Study case flow diagram for WES of translational specimens from patients enrolled in GOG281. One hundred thirty-four samples underwent successful WES, of which 112 were also evaluable for pERK via IHC. Additionally, 36 samples were evaluable for pERK IHC that did not have matching WES.

Purpose: Low-grade serous ovarian carcinoma (LGSOC) is a distinct form of ovarian cancer characterized by younger patient age and relative chemoresistance. The GOG281/LOGS trial (NCT02101788) investigated the efficacy of the MEK inhibitor trametinib compared with physician's choice standard-of-care (SOC) in patients with LGSOC with persistent/recurrent disease. The study demonstrated significantly improved progression-free survival (PFS) in the trametinib-treated arm. Experimental Design: Two hundred and sixty patients with recurrent/persistent LGSOC were enrolled and randomly assigned in GOG281. We performed molecular analysis of 170 patients with available tumor specimens, comprising whole-exome sequencing and phospho-ERK (pERK) IHC, to identify biomarkers of clinical benefit from trametinib. The demographics of the translational cohort (n = 170) were comparable with those of the total trial cohort. Results: High tumor pERK expression (greater than the median histoscore of 140) was associated with significantly prolonged PFS with trametinib treatment versus SOC (median 20.1 vs. 5.6 months, log-rank P < 0.0001; test for interaction P = 0.023). Tumors harboring canonical RAS-RAF-MAPK mutations (KRAS/BRAF/NRAS: 44/134, 32.8% of cases) had a higher response rate to trametinib (50.0% vs. 8.3%; Barnard's P = 0.0004; test for interaction P = 0.054), but KRAS/BRAF/NRAS status was not predictive of prolonged PFS (test for interaction P = 0.719). KRAS amplification (n = 5 without KRAS/NRAS/BRAF mutation) and mutation of MAPK-associated genes (n = 25 without KRAS/NRAS/BRAF mutation or KRAS copy number gain) expanded the number of cases with identifiable MAPK defects to 55.2%, but consideration of these events did not improve the discrimination of trametinib responders. Chr1p loss (49% of cases) was associated with lower pERK expression (P = 0.021). Conclusions: This exploratory analysis suggests that pERK expression and mutation of KRAS/BRAF/NRAS are candidate biomarkers of improved PFS and response to trametinib, respectively.

CTNNB1, the gene encoding β-catenin, is a frequent target for oncogenic mutations activating the canonical Wnt signaling pathway, typically through missense mutations within a degron hotspot motif in exon 3. Here, we combine saturation genome editing with a fluorescent reporter assay to quantify signaling phenotypes for all 342 possible missense mutations in the mutation hotspot. Our data define the genetic requirements for β-catenin degron function, refine the consensus motif for substrate recognition by β-TRCP and reveal diverse levels of signal activation among known driver mutations. Tumorigenesis in different human tissues involves selection for CTNNB1 mutations spanning distinct ranges of predicted activity. In hepatocellular carcinoma, mutation effect scores distinguish two tumor subclasses with different levels of β-catenin signaling, and weaker mutations predict greater immune cell infiltration in the tumor microenvironment. Our work provides a resource to understand mutational diversity within a pan-cancer mutation hotspot, with potential implications for targeted therapy.

Impact of pERK status and KRAS/BRAF/NRAS mutation status on GOG281 patient outcome. A, PFS of GOG281/LOGS patients with low-pERK tumors (pERK ≤ 140) in trametinib versus SOC arms. B, PFS of GOG281/LOGS patients with high-pERK tumors (pERK > 140) in trametinib versus SOC arms. C, PFS of GOG281/LOGS patients with KRAS/BRAF/NRAS WT tumors in trametinib versus SOC arms. D, PFS of GOG281/LOGS patients with KRAS/BRAF/NRAS-mutant tumors in trametinib versus SOC arms. Labeled HR refer to comparison of trametinib versus SOC arm.

Background Triple-negative breast cancer (TNBC) is associated with poor survival rate and high genomic instability, generating complex tumour genomes. However, the processes that generate this complexity are poorly studied in longitudinal samples. Here, we study the temporal dynamics of TNBC somatic mutations, revealing major transitions in tumour genome evolution, from diagnostic biopsies, through treatment, to cancer remission or recurrence. Methods Deep whole exome sequencing and CUTseq, a reduced representation whole genome sequencing approach, were performed in parallel, to comprehensively identify short nucleotide variants (SNVs), copy number alterations (CNAs) and aneuploidies. Tumour samples (N=74) from 22 patients were profiled before and after neoadjuvant chemotherapy (NACT), and encompassed spatially diverse samples from multiple primary breast tumours, to allow tracking of the gain and loss of candidate driver variants over time. Results Genome-wide SNV mutational burden remained stable across disease progression and RCB classes. However, recurrent SNVs were identified in several known TNBC driver genes in response to treatment, with TP53, MICA, CYP2D6, BRCA1, and BRCA2 being frequently altered. The candidate driver variants in these genes frequently exhibited dynamic changes throughout the course of a patient’s treatment, with the original SNVs in pre-treatment samples often lost, while novel variants in the same genes emerged at subsequent time points. In contrast to the stable genome-wide SNV burdens, dramatic changes in chromosome structure were seen in all tumours, with abundant CNAs and chromosome arm aneuploidies seen in pre-treatment samples, followed by frequent loss of these alterations post-treatment, and their re-emergence at recurrence. Whole genome duplication (WGD) events appear to drive these dynamics, with a higher frequency of pre-treatment WGD seen in patients with the best response to NACT. Conclusions Comprehensive longitudinal profiling of the TNBC genome demonstrates the complex interplay of SNVs and structural alterations during tumour progression, leading to diverse evolutionary trajectories impacting patient outcomes. Complex mutational patterns encompassing entire chromosomes emerge during progression, with WGD events making major contributions to intra-tumour heterogeneity, and emerging as a potential candidate biomarker of response at both tumour establishment and recurrence. ### Competing Interest Statement The authors have declared no competing interest. Genomic data generated in this study have been submitted to the European Genome/ Phenome Archive, with accession numbers EGAD00001015684 (CUTseq data) and EGAD00001015687 (WES data).

Human cancers are heterogeneous1. Dissecting how germline genetic variation and environmental factors shape tumour evolution using human datasets is limited by inherent diversity in genetic backgrounds2 and environmental exposures3-5. Here, to overcome these limitations, we re-ran early tumour evolution hundreds of times in diverged inbred mouse strains, generating matched histology and whole-genome and transcriptome sequences. The sex, environment and carcinogenic exposures were all controlled, and the study design allowed us to capture genetic variation comparable with that observed across human populations while exploiting the nested hierarchical structure of strain-litter-animal-tumour relationships. Our analyses reveal that epistatic interactions between genetic background and acquired somatic mutations result in population-specific disease progression, including choice of driver mutations, occurrence of whole-genome duplication and subclonal selection dynamics that mirror both cancer susceptibility and tumour growth rate. Even modest genetic divergence, comparable with that found across human ancestry groups, can strikingly alter selection pressures during cancer development to shape both cancer risk and the trajectory of tumour evolution.

Demographics of translational research population.

Unsupervised hierarchical clustering of chromosome arm-level copy-number alterations across biospecimens from patients enrolled in GOG281/LOGS.

Molecular landscape of tumor samples from patients enrolled in GOG281/LOGS. MAPK-associated, MAPK-associated genes as defined in the Gene Ontology Term GO:0000165; Chr1pq-aberrant, chr1p-loss with concurrent chr1q-gain.

pERK and other potential biomarkers of therapy response in LGSOC. A, pERK IHC examples demonstrating negative (0), weak (1+), moderate (2+), and intense (3+) positivity for histoscore calculation. Scale bars, 50 µm. B, Response to trametinib (top) and physician’s choice SOC (bottom) according to KRAS/BRAF/NRAS mutation status (left), pERK status (middle), and chr1 abnormalities (right). C, pERK histoscore according to KRAS/BRAF/NRAS mutation type. Labels specify the numbers within each group that were evaluable for pERK expression levels. D, pERK histoscore by chr1p-loss status. E, Frequency of pERK status between chr1p-loss and -intact groups. Chr1pq-aberrant, chr1p-loss with concurrent chr1q-gain.

Background: Half of high grade serous tubo-ovarian carcinomas (HGSOC) demonstrate homologous recombination repair (HRR) deficiency, most commonly through germline or somatic pathogenic variants in BRCA1/2 (gBRCA1/2 or sBRCA1/2). gBRCA1/2 is associated with favourable survival, greater response rate to platinum-based chemotherapy, and marked sensitivity to poly(ADP-ribose) polymerase (PARP) inhibitors. sBRCA1/2 has been assumed to confer a similar clinical phenotype; however, few studies have specifically investigated sBRCA1/2 versus gBRCA1/2 to demonstrate their equivalence. Methods: We investigated the association of gBRCA1/2, sBRCA1/2 and non-BRCA HRR gene mutations with HGSOC patient survival using two patient cohorts (cohort 1, n = 174 matched FFPE tumour and normal with panel-based sequencing; cohort 2, n = 279 matched fresh tumour and normal with whole genome sequencing). TCGA-OV samples (n = 316) were used for external validation. Results: Patients with HRR-mutant tumours (BRCA1, BRCA2, non-BRCA HRR-mutant) demonstrated prolonged survival across both cohorts (cohort 1: multivariable hazard ratio [multiHR] 0.53 [0.32-0.87]; cohort 2: multiHR 0.36 [0.25-0.51]). gBRCA1/2 and sBRCA1/2 were associated with a similar survival benefit compared to the HRR-wildtype group in the combined cohort (cohort 1 +2) (gBRCA1/2: multiHR 0.50 [0.34-0.71]; sBRCA1/2: multiHR 0.41 [0.25-0.68]). These findings were recapitulated using the TCGA-OV dataset (gBRCA1/2: multiHR 0.56 [0.34-0.91]; sBRCA1/2: multiHR 0.48 [0.25-0.92]). Non-BRCA HRR mutations were associated with marked survival advantage (multiHR vs HRR-wildtype 0.22 [0.11-0.45]). The survival advantage in BRCA1-mutant cases (germline or somatic) was less marked (multiHR for non-BRCA HRR-mutant vs BRCA1-mutant 0.41 [0.19-0.90]). gBRCA1/2, sBRCA1/2 and non-BRCA HRR mutations were all associated with high HRDetect scores measuring HRR deficiency (median 1.00 versus 0.56 in HRR-wildtype, P < 0.01). Conclusion: gBRCA1/2 and sBRCA1/2 are equivalent in their association with prolonged survival. Non-BRCA HRR gene mutations may be associated with markedly favourable survival in HGSOC.

Human cancers are heterogeneous. Their genomes evolve from genetically diverse germlines in complex and dynamic environments, including exposure to potential carcinogens. This heterogeneity of humans, our environmental exposures, and subsequent tumours makes it challenging to understand the extent to which cancer evolution is predictable. Addressing this limitation, we re-ran early tumour evolution hundreds of times in diverse, inbred mouse strains, capturing genetic variation comparable to and beyond that found in human populations. The sex, environment, and carcinogenic exposures were all controlled and tumours comprehensively profiled with whole genome and transcriptome sequencing. Within a strain, there was a high degree of consistency in the mutational landscape, a limited range of driver mutations, and all strains converged on the acquisition of a MAPK activating mutation with similar transcriptional disruption of that pathway. Despite these similarities in the phenotypic state of tumours, different strains took markedly divergent paths to reach that state. This included pronounced biases in the precise driver mutations, the strain specific occurrence of whole genome duplication, and differences in subclonal selection that reflected both cancer susceptibility and tumour growth rate. These results show that interactions between the germline genome and the environment are highly deterministic for the trajectory of tumour genome evolution, and even modest genetic divergence can substantially alter selection pressures during cancer development, influencing both cancer risk and the biology of the tumour that develops. ### Competing Interest Statement S.J.A. receives funding from AstraZeneca for a PhD studentship. J.C. has received an honorarium from Roche Diagnostics. P.F. is a member of the Scientific Advisory Board of Fabric Genomics, Inc..

Deciphering the structural variation across tumour genomes is crucial to determine the events driving tumour progression and better understand tumour adaptation and evolution. High grade serous ovarian cancer (HGSOC) is an exemplar tumour type showing extreme, but poorly characterised structural diversity. Here, we comprehensively describe the mutational landscape driving HGSOC, exploiting a large (N = 324), deeply whole genome sequenced dataset. We reveal two divergent evolutionary trajectories, affecting patient survival and involving differing genomic environments. One involves homologous recombination repair deficiency (HRD) while the other is dominated by whole genome duplication (WGD) with frequent chromothripsis, breakage-fusion-bridges and extra-chromosomal DNA. These trajectories contribute to structural variation hotspots, containing candidate driver genes with significantly altered expression. While structural variation predominantly drives tumorigenesis, we find high mtDNA mutation loads associated with shorter patient survival. We show that a combination of mutations in the mitochondrial and nuclear genomes impact prognosis, suggesting strategies for patient stratification.

BACKGROUND:Undifferentiated pleomorphic sarcoma (UPS) is a rare and aggressive soft tissue sarcoma with limited treatment options and a poor prognosis. As a complex karyotype tumor, UPS lacks recurrent targetable mutations, and response rates to standard first-line doxorubicin therapy are low. Phenotypic drug screening offers an alternative approach to identify new therapeutic targets without requiring prior knowledge of molecular mechanisms. METHODS:A library of FDA-approved compounds and a custom histone deacetylase (HDAC) inhibitor library were screened using well-annotated patient-derived cell lines. Hit compounds were further characterized using apoptosis assays and in vivo xenograft studies. Biomarkers of activity were evaluated using gene expression and western blot analyses. Synergy with doxorubicin was evaluated in combination assays. RESULTS:HDAC inhibitors emerged as a promising therapeutic class, demonstrating low IC50 values across cell lines (14.8-26.89 nM), with quisinostat taken forward for further evaluation. Gene expression changes in EPAS1, FOXO1, AMOT, and FOSL1 were observed as potential biomarkers of activity. Combination assays revealed synergy between quisinostat and doxorubicin (average ZIP score: 1.02-15.65; ZIPmax: 3.98-33.71), increasing apoptotic cell death in vitro. In vivo, quisinostat alone and in combination with doxorubicin significantly reduced the tumor volume (vehicle 160.0 ± 63.2 mm3, doxorubicin 78.0 ± 35.2 mm3, quisinostat 84.3 ± 13.1 mm3, and combination 49.2 ± 10.2 mm3). Quisinostat also showed potent activity in leiomyosarcoma (LMS) cell lines (5.82-31.32 nM), which represent an additional complex karyotype soft tissue sarcoma. CONCLUSIONS:Quisinostat demonstrated strong preclinical activity and synergy with standard-of-care doxorubicin in models of UPS and LMS.

Glioblastoma (GBM) is a heterogeneous and aggressive brain tumour that is invariably fatal despite maximal treatment. Genetic or transcriptomic 'biomarkers' could be used to stratify patients for treatments, however, pairing biomarkers with appropriate therapeutic 'targets' is challenging. Consequently, therapeutics have not yet been optimised for specific GBM patient subsets. Here we integrate genome-wide CRISPR/Cas9 knockout screening and genetic-annotation data for 60 distinct patient-derived, IDHwildtype, adult GBM cell lines, quantifying the essentiality of 15,145 genes. We describe a novel method using Targeted Learning, to estimate the effect size of GBM-relevant biomarkers on context-dependent gene essentiality (GBM-CoDE). We derive multiple target-biomarker pair hypotheses, which we release in an accessible platform to accelerate translation to biomarker-stratified clinical trials. Two of these (WWTR1 with EGFR mutation/amplification, and VRK1 with VRK2 expression suppression) have been validated in GBM, implying that our additional novel findings may be valid. Our method is readily translatable to other cancers of unmet need. ### Competing Interest Statement MTF, AE, MF, PMB, AK, SVB, CS: None. NC: is a scientific advisory board member and shareholder in Amplia Therapeutics Ltd (Melbourne, Australia); is and founder, shareholder, and management consultant of PhenoTherapeutics Ltd (Edinburgh, UK); is Director of Ther-IP Ltd (Edinburgh); and is Director of Edinburgh Innovations Ltd.

Background: Triple Negative Breast Cancer (TNBC) is characterised by extensive intra-tumour heterogeneity (ITH) where clonal lineages diverge from distinct subpopulations over time, impacting treatment resistance and influencing metastasis. However, the mutational dynamics underlying these lineages are poorly studied. Most TNBC patients with early or locally advanced disease receive neoadjuvant chemotherapy (NACT). Pathological complete response (pCR) to NACT is considered as a surrogate for good prognosis but patient response differs greatly. Both SNVs (short nucleotide variants) and copy number variants (CNVs) have been implicated as drivers of the adaptive response to chemotherapy and metastasis in TNBC. Here, we comprehensively investigated the mutational landscapes in a longitudinally sampled TNBC cohort, relating SNV and CNV patterns during the course of the disease to patient outcomes. Methods: All TNBC patients selected for the study were undergoing NACT. Samples included preNACT treatment (PreT), surgical postNACT treatment (PostT) and recurrence samples. Residual Cancer Burden (RCB) scores and tumour infiltrating lymphocytes (TILs) were reported by a breast cancer pathologist. DNA was extracted from FFPE tumour samples where homogenous tumour regions had been identified by the pathologist. Multiple regions of the PostT recurrence samples were selected for DNA extraction, resulting in 96 samples in total. Following whole exome sequencing, the raw sequencing reads were processed to identify germline and somatic variants. In addition, we optimised an affordable approach to profile genome wide CNVs in longitudinal samples. Bioinformatic analysis of SNV and CNV data then studied the dominant mutational patterns over time, and identified likely driver variants and disrupted pathways. Results: Our results demonstrate that low RCB score correlates with higher levels of TILs in the PreT samples. Tumour mutational burden (TMB) varied from 1-27 per Mb and was lowest in 2 patients with known germline mutations. SNV analysis identified variants in 69 genes previously reported to play roles in the progression of TNBC, the most frequently mutated being TP53. We also found suggestive evidence for novel driver variants under positive selection in the MICA gene. Overall, we identified an enrichment of mutations in genes associated with nucleic acid metabolic processes. The longitudinal sampling also allowed the detection of relatively early PreT mutations, showing enrichment in pathways involved in double-strand break repair and apoptotic signaling. Subsequently many of these early variants were found to be ‘conserved’ as mutations retained from PreT to PostT in samples from the same patient. In addition, we identified a novel class of SNVs that appear to arise only at later stages of the disease. In the CNV landscape, we identified regions that were commonly amplified or deleted in PreT samples, particularly a recurrent amplification of 8q. For some patients, the CNV landscape changed dramatically over the course of TNBC disease progression, with frequently altered genes differing markedly from those impacted by SNVs. Conclusions: We have developed relatively inexpensive profiling techniques to identify disease-associated variants in TNBC patients, allowing us to study their dynamics over the course of the disease. We present mutational profiles from before and after NACT from the same patient, which can be compared to reveal the variants that are gained or lost genome-wide during the evolution of a tumour. Ultimately, specific SNVs and CNVs associated with survival, recurrence and metastasis can be identified. These data will direct larger scale follow-up studies for biomarker validation and treatment stratification. Citation Format: Olga O|ikonomidou, Fiona Semple, Devin Bendixsen, Alastair Ironside, Natalie Wilson, Ailith Ewing, Colin Semple. Charting the longitudinal mutational landscape of triple negative breast cancer [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2024; 2024 Dec 10-13; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(12 Suppl):Abstract nr P2-03-23.

CTNNB1 , the gene encoding β-catenin, is a frequent target for oncogenic mutations activating the canonical Wnt signalling pathway, typically via missense mutations within a degron hotspot motif in exon 3. Here, we combine saturation genome editing with a fluorescent reporter assay to quantify signalling phenotypes for all 342 missense mutations in the mutation hotspot, including 74 recurrent mutations reported in over 6000 tumours. Our data define the genetic requirements for β-catenin degron function and reveal diverse levels of signal activation among known driver mutations. Tumorigenesis in different human tissues involves selection for CTNNB1 mutations spanning distinct ranges of effect size. In hepatocellular carcinoma, mutations that activate β-catenin relatively weakly are associated with worse prognosis compared to stronger activating mutations, despite greater immune cell infiltration in the tumour microenvironment. Our work therefore provides a resource to understand mutational diversity within a pan-cancer mutation hotspot, with potential implications for targeted therapy.