Title : Integrating personalized and precision medicine into dermatology clinical practice securing its potential to get skin diseases cured and to revolutionize dermatooncology
Abstract:
The introduction of PPM-guided tools has benefits for multiple stakeholders; patients benefit by having improved outcomes, physicians can make confident decisions in managing their patients, and the healthcare system saves significant dollars through the reduction of wasted spend. It is our mission to optimize precision diagnostics and treatment, to ultimately make this treatment type available to the majority of skin cancer patients and pre-cancer persons-at-risk. PPM utilizes an individual’s genomics to improve diagnosis, prognosis, and therapy. This paradigm has been particularly true in dermatooncology where biomarker-driven treatment paradigms have become increasingly common. Biomarkers, targets and thus targeting can overcome any kinds of bottlenecks and guide us toward PPM for skin cancers as well. With credible and systemic biomarker models, more PPM-based diagnosis and assessment could be achieved. And patients would be more likely to be cured and have a higher quality of life. Nevertheless, the progression of biomarkers in, for instance, skin carcinoma is still stymied by some factors including a complexity of the carcinoma molecular profiles and thus the biomarker panels. However, multi-molecular biomarker panels integrating the information (predictor) into one predictive model significantly improve diagnostic accuracy and enhance the predictive power in skin carcinomas. In this context, there is a need to focus on tumor heterogeneity and homogeneity, whilst providing an understanding of biomarker discovery and application for PPM of oral squamous cell carcinoma. PPM-driven strategies are based on biomarkers that are most frequently derived from tissue transcriptomic expression or genomic sequencing or from circulating cytokines. For instance, the pathologic diagnosis of cutaneous melanoma and determining the prognosis of a malignant melanocytic neoplasm can be enhanced by genomic/transcriptomic analysis. High-throughput genomic technologies have facilitated the genomic, transcriptomic and epigenomic profiling of cutaneous melanoma. The translation of this knowledge and all actual advancements into the clinical practice will be helpful in better defining the different molecular subsets of melanoma patients and provide new tools to address relevant questions on disease management. Genomic technologies might indeed allow to better predict the biological - and, subsequently, clinical - behaviour for each subset of melanoma patients or pre-cancer persons-at-risk as well as to even identify all molecular changes in tumor cell populations during disease evolution toward a real achievement of PPM-driven potential resources. For instance, silencing of LZTR1 gene locus in melanoma cell lines causes apoptotic cell death independent of major hotspot mutations or melanoma subtypes. Conversely, overexpression of LZTR1 in normal human melanocytes initiates processes associated with metastasis, including anchorage-independent growth. The above-mentioned would thus implicate LZTR1 as a key tumor promoter and therapeutic target.
By analyzing tumor DNA, genetic testing can help diagnose skin cancer, predict treatment response, and identify potential targets for therapy. Some of the key genetic tests used in skin cancer diagnosis include:
- next-generation sequencing (NGS): a high-throughput sequencing technology that enables rapid analysis of multiple genes and genetic mutations;
- PCR (polymerase chain reaction): a laboratory technique used to amplify specific DNA sequences, enabling detection of genetic mutations;
- FISH (fluorescence in situ hybridization): a cytogenetic technique used to detect genetic alterations, such as chromosomal translocations or amplifications.
Advanced imaging techniques enable healthcare providers to characterize skin cancers at the cellular and molecular level. These techniques provide valuable information on tumor morphology, depth, and other characteristics that inform treatment decisions. Some of the key advanced imaging techniques used in skin cancer diagnosis include:
- Dermoscopy: A non-invasive technique that uses a specialized microscope to examine skin lesions;
- Confocal microscopy: a technique that uses a laser to create high-resolution images of skin lesions;
- Optical coherence tomography (OCT): a non-invasive imaging technique that uses low-coherence interferometry to create detailed images of skin lesions.
Accurate (precise) and evidence-based diagnosis is the foundation of personalized cancer therapy in dermatooncology. Advanced diagnostic, predictive and prognostic techniques enable healthcare providers to characterize skin cancers at the molecular level, identifying specific biomarkers and genetic mutations that inform treatment decisions.
Targeted therapies are a cornerstone of personalized therapy in dermatologic oncology. By targeting specific molecular mechanisms that drive tumor growth and progression, targeted therapies can provide more effective and less invasive treatment options for patients with skin cancer. Some examples of crucial targeted therapies used in skin cancer treatment include:
- BRAF inhibitors: targeted therapies that inhibit the BRAF protein, which is mutated in some melanomas;
- MEK inhibitors: targeted therapies that inhibit the MEK protein, which is downstream of BRAF in the MAPK/ERK pathway;
- Hedgehog pathway inhibitors: targeted therapies that inhibit the Hedgehog pathway, which is involved in the development and progression of basal cell carcinoma.
Personalized targeted cancer therapy associated with precision biomarker-driven diagnostics is an upgraded approach that involves tailoring treatments to individual patients based on their unique characteristics, such as genetic profiles, medical histories, and lifestyle factors. By providing more effective and targeted treatments, personalized therapy can improve patient outcomes, reduce healthcare costs, and enhance quality of life. In the context of dermatologic oncology, personalized therapy has revolutionized the way skin cancers are diagnosed and treated.
The field of targeted therapy is rapidly evolving, with new agents and combinations being developed to target specific molecular mechanisms. Some emerging trends in targeted therapy research include:
- combination therapies: combining targeted therapies with other treatments, such as immunotherapies or chemotherapy, to enhance treatment response;
- PPM-guided approaches: tailoring targeted therapies to individual patients based on their unique genetic profiles and tumor characteristics;
- Novel targets: identifying new molecular targets for therapy, such as epigenetic regulators or metabolic pathways.
By leveraging advanced diagnostic techniques and targeted therapies, healthcare providers can now offer patients more effective and less invasive treatment options.
Some examples of PPM-guided Programs and Plans in dermatologic oncology would include:
- Genomic profiling: using genetic testing to identify specific genetic mutations or alterations that inform treatment decisions;
- Tumor characterization: using advanced imaging techniques to characterize tumors at the cellular and molecular level;
- Personalized health and wellness management programs and planning: developing healthcare and treatment (including preventive and prophylactic) plans that are tailored to individual patients based on their unique characteristics and tumor biology.
The integration of AI into PPM-guided dermatologic oncology is transforming skin cancer care by enabling more personalized and effective treatments, minimizing treatment-related toxicities, and enhancing patient survival rates. As AI advances, it will be pivotal in developing more targeted and successful cancer therapies. The field is still in its early stages, and future progress will benefit from establishing standards and guidelines to promote rigorous methodological design and uphold ethical principles. The advent of PPM in dermatooncology could lead to a paradigm shift in how patients are treated, with the resulting improved clinical outcomes leading to concomitant reductions in wasted healthcare expenditures.
