Pan-cancer analysis reveals recurrent BCAR4 gene fusions across solid tumors

UNLABELLED: Chromosomal rearrangements often result in active regulatory regions juxtaposed upstream of an oncogene to generate an expressed gene fusion. Repeated activation of a common downstream partner-with differing upstream regions across a patient cohort-suggests a conserved oncogenic role. Analysis of 9,638 patients across 32 solid tumor types revealed an annotated long noncoding RNA (lncRNA), Breast Cancer Anti-Estrogen Resistance 4 (BCAR4), was the most prevalent, uncharacterized, downstream gene fusion partner occurring in 11 cancers. Its oncogenic role was confirmed using multiple cell lines with endogenous BCAR4 gene fusions. Furthermore, overexpressing clinically prevalent BCAR4 gene fusions in untransformed cell lines was sufficient to induce an oncogenic phenotype. We show that the minimum common region to all gene fusions harbors an open reading frame that is necessary to drive proliferation. IMPLICATIONS: BCAR4 gene fusions represent an underappreciated class of gene fusions that may have biological and clinical implications across solid tumors

HPV transcript expression affects cervical cancer response to chemoradiation

Persistent HPV infection is causative for the majority of cervical cancer cases; however, current guidelines do not require HPV testing for newly diagnosed cervical cancer. Using an institutional cohort of 88 patients with cervical cancer treated uniformly with standard-of-care chemoradiation treatment (CRT) with prospectively collected clinical outcome data, we observed that patients with cervical tumors containing HPV genotypes other than HPV 16 have worse survival outcomes after CRT compared with patients with HPV 16+ tumors, consistent with previously published studies. Using RNA sequencing analysis, we quantified viral transcription efficiency and found higher levels of E6 and the alternative transcript E6*I in cervical tumors with HPV genotypes other than HPV 16. These findings were validated using whole transcriptome data from The Cancer Genome Atlas (n = 304). For the first time to our knowledge, transcript expression level of HPV E6*I was identified as a predictive biomarker of CRT outcome in our complete institutional data set (n = 88) and within the HPV 16+ subset (n = 36). In vitro characterization of HPV E6*I and E6 overexpression revealed that both induce CRT resistance through distinct mechanisms dependent upon p53-p21. Our findings suggest that high expression of E6*I and E6 may represent novel biomarkers of CRT efficacy, and these patients may benefit from alternative treatment strategies

Intrinsic tumor resistance to CAR T cells is a dynamic transcriptional state that is exploitable with low-dose radiation

Chimeric antigen receptor (CAR) T-cell therapy represents a major advancement for hematologic malignancies, with some patients achieving long-term remission. However, the majority of treated patients still die of their disease. A consistent predictor of response is tumor quantity, wherein a higher disease burden before CAR T-cell therapy portends a worse prognosis. Focal radiation to bulky sites of the disease can decrease tumor quantity before CAR T-cell therapy, but whether this strategy improves survival is unknown. We find that substantially reducing systemic tumor quantity using high-dose radiation to areas of bulky disease, which is commonly done clinically, is less impactful on overall survival in mice achieved by CAR T cells than targeting all sites of disease with low-dose total tumor irradiation (TTI) before CAR T-cell therapy. This finding highlights another predictor of response, tumor quality, the intrinsic resistance of an individual patient\u27s tumor cells to CAR T-cell killing. Little is known about whether or how an individual tumor\u27s intrinsic resistance may change under different circumstances. We find a transcriptional death receptor score that reflects a tumor\u27s intrinsic sensitivity to CAR T cells can be temporarily increased by low-dose TTI, and the timing of this transcriptional change correlates with improved in vivo leukemia control by an otherwise limited number of CAR T cells. This suggests an actionable method for potentially improving outcomes in patients predicted to respond poorly to this promising therapy and highlights that intrinsic tumor attributes may be equally or more important predictors of CAR T-cell response as tumor burden

Sensitive MRD detection from lymphatic fluid after surgery in HPV-associated oropharyngeal cancer

PURPOSE: Our goal was to demonstrate that lymphatic drainage fluid (lymph) has improved sensitivity in quantifying postoperative minimal residual disease (MRD) in locally advanced human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC) compared with plasma, and leverage this novel biofluid for patient risk stratification. EXPERIMENTAL DESIGN: We prospectively collected lymph samples from neck drains of 106 patients with HPV (+) OPSCC, along with 67 matched plasma samples, 24 hours after surgery. PCR and next-generation sequencing were used to quantify cancer-associated cell-free HPV (cf-HPV) and tumor-informed variants in lymph and plasma. Next, lymph cf-HPV and variants were compared with TNM stage, extranodal extension (ENE), and composite definitions of high-risk pathology. We then created a machine learning model, informed by lymph MRD and clinicopathologic features, to compare with progression-free survival (PFS). RESULTS: Postoperative lymph was enriched with cf-HPV compared with plasma (P \u3c 0.0001) and correlated with pN2 stage (P = 0.003), ENE (P \u3c 0.0001), and trial-defined pathologic risk criteria (mean AUC = 0.78). In addition, the lymph mutation number and variant allele frequency were higher in pN2 ENE (+) necks than in pN1 ENE (+) (P = 0.03, P = 0.02) or pN0-N1 ENE (-) (P = 0.04, P = 0.03, respectively). The lymph MRD-informed risk model demonstrated inferior PFS in high-risk patients (AUC = 0.96, P \u3c 0.0001). CONCLUSIONS: Variant and cf-HPV quantification, performed in 24-hour postoperative lymph samples, reflects single- and multifeature high-risk pathologic criteria. Incorporating lymphatic MRD and clinicopathologic feature analysis can stratify PFS early after surgery in patients with HPV (+) head and neck cancer. See related commentary by Shannon and Iyer, p. 1223

DANSR: A tool for the detection of annotated and novel small RNAs

Existing small noncoding RNA analysis tools are optimized for processing short sequencing reads (17-35 nucleotides) to monitor microRNA expression. However, these strategies under-represent many biologically relevant classes of small noncoding RNAs in the 36-200 nucleotides length range (tRNAs, snoRNAs, etc.). To address this, we developed DANSR, a tool for the detection of annotated and novel small RNAs using sequencing reads with variable lengths (ranging from 17-200 nt). While DANSR is broadly applicable to any small RNA dataset, we applied it to a cohort of matched normal, primary, and distant metastatic colorectal cancer specimens to demonstrate its ability to quantify annotated small RNAs, discover novel genes, and calculate differential expression. DANSR is available as an open source tool

A community challenge to evaluate RNA-seq, fusion detection, and isoform quantification methods for cancer discovery

The accurate identification and quantitation of RNA isoforms present in the cancer transcriptome is key for analyses ranging from the inference of the impacts of somatic variants to pathway analysis to biomarker development and subtype discovery. The ICGC-TCGA DREAM Somatic Mutation Calling in RNA (SMC-RNA) challenge was a crowd-sourced effort to benchmark methods for RNA isoform quantification and fusion detection from bulk cancer RNA sequencing (RNA-seq) data. It concluded in 2018 with a comparison of 77 fusion detection entries and 65 isoform quantification entries on 51 synthetic tumors and 32 cell lines with spiked-in fusion constructs. We report the entries used to build this benchmark, the leaderboard results, and the experimental features associated with the accurate prediction of RNA species. This challenge required submissions to be in the form of containerized workflows, meaning each of the entries described is easily reusable through CWL and Docker containers at https://github.com/SMC-RNA-challenge. A record of this paper's transparent peer review process is included in the supplemental information