Research ArticleClinical Studies
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Total Lesion Glycolysis Levels as Predictive Indicators in Patients With Metastatic and Recurrent Breast Cancer Undergoing Endocrine Therapy With or Without CDK4/6 Inhibitor

HIROMI OZAWA, TOMOKO HIGUCHI, YUKIE FUJIMOTO, AYAKO BUN, REIKO FUKUI, HARUKA KANAOKA, MASAYUKI NAGAHASHI, KAZUHIRO KITAJIMA, KOICHIRO YAMAKADO and YASUO MIYOSHI
Anticancer Research October 2022, 42 (10) 4813-4824; DOI: https://doi.org/10.21873/anticanres.15986

Abstract

Background/Aim: Endocrine therapy (ET) with or without CDK4/6 inhibitors is the primary treatment choice for patients with estrogen receptor (ER)-positive and HER2-negative subtype of metastatic breast cancer (MBC). We examined the metabolic parameters identified using 18F-fluorodeoxyglucose-positron emission tomography (FDG-PET) in terms of sensitivity, since no predictive factors exist. Patients and Methods: We included 136 patients with MBC treated with ET alone (n=107) or combined with CDK4/6 inhibitor (n=29) and examined using FDG-PET before treatment began. The highest maximum value of the standard uptake value (SUVmax), whole-body metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were calculated. Results: Progression-free survival (PFS) was significantly longer in patients with low levels of MTV, TLG, and SUVmax than those with higher levels (median PFS 49.5 vs. 20.7 months, p=0.001 for MTV, 49.5 vs. 20.7 months, p=0.0016 for TLG, 37.0 vs. 20.7 months, p=0.012 for SUVmax). Multivariable analysis revealed that TLG (hazard ratio=6.383, 95% confidence interval=1.167-34.913, p=0.033) was independently and significantly associated with PFS. The relationship between TLG levels and PFS was significant in patients treated with ET with (p=0.0054) and without (p=0.0188) CDK4/6 inhibitor. Conclusion: TLG at baseline was a significant predictor for sensitivity to ET alone or combined with CDK4/6 inhibitor. These data may be useful to identify patients that would benefit from ET.

Key Words

Cyclin-dependent kinase 4/6 (CDK4/6) inhibitor plus endocrine therapy (ET) is recommended as the first-line therapy for patients with estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (MBC), except for those with visceral crisis (1, 2). From 2017 to 2018, 9.3% and 64.3% of patients with ER-positive/HER2-negative MBC were treated with ET alone and the combination of ET with CDK4/6 inhibitor, respectively, as first-line therapy (3). However, predictive factors for ET with or without CDK4/6 inhibitor have yet to be identified. Clinically useful biomarkers that can be used in daily practice as alternatives to ER or HER2 status to select agents that would serve as effective treatments are urgently needed.

Clinicopathological factors including tumor grade, ER, progesterone receptor (PgR), HER2, and Ki67 are considered as prognostic factors; however, only ER is a significant predictive factor for ET (4). In the phase III FALCON study, which compared first-line treatment with anastrozole and fulvestrant for patients with MBC, longer progression-free survival (PFS) was demonstrated in the fulvestrant arm. Interestingly, in the subgroup analysis, improved PFS was consistently recognized in the non-visceral diseases, but not visceral diseases [hazard ratio (HR)=0.59, 95% confidence interval (95%CI)=0.42-0.84, median PFS 13.8 vs. 22.3 months for non-visceral diseases; HR=0.99, 95%CI=0.74-1.33, median PFS 15.9 vs. 13.8 months for visceral diseases] (5). In addition, a retrospective study identified that PFS was longer in patients with non-visceral and lung metastases than in those with liver or other visceral metastases (median PFS, non-visceral 22.8 months; lung 20.8 months; liver 6.1 months; other visceral 3.7 months) (6). These data suggest that the sensitivity of fulvestrant depends on metastatic sites.

Compared with ET alone, treatment with CDK4/6 inhibitor plus ET resulted in longer PFS irrespective of metastatic sites (7). Although a similar improved HR for PFS could be obtained by the addition of CDK4/6 inhibitor irrespective of metastatic sites, longer PFS was confirmed for patients in the aromatase inhibitor (AI)-sensitive subgroup than for those in the AI-resistant subgroup (7). Resistance mechanisms to ET alone or CDK4/6 inhibitor plus ET have been extensively investigated; several factors – including cell cycle-specific components, cyclin E-CDK2 axis, activation of Thymidine Kinase 1, and alterations in phosphatidyl inositol 3-kinase/AKT/mechanistic target of rapamycin and fibroblast growth factor receptor signaling – have been demonstrated to be involved in resistance (8-10). Therefore, precise prediction of sensitivity to ET alone or CDK4/6 inhibitor plus ET is difficult to apply in clinical practice.

Recently, 18F-fluorodeoxyglucose (FDG) positron-emission tomography/computed tomography (PET/CT) imaging has been used to investigate ET sensitivity in breast cancer (11-13). Patients with MBC whose whole-body metabolic tumor volume (MTV) was lower had longer overall (OS) (p<0.0001) (12). Kurland et al. reported that patients with lower uptake of normalized by lean body mass SULmax at baseline had longer PFS, suggesting a predictive utility of the FDG parameter for ET among patients with MBC (13). Data from eight patients who were treated with CDK4/6 inhibitor plus ET revealed that an early change in total lesion glycolysis (TLG) levels was associated with treatment response and prognosis (12).

Although the metabolic parameters determined using FDG-PET are useful for predicting the efficacy of ET with and without CDK4/6 inhibitor, the metabolic parameter offering most precise prediction remains unknown. In the present study, we aimed to demonstrate the predictive values of SUVmax and volume-based parameters, including whole-body MTV and TLG. The parameters were measured in patients with MBC treated with ET alone or in combination with CDK4/6 inhibitor using FDG-PET prior to the beginning of treatment.

Patients and Methods

Patient characteristics. In the present study, 136 patients with locally advanced or recurrent breast cancers who were treated with ET alone or in combination with CDK4/6 inhibitors and patients who received an FDG PET/CT examination prior to the start of therapy were recruited between May 2009 and October 2021. The primary sites were divided into luminal A (ER-positive, progesterone receptor (PgR) ≥20%, HER2-negative, and Ki67 <25%; n=25) and luminal B (ER-positive, PgR <20% or Ki67 ≥25%, and HER2-negative; n=84) (Table I) subtypes. The number of recruited de novo and recurrent patients was 45 and 91, respectively. We divided metastatic sites into visceral (lung, liver, adrenal gland, peritoneum, rectum, and brain; n=49) and non-visceral (bone, lymph node, local, and pleura; n=87). Chemotherapy was administered to patients for de novo or recurrence (n=61) and ET alone (n=107) or in combination with CDK4/6 inhibitors (n=29) was used as the first-line (n=67), second-line (n=46), third-line (n=15), and fourth-line or later (n=8) treatment. Aromatase inhibitors and fulvestrant were administered to 38 and 69 patients, respectively, and palbociclib (n=15) and abemaciclib (n=14) were used with fulvestrant (n=28) or aromatase inhibitor (n=1).

View this table:
Table I.

Patient characteristics treated with endocrine therapy alone or in combination with CDK4/6 inhibitors.

The Ethics Committee of Hyogo College of Medicine approved the present study (No. 1969). Written informed consent was not required from the patients because only clinical data and data obtained retrospectively from FDG-PET results were used; all data were de-identified.

FDG PET/CT procedure and imaging analyses. For the process of FDG PET/CT, a Gemini GXL16 or Gemini TF64 PET/CT scanner was used (Philips Medical Systems, Eindhoven, the Netherlands) following the injection of 4.0 or 3.0 MBq/kg body weight of FDG for the GXL16 and TF64, respectively. We obtained scanning images 60 min post injection, as described previously, prior to the start of treatment (14). The volume of interest (VOI) was obtained in all tumors of the entire body in which FDG accumulated, along the margin of tumor uptake. To quantify the 18F-FDG uptake, the SUVs were calculated as previously described (15). We set SUV as the regional radioactivity concentration (Bq/ml)/[injected dose (Bq)/patient weight (g)] in the most intense area of 18F-FDG accumulation (a region of interest: ROI) and the maximum value of SUV in the VOI was defined as the SUVmax. In the total lesion of FDG accumulation, the hottest area of metastatic sites was defined as the highest SUVmax. SUVmean was obtained as the average SUV value in the voxel that showed 40% or more volume. The volume of the voxels of 40% or more of the SUVmax in the VOI of the whole-body was defined as the MTV and whole-body TLG was obtained from MTV × SUVmean (average SUV value in the voxel which showed 40% or more volume). These parameters were determined using the computer software package GI-PET (AZE Co., Ltd., Tokyo, Japan), adjusting harmonization of data in different PET/CT systems that was performed using phantom data.

Statistical analysis. Relationships between clinicopathological characteristics and therapeutic agents or metabolic parameters were analyzed using Fisher’s exact test. PFS, measured from the start of treatment to the day of confirmed disease progression or death due to any reason, and OS, measured from the start of treatment to the day of death due to any reason, were compared among the different subgroups using Kaplan–Meier curves and log-rank test. We used Cox proportional hazard model to obtain HR with a 95%CI using univariable and multivariable analyses for clinicopathological factors and metabolic parameters. To determine the optimal cut-off values of the metabolic parameters for PFS, we used receiver operating characteristics curves (ROCs) calculated with the Youden index to determine the area under the curve (AUC). The statistical significance was set at p<0.05, and JMP Pro 15 (SAS Institute Inc., Cary, NC, USA) was used for all statistical calculations.

Results

Patient characteristics and regimen of endocrine-based therapy. ET alone was used as the first-line and second-line or later therapy in 57 (53.3%) and 50 (46.7%) patients, respectively, and 19 (65.5%) out of 29 patients were treated with CDK4/6 inhibitor plus ET as a second-line or later therapy. However, this difference was not statistically significant (Table I). No significant association was observed between patients treated with ET alone and CDK4/6 inhibitor plus ET for other parameters.

Identification of cut-off values for MTV, TLG, and SUVmax A representative FDG PET/CT image is shown in Figure 1; FDG was accumulated in multiple metastatic lesions including the breast, lymph nodes, and bone. We collected data from the total lesion of detectable area automatically. To determine optimal cut-off values of the metabolic parameters for PFS ≥12 months, we used ROCs calculated with the Youden index to determine the AUC. The cut-off values for MTV, TLG, and SUVmax were found to be 11.65 (AUC=0.600, p=0.129), 35.87 (AUC=0.603, p=0.117), and 5.58 (AUC=0.613, p=0.048), respectively.

Figure 1.
Figure 1.

Representative cases of 18F-FDG PET/CT examination of stage IV breast cancer with lymph node and multiple bone metastases. Accumulation of the isotope was marked in the breast and metastatic sites. Indicated lesions were calculated automatically using the computer software package GI-PET.

Levels of metabolic parameters according to clinicopathological characteristics. Patients with a performance status (PS) of 0 were significantly more frequent in groups with low levels of MTV (40.2% vs. 10.5%, p=0.018), TLG (39.3% vs. 10.5%, p=0.018), and SUVmax (42.7% vs. 15.8%, p=0.040) as compared with PS 1 and 2 (Table II). None of MTV, TLG and SUVmax parameters were significantly associated with subtypes, adjuvant chemotherapy, adjuvant ET, de novo/recurrence, visceral metastasis, chemotherapy for de novo/recurrence, or lines of ET (Table II).

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Table II.

Patient characteristics according to Metabolic tumor volume (MTV)a, total lesion glycolysis (TLG)b, and standard uptake value max (SUVmax)c levels.

Associations between PFS and OS and each metabolic parameter. PFS was significantly longer in patients with low levels of MTV (n=49) than in those with high levels (n=87, median 49.5 vs. 20.7 months, p=0.001, HR=0.44, 95%CI=0.27-0.73, Figure 2A). Similarly, low levels of TLG (n=48, 49.5 vs. 20.7 months, p=0.0016, HR=0.46, 95%CI=0.28-0.75, Figure 2B) and SUVmax (n=53, 37.0 vs. 20.7 months, p=0.012, HR=0.55, 95%CI=0.34-0.88, Figure 2C) were significantly associated with longer PFS than with high levels (n=88 for TLG, n=83 for SUVmax). Significantly longer OS was consistently associated with lower levels of MTV (p<0.0001), TLG (p<0.0001), and SUVmax (p=0.0048) (Figure 3).

Figure 2.
Figure 2.

Kaplan–Meier curves of progression-free survival (PFS) in each metabolic parameter. PFS according to low and high levels in the (A) whole-body metabolic tumor volume (MTV); (B) whole-body total lesion glycolysis (TLG); and (C) highest maximum standardized uptake value (SUVmax). Significantly improved PFS was observed in MTV (p=0.001), TLG (p=0.0016), and SUVmax (p=0.012). HR: Hazard ratio (95% confidence interval), median value.

Figure 3.
Figure 3.

Kaplan–Meier curves of overall survival (OS) in each metabolic parameter. OS according to low and high levels in the (A) whole body metabolic tumor volume (MTV); (B) whole-body total lesion glycolysis (TLG); and (C) highest maximum standardized uptake value (SUVmax). Significantly improved OS was observed in MTV (p<0.0001), TLG (p<0.0001), and SUVmax (p=0.0048). HR: Hazard ratio (95% confidence interval), median value; NR: not reached.

Univariable and multivariable analyses of PFS including metabolic parameters. In the univariable analysis, subtypes (p=0.008), chemotherapy for de novo/recurrence (p<0.0001), MTV (p=0.001), TLG (p=0.002), and SUVmax (p=0.013) were significant predictors of PFS (Table III). Multivariable analysis of factors that were significant in univariable analysis revealed that subtypes (HR=2.681, 95%CI=1.217-5.908, p=0.014), chemotherapy (HR=3.516, 95%CI=1.955-6.324, p<0.0001), and TLG (HR=6.383, 95%CI=1.167-34.913, p=0.033) were independently significant. Although MTV, TLG, and SUVmax were significantly associated with OS in univariable analysis (HR=4.092, 95%CI=1.994-8.398 for MTV; HR=3.702, 95%CI=1.857-7.383 for TLG; HR=2.392, 95%CI=1.281-4.468 for SUVmax), no significant association was found using multivariable analysis among these three parameters (Table IV).

View this table:
Table III.

Univariable and multivariable analyses for progression-free survival.

View this table:
Table IV.

Univariable and multivariable analyses for overall survival.

Associations between TLG and prognosis based on metastatic sites or ET with/without CDK4/6 inhibitor. Since multivariable analysis indicated that TLG was a superior predictor for PFS compared to MTV and SUVmax, we further investigated the prognostic significance of TLG in each subgroup. According to the forest plot of the subgroups, the longer PFS of patients with low TLG was consistently observed irrespective of the subgroup, except for visceral disease (HR=0.92, 95%CI=0.42-2.02, p=0.826 for visceral disease; HR=0.35, 95%CI=0.18-0.66, p=0.001 for non-visceral disease) (Figure 4). Figure 5 demonstrates Kaplan–Meier curves of low and high TLG groups according to treatment regimen. Significantly longer PFS and OS were consistently recognized in the ET alone group (p=0.0188 for PFS, p=0.0008 for OS, Figure 5A and C) and the CDK4/6 inhibitor plus ET group (p=0.0054 for PFS, p=0.0305 for OS, Figure 5B and D). In contrast, significant association between TLG levels and PFS or OS was exclusively demonstrated in the non-visceral group (non-visceral, p=0.0007 for PFS and p=0.0006 for OS; visceral, p=0.826 for PFS and p=0.062 for OS; Figure 6).

Figure 4.
Figure 4.

Subgroup analysis of relationships between whole body total lesion glycolysis (TLG) levels and progression-free survival in each subgroup. aTotal lesion glycolysis (TLG)-high ≥35.87, -low <35.87; bhazard ratio (HR); c95% confidence interval; dluminal A (ER-positive, progesterone receptor (PgR) ≥20%, HER2-negative, and Ki67 <25%); luminal B (ER-positive, PgR <20% or Ki67 ≥25%, and HER2-negative).

Figure 5.
Figure 5.

Kaplan–Meier curves of progression-free survival (PFS) and overall survival (OS) according to whole body total lesion glycolysis (TLG) levels in the endocrine therapy (ET) alone or CDK4/6 inhibitor plus ET. PFS (A, B) and OS (C, D) according to low and high levels of TLG in the ET alone (A, C) and CDK4/6 inhibitor plus ET (B, D). Significant association was recognized in the ET alone (PFS, p=0.0188; OS, p=0.0008) and in the CDK4/6 inhibitor plus ET (PFS, p=0.0054; OS, p=0.0305). HR: Hazard ratio (95% confidence interval), median value; NR: not reached.

Figure 6.
Figure 6.

Kaplan–Meier curves of progression-free survival (PFS) and overall survival (OS) according to whole body total lesion glycolysis (TLG) levels in visceral disease and in non-visceral disease. PFS (A, B) and OS (C, D) according to low and high levels of TLG in the visceral (A, C) and non-visceral disease (B, D). A significant association was identified in the non-visceral disease (PFS, p=0.0007; OS, p=0.0006), but not in the visceral disease (PFS, p=0.826; OS, p=0.062). HR: Hazard ratio (95% confidence interval), median value; NR: not reached.

Discussion

In the present study, we demonstrated that low levels of TLG at baseline were significantly associated with longer PFS and OS in patients with MBC treated with ET with or without CDK4/6 inhibitor. These data suggest the usefulness of the volume parameter TLG, derived using FDG-PET at baseline, as a predictive factor. We evaluated three metabolic parameters: the semiquantitative tumor volume parameter SUVmax and volume-based variables whole-body MTV and TLG. Tumor aggressiveness evaluated using SUVmax and whole-body tumor volume evaluated using MTV or TLG may be effective predictors for treatment efficacy and prognosis; the volume-based parameters derived from PET are especially useful in MBC. In line with this finding, TLG or MTV were strongly correlated with the OS of patients with MBC rather than SUVmax (12, 16, 17). Interestingly, the prognostic values of quantitative metabolic parameters for MBC differed depending on metastatic sites (18). A less favorable OS rate was significantly observed in the upper tertile as compared with the bottom tertile for SUVmax (HR=3.11, 95%CI=1.80-5.39) and TLG (HR=2.15, 95%CI=1.26-3.67) in bone metastases (18). In contrast, both MTV and TLG, but not SUVmax levels were significantly associated with the OS of patients with lymph node and liver metastases. For lung metastases, none of these parameters were a predictor of OS. These data might suggest the prognostic usefulness of MTV and TLG rather than SUVmax in patients with MBC although their effectiveness may be different depending on metastatic sites.

The issue of clinical benefit of using metabolic parameters for determining MBC treatment efficacy has rarely been investigated. Both SUVmax and SUVpeak were superior parameters of response than TLG in 36 patients with MBC (19). Kitajima et al. examined the highest SUVmax of all lesions, whole-body MTV, and whole-body TLG in 65 patients with Stage IV and demonstrated that whole-body TLG was a significant predictor for OS, but the difference in PFS of the first-line therapy was marginal (p=0.057) (20). In contrast, Li et al. reported that PFS of first-line therapy was significantly associated with SUVmax, SUVmean, MTV, and TLG levels at baseline in 177 patients with MBC (21). Thus, the predictive significance of MTV and TLG has yet to be discovered so far. The studies conducted by Kitajima et al. and Li et al. included different breast cancer subtypes and different first-line treatments (20, 21). The MTV and TLG were significantly associated with PFS in patients with the triple negative subtype (n=60, p=0.001 and p=0.023, respectively) but not in those with the hormone receptor (HR)-positive/HER2-negative subtype (n=87, p=0.151 and p=0.151, respectively) (21). Although the matter of whether MTV and TLG are predictive factors or not is currently inconclusive, the association between PFS and TLG was consistent in the non-visceral diseases, but not in the visceral diseases (Figure 6), which may indicate that TLG is not a general prognostic factor, but has the ability to be a predictive factor for non-visceral diseases of MBC according to the present study. Based on these results, we hypothesize that the predictive usefulness of MTV and TLG are different depending on subtypes or treatments. For bone metastases, evaluation of response to treatment by tumor size is usually infeasible; therefore, TLG on metastatic lesions is a good biomarker for treatment efficacy (22). We focused on ET in which bone metastasis is predominantly of the HR-positive/HER2-negative subtype and confirmed that TLG is also a predictor for PFS in the subgroup of patients with bone metastasis only (data not shown).

Present results demonstrated that baseline values of MTV, TLG, and SUVmax are significant predictors of PFS in patients with MBC that are treated not only with ET alone, but also with ET in combination with CDK4/6 inhibitor. Based on multivariable analysis, TLG seems to have a superior ability for predicting PFS than those of MTV and SUVmax (Table III). However, the question of whether TLG is the best metabolic parameter or not is currently unknown. There are a limited number of studies that investigated the predictive significance of metabolic parameters in terms of response to ET (23-26). Kruse et al. reported that a larger decrease of SUVmax was significantly associated with longer PFS (median PFS 10.1 vs. 6.7 months, p=0.033) on the basis of comparison of FDG-PET between pre- and post-start of treatment in MBC patients treated with ET alone (24). Similarly, the percentage change in SUVmax of patients with progressive disease (PD) (PFS <24 weeks) was significantly smaller as compared with non-PD (−4.8% vs. −28.6%, p=0.005) for bone-predominant MBC and significant associations between a decreased percentage of the parameters and response to ET were similarly obtained from SUVmax, MTV, and total lesion metabolism (25). In addition, an early change in the FDG-PET uptake in tumors treated with CDK4/6 inhibitors plus either aromatase inhibitor or fulvestrant was measured at baseline and 14 days post-start of treatment (27). A greater decline in TLG was significantly associated with disease control (−55.3 vs. 16.7%, p<0.05). Although only a small number of patients were included in the study, these data seem to be in line with the usefulness of early change of metabolic parameters for predicting sensitivity to CDK4/6 inhibitors and TLG rather than MTV may be more a precise predictor of sensitivity. In the current study, we found that low levels of TLG at baseline strongly predict a longer PFS compared with that of patients with high levels treated with ET and CDK4/6 inhibitors (Figure 5). As far as we know, this is the first study which demonstrated the predictive usefulness of metabolic parameter at baseline for ET in combination with CDK4/6 inhibitor treatment. Since the change of metabolic parameters is yet to be examined, whether the decrease of metabolic parameters provides any additional information or not is currently unknown.

Several genomic mutations identified post-treatment with palbociclib plus fulvestrant were identified in the samples of PALOMA-3 (28). These molecular alterations seem to contribute to the resistance to CDK4/6 inhibitor plus ET treatment, however, such a method does not predict efficacy prior to the start of treatment. Since FDG-PET is a simple and clinically available modality, the usefulness of TLG for predicting the efficacy of treatment of CDK4/6 inhibitor plus ET remains advantageous for clinical use. Standard response evaluation criteria in solid tumors (RECIST) evaluation based on changes of tumor size in response to treatment concerning bone metastases is usually infeasible, the metabolic parameters demonstrated in the present study have superior benefit.

In the present study, we demonstrated that low levels of MTV, TLG, and SUVmax at baseline, assessed by FDG PET/CT examination, are significantly associated with longer PFS as well as OS of patients treated with ET alone or in combined with CDK4/6 inhibitor. Using multivariate analysis, TLG was found to be a significant predictor of PFS among the three parameters. Interestingly, the significant association between TLG and prognosis was recognized not in visceral disease, but in non-visceral disease. These data may be useful in identifying patients who could benefit from ET especially among patients with non-visceral disease.

This study has the following limitations. The number of patients treated with CDK4/6 inhibitor was small. We evaluated the values of the metabolic parameters at baseline, but changes in these parameters have yet to be studied. These issues need to be investigated in future studies comprising a larger number of patients. Despite these limitations, the evaluation of TLG at baseline may be useful for predicting efficacy in patients with HR-positive/HER2-negative MBC treated with ET alone or in combination with CDK4/6 inhibitor.

Acknowledgements

This study was supported by a Grant-in-Aid from the Ministry of Education, Culture, Sports, Science, and Technology of Japan [grant number 26461963]. The funder had no role in the study design; in the collection, analysis or interpretation of data; in the writing of the report; or in the decision to submit the article for publication. The Authors thank Editage (www.editage.jp) for English language editing.

Footnotes

  • Authors’ Contributions

    H.O., Y.F., A.B., R.F., and H.K. contributed to data acquisition; H.O., T.H., and M.N. performed data analysis; K.K, and K.Y. provided supervision and methodology; Y.M. conceived and designed the study; H.O. and Y.M. contributed writing and drafting; all Authors take responsibility for the accuracy and integrity of the manuscript and data and approved the final version of the manuscript.

  • Conflicts of Interest

    Y. M. received grants from Eisai, Chugai, MSD, Kyowa-Kirin, Eli Lilly, and Taiho and personal fees from Eisai, Chugai, AstraZeneca, Eli Lilly, Daiichi Sankyo, and Pfizer. M. N. received honoraria from AstraZeneca, Eli Lilly, Pfizer, Novartis, Chugai, Taiho, Daiichi Sankyo, Esai, Kyowa-Kirin, and Denka. All other Authors declare no conflicts of interest.

  • Received July 23, 2022.
  • Revision received August 15, 2022.
  • Accepted August 22, 2022.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

References

  1. ↵
    1. Gennari A,
    2. André F,
    3. Barrios CH,
    4. Cortés J,
    5. de Azambuja E,
    6. DeMichele A,
    7. Dent R,
    8. Fenlon D,
    9. Gligorov J,
    10. Hurvitz SA,
    11. Im SA,
    12. Krug D,
    13. Kunz WG,
    14. Loi S,
    15. Penault-Llorca F,
    16. Ricke J,
    17. Robson M,
    18. Rugo HS,
    19. Saura C,
    20. Schmid P,
    21. Singer CF,
    22. Spanic T,
    23. Tolaney SM,
    24. Turner NC,
    25. Curigliano G,
    26. Loibl S,
    27. Paluch-Shimon S,
    28. Harbeck N and ESMO Guidelines Committee
    : ESMO Clinical Practice Guideline for the diagnosis, staging and treatment of patients with metastatic breast cancer. Ann Oncol 32(12): 1475-1495, 2021. PMID: 34678411. DOI: 10.1016/j.annonc.2021.09.019
    OpenUrlCrossRefPubMed
  2. ↵
    1. Awada A,
    2. Gligorov J,
    3. Jerusalem G,
    4. Preusser M,
    5. Singer C and
    6. Zielinski C
    : CDK4/6 inhibition in low burden and extensive metastatic breast cancer: summary of an ESMO Open-Cancer Horizons pro and con discussion. ESMO Open 4(6): e000565, 2019. PMID: 31798979. DOI: 10.1136/esmoopen-2019-000565
    OpenUrlAbstract/FREE Full Text
  3. ↵
    1. Schneeweiss A,
    2. Ettl J,
    3. Lüftner D,
    4. Beckmann MW,
    5. Belleville E,
    6. Fasching PA,
    7. Fehm TN,
    8. Geberth M,
    9. Häberle L,
    10. Hadji P,
    11. Hartkopf AD,
    12. Hielscher C,
    13. Huober J,
    14. Ruckhäberle E,
    15. Janni W,
    16. Kolberg HC,
    17. Kurbacher CM,
    18. Klein E,
    19. Lux MP,
    20. Müller V,
    21. Nabieva N,
    22. Overkamp F,
    23. Tesch H,
    24. Laakmann E,
    25. Taran FA,
    26. Seitz J,
    27. Thomssen C,
    28. Untch M,
    29. Wimberger P,
    30. Wuerstlein R,
    31. Volz B,
    32. Wallwiener D,
    33. Wallwiener M and
    34. Brucker SY
    : Initial experience with CDK4/6 inhibitor-based therapies compared to antihormone monotherapies in routine clinical use in patients with hormone receptor positive, HER2 negative breast cancer - Data from the PRAEGNANT research network for the first 2 years of drug availability in Germany. Breast 54: 88-95, 2020. PMID: 32956934. DOI: 10.1016/j.breast.2020.08.011
    OpenUrlCrossRefPubMed
  4. ↵
    1. Freelander A,
    2. Brown LJ,
    3. Parker A,
    4. Segara D,
    5. Portman N,
    6. Lau B and
    7. Lim E
    : Molecular biomarkers for contemporary therapies in hormone receptor-positive breast cancer. Genes (Basel) 12(2): 285, 2021. PMID: 33671468. DOI: 10.3390/genes12020285
    OpenUrlCrossRefPubMed
  5. ↵
    1. Robertson JFR,
    2. Bondarenko IM,
    3. Trishkina E,
    4. Dvorkin M,
    5. Panasci L,
    6. Manikhas A,
    7. Shparyk Y,
    8. Cardona-Huerta S,
    9. Cheung KL,
    10. Philco-Salas MJ,
    11. Ruiz-Borrego M,
    12. Shao Z,
    13. Noguchi S,
    14. Rowbottom J,
    15. Stuart M,
    16. Grinsted LM,
    17. Fazal M and
    18. Ellis MJ
    : Fulvestrant 500 mg versus anastrozole 1 mg for hormone receptor-positive advanced breast cancer (FALCON): an international, randomised, double-blind, phase 3 trial. Lancet 388(10063): 2997-3005, 2016. PMID: 27908454. DOI: 10.1016/S0140-6736(16)32389-3
    OpenUrlCrossRefPubMed
  6. ↵
    1. Ozawa H,
    2. Sata A,
    3. Fukui R,
    4. Bun A,
    5. Higuchi T,
    6. Fujimoto Y,
    7. Miyagawa Y,
    8. Imamura M and
    9. Miyoshi Y
    : A single-centre, retrospective, observational analysis of fulvestrant for recurrent/metastatic breast cancer according to metastatic site. Anticancer Res 39(10): 5653-5662, 2019. PMID: 31570463. DOI: 10.21873/anticanres.13762
    OpenUrlAbstract/FREE Full Text
  7. ↵
    1. Piezzo M,
    2. Chiodini P,
    3. Riemma M,
    4. Cocco S,
    5. Caputo R,
    6. Cianniello D,
    7. Di Gioia G,
    8. Di Lauro V,
    9. Rella FD,
    10. Fusco G,
    11. Iodice G,
    12. Nuzzo F,
    13. Pacilio C,
    14. Pensabene M and
    15. De Laurentiis M
    : Progression-free survival and overall survival of CDK 4/6 inhibitors plus endocrine therapy in metastatic breast cancer: a systematic review and meta-analysis. Int J Mol Sci 21(17): 6400, 2020. PMID: 32899139. DOI: 10.3390/ijms21176400
    OpenUrlCrossRefPubMed
  8. ↵
    1. Chien TJ
    : A review of the endocrine resistance in hormone-positive breast cancer. Am J Cancer Res 11(8): 3813-3831, 2021. PMID: 34522451.
    OpenUrlPubMed
    1. Al-Qasem AJ,
    2. Alves CL and
    3. Ditzel HJ
    : Resistance mechanisms to combined CDK4/6 inhibitors and endocrine therapy in ER+/HER2− advanced breast cancer: Biomarkers and potential novel treatment strategies. Cancers (Basel) 13(21): 5397, 2021. PMID: 34771560. DOI: 10.3390/cancers13215397
    OpenUrlCrossRefPubMed
  10. ↵
    1. Fang H,
    2. Huang D,
    3. Yang F and
    4. Guan X
    : Potential biomarkers of CDK4/6 inhibitors in hormone receptor-positive advanced breast cancer. Breast Cancer Res Treat 168(2): 287-297, 2018. PMID: 29236235. DOI: 10.1007/s10549-017-4612-y
    OpenUrlCrossRefPubMed
  11. ↵
    1. Lin CY,
    2. Lin CL and
    3. Kao CH
    : Staging/restaging performance of F18-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging in breast cancer: A review and meta-analysis. Eur J Radiol 107: 158-165, 2018. PMID: 30292261. DOI: 10.1016/j.ejrad.2018.09.003
    OpenUrlCrossRefPubMed
  12. ↵
    1. Son SH,
    2. Lee SW,
    3. Jeong SY,
    4. Song BI,
    5. Chae YS,
    6. Ahn BC and
    7. Lee J
    : Whole-body metabolic tumor volume, as determined by (18)F-FDG PET/CT, as a prognostic factor of outcome for patients with breast cancer who have distant metastasis. AJR Am J Roentgenol 205(4): 878-885, 2015. PMID: 26204115. DOI: 10.2214/AJR.14.13906
    OpenUrlCrossRefPubMed
  13. ↵
    1. Kurland BF,
    2. Peterson LM,
    3. Lee JH,
    4. Schubert EK,
    5. Currin ER,
    6. Link JM,
    7. Krohn KA,
    8. Mankoff DA and
    9. Linden HM
    : Estrogen receptor binding (18F-FES PET) and glycolytic activity (18F-FDG PET) predict progression-free survival on endocrine therapy in patients with ER+ breast cancer. Clin Cancer Res 23(2): 407-415, 2017. PMID: 27342400. DOI: 10.1158/1078-0432.CCR-16-0362
    OpenUrlAbstract/FREE Full Text
  14. ↵
    1. Kitajima K,
    2. Miyoshi Y,
    3. Yamano T,
    4. Odawara S,
    5. Higuchi T and
    6. Yamakado K
    : Prognostic value of FDG-PET and DWI in breast cancer. Ann Nucl Med 32(1): 44-53, 2018. PMID: 29134565. DOI: 10.1007/s12149-017-1217-9
    OpenUrlCrossRefPubMed
  15. ↵
    1. Higuchi T,
    2. Fujimoto Y,
    3. Ozawa H,
    4. Bun A,
    5. Fukui R,
    6. Miyagawa Y,
    7. Imamura M,
    8. Kitajima K,
    9. Yamakado K and
    10. Miyoshi Y
    : Significance of metabolic tumor volume at baseline and reduction of mean standardized uptake value in 18F-FDG-PET/CT imaging for predicting pathological complete response in breast cancers treated with preoperative chemotherapy. Ann Surg Oncol 26(7): 2175-2183, 2019. PMID: 30941655. DOI: 10.1245/s10434-019-07325-8
    OpenUrlCrossRefPubMed
  16. ↵
    1. Satoh Y,
    2. Nambu A,
    3. Ichikawa T and
    4. Onishi H
    : Whole-body total lesion glycolysis measured on fluorodeoxyglucose positron emission tomography/computed tomography as a prognostic variable in metastatic breast cancer. BMC Cancer 14: 525, 2014. PMID: 25048880. DOI: 10.1186/1471-2407-14-525
    OpenUrlCrossRefPubMed
  17. ↵
    1. Naghavi-Behzad M,
    2. Petersen CB,
    3. Vogsen M,
    4. Braad PE,
    5. Hildebrandt MG and
    6. Gerke O
    : Prognostic value of dual-time-point 18F-Fluorodeoxyglucose PET/CT in metastatic breast cancer: an exploratory study of quantitative measures. Diagnostics (Basel) 10(6): 398, 2020. PMID: 32545312. DOI: 10.3390/diagnostics10060398
    OpenUrlCrossRefPubMed
  18. ↵
    1. Ulaner GA,
    2. Eaton A,
    3. Morris PG,
    4. Lilienstein J,
    5. Jhaveri K,
    6. Patil S,
    7. Fazio M,
    8. Larson S,
    9. Hudis CA and
    10. Jochelson MS
    : Prognostic value of quantitative fluorodeoxyglucose measurements in newly diagnosed metastatic breast cancer. Cancer Med 2(5): 725-733, 2013. PMID: 24403238. DOI: 10.1002/cam4.119
    OpenUrlCrossRefPubMed
  19. ↵
    1. Goulon D,
    2. Necib H,
    3. Henaff B,
    4. Rousseau C,
    5. Carlier T and
    6. Kraeber-Bodere F
    : Quantitative evaluation of therapeutic response by FDG-PET-CT in metastatic breast cancer. Front Med (Lausanne) 3: 19, 2016. PMID: 27243012. DOI: 10.3389/fmed.2016.00019
    OpenUrlCrossRefPubMed
  20. ↵
    1. Kitajima K,
    2. Miyoshi Y,
    3. Sekine T,
    4. Takei H,
    5. Ito K,
    6. Suto A,
    7. Kaida H,
    8. Daisaki H and
    9. Yamakado K
    : Harmonized pretreatment quantitative volume-based 18F-FDG PET/CT parameters for stage IV breast cancer prognosis. Multicenter study in Japan. Hell J Nucl Med 23(3): 272-289, 2020. PMID: 33367302. DOI: 10.1967/s002449912218
    OpenUrlCrossRefPubMed
  21. ↵
    1. Li Y,
    2. Liu C,
    3. Wang B,
    4. Hu X,
    5. Gong C,
    6. Zhao Y,
    7. Xie Y,
    8. Zhang Y,
    9. Song S,
    10. Yang Z and
    11. Wang B
    : Prediction of pretreatment 18F-FDG-PET/CT parameters on the outcome of first-line therapy in patients with metastatic breast cancer. Int J Gen Med 14: 1797-1809, 2021. PMID: 34007206. DOI: 10.2147/IJGM.S293998
    OpenUrlCrossRefPubMed
  22. ↵
    1. Koizumi M,
    2. Motegi K and
    3. Umeda T
    : A novel biomarker, active whole skeletal total lesion glycolysis (WS-TLG), as a quantitative method to measure bone metastatic activity in breast cancer patients. Ann Nucl Med 33(7): 502-511, 2019. PMID: 30982124. DOI: 10.1007/s12149-019-01359-4
    OpenUrlCrossRefPubMed
  23. ↵
    1. Mortazavi-Jehanno N,
    2. Giraudet AL,
    3. Champion L,
    4. Lerebours F,
    5. Le Stanc E,
    6. Edeline V,
    7. Madar O,
    8. Bellet D,
    9. Pecking AP and
    10. Alberini JL
    : Assessment of response to endocrine therapy using FDG PET/CT in metastatic breast cancer: a pilot study. Eur J Nucl Med Mol Imaging 39(3): 450-460, 2012. PMID: 22183107. DOI: 10.1007/s00259-011-1981-z
    OpenUrlCrossRefPubMed
  24. ↵
    1. Kruse V,
    2. VAN DE Wiele C,
    3. Maes A,
    4. Borms M,
    5. Pottel H,
    6. VAN Belle S and
    7. Cocquyt V
    : Stable metabolic disease on FDG-PET provides information on response to endocrine therapy for breast cancer. Q J Nucl Med Mol Imaging 61(1): 108-114, 2017. PMID: 25289633. DOI: 10.23736/S1824-4785.16.02727-8
    OpenUrlCrossRefPubMed
  25. ↵
    1. Azad GK,
    2. Taylor BP,
    3. Green A,
    4. Sandri I,
    5. Swampillai A,
    6. Harries M,
    7. Kristeleit H,
    8. Mansi J,
    9. Goh V and
    10. Cook GJR
    : Prediction of therapy response in bone-predominant metastatic breast cancer: comparison of [18F] fluorodeoxyglucose and [18F]-fluoride PET/CT with whole-body MRI with diffusion-weighted imaging. Eur J Nucl Med Mol Imaging 46(4): 821-830, 2019. PMID: 30506455. DOI: 10.1007/s00259-018-4223-9
    OpenUrlCrossRefPubMed
  26. ↵
    1. Azad GK,
    2. Cousin F,
    3. Siddique M,
    4. Taylor B,
    5. Goh V and
    6. Cook GJR
    : Does measurement of first-order and heterogeneity parameters improve response assessment of bone metastases in breast cancer compared to SUVmax in [18F]fluoride and [18F]FDG PET? Mol Imaging Biol 21(4): 781-789, 2019. PMID: 30250989. DOI: 10.1007/s11307-018-1262-3
    OpenUrlCrossRefPubMed
  27. ↵
    1. Seifert R,
    2. Küper A,
    3. Tewes M,
    4. Heuschmid M,
    5. Welt A,
    6. Fendler WP,
    7. Herrmann K and
    8. Decker T
    : [18F]-Fluorodeoxyglucose positron emission tomography/CT to assess the early metabolic response in patients with hormone receptor-positive HER2-negative metastasized breast cancer treated with cyclin-dependent 4/6 kinase inhibitors. Oncol Res Treat 44(7-8): 400-407, 2021. PMID: 34102639. DOI: 10.1159/000516422
    OpenUrlCrossRefPubMed
  28. ↵
    1. O’Leary B,
    2. Cutts RJ,
    3. Liu Y,
    4. Hrebien S,
    5. Huang X,
    6. Fenwick K,
    7. André F,
    8. Loibl S,
    9. Loi S,
    10. Garcia-Murillas I,
    11. Cristofanilli M,
    12. Huang Bartlett C and
    13. Turner NC
    : The genetic landscape and clonal evolution of breast cancer resistance to palbociclib plus fulvestrant in the PALOMA-3 trial. Cancer Discov 8(11): 1390-1403, 2018. PMID: 30206110. DOI: 10.1158/2159-8290.CD-18-0264
    OpenUrlAbstract/FREE Full Text
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Total Lesion Glycolysis Levels as Predictive Indicators in Patients With Metastatic and Recurrent Breast Cancer Undergoing Endocrine Therapy With or Without CDK4/6 Inhibitor
HIROMI OZAWA, TOMOKO HIGUCHI, YUKIE FUJIMOTO, AYAKO BUN, REIKO FUKUI, HARUKA KANAOKA, MASAYUKI NAGAHASHI, KAZUHIRO KITAJIMA, KOICHIRO YAMAKADO, YASUO MIYOSHI
Anticancer Research Oct 2022, 42 (10) 4813-4824; DOI: 10.21873/anticanres.15986
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