Stathmin Expression and its Relationship to Microtubule Associated Protein Tau and Outcome in Breast Cancer

Abstract

Background

Microtubule associated proteins (MAPs) endogenously regulate microtubule stability. Here we assess the prognostic value of stathmin, a destabilizing protein in combination with MAP-tau, a stabilizing protein, in order to assess microtubule stabilization as a potential biomarker.

Methods

Stathmin and MAP-tau expression levels were measured in a breast cancer cohort (n = 651) using the tissue microarray format and quantitative immunofluorescence (AQUA) technology, then correlated with clinical and pathological characteristics and disease free survival.

Results

Univariate Cox proportional hazards (PH) models indicated that high stathmin expression predicts worse overall survival (HR = 1.48; 95% CI = 1.119–1.966; P = 0.0061). Survival analysis showed 10-year survival of 53.1% for patients with high stathmin expression versus 67% for low expressers (log rank, P<.003). Cox multivariate analysis showed high stathmin expression was independent of age, menopausal status, nodal status, nuclear grade, tumor size, ER, PR, and HER2 expression (HR = 1.19; 95% CI= 1.03–1.37; P = 0.01). The ratio of MAP-tau to stathmin expression showed a positive correlation to disease free survival (HR = 0.679; 95% CI = 0.517–0.891; P = 0.0053) with a 10-year survival of 65.4% for patients with high MAP-tau to stathmin ratio versus 52.5% survival rate for low ratio (log rank, P = 0.0009). Cox multivariate showed MAP-tau to stathmin ratio was an independent predictor of overall survival (HR = 0.609; 95% CI = 0.422–0.879; P = 0.008).

Conclusion

Low stathmin and high MAP-tau are associated with increased microtubule stability and better prognosis in breast cancer.

Introduction

Accumulating evidence indicates that microtubule associated proteins (MAPs) may be associated with varying therapeutic response rates in breast cancer patients and resistance to taxanes ^{1, 2, 3, 4, 5, 6, 7}. MAP-tau is among the best characterized microtubule stabilizing protein that functions to bundle, space, and assemble microtubules ^{8, 9, 10, 11}. In contrast, Stathmin (stathmin1, OP18, metablastin, p19, prosolin) is a ubiquitous cytosolic phosphoprotein and key regulator of cell division due to its depolymerization of microtubules in a phosphorylation-dependent manner. Proper assembly of the mitotic spindle requires desphosphorylation and inactivation of stathmin before cell entry into mitosis followed by stathmin reactivation during cytokinesis ^{12, 13, 14}. When activated outside of mitosis (e.g. during cytokinesis), stathmin regulates dynamic equilibrium of tubulin polymerization through α-β tubulin dimer sequestration and/or promotion of microtubule plus-end catastrophe ^{15, 16, 17, 18} and influences microtubule-actin associations ¹⁹. The ability of stathmin to remodel microtubule networks through tubulin polymerization and its microtubule-actin associations indicates a role for stathmin in tumor cell migration and invasion ^{20, 21}.

The constitutive activation and overexpression of stathmin expression has been associated with a variety of human malignancies including breast, lung, gastric, ovarian, cervical, prostate, urothelial, hepatocellular and colorectal carcinomas ^{22, 23, 24, 25, 26, 27, 28}. In breast cancer cell lines, stathmin overexpression has been associated with reduced taxane sensitivity and increased resistance to taxane-based chemotherapy due to delayed entry into mitosis ^{29, 30, 2, 7}. In breast cancer patients, over-expression of stathmin mRNA has been correlated with high mitotic index, loss of ER and PR and poor prognosis ³¹. Upon examination by IHC, high stathmin was associated with PTEN negative tumors and predicted distant metastasis ³².

The goal of this study was to assess the expression of stathmin to determine its prognostic value in a large cohort of primary breast cancer patients. Furthermore, since cellular functions require a critical balance between both microtubule stabilizers such as MAP-tau and destabilizers like stathmin, we hypothesized that a two-marker model might provide improved prognostic information for breast cancer patients.

Materials and Methods

Patient and Cohort Characteristics

Formalin-fixed paraffin-embedded primary breast cancer tumors resected from 651 patients at Yale University/New Haven hospital between 1962 and 1983 were obtained from the archives of the Pathology Department, Yale University (New Haven, CT) and have been previously described in detail ³³. Specimens and associated clinical information were collected under the guidelines and approval of the Yale Human Investigation Committee under protocol #8219 to D.L.R. All tissue used in these studies was collected after patient consent or waiver of patient consent (for example when patients were deceased) in accordance with protocol #8219.

Tissue Microarrays (TMAs)

Tissue microarrays were constructed as previously described ³³ Index TMAs were made from cell pellets from cell lines: BT-20, BT-474, MCF-7, MDA-MB-231, MDA-MB-361, MDA-MB-453, MDA-MB-468, SKBR3, ZR-75-1, and CaCo2 were formalin-fixed and paraffin-embedded (detailed protocol is described elsewhere ^{34, 35}). Pellets were then cored and added to a panel of 40 breast cancer patient controls on a tissue microarray. Index TMAs served as control arrays during antibody validation and immunofluorescence staining to confirm assay reproducibility and for normalization of scores between slides.

Cell Culture

A panel of breast cancer cell lines and several non-breast controls were purchased from ATCC (Manassas, VA) and cultured in order to measure endogenous levels of stathmin and included: BT-20, BT-474, MCF-7, MDA-MB-231, MDA-MB-361, MDA-MB-453, MDA-MB-468, SKBR3, ZR-75-1, and UAC812, and CaCo2. Cells were maintained per ATCC instructions. Since cell lines are used as expression controls, they were not authenticated after purchase.

Western Blotting

Whole-cell lysates were prepared and Western blots were performed using standard methods. Bands were quantified with NIH ImageJ software and normalized to β-actin. The area under the curve (AUC, as measured by Image J) versus AQUA score for each cell line was plotted and the linear regression was determined (figure 1).

Figure 1. Stathmin expression in cell line controls and frequency distribution in normal breast tissue and in the Yale University Cohort.

(A) Stathmin protein detected by Western blot in 11 cell line controls (top panel); CACO2 cells were inserted as a positive control and β-actin served as a loading control; (bottom panel) the distribution of stathmin AQUA scores from the same cell lines embedded in the breast cancer Index Array. Note: we were unable to find a cell line that did not express stathmin. (B) Stathmin siRNA knockdown with scrambled control after 24 hours shown by immunofluorescence of BT20 cells (upper panel) and western blot from lysates from the same cells. (C) Distribution of average stathmin AQUA scores in the Yale University cohort showing stratification of the cohort using the cutpoint of 25 derived from the mean level of expression in normal breast tissue. Inset is the distribution of average stathmin AQUA scores in normal breast tissue.

siRNA Knockdown

For siRNA transfection, 2 × 10⁵ BT 20 cells were seeded onto 6-well plates in triplicate. The next day cells were transfected with 100 pmol siRNA duplexes targeting scrambled or stathmin using Lipofectamine RNAiMax (Invitrogen) and incubated for 24, 48, and 72 hours. Cells were collected and lysed in SDS sample buffer for protein extraction and SDS polyacrylamide gel electrophoresis and immunoblotting was used to evaluate inhibitory effects. Stealth RNAi siRNA for Stathmin (HSS142799) and Stealth RNAi siRNA Negative Control Lo GC (12935-200) were purchased from Invitrogen. In addition, cells were seeded onto coverslips and treated as above for immunofluorescence analysis of Stathmin siRNA. Again cells were incubated for 24, 48 and 72 hours after transfection, then fixed with 4% paraformaldehyde, permeabilized with 0.2% Triton X-100 in PBS (American Bioanalytical), blocked with 2%BSA in PBS, incubated with stathmin rabbit monoclonal antibody for 1 hour, incubated with Alexa-546 conjugated goat anti-mouse secondary antibody (Invitrogen) for 1 hour, and finally coverslipped with Prolong mounting medium (ProLong Gold, P36931, Molecular Probes) containing 4′,6-Diamidino-2-phenylindole (DAPI).

Antibodies and Immunofluorescence

Yale University cohort TMAs were immunostained using 1) MAP-tau monoclonal antibody which recognizes all human MAP-tau isoforms (1:750; mouse monoclonal, clone 2B2.100/T1029, US Biological, Swampscott, MA) and 2) stathmin/op18, monoclonal antibody (1:200,000; rabbit monoclonal, clone EP1573Y, Epitomics, Burlingame, CA). MAP-tau was previously validated by immunoblot analysis and siRNA knock down ⁴ and stathmin was validated in this laboratory by immunoblot analysis and siRNA knockdown (Fig. 1A and B). Serial sections of the Index Array TMA were stained alongside each Yale cohort slide to confirm assay reproducibility. Normal breast epithelium in the Yale University cohort TMA served as internal positive controls while omission of the primary antibody served as the negative control for each immunostaining event. Immunofluorescence staining was performed as described previously³⁶.

TMA Image Capture and Analysis

Details of the AQUA method of quantitative immunofluorescence has been previously described ³⁶. The TMA cohorts were captured and analyzed using V1.6 of the AQUA software (HistoRx, Branford CT) on the PM2000 platform. Specific parameters related to the TMA data collection are found in previous manuscripts³⁶.

Statistical Analysis

Average values for MAP-tau and stathmin AQUA scores were calculated from two-fold redundant samples and treated as independent continuous variables. Survival curves for both cohorts were constructed using Kaplan Meier methods and the Cox-Mantel log-rank test was used to calculate the association between expression and survival. Cox proportional hazards (PH) regression analysis was used to determine which independent factors significantly impacted overall survival (OS) in the Yale University cohort. All p-values were based on two-sided testing and differences were considered significant at p < 0.05. Statistical analysis was performed using JMP Statistical Discovery Software, Version 7.0.1 (SAS Institute, Inc., Cary, NC).

Results

Stathmin Antibody Validation

Stathmin expression was evaluated in ten breast cancer cell lines and in a colorectal cancer cell line by western blot and tissue microarray. Western blots showed bands at the appropriate migration distances compared to molecular weight standards (Fig. 1a). AQUA scores were collected for an overlapping series of cells lines that showed a range of expression with lowest expression observed in SKBR3 cells (AQUA score = 63) and highest in UACC 812 (AQUA score = 1,903). In addition, stathmin siRNA knockdown was performed in a BT20 cell line indicating decreased stathmin expression after 24 hours (Fig. 1b) and providing evidence of antibody specificity. Finally, two different lots of stathmin antibody were purchased and tested on breast TMAs cored from the same tissue block to confirm reproducibility of the antibody.

Stathmin Expression Pattern in Normal Breast Tissue and the Yale University Cohort

Stathmin was measured in normal epithelial ducts and lobules using a normal breast TMA (n= 110) with two-fold redundancy to determine the level of expression in normal breast tissue. Consistent cytoplasmic localization was observed and stathmin average expression scores in normal breast tissue showed mean and median AQUA scores of 25 and 18, respectively, and a score range between 13 and 127. A frequency distribution of these scores is shown (figure 1c). Normal tissue TMA and an Index TMA were also used to determine the threshold of signal to noise. We found AQUA scores below 18 represent non-specific or background signal (images not shown). The threshold for detection was determined by measuring a control slide in which the primary antibody was omitted. All subsequent AQUA scores were normalized to this AQUA score range using an Index TMA.

Next we examined stathmin expression within the Yale University cohort (n= 651), a primary breast cancer cohort previously used to study many other biomarkers ^{33, 36, 37}. Stathmin showed cytoplasmic localization similar to our observations in normal breast tissue. A stathmin AQUA score was computed for each case by averaging observations from two TMA spots and normalizing using the Index TMA. The frequency distribution of stathmin expression scores in the Yale University cohort is shown along with the mean and median AQUA scores of 62 and 30, respectively, with a score range of 4 to 1,092 (Figure 1C). A total of 474 cases had sufficient tumor tissue for analysis. The mean stathmin expression score in normal breast tissue was used in all analyses to stratify patients as high expressers (AQUA score ≥ 25) versus low (AQUA < 25) with 41.8% classified as low stathmin expressers compared with 58.2% classified as high expressers in the Yale University cohort (Table 1)

Table 1.

Univariate analysis of tumor and clinical risk factors for overall survival in the Yale University cohort.

Yale University Cohort
		Univariate
Variable	No. of Patients (%)(n = 651)	HR	95% CI	P*
Age at Diagnosis	645 (99.1)	1.008	0.996–1.020	0.178
Unknown/Missing	6 (0.9)
Menopausal Status
Premenopausal	196 (30.1)	1.000		0.021
Postmenopausal	449 (69.0)	1.434	1.055–1.950
Unknown/Missing	6 (0.9)
Tumor Size (cm)
≤2	215 (33.0)	1.000	0.204–0.446	<.0001
> 2	384 (59.0)	2.158	1.555–2.996
Other	52 (8.0)
Nodal Status
Negative for Node Metastasis	327 (50.2)	1.000		<.0001
Positive for Node Metastasis	320 (49.2)	2.338	1.761–3.104
Unknown/Missing	4 (0.6)
Nuclear Grade
Small/uniform nuclei	113 (17.4)	1.000		0.024
Intermediate nuclei	315 (48.4)	1.112	0.705–1.756
Large nuclei	170 (26.1)	1.853	1.158–2.967
Other	53 (8.1)
ER Status
ER Positive	326 (50.1)	1.000		0.015
ER Negative	289 (44.4)	1.402	1.257–2.288
Other	36 (5.5)
PR Status
PR Positive	302 (46.4)	1.000		0.013
PR Negative	294 (45.2)	1.421	1.075–1.877
Other	55 (8.4)
HER2 Status
HER2 Positive	109 (16.7)	1.000		0.606
HER2 Negative	495 (76.0)	0.913	0.646–1.290
Other	47 (7.2)
MAP-tau Expression
MAP-tau Low Expression	376 (57.8)	1.000		0.0042
MAP-tauHigh Expression	104 (16.0)	0.691	0.489–0.974
Unknown/Missing	171 (26.3)
Stathmin Expression
Stathmin Low Expression	198 (30.4)	1.000		0.0061
Stathmin High Expression	276 (42.4)	1.483	1.119–1.966
Unknown/Missing	177 (27.2)
Ratio for MAP-tau to Stathmin
Low MAP-tau: High Stathmin	237 (36.4)	1.000		0.0053
High MAP-tau:Low Stathmin	237 (36.4)	0.679	0.517–0.891
Unknown/Missing	177 (27.2)

^*P is given for Cox univariate analysis, statistically significant p values (p<0.05) are in boldface, trending p values are in italics; HR, hazard ratio; ER, estrogen receptor; PR, progesterone receptor; HER2, human epidermal growth factor receptor 2.

Premenopausal status, high nuclear grade, and ER negative status correlated most frequently with high stathmin expression compared to low expression (34.4% vs. 22.6%) (P = 0.005); (34.6% vs. 22.12%) (P = 0.0004), and (50.6% vs. 38.9%) (P = 0.0136). Stathmin expression did not correlate with tumor size, nodal status, PR or HER2 status (data not shown).

Stathmin Prognostic Value in the Yale University Cohort

The expression status of stathmin was evaluated for association with overall survival. Using Kaplan Meier analysis, patients with low stathmin expression (n=195) showed improved survival compared to those with high expression (n= 273) (66.6% vs 53.3 %, respectively; log-rank, P = 0.003; Figure 2A). When stratified by ER status, stathmin retained prognostic value with ER positive/low stathmin expressers (n = 114) showing improved survival compared to ER negative/high stathmin expressers (n=136; 70.9% vs 48%; log-rank, P = 0.012; data not shown). Similarly, patients stratified by HER2 status indicated improved survival with HER2 negative/low stathmin expression (n= 156) compared to HER2 positive/high stathmin expression (n= 60) (66.4% vs 53.0% respectively; log-rank, P = 0.006).

Figure 2. Kaplan Meier survival analysis in the Yale University Cohort.

(A) 10 year survival for high stathmin expression (n = 273) versus low expression for all invasive breast carcinoma patients in the Yale University Cohort. An AQUA score of 25 was used as the cut-point based on the mean expression score from normal breast tissue. (B) Kaplan Meier survival for MAP-tau expression in the Yale University Cohort with cohort division using the cutpoint based on MAP-tau expression in normal breast tissue Baquero, et al., 2011 (in press). (C) Survival analysis for the ratio of MAP-tau to stathmin using the median ratio score as the cutpoint to differentiate high MAP-tau/stathmin expression ratio. (D) Frequency distribution for AQUA ratio scores in the Yale University cohort showing stratification of the cohort using the median score.

In univariate analysis, high stathmin expression, postmenopausal status, nodal metastasis, ER negative and PR negative status were associated with worse overall survival (OS) (HR = 1.483, 1.434, 2.338, 1.402, 1.421, P = 0.0006, <0.001, 0.015, and 0.013, respectively) while small tumor size and low nuclear grade were associated with improved OS (HR = 0.493 and 0.614, P <0.001 and 0.024, respectively) (Table 1). Using the Cox PH model, multivariate analysis indicates that high stathmin expression has independent prognostic value with a hazard ratio of 1.566 (95% CI, 1.091 to 2.248, P = 0.015; Table 2). Large tumor size, nodal metastasis, and ER negative status were also associated with worse OS.

Table 2.

Multivariate analysis of tumor and clinical risk factors for overall survival in the Yale University cohort.

		Yale University Cohort
		MAP-tau			Stathmin			Ratio of MAP-tau to Stathmin
Variable	No. of Patients (%)(n = 651)	HR	95% CI	P*	HR	95% CI	P*	HR	95% CI	P*
Age at Diagnosis	645 (99.1)	1.004	0.981–1.026	0.718	0.998	0.975–1.021	0.844	0.999	0.977–1.022	0.952
Unknown	6 (0.9)
Menopausal Status
Premenopausal	196 (30.1)	1.000		0.339	1.000		0.205	1.000		0.357
Postmenopausal	449 (69.0)	1.158	0.857–1.569		1.489	0.804–2.759		1.336	0.721–2.474
Other	6 (0.9)
Tumor Size (cm)
≤2	215 (33.0)	1.000		<.0001	1.000		<.0001	1.000		<.0001
> 2	384 (69.0)	2.069	1.459–2.934		2.017	1.421–2.862		2.042	1.440–2.896
Unknown	52 (8.0)
Nodal Status
Negative for Node Metastasis	327 (50.2)	1.000		<.0001	1.000		<.0001	1.000		<.0001
Positive for Node Metastasis	320 (49.2)	1.578	1.307–1.922		2.627	1.791–3.854		2.716	1.849–3.989
Unknown	4 (0.6)
Nuclear Grade
Small/uniform nuclei	113 (17.4)	1.000		0.421	1.000		0.1949	1.000		0.296
Intermediate nuclei	315 (48.4)	1.015	0.624–1.725		0.676	0.374–1.222		0.851	0.460–1.575
Large nuclei	170 (26.1)	1.272	0.868–1.853		1.186	0.738–1.906		1.251	0.760–1.940
Unknown	53 (8.1)
ER Status
ER Positive	326 (50.1)	1.000		0.308	1.000		0.031	1.000		0.101
ER Negative	289 (44.4)	0.903	0.740–1.097		1.521	1.037–2.231		1.380	0.939–2.029
Unknown	36 (5.5)
PR Status
PR Positive	302 (46.4)	1.000		0.433	1.000		0.202	1.000		0.395
PR Negative	294 (45.2)	0.929	0.769–1.114		1.253	0.886–1.771		1.165	0.819–1.657
Unknown	55 (8.4)
HER2 Status
HER2 Positive	109 (16.7)	1.000		0.020	1.000		0.067	1.000		0.102
HER2 Negative	495 (76.0)	1.292	1.041–1.586		0.675	0.443–1.029		0.704	0.461–1.073
Unknown	47 (7.2)
MAP-tau Expression
MAP-tau Low Expression	376 (57.8)	1.000		0.018	--	--	--	--	--	--
MAP-tau High Expression	104 (16.0)	0.765	0.598–0.957		--	--	--	--	--	--
Other	171 (26.3)
Stathmin Expression
Stathmin Low Expression	198 (30.4)	--	--	--	1.000		0.0150	--	--	--
Stathmin High Expression	276 (42.4)	--	--	--	1.566	1.091–2.248		--	--	--
Other	177 (27.2)
Ratio for MAP-tau to Stathmin
Low MAP-tau: High Stathmin	237 (36.4)	--	--	--	--	--	--	1.000		0.0081
High MAP-tau:Low Stathmin	237 (36.4)	--	--	--	--	--	--	0.609	0.422–0.879
Other	177 (27.2)

^*P is given for Cox multivariate analysis, statistically significant p values (p<0.05) are in boldface, trending p values are in italics; HR, hazard ratio; ER, estrogen receptor; PR, progesterone receptor; HER2, human epidermal growth factor receptor 2.

Prognostic value for the ratio of MAP-tau to stathmin in the Yale University Cohort

We have shown that high MAP-tau is associated with favorable outcome (see figure 2B). Since MAP-tau and stathmin play opposite but complimentary roles in tubulin stabilization, we assessed the ratio of MAP-tau to stathmin expression levels. The frequency distribution of ratio scores for MAP-tau to stathmin expression in our cohort showed mean and median AQUA scores of 13 and 7, respectively, with a ratio score range of 0.098–184 and is shown in figure 2D. The median ratio score of 7 was used as the cut-point to differentiate high MAP- tau/stathmin expressers from low MAP-tau/stathmin expressers (Table 1). Low MAP-tau/stathmin expression ratio correlated with premenopausal status, high nuclear grade, ER and PR negative status, and HER2 positive status.

Using Kaplan Meier survival analysis, patients with high MAP-tau/stathmin expression (n= 231) showed improved survival compared to those with low MAP-tau/stathmin expression (n= 237) (65.4% vs 52.5 %, respectively; log-rank, P = 0.0009; Figure 2C). When stratified by ER status, in ER+ patients, the MAP-tau ratio has no prognostic value. But in ER- patients, high MAP-tau/stathmin expression showed improved survival compared to ER- and low MAP-tau/stathmin expression (n=139; 66.1% vs 45.5%; log-rank, P = 0.009). When patients were stratified by HER2 status, improved survival with high MAP-tau:low stathmin expression was seen in both HER2 positive and negative subgroups.

In univariate analysis, high MAP-tau/stathmin expression ratio was associated with improved OS (HR = 0.679; 95% CI, 0.517 to 0.891, P= 0.0053, see Table 1). The ratio was also significant by multivariate analysis where patients with high MAP-tau/stathmin expression showed a hazard ratio of 0.609 (95% CI, 0.422 to 0.879, P = 0.008; Table 2).

As a destabilizing protein, we hypothesized that stathmin would have an inverse relationship to MAP-tau. Figure 3a shows that in normal breast tissue that is not seen. However, in breast tumors, shown in 3b, there are many cases with high stathmin and low MAP-tau and visa versa and they define a subset of cases with the hypothesized inverse relationship. However, there are also many cases that are low for both proteins and no inverse relationship is seen. Since these cases predominate, no statistically significant inverse relationship is seen when assessing the whole cohort.

Figure 3. Correlation between stathmin expression and MAP-tau expression in normal versus Yale Cohort breast tissue.

(A) Correlation between stathmin and MAP-tau expression AQUA scores in normal breast tissue showing no correlation. (B) Correlation between stathmin and MAP-tau expression AQUA scores in the Yale University Cohort suggesting an inverse correlation.

Discussion

Stathmin expression has been evaluated extensively in a variety of cell lines and has been correlated with prognosis using mRNA levels ^{2, 7, 29, 31}. However, only one small study using traditional IHC has evaluated stathmin protein expression with stathmin expression examined as a surrogate marker for a PTEN gene expression signature ³². In that study, Saal and colleagues found stathmin IHC staining scores were significantly higher in PTEN negative tumors than in PTEN positive tumors (P = 0.005) indicating that loss of the tumor suppressor PTEN (and subsequent activation of the oncogenic PI3K pathway) was associated with increased stathmin expression. In addition, high stathmin expressing patients experienced significantly worse distant disease free survival (DDFS) than low-stathmin expressing patients. Our current study confirms these results using a larger cohort.

Since entry and exit from mitosis requires the coordinated activity of both microtubule stabilizers and destabilizers, we hypothesized that a two-marker model would provide improved prognostic information for breast cancer patients not currently available through single-marker evaluation of either Map-tau or stathmin alone. Previous evaluation of MAP-tau in the Yale University cohort, provided an opportunity to generate a combined tissue biomarker containing information from both a microtubule stabilizer and destabilizer. This analysis showed that the ratio of high MAP-tau: stathmin is prognostic for improved survival in breast cancer patients. When the evaluation of MAP-tau is compared to the expression levels of stathmin, an inverse relationship is seen in a subset of the cases. When combined as a ratio, the combined variable is more prognostic that either variable alone, although the improvement is not statistically significantly better.

A key limitation of this work is the lack of a taxane-treated cohort in which to assess the predictive power of either stathmin or the MAP-tau/stathmin ratio for response to taxane therapy. Although we were able to access a taxane trial to which showed no predictive value for MAP-tau(Baquero et al, in press), the tissue from that cohort is exhausted. Other cohorts are being sought to investigate stathmin and other variables related to microtubule stability.

Due to varying response rates to taxanes in breast cancer patients and significant adverse effects, a method to predict response to these chemotherapeutic agents is desirable. Currently, no diagnostic test is recommended to differentiate patients who would benefit from taxane therapy from those who could avoid its potential cytotoxic effects. Recently, Beta III tubulin was assessed as a candidate companion diagnostic test, but has not proven valuable after disappointing clinical trial results ^{38, 39, 40} However, a new and promising marker, TLE3 (transducin-like enhancer of split 3), is now being assessed for usefulness in selecting patients that respond to taxanes. Data in single institutional studies in both lung and ovarian cancer show that TLE3 levels correlate with response to therapy ^{41, 42}.

In summary, the present study uses a quantitative method to assess stathmin expression and finds a significant prognostic relationship with high stathmin expression associated with worse outcome in breast cancer patients. Furthermore, combining this work with previous quantitative assessments of MAP-tau allowed the construction of a novel tissue biomarker reflecting opposite but complimentary cellular roles for MAP-tau and stathmin. In our analysis, the ratio of MAP-tau to stathmin expression was associated with improved overall survival and showed greater prognostic magnitude than either marker examined individually. Future efforts to test this ratio for predictive value in anti-microtubule treated patients are indicated.