Lynette Marie Sholl

Examining the Role of Extrachromosomal DNA in Lung Cancer

This study examines ecDNA in lung cancer, finding it in 18.9% of patients and associating it with worse survival and genomic instability.

Genomic Characterization of Lung Cancer in Never-Smokers Using Deep Learning

This paper develops a deep learning model to predict molecular alterations in never-smoker lung adenocarcinomas from histological images, achieving high accuracy for most features.

Revealing the Drivers Underlying Distinct Evolutionary Trajectories in Lung Adenocarcinoma

This study identifies three distinct evolutionary trajectories in lung adenocarcinomas using whole-genome sequencing, revealing that some never-smoking tumors follow smoking-like paths driven by KRAS mutations.

Pan-cancer spatial characterization of key immune biomarkers in the tumor microenvironment

The paper provides a pan-cancer spatial analysis of immune biomarkers in the tumor microenvironment using multiplex immunofluorescence data from 2,019 tumors across 14 cancer types.

A prognostic signature for lung adenocarcinoma in people who have never smoked

The paper identifies three subtypes of NS-LUAD using RNA-seq data and develops a 60-gene signature that predicts survival across subgroups.

Clinicogenomic characterization of inflammatory breast cancer

This study analyzes genomic alterations in a large IBC cohort, finding high TP53 mutation frequency and NOTCH pathway enrichment, but no major genomic differences compared to non-IBC cases.

Deciphering lung adenocarcinoma evolution and the role of LINE-1 retrotransposition

This study analyzes 1024 lung adenocarcinomas to identify evolutionary patterns and mutational mechanisms, revealing distinct trajectories linked to smoking, ancestry, and retrotransposition.

Leukemia inhibitory factor (LIF) receptor amplifies pathogenic activation of fibroblasts in lung fibrosis

This study identifies LIFR as a master amplifier of fibroblast activation in IPF, showing that blocking LIFR reduces fibrosis in ex vivo tissue.

Utilizing Electronic Health Records (EHR) and Tumor Panel Sequencing to Demystify Prognosis of Cancer of Unknown Primary (CUP) patients

This paper develops OncoNPC, a machine learning classifier for CUP patients using tumor sequencing data, showing improved survival outcomes with treatment aligned to predicted cancer types.

Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases

MatchMiner: An open source computational platform for real-time matching of cancer patients to precision medicine clinical trials using genomic and clinical criteria

MatchMiner automates matching cancer patients to precision medicine trials using genomic and clinical criteria, enabling efficient and accurate trial enrollment.