Currently, decisions to systemically treat cancer patients are generally based on clinical and pathological factors, such as age, tumor size and lymph node status.
These factors mostly predict the chance of patients to develop metastasis and subsequently whether they are in need of systemic treatment (prognostic factors).
The type and class of systemic treatment depends per tumor type on large clinical trials performed in a general cancer population.
However, these trials do not take into account the heterogeneity of tumors within one cancer type and subsequently the heterogeneity of response in individual patients.
Unfortunately, there are still few factors known which are able predict which specific systemic treatment suits an individual patient best (predictive factors).
For breast cancer, causing most cancer deaths in women in the Western world, predictive factors can be counted on one hand.
Hormone receptor status and HER2-receptor status are used to select patients for either hormonal treatment or trastuzumab treatment, respectively.
However, for the most frequently used systemic therapy, namely chemotherapy, predictive factors remain elusive. Furthermore, even the predictive factors currently used could be improved.
The aim of the project is to identify factors and methods that predict response to systemic therapy in breast cancer patients.
1. Predictive markers for platinum-based high dose alkylating chemotherapy in breast cancer patients
2. Characterization of potential therapeutic targets in lobular breast cancer
Predictive markers for platinum-based high dose alkylating chemotherapy
Background: Maintenance of DNA integrity depends on homologous recombination, a conservative mechanism for error-free repair of double strand breaks (DSB). When homologous recombination is absent, alternative error-prone mechanisms such as non-homologous end joining are invoked, leading to genomic instability. This instability is thought to predispose to familial cancers in patients carrying mutations in genes which are involved in homologous recombination, for example BRCA1 or BRCA2. Another hallmark of cells with homologous recombination deficiency (HRD) is their hypersensitivity to alkylating agents that form DNA cross-links and subsequently result in irreparable DSBs in DNA. In sporadic, non-BRCA mutated breast cancers HRD has also been reported (‘BRCAness’) and might be present in up to 35% of all breast cancers. Unfortunately, so far we can not recognize these sporadic variants of HRD in breast cancer. It has been suggested that Comparative Genomic Hybridization (CGH) can be useful in identifying the genomic instability inherent to HRD tumours by visualizing the copy number aberrations (CNAs). In our institute a BRCA1 CGH classifier (BRCA1-profile) was constructed using the characteristic CNAs of BRCA1-mutated breast tumours in BRCA1 germ-line carriers.
Preliminary results: We screened 40 tumors of metastatic breast cancer patients who had been treated with platinum containing, high-dose alkylating chemotherapy for the presence of this BRCA1-profile and for the majority of BRCA1 and BRCA2 mutations present in Dutch BRCA1 and BRCA2 families. We found that sixteen patients had a tumor with a BRCA1-profile. These patients had a better response to alkylating chemotherapy, defined by achievement of a complete remission (p=0.01) and longer progression free survival (unadjusted hazard ratio 0.30, 95%CI: 0.14-0.64, p=0.002, adjustment did not substantially modify the hazard ratio). Moreover, all six patients who remained in continuous complete remission (55+ to 146+ months) had a tumor with a BRCA1-profile. Only two BRCA1 and two BRCA2 mutations were found in 4 patients of whom 3 had a BRCA1-profile. Furthermore we found that BRCA1-like tumors showed an expansive growth pattern through the microscope, were generally HER2-receptor negative and estrogen receptor (ER) negative.
First Aim: To further investigate whether BRCA1-like tumors are chemosensitive in general, or are sensitive specifically to alkylating chemotherapy, we studied outcome of breast cancer patients with at least 4 metastases in the lymph nodes who had participated in a randomized trial of adjuvant conventional chemotherapy versus adjuvant conventional chemotherapy plus one time alkylating chemotherapy.
Our previous project focuses mainly on patients with ER-negative tumors. However, approximately ~70% of the breast cancer patients have an ER-positive tumor. Furthermore, homologous recombination deficiency is not restricted to patients with ER-negative tumors, as 65% of the patients with a BRCA2-mutation have an ER-positive tumor (similar frequencies as sporadic tumors).
Second Aim: To investigate whether a BRCA2-like aCGH classifier can predict response to platinum-based high dose alkylating chemotherapy in breast cancer patients.
Characterization of potential therapeutic targets in lobular breast cancer
Background: Of all breast cancer patients 10-15% will have a lobular subtype which is based upon the histology. This subtype seems to be a different molecular entity since they are more often estrogen and progesterone positive and they virtually always show a loss of E-cadherin. Recently gene expression arrays found differentially expressed genes between ductal and lobular breast cancer. Such studies suggest that lobular tumors develop and progress via a distinct pathway from ductal tumors. Nevertheless, treatment for lobular breast cancer is similar to ductal breast carcinomas, although interesting differences between these tumor subtypes are seen in pathological complete remission (pCR) rates to neoadjuvant chemotherapy. Lobular breast cancer patients seem relatively resistant to anthracycline based chemotherapy, with a pCR rate in the neoadjuvant setting of only 3% compared to 15% in ductal carcinomas. These findings suggest that lobular breast cancer patients do not benefit as much from (neoadjuvant) chemotherapy and that alternative systemic treatment should be looked for.
Aim: To identify the pathways that drive lobular breast cancer, in order to be able to select alternative systemic treatments targeting these pathways.
Methods: We will analyze gene expression profiles of 100 untreated ILC patients and will use 2 methods of analyses. First we will try to find different subsets with unsupervised clustering and examine whether these clusters also have a prognostic influence (as with the well known Perou subtypes, but then for specifically for lobular breast cancer) and identify the pathways responsible for this clustering. If this fails, we can use supervised clustering based on outcome (recurrence versus none) and look for pathways in this analysis. Identified pathways (i.e. treatment) can be studied in gene expression datasets of the cell lines derived from the Kcre;Cdh1flox/flox;p53flox/flox conditional mouse model and tumors from the models.