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Immune Checkpoint Inhibitors

Immune Checkpoint Inhibitors are a class of immunotherapeutic agents that target immune checkpoint proteins, such as PD-1, PD-L1, and CTLA-4, to enhance the body's natural immune response against cancer.
These innovative therapies have revolutionized the treatment of various malignancies by unleashing the power of the immune system.
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Most cited protocols related to «Immune Checkpoint Inhibitors»

1
Immune and Tumor Profiling in NSCLC and Follicular Lymphoma
Cited 66 times
All patient samples in this study were collected with informed consent for research use and were approved by the Stanford Institutional Review Board in accordance with the Declaration of Helsinki. For a patient with metastatic NSCLC treated with an immune checkpoint inhibitor (Pembrolizumab, Merck), peripheral blood was obtained on the first day of treatment prior to infusion (Fig. 2a; NCT00349830 and NCT02955758). Fresh tumor biopsies from patients with early stage NSCLC were obtained during routine primary surgical resection (Figs. 3g and 5, Supplementary Fig. 13c-f). Fresh or frozen surgical biopsies of follicular lymphoma tumors were obtained from previously untreated FL patients enrolled in a phase III clinical trial (NCT0001729063 (link)), as well as from patients seen as part of the Stanford University Lymphoma Program Project (NCT00398177; Figs. 3b-f, 5a-c, Supplementary Figs. 6a-c, 14). Whole blood samples from 12 healthy adult donors were obtained from the Stanford Blood Center (Fig. 2b,e and Supplementary Figs. 1d,k,l, 2a,d).
Newman A.M., Steen C.B., Liu C.L., Gentles A.J., Chaudhuri A.A., Scherer F., Khodadoust M.S., Esfahani M.S., Luca B.A., Steiner D., Diehn M, & Alizadeh A.A. (2019). Determining cell-type abundance and expression from bulk tissues with digital cytometry. Nature biotechnology, 37(7), 773-782.
Publication 2019
Adult Biopsy BLOOD Donor, Blood Ethics Committees, Research Figs Freezing Immune Checkpoint Inhibitors Lymphoma Lymphoma, Follicular Neoplasms Non-Small Cell Lung Carcinoma Operative Surgical Procedures Patients pembrolizumab Vision
2
Immune and Tumor Profiling in NSCLC and Follicular Lymphoma
Cited 36 times
All patient samples in this study were collected with informed consent for research use and were approved by the Stanford Institutional Review Board in accordance with the Declaration of Helsinki. For a patient with metastatic NSCLC treated with an immune checkpoint inhibitor (Pembrolizumab, Merck), peripheral blood was obtained on the first day of treatment prior to infusion (Fig. 2a; NCT00349830 and NCT02955758). Fresh tumor biopsies from patients with early stage NSCLC were obtained during routine primary surgical resection (Figs. 3g and 5, Supplementary Fig. 13c-f). Fresh or frozen surgical biopsies of follicular lymphoma tumors were obtained from previously untreated FL patients enrolled in a phase III clinical trial (NCT0001729063 (link)), as well as from patients seen as part of the Stanford University Lymphoma Program Project (NCT00398177; Figs. 3b-f, 5a-c, Supplementary Figs. 6a-c, 14). Whole blood samples from 12 healthy adult donors were obtained from the Stanford Blood Center (Fig. 2b,e and Supplementary Figs. 1d,k,l, 2a,d).
Newman A.M., Steen C.B., Liu C.L., Gentles A.J., Chaudhuri A.A., Scherer F., Khodadoust M.S., Esfahani M.S., Luca B.A., Steiner D., Diehn M, & Alizadeh A.A. (2019). Determining cell-type abundance and expression from bulk tissues with digital cytometry. Nature biotechnology, 37(7), 773-782.
Publication 2019
Adult Biopsy BLOOD Donor, Blood Ethics Committees, Research Figs Freezing Immune Checkpoint Inhibitors Lymphoma Lymphoma, Follicular Neoplasms Non-Small Cell Lung Carcinoma Operative Surgical Procedures Patients pembrolizumab Vision
3
Liver Cancer Biopsies and Immunotherapy
Cited 23 times

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Publication 2021
Aftercare Biopsy Cancer of Liver CD274 protein, human CTLA4 protein, human durvalumab Fatty Liver Immune Checkpoint Inhibitors Neoplasms Neoplasms, Liver Patients pembrolizumab tremelimumab
4
Avelumab plus Axitinib vs. Sunitinib in Renal-Cell Carcinoma
Cited 16 times
This was a multicenter, randomized, open-label, phase 3 trial comparing avelumab plus axitinib with sunitinib. Randomization (in a 1:1 ratio) was stratified according to ECOG performance-status score (0 vs. 1) and geographic region (United States vs. Canada and Western Europe vs. the rest of the world).
Avelumab was administered at a dose of 10 mg per kilogram of body weight as a 1-hour intravenous infusion every 2 weeks. An antihistamine and acetaminophen were administered approximately 30 to 60 minutes before each infusion. Axitinib was administered orally at a starting dose of 5 mg twice daily on a continuous dosing schedule. Sunitinib was administered at a dose of 50 mg orally once daily for 4 weeks of a 6-week cycle. Dose escalations and reductions of axitinib and dose reductions of sunitinib are described in the protocol (available at NEJM. org).17 ,18 Dose reductions of avelumab were not permitted, but subsequent infusions could be omitted in response to persisting toxic effects. The original primary objective was to show the superiority of avelumab plus axitinib over sunitinib in prolonging progression-free survival among patients with advanced renal-cell carcinoma, irrespective of PD-L1 expression. A June 2017 protocol amendment, while data were still masked, was based on new data from a single-group phase 1b trial14 (link) and two trials of immune checkpoint inhibitors that showed an overall survival benefit among patients with renal-cell carcinoma.5 (link),6 (link) This amendment changed the primary objective of the trial to show the superiority of avelumab plus axitinib over sunitinib with respect to either progression-free or overall survival among patients with PD-L1–positive tumors.
Motzer R.J., Penkov K., Haanen J., Rini B., Albiges L., Campbell M.T., Venugopal B., Kollmannsberger C., Negrier S., Uemura M., Lee J.L., Vasiliev A., Miller WH J.r., Gurney H., Schmidinger M., Larkin J., Atkins M.B., Bedke J., Alekseev B., Wang J., Mariani M., Robbins P.B., Chudnovsky A., Fowst C., Hariharan S., Huang B., di Pietro A, & Choueiri T.K. (2019). Avelumab plus Axitinib versus Sunitinib for Advanced Renal-Cell Carcinoma. The New England journal of medicine, 380(12), 1103-1115.
Publication 2019
Acetaminophen avelumab Axitinib Body Weight CD274 protein, human Disease Progression Drug Tapering Electrocorticography Histamine H1 Antagonists Immune Checkpoint Inhibitors Intravenous Infusion Neoplasms Patients Renal Cell Carcinoma Sunitinib
5
Molecular Profiling of Metastatic Gastrointestinal Cancers
Cited 14 times
Patients with metastatic esophageal, gastric, and gastroesophageal junction adenocarcinoma receiving therapy at Memorial Sloan Kettering Cancer Center (MSK) were consented to an institutional review board approved protocol for prospective tumor genomic profiling between February 2014 and February 2017. The studies were conducted in accordance with the Declaration of Helsinki, International Ethical Guidelines for Biomedical Research Involving Human Subjects (CIOMS), Belmont Report, or U.S. Common Rule.
All tumors were prospectively reviewed to confirm histologic subtype, Lauren classification, and to estimate tumor content. Of 376 tumors submitted for sequencing, 318 samples were included in the final analysis (see CONSORT diagram in Supplementary Figure 4). We integrated genomic data with clinical characteristics, treatment history, response, and survival data (as of September 2017). Overall survival (OS) time was measured from the date of diagnosis of Stage IV disease until the date of death or last follow-up. Progression-free survival (PFS) and OS on first-line platinum therapy and first-line chemotherapy with trastuzumab and immune checkpoint inhibitors in chemotherapy-refractory patients was calculated from the date of start of treatment to the date of radiographic disease progression, death or last evaluation. Clinical HER2 status was based on HER2 protein expression by immunohistochemistry (IHC, positive defined as 3+) or ERBB2 gene amplification by FISH using College of American Pathologists (CAP)/American Society of Clinical Oncology (ASCO) criteria. IHC analysis of mismatch repair (MMR) proteins, and beta 2 microglobulin (B2M), and Epstein-Barr encoding region (EBER) in situ hybridization analysis was performed on a subset of tumors from patients treated with checkpoint inhibitors.
The MSK-IMPACT assay was performed in a CLIA-certified laboratory, initially using a 341 and more recently 410 and 468 gene panels (Supplementary Table 5), as previously described, with results reported in the electronic medical record (12 (link),31 (link)). The assay is capable of detecting mutations, small insertions and deletions, copy number alterations and select structural rearrangements. In a previously published validation set, ERBB2 amplification calls on this NGS assay had an overall concordance of 98.4% with the combined IHC/FISH results (20 (link)). The PPV and NPV of our NGS assay with respect to HER2 IHC/FISH was calculated in this cohort.
Tumors were assigned to consensus TCGA molecular subtypes: CIN, GS, EBV, MSI-H (3 (link)). We assessed tumors for microsatellite instability (MSI) using the MSI-sensor method, and samples with a score >=10 were classified as MSI-high (MSI-H). Tumors were characterized as genomically stable (GS) if the fraction of the autosomal genome affected by DNA copy number alterations of any kind (FGA) was less than 5%. We classified tumors that were neither EBV-positive, MSI, or GS as CIN (chromosomal instability). The OncoKB Precision Oncology Knowledge Base was used (data from May 2017) (14 ) to infer the oncogenic effect and clinical actionability of individual somatic mutations. Recurrent mutational hotspots were annotated using cancerhotspots.org (32 (link)). We inferred allele-specific DNA copy number using FACETS (33 (link)) to determine the zygosity of key mutant tumor suppressors as well as to generate estimates of tumor purity. We also inferred large-scale state transition (LST) scores (34 (link)), based on the copy number data, from tumors with an analytically estimated tumor purity greater than 20%. Samples with <20% tumor content were excluded from the analysis.
Janjigian Y.Y., Sanchez-Vega F., Jonsson P., Chatila W.K., Hechtman J.F., Ku G.Y., Riches J.C., Tuvy Y., Kundra R., Bouvier N., Vakiani E., Gao J., Heins Z.J., Gross B.E., Kelsen D.P., Zhang L., Strong V.E., Schattner M., Gerdes H., Coit D.G., Bains M., Stadler Z.K., Rusch V.W., Jones D.R., Molena D., Shia J., Robson M.E., Capanu M., Middha S., Zehir A., Hyman D.M., Scaltriti M., Ladanyi M., Rosen N., Ilson D.H., Berger M.F., Tang L., Taylor B.S., Solit D.B, & Schultz N. (2017). Genetic predictors of response to systemic therapy in esophagogastric cancer. Cancer discovery, 8(1), 49-58.
Publication 2017
Adenocarcinoma Alleles BETA MICROGLOBULIN 2 Biological Assay Cell Cycle Checkpoints Chromosomal Instability Copy Number Polymorphism Diagnosis Diploid Cell Disease Progression ERBB2 protein, human Esophagogastric Junction Ethics Committees, Research Fishes Gene Amplification Gene Deletion Gene Rearrangement Genes Genome Immune Checkpoint Inhibitors Immunohistochemistry inhibitors Insertion Mutation In Situ Hybridization Malignant Neoplasms Microsatellite Instability Mismatch Repair Mutation Neoplasms Oncogenes Pathologists Patients Pharmacotherapy Platinum Proteins Stomach Trastuzumab Tumor Suppressor Genes X-Rays, Diagnostic

Most recents protocols related to «Immune Checkpoint Inhibitors»

1
Targeting ADAR1 in High Interferon Tumors
Not available on PMC !

Example 17

Since interferon signaling is spontaneously activated in a subset of cancer cells and exposes potential therapeutic vulnerabilities, it was tested whether there is evidence for similar endogenous interferon activation in primary human tumors. An IFN-GES threshold was computed to predict ADAR dependency across the CCLE cell lines and was determined to be a z-score above 2.26 (FIG. 66, panel A). This threshold was applied to The Cancer Genome Atlas (TCGA) tumors, to identify primary cancers with similarly high interferon activation. Restricting the analysis to the 4,072 samples analyzed by TCGA with at least 70% tumor purity as estimated by the ABSOLUTE algorithm (Carter et al. (2012) Nat. Biotechnol. 30:413-421), 2.7% of TCGA tumors displayed IFN-GESs above this threshold (FIG. 66, panel B and. GSEA of amplified genes in these high purity, high interferon tumors revealed the top pathway as “Type I Interferon Receptor Binding”, comprising 17 genes that all encode type I interferons and are clustered on chromosome 9p21.3 (FIG. 67).

Furthermore, analysis of TCGA copy number data showed that the interferon gene cluster including IFN-β (IFNβI), IFN-ε (IFNE), IFN-ω (IFNWI), and all 13 subtypes of IFN-α on chromosome 9p21.3, proximal to the CDKN2A/CDKN2B tumor suppressor locus, is one of the most frequently homozygously deleted regions in the cancer genome. The interferon genes comprise 16 of the 26 most frequently deleted coding genes across 9,853 TCGA cancer specimens for which ABSOLUTE copy number data are available (FIG. 66, panels C and D). Interferon signaling and activation, both in tumors with high IFN-GESs or deletions in chromosome 9p, therefore represent a biomarker to stratify patients who benefit from interferon modulating therapies.

In summary, specific cancer cell lines have been identified with elevated IFN-β signaling triggered by an activated cytosolic DNA sensing pathway, conferring dependence on the RNA editing enzyme, ADAR1. In cells with low, basal interferon signaling, the cGAS-STING pathway is inactive and PKR levels are reduced (FIG. 68, panel A). Upon cGAS-STING activation, interferon signaling and PKR protein levels are elevated but ADAR1 is still able to suppress PKR activation (FIG. 68, panel B). However, once ADAR1 is deleted, the abundant PKR becomes activated and leads to downstream signaling and cell death (FIG. 68, panel C). This is also shown in normal cells lines (e.g. A549 and NCI-H1437) once exogenous interferon is introduced (FIG. 68, panel D). ADAR1 deficiency in cell lines with high interferon levels, whether from endogenous or exogenous sources, led to phosphorylation and activation of PKR, ATF4-mediated gene expression, and apoptosis. Recent studies have shown that cGAS activation and innate interferon signaling, induced by cytosolic DNA released from the nucleus by DNA damage and genome instability (Mackenzie et al. (2017) Nature 548:461-465; Harding et al. (2017) Nature 548:466-470), led to elevated interferon-related gene expression signatures, which have been linked to resistance to DNA damage, chemotherapy, and radiation in cancer cells (Weichselbaum et al. (2008) Proc. Natl. Acad. Sci. USA 105:18490-18495). In high-interferon tumors, blocking ADAR1 might be effective to induce PKR-mediated apoptotic pathways while upregulating type I interferon signaling, which could contribute to anti-tumor immune responses (Parker et al. (2016) Nature 16:131-144). Alternatively, in tumors without activated interferon signaling, ADAR1 inhibition can be combined with localized interferon inducers, such as STING agonists, chemotherapy, or radiation. Generation of specific small molecule inhibitors targeting ADAR1 exploits this novel vulnerability in lung and other cancers and serves to enhance innate immunity in combination with immune checkpoint inhibitors.

US11873486B2. Modulating dsRNA editing, sensing, and metabolism to increase tumor immunity and improve the efficacy of cancer immunotherapy and/or modulators of intratumoral interferon (2024-01-16). Dana-Farber Cancer Institute, Inc. [US]. Inventors: Matthew Meyerson [US], William N. Haining [US], Jeffrey Ishizuka [US], Robert Manguso [US], Hugh Gannon [US].
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Patent 2024
agonists Apoptosis ATF4 protein, human Biological Markers CDKN2A Gene Cell Death Cell Lines Cell Nucleus Cells Chromogranin A Chromosome Deletion Chromosomes, Human, Pair 3 Cytosol DNA Damage Electromagnetic Radiation Enzymes Gene, Cancer Gene Clusters Gene Expression Genes Genome Genomic Instability Homo sapiens IFNAR2 protein, human Immune Checkpoint Inhibitors Immunity, Innate inhibitors Interferon-alpha Interferon Inducers interferon omega 1 Interferons Interferon Type I Lung Malignant Neoplasms Neoplasms Oncogenes Patients Pharmacotherapy Phosphorylation Proteins Psychological Inhibition Response, Immune Tumor Suppressor Genes
2
Predicting Immunotherapy Response with IPS and TIDE
In the immunotherapy response analyses, immunophenoscore (IPS) was a superior predictor of response to anti-cytotoxic T lymphocyte antigen-4 (CTLA-4) and anti-programmed cell death protein 1 (PD-1) antibodies [25 (link)]. IPS, available through The Cancer Immunome Atlas (TCIA) (https://tcia.at/), is developed from four categories: effector cells (activated CD4 + T cells, activated CD8 + T cells, effector memory CD4 + T cells, and effector memory CD8 + T cells), suppressive cells (Tregs and MDSCs), MHC-related molecules, and checkpoints or immunomodulators. Tumor Immune Dysfunction and Exclusion (TIDE) was calculated online (http://tide.dfci.harvard.edu/) and had potential clinical efficacy to assess the responsiveness of patients in different risk groups to immune checkpoint inhibitors (ICIs) therapy. The TIDE score is superior to recognized immunotherapy biomarkers (PD-L1 level, and interferon γ) for assessing anti-PD1 and anti-CTLA4 effectiveness. The responses to chemotherapy and target therapy were assessed using the “pRRophetic” package based on the Genomics of Drug Sensitivity in Cancer (GDSC) website (https://www.cancerrxgene.org/). A lower half-maximal inhibitory concentration (IC50) referred to a higher sensitivity to the drug treatment.
Liu Q., Li R., Wu H, & Liang Z. (2023). A novel cuproptosis-related gene model predicts outcomes and treatment responses in pancreatic adenocarcinoma. BMC Cancer, 23, 226.
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Publication 2023
Antibodies Antineoplastic Agents Biological Markers Biological Response Modifiers CD4 Positive T Lymphocytes CD8-Positive T-Lymphocytes CD274 protein, human Cell Cycle Checkpoints Cells CTLA4 protein, human Effector Memory T Cells Group Therapy Hypersensitivity Immune Checkpoint Inhibitors Immune System Diseases Immunotherapy Interferon Type II Malignant Neoplasms Myeloid-Derived Suppressor Cells Neoplasms Patients Pharmaceutical Preparations Pharmacotherapy Psychological Inhibition
3
Systemic Treatments for Advanced Squamous NSCLC
The target population was Chinese adults (aged ≥ 18 years) who had pathologically confirmed stage IIIB–IV wild-type sq-NSCLC with unlimited PD-L1 expression. The population received no previous systemic therapy. We modeled a hypothetical cohort with the same baseline characteristics as the patients enrolled in the original clinical trials. For dosage calculation, the body surface area and creatinine clearance rate were assumed as 1.72 m2 and 70 ml/min (22 (link)). According to the CSCO 2022 (21 ), the first-level recommended first-line regimens for performance status (PS) 0–1 patients with advanced sq-NSCLC and unlimited PD-L1 expression include cisplatin or carboplatin combined with gemcitabine, docetaxel, or paclitaxel (standard chemotherapy), nedaplatin combined with docetaxel (N + C), paclitaxel and platinum combined with pembrolizumab (P + C), paclitaxel and platinum combined with tislelizumab (T + C), paclitaxel and platinum combined with camrelizumab (CA + C), platinum combined with gemcitabine and sintilimab (SI + C), paclitaxel and platinum combined with sugemalimab (SU + C). Among these seven first-line therapies, T + C, CA + C, SI + C, and SU + C were newly approved for sq-NSCLC since 2021 in China. Nivolumab, tislelizumab and docetaxel are first-level recommended second-line treatments options for these patients, and tislelizumab was newly approved in 2022 for second-line treatment of sq-NSCLC. Because of the possible resistance among PD-1/PD-L1 drugs, few clinical applications and evidence, we did not consider cases where immune checkpoint inhibitors were used in the first- and second-line treatments simultaneously. Therefore, we assessed 11 treatment strategies (see Figure 1): 1. first-line N + C followed by second-line docetaxel (ND); 2. first-line N + C followed by second-line tislelizumab (NT); 3. first-line N + C followed by second-line nivolumab (NN) (16 (link)); 4. first-line standard chemotherapy followed by second-line docetaxel (CD); 5. first-line standard chemotherapy followed by second-line tislelizumab (CT); 6. first-line standard chemotherapy followed by second-line nivolumab (CN) (10 (link)–13 (link), 16 (link), 20 (link)); 7. first-line P + C followed by second-line docetaxel (PED) (13 (link)); 8. first-line SI + C followed by second-line docetaxel (SID) (12 (link)); 9. first-line CA + C followed by second-line docetaxel (CAD) (11 (link)); 10. first-line T + C followed by second-line docetaxel (TID) (20 (link)); 11. first-line SU + C followed by second-line docetaxel (SUD) (10 (link)). According to randomized clinical trials (RCTs) (23 (link), 24 (link)), clinical diagnosis, and treatment experience (25 (link), 26 (link)), the PS of patients with advanced sq-NSCLC tends to be poor after two-line active treatments. Therefore, the best supportive treatment (BSC) accounts for the largest proportion of third-line treatment, surpassing sum of other active treatments' proportions. Thus, patients with disease progression after the first- and second-line treatments were assumed to receive the BSC in this model. Standard chemotherapy and docetaxel were used as comparators for first-line and second-line treatments, respectively. We explored the impact of uncertainty about the third-line treatment on the results by scenario analysis. Specific medication, dosages, treatment durations are provided in the Supplementary material 1.
Zhao M., Shao T., Chi Z, & Tang W. (2023). Effectiveness and cost-effectiveness analysis of 11 treatment paths, seven first-line and three second-line treatments for Chinese patients with advanced wild-type squamous non-small cell lung cancer: A sequential model. Frontiers in Public Health, 11, 1051484.
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Publication 2023
Adult Body Surface Area camrelizumab Carboplatin CD274 protein, human Chinese Cisplatin Creatinine Diagnosis Disease Progression Docetaxel Gemcitabine Immune Checkpoint Inhibitors LINE-1 Elements Metabolic Clearance Rate nedaplatin Nivolumab Non-Small Cell Lung Carcinoma Paclitaxel Patients pembrolizumab Pharmaceutical Preparations Pharmacotherapy Platinum Resistance, Drug sintilimab Target Population tislelizumab Treatment Protocols
4
Systematic Review on Immunotherapies and SBRT
This study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines (Supplementary Checklist S1, Supplemental Digital Content, http://links.lww.com/MD/I616).[8 (link),9 (link)] Two investigators independently searched for studies published before October 31, 2022 in PubMed, Embase, Cochrane Library, and Web of Science. The search keywords were “immune checkpoint inhibitors, ‘PD1 inhibitors’, ‘PDL1 inhibitors’, ‘nivolumab’, ‘pembrolizumab’, ‘camrelizumab’, and ‘radiotherapy’, ‘Stereotactic body radiation therapy’, ‘SBRT’, and ‘angiogenesis inhibitors’, ‘bevacizumab’, ‘apatinib’, ‘sorafenib’, and,” “cancer,” “carcinoma,” “carcinoma,” “tumor”; the search strategy for each database is shown in Supplementary Table S1, Supplemental Digital Content, http://links.lww.com/MD/I617. In addition, references to reviews and original studies were scanned to avoid missing studies that should be included.
Xian F., Wu J., Zhong L, & Xu G. (2023). Efficacy and safety of PD1/PDL1 inhibitors combined with radiotherapy and anti-angiogenic therapy for solid tumors: A systematic review and meta-analysis. Medicine, 102(10), e33204.
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Publication 2023
Angiogenesis Inhibitors apatinib Bevacizumab camrelizumab Carcinoma CD274 protein, human cDNA Library Human Body Immune Checkpoint Inhibitors inhibitors Malignant Neoplasms Neoplasms Nivolumab pembrolizumab Programmed Cell Death Protein 1 Inhibitor Radiosurgery, Stereotactic Radiotherapy Sorafenib
5
Feasibility of RATS After Neoadjuvant Chemoimmunotherapy in NSCLC
This research was a retrospective study conducted at Xiangya Hospital, Central South University, and was designed to evaluate the safety and feasibility of RATS after neoadjuvant chemoimmunotherapy in NSCLC patients.
Patients who received surgery for NSCLC from May 2020 to August 2022 were included if they met the following inclusion criteria: pathological types of NSCLC were confirmed by pathology results before neoadjuvant chemoimmunotherapy; NSCLC stages before neoadjuvant chemoimmunotherapy were diagnosed as IIA–IIIB (American Joint Committee on Cancer, 8th edition) (10 (link)); received three cycles neoadjuvant chemoimmunotherapy, with PD-1/PD-L1 immune checkpoint inhibitors plus platinum-based doublet chemotherapy; and their Eastern Cooperative Oncology Group performance-status score before neoadjuvant chemoimmunotherapy was 0 or 1. Patients were excluded if they met any of the exclusion criterion as follows: aged < 18 years old; stage IIIB patients who were diagnosed with N3 lymph node metastasis positive; chose thoracotomy as the initial surgical approach; received extra medicine for neoadjuvant chemoimmunotherapy at the same time; or clinical data was incomplete.
Zeng J., Yi B., Chang R., Chen Y., Yu Z, & Gao Y. (2023). Safety and feasibility of robotic-assisted thoracic surgery after neoadjuvant chemoimmunotherapy in non-small cell lung cancer. Frontiers in Oncology, 13, 1134713.
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Publication 2023
CD274 protein, human Immune Checkpoint Inhibitors Joints Lymph Node Metastasis Malignant Neoplasms Neoadjuvant Therapy Neoplasms Non-Small Cell Lung Carcinoma Operative Surgical Procedures Patients Pharmaceutical Preparations Pharmacotherapy Platinum Rattus norvegicus Safety Thoracotomy

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More about "Immune Checkpoint Inhibitors"

Immune Checkpoint Inhibitors are a revolutionary class of immunotherapeutic agents that have transformed cancer treatment by harnessing the power of the body's natural immune system.
These innovative therapies target immune checkpoint proteins, such as PD-1, PD-L1, and CTLA-4, to enhance the immune response against various malignancies.
Researchers can optimize their research protocols for Immune Checkpoint Inhibitors using the cutting-edge AI-driven platform from PubCompare.ai.
This platform provides access to a vast database of protocols from scientific literature, pre-prints, and patents.
Researchers can utilize intelligent comparison tools to identify the best protocols and products for their specific needs, taking their research to new heights with state-of-the-art technology.
The use of Immune Checkpoint Inhibitors has been extensively studied in various contexts, including the BE0146 and HPD-1/hPD-L1 Blockade Bioassay protocols.
Additionally, related techniques such as the Bio-GloTM Assay reagent and the use of BALB/c mice have been employed in the research of these novel therapies.
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