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Circulating tumor DNA (ctDNA) has become an attractive biomarker in human oncology, and its use may be informative in canine cancer. Thus, we used droplet digital PCR or PCR for antigen receptor rearrangement, to explore tumor-specific point mutations, copy number alterations, and chromosomal rearrangements in the plasma of cancer-affected dogs. We detected ctDNA in 21/23 (91.3%) of histiocytic sarcoma (HS), 2/8 (25%) of oral melanoma, and 12/13 (92.3%) of lymphoma cases. The utility of ctDNA in diagnosing HS was explored in 133 dogs, including 49 with HS, and the screening of recurrent PTPN11 mutations in plasma had a specificity of 98.8% and a sensitivity between 42.8 and 77% according to the clinical presentation of HS. Sensitivity was greater in visceral forms and especially related to pulmonary location. Follow-up of four dogs by targeting lymphoma-specific antigen receptor rearrangement in plasma showed that minimal residual disease detection was concordant with clinical evaluation and treatment response. Thus, our study shows that ctDNA is detectable in the plasma of cancer-affected dogs and is a promising biomarker for diagnosis and clinical follow-up. ctDNA detection appears to be useful in comparative oncology research due to growing interest in the study of natural canine tumors and exploration of new therapies.

Background Artificial intelligence (AI) has the potential to transform our healthcare systems significantly. New AI technologies based on machine learning approaches should play a key role in clinical decision-making in the future. However, their implementation in health care settings remains limited, mostly due to a lack of robust validation procedures. There is a need to develop reliable assessment frameworks for the clinical validation of AI. We present here an approach for assessing AI for predicting treatment response in triple-negative breast cancer (TNBC), using real-world data and molecular -omics data from clinical data warehouses and biobanks. Methods The European “ITFoC (Information Technology for the Future Of Cancer)” consortium designed a framework for the clinical validation of AI technologies for predicting treatment response in oncology. Results This framework is based on seven key steps specifying: (1) the intended use of AI, (2) the target population, (3) the timing of AI evaluation, (4) the datasets used for evaluation, (5) the procedures used for ensuring data safety (including data quality, privacy and security), (6) the metrics used for measuring performance, and (7) the procedures used to ensure that the AI is explainable. This framework forms the basis of a validation platform that we are building for the “ITFoC Challenge”. This community-wide competition will make it possible to assess and compare AI algorithms for predicting the response to TNBC treatments with external real-world datasets. Conclusions The predictive performance and safety of AI technologies must be assessed in a robust, unbiased and transparent manner before their implementation in healthcare settings. We believe that the consideration of the ITFoC consortium will contribute to the safe transfer and implementation of AI in clinical settings, in the context of precision oncology and personalized care.

The genetic etiology of childhood cancers still remains largely unknown. It is therefore essential to develop novel strategies to unravel the spectrum of pediatric cancer genes. Statistical network modeling techniques have emerged as powerful methodologies for enabling the inference of gene-disease relationship and have been performed on adult but not pediatric cancers. We performed a deep multi-layer understanding of pan-cancer transcriptome data selected from the Treehouse Childhood Cancer Initiative through a co-expression network analysis. We identified six modules strongly associated with pediatric tumor histotypes that were functionally linked to developmental processes. Topological analyses highlighted that pediatric cancer predisposition genes and potential therapeutic targets were central regulators of cancer-histotype specific modules. A module was related to multiple pediatric malignancies with functions involved in DNA repair and cell cycle regulation. This canonical oncogenic module gathered most of the childhood cancer predisposition genes and clinically actionable genes. In pediatric acute leukemias, the driver genes were co-expressed in a module related to epigenetic and post-transcriptional processes, suggesting a critical role of these pathways in the progression of hematologic malignancies. This integrative pan-cancer study provides a thorough characterization of pediatric tumor-associated modules and paves the way for investigating novel candidate genes involved in childhood tumorigenesis.

BackgroundWith the development of precision oncology, Molecular Tumor Boards (MTB) are developing in many institutions. However, the implementation of MTB in routine clinical practice has still not been thoroughly studied.Material and methodsSince the first drugs approved for targeted therapies, patient tumor samples were centralized to genomic testing platforms. In our institution, all tumor samples have been analyzed since 2014 by Next Generation Sequencing (NGS). In 2015, we established a regional MTB to discuss patient cases with 1 or more alterations identified by NGS, in genes different from those related to drug approval. We conducted a retrospective comparative analysis to study whether our MTB increased the prescriptions of Molecular Targeted Therapies (MTT) and the inclusions of patients in clinical trials with MTT, in comparison with patients with available NGS data but no MTB discussion.ResultsIn 2014, 86 patients had UGA, but the results were not available to clinicians and not discussed in MTB. During the years 2015 and 2016, 113 patients with an UGA (unreferenced genomic alteration) were discussed in MTB. No patients with an UGA were included in 2014 in a clinical trial, versus 2 (2%) in 2015–2016. 13 patients with an UGA (12%) were treated in 2015–2016 with a MTT whereas in 2014, no patient (p = 0.001).ConclusionsIn this retrospective analysis, we showed that the association of large-scale genomic testing and MTB was feasible, and could increase the prescription of MTT. However, in routine clinical practice, the majority of patients with UGA still do not have access to MTT.

Accurate testing for epidermal growth factor receptor ( EGFR ) variants is essential for informing treatment decisions in non-small cell lung cancer (NSCLC). Automated diagnostic workflows may allow more streamlined initiation of targeted treatments, where appropriate, while comprehensive variant analysis is ongoing. FACILITATE, a real-world, prospective, multicenter, European study, evaluated performance and analytical turnaround time of the Idylla™ EGFR Mutation Test compared with local reference methods. Sixteen sites obtained formalin-fixed paraffin-embedded biopsy samples with ≥ 10% neoplastic cells from patients with NSCLC. Consecutive 5 μm sections from patient samples were tested for clinically relevant NSCLC-associated EGFR variants using the Idylla™ EGFR Mutation Test and local reference methods; performance (concordance) and analytical turnaround time were compared. Between January 2019 and November 2020, 1,474 parallel analyses were conducted. Overall percentage agreement was 97.7% [ n = 1,418; 95% confidence interval (CI): 96.8–98.3], positive agreement, 87.4% ( n = 182; 95% CI: 81.8–91.4) and negative agreement, 99.2% ( n = 1,236; 95% CI: 98.5–99.6). There were 38 (2.6%) discordant cases. Ninety percent of results were returned with an analytical turnaround time of within 1 week using the Idylla™ EGFR Mutation Test versus ∼22 days using reference methods. The Idylla™ EGFR Mutation Test performed well versus local methods and had shorter analytical turnaround time. The Idylla™ EGFR Mutation Test can thus support application of personalized medicine in NSCLC.

Mismatch repair deficiency (d-MMR)/microsatellite instability (MSI), KRAS, and BRAF mutational status are crucial for treating advanced colorectal cancer patients. Traditional methods like immunohistochemistry or polymerase chain reaction (PCR) can be challenged by artificial intelligence (AI) based on whole slide images (WSI) to predict tumor status. In this systematic review, we evaluated the role of AI in predicting MSI status, KRAS, and BRAF mutations in colorectal cancer. Studies published in PubMed up to June 2023 were included (n = 17), and we reported the risk of bias and the performance for each study. Some studies were impacted by the reduced number of slides included in the data set and the lack of external validation cohorts. Deep learning models for the d-MMR/MSI status showed a good performance in training cohorts (mean AUC = 0.89, [0.74–0.97]) but slightly less than expected in the validation cohort when available (mean AUC = 0.82, [0.63–0.98]). Contrary to the MSI status, the prediction of KRAS and BRAF mutations was less explored with a less robust methodology. The performance was lower, with a maximum of 0.77 in the training cohort, 0.58 in the validation cohort for KRAS, and 0.82 AUC in the training cohort for BRAF.

By analyzing the gene expression profile between tumor cells and revertant counterparts that have a suppressed malignant phenotype, we previously reported a significant down-regulation of translationally controlled tumor protein (TCTP) in the revertants. In the present study, we derived, by using the H1 parvovirus as a selective agent, revertants from three major solid cancers: colon, lung, and melanoma cell lines. These cells have a strongly suppressed malignant phenotype both in vitro and in vivo. The level of TCTP is decreased in most of the revertants. To verify whether inhibition of TCTP expression induces changes in the malignant phenotype, in the classical, well established model of \"flat reversion,\" v-src-transformed NIH3T3 cells were transfected with antisense TCTP. By inhibiting the expression of TCTP, the number of revertant cells was raised to 30%, instead of the reported rate for spontaneous flat revertants of 10-6. Because TCTP encodes for a histamine-releasing factor, we tested the hypothesis that inhibitors of the histaminic pathway could be effective against tumor cells. We show that some antihistaminic compounds (hydroxyzine and promethazine) and other pharmacological compounds with a related structure (including thioridazine and sertraline) kill tumor cells and significantly decrease the level of TCTP. All together, these data suggest that, with tumor reversion used as a working model, TCTP was identified as a target and drugs were selected that decrease its expression and kill tumor cells.

Siah proteins are E3 ubiquitin ligases. They are homologues of the Drosophila seven in absentia (Sina), a protein required for the R7 photoreceptor development. We have previously found that the expression of human siah-1 and its mouse homologue siah-1b are induced by p53 during apoptosis and tumor reversion. So far, no evidence that the siah-1b gene is a direct transcriptional target of p53 has been provided. In the present study we investigate this issue. Northern blot analysis with a specific probe demonstrates an increase in siah-1b transcription on activation of endogenous and inducible exogenous p53. To explore whether this effect is directly mediated by p53 we analyzed 20 kb of chromosome X DNA, containing the siah-1b locus. A p53-binding site was identified in the siah-1b promoter, located at nucleotides -2155/-2103 relative to the translational start site. This site is composed of two half-sites, conforming to the p53-binding consensus sequence but separated by a nonclassical 33-bp spacer. In luciferase assays, p53 induces a substantial increase in siah-1b promoter activity. Gel shift and DNase-I-footprinting studies, combined with mutational analysis and chromatin immunoprecipitation, indicate that p53 effectively binds the siah-1b promoter in vitro and in vivo. Thus, the siah-1b gene is a direct transcriptional target of p53.

The p53 tumor suppressor protein plays a crucial role in tumori-genesis by controlling cell-cycle progression and apoptosis. We have previously described a transcript designated tumor suppressor activated pathway-6 (TSAP6) that is up-regulated in the p53-inducible cell line, LTR6. Cloning of the murine and human full-length TSAP6 cDNA revealed that it encodes a 488-aa protein with five to six transmembrane domains. This gene is the murine and human homologue of the recently published rat pHyde. Antibodies raised against murine and human TSAP6 recognize a 50- to 55-kDa band induced by p53. Analysis of the TSAP6 promoter identified a functional p53-responsive element. Functional studies demonstrated that TSAP6 antisense cDNA diminished levels of the 50- to 55-kDa protein and decreased significantly the levels of p53-induced apoptosis. Furthermore, TSAP6 small interfering RNA inhibited apoptosis in TSAP6-overexpressing cells. Yeast two-hybrid analysis followed by GST/in vitro-transcribed/translated pull-down assays and in vivo coimmunoprecipitations revealed that TSAP6 associated with Nix, a proapoptotic Bcl-2-related protein and the Myt1 kinase, a negative regulator of the G2/M transition. Moreover, TSAP6 enhanced the susceptibility of cells to apoptosis and cooperated with Nix to exacerbate this effect. Cell-cycle studies indicated that TSAP6 could augment Myt1 activity. Overall, these data suggest that TSAP6 may act downstream to p53 to interface apoptosis and cell-cycle progression.

TSAP6 (tumor suppressor-activated pathway 6), also known as Steap3 , is a direct p53 transcriptional target gene. It regulates protein secretion, for example translationally controlled tumor protein (TCTP), which is implicated in tumor reversion. In keeping with the latter, we show herein that TSAP6 is a glycosylated protein present in the trans-Golgi network, endosomal–vesicular compartment and cytoplasmic membrane. To further investigate the physiological function of TSAP6, we have generated TSAP6-deficient mice. These mice exhibit microcytic anemia with abnormal reticulocyte maturation and deficient transferrin receptor downregulation, a process known to be dependent on exosomal secretion. Moreover, we provide direct evidence that exosome production is severely compromised in TSAP6-null cells. Finally, we show that the DNA damage-induced p53-dependent nonclassical exosomal secretory pathway is abrogated in TSAP6-null cells. Given the fact that exosomes are used as cell-free vaccines against cancer and that they could be involved in the biogenesis and spread of human immunodeficiency virus, it is important to understand their regulation. The results presented here provide the first genetic demonstration that exosome formation is a tightly controlled biological process dependent of TSAP6.