Proteomics, Personalized Medicine and Cancer

Diagnostic use of circulating cells and sub-cellular bio-particles

In the bloodstream or other physiological fluids, "circulating cells and sub-cellular bio-particles" include many microscopic biological elements such as circulating tumor cells (CTCs), cell-free DNA (cfDNA), exosomes, microRNAs, platelets, immune cells, and proteins are the most well-known and investigated. These structures are crucial biomarkers in healthcare and medical research for the early detection of cancer and other disorders, enabling treatment to commence before the onset of clinical symptoms and enhancing the efficacy of treatments. As the size of these biomarkers to be detected decreases and their numbers in body fluids diminishes, the detection materials, ranging from visual inspection to advanced microscopy techniques, begin to become smaller, more sensitive, faster, and more effective, thanks to developing nanotechnology. This review first defines the circulating cells and subcellular bio-particles with their biological, physical, and mechanical properties and second focuses on their diagnostic importance, including their most recent applications as biomarkers, the biosensors that are utilized to detect them, the present obstacles that must be surmounted, and prospective developments in the domain. As technology advances and biomolecular pathways are deepens, diagnostic tests will become more sensitive, specific, and thorough. Finally, integrating recent advances in the diagnostic use of circulating cells and bioparticles into clinical practice is promising for precision medicine and patient outcomes.

Radiomolecular Theranostics With Fibroblast-Activation-Protein Inhibitors and Peptides

The advancement of theranostics, which combines therapeutic and diagnostic capabilities in oncology, has significantly impacted cancer management. This review explores fibroblast activation protein (FAP) expression in the tumor microenvironment (TME) and its association with various malignancies, highlighting its potential as a theranostic marker for PET/CT imaging using FAP-targeted tracers and for FAP-targeted radiopharmaceutical therapy. We examine the development and clinical applications of FAP inhibitors (FAPIs) and peptides, providing insights into their diagnostic accuracy, initial therapeutic efficacy, and clinical impact across diverse cancer types, as well as the synthesis of novel FAP-targeted ligands. This review aims to showcase the promising outcomes and challenges in integrating FAP-targeted approaches into cancer management.

Exploring novel protein-based biomarkers for advancing breast cancer diagnosis: A review

This review provides a contemporary examination of the evolving landscape of breast cancer (BC) diagnosis, focusing on the pivotal role of novel protein-based biomarkers. The overview begins by elucidating the multifaceted nature of BC, exploring its prevalence, subtypes, and clinical complexities. A critical emphasis is placed on the transformative impact of proteomics, dissecting the proteome to unravel the molecular intricacies of BC. Navigating through various sources of samples crucial for biomarker investigations, the review underscores the significance of robust sample processing methods and their validation in ensuring reliable outcomes. The central theme of the review revolves around the identification and evaluation of novel protein-based biomarkers. Cutting-edge discoveries are summarised, shedding light on emerging biomarkers poised for clinical application. Nevertheless, the review candidly addresses the challenges inherent in biomarker discovery, including issues of standardisation, reproducibility, and the complex heterogeneity of BC. The future direction section envisions innovative strategies and technologies to overcome existing challenges. In conclusion, the review summarises the current state of BC biomarker research, offering insights into the intricacies of proteomic investigations. As precision medicine gains momentum, the integration of novel protein-based biomarkers emerges as a promising avenue for enhancing the accuracy and efficacy of BC diagnosis. This review serves as a compass for researchers and clinicians navigating the evolving landscape of BC biomarker discovery, guiding them toward transformative advancements in diagnostic precision and personalised patient care.

Peptosome: A New Efficient Transfection Tool as an Alternative to Liposome

Gene therapy is one of the most promising techniques for treating genetic diseases and cancer. The current most important problem in gene therapy is gene delivery. Viral and non-viral vectors like liposomes, used for gene delivery, have many limitations. We have developed new hybrid peptides by combining cell-penetrating peptides (CPPs) with the DNA-binding domain of the human histone H4 protein. These small peptides bind to DNA molecules through their histone domain, leaving the CPP part free and available for binding and penetration into cells, forming complexes that we named "peptosomes". We evaluated the transfection efficiency of several hybrid peptides by delivering a plasmid carrying the green fluorescent protein gene and following its expression by fluorescent microscopy. Among several hybrid peptides, TM3 achieved a gene delivery efficiency of 76%, compared to 52% for Lipofectamine 2000. TM3 peptosomes may become important gene delivery tools with several advantages over current gene delivery agents.

Deguelin Restores Paclitaxel Sensitivity in Paclitaxel-Resistant Ovarian Cancer Cells via Inhibition of the EGFR Signaling Pathway

Background

Ovarian cancer is one of women's malignancies with the highest mortality among gynecological cancers. Paclitaxel is used in first-line ovarian cancer chemotherapy. Research on paclitaxel-resistant ovarian cancer holds significant clinical importance.

Methods

Cell viability and flow cytometric assays were conducted at different time and concentration points of deguelin and paclitaxel treatment. Immunoblotting was performed to assess the activation status of key signaling molecules important for cell survival and proliferation following treatment with deguelin and paclitaxel. The fluo-3 acetoxymethyl assay for P-glycoprotein transport activity assay and cell viability assay in the presence of N-acetyl-L-cysteine were also conducted.

Results

Cell viability and flow cytometric assays demonstrated that deguelin resensitized paclitaxel in a dose- and time-dependent manner. Cotreatment with deguelin and paclitaxel inhibited EGFR and its downstream signaling molecules, including AKT, ERK, STAT3, and p38 MAPK, in SKOV3-TR cells. Interestingly, cotreatment with deguelin and paclitaxel suppressed the expression level of EGFR via the lysosomal degradation pathway. Cotreatment did not affect the expression and function of P-glycoprotein. N-acetyl-L-cysteine failed to restore cell cytotoxicity when used in combination with deguelin and paclitaxel in SKOV3-TR cells. The expression of BCL-2, MCL-1, and the phosphorylation of the S155 residue of BAD were downregulated. Moreover, inhibition of paclitaxel resistance by deguelin was also observed in HeyA8-MDR cells.

Conclusion

Our research showed that deguelin effectively suppresses paclitaxel resistance in SKOV3-TR ovarian cancer cells by downregulating the EGFR and its downstream signaling pathway and modulating the BCL-2 family proteins. Furthermore, deguelin exhibits inhibitory effects on paclitaxel resistance in HeyA8-MDR ovarian cancer cells, suggesting a potential mechanism for paclitaxel resensitization that may not be cell-specific. These findings suggest that deguelin holds promise as an anticancer therapeutic agent for overcoming chemoresistance in ovarian cancer.

Current trends in clinical trials and the development of small molecule epigenetic inhibitors as cancer therapeutics

Epigenetic mechanisms control and regulate normal chromatin structure and gene expression patterns, with epigenetic dysregulation observed in many different cancer types. Importantly, epigenetic modifications are reversible, offering the potential to silence oncogenes and reactivate tumor suppressors. Small molecule drugs manipulating these epigenetic mechanisms are at the leading edge of new therapeutic options for cancer treatment. The clinical use of histone deacetyltransferases inhibitors (HDACi) demonstrates the effectiveness of targeting epigenetic mechanisms for cancer treatment. Notably, the development of new classes of inhibitors, including lysine acetyltransferase inhibitors (KATi), are the future of epigenetic-based therapeutics. We outline the progress of current classes of small molecule epigenetic drugs for use against cancer (preclinical and clinical) and highlight the potential market growth in epigenetic-based therapeutics.

Review of Personalized Medicine and Pharmacogenomics of Anti-Cancer Compounds and Natural Products

In recent years, the FDA has approved numerous anti-cancer drugs that are mutation-based for clinical use. These drugs have improved the precision of treatment and reduced adverse effects and side effects. Personalized therapy is a prominent and hot topic of current medicine and also represents the future direction of development. With the continuous advancements in gene sequencing and high-throughput screening, research and development strategies for personalized clinical drugs have developed rapidly. This review elaborates the recent personalized treatment strategies, which include artificial intelligence, multi-omics analysis, chemical proteomics, and computation-aided drug design. These technologies rely on the molecular classification of diseases, the global signaling network within organisms, and new models for all targets, which significantly support the development of personalized medicine. Meanwhile, we summarize chemical drugs, such as lorlatinib, osimertinib, and other natural products, that deliver personalized therapeutic effects based on genetic mutations. This review also highlights potential challenges in interpreting genetic mutations and combining drugs, while providing new ideas for the development of personalized medicine and pharmacogenomics in cancer study.

Molecular World Today and Tomorrow: Recent Trends in Biological Sciences 2.0

Molecular techniques have become influential instruments in biological study, transforming our comprehension of life at the cellular and genetic levels [...].

Recent developments in mass-spectrometry-based targeted proteomics of clinical cancer biomarkers

Routine measurement of cancer biomarkers is performed for early detection, risk classification, and treatment monitoring, among other applications, and has substantially contributed to better clinical outcomes for patients. However, there remains an unmet need for clinically validated assays of cancer protein biomarkers. Protein tumor markers are of particular interest since proteins carry out the majority of biological processes and thus dynamically reflect changes in cancer pathophysiology. Mass spectrometry-based targeted proteomics is a powerful tool for absolute peptide and protein quantification in biological matrices with numerous advantages that make it attractive for clinical applications in oncology. The use of liquid chromatography-tandem mass spectrometry (LC-MS/MS) based methodologies has allowed laboratories to overcome challenges associated with immunoassays that are more widely used for tumor marker measurements. Yet, clinical implementation of targeted proteomics methodologies has so far been limited to a few cancer markers. This is due to numerous challenges associated with paucity of robust validation studies of new biomarkers and the labor-intensive and operationally complex nature of LC-MS/MS workflows. The purpose of this review is to provide an overview of targeted proteomics applications in cancer, workflows used in targeted proteomics, and requirements for clinical validation and implementation of targeted proteomics assays. We will also discuss advantages and challenges of targeted MS-based proteomics assays for clinical cancer biomarker analysis and highlight some recent developments that will positively contribute to the implementation of this technique into clinical laboratories.

Overcoming Microbiome-Acquired Gemcitabine Resistance in Pancreatic Ductal Adenocarcinoma

Gastrointestinal cancers (GICs) are one of the most recurrent diseases in the world. Among all GICs, pancreatic cancer (PC) is one of the deadliest and continues to disrupt people's lives worldwide. The most frequent pancreatic cancer type is pancreatic ductal adenocarcinoma (PDAC), representing 90 to 95% of all pancreatic malignancies. PC is one of the cancers with the worst prognoses due to its non-specific symptoms that lead to a late diagnosis, but also due to the high resistance it develops to anticancer drugs. Gemcitabine is a standard treatment option for PDAC, however, resistance to this anticancer drug develops very fast. The microbiome was recently classified as a cancer hallmark and has emerged in several studies detailing how it promotes drug resistance. However, this area of study still has seen very little development, and more answers will help in developing personalized medicine. PC is one of the cancers with the highest mortality rates; therefore, it is crucial to explore how the microbiome may mold the response to reference drugs used in PDAC, such as gemcitabine. In this article, we provide a review of what has already been investigated regarding the impact that the microbiome has on the development of PDAC in terms of its effect on the gemcitabine pathway, which may influence the response to gemcitabine. Therapeutic advances in this type of GIC could bring innovative solutions and more effective therapeutic strategies for other types of GIC, such as colorectal cancer (CRC), due to its close relation with the microbiome.

Salivary glands adenoid cystic carcinoma: a molecular profile update and potential implications

Adenoid cystic carcinoma (ACC) is an aggressive tumor with a high propensity for distant metastasis and perineural invasion. This tumor is more commonly found in regions of the head and neck, mainly the salivary glands. In general, the primary treatment modality for ACC is surgical resection and, in some cases, postoperative radiotherapy. However, no effective systemic treatment is available for patients with advanced disease. Furthermore, this tumor type is characterized by recurrent molecular alterations, especially rearrangements involving the MYB, MYBL1, and NFIB genes. In addition, they also reported copy number alterations (CNAs) that impact genes. One of them is C-KIT, mutations that affect signaling pathways such as NOTCH, PI3KCA, and PTEN, as well as alterations in chromatin remodeling genes. The identification of new molecular targets enables the development of specific therapies. Despite ongoing investigations into immunotherapy, tyrosine kinase inhibitors, and anti-angiogenics, no systemic therapy is approved by the FDA for ACC. In this review, we report the genetic and cytogenetic findings on head and neck ACC, highlighting possible targets for therapeutic interventions.

The 2022 Report on the Human Proteome from the HUPO Human Proteome Project

The 2022 Metrics of the Human Proteome from the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 407 (93.2%) of the 19 750 predicted proteins coded in the human genome, a net gain of 50 since 2021 from data sets generated around the world and reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 78 from 1421 to 1343. This represents continuing experimental progress on the human proteome parts list across all the chromosomes, as well as significant reclassifications. Meanwhile, applying proteomics in a vast array of biological and clinical studies continues to yield significant findings and growing integration with other omics platforms. We present highlights from the Chromosome-Centric HPP, Biology and Disease-driven HPP, and HPP Resource Pillars, compare features of mass spectrometry and Olink and Somalogic platforms, note the emergence of translation products from ribosome profiling of small open reading frames, and discuss the launch of the initial HPP Grand Challenge Project, "A Function for Each Protein".

Signaling pathways of oxidative stress response: the potential therapeutic targets in gastric cancer

Gastric cancer is one of the top causes of cancer-related death globally. Although novel treatment strategies have been developed, attempts to eradicate gastric cancer have been proven insufficient. Oxidative stress is continually produced and continually present in the human body. Increasing evidences show that oxidative stress contributes significantly to the development of gastric cancer, either through initiation, promotion, and progression of cancer cells or causing cell death. As a result, the purpose of this article is to review the role of oxidative stress response and the subsequent signaling pathways as well as potential oxidative stress-related therapeutic targets in gastric cancer. Understanding the pathophysiology of gastric cancer and developing new therapies for gastric cancer depends on more researches focusing on the potential contributors to oxidative stress and gastric carcinogenesis.

Artificial intelligence-based multi-omics analysis fuels cancer precision medicine

With biotechnological advancements, innovative omics technologies are constantly emerging that have enabled researchers to access multi-layer information from the genome, epigenome, transcriptome, proteome, metabolome, and more. A wealth of omics technologies, including bulk and single-cell omics approaches, have empowered to characterize different molecular layers at unprecedented scale and resolution, providing a holistic view of tumor behavior. Multi-omics analysis allows systematic interrogation of various molecular information at each biological layer while posing tricky challenges regarding how to extract valuable insights from the exponentially increasing amount of multi-omics data. Therefore, efficient algorithms are needed to reduce the dimensionality of the data while simultaneously dissecting the mysteries behind the complex biological processes of cancer. Artificial intelligence has demonstrated the ability to analyze complementary multi-modal data streams within the oncology realm. The coincident development of multi-omics technologies and artificial intelligence algorithms has fuelled the development of cancer precision medicine. Here, we present state-of-the-art omics technologies and outline a roadmap of multi-omics integration analysis using an artificial intelligence strategy. The advances made using artificial intelligence-based multi-omics approaches are described, especially concerning early cancer screening, diagnosis, response assessment, and prognosis prediction. Finally, we discuss the challenges faced in multi-omics analysis, along with tentative future trends in this field. With the increasing application of artificial intelligence in multi-omics analysis, we anticipate a shifting paradigm in precision medicine becoming driven by artificial intelligence-based multi-omics technologies.

Clinical applications of plasma proteomics and peptidomics: Towards precision medicine

In the context of precision medicine, disease treatment requires individualized strategies based on the underlying molecular characteristics to overcome therapeutic challenges posed by heterogeneity. For this purpose, it is essential to develop new biomarkers to diagnose, stratify, or possibly prevent diseases. Plasma is an available source of biomarkers that greatly reflects the physiological and pathological conditions of the body. An increasing number of studies are focusing on proteins and peptides, including many involving the Human Proteome Project (HPP) of the Human Proteome Organization (HUPO), and proteomics and peptidomics techniques are emerging as critical tools for developing novel precision medicine preventative measures. Excitingly, the emerging plasma proteomics and peptidomics toolbox exhibits a huge potential for studying pathogenesis of diseases (e.g., COVID-19 and cancer), identifying valuable biomarkers and improving clinical management. However, the enormous complexity and wide dynamic range of plasma proteins makes plasma proteome profiling challenging. Herein, we summarize the recent advances in plasma proteomics and peptidomics with a focus on their emerging roles in COVID-19 and cancer research, aiming to emphasize the significance of plasma proteomics and peptidomics in clinical applications and precision medicine.

Computational Screening of Anti-Cancer Drugs Identifies a New BRCA Independent Gene Expression Signature to Predict Breast Cancer Sensitivity to Cisplatin

Simple Summary

Using a collection of publicly available drug screening resources, we identified different partners of genes associated with either sensitivity or resistance to 90 anti-cancer therapies. When subsequently applying these signatures to multiple datasets, we found that these predictive models could predict a large range of drug responses in patient samples. In particular, we discovered a new gene signature to identify breast cancer tumors that are likely to respond to cisplatin in the absence of BRCA1 mutations. This work constitutes an important advance to accelerate the application of platinum-based therapies in patient groups that are not routinely treated with these drugs. In the future, this approach may help to guide the choice of drugs based on the molecular profile of the tumors.

Abstract

The development of therapies that target specific disease subtypes has dramatically improved outcomes for patients with breast cancer. However, survival gains have not been uniform across patients, even within a given molecular subtype. Large collections of publicly available drug screening data matched with transcriptomic measurements have facilitated the development of computational models that predict response to therapy. Here, we generated a series of predictive gene signatures to estimate the sensitivity of breast cancer samples to 90 drugs, comprising FDA-approved drugs or compounds in early development. To achieve this, we used a cell line-based drug screen with matched transcriptomic data to derive in silico models that we validated in large independent datasets obtained from cell lines and patient-derived xenograft (PDX) models. Robust computational signatures were obtained for 28 drugs and used to predict drug efficacy in a set of PDX models. We found that our signature for cisplatin can be used to identify tumors that are likely to respond to this drug, even in absence of the BRCA-1 mutation routinely used to select patients for platinum-based therapies. This clinically relevant observation was confirmed in multiple PDXs. Our study foreshadows an effective delivery approach for precision medicine.

Application of two-dimensional difference gel electrophoresis to identify protein changes between center, margin, and adjacent non-tumor tissues obtained from non-small-cell lung cancer with adenocarcinoma or squamous cell carcinoma subtype

Lung cancer is responsible for the most cancer-related mortality worldwide and the mechanism of its development is poorly understood. Proteomics has become a powerful tool offering vital knowledge related to cancer development. Using a two-dimensional difference gel electrophoresis (2D-DIGE) approach, we sought to compare tissue samples from non-small-cell lung cancer (NSCLC) patients taken from the tumor center and tumor margin. Two subtypes of NSCLC, adenocarcinoma (ADC) and squamous cell carcinoma (SCC) were compared. Data are available via ProteomeXchange with identifier PXD032736 and PXD032962 for ADC and SCC, respectively. For ADC proteins, 26 significant canonical pathways were identified, including Rho signaling pathways, a semaphorin neuronal repulsive signaling pathway, and epithelial adherens junction signaling. For SCC proteins, nine significant canonical pathways were identified, including hypoxia-inducible factor-1α signaling, thyroid hormone biosynthesis, and phagosome maturation. Proteins differentiating the tumor center and tumor margin were linked to cancer invasion and progression, including cell migration, adhesion and invasion, cytoskeletal structure, protein folding, anaerobic metabolism, tumor angiogenesis, EMC transition, epithelial adherens junctions, and inflammatory responses. In conclusion, we identified several proteins that are important for the better characterization of tumor development and molecular specificity of both lung cancer subtypes. We also identified proteins that may be important as biomarkers and/or targets for anticancer therapy.

Nanoengineering a metal-organic framework for osteosarcoma chemo-immunotherapy by modulating indoleamine-2,3-dioxygenase and myeloid-derived suppressor cells

Background

The high postoperative recurrence rate and refractoriness of relapsed tumors are still a conundrum for the clinical management of osteosarcoma (OS). New therapeutic options are urgently needed. Depriving the nourishment of myeloid-derived suppressor cells is a novel strategy to improve the immunosuppressive tumor microenvironment for enhanced OS therapy.

Methods

We synthesized a hyaluronic acid (HA)-modified metal–organic framework for combinational chemotherapy and immunotherapy of OS. Zeolitic Imidazolate Framework-8 (ZIF-8) was prepared by a one-pot synthetic method, Gemcitabine (Gem) and D-1-Methyltryptophan (D-1-MT) were loaded into the ZIF-8 during the synthesis process to make ZIF-8@Gem/D-1-MT nanoparticles (NPs). The end product (HA/ZIF-8@Gem/D-1-MT NPs) was obtained by HA modification on the surface of ZIF-8@Gem/D-1-MT NPs. The obtained HA/ZIF-8@Gem/D-1-MT NPs have excellent potential as a drug delivery vector for chemotherapy and immunotherapy in vitro and vivo.

Results

The results indicate that HA/ZIF-8@Gem/D-1-MT NPs were readily taken up by OS cells, and that the Gem and D-1-MT were effectively released into the acidic environment. The HA/ZIF-8@Gem/D-1-MT NPs could efficiently decrease OS cell viability (proliferation, apoptosis, cell cycle, migration and invasion). And HA/ZIF-8@Gem/D-1-MT NPs could reactivate antitumor immunity by inhibiting indoleamine 2,3 dioxygenase and myeloid-derived suppressor cells. Furthermore, animal experiments confirmed that HA/ZIF-8@Gem/D-1-MT NPs could induce intratumoral immune responses and inhibit tumor growth. Additionally, HA/ZIF-8@Gem/D-1-MT NPs have a good safety profile.

Conclusions

Our findings demonstrate that the combination of Gem with D-1-MT brings new hope for the improved treatment of OS, while the generation of the nanosystem has increased the application potential and flexibility of this strategy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02372-8.

Multi-omics strategies for personalized and predictive medicine: past, current, and future translational opportunities

Precision medicine is driven by the paradigm shift of empowering clinicians to predict the most appropriate course of action for patients with complex diseases and improve routine medical and public health practice. It promotes integrating collective and individualized clinical data with patient specific multi-omics data to develop therapeutic strategies, and knowledgebase for predictive and personalized medicine in diverse populations. This study is based on the hypothesis that understanding patient's metabolomics and genetic make-up in conjunction with clinical data will significantly lead to determining predisposition, diagnostic, prognostic and predictive biomarkers and optimal paths providing personalized care for diverse and targeted chronic, acute, and infectious diseases. This study briefs emerging significant, and recently reported multi-omics and translational approaches aimed to facilitate implementation of precision medicine. Furthermore, it discusses current grand challenges, and the future need of Findable, Accessible, Intelligent, and Reproducible (FAIR) approach to accelerate diagnostic and preventive care delivery strategies beyond traditional symptom-driven, disease-causal medical practice.

Integrating Molecular Biomarker Inputs Into Development and Use of Clinical Cancer Therapeutics

Biomarkers can contribute to clinical cancer therapeutics at multiple points along the patient’s diagnostic and treatment course. Diagnostic biomarkers can screen or classify patients, while prognostic biomarkers predict their survival. Biomarkers can also predict treatment efficacy or toxicity and are increasingly important in development of novel cancer therapeutics. Strategies for biomarker identification have involved large-scale genomic and proteomic analyses. Pathway-specific biomarkers are already in use to assess the potential efficacy of immunotherapy and targeted cancer therapies. Judicious application of machine learning techniques can identify disease-relevant features from large data sets and improve predictive models. The future of biomarkers likely involves increasing utilization of liquid biopsy and multiple samplings to better understand tumor heterogeneity and identify drug resistance.

TYK2 in Cancer Metastases: Genomic and Proteomic Discovery

Advances in genomic analysis and proteomic tools have rapidly expanded identification of biomarkers and molecular targets important to cancer development and metastasis. On an individual basis, personalized medicine approaches allow better characterization of tumors and patient prognosis, leading to more targeted treatments by detection of specific gene mutations, overexpression, or activity. Genomic and proteomic screens by our lab and others have revealed tyrosine kinase 2 (TYK2) as an oncogene promoting progression and metastases of many types of carcinomas, sarcomas, and hematologic cancers. TYK2 is a Janus kinase (JAK) that acts as an intermediary between cytokine receptors and STAT transcription factors. TYK2 signals to stimulate proliferation and metastasis while inhibiting apoptosis of cancer cells. This review focuses on the growing evidence from genomic and proteomic screens, as well as molecular studies that link TYK2 to cancer prevalence, prognosis, and metastasis. In addition, pharmacological inhibition of TYK2 is currently used clinically for autoimmune diseases, and now provides promising treatment modalities as effective therapeutic agents against multiple types of cancer.

The Multifaceted Role of Flavonoids in Cancer Therapy: Leveraging Autophagy with a Double-Edged Sword

Flavonoids are considered as pleiotropic, safe, and readily obtainable molecules. A large number of recent studies have proposed that flavonoids have potential in the treatment of tumors by the modulation of autophagy. In many cases, flavonoids suppress cancer by stimulating excessive autophagy or impairing autophagy flux especially in apoptosis-resistant cancer cells. However, the anti-cancer activity of flavonoids may be attenuated due to the simultaneous induction of protective autophagy. Notably, flavonoids-triggered protective autophagy is becoming a trend for preventing cancer in the clinical setting or for protecting patients from conventional therapeutic side effects in normal tissues. In this review, focusing on the underlying autophagic mechanisms of flavonoids, we hope to provide a new perspective for clinical application of flavonoids in cancer therapy. In addition, we highlight new research ideas for the development of new dosage forms of flavonoids to improve their various pharmacological effects, establishing flavonoids as ideal candidates for cancer prevention and therapy in the clinic.