Liu, Yi

Abstract Triple-Negative Breast Cancer (TNBC) presents a significant clinical challenge due to its heterogeneity and lack of targeted treatment options, with chemotherapy and immunotherapy combinations currently serving as the main therapeutic strategy. Efforts to address TNBC heterogeneity have largely focused on classifying intrinsic cancer subtypes based on differential tumor mRNA expression, a strategy that has proven effective in hormone receptor-positive breast cancers but has yet to yield a clinically useful predictor of survival or treatment response in TNBC. We hypothesize that both the intrinsic characteristics of TNBC and the surrounding immune microenvironment influence treatment outcomes and that immune cell infiltration affects TNBC subtype classification and response variability. To explore this hypothesis, we compared the predictive and prognostic capabilities of cancer subtype-based (TNBC-type) gene signatures and immune cell deconvolution methods (CIBERSORT) within the same TNBC datasets. We found that immune cell abundance outperformed TNBC subtype-signatures and multicellular immune cell aggregates showed the highest performance of all. More specifically, aggregate immune cells associated with tertiary lymphoid structures and tumor associated macrophages/monocytes demonstrated statistically significant predictive value. These findings were confirmed in an independent cohort of 67 TNBC patients treated with neoadjuvant chemotherapy. Further, single-cell RNA sequencing analysis revealed that the predictive power of cancer-subtype could be partially explained by immune- and stromal features. Examination of single-cell resolution spatial transcriptomic data confirmed presence of TLS-like, TAM- and cancer-stromal niches within TNBC biopsy samples that were associated with treatment response. Overall, our results highlight that immune cell aggregates, which capture the spatial organization of the TME, outperform cell-type specific gene signatures in predicting TNBC outcomes. Our novel approach provides a robust framework for interpreting spatial relationships in bulk RNA-seq data, offering a pathway for reconciling past data with current advancements in spatial profiling technologies. This work paves the way for future studies to leverage the multi-cellular complexity of TNBC, enhancing diagnostic precision and facilitating the development of therapies that strategically modulate the tumor microenvironment for improved anti-cancer responses.

ABSTRACT Glioblastoma (GBM) is universally lethal despite decades of research to find effective treatments. This highlights the need to identify druggable targets essential for sustaining the malignant phenotype but dispensable for normal tissue. We propose that the enzyme α-tubulin acetyl transferase ( ATAT1 ) meets these criteria. ATAT1 acetylates α-tubulin at lysine 40, which increases microtubule stability and promotes microtubule-based transport. While ATAT1 knockout mice have only a very mild phenotype, ATAT1 suppression in GBM has multiple therapeutic effects by reducing tumor invasion, proliferation, and therapeutic resistance. These translate not only into improved survival with ATAT1 targeting by itself, but also into synergy when ATAT1 deletion is combined with FDA approved therapies. This study strongly supports our conclusion that ATAT1 is a promising therapeutic target in GBM.

Abstract Lung squamous cell carcinoma (LUSC) is a major histological subtype of lung cancer accounting for ~30% of all lung cancer diagnoses. LUSC patients suffer from poor therapeutic response, high relapse rate, and poor prognosis. A major reason for this bleak outcome is the lack of well characterized oncogenic drivers of LUSC. This has stalled the generation of relevant genetic pre-clinical mouse models amenable to studying LUSC tumorigenesis in vivo and developing targeted therapeutics to treat LUSC patients. Our group has identified concomitant 3q26 copy number gain (CNG) and TP53 loss as defining genetic alterations present in ~90% of LUSC tumors. Furthermore, we have identified three 3q26 oncogenes (PRKCI, ECT2 and SOX2) that genetically and biochemically collaborate to drive LUSC tumor formation. Coordinate overexpression of Prkci, Ect2 and Sox2, and loss of Trp53 in ex vivo cultures of lung basal stem cells (LBSCs; a potential cell of origin for LUSC) is both necessary and sufficient to transform these cells into orthotopic LUSC tumors in syngeneic mice. These findings indicate that 3q26 amplification and TP53 loss play a critical role in the initiation and progression of LUSC. Based on these data, we have developed the first autochthonous genetically engineered mouse model (GEMM) to study the role of 3q26 CNG in LUSC tumorigenesis in vivo. Our GEMM allows inducible overexpression of Prkci, Ect2, and Sox2 and knockout of Trp53 (PES/Trp53−/−) in lung tissue. Tumorigenesis will be initiated in PES/Trp53−/− mice using an established protocol to target transgene recombination to LBSCs in vivo. These mice will be assessed for tumor latency, survival, tumor burden, and metastatic potential. In related studies, we used bioinformatics analyses on primary LUSC tumors from the Cancer Genome Atlas’ database to identify 13 genes in addition to PRKCI, ECT2 and SOX2, whose expression is driven by 3q26 amplification. These genes were functionally characterized by assessing the effect of shRNA-mediated gene silencing on soft-agar growth of human H520 LUSC cells, a cell line that harbors 3q26 amplification. Our results revealed that knockdown of each of these genes independently resulted in a significant decrease in soft agar colony formation. We further assessed these genes through RT-qPCR mRNA expression profiling comparing PES/Trp53−/- transformed LBSCs to non-transformed LBSCs. These genes were significantly upregulated in PES/Trp53−/- transformed LBSCs, suggesting that they play important roles in LBSC transformation. Future work will further assess the molecular mechanisms by which these additional 3q26 genes contribute to LUSC cell transformation and assess the role of alternate cells of origin (Club and AT2) in 3q26-driven LUSC tumor formation using our PES/Trp53−/− GEMM. Citation Format: Kayleah M. Meneses, Capella Weems, Yi Liu, Verline Justilien, Nicole R. Murray, Alan P. Fields. Characterizing 3q26 copy number gain in lung squamous cell carcinoma through a novel genetically engineered mouse model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 27.

Abstract In glioblastoma (GBM), invasion and proliferation are reciprocally related—e.g., targeting one stimulates the other. Thus, effective therapy for GBM requires finding targets that drive both invasion and proliferation and which are druggable, ideally with FDA approved therapeutics. We find that the atypical protein kinase C isoform, PKCi meets these criteria. Using a human GBM tissue microarray, we find that PKCi protein expression fits a bimodal distribution, with >35% of GBMs showing high levels of PKCi expression. Genetic deletion of Prkci, the gene encoding mouse PKCi, impairs tumor invasion and proliferation both in vitro and in vivo, and significantly prolongs survival in an immunocompetent PDGF-driven orthotopic mouse model of GBM. PKCi can be selectively targeted with Auranofin, a small molecule PKCi inhibitor that has been FDA approved for treatment of inflammatory diseases. Like genetic deletion of Prkci Auranofin treatment significantly prolongs survival in our murine GBM model, and does so to a similar degree. Interestingly, analysis of a panel of human and murine GBM cells reveals that sensitivity to Auranofin inhibition of transformed growth directly correlates with expression of PKCi, indicating that PKCi expression profiling could serve as a predictive biomarker for responsiveness to Auranofin. However, genetically deleting or pharmacologically inactivating PKCi does not permanently arrest tumor growth, implying that GBM cells acquire mechanisms that allow them to compensate for the loss of this important signaling molecule. We are currently examining potential “escape” mechanisms through ‘omics-based approaches, which may enable us to enhance the therapeutic potential of Auranofin. Taken together, our results demonstrate that PKCi is a compelling therapeutic target for treatment of GBM that deserves further investigation.

Abstract Purpose: DNA topoisomerase inhibitors are commonly used for treating small-cell lung cancer (SCLC). Tyrosyl-DNA phosphodiesterase (TDP1) repairs DNA damage caused by this class of drugs and may therefore influence treatment outcome. In this study, we investigated whether common TDP1 single-nucleotide polymorphisms (SNP) are associated with overall survival among SCLC patients. Experimental Design: Two TDP1 SNPs (rs942190 and rs2401863) were analyzed in 890 patients from 10 studies in the International Lung Cancer Consortium (ILCCO). The Kaplan–Meier method and Cox regression analyses were used to evaluate genotype associations with overall mortality at 36 months postdiagnosis, adjusting for age, sex, race, and tumor stage. Results: Patients homozygous for the minor allele (GG) of rs942190 had poorer survival compared with those carrying AA alleles, with a HR of 1.36 [95% confidence interval (CI): 1.08–1.72, P = 0.01), but no association with survival was observed for patients carrying the AG genotype (HR = 1.04, 95% CI, 0.84–1.29, P = 0.72). For rs2401863, patients homozygous for the minor allele (CC) tended to have better survival than patients carrying AA alleles (HR = 0.79; 95% CI, 0.61–1.02, P = 0.07). Results from the Genotype Tissue Expression (GTEx) Project, the Encyclopedia of DNA Elements (ENCODE), and the ePOSSUM web application support the potential function of rs942190. Conclusions: We found the rs942190 GG genotype to be associated with relatively poor survival among SCLC patients. Further investigation is needed to confirm the result and to determine whether this genotype may be a predictive marker for treatment efficacy of DNA topoisomerase inhibitors. Clin Cancer Res; 23(24); 7550–7. ©2017 AACR.