Type I IFNs promote cancer cell stemness by triggering the epigenetic regulator KDM1B.

Cancer stem cells (CSCs) are a subpopulation of cancer cells endowed with high tumorigenic, chemoresistant and metastatic potential. Nongenetic mechanisms of acquired resistance are increasingly being discovered, but molecular insights into the evolutionary process of CSCs are limited. Here, we show that type I interferons (IFNs-I) function as molecular hubs of resistance during immunogenic chemotherapy, triggering the epigenetic regulator demethylase 1B (KDM1B) to promote an adaptive, yet reversible, transcriptional rewiring of cancer cells towards stemness and immune escape. Accordingly, KDM1B inhibition prevents the appearance of IFN-I-induced CSCs, both in vitro and in vivo. Notably, IFN-I-induced CSCs are heterogeneous in terms of multidrug resistance, plasticity, invasiveness and immunogenicity. Moreover, in breast cancer (BC) patients receiving anthracycline-based chemotherapy, KDM1B positively correlated with CSC signatures. Our study identifies an IFN-I → KDM1B axis as a potent engine of cancer cell reprogramming, supporting KDM1B targeting as an attractive adjunctive to immunogenic drugs to prevent CSC expansion and increase the long-term benefit of therapy.

Clinical bioinformatics desiderata for molecular tumor boards.

Clinical Bioinformatics is a knowledge framework required to interpret data of medical interest via computational methods. This area became of dramatic importance in precision oncology, fueled by cancer genomic profiling: most definitions of Molecular Tumor Boards require the presence of bioinformaticians. However, all available literature remained rather vague on what are the specific needs in terms of digital tools and expertise to tackle and interpret genomics data to assign novel targeted or biomarker-driven targeted therapies to cancer patients. To fill this gap, in this article, we present a catalog of software families and human skills required for the tumor board bioinformatician, with specific examples of real-world applications associated with each element presented.

Comprehensive genomic profiling on metastatic Melanoma: results from a network screening from 7 Italian Cancer Centres.

BACKGROUND: The current therapeutic algorithm for Advanced Stage Melanoma comprises of alternating lines of Targeted and Immuno-therapy, mostly via Immune-Checkpoint blockade. While Comprehensive Genomic Profiling of solid tumours has been approved as a companion diagnostic, still no approved predictive biomarkers are available for Melanoma aside from BRAF mutations and the controversial Tumor Mutational Burden. This study presents the results of a Multi-Centre Observational Clinical Trial of Comprehensive Genomic Profiling on Target and Immuno-therapy treated advanced Melanoma. METHODS: 82 samples, collected from 7 Italian Cancer Centres of FFPE-archived Metastatic Melanoma and matched blood were sequenced via a custom-made 184-gene amplicon-based NGS panel. Sequencing and bioinformatics analysis was performed at a central hub. Primary analysis was carried out via the Ion Reporter framework. Secondary analysis and Machine Learning modelling comprising of uni and multivariate, COX/Lasso combination, and Random Forest, was implemented via custom R/Python scripting. RESULTS: The genomics landscape of the ACC-mela cohort is comparable at the somatic level for Single Nucleotide Variants and INDELs aside a few gene targets. All the clinically relevant targets such as BRAF and NRAS have a comparable distribution thus suggesting the value of larger scale sequencing in melanoma. No comparability is reached at the CNV level due to biotechnological biases and cohort numerosity. Tumour Mutational Burden is slightly higher in median for Complete Responders but fails to achieve statistical significance in Kaplan-Meier survival analysis via several thresholding strategies. Mutations on PDGFRB, NOTCH3 and RET were shown to have a positive effect on Immune-checkpoint treatment Overall and Disease-Free Survival, while variants in NOTCH4 were found to be detrimental for both endpoints. CONCLUSIONS: The results presented in this study show the value and the challenge of a genomics-driven network trial. The data can be also a valuable resource as a validation cohort for Immunotherapy and Target therapy genomic biomarker research.

The Glioma-IRE project - Molecular profiling in patients with glioma: steps toward an individualized diagnostic and therapeutic approach.

BACKGROUND: This study aimed to characterize the genetic profile of patients with glioma and discuss the impact of next-generation sequencing in glioma diagnosis and treatment. METHODS: Between 2019 and 2022, we analyzed the genetic profile of 99 patients with glioma through the Oncomine Focus Assay. The assay enables the detection of mutations in 52 driver genes, including single nucleotide variants (SNVs), copy number variants (CNVs), and gene fusions. We also collected and analyzed patients' clinic characteristics and treatment outcomes. RESULTS: Over a period of 35 months, 700 patients with glioma followed by our neuro-oncology unit were screened, and 99 were enrolled in the study; most of the patients were excluded for inadequate non-morphological MRI or lack/inadequacy of the tissue samples. Based on our findings, most patients with glioma present mutations, such as SNVs, CNVs or gene fusions. Our data were similar to those reported by The Cancer Genome Atlas Program in terms of frequency of SNVs and CNVs, while we observed more cases of gene fusions. Median overall survival, progression-free survival, and time to progression were significantly lower for patients with grade VI glioblastoma than those with other gliomas. Only four patients were offered a targeted treatment based on the mutation detected; however, only one received treatment, the others could not receive the selected treatment because of worsening clinical status. CONCLUSION: Routine timely molecular profiling in patients with glioma should be implemented to offer patients an individualized diagnostic approach and provide them with advanced targeted therapy options if available.

The Molecular Tumor Board of the Regina Elena National Cancer Institute: from accrual to treatment in real-world.

BACKGROUND: Molecular Tumor Boards (MTB) operating in real-world have generated limited consensus on good practices for accrual, actionable alteration mapping, and outcome metrics. These topics are addressed herein in 124 MTB patients, all real-world accrued at progression, and lacking approved therapy options. METHODS: Actionable genomic alterations identified by tumor DNA (tDNA) and circulating tumor DNA (ctDNA) profiling were mapped by customized OncoKB criteria to reflect diagnostic/therapeutic indications as approved in Europe. Alterations were considered non-SoC when mapped at either OncoKB level 3, regardless of tDNA/ctDNA origin, or at OncoKB levels 1/2, provided they were undetectable in matched tDNA, and had not been exploited in previous therapy lines. RESULTS: Altogether, actionable alterations were detected in 54/124 (43.5%) MTB patients, but only in 39 cases (31%) were these alterations (25 from tDNA, 14 from ctDNA) actionable/unexploited, e.g. they had not resulted in the assignment of pre-MTB treatments. Interestingly, actionable and actionable/unexploited alterations both decreased (37.5% and 22.7% respectively) in a subset of 88 MTB patients profiled by tDNA-only, but increased considerably (77.7% and 66.7%) in 18 distinct patients undergoing combined tDNA/ctDNA testing, approaching the potential treatment opportunities (76.9%) in 147 treatment-naïve patients undergoing routine tDNA profiling for the first time. Non-SoC therapy was MTB-recommended to all 39 patients with actionable/unexploited alterations, but only 22 (56%) accessed the applicable drug, mainly due to clinical deterioration, lengthy drug-gathering procedures, and geographical distance from recruiting clinical trials. Partial response and stable disease were recorded in 8 and 7 of 19 evaluable patients, respectively. The time to progression (TTP) ratio (MTB-recommended treatment vs last pre-MTB treatment) exceeded the conventional Von Hoff 1.3 cut-off in 9/19 cases, high absolute TTP and Von Hoff values coinciding in 3 cases. Retrospectively, 8 patients receiving post-MTB treatment(s) as per physician's choice were noted to have a much longer overall survival from MTB accrual than 11 patients who had received no further treatment (35.09 vs 6.67 months, p = 0.006). CONCLUSIONS: MTB-recommended/non-SoC treatments are effective, including those assigned by ctDNA-only alterations. However, real-world MTBs may inadvertently recruit patients electively susceptible to diverse and/or multiple treatments.

Development of a somatic variant registry in a National Cancer Center: towards Molecular Real World Data preparedness.

The Biomedical Research field is currently advancing to develop Clinical Trials and translational projects based on Real World Evidence. To make this transition feasible, clinical centers need to work toward Data Accessibility and Interoperability. This task is particularly challenging when applied to Genomics, that entered in routinary screening in the last years via mostly amplicon-based Next-Generation Sequencing panels. Said experiments produce up to hundreds of features per patient, and their summarized results are often stored in static clinical reports, making critical information inaccessible to automated access and Federated Search consortia. In this study, we present a reanalysis of 4620 solid tumor sequencing samples in five different histology settings. Furthermore, we describe all the Bioinformatics and Data Engineering processes that were put in place in order to create a Somatic Variant Registry able to deal with the large biotechnological variability of routinary Genomics Profiling.

Machine learning endometrial cancer risk prediction model: integrating guidelines of European Society for Medical Oncology with the tumor immune framework.

OBJECTIVE: Current prognostic factors for endometrial cancer are not sufficient to predict recurrence in early stages. Treatment choices are based on the prognostic factors included in the risk classes defined by the ESMO-ESGO-ESTRO (European Society for Medical Oncology-European Society of Gynaecological Oncology-European Society for Radiotherapy and Oncology) consensus conference with the new biomolecular classification based on POLE, TP53, and microsatellite instability status. However, a minority of early stage cases relapse regardless of their low risk profiles. Integration of the immune context status to existing molecular based models has not been fully evaluated. This study aims to investigate whether the integration of the immune landscape in the tumor microenvironment could improve clinical risk prediction models and allow better profiling of early stages. METHODS: Leveraging the potential of in silico deconvolution tools, we estimated the relative abundances of immune populations in public data and then applied feature selection methods to generate a machine learning based model for disease free survival probability prediction. RESULTS: We included information on International Federation of Gynecology and Obstetrics (FIGO) stage, tumor mutational burden, microsatellite instability, POLEmut status, interferon γ signature, and relative abundances of monocytes, natural killer cells, and CD4+T cells to build a relapse prediction model and obtained a balanced accuracy of 69%. We further identified two novel early stage profiles that undergo different pathways of recurrence. CONCLUSION: This study presents an extension of current prognostic factors for endometrial cancer by exploiting machine learning models and deconvolution techniques on available public biomolecular data. Prospective clinical trials are advisable to validate the early stage stratification.

Molecular dissection of a hyper-aggressive CBFB-MYH11/FLT3-ITD-positive acute myeloid leukemia.

Acute Myeloid Leukaemia (AML) is a haematological malignancy showing a hypervariable landscape of clinical outcomes and phenotypic differences, explainable by heterogeneity at the cellular and molecular level. Among the most common genomic alterations, CBFB-MYH11 rearrangement and FLT3-ITD gene mutations, have opposite clinical significance and are unfrequently associated. We present here a Molecular Case Report in which these two events co-exist an ultra-aggressive phenotype resulting in death in 4 days from hospital admittance. Somatic and germline Whole Exome Sequencing analysis was performed to uncover other putative driver mutations, de-novo genomic structural events or germline clusters increasing cancer insurgence. Only three mutations in LTK, BCAS2 and LGAS9 were found, unlikely causative of the exhibited phenotype, prompting to additional investigation of the rare CBFB-MYH11/ FLT3-ITD scenario.

Hepatitis B protein HBx binds the DLEU2 lncRNA to sustain cccDNA and host cancer-related gene transcription.

OBJECTIVE: The HBV HBx regulatory protein is required for transcription from the covalently closed circular DNA (cccDNA) minichromosome and affects the epigenetic control of both viral and host cellular chromatin. DESIGN: We explored, in relevant cellular models of HBV replication, the functional consequences of HBx interaction with DLEU2, a long non-coding RNA (lncRNA) expressed in the liver and increased in human hepatocellular carcinoma (HCC), in the regulation of host target genes and the HBV cccDNA. RESULTS: We show that HBx binds the promoter region, enhances the transcription and induces the accumulation of DLEU2 in infected hepatocytes. We found that nuclear DLEU2 directly binds HBx and the histone methyltransferase enhancer of zeste homolog 2 (EZH2), the catalytic active subunit of the polycomb repressor complex 2 (PRC2) complex. Computational modelling and biochemical evidence suggest that HBx and EZH2 share two preferential binding sites in DLEU2 intron 1. HBx and DLEU2 co-recruitment on the cccDNA displaces EZH2 from the viral chromatin to boost transcription and viral replication. DLEU2-HBx association with target host promoters relieves EZH2 repression and leads to the transcriptional activation of a subset of EZH2/PRC2 target genes in HBV-infected cells and HBV-related HCCs. CONCLUSIONS: Our results highlight the ability of HBx to bind RNA to impact on the epigenetic control of both viral cccDNA and host genes and provide a new key to understand the role of DLEU2 and EZH2 overexpression in HBV-related HCCs and HBx contribution to hepatocytes transformation.

Design of a companion bioinformatic tool to detect the emergence and geographical distribution of SARS-CoV-2 Spike protein genetic variants.

BACKGROUND: Tracking the genetic variability of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) is a crucial challenge. Mainly to identify target sequences in order to generate robust vaccines and neutralizing monoclonal antibodies, but also to track viral genetic temporal and geographic evolution and to mine for variants associated with reduced or increased disease severity. Several online tools and bioinformatic phylogenetic analyses have been released, but the main interest lies in the Spike protein, which is the pivotal element of current vaccine design, and in the Receptor Binding Domain, that accounts for most of the neutralizing the antibody activity. METHODS: Here, we present an open-source bioinformatic protocol, and a web portal focused on SARS-CoV-2 single mutations and minimal consensus sequence building as a companion vaccine design tool. Furthermore, we provide immunogenomic analyses to understand the impact of the most frequent RBD variations. RESULTS: Results on the whole GISAID sequence dataset at the time of the writing (October 2020) reveals an emerging mutation, S477N, located on the central part of the Spike protein Receptor Binding Domain, the Receptor Binding Motif. Immunogenomic analyses revealed some variation in mutated epitope MHC compatibility, T-cell recognition, and B-cell epitope probability for most frequent human HLAs. CONCLUSIONS: This work provides a framework able to track down SARS-CoV-2 genomic variability.

Che-1 is targeted by c-Myc to sustain proliferation in pre-B-cell acute lymphoblastic leukemia.

Despite progress in treating B-cell precursor acute lymphoblastic leukemia (BCP-ALL), disease recurrence remains the main cause of treatment failure. New strategies to improve therapeutic outcomes are needed, particularly in high-risk relapsed patients. Che-1/AATF (Che-1) is an RNA polymerase II-binding protein involved in proliferation and tumor survival, but its role in hematological malignancies has not been clarified. Here, we show that Che-1 is overexpressed in pediatric BCP-ALL during disease onset and at relapse, and that its depletion inhibits the proliferation of BCP-ALL cells. Furthermore, we report that c-Myc regulates Che-1 expression by direct binding to its promoter and describe a strict correlation between Che-1 expression and c-Myc expression. RNA-seq analyses upon Che-1 or c-Myc depletion reveal a strong overlap of the respective controlled pathways. Genomewide ChIP-seq experiments suggest that Che-1 acts as a downstream effector of c-Myc. These results identify the pivotal role of Che-1 in the control of BCP-ALL proliferation and present the protein as a possible therapeutic target in children with relapsed BCP-ALL.

Combinations of immuno-checkpoint inhibitors predictive biomarkers only marginally improve their individual accuracy.

BACKGROUND: There are no accepted universal biomarkers capable to accurately predict response to immuno-checkpoint inhibitors (ICI). Although recent literature has been flooded with studies on ICI predictive biomarkers, available data show that currently approved companion diagnostics either leave out many possible responders, as in the case of PD-L1 testing for first-line metastatic lung cancer, or apply to a small subset of patients, such as the recently approved treatment for microsatellite instability-high or mismatch repair deficiency tumors. In this study, we conducted a survey of the available data on ICI trials with matched genomic or transcriptomic datasets in order to cross-validate the proposed biomarkers, to assess whether their prediction power was confirmed and, mainly, to investigate if their combination was able to generate a better predictive tool. METHODS: We extracted clinical information and sequencing data details from publicly available datasets, along with a list of possible biomarkers obtained from the recent literature. After an operation of data harmonization, we validated the performance of all the biomarkers taken individually. Furthermore, we tested two strategies to combine the best performing biomarkers in order to improve their predictive value. RESULTS: When considered individually, some of the biomarkers, such as the ImmunoPhenoScore, and the IFN-γ signature, did not confirm their originally proposed predictive power. The best absolute scoring biomarkers are TIDE, one of the ICB resistance signatures and CTLA4 with a mean AUC > 0.66. Among the combinations tested, generalized linear models showed the best performance with an AUC of 0.78. CONCLUSIONS: We confirmed that the available biomarkers, taken individually, fail to provide a satisfactory predictive value. Unfortunately, also combination of some of them only provides marginal improvements. Hence, in order to generate a more robust way to predict ICI efficacy it is necessary to analyze and combine additional biomarkers and interrogate a wider set of clinical data.

CHK1-targeted therapy to deplete DNA replication-stressed, p53-deficient, hyperdiploid colorectal cancer stem cells.

OBJECTIVE: Cancer stem cells (CSCs) are responsible for tumour formation and spreading, and their targeting is required for tumour eradication. There are limited therapeutic options for advanced colorectal cancer (CRC), particularly for tumours carrying RAS-activating mutations. The aim of this study was to identify novel CSC-targeting strategies. DESIGN: To discover potential therapeutics to be clinically investigated as single agent, we performed a screening with a panel of FDA-approved or investigational drugs on primary CRC cells enriched for CSCs (CRC-SCs) isolated from 27 patients. Candidate predictive biomarkers of efficacy were identified by integrating genomic, reverse-phase protein microarray (RPPA) and cytogenetic analyses, and validated by immunostainings. DNA replication stress (RS) was increased by employing DNA replication-perturbing or polyploidising agents. RESULTS: The drug-library screening led to the identification of LY2606368 as a potent anti-CSC agent acting in vitro and in vivo in tumour cells from a considerable number of patients (∼36%). By inhibiting checkpoint kinase (CHK)1, LY2606368 affected DNA replication in most CRC-SCs, including RAS-mutated ones, forcing them into premature, lethal mitoses. Parallel genomic, RPPA and cytogenetic analyses indicated that CRC-SCs sensitive to LY2606368 displayed signs of ongoing RS response, including the phosphorylation of RPA32 and ataxia telangiectasia mutated serine/threonine kinase (ATM). This was associated with mutation(s) in TP53 and hyperdiploidy, and made these CRC-SCs exquisitely dependent on CHK1 function. Accordingly, experimental increase of RS sensitised resistant CRC-SCs to LY2606368. CONCLUSIONS: LY2606368 selectively eliminates replication-stressed, p53-deficient and hyperdiploid CRC-SCs independently of RAS mutational status. These results provide a strong rationale for biomarker-driven clinical trials with LY2606368 in patients with CRC.

Conditionally reprogrammed cells (CRC) methodology does not allow the in vitro expansion of patient-derived primary and metastatic lung cancer cells.

Availability of tumor and non-tumor patient-derived models would promote the development of more effective therapeutics for non-small cell lung cancer (NSCLC). Recently, conditionally reprogrammed cells (CRC) methodology demonstrated exceptional potential for the expansion of epithelial cells from patient tissues. However, the possibility to expand patient-derived lung cancer cells using CRC protocols is controversial. Here, we used CRC approach to expand cells from non-tumoral and tumor biopsies of patients with primary or metastatic NSCLC as well as pulmonary metastases of colorectal or breast cancers. CRC cultures were obtained from both tumor and non-malignant tissues with extraordinary high efficiency. Tumor cells were tracked in vitro through tumorigenicity assay, monitoring of tumor-specific genetic alterations and marker expression. Cultures were composed of EpCAM+ lung epithelial cells lacking tumorigenic potential. NSCLC biopsies-derived cultures rapidly lost patient-specific genetic mutations or tumor antigens. Similarly, pulmonary metastases of colon or breast cancer generated CRC cultures of lung epithelial cells. All CRC cultures examined displayed epithelial lung stem cell phenotype and function. In contrast, brain metastatic lung cancer biopsies failed to generate CRC cultures. In conclusion, patient-derived primary and metastatic lung cancer cells were negatively selected under CRC conditions, limiting the expansion to non-malignant lung epithelial stem cells from either tumor or non-tumor tissue sources. Thus, CRC approach cannot be applied for direct therapeutic testing of patient lung tumor cells, as the tumor-derived CRC cultures are composed of (non-tumoral) airway basal cells.

Expression of the Hippo transducer TAZ in association with WNT pathway mutations impacts survival outcomes in advanced gastric cancer patients treated with first-line chemotherapy.

BACKGROUND: An extensive crosstalk co-regulates the Hippo and Wnt pathway. Preclinical studies revealed that the Hippo transducers YAP/TAZ mediate a number of oncogenic functions in gastric cancer (GC). Moreover, comprehensive characterization of GC demonstrated that the Wnt pathway is targeted by oncogenic mutations. On this ground, we hypothesized that YAP/TAZ- and Wnt-related biomarkers may predict clinical outcomes in GC patients treated with chemotherapy. METHODS: In the present study, we included 86 patients with advanced GC treated with first-line chemotherapy in prospective phase II trials or in routine clinical practice. Tissue samples were immunostained to evaluate the expression of YAP/TAZ. Mutational status of key Wnt pathway genes (CTNNB1, APC and FBXW7) was assessed by targeted DNA next-generation sequencing (NGS). Survival curves were estimated and compared by the Kaplan-Meier product-limit method and the log-rank test, respectively. Variables potentially affecting progression-free survival (PFS) were verified in univariate Cox proportional hazard models. The final multivariate Cox models were obtained with variables testing significant at the univariate analysis, and by adjusting for all plausible predictors of the outcome of interest (PFS). RESULTS: We observed a significant association between TAZ expression and Wnt mutations (Chi-squared p = 0.008). Combined TAZ expression and Wnt mutations (TAZpos/WNTmut) was more frequently observed in patients with the shortest progression-free survival (negative outliers) (Fisher p = 0.021). Uni-and multivariate Cox regression analyses revealed that patients whose tumors harbored the TAZpos/WNTmut signature had an increased risk of disease progression (univariate Cox: HR 2.27, 95% CI 1.27-4.05, p = 0.006; multivariate Cox: HR 2.73, 95% CI 1.41-5.29, p = 0.003). Finally, the TAZpos/WNTmut signature negatively impacted overall survival. CONCLUSIONS: Collectively, our findings indicate that the oncogenic YAP/TAZ-Wnt crosstalk may be active in GC, conferring chemoresistant traits that translate into adverse survival outcomes.

Coexisting YAP expression and TP53 missense mutations delineates a molecular scenario unexpectedly associated with better survival outcomes in advanced gastric cancer.

We have previously reported that nuclear expression of the Hippo transducer TAZ in association with Wnt pathway mutations negatively impacts survival outcomes in advanced gastric cancer (GC) patients. Here, we extended these previous findings by investigating another oncogenic cooperation, namely, the interplay between YAP, the TAZ paralogue, and p53. The molecular output of the YAP-p53 cooperation is dependent on TP53 mutational status. In the absence of mutations, the YAP-p53 crosstalk elicits a pro-apoptotic response, whereas in the presence of TP53 mutations it activates a pro-proliferative transcriptional program. In order to study this phenomenon, we re-analyzed data from 83 advanced GC patients treated with chemotherapy whose tissue samples had been characterized for YAP expression (immunohistochemistry, IHC) and TP53 mutations (deep sequencing). In doing so, we generated a molecular model combining nuclear YAP expression in association with TP53 missense variants (YAP+/TP53mut(mv)). Surprisingly, this signature was associated with a decreased risk of disease progression (multivariate Cox for progression-free survival: HR 0.53, 95% CI 0.30-0.91, p = 0.022). The YAP+/TP53mut(mv) model was also associated with better OS in the subgroup of patients who received chemotherapy beyond the first-line setting (multivariate Cox: HR 0.36, 95% CI 0.16-0.81, p = 0.013). Collectively, our findings suggest that the oncogenic cooperation between YAP and mutant p53 may translate into better survival outcomes. This apparent paradox can be explained by the pro-proliferative program triggered by YAP and mutant p53, that supposedly renders cancer cells more vulnerable to cytotoxic therapies.

DNA damage repair and survival outcomes in advanced gastric cancer patients treated with first-line chemotherapy.

The DNA damage response (DDR) network is exploited by cancer cells to withstand chemotherapy. Gastric cancer (GC) carries deregulation of the DDR and harbors genetic defects that fuel its activation. The ATM-Chk2 and ATR-Chk1-Wee1 axes are deputed to initiate DNA repair. Overactivation of these pathways in cancer cells may represent an adaptive response for compensating genetic defects deregulating G1 -S transition (e.g., TP53) and ATM/ATR-initiated DNA repair (e.g., ARID1A). We hypothesized that DDR-linked biomarkers may predict clinical outcomes in GC patients treated with chemotherapy. Immunohistochemical assessment of DDR kinases (pATM, pChk2, pChk1 and pWee1) and DNA damage markers (γ-H2AX and pRPA32) was performed in biological samples from 110 advanced GC patients treated with first-line chemotherapy, either in phase II trials or in routine clinical practice. In 90 patients, this characterization was integrated with targeted ultra-deep sequencing for evaluating the mutational status of TP53 and ARID1A. We recorded a positive association between the investigated biomarkers. The combination of two biomarkers (γ-H2AXhigh /pATMhigh ) was an adverse factor for both progression-free survival (multivariate Cox: HR 2.23, 95%CI: 1.47-3.40) and overall survival (multivariate Cox: HR: 2.07, 95%CI: 1.20-3.58). The relationship between the γ-H2AXhigh /pATMhigh model and progression-free survival was consistent across the different TP53 backgrounds and was maintained in the ARID1A wild-type setting. Conversely, this association was no longer observed in an ARID1A-mutated subgroup. The γ-H2AXhigh /pATMhigh model negatively impacted survival outcomes in GC patients treated with chemotherapy. The mutational status of ARID1A, but apparently not TP53 mutations, affects its predictive significance.

RAP: RNA-Seq Analysis Pipeline, a new cloud-based NGS web application.

BACKGROUND: The study of RNA has been dramatically improved by the introduction of Next Generation Sequencing platforms allowing massive and cheap sequencing of selected RNA fractions, also providing information on strand orientation (RNA-Seq). The complexity of transcriptomes and of their regulative pathways make RNA-Seq one of most complex field of NGS applications, addressing several aspects of the expression process (e.g. identification and quantification of expressed genes and transcripts, alternative splicing and polyadenylation, fusion genes and trans-splicing, post-transcriptional events, etc.). METHODS: In order to provide researchers with an effective and friendly resource for analyzing RNA-Seq data, we present here RAP (RNA-Seq Analysis Pipeline), a cloud computing web application implementing a complete but modular analysis workflow. This pipeline integrates both state-of-the-art bioinformatics tools for RNA-Seq analysis and in-house developed scripts to offer to the user a comprehensive strategy for data analysis. RAP is able to perform quality checks (adopting FastQC and NGS QC Toolkit), identify and quantify expressed genes and transcripts (with Tophat, Cufflinks and HTSeq), detect alternative splicing events (using SpliceTrap) and chimeric transcripts (with ChimeraScan). This pipeline is also able to identify splicing junctions and constitutive or alternative polyadenylation sites (implementing custom analysis modules) and call for statistically significant differences in genes and transcripts expression, splicing pattern and polyadenylation site usage (using Cuffdiff2 and DESeq). RESULTS: Through a user friendly web interface, the RAP workflow can be suitably customized by the user and it is automatically executed on our cloud computing environment. This strategy allows to access to bioinformatics tools and computational resources without specific bioinformatics and IT skills. RAP provides a set of tabular and graphical results that can be helpful to browse, filter and export analyzed data, according to the user needs.