Introduction: Salivary gland cancer (SGC) is a rare cancer for which systemic treatment options are limited. Therefore, it is important to characterize its genetic landscape in search for actionable aberrations, such as NTRK gene fusions. This research aimed to identify these actionable aberrations by combining NGS-based analysis of RNA (gene fusions) and DNA (single and multiple nucleotide variants, copy number variants, microsatellite instability and tumor mutational burden) in a large cohort of SGC patients. Methods: RNA and DNA were extracted from archival tissue of 121 patients with various SGC subtypes. Gene fusion analysis was performed using a customized RNA-based targeted NGS panel. DNA was sequenced using a targeted NGS panel encompassing 523 cancer-related genes. Cross-validation of NGS-based NTRK fusion detection and pan-TRK immunohistochemistry (IHC) was performed. Results: Fusion transcripts were detected in 50% of the cases and included both known (MYB-NFIB, MYBL1-NFIB, CRTC1-MAML2) and previously unknown fusions (including transcripts involving RET, BRAF or RAD51B). Only one NTRK fusion transcript was detected, in a secretory carcinoma case. Pan-TRK IHC (clone EPR17341) was false positive in 74% of cases. The proportion of patients with targets for genetically matched therapies differed among subtypes (salivary duct carcinoma: 82%, adenoid cystic carcinoma 28%, mucoepidermoid carcinoma 50%, acinic cell carcinoma 33%). Actionable aberrations were most often located in PIK3CA (n = 18, 15%), ERBB2 (n = 15, 12%), HRAS and NOTCH1 (both n = 9, 7%). Conclusions: Actionable genetic aberrations were seen in 53.7% of all SGC cases on the RNA and DNA level, with varying percentages between subtypes.

Tumor cell invasion into heterogenous interstitial tissues consisting of network-, channel- or rift-like architectures involves both matrix metalloproteinase (MMP)-mediated tissue remodeling and cell shape adaptation to tissue geometry. Three-dimensional (3D) models composed of either porous or linearly aligned architectures have added to the understanding of how physical spacing principles affect migration efficacy; however, the relative contribution of each architecture to decision making in the presence of varying MMP availability is not known. Here, we developed an interface assay containing a cleft between two high-density collagen lattices, and we used this assay to probe tumor cell invasion efficacy, invasion mode and MMP dependence in concert. In silico modeling predicted facilitated cell migration into confining clefts independently of MMP activity, whereas migration into dense porous matrix was predicted to require matrix degradation. This prediction was verified experimentally, where inhibition of collagen degradation was found to strongly compromise migration into 3D collagen in a density-dependent manner, but interface-guided migration remained effective, occurring by cell jamming. The 3D interface assay reported here may serve as a suitable model to better understand the impact of in vivo-relevant interstitial tissue topologies on tumor invasion patterning and responses to molecular interventions.

Chromosomal rearrangements are important drivers in cancer, and their robust detection is essential for diagnosis, prognosis, and treatment selection, particularly for bone and soft tissue tumors. Current diagnostic methods are hindered by limitations, including difficulties with multiplexing targets and poor quality of RNA. A novel targeted DNA-based next-generation sequencing method, formalin-fixed, paraffin-embedded-targeted locus capture (FFPE-TLC), has shown advantages over current diagnostic methods when applied on FFPE lymphomas, including the ability to detect novel rearrangements. We evaluated the utility of FFPE-TLC in bone and soft tissue tumor diagnostics. FFPE-TLC sequencing was successfully applied on noncalcified and decalcified FFPE samples (n = 44) and control samples (n = 19). In total, 58 rearrangements were identified in 40 FFPE tumor samples, including three previously negative samples, and none was identified in the FFPE control samples. In all five discordant cases, FFPE-TLC could identify gene fusions where other methods had failed due to either detection limits or poor sample quality. FFPE-TLC achieved a high specificity and sensitivity (no false positives and negatives). These results indicate that FFPE-TLC is applicable in cancer diagnostics to simultaneously analyze many genes for their involvement in gene fusions. Similar to the observation in lymphomas, FFPE-TLC is a good DNA-based alternative to the conventional methods for detection of rearrangements in bone and soft tissue tumors.