Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution. Nature. 2009;461:809-813. [PMID: 19812674 DOI: 10.1038/nature08489]

Covalent self-assembled nanoparticles with pH-dependent enhanced tumor retention and drug release for improving tumor therapeutic efficiency

Developing a smart drug delivery system with enhanced tumor retention at the tumor site, and rapid intracellular drug release promises to improve the therapeutic index and mitigate side effects. To this end, covalent phenylboronic acid (PBA)-based self-assembly nanoparticles (BNPs) consisting of pH-responsive cores and detachable poloxamer 188 shells were constructed for loading doxorubicin (DOX) in a simple process. The poloxamer 188 coating could be easily detached when the breakage of the borate ester bonds in the external nanocores was initially triggered in the tumor extracellular weak acid environment. The concealed PBA was subsequently exposed and could react with sialic acids (SA), which are overexpressed on tumor cells, and this enhanced the tumor retention effect of the fresh nanoparticle as well as facilitating the cellular uptake after removing the protective layers. Furthermore, owing to the existence of pH-responsive esters, the uptaken fresh nanoparticles could rapidly release DOX in the acidic tumor environment, which resulted in an enhanced therapeutic efficiency in vitro and in vivo. In summary, this pH dependent behaviour of DOX/BNPs provided new insights for enhanced chemotherapeutic treatment in cancer.

Constraints in cancer evolution

Next-generation deep genome sequencing has only recently allowed us to quantitatively dissect the extent of heterogeneity within a tumour, resolving patterns of cancer evolution. Intratumour heterogeneity and natural selection contribute to resistance to anticancer therapies in the advanced setting. Recent evidence has also revealed that cancer evolution might be constrained. In this review, we discuss the origins of intratumour heterogeneity and subsequently focus on constraints imposed upon cancer evolution. The presence of (1) parallel evolution, (2) convergent evolution and (3) the biological impact of acquiring mutations in specific orders suggest that cancer evolution may be exploitable. These constraints on cancer evolution may help us identify cancer evolutionary rule books, which could eventually inform both diagnostic and therapeutic approaches to improve survival outcomes.

Next-Generation Sequencing in Oncology: Genetic Diagnosis, Risk Prediction and Cancer Classification

Next-generation sequencing (NGS) technology has expanded in the last decades with significant improvements in the reliability, sequencing chemistry, pipeline analyses, data interpretation and costs. Such advances make the use of NGS feasible in clinical practice today. This review describes the recent technological developments in NGS applied to the field of oncology. A number of clinical applications are reviewed, i.e., mutation detection in inherited cancer syndromes based on DNA-sequencing, detection of spliceogenic variants based on RNA-sequencing, DNA-sequencing to identify risk modifiers and application for pre-implantation genetic diagnosis, cancer somatic mutation analysis, pharmacogenetics and liquid biopsy. Conclusive remarks, clinical limitations, implications and ethical considerations that relate to the different applications are provided.

Identification of Diverse Adenosine-to-Inosine RNA Editing Subtypes in Colorectal Cancer

PURPOSE

RNA editing generates protein diversity by altering RNA sequences in coding regions without changing the overall DNA sequence. Adenosine-to-inosine (A-to-I) RNA editing events have recently been reported in some types of cancer, but they are rare in human colorectal cancer (CRC). Therefore, this study was conducted to identify diverse RNA editing in CRC.

MATERIALS AND METHODS

We compared transcriptome data of 39 CRC samples and paired adjacent tissues from The Cancer Genome Atlas database to identify RNA editing patterns in CRC, focusing on canonical A-to-I RNA edits in coding sequence regions. We investigated nonsynonymous RNA editing patterns by comparing tumor and normal tissue transcriptome data.

RESULTS

The number of RNA edits varied from 12 to 42 per sample. We also observed that hypoand hyper-RNA editing patterns were distinguishable within the samples. We found 10 recurrent nonsynonymous RNA editing candidates in nine genes (PDLIM, NEIL1, SRP9, GLI1, APMAP, IGFBP7, ZNF358, COPA, and ZNF587B) and validated some by Sanger sequencing and the inosine chemical erasing assay. We further showed that editing at these positions was performed by the adenosine deaminase acting on RNA 1 enzyme. Most of these genes are hypoedited in CRC, but editing of GLI1 was increased in cancer tissues compared with normal tissues.

CONCLUSION

Our results show that nonsynonymous RNA editing patterns can be used to identify CRC patients and could serve as novel biomarkers for CRC.

ADAR1 overexpression is associated with cervical cancer progression and angiogenesis

BACKGROUND

This study aimed to assess the role of RNA-dependent adenosine deaminase (ADAR1) in cervical squamous cell carcinoma occurrence and progression.

METHODS

ADAR1 expression levels in stage IA and stage IIA cervical squamous cell carcinoma (group A), cervical intraepithelial neoplasia (CIN) specimens (group B), as well as normal and inflamed cervical tissue samples (group C) were assessed by immunohistochemistry. Clinical and pathological data of cervical squamous cell carcinoma patients undergoing surgery were retrospectively evaluated. Chi-square test, comparative analysis of survival curve, disease-free survival and COX risk assessment method were used to understand the association of ADAR1 with the occurrence and progression and prognostic significance of cervical squamous cell carcinoma.

RESULTS

ADAR1 is expressed in the cytoplasm and nuclei. The expression level was high in squamous cell carcinoma tissues (81.18%), while relatively low in the CIN group (21.56%). And there was no expression in non-cancerous tissues. The differences between them were statistically significant using P < 0.05 as criterion. One-factor analysis revealed that ADAR1 was significantly correlated with tumor diameter, horizontal diffusion diameter, vascular invasion, parametrial invasion, vaginal involvement, and pathologically diagnostic criteria for perineural invasion (PNI). Meanwhile, the overall survival rate of ADAR1 positive patients was significantly lower compared with that of patients with no ADAR1 expression (P < 0.05). Analysis also showed that disease-free survival time of ADAR1 positive patients was shorter than that of ADAR1 negative patients, and the difference was significant (P < 0.01). Finally, COX risk assessment showed that parametrical invasion had independent prognostic factors for overall survival of squamous cell carcinoma.

CONCLUSIONS

Results indicated that ADAR1 might play an important role in the occurrence, progression and prognosis of cervical squamous cancer.

Scalable whole-genome single-cell library preparation without preamplification

Single-cell genomics is critical for understanding cellular heterogeneity in cancer, but existing library preparation methods are expensive, require sample preamplification and introduce coverage bias. Here we describe direct library preparation (DLP), a robust, scalable, and high-fidelity method that uses nanoliter-volume transposition reactions for single-cell whole-genome library preparation without preamplification. We examined 782 cells from cell lines and triple-negative breast xenograft tumors. Low-depth sequencing, compared with existing methods, revealed greater coverage uniformity and more reliable detection of copy-number alterations. Using phylogenetic analysis, we found minor xenograft subpopulations that were undetectable by bulk sequencing, as well as dynamic clonal expansion and diversification between passages. Merging single-cell genomes in silico, we generated 'bulk-equivalent' genomes with high depth and uniform coverage. Thus, low-depth sequencing of DLP libraries may provide an attractive replacement for conventional bulk sequencing methods, permitting analysis of copy number at the cell level and of other genomic variants at the population level.

MORC Proteins: Novel Players in Plant and Animal Health

Microrchidia (MORC) proteins comprise a family of proteins that have been identified in prokaryotes and eukaryotes. They are defined by two hallmark domains: a GHKL-type ATPase and an S5 fold. MORC proteins in plants were first discovered via a genetic screen for Arabidopsis mutants compromised for resistance to a viral pathogen. Subsequent studies expanded their role in plant immunity and revealed their involvement in gene silencing and transposable element repression. Emerging data suggest that MORC proteins also participate in pathogen-induced chromatin remodeling and epigenetic gene regulation. In addition, biochemical analyses recently demonstrated that plant MORCs have topoisomerase II (topo II)-like DNA modifying activities that may be important for their function. Interestingly, animal MORC proteins exhibit many parallels with their plant counterparts, as they have been implicated in disease development and gene silencing. In addition, human MORCs, like plant MORCs, bind salicylic acid and this inhibits some of their topo II-like activities. In this review, we will focus primarily on plant MORCs, although relevant comparisons with animal MORCs will be provided.

ADAR2 functions as a tumor suppressor via editing IGFBP7 in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC), one of the most aggressive cancers, is characterized by heterogeneous genetic and epigenetic changes. Recently, A-to-I RNA editing, catalyzed by adenosine deaminases acting on RNA (ADARs), was found to be aberrantly regulated during tumorigenesis. We previously reported that ADAR2 was downregulated in ESCC but its role was unclear. Thus, we report here that overexpression of ADAR2 can induce apoptosis in ESCC cell lines and inhibit tumor growth in vitro and in vivo. ADAR2 knockdown inhibited apoptosis in ADAR2 highly expressing tumor cells. RNA-seq assay showed that ADAR2, not ADAR1 or active-site-mutated ADAR2, could edit insulin-like growth factor binding protein 7 (IGFBP7) mRNA in ESCC. IGFBP7 knockdown or ADAR2 catalytic activity destruction abolished the pro-apoptotic function of ADAR2. Mechanistically, RNA editing may stabilize IGFBP7 protein by changing the protease recognition site of matriptase and this is essential for IGFBP7 to induce apoptosis. Western blotting revealed that ADAR2 overexpression could induce IGFBP7-dependent inhibition of Akt signaling. Thus, our data indicate that ADAR2 suppresses tumor growth and induces apoptosis by editing and stabilizing IGFBP7 in ESCC, and this may represent a novel therapeutic target for treating ESCC.

Tumour Heterogeneity: The Key Advantages of Single-Cell Analysis

Tumour heterogeneity refers to the fact that different tumour cells can show distinct morphological and phenotypic profiles, including cellular morphology, gene expression, metabolism, motility, proliferation and metastatic potential. This phenomenon occurs both between tumours (inter-tumour heterogeneity) and within tumours (intra-tumour heterogeneity), and it is caused by genetic and non-genetic factors. The heterogeneity of cancer cells introduces significant challenges in using molecular prognostic markers as well as for classifying patients that might benefit from specific therapies. Thus, research efforts for characterizing heterogeneity would be useful for a better understanding of the causes and progression of disease. It has been suggested that the study of heterogeneity within Circulating Tumour Cells (CTCs) could also reflect the full spectrum of mutations of the disease more accurately than a single biopsy of a primary or metastatic tumour. In previous years, many high throughput methodologies have raised for the study of heterogeneity at different levels (i.e., RNA, DNA, protein and epigenetic events). The aim of the current review is to stress clinical implications of tumour heterogeneity, as well as current available methodologies for their study, paying specific attention to those able to assess heterogeneity at the single cell level.

Survival with metastatic breast cancer based on initial presentation, de novo versus relapsed

PURPOSE

We hypothesized different Overall Survival (OS) in metastatic breast cancer (MBC) after relapse vs de novo presentation.

METHODS

We identified women in British Columbia with MBC diagnosed between 01/2001 and 12/2009. OS from MBC was calculated for relapsed vs de novo cohorts in 3 subgroups, based on hormone receptors (HR) and HER2 status. Age at MBC, disease-free interval (DFI), de novo vs relapsed, year of MBC diagnosis, and systemic treatment were entered into univariable and multivariable analyses.

RESULTS

We identified 3645 pts with known HR of which 2796 had known HER2. Median follow-up was 91 months. Median OS was longer for de novo vs relapsed MBC: HR+/HER2- 34 versus 23 months (mos) (p < 0.0001), HR-/HER2- (TN) 11 versus 8 mos (p = 0.02), HER2+ 29 versus 15 mos (p < 0.0001). For TN disease, no variable independently discriminated a group with increased risk of death. For both the HR +/HER2- and the HER2 + groups, relapsed vs de novo status (HzR 1.4 [95% CI 1.2-1.5; p < 0.0001], and HzR 1.6 [95% CI 1.4-1.9; p < 0.0001], respectively) and age >50 (HzR 1.2 [95% CI 1.1-1.4; p = 0.001] and HzR 1.3 [95% CI 1.1-1.5; p = 0.01], respectively) were associated with increased risk of death on multivariable analysis.

CONCLUSION

These data provide information that may guide discussions about prognosis between physicians and patients with MBC. In addition, it highlights the importance of stratifying for initial stage at diagnosis in future MBC therapeutic trials.

Genetic traits for hematogeneous tumor cell dissemination in cancer patients

Metastatic relapse in patients with solid tumors is the consequence of cancer cells that disseminated to distant sites, adapted to the new microenvironment, and escaped systemic adjuvant therapy. There is increasing evidence that hematogeneous dissemination starts at an early stage of cancer progression with single tumor cells or cell clusters leaving the primary site and entering the blood circulation. These circulating tumor cells (CTCs) can extravasate into secondary tissues where they become disseminated tumor cells (DTCs). Patients might relapse years after initial resection of the primary tumor when DTCs become overt metastases. Current diagnostic strategies for stratification of therapies against metastatic cells focus on the primary tumor tissue. This approach is based on the availability of stored primary tumors obtained at primary surgery, but it ignores that the DTCs might have evolved over years, which can affect the antimetastatic drug response. However, taking biopsies from metastatic tissues is an invasive procedure, and multiple metastases located at different sites in an individual patient show marked genomic heterogeneity. Thus, capturing CTCs from the peripheral blood as a "liquid biopsy" has obvious advantages in particular when repeated sampling is required for monitoring therapies in cancer patients. However, the biology behind tumor cell dissemination and its contribution to metastatic progression in cancer patients is still subject to controversial discussions. This manuscript reviews current theories on the genetic traits behind the spread of CTCs and progression of DTCs into overt metastases.

Catalog of genetic progression of human cancers: breast cancer

With the rapid development of next-generation sequencing, deeper insights are being gained into the molecular evolution that underlies the development and clinical progression of breast cancer. It is apparent that during evolution, breast cancers acquire thousands of mutations including single base pair substitutions, insertions, deletions, copy number aberrations, and structural rearrangements. As a consequence, at the whole genome level, no two cancers are identical and few cancers even share the same complement of "driver" mutations. Indeed, two samples from the same cancer may also exhibit extensive differences due to constant remodeling of the genome over time. In this review, we summarize recent studies that extend our understanding of the genomic basis of cancer progression. Key biological insights include the following: subclonal diversification begins early in cancer evolution, being detectable even in in situ lesions; geographical stratification of subclonal structure is frequent in primary tumors and can include therapeutically targetable alterations; multiple distant metastases typically arise from a common metastatic ancestor following a "metastatic cascade" model; systemic therapy can unmask preexisting resistant subclones or influence further treatment sensitivity and disease progression. We conclude the review by describing novel approaches such as the analysis of circulating DNA and patient-derived xenografts that promise to further our understanding of the genomic changes occurring during cancer evolution and guide treatment decision making.

The Subclonal Architecture of Metastatic Breast Cancer: Results from a Prospective Community-Based Rapid Autopsy Program "CASCADE"

BACKGROUND

Understanding the cancer genome is seen as a key step in improving outcomes for cancer patients. Genomic assays are emerging as a possible avenue to personalised medicine in breast cancer. However, evolution of the cancer genome during the natural history of breast cancer is largely unknown, as is the profile of disease at death. We sought to study in detail these aspects of advanced breast cancers that have resulted in lethal disease.

METHODS AND FINDINGS

Three patients with oestrogen-receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer and one patient with triple negative breast cancer underwent rapid autopsy as part of an institutional prospective community-based rapid autopsy program (CASCADE). Cases represented a range of management problems in breast cancer, including late relapse after early stage disease, de novo metastatic disease, discordant disease response, and disease refractory to treatment. Between 5 and 12 metastatic sites were collected at autopsy together with available primary tumours and longitudinal metastatic biopsies taken during life. Samples underwent paired tumour-normal whole exome sequencing and single nucleotide polymorphism (SNP) arrays. Subclonal architectures were inferred by jointly analysing all samples from each patient. Mutations were validated using high depth amplicon sequencing. Between cases, there were significant differences in mutational burden, driver mutations, mutational processes, and copy number variation. Within each case, we found dramatic heterogeneity in subclonal structure from primary to metastatic disease and between metastatic sites, such that no single lesion captured the breadth of disease. Metastatic cross-seeding was found in each case, and treatment drove subclonal diversification. Subclones displayed parallel evolution of treatment resistance in some cases and apparent augmentation of key oncogenic drivers as an alternative resistance mechanism. We also observed the role of mutational processes in subclonal evolution. Limitations of this study include the potential for bias introduced by joint analysis of formalin-fixed archival specimens with fresh specimens and the difficulties in resolving subclones with whole exome sequencing. Other alterations that could define subclones such as structural variants or epigenetic modifications were not assessed.

CONCLUSIONS

This study highlights various mechanisms that shape the genome of metastatic breast cancer and the value of studying advanced disease in detail. Treatment drives significant genomic heterogeneity in breast cancers which has implications for disease monitoring and treatment selection in the personalised medicine paradigm.

Patient-derived xenograft (PDX) models in basic and translational breast cancer research

Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational preclinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and "Triple-negative" (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward "credentialing" of PDX models as surrogates to represent individual patients for use in preclinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research.

Quantitative assessment of pancreatic cancer precursor lesions in IHC-stained tissue with a tissue image analysis platform

Tissue image analysis (tIA) is emerging as a powerful tool for quantifying biomarker expression and distribution in complex diseases and tissues. Pancreatic ductal adenocarcinoma (PDAC) develops in a highly complex and heterogeneous tissue environment and, generally, has a very poor prognosis. Early detection of PDAC is confounded by limited knowledge of the pre-neoplastic disease stages and limited methods to quantitatively assess disease heterogeneity. We sought to develop a tIA approach to assess the most common PDAC precursor lesions, pancreatic intraepithelial neoplasia (PanIN), in tissues from Kras^LSL-G12D/+; Trp53^LSL-R172H/+; Pdx-Cre (KPC) mice, a validated model of PDAC development. tIA profiling of training regions of PanIN and tumor microenvironment (TME) cells was utilized to guide identification of PanIN/TME tissue compartment stratification criteria. A custom CellMap algorithm implementing these criteria was applied to whole-slide images of KPC mice pancreata sections to quantify p53 and Ki-67 biomarker staining in each tissue compartment as a proof-of-concept for the algorithm platform. The algorithm robustly identified a higher percentage of p53-positive cells in PanIN lesions relative to the TME, whereas no difference was observed for Ki-67. Ki-67 expression was also quantified in a human pancreatic tissue sample available to demonstrate the translatability of the CellMap algorithm to human samples. Together, our data demonstrated the utility of CellMap to enable objective and quantitative assessments, across entire tissue sections, of PDAC precursor lesions in preclinical and clinical models of this disease to support efforts leading to novel insights into disease progression, diagnostic markers, and potential therapeutic targets.

Cancer Genomics: Large-Scale Projects Translate into Therapeutic Advances

Elaine Mardis and Marc Ladanyi discuss how large-scale genomics has driven advances in cancer translational medicine, with a focus on publications in this month's Special Issue.

The Emerging Role of MORC Family Proteins in Cancer Development and Bone Homeostasis

Microrchidia (MORC or MORC family CW-type zinc finger protein), a highly conserved nuclear protein superfamily, is an interesting new player in signaling-dependent chromatin remodeling and epigenetic regulation. MORC family proteins consist of MORC1, MORC2, MORC3, and MORC4 which display common structural determinants such as CW-type zinc finger and coiled-coil domains. They also exhibit unique structural motifs and tissue-specific expression profiles. MORC1 was first discovered as a key regulator for male meiosis and spermatogenesis. Accumulating biochemical and functional analyses unveil MORC proteins as key regulators for cancer development. More recently, using an ENU mutagenesis mouse model, MORC3 was found to play a role in regulating bone and calcium homeostasis. Here we discuss recent research progress on the emerging role of MORC proteins in cancer development and bone metabolism. Unravelling the cellular and molecular mechanisms by which MORC proteins carry out their functions in a tissue specific manner are important subjects for future investigation. J. Cell. Physiol. 232: 928-934, 2017. © 2016 Wiley Periodicals, Inc.

Genomic dynamics associated with malignant transformation in IDH1 mutated gliomas

The genomic mechanism responsible for malignant transformation remains an open question for glioma researchers, where differing conclusions have been drawn based on diverse study conditions. Therefore, it is essential to secure direct evidence using longitudinal samples from the same patient. Moreover, malignant transformation of IDH1-mutated gliomas is of potential interest, as its genomic mechanism under influence of oncometabolite remains unclear, and even higher rate of malignant transformation was reported in IDH1-mutated low grade gliomas than in wild-type IDH1 tumors. We have analyzed genomic data using next-generation sequencing technology for longitudinal samples from 3 patients with IDH1-mutated gliomas whose disease had progressed from a low grade to a high grade phenotype. Comprehensive analysis included chromosomal aberrations as well as whole exome and transcriptome sequencing, and the candidate driver genes for malignant transformation were validated with public database. Integrated analysis of genomic dynamics in clonal evolution during the malignant transformation revealed alterations in the machinery regulating gene expression, including the spliceosome complex (U2AF2), transcription factors (TCF12), and chromatin remodelers (ARID1A). Moreover, consequential expression changes implied the activation of genes associated with the restoration of the stemness of cancer cells. The alterations in genetic regulatory mechanisms may be the key factor for the major phenotypic changes in IDH1 mutated gliomas. Despite being limited to a small number of cases, this analysis provides a direct example of the genomic changes responsible for malignant transformation in gliomas.

Clinical Applications of Next-Generation Sequencing in Cancer Diagnosis

With the advancement and improvement of new sequencing technology, next-generation sequencing (NGS) has been applied increasingly in cancer genomics research fields. More recently, NGS has been adopted in clinical oncology to advance personalized treatment of cancer. NGS is utilized to novel diagnostic and rare cancer mutations, detection of translocations, inversions, insertions and deletions, detection of copy number variants, detect familial cancer mutation carriers, provide the molecular rationale for appropriate targeted, therapeutic and prognostic. NGS holds many advantages, such as the ability to fully sequence all types of mutations for a large number of genes (hundreds to thousands) and the sensitivity, speed in a single test at a relatively low cost compared to be other sequencing modalities. Here we described the technology, methods and applications that can be immediately considered and some of the challenges that lie ahead.

Mutational profiling of brain metastasis from breast cancer: matched pair analysis of targeted sequencing between brain metastasis and primary breast cancer

Although breast cancer is the second most common cause of brain metastasis with a notable increase of incidence, genes that mediate breast cancer brain metastasis (BCBM) are not fully understood. To study the molecular nature of brain metastasis, we performed gene expression profiling of brain metastasis and matched primary breast cancer (BC). We used the Ion AmpliSeq Cancer Panel v2 covering 2,855 mutations from 50 cancer genes to analyze 18 primary BC and 42 BCBM including 15 matched pairs. The most common BCBM subtypes were triple-negative (42.9%) and basal-like (36.6%). In a total of 42 BCBM samples, 32 (76.2%) harbored at least one mutation (median 1, range 0–7 mutations). Frequently detected somatic mutations included TP53 (59.5%), MLH1 (14.3%), PIK3CA (14.3%), and KIT (7.1%). We compared BCBM with patient-matched primary BC specimens. There were no significant differences in mutation profiles between the two groups. Notably, gene expression in BCBM such as TP53, PIK3CA, KIT, MLH1, and RB1 also seemed to be present in primary breast cancers. The TP53 mutation frequency was higher in BCBM than in primary BC (59.5% vs 38.9%, respectively). In conclusion, we found actionable gene alterations in BCBM that were maintained in primary BC. Further studies with functional testing and a delineation of the role of these genes in specific steps of the metastatic process should lead to a better understanding of the biology of metastasis and its susceptibility to treatment.

Development of a robust DNA quality and quantity assessment qPCR assay for targeted next-generation sequencing library preparation

Next-generation sequencing (NGS) is becoming a standard for genetic analyses of clinical samples. DNAs retrieved from formalin-fixed, paraffin-embedded (FFPE) tissue specimens are commonly degraded, and specimens such as core biopsies are sometimes too small to obtain enough DNA for NGS applications. Thus, it is important to measure both the DNA quantity and quality accurately from clinical samples. However, there is no standard method for DNA quantity and quality analyses for NGS library preparation. We tested four different methods (PicoGreen, Qubit® fluorometry, TaqMan and SYBR-Green-based qPCR assay) and compared each to RNase P TaqMan as a reference control. We found that SYBR-Green-based qPCR assay provides a consistent and accurate DNA quantification while keeping its cost relatively low and the throughput high. We designed a dual-probe SYBR-Green qPCR assay for DNA quantity and quality assessment for targeted NGS library preparation. This assay provides a Dscore (degradation score) of the interrogated DNA by analyzing two different sizes of amplicons. We show an example of a clinical sample with a very high Dscore (high degradation). With a regular DNA quantification, without considering the degradation status, no correct NGS libraries were obtained. However, after optimizing the library condition by considering its poor DNA quality, a reasonably good library and sequencing results were obtained. In summary, we developed and presented a new DNA quantity and quality analysis qPCR assay for the targeted NGS library preparation. This assay may be mostly efficient for the clinical samples with high degradation and poor DNA quality.

Patients with Concordant Triple-Negative Phenotype between Primary Breast Cancers and Corresponding Metastases Have Poor Prognosis

Purpose

We investigated the prognostic impact of discordance between the receptor status of primary breast cancers and corresponding metastases.

Methods

A total 144 patients with breast cancer and distant metastasis were investigated. The estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status of primary tumor and corresponding metastases were assessed. Tumor phenotype according to receptor status was classified as triple-negative phenotype (TNP) or non-TNP. Concordance and discordance was determined by whether there was a change in receptor status or phenotype between primary and metastatic lesions.

Results

The rates of discordance between primary breast cancer and metastatic lesions were 18.1%, 25.0%, and 10.3% for ER, PR, and HER2, respectively. The rates of concordant non-TNP, concordant TNP and discordant TNP were 65.9%, 20.9%, and 13.2%, respectively. Patients with concordant ER/PR-negative status had worse postrecurrence survival (PRS) than patients with concordant ER/PR-positive and discordant ER/PR status (p=0.001 and p=0.021, respectively). Patients who converted from HER2-positive to negative after distant metastasis had worst PRS (p=0.040). Multivariate analysis showed that concordant TNP was statistically significant factor for worse PRS (p<0.001).

Conclusion

Discordance in receptor status and tumor phenotype between primary breast cancer and corresponding metastatic lesions was observed. Patients with concordant TNP had worse long-term outcomes than patients with concordant non-TNP and discordant TNP between primary and metastatic breast cancer. Identifying the receptor status of metastatic lesions may lead to improvements in patient management and survival.

A Biobank of Breast Cancer Explants with Preserved Intra-tumor Heterogeneity to Screen Anticancer Compounds

The inter- and intra-tumor heterogeneity of breast cancer needs to be adequately captured in pre-clinical models. We have created a large collection of breast cancer patient-derived tumor xenografts (PDTXs), in which the morphological and molecular characteristics of the originating tumor are preserved through passaging in the mouse. An integrated platform combining in vivo maintenance of these PDTXs along with short-term cultures of PDTX-derived tumor cells (PDTCs) was optimized. Remarkably, the intra-tumor genomic clonal architecture present in the originating breast cancers was mostly preserved upon serial passaging in xenografts and in short-term cultured PDTCs. We assessed drug responses in PDTCs on a high-throughput platform and validated several ex vivo responses in vivo. The biobank represents a powerful resource for pre-clinical breast cancer pharmacogenomic studies (http://caldaslab.cruk.cam.ac.uk/bcape), including identification of biomarkers of response or resistance.

Using RNA-Seq SNP data to reveal potential causal mutations related to pig production traits and RNA editing

RNA-Seq technology is widely used in quantitative gene expression studies and identification of non-annotated transcripts. However this technology also can be used for polymorphism detection and RNA editing in transcribed regions in an efficient and cost-effective way. This study used SNP data from an RNA-Seq assay to identify genes and mutations underlying production trait variations in an experimental pig population. The hypothalamic and hepatic transcriptomes of nine extreme animals for growth and fatness from an (Iberian × Landrace) × Landrace backcross were analyzed by RNA-Seq methodology, and SNP calling was conducted. More than 125 000 single nucleotide variants (SNVs) were identified in each tissue, and 78% were considered to be potential SNPs, those SNVs segregating in the context of this study. Potential informative SNPs were detected by considering those showing a homozygous or heterozygous genotype in one extreme group and the alternative genotype in the other group. In this way, 4396 and 1862 informative SNPs were detected in hypothalamus and liver respectively. Out of the 32 SNPs selected for validation, 25 (80%) were confirmed as actual SNPs. Association analyses for growth, fatness and premium cut yields with 19 selected SNPs were carried out, and four potential causal genes (RETSAT, COPA, RNMT and PALMD) were identified. Interestingly, new RNA editing modifications were detected and validated for the NR3C1:g.102797 (ss1985401074) and ACSM2B:g.13374 (ss1985401075) positions and for the COG3:g3.4525 (ss1985401087) modification previously identified across vertebrates, which could lead to phenotypic variation and should be further investigated.

Remarkable similarities of chromosomal rearrangements between primary human breast cancers and matched distant metastases as revealed by whole-genome sequencing

To better understand and characterize chromosomal structural variation during breast cancer progression, we enumerated chromosomal rearrangements for 11 patients by performing low-coverage whole-genome sequencing of 11 primary breast tumors and their 13 matched distant metastases. The tumor genomes harbored a median of 85 (range 18-404) rearrangements per tumor, with a median of 82 (26-310) in primaries compared to 87 (18-404) in distant metastases. Concordance between paired tumors from the same patient was high with a median of 89% of rearrangements shared (range 61-100%), whereas little overlap was found when comparing all possible pairings of tumors from different patients (median 3%). The tumors exhibited diverse genomic patterns of rearrangements: some carried events distributed throughout the genome while others had events mostly within densely clustered chromothripsis-like foci at a few chromosomal locations. Irrespectively, the patterns were highly conserved between the primary tumor and metastases from the same patient. Rearrangements occurred more frequently in genic areas than expected by chance and among the genes affected there was significant enrichment for cancer-associated genes including disruption of TP53, RB1, PTEN, and ESR1, likely contributing to tumor development. Our findings are most consistent with chromosomal rearrangements being early events in breast cancer progression that remain stable during the development from primary tumor to distant metastasis.

MORC3, a Component of PML Nuclear Bodies, Has a Role in Restricting Herpes Simplex Virus 1 and Human Cytomegalovirus

We previously reported that MORC3, a protein associated with promyelocytic leukemia nuclear bodies (PML NBs), is a target of herpes simplex virus 1 (HSV-1) ICP0-mediated degradation (E. Sloan, et al., PLoS Pathog 11:e1005059, 2015, http://dx.doi.org/10.1371/journal.ppat.1005059). Since it is well known that certain other components of the PML NB complex play an important role during an intrinsic immune response to HSV-1 and are also degraded or inactivated by ICP0, here we further investigate the role of MORC3 during HSV-1 infection. We demonstrate that MORC3 has antiviral activity during HSV-1 infection and that this antiviral role is counteracted by ICP0. In addition, MORC3's antiviral role extends to wild-type (wt) human cytomegalovirus (HCMV) infection, as its plaque-forming efficiency increased in MORC3-depleted cells. We found that MORC3 is recruited to sites associated with HSV-1 genomes after their entry into the nucleus of an infected cell, and in wt infections this is followed by its association with ICP0 foci prior to its degradation. The RING finger domain of ICP0 was required for degradation of MORC3, and we confirmed that no other HSV-1 protein is required for the loss of MORC3. We also found that MORC3 is required for fully efficient recruitment of PML, Sp100, hDaxx, and γH2AX to sites associated with HSV-1 genomes entering the host cell nucleus. This study further unravels the intricate ways in which HSV-1 has evolved to counteract the host immune response and reveals a novel function for MORC3 during the host intrinsic immune response.

IMPORTANCE

Herpesviruses have devised ways to manipulate the host intrinsic immune response to promote their own survival and persistence within the human population. One way in which this is achieved is through degradation or functional inactivation of PML NB proteins, which are recruited to viral genomes in order to repress viral transcription. Because MORC3 associates with PML NBs in uninfected cells and is a target for HSV-1-mediated degradation, we investigated the role of MORC3 during HSV-1 infection. We found that MORC3 is also recruited to viral HSV-1 genomes, and importantly it contributes to the fully efficient recruitment of PML, hDaxx, Sp100, and γH2AX to these sites. Depletion of MORC3 resulted in an increase in ICP0-null HSV-1 and wt HCMV replication and plaque formation; therefore, this study reveals that MORC3 is an antiviral factor which plays an important role during HSV-1 and HCMV infection.

Deciphering and Targeting Oncogenic Mutations and Pathways in Breast Cancer

: Advances in DNA and RNA sequencing revealed substantially greater genomic complexity in breast cancer than simple models of a few driver mutations would suggest. Only very few, recurrent mutations or copy-number variations in cancer-causing genes have been identified. The two most common alterations in breast cancer are TP53 (affecting the majority of triple-negative breast cancers) and PIK3CA (affecting almost half of estrogen receptor-positive cancers) mutations, followed by a long tail of individually rare mutations affecting <1%-20% of cases. Each cancer harbors from a few dozen to a few hundred potentially high-functional impact somatic variants, along with a much larger number of potentially high-functional impact germline variants. It is likely that it is the combined effect of all genomic variations that drives the clinical behavior of a given cancer. Furthermore, entirely new classes of oncogenic events are being discovered in the noncoding areas of the genome and in noncoding RNA species driven by errors in RNA editing. In light of this complexity, it is not unexpected that, with the exception of HER2 amplification, no robust molecular predictors of benefit from targeted therapies have been identified. In this review, we summarize the current genomic portrait of breast cancer, focusing on genetic aberrations that are actively being targeted with investigational drugs.

IMPLICATIONS FOR PRACTICE

Next-generation sequencing is now widely available in the clinic, but interpretation of the results is challenging, and its impact on treatment selection is often limited. This work provides an overview of frequently encountered molecular abnormalities in breast cancer and discusses their potential therapeutic implications. This review emphasizes the importance of administering investigational targeted therapies, or off-label use of approved targeted drugs, in the context of a formal clinical trial or registry programs to facilitate learning about the clinical utility of tumor target profiling.

Multiplexed imaging reveals heterogeneity of PI3K/MAPK network signaling in breast lesions of known PIK3CA genotype

PURPOSE

Activating genetic changes in the phosphatidylinositol-3-kinase (PI3K) signaling pathway are found in over half of invasive breast cancers (IBCs). Previously, we discovered numerous hotspot PIK3CA mutations in proliferative breast lesions. Here, we investigate the spatial nature of PI3K pathway signaling and its relationship with PI3K genotype in breast lesions.

METHODS

We identified PI3K phosphosignaling network signatures in columnar cell change (CCL), usual ductal hyperplasia (UDH), ductal carcinoma in situ (DCIS), and IBC in 26 lesions of known PIK3CA genotype from 10 human breast specimens using a hyperspectral-based multiplexed tissue imaging platform (MTIP) to simultaneously quantitate PI3K/MAPK pathway targets (pAKT473, pAKT308, pPRAS40, pS6, and pERK) in FFPE tissue, with single-cell resolution.

RESULTS

We found that breast lesional epithelia contained spatially heterogeneous patterns of PI3K pathway phosphoprotein signatures, even within microscopic areas of CCL, UDH, DCIS, and IBC. Most lesions contained 3-12 unique phosphoprotein signatures within the same microscopic field. The dominant phosphoprotein signature for each lesion was not well correlated with lesion genotype or lesion histology, yet samples from the same patient tended to group together. Further, 5 UDH/CCL lesions across different patients had a common phosphosignature at the epithelial-stromal interface (possible myoepithelial cells) that was distinct from both the adjacent lesional epithelium and distinct from adjacent stroma.

CONCLUSION

We present the first spatial mapping of PI3K phosphoprotein networks in proliferative breast lesions and demonstrate complex PI3K signaling heterogeneity that defies simple correlation between PIK3CA genotype and phosphosignal pattern.

RNA2DNAlign: nucleotide resolution allele asymmetries through quantitative assessment of RNA and DNA paired sequencing data

We introduce RNA2DNAlign, a computational framework for quantitative assessment of allele counts across paired RNA and DNA sequencing datasets. RNA2DNAlign is based on quantitation of the relative abundance of variant and reference read counts, followed by binomial tests for genotype and allelic status at SNV positions between compatible sequences. RNA2DNAlign detects positions with differential allele distribution, suggesting asymmetries due to regulatory/structural events. Based on the type of asymmetry, RNA2DNAlign outlines positions likely to be implicated in RNA editing, allele-specific expression or loss, somatic mutagenesis or loss-of-heterozygosity (the first three also in a tumor-specific setting). We applied RNA2DNAlign on 360 matching normal and tumor exomes and transcriptomes from 90 breast cancer patients from TCGA. Under high-confidence settings, RNA2DNAlign identified 2038 distinct SNV sites associated with one of the aforementioned asymetries, the majority of which have not been linked to functionality before. The performance assessment shows very high specificity and sensitivity, due to the corroboration of signals across multiple matching datasets. RNA2DNAlign is freely available from http://github.com/HorvathLab/NGS as a self-contained binary package for 64-bit Linux systems.

Detection of canonical A-to-G editing events at 3' UTRs and microRNA target sites in human lungs using next-generation sequencing

RNA editing is a post-transcriptional modification of RNA. The majority of these changes result from adenosine deaminase acting on RNA (ADARs) catalyzing the conversion of adenosine residues to inosine in double-stranded RNAs (dsRNAs). Massively parallel sequencing has enabled the identification of RNA editing sites in human transcriptomes. In this study, we sequenced DNA and RNA from human lungs and identified RNA editing sites with high confidence via a computational pipeline utilizing stringent analysis thresholds. We identified a total of 3,447 editing sites that overlapped in three human lung samples, and with 50% of these sites having canonical A-to-G base changes. Approximately 27% of the edited sites overlapped with Alu repeats, and showed A-to-G clustering (>3 clusters in 100 bp). The majority of edited sites mapped to either 3′ untranslated regions (UTRs) or introns close to splice sites; whereas, only few sites were in exons resulting in non-synonymous amino acid changes. Interestingly, we identified 652 A-to-G editing events in the 3′ UTR of 205 target genes that mapped to 932 potential miRNA target binding sites. Several of these miRNA edited sites were validated in silico. Additionally, we validated several A-to-G edited sites by Sanger sequencing. Altogether, our study suggests a role for RNA editing in miRNA-mediated gene regulation and splicing in human lungs. In this study, we have generated a RNA editome of human lung tissue that can be compared with other RNA editomes across different lung tissues to delineate a role for RNA editing in normal and diseased states.

Optimal treatment and stochastic modeling of heterogeneous tumors

In this work we review past articles that have mathematically studied cancer heterogeneity and the impact of this heterogeneity on the structure of optimal therapy. We look at past works on modeling how heterogeneous tumors respond to radiotherapy, and take a particularly close look at how the optimal radiotherapy schedule is modified by the presence of heterogeneity. In addition, we review past works on the study of optimal chemotherapy when dealing with heterogeneous tumors.

REVIEWERS

This article was reviewed by Thomas McDonald, David Axelrod, and Leonid Hanin.

Comprehensive comparison of molecular portraits between cell lines and tumors in breast cancer

Background

Proper cell models for breast cancer primary tumors have long been the focal point in the cancer’s research. The genomic comparison between cell lines and tumors can investigate the similarity and dissimilarity and help to select right cell model to mimic tumor tissues to properly evaluate the drug reaction in vitro. In this paper, a comprehensive comparison in copy number variation (CNV), mutation, mRNA expression and protein expression between 68 breast cancer cell lines and 1375 primary breast tumors is conducted and presented.

Results

Using whole genome expression arrays, strong correlations were observed between cells and tumors. PAM50 gene expression differentiated them into four major breast cancer subtypes: Luminal A and B, HER2amp, and Basal-like in both cells and tumors partially. Genomic CNVs patterns were observed between tumors and cells across chromosomes in general. High C > T and C > G trans-version rates were observed in both cells and tumors, while the cells had slightly higher somatic mutation rates than tumors. Clustering analysis on protein expression data can reasonably recover the breast cancer subtypes in cell lines and tumors. Although the drug-targeted proteins ER/PR and interesting mTOR/GSK3/TS2/PDK1/ER_P118 cluster had shown the consistent patterns between cells and tumor, low protein-based correlations were observed between cells and tumors. The expression consistency of mRNA verse protein between cell line and tumors reaches 0.7076. These important drug targets in breast cancer, ESR1, PGR, HER2, EGFR and AR have a high similarity in mRNA and protein variation in both tumors and cell lines. GATA3 and RP56KB1 are two promising drug targets for breast cancer. A total score developed from the four correlations among four molecular profiles suggests that cell lines, BT483, T47D and MDAMB453 have the highest similarity with tumors.

Conclusions

The integrated data from across these multiple platforms demonstrates the existence of the similarity and dissimilarity of molecular features between breast cancer tumors and cell lines. The cell lines only mirror some but not all of the molecular properties of primary tumors. The study results add more evidence in selecting cell line models for breast cancer research.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2911-z) contains supplementary material, which is available to authorized users.

The Role of Genomic Profiling in Advanced Breast Cancer: The Two Faces of Janus

Recent advances in genomic technology have led to considerable improvement in our understanding of the molecular basis that underpins breast cancer biology. Through the use of comprehensive whole genome genomic profiling by next-generation sequencing, an unprecedented bulk of data on driver mutations, key genomic rearrangements, and mechanisms on tumor evolution has been generated. These developments have marked the beginning of a new era in oncology called “personalized or precision medicine.” Elucidation of biologic mechanisms that underpin carcinogenetic potential and metastatic behavior has led to an inevitable explosion in the development of effective targeted agents, many of which have gained approval over the past decade. Despite energetic efforts and the enormous support gained within the oncology community, there are many obstacles in the clinical implementation of precision medicine. Other than the well-known biologic markers, such as ER and Her-2/neu, no proven predictive marker exists to determine the responsiveness to a certain biologic agent. One of the major issues in this regard is teasing driver mutations among the background noise within the bulk of coexisting passenger mutations. Improving bioinformatics tools through electronic models, enhanced by improved insight into pathway dependency may be the step forward to overcome this problem. Next, is the puzzle on spatial and temporal tumoral heterogeneity, which remains to be solved by ultra-deep sequencing and optimizing liquid biopsy techniques. Finally, there are multiple logistical and financial issues that have to be meticulously tackled in order to optimize the use of “precision medicine” in the real-life setting.

ADAR1 Activation Drives Leukemia Stem Cell Self-Renewal by Impairing Let-7 Biogenesis

Post-transcriptional adenosine-to-inosine RNA editing mediated by adenosine deaminase acting on RNA1 (ADAR1) promotes cancer progression and therapeutic resistance. However, ADAR1 editase-dependent mechanisms governing leukemia stem cell (LSC) generation have not been elucidated. In blast crisis chronic myeloid leukemia (BC CML), we show that increased JAK2 signaling and BCR-ABL1 amplification activate ADAR1. In a humanized BC CML mouse model, combined JAK2 and BCR-ABL1 inhibition prevents LSC self-renewal commensurate with ADAR1 downregulation. Lentiviral ADAR1 wild-type, but not an editing-defective ADAR1(E912A) mutant, induces self-renewal gene expression and impairs biogenesis of stem cell regulatory let-7 microRNAs. Combined RNA sequencing, qRT-PCR, CLIP-ADAR1, and pri-let-7 mutagenesis data suggest that ADAR1 promotes LSC generation via let-7 pri-microRNA editing and LIN28B upregulation. A small-molecule tool compound antagonizes ADAR1's effect on LSC self-renewal in stromal co-cultures and restores let-7 biogenesis. Thus, ADAR1 activation represents a unique therapeutic vulnerability in LSCs with active JAK2 signaling.

Direct Transcriptional Consequences of Somatic Mutation in Breast Cancer

Disordered transcriptomes of cancer encompass direct effects of somatic mutation on transcription, coordinated secondary pathway alterations, and increased transcriptional noise. To catalog the rules governing how somatic mutation exerts direct transcriptional effects, we developed an exhaustive pipeline for analyzing RNA sequencing data, which we integrated with whole genomes from 23 breast cancers. Using X-inactivation analyses, we found that cancer cells are more transcriptionally active than intermixed stromal cells. This is especially true in estrogen receptor (ER)-negative tumors. Overall, 59% of substitutions were expressed. Nonsense mutations showed lower expression levels than expected, with patterns characteristic of nonsense-mediated decay. 14% of 4,234 rearrangements caused transcriptional abnormalities, including exon skips, exon reusage, fusions, and premature polyadenylation. We found productive, stable transcription from sense-to-antisense gene fusions and gene-to-intergenic rearrangements, suggesting that these mutation classes drive more transcriptional disruption than previously suspected. Systematic integration of transcriptome with genome data reveals the rules by which transcriptional machinery interprets somatic mutation.

•

Greater transcriptional activity in cancer than stromal cells, particularly when ER-ve

•

Intron mutations only infrequently affect splicing, even at essential splice sites

•

Distinctive RNA effects of sense-to-antisense and gene-to-intergenic rearrangements

•

Exhaustive pipeline for identifying aberrant transcripts from RNA-sequencing data

SNVSniffer: an integrated caller for germline and somatic single-nucleotide and indel mutations

BACKGROUND

Various approaches to calling single-nucleotide variants (SNVs) or insertion-or-deletion (indel) mutations have been developed based on next-generation sequencing (NGS). However, most of them are dedicated to a particular type of mutation, e.g. germline SNVs in normal cells, somatic SNVs in cancer/tumor cells, or indels only. In the literature, efficient and integrated callers for both germline and somatic SNVs/indels have not yet been extensively investigated.

RESULTS

We present SNVSniffer, an efficient and integrated caller identifying both germline and somatic SNVs/indels from NGS data. In this algorithm, we propose the use of Bayesian probabilistic models to identify SNVs and investigate a multiple ungapped alignment approach to call indels. For germline variant calling, we model allele counts per site to follow a multinomial conditional distribution. For somatic variant calling, we rely on paired tumor-normal pairs from identical individuals and introduce a hybrid subtraction and joint sample analysis approach by modeling tumor-normal allele counts per site to follow a joint multinomial conditional distribution. A comprehensive performance evaluation has been conducted using a diversity of variant calling benchmarks. For germline variant calling, SNVSniffer demonstrates highly competitive accuracy with superior speed in comparison with the state-of-the-art FaSD, GATK and SAMtools. For somatic variant calling, our algorithm achieves comparable or even better accuracy, at fast speed, than the leading VarScan2, SomaticSniper, JointSNVMix2 and MuTect.

CONCLUSIONS

SNVSniffers demonstrates the feasibility to develop integrated solutions to fast and efficient identification of germline and somatic variants. Nonetheless, accurate discovery of genetic variations is critical yet challenging, and still requires substantially more research efforts being devoted. SNVSniffer and synthetic samples are publicly available at http://snvsniffer.sourceforge.net .

Intra-patient Inter-metastatic Genetic Heterogeneity in Colorectal Cancer as a Key Determinant of Survival after Curative Liver Resection

Chromosomal instability is a well-defined hallmark of tumor aggressiveness and metastatic progression in colorectal cancer. The magnitude of genetic heterogeneity among distinct liver metastases from the same patient at the copy number level, as well as its relationship with chemotherapy exposure and patient outcome, remains unknown. We performed high-resolution DNA copy number analyses of 134 liver metastatic deposits from 45 colorectal cancer patients to assess: (i) intra-patient inter-metastatic genetic heterogeneity using a heterogeneity score based on pair-wise genetic distances among tumor deposits; and (ii) genomic complexity, defined as the proportion of the genome harboring aberrant DNA copy numbers. Results were analyzed in relation to the patients' clinical course; previous chemotherapy exposure and outcome after surgical resection of liver metastases. We observed substantial variation in the level of intra-patient inter-metastatic heterogeneity. Heterogeneity was not associated with the number of metastatic lesions or their genomic complexity. In metachronous disease, heterogeneity was higher in patients previously exposed to chemotherapy. Importantly, intra-patient inter-metastatic heterogeneity was a strong prognostic determinant, stronger than known clinicopathological prognostic parameters. Patients with a low level of heterogeneity (below the median level) had a three-year progression-free and overall survival rate of 23% and 66% respectively, versus 5% and 18% for patients with a high level (hazard ratio0.4, 95% confidence interval 0.2-0.8, P = 0.01; and hazard ratio0.3,95% confidence interval 0.1-0.7, P = 0.007). A low patient-wise level of genomic complexity (below 25%) was also a favorable prognostic factor; however, the prognostic association of intra-patient heterogeneity was independent of genomic complexity in multivariable analyses. In conclusion, intra-patient inter-metastatic genetic heterogeneity is a pronounced feature of metastatic colorectal cancer, and the strong prognostic association reinforces its clinical relevance and places it as a key feature to be explored in future patient cohorts.

Tumour heterogeneity: principles and practical consequences

Two major reasons compel us to study tumour heterogeneity: firstly, it represents the basis of acquired therapy resistance, and secondly, it may be one of the major sources of the low level of reproducibility in clinical cancer research. The present review focuses on the heterogeneity of neoplastic disease, both within the primary tumour and between primary tumour and metastases. We discuss different levels of heterogeneity and the current understanding of the phenomenon, as well as imminent developments relevant for clinical research and diagnostic pathology. It is necessary to develop new tools to study heterogeneity and new biomarkers for heterogeneity. Established and new in situ methods will be very useful. In future studies, not only clonal heterogeneity needs to be addressed but also non-clonal phenotypic heterogeneity which might be important for therapy resistance. We also review heterogeneity established in major tumour types, in order to explore potential similarities that might help to define new strategies for targeted therapy.

Mutations in the Kinase Domain of the HER2/ERBB2 Gene Identified in a Wide Variety of Human Cancers

The HER2 (official name ERBB2) gene encodes a membrane receptor in the epidermal growth factor receptor family amplified and overexpressed in adenocarcinoma. Activating mutations also occur in several cancers. We report mutation analyses of the HER2 kinase domain in 7497 histologically diverse cancers. Forty-five genes, including the kinase domain of HER2 with HER2 IHC and dual in situ hybridization, were analyzed in tumors from 7497 patients with cancer, including 850 breast, 770 colorectal, 910 non-small cell lung, 823 uterine or cervical, 1372 ovarian, and 297 pancreatic cancers, as well as 323 melanomas and 2152 other solid tumors. Sixty-nine HER2 kinase domain mutations were identified in tumors from 68 patients (approximately 1% of all cases, ranging from absent in sarcomas to 4% in urothelial cancers), which included previously published activating mutations and 13 novel mutations. Fourteen cases with coexisting HER2 mutation and amplification and/or overexpression were identified. Fifty-two of 68 patients had additional mutations in other analyzed genes, whereas 16 patients (23%) had HER2 mutations identified as the sole driver mutation. HER2 mutations coexisted with HER2 gene amplification and overexpression and with mutations in other functionally important genes. HER2 mutations were identified as the only driver mutation in a significant proportion of solid cancers. Evaluation of anti-HER2 therapies in nonamplified, HER2-mutated cancers is warranted.

New generation of breast cancer clinical trials implementing molecular profiling

The implementation of molecular profiling technologies in oncology deepens our knowledge for the molecular landscapes of cancer diagnoses, identifying aberrations that could be linked with specific therapeutic vulnerabilities. In particular, there is an increasing list of molecularly targeted anticancer agents undergoing clinical development that aim to block specific molecular aberrations. This leads to a paradigm shift, with an increasing list of specific aberrations dictating the treatment of patients with cancer. This paradigm shift impacts the field of clinical trials, since the classical approach of having clinico-pathological disease characteristics dictating the patients' enrolment in oncology trials shifts towards the implementation of molecular profiling as pre-screening step. In order to facilitate the successful clinical development of these new anticancer drugs within specific molecular niches of cancer diagnoses, there have been developed new, innovative trial designs that could be classified as follows: i) longitudinal cohort studies that implement (or not) "nested" downstream trials, 2) studies that assess the clinical utility of molecular profiling, 3) "master" protocol trials, iv) "basket" trials, v) trials following an adaptive design. In the present article, we review these innovative study designs, providing representative examples from each category and we discuss the challenges that still need to be addressed in this era of new generation oncology trials implementing molecular profiling. Emphasis is put on the field of breast cancer clinical trials.

Analysis of Paired Primary-Metastatic Hormone-Receptor Positive Breast Tumors (HRPBC) Uncovers Potential Novel Drivers of Hormonal Resistance

We sought to identify genetic variants associated with disease relapse and failure to hormonal treatment in hormone-receptor positive breast cancer (HRPBC). We analyzed a series of HRPBC with distant relapse, by sequencing pairs (n = 11) of tumors (primary and metastases) at >800X. Comparative genomic hybridization was performed as well. Top hits, based on the frequency of alteration and severity of the changes, were tested in the TCGA series. Genes determining the most parsimonious prognostic signature were studied for their functional role in vitro, by performing cell growth assays in hormonal-deprivation conditions, a setting that mimics treatment with aromatase inhibitors. Severe alterations were recurrently found in 18 genes in the pairs. However, only MYC, DNAH5, CSFR1, EPHA7, ARID1B, and KMT2C preserved an independent prognosis impact and/or showed a significantly different incidence of alterations between relapsed and non-relapsed cases in the TCGA series. The signature composed of MYC, KMT2C, and EPHA7 best discriminated the clinical course, (overall survival 90,7 vs. 144,5 months; p = 0.0001). Having an alteration in any of the genes of the signature implied a hazard ratio of death of 3.25 (p<0.0001), and early relapse during the adjuvant hormonal treatment. The presence of the D348N mutation in KMT2C and/or the T666I mutation in the kinase domain of EPHA7 conferred hormonal resistance in vitro. Novel inactivating mutations in KMT2C and EPHA7, which confer hormonal resistance, are linked to adverse clinical course in HRPBC.

The Role of PIWIL4, an Argonaute Family Protein, in Breast Cancer

P-element-induced wimpy testis (PIWI) proteins bind to PIWI-interacting RNAs and play key roles in the biogenesis and functions of PIWI-interacting RNAs. It has been reported that PIWI proteins are essential for stem cell self-renewal and germline development in diverse organisms and that they are ectopically expressed in multiple forms of cancer. However, the role of PIWI in cancer remains elusive. Here we report that one of the four PIWI proteins in humans, PIWIL4, is highly expressed in both breast cancer tissues and the cytoplasm of MDA-MB-231 cells derived from breast cancer. Reducing PIWIL4 expression drastically impairs the migration ability of MDA-MB-231 cells, significantly increases their apoptosis, and mildly affects their proliferation. Our transcriptome and proteome analysis reveal that these functions are at least partially achieved via the PIWIL4 regulation of TGF-β and FGF signaling pathways and MHC class II proteins. These findings suggest that PIWIL4 may serve as a potential therapeutic target for breast cancer.

Serial monitoring of circulating tumor DNA in patients with primary breast cancer for detection of occult metastatic disease

Metastatic breast cancer is usually diagnosed after becoming symptomatic, at which point it is rarely curable. Cell-free circulating tumor DNA (ctDNA) contains tumor-specific chromosomal rearrangements that may be interrogated in blood plasma. We evaluated serial monitoring of ctDNA for earlier detection of metastasis in a retrospective study of 20 patients diagnosed with primary breast cancer and long follow-up. Using an approach combining low-coverage whole-genome sequencing of primary tumors and quantification of tumor-specific rearrangements in plasma by droplet digital PCR, we identify for the first time that ctDNA monitoring is highly accurate for postsurgical discrimination between patients with (93%) and without (100%) eventual clinically detected recurrence. ctDNA-based detection preceded clinical detection of metastasis in 86% of patients with an average lead time of 11 months (range 0–37 months), whereas patients with long-term disease-free survival had undetectable ctDNA postoperatively. ctDNA quantity was predictive of poor survival. These findings establish the rationale for larger validation studies in early breast cancer to evaluate ctDNA as a monitoring tool for early metastasis detection, therapy modification, and to aid in avoidance of overtreatment.