FGFR4 regulates tumor subtype differentiation in luminal breast cancer and metastatic disease

Mechanisms driving tumor progression from less aggressive subtypes to more aggressive states represent key targets for therapy. We identified a subset of luminal A primary breast tumors that give rise to HER2-enriched (HER2E) subtype metastases, but remain clinically HER2 negative (cHER2-). By testing the unique genetic and transcriptomic features of these cases, we developed the hypothesis that FGFR4 likely participates in this subtype switching. To evaluate this, we developed 2 FGFR4 genomic signatures using a patient-derived xenograft (PDX) model treated with an FGFR4 inhibitor, which inhibited PDX growth in vivo. Bulk tumor gene expression analysis and single-cell RNA sequencing demonstrated that the inhibition of FGFR4 signaling caused molecular switching. In the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) breast cancer cohort, FGFR4-induced and FGFR4-repressed signatures each predicted overall survival. Additionally, the FGFR4-induced signature was an independent prognostic factor beyond subtype and stage. Supervised analysis of 77 primary tumors with paired metastases revealed that the FGFR4-induced signature was significantly higher in luminal/ER+ tumor metastases compared with their primaries. Finally, multivariate analysis demonstrated that the FGFR4-induced signature also predicted site-specific metastasis for lung, liver, and brain, but not for bone or lymph nodes. These data identify a link between FGFR4-regulated genes and metastasis, suggesting treatment options for FGFR4-positive patients, whose high expression is not caused by mutation or amplification.

Integrative Analysis of miRNAs Identifies Clinically Relevant Epithelial and Stromal Subtypes of Head and Neck Squamous Cell Carcinoma

PURPOSE

The objective of this study is to characterize the role of miRNAs in the classification of head and neck squamous cell carcinoma (HNSCC).

EXPERIMENTAL DESIGN

Here, we analyzed 562 HNSCC samples, 88 from a novel cohort and 474 from The Cancer Genome Atlas, using miRNA microarray and miRNA sequencing, respectively. Using an integrative correlations method followed by miRNA expression-based hierarchical clustering, we validated miRNA clusters across cohorts. Evaluation of clusters by logistic regression and gene ontology approaches revealed subtype-based clinical and biological characteristics.

RESULTS

We identified two independently validated and statistically significant (P < 0.01) tumor subtypes and named them "epithelial" and "stromal" based on associations with functional target gene ontology relating to differing stages of epithelial cell differentiation. miRNA-based subtypes were correlated with individual gene expression targets based on miRNA seed sequences, as well as with miRNA families and clusters including the miR-17 and miR-200 families. These correlated genes defined pathways relevant to normal squamous cell function and pathophysiology. miRNA clusters statistically associated with differential mutation patterns including higher proportions of TP53 mutations in the stromal class and higher NSD1 and HRAS mutation frequencies in the epithelial class. miRNA classes correlated with previously reported gene expression subtypes, clinical characteristics, and clinical outcomes in a multivariate Cox proportional hazards model with stromal patients demonstrating worse prognoses (HR, 1.5646; P = 0.006).

CONCLUSIONS

We report a reproducible classification of HNSCC based on miRNA that associates with known pathologically altered pathways and mutations of squamous tumors and is clinically relevant.

B Cells and T Follicular Helper Cells Mediate Response to Checkpoint Inhibitors in High Mutation Burden Mouse Models of Breast Cancer

This study identifies mechanisms mediating responses to immune checkpoint inhibitors using mouse models of triple-negative breast cancer. By creating new mammary tumor models, we find that tumor mutation burden and specific immune cells are associated with response. Further, we developed a rich resource of single-cell RNA-seq and bulk mRNA-seq data of immunotherapy-treated and non-treated tumors from sensitive and resistant murine models. Using this, we uncover that immune checkpoint therapy induces T follicular helper cell activation of B cells to facilitate the anti-tumor response in these models. We also show that B cell activation of T cells and the generation of antibody are key to immunotherapy response and propose a new biomarker for immune checkpoint therapy. In total, this work presents resources of new preclinical models of breast cancer with large mRNA-seq and single-cell RNA-seq datasets annotated for sensitivity to therapy and uncovers new components of response to immune checkpoint inhibitors.

Virus expression detection reveals RNA-sequencing contamination in TCGA

Background

Contamination of reagents and cross contamination across samples is a long-recognized issue in molecular biology laboratories. While often innocuous, contamination can lead to inaccurate results. Cantalupo et al., for example, found HeLa-derived human papillomavirus 18 (H-HPV18) in several of The Cancer Genome Atlas (TCGA) RNA-sequencing samples. This work motivated us to assess a greater number of samples and determine the origin of possible contaminations using viral sequences. To detect viruses with high specificity, we developed the publicly available workflow, VirDetect, that detects virus and laboratory vector sequences in RNA-seq samples. We applied VirDetect to 9143 RNA-seq samples sequenced at one TCGA sequencing center (28/33 cancer types) over 5 years.

Results

We confirmed that H-HPV18 was present in many samples and determined that viral transcripts from H-HPV18 significantly co-occurred with those from xenotropic mouse leukemia virus-related virus (XMRV). Using laboratory metadata and viral transcription, we determined that the likely contaminant was a pool of cell lines known as the “common reference”, which was sequenced alongside TCGA RNA-seq samples as a control to monitor quality across technology transitions (i.e. microarray to GAII to HiSeq), and to link RNA-seq to previous generation microarrays that standardly used the “common reference”. One of the cell lines in the pool was a laboratory isolate of MCF-7, which we discovered was infected with XMRV; another constituent of the pool was likely HeLa cells.

Conclusions

Altogether, this indicates a multi-step contamination process. First, MCF-7 was infected with an XMRV. Second, this infected cell line was added to a pool of cell lines, which contained HeLa. Finally, RNA from this pool of cell lines contaminated several TCGA tumor samples most-likely during library construction. Thus, these human tumors with H-HPV or XMRV reads were likely not infected with H-HPV 18 or XMRV.

Abstract 1678: Accurate detection of expressed variation in RNA-seq

Somatic variant detection has long been an area of great interest and critical importance in cancer research and treatment. DNA-Seq based somatic variant calling pipelines have been maturing over the last several years and although there is still room for improvement, several methods have been developed capable of accurately detecting somatic variants from matched tumor/normal DNA. RNA-Seq has become a widely used tool for measuring gene and isoform abundance, identifying alternative splicing, and detection of gene fusions. Detection of expressed variation is receiving growing interest, however computational methods to detect this variation have received far less attention than that of DNA-Seq. We have developed an optimized RNA-Seq pipeline based upon the ABRA2 realigner capable of accurately detecting expressed somatic variation in RNA-Seq.

We applied this pipeline to the TCGA Breast Cancer dataset. To assess the impact of identification of expressed variation as an indicator of variant significance, we compared the expression state of the top 20 cohort wide significantly mutated genes (SMG) as identified by The Cancer Genome Atlas Network (2012) with all other genes. At the median for SMGs, 23 somatic variants are expressed with over 90% of variants detected in DNA being expressed. For non-SMGs, the median number of expressed variants is 1 and the median fraction of expressed variants is 50%. Among non-SMGs, a total of six genes exceed the median total number of expressed variants and fraction of expressed variants for SMGs (AHNAK, CHD4, ERBB2, FASN, FOXA1 and MYH9). All of these variants have been previously implicated in breast cancer, however none of these variants were among the cohort wide SMGs identified in the original study and only FOXA1 was identified as being a subtype specific SMG (ER+,ER+/HER2-). Notably, variants in the massive TTN gene are found to be coding 73% of the time, but expressed in only 8% of cases. This is substantially less than the 90% found in SMGs and a likely indicator that TTN mutations are passenger variants. The median and third quartile RNA variant allele frequency (VAF) for SMGs is .41 and .69 versus .32 and .46 for DNA. By comparison, the median and third quartile VAF for non-SMGS was 0 and .27 in RNA and .20 and .30 for DNA. The increased VAF for RNA SMGs is a likely indicator of selection and can potentially further be used to identify variants of significance. We believe these results demonstrate the utility of variant expression as a potentail tool to aid in assessment of variant significance.

Citation Format: Lisle E. Mose, David Marron, Joel S. Parker. Accurate detection of expressed variation in RNA-seq [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1678.

Multiplexed digital PCR for detection of HPV in tissue samples from oropharyngeal cancer patients

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Background: p16 immunohistochemistry (IHC) is a commonly used method for identifying HPV-associated oropharyngeal squamous cell carcinoma (OPSCC). However, p16 overexpression in a minority of HPV negative OPSCC can give rise to false positive results. In contrast, HPV nucleic acid testing lacks adequate sensitivity for routine diagnostic testing. The goal of this study was to investigate whether a multiplexed digital PCR assay can detect and quantify HPV DNA in p16 positive OPSCC treated with definitive chemo-radiotherapy (CRT). Methods: Formalin-fixed paraffin embedded (FFPE) residual diagnostic biopsy specimens were collected from 57 patients. Macrodissection was performed to ensure tumor cellularity > 70%. Extracted genomic DNA was analyzed by next generation sequencing (NGS) using a hybrid capture assay (UNCSeq) targeting > 200 cellular genes and HPV 16/18 genomes. We also designed, validated, and implemented an multiplexed droplet digital PCR (dPCR) assay to detect and quantify HPV DNA (strains 16, 18, 31, 33 and 35) in tissue samples, relative to a genomic control locus (chromosome 6). Results: HPV strain 16 DNA was identified in 50 patients (87.7%), whereas 5 patients (8.8%) had HPV DNA from an alternative high-risk strain (18/31/33/35). HPV DNA was undetectable in 2 patients, indicating a false positive rate of 3.5% for p16 IHC testing in this cohort. HPV DNA copy number per diploid genome equivalent varied significantly across samples, with a median value of 19.7 (range 0.23-1712). A significant correlation was observed between the copies of HPV detected by dPCR and NGS (R2 = 0.5853, p < 0.0001). Evidence for HPV integration was detected by NGS in 23 out of 56 evaluable tumors (42%). There was a trend towards a higher prevalence of HPV integration in tumors with less than 10 HPV copies per diploid genome relative to cancers with > / = 10 HPV copy number (63% versus 34%, p = 0.07). Conclusions: Multiplexed digital PCR demonstrates excellent sensitivity for detection and typing of HPV DNA in diagnostic FFPE specimens from patients with p16 positive oropharyngeal cancer. HPV copy number varies significantly across samples, with a possible association with HPV integration status. Future investigations of potential correlation between HPV copy number, integration status, and clinical outcomes are warranted. Clinical trial information: NCT02281955, NCT03077243.

Rapid Clearance Profile of Plasma Circulating Tumor HPV Type 16 DNA during Chemoradiotherapy Correlates with Disease Control in HPV-Associated Oropharyngeal Cancer

PURPOSE

To identify a profile of circulating tumor human papilloma virus (HPV) DNA (ctHPVDNA) clearance kinetics that is associated with disease control after chemoradiotherapy (CRT) for HPV-associated oropharyngeal squamous cell carcinoma (OPSCC).

EXPERIMENTAL DESIGN

A multi-institutional prospective biomarker trial was conducted in 103 patients with (i) p16-positive OPSCC, (ii) M0 disease, and (iii) receipt of definitive CRT. Blood specimens were collected at baseline, weekly during CRT, and at follow-up visits. Optimized multianalyte digital PCR assays were used to quantify ctHPVDNA (types 16/18/31/33/35) in plasma. A control cohort of 55 healthy volunteers and 60 patients with non-HPV-associated malignancy was also analyzed.

RESULTS

Baseline plasma ctHPVDNA had high specificity (97%) and high sensitivity (89%) for detecting newly diagnosed HPV-associated OPSCC. Pretreatment ctHPV16DNA copy number correlated with disease burden, tumor HPV copy number, and HPV integration status. We define a ctHPV16DNA favorable clearance profile as having high baseline copy number (>200 copies/mL) and >95% clearance of ctHPV16DNA by day 28 of CRT. Nineteen of 67 evaluable patients had a ctHPV16DNA favorable clearance profile, and none had persistent or recurrent regional disease after CRT. In contrast, patients with adverse clinical risk factors (T4 or >10 pack years) and an unfavorable ctHPV16DNA clearance profile had a 35% actuarial rate of persistent or recurrent regional disease after CRT (P = 0.0049).

CONCLUSIONS

A rapid clearance profile of ctHPVDNA may predict likelihood of disease control in patients with HPV-associated OPSCC patients treated with definitive CRT and may be useful in selecting patients for deintensified therapy.

Integrated RNA and DNA sequencing reveals early drivers of metastatic breast cancer

Breast cancer metastasis remains a clinical challenge, even within a single patient across multiple sites of the disease. Genome-wide comparisons of both the DNA and gene expression of primary tumors and metastases in multiple patients could help elucidate the underlying mechanisms that cause breast cancer metastasis. To address this issue, we performed DNA exome and RNA sequencing of matched primary tumors and multiple metastases from 16 patients, totaling 83 distinct specimens. We identified tumor-specific drivers by integrating known protein-protein network information with RNA expression and somatic DNA alterations and found that genetic drivers were predominantly established in the primary tumor and maintained through metastatic spreading. In addition, our analyses revealed that most genetic drivers were DNA copy number changes, the TP53 mutation was a recurrent founding mutation regardless of subtype, and that multiclonal seeding of metastases was frequent and occurred in multiple subtypes. Genetic drivers unique to metastasis were identified as somatic mutations in the estrogen and androgen receptor genes. These results highlight the complexity of metastatic spreading, be it monoclonal or multiclonal, and suggest that most metastatic drivers are established in the primary tumor, despite the substantial heterogeneity seen in the metastases.