Immune Checkpoint Inhibitors Response Research Articles

Non-Small Cell Lung Cancer Metastatic Without Oncogenic Alterations.

This overview provides a thorough review of current treatment approaches for first-line management of nononcogenic addicted non-small cell lung cancer. We also address pertinent clinical decision-making queries encountered in everyday practice, such as the optimal treatment strategy for PD-L1-high patients, predictive factors for response to immune checkpoint inhibitors (ICI) both in terms of patient and cancer characteristics, the potential benefits of dual checkpoint blockade, and the unresolved issue of safe discontinuation strategies for long-term responders. Around one in five patients falls into this latter category while the majority develop either primary or acquired resistance to ICI-based first-line therapy, necessitating effective subsequent lines of treatment. Docetaxel, with or without combination of antiangiogenic agents, serves as the backbone of treatment, although evidence in the post-ICI setting is limited. Given that an inflamed tumor microenvironment (TME) is crucial for ICI responses, targeting the TME in cases of acquired resistance alongside continued ICI administration appears rational, although clinical trials so far have failed to confirm this hypothesis. Antibody-drug conjugates have emerged as a promising treatment modality, offering the potential for reduced toxicity and improved efficacy by targeting specific cancer antigens. Moreover, several chemotherapy-free approaches are currently under investigation for treatment-naïve patients, including alternative ICI and drugs targeting epitopes on both cancer and immune cells.

Integrated analysis of single-cell and bulk RNA sequencing data reveals a myeloid cell-related regulon predicting neoadjuvant immunotherapy response across cancers

BackgroundImmunotherapy has brought about a paradigm shift in the treatment of cancer. However, the majority of patients exhibit resistance or become refractory to immunotherapy, and the underlying mechanisms remain to be explored.MethodsSing-cell RNA sequencing (scRNA‑seq) datasets derived from 1 pretreatment and 1 posttreatment achieving pathological complete response (pCR) patient with lung adenocarcinoma (LUAD) who received neoadjuvant immunotherapy were collected, and pySCENIC was used to find the gene regulatory network (GRN) between cell types and immune checkpoint inhibitor (ICI) response. A regulon predicting ICI response was identified and validated using large‑scale pan-cancer data, including a colorectal cancer scRNA‑seq dataset, a breast cancer scRNA‑seq dataset, The Cancer Genome Atlas (TCGA) pan-cancer cohort, and 5 ICI transcriptomic cohorts. Symphony reference mapping was performed to construct the myeloid cell map.ResultsThirteen major cluster cell types were identified by comparing pretreatment and posttreatment patients, and the fraction of myeloid cells was higher in the posttreatment group (19.0% vs. 11.8%). A PPARG regulon (containing 23 target genes) was associated with ICI response, and its function was validated by a colorectal cancer scRNA‑seq dataset, a breast cancer scRNA‑seq dataset, TCGA pan-cancer cohort, and 5 ICI transcriptomic cohorts. Additionally, a myeloid cell map was developed, and cluster I, II, and III myeloid cells with high expression of PPARG were identified. Moreover, we constructed a website called PPARG (https://pparg.online/PPARG/ or http://43.134.20.130:3838/PPARG/), which provides a powerful discovery tool and resource value for researchers.ConclusionsThe PPARG regulon is a predictor of ICI response. The myeloid cell map enables the identification of PPARG subclusters in public scRNA-seq datasets and provides a powerful discovery tool and resource value.

The correlation between immune-related adverse events and efficacy of immune checkpoint inhibitors.

Immune checkpoint inhibitors have revolutionized cancer treatment by targeting the cytotoxic T lymphocyte antigen-4 and programmed death-1/ligand-1. Although immune checkpoint inhibitors show promising therapeutic efficacy, they often cause immune-related adverse events. Immune-related adverse events differ from the side effects of conventional chemotherapy and require vigilant monitoring. These events predominantly affect organs, such as the colon, liver, lungs, pituitary gland, thyroid and skin, with rare cases affecting the heart, nervous system and other tissues. As immune-related adverse events result from immune activation, indicating the reinvigoration of exhausted immune cells that attack both tumors and normal tissues, it is theoretically possible that immune-related adverse events may signal a better response to immune checkpoint inhibitor therapy. Recent retrospective studies have explored the link between immune-related adverse event development and clinical efficacy; however, the predictive value of immune-related adverse events in the immune checkpoint inhibitor response remains unclear. Additionally, studies have focused on immune-related adverse events, timing of onset and immunosuppressive treatments. This review focuses on pivotal studies of the association between immune-related adverse events and outcomes in patients treated with immune checkpoint inhibitors.

Effectiveness and safety of PD-1/PD-L1 inhibitors monotherapy in patients with endometrial cancer

BackgroundStudies evaluating the effectiveness of immune checkpoint inhibitors (ICI) for endometrial cancer (EC) are limited. This study aimed to assess the efficacy of PD-1/PD-L1 inhibitors as monotherapy for EC by conducting a meta-analysis. The predictive significance of MMR status, a biomarker for ICI response, also required further investigation.MethodsA systematic literature search was conducted in English databases until September 2023. The analysis included objective response rate (ORR), disease control rate (DCR), adverse events (AEs), and odds ratios (OR), along with their corresponding 95% confidence intervals (CI).ResultsThere were twelve trials totaling 685 individuals. PD-1/PD-L1 inhibitor monotherapy resulted in an ORR for 34% (95% CI = 24–44%) of the pooled EC patients. Subgroup analysis revealed a significantly higher ORR in dMMR EC (45%) compared to pMMR EC (8%), with an OR of 6.36 (95% CI = 3.64–11.13). The overall DCR was 42%, with dMMR EC at 51% and pMMR EC at 30% (OR = 2.61, 95% CI = 1.69–4.05). Grade three or higher adverse events (AEs) occurred in 15% of cases (95% CI = 9–24%) of the pooled incidence of AEs, which was 68% (95% CI = 65–72%).ConclusionsThis meta-analysis provides significant evidence for the effectiveness of PD-1/PD-L1 inhibitors as monotherapy for EC. Notably, dMMR EC patients demonstrated superior treatment efficacy with PD-1/PD-L1 inhibitor immunotherapy. Further research is required to explore subclassifications of EC based on dMMR molecular subtypes, enabling improved treatment strategies and outcomes for EC patients.

Association between pretreatment emotional distress and immune checkpoint inhibitor response in non-small-cell lung cancer.

Emotional distress (ED), commonly characterized by symptoms of depression and/or anxiety, is prevalent in patients with cancer. Preclinical studies suggest that ED can impair antitumor immune responses, but few clinical studies have explored its relationship with response to immune checkpoint inhibitors (ICIs). Here we report results from cohort 1 of the prospective observational STRESS-LUNG study, which investigated the association between ED and clinical efficacy of first-line treatment of ICIs in patients with advanced non-small-cell lung cancer. ED was assessed by Patient Health Questionnaire-9 and Generalized Anxiety Disorder 7-item scale. The study included 227 patients with 111 (48.9%) exhibiting ED who presented depression (Patient Health Questionnaire-9 score ≥5) and/or anxiety (Generalized Anxiety Disorder 7-item score ≥5) symptoms at baseline. On the primary endpoint analysis, patients with baseline ED exhibited a significantly shorter median progression-free survival compared with those without ED (7.9 months versus 15.5 months, hazard ratio 1.73, 95% confidence interval 1.23 to 2.43, P = 0.002). On the secondary endpoint analysis, ED was associated with lower objective response rate (46.8% versus 62.1%, odds ratio 0.54, P = 0.022), reduced 2-year overall survival rate of 46.5% versus 64.9% (hazard ratio for death 1.82, 95% confidence interval 1.12 to 2.97, P = 0.016) and detriments in quality of life. The exploratory analysis indicated that the ED group showed elevated blood cortisol levels, which was associated with adverse survival outcomes. This study suggests that there is an association between ED and worse clinical outcomes in patients with advanced non-small-cell lung cancer treated with ICIs, highlighting the potential significance of addressing ED in cancer management. ClinicalTrials.gov registration: NCT05477979 .

Harmonizing tumor mutational burden analysis: Insights from a multicenter study using in silico reference data sets in clinical whole-exome sequencing (WES).

Tumor mutational burden (TMB) is a significant biomarker for predicting immune checkpoint inhibitor response, but the clinical performance of whole-exome sequencing (WES)-based TMB estimation has received less attention compared to panel-based methods. This study aimed to assess the reliability and comparability of WES-based TMB analysis among laboratories under routine testing conditions. A multicenter study was conducted involving 24 laboratories in China using in silico reference data sets. The accuracy and comparability of TMB estimation were evaluated using matched tumor-normal data sets. Factors such as accuracy of variant calls, limit of detection (LOD) of WES test, size of regions of interest (ROIs) used for TMB calculation, and TMB cutoff points were analyzed. The laboratories consistently underestimated the expected TMB scores in matched tumor-normal samples, with only 50% falling within the ±30% TMB interval. Samples with low TMB score (<2.5) received the consensus interpretation. Accuracy of variant calls, LOD of the WES test, ROI, and TMB cutoff points were important factors causing interlaboratory deviations. This study highlights real-world challenges in WES-based TMB analysis that need to be improved and optimized. This research will aid in the selection of more reasonable analytical procedures to minimize potential methodologic biases in estimating TMB in clinical exome sequencing tests. Harmonizing TMB estimation in clinical testing conditions is crucial for accurately evaluating patients' response to immunotherapy.

Deep learning based digital pathology for predicting treatment response to first-line PD-1 blockade in advanced gastric cancer

BackgroundAdvanced unresectable gastric cancer (GC) patients were previously treated with chemotherapy alone as the first-line therapy. However, with the Food and Drug Administration’s (FDA) 2022 approval of programmed cell death protein 1 (PD-1) inhibitor combined with chemotherapy as the first-li ne treatment for advanced unresectable GC, patients have significantly benefited. However, the significant costs and potential adverse effects necessitate precise patient selection. In recent years, the advent of deep learning (DL) has revolutionized the medical field, particularly in predicting tumor treatment responses. Our study utilizes DL to analyze pathological images, aiming to predict first-line PD-1 combined chemotherapy response for advanced-stage GC.MethodsIn this multicenter retrospective analysis, Hematoxylin and Eosin (H&E)-stained slides were collected from advanced GC patients across four medical centers. Treatment response was evaluated according to iRECIST 1.1 criteria after a comprehensive first-line PD-1 immunotherapy combined with chemotherapy. Three DL models were employed in an ensemble approach to create the immune checkpoint inhibitors Response Score (ICIsRS) as a novel histopathological biomarker derived from Whole Slide Images (WSIs).ResultsAnalyzing 148,181 patches from 313 WSIs of 264 advanced GC patients, the ensemble model exhibited superior predictive accuracy, leading to the creation of ICIsNet. The model demonstrated robust performance across four testing datasets, achieving AUC values of 0.92, 0.95, 0.96, and 1 respectively. The boxplot, constructed from the ICIsRS, reveals statistically significant disparities between the well response and poor response (all p-values < = 0.001).ConclusionICIsRS, a DL-derived biomarker from WSIs, effectively predicts advanced GC patients’ responses to PD-1 combined chemotherapy, offering a novel approach for personalized treatment planning and allowing for more individualized and potentially effective treatment strategies based on a patient’s unique response situations.

Abstract PO2-06-10: Prevalence of genomic alterations in Xerna tumor microenvironment subtypes in triple negative breast cancer patients

Abstract Introduction: Immune checkpoint inhibitors (ICI) are an important therapeutic option for patients with triple negative breast cancer (TNBC). However, identification of patients most likely to respond is challenging. PD-L1 positivity by immunohistochemistry is the standard biomarker used for ICI therapy selection in TNBC. However, other biomarkers, such as analysis of the tumor microenvironment (TME) may be more accurate in predicting response. The XernaTM TME Panel uses RNA sequencing data and machine learning to analyze the TME, utilizing the angiogenic and immunogenic biology of the TME to classify tumors into four TME subtypes. In this study, the distribution of Xerna TME subtypes and associated genomic alterations in TNBC were investigated for their potential use in therapy selection. Methods: A total of 203 TNBC patient samples underwent tumor-normal whole-exome, whole-transcriptome sequencing testing with the OncoExTraTM assay. The whole-transcriptome expression data were analyzed using the Xerna TME Panel to assign each sample to one of four subtypes: Immune Active (IA), Immune Suppressed (IS), Immune Desert (ID) and Angiogenic (A). The IA and IS subtypes both have high immune scores that may be particularly sensitive to ICI therapy. Actionable alterations, defined as those with FDA-approved matched therapies in any cancer, with matched clinical trials, or with evidence in cancer guidelines or the literature for possible matched therapies, were also identified and associations across Xerna subtypes were explored. Results: Approximately half (100 of 203; 49.3%) of the patient samples had high (IA+IS) immune subtypes (Table 1). Targetable alterations associated with an FDA-approved therapy were present in 114 (56.2%) patients. No biomarkers were significantly associated (p &amp;lt; 0.05) with high (IA+IS) versus low (ID+A) immune scores. Biomarkers associated with ICI response, namely mismatch repair gene alterations (MSH2/3/6, MLH1/3, PMS1/2), high tumor mutational burden (TMB-high) and microsatellite instability were detected in only 6 (3.0%), 3 (1.5%) and 1 (0.5%) patient samples respectively, and all but 1, an MSH6 alteration, were in high immune subtype samples. Conclusions: The Xerna TME Panel classified 49.3% of TNBC patient tumors to IA or IS, suggesting they may respond to ICI therapy. Many (56.2%) patient tumors harbored alterations associated with FDA-approved therapies, providing the potential for novel combination therapies. These findings warrant further study and clinical validation in TNBC patients treated with ICI therapy. Table 1. Frequency of actionable biomarkers that were present in at least 10 (5%) TNBC patient samples. Citation Format: Gargi Basu, Janine Lobello, Snehal Thakkar, Jessica Aldrich, Matthew Halbert, Patrick Eimerman, Cynthia Flannery, Nishitha Therala, David Hall, Daniel Pointing, Lea Vohar, Roman Luštrik, Luka Ausec, Mark Uhlik, Seema Iyer, Laura Benjamin, Frederick Baehner. Prevalence of genomic alterations in Xerna tumor microenvironment subtypes in triple negative breast cancer patients [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-06-10.

Abstract PO2-20-10: Exceptional long-term disease control on pembrolizumab monotherapy in a patient with TMB-high PMS2-mutated MMR-deficient triple negative breast cancer brain metastasis

Abstract Introduction The brain is among the most common sites of breast cancer (BC) spread. Prognosis of BC brain metastasis (BCBM) differs by receptor subtype, with poorest median overall survival (OS) for triple-negative (TN) BCBM at under 5 months. Though treatment guidelines have evolved in recent years, most strategies have focused on local therapies including surgery and stereotactic radiotherapy (SRT), rather than on systemic agents. The 2020 FDA approval of pembrolizumab (pembro) for patients (pts) with metastatic high-tumor mutational burden (TMB-h, ≥ 10 mutations/megabase) solid tumors, agnostic of primary site, combined with clinical trials in melanoma reporting efficacy of immune checkpoint inhibitors (ICI) against BM, suggest a potential use of ICI for pts with TMB-h BCBM. Results of the TAPUR study supported modest therapeutic benefit of pembro for 28 pts with metastatic BC selected for TMB-h, with median OS of 30.6 weeks, but did not include pts with active BCBM. TMB-h is uncommon in BC, and further genomic signatures remain to be elucidated to identify pts with BCBM responsive to ICI. We present a remarkable case of a pt with Lynch Syndrome (LS) due to a germline PMS2 mutation, who developed TMB-h, mismatch repair (MMR)-deficient TN BCBM, and has maintained stable disease for over 6 years on pembro monotherapy. Case description A 62-y.o. woman underwent screening mammography that identified a right breast mass. Pt has a family history of a mother with uterine and pancreatic cancer, and father with bladder cancer. Biopsy confirmed invasive ductal carcinoma (IDC), grade 1 (G1), ER/PR-positive, HER2 score 0. She underwent partial mastectomy, axillary dissection, radiation, and received adjuvant anastrozole. Three years later, while still on anastrozole, she presented with a 6 cm right breast mass. Mastectomy disclosed G3, ER/PR-negative, HER2-positive (3+, Her2:CEP17 ratio 5.6) IDC. She received adjuvant chemotherapy (AC-T) and 1 year of trastuzumab. Seven years later, pt presented with headaches and word finding difficulties. MRI identified a 3.6 cm frontal mass, which biopsy revealed as TN BCBM. Systemic imaging ruled out distant metastases. Pt proceeded with SRT and exemestane (despite receptor staining ER- in case of a possible false negative result). Despite radiotherapy, pt had BCBM progression within the same year with the largest mass diameter grown to 4.8 cm. Resection (followed by SRT) identified the dominant histology as G3 TNBC. Following transition of care to our institution, germline testing revealed a pathogenic mutation in PMS2 (c943C &amp;gt;T). Tumor sequencing of the resected brain metastasis showed TMB of 48 and MMR deficiency. Therefore, systemic therapy with pembro monotherapy was initiated and maintained with good tolerability. Two years later, concern for progression from rising tumor markers led to addition of concurrent carboplatin/gemcitabine for 5 cycles. Imaging and tumor markers stabilized, and pt returned to pembro monotherapy. Today, 3 years later, and over 6.5 years after initial TN BCBM diagnosis, pt continues to have stable disease on pembro with an excellent performance status (ECOG 0) and no evidence of intracranial or extracranial progression. Discussion We document an exceptional case of prolonged benefit to pembro in a pt with TMB-h PMS2-mutated MMR-deficient TN BCBM. This case highlights two major pragmatic points to clinical practice; (i) the significance of germline testing in all pts with metastatic BC, and (ii) the impact of molecular testing of tumor tissue to identify rare alterations which may have dramatic effects on pt outcomes. Altogether, this case is a remarkable addition to growing evidence that TMB could be a biomarker for predicting response to ICI therapy and provides an example of ICI efficacy in the setting of BCBM. Further research on additional genomic, clinical, and pathologic features associated with ICI responsiveness is warranted for greater precision in BCBM management. Citation Format: Jaeyoon Cha, Albert Grinshpun, Lauren Buckley, Brian Alexander, Sara Tolaney, Nancy Lin. Exceptional long-term disease control on pembrolizumab monotherapy in a patient with TMB-high PMS2-mutated MMR-deficient triple negative breast cancer brain metastasis [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-20-10.

Clinical Validation of Artificial Intelligence-Powered PD-L1 Tumor Proportion Score Interpretation for Immune Checkpoint Inhibitor Response Prediction in Non-Small Cell Lung Cancer.

Evaluation of PD-L1 tumor proportion score (TPS) by pathologists has been very impactful but is limited by factors such as intraobserver/interobserver bias and intratumor heterogeneity. We developed an artificial intelligence (AI)-powered analyzer to assess TPS for the prediction of immune checkpoint inhibitor (ICI) response in advanced non-small cell lung cancer (NSCLC). The AI analyzer was trained with 393,565 tumor cells annotated by board-certified pathologists for PD-L1 expression in 802 whole-slide images (WSIs) stained by 22C3 pharmDx immunohistochemistry. The clinical performance of the analyzer was validated in an external cohort of 430 WSIs from patients with NSCLC. Three pathologists performed annotations of this external cohort, and their consensus TPS was compared with AI-based TPS. In comparing PD-L1 TPS assessed by AI analyzer and by pathologists, a significant positive correlation was observed (Spearman coefficient = 0.925; P < .001). The concordance of TPS between AI analyzer and pathologists according to TPS ≥50%, 1%-49%, and <1% was 85.7%, 89.3%, and 52.4%, respectively. In median progression-free survival (PFS), AI-based TPS predicted prognosis in the TPS 1%-49% or TPS <1% group better than the pathologist's reading, with the TPS ≥50% group as a reference (hazard ratio [HR], 1.49 [95% CI, 1.19 to 1.86] v HR, 1.36 [95% CI, 1.08 to 1.71] for TPS 1%-49% group, and HR, 2.38 [95% CI, 1.69 to 3.35] v HR, 1.62 [95% CI, 1.23 to 2.13] for TPS <1% group). PD-L1 TPS assessed by AI analyzer correlates with that of pathologists, with clinical performance also being comparable when referenced to PFS. The AI model can accurately predict tumor response and PFS of ICI in advanced NSCLC via assessment of PD-L1 TPS.

Harnessing genetic interactions for prediction of immune checkpoint inhibitors response signature in cancer cells

Genetic interactions (GIs) refer to two altered genes having a combined effect that is not seen individually. They play a crucial role in influencing drug efficacy. We utilized CGIdb 2.0 (http://www.medsysbio.org/CGIdb2/), an updated database of comprehensively published GIs information, encompassing synthetic lethality (SL), synthetic viability (SV), and chemical-genetic interactions. CGIdb 2.0 elucidates GIs relationships between or within protein complex models by integrating protein-protein physical interactions. Additionally, we introduced GENIUS (GENetic Interactions mediated drUg Signature) to leverage GIs for identifying the response signature of immune checkpoint inhibitors (ICIs). GENIUS identified high MAP4K4 expression as a resistance signature and high HERC4 expression as a sensitivity signature for ICIs treatment. Melanoma patients with high expression of MAP4K4 were associated with decreased efficacy and poorer survival following ICIs treatment. Conversely, overexpression of HERC4 in melanoma patients correlated with a positive response to ICIs. Notably, HERC4 enhances sensitivity to immunotherapy by facilitating antigen presentation. Analyses of immune cell infiltration and single-cell data revealed that B cells expressing MAP4K4 may contribute to resistance to ICIs in melanoma. Overall, CGIdb 2.0, provides integrated GIs data, thus serving as a crucial tool for exploring drug effects.

The immune response-related genomic alterations in patients with malignant melanoma.

Immune checkpoint inhibitors (ICIs) significantly improve the survival outcomes of patients with advanced melanoma. However, response varies among from patient to patient and predictive biomarkers are urgently needed. We integrated mutational profiles from next-generation sequencing (NGS) data and clinicopathologic characteristics of melanoma patients to investigate whether tumor genomic profiling contribute to clinical benefit of ICIs treatment. The majority of genes identified with high mutation frequency have all been reported as well-known immunotherapy-related genes. Thirty-five patients (43.2%) had at least 1 BRAF/RAS/NF1 mutation. The other 46 (56.8%) melanomas without BRAF/RAS/NF1 mutation were classified as Triple-WT. We identified mutational signature 6 (known as associated with defective DNA mismatch repair) among cases in this cohort. Compared to patients with PD-L1 expression (TPS < 1%), patients with PD-L1 expression (TPS ≥ 1%) had significantly higher median progression-free survival (mPFS), but no significantly higher durable clinical benefit (DCB) rate. In contrast, FAT1, ATM, BRCA2, LRP1B, and PBRM1 mutations only occurred frequently in patients with DCB, irrespective of PD-L1 expression status. Our study explored molecular signatures of melanoma patients who respond to ICIs treatment and identified a series of mutated genes that might serve as predictive biomarker for ICIs responses in melanoma.

Photodynamic therapy upregulates expression of HIF-1α and PD-L1 in related pathways and its clinical relevance in non-small-cell lung cancer

BackgroundPhotodynamic therapy (PDT) is a promising interventional treatment approach that contributes to antitumor immunity. It has been reported that PDT can enhance the effectiveness of immune checkpoint inhibitors (ICIs), but its mechanism is yet unclear. Herein, we implemented bioinformatics analysis to detect common pathways and potential biomarkers in non-small cell lung cancer (NSCLC), PDT, and NSCLC immunotherapy to investigate potential links between PDT, immunotherapy and NSCLC, and their clinical impact.MethodsDifferentially expressed genes in NSCLC- and NSCLC immunotherapy-related data in the GEO database were intersected with PDT-related genes in the GeneCards database to obtain candidate genes and shared pathways. Enrichment analysis and protein–protein interaction were established to identify key genes in functionally enriched pathways. The expression profiles and the prognostic significance of key genes were depicted.ResultsBioinformatics analysis showed that HIF-1α was screened as a prognostic gene in hypoxia, HIF-1, and PD-L1-related signaling pathways, which was associated with clinical response in NSCLC patients after PDT and immunotherapy. In vivo experiments showed that PDT could inhibit tumor growth and upregulate HIF-1α and PD-L1 expressions in NSCLC tissues with a positive correlation, which might influence the blocking activity of ICIs on the HIF-1, and PD-L1-related signaling pathways.ConclusionsPDT might improve the clinical response of ICIs by upregulating tumor HIF-1α and PD-L1 expressions in NSCLC.

Stroma-infiltrating T cell spatiotypes define immunotherapy outcomes in adolescent and young adult patients with melanoma

The biological underpinnings of therapeutic resistance to immune checkpoint inhibitors (ICI) in adolescent and young adult (AYA) melanoma patients are incompletely understood. Here, we characterize the immunogenomic profile and spatial architecture of the tumor microenvironment (TME) in AYA (aged ≤ 30 years) and older adult (aged 31–84 years) patients with melanoma, to determine the AYA-specific features associated with ICI treatment outcomes. We identify two ICI-resistant spatiotypes in AYA patients with melanoma showing stroma-infiltrating lymphocytes (SILs) that are distinct from the adult TME. The SILhigh subtype was enriched in regulatory T cells in the peritumoral space and showed upregulated expression of immune checkpoint molecules, while the SILlow subtype showed a lack of immune activation. We establish a young immunosuppressive melanoma score that can predict ICI responsiveness in AYA patients and propose personalized therapeutic strategies for the ICI-resistant subgroups. These findings highlight the distinct immunogenomic profile of AYA patients, and individualized TME features in ICI-resistant AYA melanoma that require patient-specific treatment strategies.

Abstract LB248: Interrogating the cancer-immunity cycle through the lens of a large-scale single-cell atlas of immune checkpoint inhibition response and resistance

Abstract Introduction. The cancer-immunity cycle (CIC; Chen et al. 2013; Mellman et al. 2023) systematizes the current understanding of the factors (both suppressive and promoting) that together determine the anticancer immune responses. While the CIC is not limited to any single therapeutic modality, the framework is useful for understanding the mechanisms of immune checkpoint inhibition (ICI) response and resistance. Given its importance in the field, it is critical to be able to systematically examine and expand the CIC (or related frameworks) using new high-throughput data. Here we intersect the CIC framework with a large-scale atlas of single-cell RNA-seq data to provide a window into the CIC factors supported across multiple tumor types. Approach. We have previously developed the Single-Cell Immune Checkpoint Inhibition Atlas (ICI Atlas) which in its original version spanned 27 datasets and 1.9 million cells across a range of tumor types and ICI therapies. Motivated by rapid growth of data in the field, here we develop version 2 of the Atlas, over twice as large and consisting of 55 datasets and 4.4 million cells with cross-dataset integration via a transformer-based deep learning model. Of the 55 datasets, 47 contain both pre- and post-treatment samples, 2 contain only pre-treatment samples, and 6 contain only post-treatment samples. The Atlas spans 124 cell types and covers 19 different cancer types as well as 31 treatment strategies including 19 ICI therapies. Results. To determine the ICI Atlas support for each factor in the CIC, we analyzed the percent of studies where the factor’s cell type-specific pre-treatment expression was significantly higher in ICI responders (for promoting factors) or in non-responders (for inhibiting factors). We found that 16 cell type-specific CIC factors (12 promoting and 4 inhibiting) had strong support in the ICI Altas (supported in ≥ 50% of relevant studies). Specific steps of the CIC were associated with well-supported promoting factors, e.g. Step 2: interferon alpha/beta signaling pathway (dendritic cells/APCs, 50-100% of studies); Step 3: TCR signaling pathway (T cells; 58%); Step 5: CXCL9/10/11 (macrophages, 50-75%) and CCL5 (T cells, 58%); Step 5a: SELL (T cells, 68%); or inhibiting factors, e.g. Step 5b: IL10 (T cells, 53%). For some factors the support is tissue-specific, e.g. in tumor samples type-I IFN signaling was higher in dendritic cells and monocytes of responders while in blood this was reversed. Interestingly, certain co-stimulatory factors showed higher expression in non-responders (e.g. OX40 in T-cells, 53% of analyses, and 4-1BBL in macrophages, 50%). Our analysis also identifies a number of new factors whose expression is associated with response to ICI across the majority of ICI Atlas studies, providing opportunities for expanding current knowledge of cancer-immune system interplay and ICI response. Citation Format: Piotr Topolewski, Zofia Kochańska, Marlena Osipowicz, Roy Ronen, Janusz Dutkowski. Interrogating the cancer-immunity cycle through the lens of a large-scale single-cell atlas of immune checkpoint inhibition response and resistance [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 LB248.

Abstract LB091: A multigene signature for immunotherapy in patients with high risk non-muscle-invasive bladder cancer

Abstract Introduction: Approximately 80% of bladder cancer patients are initially diagnosed with non-muscle invasive bladder cancer (NMIBC). However, most NMIBC patients have a high recurrence rates, and up to 45% progress to muscle-invasive bladder cancer (MIBC) and metastatic disease. Treatment for NMIBC includes transurethral resection and, depending on the risk of recurrence or progression, intravesical chemotherapy or immunotherapy, such as Bacillus Calmette-Guérin(BCG). Our aim is to use a multigene signature in patients with high-risk NMIBC to determine whether patients may benefit from improved ICIs compared to conventional PD-L1 expression and to evaluate the clinical utility. Methods: A multi-gene signature obtained from the various NMIBC data was applied to stratify the UROMOL2021 cohort (n=535) using consensus clustering. Each subtype was distinguished by biological pathway analysis. Validation analysis was performed in three independent cohorts including the IMvigor210 (n=298), IMvigor010 (n=377) and ABACUS (n=148) clinical trials treated with PD-L1 inhibitors. The log-rank test, chi-square test, Fisher’s exact test, and cox regression analysis were used to evaluate clinical utility. Results: Based on consensus cluster analysis, NMIBC patients in the UROMOL2021 cohort were classified into five subgroups exhibiting unique characteristics, including DNA damage repair (DDR). Cross-validation was performed using two independent NMIBC cohorts and one MIBC cohort. Survival analysis showed that the subgroup associated with DDR (DDR and DDR+Tcell) had the highest rates of relapse and disease progression (progression-free survival, p&amp;lt;0.001) and benefited from Immune checkpoint inhibitors (ICIs) (response, p=0.01; overall survival, p=0.004). Conclusions: This study suggests that the multi-gene signature may play a role to enhance the responsiveness of ICIs for high-risk NMIBC. Additionally, it is important to help improve ICI treatment approaches that currently focus on PD-L1 expression on cancer cells, allowing more patients to receive priority consideration for ICI therapy. Citation Format: Seung-Woo Baek, Seon-Kyu Kim, Sun-Hee Leem, In-Sun Chu. A multigene signature for immunotherapy in patients with high risk non-muscle-invasive bladder cancer [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 LB091.

Effect of longitudinal changes of cachexia on the efficacy and toxicity of immune checkpoint inhibitors in esophageal squamous cell cancer (ESCC) patients

PurposeImmune checkpoint inhibitors (ICIs) have enhanced survival in advanced esophageal squamous cell cancer (ESCC) patients, but their efficacy varies. Cachexia, characterized by muscle loss and significant weight loss, might influence ICI response. This study examines the relationship between cachexia's longitudinal changes and ICI outcomes in ESCC patients. MethodsESCC patients undergoing at least two ICI cycles from 2017 to 2021 were studied. Cachexia's baseline and evolving patterns during ICI treatment were observed. Kaplan-Meier and Cox regression analyses were used to assess cachexia's effect on ICI efficacy. Chi-square tests were used to determine cachexia's link to immune-related adverse effects (irAEs). ResultsTwo hundred seventy-eight ICI-treated patients had a median progression-free survival (PFS) of 5.78 months and overall survival (OS) of 8.3 months. Pretreatment cachexia led to worse outcomes: PFS 7.87 versus 5.3 months, time to progression (TTP) 10.9 versus 6.1 months, and OS 14.3 versus 9.2 months. Irreversible cachexia showed the poorest results. Cachexia's changes weren't associated with irAEs. ConclusionBaseline and evolving cachexia significantly impact ICI efficacy in ESCC patients. Continuous cachexia monitoring during ICI therapy is crucial for optimal ESCC management.

Pan-Cancer Single-Cell and Spatial-Resolved Profiling Reveals the Immunosuppressive Role of APOE+ Macrophages in Immune Checkpoint Inhibitor Therapy.

The heterogeneity of macrophages influences the response to immune checkpoint inhibitor (ICI) therapy. However, few studies explore the impact of APOE+ macrophages on ICI therapy using single-cell RNA sequencing (scRNA-seq) and machine learning methods. The scRNA-seq and bulk RNA-seq data are Integrated to construct an M.Sig model for predicting ICI response based on the distinct molecular signatures of macrophage and machine learning algorithms. Comprehensive single-cell analysis as well as in vivo and in vitro experiments are applied to explore the potential mechanisms of the APOE+ macrophage in affecting ICI response. The M.Sig model shows clear advantages in predicting the efficacy and prognosis of ICI therapy in pan-cancer patients. The proportion of APOE+ macrophages is higher in ICI non-responders of triple-negative breast cancer compared with responders, and the interaction and longer distance between APOE+ macrophages and CD8+ exhausted T (Tex) cells affecting ICI response is confirmed by multiplex immunohistochemistry. In a 4T1 tumor-bearing mice model, the APOE inhibitor combined with ICI treatment shows the best efficacy. The M.Sig model using real-world immunotherapy data accurately predicts the ICI response of pan-cancer, which may be associated with the interaction between APOE+ macrophages and CD8+ Tex cells.

Dual‐Sensing Nanoreporter for Dynamic and High‐Throughput Monitoring of Immune Checkpoint Inhibitor Responses in Tumor‐Derived Organoids

AbstractHeterogenous immune responses to checkpoint blockade therapy remain a major challenge to early prediction of treatment efficacy. Current methods of evaluating treatment efficacy in tumors are ineffective in accurately monitoring the disease status after immunotherapy early on. This study reports an immune response monitoring strategy that longitudinally reports on two crucial protease activities involved in T cell‐mediated target cell death, granzyme B (GrzB) and downstream caspase 3 (Casp3), during and after immune checkpoint antibody treatment. Specifically, activatable nanoreporters are engineered to sensitively and selectively capture the activity of GrzB and Casp3 enzymes in tumor cells triggered by cytotoxic T cells in real‐time, providing a direct readout of the tumor response to immune checkpoint inhibitors (ICIs). Furthermore, incorporating 3D tumor‐derived organoids and ex vivo cultures on microfluidic devices with nanoreporters enables high‐throughput screening of various ICIs and their combinations in immunocompetent tumor models. These findings suggest that efficient monitoring of dynamic immunological processes in the tumor microenvironment could help uncover mechanisms associated with ICI response or resistance. It is further anticipated that combining the dual‐sensing nanoreporter with tumor‐derived organoid‐on‐chip technology could lead to an early prediction of treatment outcomes with high fidelity and accelerate the development of optimal treatment in immuno‐oncology.

Targeted DNA Sequencing of Cutaneous Melanoma Identifies Prognostic and Predictive Alterations.

Cutaneous melanoma (CM) can be molecularly classified into four groups: BRAF mutant, NRAS mutant, NF1 mutant and triple wild-type (TWT) tumors lacking any of these three alterations. In the era of immune checkpoint inhibition (ICI) and targeted molecular therapy, the clinical significance of these groups remains unclear. Here, we integrate targeted DNA sequencing with comprehensive clinical follow-up in CM patients. This was a retrospective cohort study that assessed clinical and molecular features from patients with localized or metastatic CM who underwent targeted next-generation sequencing as part of routine clinical care. A total of 254 patients with CM who had a CLIA-certified targeted sequencing assay performed on their tumor tissue were included. Of the 254 patients with cutaneous melanoma, 77 were BRAF mutant (30.3%), 77 were NRAS mutant (30.3%), 47 were NF1 mutant (18.5%), 33 were TWT (13.0%) and the remaining 20 (7.9%) carried mutations in multiple driver genes (BRAF/NRAS/NF1 co-mutated). The majority of this co-mutation group carried mutations in NF1 (n = 19 or 90%) with co-occurring mutations in BRAF or NRAS, often with a weaker oncogenic variant. Consistently, NF1 mutant tumors harbored numerous significantly co-altered genes compared to BRAF or NRAS mutant tumors. The majority of TWT tumors (n = 29, 87.9%) harbor a pathogenic mutation within a known Ras/MAPK signaling pathway component. Of the 154 cases with available TMB data, the median TMB was 20 (range 0.7-266 mutations/Mb). A total of 14 cases (9.1%) were classified as having a low TMB (≤5 mutations/Mb), 64 of 154 (41.6%) had an intermediate TMB (>5 and ≤20 mutations/Mb), 40 of 154 (26.0%) had a high TMB (>20 and ≤50 mutations/Mb) and 36 of 154 (23.4%) were classified as having a very high TMB (>50 mutations/Mb). NRAS mutant melanoma demonstrated significantly decreased overall survival on multivariable analysis (HR for death 2.95, 95% CI 1.13-7.69, p = 0.027, log-rank test) compared with other TCGA molecular subgroups. Of the 116 patients in our cohort with available treatment data, 36 received a combination of dual ICI with anti-CTLA4 and anti-PD1 inhibition as first-line therapy. Elevated TMB was associated with significantly longer progression-free survival following dual-agent ICI (HR 0.26, 95% CI 0.07-0.90, p = 0.033, log-rank test). NRAS mutation in CMs correlated with significantly worse overall survival. Elevated TMB was associated with increased progression-free survival for patients treated with a combination of dual ICI, supporting the potential utility of TMB as a predictive biomarker for ICI response in melanoma.