Tumour cell dissemination and growth of metastasis

A natural history and copula-based joint model for regional and distant breast cancer metastasis

The few existing statistical models of breast cancer recurrence and progression to distant metastasis are predominantly based on multi-state modelling. While useful for summarising the risk of recurrence, these provide limited insight into the underlying biological mechanisms and have limited use for understanding the implications of population-level interventions. We develop an alternative, novel, and parsimonious approach for modelling latent tumour growth and spread to local and distant metastasis, based on a natural history model with biologically inspired components. We include marginal sub-models for local and distant breast cancer metastasis, jointly modelled using a copula function. Different formulations (and correlation shapes) are allowed, thus we can incorporate and directly model the correlation between local and distant metastasis flexibly and efficiently. Submodels for the latent cancer growth, the detection process, and screening sensitivity, together with random effects to account for between-patients heterogeneity, are included. Although relying on several parametric assumptions, the joint copula model can be useful for understanding - potentially latent - disease dynamics, obtaining patient-specific, model-based predictions, and studying interventions at a population level, for example, using microsimulation. We illustrate this approach using data from a Swedish population-based case-control study of postmenopausal breast cancer, including examples of useful model-based predictions.

Estimating latent, dynamic processes of breast cancer tumour growth and distant metastatic spread from mammography screening data

We propose a framework for jointly modelling tumour size at diagnosis and time to distant metastatic spread, from diagnosis, based on latent dynamic sub-models of growth of the primary tumour and of distant metastatic detection. The framework also includes a sub-model for screening sensitivity as a function of latent tumour size. Our approach connects post-diagnosis events to the natural history of cancer and, once refined, may prove useful for evaluating new interventions, such as personalised screening regimes. We evaluate our model-fitting procedure using Monte Carlo simulation, showing that the estimation algorithm can retrieve the correct model parameters, that key patterns in the data can be captured by the model even with misspecification of some structural assumptions, and that, still, with enough data it should be possible to detect strong misspecifications. Furthermore, we fit our model to observational data from an extension of a case-control study of post-menopausal breast cancer in Sweden, providing model-based estimates of the probability of being free from detected distant metastasis as a function of tumour size, mode of detection (of the primary tumour), and screening history. For women with screen-detected cancer and two previous negative screens, the probabilities of being free from detected distant metastases 5 years after detection and removal of the primary tumour are 0.97, 0.89 and 0.59 for tumours of diameter 5, 15 and 35 mm, respectively. We also study the probability of having latent/dormant metastases at detection of the primary tumour, estimating that 33% of patients in our study had such metastases.

Surface-Enhanced Raman Scattering (SERS) Spectroscopy for Sensing and Characterization of Exosomes in Cancer Diagnosis

Simple Summary

The distinct molecular and biological properties of exosomes, together with their abundance and stability, make them an ideal target in liquid biopsies for early diagnosis and disease monitoring. On the other hand, in recent years, nanomaterial-based optical biosensors have been extensively investigated as novel, rapid and sensitive tools for exosome detection and discrimination. The scope of this review is to summarize and coherently discussed the diverse applications, challenges and limitations of nanosensors based on surface-enhanced Raman spectroscopy (SERS) as the optosensing technique.

Abstract

Exosomes are emerging as one of the most intriguing cancer biomarkers in modern oncology for early cancer diagnosis, prognosis and treatment monitoring. Concurrently, several nanoplasmonic methods have been applied and developed to tackle the challenging task of enabling the rapid, sensitive, affordable analysis of exosomes. In this review, we specifically focus our attention on the application of plasmonic devices exploiting surface-enhanced Raman spectroscopy (SERS) as the optosensing technique for the structural interrogation and characterization of the heterogeneous nature of exosomes. We summarized the current state-of-art of this field while illustrating the main strategic approaches and discuss their advantages and limitations.

Modeling breast cancer survival and metastasis rates from moderate-sized clinical data

Predicting time-dependent survival probability of a breast cancer patient using information such as primary tumor size, grade, node spread status, and patient age at the time of surgery can be of immense help in managing life expectations and strategizing postoperative treatment. However, for moderate-sized clinical datasets the application of standard Kaplan-Meier theory to determine survival probability as a function of multiple cofactors can become challenging when continuous variables like tumor diameter and survival time are segmented into a large number of narrow intervals, a problem commonly termed the curse of dimensionality. We circumvent this problem by modeling the patient-to-patient distribution of primary tumor diameter with a realistic, right-skewed function, and then matching the diameter-marginalized survival with the mean Kaplan-Meier survival for the data. We apply this procedure on a recent clinical data from 1875 breast cancer patients and develop parameters that can be readily used to estimate post-surgery survival for an arbitrary time length. Finally, we show that the observed fraction of node-positive patients can be quantitatively explained within a simple tumor growth and metastasis framework. Employing two different tumor growth models from the literature (i.e., Gompertz and logistic growth models), we utilize the observed fraction-node-positive data to determine metastasis rates from the surface of a primary tumor and its patient-to-patient distribution.

[Genetic instability, a factor limiting the efficiency of targeted therapies in solid oncology]

Genomic instability is one of the main properties of tumour development, promoting first the acquisition of genetic alterations and thus carcinogenesis. Then, the chronic and anarchic proliferation of cancer cells also supports and contributes to this instability allowing a continuous evolution of the tumour. The accumulation of mutations resulting from that instability contributes to tumour heterogeneity that occurs in a specific environment. The resulting diversity of oncogenic drivers further complicates the characterization of the origin of cancer cells dysfunction and consequently therapeutic decision. However, the consideration of the molecular context in oncology has initiated the development of targeted therapies. Based on the concept of oncogene addiction and synthetic lethality, these new drugs require the characterization and identification of specific tumour biomarkers. Targeted therapies have thus considerably optimized patient management, improving efficiency and quality of life while limiting the side effects observed with conventional chemotherapies. However, despite significant clinical benefits, some major limitations to their administration remain. The study of the current issues related to these new therapeutic molecules is becoming crucial for patient management towards an improvement of personalized medicine.

The emerging links between chromosomal instability (CIN), metastasis, inflammation and tumour immunity

Many cancers possess an incorrect number of chromosomes, a state described as aneuploidy. Aneuploidy is often caused by Chromosomal Instability (CIN), a process of continuous chromosome mis-segregation. CIN is believed to endow tumours with enhanced evolutionary capabilities due to increased intratumour heterogeneity, and facilitating adaptive resistance to therapies. Recently, however, additional consequences and associations with CIN have been revealed, prompting the need to understand this universal hallmark of cancer in a multifaceted context. This review is focused on the investigation of possible links between CIN, metastasis and the host immune system in cancer development and treatment. We specifically focus on these links since most cancer deaths are due to the consequences of metastasis, and immunotherapy is a rapidly expanding novel avenue of cancer therapy.

Molecular characterisation and liquid biomarkers in Carcinoma of Unknown Primary (CUP): taking the 'U' out of 'CUP'

Cancers of Unknown Primary (CUP) comprise a heterogeneous clinical entity of confirmed metastatic cancer where the primary site of origin is undetectable. It has a poor prognosis with limited treatment options. CUP is historically under-researched; however, understanding its biology has the potential to not only improve treatment and survival by implementation of biomarkers for patient management, but also to greatly contribute to our understanding of carcinogenesis and metastasis across all cancer types. Here we review the current advances in CUP research and explore the debated hypotheses underlying its biology. The evolution of molecular profiling and tissue-of-origin classifiers have the potential to transform the diagnosis, classification and therapeutic management of patients with CUP but robust evidence to support widespread use is lacking. Precision medicine has transformed treatment strategy in known tumour types; in CUP, however, there remains a clinical need for a better understanding of molecular characteristics to establish the potential role of novel or existing therapeutics. The emergence of liquid biopsies as a source of predictive and prognostic biomarkers within known tumour types is gaining rapid ground and this review explores the potential utility of liquid biopsies in CUP.

Primary Tumors Limit Metastasis Formation through Induction of IL15-Mediated Cross-Talk between Patrolling Monocytes and NK Cells

Metastases are responsible for the vast majority of cancer-related deaths. Although tumor cells can become invasive early during cancer progression, metastases formation typically occurs as a late event. How the immune response to primary tumors may dictate this outcome remains poorly understood, which hampers our capacity to manipulate it therapeutically. Here, we used a two-step experimental model, based on the highly aggressive B16F10 melanoma, that temporally segregates the establishment of primary tumors (subcutaneously) and the formation of lung metastases (from intravenous injection). This allowed us to identify a protective innate immune response induced by primary tumors that inhibits experimental metastasis. We found that in the presence of primary tumors, increased numbers of natural killer (NK) cells with enhanced IFNγ, granzyme B, and perforin production were recruited to the lung upon metastasis induction. These changes were mirrored by a local accumulation of patrolling monocytes and macrophages with high expression of MHC class II and NOS2. Critically, the protective effect on metastasis was lost upon patrolling monocyte or NK cell depletion, IL15 neutralization, or IFNγ ablation. The combined analysis of these approaches allowed us to establish a hierarchy in which patrolling monocytes, making IL15 in response to primary tumors, activate NK cells and IFNγ production that then inhibit lung metastasis formation. This work identifies an innate cell network and the molecular determinants responsible for "metastasis immunosurveillance," providing support for using the key molecular mediator, IL15, to improve immunotherapeutic outcomes. Cancer Immunol Res; 5(9); 812-20. ©2017 AACR.

CTCs in early breast cancer: A path worth taking

Circulating tumor cells (CTCs) are cellular elements of undeniable significance that spread from the tumor mass into the peripheral blood and constitute one of the main vehicles for disease diffusion. Their rarity, in addition to a number of molecular and cellular features, has severely impaired research and exploitation. CTCs have been evaluated in early breast cancer (EBC), although long from being fully accepted in this field also due to a lack of technical standardization. CTCs hold promise to be a powerful non-invasive real-time measurable biomarker in all disease stages. This hypothesis is particularly appealing in the adjuvant setting of breast cancer, as it still lacks a marker that could play a central role in monitoring disease-free intervals, predicting early relapse and guiding drug selection. This review aimed to discuss CTC characteristics and show the main results of CTC-research in EBC setting, stating the urgency to continue basic and translational research in this field to definitely translate this marker from bench to bedside.

Emerging nanomedicine approaches fighting tumor metastasis: animal models, metastasis-targeted drug delivery, phototherapy, and immunotherapy

Nanomedicine approaches may bring new opportunities for tumor metastasis treatment.