Evaluation of Response to Immune Checkpoint Inhibitors Using a Radiomics, Lesion-Level Approach.
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ABSTRACT:
SUBMITTER: Song C
PROVIDER: S-EPMC8657103 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundLocal ablative treatments improve survival in patients with oligometastatic disease in addition to chemotherapy. The application of immune checkpoint inhibitors prolonged patients' survival in different tumor entities. This raises the question if patients still benefit from intensified local treatments in combination with a more efficient systemic treatment with immune checkpoint inhibitors.MethodsThe prospective non-interventional ST-ICI trial investigates treatment with PD-1/PD-L1 (Programmed cell death protein 1/Programmed cell death 1 ligand 1) immune checkpoint inhibitors and radiotherapy in different tumor entities. Patients who started radiotherapy and immunotherapy concomitantly were included in this interim analysis. In this cohort patients with all-lesion radiotherapy (all tumor lesions irradiated, al-RT) were compared to patients with radiotherapy to only a single of their tumor lesions (single-lesion radiotherapy, sl-RT). Endpoints of the interim analysis were progression-free survival (PFS), overall survival (OS) and time to progression (TTP).ResultsA total of 104 patients were registered between April 2017 and August 2019. Fifty patients started immune checkpoint inhibitor treatment and radiotherapy concomitantly and were included. Most frequent tumor entities were non-small cell lung cancer (62%) followed by head and neck squamous cell cancer (26%). Most frequent location of radiotherapy was lung (34%) and central nervous system (20%). Median duration of follow-up was 8.6 months beginning with first administration of the immune-checkpoint-inhibitor. Median PFS was 9.2 months (95% CI, 5.8 - 12.6) in the al-RT group and 3.0 months (95% CI, 2.5 - 3.5) in the sl-RT group (p<0.001). Median OS was 11.6 months (95% CI, 8.1 - 15.1) in the al-RT group and 4.2 months (95% CI, 3.0 - 5.4) in the sl-RT group (p=0.007). Median TTP was not reached in the al-RT group compared to 4.6 months (95% CI, 1.1-8.0) in the sl-RT group (p=0.028). Univariate Cox regression analyses computed tumor entity, histology, central nervous system metastases, immunotherapy drug and al-RT as predictors of OS (with an effect p-value of ≤ 0.1). In the multivariable analysis only tumor entity and al-RT remained prognostic factors for OS.ConclusionPatients with PD-1/PD-L1 immune checkpoint inhibitor therapy benefit from local radiotherapy to all known lesions compared to single-lesion radiotherapy regarding PFS and OS.
| S-EPMC7673414 | biostudies-literature
Project description: Not available
| S-EPMC8105747 | biostudies-literature
Project description:Immune checkpoint inhibitors (ICPIs) have revolutionized the treatment paradigm of a wide range of malignancies with durable responses seen in even advanced, refractory cancers. Unfortunately, only a small proportion of patients with cancer derive meaningful benefit to ICPI therapy, and its use is also limited by significant immune and financial toxicities. Thus, there is a critical need for the development of biomarkers to reliably predict response to ICPI therapy. Only a few biomarkers are validated and approved for use with currently Food and Drug administration (FDA)-approved ICPIs. The development and broad application of biomarkers is limited by the lack of complete understanding of the complex interactions of tumor-host environment, the effect of immunotherapies on these already complex interactions, a lack of standardization and interpretation of biomarker assays across tumor types. Despite these challenges, the field of identifying predictive biomarkers is evolving at an unprecedented pace leaving the clinician responsible for identifying the patients that may derive optimal benefit from ICPIs. In this review, we provide clinicians with a current and practical update on the key, clinically relevant biomarkers of response to ICPIs. We categorize the current and emerging biomarkers of response to ICPIs in four major categories that govern anticancer response-the inflamed tumor, tumor antigens, immune suppression, and overall host environment.
| S-EPMC8267267 | biostudies-literature
Project description:Over the last decade, the therapeutic scenario for advanced non-small-cell lung cancer (NSCLC) has undergone a major paradigm shift. Immune checkpoint inhibitors (ICIs) have shown a meaningful clinical and survival improvement in different settings of the disease. However, the real benefit of this therapeutic approach remains controversial in selected NSCLC subsets, such as those of the elderly with active brain metastases or oncogene-addicted mutations. This is mainly due to the exclusion or underrepresentation of these patient subpopulations in most pivotal phase III studies; this precludes the generalization of ICI efficacy in this context. Moreover, no predictive biomarkers of ICI response exist that can help with patient selection for this therapeutic approach. Here, we critically summarize the current state of ICI efficacy in the most common "special" NSCLC subpopulations.
| S-EPMC10454231 | biostudies-literature
Project description:Modern immunotherapy together with targeted therapy has revolutionized the treatment of advanced melanoma. Inhibition of immune checkpoints significantly improved the median overall survival and gave hope to many melanoma patients. However, this treatment has three serious drawbacks: high cost, serious side effects, and an effectiveness limited only to approximately 50% of patients. Some patients do not derive any or short-term benefit from this treatment due to primary or secondary resistance. The response to immunotherapy depends on many factors that fall into three main categories: those associated with melanoma cells, those linked to a tumor and its microenvironment, and those classified as individual ontogenic and physiological features of the patient. The first category comprises expression of PD-L1 and HLA proteins on melanoma cells as well as genetic/genomic metrics such as mutational load, (de)activation of specific signaling pathways and epigenetic factors. The second category is the inflammatory status of the tumor: "hot" versus "cold" (i.e., high versus low infiltration of immune cells). The third category comprises metabolome and single nucleotide polymorphisms of specific genes. Here we present up-to-date data on those biological factors influencing melanoma response to immunotherapy with a special focus on signaling pathways regulating the complex process of anti-tumor immune response. We also discuss their potential predictive capacity.
| S-EPMC7313051 | biostudies-literature
Project description:Cancer cells can leverage several cell-intrinsic and -extrinsic mechanisms to escape immune system recognition. The inherent complexity of the tumor microenvironment, with its multicellular and dynamic nature, poses great challenges for the extraction of biomarkers of immune response and immunotherapy efficacy. Here, we use RNA-sequencing (RNA-seq) data combined with different sources of prior knowledge to derive system-based signatures of the tumor microenvironment, quantifying immune-cell composition and intra- and intercellular communications. We applied multi-task learning to these signatures to predict different hallmarks of immune responses and derive cancer-type-specific models based on interpretable systems biomarkers. By applying our models to independent RNA-seq data from cancer patients treated with PD-1/PD-L1 inhibitors, we demonstrated that our method to Estimate Systems Immune Response (EaSIeR) accurately predicts therapeutic outcome. We anticipate that EaSIeR will be a valuable tool to provide a holistic description of immune responses in complex and dynamic systems such as tumors using available RNA-seq data.
| S-EPMC8369166 | biostudies-literature
Project description:IntroductionImmune checkpoint inhibitors (ICIs) only benefit a subset of cancer patients, underlining the need for predictive biomarkers for patient selection. Given the limitations of tumor tissue availability, flow cytometry of peripheral blood mononuclear cells (PBMCs) is considered a noninvasive method for immune monitoring. This study explores the use of spectrum flow cytometry, which allows a more comprehensive analysis of a greater number of markers using fewer immune cells, to identify potential blood immune biomarkers and monitor ICI treatment in non-small-cell lung cancer (NSCLC) patients.MethodsPBMCs were collected from 14 non-small-cell lung cancer (NSCLC) patients before and after ICI treatment and 4 healthy human donors. Using spectrum flow cytometry, 24 immune cell markers were simultaneously monitored using only 1 million PBMCs. The results were also compared with those from clinical flow cytometry and bulk RNA sequencing analysis.ResultsOur findings showed that the measurement of CD4+ and CD8+ T cells by spectrum flow cytometry matched well with those by clinical flow cytometry (Pearson R ranging from 0.75 to 0.95) and bulk RNA sequencing analysis (R=0.80, P=1.3 x 10-4). A lower frequency of CD4+ central memory cells before treatment was associated with a longer median progression-free survival (PFS) [Not reached (NR) vs. 5 months; hazard ratio (HR)=8.1, 95% confidence interval (CI) 1.5-42, P=0.01]. A higher frequency of CD4-CD8- double-negative (DN) T cells was associated with a longer PFS (NR vs. 4.45 months; HR=11.1, 95% CI 2.2-55.0, P=0.003). ICIs significantly changed the frequency of cytotoxic CD8+PD1+ T cells, DN T cells, CD16+CD56dim and CD16+CD56- natural killer (NK) cells, and CD14+HLDRhigh and CD11c+HLADR + monocytes. Of these immune cell subtypes, an increase in the frequency of CD16+CD56dim NK cells and CD14+HLADRhigh monocytes after treatment compared to before treatment were associated with a longer PFS (NR vs. 5 months, HR=5.4, 95% CI 1.1-25.7, P=0.03; 7.8 vs. 3.8 months, HR=5.7, 95% CI 169 1.0-31.7, P=0.04), respectively.ConclusionOur preliminary findings suggest that the use of multicolor spectrum flow cytometry helps identify potential blood immune biomarkers for ICI treatment, which warrants further validation.
| S-EPMC10449448 | biostudies-literature
Project description:PurposeThis study evaluated pretreatment 2[18F]fluoro-2-deoxy-D-glucose (FDG)-PET/CT-based radiomic signatures for prediction of hyperprogression in metastatic melanoma patients treated with immune checkpoint inhibition (ICI).Material and methodFifty-six consecutive metastatic melanoma patients treated with ICI and available imaging were included in the study and 330 metastatic lesions were individually, fully segmented on pre-treatment CT and FDG-PET imaging. Lesion hyperprogression (HPL) was defined as lesion progression according to RECIST 1.1 and doubling of tumor growth rate. Patient hyperprogression (PD-HPD) was defined as progressive disease (PD) according to RECIST 1.1 and presence of at least one HPL. Patient survival was evaluated with Kaplan-Meier curves. Mortality risk of PD-HPD status was assessed by estimation of hazard ratio (HR). Furthermore, we assessed with Fisher test and Mann-Whitney U test if demographic or treatment parameters were different between PD-HPD and the remaining patients. Pre-treatment PET/CT-based radiomic signatures were used to build models predicting HPL at three months after start of treatment. The models were internally validated with nested cross-validation. The performance metric was the area under receiver operating characteristic curve (AUC).ResultsPD-HPD patients constituted 57.1% of all PD patients. PD-HPD was negatively related to patient overall survival with HR=8.52 (95%CI 3.47-20.94). Sixty-nine lesions (20.9%) were identified as progressing at 3 months. Twenty-nine of these lesions were classified as hyperprogressive, thereby showing a HPL rate of 8.8%. CT-based, PET-based, and PET/CT-based models predicting HPL at three months after the start of treatment achieved testing AUC of 0.703 +/- 0.054, 0.516 +/- 0.061, and 0.704 +/- 0.070, respectively. The best performing models relied mostly on CT-based histogram features.ConclusionsFDG-PET/CT-based radiomic signatures yield potential for pretreatment prediction of lesion hyperprogression, which may contribute to reducing the risk of delayed treatment adaptation in metastatic melanoma patients treated with ICI.
| S-EPMC9730880 | biostudies-literature
Project description:Gastrointestinal (GI) cancers account for a large proportion of cancer deaths worldwide and pose a major public health challenge. Immunotherapy is considered to be one of the prominent and successful approaches in cancer treatment in recent years. Among them, immune checkpoint inhibitor (ICI) therapy, has received widespread attention, and many clinical findings support the feasibility of ICIs, with sustained responses and significantly prolonged lifespan observed in a wide range of tumors. However, patients treated with ICIs have not fully benefited, and therefore, the identification and development of biomarkers for predicting ICI treatment response have received further attention and exploration. From tumor genome to molecular interactions in the tumor microenvironment, and further expanding to circulating biomarkers and patient characteristics, the exploration of biomarkers is evolving with high-throughput sequencing as well as bioinformatics. More large-scale prospective and specific studies are needed to explore biomarkers in GI cancers. In this review, we summarize the known biomarkers used in ICI therapy for GI tumors. In addition, some ICI biomarkers applied to other tumors are included to provide insights and further validation for GI tumors. Moreover, we present single-cell analysis and machine learning approaches that have emerged in recent years. Although there are no clear applications yet, it can be expected that these techniques will play an important role in the application of biomarker prediction.
| S-EPMC8790411 | biostudies-literature
Project description:Dietary methionine restriction, defined as reduction of methionine intake by around 80%, reproducibly decreases tumor growth and synergizes with cancer therapies. Here, we combined dietary methionine restriction with immune checkpoint inhibitors in a model of colon adenocarcinoma. In vitro , we observed that methionine restriction increased the expression of MHC-I and PD-L1 in both mouse and human colorectal cancer cells. We also saw an increase in the gene expression of STING, a known inducer of type I interferon signaling. Inhibition of the cGAS-STING pathway, pharmacologically or with siRNA, blunted the increase in MHC-I and PD-L1 surface and gene expression following methionine restriction. PD-L1 expression was also This indicated that the cGAS-STING pathway in particular, and interferon in general, is playing a role in the immune response to methionine restriction. We then combined dietary methionine restriction with immune checkpoint inhibitors targeted against CTLA-4 and PD-1 in a MC38 colorectal cancer tumor model in C57BL/6 mice. The combination treatment was five times more effective at reducing tumor size than immune checkpoint inhibition alone in males. We noted sex differences in the response to dietary methionine restriction for the MC38 tumor model in C57BL/6 mice. Finally, we observed an increase in PD-L1 protein expression in MC38 tumors from animals who were fed a methionine-restricted diet. Furthermore, the distribution of CD8 staining changed from mostly peripheric in the controls, to intratumoral in the methionine-restricted tumors. MHC-I, which has a high basal expression in MC38 cells, was highly expressed in all tumors. These results indicate that methionine restriction improves the response to immune checkpoint inhibitors in mice, and that this improvement is associated with the cGAS-STING pathway and interferon signaling.
| S-EPMC10104076 | biostudies-literature