Negative impact of the microvascular area to tumor area ratio on the response to EGFR tyrosine kinase inhibitors in non-small cell lung cancer with EGFR mutation

doi:10.21203/rs.3.rs-2462834/v1

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Negative impact of the microvascular area to tumor area ratio on the response to EGFR tyrosine kinase inhibitors in non-small cell lung cancer with EGFR mutation

https://doi.org/10.21203/rs.3.rs-2462834/v1

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Purpose

Microvessel density plays an essential role in tumor development. However, whether a tumor microenvironment, abundant in microvessels, affects epidermal growth factor receptor–tyrosine kinase inhibitor (EGFR-TKI) efficacy in patients with non-small cell lung cancer (NSCLC) and EGFR mutations remains unclear. We aimed to investigate the impact of tumor microvessels on EGFR-TKI efficacy in patients with NSCLC and EGFR mutations.

Methods

We retrospectively studied the data of 40 post-operative patients with recurrent NSCLC and EGFR mutations who received EGFR-TKIs as a first-line treatment at Kumamoto University Hospital between January 2010 and February 2021. Tumor sections were retrieved from the tissue registry and analyzed for CD34-positive microvessels using immunohistochemical techniques. The microvascular area ratio (MVR), which is the CD34-positive microvascular area compared to the total tumor area, was measured using StrataQuest. The predictive value of MVR on treatment outcome, assessed via progression-free survival (PFS), was evaluated using a multivariate Cox proportional hazard model.

Results

The median MVR and PFS values of EGFR-TKI were 0.058 (range, 0.013–0.094) and 610 d (range, 102–2807 d), respectively. The median PFS in the high MVR group (≥ 0.058) was significantly shorter than that in the low MVR group (< 0.058; 296 d [95% confidence interval [CI]: 217–374 d] vs. 918 d [95% CI: 279–1556 d], P = 0.002). Multivariate analysis revealed that high MVR was an independent negative predictor of PFS (hazard ratio, 3.21 [95% CI: 1.18–8.76], P = 0.022).

Conclusions

High MVR may critically affect EGFR-TKI resistance in patients with NSCLC and EGFR mutations.

non-small cell lung cancer

EGFR-TKI

microvascular area

microvascular density

Tumor angiogenesis plays a crucial role in cancer progression and distant metastasis. Compared to normal vasculature, tumor vasculature resulting from angiogenesis has abnormal structural and functional features, such as tortuosity, leakage, ramification, and poor pericyte support (Carmeliet and Jain, 2000). These blood vessels characterized by high permeability lead to interstitial hypertension, which decreases drug delivery into the tumor and is likely to lead to resistance to treatment (Heldin et al., 2004).

Microvascular density (MVD) based on pathological methods is generally recognized as an indicator of tumor angiogenesis in various cancers, including lung cancer. MVD is calculated as the ratio of microvascular number per area of cancer tissue and has been reported to be a prognostic factor in lung and other types of cancers (Balac et al., 2012; Chen et al., 2014; Li et al., 2015; Zhang et al., 2021; Zhao et al., 2012). However, assessment of MVD, in which observers count the number of microvessels via immunohistochemistry staining of vascular endothelial cells, involves the subjectivity of observers, such as in determining the size and morphology of microvessels (Vermeulen et al., 1997). Development of quantitative evaluation methods based on image analysis software has enabled automatic analysis of the microvascular area. These analyses are expected to allow for more objective and reproducible measurements for microvascular evaluations.

Epidermal growth factor receptor (EGFR) mutations are the most common driver mutations in non-small cell lung cancer (NSCLC) and are detected in approximately 40% of lung adenocarcinomas in Asian populations (Yatabe et al., 2015). EGFR tyrosine kinase inhibitors (EGFR-TKIs) for patients with NSCLC with EGFR mutations provided therapeutic benefits compared to cytotoxic anticancer agents in several randomized phase III studies and are used as the standard treatment in the first-line setting (Mitsudomi et al., 2010; Mok et al., 2009; Soria et al., 2018; Wu et al., 2014). In EGFR mutation-positive adenocarcinoma, a tumor microenvironment with abundant microvessels was reported to be associated with aggressive behavior (Saruwatari et al., 2016); however, the clinical impact of tumor microvessels on the efficacy of EGFR-TKIs in EGFR mutation-positive NSCLC is unclear.

In this study, we measured tumor microvessel areas (MVAs) using image analysis software and calculated the microvascular to tumor area ratio (MVR), which is the microvessel areas divided by the field view area. Additionally, we aimed to clarify the impact of MVR on the efficacy of EGFR-TKIs in patients with NSCLC with EGFR mutations.

Study design and patients

This study included 40 consecutive post-operative recurrent NSCLC patients with EGFR mutations who were treated with EGFR-TKIs as first-line treatment at Kumamoto University Hospital between 1 January 2010 and 28 February 2021. We retrospectively collected the following data from the medical records: age, sex, smoking history, Eastern Cooperative Oncology Group (ECOG) performance status (PS), histology, pathological stage, EGFR mutation status, and the type of EGFR-TKI (gefitinib, erlotinib, afatinib, or osimertinib). EGFR mutations were examined using the Cobas ^® EGFR mutation test v2 (Roche Molecular Systems Inc., Pleasanton, CA, USA) or Oncomine Dx Target Test (Thermo Fisher, Waltham, MA, USA).

This study was approved by our institutional review board (IRB number 2364) and conducted in accordance with the Declaration of Helsinki. Informed consent was waived due to the retrospective nature of the study and was obtained using the opt-out method on the website of Kumamoto University Hospital.

Immunohistochemical analysis

Sections of formalin-fixed, paraffin-embedded tissues were depleted of paraffin and hydrated. They were incubated with 3% H₂O₂ for 5 min, washed with 0.05% Tween in Tris-buffered saline (TBST), exposed to blocking buffer (5% goat serum and 0.5% bovine serum albumin in phosphate-buffered saline [PBS]) in PBS for 10 min at room temperature, and incubated with mouse anti-CD34 antibodies (ab8536; clone QBEND-10; Abcam, Cambridge, UK) for 60 min. They were then washed with TBST, incubated with biotinylated secondary antibodies (Vector Laboratories, CA, USA) for 10 min at room temperature, and washed again, after which immune complexes were detected using an avidin-peroxidase complex (Vector Laboratories) and 3,3′-diaminobenzidine (Vector Laboratories). The sections were counterstained with Mayer’s hematoxylin, dehydrated using a graded series of ethanol, and mounted in Marinol (Muto Pure Chemicals, Tokyo, Japan).

Assessment of microvessels

Three images with the highest density of CD34-positive microvessels as the hotspot field of the tumor section were captured using a BX51 microscope (Olympus, Tokyo, Japan) at 200 × magnification. The number of CD34-positive microvessels was counted by two independent investigators (M.A. and K.S.). MVD was recorded as the average count of CD34-positive microvessels in three images. The MVAs in each image were automatically measured using StrataQuest (TissueGnostics, Vienna, Austria). The MVR in each image was calculated as the area occupied by CD34-positive microvessels divided by the total area of the field of view (area of 0.175 mm² per field of view). The MVR in each case was recorded as the average MVR of three images. Representative images of the MVR measurements are shown in Fig. 1.

Clinical outcome parameter

Progression-free survival (PFS) was calculated from the initial date of EGFR-TKI therapy to the date of progressive disease or last follow-up. Overall survival (OS) was calculated from the initial date of EGFR-TKI therapy to the date of death or last follow-up. The best tumor response was evaluated based on the Response Evaluation Criteria in Solid Tumours guidelines version 1.1.

Statistical analysis

Chi-square test, Fisher’s exact test, or Mann-Whitney U test was used to investigate the association of clinical factors. The Spearman's rank correlation coefficient was used to assess the correlation between MVD and MVR. Survival curves were generated using the Kaplan-Meier method and compared using the log-rank test. Univariate and multivariate analyses were performed using a Cox proportional hazard model to identify independent predictive factors of PFS and OS. Age, sex, smoking, PS, pathological stage, EGFR mutation type and MVR were included in multivariable model as covariates. All statistical analyses were performed using SPSS (version 23.0; IBM, Armonk, NY, USA). Statistical significance was set at P < 0.05.

Patient characteristics

The median age at diagnosis was 71.5 years. Of the patients, 22 (55%) were male, 36 (90%) had ECOG PS 0–1, 38 (95%) had adenocarcinoma, 19 (48%) had pathological stage I, 19 (48%) had vascular invasion, and 15 (38%) had pleural invasion (Table 1). Regarding the type of EGFR mutation, 24 patients (60%) had exon19 deletions and 15 patients (37.5%) had exon 21 mutations. The EGFR-TKI drugs administered as first-line treatment for post-operative recurrence were as follows: gefitinib in 11 patients (28%); erlotinib in 7 (18%); afatinib 11 (28%); and osimertinib 11 (28%).

Table 1

Baseline patient characteristics
		N = 40
Age, years	Median (range)	71.5(43–89)
Sex	Male Female	22 18
Smoking	Yes No	17 23
ECOG PS	0 1 2 3 4	20 16 3 0 1
Histology	Ad Non-Ad	38 2
EGFR mutation type	Exon 19 deletions Exon 21 mutations L858R L861Q	24 15 1
Vascular invasion	Absence Presence	17 23
Pleural invasion	Absence Presence	21 19
Pathological stage	I II III	19 12 9
Abbreviations: ECOG PS, Eastern Cooperative Oncology Group performance status; Ad, adenocarcinoma; EGFR epidermal growth factor receptor mutation

Assessment of correlation between MVD and MVR

The median MVD and MVR were 123/mm² (range, 70–470) and 0.058 (range, 0.013–0.094), respectively. Scatter plots of the MVD and MVR data are shown in Fig. 2. A significant moderate positive correlation was observed between MVD and MVR (r = 0.47, P = 0.020).

Comparison of clinicopathological features according to MVR

Using the median MVR as the cut-off value, we divided the patients into high (≥ 0.058) and low (< 0.058) MVR groups. No significant difference in clinicopathological factors was observed between the two groups (Table 2).

Table 2

Patient characteristics and clinicopathological features according to MVR status
		MVR
		High N = 20 (%)		Low N = 20 (%)			P
Age, years	Median (range)	72.5 (46–89)		71 (43–85)			0.659
Sex	Male Female	13 7	(75) (25)	9 11	(35) (65)	0.341
Smoking	Yes No	11 9	(55) (45)	6 14	(30) (70)		0.200
ECOG PS	0–1 2–4	17 3	(85) (15)	20 0	(100) (0)		0.231
Histology	Ad Non-Ad	19 1	(95) (5)	19 1	(95) (5)		1.000
Vascular invasion	Absence Presence	8 12	(40) (60)	15 5	(75) (25)		0.054
Pleural invasion	Absence Presence	14 6	(70) (30)	7 13	(35) (65)		0.056
Pathological stage	I-Ⅱ III	16 4	(80) (20)	15 5	(75) (15)		1.000
EGFR mutation type	Exon 19 deletions Exon 21 mutations	9 11	(45) (55)	15 5	(75) (25)		0.105
Abbreviations: ECOG PS, Eastern Cooperative Oncology Group performance status; Ad, adenocarcinoma; EGFR, epidermal growth factor receptor mutation

Tumor response, PFS, and OS analyses with EGFR-TKI according to MVR

Among the 30 patients with measurable lesions, 4 had complete response, 17 had partial response, 5 had stable disease, 1 had progressive disease, and 3 were not evaluable (Supplementary Table 1). The best objective response rate was 73% (95% confidence interval [95% CI]:52.0–83.5), and no significant difference was observed between the high and low MVR groups.

The median follow-up time from the initiation of EGFR-TKI therapy in the first-line setting was 1059.5 d (range, 120–2807 d). The median PFS and OS were 610 d (range 102–2807 d) and 1602 d (146–2933 d), respectively. The median PFS was significantly shorter in the high MVR group than in the low MVR group (296 d [95% CI: 217–374 d] vs. 918 d [95% CI: 279–1556 d], P = 0.002; Fig. 3a). However, no significant differences in OS were observed between the high and low MVR groups (1586 d [95% CI: 422–2749 d] vs. 1839 d [95% CI: 1361–2316 d], P = 0.355; Fig. 3b).

Univariate and multivariate analysis for PFS and OS

The univariate and multivariate analyses of PFS and OS are summarized in Table 3. Univariate analysis showed that PFS was significantly associated with MVR (HR: 3.25, 95% CI: 1.48–7.16, P = 0.003). Multivariate analysis revealed that only high MVR (HR: 3.21, 95% CI: 1.18–8.76, P = 0.022) were significant independent negative predictive factors for PFS after first-line EGFR-TKI treatment.

Table 3. Univariate and multivariate analysis for PFS (A) and OS (B)

(A)

		Univariate		Multivariate
		HR (95%CI)	P	HR (95%CI)	P
Age	<75 years	Ref	0.630	Ref
	≥75 years	0.82 (0.36-1.87)		1.12 (0.40-3.16)	0.830
Sex	Male	Ref	0.371	Ref
	Female	1.42 (0.66-3.04)		3.77 (1.00-14.23)	0.050
Smoking	No	Ref	0.405	Ref
	Yes	0.72 (0.33-1.56)		0.39 (0.87-1.78)	0.225
PS	0-1	Ref	0.963	Ref
	≥2	1.05 (0.14-7.82)		0.58 (0.64-5.337)	0.633
Stage	I-Ⅱ	Ref	0.367	Ref
	III	0.61 (0.21-1.78)		0.50 (0.23-1.09)	0.810
EGFR mut	Exon 19 deletions	Ref	0.370	Ref
	Exon 21 mutations	1.43 (0.66-3.10)		0.913 (0.35-2.36)	0.851
MVR	Low	Ref	0.003	Ref
	High	3.25 (1.48-7.16)		3.21 (1.18-8.76)	0.022

(B)

		Univariate		Multivariate
		HR (95%CI)	P	HR (95%CI)	P
Age	<75 years	Ref	0.969	Ref
	≥75 years	0.98 (0.36-2.67)		1.07 (0.27-4.24)	0.926
Sex	Male	Ref	0.271	Ref
	Female	1.78 (0.63-5.00)		3.11 (0.64-15.12)	0.161
Smoking	No	Ref	0.998	Ref
	Yes	1.00 (0.38-2.67)		0.65 (0.13-3.29)	0.602
PS	0-1	Ref	0.009	Ref
	≥2	2.93 (1.03-6.60)		12.59 (1.34-118.30)	0.027
Stage	I-Ⅱ	Ref	0.801	Ref
	III	1.16 (0.37-3.60)		0.74 (0.17-3.20)	0.687
EGFR mut	Exon 19 deletions	Ref	0.761	Ref
	Exon 21 mutations	0.85 (0.30-2.44)		0.53 (0.14-1.92)	0.331
MVR	Low	Ref	0.359	Ref
	High	1.58 (0.60-4.16)		1.33 (0.32-5.47)	0.697

Abbreviations: HR, hazard ratio; CI, confidence interval; MVR, microvascular area ratio

Univariate analysis showed that OS was significantly associated with ECOG PS (HR: 2.93, 95% CI: 1.03–6.60, P = 0.009), but no significant differences were found in MVR (HR: 1.58; 95% CI: 0.60–4.16, P = 0.359). Multivariate analysis revealed that ECOG PS ≥ 2 (HR: 12.59, 95% CI: 1.34–118.30, P = 0.027) was a significant independent negative predictive factor for OS.

This investigation is the first to assess the association between MVR and antitumor efficacy of EGFR-TKIs in patients with NSCLC with EGFR mutations. This study showed a significant positive correlation between MVD and MVR, suggesting that MVR might be an indicator of angiogenesis, as well as MVD. Moreover, we found that high MVR in patients with EGFR mutation-positive NSCLC was a negative predictive factor for PFS of EGFR-TKI; thus, a novel treatment strategy for EGFR-TKI, such as a combination of EGFR-TKI and angiogenesis inhibitors, might be necessary in EGFR mutation-positive NSCLC with abundant tumor microvessels.

Numerous studies using MVD based on immunohistochemistry have shown that MVD is correlated with lung cancer development and prognosis (Bing et al., 2014; Meert et al., 2002; Zhang et al., 2021). In contrast, MVA has been reported to be a prognostic factor in breast cancer and renal cell carcinoma (Sato et al., 2014; Sharma et al., 2011; Sullivan et al., 2009). Moreover, Sullivan et al. (2009) described that the evaluation of MVA by automated image analysis was correlated with pathologist-diagnosed MVD (Sullivan et al., 2009), indicating that MVA is an alternative angiogenetic marker of MVD. However, MVA is measured as the total area of blood vessels per field of view and is dependent on magnification of the microscope and whole tumor size, which makes it difficult to consistently evaluate the overall assessment of angiogenesis status in whole cancer tissue. In the current study, MVR was defined as the ratio of microvascular area to field of view, likely to be estimated independently of tumor size, and was found to be positively correlated with MVD. Thus, the measurement of MVR using image analysis software could be an alternative indicator of tumor angiogenesis as well as MVD.

We found that the PFS of EGFR-TKI in the higher MVR group was significantly shorter than that in the lower MVR group. Tumor angiogenesis assessed by MVD has been reported to be associated with resistance to cytotoxic chemotherapy in several cancers, including breast, cervical, and ovarian cancers (Hasan et al., 2002; Li et al., 2021). One cause of drug resistance is the vascular endothelial growth factor (VEGF). VEGF plays an important role in tumor angiogenesis and leads to leakage from microvessels in tumor tissues and elevation of interstitial fluid pressure, which decreases drug delivery and results in drug resistance (Goel et al., 2012; Jain, 1994, 2013; Jain et al., 2014). Previous reports have shown MVD to be significantly correlated with plasma and tumor VEGF levels in NSCLC and esophageal and gastric cancers (Du et al., 2003; Tamura et al., 2001). Thus, EGFR mutation-positive NSCLC with higher MVR is suggested to be a microenvironment with abundant VEGF, which might reduce the efficacy of EGFR-TKIs due to inhibition of drug delivery.

Angiogenesis inhibitors, such as bevacizumab and ramucirumab, have demonstrated clinical efficacy and have been used for patients with NSCLC in routine practice. Recently, randomized phase III studies comparing the combination therapy of EGFR-TKI and angiogenesis inhibitors to EGFR-TKI monotherapy in EGFR mutation-positive NSCLC showed that the former resulted in longer PFS (Nakagawa et al., 2019; Saito et al., 2019). In ovarian and colorectal cancers, high MVD assessed by immunohistochemistry has been reported to be a potential predictive factor of bevacizumab (Bais et al., 2017; Bianconi et al., 2020). Furthermore, Zhao et al. (2012) reported a positive correlation between MVD and tumor shrinkage rate in patients with NSCLC treated with platinum doublets and bevacizumab (Zhao et al., 2012). We found that EGFR mutation-positive NSCLC with a high MVR was resistant to EGFR-TKI monotherapy compared to that with a low MVR. Based on these findings, EGFR mutation-positive NSCLC with abundant tumor microvessels might be preferable in combination with EGFR-TKI and angiogenesis inhibitors.

Despite these findings, our study had several limitations. First, this was a retrospective study performed in a single institution; therefore, various selection biases might be included. Second, this study used surgical specimens from patients with post-operative recurrence. The tumor microenvironment, including angiogenesis status, might have changed between the surgical and post-operative recurrent specimens, and these differences in microvasculature might have affected the results of our study. Third, the median value of MVR that we provisionally employed was cut off level in order to analyze the predictive factor of EGFR-TKI. Therefore, a large prospective study using advanced and post-operative recurrent NSCLC specimens is required to clarify the optimal cut-off value of MVR for the predictive value of response to EGFR-TKIs.

High MVR in NSCLC harboring EGFR mutations is a negative predictive factor for EGFR-TKI, suggesting that the tumor microenvironment with abundant microvessels in EGFR mutation-positive NSCLC is associated with resistance to EGFR-TKI. In these populations, the combination of EGFR-TKIs and angiogenesis inhibitors may be an appropriate treatment strategy.

Acknowledgments

We are grateful to Ms. Takahashi, who is a technical assistant at the Department of Respiratory Medicine at Kumamoto University Hospital, for her support.

Conflicts of Interest

The authors declare no conflicts of interest.

Author contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Moriyasu anai and Koichi saruwatari. The first draft of the manuscript was written by Moriyasu anai and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Funding

This research did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors.

Data statement

All data in this study were obtained from the electronic medical records of the Kumamoto University Hospital.

Data availability

The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.

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No competing interests reported.

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Negative impact of the microvascular area to tumor area ratio on the response to EGFR tyrosine kinase inhibitors in non-small cell lung cancer with EGFR mutation

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Purpose

Methods

Results

Conclusions

Figures

Introduction

Materials And Methods

Study design and patients

Immunohistochemical analysis

Assessment of microvessels

Clinical outcome parameter

Statistical analysis

Results

Patient characteristics

Assessment of correlation between MVD and MVR

Comparison of clinicopathological features according to MVR

Tumor response, PFS, and OS analyses with EGFR-TKI according to MVR

Univariate and multivariate analysis for PFS and OS

Discussion

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1