Implications of personalized medicine—perspective from a cancer center

A Review of Artificial Intelligence and Robotics in Transformed Health Ecosystems

Health care is shifting toward become proactive according to the concept of P5 medicine-a predictive, personalized, preventive, participatory and precision discipline. This patient-centered care heavily leverages the latest technologies of artificial intelligence (AI) and robotics that support diagnosis, decision making and treatment. In this paper, we present the role of AI and robotic systems in this evolution, including example use cases. We categorize systems along multiple dimensions such as the type of system, the degree of autonomy, the care setting where the systems are applied, and the application area. These technologies have already achieved notable results in the prediction of sepsis or cardiovascular risk, the monitoring of vital parameters in intensive care units, or in the form of home care robots. Still, while much research is conducted around AI and robotics in health care, adoption in real world care settings is still limited. To remove adoption barriers, we need to address issues such as safety, security, privacy and ethical principles; detect and eliminate bias that could result in harmful or unfair clinical decisions; and build trust in and societal acceptance of AI.

Dynamics-Adapted Radiotherapy Dose (DARD) for Head and Neck Cancer Radiotherapy Dose Personalization

Standard of care radiotherapy (RT) doses have been developed as a one-size-fits all approach designed to maximize tumor control rates across a population. Although this has led to high control rates for head and neck cancer with 66-70 Gy, this is done without considering patient heterogeneity. We present a framework to estimate a personalized RT dose for individual patients, based on pre- and early on-treatment tumor volume dynamics-a dynamics-adapted radiotherapy dose (D_DARD). We also present the results of an in silico trial of this dose personalization using retrospective data from a combined cohort of n = 39 head and neck cancer patients from the Moffitt and MD Anderson Cancer Centers that received 66-70 Gy RT in 2-2.12 Gy weekday fractions. This trial was repeated constraining D_DARD between (54, 82) Gy to test more moderate dose adjustment. D_DARD was estimated to range from 8 to 186 Gy, and our in silico trial estimated that 77% of patients treated with standard of care were overdosed by an average dose of 39 Gy, and 23% underdosed by an average dose of 32 Gy. The in silico trial with constrained dose adjustment estimated that locoregional control could be improved by >10%. We demonstrated the feasibility of using early treatment tumor volume dynamics to inform dose personalization and stratification for dose escalation and de-escalation. These results demonstrate the potential to both de-escalate most patients, while still improving population-level control rates.

Prognostic significance of the Controlling Nutritional Status (CONUT) score in surgically treated breast cancer patients

Background

Breast cancer is one of the most common malignancy in women with high mortality rate. Given the growing evidence shows that immune-inflammatory system influences the survival of patients with cancer, we assessed the prognostic significance of the preoperative Controlling Nutritional Status (CONUT) score in patients with breast cancer who underwent surgery.

Methods

We conducted a retrospective analysis of 1,367 breast cancer patients who underwent surgery between December 2010 and October 2012. All individual preoperative serum albumin concentration, total cholesterol concentration, and total peripheral lymphocyte count were counted to calculate CONUT. Higher CONUT score is in line with worse nutritional status. The optimal cut-off of CONUT score was set at 3 to categorize the investigated patients into two groups, namely a high- or low-CONUT score group. We adopted univariate and multivariate analyses (Cox proportional hazards regression model) statistical method.

Results

Patients in the high-CONUT score group had shorter overall survival (OS) and recurrence-free survival (RFS) in comparison with those in the low-CONUT score group, 66.43 vs. 69.30 months and 54.70 vs. 59.98 months respectively (all P value <0.05). Univariate and multivariate analyses revealed that the CONUT score was an independent predictor of OS (P=0.029 and 0.046, respectively) and RFS (P=0.001, P=0.013, respectively).

Conclusions

The CONUT score was identified as an independent prognostic indicator in surgically treated breast cancer patients, indicating that, compared with the low CONUT score, a high CONUT score may lead to poorer prognosis.

Comprehensive analysis of genomic alterations detected by next-generation sequencing-based tissue and circulating tumor DNA assays in Chinese patients with non-small cell lung cancer

While tumor genotyping is the standard treatment for patients with non-small cell lung cancer (NSCLC), spatial and temporal tumor heterogeneity and insufficient specimens can lead to limitations in the use of tissue-based sequencing. Circulating tumor DNA (ctDNA) fully encompasses tumor-specific sequence alterations and offers an alternative to tissue sample biopsies. However, few studies have evaluated whether the frequency of multiple genomic alterations observed following ctDNA sequencing is similar to that observed following tissue sequencing in NSCLC. Therefore, in the present study, targeted next-generation sequencing (NGS) was performed on tissue and plasma ctDNA samples in 99 patients with NSCLC. Overall, the frequencies of genetic alterations detected in ctDNA were positively correlated with those detected via tissue profiling (r=0.812; P=0.022). Genomic data revealed significant mutual exclusivity between alterations in epidermal growth factor receptor (EGFR) and tumor protein 53 (TP53; P=0.020), and between alterations in EGFR and KRAS (P=0.008), as well as potential mutual exclusivity between alterations in EGFR and Erb-B2 receptor tyrosine kinase 2 (P=0.059). Furthermore, the EGFR mutant allele frequency (MAF) was positively correlated with the TP53 MAF in individual tumors (r=0.773; P=0.005), and there was a marked difference in the EGFR MAF between patients with and without the TP53 mutation (P=0.001). Levels of the tumor serum marker CA242 in patients with ctDNA-detectable mutations were higher compared with those in patients without ctDNA-detectable mutations. The data from the present study highlight the importance of tissue and plasma ctDNA screening by NGS to guide personalized therapy and promote the clinical management of patients with NSCLC.

Overcoming BET Inhibitor Resistance in Malignant Peripheral Nerve Sheath Tumors

PURPOSE

BET bromodomain inhibitors have emerged as a promising therapy for numerous cancer types in preclinical studies, including neurofibromatosis type 1 (NF1)-associated malignant peripheral nerve sheath tumor (MPNST). However, potential mechanisms underlying resistance to these inhibitors in different cancers are not completely understood. In this study, we explore new strategy to overcome BET inhibitor resistance in MPNST.Experimental Design: Through modeling tumor evolution by studying genetic changes underlying the development of MPNST, a lethal sarcoma with no effective medical treatment, we identified a targetable addiction to BET bromodomain family member BRD4 in MPNST. This served as a controlled model system to delineate mechanisms of sensitivity and resistance to BET bromodomain inhibitors in this disease.

RESULTS

Here, we show that a malignant progression-associated increase in BRD4 protein levels corresponds to partial sensitivity to BET inhibition in MPNST. Strikingly, genetic depletion of BRD4 protein levels synergistically sensitized MPNST cells to diverse BET inhibitors in culture and in vivo.

CONCLUSIONS

Collectively, MPNST sensitivity to combination genetic and pharmacologic inhibition of BRD4 revealed the presence of a unique addiction to BRD4 in MPNST. Our discovery that a synthetic lethality exists between BET inhibition and reduced BRD4 protein levels nominates MPNST for the investigation of emerging therapeutic interventions such as proteolysis-targeting chimeras (PROTACs) that simultaneously target bromodomain activity and BET protein abundance.

The clinical characteristics and prognostic analysis of Chinese advanced NSCLC patients based on circulating tumor DNA sequencing

Purpose

Circulating tumor DNA (ctDNA) is a noninvasive and real-time marker for tumor diagnosis, prognosis, and prediction. However, further investigations about ctDNA prognostic and predictive value are still needed, and conclusions from several studies were inconsistent.

Experimental design

We performed capture-based targeted ultradeep sequencing on liquid biopsies from a cohort of 34 advanced Chinese non-small-cell lung cancer (NSCLC) patients and analyzed the clinical use of ctDNA in this study.

Results

On the basis of clinical characteristics of the 34 NSCLC patients, we found that brain metastasis correlated with shorter progression-free survival (PFS) and is more prone to happen in younger patients. After ctDNA sequencing, we analyzed the prognostic value of baseline ctDNA. In osimertinib-treated group, high max allelic fraction (maxAF) correlated with shorter PFS. But for the cohort of 34 patients, no correlation can be observed between maxAF and PFS. We also presented two cases to demonstrate the value of disease progression prediction by ctDNA, which can be detected earlier than clinical response.

Conclusion

In this study, we demonstrated that ctDNA is a prognostic marker for evaluating treatment response and predicting recurrence in advanced NSCLC. Further investigations with larger cohort and uniformed patient background are still needed to validate our findings.

Towards personalized medicine of colorectal cancer

Efforts in colorectal cancer (CRC) research aim to improve early detection and treatment for metastatic stages which could translate into better prognosis of this disease. One of the major challenges that hinder these efforts is the heterogeneous nature of CRC and involvement of diverse molecular pathways. New large-scale 'omics' technologies are making it possible to generate, analyze and interpret biological data from molecular determinants of CRC. The developments of sophisticated computational analyses would allow information from different omics platforms to be integrated, thus providing new insights into the biology of CRC. Together, these technological advances and an improved mechanistic understanding might allow CRC to be clinically managed at the level of the individual patient. This review provides an account of the current challenges in CRC management and an insight into how new technologies could allow the development of personalized medicine for CRC.

Participant Attitudes Toward an Intensive Trial of Multiple Biopsies, Multidimensional Molecular Analysis, and Reporting of Results in Metastatic Triple-Negative Breast Cancer

Purpose

Multidimensional molecular analysis of tumor tissue intensively over space and time can provide insight into how cancers evolve and escape treatment. Attitudes of participants in such trials have not been assessed. We explored patient views regarding an intensive study incorporating multiple biopsies, multidimensional molecular testing, and drug response predictions that are reported to the oncologist and patient.

Patients and Methods

A structured, self-administered survey was conducted among the first 15 patients enrolled in ITOMIC-001 (Intensive Trial of Omics in Cancer). Patients with metastatic triple-negative breast cancer were accrued at two sites in Washington state. Surveys containing 17 items were administered at enrollment and after the return of results. Surveys explored perceptions regarding risks, personal benefits, benefits to others, uncertainties associated with interpreting complex molecular results, concerns regarding multiple biopsies, and potential loss of confidentiality. At follow-up, three additional unique items explored patient coping.

Results

All participants expressed a strong desire for their experiences to benefit others, and all perceived a higher likelihood of deriving benefit than described during detailed consent discussions. Loss of confidentiality ranked lowest among patient concerns. Despite acknowledging uncertainties and risks inherent in complex molecular testing for clinical reporting, participants wanted access to findings in evaluating treatment choices, even if the best available evidence was weak. Follow-up surveys demonstrated relatively little change in attitudes, although concern about study biopsies generally declined. Study participation helped several patients cope better with their disease.

Conclusion

In advanced breast cancer, these findings demonstrate the feasibility of engaging motivated patients in trials that navigate the uncertainties associated with intensive spatial and longitudinal multidimensional molecular testing for the purpose of advancing precision medicine.

A genome-based model for adjusting radiotherapy dose (GARD): a retrospective, cohort-based study

BACKGROUND

Despite its common use in cancer treatment, radiotherapy has not yet entered the era of precision medicine, and there have been no approaches to adjust dose based on biological differences between or within tumours. We aimed to assess whether a patient-specific molecular signature of radiation sensitivity could be used to identify the optimum radiotherapy dose.

METHODS

We used the gene-expression-based radiation-sensitivity index and the linear quadratic model to derive the genomic-adjusted radiation dose (GARD). A high GARD value predicts for high therapeutic effect for radiotherapy; which we postulate would relate to clinical outcome. Using data from the prospective, observational Total Cancer Care (TCC) protocol, we calculated GARD for primary tumours from 20 disease sites treated using standard radiotherapy doses for each disease type. We also used multivariable Cox modelling to assess whether GARD was independently associated with clinical outcome in five clinical cohorts: Erasmus Breast Cancer Cohort (n=263); Karolinska Breast Cancer Cohort (n=77); Moffitt Lung Cancer Cohort (n=60); Moffitt Pancreas Cancer Cohort (n=40); and The Cancer Genome Atlas Glioblastoma Patient Cohort (n=98).

FINDINGS

We calculated GARD for 8271 tissue samples from the TCC cohort. There was a wide range of GARD values (range 1·66-172·4) across the TCC cohort despite assignment of uniform radiotherapy doses within disease types. Median GARD values were lowest for gliomas and sarcomas and highest for cervical cancer and oropharyngeal head and neck cancer. There was a wide range of GARD values within tumour type groups. GARD independently predicted clinical outcome in breast cancer, lung cancer, glioblastoma, and pancreatic cancer. In the Erasmus Breast Cancer Cohort, 5-year distant-metastasis-free survival was longer in patients with high GARD values than in those with low GARD values (hazard ratio 2·11, 95% 1·13-3·94, p=0·018).

INTERPRETATION

A GARD-based clinical model could allow the individualisation of radiotherapy dose to tumour radiosensitivity and could provide a framework to design genomically-guided clinical trials in radiation oncology.

FUNDING

None.

From Uniplex to Multiplex Molecular Profiling in Advanced Non-Small Cell Lung Carcinoma

Non-small cell lung carcinoma is a leading cause of cancer death worldwide. Understanding the molecular biology of survival and proliferation of cancer cells led to a new molecular classification of lung cancer and the development of targeted therapies with promising results. With the advances of image-guided biopsy techniques, tumor samples are becoming smaller, and the molecular testing techniques have to overcome the challenge of integrating the characterization of a panel of abnormalities including gene mutations, copy-number changes, and fusions in a reduced number of assays using only a small amount of genetic material. This article reviews the current knowledge about the most frequent actionable molecular abnormalities in non-small cell lung carcinoma, the new approaches of molecular analysis, and the implications of these findings in the context of clinical practice.

What's in a word? The person of personalized (nano)medicine

Personalized medicine has recently become a main goal for healthcare policy. It is often defined as the tailoring of diagnosis and therapies to the genetic profile of each patient, and as such it is supposed to overcome the major thorny issues at stake in biomedicine today. This challenging program is primarily carried out by new approaches in biomedical imaging, molecular analysis, drug delivery and follow-up, taking more and more advantage of nanotechnology. However, in current literature and debates, the term ‘personalized medicine’ appears to be polysemous. The paper examines this polysemy. It links it to rival epistemic and technological choices in research programs, and it finally argues that this techno-epistemic plurality echoes conflicting expectations and values among today's biomedicine actors.

[The invention of personalized medicine, between technological upheavals and utopia]

The idea of personalized medicine raises a series of questions. If one considers that the physician takes into account the uniqueness of his patient in the frame of the medical consultation, is the definition of medicine as "personalized" not a pleonasm? If not, why has this ambiguous denomination been adopted? In addition, is this form of medicine a novel discipline capable of revolutionizing therapeutic approaches as claimed in its accompanying discourses or is it in continuity with the molecular conception of biomedicine? Rather than attempting to directly answer these questions, we focused our attention on the organizing concepts, the technological breakthroughs and the transformations in medical practices that characterize this medicine. Following this brief analysis, it appears that the choice of a term as equivocal as personalized medicine and the emphasis on the antagonistic notions of revolution and continuity in medicine are the signs of reshuffling that is emerging between actors in the health care system, in academia and in pharmaceutical companies.

[Promises and limits of genomics and its applications]

This text traces the extraordinary advances made in genomics for 40 years: recombinant DNA, transgenesis or genetic sequencing. In recent years, the model "all genetics" was questioned and post-genomics emerged in the molecular landscape. The promises of medical advances are many and the ethical issues that accompany them are challenges. Advances in synthetic biology are a relevant illustration of these promises and challenges.

The challenge of intratumour heterogeneity in precision medicine

Cells within tumours have diverse genomes and epigenomes and interact differentially with their surrounding microenvironment generating intratumour heterogeneity, which has critical implications for treating cancer patients. Understanding the cellular and microenvironment composition and characteristics in individual tumours is critical to stratify the patient population that is likely to benefit from specific treatment regimens. Here, we will review the current understanding of intratumour heterogeneity at the genomic, epigenomic and microenvironmental levels. We will also discuss the clinical implications and the challenges posed by intratumour heterogeneity and evaluate noninvasive methods such as circulating biomarkers to characterize the cellular diversity of tumours. Comprehensive assessment of the molecular features of patients based on tumour specimen characterization (including intratumour spatial and temporal variations), ancillary noninvasive methods (such as circulating biomarkers and molecular imaging approaches) and the correct design of clinical trials are required to guide administration of targeted therapy and to control therapeutic resistance. Finding the means to accurately determine and effectively control tumour heterogeneity and translate these achievements into patient benefit are major goals in modern oncology.

Issues in clinical research for metastatic breast cancer

PURPOSE OF REVIEW

Technical advances and progresses in tumor biology hold promise for the advent of new anticancer agents. These changes are impacting the conduct and design of clinical trials. This review describes the changing landscape of clinical research in metastatic breast cancer (MBC).

RECENT FINDINGS

Clinical trials in breast cancer that started between 2007 and 2011 were analyzed. In the metastatic setting, 72% (n = 479) of these studies evaluated targeted therapies and 21% (n = 139) conventional treatments. During this period, the number of phase II trials decreased over time, whereas biology-driven studies, although small in terms of absolute number, now represent 15% of the total. Nevertheless, genomic segments are too rare to allow conventional drug development and require changes in the way clinical trials are being done. Several options are being explored to address this challenge: develop large consortium, perform molecular screening in larger populations, develop clinical trials testing algorithm for treatment decision, and no longer drugs.

SUMMARY

The landscape of clinical research in MBC is changing with the development of molecular medicine. Research institutions and cooperative groups will need to adapt to this changing landscape in clinical research.

Could magnetic resonance provide in vivo histology?

The diagnosis of a suspected tumor lesion faces two basic problems: detection and identification of the specific type of tumor. Radiological techniques are commonly used for the detection and localization of solid tumors. Prerequisite is a high intrinsic or enhanced contrast between normal and neoplastic tissue. Identification of the tumor type is still based on histological analysis. The result depends critically on the sampling sites, which given the inherent heterogeneity of tumors, constitutes a major limitation. Non-invasive in vivo imaging might overcome this limitation providing comprehensive three-dimensional morphological, physiological, and metabolic information as well as the possibility for longitudinal studies. In this context, magnetic resonance based techniques are quite attractive since offer at the same time high spatial resolution, unique soft tissue contrast, good temporal resolution to study dynamic processes and high chemical specificity. The goal of this paper is to review the role of magnetic resonance techniques in characterizing tumor tissue in vivo both at morphological and physiological levels. The first part of this review covers methods, which provide information on specific aspects of tumor phenotypes, considered as indicators of malignancy. These comprise measurements of the inflammatory status, neo-vascular physiology, acidosis, tumor oxygenation, and metabolism together with tissue morphology. Even if the spatial resolution is not sufficient to characterize the tumor phenotype at a cellular level, this multiparametric information might potentially be used for classification of tumors. The second part discusses mathematical tools, which allow characterizing tissue based on the acquired three-dimensional data set. In particular, methods addressing tumor heterogeneity will be highlighted. Finally, we address the potential and limitation of using MRI as a tool to provide in vivo tissue characterization.

Establishment of a human 3D lung cancer model based on a biological tissue matrix combined with a Boolean in silico model

For the development of new treatment strategies against cancer, understanding signaling networks and their changes upon drug response is a promising approach to identify new drug targets and biomarker profiles. Pre‐requisites are tumor models with multiple read‐out options that accurately reflect the clinical situation. Tissue engineering technologies offer the integration of components of the tumor microenvironment which are known to impair drug response of cancer cells. We established three‐dimensional (3D) lung carcinoma models on a decellularized tissue matrix, providing a complex microenvironment for cell growth. For model generation, we used two cell lines with (HCC827) or without (A549) an activating mutation of the epidermal growth factor receptor (EGFR), exhibiting different sensitivities to the EGFR inhibitor gefitinib. EGFR activation in HCC827 was inhibited by gefitinib, resulting in a significant reduction of proliferation (Ki‐67 proliferation index) and in the induction of apoptosis (TUNEL staining, M30‐ELISA). No significant effect was observed in conventional cell culture. Results from the 3D model correlated with the results of an in silico model that integrates the EGFR signaling network according to clinical data. The application of TGFβ1 induced tumor cell invasion, accompanied by epithelial–mesenchymal transition (EMT) both in vitro and in silico. This was confirmed in the 3D model by acquisition of mesenchymal cell morphology and modified expression of fibronectin, E‐cadherin, β‐catenin and mucin‐1. Quantitative read‐outs for proliferation, apoptosis and invasion were established in the complex 3D tumor model. The combined in vitro and in silico model represents a powerful tool for systems analysis.

Combination of a human 3D lung tumor tissue model with a Boolean in silico Model.

Establishment of in silico signaling network topology for personalized medicine.

Significant decrease of tumor proliferation and induction of apoptosis upon in vitro treatment with tyrosine kinase inhibitors.

Decreased proliferation of tumor cells in the 3D model compared to 2D conditions.

Induction of invasion with EMT by TGFβ stimulation.

High-throughput, multiparameter analysis of single cells

Heterogeneity of cell populations in various biological systems has been widely recognized, and the highly heterogeneous nature of cancer cells has been emerging with clinical relevance. Single-cell analysis using a combination of high-throughput and multiparameter approaches is capable of reflecting cell-to-cell variability, and at the same time of unraveling the complexity and interdependence of cellular processes in the individual cells of a heterogeneous population. In this review, analytical methods and microfluidic tools commonly used for high-throughput, multiparameter single-cell analysis of DNA, RNA, and proteins are discussed. Applications and limitations of currently available technologies for cancer research and diagnostics are reviewed in the light of the ultimate goal to establish clinically applicable assays.

[Evolving strategies over time for treatment of breast cancer]

The natural history of breast diseases has changed overtime and successive therapeutic strategies have been adapted accordingly. Recently, biological findings on geno- and phenotypic characteristics of tumor cells offer new basis for the development of treatments that target homogenous and various subtypes of breast cancer. Unfortunately, traditional clinical research tools are not in phase with rapid changes in both biological knowledge of the disease and new targeted agents. New methodological approaches are urgently needed to validate such changes and improvements in prognosis.

Pilot studies for personalized cancer medicine: focusing on the patient for treatment selection

Advances in diagnostics and targeted therapies during the past decade have changed how oncology is viewed. "Stratified medicine" has emerged from the accumulated evidence garnered from matching targeted therapies with tumor molecular aberrations. Concomitantly, current knowledge derived from large-scale, massively parallel sequencing technologies and global research initiatives such as the international 1000 Genomes Project, the Cancer Genome Atlas, the International Cancer Genome Consortium, and publicly available catalogs such as the Catalogue of Somatic Mutations in Cancer and Genomics of Drug Sensitivity in Cancer have illuminated the utility of understanding the molecular basis of cancer through genome analysis. In addition, multiple collaborative efforts are widening the possibility of universally personalizing cancer care. Although several key challenges of personalized cancer medicine (PCM) need to be addressed, some pilot studies are transforming the way we analyze tumor tissue molecular aberrations, design clinical trials, and measure treatment efficacy. Taken together, these pilot studies are paving the way for clinical trials that are designed to empirically test the concept of PCM. In this paper, we describe lessons learned from the first pilot initiatives of PCM and how this knowledge is being used to design novel clinical trials.

CancerDR: cancer drug resistance database

Cancer therapies are limited by the development of drug resistance, and mutations in drug targets is one of the main reasons for developing acquired resistance. The adequate knowledge of these mutations in drug targets would help to design effective personalized therapies. Keeping this in mind, we have developed a database “CancerDR”, which provides information of 148 anti-cancer drugs, and their pharmacological profiling across 952 cancer cell lines. CancerDR provides comprehensive information about each drug target that includes; (i) sequence of natural variants, (ii) mutations, (iii) tertiary structure, and (iv) alignment profile of mutants/variants. A number of web-based tools have been integrated in CancerDR. This database will be very useful for identification of genetic alterations in genes encoding drug targets, and in turn the residues responsible for drug resistance. CancerDR allows user to identify promiscuous drug molecules that can kill wide range of cancer cells. CancerDR is freely accessible at http://crdd.osdd.net/raghava/cancerdr/

Individualized therapy for metastatic colorectal cancer

Systemic therapeutic efficacy is central to determining the outcome of patients with metastatic colorectal cancer (CRC). In these patients, there is a critical need for predictive biomarkers to optimize efficacy whilst minimizing toxicity. The integration of a new generation of molecularly targeted drugs into the treatment of CRC, coupled with the development of sophisticated technologies for individual tumours as well as patient molecular profiling, underlines the potential for personalized medicine. In this review, we focus on the latest progress made within the genomic and proteomic fields, concerning predictive biomarkers for individualized therapy in metastatic CRC.

Quo vadis radiotherapy? Technological advances and the rising problems in cancer management

Purpose. Despite the latest technological advances in radiotherapy, cancer control is still challenging for several tumour sites. The survival rates for the most deadly cancers, such as ovarian and pancreatic, have not changed over the last decades. The solution to the problem lies in the change of focus: from local treatment to systemic therapy. The aim of this paper is to present the current status as well as the gaps in radiotherapy and, at the same time, to look into potential solutions to improve cancer control and survival. Methods. The currently available advanced radiotherapy treatment techniques have been analysed and their cost-effectiveness discussed. The problem of systemic disease management was specifically targeted. Results. Clinical studies show limited benefit in cancer control from hadron therapy. However, targeted therapies together with molecular imaging could improve treatment outcome for several tumour sites while controlling the systemic disease. Conclusion. The advances in photon therapy continue to be competitive with the much more expensive hadron therapy. To justify the cost effectiveness of proton/heavy ion therapy, there is a need for phase III randomised clinical trials. Furthermore, the success of systemic disease management lies in the fusion between radiation oncology technology and microbiology.

Mechanistic understanding in clinical practice: complementing evidence-based medicine with personalized medicine

In the last century, medicine has undergone an unprecedented wave of radical changes. From the implementation of surgery up to the development of single gene-targeted therapies, clinical decision making has become increasingly complex to handle. Today, this complexity needs to be rethought in the light of two emerging paradigms: evidence-based medicine (EBM) and personalized medicine (P-Med). The new availability of diverse sources of scientific evidence raises significant issues concerning how clinicians will compare, evaluate and orient their decisions in front of a rapidly growing plethora of therapies, procedures, medical technologies and drugs. In this paper, we compare the background visions behind these two paradigms, evaluating their respective relevance for present and future clinical decision making. In particular, we argue that EBM and P-Med are driven by two diverse modes of reasoning about 'evidence making' in medicine. EBM is grounded on statistical notions and epidemiological data, generally gathered through systematic meta-reviews of randomized controlled trials; P-Med, instead, is grounded on mechanistic explanations of molecular interactions, metabolic pathways and biomarkers. While both paradigms are epistemically sound, we argue that they cannot, and should not, be hybridized into a unique model. Rather, they ought to represent two compatible, but alternative ways of informing the clinical practice. Hence, we conclude that clinicians may expect to see their responsibility increasing as they will deal with diverse, but equally compelling, ways of reasoning and deciding about which intervention will qualify as the 'best one' in each individual case.

Triple-negative breast cancer: are we making headway at least?

The so-called triple-negative breast cancer, as defined by tumors that lack estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 (HER2) overexpression, has generated growing interest in recent years despite representing less than 20% of all breast cancers. These tumors constitute an important clinical challenge, as they do not respond to endocrine treatment and other targeted therapies. As a group they harbor an aggressive clinical phenotype with early development of visceral metastases and a poor long-term prognosis. While chemotherapy remains effective in triple-negative disease, research continues to further identify potential new targets based on phenotypical and molecular characteristics of these tumors. In this respect, the presence of a higher expression of different biomarkers including epidermal growth factor receptor, vascular endothelial growth factor receptor, fibroblast growth factor receptor and Akt activation has led to a proliferation of clinical trials assessing the role of inhibitors to these pathways in triple-negative tumors. Moreover, the described overlap between triple-negative and basal-like tumors, and the similarities with tumors arising in the BRCA1 mutation carriers has offered potential therapeutic avenues for patients with these cancers including poly (ADP-ribose) polymerase inhibitors and a focus on a higher sensitivity to alkylating chemotherapy agents. Results from these trials have shown some benefit in small subgroups of patients, even in single-agent therapy, which reflects the heterogeneity of triple-negative breast cancer and highlights the need for a further subclassification of these types of tumors for better prognosis identification and treatment individualization.

[Genomics and clinical research for breast cancer]

Genomics of breast cancer is paving the way towards more and more tailored treatments. The number of molecularly targeted therapies under development is increasing. In parallel, the high-throughput analyses revealed the molecular heterogeneity of disease, and identified several very different molecular subtypes, numerous and sometimes very scarce molecular alterations, and multigenic signatures predictive for clinical outcome, some of which are being tested in prospective clinical trials. This molecular segmentation of breast cancer and the multitude of new drugs to be tested (alone and in combination) lead to develop clinical trials based on the molecular profile of tumors to guide the patient towards the most suitable drug.

A new frontier in personalized cancer therapy: mapping molecular changes

Mutations in the genome of a normal cell can affect the function of its many genes and pathways. These alterations could eventually transform the cell from a normal to a malignant state by allowing an uncontrolled proliferation of the cell and formation of a cancer tumor. Each tumor in an individual patient can have hundreds of mutated genes and perturbed pathways. Cancers clinically presenting as the same type or subtype could potentially be very different at the molecular level and thus behave differently in response to therapy. The challenge is to distinguish the key mutations driving the cancer from the background of mutational noise and find ways to effectively target them. The promise is that such a molecular approach to classifying cancer will lead to better diagnostic, prognostic and personalized treatment strategies. This article provides an overview of advances in the molecular characterization of cancers and their applications in therapy.

p-Medicine: From data sharing and integration via VPH models to personalized medicine

The Worldwide innovative Networking in personalized cancer medicine (WIN) initiated by the Institute Gustave Roussy (France) and The University of Texas MD Anderson Cancer Center (USA) has dedicated its 3rd symposium (Paris, 6-8 July 2011) to discussion on gateways to increase the efficacy of cancer diagnostics and therapeutics (http://www.winconsortium.org/symposium.html).Speakers ranged from clinical oncologist to researchers, industrial partners, and tools developers; a famous patient was present: Janelle Hail, a 30-year breast cancer survivor, founder and CEO of the National Breast Cancer Foundation, Inc. (NBCF).The p-medicine consortium found this venue a perfect occasion to present a poster about its activities that are in accordance with the take home message of the symposium.In this communication, we summarize what we presented with particular attention to the interaction between the symposium's topic and content and our project.