Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation

The Immune Landscape of Cancer

We performed an extensive immunogenomic anal-ysis of more than 10,000 tumors comprising 33diverse cancer types by utilizing data compiled byTCGA. Across cancer types, we identified six im-mune subtypes\u2014wound healing, IFN-gdominant,inflammatory, lymphocyte depleted, immunologi-cally quiet, and TGF-bdominant\u2014characterized bydifferences in macrophage or lymphocyte signa-tures, Th1:Th2 cell ratio, extent of intratumoral het-erogeneity, aneuploidy, extent of neoantigen load,overall cell proliferation, expression of immunomod-ulatory genes, and prognosis. Specific drivermutations correlated with lower (CTNNB1,NRAS,orIDH1) or higher (BRAF,TP53,orCASP8) leukocytelevels across all cancers. Multiple control modalitiesof the intracellular and extracellular networks (tran-scription, microRNAs, copy number, and epigeneticprocesses) were involved in tumor-immune cell inter-actions, both across and within immune subtypes.Our immunogenomics pipeline to characterize theseheterogeneous tumors and the resulting data areintended to serve as a resource for future targetedstudies to further advance the field

Molecular characterization and clinical relevance of metabolic expression subtypes in human cancers.

Metabolic reprogramming provides critical information for clinical oncology. Using molecular data of 9,125 patient samples from The Cancer Genome Atlas, we identified tumor subtypes in 33 cancer types based on mRNA expression patterns of seven major metabolic processes and assessed their clinical relevance. Our metabolic expression subtypes correlated extensively with clinical outcome: subtypes with upregulated carbohydrate, nucleotide, and vitamin/cofactor metabolism most consistently correlated with worse prognosis, whereas subtypes with upregulated lipid metabolism showed the opposite. Metabolic subtypes correlated with diverse somatic drivers but exhibited effects convergent on cancer hallmark pathways and were modulated by highly recurrent master regulators across cancer types. As a proof-of-concept example, we demonstrated that knockdown of SNAI1 or RUNX1—master regulators of carbohydrate metabolic subtypes-modulates metabolic activity and drug sensitivity. Our study provides a system-level view of metabolic heterogeneity within and across cancer types and identifies pathway cross-talk, suggesting related prognostic, therapeutic, and predictive utility

Immunothérapie antitumorale : étude de l'efficacité et de l'innocuité d'un vaccin à base de mélanine

Les vaccins thérapeutiques représentent une stratégie thérapeutique prometteuse contre le cancer. Les vaccins peptidiques sont en particulier intéressants en raison de leur facilité de production. De plus, les récents progrès en matière de séquençage et analyse bio-informatique fournissent un nombre toujours croissant d'épitopes spécifiquement associés aux tumeurs (néoantigènes). Divers modèles précliniques ont montré des résultats encourageants, mais l'efficacité des vaccins peptidiques lors des essais cliniques sont restés jusqu'à présent décevants. En effet, les vaccins dirigés contre les cancers doivent surmonter des obstacles essentiels pour obtenir un bénéfice clinique, parmi lesquels les plus importants sont : (i) la faible immunogenicité des antigènes tumoraux, (ii) la petite quantité d'antigènes qui arrive aux tissus lymphoïdes secondaires, (iii) la nature immunosuppressive du microenvironnement tumoral, (iv) le phénomène dit d'immunoediting, dans lequel la tumeur perd l'expression de l'antigène. Dans ce contexte, l'optimisation de la formulation vaccinale augmente les chances d'efficacité anti-tumorale. Notre laboratoire a développé une nouvelle stratégie vaccinale à base de mélanine synthétique (à partir de L-DOPA) et CpG oligodeoxynucleotide comme adjuvant. Le but général de ce projet de thèse est d'apporter des données supplémentaires concernant l'efficacité et les mécanismes de cette approche, avec deux objectifs spécifiques : (i) comparer l'efficacité de la formulation vaccinale à base de mélanine et CpG avec celle de la formulation classique à base d'IFA (incomplete Freund's adjuvant) et CpG ; (ii) éclaircir les mécanismes d'action de ce vaccin. Le premier article rapporte les études d'efficacité du vaccin à base de mélanine dans deux modèles tumoraux : E.G7-OVA (lignée cellulaire E.G7 transfectée avec ovalbumine) et MC38 qui exprime spontanément le neoantigène mAdpgk. Le vaccin à base de mélanine s'est révélé efficace pour stimuler une forte réponse cytotoxique contre ces deux antigènes, de façon significativement plus élevée qu'avec le vaccin à base d'IFA et CpG. Dans le modèle thérapeutique de E.G7-OVA, le vaccin à base de mélanine a montré un effet anti-tumoral significatif, contrairement au vaccin à base d'IFA et CpG. En revanche, nous n'avons pas observé d'effet anti-tumoral dans le modèle MC38, malgré une forte réponse CD8+ spécifique périphérique. Cet échec était lié à une faible présentation de l'antigène par les cellules cancéreuse, une cause très commune de résistance observée dans les essais cliniques par immunothérapie. Le second papier inclut les études explorant les mécanismes d'action de la mélanine synthétique. Globalement, la mélanine semble agir comme transporteur pour les peptides, leur permettant d'arriver efficacement au ganglion drainant la zone d'injection et d'y rester jusqu'à 3 semaines après l'immunisation. Aucun effet immunostimulant direct de la mélanine synthétique n'a été observé sur les principales cellules présentatrices d'antigène in vitro (cellules dendritiques et macrophages murins dérivés de la moelle osseuse). En conclusion, le vaccin à base de mélanine synthétique et CpG est une stratégie efficace pour déclencher une réponse CD8+ contre des peptides longs comme courts dans un contexte tumoral et son efficacité s'est révélée supérieure à la formulation IFA et CpG. Cet effet est principalement dû à une activité de carrier de la mélanine synthétique qui permet aux peptides d'atteindre efficacement les ganglions lymphatiques et y rester jusqu'à 3 semaines après l'injection. L'absence d'effet immunostimulant direct de la mélanine synthétique souligne le besoin d'inclure un adjuvant immunostimulant (comme les CpG) dans la formulation vaccinale.Therapeutic cancer vaccines represent an attractive strategy to trigger immune response against cancer cells. Peptide cancer vaccine have especially attracted attention given their low cost and easy manufacturing. In addition, the recent advances in sequencing and bioinformatic analysis are providing an increasing number of tumor-specific epitopes. However, despite the encouraging results in preclinical models, subunit vaccines with conventional adjuvants have not yet reached significant clinical efficacy. Cancer vaccines are indeed facing several substantial obstacles, including (i) the poor immunogenicity of tumor antigens, (ii) the low amount of antigens that reaches the secondary lymphoid tissues, (iii) the suppressive nature of the tumor microenvironment and the general impairment of the immune system in cancer patients, and (iv) the immunoediting that often leads to tumor escape by loss of antigen expression on cancer cells. In this framework, the optimization of vaccine formulation is crucial to obtain an effective anti-tumor response, and the combination of an immunostimulatory agent and a delivery system to improve the target of APCs (antigen-presenting cells) is an interesting strategy, especially for peptide vaccines. Our laboratory developed a novel strategy of peptide cancer vaccine that uses a synthetic melanin (from L-DOPA) and CpG oligodeoxynucleotide as adjuvants. The general purpose of my thesis has been to provide some additional data about this vaccine approach, with two specific objectives: (i) to compare the efficacy of the melanin-based vaccine with classic vaccine formulations in tumor mouse models and (ii) to elucidate the immune mechanisms of this vaccine. The first article explored the efficacy of L-DOPA melanin-based (peptide-melanin + CpG) in two tumor models: E.G7-OVA (E.G7 cell line transfected with ovalbumin) and MC38 that spontaneously express the neoantigen mAdpgk. The L-DOPA melanin-based vaccine has shown a stronger CTL response against both antigens compared with the classic IFA-based formulation. In a therapeutic setting, only L-DOPA melanin-based vaccine proved an anti-tumor efficacy in E.G7-OVA model. In the MC38 model, the vaccine did not significantly inhibit the tumor growth, despite a strong peripheral CTL response, likely because of a poor presentation of mAdpgk epitope by cancer cells, which is a common issue to face with in clinics. The second paper investigated the mechanisms of action of L-DOPA melanin within the peptide vaccine formulation. We showed that L-DOPA melanin efficiently reach the draining lymph node and probably to remain up to 3 weeks, making it likely that melanin acts as carrier for antigen. No direct immunostimulatory effect of L-DOPA melanin was observed upon the main antigen-presenting cells in vitro: murine bone marrow derived dendritic cells and macrophages. In conclusion, L-DOPA melanin-based vaccine provides an efficient strategy to trigger cytotoxic responses against short and long synthetic peptides for tumor immunotherapy and compared favorably to the classic combination of IFA and Toll-like receptor 9 (TLR9) agonist in mice. L-DOPA melanin is likely to act as a carrier for peptides, allowing them to efficiently reach and probably to remain up to 3 weeks into lymph nodes. No direct immunomodulatory effect was instead found, underlying the need for an immunostimulatory agent such as TLR9 agonist in the vaccine formulation