ABSTRACT
The liver is the most common site of metastatic disease1. Although this metastatic tropism may reflect the mechanical trapping of circulating tumour cells, liver metastasis is also dependent, at least in part, on the formation of a 'pro-metastatic' niche that supports the spread of tumour cells to the liver2,3. The mechanisms that direct the formation of this niche are poorly understood. Here we show that hepatocytes coordinate myeloid cell accumulation and fibrosis within the liver and, in doing so, increase the susceptibility of the liver to metastatic seeding and outgrowth. During early pancreatic tumorigenesis in mice, hepatocytes show activation of signal transducer and activator of transcription 3 (STAT3) signalling and increased production of serum amyloid A1 and A2 (referred to collectively as SAA). Overexpression of SAA by hepatocytes also occurs in patients with pancreatic and colorectal cancers that have metastasized to the liver, and many patients with locally advanced and metastatic disease show increases in circulating SAA. Activation of STAT3 in hepatocytes and the subsequent production of SAA depend on the release of interleukin 6 (IL-6) into the circulation by non-malignant cells. Genetic ablation or blockade of components of IL-6-STAT3-SAA signalling prevents the establishment of a pro-metastatic niche and inhibits liver metastasis. Our data identify an intercellular network underpinned by hepatocytes that forms the basis of a pro-metastatic niche in the liver, and identify new therapeutic targets.
Subject(s)
Hepatocytes/pathology , Liver Neoplasms/pathology , Liver Neoplasms/secondary , Liver/pathology , Neoplasm Metastasis , Pancreatic Neoplasms/pathology , Tumor Microenvironment , Animals , Carcinoma, Pancreatic Ductal/pathology , Colorectal Neoplasms/pathology , Colorectal Neoplasms/secondary , Female , Interleukin-6/metabolism , Male , Mice , STAT3 Transcription Factor/metabolism , Serum Amyloid A Protein/metabolismABSTRACT
Novel screening techniques for early detection of lung cancer are urgently needed. Profiling circulating tumor cell-free DNA (ctDNA) has emerged as a promising tool for biopsy-free tumor genotyping. However, both the scarcity and short half-life of ctDNA substantially limit the sensitivity and clinical utility of ctDNA detection methodologies. Our discovery that red blood cells (RBCs) sequester mitochondrial DNA opens a new avenue for detecting circulating nucleic acids, as RBCs represent an unrecognized reservoir of circulating nucleic acid. Here, we show that RBCs acquire tumor DNA following coculture with lung cancer cell lines harboring Kirsten rat sarcoma viral oncogene homolog (KRAS) and epidermal growth factor receptor (EGFR) mutations. RBC-bound tumor DNA is detectable in patients with early-stage non-small cell lung cancer (NSCLC) but not in healthy controls by qPCR. Our results collectively uncover a previously unrecognized yet easily accessible reservoir of tumor DNA, offering a promising foundation for future RBC-based tumor diagnostics.NEW & NOTEWORTHY We present a novel method for lung cancer detection by revealing RBCs as a reservoir for tumor DNA, overcoming the limitations of current circulating tumor ctDNA methodologies. By demonstrating that RBCs can capture tumor DNA, including critical mutations found in lung cancer, we provide a promising, biopsy-free avenue for early cancer diagnostics. This discovery opens up exciting possibilities for developing RBC-based diagnostic tools, significantly enhancing the sensitivity and clinical utility of noninvasive cancer detection.
Subject(s)
Carcinoma, Non-Small-Cell Lung , Circulating Tumor DNA , Erythrocytes , Lung Neoplasms , Humans , Lung Neoplasms/genetics , Lung Neoplasms/blood , Lung Neoplasms/pathology , Lung Neoplasms/diagnosis , Erythrocytes/metabolism , Circulating Tumor DNA/genetics , Circulating Tumor DNA/blood , Carcinoma, Non-Small-Cell Lung/genetics , Carcinoma, Non-Small-Cell Lung/blood , Carcinoma, Non-Small-Cell Lung/pathology , Carcinoma, Non-Small-Cell Lung/diagnosis , Mutation , Cell Line, Tumor , ErbB Receptors/genetics , ErbB Receptors/metabolism , DNA, Mitochondrial/genetics , DNA, Mitochondrial/blood , Proto-Oncogene Proteins p21(ras)/genetics , Male , Female , Biomarkers, Tumor/genetics , Biomarkers, Tumor/blood , DNA, Neoplasm/blood , DNA, Neoplasm/geneticsABSTRACT
The therapeutic landscape for patients with advanced malignancies has changed dramatically over the last twenty years. The growing number of targeted therapies and immunotherapeutic options available have improved response rates and survival for a subset of patients, however determining which patients will experience clinical benefit from these therapies in order to avoid potential toxicities and reduce healthcare costs remains a clinical challenge. Cell-free circulating tumor DNA (ctDNA) is shed by tumor cells into systemic circulation and is already an integral part of routine clinical practice for the non-invasive tumor genotyping in advanced non-small cell lung cancer as well as other malignancies. The short half-life of ctDNA offers a unique opportunity to utilize early on-treatment changes in ctDNA for real-time assessment of therapeutic response and outcome, termed molecular response. Here, we provide a summary and review of the use of molecular response for the prediction of outcomes in patients with advanced cancer, including the current state of science, its application in clinic, and next steps for the development of this predictive tool.
Subject(s)
Carcinoma, Non-Small-Cell Lung , Circulating Tumor DNA , Lung Neoplasms , Humans , Circulating Tumor DNA/genetics , Carcinoma, Non-Small-Cell Lung/drug therapy , Carcinoma, Non-Small-Cell Lung/genetics , Lung Neoplasms/drug therapy , Biomarkers, Tumor/genetics , MutationABSTRACT
Plasma cell-free DNA (cfDNA) genotyping is an alternative to tissue genotyping, particularly when tissue specimens are insufficient or unavailable, and provides critical information that can be used to guide treatment decisions in managing patients with non-small cell lung cancer (NSCLC). In this article, we review the evolution of plasma cfDNA genotyping from an emerging concept, through development of analytical methods, to its clinical applications as a standard-of-care tool in NSCLC. The number of driver or resistance mutations recommended for testing in NSCLC continues to increase. Because of the expanding list of therapeutically relevant variants, comprehensive testing to investigate larger regions of multiple genes in a single run is often preferable and saves on time and cost, compared with performing serial single-gene assays. Recent advances in nucleic acid next-generation sequencing have led to a rapid expansion in cfDNA genotyping technologies. Analytic assays that have received regulatory approval are now routinely used as diagnostic companions in the setting of metastatic NSCLC. As the demand for plasma-based technologies increases, more regulatory approvals of cfDNA genotyping assays are expected in the future. Plasma cfDNA genotyping is currently aiding oncologists in the delivery of personalized care by facilitating matching of patients with targeted therapy and monitoring emergence of resistance to therapy in NSCLC. Further advances currently underway to increase assay sensitivity and specificity will potentially expand the use of plasma cfDNA genotyping in early cancer detection, monitoring response to therapy, detection of minimal residual disease, and measurement of tumor mutational burden in NSCLC. IMPLICATIONS FOR PRACTICE: Plasma cell-free DNA (cfDNA) genotyping offers an alternative to tissue genotyping, particularly when tissue specimens are insufficient or unavailable. Advances in cfDNA genotyping technologies have led to analytic assays that are now routinely used to aid oncologists in the delivery of personalized care by facilitating matching of patients with targeted therapy and monitoring emergence of resistance to therapy. Further advances underway to increase assay sensitivity and specificity will potentially expand the use of plasma cfDNA genotyping in early cancer detection, monitoring response to therapy, detection of minimal residual disease, and evaluation of tumor mutational burden in non-small cell lung cancer.
Subject(s)
Carcinoma, Non-Small-Cell Lung , Cell-Free Nucleic Acids , Lung Neoplasms , Biomarkers, Tumor/genetics , Carcinoma, Non-Small-Cell Lung/genetics , Cell-Free Nucleic Acids/genetics , Genotype , Humans , Lung Neoplasms/genetics , MutationSubject(s)
Cell-Free Nucleic Acids , Lung Neoplasms , Humans , Early Detection of Cancer/methods , Lung Neoplasms/diagnosis , Lung , DNAABSTRACT
PURPOSE: Effective identification of malignant part-solid lung nodules is crucial to eliminate risks due to therapeutic intervention or lack thereof. We aimed to develop delta radiomics and volumetric signatures, characterize changes in nodule properties over three presurgical time points, and assess the accuracy of nodule invasiveness identification when combined with immediate presurgical time point radiomics signature and clinical biomarkers. MATERIALS AND METHODS: Cohort included 156 part-solid lung nodules with immediate presurgical CT scans and a subset of 122 nodules with scans at 3 presurgical time points. Region of interest segmentation was performed using ITK-SNAP, and feature extraction using CaPTk. Image parameter heterogeneity was mitigated at each time point using nested ComBat harmonization. For 122 nodules, delta radiomics features (ΔRAB= (RB-RA)/RA) and delta volumes (ΔVAB= (VB-VA)/VA) were computed between the time points. Principal Component Analysis was performed to construct immediate presurgical radiomics (Rs1) and delta radiomics signatures (ΔRs31+ ΔRs21+ ΔRs32). Identification of nodule pathology was performed using logistic regression on delta radiomics and immediate presurgical time point signatures, delta volumes (ΔV31+ ΔV21+ ΔV32), and clinical variable (smoking status, BMI) models (train test split (2:1)). RESULTS: In delta radiomics analysis (n= 122 nodules), the best-performing model combined immediate pre-surgical time point and delta radiomics signatures, delta volumes, and clinical factors (classification accuracy [AUC]): (77.5% [0.73]) (train); (71.6% [0.69]) (test). CONCLUSIONS: Delta radiomics and volumes can detect changes in nodule properties over time, which are predictive of nodule invasiveness. These tools could improve conventional radiologic assessment, allow for earlier intervention for aggressive nodules, and decrease unnecessary intervention-related morbidity.
ABSTRACT
Although immune checkpoint blockade (ICB) is currently approved for the treatment of extensive-stage small-cell lung cancer (SCLC) in combination with chemotherapy, relatively few patients have demonstrated durable clinical benefit (DCB) to these therapies. Biomarkers predicting responses are needed. Biopsies from 35 SCLC patients treated with ICB were subjected to transcriptomic analysis; gene signatures were assessed for associations with responses. Twenty-one patients were treated with ICB in the first-line setting in combination with platinum-based chemotherapy; fourteen patients were treated in the second-line setting with ICB alone. DCB after ICB in SCLC in the second-line setting (3 of 14 patients) was associated with statistically higher transcriptomic levels of genes associated with inflammation (p = 0.003), antigen presentation machinery (p = 0.03), interferon responses (p < 0.05), and increased CD8 T cells (p = 0.02). In contrast, these gene signatures were not significantly different in the first-line setting. Our data suggest that responses to ICB in SCLC in the second-line setting can be predicted by the baseline inflammatory state of the tumor; however, this strong association with inflammation was not seen in the first-line setting. We postulate that chemotherapy alters the immune milieu allowing a response to ICB. Other biomarkers will be needed to predict responses in first-line therapy patients.
ABSTRACT
INTRODUCTION: The patterns of failure (POF) for metastatic non-small-cell lung cancer (mNSCLC) treated with immunotherapy are not well established. METHODS: We conducted a retrospective cohort study of mNSCLC that received first-line pembrolizumab with or without chemotherapy at a single academic center from 2015 to 2021. We defined POF with 2 classifications: 1) local, regional, or distant failure, or 2) failure in existing lesions, new lesions, or a combination. Oligoprogression was defined as disease progression (PD) in ≤3 sites of failure. Overall survival (OS) was measured via Kaplan-Meier and modelled with Cox regression. RESULTS: Of 298 patients identified, 198 had PD. Using POF classification 1, most failures were distant (43.9%) or a combination of locoregional and distant (34.4%). For POF classification 2, failures occurred in a combination of new and existing lesions (45.0%), existing lesions alone (33.3%), or in new lesions only (21.7%). Oligoprogression occurred in 39.9% (n = 79) cases. Median OS was higher in the following: PD in existing lesions vs. new or new + existing lesions (28.7 vs. 20.2 vs. 13.9 months, P < .001) and oligoprogression vs. polyprogression (35.1 vs. 12.2 months, P < .001). In oligoprogression, median OS was better for those who received radiation to all sites of PD (62.2 months) than for those who changed systemic therapy (22.9 months, P = .007). On multivariable analysis, radiation for oligoprogression (HR 0.35, 95% CI: 0.20-0.62, P < .001) was associated with improved OS. CONCLUSIONS: In mNSCLC treated with pembrolizumab, oligoprogression is relatively common. Randomized data are needed to define the benefits of radiation in oligoprogressive mNSCLC.
Subject(s)
Carcinoma, Non-Small-Cell Lung , Lung Neoplasms , Humans , Carcinoma, Non-Small-Cell Lung/pathology , Lung Neoplasms/pathology , Retrospective Studies , Antibodies, Monoclonal, HumanizedABSTRACT
Drawing from insights from communication science and behavioral economics, the University of Pennsylvania Telehealth Research Center of Excellence (Penn TRACE) is designing and testing telehealth strategies with the potential to transform access to care, care quality, outcomes, health equity, and health-care efficiency across the cancer care continuum, with an emphasis on understanding mechanisms of action. Penn TRACE uses lung cancer care as an exemplar model for telehealth across the care continuum, from screening to treatment to survivorship. We bring together a diverse and interdisciplinary team of international experts and incorporate rapid-cycle approaches and mixed methods evaluation in all center projects. Our initiatives include a pragmatic sequential multiple assignment randomized trial to compare the effectiveness of telehealth strategies to increase shared decision-making for lung cancer screening and 2 pilot projects to test the effectiveness of telehealth to improve cancer care, identify multilevel mechanisms of action, and lay the foundation for future pragmatic trials. Penn TRACE aims to produce new fundamental knowledge and advance telehealth science in cancer care at Penn and nationally.
Subject(s)
Lung Neoplasms , Telemedicine , Humans , Pennsylvania , Lung Neoplasms/therapy , Lung Neoplasms/diagnosis , Universities , Early Detection of Cancer/methods , Pilot ProjectsABSTRACT
PURPOSE: Less than half of the patients with newly diagnosed metastatic non-small cell lung cancer (NSCLC) undergo comprehensive molecular testing. We designed an electronic medical record (EMR)-based "nudge intervention" to prompt plasma-based molecular testing at the time of initial medical oncology consultation. METHODS: A nonrandomized prospective trial was conducted at the University of Pennsylvania's academic practice and two affiliated community practices. Molecular genotyping was performed by tissue- and/or plasma-based next generation sequencing methods. Comprehensive testing was defined as testing for EGFR, ALK, BRAF, ROS1, MET, RET, KRAS, and NTRK. Guideline-concordant treatment was defined as the use of the appropriate first-line (1L) therapy as per the National Comprehensive Cancer Network (NCCN) guidelines. Proportion of patients with comprehensive molecular genotyping results available at any time, molecular results available before 1L therapy, and guideline-concordant 1L treatment were compared between the preintervention and postintervention cohorts using Fisher's exact test or Pearson's chi-squared test. RESULTS: Five hundred and thirty-three patients were included, 376 in the preintervention cohort and 157 in the postintervention cohort. After implementation of the EMR-based nudge, a higher proportion of patients underwent comprehensive molecular testing in the postintervention versus the preintervention cohort (100% v 88%, P = <.001), had results of comprehensive molecular testing available before initiating 1L treatment (97.3% v 91.6%, P = .026), and received NCCN guideline-concordant care (89.8% v 78.2%, P = .035). CONCLUSION: Across three practice sites in a large health system, implementation of a provider team-focused EMR-based nudge intervention was feasible, and led to a higher number of patients with NSCLC undergoing comprehensive molecular genotyping. These findings demonstrate that behavioral nudges can promote molecular testing and should be studied further as a tool to improve guideline-concordant care in both community and academic sites.
ABSTRACT
Lung cancer screening via annual low-dose computed tomography (LDCT) has poor adoption. We conducted a prospective case-control study among 958 individuals eligible for lung cancer screening to develop a blood-based lung cancer detection test that when positive is followed by an LDCT. Changes in genome-wide cell-free DNA (cfDNA) fragmentation profiles (fragmentomes) in peripheral blood reflected genomic and chromatin characteristics of lung cancer. We applied machine learning to fragmentome features to identify individuals who were more or less likely to have lung cancer. We trained the classifier using 576 cases and controls from study samples, and then validated it in a held-out group of 382 cases and controls. The validation demonstrated high sensitivity for lung cancer, and consistency across demographic groups and comorbid conditions. Applying test performance to the screening eligible population in a five-year model with modest utilization assumptions suggested the potential to prevent thousands of lung cancer deaths.
ABSTRACT
PURPOSE: Current guidelines recommend molecular genotyping for patients newly diagnosed with metastatic nonsquamous (mNSq) non-small-cell lung cancer (NSCLC). The association between availability of molecular genotyping before first line (1L) therapy and overall survival (OS) is not known. METHODS: We conducted a real-world cohort study using electronic health records in patients newly diagnosed with mNSq NSCLC. Cox proportional-hazards multivariable regression models were constructed to examine the association between OS and test result availability before 1L therapy, adjusting for covariates. Additional analyses were conducted to assess the consistency and strength of the relationship. Multivariable logistic regression models were used to examine the association between concurrent tissue and plasma testing (v tissue alone) and result availability. RESULTS: Three hundred twenty-six patients were included, 80% (261/326) with results available before 1L (available testing group), and 20% (65/326) without results available (unavailable testing group). With 14.2-month median follow-up, patients in the available testing group had significantly longer OS relative to the unavailable testing group (adjusted hazard ratio, 0.43; 95% CI, 0.30 to 0.62; P < .0001). The adjusted odds of availability of results before 1L therapy was higher with concurrent tissue and plasma testing (v tissue testing alone; adjusted odds ratio, 2.06; 95% CI, 1.09 to 3.90; P = .026). CONCLUSION: Among patients with mNSq NSCLC in a real-world cohort, availability of molecular genotyping results before 1L therapy was associated with significantly better OS. Concurrent tissue and plasma testing was associated with a higher odds of availability of results before 1L therapy. These findings warrant renewed attention to the completion of molecular genotyping before 1L therapy.
Subject(s)
Carcinoma, Non-Small-Cell Lung , Lung Neoplasms , Humans , Carcinoma, Non-Small-Cell Lung/pathology , Lung Neoplasms/pathology , Cohort Studies , Genotype , Proportional Hazards ModelsABSTRACT
We aim to determine the feasibility of a novel radiomic biomarker that can integrate with other established clinical prognostic factors to predict progression-free survival (PFS) in patients with non-small cell lung cancer (NSCLC) undergoing first-line immunotherapy. Our study includes 107 patients with stage 4 NSCLC treated with pembrolizumab-based therapy (monotherapy: 30%, combination chemotherapy: 70%). The ITK-SNAP software was used for 3D tumor volume segmentation from pre-therapy CT scans. Radiomic features (n = 102) were extracted using the CaPTk software. Impact of heterogeneity introduced by image physical dimensions (voxel spacing parameters) and acquisition parameters (contrast enhancement and CT reconstruction kernel) was mitigated by resampling the images to the minimum voxel spacing parameters and harmonization by a nested ComBat technique. This technique was initialized with radiomic features, clinical factors of age, sex, race, PD-L1 expression, ECOG status, body mass index (BMI), smoking status, recurrence event and months of progression-free survival, and image acquisition parameters as batch variables. Two phenotypes were identified using unsupervised hierarchical clustering of harmonized features. Prognostic factors, including PDL1 expression, ECOG status, BMI and smoking status, were combined with radiomic phenotypes in Cox regression models of PFS and Kaplan Meier (KM) curve-fitting. Cox model based on clinical factors had a c-statistic of 0.57, which increased to 0.63 upon addition of phenotypes derived from harmonized features. There were statistically significant differences in survival outcomes stratified by clinical covariates, as measured by the log-rank test (p = 0.034), which improved upon addition of phenotypes (p = 0.00022). We found that mitigation of heterogeneity by image resampling and nested ComBat harmonization improves prognostic value of phenotypes, resulting in better prediction of PFS when added to other prognostic variables.
Subject(s)
Carcinoma, Non-Small-Cell Lung , Lung Neoplasms , Biomarkers , Carcinoma, Non-Small-Cell Lung/diagnostic imaging , Carcinoma, Non-Small-Cell Lung/drug therapy , Humans , Immunotherapy/methods , Lung Neoplasms/diagnostic imaging , Lung Neoplasms/drug therapy , Progression-Free SurvivalABSTRACT
Introduction: The availability of targeted therapies has transformed the management of advanced NSCLC; however, most patients do not undergo guideline-recommended tumor genotyping. The impact of plasma-based next-generation sequencing (NGS) performed simultaneously with diagnostic biopsy in suspected advanced NSCLC has largely been unexplored. Methods: We performed a prospective cohort study of patients with suspected advanced lung cancer on the basis of cross-sectional imaging results. Blood from the time of biopsy was sequenced using a commercially available 74-gene panel. The primary outcome measure was time to first-line systemic treatment compared with a retrospective cohort of consecutive patients with advanced NSCLC with reflex tissue NGS. Results: We analyzed the NGS results from 110 patients with newly diagnosed advanced NSCLC: cohorts 1 and 2 included 55 patients each and were well balanced regarding baseline demographics. In cohort 1, plasma NGS identified therapeutically informative driver mutations in 32 patients (58%) (13 KRAS [five KRAS G12C], 13 EGFR, two ERRB2, two MET, one BRAF, one RET). The NGS results were available before the first oncology visit in 85% of cohort 1 versus 9% in cohort 2 (p < 0.0001), with more cohort 1 patients receiving a guideline-concordant treatment recommendation at this visit (74% versus 46%, p = 0.005). Time-to-treatment was significantly shorter in cohort 1 compared with cohort 2 (12 versus 20 d, p = 0.003), with a shorter time-to-treatment in patients with specific driver mutations (10 versus 19 d, p = 0.001). Conclusions: Plasma-based NGS performed at the time of diagnostic biopsy in patients with suspected advanced NSCLC is associated with decreased time-to-treatment compared with usual care.
ABSTRACT
PURPOSE: As immune checkpoint inhibitors (ICI) become increasingly used in frontline settings, identifying early indicators of response is needed. Recent studies suggest a role for circulating tumor DNA (ctDNA) in monitoring response to ICI, but uncertainty exists in the generalizability of these studies. Here, the role of ctDNA for monitoring response to ICI is assessed through a standardized approach by assessing clinical trial data from five independent studies. PATIENTS AND METHODS: Patient-level clinical and ctDNA data were pooled and harmonized from 200 patients across five independent clinical trials investigating the treatment of patients with non-small-cell lung cancer with programmed cell death-1 (PD-1)/programmed death ligand-1 (PD-L1)-directed monotherapy or in combination with chemotherapy. CtDNA levels were measured using different ctDNA assays across the studies. Maximum variant allele frequencies were calculated using all somatic tumor-derived variants in each unique patient sample to correlate ctDNA changes with overall survival (OS) and progression-free survival (PFS). RESULTS: We observed strong associations between reductions in ctDNA levels from on-treatment liquid biopsies with improved OS (OS; hazard ratio, 2.28; 95% CI, 1.62 to 3.20; P < .001) and PFS (PFS; hazard ratio 1.76; 95% CI, 1.31 to 2.36; P < .001). Changes in the maximum variant allele frequencies ctDNA values showed strong association across different outcomes. CONCLUSION: In this pooled analysis of five independent clinical trials, consistent and robust associations between reductions in ctDNA and outcomes were found across multiple end points assessed in patients with non-small-cell lung cancer treated with an ICI. Additional tumor types, stages, and drug classes should be included in future analyses to further validate this. CtDNA may serve as an important tool in clinical development and an early indicator of treatment benefit.
Subject(s)
Antineoplastic Agents, Immunological , Carcinoma, Non-Small-Cell Lung , Circulating Tumor DNA , Lung Neoplasms , Antineoplastic Agents, Immunological/therapeutic use , Biomarkers, Tumor/genetics , Carcinoma, Non-Small-Cell Lung/drug therapy , Circulating Tumor DNA/genetics , Clinical Trials as Topic , Humans , Immune Checkpoint Inhibitors/pharmacology , Lung Neoplasms/drug therapy , PrognosisABSTRACT
CASE PRESENTATION: A 53-year-old man presented to the ED at a time of low severe acute respiratory syndrome coronavirus 2, also known as coronavirus disease 2019 (COVID-19), prevalence and reported 2 weeks of progressive shortness of breath, dry cough, headache, myalgias, diarrhea, and recurrent low-grade fevers to 39°C for 1 week with several days of recorded peripheral capillary oxygen saturation of 80% to 90% (room air) on home pulse oximeter. Five days earlier, he had visited an urgent care center where a routine respiratory viral panel was reportedly negative. A COVID-19 reverse transcriptase polymerase chain reaction test result was pending at the time of ED visit. He reported a past medical history of gastroesophageal reflux disease that was treated with famotidine. Travel history included an out-of-state trip 3 weeks earlier, but no recent international travel.
Subject(s)
COVID-19/diagnostic imaging , Lung/diagnostic imaging , Bacteremia/complications , COVID-19/complications , COVID-19/physiopathology , COVID-19 Nucleic Acid Testing , Cerebellar Diseases/complications , Cerebellar Diseases/diagnostic imaging , Cough/physiopathology , Diarrhea/physiopathology , Disease Progression , Dyspnea/physiopathology , Emergency Service, Hospital , Fever/physiopathology , Headache/physiopathology , Humans , Ischemic Stroke/complications , Ischemic Stroke/diagnostic imaging , Lymphopenia/physiopathology , Magnetic Resonance Imaging , Male , Middle Aged , Myalgia/physiopathology , Oximetry , Pneumonia, Staphylococcal/complications , Radiography, Thoracic , SARS-CoV-2 , Staphylococcal Infections/complications , Tomography, X-Ray ComputedABSTRACT
We investigated racial disparities in a 30-day composite outcome of readmission and death among patients admitted across a 5-hospital health system following an index COVID-19 admission. A dataset of 1,174 patients admitted between March 1, 2020 and August 21, 2020 for COVID-19 was retrospectively analyzed for odds of readmission among Black patients compared to all other patients, with sequential adjustment for demographics, index admission characteristics, type of post-acute care, and comorbidities. Tabulated results demonstrated a significantly greater odds of 30-day readmission or death among Black patients (18.0% of Black patients vs. 11.3% of all other patients; Univariate Odds Ratio: 1.71, p = 0.002). Sequential adjustment via logistic regression revealed that the odds of 30-day readmission or death were significantly greater among Black patients after adjustment for demographics, index admission characteristics, and type of post-acute care, but not comorbidities. Stratification by type of post-acute care received on discharge revealed that the same disparity in odds of 30-day readmission or death existed among patients discharged home without home services, but not those discharged to home with home services or to a skilled nursing facility or acute rehab facility. Collectively, the findings suggest that weighing comorbidity burdens in post-acute care decisions may be relevant in addressing racial disparities in 30-day outcomes following discharge from an index COVID-19 admission.
ABSTRACT
This study tackles interobserver variability with respect to specialty training in manual segmentation of non-small cell lung cancer (NSCLC). Four readers included for segmentation are: a data scientist (BY), a medical student (LS), a radiology trainee (MH), and a specialty-trained radiologist (SK) for a total of 293 patients from two publicly available databases. Sørensen-Dice (SD) coefficients and low rank Pearson correlation coefficients (CC) of 429 radiomics were calculated to assess interobserver variability. Cox proportional hazard (CPH) models and Kaplan-Meier (KM) curves of overall survival (OS) prediction for each dataset were also generated. SD and CC for segmentations demonstrated high similarities, yielding, SD: 0.79 and CC: 0.92 (BY-SK), SD: 0.81 and CC: 0.83 (LS-SK), and SD: 0.84 and CC: 0.91 (MH-SK) in average for both databases, respectively. OS through the maximal CPH model for the two datasets yielded c-statistics of 0.7 (95% CI) and 0.69 (95% CI), while adding radiomic and clinical variables (sex, stage/morphological status, and histology) together. KM curves also showed significant discrimination between high- and low-risk patients (p-value < 0.005). This supports that readers' level of training and clinical experience may not significantly influence the ability to extract accurate radiomic features for NSCLC on CT. This potentially allows flexibility in the training required to produce robust prognostic imaging biomarkers for potential clinical translation.
ABSTRACT
Among non-small cell lung cancer (NSCLC) patients with therapeutically targetable tumor mutations in epidermal growth factor receptor (EGFR), not all patients respond to targeted therapy. Combining circulating-tumor DNA (ctDNA), clinical variables, and radiomic phenotypes may improve prediction of EGFR-targeted therapy outcomes for NSCLC. This single-center retrospective study included 40 EGFR-mutant advanced NSCLC patients treated with EGFR-targeted therapy. ctDNA data included number of mutations and detection of EGFR T790M. Clinical data included age, smoking status, and ECOG performance status. Baseline chest CT scans were analyzed to extract 429 radiomic features from each primary tumor. Unsupervised hierarchical clustering was used to group tumors into phenotypes. Kaplan-Meier (K-M) curves and Cox proportional hazards regression were modeled for progression-free survival (PFS) and overall survival (OS). Likelihood ratio test (LRT) was used to compare fit between models. Among 40 patients (73% women, median age 62 years), consensus clustering identified two radiomic phenotypes. For PFS, the model combining radiomic phenotypes with ctDNA and clinical variables had c-statistic of 0.77 and a better fit (LRT p = 0.01) than the model with clinical and ctDNA variables alone with a c-statistic of 0.73. For OS, adding radiomic phenotypes resulted in c-statistic of 0.83 versus 0.80 when using clinical and ctDNA variables (LRT p = 0.08). Both models showed separation of K-M curves dichotomized by median prognostic score (p < 0.005). Combining radiomic phenotypes, ctDNA, and clinical variables may enhance precision oncology approaches to managing advanced non-small cell lung cancer with EGFR mutations.
Subject(s)
Carcinoma, Non-Small-Cell Lung/diagnostic imaging , Genes, erbB-1 , Image Processing, Computer-Assisted , Lung Neoplasms/diagnostic imaging , Tomography, X-Ray Computed , Aged , Aged, 80 and over , Antineoplastic Agents/pharmacology , Antineoplastic Agents/therapeutic use , Carcinoma, Non-Small-Cell Lung/drug therapy , Carcinoma, Non-Small-Cell Lung/genetics , Carcinoma, Non-Small-Cell Lung/pathology , Circulating Tumor DNA/analysis , ErbB Receptors/antagonists & inhibitors , ErbB Receptors/genetics , Feasibility Studies , Female , Humans , Liquid Biopsy , Lung Neoplasms/drug therapy , Lung Neoplasms/genetics , Lung Neoplasms/pathology , Male , Middle Aged , Pharmacogenomic Variants , Phenotype , Retrospective StudiesABSTRACT
Circulating cell-free DNA (ccfDNA) is used increasingly as a cancer biomarker for prognostication, as a correlate for tumor volume, or as input for downstream molecular analysis. Determining optimal blood processing and ccfDNA quantification are crucial for ccfDNA to serve as an accurate biomarker as it moves into the clinical realm. Whole blood was collected from 50 subjects, processed to plasma, and used immediately or frozen at -80°C. Plasma ccfDNA was extracted and concentration was assessed by real-time quantitative PCR (qPCR), fluorimetry, and droplet digital PCR (ddPCR). For the 24 plasma samples from metastatic pancreatic cancer patients, the variant allele fractions (VAF) of KRAS G12/13 pathogenic variants in circulating tumor DNA (ctDNA) were measured by ddPCR. Using a high-speed (16,000 × g) or slower-speed (4100 × g) second centrifugation step showed no difference in ccfDNA yield or ctDNA VAF. A two- versus three-spin centrifugation protocol also showed no difference in ccfDNA yield or ctDNA VAF. A higher yield was observed from fresh versus frozen plasma by qPCR and fluorimetry, whereas a higher yield was observed for frozen versus fresh plasma by ddPCR, however, no difference was observed in ctDNA VAF. Overall, our findings suggest factors to consider when implementing a ccfDNA extraction and quantification workflow in a research or clinical setting.