Challenging single- and multi-probesets gene expression signatures of pathological complete response to neoadjuvant chemotherapy in breast cancer: experience of the REMAGUS 02 phase II trial

A Network of 17 Microtubule-Related Genes Highlights Functional Deregulations in Breast Cancer

A wide panel of microtubule-associated proteins and kinases is involved in coordinated regulation of the microtubule cytoskeleton and may thus represent valuable molecular markers contributing to major cellular pathways deregulated in cancer. We previously identified a panel of 17 microtubule-related (MT-Rel) genes that are differentially expressed in breast tumors showing resistance to taxane-based chemotherapy. In the present study, we evaluated the expression, prognostic value and functional impact of these genes in breast cancer. We show that 14 MT-Rel genes (KIF4A, ASPM, KIF20A, KIF14, TPX2, KIF18B, KIFC1, AURKB, KIF2C, GTSE1, KIF15, KIF11, RACGAP1, STMN1) are up-regulated in breast tumors compared with adjacent normal tissue. Six of them (KIF4A, ASPM, KIF20A, KIF14, TPX2, KIF18B) are overexpressed by more than 10-fold in tumor samples and four of them (KIF11, AURKB, TPX2 and KIFC1) are essential for cell survival. Overexpression of all 14 genes, and underexpression of 3 other MT-Rel genes (MAST4, MAPT and MTUS1) are associated with poor breast cancer patient survival. A Systems Biology approach highlighted three major functional networks connecting the 17 MT-Rel genes and their partners, which are centered on spindle assembly, chromosome segregation and cytokinesis. Our studies identified mitotic Aurora kinases and their substrates as major targets for therapeutic approaches against breast cancer.

Emerging Evidences for an Implication of the Neurodegeneration-Associated Protein TAU in Cancer

Neurodegenerative disorders and cancer may appear unrelated illnesses. Yet, epidemiologic studies indicate an inverse correlation between their respective incidences for specific cancers. Possibly explaining these findings, increasing evidence indicates that common molecular pathways are involved, often in opposite manner, in the pathogenesis of both disease families. Genetic mutations in the MAPT gene encoding for TAU protein cause an inherited form of frontotemporal dementia, a neurodegenerative disorder, but also increase the risk of developing cancer. Assigning TAU at the interface between cancer and neurodegenerative disorders, two major aging-linked disease families, offers a possible clue for the epidemiological observation inversely correlating these human illnesses. In addition, the expression level of TAU is recognized as a prognostic marker for cancer, as well as a modifier of cancer resistance to chemotherapy. Because of its microtubule-binding properties, TAU may interfere with the mechanism of action of taxanes, a class of chemotherapeutic drugs designed to stabilize the microtubule network and impair cell division. Indeed, a low TAU expression is associated to a better response to taxanes. Although TAU main binding partners are microtubules, TAU is able to relocate to subcellular sites devoid of microtubules and is also able to bind to cancer-linked proteins, suggesting a role of TAU in modulating microtubule-independent cellular pathways associated to oncogenesis. This concept is strengthened by experimental evidence linking TAU to P53 signaling, DNA stability and protection, processes that protect against cancer. This review aims at collecting literature data supporting the association between TAU and cancer. We will first summarize the evidence linking neurodegenerative disorders and cancer, then published data supporting a role of TAU as a modifier of the efficacy of chemotherapies and of the oncogenic process. We will finish by addressing from a mechanistic point of view the role of TAU in de-regulating critical cancer pathways, including the interaction of TAU with cancer-associated proteins.

Comedications influence immune infiltration and pathological response to neoadjuvant chemotherapy in breast cancer

Immunosurveillance plays an important role in breast cancer (BC) prognosis and progression, and can be geared by immunogenic chemotherapy. In a cohort of 1023 BC patients treated with neoadjuvant chemotherapy (NAC), 40% of the individuals took comedications mostly linked to aging and comorbidities. We systematically analyzed the off-target effects of 1178 concurrent comedications (classified according to the Anatomical Therapeutic Chemical (ATC) Classification System) on the density of tumor-infiltrating lymphocytes (TILs) and pathological complete responses (pCR). At level 1 of the ATC system, the main anatomical classes of drugs were those targeting the nervous system (class N, 39.1%), cardiovascular disorders (class C, 26.6%), alimentary and metabolism (class A, 16.9%), or hormonal preparations (class H, 6.5%). At level 2, the most frequent therapeutic classes were psycholeptics (N05), analgesics (N02), and psychoanaleptics (N06). Pre-NAC TIL density in triple-negative BC (TNBC) was influenced by medications from class H, N, and A, while TIL density in HER2⁺ BC was associated with the use of class C. Psycholeptics (N05) and agents acting on the renin-angiotensin system (C09) were independently associated with pCR in the whole population of BC or TNBC, and in HER2-positive BC, respectively. Importantly, level 3 hypnotics (N05C) alone were able to reduce tumor growth in BC bearing mice and increased the anti-cancer activity of cyclophosphamide in a T cell-dependent manner. These findings prompt for further exploration of drugs interactions in cancer, and for prospective drug-repositioning strategies to improve the efficacy of NAC in BC.

Improving breast cancer sensitivity to paclitaxel by increasing aneuploidy

Predictive biomarkers for tumor response to neoadjuvant chemotherapy are needed in breast cancer. This study investigates the predictive value of 280 genes encoding proteins that regulate microtubule assembly and function. By analyzing 3 independent multicenter randomized cohorts of breast cancer patients, we identified 17 genes that are differentially regulated in tumors achieving pathological complete response (pCR) to neoadjuvant chemotherapy. We focused on the MTUS1 gene, whose major product, ATIP3, is a microtubule-associated protein down-regulated in aggressive breast tumors. We show here that low levels of ATIP3 are associated with an increased pCR rate, pointing to ATIP3 as a predictive biomarker of breast tumor chemosensitivity. Using preclinical models of patient-derived xenografts and 3-dimensional models of breast cancer cell lines, we show that low ATIP3 levels sensitize tumors to the effects of taxanes but not DNA-damaging agents. ATIP3 silencing improves the proapoptotic effects of paclitaxel and induces mitotic abnormalities, including centrosome amplification and multipolar spindle formation, which results in chromosome missegregation leading to aneuploidy. As shown by time-lapse video microscopy, ATIP3 depletion exacerbates cytokinesis failure and mitotic death induced by low doses of paclitaxel. Our results favor a mechanism by which the combination of ATIP3 deficiency and paclitaxel treatment induces excessive aneuploidy, which in turn results in elevated cell death. Together, these studies highlight ATIP3 as an important regulator of mitotic integrity and a useful predictive biomarker for a population of chemoresistant breast cancer patients.

Effectiveness of Added Targeted Therapies to Neoadjuvant Chemotherapy for Breast Cancer: A Systematic Review and Meta-analysis

Over the past several years, targeted therapy has been increasingly used in the management of breast cancer. Reported results for targeted therapies are variable, as some randomized controlled trials (RCTs) reported a strong effect, whereas others reported no or minimal effect on the outcomes. Accordingly, the present study aimed to assess the effect of the addition of targeted therapies to neoadjuvant chemotherapy on tumor response rates, breast conserving surgeries, and survival outcomes. PubMed and the Cochrane register of clinical trials were searched on April 28, 2017 for RCTs comparing addition of targeted therapies to neoadjuvant chemotherapy. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the screening of records and data extraction were performed by 2 independent reviewers. Publication bias and risk of bias were assessed by the Egger test and the Cochrane tool for risk of bias assessment, respectively. The fixed effect method or random effect method were used to synthesize the results depending on the heterogeneity assessed by the I2 statistic. A total of 17 RCTs including trastuzumab (n = 5), bevacizumab (n = 7), and other targeted therapies (n = 5) were found eligible. Pathologic complete response was significantly higher with trastuzumab (relative risk [RR], 2.20; 95% confidence interval [CI], 1.62-2.99) and bevacizumab (RR, 1.23; 95% CI, 1.11-1.37), but not with other targeted therapies. Bevacizumab for human epidermal growth factor receptor 2 (HER2)-negative breast cancer was found to be associated with improved overall (hazard ratio, 0.69; 95% CI, 0.53-0.90) and disease-free survival (hazard ratio, 0.83; 95% CI, 0.67-1.03). The addition of targeted therapies may not significantly increase breast conserving surgery rates (RR, 1.04; 95% CI, 0.97-1.12). The addition of targeted therapies, especially trastuzumab for patients with HER2-positive breast cancer and bevacizumab for patients with HER2-negative breast cancer significantly increased pathologic complete response, overall response, and clinical complete response but not breast conserving surgery rates.

BIRC5 (survivin): a pejorative prognostic marker in stage II/III breast cancer with no response to neoadjuvant chemotherapy

PURPOSE

Neoadjuvant systemic therapy (NAC) is currently used in the treatment of stage II/III breast cancer. Pathological complete response as a surrogate endpoint for clinical outcomes is not completely validated for all subgroups of breast cancers. Therefore, there is a need for reliable predictive tests of the most effective treatment.

METHODS

We used a combination of predictive clinical, pathological, and gene expression-based markers of response to NAC in a prospective phase II multicentre randomized clinical trial in breast cancer patients, with a long follow-up (8 years). This study concerned the subpopulation of 188 patients with similar levels of pathological response rates to sequential epirubicin/cyclophosphamide and docetaxel to determine predictive marker of pCR and DFS. We used a set of 45 genes selected from high throughput analysis and a standardized RT-qPCR. We analyzed the predictive markers of pathological complete response (pCR) and DFS in the overall population and DFS the subpopulation of 159 patients with no pCR.

RESULTS

In the overall population, combining both clinical and genomic variables, large tumor size, low TFF1, and MYBL2 overexpression were significantly associated with pCR. T4 Stage, lymphovascular invasion, negative PR status, histological type, and high values of CCNB1 were associated with DFS. In the no pCR population, only lymphovascular invasion and high values of BIRC5 were associated with DFS.

CONCLUSIONS

We confirm the importance of ER-related and proliferation genes in the prediction of pCR in NAC-treated breast cancer patients. Furthermore, we identified BIRC5 (survivin) as a main pejorative prognostic factor in patients with breast cancers with no pCR. These results also open perspective for predictive markers of new targeted therapies.

The Discovery of Novel Biomarkers Improves Breast Cancer Intrinsic Subtype Prediction and Reconciles the Labels in the METABRIC Data Set

BACKGROUND

The prediction of breast cancer intrinsic subtypes has been introduced as a valuable strategy to determine patient diagnosis and prognosis, and therapy response. The PAM50 method, based on the expression levels of 50 genes, uses a single sample predictor model to assign subtype labels to samples. Intrinsic errors reported within this assay demonstrate the challenge of identifying and understanding the breast cancer groups. In this study, we aim to: a) identify novel biomarkers for subtype individuation by exploring the competence of a newly proposed method named CM1 score, and b) apply an ensemble learning, as opposed to the use of a single classifier, for sample subtype assignment. The overarching objective is to improve class prediction.

METHODS AND FINDINGS

The microarray transcriptome data sets used in this study are: the METABRIC breast cancer data recorded for over 2000 patients, and the public integrated source from ROCK database with 1570 samples. We first computed the CM1 score to identify the probes with highly discriminative patterns of expression across samples of each intrinsic subtype. We further assessed the ability of 42 selected probes on assigning correct subtype labels using 24 different classifiers from the Weka software suite. For comparison, the same method was applied on the list of 50 genes from the PAM50 method.

CONCLUSIONS

The CM1 score portrayed 30 novel biomarkers for predicting breast cancer subtypes, with the confirmation of the role of 12 well-established genes. Intrinsic subtypes assigned using the CM1 list and the ensemble of classifiers are more consistent and homogeneous than the original PAM50 labels. The new subtypes show accurate distributions of current clinical markers ER, PR and HER2, and survival curves in the METABRIC and ROCK data sets. Remarkably, the paradoxical attribution of the original labels reinforces the limitations of employing a single sample classifiers to predict breast cancer intrinsic subtypes.