Sequencing RNA modifications is challenging due to the existence of over 170 unique chemical nucleotide alterations. tRNAs, constituting about 25% of cellular RNA and decoding 61 mRNA codons, often have 8-14 modifications each. These modifications are central to functional diversity, cellular regulation, and diseases such as cancer and neurological disorders. Unbiased, comprehensive sequencing of RNA modifications is vital for understanding these complex processes. Current techniques, including Next-Generation Sequencing (NGS), depend on complementary DNA (cDNA) intermediates, failing to capture the complete tRNA modification profile. They often overlook or bias certain types, and are not suitable for tRNAs, which have reverse-transcriptase-blocking nucleotide modifications. The heterogeneity of tRNA modifications, with over 100 identified types showing varying modification levels, adds complexity. Although nanopores show potential for sequencing all RNA modifications, training over 170 different standard nucleotide modifications while preserving unique signature electronic signals presents formidable challenges. Mass spectrometry (MS), despite its ability to characterize RNA modifications without bias, has limitations. Conventional MS methods like tandem MS (MS2) lose essential details about modified nucleotide location and co-occurrence, and the complexity of its spectra obstructs high-throughput sequencing of intricate tRNAs. To counter these challenges, we've developed next-generation mass spectrometry-based sequencing (NGMS-Seq) methods. Utilizing two-dimensional (2D) mass-retention time ladders instead of MS2 fragmentation, NGMS-Seq has demonstrated the potential to sequence specific tRNAs de novo and simultaneously sequence and quantify all nucleotide modifications without bias. In this application, our aims are to: 1) advance NGMS-Seq toward high throughput for direct sequencing of various tRNA samples, including physiologically relevant ones, and 2) enhance technologies to quantitatively map tRNA modifications site-specifically and track their dynamic changes within a melanoma model. Our refined techniques, initially tailored for tRNA, have the potential to extend to longer RNAs and small noncoding RNAs. Through our commercialization initiatives, we aim to make NGMS-Seq widely accessible, providing comprehensive RNA sequence and modification data, thereby offering vital insights into RNA- associated diseases.