DOI: 10.1200/jco.2026.44.19_suppl.163 ISSN: 0732-183X

Upfront 69-gene next-generation sequencing versus reflex PCR in BCR::ABL1-negative myeloproliferative neoplasms: Diagnostic yield, prognostic impact, and cost analysis in an Indian cohort.

Moin Makda, Shrinidhi Nathany, Hrithik Bagga, Swarsat Kaushik Nath, Siddharth Sagar, Haristuti Verma, Anusha Swaminathan, Ragesh Nair, Vikas Dua, Rayaz Ahmed, Dinesh Bhurani, Rahul Bhargava

163

Background: Sequential PCR testing for JAK2, CALR, and MPL mutations remains standard in MPN evaluation but misses non-canonical drivers and high-molecular-risk (HMR) mutations that inform MIPSS70+ v2.0 and GIPSS prognostic scoring. No Indian study has quantified the combined clinical and economic impact of upfront NGS. Methods: We analyzed 195 consecutive patients with suspected BCR::ABL1-negative MPNs at an Indian tertiary referral center. All underwent 69-gene targeted NGS (Oncomine Myeloid GX v2, Genexus platform). Quality control excluded variants with VAF <2%, VUS with VAF <5%, and non-MPN genes. Prognostic reclassification was assessed by MIPSS70+ v2.0 and GIPSS. A Markov model compared reflex-PCR-then-NGS versus NGS-first strategies using real-world laboratory costs (PCR ₹3,500–5,000/assay; 69-gene NGS ₹18,000/panel). Results: Median age was 47 years (range 10–86); 66% male. Canonical drivers were identified in 86 patients (44.1%): JAK2 V617F in 70 (35.9%), CALR in 14 (7.2%), MPL in 1 (0.5%), JAK2 exon 12 in 1 (0.5%). Among 109 triple-negative patients, NGS detected non-canonical mutations in 41 (21.0% of cohort). HMR mutations (ASXL1, SRSF2, EZH2, IDH1/2) were present in 21 (10.8%); 11 (52%) were PCR-invisible. Applying MIPSS70+ v2.0 and GIPSS, 32 patients (16.4%) were reclassified to higher risk categories based solely on NGS-detected mutations, directly informing transplant eligibility. Specifically, standard PCR algorithms missed crucial HMR mutations co-occurring with canonical drivers in 10 patients, resulting in artificially underestimated MIPSS70+ risk scores prior to NGS. The most frequent cooperating genes were TET2 (11.7%), SRSF2 (6.6%), and ASXL1 (4.1%). Fifty-nine patients (30.3%) harbored two or more co-occurring mutations. Notably, canonical driver mutations exhibited significantly higher variant allele frequencies compared to non-canonical cooperating mutations (mean 46.3% vs. 27.3%, p<0.001). The NGS-first strategy was economically dominant (Table). Conclusions: Upfront NGS detected actionable mutations in 65.1% of patients, reclassified 16.4% to higher MIPSS70+ v2.0/GIPSS risk, and was both cheaper and faster than reflex PCR workflows. These data support NGS as first-line diagnostic standard for MPN evaluation in resource-conscious settings.

Outcome
NGS-First
Reflex-then-NGS
Canonical drivers detected, n (%)
86 (44.1)
86 (44.1)
Non-canonical mutations detected, n (%)
41 (21.0) 0 (0)
HMR mutations detected, n (%)
21 (10.8) 10 (5.1)
Prognostic reclassification, n (%)
32 (16.4) 0 (0)
Mean cost per patient (₹)
18,000 21,633
Mean turnaround time (days)
3.0 6.6
Cost saving per patient (₹)
3,633 Reference

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