Reconstructing tumor history in breast cancer: signatures of mutational processes and response to neoadjuvant chemotherapy⋆

BACKGROUND

Different endogenous and exogenous mutational processes act over the evolutionary history of a malignant tumor, driven by abnormal DNA editing, mutagens or age-related DNA alterations, among others, to generate the specific mutational landscape of each individual tumor. The signatures of these mutational processes can be identified in large genomic datasets. We investigated the hypothesis that genomic patterns of mutational signatures are associated with the clinical behavior of breast cancer, in particular chemotherapy response and survival, with a particular focus on therapy-resistant disease.

PATIENTS AND METHODS

Whole exome sequencing was carried out in 405 pretherapeutic samples from the prospective neoadjuvant multicenter GeparSepto study. We analyzed 11 mutational signatures including biological processes such as APOBEC-mutagenesis, homologous recombination deficiency (HRD), mismatch repair deficiency and also age-related or tobacco-induced alterations.

RESULTS

Different subgroups of breast carcinomas were defined mainly by differences in HRD-related and APOBEC-related mutational signatures and significant differences between hormone-receptor (HR)-negative and HR-positive tumors as well as correlations with age, Ki-67 and immunological parameters were observed. We could identify mutational processes that were linked to increased pathological complete response rates to neoadjuvant chemotherapy with high significance. In univariate analyses for HR-positive tumors signatures, S3 (HRD, P < 0.001) and S13 (APOBEC, P = 0.001) as well as exonic mutation rate (P = 0.002) were significantly correlated with increased pathological complete response rates. The signatures S3 (HRD, P = 0.006) and S4 (tobacco, P = 0.011) were prognostic for reduced disease-free survival of patients with chemotherapy-resistant tumors.

CONCLUSION

The results of this investigation suggest that the clinical behavior of a tumor, in particular, response to neoadjuvant chemotherapy and disease-free survival of therapy-resistant tumors, could be predicted by the composition of mutational signatures as an indicator of the individual genomic history of a tumor. After additional validations, mutational signatures might be used to identify tumors with an increased response rate to neoadjuvant chemotherapy and to define therapy-resistant subgroups for future therapeutic interventions.

Abstract P2-09-04: Identification of a neoantigen targeted by tumor-infiltrating lymphocytes in a patient with Her2+ breast cancer

Background: Recent studies have demonstrated that the number of tumor infiltrating lymphocytes (TILs) positively correlates with outcome and response to chemotherapy in patients with HER2+ and Triple-Negative Breast Cancer (TNBC). Furthermore, first studies of immune-checkpoint inhibitors showed promising results in those patients. However, the targets of those TILs remain unknown. Neoantigens, which arise in the process of tumorigenesis, appear as potential targets. They can elicit high avidity, tumor-specific T-cell responses. Thus, it is the aim of our study to ascertainif these TILs are directed against tumor-specific mutations.

Methods: TILs from breast cancer biopsies taken at the time point of diagnosis were expanded by unspecific stimulation. Additionally, we used the Gentle Macs Dissociator in combination with flow cytometry to investigate the number of TILs in the tumor tissue. Furthermore, we performed whole-genome sequencing of tumor tissue and as reference autologous blood cells to determine tumor-specific mutations. Mutations leading to a non-synonymous amino acid change were analyzed for RNA expression of the encoding gene as well as to determine potential neoantigens. Neoantigens were evaluated for their potential binding to the patient's specific HLA molecules. Peptides for potential neoantigens were synthesized, loaded onto autologous antigen presenting cells (APCs) and cocultured with TILs. All IFNγ producing T-cells were clonally expanded and retested for peptide specificity to identify neoantigen specific T-cell clones.

Results: Our flow cytometric analysis of the tumor biopsy for more than 300 patients showed higher frequencies of TILs in TNBC as compared to other types of breast cancer or patients without malignancy. Screening for neoantigen specific T-cells in one patient led to identification of three peptide-specific CD4+ T-cell clones isolated from HER2+ breast cancer tissue taken at the time point of diagnosis. All T-cell clones specifically recognized the same tumor-specific mutation and not the wildtype counterpart. Furthermore, we demonstrated that these T-cell clones also recognized the endogenously expressed mutated antigen. This verified the ability of processing and presentation of the respective protein. Interestingly, we could also isolate a T-cell clone recognizing the same neoantigen in the resected tumor tissue after neoadjuvant therapy. Based on CDR3 sequencing we could prove that the four T-cell clones represented individual clones. This confirms the polyclonal nature of the immune response. Moreover, we showed that the same neoepitope was presented in two different HLA restriction molecules of the patient with three of the clones recognizing it in HLA-DPB1*0401 and one in HLA-DPB1*0201. These results further underline the immunogenicity of this neoantigen.

Conclusion: In conclusion, our data demonstrate tumor-specificity of TILs in a patient with HER2+ breast cancer. Furthermore, we show the feasibility to identify individual cancer specific T-cell targets in breast cancer patients. These results may contribute to the development of targeted patient-specific immunotherapies in the future.

Citation Format: Reimann H, Nguyen A, Hübner H, Erber R, Bausenwein J, Van der Meijden ED, Lux MP, Jud S, Griffioen M, Rauh C, Sanborn JZ, Benz SC, Rabizadeh S, Beckmann MW, Mackensen A, Rübner M, Fasching PA, Kremer AN. Identification of a neoantigen targeted by tumor-infiltrating lymphocytes in a patient with Her2+ breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P2-09-04.

Abstract P2-04-26: Identifying patient-specific neoepitopes for cell-based and vaccine immunotherapy across breast cancer classifications reveals rarely shared recurrent neoepitopes

Introduction: Targeted therapies for breast cancers such as trastuzumab and everolimus have durable clinical benefits for patients that express the relevant biomarkers (HER2 and mTOR respectively). Triple negative breast cancer patients lack these biomarkers and are left with few options. Recent advances in immunotherapy agents against PD-1/CTLA4 for patients with melanoma have yielded amazing clinical benefits for a subset of patients and may have similar results in breast cancer patients, but again the vast majority of patients still undergo disease progression. We analyzed whole genome sequencing (WGS) and RNA sequencing data from The Cancer Genome Atlas (TCGA) to identify neoepitopes among breast cancer patients that could be used to develop next-generation, patient-specific cancer immunotherapies. Neoepitopes are tumor specific markers that arise from mutations acquired from cancer and may represent a path to targeted therapies even in triple negative breast cancers.

Results: We analyzed 99 breast cancer patients from TCGA, containing a mixture of PR+/HER2+/ER+ and TNBC classifications. These breast cancer patient samples were selected by the availability of whole genome sequencing (WGS) data, RNA-sequencing data as well as clinical outcome data. We identified an average of 680 potential neoepitopes per patient based solely on WGS data. To further refine and select high quality neoepitopes we restricted these neoepitopes based on gene expression yielding an average of 304 expressed neoepitopes per patient. We predicted each patient's HLA typing using only omics data, which we then used to predict HLA-expressed neoepitope binding analysis resulting in an average of 11 high-quality tumor specific neoepitopes per patient. We identified few recurrent neoepitopes that were bound and expressed, indicating the need for a personalized medicine approach.

Conclusions: Within the TCGA dataset, the majority of neoepitopes among patients with breast cancer were unique to each patient. Rarely within subsets of breast cancers such as HER2+, we identify neoepitopes that are shared between patients. For breast cancer patients who do not respond to targeted therapies, high-throughput identification of neoepitopes could serve as the basis for the development of next-generation, patient-specific immunotherapies.

Citation Format: Nguyen A, Sanborn JZ, Vaske CJ, Rabizadeh S, Niazi K, Soon-Shiong P, Benz SC. Identifying patient-specific neoepitopes for cell-based and vaccine immunotherapy across breast cancer classifications reveals rarely shared recurrent neoepitopes [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P2-04-26.

Abstract P6-04-14: Integrating whole genome sequencing data with RNAseq, pathway analysis, and quantitative proteomics to determine prognosis after standard adjuvant treatment with trastuzumab and chemotherapy in primary breast cancer patients

Background: Despite improvements in the treatment of HER2+ breast cancer (BC), almost all patients (pts) progress in the metastatic setting. Three examples of resistance mechanisms are: PI3K mutations, lack of ADCC, or low expression of HER2. We recently showed that among 237 pts who had HER2 amplifications, 49% had normal or low levels of HER2 RNA. In addition, quantification of HER2 protein by selected reaction monitoring mass spectrometry (SRM-MS) accurately predicted HER2 expression status compared with IHC (3+)/ISH (≥2.0). Here we report a comprehensive panomic approach that integrates whole genome sequencing (WGS), RNASeq, quantitative proteomics, and pathway analysis to determine associations between tumor molecular profiles and prognosis among HER2+ pts.

Methods: Matched tumor-normal samples (FFPE tumors and blood) were obtained from 58 pts with HER2+ BC who had received standard adjuvant chemotherapy and trastuzumab. Pts were divided into 2 groups: those who had no recurrence after 5 years and those who had developed metastases. The HER2 status of each pt was previously determined using IHC/FISH. Samples underwent WGS and RNASeq according to NantOmics CLIA-approved assay specifications. WGS data were processed using Contraster; RNASeq data confirmed the presence of gene mutations and was used to identify mutational and transcript abundance. PARADIGM was used to reveal associations between gene mutations and pathway levels. SRM-MS was used for proteomics analysis of a panel of 53 proteins. Tumor areas from FFPE tissue sections were analyzed after laser microdissection. Absolute protein quantitation was accomplished through simultaneous detection of endogenous target and synthetic labeled heavy peptide identical to analytical targets. Genetic alterations in germline and tumor DNA were compared in pts with vs without recurrence.

Results: There was no statistically significant difference in the mean concentration of HER2 in the tumors of pts with vs without recurrence: 2.34 fmol/µL vs 2.56 fmol/µL. Other analyzed proteins did not appear to be associated with recurrence; however, expected correlations between pt and tumor characteristics and protein expression were found. With regard to clinically relevant mutations, we found one germline BRCA2 mutation in a pt with no family history of this mutation. The most commonly found somatic mutations were in TP53 (11 pts), AMBRA1 (11 pts), MORC4 (10 pts), SETD2 (8 pts), CDC27 (6 pts), BCLAF1 (5 pts), ZNF479 (4 pts) , PIK3CA (3 pts), PIK3R1 (3 pts), RUNX1 (3 pts), and GATA3 (3 pts).

Conclusion: Whereas HER2 expression status was predictive of OS and PFS in pts treated with trastuzumab (Nuciforo et al. Mol Onc. 2015), in this small exploratory study of HER2+ BC pts, HER2 expression status was not predictive of recurrence. To better understand the molecular mechanisms driving recurrence beyond HER2 status alone, genomic sequencing may define a signature of recurrence after anti-HER2 therapy.

Citation Format: Benz SC, Rabizadeh S, Cecchi F, Beckman MW, Brucker SY, Hartmann A, Golovato J, Hembrough T, Janni W, Rack B, Sanborn JZ, Schneeweiss A, Vaske CJ, Soon-Shiong P, Fasching PA. Integrating whole genome sequencing data with RNAseq, pathway analysis, and quantitative proteomics to determine prognosis after standard adjuvant treatment with trastuzumab and chemotherapy in primary breast cancer patients. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P6-04-14.

Glioblastoma adaptation traced through decline of an IDH1 clonal driver and macro-evolution of a double-minute chromosome

BACKGROUND

Glioblastoma (GBM) is the most common malignant brain cancer occurring in adults, and is associated with dismal outcome and few therapeutic options. GBM has been shown to predominantly disrupt three core pathways through somatic aberrations, rendering it ideal for precision medicine approaches.

METHODS

We describe a 35-year-old female patient with recurrent GBM following surgical removal of the primary tumour, adjuvant treatment with temozolomide and a 3-year disease-free period. Rapid whole-genome sequencing (WGS) of three separate tumour regions at recurrence was carried out and interpreted relative to WGS of two regions of the primary tumour.

RESULTS

We found extensive mutational and copy-number heterogeneity within the primary tumour. We identified a TP53 mutation and two focal amplifications involving PDGFRA, KIT and CDK4, on chromosomes 4 and 12. A clonal IDH1 R132H mutation in the primary, a known GBM driver event, was detectable at only very low frequency in the recurrent tumour. After sub-clonal diversification, evidence was found for a whole-genome doubling event and a translocation between the amplified regions of PDGFRA, KIT and CDK4, encoded within a double-minute chromosome also incorporating miR26a-2. The WGS analysis uncovered progressive evolution of the double-minute chromosome converging on the KIT/PDGFRA/PI3K/mTOR axis, superseding the IDH1 mutation in dominance in a mutually exclusive manner at recurrence, consequently the patient was treated with imatinib. Despite rapid sequencing and cancer genome-guided therapy against amplified oncogenes, the disease progressed, and the patient died shortly after.

CONCLUSION

This case sheds light on the dynamic evolution of a GBM tumour, defining the origins of the lethal sub-clone, the macro-evolutionary genomic events dominating the disease at recurrence and the loss of a clonal driver. Even in the era of rapid WGS analysis, cases such as this illustrate the significant hurdles for precision medicine success.

Abstract P2-06-05: Single-cell RNA sequencing of paclitaxol-treated breast cancer cell lines to find individual cell response

Cancer treatments act on a population of cells, each of which may experience different individual responses to treatment. Such differential response will result in resistance to treatment even if a majority of cancerous cells are eliminated. To examine differential cell response, we simultaneously profiled the gene expression and mutation spectrum of individual cells from the MDAMB231 cell line using next generation sequencing of isolated RNA. A total of 23 transcriptomes were characterized from paclitaxel-treated and paclitaxel-surviving cells. We found significant different changes in mutation rates between paclitaxel treated cells, with a dose-dependent increase in single nucleotide changes in RNA in paclitaxel-treated cells. Cells undergoing exposure to paclitaxel also showed higher pathway activity in SRC, as well as an integrin switch from ITGB1 to ITGB3. In contrast, cells that survived a high dose of paclitaxel showed an insignificant number of single nucleotide changes, suggesting that these cells either evaded initial paclitaxel exposure or were better able to repair the effects of paclitaxel exposure. Despite the RNA sequence similarity between surviving and untreated cells, there were changes in gene expression and pathway activities including higher PI3K activity. Paclitaxel-surviving cells also showed activation of pathways associated with higher proliferation.

Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P2-06-05.

P3-06-07: Integrated Genomic and Pathway Analysis Reveals Key Pathways across Breast Subtypes

Cancer is a disease of genomic perturbations that lead to dysregulation of multiple pathways within the cellular system. While common pathways are believed to be shared within specific cancer types, the mechanisms behind why particular patients respond differently to treatment is not well understood. Genomics studies such as The Cancer Genome Atlas (TCGA) and Stand Up To Cancer (SU2C) attempt to address this issue by collecting large-scale whole-genome measurements of mRNA expression, DNA copy number, and epigenetic features. Common analysis of these measurements integrates data across multiple samples to distinguish signal from noise. However, serious challenges remain in identifying genomic features and pathways significant for prognosis and clinical treatment classifications.

We have created the Five3 Analysis Pipeline to streamline discovery of individual samples’ mutations, small indels, copy number alterations, genome rearrangements, expression changes, and resulting pathway activities. This pipeline is capable of processing and integrating data from both next generation sequencing and microarray platforms in the analysis of single or multiple tumor samples. Our sequence analysis corrects for both tumor sample impurity and germline variation to accurately identify somatic mutations present in the tumor. Our pathway analysis incorporates gene copy number, mutations, expression, and promoter methylation on a superimposed pathway constructed from several curated pathway databases in a sample-specific manner.

By applying this pipeline to the TCGA breast cancer datasets, we recapitulate established breast subtypes at a pathway-dependent level. For example, basal tumors appear enriched for proliferation pathways compared to luminal samples within this cohort. Expanding the pathway analysis to include TCGA lung cancer samples, we find similar subnetworks activated between basal and squamous lung and between luminal and lung adenocarcinomas. This hints at similar genomic mechanisms for these subtypes independent of tissue of origin. Finally, by analyzing genomic alterations across all breast cancers we see mutational clusters in PIK3CA that correspond with publicly-available hotspots [1]. As suggested by previous reports [2], we find that samples with mutations clustered in exon 10 exhibit differential pathway activities relative to those samples with mutations clustered in exon 21, independent of subtype and TP53 mutation status. These results show the power of this integrated genomic platform in elucidating pathway signatures and the need to consider cross cancer analyses to identify shared tumorigenic mechanisms that may suggest common therapeutic targets.

[1] Forbes, S.A et al. COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer. Nucl. Acids Res. (2011) 39: D945-D950

[2] Vasudevan KM et al. AKT-independent signaling downstream of oncogenic PIK3CA mutations in human cancer. Cancer Cell 2009 Jul.;16(1):21–32.

Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P3-06-07.

UCSC cancer genomics browser

Abstract #2022

As experimental techniques for a comprehensive survey of the cancer landscape mature, there is a great demand in the cancer research field to develop advanced analysis and visualization tools for the characterization and integrative analysis of the large, complex genomic datasets arising from different technology platforms.&#x2028; The UCSC Cancer Genomics Browser is a suite of web-based tools designed to integrate, visualize and analyze genomic and clinical data. The secured-access browser, available at https://cancer.cse.ucsc.edu/, consists of three major components: hgHeatmap, hgFeatureSorter, and hgPathSorter. The main panel, hgHeatmap, displays a whole-genome-oriented view of genome-wide experimental measurements for individual and sets of samples/patients alongside their clinical information. hgFeatureSorter and hgPathSorter together enable investigators to order, filter, aggregate and display data interactively based on any given feature set ranging from clinical features to annotated biological pathways to user-edited collections of genes. Standard and advanced statistical tools are available to provide quantitative analysis of whole genomic data or any of its subsets. The UCSC Cancer Genomics Browser is an extension of the UCSC Genome Browser; thus it inherits and integrates the Genome Browser's existing rich set of human biology and genetics data to enhance the interpretability of cancer genomics data.&#x2028; We demonstrate the UCSC Cancer Genomics Browser by integrating several independent studies on breast cancer including the I-SPY chemotherapy clinical trial and other studies focused on chemotherapeutic response or long-term survival. The types of data that are visualized and analyzed by the browser include microarray measurements of gene expression, copy number variation and phosphoprotein expression, MRI imaging measurements, and clinical parameters.&#x2028; Collectively, these tools facilitate a synergistic interaction among clinicians, experimental biologists, and bioinformaticians. They enable cancer researchers to better explore the breadth and depth of the cancer genomics data resources, and to further characterize molecular pathways that influence cellular dynamics and stability in cancer. Ultimately, insights gained by applying these tools may advance our knowledge of human cancer biology and stimulate the discovery of new prognostic and diagnostic markers, as well as the development of therapeutic and prevention strategies.&#x2028; Funding sources: CALGB CA31964 and CA33601, ACRIN U01 CA079778 and CA080098, NCI SPORE CA58207, California Institute for Quantitative Biosciences, NHGRI.

Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 2022.

In vitro and in vivo assessment of the effect of impurities and chirality on methamidophos-induced neuropathy target esterase aging

In vitro and in vivo studies evaluated neuropathy target esterase (NTE) inhibition and aging (i.e., loss of reactivation potential) by analytical and technical grade racemic and resolved L-(-) and D-(+) isomers of methamidophos (O,S-dimethyl phosphoramidothioate). For studies in vitro, microsomal protein from phenobarbital-induced livers was isolated from chick embryos and NTE inhibition assays were performed using chick embryo brain homogenate treated with 1 or 5 mM methamidophos (with and without metabolic enzymes); for studies in vivo, hens received 30 to 35 mg/kg methamidophos injected into the pectoral muscle. NTE aging in hens was assessed 24 h later or after 30 min to 1 h incubation in vitro using solutions of potassium fluoride (KF) reactivator. Technical methamidophos produced significantly higher levels of aged-inhibited NTE than analytical methamidophos or isolated optical isomers. In vivo, technical methamidophos produced 61% total NTE inhibition with 18% aged and 43% unaged NTE; hens receiving analytical grade averaged 6% aged, 52% unaged, and 58% total NTE inhibition. Results for 1 mM analytical methamidophos in vitro were 5% aged, 54% unaged, and 59% total inhibition; for 1 mM technical methamidophos, values averaged 11% aged, 50% unaged, and 60% total NTE inhibition. The degree of NTE aging obtained both in vivo and in vitro for the isolated D-(+) and L-(-) isomers never exceeded that obtained using analytical grade. These data indicate that impurities in methamidophos could contribute to OPIDN potential. The in vitro methodology described could be applied to first tier screening for detection of NTE inhibition and aging, thus reducing the need for whole-animal testing for OPIDN.