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Record W2108410958 · doi:10.5858/arpa.2015-0278-cp

Template for Reporting Results of Biomarker Testing of Specimens From Patients With Melanoma

2015· article· en· W2108410958 on OpenAlexaff
Lynette M. Sholl, Aleodor A. Andea, Julia A. Bridge, Liang Cheng, Michael A. Davies, Mani Ehteshami, Tara C. Gangadhar, Suzanne Kamel‐Reid, Alexander J. Lazar, Kirtee Raparia, Alan Siroy, K Watson

Bibliographic record

VenueArchives of Pathology & Laboratory Medicine · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsBiomarkerMelanomaMedicinePathologyBiologyCancer research

Abstract

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The College of American Pathologists offers these templates to assist pathologists in providing clinically useful and relevant information when reporting results of biomarker testing. The College regards the reporting elements in the templates as important elements of the biomarker test report, but the manner in which these elements are reported is at the discretion of each specific pathologist, taking into account clinician preferences, institutional policies, and individual practice.The College developed these templates as educational tools to assist pathologists in the useful reporting of relevant information. It did not issue them for use in litigation, reimbursement, or other contexts. Nevertheless, the College recognizes that the templates might be used by hospitals, attorneys, payers, and others. The College cautions that use of the templates other than for their intended educational purpose may involve additional considerations that are beyond the scope of this document.Completion of the template is the responsibility of the laboratory performing the biomarker testing and/or providing the interpretation. When both testing and interpretation are performed elsewhere (eg, a reference laboratory), synoptic reporting of the results by the laboratory submitting the tissue for testing is also encouraged to ensure that all information is included in the patient's medical record and thus readily available to the treating clinical team.Select a single response unless otherwise indicated.Note: Use of this template is optional.**Reporting on the data elements in this template is not required.Note: If a marker is tested by more than 1 method (eg, polymerase chain reaction and immunohistochemistry), please document the additional result(s) and method(s) in the “Comments” section of the report.BRAF Mutational Analysis (note A)NRAS Mutational Analysis (note B)KIT Mutational Analysis (note C)Other Markers TestedBRAF Mutational Analysis Testing MethodNote: Assay sensitivity should be defined as lowest acceptable tumor percentage in a sample according to the pathologist's estimate.NRAS Mutational Analysis Testing MethodNote: Assay sensitivity should be defined as lowest acceptable tumor percentage in a sample according to the pathologist's estimate.KIT Mutational Analysis Testing MethodNote: Assay sensitivity should be defined as lowest acceptable tumor percentage in a sample according to the pathologist's estimate.Testing Method for Other MarkersGene names should follow recommendations of The Human Genome Organisation (HUGO) Nomenclature Committee (www.genenames.org; accessed February 10, 2015).All reported gene sequence variations should be identified by following the recommendations of the Human Genome Variation Society (www.hgvs.org/mutnomen/; accessed February 10, 2015).The incidence of melanoma has increased 2% per year during the last decade, with a concomitant 1% increase per year in mortality in the same period.1 Melanoma is unique among human tumors in its tendency to give rise to metastatic disease even when only a few millimeters in size and at low primary stage.2 Historically, there were few effective therapies for metastatic melanoma; however, recent breakthroughs in targeted therapies against commonly activated oncogenes have led to improvements in response rates and survival. In most melanomas, oncogenic growth/proliferation signaling appears to be driven by alterations in the RAS/RAF/MAPK and PI3K pathways, with 70% to 80% of cutaneous melanomas containing somatic oncogenic mutations in 1 of 3 oncogenes and 2 tumor suppressors—BRAF, NRAS, KIT, PTEN, NF1—highlighting the importance of the ERK and AKT pathways in this disease.3 Only BRAF activating mutations are currently validated for use in clinical practice as a predictive marker of response for approved therapies, but this field is rapidly evolving.BRAF mutations occur in up to 50% of melanomas. Of these mutations, 95% occur at amino acid 600, most commonly as Val600Glu (V600E) or sometimes Val600Lys (V600K), and lead to constitutive MAPK pathway activation.4 A randomized phase III trial of a targeted inhibitor of V600E mutated BRAF, vemurafenib, was first published in 2011. This trial was limited to BRAF V600–mutated melanomas and demonstrated a significant improvement in overall survival at 6 months in patients treated with vemurafenib as compared to dacarbazine, the only chemotherapeutic agent approved for treatment of metastatic melanoma at the time.5 Approximately 50% of patients in this trial demonstrated a rapid objective response to therapy (as compared to 5% in the dacarbazine arm); however, subsequent trials with longer follow-up demonstrated a median duration of response of less than 7 months.6 Similar results have been reported for a randomized phase III trial of the BRAF inhibitor dabrafenib.7 In most cases, tissues taken at relapse show increased ERK activation via phosphorylation; genomic profiling at relapse has demonstrated acquired mutations in MEK1 and NRAS in a subset of cases, though additional biochemical adaptations in signaling have also been noted.8 MEK inhibition with trametinib has also shown a significant benefit in BRAF-mutant melanoma as compared to chemotherapy in a randomized phase III trial that included patients with either BRAF V600E– or V600K–mutant melanoma.9 Trials combining BRAF inhibitors with MEK and other pathway inhibitors are ongoing. Trials combining MEK and BRAF inhibitors are associated with superior disease control, compared with single use of either agent as measured by percentage response and progression-free survival of the cohorts.10–12 Most patients enrolled in these trials had tumors harboring the BRAF V600E mutation; however, a small number of patients had V600K-mutant tumors, which can also respond to BRAF and MEK inhibitors. There are limited case reports of patients with V600R-mutated tumors showing objective responses to BRAF inhibitors.13 Several clinical trials of combination therapy with both targeted and immune therapies are available for patients with BRAF-mutant melanoma. Much less commonly encountered are non–BRAF V600 cases that include exon 15 mutations in codons surrounding V600 and additional mutations in exon 11. Many of these are weaker activators of the MEK/ERK pathway than are the V600 mutants. Responses of these cases to BRAF and MEK inhibitors are an active area of investigation, and in many cases their responses are less impressive than those in the V600-mutated cases. There are now a large number of publications demonstrating excellent correlation between BRAF V600E (VE1) mutation-specific immunohistochemistry and molecular-based analysis.4 However, in the absence of established proficiency testing or clear regulatory guidelines, laboratories using this immunohistochemistry assay should perform rigorous validation and have available confirmatory molecular testing.NRAS is mutated in approximately 20% of melanomas, with approximately 80% of mutations occurring in exon 3 at codons 60 and 61 and approximately 20% in exon 2 at codons 12 and 13.14 To date, direct inhibitors of NRAS have not demonstrated significant clinical activity. In untreated tumors, NRAS and BRAF V600 mutations generally occur in a mutually exclusive fashion. Clinical trials of single-agent targeted therapies and combinations are an active area of clinical investigation for patients with NRAS-mutant melanoma.KIT is a receptor tyrosine kinase expressed at the cell surface that binds stem cell factor and triggers downstream MAPK, PI3K, JNK, and JAK/STAT pathways leading to cell growth, proliferation, migration, and differentiation.15 KIT is mutated in fewer than 5% of melanomas and most frequently occurs in melanomas arising in mucosal, acral, and chronically sun-damaged skin. These mutations are scattered throughout the kinase domain in a pattern similar to that described in gastrointestinal stromal tumors (GISTs), except that missense mutations are predominant and deletions and insertion/duplications are rare. In addition, the mutations are more commonly seen in KIT exons 13 and 17 in melanoma than in GIST. The most common alterations occur in exons 11 and 13, with L576P and K642E accounting for close to 50% of melanoma-specific mutations in this gene.4 Small insertions and deletions in exon 11 are rare in melanoma. Targeted inhibitors of KIT and related tyrosine kinase receptors have demonstrated some efficacy in KIT-mutated but not in KIT wild-type melanomas in case reports and clinical trials, with best response documented most consistently in patients with tumors harboring mutations in the L576 and K642 hotspots. KIT copy number gain, including gene amplification alone, does not appear to independently predict response to KIT inhibitors in clinical trials.16,17 No KIT inhibitors are currently approved for melanoma; clinical trials are available for patients with KIT-mutant melanoma.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.025
metaresearch head score (Gemma)0.114
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.975
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.114
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0400.030

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.276
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainReporting
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations9
Published2015
Admission routes1
Has abstractyes

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