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Tempus Finds Tumor-Normal Sequencing, RNA Profiling Aid Patient Matching to Therapies, Trials

NEW YORK – Integrated analysis of tumor and normal samples from cancer patients combined with RNA profiling of their tumor helps match those patients to targeted therapies and clinical trials, according to a new study from Tempus Labs.

In their paper, appearing today in Nature Biotechnology, Tempus researchers applied their approach to 500 patient samples representing a range of tumor types.

Tempus's xT assay sequences nearly 600 genes to uncover SNVs, indels, CNVs, or chromosomal rearrangements. It also includes RNA sequencing of the tumor to detect gene fusions. In addition, its xT immuno-oncology assays include immunohistochemistry testing for DNA mismatch repair deficiency and PD-1/PD-L1 status, microsatellite instability testing, tumor mutational burden testing, neoantigen prediction, and expression analysis of the tumor microenvironment.

The researchers reported they could match more than 40 percent of patients to a targeted treatment and about three quarters to a clinical trial, a higher rate than what they estimated would be possible with tumor-only DNA panel testing. The firm has recently launched a clinical trial matching service.

"Our results demonstrate the value of harnessing tumor–normal genomic sequencing, gene expression profiling, genomic rearrangement detection, and immunotherapy biomarker prediction to address emergent clinical indications," the researchers wrote in their paper.

For their analysis, they applied the Tempus platform to a set of tumors from 500 randomly selected patients with common cancers. They generated both clinical and research-use-only data using tumors and matched normal samples to examine the DNA mutational spectra of the tumors. They also profiled the transcriptome of the tumors, detected chromosomal rearrangements, and, with immunotherapy biomarkers, examined the immunogenic landscape.

The tumors largely reflected other broad cancer cohorts, the researchers noted, as the most commonly mutated genes in this cohort were TP53, KRAS, and PIK3CA, which were present at similar frequencies as in a published pan-cancer analysis from Memorial Sloan Kettering Cancer Center.

Based on the transcriptome data, the researchers reported they could correctly classify most tumor types, identifying 100 percent of breast cancers, 98 percent of prostate cancers, and 88 percent of lung cancers. The lower identification rate for endometrial cancers — 58 percent — was likely due to low tumor purity, they said.

The researchers similarly were able to identify a number of oncogenic gene fusions within these samples, as well as immunotherapy biomarkers.

Based on the molecular profiles they generated, they attempted to match patients to therapies from which they might benefit. Across all evidence levels, they could match nearly 92 percent of patients to a therapeutic option.

When they restricted their analysis to high levels of clinical evidence — such as from consensus clinical guidelines — they were able to match about 30 percent of patients to a targeted therapy based on DNA-sequencing evidence alone. The addition of addition of RNA sequencing and immunotherapy biomarker results could boost that to 43 percent of patients, they noted.

They were also able to use these molecular profiles in conjunction with clinical data to find clinical trials patients could potentially enroll in. In particular, the researchers uncovered at least one clinical trial option for more than 96 percent of patients and a biomarker-based match for nearly 77 percent of them.

This approach, the researchers said, could better match patients to possible therapies than analyses based solely on DNA sequencing of tumors. They analyzed 50 patients from their cohort with a tumor-only pipeline, feeding those results into the My Cancer Genome website. For these 50 samples, 43 cases were matched to therapies when the full xT assay was applied, but only five were matched to therapies via My Cancer Genome analysis.

"These results indicate that extensive molecular profiling combined with clinical data identifies personalized therapies and clinical trials for a large proportion of patients with cancer and that paired tumor–normal plus transcriptome sequencing outperforms tumor-only DNA panel testing," the Tempus team wrote.