Molecular profiling of solid tumors by next-generation sequencing: an experience from a clinical laboratory

Advancing Cancer Care in Colombia: Results of the First In Situ Implementation of Comprehensive Genomic Profiling

BACKGROUND

Comprehensive genomic profiling (CGP) identifies genetic alterations and patterns that are crucial for therapy selection and precise treatment development. In Colombia, limited access to CGP tests underscores the necessity of documenting the prevalence of treatable genetic alterations. This study aimed to describe the somatic genetic profile of specific cancer types in Colombian patients and assess its impact on treatment selection.

METHODS

A retrospective cohort study was conducted at Clínica Colsanitas S.A. from March 2023 to June 2024. Sequencing was performed on the NextSeq2000 platform with the TruSight Oncology 500 (TSO500) assay, which simultaneously evaluates 523 genes for DNA analysis and 55 for RNA; additionally, analyses were performed with the SOPHiA DDM software. The tumor mutational burden (TMB), microsatellite instability (MSI), and programmed cell death ligand 1 (PDL1) were assessed.

RESULTS

Among 111 patients, 103 were evaluated, with gastrointestinal (27.93%), respiratory (13.51%), and central nervous system cancers (10.81%) being the most prevalent. TP53 (37%), KMT2C (28%), and KRAS (21%) were frequent mutations. Actionable findings were detected in 76.7% of cases, notably in digestive (20 patients) and lung cancers (8 patients). MSI was stable at 82.52% and high at 2.91%, whilst TMB was predominantly low (91.26%).

CONCLUSIONS

The test has facilitated access to targeted therapies, improving clinical outcomes in Colombian patients. This profiling test is expected to increase opportunities for personalized medicine in Colombia.

Molecular insights into the role of mixed lineage kinase 3 in cancer hallmarks

Mixed-lineage kinase 3 (MLK3) is a serine/threonine kinase of the MAPK Kinase kinase (MAP3K) family that plays critical roles in various biological processes, including cancer. Upon activation, MLK3 differentially activates downstream MAPKs, such as JNK, p38, and ERK. In addition, it regulates various non-canonical signaling pathways, such as β-catenin, AMPK, Pin1, and PAK1, to regulate cell proliferation, apoptosis, invasion, and metastasis. Recent studies have also uncovered other potentially diverse roles of MLK3 in malignancy, which include metabolic reprogramming, cancer-associated inflammation, and evasion of cancer-related immune surveillance. The role of MLK3 in cancer is complex and cancer-specific, and an understanding of its function at the molecular level aligned specifically with the cancer hallmarks will have profound therapeutic implications for diagnosing and treating MLK3-dependent cancers. This review summarizes the current knowledge about the effect of MLK3 on the hallmarks of cancer, providing insights into its potential as a promising anticancer drug target.

Molecular, Metabolic, and Subcellular Mapping of the Tumor Immune Microenvironment via 3D Targeted and Non-Targeted Multiplex Multi-Omics Analyses

Most platforms used for the molecular reconstruction of the tumor-immune microenvironment (TIME) of a solid tumor fail to explore the spatial context of the three-dimensional (3D) space of the tumor at a single-cell resolution, and thus lack information about cell-cell or cell-extracellular matrix (ECM) interactions. To address this issue, a pipeline which integrated multiplex spatially resolved multi-omics platforms was developed to identify crosstalk signaling networks among various cell types and the ECM in the 3D TIME of two FFPE (formalin-fixed paraffin embedded) gynecologic tumor samples. These platforms include non-targeted mass spectrometry imaging (glycans, metabolites, and peptides) and Stereo-seq (spatial transcriptomics) and targeted seqIF (IHC proteomics). The spatially resolved imaging data in a two- and three-dimensional space demonstrated various cellular neighborhoods in both samples. The collection of spatially resolved analytes in a voxel (3D pixel) across serial sections of the tissue was also demonstrated. Data collected from this analytical pipeline were used to construct spatial 3D maps with single-cell resolution, which revealed cell identity, activation, and energized status. These maps will provide not only insights into the molecular basis of spatial cell heterogeneity in the TIME, but also novel predictive biomarkers and therapeutic targets, which can improve patient survival rates.