Reconstructing tumor history in breast cancer: signatures of mutational processes and response to neoadjuvant chemotherapy⋆

BACKGROUND

Different endogenous and exogenous mutational processes act over the evolutionary history of a malignant tumor, driven by abnormal DNA editing, mutagens or age-related DNA alterations, among others, to generate the specific mutational landscape of each individual tumor. The signatures of these mutational processes can be identified in large genomic datasets. We investigated the hypothesis that genomic patterns of mutational signatures are associated with the clinical behavior of breast cancer, in particular chemotherapy response and survival, with a particular focus on therapy-resistant disease.

PATIENTS AND METHODS

Whole exome sequencing was carried out in 405 pretherapeutic samples from the prospective neoadjuvant multicenter GeparSepto study. We analyzed 11 mutational signatures including biological processes such as APOBEC-mutagenesis, homologous recombination deficiency (HRD), mismatch repair deficiency and also age-related or tobacco-induced alterations.

RESULTS

Different subgroups of breast carcinomas were defined mainly by differences in HRD-related and APOBEC-related mutational signatures and significant differences between hormone-receptor (HR)-negative and HR-positive tumors as well as correlations with age, Ki-67 and immunological parameters were observed. We could identify mutational processes that were linked to increased pathological complete response rates to neoadjuvant chemotherapy with high significance. In univariate analyses for HR-positive tumors signatures, S3 (HRD, P < 0.001) and S13 (APOBEC, P = 0.001) as well as exonic mutation rate (P = 0.002) were significantly correlated with increased pathological complete response rates. The signatures S3 (HRD, P = 0.006) and S4 (tobacco, P = 0.011) were prognostic for reduced disease-free survival of patients with chemotherapy-resistant tumors.

CONCLUSION

The results of this investigation suggest that the clinical behavior of a tumor, in particular, response to neoadjuvant chemotherapy and disease-free survival of therapy-resistant tumors, could be predicted by the composition of mutational signatures as an indicator of the individual genomic history of a tumor. After additional validations, mutational signatures might be used to identify tumors with an increased response rate to neoadjuvant chemotherapy and to define therapy-resistant subgroups for future therapeutic interventions.

A randomised phase II study investigating durvalumab in addition to an anthracycline taxane-based neoadjuvant therapy in early triple-negative breast cancer: clinical results and biomarker analysis of GeparNuevo study

BACKGROUND

Combining immune-checkpoint inhibitors with chemotherapy yielded an increased response rates in patients with metastatic triple-negative breast cancer (TNBC). Therefore, we evaluated the addition of durvalumab to standard neoadjuvant chemotherapy (NACT) in primary TNBC.

PATIENTS AND METHODS

GeparNuevo is a randomised phase II double-blind placebo-controlled study randomising patients with TNBC to durvalumab or placebo given every 4 weeks in addition to nab-paclitaxel followed by standard EC. In the window-phase durvalumab/placebo alone was given 2 weeks before start of nab-paclitaxel. Randomisation was stratified by stromal tumour-infiltrating lymphocyte (sTILs). Patients with primary cT1b-cT4a-d disease, centrally confirmed TNBC and sTILs were included. Primary objective was pathological complete response (pCR) (ypT0 ypN0).

RESULTS

A total of 174 patients were randomised, 117 participated in the window-phase. Median age was 49.5 years (range 23-76); 47 patients (27%) were younger than 40 years; 113 (65%) had stage ≥IIA disease, 25 (14%) high sTILs, 138 of 158 (87%) were PD-L1-positive. pCR rate with durvalumab was 53.4% (95% CI 42.5% to 61.4%) versus placebo 44.2% (95% CI 33.5% to 55.3%; unadjusted continuity corrected χ2P = 0.287), corresponding to OR = 1.45 (95% CI 0.80-2.63, unadjusted Wald P = 0.224). Durvalumab effect was seen only in the window cohort (pCR 61.0% versus 41.4%, OR = 2.22, 95% CI 1.06-4.64, P = 0.035; interaction P = 0.048). In both arms, significantly increased pCR (P < 0.01) were observed with higher sTILs. There was a trend for increased pCR rates in PD-L1-positive tumours, which was significant for PD-L1-tumour cell in durvalumab (P = 0.045) and for PD-L1-immune cell in placebo arm (P = 0.040). The most common immune-related adverse events were thyroid dysfunction any grade in 47%.

CONCLUSIONS

Our results suggest that the addition of durvalumab to anthracycline-/taxane-based NACT increases pCR rate particularly in patients treated with durvalumab alone before start of chemotherapy.

TRIAL REGISTRATION

ClinicalTrials.gov number: NCT02685059.

Abstract P3-10-01: Single-cell profiling identifies hypoxic carcinoma cells as source of an immunosuppressive VEGFA metagene

Background:

We have previously shown that expression of the IL8/VEGFA-metagene eliminates the good prognostic effect of TILs in TNBC (PMID 21978456, 28750120). We also showed that the VEGFA metagene predicted response to neoadjuvant bevacizumab in the GeparQuinto trial (Karn 2017 SABCS #851166). The main cellular sources of the transcripts that comprise the VEGFA metagene are unknown since mRNA profiling of bulk biopsies contains signals from different cell types.

Methods:

Individual genes that comprise the VEGFA metagene were measured in bulk tissue- and single cell-RNA-Seq from breast cancer subtypes and normal cells on different platforms (Affymetrix n=4915, Agilent n=597, Illumina n=2433, RNA-Seq n=1215, Exome Capture RNA-Seq n=226, HTG-Seq n=243, sc-RNA-Seq n=24710). For blinded, orthogonal validation we performed immunohistochemistry. Effect of neoadjuvant chemotherapy with or without bevacizumab was studied by RNA-Seq and IHC on samples from GeparQuinto trial. SWOG S0800 (GSE114403), PROMIX (GSE87455), and GeparSixto trials were used for validation. TCGA was mined for mutations and somatic CNA. RNA-Seq from GeparNuevo was used for correlation with checkpoint inhibitor treatment.

Results:

We identified a stable core of six genes (VEGFA, ANGPTL4, ADM, NDRG1, DDIT4, CSTB) in different cohorts. Strong expression of this signature was mainly restricted to TNBC subtype and associated with poor prognosis within this subgroup. Single cell RNA-Seq of breast epithelial cells from 4 reduction mammoplasties and 4 TNBC revealed that these genes are coexpressed in individual epithelial cells and not associated with endothelial cells. In line with their presumed functions in cellular stress and hypoxia, immunohistochemistry revealed strong para-necrotic expression in TNBC. Moreover, high gene expression in TNBC was associated with mutations in DNA damage control pathways, somatic copy number alterations, and lower TILs. While chemotherapy led to downregulation, bevacizumab increased expression. In multivariate analysis, high pretreatment values predict pCR to both bevacizumab and chemotherapy (OR 2.40, P=0.006), which may be explained by sensitivity of tumors which are already under cellular stress. On the other hand, expression of the VEGFA metagene seems to create an immunosuppressive environment that counteracts the positive prognostic effect of TILs. In pre-treatment biopsies from the GeparNuevo checkpoint inhibitor trial we found a negative correlation of VEGFA metagene expression with the amount of the recently identified tissue-resident memory T cell subset (CD8TRM, PMID 29942092; P=0.002), while the subsequent increase of CD8TRM during treatment was larger in tumors with high VEGFA (P=0.019).

Conclusions:

Perinecrotic carcinoma cells under stress from hypoxia and or chromosomal instability are the source of the VEGFA metagene signature. Its predictive value in TNBC suggests estimating and reporting the amount of necrosis in the pathology report may be helpful in predicting response to preoperative chemotherapy, and could be used as stratification factor in clinical trials. The signature indicates an immunosuppressive environment and should be further studied in the context of immune therapies in combinations with anti-angiogenic treatment.

Citation Format: Karn T, Denkert C, Sinn BV, Weber K, Nekljudova V, Rody A, Meissner T, Hatzis C, El-Balat A, Becker S, Solbach C, Untch M, Schneeweiss A, von Minckwitz G, Loibl S, Pusztai L, Holtrich U. Single-cell profiling identifies hypoxic carcinoma cells as source of an immunosuppressive VEGFA metagene [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-10-01.

Abstract PD5-05: Pre-therapeutic PD-L1 expression and dynamics of Ki-67 and gene expression during neoadjuvant immune-checkpoint blockade and chemotherapy to predict response within the GeparNuevo trial

Background

In the GeparNuevo trial, the PD-L1 inhibitor durvalumab increased the rate of pathologic complete response (pCR; ypT0 ypN0) in triple-negative breast cancer if treatment started in a two-week window before neoadjuvant taxane/anthracycline chemotherapy (61 % pCR vs. 41%; p = 0.048; Loibl et al. ASCO 2018). Overall, pCR rates increased only numerically from 53 % to 44 % (p = 0.281). Herein, we aimed to evaluate the predictive value of PD-L1 immunohistochemistry in pre-therapeutic core biopsies. In addition, we identified dynamics in gene expression using repeated biopsies.

Patients and Methods

174 patients were randomized to receive durvalumab or placebo with neoadjuvant chemotherapy. In the window part, 117 patients received a single dose of durvalumab (or placebo) before chemotherapy. Core biopsies were taken at three times: pre-treatment (“A”; N=174), after the window part (“B”; N=88) and after 12 weeks of nab-Paclitaxel (“C”; N=33). PD-L1 immunohistochemistry in A-biopsies (Ventana SP263 Assay) was recorded as percentage of cells with membranous staining in tumor cells and lymphocytes (TILs). We defined a tumor as PD-L1 high if ≥ 25 % of either compartment was stained. Ki-67 was stained on all available A, B and C biopsies (MIB-1, Dako, 1:100) and recorded as the percentage of tumor cells with nuclear staining. We profiled all available biopsies with targeted RNASeq using the HTG EdgeSeq platform (Oncology Biomarker panel, 2560 genes). Sequencing (IonTorrent S5) was successful in 162 A-, 79 B- and 31 C-biopsies.

Results

PD-L1 expression was high in 24 % of A-biopsies and was predictive for pCR in the complete cohort (OR 2.561; 1.183-5.554; p = 0.017). PD-L1 status of the TILs, but not of the tumor cells, was predictive (OR 1.313; 1.040-1.656; P= 0.022). The effect was not specific for durvalumab treatment. Higher levels of Ki-67 were predictive for pCR in B- biopsies in all patients (OR 1.399; 1.053-1.858; P =0.021) and in the placebo arm, but not in the durvalumab arm. Ki-67 levels in C-biopsies were not predictive; neither was the change in Ki-67 between pre-treatment and later time points (B vs. A or C vs. A).

In a differential mRNA expression analysis (A vs. B), we found seven differentially expressed genes after one dose of durvalumab. We observed strong effects on gene expression after taxane treatment (A vs. C), but no significant difference according to treatment. These genes were associated with biological processes involved in therapy response. The pre-treatment levels of 12 of 69 markedly differentially expressed genes were associated with worse response to chemotherapy.

Conclusion

In A-biopsies, PD-L1 in TILs was predictive for response, and in B-biopsies, Ki-67 was predictive, but neither marker could specifically predict response to durvalumab. We observed limited effects of a single half-dose of durvalumab on global gene expression, but could identify substantial differential expression after taxane treatment. The evaluation of gene expression dynamic offers a promising approach for the identification of resistance-associated markers.

The study was financially supported by AstraZeneca and Celgene

Citation Format: Sinn BV, Loibl S, Karn T, Untch M, Kunze CA, Weber KE, Treue D, Wagner K, Hanusch CA, Klauschen F, Fasching PA, Huober J, Zahm D-M, Jackisch C, Thomalla J, Blohmer J-U, van Mackelenbergh M, Rhiem K, Felder B, von Minckwitz G, Burchardi N, Schneeweiss A, Denkert C. Pre-therapeutic PD-L1 expression and dynamics of Ki-67 and gene expression during neoadjuvant immune-checkpoint blockade and chemotherapy to predict response within the GeparNuevo trial [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD5-05.

Abstract P4-08-20: Pre-analytical effects of FFPE extraction methods on targeted and whole transcriptome sequencing assays for endocrine sensitivity in metastatic breast cancer

Background: The clinical management of patients with metastatic HR-positive breast cancer is often uncertain due to decreased sensitivity to anti-estrogen therapy over time. Recently, we developed a targeted RNAseq based 18-transcript SET ER/PR assay of endocrine sensitivity from biopsies of metastatic cancer. In this work we assess the effect of pre-analytical factors, specifically RNA extraction methods for FFPE tissue samples, on the reliability of the targeted RNAseq assay.

Methods: FFPE blocks and matched fresh frozen (FF) sections from 12 tumors were collected at MD Anderson Cancer Center. RNA from FFPE slides was extracted in duplicate using three kits (Norgen, Qiagen, Roche), and RNAseq libraries from all samples were prepared using Kapa Total RNAseq kit. Targeted RNA libraries were prepared using droplet-based PCR (RainDance), and also by transcriptome-wide RNAseq for comparison. Reads were mapped to genomic sequence using STAR and expression was quantified using RSEM. Expression data were normalized based on expression of 10 reference genes. The effect of FFPE RNA extraction kit on the reliability of the SET index was assessed using linear mixed effects model (LME) analysis, and agreement with FF was assessed using the concordance correlation coefficient (CCC).

Results: Analysis of the whole transcriptome RNAseq data confirmed minimal 3'-end transcript bias from FFPE samples, irrespective of transcript size or FFPE kit. All 18 genes included in the SET index had high overall concordance between FFPE and FF (median CCC percentile=98.8, range 57.2-99.9 for Norgen; similar for the other two kits) and relatively consistent bias across genes, as estimated by the random effects of the LME model. Furthermore, compared to random 18-gene indices, concordance in the SET index values between FF and FFPE was higher than 99.8% of the random samples, verifying the analytical reliability of the selected genes. For the targeted RNAseq assay, RNA from FFPE extracted with the Norgen kit showed the highest concordance compared to FF (CCC=0.956, 95%CI 0.871-0.985). In general, the analytical variation of SET from FFPE samples was greater than that from FF (1.71-2.71 fold greater), with the lowest variation associated with the Norgen kit. The SET index values from targeted RNAseq for both FF and FFPE samples were consistently lower compared to transcriptome-wide RNAseq but were highly correlated, with the Norgen kit having the highest correlation between targeted and transcriptome-wide RNAseq (rho=0.915).

Conclusions: All three FFPE RNA extraction kits have excellent analytical performance compared to FF samples. The Norgen kit may be marginally better yielding higher concordance with FF and lower analytical variation between replicates. All genes in the SET ER/PR showed very good analytical performance in comparison to random indices and individual genes. Targeted gene RNA sequencing appears very promising as a platform for clinical deployment of quantitative assays, showing only a small (fixable) bias compared to RNAseq.

Citation Format: Marczyk M, Fu C, Lau R, Du L, Trevarton AJ, Sinn BV, Gould RE, Symmans WF, Hatzis C. Pre-analytical effects of FFPE extraction methods on targeted and whole transcriptome sequencing assays for endocrine sensitivity in metastatic breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-08-20.

Abstract PD2-07: mRNA signatures predict response to durvalumab therapy in triple negative breast cancer (TNBC)– Results of the translational biomarker programme of the neoadjuvant double-blind placebo controlled GeparNuevo trial

Background: The GeparNuevo trial showed a numerical increase in the pCR rate to 53% vs 44%; p=0.281 compared to placebo in TNBC with the addition of the anti-PD-L1 antibody durvalumab to a neoadjuvant anthracycline-taxane containing chemotherapy (Loibl S et al. ASCO 2018). In a predefined subgroup analysis, a significant increase of the pCR rate was observed for patients that received durvalumab for 2 weeks alone prior to the start of chemotherapy in a window phase (61% vs 41%, p interaction=0.048), while the pCR rate was not increased for the subset of patients that did start durvalumab together with chemotherapy.

Here we report the main results of the translational programme for GeparNuevo with a focus on mRNA signatures predictive for pCR in pretherapeutic core biopsies.

Methods: A total of 162 baseline FFPE core biopsies were evaluable for expression of 2560 genes using the HTG EdgeSeq® system that combines a modified nuclease protection assay with next generation sequencing. Data was processed as recommended by the HTG and median transformed for further analyses. For differential gene expression analyses, the data was scale-normalized (TMM normalization; EdgeR package) and linear models were fit (limma package). Prior to these analyses, genes were filtered based on minimal expression (&gt; 4) and variability (IQR &gt; 1). As a first step, predefined immune-genes signature (TILs signature) (Denkert et al. JCO 2016) as well as IFN-gamma signatures were evaluated for correlation with pCR in logistic regression models. Subsequently, we performed a differential gene expression analysis according to therapy response for the durvalumab-arm and the placebo arm using the pre-filtered candidate genes. Gene names are not included in this abstract to allow filing of IP, but full gene names will be presented at the SABCS meeting.

Results: The predefined TIL- and IFN-gamma signatures were associated with increased pCR rates in the complete cohort (TIL-signature: OR 1.44, 95% CI 1.15-1.82, p=0.002; IFN-Gamma-signature: OR 1.63, 95% CI 1.22-2.24, p=0.002) as well as in the durvalumab arm (p=0.012 and 0.042) and the placebo arm (p=0.050 and 0.011). These signatures were general pCR predictors without specificity for durvalumab response.

Additional 44 genes were significantly (p&lt;0.05) correlated with pCR in the durvalumab arm. Of those, 21 genes were upregulated and 23 genes were downregulated in pCR patients. 14 of the 21 upregulated genes are related to tumorbiologically relevant immune cell functions. A total of 6 of the 44 genes had a positive test for interaction (interaction p&lt;0.05) with the therapy arm (durvalumab + NACT vs. placebo + NACT), suggesting that these genes might specifically predict response to durvalumab. Additional analyses investigating the role of molecular tumor subtypes, additional immune gene signatures and other subgroup analyses will be presented at the meeting.

Conclusion: Our results show that specific immune-related gene expression signatures predict response to durvalumab in primary triple negative breast cancer.

The trial was financially supported by Astra Zeneca and Celgene

Citation Format: Loibl S, Sinn BV, Karn T, Untch M, Treue D, Sinn H-P, Weber KE, Hanusch CA, Fasching PA, Huober J, Zahm D-M, Jackisch C, Thomalla J, Blohmer J-U, Marmé F, Klauschen F, Rhiem K, Felder B, von Minckwitz G, Burchardi N, Schneeweiss A, Denkert C. mRNA signatures predict response to durvalumab therapy in triple negative breast cancer (TNBC)– Results of the translational biomarker programme of the neoadjuvant double-blind placebo controlled GeparNuevo trial [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD2-07.

Abstract P1-07-01: HLA class I expression is associated with tumor-infiltrating lymphocytes and response and survival after neoadjuvant chemotherapy in hormone receptor-positive, HER2-negative breast cancer

Background: Interactions between cancer cells and the host immune system influence tumor biology, response to therapy and patient survival and their modulation offers promising new approaches for cancer therapy. The downregulation or loss of HLA class I expression in breast cancer cells might be an effective mechanism to evade the recognition by the immune system facilitating malignant behavior.

Aim: To evaluate the association of tumor-infiltrating lymphocytes (TILs) with HLA class I expression and its theranostic value for therapy response and survival after neoadjuvant chemotherapy.

Methods: HLA class I expression was evaluated by immunohistochemistry in a cohort of 732 pre-therapeutic core biopsies from breast cancer patients treated within the neoadjuvant GeparTrio trial. Patients received anthracycline- and taxane-based neoadjuvant therapy and adjuvant endocrine treatment if hormone receptor-positive (HR+). A publicly available microarray dataset of pre-therapeutic core biopsies from 508 breast cancer patients that received neoadjuvant chemotherapy and endocrine treatment if HR+ was used for validation of the results. The association of HLA class I expression with predefined genomic signatures for immune cell populations was evaluated in publicly available data from the cancer genome atlas.

Results: HLA class I expression was associated with TILs (p &lt; 0.001) and was predictive of better response to neoadjuvant chemotherapy in the subgroup of patients with HR+/HER2- breast cancer (14 % in tumors with high HLA vs. 7 % in tumors with low HLA, p = 0.029). Interestingly, high HLA was also predictive for shorter progression-free survival in univariate analysis (HR 1.590, 95 % CI 1.062—2.380; p = 0.024) and after adjustment to clinical and pathological parameters (HR 1.701, 95 % CI 1.105—2.618; p = 0.016). The results could be validated in the independent microarray-based dataset (HR 1.521, 95% CI 1.088 – 2.129; p = 0.0142). HLA class I was not associated with therapy response or survival in hormone receptor-negative breast cancer. HLA class I was associated with a predefined signature for T-cells and cytotoxic T- cells in the cancer genome atlas dataset (rho = 0.546).

Conclusion: HLA class I expression is associated with better response but shorter progression-free survival in HR+/HER2- breast cancer following neoadjuvant chemotherapy. The underlying mechanisms warrant further investigation.

Citation Format: Sinn BV, Weber K, Denkert C, Fasching PA, Schmitt WD, Thomas K, Ingold-Heppner B, van Mackelenbergh M, Symmans WF, Marmé F, Taube E, Müller V, Kunze CA, Schem C, Pfitzner BM, Stickeler E, von Minckwitz G, Loibl S. HLA class I expression is associated with tumor-infiltrating lymphocytes and response and survival after neoadjuvant chemotherapy in hormone receptor-positive, HER2-negative breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P1-07-01.

Abstract P6-09-23: SETER/PR - A robust 18-gene predictor of sensitivity to endocrine therapy in metastatic breast cancer

Rationale: A robust index for gene expression related to activity of estrogen (ESR1) and progesterone (PGR) receptors could predict sensitivity to endocrine therapy in metastatic breast cancer.

Methods: Transcripts correlated with ESR1 and PGR expression in 389 hormone receptor-positive breast cancer samples (Affymetrix U133A microarrays) were ranked for reliability according to their pre-analytical (intratumoral heterogeneity, biopsy type) and analytical reproducibility. Eighteen target and ten reference genes were selected and summarized as the SETER/PR index. The SETER/PR index was evaluated in a different set of 140 biopsies from distant metastases of hormone receptor-positive and HER2-negative (HR+/HER2-) breast cancer, and in additional pre-analytical and analytical sample cohorts. Thereafter, SETER/PR was translated to a customized format for application to formalin-fixed and paraffin-embedded (FFPE) sections.

Results: Higher SETER/PR in a metastasis was associated with longer progression-free survival (PFS, 9 vs. 2 months) and overall survival (OS, 50 vs. 19 months) following endocrine therapy in the cohort with metastatic breast cancer (MBC) and relapsed disease (n=79), so a cut point was defined in that cohort. SETER/PR was also significantly associated with PFS after adjusting for PR status of the metastasis, presence of visceral metastases, number of previous relapse events, and clinical history of previous sensitivity to endocrine therapy (HR 0.485, 95%CI 0.265 – 0.889, p = 0.019). Technically, SETER/PR was highly reproducible under different pre-analytical and analytical conditions, including host organ contamination. The translated SETER/PR assay used a single 10 µm FFPE tissue section, did not require RNA purification, and represented the microarray results from matched fresh samples with excellent agreement (correlation = 0.980, n = 31).

Conclusion: The SETER/PR index is a new biomarker to predict PFS and OS for patients with HR+/HER2- MBC who receive endocrine therapy. The assay is applicable to FFPE tissue sections from small biopsies of metastases. Additional independent (blinded) validation studies will be necessary to confirm these results.Rationale: A robust index for gene expression related to activity of estrogen (ESR1) and progesterone (PGR) receptors could predict sensitivity to endocrine therapy in metastatic breast cancer.

Methods: Transcripts correlated with ESR1 and PGR expression in 389 hormone receptor-positive breast cancer samples (Affymetrix U133A microarrays) were ranked for reliability according to their pre-analytical (intratumoral heterogeneity, biopsy type) and analytical reproducibility. Eighteen target and ten reference genes were selected and summarized as the SETER/PR index. The SETER/PR index was evaluated in a different set of 140 biopsies from distant metastases of hormone receptor-positive and HER2-negative (HR+/HER2-) breast cancer, and in additional pre-analytical and analytical sample cohorts. Thereafter, SETER/PR was translated to a customized format for application to formalin-fixed and paraffin-embedded (FFPE) sections.

Results: Higher SETER/PR in a metastasis was associated with longer progression-free survival (PFS, 9 vs. 2 months) and overall survival (OS, 50 vs. 19 months) following endocrine therapy in the cohort with metastatic breast cancer (MBC) and relapsed disease (n=79), so a cut point was defined in that cohort. SETER/PR was also significantly associated with PFS after adjusting for PR status of the metastasis, presence of visceral metastases, number of previous relapse events, and clinical history of previous sensitivity to endocrine therapy (HR 0.485, 95%CI 0.265 – 0.889, p = 0.019). Technically, SETER/PR was highly reproducible under different pre-analytical and analytical conditions, including host organ contamination. The translated SETER/PR assay used a single 10 µm FFPE tissue section, did not require RNA purification, and represented the microarray results from matched fresh samples with excellent agreement (correlation = 0.980, n = 31).

Conclusion: The SETER/PR index is a new biomarker to predict PFS and OS for patients with HR+/HER2- MBC who receive endocrine therapy. The assay is applicable to FFPE tissue sections from small biopsies of metastases. Additional independent (blinded) validation studies will be necessary to confirm these results.

Citation Format: Sinn BV, Tsai T-H, Lau R, Fu C, Gould R, Murthy R, King TA, Hatzis C, Kwiatkowski DN, Valero V, Symmans WF. SETER/PR - A robust 18-gene predictor of sensitivity to endocrine therapy in metastatic breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P6-09-23.

Human equilibrative nucleoside transporter 1 expression analysed by the clone SP 120 rabbit antibody is not predictive in patients with pancreatic cancer treated with adjuvant gemcitabine - Results from the CONKO-001 trial

BACKGROUND

High expression of human equilibrative nucleoside transporter 1 (hENT1) is considered to predict survival in patients treated with adjuvant gemcitabine for pancreatic cancer. A standard evaluation system for immunohistochemical analysis (antibody, scoring system) has not yet been established.

METHODS

CONKO-001, a prospective randomised phase III study investigated the role of adjuvant gemcitabine (gem) as compared to observation (obs). Tumour samples of 156 patients were analysed by immunohistochemistry with the rabbit monoclonal antibody SP120 (Ventana Medical Systems) for expression of hENT1. Kaplan-Meier analyses for median disease-free survival (DFS) and overall survival (OS) were performed in dependence of hENT1 expression measured analogously to Farrell et al. 2009 and Poplin et al. 2013.

RESULTS

For the 88 gem and 68 obs patients, median DFS/OS was 12.9/22.7 months and 6.2/19.1 months. High hENT1 expression was not associated with improved median DFS (Farrell: no hENT1 22.2 months, low hENT1 13.7 months, high hENT1 12.1 months, p=0.248; Poplin: low hENT1 13.2 months versus high hENT1 11.5 months, p=0.5) or median OS (Farrell: no hENT1 21.7 months, low hENT1 24.7 months, high hENT1 19.5, p=0.571; Poplin: low hENT1 24.4 months versus high hENT1 19.7 months, p=0.92;) in the gem group or in the obs group (median DFS Farrell: no hENT1 5.1 months, low hENT1 6.2 months, high hENT1 7.5 months, p=0.375; Poplin: low hENT1 6.2 months versus high hENT1 5.9 months, p=0.83; median OS Farrell: no hENT1 20.2months, low hENT1 17.7 months, high HENT1 19.1 months, p=0.738; Poplin: low hENT1 17.7 months versus high hENT1 20.4 months, p=0.65) measured by the Farrell or Poplin Score.

CONCLUSIONS

We cannot confirm a predictive role of hENT1 measured by the clone SP120 rabbit antibody in our study population. Reproducible standard procedures are urgently needed prior to the implementation or exclusion of hENT1 as a predictive biomarker in the treatment of pancreatic cancer.

TRIAL REGISTRATION

ISRCTN34802808.

Expression of secreted protein acidic and rich in cysteine (SPARC) in breast cancer and response to neoadjuvant chemotherapy

BACKGROUND

Secreted protein acidic and rich in cysteine (SPARC) has been suggested as a new biomarker and therapeutic target in breast cancer, as well as other tumor types.

PATIENTS AND METHODS

We evaluated the frequency of SPARC expression among different molecular breast cancer subtypes and its role for therapy response after neoadjuvant chemotherapy. In this study, pretherapeutic core biopsies of 667 patients from the neoadjuvant GeparTrio trial were evaluated for SPARC expression by immunohistochemistry using a standardized immunoreactive score (IRS).

RESULTS

An increased SPARC expression (IRS ≥6) was observed in 26% of all tumors. In triple-negative tumors, SPARC expression was increased in 37% of tumors, compared with other molecular subtypes (23% HR+/HER2-, 29% HR+/HER2+ and 22% HR-/HER2+; P = 0.038). Increased SPARC expression was associated with an increased pathological complete response (pCR) rate of 27%, compared with 15% in tumors with low SPARC expression (P < 0.001). In the triple-negative subgroup, pCR rates were 47% in tumors with high SPARC expression, compared with 26% in tumors with low SPARC expression (P = 0.032). In multivariable analysis, SPARC was independently predictive in the overall population (P = 0.010) as well as the triple-negative subgroup (P = 0.036).

CONCLUSIONS

SPARC is frequently expressed in breast cancer with triple-negative breast cancer revealing the highest expression rate. High SPARC expression of the primary tumor is associated with a higher chance of achieving a pathological complete remission after TAC or TAC-NX chemotherapy. As SPARC is an albumin-binding protein and might mediate intratumoral accumulation of albumin bound drugs, SPARC should be further evaluated as a predictive marker especially for response to albumin-bound drugs like nab-paclitaxel.

CLINICAL TRIAL NUMBER

NCT00544765.

SPARC expression in resected pancreatic cancer patients treated with gemcitabine: results from the CONKO-001 study

BACKGROUND

Previous investigations in pancreatic cancer suggested a prognostic role for secreted protein acidic and rich in cysteine (SPARC) expression in the peritumoral stroma but not for cytoplasmic SPARC expression. The aim of this study was to evaluate the impact of SPARC expression in pancreatic cancer patients treated with gemcitabine compared with untreated patients.

PATIENTS AND METHODS

CONKO-001 was a prospective randomized phase III study investigating the role of adjuvant gemcitabine when compared with observation. Tissue samples of 160 patients were available for SPARC immunohistochemistry on tissue microarrays to evaluate its impact on patient outcome.

RESULTS

Strong stromal SPARC expression was associated with worse disease-free survival (DFS) and overall survival (OS) in the overall study population (DFS: P = 0.005, OS: P = 0.033). Its negative prognostic impact was restricted to patients treated with gemcitabine (DFS: P = 0.007, OS: P = 0.006). High cytoplasmic SPARC expression also was associated with worse patient outcome (DFS: P = 0.041, OS: P = 0.011). Again the effect was restricted to patients treated with gemcitabine (DFS: P = 0.002, OS: P = 0.003). In multivariable analysis, SPARC expression was independently predictive of patient outcome.

CONCLUSIONS

Our data confirm the prognostic significance of SPARC expression after curatively intended resection. The negative prognostic impact was restricted to patients who received adjuvant treatment with gemcitabine, suggesting SPARC as a predictive marker for response to gemcitabine.

Evaluation of Mucin-1 protein and mRNA expression as prognostic and predictive markers after neoadjuvant chemotherapy for breast cancer

BACKGROUND

Mucin-1 (MUC1) is a promising antigen for the development of tumor vaccines. We evaluated the frequency of MUC1 expression and its impact on therapy response and survival after neoadjuvant chemotherapy for breast cancer.

PATIENTS AND METHODS

Pre-treatment core biopsies of patients from the GeparTrio neoadjuvant trial (NCT 00544765) were evaluated for MUC1 by immunohistochemistry (IHC; N = 691) and quantitative RT-PCR (qRT-PCR; N = 286) from formalin-fixed paraffin-embedded (FFPE) samples.

RESULTS

MUC1 protein and mRNA was detectable in the majority of cases and was associated with hormone-receptor-positive status (P < 0.001). High MUC1 protein and mRNA expression were associated with lower probability of pathologic complete response (P = 0.017 and P < 0.001) and with longer patient survival (P = 0.03 and P < 0.001). In multivariable analysis, MUC1 protein and mRNA expression were independently predictive (P = 0.001 and P < 0.001). MUC1 protein and mRNA expression were independently prognostic for overall survival (P = 0.029 and P = 0.015).

CONCLUSIONS

MUC1 is frequently expressed in breast cancer and detectable on mRNA and protein level from FFPE tissue. It provides independent predictive information for therapy response and survival after neoadjuvant chemotherapy. In clinical immunotherapy trials, MUC1 expression may serve as a predictive marker.