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Nanotechnology in Modern Photodynamic Therapy of Cancer: A Review of Cellular Resistance Patterns Affecting the Therapeutic Response.

ABSTRACT: Photodynamic therapy (PDT) has emerged as a potential therapeutic option for most localized cancers. Its high measure of specificity and minimal risk of side effects compared to other therapies has put PDT on the forefront of cancer research in the current era. The primary cause of treatment failure and high mortality rates is the occurrence of cancer resistance to therapy. Hence, PDT is designed to be selective and tumor-specific. However, because of complex biological characteristics and cell signaling, cancer cells have shown a propensity to acquire cellular resistance to PDT by modulating the photosensitization process or its products. Fortunately, nanotechnology has provided many answers in biomedical and clinical applications, and modern PDT now employs the use of nanomaterials to enhance its efficacy and mitigate the effects of acquired resistance. This review, therefore, sought to scrutinize the mechanisms of cellular resistance that affect the therapeutic response with an emphasis on the use of nanomaterials as a way of overriding cancer cell resistance. The resistance mechanisms that have been reported are complex and photosensitizer (PS)-specific. We conclude that altering the structure of PSs using nanotechnology is an ideal paradigm for enhancing PDT efficacy in the presence of cellular resistance.

SUBMITTER: Chizenga EP

PROVIDER: S-EPMC7407821 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Nanotechnology in Modern Photodynamic Therapy of Cancer: A Review of Cellular Resistance Patterns Affecting the Therapeutic Response.

Chizenga Elvin Peter EP Abrahamse Heidi H

Pharmaceutics 20200706 7

Photodynamic therapy (PDT) has emerged as a potential therapeutic option for most localized cancers. Its high measure of specificity and minimal risk of side effects compared to other therapies has put PDT on the forefront of cancer research in the current era. The primary cause of treatment failure and high mortality rates is the occurrence of cancer resistance to therapy. Hence, PDT is designed to be selective and tumor-specific. However, because of complex biological characteristics and cell ...[more]

PMID: 32640564

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Project description:Background: Hepatocellular carcinoma (HCC) is a prevalent malignancy with a high mortality rate. Cellular senescence, an irreversible state of cell cycle arrest, plays a paradoxical role in cancer progression. Here, we aimed to identify Hepatocellular carcinoma subtypes by cellular senescence-related genes (CSGs) and to construct a cellular senescence-related gene subtype predictor as well as a novel prognostic scoring system, which was expected to predict clinical outcomes and therapeutic response of Hepatocellular carcinoma. Methods: RNA-seq data and clinical information of Hepatocellular carcinoma patients were derived from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). The "multi-split" selection was used to screen the robust prognostic cellular senescence-related genes. Unsupervised clustering was performed to identify CSGs-related subtypes and a discriminant model was obtained through multiple statistical approaches. A CSGs-based prognostic model-CSGscore, was constructed by LASSO-Cox regression and stepwise regression. Immunophenoscore (IPS) and Tumor Immune Dysfunction and Exclusion (TIDE) were utilized to evaluate the immunotherapy response. Tumor stemness indices mRNAsi and mDNAsi were used to analyze the relationship between CSGscore and stemness. Results: 238 robust prognostic differentially expressed cellular senescence-related genes (DECSGs) were used to categorize all 336 hepatocellular carcinoma patients of the TCGA-LIHC cohort into two groups with different survival. Two hub genes, TOP2A and KIF11 were confirmed as key indicators and were used to form a precise and concise cellular senescence-related gene subtype predictor. Five genes (PSRC1, SOCS2, TMEM45A, CCT5, and STC2) were selected from the TCGA training dataset to construct the prognostic CSGscore signature, which could precisely predict the prognosis of hepatocellular carcinoma patients both in the training and validation datasets. Multivariate analysis verified it as an independent prognostic factor. Besides, CSGscore was also a valuable predictor of therapeutic responses in hepatocellular carcinoma. More downstream analysis revealed the signature genes were significantly associated with stemness and tumor progression. Conclusion: Two subtypes with divergent outcomes were identified by prognostic cellular senescence-related genes and based on that, a subtype indicator was established. Moreover, a prognostic CSGscore system was constructed to predict the survival outcomes and sensitivity of therapeutic responses in hepatocellular carcinoma, providing novel insight into hepatocellular carcinoma biomarkers investigation and design of tailored treatments depending on the molecular characteristics of individual patients.

Dataset Information

Nanotechnology in Modern Photodynamic Therapy of Cancer: A Review of Cellular Resistance Patterns Affecting the Therapeutic Response.

Publications

Nanotechnology in Modern Photodynamic Therapy of Cancer: A Review of Cellular Resistance Patterns Affecting the Therapeutic Response.

Similar Datasets

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