Univariate and multivariate logistic regression analyses for selected variables
1. Introduction
Sunitinib malate (Sutent, Pfizer inc., New York, NY) is an orally administered, multitargeted inhibitor of tyrosine kinases, including vascular endothelial growth factor (VEGF) receptor, platelet-derived growth factor (PDGF) receptor, stem cell factor receptor (KIT), fms-like tyrosine kinase (FLT) -3, CSF-1R, and RET. Since the introduction of sunitinib for patients with advanced renal tumor [1], significant objective responses of sunitnib have been revealed [2-6]. In a randomized, multicenter, phase III trial enrolled 750 patients with previously-untreated metastatic renal tumor to receive either sunitinib or interferon (IFN) -α, sunitinib was superior to IFN-α in the objective response rate (47%
It has been advocated that the necessity of determining molecular and clinical biomarkers that may predict efficacy of sunitinib. The identification of biomarkers to predict response is urgently needed. This chapter provides a brief overview of the signaling pathways of renal tumors and introduces biomarkers to predict response to sunitinib of clinical variables.
2. Signaling pathways in renal tumors
Renal tumors originates from the tubular structures of the kidney and is calssified into four major histological cell types. Clear-cell renal tumor is the most common type, accounting for approximately 75% of all renal tumors. Other types are followed by papillary renal tumor (approximately 15%), chromophobe renal tumor (approximately 5%), and renal oncocytoma (approximately 5%) [7].
The most important molecular disorder in renal tumors involves the von Hippel-Lindau (VHL) tumor suppressor gene, which is responsible for clear-cell renal tumors. The protein production of the
Alterations in proto-oncogenes and tumor suppressor genes leads to dysregulated signal transduction that underlies the abnormal growth and proliferation of cancer cells. Signaling proteins that are centrally located in important cancer-associated signaling networks can serve as therapeutic targets [10].
2.1. Angiogenetic signaling pathways
Renal tumors are frequnently characterized by hypoxic conditions. Hypoxia and compensatory hyperactivation of angiogenesis are thought to be particularly important in renal tumors, given the highly vascularized nature and the specific association of mutation in
2.2. PI3K/AKT/mTOR pathway
Mammalian target of rapamycin (mTOR) and protein kinase B (AKT) are key oncogenic process including cell proliferation, survival, and angiogenesis. PI3K promotes the generation of phosphatidylinositol-3, 4, 5-triphosphate. Signaling from VEGF and PDGF through AKT activates mTOR. Components of this PI3K/AKT/mTOR pathway are constitutively activated in renal tumors compared to normal renal tissues [11].
2.3. HGF/MET pathway
Changes in expression and activity of hepatocyte growth factor (HGF) and its receptor c-MET have been associated with renal tumors. HGF binding to MET leads to phosphorylation of two tyrosine residues at the C-terminus of MET, which leads to the recruitment of adapter proteins and activation of PI3K/AKT pathway to promote renal tumor growth and metastasis [12].
3. Biomarkers of response to sunitinib in renal tumors
3.1. Prognostic model
In the cytokine era, Motzer et al. [13] reported Memorial Sloan-Kettering Cancer Center (MSKCC) risk classification, which is based on data from 463 patients with advanced renal tumor who were treated with IFN-α cytokine therapy as first-line systemic therapy. The MSKCC risk classification extracted five variable risk factors for short survival: low Karnofsky performance status (PS) (< 80%), high lactate dehydrogenase (> 1.5 times the upper limit of normal), low serum hemoglobin, high corrected serum calcium (> 10 mg/dL), and time from initial renal tumor diagnosis to IFN-α therapy of less than one year. Each patient was assigned to one of three risk groups: those with zero risk factors (favorable risk), those with one or two risk factors (intermediate risk), and those with three or more risk factors (poor risk). The median time to death was 30, 14, and 5 months in the favorable, intermediate, and poor-risk groups, respectively [13]. These five risk criteria are now most frequently used prognostic model for patients with advanced renal tumor.
In the era of targeted therapy, Heng et al. [14] reported a new prognostic model that added platelet and neutrophil counts to the MSKCC model from a large multicenter study of 645 patients with metastatic renal tumor who were treated with targeted therapy. This study included three groups of patients: 396 patients treated with sunitinib, 200 patients treated with sorafenib, and 49 patients treated with bevacizumab. Four of the five adverse prognostic factors according to the MSKCC risk classification−low hemoglobin, high corrected serum calcium, low Karnofsky PS, and time from the initial renal tumor diagnosis to the start of treatment of less than one year−emerged as independent predictors of poor survival. Additionally, platelets greater than the upper limit of normal range, and neutrophils greater than the upper limit of normal range, emerged as independent adverse prognostic factors. MSKCC model with the addition of platelet and neutrophil counts can be incorporated into patient care of targeted therapies [14].
3.2. C-reactive protein
C-reactive protein (CRP), a non-specific inflammatory acute-phase protein, is a representative marker of systemic inflammatory response. CRP levels correlate with the production of proinflammatory cytokines, such as interleukin (IL) -6 [15], and with tumor progression [16, 17]. It has been recognized as an important prognostic marker in the cytokine era. Atzpodien et al. [16] reported data from 425 patients who received cytokine-based home therapy. On multivariate analysis, elevated CRP (≥ 1.1 mg/dL) was a poor prognostic factor, and Kaplan-Meier analysis demonstrated that patients with elevated CRP had significantly worse overall survival [16]. Casamassima et al. [17] reported that normal CRP (≤ 0.8 mg/dL) was the most independent prognostic factor for 110 patients treated with IL-2-based immunotherapy. Ramsey et al. [18] investigated the Glasgow Prognostic Score, which is based on a combination of hypoalbuminemia and elevated CRP (> 1.0 mg/dL). They found that CRP was independently associated with cancer-specific survival in 119 patients receiving immunotherapy [18]. Saito et al. [19] described that CRP kinetics have an impact on survival in patients with metastatic renal tumor treated with immunotherapy and/or metastasectomy. A decrease of CRP level during treatment predicts better prognosis in patients with metastatic renal tumor, and prolonged normalized CRP period is associated with prolonged survival [19].
Variable | Univariate | Multivariate | ||
Odds Ratio (95% Confidence Interval) |
|
Odds Ratio (95% Confidence Interval) |
|
|
Pretreatment | ||||
Age | 0.988 (0.920−1.061) | 0.7410 | ||
Gender | 0.573 (0.139−2.355) | 0.4384 | ||
ECOG PS0 | 4.200 (0.884−19.947) | 0.0598 | ||
MSKCC non-poor | 0.150 (0.026−0.864) | 0.0206 | 0.632 (0.058−6.850) | 0.7042 |
First-line | 0.879 (0.238−3.249) | 0.8468 | ||
Normal CRP | 17.600 (1.961−157.970) | 0.0011 | 13.525 (1.111−164.602) | 0.0163 |
Adverse events | ||||
Hypertension | 3.667 (0.954−14.094) | 0.0523 | ||
HFS | 6.500 (1.537−27.490) | 0.0069 | 2.272 (0.324−15.930) | 0.4104 |
Stomatitis | 3.200 (0.826−12.404) | 0.0844 | ||
Diarrhea | 1.375 (0.368−5.136) | 0.6347 | ||
Altered taste | 8.250 (1.498−45.436) | 0.0064 | 4.422 (0.533−36.655) | 0.1517 |
Fatigue | 5.133 (1.131−23.303) | 0.0238 | 1.572 (0.192−12.841) | 0.6740 |
Leukopenia | 8.333 (0.867−80.130) | 0.0337 | 5.436 (0.190−155.246) | 0.2717 |
Anemia | 1.771 (0.392−8.003) | 0.4559 | ||
Thrombocytopenia | 758.701 (0.000) | 0.0670 | ||
Increased creatinine | 2.182 (0.566−8.415) | 0.2505 | ||
TSH abnormalities | 2.812 (0.734−10.774) | 0.1255 |
In the targeted therapy era, Fujita et al. [20] recently reported that CRP is an independent prognostic indicator for patients with advanced renal tumor treated with sunitinib. A total of 41 consecutive patients between December 2008 and August 2011 were enrolled in this study. All patients had histologically proven clear-cell renal tumor. Non-tumor variables which were selected from pretreatment characteristics and treatment-related adverse events were analyzed on univariate and multivariate logistic regression analysis. Pretreatment characteristics were age, gender, Eastern Cooperative Oncology Group (ECOG) PS 0, MSKCC non-poor (favorable and intermediate) risk, first-line treatment, and normal CRP. Treatment-related adverse events were hypertension, hand-foot skin reaction (HFS), stomatitis, diarrhea, altered taste, fatigue, leukopenia, anemia, thrombocytopenia, increased creatinine, and thyroid-stimulating hormone (TSH) abnormalities. On univariate analyses among pretreatment characteristics, MSKCC non-poor risk classification and normal CRP level were significantly correlated with response to treatment (
Patients were grouped into two cohorts: those with normal CRP levels (≤ 0.30 mg/dL) and those with elevated CRP levels (> 0.30 mg/dL), according to the normal values provided by the manufacturer. The cohort with normal CRP comprised 10 males and 3 females (total 13 patients; 31.7%) with a median age of 63 years (range 46−77 years). The elevated CRP cohort comprised 20 males and 8 females (total 28 patients; 68.3%) with a median age of 64 years (range 36−80 years). MSKCC risk classification was favorable for 15.4% of the normal CRP cohort and intermediate for 86.4%. In contrast, in the elevated CRP cohort, MSKCC risk classification was favorable for 21.4%, intermediate for 46.4%, and poor for 32.2%. The difference in risk classification between the two groups was statistically significant (
|
|||
13 (31.7%) | 28 (68.3%) | ||
Gender ( |
0.7118 | ||
Male | 10 (76.9) | 20 (71.4) | |
Female | 3 (23.1) | 8 (28.6) | |
Age (years) | 0.5953 | ||
Median | 63 | 64 | |
Range | 46−77 | 36−80 | |
Mean ± standard deviation | 64.8 ± 9.0 | 63.2 ± 9.1 | |
ECOG PS ( |
0.0595 | ||
0 | 12 (92.3) | 18 (64.3) | |
≥ 1 | 1 (7.7) | 10 (35.7) | |
MSKCC risk classification ( |
0.0377 | ||
Favorable | 2 (15.4) | 6 (21.4) | |
Intermediate | 11 (84.6) | 13 (46.4) | |
Poor | 0 (0) | 9 (32.2) | |
Prior nephrectomy ( |
0.2767 | ||
Yes | 12 (92.3) | 22 (78.6) | |
No | 1 (7.7) | 6 (21.4) | |
T stage ( |
0.8187 | ||
T1 or T2 | 6 (46.2) | 14 (50.0) | |
≥ T3 | 7 (53.8) | 14 (50.0) | |
Grade ( |
0.6628 | ||
1 or 2 | 9 (69.2) | 17 (60.7) | |
3 | 3 (23.1) | 8 (28.6) | |
Prior immunotherapy ( |
0.2482 | ||
IFN-α | 9 | 14 | |
IL-2 and IFN-α | 3 | 6 | |
Prior targeted therapy ( |
0.8651 | ||
Sorafenib | 5 | 10 | |
Metastatic sites ( |
|||
Lung | 12 | 21 | |
Bone | 2 | 12 | |
Lymph nodes | 3 | 7 | |
Brain | 1 | 3 | |
Pancreas | − | 4 | |
Adrenal | − | 4 | |
Skin | − | 3 | |
Kidney | − | 2 | |
Local | − | 2 | |
Liver | − | 2 | |
Prostate | 1 | − | |
No. metastatic sites ( |
0.1929 | ||
1 | 6 (46.1) | 8 (28.6) | |
≥ 2 | 6 (46.1) | 20 (71.4) | |
Treatment ( |
0.2122 | ||
First-line | 3 (23.1) | 13 (46.4) | |
Second-line | 6 (46.1) | 6 (21.4) | |
Third-line | 4 (30.8) | 9 (32.2) | |
Responses ( |
0.0022 | ||
Partial response plus stable disease | 11 (84.6) | 10 (35.7) |
The median progression-free survival time for the elevated CRP cohort was 6.0 months. In contrast, the median progression-free survival time for the normal CRP cohort was significantly longer, at 19.0 months (log-rank
CRP is a significant independent prognostic indicator for patients with advanced renal tumor treated with sunitinib. Pretreatment CRP level could be a useful biomarker for response to sunitinib treatment [20].
3.3. Selected adverse events
Sunitinib has been related a variety of adverse events, key notable clinical adverse events included diarrhea (61%), fatigue (54%), hypertension (30%), stomatitis (30%), HFS (29%), and asthenia (20%) [4]. Laboratory abnormalities also found that included leukopenia (78%), anemia (79%), increased creatinine (70%), and thrombocytopenia (68%) [4]. If adverse events depends on the degree of systemic exposure to sunitinib, on which clinical efficacy also depends, adverse events might be potential predictors of sunitinib efficacy [21]. Several authors have described the correlation between sunitinib responses and selected treatment-related adverse events.
3.3.1. Hypertension
Hypertension is commonly associated with targeted therapy. It develops when VEGF stimulates production of nitric oxide and prostacyclins in vascular endothelial cells [22, 23], vasodilatory mechanisms become inhibited, and peripheral vascular resistance increases, leading to increased blood pressure.
Rini et al. [24] demonstrated that sunitinib-associated hypertension is associated with improved clinical outcomes without clinically significant increases in hypertension-associated adverse events. This analysis included large pooled data from four clinical trilas of 4915 patients with metastatic renal tumor who were treated with sunitinib. Sunitinib-induced hypertension had significantly better outcomes than those without treatment-induced hypertension in the objective response rate (54.8%
Bono et al. [25] reported that sunitinib-induced hypertension was associated with frequent tumor response (
Szmit et al. [26] reported that patients who developed hypertension related to sunitinib treatment experienced significantly longer progression-free survival time and overall survival time compared to those who did not hypertension (
Rixe et al. [27] reported that appearance or worsening hypertension was found to be the single independent predictor of a better clinical response to sunitinib on multivariate analysis using logistic regression model (
Overall, hypertension related to sunitinib was a positive predictive factor associated with significantly better objective response rate, longer progression-free survival and overall survival in patients with metastatic renal tumor treated with sunitinib.
3.3.2. Hypothyroidism
Treatment-related hypothyroidism has been reported a useful predictor of progression-free survival for metastatic renal tumors undergoing treatment with sunitinib [28]. In the 52 patients with metastatic renal tumor treated with sunitinib, 13 patients (25.0%) developed hypothyroidism during treatment. Subclinical hypothyroidism was defined as serum TSH above the upper limit of normal, with total triiodothyronine (T3) and thyroxine (T4) within normal limits. Clinical hypothyroidism was defined as low serum T3 and T4 together with elevated TSH. Hypothyroidism was associated with a longer progression-free survival time (
3.4. Others
Han et al. [29] reported the initial tumor enhancement on contrast-enhanced computed tomography (CT) could be useful as a clinical predictor during targeted therapy in 198 metastatic lesions of 46 patients. On multivariate analyses, tumor enhancement and enhancement pattern were associated with objective responses (
Kayani et al [30] revealed prognostic significance of 18F-fluorodeoxyglucose-positron emission tomography (FDG-PET)/CT as a biomarker of response to sunitinib. A total of 44 patients with newly diagnosed untreated metastatic renal tumor were enrolled in this study. 18F-FDG-PET/CT scans were conducted before, after 4 weeks, and after 16 weeks of sunitinib given. On multivariate analysis, a high SUVmax and an increased number of PET-positive lesions correlated with shorter overall survival. The early metabolic responses are associated with a pharmacodynamic effect of drug and it is not until later identification with acquired resistance occurs [30].
Yuasa et al. [31] reported that initial tumor size is inversely associated with the tumor reduction rate of individual metastatic sites and primary tumors in patients with metastatic renal tumor who underwent targeted therapy. A data from 139 metastatic and 16 primary lesions treated with targeted agents were analyzed. Both univariate and multivariate linear regression analyses revealed that only the initial tumor size was associated with the rate of reduction in individual tumors (
Abel et al. [32] reported that early 10% decrease in tumor diameter of the primary tumor was predictive of improved overall survival in patients with metastatic renal tumor treated with sunitinib. In 75 consecutive treatment-naive patients, median overall survival time for patients without minor primary tumor response, with minor primary tumor response after 60 days, and with early minor primary tumor response was 10.3, 16.5, and 30.2 months, respectively. On multivariate analysis, early minor response was an independent predictor of improved overall survival (
High visceral fat area could be a predictive biomarker from shorter survival in patients given first-line antiangiogenic agents including sunitinib for metastatic renal tumors [33]. In 113 study population, 46 patients received sunitinib as first-line therapy. Visceral fat area was measured retrospectively on the available CT scans performed before sunitinib initiation at the level of the umbilicus with the patient in the supine position. ImageJ software was used to measure pixels with densities in the -190 Hounsfield units to -30 Hounsfield units range to delineate the visceral compartment and to compute the cross-sectional area of each in cm2. On multivariate analysis, high visceral fat area was independently associated with shorter time to progression and overall survival. Visceral fat area measured before starting first-line targeted therapy is likely to be a simple predictive biomarker in patients with metastatic renal tumor [33].
Finally, hyponatremia seem to represent significant predictive factor for cancer-specific survival in metastatic renal tumors treated with targeted therapy as first-line therapy [34]. A total of 87 patients treated with targeted therapy including sunitinib, severe (≤ 134 mEq/L) and mild (135-137 mEq/L) hyponatremia was shown to be significantly associated with cancer-specific survival time (
4. Conclusions
Candidate biomarkers to predict response to sunitinib have been shown. Among clinical factors, CRP is a significant independent prognostic indicator for sunitinib. Severe adverse events, hypertension and hypothyroidism also recognized as biomarkers of favorable efficacy. Additionally, tumor enhancement, SUVmax on FDG/PET-CT, tumor size, visceral fat area and hyponatremia have been revealed clinical significance of sunitinib responses. Although further investigation will be required, these biomarkers can be utilized to measure therapeutic response and design treatment strategies for advanced renal tumors treated with sunitinib.
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