Tumour mutational burden as a biomarker for immunotherapy: Current data and emerging concepts

Diverse RNA methylation patterns in neutrophils: key drivers in hepatocellular carcinoma

BACKGROUND

Neutrophils, crucial in the immune system, have recently been implicated in promoting malignancy. RNA methylation, an essential epigenetic feature, plays a key role in tumor microenvironment (TME) reprogramming. However, the relationship between neutrophils and RNA methylation in hepatocellular carcinoma (HCC) remains unclear.

METHODS

We analyzed single-cell sequencing data from HCC, focusing on cell subtype and TME construction. RNA methylation "writers" were selected, and their expression in neutrophils was evaluated. Two neutrophil subtypes (high/low RNA methylation) were identified. Differentially expressed genes (DEGs) between these subtypes were confirmed, leading to the identification of 6 molecular subtypes via consensus clustering. A prognostic scoring system was developed using LASSO Cox regression, resulting in a novel neutrophil RNA methylation (NRM) scoring system to assess TME heterogeneity and clinical features.

RESULTS

TRPM3, specifically expressed in HCC-infiltrating neutrophils, may regulate RNA modification in tumor pathogenesis. HCC patients were stratified into low/high-NRM score groups, further refined into an advanced NRM (a-NRM) score by incorporating lncRNA data. High a-NRM scores correlated with advanced TNM stage, higher pathological grade, and increased suppressive immune cells. A nomogram incorporating the a-NRM score demonstrated a concordance index indicative of good predictive performance.

CONCLUSIONS

The a-NRM score is a reliable predictor of prognosis and could guide treatment selection in HCC patients, enhancing clinical response to immunotherapy. TRPM3 also presents as a potential therapeutic target in HCC.

Pan‑cancer analysis of oncogene SFXN1 to identify its prognostic and immunological roles in lung adenocarcinoma

As cancer incidence and mortality rates continue to rise, the urgency for research in this field has increased globally. Sideroflexin 1 (SFXN1), a pivotal member of the SFXN protein family, serves a crucial role in transporting serine to mitochondria and participates in one‑carbon metabolism, thereby influencing cell proliferation and differentiation. While SFXN1 is linked to lung cancer and glioma, its role in other malignancies remains largely unexplored. Utilizing The Cancer Genome Atlas, Human Protein Atlas, Gene Expression Profiling Interactive Analysis and University of Alabama at Birmingham Cancer Data Analysis Portal databases, the present study investigated the expression patterns, prognostic implications and association with immune cell infiltration of SFXN1. The present findings revealed that SFXN1 was differentially expressed across various tumor types, and exhibited significant associations with clinicopathological features and patient prognosis. Through immune infiltration analysis, a significant correlation between SFXN1 and T cells, B cells and immune checkpoint genes was established in numerous tumor types. Notably, loss‑of‑function experiments demonstrated that silencing of SFXN1 decreased cell proliferation, migration and invasion, while simultaneously increasing apoptosis in lung adenocarcinoma cells. Collectively, these findings suggested that SFXN1 expression could potentially serve as a biomarker for tumor diagnosis and prognosis, also emerging as a novel therapeutic target in cancer immunotherapy. The present study highlights the critical role of SFXN1 in cancer biology and paves the way for future translational efforts aimed at leveraging its potential in clinical oncology.

Identification and dissection of prostate cancer grounded on fatty acid metabolism-correlative features for predicting prognosis and assisting immunotherapy

BACKGROUND

Fatty acid metabolism (FAM) plays a critical role in tumor progression and therapeutic resistance by enhancing lipid biosynthesis, storage, and catabolism. Dysregulated FAM is a hallmark of prostate cancer (PCa), enabling cancer cells to adapt to extracellular signals and metabolic changes, with the tumor microenvironment (TME) playing a key role. However, the prognostic significance of FAM in PCa remains unexplored.

METHODS

We analyzed 309 FAM-related genes to develop a prognostic model using least absolute shrinkage and selection operator (LASSO) regression based on The Cancer Genome Atlas (TCGA) database. This model stratified PCa patients into high- and low-risk groups and was validated using the Gene Expression Omnibus (GEO) database. We constructed a nomogram incorporating risk score, clinical variables (T and N stage, Gleason score, age), and assessed its performance with calibration curves. The associations between risk score, tumor mutation burden (TMB), immune checkpoint inhibitors (ICIs), and TME features were also examined. Finally, a hub gene was identified via protein-protein interaction (PPI) networks and validated.

RESULTS

The risk score was an independent prognostic factor for PCa. High-risk patients showed worse survival outcomes but were more responsive to immunotherapy, chemotherapy, and targeted therapies. A core gene with high expression correlated with poor prognosis, unfavorable clinicopathological features, and immune cell infiltration.

CONCLUSION

These findings reveal the prognostic importance of FAM in PCa, providing novel insights into prognosis and potential therapeutic targets for PCa management.

Revolutionary Cancer Therapy for Personalization and Improved Efficacy: Strategies to Overcome Resistance to Immune Checkpoint Inhibitor Therapy

Cancer remains a significant public health issue worldwide, standing as a primary contributor to global mortality, accounting for approximately 10 million fatalities in 2020 [...].

Prognostic Biomarkers in Evolving Melanoma Immunotherapy

Melanoma, a highly aggressive form of skin cancer, has seen significant advancements in treatment through the introduction of immunotherapy. However, the variability in patient responses underscores the need for reliable biomarkers to guide treatment decisions. This article reviews key biomarkers in melanoma immunotherapy, such as PD-L1 expression, tumor mutational burden (TMB), and gene expression profiles (GEPs). It also explores emerging biomarkers, including LAG-3 expression, immune cell phenotyping in tissue and blood, gut microbiota, and circulating tumor DNA (ctDNA). Notably, ctDNA may offer valuable insights into the efficacy of T cell-engaging bispecific molecules, such as tebentafusp. The review provides a comprehensive overview of the evolving landscape of melanoma biomarkers, their role in personalizing treatment, and future research directions, including neoadjuvant immune checkpoint inhibition.

Microfluidic Systems: Recent Advances in Chronic Disease Diagnosis and Their Therapeutic Management

Microfluidics has advanced the area of diagnostics during the past ten years by offering fresh approaches that weren't achievable with traditional detection and treatment techniques. High-throughput operations can be carefully controlled by using microfluidics and are very cost-effective too. It has been accepted to be a quick and effective method for controlled medication delivery, biological sample preparation, and analysis. This new technology has made it possible to create a wide range of micro and nanocarriers for poorly soluble medications, which has many advantages over traditional drug delivery techniques. Furthermore, a targeted medication delivery system utilizing microfluidic technology can be developed to enhance the drug's local bioavailability. Over the years, extensive R&D in microfluidic technology has led to the creation of various advanced applications in both laboratory and consumer biotechnology. Miniaturized genetic and proteasome analyzers, cell culture and control platforms, biosensors, disease detection, optical imaging devices, diagnostic advanced drugs, drug delivery schemes, and innovative products are some of the advanced applications of the microfluidics system. Also, these are highly adaptable microfluidic tools for disease detection and organ modeling, as well as transduction devices used in biomedical applications to detect biological and chemical changes. Beyond the specialized difficulties in studying cell-cell interactions, microfluidics has several difficulties in biomedical applications, especially for diagnostic devices where minute interactions can lead to imprecise evaluations. Assay function can be significantly changed by the way plastics, adhesives, and other materials interact. Therefore, the foundation of microfluidic technology needs to be grounded in real-world uses that can be produced on a big scale and at a reasonable cost. Further, it is a very interdisciplinary field that requires the collaboration of professionals in fluidics, assay science, materials science, and instrumentation to provide devices with the proper and needed functionality. In this article, we have discussed the advanced disease diagnosis and their therapeutic management which will help to understand the current scenario in the field of microfluidics diagnosis and will fill knowledge about the 'gap' in the system.

Pan-cancer analysis reveals SMARCAL1 expression is associated with immune cell infiltration and poor prognosis in various cancers

Although immune checkpoint inhibition in particular has shown promise in cancer immunotherapy, it is not always efficient. Recent studies suggest that SMARCAL1 may play a role in tumor immune evasion, yet its pan-cancer role is unclear. We conducted a comprehensive analysis of SMARCAL1 using TCGA, GTEx, and CCLE databases, evaluating its expression, genetic alterations, epigenetic modifications, and their clinical correlations across 33 cancer types. Our findings indicate that SMARCAL1 is overexpressed in several cancers, such as Glioma, LUAD, KIRC, and LIHC, impacting prognosis. Elevated SMARCAL1 is linked to poor outcomes in Glioma, LUAD, and LIHC but correlates with better survival in KIRC. We also found significant associations between SMARCAL1 expression and DNA methylation in 13 cancers. Furthermore, SMARCAL1 expression correlates with immune infiltration, suggesting it as a potential therapeutic target in cancer immunotherapy. This study underscores the need for further research on SMARCAL1 to enhance immunotherapeutic strategies.

Predicting immunotherapy prognosis and targeted therapy sensitivity of colon cancer based on a CAF-related molecular signature

The role of cancer-associated fibroblasts (CAFs) in modulating the tumor microenvironment (TME) is gaining attention, yet their impact on prognosis and therapeutic response in colon cancer remains unclear. Here, we identified genes associated with CAF infiltration via weighted gene co-expression network analysis (WGCNA) utilizing data from The Cancer Genome Atlas (TCGA) and GSE39582 cohorts. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used to construct CAF molecular signatures (CAFscore). Patients were categorized into high and low CAFscore groups to analyze clinicopathological traits, somatic mutations, immune evasion, and treatment responses. In this study, a total of 244 genes were correlated with CAF infiltration, with 11 linked to overall survival. Notably, FSTL3, CRIP2, and SLC2A3 were selected for the CAFscore. A higher CAFscore was associated with poorer prognoses, increased malignancy, and therapeutic resistance, particularly among patients with high tumor mutation burden and microsatellite instability. Furthermore, elevated FSTL3 expression was associated with reduced CD8+ T cell infiltration, indicating a suppressive TME. Mechanistically, CAFs may promote immune evasion via NAMPT ligand-receptor interactions based on single-cell RNA sequencing data. Thus, the CAFscore is crucial for personalizing treatment strategies and identifying patients who require more aggressive management.

Remodelling of the immune landscape by IFNγ counteracts IFNγ-dependent tumour escape in mouse tumour models

Loss of IFNγ-sensitivity by tumours is thought to be a mechanism enabling evasion, but recent studies suggest that IFNγ-resistant tumours can be sensitised for immunotherapy, yet the underlying mechanism remains unclear. Here, we show that IFNγ receptor-deficient B16-F10 mouse melanoma tumours are controlled as efficiently as WT tumours despite their lower MHC class I expression. Mechanistically, IFNγ receptor deletion in B16-F10 tumours increases IFNγ availability, triggering a remodelling of the immune landscape characterised by inflammatory monocyte infiltration and the generation of 'mono-macs'. This altered myeloid compartment synergises with an increase in antigen-specific CD8+ T cells to promote anti-tumour immunity against IFNγ receptor-deficient tumours, with such an immune crosstalk observed around blood vessels. Importantly, analysis of transcriptomic datasets suggests that similar immune remodelling occurs in human tumours carrying mutations in the IFNγ pathway. Our work thus serves mechanistic insight for the crosstalk between tumour IFNγ resistance and anti-tumour immunity, and implicates this regulation for future cancer therapy.

Immune biomarkers and predictive signatures in gastric cancer: Optimizing immunotherapy responses

Gastric cancer is a malignant disease with a poor prognosis and few therapeutic options once it has advanced. Immunotherapy using ICIs has emerged as a viable therapeutic method; nevertheless, reliable immunological biomarkers are required to identify who may benefit from these therapies. It focuses on key immune biomarkers and predictive signatures in gastric cancer, such as PD-L1 expression, microsatellite instability (MSI), tumor mutational burden (TMB), and Epstein-Barr virus (EBV) status, to optimize gastric cancer patients' immunotherapy responses. PD-L1 expression is a popular biomarker for ICI effectiveness. Tumors with high MSI-H and TMB are the most susceptible to ICIs because they are highly immunogenic. EBV-positive stomach tumors are highly immunogenic, and immunotherapy has a high response rate. Combining composite biomarker panels with multi-omics-based techniques improved patient selection accuracy. In recent years, machine learning models have been integrated into next-generation sequencing. Dynamic, real-time-monitorable biomarkers for real-time immune response monitoring are also being considered. Thus, enhancing biomarker-driven immunotherapy is critical for improving clinical outcomes with gastric cancer. There is still more work to be done in this field, and verifying developing biomarkers will be an important component in the future of customized cancer therapy.

Immunotherapy for Limited-Stage Small Cell Lung Cancer: Innovative Treatments and Future Perspectives

BackgroundLimited-stage small cell lung cancer (LS-SCLC) is a highly aggressive tumor characterized by a poor prognosis. While concurrent chemoradiotherapy (CCRT) remains the standard treatment, the high rates of recurrence and poor long-term survival highlight the pressing need for novel therapeutic approaches.PurposeIn recent years, the introduction of immunotherapy, particularly immune checkpoint inhibitors (ICIs), has opened new avenues for the treatment of LS-SCLC. This review highlights the clinical advancements of ICIs in CCRT, consolidation therapy, and neoadjuvant therapy, emphasizing their potential to improve progression-free survival (PFS) and overall survival (OS). This review also discusses management of immunotherapy-related side effects.Research DesignThis is a review article that synthesizes recent research findings on immunotherapy for LS-SCLC.Study SampleNot applicable (review of existing literature).Data Collection and/or AnalysisThis review summarizes key studies exploring the application of immunotherapy in limited-stage small cell lung cancer.Additionally, it examines the role of the tumor microenvironment, tumor mutation burden (TMB), and Programmed cell death 1 ligand 1(PD-L1) as biomarkers for predicting the efficacy of immunotherapy.ResultsThis review emphasizes their potential to improve PFS and OS.ConclusionsDespite the significant advancements in research, the use of ICIs in LS-SCLC continues to face challenges, including the identification of optimal treatment regimens, validation of long-term efficacy, and development of personalized predictive biomarkers. Future research should prioritize large-scale, multicenter clinical trials to refine combination therapy strategies, establish customized treatment approaches, and enhance patient outcomes.

PD-L1 as a Biomarker in Gastric Cancer Immunotherapy

Combining chemotherapy with immune checkpoint inhibitors (ICIs) that target the programmed death-1 (PD-1) protein has been shown to be a clinically effective first-line treatment for human epidermal growth factor receptor 2 (HER2)-negative and -positive advanced or metastatic gastric cancer (GC). Currently, PD-1 inhibitors combined with chemotherapy are the standard treatment for patients with HER2-negative/positive locally advanced or metastatic GC. Programmed death-ligand 1 (PD-L1) expression, as assessed using immunohistochemistry (IHC), is a crucial biomarker for predicting response to anti-PD-1/PD-L1 agents in various solid tumors, including GC. In GC, the PD-L1 IHC test serves as a companion or complementary diagnostic test for immunotherapy, and an accurate interpretation of PD-L1 status is essential for selecting patients who may benefit from immunotherapy. However, PD-L1 IHC testing presents several challenges that limit its reliability as a biomarker for immunotherapy. In this review, we provide an overview of the current practices of immunotherapy and PD-L1 testing in GC. In addition, we discuss the clinical challenges associated with PD-L1 testing and its future use as a biomarker for immunotherapy. Finally, we present prospective biomarkers currently under investigation as alternative predictors of immunotherapy response in GC.

Construction of molecular subtype and prognostic model for gastric cancer based on nucleus-encoded mitochondrial genes

Gastric cancer (GC) is a common digestive system cancer, characterized by a significant mortality rate. Mitochondria is an indispensable organelle in eukaryotic cells. It was previously revealed that a series of nucleus-encoded mitochondrial genes (NMG) mutations and dysfunctions potentially contribute to the initiation and progression of GC. However, the correlation between NMG mutations and survival outcomes for GC patients is still unclear. In this study, NMG expression profile and clinical information in GC samples were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Through consistent clustering and functional enrichment analysis, we have identified three NMG clusters and three gene clusters that are associated with patterns of immune cell infiltration. Prognostic genes were identified through Univariate Cox regression analysis. The principal component analysis was conducted to set up a scoring system. Subsequently, the Single‑cell RNA sequencing (scRNA-seq) data of GC patients and cancer cell drug sensitivity data were retrieved from the GEO database. Patients with high NMG scores exhibited increased microsatellite instability status and a heightened tumor mutation rate compared to those with low NMG scores. Survival analysis revealed that GC samples with high NMG scores could achieve a better prognosis. Additionally, These patients were observed to be more responsive to immunotherapy. Moreover, we delved into prognostic genes at the level of single cells, revealing that MRPL4 and MRPL37 exhibit high expression in epithelial cells, while TPM1 demonstrates high expression in tissue stem cells. Utilizing cancer cell drug sensitivity data from the Drug Sensitivity in Cancer (GDSC) database, we noted a heightened sensitivity to chemotherapy in the high NMG group. Furthermore, we discovered a significant enrichment of cuproptosis-related genes in clusters with high NMG scores. Consequently, employing the scoring system could facilitate the prediction of GC patients' sensitivity to cuproptosis-induced therapy. Our study confirmed the potency of this scoring system as a therapeutic response biomarker for gastric cancer, potentially informing clinical treatment strategies.

A comprehensive and systematic analysis of Dihydrolipoamide S-acetyltransferase (DLAT) as a novel prognostic biomarker in pan-cancer and glioma

Background

Dihydrolipoamide S-acetyltransferase (DLAT) is a subunit of the pyruvate dehydrogenase complex (PDC), a rate-limiting enzyme complex, that can participate in either glycolysis or the tricarboxylic acid cycle (TCA). However, the pathogenesis is not fully understood. We aimed to perform a more systematic and comprehensive analysis of DLAT in the occurrence and progression of tumors, and to investigate its function in patients' prognosis and immunotherapy.

Methods

The differential expression, diagnosis, prognosis, genetic and epigenetic alterations, tumor microenvironment, stemness, immune infiltration cells, function enrichment, single-cell analysis, and drug response across cancers were conducted based on multiple computational tools. Additionally, we validated its carcinogenic effect and possible mechanism in glioma cells.

Results

We exhibited that DLAT expression was increased in most tumors, especially in glioma, and affected the survival of tumor patients. DLAT was related to RNA modification genes, DNA methylation, immune infiltration, and immune infiltration cells, including CD4+ T cells, CD8+ T cells, Tregs, and cancer-associated fibroblasts. Single-cell analysis displayed that DLAT might regulate cancer by mediating angiogenesis, inflammation, and stemness. Enrichment analysis revealed that DLAT might take part in the cell cycle pathway. Increased expression of DLAT leads tumor cells to be more resistant to many kinds of compounds, including PI3Kβ inhibitors, PKC inhibitors, HSP90 inhibitors, and MEK inhibitors. In addition, glioma cells with DLAT silence inhibited proliferation, migration, and invasion ability, and promoted cell apoptosis.

Conclusion

We conducted a comprehensive analysis of DLAT in the occurrence and progression of tumors, and its possible functions and mechanisms. DLAT is a potential diagnostic, prognostic, and immunotherapeutic biomarker for cancer patients.

Perioperative immunotherapy for patients with EGFR mutant non-small cell lung cancer: Unexpected potential benefits

Given that immunotherapy has resulted in a significant overall survival (OS) benefit in advanced-stage disease, it is of notable interest to determine the effectiveness of these agents in early-stage non-small cell lung cancer (NSCLC). The potential exists for the immunotherapeutic approach in early-stage NSCLC to mirror the paradigm seen in advanced NSCLC, wherein survival enhancements have notably benefited the majority of patients. However, their performance in early-stage epidermal growth factor receptor (EGFR) mutant NSCLC is controversial. In the limited studies that included patients with EGFR mutation status, we found unexpected, good survival benefits of perioperative immune checkpoint inhibitors (ICIs) in resectable EGFR-positive NSCLC, which is controversial with those in advanced EGFR-mutant NSCLC. It is possible because of the shift toward immunosuppression that the immune environment undergoes during tumor progression. In the early disease stages, the anti-tumor immune response can be activated with fewer hindrances. In the context of EGFR mutant tumors, intratumor genetic heterogeneity can generate treatment-sensitive and -resistant subclones. The subclonality of the resistant subclone is pivotal in therapy response, with tyrosine kinase inhibitors (TKIs) selectively controlling EGFR-mutant cell proliferation and "competitive release" potentially explaining lower pathological responses in adjuvant TKIs trials. This review delves into emerging data on perioperative treatment modalities for early-stage EGFR mutant NSCLC, exploring unique mechanisms and predictive biomarkers to guide perioperative management strategies.

SG-Fusion: A swin-transformer and graph convolution-based multi-modal deep neural network for glioma prognosis

The integration of morphological attributes extracted from histopathological images and genomic data holds significant importance in advancing tumor diagnosis, prognosis, and grading. Histopathological images are acquired through microscopic examination of tissue slices, providing valuable insights into cellular structures and pathological features. On the other hand, genomic data provides information about tumor gene expression and functionality. The fusion of these two distinct data types is crucial for gaining a more comprehensive understanding of tumor characteristics and progression. In the past, many studies relied on single-modal approaches for tumor diagnosis. However, these approaches had limitations as they were unable to fully harness the information from multiple data sources. To address these limitations, researchers have turned to multi-modal methods that concurrently leverage both histopathological images and genomic data. These methods better capture the multifaceted nature of tumors and enhance diagnostic accuracy. Nonetheless, existing multi-modal methods have, to some extent, oversimplified the extraction processes for both modalities and the fusion process. In this study, we presented a dual-branch neural network, namely SG-Fusion. Specifically, for the histopathological modality, we utilize the Swin-Transformer structure to capture both local and global features and incorporate contrastive learning to encourage the model to discern commonalities and differences in the representation space. For the genomic modality, we developed a graph convolutional network based on gene functional and expression level similarities. Additionally, our model integrates a cross-attention module to enhance information interaction and employs divergence-based regularization to enhance the model's generalization performance. Validation conducted on glioma datasets from the Cancer Genome Atlas unequivocally demonstrates that our SG-Fusion model outperforms both single-modal methods and existing multi-modal approaches in both survival analysis and tumor grading.

SPECC1 as a pan-cancer biomarker: unraveling its role in drug sensitivity and resistance mechanisms

Previous studies have shown a relationship between SPECC1 and the prognosis of breast cancer, indicating a potential function for SPECC1 in the initiation and progression of cancer. However, the role played by SPECC1 in other tumors is not yet known. Therefore, we used bioinformatics techniques to conduct a thorough investigation into the possible mechanism of SPECC1 in pan-cancer, analyzing data reported in the literature as well as databases such as GTEx and CCLE, cBioportal, TCGA, and UCSC XENA. Comparing the results with matching normal tissues, the majority of cancers, including pancreatic adenocarcinoma (PAAD) and breast invasive carcinoma (BRCA), exhibited higher levels of SPECC1, while hepatocellular carcinoma (HCC) showed lower expression levels. SPECC1 was also found to be genetically mutated in endometrial cancer, sarcoma, and esophageal cancer. The prognosis of lung adenocarcinoma, kidney papillary cell carcinoma, and breast cancer is highly correlated with dysregulation of SPECC1 expression. This work helps guide clinical therapy by highlighting the sensitivity of tumor-treating medicines and the prognostic importance of SPECC1 in various malignancies. KEGG pathway enrichment analysis revealed focused adhesion, collagen-containing extracellular matrix (collagen), and the primary enrichment domains for SPECC1-related genes. These findings were obtained through gene annotation (GO) examination of SPECC1 expression. Primary mediators of the cytokine-cytokine receptor interaction include PICOC1-associated genes, cell-substrate junction genes, and extracellular matrix containing collagen. PICOC1-associated genes primarily mediate the PI3K-AKT signaling pathway. Drug sensitivity assay showed that SPECC1 high-expressing cell lines were more sensitive to docetaxel, doxorubicin, etc. In conclusion, the current study shows how SPECC1 is expressed in different cancers and how this expression relates to the prognosis of the tumor. It also revealed the mutations and copy number variations of SPECC1 in various tumors and its potential involvement in cellular pathway regulatory networks and cytological processes. This study examines the relationship between immune genes, cellular infiltration, and immunological scores in the tumor microenvironment, which explain the severity of the disease. This study looks at the response of SPEC1 expression to anticancer therapy. Explains the prognostic significance and drug response of SPECC-1.

Comprehensive Analysis of NADH:Ubiquinone Oxidoreductase Subunit B3 in Gynecological Tumors and Identification of Its Natural Inhibitor Wedelolactone

The aim of this study was to explore the role of NADH:ubiquinone oxidoreductase subunit B3 (NDUFB3) in human gynecological malignancies and to screen potential natural compounds targeting it. GEPIA and HPA databases were used to study the expression characteristics of NDUFB3. GO and KEGG enrichment analyses were performed using the R software clusterProfiler package. GSEA for NDUFB3 was performed using the LinkedOmics database. Natural compounds targeting NDUFB3 were screened by virtual screening and molecular docking. After NDUFB3 was depleted or wedelolactone treatment, cell proliferation was detected by CCK-8 assay. The production of reactive oxide species (ROS) in tumor cells was detected by dihydroethidium fluorescent probe. The cell cycle and apoptosis were evaluated by flow cytometry. It was revealed that NDUFB3 was highly expressed in ovarian cancer (OV), uterine corpus endometrial carcinoma (UCEC), and cervical squamous cell carcinoma (CESC). NDUFB3 expression was associated with multiple immunomodulators in CESC, OV, and UCEC. NDUFB3 was predicted to modulate MAPK signaling pathways in CESC, OV, and UCEC. Knocking down NDUFB3 inhibited the proliferation of CESC, OV, and UCEC cells, increased intracellular ROS production, and induced cell cycle arrest and apoptosis. Wedelolactone was a potential small molecule with a strong ability to bind with the active pocket of NDUFB3, and wedelolactone could kill CESC, OV, and UCEC cells partly via NDUFB3. In conclusion, NDUFB3 may be a potential biomarker and a new target for gynecological tumors, and wedelolactone may exert antitumor activity via targeting NDUFB3.

Establishing a predictive model for tumor mutation burden status based on 18F-FDG PET/CT and clinical features of non-small cell lung cancer patients

Background

Tumor mutation burden (TMB) has emerged as a promising biomarker for immune checkpoint inhibitors (ICI) response, but its detection through whole exome sequencing (WES) is costly and invasive. This study aims to establish a predictive model for TMB using baseline metabolic parameters (MPs) of 18F-fluorodeoxyglucose (FDG) uptake on positron emission tomography/computed tomography (PET/CT) and clinical features in non-small cell lung cancer (NSCLC) patients, potentially offering a non-invasive and cost-effective method to predict TMB status.

Methods

A total of 223 NSCLC patients with baseline 18F-FDG PET/CT scans and TMB detection results were retrospectively enrolled from January 2019 to September 2023, and were divided into two groups: TMB-high (≥4 mutations/Mb, 96 patients) and TMB-low (<4 mutations/Mb, 127 patients). Twelve clinical features and five PET parameters were assessed. Univariate analysis was conducted in all patients to reveal the preliminary associations between variables and TMB status. All patients were randomly divided into a training set (n=135) and a validation set (n=88). Feature selection was performed using lasso regression and logistic regression analyses. A predictive model and nomogram were established with the features selected above. Decision curve analysis (DCA) was performed to assess the clinical utility of the developed model.

Results

Two clinical features and two PET parameters were identified through lasso regression and logistic regression analysis including pathology type, cancer antigen 125 (CA125) level, maximum standardized uptake value (SUVmax), and metabolic tumor volume (MTV). The predictive model exhibited an area under the curve (AUC) of 0.822 [95% confidence interval (CI), 0.751-0.894], and internal validation yielded an AUC of 0.822 (95% CI, 0.731-0.912). The model was well-calibrated. The developed nomogram, incorporating the four selected variables, showed promising potential in evaluating TMB status in NSCLC patients.

Conclusions

In this study, a predictive model combining 18F-FDG PET/CT and clinical features of NSCLC patients effectively distinguished between TMB-high and TMB-low status. The nomogram generated from this model holds significant promise for predicting TMB status, offering valuable insights for clinical decision-making.

Personalized Immunotherapy Achieves Complete Response in Metastatic Adenoid Cystic Carcinoma Despite Lack of Conventional Biomarkers

There is currently no effective treatment strategy for recurrent/metastatic adenoid cystic carcinoma (R/M ACC). Furthermore, recent single-agent and combination immunotherapy trials have failed in unselected ACC cohorts, unlike non-ACC salivary gland cancers. Genomic profiling revealed no actionable targets but NOTCH1 and KDM6A frameshift and CTCF splice site mutations (no MYB/L fusion) with a low tumor mutational burden (TMB), microsatellite stable (MSS) and negative programmed death ligand 1 (PD-L1) were observed. We recommended an anti-programmed cell death protein 1 (anti-PD-1) plus anti-Cytotoxic T-lymphocyte-associated protein 4 (anti-CTLA-4) combination based on TMB 2-fold greater-than-median TMB in ACC, tumor harboring multiple immunogenic frameshift or splice site mutations, and PD-L1 negativity. Accordingly, we achieved a complete response in a radiotherapy (RT) and chemotherapy (CT)-refractory patient with locally recurrent lacrimal gland (LG) ACC and lung metastasis following personalized immunotherapy in combination with integrative therapeutics. Therefore, it is crucial to assess not only conventional immune biomarkers but also patient-specific parameters, especially in "immune-cold" cancer types.

An integrative pan-cancer analysis of MASP1 and the potential clinical implications for the tumor immune microenvironment

Mannose-binding lectin-associated serine protease 1 (MASP1) plays a crucial role in the complement lectin pathway and the mediation of immune responses. However, comprehensive research on MASP1 across various cancer types has not been performed to date. This study aimed to evaluate the significance of MASP1 in pan-cancer. The Cancer Genome Atlas (TCGA), UCSC Xena and Genotype Tissue Expression (GTEx) databases were used to evaluate the expression profiles, genomic features, prognostic relevance, and immune microenvironment associations of MASP1 across 33 cancer types. We observed significant dysregulation of MASP1 expression in multiple cancers, with strong associations between MASP1 expression levels and diagnostic value as well as patient prognosis. Mechanistic insights revealed significant correlations between MASP1 levels and various immunological and genomic factors, including tumor-infiltrating immune cells (TIICs), immune-related genes, mismatch repair (MMR), tumor mutation burden (TMB), and microsatellite instability (MSI), highlighting a critical regulatory function of MASP1 within the tumor immune microenvironment (TIME). In vitro and in vivo experiments demonstrated that MASP1 expression was markedly decreased in liver hepatocellular carcinoma (LIHC). Moreover, the overexpression of MASP1 in hepatocellular carcinoma (HCC) cell lines significantly inhibited their proliferation, invasion and migration. In conclusion, MASP1 exhibits differential expression in the pan-cancer analyses and might play an important role in TIME. MASP1 is a promising prognostic biomarker and a potential target for immunological research, particularly in LIHC.

WD repeat domain 43 as a new predictive indicator and its connection with tumor immune cell infiltration in pan-cancer

BACKGROUND

WD repeat domain 43 (WDR43) is a protein component that encodes WD-repeats and is involved in ribosome biogenesis. However, little is known about the role of WDR43 in cancer prognosis and immune modulation.

METHODS

In this study, we analyzed the expression and prognostic significance of WDR43 in pan-cancer using the Cancer Genome Atlas, the Genotype-Tissue Expression, and the Human Protein Atlas. We also examined the differential expression of WDR43 in liver hepatocellular carcinoma (LIHC) and adjacent tissues of 48 patients using immunohistochemistry. Additionally, we investigated the correlation between WDR43 and clinical characteristics, gene alterations, tumor mutation burden, microsatellite instability, mismatch repair, tumor microenvironment, immune infiltrating cells, and immune-related genes using bioinformatics methods. Gene set enrichment analysis was conducted, and potential biological mechanisms were identified.

RESULTS

Immunohistochemistry staining showed that WDR43 was overexpressed in LIHC among 48 patients. Upregulation of WDR43 was associated with unfavorable prognosis, including overall survival in various types of cancer such as LIHC, uterine corpus endometrial cancer, head and neck squamous cell carcinoma, and pancreatic adenocarcinoma. Differential expression of WDR43 was significantly correlated with microsatellite instability, mismatch repair, and immune cell infiltration. Gene ontology annotation analysis revealed that these genes were significantly enriched in immune-related functions, including immune response, immune regulation, and signaling pathways.

CONCLUSION

We conducted a thorough investigation of the clinical features, phases of tumor development, immune infiltration, gene mutation, and functional enrichment analysis of WDR43 in various types of cancer. This research offers valuable insight into the significance and function of WDR43 in clinical therapy.

Negative association of steroids with immunotherapy efficacy in a multi-tumor cohort: time and dose-dependent

Previous studies have suggested a negative impact of steroids on the efficacy of immune checkpoint inhibitors (ICI), but how this effect is modulated by the dosage and time of administration is yet to be clarified. We have performed a retrospective analysis of 475 patients with advanced solid tumors treated with ICI as monotherapy from 2015 to 2022. Data regarding immune-related adverse events (irAEs) and clinical outcomes were collected. For each patient, the daily steroid dose (in mg/kg of prednisone) was registered until disease progression or death. The impact of cumulative doses on response rates and survival outcomes was analyzed within different periods. The objective response rate (ORR) was significantly lower among patients exposed to steroids within 30 days before the first cycle of ICI (C1) (20.3% vs. 36.7%, p < 0.01) and within the first 90 days of treatment (25.7% vs. 37.7%, p = 0.01). This negative association was confirmed by multivariable analysis. Higher mean steroid doses were observed among non-responders, and cumulative doses were inversely correlated with the disease control rate (DCR) around ICI initiation. Remarkably, poorer outcomes were observed even in patients belonging to the lowest dose quartile compared to the steroid-naïve population. The exposure to steroids after 6 months of ICI was not associated with worse survival outcomes. Our results suggest that the potential impact of steroids on ICI efficacy may be time-dependent, prevailing around ICI initiation, and dose-dependent, with modulation of neutrophil-to-lymphocyte ratio as a possible underlying mechanism.

Clinical practice recommendations for the use of next-generation sequencing in patients with solid cancer: a joint report from KSMO and KSP

In recent years, next-generation sequencing (NGS)-based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Clinical Practice Recommendations for the Use of Next-Generation Sequencing in Patients with Solid Cancer: A Joint Report from KSMO and KSP

In recent years, next-generation sequencing (NGS)-based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Immune-related adverse events of antibody-based biological medicines in cancer therapy

Recombinant antibodies (Abs) are an integral modality for the treatment of multiple tumour malignancies. Since the Food and Drug Administration (FDA) approval of rituximab as the first monoclonal antibody (mAb) for cancer treatment, several mAbs and antibody (Ab)-based therapies have been approved for the treatment of solid tumour malignancies and other cancers. These Abs function by either blocking oncogenic pathways or angiogenesis, modulating immune response, or by delivering a conjugated drug. The use of Ab-based therapy in cancer patients who could benefit from the treatment, however, is still limited by associated toxicity profiles which may stem from biological features and processes related to target binding, alongside biochemical and/or biophysical characteristics of the therapeutic Ab. A significant immune-related adverse event (irAE) associated with Ab-based therapies is cytokine release syndrome (CRS), characterized by the development of fever, rash and even marked, life-threatening hypotension, and acute inflammation with secondary to systemic uncontrolled increase in a range of pro-inflammatory cytokines. Here, we review irAEs associated with specific classes of approved, Ab-based novel cancer immunotherapeutics, namely immune checkpoint (IC)-targeting Abs, bispecific Abs (BsAbs) and Ab-drug-conjugates (ADCs), highlighting the significance of harmonization in preclinical assay development for safety assessment of Ab-based biotherapeutics as an approach to support and refine clinical translation.

Genomic and Epigenomic Biomarkers of Immune Checkpoint Immunotherapy Response in Melanoma: Current and Future Perspectives

Immune checkpoint inhibitors (ICIs) demonstrate durable responses, long-term survival benefits, and improved outcomes in cancer patients compared to chemotherapy. However, the majority of cancer patients do not respond to ICIs, and a high proportion of those patients who do respond to ICI therapy develop innate or acquired resistance to ICIs, limiting their clinical utility. The most studied predictive tissue biomarkers for ICI response are PD-L1 immunohistochemical expression, DNA mismatch repair deficiency, and tumour mutation burden, although these are weak predictors of ICI response. The identification of better predictive biomarkers remains an important goal to improve the identification of patients who would benefit from ICIs. Here, we review established and emerging biomarkers of ICI response, focusing on epigenomic and genomic alterations in cancer patients, which have the potential to help guide single-agent ICI immunotherapy or ICI immunotherapy in combination with other ICI immunotherapies or agents. We briefly review the current status of ICI response biomarkers, including investigational biomarkers, and we present insights into several emerging and promising epigenomic biomarker candidates, including current knowledge gaps in the context of ICI immunotherapy response in melanoma patients.

Identification and Validation of JAM-A as a Novel Prognostic and Immune Factor in Human Tumors

Junctional adhesion molecule-A (JAM-A), also known as F11 receptor (F11R), is a transmembrane glycoprotein that is involved in various biological processes, including cancer initiation and progression. However, the functional characteristics and significance of JAM-A in pan-cancer remain unexplored. In this study, we used multiple databases to gain a comprehensive understanding of JAM-A in human cancers. JAM-A was widely expressed in various tissues, mainly located on the microtubules and cell junctions. Aberrant expression of JAM-A was detected in multiple cancers at both mRNA and protein levels, which can be correlated with poorer prognosis and may be attributed to genetic alterations and down-regulated DNA methylation. JAM-A expression was also associated with immune infiltration and may affect immunotherapy responses in several cancers. Functional enrichment analysis indicated that JAM-A participated in tight junction and cancer-related pathways. In vitro experiments verified that JAM-A knockdown suppressed the proliferation and migration abilities of breast cancer cells and liver cancer cells. Overall, our study suggests that JAM-A is a pan-cancer regulator and a potential biomarker for predicting prognosis and immune-therapeutic responses for different tumors.

Predictive Impact of Tumor Mutational Burden on Real-World Outcomes of First-Line Immune Checkpoint Inhibition in Metastatic Melanoma

PURPOSE

The choice of threshold and reliability of high tumor mutational burden (TMB) to predict outcomes and guide treatment choice for patients with metastatic melanoma receiving first-line immune checkpoint inhibitor (ICI) therapy in the real world is not well known.

METHODS

Using a deidentified nationwide (US-based) melanoma clinicogenomic database, we identified a real-world cohort of patients with metastatic melanoma (N = 497) who received first-line monotherapy anti-PD-1 (n = 240) or dual anti-PD-1 and anti-CTLA-4 ICI (n = 257) and had a tissue-based comprehensive genomic profiling test TMB score.

RESULTS

TMB-high (TMB-H; ≥10 mutations per megabase [muts/Mb], n = 352, 71%) was independently predictive of superior real-world progression-free survival and overall survival versus TMB-low (<10 mut/Mb, n = 145, 29%) in both mono ICI (hazard ratio [HR], 0.45 [95% CI, 0.32 to 0.63]; P < .001; HR, 0.61 [95% CI, 0.41 to 0.90]; P = .01, respectively) and dual ICI (HR, 0.67 [95% CI, 0.49 to 0.90]; P = .009; HR, 0.61 [95% CI, 0.42 to 0.88]; P = .007, respectively) patients. Dual ICI offered no significant advantage in BRAFwt patients and unexpectedly demonstrated greatest benefit in the TMB 10-19 mut/Mb group, identifying a TMB-very high (≥20 mut/Mb, n = 247, 50%) BRAFmut patient subgroup for whom mono ICI may be preferable.

CONCLUSION

TMB-H predicts superior outcomes on ICI while coassessment of BRAF status and TMB may inform first-line regimen choice.

Peimenine unleashes therapeutic promise in urothelial bladder cancer: inhibition of proliferation, induction of cell death and modulation of key pathways

Peimenine (PEI) is a steroid alkaloid substance isolated from Fritillaria thunbergii bulbs. It has various pharmacological activities, such as relief from coughs and asthma, expectorant properties, antibacterial effects, sedative qualities, and anti-inflammatory properties. Notably, PEI can effectively inhibit the proliferation and tumor formation of liver cancer and osteosarcoma cells by inducing autophagic cell death. However, the precise effect and mechanisms of PEI on urothelial bladder cancer (UBC) cells remain uncertain. Thus, this study aims to investigate the impact of PEI on UBC cells both in vivo and in vitro. The IC50 values of BIU-87 and EJ-1 cells after 48 h were 710.3 and 651.1 μg/mL, respectively. Additionally, PEI blocked the cell cycle in BIU-87 and EJ-1 cells during the G1 phase. Furthermore, it hindered the migration of BIU-87 and EJ-1 cells substantially. PEI significantly inhibited the tumor development of EJ-1 cells within the xenograft tumor model in vivo. Mechanically, PEI augmented the protein and mRNA expression of BIM, BAK1, and Cytochrome C (CYCS) in UBC cells. Taken together, PEI suppressed the proliferation of UBC cells both in vitro and in vivo by inducing cell death and cell cycle arrest, suggesting that PEI could be applied in the treatment of UBC.

The prognostic and immune significance of PLBD1 in pan-cancer and its roles in proliferation and invasion of glioma

Cancer is a destructive disease and is currently the leading cause of major threats to human health. PLBD1 is a transcription factor that regulates phospholipid metabolism, but its role in tumors is unknown. We assessed pan-cancer expression, methylation, and mutation data of PLBD1 by multiple databases to investigate its clinical prognostic value. In addition, we examined the pan-cancer immunological signature of PLBD1, particularly in gliomas. Furthermore, we assessed the impact of PLBD1 knockdown on the proliferation and invasive capacity of glioma cells by in vitro experiments. Our results suggest that PLBD1 is highly expressed in multiple types of cancers, and it can serve as an independent prognostic factor for gliomas. In addition, we found that the epigenetic alterations of PLBD1 were highly heterogeneous in a variety of cancers, including gliomas, and that its high methylation was associated with poor prognosis in a broad range of cancers. Immunological profiling demonstrated that PLBD1 was significantly associated with immune cell infiltration and multiple immune checkpoints in gliomas and is a potential biomarker for gliomas. Furthermore, cellular experiments showed that knockdown of PLBD1 significantly inhibited the proliferation and invasive ability of glioma cells. In conclusion, PLBD1 is a potential tumor prognostic biomarker and immunotherapeutic target that plays a crucial role in glioma cell proliferation, invasion and immunotherapy.

Based on Immune Microenvironment and Genomic Status, Exploring Immunotherapy in Advanced Hidradenocarcinoma: A Retrospective Analysis

There are no standard treatment guidelines for hidradenocarcinoma, and the immune microenvironment and genomic data are very limited. Thus, in this study the immune microenvironment and genomic indicators in hidradenocarcinoma was investigated, and immunotherapy for hidradenocarcinoma was initially explored. Forty-seven hidradenocarcinoma patients were retrospectively collected. Immunohistochemical staining was performed to identify CD3/CD8+ T cells and programmed death ligand-1 expression. In total, 89.4% and 10.6% of samples had Immunoscores of 0-25% and 25-70%. Tumour proportion score distribution was as follows: tumour proportion score < 1% in 72.4%, 1-5% in 17.0%, and > 5% in 10.6%. Combined positive score distribution was as follows: combined positive score < 1 in 63.8%, 1-5 in 14.9%, and > 5 in 21.3%. Next-generation sequencing revealed that TP53 (33%), PI3KCA (22%), and ERBB3 (22%) were the most frequently mutated genes. The PI3K-Akt signalling pathway, growth, and MAPK signalling pathways were significantly enriched. Five patients had a low TMB (< 10 muts/Mb), and 9 patients had MSS. Three patients treated with immune combined with chemotherapy achieved significant tumour regression, and the progression-free survival was 28.8 months. In conclusion, the hidradenocarcinoma immune microenvironment tends to be noninflammatory. Evidence-based targets for targeted therapy are lacking. Immunotherapy combined with chemotherapy may be better for most advanced hidradenocarcinoma patients with a noninflammatory microenvironment.

Pan-Cancer Analysis of ART1 and its Potential Value in Gastric Cancer

Objective: To comprehensively explore the impact of Mono-ADP-ribosyltransferases-1 expression on both prognosis and the intricate landscape of the tumor immune microenvironment across diverse cancer types, our study seeks to delve into the multifaceted interplay between Mono-ADP-ribosyltransferases-1 expression levels and their implications for clinical outcomes and the dynamic milieu of immune responses within tumors. Methods: Genomic, transcriptomic, and clinical datasets spanning diverse cancer types were meticulously curated from The Cancer Genome Atlas and Genotypic Tissue Expression repositories. Initially, our inquiry focused on discerning the prognostic significance and immunological implications of Mono-ADP-ribosyltransferases-1 expression across this heterogeneous spectrum of malignancies. Subsequently, we scrutinized the relationships between Mono-ADP-ribosyltransferases-1 expression levels and a spectrum of factors including RNA modification genes, genetic mutations, and the emergent concept of tumor stemness. Employing functional enrichment analyses, we endeavored to unravel the underlying mechanistic pathways modulated by Mono-ADP-ribosyltransferases-1. Leveraging Bayesian co-localization analysis, we sought to discern the spatial convergence of Mono-ADP-ribosyltransferases-1 expression particularly within the context of digestive tract tumors. Lastly, to corroborate our findings, we conducted in vitro experiments, specifically focusing on Gastric Cancer, thus corroborating the putative oncogenic role attributed to Mono-ADP-ribosyltransferases-1 in this malignancy. Results: Across diverse tumor types, Mono-ADP-ribosyltransferases-1 expression exhibits distinctive patterns compared to normal and adjacent tissues, thereby intertwining with the prognostic outcomes of numerous cancer patients. Noteworthy findings from our immune role identification underscore the pivotal involvement of Mono-ADP-ribosyltransferases-1 in the landscape of tumor immunotherapy. Furthermore, Kyoto Encyclopedia of Genes and Genomes analysis elucidates the enrichment of Mono-ADP-ribosyltransferases-1-associated genes predominantly within the NF-kB, Foxo, and PI3K-Akt signaling cascades, shedding light on potential mechanistic pathways underlying its influence. Bayesian co-localization analysis unveils a compelling genetic correlation between Mono-ADP-ribosyltransferases-1 and digestive tract tumors, accentuating its relevance within this specific oncological domain. Importantly, experimental validation attests to the therapeutic promise of targeting Mono-ADP-ribosyltransferases-1 in the treatment paradigm of gastric cancer, thereby underscoring its potential as a viable therapeutic target deserving of further exploration and clinical translation. Conclusion: This comprehensive pan-cancer analysis unveils crucial insights into the intricate role played by Mono-ADP-ribosyltransferases-1 in the tumorigenesis of diverse malignancies, thereby establishing a robust theoretical framework for subsequent in-depth investigations. Leveraging these insights, targeting Mono-ADP-ribosyltransferases-1-related signaling pathways within the dynamic tumor microenvironment emerges as a promising avenue for novel therapeutic interventions in the realm of tumor immunotherapy. By delineating the interplay between Mono-ADP-ribosyltransferases-1 expression and tumorigenic processes across various cancer types, this study paves the way for innovative therapeutic strategies aimed at disrupting oncogenic signaling cascades and bolstering immune-mediated antitumor responses.

HCCDB v2.0: Decompose Expression Variations by Single-cell RNA-seq and Spatial Transcriptomics in HCC

Large-scale transcriptomic data are crucial for understanding the molecular features of hepatocellular carcinoma (HCC). Integrated 15 transcriptomic datasets of HCC clinical samples, the first version of HCC database (HCCDB v1.0) was released in 2018. Through the meta-analysis of differentially expressed genes and prognosis-related genes across multiple datasets, it provides a systematic view of the altered biological processes and the inter-patient heterogeneities of HCC with high reproducibility and robustness. With four years having passed, the database now needs integration of recently published datasets. Furthermore, the latest single-cell and spatial transcriptomics have provided a great opportunity to decipher complex gene expression variations at the cellular level with spatial architecture. Here, we present HCCDB v2.0, an updated version that combines bulk, single-cell, and spatial transcriptomic data of HCC clinical samples. It dramatically expands the bulk sample size by adding 1656 new samples from 11 datasets to the existing 3917 samples, thereby enhancing the reliability of transcriptomic meta-analysis. A total of 182,832 cells and 69,352 spatial spots are added to the single-cell and spatial transcriptomics sections, respectively. A novel single-cell level and 2-dimension (sc-2D) metric is proposed as well to summarize cell type-specific and dysregulated gene expression patterns. Results are all graphically visualized in our online portal, allowing users to easily retrieve data through a user-friendly interface and navigate between different views. With extensive clinical phenotypes and transcriptomic data in the database, we show two applications for identifying prognosis-associated cells and tumor microenvironment. HCCDB v2.0 is available at http://lifeome.net/database/hccdb2.

Development and validation of an MRI-Based nomogram to predict the effectiveness of immunotherapy for brain metastasis in patients with non-small cell lung cancer

Introduction

The variability and unpredictability of immune checkpoint inhibitors (ICIs) in treating brain metastases (BMs) in patients with advanced non-small cell lung cancer (NSCLC) is the main concern. We assessed the utility of novel imaging biomarkers (radiomics) for discerning patients with NSCLC and BMs who would derive advantages from ICIs treatment.

Methods

Data clinical outcomes and pretreatment magnetic resonance images (MRI) were collected on patients with NSCLC with BMs treated with ICIs between June 2019 and June 2022 and divided into training and test sets. Metastatic brain lesions were contoured using ITK-SNAP software, and 3748 radiomic features capturing both intra- and peritumoral texture patterns were extracted. A clinical radiomic nomogram (CRN) was built to evaluate intracranial progression-free survival, progression-free survival, and overall survival. The prognostic value of the CRN was assessed by Kaplan-Meier survival analysis and log-rank tests.

Results

In the study, a total of 174 patients were included, and 122 and 52 were allocated to the training and validation sets correspondingly. The intratumoral radiomic signature, peritumoral radiomic signature, clinical signature, and CRN predicted intracranial objective response rate. Kaplan-Meier analyses showed a significantly longer intracranial progression-free survival in the low-CRN group than in the high-CRN group (p < 0.001). The CRN was also significantly associated with progression-free survival (p < 0.001) but not overall survival.

Discussion

Radiomics biomarkers from pretreatment MRI images were predictive of intracranial response. Pretreatment radiomics may allow the early prediction of benefits.

Exploring the Cost Effectiveness of a Whole-Genome Sequencing-Based Biomarker for Treatment Selection in Patients with Advanced Lung Cancer Ineligible for Targeted Therapy

OBJECTIVE

We aimed to perform an early cost-effectiveness analysis of using a whole-genome sequencing-based tumor mutation burden (WGS-TMB), instead of programmed death-ligand 1 (PD-L1), for immunotherapy treatment selection in patients with non-squamous advanced/metastatic non-small cell lung cancer ineligible for targeted therapy, from a Dutch healthcare perspective.

METHODS

A decision-model simulating individual patients with metastatic non-small cell lung cancer was used to evaluate diagnostic strategies to select first-line immunotherapy only or the immunotherapy plus chemotherapy combination. Treatment was selected using PD-L1 [A, current practice], WGS-TMB [B], and both PD-L1 and WGS-TMB [C]. Strategies D, E, and F take into account a patient's disease burden, in addition to PD-L1, WGS-TMB, and both PD-L1 and WGS-TMB, respectively. Disease burden was defined as a fast-growing tumor, a high number of metastases, and/or weight loss. A threshold of 10 mutations per mega-base was used to classify patients into TMB-high and TMB-low groups. Outcomes were discounted quality-adjusted life-years (QALYs) and healthcare costs measured from the start of first-line treatment to death. Healthcare costs includes drug acquisition, follow-up costs, and molecular diagnostic tests (i.e., standard diagnostic techniques and/or WGS for strategies involving TMB). Results were reported using the net monetary benefit at a willingness-to-pay threshold of €80,000/QALY. Additional scenario and threshold analyses were performed.

RESULTS

Strategy B had the lowest QALYs (1.84) and lowest healthcare costs (€120,800). The highest QALYs and healthcare costs were 2.00 and €140,400 in strategy F. In the base-case analysis, strategy A was cost effective with the highest net monetary benefit (€27,300), followed by strategy B (€26,700). Strategy B was cost effective when the cost of WGS testing was decreased by at least 24% or when immunotherapy results in an additional 0.5 year of life gained or more for TMB high compared with TMB low. Strategies C and F, which combined TMB and PD-L1 had the highest net monetary benefit (≥ €76,900) when the cost of WGS testing, immunotherapy, and chemotherapy acquisition were simultaneously reduced by at least 47%, 39%, and 43%, respectively. Furthermore, strategy C resulted in the highest net monetary benefit (≥ €39,900) in a scenario where patients with both PD-L1 low and TMB low were treated with chemotherapy instead of immunotherapy plus chemotherapy.

CONCLUSIONS

The use of WGS-TMB is not cost effective compared to PD-L1 for immunotherapy treatment selection in non-squamous metastatic non-small cell lung cancer in the Netherlands. WGS-TMB could become cost effective provided there is a reduction in the cost of WGS testing or there is an increase in the predictive value of WGS-TMB for immunotherapy effectiveness. Alternatively, a combination strategy of PD-L1 testing with WGS-TMB would be cost effective if used to support the choice to withhold immunotherapy in patients with a low expected benefit of immunotherapy.

Comprehensive Analysis of N6-Methylandenosine-Related lncRNAs in Clear Cell Renal Cell Carcinoma: A Correlation With Prognosis, Tumor Progression, and Therapeutic Response

This study aims to develop a prognostic signature based on m6A-related lncRNAs for clear cell renal cell carcinoma (ccRCC). Differential expression analysis and Pearson correlation analysis were used to identify m6A-related lncRNAs associated with patient outcomes in The Cancer Genome Atlas (TCGA) database. Our approach led to the development of an m6A-related lncRNA risk score (MRLrisk), formulated using six identified lncRNAs: NFE4, AL008729.2, AL139123.1, LINC02154, AC124854.1 and ARHGAP31-AS1. Higher MRLrisk was identified as a risk factor for patients' prognosis in ccRCC. Furthermore, an MRLrisk-based nomogram was developed and demonstrated as a reliable tool for prognosis prediction in ccRCC. Enrichment analysis and tumor mutation signature studies were conducted to investigate MRLrisk-related biological phenotypes. The tumor immune dysfunction and exclusion (TIDE) score was employed to infer patients' response to immunotherapy, indicating a negative correlation between high MRLrisk and immunotherapy response. Our focus then shifted to LINC02154 for deeper exploration. We assessed LINC02154 expression in 28 ccRCC/normal tissue pairs and 3 ccRCC cell lines through quantitative real-time polymerase chain reaction (qRT-PCR). Functional experiments, including EdU incorporation, flow cytometry and transwell assays, were performed to assess the role of LINC02154 in ccRCC cell functions, discovering that its downregulation hinders cancer cell proliferation and migration. Furthermore, the influence of LINC02154 on ccRCC cells' sensitivity to Sunitinib was explored using CCK-8 assays, demonstrating that decreased LINC02154 expression increases Sunitinib sensitivity. In summary, this study successfully developed an MRLrisk model with significant prognostic value for ccRCC and established LINC02154 as a critical biomarker and prospective therapeutic target in ccRCC management.

Off-label prescribing of immune checkpoint inhibitor therapy at a single pediatric cancer center

BACKGROUND

Immune checkpoint inhibitors (ICI) have improved outcomes in a variety of adult cancers and are prescribed with increasing frequency across oncology. However, patterns of off-label use of ICI in pediatrics remain unclear.

METHODS

This is a single-institution, retrospective cohort study evaluating off-label ICI use in pediatric and young adult patients with cancer treated at our institution from 2014 to 2022. Response was based on clinician assessment derived from clinical records. Immune-related adverse events (iRAEs) were classified according to CTCAE v5.0.

RESULTS

We identified 50 unique patients treated with off-label ICI (28 with solid tumors, 20 with central nervous system (CNS) tumors, 2 with hematologic malignancies). At time of ICI initiation, only five patients (10%) had localized disease, and all but one patient was treated in the relapsed/refractory setting. All patients were treated with the FDA-approved weight-based dosing recommendations. Overall, there was disease control in 21 patients (42%), with best response including one complete response (melanoma), two partial responses (high-grade glioma, CNS nongerminomatous germ cell tumor), and 18 patients with stable disease. Forty-four patients (88%) eventually experienced disease progression. Among 22 patients (44%) experiencing iRAEs, 10 (20%) had a grade ≥3 irAE, 12 (24%) required corticosteroids, and 14 (28%) required ICI discontinuation. irAE occurrence was associated with significantly improved progression-free survival (HR 0.35; 95% CI: 0.18 to 0.68; p = 0.002) and overall survival (HR 0.33; 95% CI: 0.17 to 0.66; p = 0.002).

CONCLUSIONS

At our institution, ICI was most commonly prescribed in the relapsed/refractory setting to patients with metastatic disease. The treatment was generally well-tolerated in the pediatric population. The overall response rate was low, and the majority of patients eventually experienced disease progression. A few patients, however, had durable treatment responses. Further studies are needed to identify which pediatric patients are most likely to benefit from ICI.

Single cell and bulk RNA sequencing identifies tumor microenvironment subtypes and chemoresistance-related IGF1+ cancer-associated fibroblast in gastric cancer

BACKGROUND

The tumor microenvironment (TME) significantly influences prognosis and drug resistance in various tumors, yet its heterogeneity and the mechanisms affecting therapeutic response remain unclear in gastric cancer (GC).

METHODS

The heterogenous TME were explored with single-cell RNA-sequencing (scRNA-seq) data of 50 primary GC samples. We then identified four GC TME subtypes with nonnegative matrix factorization (NMF) and constructed a pearson nearest-centroid classifier based on subtype-specific upregulated genes. Genomic features and clinical significance of four subtypes were comprehensively evaluated. We reclustered fibroblasts to identify cancer-associated fibroblast (CAF) subtype associated with poor clinical outcomes. RT-qPCR and double immunofluorescence staining were applied to validate the findings. Cellchat analysis elucidated potential molecular mechanisms of the CAF subtype in GC disease progression and chemotherapy resistance.

FINDINGS

The GC TME exhibited high heterogeneity, influencing chemo-sensitivity. Four TME-based subtypes predicting response to immunotherapy and chemotherapy were identified and validated in 1406 GC patients. Among which, ISG1 subtype displayed higher fibroblasts infiltration and heightened oncogenic pathways, and inferior response to chemotherapy with unfavorable prognosis. Microsatellite instability-high (MSI-H) GCs within four TME subtypes showed immunological heterogeneity. We then reported an IGF1-overexpressing CAF was associated with chemo-resistance and GC recurrence. Cell communication analysis revealed IGF1+ CAF may induce drug-resistant phenotypes in tumor cells through IGF1-α6β4 integrin ligand-receptor binding and activation of EMT biological process.

INTERPRETATION

We identified four TME-based subtypes with different clinical outcomes and IGF1+ CAFs contributing to poor clinical outcomes in GC, which might provide guidance for individualized treatment and facilitate the development of novel therapeutic targets.

Pancancer analysis of the prognostic and immunological role of FANCD2: a potential target for carcinogenesis and survival

Recent evidence has shed light on the significant role of FANCD2 in cancer initiation, development, and progression. However, a comprehensive pan-cancer analysis of FANCD2 has been lacking. In this study, we have conducted a thorough investigation into the expression profiles and prognostic significance of FANCD2, as well as its correlation with clinicopathological parameters and immune cell infiltration, using advanced bioinformatic techniques. The results demonstrate that FANCD2 is significantly upregulated in various common cancers and is associated with prognosis. Notably, higher expression levels of FANCD2 are linked to poor overall survival, as indicated by Cox regression and Kaplan-Meier analyses. Additionally, we have observed a decrease in the methylation of FANCD2 DNA in some cancers, and this decrease is inversely correlated with FANCD2 expression. Genetic alterations in FANCD2 predominantly manifest as mutations, which are associated with overall survival, disease-specific survival, disease-free survival, and progression-free survival in certain tumor types. Moreover, FANCD2 exhibits a strong correlation with infiltrating cell levels, immune checkpoint genes, tumor mutation burden (TMB), and microsatellite instability (MSI). Enrichment analysis further highlights the potential impact of FANCD2 on Fanconi anemia (FA) pathway and cell cycle regulation. Through this comprehensive pan-cancer analysis, we have gained a deeper understanding of the functions of FANCD2 in oncogenesis and metastasis across different types of cancer.

Construction and validation of a colon cancer prognostic model based on tumor mutation burden-related genes

Currently, immunotherapy has entered the clinical diagnosis and treatment guidelines for colon cancer, but existing immunotherapy markers cannot predict the effectiveness of immunotherapy well. This study utilized the TCGA-COAD queue to perform differential gene analysis on high and low-mutation burden samples, and screen differentially expressed genes (DEGs). To explore new molecular markers or predictive models of immunotherapy by using DEGs for NMF classification and prognostic model construction. Through systematic bioinformatics analysis, the TCGA-COAD cohort was successfully divided into high mutation burden subtypes and low mutation burden subtypes by NMF typing using DEGs. The proportion of MSI-H between high mutation burden subtypes was significantly higher than that of low mutation burden subtypes, but there was no significant difference in immunotherapy efficacy between the two subtypes. Drug sensitivity analysis showed significant differences in drug sensitivity between the two subtypes. Subsequently, we constructed a prognostic model using DEGs, which can effectively predict patient survival and immunotherapy outcomes. The prognosis and immunotherapy outcomes of the low-risk group were significantly better than those of the high-risk group. The external dataset validation of the constructed prognostic model using the GSE39582 dataset from the GEO database yielded consistent results. At the same time, we also analyzed the TMB and MSI situation between the high and low-risk groups, and the results showed that there was no significant difference in TMB between the high and low-risk groups, but the proportion of MSI-H in the high-risk group was significantly higher than that in the low-risk group. Finally, we conclude that TMB is not a suitable molecular marker for predicting the efficacy of immunotherapy in colon cancer. The newly constructed prognostic model can effectively differentiate the prognosis of colon cancer patients and predict their immunotherapy efficacy.

Sustained Clinical Response to Immunotherapy Followed by BET Inhibitor in a Patient with Unresectable Sinonasal NUT Carcinoma

NUT carcinomas (NCs) are a group of rare tumors that can occur anywhere in the body and are defined by the fusion of the nuclear protein in testis (NUTM1) resulting in increased transcription of proto-oncogenes. NCs have a poor prognosis that varies according to the site of origin with an urgent need to develop new treatment strategies. Case reports on immunotherapy in pulmonary NC have been published, and bromodomain and extraterminal (BET) inhibitors have shown activity in NC in phase I/II trials. We present the case of a 27-year-old woman with an unresectable sinonasal NC who had a sustained clinical response to both immunotherapy and BET inhibitor therapy. This is the first reported case of immunotherapy in sinonasal NC, and it highlights the different responses to a range of treatments including BET inhibitor therapy. This case supports the theory that NCs arising from different primary sites have differing prognoses.

Molecular pathology as basis for timely cancer diagnosis and therapy

Precision and personalized therapeutics have witnessed significant advancements in technology, revolutionizing the capabilities of laboratories to generate vast amounts of genetic data. Coupled with computational resources for analysis and interpretation, and integrated with various other types of data, including genomic data, electronic medical health (EMH) data, and clinical knowledge, these advancements support optimized health decisions. Among these technologies, next-generation sequencing (NGS) stands out as a transformative tool in the field of cancer treatment, playing a crucial role in precision oncology. NGS-based workflows are employed across a range of applications, including gene panels, exome sequencing, and whole-genome sequencing, supporting comprehensive analysis of the entire cancer genome, including mutations, copy number variations, gene expression profiles, and epigenetic modifications. By utilizing the power of NGS, these workflows contribute to enhancing our understanding of disease mechanisms, diagnosis confirmation, identifying therapeutic targets, and guiding personalized treatment decisions. This manuscript explores the diverse applications of NGS in cancer treatment, highlighting its significance in guiding diagnosis and treatment decisions, identifying therapeutic targets, monitoring disease progression, and improving patient outcomes.

Comparative analyses of tumour immune microenvironment between collecting duct carcinoma and fumarate hydratase-deficient renal cell carcinoma

AIMS

Collecting duct carcinoma (CDC) and fumarate hydratase-deficient renal cell carcinoma (FH-deficient RCC) have similar histological morphologies and both show a poor prognosis. Programmed death ligand 1 (PD-L1) inhibitor has been approved for the treatment of RCC. However, tumour-infiltrating neutrophils stimulated by interleukin-8 (IL-8) interfere with PD-L1 inhibitors. Here, we retrospectively analysed PD-L1 and IL-8 expression, and examined its relationship with infiltrating immune cells.

METHODS

Nine cases of CDC and seven cases of FH-deficient RCC were selected. We defined PD-L1 and IL-8 expression by the Tumour Proportion Score and Combined Positive Score (CPS). We counted the numbers of CD8+, CXCR2+, CD11b+, CD66b+ and CD33+ immune cells located in the tumour components.

RESULTS

A number of CXCR2+ (p=0.0058), CD11b+ (p=0.0070) and CD66b+ (p=0.0067) immune cells infiltrating into CDC were significantly higher than those infiltrating into FH-deficient RCC. In CDC, PD-L1 expression was correlated with a high density of CD8+ lymphocytes (p=0.0389), but was not in FH-deficient RCC (p=0.6985). IL-8 CPS was significantly higher in CDC than in FH-deficient RCC (p=0.0069). In addition, among the CDC cases, IL-8 CPS showed significant positive correlations with CXCR2+, CD11b+ and CD66b+ immune cell densities (p=0.0250, p=0.0104 and p=0.0374, respectively), whereas FH-deficient RCC showed no significant correlations between IL-8 CPS and immune cell densities.

CONCLUSIONS

Our results suggest the difference of each tumour microenvironment between CDC and FH-deficient RCC, and IL-8 is a potential therapeutic target for treating CDC, but not FH-deficient RCC.

Immune landscape and heterogeneity of cervical squamous cell carcinoma and adenocarcinoma

Despite the differences in disease outcomes and pathological features between cervical squamous cell carcinoma (CSCC) and adenocarcinoma (ADC), the molecular characteristics in immune heterogeneity of the tumor microenvironment remain unclear. Here, we explored the immune landscape and heterogeneity between CSCC and ADC. Gene expression and clinical characteristics of cervical carcinoma from The Cancer Genome Atlas (TCGA) were downloaded. Differentially expressed genes (DEGs), immune cell infiltration, and pathway enrichment analyses were used to explore the immune landscape and heterogeneity between CSCC and ADC. Furthermore, distinct immune signatures between CSCC and ADC were validated based on clinical samples. In total, 4,132 upregulated DEGs and 2,307 down-regulated DEGs were identified between CSCC and ADC, with enrichments in immune related-pathways in CSCC. In addition, 54 hub DEGs correlated with patients' prognosis and immunocytes infiltration were identified. The CSCC patients had a higher ImmuneScore and more abundant immunocytes infiltration compared to ADC patients, as validated by immunohistochemistry (IHC) and multicolor immunofluorescence (mIF) analyses of collected samples. Furthermore, CSCC displayed higher inhibitory immune checkpoints expression, tumor mutation burden (TMB), and microsatellite instability (MSI) compared to ADC, which indicated CSCC patients were more likely to benefit from immunotherapy. In summary, our results revealed the huge immune heterogeneity between CSCC and ADC, and provided guidance for immunotherapy selection for different pathological types of cervical cancer.

Tumor Mutational Burden as a Biomarker of Immunotherapy Response: An Immunogram Approach in Onco-immunology

Immune checkpoint inhibitors have revolutionized cancer treatment by allowing T cells to reactivate. Tumor mutational burden (TMB) is a biomarker that has emerged as a viable diagnostic for locating patients who would benefit from immunotherapy in particular cancer types. Greater neo-antigens mean more opportunities for T cell identification, and TMB is clinically linked to better immune checkpoint inhibitors. Tumor foreignness is a cancer immunogram, and TMB can be used as a substitute for foreignness. The role of TMB analysis as an independent predictor of immunotherapy response in the context of immune checkpoint inhibitor medications is the subject of this mini-review.

Understanding the mechanistic pathways and clinical aspects associated with protein and gene based biomarkers in breast cancer

Cancer is one of the most widespread and severe diseases with a huge mortality rate. In recent years, the second-leading mortality rate of any cancer globally has been breast cancer, which is one of the most common and deadly cancers found in women. Detecting breast cancer in its initial stages simplifies treatment, decreases death risk, and recovers survival rates for patients. The death rate for breast cancer has risen to 0.024 % in some regions. Sensitive and accurate technologies are required for the preclinical detection of BC at an initial stage. Biomarkers play a very crucial role in the early identification as well as diagnosis of women with breast cancer. Currently, a wide variety of cancer biomarkers have been discovered for the diagnosis of cancer. For the identification of these biomarkers from serum or other body fluids at physiological amounts, many detection methods have been developed. In the case of breast cancer, biomarkers are especially helpful in discovering those who are more likely to develop the disease, determining prognosis at the time of initial diagnosis and choosing the best systemic therapy. In this study we have compiled various clinical aspects and signaling pathways associated with protein-based biomarkers and gene-based biomarkers.

Pan-cancer Analysis Identifies AIMP2 as a Potential Biomarker for Breast Cancer

Introduction

Aminoacyl tRNA synthetase complex interacting with multifunctional protein 2 (AIMP2) is a significant regulator of cell proliferation and apoptosis. Despite its abnormal expression in various tumor types, the specific functions and effects of AIMP2 on tumor immune cell infiltration, proliferation, and migration remain unclear.

Materials and Methods

To assess AIMP2's role in tumor immunity, we conducted a pan-cancer multi-database analysis using the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Lines Encyclopedia (CCLE) datasets, examining expression levels, prognosis, tumor progression, and immune microenvironment. Additionally, we investigated AIMP2's impact on breast cancer (BRCA) proliferation and migration using cell counting kit 8 (CCK-8) assay, transwell assays, and western blot analysis.

Results

Our findings revealed that AIMP2 was overexpressed in 24 tumor tissue types compared to normal tissue and was associated with four tumor stages. Survival analysis indicated that AIMP2 expression was strongly correlated with overall survival (OS) in certain cancer patients, with high AIMP2 expression linked to poorer prognosis in five cancer types.

Conclusion

Finally, siRNA-mediated AIMP2 knockdown inhibited BRCA cell proliferation and migration in vitro. In conclusion, our pan-cancer analysis suggests that AIMP2 may play a crucial role in tumor immunity and could serve as a potential prognostic marker, particularly in BRCA.

A pan-cancer analysis of TNFAIP8L1 in human tumors

TNFAIP8L1, as a recently identified member in TNFAIP8 family, plays an important role in tumorigenesis. However, a pan-cancer analysis of TNFAIP8L1 in human tumors has not been conducted until now. The main purpose of study is to investigate TNFAIP8L1 during 33 different types of human tumors by using TCGA and GTEx. The pan-cancer analysis showed that TNFAIP8L1 was significantly over-expressed in 15 cancers and low-expressed in 9 cancers. There were distinct relations between TNFAIP8L1 expression and prognosis of patients with cancer. Furthermore, we also found that DNA methylation and RNA modification of TNFAIP8L1 were associated with many cancers. And then, we detected that TNFAIP8L1 level was positively associated with cancer-associated fibroblasts (CAFs) in many tumors. And, we obtained that TNFAIP8L1 expression was related with most of immune inhibitory and stimulatory genes in multiple types of tumors. We also found TNFAIP8L1 expression was correlated with most of chemokine, receptor, MHC, immunoinhibitor and immunostimulator gens in most of cancers. Moreover, we detected TNFAIP8L1 expression was associated with TMB and MSI in several tumors. Finally, TNFAIP8L1 gene had a significant positive association with 5 genes including BCL6B, DLL4, PCDH12, COL4A1 and DLL4 in the majority of tumors. GO enrichment and KEGG pathway analyses showed that TNFAIP8L1 in thepathogenesis of cancer may be related to "purine nucleoside binding," "purine ribonucleoside binding," "ECM-receptor interaction," etc. Our first pan-cancer study may provide a deep comprehending of TNFAIP8L1 in tumoeigenesis from different tumors.

Navigating a Complex Intersection: Immunotherapy and Radiotherapy Synergy in Squamous Cell Carcinoma of the Skin—A Comprehensive Literature Review

Skin squamous cell carcinoma (SCC) represents a major public health concern due to its high incidence and potential for local invasion and metastasis. Compared to local recurrence, metastatic SCC represents an even greater therapeutic challenge. Once distant metastasis occurs, the disease becomes incurable, and treatment focuses on palliation and prolonging survival. The immune microenvironment of SCC is characterized by an infiltration of immune cells, including tumor-infiltrating lymphocytes. In addition to its direct cytotoxic effects, radiotherapy also induces immunomodulatory effects within the tumor microenvironment. Radiation can promote the release of tumor-associated antigens and induce immunogenic cell death, thereby enhancing the recognition of tumor cells by the immune system. Immunotherapy and radiotherapy have emerged as promising therapeutic modalities for metastatic SCC. This literature review aims to evaluate the potential synergy between these treatments and shed light on their combined efficacy. Within the manuscript, we present a compelling case report of a patient with advanced SCC who exhibited resistance to the combined regimen of immunotherapy and radiotherapy, leading to disease progression. Despite the increasing evidence supporting the synergy between these modalities, this case underscores the complex nature of treatment response and the importance of considering individual patient characteristics.