A comprehensive algorithmic dissection yields biomarker discovery and insights into the discrete stage-wise progression of colorectal cancer
medRxiv (Cold Spring Harbor Laboratory)(2022)
摘要
Colorectal cancer remains an increasingly common condition with uncommon burden of disease, heterogeneity in manifestation, and no definitive treatment. Against this backdrop, renewed efforts to unravel the genetic drivers of colorectal cancer progression are paramount. Early-stage detection contributes to the success of cancer therapy and increases the likelihood of a favorable prognosis. Here, we have executed a comprehensive computational workflow aimed at uncovering the discrete stagewise genetic drivers of colorectal cancer progression. Using the TCGA COADREAD expression data and clinical metadata, we constructed stage-specific linear models as well as contrast models to identify stage-specific differentially expressed genes. Stage-specific differentially expressed genes with a significant monotone trend of expression across the stages were identified as progression-significant biomarkers. Among the biomarkers identified are: CRLF1, CALB2 (stage-I specific), GREM2, ADCY5, PLAC2, DMRT3 (stage-II specific), PIGR, SLC26A9 (stage-III specific), GABRD, DLX3, CST6, HOTAIR (stage-IV specific), and CDH3, KRT80, AADACL2, OTOP2, FAM135B, HSP90AB1 (top linear model genes). In particular the study yielded 31 genes that are progression-significant such as ESM1, DKK1, SPDYC, IGFBP1, BIRC7, NKD1, CXCL13, VGLL1, PLAC1, SPERT, UPK2, and interestingly three members of the LY6G6 family. Significant monotonic linear model genes included HIGD1A, ACADS, PEX26, and SPIB. The existing literature for many of these biomarkers is discussed to document positive translational potential needing clinical evidence. The study yielded many classes of biomarkers, which could serve in signature panels for early-stage colorectal cancer diagnosis as well as establish strategies for therapy. Our work is a concrete step in the direction of establishing the molecular signatures of the discrete progressive stages of colorectal cancer, with the future goal of securing more effective treatment for the condition.
### Competing Interest Statement
The authors have declared no competing interest.
### Funding Statement
This study was funded by DST-SERB grant no. EMR/2017/000470, India.
### Author Declarations
I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
Yes
I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.
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I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).
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I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.
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All data produced in the present work are either contained in the manuscript or available online at: https://doi.org/10.6084/m9.figshare.20489211.v2
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关键词
colorectal cancer,comprehensive algorithmic dissection yields,biomarker,discovery,stage-wise
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