Paradoxical relationship between chromosomal instability and survival outcome in cancer

Cancer chromosomal instability: therapeutic and diagnostic challenges

Chromosomal instability (CIN)-which is a high rate of loss or gain of whole or parts of chromosomes-is a characteristic of most human cancers and a cause of tumour aneuploidy and intra-tumour heterogeneity. CIN is associated with poor patient outcome and drug resistance, which could be mediated by evolutionary adaptation fostered by intra-tumour heterogeneity. In this review, we discuss the clinical consequences of CIN and the challenges inherent to its measurement in tumour specimens. The relationship between CIN and prognosis supports assessment of CIN status in the clinical setting and suggests that stratifying tumours according to levels of CIN could facilitate clinical risk assessment.

Karyotypic determinants of chromosome instability in aneuploid budding yeast

Recent studies in cancer cells and budding yeast demonstrated that aneuploidy, the state of having abnormal chromosome numbers, correlates with elevated chromosome instability (CIN), i.e. the propensity of gaining and losing chromosomes at a high frequency. Here we have investigated ploidy- and chromosome-specific determinants underlying aneuploidy-induced CIN by observing karyotype dynamics in fully isogenic aneuploid yeast strains with ploidies between 1N and 2N obtained through a random meiotic process. The aneuploid strains exhibited various levels of whole-chromosome instability (i.e. chromosome gains and losses). CIN correlates with cellular ploidy in an unexpected way: cells with a chromosomal content close to the haploid state are significantly more stable than cells displaying an apparent ploidy between 1.5 and 2N. We propose that the capacity for accurate chromosome segregation by the mitotic system does not scale continuously with an increasing number of chromosomes, but may occur via discrete steps each time a full set of chromosomes is added to the genome. On top of such general ploidy-related effect, CIN is also associated with the presence of specific aneuploid chromosomes as well as dosage imbalance between specific chromosome pairs. Our findings potentially help reconcile the divide between gene-centric versus genome-centric theories in cancer evolution.

Centromere protein-A, an essential centromere protein, is a prognostic marker for relapse in estrogen receptor-positive breast cancer

INTRODUCTION

Centromere protein A (CENP-A), an essential centromere protein, has been associated with high grade cancers. This study was undertaken to determine if CENP-A is a prognostic factor for breast cancer patients not receiving systemic therapy or predictive of response to tamoxifen or neoadjuvant chemotherapy.

METHODS

mRNA levels of CENP-A and CENP-B, a centromere protein that binds independently of CENP-A, were measured in breast cancer specimens from 484 patients receiving no systemic therapy, 276 patients receiving tamoxifen, and 233 patients treated with neoadjuvant chemotherapy. Associations between CENP-A, CENP-B, Ki-67, relapse, and chemotherapy response were determined.

RESULTS

CENP-A but not CENP-B was higher in estrogen receptor (ER)-negative tumors than ER-positive tumors and positively correlated with Ki-67 expression. Among patients with ER-positive disease who received no systemic therapy or tamoxifen, higher levels of CENP-A were associated with lower rates of 5-year distant relapse free survival (DRFS). On multivariate analyses including Ki-67, high CENP-A expression had a hazard ratio of 10.9 for relapse in patients with ER-positive disease not receiving systemic therapy (95% CI, 2.86 to 41.78; P = 0.00047) and 1.64 for patients with ER-positive disease receiving tamoxifen (95% CI, 0.99 to 2.71; P = 0.054). CENP-A was not an independent prognostic marker in ER-negative tumors. For both ER-positive and ER-negative tumors, CENP-A was not a significant independent predictor of chemotherapy response.

CONCLUSIONS

CENP-A was a significant independent prognostic marker for patients with ER-positive breast cancer not treated with systemic therapy but had limited predictive value in tamoxifen treated patients and was not predictive of response to neoadjuvant chemotherapy.

Chromosomal instability and cancer: a complex relationship with therapeutic potential

Chromosomal instability (CIN) is a hallmark of human neoplasms. Despite its widespread prevalence, knowledge of the mechanisms and contributions of CIN in cancer has been elusive. It is now evident that the role of CIN in tumor initiation and growth is more complex than previously thought. Furthermore, distinguishing CIN, which consists of elevated rates of chromosome missegregation, from aneuploidy, which is a state of abnormal chromosome number, is crucial to understanding their respective contributions in cancer. Collectively, experimental evidence suggests that CIN enables tumor adaptation by allowing tumors to constantly sample the aneuploid fitness landscape. This complex relationship, together with the potential to pharmacologically influence chromosome missegregation frequencies in cancer cells, offers previously unrecognized means to limit tumor growth and its response to therapy.

Genetic heterogeneity and cancer drug resistance

Despite the success of targeted therapies in the treatment of cancer, the development of resistance limits the ability to translate this method into a curative treatment. The mechanisms of resistance have traditionally been thought of as intrinsic (ie, present at baseline) or acquired (ie, developed after initial response). Recent evidence has challenged the notion of acquired resistance. Although cancers are traditionally thought to be clonal, there is now evidence of intra-tumour genetic heterogeneity in most cancers. The clinical pattern of acquired resistance in many circumstances represents outgrowth of resistant clones that might have originally been present in the primary cancer at low frequency but that have expanded under the selective pressure imposed by targeted therapies. Here, we describe the potential role of clonal heterogeneity in resistance to targeted therapy, discuss genetic instability as one of its causes, and detail approaches to tackle intra-tumour heterogeneity in the clinic.

A breast cancer meta-analysis of two expression measures of chromosomal instability reveals a relationship with younger age at diagnosis and high risk histopathological variables

Breast cancer in younger patients often presents with adverse histopathological features, including increased frequency of estrogen receptor negative and lymph node positive disease status. Chromosomal instability (CIN) is increasingly recognised as an important prognostic variable in solid tumours. In a breast cancer meta-analysis of 2423 patients we examine the relationship between clinicopathological parameters and two distinct chromosomal instability gene expression signatures in order to address whether younger age at diagnosis is associated with increased tumour genome instability. We find that CIN, assessed by the two independently derived CIN expression signatures, is significantly associated with increased tumour size, ER negative or HER2 positive disease, higher tumour grade and younger age at diagnosis in ER negative breast cancer. These data support the hypothesis that chromosomal instability may be a defining feature of breast cancer biology and clinical outcome.

Tumour heterogeneity and drug resistance: personalising cancer medicine through functional genomics

Intrinsic and acquired drug resistance leads to the eventual failure of cancer treatment regimens in the majority of advanced solid tumours. Understanding drug resistance mechanisms will prove vital in the future development of personalised therapeutic approaches. Functional genomics technologies may permit the discovery of predictive biomarkers by unravelling pathways involved in drug resistance and allow the systematic identification of novel therapeutic targets. Such technologies offer the opportunity to develop personalised treatments and diagnostic tools that may improve the survival and quality of life of patients with cancer. However, despite progress in biomarker and drug target discovery, inter-tumour and intra-tumour molecular heterogeneity will limit the effective treatment of this disease. Combining an improved understanding of cancer cell survival mechanisms associated with intra-tumour heterogeneity and drug resistance may allow the selection of patients for specific treatment regimens that will maximise benefit, limit the acquisition of drug resistance and lessen the impact of deleterious side effects.

Delineation of two clinically and molecularly distinct subgroups of posterior fossa ependymoma

Despite the histological similarity of ependymomas from throughout the neuroaxis, the disease likely comprises multiple independent entities, each with a distinct molecular pathogenesis. Transcriptional profiling of two large independent cohorts of ependymoma reveals the existence of two demographically, transcriptionally, genetically, and clinically distinct groups of posterior fossa (PF) ependymomas. Group A patients are younger, have laterally located tumors with a balanced genome, and are much more likely to exhibit recurrence, metastasis at recurrence, and death compared with Group B patients. Identification and optimization of immunohistochemical (IHC) markers for PF ependymoma subgroups allowed validation of our findings on a third independent cohort, using a human ependymoma tissue microarray, and provides a tool for prospective prognostication and stratification of PF ependymoma patients.

Relationship of extreme chromosomal instability with long-term survival in a retrospective analysis of primary breast cancer

BACKGROUND

Chromosomal instability (CIN) is thought to be associated with poor prognosis in solid tumors; however, evidence from preclinical and mouse tumor models suggest that CIN may paradoxically enhance or impair cancer cell fitness. Breast cancer prognostic expression signature sets, which reflect tumor CIN status, efficiently delineate outcome in estrogen receptor ER-positive breast cancer in contrast to ER-negative breast cancer, suggesting that the relationship of CIN with prognosis differs in these two breast cancer subtypes.

METHODS

Direct assessment of CIN requires single-cell analysis methods, such as centromeric FISH, aimed at determining the variation around the modal number of two or more chromosomes within individual tumor nuclei. Here, we document the frequency of tumor CIN by dual centromeric FISH analysis in a retrospective primary breast cancer cohort of 246 patients with survival outcome.

RESULTS

There was increased CIN and clonal heterogeneity in ER-negative compared with ER-positive breast cancer. Consistent with a negative impact of CIN on cellular fitness, extreme CIN in ER-negative breast cancer was an independent variable associated with improved long-term survival in multivariate analysis. In contrast, a linear relationship of increasing CIN with poorer prognosis in ER-positive breast cancer was observed, using three independent measures of CIN.

CONCLUSIONS

The paradoxical relationship between extreme CIN and cancer outcome in the ER-negative cohorts may explain why prognostic expression signatures, reflecting tumor CIN status, fail to predict outcome in this subgroup.

IMPACT

Assessment of tumor CIN status may support risk stratification in ER-negative breast cancer and requires prospective validation.

Centrosome clustering and chromosomal (in)stability: a matter of life and death

Centrosome abnormalities occur commonly in cancer, and contribute to chromosomal instability and tumorigenesis. New evidence on a phylogenetically conserved mechanism termed 'centrosomal clustering' provides exciting insights into how cells with supernumerary centrosomes adapt to avoid lethal multipolar divisions. Here, we highlight the emerging molecular basis of centrosome clustering, and its impact on asymmetric divisions of stem cells, chromosomal (in)stability and malignant transformation. Finally, pharmacological inhibition of centrosome clustering promises to selectively target tumor cells.