Tumors have evolved in various mechanisms to evade the immune system, hindering the antitumor immune response and facilitating tumor progression. Immunotherapy has become a potential treatment strategy specific to different cancer types by utilizing multifarious molecular mechanisms to enhance the immune response against tumors. Among these mechanisms, the ubiquitin-proteasome system (UPS) is a significant non-lysosomal pathway specific to protein degradation, regulated by deubiquitinating enzymes (DUBs) that counterbalance ubiquitin signaling. Ubiquitin-specific proteases (USPs), the largest DUB family with the strongest variety, play critical roles in modulating immune cell function, regulating immune response, and participating in antigen processing and presentation during tumor progression. According to recent studies, the expressions of some USP family members in tumor cells are involved in tumor immune escape and immune microenvironment. This review explores the potential of targeting USPs as a new approach for cancer immunotherapy, highlighting recent basic and preclinical studies investigating the applications of USP inhibitors. By providing insights into the structure and function of USPs in cancer immunity, this review aims at assisting in developing new therapeutic approaches for enhancing the immunotherapy efficacy. 

Targeting ubiquitin specific proteases (USPs) in cancer immunotherapy: from basic research to preclinical application

Programmed death ligand 1 (PD‐L1) has been demonstrated to facilitate tumor progression and therapeutic resistance in an immune‐independent manner. Nevertheless, the function and underlying signaling network(s) of cancer cell‐intrinsic PD‐L1 action remain largely unknown. Herein, we sought to better understand how ubiquitin‐specific peptidase 51 (USP51)/PD‐L1/integrin beta‐1 (ITGB1) signaling performs a cell‐intrinsic role in mediating chemotherapeutic resistance in non‐small cell lung cancer (NSCLC).

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/cac2.12460

USP51/PD‐L1/ITGB1‐deployed juxtacrine interaction plays a cell‐intrinsic role in promoting chemoresistant phenotypes in non‐small cell lung cancer

Cancer is considered a leading cause of mortality. This rising cancer death rate and several existing limitations like side effects, poor efficacies, and high cost of the present chemotherapeutic agents have increased the demand for more potent and alternative cancer treatments. This review elucidated a brief overview of Biochanin A (BCA) and its potentiality on various cancers with details of anticancer mechanism. According to our review, a number of studies including in silico, in vitro, pre‐clinical, and clinical trials have tested to evaluate the efficacy of BCA. This compound is effective against 15 types of cancer, including breast, cervical, colorectal, gastric, glioblastoma, liver, lung, melanoma, oral, osteosarcoma, ovarian, pancreatic, pharynx, prostate, and umbilical vein cancer. The general anticancer activities of this compound are mediated via several molecular processes, including regulation of apoptosis, cell proliferation, metastasis and angiogenesis, signaling, enzymatic pathways, and other mechanisms. Targeting both therapeutic and oncogenic proteins, as well as different pathways, makes up the molecular mechanism underlying the anticancer action. Many signaling networks and their components, such as EFGR, PI3K/Akt/mTOR, MAPK, MMP‐2, MMP‐9, PARP, Caspase‐3/8/9, Bax, Bcl2, PDL‐1, NF‐κB, TNF‐α, IL‐6, JAK, STAT3, VEGFR, VEGF, c‐MY, Cyclin B1, D1, E1 and CDKs, Snail, and E‐cadherin proteins, can be regulated in cancer cells by BCA. Such kind of anticancer properties of BCA could be a result of its correct structural chemistry. The use of BCA‐based therapies as nano‐carriers for the delivery of chemotherapeutic medicines has the potential to be very effective. This natural compound synergises with other natural compounds and standard drugs, including sorafenib, 5‐fluorouracil, temozolomide, doxorubicin, apigenin, and genistein. Moreover, proper use of this compound can reverse multidrug resistance through numerous mechanisms. BCA has better drug‐likeness and pharmacokinetic properties and is nontoxic (eye, liver, kidney, skin, cardio) in human bodies. As having a wide range of cancer‐fighting mechanisms, synergistic effects, and good pharmacokinetic properties, BCA can be used as a supplementary food until standard drugs are available at pharma markets.

Comprehensive exploration of Biochanin A as an oncotherapeutics potential in the treatment of multivarious cancers with molecular insights.

Lung adenocarcinoma represents a significant global health challenge. Despite advances in diagnosis and treatment, the prognosis remains poor for many patients. In this study, we aimed to identify cuproptosis-related genes and to develop a deep neural network model to predict the prognosis of lung adenocarcinoma. We screened differentially expressed genes from The Cancer Genome Atlas data through differential analysis of cuproptosis-related genes. We then used this information to establish a prognostic model using a deep neural network, which we validated using data from the Gene Expression Omnibus. Our deep neural network model incorporated nine cuproptosis-related genes and achieved an area under the curve of 0.732 in the training set and 0.646 in the validation set. The model effectively distinguished between distinct risk groups, as evidenced by significant differences in survival curves (p < 0.001), and demonstrated significant independence as a standalone prognostic predictor (p < 0.001). Functional analysis revealed differences in cellular pathways, the immune microenvironment, and tumor mutation burden between the risk groups. Furthermore, our model provided personalized survival probability predictions with a concordance index of 0.795 and identified the drug candidate BMS-754807 as a potentially sensitive treatment option for lung adenocarcinoma. In summary, we presented a deep neural network prognostic model for lung adenocarcinoma, based on nine cuproptosis-related genes, which offers independent prognostic capabilities. This model can be used for personalized predictions of patient survival and the identification of potential therapeutic agents for lung adenocarcinoma, which may ultimately improve patient outcomes.

/pdf/a-deep-learning-approach-for-prognostic-evaluation-of-lung-211mnv9r.pdf

A Deep Learning Approach for Prognostic Evaluation of Lung Adenocarcinoma Based on Cuproptosis-Related Genes

Abstract The interaction between programmed cell death ligand 1 (PD-L1), which is expressed on the surface of tumor cells, and programmed cell death 1 (PD-1), which is expressed on T cells, impedes the effective activation of tumor antigen-specific T cells, resulting in the evasion of tumor cells from immune-mediated killing. Blocking the PD-1/PD-L1 signaling pathway has been shown to be effective in preventing tumor immune evasion. PD-1/PD-L1 blocking antibodies have garnered significant attention in recent years within the field of tumor treatments, given the aforementioned mechanism. Furthermore, clinical research has substantiated the efficacy and safety of this immunotherapy across various tumors, offering renewed optimism for patients. However, challenges persist in anti-PD-1/PD-L1 therapies, marked by limited indications and the emergence of drug resistance. Consequently, identifying additional regulatory pathways and molecules associated with PD-1/PD-L1 and implementing judicious combined treatments are imperative for addressing the intricacies of tumor immune mechanisms. This review briefly outlines the structure of the PD-1/PD-L1 molecule, emphasizing the posttranslational modification regulatory mechanisms and related targets. Additionally, a comprehensive overview on the clinical research landscape concerning PD-1/PD-L1 post-translational modifications combined with PD-1/PD-L1 blocking antibodies to enhance outcomes for a broader spectrum of patients is presented based on foundational research. 

Emerging therapeutic frontiers in cancer: insights into posttranslational modifications of PD-1/PD-L1 and regulatory pathways

Abstract Lung adenocarcinoma is the major subtype of lung cancer, accounting for approximately 40% of lung cancers. During clinical treatment, the emergence of chemotherapy resistance seriously affects the effectiveness of treatment. Thus, finding new chemotherapeutic sensitizers is considered to be one of the effective solutions. Biochanin A, as a naturally occurring isoflavone, has been demonstrated to exhibit anticancer effects in various tumors. However, the potential mechanisms of Biochanin A to inhibit tumor development have not been clarified. In the present study, we found that the combinational treatment of cisplatin and Biochanin A exhibited strong synergistic repression on lung adenocarcinoma growth and progression in vitro and in vivo. Considering that epithelial–mesenchymal transition (EMT) is recognized to be associated with both chemoresistance and metastasis, we examined the EMT-related markers and found that Biochanin A could specifically inhibit the expression of ZEB1. Importantly, Biochanin A chemosensitizes lung adenocarcinoma and inhibits cancer cell metastasis by suppressing ZEB1. At the molecular level, Biochanin A affects the stability of ZEB1 protein through the deubiquitination pathway and thereby influences the progression of lung adenocarcinoma. In conclusion, our finding elucidates the potential efficacy of Bichanin A as a chemosensitizer and provides new strategy for the chemotherapy of advanced lung adenocarcinoma. 

/pdf/biochanin-a-inhibits-lung-adenocarcinoma-progression-by-3ug0bz3h.pdf

Biochanin A inhibits lung adenocarcinoma progression by targeting ZEB1

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USP51/PD‐L1/ITGB1‐deployed juxtacrine interaction plays a cell‐intrinsic role in promoting chemoresistant phenotypes in non‐small cell lung cancer

Biochanin A inhibits lung adenocarcinoma progression by targeting ZEB1