Background Cancer of unknown primary (CUP), representing approximately 3-5% of all malignancies, is defined as metastatic cancer where a primary site of origin cannot be found despite a standard diagnostic workup. Because knowledge of a patient's primary cancer remains fundamental to their treatment, CUP patients are significantly disadvantaged and most have a poor survival outcome. Developing robust and accessible diagnostic methods for resolving cancer tissue of origin, therefore, has significant value for CUP patients. Methods We developed an RNA-based classifier called CUP-AI-Dx that utilizes a 1D Inception convolutional neural network (1D-Inception) model to infer a tumor's primary tissue of origin. CUP-AI-Dx was trained using the transcriptional profiles of 18,217 primary tumours representing 32 cancer types from The Cancer Genome Atlas project (TCGA) and International Cancer Genome Consortium (ICGC). Gene expression data was ordered by gene chromosomal coordinates as input to the 1D-CNN model, and the model utilizes multiple convolutional kernels with different configurations simultaneously to improve generality. The model was optimized through extensive hyperparameter tuning, including different max-pooling layers and dropout settings. For 11 tumour types, we also developed a random forest model that can classify the tumour's molecular subtype according to prior TCGA studies. The optimised CUP-AI-Dx tissue of origin classifier was tested on 394 metastatic samples from 11 tumour types from TCGA and 92 formalin-fixed paraffin-embedded (FFPE) samples representing 18 cancer types from two clinical laboratories. The CUP-AI-Dx molecular subtype was also independently tested on independent ovarian and breast cancer microarray datasets Findings CUP-AI-Dx identifies the primary site with an overall top-1-accuracy of 98.54% in cross-validation and 96.70% on a test dataset. When applied to two independent clinical-grade RNA-seq datasets generated from two different institutes from the US and Australia, our model predicted the primary site with a top-1-accuracy of 86.96% and 72.46% respectively. Interpretation The CUP-AI-Dx predicts tumour primary site and molecular subtype with high accuracy and therefore can be used to assist the diagnostic work-up of cancers of unknown primary or uncertain origin using a common and accessible genomics platform. Funding NIH R35 GM133562, NCI P30 CA034196, Victorian Cancer Agency Australia.

Pheochromocytomas (PC) and paragangliomas (PGL) are endocrine tumors for which the genetic and clinicopathological features of metastatic progression remain incompletely understood. As a result, the risk of metastasis from a primary tumor cannot be predicted. Early diagnosis of individuals at high risk of developing metastases is clinically important and the identification of new biomarkers that are predictive of metastatic potential is of high value. Activation of has been associated with a number of malignant tumors, including PC/PGL. However, the mechanism of activation in the majority of PC/PGL remains unclear. As promoter mutations occur rarely in PC/PGL, we hypothesized that other mechanisms - such as structural variations - may underlie activation in these tumors. From 35 PC and four PGL, we identified three primary PCs that developed metastases with elevated expression, each of which lacked promoter mutations and promoter DNA methylation. Using whole genome sequencing, we identified somatic structural alterations proximal to the locus in two of these tumors. In both tumors, the genomic rearrangements led to the positioning of super-enhancers proximal to the promoter, that are likely responsible for the activation of the normally tightly repressed expression in chromaffin cells.

Cancer of unknown primary (CUP) is a syndrome defined by clinical absence of a primary cancer after standardised investigations. Gene expression profiling (GEP) and DNA sequencing have been used to predict primary tissue of origin (TOO) in CUP and find molecularly guided treatments; however, a detailed comparison of the diagnostic yield from these two tests has not been described. Here, we compared the diagnostic utility of RNA and DNA tests in 215 CUP patients (82% received both tests) in a prospective Australian study. Based on retrospective assessment of clinicopathological data, 77% (166/215) of CUPs had insufficient evidence to support TOO diagnosis (clinicopathology unresolved). The remainder had either a latent primary diagnosis (10%) or clinicopathological evidence to support a likely TOO diagnosis (13%) (clinicopathology resolved). We applied a microarray (CUPGuide) or custom NanoString 18-class GEP test to 191 CUPs with an accuracy of 91.5% in known metastatic cancers for highmedium confidence predictions. Classification performance was similar in clinicopathology-resolved CUPs -80% had high-medium predictions and 94% were concordant with pathology. Notably, only 56% of the clinicopathology-unresolved CUPs had high-medium confidence GEP predictions. Diagnostic DNA features were interrogated in 201 CUP tumours guided by the cancer type specificity of mutations observed across 22 cancer types from the AACR Project GENIE database (77,058 tumours) as well as mutational signatures (e.g. smoking). Among the clinicopathology-unresolved CUPs, mutations and mutational signatures provided additional diagnostic evidence in 31% of cases. GEP classification was useful in only 13% of cases and oncoviral detection in 4%. Among CUPs where genomics informed TOO, lung and biliary cancers were the most frequently identified types, while kidney tumours

Context von Hippel-Lindau (VHL) disease, comprising renal cancer, hemangioblastoma, and/or pheochromocytoma (PHEO), is caused by missense or truncating variants of the VHL tumor-suppressor gene, which is involved in degradation of hypoxia-inducible factors (HIFs). However, the role of synonymous VHL variants in the disease is unclear. Objective We evaluated a synonymous VHL variant in patients with familial PHEO or VHL disease without a detectable pathogenic VHL mutation. Design We performed genetic and transcriptional analyses of leukocytes and/or tumors from affected and unaffected individuals and evaluated VHL splicing in existing cancer databases. Results We identified a synonymous VHL variant (c.414A>G, p.Pro138Pro) as the driver event in five independent individuals/families with PHEOs or VHL syndrome. This variant promotes exon 2 skipping and hence, abolishes expression of the full-length VHL transcript. Exon 2 spans the HIF-binding domain required for HIF degradation by VHL. Accordingly, PHEOs carrying this variant display HIF hyperactivation typical of VHL loss. Moreover, other exon 2 VHL variants from the The Cancer Genome Atlas pan-cancer datasets are biased toward expression of a VHL transcript that excludes this exon, supporting a broader impact of this spliced variant. Conclusion A recurrent synonymous VHL variant (c.414A>G, p.Pro138Pro) confers susceptibility to PHEO and VHL disease through splice disruption, leading to VHL dysfunction. This finding indicates that certain synonymous VHL variants may be clinically relevant and should be considered in genetic testing and surveillance settings. The observation that other coding VHL variants can exclude exon 2 suggests that dysregulated splicing may be an underappreciated mechanism in VHL-mediated tumorigenesis.

Merkel cell carcinomas (MCC) are immunogenic skin cancers associated with viral infection or UV mutagenesis. To study T-cell infiltrates in MCC, we analyzed 58 MCC lesions from 39 patients using multiplex-IHC/immunofluorescence (m-IHC/IF). CD4+ or CD8+ T cells comprised the majority of infiltrating T lymphocytes in most tumors. However, almost half of the tumors harbored prominent CD4/CD8 double-negative (DN) T-cell infiltrates (>20% DN T cells), and in 12% of cases, DN T cells represented the majority of T cells. Flow cytometric analysis of single-cell suspensions from fresh tumors identified DN T cells as predominantly Vδ2− γδ T cells. In the context of γδ T–cell inflammation, these cells expressed PD-1 and LAG3, which is consistent with a suppressed or exhausted phenotype, and CD103, which indicates tissue residency. Furthermore, single-cell RNA sequencing (scRNA-seq) identified a transcriptional profile of γδ T cells suggestive of proinflammatory potential. T-cell receptor (TCR) analysis confirmed clonal expansion of Vδ1 and Vδ3 clonotypes, and functional studies using cloned γδ TCRs demonstrated restriction of these for CD1c and MR1 antigen-presenting molecules. On the basis of a 13-gene γδ T–cell signature derived from scRNA-seq analysis, gene-set enrichment on bulk RNA-seq data showed a positive correlation between enrichment scores and DN T-cell infiltrates. An improved disease-specific survival was evident for patients with high enrichment scores, and complete responses to anti–PD-1/PD-L1 treatment were observed in three of four cases with high enrichment scores. Thus, γδ T–cell infiltration may serve as a prognostic biomarker and should be explored for therapeutic interventions. See related Spotlight on p. 600