Current Cancer Therapy Reviews - Volume 21, Issue 3, 2025

Cancer is a highly perilous disease that can be fatal. While chemotherapy has been introduced as a treatment for cancer, it often comes with side effects and toxicities, making it less effective against cancer cells. In recent years, there has been a growing focus on innovative drug delivery systems to enhance the effectiveness and selectivity of chemotherapeutic drugs. In this context, researchers have developed a novel delivery system involving calixarene, which allows for lower drug concentrations and reduces side effects and toxicities. Calixarene and its derivatives are capable of encapsulating anticancer drugs, thereby enhancing the efficacy of chemotherapy. This approach improves the bioavailability, stability, solubility, and potency of the drug at its target site. This review provides a summary of recent research in the field of calixarene-based drug delivery systems, aiming to increase the effectiveness of anticancer treatments. It focuses on strategies involving the encapsulation of various anticancer drugs.

Breast cancer remains a significant global health challenge, necessitating innovative approaches to improve treatment efficacy while minimizing side effects. This review explores the promising advancements in breast cancer drug delivery driven by the transformative potential of bioinformatics and Artificial Intelligence (AI). Bioinformatics plays a pivotal role in unraveling the intricate genomic landscape of breast cancer, enabling the identification of potential drug targets and biomarkers. The integration of multi-omics data facilitates a comprehensive understanding of the disease, guiding personalized treatment strategies. Moreover, bioinformatics-driven approaches aid in biomarker discovery and prediction, offering novel tools for prognosis and treatment response assessment. AI, particularly machine learning and deep learning, has revolutionized breast cancer research. Machine learning models empower accurate diagnosis through image analysis, improve survival prediction, and enhance risk assessment. Deep learning algorithms, such as convolutional neural networks, enable precise tumor detection and classification from medical imaging data, notably mammograms and MRI scans. Additionally, natural language processing techniques facilitate the mining of vast scientific literature, uncovering hidden insights and identifying potential drug targets. Network-based approaches integrated with AI algorithms facilitate the identification of central proteins as promising drug targets within complex biological networks. This review also examines AI-optimized nanoformulations designed to enhance targeted drug delivery. AI-guided design of drug-loaded nanoparticles improves drug encapsulation efficiency, release kinetics, and site-specific delivery, offering promising solutions to overcome the challenges of conventional drug delivery.

In recent years, the applications of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) technology have revolutionized genetics and molecular biology. It has expanded beyond genetic editing to include innovative cancer treatment and nanotechnology approaches as a ground-breaking genome editing tool. It has emerged as a potent tool in the battle against cancer. By targeting and modifying specific genes associated with tumor development and growth, CRISPR offers a precise means of combating this devastating disease. Researchers are increasingly utilizing CRISPR to enhance cancer therapies, from boosting the efficacy of traditional treatments to developing novel immunotherapies. Simultaneously, nanotechnology, on the other hand, has opened up new avenues in diagnosing and treating cancer. Due to their unique physical properties, nanoparticles can be engineered for targeted drug delivery and imaging and even be used as vehicles for gene-editing tools like CRISPR. These nanoparticles can navigate the intricate biological environment, targeting cancer cells while minimizing collateral damage to healthy tissue. This precision is essential in reducing side effects and enhancing the therapeutic potential of anticancer agents. In this review, we emphasize the synergistic potential of CRISPR and nanotechnology, particularly in cancer treatment, highlighting their valuable role in advancing immunotherapy approaches. This nanotechnological perspective contributes significantly to the evolving landscape of research in this field.

New therapies for life-threatening ailments like breast carcinoma are urgently required to relieve the ever-increasing burden of the mortality associated with it. The very specific feature associated with life-giving natural products is their lesser toxicity concerning existing strategies viz chemotherapy or adjuvant modalities. In our review, we have tried to compile the existing data on exploring herbal extracts and bio-actives through various in vitro and in vivo techniques. An attempt has been made to accumulate data for a scrupulous literature review retrieved via pertinent keywords in authentic records. Web of Science, Scopus, and Science Direct. The major keywords included herbal extract, in vitro, anticancer, and metastasis. A comprehensive exploration unveiled an imperative role against malignancies of various tissues, but we focussed on breast cancer cell lines. Still, extensive reports on herbal alternatives and their bio-active mechanism are highly implicated in tapping their potential as standardized regimens. Scientific evidence, correlations, and proper safety data may substantiate interventions in cancer therapy.

Gliomas, a heterogeneous class of brain cancers, pose significant challenges as they are considered incurable. They represent the most recurrent primary intracranial cancer and exhibit distinct clinical and biological characteristics. Traditional treatment options for glioma include radiotherapy, chemotherapy, and surgery; however, the emergence of molecular-targeted therapy has provided a new avenue for improved therapeutic responses. One intriguing oncogene type of long non-coding RNAs (lncRNAs) in glioma is the HOX Transcript Antisense RNA, commonly referred to as HOTAIR. HOTAIR is characterized by its overexpression in various cancers and is situated in the intergenic region between HOXC12 and HOXC11 of the HOXC cluster on chromosome 12. Its upregulation in glioma has been found to be associated with tumor grade and plays a significant role in disease progression. HOTAIR exerts vital functions in glioma, including promoting angiogenesis, modulating glutamine catabolism, and influencing sensitivity to temozolomide (TMZ), a commonly used chemotherapy drug. Knockdown of HOTAIR has been shown to suppress cell invasion, migration, and proliferation, while inducing apoptosis, ultimately leading to tumor repression. HOTAIR achieves its biological effects, by targeting specific microRNAs (miRNAs). In this review study, we have summarized several signaling pathways that are intricately linked to HOTAIR in the context of glioma. Understanding the mechanisms and interactions involving HOTAIR and these signaling pathways may provide valuable insights for the development of targeted therapies and improved management strategies for glioma. This review provides a summary of the potential roles of HOTAIR in glioma, encompassing its effects in commercial cell lines, patient-derived cell lines, animal studies, and clinical trials.

As the third most prevalent cancer, there is no convincing treatment for colorectal cancer. Growth Hormone-releasing Hormone (GHRH) is an important hormone for the growth and maturity of humans and other animals. Also, recent studies show both GHRH and GHRH receptor to be expressed in many types of cancers, such as lung, breast, colon, ovarian, gastric, and pancreatic cancer. GHRH has been shown to augment the growth and proliferation of cancer cells in in vivo and in vitro studies, but studies have shown that its antagonist can inhibit the growth or even metastasis of cancer cells. The development of many classes of GHRH-R antagonists over the past three decades has shown strong in vivo and in vitro growth inhibitory effects on cancer. The present study is an attempt to review the studies on the association between GHRH and colorectal cancer and examine if the hormone can be targeted for therapy or used as a prognostic marker for colorectal cancer or not.

One common cancer among women is breast cancer. Chemotherapy, radiation therapy, and surgery have historically been used as breast cancer treatments. Thanks to recent technological advancements, we have been able to progressively comprehend the complexity and heterogeneity of diseases, which has led to the development of more effective treatments for many conditions. Working with variably shaped nanoparticles, nanotechnology has recently enabled us to work on tumor targeting and drug delivery, and it has undoubtedly helped to reduce the spread and death of breast cancer. The efficacy of treatment for breast cancer can be increased by a variety of target therapies made possible by nanotechnology. The current review discusses the advantages and disadvantages of nanotechnology-based therapy for breast cancer while also highlighting the disease's current state. The article will provide an overview of the current strategy available for better treatment of breast cancer and aid in understanding the various drug delivery systems designed to provide effective treatment for the disease. By utilizing cutting-edge technologies and early screening, breast cancer fatalities can be decreased. Drug delivery methods based on nano carriers enable medication to reach the target site at the ideal concentration with the least amount of harmful side effects.

Polymers are the mainstay of drug delivery systems. They may be natural, semisynthetic, or synthetic and used to program the release of drugs as per requirement. They are used to enhance the bioavailability and hence solubility, stability, and site specificity, or to release to drug either in a controlled, pulsatile, sustained, immediate release pattern. In the present review, we have discussed the recent prose and patents of poly(lactic-co-glycolic acid) and PLGA applicability in preparing formulations against cancer. Synthetic polymer, PLGA comprises monomers of glycolide and lactide available in various grades with varying physicochemical properties thus serving the formulators to fabricate preparations having designed release patterns. In this review, current literature and patents of poly(lactic-co-glycolic acid); PLGA using anticancer preparations have been covered. PLGA has demonstrated its potential as a polymer to program the release of drugs as a coating polymer and the development of a matrix in various drug delivery systems. It can augment the bioavailability of the drug reducing the toxicity/side effects and delivering the drug at the target site. The potential of PLGA to transfer the drug may unclutter novel ways for therapeutic interventions in various tumors.

Since breast cancer affects one in every four women, it is an utmost need to investigate novel diagnostic technologies and treatment techniques. This requires the development of diagnostic techniques to simplify the identification of cancer cells, which can facilitate cancer therapy. One of the most significant obstacles in chemotherapy is the absence of technologies that can measure its effectiveness while it is being administered. Additionally, due to its steadily expanding prevalence and mortality rate, cancer has surpassed AIDS as the world's second leading cause of death. Breast cancer accounts for a disproportionately high number of cancer-related deaths among women worldwide, making precise, sensitive imaging a necessity for this disease. Breast cancer can be successfully treated if it is diagnosed early. As an alternate strategy, the use of cutting-edge computational methodologies has been advocated for developing innovative breast cancer diagnostic imaging techniques. The following article provides an overview of the traditional diagnostic procedures that have historically been employed for the detection of breast carcinoma, as well as the current methods that are being utilized. Furthermore, a comprehensive overview of various mathematical frameworks is provided, including machine learning, deep learning, artificial neural networks, and robotics, highlighting their progress and potential applications in the field of breast cancer diagnostic imaging.

Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized various industries, including cancer research and drug discovery. This article provides a summary of the history of AI and ML, highlighting their resurgence in the 1990s with advancements in computational power and new algorithms. In the context of drug discovery, AI and ML techniques have been applied to accelerate the development of new drugs, from target identification and lead generation to drug repurposing. AI applications in drug design and virtual screening have improved the efficiency of identifying potential drug candidates. Deep learning, a division of ML, has been particularly effective in predicting protein structures and optimizing lead compounds. In anti-cancer drug target prediction, AI and ML algorithms analyze large-scale genomic, proteomic, and clinical data to identify potential targets for cancer therapy. AI has also transformed cancer imaging and diagnosis by enhancing the accuracy and efficiency of cancer detection, classification, and prognosis. Medical imaging analysis, pathology, and radiology have benefited from AI algorithms’ ability to interpret and analyze various imaging modalities. Moreover, AI applications in cancer treatment have facilitated the development of predictive models for treatment response, enabling personalized and targeted therapies based on individual patient characteristics. The purpose of the study was to provide facts regarding the integration of artificial intelligence and machine learning in drug discovery and cancer therapy and their significant prospects for improving efficiency, decreasing costs, and improving patient outcomes.

Cancer is still a significant worldwide health issue that requires novel techniques for diagnosis and treatment. The complications associated with cancer are explored in this article, which also introduces the novel concept of biomimetic nanoparticles as potential breakthrough in the fight against the disease. The introduction gives a general review of cancer, explaining its complexity and the underlying mechanisms that give rise to it. Epidemiological findings highlight the impact of cancer on the entire world and the most extensively found cancer driving the demand for innovative therapeutic approaches. A comprehensive review of the various cancer types follows with emphasis on unique traits, diagnostic methods, and treatment modalities, highlighting the variety of difficulties. An achievable path forward for targeted cancer therapy is the emerging science of biomimetic nanoparticles. A thorough review of their many varieties and applications follows their introduction. These nanoparticles’ inventive nature, which was inspired by biological systems, is highlighted by the explanation of how they were synthesized. The focus is on biomimetic nanoparticles based on cancer cell membranes as a novel means of medication administration and targeted therapy. Their use in the treatment of cancer is being investigated, with an emphasis on their potential to improve therapeutic efficacy and lessen side effects. Particularly noteworthy are the in-depth discussions of the unique difficulties encountered in treating lung, breast, prostate, colon, colorectal, ovarian, leukemia, lymphoma, melanoma, pancreatic, bladder, oral, gastric, hepatic, perihilar cholangiocarcinoma, and cervical cancers. The article also mentions the various challenges which may occur during this entire process.

Since the beginning of the 21st century, there have been significant advancements in the field of cancer treatment, resulting in markedly improved outcomes for patients. This review provides an updated view of some recently developed and FDA-approved small molecules that have been used to treat various types of cancer on different indications and targets. Some popular search engines, such as Pubmed, Google Scholar, etc., were considered for the literature review, and drugs approved by the FDA from 2019 to 2023 were considered for study in this review. This review focuses on the mechanism of actions and targets via which these FDA-approved small molecules could demonstrate their clinical efficacy. Moreover, this review would pave the way for the scientific community to look into the chemical structures of these small molecules to discover more small synthetic compounds after modification based on structural activity that might be useful in treating various types of cancer. However, much attention is being paid to how new therapies and tools will change how cancer is treated in the coming years. This review indicated the increased rate of approvals by the FDA for oncology treatment during 2019-2023. This surge is primarily driven by the approval of targeted therapies and the introduction of novel therapeutic approaches.