Shallow whole-genome sequencing of plasma cell-free DNA accurately differentiates small from non-small cell lung carcinoma

Background Accurate lung cancer classification is crucial to guide therapeutic decisions. However, histological subtyping by pathologists requires tumor tissue-a necessity that is often intrinsically associated with procedural difficulties. The analysis of circulating tumor DNA present in minimal-invasive blood samples, referred to as liquid biopsies, could therefore emerge as an attractive alternative. Methods Concerning adenocarcinoma, squamous cell carcinoma, and small cell carcinoma, our proof of concept study investigates the potential of liquid biopsy-derived copy number alterations, derived from single-end shallow whole-genome sequencing (coverage 0.1-0.5x), across 51 advanced stage lung cancer patients. Results Genomic abnormality testing reveals anomalies in 86.3% of the liquid biopsies (16/20 for adenocarcinoma, 13/16 for squamous cell, and 15/15 for small cell carcinoma). We demonstrate that copy number profiles from formalin-fixed paraffin-embedded tumor biopsies are well represented by their liquid equivalent. This is especially valid within the small cell carcinoma group, where paired profiles have an average Pearson correlation of 0.86 (95% CI 0.79-0.93). A predictive model trained with public data, derived from 843 tissue biopsies, shows that liquid biopsies exhibit multiple deviations that reflect histological classification. Most notably, distinguishing small from non-small cell lung cancer is characterized by an area under the curve of 0.98 during receiver operating characteristic analysis. Additionally, we investigated how deeper paired-end sequencing, which will eventually become feasible for routine diagnosis, empowers tumor read enrichment by insert size filtering: for all of the 29 resequenced liquid biopsies, the tumor fraction could be increased in silico, thereby "rescuing" three out of five cases with previously undetectable alterations. Conclusions Copy number profiling of cell-free DNA enables histological classification. Since shallow whole-genome sequencing is inexpensive and often fully operational at routine molecular laboratories, this finding has current diagnostic potential, especially for patients with lesions that are difficult to reach

Shallow-depth sequencing of cell-free DNA for Hodgkin and diffuse large B-cell lymphoma (differential) diagnosis: a standardized approach with underappreciated potential

Shallow-depth sequencing of cell-free DNA, an inexpensive and standardized approach to obtain molecular information on tumors non-invasively, has been insufficiently explored for the diagnosis of lymphoma and disease follow-up. This study collected 318 samples, including longitudinal liquid and paired solid biopsies, from a prospectively- recruited cohort of 38 Hodgkin lymphoma (HL) and 85 aggressive B-cell non-HL patients, represented by 81 diffuse large B-cell lymphoma (DLBCL) cases. Following sequencing, copy number alterations and viral read fractions were derived and analyzed. At diagnosis, liquid biopsies showed detectable copy number alterations in 84.2% of HL patients (88.6% for classical HL) and 74.1% of DLBCL patients. Of the DLBCL patients, copy number profiles between liquid-solid pairs were highly concordant (r=0.815±0.043); and, compared to tissue, HL liquid biopsies had abnormalities with higher amplitudes (P=0.010). This implies that tumor DNA is more abundant in plasma. Additionally, 39.5% of HL and 13.6% of DLBCL cases had a significantly elevated number of plasma Epstein-Barr virus DNA fragments, achieving a sensitivity of 100% compared to the current standard. A longitudinal analysis determined that, when detectable, copy number patterns were similar across (re)staging moments in refractory or relapsed patients. Further, the overall profile anomaly correlated highly with the total metabolic tumor volume (P<0.001). To conclude, as a proof of principle, we demonstrate that liquid biopsy-derived copy numbers can aid diagnosis: e.g., by differentiating HL from DLBCL, random forest modeling is represented by an area under the receiver operating characteristic curve of 0.967. This application is potentially useful when tissue is difficult to obtain or when biopsies are small and inconclusive

DeltaMSI : artificial intelligence-based modeling of microsatellite instability scoring on next-generation sequencing data

BackgroundDNA mismatch repair deficiency (dMMR) testing is crucial for detection of microsatellite unstable (MSI) tumors. MSI is detected by aberrant indel length distributions of microsatellite markers, either by visual inspection of PCR-fragment length profiles or by automated bioinformatic scoring on next-generation sequencing (NGS) data. The former is time-consuming and low-throughput while the latter typically relies on simplified binary scoring of a single parameter of the indel distribution. The purpose of this study was to use machine learning to process the full complexity of indel distributions and integrate it into a robust script for screening of dMMR on small gene panel-based NGS data of clinical tumor samples without paired normal tissue.MethodsScikit-learn was used to train 7 models on normalized read depth data of 36 microsatellite loci in a cohort of 133 MMR proficient (pMMR) and 46 dMMR tumor samples, taking loss of MLH1/MSH2/PMS2/MSH6 protein expression as reference method. After selection of the optimal model and microsatellite panel the two top-performing models per locus (logistic regression and support vector machine) were integrated into a novel script (DeltaMSI) for combined prediction of MSI status on 28 marker loci at sample level. Diagnostic performance of DeltaMSI was compared to that of mSINGS, a widely used script for MSI detection on unpaired tumor samples. The robustness of DeltaMSI was evaluated on 1072 unselected, consecutive solid tumor samples in a real-world setting sequenced using capture chemistry, and 116 solid tumor samples sequenced by amplicon chemistry. Likelihood ratios were used to select result intervals with clinical validity.ResultsDeltaMSI achieved higher robustness at equal diagnostic power (AUC = 0.950; 95% CI 0.910-0.975) as compared to mSINGS (AUC = 0.876; 95% CI 0.823-0.918). Its sensitivity of 90% at 100% specificity indicated its clinical potential for high-throughput MSI screening in all tumor types.Clinical Trial Number/IRB B1172020000040, Ethical Committee, AZ Delta General Hospital

Antitumoral activity of tyrosine kinase inhibitors in patients with non-small cell lung cancer harbouring rare epidermal growth factor receptor mutations

Introduction: Mutations in the epidermal growth factor receptor (EGFR) have been reported as predictive markers of tumour response to tyrosine kinase inhibitors (TKIs) in patients with non-small cell lung cancer (NSCLC). Although the "common" EGFR mutations have been associated with response to EGFR-TKIs, the correlation with response to treatment for many other rare mutations is still unclear. The aim of this study was to investigate the clinical significance of rare and complex mutations, and the efficacy of EGFR-TKIs in this selected group of patients. Methods: Three hundred and thirty patients with stage IIIB/IV NSCLC (106 females aged 62.5 +/- 1.1 years; 224 males aged 68.0 +/- 0.6 years) were enrolled in the study. Formalin fixed paraffin embedded tissue samples were screened for mutations using a high resolution melting technique, followed by Sanger sequencing of exons 18-21 of the EGFR-gene. Mutation status was also tested using the Roche Cobas (R) EGFR mutation test. Results: EGFR mutations were detected in 31 tumours (9.4 %). Eleven cases carried novel mutations, six of these patients were treated with erlotinib or gefitinib. A response rate (RR) of 50.0 % was obtained in the group with rare EGFR mutations, the PFS was 3.0 months [standard deviation (STD) = 5.4 months]. The RR to EGFR-TKIs in patients with conventional EGFR mutations was 85 % with a median PFS of 10.5 months (STD = 3.6 months). Conclusion: We reported six patients with rare EGFR mutations of unknown clinical significance and their association with EGFR-TKIs. Report of cases harbouring rare mutations can support the decision making progress in this subset of patients

Comparison of microsatellite instability detection by immunohistochemistry and molecular techniques in colorectal and endometrial cancer

Abstract DNA mismatch repair deficiency (dMMR) testing is crucial for diagnosing Lynch syndrome and detection of microsatellite unstable (MSI) tumors eligible for immunotherapy. The aim of this study was to compare the relative diagnostic performance of three molecular MSI assays: polymerase chain reaction (PCR), MSI testing by Idylla and next-generation-sequencing (NGS) on 49 tumor samples (28 colorectal and 21 endometrial adenocarcinomas) versus immunohistochemistry (IHC). Discrepancies were investigated by MLH1 methylation analysis and integrated with germline results if available. Overall, the molecular assays achieved equivalent diagnostic performance for MSI detection with area under the ROC curves (AUC) of respectively 0.91 for Idylla and PCR, and 0.93 for NGS. In colorectal cancers with tumor cell percentages ≥ 30% all three molecular assays achieved 100% sensitivity and specificity (AUC = 1) versus IHC. Also, in endometrial cancers, all three molecular assays showed equivalent diagnostic performance, albeit at a clearly lower sensitivity ranging from 58% for Idylla to 75% for NGS, corresponding to negative predictive values from 78 to 86%. PCR, Idylla and NGS show similar diagnostic performance for dMMR detection in colorectal and endometrial cancers. Molecular MSI analysis has lower sensitivity for dMMR detection in endometrial cancer indicating that combined use of both IHC and molecular methods is recommended. Clinical Trial Number/IRB: B1172020000040, Ethical Committee, AZ Delta General Hospital

Guidelines for the detection of NTRK fusions. A report from the Belgian Molecular Pathology Working Group.

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