Abstract 1010: LIG1 deletion predicts chemotherapy resistance, chromosomal instability, and poor prognosis in triple negative breast cancer

Introduction: Cytotoxic chemotherapy for sporadic Triple Negative Breast Cancer (TNBC) remains the standard of care and the recent approval for adjuvant PD1 therapy is not biomarker guided. Pathological complete response (pCR) is often not achieved and portends poor survival. Predictive markers for individual drugs have proven elusive.

Approach: Microscaled proteogenomics (MPG) was applied to snap-frozen TNBC clinical trial core needle biopsies obtained before treatment with carboplatin and docetaxel (WashU: NCT201404107 and BCM: NCT02544987). Clinical endpoints for discovery analysis were pathological complete response (pCR) and residual cancer burden (RCB). Standard non-parametric statistical tests were employed to identify proteogenomic features associated with these endpoints.

Results: Copy number aberrations (CNA) are a recurrent feature of TNBC and a potential driver of chemotherapy sensitivity. We therefore sought CNA with concordant changes at the mRNA and protein levels that also associate with pCR status. Genes located within a recurrent interstitial deletion at chromosomal location 19q13.3 were the most significantly down-regulated at mRNA and protein level in chemotherapy resistant cases. 19q13.3 encodes multiple DNA damage response (DDR) genes; however, only LIG1, a DNA ligase required for lagging strand synthesis and DNA repair, showed concordant changes at both the mRNA and protein level. In multiple independent TNBC data sets, LIG1 deletion was associated lack of pCR and poor metastasis-free survival. Additionally in the BrighTNess TNBC trial lower LIG1 mRNA levels were associated with increased chemotherapy resistance in the carboplatin containing arms (no pCR and residual cancer burden I-III; p=0.0008 and 0.003 respectively). In PDX-derived short-term cultures and PDXs treated with docetaxel or carboplatin, a specific association of carboplatin resistance with LIG1 deletion was observed. LIG1 depleted-tumors did not harbor elevated scores for homologous recombination defect signature, suggesting LIG1 loss is an orthogonal pathway for TNBC pathogenesis The high chromosomal instability index in LIG1 deletion tumors in our TNBC study was robustly reproduced in multiple datasets (including TCGA-BRCA ; Metastatic breast cancer project). LIG1 copy number deletion was also associated with poor progression free survival, and high chromosomal instability in multiple other cancers (including TCGA-​UCEC HR=2.23, TCGA-HNSC HR=1.46, TCGA-PRAD HR=2.07, TCGA- COAD HR=1.75 and TCGA-KIRP HR=4.00).

Conclusion: Deletion of LIG1 is associated with chromosomal instability in TNBC and occurs in tumors without genomic evidence for defects in homologous recombination. Other clinical features of LIG1 deleted TNBC and how LIG1 loss may cause chromosomal instability and tumorigenesis will be discussed.

Citation Format: Meenakshi Anurag, Eric Jaehnig, Jonathan Lei, Beom-Jun Kim, Anh Minh Tran Huynh, Yongchao Dou, Tanmayi Vashist, Erik Bergstrom, Xuxu Gou, Viktoriya Korchina, Donna Marie Muzny, Kristen Otte, Harshavardhan Doddapaneni, Lacey Dobrolecki, Gloria Vittone Echeverria, Bora Lim, Mothaffar Rimawi, Karsten Krug, Ian Hageman, Henry Rodriguez, Ana I. Robles, Tara Hiltke, Kent Osborne, Michael Gillette, George Miles, Steven Carr, Michael T Lewis, Bing Zhang, Foluso Ademuyiwa, Shankha Satpathy, Matthew J. Ellis. LIG1 deletion predicts chemotherapy resistance, chromosomal instability, and poor prognosis in triple negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1010.

Abstract 2877: LUZP1 is an understudied transcriptional regulator in triple negative breast cancer (TNBC)

Introduction: TNBC is associated with poorer prognosis compared to other types of breast cancer due to poorly understood aggressive metastatic behavior. Proteomic profiling prioritized Leucine-Zipper Protein 1 (LUZP1) as an understudied TNBC-specific protein from an analysis of breast cancer patient-derived xenografts (PDXs) [PMC5379071].

Approach: RNA-seq data and isobaric tags for relative and absolute quantitation (iTRAQ) data from 16 PDXs were used to identify differentially expressed genes in basal-like and claudin-low breast cancers, compared to luminal and HER2-enriched subtypes. Multiple datasets (DepMap, METABRIC, and TCGA) were used to validate the enrichment of LUZP1 in TNBC. T-test was applied to identify differential genes/proteins. Pearson correlation analysis was used to identify RNAs that are correlated with LUZP1 protein level in CTPAC proteogenomic clinical sample data [PMC5102256 and Cell in press]. Gene Set Enrichment Analysis (GSEA) was used to identify enriched pathways. Cell fractionation was used to determine the subcellular expression of LUZP1. qPCR was used to validate differential expression observed in RNA-seq.

Results: Leucine-Zipper Protein 1 (LUZP1) was differentially elevated in basal-like and claudin-low PDX models versus luminal and HER2-enriched at the mRNA and protein levels across 16 PDXs. Furthermore, LUZP1 mRNA was significantly enriched in TNBCs, relative to luminal and HER2-enriched subtypes, in breast cancer cell lines (data from DepMap), and human breast tumors (data from METABRIC and TCGA). LUZP1 has three putative nuclear localization signals and three leucine-zipper motifs, thought to mediate its protein dimerization and DNA-binding properties. Fractionation of TNBC cells showed that LUZP1 was predominately present in the nucleus. RNA-sequencing of control and MDA-MB-231 LUZP1 knockdown cells revealed that several extracellular matrix (ECM)-related pathways and epithelial-to-mesenchymal transition (EMT) were regulated by LUZP1. In particular, expression of migration, invasion, and metastasis genes such as matrix metalloproteinases (MMPs), Bone Morphogenetic Protein 2 (BMP2), and Transforming Growth Factor Beta 2 (TGFB2) were found to be LUZP1 regulated. Additionally, in CPTAC breast cancer proteogenomic data, LUZP1-correlated proteins and transcripts were enriched in ECM-related pathways and EMT, confirming the pathophysiological relevance of the cell-line knock-down data.

Conclusion: LUZP1 is a novel TNBC-enriched protein in breast cancer PDXs, cell lines, and human tumors data. Gene silencing experiments demonstrated that LUZP1 transcriptionally regulates metastasis-related genes, and thus may drive a transcriptional program responsible for invasion, metastasis and EMT in TNBC. Functional data will be presented.

Citation Format: Junkai Wang, Doug Chan, Beom-Jun Kim, Gloria V. Echeverria, Eric Jaehnig, Bing Zhang, Matthew J. Ellis. LUZP1 is an understudied transcriptional regulator in triple negative breast cancer (TNBC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2877.

Abstract 5118: Proteogenomics characterization of HPV-negative head and neck squamous cell carcinomas

Patients with head and neck squamous cell carcinomas (HNSCCs) are treated with surgery, radiation, chemotherapy, and limited targeted therapies. Compared to human papillomavirus (HPV)-positive HNSCCs, HPV-negative cases have worse treatment response and prognosis and represent an unmet clinical need. We performed comprehensive proteogenomic characterization of tumor specimens, matched normal adjacent tissues (NATs), and blood samples from 109 HPV-negative HNSCC patients. This cohort is dominated by tumors from oral cavity (45, 41%) and larynx (49, 45%). Somatic mutation and somatic copy number analyses validated previously reported genomic aberrations in HPV-negative HNSCC. Proteomics analysis linked p53 loss of heterozygosity to increased expression of EPCAM, a stemness marker. Additionally, FAT1 truncation mutations were associated with increased expression of proteins involved in keratinization, a key feature of SCC differentiation. Deletions of 3p and 9p led to the loss of genes encoding p16, chemokine receptors, and interferon/JAK/STAT signaling pathway proteins, whereas amplifications of 3q and 11q led to overexpression of proteins involved in cell proliferation and anti-apoptosis pathways. Comparative analysis of tumor and NAT proteomes and phosphoproteomes identified putative diagnostic biomarkers and druggable targets, and proteogenomic integration further identified putative neoantigens. Tumor site-specific characterization associated epigenetic silencing of neurofilaments with laryngeal but not oral cavity SCC. Protein targets of FDA approved or investigational drugs for HNSCC treatment showed high inter-tumor heterogeneity in their protein abundances. DNA copy number and RNA expression level were good surrogates of protein abundance for some targets, such as EGFR and PD-L1, but they failed to reflect protein levels or kinase activities for other targets, such as MMP9 and MTOR. Thus, there is a critical need for protein biomarker-driven treatment stratification. Deconvolution of bulk tumor gene expression data revealed an immune-hot subgroup and an immune-cold subgroup. Immune-hot tumors broadly overexpressed multiple immune checkpoints including PD-L1, IDO1, and CTLA4, underscoring the necessity of combination immune checkpoint inhibition to improve treatment efficacy. Immune-cold tumors were characterized by smoking, chromosomal instability, and activation of the CDK4/6-pRb axis, suggesting they could be targeted by CDK4/6 inhibitors. We also noted that EGFR-amplified tumors frequently harbor copy number aberrations of downstream signaling components of the EGFR pathway. This may explain the low response rate of EGFR-amplified tumors to EGFR inhibitors, and targeting multiple pathway components, including EGFR, PIK3CA and STAT3, may be required for these tumors. In summary, our integrative proteogenomic characterization revealed multiple novel insights into the pathogenesis and treatment of HPV-negative HNSCCs.

Citation Format: Chen Huang, Lijun Chen, Yize Li, Sara Savage, Michael Schnaubelt, Felipe V. Leprevost, Marcin Cieslik, Yongchao Dou, Bo Wen, Jonathan T. Lei, Kai Li, Eric Jaehnig, Zhiao Shi, Meenakshi Anurag, Jianbo Pan, Yingwei Hu, Rodrigo V. Eguez, David J. Clark, Matthew Wyczalkowski, Saravana M. Dhanasekaran, Chandan Kumar, Antonio Colaprico, Karsten Krug, Michael Gillette, D. R. Mani, Seungyeul Yoo, Jiayi Ji, Xiaoyu Song, Weiping Ma, Xi Steven Chen, Alex Pico, Nathan J. Edwards, Scott D. Jewell, Mathangi Thiagarajan, Emily S. Boja, Henry Rodriguez, Andrew Sikora, Pei Wang, Matthew Ellis, Gilbert S. Omenn, Li Ding, Alexey I. Nesvizhskii, Adel K. EI-Naggar, Daniel W. Chan, Hui Zhang, Bing Zhang, Clinical Proteomic Tumor Analysis Consortium. Proteogenomics characterization of HPV-negative head and neck squamous cell carcinomas [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5118.

Abstract 4385: Proteogenomics-driven synthetic lethality discovery to predict targetable protein dependencies induced by somatic deletions

Computational prediction of synthetic lethality has been shown as a promising approach to identify therapeutic vulnerabilities in many cancer types but has been limited to using genomics and transcriptomics data for discovery. Recent advancements on integrating mass spectrometry (MS)-based proteomics with genomics and transcriptomics in cancer research have produced proteogenomics datasets on large tumor cohorts, enabling the integration of proteomics data into synthetic lethality discovery. This is particularly attractive for tumors driven by loss-of-function alterations such as somatic deletions. Although deletions are challenging to target themselves, they may induce targetable protein dependencies, and this relationship can be identified through computational prediction of synthetic lethality. Here, we performed an unbiased discovery of such synthetic lethal interactions by identifying protein targets of drugs for which under-expression is observed significantly less than expected by chance with gene deletions using proteogenomics data from a breast cancer cohort with 105 tumors. We found many significant pairs uniquely driven by either protein under-expression (18,897 pairs) or mRNA under-expression (42,754 pairs) while only 5% (3,042 pairs) were supported by both protein and mRNA measurements. To systematically evaluate candidate synthetic lethal pairs, an AUROC analysis was performed using publicly available drug response data from breast cancer cells. Results showed synthetic lethal relationships supported by both protein and mRNA-based analyses were substantially more predictive of drug response (AUC = 81%) than protein alone (AUC = 65%) or mRNA alone (AUC = 61%). Despite having comparable AUCs, protein-based analysis showed much higher sensitivity than mRNA-based analysis when limiting false positive rate to less than 10%. An example of a synthetic lethal pair supported by both protein and mRNA-based analyses include tumors with low AURKA protein/mRNA and PARP2 deletions, which were significantly under-represented in the proteogenomics dataset (p = 0.003). Interestingly, these tumors were enriched for triple-negative breast tumors (p = 0.001), a type of breast cancer that lacks biomarkers to guide clinical treatment. This finding suggests AURKA as a putative dependency in triple-negative tumors with PARP2 deletion as a biomarker. Taken together, these results demonstrate that a multi-omics approach using proteomics to complement transcriptomics along with genomic changes may better predict therapeutic vulnerabilities in breast cancer with driver gene deletions than using proteomics or transcriptomics alone. As genomic testing has become more widely implemented as part of precision oncology programs, our approach to identifying protein dependencies induced by loss-of-function genomic alterations may provide new treatment opportunities for many patients with breast cancer or other tumor types.

Citation Format: Jonathan T. Lei, Eric Jaehnig, Bing Zhang. Proteogenomics-driven synthetic lethality discovery to predict targetable protein dependencies induced by somatic deletions [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4385.

Abstract GS2-05: Microscaled proteogenomic methods for precision oncology

Cancer proteogenomics combines genomics, transcriptomics and mass spectrometry-based proteomics to gain insights into cancer biology and treatment responsiveness. While proteogenomics analyses have already shown great potential to deepen our understanding of cancer tissue complexity and signaling, how a patient’s tumor changes upon treatment has largely been the province of genomics. This is due to technical difficulties associated with doing proteogenomic analysis on clinic-derived core-needle biopsies. To address this critical need, we have developed a “microscaled” proteogenomics approach for tumor-rich OCT-embedded core needle biopsies. Tissue-sparing specimen processing (“Biopsy Trifecta EXTraction”, BioTExt) and microscaled proteomics (MiProt) methodologies allowed generation of deep-scale proteogenomics datasets, with copy number and transcript information for >20,000 genes and mass spectrometry-based identification and quantification of nearly all expressed proteins in a tumor (>10,000 proteins) and more than >20,000 phosphosites starting with just 25 micrograms of protein per sample. In order to understand the capabilities and limitations our our approach relative to more conventional deepscale proteomics requiring >10X more starting material, we compared preclinical patient derived xenograft (PDX) models at conventional scale with data obtained by core-needle biopsy of the same tissues. Comparable depth and biological insights were obtained from the cores relative to surgically resected tumors. As a proof-of-concept for implementation in clinical trials, we applied microscaled proteogenomic methods to a small-scale clinical study where biopsies were accrued from patients with ERBB2+ locally advanced breast cancer before and 48 to 72 hours after the first dose of neoadjuvant Trastuzumab-based chemotherapy. Multi-omics comparisons were conducted between samples associated with residual disease versus samples associated with complete pathological response. Integrative, microscaled proteogenomic analyses efficiently diagnosed the molecular bases of diverse candidate treatment resistance mechanisms including: 1) absence of ERBB2 amplification (false-ERBB2+); 2) insufficient ERBB2 activity for therapeutic sensitivity despite ERBB2 amplification (pseudo-ERBB2+); 3) resistance features in true-ERBB2+ cases including androgen receptor signaling, mucin expression and an inactive immune microenvironment; 4) lack of acute phospho-ERBB2 down-regulation in non-pCR cases. In summary, we have developed a robust proteogenomics pipeline well suited for large-scale cancer clinical studies to identify potential resistance mechanism in patients. We conclude that microscaled cancer proteogenomics could improve diagnostic precision in the clinical setting.

Citation Format: Shankha Satpathy, Eric Jaehnig, Krug Karsten, Beom-Jun Kim, Alexander Saltzman, Doug Chan, Kimberly Holloway, Meenakshi Anurag, Chen Huang, Purba Singh, Ari Gao, Noel Namai, Yongchao Dou, Bo Wen, Suhas Vasaikar, David Mutch, Mark Watson, Cynthia Ma, Foluso Ademuyiwa, Mothaffar Rimawi, Jeremy Hoog, Samuel Jacobs, Anna Malovannaya, Terry Hyslop, D.R Mani, Charles Perou, George Miles, Bing Zhang, Michael Gillette, Steven Carr, Matthew Ellis. Microscaled proteogenomic methods for precision oncology [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr GS2-05.

Abstract TS1-2: Proteogenomic Landscape of Prospectively Collected Breast Cancer

A persistent central deficiency in our knowledge of cancer concerns how genomic changes drive the proteome and phosphoproteome to execute phenotypic characteristics. Furthermore increasing evidence implicating epigenetic and post-translational changes in cancer biology reinforce the notion that molecular profiles based on nucleic acids are incomplete and are critically complemented by analyses of proteins and their post-translational modifications. We present the first integrated proteogenomic study on a prospectively collected breast cancer cohort, and provide new insights including on taxonomy, metabolic dependencies, and immune milieu. 122 invasive ductal breast cancer samples were collected under the auspices of the National Cancer Institute’s Clinical Proteomics Tumor Analysis Consortium using rigorous protocols to minimize ischemic time and other pre-analytical variability. Samples underwent comprehensive genomic and proteomic characterization, providing whole exome, whole genome, copy number, RNAseq, global proteome, phosphoproteome, and acetylome data. Multi-omics clustering by nonnegative matrix factorization revealed basal-, luminal A-, and HER2-enriched clusters, as well as a combined luminal A/B cluster. Luminal A and A/B clusters were distinguished by differential expression of cytoskeletal signatures possibly driven by YAP1 overexpression and hyper-phosphorylation in the luminal A subset. Kinase outlier analysis revealed luminal A enrichment of PEAK1, an atypical kinase that regulates YAP1 expression. PTPN2, recently shown to synergize with anti-PD1 therapy, was an outlier in basal tumors, suggesting therapeutic opportunities in that difficult-to-treat subtype. Acetylation plays a dominant role in mitochondrial metabolism, and downregulation of deacetylase SIRT3 in basal and HER2-enriched samples was associated with upregulation of TCA cycle- and amino acid metabolism-related proteins suggesting metabolic dependencies that could be exploited. Immunological subtyping of the breast cohort identified immune-cold, immune-hot, immune-excluded and interferon-independent clusters associated with distinct patterns of tumor-infiltrating lymphocytes. Basal tumors generally overexpressed PDL1 relative to other subtypes, whereas the newly described immuno-oncology target SIGLEC15 was overexpressed in luminal tumors. While these and other analyses are intended to provide new insights into breast cancer biology and facilitate testable therapeutic hypotheses, the larger purpose of the program is to provide a resource to the breast cancer and broader scientific communities. To facilitate this, these and previously published data will be integrated to provide a sample set of 199 proteogenomically characterized breast cancers for further exploration.

Citation Format: M Gillette, K Krug, S Satpathy, E Jaehnig, A Karpova, K Clauser, L Tang, L Blumenberg, R Kothadia, K Ruggles, B Zhang, L Ding, P Mertins, DR Mani, M Ellis, S Carr. Proteogenomic Landscape of Prospectively Collected Breast Cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr TS1-2.

Multiple determinants contribute to the virulence of HSV ocular and CNS infection and identification of serine 34 of the US1 gene as an ocular disease determinant

PURPOSE

The virulence of any given strain of herpes simplex virus (HSV) is probably due to the effects of the constellation of genes in that strain and how they act in concert to promote disease. The goal of this work was to develop a system to identify and study the role of multiple genes in HSV disease.

METHODS

Mixed ocular infection with HSV-1 strains CJ394 and OD4 yield recombinants with increased ocular and central nervous system (CNS) virulence. Clones and subclones of the CJ394 genome were cotransfected with intact OD4 DNA into Vero cells, the transfection pools were inoculated into BALB/c mouse eyes, and disease severity was scored. Fragments transferring increased ocular or CNS disease were sequenced. Site-directed mutagenesis was used to revert one mutation to wild type.

RESULTS

Five of the determinants (UL9, -33, -41, and -42 and US1) increased ocular disease when transferred singly. Transfer of the UL36/37 determinant increased both ocular and CNS disease. Transfer of the UL41 and -42 genes increased mortality and a combination of the UL36/37, -41, and -42 determinants increased virulence further. Reversion of the S34A change in the OD4 US1 gene to wild type restored ocular virulence.

CONCLUSIONS

Multiple HSV genes can operate to increase virulence. The UL9, -33, -36/37, and -42 genes have not previously been identified as virulence determinants. The UL41 and US1 genes are known to affect disease, but the changes identified had not been described. Multiple novel mutations were found in the OD4, UL9, UL36, and US1 genes, and we showed that S34 in the US1 gene is essential in ocular disease.