Concurrent Tissue and Circulating Tumor DNA Molecular Profiling to Detect Guideline-Based Targeted Mutations in a Multicancer Cohort.

Importance: Tissue-based next-generation sequencing (NGS) of solid tumors is the criterion standard for identifying somatic mutations that can be treated with National Comprehensive Cancer Network guideline-recommended targeted therapies. Sequencing of circulating tumor DNA (ctDNA) can also identify tumor-derived mutations, and there is increasing clinical evidence supporting ctDNA testing as a diagnostic tool. The clinical value of concurrent tissue and ctDNA profiling has not been formally assessed in a large, multicancer cohort from heterogeneous clinical settings. Objective: To evaluate whether patients concurrently tested with both tissue and ctDNA NGS testing have a higher rate of detection of guideline-based targeted mutations compared with tissue testing alone. Design, Setting, and Participants: This cohort study comprised 3209 patients who underwent sequencing between May 2020, and December 2022, within the deidentified, Tempus multimodal database, consisting of linked molecular and clinical data. Included patients had stage IV disease (non-small cell lung cancer, breast cancer, prostate cancer, or colorectal cancer) with sufficient tissue and blood sample quantities for analysis. Exposures: Received results from tissue and plasma ctDNA genomic profiling, with biopsies and blood draws occurring within 30 days of one another. Main Outcomes and Measures: Detection rates of guideline-based variants found uniquely by ctDNA and tissue profiling. Results: The cohort of 3209 patients (median age at diagnosis of stage IV disease, 65.3 years [2.5%-97.5% range, 43.3-83.3 years]) who underwent concurrent tissue and ctDNA testing included 1693 women (52.8%). Overall, 1448 patients (45.1%) had a guideline-based variant detected. Of these patients, 9.3% (135 of 1448) had variants uniquely detected by ctDNA profiling, and 24.2% (351 of 1448) had variants uniquely detected by solid-tissue testing. Although largely concordant with one another, differences in the identification of actionable variants by either assay varied according to cancer type, gene, variant, and ctDNA burden. Of 352 patients with breast cancer, 20.2% (71 of 352) with actionable variants had unique findings in ctDNA profiling results. Most of these unique, actionable variants (55.0% [55 of 100]) were found in ESR1, resulting in a 24.7% increase (23 of 93) in the identification of patients harboring an ESR1 mutation relative to tissue testing alone. Conclusions and Relevance: This study suggests that unique actionable biomarkers are detected by both concurrent tissue and ctDNA testing, with higher ctDNA identification among patients with breast cancer. Integration of concurrent NGS testing into the routine management of advanced solid cancers may expand the delivery of molecularly guided therapy and improve patient outcomes.

Comparative genomic analysis of PIK3R1-mutated and wild-type breast cancers.

PURPOSE: The PIK3R1 gene encodes the regulatory subunit-p85a-of the PI3K signaling complex. Prior studies have found that pathogenic somatic alterations in PIK3R1 are enriched in human breast cancers but the genomic landscape of breast cancer patients harboring PIK3R1 mutations has not been extensively characterized. METHODS: We retrospectively analyzed 6,009 patient records that underwent next-generation sequencing (NGS) using the Tempus xT solid tumor assay. All patients had breast cancer with known HER2 (+/-) and hormone receptor (HR; +/-) status and were classified according to the presence of PIK3R1 mutations including short variants and copy number alterations. RESULTS: The frequency of PIK3R1 mutations varied according to subtype: 6% in triple negative (TNBC, 89/1,475), 2% in HER2-/HR+ (80/3,893) and 2.3% in HER2+ (15/641) (p < 0.001). Co-mutations in PTEN, TP53 and NF1 were significantly enriched, co-mutations in PIK3CA were significantly less prevalent, and tumor mutational burden was significantly higher in PIK3R1-mutated HER2- samples relative to PIK3R1 wild-type. At the transcriptional-level, PIK3R1 RNA expression in HER2- disease was significantly higher in PIK3R1-mutated (excluding copy number loss) samples, regardless of subtype. CONCLUSION: This is the largest investigation of the PIK3R1 mutational landscape in breast cancer patients (n = 6,009). PIK3R1 mutations were more common in triple-negative breast cancer (~ 6%) than in HER2 + or HER2-/HR + disease (approximately 2%). While alterations in the PI3K/AKT pathway are often actionable in HER2-/HR + breast cancer, our study suggests that PIK3R1 could be an important target in TNBC as well.

Assessing the utility of molecular diagnostic classification for cancers of unknown primary.

BACKGROUND: Roughly 5% of metastatic cancers present with uncertain origin, for which molecular classification could influence subsequent management; however, prior studies of molecular diagnostic classifiers have reported mixed results with regard to clinical impact. In this retrospective study, we evaluated the utility of a novel molecular diagnostic classifier by assessing theoretical changes in treatment and additional testing recommendations from oncologists before and after the review of classifier predictions. METHODS: We retrospectively analyzed de-identified records from 289 patients with a consensus diagnosis of cancer of uncertain/unknown primary (CUP). Two (or three, if adjudication was required) independent oncologists separately reviewed patient clinical information to determine the course of treatment before they reviewed results from the molecular diagnostic classifier and subsequently evaluated whether the predicted diagnosis would alter their treatment plan. RESULTS: Results from the molecular diagnostic classifier changed the consensus oncologist-reported treatment recommendations for 235 out of 289 patients (81.3%). At the level of individual oncologist reviews (n = 414), 64.7% (n = 268) of treatment recommendations were based on CUP guidelines prior to review of results from the molecular diagnostic classifier. After seeing classifier results, 98.1% (n = 207) of the reviews, where treatment was specified (n = 211), were guided by the tissue of origin-specific guidelines. Overall, 89.9% of the 414 total reviews either expressed strong agreement (n = 242) or agreement (n = 130) that the molecular diagnostic classifier result increased confidence in selecting the most appropriate treatment regimen. CONCLUSIONS: A retrospective review of CUP cases demonstrates that a novel molecular diagnostic classifier could affect treatment in the majority of patients, supporting its clinical utility. Further studies are needed to prospectively evaluate whether the use of molecular diagnostic classifiers improves clinical outcomes in CUP patients.

Validation of a Transcriptome-Based Assay for Classifying Cancers of Unknown Primary Origin.

INTRODUCTION: Cancers assume a variety of distinct histologies, and may originate from a myriad of sites including solid organs, hematopoietic cells, and connective tissue. Clinical decision-making based on consensus guidelines such as the National Comprehensive Cancer Network (NCCN) is often predicated on a specific histologic and anatomic diagnosis, supported by clinical features and pathologist interpretation of morphology and immunohistochemical (IHC) staining patterns. However, in patients with nonspecific morphologic and IHC findings-in addition to ambiguous clinical presentations such as recurrence versus new primary-a definitive diagnosis may not be possible, resulting in the patient being categorized as having a cancer of unknown primary (CUP). Therapeutic options and clinical outcomes are poor for patients with CUP, with a median survival of 8-11 months. METHODS: Here, we describe and validate the Tempus Tumor Origin (Tempus TO) assay, an RNA-sequencing-based machine learning classifier capable of discriminating between 68 clinically relevant cancer subtypes. Model accuracy was assessed using primary and/or metastatic samples with known subtype. RESULTS: We show that the Tempus TO model is 91% accurate when assessed on both a retrospectively held out cohort and a set of samples sequenced after model freeze that collectively contained 9210 total samples with known diagnoses. When evaluated on a cohort of CUPs, the model recapitulated established associations between genomic alterations and cancer subtype. DISCUSSION: Combining diagnostic prediction tests (e.g., Tempus TO) with sequencing-based variant reporting (e.g., Tempus xT) may expand therapeutic options for patients with cancers of unknown primary or uncertain histology.

Clinical, Genomic, and Transcriptomic Data Profiling of Biliary Tract Cancer Reveals Subtype-Specific Immune Signatures.

PURPOSE: Biliary tract cancers (BTCs) are aggressive cancers that carry a poor prognosis. An enhanced understanding of the immune landscape of anatomically and molecularly defined subsets of BTC may improve patient selection for immunotherapy and inform immune-based combination treatment strategies. METHODS: We analyzed deidentified clinical, genomic, and transcriptomic data from the Tempus database to determine the mutational frequency and mutational clustering across the three major BTC subtypes (intrahepatic cholangiocarcinoma [IHC], extrahepatic cholangiocarcinoma, and gallbladder cancer). We subsequently determined the relationship between specific molecular alterations and anatomical subsets and features of the BTC immune microenvironment. RESULTS: We analyzed 454 samples of BTC, of which the most commonly detected alterations were TP53 (42.5%), CDKN2A (23.4%), ARID1A (19.6%), BAP1 (15.5%), KRAS (15%), CDKN2B (14.2%), PBRM1 (11.7%), IDH1 (11.7%), TERT (8.4%), KMT2C (10.4%) and LRP1B (8.4%), and FGFR2 fusions (8.7%). Potentially actionable molecular alterations were identified in 30.5% of BTCs including 39.1% of IHC. Integrative cluster analysis revealed four distinct molecular clusters, with cluster 4 predominately associated with FGFR2 rearrangements and BAP1 mutations in IHC. Immune-related biomarkers indicative of an inflamed tumor-immune microenvironment were elevated in gallbladder cancers and in cluster 1, which was enriched for TP53, KRAS, and ATM mutations. Multiple common driver genes, including TP53, FGFR2, IDH1, TERT, BRAF, and BAP1, were individually associated with unique BTC immune microenvironments. CONCLUSION: BTC subtypes exhibit diverse DNA alterations, RNA inflammatory signatures, and immune biomarkers. The association between specific BTC anatomical subsets, molecular alterations, and immunophenotypes highlights new opportunities for therapeutic development.