Characterization of Promoter Activities of Four Different Japanese Flounder Promoters in Transgenic Zebrafish

An important consideration in transgenic research is the choice of promoter for regulating the expression of a foreign gene. In this study several tissue-specific and inducible promoters derived from Japanese flounder Paralichthys olivaceus were identified, and their promoter activity was examined in transgenic zebrafish. The 5′ flanking regions of the Japanese flounder complement component C3, gelatinase B, keratin, and tumor necrosis factor (TNF) genes were linked to green fluorescence protein (GFP) as a reporter gene. The promoter regulatory constructs were introduced into fertilized zebrafish eggs. As a result we obtained several stable transgenic zebrafish that displayed green fluorescence in different tissues. Complement component C3 promoter regulated GFP expression in liver, and gelatinase B promoter regulated it in the pectoral fin and gills. Keratin promoter regulated GFP expression in skin and liver. TNF gene promoter regulated GFP expression in the pharynx and heart. TNF promoter had lipoplysaccharide-inducible activity, such that when transgenic embryos were immersed lipopolysaccharide, GFP expression increased in the epithelial tissues. These 4 promoters regulated the expression of GFP in different patterns in transgenic zebrafish.
Introduction
Transgenic technology is a powerful tool not only for analyzing molecular biological functions but also for obtaining commercially important traits for aquaculture. In the last decade fish transgenesis has become common and has progressed considerably (Chen et al., 1996; Hackett and Alvarez, 2000). Various transgenic fish that possess commercially important traits, such as growth enhancement (Zhang et al., 1990) or disease resistance (Sarmasik et al., 2002), have been generated. One of the most critical factors in transgenic research is the regulation of foreign gene expression. Early fish transgenic research was conducted using housekeeping gene promoters such as β-actin (Liu et al., 1990; Higashijima et al., 1997; Hwang et al., 2003; Noh et al., 2003) and elongation factor (EF) (Gao et al., 1997; Kinoshita et al., 2000). These promoters resulted in excess expression in various tissues. However, tissue-specific or inducible promoters are needed to regulate foreign genes in different situations. The activities of tissue-specific promoters were assessed in zebrafish using green fluorescence protein (GFP) as a reporter gene (Udvadia and Linney, 2003). This technique has provided a powerful tool for analyzing the regulation of gene expression in living fish. The pattern of expression of GFP in these transgenic zebrafish was the same as that of the gene from which the promoter was derived. However, promoters derived from most marine aquaculture species have not been described. To generate transgenic aquaculture fish, tissue-specific and stress-inducible promoters from these species need to be identified.
Japanese flounder Paralichthys olivaceus is widely cultured and one of the most important food fish in East Asia. Because this industry is seriously affected by disease, the development of disease-resistant strains is a high priority. Previous studies by our laboratory have used expressed sequence tags (ESTs) (Aoki et al., 1999, 2000; Nam et al., 2000, 2003) and molecular genetic analyses, especially of immune-related genes in Japanese flounder (Hirono et al., 2003). In these reports we focused on cDNA clones that displayed tissue-specific expression or inducible expression, and 4 Japanese flounder genes were chosen for this study: complement component C3, gelatinase B, keratin, and tumor necrosis factor (TNF) genes. These genes were chosen because they were revealed to be expressed in specific tissues of Japanese flounder by EST analysis. We assumed that the promoter region of these genes would show tissue-specific or inducible activities.
It is possible to generate an effective transgenic fish using tissue-specific or inducible promoters. Indeed, such promoters can regulate foreign gene expression faithfully. In contrast, use of a housekeeping gene promoter would result in nonspecific expression (i.e., overexpression) of foreign genes that may be harmful to the host fish. In this study we developed several Japanese flounder promoters that showed tissue-specific or inducible gene expression with the aim of using these in Japanese flounder. Although we have succeeded in introducing a foreign gene into Japanese flounder fertilized eggs and shown transient expression in Japanese flounder embryos, it has been difficult to conduct promoter assays in vivo because the technology has not been sufficiently developed to produce transgenic Japanese flounder with the necessary efficiency. However, the transgenic zebrafish model system has the advantages of shorter generation time, better optical transparency, and easier treatment schemes when compared with Japanese flounder. In this study, promoter regions of the complement component C3, gelatinase B, keratin and TNF genes were isolated and their promoter activities were characterized in transgenic zebrafish.
Materials and Methods
mRNA Expression in Japanese Flounder Tissues
Total RNA was extracted from spleen, fin, liver, head kidney, post kidney, skin, blood, heart, intestine, ovary, gill, leukocyte, and peripheral blood leukocytes (PBLs) stimulated with lipopolysaccharide (LPS) using TRIzol (Invitrogen). The purified total RNA (10 μg) was reverse transcribed into cDNA using an avian myeloblastosis virus (AMV) transcriptase First-strand cDNA synthesis kit (Amersham Bioscience). The reverse-transcribed sample (1 μl) was used in 50 μl of PCR mixture. The PCR primers for Japanese flounder complement component C3 mRNA detection were (sense) 5′-GCTGGAGAAAG TCGTCTTGG-3′ and (anti) 5′-GGATACCTCTCAACTCTG CC-3′, gelatinase B mRNA detection, (sense) 5′-GCA GGAGCCACCAGTCAAAA-3′ and (anti) 5′-GGTCCAGTG TTCATCATCGT-3′, keratin mRNA detection, (sense) 5′-ACTCCGTCGCACAATGCAGA-3′ and (anti) 5′-CTGCA ATTTCCATCTCCAGC-3′, and TNF mRNA detection, (sense) 5′-CCCTATGAACTGTAACAGTTTG-3′ and (anti) 5′-GTCAGGTACTTAACCCTCAT-3′. The ß-actin primer set for an internal control was (sense) 5′-TTTCCCT CCATTGTTGGTCG-3′ and (anti) 5′-GCGACTCTCAGCTC GTTGTA-3′. The PCR was performed with an initial denaturation step of 2 minutes at 95°C and then 20 cycles were run as follows: 30 seconds of denaturation at 95°C, 30 seconds of annealing at 55°C, and 1 minute of extension at 72°C. The reaction products were electrophoresed in a 2.0% agarose gel.
Identification of 5′ Flanking Region Sequences
The 5′ flanking regions of 4 genes were isolated from a Japanese flounder genomic BAC library (Katagiri et al., 2000) using cDNA clones of complement component C3 (AB021653), gelatinase B (AU091035), keratin (AB079729), and TNF (AB040448), as probes for gene screening. To determine the transcription start site, the primer extention method was performed according to a modified version of that in Hikima et al. (2001). A 20mer synthetic oligonucleotide corresponding to the complementary sequence of the first exon was labeled with fluorochrome. The fluorochrome-labeled primer was hybridized to 10 μg of kidney total RNA (extracted using Trizol, Invitrogen) and then extended using an AMV reverse transcriptase first-strand cDNA synthesis kit (Amersham Bioscience). Subcloned plasmid DNA, containing the first exon of each gene, was adopted as a template for the sequencing using the same fluorochrome-labeled primer. The sequence products were analyzed with primer-extended cDNA fragment by the cycle sequencing method.
Construction of Promoter-EGFP Plasmid
The reporter gene vector pEGFP-1 (Clontech) was used for the construct. Four different Japanese flounder promoters including 5′ untranslated region (UTR) were amplified by specific PCR primers and inserted into the multiple cloning site of pEGFP-1. GFP reporter gene was the endogenous initiation codon directly replaced with that of GFP. To confirm the sequence and direction of insert, the recombinant plasmid was sequenced using a Thermo Sequenase II kit and automated DNA sequencer 373A with a primer designed for pEGFP-1.
Production of Transgenic Zebrafish
Adult zebrafish (Danio rerio) and embryos were maintained at 28.5°C on a 14-hour light and 10-hour dark cycle. The recombinant plasmid was propagated in Escherichia coli JM109 and purified using a GFX Micro Plasmid prep kit (Amersham Biosciences). Purified plasmid DNA was adjusted to 50 ng/μl in distilled water and microinjected into one-celle-stage zebrafish embryos. Initially 400 to 500 embryos were injected with plasmid DNA in each promoter-GFP construct. Living embryos were examined under an SZX12 fluorescence microscope (Olympus), and GFP-positive zebrafish embryos were selected. After maturation the GFP-positive fish were mated with wild types to select fish for germline transmission. GFP expression in F1 embryos was also examined under the fluorescence microscope in each developmental stage.
LPS Treatment of TNF-GFP Transgenic Zebrafish Embryo
F2 generations of transgenic zebrafish injected with TNF-GFP at 30 hours postfertilization (hpf) were stimulated with LPS (Sigma) at 140 μg/ml for 30 minutes and then washed in sterilized water. GFP expression in F2 embryos was examined under the fluorescence microscope at 48 hpf.
Detection of GFP Gene Expression in Adult Transgenic Zebrafish by RT-PCR
Total RNA extraction and PCR was performed as described above. Total RNA was extracted from fin, skin, liver, kidney, muscle, and brain of adult transgenic zebrafish. The following PCR primers were designed for the detection of EGFP gene: GFP-F, 5′-GGTCG AGCTGGACGGCGACG-3′, and GFP-R, 5′-ACGAACTCC AGCAGGACCAT-3′. The zebrafish ß-actin primer set for internal control was zactin-F, 5′-TTTCCCTCCATT GTTGGTCG-3′, and zactin-R, 5′-GCGACTCTCAGCTCG TTGTA-3′.
Results and Discussion
The expression of complement component C3, gelatinase B, keratin, TNF and β-actin genes in Japanese flounder was detected by reverse transcriptase polymerase chain reaction (RT-PCR). The complement component C3 gene was expressed only in the liver. The gelatinase B gene was expressed in the kidney, blood, and leukocytes. The keratin gene was expressed in various tissues. The TNF gene was expressed only in PBLs when stimulated with LPS. The β-actin gene used as an internal control was expressed in all tissues (Figure 1). Thus the expression patterns of these genes were different in different Japanese flounder tissues. We assumed that the tissue-specific and inducible expression of these genes was regulated by their promoter region.Fig. 1.Expression of Japanese flounder tissue-specific genes in different tissues. Messenger RNA expression of complement component C3, gelatinase B, keratin, and TNF genes in spleen, fin, liver, head kidney, post kidney, skin, blood, heart, intestine, ovary, gills, leukocyte, and PBLs stimulated with LPS from Japanese flounder were detected by RT-PCR.
The 5′ flanking regions of the genes for complement component C3 (1381 bp), gelatinase B (1420 bp), keratin (1288 bp), and TNF (2351 bp) were isolated, and the respective transcriptional initiation sites were determined (Figure 2). There were some predicted transcriptional factor binding sites, such as TATA box, CAAT box or NF-κB binding site, in the 5′ flanking region. These sites were highly homologous with mammalian transcriptional factor binding sites. It is not certain that these predicted transcriptional factor binding sites can be applied to Japanese flounder promoters as there are few reports on fish transcriptional factor binding protein. It should be interesting to determine if these transcriptional factor binding sites are common to mammal and fish. These promoter regions were cloned into pEGFP-1 plasmid vector. These promoter regulatory constructs were designated C3-GFP, gelatinase-GFP, keratin-GFP, and TNF-GFP, respectively.Fig. 2.The 5′ flanking region sequence of the Japanese flounder gene: complement component C3 (A); gelatinase B (B); keratin (C); and TNF gene (D). We isolated 1381 bp of the 5′ flanking regions from transcription initiation codon for complement component C3; 1420 bp for gelatinase B; 1288 bp for keratin; and 2351 bp for TNF. The first exon is indicated in capital letters. The coding region and deduced amino acids are indicated in boldface capital letters. The transcription initiation site is shown by an asterisk. The predictive transcriptional factor binding site is underlined.
We obtained F1 transgenic individuals using each promoter regulatory constructs. An F2 strain was established with the C3-GFP, gelatinase-GFP, and keratin-GFP construcst, and two F2 strains from two different founders were established with the TNF-GFP construct. Similar GFP expression patterns were shown in F1 individuals and their F2 strains. GFP expression controlled by the complement component C3 promoter was observed in the yolk sac from the gastrula stage, in F2 transgenic zebrafish strains. In 10-day embryos strong GFP expression was observed only in the liver (Figure 3). GFP expression could not be observed in adults. The RT-PCR analysis showed that complement component C3 promoter also induced GFP expression in the adult liver (see Figure 7). Fish complement component C3 gene has the same function as the mammalian gene, and is expressed mainly in the liver (Abelseth et al., 2003). Japanese flounder complement component C3 was also expressed mainly in the liver (Figure 1). This was similar to the promoter activity observed in transgenic zebrafish. This suggests that Japanese flounder complement component C3 promoter could also induce expression of genes in the same tissues in zebrafish.Fig. 3.GFP expression in C3-GFP transgenic zebrafish embryos. The larval embryos at 24 hpf (A) and liver of the 10-day embryos (B) of F2 transgenic strain. Arrowheads indicate bladder and eye.
GFP expression regulated by the gelatinase B promoter was observed after the one-cell stage, and was expressed strongly in the whole body until 48 hpf. However, GFP expression in the whole body decreased in the course of development. In 5-day embryos, strong GFP expression was detected only in the pectoral fins and gills (Figure 4). In adult transgenic fish gelatinase B promoter regulated GFP expression in the fin (see Figure 7). This result agrees with the GFP expression at embryonic stage. The GFP expression under the control of the Japanese flounder gelatinase B gene promoter in the transgenic zebrafish was not identical with the expression of the gelatinase B gene in Japanese flounder, in which it was expressed mainly in hematopoietic tissues (Figure 1). This promoter may lack a region essential for tissue-specific expression.Fig. 4.GFP expression of gelatinase B-GFP transgenic zebrafish. GFP expression at one-cell stage (A), 7 hpf (B), 12 hpf (C), 48 hpf (D), and 5-day embryo, lateral view (E) and dorsal view (F).
The keratin promoter regulated strong GFP expression from the embryo stage to the adult stage. In the embryo strong GFP expression was observed in the epithelial tissues and liver. In adult fish GFP expression was detected in skin, gills, fins, and liver (Figure 5). This expression pattern was similar to that of the Japanese flounder keratin gene (Figure 1). The zebrafish keratin 8 promoter was found to induce expression only in the skin (Gong et al., 2002). These results indicate that the promoter of the Japanese flounder keratin gene induces gene expression in the same tissues in zebrafish as in Japanese flounder. However, the sequences of the keratin promoter region of zebrafish and Japanese flounder are not the same (data not shown). This may be because some transcription factors that enhance skin-specific expression in zebrafish can bind and enhance the promoter activity of keratin promoter derived from Japanese flounder in transgenic zebrafish embryo.Fig. 5.GFP expression in keratin-GFP F2 transgenic zebrafish under the fluorescence microscope. A: The 4-day embryo. B: Adult fish. C: Adult fish with operculum removed and abdominal muscle surgically opened. Arrowheads indicate gill and liver.
The TNF promoter regulated GFP expression only in the heart and pharynx in 5-day embryos. GFP expression was strongly induced in the epithelial tissues in 2-day transgenic embryos after LPS treatment (Figure 6). GFP expression was not detected in adult transgnic zebrafish by RT-PCR. This result suggested that TNF promoter controlled GFP expression in transgenic zebrafish under normal conditions (Figure 7). The Japanese flounder TNF promoter has inducible activity in zebrafish similar to that of Japanese flounder TNF gene expression in LPS-stimulated PBLs (Hirono et al., 2000). These results suggest that the Japanese flounder TNF promoter used in this study is sufficient to regulate the expression of a downstream gene.Fig. 6.GFP expression in TNF-GFP transgenic zebrafish under the fluorescence microscope. A: The 5-day embryo of wild type. B: F2 transgenic strain, 5-day embryo. Arrowheads indicate heart and pharynx. C: Nontreated 3-day transgenic zebrafish embryo. D: LPS-treated 3-day transgenic zebrafish embryo.Fig. 7.Detection of mRNA expression of GFP gene in fin, skin, liver, kidney, muscle, and brain from adult transgenic zebrafish by RT-PCR. GFP expression regulated by TNF promoter was not detected. N.C. indicates negative control.
In this study we showed that heterologous promoters derived from Japanese flounder worked in transgenic zebrafish. However, the expression patterns different from endogenous Japanese flounder expression patterns. Notably, the keratin and TNF promoters seemed to work faithfully in zebrafish embryos, but the gelatinase B promoter result differed from the results predicted from Japanese flounder. This may have been due to the short 5′ flanking region used in this study. Furthermore, we only observed the GFP expression pattern in a single transgenic line. Whether this GFP expression pattern is representative of gelatinase B promoter activity needs to confirmed in future studies by establishing multiple transgenic lines. Similarly, the fate of these promoters in Japanese flounder needs to be determined by production of transgenic lines of Japanese flounder.
The Japanese flounder promoters developed in this study can be adapted for transgenic fish in a variety of situations. Keratin promoter induced expression in epithelial tissues, where it acts as a first line of defense against bacterial infection. It is possible to generate disease-resistant transgenic fish expressing an antibacterial or antiviral peptide only in epithelial tissues. Moreover, using the Japanese flounder TNF promoter, it is possible to generate transgenic fish expressing an antibacterial or antiviral peptide only in cases of infection with pathogens. Thus these promoters should be useful for production of disease-resistant transgenic fish. The overexpression of a foreign gene, especially the gene for an antimicrobial peptide, may suppress growth or maturity of the host fish. In addition, these transgenic fish are safe for human consumption, as the foreign gene is not expressed in the muscle. The Japanese flounder TNF gene promoter can also be used to monitor bacterial infection in live fish using GFP as an indicator. Furthermore, these transgenic zebrafish were suitable for developmental analysis of specific tissues or organs. It is possible to observe development of liver, gills, and skin in living embryos using GFP expression.
We also developed a method for introducing a gene into Japanese flounder fertilized eggs by particle gun bombardment (Yazawa et al., 2005). The development of tissue-specific, inducible promoters in this study will support the establishment of transgenic technology for Japanese flounder and should contribute to a better understanding of the biology and culture of this fish species.

japanese flounder
transgenic zebrafish
inducible promoter
green fluorescence protein (gfp)
tissue-specific promoter


An overview of prognostic factors for long-term survivors of breast cancer

Background Numerous studies have examined prognostic factors for survival of breast cancer patients, but relatively few have dealt specifically with 10+-year survivors.
Introduction
Breast cancer (BC) is the most common cancer among women, with a lifetime risk of up to 12% and a risk of death of up to 5% [1]. Its incidence has been increasing but after a period of continuous rise in many industrialized countries BC mortality has been stable or has even decreased in the last 10–15 years [2, 3]. The introduction of mass mammographic screening programmes also resulted in earlier detection and diagnosis of small and less aggressive tumours. This, in combination with therapeutic improvements, has led to a substantial increase in BC survivors over the last few decades (Fig. 1). A long-term survivor is commonly defined as a person who is still alive 5 years after cancer diagnosis [4]. For BC, the relative survival at 5 and 10 years after diagnosis is 88% and 77%, respectively, both substantially higher than the 5-year relative survival of all cancers together (64%) [4]. Thus, it seems logical to consider factors known to play an important role in predicting 5-year survival of BC patients and to question their importance in survival 10 years after diagnosis and even longer. Furthermore, in recent years major advances in the prognostic value of several molecular markers have been achieved, hence the need to incorporate this data into our current knowledge. Therefore, we have summarized available knowledge on the determinants of survival 10 years or more after breast cancer diagnosis. We supported our analyses and considerations with data from the population-based, long-standing Eindhoven cancer registry in the Netherlands.Fig. 1Proportion of breast cancer patients (3-year moving average) diagnosed between 1973 and 1993 who survived 10 years or longer in Southeastern Netherlands
Methods
We initially searched PubMed, using the search MESH term for ‘breast neoplasms’ AND ‘prognoses’ AND ‘long-term’. Only papers published in English between 1995 and 2006 (September) which researched female adults (19+ years) were included. We retrieved 528 articles and studied the abstracts (sometimes also the methods section). We selected only articles that assess or show the results for those surviving 10 years or longer with cohorts having a mean/median follow-up of 10 years or longer. If mean/median follow-up time was not reported, we examined the proportion of patients who survived 10 years after diagnosis, and this ought to be larger than 50%. If, for a specific topic of interest, no relevant studies with a follow-up of at least 10 years were found (such as BRCA mutation or gene profiling, which have been studied only during the last decade), then studies with the longest available follow-up were chosen. Furthermore, the following inclusion criteria were used: overall and/or BC-specific survival was reported; relative risk or hazard rate and statistical probability values were given; at least 250 BC patients included at the beginning of study. We also searched the reference lists collected by this search strategy and selected those that were relevant to both our study question and inclusion criteria. Reviews and books that gave general overviews were also included in the reference list.
We present data from the Eindhoven Cancer Registry (ECR) to illustrate the role of factors such as age, tumour size, lymph node involvement and time since diagnosis. Within the Netherlands, ECR is unique because it has collected follow-up data since 1970, including clinical aspects of cancer patients. This is a population-based cancer registry covering a population of almost 2.4 million people in 2004 [5]. Cumulative survival proportion was calculated using the Kaplan Meier method. Relative survival was calculated by comparing the survival of BC patients to the general population.
Throughout the text the term long-term and/or survival will frequently be mentioned; this corresponds to at least 10-year survival unless otherwise indicated.
Results and discussions
Determinants of survival BC 10 years or longer
Patient characteristics
Age at diagnosis
Very young women, i.e. younger than 30/35 years [6, 7], exhibited a particularly poor survival as do those older than 70 (Fig. 2) [8, 9]. Young BC patients were more likely to have a more negative clinical presentation, such as affected lymph nodes, negative for oestrogen receptors, and have large tumour with a high fraction of p53 nuclei and overexpression of c-erb-2 oncoprotein [6, 10, 11]. However, current adjuvant treatment seems to diminish the poor prognostic value of young age [6]; young women who did not receive adjuvant treatment had a significantly increased risk of dying; those diagnosed at 35–39 years and <35 years had a 1.4 and 2.2 higher risk of death, respectively, compared to those of 45–49 years [6]. Older patients exhibited higher mortality rates [12], probably because of less extensive treatment (either related to advanced age itself or the presence of serious concomitant diseases (comorbidity)) [13].Fig. 2Relative survival of breast cancer patients (n: 13,279) diagnosed in 1990–2002 and followed until 2004, according to age at diagnosis in southeastern Netherlands
Comorbidity
Concurrent health conditions (comorbidity) at the time of BC diagnosis have a significant impact on early [13] as well as long-term survival of BC patients [12]. The most prevalent conditions were cardiovascular disease (7%), previous cancer (7%) and diabetes mellitus (6%), all becoming more common with increasing age [13]. Compared to those without comorbidity whose 5-year relative survival was 87%, those with diabetes mellitus or cardiovascular disease represented 78% and 83% of the respective survival estimates [13]. Patients with severe comorbidity exhibited a 2.7–3.4 higher risk of death in 10 years compared to those without comorbidity [12, 14].
Period of diagnosis
Access to care and treatment of BC has improved over time in most industrialized countries, which is reflected in the higher long-term survival of BC cases across all age groups and the tumour characteristics of those diagnosed more recently [15–18]. In Finland, relative survival 10 years after diagnosis among patients younger than 50 years increased from 49% for those diagnosed in 1953–1959 to 68% for the 1983–1989 cohort [15]. Furthermore, 60% of node-positive BC patients diagnosed in 1978–1979 in Italy survived 10 years or longer compared to the 50% probability 10-year survival for those diagnosed in 1968–1969 [17]. In addition, changes in BC diagnosis, e.g. screening[19, 20] and better staging [17], may partly be responsible for the observed increase in the proportion of survivors.
Time after diagnosis
The longer a woman survives BC the more the prognosis improves, illustrated by conditional survival [16, 21]. Probably the subgroup of patients who survived longer had less aggressive tumours due to a different genetic make-up or better life-style. In Australia, 79% of women with localized BC survived 10 years after diagnosis, yet among those still alive 5 years after diagnosis 84% had a 10-year survival [16]. The respective values for regional vs. advanced BC were 53% and 68% [16]. Unlike other cancers, relative conditional survival remained stable below 100% after 12 years of survival and decreased again after about 19 years (Fig. 3) [5]. This may be a consequence of late recurrences and metastases, second cancers or late side-effects of treatment [23].Fig. 3Conditional 5-year relative survival (calculated using period analysis [22] of breast cancer patients diagnosed in southern Netherlands in 1985–2002 and followed until 2004, according to age. (Dashed line): diagnosed at 25–49 years, (solid line): diagnosed at 50–74 years
Socioeconomic status (SES) and race
A population-based study of BC patients diagnosed in 1968–1999 in France showed a diminishing role of SES on excess mortality among women with BC over these periods [24]. Long-term follow-up studies reported that women with BC from low social classes had a 20–50% poorer survival compared to patients from higher social classes [25, 26], although others contradicted this [27]. Low SES patients were more likely to be diagnosed at a later stage, had more aggressive tumour characteristics and might have received sub-optimal treatment. However, differences in these prognostic factors did not fully explain the variation in survival according to social class [25]. This is also the case when breast cancer survival is studied according to race/ethnicity. Ten years after treatment 58% of African Americans were still alive compared to 66% of the white Americans. After adjusting for other prognostic factors, 41% excess mortality from all causes was still observed among African Americans compared to caucasians [28]. This suggests other residual factors such as lifestyle (higher body weight was observed among African Americans), comorbidity [14], genetics or variation in the delivery of treatment, which influence outcome beyond variation in tumour aggressiveness [29].
Tumour-related characteristics
Tumour size
Tumour size is one of the strongest prognostic indicators (Fig. 4) [7, 30], even after 20 years of follow-up [8, 31]. A larger tumour has been related to more positive lymph nodes [32], thus their interaction further influences the survival from BC. Nonetheless, the independence of survival by node status is shown by the lower 10-year overall survival rate found for node-negative patients with a tumour of 2–5 cm compared to those with a tumour smaller than 1 cm, 66% vs. 79%, respectively [33].Fig. 4Cumulative survival proportion of breast cancer patients diagnosed in southern Netherlands in 1970–1994 and followed until 2004, according to tumor size (based on pathological diagnosis). ■ tumor size: <2 cm (n: 3263) • tumor size: 2–5 cm (n: 3420) ▴ tumor size: >5 cm (n: 474) x tumor size: involvement of skin (n: 1133) and unknown/not applicable tumor size: 1410
Histological type
The prognostic value of histological type can be grouped into four: excellent, good, poor and very poor prognosis [34]. BC with an excellent prognosis, such as invasive cribriform, tubular [35], tubulo-lobular and mucinous [36, 37] showed >80% survival at 10 years [9]. Tubular mixed, mixed ductal with special type, atypical medullary [38] and alveolar lobular carcinoma have a good prognosis with a 60–80% 10-year survival. Those with invasive papillary, classic lobular and medullary cancers have a worse prognosis. Finally, 10-year survival among those with ductal, solid lobular, mixed ductal and lobular carcinoma is below 50% [34]. In most populations infiltrating ductal carcinoma covers about 70% of all diagnoses [36, 39]. Inflammatory BC has a particularly poor prognosis: about 30% survived 10 years [40].
Histological grade
The most widely used grading systems are Scarff-Bloom-Richardson classification, Fisher grading nuclear system and Nottingham Combined Histologic Grade (NCHG) [41]. The validity of grading has been subjected to inter-observer reproducibility and subjectivity [42]. However, higher grades have been quite consistently associated with lower long-term survival [7, 8, 31, 43–45]. Depending on other prognostic factors, such as nodal status or tumour size [46, 47], cumulative survival among patients with the lowest score was 90–94% 10 years after diagnosis and 30–78% among those with the highest score [37, 48].
Regional lymph node involvement
Lymph node involvement is a valuable indicator of long-term survival (Fig. 5) [8, 32]. Node- positive patients have about a 4–8 times higher mortality than those without nodal involvement [8, 9, 49]. The more nodes involved the worse the prognosis. Prognosis for patients with 10 or more involved axillary nodes showed 70% more deaths at 10 years than for those with 1–3 involved nodes [32]. The survival of node-positive patients improved due to better staging procedures and application of systemic treatment [7, 31, 50].Fig. 5Cumulative survival proportion of breast cancer patients diagnosed in southern Netherlands in 1970–1994 and followed until 2004, according to nodal status (based on pathological diagnosis). ■ node negative (n: 4452) • node status: 1–3 positive nodes (n: 3266) ▴ node status: 4–9 positive nodes (n: 255) x node status: 10+ positive nodes (n: 189), unknown/not applicable node status: 1538
Lymphovascular invasion (LVI) and molecular markers of tumours angiogenesis
At the St. Gallen meeting in 2005, LVI was added to the prognostics for node-negative patients [51]. Compared to patients having no LVI, a 60% higher BC mortality was observed for node-negative BC patients having positive LVI [52, 53], although others did not observe the independent role of LVI [46, 50]. In this line of research, studies have also focused on the value of microvessel density [44], blood invasion (BVI) [54] and markers of angiogenesis (VEGFR (vascular endothelial growth factor receptor), CD105, Tie-2) [55, 56] in predicting long-term survival of BC patients, although the results are still conflicting.
Grouped prognostic factors
Some of the prognostic factors have been combined into a prognostic index, such as the TNM classification and also the more current Nottingham Prognostic Index (NPI), both highly predictive for estimating long-term survival [41]. TNM staging consists of information on primary tumour size, involvement of the regional lymph node and the presence of distant metastasis. Only 53% of patients with regional or locally advanced BC had survived 10 years after diagnosis compared to 79% of those with localised BC [16]. Patients with metastasis (stage: M1) at diagnosis exhibited very poor 10-year survival (3.4%) [57].Fig. 6Cumulative survival of breast cancer patients diagnosed in southern Netherlands in 1970–1994 and followed-up until 2004, according to second cancer. Follow-up for patients with second cancer begins at the date of second cancer diagnosis. ■ no second cancer (n: 8137) • second breast cancer (n: 744) ▴ second non-breast cancer (n: 819)
Tumour size, grade and lymph node status make up the NPI [11, 46, 49]. In a large series of 2879 BC patients, 10-year survival proportion was 85% for those with the lowest NPI score and 19% for those with the highest score [11].
Recurrence, metastasis and second cancer
Patients with recurrent, metastasized or second cancer generally exhibited lower long-term survival than those without [9, 21, 58–61]. Ten years after surgery, the probability for survival for another 10 years, thus 20 years after diagnosis, for node-negative patients aged ≥45 years, tumour ≤1 cm, grade 1 and without a recurrence or metastasis was 0.89. If a recurrence occurred, the probability of being alive at 20 years dropped to 0.72. If a metastasis was observed the probability of survival was only 0.18 [21]. The prognosis decreases with larger primary tumour size, nodal involvement [62], higher grade,[21] early recurrence (within 5 years of surgery)[63], location of recurrence (regional rather than local ipsilateral) [59] and inadequate primary cancer treatment [9, 64]. In the dataset of the ECR, overall survival was better for women without second primary tumours than for women who developed a new primary cancer (Fig. 6). Only 68% of early BC patients with second malignancies had survived 10 years of follow-up compared to 78% of those without multiple cancers [65]. Younger BC patients are reported to have poorer survival and a higher risk of second cancer [59]. Corrected for race and grade, women in the 20-29 year old category who had a second BC had a probability of 10-year survival probability of only 23% compared to 57% for those without multiple cancers.
Other tumour markers
Hormone receptors
The presence of hormone receptors such as oestrogen (ER) and progesterone (PR) receptors predicts the long-term outcome of hormonal therapy [66], thus they have been more commonly used as a predictive marker rather than as a prognostic marker. Thus given a particular treatment, e.g. tamoxifen, ER-positive patients have a considerably better prognosis than ER-negative patients. The prognostic value is weak [30, 43] or negligible [37], particularly in the early years after diagnosis [67].
HER-2 expression
Node-positive patients with BC cells showing amplification of the gene for human epidermal growth factor receptor type 2 (HER2), and/or overexpression of its product had a lower 10-year overall survival proportion, 50% versus 65% for those without HER2 amplification [17, 68]. After 10 years the difference in survival persisted, although it became somewhat smaller[17]. Tumours that overexpress HER2 are more likely to contain p53 abnormalities, to be hormone receptor- and bcl-2-negative and to have lymphoid infiltration and a high mitotic index, all known to be markers of poor prognosis for BC [17, 69, 70]. As for patients with node- negative tumours, HER2 did not seem to affect long-term survival significantly [17, 37, 69]. HER-2 expression has been valuable in predicting treatment responses to trastuzumab, certain endocrine therapies and chemotherapy, adding to it’s role as a predictive marker [68].
Mitotic Activity Index (MAI)
MAI is an indicator of tumour proliferative activity that represents the mitotic activity in a given area of the tumour. Combined with another prognostic factor (NCHG), MAI has proven to be an accurate tool for assessment of long-term survival [48]. In a population-based study women with node-negative tumours <5 cm and a MAI ≥10 exhibited 80% survival at 10 years compared to 90% for an MAI <10 [71].
Gene expression profile
A very promising new finding is the microarrays method, in which a set of intrinsic genes is clustered and segregated into major subgroups; BC with a good and poor prognosis profile is correlated to the probability of distant metastases [72] or a tumour with basal or luminal characteristics which are strongly associated with ER status [73]. In a study of 295 patients diagnosed with stage I or II breast cancer, those classified as having a good prognosis profile had a 95% overall 10-year survival rate compared to 55% for those with a poor profile [74]. This classification predicted outcome regardless of the nodal status, implying that more accurate criteria have become available for administering adjuvant systemic treatment.
Various molecular markers
BRCA1 & 2 mutations were first identified in 1994 and are BC risk factors for some specific groups [75]. Their role as prognostic indicator for long-term (more than 10-year) survival has not yet been established. A study of 496 women (median follow-up: 116 months), 56 of whom (11%) carried a BRCA1/BRCA2 mutation, showed worse BC-specific survival for women with BRCA1 mutations than for those without (62% at 10 years versus 86%; P < 0.0001), but not for women with the BRCA2 mutation [76]. However, another study which compared patients from BRCA1, BRCA2 and non-BRCA1/2 families as well as sporadic cases did not confirm the prognostic role of BRCA1/2 [77].
Long-term follow-up studies have not demonstrated an independent effect of p53 mutations on long-term survival. The P53 mutation was related to a poor clinical profile for patients, hence in multivariate analysis its role on survival diminished [10, 69, 78, 79].
A high level of tissue urokinase-type plasminogen activator (uPA) and its inhibitors has been correlated with poor outcome for node-negative and node-positive patients. Those having the highest level of uPA have a five times greater risk of dying from BC compared to those with the lowest level [69]. Other factors such as Ki67 (MIB-1), cathepsin-D, DNA ploidy and S-phase have been suggested as prognosticators of survival, with conflicting results, particularly among long-term survivors. Their use in general clinical settings is therefore not recommended [80, 81].
Miscellaneous
Lifestyle
Generally, increased death rates due to BC (13–20%), other causes (49–86%) and all causes (14–70%) have been observed among obese patients [82–85]. Normal body weight tended be more beneficial in death from other causes than from BC: [83, 84] 9.5% of obese patients died from non-BC causes compared to 6.4% and 5.8%, respectively, of the normal or intermediate groups [82]. Obesity was also related to a 2-fold increased risk of postmenopausal contralateral BC and a 60% higher occurrence of second other cancers [84]. Therefore, normal weight may reduce the risk of second post-menopausal BC, second other cancers and overall mortality [83, 84, 86].
Compared with women who engaged in less than 9 metabolic equivalent task (MET)-hours per week of activity, women who engaged in 9 or more MET-hours per week had a 40% lower risk of death from all causes, translating into a 6% absolute (unadjusted) reduction in mortality [87], which emphasizes the need to advise physical activity.
So far, although studies have not convincingly shown the positive influence of eating fruit, vegetables and soy bean on long-term BC survival [85, 88], diets high in fruits, vegetables, legumes, poultry, and fish and a low intake of red meat, desserts and high fat dairy products are likely to protect against mortality from non-BC causes [89].
Modification of BC’s prognostic factors
Various studies have questioned the role of BC risk factors in determining the biological tumour features as mentioned above. Indeed, BC risk factors seem to differ according to histological type, grade, size, nodal status and ER/PR receptor status [90–93]. For example, excessive alcohol intake and obesity increased the risk for the development of ER-positive tumours [92, 93]. As for late age at first full-term birth and obesity are related to an increased risk of large tumours [91]. Hence, risk factors for BC may also affect breast biology and clinical behaviour, thus also BC prognosis.
Changing importance of prognostic factors over time after diagnosis
Commonly, the value of prognostic factors decreases depending on the length of the follow-up period [31, 94]. Survival curves according to prognostic factors usually show a large drop in survival for all stages during the first 5 years; afterwards the curve stabilizes. Studies agreed on the long-lasting influence of tumour size at diagnosis on survival, albeit attenuating over time [31, 94, 95]. Grade, nodal status and metastases were also valuable in predicting survival up to 20 years after diagnosis [31, 95]. Although, others have reported that 10 years after diagnosis only tumour size [94] or nodal status [8] or old age [8] remained as an independent predictor of long-term survival. Similarly, ER/PR status and MAI only had a significant prognostic role in the first 5–10 years after diagnosis [67, 71, 96]. Because even 10 years after BC diagnosis the probability of survival for BC patients does not seem to reach that of the general population, the role of other prognostic factors in determining survival for long-term survivors still needs to be determined.
The role of early detection
Increased awareness among women and improvement in diagnostic procedures have enabled earlier and better detection of BC. Trials on population screening have reported 21–29% reduction in BC mortality for women invited for screening within 14–16 years of follow-up [19, 97]. Screening identified tumours at an early stage consequently, survival improved [98, 99]. Screening also identified patients with slowly growing tumours who might receive unnecessarily aggressive cancer treatment. Thus, Joensuu et al. [100] examined recurrence rates among patients detected by screening compared to those detected outside screening. After adjusting for tumour aggressiveness (tumour size, nodal status, grade, age, treatment, PR status, HER-2), hence eliminating bias towards detection of indolent cancers (length bias), the benefit of screening for the prognosis for BC patients remained evident.[100] This suggests that other factors explain the indolent behaviour of BC detected by screening. Hence, until this factor is established, detection mode should probably be considered as a prognostic factor and thus be taken into account in patient management.
The role of treatment
Improvement in BC treatment has undoubtedly also increased the long-term survival of BC patients [101], as reflected by the improved overall survival across all BC stages [16]. Using historical data from population-based studies in periods when effective treatment was not available, it was estimated that without treatment only 4% of BC patients would survive 10 years or longer [102]. BC treatment guidelines have been modified continuously in the last 28 years, tailored to most of the prognosticators mentioned earlier [51]. Effectiveness of various treatment modalities has been summarized by others who conclude that radiation, chemotherapy and hormonal therapy may reduce long-term mortality by up to 57% [66, 103–105]. Emerging new therapeutic approaches using a monoclonal antibody directed against HER-2 have yielded improved short-term survival for advanced stage [106] as well as operable BC patients [107]. Quality of treatment as indicated by loco-regional failure [108], surgeon workload [109] or hospital volume [110], may affect survival although its role on long-term survival still needs confirmation. In conclusion, on the one hand we have observed a shift in stage towards less aggressive cancers; on the other hand, better and more (systemic) treatment has become available, leading to improved survival for BC patients.
Conclusion
The prognosis of BC has become relatively good, with current 10-year relative survival about 70% in most western populations [16, 111], especially if up-to-date statistical method such as the period analyses is used [111] (Table 1). Even better, the longer patients survive their BC the higher their survival chance [16]. Our review shows conventional prognostic factors of survival, such as tumour size, lymph node status and grade, remain the most important determinants of 10-year survival for BC patients (Table 2). Most studies agreed on the value of MAI and LVI for prediction of long-term survival. The influence of host factors including age, race/ethnicity or socio-economic factors and tumour-related factors such as histological type and angiogenesis diminishes after correction for other factors. For most recent markers such as Her2, gene profiling, p53 mutation and uPA level longer follow-up is needed. Recurrence, metastases and a second cancer double the burden of disease thus increase risk of mortality. Similarly, co-occurrence with other diseases is in no doubt decrease survival.Table 1Overview of studies reporting long-term prognostic factors for breast cancer (BC) patientsNo.Author, yearNo. of patientsMean/median follow-up (yrs)Univariate (UV) analysis significantMultivariate (UV) analysis significantNot significantRemarks1Haerslev and Jacobsen 1995 [70]a49010.6MS, T, N, Htyp, MI, G, PR, Her2All patients: N & PR In N+: MI & PR In N-: MS & GHer2Overall survival was measured. P53 was related to absence of tubular formation, high G, ER-negative, high PCNA (proliferating cell nuclear antigen) score2Pietilainen 1995 [10]39211.1P53, N, T, Htyp, tubular formation, intraductal growth, margin formation, necrosis, DNA ploidy, S-phase fractionAll patients: N, T, MI In N+: T, MI In N−: T, p53, GOverall survival was measured. P53 is related to younger age, MI, AI, G, nuclear pleomorphism3Haerslev 1995 [79]a49011PCNAT, G, PRHer2 & PCNA (Proliferating cell nuclear antigen)Overall survival was measured. PR was only an independent factor in N-positive pts. Her2 & PCNA were related to more positive N, higher G, ER-/PR-negative4Gamel 1996 [39]163,808NR. Range 1mos-19 yrsHistological type by stage (localized & regional BC)Breast cancer specific survival was measured5West 1996 [12]1196NR. Diagnosed: 1973–1986. End FU: 1994.ComorbidityLevel of comorbidityAdjusted for age, race, stage, N, therapy. Values for these factors were not shownOverall survival was measured. Charlson comorbidity index was used. There is no difference in the significance of comorbidity on survival of Caucasians and African American (AA)6Haerslev 1996 [112]a487>10Ki-67, PCNAT, G, PRKi-67 & PCNA.Overall survival was measured. PR only an independent factor for N+ patients. Ki-67 was related to T, MI, G7Northridge 1997 [36]Mucinous BC: 4082. Infiltrating duct BC: 139,154NR. Diagnosed: 1973–1990HTyp, period of diagnosis, Stage, GAgeBreast cancer specific survival was measured8Kollias 1997 [11]a2879 age ≤70, T <5cm>10Age <35, NPIT, G, NAgeOverall survival was measured. Younger than 35 yrs had higher grade, more LVI and worse NPI group. After 10yrs NPI did not change OS9Zahl and Tretli 1997 [95]8802 age <70Diagnosed: 1965–74. End FU: 1991Survival categorized by age, stage and follow-up timeExcess hazard from breast cancer was measured. After 8 yrs being younger than 35 does not influence survival. Stage was an important prognosticator up to 20 yrs10Pinder 1998 [47]46512N by grade, Treatment by gradeOverall survival was measured. The study aimed to confirm value of Nottingham grading system for survival. N+G3 patients benefited from prolonged chemotherapy11Gaffney 1998 [113]BRCA1: 30BRCA2: 20 Control: 18278 BC ptsBRCA1: 9.8 BRCA2: 7.5 Control: NRBRCA1 vs. BRCA2 vs. controlOverall survival was measured Case and control were matched for date of birth, date of diagnosis and tumour size. Patients with BRCA+ were younger. Patients with BRCA1 had higher grade12Wojcik 1998 [28]6577 patients Whites: 5879 African American (AA): 698At 10 yrs 59–67% patients were aliveRace, G, N, T, stage, waiting time, smoking, being a widow, having other family as dependentRace, age, stageUV: alcohol, family historyOverall survival was measured. AA is more likely to be younger at diagnosis, have larger tumour, higher stage and more lymph nodes13Mansi 1999 [114]35012.5Bone marrow micrometastasesN, TBone marrow micrometastases, LVIOverall and breast cancer-specific survival was measured. Bone marrow metastases may be useful as prognostic factor for BC pts without information on T and N14Kollias 1999 [46]a319 T ≤1cm>10G, N, LVI, NPIG, NLVIOverall survival was measured15Tabar 1999 [45]2468NR. Diagnosed: 1977–85. End FU: 1996T, N, G, detection mode, HTypTXN, age*N, Htyp*N, T*N*GOverall survival was measured. Screening arrests disease progression. Tumour progression is more rapid in BC patients <50 yrs. OS of T1a(1–5 mm) vs. T1b(6–10 mm) NS.16Holmes 1999 [85]198213.1BMI ≥303rd  to 5th quintile of protein protein intake after diagnosis, N, T, GBMI, protein intake prior diagnosis, alcohol intakeAll cause mortality was measured. MV for BMI was corrected for age, diet interval, oral contraceptive use, hormone replacement therapy, MS, age at menarche, aget at birth and parity, smoking, T, G, N, ER, PR BMI <21 and 1st quintile of protein intake were reference. Significant trend of higher mortality from lowest to highest quintiles of fibre, lutein and zeaxanthin, calcium and protein intake, with 13–35% lowest mortality in the lowest quintile17Nomura 1999 [58]1857 <80 yrs stage I-III12Second cancer and recurrenceAge, ER, N, recurrence, second cancerOverall survival was measuredRecurrence is related to higher stage, younger age at diagnosis, Htyp, and therapy. Second cancer is related to younger age. Death related to recurrence and second cancer is increased 12 yrs after diagnosis.18Reed 1999 [37]613 T1-2N015.5Age >50, T, GG, T, treatmentUV: treatment, ER, PR, Her2, P53Overall survival was measured. Her2 was related to PR-, ER-negative, P53, G. P53 was related to PR-. Treatment was ovarian & locoregional irradiation that had lower mortality rate19Aebi 2000 [7]3700 pre- & perimenopausal12Age <35 vs. ≥35N, T, G, age <35*ER+Age, EROverall survival was measured. Younger patients with ER+ who were not amenorrhoea had a significantly shorter survival20Ferrero 2000 [78]297 N-11T, ER, P53T, ERAge, PR, GBreast cancer-specific survival was measured. P53 was related to grade, T, ER-negative. P53 was continuous variable21Kroman 2000 [6]10,356 age <50NR. Diagnosed: 1978–96.Age, T, N, GPeriod of treatment and surgeryRelative survival was measured for excess mortality due to BC. When chemotherapy was given BC at young age does have worse prognosis22Ferrero-Pous 2000 [69]48810ER, uPA, G, N, PR, P53 by Her2All patients: uPA, N, T, Her2, age In N−: uPA, T In N+: N: uPA, T, age, Her2Overall survival was measured. For patients who received chemotherapy uPA, T & N determined OS. For patients who received hormonal therapy uPA, Her2 & N determined OS23Kato 2001 [44]a37710T, N, GAMC, T, N, GNecrosisOverall survival was measured. AMC is a good prognostic factor for N- and T2-3 patients24Liu 2001 [96]79116.3T, N, G, ER, Her2, p53, MIB-1, MAI, AIAll patients: N, T, G, ER, Her-2 In N−: G In N+: N, age, ER, Her2UV: age. MV All patients: AI, MI, MIB-1, ER, G MV in N- & N+: AI, MI, ER, G.Breast cancer-specific mortality was measured. When patient FU was truncated at 5 yrs, MI was prognostic factor for N+ and N-25Page 2001 [115]311 no adjuvant therapy.11.6High risk group (ER- or T≥3cm) vs. low risk (ER+ and T <2 cm)T, risk group (high vs. low)G, MIOverall survival was measured. MI was only significant when FU was truncated at 5 yrs. Grade was significant prognostic factor for short- and long-term survival26Frkovic-Grazio and Bracko 2001 [48]270 T1N0M012.5G, Tubular score, MITubular score and MIBreast cancer-specific survival was measured. This study confirmed the use of Nottingham grading system in their cohort27D’Eredita 2001 [49]402≥16T, N, Htyp, G, LVI, NPIT, N, GUV: Age, MS, ER, type of surgery MV: LVI & HtypOverall survival was measured. NPI gives similar survival prognosis as T, N, G28Thomson 2001 [26]23786At 10 yrs about 50% patients were aliveAge stratified by SESIntermediate vs. high SES group corrected for age, ER, N, T, stageDeprived vs. high SES group corrected for age, ER, N, T, stageDeprived women have more ER- tumours. ER distribution and treatment method accounted for 20% of disparities in survival29Vorgias 2001 [30]269 stage II12NRT, N, age, ER/PRMS, therapyOverall survival was measured30Vincent-Salomon 2001 [43]685 T≤3 cm10.8G, N, ER, necrosisN, necrosis, GUV: Vascular density, LVI, age, PROverall survival was measured. Intratumoral vascular density was related to larger tumour size and higher grade31Eerola 2001 [77]Familial BC: 359Sporadic BC: 59517NR Diagnosed: 1953–1995 End FU: 1997Stage, age, period of BC diagnosis, FU time (after 2 and 3 yrs of diagnosis)BRCA1, BRCA25-year relative survival was measured for excess mortality due to BC32Kitchen 2001 [35]952012Tubular BC type vs. other type, by nodal status and chemotherapyOverall survival was measured. Tubular BC type had better prognosis than other type. This type was more likely to have low G & ER+33Kato 2002 [50]a42210P53, MI, necrosis, T, N, LVIMI, T, NUV: AIOverall survival was measuredIn MV P53 & MI were independent prognostic factors for N-patients only. P53 was related to MI, AI, necrosis, G, T, N, ER/PR34Kato 2002 [54]a39810BVI, T, N, G, chemotherapyBVI, T, N, G, chemotherapyUV: necrosisOverall survival was measured35Costa 2002 [67]67011.4N, T, age, ER/PRN, T, ageMS, ER/PRBreast cancer-specific survival was measured. After 5 yrs of FU ER and PR were not independent prognostic factors36Menard 2002 [17]1928Diagnosed in 1968–69 and 1978–79Her2, N, T, MS, lymphoid infiltration, PR-G, T, N, lymphoid infiltrationOverall survival was measured. HER-2 was related to large tumours, higher G, lymphoid infiltration, higher mitotic index, PR-37Van de Vijver 2002 [74]295 age <53, stage I-II6.7Gene profile (Good vs. bad prognosis) for all patients, N+, N−Gene profile, T, N, chemotherapyVI, G, age, hormonal therapyOverall survival was measured38Van’t Veer 2002 [72]117 age <55NRBetter classification of patients with high risk of metastasis and in need of chemotherapy39Hatteville 2002 [21]318015.8OS <5 year: N, G, recurrence or metastasis OS≥5 yr: G and recurrence or metastasisAge, TIf patient remains without recurrence or metastasis, effect of prognostic factors decreases over time. With metastases, this effect increases40Sotiriou 2003 [73]996.1Gene profile (luminal 1–3 vs. basal 1–2 & Her2 type)Luminal-like 1–3 was predominantly ER+. Basal-like 1–2 and Her2 was predominantly ER-41Dignam 2003 [83]3385 N−, ER+13.8BMI <18.5 and BMI ≥30 higher total mortality and other deaths.BMI on deaths after BC events.Total mortality, death after BC events and other deaths as well as recurrence rate and occurrence of a second cancer was were measured. MV was adjusted for treatment, age, MS, race, T, ER and PR. Reference group was BMI 18.5–24.9.42Olivotto 2003 [57]620 stage IIIB-M1>20Supraclavicular BC, Stage IIIB and M1Overall and breast cancer specific survival were measured. Patients with supraclavicular metastases had significantly better survival than patients with M1. Survival of these patients resembles that of BC stage IIB. (FU for living patients 20 yrs, for all patients 4.5 yrs)43Weiss 2003 [32]905 N+ Chemotherapy+22.6N+ (N1–3 vs. N4–9 vs. N >10), also by treatment and follow-up timeN, T, MSMV: NXT, MSXT, additional vincristine and prednisonOverall survival was measured. N was related to T. MS was related to receptor status44Taylor 2003 [16]54,228At 10 yrs 65% patients were alivePeriod of diagnosis, stage by age, FU time by stageRelative survival was measured for excess mortality due to BCThe longer the survival the better the prognosis. Improvement in relative survival for all patients and all stages since 197245Dales 2004 [56]905 aged 25–8111.7In N- : CD105+ vessels. In all pts: CD31, Tie-2/TekIn all pts: G, CD105 vessels, ER In N−: G, CD105 vessels, PRIn all pts: T, Htyp, CD31, PR, age. In N−: T, CD31 vessels, ER, ageOverall survival was measured. MV: Tie-2/Tek showed significant role for predicting OS in all patients and N- patients46Brenner and Hakulinen 2004 [15]18,578 age <50NR. Diagnosed: 1953–1999.Period of diagnosis, stage, stage*period, time after diagnosisImprovement of prognosis for BC patients younger than 50 over the past decades. Relative survival remains lowered even 40 yrs after diagnosis47Robson 2004 [76]584 Ashkenazi Jewish116BRCA1, T, N, ER, age, chemotherapyBRCA1, T, N, AgeTamoksifen, BRCA2Breast cancer-specific survival was measured. No effect of BRCA on non-BC death. BRCA1 only predicted BC death in patients without chemotherapy48Chia 2004 [33]1187 LVI-, N-, Adjuvant systemic therapy-10.4T, GTXGOverall and breast cancer specific survival were measured. Patients with higher grade and size have greater chance to die from other & those with low risk disease greater chance of death from BC49Yoshimoto 2004 [18]15,416NR. Diagnosed 1946–2001.Period of diagnosisOver the decades, there were less extensive surgery and lymph node examination, less radiotherapy, more chemo- and hormonal therapy50Houterman 2004 [116]527 age ≥404.7Comorbidity, N, Therapy, age≥70, comorbidity*NIn age <70: comorbidity, N In age ≥70: comorbidity, ageIn age <70: therapy In pts age≥70: N, therapyRelative survival was measured for excess mortality due to BC Older patients with comorbidity were not treated differently but had a worse prognosis51Schoppmann 2004 [53]37422.4LVI, G, N, TherapyLVI, G, NLMVD (Lymphatic Microvessel Density), T, Htyp, ER, age, MSOverall survival was measured. LVI is related to young premenopausal BC, lower G, N+52Warwick 2004 [31]2299>10G, N, T, MetastasesG, N, T, MetastasesBreast cancer specific survival was measured. All studied factors predicted long-term survival, but their value decreased over time53Berclaz 2004 [82]679214BMI 25–29, BMI ≥30 lower overall survivalBMI ≥30BMI 25–29Overall survival and also disease free survival were measured. Reference group was BMI ≤ 24.9. MV adjusted for ER, T, N, MS, treatment, chemotherapy, hormonal- in combination with chemotherapy54Dignam 2005 [84]4077 N-, ER-NRBMI ≥35 and AA had higher overall mortality and non- BC deathBMI and race on death after BC eventsTotal mortality, death after BC events and other deaths as well as recurrence rate and occurrence of a second cancer were measured. MV was adjusted for treatment, age, MS, race, T, ER and PR Reference group was BMI ≤24.955Holmes 2005 [87]298796 monthsPhysical activity after diagnosis (MET ≥9) on BC and total mortalityBreast cancer and total mortality were measured. MV corrected for age, interval between diagnosis and physical activity assessment, smoking, BMI, MS, hormone therapy use, age at first birth, parity, energy intake, stage and treatment. MET: metabolic equivalent task hours per week. Patients with BMI ≥25 and more physical activity before diagnosis there was a significant trend for less breast cancer death56Robsahm and Tretli 2005 [27]5042NR. Diagnosed: 1964–92. End FU: 1992NRLocation of home, age at first child, physical activity at workMV corrected for: age, period of diagnosis, birth cohort, educational levelBreast cancer-specific survival was measured. Incidence of BC increases with higher educational level, and case fatality decreases by increasing education level57Vu-Nishino 2005 [38]1490 received breast- conserving treatment13.9Medullary BC vs. other BC typeOverall survival was measured. Medullary BC type had better prognosis than other type. This type was more likely to have ER+, PR+ & less BRCA1/2 mutation. Medullary type was only a prognostic factor for the first 5 yrs58Galper 2005 [63]2102 stage I-II, 314 with local recurrence (LR)13.1NRNo LR treatment, Invasive LR, time (yrs) to local recurrence, age at initial BC diagnosisT, detection method, number of nodes sampled, ER/PR, histological type, G, LVI, marginsMeasure of survival: distant failure, second malignancy, or death Patients with a longer time to recurrence have prolonged survival59Voogd 2005 [62]266 BC with LR11.2 after LR for living ptsNRLocation of LR, size of LR, skin involvement of LR, N+ for primary tumourOverall survival was measured. Early detection of local recurrence may improve the treatment outcome60Louwman 2005 [13]8966Diagnosed 1995–2001. End FU: 20042 or more comorbidities, diabetes mellitus and previous cancerPrevious cancer, CVD, DM, cerebrovascular disease, dementia, 2 or more comorbidities, stage, treatment (RT, ST, age)Overall as well as relative survival was measured for excess mortality due to BC Primary treatment of BC patients with serious comorbidity was less extensive than treatment of those without comorbidity61Tammemagi 2005 [14]90610Number of severe comorbidities, race, type of comorbidityAll patients: 3 or more comorbidities adjusted for stage, age, ER, surgery, chemotherapy, radiotherapyOverall survival was measured. AA had more diabetes and hypertension. After adjustment for these 2 comorbidities disparity disappeared62Meunier-Carpentier 2005 [55]909/918 age: 25–8111.3Tie2–UV: VEGFR-2, VEGFR-2Overall survival was measured. VEGFR-1 and Tie2 were reported as independent prognostic factors corrected for T, G, Htyp, in all patients and N-63Tai 2005 [40]6184 Inflammatory BCNR. Diagnosed 1973–1995. End FU: 2000Period of diagnosisBreast cancer-specific survival was measured. Prognosis has improved over the decades due to more aggressive therapy64Louwman 2005 [71]492 T1–2 N0>10 yrsMAIOS: age, T BCS: MAIOS: HTyp, therapy, period of diagnosis. BCS: therapy, period of diagnosis, age, T, HtypOverall (OS) as well as relative survival (BCS) was measured for excess mortality due to BC Higher MAI was a significant prognostic factor for N− and N+, but only during the first 10 yrs of FU65Arrigada 2006 [8]2410 T ≤7 cm N1–219T, skin fixation, muscle fixation, G, N, ageTotal FU: T, N, G, age <35, age≥55 FU 0–5 yrs: T, N, G, age ≥55 FU 5–10 yrs: N, G, age <35, age ≥ 55 FU 10–15 yrs: N >10, age >55. FU 15–20yrs: age≥65Overall survival was measured. Long-term effect of prognostic factors vanishing66Newman 2006 [29]90,124. White American: 76,111. AA: 14,013Age, stage, SESMeta-analysis. African American is an independent predictor of poor outcome for overall survival and breast cancer specific mortality67Menvielle 2006 [24]407,435 women followed for BC death (N:1408)Women who died of BC in 1968–96Level of education by period of diagnosisBreast cancer death among women with the highest education compared to women with the lowest education in 1968–74 was 0.43; and in 1990–96: 1.17 (NS)68Bouchardy 2006 [25]3920 age <70NR. Diagnosed in 1980–2000SESSES corrected for age, period of diagnosis, marital status, country of birth, Htyp, ER, detection method, stage, sector of care, therapyOverall survival was measured. Lowest SES had less frequently screen-detected cancers, less stage I, less lobular BC, less BCT, less lymph node dissection69Siegelmann-Danieli 2006 [117]992, age ≥706.9Being in wheelchair, renal insufficiency, dementia, CHF, cardiac arrhythmia, DM, IHD, osteoporosis, PVD, cerebrovascular disease, COPD, Parkinson’s disease, valvular heart diseaseIn stage 1A-2A: age, CHF, DM, PVD, stage, cardiac arrhythmia, Parkinson’s disease, renal insufficiency In stage 2B-4: G, stage, N, wheelchair-bound, renal insufficiency, COPD, age, DMSystemic therapyOverall survival was measured. CHF: Cardiac Heart Failure. DM: Diabetes Mellitus. IHD: Ischemic Heart Disease. PVD: Peripheral Heart Disease. COPD: Chronic Obstructive Pulmonary Disease. Role of comorbidity varies by age70Pritchard 2006 [68]639 premenopausal N+10Her2 amplificationHer2 corrected for age, N, ER, type of surgeryOverall survival was measured. Those with amplified Her2 have improved survival with CEF71Lee 2006 [52](A) Adjuvant therapy − : 990. (B) Adjuvant treatment +: 1765Group A: 13 Group B: 6.8.LVIGroup A: T, G, LVI, HtypGroup B: T, G, LVI, chemotherapy, hormonal therapyB: ER, age, HtypBreast cancer-specific survival was measuredFor patients without adjuvant treatment, role of G in survival was higher in the first 5 yrs. Role of Htyp was not significant for the first 5 yrs of FUaindicates the overlapping patients used by the same author to answer another research question; yrs: years; UV: Univariate analysis. MV: Multivariate analysis. MS: Menopausal Status; T: Tumour size; N: Nodal involvement; Htyp: Histological type; MI: Mitotic Index; G: Grade; PR: Progesterone Receptor status; ER: Oestrogen Receptor status; PCNA: proliferating cell nuclear antigen; mos: months; NR: Not Reported; AA: African American; age: is in year and indicate age at primary breast cancer unless otherwise state; NPI: Nottingham Prognostic Index; LVI: Lymphovascular Invasion; (Prognostic factor)*(Prognostic factor): interaction between two factors; BMI: Body Mass Index; AMC: Average Microvessel Count; MAI: Mitotic Activity Index; AI: Apoptosis Index; FU: Follow-up; SES: Socioeconomic Status; BVI: Blood vessel Invasion; LMVD: Lymphatic Microvessel Density; LR: local recurrence; CVD: Cardiovascular Disease; DM: Diabetes Mellitus; RT: radiotherapy; ST: Systemic therapy; VEGFR: Vascular Endothelial Growth Factor Receptor; OS: Overall survival; BCS: Breast Cancer Specific Survival; NS: not significant; CHF: Cardiac Heart Failure; IHD: Ischemic Heart Disease. PVD: Peripheral Heart Disease. COPD: Chronic Obstructive Pulmonary. CEF: cyclophosphamide, epirubicin and fluorouracilTable 2Selected prognostic factors for long-term overall mortality of breast cancer (BC) patientsPatient groups basedHazard ratio (HR) for overall follow-up or survival probability (S) 10 years after diagnosisMorphology basedHazard ratio (HR) for overall follow-up or survival probability (S) 10 years after diagnosisMolecular basedHazard ratio (HR) for overall follow-up or survival probability (S) 10 years after diagnosisAge at diagnosis [8]HR:Lymph node status [31]HR:HER2[69]HR:       <35 vs. 35–441.4 (P: 0.07)  N≥1 vs. N02.4 (1.9–2.9)  >500 vs. ≤5001.82 (1.1–2.9)      45–54 vs. 35–441.1 (ns)Metastases vs. N022.73 (16.1–32.2)Only in node-positive       55–64 vs. 35–442.0 (P: 0.000)      65–75 vs. 35–442.5 (P: 0.000)Period of diagnosis [16]Relative survivalb:Tumour size (mm)[31]HR:Cell proliferation indexHR:      1972–197659%  T10–14 vs. T1–91.2 (0.8–1.9)(MAI)      1977–198664%  T15–19 vs. T1–91.7 (1.1–2.6)  >10 vs. ≤10 [10]1.02 (1.00–1.03)      1987–199170%  T20–29 vs. T1–92.5 (1.6–3.9)Only in node-positive patients  T30–49 vs. T1–93.8 (2.4–6.0)  T≥50 vs. T1–94.6 (2.9–7.6)Time after diagnosis [16]Relative survival:Tumour grade [44]HR:Gene expression profile [74]S:    0 vs. 5 yrs after diagnosis  II vs. I2.5 (1.0–6.1)55% vs. 95%       Regional BC79% vs. 84%  III vs. I5.7(2.6–12.4)  Poor vs. good signaturef       Locally advanced BC53% vs. 68%Socioeconomic status [26]HR:Tumour type[34]S:ER/PR status [30]HR:       Intermediate vs. affluent1.2 (1.0–1.4)  Poor vs. excellent d,e<50% vs. >80%  Positive vs. negative0.38 (0.02–1.06)       Deprived vs. affluent1.2 (0.99–1.53)LifestyleHR:       Body Mass Index              <21 vs. 29+ kg/m21.4 (0.97–2.00) [85] c       Physical activity              < 3 vs. 23.9 MET-h/wka0.56 (0.4–0.8) [87]HR: Hazard ratio calculated within multivariate analysis of breast cancer patients followed for a median/mean of 10 years or longer a Metabolic equivalent task hours per week; b Estimates taken from graph; c Higher alcohol intake no significant effect on mortality. Significant trend of higher mortality for lowest compared to highest quintiles of fibre, lutein and zeaxanthin, calcium & protein intake; d Becomes larger as numbers of involved lymph nodes increases [8]; e Excellent prognosis: tubular, invasive cribriform, mucinous, tubulolobular. Poor prognosis: mixed lobular, solid lobular, ductal and mixed ductal lobular; f unadjusted estimates
Healthier lifestyle generally increases long-term survival. Modifiable risk factors (such as alcohol consumption and obesity) not only affect incidence but also tumour’ clinical behaviour and thus survival.
Although a lot is known about the prognosis for BC patients, effect of traditional prognostic factors appears to attenuate over time, leaving room for studies on the role of other and newer factors for long-term survival.

prognostic factors
long-term
survival
breast cancer


Protein kinase D enzymes are dispensable for proliferation, survival and antigen receptor-regulated NFκB activity in vertebrate B-cells

To investigate the importance of protein kinase D (PKD) enzymes we generated a PKD-null DT40 B-lymphocyte cell line. Previously we have shown that PKDs have an essential role in regulating class II histone deacetylases in DT40 B-cells [Matthews, S.A., Liu, P., Spitaler, M., Olson, E.N., McKinsey, T.A., Cantrell, D.A. and Scharenberg, A.M. (2006) Essential role for protein kinase D family kinases in the regulation of class II histone deacetylases in B lymphocytes. Mol. Cell Biol. 26, 1569–1577]. We now show that PKDs are also required to regulate HSP27 phosphorylation in DT40 B-cells. However, in contrast to previous observations in other cell types, PKD enzymes do not regulate basic cellular processes such as proliferation or survival responses, nor NFκB transcriptional activity downstream of the B cell antigen receptor. Thus, PKDs have a selective role in DT40 B-cell biology.
1
Introduction
The protein kinase D (PKD) serine/threonine kinase family has three members: PKD1, PKD2 and PKD3. Most cell types express at least two PKD isoforms but PKD enzymes are especially highly expressed in haematopoietic cells, where they are activated in response to antigen receptors stimulation [2,3]. A conserved signalling pathway linking antigen receptors to PKDs involves the activation of PLCγ and the subsequent production of diacylglycerol (DAG) which stimulates classical and/or novel protein kinase Cs (PKC) that phosphorylate two key regulatory serine residues in the activation loop of PKD kinases [3–6]. The N-terminal regulatory region of PKD enzymes contains a DAG binding domain and direct binding of DAG also contributes to PKD1 activation [7] as well as regulating the spatial location of PKD enzymes within cells [8–12].
PKD enzymes have been proposed to regulate numerous cellular functions, including cell proliferation [13–16], anti-apoptotic signals [17,18] and thymocyte development [19]. Expression of mutant catalytically inactive and constitutively activated PKDs can also modify Golgi function, cell adhesion and cell motility (reviewed in [20]). In particular, PKDs have been widely linked to the activation of the NFκB transcription factor and in regulating cell survival during oxidative stress [17,21–23]. Another recently proposed PKD1 substrate is HSP27 [24], a small heat shock protein involved in regulating cell migration and cell survival [25]. An essential role for PKD enzymes in regulating class II histone deacetylases (HDACs), enzymes that repress MEF2-dependent gene transcription, has also been demonstrated [1,26–28].
To investigate the biological role of PKDs we have generated DT40 B cell lines that lack expression of one or more members of the PKD family [1], allowing us to investigate the function(s) of PKD isoforms following B cell antigen receptor (BCR) stimulation, as well addressing the issue of functional redundancy between the different PKD family members. Previous studies have shown that PKDs are indispensable for HDAC regulation in B cells [1]. Herein we show that PKDs are also indispensable for HSP27 phosphorylation in B cells. However, PKD-null DT40 B cells are viable and proliferate normally. Moreover, loss of the entire cellular pool of PKD does not critically affect oxidative stress responses in B cells nor do PKD kinases play an essential role in regulating NFκB transcriptional activity. Together, these findings reveal that in B lymphocytes, PKD kinases are not critical regulators of many of the cellular processes previously ascribed to them in other cellular systems.
2
Materials and methods
2.1
Cell culture, transient transfections and cell stimulation
The generation, culture and activation of PKD1−/−, PKD3−/− and PKD1/3−/− knockout DT40 B cell lines have been described previously [1]. Cells were lysed and protein extracts were analysed in Western blotting experiments as previously described [1]. Chloramphenicol acetyl transferase assays have been described previously [29].
2.2
sIgM staining
DT40 B cells (2 × 106 cells per point) were resuspended in 200 μl buffer (RPMI 1640 media, 1% foetal calf serum) containing anti-chicken M1 monoclonal antibody conjugated to FITC for 20 min on ice. The cells were washed twice and fluorescent intensity was analysed by flow cytometry.
All results shown are representative of at two to four independent experiments unless otherwise indicated.
3
Results
3.1
Loss of HSP27 phosphorylation in DT40 B cells lacking expression of PKD family kinases
DT40 B cells express two PKD isoforms, PKD1 and PKD3, and as previously described we have recently generated DT40 B cell lines that lack expression of either PKD1 or PKD3 or both enzymes [1]. In generating the double knockout cell lines we targeted the PKD1 loci in a PKD3−/− cell line that expressed a Flag-PKD3 transgene under the control of a doxycycline-inducible promoter. Hence, in the presence of doxycycline, Flag-PKD3 expression in PKD1/3 double knockout cells is comparable to endogenous PKD3 present in wild-type DT40 cells and removal of doxycycline from the culture media for 5 days results in a completely null PKD phenotype (Fig. 1A).
Previously, we have demonstrated that phosphorylation and nuclear exclusion of class II histone deacetylases (HDACs) during BCR engagement is defective in PKD1/3−/− B cells and can restored upon re-expression of a single PKD isoform [1]. The small heat shock protein HSP27 has recently been proposed as a PKD1 substrate [24] and we accordingly assessed whether PKD-null DT40 cells have defective phosphorylation of HSP27 on serine 82, the proposed PKD1 substrate sequence. We initially investigated the regulation of HSP27 phosphorylation in single knockout DT40 B cells lacking either PKD1 or PKD3. As shown in Fig. 1B, activation of the BCR or treatment with the DAG-mimetic PdBu increased the levels of HSP27 phosphorylation at S82 in wild-type DT40 B cells. BCR and phorbol ester signals were also able to increase HSP27 phosphorylation in PKD1 or PKD3 single knockout DT40 B cells (Fig. 1B). However, BCR- and phorbol ester-induced phosphorylation of HSP27 on S82 was abolished in B cells that lacked both PKD1 and PKD3 (Fig. 1C). Significantly, doxycycline-induced expression of the Flag-PKD3 transgene in the double knockout cells was sufficient to restore normal regulation of HSP27 phosphorylation (Fig. 1C). In contrast, expression of a kinase-deficient PKD3 mutant protein in the double knockout cells was not able to restore BCR- or phorbol ester-induced HSP27 phosphorylation (Fig. 1D). Hence, PKD3 as well as PKD1 can regulate HSP27 phosphorylation and in DT40 B cells they are functionally redundant as HSP27 kinases.
3.2
Cellular proliferation and survival in DT40 B cells lacking expression of PKD family kinases
PKD enzymes have previously been linked to the regulation of cell proliferation and survival (reviewed in [20]). To investigate the effect that loss of PKD kinases had on B cell survival and/or proliferation we cultured wild-type and PKD-null cells in the presence (PKD1/3−/−: Flag-PKD3+ve) or absence (PKD1/3−/−) of doxycycline and monitored exponential growth. As shown in Fig. 2A, PKD1/3−/− cells proliferated exponentially and re-expression of Flag-PKD3 in these cells had no impact on the rate of proliferation. Furthermore, the viability of PKD1/3−/− B cells during routine culturing was not significantly different from that of wild-type B cells (data not shown). It was noted that the population doubling time of PKD1/3−/− cells was slightly slower than that of wild type DT40 cells (12.7 ± 2.8 h versus 10.2 ± 0.4 h) but the failure of PKD3 re-expression to modify the proliferation rate of PKD1/3−/− cells suggests that these small differences were most likely the result of clonal variation and were not caused specifically by loss of PKD enzymes. Thus, PKD family enzymes are not essential for regulating basal survival and proliferation of DT40 B cells.
PKD enzymes, specifically PKD1 and PKD2, have previously been linked to a protective role against oxidative stress-induced injury in 3T3 fibroblast, HeLa and epithelial cell lines [17,30–32]. We therefore addressed the role of PKD family kinases in regulating B cell survival in response to oxidative stress and other stress stimuli. As shown in Fig. 2B, loss of PKD1/3 expression had no significant impact on the survival of DT40 B cells in response to mitochondrial stress stimuli (H2O2 or serum deprivation); DNA damaging agents (etoposide or doxorubicin); ER pathway stress due to calcium overload (thapsigargin) or following prolonged treatment with phorbol esters or Trichostatin A, an inhibitor of class I/II HDACs. Thus, PKD kinases do not play an essential role in regulating B cell survival in response to a range of different stress stimuli.
3.3
Antigen receptor regulated signalling pathways in PKD-null DT40 B cells
To further explore the contribution of PKD kinases to DT40 B cell biology we investigated whether specific BCR-regulated signalling events were defective in the PKD-null B cells. Initial experiments revealed that surface expression of the BCR was reduced in PKD1/3−/− (and in PKD1/3−/−:Flag-PKD3+ve) cells compared to wild-type DT40 B cells (Fig. 3A and data not shown). Nevertheless, BCR-crosslinking of PKD1/3−/− cells was sufficient to induce the activation of a number of signalling cascades, similar to that observed in wild-type cells (Fig. 3B). Hence, BCR-induced activation of the Akt, mTOR/p70 S6 kinase (as shown by S6 ribosomal protein phosphorylation) and MAPK signalling pathways was clearly detectable in PKD1/3-null B cells (Fig. 3B). Furthermore, enhanced tyrosine phosphorylation of multiple cellular proteins as well as an increase in intracellular calcium levels was also observed following BCR stimulation of PKD1/3-null B cells (data not shown). We did observe that the strength of BCR (but not phorbol ester)-induced regulation of the Erk1-RSK1 signalling pathway was reduced in PKD1/3−/− B cells compared to wild-type B cells (Fig. 3B). One interpretation of this data is that PKD enzymes may modulate Erk activation. Indeed, PKD enzymes have previously been linked to the growth factor-regulated Erk signalling in fibroblast and endothelial cell lines [33–35]. However, BCR-induced Erk phosphorylation was also reduced in PKD1/3−/−-Flag-PKD3+ B cells (data not shown) suggesting that reduced BCR levels on the surface of PKD1/3−/− (and PKD1/3−/−-Flag-PKD3+) B cells may itself impact on the strength of activation of this specific intracellular signalling pathway.
To search for other potential PKD targets that may show defective regulation in PKD1/3−/− DT40 B cells, we used a PKD substrate phospho-antibody that recognises consensus phosphorylation sequences targeted by PKD enzymes (LxRxxpS/T) [36]. As shown in Fig. 3C, phorbol ester- and BCR-induced phosphorylation of cellular substrates detected by this phospho-antibody was similar in wild-type and PKD1/3−/− cells and is therefore independent of PKD enzymes. However, pretreatment of both wild-type and PKD1/3−/− DT40 B cells with GF109203X, a bisindoylmaleimide derivative that inhibits PKCs prevented the induction of proteins that contain phosphorylated LxRxxS/T motifs. Thus loss of PKD1/3 enzymes does not globally disrupt the phosphorylation of cellular proteins that contain LxRxxpS/T motifs. This result is perhaps not surprising as LxRxxS/T motifs also act as good substrates for other serine/threonine kinases such as MAPKAPK2. However these experiments do provide further evidence that phosphospecific antisera are not sufficiently selective to be designated kinase specific substrate antisera.
BCR-induced signalling pathways culminate in the activation of gene transcription events that control B cell survival, proliferation and function. In this context, it has been proposed that PKD family members control of gene transcription through activation of the NFκB transcription factor. Thus, PKD-mediated activation of NFκB occurs downstream of a variety of different signals, including mROS/oxidative stress, lysophosphatidic acid and the Bcr-Abl oncogene [17,21,23,30,37]. Furthermore, expression of an activated PKD1 mutant enhances HPK1-mediated NFκB activation [38]. In B cells, NFκB is known to be regulated via DAG and PKCβ [39,40] but whether PKDs are key intermediaries for NFκB regulation has not been explored.
The data (Fig. 4A) show that NFκB transcriptional activity was strongly induced in both wild-type and PKD1/3−/− DT40 B cells in response to either phorbol ester or BCR stimulation. In contrast, BCR and phorbol ester-induced NFκB transcriptional activity was abolished in PKCβ−/− DT40 B cells (Fig. 4A), although strong activation of PKD kinases (as assessed by autophosphorylation of PKD1 at S916) was observed in the PKCβ−/− cells (Fig. 4B). Thus, PKD kinases are neither essential nor sufficient to mediate BCR-induced NFκB activation in DT40 B cells and hence do not participate in DAG/PKC mediated control of NFκB.
4
Discussion
Protein kinase D serine kinases have been proposed to regulate diverse cellular functions including the phosphorylation and nuclear localisation of class II HDACs and the phosphorylation of HSP27. It has also been suggested that PKDs act as mitochondrial sensors for oxidative stress and play a role in regulating NFκB transcription factors [41]. Most of the data about the function of PKDs has come from experiments that ectopically express active or inhibitory PKD mutants or that use RNAi to reduce PKD expression. We have used gene targeting to specifically delete PKD alleles in DT40 chicken B cells and can thus use PKD-null DT40 cells to assess the relative contribution of individual PKD isoforms in class II HDAC control versus oxidative stress responses and NFκB regulation in lymphocytes. We have previously used these PKD-null DT40 cells to define an essential role for PKDs in regulation of class II HDACs, the present report now describes an indispensable role for PKDs in regulating the phosphorylation of HSP27 on serine 82, a site previously identified as a target for the p38-MAPKAPK2 signalling cascade [42]. However, studies of PKD-null DT40 cells reveal that PKD family kinases are not essential for oxidative stress survival responses nor are they required for activation of NFκB transcription factors. These latter findings are in striking contrast to previous observations in HeLa and epithelial cell lines where overexpression/RNAi approaches have implicated PKD1/2 in the control of proliferation, survival and NFκB activation [20,23]. Hence, the present report shows that the proposed roles for PKDs as key sensors that modulate survival pathways in response to oxidative stress and regulate cell survival and proliferation are not ubiquitous and may be restricted to certain cell lineages. Taken together, these data indicate that loss of expression of PKD family members does not globally impact on early BCR-regulated signalling pathways.

protein kinase d
proliferation
survival
nfκb
pkd
hsp27
pkd, protein kinase d
pkc, protein kinase c
bcr, b cell antigen receptor