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To investigate pharmacogenetic interactions among VEGF-A, VEGFR-2, IL-8, HIF-1α, EPAS-1, and TSP-1 SNPs and their role on progression-free survival (PFS) in metastatic breast cancer (MBC)

patients treated with bevacizumab plus first-line paclitaxel or with paclitaxel alone. Analyses were performed on germline DNA, and SNPs were investigated by real-time PCR technique. The

multifactor dimensionality reduction (MDR) methodology was applied to investigate the interaction between SNPs. The present study was an explorative, ambidirectional cohort study: 307

patients from 11 Oncology Units were evaluated retrospectively from 2009 to 2016, then followed prospectively (NCT01935102). Two hundred and fifteen patients were treated with paclitaxel and

bevacizumab, whereas 92 patients with paclitaxel alone. In the bevacizumab plus paclitaxel group, the MDR software provided two pharmacogenetic interaction profiles consisting of the

combination between specific VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes. Median PFS for favorable genetic profile was 16.8 vs. the 10.6 months of unfavorable genetic profile (p = 

0.0011). Cox proportional hazards model showed an adjusted hazard ratio of 0.64 (95% CI, 0.5–0.9; p = 0.004). Median OS for the favorable genetic profile was 39.6 vs. 28 months of

unfavorable genetic profile (p = 0.0103). Cox proportional hazards model revealed an adjusted hazard ratio of 0.71 (95% CI, 0.5–1.01; p = 0.058). In the 92 patients treated with paclitaxel

alone, the results showed no effect of the favorable genetic profile, as compared to the unfavorable genetic profile, either on the PFS (p = 0.509) and on the OS (p = 0.732). The

pharmacogenetic statistical interaction between VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes may identify a population of bevacizumab-treated patients with a better PFS.

The treatment of metastatic breast cancer (MBC) patients with hormone-receptors positive (HR+) and human epidermal receptor 2 negative (HER2−) tumors is dramatically changed over the years.

In this setting, cyclin-dependent kinase 4/6 inhibitors (CDK4/6i), such as palbociclib, ribociclib and abemaciclib, in combination with aromatase inhibitors or fulvestrant represent today

the first and later lines of therapy1.

However, chemotherapy-based treatment is still a therapeutic choice when hormone resistance occurs, in triple-negative tumor or in case of visceral crisis2,3. In this scenario, the humanized

monoclonal antibody bevacizumab, in combination with paclitaxel, is a treatment option compared to chemotherapy alone4. Although a significant improvement in progression-free survival (PFS)

was observed from three comparative studies, the US Food and Drug Administration (FDA), but not the European Medicines Agency (EMA), revoked the initial approval of bevacizumab for the

first-line treatment of MBC patients because of the lack of benefit in terms of overall survival (OS). However, it has been theorized that when a long survival post first-line progression is

expected after a first-line chemotherapy, such as in breast cancer, the lack of an apparent benefit in OS could not mean a lack of improvement in OS for the first line of

treatment4,5,6,7,8.

Different strategies have been investigated to find possible predictive biomarkers and select those patients with the best chance of response to bevacizumab. Indeed, the PFS improvement due

to bevacizumab was identical for magnitude in all subgroups of patients with different clinical and pathological characteristics9, and therefore new selective biomarkers should be needed to

identify those patients who can have a major advantage in terms of outcome. Despite many attempts have been done, no validated biomarkers are currently available in the clinical practice and

the prospective MERiDiAN trial failed to demonstrate a possible role of VEGF-A baseline in predicting the response to bevacizumab in breast cancer patients10,11,12,13,14,15.

Germline and somatic polymorphisms of genes involved in the angiogenic pathways have also been widely investigated in this research area to predict bevacizumab outcome, with contrasting

results12,16,17,18. Due to the retrospective nature of these studies and to their inconclusive results, the role of single nucleotide polymorphisms (SNPs) as predictive markers remains to

define19. Therefore, the current approach of correlating the bevacizumab response to a single SNP may be replaced by a genetic analysis of the interaction between SNPs, defined as non-linear

interaction or epistasis. Moore and colleagues have established and validated a methodology, called multifactor dimensionality reduction (MDR) analysis, to identify a genetic profile with

the ability to predict the drug response20. To test this hypothesis, we conducted a retrospective study on 113 MBC patients to assess the ability of MDR methodology to identify a favorable

pharmacogenetic profile associated to PFS in patients treated with bevacizumab, combined with first-line paclitaxel. The MDR analysis provided two pharmacogenetic interaction profiles

consisting of the combination between specific VEGFR-2 rs11133360 and IL-8 rs4073 genotypes. The median PFS was 14.1 months (95% CI, 11.4–16.8) and 10.2 months (95% CI, 8.8–11.5) for the

favorable and the unfavorable genetic profile, respectively (HR = 0.44; 95% CI, 0.29–0.66; p C and TYMS-TSER polymorphisms, instead of an individual polymorphism, seemed to predict the

CAPOX-B (capecitabine, oxaliplatin, and bevacizumab combination) response in terms of PFS, suggesting a paradigm shift from SNPs to a more complex interaction gene analysis able to predict

response to antitumor agents.

The current study was planned to evaluate the effects of the combination of paclitaxel with bevacizumab versus paclitaxel alone on MBC patients harboring different genetic profiles,

exploring the possibility to predict the best favorable profile in terms of PFS. The second step was to test if the eventual seen PFS advantage could be maintained also in terms of OS in

these patients. The previous study on VEGFR-2 and IL-8 genetic interaction analysis21, the favorable profile in terms of PFS was not predictive of OS benefit. In the present study, the seen

advantage in PFS was indeed confirmed in OS (an adjusted hazard ratio of 0.71) but with a p = 0.058, a value very close to a statistically significance, but not significant. However, the

reported data, although statistically negative, seem to suggest that the favorable profile in terms of PFS may probably be maintained also in terms of OS and undoubtedly merits further

investigations in a validation prospective study. Indeed, evaluation and confirmation of these findings in an independent cohort is critical because of the exploratory nature of our

ambidirectional trial.

The analyses conducted with the MDR methodology in this unselected population of MBC patients revealed more than a genetic interaction profile, consisting of the combination between specific

genotypes, but, due to nature of the MDR methodology, we investigated the genetic profile with a benefit in terms of both PFS and OS. The analysis conducted revealed a genetic interaction

profile, consisting of the combination between specific genotypes of VEGF rs833061 and VEGFR-2 rs1870377. Particularly, two genetic profiles were identified in patients, as reported in Table

5. The first one was associated with a greater both PFS and OS benefit compared to the second one. However, this model considered all the candidates and allows for any and all combination

of SNPs to correlate with outcome. Thus, there are other significant or borderline permutations. Indeed, we have also included, as an example in the supplementary data (Supplementary Table 2

and Supplementary Fig. 2), another interesting genetic profile with a significant advantage in term of PFS but without any advantage in OS (not even a tendency).

Therefore, in our study we demonstrated, through the MDR methodology, a statistical interaction between VEGF-A and VEGFR-2 gene SNPs that potentially relates to bevacizumab efficacy on both

PFS and OS. The two genes, and, consequently, the two proteins belong to the same signaling pathway, and it has been clearly demonstrated that VEGF-A stimulates VEGFR-2 phosphorylation and

tumor angiogenesis24. Based on these premises, it is conceivable to hypothesize that, in patients carrying the favorable genetic profile, the tumor angiogenesis is successfully inhibited in

the presence of bevacizumab. The pharmacological inhibition of the angiogenic process by bevacizumab could be effective because of the physiological (not increased) production of VEGF-A due

to the presence of VEGF-A rs833061 CC genotype or C allele. Indeed, for this SNP VEGF-A rs833061 C>T it has been described an increased promoter activity due to the T allele25 that may

explain an eventual resistance to the treatment. Moreover, the VEGFR-2 rs1870377 is a nonsynonymous SNP substituting glycine with histidine (Q472H) located in the extracellular ligand

binding region of the receptor, potentially impacting VEGFR-2 degradation26. The VEGFR-2 rs1870377 TT genotype or T allele present in the favorable profile synthetize a receptor not modified

in its structure, suggesting that it is not abnormally activated or degraded. Therefore, it might be plausible that the genetic background characterized by a physiological activation of the

VEGF-A pathway may be responsible, in part, for the positive effect of bevacizumab maintenance therapy in these MBC patients. In contrast, in patients with an unfavorable genetic profile,

the microenvironment conditions due to the different genotype combinations may result in an increase of the VEGF-A production and/or the presence of an altered VEGFR-2 on tumor endothelial

cells which may be capable to proliferate, migrate or survive because the VEGF action is not completely blocked by bevacizumab.

The absence of any advantage in terms of efficacy in the patients treated with chemotherapy without bevacizumab could suggest a possible predictive role of the favorable genetic profile for

bevacizumab response, but the exploratory nature of this ambidirectional study may limit this hypothesis. However, the main findings of our analyses support the conclusion that a genetic

profile may identify a group of patients with longer PFS and OS, predicting the response to bevacizumab in combination with paclitaxel.

The MDR approach is a major reason for differences between our trial and other studies on bevacizumab biomarkers such as E210016. There are additional aspects between the E2100 US patients

and the Italian population of our study that may account for different results. First of all, Italian patients were of Caucasian origin and no patients of African origin were represented.

Secondly, although the frequencies of our studied VEGF-A and VEGFR-2 SNPs were superimposable with the ones of the Caucasian patients published in the article by Schneider and colleagues16,

there was an exception regarding the VEGFR-2 889A/G (rs2071559). In that case, the frequency of the minor allele A in our population was 0.49 whereas in the E2100 study was 0.09.

New pharmacogenetic favorable biomarkers of bevacizumab-combined therapies could be retrieved from a genetic analysis of the interaction among SNPs rather than from the examination of a

single SNP of a single gene. Surely, a multigene-risk biomarkers may be more beneficial from a comprehensive agnostic approach using genome-wide association studies (GWAS) rather than a

candidate gene approach as the one that we have used in our study. However, some challenges have been faced when scientists tried the scaling of MDR to big data, as the one from GWAS, such

as the necessity to filter the data prior to MDR analysis27, also using biological knowledge through tools such as BioFilter28. Moreover, our work can definitively be strengthened by the

biological characterization of the VEGF expression in the pre-treatment tissue. Indeed, since rs833061 is located in the promoter region of VEGF-A, the difference in expression levels of

VEGF-A in tumors of patients harboring the favorable vs. unfavorable profile could be an important strategy to confirm our statistical findings.

In conclusion, the MDR methodology could be successfully used as witnessed by the experience in this unselected MBC patients where the investigation of an interaction between VEGF-A rs833061

and VEGFR-2 rs1870377 gene polymorphisms resulted in the identification of a genetic profile associated with a longer PFS.

This is an explorative, ambidirectional cohort study, meaning that eligible patients were enrolled and evaluated retrospectively from January 2009 until September 2016 and then followed

prospectively. The oncology units, all located in the north or center of Italy, were selected based on their clinical experience in the use of the combination of paclitaxel and bevacizumab

as first-line therapy in histologically confirmed HER-2-negative MBC patients. Two-hundred fifteen patients from 11 Italian divisions of Medical Oncology, with histologically confirmed

HER2-negative MBC, were treated with a first-line therapy including bevacizumab 10 mg/m2 i.v. on days 1 and 15 combined with first-line paclitaxel 90 mg/m2 i.v. on days 1, 8, and 15, every 4

weeks, and they were enrolled for the present pharmacogenetic study. Ninety-two MBC patients treated with a first-line chemotherapy including paclitaxel without bevacizumab, during the same

period, were also included into the study as a control group. The patients enrolled in the previously published study21 have been also included in the present analysis. Basal and

pathological characteristics recorded from both groups were the following: age (≤ or >65 years); Eastern Cooperative Oncology Group (ECOG) performance status (0 or 1–2); hormonal-receptor

status (positive or negative); previous adjuvant chemotherapy (none, anthracycline or anthracycline plus taxanes); previous hormonal therapy (adjuvant or metastatic); disease-free interval

from the first diagnosis of breast cancer (≤ or >12 months); extent of disease (≤ or >3 sites); location of disease (viscera or bone); disease evaluation (measurable or non-measurable).

Patients with human epidermal growth factor receptor type 2 (HER2)-positive, were excluded from the present study. The characteristics of the patients are summarized in Table 1.

The treatment with chemotherapy was continued until either disease progression occurred or unacceptable toxicities registered, or it was stopped for medical choice. The bevacizumab

maintenance was continued, and hormone therapy added for both groups when indicated, until disease progression or unacceptable toxicities occurred.

Sites of metastatic disease were radiologically re-evaluated according to the RECIST criteria 1.1, in patients with measurable disease, every 2 months. In patients without measurable

lesions, progression of disease was defined when new lesions appeared or when existing lesions evolved. Likewise, in the case of non-measurable lesions, deterioration of clinical condition

not due to treatment toxicity, was defined as progression of disease.

PFS was defined as the period from the beginning of the treatment to the first observation of disease progression as above described, or death from any cause. OS was defined as the period

from the beginning of the treatment to death from any cause. All patients were assessed for response, PFS and OS. Each patient entering the study signed the informed consent. The disease

assessment was conducted by the investigators based on the approved protocol and all the oncology units followed the same assessment schedule and criteria for the prospective follow-up. The

protocol was approved by ethic committee of Azienda Ospedaliera-Universitaria Pisana (CESM-AOUP 3077/2010; clinicaltrials.gov identifier NCT01935102) for Pisa, Livorno, Lucca, Massa Carrara,

Versilia, and Pontedera Hospitals, and by the ethic committees of all participating centers.

Blood samples (3 ml) were collected in EDTA tubes and stored at −80 °C. Genes and polymorphisms, involved in the angiogenesis pathways, were selected for the present analyses based on our

previous study21. In the Table 9, the selected polymorphisms are reported. Germline DNA extraction was performed using QIAamp DNA Blood Mini Kit (Qiagen, Valencia, CA, USA). Allelic

discrimination of genes was performed using an ABI PRISM 7900 SDS (Applied Biosystems, Carlsbad, CA, USA) and with validated TaqMan® SNP genotyping assays (Table 9; Applied Biosystems). PCR

reactions were carried out according to the manufacturer’s protocol. Genotyping was not performed until an adequate number of events (>80% on study population) was reported in terms of PFS.

All the samples were analyzed twice to replicate the obtained genotype.

The investigators responsible for data analysis were blinded to which samples were from patients treated with paclitaxel alone and paclitaxel plus bevacizumab.

The aim of the present study was to identify a favorable genetic profile in terms of PFS in MBC patients treated with bevacizumab in association with paclitaxel. The corresponding OS in

these patients remained a secondary endpoint as well as response rate. All polymorphisms were analysed for deviation from the Hardy–Weinberg Equilibrium (HWE) by means of comparison between

observed allelic distributions with those expected from the HWE by on χ2 test (see Supplementary Tables 3 and 4).

Any association between gene polymorphisms and response rate was analysed by the two-sided Fisher’s exact test. The association between each individual polymorphism and the most relevant

clinical-pathological characteristics with PFS and OS was tested using a Cox proportional hazards model. In these analyses we used Bonferroni’s correction and the p value