Biology subjects

Hirst, G. L.

Publications and source records attributed to Hirst, G. L..

3 recordsLinked to original sources

bioRxiv2023

Tumor microenvironmental determinants of high-risk DCIS progression

ABSTRACT/SUMMARYDuctal carcinoma in situ (DCIS) constitutes an array of morphologically recognized intraductal neoplasms in the mammary ductal tree defined by an increased risk for subsequent invasive carcinomas at or near the site of biopsy detection. However, only 15-45% of untreated DCIS cases progress to invasive cancer, so understanding mechanisms that prevent progression is key to avoid overtreatment and provides a basis for alternative therapies and prevention. This study was designed to characterize the tumor microenvironment and molecular profile of high-risk DCIS that grew to a large size but remained as DCIS. All patients had DCIS lesions >5cm in size with at least one additional high-risk feature: young age (<45 years), high nuclear grade, hormone receptor negativity, HER2 positivity, the presence of comedonecrosis, or a palpable mass. The tumor immune microenvironment was characterized using multiplex immunofluorescence to identify immune cells and their spatial relationships within the ducts and stroma. Gene copy number analysis and whole exome DNA sequencing identified the mutational burden and driver mutations, and quantitative whole-transcriptome/gene expression analyses were performed. There was no association between the percent of the DCIS genome characterized by copy number variants (CNAs) and recurrence events (DCIS or invasive). Mutations, especially missense mutations, in the breast cancer driver genes PIK3CA and TP53 were common in this high-risk DCIS cohort (47% of evaluated lesions). Tumor infiltrating lymphocyte (TIL) density was higher in DCIS lesions with TP53 mutations (p=0.0079) compared to wildtype lesions, but not in lesions with PIK3CA mutations (p=0.44). Immune infiltrates were negatively associated with hormone receptor status and positively associated with HER2 expression. High levels of CD3+CD8-T cells were associated with good outcomes with respect to any subsequent recurrence (DCIS or invasive cancer), whereas high levels of CD3+Foxp3+ Treg cells were associated with poor outcomes. Spatial proximity analyses of immune cells and tumor cells demonstrated that close proximity of T cells with tumor cells was associated with good outcomes with respect to any recurrence as well as invasive recurrences. Interestingly, we found that myoepithelial continuity (distance between myoepithelial cells surrounding the involved ducts) was significantly lower in DCIS lesions compared to normal tissue (p=0.0002) or to atypical ductal hyperplasia (p=0.011). Gene set enrichment analysis identified several immune pathways associated with low myoepithelial continuity and a low myoepithelial continuity score was associated with better outcomes, suggesting that gaps in the myoepithelial layer may allow access/interactions between immune infiltrates and tumor cells. Our study demonstrates the immune microenvironment of DCIS, in particular the spatial proximity of tumor cells and T cells, and myoepithelial continuity are important determinants for progression of disease.

cancer biology↗

bioRxiv2023

Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatments and receptor subtypes

Drug resistance is a major obstacle in cancer treatment and can involve a variety of different factors. Identifying effective therapies for drug resistant tumors is integral for improving patient outcomes. In this study, we applied a computational drug repositioning approach to identify potential agents to sensitize primary drug resistant breast cancers. We extracted drug resistance profiles from the I-SPY 2 TRIAL, a neoadjuvant trial for early stage breast cancer, by comparing gene expression profiles of responder and non-responder patients stratified into treatments within HR/HER2 receptor subtypes, yielding 17 treatment-subtype pairs. We then used a rank-based pattern-matching strategy to identify compounds in the Connectivity Map, a database of cell line derived drug perturbation profiles, that can reverse these signatures in a breast cancer cell line. We hypothesize that reversing these drug resistance signatures will sensitize tumors to treatment and prolong survival. We found that few individual genes are shared among the drug resistance profiles of different agents. At the pathway level, however, we found enrichment of immune pathways in the responders in 8 treatments within the HR+HER2+, HR+HER2-, and HR-HER2-receptor subtypes. We also found enrichment of estrogen response pathways in the non-responders in 10 treatments primarily within the hormone receptor positive subtypes. Although most of our drug predictions are unique to treatment arms and receptor subtypes, our drug repositioning pipeline identified the estrogen receptor antagonist fulvestrant as a compound that can potentially reverse resistance across 13/17 of the treatments and receptor subtypes including HR+ and triple negative. While fulvestrant showed limited efficacy when tested in a panel of 5 paclitaxel-resistant breast cancer cell lines, it did increase drug response in combination with paclitaxel in HCC-1937, a triple negative breast cancer cell line.

cell biology↗

bioRxiv2020

Mutational profiling of micro-dissected pre-malignant lesions from archived specimens

BackgroundSystematic cancer screening has led to the increased detection of pre-malignant lesions (PMLs). The absence of reliable prognostic markers has led mostly to over treatment resulting in potentially unnecessary stress, or potentially insufficient treatment and avoidable progression. Importantly, most mutational profiling studies have relied on PML synchronous to invasive cancer, or performed in patients without outcome information, hence limiting their utility for biomarker discovery. The limitations in comprehensive mutational profiling of PMLs are in large part due to the significant technical and methodological challenges: most PML specimens are small, fixed in formalin and paraffin embedded (FFPE) and lack matching normal DNA. MethodsUsing test DNA from a highly degraded FFPE specimen, multiple targeted sequencing approaches were evaluated, varying DNA input amount (3-200 ng), library preparation strategy (BE: Blunt-End, SS: Single-Strand, AT: A-Tailing) and target size (whole exome vs cancer gene panel). Variants in high-input DNA from FFPE and mirrored frozen specimens were used for PML-specific variant calling training and testing, respectively. The resulting approach was applied to profile and compare multiple regions micro-dissected (mean area 5 mm2) from 3 breast ductal carcinoma in situ (DCIS). ResultsUsing low-input FFPE DNA, BE and SS libraries resulted in 4.9 and 3.7 increase over AT libraries in the fraction of whole exome covered at 20x (BE:87%, SS:63%, AT:17%). Compared to high-confidence somatic mutations from frozen specimens, PML-specific variant filtering increased recall (BE:85%, SS:80%, AT:75%) and precision (BE:93%, SS:91%, AT:84%) to levels expected from sampling variation. Copy number alterations were consistent across all tested approaches and only impacted by the design of the capture probe-set. Applied to DNA extracted from 9 micro-dissected regions (8 PML, 1 normal epithelium), the approach achieved comparable performance, illustrated the data adequacy to identify candidate driver events (GATA3 mutations, ERBB2 or FGFR1 gains, TP53 loss) and measure intra-lesion genetic heterogeneity. ConclusionAlternate experimental and analytical strategies increased the accuracy of DNA sequencing from archived micro-dissected PML regions, supporting the deeper molecular characterization of early cancer lesions and achieving a critical milestone in the development of biology-informed prognostic markers and precision chemo-prevention strategies.

genomics↗