Computational deconvolution of transcriptomic data for the study of tumor-infiltrating immune cells:

Cancer is a complex disease characterized by a wide array of mutually interacting components constituting the tumor microenvironment (connective tissue, vascular system, immune cells), many of which are targeted therapeutically. In particular, immune checkpoint inhibitors have recently become an established part of the treatment of cancer. Despite great promise, only a portion of the patients display durable response. Current research efforts are concentrated on the determination of tumor-specific biomarkers predictive of response, such as tumor mutational burden, microsatellite instability, and neo-antigen presentation. However, it is clear that several additional characteristics pertaining to the tumor microenvironment play a critical role in the effectiveness of immunotherapy. Here we comment on the computational methods that are used for the analysis of the tumor microenvironment components from transcriptomic data, discuss the critical needs, and foresee potential evolutions in the field

Massive NGS data analysis reveals hundreds of potential novel gene fusions in human cell lines

Background: Gene fusions derive from chromosomal rearrangements and the resulting chimeric transcripts are often endowed with oncogenic potential. Furthermore, they serve as diagnostic tools for the clinical classification of cancer subgroups with different prognosis and, in some cases, they can provide specific drug targets. So far, many efforts have been carried out to study gene fusion events occurring in tumor samples. In recent years, the availability of a comprehensive Next Generation Sequencing dataset for all the existing human tumor cell lines has provided the opportunity to further investigate these data in order to identify novel and still uncharacterized gene fusion events. Results: In our work, we have extensively reanalyzed 935 paired-end RNA-seq experiments downloaded from "The Cancer Cell Line Encyclopedia" repository, aiming at addressing novel putative cell-line specific gene fusion events in human malignancies. The bioinformatics analysis has been performed by the execution of four different gene fusion detection algorithms. The results have been further prioritized by running a bayesian classifier which makes an in silico validation. The collection of fusion events supported by all of the predictive softwares results in a robust set of ∼ 1,700 in-silico predicted novel candidates suitable for downstream analyses. Given the huge amount of data and information produced, computational results have been systematized in a database named LiGeA. The database can be browsed through a dynamical and interactive web portal, further integrated with validated data from other well known repositories. Taking advantage of the intuitive query forms, the users can easily access, navigate, filter and select the putative gene fusions for further validations and studies. They can also find suitable experimental models for a given fusion of interest. Conclusions: We believe that the LiGeA resource can represent not only the first compendium of both known and putative novel gene fusion events in the catalog of all of the human malignant cell lines, but it can also become a handy starting point for wet-lab biologists who wish to investigate novel cancer biomarkers and specific drug targets

Avian and canine aldehyde oxidases. Novel insights into the biology and evolution of molybdo-flavoenzymes.

Aldehyde oxidases are molybdo-flavoenzymes structurally related to xanthine oxidoreductase. They catalyze the oxidation of aldehydes or N-heterocycles of physiological, pharmacological, and toxicological relevance. Rodents are characterized by four aldehyde oxidases as follows: AOX1 and aldehyde oxidase homologs 1-3 (AOH1, AOH2, and AOH3). Humans synthesize a single functional aldehyde oxidase, AOX1. Here we define the structure and the characteristics of the aldehyde oxidase genes and proteins in chicken and dog. The avian genome contains two aldehyde oxidase genes, AOX1 and AOH, mapping to chromosome 7. AOX1 and AOH are structurally very similar and code for proteins whose sequence was deduced from the corresponding cDNAs. AOX1 is the ortholog of the same gene in mammals, whereas AOH represents the likely ancestor of rodent AOH1, AOH2, and AOH3. The dog genome is endowed with two structurally conserved and active aldehyde oxidases clustering on chromosome 37. Cloning of the corresponding cDNAs and tissue distribution studies demonstrate that they are the orthologs of rodent AOH2 and AOH3. The vestiges of dog AOX1 and AOH1 are recognizable upstream of AOH2 and AOH3 on the same chromosome. Comparison of the complement and the structure of the aldehyde oxidase and xanthine oxidoreductase genes in vertebrates and other animal species indicates that they evolved through a series of duplication and inactivation events. Purification of the chicken AOX1 protein to homogeneity from kidney demonstrates that the enzyme possesses retinaldehyde oxidase activity. Unlike humans and most other mammals, dog and chicken are devoid of liver aldehyde oxidase activity

Evaluating Translational Methods for Personalized Medicine—A Scoping Review

The introduction of personalized medicine, through the increasing multi-omics characterization of disease, brings new challenges to disease modeling. The scope of this review was a broad evaluation of the relevance, validity, and predictive value of the current preclinical methodologies applied in stratified medicine approaches. Two case models were chosen: oncology and brain disorders. We conducted a scoping review, following the Joanna Briggs Institute guidelines, and searched PubMed, EMBASE, and relevant databases for reports describing preclinical models applied in personalized medicine approaches. A total of 1292 and 1516 records were identified from the oncology and brain disorders search, respectively. Quantitative and qualitative synthesis was performed on a final total of 63 oncology and 94 brain disorder studies. The complexity of personalized approaches highlights the need for more sophisticated biological systems to assess the integrated mechanisms of response. Despite the progress in developing innovative and complex preclinical model systems, the currently available methods need to be further developed and validated before their potential in personalized medicine endeavors can be realized. More importantly, we identified underlying gaps in preclinical research relating to the relevance of experimental models, quality assessment practices, reporting, regulation, and a gap between preclinical and clinical research. To achieve a broad implementation of predictive translational models in personalized medicine, these fundamental deficits must be addressed.publishedVersio

The ER stress response mediator ERO1 triggers cancer metastasis by favoring the angiogenic switch in hypoxic conditions

: Solid tumors are often characterized by a hypoxic microenvironment which contributes, through the hypoxia-inducible factor HIF-1, to the invasion-metastasis cascade. Endoplasmic reticulum (ER) stress also leads tumor cells to thrive and spread by inducing a transcriptional and translational program, the Unfolded Protein Response (UPR), aimed at restoring ER homeostasis. We studied ERO1 alpha (henceforth ERO1), a protein disulfide oxidase with the tumor-relevant characteristic of being positively regulated by both ER stress and hypoxia. Analysis of the redox secretome indicated that pro-angiogenic HIF-1 targets, were blunted in ERO1-devoid breast cancer cells under hypoxic conditions. ERO1 deficiency reduced tumor cell migration and lung metastases by impinging on tumor angiogenesis, negatively regulating the upstream ATF4/CHOP branch of the UPR and selectively impeding oxidative folding of angiogenic factors, among which VEGF-A. Thus, ERO1 deficiency acted synergistically with the otherwise feeble curative effects of anti-angiogenic therapy in aggressive breast cancer murine models and it might be exploited to treat cancers with pathological HIF-1-dependent angiogenesis. Furthermore, ERO1 levels are higher in the more aggressive basal breast tumors and correlate inversely with the disease- and metastasis-free interval of breast cancer patients. Thus, taking advantage of our in vitro data on ERO1-regulated gene products we identified a gene set associated with ERO1 expression in basal tumors and related to UPR, hypoxia, and angiogenesis, whose levels might be investigated in patients as a hallmark of tumor aggressiveness and orient those with lower levels toward an effective anti-angiogenic therapy

Platinum sensitivity and DNA repair in a recently established panel of patient-derived ovarian carcinoma xenografts

A xenobank of patient-derived (PDX) ovarian tumor samples has been established consisting of tumors with different sensitivity to cisplatin (DDP), from very responsive to resistant. As the DNA repair pathway is an important driver in tumor response to DDP, we analyzed the mRNA expression of 20 genes involved in the nucleotide excision repair, fanconi anemia, homologous recombination, base excision repair, mismatch repair and translesion repair pathways and the methylation patterns of some of these genes. We also investigated the correlation with the response to platinum-based therapy. The mRNA levels of the selected genes were evaluated by Real Time-PCR (RT-PCR) with ad hoc validated primers and gene promoter methylation by pyrosequencing. All the DNA repair genes were variably expressed in all 42 PDX samples analyzed, with no particular histotype-specific pattern of expression. In high-grade serous/endometrioid PDXs, the CDK12 mRNA expression levels positively correlated with the expression of TP53BP1, PALB2, XPF and POLB. High-grade serous/endometrioid PDXs with TP53 mutations had significantly higher levels of POLQ, FANCD2, RAD51 and POLB than high-grade TP53 wild type PDXs. The mRNA levels of CDK12, PALB2 and XPF inversely associated with the in vivo DDP antitumor activity; higher CDK12 mRNA levels were associated with a higher recurrence rate in ovarian patients with low residual tumor. These data support the important role of CDK12 in the response to a platinum based therapy in ovarian patients

Minimal information for chemosensitivity assays (MICHA): a next-generation pipeline to enable the FAIRification of drug screening experiments

Chemosensitivity assays are commonly used for preclinical drug discovery and clinical trial optimization. However, data from independent assays are often discordant, largely attributed to uncharacterized variation in the experimental materials and protocols. We report here the launching of Minimal Information for Chemosensitivity Assays (MICHA), accessed via https://micha-protocol.org. Distinguished from existing efforts that are often lacking support from data integration tools, MICHA can automatically extract publicly available information to facilitate the assay annotation including: 1) compounds, 2) samples, 3) reagents and 4) data processing methods. For example, MICHA provides an integrative web server and database to obtain compound annotation including chemical structures, targets and disease indications. In addition, the annotation of cell line samples, assay protocols and literature references can be greatly eased by retrieving manually curated catalogues. Once the annotation is complete, MICHA can export a report that conforms to the FAIR principle (Findable, Accessible, Interoperable and Reusable) of drug screening studies. To consolidate the utility of MICHA, we provide FAIRified protocols from five major cancer drug screening studies as well as six recently conducted COVID-19 studies. With the MICHA web server and database, we envisage a wider adoption of a community-driven effort to improve the open access of drug sensitivity assays.Peer reviewe

Cellular and molecular determinants of all-trans retinoic acid sensitivity in breast cancer: Luminal phenotype and RARα expression

Forty-two cell lines recapitulating mammary carcinoma heterogeneity were profiled for all-trans retinoic acid (ATRA) sensitivity. Luminal and ER+ (estrogen-receptor-positive) cell lines are generally sensitive to ATRA, while refractoriness/low sensitivity is associated with a Basal phenotype and HER2 positivity. Indeed, only 2 Basal cell lines (MDA-MB157 and HCC-1599) are highly sensitive to the retinoid. Sensitivity of HCC-1599 cells is confirmed in xenotransplanted mice. Short-term tissue-slice cultures of surgical samples validate the cell-line results and support the concept that a high proportion of Luminal/ER+ carcinomas are ATRA sensitive, while triple-negative (Basal) and HER2-positive tumors tend to be retinoid resistant. Pathway-oriented analysis of the constitutive gene-expression profiles in the cell lines identifies RARα as the member of the retinoid pathway directly associated with a Luminal phenotype, estrogen positivity and ATRA sensitivity. RARα3 is the major transcript in ATRA-sensitive cells and tumors. Studies in selected cell lines with agonists/antagonists confirm that RARα is the principal mediator of ATRA responsiveness. RARα over-expression sensitizes retinoid-resistant MDA-MB453 cells to ATRA anti-proliferative action. Conversely, silencing of RARα in retinoid-sensitive SKBR3 cells abrogates ATRA responsiveness. All this is paralleled by similar effects on ATRA-dependent inhibition of cell motility, indicating that RARα may mediate also ATRA anti-metastatic effects. We define gene sets of predictive potential which are associated with ATRA sensitivity in breast cancer cell lines and validate them in short-term tissue cultures of Luminal/ER+ and triple-negative tumors. In these last models, we determine the perturbations in the transcriptomic profiles afforded by ATRA. The study provides fundamental information for the development of retinoid-based therapeutic strategies aimed at the stratified treatment of breast cancer subtypes

Recommendations for robust and reproducible preclinical research in personalised medicine

BACKGROUND: Personalised medicine is a medical model that aims to provide tailor-made prevention and treatment strategies for defined groups of individuals. The concept brings new challenges to the translational step, both in clinical relevance and validity of models. We have developed a set of recommendations aimed at improving the robustness of preclinical methods in translational research for personalised medicine. METHODS: These recommendations have been developed following four main steps: (1) a scoping review of the literature with a gap analysis, (2) working sessions with a wide range of experts in the field, (3) a consensus workshop, and (4) preparation of the final set of recommendations. RESULTS: Despite the progress in developing innovative and complex preclinical model systems, to date there are fundamental deficits in translational methods that prevent the further development of personalised medicine. The literature review highlighted five main gaps, relating to the relevance of experimental models, quality assessment practices, reporting, regulation, and a gap between preclinical and clinical research. We identified five points of focus for the recommendations, based on the consensus reached during the consultation meetings: (1) clinically relevant translational research, (2) robust model development, (3) transparency and education, (4) revised regulation, and (5) interaction with clinical research and patient engagement. Here, we present a set of 15 recommendations aimed at improving the robustness of preclinical methods in translational research for personalised medicine. CONCLUSIONS: Appropriate preclinical models should be an integral contributor to interventional clinical trial success rates, and predictive translational models are a fundamental requirement to realise the dream of personalised medicine. The implementation of these guidelines is ambitious, and it is only through the active involvement of all relevant stakeholders in this field that we will be able to make an impact and effectuate a change which will facilitate improved translation of personalised medicine in the future

Longitudinal study of computerised cardiotocography in early fetal growth restriction.

OBJECTIVES: To explore if in early fetal growth restriction (FGR) the longitudinal pattern of short-term fetal heart rate (FHR) variation (STV) can be used for identifying imminent fetal distress and if abnormalities of FHR registration associate with two-year infant outcome. METHODS: The original TRUFFLE study assessed if in early FGR the use of ductus venosus Doppler pulsatility index (DVPI), in combination with a safety-net of very low STV and / or recurrent decelerations, could improve two-year infant survival without neurological impairment in comparison to computerised cardiotocography (cCTG) with STV calculation only. For this secondary analysis we selected women, who delivered before 32 weeks, and who had consecutive STV data for more than 3 days before delivery, and known infant two-year outcome data. Women who received corticosteroids within 3 days of delivery were excluded. Individual regression line algorithms of all STV values except the last one were calculated. Life table analysis and Cox regression analysis were used to calculate the day by day risk for a low STV or very low STV and / or FHR decelerations (DVPI group safety-net) and to assess which parameters were associated to this risk. Furthermore, it was assessed if STV pattern, lowest STV value or recurrent FHR decelerations were associated with two-year infant outcome. RESULTS: One hundred and fourty-nine women matched the inclusion criteria. Using the individual STV regression lines prediction of a last STV below the cCTG-group cut-off had a sensitivity of 0.42 and specificity of 0.91. For each day after inclusion the median risk for a low STV(cCTG criteria) was 4% (Interquartile range (IQR) 2% to 7%) and for a very low STV and / or recurrent decelerations (DVPI safety-net criteria) 5% (IQR 4 to 7%). Measures of STV pattern, fetal Doppler (arterial or venous), birthweight MoM or gestational age did not improve daily risk prediction usefully. There was no association of STV regression coefficients, a last low STV or /and recurrent decelerations with short or long term infant outcomes. CONCLUSION: The TRUFFLE study showed that a strategy of DVPI monitoring with a safety-net delivery indication of very low STV and / or recurrent decelerations could increase infant survival without neurological impairment at two years. This post-hoc analysis demonstrates that in early FGR the day by day risk of an abnormal cCTG as defined by the DVPI protocol safety-net criteria is 5%, and that prediction of this is not possible. This supports the rationale for cCTG monitoring more often than daily in these high-risk fetuses. Low STV and/or recurrent decelerations were not associated with adverse infant outcome and it appears safe to delay intervention until such abnormalities occur, as long as DVPI is in the normal range