Genetic heterogeneity and cancer drug resistance

Characteristics of Tumor Infiltrating Lymphocyte and Circulating Lymphocyte Repertoires in Pancreatic Cancer by the Sequencing of T Cell Receptors

Pancreatic cancer has a poor prognosis and few effective treatments. The failure of treatment is partially due to the high heterogeneity of cancer cells within the tumor. T cells target and kill cancer cells by the specific recognition of cancer-associated antigens. In this study, T cells from primary tumor and blood of sixteen patients with pancreatic cancer were characterized by deep sequencing. T cells from blood of another eight healthy volunteers were also studied as controls. By analyzing the complementary determining region 3 (CDR3) gene sequence, we found no significant differences in the T cell receptor (TCR) repertoires between patients and healthy controls. Types and length of CDR3 were similar among groups. However, two clusters of patients were identified according to the degree of CDR3 overlap within tumor sample group. In addition, clonotypes with low frequencies were found in significantly higher numbers in primary pancreatic tumors compared to blood samples from patients and healthy controls. This study is the first to characterize the TCR repertoires of pancreatic cancers in both primary tumors and matched blood samples. The results imply that specific types of pancreatic cancer share potentially important immunological characteristics.

Mutation tracking in circulating tumor DNA predicts relapse in early breast cancer

The identification of early-stage breast cancer patients at high risk of relapse would allow tailoring of adjuvant therapy approaches. We assessed whether analysis of circulating tumor DNA (ctDNA) in plasma can be used to monitor for minimal residual disease (MRD) in breast cancer. In a prospective cohort of 55 early breast cancer patients receiving neoadjuvant chemotherapy, detection of ctDNA in plasma after completion of apparently curative treatment-either at a single postsurgical time point or with serial follow-up plasma samples-predicted metastatic relapse with high accuracy [hazard ratio, 25.1 (confidence interval, 4.08 to 130.5; log-rank P < 0.0001) or 12.0 (confidence interval, 3.36 to 43.07; log-rank P < 0.0001), respectively]. Mutation tracking in serial samples increased sensitivity for the prediction of relapse, with a median lead time of 7.9 months over clinical relapse. We further demonstrated that targeted capture sequencing analysis of ctDNA could define the genetic events of MRD, and that MRD sequencing predicted the genetic events of the subsequent metastatic relapse more accurately than sequencing of the primary cancer. Mutation tracking can therefore identify early breast cancer patients at high risk of relapse. Subsequent adjuvant therapeutic interventions could be tailored to the genetic events present in the MRD, a therapeutic approach that could in part combat the challenge posed by intratumor genetic heterogeneity.

DREAMing: a simple and ultrasensitive method for assessing intratumor epigenetic heterogeneity directly from liquid biopsies

Many cancers comprise heterogeneous populations of cells at primary and metastatic sites throughout the body. The presence or emergence of distinct subclones with drug-resistant genetic and epigenetic phenotypes within these populations can greatly complicate therapeutic intervention. Liquid biopsies of peripheral blood from cancer patients have been suggested as an ideal means of sampling intratumor genetic and epigenetic heterogeneity for diagnostics, monitoring and therapeutic guidance. However, current molecular diagnostic and sequencing methods are not well suited to the routine assessment of epigenetic heterogeneity in difficult samples such as liquid biopsies that contain intrinsically low fractional concentrations of circulating tumor DNA (ctDNA) and rare epigenetic subclonal populations. Here we report an alternative approach, deemed DREAMing (Discrimination of Rare EpiAlleles by Melt), which uses semi-limiting dilution and precise melt curve analysis to distinguish and enumerate individual copies of epiallelic species at single-CpG-site resolution in fractions as low as 0.005%, providing facile and inexpensive ultrasensitive assessment of locus-specific epigenetic heterogeneity directly from liquid biopsies. The technique is demonstrated here for the evaluation of epigenetic heterogeneity at p14^ARF and BRCA1 gene-promoter loci in liquid biopsies obtained from patients in association with non-small cell lung cancer (NSCLC) and myelodysplastic/myeloproliferative neoplasms (MDS/MPN), respectively.

Nanoparticle modulation of the tumor microenvironment enhances therapeutic efficacy of cisplatin

The tumor microenvironment (TME) serves as a multidrug resistant center for tumors under the assault of chemotherapy and a physiological barrier against the penetration of therapeutic nanoparticles (NPs). Previous studies have indicated the ability for therapeutic NP to distribute into, and deplete tumor-associated fibroblasts (TAFs) for improved therapeutic outcomes. However, a drug resistant phenotype gradually arises after repeated doses of chemotherapeutic NP. Herein, the acquisition of drug resistant phenotypes in the TME after repeated cisplatin NP treatment was examined. Particularly, this study was aimed at investigating the effects of NP damaged TAFs on neighboring cells and alteration of stromal structure after cisplatin treatment. Findings suggested that while off-targeted NP damaged TAFs and inhibited tumor growth after an initial dose, chronic exposure to cisplatin NP led to elevated secretion of Wnt16 in a paracrine manner in TAFs. Wnt16 upregulation was then attributed to heightened tumor cell resistance and stroma reconstruction. Results attest to the efficacy of Wnt16 knockdown in damaged TAFs as a promising combinatory strategy to improve efficacy of cisplatin NP in a stroma-rich bladder cancer model.

Impact of Cell-surface Antigen Expression on Target Engagement and Function of an Epidermal Growth Factor Receptor × c-MET Bispecific Antibody

The efficacy of engaging multiple drug targets using bispecific antibodies (BsAbs) is affected by the relative cell-surface protein levels of the respective targets. In this work, the receptor density values were correlated to the in vitro activity of a BsAb (JNJ-61186372) targeting epidermal growth factor receptor (EGFR) and hepatocyte growth factor receptor (c-MET). Simultaneous binding of the BsAb to both receptors was confirmed in vitro. By using controlled Fab-arm exchange, a set of BsAbs targeting EGFR and c-MET was generated to establish an accurate receptor quantitation of a panel of lung and gastric cancer cell lines expressing heterogeneous levels of EGFR and c-MET. EGFR and c-MET receptor density levels were correlated to the respective gene expression levels as well as to the respective receptor phosphorylation inhibition values. We observed a bias in BsAb binding toward the more highly expressed of the two receptors, EGFR or c-MET, which resulted in the enhanced in vitro potency of JNJ-61186372 against the less highly expressed target. On the basis of these observations, we propose an avidity model of how JNJ-61186372 engages EGFR and c-MET with potentially broad implications for bispecific drug efficacy and design.

Evolutionary strategy for systemic therapy of metastatic breast cancer: balancing response with suppression of resistance

Conventional systemic therapy for disseminated breast cancer is based on the general assumption that the greatest patient benefit is achieved by killing the maximum number of tumor cells. While this strategy often achieves a significant reduction in tumor burden, most patients with metastatic breast cancer ultimately die from their disease as therapy fails because tumor cells evolve resistance. We propose that the conventional maximum dose/maximum cell kill cancer therapy, when viewed from an evolutionary vantage, is suboptimal and likely even harmful as it accelerates evolution and growth of the resistant phenotypes that ultimately cause patient death. As an alternative, we are investigating evolutionary therapeutic strategies that shift the treatment goal from killing the maximum number of cancer cells to maximizing patient survival. Here we introduce two novel approaches for systemic therapy for metastatic breast cancer, considering the evolutionary nature of tumor progression; adaptive therapy and double-bind therapy.

ESR1 mutations—a mechanism for acquired endocrine resistance in breast cancer

Approximately 70% of breast cancers are oestrogen receptor α (ER) positive, and are, therefore, treated with endocrine therapies. However, about 25% of patients with primary disease and almost all patients with metastases will present with or eventually develop endocrine resistance. Despite the magnitude of this clinical challenge, the mechanisms underlying the development of resistance remain largely unknown. In the past 2 years, several studies unveiled gain-of-function mutations in ESR1, the gene encoding the ER, in approximately 20% of patients with metastatic ER-positive disease who received endocrine therapies, such as tamoxifen and aromatase inhibitors. These mutations are clustered in a 'hotspot' within the ligand-binding domain (LBD) of the ER and lead to ligand-independent ER activity that promotes tumour growth, partial resistance to endocrine therapy, and potentially enhanced metastatic capacity; thus, ER LBD mutations might account for a mechanism of acquired endocrine resistance in a substantial fraction of patients with metastatic disease. In general, the absence of detectable ESR1 mutations in patients with treatment-naive disease, and the correlation between the frequency of patients with tumours harbouring these mutations and the number of endocrine treatments received suggest that, under selective treatment pressure, clonal expansion of rare mutant clones occurs, leading to resistance. Preclinical and clinical development of rationale-based novel therapeutic strategies that inhibit these ER mutants has the potential to substantially improve treatment outcomes. We discuss the contribution of ESR1 mutations to the development of acquired resistance to endocrine therapy, and evaluate how mutated ER can be detected and targeted to overcome resistance and improve patient outcomes.

The side population of ovarian cancer cells defines a heterogeneous compartment exhibiting stem cell characteristics

Cancer stem cells (CSC) are believed to be involved in tumor evasion of classical antitumor therapies and have thus become an attractive target for further improvement of anticancer strategies. However, the existence and identity of CSC are still a matter of controversy. In a systematic screen of 13 ovarian cancer cell lines we show that cells with stem cell properties are reliably detectable as a minor population, characterized by ABC transporter expression resulting in the side population (SP) phenotype. In different cell lines, either ABCG2 or ABCB1 was found to be responsible for this effect. Purified SP cells featured virtually all characteristics of bona fide CSC, including clonogenicity, asymmetric division and high tumorigenicity in vivo. Using in-depth phenotyping by multicolor flow cytometry, we found that among the investigated ovarian cancer cell lines the SP compartment exhibits tremendous heterogeneity and is composed of multiple phenotypically distinct subpopulations. Thus, our study confirms previous results showing that CSC are contained within the SP. However, the exact identity of the CSC is still disguised by the high complexity of the CSC-containing compartment. Further functional studies are needed to determine whether a single cellular subset can unambiguously be defined as CSC or whether multiple stem cell-like cells with different properties coexist. Moreover, the observed heterogeneity may reflect a high level of plasticity and likely influences tumor progression, escape from immune-surveillance and development of resistance to anticancer therapies and should therefore be considered in the development of new treatment strategies.

Challenges in the management of advanced, ER-positive, HER2-negative breast cancer

Hormone-receptor-positive breast cancer accounts for the majority-up to 80%-of all breast cancers. The evolution of breast cancer from early stage to the metastatic setting leads to increased heterogeneity, the occurrence of new mutations, and the development of treatment resistance representing a great challenge for management decisions. Unfortunately, little data exist to offer guidance in this context, and a reliance on traditional clinical parameters remains when deciding on optimal treatment. In advanced-stage oestrogen receptor-positive (ER+) disease, ongoing issues include the choice between endocrine therapy and chemotherapy, the appropriate sequence of treatment agents, and the incorporation of biological agents, such as everolimus, into the treatment armamentarium. In metastatic disease, repeated biopsies can help to reassess the receptor or genetic mutational status; however, the evidence to support this approach is limited. In this Review, we examine the current evidence that can guide treatment decisions in patients with advanced-stage ER+ breast cancer, discuss how to tackle these therapeutic challenges and provide suggestions for the optimal management of this patient population.

MALDI Imaging mass spectrometry: current frontiers and perspectives in pathology research and practice

MALDI Imaging mass spectrometry has entered the field of tissue-based research by providing unique advantages for analyzing tissue specimen in an unprecedented detail. A broad spectrum of analytes ranging from proteins, peptides, protein modification over small molecules, drugs and their metabolites as well as pharmaceutical components, endogenous cell metabolites, lipids, and other analytes are made accessible by this in situ technique in tissue. Some of them were even not accessible in tissues within the histological context before. Thereby, the great advantage of MALDI Imaging is the correlation of molecular information with traditional histology by keeping the spatial localization information of the analytes after mass spectrometric measurement. This method is label-free and allows multiplex analysis of hundreds to thousands of molecules in the very same tissue section simultaneously. Imaging mass spectrometry brings a new quality of molecular data and links the expert discipline of pathology and deep molecular mass spectrometric analysis to tissue-based research. This review will focus on state-of-the-art of MALDI Imaging mass spectrometry, its recent applications by analyzing tissue specimen and the contributions in understanding the biology of disease as well as its perspectives for pathology research and practice.

Elevated levels of the complement activation product C4d in bronchial fluids for the diagnosis of lung cancer

Molecular markers in bronchial fluids may contribute to the diagnosis of lung cancer. We previously observed a significant increase of C4d-containing complement degradation fragments in bronchoalveolar lavage (BAL) supernatants from lung cancer patients in a cohort of 50 cases and 22 controls (CUN cohort). The present study was designed to determine the diagnostic performance of these complement fragments (hereinafter jointly referred as C4d) in bronchial fluids. C4d levels were determined in BAL supernatants from two independent cohorts: the CU cohort (25 cases and 26 controls) and the HUVR cohort (60 cases and 98 controls). A series of spontaneous sputum samples from 68 patients with lung cancer and 10 controls was also used (LCCCIO cohort). Total protein content, complement C4, complement C5a, and CYFRA 21-1 were also measured in all cohorts. C4d levels were significantly increased in BAL samples from lung cancer patients. The area under the ROC curve was 0.82 (95%CI = 0.71-0.94) and 0.67 (95%CI = 0.58-0.76) for the CU and HUVR cohorts, respectively. In addition, unlike the other markers, C4d levels in BAL samples were highly consistent across the CUN, CU and HUVR cohorts. Interestingly, C4d test markedly increased the sensitivity of bronchoscopy in the two cohorts in which cytological data were available (CUN and HUVR cohorts). Finally, in the LCCCIO cohort, C4d levels were higher in sputum supernatants from patients with lung cancer (area under the ROC curve: 0.7; 95%CI = 0.56-0.83). In conclusion, C4d is consistently elevated in bronchial fluids from lung cancer patients and may be used to improve the diagnosis of the disease.

Aloperine executes antitumor effects against multiple myeloma through dual apoptotic mechanisms

BACKGROUND

Aloperine, a natural alkaloid constituent isolated from the herb Sophora alopecuroides displays anti-inflammatory properties in vitro and in vivo. Our group previously demonstrated that aloperine significantly induced apoptosis in colon cancer SW480 and HCT116 cells. However, its specific target(s) remain to be discovered in multiple myeloma (MM) and have not been investigated.

METHODS

Human myeloma cell lines (n = 8), primary myeloma cells (n = 12), drug-resistant myeloma cell lines (n = 2), and animal models were tested for their sensitivity to aloperine in terms of proliferation and apoptosis both in vitro and in vivo, respectively. We also examined the functional mechanisms underlying the apoptotic pathways triggered by aloperine.

RESULTS

Aloperine induced MM cell death in a dose- and time-dependent manner, even in the presence of the proliferative cytokines interleukin-6 and insulin-like growth factor I. Mechanistic studies revealed that aloperine not only activated caspase-8 and reduced the expression of FADD-like interleukin-1β-converting enzyme (FLICE)-like inhibitory protein long (FLIPL) and FLICE-inhibitory proteins (FLIPS) but also activated caspase-9 and decreased the expression of phosphorylated (p)-PTEN. Moreover, co-activation of the caspase-8/cellular FLICE-inhibitory protein (cFLIP)- and caspase-9/p-PTEN/p-AKT-dependent apoptotic pathways by aloperine caused irreversible inhibition of clonogenic survival. Aloperine induce more MM apoptosis with tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) or borterzomib. A U266 xenograft tumor model and 5T33 MM cells recapitulated the antitumor efficacy of aloperine, and the animals displayed excellent tolerance of the drug and few adverse effects.

CONCLUSIONS

Aloperine has multifaceted antitumor effects on MM cells. Our data support the clinical development of aloperine for MM therapy.

Targeting nodal in conjunction with dacarbazine induces synergistic anticancer effects in metastatic melanoma

Metastatic melanoma is a highly aggressive skin cancer with a poor prognosis. Despite a complete response in fewer than 5% of patients, the chemotherapeutic agent dacarbazine (DTIC) remains the reference drug after almost 40 years. More recently, FDA-approved drugs have shown promise but patient outcome remains modest, predominantly due to drug resistance. As such, combinatorial targeting has received increased attention, and will advance with the identification of new molecular targets. One attractive target for improving melanoma therapy is the growth factor Nodal, whose normal expression is largely restricted to embryonic development, but is reactivated in metastatic melanoma. In this study, we sought to determine how Nodal-positive human melanoma cells respond to DTIC treatment and to ascertain whether targeting Nodal in combination with DTIC would be more effective than monotherapy. A single treatment with DTIC inhibited cell growth but did not induce apoptosis. Rather than reducing Nodal expression, DTIC increased the size of the Nodal-positive subpopulation, an observation coincident with increased cellular invasion. Importantly, clinical tissue specimens from patients with melanomas refractory to DTIC therapy stained positive for Nodal expression, both in pre- and post-DTIC tumors, underscoring the value of targeting Nodal. In vitro, anti-Nodal antibodies alone had some adverse effects on proliferation and apoptosis, but combining DTIC treatment with anti-Nodal antibodies decreased cell growth and increased apoptosis synergistically, at concentrations incapable of producing meaningful effects as monotherapy.

IMPLICATIONS

Targeting Nodal in combination with DTIC therapy holds promise for the treatment of metastatic melanoma.

Single cell transcriptomics: methods and applications

Traditionally, gene expression measurements were performed on “bulk” samples containing populations of thousands of cells. Recent advances in genomic technology have made it possible to measure gene expression in hundreds of individual cells at a time. As a result, cellular properties that were previously masked in “bulk” measurements can now be observed directly. In this review, we will survey emerging technologies for single cell transcriptomics, and describe how they are used to study complex disease such as cancer, as well as other biological phenomena such as tissue regeneration, embryonic development, and immune response.

Introduction of the hybcell-based compact sequencing technology and comparison to state-of-the-art methodologies for KRAS mutation detection

The detection of KRAS mutations in codons 12 and 13 is critical for anti-EGFR therapy strategies; however, only those methodologies with high sensitivity, specificity, and accuracy as well as the best cost and turnaround balance are suitable for routine daily testing. Here we compared the performance of compact sequencing using the novel hybcell technology with 454 next-generation sequencing (454-NGS), Sanger sequencing, and pyrosequencing, using an evaluation panel of 35 specimens. A total of 32 mutations and 10 wild-type cases were reported using 454-NGS as the reference method. Specificity ranged from 100% for Sanger sequencing to 80% for pyrosequencing. Sanger sequencing and hybcell-based compact sequencing achieved a sensitivity of 96%, whereas pyrosequencing had a sensitivity of 88%. Accuracy was 97% for Sanger sequencing, 85% for pyrosequencing, and 94% for hybcell-based compact sequencing. Quantitative results were obtained for 454-NGS and hybcell-based compact sequencing data, resulting in a significant correlation (r = 0.914). Whereas pyrosequencing and Sanger sequencing were not able to detect multiple mutated cell clones within one tumor specimen, 454-NGS and the hybcell-based compact sequencing detected multiple mutations in two specimens. Our comparison shows that the hybcell-based compact sequencing is a valuable alternative to state-of-the-art methodologies used for detection of clinically relevant point mutations.

Breast cancer genomics from microarrays to massively parallel sequencing: paradigms and new insights

Rapid advancements in massively parallel sequencing methods have enabled the analysis of breast cancer genomes at an unprecedented resolution, which have revealed the remarkable heterogeneity of the disease. As a result, we now accept that despite originating in the breast, estrogen receptor (ER)-positive and ER-negative breast cancers are completely different diseases at the molecular level. It has become apparent that there are very few highly recurrently mutated genes such as TP53, PIK3CA, and GATA3, that no two breast cancers display an identical repertoire of somatic genetic alterations at base-pair resolution and that there might not be a single highly recurrently mutated gene that defines each of the "intrinsic" subtypes of breast cancer (ie, basal-like, HER2-enriched, luminal A, and luminal B). Breast cancer heterogeneity, however, extends beyond the diversity between tumors. There is burgeoning evidence to demonstrate that at least some primary breast cancers are composed of multiple, genetically diverse clones at diagnosis and that metastatic lesions may differ in their repertoire of somatic genetic alterations when compared with their respective primary tumors. Several biological phenomena may shape the reported intratumor genetic heterogeneity observed in breast cancers, including the different mutational processes and multiple types of genomic instability. Harnessing the emerging concepts of the diversity of breast cancer genomes and the phenomenon of intratumor genetic heterogeneity will be essential for the development of optimal methods for diagnosis, disease monitoring, and the matching of patients to the drugs that would benefit them the most.

Drug radiotherapy combinations: review of previous failures and reasons for future optimism

Combining chemotherapy with radiotherapy has resulted in significant clinical improvements in many different tumour types. However, the non-specific mechanisms by which these drugs exert their effects mean that this is often at the expense of increased side effects. Previous attempts at using targeted drugs to induce more tumour specific radiosensitisation have been generally disappointing. Although cetuximab, an EGFR monoclonal antibody, resulted in improved overall survival in HNSCC when combined with radiotherapy, it has failed to show benefit when added to chemo-radiotherapy. In addition, our inability to successfully use drug treatments to reverse tumour hypoxia is underlined by the fact that no such treatment is currently in widespread clinical use. The reasons for these failures include the lack of robust biomarkers, and the previous use of drugs with unacceptable side-effect profiles. Despite these disappointments, there is reason for optimism. Our improved understanding of key signal transduction pathways and of tumour specific DNA repair deficiencies has produced new opportunities to specifically radiosensitise tumours. Novel strategies to reduce tumour hypoxia include the use of drugs that cause vascular normalisation and drugs that reduce tumour oxygen consumption. These new strategies, combined with better compounds at our disposal, and an ability to learn from our previous mistakes, mean that there is great promise for future drug-radiotherapy combinations to result in significant clinical benefits.

A serum microRNA signature predicts tumor relapse and survival in triple-negative breast cancer patients

PURPOSE

Triple-negative breast cancers (TNBC) are associated with high risk of early tumor recurrence and poor outcome. Common prognostic biomarkers give very restricted predictive information of tumor recurrences in TNBC. Human serum contains stably expressed microRNAs (miRNAs), which have been discovered to predict prognosis in patients with cancer. The purpose of this study was to identify circulating biomarkers able to predict clinical outcome in TNBC.

EXPERIMENTAL DESIGN

We performed genome-wide serum miRNA expression and real-time PCR analyses to investigate the ability of miRNAs in predicting tumor relapse in serum samples from 60 primary TNBC. Patients were divided into training and testing cohorts.

RESULTS

By Cox regression analysis, we identified a four-miRNA signature (miR-18b, miR-103, miR-107, and miR-652) that predicted tumor relapse and overall survival. This miRNA signature was further validated in an independent cohort of 70 TNBC. A high-risk signature score was developed and significantly associated with tumor recurrence and reduced survival. Multivariate Cox regression models indicated that the risk score based on the four-miRNA signature was an independent prognostic classifier of patients with TNBC.

CONCLUSIONS

This signature may serve as a minimally invasive predictor of tumor relapse and overall survival for patients with TNBC. This prediction model may ultimately lead to better treatment options for patients with TNBC.

Microenvironmental regulation of therapeutic response in cancer

The tumor microenvironment (TME) not only plays a pivotal role during cancer progression and metastasis but also has profound effects on therapeutic efficacy. In the case of microenvironment-mediated resistance this can involve an intrinsic response, including the co-option of pre-existing structural elements and signaling networks, or an acquired response of the tumor stroma following the therapeutic insult. Alternatively, in other contexts, the TME has a multifaceted ability to enhance therapeutic efficacy. This review examines recent advances in our understanding of the contribution of the TME during cancer therapy and discusses key concepts that may be amenable to therapeutic intervention.

On-chip enzyme quantification of single Escherichia coli bacteria by immunoassay-based analysis

Individual bacteria of an isogenic population can differ significantly in their phenotypic characteristics. This cellular heterogeneity is thought to increase the adaptivity to environmental changes on a population level. Analytical methods for single-bacteria analyses are essential to reveal the different factors that may contribute to this cellular heterogeneity, among them the stochastic gene expression, cell cycle stages and cell aging. Although promising concepts for the analysis of single mammalian cells based on microsystems technology were recently developed, platforms suitable for proteomic analyses of microbial cells are by far more challenging. Here, we present a microfluidic device optimized for the analysis of single Escherichia coli bacteria. Individual bacteria are captured in a trap and isolated in a volume of only 155 pL. In combination with an immunoassay-based analysis of the cell lysate, the platform allowed the selective and sensitive analysis of intracellular enzymes. The limit of detection of the developed protocol was found to be 200 enzymes. Using this platform, we could investigate the levels of β-galactosidase in cells grown under different nutrient conditions. We successfully determined the enzyme copy numbers in cells cultured in defined medium (3517 ± 1578) and in complex medium (4710 ± 2643), and verified the down-regulation of expression in medium that contained only glucose as carbon source. The strong variations we found for individual bacteria confirm the phenotype heterogeneity. The capability to quantify proteins and other molecules in single bacterial lysates is encouraging to use the new analysis platform in future proteomics studies of isogenic bacteria populations.

Individualized chemotherapy for osteosarcoma and identification of gene mutations in osteosarcoma

The study aims to identify novel gene mutations in osteosarcoma and to guide individualized preoperative chemotherapy for osteosarcoma based on the analysis of expression and mutations of the drug-metabolism-related genes. Twenty-eight osteosarcoma patients received individualized preoperative chemotherapy regimens. Expression levels and mutations of chemotherapy-related genes in samples collected from the patients were determined using real-time PCR and DNA sequencing, respectively. Patient sensitivity to chemotherapeutic agents was evaluated by systematic analysis of the PCR and sequencing results. Novel mutations were identified via high-throughput sequencing of 339 genes in 10 osteosarcoma samples. Individualized preoperative chemotherapy outcomes were valid for nine patients (n = 9/28, 32.1%). Chemosensitivity assays showed that all 28 patients were sensitive to ifosfamide, whereas 46.4 and 39.2% were sensitive to docetaxel and platinum, respectively. More importantly, patients receiving highly chemosensitive chemotherapy agents had better prognosis and treatment outcomes than those receiving less chemosensitive agents (P < 0.05). In addition, 39 gene mutations were detected in at least five osteosarcoma tumor samples. Analysis of the expression and mutation of drug-metabolism-related genes will aid in the design of effective individualized preoperative chemotherapy regimens for osteosarcoma. Determining the chemosensitivity of individual tumors to chemotherapeutic agents will facilitate the development of better therapeutic approaches. Individualized treatment of osteosarcoma may improve chemotherapy efficacy and the survival rate of osteosarcoma patients. High-throughput genotyping allows mapping of osteosarcoma mutations, and novel gene mutations offered new candidates for diagnosis and therapeutic targeting.

De novo discovery of phenotypic intratumour heterogeneity using imaging mass spectrometry

An essential and so far unresolved factor influencing the evolution of cancer and the clinical management of patients is intratumour clonal and phenotypic heterogeneity. However, the de novo identification of tumour subpopulations is so far both a challenging and an unresolved task. Here we present the first systematic approach for the de novo discovery of clinically detrimental molecular tumour subpopulations. In this proof-of-principle study, spatially resolved, tumour-specific mass spectra were acquired, using matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry, from tissues of 63 gastric carcinoma and 32 breast carcinoma patients. The mass spectra, representing the proteomic heterogeneity within tumour areas, were grouped by a corroborated statistical clustering algorithm in order to obtain segmentation maps of molecularly distinct regions. These regions were presumed to represent different phenotypic tumour subpopulations. This was confirmed by linking the presence of these tumour subpopulations to the patients' clinical data. This revealed several of the detected tumour subpopulations to be associated with a different overall survival of the gastric cancer patients (p = 0.025) and the presence of locoregional metastases in patients with breast cancer (p = 0.036). The procedure presented is generic and opens novel options in cancer research, as it reveals microscopically indistinct tumour subpopulations that have an adverse impact on clinical outcome. This enables their further molecular characterization for deeper insights into the biological processes of cancer, which may finally lead to new targeted therapies.

Association between the cytogenetic profile of tumor cells and response to preoperative radiochemotherapy in locally advanced rectal cancer

Neoadjuvant radiochemotherapy to locally advanced rectal carcinoma patients has proven efficient in a high percentage of cases. Despite this, some patients show nonresponse or even disease progression. Recent studies suggest that different genetic alterations may be associated with sensitivity versus resistance of rectal cancer tumor cells to neoadjuvant therapy. We investigated the relationship between intratumoral pathways of clonal evolution as assessed by interphase fluorescence in situ hybridization (51 different probes) and response to neoadjuvant radiochemotherapy, evaluated by Dworak criteria in 45 rectal cancer tumors before (n = 45) and after (n = 31) treatment. Losses of chromosomes 1p (44%), 8p (53%), 17p (47%), and 18q (38%) and gains of 1q (49%) and 13q (75%) as well as amplification of 8q (38%) and 20q (47%) chromosomal regions were those specific alterations found at higher frequencies. Significant association (P < 0.05) was found between alteration of 1p, 1q, 11p, 12p, and 17p chromosomal regions and degree of response to neoadjuvant therapy. A clear association was observed between cytogenetic profile of the ancestral tumor cell clone and response to radiochemotherapy; cases presenting with del(17p) showed a poor response to neoadjuvant treatment (P = 0.03), whereas presence of del(1p) was more frequently observed in responder patients (P = 0.0002). Moreover, a significantly higher number of copies of chromosomes 8q (P = 0.004), 13q (P = 0.003), and 20q (P = 0.002) were found after therapy versus paired pretreatment rectal cancer samples. Our results point out the existence of an association between tumor cytogenetics and response to neoadjuvant therapy in locally advanced rectal cancer. Further studies in larger series of patients are necessary to confirm our results.

Tumor heterogeneity and personalized cancer medicine: are we being outnumbered?

Tumor heterogeneity is regarded as a major obstacle to successful personalized cancer medicine. The lack of reliable response assays reflective of in vivo tumor heterogeneity and associated resistance mechanisms hampers identification of reliable biomarkers. By contrast, oncogene addiction and paracrine signaling enable systemic responses despite tumor heterogeneity. This strengthens researchers in their efforts towards personalized cancer medicine. Given the fact that tumor heterogeneity is an integral part of cancer evolution, diagnostic tools need to be developed in order to better understand the dynamics within a tumor. Ultra-deep sequencing may reveal future resistant clones within a (liquid) tumor biopsy. On-treatment biopsies may provide insight into intrinsic or acquired drug resistance. Subsequently, upfront combinatorial treatment or sequential therapy strategies may forestall drug resistance and improve patient outcome. Finally, innovative response assays, such as organoid cultures or patient-derived tumor xenografts, provide an extra dimension to correlate molecular profiles with drug efficacy and control cancer growth.

The effect of gefitinib in patients with postoperative recurrent non-small cell lung cancer harboring mutations of the epidermal growth factor receptor

BACKGROUND

It is unclear whether there is a difference in the effect of gefitinib treatment between patients with postoperative recurrent non-small cell lung cancer (NSCLC) and those with stage IV NSCLC harboring mutations in the epidermal growth factor receptor (EGFR).

METHODS

We retrospectively reviewed the medical records of consecutive patients with postoperative recurrent NSCLC (postoperative group) or stage IV NSCLC (stage IV group) harboring EGFR mutations who were treated with gefitinib at the Shizuoka Cancer Center between September 2002 and March 2012 to compare the effect of gefitinib on survival from treatment initiation.

RESULTS

A total of 168 patients were treated with gefitinib (postoperative group, 49 patients; stage IV group, 119 patients). The response rate of gefitinib treatment in the postoperative group was similar to that in the stage IV group (58 vs. 61 %, p = 0.613). In contrast, median progression-free survival (PFS; 15.8 vs. 9.8 months, p < 0.001) and median overall survival (OS; 51.1 vs. 22.2 months, p < 0.001) were significantly longer in the postoperative group. In addition, postoperative recurrent disease, performance status (0-1), and a single metastatic organ were independent favorable prognostic factors in the multivariate analysis of survival.

CONCLUSIONS

PFS and OS were superior in patients with postoperative recurrent NSCLC harboring EGFR mutations treated by gefitinib than in those with stage IV disease. These results suggest that postoperative recurrent disease may be considered a stratification factor in clinical trials for NSCLC with EGFR mutations.

Statistical measures of transcriptional diversity capture genomic heterogeneity of cancer

BACKGROUND

Molecular heterogeneity of tumors suggests the presence of multiple different subclones that may limit response to targeted therapies and contribute to acquisition of drug resistance, but its quantification has remained challenging.

RESULTS

We performed simulations to evaluate statistical measures that best capture the molecular diversity within a group of tumors for either continuous (gene expression) or discrete (mutations, copy number alterations) molecular data. Dispersion based metrics in the principal component space best captured the underlying heterogeneity. To demonstrate utility of these measures, we characterized the diversity in transcriptional and genomic profiles of different breast tumor subtypes, and showed that basal-like or triple-negative breast cancers (TNBC) are significantly more heterogeneous molecularly than other subtypes. Our analysis also suggests that transcriptional diversity is a global characteristic of the tumors observed across the majority of molecular pathways. Among basal-like tumors, those that were resistant to multi-agent chemotherapy showed greater transcriptional diversity compared to chemotherapy-sensitive tumors, suggesting that potentially multiple mechanisms may be contributing to chemotherapy resistance.

CONCLUSIONS

We proposed and validated measures of transcriptional and genomic diversity that can quantify the molecular diversity of tumors. We applied the new measures to genomic data from breast tumors and demonstrated that basal-like breast cancers are significantly more diverse than other breast cancers. The observation that chemo-resistant tumors are significantly more diverse molecularly than chemosensitive tumors implies that multiple resistance mechanisms may be active, thus limiting the sensitivity and accuracy of predictive markers of chemotherapy response.

Gene Expression Profiling of Tumors From Heavily Pretreated Patients With Metastatic Cancer for the Selection of Therapy: A Pilot Study

BACKGROUND

Recently, it has been shown that it is possible to identify tumor profiles of sensitivity for potentially useful drugs, both conventional and experimental, based on whole oligonucleotide microarray gene expression studies in heavily pretreated patients with metastatic solid tumors.

METHODS

Fresh-frozen tumor biopsies for molecular profiling (MP) were obtained from patients with advanced and refractory cancer. Total tumor and control tissue RNA was hybridized to a whole human genome oligonucleotide microarray. Differentially expressed genes interacting with potential therapeutic targets were identified. Results were complemented with DNA sequencing of selected driver genes and with immunohistochemistry and fluorescent "in situ" hybridization. The results were used to guide experimental treatment.

RESULTS

MP assays led to a potentially active available drug in 91.2% of the patients. The median number of available active drugs per tumor was 5 (range, 1 to 9). Nine treated patients were not evaluable for response. Partial response was observed in 18 patients (33%), stable disease in 22 patients (40%) (clinical benefit rate of 73%), and progression in 15 (27%). Overall median progression-free survival and overall survival were 8 and 13 months, respectively.

CONCLUSION

MP-guided therapy is feasible and seems to improve the clinical outcome of extensively pretreated patients but prospective and confirmatory trials are needed.

Translation in solid cancer: are size-based response criteria an anachronism?

The purpose of translation is the development of effective medicinal products based on validated science. A parallel objective is to obtain marketing authorization for the translated product. Unfortunately, in solid cancer, these two objectives are not mutually consistent as evidenced by the contrast between major advances in science and the continuing dismal record of pharmaceutical productivity. If the problem is unrelated to science, then the process of translation may require a closer examination, namely, the criteria for regulatory approval. This realization is important because, in this context, the objective of translation is regulatory approval, and science does not passively translate into useful medicinal products. Today, in solid cancer, response criteria related to tumor size are less useful than during the earlier cytotoxic drugs era; advanced imaging and biomarkers now allow for tracking of the natural history of the disease in the laboratory and the clinic. Also, it is difficult to infer clinical benefit from tumor shrinkage since it is rarely sustained. Accordingly, size-based response criteria may represent an anachronism relative to translation in solid cancer and it may be appropriate to align preclinical and clinical effort and shift the focus to local invasion and metastasis. The shift from a cancer cell-centric model to a stroma centric model offers novel opportunities not only to interupt the natural history of the disease, but also to rethink the relevance of outdated criteria of clinical response. Current evidence favors the opinion that, in solid cancer, a different, broader, and contextual approach may lead to interventions that could delay local invasion and metastasis. All elements supporting this shift, especially advanced imaging, are in place.

The intra-tumor heterogeneity of cell signaling factors in breast cancer: p4E-BP1 and peIF4E are diffusely expressed and are real potential targets

Breast cancers and most malignant tumors are composed of heterogeneous tumor cells both at genetic and morphological levels; intra-tumor heterogeneity can be one underlying cause of therapeutic resistance. Classical studies have focused on analyses of the relationship between primary tumors and metastatic dissemination, and on subclone evolution. However, it should be noted that tumor heterogeneity at the level of protein expression (proteomics) has not been yet studied in depth. The differences in protein expression also can play an important role in elucidating the relationship between intra-tumor heterogeneity and resistance to systemic therapy. In fact, in human tumors there is not always a homogeneous expression of many of the crucial factors involved in cell signaling, such as pMAPK, pAKt, pMTOR, even with constitutive oncogenic alterations upstream, such as HER2, PI3 K. Conversely, two of these factors, peIF4E and p4E-BP1, which are downstream, and control protein translation, show a diffuse and strong protein expression. In summary, most of cell signaling factors show a heterogeneous expression, regardless of oncogenic alterations. Tissue heterogeneity could be driven by local factors, including hypoxia. The fact that the phosphorylation of crucial proteins such as 4E-BP1 and eIF4E is observed homogeneously throughout most tumors and are druggable opens the chance to get real potential targets in cancer therapy.

Identifying and quantifying heterogeneity in high content analysis: application of heterogeneity indices to drug discovery

One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation. To address this important issue we sought to define a method that could be readily implemented to identify, quantify and characterize heterogeneity in cellular and small organism assays to guide decisions during drug discovery and experimental cell/tissue profiling. Our study revealed that heterogeneity can be effectively identified and quantified with three indices that indicate diversity, non-normality and percent outliers. The indices were evaluated using the induction and inhibition of STAT3 activation in five cell lines where the systems response including sample preparation and instrument performance were well characterized and controlled. These heterogeneity indices provide a standardized method that can easily be integrated into small and large scale screening or profiling projects to guide interpretation of the biology, as well as the development of therapeutics and diagnostics. Understanding the heterogeneity in the response to perturbagens will become a critical factor in designing strategies for the development of therapeutics including targeted polypharmacology.

Going with the flow: from circulating tumor cells to DNA

Molecular analyses of circulating tumor DNA (ctDNA) in plasma from cancer patients have the potential to deliver minimally invasive diagnostic and disease-monitoring biomarkers. Drawing from experience gained through the translation of circulating tumor cell detection to clinical tests, we discuss ctDNA as a source of tumor material for biomarker development.

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.

Single-cell analysis of the transcriptome and its application in the characterization of stem cells and early embryos

Cellular heterogeneity within a cell population is a common phenomenon in multicellular organisms, tissues, cultured cells, and even FACS-sorted subpopulations. Important information may be masked if the cells are studied as a mass. Transcriptome profiling is a parameter that has been intensively studied, and relatively easier to address than protein composition. To understand the basis and importance of heterogeneity and stochastic aspects of the cell function and its mechanisms, it is essential to examine transcriptomes of a panel of single cells. High-throughput technologies, starting from microarrays and now RNA-seq, provide a full view of the expression of transcriptomes but are limited by the amount of RNA for analysis. Recently, several new approaches for amplification and sequencing the transcriptome of single cells or a limited low number of cells have been developed and applied. In this review, we summarize these major strategies, such as PCR-based methods, IVT-based methods, phi29-DNA polymerase-based methods, and several other methods, including their principles, characteristics, advantages, and limitations, with representative applications in cancer stem cells, early development, and embryonic stem cells. The prospects for development of future technology and application of transcriptome analysis in a single cell are also discussed.

The biological and clinical importance of epithelial-mesenchymal transition in circulating tumor cells

Movement of tumor cells from a primary tumor to a nonadjacent or distant site is a contiguous and complex process. Among the multiple natural cellular programs that promote initiation and progression of tumor metastasis, epithelial-mesenchymal transition (EMT) may play a key role in the ultimate generation of a metastatic foci. Acquisition of the EMT phenotype by tumor cells not only increases their migration and invasion potentials, thereby facilitating their ability to infiltrate blood vessels and to produce circulating tumor cells (CTCs), but also promotes survival of CTCs in the bloodstream and their ability to extravasate out of the circulatory system and invade proximal tissues. In organs distal to the primary tumor, the phenotypic switching mechanism of mesenchymal-epithelial transition (MET) enables CTCs to grow and colonize, enhancing the likelihood of establishing metastasis. In addition, CTCs that have undergone EMT attain increased resistance to chemotherapy and targeted therapy. CTCs with the EMT phenotype have become recognized as an active source of metastases, and targeting EMT/MET processes during the individual steps of tumor metastasis represents a promising new approach for alleviating cancer metastasis and recurrence. In this article, we focus on the biological and clinical importance of EMT and/or MET in CTCs during the individual steps of tumor metastasis, summarizing the recent findings of the regulatory roles played by EMT and/or MET in the generation, survival, and recolonization of CTCs and discussing the EMT-targeting strategies developed for tumor diagnosis as well as their potential for management of metastatic malignant diseases.

Tumor heterogeneity in the clinic: is it a real problem?

Tumor heterogeneity is one of the major problems limiting the efficacy of targeted therapies and compromising treatment outcomes. A better understanding of tumor biology has advanced our knowledge of the molecular landscape of cancer to an unprecedented level. However, most patients with advanced cancers treated with appropriately selected targeted therapies become resistant to the therapy, ultimately developing disease progression and succumbing to metastatic disease. Multiple factors account for therapeutic failures, which include cancer cells accumulating new molecular aberrations as a consequence of tumor progression and selection pressure of cancer therapies. Therefore, single agent targeted therapies, often administered in advanced stages, are unlikely to have a sufficiently lethal effect in most cancers. Finally, the molecular profile of cancer can change over time, which we are not able to monitor with existing strategies using tumor tissue biopsies as the gold standard for molecular diagnostics. Novel technologies focusing on testing low-risk, easily obtainable material, such as molecular cell-free DNA from plasma, can fill that gap and allow personalized therapy to be delivered in real time.

Predictive performance of microarray gene signatures: impact of tumor heterogeneity and multiple mechanisms of drug resistance

Gene signatures have failed to predict responses to breast cancer therapy in patients to date. In this study, we used bioinformatic methods to explore the hypothesis that the existence of multiple drug resistance mechanisms in different patients may limit the power of gene signatures to predict responses to therapy. In addition, we explored whether substratification of resistant cases could improve performance. Gene expression profiles from 1,550 breast cancers analyzed with the same microarray platform were retrieved from publicly available sources. Gene expression changes were introduced in cases defined as sensitive or resistant to a hypothetical therapy. In the resistant group, up to five different mechanisms of drug resistance causing distinct or overlapping gene expression changes were generated bioinformatically, and their impact on sensitivity, specificity, and predictive values of the signatures was investigated. We found that increasing the number of resistance mechanisms corresponding to different gene expression changes weakened the performance of the predictive signatures generated, even if the resistance-induced changes in gene expression were sufficiently strong and informative. Performance was also affected by cohort composition and the proportion of sensitive versus resistant cases or resistant cases that were mechanistically distinct. It was possible to improve response prediction by substratifying chemotherapy-resistant cases from actual datasets (non-bioinformatically perturbed datasets) and by using outliers to model multiple resistance mechanisms. Our work supports the hypothesis that the presence of multiple resistance mechanisms in a given therapy in patients limits the ability of gene signatures to make clinically useful predictions.

Breast cancer intra-tumor heterogeneity

In recent years it has become clear that cancer cells within a single tumor can display striking morphological, genetic and behavioral variability. Burgeoning genetic, epigenetic and phenomenological data support the existence of intra-tumor genetic heterogeneity in breast cancers; however, its basis is yet to be fully defined. Two of the most widely evoked concepts to explain the origin of heterogeneity within tumors are the cancer stem cell hypothesis and the clonal evolution model. Although the cancer stem cell model appeared to provide an explanation for the variability among the neoplastic cells within a given cancer, advances in massively parallel sequencing have provided several lines of evidence to suggest that intra-tumor genetic heterogeneity likely plays a fundamental role in the phenotypic heterogeneity observed in cancers. Many challenges remain, however, in the interpretation of the next generation sequencing results obtained so far. Here we review the models that explain tumor heterogeneity, the causes of intra-tumor genetic diversity and their impact on our understanding and management of breast cancer, methods to study intra-tumor heterogeneity and the assessment of intra-tumor genetic heterogeneity in the clinic.

Digital expression profiling identifies RUNX2, CDC5L, MDM2, RECQL4, and CDK4 as potential predictive biomarkers for neo-adjuvant chemotherapy response in paediatric osteosarcoma

Osteosarcoma is the most common malignancy of bone, and occurs most frequently in children and adolescents. Currently, the most reliable technique for determining a patients’ prognosis is measurement of histopathologic tumor necrosis following pre-operative neo-adjuvant chemotherapy. Unfavourable prognosis is indicated by less than 90% estimated necrosis of the tumor. Neither genetic testing nor molecular biomarkers for diagnosis and prognosis have been described for osteosarcomas. We used the novel nanoString mRNA digital expression analysis system to analyse gene expression in 32 patients with sporadic paediatric osteosarcoma. This system used specific molecular barcodes to quantify expression of a set of 17 genes associated with osteosarcoma tumorigenesis. Five genes, from this panel, which encoded the bone differentiation regulator RUNX2, the cell cycle regulator CDC5L, the TP53 transcriptional inactivator MDM2, the DNA helicase RECQL4, and the cyclin-dependent kinase gene CDK4, were differentially expressed in tumors that responded poorly to neo-adjuvant chemotherapy. Analysis of the signalling relationships of these genes, as well as other expression markers of osteosarcoma, indicated that gene networks linked to RB1, TP53, PI3K, PTEN/Akt, myc and RECQL4 are associated with osteosarcoma. The discovery of these networks provides a basis for further experimental studies of role of the five genes (RUNX2, CDC5L, MDM2, RECQL4, and CDK4) in differential response to chemotherapy.

Primary and acquired resistance to EGFR-targeted therapies in colorectal cancer: impact on future treatment strategies

Only approximately 10 % of genetically unselected patients with chemorefractory metastatic colorectal cancer experience tumor regression when treated with the anti-epidermal growth factor receptor (EGFR) antibodies cetuximab or panitumumab (“primary” or “de novo” resistance). Moreover, nearly all patients whose tumors initially respond inevitably become refractory (“secondary” or “acquired” resistance). An ever-increasing number of predictors of both primary and acquired resistance to anti-EGFR antibodies have been described, and it is now evident that most of the underlying mechanisms significantly overlap. By trying to extrapolate a unifying perspective out of many idiosyncratic details, here, we discuss the molecular underpinnings of therapeutic resistance, summarize research efforts aimed to improve patient selection, and present alternative therapeutic strategies that are now under development to increase response and combat relapse.

Androgen receptor and gene network: Micromechanics reassemble the signaling machinery of TMPRSS2-ERG positive prostate cancer cells

Prostate cancer is a gland tumor in the male reproductive system. It is a multifaceted and genomically complex disease. Transmembrane protease, serine 2 and v-ets erythroblastosis virus E26 homolog (TMPRSS2-ERG) gene fusions are the common molecular signature of prostate cancer. Although tremendous advances have been made in unraveling various facets of TMPRSS2-ERG-positive prostate cancer, many research findings must be sequentially collected and re-interpreted. It is important to understand the activation or repression of target genes and proteins in response to various stimuli and the assembly in signal transduction in TMPRSS2-ERG fusion-positive prostate cancer cells. Accordingly, we divide this multi-component review ofprostate cancer cells into several segments: 1) The role of TMPRSS2-ERG fusion in genomic instability and methylated regulation in prostate cancer and normal cells; 2) Signal transduction cascades in TMPRSS2-ERG fusion-positive prostate cancer; 3) Overexpressed genes in TMPRSS2-ERG fusion-positive prostate cancer cells; 4) miRNA mediated regulation of the androgen receptor (AR) and its associated protein network; 5) Quantitative control of ERG in prostate cancer cells; 6) TMPRSS2-ERG encoded protein targeting; In conclusion, we provide a detailed understanding of TMPRSS2-ERG fusion related information in prostate cancer development to provide a rationale for exploring TMPRSS2-ERG fusion-mediated molecular network machinery.

The genetic complexity of common cancers and the promise of personalized medicine: is there any hope?

Molecular characterization of frequent cancers has shown that these entities actually include a very large number of rare genomic diseases. The progression of each of these rare diseases is being driven by specific genomic alterations, leading to abnormal proteins that can be targeted. Based on this observation, several personalized medicine programmes have been launched. They consist in profiling the tumour samples from each patient, identifying key oncogenic drivers, and treating the patient accordingly. Several preliminary data suggest that this approach is feasible and could lead to anti-tumour effects that are currently modest. Several reasons could explain why personalized medicine programmes only report modest activity to targeted agents. First, the identification of key oncogenic drivers among several genomic alterations can be challenging. Second, the intratumour heterogeneity could lead to the emergence of resistant clones. Finally, several genomic alterations could contribute to cancer progression. These observations are leading to the second generation of personalized medicine trials, where targeted therapies are combined with each other and with immunotherapeutics, and where patients are selected to present a tumour with a low level of genetic instability.

Epistatic interactions and drug response

The advent of massively parallel sequencing has allowed for an unprecedented genetic characterization of cancers, which has revealed not only the complexity of cancer genomes, but also the fact that tumours from the same anatomical site or even of the same histological and/or molecular subtype display distinct constellations of somatic genetic aberrations. Epistatic interactions (ie the interplay between genetic aberrations) are likely to play pivotal roles not only in terms of tumourigenesis and disease progression, but also in response to therapeutic interventions. In this review, we discuss the challenges posed by the complexity of tumour genomes and epistatic interactions, and approaches for harnessing the wealth of genetic information on human cancers for the implementation of precision medicine.

Establishing the origin of metastatic deposits in the setting of multiple primary malignancies: the role of massively parallel sequencing

In this proof-of-principle study, we sought to define whether targeted capture massively parallel sequencing can be employed to determine the origin of metastatic deposits in cases of synchronous primary malignancies and metastases in distinct anatomical sites. DNA samples extracted from synchronous tumor masses in the breast, adnexal, and pelvic-peritoneal regions from a 62-year-old BRCA1 germline mutation carrier were subjected to targeted massively parallel sequencing using a platform comprising 300 cancer genes known to harbor actionable mutations. In addition to BRCA1 germline mutations, all lesions harbored somatic loss of the BRCA1 wild-type allele and TP53 somatic mutations. The primary breast cancer displayed a TP53 frameshift (p.Q317fs) mutation, whereas and the adnexal lesion harbored a TP53 nonsense (p.R213*) mutation, consistent with a diagnosis of two independent primary tumors (i.e. breast and ovarian cancer). The adnexal tumor and all pelvic-peritoneal implants harbored identical TP53 (p.R213*) and NCOA2 (p.G952R) somatic mutations. Evidence of genetic heterogeneity within and between lesions was observed, both in terms of somatic mutations and copy number aberrations. The repertoires of somatic genetic aberrations found in the breast, ovarian, and pelvic-peritoneal lesions provided direct evidence in support of the distinct origin of the breast and ovarian cancers, and established that the pelvic-peritoneal implants were clonally related to the ovarian lesion. These observations were consistent with those obtained with immunohistochemical analyses employing markers to differentiate between carcinomas of the breast and ovary, including WT1 and PAX8. Our results on this case of a patient with BRCA1-mutant breast and ovarian cancer demonstrate that massively parallel sequencing may constitute a useful tool to define the relationship, clonality and intra-tumor genetic heterogeneity between primary tumor masses and their metastatic deposits in patients with multiple primary malignancies and synchronous metastases.

Anti-angiogenic therapy for cancer: current progress, unresolved questions and future directions

Tumours require a vascular supply to grow and can achieve this via the expression of pro-angiogenic growth factors, including members of the vascular endothelial growth factor (VEGF) family of ligands. Since one or more of the VEGF ligand family is overexpressed in most solid cancers, there was great optimism that inhibition of the VEGF pathway would represent an effective anti-angiogenic therapy for most tumour types. Encouragingly, VEGF pathway targeted drugs such as bevacizumab, sunitinib and aflibercept have shown activity in certain settings. However, inhibition of VEGF signalling is not effective in all cancers, prompting the need to further understand how the vasculature can be effectively targeted in tumours. Here we present a succinct review of the progress with VEGF-targeted therapy and the unresolved questions that exist in the field: including its use in different disease stages (metastatic, adjuvant, neoadjuvant), interactions with chemotherapy, duration and scheduling of therapy, potential predictive biomarkers and proposed mechanisms of resistance, including paradoxical effects such as enhanced tumour aggressiveness. In terms of future directions, we discuss the need to delineate further the complexities of tumour vascularisation if we are to develop more effective and personalised anti-angiogenic therapies.

Paracrine signaling in mammary gland development: what can we learn about intratumoral heterogeneity?

Paracrine signaling mechanisms play a critical role in both normal mammary gland development and breast cancer. Dissection of these mechanisms using genetically engineered mouse models has provided significant insight into our understanding of the mechanisms that guide intratumoral heterogeneity. In the following perspective, we briefly review some of the emerging concepts in this field and emphasize why elucidation of these pathways will be important for future progress in devising new and improved combinatorial therapeutic approaches for breast and other solid cancers.

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity

Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and posttreatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution.