The original study made a striking claim. By profiling the genomic landscape of stage II melanoma, the researchers identified deletions at chromosomal region 11q23.1-q23.3 as a potential prognostic marker in RAS-mutant melanoma, and they reported an enrichment of small variants in CBL, particularly within the NF1 molecular subtype of the disease. Because CBL encodes an E3 ubiquitin ligase that negatively regulates receptor tyrosine kinase and MAPK signalling, the same pathway that drives melanoma through BRAF, NRAS and NF1 alterations, the gene is a plausible candidate. Losing a brake on this pathway could, in principle, fuel tumour growth. The study also reported a significant mutation hotspot at positions 417 and 418 in the RING finger domain of the protein, the structural element that gives the ubiquitin ligase its catalytic power, and robust in-silico predictions that these changes are damaging.

Poon and Koay do not dispute that CBL deserves attention. Their concern is that plausibility is not proof, and that the presentation of the variant data in the original paper leaves too many questions unanswered for the driver label to stand. Their critique begins with a deceptively simple technical point: the variants in the study’s main table were reported using only protein-level nomenclature, without the corresponding cDNA descriptions. Without cDNA notation, independent researchers cannot reliably verify the exact nucleotide changes, cross-reference databases, or reproduce the analysis. In a field where reproducibility is the currency of credibility, that omission matters.

The second concern cuts deeper. No variant allele frequencies were provided for the CBL mutations. Variant allele frequency, the fraction of sequencing reads carrying the mutant allele, is the primary tool for judging whether a variant is clonal, present in most tumour cells and therefore likely an early, cancer-relevant event, or subclonal and possibly a passenger. It is also the first line of defence against sequencing artefacts. This is especially important because the original study relied on formalin-fixed paraffin-embedded tissue, the standard archival material in pathology but notoriously prone to chemical damage that can generate false-positive mutations. Without allele frequency data, readers cannot distinguish a genuine tumour mutation from an artefact of fixation and sequencing chemistry.

The copy-number context of some variants raises further puzzles. Several CBL variants coexisted with heterozygous deletions of the region, a pattern consistent with a loss-of-function driver, since deleting the remaining copy of a tumour-suppressor-like gene is a classic two-hit mechanism. But one case showed coexistence with an amplification instead. For a hypothesised loss-of-function driver, amplification of the very locus supposed to be inactivated is biologically incongruous, and it forces the question of what CBL is actually doing in that tumour. The gene’s role may be context-dependent: in some settings CBL loss promotes signalling, while in others CBL has been implicated in oncogenic functions, which complicates any simple narrative.

Database evidence also came under scrutiny. The COSMIC catalogue counts cited in support of the variants were not consistently melanoma-specific, meaning mutations observed in entirely different tumour types were being marshalled as evidence of relevance in skin cancer. Similarly, the OncoKB classifications used to argue oncogenicity were based on evidence from other cancers. A variant that is oncogenic in myeloid leukaemia or another CBL-linked malignancy is not automatically oncogenic in melanoma, where cellular context, co-mutations and selective pressures differ profoundly. Cross-cancer evidence can generate hypotheses, Poon and Koay argue, but it cannot substitute for melanoma-specific proof.

Perhaps the most statistically pointed objection concerns recurrence, a cornerstone criterion for driver nomination. Genuine drivers are hit repeatedly by tumours because mutating them confers a selective growth advantage, the defining idea that Stratton, Campbell and Futreal articulated in their landmark 2009 Nature paper on the cancer genome. Yet of the 24 CBL variants found across 20 tumours in the study, 21 were unique. That near-total absence of the same variant appearing twice sits uneasily with driver status and suggests the enrichment signal may be driven by aggregation of heterogeneous, individually rare alterations rather than by repeated targeting of functionally critical residues. The correspondents also ask whether excluding variants of uncertain significance, the notorious VUS category, from the enrichment analysis would change the statistical significance of CBL as a driver. Including unclassified variants in such calculations can inflate or bias statistical signals, since VUS have not been shown to alter protein function at all.

Underlying the entire exchange is a structural gap in the variant-interpretation infrastructure. No ClinGen Gene Curation Expert Panel currently exists for CBL, the specialised bodies that convene to establish rigorous, gene-specific rules for judging pathogenicity. In their absence, interpretation of CBL variants must lean on general somatic variant guidelines, including the joint consensus recommendations of the Association for Molecular Pathology, the American Society of Clinical Oncology and the College of American Pathologists, and the more recent oncogenicity standards from ClinGen, the Cancer Genomics Consortium and the Variant Interpretation for Cancer Consortium. Those frameworks are powerful, but they are designed to be applied variant by variant with careful evidence weighing, not to rubber-stamp an entire gene as a driver on the strength of an enrichment statistic.

The stakes extend well beyond an academic quarrel. Driver gene designations shape prognostic stratification, therapeutic development and, eventually, clinical decision-making. If CBL deletions at 11q23.1-q23.3 genuinely mark aggressive RAS-mutant stage II melanomas, patients carrying them might be candidates for intensified surveillance or adjuvant therapy, and the CBL protein itself, as a regulator of RTK-MAPK signalling, could become a drug target. But if the signal is an artefact of FFPE sequencing, unverified nomenclature, cross-cancer evidence borrowing and VUS-inflated statistics, then building a biomarker on it risks misclassifying patients. The distinction between driver and passenger is not a stylistic preference; it is the foundational inference of cancer genomics, and it demands evidence that an alteration actually confers a selective growth advantage.

The path forward, as Poon and Koay make clear, runs through the laboratory rather than through larger statistical models. Functional studies are needed to validate the oncogenicity of the specific CBL variants, particularly the RING finger hotspot at positions 417 and 418, in melanoma-relevant cellular contexts. Variant-level interpretation should follow established somatic classification standards, with cDNA-level reporting, allele frequency transparency, melanoma-specific database comparisons and careful handling of copy-number co-occurrence. Until such work is done, the correspondents conclude, CBL should be regarded as a candidate requiring validation rather than an established driver in melanoma. Their letter is a reminder that in precision oncology, the hardest step is often not finding a candidate gene but proving that the tumour, and not the method, put the mutation there.

Subject of Research: Variant interpretation and driver gene designation for CBL in stage II melanoma

Article Title: CBL in stage II melanoma: considerations of variant interpretation for driver gene designation

Article References: Poon, K.-S., & Koay, E. S.-C. (2026). CBL in stage II melanoma: considerations of variant interpretation for driver gene designation. British Journal of Cancer. https://doi.org/10.1038/s41416-026-03629-1

Image Credits: AI Generated

DOI: 10.1038/s41416-026-03629-1

Keywords: CBL, stage II melanoma, driver genes, variant interpretation, cancer genomics, 11q23 deletions, RTK-MAPK signalling, VUS, FFPE artefacts, ClinGen, OncoKB, British Journal of Cancer

The original study, led by Lindner and colleagues, analysed tumours from 193 treatment-naïve patients with stage II melanoma, a disease stage in which the primary tumour is thick but has not yet spread to distant sites, and in which clinicians urgently need better tools to decide who requires intensive surveillance or adjuvant therapy. Among the many alterations catalogued in that work, one finding stood out: a deletion spanning the chromosomal region 11q23.1-3, which contains the CBL gene, was associated with relapse-free survival in the overall cohort when tested in a rigorous multivariate analysis. The Dalian-based team is quick to acknowledge the strength of that result, describing it as a compelling foundation for exploring CBL loss as a potential prognostic biomarker. Their concerns arise not from the headline finding, but from what happens when that finding is pushed into finer molecular subgroups.

CBL is no incidental passenger. The gene encodes an E3 ubiquitin ligase, a molecular machine that tags proteins for degradation and thereby acts as a critical regulator of signalling pathways driven by receptor tyrosine kinases. Because melanomas are classically stratified by driver mutations in BRAF, RAS and NF1, with a residual group classified as triple wild-type, any genomic alteration that appears to carry prognostic weight within one of these subtypes immediately attracts attention. The Lindner study reported that the 11q23.1-3 deletion showed a prognostic trend within the RAS-mutated subgroup of patients, and it is precisely this subgroup-specific claim that Han, Gao and Jiang dissect in their correspondence.

The heart of their critique concerns the difference between an unadjusted p-value and an adjusted one. In the RAS-mutated subgroup, the original report highlighted an unadjusted p-value of 0.044 for relapse-free survival, a figure that sits just below the conventional 0.05 threshold and therefore appears, at first glance, to signal genuine statistical significance. But when the analysis was corrected for multiple testing, the adjusted p-value rose to 0.178, well above the threshold that most researchers would accept as evidence of a reliable effect. The distinction is far from pedantic. When investigators test many genomic subgroups simultaneously, as happens when BRAF, RAS, NF1 and triple wild-type tumours are each interrogated for prognostic associations, the probability of stumbling across at least one apparently significant result by pure chance rises steeply. This phenomenon, known as a Type I error, is the false positive that multiple-testing adjustments are designed to suppress.

Han and colleagues argue that in exploratory subgroup analyses spanning multiple genomic subtypes, adjusting for multiple comparisons is generally recommended to prevent exactly these spurious discoveries. They point to the influential 2007 New England Journal of Medicine commentary by Wang, Lagakos, Ware, Hunter and Drazen on the reporting of subgroup analyses in clinical trials, a paper that has shaped how statisticians and clinicians interpret claims carved out of broader datasets. That commentary warned that subgroup findings are frequently overinterpreted, particularly when unadjusted significance levels are emphasized over corrected ones. By foregrounding the unadjusted p-value of 0.044 while the adjusted figure of 0.178 tells a more cautious story, the original presentation, the correspondents suggest, risks conveying a degree of predictive confidence in the RAS-mutated subgroup that the data do not yet support.

There is also the matter of sub-stage confounding, a second analytical nuance the letter raises. Stage II melanoma is not a single homogeneous category. Under the American Joint Committee on Cancer eighth edition staging system, refined in the landmark 2017 update by Gershenwald and colleagues, stage II encompasses patients with tumours of markedly different thicknesses and ulceration statuses, and these features themselves carry powerful prognostic information. When a cohort is subdivided first by molecular subtype and then examined for survival associations, imbalances in tumour thickness, ulceration or other clinicopathological variables between patients with and without the CBL region deletion can masquerade as genuine biological effects. Disentangling whether the deletion independently forecasts relapse, or merely travels alongside known risk factors that happen to cluster within the subgroup, demands careful covariate adjustment and transparent reporting of how residual confounding was handled.

The correspondents anchor their argument in established reporting standards, invoking the REMARK guidelines, the Reporting Recommendations for Tumor Marker Prognostic Studies published by McShane and colleagues in 2005 in the Journal of the National Cancer Institute. REMARK was developed precisely because biomarker prognostic studies have historically been plagued by small samples, selective reporting and optimistic interpretation, leading to markers that fail repeatedly upon validation. The guidelines call for complete documentation of statistical methods, prespecified hypotheses, transparent handling of multiple testing and honest characterisation of exploratory versus confirmatory findings. Emphasising adjusted p-values, Han, Gao and Jiang contend, aligns with these norms and helps readers accurately gauge the robustness of the CBL alteration within specific molecular subsets rather than being swept up in an apparently significant number.

None of this diminishes the value of the underlying discovery. The genomic classification of cutaneous melanoma established by The Cancer Genome Atlas Network in 2015 demonstrated that melanoma biology divides cleanly into the BRAF-mutant, RAS-mutant, NF1-mutant and triple wild-type categories, and subsequent efforts to layer prognostic information onto that framework have been a major research priority. A driver gene and biomarker candidate emerging from a 193-patient cohort of therapy-naïve stage II patients is genuinely noteworthy, particularly for a disease stage in which sentinel lymph node status and tumour thickness remain the dominant but imperfect guides to management. The Dalian team frames its letter as constructive engagement, crediting the original authors with a robust cohort and a rigorous multivariate analysis in the overall population, while urging that subgroup-level claims be contextualised with the statistical caution they require.

The broader lesson radiates well beyond melanoma genomics. Modern high-throughput studies routinely generate dozens or hundreds of candidate associations, and the path from an exploratory signal to a clinically actionable biomarker runs through validation in independent cohorts, replication under pre-specified analytical plans and harmonisation with existing staging and risk models. A deletion at 11q23.1-3 affecting CBL may yet prove to be a genuine driver event with prognostic power, and the original study’s evidence in the overall cohort suggests the hypothesis is worth pursuing vigorously. But as Han, Gao and Jiang make clear, the credibility of that pursuit depends on how the statistics are handled at each step, and on whether the field resists the temptation to treat a subgroup p-value of 0.044 as a verdict rather than a prompt for further, more stringently powered investigation.

For patients with stage II melanoma, the stakes are concrete: biomarkers of this kind could ultimately refine who is monitored most intensively, who is considered for adjuvant intervention and who can be reassured. Ensuring that such tools rest on statistically sound foundations is therefore not an academic quibble but a patient-safety issue. The correspondence, received on 5 June 2026, revised on 14 June and accepted on 3 September before publication on 21 September, stands as a reminder that in precision oncology, the rigour of the analysis is inseparable from the value of the discovery, and that the most important filters between a genomic observation and a clinical biomarker are multiple-testing correction, confounder control and disciplined adherence to reporting guidelines such as REMARK.

Subject of Research: Methodological evaluation of the 11q23.1-3 CBL deletion as a prognostic biomarker in stage II melanoma

Article Title: Methodological considerations in defining CBL as a prognostic biomarker in stage II melanoma

Article References: Methodological considerations in defining CBL as a prognostic biomarker in stage II melanoma. (n.d.). https://doi.org/10.1038/s41416-026-03628-2

Image Credits: AI Generated

DOI: 10.1038/s41416-026-03628-2

Keywords: stage II melanoma, CBL, 11q23.1-3 deletion, prognostic biomarker, RAS-mutated melanoma, multiple testing adjustment, REMARK guidelines, subgroup analysis, relapse-free survival, AJCC staging, melanoma genomics, statistical methodology