Risk of cancer development in patients with keloids

Multi-ancestry meta-analysis of keloids uncovers novel susceptibility loci in diverse populations

Keloids are raised scars that grow beyond original wound boundaries, resulting in pain and disfigurement. Reasons for keloid development are not well-understood, and current treatment options are limited. Keloids are more likely to occur in darker-skinned individuals of African and Asian descent than in Europeans. We performed a genome-wide association study (GWAS) examining keloid risk across and within continental ancestry groups, incorporating 7,837 cases and 1,593,009 controls. We detected 21 novel independent loci in the multi-ancestry analysis, including several previously associated with fibroproliferative disorders. Heritability estimates were 6%, 21%, and 34% for the European, East Asian, and African ancestry analyses, respectively. Genetically predicted gene expression and colocalization analyses identified 27 gene-tissue pairs, including nine in skin and fibroblasts. Pathway analysis implicated integrin signaling and upstream regulators involved in cancer, fibrosis, and sex hormone signaling. This investigation nearly quintuples the number of keloid-associated risk loci, illuminating biological processes in keloid pathology.

Construction of ceRNA Network and Disease Diagnosis Model for Keloid Based on Tumor Suppressor ERRFI1

The aim of this study is to identify the key biomarker of keloid (KD) with significant diagnostic value and to construct the related competing endogenous RNA (ceRNA) network and disease diagnostic model to provide new ideas for the early diagnosis and prevention of KD. Public databases were used to identify the key gene of KD. Enrichment analysis and immune cell infiltration (ICI) analysis revealed its functional and immune characteristics. Then, a ceRNA network was constructed to explore the potential pathways of it. Random forest (RF) analysis was applied to construct a predictive model for the disease diagnosis of KD. Finally, immunohistochemistry (IHC) and RT-qPCR were used to verify the differential expression of key gene. ERRFI1 was identified as a key biomarker in KD and was lowly expressed in KD. The ceRNA network revealed that H0TAIRM1-has-miR-148a-3p-ERRFI1 may be a potential pathway in KD. Finally, a 2-gene diagnostic prediction model (ERRFI1, HSD3B7) was constructed and externally validated and the results suggested that the model had good diagnostic performance. ERRFI1 is a downregulated gene in KD and is expected to be a promising predictive marker and disease diagnostic gene. ICI may play a role in the progression of KD. The ceRNA network may provide new clues to the potential pathogenesis of KD. Finally, the new KD diagnostic model could be an effective tool for assessing the risk of KD development.

Scar matrix drives Piezo1 mediated stromal inflammation leading to placenta accreta spectrum

Scar tissue formation is a hallmark of wound repair in adults and can chronically affect tissue architecture and function. To understand the general phenomena, we sought to explore scar-driven imbalance in tissue homeostasis caused by a common, and standardized surgical procedure, the uterine scar due to cesarean surgery. Deep uterine scar is associated with a rapidly increasing condition in pregnant women, placenta accreta spectrum (PAS), characterized by aggressive trophoblast invasion into the uterus, frequently necessitating hysterectomy at parturition. We created a model of uterine scar, recapitulating PAS-like invasive phenotype, showing that scar matrix activates mechanosensitive ion channel, Piezo1, through glycolysis-fueled cellular contraction. Piezo1 activation increases intracellular calcium activity and Protein kinase C activation, leading to NF-κB nuclear translocation, and MafG stabilization. This inflammatory transformation of decidua leads to production of IL-8 and G-CSF, chemotactically recruiting invading trophoblasts towards scar, initiating PAS. Our study demonstrates aberrant mechanics of scar disturbs stroma-epithelia homeostasis in placentation, with implications in cancer dissemination.

Targeting Diverse Wounds and Scars: Recent Innovative Bio-design of Microneedle Patch for Comprehensive Management

Wounds and the subsequent formation of scars constitute a unified and complex phased process. Effective treatment is crucial; however, the diverse therapeutic approaches for different wounds and scars, as well as varying treatment needs at different stages, present significant challenges in selecting appropriate interventions. Microneedle patch (MNP), as a novel minimally invasive transdermal drug delivery system, has the potential for integrated and programmed treatment of various diseases and has shown promising applications in different types of wounds and scars. In this comprehensive review, the latest applications and biotechnological innovations of MNPs in these fields are thoroughly explored, summarizing their powerful abilities to accelerate healing, inhibit scar formation, and manage related symptoms. Moreover, potential applications in various scenarios are discussed. Additionally, the side effects, manufacturing processes, and material selection to explore the clinical translational potential are investigated. This groundwork can provide a theoretical basis and serve as a catalyst for future innovations in the pursuit of favorable therapeutic options for skin tissue regeneration.

Risk factors for local recurrence of keloids and hypertrophic scars after postoperative electron beam radiotherapy

OBJECTIVE

Keloids and hypertrophic scars are benign fibroproliferative lesions that occur as a result of skin injury. Postoperative radiation therapy is used to reduce the recurrence rate because of the high recurrence rate with surgical treatment alone. This study aimed to identify the risk factors for recurrence after postoperative electron beam radiotherapy.

MATERIALS AND METHODS

Patients with keloid or hypertrophic scars with at least one lesion and who underwent postoperative electron beam radiotherapy at our institution from June 2013 to March 2022 were included in the study, while patients with a follow-up period of fewer than three months were excluded.

RESULTS

A retrospective analysis was performed on 94 lesions in 81 patients. Exactly two years after the treatment, the actuarial local control rate was 86.4%. The chest wall, shoulder, and suprapubic area were identified as high-risk recurrence sites. Compared to other body sites, these sites had significantly lower local control rates (two-year local control rates: 75.5% vs. 95.2%, P = 0.005). After multivariate analysis, treatment site (P = 0.014), male gender (P = 0.019), and younger age (P = 0.029) were revealed to be statistically significant risk factors for local recurrence. Risk factors for keloid recurrence after postoperative electron beam radiotherapy were therefore identified.

CONCLUSION

This result could be used for follow-up and as a determinant for the optimal dose/fractionation of postoperative radiotherapy.

Scars

Wound healing occurs as a response to disruption of the epidermis and dermis. It is an intricate and well-orchestrated response with the goal to restore skin integrity and function. However, in hundreds of millions of patients, skin wound healing results in abnormal scarring, including keloid lesions or hypertrophic scarring. Although the underlying mechanisms of hypertrophic scars and keloid lesions are not well defined, evidence suggests that the changes in the extracellular matrix are perpetuated by ongoing inflammation in susceptible individuals, resulting in a fibrotic phenotype. The lesions then become established, with ongoing deposition of excess disordered collagen. Not only can abnormal scarring be debilitating and painful, it can also cause functional impairment and profound changes in appearance, thereby substantially affecting patients' lives. Despite the vast demand on patient health and the medical society, very little progress has been made in the care of patients with abnormal scarring. To improve the outcome of pathological scarring, standardized and innovative approaches are required.

Modelling Keloids Dynamics: A Brief Review and New Mathematical Perspectives

Keloids are fibroproliferative disorders described by excessive growth of fibrotic tissue, which also invades adjacent areas (beyond the original wound borders). Since these disorders are specific to humans (no other animal species naturally develop keloid-like tissue), experimental in vivo/in vitro research has not led to significant advances in this field. One possible approach could be to combine in vitro human models with calibrated in silico mathematical approaches (i.e., models and simulations) to generate new testable biological hypotheses related to biological mechanisms and improved treatments. Because these combined approaches do not really exist for keloid disorders, in this brief review we start by summarising the biology of these disorders, then present various types of mathematical and computational approaches used for related disorders (i.e., wound healing and solid tumours), followed by a discussion of the very few mathematical and computational models published so far to study various inflammatory and mechanical aspects of keloids. We conclude this review by discussing some open problems and mathematical opportunities offered in the context of keloid disorders by such combined in vitro/in silico approaches, and the need for multi-disciplinary research to enable clinical progress.

Multifaced roles of desmoplastic reaction and fibrosis in pancreatic cancer progression: Current understanding and future directions

Desmoplastic reaction is a fibrosis reaction that is characterized by a large amount of dense extracellular matrix (ECM) and dense fibrous stroma. Fibrotic stroma around the tumor has several different components, including myofibroblasts, collagen, and other ECM molecules. This stromal reaction is a natural response to the tissue injury process, and fibrosis formation is a key factor in pancreatic cancer development. The fibrotic stroma of pancreatic cancer is associated with tumor progression, metastasis, and poor prognosis. Reportedly, multiple processes are involved in fibrosis, which is largely associated with the upregulation of various cytokines, chemokines, matrix metalloproteinases, and other growth factors that promote tumor growth and metastasis. Fibrosis is also associated with immunosuppressive cell recruitment, such as regulatory T cells (Tregs) with suppressing function to antitumor immunity. Further, dense fibrosis restricts the flow of nutrients and oxygen to the tumor cells, which can contribute to drug resistance. Furthermore, the dense collagen matrix can act as a physical barrier to block the entry of drugs into the tumor, thereby further contributing to drug resistance. Thus, understanding the mechanism of desmoplastic reaction and fibrosis in pancreatic cancer will open an avenue to innovative medicine and improve the prognosis of patients suffering from this disease.

[Keloid nomogram prediction model based on weighted gene co-expression network analysis and machine learning]

Keloids are benign skin tumors resulting from the excessive proliferation of connective tissue in wound skin. Precise prediction of keloid risk in trauma patients and timely early diagnosis are of paramount importance for in-depth keloid management and control of its progression. This study analyzed four keloid datasets in the high-throughput gene expression omnibus (GEO) database, identified diagnostic markers for keloids, and established a nomogram prediction model. Initially, 37 core protein-encoding genes were selected through weighted gene co-expression network analysis (WGCNA), differential expression analysis, and the centrality algorithm of the protein-protein interaction network. Subsequently, two machine learning algorithms including the least absolute shrinkage and selection operator (LASSO) and the support vector machine-recursive feature elimination (SVM-RFE) were used to further screen out four diagnostic markers with the highest predictive power for keloids, which included hepatocyte growth factor (HGF), syndecan-4 (SDC4), ectonucleotide pyrophosphatase/phosphodiesterase 2 (ENPP2), and Rho family guanosine triphophatase 3 (RND3). Potential biological pathways involved were explored through gene set enrichment analysis (GSEA) of single-gene. Finally, univariate and multivariate logistic regression analyses of diagnostic markers were performed, and a nomogram prediction model was constructed. Internal and external validations revealed that the calibration curve of this model closely approximates the ideal curve, the decision curve is superior to other strategies, and the area under the receiver operating characteristic curve is higher than the control model (with optimal cutoff value of 0.588). This indicates that the model possesses high calibration, clinical benefit rate, and predictive power, and is promising to provide effective early means for clinical diagnosis.

Mapping variation of extracellular matrix in human keloid scar by label-free multiphoton imaging and machine learning

Significance

Rapid diagnosis and analysis of human keloid scar tissues in an automated manner are essential for understanding pathogenesis and formulating treatment solutions.

Aim

Our aim is to resolve the features of the extracellular matrix in human keloid scar tissues automatically for accurate diagnosis with the aid of machine learning.

Approach

Multiphoton microscopy was utilized to acquire images of collagen and elastin fibers. Morphological features, histogram, and gray-level co-occurrence matrix-based texture features were obtained to produce a total of 28 features. The minimum redundancy maximum relevancy feature selection approach was implemented to rank these features and establish feature subsets, each of which was employed to build a machine learning model through the tree-based pipeline optimization tool (TPOT).

Results

The feature importance ranking was obtained, and 28 feature subsets were acquired by incremental feature selection. The subset with the top 23 features was identified as the most accurate. Then stochastic gradient descent classifier optimized by the TPOT was generated with an accuracy of 96.15% in classifying normal, scar, and adjacent tissues. The area under curve of the classification results (scar versus normal and adjacent, normal versus scar and adjacent, and adjacent versus normal and scar) was 1.0, 1.0, and 0.99, respectively.

Conclusions

The proposed approach has great potential for future dermatological clinical diagnosis and analysis and holds promise for the development of computer-aided systems to assist dermatologists in diagnosis and treatment.

Comorbidities of Keloid and Hypertrophic Scars Among Participants in UK Biobank

Importance

Keloids and hypertrophic scars (excessive scarring) are relatively understudied disfiguring chronic skin conditions with high treatment resistance.

Objective

To evaluate established comorbidities of excessive scarring in European individuals, with comparisons across ethnic groups, and to identify novel comorbidities via a phenome-wide association study (PheWAS).

Design, Setting, and Participants

This multicenter cross-sectional population-based cohort study used UK Biobank (UKB) data and fitted logistic regression models for testing associations between excessive scarring and a variety of outcomes, including previously studied comorbidities and 1518 systematically defined disease categories. Additional modeling was performed within subgroups of participants defined by self-reported ethnicity (as defined in UK Biobank). Of 502 701 UKB participants, analyses were restricted to 230078 individuals with linked primary care records.

Exposures

Keloid or hypertrophic scar diagnoses.

Main Outcomes and Measures

Previously studied disease associations (hypertension, uterine leiomyoma, vitamin D deficiency, atopic eczema) and phenotypes defined in the PheWAS Catalog.

Results

Of the 972 people with excessive scarring, there was a higher proportion of female participants compared with the 229 106 controls (65% vs 55%) and a lower proportion of White ethnicity (86% vs 95%); mean (SD) age of the total cohort was 64 (8) years. Associations were identified with hypertension and atopic eczema in models accounting for age, sex, and ethnicity, and the association with atopic eczema (odds ratio [OR], 1.68; 95% CI, 1.36-2.07; P < .001) remained statistically significant after accounting for additional potential confounders. Fully adjusted analyses within ethnic groups revealed associations with hypertension in Black participants (OR, 2.05; 95% CI, 1.13-3.72; P = .02) and with vitamin D deficiency in Asian participants (OR, 2.24; 95% CI, 1.26-3.97; P = .006). The association with uterine leiomyoma was borderline significant in Black women (OR, 1.93; 95% CI, 1.00-3.71; P = .05), whereas the association with atopic eczema was significant in White participants (OR, 1.68; 95% CI, 1.34-2.12; P < .001) and showed a similar trend in Asian (OR, 2.17; 95% CI, 1.01-4.67; P = .048) and Black participants (OR, 1.89; 95% CI, 0.83-4.28; P = .13). The PheWAS identified 110 significant associations across disease systems; of the nondermatological, musculoskeletal disease and pain symptoms were prominent.

Conclusions and Relevance

This cross-sectional study validated comorbidities of excessive scarring in UKB with comprehensive coverage of health outcomes. It also documented additional phenome-wide associations that will serve as a reference for future studies to investigate common underlying pathophysiologic mechanisms.

The deubiquitinating enzyme USP37 promotes keloid fibroblasts proliferation and collagen production by regulating the c‐Myc expression

Previous research testifies that c-Myc may promote keloid fibroblast proliferation and collagen accumulation. Ubiquitin-specific peptidase 37 (USP37)-mediated deubiquitination and stabilisation of c-Myc are vital for lung cancer proliferation, while the potential role of USP37 in keloid fibroblasts is not investigated. Elevated USP37, c-Myc, and Collagen I content were detected in keloid tissue with RT-PCR or ELISA assay. USP37 over-expression plasmids or USP37 short hairpin RNAs (shRNAs) were transfected into keloid fibroblasts with Lipofectamine 3000 to decipher the role of USP37 in keloid fibroblasts. USP37 overexpression could promote the proliferation of keloid fibroblasts with increased c-Myc and Collagen I expression. On the other hand, USP37 shRNAs inhibited the proliferation of keloid fibroblasts with diminished c-Myc and Collagen I expression. It was worth noting that C-Myc overexpression promoted the proliferation of keloid fibroblasts inhibited by USP37 shRNAs with increasing Collagen I expression. All of these results demonstrate that USP37 could regulate c-Myc to promote the proliferation and collagen deposit of keloid fibroblasts, and USP37 could be targeted in future keloid therapy.

The m6A-methylated mRNA pattern and the activation of the Wnt signaling pathway under the hyper-m6A-modifying condition in the keloid

Purpose: The present study was carried out to investigate the global m⁶A-modified RNA pattern and possible mechanisms underlying the pathogenesis of keloid. Method: In total, 14 normal skin and 14 keloid tissue samples were first collected on clinics. Then, three samples from each group were randomly selected to be verified with the Western blotting to determine the level of methyltransferase and demethylase. The total RNA of all samples in each group was isolated and subjected to the analysis of MeRIP sequencing and RNA sequencing. Using software of MeTDiff and htseq-count, the m⁶A peaks and differentially expressed genes (DEGs) were determined within the fold change >2 and p-value < 0.05. The top 10 pathways of m⁶A-modified genes in each group and the differentially expressed genes were enriched by the Kyoto Encyclopedia of Genes and Genomes signaling pathways. Finally, the closely associated pathway was determined using the Western blotting and immunofluorescence staining. Results: There was a higher protein level of WTAP and Mettl3 in the keloid than in the normal tissue. In the keloid samples, 21,020 unique m⁶A peaks with 6,573 unique m⁶A-associated genetic transcripts appeared. In the normal tissue, 4,028 unique m⁶A peaks with 779 m⁶A-associated modified genes appeared. In the RNA sequencing, there were 847 genes significantly changed between these groups, transcriptionally. The genes with m⁶A-methylated modification and the upregulated differentially expressed genes between two tissues were both mainly related to the Wnt signaling pathway. Moreover, the hyper-m⁶A-modified Wnt/β-catenin pathway in keloid was verified with Western blotting. From the immunofluorescence staining results, we found that the accumulated fibroblasts were under a hyper-m⁶A condition in the keloid, and the Wnt/β-Catenin signaling pathway was mainly activated in the fibroblasts. Conclusion: The fibroblasts in the keloid were under a cellular hyper-m⁶A-methylated condition, and the hyper-m⁶A-modified highly expressed Wnt/β-catenin pathway in the dermal fibroblasts might promote the pathogenesis of keloid.

A Signature of Genes Featuring FGF11 Revealed Aberrant Fibroblast Activation and Immune Infiltration Properties in Keloid Tissue

Keloid is a fibroproliferative disorder in the skin, which manifested with extensive deposition of collagen and extracellular matrix. Its etiology remains a mystery and its recurrence rate remains high despite combinative treatment regimens. Current hypotheses of its pathogenesis centered on the role of inflammatory processes as well as immune infiltration in the microenvironment. However, there are a lot of discrepancies when it comes to the verification of certain well-recognized pathways involved in the dysfunctional fibroblast. Further exploration and characterization are required to reveal the driving force and even leading genes responsible for keloid formation. In this study, we provided supportive evidence of the immunologic nature of keloids distinct from normal fibroblasts and physiological scars by incorporating multiple available expressional profiles in the Gene Expression Omnibus (GEO). Through differential analyses and functional analyses, we identified a set of genes that successfully captures the dissimilarities between keloid lesions and nonlesions. They were differentially regulated in keloid samples and had opposite behavior in exposure to hydrocortisone. A key signature of six genes featuring FGF11 not only was highly correlated with significantly dysregulated fibroblast activation but also reflected various levels of immune cell infiltration. FGF11, in particular, revealed the heterogenous immunologic nature of keloid lesions. This study further supported that aberrant fibroblast was one of the main contributing factors and shed some light on investigating immune properties in future studies.

Epigenetic Influences on Wound Healing and Hypertrophic-Keloid Scarring: A Review for Basic Scientists and Clinicians

Primary care physicians and dermatologists are challenged by patients affected by keloid or hypertrophic scarring resulting from accidental wounding, surgical incisions, tattooing, or “branding” procedures to demonstrate their association with a specific culture, fraternity, or cult. The dysregulated wound healing associated with keloids and hypertrophic scarring adversely affects genetically susceptible individuals, especially persons of color with Fitzpatrick Skin types IV-VI. Although the specific mechanisms of bulky hypertrophic/keloid scarring and its association with oxidative stress and inflammation remain unclear, the current knowledge base is sufficient to provide some guidance to health practitioners who must serve, treat, and counsel affected individuals. This review focuses on providing insight to healthcare professionals about the role of epigenetics, oxidative stress, poor local oxygenation, and its relationship to impaired wound healing. The goal is to promote further research on bulky hypertrophic and keloid scarring for its prevention and to develop evidence-based clinical guidelines for optimal treatment.