My PhD Story: Rachel TEH

By: Rachel TEH

What a relief to submit the final revision for my thesis! My name is Rachel Teh and after a long and arduous four years, I’ve completed my Doctor of Philosophy in Medicine and Health. My work focused on the use of proteomic methodologies to investigate early melanoma in melanocytic lesions. Specifically I utilised mass spectrometry technologies and data-independent acquisition (DIA) methodology to identify and quantify proteins of formalin-fixed paraffin-embedded (FFPE) skin biopsy tissue and tape-stripped (scarless) samples of the stratum corneum with the aim to develop a biomarker signature to diagnose melanoma.

My review of the literature found no biomarkers clinically validated for use to identify early melanoma in benign pigmented lesions such as benign naevi and dysplastic naevi. My recently published paper in Experimental Dermatology DOI: 10.1111/exd.14705 (Nov 2022) highlights the need for a comprehensive approach to enrich our understanding of pigmented lesions and how some progress to malignancy.

The genomic field has contributed to a great deal of information on genetic and associated modifications and mutations in early melanoma and benign lesions. In contrast, in the field of proteomics, there have been a limited number of studies looking into this area. In this paper, I highlight the progress the field of diagnostics has made in the use of non-invasive techniques and technologies such as 3D total body photography and tape-stripping which have great potential in providing efficient and accurate diagnoses however, these methods require further research, validation, and standardisation before they can be readily adopted in the clinical setting.

The initial stages of my PhD required the generation of a spectral ion library specialised for skin diseases; keratinocyte cancers and melanoma which was published as a dataset brief in Proteomics DOI: 10.1002/pmic.202100128 (Aug 2021). This ~8000 protein library was used to help identify skin-specific proteins in our studies which is available for download from Proteome Exchange PXD025791. In the undertaking of this paper, I showed the results of using the OneOmics platform to merge established libraries compared to the stand-alone ProteinPilot software and found the OneOmics platform was an efficient way of generating a spectral library.

Finally, and importantly, in a total of three chapters, the main study portions of my thesis describe my findings in utilising DIA methodology to identify and quantify over 1000 proteins of FFPE and scarless samples. Specifically, I looked at benign naevi, dysplastic naevi, melanoma in situ and early melanoma samples. With the help of the bioinformatics team, identified differentially abundant proteins which could have potential as biomarkers. They used machine learning algorithms (random forest, SVM, DLDA, and kNN) to assess the proteins for classification potential. Briefly, using balanced accuracy as a metric, we found the top-most differentiating proteins (up to 20) were able to acquire a classification performance of at least ~75-80% in lesions compared to melanoma in FFPE and scarless samples. In these studies, I identified proteins previously reported in the literature involved in biological functions and processes relevant to carcinogenic progression. We hope to investigate these proteins further to understand their role in melanoma progression and potential therapeutic targets.

Altogether, I show that proteomics in FFPE and scarless is a valuable tool and resource to investigate skin conditions such as melanoma and melanocytic lesions leading to more personalized and effective diagnoses and potential therapeutic targets for patients. The thesis is awaiting final approval.