Literature DB >> 23825533

Triple negative breast cancers have a reduced expression of DNA repair genes.

Enilze Ribeiro1, Monica Ganzinelli, Daniele Andreis, Ramona Bertoni, Roberto Giardini, Stephen B Fox, Massimo Broggini, Alberto Bottini, Vanessa Zanoni, Letizia Bazzola, Chiara Foroni, Daniele Generali, Giovanna Damia.   

Abstract

DNA repair is a key determinant in the cellular response to therapy and tumor repair status could play an important role in tailoring patient therapy. Our goal was to evaluate the mRNA of 13 genes involved in different DNA repair pathways (base excision, nucleotide excision, homologous recombination, and Fanconi anemia) in paraffin embedded samples of triple negative breast cancer (TNBC) compared to luminal A breast cancer (LABC). Most of the genes involved in nucleotide excision repair and Fanconi Anemia pathways, and CHK1 gene were significantly less expressed in TNBC than in LABC. PARP1 levels were higher in TNBC than in LABC. In univariate analysis high level of FANCA correlated with an increased overall survival and event free survival in TNBC; however multivariate analyses using Cox regression did not confirm FANCA as independent prognostic factor. These data support the evidence that TNBCs compared to LABCs harbour DNA repair defects.

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Year:  2013        PMID: 23825533      PMCID: PMC3692506          DOI: 10.1371/journal.pone.0066243

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Triple negative breast cancer (TNBC) defines a clinical subset of breast cancer negative for estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor type 2 (HER2). It accounts for about 15% of breast tumors and is characterized by an aggressive clinical course with therapeutic resistance, high rates of local and systemic relapse, and poor survival. This is probably due to the intrinsic biology of this type of tumor as well as to the absence of specific targeted treatments such as hormonal therapy used for ER positive tumors and trastuzumab/lapatinib for HER2 over-expressing tumors [1], [2]. TNBC encompasses more than one subtype [3], [4]. Morphologically they include metaplastic, adenoid cystic and medullary like and at a molecular level they display different mRNA profiles such as basal and claudin type [5], [6]. Cumulating evidence suggest that the triple negative phenotype on clinical assays enriches for basal-like cancer, but no complete overlap exists between the two groups [7], [8]. Indeed, 25% of the TNBCs are not basal-like on gene expression profile and similarly there are basal-like tumors that are not triple negative by immunohistochemistry. Most of the tumors that develop in women with germline mutations in the BRCA1 breast cancer susceptibility gene are TNBC [9], [10]. BRCA1 has a crucial role in the repair of double-strand breaks and its mutation leads to cancer predisposition and genomic instability [11], [12]. BRCA1 related TNBCs share several pathological features with sporadic TNBCs and cluster within the basal subtype by gene expression profile [13]. Thus it is not surprising that there are data suggesting that a proportion of sporadic basal-like breast cancers may have a dysfunctional BRCA1 pathway, due to gene promoter methylation or transcriptional inactivation [13], [14]. Deficits in other DNA-repair pathways, such as base excision repair (BER) inactivation [15], MTMG promoter methylation [16] and lack of hOGG1 [17] have been reported in TNBCs. These tumors also exhibit higher DNA copy alterations and loss of heterozygosity than other breast cancer types, suggesting higher genomic instability [18]–[20]. These latter data, together with the reported association between BRCA1 deficiency and TNBC, suggest that DNA repair alterations may be important for the development of this tumor type. If this is the case, there could have important prognostic and predictive implications, such as the response to the currently used anticancer agents and to novel targeted agents, as the poly-ADP-ribose polymerase (PARP) inhibitors [21]. While tests for the evaluation of DNA repair defects in primary cells or in clinical samples have been described [22], [23], to our knowledge validated functional assays for the quantification of the tumor DNA repair capabilities to be used in clinical setting do not exist. There are however some biomarkers that, even if not completely validated [24]–[27], have been used as surrogate of DNA repair functionality, i.e. the mRNA and/or expression levels of key proteins involved in DNA repair pathways. Aim of our study was to evaluate in a multiparametric manner the mRNA expression level of different key player of DNA repair pathways (i.e. base excision repair-BER-, nucleotide excision repair-NER- and homologous recombination- HR- and Fanconi anemia- FA) in TNBCs compared with LABCs and to correlate with clinico-pathological patient characteristics.

Materials and Methods

Patients and samples

150 formalin-fixed paraffin embedded core breast cancer samples, diagnosed as triple negative (80 cases) and luminal A (70 cases), were retrospectively collected from patients who came to the medical observation at the Breast Care Unit, A.O. Istituti Ospitalieri di Cremona, Italy. Ethical permission for the study was obtained from the A.O. Istituti Ospitalieri di Cremona (Italy) ethical committee. Written informed consent was obtained from patients, if applicable. All the samples were anonymized by a pathologist staff member and none of the researcher conducting the gene expression analysis had access to disclosed clinico-pathological data. The patients characteristics are summarized in Table 1.
Table 1

Baseline patients' demographic.

CLINICAL PARAMETERSTNBC (N = 80)LABC (N = 70)
Follow-up time – years
Median (range)5.5 (0.1–16.0)3.16 (0.6–17.3)
Mean ± SD6.7±4.75.9±5.5
Age – years
Median (range)59.5 (33.1–91.3)66.6 (36.5–84.5)
Mean ± SD60.2±14.463.1±11.5
Age – no. (%)
<6546 (57.5)31 (44.3)
≥6534 (42.5)39 (55.7)
Menopausal status – no. (%)
Pre-19 (23.7)12 (17.1)
Post-59 (73.8)58 (82.9)
not known2 (2.5)0 (0.0)
Clinical tumor size – no. (%)
≤20 mm16 (20.0)21 (30.0)
>20 mm36 (45.0)12 (17.1)
not known28 (35.0)37 (52.9)
Tumor size at surgery – no. (%)
≤20 mm36 (45.0)42 (60.0)
>20 mm22 (27.5)11 (15.7)
not known22 (27.5)17 (24.3)
Pathological T staging – no. (%)
T141 (51.3)48 (68.6)
T220 (25.0)11 (15.7)
T32 (2.5)1 (1.4)
T44 (5.0)3 (4.3)
not known13 (16.2)7 (10.0)
Pathological N staging – no. (%)
N037 (46.3)66 (94.3)
N+18 (22.5)0 (0.0)
not known25 (31.2)4 (5.7)
Metastatic status – no. (%)
M060 (75.0)68 (97.1)
M14 (5.0)0 (0.0)
not known16 (20.0)2 (2.9)
Pathological staging – no. (%)
Stage I28 (35.0)48 (68.6)
Stage IIA13 (16.3)11 (15.7)
Stage IIB5 (6.2)1 (1.4)
Stage IIIA4 (5.0)0 (0.0)
Stage IIIB4 (5.0)3 (4.3)
Stage IV4 (5.0)0 (0.0)
not known22 (27.5)7 (10.0)
Basal histotype – no. (%)
IDC66 (82.5)23 (32.9)
ILC5 (6.2)16 (22.9)
Other7 (8.8)30 (42.8)
not known2 (2.5)1 (1.4)
Basal tumor grade – no. (%)
11 (1.2)6 (8.6)
214 (17.5)47 (67.1)
364 (80.1)15 (21.4)
not known1 (1.2)2 (2.9)
Basal Ki67 – no. (%)
Median (range)37 (3–90)7.5 (1–16)
Mean ± SD44.6±26.47.3±3.3
<103 (3.7)50 (71.4)
≥1075 (93.8)20 (28.6)
<2015 (18.7)70 (100.0)
≥2063 (78.8)0 (0.0)
not known2 (2.5)0 (0.0)
Neoadjuvant treatment – no. (%)
Done35 (43.8)19 (27.2)
not done38 (47.5)50 (71.4)
not known7 (8.7)1 (1.4)
Surgical treatment – no. (%)
Mastectomy21 (26.3)14 (20.0)
Breast conservation48 (60.0)54 (77.1)
not known11 (13.7)2 (2.9)
Vital status – no. (%)
Alive53 (66.2)69 (98.6)
Dead27 (33.8)1 (1.4)

SD: standard deviation; IDC: invasive ductal carcinoma; ILC: invasive lobular carcinoma.

SD: standard deviation; IDC: invasive ductal carcinoma; ILC: invasive lobular carcinoma.

Definition of molecular classes

Tumour grade was evaluated using the modified Bloom and Richardson method. Immunohistochemical evaluation was performed on paraffin-embedded tumour samples obtained at diagnosis. Estrogen receptor, progesterone receptor, HER2 staining were carried out at the Pathology Unit of the A.O. Istituti Ospitalieri di Cremona, Italy. The immunohistochemical method used for routine markers is fully described elsewhere [28]. Tumors were classified as: luminal A (hormone receptor positive: estrogen receptor + and/or progesterone receptor + and HER2–), and triple-negative (ER-ve, PR-ve, HER2-ve) [29].

RNA and real time

RNA was extracted from core biopses with the High Pure FFPE RNA Micro Kit (Roche). RNA concentrations were then measured by NanoDrop spectrophotometer and retro-transcription to cDNA was performed using High Capacity cDNA Reverse Transcription Kit (Applied Biosystem) in a 96well plate, one for each hystological subgroup. 15ug are preamplified with TaqMan Preamp Master mix (Applied Biosystem) and with the pool of primers used later for real time PCR reactions. Genes selected have a key role in the BER (PARP1); in the NER pathway (ERCC1, XPA, XPD, XPF and XPG); in the FA pathway (BRCA1, FANCA, FANCC, FANCD2, FANCF and PALB2); in DNA damage checkpoint pathway (Chk1). Optimal primer pairs (Table 2) were chosen, spanning splice junctions, using PRIMER-3 software (http://frodo.wi.mit.edu/cgi-bin/primer3/primer3_www.cgi) and the specificity was verified by detecting single-band amplicons of the PCR products. The EP Motion robot (Eppendorf) dispensed 10 ng of cDNA in triplicate on a 384 wells plate, one for each gene and for each subgroup. The reaction was performed with Sybr Green PCR master mix (Applied Biosystem) and the curve of dissociation was evaluated. A standard curve for each specific gene was included in each plate for an absolute quantification of the copy of RNA. Samples were then normalized using the absolute copy number of the housekeeping gene (ciclophilin A). The two different sample plates (TNBC and LABC) were calibrated using inter-run calibrators samples (four different breast cancer cell lines) to correct for run to run technical variation. The calibration procedure was performed on a gene per gene basis.
Table 2

Real Time PCR primers.

GENEPRIMER FPRIMER R
CICLOPHILIN A GACCCAACACAAATGGTTCC TTTCACTTTGCCAAACACCA
PARP1 AAGAAATGCAGCGAGAGCAT CCAGTGTGGGACTTTTCCAT
ERCC1 GGCCTATGAGCAGAAACCAG TTCACGGTGGTCAGACATTC
XPA GAACCACTTTGATTTGCCAAC TTGTTTTGCCTCTGTTTTGG
XPF GAGAAATCTTTTTGTGAGGAAACTG CAACTTCAGGTTTGTGCTGTTC
XPG AAGCCATCAAAACTGCCTTC TCGTTTTCTCTTCGAACTTGG
XPD GTGGCCATCAGCTCCAAAT CAGCAGGAGGTTCCCATAGT
BRCA1 GCCAGAAAACACCACATCAC CAGTGTCCGTTCACACACAA
FANCA GAGGTTCTTCAGTCATACCCTGA TCTCTCTGCATCTGAACAGCA
FANCC CCAGCCAGAGTTCTTTGAGG CGAAGCCAGAGGCAGACTAC
FANCD2 CCCATCTGCTATGATGATGAA CGTATTTGCTGAGGGGATATG
FANCF GCTAGTCCACTGGCTTCTGG GGTGGCGGCTAGTCACTAAA
PALB2 TGGGACCCTTTCTGATCAAC GGGGCATCAAAAATTGGTTT
CHK1 GGTCACAGGAGAGAAGGAAT TCTCTGACCATCTGGTTCAGG

Data and statistical analysis

The Mann-Whitney U test was chosen to compare clinicopathological and gene expression data between the two groups of TNBCs and LABCs. The median is taken as valid proxy for expression level of all genes. Relationships between family gene expression levels were examined using the Spearman's rank correlation. Each gene distribution was split into three expression levels (low, intermediate and high level) defined by the two tertiles calculated on patients who did not die at the end of the study. For further testing, each gene distribution was dichotomized (low and high level) using the median gene expression value as the cut-off point. Consistently, patients were divided into different subgroups based on different gene expression level. Univariate comparisons for all categorical variables were performed by Pearson's chi-squared test with Yates's correction for continuity or Fisher's exact test, when appropriate. Overall survival (OS) and event-free survival (EFS) were classified as outcome measures and defined as the length of time from the start of neoadjuvant chemotherapy or the date of curative surgery (in patients treated with only adjuvant therapy) or the date of diagnosis (in patients diagnosed with metastases) to the last follow-up date or death (irrespective of the cause) or to the first relapse or progression event. OS and EFS curves were plotted with the Kaplan-Meier method. The log-rank test and Cox proportional hazard models were used to compare time-to-event distributions between subgroups. All analyses were performed using SPSS (version 10.0– Chicago, IL) and STATISTICA software system (version 6– Tulsa, OK). All tests were performed two-sided and p values <0.05 were considered statistically significant.

Results

Patients' characteristics

We considered a cohort of 150 paraffin embedded core biopsies, 80 with a pathological diagnosis of TNBC and 70 with a diagnosis of LABC that came to the medical attention of a single medical center, the Breast Care Unit of A.O. Istituti Ospitalieri di Cremona from January 5th, 1995 to August 19th, 2008. The two groups (TNBC vs LABC), whose characteristics are depicted in Table 1, were comparable in terms of age (p = 0.2056) and menopausal status at diagnosis (p = 0.4493), surgical treatment (p = 0.3200), pathological T staging at surgery (p = 0.1404), and follow-up time (p = 0.0649).

mRNA expression of the 13 genes involved in DNA repair pathways

Genes involved in different DNA repair pathways were studied by RT-PCR and Table 3 summarizes the data for both TNBC and LABC. There was considerable variability in expression levels in the individual genes. The levels of the NER genes, ERCC1, XPA, XPF and XPD genes were significantly lower in TNBCs than in LABCs, while there was no difference for XPG. FA genes were less expressed than NER genes in TNBC. BRCA1, FANCD2, FANCF and PALB2 genes were significantly less expressed in TNBCs than in LABCs. CHK1 gene was significantly less expressed in TNBCs than in LABCs. On the contrary, PARP1 levels were higher in TNBCs than in LABCs.
Table 3

Normalized and calibrated values (mean± SD and median) of the different DNA repair genes in tumor samples.

PATH WAYGENETNBC (N = 80)LABC (N = 70)p value*
Mean ± SDMedianMean ± SDMedian
BER PARP1 10.87±10.928.2507.05±5.465.221 0.0002
NER ERCC1 0.71±0.660.6336.87±20.771.040 <0.0001
XPA 0.10±0.080.0800.16±0.210.104 0.0309
XPF 23.35±55.615.10868.93±107.0521.996 <0.0001
XPG 0.66±0.710.4681.51±3.520.2870.1534
XPD 0.276±0.3600.1866.68±10.263.662 <0.0001
FA BRCA1 0.028±0.0250.0200.83±3.360.062 <0.0001
FANCA 0.138±0.2790.0570.27±0.710.0940.8293
FANCC 0.005±0.0070.0030.002±0.0500.0030.3627
FANCD2 0.08±0.1240.0544.45±23.320.150 <0.0001
FANCF 0.026±0.0270.0180.451±1.1700.031 <0.0001
PALB2 0.453±0.5630.3065.91±23.032.010 0.0006
SEN SOR CHK1 0.179±0.3000.10811.51±46.441.779 <0.0001

p value indicate the difference of the gene expression levels between TNBC anl LABC; p value in bold are significant.

p value indicate the difference of the gene expression levels between TNBC anl LABC; p value in bold are significant.

Association between gene expression and clinic-pathological characteristics

Table 4 reports the p values found between the gene expression level based on tertiles (low, intermediate and high level as specified in Materials and Methods) and some clinic-pathological characteristics in TNBC. Lower levels of XPG and FANCA were associated with higher pathological T classification at surgery (pT2-4 vs pT1); higher level of XPF was associated with no lymph node involvement (pN0 vs pN1-3), and higher levels of FANCA correlated with vital status. Using the median gene expression value as a cut-off point of categorization (low and high level), only the association of XPG and FANCA expression levels with pT classification remained statistically significant. No other associations were found among the other clinic-pathological evaluated parameters (age at diagnosis-65 years vs ≥65 years-; menopausal status-pre-menopausal vs post-menopausal-; clinical dimension at diagnosis-≤20 mm vs >20 mm-; basal histotype-ductal infiltrating carcinoma vs others-; basal grading-G1-2 vs G3-; basal Ki67-<14% vs ≥14% and <20% vs ≥20%-; clinical complete response-cCR vs not cCR-; pathological complete response-pCR vs not pCR-). When the same analysis was performed in the LABC cohort of patients, none association could be found.
Table 4

Significantp values for the association between gene expression and clinic-pathological characteristics of triple negative breast cancer patients (univariate analysis, categorization based on tertiles).

PATHWAYGENEpT classificationpN classificationVital status
at surgeryat surgeryat last follow up
BER PARP1
NER ERCC1
XPA
XPF 0.0162
XPG 0.0437
XPD
FA BRCA1
FANCA 0.03660.0144
FANCC
FANCD2
FANCF
PALB2
SENSOR CHK1
We correlated the different gene expression levels based on tertiles with OS and EFS. As depicted in Table 5, the intermediate level of XPG correlated on univariate analysis with increased OS compared to the low level. Interesting enough, the high level of FANCA correlated with an increased OS and EFS compared to the low level. Again, the intermediate level of FANCA correlated with an increase in EFS compared to the low level. The Kaplan-Meier curves (Figure 1) shows that higher level of FANCA correlated with an increased OS (p = 0.0153) and an increased EFS (p = 0.0207). Furthermore, using the median gene expression value as a cut-off point of categorization, we again found a trend (not significant) toward better OS (p = 0.0906) and EFS (p = 0.0999) in patients with high level of FANCA. Multivariate analyses using Cox regression, however, showed that the FANCA expression level was not an independent prognostic factor in TNBC patients adjusted for the potential confounding factors: age at diagnosis, surgical treatment, pathological T and N staging at surgery. As regards LABCs, OS and EFS data were not yet mature.
Table 5

Overall survival and event-free survival in triple negative breast cancer patients by expression of the different genes (univariate analysis, categorization based on tertiles).

TNBC (N = 80)
PATHWAYGENEEXPRESSIONOSEFS
p value p value
BER PARP1 II-I terziles0.30560.2334
III-I terziles0.61400.4632
NER ERCC1 II-I terziles0.99930.9450
III-I terziles0.18680.3955
XPA II-I terziles0.20350.0957
III-I terziles0.70710.9908
XPF II-I terziles0.78130.9566
III-I terziles0.10880.4704
XPG II-I terziles 0.0344 0.0674
III-I terziles0.28700.2902
XPD II-I terziles0.10100.0764
III-I terziles0.14030.2480
FA BRCA1 II-I terziles0.48120.6162
III-I terziles0.41960.5115
FANCA II-I terziles0.1088 0.0408
III-I terziles 0.0045 0.0141
FANCC II-I terziles0.35790.5383
III-I terziles0.08500.0736
FANCD2 II-I terziles0.08450.1352
III-I terziles0.15540.2216
FANCF II-I terziles0.75560.9254
III-I terziles0.61920.7587
PALB2 II-I terziles0.51700.5381
III-I terziles0.20100.1617
PARP1 II-I terziles0.30560.2334
III-I terziles0.61400.4632
SENSOR CHK1 II-I terziles0.77400.4396
III-I terziles0.23250.2601

The mRNA expression distribution of all the genes was split into three groups, as described in Materials and Methods. p value in bold are significant.

Figure 1

Kaplan-Meier estimates for event-free survival (panel A) and overall survival (panel B) in TNBC patients stratifies by the different level ofFANCA expression (univariate analysis, categorization based on tertiles).

The mRNA expression distribution of all the genes was split into three groups, as described in Materials and Methods. p value in bold are significant.

Discussion

TNBC represents a subset of breast cancer with well documented poor prognosis, whose real causes are still to be defined even if a number of adverse factors have been advocated, such as the fact that these tumors are at the diagnosis commonly of high nuclear mitotic grade, of larger tumor size and with a more aggressive expression profile (low BCL2 and high p53 and Ki67 expression) [5], [30], [31]. Several studies have demonstrated significant lower EFS in patients with TNBC compared to patients with non-TNBC; in addition, shorter OS in TNBC patients is widely reported [3], [32]–[34]. Despite the poor prognosis, these tumors are particularly chemosensitive at least in a short-term time frame [35], [36]. In fact, patients with TNBC have increased pathologic complete response (pCR) rates compared to non-TNBC patients after treatment with taxanes and antracycline agents. Wang at al reported a 38% of pCR in TNBC and 14% in non-TNBC patients treated with taxane in combination with antracycline [37]. Better response rates were also reported after treatment with alkylating agents, including cyclophosphamide, cisplatin, and carboplatin [38]. TNBC have been shown to harbour DNA repair deficiencies, including BRCA1 dysfunction, due to promoter methylation or deregulation of other genes involved in their transcriptional regulation [9], BER inactivation [15], MTMG promoter hypermethylation [16] and lack of hOGG1 [17]. Given the importance of the cellular DNA repair in determining the cellular response to different anticancer agents [39]–[43], a priori knowledge of the repair status of a given tumor could play an important role in selection of the most appropriate therapy. Attempts to investigate the functionality of a given DNA repair pathway have been undertaken and shown to be feasible. Willers et al reported the successful detection of BRCA1, FANCD2 and RAD51 foci in seven breast cancer biopsies irradiated ex vivo, suggesting the possibility to detect defects within the complex FA/BRCA DNA damage response pathway [44]. Isolation of epithelial cells from breast tumor specimens and application of specific functional DNA repair assay systems led to the detection of specific defects in double strand breaks repair [22], while homologous recombination status could be determined in ovarian cancer samples by RAD51 foci formation after in vitro treatment with a PARP inhibitor [23]. However, all these assays still need to be technically improved (ie. requirement for an automated foci scoring and setting up of tumor specific primary cultures) rendering difficult their wide spread clinical use. An alternative approach is the study of biomarkers that, even if not completely validated [24]–[27], can be considered surrogate of DNA repair functionality, i.e. the mRNA and/or expression levels of key proteins involved in DNA repair pathways. The expression profile of a number of genes involved in the different DNA repair pathways was studied in a cohort of TNBC samples as a surrogate markers of DNA repair status and correlated with different clinic-pathological characteristics, including survival. These data were compared to the ones obtained in a group of patients with LABC, that represent the breast cancer subtype with the best prognosis. The levels of expression of all the genes involved in the NER and FA pathways were significantly lower in TNBC as compared to LABC samples, with the exception of XPG, FANCA and FANCC whose difference did not reach a statistically significant value. These expression data might in part explain the extremely high sensitivity of TNBC patients to chemotherapy. It has in fact been demonstrated that not only the deficiency, but also low levels of mRNA/protein involved in NER, i.e ERCC1 and XPF or FA genes are associated with increased sensitivity to alkylating agents in different cellular systems [45]. At the same time, the low expression level of these genes might explain the bad prognosis of the tumors, even if they do respond well to chemotherapy. The low DNA repair capacity would in fact increase the genomic instability of the tumor cells enabling them to accumulate much more mutations through which cells would became more aggressive. Sporadic stage I breast cancer have recently been reported to exhibite a significant deficiency of NER capacity relative to epithelial control tissue [46] by both functional unscheduled DNA synthesis and mRNA expression of NER genes. Low expression of 4 proteins – XPF, FANCD2, MLH1 and pMK2– assessed in FFPE tumor specimens by semiquantitative immunohistochemistry, was associated with shorter recurrence free survival in multivariate analysis [47], corroborating the idea that tumors with reduced DNA repair capacity will have a higher degree of genomic instability and therefore behave more aggressively. The data on FANCA are, on the contrary, counter-intuitive and intriguing. FANCA was not differentially expressed between TNBC and LABC, but it was found to positively correlate in univariate analysis with both EFS and OS (higher level correlated with longer EFS and OS). FANCA is one of the 13 proteins cooperating in a common DNA repair pathway (for rev see [48], [49]). FANCA, higher expression correlated with an improved outcome that could be a consequence of a less malignant phenotype, due to a more stable tumor genome. This resembles what observed for the expression of ERCC1 in non small cell lung cancer (NSCLC), where it has been shown that higher ERCC1 levels were correlated with a better prognosis [50], [51], but was also higher levels of ERCC1 were a marker of resistance to a platinum containing regimens [50]. Recently, the experimental finding that ERCC1 negative NSLC samples display a higher genomic instability corroborate the more unstable and then the worst clinical history of ERCC1 low/negative tumors [52]. There are few, but contrasting data, on CHK1 expression in different breast cancer subtypes. CHK1 is a kinase that has an important role in both the maintenance of genomic instability and in the transduction pathways after DNA damage [53]. Verlinden et al. [54] reported a twofold higher expression (as assessed by RT-PCR) of CHK1 in grade 3 TNBC than in other grade 3 tumor breast subtype; while no difference CHK1 protein expression was found in different breast cancer cell lines. These discrepancies can be related to the different methodologies used (RT-PCR vs western blotting; relative vs absolute RT-PCR values), samples size and the pathological classification of the different tumor analyzed. All tumor samples analyzed expressed PARP1 mRNA, whose levels were higher in TNBC compared to LABC, reinforcing the data that neoplastic tumors express high level of PARP [55], [56]. There are a number of issues that limits the present study: i.e. its retrospective nature, the relative small sample size and the fact it analysed the mRNA expression levels of DNA repair protein rather than the quantification of a functional DNA repair status. Nevertheless, our data are the first to show the mRNA expression of multiple DNA repair genes involved in three different DNA repair pathways (BER, NER and FA) in a cohort of TNBC and LABC. These data support the experimental evidence that TNBC harbour DNA repair defects and this could explain both the extremely chemo-sensitivity of this tumor type to chemotherapy in a short term and the worse outcome probably correlated with the inability to counteract the increased genomic instability for the lack of an efficient DNA damage status.
  56 in total

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2.  Directed therapy of subtypes of triple-negative breast cancer.

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3.  Utility of DNA repair protein foci for the detection of putative BRCA1 pathway defects in breast cancer biopsies.

Authors:  Henning Willers; Alphonse G Taghian; Chen-Mei Luo; Alejandro Treszezamsky; Dennis C Sgroi; Simon N Powell
Journal:  Mol Cancer Res       Date:  2009-08-11       Impact factor: 5.852

4.  Molecular subtyping of male breast cancer by immunohistochemistry.

Authors:  Robert Kornegoor; Anoek H J Verschuur-Maes; Horst Buerger; Marieke C H Hogenes; Peter C de Bruin; Joost J Oudejans; Petra van der Groep; Bernd Hinrichs; Paul J van Diest
Journal:  Mod Pathol       Date:  2011-11-04       Impact factor: 7.842

5.  Development of a functional assay for homologous recombination status in primary cultures of epithelial ovarian tumor and correlation with sensitivity to poly(ADP-ribose) polymerase inhibitors.

Authors:  Asima Mukhopadhyay; Ahmed Elattar; Aiste Cerbinskaite; Sarah J Wilkinson; Yvette Drew; Suzanne Kyle; Gerrit Los; Zdenek Hostomsky; Richard J Edmondson; Nicola J Curtin
Journal:  Clin Cancer Res       Date:  2010-04-06       Impact factor: 12.531

6.  DNA repair protein biomarkers associated with time to recurrence in triple-negative breast cancer.

Authors:  Brian M Alexander; Kam Sprott; D Allan Farrow; XiaoZhe Wang; Alan D D'Andrea; Stuart J Schnitt; Laura C Collins; David T Weaver; Judy E Garber
Journal:  Clin Cancer Res       Date:  2010-12-01       Impact factor: 12.531

7.  Molecular characterization of breast cancer with high-resolution oligonucleotide comparative genomic hybridization array.

Authors:  Fabrice Andre; Bastien Job; Philippe Dessen; Attila Tordai; Stefan Michiels; Cornelia Liedtke; Catherine Richon; Kai Yan; Bailang Wang; Gilles Vassal; Suzette Delaloge; Gabriel N Hortobagyi; W Fraser Symmans; Vladimir Lazar; Lajos Pusztai
Journal:  Clin Cancer Res       Date:  2009-01-15       Impact factor: 12.531

8.  A sensitive test for the detection of specific DSB repair defects in primary cells from breast cancer specimens.

Authors:  Marlen Keimling; Jatinder Kaur; Sarangadhara Appala Raju Bagadi; Rolf Kreienberg; Lisa Wiesmüller; Ranju Ralhan
Journal:  Int J Cancer       Date:  2008-08-01       Impact factor: 7.396

9.  Absence of the DNA repair enzyme human 8-oxoguanine glycosylase is associated with an aggressive breast cancer phenotype.

Authors:  P Karihtala; S Kauppila; U Puistola; A Jukkola-Vuorinen
Journal:  Br J Cancer       Date:  2011-11-22       Impact factor: 7.640

10.  Basal-like Breast cancer DNA copy number losses identify genes involved in genomic instability, response to therapy, and patient survival.

Authors:  Victor J Weigman; Hann-Hsiang Chao; Andrey A Shabalin; Xiaping He; Joel S Parker; Silje H Nordgard; Tatyana Grushko; Dezheng Huo; Chika Nwachukwu; Andrew Nobel; Vessela N Kristensen; Anne-Lise Børresen-Dale; Olufunmilayo I Olopade; Charles M Perou
Journal:  Breast Cancer Res Treat       Date:  2011-11-03       Impact factor: 4.872

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  19 in total

1.  A Preliminary Study: Human Fibroid Stro-1+/CD44+ Stem Cells Isolated From Uterine Fibroids Demonstrate Decreased DNA Repair and Genomic Integrity Compared to Adjacent Myometrial Stro-1+/CD44+ Cells.

Authors:  Lauren E Prusinski Fernung; Ayman Al-Hendy; Qiwei Yang
Journal:  Reprod Sci       Date:  2018-06-28       Impact factor: 3.060

2.  A Novel Brain-Permeant Chemotherapeutic Agent for the Treatment of Brain Metastasis in Triple-Negative Breast Cancer.

Authors:  Jiaojiao Deng; Sophia B Chernikova; Yuelong Wang; Mirna L Rodriguez; Stephanie J Andersen; Maxine C Umeh-Garcia; Bryanna O Godfrey; Saman S Ahmadian; Wolf-Nicolas Fischer; Kerry J Koller; Bernd Jandeleit; Gordon M Ringold; Melanie Hayden Gephart
Journal:  Mol Cancer Ther       Date:  2021-10-11       Impact factor: 6.261

3.  Suicide Gene Therapy for Cancer - Current Strategies.

Authors:  Paul Zarogoulidis; Kaid Darwiche; Antonios Sakkas; Lonny Yarmus; Haidong Huang; Qiang Li; Lutz Freitag; Konstantinos Zarogoulidis; Marek Malecki
Journal:  J Genet Syndr Gene Ther       Date:  2013-08-09

4.  Dynamin impacts homology-directed repair and breast cancer response to chemotherapy.

Authors:  Sophia B Chernikova; Rochelle B Nguyen; Jessica T Truong; Stephano S Mello; Jason H Stafford; Michael P Hay; Andrew Olson; David E Solow-Cordero; Douglas J Wood; Solomon Henry; Rie von Eyben; Lei Deng; Melanie Hayden Gephart; Asaithamby Aroumougame; Claudia Wiese; John C Game; Balázs Győrffy; J Martin Brown
Journal:  J Clin Invest       Date:  2018-10-29       Impact factor: 14.808

Review 5.  The chemosensitivity of testicular germ cell tumors.

Authors:  Ioannis A Voutsadakis
Journal:  Cell Oncol (Dordr)       Date:  2014-04-02       Impact factor: 6.730

Review 6.  DNA double-strand break repair in cancer: A path to achieving precision medicine.

Authors:  Taneisha Gillyard; Jamaine Davis
Journal:  Int Rev Cell Mol Biol       Date:  2021-08-03       Impact factor: 6.813

7.  ERCC1 and telomere status in breast tumours treated with neoadjuvant chemotherapy and their association with patient prognosis.

Authors:  Mathilde Gay-Bellile; Pierre Romero; Anne Cayre; Lauren Véronèse; Maud Privat; Shalini Singh; Patricia Combes; Fabrice Kwiatkowski; Catherine Abrial; Yves-Jean Bignon; Philippe Vago; Frédérique Penault-Llorca; Andreï Tchirkov
Journal:  J Pathol Clin Res       Date:  2016-07-13

8.  Clinical, Radiometabolic and Immunologic Effects of Olaparib in Locally Advanced Triple Negative Breast Cancer: The OLTRE Window of Opportunity Trial.

Authors:  Francesco Schettini; Silvia Paola Corona; Fabiola Giudici; Carla Strina; Marianna Sirico; Ottavia Bernocchi; Manuela Milani; Nicoletta Ziglioli; Sergio Aguggini; Carlo Azzini; Giuseppina Barbieri; Valeria Cervoni; Maria Rosa Cappelletti; Alfredo Molteni; Maria Chiara Lazzari; Giuseppina Ferrero; Marco Ungari; Elena Marasco; Alice Bruson; Luciano Xumerle; Elisa Zago; Davide Cerra; Marco Loddo; Gareth H Williams; Ida Paris; Giovanni Scambia; Daniele Generali
Journal:  Front Oncol       Date:  2021-06-28       Impact factor: 6.244

9.  Chk1 inhibition as a novel therapeutic strategy for treating triple-negative breast and ovarian cancers.

Authors:  Christopher Bryant; Rebecca Rawlinson; Andrew J Massey
Journal:  BMC Cancer       Date:  2014-08-07       Impact factor: 4.430

10.  Heterozygous PALB2 c.1592delT mutation channels DNA double-strand break repair into error-prone pathways in breast cancer patients.

Authors:  K Obermeier; J Sachsenweger; T W P Friedl; H Pospiech; R Winqvist; L Wiesmüller
Journal:  Oncogene       Date:  2015-12-07       Impact factor: 9.867

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