Immune Checkpoint Inhibitors Response Research Articles

The Role of Aging and Senescence in Immune Checkpoint Inhibitor Response and Toxicity.

Cellular senescence accumulates with age and has been shown to impact numerous physiological and pathological processes, including immune function. The role of cellular senescence in cancer is multifaceted, but the impact on immune checkpoint inhibitor response and toxicity has not been fully evaluated. In this review, we evaluate the impact of cellular senescence in various biological compartments, including the tumor, the tumor microenvironment, and the immune system, on immune checkpoint inhibitor efficacy and toxicity. We provide an overview of the impact of cellular senescence in normal and pathological contexts and examine recent studies that have connected aging and cellular senescence to immune checkpoint inhibitor treatment in both the pre-clinical and clinical contexts. Overall, senescence plays a multi-faceted, context-specific role and has been shown to modulate immune-related adverse event incidence as well as immune checkpoint inhibitor response.

Comprehensive analysis of single cell and bulk RNA sequencing reveals the heterogeneity of melanoma tumor microenvironment and predicts the response of immunotherapy.

Tumor microenvironment (TME) heterogeneity is an important factor affecting the treatment response of immune checkpoint inhibitors (ICI). However, the TME heterogeneity of melanoma is still widely characterized. We downloaded the single-cell sequencing data sets of two melanoma patients from the GEO database, and used the "Scissor" algorithm and the "BayesPrism" algorithm to comprehensively analyze the characteristics of microenvironment cells based on single-cell and bulk RNA-seq data. The prediction model of immunotherapy response was constructed by machine learning and verified in three cohorts of GEO database. We identified seven cell types. In the Scissor+ subtype cell population, the top three were T cells, B cells and melanoma cells. In the Scissor- subtype, there are more macrophages. By quantifying the characteristics of TME, significant differences in B cells between responders and non-responders were observed. The higher the proportion of B cells, the better the prognosis. At the same time, macrophages in the non-responsive group increased significantly. Finally, nine gene features for predicting ICI response were constructed, and their predictive performance was superior in three external validation groups. Our study revealed the heterogeneity of melanoma TME and found a new predictive biomarker, which provided theoretical support and new insights for precise immunotherapy of melanoma patients.

Mutational variant allele frequency profile as a biomarker of response to immune checkpoint blockade in non-small cell lung Cancer

IntroductionIdentifying new biomarkers for predicting immune checkpoint inhibitors (ICIs) response in non-small cell lung cancer (NSCLC) is crucial. We aimed to assess the variant allele frequency (VAF)-related profile as a novel biomarker for NSCLC personalized therapy.MethodsWe utilized genomic data of 915 NSCLC patients via cBioPortal and a local cohort of 23 patients for model construction and mutational analysis. Genomic, transcriptomic data from 952 TCGA NSCLC patients, and immunofluorescence (IF) assessment with the local cohort supported mechanism analysis.ResultsUtilizing the random forest algorithm, a 15-gene VAF-related model was established, differentiating patients with durable clinical benefit (DCB) from no durable benefit (NDB). The model demonstrated robust performance, with ROC-AUC values of 0.905, 0.737, and 0.711 across training (n = 313), internal validation (n = 133), and external validation (n = 157) cohorts. Stratification by the model into high- and low-score groups correlated significantly with both progression-free survival (PFS) (training: P < 0.0001, internal validation: P < 0.0001, external validation: P = 0.0066) and overall survival (OS) (n = 341) (P < 0.0001). Notably, the stratification system was independent of PD-L1 (P < 0.0001) and TMB (P < 0.0001). High-score patients exhibited an increased DCB ratio and longer PFS across both PD-L1 and TMB subgroups. Additionally, the high-score group appeared influenced by tobacco exposure, with activated DNA damage response pathways. Whereas, immune/inflammation-related pathways were enriched in the low-score group. Tumor immune microenvironment analyses revealed higher proportions of exhausted/effector memory CD8 + T cells in the high-score group.ConclusionsThe mutational VAF profile is a promising biomarker for ICI therapy in NSCLC, with enhanced therapeutic stratification and management as a supplement to PD-L1 or TMB.

Unveiling major histocompatibility complex-mediated pan-cancer immune features by integrated single-cell and bulk RNA sequencing

Immune checkpoint inhibitors (ICIs) have transformed cancer therapy, yet persistent challenges such as low response rate and significant heterogeneity necessitate attention. The pivotal role of the major histocompatibility complex (MHC) in ICI efficacy, its intricate impacts and potentials as a prognostic marker, warrants comprehensive exploration. This study integrates single-cell RNA sequencing (scRNA-seq), bulk RNA-seq, and spatial transcriptomic analyses to unveil pan-cancer immune characteristics governed by the MHC transcriptional feature (MHC.sig). Developed through scRNA-seq analysis of 663,760 cells across diverse cohorts and validated in 30 solid cancer types, the MHC.sig demonstrates a robust correlation between immune-related genes and infiltrating immune cells, highlighting its potential as a universal pan-cancer marker for anti-tumor immunity. Screening the MHC.sig for therapeutic targets using CRISPR data identifies potential genes for immune therapy synergy and validates its predictive efficacy for ICIs responsiveness across diverse datasets and cancer types. Finally, analysis of cellular communication patterns reveals interactions between C1QC+macrophages and malignant cells, providing insights into potential therapeutic agents and their sensitivity characteristics. This comprehensive analysis positions the MHC.sig as a promising marker for predicting immune therapy outcomes and guiding combinatorial therapeutic strategies.

Defining clinically useful biomarkers of immune checkpoint inhibitors in solid tumours.

Although more than a decade has passed since the approval of immune checkpoint inhibitors (ICIs) for the treatment of melanoma and non-small-cell lung, breast and gastrointestinal cancers, many patients still show limited response. US Food and Drug Administration (FDA)-approved biomarkers include programmed cell death 1 ligand 1 (PDL1) expression, microsatellite status (that is, microsatellite instability-high (MSI-H)) and tumour mutational burden (TMB), but these have limited utility and/or lack standardized testing approaches for pan-cancer applications. Tissue-based analytes (such as tumour gene signatures, tumour antigen presentation or tumour microenvironment profiles) show a correlation with immune response, but equally, these demonstrate limited efficacy, as they represent a single time point and a single spatial assessment. Patient heterogeneity as well as inter- and intra-tumoural differences across different tissue sites and time points represent substantial challenges for static biomarkers. However, dynamic biomarkers such as longitudinal biopsies or novel, less-invasive markers such as blood-based biomarkers, radiomics and the gut microbiome show increasing potential for the dynamic identification of ICI response, and patient-tailored predictors identified through neoadjuvant trials or novel ex vivo tumour models can help to personalize treatment. In this Perspective, we critically assess the multiple new static, dynamic and patient-specific biomarkers, highlight the newest consortia and trial efforts, and provide recommendations for future clinical trials to make meaningful steps forwards in the field.

Strategies for overcoming tumour resistance to immunotherapy: harnessing the power of radiation therapy.

Immune checkpoint inhibitors (ICI) have revolutionized cancer treatment; yet their efficacy remains variable across patients. This review delves into the intricate interplay of tumour characteristics contributing to resistance against ICI therapy and suggests that combining with radiotherapy holds promise. Radiation, known for its ability to trigger immunogenic cell death and foster an in situ vaccination effect, may counteract these resistance mechanisms, enhancing ICI response and patient outcomes. However, particularly when delivered at high-dose, it may trigger immunosuppressive mechanism and consequent side-effects. Notably, low-dose radiotherapy (LDRT), with its capacity for tumour reprogramming and reduced side effects, offers the potential for widespread application. Preclinical and clinical studies have shown encouraging results in this regard.

A phase I/II trial of palbociclib, pembrolizumab, and endocrine therapy for patients with HR+/HER2- locally advanced or metastatic breast cancer (MBC): Clinical outcomes and stool microbial profiling.

1038 Background: Based on preclinical data highlighting synergy between CDK4/6 inhibitors and immune checkpoint inhibitors (ICIs), we conducted a phase I/II study of palbociclib, pembrolizumab, and endocrine therapy (ET) in pts with HR+/HER2- MBC. Given evidence suggesting a correlation between ICI response and stool microbiome composition in a wide array of cancers, we sought to determine if this biomarker could segregate responders in our cohort. Methods: Pts with stage IV HR+/HER2- MBC were enrolled and treated with palbociclib, pembrolizumab, and ET. Cohort 1 enrolled pts with stable disease on palbociclib + ET for at least 6 months. Cohort 2 and 3 enrolled pts in the first-line (1L) setting, with cohort 3 designed with a palbociclib + ET lead-in to evaluate the immune potentiating effect of palbociclib (not included in this report). The primary endpoint was objective response rate (ORR); secondary endpoints included progression-free survival (PFS), overall survival (OS), and toxicity. Correlative studies assessed the association between the gut microbiome and response using previously published methods (1). Results: Between March 2017 and May 2022, 40 pts were accrued, with 4, 19 and 17 pts in cohorts 1, 2 and 3, respectively. There were 39 females and 1 male, with a median age of 51 (range 39-75). The ORR in cohorts 1, 2 and 3 were 2/4 (50%), 11/19 (58%) and 13/17 (76%), respectively. Median PFS across cohorts 2 and 3 (reflecting 1L therapy) was 25 mo (95% CI 21- not reached), and at a median follow-up of 35 mo, OS was 76% (95% CI 0.60-0.96). The most common grade 3/4 adverse events across all cohorts included neutropenia (83%), leukopenia (56%), elevated alanine aminotransferase (13%), elevated aspartate aminotransferase (13%), and thrombocytopenia (10%). Gut microbial profiling (total N=24 pts; Arm 2 N=7, Arm 3 N=17) demonstrated multiple species higher in abundance in pts with a response (p &lt; 0.05), with notable species belonging to the families Lachnospiraceae, Ruminococcaceae, and Rikenellaceae. Several metabolic pathways were enriched in responders (p-value &lt; 0.05), including pathways related to fatty acid biosynthesis and the tricarboxylic acid (TCA) cycle. Conclusions: Pembrolizumab added to palbociclib + ET in the 1L setting demonstrated a higher response rate compared to palbociclib + ET alone in HR+/HER2- MBC. Specific gut profiles were associated with response, with similar taxa of bacteria associated with ICI response in other tumor types (2). Enriched metabolic pathways may generate microbiota-derived metabolites that have an immunomodulatory effect. These results suggest that the gut microbiome may be associated with response to ICI combination therapy in MBC, which warrants further evaluation. 1. Dizman et al.,Nature Med 2022. 2. Spencer et al Science 2021. Clinical trial information: NCT02778685 .

Prognostic and predictive value of ultrasensitive ctDNA monitoring in a metastatic pan-cancer cohort treated with immune checkpoint inhibitors in the context of phase 1 clinical trials.

2510 Background: Determining which patients will achieve clinical benefit from immune checkpoint inhibition (ICI) therapy remains an open question. Liquid biopsy tests to assess baseline and early dynamics of circulating tumor DNA (ctDNA) may allow clinicians to track response more granularly and predict ICI response or resistance prior to imaging. However, lack of sensitivity may hinder accurate detection of low ctDNA levels in tumors with low shedding rates or during substantial drops and clearance in response. Methods: This study represents a cohort of 175 patients with refractory metastatic tumors from 18 different cancer types, who received 1-3 successive lines of ICI treatment in the context of phase-1 clinical trials. Thus far, 609 plasma samples from 90 stage-IV cancer patients receiving immune checkpoint inhibitor (ICI) treatment have been processed. ctDNA was profiled using the NeXT Personal assay, a liquid biopsy platform that leverages whole-genome sequencing of tumor and normal samples to create custom, patient-specific panels that include up to 1,800 somatic variants. This enables the detection of molecular residual disease (MRD) down to a detection threshold of 1 part per million (PPM) of ctDNA. Results: NeXT Personal assay detected positive levels of ctDNA in 99% (81/82) of plasma baseline samples, with a wide dynamic range, extending from 4.2 PPM (~0.00042% TF) to ~640,000 PPM (~64% TF) (median limit of detection = 2 PPM, 0.0002% TF). Lower ctDNA values at baseline were correlated with increased duration of PFS (log-rank p=0.017, HR=0.57, 95% CI 0.36-0.91) and extended OS (log-rank p=0.002, HR=0.46, 95% CI 0.28-0.75). Early reduction in ctDNA level from baseline to treatment cycle 3 was associated with significant increases in PFS (log-rank p=0.001, HR=0.36, 95% CI 0.19-0.67) and OS (log-rank p=0.015, HR=0.44, 95% CI 0.22-0.87), representing a &gt;3-fold increase in both median PFS and OS. ctDNA clearance resulted in significant improvement in both PFS and OS (PFS: log-rank p=0.002, HR=0.24, 95% CI 0.09-0.62; OS: log-rank p=0.01, HR=0.29, 95% CI 0.1-0.8). All plasma timepoints from periods of durable complete response (CR) assessed via RECIST 1.1 were ctDNA-negative, with a molecular clearance lead time of 277 days over radiographically confirmed CR. Conclusions: We demonstrate that early ctDNA dynamics are predictive of long-term ICI response in the advanced, pan-cancer ECT setting. Even in this refractory advanced cancer cohort, an ultra-sensitive assay was required for accurate MRD status determination, with low ctDNA detections down to 4.2 PPM that might otherwise have been missed. Taken together, these findings suggest a high sensitivity ctDNA assay is crucial for accurate monitoring of ICI response, providing information for more accurate patient management.

Tumor-derived ILT3 inhibition to reshape the immunosuppressive microenvironment and potentiate the PD-L1 blockade immunotherapy in lung adenocarcinoma.

e14647 Background: The low response of immune checkpoint inhibitors against PD-1/PD-L1 in cancer patients calls for further development of new immune targets. Immunoglobulin-like transcript (ILT)3 and its ligand ApoE have been demonstrated to be highly expressed in a variety of malignant tumor cells and involved in tumor biological behaviors, including invasion and angiogenesis. ILT3 targeting drugs are undergoing increasing preclinical and clinical trials. However, the role of tumor-derived ILT3 in immune regulation is unclear. The aim of this study was to investigate the immunomodulatory effect of tumor-derived ILT3 and its immunotherapy therapeutic efficacy that combination with PD-L1 blockade in NSCLC. Methods: The correlations between ILT3/ApoE expression and prognosis of NSCLC patients were analyzed basing on public databases. Multiplex immunofluorescence was performed to analyze the correlations between tumor-derived ILT3/ApoE expression and intratumoral immune cells infiltration in human adenocarcinoma tissues. The impact of ILT3 and ApoE on tumor-associated macrophage (TAM) recruitment and polarization were evaluated by transwell migration assay, flow cytometry, and RT-PCR, while their direct impact on T cell survival and cytotoxicity was detected by flow cytometry. Using lung cancer xenograft murine models, we further confirmed the pro-tumoural activity of tumor-derived gp49B and analyzed its correlations with immune cells in vivo. Tumor immunotherapy models targeting at gp49B and/or PD-L1 were established in C57BL/6 mice inoculated with LLC cells. Gp49b inhibition was implemented by infection of specific knockdown lentivirus and PD-L1 was blocked using mouse neutralizing antibodies. Flow cytometry was performed to detect the frequency and phenotype of macrophages and T cells in the tumors, spleen, and blood of the mice. Results: Patients with high expression of ILT3 had significantly worse prognosis in LUAD, but not in LUSC. In vitro assays demonstrated that tumor-derived ILT3/ApoE promoted recruitment and M2-like polarization of TAMs and directly inhibited the proliferation and cytotoxicity of T cells, which had been further confirmed in vivo models. Moreover, ILT3 (gp49B) inhibition enhanced anti-tumor immunity and suppressed tumor progression by counteracting TAM- and dysfunctional T cell- induced immunosuppressive TME; the combined inhibition of gp49B and PD-L1 showed the most dramatic tumor retraction in LLC xenograft models. Conclusions: Tumor-derived ILT3 overexpression suppressed anti-tumor immunity by recruiting M2-like TAMs and directly impairing T cell activities, while ILT3 inhibition counteracted above immunosuppression and potentiated the efficacy of PD-L1 blockade in LUAD. Our study verified that ILT3 may be a promising novel immunotherapeutic target for LUAD patients.

Durability of immune checkpoint inhibitor (ICI) response following treatment discontinuation in advanced merkel cell carcinoma (MCC).

9596 Background: Advanced MCC has a high response rate to ICI therapy, but the durability of responses once treatment is discontinued remains unclear. We therefore reviewed the long-term outcomes of advanced MCC patients at our institution who discontinued ICI treatment after achieving favorable initial response. Methods: In an IRB-approved single institution retrospective review of advanced MCC patients, we analyzed all patients who received at least one dose of anti-PD(L)1 monotherapy for unresectable or metastatic disease, achieved stable disease (SD) or better, and discontinued treatment for a reason other than disease progression. Duration of response and outcomes of subsequent therapy were assessed. Results: Of 195 advanced MCC patients treated with ICI, we identified 45 who met study criteria. Of these, 21 (47%) had a complete response (CR) to initial ICI treatment, 23 (51%) a partial response (PR) and 1 (2%) SD. Twenty-five (56%) patients discontinued ICI electively and 20 (44%) discontinued due to toxicity. In total, 21 of the 45 patients (47%) experienced disease progression at a median of 11.2 months (range 2.1-22.7 months) from ICI cessation. The median follow-up after ICI discontinuation for patients who have not experienced progression is 22.8 months (5.8-82.0 months). There was a lower rate of progression in patients who achieved CR vs. non-CR (24% vs 67%, p=0.006) and a trend towards a lower rate in those who discontinued electively vs. due to toxicity (36% vs 60%, p=0.14). For patients in whom the molecular subtype was known, there was a higher risk for progression in patients with viral MCC (12 of 16, 75%) compared to UV-associated MCC (4 of 13, 31%, p=0.02). Fifteen of the 21 patients (71%) who experienced progression were rechallenged with ICI therapy, including both single agent (12 patients, 57%) and combination (3, 14%) therapy. The remaining patients received locally-directed therapy only (3, 14%), chemotherapy (1, 5%), declined further treatment (1, 5%), or transferred care and were lost to follow up (1, 5%). Eleven of 15 ICI-retreated patients (73%) achieved an objective response to rechallenge, including all 3 patients who received combination therapy with ipilimumab+nivolumab. Twelve of the 45 patients have expired; 6 due to progressive MCC and remaining 6 known or suspected from unrelated causes. Conclusions: Patients with advanced MCC have a substantial risk of disease progression following treatment discontinuation despite initial favorable ICI response, 47% in our series with a median time to event of 11.2 months, particularly in those that achieve less than a complete response. In the setting of disease progression post-ICI discontinuation, most patients maintain sensitivity to retreatment with the same drug class. Virus-positive MCC may be a risk factor for post-discontinuation relapse, which should be validated in future studies.

CheckpointPx: A predictive radiology AI model of immune checkpoint inhibitor (ICI) benefit in non-small cell lung cancer (NSCLC).

8632 Background: Immune checkpoint inhibitors (ICIs) have dramatically transformed the field of non-small cell lung cancer (NSCLC) treatment. Despite the widespread use of PD-L1 as a biomarker in NSCLC, it has significant limitations as a reliable predictive biomarker for ICI response. Addressing this limitation, we have developed CheckpointPx, a non-invasive radiology AI tool to assist in ICI treatment selection for patients using only baseline CT scans. Here we demonstrate that CheckpointPx can predict improved outcomes specific to treatment with ICIs, presenting a new tool to address the shortage of reliable predictive ICI biomarkers in NSCLC and ultimately improve outcomes for patients undergoing immunotherapeutic interventions. Methods: CheckpointPx (v1.11) was trained on pre-treatment CT scans to predict response to ICIs from training data (D1: n=252 ICI recipients) from three institutions (A-C). In this study, we evaluated its performance in predicting response in two validation cohorts: a Treatment Dataset of patients receiving immunotherapy (D2: n=224, institutions B-D) and a Control Dataset of patients receiving platinum-based chemotherapy alone (D3: n=76, institution B). The response was defined as disease control per RECIST v1.1. Experienced radiologists and physicians delineated target lesions, and a deep learning model segmented pulmonary vessels. From these segmented regions, radiomic features were extracted using the Picture Health Px platform and were used to generate a radiomics benefit score and corresponding benefit groups using D1. The ability of benefit groups to stratify patients by progression-free survival (PFS) was compared across D2 and D3 to evaluate its utility in identifying patients who would benefit from ICI over chemotherapy. Results: D2 and D3 contained a mix of treatment lines (1st-4th) and predominantly late-stage tumors (Stage 3/4, &gt;85%). CheckpointPx included 16 features, such as measurements of intra-tumoral heterogeneity and vessel twistedness and branching patterns. Within the treatment dataset (D2), CheckpointPx was found to significantly stratify ICI patients by progression-free survival (PFS) with HR=0.68 (95% CI: 0.52 - 0.93, p=0.019). When applied to the control dataset, D3, benefit groups failed to stratify patients treated with chemotherapy by outcome (HR=0.91 [95% CI: 0.51-1.61], p=0.740), indicating that the signature was specific to ICI response. Conclusions: CheckpointPx demonstrated the ability to identify NSCLC patients who would benefit from ICI over chemo. The model’s association with PFS among ICI recipients, but not patients receiving chemotherapy alone, suggests that the signature is predictive of immunotherapy-related outcomes rather than generally prognostic. Additional independent, multi-site and prospective validation is warranted.

Exploring the correlation between high HRD status and immunotherapy response in melanoma.

e21541 Background: Homologous recombination deficiency (HRD) status demonstrates DNA instability in tumor cells and has been implicated as a response marker for immune checkpoint inhibitors (ICI). Here, we explore the correlation between high HRD status and ICI response biomarkers, homologous recombination repair (HRR) mutations, and the prognostic advantage of high HRD status following ICI in cutaneous melanoma patients. Methods: Melanoma samples (N = 2158) were profiled for genomic loss of heterozygosity (LOH) by NGS at Caris Life Sciences (Phoenix, AZ). As a surrogate for HRD, LOH-high was defined as LOH at ≥ 16% of the segments analyzed (up to 552). PD-L1 expression was assessed using IHC (SP142; positive (+): ≥ 1%). Mismatch repair deficiency/microsatellite instability-high (dMMR/MSI-H) was tested by IHC/NGS.Tumor mutational burden (TMB)-high was defined as ≥ 10 mutations/Mb. interferon gamma (IFN-g) and T-cell inflamed scores. Real-world overall survival (rw-OS) information was obtained from insurance claims data, with Kaplan-Meier estimates calculated from the start of immunotherapy until the last date of contact. Mann-Whitney U, Chi-square, and Fisher exact tests were applied where appropriate, with p-values adjusted for multiple comparisons. Results: Melanoma patient samples include - cutaneous: 1853; acral: 130; mucosal: 175, with LOH-high observed in 8.3% of cutaneous specimens, 13.1% of acral, and 30.9% of mucosal. Firstly, most biomarkers associated with response to ICI (PD-L1, TMB-high, total neoantigen load, IFN-g score, T-cell inflamed level, and dMMR/MSI-H) were not significantly different between LOH-high and LOH-low cohorts in all melanoma subtypes. However, TMB-high was significantly more prevalent in LOH-low cutaneous melanoma patients (54.9% vs 63.3%, p = 0.039). Prevalence of HRR gene mutations was not significantly different between high and low LOH groups in all cohorts, except for the ATRX gene which exhibited a significantly higher prevalence in the high LOH cutaneous (8.6% vs 1.3%, p &lt; 0.001) and mucosal (28.8% vs 2.5%, p &lt; 0.00001) melanoma specimens. Analysis of rw-OS showed no improvement in the treatment of LOH-high cutaneous melanoma patients with ICI compared to LOH-low (HR: 1.397 [95% CI: 0.759- 2.569], p = 0.281). Conclusions: This study demonstrates that HRDness reflected by the high-LOH status in melanoma did not correlate with mutations in HRR genes. In addition, melanoma specimens with high HRD status did not exhibit an overall higher prevalence of biomarkers associated with ICI response. Our study did not demonstrate improved survival outcomes in patients with high HRD status following anti-PD1 therapies. Future investigation is needed to assess other therapeutic approaches for these patients such as PARP inhibitors.

Prediction of immune checkpoint inhibitor (ICI) response in patients with urothelial cancer (UC) by a novel RNA-based ICI response signature (ICI-PRS).

Prediction of immune checkpoint inhibitor (ICI) response in patients with urothelial cancer (UC) by a novel RNA-based ICI response signature (ICI-PRS).

Relationship between dynamic changes in circulating tumor fraction and real-world imaging with real-world survival in patients with solid tumors treated with immunotherapy.

3046 Background: There is an unmet need for a sensitive biomarker that can determine which patients will confer long term benefit from immune checkpoint inhibitors (ICI). While radiologic imaging is the current standard of care for assessing ICI response, imaging can be difficult to interpret and is typically only assessed at 3 month intervals. Dynamic changes in circulating tumor fraction (TF) is a potential biomarker for monitoring ICI response. Here we evaluate the clinical benefit of a molecular biomarker, xM for treatment response monitoring (TRM), in addition to imaging, in a real-world (rw), pan-cancer cohort treated with ICIs. Methods: Using the Tempus liquid biopsy assay, ctDNA TF was computed by applying an ensemble algorithm incorporating copy number variant data and pathogenic variant allele frequencies. Deidentified patient records from the Tempus multimodal database were analyzed if patients had a baseline xF test ≤ 40 days prior to the start of ICI (alone or in combination with chemotherapy [CT], median = 13 days) and an on-treatment xF test 15-180 days post-ICI (median=93 days) and clinical response evaluated via imaging 15-126 days post ICI (median=77 days). Molecular responders (MR) were defined as patients with a ≥ 50% decrease in TF between tests. Rw-imaging, as documented by a provider in their clinical notes, was categorized as complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD), Rw overall survival (rwOS) was defined as time from the imaging date closest to on-treatment xF test to death. A likelihood ratio test at a two-sided 5% significance level was performed to assess if a Cox proportional hazards model incorporating both xM Monitor and rw-imaging as covariates (full model) had predictive power over a reduced model with only rw-imaging as a covariate. Results: The evaluable cohort (N=51) – 53% female, median age 64 yrs – had &gt;10 advanced solid tumors (NSCLC 29% and breast cancer 18%). The majority of patients (69%) received ICI + CT, while 31% received ICI alone. 24 patients achieved MR (79% on ICI monotherapy, 21% on ICI + CT). Concordance of response markers is shown in the table. In the full model, xM was a significant predictor of rwOS (HR=0.33 [0.13, 0.84], p=0.02). The added information provided from xM was significant and superior compared to the reduced model of only rw-imaging (p=0.02). For patients with nMR and CR/PR/SD predicted median survival was 10 months whereas for patients with MR and CR/PR/SD predicted median survival was 16 months. Conclusions: MRs achieved significantly longer rwOS than nMRs and provides significant power in predicting rwOS beyond rw-imaging response. xM used for TRM can help identify nMRS who can discontinue therapy and be spared ICI toxicity. [Table: see text]

Correlation between metastatic site and immunotherapy efficacy in patients with advanced dMMR/MSI colorectal cancer: Real-World Italian multicentric retrospective study (Colon-MSI).

e15544 Background: Immune checkpoint inhibitors (ICIs) are the gold standard therapy in metastatic colorectal cancer (mCRC) patients (pts) with microsatellite instability (MSI). The Colon-MSI study aimed to describe a cohort of MSI mCRC pts treated with ICIs before Italian pembrolizumab approval and to evaluate the efficacy, safety, and possible predictive factors of response in a real-world setting. Methods: We retrospectively collected data of pts with MSI mCRC treated with ICIs before June 30, 2023, in 16 Italian Cancer Centers. The OS was calculated from the diagnosis of metastatic disease, and the PFS from the beginning of ICIs. We explored the correlation between clinicopathological factors, survival outcomes, and treatment response. Results: Between January 2021 and June 2023, we reported 83 consecutive pts with data available. Among all, the median age was 61 years (23-86), 42 (51%) were female, and 45 (54%) had a ECOG PS 0; 35 (42%) pts were at stage IV at diagnosis, and 61 (74%) had right colon tumor site. The most common metastatic sites were liver (35%), lymph nodes (43%), peritoneum (31%), and lung (15%); 48 (58%) pts had a single metastatic site. 33 (39%) pts had a mucinous adenocarcinoma, 32 (39%) BRAF mutated, 32 (39%) RAS mutated, and 26% presented a Lynch syndrome. The majority of pts (69%) were pre-treated, and 26 pts (31%) received ICIs in first line. Nivolumab alone or plus Ipilimumab, and Pembrolizumab, were administered in 23 (28%), 3 (4%), and 57 (68%) pts, respectively. The median follow-up was 23 (1-65) months (m) and the median duration of treatment was 23 m (0-65) with 27 pts still ongoing. Treatment-related severe toxicities (G3 or G4) were observed only in 5.6% of pts. The median OS and PFS were not reached; the mean OS was 45.6 m (IC 95% 39.6-51.6) and the mean PFS was 38.8 m (IC 95% 32.5-45.1). Complete response (CR) was observed in 20 pts (24%), partial response (PR) in 28 (34%), stable disease (SD) in 19 (23%) and progression disease (PD) in 16 (19%). Overall response (ORR) was observed in 48 pts (57.8%; 95 %IC 0.31- 0.53), and disease control rate in 67 pts (80.7%; 95% IC 0.11– 0.29). Lung metastatic site was associated with poorer outcome in terms of OS (p = 0.001, HR 3.88 IC 95% 1.7-8.9), PFS (p = 0.045 HR = 2.31 IC95% 1-5.2), and ORR (p = 0.015 OR = 6.19 IC95% 1.4-26.9). Significantly worse PFS was also observed in pts with liver metastasis (p = 0.009 HR = 2.5 IC 95% 1.3-4.9). Conclusions: Our data confirm that ICIs are effective and well-tolerated treatment in MSI mCRC pts, with long-term clinical outcomes reported. These results suggest an unfavorable correlation between lung and liver metastasis and the ICI response. Further biomolecular analysis will be provided in the future.

Real-world and clinical trial validation of a deep learning radiomic biomarker for PD-(L)1 immune checkpoint inhibitor response in stage IV NSCLC.

102 Background: Immune checkpoint inhibitor (ICI) therapy is standard-of-care for treatment of mutation-negative advanced non-small cell lung cancer (NSCLC). However, given known inaccuracy of PD-(L)1 markers, there is an unmet need to better identify patients most likely to derive clinical benefit from ICI. We developed and externally validated a generalizable CT imaging-based biomarker to predict response to ICI. Methods: We developed and validated a deep learning radiomic biomarker using an internally curated real-world dataset (RWD) of 2,010 stage IV NSCLC patients treated with PD-(L)1 ICIs in academic and community settings from US and Europe. Patients with missing baseline imaging, missing follow-up data, or EGFR/ALK oncogenic driver mutations were excluded, resulting in a total of 1,188 subjects. This RWD consisted of a discovery cohort (Dataset A, N=844) and a temporally distinct holdout cohort (Dataset B, N=344), which were used to generate performance metrics of the biomarker. To test generalizability, we validated our biomarker in a prospective clinical trial dataset evaluating Sasanlimab in PD-(L)1 therapy-naïve, advanced NSCLC patients (NCT02573259, Dataset C, N=54). We utilized a two-stage learning approach to model 6-month PFS. First, we used an independent multi-task deep-learning feature extractor trained on 19,184 whole chest CT scans. Second, we input the extracted features into a Cox proportional hazard (CoxPH) model along with age, sex, and baseline lesion measurements (sum of longest diameter and distant metastases counts), and the model generated a time-dependent PFS function and a response score. We performed 6-fold cross-validation on Dataset A to train and evaluate the models, which were subsequently ensembled and applied to independent Datasets B and C. To assess independence from PD-L1 status and key demographic covariates, we herein report multivariate adjusted hazard ratios (HR) for the group identified as low-risk based on the biomarker. Results: In Dataset A, the biomarker showed a cross-validation PFS adjusted HR of 0.49 (95% CI 0.38-0.63) in the all-comers cohort and 0.28 (0.17-0.46) in the first-line ICI monotherapy cohort (1LMono). In Dataset B, the PFS adjusted HRs were 0.54 (0.35-0.83) in all-comers and 0.18 (0.05-0.61) in 1LMono. In Dataset C, the adjusted HRs were 0.30 (0.14-0.68) for PFS, 0.29 (0.10-0.83) for OS, 0.31 (0.14-0.72) for TTP. Conclusions: In our validations in RWD and clinical trial cohorts, a deep-learning radiomic biomarker based on routine pre-treatment CT scans predicted response to ICI and stratified patients independently from PD-L1 status. This tool may inform clinical decision-making, such as to help guide whether concomitant chemotherapy may not be needed. In future work, we plan to further validate our approach in larger prospective datasets and expand its use to new indications.

Retrospective analysis on association of body mass index and immune checkpoint inhibitor response.

e14536 Background: The relationship between Body Mass Index (BMI) and cancer is a complex. We aim to study the impact of BMI on the response to immunotherapy in cancer patients. Methods: We did a retrospective observational study to investigate the influence of different BMI groups on patients receiving Immune Checkpoint Inhibitors (ICIs) at the University of Vermont Cancer Centre. We examined the medical records of people who received ICIs between January 2017 and June 2022 and collected demographic data, including age, sex, ethnicity, cancer stage, BMI, type and metastasis. We looked at Hazard Ratio (HR) in BMI subcategories compared to normal. The occurrence of immune-related adverse events (irAEs), metastasis and receipt of chemotherapy in different BMI subgroups was evaluated with relative risks (RRs). Results: A total of 288 cases were identified, out of which 269 had documented BMI, including 58% males, 94.8% whites with 64.17 years mean age. Lung cancer was most common at 41.3%, 46.5% were and 63.2% were stage 4. Total 71.4% of people received Pembrolizumab and 42.8% had concomitant chemotherapy. The median ECOG was 1 and the Charlson comorbidity index was 6. irAEs observed in 33% of cases, whereas mortality in 36%. The BMI distribution had 36.1% normal, 27.1% overweight, 16.5% obese, 14.5% extremely obese and 5.6% underweight. The HR in underweight subgroup was significant at 5.223 (p &lt;0.001; 95CI: 2.2 to 12.4) compared to normal. The HR of overweight, obese and extremely obese decreased with HR of 1.15, 0.77 and 0.18 respectively but wasn’t significant as seen in Table 1. Table also shows that relative risk of irAEs, cancer stage, metastasis and concomitant chemotherapy were not significant. Conclusions: Clinically significant association was found between being underweight and mortality in cancer patients receiving immunotherapy. [Table: see text]

Interplay of cachexia progression on the efficacy and toxicity of immune checkpoint inhibitors in patients with esophageal squamous cell cancer (ESCC): A longitudinal perspective.

e14629 Background: Immune checkpoint inhibitors (ICIs) have significantly improved the survival of patients with advanced esophageal squamous cell cancer (ESCC), however, the benefit of ICIs was limited to a few patients. It is vital to comprehend the factors influencing the response in order to identify patients who might benefit from ICIs. Cachexia, an intricate multifaceted syndrome characterized by the loss of skeletal muscle and substantial weight reduction, might impact on the immune response and efficacy of ICIs in cancer patients. The purpose of this study is to explore the impact of longitudinal dynamics of cachexia on the efficacy and adverse effect of ICIs for advanced ESCC patients. Methods: Advanced ESCC patients received at least two cycles of ICIs were enrolled from 2017 to 2021. The baseline and longitudinal changes of cachexia during ICI treatment were collected. Based on the longitudinal weight changes during ICI treatment, patients exhibiting cachexia at baseline were categorized into "reversible cachexia" and "irreversible cachexia" group, and patients without cachexia at baseline were also divided into "latent cachexia" and "cachexia-free" group. Kaplan-Meier curves and Cox regression analysis were performed to explore the impact of cachexia on the efficacy ICIs for ESCC patients. And chi-square test was used to evaluate the correlation between cachexia and immune-related adverse effects (irAEs). Results: A total of 278 individuals who had either received or were presently undergoing ICI treatment were enrolled, with the median progression free survival (PFS) of 5.8 months and overall survival (OS) of 8.3 months. Patients with cachexia before treatment had notably poorer outcomes, with median PFS of 7.9 vs 5.3 months (P=0.001), median time to progression (TTP) of 10.9 vs 6.1 months (P&lt;0.001), and median OS of 14.3 vs 9.2 months (P=0.001). In terms of the longitudinal dynamics of cachexia, significantly inferior outcomes were observed for patients in irreversible cachexia compared to reversible cachexia, with the PFS of 4.4 months and 9 months (P&lt;0.001), the TTP of 4.9 months and 9 months (P=0.006), and the OS of 7.8 months and 15 months, respectively (P=0.003). Although patients in latent cachexia group had inferior survival compared to cachexia-free group, no statistical difference was observed, with the PFS of 10.0 and 7.9 months and OS of 13.9 and 16.2 months. Besides, neither baseline nor longitudinal changes of cachexia was associated with irAEs for ESCC patients. Conclusions: This study indicated the impact of baseline and longitudinal cachexia on the efficacy of ICIs for advanced ESCC patients with ICIs. Dynamic monitoring and management of cachexia was recommended during the ICI treatment of ESCC patients.

Comparison of checkpoint inhibitor–based regimens as first-line therapy in advanced hepatocellular carcinoma: A Frequentist Network meta-analysis of randomized clinical trials.

e16136 Background: Multiple immune checkpoint inhibitor (ICI) based regimens have shown better responses and survival rates than previously used sorafenib/lenvatinib in advanced hepatocellular carcinoma (HCC). However, there was no direct comparison done among different ICI-based regimens. This network meta-analysis focuses on the efficacy of different ICI-based regimens in advanced HCC as first-line therapy. Methods: A comprehensive literature search was performed on PubMed, and Embase from the inception of data till 12/30/2023 with keywords for “Hepatocellular carcinoma” AND “Immune Checkpoint Inhibitors”. We screened 5120 articles and included 8 randomized clinical trials (RCTs, N = 5834). “R” software and netmeta package was used to conduct this network meta-analysis. Atezolizumab + cabozantinib was randomly chosen as the comparator group. Results: 2208 patients were treated with ICI-based two-drug regimens, 1102 patients were treated with ICI monotherapy, 1937 patients were treated with sorafenib, and 399 patients were treated with lenvatinib. Overall survival (OS) was 0.63 (0.43-0.93), 0.64 (0.43-0.98), and 0.69 (0.48-0.99) in favor of sintilimab + bevacizumab, atezolizumab + bevacizumab, and camrelizumab + rivoceranib, respectively, as compared to atezolizumab + cabozantinib. Progression free survival (PFS) was 0.83 (0.54-1.27), 0.89 (0.58-1.35), and 0.94 (0.61-1.45) in favor of camrelizumab + rivoceranib, sintilimab + bevacizumab, and atezolizumab + bevacizumab, respectively, as compared to atezolizumab + cabozentinib. Odds ratio of overall response rate (ORR) 2.03 (0.67-6.13), 1.7 (0.65-4.43), and 1.46 (0.58-3.67) in favor of sintilimab + bevacizumab, camrelizumab + rivoceranib, and tremlimumab + durvalumab, respectively, as compared to atezolizumab + cabozantinib. P-scores for each regimen are in Table. Conclusions: Among ICI combinations, better survival and response rates were reported with sintilimab + bevacizumab, atezolizumab + bevacizumab, and camrelizumab + rivoceranib. Therefore, these regimens should be preferred for treatment of advanced HCC as first line therapy in patients who can tolerate these regimens. [Table: see text]

Effect of aberrant N-glycosylation of PD-L1 on the potency of anti-PD-1 treatments.

e14599 Background: Immune checkpoint inhibitors (ICIs) targeting the PD1/PDL1 axis have revolutionized the way we treat cancer patient. Yet, response rate to these treatments remains low. Post translational modifications of PD-L1 in the form of N-glycosylation play a crucial role in both receptor-ligand interaction and in the potency of PD1/PDL1 ICIs. Understanding the effect of each N-glycosylation site is crucial for patient stratification for treatment groups and may help to increase response rate to anti-PD1/PDL1 ICIs. We recently developed the Immune-Checkpoint Artificial Reporter (IcAR) technology to assess specific ICI potency for target tumors including clinical samples. Using IcAR expressing recombinant human PD1 receptor we can analyze clinical response of patients to PD1-PDL1 blocking drugs and analyze the glycan-modified PDL1 expressing cancer cells. Methods: We have created two cell lines (MDA-MB231 and MCF7) overexpressing PD-L1 in its wildtype form, single mutated glycosylation sites (N35A, N192A, N200A, N219A) and all sites mutated together (Nx4). Using IcAR-PD1 we measured the functional binding of the different mutated cell lines, cell derived xenografts (CDX) and fixed cell samples to evaluate baseline binding. Later we have incubated IcAR-PD1 and mutated cell liens together with multiple clinically used PD1/PDL1 ICIs to evaluate the inhibition of interaction of each ICI. Results: While staining and functional interaction of PDL1 and single mutants is similar, removing all four N-glycosylation sites (Nx4) decreased both the staining of PDL1 and functional binding. Interestingly, blocking capacity of different ICIs was impaired by N35A PDL1 mutation, and was absolute through all concentration (2.5 to 40 ug/mL) when employed on the Nx4 cell lines. While anti-PDL1 ICIs were managed to block PD-1/PD-L1 interaction trough all cell lines and mutants, the inhibitory capacity of anti-PD1 ICIs was impaired by glycosylation, especially on N35. Conclusions: Aberrant glycosylation of PD-L1 impair the potency of anti-PD-1 treatment in cancer cell lines. These results might explain why patients with negative PD-L1 staining (Nx4), might respond to ICIs, and suggest an explanation of mechanism in which patients with high PD-L1 staining (i.e. N35), might not respond to anti-PD-1 treatments. Our results shed a light on the mechanism of ICI resistance and response – using this knowledge patient will be stratify better into treatment groups, getting oncology a step closer to precision immunology.