Precision medicine for cancer with next-generation functional diagnostics

Integrative clinical genomics of metastatic cancer

Metastasis is the primary cause of cancer-related deaths. Although The Cancer Genome Atlas has sequenced primary tumour types obtained from surgical resections, much less comprehensive molecular analysis is available from clinically acquired metastatic cancers. Here we perform whole-exome and -transcriptome sequencing of 500 adult patients with metastatic solid tumours of diverse lineage and biopsy site. The most prevalent genes somatically altered in metastatic cancer included TP53, CDKN2A, PTEN, PIK3CA, and RB1. Putative pathogenic germline variants were present in 12.2% of cases of which 75% were related to defects in DNA repair. RNA sequencing complemented DNA sequencing to identify gene fusions, pathway activation, and immune profiling. Our results show that integrative sequence analysis provides a clinically relevant, multi-dimensional view of the complex molecular landscape and microenvironment of metastatic cancers.

Versatile ion S5XL sequencer for targeted next generation sequencing of solid tumors in a clinical laboratory

BACKGROUND

Next generation sequencing based tumor tissue genotyping involves complex workflow and a relatively longer turnaround time. Semiconductor based next generation platforms varied from low throughput Ion PGM to high throughput Ion Proton and Ion S5XL sequencer. In this study, we compared Ion PGM and Ion Proton, with a new Ion S5XL NGS system for workflow scalability, analytical sensitivity and specificity, turnaround time and sequencing performance in a clinical laboratory.

METHODS

Eighteen solid tumor samples positive for various mutations as detected previously by Ion PGM and Ion Proton were selected for study. Libraries were prepared using DNA (range10-40ng) from micro-dissected formalin-fixed, paraffin-embedded (FFPE) specimens using the Ion Ampliseq Library Kit 2.0 for comprehensive cancer (CCP), oncomine comprehensive cancer (OCP) and cancer hotspot panel v2 (CHPv2) panel as per manufacturer's instructions. The CHPv2 were sequenced using Ion PGM whereas CCP and OCP were sequenced using Ion Proton respectively. All the three libraries were further sequenced individually (S540) or multiplexed (S530) using Ion S5XL. For S5XL, Ion chef was used to automate template preparation, enrichment of ion spheres and chip loading. Data analysis was performed using Torrent Suite 4.6 software on board S5XL and Ion Reporter. A limit of detection and reproducibility studies was performed using serially diluted DLD1 cell line.

RESULTS

A total of 241 variant calls (235 single nucleotide variants and 6 indels) expected in the studied cohort were successfully detected by S5XL with 100% and 97% concordance with Ion PGM and Proton, respectively. Sequencing run time was reduced from 4.5 to 2.5 hours with output range of 3-5 GB (S530) and 8-9.3Gb (S540). Data analysis time for the Ion S5XL is faster 1 h (S520), 2.5 h (S530) and 5 h (S540) chip, respectively as compared to the Ion PGM (3.5-5 h) and Ion Proton (8h). A limit detection of 5% allelic frequency was established along with high inter-run reproducibility.

CONCLUSION

Ion S5XL system simplified workflow in a clinical laboratory, was feasible for running smaller and larger panels on the same instrument, had a shorter turnaround time, and showed good concordance for variant calls with similar sensitivity and reproducibility as the Ion PGM and Proton.

VGLL4 Selectively Represses YAP-Dependent Gene Induction and Tumorigenic Phenotypes in Breast Cancer

Members of the mammalian Vestigial-like (VGLL) family of transcriptional cofactors activate genes in response to a wide variety of environmental cues. Recently, VGLL proteins have been proposed to regulate key signaling networks involved in cancer development and progression. However, the biological and clinical significance of VGLL dysregulation in human breast cancer pathogenesis remains unknown. Here, we report that diminished VGLL4 expression, but not VGLL1-3, correlated with both shorter relapse-free survival and shorter disease-specific survival of cancer patients with different molecular subtypes of breast cancer. Additionally, we further demonstrate that overexpression of VGLL4 reduces breast cancer cell proliferation, migration, intravasation/extravasation potential, favors cell death, and suppresses tumor growth in vivo. Mechanistically, VGLL4 negatively regulates the TEAD1-YAP1 transcriptional complex and exerts its growth inhibitory control through its evolutionary conserved TDU2 domain at its C-terminus. The results suggest that VGLL4 is a candidate tumor suppressor gene which acts by selectively antagonizing YAP-dependent tumor growth. VGLL4 may be a promising therapeutic target in breast cancer.

Collagen triple helix repeat containing-1 negatively regulated by microRNA-30c promotes cell proliferation and metastasis and indicates poor prognosis in breast cancer

Background

Collagen triple helix repeat containing-1 (CTHRC1), which was firstly identified overexpressed in the adventitia and neointima of injured rat arteries, could inhibit collagen expression and increase cell migration. It was then found to be ubiquitously expressed in numerous cell types such as fibroblasts and smooth muscle cells, and aberrantly up-regulated in several malignant tumors. However, the functional role of CTHRC1 and its related mechanism in breast cancer still remains unclear.

Methods

CTHRC1 expressions in breast cancer tissues and cells were assessed by qRT-PCR, western blot and immunohistochemistry. The relative expression level of miR-134, miR-155, miR-30c and miR-630 in breast cancer cells respectively was detected by qRT-PCR. Wild type (Wt) and Mutant type (Mut) CTHRC1 3’UTR sequences were cloned into a psi-CHECK2 reporter vector, and the relative luciferase activity was detected by dual-luciferase reporter assay in indicated cells. The effect of ectopic expression of miR-30c or gain and loss of CTHRC1 on cell viability, cell proliferation, cell cycle progression and apoptosis, cell invasion and migration was respectively detected by CCK-8 assay, colony formation assay, flow cytometry analysis, transwell invasion/migration assay. Protein levels of β-catenin, active β-catenin, normal and phosphorylated form of GSK-3β were detected by western blot in indicated cells. Immunofluorescence staining of β-catenin was performed to observe nuclear localization.

Results

We found CTHRC1 was frequently up-regulated in human breast cancer cells and tissues. Then our cohort study and further meta-analysis validated high expression of CTHRC1 was associated with aggressive clinicopathological features and poor clinical outcome of breast cancer patients. In addition, CTHRC1 promoted cell proliferation, invasion and migration and suppressed cell apoptosis in breast cancer, which might be by activating GSK-3β/β-catenin signaling and inhibiting Bax/Caspase-9/Caspase-3 signaling respectively; and these biological functions of CTHRC1 could be directly negatively regulated by miR-30c.

Conclusion

Taken together, we identified the role of miR-30c/CTHRC1 axis in breast cancer progression and demonstrated CTHRC1 may serve as a prognostic biomarker and therapeutic target for breast cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/s13046-017-0564-7) contains supplementary material, which is available to authorized users.

Patient-derived induced pluripotent stem cells in cancer research and precision oncology

Together with recent advances in the processing and culture of human tissue, bioengineering, xenotransplantation and genome editing, Induced pluripotent stem cells (iPSCs) present a range of new opportunities for the study of human cancer. Here we discuss the main advantages and limitations of iPSC modeling, and how the method intersects with other patient-derived models of cancer, such as organoids, organs-on-chips and patient-derived xenografts (PDXs). We highlight the opportunities that iPSC models can provide beyond those offered by existing systems and animal models and present current challenges and crucial areas for future improvements toward wider adoption of this technology.

Chemoresistance and chemosensitization in cholangiocarcinoma

One of the main difficulties in the management of patients with advanced cholangiocarcinoma (CCA) is their poor response to available chemotherapy. This is the result of powerful mechanisms of chemoresistance (MOC) of quite diverse nature that usually act synergistically. The problem is often worsened by altered MOC gene expression in response to pharmacological treatment. Since CCA includes a heterogeneous group of cancers their genetic signature coding for MOC genes is also diverse; however, several shared traits have been defined. Some of these characteristics are shared with other types of liver cancer, namely hepatocellular carcinoma and hepatoblastoma. An important goal in modern oncologic pharmacology is to develop novel strategies to overcome CCA chemoresistance either by increasing drug specificity, such as in targeted therapies aimed to inhibit receptors with tyrosine kinase activity, or to increase the amounts of active agents inside CCA cells by enhancing drug uptake or reducing efflux through export pumps. This article is part of a Special Issue entitled: Cholangiocytes in Health and Diseaseedited by Jesus Banales, Marco Marzioni, Nicholas LaRusso and Peter Jansen.

Precision Medicine in Myeloma: Challenges in Defining an Actionable Approach

Recently, large sequencing studies have provided insights into the mutational landscape of multiple myeloma (MM), identifying actionable mutations and giving a precious opportunity for exploring new targeted therapies. The main goal of precision medicine, matching patients with the right drug, seems to be closer than ever. However, no targeted therapies in MM are approved yet. Several clinical trials testing targeted drugs and enrolling patients with MM are currently ongoing and will provide predictive biomarkers that might support clinical decision making. In this review, we evaluate the evidence supporting the implementation of precision medicine in MM and we discuss the challenges that should be dealt with in this imminent and promising new era.

Signaling pathway profiling using reverse-phase protein array and its clinical applications

INTRODUCTION

Increased accessibility to next-generation sequencing within the last decade has led to a paradigm shift in cancer treatment from one-size-fits-all medicine to precision medicine providing therapeutic strategies tailored to the requirements of individual patients. However, the effect of even the most successful agent yet tested is only transient, and durable efficacy has yet to be achieved. Genome- and transcriptome-based approaches cannot fully predict the diversity of protein expression patterns or post-translational modifications that directly contribute to cancer pathogenesis and physiology. This underscores the need for concordant proteomic analysis in the next stage of precision medicine. Areas covered: This review begins with an overview of the recent advances and trends in precision medicine that currently rely on genomics, and highlights the utility of antibody-based reverse-phase protein array (RPPA) technology as a proteomic tool in this context. Expert commentary: RPPA is well suited for pharmacodynamics analysis in view of its ability to precisely map signaling status using limited amounts of clinical samples. In addition, the cost-effectiveness and rapid turn-around time of the RPPA platform offer a substantial advantage over existing molecular profiling technologies in clinical settings.

Autophagy and Ferroptosis - What's the Connection?

PURPOSE OF REVIEW

Autophagy is a conserved intracellular degradation system and plays a dual role in cell death, depending on context and phase. Ferroptosis is a new form of regulated cell death that mainly depends on iron accumulation and lipid peroxidation. In this review, we summarize the processes of autophagy and ferroptosis and discuss their crosstalk mechanisms at the molecular level.

RECENT FINDINGS

The original study shows that ferroptosis is morphologically, biochemically, and genetically distinct from autophagy and other types of cell death. However, recent studies demonstrate that activation of ferroptosis is indeed dependent on the induction of autophagy. Additionally, many ferroptosis regulators such as SLC7A11, GPX4, NRF2, p53, HSPB1, CISD1, FANCD2, and ACSL4 have been identified as potential regulators of autophagy.

SUMMARY

This review not only highlights the importance of autophagy as an emerging mechanism of ferroptosis, but also raises new insights regarding regulated cell death.

The novel long intergenic noncoding RNA UCC promotes colorectal cancer progression by sponging miR-143

The human genome contains thousands of long intergenic noncoding RNAs (lincRNAs). However, the functional roles of these transcripts and the mechanisms responsible for their deregulation in colorectal cancer (CRC) remain elusive. A novel lincRNA termed upregulated in CRC (UCC) was found to be highly expressed in human CRC tissues and cell lines. UCC levels correlated with lymph node metastasis, Dukes' stage, and patient outcomes. In SW480 and SW620 cells, knockdown of UCC inhibited proliferation, invasion, and cell cycle progression and induced apoptosis in vitro. Xenograft tumors grown from UCC-silenced SW620 cells had smaller mean volumes and formed more slowly than xenograft tumors grown from control cells. Inversely, overexpression of UCC in HCT116 promoted cell growth and invasion in vitro. Bioinformatics analysis, dual-luciferase reporter assays, and RNA immunoprecipitation assays showed that miR-143 can interact with UCC, and we found that UCC expression inversely correlates with miR-143 expression in CRC specimens. Moreover, mechanistic investigations showed that UCC may act as an endogenous sponge by competing for miR-143, thereby regulating the targets of this miRNA. Our results suggest that UCC and miR-143 may be promising molecular targets for CRC therapy.

Feasibility of Ultra-High-Throughput Functional Screening of Melanoma Biopsies for Discovery of Novel Cancer Drug Combinations

Purpose: Successful development of targeted therapy combinations for cancer patients depends on first discovering such combinations in predictive preclinical models. Stable cell lines and mouse xenograft models can have genetic and phenotypic drift and may take too long to generate to be useful as a personalized medicine tool.Experimental Design: To overcome these limitations, we have used a platform of ultra-high-throughput functional screening of primary biopsies preserving both cancer and stroma cell populations from melanoma patients to nominate such novel combinations from a library of thousands of drug combinations in a patient-specific manner within days of biopsy. In parallel, patient-derived xenograft (PDX) mouse models were created and novel combinations tested for their ability to shrink matched PDXs.Results: The screening method identifies specific drug combinations in tumor cells with patterns that are distinct from those obtained from stable cell lines. Screening results were highly specific to individual patients. For patients with matched PDX models, we confirmed that individualized novel targeted therapy combinations could inhibit tumor growth. In particular, a combination of multi-kinase and PI3K/Akt inhibitors was effective in some BRAF-wild-type melanomas, and the addition of cediranib to the BRAF inhibitor PLX4720 was effective in a PDX model with BRAF mutation.Conclusions: This proof-of-concept study demonstrates the feasibility of using primary biopsies directly for combinatorial drug discovery, complementing stable cell lines and xenografts, but with much greater speed and efficiency. This process could potentially be used in a clinical setting to rapidly identify therapeutic strategies for individual patients. Clin Cancer Res; 23(16); 4680-92. ©2017 AACR.

A clinically feasible multiplex proteomic immunoassay as a novel functional diagnostic for pancreatic ductal adenocarcinoma

To date, targeted therapy for pancreatic ductal adenocarcinoma (PDAC) remains largely unsuccessful in the clinic. Current genomics-based technologies are unable to reflect the quantitative, dynamic signaling changes in the tumor, and require larger tumor samples that are difficult to obtain in PDAC patients. Therefore, a highly sensitive functional tool that can reliably and comprehensively inform intra-tumoral signaling events is direly needed to guide treatment decision. We tested the utility of a highly sensitive proteomics-based functional diagnostic platform, Collaborative Enzyme Enhanced Reactive-immunoassay (CEERTM), on fine-needle aspiration (FNA) samples obtained from 102 patients with radiographically-evident pancreatic tumors. Two FNA passes were collected from each patient, hybridized to customized chips coated with an array of capture antibodies, and detected using two enzyme-conjugated antibodies which emit quantifiable signals. We demonstrate that this technique is highly sensitive in detecting total and phosphorylated forms of multiple signaling molecules in FNA specimens, with reasonable correlation of marker intensities between two different FNA passes. Notably, signals of several markers were significantly higher in PDAC compared to non-cancerous samples. In PDAC samples, we found high total c-Met signal to be associated with poor survival, and confirmed this finding using an independent PDAC tissue microarray.

Spatiotemporal diversification of intrapatient genomic clones and early drug development concepts realize the roadmap of precision cancer medicine

The unmet clinical needs of high relapse and cancer-related death rates are reflected by the poor understanding of the genome-wide mutational landscape and molecular mechanisms orchestrating therapeutic resistance. Emerging potential solutions to this challenge include the exploration of cancer genome dynamic evolution in time and space. Breakthrough next-generation sequencing (NGS) applications including multiregional NGS for intratumor heterogeneity identification, repeated cell-free DNA/circulating tumor DNA-NGS for detecting circulating genomic subclones and their comparison to reveal intrapatient heterogeneity (IPH) could identify the dynamic emergence of resistant subclones in the neoadjuvant, adjuvant and metastatic setting. Based on genome-phenotype map, and potential promising findings, rigorous evaluation of IPH spatiotemporal evolution and early drug development concepts in innovative clinical trials could dramatically speed up the translational process to achieve clinical precision oncology.

PARP inhibitors as precision medicine for cancer treatment

Personalized or precision medicine is an emerging treatment approach tailored to individuals or certain groups of patients based on their unique characteristics. These types of therapies guided by biomarkers tend to be more effective than traditional approaches, especially in cancer. The inhibitor against poly (ADP-ribose) polymerase (PARP), olaparib (Lynparza, AstraZeneca), which was approved by the US Food and Drug Administration (FDA) in 2014, demonstrated efficacy specifically for ovarian cancer patients harboring mutations in BRCA genes, which encode proteins in DNA double-strand break repairs. However, the response to PARP inhibitors has been less encouraging in other cancer types that also carry defects in the BRCA genes. Thus, furthering our understanding of the underlying mechanism of PARP inhibitors and resistance is critical to improve their efficacy. In this review, we summarize the results of preclinical studies and the clinical application of PARP inhibitors, and discuss the future direction of PARP inhibitors as a potential marker-guided personalized medicine for cancer treatment.

Co-clinical Analysis of a Genetically Engineered Mouse Model and Human Prostate Cancer Reveals Significance of NKX3.1 Expression for Response to 5α-reductase Inhibition

BACKGROUND

Although men on active surveillance for prostate cancer (PCa) may benefit from intervention with 5α-reductase inhibitors (5-ARIs), it has not been resolved whether 5-ARIs are effective for delaying disease progression and, if so, whether specific patients are more likely to benefit.

OBJECTIVE

To identify molecular features predictive of patient response to 5-ARIs.

DESIGN, SETTING, AND PARTICIPANTS

Nkx3.1 mutant mice, a model of early-stage PCa, were treated with the 5-ARI finasteride, and histopathological and molecular analyses were performed. Cross-species computational analyses were used to compare expression profiles for treated mice with those of patients who had received 5-ARIs before prostatectomy.

INTERVENTION

Finasteride administered to Nkx3.1 mutant mice. 5-ARI-treated patient specimens obtained retrospectively.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Endpoints in mice included histopathology, immunohistochemistry, and molecular profiling. GraphPad Prism software, R-studio, and Matlab were used for statistical and data analyses.

RESULTS AND LIMITATIONS

Finasteride treatment of Nkx3.1 mutant mice resulted in a significant reduction in prostatic intraepithelial neoplasia (PIN), as evident from histopathological and expression profiling analyses. Cross-species computational analysis comparing finasteride-treated mice with two independent 5-ARI-treated patient cohorts showed that reduced NKX3.1 expression is predictive of response to 5-ARI. A limitation of the study is that these retrospective human cohorts have relatively few patients with limited clinical outcome data. Future prospective clinical trials are needed to validate whether stratifying patients on the basis of NKX3.1 expression improves the benefit of 5-ARIs during active surveillance.

CONCLUSIONS

This co-clinical study implicates NKX3.1 status as a predictor of response to 5-ARIs, and suggests that molecular features, including NKX3.1 expression, may help to identify PCa patients most likely to benefit from 5-ARIs during active surveillance.

PATIENT SUMMARY

The aim of precision cancer prevention is to tailor interventions on the basis of individualized patient characteristics. We propose that patients with low NKX3.1 expression are optimal candidates for intervention with 5α-reductase inhibitors as an adjunct to active surveillance.

Tissue-specific tumorigenesis: context matters

How can we treat cancer more effectively? Traditionally, tumours from the same anatomical site are treated as one tumour entity. This concept has been challenged by recent breakthroughs in cancer genomics and translational research that have enabled molecular tumour profiling. The identification and validation of cancer drivers that are shared between different tumour types, spurred the new paradigm to target driver pathways across anatomical sites by off-label drug use, or within so-called basket or umbrella trials which are designed to test whether molecular alterations in one tumour entity can be extrapolated to all others. However, recent clinical and preclinical studies suggest that there are tissue- and cell type-specific differences in tumorigenesis and the organization of oncogenic signalling pathways. In this Opinion article, we focus on the molecular, cellular, systemic and environmental determinants of organ-specific tumorigenesis and the mechanisms of context-specific oncogenic signalling outputs. Investigation, recognition and in-depth biological understanding of these differences will be vital for the design of next-generation clinical trials and the implementation of molecularly guided cancer therapies in the future.

Multidrug Analyses in Patients Distinguish Efficacious Cancer Agents Based on Both Tumor Cell Killing and Immunomodulation

The vision of a precision medicine-guided approach to novel cancer drug development is challenged by high intratumor heterogeneity and interpatient diversity. This complexity is rarely modeled accurately during preclinical drug development, hampering predictions of clinical drug efficacy. To address this issue, we developed Comparative In Vivo Oncology (CIVO) arrayed microinjection technology to test tumor responsiveness to simultaneous microdoses of multiple drugs directly in a patient's tumor. Here, in a study of 18 canine patients with soft tissue sarcoma (STS), CIVO captured complex, patient-specific tumor responses encompassing both cancer cells and multiple immune infiltrates following localized exposure to different chemotherapy agents. CIVO also classified patient-specific tumor resistance to the most effective agent, doxorubicin, and further enabled assessment of a preclinical autophagy inhibitor, PS-1001, to reverse doxorubicin resistance. In a CIVO-identified subset of doxorubicin-resistant tumors, PS-1001 resulted in enhanced antitumor activity, increased infiltration of macrophages, and skewed this infiltrate toward M1 polarization. The ability to evaluate and cross-compare multiple drugs and drug combinations simultaneously in living tumors and across a diverse immunocompetent patient population may provide a foundation from which to make informed drug development decisions. This method also represents a viable functional approach to complement current precision oncology strategies. Cancer Res; 77(11); 2869-80. ©2017 AACR.

Toward Precision Healthcare: Context and Mathematical Challenges

Precision medicine refers to the idea of delivering the right treatment to the right patient at the right time, usually with a focus on a data-centered approach to this task. In this perspective piece, we use the term "precision healthcare" to describe the development of precision approaches that bridge from the individual to the population, taking advantage of individual-level data, but also taking the social context into account. These problems give rise to a broad spectrum of technical, scientific, policy, ethical and social challenges, and new mathematical techniques will be required to meet them. To ensure that the science underpinning "precision" is robust, interpretable and well-suited to meet the policy, ethical and social questions that such approaches raise, the mathematical methods for data analysis should be transparent, robust, and able to adapt to errors and uncertainties. In particular, precision methodologies should capture the complexity of data, yet produce tractable descriptions at the relevant resolution while preserving intelligibility and traceability, so that they can be used by practitioners to aid decision-making. Through several case studies in this domain of precision healthcare, we argue that this vision requires the development of new mathematical frameworks, both in modeling and in data analysis and interpretation.

Exome Sequencing Identifies Potentially Druggable Mutations in Nasopharyngeal Carcinoma

In this study, we first performed whole exome sequencing of DNA from 10 untreated and clinically annotated fresh frozen nasopharyngeal carcinoma (NPC) biopsies and matched bloods to identify somatically mutated genes that may be amenable to targeted therapeutic strategies. We identified a total of 323 mutations which were either non-synonymous (n = 238) or synonymous (n = 85). Furthermore, our analysis revealed genes in key cancer pathways (DNA repair, cell cycle regulation, apoptosis, immune response, lipid signaling) were mutated, of which those in the lipid-signaling pathway were the most enriched. We next extended our analysis on a prioritized sub-set of 37 mutated genes plus top 5 mutated cancer genes listed in COSMIC using a custom designed HaloPlex target enrichment panel with an additional 88 NPC samples. Our analysis identified 160 additional non-synonymous mutations in 37/42 genes in 66/88 samples. Of these, 99/160 mutations within potentially druggable pathways were further selected for validation. Sanger sequencing revealed that 77/99 variants were true positives, giving an accuracy of 78%. Taken together, our study indicated that ~72% (n = 71/98) of NPC samples harbored mutations in one of the four cancer pathways (EGFR-PI3K-Akt-mTOR, NOTCH, NF-κB, DNA repair) which may be potentially useful as predictive biomarkers of response to matched targeted therapies.

Fluorescence in situ hybridization in surgical pathology: principles and applications

Identification of recurrent tumour‐specific chromosomal translocations and novel fusion oncogenes has important diagnostic, therapeutic and prognostic implications. Over the past decade, fluorescence in situ hybridization (FISH) analysis of tumour samples has been one of the most rapidly growing areas in genomic medicine and surgical pathology practice. Unlike traditional cytogenetics, FISH affords a rapid analysis of formalin‐fixed, paraffin‐embedded cells within a routine pathology practice workflow. As more diagnostic and treatment decisions are based on results of FISH, demand for the technology will become more widespread. Common FISH‐detected alterations are chromosome deletions, gains, translocations, amplifications and polysomy. These chromosome alterations may have diagnostic and therapeutic implications for many tumour types. Integrating genomic testing into cancer treatment decisions poses many technical challenges, but rapid progress is being made to overcome these challenges in precision medicine. FISH assessment of chromosomal changes relevant to differential diagnosis and cancer treatment decisions has become an important tool for the surgical pathologist. The aim of this review is to provide a theoretical and practical survey of FISH detected translocations with a focus on strategies for clinical application in surgical pathology practice.

Conditional reprogramming and long-term expansion of normal and tumor cells from human biospecimens

Historically, it has been difficult to propagate cells in vitro that are derived directly from human tumors or healthy tissue. However, in vitro preclinical models are essential tools for both the study of basic cancer biology and the promotion of translational research, including drug discovery and drug target identification. This protocol describes conditional reprogramming (CR), which involves coculture of irradiated mouse fibroblast feeder cells with normal and tumor human epithelial cells in the presence of a Rho kinase inhibitor (Y-27632). CR cells can be used for various applications, including regenerative medicine, drug sensitivity testing, gene expression profiling and xenograft studies. The method requires a pathologist to differentiate healthy tissue from tumor tissue, and basic tissue culture skills. The protocol can be used with cells derived from both fresh and cryopreserved tissue samples. As approximately 1 million cells can be generated in 7 d, the technique is directly applicable to diagnostic and predictive medicine. Moreover, the epithelial cells can be propagated indefinitely in vitro, yet retain the capacity to become fully differentiated when placed into conditions that mimic their natural environment.

Tissue-based next generation sequencing: application in a universal healthcare system

In the context of solid tumours, the evolution of cancer therapies to more targeted and nuanced approaches has led to the impetus for personalised medicine. The targets for these therapies are largely based on the driving genetic mutations of the tumours. To track these multiple driving mutations the use of next generation sequencing (NGS) coupled with a morphomolecular approach to tumours, has the potential to deliver on the promises of personalised medicine. A review of NGS and its application in a universal healthcare (UHC) setting is undertaken as the technology has a wide appeal and utility in diagnostic, clinical trial and research paradigms. Furthermore, we suggest that these can be accommodated with a unified integromic approach. Challenges remain in bringing NGS to routine clinical use and these include validation, handling of the large amounts of information flow and production of a clinically useful report. These challenges are particularly acute in the setting of UHC where tests are not reimbursed and there are finite resources available. It is our opinion that the challenges faced in applying NGS in a UHC setting are surmountable and we outline our approach for its routine application in diagnostic, clinical trial and research paradigms.

Light in diagnosis, therapy and surgery

Light and optical techniques have made profound impacts on modern medicine, with numerous lasers and optical devices being currently used in clinical practice to assess health and treat disease. Recent advances in biomedical optics have enabled increasingly sophisticated technologies — in particular those that integrate photonics with nanotechnology, biomaterials and genetic engineering. In this Review, we revisit the fundamentals of light–matter interactions, describe the applications of light in imaging, diagnosis, therapy and surgery, overview their clinical use, and discuss the promise of emerging light-based technologies.

How to unleash mitochondrial apoptotic blockades to kill cancers?

Apoptosis, especially the intrinsic mitochondrial cell death pathway, is regulated by the BCL-2 family of proteins. Defects in apoptotic machinery are one of the main mechanisms that cells employ to evade cell death and become cancerous. Targeting the apoptotic defects, either by direct inhibition of BCL-2 family proteins or through modulation of regulatory pathways, can restore cell sensitivity to cell death. This review will focus on the aspects of BCL-2 family proteins, their interactions with kinase pathways, and how novel targeted agents can help overcome the apoptotic blockades. Furthermore, functional assays, such as BH3 profiling, may help in predicting responses to chemotherapies and aid in the selection of combination therapies by determining the mitochondrial threshold for initiating cell death.

Application of Multimodality Imaging Fusion Technology in Diagnosis and Treatment of Malignant Tumors under the Precision Medicine Plan

Objective:

The arrival of precision medicine plan brings new opportunities and challenges for patients undergoing precision diagnosis and treatment of malignant tumors. With the development of medical imaging, information on different modality imaging can be integrated and comprehensively analyzed by imaging fusion system. This review aimed to update the application of multimodality imaging fusion technology in the precise diagnosis and treatment of malignant tumors under the precision medicine plan. We introduced several multimodality imaging fusion technologies and their application to the diagnosis and treatment of malignant tumors in clinical practice.

Date Sources:

The data cited in this review were obtained mainly from the PubMed database from 1996 to 2016, using the keywords of “precision medicine”, “fusion imaging”, “multimodality”, and “tumor diagnosis and treatment”.

Study Selection:

Original articles, clinical practice, reviews, and other relevant literatures published in English were reviewed. Papers focusing on precision medicine, fusion imaging, multimodality, and tumor diagnosis and treatment were selected. Duplicated papers were excluded.

Results:

Multimodality imaging fusion technology plays an important role in tumor diagnosis and treatment under the precision medicine plan, such as accurate location, qualitative diagnosis, tumor staging, treatment plan design, and real-time intraoperative monitoring. Multimodality imaging fusion systems could provide more imaging information of tumors from different dimensions and angles, thereby offing strong technical support for the implementation of precision oncology.

Conclusion:

Under the precision medicine plan, personalized treatment of tumors is a distinct possibility. We believe that multimodality imaging fusion technology will find an increasingly wide application in clinical practice.

Towards the Design of a Patient-Specific Virtual Tumour

The design of a patient-specific virtual tumour is an important step towards Personalized Medicine. However this requires to capture the description of many key events of tumour development, including angiogenesis, matrix remodelling, hypoxia, and cell state heterogeneity that will all influence the tumour growth kinetics and degree of tumour invasiveness. To that end, an integrated hybrid and multiscale approach has been developed based on data acquired on a preclinical mouse model as a proof of concept. Fluorescence imaging is exploited to build case-specific virtual tumours. Numerical simulations show that the virtual tumour matches the characteristics and spatiotemporal evolution of its real counterpart. We achieved this by combining image analysis and physiological modelling to accurately described the evolution of different tumour cases over a month. The development of such models is essential since a dedicated virtual tumour would be the perfect tool to identify the optimum therapeutic strategies that would make Personalized Medicine truly reachable and achievable.

Oxidative stress downstream of mTORC1 but not AKT causes a proliferative defect in cancer cells resistant to PI3K inhibition

Compounds targeting phosphatidylinositol-3-kinase/mammalian target of rapamycin (PI3K/mTOR) signaling are being investigated in multiple clinical settings, but drug resistance may reduce their benefit. Compound rechallenge after drug holidays can overcome such resistance, yet little is known about the impact of drug holidays on cell biochemistry. We found that PI3K inhibitor (PI3Ki)-resistant cells cultured in the absence of PI3Ki developed a proliferative defect, increased oxygen consumption and accumulated reactive oxygen species (ROS), leading to lactate production through hypoxia-inducible factor-1α. This metabolic imbalance was reversed by mammalian target of rapamycin complex 1 (mTORC1) inhibitors. Interestingly, neither AKT nor c-MYC was involved in mediating the metabolic phenotype, despite the latter contributing to resistant cells' proliferation. These data suggest that an AKT-independent PI3K/mTORC1 axis operates in these cells. The excessive ROS hampered cell division, and the metabolic phenotype made resistant cells more sensitive to hydrogen peroxide and nutrient starvation. Thus, the proliferative defect of PI3Ki-resistant cells during drug holidays is caused by defective metabolic adaptation to chronic PI3K/mTOR pathway inhibition. This metabolic imbalance may open the therapeutic window for challenge with metabolic drugs during drug holidays.

CPX-351 exhibits potent and direct ex vivo cytotoxicity against AML blasts with enhanced efficacy for cells harboring the FLT3-ITD mutation

PURPOSE

Identify AML patients most likely to respond to CPX-351, a nano-scale liposome formulation containing cytarabine and daunorubicin co-encapsulated at a 5:1 molar ratio.

METHODS

We examined the ex vivo cytotoxic activity of CPX-351 against leukemic cells isolated from 53 AML patients and an additional 127 samples including acute lymphoblastic leukemia, myelodysplastic syndrome/myeloproliferative neoplasms, or chronic lymphocytic leukemia/lymphoma. We assessed activity with respect to common molecular lesions and used flow cytometry to assess CPX-351 cellular uptake.

RESULTS

AML specimen sensitivity to CPX-351 was similar across conventional risk groups. FLT3-ITD cases were five-fold more sensitive to CPX-351. CPX-351 was active across other indications with nearly all cases exhibiting IC₅₀ values markedly lower than reported 72-h plasma drug concentration in patients receiving CPX-351. The range and distribution of CPX-351 IC₅₀ values were comparable for AML, CLL, and ALL, whereas MDS/MPN cases were less sensitive. CPX-351 uptake analysis revealed a correlation between uptake of CPX-351 and cytotoxic potency.

CONCLUSIONS

Our findings are consistent with clinical data, in which CPX-351 activity is retained in high-risk AML patients. Ex vivo analysis of cytotoxic potency may provide a means to identify specific AML subsets, such as FLT3-ITD, that benefit most from CPX-351 and warrant additional clinical evaluation.

A microchip for integrated single-cell genotoxicity assay

With the development of large-scale biologic databases, precision medicine is becoming a frontier in biomedical research. As a main focus of precision medicine study, cancer has been widely accepted as a disease born out of inherited genetic variations or accumulating genomic damage. At the single-cell level, microfluidics or lab-on-a-chip technology for cancer study is an emerging tool for improving risk assessment, diagnostic categories and therapeutic strategies. This work presents a multi-layer microchip for single-cell gene expression profiling. Treated by three drug reagents (i.e. methyl methanesulfonate, docetaxel and colchicine) with varied concentrations and time lengths, individual human breast cancer cells (MCF-7) are then lysed on-chip, and the released mRNA templates are captured and reversely transcribed into cDNA on microbead surface. Three genes (GAPDH, CDKN1A, AURKA) are amplified and quantified simultaneously through triplex real-time polymerase chain reactions (qPCR). Readout per run is set to be eighteen, and can be further improved following same approach. The microchip is able to integrate all steps of single-cell gene expression profiling, and provide precision study of drug induced genotoxicity with reduced reagents consumption per reaction and instrumental cost.

Integrating next-generation sequencing into clinical oncology: strategies, promises and pitfalls

We live in an era of genomic medicine. The past five years brought about many significant achievements in the field of cancer genetics, driven by rapidly evolving technologies and plummeting costs of next-generation sequencing (NGS). The official completion of the Cancer Genome Project in 2014 led many to envision the clinical implementation of cancer genomic data as the next logical step in cancer therapy. Stemming from this vision, the term 'precision oncology' was coined to illustrate the novelty of this individualised approach. The basic assumption of precision oncology is that molecular markers detected by NGS will predict response to targeted therapies independently from tumour histology. However, along with a ubiquitous availability of NGS, the complexity and heterogeneity at the individual patient level had to be acknowledged. Not only does the latter present challenges to clinical decision-making based on sequencing data, it is also an obstacle to the rational design of clinical trials. Novel tissue-agnostic trial designs were quickly developed to overcome these challenges. Results from some of these trials have recently demonstrated the feasibility and efficacy of this approach. On the other hand, there is an increasing amount of whole-exome and whole-genome NGS data which allows us to assess ever smaller differences between individual patients with cancer. In this review, we highlight different tumour sequencing strategies currently used for precision oncology, describe their individual strengths and weaknesses, and emphasise their feasibility in different clinical settings. Further, we evaluate the possibility of NGS implementation in current and future clinical trials, and point to the significance of NGS for translational research.

Detergents: Friends not foes for high-performance membrane proteomics toward precision medicine

Precision medicine, particularly therapeutics, emphasizes the atomic-precise, dynamic, and systems visualization of human membrane proteins and their endogenous modifiers. For years, bottom-up proteomics has grappled with removing and avoiding detergents, yet faltered at the therapeutic-pivotal membrane proteins, which have been tackled by classical approaches and are known for decades refractory to single-phase aqueous or organic denaturants. Hydrophobicity and aggregation commonly challenge tissue and cell lysates, biofluids, and enriched samples. Frequently, expected membrane proteins and peptides are not identified by shotgun bottom-up proteomics, let alone robust quantitation. This review argues the cause of this proteomic crisis is not detergents per se, but the choice of detergents. Recently, inclusion of compatible detergents for membrane protein extraction and digestion has revealed stark improvements in both quantitative and structural proteomics. This review analyzes detergent properties behind recent proteomic advances, and proposes that rational use of detergents may reconcile outstanding membrane proteomics dilemmas, enabling ultradeep coverage and minimal artifacts for robust protein and endogenous PTM measurements. The simplicity of detergent tools confers bottom-up membrane proteomics the sophistication toward precision medicine.

Cancer Precision Medicine: From Cancer Screening to Drug Selection and Personalized Immunotherapy

With the accelerating progress in basic and clinical cancer research, a huge body of new discoveries and powerful technologies has allowed us to implement a 'Cancer Precision Medicine (CPM)' system for cancer patients. The CPM system covers a wide range of cancer management including cancer screening, monitoring of relapse/recurrence, selection/prediction of effective drugs/treatments, and personalized immunotherapy. In this system individual cancer patients expect to receive personalized care: an appropriate dose of the right drug at the right time. We here aim to summarize and discuss a possible workflow for precision medicine for cancer patients by reviewing recent booming technologies and treatments that have been used or will potentially be used in the CPM system.

Magnetically Actuated Protease Sensors for in Vivo Tumor Profiling

Targeted cancer therapies require a precise determination of the underlying biological processes driving tumorigenesis within the complex tumor microenvironment. Therefore, new diagnostic tools that capture the molecular activity at the disease site in vivo are needed to better understand tumor behavior and ultimately maximize therapeutic responses. Matrix metalloproteinases (MMPs) drive multiple aspects of tumorigenesis, and their activity can be monitored using engineered peptide substrates as protease-specific probes. To identify tumor specific activity profiles, local sampling of the tumor microenvironment is necessary, such as through remote control of probes, which are only activated at the tumor site. Alternating magnetic fields (AMFs) provide an attractive option to remotely apply local triggering signals because they penetrate deep into the body and are not likely to interfere with biological processes due to the weak magnetic properties of tissue. Here, we report the design and evaluation of a protease-activity nanosensor that can be remotely activated at the site of disease via an AMF at 515 kHz and 15 kA/m. Our nanosensor was composed of thermosensitive liposomes containing functionalized protease substrates that were unveiled at the target site by remotely triggered heat dissipation of coencapsulated magnetic nanoparticles (MNPs). This nanosensor was combined with a unique detection assay to quantify the amount of cleaved substrates in the urine. We applied this spatiotemporally controlled system to determine tumor protease activity in vivo and identified differences in substrate cleavage profiles between two mouse models of human colorectal cancer.

Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate

Assays that can determine the response of tumor cells to cancer therapeutics could greatly aid the selection of drug regimens for individual patients. However, the utility of current functional assays is limited, and predictive genetic biomarkers are available for only a small fraction of cancer therapies. We found that the single-cell mass accumulation rate (MAR), profiled over many hours with a suspended microchannel resonator, accurately defined the drug sensitivity or resistance of glioblastoma and B-cell acute lymphocytic leukemia cells. MAR revealed heterogeneity in drug sensitivity not only between different tumors, but also within individual tumors and tumor-derived cell lines. MAR measurement predicted drug response using samples as small as 25 μl of peripheral blood while maintaining cell viability and compatibility with downstream characterization. MAR measurement is a promising approach for directly assaying single-cell therapeutic responses and for identifying cellular subpopulations with phenotypic resistance in heterogeneous tumors.

Recent Advances of Light-Mediated Theranostics

Currently, precision theranostics have been extensively demanded for the effective treatment of various human diseases. Currently, efficient therapy at the targeted disease areas still remains challenging since most available drug molecules lack of selectivity to the pathological sites. Among different approaches, light-mediated therapeutic strategy has recently emerged as a promising and powerful tool to precisely control the activation of therapeutic reagents and imaging probes in vitro and in vivo, mostly attributed to its unique properties including minimally invasive capability and highly spatiotemporal resolution. Although it has achieved initial success, the conventional strategies for light-mediated theranostics are mostly based on the light with short wavelength (e.g., UV or visible light), which may usually suffer from several undesired drawbacks, such as limited tissue penetration depth, unavoidable light absorption/scattering and potential phototoxicity to healthy tissues, etc. Therefore, a near-infrared (NIR) light-mediated approach on the basis of long-wavelength light (700-1000 nm) irradiation, which displays deep-tissue penetration, minimized photo-damage and low autofluoresence in living systems, has been proposed as an inspiring alternative for precisely phototherapeutic applications in the last decades. Despite numerous NIR light-responsive molecules have been currently proposed for clinical applications, several inherent drawbacks, such as troublesome synthetic procedures, low water solubility and limited accumulation abilities in targeted areas, heavily restrict their applications in deep-tissue therapeutic and imaging studies. Thanks to the amazing properties of several nanomaterials with large extinction coefficient in the NIR region, the construction of NIR light responsive nanoplatforms with multifunctions have become promising approaches for deep-seated diseases diagnosis and therapy. In this review, we summarized various light-triggered theranostic strategies and introduced their great advances in biomedical applications in recent years. Moreover, some other promising light-assisted techniques, such as photoacoustic and Cerenkov radiation, were also systemically discussed. Finally, the potential challenges and future perspectives for light-mediated deep-tissue diagnosis and therapeutics were proposed.

Homoharringtonine (omacetaxine mepesuccinate) as an adjunct for FLT3-ITD acute myeloid leukemia

An in vitro drug-screening platform on patient samples was developed and validated to design personalized treatment for relapsed/refractory acute myeloid leukemia (AML). Unbiased clustering and correlation showed that homoharringtonine (HHT), also known as omacetaxine mepesuccinate, exhibited preferential antileukemia effect against AML carrying internal tandem duplication of fms-like tyrosine kinase 3 (FLT3-ITD). It worked synergistically with FLT3 inhibitors to suppress leukemia growth in vitro and in xenograft mouse models. Mechanistically, the effect was mediated by protein synthesis inhibition and reduction of short-lived proteins, including total and phosphorylated forms of FLT3 and its downstream signaling proteins. A phase 2 clinical trial of sorafenib and HHT combination treatment in FLT3-ITD AML patients resulted in complete remission (true or with insufficient hematological recovery) in 20 of 24 patients (83.3%), reduction of ITD allelic burden, and median leukemia-free and overall survivals of 12 and 33 weeks. The regimen has successfully bridged five patients to allogeneic hematopoietic stem cell transplantation and was well tolerated in patients unfit for conventional chemotherapy, including elderly and heavily pretreated patients. This study validated the principle and clinical relevance of in vitro drug testing and identified an improved treatment for FLT3-ITD AML. The results provided the foundation for phase 2/3 clinical trials to ascertain the clinical efficacy of FLT3 inhibitors and HHT in combination.

Dual specificity phosphatase 5 is a novel prognostic indicator for patients with advanced colorectal cancer

Dual specificity phosphatase 5 (DUSP5) is a negative regulator of Mitogen-activated protein kinase (MAPK) signaling pathway and has recently been identified as a tumor suppressor in several human malignancies. However, its clinical significance in colorectal cancer (CRC) remains unclear. In this study, we aimed to investigate the potential utility of DUSP5 as a novel biomarker for progression indication and chemotherapy benefit in CRC patients. Through quantitative real time-polymerase chain reaction and western blot, we determined that DUSP5 expression is dramatically lower in CRC tissues than that in matched normal tissues. The statistical analysis based on immunohistochemistry revealed that DUSP5 expression is significantly correlated with tumor differentiation, TNM stage, lymph node metastasis and distant metastasis. For the whole study cohort, patients with high DUSP5 expression had a better CRC-specific and disease-free survival than those with low DUSP5 expression and DUSP5 expression is an independent prognostic factor for patient survival. In subgroup analysis, DUSP5 has no prognostic significance in low-risk stage II patients, but could predict treatment response in high-risk stage II and stage III/IV patients who received standard FOLFOX chemotherapy scheme. Finally, the correlation analysis suggested that DUSP5 expression is associated with Epithelial-to-Mesenchymal Transition (EMT) phenotype in CRC tissues, suggesting that downregulated DUSP5 may contribute to poor prognosis partly by involving EMT. Taken together, our study proposes that DUSP5 is a promising biomarker for predicting CRC progression and advanced patients with high DUSP5 expression appear to benefit from standard FOLFOX chemotherapy scheme.

Using Pharmacogenomic Databases for Discovering Patient-Target Genes and Small Molecule Candidates to Cancer Therapy

With multiple omics strategies being applied to several cancer genomics projects, researchers have the opportunity to develop a rational planning of targeted cancer therapy. The investigation of such numerous and diverse pharmacogenomic datasets is a complex task. It requires biological knowledge and skills on a set of tools to accurately predict signaling network and clinical outcomes. Herein, we describe Web-based in silico approaches user friendly for exploring integrative studies on cancer biology and pharmacogenomics. We briefly explain how to submit a query to cancer genome databases to predict which genes are significantly altered across several types of cancers using CBioPortal. Moreover, we describe how to identify clinically available drugs and potential small molecules for gene targeting using CellMiner. We also show how to generate a gene signature and compare gene expression profiles to investigate the complex biology behind drug response using Connectivity Map. Furthermore, we discuss on-going challenges, limitations and new directions to integrate molecular, biological and epidemiological information from oncogenomics platforms to create hypothesis-driven projects. Finally, we discuss the use of Patient-Derived Xenografts models (PDXs) for drug profiling in vivo assay. These platforms and approaches are a rational way to predict patient-targeted therapy response and to develop clinically relevant small molecules drugs.

SparkText: Biomedical Text Mining on Big Data Framework

Background

Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment.

Results

In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes.

Conclusions

This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

Next generation sequencing in cancer: opportunities and challenges for precision cancer medicine

Over the past decade, testing the genes of patients and their specific cancer types has become standardized practice in medical oncology since somatic mutations, changes in gene expression and epigenetic modifications are all hallmarks of cancer. However, while cancer genetic assessment has been limited to single biomarkers to guide the use of therapies, improvements in nucleic acid sequencing technologies and implementation of different genome analysis tools have enabled clinicians to detect these genomic alterations and identify functional and disease-associated genomic variants. Next-generation sequencing (NGS) technologies have provided clues about therapeutic targets and genomic markers for novel clinical applications when standard therapy has failed. While Sanger sequencing, an accurate and sensitive approach, allows for the identification of potential novel variants, it is however limited by the single amplicon being interrogated. Similarly, quantitative and qualitative profiling of gene expression changes also represents a challenge for the cancer field. Both RT-PCR and microarrays are efficient approaches, but are limited to the genes present on the array or being assayed. This leaves vast swaths of the transcriptome, including non-coding RNAs and other features, unexplored. With the advent of the ability to collect and analyze genomic sequence data in a timely fashion and at an ever-decreasing cost, many of these limitations have been overcome and are being incorporated into cancer research and diagnostics giving patients and clinicians new hope for targeted and personalized treatment. Below we highlight the various applications of next-generation sequencing in precision cancer medicine.

A SNaPshot of potentially personalized care: Molecular diagnostics in gynecologic cancer

BACKGROUND

Genetic abnormalities underlie the development and progression of cancer, and represent potential opportunities for personalized cancer therapy in Gyn malignancies.

METHODS

We identified Gyn oncology patients at the MGH Cancer Center with tumors genotyped for a panel of mutations by SNaPshot, a CLIA approved assay, validated in lung cancer, that uses SNP genotyping in degraded DNA from FFPE tissue to identify 160 described mutations across 15 cancer genes (AKT1, APC, BRAF, CTNNB1, EGFR, ERBB2, IDH1, KIT, KRAS, MAP2KI, NOTCH1, NRAS, PIK3CA, PTEN, TP53).

RESULTS

Between 5/17/10 and 8/8/13, 249 pts consented to SNaPshot analysis. Median age 60 (29-84) yrs. Tumors were ovarian 123 (49%), uterine 74(30%), cervical 14(6%), fallopian 9(4%), primary peritoneal 13(5%), or rare 16(6%) with the incidence of testing high grade serous ovarian cancer (HGSOC) halving over time. SNaPshot was positive in 75 (30%), with 18 of these (24%) having 2 or 3 (n=5) mutations identified. TP53 mutations are most common in high-grade serous cancers yet a low detection rate (17%) was likely related to the assay. However, 4 of the 7 purely endometrioid ovarian tumors (57%) harbored a p53 mutation. Of the 38 endometrioid uterine tumors, 18 mutations (47%) in the PI3Kinase pathway were identified. Only 9 of 122 purely serous (7%) tumors across all tumor types harbored a 'drugable' mutation, compared with 20 of 45 (44%) of endometrioid tumors (p<0.0001). 17 pts subsequently enrolled on a clinical trial; all but 4 of whom had PIK3CA pathway mutations. Eight of 14 (47%) cervical tumors harbored a 'drugable' mutation.

CONCLUSION

Although SNaPshot can identify potentially important therapeutic targets, the incidence of 'drugable' targets in ovarian cancer is low. In this cohort, only 7% of subjects eventually were treated on a relevant clinical trial. Geneotyping should be used judiciously and reflect histologic subtype and available platform.

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MOLECULAR EVALUATION OF METASTATIC DISEASE

WHY PATHOLOGY REMAINS (AND WILL REMAIN) MANDATORY?: Numerous techniques are now available for the molecular evaluation of a tissular or cellular sample in the context of metastatic disease. They include in situ molecular techniques, such as immunohistochemistry for the study of proteins and peptides, in situ hybridization for the study of nucleic acids and in situ cytogenetics (FISH and its variants) for the demonstration of chromosome alterations. They also include all the techniques of molecular biology, which can now be applied to frozen as well as fixed tissue samples. The combination of all these techniques makes it possible an integrated and coherent approach, not limited to the description of DNA abnormalities, but able to correlate genomic alterations with functional, and even structural changes. A second major interest of the analysis of tissue samples is that they make it possible to analyzing not only tumor cells, but also their environment, formed by the stroma and its populations. The study of stroma and of stromal cells, in particular of immune cells, is now of paramount importance for providing new prognostic and predictive biomarkers, especially for anti-angiogenic strategies and for cancer immunotherapy. Tissue analysis is therefore the only way to perform a « total », « phenogenomic » characterization of the tumor as an organ : this is particularly important in the moment in which descriptive genomics is substituted by functional genomics and integrated biology.

Precision medicine for hepatocellular carcinoma: Perspectives and obstacles

Hepatocellular carcinoma (HCC) is one of the most common cancers in China. HCC patients have a poor prognosis due to the lack of effective drugs. The marketing of sorafenib in 2007 has terminated the history that there is no effective drug for HCC. Unfortunately, sorafenib prolongs the survival of advanced HCC patients by only 2-3 mo, and remains the unique systemic drug as no alternative effective agents have been demonstrated to be superior to sorafenib in treating HCC. Precision medicine, a novel concept and medicinal model, has recently emerged and been spreading globally, with the development of gene sequencing techniques, bioinformatics, big data and so on. Detecting, analyzing, verifying and utilizing the specific tumor biomarkers with the advanced technology have made it possible to apply "personalized and precision therapy" in the treatment of advanced HCC. In the present article we summarize the recent progress of HCC therapy under the guidance of precision medicine, and analyze the major obstacles for its clinical application, with an aim to provide some new clues for clinicians and researchers engaged in the clinical and basic research of HCC.

Precision or Personalized Medicine for Cancer Chemotherapy: Is there a Role for Herbal Medicine

Although over 100 chemotherapeutic agents are currently available for the treatment of cancer patients, the overall long term clinical benefit is disappointing due to the lack of effectiveness or severe side effects from these agents. In order to improve the therapeutic outcome, a new approach called precision medicine or personalized medicine has been proposed and initiated by the U.S. National Institutes of Health. However, the limited availability of effective medications and the high cost are still the major barriers for many cancer patients. Thus alternative approaches such as herbal medicines could be a feasible and less costly option. Unfortunately, scientific evidence for the efficacy of a majority of herbal medicines is still lacking and their development to meet FDA approval or other regulatory agencies is a big challenge. However, herbal medicines may be able to play an important role in precision medicine or personalized medicine. This review will focus on the existing and future technologies that could speed the development of herbal products for treatment of resistant cancer in individual patients. Specifically, it will concentrate on reviewing the phenotypic (activity based) rather than genotypic (mechanism based) approach to develop herbal medicine useful for personalized cancer chemotherapy.

Translational Research to Improve the Efficacy of Carbon Ion Radiotherapy: Experience of Gunma University

Carbon ion radiotherapy holds great promise for cancer therapy. Clinical data show that carbon ion radiotherapy is an effective treatment for tumors that are resistant to X-ray radiotherapy. Since 1994 in Japan, the National Institute of Radiological Sciences has been heading the development of carbon ion radiotherapy using the Heavy Ion Medical Accelerator in Chiba. The Gunma University Heavy Ion Medical Center (GHMC) was established in the year 2006 as a proof-of-principle institute for carbon ion radiotherapy with a view to facilitating the worldwide spread of compact accelerator systems. Along with the management of more than 1900 cancer patients to date, GHMC engages in translational research to improve the treatment efficacy of carbon ion radiotherapy. Research aimed at guiding patient selection is of utmost importance for making the most of carbon ion radiotherapy, which is an extremely limited medical resource. Intratumoral oxygen levels, radiation-induced cellular apoptosis, the capacity to repair DNA double-strand breaks, and the mutational status of tumor protein p53 and epidermal growth factor receptor genes are all associated with X-ray sensitivity. Assays for these factors are useful in the identification of X-ray-resistant tumors for which carbon ion radiotherapy would be beneficial. Research aimed at optimizing treatments based on carbon ion radiotherapy is also important. This includes assessment of dose fractionation, normal tissue toxicity, tumor cell motility, and bystander effects. Furthermore, the efficacy of carbon ion radiotherapy will likely be enhanced by research into combined treatment with other modalities such as chemotherapy. Several clinically available chemotherapeutic drugs (carboplatin, paclitaxel, and etoposide) and drugs at the developmental stage (Wee-1 and heat shock protein 90 inhibitors) show a sensitizing effect on tumor cells treated with carbon ions. Additionally, the efficacy of carbon ion radiotherapy can be improved by combining it with cancer immunotherapy. Clinical validation of preclinical findings is necessary to further improve the treatment efficacy of carbon ion radiotherapy.