Psoriasis is one of the most common and chronic skin diseases (1). It is characterized by rough scales on the skin. It could appear on any part of the body and it affects both children and adults (1). About 2-3% individuals are affected by psoriasis worldwide, that means more than 125 million people suffer from psoriasis (2). Males and females are equally targeted by psoriasis i.e., male to female ratio is 1:1. The usual onset of the disease is reported to be between 18 and 39 years, or between 50 and 69 years (2). The onset age of the disease is associated with genetic and epigenetic factors (2). The incidence rate of psoriasis is also observed to increase with time (3). The pathogenesis of psoriasis is still unclear and there are two hypotheses regarding it (4). The first hypothesis assumes that in psoriasis the immune system of the body appears to be hyperactive to an extent that it attacks itself (4); which is the characteristic of the autoimmune disease. Therefore, psoriasis shows characteristics of an autoimmune disorder (4, 5). According to the second hypothesis, the life cycle of the skin cells speeds up in psoriasis from 28 days to 3-6 days, which results in excessive cell growth (4, 6). It eventually causes the formation of dead skin cells. Despite of being shed off, these dead cells accumulate at the surface of the skin and form lesions and patches (6). Frequently, red patches or dry scales appear on elbows, knees, and scalps (7). In an individual’s lifetime psoriasis often occur repeatedly (7). The exact cause and cure of psoriasis has not yet been discovered. However, multiple factors including environmental & genetic factors and immune system of the body are considered for it (8). It is predicted that environmental factors like cold and dry weather could trigger the symptoms of psoriasis (9). Moreover, the symptoms of psoriasis could appear after certain infections like strep throat and even in stress (9). Both genetic and epigenetic factors play the substantial role in the formation and exacerbation of the symptoms of the disease (10). Genetic risk factors are HLA-Cw6, mutations in CARD14 (10). CARD14 is caspase recruitment domain family member 14 gene. Obesity, stress, smoking, alcohol consumption, HIV infection, and certain medications serve as the epigenetic factors of the disease (11).

Association of psoriasis with other comorbidities, like cardiovascular diseases, diabetes, and metabolic syndrome, has been observed (12). An interesting study (13) was conducted for analyzing the implication of cutaneous squamous cell carcinoma (cSCC) antigen with psoriasis. This study was based on the fact that serum (fluid after blood coagulation) examination of psoriasis patients always revealed the presence of cSCC antigen. The study confirmed the concentration and over-expression of cSCC antigen in psoriatic lesions. A transcriptome level analysis was performed to reveal common patterns in cSCC and psoriasis (14). In this experiment, expression levels in cSCC were compared with multiple cutaneous disorders by performing microarray analysis. The comparison of cSCC with psoriasis (psoriasis vulgaris) revealed some genes depicting same expression behavior by up regulation in both disease states of cSCC and psoriasis. Subsequently, RT (real time) reverse transcription PCR (polymerase chain reaction) along with immunohistochemistry were also performed to validate the differential expression of genes attained after comparison in both disease states of cSCC and psoriasis. The common over-expressed genes found in both cSCC and psoriasis were: DEFB4 (defensin B4), SERPINB3, STAT1, K16 (keratin 16), WNT5A, and CEACAM5. In another study (15), histopathological examination of a biopsy of a psoriasis patient revealed the development of cSCC. That patient showed negative family history regarding psoriasis and only received homeopathic treatment for psoriasis.

Studies have revealed the possibility of association of psoriasis with skin cancers, particularly non melanoma skin cancer (NMSC), which include basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) (12, 16). A cohort study (1988-2011) (16) was conducted for estimating malignancy rates in psoriasis patients treated with systemic therapy. This study reported that there exists a higher rate of developing cSCC among psoriasis patients who were treated with biologics as a treatment. The speculation regarding the association of psoriasis with NMSC was built on the fact that immunosuppressors and ultraviolet phototherapy are used for treating psoriasis (12, 16). Moreover, the long-lasting inflammatory nature of psoriasis might also escalate the threat of NMSC in psoriasis patients (12). That is why, the second studied disease in this study is cSCC.

Most commonly, skin cancer is characterized by the abnormal growths of the skin (17). A sore that does not heal or takes time to heal could also be the indicator of skin cancer. Symptoms of skin cancer vary differently for its different subtypes. For instance, it could appear as small, smooth lumps. However, in some cases skin cancer appears as scaly, hard lumps that often bleed (17). Skin cancer is divided into melanoma and non-melanoma categories. Basal Cell Carcinoma (BCC) and Squamous Cell Carcinoma (SCC) set up non-melanoma skin cancer (17, 18). Squamous Cell Carcinoma is also known as cutaneous squamous cell carcinoma (cSCC). cSCC is the second most prevalent non-melanoma skin cancer (19, 20) and has the potential to recur/revert (19). It is mostly reported to appear in the Caucasian population (21). Furthermore, cSCC also accounts for about 20% of all the cutaneous cancers (19, 20, 22, 23). Regardless of the low occurrence of cutaneous SCC, it is responsible for the majority of the metastasis in disease, eventually causing deaths (24). It is stated to be counted in the list of topmost expensive cancers in the US (United States) (24). The prevalence rate of the cSCC is also vastly growing annually (25). Cutaneous SCC is caused by malignant multiplication and spread of epidermal keratinocytes (26). Often it appears on the sun exposed areas of the body; like face, head, hands, dorsal side of forearms and neck regions (17), and is more prevalent in elderly males (26). It has also been observed and reported that the particular rough patches resulted from sun exposure (aka Actinic Keratosis) also transform or lead to cSCC (17, 26, 27). Light skin tone, ultraviolet radiations, arsenic compounds, and immunosuppression are the reported risk factors and are found to increase the likelihood of developing cSCC (28). Some of the common pathological and clinical factors for the examination of the disease are age, gender, ethnicity, tumor size, histology, organ transplantation, psoriasis, leukemia, history of previously injured skin & nodal metastasis (29). Along with patient’s characteristics, tumor site & size, tumor depth, and histologic features accounts for recurrence and metastasis risks of cSCC (26). Genes which are reported to be frequently mutated in cSCC are TP53, CDKN2A, Ras, and NOTCH1 (20).

With the increasing annual incidence of psoriasis and cSCC, there is a great urge to comprehend and compare the diseases at the molecular level by interpreting the genomic data. There is a need to validate known biomarkers of psoriasis and cSCC through high throughput data. Moreover, common therapeutic target for both the diseases is not yet discovered. It has also been discussed that prolonged psoriasis could lead to cSCC (15). According to our understanding, the association of both the diseases has not been comparatively analyzed at molecular level in detail. In the current study, microarray and RNA-seq data analyses have been performed on the publicly available datasets of both psoriasis and cSCC to reveal the common and uncommon patterns in both the diseases.

The workflow to identify potential biomarkers, therapeutic targets, and to comprehend the association between cSCC and psoriasis, is given in Figure 1 and described below in detail.

Psoriasis is one of the most common and chronic skin diseases (1). It is characterized by rough scales on the skin. It could appear on any part of the body and it affects both children and adults (1). About 2-3% individuals are affected by psoriasis worldwide (2), and the incidence rate of psoriasis is also observed to increase with time (3). Association of psoriasis with other comorbidities, like cardiovascular diseases, diabetes, and metabolic syndrome, has been observed (12). Studies have also revealed the possibility of association of psoriasis with skin cancers, particularly non-melanoma skin cancers (NMSC), which include basal cell carcinoma (BCC) and cutaneous Squamous Cell Carcinoma (cSCC) (12, 16). Hence, the second analyzed disease in this study is cSCC. It is the second most prevalent nonmelanoma skin cancer (19, 20) with potential to metastasize and recur in some cases (19). Moreover, the incidence rate of cSCC is also increasing annually (19, 20). Therefore, there exists a dire need to analyze both the diseases at the molecular level to propose potential biomarkers and common therapeutic targets.

This study was designed to interpret and compare the high-throughput data of psoriasis and cSCC, aiming to reveal potential biomarkers, common therapeutic targets, and the association between the two diseases. Microarray and RNA-seq data analyses were performed on the datasets of psoriasis and cSCC (given in Table 1 ) to reveal the common and uncommon patterns. After performing differential expression analysis, pathway analysis was performed to analyze the disrupted pathways and their possible relation with the disease. The common pathway between the diseases was selected for further analysis. Afterwards, quantitative systems biology was implemented, by using SimBiology application in Matlab (30), to analyze the results at a holistic level. The differential expression analysis of both the analyzed diseases resulted in the identification of DEGs. Top 10 DEGs (along with p-value and Log₂FC) from all the analyzed datasets are provided in Supplementary Tables S1–S18 . The identified number of DEGs from microarray data analysis are given in Table 2 . The comparison of microarray datasets of psoriasis resulted in one common DEG, named S100A8. The significant role of S100A8 in prognosis of psoriasis is also illustrated in the literature (48). The overexpression of S100A8 causes keratinocyte proliferation and angiogenesis in psoriatic skin (47, 49). The comparison of microarray datasets of cSCC resulted in no common gene. The number of identified DEGs from RNA-seq data analysis is given in Table 3 . The comparison of RNA-seq datasets resulted in 16 and 26 common DEGs for psoriasis and cSCC, respectively (given in Table 3 ). These common DEGs could be proposed as potential biomarkers of the diseases. The overall comparative analysis of identified DEGs from all the analyzed datasets of both the diseases resulted in common DEGs between the two diseases, as given in Table 6 . These DEGs may represent the potential biomarkers or therapeutic targets of psoriasis and cSCC.

Pathway analysis of DEGs of psoriasis and cSCC revealed the enrichment of these DEGs in various pathways (provided in Supplementary Table 1 ). The current study has proposed one common significant pathway, IL-17 signaling pathway, based on the enrichment of DEGs of both the diseases in that pathway (given in Table 4 ). Genome-wide association and other genetic studies have clearly linked multiple IL-17–related genes to psoriasis pathogenesis. Psoriasis is one of the most typical IL-17A-driven human diseases (50). The expression of various IL-17 signaling pathway genes elevated in psoriatic lesional tissue compared with non-lesional tissue (51). The significance of IL-17 signaling pathway in the prognosis of cSCC is also illustrated in the literature, as the disrupted IL-17 pathway promotes tumor development by activating cytokines production (52).

IL-17 signaling pathway was selected for further analysis, as it was common in both psoriasis and cSCC datasets. IL-17 signaling play a critical role in tumor microenvironment by facilitating tumor formation and metastasis (53). Quantitative systems biology was implemented to analyze the results at a holistic level. A sub-section of complete IL-17 pathway was modeled by using SimBiology application in Matlab (30). The average expressions values of DEGs that were present in the pathway were calculated for microarray datasets of psoriasis and cSCC, as given in Table 5 . The model was then simulated by adding the average expression values to the species (genes) as initial state values. The biological processes being analyzed in the model were autoimmune pathology, neutrophil recruitment, and immunity to extracellular pathogens. Autoimmunity is defined as when the immune system of the body becomes hyperactive and acts against self-antigen, thus, resulting in tissue damage (54). Cancer is often associated with autoimmunity. Autoimmune disorders like scleroderma and myositis might increase the risk of cancer (55). Neutrophils are the type of leukocytes that protect the body in state of infections and inflammation (56). Clinical evidence has revealed that tumor associated neutrophils (TANs) might play a critical role in tumor progression. Adaptive immune system of the host becomes activated by exhibiting particular responses to extracellular pathogens (57). The clinical evidence has suggested that abnormal adaptive immunity lead to tumor cell proliferation by inducing immunosuppression (58).

The Figures 5A, B depict simulated processes of autoimmune pathology, neutrophil recruitment, and immunity to extracellular pathogens in psoriasis and cSCC, respectively. It is cleared from Figures 5A, B that the rate of these biological processes increases over time in both psoriasis and cSCC. However, the rate is relatively higher in psoriasis. The peak value of these biological processes in psoriasis is around 28 in 9.5 time units, whereas it is observed to be around 21 in 10 time units in cSCC.

After simulation of the model, sensitivity analysis was performed to analyze the response of the biological processes to model quantities (DEGs and genes). The sensitivity analysis revealed that autoimmune pathology, neutrophil recruitment, and immunity to extracellular pathogens are highly sensitive towards MAPKs, chemokines, tissue remodeling genes, and AP-1 (FOSL1 and FOS genes) in psoriasis, having sensitivity values greater than 1.5 Figure 6 . It indicates that the slight changes in these genes profoundly affect the biological processes. These results are also consistent with the literature. Disrupted signaling pathways are associated with the complex pathogenesis of psoriasis, particularly, the possible pathogenic role of disrupted MAPK signaling in the development of psoriasis (59, 60). Chemokines and chemokine receptors are involved in the pathogenesis of psoriasis by facilitating the trafficking of T-cells in psoriasis (61). Therefore, targeting chemokines in psoriasis would result in therapeutic effect and improved treatment for psoriasis (61, 62). Tissue remodeling genes (MMPs) contribute to the pathogenesis of psoriasis by stimulating angiogenesis and intrusion of immune cells in the dermal tissue (63). AP-1 (the transcription factor activator protein 1) functions in cell proliferation. However, the binding ability of AP-1 is highly damaged in psoriatic lesional skin (64), thus genes for AP-1 are significant in pathogenesis of psoriasis and proposed as candidate target genes (65).

Whereas the sensitivity analysis of cSCC revealed that the biological processes are highly sensitive towards MAPKs, AP-1 (FOSL1 and JUN genes), and TNF genes, having sensitivity values greater than 1.5 as shown in Figure 7 . The slight changes in these genes profoundly affect the biological processes. These results are also consistent with the literature. Dysregulated MAPK signaling by high levels of HMG-1 protein stimulates metastasis in cSCC (66). Dysregulation in the expression of the genes for AP-1 (the transcription factor activator protein 1) promote cancer development as AP-1 factors are involved in keratinocyte proliferation of skin (67). TNF(Tumor necrosis factor) is a proinflammatory cytokine that mainly functions in cell proliferation, differentiation, and death, hence plays an important role in carcinogenesis (68).

Sensitivity analysis of the biological processes of both psoriasis and cSCC revealed MAPKs and genes for AP-1 as significant genes. Slight change in these genes would greatly impact autoimmune pathology, neutrophil recruitment, and immunity to extracellular pathogens. Therefore, consistent with the discussion we propose that MAPKs (MAPK13 and MAPK14) and genes for AP-1 (FOSL1 and FOS) identified from sensitivity analysis of psoriasis are significant genes that might lead psoriasis towards cancer.

In the current study, the integrated data analysis of microarray and RNA-seq was performed to reveal common patterns between psoriasis and cSCC. The differential expression analysis of both the diseases resulted in common DEGs, which are proposed as potential biomarkers and therapeutic targets for psoriasis and cSCC. IL-17 signaling pathway is identified as common significant pathway as DEGs of both the diseases were enriched in that pathway. IL-17 was further studied, and sensitivity analysis was performed that resulted in the identification of significant genes in psoriasis, that might lead psoriasis towards cancer. These significant genes are MAPKs (MAPK13 and MAPK14) and genes for AP-1 (FOSL1 and FOS). These genes should be further investigated at experimental level for validating their roles in the transfer of psoriatic condition to cSCC.

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .

SA and RP conceived and designed the study. SA conducted the analysis and wrote the manuscript. All authors contributed to the article and approved the submitted version.

National University of Sciences and Technology, Islamabad paid the publication fee for this article.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.