcinoembryonic Antigen in Diabetic Inpatients with Poor Glycemic Control

INTRODUCTION

Higher serum carcinoembryonic antigen (CEA) was found in diabetic patients rather than controls. However, the prevalence of abnormal CEA among diabetic inpatients with a large proportion of poor glycemic control is unclear.

METHODS

A total of 385 diabetic inpatients were included in this study. We collected information from a large clinical database. Patients with malignant tumors were excluded by examination and follow-up.

RESULTS

We found a surprisingly high prevalence (14.3%) of diabetic inpatients with CEA above normal. The proportion of patients with abnormal CEA was significantly different in subgroups with different blood glucose levels, 20.4% in the HbA1c ≥ 9% group, and 8.5% in the HbA1c < 9%, p = 0.000. We found that the CEA levels were correlated with age, body mass index and HbA1c. The regression coefficient of HbA1c was the highest, B = 0.284, p = 0.000. We also found that the CEA levels were higher in diabetic inpatients with BMI < 24 kg/m2 than the overweight or obesity patients. There was a significant difference in the insulin level and C peptide level between the elevated CEA group and the non-elevated CEA group.

CONCLUSION

The elevation of CEA is common in diabetic inpatients, especially those with poor hyperglycemia controlled (HbA1c ≥ 9%). The underlying mechanism may be related to glucose toxicity.

[Predicting the risk of tumor progression in patients with early stages of adenocarcinoma and squamous cell lung carcinoma based on laboratory parameters]

Non-small cell carcinoma (NSCLC) prevails in the structure of the incidence of lung cancer. In patients with I stage NSCLC, only 60-70% overcome the 5-year survival barrier, and at II stage it decreases to 35-40%. The reason for such a high mortality rate is almost always a relapse of the disease. The main histological forms of NSCLC - adenocarcinoma (AC) and squamous cell carcinoma (SCLC) - differ in the course, protocols and effectiveness of the treatment. Comparative survival data for AK and PCLC are controversial, and reliable biomarkers for determining the risk of tumor progression are lacking. In thus study we have investigated the possibility of using laboratory parameters characterizing the level of some blood proteins involved in carcinogenesis in patients with early stages of AC and SCLC to determine the risk of disease progression. We retrospectively analyzed the duration of the relapse-free period after surgical treatment for one year in 1250 patients (816 with stages I and II of adenocarcinoma, G1-3 and 434 with early stages of SCLC, G1-3). In 81 patients with AC and 36 - with SCLC (stages I-II, G1-3) the level of CYFRA 21-1 and SCC by electrochemiluminescent method, chemokines CXCL5, CXCL8, TPA, pyruvate kinase M2, HIF-1α and hyaluronic acid by enzyme immunoassay, receptors CXCR1, CXCR2, CD44v6 by flow cytometry were determined. Using the Kaplan-Meier graphical analysis, groups of low (stage I G1-2 + stage II G1) and high (stage I G3 + stage II G2-3) risk of tumor progression were identified. In the case of the one-year survival rate of patients with AC was higher than with SCLC. In patients with AC and a high risk of tumor recurrence, compared with a low one, the level of CYFRA 21-1, the mean intensity of fluorescence (MFI) of the CXCR1 receptor in granulocytes, and the relative content of the CXCR2 receptor in lymphocytes were higher. In the case of rapid progression of SCLC in patients, the relative content of the CXCR2 receptor in lymphocytes, the proportion of monocytes equipped with the CD44v6 receptor, and the SCC level were higher than with slow progression. Regression equations, including combinations of the above parameters (threshold value for AC - 0,512, for SCLC - 0,409, sensitivity - 91,9% and 90,0%, specificity - 90,0% and 87,5%, respectively), allow to predict the probability of tumor recurrence.