43 research outputs found

    A phase I study of afatinib combined with paclitaxel and bevacizumab in patients with advanced solid tumors

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    Purpose The combination of afatinib, an irreversible ErbB family blocker, with paclitaxel and bevacizumab was assessed in patients with advanced solid tumors.Methods This phase I study used a 3 + 3 design to determine the maximum tolerated dose (MTD) of afatinib combined with paclitaxel and bevacizumab. Safety, pharmacokinetics, and anti-tumor activity were also assessed. The starting dose was oral afatinib 40 mg once daily plus intravenous paclitaxel (fixed dose 80 mg/m2, Days 1, 8, and 15 of a 4-week cycle) and intravenous bevacizumab 5 mg/kg every 2 weeks.Results Twenty-nine patients were enroled. The afatinib dose was de-escalated to 30 mg and then 20 mg after 2/6 and 2/5 evaluable patients developed dose-limiting toxicities at 40 and 30 mg, respectively, when combined with paclitaxel and bevacizumab 5 mg/kg. The bevacizumab dose was subsequently escalated to 10 mg/kg, and MTD was defined as afatinib 20 mg plus paclitaxel 80 mg/m2 and bevacizumab 10 mg/kg. Frequent (any grade) treatment-related adverse events (AEs) included diarrhea (83%), rash/acne (83%), fatigue (79%), mucosal inflammation (59%), and nausea (59%). Based on overall safety, bevacizumab was amended to 7.5 mg/kg for the recommended phase II dose. Pharmacokinetic analyses suggested no relevant drug-drug interactions. Three (10%) confirmed partial responses were observed; 15 (52%) patients had stable disease.Conclusions The recommended phase II dose schedule was afatinib 20 mg/day with paclitaxel 80 mg/m2 (Days 1, 8, and 15 every 4 weeks) and bevacizumab 7.5 mg/kg every 2 weeks. At this dose schedule, AEs were manageable, and anti-tumor activity was observed

    Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes

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    BackgroundIntracellular communication within the tumour is complex and extracellular vesicles (EVs) have been identified as major contributing factors for the cell-to-cell communication in the local and distant tumour environments. Here, we examine the differential effects of breast cancer (BC) subtype-specific patient serum and cell-line derived EVs in the regulation of T cell mediated immune responses. MethodsUltracentrifugation was used to isolate EVs from sera of 63 BC patients, 15 healthy volunteers and 4 human breast cancer cell lines. Longitudinal blood draws for EV isolation for patients on neoadjuvant chemotherapy was also performed. Characterization of EVs was performed by Nanoparticle Tracking Analysis (NTA), transmission electron microscopy (TEM) and immunoblotting. CD63 staining was performed on a tissue microarray of 218 BC patients. In-house bioinformatics algorithms were utilized for the computation of EV associated expression scores within The Cancer Genome Atlas (TCGA) and correlated with tumour infiltrating lymphocyte (TIL) scores. In vitro stimulation of PBMCs with EVs from serum and cell-line derived EVs was performed and changes in the immune phenotypes characterized by flow cytometry. Cytokine profiles were assessed using a 105-plex immunoassay or IL10 ELISA. ResultsPatients with triple negative breast cancers (TNBCs) exhibited the lowest number of EVs in the sera; whilst the highest was detected in ER+HER2+ cancers; reflected also in the higher level of CD63+ vesicles found within the ER+HER2+ local tumour microenvironment. Transcriptomic analysis of the TCGA data identified that samples assigned with lower EV scores had significantly higher abundance of CD4+ memory activated T cells, T follicular cells and CD8 T cells, plasma, and memory B cells; whilst samples with high EV scores were more enriched for anti-inflammatory M2 macrophages and mast cells. A negative correlation between EV expression scores and stromal TIL counts was also observed. In vitro experiments confirmed that circulating EVs within breast cancer subtypes have functionally differing immunomodulatory capabilities, with EVs from patients with the most aggressive breast cancer subtype (TNBCs) demonstrating the most immune-suppressive phenotype (decreased CD3+HLA-DR+ but increased CD3+PD-L1 T cells, increased CD4+CD127-CD25hi T regulatory cells with associated increase in IL10 cytokine production). In depth assessment of the cytokine modulation triggered by the serum/cell line derived exosomes confirmed differential inflammatory cytokine profiles across differing breast cancer subtypes. Studies using the MDA-231 TNBC breast cancer cell-line derived EVs provided further support that TNBC EVs induced the most immunosuppressive response within PBMCs.DiscussionOur study supports further investigations into how tumour derived EVs are a mechanism that cancers can exploit to promote immune suppression; and breast cancer subtypes produce EVs with differing immunomodulatory capabilities. Understanding the intracellular/extracellular pathways implicated in alteration from active to suppressed immune may provide a promising way forward for restoring immune competence in specific breast cancer patient populations

    Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes

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    Background: Intracellular communication within the tumour is complex and extracellular vesicles (EVs) have been identified as major contributing factors for the cell-to-cell communication in the local and distant tumour environments. Here, we examine the differential effects of breast cancer (BC) subtype-specific patient serum and cell-line derived EVs in the regulation of T cell mediated immune responses. Methods: Ultracentrifugation was used to isolate EVs from sera of 63 BC patients, 15 healthy volunteers and 4 human breast cancer cell lines. Longitudinal blood draws for EV isolation for patients on neoadjuvant chemotherapy was also performed. Characterization of EVs was performed by Nanoparticle Tracking Analysis (NTA), transmission electron microscopy (TEM) and immunoblotting. CD63 staining was performed on a tissue microarray of 218 BC patients. In-house bioinformatics algorithms were utilized for the computation of EV associated expression scores within The Cancer Genome Atlas (TCGA) and correlated with tumour infiltrating lymphocyte (TIL) scores. In vitro stimulation of PBMCs with EVs from serum and cell-line derived EVs was performed and changes in the immune phenotypes characterized by flow cytometry. Cytokine profiles were assessed using a 105-plex immunoassay or IL10 ELISA. Results: Patients with triple negative breast cancers (TNBCs) exhibited the lowest number of EVs in the sera; whilst the highest was detected in ER+HER2+ cancers; reflected also in the higher level of CD63+ vesicles found within the ER+HER2+ local tumour microenvironment. Transcriptomic analysis of the TCGA data identified that samples assigned with lower EV scores had significantly higher abundance of CD4+ memory activated T cells, T follicular cells and CD8 T cells, plasma, and memory B cells; whilst samples with high EV scores were more enriched for anti-inflammatory M2 macrophages and mast cells. A negative correlation between EV expression scores and stromal TIL counts was also observed. In vitro experiments confirmed that circulating EVs within breast cancer subtypes have functionally differing immunomodulatory capabilities, with EVs from patients with the most aggressive breast cancer subtype (TNBCs) demonstrating the most immune-suppressive phenotype (decreased CD3+HLA-DR+ but increased CD3+PD-L1 T cells, increased CD4+CD127-CD25hi T regulatory cells with associated increase in IL10 cytokine production). In depth assessment of the cytokine modulation triggered by the serum/cell line derived exosomes confirmed differential inflammatory cytokine profiles across differing breast cancer subtypes. Studies using the MDA-231 TNBC breast cancer cell-line derived EVs provided further support that TNBC EVs induced the most immunosuppressive response within PBMCs. Discussion: Our study supports further investigations into how tumour derived EVs are a mechanism that cancers can exploit to promote immune suppression; and breast cancer subtypes produce EVs with differing immunomodulatory capabilities. Understanding the intracellular/extracellular pathways implicated in alteration from active to suppressed immune state may provide a promising way forward for restoring immune competence in specific breast cancer patient populations

    COVID-19 Risk Factors for Cancer Patients: A First Report with Comparator Data from COVID-19 Negative Cancer Patients

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    none32siSimple SummaryThe COVID-19 pandemic has had a detrimental impact on cancer patients globally. Whilst there are several studies looking at the potential risk factors for COVID-19 disease and related death, most of these include non-cancerous patients as the COVID-19 negative comparator group, meaning it is difficult to draw hard conclusions as to the implications for cancer patients. In our study, we utilized data from over 2000 cancer patients from a large tertiary Cancer Centre in London. In summary, our study found that patients who are male, of Black or Asian ethnicity, or with a hematological malignancy are at an increased risk of COVID-19. The use of cancer patients as the COVID-19 negative comparator group is a major advantage to the study as it means we can better understand the true impact of COVID-19 on cancer patients and identify which factors pose the biggest risk to their likelihood of infection with SARS-CoV2.Very few studies investigating COVID-19 in cancer patients have included cancer patients as controls. We aimed to identify factors associated with the risk of testing positive for SARS CoV2 infection in a cohort of cancer patients. We analyzed data from all cancer patients swabbed for COVID-19 between 1(st) March and 31(st) July 2020 at Guy's Cancer Centre. We conducted logistic regression analyses to identify which factors were associated with a positive COVID-19 test. Results: Of the 2152 patients tested for COVID-19, 190 (9%) tested positive. Male sex, black ethnicity, and hematological cancer type were positively associated with risk of COVID-19 (OR = 1.85, 95%CI:1.37-2.51; OR = 1.93, 95%CI:1.31-2.84; OR = 2.29, 95%CI:1.45-3.62, respectively) as compared to females, white ethnicity, or solid cancer type, respectively. Male, Asian ethnicity, and hematological cancer type were associated with an increased risk of severe COVID-19 (OR = 3.12, 95%CI:1.58-6.14; OR = 2.97, 95%CI:1.00-8.93; OR = 2.43, 95%CI:1.00-5.90, respectively). This study is one of the first to compare the risk of COVID-19 incidence and severity in cancer patients when including cancer patients as controls. Results from this study have echoed those of previous reports, that patients who are male, of black or Asian ethnicity, or with a hematological malignancy are at an increased risk of COVID-19.openRussell, Beth; Moss, Charlotte L; Palmer, Kieran; Sylva, Rushan; D'Souza, Andrea; Wylie, Harriet; Haire, Anna; Cahill, Fidelma; Steel, Renee; Hoyes, Angela; Wilson, Isabelle; Macneil, Alyson; Shifa, Belul; Monroy-Iglesias, Maria J; Papa, Sophie; Irshad, Sheeba; Ross, Paul; Spicer, James; Kordasti, Shahram; Crawley, Danielle; Zaki, Kamarul; Sita-Lumsden, Ailsa; Josephs, Debra; Enting, Deborah; Swampillai, Angela; Sawyer, Elinor; Fields, Paul; Wrench, David; Rigg, Anne; Sullivan, Richard; Van Hemelrijck, Mieke; Dolly, SaoirseRussell, Beth; Moss, Charlotte L; Palmer, Kieran; Sylva, Rushan; D'Souza, Andrea; Wylie, Harriet; Haire, Anna; Cahill, Fidelma; Steel, Renee; Hoyes, Angela; Wilson, Isabelle; Macneil, Alyson; Shifa, Belul; Monroy-Iglesias, Maria J; Papa, Sophie; Irshad, Sheeba; Ross, Paul; Spicer, James; Kordasti, Shahram; Crawley, Danielle; Zaki, Kamarul; Sita-Lumsden, Ailsa; Josephs, Debra; Enting, Deborah; Swampillai, Angela; Sawyer, Elinor; Fields, Paul; Wrench, David; Rigg, Anne; Sullivan, Richard; Van Hemelrijck, Mieke; Dolly, Saoirs

    RORγt+ innate lymphoid cells promote lymph node metastasis of breast cancers

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    Cancer cells tend to metastasize first to tumor-draining lymph nodes, but the mechanisms mediating cancer cell invasion into the lymphatic vasculature remain little understood. Here, we show that in the human breast tumor microenvironment (TME), the presence of increased numbers of RORγt+ group 3 innate lymphoid cells (ILC3) correlates with an increased likelihood of lymph node metastasis. In a preclinical mouse model of breast cancer, CCL21-mediated recruitment of ILC3 to tumors stimulated the production of the CXCL13 by TME stromal cells, which in turn promoted ILC3–stromal interactions and production of the cancer cell motile factor RANKL. Depleting ILC3 or neutralizing CCL21, CXCL13, or RANKL was sufficient to decrease lymph node metastasis. Our findings establish a role for RORγt+ILC3 in promoting lymphatic metastasis by modulating the local chemokine milieu of cancer cells in the TME

    Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: a report of the international immuno‐oncology biomarker working group

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    The clinical significance of the tumor-immune interaction in breast cancer (BC) has been well established, and tumor-infiltrating lymphocytes (TILs) have emerged as a predictive and prognostic biomarker for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2 negative) breast cancer (TNBC) and HER2-positive breast cancer. How computational assessment of TILs can complement manual TIL-assessment in trial- and daily practices is currently debated and still unclear. Recent efforts to use machine learning (ML) for the automated evaluation of TILs show promising results. We review state-of-the-art approaches and identify pitfalls and challenges by studying the root cause of ML discordances in comparison to manual TILs quantification. We categorize our findings into four main topics; (i) technical slide issues, (ii) ML and image analysis aspects, (iii) data challenges, and (iv) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns, or design choices in the computational implementation. To aid the adoption of ML in TILs assessment, we provide an in-depth discussion of ML and image analysis including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial- and routine clinical management of patients with TNBC
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