<![CDATA[Cancer molecular profiling produces heterogeneous data streams, including patient metadata, biological sample information, single-nucleotide variant (SNV) records, variant annotations, and cancer stage labels. In many hospital and laboratory settings, these elements remain fragmented across spreadsheets, variant call files, and narrative reports, limiting the ability of clinicians and researchers to obtain rapid sample-to-insight interpretation. This study presents MolecuTrace, a web-based molecular oncology dashboard designed to integrate sample metadata, SNV profiles, and cancer stage classification into a structured decision-support prototype. A design science research approach was used to define requirements, model the database, implement an analytics workflow, and evaluate the prototype with a simulated demonstration dataset of 120 oncology samples and 253 SNV records. The system consists of a sample registry, SNV import and validation module, annotation layer, risk-scoring engine, dashboard visualization, and exportable report interface. The demonstration dataset showed a mean age of 53.9 years, 44.2% metastatic cases, and TP53 as the most frequently observed altered gene. MolecuTrace generated summary indicators for cancer type distribution, sample source composition, top altered genes, metastatic status, and molecular risk classes. The proposed prototype contributes an interoperable, auditable, and clinically readable model for transforming molecular oncology data into actionable visual summaries. Although the current evaluation uses simulated data and requires external clinical validation, the framework demonstrates how a lightweight information system can support precision oncology workflows in resource-constrained healthcare settings.]]>
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