Oncogene-induced replication stress (RS) promotes cancer development but also impedes tumor growth by activating anti-cancer barriers. To determine how cancer cells adapt to RS, we have monitored the ...expression of different components of the ATR-CHK1 pathway in primary tumor samples. We show that unlike upstream components of the pathway, the checkpoint mediators Claspin and Timeless are overexpressed in a coordinated manner. Remarkably, reducing the levels of Claspin and Timeless in HCT116 cells to pretumoral levels impeded fork progression without affecting checkpoint signaling. These data indicate that high level of Claspin and Timeless increase RS tolerance by protecting replication forks in cancer cells. Moreover, we report that primary fibroblasts adapt to oncogene-induced RS by spontaneously overexpressing Claspin and Timeless, independently of ATR signaling. Altogether, these data indicate that enhanced levels of Claspin and Timeless represent a gain of function that protects cancer cells from of oncogene-induced RS in a checkpoint-independent manner.
Lopez‐Garcia M A, Geyer F C, Lacroix‐Triki M, Marchió C & Reis‐Filho J S (2010) Histopathology 57, 171–192 Breast cancer precursors revisited: molecular features and progression pathways
Increasingly ...more coherent data on the molecular characteristics of benign breast lesions and breast cancer precursors have led to the delineation of new multistep pathways of breast cancer progression through genotypic–phenotypic correlations. It has become apparent that oestrogen receptor (ER)‐positive and ‐negative breast lesions are fundamentally distinct diseases. Within the ER‐positive group, histological grade is strongly associated with the number and complexity of genetic abnormalities in breast cancer cells. Genomic analyses of high‐grade ER‐positive breast cancers have revealed that a substantial proportion of these tumours harbour the characteristic genetic aberrations found in low‐grade ER‐positive disease, suggesting that at least a subgroup of high‐grade ER‐positive breast cancers may originate from low‐grade lesions. The ER‐negative group is more complex and heterogeneous, comprising distinct molecular entities, including basal‐like, HER2 and molecular apocrine lesions. Importantly, the type and pattern of genetic aberrations found in ER‐negative cancers differ from those of ER‐positive disease. Here, we review the available molecular data on breast cancer risk indicator and precursor lesions, the putative mechanisms of progression from in situ to invasive disease, and propose a revised model of breast cancer evolution based on the molecular characteristics of distinct subtypes of in situ and invasive breast cancers.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Summary Background Breast cancer is characterised by genomic alterations. We did a multicentre molecular screening study to identify abnormalities in individual patients with the aim of providing ...targeted therapy matched to individuals' genomic alterations. Methods From June 16, 2011, to July 30, 2012, we recruited patients who had breast cancer with a metastasis accessible for biopsy in 18 centres in France. Comparative genomic hybridisation (CGH) array and Sanger sequencing on PIK3CA (exon 10 and 21) and AKT1 (exon 4) were used to assess metastatic biopsy samples in five centres. Therapeutic targets were decided on the basis of identified genomic alterations. The primary objective was to include 30% of patients in clinical trials testing a targeted therapy and, therefore, the primary outcome was the proportion of patients to whom a targeted therapy could be offered. For the primary endpoint, the analyses were done on the overall population registered for the trial. This trial is registered with ClinicalTrials.gov , number NCT01414933. Findings 423 patients were included, and biopsy samples were obtained from 407 (metastatic breast cancer was not found in four). CGH array and Sanger sequencing were feasible in 283 (67%) and 297 (70%) patients, respectively. A targetable genomic alteration was identified in 195 (46%) patients, most frequently in PIK3CA (74 25% of 297 identified genomic alterations), CCND1 (53 19%), and FGFR1 (36 13%). 117 (39%) of 297 patients with genomic tests available presented with rare genomic alterations (defined as occurring in less than 5% of the general population), including AKT1 mutations, and EGFR, MDM2, FGFR2, AKT2, IGF1R , and MET high-level amplifications. Therapy could be personalised in 55 (13%) of 423 patients. Of the 43 patients who were assessable and received targeted therapy, four (9%) had an objective response, and nine others (21%) had stable disease for more than 16 weeks. Serious (grade 3 or higher) adverse events related to biopsy were reported in four (1%) of enrolled patients, including pneumothorax (grade 3, one patient), pain (grade 3, one patient), haematoma (grade 3, one patient), and haemorrhagic shock (grade 3, one patient). Interpretation Personalisation of medicine for metastatic breast cancer is feasible, including for rare genomic alterations. Funding French National Cancer Institute, Breast Cancer Research Foundation, Odyssea, Operation Parrains Chercheurs.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
The aim of the current study was to conduct a pooled analysis of studies that have investigated the prognostic value of tumor-infiltrating lymphocytes (TILs) in early-stage triple negative breast ...cancer (TNBC).
Participating studies had evaluated the percentage infiltration of stromally located TILs (sTILs) that were quantified in the same manner in patient diagnostic samples of early-stage TNBC treated with anthracycline-based chemotherapy with or without taxanes. Cox proportional hazards regression models stratified by trial were used for invasive disease-free survival (iDFS; primary end point), distant disease-free survival (D-DFS), and overall survival (OS), fitting sTILs as a continuous variable adjusted for clinicopathologic factors.
We collected individual data from 2,148 patients from nine studies. Average age was 50 years (range, 22 to 85 years), and 33% of patients were node negative. The average value of sTILs was 23% (standard deviation, 20%), and 77% of patients had 1% or more sTILs. sTILs were significantly lower with older age ( P = .001), larger tumor size ( P = .01), more nodal involvement ( P = .02), and lower histologic grade ( P = .001). A total of 736 iDFS and 548 D-DFS events and 533 deaths were observed. In the multivariable model, sTILs added significant independent prognostic information for all end points (likelihood ratio χ
, 48.9 iDFS; P < .001; χ
, 55.8 D-DFS; P < .001; χ
, 48.5 OS; P < .001). Each 10% increment in sTILs corresponded to an iDFS hazard ratio of 0.87 (95% CI, 0.83 to 0.91) for iDFS, 0.83 (95% CI, 0.79 to 0.88) for D-DFS, and 0.84 (95% CI, 0.79 to 0.89) for OS. In node-negative patients with sTILs ≥ 30%, 3-year iDFS was 92% (95% CI, 89% to 98%), D-DFS was 97% (95% CI, 95% to 99%), and OS was 99% (95% CI, 97% to 100%).
This pooled data analysis confirms the strong prognostic role of sTILs in early-stage TNBC and excellent survival of patients with high sTILs after adjuvant chemotherapy and supports the integration of sTILs in a clinicopathologic prognostic model for patients with TNBC. This model can be found at www.tilsinbreastcancer.org .
Aims Over 50% of breast cancer cases are “Human epidermal growth factor receptor 2 (HER2) low breast cancer (BC)”, characterized by HER2 immunohistochemistry (IHC) scores of 1+ or 2+ alongside no ...amplification on fluorescence in situ hybridization (FISH) testing. The development of new anti‐HER2 antibody‐drug conjugates (ADCs) for treating HER2‐low breast cancers illustrates the importance of accurately assessing HER2 status, particularly HER2‐low breast cancer. In this study we evaluated the performance of a deep‐learning (DL) model for the assessment of HER2, including an assessment of the causes of discordances of HER2‐Null between a pathologist and the DL model. We specifically focussed on aligning the DL model rules with the ASCO/CAP guidelines, including stained cells' staining intensity and completeness of membrane staining. Methods and Results We trained a DL model on a multicentric cohort of breast cancer cases with HER2‐IHC scores ( n = 299). The model was validated on two independent multicentric validation cohorts ( n = 369 and n = 92), with all cases reviewed by three senior breast pathologists. All cases underwent a thorough review by three senior breast pathologists, with the ground truth determined by a majority consensus on the final HER2 score among the pathologists. In total, 760 breast cancer cases were utilized throughout the training and validation phases of the study. The model's concordance with the ground truth (ICC = 0.77 0.68–0.83; Fisher P = 1.32e‐10) is higher than the average agreement among the three senior pathologists (ICC = 0.45 0.17–0.65; Fisher P = 2e‐3). In the two validation cohorts, the DL model identifies 95% 93% ‐ 98% and 97% 91% ‐ 100% of HER2‐low and HER2‐positive tumours, respectively. Discordant results were characterized by morphological features such as extended fibrosis, a high number of tumour‐infiltrating lymphocytes, and necrosis, whilst some artefacts such as nonspecific background cytoplasmic stain in the cytoplasm of tumour cells also cause discrepancy. Conclusion Deep learning can support pathologists' interpretation of difficult HER2‐low cases. Morphological variables and some specific artefacts can cause discrepant HER2‐scores between the pathologist and the DL model.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Major advances have been achieved in the characterization of early breast cancer (eBC) genomic profiles. Metastatic breast cancer (mBC) is associated with poor outcomes, yet limited information is ...available on the genomic profile of this disease. This study aims to decipher mutational profiles of mBC using next-generation sequencing.
Whole-exome sequencing was performed on 216 tumor-blood pairs from mBC patients who underwent a biopsy in the context of the SAFIR01, SAFIR02, SHIVA, or Molecular Screening for Cancer Treatment Optimization (MOSCATO) prospective trials. Mutational profiles from 772 primary breast tumors from The Cancer Genome Atlas (TCGA) were used as a reference for comparing primary and mBC mutational profiles. Twelve genes (TP53, PIK3CA, GATA3, ESR1, MAP3K1, CDH1, AKT1, MAP2K4, RB1, PTEN, CBFB, and CDKN2A) were identified as significantly mutated in mBC (false discovery rate FDR < 0.1). Eight genes (ESR1, FSIP2, FRAS1, OSBPL3, EDC4, PALB2, IGFN1, and AGRN) were more frequently mutated in mBC as compared to eBC (FDR < 0.01). ESR1 was identified both as a driver and as a metastatic gene (n = 22, odds ratio = 29, 95% CI 9-155, p = 1.2e-12) and also presented with focal amplification (n = 9) for a total of 31 mBCs with either ESR1 mutation or amplification, including 27 hormone receptor positive (HR+) and HER2 negative (HER2-) mBCs (19%). HR+/HER2- mBC presented a high prevalence of mutations on genes located on the mechanistic target of rapamycin (mTOR) pathway (TSC1 and TSC2) as compared to HR+/HER2- eBC (respectively 6% and 0.7%, p = 0.0004). Other actionable genes were more frequently mutated in HR+ mBC, including ERBB4 (n = 8), NOTCH3 (n = 7), and ALK (n = 7). Analysis of mutational signatures revealed a significant increase in APOBEC-mediated mutagenesis in HR+/HER2- metastatic tumors as compared to primary TCGA samples (p < 2e-16). The main limitations of this study include the absence of bone metastases and the size of the cohort, which might not have allowed the identification of rare mutations and their effect on survival.
This work reports the results of the analysis of the first large-scale study on mutation profiles of mBC. This study revealed genomic alterations and mutational signatures involved in the resistance to therapies, including actionable mutations.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The importance of integrating biomarkers into the TNM staging has been emphasized in the 8
Edition of the American Joint Committee on Cancer (AJCC) Staging system. In a pooled analysis of 2148 ...TNBC-patients in the adjuvant setting, TILs are found to strongly up and downstage traditional pathological-staging in the Pathological and Clinical Prognostic Stage Groups from the AJJC 8
edition Cancer Staging System. This suggest that clinical and research studies on TNBC should take TILs into account in addition to stage, as for example patients with stage II TNBC and high TILs have a better outcome than patients with stage I and low TILs.
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