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Circulating tumour DNA (ctDNA) detection and monitoring have enormous potential clinical utility in oncology. We describe here a fast, flexible and cost-effective method to profile multiple genes simultaneously in low input cell-free DNA (cfDNA): Next Generation-Targeted Amplicon Sequencing (NG-TAS). We designed a panel of 377 amplicons spanning 20 cancer genes and tested the NG-TAS pipeline using cell-free DNA from two HapMap lymphoblastoid cell lines. NG-TAS consistently detected mutations in cfDNA when mutation allele fraction was > 1%. We applied NG-TAS to a clinical cohort of metastatic breast cancer patients, demonstrating its potential in monitoring the disease. The computational pipeline is available at https://github.com/cclab-brca/NGTAS_pipeline .

Background: Interactions between cancer cells and the surrounding microenvironment are crucial determinants of cancer progression. During this process, bi-directional communication among tumor cells and cancer associated fibroblasts (CAF) regulate extracellular matrix (ECM) deposition and remodeling. As a result of this dynamic process, soluble ECM proteins can be released into the bloodstream and may represent novel circulating biomarkers useful for cancer diagnosis. The aim of the present study was to measure the levels of three circulating ECM related proteins (COL11A1, COL10A1 and SPARC) in plasma samples of lung cancer patients and in healthy heavy-smokers controls and test whether such measurements have diagnostic or prognostic value., Methods: Gene expression profiling of lung fibroblasts isolated from paired normal and cancer tissue of NSCLC patients was performed by gene expression microarrays. The prioritization of the candidates for the study of circulating proteins in plasma was based on the most differentially expressed genes in cancer associated fibroblasts. Soluble ECM proteins were assessed by western blot in the conditioned medium of lung fibroblasts and by ELISA assays in plasma samples., Results: Plasma samples from lung cancer patients and healthy heavy-smokers controls were tested for levels of COL11A1 and COL10A1 (n = 57 each) and SPARC (n = 90 each). Higher plasma levels of COL10A1 were detected in patients (p ≤ 0.001), a difference that was driven specifically by females (p < 0.001). No difference in COL11A1 levels between patients and controls was found. SPARC levels were also higher in plasma patients than controls (p < 0.001) with good performance in discriminating the two groups (AUC = 0.744). No significant association was observed between plasma proteins levels and clinicopathological features or survival., Conclusion: Soluble factors related to proficient tumor-stroma cross-talk are detectable in plasma of primary lung cancer patients and may represent a valuable complementary diagnostic tool to discriminate lung cancer patients from healthy heavy-smokers individuals as shown for the SPARC protein.

Background: Patient-Derived Tumour Xenografts (PDTXs) have emerged as the pre-clinical models that best represent clinical tumour diversity and intra-tumour heterogeneity. The molecular characterization of PDTXs using High-Throughput Sequencing (HTS) is essential; however, the presence of mouse stroma is challenging for HTS data analysis. Indeed, the high homology between the two genomes results in a proportion of mouse reads being mapped as human., Results: In this study we generated Whole Exome Sequencing (WES), Reduced Representation Bisulfite Sequencing (RRBS) and RNA sequencing (RNA-seq) data from samples with known mixtures of mouse and human DNA or RNA and from a cohort of human breast cancers and their derived PDTXs. We show that using an In silico Combined human-mouse Reference Genome (ICRG) for alignment discriminates between human and mouse reads with up to 99.9% accuracy and decreases the number of false positive somatic mutations caused by misalignment by >99.9%. We also derived a model to estimate the human DNA content in independent PDTX samples. For RNA-seq and RRBS data analysis, the use of the ICRG allows dissecting computationally the transcriptome and methylome of human tumour cells and mouse stroma. In a direct comparison with previously reported approaches, our method showed similar or higher accuracy while requiring significantly less computing time., Conclusions: The computational pipeline we describe here is a valuable tool for the molecular analysis of PDTXs as well as any other mixture of DNA or RNA species.

Bioinformatic analysis of genomic sequencing data to identify somatic mutations in cancer samples is far from achieving the required robustness and standardisation. In this study we generated a whole exome sequencing benchmark dataset using the platinum genome sample NA12878 and developed an intersect-then-combine (ITC) approach to increase the accuracy in calling single nucleotide variants (SNVs) and indels in tumour-normal pairs. We evaluated the effect of alignment, base quality recalibration, mutation caller and filtering on sensitivity and false positive rate. The ITC approach increased the sensitivity up to 17.1%, without increasing the false positive rate per megabase (FPR/Mb) and its validity was confirmed in a set of clinical samples.

Background: Plasma miRNAs have the potential as cancer biomarkers but no consolidated guidelines for data mining in this field are available. The purpose of the study was to apply a supervised data analysis strategy in a context where prior knowledge is available, i.e., that of hemolysis-related miRNAs deregulation, so as to compare our results with existing evidence., Results: We developed a structured strategy with innovative applications of existing bioinformatics methods for supervised analyses including: 1) the combination of two statistical (t- and Anderson-Darling) test results to detect miRNAs with significant fold change or general distributional differences in class comparison, which could reveal hidden differential biological processes worth to be considered for building predictive tools; 2) a bootstrap selection procedure together with machine learning techniques in class prediction to guarantee the transferability of results and explore the interconnections among the selected miRNAs, which is important for highlighting their inherent biological dependences. The strategy was applied to develop a classifier for discriminating between hemolyzed and not hemolyzed plasma samples, defined according to a recently published hemolysis score. We identified five miRNAs with increased expression in hemolyzed plasma samples (miR-486-5p, miR-92a, miR-451, miR-16, miR-22)., Conclusions: We identified four miRNAs previously reported in the literature as hemolysis related together with a new one (miR-22).which needs further investigations. Our findings confirm the validity of the proposed strategy and, in parallel, the hemolysis score capability to be used as pre-analytic hemolysis detector. R codes for implementing the approaches are provided.

Background: Cellular plasticity confers cancer cells the ability to adapt to microenvironmental changes, a fundamental requirement for tumour progression and metastasis. The epithelial to mesenchymal transition (EMT) is a transcriptional programme associated with increased cell motility and stemness. Besides EMT, the mesenchymal to amoeboid transition (MAT) has been described during tumour progression but to date, little is known about its transcriptional control and involvement in stemness. The aim of this manuscript is to investigate (i) the transcriptional profile associated with the MAT programme and (ii) to study whether MAT acquisition in melanoma cancer cells correlates with clonogenic potential to promote tumour growth., Results: By using a multidisciplinary approach, we identified four different treatments able to induce MAT in melanoma cells: EphA2 overexpression, Rac1 functional inhibition using its RacN17 dominant negative mutant, stimulation with Ilomastat or treatment with the RhoA activator Calpeptin. First, gene expression profiling identified the transcriptional pathways associated with MAT, independently of the stimulus that induces the MAT programme. Notably, gene sets associated with the repression of mesenchymal traits, decrease in the secretion of extracellular matrix components as well as increase of cellular stemness positively correlate with MAT. Second, the link between MAT and stemness has been investigated in vitro by analysing stemness markers and clonogenic potential of melanoma cells undergoing MAT. Finally, the link between MAT inducing treatments and tumour initiating capability has been validated in vivo., Conclusion: Taken together, our results demonstrate that MAT programme in melanoma is characterised by increased stemness and clonogenic features of cancer cells, thus sustaining tumour progression. Furthermore, these data suggest that stemness is not an exclusive feature of cells undergoing EMT, but more generally is associated with an increase in cellular plasticity of cancer cells.

Background: Aberrant expression of microRNAs, small non-coding RNA molecules that post-transcriptionally repress gene expression, seems to be causatively linked to the pathogenesis of cancer. In this context, miR-21 was found to be overexpressed in different human cancers (e.g. glioblastoma, breast cancer). In addition, it is thought to be endowed with oncogenic properties due to its ability to negatively modulate the expression of tumor-suppressor genes (e.g. PTEN) and to cause the reversion of malignant phenotype when knocked- down in several tumor models. On the basis of these findings, miR-21 has been proposed as a widely exploitable cancer-related target. However, scanty information is available concerning the relevance of miR-21 for prostate cancer. In the present study, we investigated the role of miR-21 and its potential as a therapeutic target in two prostate cancer cell lines, characterized by different miR-21 expression levels and PTEN gene status., Results: We provide evidence that miR-21 knockdown in prostate cancer cells is not sufficient per se i) to affect the proliferative and invasive potential or the chemo- and radiosensitivity profiles or ii) to modulate the expression of the tumor-suppressors PTEN and Pdcd4, which in other tumor types were found to be regulated by miR-21. We also show that miR-21 is not differently expressed in carcinomas and matched normal tissues obtained from 36 untreated prostate cancer patients subjected to radical prostatectomy., Conclusions: Overall, our data suggest that miR-21 is not a central player in the onset of prostate cancer and that its single hitting is not a valuable therapeutic strategy in the disease. This supports the notion that the oncogenic properties of miR-21 could be cell and tissue dependent and that the potential role of a given miRNA as a therapeutic target should be contextualized with respect to the disease.

Background: Gene expression profiling is moving from the research setting to the practical clinical use. Gene signatures able to correctly identify high risk breast cancer patients as well as to predict response to treatment are currently under intense investigation. While technical issues dealing with RNA preparation, choice of array platforms, statistical analytical tools are taken into account, the tissue collection process is seldom considered. The time elapsed between surgical tissue removal and freezing of samples for biological characterizations is rarely well defined and/or recorded even for recently stored samples, despite the publications of standard operating procedures for biological sample collection for tissue banks., Methods: Breast cancer samples from 11 patients were collected immediately after surgical removal and subdivided into aliquots. One was immediately frozen and the others were maintained at room temperature for respectively 2, 6 and 24 hrs. RNA was extracted and gene expression profile was determined using cDNA arrays. Phosphoprotein profiles were studied in parallel., Results: Delayed freezing affected the RNA quality only in 3 samples, which were not subjected to gene profiling. In the 8 breast cancer cases with apparently intact RNA also in sample aliquots frozen at delayed times, 461 genes were modulated simply as a function of freezing timing. Some of these genes were included in gene signatures biologically and clinically relevant for breast cancer. Delayed freezing also affected detection of phosphoproteins, whose pattern may be crucial for clinical decision on target-directed drugs., Conclusion: Time elapsed between surgery and freezing of samples appears to have a strong impact and should be considered as a mandatory variable to control for clinical implications of inadequate tissue handling.

Background: The cancer transcriptome is difficult to explore due to the heterogeneity of quantitative and qualitative changes in gene expression linked to the disease status. An increasing number of "unconventional" transcripts, such as novel isoforms, non-coding RNAs, somatic gene fusions and deletions have been associated with the tumoral state. Massively parallel sequencing techniques provide a framework for exploring the transcriptional complexity inherent to cancer with a limited laboratory and financial effort. We developed a deep sequencing and bioinformatics analysis protocol to investigate the molecular composition of a breast cancer poly(A)+ transcriptome. This method utilizes a cDNA library normalization step to diminish the representation of highly expressed transcripts and biology-oriented bioinformatic analyses to facilitate detection of rare and novel transcripts., Results: We analyzed over 132,000 Roche 454 high-confidence deep sequencing reads from a primary human lobular breast cancer tissue specimen, and detected a range of unusual transcriptional events that were subsequently validated by RT-PCR in additional eight primary human breast cancer samples. We identified and validated one deletion, two novel ncRNAs (one intergenic and one intragenic), ten previously unknown or rare transcript isoforms and a novel gene fusion specific to a single primary tissue sample. We also explored the non-protein-coding portion of the breast cancer transcriptome, identifying thousands of novel non-coding transcripts and more than three hundred reads corresponding to the non-coding RNA MALAT1, which is highly expressed in many human carcinomas., Conclusion: Our results demonstrate that combining 454 deep sequencing with a normalization step and careful bioinformatic analysis facilitates the discovery and quantification of rare transcripts or ncRNAs, and can be used as a qualitative tool to characterize transcriptome complexity, revealing many hitherto unknown transcripts, splice isoforms, gene fusion events and ncRNAs, even at a relatively low sequence sampling.

Background: Genetic experiments have clarified that p63 is a key transcription factor governing the establishment and maintenance of multilayered epithelia. Key to our understanding of p63 strategy is the identification of target genes. We perfomed an RNAi screening in keratinocytes for p63, followed by profiling analysis., Results: C/EBPdelta, member of a family with known roles in differentiation pathways, emerged as a gene repressed by p63. We validated C/EBPdelta as a primary target of DeltaNp63alpha by RT-PCR and ChIP location analysis in HaCaT and primary cells. C/EBPdelta is differentially expressed in stratification of human skin and it is up-regulated upon differentiation of HaCaT and primary keratinocytes. It is bound to and activates the DeltaNp63 promoter. Overexpression of C/EBPdelta leads to alteration in the normal profile of p63 isoforms, with the emergence of DeltaNp63beta and gamma, and of the TA isoforms, with different kinetics. In addition, there are changes in the expression of most p63 targets. Inactivation of C/EBPdelta leads to gene expression modifications, in part due to the concomitant repression of DeltaNp63alpha. Finally, C/EBPdelta is found on the p63 targets in vivo by ChIP analysis, indicating that coregulation is direct., Conclusion: Our data highlight a coherent cross-talk between these two transcription factors in keratinocytes and a large sharing of common transcriptional targets.