Cancer Immunotherapy Response Research Articles

Exploring GZMK as a prognostic marker and predictor of immunotherapy response in breast cancer: unveiling novel insights into treatment outcomes

BackgroundGranzyme K (GZMK) is a crucial mediator released by immune cells to eliminate tumor cells, playing significant roles in inflammation and tumorigenesis. Despite its importance, the specific role of GZMK in breast cancer and its mechanisms are not well understood.MethodsWe utilized data from the TCGA and GEO databases and employed a range of analytical methods including GO, KEGG, GSEA, ssGSEA, and PPI to investigate the impact of GZMK on breast cancer. In vitro studies, including RT-qPCR, CCK-8 assay, cell cycle experiments, apoptosis assays, Celigo scratch assays, Transwell assays, and immunohistochemical methods, were conducted to validate the effects of GZMK on breast cancer cells. Additionally, Cox regression analysis integrating TCGA and our clinical data was used to develop an overall survival (OS) prediction model.ResultsAnalysis of clinical pathological features revealed significant correlations between GZMK expression and lymph node staging, differentiation grade, and molecular breast cancer subtypes. High GZMK expression was associated with improved OS, progression-free survival (PFS), and recurrence-free survival (RFS), as confirmed by multifactorial Cox regression analysis. Functional and pathway enrichment analyses of genes positively correlated with GZMK highlighted involvement in lymphocyte differentiation, T cell differentiation, and T cell receptor signaling pathways. A robust association between GZMK expression and T cell presence was noted in the breast cancer tumor microenvironment (TME), with strong correlations with ESTIMATEScore (Cor = 0.743, P < 0.001), ImmuneScore (Cor = 0.802, P < 0.001), and StromalScore (Cor = 0.516, P < 0.001). GZMK also showed significant correlations with immune checkpoint molecules, including CTLA4 (Cor = 0.856, P < 0.001), PD-1 (Cor = 0.82, P < 0.001), PD-L1 (Cor = 0.56, P < 0.001), CD48 (Cor = 0.75, P < 0.001), and CCR7 (Cor = 0.856, P < 0.001). Studies indicated that high GZMK expression enhances patient responsiveness to immunotherapy, with higher levels observed in responsive patients compared to non-responsive ones. In vitro experiments confirmed that GZMK promotes cell proliferation, cell division, apoptosis, cell migration, and invasiveness (P < 0.05).ConclusionOur study provides insights into the differential expression of GZMK in breast cancer and its potential mechanisms in breast cancer pathogenesis. Elevated GZMK expression is associated with improved OS and RFS, suggesting its potential as a prognostic marker for breast cancer survival and as a predictor of the efficacy of immunotherapy.

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

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

Discovery of a T cell proliferation-associated regulator signature correlates with prognosis risk and immunotherapy response in bladder cancer.

The efficacy of immunotherapy is heavily influenced by T cell activity. This study aimed to examine how T cell proliferation regulators can predict the prognosis and response to immunotherapy in patients with bladder cancer (BCa). T cell proliferation-related subtypes were determined by employing the non-negative matrix factorization (NMF) algorithm that analyzed the expression patterns of T cell proliferation regulators. Subtypes were assessed for variations in prognosis, immune infiltration, and functional behaviors. Subsequently, a risk model related to T cell proliferation was created through Cox and Lasso regression analyses in the TCGA cohort and then confirmed in two GEO cohorts and an immunotherapy cohort. BCa patients were categorized into two subtypes (C1 and C2) according to the expression profiles of 31T cell proliferation-related genes (TRGs) with distinct prognoses and immune landscapes. The C2 subtype had a shorter overall survival (OS), with higher levels of M2 macrophage infiltration, and the activation of cancer-related pathways than the C1 subtype. Following this, thirteen prognosis-related genes that were involved in T cell proliferation were utilized to create the prognostic signature. The model's predictive accuracy was confirmed by analyzing both internal and external datasets. Individuals in the high-risk category experienced a poorer prognosis, increased immunosuppressive factors in the tumor microenvironment, and diminished responses to immunotherapy. Additionally, the immunotherapeutic prediction efficacy of the model was further confirmed by an immunotherapy cohort (anti-PD-L1 in the IMvigor210 cohort). Our study characterized two subtypes linked to T cell proliferation in BCa patients with distinct prognoses and tumor microenvironment (TME) patterns, providing new insights into the heterogeneity of T cell proliferation in BCa and its connection to the immune landscape. The signature has prospective clinical implications for predicting outcomes and may help physicians to select prospective responders who prioritize current immunotherapy.

SLC7A5 correlated with malignancies and immunotherapy response in bladder cancer

BackgroundMetabolic reprogramming contributes to bladder cancer development. This study aimed to understand the role of SLC7A5 in bladder cancer.MethodsWe systematically analyzed the correlation between SLC7A5 and bladder cancer through various approaches, including bioinformatics, western blotting, cell cycle analysis, cell proliferation assays, and invasion experiments. We also investigated the immunological features within the tumor microenvironment (TME), encompassing cancer immune cycles, immune modulators, immune checkpoints, tumor-infiltrating immune cells (TIIC), T cell inflammation scores, and treatment responses. Additionally, for a comprehensive assessment of the expression patterns and immunological roles of SLC7A5, pan-cancer analysis was performed using cancer genomics datasets.ResultsSLC7A5 was associated with adverse prognosis in bladder cancer patients, activating the Wnt pathway and promoting bladder cancer cell cycle progression, proliferation, migration, and invasion. Based on the evidence that SLC7A5 positively correlated with immunomodulators, TIIC, the cancer immune cycle, immune checkpoint and T cell inflammation scores, we also found that SLC7A5 was associated with the inflammatory tumor immune microenvironment. EGFR-targeted therapy, cancer immunotherapy, and radiation therapy were effective for patients with high SLC7A5 expression in bladder cancer. Low SLC7A5 patients were, however, sensitive to targeted therapies and anti-angiogenic therapy, such as blocking β-catenin network, PPAR-γ and FGFR3 signaling. Anti-SLC7A5 combined with cancer immunotherapy may have greater effectiveness than either therapy alone. Furthermore, we observed specific overexpression of SLC7A5 in TME of various cancers.ConclusionSLC7A5 can predict therapeutic response to immunotherapy, radiotherapy and chemotherapy in bladder cancer patients. Targeting SLC7A5 in combination with immunotherapy may be a potentially appropriate treatment option.

Exploiting tertiary lymphoid structures gene signature to evaluate tumor microenvironment infiltration and immunotherapy response in colorectal cancer

BackgroundTertiary lymphoid structures (TLS) is a particular component of tumor microenvironment (TME). However, its biological mechanisms in colorectal cancer (CRC) have not yet been understood. We desired to reveal the TLS gene signature in CRC and evaluate its role in prognosis and immunotherapy response.MethodsThe data was sourced from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Based on TLS-related genes (TRGs), the TLS related subclusters were identified through unsupervised clustering. The TME between subclusters were evaluated by CIBERSORT and xCell. Subsequently, developing a risk model and conducting external validation. Integrating risk score and clinical characteristics to create a comprehensive nomogram. Further analyses were conducted to screen TLS-related hub genes and explore the relationship between hub genes, TME, and biological processes, using random forest analysis, enrichment and variation analysis, and competing endogenous RNA (ceRNA) network analysis. Multiple immunofluorescence (mIF) and immunohistochemistry (IHC) were employed to characterize the existence of TLS and the expression of hub gene.ResultsTwo subclusters that enriched or depleted in TLS were identified. The two subclusters had distinct prognoses, clinical characteristics, and tumor immune infiltration. We established a TLS-related prognostic risk model including 14 genes and validated its predictive power in two external datasets. The model’s AUC values for 1-, 3-, and 5-year overall survival (OS) were 0.704, 0.737, and 0.746. The low-risk group had a superior survival rate, more abundant infiltration of immune cells, lower tumor immune dysfunction and exclusion (TIDE) score, and exhibited better immunotherapy efficacy. In addition, we selected the top important features within the model: VSIG4, SELL and PRRX1. Enrichment analysis showed that the hub genes significantly affected signaling pathways related to TLS and tumor progression. The ceRNA network: PRRX1-miRNA (hsa-miR-20a-5p, hsa-miR-485–5p) -lncRNA has been discovered. Finally, IHC and mIF results confirmed that the expression level of PRRX1 was markedly elevated in the TLS- CRC group.ConclusionWe conducted a study to thoroughly describe TLS gene signature in CRC. The TLS-related risk model was applicable for prognostic prediction and assessment of immunotherapy efficacy. The TLS-hub gene PRRX1, which had the potential to function as an immunomodulatory factor of TLS, could be a therapeutic target for CRC.

Competing endogenous RNA networks and ferroptosis in cancer: novel therapeutic targets.

As a newly identified regulated cell death, ferroptosis is a metabolically driven process that relies on iron and is associated with polyunsaturated fatty acyl peroxidation, elevated levels of reactive oxygen species (ROS), and mitochondrial damage. This distinct regulated cell death is dysregulated in various cancers; activating ferroptosis in malignant cells increases cancer immunotherapy and chemoradiotherapy responses across different malignancies. Over the last decade, accumulating research has provided evidence of cross-talk between non-coding RNAs (ncRNAs) and competing endogenous RNA (ceRNA) networks and highlighted their significance in developing and progressing malignancies. Aside from pharmaceutical agents to regulate ferroptosis, recent studies have shed light on the potential of restoring dysregulated ferroptosis-related ceRNA networks in cancer treatment. The present study provides a comprehensive and up-to-date review of the ferroptosis significance, ferroptosis pathways, the role of ferroptosis in cancer immunotherapy and chemoradiotherapy, ceRNA biogenesis, and ferroptosis-regulating ceRNA networks in different cancers. The provided insights can offer the authorship with state-of-the-art findings and future perspectives regarding the ferroptosis and ferroptosis-related ceRNA networks and their implication in the treatment and determining the prognosis of affected patients.

Identification of ferroptosis-related lncRNAs for predicting prognosis and immunotherapy response in non-small cell lung cancer

Increasing evidences have demonstrated the ferroptosis-related lncRNAs are key regulators of non- small cell lung cancer (NSCLC) progression and new targets for NSCLC therapy. However, the function of ferroptosis-related lncRNAs in prognosis and immunotherapy of NSCLC still needs to be further explored. In this study, we identified the value of ferroptosis-related lncRNAs in predicting the prognosis and the immunotherapy response in NSCLC patients by integrating anal- ysis of Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data. The most appropriate predictors associated with NSCLC prognosis and immunotherapy response, in- cluding LINC00304, LINC00968, LINC00312, LINC00853, LINC-PINT, SLC12A2-DT, DANCR, LINC00491 and LINC00310, were identified by differential expression analysis, Pearson correlation analysis, univariate and multivariate Cox regression analysis. The Risk-Score prediction model was successfully established. Kaplan-Meier analysis, time-dependent receiver operating characteristic (ROC) curves analysis and independent data sets analysis demonstrated that the model has excellent predictive ability and robustness. Further, it was revealed that the Risk-Score model of nine ferroptosis- related lncRNAs are good at predicting immunotherapy response. In conclusion, a Risk-Score model of 9 ferroptosis-related lncRNAs can predict prognosis and immunotherapy response with NSCLC.

Time of day determines cancer immunotherapy response.

Time of day determines cancer immunotherapy response.

Increased co-expression of 4-1BB with PD-1 on CD8+ tumor-infiltrating lymphocytes is associated with improved prognosis and immunotherapy response in cervical cancer.

The combination of agonistic antibodies with immune checkpoint inhibitors presents a promising avenue for cancer immunotherapy. Our objective is to explore the co-expression of 4-1BB, ICOS, CD28, with PD-1 on CD8+ T cells in the peripheral blood and tumor tissue of cervical cancer(CC) patients, with a specific focus on the association between the co-expression levels of 4-1BB with PD-1 and clinical features, prognosis as well as immunotherapy response. The goal is to offer valuable insights into cervical cancer immunotherapy. In this study, 50 treatment-naive patients diagnosed with CC were enrolled. Flow cytometry was used to detect PD-1/4-1BB, PD-1/ICOS and PD-1/CD28 co-expression on CD8+ T cells. Subsequent analysis aimed to investigate the differential co-expression between peripheral blood and cancer tissue, and also the correlation between co-expression and clinical features in these patients. Gene Expression Omnibus (GEO) datasets, The Cancer Genome Atlas (TCGA) cohort, The IMvigor210 cohort, The BMS038cohort and Immunophenoscores were utilized to investigate the correlation between PD-1/4-1BB and the immune microenvironment, prognosis, immunotherapy, and drug sensitivity in cervical cancer. The co-expression levels of PD-1/4-1BB, PD-1/ICOS, and PD-1/CD28 on CD8+ tumor-infiltrating lymphocytes (TILs) were significantly higher in cervical cancer patients compared to those in peripheral blood. Clinical feature analysis reveals that on CD8+ TILs, the co-expression of PD-1/4-1BB is more closely correlated with clinical characteristics compared to PD-1/ICOS, PD-1/CD28, PD-1, and 4-1BB. Pseudo-time analysis and cell communication profiling reveal close associations between the subgroups harboring 4-1BB and PD-1. The prognosis, tumor mutation burden, immune landscape, and immunotherapy response exhibit statistically significant variations between the high and low co-expression groups of PD-1/4-1BB. The high co-expression group of PD-1/4-1BB is more likely to benefit from immunotherapy. PD-1/4-1BB, PD-1/ICOS, and PD-1/CD28 exhibit elevated co-expression on CD8+TILs of cervical cancer, while demonstrating lower expression in circulating T cells. The co-expression patterns of PD-1/4-1BB significantly contributed to the prediction of immune cell infiltration characteristics, prognosis, and tailored immunotherapy tactics. PD-1/4-1BB exhibits potential as a target for combination immunotherapy in cervical cancer.

Deciphering the role of apoptosis signature on the immune dynamics and therapeutic prognosis in breast cancer: Implication for immunotherapy.

Background: In breast cancer oncogenesis, the precise role of cell apoptosis holds untapped potential for prognostic and therapeutic insights. Thus, it is important to develop a model predicated for breast cancer patients' prognosis and immunotherapy response based on apoptosis-related signature. Methods: Our approach involved leveraging a training dataset from The Cancer Genome Atlas (TCGA) to construct an apoptosis-related gene prognostic model. The model's validity was then tested across several cohorts, including METABRIC, Sun Yat-sen Memorial Hospital Sun Yat-sen University (SYSMH), and IMvigor210, to ensure its applicability and robustness across different patient demographics and treatment scenarios. Furthermore, we utilized Quantitative Polymerase Chain Reaction (qPCR) analysis to explore the expression patterns of these model genes in breast cancer cell lines compared to immortalized mammary epithelial cell lines, aiming to confirm their differential expression and underline their significance in the context of breast cancer. Results: Through the development and validation of our prognostic model based on seven apoptosis-related genes, we have demonstrated its substantial predictive power for the survival outcomes of breast cancer patients. The model effectively stratified patients into high and low-risk categories, with high-risk patients showing significantly poorer overall survival in the training cohort and across all validation cohorts. Importantly, qPCR analysis confirmed that the genes constituting our model indeed exhibit differential expression in breast cancer cell lines when contrasted with immortalized mammary epithelial cell lines. Conclusion: Our study establishes a groundbreaking prognostic model using apoptosis-related genes to enhance the precision of breast cancer prognosis and treatment, particularly in predicting immunotherapy response.

A novel Natural killer cell-related gene signature for improving the prediction of prognosis and immunotherapy response in bladder cancer.

Bladder cancer (BLCA) is a commonly diagnosed cancer worldwide that exhibits high rates of recurrence and metastasis. Immunotherapy is increasingly being recognised in the clinical management of bladder cancer. In addition, the prospect of developing Natural Killer (NK) cell-related immunotherapy is promising in BLCA. We established and verified a prognostic signature based on NK cell-related gene expression. We then calculated the NKscore of BLCA samples and correlated it with the clinical outcomes, molecular subtypes of BLCA, tumour microenvironment (TME), and predicted efficacy of immune checkpoint inhibitors (ICI) and chemotherapy drugs to thoroughly explore the implications of the NKscore. Finally, the role of the NK signature gene HECTD1 in BLCA was verified by Quantitative Real-time PCR, Cell Counting Kit-8 Assay (CCK-8), Transwell Assay and Colony Formation Experiment. We analysed NK cell-associated genes and identified six genes with significant prognostic relevance. A high NK score significantly represents a worse prognosis. NKscore was significantly correlated with seven types of classical molecular subtype classifications of BLCA. In addition, NKscore positively correlates with NK-related immune checkpoints, suggesting that emerging NK cell immune checkpoint inhibitors, such as monalizumab, may have potential therapeutic promise for patients with high NKscore. The results of the T cell inflamed score (TIS) and tumour immune dysfunction exclusion (TIDE) score confirmed the suitability of immunotherapy for patients with a high NK score. Likewise, patients with a high NK score may be more suitable for several significant chemotherapeutic drugs. Functional experiments showed that the knockdown of HECTD1 significantly attenuated the proliferation, migration, and invasion ability of tumour cells. to sum up, the capability of our signature to predict prognosis and immunotherapy response was robust. Hopefully, these results will provide new insights for BLCA research and patient immunotherapy.

Epithelial Expressed B7-H4 Drives Differential Immunotherapy Response in Murine and Human Breast Cancer.

This translational study confirms the association of B7-H4 expression with a cold immune microenvironment in breast cancer and offers preclinical studies demonstrating a potential role for B7-H4 in suppressing response to checkpoint therapy. However, analysis of two clinical trials with checkpoint inhibitors in the early and metastatic settings argue against B7-H4 as being a mechanism of clinical resistance to checkpoints, with clear implications for its candidacy as a therapeutic target.

Predicting prognosis and immunotherapy response in colorectal cancer by pericytes insights from single-cell RNA sequencing.

Immunotherapy has revolutionized the treatment of tumors, but there are still a large number of patients who do not benefit from immunotherapy. Pericytes play an important role in remodeling the immune microenvironment. However, how pericytes affect the prognosis and treatment resistance of tumors is still unknown. This study jointly analyzed single-cell RNA sequencing (scRNA-seq) data and bulk RNA sequencing data of multiple cancers to reveal pericyte function in the colorectal cancer microenvironment. Analyzing over 800 000 cells, it was found that colorectal cancer had more pericyte enrichment in tumor tissues than other cancers. We then combined the TCGA database with multiple public datasets and enrolled more than 1000 samples, finding that pericyte may be closely related to poor prognosis due to the higher epithelial-mesenchymal transition (EMT) and hypoxic characteristics. At the same time, patients with more pericytes have higher immune checkpoint molecule expressions and lower immune cell infiltration. Finally, the contributions of pericyte in poor treatment response have been demonstrated in multiple immunotherapy datasets (n = 453). All of these observations suggest that pericyte can be used as a potential biomarker to predict patient disease progression and immunotherapy response.

5-Hydroxymethylcytosine in Cell-Free DNA Predicts Immunotherapy Response in Lung Cancer.

Immune checkpoint inhibitors (ICIs) drastically improve therapeutic outcomes for lung cancer, but accurately predicting individual patient responses to ICIs remains a challenge. We performed the genome-wide profiling of 5-hydroxymethylcytosine (5hmC) in 85 plasma cell-free DNA (cfDNA) samples from lung cancer patients and developed a 5hmC signature that was significantly associated with progression-free survival (PFS). We built a 5hmC predictive model to quantify the 5hmC level and validated the model in the validation, test, and control sets. Low weighted predictive scores (wp-scores) were significantly associated with a longer PFS compared to high wp-scores in the validation [median 7.6 versus 1.8 months; p = 0.0012; hazard ratio (HR) 0.12; 95% confidence interval (CI), 0.03-0.54] and test (median 14.9 versus 3.3 months; p = 0.00074; HR 0.10; 95% CI, 0.02-0.50) sets. Objective response rates in patients with a low or high wp-score were 75.0% (95% CI, 42.8-94.5%) versus 0.0% (95% CI, 0.0-60.2%) in the validation set (p = 0.019) and 80.0% (95% CI, 44.4-97.5%) versus 0.0% (95% CI, 0.0-36.9%) in the test set (p = 0.0011). The wp-scores were also significantly associated with PFS in patients receiving single-agent ICI treatment (p < 0.05). In addition, the 5hmC predictive signature demonstrated superior predictive capability to tumor programmed death-ligand 1 and specificity to ICI treatment response prediction. Moreover, we identified novel 5hmC-associated genes and signaling pathways integral to ICI treatment response in lung cancer. This study provides proof-of-concept evidence that the cfDNA 5hmC signature is a robust biomarker for predicting ICI treatment response in lung cancer.

Abstract LB090: Predictive genomic biomarkers for atezolizumab plus bevacizumab combination immunotherapy response in liver cancer: Insights from the IMbrave150 trial

Abstract Introduction: Combination immunotherapy regimens, exemplified by atezolizumab plus bevacizumab or sintilimab paired with a bevacizumab biosimilar (IBI305), have become the established standard of care for individuals with inoperable hepatocellular carcinoma (HCC). Despite this advancement, the absence of clear predictive biomarkers and a comprehensive understanding of the mechanisms governing response and resistance to these combined therapies pose challenges. Our aim is to evaluate whether previously defined immune signature scores (ISS) from the TCGA pan-cancer study can identify HCC patients likely to derive enhanced benefit from the combination immunotherapy. Methods: We applied ISS predictor to gene expression data from IMbrave150 clinical trial in which HCC patients were treated with atezolizumab plus bevacizumab or sorafenib and stratify the patients into responders and non-responders (cutoff of 0.5). The significance of the stratification was assessed by multiple statistical approaches using Kaplan-Meier plots, the log-rank test, chi-square tests, and cox regression analysis. Results: In the IMBrave150 trial cohort, data on gene expression and outcomes were accessible for 247 patients who received atezolizumab plus bevacizumab, and 48 patients who received sorafenib. The high ISS demonstrated a significant association with enhanced PFS in the atezolizumab plus bevacizumab group (p=0.003), while no such association was observed in the sorafenib group (p=0.6). Similarly, in the high ISS subgroup, the combination therapy exhibited superior OS (p.0.001) and PFS (p=0.02) compared to sorafenib, but no discernible benefit was noted in the low ISS subgroup (both p&amp;gt;0.7). The OS hazard ratio for the combination versus sorafenib was 0.26 (95% CI 0.14-0.51, p&amp;lt;0.001) among high ISS patients, while it was not statistically significant in low ISS (HR 0.88, p=0.68). Interaction testing confirmed a notable interaction between ISS subtype and treatment benefit, particularly for OS (p=0.01). In the combination arm, the objective response rate was 45.6% in the high ISS group versus 22.8% in the low ISS group. Conclusions: Our study suggests that ISS may serve as a promising predictive biomarker for enhanced therapeutic outcomes in patients undergoing combination immunotherapy for HCC. The identification of such markers is crucial for refining patient stratification and personalized treatment approaches, thereby advancing the effectiveness of current standard-of-care regimens in both early and advanced stage HCC. Further validation studies are warranted to solidify the clinical utility of ISS and its integration into the decision-making process for HCC immunotherapy. Citation Format: Ju-Seog Lee, Sun Young Yim, Seung-Woo Baek, Sung Hwan Lee, BoHwa Sohn, Yun Seong Jeong, Sanghee Kang, Kena Park, Hyewon Park, Sunyoung S. Lee, Ahmed O. Kaseb, Ji Hoon Kim, In-Sun Chu. Predictive genomic biomarkers for atezolizumab plus bevacizumab combination immunotherapy response in liver cancer: Insights from the IMbrave150 trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB090.

Abstract 5359: Targeted engineering mRNA 3′UTR length enhances immunotherapy response in prostate cancer

Abstract Background: Global mRNA 3′untranslated region (3′UTR) shortening through alternative polyadenylation (APA) has been widely observed in most cancers; however, it has not been demonstrated whether targeted interference of specific oncogenic mRNA 3′UTR lengths can inhibit tumor growth and potentiate immunotherapy response in prostate cancer. Methods: DaPars algorithm was applied for de novo identification of dynamic alternative polyadenylation (APA) during prostate cancer progression to the lethal phase; 3′UTR polyadenylation site (PAS) locations and usages were identified by Poly(A)-ClickSeq (PAC-seq) and 3′RACE; APA transcripts were quantified by RHAPA assay; a 3′UTR CRISPR/dCas13 Engineering System (3′UTRCES) was developed to manipulate the length of desired 3′UTRs; RIP-qPCR and PAR-CLIP-qPCR assays were used to determine the mechanistic basis of 3′UTRCES in APA editing; RNA-seq was utilized to evaluate the off-target effects; TT3 Lipid-like nanoparticles (LLN) were applied for intratumoral delivery of 3′UTRCES RNA molecules for targeted 3′UTR therapy. Quantitative proteomics and immunoprecipitation assays were conducted to investigate how major histocompatibility complex class I (MHC-I) substrates were recognized by SPSB1-containing ubiquitin ligase complex for degradation; Flow cytometry and T cell cytotoxicity assays were performed to evaluate MHC-I level and killing of tumor cells by antigen-stimulated CD8+ T cells. Results: 3′UTR globally shortens during prostate cancer progression to castration-resistance. Through blocking the proximal PASs, 3′UTRCES efficiently and specifically reverses the 3′UTR shortening of novel APA-linked, clinically-relevant prostate cancer oncogenic mRNAs, such as SPSB1, leading to reduced SPSB1 mRNA translation and prostate cancer cell proliferation. Intratumoral injection of TT3 LLN encapsulating 3′UTRCES RNA molecules effectively and safely inhibits prostate tumor growth in engrafted and transgenic mouse models. Notably, downregulation of SPSB1 protein by 3′UTRCES disrupts the interactions of SPSB1-containing ubiquitin ligase complex, leading to compromised ubiquitination-mediated MHC-I degradation and increased stability and abundance of MHC-I protein. Consistently, 3′UTRCES enhances MHC-I-regulated antigen presentation and thereby augments CD8+ T cell-mediated cytotoxicity, which suggest the potentials of 3′UTRCES to sensitize prostate cancer to immune checkpoint therapies. Importantly, 3′UTR shortening of SPSB1 mRNA is significantly associated with decreased MHC-I expression, reduced cytotoxic T-cell infiltration and activation in castration resistant prostate cancer patients. Conclusions: Our results establish the concept of “3′UTR targeted therapy” for treatment of prostate cancer with broad applications to other cancers and other 3′UTR-related diseases. Citation Format: Furong Huang, Fuwen Yuan, Ya Cui, Lei Li, Kexin Li, Zhifen Cui, Jingyue Yan, Qiang Chen, Christopher Nicchitta, Wenbin Ye, Yuebao Zhang, William Hankey, Jeffrey Everitt, Ming Chen, Jiaoti Huang, Hongyan Wang, Xin Lu, Eric Wagner, Yizhou Dong, Wei Li, Qianben Wang. Targeted engineering mRNA 3′UTR length enhances immunotherapy response in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5359.

Abstract 7385: Explainable AI model incorporating uncertainty estimation for enhanced MSI-H prediction and immunotherapy response in gastrointestinal cancer

Abstract Background: Microsatellite instability-high (MSI-H) tumors respond well to immune checkpoint blockade and oftentimes not to chemotherapeutics. Despite value of determining MSI status to guide therapy, many patients’ samples are not untested. Deep learning models may be able to predict MSI status by analyzing hematoxylin and eosin (H&amp;E) stained whole-slide images (WSIs). Validation of this tool will provide another tool to increase MSI testing. However, to be deployed into clinical routine care, prediction models need be externally validated in large and diverse patient cohorts. In addition, these models should provide uncertainty of prediction to help clinicians make informed decisions. Results: In this study, we introduce a novel Bayesian prediction model using whole-slide images (WSIs) and deep Gaussian processes (DGPs) in a weakly supervised learning context. Extensively tested on large datasets (n=3,146) from multiple centers, our model not only demonstrated superior performance but also showed that incorporating uncertainty into predictions significantly improves MSI prediction accuracy, achieving AUROC of &amp;gt;0.91 in colon cancer and &amp;gt;0.94 in gastric cancer. Additionally, an in-depth analysis within the gastric cancer cohort indicated a significant correlation between predicted MSI-H regions and immunotherapy response. Patients who responded to immune checkpoint inhibitors had a higher proportion of MSI-H regions (P-value &amp;lt; 0.05). This correlation was also observed in patients categorized as MSS but responsive to ICIs, highlighting the potential of our model to identify MSI-H patterns not detected through standard laboratory tests. This advancement could lead to more precise patient selection for ICI therapy, enhancing personalized treatment strategies in gastrointestinal cancer. Citation Format: Sunho Park, Minj Kim, Ji-Youn Sung, Jeong Hwan Park, Sung Hak Lee, Sam C. Wang, Jaeho Cheong, Tae Hyun Hwang. Explainable AI model incorporating uncertainty estimation for enhanced MSI-H prediction and immunotherapy response in gastrointestinal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7385.

Abstract 6557: Longitudinal cell-free tumor load dynamics represent an early endpoint for immunotherapy response in non-small cell lung cancer

Abstract Background: Liquid biopsies can inform treatment strategies by rapidly and accurately assessing tumor burden; with emerging data supporting the clinical utility of circulating cell-free tumor DNA (ctDNA) as an early endpoint of immunotherapy response. Methods: We performed targeted error-correction sequencing of ctDNA (n=330) and matched white blood cell (WBC) DNA (n=109) from 109 patients with advanced non-small cell lung cancer (NSCLC) who received immune checkpoint inhibitor monotherapy (n=79) or immunotherapy-containing combination regimens (n=30). Variant cellular origin was determined using a tumor-independent WBC DNA-informed approach. The maximum mutant allele fraction (maxMAF) of tumor-derived mutations was tracked longitudinally to assess changes in total cell-free tumor load (cfTL). Results: Among 3,418 variants with resolved cellular origin, 2,452 (72%) were tumor-derived, 125 (4%) were germline, while 841 (25%) were related to clonal haematopoiesis (CH). Cell-free DNA fragments harbouring tumor-derived mutations were significantly shorter than fragments containing wild-type alleles; however, fragment length alone was insufficient to distinguish CH variants from wild-type. Overall, 97 (89%) patients with &amp;gt;1 detectable tumor mutation were considered for cfTL tracking and molecular response assessment. Clearance of cfTL indicated molecular response (mR) whereas persistence indicated molecular progression (mPD). Time-course analyses, aiming to establish the optimal timing for molecular response assessment, revealed that early cfTL clearance within 3-9 weeks was significantly linked to improved survival outcomes. Notably, blood tumor mutation burden above or below 16 mutations/megabase showed no association with overall survival (OS; log rank p=0.98) or progression-free survival (PFS; log rank p=0.95). Of 81 patients evaluated for early on-therapy molecular responses, 28 (35%) were classified as having an mR, while 53 (65%) patients were classified in the mPD category. The median time to mR was 5 weeks in patients receiving immune checkpoint monotherapy and 6 weeks in patients receiving chemo-immunotherapy combination regimens. Patients in the mR group achieved longer OS (log rank p=0.001) and PFS (log rank p=0.0003) compared to those with mPD. Assessment of landmark PFS at 6 months demonstrated a significant association between ctDNA molecular response and durable clinical benefit (DCB) in patients receiving immune checkpoint monotherapy (p &amp;lt; 0.001, Fisher’s exact test), and a numerical association with DCB in patients on chemo-immunotherapy (p=0.07, Fisher’s exact test). Conclusions: Longitudinal tracking of ctDNA provides a real-time and accurate approach for monitoring immunotherapy response. These findings underscore the clinical utility of employing ctDNA molecular response to inform clinical decision-making. Citation Format: Lavanya Sivapalan, Bahar Alipanahi, Archana Balan, Jamie E. Medina, Noushin Niknafs, Erica Peters, Jaime Wehr, Alissa Konicki, Mimi Najjar, Bryan Chesnick, Gavin Pereira, Sarah Rongione, Nisha Rao, Michael Rongione, Brittany Shavatt, Lorenzo Rinaldi, Benjamin Levy, Victor E. Velculescu, Patrick M. Forde, Valsamo Anagnostou. Longitudinal cell-free tumor load dynamics represent an early endpoint for immunotherapy response in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6557.

Abstract 2408: Comprehensive genomic profiling of ctDNA reveals distinct genomic signatures and therapeutic implications for immunotherapy response in advanced head and neck cancer

Abstract Background: Head and Neck Cancer (HNC) is highly prevalent malignancy in Southeast Asia. We investigated comprehensive genomic profiling (CGP) of ctDNA, aimed to compare genomic landscapes between responders (R) and non-responders (NR) to immunotherapy among advanced HNC patients. Methods: An observational study, ctDNA was evaluated in 69 advanced HNC patients both at the baseline (BL) and during follow up (FL). OncoIndx® CGP was used to identify patient-specific genomic alterations in the ctDNA cohort. Raw sequence alignment and variant calling were performed using iCare® software. Progression-free survival (PFS) and overall survival (OS) were assessed using Kaplan-Meier statistics. Results: Total 250 mutations, encompassing pathogenic (P), likely pathogenic (LP), and variants of unknown significance (VUS), were identified at BL. In FL samples a slight decrease in the overall number of mutations was observed. Loss-of-function (LOF) KMT2C, MSH6 mutations, and activating HNF1α mutations were consistently present at comparable frequencies in BL and FL samples, exhibiting ubiquity across immunotherapy R and NR populations (F test, P 0.00063, OR 13). The variants did not demonstrate statistically significant association with PFS and OS. Most prevalent variants at follow-up emerged from tumor suppressor genes TP53, BRIP1, STAT5B, NF1, suggesting their potential role as therapy-resistant variants. PFS and OS were notably lower for patients with TP53 + BRCA pathway variants compared to their wild-type counterparts (median PFS TP53 + BRCA pathway mutated 2.7 months vs wt 9.1 months, HR = 4.1; median OS TP53 + BRCA pathway mutated 4.7 months vs 12.8 months for wt, HR 7.7). Similarly STAT5B carriers compared to the wild-type STAT5B-bearing population. Multivariate analysis further confirmed the independent role of TP53 + BRCA pathway and STAT5B variants as determinants for worst outcome (P 0.006, HR2.5). Population with prevalent TP53 and STAT5B LOF variants exhibited a strong negative correlation with the PD-L1 score compared to the population with their wild-type counterparts (P 0.03). Average scores for genome-wide homologous recombination deficiency (HRD), bTMB, and loss of LOH were low at BL and FL and did not correlate with the PD-L1 score. Interestingly, bTMB was low for the cohort, Tumor fraction (TF) emerged as an independent prognosticator for OS and PFS. Conclusions: ctDNA revealed distinct genomic signatures in R and NR populations at BL and FL. Significant prevalence of TP53, BRIP1, STAT5B, and NF1 in the NR population suggest a potential role in conferring immunotherapy resistance. Genomic signatures, TMB and TF impacted survival of immunotherapy responders. Integrating CGP into SOC protocol may help in identifying therapy resistance in advanced HNC patients who did not respond to initial treatment. Citation Format: Atul Bharde, Vanita Noronha, Mrunal Ratnaparkhi, Vijay Patil, Bhagwat Jadhav, Sangeeta Prajapati, Anuradha Choughule, Pratik Chandrani, Sumit Haldar, Fauzul Moubeen, Nandini Menon, Kanchan Hariramani, Madhura Basavalingegowda, Aarthi Ramesh, Jayant Khandare, Pankaj Chaturvedi, Gowhar Shafi, Kumar Prabhash. Comprehensive genomic profiling of ctDNA reveals distinct genomic signatures and therapeutic implications for immunotherapy response in advanced head and neck cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2408.

Abstract 7620: Immuno-transcriptomic profiling of blood and tumor tissue identifies gene signatures associated with immunotherapy response in metastatic bladder cancer

Abstract Muscle-invasive bladder cancer (MIBC) accounts for 25% of bladder cancer cases. Despite the broader usage of immune checkpoint blockade targeting the PD-1/PD-L1 axis, the response rate and survival of patients remain low for this disease. Redirecting swiftly these patients toward alternative therapeutic strategies upon immunotherapy failure should be a priority. So far, no marker allows to precisely determine early outcome to the treatment.Blood-based biomarkers represent ideal candidates for the development of non-invasive immuno-oncology-based assays. However, to date, no blood biomarker has been validated to predict clinical response to immunotherapy. In this study, we used next generation sequencing (RNAseq) on bulk RNA extracted from whole blood and tumor samples in a pre-clinical MIBC mouse model. We aimed at identifying biomarkers associated with immunotherapy response and to assess the potential application of simple non-invasive blood biomarkers as therapeutic decision-making assay compared to tissue-based biomarkers. We established that circulating immune cells and the tumor microenvironment (TME) display highly organ-specific transcriptional responses to ICI. Interestingly, a common lymphocytic activation signature can be identified in both compartments associated with the efficient response to immunotherapy, including a blood specific CD8+ T cell activation/proliferation signature which predicts immunotherapy response. Citation Format: Pedro J. Romero, Emma Desponds, Davide Croci, Victoria Wosika, Noushin Hadadi, Sara Fonseca Cost, Laura Ciarloni, Marco Ongaro, Hana Zdimerova, Marine M. Leblond, Sahar Hosseinian-Ehrensberger, Grégory Verdeil. Immuno-transcriptomic profiling of blood and tumor tissue identifies gene signatures associated with immunotherapy response in metastatic bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7620.