The current state of melanoma research: insights & analytics...team at Elsevier, the melanoma global DALY rate is 22%. This demonstrates that melanoma is responsible for more than

The current state of melanoma research: insights & analytics

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ContentsExecutive summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Melanoma introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Key findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Protein targets & melanoma publication analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Small molecules and targets in melanoma pipeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Genetic predisposition & cancer driver mutations linked to melanoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Melanoma, immune suppression & gaps in melanoma treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Comparison of the adverse events for Keytruda & YERVOY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Trending topics in melanoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Who we are . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

About Elsevier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

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• Melanoma, the most serious type of skin cancer, is a malignant tumor that arises from uncontrolled proliferation of melanocytes. The rates of melanoma are increasing each year, but death rates are slowly decreasing. In this report, we look at the current landscape of melanoma R&D, the biology and mechanisms of the disease, general knowledge gaps, therapeutics, and the new emerging topic of the microbiome-melanoma association.

• 23 genes are linked to hereditary melanoma, of which, 12 genes have 177 genetic variants linked to melanoma. Moreover, the 11 other genes genetically linked to melanoma currently have no known reported genetic variants, elucidating a potential gap in our knowledge of melanoma.

• In non-hereditary (sporadic) melanoma, there is a subset of variants that are not currently genetically linked to any known melanoma genes, again suggesting a knowledge gap in the understanding of melanoma that requires further research.

• Analyzing proteins secreted or expressed on the surface of melanoma cells reveals over 350 proteins that inhibit the immune response, providing evidence that personalized immunotherapy would dramatically benefit patients with melanoma.

• Over the last three decades B-Raf proto-oncogene, serine/threonine kinase (BRAF) and programmed cell death 1 (PDCD1) have been the most commonly published melanoma targets, and the top five published targets, which include BRAF and PDCD1, are all involved in cell function and the immune response.

• A two-fold increase in marketed melanoma drugs have been approved in the last 10 years—these include drugs targeting BRAF (Zelboraf and Tafinlar) and PDCD1 (Opdivo and Keytruda).

• The analysis of two melanoma blockbuster drugs, Keytruda and YERVOY, shows that inflammatory and thyroid adverse events are more likely to be reported for Keytruda, while inflammatory and liver adverse events are more likely to be reported for YERVOY. The likelihood of death being reported while taking Keytruda and YERVOY are not significantly different compared to other drugs.

• Keytruda would be more effective in combination immunotherapy in melanoma patients with non-PDCD1 related suppressed immune systems, as Keytruda only works on PDCD1.

• One of the emerging topics in melanoma research is the involvement of the microbiome in patient response to melanoma treatment. The microbiome is implicated in the onset and progression of cancers as well as the toxicity and response rate of cancer treatments. This topic is trending due to the recent findings that show that the response to immune checkpoint inhibitors correlates with the composition, diversity, and functional differences in patients’ microbiomes.

Executive summary

Melanoma is a malignancy that poses substantial metastatic risk when depth of invasion increases. Melanoma is most commonly cutaneous, but it may also affect the uveal tract of the eye, the mucous membranes of the head and neck, the gastrointestinal tract, and the genital tract. Risk factors include UV light exposure, tanning bed exposure, fair skin types (i.e. light skin with little or no tanning ability), blond or red hair, blue eyes, family history of melanoma, dysplastic nevi, and congenital nevi. A report published by Elsevier’s Analytical Services provided valuable insight into how immunotherapy is the most prominent topic in melanoma research globally as well as the countries and institutions leading the way in melanoma research.

EpidemiologyThe rate of new melanoma cases worldwide is estimated to be almost 300,000 each year 1. Despite melanoma only accounting for <5% of skin cancer cases, the Disability Adjusted Life Years (DALYs), which is the sum of years of life lost and years lived with disability, shows the dramatic impact of melanoma. Death rates are affected, and as reported by the Analytical Services team at Elsevier, the melanoma global DALY rate is 22%. This demonstrates that melanoma is responsible for more than 20 years of life lost and years lived with disability worldwide per

100,000 people, and that it has killed 1 in 123,457 individuals in 2017 (0.81 people per 100,000). The report, “The Melanoma Research Insights: Impact, Trends, Opportunities,” determines that the greatest impact of melanoma is in Australia, Northern Europe, and North America, whilst the lowest DALYs are in South America, Africa, and South Asia.

The United States has a high incidence of melanoma, and the American Cancer Society has estimated that >96,000 new cases and >7200 deaths will be attributed to melanoma in the US in 20192. According to Conn’s Current Therapy, the prevalence of melanoma in the United States has doubled between 1982 and 2011, and the lifetime risk for developing it is about 1 in 50 for Caucasians, 1 in 1000 for African Americans, and 1 in 200 for Latin Americans 3. Analysis of the CDC melanoma data demonstrates that new cases of melanoma have steadily increased between 1999 and 2016; however, there is a trend that melanoma-related deaths have started to decline, which is attributed to changes in risk factor exposure, screenings, and treatment improvements (Figure 1) 4.

Prevalence of melanoma in the US and related deaths

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Figure 1: Rates of melanoma diagnoses and deaths

Melanoma introduction

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Key findings

In 2018, two out of three of the most cited research papers mentioning melanoma in the title, abstract or keywords explore the influence of the microbiome in response to melanoma patients.

Two blockbuster drugs that treat melanoma, Keytruda and YERVOY, have been proven safe, as there is no increased likelihood of death reported as an adverse event compared to all other drugs. But results do show a higher likelihood of having reports of inflammatory, thyroid and liver adverse events.

Keytruda should be used in combination with other immune-activating drugs for specific patients with non-PDCD1-suppressed immune responses.

Survival depends on the stage and extent of the disease at presentation. There is a positive five-year survival outcome (which is the estimated percentage of cancer patients who will not have died from cancer five years after diagnosis) in localized disease cases (about 98%), but can be widely variable in node-positive disease cases (20%–70%), and can be poor in disease cases with distant metastases (about 23%), and these survival

rates are based on US data5. However, the survival rates are age dependent (Figure 2) 4, and survival rates decrease by 10% for the 75+ age group compared to the <45–years age group. About 70% of non-sun damage related melanomas carry BRAF mutations, and genetic studies show that 50% of familial and 25% of sporadic melanomas may be due to mutations in the tumor suppressor gene p16 3.

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Figure 2: five-year survival estimates for melanoma patients in the US

Pathophysiology

When querying Elsevier’s biology database, Resnet, for melanoma and the protein targets, a publication analysis was created to analyze the change in protein target landscape in journal articles. Melanoma targets researched between 1987 and 2019 were queried and limited to those mentioned in at least three publications in a single year (Figure 3). The protein targets most studied over this time period are B-Raf proto-oncogene serine/threonine kinase (BRAF), programmed cell death 1 (PDCD1), cyclin dependent kinase inhibitor 2A (CDKN2A), melanocyte inducing transcription factor (MITF), and interleukin 2 (IL2). These protein targets are all involved in autophagy, immune response, cell development, cell differentiation, cell function, cell growth, cell migration, cell phenotype, cell survival, and tumor growth.

BRAF and PDCD1 are the two proteins with the highest citation counts over time. BRAF is involved in the mitogen/activated protein kinase (MAPK) pathway, which is a signaling cascade that

regulates cellular proliferation, differentiation and survival. BRAF was identified as an oncogene, and display oncogenic mutations in around 60–70% of melanoma cases6–9. PDCD1 encodes the PD-1 protein, which is an immune-checkpoint receptor mainly expressed by T cells, and negatively regulating human immune response. PD-1 expression in various melanomas ranges from 10–60% 10,11. Focusing on just the data for BRAF and PDCD1, it shows that there were no publications related to PDCD1 involvement in melanoma during the 2008–2009 time period (Figure 4); not until 2011 did publications relating to the involvement of PDCD1 in melanoma begin to emerge. The number of publications has exponentially increased year on year, and by 2018, PDCD1 began to overtake BRAF as the number one target protein published in relation to melanoma —further supporting the concept that immunotherapy is a top trend in current melanoma research.

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Protein targets & melanoma publication analysis

Figure 3: Top 10 protein targets relating to melanoma from 1987–2019

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Count of publications regarding BRAF or PDCD1 & melanoma per yearN

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Reaxys® Medicinal Chemistry was used to analyze the protein targets in each clinical phase to help determine if any particular target has been more successful for the treatment of melanoma.

From 2008–2009, there were 18 drugs marketed for the treatment of melanoma and 48 small molecules in pre-clinical or clinical phases (Figure 5). A decade later, from 2018–2019, a total of 39 small molecules were approved to treat melanoma and 41 small molecules in pre-clinical or clinical phases (Figure 5), showing a marked increase in the success rate of drugs targeting melanoma. The discontinuation rate of melanoma drugs in 2018–2019 (14 discontinued small molecules) was significantly lower compared to in 2008–2009 (23 discontinued small molecules, and one withdrawn).

One small molecule that was discontinued was estradiol, which is the principal intracellular human estrogen. It was initially

shown in studies to interact with both alpha- and beta-estrogen receptors, which play a role in promoting cell growth and cellular antiproliferation, respectively 12. In vitro and in vivo studies showed that estradiol resulted in inhibition of melanoma cell growth13,14, elucidating a potential melanoma drug candidate. However, later studies showed that the inhibition of beta-estrogen receptor caused by estradiol increased the risk for developing cutaneous melanoma and spread of metastatic cells, resulting in an increased risk of skin malignant melanoma 15–18. Now, due to these findings, melanoma patients with increased levels of endogenous estrogens during pregnancy, those exposed to oral contraceptives and hormone replacement therapies containing estradiol should be advised of the increased risk of melanoma development or melanoma progression.

Figure 4: Number of publications citing BRAF or PDCD1 and melanoma per year

Small molecules and targets in melanoma pipeline

The analysis of the protein targets against melanoma provides insight into the current development and approval of marketed drugs against melanoma and skin cancers. In 2008–2009 the majority of drugs approved for market were kinases, growth factors, members of cytochrome P450 family, and histone deacetylases (Table 1 left-hand column). Similarly, in 2018–2019, drugs approved for melanoma were again kinases, growth factors, members of cytochrome P450 family, and histone deacetylases, but a significant increase in other protein targets is also observed (Table 1 right-hand column). Of note is the

increase in drugs approved for mutant proteins and targeting specific populations. Dabrafenib was approved by the FDA in 2018 and is indicated as single-agent therapy for the treatment of unresectable or metastatic melanoma in patients with BRAF V600E mutations 19–21. Afatinib was approved in 2018 for the treatment of melanoma because of its ability to inhibit the tyrosine kinase activity of EGFR receptor carrying the L858R mutation22. It is therefore apparent that there is an increased focus on targeted therapeutics toward patients with specific melanoma gene mutations.

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B-RAF (T119S,V600E) Activin receptor type-1B

B-RAF (V600D) ALK tyrosine kinase receptor

Cytochrome P450 2C19 Amine oxidase [flavin-containing] A

Cytochrome P450 2C9 arachidonate 5-lipoxygenase

Cytochrome P450 2D6 Carbonic anhydrase 1

Cytochrome P450 3A4 Carbonic anhydrase 12

Ectonucleotide pyrophosphatase/phosphodiesterase family member 2 Carbonic anhydrase 2

Epidermal growth factor receptor Carbonic anhydrase 9

Estrogen receptor Cyclin-dependent kinase 4

Hepatocyte growth factor receptor Cyclin-dependent kinase 6

Histone deacetylase Cyclin-dependent-like kinase 5

Histone deacetylase 1 Cystine/glutamate transporter

Histone deacetylase 2 Cytochrome P450 2C9

Histone deacetylase 4 Cytochrome P450 3A4

Figure 5: Number of melanoma drugs in each clinical phase from compared to 2008–2009

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Data and analytics generated using RMC www.elsevier.com/solutions/reaxys/who-we-serve/pharma-rd/reaxys-medicinal-chemistry

Protein Targets Against Melanoma 2008–2009 Protein Targets Against Melanoma 2018–2019

Histone deacetylase 8 Dihydroorotate dehydrogenase (quinone), mitochondrial

Histone deacetylase 9 Dual specificity mitogen-activated protein kinase kinase 1

RAC-alpha serine/threonine-protein kinase Dual specificity mitogen-activated protein kinase kinase 2

Receptor tyrosine-protein kinase erbB-2 E3 ubiquitin-protein ligase SIAH1

Receptor tyrosine-protein kinase erbB-4 E3 ubiquitin-protein ligase SIAH2

Serine/threonine-protein kinase B-raf Echinoderm microtubule-associated protein-like 4

Serine/threonine-protein kinase B-raf (V600E) Epidermal growth factor receptor

Solute carrier family 22 member 8 Epidermal growth factor receptor (EGFR delE746_A750)

Thymidylate synthase (gene TYMS) Epidermal growth factor receptor (L858R)

Epidermal growth factor receptor (L858R/T790M)

Epidermal growth factor receptor (T790M)

Epidermal growth factor-activated receptor

Hepatocyte growth factor receptor

Histone deacetylase

Histone deacetylase 1

Histone deacetylase 2

Histone deacetylase 3

Histone deacetylase 6

Histone deacetylase 8

Lysophosphatidic acid receptor 5

MAP kinase kinase

Mast/stem cell growth factor receptor Kit (V560D)

Meiosis-specific serine/threonine-protein kinase MEK1

Nuclear factor kappa-B

Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit delta isoform

Poly [ADP-ribose] polymerase (gene PARP)

Poly [ADP-ribose] polymerase 1

Poly [ADP-ribose] polymerase 2

Probable histone deacetylase 1-A

Proteasome subunit beta type-5

Protein disulfide-isomerase A6

Protein disulfide-isomerase EUG1 Proto-oncogene tyrosine-protein kinase Src

RAF proto-oncogene serine/threonine-protein kinase

Receptor tyrosine-protein kinase erbB-2

RNA-binding protein 39

Serine/threonine-protein kinase A-Raf

Serine/threonine-protein kinase B-raf

Serine/threonine-protein kinase B-raf (V600E)

Serine/threonine-protein kinase B-raf (V600K)

Serine/threonine-protein kinase mTOR

Serine/threonine-protein phosphatase 4 regulatory subunit 3B

Thioredoxin

Toll-like receptor 7

Toll-like receptor 8

Tubulin

Tumor necrosis factor

Tyrosinase

Tyrosine-protein kinase Abl

Tyrosine-protein kinase BTK

Tyrosine-protein kinase CSK

Table 1: Protein targets for marketed drugs against melanoma

To understand the genetic predisposition and cancer driver mutations linked to melanoma, using Resnet biology data and semantic search, we explored the molecular interactions and the cause and effect relationships associated with biological processes.

23 genes were shown to be linked to hereditary melanoma. From these 23 genes, 12 genes have 177 genetic variants that are linked to melanoma, suggesting that they predispose one to melanoma and are clinically significant variants that are supported through the semantic associations observed in the publications links between the gene variants and melanoma (Figure 6—See Appendix 1 for legend).

There are a further 11 genes that are genetically linked to melanoma that currently have no known genetic variants associated with melanoma. Further research is therefore required in order to: a) map genetic variants, b) determine which variant is clinically significant, c) understand the impact of variant on gene function—whether variation activates or inhibits the gene.

For non-hereditary (sporadic) melanoma, the analysis showed that there are 752 genes genetically linked to sporadic melanoma and its subtypes, and 449 genetic variants genetically linked to sporadic melanoma and its subtypes. Out of the 449 genetic variants, 395 are from 78 genes that are genetically linked to melanoma. The remaining missing 54

variants are not currently genetically linked in the platform to any known melanoma gene; this could therefore be a potential area for further research.

We found 24 genetic variations predisposing to melanoma that influence the response to 39 melanoma drugs (Figure 7—See Appendix 2 for legend). For example, the rs113488022 genetic variant (BRAF V600E mutation) influences treatment outcome with sorafenib which slowed tumor development by inhibiting V600E BRAF activity, phosphorylation of MEK and extracellular signal-regulated kinase, and vascular development 23. The rs121434592 mutation that results in E17K substitution in AKT serine/threonine kinase 1 and has recently been reported in 2019 to promote melanoma-brain metastasis 24. In patients with endometrial cancer containing the rs121434592 gene variant and treated with temsirolimus, these patients had longer progression free survival 25. In the efficacy module of the PharmaPendium database, temsirolimus is currently in phase III clinical trials as a treatment for advanced renal cell carcinoma, glioma, lymphoma mantle cell, neuroblastoma, and rhabdomyosarcoma, and if successfully approved it could warrant investigation into the effects of temsirolimus to treat melanoma patients carrying the AKT E17K mutation.

Data and analytics generated using Pathway Studio www.elsevier.com/solutions/pathway-studio-biological-research

Figure 6: Genes linked to hereditary melanoma

Genetic predisposition & cancer driver mutations linked to melanoma

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Our analysis shows 210 melanoma related concepts which were interrogated for their ability to suppress the immune system either by activating 291 immunosuppression related concepts or by inhibiting 1,367 immune system activating concepts (Figure 8).

Analysis shows 226 proteins secreted or expressed on a cell surface by melanoma that are capable of inhibiting activation of the immune system. Moreover, 142 proteins secreted or expressed on a cell surface by melanoma can activate immune tolerance; bringing a total of 368 potential mechanisms for melanoma cells to inhibit immune response. In order to develop personalized immunotherapy, molecular profiling of

a melanoma biopsy must be performed to determine the exact immunosuppression mechanism.

The pathway diagram indicates potential mechanisms for the ineffectiveness of immunotherapy drug Pembrolizumab (Keytruda) in some patients that results from immune response suppressed by non-PDCD1 mechanisms, as melanoma can overexpress either PDCD1 or PDCD1LG2 to suppress the immune response and Keytruda only works against PDCD1 (Figure 9—see Appendix 3 for legend).

Data and analytics generated using Pathway Studio www.elsevier.com/solutions/pathway-studio-biological-research

Figure 7: Genetic variants influencing response to melanoma drugs

Melanoma, immune suppression & gaps in melanoma treatment

Figure 8: Pathway Studio results showing concepts that positively and negatively suppress immune response

Keytruda is a programmed death receptor-1 (PD-1)-blocking antibody that has been approved for the treatment of patients with unresectable or metastatic melanoma26, and for the adjuvant treatment of patients with melanoma with the involvement of lymph node(s) following complete resection27. Ipilimumab (YERVOY) is a human cytotoxic T-lymphocyte antigen 4 (CTLA-4)-blocking antibody approved for the treatment of adults and pediatric patients (12 years and older) with unresectable or metastatic melanoma. Moreover, it is also approved for the adjuvant treatment of patients with cutaneous melanoma with pathologic involvement of regional lymph nodes of more than 1 mm who have undergone complete resection, including total lymphadenectomy 28. Keytruda sales in the fourth quarter of 2018 exceeded $2 billion 29, while YERVOY sales were $6 billion in the same time period 30. Clinical studies carried out have reported that Keytruda improves overall survival when compared

to YERVOY 31. Results from an open-label, multicenter, randomized, controlled, phase 3 study between Keytruda and YERVOY demonstrated that grade 3–4 treatment-related adverse events occurred in 17% of Keytruda treated patients and in 20% of the YERVOY group 32. The clinical study found that the most common adverse events were colitis, diarrhea, and fatigue 32. The five-year rate of recurrence-free survival was 40.8% in the YERVOY group 33. In other trials it has been shown that the adverse event profile of YERVOY resulted in around 40% of patients discontinuing treatment by the end of the initial dosing period 34. The estimated five-year overall survival for Keytruda patients was 34% with an estimated five-year progression-free survival rate of 21% 35. Although the endpoints of these two studies are different, they do show the benefits of both Keytruda and YERVOY.

Comparison of the adverse events for Keytruda & YERVOY

Figure 9: Pathway linking the potential mechanism for the ineffectiveness of Keytruda in some patients due to non-PDCD1 suppression

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Using the pre-and post-market drug safety data for Keytruda and YERVOY, a comparative analysis was performed to investigate the adverse events (AEs) reported in pre-clinical and clinical studies, and post-marketing FDA Adverse Event Reporting System (FAERS) data.

Table 2 shows the top reported adverse events in primates for Keytruda from 2014–2016, and for YERVOY in 2011 and 2018, based on the pre-clinical data. The main adverse events reported for Keytruda are involved in the endocrine system, while those for YERVOY still involve the endocrine system but a marked increase in events related to animal model pregnancy (Table 2).

In Keytruda clinical studies, the greatest frequencies of reported AEs are pneumonitis, diarrhea, fatigue, colitis, rash, hypothyroidism (Figure 10). There are some overlaps between the reported pre-clinical and clinical AEs for Keytruda, including reports of events relating to the thyroid and enzymes involved in liver function. In comparison, clinical AEs for YERVOY are more related to the liver, skin, digestive system, and enzyme level changes events (Figure 11), many of which were not observed in pre-clinical studies (Table 2).

Keytruda Preclinical Adverse Event YERVOY Preclinical Adverse Event

Biopsy thyroid gland abnormal Death neonatal

Spleen disorder Stillbirth

Biopsy kidney abnormal Abortion

Biopsy muscle abnormal Premature labour

Biopsy oesophagus abnormal Spleen disorder

Biopsy parathyroid gland abnormal Testicular disorder

Thymus disorder Weight decrease neonatal

Thyroid cyst Biopsy site unspecified abnormal

Adrenal disorder Lymph node palpable

Alanine aminotransferase increased Lymphadenopathy

Aspartate aminotransferase increased Abortion spontaneous

Biopsy heart abnormal Anaemia

Biopsy liver abnormal Biopsy lymph gland abnormal

Biopsy lymph gland abnormal Congenital genitourinary abnormality

Biopsy spleen abnormal Cyanosis

Blood calcium decreased Drug specific antibody present

Blood phosphorus decreased Erythema

Blood potassium decreased Faeces discoloured

Injection site haemorrhage Gastrointestinal neoplasm

Ovarian cyst Haematocrit decreased

Table 2: Pre-clinical adverse events reported in primate models for Keytruda and YERVOY

Top 10 clinical adverse events reported for KeytrudaCo

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Figure 11: Top 10 clinical adverse events reported for YERVOY and associated proportional reporting ratio (PRR)

Figure 10: Top 10 clinical adverse events reported for Keytruda and associated proportional reporting ratio (PRR)

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Calculating the Proportional Reporting Ratio (PRR) for the top 10 AEs for Keytruda and YERVOY provides insight into signal generation from spontaneous reporting data. PRR is a measure of how common an adverse event for a particular drug is compared to how common it is in the overall PharmaPendium database. A PRR > 1 indicates that a greater proportion of the reports for the drug are more frequent that for other drugs in the PharmaPendium database. Therefore, it provides a statistical analysis regarding whether a particular AE is more likely for a specific drug compared to other drugs. Pneumonitis, colitis, hypothyroidism, and hyperthyroidism are significantly more likely to occur while taking Keytruda compared to other drugs in PharmaPendium, while nausea is less likely to be a reported AE (Figure 10, secondary Y-axis). Many other AEs, such as diarrhea and rash, are not any more likely to be reported compared to other drugs. Colitis is also significantly more likely to occur while being treated with YERVOY, but also hepatitis (Figure 11, secondary Y-axis). Fatigue, pyrexia, and abdominal pain are not any more likely to be reported for YERVOY compared to other drugs.

Analysis of “death” as an adverse event for Keytruda and YERVOY shows that the PRR is 1.0 and 0.8 respectively (Table 3), demonstrating that this is not a significant increase in the likelihood of death compared to other drugs in the PharmaPendium database.

A comparative analysis of 10 of the most frequent post-marketing AEs reported for Keytruda and YERVOY (these selected AEs were based on being found in the top 20 reported events for both Keytruda and YERVOY). Malignant neoplasm progression and death were reported significantly more compared to any other AEs for patients taking Keytruda (Figure 12). However, the likelihood of death being reported is not any more likely than a patient taking any other drug (Figure 12, secondary Y-axis). Moreover, malignant neoplasm progression, death, and diarrhea are the most common post-marketed AEs reported (Figure 12). YERVOY is less likely to have reports of malignant neoplasm progression compared to Keytruda, but still significantly more likely than the other marketed drugs (Figure 12, secondary Y-axis). This causality regarding the increase of neoplasm is likely related to the patients having various metastases and unlikely due to the drug itself. That is, it may reflect the patient demographic. The statistical likelihood of death being reported for YERVOY is slightly less compared to all other drugs in the PharmaPendium database and is also slightly lower than Keytruda. Overall, normalized rates of post-marketing adverse event reporting for Keytruda and YERVOY are 6265 and 2728 reported AE’s per year, respectively.

Data and analytics generated using PharmaPendium www.elsevier.com/solutions/pharmapendium-clinical-data

Deaths attributed to Keytruda Keytruda PRR Deaths attributed

to YERVOY YERVOY PRR Death reports for all drugs

45 1.0 22 0.8 9005

Table 3: Number of deaths attributed to Keytruda and YERVOY with associated PRR

In 2018, two out of the three most cited research papers with the term melanoma in the title, abstract, or keywords discussed the influence of the microbiome on the response to melanoma treatment in humans.

Recent research shows a growing interest in the various ways in which microbiota affects us in sickness and in health. Multiple publications implicate microbiota in the onset and progression of cancers, as well as toxicity and the response rate of cancer treatments.

The chart below shows the increase in the number of articles linking cancers to microbiota for five cancer types with the highest number of reports overall (Figure 13). The data was retrieved using Elsevier Text Mining solution by querying over 12 million full-text publications, 29 million abstracts and 521,000 grant applications for semantic relations between cancers and microbiota.

The link between melanoma and the microbiome is trending due to the recent findings that show that response to immune checkpoint inhibitors, a new class of drugs effective in melanoma treatment, correlates with the composition, diversity and functional differences in patients’ microbiomes. First shown in animal models, this connection was further confirmed in human studies, two of which, based on Elsevier’s Scopus data, landed in the top three most cited research articles about melanoma for 2018 with over 700 citations as of today 36,37.

The chart below shows an increasing number of publications exploring relations between microbiota, immune checkpoint and immune checkpoint inhibitors (Figure 14). The data was retrieved using Elsevier Text Mining solution by querying for semantic relations between microflora and concepts related to the immune checkpoint (e.g. drugs and prominent regulators).

10 common post-marketing adverse events & associated PRR

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Figure 12: Ten common AEs from the top 20 post-marketing events reported for Keytruda and YERVOY with associated PRR

Trending topics in melanoma

17Life Sciences Professional Services

Bacterial species, genera and families with the highest number of mentions in the same sentence with immune checkpoint-related concepts is shown in the chart below (Figure 15).

A growing body of evidence suggests the importance of looking for predictors of therapeutic response beyond the tumor by focusing on host factors, such as microbiota and host genomics38. Importantly, microbiota is a modifiable factor, and potentially can become not just a predictive marker but also a potential target in order to improve outcomes for melanoma patients.

Since 2018, four clinical trials aimed at studying and modulating the gut microbiome’s impact on response to immunotherapy of melanoma have been registered at clinicaltrials.gov and are currently recruiting patients or about to start the recruitment. As pointed out by Li et al, “the era of microbiomes has quietly come, and pioneering reports of preclinical and clinical research on the role of microbiome in cancer have made gut microbiome a promising strategy for cancer treatment” 39.

Data and analytics generated using Elsevier Text Mining www.elseviertextmining.com/about.html & Scopus www.elsevier.com/solutions/scopus

MelanomaGastric cancerHepatocellular carcinoma Colon cancerColorectal cancer

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

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Figure 13: Trend of reports linking cancers to the microbiota from 2008–present

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0 50 100 150 200 250 300

Figure 14: Trend of number of reports linking immune checkpoint to microbiota from 2014–present

Figure 15: Bacterial species mentioned in conjunction with immune checkpoint related terms

19Life Sciences Professional Services

With the prevalence of melanoma continuing to rise and the observed linear increase from our analysis of the CDC data (Figure 1), by 2030 the number of melanoma cases could range from 100,000 to 125,000 in the US alone if the current trend persists. And the greatest melanoma instances are observed in Australasian, North American, European, elderly, and male populations40. However, in the face of increases in incidences of melanoma, the death rates are the lowest they have been in the US since 2005, which is probably due to increased awareness and preventative measures, better diagnosis, and improvement in treatments.

Analyzing publications, it is apparent that BRAF and PDCD1 predominate in research regarding melanoma, and while BRAF has persisted over a long publication timeframe, the research regarding PDCD1’s involvement in melanoma is relatively new in comparison. Moreover, there is a current trend in investigating gene variants and their involvement in driving the disease in patients carrying these mutations. A potential gap discovered through the analysis of genes that are genetically linked to melanoma for both hereditary and sporadic cases are the genes with no known genetic variants associated with the disease. This opens up the opportunity to determine if variants are clinically significant and, if so, what impact do they have on the disease state. Understanding the biological pathways of melanoma provides novel opportunities to target the disease in a more directed approach, and discovery and research of genetic variants opens up new avenues for treatment design in specific populations, as noted for the potential investigation treatment of patients carrying the AKT E17K mutation with temsirolimus.

The increase in development of small molecule therapeutics is evident, and there is an encouraging trend in increased

approvals of drugs targeting melanoma, as well as promising therapeutics in the pre-clinical and clinical pipeline. This is observed in the AstraZeneca clinical trials on the use of selumetinib in patients with uveal melanoma, which is reported to block the methyl ethyl ketone (MEK) protein that is activated in some uveal melanoma cells, and the therapeutic is reported to inhibit cancer growth. More targeted immunotherapies are being approved and under development for melanoma, and there are currently seven FDA approved immunotherapies to treat melanoma, including YERVOY, a checkpoint inhibitor that targets the CTLA-4 pathway, and Keytruda, a checkpoint inhibitor that targets the PD-1/PD-L1 pathway. Moreover, more combination therapies are also being trialed and approved such, as the combination of OPDIVO and YERVOY, and the recent FDA approval of Array Biopharma’s (recently acquired by Pfizer) combination therapy of BRAFTOVI and MEKTOVI for patients with unresectable or metastatic melanoma with a BRAF V600E or V600K mutation. Through this analysis, it was noted that Keytruda acts on PDCD1, and would be beneficial to be given in combination with other immunomodulatory therapeutics in patients with non-PDCD1 immune-suppressed melanoma cases.

Trending topics in melanoma show the importance of the microbiome and its involvement in cancer progression and treatment. It is an attractive future research avenue to recognize how a patient’s microorganisms’ genome, both symbiotic and pathogenic, can dramatically affect treatment plans and outcomes. Positively influencing the microbiome in melanoma patients needs further study that could lead to exciting opportunities for patients and for drug discovery.

Conclusion

Appendix

Appendix 1: Pathway Studio Legend Appendix 2: Pathway Studio Legend Appendix 3: Pathway Studio Legend

Appendix 4: Gene symbols & Protein full names with Entrez Gene ID

Official Symbol Official Full Name Entrez GeneID

BRAF B-Raf proto-oncogene, serine/threonine kinase 673

PDCD1 programmed cell death 1 5133

CDKN2A cyclin dependent kinase inhibitor 2A 1029

MITF melanocyte inducing transcription factor 4286

IL2 interleukin 2 3558

CTLA4 cytotoxic T-lymphocyte associated protein 4 1493

TNF tumor necrosis factor 7124

KIT KIT proto-oncogene, receptor tyrosine kinase 3815

NRAS NRAS proto-oncogene, GTPase 4893

AKT1 AKT serine/threonine kinase 1 207

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