Machine Learning Predictor of Immune Checkpoint Blockade Response in Gastric Cancer.
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ABSTRACT:
SUBMITTER: Sung JY
PROVIDER: S-EPMC9265060 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Gastric cancer (GC) is one of the most important malignancies worldwide because of its high incidence and mortality. The very low survival rates are mainly related to late diagnosis and limited treatment options. GC is the final clinical outcome of a stepwise process that starts with a chronic and sustained inflammatory reaction mounted in response to Helicobacter pylori infection. The bacterium modulates innate and adaptive immunity presumably as part of the strategies to survive, which favors the creation of an immunosuppressive microenvironment that ultimately facilitates GC progression. T-cell exhaustion, which is characterized by elevated expression of immune checkpoint (IC) proteins, is one of the most salient manifestations of immunosuppressive microenvironments. It has been consistently demonstrated that the tumor-immune microenvironment(TIME)-exhausted phenotype can be reverted by blocking ICs with monoclonal antibodies. Although these therapies are associated with long-lasting response rates, only a subset of patients derive clinical benefit, which varies according to tumor site. The search for biomarkers to predict the response to IC inhibition is a matter of intense investigation as this may contribute to maximize disease control, reduce side effects, and minimize cost. The approval of pembrolizumab for its use in GC has rocketed immuno-oncology research in this cancer type. In this review, we summarize the current knowledge centered around the immune contexture and recent findings in connection with IC inhibition in GC.
| S-EPMC6778883 | biostudies-literature
Project description:Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment. However, only some patients respond to ICIs, and current biomarkers for ICI efficacy have limited performance. Here, we devised an interpretable machine learning (ML) model trained using patient-specific cell-cell communication networks (CCNs) decoded from the patient's bulk tumor transcriptome. The model could (i) predict ICI efficacy for patients across four cancer types (median AUROC: 0.79) and (ii) identify key communication pathways with crucial players responsible for patient response or resistance to ICIs by analyzing more than 700 ICI-treated patient samples from 11 cohorts. The model prioritized chemotaxis communication of immune-related cells and growth factor communication of structural cells as the key biological processes underlying response and resistance to ICIs, respectively. We confirmed the key communication pathways and players at the single-cell level in patients with melanoma. Our network-based ML approach can be used to expand ICIs' clinical benefits in cancer patients.
| S-EPMC10830106 | biostudies-literature
Project description:: More than 1.6 million new cases of cancer will be diagnosed in the U.S. in 2016, resulting in more than 500,000 deaths. Although chemotherapy has been the mainstay of treatment in advanced cancers, immunotherapy development, particularly with PD-1 inhibitors, has changed the face of treatment for a number of tumor types. One example is the subset of tumors characterized by mismatch repair deficiency and microsatellite instability that are highly sensitive to PD-1 blockade. Hereditary forms of cancer have been noted for more than a century, but the molecular changes underlying mismatch repair-deficient tumors and subsequent microsatellite unstable tumors was not known until the early 1990s. In this review article, we discuss the history and pathophysiology of mismatch repair, the process of testing for mismatch repair deficiency and microsatellite instability, and the role of immunotherapy in this subset of cancers.Mismatch repair deficiency has contributed to our understanding of carcinogenesis for the past 2 decades and now identifies a subgroup of traditionally chemotherapy-insensitive solid tumors as sensitive to PD-1 blockade. This article seeks to educate oncologists regarding the nature of mismatch repair deficiency, its impact in multiple tumor types, and its implications for predicting the responsiveness of solid tumors to immune checkpoint blockade.
| S-EPMC5061538 | biostudies-other
Project description:An effective antitumor immune response requires interaction between cells of the adaptive and innate immune system. Three key elements are required: generation of activated tumor-directed T cells, infiltration of activated T cells into the tumor microenvironment, and killing of tumor cells by activated T cells. Tumor immune evasion can occur as a result of the disruption of each of these three key T cell activities, resulting in three distinct cancer-immune phenotypes. The immune inflamed phenotype, characterized by the presence of a robust tumor immune infiltrate, suggests impaired activated T cell killing of tumor cells related to the presence of inhibitory factors. Programmed death receptor-1 (PD-1) is an inhibitory transmembrane protein expressed on T cells, B cells, and NK cells. The interaction between PD-1 and its ligands (PD-L1/L2) functions as an immune checkpoint against unrestrained cytotoxic T effector cell activity-it promotes peripheral T effector cell exhaustion and conversion of T effector cells to immunosuppressive T regulatory (Treg) cells. Immune checkpoint inhibitors, which block the PD-1/PD-L1 axis and reactivate cytotoxic T effector cell function, are actively being investigated for the treatment of breast cancer.
| S-EPMC6061922 | biostudies-literature
Project description:Despite impressive durable responses, immune checkpoint inhibitors do not provide a long-term benefit to the majority of patients with cancer. Understanding genomic correlates of response and resistance to checkpoint blockade may enhance benefits for patients with cancer by elucidating biomarkers for patient stratification and resistance mechanisms for therapeutic targeting. Here we review emerging genomic markers of checkpoint blockade response, including those related to neoantigens, antigen presentation, DNA repair, and oncogenic pathways. Compelling evidence also points to a role for T cell functionality, checkpoint regulators, chromatin modifiers, and copy-number alterations in mediating selective response to immune checkpoint blockade. Ultimately, efforts to contextualize genomic correlates of response into the larger understanding of tumor immune biology will build a foundation for the development of novel biomarkers and therapies to overcome resistance to checkpoint blockade.
| S-EPMC6599710 | biostudies-literature
Project description:BackgroundOropharyngeal cancer (OPC) exhibits diverse immunological properties; however, their implications for immunotherapy are unknown.MethodsWe analysed 37 surgically resected and nine recurrent or metastatic anti-programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1)-treated OPC tumours. OPCs were classified into immune-rich (IR), mesenchymal (MS) and xenobiotic (XB) subtypes based on RNA-sequencing data.ResultsAll IR type tumours were human papillomavirus (HPV) positive, most XB types were HPV negative, and MS types showed mixed HPV status. The IR type showed an enriched T cell exhaustion signature with PD-1+ CD8+ T cells and type I macrophages infiltrating the tumour nest on multiplex immunohistochemistry. The MS type showed an exclusion of CD8+ T cells from the tumour nest and high MS and tumour growth factor-β signatures. The XB type showed scant CD8+ T cell infiltration and focal CD73 expression. The IR type was associated with a favourable response signature during anti-PD-1/PD-L1 therapy and showed a high APOBEC mutation signature, whereas the MS and XB types showed resistance signature upregulation. Among anti-PD-1/PD-L1-treated OPC patients, the IR type showed a favourable clinical response (3/4 patients), whereas the XB type showed early progression (3/3 patients).ConclusionOur analysis classified OPCs into three subtypes with distinct immune microenvironments that are potentially related to the response to anti-PD-1/PD-L1 therapy.
| S-EPMC7251088 | biostudies-literature
Project description:Gastric cancer (GC) is one of the main causes of cancer death. The tumor microenvironment has a profound effect on inducing tumor growth, metastasis, and immunosuppression. Fibroblast activation protein-? (FAP) is a protein that is usually expressed in fibroblasts, such as cancer-associated fibroblasts, which are major components of the tumor microenvironment. However, the role of FAP in GC progression and treatment is still unknown. In this study, we explored these problems based on GC patient samples and experimental models. We found that high FAP expression was an independent prognosticator of poor survival in GC patients. FAP+ cancer-associated fibroblasts (CAFs) promoted the survival, proliferation, and migration of GC cell lines in vitro. Moreover, they also induced drug resistance of the GC cell lines and inhibited the antitumor functions of T cells in the GC tumor microenvironment. More importantly, we found that targeting FAP+ CAFs substantially enhanced the antitumor effects of immune checkpoint blockades in GC xenograft models. This evidence highly suggested that FAP is a potential prognosticator of GC patients and a target for synergizing with other treatments, especially immune checkpoint blockades in GC.
| S-EPMC7841289 | biostudies-literature
Project description:BACKGROUND:Despite the great achievements made in immune-checkpoint-blockade (ICB) in cancer therapy, there are no effective predictive biomarkers in gastrointestinal (GI) cancer. METHODS:This study included 93 metastatic GI patients treated with ICBs. The first cohort comprising 73?GI cancer patients were randomly assigned into discovery (n=44) and validation (n=29) cohorts. Comprehensive genomic profiling was performed on all samples to determine tumor mutational burden (TMB) and copy-number alterations (CNAs). A subset of samples was collected for RNA immune oncology (IO) panel sequencing, microsatellite instability (MSI)/mismatch repair and program death ligand 1 (PD-L1) expression evaluation. In addition, 20 gastric cancer (GC) patients were recruited as the second validation cohort. RESULTS:In the first cohort of 73?GI cancer patients, a lower burden of CNA was observed in patients with durable clinical benefit (DCB). In both the discovery (n=44) and validation (n=29) subsets, lower burden of CNA was associated with an improved clinical benefit and better overall survival (OS). Efficacy also correlated with a higher TMB. Of note, a combinatorial biomarker of TMB and CNA may better stratify DCB patients from ICB treatment, which was further confirmed in the second validation cohort of 20 GC patients. Finally, patients with lower burden of CNA revealed increased immune signatures in our cohort and The Cancer Genome Atlas data sets as well. CONCLUSIONS:Our results suggest that the burden of CNA may have superior predictive value compared with other signatures, including PD-L1, MSI and TMB. The joint biomarker of CNA burden and TMB may better stratify DCB patients, thereby providing a rational choice for GI patients treated with ICBs.
| S-EPMC7430454 | biostudies-literature
Project description:BackgroundImmune checkpoint blockade (ICB) therapy has yielded successful clinical responses in treatment of a minority of patients in certain cancer types. Substantial efforts were made to establish biomarkers for predicting responsiveness to ICB. However, the systematic assessment of these ICB response biomarkers remains insufficient.MethodsWe collected 22 transcriptome-based biomarkers for ICB response and constructed multiple benchmark datasets to evaluate the associations with clinical response, predictive performance, and clinical efficacy of them in pre-treatment patients with distinct ICB agents in diverse cancers.ResultsOverall, "Immune-checkpoint molecule" biomarkers PD-L1, PD-L2, CTLA-4 and IMPRES and the "Effector molecule" biomarker CYT showed significant associations with ICB response and clinical outcomes. These immune-checkpoint biomarkers and another immune effector IFN-gamma presented predictive ability in melanoma, urothelial cancer (UC) and clear cell renal-cell cancer (ccRCC). In non-small cell lung cancer (NSCLC), only PD-L2 and CTLA-4 showed preferable correlation with clinical response. Under different ICB therapies, the top-performing biomarkers were usually mutually exclusive in patients with anti-PD-1 and anti-CTLA-4 therapy, and most of biomarkers presented outstanding predictive power in patients with combined anti-PD-1 and anti-CTLA-4 therapy.ConclusionsOur results show these biomarkers had different performance in predicting ICB response across distinct ICB agents in diverse cancers.
| S-EPMC8037221 | biostudies-literature
Project description:PD-1/PD-L1 signaling promotes tumor growth while inhibiting effector cell-mediated antitumor immune responses. Here, we assessed the impact of single and dual blockade of PD-1/PD-L1, alone or in combination with lenalidomide, on accessory and immune cell function as well as multiple myeloma cell growth in the bone marrow (BM) milieu.Surface expression of PD-1 on immune effector cells, and PD-L1 expression on CD138(+) multiple myeloma cells and myeloid-derived suppressor cells (MDSC) were determined in BM from newly diagnosed (ND) multiple myeloma and relapsed/refractory (RR) multiple myeloma versus healthy donor (HD). We defined the impact of single and dual blockade of PD-1/PD-L1, alone and with lenalidomide, on autologous anti-multiple myeloma immune response and tumor cell growth.Both ND and RR patient multiple myeloma cells have increased PD-L1 mRNA and surface expression compared with HD. There is also a significant increase in PD-1 expression on effector cells in multiple myeloma. Importantly, PD-1/PD-L1 blockade abrogates BM stromal cell (BMSC)-induced multiple myeloma growth, and combined blockade of PD-1/PD-L1 with lenalidomide further inhibits BMSC-induced tumor growth. These effects are associated with induction of intracellular expression of IFN? and granzyme B in effector cells. Importantly, PD-L1 expression in multiple myeloma is higher on MDSC than on antigen-presenting cells, and PD-1/PD-L1 blockade inhibits MDSC-mediated multiple myeloma growth. Finally, lenalidomide with PD-1/PD-L1 blockade inhibits MDSC-mediated immune suppression.Our data therefore demonstrate that checkpoint signaling plays an important role in providing the tumor-promoting, immune-suppressive microenvironment in multiple myeloma, and that PD-1/PD-L1 blockade induces anti-multiple myeloma immune response that can be enhanced by lenalidomide, providing the framework for clinical evaluation of combination therapy.
| S-EPMC4609232 | biostudies-literature