Exploring the presence of bovine leukemia virus among breast cancer tumors in a rural state

PURPOSE

The bovine leukemia virus (BLV) is a deltaretrovirus that causes malignant lymphoma and lymphosarcomas in cattle globally and has high prevalence among large scale U.S. dairy herds. Associations between presence of BLV DNA in human mammary tissue and human breast cancer incidence have been reported. We sought to estimate the prevalence of BLV DNA in breast cancer tissue samples in a rural state with an active dairy industry.

METHODS

We purified genomic DNA from 56 fresh-frozen breast cancer tissue samples (51 tumor samples, 5 samples representing adjacent normal breast tissue) banked between 2016 and 2019. Using nested PCR assays, multiple BLV tax sequence primers and primers for the long terminal repeat (LTR) were used to detect BLV DNA in tissue samples and known positive control samples, including the permanently infected fetal lamb kidney cell line (FLK-BLV) and blood from BLV positive cattle.

RESULTS

The median age of patients from which samples were obtained at the time of treatment was 60 (40-93) and all were female. Ninety percent of patients had invasive ductal carcinoma. The majority were poorly differentiated (60%). On PCR assay, none of the tumor samples tested positive for BLV DNA, despite having consistent signals in positive controls.

CONCLUSION

We did not find BLV DNA in fresh-frozen breast cancer tumors from patients presenting to a hospital in Vermont. Our findings suggest a low prevalence of BLV in our patient population and a need to reevaluate the association between BLV and human breast cancer.

Plasma-derived extracellular vesicle analysis and deconvolution enable prediction and tracking of melanoma checkpoint blockade outcome

Immune checkpoint inhibitors (ICIs) show promise, but most patients do not respond. We identify and validate biomarkers from extracellular vesicles (EVs), allowing non-invasive monitoring of tumor- intrinsic and host immune status, as well as a prediction of ICI response. We undertook transcriptomic profiling of plasma-derived EVs and tumors from 50 patients with metastatic melanoma receiving ICI, and validated with an independent EV-only cohort of 30 patients. Plasma-derived EV and tumor transcriptomes correlate. EV profiles reveal drivers of ICI resistance and melanoma progression, exhibit differentially expressed genes/pathways, and correlate with clinical response to ICI. We created a Bayesian probabilistic deconvolution model to estimate contributions from tumor and non-tumor sources, enabling interpretation of differentially expressed genes/pathways. EV RNA-seq mutations also segregated ICI response. EVs serve as a non-invasive biomarker to jointly probe tumor-intrinsic and immune changes to ICI, function as predictive markers of ICI responsiveness, and monitor tumor persistence and immune activation.

Abstract 4282: Deconvolution of plasma-derived exosomes for tracking and prediction of immunotherapy across multiple tissues

There is a critical need for robust and minimally invasive biomarkers for predicting and monitoring tumor progression and response to treatment. Transcriptomes of plasma-derived exosomes (PDEs) are suitable candidates to fulfill such a role, since they contain a subtranscriptome of their cell of origin, and, since nearly all cell types secrete exosomes, this allows for the potential monitoring of multiple cell types concurrently. However, a major issue preventing the widespread adoption of plasma-derived exosome as biomarkers is that observed plasma exosomes actually result from a mixture of exosomes from multiple cell types. This confounds detailed dissection and interpretation of putative plasma-derived exosomal biomarkers. To address this issue, we develop a two-component Bayesian deconvolution model to infer the tumor-derived and immune-derived exosomal contribution to the observed mixed plasma-derived exosome signal. Our model leverages transcriptomic information from 3 different sources: (1) paired patient bulk and plasma-derived exosomes, (2) paired cell-line tumor and cell-line tumor-derived exosomes, and (3) healthy control plasma-derived exosomes to learn gene-by-gene mixing fractions between tumor and immune components and the mapping from tumor to tumor-derived exosomes transcriptomic profiles. Using this information, we are able to further infer the patient-specific tumor-derived and immune-derived exosomal transcriptomic profiles for each gene. The outputs from our model enable us to derive tumor-specific and immune-specific exosomal biomarkers. We first show that our model is performant in an extensive set of in silico simulations. Next, we applied our model to transcriptomes collected prior to and during aPD1 immunotherapy treatment from a pilot cohort of N=44 patients (N=29 responders, N=15 nonresponders) with metastatic melanoma. Analysis of our deconvolved profiles yields novel and biologically informative immune-derived and tumor-derived exosomal biomarkers that predict immunotherapy success. Moreover, time-series analysis of the deconvolved profiles show that we are able to identify significantly different tumor and immune related genes whose time dynamics differ significantly between responders and nonresponders, suggesting that plasma-derived exosomes can enable longitudinal tracking of both immune and tumor components of immunotherapy response. Finally, we show that a more sophisticated extension of our deconvolution model is able to provide an estimate of global tumor fraction for each patient, potentially allowing us to infer tumor burden through plasma-derived exosomal transcriptomic signatures. Overall, our plasma-derived exosomal deconvolution model paves the way for more widespread usage of plasma-derived exosomes as a clinical monitoring prediction and monitoring tool.

Citation Format: Alvin Shi, Gyulnara Kasumova, Isabel Chien, Jessica Cintolo-Gonzalez, Dennie T. Frederick, Roman Alpatov, William A. Michaud, Deborah Plana, Ryan Corcoran, Keith Flaherty, Ryan Sullivan, Manolis Kellis, Genevieve Boland. Deconvolution of plasma-derived exosomes for tracking and prediction of immunotherapy across multiple tissues [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4282.

Abstract B087: HER-2/neu expression regulates the immune response and tumor senescence in breast cancer

Background: Over-expression of the receptor tyrosine kinase ErbB2 (HER-2) has been widely implicated in malignant transformation, cell survival, motility and invasion in breast cancers. Intermediate expression of HER-2 has been identified in luminal breast cancer stem cells. HER-2 over-expression down regulates major histocompatibility complex class I molecules (MHCI) expression in breast cancer cells.

Results: We investigated the expression of HER-2 in various HER-2 expressing cell lines and measured HLA A-2 MHC class I expression. High Her-2 expressing cell lines SKBR3 and SKOVA3 and intermediate expressing cell lines MCF7 demonstrated extremely low HLA A-2 expression, while low Her-2 expressing MDAMB231 demonstrated low HER-2 expression and high HLA A2 expression. Anti-HER-2 CD8 T cells recognize the latter cells but not high or intermediate expressing HER-2 expressing cells. Treatment of intermediate expressing cell lines but not high HER-2 expressing cells with interferon-gamma; (IFN- gamma) and TNF-alpha; result in markedly increased HLA A2 expression and 3 fold increase in CD8 T cell killing of the MCF7 cells. Treatment of high expressing HER-2 cells with trastuzumab but not lapatinib decreased HER-2 expression and combined with IFN-gamma; and TNF-alpha; result in increased HLA- A2 expression and dramatic increase in CD8 T cell recognition. In contrast, high and intermediate HER-2 expressing cells are sensitive to lysis and tumor senescence induction when treated with combinations of IFN-gamma; and TNF-alpha; in a dose dependent manner. Low HER-2 expressing cells are less sensitive to senescence induction.

Conclusions: In conclusion, our results establish a potential role for HER-2 in regulating the immune response against breast cancer and suggest that CD8 T cells are more effective in eliminating low and intermediate HER-2 expressing cells while CD4 T cell derived IFN-gamma; and TNF-alpha; together with trastuzumab may be more effective in eliminating high expressing HER-2 breast cancer cells and inducing tumor senescence preventing recurrence.

Citation Format: Cinthia Rosemblit, Jessica Cintolo-Gonzalez, Shuwen Xu, Brian J. Czerniecki. HER-2/neu expression regulates the immune response and tumor senescence in breast cancer. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research: Genetics, Biology, and Clinical Applications; Oct 3-6, 2013; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2013;11(10 Suppl):Abstract nr B087.