BRAF mutation testing for patients diagnosed with stage III or stage IV melanoma: practical guidance for the Australian setting

97 Machine learning algorithms in the prognosis of cutaneous melanoma: a population-based study

OBJECTIVES

To establish a predictive model for prognosis of cutaneous melanoma using machine learning algorithms in large sample data.

METHODS

A retrospective analysis of patients diagnosed with cutaneous melanoma in the SEER database from 2010 to 2015 was performed using 12 different machine learning algorithms, for a total of 97 algorithm combinations, to screen for variables associated with cutaneous melanoma prognosis and to build predictive models.

RESULTS

A total of 24,457 cases were collected in this study, and 8,441 cases were finally included. Among them, 5908 cases in the training set and 2533 cases in the test set. The results of the study show that StepCox[both] + RSF is the best model. The variable features screened by the best model were Sex, Age, Marital, T stage, N stage, Ulcer, Site, Histologic, Surgery, Chemotherapy, Bone metastasis, Liver metastasis and Lung metastasis.

CONCLUSION

We have developed a predictive model with good accuracy for cutaneous melanoma prognosis using a combination of 97 machine learning algorithms in a large sample database.

Facts and Hopes on Biomarkers for Successful Early Clinical Immunotherapy Trials: Innovative Patient Enrichment Strategies

Despite the clinical validation and unequivocal benefit to patients, the development of cancer immunotherapies is facing some key challenges and the attrition rate in early phases of development remains high. Identifying the appropriate patient population that would benefit most from the drug is on the critical path for successful clinical development. We believe that a systematic implementation of patient enrichment strategies early in the drug development process and trial design, is the basis for an innovative, more efficient, and leaner clinical development to achieve earlier a clear proof of concept or proof of failure. In this position article, we will describe and propose key considerations for the implementation of patient enrichment strategies as an opportunity to provide decision-enabling data earlier in the drug development process. We introduce an innovative multidimensional tool for immuno-oncology drug development that focuses on facilitating the identification and prioritization of enrichment-relevant biomarkers, based on the drug mechanism of action. To illustrate its utility, we discuss patient enrichment examples and use a case in the field of cancer immunotherapy, together with technical and regulatory considerations. Overall, we propose to implement fit for purpose enrichment strategies for all investigational drugs as early as possible in the development process. We believe that this will increase the success rate of immuno-oncology clinical trials, and eventually bring new and better medicines to patients faster.

Prognostic and predictive biomarkers in melanoma

Biomarkers help to inform the clinical management of patients with melanoma. For patients with clinically localised primary melanoma, biomarkers can help to predict post-surgical outcome (including via the use of risk prediction tools), better select patients for sentinel lymph node biopsy, and tailor catch-all follow-up protocols to the individual. Systemic drug treatments, including immune checkpoint inhibitor (ICI) therapies and BRAF-targeted therapies, have radically improved the prognosis of metastatic (stage III and IV) cutaneous melanoma patients, and also shown benefit in the earlier setting of stage IIB/C primary melanoma. Unfortunately, a response is far from guaranteed. Here, we review clinically relevant, established, and emerging, prognostic, and predictive pathological biomarkers that refine clinical decision-making in primary and metastatic melanoma patients. Gene expression profile assays and nomograms are emerging tools for prognostication and sentinel lymph node risk prediction in primary melanoma patients. Biomarkers incorporated into clinical practice guidelines include BRAF V600 mutations for the use of targeted therapies in metastatic cutaneous melanoma, and the HLA-A∗02:01 allele for the use of a bispecific fusion protein in metastatic uveal melanoma. Several predictive biomarkers have been proposed for ICI therapies but have not been incorporated into Australian clinical practice guidelines. Further research, validation, and assessment of clinical utility is required before more prognostic and predictive biomarkers are fluidly integrated into routine care.

Microneedles-mediated drug delivery system for the diagnosis and treatment of melanoma

As an emerging novel drug delivery system, microneedles (MNs) have a wide range of applications in the medical field. They can overcome the physiological barriers of the skin, penetrate the outermost skin of the human body, and form hundreds of reversible microchannels to enhance the penetration of drugs and deliver drugs to the diseased sites. So they have great applications in the diagnosis and treatment of melanoma. Melanoma is a kind of malignant tumor, the survival rate of patients with metastases is extremely low. The traditional methods of surgery and drug treatment for melanoma are often accompanied by large adverse reactions in the whole body, and the drug concentration is low. The use of MNs for transdermal administration can increase the drug concentration, reduce adverse reactions in the treatment process, and have good therapeutic effect on melanoma. This paper introduced various types of MNs and their preparation methods, summarized the diagnosis and various treatment options for melanoma with MNs, focused on the treatment of melanoma with dissolved MNs, and made prospect of MNs-mediated transdermal drug delivery in the treatment of melanoma.

Pathologist initiated reflex BRAF mutation testing in metastatic melanoma: experience at a specialist melanoma treatment centre

Testing for BRAF mutations in metastatic melanoma is pivotal to identifying patients suitable for targeted therapy and influences treatment decisions regarding single agent versus combination immunotherapy. Knowledge of BRAF V600E immunohistochemistry (IHC) results can streamline decisions during initial oncology consultations, prior to DNA-based test results. In the absence of formal guidelines that require pathologist initiated ('reflex') BRAF mutation testing, our institution developed a local protocol to perform BRAF V600E IHC on specimens from all stage III/IV melanoma patients when the status is otherwise unknown. This study was designed to evaluate the application of this protocol in a tertiary referral pathology department. A total of 408 stage III/IV melanoma patients had tissue specimens accessioned between 1 January and 31 March in three consecutive years (from 2019 to 2021), reported by 32 individual pathologists. The BRAF mutation status was established by pathologists in 87% (352/408) of cases. When a prior BRAF mutation status was previously known, as confirmed in linked electronic records (202/408), this status had been communicated by the clinician on the pathology request form in 1% of cases (3/202). Pathologists performed BRAF V600E IHC in 153 cases (74% of cases where the status was unknown, 153/206) and testing was duplicated in 5% of cases (20/408). Reflex BRAF IHC testing was omitted in 26% of cases (53/206), often on specimens with small volume disease (cytology specimens or sentinel node biopsies) despite adequate tissue for testing. Incorporating BRAF IHC testing within routine diagnostic protocols of stage III/IV melanoma was both feasible and successful in most cases. Communication of a patient's BRAF mutation status via the pathology request form will likely improve implementation of pathologist initiated BRAF mutation testing and may result in a reduction of duplicate tests. To improve pathologist reflex testing rates, we advocate for the use of an algorithmic approach to pathologist initiated BRAF mutation testing utilising both IHC and DNA-based methodologies for stage III/IV melanoma patients.