Cancer Molecular Analysis Project (CMAP)

Category Cross-Omics>Knowledge Bases/Databases/Tools

Abstract The Cancer Molecular Analysis Project (CMAP) of the National Cancer Institute (NCI) has integrated diverse cancer research data to elucidate fundamental etiologic processes, enable development of novel therapeutic approaches, and facilitate the bridging of basic and clinical science.

The information presented to the community is accessed through different high-level organizational views that help researchers approach the fully integrated dataset within a contextually familiar environment.

Currently, there are four (4) entry points to CMAP information: molecular profiles, molecular targets, targeted agents, and trials of targeted agents.

These entry points roughly approximate the steps associated with selection, development, and validation of a targeted therapy.

1) The molecular profiles section - contains molecular signatures of cancer types (co-occurring sets of anomalies associated with specific cancer types).

The ability to find the signatures of a specific cancer type or find the cancer type that most closely matches a particular signature.

2) The molecular targets section - contains collections of genes organized by pathways and by ontology (functional classification) permitting aggregate evaluation of anomalies (over-expression, under-expression, mutation).

3) The agents section provides - agents (drugs and other interventions) targeted to specific profiles, molecular anomalies, pathways, and ontologies.

4) The trials section - catalogs and describes information on cancer clinical trials evaluating molecular targeted agents, organized by therapeutic agent and by cancer type.

Orthogonal to these entry points is the ability to determine the cancer context through which information is obtained and integrated.

Information retrieval spans the continuum from all cancers of all types to specific histological subtypes of cancer of a given tissue type. This variability enables two different lines of inquiry.

When queried from a histologically specific perspective, it is possible to discover molecular heterogeneity within a cancer type.

Alternatively, a query that aggregates over multiple cancer types facilitates the identification of commonalties among their molecular architectures.

In silico hypothesis generation through CMAP -

Each of the individual sections provides opportunities to discover patterns, view information in biological contexts, and/or integrate across the various cancer research disciplines.

While obviously Not a replacement for actual experimentation, the infrastructure facilitates hypothesis generation from integration of compiled cross-disciplinary data resources.

How CMAP Data is organized --

CMAP data is organized around several key concepts: context, target, anomaly, profile, agent, and trial.

Context --

A CMAP user may wish to see data that is directly relevant to a particular kind of cancer. Therefore, CMAP allows a user to select a specific combination of tissue and disease, e.g. “brain, astrocytoma”.

A particular combination of tissue and disease is a ‘context’. Some data in CMAP, e.g., anomalies, can be filtered for a specific context.

Note: Data displayed on the Gene Info page is NOT context specific.:

Contexts can be logically nested. For example, the broader context “brain, neoplasia” logically includes the narrower context “brain, astrocytoma”. The broadest context, “any tissue, neoplasia,” includes all other contexts.

Target --

A target is a molecule that holds special diagnostic or therapeutic interest for cancer research. The association between the molecule and cancer may be established or merely hypothesized.

In CMAP, a target (established or hypothesized) is treated as a potential target in any cancer; thus targets are Not specific to contexts. Context specificity is achieved by linking a target to an anomaly.

Target Types -

A target can be a protein, a complex, or an antigen. At present, however, CMAP recognizes only simple protein targets, identified by their encoding genes.

Functional Classification of Targets -

Targets are classified by function. CMAP has two (2) kinds of functional classification: ontology and pathway. Elements of a class in an ontology are thought of as being similar because each element performs the same function.

For example, both MMP1 and MMP2 are in the class Matrix Metalloproteinase because they have similar biochemical functions and share the protein motifs Peptidase M10 and hemopexin.

On the other hand, elements of a pathway, while differing in structure and biochemical function, are connected dynamically in a chain of biochemical interactions that constitutes a higher-level biological process.

For example, p53 and BAX differ in structure and in individual biochemical function but cooperate in the p53 signaling pathway.

The distinction between ontology and pathway may become blurred if the ontology includes classes that represent higher-level biological processes. Nevertheless, in general, members of a class in ontology are viewed as a list of similar individuals, while participants in a pathway are viewed as an interaction among diverse individuals.

CMAP uses two (2) ontologies: a simple classification that is used internally by the Cancer Therapy Evaluation Program and the more complex Gene Ontology developed by the Gene Ontology (GO) Consortium.

Currently, CMAP uses pathway diagrams published by BioCarta.

In addition to the standard BioCarta representation of pathways, CMAP also publishes versions that are annotated with anomalies.

Since a target is Not linked to a context directly, when CMAP is queried by ontology class, CMAP will retrieve all potential targets in the queried class, regardless of context.

The treatment of pathways is slightly more complicated. When CMAP is queried for a list of pathways, CMAP will retrieve every pathway that contains at least one potential target that is expressed in the context.

But when CMAP is queried for targets in a given pathway, CMAP will retrieve every potential target in the pathway without regard to context.

Target Expression --

Anomaly -

An anomaly is a deviation in the structure or expression of a target. Examples of anomalies are over-expression of EGFR, reduced expression of CDKN1B, and mutation of p53. An anomaly is associated with one or more kinds of cancer and therefore can be filtered by context.

Profile -

A profile of a kind of cancer is a set of anomalies that characterize that cancer, distinguishing it from other kinds of cancer and from normal states.

While a goal of CMAP is to assist in the discovery of cancer profiles, at present the CMAP data does Not include validated profiles. Currently the Profiles section of the CMAP site is limited to expression data on the NCI 60 cell lines.

Agent -

An agent is a drug or other intervention that is effective in the presence of one or more specific targets. In the current version of CMAP, an agent may be linked to one or more targets and to one or more contexts.

When, in the future, CMAP includes a set of profiles, an agent will be linked to one or more profiles, each profile being a molecular characterization of a kind of cancer for which the agent is effective.

Trial -

A clinical trial is linked to a context and to one or more agents. A trial is Not linked directly to any target.

System Requirements



Manufacturer Web Site Cancer Molecular Analysis Project (CMAP)

Price Contact manufacturer.

G6G Abstract Number 20768

G6G Manufacturer Number 104346