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Tumor mutational burden (TMB) has been recognized as a predictive biomarker for immunotherapy response in several tumor types. Several laboratories offer TMB testing, but there is significant variation in how TMB is calculated, reported, and interpreted among laboratories. TMB standardization efforts are underway, but no published guidance for TMB validation and reporting is currently available. Recognizing the current challenges of clinical TMB testing, the Association for Molecular Pathology convened a multidisciplinary collaborative working group with representation from the American Society of Clinical Oncology, the College of American Pathologists, and the Society for the Immunotherapy of Cancer to review the laboratory practices surrounding TMB and develop recommendations for the analytical validation and reporting of TMB testing based on survey data, literature review, and expert consensus. These recommendations encompass pre-analytical, analytical, and postanalytical factors of TMB analysis, and they emphasize the relevance of comprehensive methodological descriptions to allow comparability between assays.
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Biomarcadores de Tumor , Mutación , Neoplasias , Humanos , Neoplasias/genética , Neoplasias/terapia , Neoplasias/inmunología , Biomarcadores de Tumor/genética , Inmunoterapia/métodos , Patología Molecular/métodos , Consenso , Sociedades Médicas , Estados Unidos , Patólogos , Reproducibilidad de los Resultados , Análisis Mutacional de ADN/métodos , Análisis Mutacional de ADN/normasRESUMEN
(1) Background: Digital pathology (DP) is transforming the landscape of clinical practice, offering a revolutionary approach to traditional pathology analysis and diagnosis. (2) Methods: This innovative technology involves the digitization of traditional glass slides which enables pathologists to access, analyze, and share high-resolution whole-slide images (WSI) of tissue specimens in a digital format. By integrating cutting-edge imaging technology with advanced software, DP promises to enhance clinical practice in numerous ways. DP not only improves quality assurance and standardization but also allows remote collaboration among experts for a more accurate diagnosis. Artificial intelligence (AI) in pathology significantly improves cancer diagnosis, classification, and prognosis by automating various tasks. It also enhances the spatial analysis of tumor microenvironment (TME) and enables the discovery of new biomarkers, advancing their translation for therapeutic applications. (3) Results: The AI-driven immune assays, Immunoscore (IS) and Immunoscore-Immune Checkpoint (IS-IC), have emerged as powerful tools for improving cancer diagnosis, prognosis, and treatment selection by assessing the tumor immune contexture in cancer patients. Digital IS quantitative assessment performed on hematoxylin-eosin (H&E) and CD3+/CD8+ stained slides from colon cancer patients has proven to be more reproducible, concordant, and reliable than expert pathologists' evaluation of immune response. Outperforming traditional staging systems, IS demonstrated robust potential to enhance treatment efficiency in clinical practice, ultimately advancing cancer patient care. Certainly, addressing the challenges DP has encountered is essential to ensure its successful integration into clinical guidelines and its implementation into clinical use. (4) Conclusion: The ongoing progress in DP holds the potential to revolutionize pathology practices, emphasizing the need to incorporate powerful AI technologies, including IS, into clinical settings to enhance personalized cancer therapy.
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Digital pathology poses unique computational challenges, as a standard gigapixel slide may comprise tens of thousands of image tiles1-3. Prior models have often resorted to subsampling a small portion of tiles for each slide, thus missing the important slide-level context4. Here we present Prov-GigaPath, a whole-slide pathology foundation model pretrained on 1.3 billion 256 × 256 pathology image tiles in 171,189 whole slides from Providence, a large US health network comprising 28 cancer centres. The slides originated from more than 30,000 patients covering 31 major tissue types. To pretrain Prov-GigaPath, we propose GigaPath, a novel vision transformer architecture for pretraining gigapixel pathology slides. To scale GigaPath for slide-level learning with tens of thousands of image tiles, GigaPath adapts the newly developed LongNet5 method to digital pathology. To evaluate Prov-GigaPath, we construct a digital pathology benchmark comprising 9 cancer subtyping tasks and 17 pathomics tasks, using both Providence and TCGA data6. With large-scale pretraining and ultra-large-context modelling, Prov-GigaPath attains state-of-the-art performance on 25 out of 26 tasks, with significant improvement over the second-best method on 18 tasks. We further demonstrate the potential of Prov-GigaPath on vision-language pretraining for pathology7,8 by incorporating the pathology reports. In sum, Prov-GigaPath is an open-weight foundation model that achieves state-of-the-art performance on various digital pathology tasks, demonstrating the importance of real-world data and whole-slide modelling.
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Conjuntos de Datos como Asunto , Procesamiento de Imagen Asistido por Computador , Aprendizaje Automático , Patología Clínica , Humanos , Benchmarking , Procesamiento de Imagen Asistido por Computador/métodos , Neoplasias/clasificación , Neoplasias/diagnóstico , Neoplasias/patología , Patología Clínica/métodos , Masculino , FemeninoRESUMEN
Preclinical murine data indicate that fragment crystallizable (Fc)-dependent depletion of intratumoral regulatory T cells (Treg) is a major mechanism of action of anti-CTLA-4. However, the two main antibodies administered to patients (ipilimumab and tremelimumab) do not recapitulate these effects. Here, we investigate the underlying mechanisms responsible for the limited Treg depletion observed with these therapies. Using an immunocompetent murine model humanized for CTLA-4 and Fcγ receptors (FcγR), we show that ipilimumab and tremelimumab exhibit limited Treg depletion in tumors. Immune profiling of the tumor microenvironment (TME) in both humanized mice and humans revealed high expression of the inhibitory Fc receptor, FcγRIIB, which limits antibody-dependent cellular cytotoxicity/phagocytosis. Blocking FcγRIIB in humanized mice rescued the Treg-depleting capacity and antitumor activity of ipilimumab. Furthermore, Fc engineering of antibodies targeting Treg-associated targets (CTLA-4 or CCR8) to minimize FcγRIIB binding significantly enhanced Treg depletion, resulting in increased antitumor activity across various tumor models. Our results define the inhibitory FcγRIIB as an immune checkpoint limiting antibody-mediated Treg depletion in the TME, and demonstrate Fc engineering as an effective strategy to overcome this limitation and improve the efficacy of Treg-targeting antibodies.
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Neoplasias , Linfocitos T Reguladores , Humanos , Animales , Ratones , Ipilimumab/farmacología , Ipilimumab/uso terapéutico , Antígeno CTLA-4 , Microambiente Tumoral , Neoplasias/tratamiento farmacológicoRESUMEN
BACKGROUND: The Immunoscore (IS) is a quantitative digital pathology assay that evaluates the immune response in cancer patients. This study reports on the reproducibility of pathologists' visual assessment of CD3+- and CD8+-stained colon tumors, compared to IS quantification. METHODS: An international group of expert pathologists evaluated 540 images from 270 randomly selected colon cancer (CC) cases. Concordance between pathologists' T-score, corresponding hematoxylin-eosin (H&E) slides, and the digital IS was evaluated for two- and three-category IS. RESULTS: Non-concordant T-scores were reported in more than 92% of cases. Disagreement between semi-quantitative visual assessment of T-score and the reference IS was observed in 91% and 96% of cases before and after training, respectively. Statistical analyses showed that the concordance index between pathologists and the digital IS was weak in two- and three-category IS, respectively. After training, 42% of cases had a change in T-score, but no improvement was observed with a Kappa of 0.465 and 0.374. For the 20% of patients around the cut points, no concordance was observed between pathologists and digital pathology analysis in both two- and three-category IS, before or after training (all Kappa < 0.12). CONCLUSIONS: The standardized IS assay outperformed expert pathologists' T-score evaluation in the clinical setting. This study demonstrates that digital pathology, in particular digital IS, represents a novel generation of immune pathology tools for reproducible and quantitative assessment of tumor-infiltrated immune cell subtypes.
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The discovery and development of novel treatments that harness the patient's immune system and prevent immune escape has dramatically improved outcomes for patients across cancer types. However, not all patients respond to immunotherapy, acquired resistance remains a challenge, and responses are poor in certain tumors which are considered to be immunologically cold. This has led to the need for new immunotherapy-based approaches, including adoptive cell transfer (ACT), therapeutic vaccines, and novel immune checkpoint inhibitors. These new approaches are focused on patients with an inadequate response to current treatments, with emerging evidence of improved responses in various cancers with new immunotherapy agents, often in combinations with existing agents. The use of cell therapies, drivers of immune response, and trends in immunotherapy were the focus of the Immunotherapy Bridge (November 30th-December 1st, 2022), organized by the Fondazione Melanoma Onlus, Naples, Italy, in collaboration with the Society for Immunotherapy of Cancer.
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Melanoma , Humanos , Inmunoterapia , Inmunoterapia Adoptiva , Italia , Melanoma/patología , Microambiente TumoralRESUMEN
Most detailed patient information in real-world data (RWD) is only consistently available in free-text clinical documents. Manual curation is expensive and time consuming. Developing natural language processing (NLP) methods for structuring RWD is thus essential for scaling real-world evidence generation. We propose leveraging patient-level supervision from medical registries, which are often readily available and capture key patient information, for general RWD applications. We conduct an extensive study on 135,107 patients from the cancer registry of a large integrated delivery network (IDN) comprising healthcare systems in five western US states. Our deep-learning methods attain test area under the receiver operating characteristic curve (AUROC) values of 94%-99% for key tumor attributes and comparable performance on held-out data from separate health systems and states. Ablation results demonstrate the superiority of these advanced deep-learning methods. Error analysis shows that our NLP system sometimes even corrects errors in registrar labels.
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Background: The prognostic value of Immunoscore was evaluated in Stage II/III colon cancer (CC) patients, but it remains unclear in Stage I/II, and in early-stage subgroups at risk. An international Society for Immunotherapy of Cancer (SITC) study evaluated the pre-defined consensus Immunoscore in tumors from 1885 AJCC/UICC-TNM Stage I/II CC patients from Canada/USA (Cohort 1) and Europe/Asia (Cohort 2). METHODS: Digital-pathology is used to quantify the densities of CD3+ and CD8+ T-lymphocyte in the center of tumor (CT) and the invasive margin (IM). The time to recurrence (TTR) was the primary endpoint. Secondary endpoints were disease-free survival (DFS), overall survival (OS), prognosis in Stage I, Stage II, Stage II-high-risk, and microsatellite-stable (MSS) patients. RESULTS: High-Immunoscore presented with the lowest risk of recurrence in both cohorts. In Stage I/II, recurrence-free rates at 5 years were 78.4% (95%-CI, 74.4−82.6), 88.1% (95%-CI, 85.7−90.4), 93.4% (95%-CI, 91.1−95.8) in low, intermediate and high Immunoscore, respectively (HR (Hi vs. Lo) = 0.27 (95%-CI, 0.18−0.41); p < 0.0001). In Cox multivariable analysis, the association of Immunoscore to outcome was independent (TTR: HR (Hi vs. Lo) = 0.29, (95%-CI, 0.17−0.50); p < 0.0001) of the patient's gender, T-stage, sidedness, and microsatellite instability-status (MSI). A significant association of Immunoscore with survival was found for Stage II, high-risk Stage II, T4N0 and MSS patients. The Immunoscore also showed significant association with TTR in Stage-I (HR (Hi vs. Lo) = 0.07 (95%-CI, 0.01−0.61); P = 0.016). The Immunoscore had the strongest (69.5%) contribution χ2 for influencing survival. Patients with a high Immunoscore had prolonged TTR in T4N0 tumors even for patients not receiving chemotherapy, and the Immunoscore remained the only significant parameter in multivariable analysis. CONCLUSION: In early CC, low Immunoscore reliably identifies patients at risk of relapse for whom a more intensive surveillance program or adjuvant treatment should be considered.
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Despite pre-clinical murine data supporting T regulatory (Treg) cell depletion as a major mechanism by which anti-CTLA-4 antibodies function in vivo, the two main antibodies tested in patients (ipilimumab and tremelimumab) have failed to demonstrate similar effects. We report analogous findings in an immunocompetent murine model humanized for CTLA-4 and Fcy receptors (hCTLA-4/hFcyR mice), where both ipilimumab and tremelimumab fail to show appreciable Treg depletion. Immune profiling of the tumor microenvironment (TME) in both mice and human samples revealed upregulation of the inhibitory Fcy receptor, FcyRIIB, which limits the ability of the antibody Fc fragment of human anti-CTLA-4 antibodies to induce effective antibody dependent cellular cytotoxicty/phagocytosis (ADCC/ADCP). Blocking FcyRIIB in humanized mice rescues Treg depleting capacity and anti-tumor activity of ipilimumab. For another target, CC motif chemokine receptor 8 (CCR8), which is selectively expressed on tumor infiltrating Tregs, we show that Fc engineering to enhance binding to activating Fc receptors, while limiting binding to the inhibitory Fc receptor, leads to consistent Treg depletion and single-agent activity across multiple tumor models, including B16, MC38 and MB49. These data reveal the importance of reducing engagement to the inhibitory Fc receptor to optimize Treg depletion by TME targeting antibodies. Our results define the inhibitory FcyRIIB receptor as a novel immune checkpoint limiting antibody-mediated Treg depletion in tumors, and demonstrate Fc variant engineering as a means to overcome this limitation and augment efficacy for a repertoire of antibodies currently in use or under clinical evaluation in oncology.
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Tumor mutational burden (TMB), a surrogate for tumor neoepitope burden, is used as a pan-tumor biomarker to identify patients who may benefit from anti-program cell death 1 (PD1) immunotherapy, but it is an imperfect biomarker. Multiple additional genomic characteristics are associated with anti-PD1 responses, but the combined predictive value of these features and the added informativeness of each respective feature remains unknown. We evaluated whether machine learning (ML) approaches using proposed determinants of anti-PD1 response derived from whole exome sequencing (WES) could improve prediction of anti-PD1 responders over TMB alone. Random forest classifiers were trained on publicly available anti-PD1 data (n = 104), and subsequently tested on an independent anti-PD1 cohort (n = 69). Both the training and test datasets included a range of cancer types such as non-small cell lung cancer (NSCLC), head and neck squamous cell carcinoma (HNSCC), melanoma, and smaller numbers of patients from other tumor types. Features used include summaries such as TMB and number of frameshift mutations, as well as more gene-level features such as counts of mutations associated with immune checkpoint response and resistance. Both ML algorithms demonstrated area under the receiver-operator curves (AUC) that exceeded TMB alone (AUC 0.63 "human-guided," 0.64 "cluster," and 0.58 TMB alone). Mutations within oncogenes disproportionately modulate anti-PD1 responses relative to their overall contribution to tumor neoepitope burden. The use of a ML algorithm evaluating multiple proposed genomic determinants of anti-PD1 responses modestly improves performance over TMB alone, highlighting the need to integrate other biomarkers to further improve model performance.
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BACKGROUND: In this study, we evaluated the prognostic value of Immunoscore in patients with stage I−III colon cancer (CC) in the Asian population. These patients were originally included in an international study led by the Society for Immunotherapy of Cancer (SITC) on 2681 patients with AJCC/UICC-TNM stages I−III CC. METHODS: CD3+ and cytotoxic CD8+ T-lymphocyte densities were quantified in the tumor and invasive margin by digital pathology. The association of Immunoscore with prognosis was evaluated for time to recurrence (TTR), disease-free survival (DFS), and overall survival (OS). RESULTS: Immunoscore stratified Asian patients (n = 423) into different risk categories and was not impacted by age. Recurrence-free rates at 3 years were 78.5%, 85.2%, and 98.3% for a Low, Intermediate, and High Immunoscore, respectively (HR[Low-vs-High] = 7.26 (95% CI 1.75−30.19); p = 0.0064). A High Immunoscore showed a significant association with prolonged TTR, OS, and DFS (p < 0.05). In Cox multivariable analysis stratified by center, Immunoscore association with TTR was independent (HR[Low-vs-Int+High] = 2.22 (95% CI 1.10−4.55) p = 0.0269) of the patient's gender, T-stage, N-stage, sidedness, and MSI status. A significant association of a High Immunoscore with prolonged TTR was also found among MSS (HR[Low-vs-Int+High] = 4.58 (95% CI 2.27−9.23); p ≤ 0.0001), stage II (HR[Low-vs-Int+High] = 2.72 (95% CI 1.35−5.51); p = 0.0052), low-risk stage-II (HR[Low-vs-Int+High] = 2.62 (95% CI 1.21−5.68); p = 0.0146), and high-risk stage II patients (HR[Low-vs-Int+High] = 3.11 (95% CI 1.39−6.91); p = 0.0055). CONCLUSION: A High Immunoscore is significantly associated with the prolonged survival of CC patients within the Asian population.
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Over the past decade, immunotherapy has become an increasingly fundamental modality in the treatment of cancer. The positive impact of immune checkpoint inhibition, especially anti-programmed death (PD)-1/PD-ligand (L)1 blockade, in patients with different cancers has focused attention on the potential for other immunotherapeutic approaches. These include inhibitors of additional immune checkpoints, adoptive cell transfer (ACT), and therapeutic vaccines. Patients with advanced cancers who previously had limited treatment options available may now benefit from immunotherapies that can offer durable responses and improved survival outcomes. However, despite this, a significant proportion of patients fail to respond to immunotherapy, especially those with less immunoresponsive cancer types, and there remains a need for new treatment strategies.The virtual Immunotherapy Bridge (December 1st-2nd, 2021), organized by the Fondazione Melanoma Onlus, Naples, Italy in collaboration with the Society for Immunotherapy of Cancer addressed several areas of current research in immunotherapy, including lessons learned from cell therapies, drivers of immune response, and trends in immunotherapy across different cancers, and these are summarised here.
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Biomarcadores de Tumor , Melanoma , Biomarcadores de Tumor/metabolismo , Humanos , Factores Inmunológicos , Inmunoterapia , ItaliaRESUMEN
BACKGROUND: This review summarizes the case studies of PCM1-JAK2 fusion tyrosine kinase gene-related neoplasia. Recommended treatment includes JAK2 inhibitors and hematologic stem cell transplantation (HSCT), although the small number of patients has limited study of their efficacy. Herein, we present all available cases in the current searchable literature with their demographics, diagnoses, treatments, and outcomes. METHODS: PubMed, ScienceDirect, Publons, the Cochrane Library, and Google were searched with the following terms: PCM1-JAK2, ruxolitinib and myeloid/lymphoid. RESULTS: Sixty-six patients (mean age = 50, 77% male) had an initial diagnosis of myeloproliferative neoplasm (MPN) in 40, acute leukemia in 21 and T-cell cutaneous lymphoma in 5. Thirty-five patients (53%) had completed 5-year follow-up. The 5-year survival for the MPN, acute myelogenous leukemia (AML), acute lymphocytic leukemia, and lymphoma groups are 62.7, 14.9%, 40.0%, and 100%, respectively. Too few patients have been treated with ruxolitinib to draw conclusions regarding its effect on survival while the 5-year survival for MPN patients with or without HSCT was 80.2% (40.3%-94.8%) versus 51.5% (22.3%-74.6%), respectively. The T-cell cutaneous lymphoma patients have all survived at least 7 years. CONCLUSION: This rare condition may be increasingly detected with wider use of genomics. Ruxolitinib can yield hematologic and molecular remissions. However, HSCT is, at this time, the only potentially curative treatment. Useful prognostic markers are needed to determine appropriate timing for HSCT in patients with MPN. Patients presenting with acute leukemia have a poor prognosis.
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Leucemia , Linfoma , Trastornos Mieloproliferativos , Femenino , Humanos , Janus Quinasa 2/genética , Leucemia/patología , Masculino , Persona de Mediana Edad , Trastornos Mieloproliferativos/diagnóstico , Trastornos Mieloproliferativos/genética , Trastornos Mieloproliferativos/terapia , Proteínas de Fusión OncogénicaRESUMEN
Tumor-infiltrating neoantigen-reactive T cells can mediate regression of metastatic gastrointestinal cancers yet remain poorly characterized. We performed immunological screening against personalized neoantigens in combination with single-cell RNA sequencing on tumor-infiltrating lymphocytes from bile duct and pancreatic cancer patients to characterize the transcriptomic landscape of neoantigen-reactive T cells. We found that most neoantigen-reactive CD8+ T cells displayed an exhausted state with significant CXCL13 and GZMA co-expression compared with non-neoantigen-reactive bystander cells. Most neoantigen-reactive CD4+ T cells from a patient with bile duct cancer also exhibited an exhausted phenotype but with overexpression of HOPX or ADGRG1 while lacking IL7R expression. Thus, neoantigen-reactive T cells infiltrating gastrointestinal cancers harbor distinct transcriptomic signatures, which may provide new opportunities for harnessing these cells for therapy.
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Linfocitos T CD8-positivos , Neoplasias Gastrointestinales , Antígenos de Neoplasias , Neoplasias Gastrointestinales/genética , Humanos , Linfocitos Infiltrantes de Tumor , TranscriptomaRESUMEN
Cancer heterogeneity is a result of genetic mutations within the cancer cells. Their proliferation is not only driven by autocrine functions but also under the influence of cancer microenvironment, which consists of normal stromal cells such as infiltrating immune cells, cancer-associated fibroblasts, endothelial cells, pericytes, vascular and lymphatic channels. The relationship between cancer cells and cancer microenvironment is a critical one and we are just on the verge to understand it on a molecular level. Cancer microenvironment may serve as a selective force to modulate cancer cells to allow them to evolve into more aggressive clones with ability to invade the lymphatic or vascular channels to spread to regional lymph nodes and distant sites. It is important to understand these steps of cancer evolution within the cancer microenvironment towards invasion so that therapeutic strategies can be developed to control or stop these processes.
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Neoplasias , Microambiente Tumoral , Células Endoteliales , Genómica , Humanos , Ganglios Linfáticos/patología , Neoplasias/irrigación sanguínea , Microambiente Tumoral/genéticaRESUMEN
Improved understanding of tumor immunology has enabled the development of therapies that harness the immune system and prevent immune escape. Numerous clinical trials and real-world experience has provided evidence of the potential for long-term survival with immunotherapy in various types of malignancy. Recurring observations with immuno-oncology agents include their potential for clinical application across a broad patient population with different tumor types, conventional and unconventional response patterns, durable responses, and immune-related adverse events. Despite the substantial achievements to date, a significant proportion of patients still fail to benefit from current immunotherapy options, and ongoing research is focused on transforming non-responders to responders through the development of novel treatments, new strategies to combination therapy, adjuvant and neoadjuvant approaches, and the identification of biomarkers of response. These topics were the focus of the virtual Immunotherapy Bridge (December 2nd-3rd, 2020), organized by the Fondazione Melanoma Onlus, Naples, Italy, in collaboration with the Society for Immunotherapy of Cancer and are summarised in this report.
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Biomarcadores de Tumor , Melanoma , Humanos , Inmunoterapia , Italia , Recurrencia Local de NeoplasiaRESUMEN
BACKGROUND: Checkpoint inhibitors targeting programmed death receptor-1 (PD-1) have been tested in the neoadjuvant setting for the treatment of locoregionally advanced head and neck squamous cell carcinoma (HNSCC); however, response rates are modest. We hypothesized that adding stereotactic body radiation therapy (SBRT) to anti-PD-1 would be safe prior to definitive surgical resection and would enhance pathological response compared with historical cohorts of patients with locoregionally advanced HNSCC treated with checkpoint inhibitor alone. METHODS: The Neoadjuvant Immuno-Radiotherapy Trial was an investigator-initiated single institution phase Ib clinical trial that enrolled patients with previously untreated locally advanced HPV-positive and HPV-negative HNSCC between 2018 and 2019. Eligible patients were treated with neoadjuvant SBRT at a total dose of either 40 Gy in 5 fractions or 24 Gy in 3 fractions, delivered in a 1-week timespan, with or without nivolumab, prior to definitive surgical resection. Patients were then planned for treatment with adjuvant nivolumab for 3 months. The primary safety endpoint was unplanned delay in surgery considered to be at least possibly related to neoadjuvant treatment. The primary efficacy endpoints included pathological complete response (pCR), major pathological response (mPR), and the rate of clinical to pathological downstaging after neoadjuvant treatment. RESULTS: Twenty-one patients underwent neoadjuvant treatment, which was well tolerated and did not delay surgery, thus meeting the primary endpoint. Tissue responses were characterized by robust inflammatory infiltrates in the regression bed, plasma cells and cholesterol clefts. Among the entire study group, the mPR and pCR rate was 86% and 67%, respectively. Clinical to pathological downstaging occurred in 90% of the patients treated. CONCLUSION: These data demonstrate that radiation delivered only to the gross tumor volume combined with immunotherapy was safe, resulted in a high rate of mPR and should be further evaluated as a locally focused neoadjuvant therapy for patients with head and neck cancer. TRIAL REGISTRATION NUMBER: This study is registered with clinicaltrials.gov (NCT03247712) and is active, but closed to patient accrual.
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Neoplasias de Cabeza y Cuello/terapia , Inhibidores de Puntos de Control Inmunológico/uso terapéutico , Inmunoterapia , Terapia Neoadyuvante , Nivolumab/uso terapéutico , Radiocirugia , Carcinoma de Células Escamosas de Cabeza y Cuello/terapia , Anciano , Fraccionamiento de la Dosis de Radiación , Femenino , Neoplasias de Cabeza y Cuello/inmunología , Neoplasias de Cabeza y Cuello/patología , Humanos , Inhibidores de Puntos de Control Inmunológico/efectos adversos , Inmunoterapia/efectos adversos , Masculino , Persona de Mediana Edad , Terapia Neoadyuvante/efectos adversos , Estadificación de Neoplasias , Nivolumab/efectos adversos , Oregon , Receptor de Muerte Celular Programada 1/antagonistas & inhibidores , Receptor de Muerte Celular Programada 1/inmunología , Radiocirugia/efectos adversos , Radioterapia Adyuvante , Carcinoma de Células Escamosas de Cabeza y Cuello/inmunología , Carcinoma de Células Escamosas de Cabeza y Cuello/patología , Factores de Tiempo , Resultado del TratamientoRESUMEN
Pancreatic ductal adenocarcinoma (PDAC) has traditionally been thought of as an immunologically quiescent tumor type presumably because of a relatively low tumor mutational burden (TMB) and poor responses to checkpoint blockade therapy. However, many PDAC tumors exhibit T cell inflamed phenotypes. The presence of tertiary lymphoid structures (TLS) has recently been shown to be predictive of checkpoint blockade response in melanomas and sarcomas, and are prognostic for survival in PDAC. In order to more comprehensively understand tumor immunity in PDAC patients with TLS, we performed RNA-seq, single and multiplex IHC, flow cytometry and predictive genomic analysis on treatment naïve, PDAC surgical specimens. Forty-six percent of tumors contained distinct T and B cell aggregates reflective of "early-stage TLS" (ES-TLS), which correlated with longer overall and progression-free survival. These tumors had greater CD8+ T cell infiltration but were not defined by previously published TLS gene-expression signatures. ES-TLS+ tumors were enriched for IgG1 class-switched memory B cells and memory CD4+ T cells, suggesting durable immunological memory persisted in these patients. We also observed the presence of active germinal centers (mature-TLS) in 31% of tumors with lymphocyte clusters, whose patients had long-term survival (median 56 months). M-TLS-positive tumors had equivalent overall T cell infiltration to ES-TLS, but were enriched for activated CD4+ memory cells, naive B cells and NK cells. Finally, using a TCGA-PDAC dataset, ES-TLS+ tumors harbored a decreased TMB, but M-TLS with germinal centers expressed significantly more MHCI-restricted neoantigens as determined by an in silico neoantigen prediction method. Interestingly, M-TLS+ tumors also had evidence of increased rates of B cell somatic hypermutation, suggesting that germinal centers form in the presence of high-quality tumor neoantigens leading to increased humoral immunity that confers improved survival for PDAC patients. AbbreviationsTLS: tertiary lymphoid structures; GC: germinal center(s); PDAC: pancreatic ductal adenocarcinoma; RNA-seq: RNA sequencing; BCRseq: B cell receptor sequencing; HEV: high endothelial venule; PNAd: peripheral node addressin; TMB: tumor mutational burden; TCGA: the cancer genome atlas; PAAD: pancreatic adenocarcinoma; FFPE: formalin fixed paraffin embedded; TIME: tumor immune microenvironment.