To Örebro University

Background: The aim of this study was to investigate the clinical value of liquid biopsy as a primary source for variant analysis in lung cancer. In addition, we sought to characterize liquid biopsy variants and to correlate mutational load to clinical data.

Methods: Circulating cell-free DNA was extracted from plasma from patients with lung cancer (n = 60) and controls with benign lung disease (n = 16). Variant analysis was performed using the AVENIO ctDNA Surveillance kit and the results were correlated to clinical and variant analysis data from tumor tissue or cytology retrieved from clinical routine diagnostics.

Results: There were significantly more variants detected in lung cancer cases compared to controls (p = 0.011), but no difference between the histological subgroups of lung cancer was found (p = 0.465). Furthermore, significantly more variants were detected in patients with stage IIIb-IV disease compared to patients with stage I-IIIa (median 7 vs 4, p = 0.017). Plasma cfDNA mutational load was significantly associated with overall survival (p = 0.010). The association persisted when adjusted for stage and ECOG performance status (HR: 3.64, 95% CI 1.37-9.67, p = 0.009). Agreement between tumor and plasma samples significantly differed with stage; patients with stage IIIb-IV disease showed agreement in 88.2% of the cases with clinically relevant variants, compared to zero cases in stage I-IIIa (p = 0.004). Furthermore, one variant in EGFR, two in KRAS, and one in BRAF were detected in plasma but not in tumor samples.

Conclusion: This study concludes that in the vast majority of advanced NSCLC patients a reliable variant analysis can be performed using liquid biopsy from plasma. Furthermore, we found that the number of variants in plasma is associated with prognosis, possibly indicating a strategy for closer follow up on this crucial patient group.

We aimed to investigate the use of free glycosaminoglycan profiles (GAGomes) and cfDNA in plasma to differentiate between lung cancer and benign lung disease, in a cohort of 113 patients initially suspected of lung cancer. GAGomes were analyzed in all samples using the MIRAM® Free Glycosaminoglycan Kit with ultra-high-performance liquid chromatography and electrospray ionization triple quadrupole mass spectrometry. In a subset of samples, cfDNA concentration and NGS-data was available. We detected two GAGome features, 0S chondroitin sulfate (CS), and 4S CS, with cancer-specific changes. Based on the observed GAGome changes, we devised a model to predict lung cancer. The model, named the GAGome score, could detect lung cancer with 41.2% sensitivity (95% CI: 9.2-54.2%) at 96.4% specificity (95% CI: 95.2-100.0%, n = 113). When we combined the GAGome score with a cfDNA-based model, the sensitivity increased from 42.6% (95% CI: 31.7-60.6%, cfDNA alone) to 70.5% (95% CI: 57.4-81.5%) at 95% specificity (95% CI: 75.1-100%, n = 74). Notably, the combined GAGome and cfDNA testing improved the sensitivity, compared to cfDNA alone, especially in ASCL stage I (55.6% vs 11.1%). Our findings show that plasma GAGome profiles can enhance cfDNA testing performance, highlighting the applicability of a multiomics approach in lung cancer diagnostics.

BACKGROUND: Human papillomavirus (HPV) has emerged as a significant contributor to cancer incidence globally, particularly in the context of oropharyngeal squamous cell carcinoma (OPSCC) and cancer of unknown primary (HNCUP). This study aimed to develop and validate droplet digital PCR (ddPCR) assays for the detection of circulating tumor HPV DNA (ctHPV-DNA) in plasma, focusing on high-risk HPV genotypes associated with these cancers.

METHODS: ddPCR assays for HPV16, 18, 33, 35, 56, and 59 were developed and tested using gBlocks, HPV cell-free DNA, fragmented tumor HPV+ DNA, and plasma samples from patients with HPV+ OPSCC (n = 110) and HNCUP (n = 9).

RESULTS: Assays demonstrated robust technical sensitivity across all tested HPV genotypes. Clinical application of the assays on a cohort of patients with HPV+ OPSCC and HNCUP revealed high sensitivity (91.6%) and wide variability in ctHPV-DNA levels. Analyses revealed correlations between ctHPV-DNA levels and TNM stage and tumor viral load. The association between ctHPV-DNA and tumor viral load persisted even after adjusting for TNM stage. At posttreatment, 72.5% of samples had reached undetectable ctHPV-DNA levels. Having detectable ctHPV-DNA posttreatment was associated with a higher ctHPV-DNA level at diagnosis and higher viral load at diagnosis.

CONCLUSION: The findings underscore the potential of ctHPV-DNA as a biomarker for monitoring HPV+ cancers and offer insights into tumor dynamics. Implementation of these assays in clinical practice could enhance no-invasive treatment monitoring and recurrence detection in HPV-associated cancers.

CLINICAL TRIALS: NCT05904327.