Background Colorectal cancer is a common cancer all over the world. Aberrations in the cell cycle checkpoints have been shown to be of prognostic significance in colorectal cancer.
Background
Colorectal cancer is a common cancer all over the world. Aberrations in the cell cycle checkpoints have been shown to be of prognostic significance in colorectal cancer.Methods The expression of  cyclin D1 ,  cyclin A ,  histone H3  and  Ki-67  was examined in 60 colorectal cancer cases for co-regulation and impact on overall survival using immunohistochemistry, southern blot and in situ hybridization techniques. Immunoreactivity was evaluated semi quantitatively by determining the staining index of the studied proteins.
Methods
The expression of  cyclin D1 ,  cyclin A ,  histone H3  and  Ki-67  was examined in 60 colorectal cancer cases for co-regulation and impact on overall survival using immunohistochemistry, southern blot and in situ hybridization techniques. Immunoreactivity was evaluated semi quantitatively by determining the staining index of the studied proteins.cyclin D1cyclin Ahistone H3Ki-67Results There was a significant correlation between  cyclin D1  gene amplification and protein overexpression (concordance = 63.6%) and between  Ki-67  and the other studied proteins. The staining index for  Ki-67, cyclin A and D1  was higher in large, poorly differentiated tumors. The staining index of  cyclin D1  was significantly higher in cases with deeply invasive tumors and nodal metastasis. Overexpression of  cyclin A  and  D1  and amplification of  cyclin D1  were associated with reduced overall survival. Multivariate analysis shows that  cyclin D1 and A  are two independent prognostic factors in colorectal cancer patients.
Results
There was a significant correlation between  cyclin D1  gene amplification and protein overexpression (concordance = 63.6%) and between  Ki-67  and the other studied proteins. The staining index for  Ki-67, cyclin A and D1  was higher in large, poorly differentiated tumors. The staining index of  cyclin D1  was significantly higher in cases with deeply invasive tumors and nodal metastasis. Overexpression of  cyclin A  and  D1  and amplification of  cyclin D1  were associated with reduced overall survival. Multivariate analysis shows that  cyclin D1 and A  are two independent prognostic factors in colorectal cancer patients.cyclin D1Ki-67Ki-67, cyclin A and D1cyclin D1cyclin AD1cyclin D1cyclin D1 and AConclusions Loss of cell cycle checkpoints control is common in colorectal cancer.  Cyclin A and D1  are superior independent indicators of poor prognosis in colorectal cancer patients. Therefore, they may help in predicting the clinical outcome of those patients on an individual basis and could be considered important therapeutic targets.
Conclusions
Loss of cell cycle checkpoints control is common in colorectal cancer.  Cyclin A and D1  are superior independent indicators of poor prognosis in colorectal cancer patients. Therefore, they may help in predicting the clinical outcome of those patients on an individual basis and could be considered important therapeutic targets.Cyclin A and D1

Background Colorectal cancer (CRC) is the third most common cancer in Western countries [ 1 ]. In Egypt, CRC has unique characteristics that differ from that reported in other countries of the western society. It was estimated that 35.6% of the Egyptian CRC cases are below 40 years of age and patients usually present with advanced stage, high grade tumors that carry more mutations [ 2 ]. This uniquely high proportion of early-onset CRC, the early and continuous exposure to hazardous environmental agents, the different mutational spectrum and the prevalent consanguinity in Egypt justify further studies [ 3 ]. It was proved that most cancers result from accumulation of genetic alterations involving certain groups of genes, the majority of which are cell cycle regulators that either stimulate or inhibit cell cycle progression [ 1 ]. Cell proliferation allows orderly progression through the cell cycle, which is governed by a number of proteins including  cyclin s and  cyclin  dependent kinases [ 4 , 5 ]. The  cyclin s belong to a superfamily of genes whose products complex with various  cyclin -dependent kinases ( cdks ) to regulate transitions through key checkpoints of the cell cycle [ 6 ]. Abnormalities of several  cyclins  have been reported in different tumor types, implicating, in particular,  cyclin A, cyclin E  and  cyclin D  [ 6 , 7 ]. Cyclin D1  is a G1  cyclin  that regulates the transition from G1 to S phase since its peak level and maximum activity are reached during the G1 phase of the cell cycle. Whereas  cyclin A  is regarded a regulator of the transition to mitosis since it reaches its maximum level during the S and G2 phases [ 8 ]. The mechanisms likely to activate the oncogenic properties of the  cyclins  include chromosomal translocations, gene amplification and aberrant protein overexpression [ 7 , 9 ]. Several studies have shown that,  histone H3  mRNA expression can be used to identify the S phase fraction (SPF) through the in situ hybridization (ISH) technique [ 10 , 11 ]. The level of  histone H3  mRNA reaches its peak during the S phase and then drops rapidly at the G2 phase [ 12 ]. In face of the increasing incidence of CRC and its peculiar pattern in the Egyptian population, the present study was conducted to assess the role of  Ki-67  (pan-cell cycle marker),  cyclin D1  (G1 phase marker),  histone H3  mRNA (S phase marker),  cyclin A  (S to G2 phase marker) in CRC. The expression level of these markers was correlated to the clinicopathologic features and the overall survival of patients.
Background
Colorectal cancer (CRC) is the third most common cancer in Western countries [ 1 ]. In Egypt, CRC has unique characteristics that differ from that reported in other countries of the western society. It was estimated that 35.6% of the Egyptian CRC cases are below 40 years of age and patients usually present with advanced stage, high grade tumors that carry more mutations [ 2 ]. This uniquely high proportion of early-onset CRC, the early and continuous exposure to hazardous environmental agents, the different mutational spectrum and the prevalent consanguinity in Egypt justify further studies [ 3 ]. It was proved that most cancers result from accumulation of genetic alterations involving certain groups of genes, the majority of which are cell cycle regulators that either stimulate or inhibit cell cycle progression [ 1 ]. Cell proliferation allows orderly progression through the cell cycle, which is governed by a number of proteins including  cyclin s and  cyclin  dependent kinases [ 4 , 5 ]. The  cyclin s belong to a superfamily of genes whose products complex with various  cyclin -dependent kinases ( cdks ) to regulate transitions through key checkpoints of the cell cycle [ 6 ]. Abnormalities of several  cyclins  have been reported in different tumor types, implicating, in particular,  cyclin A, cyclin E  and  cyclin D  [ 6 , 7 ].cyclincyclincyclincyclincdkscyclinscyclin A, cyclin Ecyclin DCyclin D1  is a G1  cyclin  that regulates the transition from G1 to S phase since its peak level and maximum activity are reached during the G1 phase of the cell cycle. Whereas  cyclin A  is regarded a regulator of the transition to mitosis since it reaches its maximum level during the S and G2 phases [ 8 ]. The mechanisms likely to activate the oncogenic properties of the  cyclins  include chromosomal translocations, gene amplification and aberrant protein overexpression [ 7 , 9 ].Cyclin D1cyclincyclin AcyclinsSeveral studies have shown that,  histone H3  mRNA expression can be used to identify the S phase fraction (SPF) through the in situ hybridization (ISH) technique [ 10 , 11 ]. The level of  histone H3  mRNA reaches its peak during the S phase and then drops rapidly at the G2 phase [ 12 ].histone H3histone H3In face of the increasing incidence of CRC and its peculiar pattern in the Egyptian population, the present study was conducted to assess the role of  Ki-67  (pan-cell cycle marker),  cyclin D1  (G1 phase marker),  histone H3  mRNA (S phase marker),  cyclin A  (S to G2 phase marker) in CRC. The expression level of these markers was correlated to the clinicopathologic features and the overall survival of patients.Ki-67cyclin D1histone H3cyclin AMethods Tissue samples Paraffin-embedded tumor tissues were obtained from 60 CRC patients (47 colon and 13 rectal carcinomas) that were diagnosed and treated at the National Cancer Institute, Cairo, Egypt during the period from January, 1997 to June, 2002. Clinicopathological data of the studied cases are illustrated in table  1 . None of the patients received any chemotherapy or irradiation prior to surgery. Histological diagnosis of all cases was done by 2 independent pathologists according to the WHO Histological Classification. Tumors were staged according to the TNM staging system [ 13 ]. The depth of tumor invasion was classified as invasion of the mucosa including muscularis mucosa (m), invasion of the submucosa (sm), or invasion beyond the submucosa [ 8 ]. Normal colonic tissues were obtained from autopsy specimens (n = 20) and were used as a control. The actual survival rate of the patients was calculated from the date of resection to the date of death. Table 1 Clinicopathological features of patients in relation to the staining index (SI) of  Ki-67 ,  cyclin D1 ,  cyclin A ,  histone H3 SI (mean + SD) Variables No. of cases Ki-67 Cyclin DI Cyclin A Histone H3 Sex   Male 36 18.0 ± 6.4 6.7 ± 4.3 12.7 ± 5.7 10.7 ± 5.3   Female 24 20.1 ± 5.8 8.8 ± 8.4 10.0 ± 6.0 10.7 ± 5.4 Age (years)   ≥50 41 11.7 ± 6.0* 5.6 ± 5.2 10.0 ± 5.3 6.0 ± 5.0*   <50 19 23.8 ± 5.6 7.7 ± 6.8 13.6 ± 5.7 22.0 ± 5.2 Tumor size (cm)   <5.0 33 12.2 ± 6.3* 5.3 ± 3.8* 11.5 ± 6.1* 10.3 ± 4.9*   ≥5.0 27 30.1 ± 6.2 22.8 ± 7.2 28.6 ± 5.6 24.0 ± 5.6 Histology   Normal 20 3.5 ± 2.0* 0.6 ± 0.2* 2.3 ± 1.1* 2.2 ± 0.9   Carcinoma 60 30.3 ± 6.2 24.9 ± 6.3 27.2 ± 5.8 10.7 ± 5.3   GI 15 11.7 ± 6.2 6.6 ± 4.0 10.0 ± 5.4 11.4 ± 4.9   GII 21 11.8 ± 5.6 8.9 ± 3.6 12.3 ± 6.5 7.8 ± 5.4   GIII 24 30.0 ± 4.3 22.0 ± 8.1 27.0 ± 4.9 11.5 ± 5.4 Lymph node   Negative 33 19.5 ± 7.0 5.4 ± 5.3* 11.9 ± 6.5 12.3 ± 5.5   Positive 27 21.3 ± 4.9 20.6 ± 6.9 12.5 ± 5.0 14.2 ± 5.0 Depth of invasion   m, sm 17 20.7 ± 6.7 3.1 ± 3.1* 11.9 ± 7.2 10.4 ± 5.1   beyond sm 43 21.9 ± 6.2 12.4 ± 6.5 12.2 ± 5.6 10.7 ± 5.4 Stage   I 6 20.6 ± 6.7 5.7 ± 6.9 24.2 ± 6.9 11.1 ± 5.3   II 27 20.8 ± 6.9 5.3 ± 4.3 24.6 ± 6.0 10.4 ± 5.7   III 12 22.0 ± 5.4 7.7 ± 6.0 27.1 ± 5.2 10.4 ± 4.9   IV 15 24.7 ± 6.1 11.3 ± 9.6 27.5 ± 5.5 12.3 ± 6.2 * p. value < 0.05 (significant) Immunohistochemistry Four micron sections of each normal and tumor specimen were cut onto positive-charged slides; air dried overnight, de-paraffinized in xylene, hydrated through a series of graded alcohol and washed in distilled water and 0.01 PBS (pH 7.4). Slides were then processed for IHC as described by Handa et al. [ 8 ]. using the following antibodies:  Ki-67  (MIB-1, Dako),  cyclin A  (6E6; Novocastra, Newcastle-Upon-Tyne, UK) and  cyclin D1  (DCS-6, Dako). A case of invasive breast cancer was used as a positive control for  Ki-67  and  cyclin A  whereas a case of mantle cell lymphoma was used as a control for  cyclin D1 . Negative controls were obtained by replacing the primary antibody by non-immunized rabbit or mouse serum. Brown nuclear staining was regarded as a positive result for all studied markers. The proportion of positively-stained cells and the intensity of staining were scored in tumor and normal colorectal mucosal sections at medium power (×200). The degree of positive tumor staining (percentage of positive tumor cells in the examined section) was scored from 1–6 and the staining intensity was scored from 0–6 according to the pattern of staining in the examined section. Staining index (SI) was calculated by multiplying the cellularity and staining scores as described by King et al. [ 14 ]. In situ hybridization All tumor samples and 5 normal controls were assessed for  histone H3  mRNA by ISH using the commercially available 550 base fluorescein-labeled DNA probe (Dako, Carpinteria, CA) as described by Nagao et al., 1996. This probe hybridizes to the whole mRNA transcript of the human  histoneH3  gene including the5' and 3' un-translated regions. Scoring of  histone H3  mRNA was performed as for immunohistochemistry, however, hybridization signals were detected in the cytoplasm. Molecular detection of cyclin D1 gene amplification High molecular weight DNA was extracted from paraffin-embedded tissues of the tumor and normal colorectal mucosal samples as previously described [ 15 ]. The proportion of neoplastic and normal cells was determined in each tumor sample by examining hematoxylin and eosin-stained slides obtained from the edge of the specimen used for DNA extraction. Tumor samples were evaluated for amplification of  cyclin D1  if more than 75% of the examined sections were formed of neoplastic cells. Accordingly, 50 cases were eligible for the analysis. Ten micrograms of the extracted DNA was digested with  Eco R1. DNA from selected cases was also digested with  Bgl II and  Hind III. Samples were separated on 0.8% agarose gels and transferred to Hybond-N membranes (Amersham Int., Amersham, UK). The membranes were hybridized with 50% formamide, 5 × SSC, 5 × Denhardt's, 500 μg/ml denatured salmon sperm DNA, 10% dextran sulphate and 10 6  cpm/ml of  32 P-labeled  PRAD-1  probe for 24 h. Membranes were washed with 2 × SSC, 0.1% SDS at room temperature for 30 min followed by 2 × SSC, 0.1% SDS at 60°C for 30 min and 0.1 × SSC, 0.1% SDS at 60°C for 1 h. Filters were autoradiographed using an intensifying screen at -70°C for 24–72 h. After being stripped free of the  PRAD-1  probe, the same blots were hybridized with  32 P-labeled  B-actin  probe to normalize against possible variations in the loading or transfer of DNA. The autoradiograms were analyzed using a densitometer. Intensities of  PRAD-1/cyclin D1  were normalized to the  β-actin  control bands. The degree of amplification was calculated from these normalized values. Amplification was considered when the signal of the tumor band was ≥2-fold the value of the matched normal mucosa [ 16 ]. Statistical analysis The Mann-Whitney non-parametric test was used to compare the SIs of pairs of subjects whereas the Kruskal-wallis was used for categorial data. Correlation between indices was performed using a simple linear regression test. The Kaplan-Meier method was used to create survival curves which were analyzed by the log-rank test. The impact of different variables on survival was determined using the Cox proportional hazards model.  p . values less than 0.05 were considered significant.
Methods
Tissue samples Paraffin-embedded tumor tissues were obtained from 60 CRC patients (47 colon and 13 rectal carcinomas) that were diagnosed and treated at the National Cancer Institute, Cairo, Egypt during the period from January, 1997 to June, 2002. Clinicopathological data of the studied cases are illustrated in table  1 . None of the patients received any chemotherapy or irradiation prior to surgery. Histological diagnosis of all cases was done by 2 independent pathologists according to the WHO Histological Classification. Tumors were staged according to the TNM staging system [ 13 ]. The depth of tumor invasion was classified as invasion of the mucosa including muscularis mucosa (m), invasion of the submucosa (sm), or invasion beyond the submucosa [ 8 ]. Normal colonic tissues were obtained from autopsy specimens (n = 20) and were used as a control. The actual survival rate of the patients was calculated from the date of resection to the date of death. Table 1 Clinicopathological features of patients in relation to the staining index (SI) of  Ki-67 ,  cyclin D1 ,  cyclin A ,  histone H3 SI (mean + SD) Variables No. of cases Ki-67 Cyclin DI Cyclin A Histone H3 Sex   Male 36 18.0 ± 6.4 6.7 ± 4.3 12.7 ± 5.7 10.7 ± 5.3   Female 24 20.1 ± 5.8 8.8 ± 8.4 10.0 ± 6.0 10.7 ± 5.4 Age (years)   ≥50 41 11.7 ± 6.0* 5.6 ± 5.2 10.0 ± 5.3 6.0 ± 5.0*   <50 19 23.8 ± 5.6 7.7 ± 6.8 13.6 ± 5.7 22.0 ± 5.2 Tumor size (cm)   <5.0 33 12.2 ± 6.3* 5.3 ± 3.8* 11.5 ± 6.1* 10.3 ± 4.9*   ≥5.0 27 30.1 ± 6.2 22.8 ± 7.2 28.6 ± 5.6 24.0 ± 5.6 Histology   Normal 20 3.5 ± 2.0* 0.6 ± 0.2* 2.3 ± 1.1* 2.2 ± 0.9   Carcinoma 60 30.3 ± 6.2 24.9 ± 6.3 27.2 ± 5.8 10.7 ± 5.3   GI 15 11.7 ± 6.2 6.6 ± 4.0 10.0 ± 5.4 11.4 ± 4.9   GII 21 11.8 ± 5.6 8.9 ± 3.6 12.3 ± 6.5 7.8 ± 5.4   GIII 24 30.0 ± 4.3 22.0 ± 8.1 27.0 ± 4.9 11.5 ± 5.4 Lymph node   Negative 33 19.5 ± 7.0 5.4 ± 5.3* 11.9 ± 6.5 12.3 ± 5.5   Positive 27 21.3 ± 4.9 20.6 ± 6.9 12.5 ± 5.0 14.2 ± 5.0 Depth of invasion   m, sm 17 20.7 ± 6.7 3.1 ± 3.1* 11.9 ± 7.2 10.4 ± 5.1   beyond sm 43 21.9 ± 6.2 12.4 ± 6.5 12.2 ± 5.6 10.7 ± 5.4 Stage   I 6 20.6 ± 6.7 5.7 ± 6.9 24.2 ± 6.9 11.1 ± 5.3   II 27 20.8 ± 6.9 5.3 ± 4.3 24.6 ± 6.0 10.4 ± 5.7   III 12 22.0 ± 5.4 7.7 ± 6.0 27.1 ± 5.2 10.4 ± 4.9   IV 15 24.7 ± 6.1 11.3 ± 9.6 27.5 ± 5.5 12.3 ± 6.2 * p. value < 0.05 (significant)
Tissue samples
Paraffin-embedded tumor tissues were obtained from 60 CRC patients (47 colon and 13 rectal carcinomas) that were diagnosed and treated at the National Cancer Institute, Cairo, Egypt during the period from January, 1997 to June, 2002. Clinicopathological data of the studied cases are illustrated in table  1 . None of the patients received any chemotherapy or irradiation prior to surgery. Histological diagnosis of all cases was done by 2 independent pathologists according to the WHO Histological Classification. Tumors were staged according to the TNM staging system [ 13 ]. The depth of tumor invasion was classified as invasion of the mucosa including muscularis mucosa (m), invasion of the submucosa (sm), or invasion beyond the submucosa [ 8 ]. Normal colonic tissues were obtained from autopsy specimens (n = 20) and were used as a control. The actual survival rate of the patients was calculated from the date of resection to the date of death.Clinicopathological features of patients in relation to the staining index (SI) of  Ki-67 ,  cyclin D1 ,  cyclin A ,  histone H3Ki-67cyclin D1cyclin Ahistone H3SI (mean + SD)SI (mean + SD)VariablesVariablesNo. of casesNo. of casesKi-67Ki-67Cyclin DICyclin DICyclin ACyclin AHistone H3Histone H3SexSexMaleMaleFemaleFemaleAge (years)Age (years)≥50≥50<50<50Tumor size (cm)Tumor size (cm)<5.0<5.0≥5.0≥5.0HistologyHistologyNormalNormalCarcinomaCarcinomaGIGIGIIGIIGIIIGIIILymph nodeLymph nodeNegativeNegativePositivePositiveDepth of invasionDepth of invasionm, smm, smbeyond smbeyond smStageStageIIIIIIIIIIIIIVIV* p. value < 0.05 (significant)Immunohistochemistry Four micron sections of each normal and tumor specimen were cut onto positive-charged slides; air dried overnight, de-paraffinized in xylene, hydrated through a series of graded alcohol and washed in distilled water and 0.01 PBS (pH 7.4). Slides were then processed for IHC as described by Handa et al. [ 8 ]. using the following antibodies:  Ki-67  (MIB-1, Dako),  cyclin A  (6E6; Novocastra, Newcastle-Upon-Tyne, UK) and  cyclin D1  (DCS-6, Dako). A case of invasive breast cancer was used as a positive control for  Ki-67  and  cyclin A  whereas a case of mantle cell lymphoma was used as a control for  cyclin D1 . Negative controls were obtained by replacing the primary antibody by non-immunized rabbit or mouse serum. Brown nuclear staining was regarded as a positive result for all studied markers. The proportion of positively-stained cells and the intensity of staining were scored in tumor and normal colorectal mucosal sections at medium power (×200). The degree of positive tumor staining (percentage of positive tumor cells in the examined section) was scored from 1–6 and the staining intensity was scored from 0–6 according to the pattern of staining in the examined section. Staining index (SI) was calculated by multiplying the cellularity and staining scores as described by King et al. [ 14 ].
Immunohistochemistry
Four micron sections of each normal and tumor specimen were cut onto positive-charged slides; air dried overnight, de-paraffinized in xylene, hydrated through a series of graded alcohol and washed in distilled water and 0.01 PBS (pH 7.4). Slides were then processed for IHC as described by Handa et al. [ 8 ]. using the following antibodies:  Ki-67  (MIB-1, Dako),  cyclin A  (6E6; Novocastra, Newcastle-Upon-Tyne, UK) and  cyclin D1  (DCS-6, Dako). A case of invasive breast cancer was used as a positive control for  Ki-67  and  cyclin A  whereas a case of mantle cell lymphoma was used as a control for  cyclin D1 . Negative controls were obtained by replacing the primary antibody by non-immunized rabbit or mouse serum.Ki-67cyclin Acyclin D1Ki-67cyclin Acyclin D1Brown nuclear staining was regarded as a positive result for all studied markers. The proportion of positively-stained cells and the intensity of staining were scored in tumor and normal colorectal mucosal sections at medium power (×200). The degree of positive tumor staining (percentage of positive tumor cells in the examined section) was scored from 1–6 and the staining intensity was scored from 0–6 according to the pattern of staining in the examined section. Staining index (SI) was calculated by multiplying the cellularity and staining scores as described by King et al. [ 14 ].In situ hybridization All tumor samples and 5 normal controls were assessed for  histone H3  mRNA by ISH using the commercially available 550 base fluorescein-labeled DNA probe (Dako, Carpinteria, CA) as described by Nagao et al., 1996. This probe hybridizes to the whole mRNA transcript of the human  histoneH3  gene including the5' and 3' un-translated regions. Scoring of  histone H3  mRNA was performed as for immunohistochemistry, however, hybridization signals were detected in the cytoplasm.
In situ hybridization
All tumor samples and 5 normal controls were assessed for  histone H3  mRNA by ISH using the commercially available 550 base fluorescein-labeled DNA probe (Dako, Carpinteria, CA) as described by Nagao et al., 1996. This probe hybridizes to the whole mRNA transcript of the human  histoneH3  gene including the5' and 3' un-translated regions. Scoring of  histone H3  mRNA was performed as for immunohistochemistry, however, hybridization signals were detected in the cytoplasm.histone H3histoneH3histone H3Molecular detection of cyclin D1 gene amplification High molecular weight DNA was extracted from paraffin-embedded tissues of the tumor and normal colorectal mucosal samples as previously described [ 15 ]. The proportion of neoplastic and normal cells was determined in each tumor sample by examining hematoxylin and eosin-stained slides obtained from the edge of the specimen used for DNA extraction. Tumor samples were evaluated for amplification of  cyclin D1  if more than 75% of the examined sections were formed of neoplastic cells. Accordingly, 50 cases were eligible for the analysis. Ten micrograms of the extracted DNA was digested with  Eco R1. DNA from selected cases was also digested with  Bgl II and  Hind III. Samples were separated on 0.8% agarose gels and transferred to Hybond-N membranes (Amersham Int., Amersham, UK). The membranes were hybridized with 50% formamide, 5 × SSC, 5 × Denhardt's, 500 μg/ml denatured salmon sperm DNA, 10% dextran sulphate and 10 6  cpm/ml of  32 P-labeled  PRAD-1  probe for 24 h. Membranes were washed with 2 × SSC, 0.1% SDS at room temperature for 30 min followed by 2 × SSC, 0.1% SDS at 60°C for 30 min and 0.1 × SSC, 0.1% SDS at 60°C for 1 h. Filters were autoradiographed using an intensifying screen at -70°C for 24–72 h. After being stripped free of the  PRAD-1  probe, the same blots were hybridized with  32 P-labeled  B-actin  probe to normalize against possible variations in the loading or transfer of DNA. The autoradiograms were analyzed using a densitometer. Intensities of  PRAD-1/cyclin D1  were normalized to the  β-actin  control bands. The degree of amplification was calculated from these normalized values. Amplification was considered when the signal of the tumor band was ≥2-fold the value of the matched normal mucosa [ 16 ].
Molecular detection of cyclin D1 gene amplification
High molecular weight DNA was extracted from paraffin-embedded tissues of the tumor and normal colorectal mucosal samples as previously described [ 15 ]. The proportion of neoplastic and normal cells was determined in each tumor sample by examining hematoxylin and eosin-stained slides obtained from the edge of the specimen used for DNA extraction. Tumor samples were evaluated for amplification of  cyclin D1  if more than 75% of the examined sections were formed of neoplastic cells. Accordingly, 50 cases were eligible for the analysis. Ten micrograms of the extracted DNA was digested with  Eco R1. DNA from selected cases was also digested with  Bgl II and  Hind III. Samples were separated on 0.8% agarose gels and transferred to Hybond-N membranes (Amersham Int., Amersham, UK). The membranes were hybridized with 50% formamide, 5 × SSC, 5 × Denhardt's, 500 μg/ml denatured salmon sperm DNA, 10% dextran sulphate and 10 6  cpm/ml of  32 P-labeled  PRAD-1  probe for 24 h. Membranes were washed with 2 × SSC, 0.1% SDS at room temperature for 30 min followed by 2 × SSC, 0.1% SDS at 60°C for 30 min and 0.1 × SSC, 0.1% SDS at 60°C for 1 h. Filters were autoradiographed using an intensifying screen at -70°C for 24–72 h. After being stripped free of the  PRAD-1  probe, the same blots were hybridized with  32 P-labeled  B-actin  probe to normalize against possible variations in the loading or transfer of DNA. The autoradiograms were analyzed using a densitometer. Intensities of  PRAD-1/cyclin D1  were normalized to the  β-actin  control bands. The degree of amplification was calculated from these normalized values. Amplification was considered when the signal of the tumor band was ≥2-fold the value of the matched normal mucosa [ 16 ].cyclin D1EcoBglHindPRAD-1PRAD-1B-actinPRAD-1/cyclin D1β-actinStatistical analysis The Mann-Whitney non-parametric test was used to compare the SIs of pairs of subjects whereas the Kruskal-wallis was used for categorial data. Correlation between indices was performed using a simple linear regression test. The Kaplan-Meier method was used to create survival curves which were analyzed by the log-rank test. The impact of different variables on survival was determined using the Cox proportional hazards model.  p . values less than 0.05 were considered significant.
Statistical analysis
The Mann-Whitney non-parametric test was used to compare the SIs of pairs of subjects whereas the Kruskal-wallis was used for categorial data. Correlation between indices was performed using a simple linear regression test. The Kaplan-Meier method was used to create survival curves which were analyzed by the log-rank test. The impact of different variables on survival was determined using the Cox proportional hazards model.  p . values less than 0.05 were considered significant.pResults The results of IHC are illustrated in figures  1  and  2 . In general, the staining index (SIs) of all studied markers was higher in carcinomas than in normal colonic mucosal samples ( p  = 0.0001). Normal colorectal mucosa revealed positive imunostaining for  Ki-67  in the lower half of the crypts only. A heterogeneous staining pattern was detected in the neoplastic cells of well and moderately-differentiated adenocarcinomas whereas a diffuse homogeneous staining pattern was detected in poorly-differentiated carcinomas. The SI ranged from 10–40.2 (mean: 24.6 ± 6.5). Figure 1 Normal colonic mucosa showing positive nuclear immunostaining for: (a)  cyclin D1 , (b) ISH of  histone H3  mRNA, (c)  Ki-67  and (d)  cyclin A Figure 2 A case of well differentiated adenocarcinoma with positive immunostaining for: (a)  cyclin D1 , (b)  histone H3  mRNA, (c)  Ki-67 , and (d)  cyclin A . Another case of moderately differentiated denocarcinoma with positive immunostaining for: (e)  c yclin D1, (f)  histone H3  mRNA, (g)  Ki-67 , and (h)  cyclin A . A case of poorly differentiated adenocarcinoma with diffuse staining for: (i)  cyclin D1 , (j) ISH of  histone H3  mRNA, (k)  Ki-67  and (l)  cyclin A . Immunostaining for  cyclin D1  was predominantly nuclear but cytoplasmic staining was detected in some cases. However, unless a nuclear staining was also detected, cases with cytoplasmic staining were considered negative. Normal colorectal mucosal samples were almost negative for  cyclin D1  whereas 41 out of the 60 (68.3%) CRC cases were positive. Marked heterogeneity was observed in well- and moderately-differentiated adenocarcinomas even within the same tumor. Poorly-differentiated carcinomas revealed a diffuse staining pattern with more darkly-stained nuclei. The SI ranged from 0.5–28.6 (mean: 9.3 ± 4.2). Positive nuclear staining for  cyclin A  was detected in 80% (48/60) of CRC cases and in all non-neoplastic control samples. Positively-stained nuclei were confined to the lower half of the crypts in normal colonic mucosa and diffusely-dispersed in carcinomas. The SI ranged from 3.3–30.2 (mean: 15.1 ± 6.6). Histone H3  mRNA was intensely expressed in the cytoplasm of all examined samples either neoplastic or non-neoplastic. The distribution of  histone H3  mRNA was similar to that of  cyclin A  and  Ki-67  however, the proportion of  histone H3  mRNA positive cells was less than that of  Ki-67 . The SI ranged from 1.8–24.2 (mean: 12.4 ± 5.3). The  PRAD-1  probe detected 3  Eco RI fragments of 4.0, 2.2 and 2.0 and 1  Bgl II fragment of 15 Kb.  PRAD-1/cyclin D1  gene amplification was detected in 22/50 (44%) cases analyzed. The degree of amplification was heterogeneous with 2–10 fold increase when compared to normal mucosal samples (Figure  3 ). Amplification was confirmed by other restriction enzymes. Figure 3 A:  Southern blot analysis of normal mucosa (N) and their seven corresponding cases of colonic adenocarcinomas (T1–T7), cases No. 1, 2, 4, and 5 are poorly differentiated whereas cases No. 3, 6, and 7 are moderately differentiated. Genomic DNA was digested with  Bgl II, fractionated by electrophoresis in agarose gel, transferred onto membranes and hybridized with  PRAD1  and  β-actin . Tumors number 1–6 (Lanes 1–6) show different degrees of  PRAD1/cyclin D1  amplification, tumor number 7 (lane 7) was not amplified.  B : Southern blot analysis of 3 cases of adenocarcinomas (T) and matched normal colonic mucosa (N). Genomic DNA was digested with  Eco RI, fractionated by electrophoresis in agarose gel, transferred onto membranes and hybridized with  PRAD1  and  β-actin  probes for loading control. The identification of the 3 tumors is the same as in Fig. 3A with amplification of  PRAD1/cyclin D1  in tumors number 4, 5 (Lanes 1, 2) but not 7 (Lane 3). Correlations There was a significant correlation between  cyclin D1  gene amplification and protein overexpression. Out of the 22 cases that showed amplification 14 showed protein overexpression (concordance = 63.6%). Linear regression analysis of SIs revealed a significant correlation between  Ki-67  and  cyclin D1, cyclin A, histone H3  as well as between the SIs of  cyclin A  and  histone H3  ( p  = 0.008, 0.0001, and 0.0001 respectively) (Figure  4 ). There was a significant relationship between the SI of both  Ki-67  and  cyclin A  and the degree of differentiation of tumors as well as the size of the tumor ( p  < 0.001 and  p  < 0.01 respectively). In addition, SI of  Ki-67  and  histone H3  were higher in patients <50 years than in those ≥50 years ( p  < 0.05) (table  1 ). Figure 4 Correlation between the staining intensity of (a)  Ki-67 vs. cyclin D1 , (b)  Ki-67 vs. histone H3 , (c)  Ki-67 vs. cyclin A  and (d)  cyclin A vs. histone H3  mRNA expression. In addition table  2  shows a significant relationship between high  cyclin D1  SI and large, poorly-differentiated tumors, carcinomas with positive lymph node metastasis and deeply-invasive carcinomas ( p  < 0.05,  p  < 0.001,  p  < 0.05 and  p  < 0.05 respectively). Whereas  cyclin D1  gene amplification was significantly associated with an advanced disease stage since amplification was detected in 10/15 (66.7%) of stage IV tumors compared to 12/45 (26.7%) of stage I-III tumors ( p  = 0.002). Similarly, DNA amplification was detected in 60.5% (26/43) of the carcinomas with extensive local invasion (beyond sm) but only in 23.5% (4/17) of the carcinomas with limited invasion (m, sm) ( p  = 0.001). A significant correlation was also present between  cyclin D1  gene amplification and the presence of lymph node metastasis ( p  = 0.008) as well as between the SI of  histone H3 , the size of the tumor and the patient's age ( p  < 0.05,  p  < 0.001 respectively). The SI was higher in tumors >5 cm in diameter and in patients <50 years. Table 2 The relation between  cyclin D1  overexpression vs  cyclin D1  amplification and clinicopathological prognostic markers. Variables No. of cases Cyclin DI overexpression Cyclin D1 Amplification Tumor size (cm)   <5.0 33 5.3 ± 3.8* 13/33   ≥5.0 27 22.8 ± 7.2  p  < 0.05 9/27 p < 0.236 Histology   GI 15 6.6 ± 4.0 7/15   GII 21 8.9 ± 3.6 8/21   GIII 24 22.0 ± 8.1  p  < 0.001 7/24  p  < 0.075 Lymph node   Negative 33 5.4 ± 5.3* 6/33 (18.2%)   Positive 27 20.6 ± 6.9  p  < 0.05 16/27 (59.3%)  p  < 0.008 Depth of invasion   m, sm 17 3.1 ± 3.1* 4/17 (23.5%)   beyond sm 43 12.4 ± 6.5  p  < 0.05 26/43 (60.5%)  p  < 0.001 Stage   early 45 5.5 ± 10.1 12/45 (26.7%)   late 15 11.3 ± 9.6 P =  0.175 10/15 (66.7%)  p  < 0.002 Survival analysis The mean follow-up period for all patients was 30 months (range: 1–66 months). Eighteen of 60 patients had already died by the time the study was completed. We defined the cutoff level for overexpression of each cell cycle marker at the point that showed the maximum difference of survival rate between the 2 groups separated by that point. Cox regression analysis revealed that  cyclin A  overexpression (our definition: SI ≥ 10.5),  cyclin D1  overexpression (our definition: SI ≥ 6.1), poorly differentiated histology, lymph node metastasis, TNM stage, tumor size and depth of invasion were all significant prognostic variables for survival (Table  3 ). The Kaplan-Meier survival curves for the subgroups of patients who are subdivided according to each marker's status are shown in Figure  5 . Patient with tumors that showed  Ki-67  overexpression (our definition: SI ≥ 11.5) and  histone H3  overexpression (our definition: SI ≥ 8.2) tended to have poor prognosis but this did not reach a statistically significant level, however the overall survival was significantly lower in patient with  cyclin A  and  cyclin D1  overexpression. Cox multivariate regression analysis revealed that lymph node metastasis,  cyclin A  and  cyclin D1  overexpression were independent negative prognostic factors after adjustment for the depth of tumor invasion, age and sex of the patient (Table  4 ). Table 3 Uunivariate analysis of the relationship between survival and the tested markers PredictiveVariables Median Survival HR CI P Ki-67  <11.5 36  ≥11.5 32 1.826 0.636 – 5.243 0.26 Cyclin D1  <6.1 35  ≥6.1 18 7.246 1.007 – 45.150 0.03* Histone H3  <8.2 35  ≥8.2 29 4.639 0.854 – 25.196 0.07 Cyclin A  <10.5 35  ≥10.5 15 7.820 1.017 – 60.122 0.02* Histological grade   Low 38   High 10 7.331 2.696 – 19.940 0.0001* Lymph node   Negative 38   Positive 15 6.826 1.973 – 23.621 0.002* Stage   I, II, III 38   IV 12 6.378 1.842 – 22.083 0.001* Tumor size (cm)  <5.0 35  ≥5.0 13 4.835 1.386 – 16.868 0.01* Depth of invasion  T1, T2 36  T3, T4 20 7.759 1.024 – 58.789 0.04* Age (years)  <50 38  ≥50 28 2.802 0.988 – 7.943 0.0526 Sex   Male 38   Female 36 0.696 00.274 – 1.766 0.4449 * p. value < 0.05 (significant) HR: Hazard Ratio CI: 95% confidence Interval Figure 5 Kaplan-Meier survival curves for colorectal carcinoma. Overall survival is significantly lower in patients with (a)  cyclin A  and (b)  cyclin D1  overexpression. Patients with high SI for  histone H3  mRNA have poorer prognosis but this was not statistically significant (c). No significant difference was present between patients with high  Ki-67  SI and those with low  Ki-67  SI (d). Table 4 Multivariate analysis ofthe relationship between survival and thetested markers PredictiveVariables HR CI P Cyclin D1 10.864 1.055 – 86.250 0.03*  (baseline < 6.1) - - - Cyclin A 13.886 1.012 – 190.579 0.0490*  (baseline < 10.5) - - - Positive Lymph node metastasis 3.921 1.057 – 14.472 0.0410* Stage IV 3.411 1.048 – 12.083 0.03* Depth of invasion  T3, T4 5.408 0.449 – 65.080 0.1836 Age (years) ≥50 1.996 0.678 – 5.878 0.2310 Sex 0.910 0.315 – 2.358 0.8453 p. value < 0.05 (significant) HR: Hazard Ratio CI: 95% confidence Interval
Results
The results of IHC are illustrated in figures  1  and  2 . In general, the staining index (SIs) of all studied markers was higher in carcinomas than in normal colonic mucosal samples ( p  = 0.0001). Normal colorectal mucosa revealed positive imunostaining for  Ki-67  in the lower half of the crypts only. A heterogeneous staining pattern was detected in the neoplastic cells of well and moderately-differentiated adenocarcinomas whereas a diffuse homogeneous staining pattern was detected in poorly-differentiated carcinomas. The SI ranged from 10–40.2 (mean: 24.6 ± 6.5).pKi-67Immunostaining for  cyclin D1  was predominantly nuclear but cytoplasmic staining was detected in some cases. However, unless a nuclear staining was also detected, cases with cytoplasmic staining were considered negative. Normal colorectal mucosal samples were almost negative for  cyclin D1  whereas 41 out of the 60 (68.3%) CRC cases were positive. Marked heterogeneity was observed in well- and moderately-differentiated adenocarcinomas even within the same tumor. Poorly-differentiated carcinomas revealed a diffuse staining pattern with more darkly-stained nuclei. The SI ranged from 0.5–28.6 (mean: 9.3 ± 4.2).cyclin D1cyclin D1Positive nuclear staining for  cyclin A  was detected in 80% (48/60) of CRC cases and in all non-neoplastic control samples. Positively-stained nuclei were confined to the lower half of the crypts in normal colonic mucosa and diffusely-dispersed in carcinomas. The SI ranged from 3.3–30.2 (mean: 15.1 ± 6.6).cyclin AHistone H3  mRNA was intensely expressed in the cytoplasm of all examined samples either neoplastic or non-neoplastic. The distribution of  histone H3  mRNA was similar to that of  cyclin A  and  Ki-67  however, the proportion of  histone H3  mRNA positive cells was less than that of  Ki-67 . The SI ranged from 1.8–24.2 (mean: 12.4 ± 5.3).Histone H3histone H3cyclin AKi-67histone H3Ki-67The  PRAD-1  probe detected 3  Eco RI fragments of 4.0, 2.2 and 2.0 and 1  Bgl II fragment of 15 Kb.  PRAD-1/cyclin D1  gene amplification was detected in 22/50 (44%) cases analyzed. The degree of amplification was heterogeneous with 2–10 fold increase when compared to normal mucosal samples (Figure  3 ). Amplification was confirmed by other restriction enzymes.PRAD-1EcoBglPRAD-1/cyclin D1Correlations There was a significant correlation between  cyclin D1  gene amplification and protein overexpression. Out of the 22 cases that showed amplification 14 showed protein overexpression (concordance = 63.6%). Linear regression analysis of SIs revealed a significant correlation between  Ki-67  and  cyclin D1, cyclin A, histone H3  as well as between the SIs of  cyclin A  and  histone H3  ( p  = 0.008, 0.0001, and 0.0001 respectively) (Figure  4 ). There was a significant relationship between the SI of both  Ki-67  and  cyclin A  and the degree of differentiation of tumors as well as the size of the tumor ( p  < 0.001 and  p  < 0.01 respectively). In addition, SI of  Ki-67  and  histone H3  were higher in patients <50 years than in those ≥50 years ( p  < 0.05) (table  1 ). Figure 4 Correlation between the staining intensity of (a)  Ki-67 vs. cyclin D1 , (b)  Ki-67 vs. histone H3 , (c)  Ki-67 vs. cyclin A  and (d)  cyclin A vs. histone H3  mRNA expression. In addition table  2  shows a significant relationship between high  cyclin D1  SI and large, poorly-differentiated tumors, carcinomas with positive lymph node metastasis and deeply-invasive carcinomas ( p  < 0.05,  p  < 0.001,  p  < 0.05 and  p  < 0.05 respectively). Whereas  cyclin D1  gene amplification was significantly associated with an advanced disease stage since amplification was detected in 10/15 (66.7%) of stage IV tumors compared to 12/45 (26.7%) of stage I-III tumors ( p  = 0.002). Similarly, DNA amplification was detected in 60.5% (26/43) of the carcinomas with extensive local invasion (beyond sm) but only in 23.5% (4/17) of the carcinomas with limited invasion (m, sm) ( p  = 0.001). A significant correlation was also present between  cyclin D1  gene amplification and the presence of lymph node metastasis ( p  = 0.008) as well as between the SI of  histone H3 , the size of the tumor and the patient's age ( p  < 0.05,  p  < 0.001 respectively). The SI was higher in tumors >5 cm in diameter and in patients <50 years. Table 2 The relation between  cyclin D1  overexpression vs  cyclin D1  amplification and clinicopathological prognostic markers. Variables No. of cases Cyclin DI overexpression Cyclin D1 Amplification Tumor size (cm)   <5.0 33 5.3 ± 3.8* 13/33   ≥5.0 27 22.8 ± 7.2  p  < 0.05 9/27 p < 0.236 Histology   GI 15 6.6 ± 4.0 7/15   GII 21 8.9 ± 3.6 8/21   GIII 24 22.0 ± 8.1  p  < 0.001 7/24  p  < 0.075 Lymph node   Negative 33 5.4 ± 5.3* 6/33 (18.2%)   Positive 27 20.6 ± 6.9  p  < 0.05 16/27 (59.3%)  p  < 0.008 Depth of invasion   m, sm 17 3.1 ± 3.1* 4/17 (23.5%)   beyond sm 43 12.4 ± 6.5  p  < 0.05 26/43 (60.5%)  p  < 0.001 Stage   early 45 5.5 ± 10.1 12/45 (26.7%)   late 15 11.3 ± 9.6 P =  0.175 10/15 (66.7%)  p  < 0.002
Correlations
There was a significant correlation between  cyclin D1  gene amplification and protein overexpression. Out of the 22 cases that showed amplification 14 showed protein overexpression (concordance = 63.6%).cyclin D1Linear regression analysis of SIs revealed a significant correlation between  Ki-67  and  cyclin D1, cyclin A, histone H3  as well as between the SIs of  cyclin A  and  histone H3  ( p  = 0.008, 0.0001, and 0.0001 respectively) (Figure  4 ). There was a significant relationship between the SI of both  Ki-67  and  cyclin A  and the degree of differentiation of tumors as well as the size of the tumor ( p  < 0.001 and  p  < 0.01 respectively). In addition, SI of  Ki-67  and  histone H3  were higher in patients <50 years than in those ≥50 years ( p  < 0.05) (table  1 ).Ki-67cyclin D1, cyclin A, histone H3cyclin Ahistone H3pKi-67cyclin AppKi-67histone H3pIn addition table  2  shows a significant relationship between high  cyclin D1  SI and large, poorly-differentiated tumors, carcinomas with positive lymph node metastasis and deeply-invasive carcinomas ( p  < 0.05,  p  < 0.001,  p  < 0.05 and  p  < 0.05 respectively). Whereas  cyclin D1  gene amplification was significantly associated with an advanced disease stage since amplification was detected in 10/15 (66.7%) of stage IV tumors compared to 12/45 (26.7%) of stage I-III tumors ( p  = 0.002). Similarly, DNA amplification was detected in 60.5% (26/43) of the carcinomas with extensive local invasion (beyond sm) but only in 23.5% (4/17) of the carcinomas with limited invasion (m, sm) ( p  = 0.001). A significant correlation was also present between  cyclin D1  gene amplification and the presence of lymph node metastasis ( p  = 0.008) as well as between the SI of  histone H3 , the size of the tumor and the patient's age ( p  < 0.05,  p  < 0.001 respectively). The SI was higher in tumors >5 cm in diameter and in patients <50 years.cyclin D1ppppcyclin D1ppcyclin D1phistone H3ppThe relation between  cyclin D1  overexpression vs  cyclin D1  amplification and clinicopathological prognostic markers.cyclin D1cyclin D1VariablesVariablesNo. of casesNo. of casesCyclin DI overexpressionCyclin DI overexpressionCyclin D1 AmplificationCyclin D1 AmplificationTumor size (cm)Tumor size (cm)<5.0<5.0≥5.0≥5.0p0.050.050.236HistologyHistologyGIGIGIIGIIGIIIGIIIp0.0010.001p0.0750.075Lymph nodeLymph nodeNegativeNegativePositivePositivep0.050.05p0.0080.008Depth of invasionDepth of invasionm, smm, smbeyond smbeyond smp0.050.05p0.0010.001StageStageearlyearlylatelate0.175p0.0020.002Survival analysis The mean follow-up period for all patients was 30 months (range: 1–66 months). Eighteen of 60 patients had already died by the time the study was completed. We defined the cutoff level for overexpression of each cell cycle marker at the point that showed the maximum difference of survival rate between the 2 groups separated by that point. Cox regression analysis revealed that  cyclin A  overexpression (our definition: SI ≥ 10.5),  cyclin D1  overexpression (our definition: SI ≥ 6.1), poorly differentiated histology, lymph node metastasis, TNM stage, tumor size and depth of invasion were all significant prognostic variables for survival (Table  3 ). The Kaplan-Meier survival curves for the subgroups of patients who are subdivided according to each marker's status are shown in Figure  5 . Patient with tumors that showed  Ki-67  overexpression (our definition: SI ≥ 11.5) and  histone H3  overexpression (our definition: SI ≥ 8.2) tended to have poor prognosis but this did not reach a statistically significant level, however the overall survival was significantly lower in patient with  cyclin A  and  cyclin D1  overexpression. Cox multivariate regression analysis revealed that lymph node metastasis,  cyclin A  and  cyclin D1  overexpression were independent negative prognostic factors after adjustment for the depth of tumor invasion, age and sex of the patient (Table  4 ). Table 3 Uunivariate analysis of the relationship between survival and the tested markers PredictiveVariables Median Survival HR CI P Ki-67  <11.5 36  ≥11.5 32 1.826 0.636 – 5.243 0.26 Cyclin D1  <6.1 35  ≥6.1 18 7.246 1.007 – 45.150 0.03* Histone H3  <8.2 35  ≥8.2 29 4.639 0.854 – 25.196 0.07 Cyclin A  <10.5 35  ≥10.5 15 7.820 1.017 – 60.122 0.02* Histological grade   Low 38   High 10 7.331 2.696 – 19.940 0.0001* Lymph node   Negative 38   Positive 15 6.826 1.973 – 23.621 0.002* Stage   I, II, III 38   IV 12 6.378 1.842 – 22.083 0.001* Tumor size (cm)  <5.0 35  ≥5.0 13 4.835 1.386 – 16.868 0.01* Depth of invasion  T1, T2 36  T3, T4 20 7.759 1.024 – 58.789 0.04* Age (years)  <50 38  ≥50 28 2.802 0.988 – 7.943 0.0526 Sex   Male 38   Female 36 0.696 00.274 – 1.766 0.4449 * p. value < 0.05 (significant) HR: Hazard Ratio CI: 95% confidence Interval Figure 5 Kaplan-Meier survival curves for colorectal carcinoma. Overall survival is significantly lower in patients with (a)  cyclin A  and (b)  cyclin D1  overexpression. Patients with high SI for  histone H3  mRNA have poorer prognosis but this was not statistically significant (c). No significant difference was present between patients with high  Ki-67  SI and those with low  Ki-67  SI (d). Table 4 Multivariate analysis ofthe relationship between survival and thetested markers PredictiveVariables HR CI P Cyclin D1 10.864 1.055 – 86.250 0.03*  (baseline < 6.1) - - - Cyclin A 13.886 1.012 – 190.579 0.0490*  (baseline < 10.5) - - - Positive Lymph node metastasis 3.921 1.057 – 14.472 0.0410* Stage IV 3.411 1.048 – 12.083 0.03* Depth of invasion  T3, T4 5.408 0.449 – 65.080 0.1836 Age (years) ≥50 1.996 0.678 – 5.878 0.2310 Sex 0.910 0.315 – 2.358 0.8453 p. value < 0.05 (significant) HR: Hazard Ratio CI: 95% confidence Interval
Survival analysis
The mean follow-up period for all patients was 30 months (range: 1–66 months). Eighteen of 60 patients had already died by the time the study was completed. We defined the cutoff level for overexpression of each cell cycle marker at the point that showed the maximum difference of survival rate between the 2 groups separated by that point. Cox regression analysis revealed that  cyclin A  overexpression (our definition: SI ≥ 10.5),  cyclin D1  overexpression (our definition: SI ≥ 6.1), poorly differentiated histology, lymph node metastasis, TNM stage, tumor size and depth of invasion were all significant prognostic variables for survival (Table  3 ). The Kaplan-Meier survival curves for the subgroups of patients who are subdivided according to each marker's status are shown in Figure  5 . Patient with tumors that showed  Ki-67  overexpression (our definition: SI ≥ 11.5) and  histone H3  overexpression (our definition: SI ≥ 8.2) tended to have poor prognosis but this did not reach a statistically significant level, however the overall survival was significantly lower in patient with  cyclin A  and  cyclin D1  overexpression. Cox multivariate regression analysis revealed that lymph node metastasis,  cyclin A  and  cyclin D1  overexpression were independent negative prognostic factors after adjustment for the depth of tumor invasion, age and sex of the patient (Table  4 ).cyclin Acyclin D1Ki-67histone H3cyclin Acyclin D1cyclin Acyclin D1Uunivariate analysis of the relationship between survival and the tested markersPredictiveVariablesPredictiveVariablesMedian SurvivalMedian SurvivalHRHRCICIPPKi-67Ki-67Cyclin D1Cyclin D1Histone H3Histone H3Cyclin ACyclin AHistological gradeHistological gradeLowLowHighHighLymph nodeLymph nodeNegativeNegativePositivePositiveStageStageI, II, IIII, II, IIIIVIVTumor size (cm)Tumor size (cm)Depth of invasionDepth of invasionAge (years)Age (years)SexSexMaleMaleFemaleFemale* p. value < 0.05 (significant)HR: Hazard RatioCI: 95% confidence IntervalMultivariate analysis ofthe relationship between survival and thetested markersPredictiveVariablesPredictiveVariablesHRHRCICIPPCyclin D1Cyclin D1Cyclin ACyclin APositive Lymph node metastasisPositive Lymph node metastasisStage IVStage IVDepth of invasionDepth of invasionAge (years)Age (years)SexSexp. value < 0.05 (significant)HR: Hazard RatioCI: 95% confidence IntervalDiscussion The proliferative activity of CRC cells has been investigated in several studies either by immunohistochemical determination of cell proliferation index using antibodies to some types of  cyclins  or by flowcytometric determination of the SPF of the cell cycle [ 8 ]. Although Leach et al. [ 17 ] did not find  cyclin D1  gene amplification in a panel of 47 CRC cell lines; its protein was overexpressed in about 30% of CRC cases that were included in the studies of Bartakova et al. [ 6 ] and Arber et al. [ 18 ]. In the former study [ 6 ] cyclin D1  was aberrantly accumulated in a significant subset of human CRC cases and the cell lines derived from these cases were dependent on  cyclin  in their cell cycle progression. In the second study [ 18 ], overexpression of  cyclin D1  was detected in 30% of adenomatous polyps indicating that overexpression is a relatively early event in colon carcinogenesis which is possibly responsible for the pathological changes in the mucosa preceding neoplastic transformation. More recently, Holland et al. [ 19 ], Pasz-Walczak et al. [ 20 ] and Utsunomiya et al. [ 21 ] reported up-regulation of  cyclin D1  in 58.7%, 100% and 43% of their studied cases respectively. In the present study, up-regulation of  cyclin D1  was detected in 68.3% of the cases. The SI was significantly higher in carcinomas than in normal colorectal mucosa and in poorly-differentiated adenocarcinomas it was approximately twice that of other histological types. Amplification and/or overexpression of  cyclin D1  significantly correlated with deeply invasive tumors and positive lymph node metastasis. Our results in this regards are consistent with previous studies [ 8 , 22 ]. In 2001, Holland et al. [ 19 ]. demonstrated that deregulation of  cyclin D1  and  p21 waf  proteins are important in colorectal tumorigenesis and have implications for patient prognosis. Similarly McKay et al. [ 23 ] found that  cyclin D1  was the only protein in their panel ( cyclin D1, p53, p16, Rb-1, PCNA and p27 ) that correlated with improved outcome in CRC patients. However, few studies failed to detect any correlation between  cyclin D1  overexpression and the clinicopathological factors in CRC [ 6 , 18 ]. This controversy in results could partially be explained by the difference in the sampling of studied cases. The present study included 24 cases of poorly differentiated adenocarcinoma, which is not common in other studies of CRC in western countries. This was possible because the majority of CRC cases diagnosed in Egypt are of high histological grade [ 3 ]. The correlation between  cyclin D1  overexpression and the high histological grade was also reported in other tumor types including non-small cell lung carcinomas [ 24 ] and squamous cell carcinomas of the larynx [ 16 ]. Another possible explanation for the observed controversy in the results of different studies is the detection method used. In the present work, overexpression of  cyclin D1  was more common than gene amplification of the  PRAD-1/cyclin D1  gene with a 63.6% concordance. This was similarly reported by Bartakova et al. [ 6 ] who mentioned that there is a subset of CRC cases in which  cyclin D1  is overexpressed without  PRAD-1/cyclin D1  gene amplification. Consistent with this hypothesis are reports of elevated  cyclin D1  mRNA levels and immunohistochemically detectable accumulation of the protein in over one third of breast cancer cases at a frequency significantly higher than that deduced from DNA amplification studies [ 9 , 25 ]. These data imply that mechanisms other than gene amplification can also lead to deregulation and accumulation of  cyclin D1  in solid tumors. So far, several studies were done to reveal the prognostic significance of  cyclin D1  overexpression in various carcinomas, including CRC [ 22 ]. However, these studies yielded conflicting results which could be attributed to organ heterogeneity. In our study, patients with tumors that exhibited  cyclin D1  overexpression tended to have poor prognosis. It was reported that, patients with  cyclin A  positive carcinomas had significantly shorter median survival times. Handa et al. [ 8 ] were able to detect  cyclin A  overexpression in 77% of their CRC cases. They also demonstrated that,  cylcin A  could be used as a prognostic factor of CRC. More recently, Habermann et al. [ 26 ] studied cases of ulcerative colitis with and without an associated adenocarcinoma for the presence of  cyclin A  overexpression. They found that,  cyclin A  overexpression was higher in cases of ulcerative colitis with adenocarcinomas than in those without adenocarcinomas. Consequently, they concluded that,  cyclin A  could be used for monitoring ulcerative colitis patients and for the early detection of an emerging carcinoma in this high risk group of patients. In our study,  cyclin A  was detected in 80% of the patients and Cox regression analysis showed that it could be used as a prognostic marker in CRC in addition to  cyclin D1 . It would have been useful if we assessed the expression level of  cyclin A  by another technique (DNA amplification). This would have added more information regarding the gene status on one hand and confirmed the results of IHC on the other hand. Unfortunately, this was not possible because in most of the cases included in the present work, the extracted DNA was not sufficient to study  cyclin amplification  after the assessment of  cyclin D1 . In 1996, Nagao et al. [ 11 ] reported that  histone H3  labeling index significantly correlated with ki-67 immunostaining and was high in poorly differentiated human hepatocellular carcinoma. This was similarly reported in the present work since we found a significant correlation between the SI of  histone H3  and  Ki-67 . However, no statistically significant correlation was found between  histone H3  SI and any of the studied clinicopathological factors. Although  Ki-67  immunostaining reflects the proliferative activity of CRC, it has not been recognized as a significant prognostic factor in this type of tumors [ 27 , 28 ]. However, Suzuki at al. [ 29 ] found a significant correlation between  Ki-67  labeling index and local invasion of CRC. In the present study there was a significant relationship between the SI of  Ki-67 , tumor size and grade. However, Kaplan-Meier survival curves showed no significant difference in survival rates between patients with- and without overexpression of  Ki-67 .
Discussion
The proliferative activity of CRC cells has been investigated in several studies either by immunohistochemical determination of cell proliferation index using antibodies to some types of  cyclins  or by flowcytometric determination of the SPF of the cell cycle [ 8 ]. Although Leach et al. [ 17 ] did not find  cyclin D1  gene amplification in a panel of 47 CRC cell lines; its protein was overexpressed in about 30% of CRC cases that were included in the studies of Bartakova et al. [ 6 ] and Arber et al. [ 18 ]. In the former study [ 6 ] cyclin D1  was aberrantly accumulated in a significant subset of human CRC cases and the cell lines derived from these cases were dependent on  cyclin  in their cell cycle progression. In the second study [ 18 ], overexpression of  cyclin D1  was detected in 30% of adenomatous polyps indicating that overexpression is a relatively early event in colon carcinogenesis which is possibly responsible for the pathological changes in the mucosa preceding neoplastic transformation. More recently, Holland et al. [ 19 ], Pasz-Walczak et al. [ 20 ] and Utsunomiya et al. [ 21 ] reported up-regulation of  cyclin D1  in 58.7%, 100% and 43% of their studied cases respectively.cyclinscyclin D1cyclin D1cyclincyclin D1cyclin D1In the present study, up-regulation of  cyclin D1  was detected in 68.3% of the cases. The SI was significantly higher in carcinomas than in normal colorectal mucosa and in poorly-differentiated adenocarcinomas it was approximately twice that of other histological types. Amplification and/or overexpression of  cyclin D1  significantly correlated with deeply invasive tumors and positive lymph node metastasis. Our results in this regards are consistent with previous studies [ 8 , 22 ]. In 2001, Holland et al. [ 19 ]. demonstrated that deregulation of  cyclin D1  and  p21 waf  proteins are important in colorectal tumorigenesis and have implications for patient prognosis. Similarly McKay et al. [ 23 ] found that  cyclin D1  was the only protein in their panel ( cyclin D1, p53, p16, Rb-1, PCNA and p27 ) that correlated with improved outcome in CRC patients. However, few studies failed to detect any correlation between  cyclin D1  overexpression and the clinicopathological factors in CRC [ 6 , 18 ]. This controversy in results could partially be explained by the difference in the sampling of studied cases. The present study included 24 cases of poorly differentiated adenocarcinoma, which is not common in other studies of CRC in western countries. This was possible because the majority of CRC cases diagnosed in Egypt are of high histological grade [ 3 ]. The correlation between  cyclin D1  overexpression and the high histological grade was also reported in other tumor types including non-small cell lung carcinomas [ 24 ] and squamous cell carcinomas of the larynx [ 16 ]. Another possible explanation for the observed controversy in the results of different studies is the detection method used.cyclin D1cyclin D1cyclin D1p21wafcyclin D1cyclin D1, p53, p16, Rb-1, PCNA and p27cyclin D1cyclin D1In the present work, overexpression of  cyclin D1  was more common than gene amplification of the  PRAD-1/cyclin D1  gene with a 63.6% concordance. This was similarly reported by Bartakova et al. [ 6 ] who mentioned that there is a subset of CRC cases in which  cyclin D1  is overexpressed without  PRAD-1/cyclin D1  gene amplification. Consistent with this hypothesis are reports of elevated  cyclin D1  mRNA levels and immunohistochemically detectable accumulation of the protein in over one third of breast cancer cases at a frequency significantly higher than that deduced from DNA amplification studies [ 9 , 25 ]. These data imply that mechanisms other than gene amplification can also lead to deregulation and accumulation of  cyclin D1  in solid tumors.cyclin D1PRAD-1/cyclin D1cyclin D1PRAD-1/cyclin D1cyclin D1cyclin D1So far, several studies were done to reveal the prognostic significance of  cyclin D1  overexpression in various carcinomas, including CRC [ 22 ]. However, these studies yielded conflicting results which could be attributed to organ heterogeneity. In our study, patients with tumors that exhibited  cyclin D1  overexpression tended to have poor prognosis.cyclin D1cyclin D1It was reported that, patients with  cyclin A  positive carcinomas had significantly shorter median survival times. Handa et al. [ 8 ] were able to detect  cyclin A  overexpression in 77% of their CRC cases. They also demonstrated that,  cylcin A  could be used as a prognostic factor of CRC. More recently, Habermann et al. [ 26 ] studied cases of ulcerative colitis with and without an associated adenocarcinoma for the presence of  cyclin A  overexpression. They found that,  cyclin A  overexpression was higher in cases of ulcerative colitis with adenocarcinomas than in those without adenocarcinomas. Consequently, they concluded that,  cyclin A  could be used for monitoring ulcerative colitis patients and for the early detection of an emerging carcinoma in this high risk group of patients.cyclin Acyclin Acylcin Acyclin Acyclin Acyclin AIn our study,  cyclin A  was detected in 80% of the patients and Cox regression analysis showed that it could be used as a prognostic marker in CRC in addition to  cyclin D1 .cyclin Acyclin D1It would have been useful if we assessed the expression level of  cyclin A  by another technique (DNA amplification). This would have added more information regarding the gene status on one hand and confirmed the results of IHC on the other hand. Unfortunately, this was not possible because in most of the cases included in the present work, the extracted DNA was not sufficient to study  cyclin amplification  after the assessment of  cyclin D1 .cyclin Acyclin amplificationcyclin D1In 1996, Nagao et al. [ 11 ] reported that  histone H3  labeling index significantly correlated with ki-67 immunostaining and was high in poorly differentiated human hepatocellular carcinoma. This was similarly reported in the present work since we found a significant correlation between the SI of  histone H3  and  Ki-67 . However, no statistically significant correlation was found between  histone H3  SI and any of the studied clinicopathological factors.histone H3histone H3Ki-67histone H3Although  Ki-67  immunostaining reflects the proliferative activity of CRC, it has not been recognized as a significant prognostic factor in this type of tumors [ 27 , 28 ]. However, Suzuki at al. [ 29 ] found a significant correlation between  Ki-67  labeling index and local invasion of CRC. In the present study there was a significant relationship between the SI of  Ki-67 , tumor size and grade. However, Kaplan-Meier survival curves showed no significant difference in survival rates between patients with- and without overexpression of  Ki-67 .Ki-67Ki-67Ki-67Ki-67Conclusions Our results demonstrate that  cyclin D1, cyclin A, histone H3  and  Ki-67  are overexpressed in a subset of CRC, however only  cyclin D1  and  cyclin A  overexpression correlates with poor differentiation and tumor progression. This indicates the superiority of  cyclin A  and  cyclin D1  as indicators of poor prognosis compared to  Ki-67  and  histone H3  mRNA in CRC.  Cyclin A and D1  could therefore be considered significant, independent prognostic factors in CRC patients. These findings are especially important in stage II patients since 25–30% of those patients have poor prognosis in spite of being node-negative. However, the standard clinicopathologic prognostic factors can not identify this subset accurately and therefore; there is a great demand for more accurate, individually-based, biological prognostic parameters that help in detecting this high risk group of patients who can benefit from an adjuvant therapy. If the findings of the present study are confirmed in a larger study, evaluation of  cyclin A and D1  may be applicable to clinical management of CRC, allowing the identification of patients with poor prognosis.
Conclusions
Our results demonstrate that  cyclin D1, cyclin A, histone H3  and  Ki-67  are overexpressed in a subset of CRC, however only  cyclin D1  and  cyclin A  overexpression correlates with poor differentiation and tumor progression. This indicates the superiority of  cyclin A  and  cyclin D1  as indicators of poor prognosis compared to  Ki-67  and  histone H3  mRNA in CRC.  Cyclin A and D1  could therefore be considered significant, independent prognostic factors in CRC patients. These findings are especially important in stage II patients since 25–30% of those patients have poor prognosis in spite of being node-negative. However, the standard clinicopathologic prognostic factors can not identify this subset accurately and therefore; there is a great demand for more accurate, individually-based, biological prognostic parameters that help in detecting this high risk group of patients who can benefit from an adjuvant therapy. If the findings of the present study are confirmed in a larger study, evaluation of  cyclin A and D1  may be applicable to clinical management of CRC, allowing the identification of patients with poor prognosis.cyclin D1, cyclin A, histone H3Ki-67cyclin D1cyclin Acyclin Acyclin D1Ki-67histone H3Cyclin A and D1cyclin A and D1Competing interests The author(s) declare that they have no competing interests.
Competing interests
The author(s) declare that they have no competing interests.List of abbreviations CRC – Colorectal cancer OS – overall survival SI – staining index SPF – S phase fraction ISH – in situ hybridization m – muscularis mucosa sm – invasion of the sub mucosa
List of abbreviations
CRC – Colorectal cancerOS – overall survivalSI – staining indexSPF – S phase fractionISH – in situ hybridizationm – muscularis mucosasm – invasion of the sub mucosaAuthors' contributions BA and ZA-R carried out the molecular genetic studies, designed, coordinated the study and drafted the manuscript. BA and El-HS carried out all the histopathological and immunohistochemical studies. El-SA participated in molecular genetic studies and drafted the manuscript. MM coordinated the study. El-SM carried out all the patient clinical data. All authors read and approved the final manuscript
Authors' contributions
BA and ZA-R carried out the molecular genetic studies, designed, coordinated the study and drafted the manuscript. BA and El-HS carried out all the histopathological and immunohistochemical studies. El-SA participated in molecular genetic studies and drafted the manuscript. MM coordinated the study. El-SM carried out all the patient clinical data. All authors read and approved the final manuscriptPre-publication history The pre-publication history for this paper can be accessed here:
Pre-publication history
The pre-publication history for this paper can be accessed here:


Islet transplantation offers hope to many patients with diabetes, who envision a life free of glucose checks and insulin injections. What are the barriers to its widespread implementation?

Diabetes: Epidemiology and Complications Treatment for, and the prognosis of, type-1 diabetes mellitus (T1DM) has progressed dramatically during the last century, but the disease remains a major cause of morbidity and mortality. Although precise figures are not available, over 1 million United States citizens currently live with the disease, with approximately 30,000 new cases diagnosed in the US each year. The total number of people with diabetes worldwide is expected to rise to 366 million in 2030, up from 171 million in 2000  [1] . The exact etiology of the disease remains uncertain, but extensive research suggests an interaction between genetic predisposition and environment. In fact, for unknown reasons, the incidence of T1DM is increasing  [2] . Diabetes continues to have a tremendous societal impact; it is both difficult and expensive to treat and is associated with a number of long-term complications, including kidney failure, blindness, nerve damage, and premature mortality (predominately due to cardiovascular problems).
Diabetes: Epidemiology and Complications
Treatment for, and the prognosis of, type-1 diabetes mellitus (T1DM) has progressed dramatically during the last century, but the disease remains a major cause of morbidity and mortality. Although precise figures are not available, over 1 million United States citizens currently live with the disease, with approximately 30,000 new cases diagnosed in the US each year. The total number of people with diabetes worldwide is expected to rise to 366 million in 2030, up from 171 million in 2000  [1] .The exact etiology of the disease remains uncertain, but extensive research suggests an interaction between genetic predisposition and environment. In fact, for unknown reasons, the incidence of T1DM is increasing  [2] . Diabetes continues to have a tremendous societal impact; it is both difficult and expensive to treat and is associated with a number of long-term complications, including kidney failure, blindness, nerve damage, and premature mortality (predominately due to cardiovascular problems).Insulin's Impact Banting and Best's discovery of insulin in the early 1920s revolutionized diabetes treatment and greatly improved the prognosis for what had previously been a rapidly fatal disease. As shown by the Diabetes Control and Complications Trial and the more recent Epidemiology of Diabetes Interventions and Complications trial, insulin therapy has made such considerable advances (with better insulin formulations and delivery systems) that many patients can maintain their blood sugar levels within a tight range and thereby reduce their risk for the disease's long-term complications [ 3 , 4 , 5 ]. In addition, improved treatment of other associated conditions such as hypertension and hyperlipidemia have helped reduce, or at least delay, many of the long-term sequelae of diabetes  [6] . However, problems with insulin-based treatment regimens persist. For the patient, treatment is expensive and difficult, requiring strict attention to blood glucose monitoring, insulin dosing, diet, and exercise. Further, good glycemia control is not easily achieved by all patients, and even for those able to achieve this goal, the treatment is not always completely effective.
Insulin's Impact
Banting and Best's discovery of insulin in the early 1920s revolutionized diabetes treatment and greatly improved the prognosis for what had previously been a rapidly fatal disease. As shown by the Diabetes Control and Complications Trial and the more recent Epidemiology of Diabetes Interventions and Complications trial, insulin therapy has made such considerable advances (with better insulin formulations and delivery systems) that many patients can maintain their blood sugar levels within a tight range and thereby reduce their risk for the disease's long-term complications [ 3 , 4 , 5 ]. In addition, improved treatment of other associated conditions such as hypertension and hyperlipidemia have helped reduce, or at least delay, many of the long-term sequelae of diabetes  [6] . However, problems with insulin-based treatment regimens persist. For the patient, treatment is expensive and difficult, requiring strict attention to blood glucose monitoring, insulin dosing, diet, and exercise. Further, good glycemia control is not easily achieved by all patients, and even for those able to achieve this goal, the treatment is not always completely effective.Promising Directions Just as financial investors balance a portfolio, with some risky investments and others that are more secure, researchers will undoubtedly continue to further refine “secure” insulin-based regimens to help patients achieve even better glycemia control. At the same time, scientists are pursuing more high-risk, high-payoff approaches to revolutionize diabetes care. One such approach is the closed-loop insulin pump (i.e., a pump that continuously monitors blood glucose and concurrently converts that data into appropriate insulin dosing), which offers the potential to serve as a mechanical pancreas. However, such a mechanical system would need be fail-safe in order to avoid devastating effects (e.g., if the monitor were to register a falsely elevated blood glucose and thereby trigger an inappropriately high insulin dose). In other, similar scenarios with no tolerance for error, NASA (for instance) sets up systems in which two independent monitoring systems must come up with similar measurements before an action is taken. Perhaps the engineering obstacles that currently limit the closed-loop insulin pump can be overcome. Other research groups are investigating whether the insulin-producing cells within the pancreas (so-called ß cells), might be promoted to regenerate (in vitro or in vivo) to replace the pool of insulin-producing cells reduced by autoimmune destruction. Another promising approach for creating cells capable of physiologically regulated insulin secretion is to “coax” stem cells—undifferentiated cells with self-regenerative capacity—to differentiate into ß-like cells. Gene therapy approaches may overcome present obstacles and result in cells capable of physiologically regulated insulin secretion  [7] . Lastly, the recent completion of the Human Genome Project suggests that the genetics of diabetes may eventually become clearer and may direct appropriate preventative approaches. While such potential therapies remain experimental, pancreas transplantation is currently performed in patients with complicated diabetes. However, a recent report that shows benefit for patients with both diabetes and kidney failure who receive a combined pancreas and kidney transplant also found that an isolated pancreas transplant (for patients with preserved kidney function) actually worsened survival  [8] . The main point is that as we develop new therapies, we must maintain humility and recognize that newer approaches may have great promise, but they also have the potential for harm.
Promising Directions
Just as financial investors balance a portfolio, with some risky investments and others that are more secure, researchers will undoubtedly continue to further refine “secure” insulin-based regimens to help patients achieve even better glycemia control. At the same time, scientists are pursuing more high-risk, high-payoff approaches to revolutionize diabetes care. One such approach is the closed-loop insulin pump (i.e., a pump that continuously monitors blood glucose and concurrently converts that data into appropriate insulin dosing), which offers the potential to serve as a mechanical pancreas. However, such a mechanical system would need be fail-safe in order to avoid devastating effects (e.g., if the monitor were to register a falsely elevated blood glucose and thereby trigger an inappropriately high insulin dose). In other, similar scenarios with no tolerance for error, NASA (for instance) sets up systems in which two independent monitoring systems must come up with similar measurements before an action is taken. Perhaps the engineering obstacles that currently limit the closed-loop insulin pump can be overcome.Other research groups are investigating whether the insulin-producing cells within the pancreas (so-called ß cells), might be promoted to regenerate (in vitro or in vivo) to replace the pool of insulin-producing cells reduced by autoimmune destruction. Another promising approach for creating cells capable of physiologically regulated insulin secretion is to “coax” stem cells—undifferentiated cells with self-regenerative capacity—to differentiate into ß-like cells. Gene therapy approaches may overcome present obstacles and result in cells capable of physiologically regulated insulin secretion  [7] . Lastly, the recent completion of the Human Genome Project suggests that the genetics of diabetes may eventually become clearer and may direct appropriate preventative approaches.While such potential therapies remain experimental, pancreas transplantation is currently performed in patients with complicated diabetes. However, a recent report that shows benefit for patients with both diabetes and kidney failure who receive a combined pancreas and kidney transplant also found that an isolated pancreas transplant (for patients with preserved kidney function) actually worsened survival  [8] . The main point is that as we develop new therapies, we must maintain humility and recognize that newer approaches may have great promise, but they also have the potential for harm.History of Islet Transplantation Islet transplantation has recently received considerable interest as a potentially definitive treatment for diabetes. The concept of islet transplantation is not new—investigators as early as the English surgeon Charles Pybus (1882–1975) attempted to graft pancreatic tissue to cure diabetes. Most, however, credit the recent era of islet transplantation research to Paul Lacy's studies dating back more than three decades. In 1967, Lacy's group described a novel collagenase-based method (later modified by Dr. Camillo Ricordi, then working with Dr. Lacy) to isolate islets, paving the way for future in vitro and in vivo islet experiments  [9] . Subsequent studies showed that transplanted islets could reverse diabetes in both rodents and non-human primates [ 10 , 11 ] ( Figure 1 ). In a summary of the 1977 Workshop on Pancreatic Islet Cell Transplantation in Diabetes, Lacy commented on the feasibility of “islet cell transplantation as a therapeutic approach [for] the possible prevention of the complications of diabetes in man”  [12] . Improvements in isolation techniques and immunosuppressive regimens ushered in the first human islet transplantation clinical trails in the mid-1980s. Yet despite continued procedural improvements, only about 10% of islet recipients in the late 1990s achieved euglycemia (normal blood glucose). In 2000, Dr. James Shapiro and colleagues published a report describing seven consecutive patients who achieved euglycemia following islet transplantation using a steroid-free protocol and large numbers of donor islets, since referred to as the Edmonton protocol  [13] . This protocol has been adapted by islet transplant centers around the world and has greatly increased islet transplant success. Figure 1 Central Concepts Underlying Islet Transplantation The main idea of islet transplantation is to process the organ donor's pancreas so as to remove the 95% of the gland responsible for its exocrine functions (secretion of digestive enzymes) and isolate the 5% of the gland responsible for the endocrine hormone secretion— the so-called pancreatic islets. Once isolated, the medical team can infuse the insulin-producing islets through a thin tube, placed in the main vein that transports blood from the intestines to the liver. Once infused, the islets are transported by the bloodstream into the liver, where they lodge, take up residence, and begin making the right amount of insulin to regulate the blood sugar. (Illustration: Giovanni Maki)
History of Islet Transplantation
Islet transplantation has recently received considerable interest as a potentially definitive treatment for diabetes. The concept of islet transplantation is not new—investigators as early as the English surgeon Charles Pybus (1882–1975) attempted to graft pancreatic tissue to cure diabetes. Most, however, credit the recent era of islet transplantation research to Paul Lacy's studies dating back more than three decades. In 1967, Lacy's group described a novel collagenase-based method (later modified by Dr. Camillo Ricordi, then working with Dr. Lacy) to isolate islets, paving the way for future in vitro and in vivo islet experiments  [9] . Subsequent studies showed that transplanted islets could reverse diabetes in both rodents and non-human primates [ 10 , 11 ] ( Figure 1 ). In a summary of the 1977 Workshop on Pancreatic Islet Cell Transplantation in Diabetes, Lacy commented on the feasibility of “islet cell transplantation as a therapeutic approach [for] the possible prevention of the complications of diabetes in man”  [12] . Improvements in isolation techniques and immunosuppressive regimens ushered in the first human islet transplantation clinical trails in the mid-1980s. Yet despite continued procedural improvements, only about 10% of islet recipients in the late 1990s achieved euglycemia (normal blood glucose). In 2000, Dr. James Shapiro and colleagues published a report describing seven consecutive patients who achieved euglycemia following islet transplantation using a steroid-free protocol and large numbers of donor islets, since referred to as the Edmonton protocol  [13] . This protocol has been adapted by islet transplant centers around the world and has greatly increased islet transplant success.Current Limitations of Islet Transplantation While significant progress has been made in the islet transplantation field  [14] , many obstacles remain that currently preclude its widespread application. Two of the most important limitations are the currently inadequate means for preventing islet rejection, and the limited supply of islets for transplantation. Current immunosuppressive regimens are capable of preventing islet failure for months to years, but the agents used in these treatments are expensive and may increase the risk for specific malignancies and opportunistic infections. In addition, and somewhat ironically, the most commonly used agents (like steroids, calcineurin inhibitors, and rapamycin) are also known to impair normal islet function and/or insulin action. Further, like all medications, the agents have other associated toxicities, with side effects such as oral ulcers, peripheral edema, anemia, weight loss, hypertension, hyperlipidemia, diarrhea, and fatigue  [15] . Perhaps of greatest concern to the patient and physician is the harmful effect of certain widely employed immunosuppressive agents on renal function. For the patient with diabetes, renal function is a crucial factor in determining long-term outcome, and calcineurin inhibitors (tacrolimus and cyclosporin) are significantly nephrotoxic. Thus, while some patients with a pancreas transplant tolerate the immunosuppressive agents well, and for such patients diabetic nephropathy can gradually improve, in other patients the net effect (decreased risk due to the improved blood glucose control, increased risk from the immunosuppressive agents) may worsen kidney function. Indeed, Ojo et al. have published an analysis indicating that among patients receiving other-than-kidney allografts, 7%–21% end up with renal failure as a result of the transplant and/or subsequent immunosuppression  [16] . Looked at another way, patients with heart, liver, lung, or kidney failure have a dismal prognosis for survival, so the toxicity associated with immunosuppression is warranted (the benefits of graft survival outweigh the risks associated with the medications). But for the subset of patients with diabetes and preserved kidney function, even those with long-standing and difficult-to-control disease, the prognosis for survival is comparatively much better. In addition to the immunosuppressive toxicities, other risks are associated with the islet transplant procedure itself, including intra-abdominal hemorrhage following the transplant, and portal vein thromboses. The fact that there is already a good alternative to islet transplantation (i.e., the modern intensive insulin regimen) forces us to regard any newer, riskier interventions with a critical eye. Like all transplantation therapies, islet transplantation is also handicapped by the limited donor pool. The numbers are striking; at least 1 million Americans have T1DM, and only a few thousand donor pancreata are available each year. To circumvent this organ shortage problem, researchers continue to look for ways to grow islets—or at least cells capable of physiologically regulated insulin secretion—in vitro, but currently only islets from cadaveric donors can be used to restore euglycemia. Further exacerbating the problem (and unlike kidney, liver, and heart transplants, where only one donor is needed for each recipient) most islet transplant patients require islets from two or more donors to achieve euglycemia. Lastly, the current methods for islet isolation need improvement, since only about half of attempted isolations produce transplant-ready islets. While islet transplantation research has made important progress and the success stories are encouraging, the long-term safety and efficacy of the procedure remain unclear. Other concerns relating to the field include questions about the impact of having insulin-producing foreign cells within the hepatic parenchyma, the long-term consequences of elevated portal pressures resulting from the islet infusion, and the fact that islet recipients can be sensitized against donor tissue types, making it more difficult to find a suitable donor should another life-saving transplant be required in the future. Also, very few islet transplant recipients have remained euglycemic without the use of any exogenous insulin beyond four years post-transplant. Thus, while most islet recipients achieve better glycemia control and suffer less serious hypoglycemia, islet transplantation continues to fall short of the definitive diabetes cure.
Current Limitations of Islet Transplantation
While significant progress has been made in the islet transplantation field  [14] , many obstacles remain that currently preclude its widespread application. Two of the most important limitations are the currently inadequate means for preventing islet rejection, and the limited supply of islets for transplantation. Current immunosuppressive regimens are capable of preventing islet failure for months to years, but the agents used in these treatments are expensive and may increase the risk for specific malignancies and opportunistic infections. In addition, and somewhat ironically, the most commonly used agents (like steroids, calcineurin inhibitors, and rapamycin) are also known to impair normal islet function and/or insulin action. Further, like all medications, the agents have other associated toxicities, with side effects such as oral ulcers, peripheral edema, anemia, weight loss, hypertension, hyperlipidemia, diarrhea, and fatigue  [15] . Perhaps of greatest concern to the patient and physician is the harmful effect of certain widely employed immunosuppressive agents on renal function. For the patient with diabetes, renal function is a crucial factor in determining long-term outcome, and calcineurin inhibitors (tacrolimus and cyclosporin) are significantly nephrotoxic. Thus, while some patients with a pancreas transplant tolerate the immunosuppressive agents well, and for such patients diabetic nephropathy can gradually improve, in other patients the net effect (decreased risk due to the improved blood glucose control, increased risk from the immunosuppressive agents) may worsen kidney function. Indeed, Ojo et al. have published an analysis indicating that among patients receiving other-than-kidney allografts, 7%–21% end up with renal failure as a result of the transplant and/or subsequent immunosuppression  [16] .Looked at another way, patients with heart, liver, lung, or kidney failure have a dismal prognosis for survival, so the toxicity associated with immunosuppression is warranted (the benefits of graft survival outweigh the risks associated with the medications). But for the subset of patients with diabetes and preserved kidney function, even those with long-standing and difficult-to-control disease, the prognosis for survival is comparatively much better. In addition to the immunosuppressive toxicities, other risks are associated with the islet transplant procedure itself, including intra-abdominal hemorrhage following the transplant, and portal vein thromboses. The fact that there is already a good alternative to islet transplantation (i.e., the modern intensive insulin regimen) forces us to regard any newer, riskier interventions with a critical eye.Like all transplantation therapies, islet transplantation is also handicapped by the limited donor pool. The numbers are striking; at least 1 million Americans have T1DM, and only a few thousand donor pancreata are available each year. To circumvent this organ shortage problem, researchers continue to look for ways to grow islets—or at least cells capable of physiologically regulated insulin secretion—in vitro, but currently only islets from cadaveric donors can be used to restore euglycemia. Further exacerbating the problem (and unlike kidney, liver, and heart transplants, where only one donor is needed for each recipient) most islet transplant patients require islets from two or more donors to achieve euglycemia. Lastly, the current methods for islet isolation need improvement, since only about half of attempted isolations produce transplant-ready islets.While islet transplantation research has made important progress and the success stories are encouraging, the long-term safety and efficacy of the procedure remain unclear. Other concerns relating to the field include questions about the impact of having insulin-producing foreign cells within the hepatic parenchyma, the long-term consequences of elevated portal pressures resulting from the islet infusion, and the fact that islet recipients can be sensitized against donor tissue types, making it more difficult to find a suitable donor should another life-saving transplant be required in the future. Also, very few islet transplant recipients have remained euglycemic without the use of any exogenous insulin beyond four years post-transplant. Thus, while most islet recipients achieve better glycemia control and suffer less serious hypoglycemia, islet transplantation continues to fall short of the definitive diabetes cure.Is Islet Transplantation Ready for Widespread Use? While no one suggests that the therapy is ready for widespread clinical application, another way of highlighting current problems is to focus on cost. Assuming present hurdles were cleared, islet transplantation costs approximately $150,000 per patient per transplant. With over 1 million Americans dealing with T1DM, it would cost over $100 billion to give each patient a single islet transplant, with little assurance as yet of any long-term benefit. In contrast, the annual direct cost of a proven therapy like intensive insulin treatment is about $3,500 per patient  [17] . The limitations of islet transplantation force us to recognize that the therapy remains experimental, and that many questions must be answered before it is incorporated into general clinical practice. At the present time, we urge a focus on the selection of only those patients for whom this procedure offers the greatest likelihood of benefit. Most people with diabetes can, with diligence and perseverance, implement an insulin regimen that maintains tight glucose control while avoiding dangerous hypoglycemia. However, there are some patients who continue to have tremendous difficulty managing their disease despite optimal care and effort. Even the statement “despite optimal care and effort” is difficult to define, and we advocate that all patients being considered for an islet transplant first be referred for several months to specialty teams that are committed to diabetes care. Since such patients whose diabetes is the most difficult to control have a poor quality of life, islet transplantation offers potential benefit. Even a low baseline level of insulin production by the transplanted islets may lower the amount of insulin required, while reducing the number and severity of hypoglycemic events. We also believe the islet transplant risk-benefit ratio is favorable for those with both T1DM and kidney failure who are listed for a life-preserving kidney transplant; such patients will have to take immunosuppressive agents after transplant to preserve the kidney allograft function, so the islets can be added without too much additional risk. Where do we go from here? Just as early studies showed islet transplantation's promise, research must now overcome the hurdles revealed by the recent islet transplant experience. New immunomodulatory agents offer the greatest hope of revolutionizing the field. New drug regimens capable of inducing tolerance to the transplanted islets would allow recipients to maintain their grafts without general immunosuppression and its associated toxicities. While many targets are currently under investigation, none are ready for clinical use. We advocate that such immunomodulatory approaches be tested first in controlled models where the results can be appropriately attributed to the agent itself.
Is Islet Transplantation Ready for Widespread Use?
While no one suggests that the therapy is ready for widespread clinical application, another way of highlighting current problems is to focus on cost. Assuming present hurdles were cleared, islet transplantation costs approximately $150,000 per patient per transplant. With over 1 million Americans dealing with T1DM, it would cost over $100 billion to give each patient a single islet transplant, with little assurance as yet of any long-term benefit. In contrast, the annual direct cost of a proven therapy like intensive insulin treatment is about $3,500 per patient  [17] .The limitations of islet transplantation force us to recognize that the therapy remains experimental, and that many questions must be answered before it is incorporated into general clinical practice. At the present time, we urge a focus on the selection of only those patients for whom this procedure offers the greatest likelihood of benefit. Most people with diabetes can, with diligence and perseverance, implement an insulin regimen that maintains tight glucose control while avoiding dangerous hypoglycemia. However, there are some patients who continue to have tremendous difficulty managing their disease despite optimal care and effort. Even the statement “despite optimal care and effort” is difficult to define, and we advocate that all patients being considered for an islet transplant first be referred for several months to specialty teams that are committed to diabetes care. Since such patients whose diabetes is the most difficult to control have a poor quality of life, islet transplantation offers potential benefit. Even a low baseline level of insulin production by the transplanted islets may lower the amount of insulin required, while reducing the number and severity of hypoglycemic events. We also believe the islet transplant risk-benefit ratio is favorable for those with both T1DM and kidney failure who are listed for a life-preserving kidney transplant; such patients will have to take immunosuppressive agents after transplant to preserve the kidney allograft function, so the islets can be added without too much additional risk.Where do we go from here? Just as early studies showed islet transplantation's promise, research must now overcome the hurdles revealed by the recent islet transplant experience. New immunomodulatory agents offer the greatest hope of revolutionizing the field. New drug regimens capable of inducing tolerance to the transplanted islets would allow recipients to maintain their grafts without general immunosuppression and its associated toxicities. While many targets are currently under investigation, none are ready for clinical use. We advocate that such immunomodulatory approaches be tested first in controlled models where the results can be appropriately attributed to the agent itself.Conclusion Less than a century ago, T1DM was invariably a fatal disease. With the advent of insulin, the prognosis changed overnight, and we have continued to witness improvements in diabetes care and outcomes. Pancreatic islet transplant has offered renewed hope to many patients with diabetes, who envision a life free of glucose checks and insulin injections. Some transplanted patients have enjoyed “success” and are pleased with their decisions; unfortunately these results are not universal. Researchers must continue to look for ways to improve the procedure while protecting the welfare of each individual patient. The field has come a long way, but we must remain cautious, as we are treating a non-fatal disease for which there is a very effective standard therapy.
Conclusion
Less than a century ago, T1DM was invariably a fatal disease. With the advent of insulin, the prognosis changed overnight, and we have continued to witness improvements in diabetes care and outcomes. Pancreatic islet transplant has offered renewed hope to many patients with diabetes, who envision a life free of glucose checks and insulin injections. Some transplanted patients have enjoyed “success” and are pleased with their decisions; unfortunately these results are not universal. Researchers must continue to look for ways to improve the procedure while protecting the welfare of each individual patient. The field has come a long way, but we must remain cautious, as we are treating a non-fatal disease for which there is a very effective standard therapy.