Cognitive changes in lung cancer associated with increased blood-brain barrier leakage in patients with non-brain metastases

doi:10.21203/rs.3.rs-1879985/v1

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Cognitive changes in lung cancer associated with increased blood-brain barrier leakage in patients with non-brain metastases

https://doi.org/10.21203/rs.3.rs-1879985/v1

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Background: To explore the relationship between cognitive function and blood-brain barrier leakage in non-brain metastasis lung cancer and healthy controls.

Methods:75 lung cancers without brain metastasis and 29 healthy controls matched with age, sex, and education were evaluated by cognitive assessment, and the Patlak pharmacokinetic model was used to calculate the average leakage in each brain region according to the automated anatomical labelling atlas. After that, the relationships between cognitive and blood-brain barrier leakage were evaluated.

Results: Compared with healthy controls, the leakage of 3 brain regions were higher in patients with early lung cancers, and the leakage of 8 brain regions was higher in patients with advanced lung cancers. In contrast to early lung cancers, the leakage of 6 brain regions was increased in advanced lung cancers. The cognitive impairment of advanced lung cancers was mainly reflected in the damage to visuospatial/executive, and delayed recall. Brain regions with increased blood-brain barrier leakage showed negative correlations with visuospatial/executive, delayed recall, tumour size, and tumour marker (r=-0.35 to -0.21, P<0.05). Blood-brain barrier leakage was positively correlated with tumour size and tumour marker CYFRA21-1 (R=0.23 to 0.66, P<0.05).

Conclusion: An increase in blood-brain barrier leakage was found in non-brain metastases of advanced lung cancers that corresponded to decreased visuospatial/executive and delayed recall. With progression in lung cancer staging, blood-brain barrier shows higher leakage and may lead to brain metastases and lower cognitive development.

Lung cancer

Staging

Cognitive impairment

Neuroimaging

blood-brain barrier

Lung cancer (LC) is the most common cancer and the leading cause of cancer death in both men and women Feng et al., 2019; Sung et al., 2021). Due to untimely diagnosis, most lung cancers are advanced at the time of diagnosis Alberg et al., 2013). The incidence of brain metastases (BMs) ranges from 22–54% and can occur at different stages of tumor development, especially in patients with advanced disease Alberg et al., 2005). BM is present in 10% of patients at the time of initial diagnosis Villano et al., 2015). The brain is the only site of tumor recurrence in 50% of patients Hu et al., 2006). Many chemotherapeutic agents are relatively poor penetrators of the central nervous system (CNS), allowing tumor cells to survive and develop into BM in the CNS. Although recent therapeutic advances including intrathecal chemotherapy, molecular targeted therapies, and immunotherapy have somewhat prolonged the survival time of BM patients, the prognosis of BM remains poor with a median overall survival of 7–13 months Kondziolka et al., 2005). BM may lead to different focal neurological symptoms and cognitive dysfunction (Chen et al., 2007; Noh & Walbert, 2018).

The blood-brain barrier (BBB) is a selective "gatekeeper" composed of endothelial cells, pericytes, and astrocyte end-foot. BBB separates the brain from systemic circulation and protects it from foreign infectious and/or toxic agents (Arvanitis et al., 2020; Cheng & Perez-Soler, 2018; Fares, Kanojia, et al., 2020). It is estimated that BBB blocks the transport of about 98% of the molecules in systemic circulation (Pardridge, 2005). The integrity of the BBB is essential to block the entry of most tumor cells.

The pathogenesis of BM is complex, and BBB dysfunction is considered to be one of its pathogenic mechanisms. Metastasis of lung cancer cells to the brain requires cancer cells to invade the circulatory system from the primary site and colonize in brain parenchyma through the invasion of BBB (Fares, Fares, et al., 2020). Research has shown that BBB is damaged in this process, resulting in increasing permeability of BBB (Langley & Fidler, 2013). BBB dysfunction (BBBD) is also a feature of other brain diseases, such as stroke (Serlin et al., 2019), subarachnoid hemorrhage (Lublinsky et al., 2019), and epilepsy (Rüber et al., 2018). Recently considered as a potential biomarker for predicting outcome (Bar-Klein et al., 2017; Kamintsky et al., 2020; Lublinsky et al., 2019; Serlin et al., 2019). Although the detailed mechanism of BBBD is unknown, paracellular leakage due to dysfunction or downregulation of tight junction proteins, as well as enhanced endothelial barrier transport across cells, are considered to be pathogenic factors (Andreone et al., 2017; Zhang et al., 2017). Currently, there is no clinically standardized method to objectively assess changes in microvascular permeability in vivo.

Dynamic enhanced magnetic resonance imaging (DCE-MRI) is increasingly being used to assess cerebrovascular permeability in neurological diseases (Sweeney et al., 2019). The widely used DCE-MRI approach is based on extended Tofts or Patlak models (Patlak et al., 1983; Sourbron & Buckley, 2013; Tofts & Kermode, 1991). In lung cancer patients without brain metastasis, there is a lack of quantitative data on BBB leakage and a lack of understanding of the spatial scope of BBB. Therefore, we aim to quantify the BBB leakage in lung cancer patients without brain metastasis and to examine the relationship between BBB leakage and cognitive function.

2.1 Participant

This study was approved by the Ethics Committee of the third affiliated Hospital of Kunming Medical University (NO. SLKYLX202118). all subjects signed informed consent before participating in the research. This work was conducted by the principles of the Declaration of Helsinki and its later amendments.

This is a cross-sectional study of lung cancer patients, which plans to scan untreated patients and include age/sex-matched healthy controls (HCs). From August 2021 to February 2022, 75 lung cancer patients (39 patients with early-stage lung cancer and 36 patients with advanced lung cancer) from the Department of Thoracic Surgery, Third Affiliated Hospital of Kunming Medical University, and 29 HCs (enrolled through online advertisement, matched for age and gender) participated in this study. All participants were untreated (i.e., surgery, radiotherapy, or immunotherapy) before pathological confirmation. According to TNM (tumor, node, metastasis) staging (8th edition) (Detterbeck et al., 2017), early-stage patients are those with stage I, advanced-stage patients are those with stage II to IV. Some participants were excluded due to excessive head movement during scanning, contrast allergy, and calculation failure (Fig. 1). Exclusion criteria for all participants were: receipt of prophylactic cranial irradiation; the presence of brain metastases; known history of stroke, cranial trauma, epilepsy, Alzheimer's disease, Parkinson's disease, other acute psychiatric or neurological disorders; history of major medical illness (e.g., anemia, severe heart disease, thyroid dysfunction, or abnormal liver or kidney function); and severe vision or hearing loss.

2.2 MRI acquisition

All data were acquired on a 3.0 T MRI scanner (Discovery MR750, GE Healthcare, Waukesha, Wisconsin, USA) with a 21-channel receiver array head and neck coil, acquired in parallel. Tight but comfortable foam pads are used to minimize head movement; earplugs and headphones are used to reduce scanner noise. For each participant, routine MRI sequences, including T2 and T1 weighted imaging and T2 fluid-attenuated inversion recovery (FLAIR) imaging, were performed to ensure that there were no visible brain lesions or brain metastases.

The sequences for BBB assessment included the following steps: (1) a T1 -weighted 3D axial sequence with variable flip angles (3D-SPGR, TR 5.9ms, TE 2.0ms, flip angle 5° and 14°, FOV 24×20.4, acquisition matrix 256×180, slice thickness 4. 0 mm, interval 0, bandwidth 62.5kHz); and (3) a T1-weighted 3D axial dynamic scan (LAVA, TR 5.9ms, TE 2.0ms, flip angle 14°, FOV 24×20.4, acquisition matrix 256×180, slice thickness 4.0 mm, interval 0, bandwidth 62.5 kHz) acquired within 650 s after intravenous injection of the magnetic contrast gadolinium (0.05 mmol/kg, flow rate 3.0

mL/s).2.3 BBB data preprocessing

Because the contrast medium leakage caused by the blood-brain barrier leakage increases the T1-weighted signal in the tissue, the contrast medium leakage can be calculated to reflect the BBB leakage. To achieve this, SPM12 (University College London, www.fil.ion.ucl.ac.UK/spm) is first used to preprocess data. The specific steps include: image format conversion; head movement correction; image registration; image segmentation; standardization; smoothing; individual space conversion.

Previous studies have shown that Patlak model is the more accurate than other models in diseases with slight BBB damage (Barnes et al., 2016; Heye et al., 2016; Patlak et al., 1983). And using DCE-MRI to measure the subtle leakage of the BBB has moderate to excellent repeatability (Wong et al., 2017). Therefore, the Patlak model will be used to calculate the K^trans value in this study. The Patlak method uses a two-compartment model, in which it is assumed that there is no reflux and infinite flow, so the leakage rate is approximately the product of vascular permeability (P) and the surface area (S) per unit tissue mass. For the Patlak graphic method, the two main determinants of the accuracy of measuring BBB are the estimation of blood concentration curve based on T1 signal intensity and the determination of vascular input function (VIF)(Larsson et al., 2009) (Fig. 2). The common method of T1 mapping is to change the flip angle(Brookes et al., 1999). The determination step of VIF also plays a key role in the estimation of kinetic parameters. The VIF is calculated by selecting the region of interest (ROI) of the superior sagittal sinus (Lavini & Verhoeff, 2010). After that, the Patlak model is used to calculate the volume transfer constant K^trans (minite^− 1) based on MATLAB (R2017b). The K^trans value is used to reflect the leakage of BBB.

K^trans is calculated as voxels. Based on the AAL atlas (Tzourio-Mazoyer et al., 2002), the whole brain is divided into 116 brain regions, and each brain region is taken as ROI to extract the average K^trans value for statistical analysis.

The continuous variables were compared by ANOVA or Kruskal-Wallis test, and the classified variable ratio was compared by the χ ² test. All statistical analyses are carried out using the software R (version 3.6.3, http://www.r-project.org/). The R language and GraphPad Prism (9.0.0, GraphPad Software, Inc., San Diego, California) were used for visualization. Multiple comparisons are corrected by Bonferroni.

4.1 Demographic and clinical features

A summary of all detailed demographic data and histological diagnosis and tumor staging is shown in Table 1. There was no significant difference in sex, age, smoking, and KPS score between LCs and HCs (P > 0.05). The longest diameter of the tumor in the eLC group was smaller than that in the aLC group (P < 0.001). The tumor markers CEA, NSE, CYFRA21-1 and SCC in the aLC group were higher than those in the eLC group.

4.2 The BBB leakage in patients with lung cancer at different stages

The average K^trans value of each brain region of all participants was calculated (104 × 116 brain regions in total). Compared with the control group, the K^trans of TPOsup.L, POmid.L, and POmid.R increased in the eLC group, and the K^trans of aLC group increased in 8 brain regions and the whole cerebral gray matter (i.e., CAL.L, SOG.R, MOG.R, IOG.L, IOG.R, TPOmid.R, left cerebellum crus1, right cerebellum6). The BBB leakage of CAL.L, IOG.R, TPOmid.R, left cerebellum crus1, left cerebellum crus2 and right cerebellum6 increased with the progression of LC. (Figs. 3 and 4)

4.3 Cognitive impairment in patients with advanced lung cancer

The cognitive impairment of aLCs was mainly reflected in the damage of visuospatial/executive, and delayed recall. There was no significant difference between eLCs and HCs. and it was considered that the cognitive function of eLCs had not been impaired. Moreover, the damage of advanced lung cancer is more obvious than that of early patients. (Fig. 5)

4.4 correlation analysis between increased brain leakage and cognitive function in patients with lung cancer at different stages

To examine the correlation between increased brain areas of BBB leakage and cognitive function, we analyzed the correlation between K^trans value and cognitive function of participants. It was found that the K^trans of the right cerebellum 6 area and whole brain gray matter was negatively correlated with visuospatial/executive (P < 0.05), and the K^trans value of the right cerebellum 6 was also negatively correlated with delayed recall (P < 0.05). We further correlated the maximum tumor diameter, serum markers (CEA, NSE, CYFRA21-1, SCC) and brain areas with increased K^trans in LCs and found that tumor diameter was negatively correlated with visuospatial/executive and delayed recall (P < 0.05). CYFRA21-1 was negatively correlated with visuospatial/executive (P < 0.05). (Fig. 6)

We also examined the relationship between leakage increased brain areas and tumor size and serum tumor markers. It was found that the maximum tumor diameter correlated with CAL.L, IOG.L, IOG.R, TPOmid.L, TPOmid.R, left cerebellum crus1, left cerebellum crus2 were positively correlated (R = 0.24–0.66, p < 0.05); CYFRA21.1 was positively correlated with TPOmid.L, TPOmid.R, left cerebellum crus1, right cerebellum 6, ktransGray (R = 0.30–0.51, P < 0.05); CEA was positively correlated with ktransGray (R = 0.23, P < 0.05).

This study was the first to quantitatively image BBB leakage in lung cancer patients who had not yet developed brain metastases and found that aLC exhibited higher levels of BBB leakage in some brain regions and correlated with cognitive impairment in patients. These findings provide a critical step in determining the role of BBBD in the pathogenesis of brain metastases from lung cancer and highlight the BBB as a potential diagnostic and predictive target.

BMs cause severe, uncontrollable symptoms and reduce quality of life, such as paralysis, increased intracranial pressure, or seizures, and the incidence of BM has shown an upward trend in the last decade, but there has been little progress in treatment options and poor outcomes(Soffietti et al., 2017). Therefore, it is important to be able to detect early BM in patients with lung cancer who are more prone to develop BM and to provide enhanced adjuvant therapy for them. In this study, BBB leakage examination was performed in patients who had not yet developed visible brain metastases, and increased leakage was found in patients with progressive disease. This suggests an increased risk of brain metastasis.

The development of BM involves a series of interrelated steps, starting with the invasion of cancer cells into the intravascular and/or lymphatic system. Due to the lack of a lymphatic system in the central nervous system (CNS), the only possible way for cancer cells to reach the brain is through blood circulation. The circulating tumor cells (CTCs) may circulate into the brain's microcirculation and adapt to the brain's microenvironment, resulting in the formation of micro-metastases, which eventually form visible tumors through "metastatic colonization"(Hanahan & Weinberg, 2011; Paduch, 2016). However, metastatic cells that invade the CNS parenchyma must pass through the BBB. During this process, changes occur in the cerebral vascular endothelium(Bart et al., 2000), including impaired tight junction structures and increased perivascular gaps(Liebner et al., 2000). In addition, windows corresponding to the surrounding vascular system can be found in these vessels, and the number and activity of cytosolic vesicles are increased(Shibata, 1989). Therefore, these vessels may reflect those of the tumor tissue rather than those of the CNS endothelium. As a result of these structural alterations leading to increased BBB leakiness, plasma leaks into the extracellular space outside the vasculature(Nduom et al., 2013). And our findings coincide with this process.

DCE-MRI allows the leakage of the extracellular gap within each voxel to be assessed by pharmacokinetic parameters (K^trans), detecting leakage of the BBB in response to the destruction of the BBB. K^trans is defined as the volume transfer constant between the plasma and the extracellular space outside the blood vessel, and it is often used as a synonym for permeability(Tofts & Kermode, 1991). DCE-MRI has been widely used in neuro-oncology imaging(Bar-Klein et al., 2017; Kamintsky et al., 2020; Lublinsky et al., 2019; Rüber et al., 2018; Serlin et al., 2019). However, measuring leakage from a relatively intact BBB is not common. And the leakage of BBB we need to measure may be microleakage, so the patlak model is used to calculate K^trans because it is more accurate in measuring microleakage(Barnes et al., 2016; Heye et al., 2016; Patlak et al., 1983).

Our findings confirm that, compared to the HCs, LCs have higher levels of BBB leakage, especially more pronounced in aLCs. It suggests that as LC progress, more and higher leakage of the BBB may occur in brain areas and the brain BBB integrity suffers disruption. And these changes indicate changes in the cerebral vascular endothelium in these brain regions, damage to tight junction structures and increased perivascular gaps(Soffietti et al., 2017). This signals the possibility of micro-metastasis, or a shift from BBB to BTB, as BTB is often considered “leakier” than BBB. Therefore, without further clinical intervention, visible BM may develop. Early detection of increased BBB leakage and enhanced clinical intervention are important to prevent the development of BMs.

Cognitive impairment in cancer patients has been of concern and increases the risk of developing dementia(Heck et al., 2008; Lovelace et al., 2019). Functional impairment of visuospatial/executive and delayed recall was found in patients with advanced lung cancer, and the decrease was more obvious with the progression of the disease. It is suggested that the development of lung cancer will impair cognitive function, giving priority to visuospatial/executive and delayed recall, but the specific mechanism is unclear. Our study also found that with the progression of lung cancer, BBB leakage increased in more brain areas, and the more obvious the damage to visuospatial/executive and delayed recall. It is suggested that the impairment of BBB may be one of the causes of cognitive impairment. So, in the treatment of lung cancer, it is necessary to consider the cognitive impairment of patients, avoid inappropriate treatment, aggravate the cognitive impairment of patients, and reduce the quality of life.

The advantages of this study include no recruitment bias, and the time between clinical evaluation and neuroimaging regimens is close, usually, after clinical evaluation, an MRI examination is completed within 1 day. However, the sample size of our cohort is small, and our imaging scheme requires a gadolinium-based contrast agent, which may cause potential damage to the kidney. BBB imaging without contrast agents may have more extensive applicability.

This study is the first to study the BBB leakage and the relationship between BBB and cognitive function in different stages of lung cancer without brain metastasis, and obtain convincing evidence. With the development of lung cancer, the leakage of BBB increases, and cognitive function is impaired. In the treatment of lung cancer, the damage to cognitive function should be fully considered to avoid aggravating the damage and reducing the quality of life. Therefore, this study provides new preliminary evidence for individualized treatment of lung cancer.

LC, Lung cancer; HC, healthy control; BBB, blood-brain barrier; BBBD, BBB dysfunction; BMs, brain metastases; aLC, advanced lung cancers; aLC, advanced lung cancers; CNS, central nervous system; DCE-MRI, Dynamic enhanced magnetic resonance imaging; ROI, region of interest; VIF, vascular input function; AAL, anatomical labeling; CEA, carcinoembryonic antigen; NSE, neuron-specific enolase; CYFRA21-1, cytokeratins21-1; SCC, squamous cell carcinoma antigen; CAL.L, left calcarine fissure and surrounding cortex; SOG.R, right superior occipital gyrus; MOG.R, middle occipital gyrus; IOG.L, inferior occipital gyrus; TPOsup.L, temporal pole: superior temporal gyrus; TPOmid.R, temporal pole: middle temporal gyrus;

Acknowledgments

This study is a joint effort of many investigators and staff members, and their contribution is gratefully acknowledged. We especially thank all patients who participated in this study.

Ethical Approval and Consent to Participate

This study was approved by the Ethics Committee of the third affiliated Hospital of Kunming Medical University (NO. SLKYLX202118). all participants signed informed consent before participating in the research. This work was conducted by the principles of the Declaration of Helsinki and its later amendments.

Consent to Publish

The Author confirms:

That the work described has not been published before (except in the form of an abstract or as part of a published lecture, review, or thesis);

That it is not under consideration for publication elsewhere;

That its publication has been approved by all co-authors;

That its publication has been approved by the responsible authorities at the institution where the work is carried out.

Author Contributions

Da-Fu Zhang: Data curation, Methodology, Software, Writing-Original draft

preparation.

Yu-Qi Chen: Conceptualization, Writing- Reviewing and Editing.

Zhen-hui Li: Visualization, Investigation.

Xiu-Feng Xu: Supervision.

Ying-Ying Ding: Writing- Reviewing and Editing.

Bin-li Shang: Software

Zhi-Ping Zhang, Yin-Fu He: Data curation

All authors reviewed the manuscript.

Funding Sources

This work was supported by the National Natural Science Foundation of China (82060259, 81760296, 82001986); Yunnan Province High-Level Health Technical Talents (leading talents) (L-2019004, L-2019011); Yunnan Province Special Project for Famous Medical Talents of the “Ten Thousand Talents Program” (YNWRMY- 2018-040, YNWR-MY-2018-041); Yunnan digitalization, development and application of biotic resource (202002AA100007); The Outstanding Youth Science Foundation of Yunnan Basic Research Project (202101AW070001). Innovation Team of Kunming Medical University (CXTD202110). The Applied Basic Research Projects of Yunnan Province(2019FE001-083).

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Data Availability Statement

The data from this article cannot be shared publicly due to the privacy of the individuals that participated in the study. The data will be shared on reasonable request to the corresponding author.

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Table 1 Demographic and clinical features of patients with Lung cancer Data are expressed as `x ± s, n (%) or Interquartile Range（P₂₅,P₅₀,P₇₅）. ^aThe P values are obtained by using the χ2 test. ^bThe P values are obtained by using one-way ANOVA. ^cThe P values are obtained by using two-sample t-test. ^dThe P values are obtained by the Kruskal-Wallis test. ^*P<0.05 is considered significant. CEA, carcinoembryonic antigen. NSE, neuron-specific enolase. CYFRA21-1, cytokeratins21-1. SCC, squamous cell carcinoma antigen.

	Controls(n=29)	Early lung cancer (n=39)	Advanced lung cancer （n=36）	χ2/F/μ	P
gender
male/female	15/14	15/24	24/12	5.986	0.05^a
Age(mean±SD), year	51.07±9.67	55.59±8.23	56.06±8.99	3.059	0.051^b
Smoking(%)	10/29	9/30	16/20	3.84	0.147^a
Tumor diameter (cm) (mean±SD)		1.62±0.94	4.93±2.35	-8.103	0.000^*c
KPS score(mean±SD)	95.00±7.77	96.15±7.11	94.44±6.95	0.568	0.568^b
Pathological type				χ2
Squamous cell carcinoma		7	13	7.396	0.092^a
Adenocarcinoma		29	18
Small Cell Lung Cancer		3	5
Tumor markers （25%,50%,75%）				Z
CEA		1.53, 2.25, 3.57	1.87,4.38, 10.33	446.50	0.007^*d
NSE		9.60, 11.80, 13.40	11.75, 13.70 ,21.96	397.50	0.001^*d
CYFRA21-1		1,40, 2.00,2.60	2.625,4.500,7.025	223.00	0.000^*d
SCC		0.70,0.80,1.00	0.72,1.10,1.47	493.00	0.026^*d

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Cognitive changes in lung cancer associated with increased blood-brain barrier leakage in patients with non-brain metastases

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Abstract

Figures

1 Introduction

2 Materials And Methods

2.1 Participant

2.2 MRI acquisition

3 Statistical Analyses

4. Result

4.1 Demographic and clinical features

4.2 The BBB leakage in patients with lung cancer at different stages

4.3 Cognitive impairment in patients with advanced lung cancer

5 Discussion

6 Conclusion

Abbreviations

Declarations

References

Tables

Competing Interests

Supplementary Files

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