Figure S16: Expansion of FRM-specific CD8T cells after priming with relevant peptide in PBMC from healthy individuals.

Figure S9: Results of NOP identification using simulated sequencing data.

Figure S15: Tetramer gating strategy.

Figure S13: In silico determined immunogenic properties of NOPs.

Figure S5: Long-read transcript sequencing statistics.

Figure S2: Long RNA splice correction, isoform identification, and translation prediction.

Figure S1: RNA-guided tumor genome reconstruction.

Figure S3: Identifying FRM0469-dextramer-positive CD8+ T cells.

Figure S4: Overview of somatic mutation statistics for tumor samples analyzed by WGS in this study.

Figure S12: Example of a genomic rearrangement resulting in the expression of multiple hidden NOPs in tumor sample BRE007.

Figure S6: Comparison of long and short read RNA gene expression quantification and transcript coverage bias.

Figure S11: Example of a hidden NOP resulting from a complex chromosomal rearrangement in tumor sample LUN022.

Figure S7: Protein mass spectrometry results for A375 NOPs.

Combined spreadsheet with Supplementary Tables S1 - S12

Figure S14: A375 immunopeptidomics.

Figure S10: A) NOP expression compared to normal genes.

BACKGROUND:Liquid biopsy approaches, especially the detection of circulating tumor DNA (ctDNA), are emerging as sensitive and reliable surrogates for tumor tissue-based routine diagnostic testing. Here, we retrospectively analyzed serially collected plasma samples of non-small cell lung cancer (NSCLC) patients obtained at first diagnosis to evaluate the added value of ctDNA analysis for detecting therapeutically relevant variants and determining the consequent clinical implications. METHODS:One hundred eighty plasma samples from consecutively recruited NSCLC patients were included. Circulating cell-free DNA (ccfDNA) was extracted and analyzed with the UltraSEEK Lung Panel v2 on the MassARRAY System. Tumor tissue next-generation sequencing (NGS) data, performed as routine molecular testing in the clinical setting, were retrieved from the national pathology registry for 132 patients. RESULTS:Here we show that in 82% of the patients, mutations are concordantly detected in tumor tissue and plasma. More mutations are reported with tumor tissue-based NGS in nineteen patients, while in four patients additional mutations are detected in plasma. Tissue-based molecular tumor profiling identifies 60 patients eligible for targeted treatment including fifteen (8%) harboring fusions currently not covered by UltraSEEK. Based on ctDNA analysis, 41 patients (23%) are identified as eligible for BRAFV600-, EGFR-, or KRASG12C-targeted therapies. In the absence of tumor tissue NGS data (n = 48), five therapeutically relevant mutations are detected. CONCLUSIONS:Molecular tumor profiling of ctDNA identifies therapeutically relevant mutations at a comparable rate to tumor tissue-based NGS and might therefore serve as an alternative or complementary test for the detection of actionable variants in plasma.

Molecular diagnostics has revolutionized cancer management, enabling the identification of diagnostic, prognostic, and predictive biomarkers. Despite advancements in technologies such as whole genome sequencing, their translation into clinical practice remains challenging due to insufficiently demonstrated clinical utility. This study identifies unmet clinical needs and requirements for innovative molecular technologies in oncology through interviews (n = 22) and an online survey (n = 116), gathering insights from hospital professionals, industry representatives, and health policy and quality assessment experts. Our findings emphasize the increasing importance of liquid biopsies (LBx), particularly plasma-based assays. Key unmet needs in this area include therapy response monitoring, minimal residual disease detection, and predictive biomarker testing. Additionally, we outline technology requirements tailored to diverse clinical biomarker applications and both centralized and decentralized laboratory settings. A central challenge lies in achieving an optimal balance between multiplexing capacity and turnaround time. By bridging the gap between technology development and real-world application, this study paves the way for the implementation of new molecular technologies that better meet the needs of the oncology community, ensuring clinical utility and ultimately improving patient care.