scholarly journals Identifying common transcriptome signatures of cancer by interpreting deep learning models

2021 ◽  
Author(s):  
Anupama Jha ◽  
Mathieu Quesnel-Vallières ◽  
Andrei Thomas-Tikhonenko ◽  
Kristen W. Lynch ◽  
Yoseph Barash
Keyword(s):  
Solid Tumor ◽  
Cancer Biology ◽  
Splice Junction ◽  
Cellular Functions ◽  
Protein Coding ◽  
Cancer Pathways ◽  
Molecular Features ◽  
Independent Test Dataset ◽  
Cancer Types ◽  
Tumor Types

Cancer is a set of diseases characterized by unchecked cell proliferation and invasion of surrounding tissues. The many genes that have been genetically associated with cancer or shown to directly contribute to oncogenesis vary widely between tumor types, but common gene signatures that relate to core cancer pathways have also been identified, signifying that cancer cases display common hallmark molecular features. It is not clear however whether there exist additional sets of genes or transcriptomic features that are less well known in cancer biology but that are also commonly deregulated across several cancer types. Here, in order to agnostically identify transcriptomic features that are commonly shared between cancer types, we used RNA-Seq datasets encompassing thousands of samples from 19 healthy tissue types and 18 solid tumor types to train three feed-forward neural networks, based either on protein-coding gene expression, lncRNA expression or splice junction use, to distinguish between healthy and tumor samples. All three models achieve high precision, recall and accuracy on test sets derived from 13 datasets used during training and on an independent test dataset, indicating that our models recognize transcriptome signatures that are consistent across tumors. Analysis of attribution values extracted from our models reveals that genes that are commonly altered in cancer by expression or splicing variations are under strong evolutionary and selective constraints, suggesting that they have important cellular functions. Importantly, we found that genes composing our cancer transcriptome signatures are not frequently affected by mutations or genomic alterations and that their functions differ widely from the genes genetically associated with cancer. Finally, our results also highlighted that deregulation of RNA-processing genes and aberrant splicing are pervasive features across a large array of solid tumor types. The transcriptomic features that we highlight here define cancer signatures that may reflect causal variations or consequences of disease state, or a combination of both.

scholarly journals Agonism of CD11b reprograms innate immunity to sensitize pancreatic cancer to immunotherapies

2019 ◽  
Vol 11 (499) ◽  
pp. eaau9240 ◽  
Author(s):  
Roheena Z. Panni ◽  
John M. Herndon ◽  
Chong Zuo ◽  
Samarth Hegde ◽  
Graham D. Hogg ◽  
...  
Keyword(s):  
Checkpoint Inhibitors ◽  
Myeloid Cell ◽  
Ductal Adenocarcinoma ◽  
Cellular Functions ◽  
Major Mechanism ◽  
Cell Responses ◽  
Partial Activation ◽  
Cell Immunity ◽  
Cancer Types ◽  
Tumor Types

Although checkpoint immunotherapies have revolutionized the treatment of cancer, not all tumor types have seen substantial benefit. Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy in which very limited responses to immunotherapy have been observed. Extensive immunosuppressive myeloid cell infiltration in PDAC tissues has been postulated as a major mechanism of resistance to immunotherapy. Strategies concomitantly targeting monocyte or granulocyte trafficking or macrophage survival, in combination with checkpoint immunotherapies, have shown promise in preclinical studies, and these studies have transitioned into ongoing clinical trials for the treatment of pancreatic and other cancer types. However, compensatory actions by untargeted monocytes, granulocytes, and/or tissue resident macrophages may limit the therapeutic efficacy of such strategies. CD11b/CD18 is an integrin molecule that is highly expressed on the cell surface of these myeloid cell subsets and plays an important role in their trafficking and cellular functions in inflamed tissues. Here, we demonstrate that the partial activation of CD11b by a small-molecule agonist (ADH-503) leads to the repolarization of tumor-associated macrophages, reduction in the number of tumor-infiltrating immunosuppressive myeloid cells, and enhanced dendritic cell responses. These actions, in turn, improve antitumor T cell immunity and render checkpoint inhibitors effective in previously unresponsive PDAC models. These data demonstrate that molecular agonism of CD11b reprograms immunosuppressive myeloid cell responses and potentially bypasses the limitations of current clinical strategies to overcome resistance to immunotherapy.

Non-coding RNAs: the cancer genome dark matter that matters!

2017 ◽  
Vol 55 (5) ◽  
Author(s):  
Hui Ling ◽  
Leonard Girnita ◽  
Octavian Buda ◽  
George A. Calin
Keyword(s):  
Cancer Biology ◽  
Drug Targets ◽  
Cancer Genome ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Sequence Complementarity ◽  
Cancer Types ◽  
Non Coding Rnas ◽  
The Many ◽  
Carcinoma Renal Cell

AbstractProtein-coding genes comprise only 3% of the human genome, while the genes that are transcribed into RNAs but do not code for proteins occupy majority of the genome. Once considered as biological darker matter, non-coding RNAs are now being recognized as critical regulators in cancer genome. Among the many types of non-coding RNAs, microRNAs approximately 20 nucleotides in length are best characterized and their mechanisms of action are well generalized. microRNA exerts oncogenic or tumor suppressor function by regulation of protein-coding genes via sequence complementarity. The expression of microRNA is aberrantly regulated in all cancer types, and both academia and biotech companies have been keenly pursuing the potential of microRNA as cancer biomarker for early detection, prognosis, and therapeutic response. The key involvement of microRNAs in cancer also prompted interest on exploration of therapeutic values of microRNAs as anticancer drugs and drug targets. MRX34, a liposome-formulated miRNA-34 mimic, developed by Mirna Therapeutics, becomes the first microRNA therapeutic entering clinical trial for the treatment of hepatocellular carcinoma, renal cell carcinoma, and melanoma. In this review, we presented a general overview of microRNAs in cancer biology, the potential of microRNAs as cancer biomarkers and therapeutic targets, and associated challenges.

scholarly journals The expanding regulatory universe of p53 in gastrointestinal cancer

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 756 ◽  
Author(s):  
Andrew Fesler ◽  
Ning Zhang ◽  
Jingfang Ju
Keyword(s):  
Gastrointestinal Cancer ◽  
Regulatory Network ◽  
Cancer Biology ◽  
Control Cell ◽  
Cellular Functions ◽  
Protein Coding ◽  
Growth Environment ◽  
Damage Repair ◽  
Non Coding Rnas ◽  
And Function

Tumor suppresser geneTP53is one of the most frequently deleted or mutated genes in gastrointestinal cancers. As a transcription factor, p53 regulates a number of important protein coding genes to control cell cycle, cell death, DNA damage/repair, stemness, differentiation and other key cellular functions. In addition, p53 is also able to activate the expression of a number of small non-coding microRNAs (miRNAs) through direct binding to the promoter region of these miRNAs.  Many miRNAs have been identified to be potential tumor suppressors by regulating key effecter target mRNAs. Our understanding of the regulatory network of p53 has recently expanded to include long non-coding RNAs (lncRNAs). Like miRNA, lncRNAs have been found to play important roles in cancer biology.  With our increased understanding of the important functions of these non-coding RNAs and their relationship with p53, we are gaining exciting new insights into the biology and function of cells in response to various growth environment changes. In this review we summarize the current understanding of the ever expanding involvement of non-coding RNAs in the p53 regulatory network and its implications for our understanding of gastrointestinal cancer.

scholarly journals MutSignatures: An R Package for Extraction and Analysis of Cancer Mutational Signatures

2020 ◽  
Author(s):  
Damiano Fantini ◽  
Vania Vidimar ◽  
Yanni Yu ◽  
Salvatore Condello ◽  
Joshua J. Meeks
Keyword(s):  
Cancer Biology ◽  
Somatic Mutations ◽  
R Package ◽  
Mutational Signatures ◽  
Computational Framework ◽  
Molecular Features ◽  
Dna Mutations ◽  
Repair Mechanisms ◽  
Cancer Types ◽  
Random Patterns

ABSTRACTCancer cells accumulate somatic mutations as result of DNA damage and inaccurate repair mechanisms. Different genetic instability processes result in distinct non-random patterns of DNA mutations, also known as mutational signatures. We developed mutSignatures, an integrated R-based computational framework aimed at deciphering DNA mutational signatures. Our software provides advanced functions for importing DNA variants, computing mutation types, and extracting mutational signatures via non-negative matrix factorization. We applied mutSignatures to analyze somatic mutations found in smoking-related cancer datasets. We characterized mutational signatures that were consistent with those reported before in independent investigations. Our work demonstrates that selected mutational signatures correlated with specific clinical and molecular features across different cancer types, and revealed complementarity of specific mutational patterns that has not previously been identified. In conclusion, we propose mutSignatures as a powerful open-source tool for detecting the molecular determinants of cancer and gathering insights into cancer biology and treatment.

scholarly journals Rebelled epigenome: histone H3S10 phosphorylation and H3S10 kinases in cancer biology and therapy

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Dorota Komar ◽  
Przemyslaw Juszczynski
Keyword(s):  
Malignant Transformation ◽  
Cancer Biology ◽  
Main Body ◽  
Cellular Functions ◽  
Post Translational Modifications ◽  
Regulatory Machinery ◽  
Initiation And Propagation ◽  
Important Player ◽  
Cancer Types ◽  
Main Components

Abstract Background With the discovery that more than half of human cancers harbor mutations in chromatin proteins, deregulation of epigenetic mechanisms has been recognized a hallmark of malignant transformation. Post-translational modifications (PTMs) of histone proteins, as main components of epigenetic regulatory machinery, are also broadly accepted as therapeutic target. Current “epigenetic” therapies target predominantly writers, erasers and readers of histone acetylation and (to a lesser extent) methylation, leaving other types of PTMs largely unexplored. One of them is the phosphorylation of serine 10 on histone H3 (H3S10ph). Main body H3S10ph is emerging as an important player in the initiation and propagation of cancer, as it facilitates cellular malignant transformation and participates in fundamental cellular functions. In normal cells this histone mark dictates the hierarchy of additional histone modifications involved in the formation of protein binding scaffolds, transcriptional regulation, blocking repressive epigenetic information and shielding gene regions from heterochromatin spreading. During cell division, this mark is essential for chromosome condensation and segregation. It is also involved in the function of specific DNA–RNA hybrids, called R-loops, which modulate transcription and facilitate chromosomal instability. Increase in H3S10ph is observed in numerous cancer types and its abundance has been associated with inferior prognosis. Many H3S10-kinases, including MSK1/2, PIM1, CDK8 and AURORA kinases, have been long considered targets in cancer therapy. However, since these proteins also participate in other critical processes, including signal transduction, apoptotic signaling, metabolic fitness and transcription, their chromatin functions are often neglected. Conclusions H3S10ph and enzymes responsible for deposition of this histone modification are important for chromatin activity and oncogenesis. Epigenetic-drugs targeting this axis of modifications, potentially in combination with conventional or targeted therapy, provide a promising angle in search for knowledge-driven therapeutic strategies in oncology.

scholarly journals JAMMIT Analysis Defines 2 Semi-Independent Immune Processes Common to 29 Solid Tumors

2021 ◽  
Author(s):  
Emory Zitello ◽  
Michael Vo ◽  
Shaoqiu Chen ◽  
Scott Bowler ◽  
Vedbar Khadka ◽  
...  
Keyword(s):  
Solid Tumors ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Published Data ◽  
Molecular Features ◽  
Solid Malignancies ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Bioinformatic Approaches ◽  
Tumor Types

AbstractImmunophenotype of solid tumors has relevance to cancer immunotherapy, as not all patients respond optimally to treatment utilizing monoclonal antibodies. Bioinformatic studies have failed to clearly identify tumor immunophenotype in a way that encompasses a wide variety of tumor types and highlights fundamental differences among them, complicating prediction of patient clinical response. The novel JAMMIT algorithm was used to analyze mRNA data for 33 cancer types in The Cancer Genome Atlas (TCGA). We found that B cells and T cells constitute the principal source of variation in most patient cohorts, and that virtually all solid malignancies formed three hierarchical clustering patterns with similar molecular features. The second main source of variability in transcriptomic studies we attribute to monocytes. We identified the three tumor types as TC1-mediated, TC17-mediated and non-immunogenic immunophenotypes and used a 3-gene signature to approximate infiltration by agranulocytes. Methods of in silico validation such as pathway analysis, Cibersort and published data from treated cohorts were used to substantiate these findings. Monocytic infiltrate is found to be related to patient survival according to immunophenotype, important differences in some solid tumors are identified and deficiencies of common bioinformatic approaches relevant to diagnosis are detailed by this work.

scholarly journals Distinct signatures of codon and codon pair usage in 32 primary tumor types in the novel database CancerCoCoPUTs for cancer-specific codon usage

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Douglas Meyer ◽  
Jacob Kames ◽  
Haim Bar ◽  
Anton A. Komar ◽  
Aikaterini Alexaki ◽  
...  
Keyword(s):  
Gene Expression ◽  
Codon Usage ◽  
Solid Tumor ◽  
Synonymous Codon ◽  
Lobular Carcinoma ◽  
Tumor Type ◽  
Codon Preference ◽  
Codon Pair ◽  
Cancer Types ◽  
Tumor Types

Abstract Background Gene expression is highly variable across tissues of multi-cellular organisms, influencing the codon usage of the tissue-specific transcriptome. Cancer disrupts the gene expression pattern of healthy tissue resulting in altered codon usage preferences. The topic of codon usage changes as they relate to codon demand, and tRNA supply in cancer is of growing interest. Methods We analyzed transcriptome-weighted codon and codon pair usage based on The Cancer Genome Atlas (TCGA) RNA-seq data from 6427 solid tumor samples and 632 normal tissue samples. This dataset represents 32 cancer types affecting 11 distinct tissues. Our analysis focused on tissues that give rise to multiple solid tumor types and cancer types that are present in multiple tissues. Results We identified distinct patterns of synonymous codon usage changes for different cancer types affecting the same tissue. For example, a substantial increase in GGT-glycine was observed in invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC), and mixed invasive ductal and lobular carcinoma (IDLC) of the breast. Change in synonymous codon preference favoring GGT correlated with change in synonymous codon preference against GGC in IDC and IDLC, but not in ILC. Furthermore, we examined the codon usage changes between paired healthy/tumor tissue from the same patient. Using clinical data from TCGA, we conducted a survival analysis of patients based on the degree of change between healthy and tumor-specific codon usage, revealing an association between larger changes and increased mortality. We have also created a database that contains cancer-specific codon and codon pair usage data for cancer types derived from TCGA, which represents a comprehensive tool for codon-usage-oriented cancer research. Conclusions Based on data from TCGA, we have highlighted tumor type-specific signatures of codon and codon pair usage. Paired data revealed variable changes to codon usage patterns, which must be considered when designing personalized cancer treatments. The associated database, CancerCoCoPUTs, represents a comprehensive resource for codon and codon pair usage in cancer and is available at https://dnahive.fda.gov/review/cancercocoputs/. These findings are important to understand the relationship between tRNA supply and codon demand in cancer states and could help guide the development of new cancer therapeutics.

scholarly journals Multi-omics analysis reveals contextual tumor suppressive and oncogenic gene modules within the acute hypoxic response

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zdenek Andrysik ◽  
Heather Bender ◽  
Matthew D. Galbraith ◽  
Joaquin M. Espinosa
Keyword(s):  
Cancer Biology ◽  
Acute Hypoxia ◽  
Transcriptional Response ◽  
Adaptation To Hypoxia ◽  
Mtor Inhibition ◽  
Collagen Remodeling ◽  
Acute Response ◽  
Relative Contribution ◽  
Transcriptional Changes ◽  
Cancer Types

AbstractCellular adaptation to hypoxia is a hallmark of cancer, but the relative contribution of hypoxia-inducible factors (HIFs) versus other oxygen sensors to tumorigenesis is unclear. We employ a multi-omics pipeline including measurements of nascent RNA to characterize transcriptional changes upon acute hypoxia. We identify an immediate early transcriptional response that is strongly dependent on HIF1A and the kinase activity of its cofactor CDK8, includes indirect repression of MYC targets, and is highly conserved across cancer types. HIF1A drives this acute response via conserved high-occupancy enhancers. Genetic screen data indicates that, in normoxia, HIF1A displays strong cell-autonomous tumor suppressive effects through a gene module mediating mTOR inhibition. Conversely, in advanced malignancies, expression of a module of HIF1A targets involved in collagen remodeling is associated with poor prognosis across diverse cancer types. In this work, we provide a valuable resource for investigating context-dependent roles of HIF1A and its targets in cancer biology.

Role of long interspersed nuclear element-1 in the regulation of chromatin landscapes and genome dynamics

2021 ◽  
pp. 153537022110312
Author(s):  
Kenneth S Ramos ◽  
Pasano Bojang ◽  
Emma Bowers
Keyword(s):  
Cancer Biology ◽  
Mobile Element ◽  
Cancer Diagnostics ◽  
Regulatory Control ◽  
Full Potential ◽  
Genome Dynamics ◽  
Human Illness ◽  
Cancer Types ◽  
Stressful Environments

LINE-1 retrotransposon, the most active mobile element of the human genome, is subject to tight regulatory control. Stressful environments and disease modify the recruitment of regulatory proteins leading to unregulated activation of LINE-1. The activation of LINE-1 influences genome dynamics through altered chromatin landscapes, insertion mutations, deletions, and modulation of cellular plasticity. To date, LINE-1 retrotransposition has been linked to various cancer types and may in fact underwrite the genetic basis of various other forms of chronic human illness. The occurrence of LINE-1 polymorphisms in the human population may define inter-individual differences in susceptibility to disease. This review is written in honor of Dr Peter Stambrook, a friend and colleague who carried out highly impactful cancer research over many years of professional practice. Dr Stambrook devoted considerable energy to helping others live up to their full potential and to navigate the complexities of professional life. He was an inspirational leader, a strong advocate, a kind mentor, a vocal supporter and cheerleader, and yes, a hard critic and tough friend when needed. His passionate stand on issues, his witty sense of humor, and his love for humanity have left a huge mark in our lives. We hope that that the knowledge summarized here will advance our understanding of the role of LINE-1 in cancer biology and expedite the development of innovative cancer diagnostics and treatments in the ways that Dr Stambrook himself had so passionately envisioned.

scholarly journals Non-Coding RNAs as Prognostic Markers for Endometrial Cancer

2021 ◽  
Vol 22 (6) ◽  
pp. 3151 ◽  
Author(s):  
Roberto Piergentili ◽  
Simona Zaami ◽  
Anna Franca Cavaliere ◽  
Fabrizio Signore ◽  
Giovanni Scambia ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Prognostic Markers ◽  
Classification Systems ◽  
Prognostic Role ◽  
Protein Coding ◽  
Pathological Characteristics ◽  
Epigenetic Events ◽  
Cancer Types ◽  
Non Coding Rnas

Endometrial cancer (EC) has been classified over the years, for prognostic and therapeutic purposes. In recent years, classification systems have been emerging not only based on EC clinical and pathological characteristics but also on its genetic and epigenetic features. Noncoding RNAs (ncRNAs) are emerging as promising markers in several cancer types, including EC, for which their prognostic value is currently under investigation and will likely integrate the present prognostic tools based on protein coding genes. This review aims to underline the importance of the genetic and epigenetic events in the EC tumorigenesis, by expounding upon the prognostic role of ncRNAs.

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