NAR Cancer

N6-methyladenosine (m6A) is the most abundant internal modification in mRNAs. Despite accumulating evidence for the profound impact of m6A on cancer biology, there are conflicting reports that alterations in genes encoding the m6A machinery proteins can either promote or suppress cancer, even in the same tumor type. Using data from The Cancer Genome Atlas, we performed a pan-cancer investigation of 15 m6A core factors in nearly 10,000 samples from 31 tumor types to reveal underlying cross-tumor patterns. Altered expression, largely driven by copy number variations at the chromosome arm level, results in the most common mode of dysregulation of these factors. YTHDF1, YTHDF2, YTHDF3, and VIRMA are the most frequently altered factors and the only ones to be uniquely altered when tumors are grouped according to the expression pattern of the m6A factors. These genes are also the only ones with coherent, pan-cancer predictive power for progression-free survival. On the contrary, METTL3, the most intensively studied m6A factor as a cancer target, shows much lower levels of alteration and no predictive power for patient survival. Therefore, we propose the non-enzymatic YTHDF and VIRMA genes as preferred subjects to dissect the role of m6A in cancer and as priority cancer targets. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/598899v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1e39eeborg.highwire.dtl.DTLVardef@d6628dorg.highwire.dtl.DTLVardef@e048a6org.highwire.dtl.DTLVardef@c19812_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundCancer is driven by the accumulation of somatic mutations, including driver mutations that confer a selective advantage to cancer cells. Driver proteins operate within complex interaction networks, and their activity is conditioned by neighbour proteins. Understanding the interplay between driver mutations and the expression of their neighbour proteins can provide insights into cancer biology and potential therapeutic targets. MethodsWe assessed associations between expression of neighbour proteins and driver mutation status, comparing both between and within cancer types. We further evaluated if neighbours were enriched in significant associations with multiple drivers and characterised the impact of neighbour expression on overall survival for all cancer types. ResultsWe found a significant correlation between the number of driver associations a neighbour gene has and the number of sign-coherent survival associations, particularly for neighbours enriched in positive associations, where high neighbour expression correlated with increased driver mutations and poorer survival. We identified 119 neighbours enriched in positive driver associations with at least two unfavourable survival associations and 25 neighbours enriched in negative driver associations with at least two favourable survival associations. ConclusionsOur study systematically identified neighbours associated with driver mutation status. Complementary evidence from survival analysis and the literature suggests that neighbours enriched in driver associations can be further explored as drug target candidates. Significance StatementCancers are caused by mutations in driver genes. The impact of those mutations in the cell can be influenced by other proteins in the cell that physically interact with the mutated protein. In this work, we analysed cancer patient data to uncover such neighbour proteins that may influence the outcome of driver mutations. We discovered a subset of neighbour proteins that are associated with mutations in multiple cancer drivers and, simultaneously, are associated with changes in survival times of patients for multiple cancer types. These neighbour proteins may help explain why some driver mutations are more common in certain cancer types. We also propose that these neighbour proteins should be explored as candidate drug targets for cancer therapy.

tRNAs are a driving force of genome evolution in Yeast and Bacteria. Their deregulation is frequently observed in tumors with Serine tRNAs being often overexpressed. This has important functional consequences, such as increased metabolism and tumor growth. In yeast, time and chemical stimulus boost alterations in the genome driven by tRNA deregulation. Therefore, we hypothesized that tRNA deregulation may contribute to the increased genome instability observed in tumors. To study the effect of tRNA deregulation in tumors, we overexpressed tRNA-Ser-AGA-2-1 in a NSCLC cell line, H460. This cell line and a Mock (control) were xenografted in nude mice and collected at 3 timepoints: T1-Naive; T2-Treated once with cisplatin/vehicle and; T3) treated twice with cisplatin/vehicle. These tumors were characterized by WES, RNAseq and Mass Spectrometry and the data obtained was integrated. The tumor mutation burden was increased in T3 tRNASerOE tumors, regardless of treatment. Although in T1 Mock and tRNASer tumors have a similar number of variants, in T2&3, tRNASerOE tumors display two times more variants than Mock tumors regardless of treatment. Interestingly, tRNASerOE exclusive variants favor proliferation and therapy resistance, which is in line with the phenotypes observed and supported by RNAseq and proteomics data. In conclusion, tRNASerOE increases the tumor mutation burden and the variants detected favor tumor growth, proving tRNA deregulation is enough to induce adaptive mutations in the genome.

Inactivation of the DNA mismatch repair (MMR) system, due to (epi)genetic alterations of MMR genes, increases the frequency of mutations across the genome, creating a phenotype known as microsatellite instability (MSI). Cancers with this phenotype have been associated with a better prognosis for some time, but only since recently it has been recognised as a predictive biomarker of response to immunotherapy. Because MSI tumours accumulate more insertions and/or deletions in coding regions of the genome containing microsatellites, there is an increase in neoantigens resulting from reading frame shifts, which promotes immunogenicity. To investigate if additional genes exist that can cause an MSI phenotype, we developed a fluorescence-based sensor to identify genes whose inactivation increases the rate of frameshift mutations on microsatellite sequences in cancer cells. Using genome-scale CRISPR/Cas9 screens, we identified MED12 as a potential new regulator of microsatellite instability. Consistent with this, we found that MED12 mutant colon cancers that lack mutations in the known MMR genes are more likely to be of the MSI phenotype.

BackgroundOncogene-induced replication stress characterizes many aggressive cancers, including triple-negative breast cancer (TNBC). Several drugs are being developed that target replication stress, although it is unclear how tumors with high levels of replication stress can be identified. We aimed to develop a gene expression signature of oncogene-induced replication stress. MethodsTNBC and non-transformed RPE1-TP53wt and RPE1-TP53mut cell lines were engineered to overexpress the oncogenes CDC25A, CCNE1 or MYC. DNA fiber analysis was used to measure replication kinetics. Analysis of RNA sequencing data of cell lines and patient-derived tumor samples (TCGA n=10,592) was used to identify differential gene expression. Immunohistochemical validation was conducted on breast cancer samples (n=330). ResultsRNA sequencing revealed 52 commonly upregulated genes after induction of CDC25A, CCNE1 or MYC in our cell line panel. Integration with gene expression data of TGCA samples with amplification of replication stress-inducing oncogenes (CDC25A, CCNE1, MYC, CCND1, MYB, MOS, KRAS, ERBB2, and E2F1), yielded a six-gene signature of oncogene-induced replication stress (NAT10, DDX27, ZNF48, C8ORF33, MOCS3, and MPP6). Expression of NAT10 in breast cancer samples was correlated with phospho-RPA (R=0.451, p=1.82x10-20) and {gamma}H2AX (R=0.304, p=2.95x10-9). Applying the oncogene-induced replication stress signature to patient samples (TCGA n=8,862 and GEO n=13,912) defined the replication stress landscape across 27 tumor subtypes, and identified diffuse large B cell lymphoma, ovarian cancer, TNBC and colorectal carcinoma as cancer subtypes with high levels of oncogene-induced replication stress. ConclusionWe developed a gene expression signature of oncogene-induced replication stress, which may facilitate patient selection for agents that target replication stress.

Extrachromosomal circular DNA (eccDNA) are circular DNA molecules that originate from chromosomal DNA but exist independently. While large eccDNA (ecDNA) contributes to tumorigenesis, the role of smaller eccDNA (<100,000 base pairs) in cancer remains unclear. Our analysis of 25 colorectal cancer (CRC) tumors and adjacent non-tumorous tissues revealed that eccDNA is significantly more abundant in tumor tissues, correlating strongly with chromosomal amplifications. The presence of whole intact genes on 1.29% of eccDNA was non-random. We identified 84 genes that recurred across tumors of multiple patients when present on eccDNA with 19% of genes being cancer-associated. eccDNA-borne genes were often accompanied by increased expression, and their contribution to expression was much larger than that from linear amplifications and the larger ecDNA. The cytokine gene CXCL5 exemplified this phenomenon, showing substantial copy-number increase and upregulation when present on eccDNA. Functional validation in cell lines showed that CXCL5 eccDNA enhanced transcriptional output and immune cell recruitment function. The recurrence and overexpression of CRC-related genes on eccDNA indicate their selection in tumors, suggest eccDNA can serve as a novel mechanism for dynamically influencing gene expression and is capable of conferring cancer phenotypes to cells. Analysis of chromatin landscapes revealed that eccDNA preferentially forms at sites of open chromatin and active transcription, with architectural boundaries marked by CTCF protein. Clinically, patients with higher eccDNA levels showed poorer relapse-free survival. These findings suggest that circular DNA elements across the entire size spectrum participate in cancer evolution, positioning eccDNA as a potential therapeutic target and prognostic biomarker.

ABSTRACTRetrotransposons are genomic DNA sequences that are capable of copying themselves to new genomic locations via RNA intermediates; LINE-1 is the only retrotransposon that remains autonomous and active in the human genome. The mobility of LINE-1 is largely repressed in somatic tissues, but LINE-1 is active in many cancers. Recent studies using LINE-1 constructs indicate that host cells activate a DNA damage response (DDR) to repair retrotransposition intermediates and resolve conflicts between LINE-1 and DNA replication. Using multi-omic data from the CPTAC project, we found correlations between LINE-1 expression and ATM-MRN-SMC DDR signalling in endometrial cancer and between LINE-1 and the ATR-CHEK1 pathway in p53 wild type breast cancer. This provides evidence that conflicts between LINE-1 and DNA replication occur in at least some human cancers. Furthermore, LINE-1 expression in these cancers is correlated with the total amount of copy number variation genome wide, indicating that, when active in cancer, pointing to a direct impact of LINE-1 associated DNA damage on genome structure. We also find that, in endometrial and ovarian cancer, LINE-1 expression is correlated with the expression of genes that drive cycle progression including E2F3, PLK1 and Aurora kinase B. This study provides evidence, supporting recent work in model cell lines, of a LINE-1/DDR connection in human tumors and raises the possibility of additional interactions between LINE-1 and the cell cycle.Competing Interest StatementThe authors have declared no competing interest.View Full Text

Recent technical advances have facilitated studies on changes in mRNA structures in response to signaling pathways. However, if mRNA structures can affect the function of the encoded protein remains poorly understood. In-cell RNA structural probing (SHAPE-MaP) demonstrates how two cancer-associated synonymous mutations (CASMs) at proline codon 34 (c.102 C>A and c.102 C>G) prevent DNA damage-induced TP53 mRNA folding, whereas the non-cancer-associated c.102C>U mutation does not. Transcript and chromatin immunoprecipitation (ChIP) analysis reveal that p53 expressed from CASM34 has reduced promoter binding and reduced induction of p53 downstream target genes PUMA and 14-3-3-{sigma}, but not p21CDKN1A. Transcriptome analysis reveals a CASM34-mediated global attenuation of DNA damage-responsive gene expression. Together, the results demonstrate that CASM34 interferes with signal-induced p53 mRNA folding during DNA damage, leading to selective modulation of protein activity. More broadly, our findings highlight a general concept by which cancer-associated synonymous mutations target signal-induced mRNA structures that influence the encoded protein. Significance statementRecent studies have revealed that synonymous mutations can target RNA metabolism and are associated with numerous diseases; however, how these mutations affect the function of the encoded protein remain unclear. Using in-cell RNA structural probing, we show that two cancer-associated synonymous mutations in TP53 disrupt DNA damage-induced folding of p53 mRNA. These mutations selectively impair p53 promoter binding and transcriptional activation of specific downstream target genes. Our results demonstrate that disruption of signal-induced mRNA folding by synonymous mutations can modulate the activity of the encoded protein. More broadly, this work identifies signal-responsive mRNA structures as functional targets of cancer-associated synonymous mutations.

SOX10 is essential for melanocyte development and maintenance and plays a critical role in uveal melanoma (UM) initiation and progression. While SOX10s transcriptional regulation of protein-coding genes is well characterized, its role on microRNA (miRNA) regulatory landscape in UM remains unexplored. Here, we employed network-based modeling to systematically characterize miRNA regulatory functions following SOX10 depletion in UM. First, we profiled mRNA and miRNA expression levels in SOX10 wild-type and knockdown UM cells. Then, we integrated the transcriptomic data, a UM network, and a Bayesian model to quantify miRNAs regulatory activities and identify key miRNAs. Subsequently, we employed pathway enrichment analysis combined with literature mining to elucidate the functional roles of identified miRNAs through their target genes and associated signaling pathways in UM. We identified 17 miRNAs that show significant changes in regulatory activities following SOX10 knockdown in UM cells. These miRNAs regulate the expression of genes involved in cancer hallmark pathways, including cell cycle progression, mTORC1 signaling, and fatty acid metabolism. Notably, miR-34a, miR-25, miR-186, and miR-211 have tumor-suppressive potential by targeting genes involved in UM progression and metastasis. Our results suggested that SOX10 depletion in UM can activate tumor-suppressive mechanisms through regulating miRNAs.

Acquiring drug resistance is a major problem in cancer treatment. As cancers adapt to chemotherapy, chromatin landscape becomes altered in subpopulations of persister cells to acquire gene expression patterns that provide drug resistance. The increased level of stress-induced random mutagenesis in cancer has also been linked to acquisition of drug resistance. Here we show that during adaptation to conventional cytotoxic chemotherapies or targeted therapies, tens of thousands of mutations are generated, and the probability of acquisition of these mutations at specific positions can reach 50% and even higher. A large fraction of these mutations is highly recurrent and non-random. The patterns of the recurrent mutations are specific to the drug target and are unrelated to the chemical nature of the drug. Surprisingly, these mutations are progressively generated at the non-dividing pseudo-senescence stage following drug exposure, and at this stage, selection is not involved in their accumulation. Notably, these mutations are highly enriched within or near binding motifs of certain transcription factors, like KLF9, IRF1 and others. Therefore, a mechanism for precise generation of mutations at specific positions with extremely high rates appears to be triggered upon drug adaptation, and these precise mutations may affect activities of a set of transcription factors.

Small activating RNAs are short double-stranded RNAs designed to upregulate transcription of target genes. By this virtue, they can be used to restore expression of genes frequently silenced in cancer. AW1-51 (also referred to as CEBPA-51), the first small activating RNA therapeutic to enter clinical evaluation, has demonstrated biological activity and safety in Phase II trials for hepatocellular carcinoma, both as monotherapy and in combination with sorafenib, and in Phase 1a/1b in combination with pembrolizumab for patients with advanced solid tumors. It targets the master regulator CCAAT enhancer-binding protein alpha, abnormally silenced by DNA methylation in a wide range of hematological and non-hematological malignancies. However, the molecular events enabling this mechanism are only partially elucidated. In this study, we uncovered the molecular basis for AW1-51-induced transcriptional reactivation of CCAAT enhancer-binding protein alpha demonstrating that by directly promoting DNA demethylation of its promoter restores its expression, protein synthesis, and consequently cell differentiation. These findings unveil AW1-51 as a prototype for RNA-based precision medicine enabling conditional expression of CCAAT enhancer-binding protein alpha in diseases characterized by aberrant gene silencing and extending its potential therapeutic impact beyond cancer.

MiRNA Epitranscriptomics has placed a new layer of complexity in the cancer field. Despite the fast-growing interest in miRNA editing and shifted miRNA isoforms, a simultaneous study of both modifications in cancer is still missing. Here, we concurrently profiled multiple miRNA modifications, including A-to-I RNA editing and shifted miRNA isoforms, in >13K adult and pediatric tumor samples across 38 distinct cancer cohorts from The Cancer Genome Atlas and The Therapeutically Applicable Research to Generate Effective Treatments datasets. We investigated the differences among canonical miRNAs and the wider miRNAome in terms of expression, clustering, dysregulation, and prognostic standpoint. The combination of canonical miRNAs/miRNA isoforms boosted the quality of clustering results, outlining unique cohorts clinical-pathological features. We described modified miRNAs showing opposite dysregulation with respect to their canonical counterparts in cancer, potentially impacting their targetome and function. The abundance of expressed miRNA isoforms directly impacted the activation/deactivation of critical carcinogenesis pathways. Finally, we experimentally validated unique targeting for a shifted and edited miRNA isoform. Our findings outlined once more the importance of going beyond the well-established paradigm of one-mature-miRNA per miRNA arm to elucidate novel mechanisms related to cancer progression.

Mutational signature analysis has greatly enhanced our understanding of the mutagenic processes found in cancer and normal tissues. As part of a recent study, we analyzed 802 treatment-naive, microsatellite-stable colorectal cancers (CRC) and identified a de novo signature, SBS_D, which was conservatively decomposed into SBS18, a signature associated with reactive oxygen species. Here, we re-evaluate this decomposition and provide evidence that SBS_D represents a distinct mutational process from that of SBS18. Through an independent analysis of 2,616 whole-genome sequenced microsatellite-stable CRCs across three distinct cohorts, we demonstrate that SBS_D is consistently present at a similar prevalence, suggesting that this signature may have been previously overlooked. Using a naive decomposition approach, we demonstrate that the pattern of SBS_D better aligns with signatures previously associated with deficiencies in DNA polymerase delta (POLD1) proofreading and mismatch repair. However, multiple lines of evidence, including the absence of pathogenic mutations in the exonuclease domain of POLD1 or in mismatch repair-associated genes, indicate that SBS_D is not driven by canonical defects in these DNA repair pathways. Overall, this study identifies a previously unrecognized mutational signature in microsatellite-stable CRC and proposes that its etiology may be linked to DNA repair infidelity emerging late in tumor development in samples without canonical defects in DNA repair pathways.

N6-Methyladenosine (m6A) is the most abundant internal modification of eukaryotic mRNAs and regulates target transcripts throughout the mRNA life cycle. Although changes in m6A have been reported in human cancers, technical limitations have hindered a comprehensive understanding of the cancer-associated m6A landscape. Here, we used GLORI-sequencing to establish the first transcriptome-wide, single-nucleotide resolution maps of m6A in cancer. Differentially methylated transcripts were enriched in oncogenic pathways relevant to UCB. We discovered two key m6A signatures in UCB: a global loss of methylation and a local hypermethylation at 3'-UTRs. Integration of RNA-sequencing data revealed that the global loss resulted from dilution of methylation marks due to increased expression of unmethylated transcripts and decreased expression of highly methylated transcripts. In contrast, local 3'-UTR hypermethylation was associated with the overexpression of VIRMA, a component of the m6A writer complex, which was linked to UCB progression. Our study is the first to describe the m6A epitranscriptomic landscape of cancer at single-base resolution and provides first insights into the processes that generate its characteristic signatures.

Epigenetic evolution is a common mechanism used by cancer cells to evade the therapeutic effects of drug treatment. In ovarian cancers, epigenetically-driven resistance may be responsible for a large number of late-stage patient deaths. Here, we describe the first investigation into the role of G-quadruplex (G4) DNA secondary structures in mediating epigenetic regulation in drug-resistant ovarian cancer cells. Through genome-wide mapping of G4s in paired drug-sensitive and drug-resistant cell lines, we find that increased G4 formation is associated with significant increase in gene expression, with high enrichment in signalling pathways previously established to promote drug-resistant states. However, in contrast to previous studies, the expression-enhancing effects of G4s were not found at gene promoters, but intergenic and intronic regions, indicating that G4s promote long-range transcriptional regulation in drug-resistant cells. Furthermore, we discovered that clusters of G4s (super-G4s) are associated with particularly high levels of transcriptional enhancement that surpass the effects of super-enhancers, which act as well established regulatory sites in many cancers. Finally, we demonstrate that targeting G4s with small molecules results in significant down-regulation of pathways associated with drug-resistance, which results in resensitisation of resistant cells to chemotherapy agents. These findings indicate that G4 structures are critical for the epigenetic regulatory networks of drug-resistant cells and may represent a promising target to treat drug-tolerant ovarian cancer.

Interrogation of big genomic data and integration with large-scale protein-protein interaction networks and pathways, can provide deep patterns that are rare- yet can prompt dramatic phenotypic alterations and serve as clinical signatures. Mapping cancer-specific co-occurring mutation-pair signatures, in primary and metastatic tumors, is indispensable in precision oncology. The additivity of co-occurring driver mutations in different genes (in trans) can lead to powerful proliferation signals. Co-occurring rare in trans combinations can serve as metastasis markers; excluded combinations may indicate candidates for oncogene-induced senescence (OIS), a tumor-suppressive mechanism. Our statistical framework of the pan-cancer mutation profiles of [~]60,000 tumor sequences from the TCGA and AACR GENIE databases, identified 3424 statistically significant different double mutations in non-redundant pathways, that is, have different downstream targets that may promote specific cancers through single or multiple pathways. Our analysis indicates that they are mostly in primary tumors. We list actionable in trans mutations for 2385 metastatic tumors and provide co-occurrence trees of metastatic breast- cancer markers. This innovative work clarifies the mechanistic conceptual basis and establishes the first of its kind tool for identifying and predicting metastasis. Crucially, when coupled with their proliferative functions and pathways, and linked with drugs, it could provide an invaluable metastasis-targeting resource.

N6-methyladenosine (m6A) is the most prevalent internal mRNA modification, enriched in the CNS yet poorly characterized in glioma. Using long-read RNA sequencing, we mapped m6A in an in vitro glioma model following knockdown (KD) of the reader IGF2BP2, writer METTL3, and eraser ALKBH5, with naive glioma cells and astrocytes as controls. Glioma cells exhibited a two-fold reduction in global m6A, suggesting progressive loss from healthy to malignant states. Integrated analysis revealed that m6A mediated control of gene expression is influenced by modification topology (CDS:3'UTR), transcript biotype, and length. Regulator KD, particularly ALKBH5 induced redistribution of m6A toward 3'UTR with consequent gene upregulation. We also identified m6A-mediated isoform switching, with a higher usage of retained intron and nonsense-mediated decay isoforms. Structural and splicing alterations at the isoform level were identified unique to each KD condition indicating m6A driven aberrant alternative splicing. At the functional level, KD specific remodeling of oncogenic signaling was also observed. ALKBH5 KD suppressed MYC targets and pro-apoptotic signaling while METTL3 KD enhanced mTOR and PI3K-AKT signaling. Collectively, these results demonstrate that m6A mediated regulation in glioma is highly context-dependent, defining distinct clinically relevant phenotypes. This has implications for future biomarker discovery and development of targeted therapeutics.

Intra-tumour heterogeneity is the molecular hallmark of renal cancer, and the molecular tumour composition determines the treatment outcome of renal cancer patients. In renal cancer tumourigenesis, in general, different tumour clones evolve over time. We analysed intra-tumour heterogeneity and subclonal mutation patterns in 178 tumour samples obtained from 89 clear cell renal cell carcinoma patients. In an initial discovery phase, whole-exome and transcriptome sequencing data from paired tumour biopsies from 16 ccRCC patients were used to design a gene panel for follow-up analysis. In this second phase, 826 selected genes were targeted at deep coverage in an extended cohort of 89 patients for a detailed analysis of tumour heterogeneity. On average, we found 22 mutations per patient. Pairwise comparison of the two biopsies from the same tumour revealed that on average 62% of the mutations in a patient were detected in one of the two samples. In addition to commonly mutated genes (VHL, PBRM1, SETD2 and BAP1), frequent subclonal mutations with low variant allele frequency (<10%) were observed in TP53 and in mucin coding genes MUC6, MUC16, and MUC3A. Of the 89 ccRCC tumours, 87 (~98%) harboured private mutations, occurring in only one of the paired tumour samples. Clonally exclusive pathway pairs were identified using the WES data set from 16 ccRCC patients. Our findings imply that shared and private mutations significantly contribute to the complexity of differential gene expression and pathway interaction, and might explain clonal evolution of different molecular renal cancer subgroups. Multi-regional sequencing is central for the identification of subclones within ccRCC.

Genomic data can facilitate personalized treatment decisions by enabling therapeutic hypotheses in individual patients. Conditional selection, which includes mutual exclusivity, is a signal that has been empirically useful for identifying mutations that may be sensitive to single agent targeted therapies. However, a low mutation frequency can underpower this signal for rare variants and prevent robust conclusions from genomic data. We develop a resampling based method for the direct pairwise comparison of conditional selection between sets of gene pairs. This effectively creates positive control guideposts of mutual exclusivity in known driver genes that normalizes differences in mutation abundance. We applied this method to a transcript variant of anaplastic lymphoma kinase (ALK) in melanoma, termed ALKATI, which has been the subject of a recent controversy in the literature. We reproduced some of the original cell transformation experiments, performed rescue experiments, and analyzed drug response data to revisit the original ALKATI findings. We found that ALKATI is not as mutually exclusive with BRAF or NRAS as BRAF and NRAS genes are with each other. We performed in vitro transformation assays and rescue assays that suggested that alternative transcript initiation in ALK is not likely to be sufficient for cellular transformation or growth and it does not predict single agent therapeutic dependency. Our work strongly disfavors the role of ALKATI as a targetable oncogenic driver that might be sensitive to single agent ALK treatment. The progress of other experimental agents in late-stage melanoma and our experimental and computational re-analysis led us to conclude that further single agent testing of ALK inhibitors in patients with ALKATI should be limited to cases where no other treatment hypotheses can be identified.

The traditional binary classification of somatic mutations in cancer as either drivers or passengers overlooks the potential cumulative impact of smaller-effect mutations. Here, we analyze 2,263 whole-genome-sequenced primary tumors across 31 cancer types to assess the functional contribution of passenger mutations in cancer development. We find that in the absence of canonical driver mutations, passenger mutations in cancer genes are significantly enriched, exhibit higher predicted pathogenicity, and are associated with aberrant expression, splicing disruption, altered transcription factor binding, and clinical outcomes that resemble those in the presence of driver mutations. The accumulation of passenger mutations in tumor suppressor genes correlates with significantly reduced expression and poorer prognosis, mirroring the functional outcomes of driver mutations. Notably, this is a previously uncharacterized mechanism of tumor suppressor inactivation, in which the accumulation of somatic mutations results in its progressive inactivation. Our results support a continuum model of mutational impact, where the collective influence of passenger mutations contributes to oncogenesis and clinical outcomes. This work advocates for integrative cancer models that incorporate all somatic mutations to more accurately reflect the complexity of tumor evolution.