Explore the vast range of titles available.

Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA ‘microsatellite instability/CpG island methylation phenotype’ transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis - and trans -effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology. Proteome analysis of The Cancer Genome Atlas (TCGA) colorectal cancer specimens reveals that DNA- or RNA-level measurements cannot reliably predict protein abundance, colorectal tumours can be separated into distinct proteotypes, and that copy number alterations drive mRNA abundance changes but few extend to protein-level changes. Proteomics/genomics of colorectal tumours A team from the Clinical Proteomics Tumor Analysis Consortium has now analysed the proteomes of 95 colon and rectal tumours previously characterized by the Cancer Genome Atlas project. Integration of the proteomics with the original genomic data demonstrates that protein abundance cannot be reliably predicted from DNA- or RNA-level measurements, and that mRNA and protein levels are modestly correlated. Proteomics identified five colorectal cancer subtypes that reflect known biological characteristics, yet capture differences that are not evident at the transcriptome level. Integrated proteogenomic analysis of this type can provide functional context to interpret genomic abnormalities in terms of cancer biology.

> Circulating tumour DNA (ctDNA) in blood plasma is an emerging tool for clinical cancer genotyping and longitudinal disease monitoring 1 . However, owing to past emphasis on targeted and low-resolution profiling approaches, our understanding of the distinct populations that comprise bulk ctDNA is incomplete 2 – 12 . Here we perform deep whole-genome sequencing of serial plasma and synchronous metastases in patients with aggressive prostate cancer. We comprehensively assess all classes of genomic alterations and show that ctDNA contains multiple dominant populations, the evolutionary histories of which frequently indicate whole-genome doubling and shifts in mutational processes. Although tissue and ctDNA showed concordant clonally expanded cancer driver alterations, most individual metastases contributed only a minor share of total ctDNA. By comparing serial ctDNA before and after clinical progression on potent inhibitors of the androgen receptor (AR) pathway, we reveal population restructuring converging solely on AR augmentation as the dominant genomic driver of acquired treatment resistance. Finally, we leverage nucleosome footprints in ctDNA to infer mRNA expression in synchronously biopsied metastases, including treatment-induced changes in AR transcription factor signalling activity. Our results provide insights into cancer biology and show that liquid biopsy can be used as a tool for comprehensive multi-omic discovery. Deep whole-genome sequencing of serial blood samples and matched metastatic tissue reveals that circulating tumour DNA profiling enables detailed study of treatment-driven subclone dynamics, epigenomics and genome-wide somatic evolution in metastatic human cancers.

In this Opinion article, Baslan and Hicks discuss how single-cell sequencing could be used to advance our understanding of tumour biology and genetics, in addition to translational applications in the clinic. The fundamental operative unit of a cancer is the genetically and epigenetically innovative single cell. Whether proliferating or quiescent, in the primary tumour mass or disseminated elsewhere, single cells govern the parameters that dictate all facets of the biology of cancer. Thus, single-cell analyses provide the ultimate level of resolution in our quest for a fundamental understanding of this disease. Historically, this quest has been hampered by technological shortcomings. In this Opinion article, we argue that the rapidly evolving field of single-cell sequencing has unshackled the cancer research community of these shortcomings. From furthering an elemental understanding of intra-tumoural genetic heterogeneity and cancer genome evolution to illuminating the governing principles of disease relapse and metastasis, we posit that single-cell sequencing promises to unravel the biology of all facets of this disease.

By integrating the expression profiles of long noncoding RNAs (lncRNAs) with clinical outcome and somatic copy-number alteration, the authors identified new lncRNAs that are associated with certain cancer subtypes and clinical prognoses. Experimental validation of the prostate cancer cell growth dependence of two new lncRNAs demonstrates the power of this approach for discovering disease-related lncRNAs. Despite growing appreciation of the importance of long noncoding RNAs (lncRNAs) in normal physiology and disease, our knowledge of cancer-related lncRNAs remains limited. By repurposing microarray probes, we constructed expression profiles of 10,207 lncRNA genes in approximately 1,300 tumors over four different cancer types. Through integrative analysis of the lncRNA expression profiles with clinical outcome and somatic copy-number alterations, we identified lncRNAs that are associated with cancer subtypes and clinical prognosis and predicted those that are potential drivers of cancer progression. We validated our predictions by experimentally confirming prostate cancer cell growth dependence on two newly identified lncRNAs. Our analysis provides a resource of clinically relevant lncRNAs for the development of lncRNA biomarkers and the identification of lncRNA therapeutic targets. It also demonstrates the power of integrating publically available genomic data sets and clinical information for discovering disease-associated lncRNAs.

ObjectiveAlthough counting of circulating tumour cells (CTC) has attracted a broad interest as potential markers of tumour progression and treatment response, the lack of functional characterisation of these cells had become a bottleneck in taking these observations to the clinic. Our objective was to culture these cells in order to understand them and exploit their therapeutic potential to the full.DesignHere, hypothesising that some CTC potentially have cancer stem cell (CSC) phenotype, we generated several CTC lines from the blood of patients with advanced metastatic colorectal cancer (CRC) based on their self-renewal abilities. Multiple standard tests were then employed to characterise these cells.ResultsOur CTC lines self-renew, express CSC markers and have multilineage differentiation ability, both in vitro and in vivo. Patient-derived CTC lines are tumorigenic in subcutaneous xenografts and are also able to colonise the liver after intrasplenic injection. RNA sequencing analyses strikingly demonstrate that drug metabolising pathways represent the most upregulated feature among CTC lines in comparison with primary CRC cells grown under similar conditions. This result is corroborated by the high resistance of the CTC lines to conventional cytotoxic compounds.ConclusionsTaken together, our results directly demonstrate the existence of patient-derived colorectal CTCs that bear all the functional attributes of CSCs. The CTC culture model described here is simple and takes <1 month from blood collection to drug testing, therefore, routine clinical application could facilitate access to personalised medicine.Clinical Trial RegistrationClinicalTrial.gov NCT01577511.

Enzalutamide and abiraterone target the androgen receptor and androgen synthesis and are used to treat castration-resistant prostate cancer. A splice variant of the androgen receptor is associated with resistance to both drugs. It is now accepted that castration-resistant prostate cancer is not androgen-independent and continues to rely on androgen signaling. 1 Owing to this new understanding, several drugs have recently emerged for the treatment of castration-resistant prostate cancer; these agents either suppress the synthesis of extragonadal androgens or target the androgen receptor directly. 2 Enzalutamide is an inhibitor of androgen-receptor signaling that exerts its activity by binding avidly to the ligand-binding domain of the androgen receptor, competing with and displacing the natural ligands of this receptor (testosterone and dihydrotestosterone) while also inhibiting translocation of the androgen receptor into the nucleus and impairing transcriptional activation . . .

Objective Campylobacter jejuni produces a genotoxin, cytolethal distending toxin (CDT), which has DNAse activity and causes DNA double-strand breaks. Although C. jejuni infection has been shown to promote intestinal inflammation, the impact of this bacterium on carcinogenesis has never been examined.DesignGerm-free (GF) ApcMin/+ mice, fed with 1% dextran sulfate sodium, were used to test tumorigenesis potential of CDT-producing C. jejuni. Cells and enteroids were exposed to bacterial lysates to determine DNA damage capacity via γH2AX immunofluorescence, comet assay and cell cycle assay. To examine the interplay of CDT-producing C. jejuni, gut microbiome and host in tumorigenesis, colonic RNA-sequencing and faecal 16S rDNA sequencing were performed. Rapamycin was administrated to investigate the prevention of CDT-producing C. jejuni-induced tumorigenesis.ResultsGF ApcMin/+ mice colonised with human clinical isolate C. jejuni81–176 developed significantly more and larger tumours when compared with uninfected mice. C. jejuni with a mutated cdtB subunit, mutcdtB, attenuated C. jejuni-induced tumorigenesis in vivo and decreased DNA damage response in cells and enteroids. C. jejuni infection induced expression of hundreds of colonic genes, with 22 genes dependent on the presence of cdtB. The C. jejuni-infected group had a significantly different microbial gene expression profile compared with the mutcdtB group as shown by metatranscriptomic data, and different microbial communities as measured by 16S rDNA sequencing. Finally, rapamycin could diminish the tumorigenic capability of C. jejuni.ConclusionHuman clinical isolate C. jejuni 81–176 promotes colorectal cancer and induces changes in microbial composition and transcriptomic responses, a process dependent on CDT production.

Neoantigens have attracted attention as biomarkers or therapeutic targets. However, accurate prediction of neoantigens is still challenging, especially in terms of its accuracy and cost. Variant detection using RNA sequencing (RNA‐seq) data has been reported to be a low‐accuracy but cost‐effective tool, but the feasibility of RNA‐seq data for neoantigen prediction has not been fully examined. In the present study, we used whole‐exome sequencing (WES) and RNA‐seq data of tumor and matched normal samples from six breast cancer patients to evaluate the utility of RNA‐seq data instead of WES data in variant calling to detect neoantigen candidates. Somatic variants were called in three protocols using: (i) tumor and normal WES data (DNA method, Dm); (ii) tumor and normal RNA‐seq data (RNA method, Rm); and (iii) combination of tumor RNA‐seq and normal WES data (Combination method, Cm). We found that the Rm had both high false‐positive and high false‐negative rates because this method depended greatly on the expression status of normal transcripts. When we compared the results of Dm with those of Cm, only 14% of the neoantigen candidates detected in Dm were identified in Cm, but the majority of the missed candidates lacked coverage or variant allele reads in the tumor RNA. In contrast, about 70% of the neoepitope candidates with higher expression and rich mutant transcripts could be detected in Cm. Our results showed that Cm could be an efficient and a cost‐effective approach to predict highly expressed neoantigens in tumor samples. We evaluated the utility of RNA‐seq data instead of WES data in variant calling to detect neoantigen candidates. We found that the method combining tumor RNA‐seq data and normal WES data (Combination method) could detect neoantigen candidates that have higher expression and rich variant transcripts, and this method may be an efficient and cost‐effective strategy alternative to the conventional method (DNA method).

The molecular basis of the resistance of anaplastic lymphoma kinase (ALK)–driven lung cancer to the ALK inhibitor, crizotinib, was identified in a patient whose tumor initially responded to crizotinib treatment and then, after 5 months, progressed despite continued treatment. EML4-ALK is a fusion-type protein tyrosine kinase that is present in 4 to 5% of cases of non–small-cell lung cancer and is generated as a result of a small inversion within the short arm of human chromosome 2. 1 – 3 EML4-ALK undergoes constitutive dimerization through interaction between the coiled-coil domain within the EML4 region of each monomer, thereby activating ALK and generating oncogenic activity. In transgenic mice that express EML4-ALK specifically in lung epithelial cells, hundreds of adenocarcinoma nodules develop in both lungs soon after birth, and oral administration of a specific inhibitor of ALK tyrosine kinase activity rapidly eradicates such . . .

Extracellular vesicles (EVs) play key roles in glioblastoma (GBM; astrocytoma grade IV) biology and are novel sources of biomarkers. EVs released from GBM tumors can cross the blood-brain-barrier into the periphery carrying GBM molecules, including small non-coding RNA (sncRNA). Biomarkers cargoed in circulating EVs have shown great promise for assessing the molecular state of brain tumors in situ. Neurosurgical aspirate fluids captured during tumor resections are a rich source of GBM-EVs isolated directly from tumor microenvironments. Using density gradient ultracentrifugation, EVs were purified from cavitron ultrasonic surgical aspirate (CUSA) washings from GBM (n = 12) and astrocytoma II-III (GII-III, n = 5) surgeries. The sncRNA contents of surgically captured EVs were profiled using the Illumina® NextSeqTM 500 NGS System. Differential expression analysis identified 27 miRNA and 10 piRNA species in GBM relative to GII-III CUSA-EVs. Resolved CUSA-EV sncRNAs could discriminate serum-EV sncRNA profiles from GBM and GII-III patients and healthy controls and 14 miRNAs (including miR-486-3p and miR-106b-3p) and cancer-associated piRNAs (piR_016658, _016659, _020829 and _204090) were also significantly expressed in serum-EVs. Circulating EV markers that correlate with histological, neuroradiographic and clinical parameters will provide objective measures of tumor activity and improve the accuracy of GBM tumor surveillance.