Comprehensive patient-level classification and quantification of driver events in TCGA PanCanAtlas cohorts

There is a growing need to develop novel therapeutics for targeted treatment of cancer. The prerequisite to success is the knowledge about which types of molecular alterations are predominantly driving tumorigenesis. To shed light onto this subject, we have utilized the largest database of human cancer mutations–TCGA PanCanAtlas, multiple established algorithms for cancer driver prediction (2020plus, CHASMplus, CompositeDriver, dNdScv, DriverNet, HotMAPS, OncodriveCLUSTL, OncodriveFML) and developed four novel computational pipelines: SNADRIF (Single Nucleotide Alteration DRIver Finder), GECNAV (Gene Expression-based Copy Number Alteration Validator), ANDRIF (ANeuploidy DRIver Finder) and PALDRIC (PAtient-Level DRIver Classifier). A unified workflow integrating all these pipelines, algorithms and datasets at cohort and patient levels was created. We have found that there are on average 12 driver events per tumour, of which 0.6 are single nucleotide alterations (SNAs) in oncogenes, 1.5 are amplifications of oncogenes, 1.2 are SNAs in tumour suppressors, 2.1 are deletions of tumour suppressors, 1.5 are driver chromosome losses, 1 is a driver chromosome gain, 2 are driver chromosome arm losses, and 1.5 are driver chromosome arm gains. The average number of driver events per tumour increases with age (from 7 to 15) and cancer stage (from 10 to 15) and varies strongly between cancer types (from 1 to 24). Patients with 1 and 7 driver events per tumour are the most frequent, and there are very few patients with more than 40 events. In tumours having only one driver event, this event is most often an SNA in an oncogene. However, with increasing number of driver events per tumour, the contribution of SNAs decreases, whereas the contribution of copy-number alterations and aneuploidy events increases.

ING Tumour Suppressors and ING Splice Variants as Coregulators of the Androgen Receptor Signalling in Prostate Cancer

Prevention and overcoming castration resistance of prostate cancer (PC) remains one of the main unsolved problems in modern oncology. Hence, many studies are focused on the investigation of novel androgen receptor (AR) regulators that could serve as potential drug targets in disease therapy. Among such factors, inhibitor of growth (ING) proteins were identified. Some ING proteins act as AR transcriptional coregulators, indicating their relevance for PC research. The ING family consists of five protein-coding genes from ING1 to ING5 and pseudogene INGX. The ING genes were revealed through their sequence homology to the first identified ING1 from an in vivo screen. ING factors are a part of histone modification complexes. With the help of the conserved plant homeodomain (PHD) motif, ING factors bind to Histone 3 Lysine 4 (H3K4) methylation mark with a stronger affinity to the highest methylation grade H3K4me3 and recruit histone acetyltransferases (HAT) and histone deacetylases (HDAC) to chromatin. ING1 and ING2 are core subunits of mSIN3a-HDAC corepressor complexes, whereas ING3–5 interact with different HAT complexes that serve as coactivators. ING members belong to type II tumour suppressors and are frequently downregulated in many types of malignancies, including PC. As the family name indicates, ING proteins are able to inhibit cell growth and tumour development via regulation of cell cycle and cancer-relevant pathways such as apoptosis, cellular senescence, DNA repair, cell migration, invasion, and angiogenesis. Many ING splice variants that enhance the diversity of ING activity were discovered. However, it seems that the existence of multiple ING splice variants is underestimated, since alternative splice variants, such as the AR coregulators ING1 and ING3, counteract full-length ING and thus play an opposite functional role. These results open a novel prospective investigation direction in understanding ING factors biology in PC and other malignancies.

Biological basis for novel mesothelioma therapies

Mesothelioma is an aggressive cancer that is associated with exposure to asbestos. Although asbestos is banned in several countries, including the UK, an epidemic of mesothelioma is predicted to affect middle-income countries during this century owing to their heavy consumption of asbestos. The prognosis for patients with mesothelioma is poor, reflecting a failure of conventional chemotherapy that has ultimately resulted from an inadequate understanding of its biology. However, recent work has revolutionised the study of mesothelioma, identifying genetic and pathophysiological vulnerabilities, including the loss of tumour suppressors, epigenetic dysregulation and susceptibility to nutrient stress. We discuss how this knowledge, combined with advances in immunotherapy, is enabling the development of novel targeted therapies.

Precision Therapy for Mesothelioma: Feasibility and New Opportunities

Malignant pleural mesotheliomas (MPMs) are characterised by their wide variation in natural history, ranging from minimally to highly aggressive, associated with both interpatient and intra-tumour genomic heterogeneity. Recent insights into the nature of this genetic variation, the identification of drivers, and the emergence of novel strategies capable of targeting vulnerabilities that result from the inactivation of key tumour suppressors suggest that new approaches to molecularly strategy therapy for mesothelioma may be feasible.

Comprehensive patient-level classification and quantification of driver events in TCGA PanCanAtlas cohorts

BackgroundThere is a growing need to develop novel therapeutics for targeted treatment of cancer. The prerequisite to success is the knowledge about which types of molecular alterations are predominantly driving tumorigenesis – single nucleotide (SNA) or copy number (CNA), in oncogenes or in tumour suppressors, gains or losses of full chromosomes or chromosomal arms (aneuploidy). However, the number and proportion of various types of driver events per tumour is still not clear, neither for cancer in general, nor for individual cancer types, stages and patient demographics (age and gender).MethodsTo shed light onto this subject, we have utilized the largest database of human cancer mutations – TCGA PanCanAtlas, multiple established algorithms for cancer driver prediction (2020plus, CHASMplus, CompositeDriver, dNdScv, DriverNet, HotMAPS, IntOGen Plus, OncodriveCLUSTL, OncodriveFML) and developed four novel computational pipelines: SNADRIF (SNA DRIver Finder), GECNAV (Gene Expression-based CNA Validator), ANDRIF (ANeuploidy DRIver Finder) and PALDRIC (PAtient-Level DRIver Classifier). A unified workflow integrating all these pipelines, algorithms and datasets at cohort and patient levels was created.ResultsBy integrating results of various driver prediction algorithms, we have found that there are on average 20 driver events per tumour, of which 1.5 are hyperactivating SNAs in oncogenes, 10.5 are amplifications of oncogenes, 2 are homozygous inactivating SNAs or deletions of tumour suppressors, 1.5 are driver chromosome losses, 2 are driver chromosome gains, 1 is a driver chromosome arm loss, and 1.5 are driver chromosome arm gains. The average number of driver events per tumour varies strongly between cancer types, from 1.7 in thyroid carcinoma to 42.4 in ovarian carcinoma. In females, the number of driver events increases most dramatically until the age of menopause (50 y.o.), whereas in males until 70 y.o. Moreover, in females, the number of driver events increases abruptly from Stage I to Stage II, after which stays more or less constant, and this increase is due to CNAs and aneuploidy but not due to SNAs. In tumours having only one driver event, this event is a SNA in an oncogene. However, with increasing number of driver events per tumour, the contribution of SNAs and tumour suppressor events decreases, whereas the contribution of oncogene amplifications and aneuploidy events increases. Patients with two driver events per tumour are the most frequent, and there are very few patients with more than 50 events.ConclusionsAs half of all driver events in a patient’s tumour appear to be amplifications of oncogenes, we suggest that future therapeutics development efforts should be focused on targeting this alteration type. Therapies aimed at gains and losses of chromosomal arms and whole chromosomes also appear very promising. On the other hand, drugs aiming at point mutations and tumour suppressors are predicted to be less successful. Overall, our results provide valuable insights into the extent of driver alterations of different types in human tumours and suggest optimal targets for candidate therapeutics.

NFIA and NFIB function as tumour suppressors in high-grade glioma in mice

Nuclear factor one (NFI) transcription factors are implicated in both brain development and cancer in mice and humans and play an essential role in glial differentiation. NFI expression is reduced in human astrocytoma samples, particularly those of higher grade, whereas over-expression of NFI protein can induce the differentiation of glioblastoma cells within human tumour xenografts and in glioblastoma cell lines in vitro. These data indicate that NFI proteins may act as tumour suppressors in glioma. To test this hypothesis, we generated complex mouse genetic crosses involving six alleles to target gene deletion of known tumour suppressor genes that induce endogenous high-grade glioma in mice, and overlaid this with loss of function Nfi mutant alleles, Nfia and Nfib, a reporter transgene and an inducible Cre allele. Deletion of Nfi resulted in reduced survival time of the mice, increased tumour load and a more aggressive tumour phenotype than observed in glioma mice with normal expression of NFI. Together, these data indicate that NFI genes represent a credible target for both diagnostic analyses and therapeutic strategies to combat high-grade glioma.