Comparison of performance of composite biomarkers of inflammatory response in determining the prognosis of breast cancer patients
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Bohuslav Melichar
Abstract
In the present study, we determined complex indices of inflammatory activity and compared the performance of these indices as prognostic biomarkers in a cohort of breast cancer patients. All proposed composite biomarkers could be evaluated in 418 out of 474 patients in the cohort with complete data on peripheral blood cell count, urinary neopterin, albumin and C-reactive protein. Neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, platelet-to-lymphocyte ratio, systemic inflammatory index, Glasgow prognostic index, modified Glasgow prognostic index, prognostic nutritional index and C-reactive protein/albumin ratio were calculated and further complex indices were proposed. Although a number of the investigated indices were significantly associated with survival in the univariate analysis, only age and stage, but none of the laboratory biomarkers or composite biomarkers, were significant predictors of survival in the whole group in the multivariate analysis. In patients evaluated before the start of the treatment, age, stage and urinary neopterin were significant predictors of survival. These results underscore the importance of neopterin as a prognostic biomarker in breast cancer.
Introduction
In cancer patients, the estimation of patient prognosis plays an indispensable role in the management and determination of the therapeutic strategy. Prognostic assessment provides help in the selection of appropriate therapeutic measures as well as avoidance of unnecessary therapy [1]. Moreover, some of the prognostic biomarkers also predict the response to therapy. Although most attention has been so far devoted to the biomarkers reflecting the properties of tumor cells, the significance of the inflammatory phenomena that are associated with the antitumor host response is currently being increasingly acknowledged [2].
Biomarkers of the inflammatory response that have been used in medical oncology over the past decades include also neopterin. Urinary or serum neopterin concentrations are elevated in a wide range of disorders, including, among others, malignant neoplasms, infectious disorders, transplant rejections, autoimmune diseases or complications of atherosclerosis [3], [4], [5], [6], [7], [8], [9], [10]. An association of increased neopterin concentrations with poor prognosis has been reported in patients with different cancers [6], [11], [12], [13], [14]. Simple biomarkers calculated as ratios of lymphocytes to other components of peripheral blood have been introduced during the last few years [15]. Neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR) and platelet-to-lymphocyte ratio (PLR) represent independent prognostic biomarkers across a spectrum of different primary tumors [16], [17], [18], [19], [20]. Because the peripheral blood cell count (PBC) and biochemical parameters like C-reactive protein or albumin are determined in virtually all patients, a number of retrospective analyses on large cohorts have been performed using retrospective databases. Other composite biomarkers like Glasgow prognostic score have also been introduced [21], [22], [23].
In an earlier investigation of the present cohort, we have reported that urinary neopterin concentration is an independent prognostic biomarker [11]. In subsequent analysis, the prognostic significance of PBC-derived ratios examined along with the prognostic significance of urinary neopterin was investigated, and neopterin, but not PBC-derived ratios, was found to be an independent predictor of survival in patients with active disease [24]. The lack of correlation between neopterin and PBC-derived ratios observed in prior studies [24], [25] opens the way for the combination of neopterin and PBC-derived ratios in complex indices of inflammatory activity that could eventually improve performance.
In the present study, we calculated more complex indices of inflammatory activity and compared the performance of these indices as prognostic biomarkers in a cohort of patients who had complete biomarker data with updated survival information.
Materials and methods
The present cohort of patients has been described in detail in previous reports [11], [24]. The projects have been approved by the institutional ethical committee, and the patients signed informed consent. Most patients in this cohort (n=216) had the laboratory parameters of interest determined before the start of any therapy (surgical and/or medical). The remaining patients were investigated in other settings, including patients evaluated after local therapy and before the start of systemic adjuvant therapy (n=47), previously treated patients investigated before the start of systemic therapy for metachronous recurrent or metastatic disease (n=16), patients studied during the course of treatment for recurrent or metastatic disease (n=12), patients evaluated during adjuvant hormonal therapy (n=84) or patients evaluated during the course of follow-up not treated with any antitumor therapy (n=13). The survival data on this cohort were updated. Urinary neopterin, serum C-reactive protein (CRP), albumin and PBC with manual differential count were determined as described earlier [25]. NLR, LMR, PLR, systemic inflammatory index (SII), Glasgow prognostic index (GPI), modified Glasgow prognostic index (mGPI), prognostic nutritional index (PNI) and CRP/albumin ratio were calculated [22], [25], [26], [27], [28]. New putative composite indices calculated here included product of CRP and urinary neopterin concentrations, neopterin/albumin ratio, SII/hemoglobin ratio, neopterin/lymphocyte ratio, product of NLR and neopterin, product of PLR and neopterin, product of LMR and neopterin, product of SII and neopterin, product of SII and CRP, SII/albumin ratio, product of neopterin/albumin ratio and SII, product of CRP/albumin ratio and SII. In many patients, the value of CRP was below detection limit, so another composite biomarker in addition to the product of CRP and neopterin was calculated. The median of numerical value of neopterin was approximately 76 times higher than CRP, so this urinary neopterin and CRP index (NCI) was calculated as the sum of neopterin plus 76× CRP. Furthermore, NCI/albumin ratio, product of NCI and SII, product of SII and NCI/albumin ratio and product of SII and NCI/albumin ratio divided by hemoglobin were calculated.
Correlations were analyzed using Spearman’s rank correlation coefficient (rs). Survival analysis was assessed using Cox proportional hazard regression. In the univariate analysis, variables with p-value <0.1 were chosen for subsequent multivariate analysis. The results were expressed as hazard ratio (HR) and 95% confidence intervals (CI) in both univariate and multivariate analyses. The decision on statistical significance was based on p=0.05 level. The analyses were performed using SAS/STAT® 9.3 software (SAS Institute Inc., Cary, NC, USA).
Results
Of the 474 patients in the original cohort, 418 (88.2%) had complete data on urinary neopterin, CRP, albumin and PBC with manual differential count, and the analysis was restricted to these patients. Although the median follow-up of surviving patients in the most recent prior report was 103.7 months [24], the median follow-up in the current report was 124.3 months. Correlations between urinary neopterin, serum CRP, albumin and established composite biomarkers, including NLR, LMR, PLR, SII, GPI and CRP/albumin ratio, are shown in Table 1. The values of GPI and mGPI were identical in this cohort (rs=1.000); therefore, only the values of GPI are indicated in the Table 1. Urinary neopterin correlated significantly with CRP, GPI and CRP/albumin ratio, but none of the PBC-derived ratios. CRP correlated, in addition to urinary neopterin and CRP/albumin ratio, with albumin (inverse correlation), NLR, LMR (inverse correlation), SII and PNI (inverse correlation). In addition to obvious correlation with GPI, CRP/albumin ratio and PNI, serum albumin correlated inversely with NLR and positively with LMR.
Correlation between urinary neopterin, CRP, albumin and established composite biomarkers in 418 patients of the present cohort.
| Urinary neopterin | CRP | Albumin | GPI | CRP/albumin | NLR | LMR | PLR | SII | |
|---|---|---|---|---|---|---|---|---|---|
| CRP | 0.432 (<0.00001) | – | – | – | – | – | – | – | – |
| Albumin | −0.046 (0.347) | −0.258 (<0.00001) | – | – | – | – | – | – | – |
| GPI | 0.144 (0.003) | 0.492 (<0.00001) | −0.251 (<0.00001) | – | – | – | – | – | – |
| CRP/albumin ratio | 0.211 (0.00001) | 0.993 (<0.00001) | −0.338 (<0.00001) | 0.489 (<0.00001) | – | – | – | – | – |
| NLR | −0.003 (0.957) | 0.206 (0.00002) | −0.150 (0.002) | 0.117 (0.016) | 0.212 (<0.00001) | – | – | – | – |
| LMR | −0.055 (0.259) | −0.127 (0.010) | 0.114 (0.020) | −0.039 (0.424) | −0.132 (0.007) | −0.500 (<0.00001) | – | – | – |
| PLR | 0.023 (0.645) | 0.081 (0.100) | −0.003 (0.948) | −0.021 (0.666) | 0.078 (0.110) | 0.692 (<0.00001) | −0.476 (<0.00001) | – | – |
| SII | −0.030 (0.544) | 0.222 (<0.00001) | −0.063 (0.198) | 0.090 (0.066) | 0.220 (<0.00001) | 0.901 (<0.00001) | −0.443 (<0.00001) | 0.775 (<0.00001) | – |
| PNI | −0.093 (0.058) | −0.180 (0.0002) | 0.728 (<0.00001) | −0.141 (0.004) | −0.238 (<0.00001) | −0.557 (<0.00001) | 0.388 (<0.00001) | −0.512 (<0.00001) | −0.381 (<0.00001) |
Shown are the values of Spearman’s correlation coefficient (rs) with p-value in parenthesis. Significant correlations are set in boldface.
By the time of the analysis 128 patients died. Table 2 shows the performance of the investigated parameters (as continuous variables) in the univariate analysis of overall survival. As indicated in the Table 2, in addition to age many of these parameters, including hemoglobin, absolute leukocyte count, relative polymorphonuclear (PMC) count, relative lymphocyte count, absolute PMN count, NLR, CRP, albumin, CRP/albumin ratio, product of CRP and neopterin, NCI, NCI/albumin ratio and SII/hemoglobin ratio were significantly associated with overall survival in univariate analysis. Given the heterogeneity of settings in which the patients were evaluated, a separate analysis was performed in the largest subgroup of patients evaluated before the start of therapy. In this subgroup of patients, in addition to age, biomarkers including urinary neopterin, relative lymphocyte count, GPI, mGPI, neopterin/lymphocyte ratio, product of NLR and neopterin, and neopterin/albumin ratio were predictive of overall survival (Table 3). However, in the multivariate analysis of the whole cohort, only age and stage, but none of the composite biomarkers, were significant predictors of survival (Table 4). In patients evaluated before the start of treatment, age, stage and urinary neopterin were significant predictors of prognosis (Table 5).
Prognostic significance of the investigated parameters in univariate analysis (entire cohort).
| Parameter | HR | 95% CI | p-Value |
|---|---|---|---|
| Age, years | 1.042 | 1.025–1.059 | <0.0001 |
| Urinary neopterin, μmol/mol creatinine | 1.000 | 1.000–1.001 | 0.420 |
| Hemoglobin, g/L | 0.982 | 0.966–0.997 | 0.021 |
| Platelet count, 109/L | 0.999 | 0.997–1.002 | 0.681 |
| Leukocyte count, 109/L | 1.150 | 1.054–1.255 | 0.002 |
| Relative PMN count, % | 1.020 | 1.003–1.038 | 0.024 |
| Relative monocyte count, % | 0.987 | 0.930–1.047 | 0.668 |
| Relative lymphocyte count, % | 0.975 | 0.955–0.994 | 0.011 |
| Absolute PMN, 106/L | 1.000 | 1.000–1.000 | 0.001 |
| Absolute monocyte count, 106/L | 1.001 | 1.000–1.001 | 0.153 |
| Absolute lymphocyte count, 106/L | 1.000 | 1.000–1.000 | 0.796 |
| PNI | 0.963 | 0.926–1.002 | 0.064 |
| NLR | 1.112 | 1.030–1.200 | 0.006 |
| PLR | 1.000 | 0.998–1.002 | 0.708 |
| LMR | 0.959 | 0.915–1.005 | 0.082 |
| SII | 1.000 | 1.000–1.001 | 0.071 |
| CRP, mg/L | 1.013 | 1.004–1.022 | 0.003 |
| Albumin, g/L | 0.905 | 0.852–0.962 | 0.001 |
| GPI | 1.723 | 0.965–3.077 | 0.066 |
| mGPI | 1.723 | 0.965–3.077 | 0.066 |
| CRP/albumin ratio | 1.694 | 1.212–2.368 | 0.002 |
| CRP×neopterin | 1.000 | 1.000–1.000 | 0.005 |
| NCI | 1.000 | 1.000–1.000 | 0.003 |
| Neopterin/albumin ratio | 1.016 | 0.987–1.045 | 0.278 |
| NCI/albumin ratio | 1.007 | 1.003–1.011 | 0.001 |
| SII/hemoglobin ratio | 1.043 | 1.005–1.081 | 0.025 |
| SII×urinary neopterin | 1.000 | 1.000–1.000 | 0.143 |
| SII×CRP | 1.000 | 1.000–1.000 | 0.220 |
| SII×NCI | 1.000 | 1.000–1.000 | 0.174 |
| SII/albumin ratio | 1.012 | 1.000–1.024 | 0.044 |
| SII×neopterin/albumin | 1.000 | 1.000–1.000 | 0.107 |
| SII×CRP/albumin | 1.000 | 1.000–1.000 | 0.207 |
| SII×NCI/albumin ratio | 1.000 | 1.000–1.000 | 0.163 |
| SII×NCI/albumin×hemoglobin | 1.000 | 1.000–1.000 | 0.108 |
| Neopterin/lymphocyte ratio | 1.192 | 0.795–1.787 | 0.396 |
| Neopterin×NLR | 1.000 | 1.000–1.000 | 0.180 |
| Neopterin×PLR | 1.000 | 1.000–1.000 | 0.444 |
| Neopterin×LMR | 1.000 | 1.000–1.000 | 0.547 |
NCI, urinary neopterin and CRP index; PMN, polymorphonuclear cells. Significant parameters are set in boldface.
Prognostic significance of the investigated parameters in univariate analysis in patients examined before the start of therapy.
| Parameter | HR | 95% CI | p-Value |
|---|---|---|---|
| Age, years | 1.043 | 1.022–1.065 | <0.0001 |
| Urinary neopterin, μmol/mol creatinine | 1.002 | 1.001–1.004 | 0.005 |
| Hemoglobin, g/L | 0.989 | 0.967–1.011 | 0.307 |
| Platelet count, 109/L | 0.997 | 0.993–1.001 | 0.111 |
| Leukocyte count, 109/L | 1.106 | 0.982–1.246 | 0.096 |
| Relative PMN count, % | 1.017 | 0.995–1.040 | 0.127 |
| Relative monocyte count, % | 1.000 | 0.928–1.078 | 0.996 |
| Relative lymphocyte count, % | 0.975 | 0.951–0.999 | 0.045 |
| Absolute PMN, 106/L | 1.000 | 1.000–1.000 | 0.052 |
| Absolute monocyte count, 106/L | 1.000 | 0.999–1.001 | 0.492 |
| Absolute lymphocyte count, 106/L | 1.000 | 1.000–1.000 | 0.542 |
| PNI | 0.969 | 0.924–1.016 | 0.189 |
| NLR | 1.074 | 0.962–1.199 | 0.202 |
| PLR | 1.000 | 0.997–1.002 | 0.796 |
| LMR | 0.964 | 0.910–1.021 | 0.214 |
| SII | 1.000 | 1.000–1.000 | 0.609 |
| CRP, mg/L | 1.008 | 0.997–1.021 | 0.165 |
| Albumin, g/L | 0.948 | 0.881–1.021 | 0.159 |
| GPI | 2.051 | 1.112–3.785 | 0.022 |
| mGPI | 2.051 | 1.112–3.785 | 0.022 |
| CRP/albumin ratio | 1.366 | 0.859–2.171 | 0.187 |
| CRP×neopterin | 1.000 | 1.000–1.000 | 0.385 |
| NCI | 1.000 | 1.000–1.000 | 0.108 |
| Neopterin/albumin ratio | 1.114 | 1.037–1.196 | 0.003 |
| NCI/albumin ratio | 1.004 | 0.999–1.010 | 0.129 |
| SII/hemoglobin ratio | 1.014 | 0.961–1.069 | 0.610 |
| SII×urinary neopterin | 1.000 | 1.000–1.000 | 0.079 |
| SII×CRP | 1.000 | 1.000–1.000 | 0.977 |
| SII×NCI | 1.000 | 1.000–1.000 | 0.937 |
| SII/albumin ratio | 1.004 | 0.988–1.020 | 0.646 |
| SII×neopterin/albumin | 1.000 | 1.000–1.000 | 0.105 |
| SII×CRP/albumin | 1.000 | 1.000–1.000 | 0.945 |
| SII×NCI/albumin ratio | 1.000 | 1.000–1.000 | 0.980 |
| SII×NCI/albumin×hemoglobin | 1.000 | 0.999–1.000 | 0.976 |
| Neopterin/lymphocyte ratio | 10.953 | 1.436–83.515 | 0.021 |
| Neopterin×NLR | 1.000 | 1.000–1.001 | 0.022 |
| Neopterin×PLR | 1.000 | 1.000–1.000 | 0.081 |
| Neopterin×LMR | 1.000 | 1.000–1.000 | 0.996 |
NCI, urinary neopterin and CRP index; PMN, polymorphonuclear cells. Significant parameters are set in boldface.
Prognostic significance of the investigated parameters in multivariate analysis (entire cohort).
| Parameter | HR | 95% CI | p-Value |
|---|---|---|---|
| Age, years | 1.044 | 1.024–1.064 | <0.0001 |
| Stage | <0.0001 | ||
| 4 vs. 2 | 8.728 | 4.861–15.671 | <0.0001 |
| 3 vs. 2 | 1.799 | 1.174–2.757 | 0.007 |
| 1 vs. 2 | 0.073 | 0.010–0.530 | 0.010 |
Prognostic significance of the investigated parameters in multivariate analysis in patients examined before the start of therapy.
| Parameter | HR | 95% CI | p-Value |
|---|---|---|---|
| Age, years | 1.037 | 1.015–1.060 | 0.001 |
| Urinary neopterin, μmol/mol creatinine | 1.002 | 1.001–1.004 | 0.009 |
| Stage | <0.0001 | ||
| 4 vs. 2 | 5.653 | 2.731–11.702 | <0.0001 |
| 3 vs. 2 | 1.443 | 0.884–2.355 | 0.134 |
Discussion
The present retrospective analysis has failed to establish any new composite biomarker of inflammatory response. Moreover, the composite biomarkers of inflammatory response already established were also not significant predictors in the multivariate analysis. These negative findings may partly be explained by the heterogeneity of the settings in which the patients in the present cohort were investigated. Rather than a single entity breast cancer is a very heterogeneous disease in terms of tumor type, biology, stage, patient age, presence of comorbidities, treatment administered and other factors. Moreover, the present cohort included patients studied at different time points during the course of the disease and therapy. However, when the analysis was restricted to patients investigated before the start of treatment, only urinary neopterin significantly predicted prognosis in addition to obvious parameters like stage and age. Thus, based on the results of this retrospective analysis, urinary neopterin appears to be superior to any of the composite biomarkers investigated. Along with prior analyses of the present cohort after a shorter follow-up [11], [24] present data demonstrate that urinary neopterin is an independent prognostic factor in untreated breast cancer patients.
The prognostic significance of PBC-derived ratios in patients with different primary tumors as well as patients affected with non-neoplastic disorders has been reported in numerous prior studies [16], [17], [18], [19], [20], [29], [30], [31], [32], [33], [34], [35]. It has been demonstrated that serum or urinary concentrations of neopterin represent a valuable biomarker in cancer patients as well as in patients with atherosclerosis [3], [4], [6]. The negative prognostic significance of increased neopterin concentrations has been described in patients with different primary tumors [6], [11], [12], including breast cancer [11], [36]. The prognostic impact of high neopterin concentrations can be explained by an association with immune dysfunction that can be detected both systemically and in the tumor microenvironment [37], [38], [39], [40].
The curability rate of breast cancer is rather high, most patients presenting with early disease are cured, and, in many instances, the cause of death is not breast cancer. The complications of atherosclerosis probably represent the most common competitive cause of death in breast cancer patients. Similarly to cancer, atherosclerosis is accompanied by inflammatory response. Neopterin and PBC-derived ratios have also been reported to represent biomarkers of atherosclerosis and complications accompanying atherosclerosis and to predict the risk of related events [7], [29], [30], [31], [32], [33], [34], [35]. Surprisingly, only limited information is currently available with regard to a correlation or comparison between PBC-derived ratios and other biomarkers of inflammatory response [41], [42].
There is little doubt that, in addition to early diagnosis, improved systemic therapy has contributed to the amelioration of outcome in breast cancer patients. At the same time, accumulating evidence indicates that the administration of systemic therapy could cause the acceleration of atherosclerosis [43]. Inflammatory response induced by tumor growth or systemic therapy may accelerate the progression of atherosclerosis in patients with breast cancer [44]. Thus, the nonspecific nature of biomarkers like neopterin and PBC-derived ratios could even be viewed as an advantage in breast cancer patients because it may simultaneously predict mortality from two principal competitive causes of death in this patient population.
Alterations of PBC-derived ratios are encountered in a similar spectrum of different pathologies as in the case of neopterin [16], [17], [18], [19], [20], [29], [30], [31], [32], [33], [34], [35]. In addition, NLR and CRP have been reported to correlate in cancer patients [42] or patients suffering from the complications of atherosclerosis [41]. Significant correlations between NLR, LMR or PLR and urinary neopterin would be expected as PBC-derived ratios as well as serum or urinary neopterin concentrations accompany the inflammatory response induced by the host response against cancer. Surprisingly and contrary to this hypothesis, no statistically significant correlation between neopterin and PBC-derived ratios was evident in large cohorts of breast cancer patients. Because neopterin and PBC-derived ratios seem to represent independent biomarkers of inflammatory response, we hypothesized that these laboratory parameters may be combined to calculate composite markers that were investigated in the present study. The aim was to identify potential new biomarkers that could be tested in future prospective studies. As indicated above, this effort has failed, and none of the new proposed biomarkers can be recommended for future study. Moreover, these results underline the value of urinary neopterin as an independent prognostic biomarker in breast cancer. In cancer patients, urinary neopterin is a prognostic biomarker, and it may also be used to monitor toxicity of anticancer therapy. For example, the gastrointestinal toxicity of anticancer therapy is difficult to monitor in the laboratory [45], [46]. In a recent study, increased neopterin concentrations during radiotherapy for rectal cancer were associated with irradiated gut volume and predicted the occurrence of serious toxicity [47].
The present study has obvious limitations that are related to its retrospective nature, and the results of an analysis on this rather heterogeneous cohort of patients should be regarded only as hypothesis generating and confirmed in prospective setting. The cohort size and the number of events were relatively small for a multivariable model, especially considering the heterogeneity of the population. The size of different subgroups precluded a statistical analysis, although separate analysis of treatment-naive patients seems meaningful. Because of the hypothesis-generating nature of this study, biomarkers were evaluated as continuous variables. Setting the cutoff values that would dichotomize the parameters would be arbitrary and associations could be obscured. The aim of this study was to identify new composite biomarkers. Trying to define a cutoff would be next step after the identification of an independent predictor of prognosis in the multivariate analysis. Since none of the composite biomarkers, whether established or newly defined, was significantly associated with prognosis in the multivariate analysis, the issue of appropriate cutoff values was not addressed in the present study that should be regarded as negative. Both urinary neopterin and PBC-derived ratios reflect systemic immune and inflammatory phenomena associated with the host response to the tumor, but even more important for the outcome of the antitumor response may be the tumor microenvironment that is difficult to assess [39], [40], [48], [49].
In conclusion, although most of the proposed composite biomarkers were predictive of prognosis in univariate analysis, none was an independent prognostic biomarker in the multivariate analysis. Neopterin represents an independent prognostic biomarker in patients before the start of therapy.
Acknowledgments
This study was supported by the grant of the Czech Health Research Council 16-32030A.
Conflict of interest statement: The authors have declared no conflicts of interest.
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Articles in the same Issue
- Frontmatter
- Reviews
- Photosensitization of peptides and proteins by pterin derivatives
- Polyamines, folic acid supplementation and cancerogenesis
- Mini review
- Medical significance of simultaneous application of red blood cell distribution width (RDW) and neopterin as diagnostic/prognostic biomarkers in clinical practice
- Original articles
- Molecular architecture of pterin deaminase from Saccharomyces cerevisiae NCIM 3458
- Quantitative analysis by flow cytometry of green fluorescent protein-tagged human phenylalanine hydroxylase expressed in Dictyostelium
- Age-dependance of pteridines in the malaria vector, Anopheles stephensi
- Seasonality of blood neopterin levels in the Old Order Amish
- Correlation of salivary neopterin and plasma fibrinogen levels in patients with chronic periodontitis and/or type 2 diabetes mellitus
- Positive association between Toxoplasma gondii IgG serointensity and current dysphoria/hopelessness scores in the Old Order Amish: a preliminary study
- Sleep onset insomnia, daytime sleepiness and sleep duration in relationship to Toxoplasma gondii IgG seropositivity and serointensity
- Concentrations of neopterin, kynurenine and tryptophan in wound secretions of patients with breast cancer and malignant melanoma: a pilot study
- Comparison of performance of composite biomarkers of inflammatory response in determining the prognosis of breast cancer patients
- Association of peripheral blood cell count-derived ratios, biomarkers of inflammatory response and tumor growth with outcome in previously treated metastatic colorectal carcinoma patients receiving cetuximab
- Neoadjuvant combination therapy with trastuzumab in a breast cancer patient with synchronous rectal carcinoma: a case report and biomarker study
Articles in the same Issue
- Frontmatter
- Reviews
- Photosensitization of peptides and proteins by pterin derivatives
- Polyamines, folic acid supplementation and cancerogenesis
- Mini review
- Medical significance of simultaneous application of red blood cell distribution width (RDW) and neopterin as diagnostic/prognostic biomarkers in clinical practice
- Original articles
- Molecular architecture of pterin deaminase from Saccharomyces cerevisiae NCIM 3458
- Quantitative analysis by flow cytometry of green fluorescent protein-tagged human phenylalanine hydroxylase expressed in Dictyostelium
- Age-dependance of pteridines in the malaria vector, Anopheles stephensi
- Seasonality of blood neopterin levels in the Old Order Amish
- Correlation of salivary neopterin and plasma fibrinogen levels in patients with chronic periodontitis and/or type 2 diabetes mellitus
- Positive association between Toxoplasma gondii IgG serointensity and current dysphoria/hopelessness scores in the Old Order Amish: a preliminary study
- Sleep onset insomnia, daytime sleepiness and sleep duration in relationship to Toxoplasma gondii IgG seropositivity and serointensity
- Concentrations of neopterin, kynurenine and tryptophan in wound secretions of patients with breast cancer and malignant melanoma: a pilot study
- Comparison of performance of composite biomarkers of inflammatory response in determining the prognosis of breast cancer patients
- Association of peripheral blood cell count-derived ratios, biomarkers of inflammatory response and tumor growth with outcome in previously treated metastatic colorectal carcinoma patients receiving cetuximab
- Neoadjuvant combination therapy with trastuzumab in a breast cancer patient with synchronous rectal carcinoma: a case report and biomarker study
