Molecular diagnosis of human cancer type by gene expression profiles and independent component analysis

2005 ◽  
Vol 13 (12) ◽  
pp. 1303-1311 ◽  
Author(s):  
Xue Wu Zhang ◽  
Yee Leng Yap ◽  
Dong Wei ◽  
Feng Chen ◽  
Antoine Danchin
2013 ◽  
Vol 106 (3) ◽  
pp. 397-403 ◽  
Author(s):  
Hélène Riquier ◽  
Anne-Catherine Wera ◽  
Anne-Catherine Heuskin ◽  
Olivier Feron ◽  
Stéphane Lucas ◽  
...  

2018 ◽  
Author(s):  
Laura Cantini ◽  
Ulykbek Kairov ◽  
Aurélien de Reyniès ◽  
Emmanuel Barillot ◽  
François Radvanyi ◽  
...  

AbstractMotivationMatrix factorization methods are widely exploited in order to reduce dimensionality of transcriptomic datasets to the action of few hidden factors (metagenes). Applying such methods to similar independent datasets should yield reproducible inter-series outputs, though it was never demonstrated yet.ResultsWe systematically test state-of-art methods of matrix factorization on several transcriptomic datasets of the same cancer type. Inspired by concepts of evolutionary bioinformatics, we design a new framework based on Reciprocally Best Hit (RBH) graphs in order to benchmark the method’s reproducibility. We show that a particular protocol of application of Independent Component Analysis (ICA), accompanied by a stabilisation procedure, leads to a significant increase in the inter-series output reproducibility. Moreover, we show that the signals detected through this method are systematically more interpretable than those of other state-of-art methods. We developed a user-friendly tool BIODICA for performing the Stabilized ICA-based RBH meta-analysis. We apply this methodology to the study of colorectal cancer (CRC) for which 14 independent publicly available transcriptomic datasets can be collected. The resulting RBH graph maps the landscape of interconnected factors that can be associated to biological processes or to technological artefacts. These factors can be used as clinical biomarkers or robust and tumor-type specific transcriptomic signatures of tumoral cells or tumoral microenvironment. Their intensities in different samples shed light on the mechanistic basis of CRC molecular subtyping.AvailabilityThe BIODICA tool is available from https://github.com/LabBandSB/[email protected] and [email protected] informationSupplementary data are available at Bioinformatics online.


Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 2-2
Author(s):  
Arpan A. Sinha ◽  
Pilar I. Andrade ◽  
Courtney Sansam ◽  
Megan Malone-Perez ◽  
Christopher Sansam ◽  
...  

MYCis a key oncogene overexpressed by many cancers, however, its oncogenic mechanisms are poorly understood. MYC is also central to acute lymphoblastic leukemia (ALL), the most common and second most lethal pediatric malignancy. Much of MYC's oncogenicity has been attributed to its transcription factor function, but data suggest MYC also deregulates replication in transcription-independent fashion. As a known master regulator of cancer transcriptomes and epigenomes, we hypothesize that MYC dramatically alters both gene expression and replication timing (non-random spatiotemporal process where some part of the genome replicates early, and other late) in both types of ALL - B-ALL and T-ALL. Conceivably, MYC exerts oncogenic effects upon the ALL transcription and replication programs, with some changes shared by B- and T-ALL, and others unique to only one. We aim to address two novel questions not been investigated before. First, in ALL, do the same genetic loci show aberrant RNA transcriptionandDNA replication? Second, how similar are the affected loci in two closely-related, yet distinct, ALL types driven by the same oncogene? The basis of our project is a unique double-transgenicrag2:hMYC,lck:GFPzebrafish pre-clinical model we established, which is the only animal model proven to develop both B-ALL and T-ALL. We previously showed that gene expression profiles (GEP) differentiating zebrafish B- and T-ALL also distinguish human B- and T-ALL, making this an ideal model system to study human ALL. In this model, B-ALL and T-ALL are induced by human MYC(hMYC) regulated by aD.rerio(zebrafish)rag2promoter.Since B and T lymphoblasts both expressrag2, both lineages over-express MYC, causing highly-penetrant B- and T-ALL. Differential activity of aD. rerio lckpromoter causes B cells to fluoresce dimly and T cells to fluoresce brightly, allowing us to identify and purify B-ALL and T-ALL by fluorescent microscopy and fluorescence-based flow cytometry, respectively. This unique model enables comparing B- and T-ALL in one genetic background. We have purified >20 zebrafish ALL (both T-ALL and B-ALL) and isolated their RNA and DNA. We are now analyzing RNA-seq gene expression profiles (GEP) and replication timing (RT) profiles via next generation sequencing (NGS). We will compare both ALL types to identify mRNA signatures that are unique to, or shared by, both types. We seek loci that shift DNA replication from early-to-late, or late-to-early, to define the regions that replicate at the same time in both ALL types, versus loci that vary by ALL type. We will also interrogate these data to determine whether GEP and RT profiles correlate with each other, and with known MYC target genes. In conclusion, GEP and RT have never been analyzed in the same cancer sample, or in related cancers driven by the same oncogene. Exploiting our expertise with thehMYCzebrafish model, we are delineating how MYC alters transcription and replication, to ascertain if these affect the same loci and define which loci are unique to one ALL type or shared by both. MYC hyper-activity is seen ~70% of human cancers - making MYC a crucial oncogene in human cancer biology, so our findings are likely to inform not only mechanisms operative in ALL, but also other MYC-driven cancers. Disclosures No relevant conflicts of interest to declare.


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