Publications

BACKGROUND: Interstitial lung abnormalities (ILA) are CT findings suggestive of interstitial lung disease in individuals without a prior diagnosis or suspicion of ILD. Previous studies have demonstrated that ILA are associated with clinically significant outcomes including mortality. The aim of this study was to determine the prevalence of ILA in a large CT lung cancer screening program and the association with clinically significant outcomes including mortality, hospitalizations, cancer and ILD diagnosis.

METHODS: This was a retrospective study of individuals enrolled in a CT lung cancer screening program from 2012 to 2014. Baseline and longitudinal CT scans were scored for ILA per Fleischner Society guidelines. The primary analyses examined the association between baseline ILA and mortality, all-cause hospitalization, and incidence of lung cancer. Kaplan-Meier plots were generated to visualize the associations between ILA and lung cancer and all-cause mortality. Cox regression proportional hazards models were used to test for this association in both univariate and multivariable models.

RESULTS: 1699 subjects met inclusion criteria. 41 (2.4%) had ILA and 101 (5.9%) had indeterminate ILA on baseline CTs. ILD was diagnosed in 10 (24.4%) of 41 with ILA on baseline CT with a mean time from baseline CT to diagnosis of 4.47 ± 2.72 years. On multivariable modeling, the presence of ILA remained a significant predictor of death, HR 3.87 (2.07, 7.21; p < 0.001) when adjusted for age, sex, BMI, pack years and active smoking, but not of lung cancer and all-cause hospital admission. Approximately 50% with baseline ILA had progression on the longitudinal scan.

CONCLUSIONS: ILA identified on baseline lung cancer screening exams are associated with all-cause mortality. In addition, a significant proportion of patients with ILA are subsequently diagnosed with ILD and have CT progression on longitudinal scans.

TRIAL REGISTRATION NUMBER: ClinicalTrials.gov; No.: NCT04503044.

Clear cell renal cell carcinoma (ccRCC) incidence has been rising in recent years, with strong association between differential microRNA (miRNA) expression and neoplastic progression. Specifically, overexpression of miR-155-5p has been associated with promoting aggressive cancer in ccRCC and other cancers. In this study, we further investigate the role of this miRNA and one of its protein targets, Jade-1, to better understand the mechanism behind aggressive forms of ccRCC. Jade-1, a tumor suppressor, is stabilized by Von-Hippel Lindau (VHL), which is frequently mutated in ccRCC. Experiments featuring downregulation of miR-155-5p in two ccRCC cell lines (786-O and Caki-1) attenuated their oncogenic potential and led to increased levels of Jade-1. Conversely, knockdown experiments with an anti-Jade-1 shRNA in 786-O and Caki-1 cells showed increased metastatic potential through elevated proliferation, migration, and invasion rates. In a mouse xenograft model, downregulation of miR-155 decreased the rate of tumor implantation and proliferation. Direct interaction between miR-155-5p and Jade-1 was confirmed through a 3'UTR luciferase reporter assay. These findings further elucidate the mechanism of action of miR-155-5p in driving an aggressive phenotype in ccRCC through its role in regulating Jade-1.

OBJECTIVE: To describe differences in the urinary microbiome of patients with pathologically confirmed lichen sclerosus (LS) urethral stricture disease (USD) vs non-lichen sclerosus (non-LS) USD pre- and post-operatively.

METHODS: Patients were pre-operatively identified and prospectively followed, all underwent surgical repair and had tissue samples obtained to make a pathological diagnosis of LS. Pre- and post-operative urine samples were collected. Bacterial genomic DNA was extracted. Alpha and beta diversity measurements were calculated and compared. A zero-inflated negative binomial model was utilized to compare taxa abundances between disease status and surgery status.

RESULTS: Urine samples were obtained from both cohorts, 69 samples in total: 36 samples were obtained pre-operatively and 33 samples were obtained post-operatively. Ten patients provided both a pre-operative and post-operative urine sample. Twenty-six patients had pathological evidence of LS and 33 patients did not. There was a statistically significant difference in alpha diversity between the pre-operative urine samples of patients with non-LS USD and LS USD, (p = 0.01). There was no significant difference in alpha diversity within post-operative urine samples between patients with non-LS USD and LS USD, (p = 0.1). A significant difference was observed in Weighed UniFrac distances with respect to disease and operative status, (p = 0.001 and 0.002).

CONCLUSIONS: LS USD have significant alterations in diversity and differential abundance of urine microbiota compared to non-LS USD controls. These findings could be used to guide further investigations into the role of the urinary microbiome in LS USD pathogenesis, severity of presentation, and stricture recurrence.

INTRODUCTION: Lung cancer remains the deadliest cancer in the world, and lung cancer survival is heavily dependent on tumor stage at the time of detection. Low-dose computed tomography screening can reduce mortality; however, annual screening is limited by low adherence in the United States of America and still not broadly implemented in Europe. As a result, less than 10% of lung cancers are detected through existing programs. Thus, there is a great need for additional screening tests, such as a blood test, that could be deployed in the primary care setting.

METHODS: We prospectively recruited 1384 individuals meeting the National Lung Screening Trial demographic eligibility criteria for lung cancer and collected stabilized whole blood to enable the pipetting-free collection of material, thus minimizing preanalytical noise. Ultra-deep small RNA sequencing (20 million reads per sample) was performed with the addition of a method to remove highly abundant erythroid RNAs, and thus open bandwidth for the detection of less abundant species originating from the plasma or the immune cellular compartment. We used 100 random data splits to train and evaluate an ensemble of logistic regression classifiers using small RNA expression of 943 individuals, discovered an 18-small RNA feature consensus signature (miLung), and validated this signature in an independent cohort (441 individuals). Blood cell sorting and tumor tissue sequencing were performed to deconvolve small RNAs into their source of origin.

RESULTS: We generated diagnostic models and report a median receiver-operating characteristic area under the curve of 0.86 (95% confidence interval [CI]: 0.84-0.86) in the discovery cohort and generalized performance of 0.83 in the validation cohort. Diagnostic performance increased in a stage-dependent manner ranging from 0.73 (95% CI: 0.71-0.76) for stage I to 0.90 (95% CI: 0.89-0.90) for stage IV in the discovery cohort and from 0.76 to 0.86 in the validation cohort. We identified a tumor-shed, plasma-bound ribosomal RNA fragment of the L1 stalk as a dominant predictor of lung cancer. The fragment is decreased after surgery with curative intent. In additional experiments, results of dried blood spot collection and sequencing revealed that small RNA analysis could potentially be conducted through home sampling.

CONCLUSIONS: These data suggest the potential of a small RNA-based blood test as a viable alternative to low-dose computed tomography screening for early detection of smoking-associated lung cancer.

BACKGROUND: Recent randomized control trials (JCOG0802 and CALGB140503) have shown sublobar resection to be noninferior to lobectomy for non-small cell lung cancer (NSCLC) ≤2.0 cm. We have previously proposed histologic criteria stratifying lung adenocarcinoma into indolent low malignant potential (LMP) and aggressive angioinvasive adenocarcinomas, resulting in better prognostication than provided by World Health Organization grade. Here we determine whether pathologic classification is reproducible and whether subsets of adenocarcinomas predict worse outcomes when treated by wedge resection compared to lobectomy.

METHODS: A retrospective cohort of 108 recipients of wedge resection and 187 recipients of lobectomy for stage I/0 lung adenocarcinomas ≤2.0 cm was assembled from 2 institutions. All tumors were classified by a single pathologist, and interobserver reproducibility was assessed in a subset (n = 92) by 5 pathologists.

RESULTS: Angioinvasive adenocarcinoma (21%-27% of cases) was associated with worse outcomes when treated with wedge resection compared to lobectomy (5-year recurrence-free survival, 57% vs 85% [P = .007]; 5-year disease-free survival [DSS], 70% vs 90% [P = .043]; 7-year overall survival, 37% vs 58% [P = .143]). Adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and LMP exhibited 100% 5-year DSS regardless of the surgical approach. Multivariable analysis showed that angioinvasion, tumor size, margin status, and extent of nodal sampling were significantly associated with recurrence but not with surgical procedure. There was substantial interobserver reproducibility among the pathologists for the diagnosis of angioinvasive adenocarcinoma (κ = 0.71) and the combined indolent AIS/MIA/LMP group (κ = 0.74).

CONCLUSIONS: The majority (∼75%) of lung adenocarcinomas ≤2 cm are adequately managed with wedge resection; however, angioinvasive adenocarcinomas (∼25%) treated by wedge resection with suboptimal nodal sampling exhibit poor outcomes, with a 40% to 45% rate of recurrence within 5 years and 60% to 65% overall mortality at 7 years.

MicroRNAs (miRNAs) are short non-coding RNAs that post-transcriptionally regulate protein expression. The human genome encodes more than 2,500 miRNAs, with each being able to modulate several targets, act along a variety of cellular pathways, and affect various tissues. They are frequently dysregulated in cancers and, via their protein targets, act as oncogenes or tumor-suppressors. As such, their effects are pervasive—miRNAs have been implicated in various biological processes including apoptosis, epithelial-to-mesenchymal transition, and angiogenesis. In this context, miRNA involved in metastasis have been termed “metastamiRs”. This chapter focuses on the role of miRNAs in the metastatic processes of prostate cancer. Our primary aims are to detail specific biological processes and molecular targets through which miRNAs act and that may serve as therapeutic targets. Secondly, we discuss the potential of miRNAs to serve as biomarkers of tumor aggression and thus potentially guide personalized therapy.

Bladder cancer is among the most common cancers globally, with significant mortality associated with more advanced disease. Early detection and diagnostic accuracy are thus fundamental to the clinical pathway for managing bladder cancer. MicroRNA (miRNA) are small, non-coding segments of RNA that regulate gene expression and have been implicated in the process of carcinogenesis. Dysregulation and aberrant expression of miRNAs have been shown to have both oncogenic and tumor suppressive effects. A vast number of miRNA, across the entire field of cancer biology, have already been identified and characterized, and many of these have been associated with bladder cancer. These miRNAs have furthered our understanding of the genetic profile of bladder cancer, and ultimately, may be utilized in the detection, prognosis, and treatment of this disease. This chapter focuses on the role of miRNA in the pathogenesis of metastatic bladder cancer and overviews many of the miRNA thought to be associated with bladder cancer.  Additionally, this chapter explores the clinical utilities of miRNAs in bladder cancer to serve as biomarkers and guide individualized treatment.

MicroRNAs are short noncoding RNAs that regulate post-transcriptional protein expression. Aberrant microRNA expression has been widely implicated in cancer biology with various effects depending on the affected downstream target(s). In renal cell carcinoma, microRNAs have been shown to influence metastasis by targeting oncogenes or tumor suppressors in complex regulatory networks­­ - leading them to be coined “metastamiRs.” This chapter aims to identify the microRNAs responsible for metastasis in renal cell carcinoma, review their molecular function and oncologic outcome, and discuss their potential roles for diagnosis, prognosis, and therapy.

Rationale: Future optimization of computed tomography (CT) lung cancer screening (CTLS) algorithms will depend on clinical outcomes data. Objectives: To report the outcomes of positive and suspicious findings in a clinical CTLS program. Methods: We retrospectively reviewed results for patients from our institution undergoing lung cancer screening from January 2012 through December 2018, with follow-up through December 2019. All exams were retrospectively rescored using Lung-RADS v1.1 (LR). Metrics assessed included positive, probably benign, and suspicious exam rates, frequency/nature of care escalation, and lung cancer detection rates after a positive, probably benign, and suspicious exam result and overall. We calculated time required to resolve suspicious exams as malignant or benign. Results were broken down by subcategories, reason for positive/suspicious designation, and screening round. Results: During the study period 4,301 individuals underwent a total of 10,897 exams. The number of positive (13.9%), suspicious (5.5%), and significant incidental (6.4%) findings was significantly higher at baseline screening. Cancer detection and false-positive rates were 2.0% and 12.3% at baseline versus 1.3% and 5.1% across subsequent screening rounds, respectively. Baseline solid nodule(s) 6 to <8 mm were the only probably benign findings resulting in lung cancer detection within 12 months. New solid nodules 6 to <8 mm were the only LR category 4A (LR4A) findings falling within the LR predicted cancer detection range of 5-15% (12.8%). 38.5% of LR4A cancers were detected within 3 months. Conclusions: Modification of the definition and suggested workup of positive and suspicious lung cancer screening findings appears warranted.

PURPOSE: Patients with cancer are at increased risk of severe COVID-19 disease, but have heterogeneous presentations and outcomes. Decision-making tools for hospital admission, severity prediction, and increased monitoring for early intervention are critical. We sought to identify features of COVID-19 disease in patients with cancer predicting severe disease and build a decision support online tool, COVID-19 Risk in Oncology Evaluation Tool (CORONET).

METHODS: Patients with active cancer (stage I-IV) and laboratory-confirmed COVID-19 disease presenting to hospitals worldwide were included. Discharge (within 24 hours), admission (≥ 24 hours inpatient), oxygen (O2) requirement, and death were combined in a 0-3 point severity scale. Association of features with outcomes were investigated using Lasso regression and Random Forest combined with Shapley Additive Explanations. The CORONET model was then examined in the entire cohort to build an online CORONET decision support tool. Admission and severe disease thresholds were established through pragmatically defined cost functions. Finally, the CORONET model was validated on an external cohort.

RESULTS: The model development data set comprised 920 patients, with median age 70 (range 5-99) years, 56% males, 44% females, and 81% solid versus 19% hematologic cancers. In derivation, Random Forest demonstrated superior performance over Lasso with lower mean squared error (0.801 v 0.807) and was selected for development. During validation (n = 282 patients), the performance of CORONET varied depending on the country cohort. CORONET cutoffs for admission and mortality of 1.0 and 2.3 were established. The CORONET decision support tool recommended admission for 95% of patients eventually requiring oxygen and 97% of those who died (94% and 98% in validation, respectively). The specificity for mortality prediction was 92% and 83% in derivation and validation, respectively. Shapley Additive Explanations revealed that National Early Warning Score 2, C-reactive protein, and albumin were the most important features contributing to COVID-19 severity prediction in patients with cancer at time of hospital presentation.

CONCLUSION: CORONET, a decision support tool validated in health care systems worldwide, can aid admission decisions and predict COVID-19 severity in patients with cancer.