Study on collagen parameters in vulvar cancer and preneoplastic lesions by Second Harmonic Generation microscopy

Castor, Maria das Graças de Fátima Cavalcanti; Torres, Leuridan Cavalcante; Mello, Roberto José Vieira de; Natal, Rodrigo de Andrade; Vassallo, José

doi:10.1038/s41598-020-62346-8

Cited by 6 publications

(5 citation statements)

References 26 publications

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Section: Discussionmentioning

confidence: 99%

“…Kalliopi 5 systematically investigated the expression profile of VSCC for the first time using the microarray technology and delineated the molecular parameters to reveal the cellular pathways involved in the pathogenesis of VSCC. Recently, second harmonic generation (SHG) microscopy has been used for the analysis of collagen fibers in VSCC and preneoplastic lesions and an evident decrease in the values of collagen fiber parameters in the VSCC was discovered by Leuridan et al 19 Previous research, 6 which mainly focused on genomic aberration patterns and expression profiles of VSCC, illustrated a concordant relationship between the imbalances scored by aCGH and the level of gene expression found by microarray. Genes located in gained regions were generally overexpressed while those located in lost regions were downregulated.…”

Section: Discussionmentioning

confidence: 99%

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Expression Profiles Reveal Involvement of VEGF, IGF1, BIRC5, and MMP1 in Vulvar Carcinogenesis

Zhang

Liu

et al. 2021

Technol Cancer Res Treat

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Objective: The objective of this study was to identify key genes and shed light on the underlying molecular mechanisms of vulvar squamous cell carcinoma (VSCC). Methods: Bioinformatic software was utilized for the identification and characterization of key differentially expressed genes (DEGs) from microarrays GSE63678 and GSE38228, which contain VSCC and normal vulvar tissue data. These microarrays were obtained from Gene Expression Omnibus (GEO). Immunohistochemical assays (55 VSCC and 50 normal vulvar tissues) were utilized to validate the expression of VEGF, IGF1, BIRC5, and MMP1 screened from the identified DEGs. SPSS 18.0 software was used for statistical analyses of the relationships between IGF1, BIRC5, VEGF, MMP1 expression levels and patient clinicopathological characteristics. Results: A total of 141 DEGs were identified, among which 18 genes were closely correlated with the biological characteristics of VSCC. Four of the 18 genes ( VEGF, IGF1, BIRC5, and MMP1) screened from the GEO database were markedly enriched in pathways in cancer ( P < 0.05), and could be considered key genes in VSCC based on KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis in DAVID (Database for Annotation, Visualization and Integrated Discovery).The expression levels of these 4 hub genes, determined by immunohistochemical assays, were consistent with the bioinformatics results. Higher expression of IGF1 showed significant association with well-differentiated carcinomas ( P = 0.017). BIRC5 expression levels showed a positive correlation with clinical stage ( P = 0.039); compared with those in menopause for over 10 years, patients in menopause for less than 10 years at the time of diagnosis tended to have significantly higher expression of BIRC5 ( P = 0.003). VEGF and MMP1 expression levels were not correlated with any of the tested clinicopathological characteristics. Conclusion: VEGF, IGF1, BIRC5, and MMP1 were identified as being associated with VSCC using integrated bioinformatic methods, which may provide important insights into the pathogenesis of this disease and help to identify new biomarkers.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Expression Profiles Reveal Involvement of VEGF, IGF1, BIRC5, and MMP1 in Vulvar Carcinogenesis

Zhang

Liu

et al. 2021

Technol Cancer Res Treat

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“…The study revealed that organization, uniformity and quantity, of collagen fibers were reduced in both preneoplastic lesions and squamous carcinoma as compared to normal tissue, Though, the difference between preneoplastic lesions and squamous carcinoma was not notable. On the other hand, the presence of distant metastasis correlated with increased collagen uniformity and quantity compared to VSCC without metastasis [81]. SH microscopy can identify three tumor-associated collagen signatures (TACS) at different stages of tumor progression.…”

Section: Applications For Cancer Imagingmentioning

confidence: 99%

Imaging at the nexus: how state of the art imaging techniques can enhance our understanding of cancer and fibrosis

Baniasadi,

Das,

Prendergast

et al. 2024

J Transl Med

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Both cancer and fibrosis are diseases involving dysregulation of cell signaling pathways resulting in an altered cellular microenvironment which ultimately leads to progression of the condition. The two disease entities share common molecular pathophysiology and recent research has illuminated the how each promotes the other. Multiple imaging techniques have been developed to aid in the early and accurate diagnosis of each disease, and given the commonalities between the pathophysiology of the conditions, advances in imaging one disease have opened new avenues to study the other. Here, we detail the most up-to-date advances in imaging techniques for each disease and how they have crossed over to improve detection and monitoring of the other. We explore techniques in positron emission tomography (PET), magnetic resonance imaging (MRI), second generation harmonic Imaging (SGHI), ultrasound (US), radiomics, and artificial intelligence (AI). A new diagnostic imaging tool in PET/computed tomography (CT) is the use of radiolabeled fibroblast activation protein inhibitor (FAPI). SGHI uses high-frequency sound waves to penetrate deeper into the tissue, providing a more detailed view of the tumor microenvironment. Artificial intelligence with the aid of advanced deep learning (DL) algorithms has been highly effective in training computer systems to diagnose and classify neoplastic lesions in multiple organs. Ultimately, advancing imaging techniques in cancer and fibrosis can lead to significantly more timely and accurate diagnoses of both diseases resulting in better patient outcomes.

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“…Collagen quantity, uniformity and organization measured with SHG and ImageJ software in both the forward and backwards directions can identify human mammary tumor subgroups [57] and collagen quantity and uniformity from SHG images can predict outcome in luminal breast cancer [58]. Similarly in human vulvar squamous cell carcinoma, increased collagen quantity and uniformity correlated with the presence of distant metastasis, suggesting that these collagen parameters could be used for prognosis in this type of cancer as well [59]. In murine colorectal cancer, SHG paired with metabolic in vivo imaging could predict response to chemotherapy [60], which could tailor personalized oncologic therapies.…”

Section: Plos Onementioning

confidence: 99%

Intratumoral collagen signatures predict clinical outcomes in feline mammary carcinoma

et al. 2020

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Breast cancer is the most common cause of cancer-related deaths in women worldwide. Identification of reliable prognostic indicators and therapeutic targets is critical for improving patient outcome. Cancer in companion animals often strongly resembles human cancers and a comparative approach to identify prognostic markers can improve clinical care across species. Feline mammary tumors (FMT) serve as models for extremely aggressive triple negative breast cancer (TNBC) in humans, with high rates of local and distant recurrence after resection. Despite the aggressive clinical behavior of most FMT, current prognostic indicators are insufficient for accurately predicting outcome, similar to human patients. Given significant heterogeneity of mammary tumors, there has been a recent focus on identification of universal tumor-permissive stromal features that can predict biologic behavior and provide therapeutic targets to improve outcome. As in human and canine patients, collagen signatures appear to play a key role in directing mammary tumor behavior in feline patients. We find that patients bearing FMTs with denser collagen, as well as longer, thicker and straighter fibers and less identifiable tumor-stromal boundaries had poorer outcomes, independent of the clinical variables grade and surgical margins. Most importantly, including the collagen parameters increased the predictive power of the clinical model. Thus, our data suggest that similarities with respect to the stromal microenvironment between species may allow this model to predict outcome and develop novel therapeutic targets within the tumor stroma that would benefit both veterinary and human patients with aggressive mammary tumors.

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Study on collagen parameters in vulvar cancer and preneoplastic lesions by Second Harmonic Generation microscopy

Cited by 6 publications

References 26 publications

Expression Profiles Reveal Involvement of VEGF, IGF1, BIRC5, and MMP1 in Vulvar Carcinogenesis

Expression Profiles Reveal Involvement of VEGF, IGF1, BIRC5, and MMP1 in Vulvar Carcinogenesis

Imaging at the nexus: how state of the art imaging techniques can enhance our understanding of cancer and fibrosis

Intratumoral collagen signatures predict clinical outcomes in feline mammary carcinoma

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