Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related death in the world. Immunological analysis of the tumor microenvironment (immunoscore) shows great promise for improved ...prognosis and prediction of response to immunotherapy. However, the exact immune cell composition in NSCLC remains unclear. Here, we used flow cytometry to characterize the immune infiltrate in NSCLC tumors, non-cancerous lung tissue, regional lymph node, and blood. The cellular identity of >95% of all CD45
immune cells was determined. Thirteen distinct immune cell types were identified in NSCLC tumors. T cells dominated the lung cancer landscape (on average 47% of all CD45
immune cells). CD4
T cells were the most abundant T cell population (26%), closely followed by CD8
T cells (22%). Double negative CD4
CD8
T cells represented a small fraction (1.4%). CD19
B cells were the second most common immune cell type in NSCLC tumors (16%), and four different B cell sub-populations were identified. Macrophages and natural killer (NK) cells composed 4.7 and 4.5% of the immune cell infiltrate, respectively. Three types of dendritic cells (DCs) were identified (plasmacytoid DCs, CD1c
DCs, and CD141
DCs) which together represented 2.1% of all immune cells. Among granulocytes, neutrophils were frequent (8.6%) with a high patient-to-patient variability, while mast cells (1.4%), basophils (0.4%), and eosinophils (0.3%) were less common. Across the cohort of patients, only B cells showed a significantly higher representation in NSCLC tumors compared to the distal lung. In contrast, the percentages of macrophages and NK cells were lower in tumors than in non-cancerous lung tissue. Furthermore, the fraction of macrophages with high HLA-DR expression levels was higher in NSCLC tumors relative to distal lung tissue. To make the method readily accessible, antibody panels and flow cytometry gating strategy used to identify the various immune cells are described in detail. This work should represent a useful resource for the immunomonitoring of patients with NSCLC.
We investigated how the prognosis for Norwegian patients with stage IV, adenocarcinoma (NSCLC) has developed during the last decade, to observe if increased survival coincides with the introduction ...of immunotherapy at a population level.
Incidence data from the Cancer Registry of Norway are virtually complete and includes information about histological subtypes and biomarkers. The data was used to analyze median and relative survival for females and males diagnosed with stage IV NSCLC, divided by histological subgroups and age-groups.
During 2010 - 2020, 14472 patients were diagnosed with lung cancer in stage IV, in Norway. Among them 6351 patients (43%) were classified with adenocarcinoma. The median survival has increased for both sexes, but the largest increase is seen in females. From 2010 to 2020, median survival for females in the 0-69 group increased from 6.7 months to 12 months and from 3.7 months to 10 months for the 70+ age group. For the equivalent male age groups, we see an increase from 6.1 months to 7.7 months for the 0-69 group, and an increase from 3.8 months to 4.5 months for the 70+ group. When excluding patients with EGFR/ALK mutations from the survival analysis, the groups continue to display an increased survival from 2010 to 2020, although modest in the male 70+ group. The 1-year relative survival (RS) has increased for both sexes, from 32.4% to 51.2 in females and 25.4% to 44.5% in males. When EGFR/ALK positive patients were excluded from the analysis 1-year RS in females rose from 32.4% to 47.4% and for males from 25.4% to 41.8%.
A real-world patient population of stage IV, NSCLC adenocarcinoma have had a clinically meaningful increase in both median and relative survival from 2010 - 2020. The steepest survival increase has taken place after 2016, the time point where immunotherapy was implemented as a treatment option for the stage IV, adenocarcinoma population not harboring targetable mutations (EGFR/ALK).
Cancer immunotherapy may alter tumor biology such that treatment effects can extend beyond radiographic progression. In the randomized, phase III OAK study of atezolizumab (anti–programmed ...death-ligand 1) versus docetaxel in advanced NSCLC, overall survival (OS) benefit with atezolizumab was observed in the overall patient population, without improvement in objective response rate (ORR) or progression-free survival (PFS). We examine the benefit-risk of atezolizumab treatment beyond progression (TBP).
Eight hundred fifty patients included in the OAK primary efficacy analysis were evaluated. Atezolizumab was continued until loss of clinical benefit. Docetaxel was administered until Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST v1.1) disease progression (PD)/unacceptable toxicity; no crossover to atezolizumab was allowed. ORR, PFS, post-PD OS, target lesion change, and safety were evaluated.
In atezolizumab-arm patients, ORR was 16% versus 14% and median PFS was 4.2 versus 2.8 months per immune-modified RECIST versus RECIST v1.1. The median post-PD OS was 12.7 months (95% confidence interval CI: 9.3–14.9) in 168 atezolizumab-arm patients continuing TBP, 8.8 months (95% CI: 6.0–12.1) in 94 patients switching to nonprotocol therapy, and 2.2 months (95% CI: 1.9–3.4) in 70 patients receiving no further therapy. Of the atezolizumab TBP patients, 7% achieved a post-progression response in target lesions and 49% had stable target lesions. Atezolizumab TBP was not associated with increased safety risks.
Within the limitations of this retrospective analysis, the post-PD efficacy and safety data from OAK are consistent with a positive benefit-risk profile of atezolizumab TBP in patients performing well clinically at the time of PD.
Targeted therapy for patients with HER2‐positive (HER2+) breast cancer has improved overall survival, but many patients still suffer relapse and death from the disease. Intratumor heterogeneity of ...both estrogen receptor (ER) and HER2 expression has been proposed to play a key role in treatment failure, but little work has been done to comprehensively study this heterogeneity at the single‐cell level. In this study, we explored the clinical impact of intratumor heterogeneity of ER protein expression, HER2 protein expression, and HER2 gene copy number alterations. Using combined immunofluorescence and in situ hybridization on tissue sections followed by a validated computational approach, we analyzed more than 13 000 single tumor cells across 37 HER2+ breast tumors. The samples were taken both before and after neoadjuvant chemotherapy plus HER2‐targeted treatment, enabling us to study tumor evolution as well. We found that intratumor heterogeneity for HER2 copy number varied substantially between patient samples. Highly heterogeneous tumors were associated with significantly shorter disease‐free survival and fewer long‐term survivors. Patients for which HER2 characteristics did not change during treatment had a significantly worse outcome. This work shows the impact of intratumor heterogeneity in molecular diagnostics for treatment selection in HER2+ breast cancer patients and the power of computational scoring methods to evaluate in situ molecular markers in tissue biopsies.
A subset of breast carcinomas exhibits substantial heterogeneity with regard to HER2 protein expression, HER2 gene copy number alteration, and estrogen receptor protein expression both between cases but also within cases (inter‐ and intratumor heterogeneity). Highly heterogeneous tumors were associated with significantly shorter disease‐free survival and fewer long‐term survivors. Addressing cell‐to‐cell variation may be of importance in diagnostic settings.
Lung cancer (LC) prognosis is closely linked to the stage of disease when diagnosed. We investigated the biomarker potential of serum RNAs for the early detection of LC in smokers at different ...prediagnostic time intervals and histological subtypes. In total, 1061 samples from 925 individuals were analyzed. RNA sequencing with an average of 18 million reads per sample was performed. We generated machine learning models using normalized serum RNA levels and found that smokers later diagnosed with LC in 10 years can be robustly separated from healthy controls regardless of histology with an average area under the ROC curve (AUC) of 0.76 (95% CI, 0.68-0.83). Furthermore, the strongest models that took both time to diagnosis and histology into account successfully predicted non-small cell LC (NSCLC) between 6 and 8 years, with an AUC of 0.82 (95% CI, 0.76-0.88), and SCLC between 2 and 5 years, with an AUC of 0.89 (95% CI, 0.77-1.0), before diagnosis. The most important separators were microRNAs, miscellaneous RNAs, isomiRs, and tRNA-derived fragments. We have shown that LC can be detected years before diagnosis and manifestation of disease symptoms independently of histological subtype. However, the highest AUCs were achieved for specific subtypes and time intervals before diagnosis. The collection of models may therefore also predict the severity of cancer development and its histology. Our study demonstrates that serum RNAs can be promising prediagnostic biomarkers in an LC screening setting, from early detection to risk assessment.
The purpose of this study was to assess the clinical value of a deep learning (DL) model for automatic detection and segmentation of brain metastases, in which a neural network is trained on four ...distinct MRI sequences using an input-level dropout layer, thus simulating the scenario of missing MRI sequences by training on the full set and all possible subsets of the input data. This retrospective, multicenter study, evaluated 165 patients with brain metastases. The proposed input-level dropout (ILD) model was trained on multisequence MRI from 100 patients and validated/tested on 10/55 patients, in which the test set was missing one of the four MRI sequences used for training. The segmentation results were compared with the performance of a state-of-the-art DeepLab V3 model. The MR sequences in the training set included pre-gadolinium and post-gadolinium (Gd) T1-weighted 3D fast spin echo, post-Gd T1-weighted inversion recovery (IR) prepped fast spoiled gradient echo, and 3D fluid attenuated inversion recovery (FLAIR), whereas the test set did not include the IR prepped image-series. The ground truth segmentations were established by experienced neuroradiologists. The results were evaluated using precision, recall, Intersection over union (IoU)-score and Dice score, and receiver operating characteristics (ROC) curve statistics, while the Wilcoxon rank sum test was used to compare the performance of the two neural networks. The area under the ROC curve (AUC), averaged across all test cases, was 0.989 ± 0.029 for the ILD-model and 0.989 ± 0.023 for the DeepLab V3 model (p = 0.62). The ILD-model showed a significantly higher Dice score (0.795 ± 0.104 vs. 0.774 ± 0.104, p = 0.017), and IoU-score (0.561 ± 0.225 vs. 0.492 ± 0.186, p < 0.001) compared to the DeepLab V3 model, and a significantly lower average false positive rate of 3.6/patient vs. 7.0/patient (p < 0.001) using a 10 mm
lesion-size limit. The ILD-model, trained on all possible combinations of four MRI sequences, may facilitate accurate detection and segmentation of brain metastases on a multicenter basis, even when the test cohort is missing input MRI sequences.
The introduction of consolidation immunotherapy after chemoradiotherapy has improved outcome for patients with locally advanced non-small cell lung cancer. However, not all patients receive this ...treatment. This study identifies factors associated with failure to start durvalumab as consolidation therapy with the aim of optimizing treatment, supportive care and prehabilitation to ensure that more patients complete the planned treatment.
Patients from two clinical trials and a named patient use program, were included in this study. All patients received platinum-doublet chemotherapy concomitant with radiotherapy to a total dose of 60-66 gray. Patient characteristics, cancer treatment, toxicity, performance status and laboratory data before and after chemoradiotherapy were recorded and patients who never started durvalumab were compared with those who did.
A total of 101 patients were included, of which 83 started treatments with durvalumab after chemoradiotherapy. The 18 patients who did not start durvalumab had significantly higher lactate dehydrogenase at baseline and a worse performance status, cumulative toxicity and higher c-reactive protein after completed chemoradiotherapy. Data also suggest that pre-treatment diabetes and reduced hemoglobin and/or diffusion capacity of the lungs for carbon monoxide contribute to the risk of treatment abruption.
Treatment plan disruption rate was 18%. Systemic inflammation and performance status were associated with failure to receive durvalumab after chemoradiation. Further studies are needed to confirm findings and prospective trials should investigate whether prehabilitation and supportive treatment could help more patients finishing the planned treatment.
clinicaltrials.gov, identifier NCT03798535; NCT04392505.
We use an integrated approach to understand breast cancer heterogeneity by modeling mRNA, copy number alterations, microRNAs, and methylation in a pathway context utilizing the pathway recognition ...algorithm using data integration on genomic models (PARADIGM). We demonstrate that combining mRNA expression and DNA copy number classified the patients in groups that provide the best predictive value with respect to prognosis and identified key molecular and stromal signatures. A chronic inflammatory signature, which promotes the development and/or progression of various epithelial tumors, is uniformly present in all breast cancers. We further demonstrate that within the adaptive immune lineage, the strongest predictor of good outcome is the acquisition of a gene signature that favors a high T-helper 1 (Th1)/cytotoxic T-lymphocyte response at the expense of Th2-driven humoral immunity. Patients who have breast cancer with a basal HER2-negative molecular profile (PDGM2) are characterized by high expression of protumorigenic Th2/humoral-related genes (24–38%) and a low Th1/Th2 ratio. The luminal molecular subtypes are again differentiated by low or high FOXM1 and ERBB4 signaling. We show that the interleukin signaling profiles observed in invasive cancers are absent or weakly expressed in healthy tissue but already prominent in ductal carcinoma in situ, together with ECM and cell-cell adhesion regulating pathways. The most prominent difference between low and high mammographic density in healthy breast tissue by PARADIGM was that of STAT4 signaling. In conclusion, by means of a pathway-based modeling methodology (PARADIGM) integrating different layers of molecular data from whole-tumor samples, we demonstrate that we can stratify immune signatures that predict patient survival.
•Risk of grade 3 lymphopenia increased with RT dose to the soft tissue and trabecular bone.•High baseline CRP/Albumin was negatively associated with overall survival.•Risk of lymphopenia may decrease ...by limiting irradiation field in palliative RT.
Lymphopenia during radiotherapy (RT) may have an adverse effect on treatment outcome. The aim of this study is to investigate associations between lymphopenia and RT parameters in patients with advanced lung cancer. Moreover, to investigate the prognostic role of lymphopenia, blood protein levels, and treatment and patient-related factors.
Sixty-two advanced stage non-small cell lung cancer (NSCLC) patients were retrospectively analyzed. Blood counts were available prior to, during, and after RT (3Gyx10). For each patient, a thoracic volume of interest (VOI) –including thoracic soft tissue and trabecular bone– was obtained by applying a CT window of −500 to 1200 HU in the planning CT. Dose parameters from thoracic VOI and other regions including lungs and vertebrae were calculated. Association between risk of lymphopenia ≥ G3 (lymphocytes at nadir according to CTCAE v4.0) and therapeutic parameters was investigated using Logistic regression. Relationships between overall survival (OS) and RT dose parameters, baseline blood counts and protein levels, and clinical factors were evaluated using Log-rank and Cox models.
Mean thoracic RT dose (odds ratio OR 1.67; p = 0.04), baseline lymphocytes (OR 0.65; p = 0.01), and corticosteroids use (OR 6.07; p = 0.02) were significantly associated with increased risk of lymphopenia ≥ G3 in multivariable analysis. Worse OS was associated with high mean thoracic RT dose, high CRP/Albumin, large tumor volume and corticosteroids use (p < 0.05, univariate analysis), but not with lymphopenia ≥ G3. CRP/Albumin ratio > 0.12 (hazard ratio HR 2.28, p = 0.03) and corticosteroid use (HR 2.52, p = 0.01) were independently associated with worse OS.
High thoracic RT dose gave a higher risk of lymphopenia ≥ G3; hence limiting dose volume to the thorax may be valuable in preventing severe lymphopenia for patients receiving palliative fractionated RT. Still, lymphopenia ≥ G3 was not associated with worse OS. however, high baseline CRP/Albumin was associated with poorer OS and may carry important information as a prognostic factor of OS in advanced NSCLC receiving palliative RT.
It has been hypothesized based on accumulated data that a class of small noncoding RNAs, termed microRNAs, are key factors in intercellular communication. Here, microRNAs present in interstitial ...breast tumor fluids have been analyzed to identify relevant markers for a diagnosis of breast cancer and to elucidate the cross‐talk that exists among cells in a tumor microenvironment. Matched tumor interstitial fluid samples (TIF, n = 60), normal interstitial fluid samples (NIF, n = 51), corresponding tumor tissue specimens (n = 54), and serum samples (n = 27) were collected from patients with breast cancer, and detectable microRNAs were analyzed and compared. In addition, serum data from 32 patients with breast cancer and 22 healthy controls were obtained for a validation study. To identify potential serum biomarkers of breast cancer, first the microRNA profiles of TIF and NIF samples were compared. A total of 266 microRNAs were present at higher level in the TIF samples as compared to normal counterparts. Sixty‐one of these microRNAs were present in > 75% of the serum samples and were subsequently tested in a validation set. Seven of the 61 microRNAs were associated with poor survival, while 23 were associated with the presence of immune cells and adipocytes. To our knowledge, these data demonstrate for the first time that profiling of microRNAs in TIF can identify novel biomarkers for the prognostic classification and detection of breast cancer. In addition, the present findings demonstrate that microRNAs may represent the cross‐talk that occurs between tumor cells and their surrounding stroma.
Tumor cells, tumor interstitial fluid (TIF), normal interstitial fluid, and serum all have a distinct microRNA profile. Specific microRNAs detected in TIF are associated with the presence of tumor‐infiltrating lymphocytes and adipocytes, reflecting the cross‐talk between the cells in stroma. Only a portion of these microRNAs are detected in serum, but are attractive candidates for biomarkers of breast cancer.
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