Development and validation of a clinical prediction rule to identify suspected breast cancer: a prospective cohort study

Rose Galvin
Doireann Joyce
Eithne Downey
Fiona Boland
Tom Fahey
Arnold K Hill
Development and validation of a clinical prediction rule to identify suspected breast cancer: a prospective cohort study
R E S E A R C H A R T I C L E Open Access
Background: The number of primary care referrals of women with breast symptoms to symptomatic breast units (SBUs) has increased exponentially in the past decade in Ireland. The aim of this study is to develop and validate a clinical prediction rule (CPR) to identify women with breast cancer so that a more evidence based approach to referral from primary care to these SBUs can be developed.Methods:We analysed routine data from a prospective cohort of consecutive women reviewed at a SBU with breast symptoms. The dataset was split into a derivation and validation cohort. Regression analysis was used to derive a CPR from the patient's history and clinical findings. Validation of the CPR consisted of estimating the number of breast cancers predicted to occur compared with the actual number of observed breast cancers across deciles of risk.Results: A total of 6,590 patients were included in the derivation study and 4.9% were diagnosed with breast cancer. Independent clinical predictors for breast cancer were: increasing age by year (adjusted odds ratio 1.08, 95% CI 1.07-1.09); presence of a lump (5.63, 95% CI 4.2-7.56); nipple change (2.77, 95% CI 1.68-4.58) and nipple discharge (2.09, 95% CI 1. 1-3.97). Validation of the rule (n = 911) demonstrated that the probability of breast cancer was higher with an increasing number of these independent variables. The Hosmer-Lemeshow goodness of fit showed no overall significant difference between the expected and the observed numbers of breast cancer (χ 2 HL : 6.74, p-value: 0.56). Conclusions: This study derived and validated a CPR for breast cancer in women attending an Irish national SBU. We found that increasing age, presence of a lump, nipple discharge and nipple change are all associated with increased risk of breast cancer. Further validation of the rule is necessary as well as an assessment of its impact on referral practice.

Background

In 2007, there were 2,463 new cases of breast cancer diagnosed in Ireland making it the most common invasive cancer in Irish women [1]. Advances in diagnosis and treatment have resulted in an increase in survival rates from breast cancer [2,3]. In spite of this, breast cancer remains the biggest cause of death from cancer in women in Ireland [1]. Following centralisation of breast cancer services, the National Cancer Control Programme (NCCP) introduced clinical guidelines to enhance the referral process to symptomatic breast units (SBU) [4]. Based on these guidelines, General Practitioners (GPs) act as gatekeepers responsible for clinical assessment and are required to prioritise patient referral as 'urgent', 'early' or 'routine' for subsequent examination at a SBU within two weeks, six weeks or 12 weeks respectively [4]. Figures from the 2012 NCCP report showed a 60% increase in SBU attendees from 23,575 in 2006 to 37,631 in 2010 [5]. The proportional increase in the benign: malignant ratio of patients in SBU means that a review of the diagnostic criteria, and their underlying evidence base is needed.

Clinical prediction rules (CPRs) are clinical tools that quantify the independent impact of factors from a patients history, physical examination and diagnostic tests and stratify patients according to the probability of having a target disorder [6]. Before widespread clinical implementation, CPRs should undergo three stages of development: (i) Derivation: factors with predictive power are identified to develop the CPR; (ii) Validation: The CPR is tested in a new population for reliability and accuracy; and (iii) Impact analysis: The impact of the rule may be examined in terms of physician behavior, patient outcomes, or costs [7]. CPRs offer one way of implementing evidence based medicine, especially if incorporated into clinical decision support systems, at the point of patient care. A CPR recently derived by McCowan et al. [8] aimed to stratify patients at risk of breast cancer. Independent clinical predictors for breast cancer were increasing age by year, presence of a discrete lump, breast thickening, lymphadenopathy and lump ≥2 cm. Patients with a score of ≥4 had a 5-8% probability of having breast cancer and the authors recommended that patients in this group should be referred for further evaluation in a SBU [8]. However in Ireland, two of the five variables included in the CPR by McCowan et al. [8] are not routinely coded in the SBU database including lump size (<2 cm/≥2 cm) and breast thickening so the existing CPR cannot be validated. The aim of this study is to develop and validate a CPR for diagnosis of breast cancer using routine data collated in an Irish national SBU so that a more evidence based approach to referral from the primary care setting can be developed.

Methods

Study design and setting

We analysed routine data collected from a prospective cohort of consecutive patients reviewed at the SBU in Beaumont hospital with breast symptoms. Beaumont hospital has one of eight designated SBUs in Ireland. The SBU serves north county Dublin and the north Leinster region with a mix of urban and rural patients. Six breast surgeons run eight triple assessment clinics each week and there are four clinics dedicated to return patients and non-urgent new referrals. The SBU database (Dendrite Clinical Systems Ltd, Oxford, UK) at Beaumont contains information on clinical, radiological and pathological data for patients attending the SBU. Ethical approval was received from the Research Ethics Committee (REC) at the Royal College of Surgeons in Ireland and from Beaumont Hospital REC. The STROBE standardised reporting guidelines for cohort studies were followed to ensure standardised conduct and reporting of the study [9].

Study population

This study comprised two cohorts of patients, a derivation cohort and a validation cohort. The first stage related to the use of data contained in the SBU from March 2011-June 2012 (inclusive) to formulate or derive a new breast cancer CPR (derivation cohort). In the second stage of the study, we validated the rule in patients entered into the database from July 2012-December 2012. Exclusion criteria were: male gender, return patients or those with known breast cancer. All data was anonymised using standardised operating procedures by a data analyst at Beaumont hospital to protect patient confidentiality and privacy. The anonymised dataset was then transferred to the research team for analysis.

Predictor variables

Patients referred to the SBU in Beaumont Hospital un dergo triple assessment. This is a three step process consisting of clinical examination, radiological examination and histological examination. The first stage comprises identifying the reason for referral/clinical history and a clinical examination of the breasts and axillae by a breast surgeon. For the purposes of our study and in-keeping with our overall aim to identify a more evidence based referral process from the primary care setting, we used the variables recorded at the time of presentation to the GP as a proxy for the findings on clinical examination. Variables recorded are binary and include the presence/absence of: mastalgia, lump, abscess, inflammation, skin change, ulceration, nipple discharge, nipple changes, family history and nodularity. A free-text box includes an option to record additional symptoms. Patients may then be referred for a radiological examination of the breast and axillae. However, if no abnormality is detected on clinical examination in a patient <35 years no imaging is requested. If no abnormality is identified in a patient ≥35 years, a baseline bilateral mammogram is ordered which will act as a reference for all future breast imaging. In patients presenting with an abnormality on clinical examination (for example a lump), she is then referred for a bilateral mammogram and an ultrasound scan of the breast containing the abnormality. In cases where an abnormality is visible on mammogram and ultrasound, a core biopsy is carried out by the consultant radiologist. This process involves infiltration of the skin and breast tissue with local anaesthetic followed by ultrasound guided biopsy of the abnormality. Three to five biopsy specimens are obtained and fixed in formalin before transfer to the pathology laboratory. All biopsy specimens are examined macroscopically and microscopically by a consultant pathologist.

Outcome

The outcome of breast cancer is recorded as a binary variable and is based on the findings from diagnostic histology on biopsy or excision biopsy.

Statistical analysis Derivation study

Descriptive statistics including means and standard deviations were computed. The first stage of the analysis was to investigate the univariate associations for the explanatory variables -clinical history and examination findings with the outcome of breast cancer. These results are expressed as odd ratios (ORs) where values >1 indicate increased odds of the presence of breast cancer and values of <1 suggest decreased odds of breast cancer. For inclusion into the multivariable logistic regression model, explanatory variables had to be considered of prior clinical importance or have a threshold p-value of ≤ 0.15 in the univariate analysis [8].

The final multivariate regression model was used to create a clinical prediction rule. We followed the method used by the Framingham Heart Study to calculate points associated with each level/category of our risk factors [10]. This points system was developed to make complex statistical models useful to practitioners by simplifying the estimation of risk. Firstly the estimates of the regression coefficients (equivalent to the logORs) of the multivariable logistic regression model were found and the referent risk factor profile determined. Secondly we calculated how far all other risk levels/categories were from the referent level/category (in regression units) and used this to assign integer points to each level/category of each risk factor. Hence, a specific risk factor profile could be obtained by summing these integer points. Finally, a reference table, with risk estimates for each points total was constructed.

Validation study

We examined two aspects of validity of our results, calibration and discrimination. Calibration (or reliability) reflects how closely predicted outcomes agree with the actual outcomes. The model was calibrated by applying the regression coefficients from the derivation cohort to the individuals in the validation cohort and generating expected probabilities of breast cancer. Deciles of risk categories of expected and observed breast cancer cases were generated for comparison using the Hosmer-Lemeshow test (HLT) [11].

Discrimination refers to the ability of the rule to distinguish correctly the patients with different outcomes (breast cancer/no breast cancer). The c statistic, or area under the curve (AUC), with 95% confidence interval (CI) was estimated to describe model discrimination. The area under a ROC curve quantifies the overall ability of the test to discriminate between those individuals with breast cancer and those without breast cancer. The c statistic ranges from 0.5 (no discrimination) to a theoretical maximum of 1, values between 0.7 and 0.9 represent moderate accuracy and greater than 0.9 represents high accuracy [12]. A c statistic of 1 represents perfect discrimination, whereby scores for all cases with breast cancer are higher than those for all the non-cases with no overlap. All statistical analyses were completed using STATA (version 12, Stata Corp, College Station, Texas, USA).

Results

Overall descriptive characteristics There were 7,784 unique patient consultations recorded at the SBU in Beaumont hospital during the study period. A total of 7,567 patients (97.2%) were female and 217 (2.8%) were male. All male patients were excluded from our analysis. A further 66 patients were also excluded due to age <18 years (n = 62) and diagnosis of recurrent or metastatic breast cancer (n = 4), leaving 7,501 for analysis (6,590 in the derivation study and 911 in the validation study). The mean age of these women was 44 years (SD 13.6 years, range 18-97 years). A total of 1,582 women underwent a biopsy in the entire cohort and 357 of these patients (4.8%) were diagnosed with breast cancer, with the remainder (n = 7144, 95.2%) having either benign breast disease or normal breasts. Table 1 displays the frequency of symptom presentation in the cohort (n = 7,501). Almost half of patients (n = 3,735) presented with a breast lump and one third presented with mastalgia (n = 2,488).

Derivation study

The derivation study examined patients attending the Beaumont hospital SBU between March 2011 and June 2012 (inclusive). A total of 6,590 patients were evaluated in this initial stage of the study. The mean age of these women was 44.3 years (SD 13.6 years, range 18-97 years) and the most common reason for referral to the SBU was the presence of a lump (n = 3,244). A primary breast cancer diagnosis was made in 320 patients (4.9%) and the remainder (n = 6,270, 95.1%) were diagnosed with no abnormality or benign breast pathology only. In the derivation cohort, 86.9% of the patients who were diagnosed with breast cancer were triaged as urgent (n = 278). Almost all referrals were received from a general practitioner (n = 6,524, 99%), representing 95% of the subsequent cancer diagnoses. Other sources of referral included referrals from the accident and emergency department (n = 17), hospital inpatient referrals (n = 25) or referrals from other hospitals (n = 24).

Univariate associations for clinical features of women presenting with breast symptoms are displayed in Table 2. Our results show that increasing age, presence of a lump and nipple changes were all associated with breast cancer. The results of the multivariate derivation model are expressed as odds ratios and displayed in Table 3. We also included nipple discharge in the final multivariate logistic regression model as it may have been recorded as a proxy for pathologic nipple discharge, a variable associated with an increased incidence of breast cancer [13]. The regression coefficients for these predictors are also displayed in Table 3 [10].

Validation study

The validation study comprised patients attending the Beaumont hospital SBU between July-December 2012 (inclusive). A total of 911 patients were included in the validation study. The mean age of these women was 41.5 years (SD 13.3 years, range 18-89 years). Thirty seven patients in this group were diagnosed with breast cancer following triple assessment (4.06%) with the remainder (n = 874, 95.9%) having either normal breasts or benign breast disease. The majority of patients (n = 22, 89.2%) who were diagnosed with breast cancer were triaged as urgent. The most common reason for referral to the SBU was a discrete breast lump which was present in 53.9% of referrals (n = 491).

Calibration

Based on the derivation model, the probability for having breast cancer in the validation cohort was used to divide subjects into deciles. In each of the deciles, the number of expected breast cancer cases (expected) was compared to the actual number of breast cancer cases (observed). Figure 1 shows that the expected number of breast cancer cases was less than the observed number of cases for some deciles of risk. This is particularly evident for patients at highest risk of breast cancer. For example the expected number of people with breast cancer was less than the number observed for the 9 th and 10 th deciles of risk. Even though Figure 1 indicates that the number of people with breast cancer was slightly underestimated for those highest at risk, the Hosmer-Lemeshow goodness of fit showed no significant difference between the expected and the observed numbers of breast cancer (χ 2 HL : 6.74, p-value: 0.56).  Discrimination Figure 2 shows the receiver operating curve (ROC), a graph of the sensitivity (y-axis) and the specificity (x-axis). In this case the area under the curve is 0. 86 (95% CI 0.79 -0.92), indicating moderate accuracy of the CPR. The simplified scoring system based on the regression model is displayed in Table 4. The variables included from the regression model were age, lump, nipple change and nipple discharge. Age was divided up into 6 categories: 18-29, 30-39, 40-49, 50-59, 60-69 and 70-99 years. Table 5 displays the incremental value of the components of the CPR and the calculation of different thresholds of risk. For example, a total score of 4 points is attributed to almost a 2% risk of breast cancer, 6 points has nearly a 6% risk, a score of ≥8 carries 17% risk and a score ≥11 has more than a 50% risk of breast cancer.

Discussion

Statement of principal findings

This study derived and validated a clinical prediction rule for diagnosis of breast cancer in symptomatic women attending an Irish national symptomatic breast unit over a 22 month period. The incidence of breast cancer was 4.9% in the overall cohort. Our results also show that increasing age, presence of a lump, nipple discharge and nipple change were all associated with breast cancer. Validation of the rule indicates that the probability of breast cancer is higher with an increasing number of these independent variables.

Results in the context of the current literature Almost five percent of referred patients in our study were found to have breast cancer, a figure similar to the Irish incidence of female breast cancer that was reported at 5.6% in 2011 [5]. The benign:malignant ratio in our study (1:19) is higher than that reported in a similar UK study where the ratio of benign to malignant detections was 1:13 in women referred to a symptomatic breast clinic [8]. The higher ratio in our study is probably a reflection of an increasing number of referrals of patients with benign breast disease to the SBU with a resultant reduction in the overall rate of cancer detection. US based studies tend to have lower ratios, most likely due to differing referral pathways and access patterns between health care systems [8,14].

The literature to date is limited around methods to identify women at risk of breast cancer, particularly in terms of identifying and prioritising those at greatest risk. A UK study by Campbell et al. [15] prospectively gathered data on 2064 patients referred to a breast unit over a 12 month period. The authors reported that increasing age (OR = 1.08, 95% CI 1.07-1.09, p < 0.001) and the presence of a discrete lump (OR = 5.08, 95% CI 3.07-8.4, p < 0.001) were significant discriminatory predictors of breast cancer, in keeping with the findings of our study. The presence of pain was not associated with the presence of breast cancer, similar to our study. A later study by McCowan et al. [8] also reported that increasing age, presence of a discrete lump, presence of a lump tethered to the skin or chest wall, a lump ≥2.0 cm in size, presence of breast thickening, lymphadenopathy all independently increased the probability of a woman having breast cancer.  Figure 1 The expected and observed breast cancers by decile of predicted risk in the validation cohort.

Our clinical prediction rule quantifies the impact of factors from a patient's history and clinical examination and subsequently stratifies patients according to their probability of having a breast cancer. The clinical variables included in the clinical prediction rule have clinical and content validity. The presence of a breast lump is the most common presenting and predictive symptom in women with breast cancer [8,16,17] while the incidence of breast cancer is consistently shown to be associated with increasing age [8,16,18]. Pathologic nipple discharge has also been associated with an increased incidence of breast cancer [13,19,20]. We included the variable 'nipple discharge' in our final model as it may have been recorded as a proxy for pathologic discharge. Almost one third of the women in our cohort presented with mastalgia, a figure higher than that reported two previous studies of this nature [8,16] but mastalgia has been reported to affect between 10-30% of women [21]. We found that the presence of mastalgia was not independently predictive of breast cancer, similar to the findings of McCowan and colleagues [8]. Research also indicates that women with a family history of breast cancer are more likely to overestimate their risk of breast cancer than women without this risk factor [22,23]. Furthermore, GPs are also more likely to refer women with a history of breast cancer [24]. We found that family history, present in one third of the entire cohort, was not predictive of breast cancer. This finding is at odds with other studies [16,25] and may be due to the different methods of data collection resulting in different prevalence estimates or the differences in settings of care. Other variables not recorded in our database that have been found to be independently predictive of a diagnosis of breast cancer include breast thickening, lymphadenopathy, size of lump, alcohol use, post-menopausal bleeding, increasing affluence, and venous thrombo-embolism [8,16].

Previous studies have questioned the value of the two week referral policy due to the low number of cancers detected in this group and have also discussed the validity of what is in essence a two tier system, whereby women triaged as 'non-urgent' referrals have to wait longer to see a specialist [26,27]. Our study supports the clinical utility of this referral process as we found that 87% the women who were subsequently diagnosed with breast cancer were triaged as 'urgent' , indicating that the waiting time between assessment by the GP and subsequent appointment in the SBU was less than two weeks.

Strengths and weaknesses of the study

This pragmatic study examined routinely collected data from over 7,500 women with suspected breast cancer to determine the factors that were most predictive of breast cancer. The predictor variables identified are easily recorded in the clinical setting and there were very few patients excluded from the analysis, optimising the external validity of the study. The incidence of cancer in our derivation and validation cohorts were also similar to national breast cancer detection figures [5]. Furthermore, we used a standard method to identify the predictor variables and derived a simple to follow rule with moderate predictive and discriminative ability. The incremental value of the components of the CPR enables the calculation of different thresholds of risk. However, the results need to be interpreted in the context of the study limitations. The data used to inform the analysis was taken from a single-centre database. Furthermore, our narrow validation study also utilised patients from the same centre, thus the model fit may be overestimated. However, we suspect that these findings can be extrapolated to the seven other SBUs nationally and most likely reflect the referral patterns and rates of diagnosis seen in the other SBUs. We used the clinical findings recorded by the GP at the time of referral as a proxy for findings of the clinical examination in the SBU. Therefore the range of symptoms included in the analysis may not reflect those present in the SBU. In addition, there is limited information recorded on side of symptoms, which was not included in the analysis.

Clinical implications

In Ireland, the introduction of clinical guidelines to enhance the referral process to SBUs has increased the referral rate to these units without an increase in the diagnostic yield. The prioritisation of referrals is not optimal either with almost 13% of those with a subsequent diagnosis of breast cancer initially classified as 'routine' or 'early' referrals. The proposed clinical prediction rule discriminates between patients at high risk of breast cancer from low risk patients and may serve as method of decreasing the number of unnecessary referrals to SBUs in women with a low probability of breast cancer. Our data indicates that the risk of breast cancer is almost 2% once a score of 4 is reached and this increased to over 5% once the score reaches a threshold of ≥6 on the CPR. However, there is a need for further multicentre broad validation studies to explore the optimal referral threshold. The tradeoff between clinical utility and patient referral has also been highlighted by other researchers [8,28]. Selecting a referral threshold would need to consider a satisfactory tradeoff in cost-effectiveness between missed cancers and unnecessary investigations. Consideration also needs to be given to situations where doctors suspect a cancer diagnosis even though their patient may not fit the guidance criteria as these are the patient group who will have a considerable gain with expedited diagnosis. On the contrary, further research is also needed to explore alternative strategies to management in women classified as low risk. For example, a woman aged 25 who presents with nipple changes to her GP has an estimated risk of 5/1000 of breast cancer. Care pathways aside from referral such as reassurance in primary care and watchful waiting warrant further consideration.

Conclusions

This study derived and validated a CPR for breast cancer in symptomatic women attending an Irish national symptomatic breast unit. We found that increasing age, presence of a lump, nipple discharge and nipple change were all associated with breast cancer. Validation of the rule indicates that the probability of breast cancer is higher with an increasing number of these independent variables. Further validation of the rule is necessary as well as an assessment of its impact on referral practice prior to adoption in the clinical setting.

*
Patients may present with more than one symptom. **Unknown/not stated (n = 1,221).

Figure 2
2Receiver operating curve for validation cohort.

Table 2
2Univariate associations between explanatory variables and breast cancer in the derivation cohortExplanatory variable
Unadjusted odds ratio
95% confidence interval (CI)
P-value

Age
1.07
1.07-1.08
<0.01

Abscess
0.53
0.20-1.44
0.22

Inflammation
0.53
0.20-1.44
0.22

Family history
0.99
0.91-1.07
0.71

Lump
3.33
2.56-4.30
<0.01

Nipple changes
1.93
1.24-3.01
<0.01

Skin changes
1.73
0.69-4.35
0.24

Nipple discharge
1.19
0.67-2.11
0.55

Ulceration
1.73
0.69-4.35
0.24

Nodularity
2.18
0.28-17.26
0.46

Note: Explanatory variables had to be considered of prior clinical importance (nipple discharge may indicate pathologic nipple discharge) or be associated with a
threshold p-value of ≤ 0.15.

Table 3
3Adjusted odds ratios and regression coefficient for the presence of breast cancer from the derivation modelExplanatory variable
Adjusted OR (95% CI)
Regression coefficient
P-value

Increasing age (additional year)
1.08 (1.07-1.09)
0.08
<0.01

Presence of a lump
5.63 (4.20-7.56)
1.73
<0.01

Nipple change
2.77 (1.68-4.58)
1.02
<0.01

Nipple discharge
2.09 (1.10-3.97)
0.74
0.03

Table 4
4Scoring System for onward referral for breast cancerRisk factor
Scoring

Lump
3

Age 18-29
0

Age 30-39
1

Age 40-49
3

Age 50-59
4

Age 60-69
5

Age 70-99
8

Nipple change
2

Nipple discharge
1

Table 5
5Risks associated with the total scores for onward referral of breast cancer* *Referral process guided by total score. The risk of breast cancer is almost 2% once a woman scores 4 points and over 5% once the score reaches a threshold of ≥6 on the CPR.Total score
Estimate of risk

0
0.0016

1
0.0030

2
0.0054

3
0.0099

4
0.0178

5
0.0320

6
0.0568

7
0.0989

8
0.1667

9
0.2671

10
0.3991

11
0.5475

12
0.6880

13
0.8007

14
0.8798

http://www.biomedcentral.com/1471-2407/14/743
Competing interestsThe authors declare that they have no competing interests.Authors' contributionsAll authors were involved in the study conception and design. ED acquired data for analysis and FB performed statistical analysis. RG and DJ interpreted the data and drafted the paper. AH and TF critically revised the draft manuscript. All authors read and approved the final manuscript.Submit your next manuscript to BioMed
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Enhanced antitumor efficacy of cisplatin in combination with HemoHIM in tumor-bearing mice

Hae-Ran Park firstname.lastname@example.com
Eun-Jin Ju
Sung-Kee Jo firstname.lastname@example.com
Uhee Jung firstname.lastname@example.com
Sung-Ho Kim email@example.com
College of Veterinary Medicine
Chonnam National University
500-757GwangjuRepublic of Korea

Sung-Tae Yee
Department of Biology
Sunchon National University
Sunchon 540-742Republic of Korea

Address: 1 Radiation Resarch Division for Bio-Technology, Advanced Radiation Technology Institute, Jeongeup Campus of Korea Atomic Energy Research Institute (KAERI)
BMC Cancer
1266 Sinjeong-dong Jeongeup-si Jeonbuk 580-185Republic of Korea

Enhanced antitumor efficacy of cisplatin in combination with HemoHIM in tumor-bearing mice
10.1186/1471-2407-9-85BioMed Central Page 1 of 10 (page number not for citation purposes) Research article * Corresponding author
Background: Although cisplatin is one of the most effective chemotherapeutic agents, cisplatin alone does not achieve a satisfactory therapeutic outcome. Also cisplatin accumulation shows toxicity to normal tissues. In this study, we examined the possibility of HemoHIM both to enhance anticancer effect with cisplatin and to reduce the side effects of cisplatin in melanoma-bearing mice.Methods: HemoHIM was prepared by adding the ethanol-insoluble fraction to the total water extract of a mixture of 3 edible herbs, Angelica Radix, Cnidium Rhizoma and Paeonia Radix. Anticancer effects of HemoHIM with cisplatin were evaluated in melanoma-bearing mice. We used a Cr 51 -release assay to measure the activity of NK/Tc cell and ELISA to evaluate the production of cytokines.

Background

Chemotherapy has been one of the major therapeutic modalities commonly used for the treatment for a variety of cancer patients. However, in many cases, chemotherapy or radiotherapy alone cannot achieve a satisfactory therapeutic outcome, namely the complete remission of tumors, and induces severe side effects at therapeutically effective doses.

Cisplatin (cis-diaminedichloroplatinum (II) or CDDP), a platinum-containing anticancer drug, is one of the most commonly used cytotoxic agents for the treatment of a variety of solid malignant tumors. Despite its excellent anticancer activity, the clinical use of cisplatin is often limited by its undesirable side effects, such as severe nephrotoxicity and hepatotoxicity [1,2]. Although the precise mechanism for the cisplatin-induced toxicity is not well understood, cisplatin is preferentially taken up and accumulated in the liver and kidney cells [3], resulting in the enhanced production of reactive oxygen species (ROS) and the decrease in antioxidant enzymes [4][5][6][7]. Therefore, antioxidants have been administered before cisplatin treatment to protect against nephrotoxicity [8][9][10].

Complementary and alternative medicine defined by the National Center as a group of diverse medical and health care systems is not normally considered to be conventional medicine [11]. Complementary and alternative medicine does not inhibit tumor growth. These treatments might be undertaken adjuvant to, or instead of, conventional treatments. Numerous herbal medical products are promoted as complementary and alternative medicines. In addition, scientific and medical studies in Korea, China, and Japan, and more recently in the United States, have increasingly shown that plant-derived polysaccharides have potent immunotherapeutic properties with respect to the prevention and treatment of cancer [12][13][14][15][16][17][18][19].

A new herbal composition, HemoHIM, was designed by adding its polysaccharide fraction into a hot water extract of an herb mixture consisting of Angelica Radix, Cnidium Rhizoma and Paeonia Radix. This composition was designed to protect the self-renewal tissues and to promote a recovery of the immune system against oxidative stresses, such as irradiation [20,21]. The general composition of HemoHIM were 60.4% carbohydrate, 6% protein and 33.6% other (Data not shown). The immune modulating components in HemoHIM were the ethanol-insoluble fraction [21], and the polysaccharide content in this fraction was 40.9% (± 3.8) (Data not shown). In addition, the functional components included in the ethanol-soluble fraction of HemoHIM were Gallic acid [0.2% (± 0.06)], chlorogenic acid [0.33% (± 0.05)], paeoniflorin [1.32% (± 0.15)], nodakenin [0.58% (± 0.04)] and ben-zoic acid [0.17% (± 0.05)] (Data not shown). Especially, these 3 herbs are listed as raw materials in the Korea Food Code. Finally, HemoHIM has been proven to be safe for long-term administration (data not shown).

Surveillance capacity to tumor cells was mediated nonspecifically by dendritic cells, macrophages and natural killer cells and was mediated specifically by T cells including cytotoxic T (Tc) cells. Both T and NK cells have been shown to be anticancer effector cells [22,23]. Also, IFN-γ and IL-2 have been shown to have anticancer activity in animals [24,25].

In this study, the possibility of HemoHIM increasing the immune surveillance capacity to tumor cells through both NK cells and Tc cells in melanoma-bearing mice treated with cisplatin was assessed. Also, we examined its protective effect against cisplatin-induced nephrotoxicity in melanoma-bearing mice. Our results suggest that Hemo-HIM may be a beneficial supplement during cisplatin chemotherapy by enhancing the anti-tumor efficacy and reducing the toxicity of cisplatin.

Methods

Animals

Research was approved and conducted according to the principles enunciated in the 'Animal Care Act', prepared by the Ministry of Agriculture and Forestry, Republic of Korea. 8-week-old female C57BL/6 (H-2 b ) mice were used (The Orient Inc.; Charles River Technology; Seoul, Korea). The mice were housed in polycarbonate cages under a specific pathogen-free condition, and were fed with a standard animal diet and water ad libitum.

Preparation of HemoHIM

A mixture of 3 edible medicinal herbs, Angelica Radix (root of Angelica gigas Nakai), Cnidii Rhizoma (rhizome of Cnidium officinale Makino), and Paeonia Radix (root of Paeonia japonica Miyabe), was decocted for 4 hours in boiling water to obtain a total extract (HIM-I). One half of HIM-I was fractionated into an ethanol-soluble fraction and into an ethanol-insoluble polysaccharide fraction by a precipitation in 80% ethanol. HemoHIM was prepared by adding the ethanol-insoluble polysaccharide fraction to the other half of HIM-I.

Cisplatin injection and HemoHIM administration in tumor-bearing mice model

Mice were divided randomly into three groups (Control, Cisplatin and Cisplatin+HemoHIM), and each group consisted of twenty mice. B16F0 melanoma (5 × 10 5 cells/ mouse) was inoculated into subcutaneous femoral left region of mice at 3 days before an initial injection of cisplatin. Cisplatin was injected intraperitoneally at 4 mg/kg body weight (B.W.) on day 0, 7 and 14 (total three injections). Experimental group was intubated with Hemo-HIM at a final concentration of 100 mg/kgB.W. by everyday from day -1 to day 16, while the control group received only water. The scheme of the administration procedure is summarized in Fig. 1. On day 17 after initial injection of cisplatin, all mice of each group were experimented, respectively, to evaluate tumor weight or tumor size. The tumor size was calculated as follows: tumor size = ab 2 /2, where a and b are the larger and smaller diameters, respectively.

Melanoma cell growth assay in vitro

The effect of cisplatin and HemoHIM on the number of viable melanoma cells was assessed by CCK-8 (WST-8; Dojindo Lab, Kumamoto, Japan). The principle underlying the cell viability assessment by CCK-8 is based on the dehydrogenase activity detection in viable cells, similar with the principle of MTT. Briefly, the melanoma cells were seeded on to 96-well plates at a density of 7 × 10 3 cells per well in 100 μl of media. After incubation for 24 hours, cells were treated with various concentration of cisplatin and with HemoHIM 100 μg/ml for 24 hours. After incubation, a CCK-8 solution was added to each well. Cells were incubated at 37°C for two hours and the optical density was measured using microplate reader (Molecular Devices) at 450 nm (-Ref. 570 nm).

Preparation of lymphocyte in the spleen

Spleens were removed aseptically from the mice and a single cell suspension was prepared by mincing the spleen. The spleen lymphocytes were prepared by a density gradient centrifugation on a Ficoll-Hypaque solution (Sigma-Aldrich Co., St. Louis, MO, USA). All the cell suspensions were maintained in the RPMI 1640 media supplemented with 10% fetal bovine serum (FBS), 2 × 10 -2 M HEPES buffer, 2 × 10 -3 M L-glutamine, 1 × 10 -3 M pyruvate, 100 U/ml penicillin, 50 μg/ml streptomycin, 5 × 10 -5 M of 2mercaptoethanol and 1% nonessential amino acid. All the supplements were purchased from GIBCO BRL (Grand Island, USA).

HemoHIM administration in MMC-treated tumor-bearing mice model

Firstly, harvested B16F0 melanoma was inactivated by mitomicin C (MMC) treatment (50 μg/ml, incubation for 40 minutes at 37°C water bath). MMC-treated B16F0 melanoma were inoculated intraperitoneally with 1 × 10 6 cells/mouse 3 days after an initial administration of HemoHIM. Experimental group was intubated with HemoHIM at a final concentration of 100 mg/kgB.W. by everyday from day -3 to day 4, while the control group was received only water. Ten days after cancer cell inoculation, spleen lymphocytes were prepared as effector cells to measure the activity of NK cells and Tc cells through Cr 51release assay.

Assay for NK cell and cytotoxic T (Tc) cell mediated cancer cell killing activity

YAC-1 tumor targets or B16F0 tumor targets were labeled with 51 Cr-sodium chromate (Amersham Pharmacia Biotech, Kangnam-ku, Seoul, Korea) at a dose of 40 μCi/10 6 cells for 60 min to measured NK cell activity or Tc cell activity, respectively. The cells were washed three times in HBSS (Hank's

The experimental schedule used for assessing the efficacy of HemoHIM in melanoma-bearing mice which were injected with cisplatin Figure 1 The experimental schedule used for assessing the efficacy of HemoHIM in melanoma-bearing mice which were injected with cisplatin. B16F0 melanoma cells (5 × 10 5 /mouse) were inoculated into subcutaneous femoral left region of mice 3 days before an initial injection of cisplatin. Cisplatin was intraperitoneally injected at 4 mg/kg B.W., and HemoHIM was daily given at 100 mg/kg B.W. from day -1 to day 16. On day 17 after initial injection of cisplatin, all mice of each group were experimented, respectively, to evaluate various parameters.

Flow cytometry analysis of NK and Tc cells in spleen lymphocytes

The spleen lymphocytes were stained with fluorescentlabeled antibodies or isotype control antibodies in phosphate buffered saline (PBS). After staining for 30 minutes, the lymphocytes were washed three times with a fresh FACS media and then analyzed by flow cytometry (Backman Coulter, Miami, Florida, USA). A fluorescence histogram of at least 50,000 counts was analyzed in each sample. The following reagents from BD PharMingen

The inhibition of tumor growth was enhanced by HemoHIM administration in melanoma-bearing mice which were injected with cisplatin

Condition for a cytokine production in vitro

The spleen lymphocytes (2 × 10 6 cells/well) obtained from the mice were stimulated with concanavalin A (ConA) at 1 μg/ml for 1 or 2 days to measure IL-2 and IFN-γ level in supernatant.

Antibodies and the enzyme-linked immunosorbent assay (ELISA)

For the IL-2, clone JES6-1A12 was used as the capture Ab, and biotin-labelled JES6-5H4 was the detecting Ab. For the IFN-γ measurements, clone R4-6A2 was used as the capture Ab, and biotin-labeled XMG1.2 was the detecting Ab. All the antibodies as well as the recombinant IFN-γ and IL-2 were purchased from BD PharMingen (San Diego, CA, USA). Cytokines were determined by previously described ELISA method [26].

Histopathological examination of kidney by hematoxylin and eosin staining

Kidney from mice of each group on day 17 after initial injection of cisplatin was removed and fixed in 10% buffered formalin for 2 days. The paraffin-embedded sections (5 μm thick) were stained with hematoxylin and eosin (H&E) for histolpathological examination and observed under light microscope at × 200 magnifications.

Statistical analysis

Data were expressed as mean ± S.D. and a statistical significance was analyzed by using a Student's t-test. Differences with a p value of less than 0.05 were taken as significant, and considerable with a p value of less than 0.1.

Results

HemoHIM enhances the antitumor efficacy of cisplatin in tumor-bearing mice

To assess the effect of HemoHIM on tumor growth inhibition in cisplatin treated B16F0 melanoma-bearing mice, we used a tumor-bearing mice model that was summarized in Fig. 1. As shown in Fig. 2A and 2B, at 20 days after melanoma inoculation, the tumor weight and size of the control group without cisplatin and HemoHIM treatment were 6.093 g (± 2.28) and 12.6 mm 3 (± 5.65), respectively. However, in the cisplatin-injected group, tumor weight (2.97 g (± 1.29)) and size (6.3 mm 3 (± 2.32)) were reduced significantly in comparison to the control group. HemoHIM supplementation with cisplatin resulted in a further reduction in both the tumor weight (2.22 g (± 1.24)) and size (4.7 mm 3 (± 2.93)). Only HemoHIM supplementation without cisplatin showed no reduction in tumor weight [6.15 g (± 1.238)] when compared with the control group (Data not shown). This suggests that HemoHIM itself did not show a reduction effect of tumor growth. Photographs are shown in Fig. 2C.

HemoHIM enhances the activity of NK and Tc cells rather than directly killing cancer cells

The anticancer effect of cisplatin mainly depends on its DNA-damaging activity, via its direct interaction with DNA to form DNA adducts [27]. As shown in Fig. 3, cisplatin inhibited melanoma cell growth in a dose-dependent manner, with IC 50 at about 15 μg/ml. However, Hemo-HIM itself did not inhibit melanoma growth in vitro (Data not shown), nor did it disturb the working of cisplatin in vitro (Fig. 3).

Because HemoHIM did not directly kill cancer cells, we thought that the activity of immune cells which were in charge of tumor surveillance may be enhanced by Hemo-HIM. We investigated the cancer cell-killing activity of NK and Tc cells, as they are in charge of innate and adaptive immunity against tumor, respectively. To investigate the activity of Tc cell, we used the mice which were immunized with mitomycin C (MMC)-treated melanoma cells. As shown in Fig. 4A and 4B, HemoHIM administration enhanced cancer cell-killing activity of NK cells and Tc cells in MMC-treated melanoma cell-bearing mice (p < 0.05 and p = 0.06, respectively). Also, the proportion of NK cell in spleen lymphocytes was increased by Hemo-HIM administration (p < 0.05), but not the proportion of Tc cells. Specially, these results were important because NK cells take part in both innate and adaptive immunity, and are regarded as interfaces between the innate and adaptive immune systems [28].

The enhanced efficacy of cisplatin with HemoHIM in melanoma-bearing mice was due to increasing IL-2 and IFNγ secretion and enhancing the activity of NK and Tc cells

As the mechanisms for an enhanced anticancer efficacy of cisplatin in combination with HemoHIM in melanoma cell-bearing mice (Fig. 1), we concentrated on the activity of NK and Tc cells because these cells play an important role on cancer surveillance. As shown Fig. 5A and 5B, cisplatin injection alone in melanoma-bearing mice did not enhance or decrease the activity of NK cells and Tc cells. However, HemoHIM administration enhanced the activity of NK cells in melanoma-bearing mice which were treated with cisplatin (p = 0.1; Fig. 5A). In addition, the activity of Tc cells was enhanced significantly by Hemo-HIM administration (p < 0.05; Fig. 5B). These data suggested that the enhanced anticancer efficacy of cisplatin in combination with HemoHIM administration was due to the increase in the activity of NK and Tc cells that are in charge of tumor surveillance.

Macrophages, dendritic cells, NK cells and Tc cells that are able to recognize, bind and subsequently kill tumor cells, were activated by cytokines such as IL-2 and IFN-γ. In our previous study, lymphocytes treated with HemoHIM alone enhanced the expression of IL-2 and IFN-γ in vitro (data not shown). Truly, IL-2 and IFN-γ are potent activa-tors of NK cell and Tc cell effector functions. We therefore ascertained whether HemoHIM administration enhanced the production of IL-2 and IFN-γ in melanoma-bearing mice treated with cisplatin. HemoHIM administration significantly enhanced IL-2 (p < 0.001; Fig. 5C) and IFN-γ (p < 0.05; Fig. 5D) production in melanoma-bearing mice treated with cisplatin.

HemoHIM decreases the cisplatin-induced nephrotoxicity in tumor-bearing mice

Undesirable side effects of cisplatin appear in the kidney and liver, due to cisplatin accumulation in these organs [3]. As one of the mechanisms for cisplatin-induced toxicity is the enhanced production of ROS in these organs, we thought that HemoHIM may have a radical scavenging activity [20,21], reducing cisplatin-induced damage.

Experimental studies in animals have shown that a minimum dose of cisplatin (5 mg/kg body weight, i.p.) was sufficient to induce nephrotoxicity in rats [29,30]. In this study, the cisplatin was injected at 4 mg/kg body weight three times once weekly. The nephrotoxicity was assessed using kidneys removed from mice on day 17 after an initial injection of cisplatin, and the representative result of each group is shown in Fig. 6. In the histopathological examination of the kidney, cisplatin destroyed renal tubular cells (Fig. 6). However HemoHIM administration reduced the destruction of renal tubular cells by cisplatin.

Discussion

HemoHIM is an herbal composition designed to protect the self-renewal tissues and to promote the recovery of the immune system against an oxidative stresses such as an Effect of HemoHIM on cancer cell killing activity of NK cells and Tc cells Figure 4 Effect of HemoHIM on cancer cell killing activity of NK cells and Tc cells. C57BL/6 mice were orally administrated with HemoHIM (100 mg/kg B.W.) and injected with MMC-treated B16F0 melanoma (1 × 10 6 cell/mouse) into peritoneal cavity. 10 days after cancer cell inoculation, the cancer cell killing activity of NK cells or Tc cells was determined by 51 Cr release assay as described in Materials and Methods. There were six mice in each group. Data show the Mean ± SD. * p = 0.06 and ** p < 0.05 compared with mice administrated water. irradiation. In this study, we examined the possibility of HemoHIM both to enhance the anticancer effect of cisplatin and to reduce its side effects in melanoma-bearing mice. In our previous studies, HemoHIM was tested for its efficacy as a radioprotective agent [20,21]. Also, we investigated the effect of HemoHIM on a restoration of the immune functions which had been impaired in aged mice [31]. Besides, in our previous study, we showed that HemoHIM accelerated the recovery of immune cells in mice treated with cyclophosphamide, which is a wellknown anticancer agent [32]. In this study, unlike cisplatin, HemoHIM alone did not directly kill the cancer cells. Nevertheless, our results showed that HemoHIM administration enhanced antitumor efficacy of cisplatin in melanoma-bearing mice.

Immune responses that are capable of killing tumor cells consist of dendritic cells, macrophages, NK cells and Tc cells. Tc cells may perform a surveillance function by rec-ognizing and killing potentially malignant cells that express peptides derived from mutant cellular proteins or oncogenic viral proteins and presented in association with class I MHC molecules. NK cells kill many types of tumor cells, especially cells that have reduced class I MHC expression and can escape killing by Tc cells [33]. In vitro studies using cells from humans and several other mammalian species, as well as in vivo studies in mice and rats, have long suggested that tumor cells are recognized as NK cell targets [34]. Also, NK cells act as regulatory cells to influence various other cell types, such as dendritic cells, helper T (Th) cells, Tc cells and B cells [35]. Many studies for immuno-cancer therapy were focused on enhancing the activity of NK cells as well as Tc cells against tumor cells. In our data, cisplatin alone decreased tumor size, but did not enhance the activity of NK cells and Tc cells (Fig.  5). Also, HemoHIM alone without cisplatin did not enhance the activity of these cells (data not shown). However, HemoHIM administration with cisplatin injection

HemoHIM administration promotes immune responses for tumor surveillance in melanoma-bearing mice which were injected with cisplatin increases the activity of NK cells and Tc cells in melanoma-bearing mice ( Fig. 5A and 5B), while the tumor size was decreased by cisplatin. Thus, we suggest that the mechanism of action of cisplatin and HemoHIM in tumor-bearing mice differ.

IL-2 and IFN-γ are potent activators of NK cell and Tc cell effecter functions. For these reasons, cytokine therapies of malignant tumors using IL-2, IL-12, and IFN-γ have been investigated extensively in experimental and clinical studies [34]. It is also well known that IL-2 and IFN-γ promote tumor-reactive lymphocyte proliferation, cytotoxicity and, to some extent, cytokine secretion [36][37][38][39][40][41]. IFN-γ is a pleiotropic immunoregulatory cytokine that has been used for clinical treatment of certain tumors [42,43]. However, the clinical application of such cytokines has been hampered largely due to their undesirable side effects [44,45]. In our data, HemoHIM administration with cisplatin injection increased the secretion of IL-2 and IFN-γ in melanoma-bearing mice.

Although cisplatin is an anticancer drug highly effective against several cancers, cisplatin is toxic to liver and kidney cells through producing ROS [1][2][3][4]30]. However, many studies to counter nephrotoxicity through the administration of antioxidants have been performed [8][9][10]. As HemoHIM was designed to protect the selfrenewal tissues and to promote a recovery of the immune system against oxidative stresses [20,21], we thought it may be able to decrease cisplatin-induced kidney damage. As expected, HemoHIM administration reduced nephrotoxicity as seen by tubular cell destruction of kidney.

Based on the overall these results, the possibility of HemoHIM both to enhance anticancer effect of cisplatin and to reduce its side effects in melanoma-bearing mice were ascertained. However, the protective efficacy of HemoHIM on cisplatin-induce damage in the kidney needs to be investigated further.

Conclusion

In conclusion, although the manner in which HemoHIM administration decreases cisplatin-induced kidney damage remains unknown, our results indicate that Hemo-HIM may be a useful complementary agent during cisplatin chemotherapy by enhancing the anti-tumor efficacy and reducing the toxicity of cisplatin.

HemoHIM reduces the cisplatin-induce damage of kidney

Control

Solution; Sigma-Aldrich Co.) and resuspended to a final concentration of 2 × 10 5 cells/ml. Twenty thousand target cells and 10 6 or 2 × 10 6 spleen effector cells were plated into the wells of a 96-well U bottom plate. The plates were then incubated at 37°C for 4 hr in humidified air containing 5% CO 2 . Following a centrifugation at 350 g for 10 min, 100 μl of the supernatant was harvested from each well andcounted for 1 min in a gamma counter (Wallac, Wellesley, MA, USA). The percent lysis was calculated as follows: % lysis = {[CPM (experimental) -CPM (spontaneous)]/[CPM (maximum) -CPM (sponstaneous)]} × 100.

Figure 2
2The inhibition of tumor growth was enhanced by HemoHIM administration in melanoma-bearing mice which were injected with cisplatin. All mice performed as described in figure 3 were sacrificed at 17 days after initial injection of cisplatin. Tumor weight (A) and size (B) were measured. (C) Photographs of melanoma solid tumor taken from all mice of each group. There were twenty mice in each group. Data show the Mean ± SD. *p < 0.1 compared with only cisplatin treated group. effect of cisplatin and HemoHIM on melanoma cells in vitro Figure 3 Growth inhibition effect of cisplatin and HemoHIM on melanoma cells in vitro.The melanoma cells were seeded at a density of 7 × 10 3 cells per well. After incubation for 24 hours, cells were treated with various concentration of cisplatin and with HemoHIM 100 μg/ml for 24 hours. After incubation, a CCK-8 solution was added to each well for 1 hour and then the optical density was measured.

(
San Diego, CA, USA) were used: PE-conjugated anti-NK1.1 and FITC-conjugated anti-CD8.

Figure 5
5HemoHIM administration promotes immune responses for tumor surveillance in melanoma-bearing mice which were injected with cisplatin. All mice performed as described in figure 3 were sacrificed at 17 days after initial injection of cisplatin. (A)(B) The cancer cell killing activity of NK cells or Tc cells was determined by 51 Cr release assay as described in Materials and Methods. (C)(D) Spleen lymphocytes were cultured with ConA (1 μg/ml). After 1 or 2 days, IL-2 and IFN-γ in culture supernatants were measured by ELISA as described in Materials and Methods. There were twenty one mice in each group. The spleens of three mice were pooled. Bars show the means ± SD of the septuple experiments. * p = 0.1, **p < 0.05 and ***p < 0.001 compared with only cisplatin treated group.

Figure 6
6HemoHIM reduces the cisplatin-induce damage of kidney. Kidney from mice of each group on day 17 after initial injection of cisplatin was removed and fixed in 10% buffered formalin for 2 days. The paraffin-embedded sections (5 μm thick) were stained with hematoxylin and eosin (H&E) for histolpathological examination and observed under light microscope at × 200 magnifications. The result shown here is representative cortex from each group. (A) Control, cortex (× 200), (B) Cisplatin control, cortex (× 200), renal tubule cell destruction (marked by arrows), (C) Cisplatin+HemoHIM, cortex (× 200).
(page number not for citation purposes)
AcknowledgementsCompeting interestsThe authors declare that they have no competing interests.Authors' contributionsHRP carried out making HemoHIM, the cell culture, Cr 51relaeas assay, animal experiments, and draft out the manuscript. EJJ performed the cell culture, ELISA analysis and histopathological examination. UHJ, SHK and STY participated in the design of study. SKJ conceived of the study, and participated in its design. All authors have read and approved the manuscript.Pre-publication historyThe pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/9/85/prepub
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