Analytical Validation of Quantitative Polymerase Chain Reaction and AscentTM Low-Pass Whole Genome Sequencing to Report on Gene Copy Number Variants in Cerebrospinal Fluid Tumor-Derived DNA
by
, , , ,
Viriya Keo
†
,
Sakshi Khurana
†,
Vindhya Udhane
,
Alexandra Larson
,
Jennifer N. Adams
,
Daniel Sanchez
,
Tarin Peltier
,
Anthony Acevedo
,
Kathleen Mitchell
,
Kala F. Schilter
,
Qian Nie
and
Honey V. Reddi
* Belay Diagnostics, 1375 W. Fulton St, Suite 530, Chicago, IL 60607, USA
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
J. Mol. Pathol. 2026, 7(2), 18; https://doi.org/10.3390/jmp7020018
Submission received: 24 March 2026
/
Revised: 3 May 2026
/
Accepted: 9 May 2026
/
Published: 12 May 2026
Abstract
Background: Evaluation of gene-level copy number variants (CNVs) for diagnosis and therapeutic decision making has become standard of care with next-generation sequencing (NGS), immunohistochemistry (IHC), and/or fluorescence in situ hybridization (FISH) being used to detect gene amplifications/deletions in tumor tissue. In contrast to most solid tumors, CNS cancers are challenging to evaluate by resection and/or biopsy due to the associated risks with invasive brain surgery that can also result in death or associated morbidity and therefore alternate methods are required.Methods: This study presents the analytical validation of using quantitative PCR (qPCR) to detect gene CNVs directly from cerebrospinal fluid (CSF)-derived DNA and from the AscentTM low-pass whole genome sequencing (LP-WGS) libraries, demonstrating concordance with the gold standard of NGS/IHC/FISH used in tumor tissue. Results: The analytical sensitivity of qPCR to detect gene amplification calls for ERBB2 (erb-b2 receptor tyrosine kinase 2) was demonstrated to be 100% and that of EGFR (epidermal growth factor receptor) was 83%, with specificities of 96% and 100%, respectively. The analytical sensitivity of qPCR to detect gene deletions for CDKN2A/2B (cyclin-dependent kinase inhibitor 2A/2B) was 60% and that for MTAP (methylthioadenosine phosphorylase) was 100% with a specificity of 100% for all three genes. AscentTM was demonstrated to have a higher sensitivity (100%) when compared to qPCR for the same genes evaluated and demonstrated 100% positive agreement and 100% negative agreement with known CNV status. Conclusions: The results demonstrate that given the paucity of cells in CSF limiting the use of IHC and FISH, qPCR and AscentTM provide highly sensitive, novel, minimally invasive methods for the evaluation of gene copy number (CN) status to inform the diagnosis and management of CNS cancers.
1. Introduction
Gene-level copy number variants (CNVs) involve abnormal gains (amplifications) or losses (deletions) of specific DNA segments, driving cancer progression, metastasis, and treatment resistance with TP53, MYC, EGFR, PIK3CA, and ERBB2 frequently affected. In primary central nervous system (CNS) cancers, outside of chromosome arm-level aneuploidy, key gene-level CNVs include the amplification of EGFR and deletion of the CDKN2A/B locus as outlined in National Comprehensive Cancer Network (NCCN) guidelines [1]. Other genes known to be affected in glioblastoma include PTEN [2] and RB1 [3] deletions and PDGFRA [2] amplification. Metastatic CNS cancers include ERBB2 amplification for breast primary [4] and MET/MYC amplification [5] for lung primary. To determine actionability for cancer, the detection of focal gene amplifications [6] and deletions [7] in tumor tissue using immunohistochemistry (IHC), which detects protein expression, and/or fluorescence in situ hybridization (FISH), which detects amplification at the DNA level, has become the standard of care [8]. Advances in technology have now facilitated the use of next-generation sequencing (NGS) to evaluate gene-level CNVs in solid tumors [9] with a natural progression to evaluate cell-free DNA (cfDNA) in peripheral blood (plasma) [10] to aid in establishing minimally invasive diagnosis and quicker therapeutic decision making.
In contrast to most solid tumors, CNS cancers are challenging to evaluate by resection and/or biopsy due to the associated risks with invasive brain surgery that can also result in death or associated morbidity [11]. To obviate these challenges, plasma liquid biopsy has been used to inform the diagnosis and management of CNS tumors, which is expected to have limited sensitivity due to the blood–brain barrier (BBB) [12], prompting the use of cerebrospinal fluid (CSF) as a more effective liquid biopsy option for CNS tumors. Belay recently launched a portfolio of CSF-based liquid biopsy tests, including the following: SummitTM 2.0, a comprehensive genomic profiling (CGP) test that evaluates 521 genes for single-nucleotide variants, gene-level copy number variants, fusions, tumor mutation burden (TMB), and microsatellite instability (MSI) [13]; AscentTM, which uses low-pass whole-genome sequencing (LP-WGS) to enable detection of chromosome arm-level copy number (CN) variants (loss and/or gain) [14]; and VantageTM, which reports on MGMT promoter methylation status [15]. Both AscentTM and VantageTM leverage the previously described MethySaferSeqS duplex sequencing methodology [16] which facilitates simultaneous genomic and epigenomic profiling within the same specimen.
Given the paucity of cells in CSF resulting in exceptionally low yields of DNA, the development of quantitative PCR (qPCR) as an alternative methodology was considered to provide results on gene-level CNVs to inform therapy decision making. As such, the test was validated using both CSF-derived DNA directly as well as LP-WGS libraries generated for the AscentTM test as input material. This study presents the analytical validation of detecting gene CNVs from low-input CSF-derived DNA and AscentTM libraries using qPCR with clinical concordance to available tumor profiling results. Additionally, assuming that direct qPCR may not always be feasible given the low yields of CSF DNA and that Belay AscentTM has been validated using extremely low-input DNA [14], the equivalence of reporting gene-level CNVs directly from AscentTM data is also demonstrated, obviating the need for qPCR when applicable.
2. Materials and Methods
2.1. Specimen Cohort
The analytical validation cohort (n = 75) included 16 no-template controls (NTC), 3 contrived controls (Seraseq ctDNA Mutation Mix 5% (Cat # 0710-0528), Seraseq ctDNA Mutation Mix WT 0% (Cat # 0710-0533), and SeraSeq Solid tumor CNV mix (Cat # 0710-2867)), 20 CSF presumed normal, non-cancer cases, 36 CSF specimens with known gene amplification or deletion status, ERBB2 amplification (n = 19), EGFR amplification (n = 10), CDKN2A/2B deletion (n = 5), and MTAP deletions (n = 2). The 36 samples comprised 2 primary CNS tumor specimens and 34 secondary CNS tumor specimens (Supplementary Table S1). The concordance cohort (n = 58) evaluated specimens that had accompanying tumor profiling results using both qPCR and AscentTM library calls and included specimens used in the validation cohort. A total of 39 specimens were evaluated for amplifications: ERBB2 (n = 19), EGFR (n = 10), and 10 CSF presumed normal. For deletions, 19 samples were evaluated: 10 specimens with CDKN2A/2B and MTAP loss and 9 CSF presumed normal. CSF presumed normal specimens used in the study were commercially obtained de-identified samples with no associated clinical information (LabCorp, Burlington, NC, USA). CSF specimens with known tumor profiling results were obtained from samples received for clinical testing that were de-identified prior to assay validation.
2.2. Quantitative Polymerase Chain Reaction (qPCR) to Detect ERBB2 and EGFR Amplification and CDKN2A/2B and MTAP Deletion
Limit of Input (LoI) was demonstrated using different concentrations (2–10 ng) of CSF tumor-derived DNA (tDNA) or amplified libraries from the AscentTM workflow for both contrived controls and clinical CSF specimens, which were used to perform qPCR for ERBB2 (Thermo Scientific, Waltham, MA, USA, Hs00817646_cn, Catalog #4400291), EGFR (Thermo Scientific, Waltham, MA, USA, Hs04960197_cn, Catalog #4400291), CDKN2A/2B (Thermo Scientific, Waltham, MA, USA, Hs03714372_cn, Hs02900430_cn, Catalog #4400291), and MTAP (Thermo Scientific, Waltham, MA, USA, Hs02079487_cn, Catalog #4400291). Delta Ct values were compared to the RNAseP reference (Thermo Scientific, Waltham, MA, USA, Catalog #4403326), and fold CN change was calculated. Limit of Detection (LoD) CN cut-offs from qPCR (Supplementary Table S2) were established as follows for gene amplifications: normal or no amplification (≥0 and <2.5 copies), positive for amplification (≥2.5 copies); and for gene deletions: normal or no deletion (≤0 and >−2 copies) and positive for deletion (≤−2). Concordance between known CN status and qPCR calls was used to determine sensitivity and specificity of qPCR and confirm LoD cut-offs to evaluate equivalence with calls from AscentTM data (Figure 1).
2.3. Detection of Gene-Level CNVs from AscentTM Low-Pass Whole-Genome Sequencing (LP-WGS) Data
After the sequencing of AscentTM libraries, chromosomal arm-level loss/gain was evaluated after demultiplexing and alignment [14] for all samples evaluated by qPCR. Log2R (number of copies relative to the Panel of Normals) thresholds were used to establish a cut-off seg.mean (average number of copies of a specific DNA segment) value for gene amplification and deletion calls at the arm level. Seg.mean values are used as proxy for tumor fraction in the evaluation of CNVs from LP-WGS [17]. For amplifications, a seg.mean cut-off of ≥0.1 was set for gain and ≥0 to <0.1 was set for no CN change, and for deletions, a seg.mean cut-off of ≤−0.2 was set for loss and ≤0 to >−0.2 was set for no CN change (Supplementary Table S2). The AscentTM calls for ERBB2 (chr17: 37500001–38000000), EGFR (chr7: 55000001–62500000), and CDKN2A/2B/MTAP (chr9: 21500001–23000000) for CN status were then correlated to values from qPCR to determine equivalence across both methodologies. Accuracy of using AscentTM to call focal amplification and deletion of genes was calculated to determine sensitivity and specificity of the methodology. Clinical concordance of AscentTM to tumor profiling results in calling gene-level CN variants in terms of positive percent agreement and negative percent agreement was determined to establish equivalence to qPCR and gold standard of IHC/FISH.
3. Results
3.1. Low-Input tDNA from CSF or AscentTM LP-WGS Libraries Is Sufficient for qPCR to Detect Gene Amplifications and Deletions
Limit of Input (LoI) studies using different concentrations (2, 4, 6, 8, and 10 ng) of DNA from contrived controls (n = 3) and CSF tDNA directly and from AscentTM LP-WGS libraries, respectively, for clinical CSF specimens (n = 5) were evaluated to determine the lowest DNA input required to provide consistent, accurate gene amplification and deletion calls. Concordant CN calls in terms of the gene loss or gain were determined across both input materials for all inputs, demonstrating that 2 ng of tDNA or AscentTM (LP-WGS) library DNA was sufficient to evaluate the CN status of ERBB2 and EGFR. Minor differences in fold change observed across different DNA inputs did not impact CN calls for either gene, with qPCR values being concordant to expected CN status, indicating that either could serve as a starting material for the evaluation of gene-level amplification. The results also confirmed the established CN cut-offs for qPCR to be ≥0 and <2.5 copies for normal or no amplification of either gene or ≥2.5 copies to be positive for amplification/gain of either gene (Supplementary Table S2), demonstrating the limit of detection (LoD) to be greater than two copies for amplifications.
Based on the limit of input results for calling gene amplifications, 2 ng from AscentTM LP-WGS libraries of contrived controls (n = 3) and clinical CSF specimens (n = 5) was used to evaluate CDKN2A/2B and MTAP deletions. The results established the CN cut-offs for deletions by qPCR to be <0 and ≥−2 copies for normal or no deletion of either gene or ≤−2.0 copies to be positive for deletion/loss of either gene (Supplementary Table S2), establishing the LoD for reporting on CNV deletions to be the loss of both copies (homozygous deletion).
3.2. Gene Amplification and Deletions Can Be Detected Using AscentTM LP-WGS Libraries by qPCR
Limit of Blank (LoB) studies using AscentTM (LP-WGS) library DNA from 11 clinical CSF samples with presumed normal CN status demonstrated amplification in one specimen for ERBB2 (potential false positive) and no amplification for EGFR (true negatives) (Table 1) across an average of three different independent operators. Accuracy studies evaluated clinical CSF with known ERBB2 status (n = 19) and known EGFR status (n = 10) based on tumor profiling results with qPCR to further confirm the CN cut-offs. In the ERBB2 cohort, one specimen failed amplification and the remaining showed 100% concordance between qPCR calls and known ERBB2 status (Table 1). In the EGFR cohort, one specimen with a known gain of EGFR had a qPCR call of normal, indicating a potential false negative based on provided clinical information (Table 1). These results demonstrated an analytical sensitivity of 100% and specificity of 96% for the evaluation of ERBB2 CN status and 83% sensitivity and 100% specificity, respectively, for EGFR CN status by qPCR (Table 2). The false positive observed with ERBB2 was just above the qPCR CN cut-off threshold of 2.5 (2.72), and the false negative observed with EGFR was just below the CN cut-off threshold of 2.5 (2.12), suggesting a likely higher signal-to-noise ratio in these two cases and mildly impacting the sensitivity and specificity for these genes.
To evaluate deletions, Limit of Blank (LoB) studies using AscentTM (LP-WGS) library DNA from nine clinical CSF samples with presumed normal CN status demonstrated no loss for CDKN2A/2B and MTAP (true negatives) (Table 1) across an average of three different independent operators. Accuracy studies evaluated clinical CSF with known CDKN2A/2B status (n = 5) and known MTAP status (n = 2) based on tumor profiling results with qPCR to further confirm the CN cut-offs. In the CDKN2A/2B cohort, two specimens failed to detect loss, and the remaining showed 100% concordance between qPCR calls and known CDKN2A/2B status. In the MTAP cohort, both specimens showed 100% concordance between qPCR calls and known MTAP status (Table 1). These results demonstrate that the analytical sensitivity of qPCR to detect gene deletions for CDKN2A/2B was 60% and that for MTAP was 100% with a specificity of 100% for all three genes (Table 2). Evaluation of the ichor plots for the two false negative CDKN2A/B cases showed a significant loss of chr 9, likely impacting primer binding and therefore the performance of qPCR.
3.3. Equivalence of AscentTM CN Calls with Known CNV Status Compared to qPCR Results
To demonstrate equivalence of AscentTM in calling gene-level CNVs, LP-WGS data from all clinical CSF specimens evaluated by qPCR (Table 1) for ERBB2 (n = 30), EGFR (n = 19), CDKN2A/2B, and MTAP (n = 10) was evaluated for the log2R and seg.mean values. Though a seg.mean cut-off of ≥0.2 was set for gain and ≤0 to <0.2 was set for no CN change, the AscentTM results for both ERBB2 (Figure 2, top panels) and EGFR (Figure 2, middle panels) demonstrated that a seg.mean ≥0.1 indicated the gain (amplification) of CN at the gene level (Table 1), establishing the LoD for amplifications to be ≥0.1 (Supplementary Table S1). In the ERBB2 cohort, for the single specimen that qPCR called a gain, AscentTM matched the predicted CNV status of no ERBB2 CN change, demonstrating a higher specificity to qPCR (Table 1). Similarly, in the EGFR cohort for the single specimen that qPCR called a “no change” in CNV status, AscentTM confirmed a CN gain, demonstrating a higher sensitivity to qPCR (Table 2).
For the CDKN2A/B and MTAP deletions evaluated, the results show that the established seg.mean thresholds of ≤−0.2 for loss and ≤0 to >−0.2 for no CN change for AscentTM data correlated well with the observed qPCR results and known CN status (Table 1). Concordance results between qPCR and tumor profiling results establish that CDKN2A/2B and MTAP (Figure 2 (bottom panels) and Table 1) are considered to be deleted when seg.mean is ≤−0.2 and have no CN change when seg.mean is ≤0 and >−0.2 (Supplementary Table S2). Overall, the results demonstrate that calling gene amplifications and deletions has higher accuracy (a 100% sensitivity and specificity) with AscentTM LP-WGS compared to qPCR for the genes evaluated based on 100% concordance (positive percent agreement and negative percent agreement) to the known CN status from the tumor profiling results (Table 2). The tumor profiling results did not specify a homozygous or heterozygous deletion of CDKN2A/B and MTAP, and, therefore, at this time, the assay is not able to distinguish between homozygous and heterozygous deletions.
4. Discussion
Brain surgery poses a significant risk to the patient including hemorrhage, neurological injury, stroke, or even death [11], and the emergence of CNS-penetrant systemic therapies [18] underscores the need for CSF liquid biopsy to fast-track diagnoses and therapeutic decision making regarding CNS tumors. Both primary and secondary CNS tumors have a considerable number of gene-level CNVs that inform diagnosis and management [1]. Recent advances in therapy have transformed the management of disease [18] with the advent of immune checkpoint inhibitors, and antibody-drug-conjugates (ADCs), particularly for gene amplifications. IHC and FISH are the most common methods used to detect gene amplifications in tumor tissue, with quantitative reverse transcription PCR (qRT-PCR) being recently used to detect RNA levels correlative to gene expression [6] in fine-needle aspirate biopsies. IHC and FISH require a large sample input that is not feasible in CSF due to its low cellularity, therefore requiring low-input and high-sensitivity methodologies. Advances in technology have facilitated the use of NGS for comprehensive genomic profiling including gene-level CNVs; however, this methodology also has certain limitations in CSF given the high complexity, longer turnaround times, and requirement for higher DNA inputs.
In this context, qPCR represents a highly practical tool due to its rapid turnaround time, low DNA input requirements, and ease of implementation in clinical laboratories [19]. This study presents the analytical validation of qPCR to detect gene amplifications and deletions using extremely low amounts of DNA (directly from CSF or from LP-WGS libraries generated for AscentTM), demonstrating high concordance with the gold standard of IHC/FISH in solid tumors. Additionally, since the AscentTM test is ordered independently or in combination with SummitTM 2.0, the study evaluated the equivalence of calling gene-level CNVs (amplification and deletions) from AscentTM LP-WGS data. The results show that AscentTM (LP-WGS) detects gene-level CNVs with a higher sensitivity than qPCR.
The accurate detection of gene-level CNVs is critical, as amplifications in genes such as ERBB2 and EGFR can inform eligibility for targeted therapies and antibody–drug conjugates, while deletions in tumor suppressor genes such as CDKN2A/2B and MTAP may provide important diagnostic and prognostic insights [20,21]. As demonstrated in this study, qPCR reliably detects gene amplifications with a high sensitivity and specificity (e.g., ERBB2 and EGFR) and, despite its lower sensitivity for certain deletions (e.g., CDKN2A/2B), it still provides clinically actionable information that can guide therapeutic decision making or prompt additional confirmatory testing, particularly when more comprehensive methods are not immediately available. The observed differences in sensitivity for amplifications vs. deletions could be due to challenges with chromosomal location or technical limitations in terms of primer design and assay performance. In case of the lower sensitivity observed with CDKN2A/2B, it was seen that the major loss of chr9 in both cases likely impacted qPCR performance.
The analytic validation and clinical sensitivity of Belay’s LP-WGS test (AscentTM) to detect chromosome arm level aneuploidy (loss/gain) have been previously established [14]. Post test launch, challenges related to limited nucleic acid yield necessitated the further evaluation of AscentTM for the accurate detection of focal gene-level CNVs (amplifications and deletions), with the goal of maximizing diagnostic yield and informing therapeutic decision making in low-input settings. In addition to qPCR, the AscentTM LP-WGS platform demonstrates significant clinical utility in reporting gene-level CNVs with a higher sensitivity, particularly in low-input CSF samples. The ability of LP-WGS to detect both broad chromosomal alterations and focal gene-level amplifications and deletions enables a more comprehensive assessment compared to targeted approaches [22,23]. Consistent with this, the results of the present study show that AscentTM achieved 100% PPA and 100% NPA in tumor informed clinical CSF specimens and resolved discordant cases observed with qPCR, highlighting its higher sensitivity and specificity. Additionally, clinical validation studies clearly demonstrate the impact of AscentTM in reporting on chromosome arm-level aneuploidy but more importantly on focal gene losses and gains to inform the diagnosis and management of primary and secondary CNS cancers [24].
Several limitations should be considered; for instance, the study evaluated a limited number of genes, which may not fully represent the spectrum of clinically relevant CNVs in CNS tumors. Sample sizes for certain analyses, particularly deletion cohorts, were small, likely impacting sensitivity estimates. Further, continued evaluation in a production setting will also help assess assay robustness across variable sample quality and DNA yield along with correlations of the effective resolution of gene-level amplification and deletion calls.
In conclusion, this study demonstrates that both qPCR and AscentTM (LP-WGS) enable the accurate detection of gene-level CNVs from low-input CSF-derived DNA. While qPCR provides a rapid and accessible method for targeted CNV analysis, AscentTM offers a higher sensitivity and accuracy from LP-WGS data. Together, these approaches represent complementary, minimally invasive strategies for the evaluation of focal gene CNV status to inform therapeutic decision making for primary and secondary CNS malignancies.
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jmp7020018/s1, Table S1: Provisional Diagnosis of 36 cancer specimens used in analytical validation; Table S2: Cut-offs for qPCR vs. AscentTM to detect gene-level CNVs.
Author Contributions
The study was conceived, designed, and overseen by H.V.R. All authors contributed to data collection and analysis. S.K., J.N.A., A.A., T.P., K.M. and D.S.—specimen processing, V.U., A.L., V.K., Q.N. and K.F.S.—data analysis and curation. The first draft of the manuscript was written by V.K. and H.V.R. and all authors commented on previous versions of the manuscript. All authors have read and agreed to the published version of the manuscript.
Funding
This study was partly supported by funding from the National Institutes of Health (NIH) (grant 1R42NS135834-01). The contents of the publication are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.
Institutional Review Board Statement
This study was conducted under an institutional IRB (Advarra) (PRO 00078800, approved 26 April 2024) that approved a full waiver of HIPAA authorization after determining that the waiver of authorization satisfies the criteria set forth in the HIPAA Privacy Rule at (45 CFR 164.512(i)(2)), in compliance with the principles of the Declaration of Helsinki and the Health Insurance Portability and Accountability Act (HIPAA).
Informed Consent Statement
Not applicable. CSF presumed normal specimens used in the study were commercially obtained de-identified samples with no associated clinical information (LabCorp, USA). CSF specimens with known tumor profiling results were obtained from samples received for clinical testing that were de-identified prior to assay validation.
Data Availability Statement
All available data is included in the manuscript.
Conflicts of Interest
All authors are employees of Belay Diagnostics and receive salary and options.
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Figure 1.
Analytical validation of using quantitative PCR to report on gene-level copy number variants (CNVs) in cerebrospinal fluid (CSF) tumor-derived DNA (tDNA) and establishing concordance/equivalence of AscentTM low-pass whole genome sequencing (LP-WGS) data to detect focal gene CNVs—schema and specimen cohort.
Figure 1.
Analytical validation of using quantitative PCR to report on gene-level copy number variants (CNVs) in cerebrospinal fluid (CSF) tumor-derived DNA (tDNA) and establishing concordance/equivalence of AscentTM low-pass whole genome sequencing (LP-WGS) data to detect focal gene CNVs—schema and specimen cohort.
Figure 2.
Representative ichor plots of gene-level amplifications and deletions for 5 genes validated by qPCR for amplifications (EGFR—top panels, ERBB2—middle panels) and deletions (CDKN2A/2B, MTAP—bottom panels). Left panels (all plots)—normal gene copy (no amplification or deletion). Right panels—amplifications (seg.mean > 0.1) and deletions (seg.mean ≤ −0.2). Dotted lines on bottom panels outline locations of MTAP and CDKN2A genes.
Figure 2.
Representative ichor plots of gene-level amplifications and deletions for 5 genes validated by qPCR for amplifications (EGFR—top panels, ERBB2—middle panels) and deletions (CDKN2A/2B, MTAP—bottom panels). Left panels (all plots)—normal gene copy (no amplification or deletion). Right panels—amplifications (seg.mean > 0.1) and deletions (seg.mean ≤ −0.2). Dotted lines on bottom panels outline locations of MTAP and CDKN2A genes.
Table 1.
Equivalence of gene amplification calls between known CNV status, qPCR, and AscentTM.
| Sample | Known CNV Status | Copy Number (qPCR) | qPCR Call | Seg.mean (LP-WGS) | AscentTM Call | Equivalence |
|---|---|---|---|---|---|---|
| ERBB2cases (n = 30) | ||||||
| ERBB2_01 (AV) | Amplified | 12.87 | Amplified | 2.31 | Gain | Yes |
| ERBB2_02 (AV) | Normal | 1.64 | Normal | −0.36 | Normal | Yes |
| ERBB2_03 (AV) | Normal | 1.87 | Normal | −0.46 | Normal | Yes |
| ERBB2_04 (AV) | Normal | 1.95 | Normal | −0.44 | Normal | Yes |
| ERBB2_05 (AV) | Normal | 1.97 | Normal | −0.21 | Normal | Yes |
| ERBB2_06 (AV) | Normal | 2.26 | Normal | −0.06 | Normal | Yes |
| ERBB2_07 (AV) | Amplified | 2.83 | Amplified | 0.43 | Gain | Yes |
| ERBB2_08 (AV) | Amplified | 4.06 | Amplified | 0.13 | Gain | Yes |
| ERBB2_09 (AV) | Amplified | 5.83 | Amplified | 0.76 | Gain | Yes |
| ERBB2_10 (AV) | Amplified | 9.6 | Amplified | 1.6 | Gain | Yes |
| ERBB2_11 (AV) | Amplified | 10.71 | Amplified | 1.2 | Gain | Yes |
| ERBB2_12 (AV) | Amplified | Sample exhausted | No results | 0.37 | Gain | Yes ** |
| ERBB2_13 (AV) | Normal | 1.89 | Normal | −0.01 | Normal | Yes |
| ERBB2_14 (AV) | Normal | 2.37 | Normal | −0.02 | Normal | Yes |
| ERBB2_15 (AV) | Normal | 2.21 | Normal | −0.07 | Normal | Yes |
| ERBB2_16 (AV) | Normal | 1.7 | Normal | −0.02 | Normal | Yes |
| ERBB2_17 (AV) | Normal | 2.22 | Normal | −0.02 | Normal | Yes |
| ERBB2_18 (AV) | Normal | 2.25 | Normal | −0.04 | Normal | Yes |
| ERBB2_19 (AV) | Amplified | 9.74 | Amplified | 1.6 | Gain | Yes |
| ERBB2_20 (LoB) | Normal | 2 | Normal | 0.05 | Normal | Yes |
| ERBB2_21 (LoB) | Normal | 1.85 | Normal | −0.02 | Normal | Yes |
| ERBB2_22 (LoB) | Normal | 2.01 | Normal | 0.01 | Normal | Yes |
| ERBB2_23 (LoB) | Normal | 2.11 | Normal | −0.03 | Normal | Yes |
| ERBB2_24 (LoB) | Normal | 1.66 | Normal | −0.02 | Normal | Yes |
| ERBB2_25 (LoB) | Normal | 1.6 | Normal | 0.02 | Normal | Yes |
| ERBB2_26 (LoB) | Normal | 2.72 | Amplified | 0.01 | Normal | Yes ** |
| ERBB2_27 (LoB) | Normal | 2.16 | Normal | −0.03 | Normal | Yes |
| ERBB2_28 (LoB) | Normal | 1.7 | Normal | 0 | Normal | Yes |
| ERBB2_29 (LoB) | Normal | 2.36 | Normal | 0 | Normal | Yes |
| ERBB2_30 (LoB) | Normal | 1.69 | Normal | 0 | Normal | Yes |
| Control_Mut | Amplified | 6.2 | Amplified | 0.39 | Gain | Yes |
| Control_WT | Normal | 2 | Normal | 0.02 | Normal | Yes |
| EGFRcases (n = 20) | ||||||
| EGFR_01 (AV) | Normal | 1.9 | Normal | 0.06 | Normal | Yes |
| EGFR_02 (AV) | Normal | 2.31 | Normal | 0.04 | Normal | Yes |
| EGFR_03 (AV) | Normal | 1.93 | Normal | 0.03 | Normal | Yes |
| EGFR_04 (AV) | Normal | 2.14 | Normal | 0.02 | Normal | Yes |
| EGFR_05 (AV) | Amplified | 5.43 | Amplified | 0.33 | Gain | Yes |
| EGFR_06 (AV) | Amplified | 5.34 | Amplified | 0.36 | Gain | Yes |
| EGFR_07 (AV) | Amplified | 2.99 | Amplified | 0.2 | Gain | Yes |
| EGFR_08 (AV) | Amplified | 2.12 | Normal | 0.2 | Gain | Yes ** |
| EGFR_09 (AV) | Amplified | 2.47 | Amplified | 0.27 | Gain | Yes |
| EGFR_10 (AV) | Amplified | 2.5 | Amplified | 0.1 | Gain | Yes |
| EGFR_11 (LoB) | Normal | 1.93 | Normal | 0.01 | Normal | Yes |
| EGFR_12 (LoB) | Normal | 1.84 | Normal | −0.01 | Normal | Yes |
| EGFR_13 (LoB) | Normal | 2.35 | Normal | 0.02 | Normal | Yes |
| EGFR_14 (LoB) | Normal | 2.18 | Normal | 0 | Normal | Yes |
| EGFR_15 (LoB) | Normal | 2.45 | Normal | −0.01 | Normal | Yes |
| EGFR_16 (LoB) | Normal | 2.29 | Normal | 0.05 | Normal | Yes |
| EGFR_17 (LoB) | Normal | 2.22 | Normal | −0.04 | Normal | Yes |
| EGFR_18 (LoB) | Normal | 1.55 | Normal | 0.04 | Normal | Yes |
| EGFR_19 (LoB) | Normal | 2.42 | Normal | −0.04 | Normal | Yes |
| EGFR_20 (LoB) | Normal | 1.74 | Normal | −0.01 | Normal | Yes |
| Control_Mut | Amplified | 6.09 | Amplified | 1.5 | Gain | Yes |
| Control_WT | Normal | 2 | Normal | −0.05 | Normal | Yes |
| CDKN2A/2Bcases (n = 19) | ||||||
| CDKN_01 | Unknown | 0.59 | Loss | −0.75 | Loss | N/A |
| CDKN_02 | Unknown | 0.67 | Loss | −0.61 | Loss | N/A |
| CDKN_03 (AV) | Loss | 0.86 | Loss | −1.40 | Loss | Yes |
| CDKN_04 (AV) | Loss | 0.94 | Loss | −1.40 | Loss | Yes |
| CDKN_05 (AV) | Loss | 1.18 | Loss | −0.41 | Loss | Yes |
| CDKN_06 | Unknown | 1.65 | Loss | −0.46 | Loss | N/A |
| CDKN_07 | Unknown | 1.81 | Loss | −0.63 | Loss | N/A |
| CDKN_08 | Unknown | 1.93 | Loss | −0.19 | Loss | N/A |
| CDKN_09 (AV) | Loss | 2.74 | Normal | −0.84 | Loss | Yes |
| CDKN_10 (AV) | Loss | 2.79 | Normal | −0.86 | Loss | Yes |
| CDKN_11 (LoB) | Normal | 2.02 | Normal | 0.00 | Normal | Yes |
| CDKN_12 (LoB) | Normal | 2.57 | Normal | −0.02 | Normal | Yes |
| CDKN_13 (LoB) | Normal | 2.39 | Normal | 0.02 | Normal | Yes |
| CDKN_14 (LoB) | Normal | 2.27 | Normal | 0.02 | Normal | Yes |
| CDKN_15 (LoB) | Normal | 2.74 | Normal | −0.01 | Normal | Yes |
| CDKN_16 (LoB) | Normal | 2.38 | Normal | −0.03 | Normal | Yes |
| CDKN_17 (LoB) | Normal | 2.13 | Normal | 0.00 | Normal | Yes |
| CDKN_18 (LoB) | Normal | 2.21 | Normal | −0.02 | Normal | Yes |
| CDKN_19 (LoB) | Normal | 2.24 | Normal | −0.01 | Normal | Yes |
| Control_Mut | Normal | 2.26 | Normal | 0.05 | Normal | Yes |
| Control_WT | Normal | 2.00 | Normal | 0.04 | Normal | Yes |
| MTAPcases (n = 19) | ||||||
| MTAP_01 | Unknown | 0.59 | Loss | −0.75 | Loss | N/A |
| MTAP_02 | Unknown | 0.67 | Loss | −0.61 | Loss | N/A |
| MTAP_03 (AV) | Loss | 0.86 | Loss | −1.4 | Loss | Yes |
| MTAP_04 (AV) | Loss | 0.94 | Loss | −1.4 | Loss | Yes |
| MTAP_05 | Unknown | 1.18 | Loss | −0.41 | Loss | N/A |
| MTAP_06 | Unknown | 1.65 | Loss | −0.46 | Loss | N/A |
| MTAP_07 | Unknown | 1.81 | Loss | −0.63 | Loss | N/A |
| MTAP_08 | Unknown | 1.93 | Loss | −0.19 | Loss | N/A |
| MTAP_09 | Unknown | 2.74 | Loss | −0.84 | Loss | N/A |
| MTAP_10 | Unknown | 2.79 | Loss | −0.86 | Loss | N/A |
| MTAP_11 (LoB) | Normal | 2.02 | Normal | 0 | Normal | Yes |
| MTAP_12 (LoB) | Normal | 2.57 | Normal | −0.02 | Normal | Yes |
| MTAP_13 (LoB) | Normal | 2.39 | Normal | 0.02 | Normal | Yes |
| MTAP_14 (LoB) | Normal | 2.27 | Normal | 0.02 | Normal | Yes |
| MTAP_15 (LoB) | Normal | 2.74 | Normal | −0.01 | Normal | Yes |
| MTAP_16 (LoB) | Normal | 2.38 | Normal | −0.03 | Normal | Yes |
| MTAP_17 (LoB) | Normal | 2.13 | Normal | 0 | Normal | Yes |
| MTAP_18 (LoB) | Normal | 2.21 | Normal | −0.02 | Normal | Yes |
| MTAP_19 (LoB) | Normal | 2.24 | Normal | −0.01 | Normal | Yes |
| Control_Mut | Normal | 2.26 | Normal | 0.05 | Normal | Yes |
| Control_WT | Normal | 2 | Normal | 0.04 | Normal | Yes |
** concordance between AscentTM LP-WGS call and tumor profiling data; N/A—not applicable, qPCR cut-offs for gene amplifications—normal or no amplification (≥0 and <2.5 copies), positive for amplification (≥2.5 copies), and for gene deletions—normal or no deletion (≤0 and >−2 copies) and positive for deletion (≤−2); AscentTM seg.mean cut-offs for amplification of ≥0 to <0.1 were set for no CN change and a cut-off of ≥0.1 was set for gain, and for deletions, a seg.mean cut-off of ≤0 to >−0.2 was set for no CN change and ≤−0.2 was set for loss.
Table 2.
Sensitivity and specificity for qPCR vs. AscentTM to detect gene-level CNVs.
| TP | TN | FP | FN | Sensitivity | Specificity | |
|---|---|---|---|---|---|---|
| Cases with known ERBB2 status (n = 30) | 8 | 22 | ||||
| qPCR | 8 | 21 | 1 | 0 | 100% | 95.45% |
| AscentTM (LP-WGS) | 8 | 22 | 0 | 0 | 100% | 100% |
| Cases with known EGFR status (n = 20) | 6 | 14 | ||||
| qPCR | 5 | 13 | 0 | 1 | 83% | 100% |
| AscentTM (LP-WGS) | 6 | 14 | 0 | 0 | 100% | 100% |
| Cases with known CDKN2A/2B status (n = 14) | 5 | 9 | ||||
| qPCR | 3 | 9 | 0 | 2 | 60% | 100% |
| AscentTM (LP-WGS) | 5 | 9 | 0 | 0 | 100% | 100% |
| Cases with known MTAP status (n = 11) | 2 | 9 | ||||
| qPCR | 2 | 9 | 0 | 0 | 100% | 100% |
| AscentTM (LP-WGS) | 2 | 9 | 0 | 0 | 100% | 100% |
TP—true positive, TN—true negative, FN—false negative, FP—false positive, qPCR—quantitative polymerase chain reaction, LP-WGS—low-pass whole-genome sequencing.
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Keo, V.; Khurana, S.; Udhane, V.; Larson, A.; Adams, J.N.; Sanchez, D.; Peltier, T.; Acevedo, A.; Mitchell, K.; Schilter, K.F.; et al. Analytical Validation of Quantitative Polymerase Chain Reaction and AscentTM Low-Pass Whole Genome Sequencing to Report on Gene Copy Number Variants in Cerebrospinal Fluid Tumor-Derived DNA. J. Mol. Pathol. 2026, 7, 18. https://doi.org/10.3390/jmp7020018
AMA Style
Keo V, Khurana S, Udhane V, Larson A, Adams JN, Sanchez D, Peltier T, Acevedo A, Mitchell K, Schilter KF, et al. Analytical Validation of Quantitative Polymerase Chain Reaction and AscentTM Low-Pass Whole Genome Sequencing to Report on Gene Copy Number Variants in Cerebrospinal Fluid Tumor-Derived DNA. Journal of Molecular Pathology. 2026; 7(2):18. https://doi.org/10.3390/jmp7020018
Chicago/Turabian StyleKeo, Viriya, Sakshi Khurana, Vindhya Udhane, Alexandra Larson, Jennifer N. Adams, Daniel Sanchez, Tarin Peltier, Anthony Acevedo, Kathleen Mitchell, Kala F. Schilter, and et al. 2026. "Analytical Validation of Quantitative Polymerase Chain Reaction and AscentTM Low-Pass Whole Genome Sequencing to Report on Gene Copy Number Variants in Cerebrospinal Fluid Tumor-Derived DNA" Journal of Molecular Pathology 7, no. 2: 18. https://doi.org/10.3390/jmp7020018
APA StyleKeo, V., Khurana, S., Udhane, V., Larson, A., Adams, J. N., Sanchez, D., Peltier, T., Acevedo, A., Mitchell, K., Schilter, K. F., Nie, Q., & Reddi, H. V. (2026). Analytical Validation of Quantitative Polymerase Chain Reaction and AscentTM Low-Pass Whole Genome Sequencing to Report on Gene Copy Number Variants in Cerebrospinal Fluid Tumor-Derived DNA. Journal of Molecular Pathology, 7(2), 18. https://doi.org/10.3390/jmp7020018
