Recently, immunotherapy has been a key therapeutic strategy for cancer. Deubiquitinating enzymes (DUBs), which are protein-modifying enzymes, have a crucial role in the pathogenesis of cancer, autoimmune diseases, and inflammation. DUBs influence the tumor immune microenvironment by regulating immune cell functions and key signaling pathways. Thus, the potential applications of DUBs in immunotherapy have piqued the interest of the scientific community. This study performed bibliometric analysis to comprehensively examine the research hotspots and trends in this field, providing theoretical foundations and guidance for future research. Studies associated with DUBs and immunotherapy conducted over a decade (2014 to 2024) were searched and extracted from Web of Science Collection database. The analysis was performed using CiteSpace, VOSviewer, and the Bibliometrix package in R software. Visualizations were generated for countries, institutions, authors, journals, references, and keyword co-occurrences. In total, 321 articles related to DUBs and immunotherapy were retrieved. The number of publications increased markedly since 2020. China had the highest number of publications, while the United States exerted the most influence in this field. Zhang Jinfang was the most influential author in this field. Zhejiang University was the institution with the highest number of publications. Nature was the most cited journal (807 total citations). Keyword analysis revealed that the primary research hotspots were expression, immunotherapy, ubiquitination, degradation, and cancer. This bibliometric analysis revealed the research trends and emerging frontiers in DUBs and immunotherapy, offering novel strategies for the application of DUBs in immunotherapy.

Immune checkpoint inhibitors (ICIs), such as anti-PD-1, anti-PD-L1, and anti-CTLA-4 therapies, have revolutionized cancer treatment by harnessing the body's immune system to eliminate cancer cells. Despite their considerable promise, the efficacy of ICIs significantly differs based on tumor types and specific patient conditions, highlighting the necessity for personalized approaches in the framework of predictive preventive personalized medicine (PPPM; 3PM).

This review proposes a stratification instrument within the 3PM framework to enhance the therapeutic efficacy of ICIs across Pan-cancer. Predictive approaches need to be utilized to enhance the effectiveness of ICIs. For example, biomarkers such as particular genetic alterations and metabolic pathways provide key information on patient treatment responses. To predict treatment outcomes, uncover resistance mechanisms, and tailor medications, we examine biomarkers including PDL-1 and CTLA4. Focusing on cancers like melanoma, bladder, and renal cell carcinoma, we highlight advances in combination therapies and cellular approaches to overcome resistance. We conducted an analysis of clinical trials and public datasets (TCGA, GEO) to evaluate ICI responses across number of cancer types. Survival analysis employed Kaplan-Meier curves and Cox regression. Pan-cancer analysis shows response rates ranging from 19.8% in bladder cancer to > 39% in melanoma when combination therapy is used, emphasizing the potential of 3PM to improve outcomes. By exploring resistance mechanisms and emerging therapeutic innovations, we propose a cost-effective model for better patient stratification and care. Validation of this model requires standardized biomarkers and prospective trials, promising a shift toward precision oncology.

Within the 3PM framework, this review addresses the urgent need for cost-effective stratification tools and adaptive combinatorial strategies to optimize outcomes.

Pyroptosis has attracted significant attention for its role in cancer chemotherapy and immunotherapy. However, few drugs have been reported to induce pyroptosis via the Caspase-3/gasdermin E (GSDME) pathway. Herein, three novel PtIV prodrugs, MRP, DRP, and HRP are rationally designed by conjugating DNA methyltransferase (DNMT) inhibitor (RG108) and/or histone deacetylase (HDAC) inhibitor (PhB) to the PtIV center. These prodrugs can be easily reduced to cisplatin (CDDP) due to the high glutathione (GSH) levels in tumors, liberating the coordinated ligands. Released RG108 reactivates the GSDME gene and reduces pyroptosis in low GSDME-expressing tumor cells. Meanwhile, PhB-induced chromatin loosening enhances CDDP-DNA binding, which not only increases Caspase-3 expression, but also upregulates GSDME. HRP demonstrates superior ability to suppress tumor growth and metastasis while reducing systemic toxicity compared with CDDP. By reactivating GSDME and loosening chromatin, HRP effectively boosts tumor cell pyroptosis and exhibits the most pronounced anticancer performance. These findings highlight HRP's potential as a therapeutic agent for triple-negative breast cancer (TNBC) and offer innovative strategies for combining chemotherapy with immunotherapy. To the best of current knowledge, this is the first report of platinum complexes inducing pyroptosis via the Caspase-3/GSDME pathway in low GSDME-expressing tumor cells.

Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortality, necessitating the identification of novel biomarkers for improved prognosis and diagnosis. This study investigates the role of epoxide hydrolase 4 (EPHX4), a member of the epoxide hydrolase family, in LUAD. Using data sourced from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, which were subsequently validated by the Gene Expression Omnibus (GEO), we analyzed levels of EPHX4 expression, mutation, and methylation in tumors versus normal tissues. Our findings revealed a significant upregulation of EPHX4 in LUAD tissues compared to normal lung tissues (p < 0.001), correlating with poorer overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI). Furthermore, EPHX4 exhibited considerable diagnostic potential, as demonstrated by an area under the curve (AUC) of 0.854 in a Receiver Operating Characteristic (ROC) analysis. Notably, EPHX4 expression was associated with immune infiltration, specifically Th2 cells, neutrophils, and macrophages, along with immune checkpoint molecules including PD-L1, PD-L2, and TIM-3. Additionally, EPHX4 was involved in pivotal tumor-associated pathways, particularly cell cycle regulation. In conclusion, an elevated EPHX4 expression is indicative of poorer prognosis in LUAD and may play a role in immune evasion and cell cycle dysregulation, highlighting its potential as a promising biomarker for the diagnosis and prognostic prediction of LUAD.

Dengue virus (DENV) infection is a major global public health problem, particularly in tropical and subtropical regions where Aedes mosquitoes are prevalent. The clinical spectrum of dengue ranges from mild febrile illness to severe conditions such as dengue hemorrhagic fever and dengue shock syndrome. Early prediction of dengue progress is crucial for timely therapeutic medications, which can reduce both morbidity and mortality. Traditional diagnostic methods such as serological tests and polymerase chain reactions are often time-consuming and require sophisticated infrastructure and skilled personnel. To overcome these limitations, the development of point-of-care (POC) diagnosis platforms and novel predictive biomarkers is crucial to providing rapid, real-time diagnostic tools that can be used in low-resource settings and at the patient's bedside. Predictive biomarkers enable the identification of disease risk in the early stages and can reduce hospitalization visits. This review offers a comprehensive overview of portable POC diagnosis platforms and emerging predictive biomarkers for the rapid diagnosis of severe DENV infection. Its provides an overview of its epidemiology, discusses the global burden of DENV, and explores DENV infection with different serotypes, as well as the clinical spectrum and severity of dengue. The key focus is on the latest advancements in POC diagnosis readout methods and portable POC devices for DENV diagnosis, including colorimetric assay, electrochemical method, lateral flow strip, and microfluidic chip platforms. In addition, the review article explores various emerging predictive biomarkers for the rapid detection of DENV, while also highlighting the limitations associated with protein, nucleic acid, and metabolic biomarkers. Finally, we address the current challenges, limitations, and potential future directions of POC diagnosis platforms for the diagnosis of severe DENV infection.

Immune checkpoint inhibitors (ICIs) have shown substantial benefit for patients with advanced non-small cell lung cancer (NSCLC). However, resistance to ICIs remains a major clinical challenge. Here, we perform a comprehensive bioinformatic analysis of plasma proteomic profiles to explore the underlying biology of treatment resistance in NSCLC.

The analysis was performed on 388 "resistance-associated proteins" (RAPs) that were previously described as pretreatment plasma proteomic predictors within the PROphet computational model designed to predict ICI clinical benefit in NSCLC. Putative tissue origins of the RAPs were explored using publicly available datasets. Enrichment analyses were performed to investigate RAP-related biological processes. Plasma proteomic data from 50 healthy subjects and 272 patients with NSCLC were compared, where patients were classified as displaying clinical benefit (CB; n=76) or no CB (NCB; n=196). Therapeutic agents targeting RAPs were identified in drug and clinical trial databases.

The RAP set was significantly enriched with proteins associated with lung cancer, liver tissue, cell proliferation, extracellular matrix, invasion, and metastasis. Comparison of RAP expression in healthy subjects and patients with NSCLC revealed five distinct RAP subsets that provide mechanistic insights. The RAP subset displaying a pattern of high expression in the healthy population relative to the NSCLC population included multiple proteins associated with antitumor activities, while the subset displaying a pattern of highest expression in the NCB population included proteins associated with various hallmarks of treatment resistance. Analysis of patient-specific RAP profiles revealed inter-patient diversity of potential resistance mechanisms, suggesting that RAPs may aid in developing personalized therapeutic strategies. Furthermore, examination of drug and clinical trial databases revealed that 17.5% of the RAPs are drug targets, highlighting the RAP set as a valuable resource for drug development.

The study provides insight into the underlying biology of ICI resistance in NSCLC and highlights the potential clinical value of RAP profiles for developing personalized therapies.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, but their association with thrombosis presents significant clinical challenges. Patients with cancer already exhibit elevated risks for venous thromboembolism and arterial thrombosis, with treatment modalities like chemotherapy further exacerbating this risk. Emerging evidence suggests that ICIs contribute to thrombotic events through multifactorial mechanisms, including immune dysregulation, T cell activation, endothelial dysfunction, elevated tissue factor expression, and impaired fibrinolysis. Additional risk factors such as obesity, smoking, prior thrombotic events, and combination ICI therapy further increase thrombosis susceptibility. The literature reports varying incidence rates of ICI-associated thrombosis, with some studies indicating comparable risks to chemotherapy, while others highlight higher rates, particularly during the initial treatment phase. Management aligns with standard protocols for cancer-associated thrombosis, using low-molecular-weight heparin or direct oral anticoagulants, though optimal treatment duration and the role of prophylactic anticoagulation require further investigation. This review provides a comprehensive overview of the mechanisms, incidence rates, and clinical management strategies of ICI-associated thrombosis, emphasizing the importance of proactive risk assessment to optimize patient outcomes.

Glioblastoma multiforme (GBM) is a pervasive and aggressive malignant brain tumor. In the tumor immune microenvironment, CD8 + TIM3 + CD101 + T cells (CCT cells) play a pivotal role in tumor progression and immune evasion. This study aimed to characterize differentially expressed genes (DEGs) in CCT cells, establish a prognostic model for GBM, and explore clinical implications.

Analysis of data from TCGA, CGGA, and GEO databases included whole-genome expression profiles, clinical data, single nucleotide mutations, and single-cell RNA sequencing. DEGs were identified, and cell trajectories were constructed using Seurat, Monocle 2, and CellChat packages. Functional enrichment analysis was conducted with clusterProfiler, and a prognostic model was developed. Immune infiltration and drug sensitivity analyses were performed to evaluate therapeutic implications.

Eight distinct cell types were distinguished, encompassing T cells, macrophages, neurons, mural cells, endothelial cells, oligodendrocytes, fibroblasts, and B cells. Comparative analysis revealed differences in these cell types between GBM samples with new adjuvant therapy and initial diagnosis controls. Pseudotime analysis indicated CD8 + TIM3 + CD101-T cells as precursors to CCT cells, unveiling unique gene expression patterns during this transition. The prognostic model, incorporating 22 gene features via LASSO regression, demonstrated strong predictive ability through Receiver Operating Characteristic (ROC) curves. Analysis of 28 immune cell types revealed differences between high-risk and low-risk groups, providing insights into GBM's immune evasion mechanisms. Drug sensitivity analysis proposed potential therapeutic strategies for high-risk patients.

This study offers an in-depth understanding of CCT cells in GBM, introducing a novel prognostic model and suggesting promising therapeutic approaches.

Hepatocellular carcinoma (HCC) stands as the fourth leading cause of cancer-related deaths worldwide. SUMO-specific peptidases, known as SENPs, emerge as critical players, regulating tumorigenesis and progression of numerous cancer types. Despite this, the specific impact of SENPs in HCC remains unclear. Hence, our study aimed to reveal the immune and prognostic implications of SENPs in HCC.

The gene expression of SENP in various cancers was examined using open-access databases including TCGA, GTEx, and CPTAC. In order to investigate the prognostic potential of the SENP family, Kaplan-Meier analysis was used. To clarify the underlying biological mechanisms, gene set enrichment analysis (GSEA) was carried out. cBioPortal database was used to evaluate genetic mutation profiles. For insight into the relationship between SENP genes and tumor immunity, various algorithms were used.

Our findings showed that SENP1, SENP2, SENP3, SENP5, SENP6, and SENP7 expression levels were significantly higher in HCC tumor tissues compared to normal tissues. In HCC patients, elevated SENP1 and SENP5 expression has been associated with tumor development and poor outcomes. Our immune infiltration patterns results also showed significant correlations between SENP5 expression and neutrophil (cor = 0.346, p < 0.001), myeloid dendritic cell (cor = 0.491, p < 0.001), macrophage (cor = 0.465, p < 0.001), and memory B cell (cor = 0.336, p < 0.001) infiltration in HCC, whereas SENP1 expression was associated with none of these infiltrations.

The prognostic and immunogenetic value of SENP1 and SENP5 in HCC was demonstrated in this study. Therefore, these two genes have the potential to function as separate prognostic biomarkers and offer promise as immunotherapeutic targets in the fight against HCC.

In patients with metastatic urothelial carcinoma (mUC) receiving programmed cell death ligand 1 (PD-L1) inhibitors, it is critically important to identify primary refractory patients very early to enable modification of therapy before clinical progression and decline of performance status. We hypothesized that baseline and early-on-treatment (EOT) parameters may help identify patients likely to have primary refractory disease.

We considered baseline and EOT variables measured up to 5 weeks after initiating therapy in the phase 3 clinical trial IMvigor211, which compared atezolizumab versus chemotherapy, in muC patients who had progressed on platinum-based chemotherapy. We used least absolute shrinkage and selection operator-regularized logistic regression models to predict the risk of primary refractory disease employing clinical and laboratory variables.

902 patients were evaluable for analysis. Our baseline model achieves an area under the curve (AUC) of 0.730, 0.717 for the atezolizumab group and 0.696 for the chemotherapy group. The AUC increases to 0.848 overall with EOT parameters, 0.871 for the atezolizumab group and 0.788 for the chemotherapy group. The EOT model suggests that 33.7% of patients receiving atezolizumab may benefit from switching to chemotherapy, reducing their risk of primary refractoriness from 67.1% to 51.5%.

Our prediction model employs readily available and routinely measured clinical and laboratory factors, such as urine-specific gravity, presence of liver metastases, and total protein and erythrocyte counts. It robustly identifies patients with early primary refractory disease to atezolizumab before clinical progression and may inform therapeutic decisions. Validation in larger independent cohorts and other treatments is required.

The tumor microenvironment is crucial for prognosis and response to immunotherapy in several tumor entities.

In a multicenter retrospective study, a total of 86 tumor samples from patients with metastatic melanoma were evaluated for baseline expression of indoleamine 2,3-dioxygenase (IDO) and programmed death ligand 1 (PD-L1). Expression patterns of IDO and PD-L1 on tumor cells and antigen-presenting cells (APCs) as determined by immunohistochemical (IHC) staining of paraffin-embedded tissue sections were correlated with response to ipilimumab and overall survival (OS). Statistical analysis was performed using the Spearman correlation, the Mann-Whitney test and Kaplan-Meier estimator.

IDO expression in tumor cells or APCs was not predictive for treatment response. The median OS was 26 months in IDO-positive and IDO-negative patients, regardless of IDO expression in tumor cells or APCs. A correlation of IHC expression scores of IDO and PD-L1 could not be documented.

The exact role of IDO in creating an immunosuppressive tumor environment and its reversal needs to be further elucidated.

Multiple myeloma (MM) progression is driven by immune dysregulation within the tumor microenvironment (TME). However, myeloma-intrinsic mechanisms underlying immune dysfunction remain poorly defined, and current immunotherapies show limited efficacy. Using RNA-seq data from 859 MM patients (MMRF-CoMMpass), we integrated xCELL, CIBERSORT, and ESTIMATE algorithms to deconvolute immune-stromal dynamics. Consensus clustering identified immune subtypes, followed by differential gene analysis and LASSO-Cox regression to construct a prognostic model validated in an independent cohort (GSE19784, N = 328). Immune Subtype Classification: Two subgroups emerged: Multiple myeloma-associated immune-related cluster 1 (N = 482): Immune-dysfunctional TME with Th2 cell enrichment, preadipocyte accumulation, and CXCL family suppression, linked to poor survival (P < 0.001). Multiple myeloma-associated immune-related cluster 2 (N = 377): Immune-active TME with cytotoxic CD8 + T/NK cell infiltration and favorable outcomes. Prognostic Gene Signature: Ten immune-related genes (UBE2T, E2F2, EXO1, SH2D2A, DRP2, WNT9A, SHROOM3, TMC8, CDCA7, and GPR132) predicted survival (The One-year AUC = 0.682 and The Over 5-years AUC = 0.714). We define a myeloma-intrinsic immune classification system and a 10-gene prognostic index, offering a framework for risk-stratified immunotherapy. Integration with flow cytometry could optimize precision treatment in MM.

GTPase IMAP family member 8 (GIMAP8) plays a key role in pathophysiology of several malignancies. The objective of this current research endeavor was to investigate the prognosis value of GIMAP8 in lung adenocarcinoma and examine how it relates to immunity. Expression profiles associated with GIMAP8 and related clinical details were acquired from The Cancer Genome Atlas database, and we conducted survival analysis, enrichment analysis and immune infiltration studies. Additionally, we evaluated the effect of GIMAP8 on radiation resistance of tumor by in vivo and in vitro experiments. Our results showed that lung adenocarcinoma tumor tissues exhibited lower GIMAP8 levels compared to nearby normal tissues. Furthermore, decreased GIMAP8 expression strongly correlated with poorer OS. The expression of GIMAP8 is closely related to the formation of radiation resistance in tumor cells. GSEA identified multiple signaling pathways linked to GIMAP8, including immune-related, chemokine, cell adhesion molecule, and NF-κB signaling pathways. GIMAP8 expression strongly correlated with the expression of immune checkpoint molecules, tumor mutational burden, tumor neoantigen burden, immune cells, and tumor immune microenvironment. GIMAP8 was found to have an inhibitory effect on lung adenocarcinoma and was closely related to the immune response. Moreover, GIMAP8 may also influence radiation resistance in tumors.

Head and neck cancers, including cancers of the mouth, throat, voice box, salivary glands, and nose, are a significant global health issue. Radiotherapy and surgery are commonly used treatments. However, due to treatment resistance and disease recurrence, new approaches such as immunotherapy are being explored. Immune checkpoint inhibitors (ICIs) have shown promise, but patient responses vary, necessitating predictive markers to guide appropriate treatment selection. This study investigates the potential of non-invasive biomarkers found in saliva, oral rinses, and tumor-derived exosomes to predict ICI response in head and neck cancer patients. The tumor microenvironment significantly impacts immunotherapy efficacy. Oral biomarkers can provide valuable information on composition, such as immune cell presence and checkpoint expression. Elevated tumor mutation load is also associated with heightened immunogenicity and ICI responsiveness. Furthermore, the oral microbiota may influence treatment outcomes. Current research aims to identify predictive salivary biomarkers. Initial studies indicate that tumor-derived exosomes and miRNAs present in saliva could identify immunosuppressive pathways and predict ICI response. While tissue-based markers like PD-L1 have limitations, combining multiple oral fluid biomarkers could create a robust panel to guide treatment decisions and advance personalized immunotherapy for head and neck cancer patients.

Immunotherapy emerges as a promising approach, marked by recent substantial progress in elucidating how the host immune response impacts tumor development and its sensitivity to various treatments. Immune checkpoint inhibitors have revolutionized cancer therapy by unleashing the power of the immune system to recognize and eradicate tumor cells. Among these, inhibitors targeting the programmed cell death protein 1 (PD-1) and its ligand (PD-L1) have garnered significant attention due to their remarkable clinical efficacy across various malignancies. This review delves into the mechanisms of action, clinical applications, and emerging therapeutic strategies surrounding PD-1/PD-L1 blockade. We explore the intricate interactions between PD-1/PD-L1 and other immune checkpoints, shedding light on combinatorial approaches to enhance treatment outcomes and overcome resistance mechanisms. Furthermore, we discuss the expanding landscape of immune checkpoint inhibitors beyond PD-1/PD-L1, including novel targets such as CTLA-4, LAG-3, TIM-3, and TIGIT. Through a comprehensive analysis of preclinical and clinical studies, we highlight the promise and challenges of immune checkpoint blockade in cancer immunotherapy, paving the way for future advancements in the field.

Immuno-oncology (IO) is one of the fastest growing therapeutic areas within oncology. IO agents work indirectly via the host's adaptive and innate immune system to recognize and eradicate tumor cells. Despite checkpoint inhibitors being only introduced to the market since 2011, they have become the second most approved product category. Current Food and Drug Administration (FDA)-approved classes of IO agents include: immune checkpoint inhibitors (ICIs), chimeric antigen receptor T-cell therapy (CAR-T), bi-specific T-cell engager (BiTE) antibody therapy, T-cell receptor (TCR) engineered T cell therapy, tumor-infiltrating lymphocyte (TIL) therapy, cytokine therapy, cancer vaccine therapy, and oncolytic virus therapy. Cancer immunotherapy has made progress in multiple cancer types including melanoma, non-small cell lung cancer (NSCLC), renal cell carcinoma (RCC), and urothelial carcinoma; however, several cancers remain refractory to immunotherapy. Future directions of IO include exploration in the neoadjuvant/perioperative setting, combination strategies, and optimizing patient selection through improved biomarkers.

PD1/PD-L1 inhibition (ICi) has recently become a new standard of care for patients with advanced MMR-deficient (MMRd) endometrial cancers. Nevertheless, response to immunotherapy is more complex than the presence of a single biomarker and therefore it remains challenging to predict patients response to ICi beyond MMRd tumors. Elevated PD-L1 expression (CPS ≥ 1) is often used as a prognostic marker as well as a predictive biomarker of response to ICi in different tumor types. In a retrospective, patient derived study, we analyzed PD1- and PD-L1 staining and correlated the results of different scores to clinical data to evaluate the prognostic impact of these scores.

Immunohistochemical analysis of the receptor PD1 and the receptor ligand PD-L1 were performed on TMAs of primary paraffin‑embedded tumor samples. All patients were treated for primary endometrial cancer in the Department of Gynecology and Obstetrics, University Medical Center Schleswig-Holstein, Campus-Lübeck, Germany between the years 2006-2018. The evaluation and determination of the tumor proportion scoring (TPS), the combined positive score (CPS) and the immune cell scoring (IC) was automatically assessed semi-quantitatively, and results were correlated with clinicopathological characteristics and survival.

130 samples were evaluable and 64% showed a positivity (IC > 0) for the receptor PD1 and 56% for the receptor ligand PD-L1. Patients with a PD1 IC Score ≥ 1 showed a significant longer disease-free survival of 140 months (95% confidence interval (CI): 124-158) compared to patients with a lower IC < 1 for PD1 of 89 months (95% confidence interval (CI): 69-110); p = 0.017). Furthermore, the disease-free survival for patients with a CPS ≥ 5 for PD1 was longer (153.7 months (95% confidence interval (CI): 134-173.6) vs. 98.6 months (95% confidence interval (CI): 83-114); p = 0.036). Additionally, a PD1 CPS ≥ 5 showed a better overall survival but the result was not statistically significant. No difference in survival was found between patients with PD-L1 higher or lower than CPS 5.

In this study we pointed out that there are significant clinical differences among several immunohistochemical scoring systems. In our trial, a PD1-positivity with CPS ≥ 5 and IC ≥ 1 were significantly associated to a better disease-free survival while there was no association with TPS. The PD1-IC scoring was associated with MMRd while the TPS scoring was not. Therefore, PD1-IC could be more appropriate for endometrial carcinomas compared to TPS and could also add prognostic information beside the more established PD-L1-staining. Further prospective studies are needed for a validation of these scores in combination with other biomarkers.

Multiple primary malignant tumors refer to the occurrence of two or more primary malignant tumors in the same organ or multiple organs or tissues at the same time or successively in the same patient, and can occur anywhere in the body. The treatment guidelines for patients with multiple primary malignant tumors are currently controversial.

A 51-year-old male patient with liver cancer and portal hypertension received 42 months of co-treatment with atezolizumab and bevacizumab. After that, the disease was rated stable disease. The patient was then diagnosed with gastric cancer. Since the patient was not sensitive to anti-programmed death ligand 1 immunosuppressive agents, a co-treatment with oxaliplatin, tegafur, apatinib, and cadonilimab was selected after multidisciplinary consultation and the patient's agreement. After four cycles of treatment, partial response and stable disease were observed in gastric and liver cancers, respectively. Surgical treatment was performed considering the high-risk factors of gastrointestinal bleeding in patients with gastroesophageal varices. Postoperative pathology showed that the Tumor Regression Grade was 1. Moreover, the genetic testing of postoperative tumor specimens indicated negative programmed death ligand 1 and microsatellite stability. In addition, the latest follow-up indicated an 8 and 40-month progression-free survival in gastric and liver cancer patients, respectively. Currently, the patient is receiving postoperative immunotherapy with cadonilimab.

Cadonilimab not only treats microsatellite stability gastric cancer patients but can also be used for liver cancer treatment.

Gastrointestinal neuroendocrine carcinoma (GI NEC) has a low incidence rate and poor prognosis. Most patients already have metastatic disease when they are diagnosed. Platinum chemotherapy is the main means of treating metastatic GI NECs. There is a lack of effective treatment methods after chemotherapy failure. Therefore, Therefore, selecting appropriate posterior-line treatment programs to improve the prognosis of patients is urgently needed.

A 64-year-old female was diagnosed with stage IV NEC of the rectum due to abdominal pain and rectal bleeding. After multiline chemotherapy, the condition progressed, and the patient was treated with a combination of camrelizumab and surufatinib. The efficacy evaluation revealed partial remission (PR) and stable conditions, with the expression of the tumor marker neuron-specific enolase (NSE) returning to normal. The adverse reactions were controllable, and the overall condition was good, with weight gain achieved in the past four years. Another 51-year-old female experienced recurrence and metastasis of a duodenal NEC after surgery. After multiline chemotherapy, she received sintilimab combined with surufatinib. The curative effect fluctuated between PR and stability. During treatment, she recovered from immune-related diabetes and later died due to deterioration of her condition. During the treatment, the patient's NSE level returned to normal.

The combination of antiangiogenic targeted drugs and immunotherapy provides a new therapeutic approach for the treatment of metastatic GI-NECs.

Over the past few years, immune checkpoint inhibitors resulted in magnificent and durable successes in treating cancer; however, only a minority of patients respond favorably to the treatment due to a broad-spectrum of tumor-intrinsic and tumor-extrinsic factors. With the recent insights gained into the mechanisms of resistance, combination treatment strategies to overcome the resistance and enhance the therapeutic potential of immune checkpoint inhibitors are emerging and showing promising results in both pre-clinical and clinical settings. This has been derived through multiple interconnected mechanisms such as enhancing tumor immunogenicity, improving neoantigen processing and presentation in addition to augmenting T cell infiltration and cytotoxic potentials. In the clinical settings, several avenues of combination treatments involving immune checkpoint inhibitors were associated with considerable improvement in the therapeutic outcome in terms of patient's survival and tumor growth control. This, in turn, increased the spectrum of cancer patients benefiting from the unprecedented and durable effects of immune checkpoint inhibitors leading to their adoption as a first-line treatment for certain cancers. Moreover, the significance of precision medicine in cancer immunotherapy and the unmet demand to develop more personalized predictive biomarkers and treatment strategies are also highlighted in this review.

Triple-negative breast cancer (TNBC) is a highly heterogeneous cancer with substantial recurrence potential. Currently, surgery and chemotherapy are the main treatments for this disease. However, chemotherapy is often limited by several factors, including low bioavailability, significant systemic toxicity, inadequate targeting, and multidrug resistance. Immune checkpoint inhibitors (ICIs), including those targeting programmed death protein-1 (PD-1) and its ligand (PD-L1), have been proven effective in the treatment of various tumours. In particular, in the treatment of TNBC with PD-1/PD-L1 inhibitors, both monotherapy and combination chemotherapy, as well as targeted drugs and other therapeutic strategies, have broad therapeutic prospects. In addition, these inhibitors can participate in the tumour immune microenvironment (TIME) through blocking PD-1/PD-L1 binding, which can improve immune efficacy. This article provides an overview of the use of PD-1/PD-L1 inhibitors in the treatment of TNBC and the progress of multiple therapeutic studies. To increase the survival of TNBC patients, relevant biomarkers for predicting the efficacy of PD-1/PD-L1 inhibitor therapy have been explored to identify new strategies for the treatment of TNBC.

ISG15, an interferon-stimulated ubiquitin-like protein, plays a multifaceted role in tumorigenesis and immune regulation. This study comprehensively evaluates ISG15 as a prognostic biomarker and predictor of immunotherapy response through pan-cancer bioinformatics analysis and experimental validation. By integrating multiomics data from TCGA, GEO, and clinical cohorts, we found that ISG15 is significantly overexpressed in multiple cancers and generally correlates with poor prognosis. Elevated ISG15 expression is associated with increased immune checkpoint gene expression, particularly PD-L1, and immune infiltration, notably M2-like tumor-associated macrophages. Immunohistochemistry and multiplexed immunofluorescence confirmed a strong positive correlation between ISG15, PD-L1, and M2-TAM infiltration in lung and gastric cancer samples. Functional analysis at the single-cell level revealed significant associations between ISG15 and tumor proliferation, angiogenesis, and immune suppression. Immunotherapy cohort analysis demonstrated that tumors with high ISG15 expression responded favorably to PD-L1 inhibitors but exhibited resistance to CTLA-4 blockade, findings further validated in lung cancer patients receiving anti-PD-1 therapy. These results suggest that ISG15 is a promising biomarker for prognosis and immunotherapy response prediction across cancers. Its integration into clinical decision-making may enhance personalized treatment strategies, improve immunotherapy outcomes, and provide new insights into the tumor immune microenvironment, cancer progression, and potential therapeutic targets for future drug development.

Cancer immunotherapy such as immune checkpoint blockade (ICB) therapy has made important breakthroughs in cancer treatment, however, currently only parts of cancer patients benefit from ICB therapy. The suppressive tumor immune microenvironment (TIME) impedes the treatment response of immunotherapy, indicating the necessity to explore new treatment targets. Here, we reported a new potential immunotherapeutic target, Dickkopf-3 (DKK3), for cancer treatment. DKK3 expression is up-regulated in the tumors from multiple cancer types, and high DKK3 expression is associated with worse survival outcome across different cancers. We observed that DKK3 directly inhibits the activation of CD8+ T cells and the Th1 differentiation of CD4+ T cells ex vivo. Also, by establishing four different mouse cancer models, we found that DKK3 blockade triggers effective anti-tumor effects and improve the survival of tumor-bearing mice in vivo. DKK3 blockade also remodels the suppressive TIME of different cancer types, including the increased infiltration of CD8+ T cells, IFN-γ+CD8+ T cells, Th1 cells, and decreased infiltration of M2 macrophages and MDSCs in the TIME. Moreover, we found that combined blockade of DKK3 and PD-1 induces synergistic tumor-control effect in our mouse cancer model. Therefore, our study reveals the impact of DKK3 in the TIME and cancer progression, which suggests that DKK3 is a novel and promising immunotherapeutic target for enhanced cancer immunotherapy.

To develop a positron emission tomography/computed tomography (PET/CT)-based radiomics model for predicting programmed cell death ligand 1 (PD-L1) expression in non-small cell lung cancer (NSCLC) patients and estimating progression-free survival (PFS) and overall survival (OS) in PD-L1-positive patients undergoing first-line immunotherapy.

We retrospectively analysed 143 NSCLC patients who underwent pretreatment 18F-fluorodeoxyglucose (18F-FDG) PET/CT scans, of whom 86 were PD-L1-positive. Clinical data collected included gender, age, smoking history, Tumor-Node-Metastases (TNM) staging system, pathologic types, laboratory parameters, and PET metabolic parameters. Four machine learning algorithms-Bayes, logistic, random forest, and Supportsupport vector machine (SVM)-were used to build models. The predictive performance was validated using receiver operating characteristic (ROC) curves. Univariate and multivariate Cox analyses identified independent predictors of OS and PFS in PD-L1-positive expression patients undergoing immunotherapy, and a nomogram was created to predict OS.

A total of 20 models were built for predicting PD-L1 expression. The clinical combined PET/CT radiomics model based on the SVM algorithm performed best (area under curve for training and test sets: 0.914 and 0.877, respectively). The Cox analyses showed that smoking history independently predicted PFS. SUVmean, monocyte percentage and white blood cell count were independent predictors of OS, and the nomogram was created to predict 1-year, 2-year, and 3-year OS based on these three factors.

We developed PET/CT-based machine learning models to help predict PD-L1 expression in NSCLC patients and identified independent predictors of PFS and OS in PD-L1-positive patients receiving immunotherapy, thereby aiding precision treatment.

BackgroundEpigenetics, encompassing DNA and RNA modifications, has emerged as a prominent area of research in the post-genomic era. Numerous studies have elucidated the impact of epigenetics on tumor regulation. However, the methylation patterns of 5-methylcytosine in cervical cancer as well as its role in the tumor microenvironment and immunotherapy remain poorly understood.MethodsUtilizing a comprehensive dataset encompassing samples from 306 patients with cervical cancer from The Cancer Genome Atlas and Gene Expression Omnibus repositories, we conducted an in-depth analysis to evaluate the potential association between the modification patterns of 5-methylcytosine and the infiltration of cells within the tumor microenvironment, taking into account 11 regulators of 5-methylcytosine modification. Subsequently, we employed stepwise regression and Least Absolute Shrinkage and Selection Operator Cox regression to quantify 5-methylcytosine modification patterns in patients with cervical squamous cell carcinoma and endocervical adenocarcinoma, yielding the 5-methylcytosine score. Our study explored the link between the 5-methylcytosine score and clinical characteristics as well as prognostic outcomes in patients with cervical squamous cell carcinoma and endocervical adenocarcinoma.ResultsA comprehensive analysis of 306 patients with cervical cancer revealed two distinct 5-methylcytosine modification patterns, henceforth labeled as 5-methylcytosine clusters A and B. These clusters exhibited distinct immunological profiles and biological attributes, with 5-methylcytosine cluster A exhibiting a higher degree of immune cell infiltration. Utilizing univariate Cox regression analysis, we identified 367 genes regulated by 5-methylcytosine that were significantly correlated with patient prognosis. This analysis further stratified the samples into three distinct genomic subtypes. Survival analyses indicated that patients belonging to gene cluster C exhibited more favorable survival outcomes than those belonging to gene clusters A and B. Intriguingly, most 5-methylcytosine regulatory factors had higher expression levels in gene cluster B than in gene cluster A. Gene set enrichment analysis of a single sample revealed elevated immune cell infiltration within gene cluster B, indicating a stronger immune response in this cluster. The 5-methylcytosine score feature was utilized to determine the 5-methylcytosine modification pattern in cervical cancer, revealing that patients with low 5-methylcytosine scores exhibited better survival rates, whereas those with high scores had increased mutation frequencies and better treatment responses.ConclusionsThis research underscores the key role of 5-methylcytosine modification patterns in cervical cancer. Analysis of these patterns will deepen our understanding of the cervical cancer tumor microenvironment, paving the way for the development of more refined and effective immunotherapy strategies.

Vaccinia-Related Kinase 2 (VRK2), a member of the vaccinia virus-related protein kinase family, is crucial in regulating apoptosis and tumor cell growth signaling pathways. Despite its established roles in various cancers, investigations into its functions in colorectal cancer have been relatively limited. Utilizing The Cancer Genome Atlas and Genotype-Tissue Expression databases, this study assesses VRK2 expression across 33 cancer types, highlighting significant upregulation and diagnostic relevance, particularly in colorectal cancer, where it marks poor prognosis. VRK2's influence extends across multiple cancer-related signaling pathways, with focused experiments confirming its vital role in the E2F signaling pathway through transcriptomic sequencing and dual-luciferase reporter assays. Deletion of VRK2 markedly inhibits proliferation, cell cycle progression, migration, and tumorigenesis in colorectal cancer cells, whereas overexpression enhances these oncogenic traits. Additionally, VRK2 expression correlates with genomic instability and the tumor microenvironment, influencing antitumor immunity and response to immunotherapy. Importantly, our analysis reveals that VRK2 modulates the chemosensitivity of tumor cells, specifically enhancing resistance to the chemotherapeutic agent 5-FU. These findings underscore VRK2's multifaceted role in promoting colorectal cancer development and suggest its potential as a therapeutic target.

Immune checkpoint therapy (ICT) has significantly impacted the treatment of malignant pleural mesothelioma (MPM). Despite some promising results from combination therapies, nearly half of MPM patients do not benefit, underscoring the urgent need for reliable predictive biomarkers. This study assesses the prognostic value of serum soluble mesothelin-related peptide (SMRP) and PD-L1 levels in MPM patients receiving ICT.

We conducted a retrospective analysis of 125 MPM patients treated with ICT by measuring pre-ICT serum levels of SMRP and PD-L1. We also examined the correlation of these serum levels with tumor mRNA expressions of mesothelin and PD-L1. Both univariable and multivariable Cox regression analyses were used to determine independent prognosticators for overall survival (OS). A prospective ICT clinical trial and our historical cohort were included for validation.

Seventy-seven patients (62%) were treated with either anti-PD-(L)1 monotherapy, and the remaining 38% received combination ICT. Higher pre-ICT SMRP levels were observed in epithelioid MPM compared to nonepithelioid MPM. Serum PD-L1 levels did not differ significantly between the different histologic groups. Univariable analysis identified durable clinical benefit, development of immune-related adverse events, and SMRP levels as significantly associated with OS. Multivariable analysis confirmed SMRP as an independent prognostic factor, with lower levels (≤1.35 nmol/L) correlating with improved OS. The association of high SMRP with worse prognosis was validated in the prospective ICT clinical trial cohort and not in our historical cohort treated without ICT.

SMRP is a promising serum biomarker for predicting survival in MPM patients treated with ICT and warrants prospective investigation.

Immunotherapy and chemoimmunotherapy are standard treatments for non-oncogene-addicted advanced non-small cell lung cancer (NSCLC). Currently, a limited number of biomarkers, including programmed death-ligand 1 (PD-L1) expression, microsatellite instability (MSI), and tumor mutational burden (TMB), are used in clinical practice to predict benefits from immune checkpoint inhibitors (ICIs). It is therefore necessary to search for novel biomarkers that could be helpful to identify patients who respond to immunotherapy. In this context, research efforts are focusing on different cells and mechanisms involved in anti-tumor immune response. Herein, we provide un updated literature review on the role of eosinophils in cancer development and immune response, and the functions of some cytokines, including IL-31 and IL-33, in eosinophil activation. We discuss available data demonstrating a correlation between eosinophils and clinical outcomes of ICIs in lung cancer. In this context, we underscore the role of absolute eosinophil count (AEC) and tumor-associated tissue eosinophilia (TATE) as promising biomarkers able to predict the efficacy and toxicities from immunotherapy. The role of eosinophils and cytokines in NSCLC, treated with ICIs, is not yet fully understood, and further research may be crucial to determine their role as biomarkers of response. Artificial intelligence, through the analysis of big data, could be exploited in the future to elucidate the role of eosinophils and cytokines in lung cancer.

Lung adenocarcinoma (LUAD) is a common histopathological variant of non-small cell lung cancer. Individuals with type 2 diabetes (T2DM) face an elevated risk of developing LUAD. We examined the common genomic characteristics between LUAD and T2DM through bioinformatics analysis.

We acquired the GSE40791, GSE25724, GSE10072, and GSE71416 datasets. Differentially expressed genes (DEGs) were identified through R software, particularly its version 4.1.3 and analyzed via gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Subsequently, we analyzed the relationship between immune cell infiltration and DEGs. we constructed a protein-protein interaction network using STRING and visualized it with Cytoscape. Moreover, gene modules were identified utilizing the MCODE plugin, and hub genes were selected through the CytoHubba plugin. Additionally, we evaluated the predictive significance of hub genes using receiver operating characteristic curves and identified the final central hub genes. Finally, we forecasted the regulatory networks of miRNA and transcription factors for the central hub genes.

A total of 748 DEGs were identified. Analysis of immune infiltration showed a notable accumulation of effector-memory CD8 T cells, T follicular helper cells, type 1 T helper cells, activated B cells, natural killer cells, macrophages, and neutrophils in both LUAD and T2DM. Moreover, these DEGs were predominantly enriched in immune-related pathways, including the positive regulation of I-κB kinase/NF-κB signaling, positive regulation of immunoglobulin production, cellular response to interleukin-7, and cellular response to interleukin-4. The TGF-β signaling pathway was significantly important among them. Additionally, seven hub genes were identified, including ATR, RFC4, MCM2, NUP155, NUP107, NUP85, and NUP37. Among them, ATR, RFC4, and MCM2 were identified as pivotal hub genes. Additionally, hsa-mir147a, hsa-mir16-5p, and hsa-mir-1-3p were associated with LUAD and T2DM. SP1 (specific protein 1) and KDM5A (lysine-specific demethylase 5A) regulated MCM2, ATR, and RFC4.

Our study elucidates the common mechanisms of immune response, TGF-β signaling pathway, and natural killer cells in LUAD and T2DM, and identifies ATR, RFC4, and MCM2 as key potential biomarkers and therapeutic targets for the comorbidity of these two conditions.

Programmed cell death protein 1 (PD-1) plays a critical role in immune tolerance and evasion within the tumor microenvironment, and anti-PD-1 immunotherapy has shown efficacy in treating advanced melanoma. However, response rates vary significantly among patients, necessitating the identification of reliable biomarkers to predict treatment efficacy. Based on within-sample relative expression orderings, we analyzed RNA sequencing data from melanoma patients to construct a predictive model comprising gene pairs associated with treatment response. The model's performance was validated across multiple independent datasets and assessed for correlations with immune infiltration and survival outcomes. The constructed 15-pair model achieved a prediction accuracy of 100% in training datasets and 89.47% in validation sets. Validation in melanoma patients lacking treatment response data revealed significant differences between predicted responders and non-responders across datasets, with the model being an independent prognostic factor. Increased immune cell infiltration was observed in responders, correlating with higher expression levels of key immune checkpoint genes. The relative expression orderings-based model shows promise as a tool for predicting responses to anti-PD-1 therapy in melanoma patients, supporting personalized treatment strategies.

Immune checkpoint inhibitors (ICIs) have improved survival rates in oncology, but there is a rising concern for immune-related adverse health outcomes. Monitoring drug serum concentration would enable tailored dosing, however this strategy has not yet been evaluated for ICIs. Fully automated analyte capture assays with time-resolved fluorometry using protein A as tracer, were developed for three different ICIs; the cytotoxic T lymphocyte Antigen-4 (CTLA4) inhibitor ipilimumab (Yervoy; Bristol-Myers Squibb) and the Programmed Death-1 (PD-1) inhibitors nivolumab (Opdivo; Bristol-Myers Squibb) and pembrolizumab (Keytruda; Merck). Drug trough levels were measured in serum samples from ICI-treated patients. Measuring ranges were 1-100 mg/L for all three drugs. Automation allowed for 110 samples to be analyzed in < 4 h. Median drug trough-levels after 5-7 weeks of treatment were 20 (range <1.0-45) mg/L for ipilimumab (n = 113), 60 (range 14-75) mg/L) for nivolumab (n = 21) and 19 (range 7.4-39) mg/L for pembrolizumab (n = 20). Routine drug concentration monitoring for ipilimumab, nivolumab and pembrolizumab is feasible using fully automated analyte capture assays constructed with commercially available reagents. The large drug serum concentration ranges in samples from real-world patients, should be further investigated to assess the clinical relevance of ICI concentration monitoring.

Major advances have been achieved in the characterization of primary breast cancer genomic profiles. Limited information is available on the genomic profile of tumors originating from different metastatic locations in recurrent/metastatic (R/M) breast cancer, especially in Asian patients. This study aims to decipher the mutational profiles of primary and R/M breast cancer in Chinese patients using next-generation sequencing.

A total of 563 breast cancer patients were enrolled, and 590 tumor tissues and matched peripheral blood samples were collected and subjected to targeted sequencing with a panel of 1,021 cancer-related genes. The mutation spectrum, DNA damage response (DDR) genes, commonly altered signal pathways, and immunotherapy-related markers were compared between primary and R/M breast cancer. The molecular differences between our cohort and the Memorial Sloan Kettering Cancer Center (MSKCC) dataset were also explored.

A total of 361 samples from primary and 229 samples from R/M breast cancer were analyzed. BRCA2, ATRX, and ATM were more frequently observed in R/M lesions among the 36 DDR genes. An ESR1 mutation and PD-L1 and PD-L2 amplification were enriched in R/M breast cancer (all p<0.05). Compared with the MSKCC dataset, we recruited more patients diagnosed at age 50 or younger and more patients with triple-negative breast cancer (TNBC) subtypes. The TNBC patients in our dataset had a higher percentage of PD-L1 amplification in metastasis tumors (p<0.05).

This study revealed the distinctive mutational features of primary and R/M tumors in Chinese breast cancer patients, which are different from those from Western countries. The enrichment of PD-L1 amplification in metastatic TNBC indicates the necessity to re-biopsy metastatic tumors for immunotherapy.

Lung cancer remains a major global health issue, with non-small cell lung cancer (NSCLC) constituting approximately 85% of cases. Ferritinophagy, a pivotal autophagic process in ferroptosis, plays an essential role in tumor initiation and progression. However, the specific contributions of ferritinophagy-related genes (FRGs) to NSCLC pathogenesis remain incompletely understood. In this study, weighted gene co-expression network analysis (WGCNA) was employed to identify key modular genes associated with FRG scores. Genes overlapping between these modules and differentially expressed genes (DEGs) were selected for further investigation. Prognostic genes were identified through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis, with subsequent validation using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) on both clinical samples and the TCGA-NSCLC dataset. A nomogram incorporating clinicopathological features and risk scores was developed to predict patient outcomes. Further analyses focused on functional enrichment, drug sensitivity, and the immune microenvironment. Cross-referencing 2,142 key modular genes with 2,764 DEGs revealed 600 candidate genes. Univariate Cox regression and LASSO analysis of these candidates identified eight prognostic genes: KLK8, MFI2, B3GNT3, MYRF, CREG2, GLB1L3, AHNAK2, and NLRP10. Two distinct risk groups exhibited significant survival differences. Both the risk score and pathological N stage were found to be independent prognostic factors, forming the basis for the nomogram. Notable correlations were observed between certain immune cells, prognostic genes, and immune responses, affecting the efficacy of immunotherapy and drug sensitivity. qRT-PCR confirmed that, except for NLRP10, all prognostic genes exhibited expression patterns consistent with TCGA-NSCLC data. This study highlights the significant role of FRGs in NSCLC prognosis and regulation, offering novel insights for personalized treatment strategies.

A 77-year-old man with large-cell gastric neuroendocrine carcinoma underwent palliative total gastrectomy after 10 cycles of carboplatin and etoposide chemotherapy for severe tumor bleeding. Despite a histological grade 0 therapeutic effect, the remnant lesions were treated with paclitaxel and ramucirumab, but progression occurred after two cycles. Nivolumab monotherapy was then initiated, resulting in complete remission after three cycles. Nivolumab was discontinued because of immune-related psoriasis, but complete remission persisted for at least 16 months. This is the first reported case of nivolumab monotherapy achieving complete remission in gastric neuroendocrine carcinoma with the patient surviving 28 months.

Ovarian tumours are these days one of the biggest oncogynecological problems. In addition to surgery, the treatment of ovarian cancer includes also chemotherapy in which platinum preparations are one of the most used chemotherapeutic drugs. The principle of antineoplastic effects of cisplatin (cis-diamminedichloroplatinum(II), CDDP) is its binding to the DNA and the formation of adducts. While DNA adducts induce the process of apoptosis, or inhibit the process of DNA replication, which prevents further division of tumour cells, various molecular mechanisms can reverse this process. On the other hand, with increasing scientific knowledge, it is becoming clearer that chemotherapy resistance is a very complex process. In this regard, factors and the amount of their expression may regulate the effect of resistance to chemotherapy. This review focuses on new molecular mechanisms and factors such as mitochondrial dynamics, epithelial-mesenchymal transition (EMT), cluster of differentiation, exosomes and others, that could be involved in the emergence of CDDP resistance.

The interactions of drugs with the host's immune cells determine the drug's efficacy and adverse effects in patients. Nonsteroidal Anti-Inflammatory Drugs (NSAID), such as corticosteroids, NSAIDs, and immunosuppressants, affect the immune cells and alter the immune response. Molecularly, drugs can interact with immune cells via cell surface receptors, changing the antigen presentation by modifying the co-stimulatory molecules and interacting with the signaling pathways of T cells, B cells, Natural killer (NK) cells, mast cells, basophils, and macrophages. Immunotoxicity, resulting from drug-induced changes in redox status, generation of Reactive Oxygen Species (ROS)/Reactive Nitrogen Species (RNS), and alterations in antioxidant enzymes within immune cells, leads to immunodeficiency. This, in turn, causes allergic reactions, autoimmune diseases, and cytokine release syndrome (CRS). The treatment options should include the evaluation of immune status and utilization of the concept of pharmacogenomics to minimize the chances of immunotoxicity. Many strategies in redox, like targeting the redox pathway or using redox-active agents, are available for the modulation of the immune system and developing drugs. Case studies highlight significant drug-immune cell interactions and patient outcomes, underscoring the importance of understanding these complexities. The future direction focuses on the drugs to deliver antiviral therapy, new approaches to immunomodulation, and modern technologies for increasing antidote effects with reduced toxicity. In conclusion, in-depth knowledge of the interaction between drugs and immune cells is critical to protect the patient from the adverse effects of the drug and improve therapeutic outcomes of the treatment process. This review focuses on the multifaceted interactions of drugs and their consequences at the cellular levels of immune cells.