Precision Drugs Research Articles

Michael Acceptors as Anti-Cancer Compounds: Coincidence or Causality?

Michael acceptors represent a class of compounds with potential anti-cancer properties. They act by binding to nucleophilic sites in biological molecules, thereby disrupting cancer cell function and inducing cell death. This mode of action, as well as their ability to be modified and targeted, makes them a promising avenue for advancing cancer therapy. We are investigating the molecular mechanisms underlying Michael acceptors and their interactions with cancer cells, in particular their ability to interfere with cellular processes and induce apoptosis. The anti-cancer properties of Michael acceptors are not accidental but are due to their chemical structure and reactivity. The electrophilic nature of these compounds allows them to selectively target nucleophilic residues on disease-associated proteins, resulting in significant therapeutic benefits and minimal toxicity in various diseases. This opens up new perspectives for the development of more effective and precise cancer drugs. Nevertheless, further studies are essential to fully understand the impact of our discoveries and translate them into clinical practice.

Ferroptosis-related lncRNAs: Distinguishing heterogeneity of the tumour microenvironment and predicting immunotherapy response in bladder cancer

Ferroptosis, a cell death pathway dependent on iron, has been shown in research to play a role in the development, advancement, and outlook of tumours through ferroptosis-related lncRNAs (FRLRs). However, the value of the FRLRs in bladder cancer (BLCA) has not been thoroughly investigated. This research project involved developing a predictive model using ten specific FRLRs (AC099850.4, AL731567.1, AL133415.1, AC021321.1, SPAG5-AS1, HMGA2-AS1, RBMS3-AS3, AC006160.1, AL583785.1, and AL662844.4) through univariate COX and LASSO regression techniques. The validation of this signature as a standalone predictor was confirmed in a group of 65 patients from the urology bladder tumour database at the First Affiliated Hospital of Wenzhou Medical University in Wenzhou, China. Patients were categorized based on their median risk score into either a low-risk group or a high-risk group. Enrichment analysis identified possible molecular mechanisms that could explain the variations in clinical outcomes observed in high-risk and low-risk groups. Moreover, we explored the correlation between FLPS and immunotherapy-related indicators. The ability of FLPS to forecast the effectiveness of immunotherapy was validated by the elevated levels of immune checkpoint genes (PD-L1, CTLA4, and PD-1) in the group at high risk. We also screened the crucial FRLR (HMGA2-AS1) through congruent expression and prognostic conditions and established a ceRNA network, indicating that HMGA2-AS1 may affect epithelial-mesenchymal transition by modulating the Wnt signalling pathway through the ceRNA mechanism. We identified the top five mRNAs (NFIB, NEGR1, JAZF1, JCAD, and ESM1) based on random forest algorithm and analysed the relationship between HMGA2-AS1, the top five mRNAs, and immunotherapy, and their interactions with drug sensitivities. Our results suggest that patients with BLCA have a greater sensitivity to four drugs (dasatinib, pazopanib, erismodegib and olaparib). Our study provides new insights into the TME, key signalling pathways, genome, and potential therapeutic targets of BLCA, with future guidance for immunotherapy and targeted precision drugs.

Abstract 5762: Engineering cell membrane nanoparticlesenhance immunotherapy and radiodynamic therapy for lung adenocarcinoma by promoting cGAS-STING and ferroptosis

Abstract Background: Immunotherapy is a promising approach for lung cancer, but its effectiveness is limited by tumor heterogeneity. Nanoparticle-based targeted drug delivery systems offer advantages such as targeted drug-loading capacity, and hypotoxicity, showing great potential in improving therapeutic efficacy. This study introduces a targeted drug delivery strategy based on immune-activating nanoparticles that achieves precise drugs delivery in tumor areas. Consequently, this approach remodels the microenvironment and induces tumor cytotoxicity. Method: In this study, we first constructed a targeted nanoparticle delivery system FP@CC. The vehicle utilized lung adenocarcinoma cell membranes as the outer shell and encapsulated iron-platinum nanoparticles and STING agonist Vadimezan. Then, TREM2 antibodies were conjugated on the outer layer. The structure of FP@CC-aT2 was characterized by HADDF-STEM and its safety was evaluated by hemolysis test. In vitro, its ability to induce death was verified by AM/PI staining, and to induce ferroptosis was detected by C11 assay. Furthermore, we evaluated its antitumor effects in subcutaneous tumor models. The composition of immune cells within the tumor microenvironment was analyzed using flow cytometry. Results: We initially performed HADDF-STEM analysis on the nanoparticle precursor FP/Vad@CC, revealing its uniform sphericity. For security, no significant hemolysis was observed at different concentrations of FP/Vad@CC. Then, the structures of FP/Vad@CC-aT2 and FP/Vad@CC are relatively stable (Fig 1).The number of dead cells significantly increased after deal with FP@CC, and the effect was significantly enhanced when combined with X-ray. Moreover, C11, utilizing to assess the changes in intracellular reactive oxygen species (ROS), found that FP@CC led to a significant increase in ROS, comparable to induction by H2O2. Both could be effectively prevented by ferroptosis inhibitor(Fig 2).In vivo, FP/Vad@CC-aT2 was applied to a subcutaneous tumor model in C57. It exhibited excellent therapeutic efficacy and biocompatibility. Flow cytometry revealed that FP/Vad@CC-aT2 had the anticipated impact on macrophages within the tumor: a significant reduction in CD11high/CD206high cells and opposite in the ratio of M1/M2-like macrophages (Fig 3). Conclusion: This study developed a targeted drug delivery strategy, FP/Vad@CC-aT2, to improve the tumor microenvironment (TME). We conducted preliminary experiments in vitro and in vivo to validate its physicochemical properties and tumor inhibitory effects, including the induction of ferroptosis. We assessed its safety in mouse and obtained initial evidence of FP/Vad@CC-aT2's ability to remodel the subtypes of macrophage.Moving forward, we will validate its therapeutic and impact on the TME after surgical procedures. Citation Format: Haiyu Zhou, Hongrui Qiu, Shiying Li, Bin Xu, Shengbo Liu, Huili Wang, Hengliang Hou. Engineering cell membrane nanoparticlesenhance immunotherapy and radiodynamic therapy for lung adenocarcinoma by promoting cGAS-STING and ferroptosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5762.

Precision Drugs are Needed for Precision Medicine to Work

Precision medicine (PM) tailors disease prevention and treatment to people’s genes, environments, and lifestyles, claiming to target the right treatments for the right patients at the right time. However, it needs precision drugs with molecular structures that interact with precisely defined disease targets to do so

Precision Drugs

The mantra of precision medicine is to prevent and treat diseases by considering individual variability in genes, environment and lifestyle for each person. However, precision drugs to enable precision medicine are not yet available. This article addresses this issue.

4D printed and multi-stimulus responsive shape memory polymer nanocomposites developed on hydrogen bonding–metal-phenolic sacrificial network: Application for hazardous chemical operations soft robots

Designing 4D printed shape memory polymers (SMPs) with mechanical robust and multi-stimulus responses applied in soft robot holds vast promise. While significant progress has been made in this area, implementing SMP composites with multi-stimulus response capabilities for fused filament fabrication (FFF) 4D printing typically sacrifices the inherent mechanical properties of the materials, limiting the requirements for robust and tough applications of SMP in soft robotics. In this work, Fe3O4 nanoparticles are employed as functional particles, and the "hydrogen bonding–metal-phenolic" sacrificial network in the nanoparticles and polymer is designed to achieve NIR light and magnetic stimulation response without sacrificing the maximum strength and toughness of the 4D printable SMP. The SMP nanocomposite developed from the sacrificial network has a tensile strength of 18.98 MPa and an elongation at break of 897 %, a 40 % increase in strength and 196 % increase in elongation at break compared to SMP nanocomposites with direct Fe3O4 addition. In addition, the shape-programmable soft robot with NIR light and magnetic stimulation response is developed based on 4D printing. The remote precision control and drugs release demonstrates the potential application of 4D printed soft robots in hazardous chemical operations.

Cuproptosis-related lncRNA scoring system to predict the clinical outcome and immune landscape in pancreatic adenocarcinoma

Cuproptosis is a recently discovered novel programmed cell death pathway that differs from traditional programmed cell death and has an important role in cancer and immune regulation. Long noncoding RNA (lncRNA) is considered new potential prognostic biomarkers in pancreatic adenocarcinoma (PAAD). However, the prognostic role and immune landscape of cuproptosis-related lncRNA in PAAD remain unclear. The transcriptome and clinical data of PAAD were obtained from The Cancer Genome Atlas (TCGA) database. Cuproptosis-related lncRNA was identified using Pearson correlation analysis. The optimal lncRNA was screened by Cox and the Least Absolute Shrinkage and Selection Operator (LASSO) regression mode, and for the construction of risk scoring system. PAAD patients were divided into high- and low-risk groups according to the risk score. Clinicopathological parameter correlation analysis, univariate and multivariate Cox regression, time-dependent receiver operating characteristic (ROC) curves, and nomogram were performed to evaluate the model. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to explore differences in biological function between different risk groups. Single-sample gene set enrichment analysis (ssGSEA) and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm were used to analyze the differences in tumor immune microenvironment (TIME) in different risk groups of PAAD. Additionally, the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to predict immunotherapy response and identify potential immune beneficiaries. Immune checkpoints and tumor mutation burden (TMB) were also systematically analyzed. Finally, drug sensitivity analysis was used to explore the reactivity of different drugs in high- and low-risk groups to provide a reference for the selection of precise therapeutic drugs. Six cuproptosis-related lncRNAs (AL117335.1, AC044849.1, AL358944.1, ZNF236-DT, Z97832.2, and CASC8) were used to construct risk model. Survival analysis showed that overall survival and progression-free survival in the low-risk group were better than those in the high-risk group, and it is suitable for PAAD patients with different clinical characteristics. Univariate and multifactorial Cox regression analysis showed that risk score was an independent prognostic factor in PAAD patients. ROC analysis showed that the AUC values of the risk score in 1 year, 3 years and 5 years were 0.707,0.762 and 0.880, respectively. Nomogram showed that the total points of PAAD patients at 1 year, 3 years, and 5 years were 0.914,0.648, and 0.543. GO and KEGG analyses indicated that the differential genes in the high- and low-risk groups were associated with tumor proliferation and metastasis and immune regulatory pathway. Immune correlation analysis showed that the amount of pro-inflammatory cells, including CD8+ T cells, was significantly higher in the low-risk group than in the high-risk group, and the expression of immune checkpoint genes, including PD-1 and CTLA-4, was increased in the low-risk group. TIDE analysis suggests that patients in the low-risk group may benefit from immunotherapy. Finally, there was significant variability in multiple chemotherapeutic and targeted drugs across the risk groups, which informs our clinical drug selection. Our cuproptosis-related lncRNA scoring system (CRLss) could predict the clinical outcome and immune landscape of PAAD patients, identify the potential beneficiaries of immunotherapy, and provide a reference for precise therapeutic drug selection.

High morbidity and mortality in children with untreated congenital deficiency of leptin or its receptor

The long-term clinical outcomes of severe obesity due to leptin signaling deficiency are unknown. We carry out a retrospective cross-sectional investigation of a large cohort of children with leptin (LEP), LEP receptor (LEPR), or melanocortin 4 receptor (MC4R) deficiency (n= 145) to evaluate the progression of the disease. The affected individuals undergo physical, clinical, and metabolic evaluations. We report a very high mortality in children with LEP (26%) or LEPR deficiency (9%), mainly due to severe pulmonary and gastrointestinal infections. In addition, 40% of surviving children with LEP or LEPR deficiency experience life-threatening episodes of lung or gastrointestinal infections. Although precision drugs are currently available for LEP and LEPR deficiencies, as yet, they are not accessible in Pakistan. An appreciation of the severe impact of LEP or LEPR deficiency on morbidity and early mortality, educational attainment, and the attendant stigmatization should spur efforts to deliver the available life-saving drugs to these children as a matter of urgency.

Classification of Epileptic Seizure Types Using Multiscale Convolutional Neural Network and Long Short-Term Memory

The accurate classification of seizure types using electroencephalography (EEG) signals plays a vital role in determining a precise treatment plan and therapy for epilepsy patients. Among the available deep network models, Convolutional Neural Networks (CNNs) are the most widely adopted models for learning and representing EEG signals. However, typical CNNs have high computational complexity, leading to overfitting problems. This paper proposes the design of two effective, lightweight deep network models; the 1D multiscale neural network (1D-MSCNet) model and the Long Short-term Memory (LSTM)-based compact CNN (EEG-LSTMNet) model. The 1D-MSCNet model comprises three modules: a spectral–temporal convolution module, a spatial convolution module, and a classification module. It extracts features from input EEG trials at multiple frequency/time ranges, identifying relationships between the spatial distribution of their channels. The EEG-LSTMNet model includes three convolutional layers, namely temporal, depthwise, and separable layers, a single LSTM layer, and two fully connected classification layers to extract discriminative EEG feature representations. Both models have been applied to the same EEG trials collected from the Temple University Hospital (TUH) database. Results revealed F1-score values of 96.9% and 98.4% for the 1D-MSCNet and EEG-LSTMNet, respectively. Based on the demonstrated outcomes, both models outperform related state-of-the-art methods due to their architectures’ adoption of 1D modules and layers that reduce the computational effort needed, solve the overfitting problem, and enhance classification efficiency. Hence, both models could be valuable additions for neurologists to help them decide upon precise treatments and drugs for patients depending on their type of seizure.

Machine learning models predict the mTOR signal pathway-related signature in the gastric cancer involving 2063 samples of 7 centers.

Gastric cancer, as a tumor with poor prognosis, has been widely studied. Distinguishing the types of gastric cancer is helpful. Using the transcriptome data of gastric cancer in our study, relevant proteins of mTOR signaling pathway were screened to identify key genes by four machine learning models, and the models were validated in external datasets. Through correlation analysis, we explored the relationship between five key genes and immune cells and immunotherapy. By inducing cellular senescence in gastric cancer cells with bleomycin, we investigated changes in the expression levels of HRAS through western blot. By PCA clustering analysis, we used the five key genes for gastric cancer typing and explored differences in drug sensitivity and enrichment pathways between different clustering groups. We found that the SVM machine learning model was superior, and the five genes (PPARA, FNIP1, WNT5A, HRAS, HIF1A) were highly correlated with different immune cells in multiple databases. These five key genes have a significant impact on immunotherapy. Using the five genes for gastric cancer gene typing, four genes were expressed higher in group 1 and were more sensitive to drugs in group 2. These results suggest that subtype-specific markers can improve the treatment and provide precision drugs for gastric cancer patients.

Prediction of Tumor Development and Urine-Based Liquid Biopsy for Molecule-Targeted Therapy of Gliomas.

The timing of the acquisition of tumor-specific gene mutations and the systems by which these gene mutations are acquired during tumorigenesis were clarified. Advances in our understanding of tumorigenesis are being made every day, and therapies targeting fundamental genetic alterations have great potential for cancer treatment. Moreover, our research team successfully estimated tumor progression using mathematical modeling and attempted early diagnosis of brain tumors. We developed a nanodevice that enables urinary genetic diagnosis in a simple and noninvasive manner. Mainly on the basis of our research and experience, this review article presents novel therapies being developed for central nervous system cancers and six molecules, which upon mutation cause tumorigenesis and tumor progression. Further understanding of the genetic characteristics of brain tumors will lead to the development of precise drugs and improve individual treatment outcomes.

Discrete polyethylene glycol derivatives as a potent impetus for next-generation biomedicines

PEGylation, which covalently modifies small-molecule drugs, peptides and proteins with polyethylene glycol (PEG) to improve their pharmacokinetics and efficacy, has become one of the most widely used drug modification techniques. However, PEG and its derivatives have been verified to be immunogenic and antigenic, which directly lead to side effects such as accelerated blood clearance (ABC) phenomenon and allergic reactions to PEGylated drugs or PEG excipients. Recent development of single molecular weight discrete PEG synthesis methodology have led to continuous and extensive focus on the difference in biological activity between conventional polydisperse PEG and single molecular weight precise PEG. Discrete PEG has demonstrated obvious advantages in resisting protein adsorption, cell adhesion and enhancing drug efficacy. These preliminary results not only confirm the significant impact of PEG chain polydispersity on its biological effect, but also reveal the possibility and potential advantages of using discrete PEG to reduce the immunogenicity and antigenicity. Hopefully, single chemical structure and molecular weight ensure the batch repeatability of newly developed discrete PEG products, and facilitate the understanding of their physicochemical properties and biological effects that promoting the clinical conversion of precise PEG drugs.

Dynamic evaluation of pathological changes in a mouse acne model by optical imaging technology.

Acne vulgaris is a disorder of the pilosebaceous unit that is primarily caused by hyperseborrhoea, colonization with Propionibacterium acnes, hyperkeratosis and an inflammatory response. Existing pharmacodynamic assessment methods primarily focus on a single causative factor at a certain time point, making it difficult to assess multiple factors simultaneously in real time. Therefore, it is crucial to establish a dynamic and nondestructive method for the assessment of acne in vivo. This study utilized four-dimensional optical imaging techniques to assess the pathogenic factors and pathological progression of acne. LSCI was employed to measure blood flow; TPEF was used to observe inflammatory changes (NAD(P)H) in epidermal granular layer cells and structural changes in collagen fibres in the dermal layer. Additionally, the dermatoscope was used to investigate the micro-characterization of the lesions. We observed that the epidermis in the lesion area was thickened, hair follicles were keratinized, and there was obvious inflammation and blood flow aggregation by optical imaging technology. Based on these findings, the pathological progression of this acne model could be divided into the inflammation phase, accompanied by bacterial colonization, and the reparative phase. These results provide a new perspective for the assessment of acne and offer an experimental basis for the selection of precise drugs for clinical use.

Abstract 3777: MicroRNA-inducible CRISPR/Cas9 for cell type-specific genome regulation in cancer

Abstract MicroRNA-dependent mRNA decay plays an important role in gene silencing by facilitating posttranscriptional and translational repression. Inspired by this intrinsic nature of microRNA-mediated mRNA cleavage, here, we describe a microRNA-targeting mRNA as a switch platform called mRNA bridge mimetics to regulate the translocation of proteins. We applied the mRNA bridge mimetics platform to Cas9 protein to confer it the ability to translocate into the nucleus via cleavage of the nuclear export signal called CRISPR Self Check-In. This system performed programmed gene editing in vitro and in vivo. Combinatorial treatment with cisplatin and miR-21-EZH2 axis-targeting CRISPR Self Check-In improved sensitivity to chemotherapeutic drugs in vivo. Using the endogenous microRNA mediated mRNA decay mechanism, our platform is able to remodel a cell’s natural biology to allow the entry of precise drugs into the nucleus, devoid of non-specific translocation. The mRNA bridge mimetics strategy is promising for applications in which the reaction must be controlled via intracellular stimuli and modulates Cas9 proteins to ensure safe genome modification in diseased conditions. Citation Format: Seung Ja Oh, Cheol-Hee Shin, Ji Min Lee, Juyong Lee, Su Chan Park. MicroRNA-inducible CRISPR/Cas9 for cell type-specific genome regulation in cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3777.

Real-world data for precision cancer medicine-A European perspective.

Leveraging real-world data (RWD) for drug access is necessary to overcome a key challenge of modern precision oncology: tackling numerous low-prevalence oncogenic mutations across cancers. Withholding a potentially active medication in patients with rare mutations for the sake of control chemotherapy or "best" supportive care is neither practicable nor ethically justifiable anymore, particularly as RWD could meanwhile be used instead, according to scientific principles outlined by the US Food and Drug Administration, European Medicines Agency and other stakeholders. However, practical implementation varies, with occasionally opposite recommendations based on the same evidence in different countries. In the face of growing need for precision drugs, more transparency of evaluation, a priori availability of guidance for the academia and industry, as well as a harmonized framework for health technology assessment across the European Union (EU) are imperative. These could in turn trigger infrastructural changes in national and pan-European registries, cancer management guidelines (e.g., frequency of routine radiologic restaging, inclusion of patient-reported outcomes), and the health data space, to ensure conformity with declared standards and facilitate extraction of RWD sets (including patient-level data) suitable for approval and pricing with minimal effort. For an EU-wide unification of precision cancer medicine, collective negotiation of drug supply contracts and funding solidarity would additionally be required to handle the financial burden. According to experience from pivotal European programs, off-label use could potentially also be harmonized across EU-states to accelerate availability of novel drugs, streamline collection of valuable RWD, and mitigate related costs through wider partnerships with pharmaceutical companies.

Epithelial-Mesenchymal Transition and Tumour Progression: An Overview

Aim: The purpose of this review is to highlight the role of the epithelial-mesenchymal transition (EMT) in tumorigenesis and assess the value of manipulating this process in cancer therapy. Method: A search was conducted for peer-reviewed articles in PubMed, Google Scholar, and ResearchGate employing keywords and phrases. Main Points: The EMT program is a key driver of tumor initiation and progression. Inhibition of EMT in carcinoma cells can yield fruitful results in the treatment of cancer, particularly in overcoming resistance to chemotherapy and precision drugs. Conclusion: Blocking the process of EMT in carcinoma cells can help overcome the resistance to chemotherapy and targeted precision medicine.

Patient-derived xenograft model in colorectal cancer basic and translational research.

Colorectal cancer (CRC) is one of the most popular malignancies globally, with 930 000 deaths in 2020. The evaluation of CRC-related pathogenesis and the discovery of potential therapeutic targets will be meaningful and helpful for improving CRC treatment. With huge efforts made in past decades, the systematic treatment regimens have been applied to improve the prognosis of CRC patients. However, the sensitivity of CRC to chemotherapy and targeted therapy is different from person to person, which is an important cause of treatment failure. The emergence of patient-derived xenograft (PDX) models shows great potential to alleviate the straits. PDX models possess similar genetic and pathological characteristics as the features of primary tumors. Moreover, PDX has the ability to mimic the tumor microenvironment of the original tumor. Thus, the PDX model is an important tool to screen precise drugs for individualized treatment, seek predictive biomarkers for prognosis supervision, and evaluate the unknown mechanism in basic research. This paper reviews the recent advances in constructed methods and applications of the CRC PDX model, aiming to provide new knowledge for CRC basic research and therapeutics.

Fast Growing Furious Races for Targeting Fibroblast Growth Factor Receptors.

Targeting fibroblast growth factor receptors (FGFRs) has been slow compared to other targeted cancer therapies for receptor tyrosine kinases, such as epidermal growth factor receptors. The low efficacy and variable response have limited the growth of FGFR inhibitors in clinical use. Nevertheless, recent systematic and genomic approaches have identified the biological conditions for effectively targeting FGFRs and can accelerate the development of targeted drugs. Under clinical and preclinical trials, the inhibitors started fast growing furious races to target FGFRs. Finally, FGFRs will be more actionable and targetable with more precise and effective drugs at the end of the race, passing the finish line.

Establishment of an epithelioid sarcoma PDCs and PDX to evaluate drug sensitivity

Epithelioid sarcoma (ES) is a very rare mesenchymal malignancy. Its oncogenesis remains unknown, and few therapies are available for advanced patients. Improved therapies, such as combined therapies, are urgently needed for the treatment of advanced ES. To identify precision drugs for advanced ES patients, the sensitivity of the drugs must be screened and evaluated before they are used for treatment. In the present study, tumour tissue from an ES patient was subjected to NGS sequencing, cell culture and the construction of a PDX model. Using the early generations of tumour-derived cells, we performed a screen and found that the combined drugs ADM and trametinib exhibited coefficiency in tumour inhibition. This conclusion was further confirmed in experiments with later generations of cells and PDX models. Therefore, we suggest that early generations of tumour-derived cells be used to test the sensitivity of ES tumours to candidate drugs. Moreover, we speculate that trametinib may be combined with chemotherapy in ES patients to prolong the duration of the chemotherapeutic response.

Prognostic Significance of Blood-Based Baseline Biomarkers in Treatment-Resistant Depression: A Literature Review of Available Studies on Treatment Response.

Major depressive disorder is a leading cause of disability worldwide and a major contributor to the overall global burden of disease. While there are several options for antidepressant treatment, only about 40–60% of patients respond to initial monotherapy, while 30–40% of patients may even show resistance to treatment. This article offers a narrative review of those studies evaluating the predictive properties of various blood-based baseline biomarkers regarding treatment responses to the pharmacological, stimulation, or behavioral treatment of patients with treatment-resistant depression (TRD). Our results show that overall, there is only a very limited number of studies assessing baseline peripheral biomarkers regarding treatment response in TRD. Although there is some evidence for the predictive significance of particular biomarkers (e.g., IL-6, CRP, BDNF), the majority of the results are either single-study reports or studies with conflicting results. This may contribute to the wide variety of treatment protocols and different TRD definition criteria, the small number of patients included, and the existence of different biological phenotypes of the disorder used within the various studies. Taken together, there does not yet appear to be any specific baseline peripheral biomarker with sufficient discriminative predictive validity that can be used in the routine clinical practice of TRD. The discovery of new biomarkers and the better clinical characterization of known biomarkers could support the better classification and staging of TRD, the development of personalized treatment algorithms with higher rates of remission and fewer side effects, and the development of new precision drugs for specific subgroups of patients.