Integrated approach to generate artificial samples with low tumor fraction for somatic variant calling benchmarking.

BACKGROUND: High-throughput sequencing (HTS) has become the gold standard approach for variant analysis in cancer research. However, somatic variants may occur at low fractions due to contamination from normal cells or tumor heterogeneity; this poses a significant challenge for standard HTS analysis pipelines. The problem is exacerbated in scenarios with minimal tumor DNA, such as circulating tumor DNA in plasma. Assessing sensitivity and detection of HTS approaches in such cases is paramount, but time-consuming and expensive: specialized experimental protocols and a sufficient quantity of samples are required for processing and analysis. To overcome these limitations, we propose a new computational approach specifically designed for the generation of artificial datasets suitable for this task, simulating ultra-deep targeted sequencing data with low-fraction variants and demonstrating their effectiveness in benchmarking low-fraction variant calling. RESULTS: Our approach enables the generation of artificial raw reads that mimic real data without relying on pre-existing data by using NEAT, a fine-grained read simulator that generates artificial datasets using models learned from multiple different datasets. Then, it incorporates low-fraction variants to simulate somatic mutations in samples with minimal tumor DNA content. To prove the suitability of the created artificial datasets for low-fraction variant calling benchmarking, we used them as ground truth to evaluate the performance of widely-used variant calling algorithms: they allowed us to define tuned parameter values of major variant callers, considerably improving their detection of very low-fraction variants. CONCLUSIONS: Our findings highlight both the pivotal role of our approach in creating adequate artificial datasets with low tumor fraction, facilitating rapid prototyping and benchmarking of algorithms for such dataset type, as well as the important need of advancing low-fraction variant calling techniques.

Tumor extrachromosomal DNA: Biogenesis and recent advances in the field.

Extrachromosomal DNA (ecDNA) is a self-replicating circular DNA originating from the chromosomal genome and exists outside the chromosome. It contains specific gene sequences and non-coding regions that regulate transcription. Recent studies have demonstrated that ecDNA is present in various malignant tumors. Malignant tumor development and poor prognosis may depend on ecDNA's distinctive ring structure, which assists in amplifying oncogenes. During cell division, an uneven distribution of ecDNA significantly enhances tumor cells' heterogeneity, allowing tumor cells to adapt to changes in the tumor microenvironment and making them more resistant to treatments. The application of ecDNA as a cancer biomarker and therapeutic target holds great potential. This article examines the latest advancements in this area and discusses the potential clinical applications of ecDNA.

Lung cancer biomarkers: Raising the clinical value of the classical and the new ones.

Blood-based diagnostics for lung cancer support the diagnosis, estimation of prognosis, prediction, and monitoring of therapy response in lung cancer patients. The clinical utility of serum tumor markers has considerably increased due to developments in serum protein tumor markers analytics and clinical biomarker studies, the exploration of preanalytical and influencing conditions, the interpretation of biomarker combinations and individual biomarker kinetics, as well as the implementation of biostatistical models. In addition, circulating tumor DNA (ctDNA) and other liquid biopsy markers are playing an increasingly prominent role in the molecular tumor characterization and the monitoring of tumor evolution over time. Thus, modern lung cancer biomarkers may considerably contribute to an individualized companion diagnostics and provide a sensitive guidance for patients throughout the course of their disease. In this special edition on Tumor Markers in Lung Cancer, experts summarize recent developments in clinical laboratory diagnostics of lung cancer and give an outlook on future challenges and opportunities.

A Quest for Survival: A Review of the Early Biomarkers of Pancreatic Cancer and the Most Effective Approaches at Present.

Pancreatic cancer (PC) is the most lethal type of cancer; it has the lowest 5-year survival rate among all other types of cancers. More than half of PC cases are diagnosed at an advanced stage due to PC's insidious and non-specific symptoms. Surgery remains the most efficacious treatment option currently available, but only 10-20% of PC cases are resectable upon diagnosis. As of now, the sole biomarker approved by the United States Food and Drug Administration (US-FDA) for PC is carbohydrate antigen 19-9 (CA19-9); however, its use is limited for early diagnosis. An increasing number of studies have investigated a combination of biomarkers. Lately, there has been considerable interest in the application of a liquid biopsy, including the utilization of microRNAs (miRNAs), circulating tumor DNA (ctDNA), and circulating tumor cells (CTCs). Screening for PC is indicated for high-risk patients; studies on new diagnostic models combined with biomarkers for early detection have also shown promising results in terms of the ability of these models and biomarkers to aid clinicians in deciding on whether to start screening. This review seeks to provide a concise overview of the advancements in relation to existing biomarkers and explore novel strategies for the early detection of PC.

ctDNA transiting into urine is ultrashort and facilitates noninvasive liquid biopsy of HPV+ oropharyngeal cancer.

BACKGROUNDTransrenal cell-free tumor DNA (TR-ctDNA), which transits from the bloodstream into urine, has the potential to enable noninvasive cancer detection for a wide variety of nonurologic cancer types.MethodsUsing whole-genome sequencing, we discovered that urine TR-ctDNA fragments across multiple cancer types are predominantly ultrashort (<50 bp) and, therefore, likely to be missed by conventional ctDNA assays. We developed an ultrashort droplet digital PCR assay to detect TR-ctDNA originating from HPV-associated oropharyngeal squamous cell carcinoma (HPV+ OPSCC) and confirmed that assaying ultrashort DNA is critical for sensitive cancer detection from urine samples.ResultsTR-ctDNA was concordant with plasma ctDNA for cancer detection in patients with HPV+ OPSCC. As proof of concept for using urine TR-ctDNA for posttreatment surveillance, in a small longitudinal case series, TR-ctDNA showed promise for noninvasive detection of recurrence of HPV+ OPSCC.ConclusionOur data indicate that focusing on ultrashort fragments of TR-ctDNA will be important for realizing the full potential of urine-based cancer diagnostics. This has implications for urine-based detection of a wide variety of cancer types and for facilitating access to care through at-home specimen collections.FundingNIH grants R33 CA229023, R21 CA225493; NIH/National Cancer Institute grants U01 CA183848, R01 CA184153, and P30CA046592; American Cancer Society RSG-18-062-01-TBG; American Cancer Society Mission Boost grant MBGI-22-056-01-MBG; and the A. Alfred Taubman Medical Research Institute.

Characterization and mitigation of artifacts derived from NGS library preparation due to structure-specific sequences in the human genome.

BACKGROUND: Hybridization capture-based targeted next generation sequencing (NGS) is gaining importance in routine cancer clinical practice. DNA library preparation is a fundamental step to produce high-quality sequencing data. Numerous unexpected, low variant allele frequency calls were observed in libraries using sonication fragmentation and enzymatic fragmentation. In this study, we investigated the characteristics of the artifact reads induced by sonication and enzymatic fragmentation. We also developed a bioinformatic algorithm to filter these sequencing errors. RESULTS: We used pairwise comparisons of somatic single nucleotide variants (SNVs) and insertions and deletions (indels) of the same tumor DNA samples prepared using both ultrasonic and enzymatic fragmentation protocols. Our analysis revealed that the number of artifact variants was significantly greater in the samples generated using enzymatic fragmentation than using sonication. Most of the artifacts derived from the sonication-treated libraries were chimeric artifact reads containing both cis- and trans-inverted repeat sequences of the genomic DNA. In contrast, chimeric artifact reads of endonuclease-treated libraries contained palindromic sequences with mismatched bases. Based on these distinctive features, we proposed a mechanistic hypothesis model, PDSM (pairing of partial single strands derived from a similar molecule), by which these sequencing errors derive from ultrasonication and enzymatic fragmentation library preparation. We developed a bioinformatic algorithm to generate a custom mutation "blacklist" in the BED region to reduce errors in downstream analyses. CONCLUSIONS: We first proposed a mechanistic hypothesis model (PDSM) of sequencing errors caused by specific structures of inverted repeat sequences and palindromic sequences in the natural genome. This new hypothesis predicts the existence of chimeric reads that could not be explained by previous models, and provides a new direction for further improving NGS analysis accuracy. A bioinformatic algorithm, ArtifactsFinder, was developed and used to reduce the sequencing errors in libraries produced using sonication and enzymatic fragmentation.

Analytical validation of NeXT Personal®, an ultra-sensitive personalized circulating tumor DNA assay.

We describe the analytical validation of NeXT Personal®, an ultra-sensitive, tumor-informed circulating tumor DNA (ctDNA) assay for detecting residual disease, monitoring therapy response, and detecting recurrence in patients diagnosed with solid tumor cancers. NeXT Personal uses whole genome sequencing of tumor and matched normal samples combined with advanced analytics to accurately identify up to ~1,800 somatic variants specific to the patient's tumor. A personalized panel is created, targeting these variants and then used to sequence cell-free DNA extracted from patient plasma samples for ultra-sensitive detection of ctDNA. The NeXT Personal analytical validation is based on panels designed from tumor and matched normal samples from two cell lines, and from 123 patients across nine cancer types. Analytical measurements demonstrated a detection threshold of 1.67 parts per million (PPM) with a limit of detection at 95% (LOD95) of 3.45 PPM. NeXT Personal showed linearity over a range of 0.8 to 300,000 PPM (Pearson correlation coefficient = 0.9998). Precision varied from a coefficient of variation of 12.8% to 3.6% over a range of 25 to 25,000 PPM. The assay targets 99.9% specificity, with this validation study measuring 100% specificity and in silico methods giving us a confidence interval of 99.92 to 100%. In summary, this study demonstrates NeXT Personal as an ultra-sensitive, highly quantitative and robust ctDNA assay that can be used to detect residual disease, monitor treatment response, and detect recurrence in patients.

Precision cancer classification using liquid biopsy and advanced machine learning techniques.

Cancer presents a significant global health burden, resulting in millions of annual deaths. Timely detection is critical for improving survival rates, offering a crucial window for timely medical interventions. Liquid biopsy, analyzing genetic variations, and mutations in circulating cell-free, circulating tumor DNA (cfDNA/ctDNA) or molecular biomarkers, has emerged as a tool for early detection. This study focuses on cancer detection using mutations in plasma cfDNA/ctDNA and protein biomarker concentrations. The proposed system initially calculates the correlation coefficient to identify correlated features, while mutual information assesses each feature's relevance to the target variable, eliminating redundant features to improve efficiency. The eXtrem Gradient Boosting (XGBoost) feature importance method iteratively selects the top ten features, resulting in a 60% dataset dimensionality reduction. The Light Gradient Boosting Machine (LGBM) model is employed for classification, optimizing its performance through a random search for hyper-parameters. Final predictions are obtained by ensembling LGBM models from tenfold cross-validation, weighted by their respective balanced accuracy, and averaged to get final predictions. Applying this methodology, the proposed system achieves 99.45% accuracy and 99.95% AUC for detecting the presence of cancer while achieving 93.94% accuracy and 97.81% AUC for cancer-type classification. Our methodology leads to enhanced healthcare outcomes for cancer patients.

Circulating Tumor DNA (ctDNA) and Its Role in Gynecologic Malignancies.

OPINION STATEMENT: Circulating tumor DNA (ctDNA) refers to small fragments of DNA released into the bloodstream by cancer cells. It is obtained through "liquid biopsy;" which most commonly refers to plasma or blood samples, but can be obtained from a number of bodily fluids including ascitic fluid, saliva, and even urine and stool. ctDNA is detected via polymerase chain reaction (PCR) or next-generation sequencing (NGS). The DNA from these samples is analyzed for the detection of point mutations, copy-number alterations, gene fusion, and DNA methylation. These results have the potential for use in cancer diagnosis, determining prognosis, targeting gene-specific therapies, and monitoring for/predicting disease recurrence and response to treatment. ctDNA offers an alternative to tissue biopsy; it is less invasive and can be monitored serially over time without multiple procedures. Moreover it may have the ability to detect disease recurrence or predict behavior in a way that solid tissue biopsies, tumor marker surveillance, and imaging cannot. Recent explosion in interest in ctDNA shows promising developments for widespread adoption of these techniques in cancer care. However, the use of ctDNA in diagnosis and treatment of gynecologic malignancies is currently limited, compared to adoption in other solid-organ tumors such as breast and colorectal cancers. Compared to other cancer types, there appear to be fewer comprehensive studies and clinical validations specifically focusing on the use of ctDNA in gynecologic cancers. More research is needed in this area to advance the potential for use of ctDNA in ovarian, endometrial, and cervical cancers before this can be routinely adopted to improve care for patients with gynecologic malignancies.

Red blood cells function as reservoirs of tumor DNA.

Novel screening techniques for early detection of lung cancer are urgently needed. Profiling circulating tumor cell-free DNA (ctDNA) has emerged as a promising tool for biopsy-free tumor genotyping. However, both the scarcity and short half-life of ctDNA substantially limit the sensitivity and clinical utility of ctDNA detection methodologies. Our discovery that red blood cells (RBCs) sequester mitochondrial DNA opens a new avenue for detecting circulating nucleic acids, as RBCs represent an unrecognized reservoir of circulating nucleic acid. Here, we show that RBCs acquire tumor DNA following coculture with lung cancer cell lines harboring Kirsten rat sarcoma viral oncogene homolog (KRAS) and epidermal growth factor receptor (EGFR) mutations. RBC-bound tumor DNA is detectable in patients with early-stage non-small cell lung cancer (NSCLC) but not in healthy controls by qPCR. Our results collectively uncover a previously unrecognized yet easily accessible reservoir of tumor DNA, offering a promising foundation for future RBC-based tumor diagnostics.NEW & NOTEWORTHY We present a novel method for lung cancer detection by revealing RBCs as a reservoir for tumor DNA, overcoming the limitations of current circulating tumor ctDNA methodologies. By demonstrating that RBCs can capture tumor DNA, including critical mutations found in lung cancer, we provide a promising, biopsy-free avenue for early cancer diagnostics. This discovery opens up exciting possibilities for developing RBC-based diagnostic tools, significantly enhancing the sensitivity and clinical utility of noninvasive cancer detection.

Application of plasma circulating KRAS mutations as a predictive biomarker for targeted treatment of pancreatic cancer.

Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations in circulating tumor deoxyribonucleic acid (ctDNA) have been reported as representative noninvasive prognostic markers for pancreatic ductal adenocarcinoma (PDAC). Here, we aimed to evaluate single KRAS mutations as prognostic and predictive biomarkers, with an emphasis on potential therapeutic approaches to PDAC. A total of 128 patients were analyzed for multiple or single KRAS mutations (G12A, G12C, G12D, G12R, G12S, G12V, and G13D) in their tumors and plasma using droplet digital polymerase chain reaction (ddPCR). Overall, KRAS mutations were detected by multiplex ddPCR in 119 (93%) of tumor DNA and 68 (53.1%) of ctDNA, with a concordance rate of 80% between plasma ctDNA and tumor DNA in the metastatic stage, which was higher than the 44% in the resectable stage. Moreover, the prognostic prediction of both overall survival (OS) and progression-free survival (PFS) was more relevant using plasma ctDNA than tumor DNA. Further, we evaluated the selective tumor-suppressive efficacy of the KRAS G12C inhibitor sotorasib in a patient-derived organoid (PDO) from a KRAS G12C-mutated patient using a patient-derived xenograft (PDX) model. Sotorasib showed selective inhibition in vitro and in vivo with altered tumor microenvironment, including fibroblasts and macrophages. Collectively, screening for KRAS single mutations in plasma ctDNA and the use of preclinical models of PDO and PDX with genetic mutations would impact precision medicine in the context of PDAC.

Analytical evaluation of circulating tumor DNA sequencing assays.

In China, circulating tumor DNA analysis is widely used and numerous assays are available. Systematic evaluation to help users make informed selections is needed. Nine circulating tumor DNA assays, including one benchmark assay, were evaluated using 23 contrived reference samples. There were two sample types (cell-free DNA and plasma samples), three circulating tumor DNA inputs (low, < 20 ng; medium, 20-50 ng; high, > 50 ng), two variant allele frequency ranges (low, 0.1-0.5%; intermediate, 0.5-2.5%), and four variant types (single nucleotide, insertion/deletion, structural, and copy number). Sensitivity, specificity, reproducibility, and all processes from cell-free DNA extraction to bioinformatics analysis were assessed. The test assays were generally comparable or superior to the benchmark assay, demonstrating high analytical sensitivity. Variations in circulating tumor DNA extraction and quantification efficiency, sensitivity, and reproducibility were observed, particularly at lower inputs. These findings will guide circulating tumor DNA assay choice for research and clinical studies, allowing consideration of multiple technical parameters.

Clinical Application of Liquid Biopsy in Pancreatic Cancer: A Narrative Review.

Pancreatic ductal adenocarcinoma contributes significantly to global cancer-related deaths, featuring only a 10% survival rate over five years. The quest for novel tumor markers is critical to facilitate early diagnosis and tailor treatment strategies for this disease, which is key to improving patient outcomes. In pancreatic ductal adenocarcinoma, these markers have been demonstrated to play a crucial role in early identification, continuous monitoring, and prediction of its prognosis and have led to better patient outcomes. Nowadays, biopsy specimens serve to ascertain diagnosis and determine tumor type. However, liquid biopsies present distinct advantages over conventional biopsy techniques. They offer a noninvasive, easily administered procedure, delivering insights into the tumor's status and facilitating real-time monitoring. Liquid biopsies encompass a variety of elements, such as circulating tumor cells, circulating tumor DNA, extracellular vesicles, microRNAs, circulating RNA, tumor platelets, and tumor endothelial cells. This review aims to provide an overview of the clinical applications of liquid biopsy as a technique in the management of pancreatic cancer.

Circulating Tumor DNA in the Immediate Postoperative Setting.

BACKGROUND: Circulating tumor DNA (ctDNA) has emerged as an accurate real-time biomarker of disease status across many solid tumor types. Most studies evaluating the utility of ctDNA have focused on time points weeks to months after surgery, which, for many cancer types, is significantly later than decision-making time points for adjuvant treatment. In this systematic review, we summarize the state of the literature on the feasibility of using ctDNA as a biomarker in the immediate postoperative period. METHODS: We performed a systematic review evaluating the early kinetics, defined here as 3 days of ctDNA in patients who underwent curative-intent surgery. RESULTS: Among the 2057 studies identified, eight cohort studies met the criteria for evaluation. Across six different cancer types, all studies showed an increased risk of cancer recurrence in patients with detectable ctDNA in the immediate postoperative period. CONCLUSION: While ctDNA clearance kinetics appear to vary based on tumor type, across all studies detectable ctDNA after surgery was predictive of recurrence, suggesting early postoperative time points could be feasibly used for determining minimal residual disease. However, larger studies need to be performed to better understand the precise kinetics of ctDNA clearance across different cancer types as well as to determine optimal postoperative time points.

Plasma cell-free DNA in canine lymphoma patients as a novel material for genotyping.

Canine lymphoma is a disease with high morbidity and poor long-term prognosis, despite a high response rate to chemotherapy. In this study, we focused on liquid biopsy, in which small amounts of substances from body fluids were analysed, to determine whether cell-free DNA (cfDNA) in the plasma can be used as a biomarker for lymphoma in dogs. We found that 23 patients with lymphoma had significantly higher cfDNA concentrations than the 12 healthy dogs (median 2360 ng/mL versus 299 ng/mL, p < .0001). Polymerase chain reaction for antigen receptor rearrangement (PARR) was also employed using cfDNA from the lymphoma group to investigate whether cfDNA could be used for the detection of genetic clonality of lymphomas, as well as the genomic DNA (gDNA) extracted from an original lesion in each case. The correlation of the PARR results between cfDNA and gDNA was observed in 100% of B-cell lymphomas (10/10), 77.8% of T-cell lymphomas (7/9), and 100% of other types of lymphomas (4/4), respectively. These results indicate that plasma cfDNA levels are increasing in canine lymphoma patients, that cfDNA concentration can be a novel diagnostic tool, and that it can be used as a diagnostic tool for PARR.

Use of Multiple Machine Learning Approaches for Selecting Urothelial Cancer-Specific DNA Methylation Biomarkers in Urine.

Diagnosing urothelial cancer (UCa) via invasive cystoscopy is painful, specifically in men, and can cause infection and bleeding. Because the UCa risk is higher for male patients, urinary non-invasive UCa biomarkers are highly desired to stratify men for invasive cystoscopy. We previously identified multiple DNA methylation sites in urine samples that detect UCa with a high sensitivity and specificity in men. Here, we identified the most relevant markers by employing multiple statistical approaches and machine learning (random forest, boosted trees, LASSO) using a dataset of 251 male UCa patients and 111 controls. Three CpG sites located in ALOX5, TRPS1 and an intergenic region on chromosome 16 have been concordantly selected by all approaches, and their combination in a single decision matrix for clinical use was tested based on their respective thresholds of the individual CpGs. The combination of ALOX5 and TRPS1 yielded the best overall sensitivity (61%) at a pre-set specificity of 95%. This combination exceeded both the diagnostic performance of the most sensitive bioinformatic approach and that of the best single CpG. In summary, we showed that overlap analysis of multiple statistical approaches identifies the most reliable biomarkers for UCa in a male collective. The results may assist in stratifying men for cystoscopy.

Tumor-Informed Circulating Tumor DNA for Minimal Residual Disease Detection in the Management of Colorectal Cancer.

PURPOSE: Recurrence after curative-intent treatment occurs in 20%-50% of patients with stage II-IV colorectal cancer (CRC), underscoring the need for early detection of minimal residual disease (MRD) using circulating tumor DNA (ctDNA). Here, we examined the pattern of use of a tumor-informed ctDNA assay in CRC MRD monitoring in routine clinical practice at Mayo Clinic, Rochester. METHODS: We conducted a retrospective analysis of health records of patients with CRC who had at least one tumor-informed ctDNA assay from May 2019 through July 1, 2022. Recurrence was defined as radiographic evidence of disease. Descriptive characteristics of the cohort, ctDNA results, and subsequent interventions were recorded. RESULTS: Of the 120 patients included, the median age at diagnosis was 67 years, 46% were female, and 94% were White. At diagnosis, 10 patients had stage I, 23 stage II, 60 stage III, and 25 stage IV disease. Of 476 ctDNA assays performed, 70% were performed in patients who had recurrent disease most commonly to monitor the effectiveness of therapeutic interventions and 16% resulted in a change in clinical decision making. There were 110 recurrences identified in 62 patients, as some patients experienced more than one recurrence over time. Compared with serum carcinoembryonic antigen levels, ctDNA results correlated better with radiologic imaging. CONCLUSION: Routine ctDNA monitoring for MRD detection has been adopted in clinical practice; however, 84% of ctDNA assays performed did not result in a change in clinical management. This suggests the need for further clinical research data to guide routine clinical use of ctDNA MRD testing in CRC.

Liquid biopsy in lung cancer.

Lung cancer is a highly prevalent malignancy worldwide and the primary cause of mortality. The absence of systematic and standardized diagnostic approaches for identifying potential pulmonary nodules, early-stage cancers, and indeterminate tumors has led clinicians to consider tissue biopsy and pathological sections as the preferred method for clinical diagnosis, often regarded as the gold standard. The conventional tissue biopsy is an invasive procedure that does not adequately capture the diverse characteristics and evolving nature of tumors. Recently, the concept of 'liquid biopsy' has gained considerable attention as a promising solution. Liquid biopsy is a non-invasive approach that facilitates repeated analysis, enabling real-time monitoring of tumor recurrence, metastasis, and response to treatment. Currently, liquid biopsy includes circulating tumor cells, circulating cell-free DNA, circulating tumor DNA, circulating cell-free RNA, extracellular vesicles, and other proteins and metabolites. With rapid progress in molecular technology, liquid biopsy has emerged as a highly promising and intriguing approach, yielding compelling results. This article critically examines the significant role and potential clinical implications of liquid biopsy in the diagnosis, treatment, and prognosis of lung cancer.

Impact of the quality of resected thyroid cancer tissue sample on next-generation sequencing testing.

Activating rearranged during transfection (RET) proto-oncogene alterations can be identified using next-generation sequencing (NGS) of tumor DNA/RNA. We assessed factors associated with NGS (Oncomine Dx Target Test [ODxTT]) success for resected thyroid cancer (TC) specimens, including sample age, processing conditions, and DNA/RNA quality. TC samples were from three Japanese hospitals, with sample age <1-<10 years, fixative 10%/15% neutralized buffered formalin (NBF), and fixation time ≤48 h/>48 h-≤72 h. NGS success rate was defined as the percentage of samples returning validated NGS results (RET fusion-positive/negative [RNA] or RET mutation-positive/negative [DNA], detected using ODxTT). DNA/RNA quality was assessed with indexes based on electrophoresis (DNA/RNA integrity number, DV200 ) and quantitative polymerase chain reaction (DNA/RNA integrity score [ddCq/ΔCq]). NGS success rate (N = 202) was 90%/93% (DNA/RNA) overall, 98%-100% (DNA and RNA) for samples <3 years old, and 91% (DNA and RNA) for samples ≥3-<5 years old fixed in 10% NBF for ≤48 h. Multivariate logistic regression analysis identified ddCq and ΔCq as significant predictors of DNA and RNA NGS success rates, respectively. Quality assessment of nucleic acid extracted from archival tissue samples is important for achieving high NGS success rates in clinical practice, especially for samples ≥3 years old.