High-throughput genomic technology in research and clinical management of breast cancer. Molecular signatures of progression from benign epithelium to metastatic breast cancer

Multiomics insights on the onset, progression, and metastatic evolution of breast cancer

Breast cancer is the most common malignant neoplasm in women. Despite progress to date, 700,000 women worldwide died of this disease in 2020. Apparently, the prognostic markers currently used in the clinic are not sufficient to determine the most appropriate treatment. For this reason, great efforts have been made in recent years to identify new molecular biomarkers that will allow more precise and personalized therapeutic decisions in both primary and recurrent breast cancers. These molecular biomarkers include genetic and post-transcriptional alterations, changes in protein expression, as well as metabolic, immunological or microbial changes identified by multiple omics technologies (e.g., genomics, epigenomics, transcriptomics, proteomics, glycomics, metabolomics, lipidomics, immunomics and microbiomics). This review summarizes studies based on omics analysis that have identified new biomarkers for diagnosis, patient stratification, differentiation between stages of tumor development (initiation, progression, and metastasis/recurrence), and their relevance for treatment selection. Furthermore, this review highlights the importance of clinical trials based on multiomics studies and the need to advance in this direction in order to establish personalized therapies and prolong disease-free survival of these patients in the future.

Molecular differences between human thyroid follicular adenoma and carcinoma revealed by analysis of a murine model of thyroid cancer

Mouse models can provide useful information to understand molecular mechanisms of human tumorigenesis. In this study, the conditional thyroid mutagenesis of Pten and Ras genes in the mouse, which induces very aggressive follicular carcinomas (FTCs), has been used to identify genes differentially expressed among human normal thyroid tissue (NT), follicular adenoma (FA), and FTC. Global gene expression of mouse FTC was compared with that of mouse normal thyroids: 911 genes were found deregulated ± 2-fold in FTC samples. Then the expression of 45 deregulated genes in mouse tumors was investigated by quantitative RT-PCR in a first cohort of human NT, FA, and FTC (discovery group). Five genes were found significantly down-regulated in FA and FTC compared with NT. However, 17 genes were found differentially expressed between FA and FTC: 5 and 12 genes were overexpressed and underexpressed in FTC vs FA, respectively. Finally, 7 gene products, selected from results obtained in the discovery group, were investigated in a second cohort of human tumors (validation group) by immunohistochemistry. Four proteins showed significant differences between FA and FTC (peroxisomal proliferator-activated receptor-γ, serum deprivation response protein, osteoglycin, and dipeptidase 1). Altogether our data indicate that the establishment of an enriched panel of molecular biomarkers using data coming from mouse thyroid tumors and validated in human specimens may help to set up a more valid platform to further improve diagnosis and prognosis of thyroid malignancies.

Molecular profiling of individual tumor cells by hyperspectral microscopic imaging

We developed a hyperspectral microscopic imaging (HMI) platform that can precisely identify and quantify 10 molecular markers in individual cancer cells in a single pass. The exploitation of an improved separation of circulating tumor cells and the application of HMI provided an opportunity (1) to identify molecular changes in these cells, (2) to recognize the coexpression of these markers, (3) to pose an important opportunity for noninvasive diagnosis, and (4) to use targeted therapy. We balanced the intensity of 10 fluorochromes bound to 10 different antibodies, each specific to a particular tumor marker, so that the intensity of each fluorochrome can be discerned from overlapping emissions. Using 2 touch preps from each primary breast cancer, the average molecular marker intensities of 25 tumor cells gave a representative molecular signature for the tumor despite some cellular heterogeneity. The intensities determined by the HMI correlate well with the conventional 0-3+ analysis by experts in cellular pathology. Because additional multiplexes can be developed using the same fluorochromes but different antibodies, this analysis allows quantification of many molecular markers on a population of tumor cells. HMI can be automated completely, and eventually, it could allow the standardization of protein biomarkers and improve reproducibility among clinical pathology laboratories.

Appearance frequency modulated gene set enrichment testing

BACKGROUND

Gene set enrichment testing has helped bridge the gap from an individual gene to a systems biology interpretation of microarray data. Although gene sets are defined a priori based on biological knowledge, current methods for gene set enrichment testing treat all genes equal. It is well-known that some genes, such as those responsible for housekeeping functions, appear in many pathways, whereas other genes are more specialized and play a unique role in a single pathway. Drawing inspiration from the field of information retrieval, we have developed and present here an approach to incorporate gene appearance frequency (in KEGG pathways) into two current methods, Gene Set Enrichment Analysis (GSEA) and logistic regression-based LRpath framework, to generate more reproducible and biologically meaningful results.

RESULTS

Two breast cancer microarray datasets were analyzed to identify gene sets differentially expressed between histological grade 1 and 3 breast cancer. The correlation of Normalized Enrichment Scores (NES) between gene sets, generated by the original GSEA and GSEA with the appearance frequency of genes incorporated (GSEA-AF), was compared. GSEA-AF resulted in higher correlation between experiments and more overlapping top gene sets. Several cancer related gene sets achieved higher NES in GSEA-AF as well. The same datasets were also analyzed by LRpath and LRpath with the appearance frequency of genes incorporated (LRpath-AF). Two well-studied lung cancer datasets were also analyzed in the same manner to demonstrate the validity of the method, and similar results were obtained.

CONCLUSIONS

We introduce an alternative way to integrate KEGG PATHWAY information into gene set enrichment testing. The performance of GSEA and LRpath can be enhanced with the integration of appearance frequency of genes. We conclude that, generally, gene set analysis methods with the integration of information from KEGG PATHWAY performs better both statistically and biologically.

Peptide and protein imaging mass spectrometry in cancer research

MALDI mass spectrometry is able to acquire protein profiles directly from tissue that can describe the levels of hundreds of distinct proteins. MALDI imaging MS can simultaneously reveal how each of these proteins varies in heterogeneous tissues. Numerous studies have now demonstrated how MALDI imaging MS can generate different protein profiles from the different cell types in a tumor, which can act as biomarker profiles or enable specific candidate protein biomarkers to be identified. MALDI imaging MS can be directly applied to patient samples where its utility is to accomplish untargeted multiplex analysis of the tissue's protein content, enabling the different regions of the tissue to be differentiated on the basis of previously unknown protein profiles/biomarkers. The technique continues to rapidly develop and is now approaching the cusp whereby its potential to provide new diagnostic/prognostic tools for cancer patients can be routinely investigated. Here the latest methodological developments are summarized and its application to a range of tumors is reported in detail. The prospects of MALDI imaging MS are then described from the perspectives of modern pathological practice and MS-based proteomics, to ensure the outlook addresses real clinical needs and reflects the real capabilities of MS-based proteomics of complex tissue samples.

Oncogenic function of microtubule end-binding protein 1 in breast cancer

Microtubule end-binding protein 1 (EB1) is an evolutionarily conserved protein that regulates microtubule dynamics and participates in diverse cell activities. Here, we demonstrate that EB1 expression is up-regulated in human breast cancer specimens and cell lines. The level of EB1 correlates with clinicopathological parameters indicating the malignancy of breast cancer, including higher histological grade, higher pathological tumour node metastasis (pTNM) stage, and higher incidence of lymph node metastasis. Knockdown of EB1 expression remarkably inhibits cancer cell proliferation, and conversely, elevation of its expression promotes cell proliferation. Our data further show that EB1 promotes colony formation and enhances tumour growth in nude mice. In addition, EB1 stimulates Aurora-B activity in breast cancer cells, and EB1 expression correlates with increased Aurora-B activity in clinical samples of breast cancer. These findings thus suggest an oncogenic role for EB1 in breast cancer.

tRNA over-expression in breast cancer and functional consequences

Increased proliferation and elevated levels of protein synthesis are characteristics of transformed and tumor cells. Though components of the translation machinery are often misregulated in cancers, what role tRNA plays in cancer cells has not been explored. We compare genome-wide tRNA expression in cancer-derived versus non-cancer-derived breast cell lines, as well as tRNA expression in breast tumors versus normal breast tissues. In cancer-derived versus non-cancer-derived cell lines, nuclear-encoded tRNAs increase by up to 3-fold and mitochondrial-encoded tRNAs increase by up to 5-fold. In tumors versus normal breast tissues, both nuclear- and mitochondrial-encoded tRNAs increase up to 10-fold. This tRNA over-expression is selective and coordinates with the properties of cognate amino acids. Nuclear- and mitochondrial-encoded tRNAs exhibit distinct expression patterns, indicating that tRNAs can be used as biomarkers for breast cancer. We also performed association analysis for codon usage-tRNA expression for the cell lines. tRNA isoacceptor expression levels are not geared towards optimal translation of house-keeping or cell line specific genes. Instead, tRNA isoacceptor expression levels may favor the translation of cancer-related genes having regulatory roles. Our results suggest a functional consequence of tRNA over-expression in tumor cells. tRNA isoacceptor over-expression may increase the translational efficiency of genes relevant to cancer development and progression.

Molecular markers of breast axillary lymph node metastasis

In breast cancer, axillary lymph node status is one of the most important prognostic variables and a crucial component to the staging system. Several clinico-histopathological parameters are considered to be strong predictors of metastasis; however, they fail to accurately classify breast tumors according to their clinical behavior and to predict which patients will have disease recurrence. Methods based on genome-wide microarray analyses have been used to identify molecular markers with respect to the development of axillary lymph node metastasis. Most of these markers can be detected in the primary tumors, which can potentially lead to the ability to identify patients at the time of diagnosis who are at high risk for lymph node metastasis, allowing for early intervention and more suitable adjuvant treatments.

Multi-faceted role of HSP40 in cancer

HSP40 (DNAJ) is an understudied family of co-chaperones. The human genome codes for over 41 members of HSP40 family that reside at distinct intracellular locations. Despite their large numbers, little is known about their physiologic roles. Recent research has revealed involvement of some of the DNAJ family members in various types of cancers. In this article we summarize the information about the involvement of human DNAJ family members in various aspects of cancer biology. Furthermore we discuss the potential role of the J domain of DNAJ proteins in cancer biology.

Prediction of breast cancer metastasis by genomic profiling: where do we stand?

Current concepts conceive “breast cancer” as a complex disease that comprises several very different types of neoplasms. Nonetheless, breast cancer treatment has considerably improved through early diagnosis, adjuvant chemotherapy, and endocrine treatments. The limited prognostic power of classical classifiers determines considerable over-treatment of women who either do not benefit from, or do not at all need, chemotherapy. Several gene expression based molecular classifiers (signatures) have been developed for a more reliable prognostication. Gene expression profiling identifies profound differences in breast cancers, most probably as a consequence of different cellular origin and different driving mutations and can therefore distinguish the intrinsic propensity to metastasize. Existing signatures have been shown to be useful for treatment decisions, although they have been developed using relatively small sample numbers. Major improvements are expected from the use of large datasets, subtype specific signatures and from the re-introduction of functional information. We show that molecular signatures encounter clear limitations given by the intrinsic probabilistic nature of breast cancer metastasis. Already today, signatures are, however, useful for clinical decisions in specific cases, in particular if the personal inclination of the patient towards different treatment strategies is taken into account.

Evaluation of the current knowledge limitations in breast cancer research: a gap analysis

BACKGROUND

A gap analysis was conducted to determine which areas of breast cancer research, if targeted by researchers and funding bodies, could produce the greatest impact on patients.

METHODS

Fifty-six Breast Cancer Campaign grant holders and prominent UK breast cancer researchers participated in a gap analysis of current breast cancer research. Before, during and following the meeting, groups in seven key research areas participated in cycles of presentation, literature review and discussion. Summary papers were prepared by each group and collated into this position paper highlighting the research gaps, with recommendations for action.

RESULTS

Gaps were identified in all seven themes. General barriers to progress were lack of financial and practical resources, and poor collaboration between disciplines. Critical gaps in each theme included: (1) genetics (knowledge of genetic changes, their effects and interactions); (2) initiation of breast cancer (how developmental signalling pathways cause ductal elongation and branching at the cellular level and influence stem cell dynamics, and how their disruption initiates tumour formation); (3) progression of breast cancer (deciphering the intracellular and extracellular regulators of early progression, tumour growth, angiogenesis and metastasis); (4) therapies and targets (understanding who develops advanced disease); (5) disease markers (incorporating intelligent trial design into all studies to ensure new treatments are tested in patient groups stratified using biomarkers); (6) prevention (strategies to prevent oestrogen-receptor negative tumours and the long-term effects of chemoprevention for oestrogen-receptor positive tumours); (7) psychosocial aspects of cancer (the use of appropriate psychosocial interventions, and the personal impact of all stages of the disease among patients from a range of ethnic and demographic backgrounds).

CONCLUSION

Through recommendations to address these gaps with future research, the long-term benefits to patients will include: better estimation of risk in families with breast cancer and strategies to reduce risk; better prediction of drug response and patient prognosis; improved tailoring of treatments to patient subgroups and development of new therapeutic approaches; earlier initiation of treatment; more effective use of resources for screening populations; and an enhanced experience for people with or at risk of breast cancer and their families. The challenge to funding bodies and researchers in all disciplines is to focus on these gaps and to drive advances in knowledge into improvements in patient care.