Novel method for rapid identification of micropapillary or solid components in early-stage lung adenocarcinoma

Intratumoral and peritumoral radiomics model for the preoperative prediction of cribriform component in invasive lung adenocarcinoma: a multicenter study

PURPOSE

This study aimed to investigate the predictive value of intratumoral and peritumoral radiomics model for the cribriform component (CC) of invasive lung adenocarcinoma (LUAD).

MATERIALS AND METHODS

The 144 patients with invasive LUAD from our center were randomly divided into training set (n = 100) and internal validation set (n = 44) in a ratio of 7:3, and 75 patients from center 2 were regarded as the external validation set. Clinical risk factors were examined using univariate and multivariate logistic regression to construct the clinical model. We extracted radiomics features from gross tumor volume (GTV), gross and peritumoral volume (GPTV), and peritumoral volume (PTV), respectively. Radiomics models were constructed with selected features. A combined model based on the optimal Radscore and clinically independent predictors was constructed, and its predictive performance was assessed by receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).

RESULTS

The area under curves (AUCs) of the GTV model were 0.882 (95% CI 0.817-0.948), 0.794 (95% CI 0.656-0.932), and 0.766 (95% CI 0.657-0.875) in the training, internal validation, and external validation sets, and the PTV model had AUCs of 0.812 (95% CI 0.725-0.899), 0.749 (95% CI 0.597-0.902), and 0.670 (95% CI 0.543-0.798) in the training, internal validation, and external validation sets, respectively. However, the GPTV radiomics model showed better predictive performance compared with the GTV and PTV radiomics models, with the AUCs of 0.950 (95% CI 0.911-0.989), 0.844 (95% CI 0.728-0.959), and 0.815 (95% CI 0.713-0.917) in the training, internal validation and external validation sets, respectively. In the clinical model, tumor shape, lobulation sign and maximal diameter were the independent predictors of CC in invasive LUAD. The combined model including independent clinical predictors and GPTV-Radscore show the considerable instructive to clinical practice, with the AUCs of 0.954(95% CI 0.918-0.990), 0.861(95% CI 0.752-0.970), and 0.794(95% CI 0.690-0.898) in training, internal validation, and external validation sets, respectively. DCA showed that the combined model had good clinical value and correction effect.

CONCLUSION

Radiomics model is a very powerful tool for predicting CC growth pattern in invasive LUAD and can help clinicians make the strategies of treatment and surveillance in patients with invasive LUAD.

The impact of postoperative adjuvant therapy on EGFR-mutated stage IA lung adenocarcinoma with micropapillary pathological subtypes

BACKGROUND

Micropapillary (MPP) adenocarcinoma is considered one of the most aggressive pathological types of lung adenocarcinoma (LADC). This retrospective study aimed to evaluate the prognostic significance and benefit of postoperative adjuvant therapy (PAT) in stage IA LADC patients with different proportions of MPP components.

MATERIALS AND METHODS

We retrospectively examined clinical stage IA LADC patients who underwent surgical resection between August 2012 and December 2019. In terms of the proportion of MPP components (TPM), the tumors were reclassified into three categories: MPP patterns absent (TPMN); low proportions of MPP components (TPML); and high proportions of MPP components (TPMH). The dates of recurrence and metastasis were identified based on physical examinations and were confirmed by histopathological examination.

RESULTS

Overall, 505 (TPMN, n = 375; TPML, n = 92; TPMH, n = 38) patients harboring EGFR mutations were enrolled in the study. Male sex (P = 0.044), high pathological stage (P < 0.001), and MPP pathological subtype (P < 0.001) were more frequent in the TPM-positive (TPMP) group than in the TPM-negative (TPMN) group. Five-year disease-free survival (DFS) rates were significantly lower in the TPMP group than in the TPMN group (84.5% vs. 93.4%, P = 0.006). In addition, patients with high proportions (greater than 10%) of MPP components had worse overall survival (OS) (91.0% vs. 98.9%, P = 0.025) than those with low proportions (5%≤ TPM ≤ 10%). However, postoperative EGFR tyrosine kinase inhibitors (TKIs) or adjuvant chemotherapy (ACT) cannot improve DFS and OS between EGFR-mutated patients with different proportions of MPP components.

CONCLUSION

MPP was related to earlier recurrence and shortened survival time, even in stage IA. Further research needs a larger sample size to clarify that EGFR-mutated stage IA patients with MPP components obtain survival benefits from adjuvant therapy.

The diagnostic potential role of thioredoxin reductase and TXNRD1 in early lung adenocarcinoma: A cohort study

BACKGROUND

Lung adenocarcinoma (LUAD) is the primary form of lung cancer, yet the reliable biomarkers for early diagnosis remain insufficient. Thioredoxin reductase (TrxR) is strongly linked to the occurrence, development, and drug resistance of lung cancer, making it a potential biomarker. However, further research is required to assess its diagnostic value in LUAD.

METHODS

A retrospective analysis was performed on patients who underwent pulmonary nodule resection at our center from 2018 to 2022. Clinical data, including preoperative TrxR levels, imaging, and laboratory characteristics, were identified as study variables. Two prediction models were constructed using multiple logistic regression, and their prediction performance was evaluated comprehensively. Besides, bioinformatics analyses of TrxR coding genes including differential expression, functional enrichment, immune infiltration, drug sensitivity, and single-cell landscape were performed based on TCGA database, which were subsequently validated by Human Protein Atlas.

RESULTS

A total of 506 eligible patients (72 benign lesions, 77 AISs, 185 MIAs and 172 IACs) were identified in the clinical cohort. Two TrxR-based models were developed, which were able to distinguish between benign and malignant pulmonary nodules, as well as pathological subtypes of LUAD, respectively. The models exhibited good predictive ability with all AUC values ranging from 0.7 to 0.9. Based on calibration curves and clinical decision analysis, the nomogram models showed high reliability. Functional analysis indicated that TXNRD1 primarily participated in cell cycle and lipid metabolism. Immune infiltration analysis showed that TXNRD1 has a strong association with immune cells and could impact immunotherapy. Then, we identified small molecular compounds that inhibit TXNRD1 and confirmed TXNRD1 expression by single-cell landscape and immunohistochemistry.

CONCLUSION

This study validated the diagnostic value of TrxR and TXNRD1 in clinical cohorts and transcriptional data, respectively. TrxR and TXNRD1 could be used in the risk diagnosis of early LUAD and facilitate personalized treatment strategies.

Downregulated CDH3 is correlated with a better prognosis for LUAD and decreases proliferation and migration of lung cancer cells

BACKGROUND

CDH3 is a glycoprotein with a single-span transmembrane domain that mediates cell-to-cell adhesion. Abnormal expression of CDH3 is associated with a poor prognosis in patients with breast, thyroid, colorectal carcinomas and glioblastoma. Soluble CDH3 in pleural effusions can be used as a marker for real-time monitoring of resistance to first- and second-generation EGFR-TKIs. The CDH3 mechanism underlying lung adenocarcinomas (LUADs) has not been established.

OBJECTIVE

This study analyzed the correlation between CDH3 expression and lung cancer prognosis and the effect of down-regulation CDH3 expression on the proliferation and migration of lung cancer cells.

METHODS

CDH3 expression was studied using the Oncomine, TIMER, PanglaoDB, and GEPIA databases. The effect of CDH3 on clinical prognosis was assessed with GEPIA, the PrognoScan database, and Kaplan-Meier plotter. The relationship between CDH3 to immune infiltrating cells was explored using TIMER and TISIDB. The function of CDH3 in lung cancer cell lines was determined by CCK-8 and wound healing assays in vitro. Furthermore, RNA sequencing was used to identify key signaling pathways and differentially-expressed genes.

RESULTS

LUAD tissues had higher CDH3 expression compared with normal tissues and were associated with worse overall survival in patients with LUAD. CDH3 expression had positive associations with infiltration of CD4 + T cells, Tregs and exhausted T cells, but negative associations with infiltration of B cells in patients with LUAD. CCK-8 and wound healing assays revealed that downregulation of CDH3 inhibited the proliferation and migration of cells. KEGG analysis revealed that the TGF-beta signaling pathways were demonstrated to be enriched pathways for genes negatively regulated by knockdown of CDH3.

CONCLUSION

CDH3 expression affects proliferation and migration of lung cancer cells and might serve as a potential prognostic marker in LUAD patients.

Comparison and fusion prediction model for lung adenocarcinoma with micropapillary and solid pattern using clinicoradiographic, radiomics and deep learning features

To investigate whether the combination scheme of deep learning score (DL-score) and radiomics can improve preoperative diagnosis in the presence of micropapillary/solid (MPP/SOL) patterns in lung adenocarcinoma (ADC). A retrospective cohort of 514 confirmed pathologically lung ADC in 512 patients after surgery was enrolled. The clinicoradiographic model (model 1) and radiomics model (model 2) were developed with logistic regression. The deep learning model (model 3) was constructed based on the deep learning score (DL-score). The combine model (model 4) was based on DL-score and R-score and clinicoradiographic variables. The performance of these models was evaluated with area under the receiver operating characteristic curve (AUC) and compared using DeLong's test internally and externally. The prediction nomogram was plotted, and clinical utility depicted with decision curve. The performance of model 1, model 2, model 3 and model 4 was supported by AUCs of 0.848, 0.896, 0.906, 0.921 in the Internal validation set, that of 0.700, 0.801, 0.730, 0.827 in external validation set, respectively. These models existed statistical significance in internal validation (model 4 vs model 3, P = 0.016; model 4 vs model 1, P = 0.009, respectively) and external validation (model 4 vs model 2, P = 0.036; model 4 vs model 3, P = 0.047; model 4 vs model 1, P = 0.016, respectively). The decision curve analysis (DCA) demonstrated that model 4 predicting the lung ADC with MPP/SOL structure would be more beneficial than the model 1and model 3 but comparable with the model 2. The combined model can improve preoperative diagnosis in the presence of MPP/SOL pattern in lung ADC in clinical practice.

Comparative genomics between matched solid and lepidic portions of semi-solid lung adenocarcinomas

BACKGROUND

Genetic changes that drive the transition from lepidic to invasive cancer development within a radiographic ground glass or semi-solid lung lesion (SSL) are not well understood. Biomarkers to predict the transition to solid, invasive cancer within SSL are needed.

METHODS

Patients with surgically resected SSL were identified retrospectively from a surgical database. Clinical characteristics and survival were compared between stage I SSL (n = 65) and solid adenocarcinomas (n = 120) resected during the same time period. Areas of normal lung, in situ lepidic, and invasive solid tumor were microdissected from within the same SSL specimens and next generation sequencing (NGS) and Affymetrix microarray of gene expression were performed.

RESULTS

There were more never smokers, Asian patients, and sub-lobar resections among SSL but no difference in 5-year survival between SSL and solid adenocarcinoma. Driver mutations found in both lepidic and solid invasive portion were EGFR (43%), KRAS (21%), and DNMT3A (5%). CEACAM5 was the most upregulated gene found in solid, invasive portions of SSL. Lepidic and invasive solid areas had many similarities in gene expression, however there were some significant differences with the gene SPP1 being a unique biomarker for the invasive component of a SSL.

CONCLUSIONS

Common lung cancer driver mutations are present in in situ lepidic as well as invasive solid portions of a SSL, suggesting early development of driver mutations. CEACAM5 and SPP1 emerged as promising biomarkers of invasive potential in semi-solid lesions. Other studies have shown both genes to correlate with poor prognosis in lung cancer and their role in evolution of semi-solid lung lesions warrants further study.

Adding predictive and diagnostic values of pulmonary ground-glass nodules on lung cancer via novel non-invasive tests

Pulmonary ground-glass nodules (GGNs) are highly associated with lung cancer. Extensive studies using thin-section high-resolution CT images have been conducted to analyze characteristics of different types of GGNs in order to evaluate and determine the predictive and diagnostic values of GGNs on lung cancer. Accurate prediction of their malignancy and invasiveness is critical for developing individualized therapies and follow-up strategies for a better clinical outcome. Through reviewing the recent 5-year research on the association between pulmonary GGNs and lung cancer, we focused on the radiologic and pathological characteristics of different types of GGNs, pointed out the risk factors associated with malignancy, discussed recent genetic analysis and biomarker studies (including autoantibodies, cell-free miRNAs, cell-free DNA, and DNA methylation) for developing novel diagnostic tools. Based on current progress in this research area, we summarized a process from screening, diagnosis to follow-up of GGNs.

Serum tumor markers level and their predictive values for solid and micropapillary components in lung adenocarcinoma

Background

This study aims to reveal the serum tumor marker (STM) levels in lung adenocarcinoma (LUAD) histological subtypes and evaluate their values in predicting the solid and micropapillary components (SMC).

Methods

We retrospectively analyzed 3100 invasive LUAD patients between January 2017 and December 2020. Associations between preoperative STMs (CEA, CYFRA21‐1, CA199, CA724, NSE, AFP) and LUAD subtypes were evaluated. Multivariate regression analyses were used to determine the independent predictors. Predictive models for SMC were constructed and AUC (area under the curve) was calculated.

Results

CEA and CYFRA21‐1 levels differed across the LUAD histological subtypes, with the SPA (solid‐predominant adenocarcinoma) having the highest level and the LPA (lepidic‐predominant adenocarcinoma) harboring the lowest level (p <0.001). Tumors with SMC also had higher CEA and CYFRA21‐1 levels than those absence of SMC. Gender, tumor size, CEA, Ki‐67, EGFR mutation (solid components only), and tumor differentiation were significantly independently associated with the containing of SMC. Patients were split into two data sets (training set: 2017–2019 and validation set: 2020). The model with gender and tumor size yielded an AUC of 0.723 (training set) and 0.704 (validation set) for the solid component. Combination of CEA, gender, and tumor size led to a significant increase in the predictive accuracy (training set: 0.771, p = 0.009; validation set: 0.747, p = 0.034). The AUC of the model for micropapillary component with only gender and tumor size was 0.699 and 0.711 in the training set and validation set, respectively. Integration of CEA with gender and tumor size significantly improved the predictive performance with an AUC of 0.746 (training set, p = 0.045) and 0.753 (validation set, p <0.001).

Conclusion

Serum CEA and CYFRA21‐1 varied considerably according to LUAD histological subtypes. The combination of serum CEA and other factors showed prominent values in predicting the SMC.

Cryobiopsy as a reliable technique for the preoperative identification of micropapillary/solid components in early-stage lung adenocarcinoma

OBJECTIVES

Micropapillary (MIP) and solid (SOL) subtypes of early-stage lung adenocarcinomas are associated with lymph node metastasis and local recurrence after limited resection. Preoperative identification of these components may influence the decisions of treatment strategy, additional lymph node evaluation, indication for limited resection, and extent of lymph node dissection. However, conventional biopsy specimens are insufficient for identifying these subtypes, especially MIP components. Cryobiopsy can collect larger tissue samples with fewer crush artifacts than conventional forceps biopsy, which would be helpful for detecting MIP/SOL components. Thus, this study aimed to analyze the feasibility of using cryobiopsy for MIP/SOL subtype detection.

MATERIAL AND METHODS

Consecutive patients who underwent surgery for clinical IA lung cancer following a preoperative diagnosis of adenocarcinoma by cryobiopsy at our institution between October 2017 and July 2019 were retrospectively examined. The concordance rate of MIP/SOL subtypes between the specimens obtained by cryobiopsy and surgery was investigated.

RESULTS

In total, 115 patients were evaluated. There were 26 (22.6%) and 14 (12.2%) patients with MIP and SOL subtypes, respectively. For concordance of MIP/SOL subtypes, the sensitivity was 65.7% (95% confidence interval [CI]: 57.7-65.7%). For the primary or secondary predominant patterns, a more satisfactory concordance rate of 72.2% (95% CI: 52.6-86.2%) was obtained. On assessing each subtype, high sensitivity was noted in SOL-predominant patterns (85.7%, 95% CI: 56.5%-96.0%) and MIP-secondary predominant patterns (83.3%, 95% CI: 45.8-97.0%). However, SOL-secondary predominant patterns revealed low sensitivity (0%, 95% CI, 0-38.2%). Overall, the MIP subtypes had higher sensitivity than the SOL subtypes (65.4% vs. 50.0%).

CONCLUSION

Cryobiopsy could be reliable for identifying MIP/SOL components, especially the MIP component, in clinical stage IA adenocarcinomas.

Surgery without preoperative histological confirmation of lung cancer: what is the current clinical practice?

BACKGROUND

There are discordances in the guidelines regarding the need to acquire histological diagnosis before surgical treatment of (presumed) lung cancer. Preoperative histological confirmation is always encouraged in this setting to prevent unnecessary surgery or when sublobar resection for small-sized tumors is considered. The aim of this retrospective cohort study was to assess the proportion of patients undergoing lung cancer resection in the Netherlands without preoperative pathological confirmation, based on the intraoperative pathological diagnosis (IOD) rate, and to determine characteristics that may influence IOD frequency.

METHODS

Data on 10,226 patients, who underwent surgical treatment for lung cancer from 2010 to 2015, were retrieved from the Netherlands National Cancer Registry. We registered an IOD when the date of diagnosis equaled the date of the first surgical intervention. Tabulations and multivariable logistic regression were used to identify predictive parameters for IOD.

RESULTS

36% of surgical procedures were classified as IOD, and decreased with increasing tumor size and extent of surgery (57% for segmentectomy, 39% for lobectomy and 11% for pneumonectomy). IOD was more frequently observed in adenocarcinoma (41%), varied between hospitals from 13% to 66% and was less common when patients were referred from a hospital where thoracic surgery was not performed. Previous history of cancer did not affect IOD.

CONCLUSIONS

More than one-third of patients with suspected lung cancer in the Netherlands was operated without preoperative histological confirmation. There was significant variation in IOD rates between different hospitals, which deserves further detailed analysis when striving for uniform surgical quality of care for patients with lung cancer.

Prediction of micropapillary and solid pattern in lung adenocarcinoma using radiomic values extracted from near-pure histopathological subtypes

OBJECTIVES

Near-pure lung adenocarcinoma (ADC) subtypes demonstrate strong stratification of radiomic values, providing basic information for pathological subtyping. We sought to predict the presence of high-grade (micropapillary and solid) components in lung ADCs using quantitative image analysis with near-pure radiomic values.

METHODS

Overall, 103 patients with lung ADCs of various histological subtypes were enrolled for 10-repetition, 3-fold cross-validation (cohort 1); 55 were enrolled for testing (cohort 2). Histogram and textural features on computed tomography (CT) images were assessed based on the "near-pure" pathological subtype data. Patch-wise high-grade likelihood prediction was performed for each voxel within the tumour region. The presence of high-grade components was then determined based on a volume percentage threshold of the high-grade likelihood area. To compare with quantitative approaches, consolidation/tumour (C/T) ratio was evaluated on CT images; we applied radiological invasiveness (C/T ratio > 0.5) for the prediction.

RESULTS

In cohort 1, patch-wise prediction, combined model (C/T ratio and patch-wise prediction), whole-lesion-based prediction (using only the "near-pure"-based prediction model), and radiological invasiveness achieved a sensitivity and specificity of 88.00 ± 2.33% and 75.75 ± 2.82%, 90.00 ± 0.00%, and 77.12 ± 2.67%, 66.67% and 90.41%, and 90.00% and 45.21%, respectively. The sensitivity and specificity, respectively, for cohort 2 were 100.0% and 95.35% using patch-wise prediction, 100.0% and 95.35% using combined model, 75.00% and 95.35% using whole-lesion-based prediction, and 100.0% and 69.77% using radiological invasiveness.

CONCLUSION

Using near-pure radiomic features and patch-wise image analysis demonstrated high levels of sensitivity and moderate levels of specificity for high-grade ADC subtype-detecting.

KEY POINTS

• The radiomic values extracted from lung adenocarcinoma with "near-pure" histological subtypes provide useful information for high-grade (micropapillary and solid) components detection. • Using near-pure radiomic features and patch-wise image analysis, high-grade components of lung adenocarcinoma can be predicted with high sensitivity and moderate specificity. • Using near-pure radiomic features and patch-wise image analysis has potential role in facilitating the prediction of the presence of high-grade components in lung adenocarcinoma prior to surgical resection.

Procedure-specific prognostic impact of micropapillary subtype may guide resection strategy in small-sized lung adenocarcinomas: a multicenter study

Background:

Limited resection has gradually become an acceptable treatment for lung adenocarcinomas (ADCs) presenting as ground-glass nodules (GGNs). However, its role in lung ADCs presenting as pure solid nodules (PSN) remains unclear. In this study, we aimed to identify potential candidates for limited resection in lung ADCs presenting as PSN.

Methods:

We retrospectively reviewed 772 patients from seven hospitals with lung ADCs ⩽2 cm, presenting as PSN on computed tomography scans, who had undergone surgery between 2009 and 2013. Histological subtypes were listed in 5% increments. To investigate the value of histological subtypes in surgical decision making, five pathologists prospectively evaluated the feasibility of identifying histological subtypes using frozen section (FS) in two cohorts.

Results:

The percentage of micropapillary (MIP) subtype had a striking impact on recurrence-free survival (RFS) and overall survival (OS) for lung ADCs ⩽2 cm presenting as PSNs. In multivariable Cox analysis, segmentectomy was significantly associated with worse RFS and OS in patients with MIP >5% than lobectomy, but not in those with MIP ⩽5%. With wedge resection, worse RFS and OS were observed in patients with MIP >5% and those with MIP ⩽5% than lobectomy. The sensitivity and specificity for detecting MIP by FS were 74.2% and 85.6%, respectively, with substantial inter-rater agreement.

Conclusion:

Segmentectomy and lobectomy had similar oncological outcomes in patients with lung ADCs ⩽2 cm presenting as PSN with MIP ⩽5%. Randomized trials are necessary to validate the feasibility of intraoperative FS to choose candidates for segmentectomy.

Novel prognostic model for stratifying survival in stage I lung adenocarcinoma patients

PURPOSE

We combined conventional clinical and pathological characteristics and pathological architectural grading scores to develop a prognostic model to identify a specific group of patients with stage I lung adenocarcinomas with poor survival following surgery.

METHODS

This retrospective study included 198 patients with stage I lung adenocarcinomas recruited from 2004 to 2013. Multivariate analyses were used to confirm independent risk factors, which were checked for internal validity using the bootstrapping method. The prognostic scores, derived from β-coefficients using the Cox regression model, classified patients into high- and low-risk groups. The predictive performance and discriminative ability of the model were assessed by the area under the receiver operating characteristic curve (AUC), concordance index (C-index) and Kaplan-Meier survival analyses.

RESULTS

Three risk factors were identified: T2 (rounding of β-coefficients = 81), necrosis (rounding of β-coefficients = 67), and pathological architectural score of 5-6 (rounding of β-coefficients = 58). The final prognostic score was the sum of points. The derived prognostic scores stratified patients into low- (score ≤ 103) and high- (score > 103) risk groups, with significant differences in 5-year overall survival (high vs. low risk: 49.3% vs. 88.0%, respectively; hazard ratio: 4.55; p < 0.001). The AUC for the proposed model was 0.717. The C-index of the model was 0.693.

CONCLUSION

An integrated prognostic model was developed to discriminate resected stage I adenocarcinoma patients into low- and high-risk groups, which will help clinicians select individual treatment strategies.

Challenges for real-time intraoperative diagnosis of high risk histology in lung adenocarcinoma: A necessity for sublobar resection

Recently, the incidence of small, peripheral lung adenocarcinoma has been increasing as lung cancer screening with radiologic examination is more widely performed. Tumor size is one of the determinants of the prognostic outcome in clinically node-negative lung adenocarcinoma. Sublobar resection has been proposed as one of the minimally invasive surgical options for small-sized adenocarcinomas. Despite the lack of robust clinical trial evidence, sublobar resection has become more popular, especially in developed countries where less extensive surgery may be of benefit in a population where the age of the elderly is growing. However, high risk histologic features such as micropapillary subtype and tumor spread through air space (STAS) have been associated with a significantly higher risk of local recurrence after sublobar resection, but not after lobectomy. Surgical decision-making based on frozen section diagnosis of high risk histologic features may be useful to prevent local control failure after sublobar resection. At the present time, there is little evidence to demonstrate the diagnostic accuracy of identifying high risk histologic features on frozen section. One study has so far demonstrated that diagnostic accuracy of identifying STAS is higher than that of identifying the micropapillary subtype. Additionally, the presence of STAS has been found to be more strongly associated with local recurrence in patients who had undergone sublobar resection. Although further investigation is required for validation of this finding, STAS diagnosis on frozen section may shed further light on intraoperative surgical decision-making during sublobar resection. To this end, we review the recently published data on the intraoperative identification of high risk features.

Fucosyltransferase 4 and 7 mediates adhesion of non-small cell lung cancer cells to brain-derived endothelial cells and results in modification of the blood-brain-barrier: in vitro investigation of CD15 and CD15s in lung-to-brain metastasis

PURPOSE

Metastatic non-small cell lung (NSCLC) cancer represents one of the most common types of brain metastasis. The mechanisms involved in how circulating cancer cells transmigrate into brain parenchyma are not fully understood. The aim of this work was to investigate the role of fucosylated carbohydrate epitopes CD15 and sialyated CD15s in cancer adhesion to brain-derived endothelial cells and determine their influence in blood-brain barrier (BBB) disruption METHODS: Three distinct, independent methods were used to measure brain endothelial integrity and include voltohmmeter (EVOM™), impedance spectroscopy (CellZscope®) and electric cell-substrate impedance sensing system (ECIS™). Two fucosyltransferases (FUT4 and 7) responsible for CD15 and CD15s synthesis were modulated in four human cancer cell lines (three lung cancer and one glioma).

RESULTS

Overexpression of CD15 or CD15s epitopes led to increase in adhesion of cancer cells to cerebral endothelial cells compared with wild-type and cells with silenced CD15 or CD15s (p < 0.01). This overexpression led to the disruption of cerebral endothelial cell monolayers (p < 0.01). Knockdown of FUT4 and FUT7 in metastatic cancer cells prevented disruption of an in vitro BBB model. Surprisingly, although the cells characterised as 'non-metastatic', they became 'metastatic' -like when cells were forced to over-express either FUT4 or FUT7.

CONCLUSIONS

Results from these studies suggest that overexpression of CD15 and CD15s could potentiate the transmigration of circulating NSCLC cells into the brain. The clinical significance of these studies includes the possible use of these epitopes as biomarkers for metastasis.