Copy number signatures and mutational processes in ovarian carcinoma

Metabolic imaging distinguishes ovarian cancer subtypes and detects their early and variable responses to treatment

High grade serous ovarian cancer displays two metabolic subtypes; a high OXPHOS subtype that shows increased expression of genes encoding electron transport chain components, increased oxygen consumption, and increased chemosensitivity, and a low OXPHOS subtype that exhibits glycolytic metabolism and is more drug resistant. We show here in patient-derived organoids and in the xenografts obtained by their subcutaneous implantation that the low OXPHOS subtype shows higher lactate dehydrogenase activity and monocarboxylate transporter 4 expression than the high OXPHOS subtype and increased lactate labeling in 13C magnetic resonance spectroscopy (MRS) measurements of hyperpolarized [1-13C]pyruvate metabolism. There was no difference between the subtypes in PET measurements of 2-deoxy-2-[fluorine-18]fluoro-D-glucose ([18F]FDG) uptake. Both metabolic imaging techniques could detect the early response to Carboplatin treatment in drug-sensitive high OXPHOS xenografts and no response in drug-resistant in low OXPHOS xenografts. 13C magnetic resonance spectroscopic imaging of hyperpolarized [1-13C]pyruvate metabolism has the potential to be used clinically to distinguish low OXPHOS and high OXPHOS tumor deposits in HGSOC patients and to detect their differential responses to treatment.

A Dirichlet-multinomial mixed model for determining differential abundance of mutational signatures

BACKGROUND

Mutational processes of diverse origin leave their imprints in the genome during tumour evolution. These imprints are called mutational signatures and they have been characterised for point mutations, structural variants and copy number changes. Each signature has an exposure, or abundance, per sample, which indicates how much a process has contributed to the overall genomic change. Mutational processes are not static, and a better understanding of their dynamics is key to characterise tumour evolution and identify cancer cell vulnerabilities that can be exploited during treatment. However, the structure of the data typically collected in this context makes it difficult to test whether signature exposures differ between conditions or time-points when comparing groups of samples. In general, the data consists of multivariate count mutational data (e.g. signature exposures) with two observations per patient, each reflecting a group.

RESULTS

We propose a mixed-effects Dirichlet-multinomial model: within-patient correlations are taken into account with random effects, possible correlations between signatures by making such random effects multivariate, and a group-specific dispersion parameter can deal with particularities of the groups. Moreover, the model is flexible in its fixed-effects structure, so that the two-group comparison can be generalised to several groups, or to a regression setting. We apply our approach to characterise differences of mutational processes between clonal and subclonal mutations across 23 cancer types of the PCAWG cohort. We find ubiquitous differential abundance of clonal and subclonal signatures across cancer types, and higher dispersion of signatures in the subclonal group, indicating higher variability between patients at subclonal level, possibly due to the presence of different clones with distinct active mutational processes.

CONCLUSIONS

Mutational signature analysis is an expanding field and we envision our framework to be used widely to detect global changes in mutational process activity. Our methodology is available in the R package CompSign and offers an ample toolkit for the analysis and visualisation of differential abundance of compositional data such as, but not restricted to, mutational signatures.

Exome sequencing identifies HELB as a novel susceptibility gene for non-mucinous, non-high-grade-serous epithelial ovarian cancer

Rare, germline loss-of-function variants in a handful of DNA repair genes are associated with epithelial ovarian cancer. The aim of this study was to evaluate the role of rare, coding, loss-of-function variants across the genome in epithelial ovarian cancer. We carried out a gene-by-gene burden test with various histotypes using data from 2573 non-mucinous cases and 13,923 controls. Twelve genes were associated at a False Discovery Rate of less than 0.1 of which seven were the known ovarian cancer susceptibility genes BRCA1, BRCA2, BRIP1, RAD51C, RAD51D, MSH6 and PALB2. The other five genes were OR2T35, HELB, MYO1A and GABRP which were associated with non-high-grade serous ovarian cancer and MIGA1 which was associated with high-grade serous ovarian cancer. Further support for the association of HELB association comes from the observation that loss-of-function variants in HELB are associated with age at natural menopause and Mendelian randomisation analysis shows an association between genetically predicted age at natural menopause and endometrioid ovarian cancer, but not high-grade serous ovarian cancer.

Patterns and variations of copy number alterations in acute myeloid leukemia: insights from the LeukAtlas database

Recent pan-cancer analysis revealed the global pattern and potential aetiologies of copy number variation signatures in human cancers, particularly those derived from non-hematopoietic tissues. In sharp contrast, the generally low CNV burden in leukemia leaves the CNV landscape and variations largely unexplored, impeding understanding of CNV in leukemia development. Through a comprehensive compilation of public datasets, we constructed LeukAtlas ( https://ngdc.cncb.ac.cn/leukemia ), a user-friendly database encompassing 12,597 CNVs from 1446 AML samples across diverse subtypes and age groups, providing tools for multidimensional CNV analysis. Our analyses suggested the CNV levels significantly varied among AML patients. We discovered two previously unknown CNV patterns in adult AML patients, dominated by segmental LOH and/or minor gain, which have been shown to be associated with chromosomal instability in solid tumors. Additionally, we defined two potential new AML subgroups based on CNVs status, providing new stratification markers within the existing karyotype framework. Representing the most extensive CNV collection in AML, LeukAtlas is a valuable resource for exploring the role of CNVs in the pathogenesis and prognosis stratification of leukemia. Interrogation of this database uncovers novel subclasses with unique CNV profiles and reveals heterogeneous CNV patterns in AML, demonstrating the potential role of chromosomal instability in AML progression.

Early Detection of Ovarian Cancer Using Cell-Free DNA Fragmentomes and Protein Biomarkers

SIGNIFICANCE

There is an unmet need for effective ovarian cancer screening and diagnostic approaches that enable earlier-stage cancer detection and increased overall survival. We have developed a high-performing accessible approach that evaluates cfDNA fragmentomes and protein biomarkers to detect ovarian cancer.

Homologous recombination deficiency (HRD) diagnostics: underlying mechanisms and new perspectives

Homologous recombination deficiency (HRD) is considered a universal and effective sign of a tumor's sensitivity to poly(ADP-ribose) polymerase (PARP) inhibitors. HRD diagnostics have undergone several stages of transformations: from detection of point mutations in HR-related genes and large regions with loss of heterozygosity detected using single-nucleotide polymorphism arrays to whole-genome signatures of single-nucleotide variants, large genomic rearrangements (LGRs), and copy number alterations. All these methods have their own advantages and limitations. HRD tests, based on signatures of LGRs and copy number alterations, show in hindsight that some progenitor cells have possessed HRD status but not the current state of the genome. The aim of this review was to compare different methods of HRD detection and mechanisms of formation of HRD-specific LGRs. In the last several years, new data appeared implying a crucial role of proteins BRCA1 and BRCA2 in the resolution of stalled replication forks that may be associated with at least some of LGRs observed in HRD-positive tumors. Reviewing current knowledge on these mechanisms, distributions of different LGR types, and limitations of sequencing technologies and algorithms of data analysis, we offer some new perspectives on HRD diagnostics. We hope that this review will help to accelerate the development of new diagnostic approaches in this important field of molecular oncology.

Transcription and DNA replication collisions lead to large tandem duplications and expose targetable therapeutic vulnerabilities in cancer

Despite the abundance of somatic structural variations (SVs) in cancer, the underlying molecular mechanisms of their formation remain unclear. In the present study, we used 6,193 whole-genome sequenced tumors to study the contributions of transcription and DNA replication collisions to genome instability. After deconvoluting robust SV signatures in three independent pan-cancer cohorts, we detected transcription-dependent, replicated-strand bias, the expected footprint of transcription-replication collision (TRC), in large tandem duplications (TDs). Large TDs are abundant in female-enriched, upper gastrointestinal tract and prostate cancers. They are associated with poor patient survival and mutations in TP53, CDK12 and SPOP. Upon inactivating CDK12, cells display significantly more TRCs, R-loops and large TDs. Inhibition of WEE1, CHK1 and ATR selectively inhibits the growth of cells deficient in CDK12. Our data suggest that large TDs in cancer form as a result of TRCs and their presence can be used as a biomarker for prognosis and treatment.

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Coordinated protein modules define DNA damage responses to carboplatin at single cell resolution in human ovarian carcinoma models

Tubo-ovarian high-grade serous carcinoma (HGSC) is the most lethal gynecological malignancy and frequently responds to platinum-based chemotherapy because of common genetic and somatic impairment of DNA damage repair (DDR) pathways. The mechanisms of clinical platinum resistance are diverse and poorly molecularly defined. Consequently, there are no biomarkers or medicines that improve patient outcomes. Herein we use single cell mass cytometry (CyTOF) to systematically evaluate the phosphorylation and abundance of proteins known to participate in the DNA damage response (DDR). Single cell analyses of highly characterized HGSC cell lines that phenocopy human patients show that cells with comparable levels of intranuclear platinum, a proxy for carboplatin uptake, undergo different cell fates. Unsupervised analyses revealed a continuum of DDR responses. Decompositional methods were used to identify eight distinct protein modules of carboplatin resistance and sensitivity at single cell resolution. CyTOF profiling of primary and secondary platinum-resistance patient models shows that a complex DDR sensitivity module is strongly associated with response, suggesting it as a potential tool to clinically characterize complex drug resistance phenotypes.

SAMURAI: shallow analysis of copy number alterations using a reproducible and integrated bioinformatics pipeline

Shallow whole-genome sequencing (sWGS) offers a cost-effective approach to detect copy number alterations (CNAs). However, there remains a gap for a standardized workflow specifically designed for sWGS analysis. To address this need, in this work we present SAMURAI, a bioinformatics pipeline specifically designed for analyzing CNAs from sWGS data in a standardized and reproducible manner. SAMURAI is built using established community standards, ensuring portability, scalability, and reproducibility. The pipeline features a modular design with independent blocks for data preprocessing, copy number analysis, and customized reporting. Users can select workflows tailored for either solid or liquid biopsy analysis (e.g. circulating tumor DNA), with specific tools integrated for each sample type. The final report generated by SAMURAI provides detailed results to facilitate data interpretation and potential downstream analyses. To demonstrate its robustness, SAMURAI was validated using simulated and real-world data sets. The pipeline achieved high concordance with ground truth data and maintained consistent performance across various scenarios. By promoting standardization and offering a versatile workflow, SAMURAI empowers researchers in diverse environments to reliably analyze CNAs from sWGS data. This, in turn, holds promise for advancements in precision medicine.

Retinoblastoma Protein Loss in p53 Abnormal Endometrial Carcinoma: Histologic and Clinicopathological Correlates

Of the 4 molecular subtypes of endometrial cancer (EC), p53-abnormal (p53abn) EC is associated with abundant copy number alterations and the worst clinical outcome. Patients with p53abn EC have the highest risk of disease recurrence and death, independent of tumor grade and histologic subtype. Currently, all invasive p53abn ECs are considered high risk, and no prognostic biomarkers have yet been found that can aid in clinical management. Here, we aimed to test whether loss of retinoblastoma (RB) protein expression using immunohistochemistry has the potential for prognostic refinement of p53abn EC. A large cohort of 227 p53abn ECs collected from the PORTEC-1/2/3 clinical trials and the Medisch Spectrum Twente cohort study was investigated, and RB loss was identified in 7.0% (n = 16/227). RB-lost p53abn ECs were predominantly high-grade endometrioid ECs (n = 6, 37.5%) and carcinosarcomas with endometrioid-type epithelial component (n = 5, 31.3%). Histologically, RB-lost p53abn ECs were typified by high-grade nuclear atypia (n = 16, 100%), predominantly solid growth pattern (n = 15/16, 93.8%), and polypoid growth (n = 9/16, 56.3%). Copy number loss involving the RB1 locus was identified in the majority of RB-lost p53abn EC (n = 13/14, 92.9%), explaining the loss of RB expression. Comparative analysis also showed that RB-lost p53abn ECs were diagnosed at earlier stages than RB-retained p53abn EC (P = .014). Interestingly, RB-lost p53abn EC showed prolonged time to overall recurrence (P = .038), even within stage I alone (P = .040). These findings highlight distinct morphomolecular features in RB-lost p53abn ECs and confirm the utility of RB immunohistochemistry as a surrogate for underlying molecular RB1 alterations. To our knowledge, this is the first study to show the potential use of RB in prognostic refinement of p53abn EC, although validation is warranted.

Prognostic Relevance of Copy Number Losses in Ovarian Cancer

BACKGROUND/OBJECTIVES

Aneuploidy is a prevalent cancer feature that occurs in many solid tumors. For example, high-grade serous ovarian cancer shows a high level of copy number alterations and genomic rearrangements. This makes genomic variants appealing as diagnostic or prognostic biomarkers, as well as for their easy detection. In this study, we focused on copy number (CN) losses shared by ovarian cancer stem cells (CSCs) to identify chromosomal regions that may be important for CSC features and, in turn, for patients' prognosis.

METHODS

Array-CGH and bioinformatic analyses on three CSCs subpopulations were performed.

RESULTS

Pathway and gene ontology analyses on genes involved in copy number loss in all CSCs revealed a significant decrease in mRNA surveillance pathway, as well as miRNA-mediated gene silencing. Then, starting from these CN losses, we validated their potential prognostic relevance by analyzing the TCGA cohort. Notably, losses of 4q34.3-q35.2, 8p21.2-p21.1, and 18q12.2-q23 were linked to increased genomic instability. Loss of 18q12.2-q23 was also related to a higher tumor stage and poor prognosis. Finally, specific genes mapping in these regions, such as PPP2R2A and TPGS2A, emerged as potential biomarkers.

CONCLUSIONS

Our findings highlight the importance of genomic alterations in ovarian cancer and their impact on tumor progression and patients' prognosis, offering advance in understanding of the application of numerical aberrations as prognostic ovarian cancer biomarkers.

Decoding the pathological and genomic profile of epithelial ovarian cancer

Ovarian cancer (OC) is one of the most common cancers in women, with a high mortality rate. Most of published studies have been focused on Caucasian populations, with the need to explore biological features and clinical outcomes of patients from other ethnicities. We described clinical outcome (progression-free survival and overall survival) and biomarkers associated with survival in a cohort of patients with OC from Tunisia. Using immunohistochemistry, we assessed the expression of 14 proteins known to be altered in OC in a cohort of 198 patients. We explored the correlation between protein expression and copy number alteration (CNA) profiles. FIGO stage, menopausal status and mismatch repair deficiency were associated with survival. ERBB2 amplification was correlated with high ERBB2 expression (OR = 69.32, p = 4.03 E-09), and high PDL1 expression was associated to CD274 amplification (OR = 4.97, p = 5.79 E-2). We identified a correlation between survival and exposure to two CNA signatures (MAPK pathway and BRCA-related homologous recombination deficiency). Moreover, Gama-H2AX protein expression was correlated with exposure to a genomic signature associated with homologous recombination deficiency. We observed that OC clinical and pathological characteristics of these patients from Tunisia were similar to those of Caucasian patients. We identified frequent CNA in this population that need to be confirmed in other sets from Africa.

Effectiveness of PARP Inhibitor Maintenance Therapy in Ovarian Cancer by BRCA1/2 and a Scar-Based HRD Signature in Real-World Practice

PURPOSE

The purpose of the study was to compare the effectiveness of PARP inhibitor maintenance therapy (mPARPi) in real-world practice by biomarker status [BRCA1/2 alterations (BRCAalt) and a homologous recombination deficiency signature (HRDsig)] in advanced ovarian cancer.

EXPERIMENTAL DESIGN

Patients with ovarian cancer receiving first-line platinum-based chemotherapy and either mPARPi or no maintenance were included. Patient data were obtained by a US-based de-identified ovarian cancer Clinico-Genomic Database, from ∼280 US cancer clinics (01/2015-03/2023). Real-world progression-free survival (rwPFS) and overall survival (rwOS) were compared by biomarker status using Cox models, weighted by propensity scores.

RESULTS

Of 673 patients, 160 received mPARPi [31.2% BRCAalt and 51.9% HRDsig(+)] and 513 no maintenance [15.6% BRCAalt and 34.1% HRDsig(+)]. BRCAalt patients receiving mPARPi versus no maintenance had favorable rwPFS [HR, 0.48; 95% confidence interval (CI), 0.26-0.87; P = 0.0154], as did BRCA wild-type (WT; HR, 0.76; 95% CI, 0.57-1.01; P = 0.0595). Favorable rwOS was not observed with mPARPi for BRCAalt or BRCA-WT. HRDsig(+) patients receiving mPARPi versus no maintenance had favorable rwPFS (HR, 0.36; 95% CI, 0.24-0.55; P < 0.001) and numerically favorable rwOS (HR, 0.46; 95% CI, 0.21-1.02; P = 0.0561). No differences were observed for HRDsig(-). mPARPi treatment interaction was observed for HRDsig(+) versus HRDsig(-) (rwPFS P < 0.001/rwOS P = 0.016) but not for BRCAalt versus BRCA-WT. Patients with BRCA-WT/HRDsig(+) receiving mPARPi had favorable rwPFS (HR, 0.40; 95% CI, 0.22-0.72; P = 0.003), whereas no difference was observed for BRCA-WT/HRDsig(-).

CONCLUSIONS

HRDsig predicted benefit of mPARPi better than BRCAalt. Patients with HRDsig(+) status experienced favorable outcomes, even if they had BRCA-WT status. In contrast, patients with HRDsig(-) status did not show significant benefit from mPARPi treatment. HRDsig might predict benefit from mPARPi regardless of BRCAalt status.

Mapping spatial organization and genetic cell-state regulators to target immune evasion in ovarian cancer

The drivers of immune evasion are not entirely clear, limiting the success of cancer immunotherapies. Here we applied single-cell spatial and perturbational transcriptomics to delineate immune evasion in high-grade serous tubo-ovarian cancer. To this end, we first mapped the spatial organization of high-grade serous tubo-ovarian cancer by profiling more than 2.5 million cells in situ in 130 tumors from 94 patients. This revealed a malignant cell state that reflects tumor genetics and is predictive of T cell and natural killer cell infiltration levels and response to immune checkpoint blockade. We then performed Perturb-seq screens and identified genetic perturbations-including knockout of PTPN1 and ACTR8-that trigger this malignant cell state. Finally, we show that these perturbations, as well as a PTPN1/PTPN2 inhibitor, sensitize ovarian cancer cells to T cell and natural killer cell cytotoxicity, as predicted. This study thus identifies ways to study and target immune evasion by linking genetic variation, cell-state regulators and spatial biology.

Recent Advances in Genomic Approaches for the Detection of Homologous Recombination Deficiency

Accurate detection of homologous recombination deficiency (HRD) in cancer patients is paramount in clinical applications, as HRD confers sensitivity to poly(ADP-ribose) polymerase (PARP) inhibitors. With the advances in genome sequencing technology, mutational profiling on a genome-wide scale has become readily accessible, and our knowledge of the genomic consequences of HRD has been greatly expanded and refined. Here, we review the recent advances in HRD detection methods. We examine the copy number and structural alterations that often accompany the genome instability that results from HRD, describe the advantages of mutational signature-based methods that do not rely on specific gene mutations, and review some of the existing algorithms used for HRD detection. We also discuss the choice of sequencing platforms (panel, exome, or whole-genome) and catalog the HRD detection assays used in key PARP inhibitor trials.

Mutations, substitutions, and selection: Linking mutagenic processes to cancer using evolutionary theory

Cancers are the product of evolutionary events, where molecular variation occurs and accumulates in tissues and tumors. Sequencing of this molecular variation informs not only which variants are driving tumorigenesis, but also the mechanisms behind what is fueling mutagenesis. Both of these details are crucial for preventing premature deaths due to cancer, whether it is by targeting the variants driving the cancer phenotype or by measures to prevent exogenous mutations from contributing to somatic evolution. Here, we review tools to determine both molecular signatures and cancer drivers, and avenues by which these metrics may be linked.

Endometrioid ovarian carcinoma landscape: pathological and molecular characterization

Endometrioid ovarian cancers (EOvC) are usually managed as serous tumors. In this study, we conducted a comprehensive molecular investigation to uncover the distinct biological characteristics of EOvC. This retrospective multicenter study involved patients from three European centers. We collected clinical data and formalin-fixed paraffin-embedded (FFPE) samples for analysis at the DNA level using panel-based next-generation sequencing and array-comparative genomic hybridization. Additionally, we examined mRNA expression using NanoString nCounter® and protein expression through tissue microarray. We compared EOvC with other ovarian subtypes and uterine endometrioid tumors. Furthermore, we assessed the impact of molecular alterations on patient outcomes, including progression-free survival (PFS) and overall survival (OS). Preliminary analysis of clinical data from 668 patients, including 86 (12.9%) EOvC, revealed more favorable prognosis for EOvC compared with serous ovarian carcinoma (5-year OS of 60% versus 45%; P = 0.001) driven by diagnosis at an earlier stage. Immunohistochemistry and copy number alteration (CNA) profiles of 43 cases with clinical data and FFPE samples available indicated that EOvC protein expression and CNA profiles were more similar to endometrioid endometrial tumors than to serous ovarian carcinomas. EOvC exhibited specific alterations, such as lower rates of PTEN loss, mutations in DNA repair genes, and P53 abnormalities. Survival analysis showed that patients with tumors harboring loss of PTEN expression had worse outcomes (median PFS 19.6 months vs. not reached; P = 0.034). Gene expression profile analysis confirmed that EOvC differed from serous tumors. However, comparison to other rare subtypes of ovarian cancer suggested that the EOvC transcriptomic profile was close to that of ovarian clear cell carcinoma. Downregulation of genes involved in the PI3K pathway and DNA methylation was observed in EOvC. In conclusion, EOvC represents a distinct biological entity and should be regarded as such in the development of specific clinical approaches.

Multimodal Spatial Profiling Reveals Immune Suppression and Microenvironment Remodeling in Fallopian Tube Precursors to High-Grade Serous Ovarian Carcinoma

High-Grade Serous Ovarian Cancer (HGSOC) originates from fallopian tube (FT) precursors. However, the molecular changes that occur as precancerous lesions progress to HGSOC are not well understood. To address this, we integrated high-plex imaging and spatial transcriptomics to analyze human tissue samples at different stages of HGSOC development, including p53 signatures, serous tubal intraepithelial carcinomas (STIC), and invasive HGSOC. Our findings reveal immune modulating mechanisms within precursor epithelium, characterized by chromosomal instability, persistent interferon (IFN) signaling, and dysregulated innate and adaptive immunity. FT precursors display elevated expression of MHC-class I, including HLA-E, and IFN-stimulated genes, typically linked to later-stage tumorigenesis. These molecular alterations coincide with progressive shifts in the tumor microenvironment, transitioning from immune surveillance in early STICs to immune suppression in advanced STICs and cancer. These insights identify potential biomarkers and therapeutic targets for HGSOC interception and clarify the molecular transitions from precancer to cancer.

Durable benefit from poly(ADP-ribose) polymerase inhibitors in metastatic prostate cancer in routine practice: biomarker associations and implications for optimal clinical next-generation sequencing testing

BACKGROUND

Controlled trials have consistently demonstrated the efficacy of poly(ADP-ribose) polymerase inhibitors (PARPis) in patients with metastatic castration-resistant prostate cancer (mCRPC) and BRCA1 or BRCA2 alterations (BRCAalt). However, the reported efficacy of PARPi for alterations in other homologous recombination repair (HRR) genes is less consistent. We sought to evaluate the routine practice effectiveness of PARPi between and within these groups.

DESIGN

Patient-level data from a deidentified nationwide (USA-based) cancer clinico-genomic database between January 2011 and September 2023 were extracted. Patients with mCRPC and comprehensive genomic profiling by liquid biopsy [circulating tumor DNA (ctDNA)] or tissue (tumor) biopsy and who received single-agent PARPi were included and grouped by BRCAalt, ATMalt, other HRR, or no HRR. We further subcategorized BRCAalt into homozygous loss (BRCAloss) and all other deleterious BRCAalt (otherBRCAalt).

RESULTS

A total of 445 patients met inclusion criteria: 214 with tumor and 231 with ctDNA. BRCAalt had more favorable outcomes to PARPi compared with ATM, other HRR, and no HRR groups. Within the BRCAalt subgroup, compared with other BRCAalt, BRCAloss had a more favorable time to next treatment (median 9 versus 19.4 months, P = 0.005), time to treatment discontinuation (median 8 versus 14 months, P = 0.006), and routine practice overall survival (median 14.7 versus 19.4 months, P = 0.016). Tumor BRCAloss prevalence (3.1%) was similar to ctDNA prevalence in liquid biopsy specimens with high tumor fraction (>20%). BRCAloss was not detected in orthogonal germline testing.

CONCLUSIONS

PARPi routine practice effectiveness between groups mirrors prospective trials. Within the BRCAalt group, BRCAloss had the best outcomes. Unless the ctDNA tumor fraction is very high, somatic tissue testing (archival or metastatic) should be prioritized to identify patients who may benefit most from PARPi. When tissue testing is not clinically feasible, sufficient ctDNA tumor fraction levels for detection are enriched at clinical timepoints associated with tumor progression.

The genomic trajectory of ovarian high-grade serous carcinoma can be observed in STIC lesions

Ovarian high-grade serous carcinoma (HGSC) originates in the fallopian tube, with secretory cells carrying a TP53 mutation, known as p53 signatures, identified as potential precursors. p53 signatures evolve into serous tubal intraepithelial carcinoma (STIC) lesions, which in turn progress into invasive HGSC, which readily spreads to the ovary and disseminates around the peritoneal cavity. We recently investigated the genomic landscape of early- and late-stage HGSC and found higher ploidy in late-stage (median 3.1) than early-stage (median 2.0) samples. Here, to explore whether the high ploidy and possible whole-genome duplication (WGD) observed in late-stage disease were determined early in the evolution of HGSC, we analysed archival formalin-fixed paraffin-embedded (FFPE) samples from five HGSC patients. p53 signatures and STIC lesions were laser-capture microdissected and sequenced using shallow whole-genome sequencing (sWGS), while invasive ovarian/fallopian tube and metastatic carcinoma samples underwent macrodissection and were profiled using both sWGS and targeted next-generation sequencing. Results showed highly similar patterns of global copy number change between STIC lesions and invasive carcinoma samples within each patient. Ploidy changes were evident in STIC lesions, but not p53 signatures, and there was a strong correlation between ploidy in STIC lesions and invasive ovarian/fallopian tube and metastatic samples in each patient. The reconstruction of sample phylogeny for each patient from relative copy number indicated that high ploidy, when present, occurred early in the evolution of HGSC, which was further validated by copy number signatures in ovarian and metastatic tumours. These findings suggest that aberrant ploidy, suggestive of WGD, arises early in HGSC and is detected in STIC lesions, implying that the trajectory of HGSC may be determined at the earliest stages of tumour development. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Genomic Catastrophe (Chromothripsis and Polyploidy) Correlates With Tumor Distribution in Extrauterine High-grade Serous Carcinoma

Most extrauterine high-grade serous carcinomas (HGSCs) are thought to develop first in the distal fallopian tube. Most models of HGSC assume origin from relatively stable, noninvasive serous tubal intraepithelial carcinomas. However, widespread tumor involvement in the absence of a serous tubal intraepithelial carcinoma could occur after catastrophic genomic events (CGEs; such as chromothripsis or polyploidy). Twenty-six HGSCs assigned to fallopian tube (n = 9, group 1) and/or ovary (n = 9, group 2), and primary peritoneal (n = 8, group 3) were assessed by microarray (Oncoscan). CGEs were identified in 15/26 (57.7%); chromothripsis-like pattern in 13/26 (50.0%) and polyploidy in 6/26 (23.1%). CGE was seen in 4/9 (44.4%), 9/9 (100%), and 2/8 (25%) cases in groups 1. 2, and 3, respectively. Overall, CGEs were seen in 9/9 (100%) cases with grossly evident ovarian parenchymal involvement versus 6/17 (35.3%) without ( P = 0.0024). Ovarian size (measured on the long axis) correlated with CGE positivity ( P = 0.016). CGEs are significantly more common in HGSCs with ovarian parenchymal involvement compared with those limited to the fallopian tube and/or extraovarian tissues. These associations suggest geographically different tumor growth patterns and support the subdivision of HGSCs according to not only the stage but also tumor distribution. They have implications for clinical and pathologic presentation, trajectory of tumor evolution, and in the case of primary peritoneal HGSCs, potentially unique precursors to tumor transitions that could inform or influence cancer prevention efforts.

Copy number signatures and CCNE1 amplification reveal the involvement of replication stress in high-grade endometrial tumors oncogenesis

PURPOSE

Managing high-grade endometrial cancer in Martinique poses significant challenges. The diversity of copy number alterations in high-grade endometrial tumors, often associated with a TP53 mutation, is a key factor complicating treatment. Due to the high incidence of high-grade tumors with poor prognosis, our study aimed to characterize the molecular signature of these tumors within a cohort of 25 high-grade endometrial cases.

METHODS

We conducted a comprehensive pangenomic analysis to categorize the copy number alterations involved in these tumors. Whole-Exome Sequencing (WES) and Homologous Recombination (HR) analysis were performed. The alterations obtained from the WES were classified into various signatures using the Copy Number Signatures tool available in COSMIC.

RESULTS

We identified several signatures that correlated with tumor stage and disctinct prognoses. These signatures all seem to be linked to replication stress, with CCNE1 amplification identified as the primary driver of oncogenesis in over 70% of tumors analyzed.

CONCLUSION

The identification of CCNE1 amplification, which is currently being explored as a therapeutic target in clinical trials, suggests new treatment strategies for high-grade endometrial cancer. This finding holds particular significance for Martinique, where access to care is challenging.

Genetic variation across and within individuals

Germline variation and somatic mutation are intricately connected and together shape human traits and disease risks. Germline variants are present from conception, but they vary between individuals and accumulate over generations. By contrast, somatic mutations accumulate throughout life in a mosaic manner within an individual due to intrinsic and extrinsic sources of mutations and selection pressures acting on cells. Recent advancements, such as improved detection methods and increased resources for association studies, have drastically expanded our ability to investigate germline and somatic genetic variation and compare underlying mutational processes. A better understanding of the similarities and differences in the types, rates and patterns of germline and somatic variants, as well as their interplay, will help elucidate the mechanisms underlying their distinct yet interlinked roles in human health and biology.

Proteomic landscape of epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is a deadly disease with limited diagnostic biomarkers and therapeutic targets. Here we conduct a comprehensive proteomic profiling of ovarian tissue and plasma samples from 813 patients with different histotypes and therapeutic regimens, covering the expression of 10,715 proteins. We identify eight proteins associated with tumor malignancy in the tissue specimens, which are further validated as potential circulating biomarkers in plasma. Targeted proteomics assays are developed for 12 tissue proteins and 7 blood proteins, and machine learning models are constructed to predict one-year recurrence, which are validated in an independent cohort. These findings contribute to the understanding of EOC pathogenesis and provide potential biomarkers for early detection and monitoring of the disease. Additionally, by integrating mutation analysis with proteomic data, we identify multiple proteins related to DNA damage in recurrent resistant tumors, shedding light on the molecular mechanisms underlying treatment resistance. This study provides a multi-histotype proteomic landscape of EOC, advancing our knowledge for improved diagnosis and treatment strategies.

The genomic landscape of lung cancer in never-smokers from the Women's Health Initiative

Over 200,000 individuals are diagnosed with lung cancer in the United States every year, with a growing proportion of cases, especially lung adenocarcinoma, occurring in individuals who have never smoked. Women over the age of 50 comprise the largest affected demographic. To understand the genomic drivers of lung adenocarcinoma and therapeutic response in this population, we performed whole genome and/or whole exome sequencing on 73 matched lung tumor/normal pairs from postmenopausal women who participated in the Women's Health Initiative. Somatic copy number alterations showed little variation by smoking status, suggesting that aneuploidy may be a general characteristic of lung cancer regardless of smoke exposure. Similarly, clock-like and APOBEC mutation signatures were prevalent but did not differ in tumors from smokers and never-smokers. However, mutations in both EGFR and KRAS showed unique allelic differences determined by smoking status that are known to alter tumor response to targeted therapy. Mutations in the MYC-network member MGA were more prevalent in tumors from smokers. Fusion events in ALK, RET, and ROS1 were absent, likely due to age-related differences in fusion prevalence. Our work underscores the profound effect of smoking status, age, and sex on the tumor mutational landscape and identifies areas of unmet medical need.

AI-based histopathology image analysis reveals a distinct subset of endometrial cancers

Endometrial cancer (EC) has four molecular subtypes with strong prognostic value and therapeutic implications. The most common subtype (NSMP; No Specific Molecular Profile) is assigned after exclusion of the defining features of the other three molecular subtypes and includes patients with heterogeneous clinical outcomes. In this study, we employ artificial intelligence (AI)-powered histopathology image analysis to differentiate between p53abn and NSMP EC subtypes and consequently identify a sub-group of NSMP EC patients that has markedly inferior progression-free and disease-specific survival (termed 'p53abn-like NSMP'), in a discovery cohort of 368 patients and two independent validation cohorts of 290 and 614 from other centers. Shallow whole genome sequencing reveals a higher burden of copy number abnormalities in the 'p53abn-like NSMP' group compared to NSMP, suggesting that this group is biologically distinct compared to other NSMP ECs. Our work demonstrates the power of AI to detect prognostically different and otherwise unrecognizable subsets of EC where conventional and standard molecular or pathologic criteria fall short, refining image-based tumor classification. This study's findings are applicable exclusively to females.

New immune phenotypes for treatment response in high-grade serous ovarian carcinoma patients

Despite advances in surgical and therapeutic approaches, high-grade serous ovarian carcinoma (HGSOC) prognosis remains poor. Surgery is an indispensable component of therapeutic protocols, as removal of all visible tumor lesions (cytoreduction) profoundly improves the overall survival. Enhanced predictive tools for assessing cytoreduction are essential to optimize therapeutic precision. Patients' immune status broadly reflects the tumor cell biological behavior and the patient responses to disease and treatment. Serum cytokine profiling is a sensitive measure of immune adaption and deviation, yet its integration into treatment paradigms is underexplored. This study is part of the IMPACT trial (NCT03378297) and aimed to characterize immune responses before and during primary treatment for HGSOC to identify biomarkers for treatment selection and prognosis. Longitudinal serum samples from 22 patients were collected from diagnosis until response evaluation. Patients underwent primary cytoreductive surgery or neoadjuvant chemotherapy (NACT) based on laparoscopy scoring. Twenty-seven serum cytokines analyzed by Bio-Plex 200, revealed two immune phenotypes at diagnosis: Immune High with marked higher serum cytokine levels than Immune Low. The immune phenotypes reflected the laparoscopy scoring and allocation to surgical treatment. The five Immune High patients undergoing primary cytoreductive surgery exhibited immune mobilization and extended progression-free survival, compared to the Immune Low patients undergoing the same treatment. Both laparoscopy and cytoreductive surgery induced substantial and transient changes in serum cytokines, with upregulation of the inflammatory cytokine IL-6 and downregulation of the multifunctional cytokines IP-10, Eotaxin, IL-4, and IL-7. Over the study period, cytokine levels uniformly decreased in all patients, leading to the elimination of the initial immune phenotypes regardless of treatment choice. This study reveals distinct pre-treatment immune phenotypes in HGSOC patients that might be informative for treatment stratification and prognosis. This potential novel biomarker holds promise as a foundation for improved assessment of treatment responses in patients with HGSOC. ClinicalTrials.gov Identifier: NCT03378297.

Targeted and Shallow Whole-Genome Sequencing Identifies Therapeutic Opportunities in p53abn Endometrial Cancers

PURPOSE

Shallow whole-genome sequencing (sWGS) can detect copy-number (CN) aberrations. In high-grade serous ovarian cancer (HGSOC) sWGS identified CN signatures such as homologous recombination deficiency (HRD) to direct therapy. We applied sWGS with targeted sequencing to p53abn endometrial cancers to identify additional prognostic stratification and therapeutic opportunities.

EXPERIMENTAL DESIGN

sWGS and targeted panel sequencing was performed on formalin-fixed, paraffin-embedded p53abn endometrial cancers. CN alterations, mutational data and CN signatures were derived, and associations to clinicopathologic and outcomes data were assessed.

RESULTS

In 187 p53abn endometrial cancers, 5 distinct CN signatures were identified. Signature 5 was associated with BRCA1/2 CN loss with features similar to HGSOC HRD signature. Twenty-two percent of potential HRD cases were identified, 35 patients with signature 5, and 8 patients with BRCA1/2 somatic mutations. Signatures 3 and 4 were associated with a high ploidy state, and CCNE1, ERBB2, and MYC amplifications, with mutations in PIK3CA enriched in signature 3. We observed improved overall survival (OS) for patients with signature 2 and worse OS for signatures 1 and 3. Twenty-eight percent of patients had CCNE1 amplification and this subset was enriched with carcinosarcoma histotype. Thirty-four percent of patients, across all histotypes, had ERBB2 amplification and/or HER2 overexpression on IHC, which was associated with worse outcomes. Mutations in PPP2R1A (29%) and FBXW7 (16%) were among the top 5 most common mutations.

CONCLUSIONS

sWGS and targeted sequencing identified therapeutic opportunities in 75% of patients with p53abn endometrial cancer. Further research is needed to determine the efficacy of treatments targeting these identified pathways within p53abn endometrial cancers.

The yin and yang of chromosomal instability in prostate cancer

Metastatic prostate cancer remains an incurable lethal disease. Studies indicate that prostate cancer accumulates genomic changes during disease progression and displays the highest levels of chromosomal instability (CIN) across all types of metastatic tumours. CIN, which refers to ongoing chromosomal DNA gain or loss during mitosis, and derived aneuploidy, are known to be associated with increased tumour heterogeneity, metastasis and therapy resistance in many tumour types. Paradoxically, high CIN levels are also proposed to be detrimental to tumour cell survival, suggesting that cancer cells must develop adaptive mechanisms to ensure their survival. In the context of prostate cancer, studies indicate that CIN has a key role in disease progression and might also offer a therapeutic vulnerability that can be pharmacologically targeted. Thus, a comprehensive evaluation of the causes and consequences of CIN in prostate cancer, its contribution to aggressive advanced disease and a better understanding of the acquired CIN tolerance mechanisms can translate into new tumour classifications, biomarker development and therapeutic strategies.

PIK3R1 fusion drives chemoresistance in ovarian cancer by activating ERK1/2 and inducing rod and ring-like structures

Gene fusions are common in high-grade serous ovarian cancer (HGSC). Such genetic lesions may promote tumorigenesis, but the pathogenic mechanisms are currently poorly understood. Here, we investigated the role of a PIK3R1-CCDC178 fusion identified from a patient with advanced HGSC. We show that the fusion induces HGSC cell migration by regulating ERK1/2 and increases resistance to platinum treatment. Platinum resistance was associated with rod and ring-like cellular structure formation. These structures contained, in addition to the fusion protein, CIN85, a key regulator of PI3K-AKT-mTOR signaling. Our data suggest that the fusion-driven structure formation induces a previously unrecognized cell survival and resistance mechanism, which depends on ERK1/2-activation.

KMT2A Mutations and High Prevalence of dMMR-associated Mutational Signatures as Prognostic Indicators in Metastatic Colorectal Cancer

The conventional treatment strategies for patients with metastatic colorectal cancer (mCRC) are predominantly guided by the status of RAS and BRAF mutations. Although patients may exhibit analogous pathological characteristics and undergo similar treatment regimens, notable disparities in their prognostic outcomes can be observed. Therefore, tissue and plasma samples from 40 mCRC patients underwent next-generation sequencing targeting 425 cancer-relevant genes. Genomic variations and canonical oncogenic pathways were investigated for their prognostic effects in association with progression-free survival (PFS) of these patients. We found that patients with BRCA2 and KMT2A mutations exhibited worse prognostic outcomes after chemotherapy-based treatment (univariate, P < 0.01). Further pathway analysis indicated that alterations in the homologous recombination pathway and in the KMT2A signaling network were also significantly associated with shortened PFS (univariate, P < 0.01). Additionally, mutation signature analysis showed that patients with higher proportions of defective mismatch repair (dMMR)-related mutational signatures. Had a worse prognosis (univariate, P = 0.02). KMT2A mutations (hazard ratio [HR], 4.47; 95% confidence interval [CI], 1-19.93; P =0.050) and dMMR signature proportions (HR, 3.57; 95% CI, 1.42-8.96; P = 0.007) remained independently associated with PFS after multivariate analysis and the results were further externally validated. These findings may enhance our understanding of this disease and may potentially facilitate the optimization of its treatment approaches.

CINner: modeling and simulation of chromosomal instability in cancer at single-cell resolution

Cancer development is characterized by chromosomal instability, manifesting in frequent occurrences of different genomic alteration mechanisms ranging in extent and impact. Mathematical modeling can help evaluate the role of each mutational process during tumor progression, however existing frameworks can only capture certain aspects of chromosomal instability (CIN). We present CINner, a mathematical framework for modeling genomic diversity and selection during tumor evolution. The main advantage of CINner is its flexibility to incorporate many genomic events that directly impact cellular fitness, from driver gene mutations to copy number alterations (CNAs), including focal amplifications and deletions, missegregations and whole-genome duplication (WGD). We apply CINner to find chromosome-arm selection parameters that drive tumorigenesis in the absence of WGD in chromosomally stable cancer types. We found that the selection parameters predict WGD prevalence among different chromosomally unstable tumors, hinting that the selective advantage of WGD cells hinges on their tolerance for aneuploidy and escape from nullisomy. Direct application of CINner to model the WGD proportion and fraction of genome altered (FGA) further uncovers the increase in CNA probabilities associated with WGD in each cancer type. CINner can also be utilized to study chromosomally stable cancer types, by applying a selection model based on driver gene mutations and focal amplifications or deletions. Finally, we used CINner to analyze the impact of CNA probabilities, chromosome selection parameters, tumor growth dynamics and population size on cancer fitness and heterogeneity. We expect that CINner will provide a powerful modeling tool for the oncology community to quantify the impact of newly uncovered genomic alteration mechanisms on shaping tumor progression and adaptation.

Exome sequencing identifies HELB as a novel susceptibility gene for non-mucinous, non-high-grade-serous epithelial ovarian cancer

Rare, germline loss-of-function variants in a handful of genes that encode DNA repair proteins have been shown to be associated with epithelial ovarian cancer with a stronger association for the high-grade serous hiostotype. The aim of this study was to collate exome sequencing data from multiple epithelial ovarian cancer case cohorts and controls in order to systematically evaluate the role of coding, loss-of-function variants across the genome in epithelial ovarian cancer risk. We assembled exome data for a total of 2,573 non-mucinous cases (1,876 high-grade serous and 697 non-high grade serous) and 13,925 controls. Harmonised variant calling and quality control filtering was applied across the different data sets. We carried out a gene-by-gene simple burden test for association of rare loss-of-function variants (minor allele frequency < 0.1%) with all non-mucinous ovarian cancer, high grade serous ovarian cancer and non-high grade serous ovarian cancer using logistic regression adjusted for the top four principal components to account for cryptic population structure and genetic ancestry. Seven of the top 10 associated genes were associations of the known ovarian cancer susceptibility genes BRCA1, BRCA2, BRIP1, RAD51C, RAD51D, MSH6 and PALB2 (false discovery probability < 0.1). A further four genes (HELB, OR2T35, NBN and MYO1A) had a false discovery rate of less than 0.1. Of these, HELB was most strongly associated with the non-high grade serous histotype (P = 1.3×10-6, FDR = 9.1×10-4). Further support for this association comes from the observation that loss of function variants in this gene are also associated with age at natural menopause and Mendelian randomisation analysis shows an association between genetically predicted age at natural menopause and endometrioid ovarian cancer, but not high-grade serous ovarian cancer.

Accurate and sensitive mutational signature analysis with MuSiCal

Mutational signature analysis is a recent computational approach for interpreting somatic mutations in the genome. Its application to cancer data has enhanced our understanding of mutational forces driving tumorigenesis and demonstrated its potential to inform prognosis and treatment decisions. However, methodological challenges remain for discovering new signatures and assigning proper weights to existing signatures, thereby hindering broader clinical applications. Here we present Mutational Signature Calculator (MuSiCal), a rigorous analytical framework with algorithms that solve major problems in the standard workflow. Our simulation studies demonstrate that MuSiCal outperforms state-of-the-art algorithms for both signature discovery and assignment. By reanalyzing more than 2,700 cancer genomes, we provide an improved catalog of signatures and their assignments, discover nine indel signatures absent in the current catalog, resolve long-standing issues with the ambiguous 'flat' signatures and give insights into signatures with unknown etiologies. We expect MuSiCal and the improved catalog to be a step towards establishing best practices for mutational signature analysis.

Targeting chromosomal instability and aneuploidy in cancer

Cancer development and therapy resistance are driven by chromosomal instability (CIN), which causes chromosome gains and losses (i.e., aneuploidy) and structural chromosomal alterations. Technical limitations and knowledge gaps have delayed therapeutic targeting of CIN and aneuploidy in cancers. However, our toolbox for creating and studying aneuploidy in cell models has greatly expanded recently. Moreover, accumulating evidence suggests that seven conventional antimitotic chemotherapeutic drugs achieve clinical response by inducing CIN instead of mitotic arrest, although additional anticancer activities may also contribute in vivo. In this review, we discuss these recent developments. We also highlight new discoveries, which together show that 25 chromosome arm aneuploidies (CAAs) may be targetable by 36 drugs across 14 types of cancer. Collectively, these advances offer many new opportunities to improve cancer treatment.

The reckoning of chromosomal instability: past, present, future

Quantitative measures of CIN are crucial to our understanding of its role in cancer. Technological advances have changed the way CIN is quantified, offering increased accuracy and insight. Here, we review measures of CIN through its rise as a field, discuss considerations for its measurement, and look forward to future quantification of CIN.

Residual ANTXR1+ myofibroblasts after chemotherapy inhibit anti-tumor immunity via YAP1 signaling pathway

Although cancer-associated fibroblast (CAF) heterogeneity is well-established, the impact of chemotherapy on CAF populations remains poorly understood. Here we address this question in high-grade serous ovarian cancer (HGSOC), in which we previously identified 4 CAF populations. While the global content in stroma increases in HGSOC after chemotherapy, the proportion of FAP+ CAF (also called CAF-S1) decreases. Still, maintenance of high residual CAF-S1 content after chemotherapy is associated with reduced CD8+ T lymphocyte density and poor patient prognosis, emphasizing the importance of CAF-S1 reduction upon treatment. Single cell analysis, spatial transcriptomics and immunohistochemistry reveal that the content in the ECM-producing ANTXR1+ CAF-S1 cluster (ECM-myCAF) is the most affected by chemotherapy. Moreover, functional assays demonstrate that ECM-myCAF isolated from HGSOC reduce CD8+ T-cell cytotoxicity through a Yes Associated Protein 1 (YAP1)-dependent mechanism. Thus, efficient inhibition after treatment of YAP1-signaling pathway in the ECM-myCAF cluster could enhance CD8+ T-cell cytotoxicity. Altogether, these data pave the way for therapy targeting YAP1 in ECM-myCAF in HGSOC.

Paradigm Shift: A Comprehensive Review of Ovarian Cancer Management in an Era of Advancements

Ovarian cancer (OC) is the female genital malignancy with the highest lethality. Patients present a poor prognosis mainly due to the late clinical presentation allied with the common acquisition of chemoresistance and a high rate of tumour recurrence. Effective screening, accurate diagnosis, and personalised multidisciplinary treatments are crucial for improving patients' survival and quality of life. This comprehensive narrative review aims to describe the current knowledge on the aetiology, prevention, diagnosis, and treatment of OC, highlighting the latest significant advancements and future directions. Traditionally, OC treatment involves the combination of cytoreductive surgery and platinum-based chemotherapy. Although more therapeutical approaches have been developed, the lack of established predictive biomarkers to guide disease management has led to only marginal improvements in progression-free survival (PFS) while patients face an increasing level of toxicity. Fortunately, because of a better overall understanding of ovarian tumourigenesis and advancements in the disease's (epi)genetic and molecular profiling, a paradigm shift has emerged with the identification of new disease biomarkers and the proposal of targeted therapeutic approaches to postpone disease recurrence and decrease side effects, while increasing patients' survival. Despite this progress, several challenges in disease management, including disease heterogeneity and drug resistance, still need to be overcome.

Causality and functional relevance of BRCA1 and BRCA2 pathogenic variants in non-high-grade serous ovarian carcinomas

The identification of causal BRCA1/2 pathogenic variants (PVs) in epithelial ovarian carcinoma (EOC) aids the selection of patients for genetic counselling and treatment decision-making. Current recommendations therefore stress sequencing of all EOCs, regardless of histotype. Although it is recognised that BRCA1/2 PVs cluster in high-grade serous ovarian carcinomas (HGSOC), this view is largely unsubstantiated by detailed analysis. Here, we aimed to analyse the results of BRCA1/2 tumour sequencing in a centrally revised, consecutive, prospective series including all EOC histotypes. Sequencing of n = 946 EOCs revealed BRCA1/2 PVs in 125 samples (13%), only eight of which were found in non-HGSOC histotypes. Specifically, BRCA1/2 PVs were identified in high-grade endometrioid (3/20; 15%), low-grade endometrioid (1/40; 2.5%), low-grade serous (3/67; 4.5%), and clear cell (1/64; 1.6%) EOCs. No PVs were identified in any mucinous ovarian carcinomas tested. By re-evaluation and using loss of heterozygosity and homologous recombination deficiency analyses, we then assessed: (1) whether the eight 'anomalous' cases were potentially histologically misclassified and (2) whether the identified variants were likely causal in carcinogenesis. The first 'anomalous' non-HGSOC with a BRCA1/2 PV proved to be a misdiagnosed HGSOC. Next, germline BRCA2 variants, found in two p53-abnormal high-grade endometrioid tumours, showed substantial evidence supporting causality. One additional, likely causal variant, found in a p53-wildtype low-grade serous ovarian carcinoma, was of somatic origin. The remaining cases showed retention of the BRCA1/2 wildtype allele, suggestive of non-causal secondary passenger variants. We conclude that likely causal BRCA1/2 variants are present in high-grade endometrioid tumours but are absent from the other EOC histotypes tested. Although the findings require validation, these results seem to justify a transition from universal to histotype-directed sequencing. Furthermore, in-depth functional analysis of tumours harbouring BRCA1/2 variants combined with detailed revision of cancer histotypes can serve as a model in other BRCA1/2-related cancers. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Computational validation of clonal and subclonal copy number alterations from bulk tumor sequencing using CNAqc

Copy number alterations (CNAs) are among the most important genetic events in cancer, but their detection from sequencing data is challenging because of unknown sample purity, tumor ploidy, and general intra-tumor heterogeneity. Here, we present CNAqc, an evolution-inspired method to perform the computational validation of clonal and subclonal CNAs detected from bulk DNA sequencing. CNAqc is validated using single-cell data and simulations, is applied to over 4000 TCGA and PCAWG samples, and is incorporated into the validation process for the clinically accredited bioinformatics pipeline at Genomics England. CNAqc is designed to support automated quality control procedures for tumor somatic data validation.

Genotoxic colibactin mutational signature in colorectal cancer is associated with clinicopathological features, specific genomic alterations and better survival

Background and Aims

The microbiome has long been suspected of a role in colorectal cancer (CRC) tumorigenesis. The mutational signature SBS88 mechanistically links CRC development with the strain of Escherichia coli harboring the pks island that produces the genotoxin colibactin, but the genomic, pathological and survival characteristics associated with SBS88-positive tumors are unknown.

Methods

SBS88-positive CRCs were identified from targeted sequencing data from 5,292 CRCs from 17 studies and tested for their association with clinico-pathological features, oncogenic pathways, genomic characteristics and survival.

Results

In total, 7.5% (398/5,292) of the CRCs were SBS88-positive, of which 98.7% (392/398) were microsatellite stable/microsatellite instability low (MSS/MSI-L), compared with 80% (3916/4894) of SBS88 negative tumors (p=1.5x10-28). Analysis of MSS/MSI-L CRCs demonstrated that SBS88 positive CRCs were associated with the distal colon (OR=1.84, 95% CI=1.40-2.42, p=1x10-5) and rectum (OR=1.90, 95% CI=1.44-2.51, p=6x10-6) tumor sites compared with the proximal colon. The top seven recurrent somatic mutations associated with SBS88-positive CRCs demonstrated mutational contexts associated with colibactin-induced DNA damage, the strongest of which was the APC:c.835-8A>G mutation (OR=65.5, 95%CI=39.0-110.0, p=3x10-80). Large copy number alterations (CNAs) including CNA loss on 14q and gains on 13q, 16q and 20p were significantly enriched in SBS88-positive CRCs. SBS88-positive CRCs were associated with better CRC-specific survival (p=0.007; hazard ratio of 0.69, 95% CI=0.52-0.90) when stratified by age, sex, study, and by stage.

Conclusion

SBS88-positivity, a biomarker of colibactin-induced DNA damage, can identify a novel subtype of CRC characterized by recurrent somatic mutations, copy number alterations and better survival. These findings provide new insights for treatment and prevention strategies for this subtype of CRC.

KLK10/LIPH/PARD6B/SLC52A3 are promising molecular biomarkers for the prognosis of pancreatic cancer through a ceRNA network

Pancreatic adenocarcinoma (PAAD) remains challenging to diagnose and treat clinically due to its difficult early diagnosis, low surgical resection rate, and high risk of postoperative recurrence and metastasis. SMAD4 is a classical mutated gene in pancreatic cancer and is lost in up to 60%-90 % of PAAD patients, and its mutation often predicts a poor prognosis and treatment resistance. In this study, based on the expression profile data in The Cancer Genome Atlas database, we identified a ceRNA network composed of 2 lncRNAs, 1 miRNA, and 4 mRNAs through differential expression analysis and survival prognosis analysis. Among them, high expression of KLK10/LIPH/PARD6B/SLC52A3 influenced the prognosis and overall survival of PAAD patients. We confirmed the high expression of these target genes in pancreatic tissue of pancreatic-specific SMAD4-deficient mice. In addition, immune infiltration analysis showed that the high expression of these target genes affects the tumor immune environment and contributes to the progression of PAAD. Abnormal overexpression of these target genes may be caused by hypermethylation. In conclusion, we found that KLK10/LIPH/PARD6B/SLC52A3 is a potential prognostic marker for PAAD based on a competing endogenous RNA-mediated mechanism and revealed the potential pathogenic mechanism by which deficient expression of SMAD4 promotes pancreatic cancer progression, which provides a new pathway and theoretical basis for targeted therapy or improved prognosis of pancreatic cancer. These data will help reveal potential therapeutic targets for pancreatic cancer and improve the prognosis of pancreatic cancer patients.

Large tandem duplications in cancer result from transcription and DNA replication collisions

Despite the abundance of somatic structural variations (SVs) in cancer, the underlying molecular mechanisms of their formation remain unclear. Here, we use 6,193 whole-genome sequenced tumors to study the contributions of transcription and DNA replication collisions to genome instability. After deconvoluting robust SV signatures in three independent pan-cancer cohorts, we detect transcription-dependent replicated-strand bias, the expected footprint of transcription-replication collision (TRC), in large tandem duplications (TDs). Large TDs are abundant in female-enriched, upper gastrointestinal tract and prostate cancers. They are associated with poor patient survival and mutations in TP53, CDK12, and SPOP. Upon inactivating CDK12, cells display significantly more TRCs, R-loops, and large TDs. Inhibition of G2/M checkpoint proteins, such as WEE1, CHK1, and ATR, selectively inhibits the growth of cells deficient in CDK12. Our data suggest that large TDs in cancer form due to TRCs, and their presence can be used as a biomarker for prognosis and treatment.

Evolutionary mode and timing of dissemination of high-grade serous carcinomas

Dissemination within the peritoneal cavity is a main determinant of poor patient outcomes from high-grade serous carcinomas (HGSCs). The dissemination process is poorly understood from a cancer evolutionary perspective. We reconstructed the evolutionary trajectories across a median of 5 tumor sites and regions from each of 23 patients based on deep whole-exome sequencing. Polyclonal cancer origin was detected in 1 patient. Ovarian tumors had more complex subclonal architectures than other intraperitoneal tumors in each patient, which indicated that tumors developed earlier in the ovaries. Three common modes of dissemination were identified, including monoclonal or polyclonal dissemination of monophyletic (linear) or polyphyletic (branched) subclones. Mutation profiles of initial or disseminated clones varied greatly among cancers, but recurrent mutations were found in 7 cancer-critical genes, including TP53, BRCA1, BRCA2, and DNMT3A, and in the PI3K/AKT1 pathway. Disseminated clones developed late in the evolutionary trajectory models of most cancers, in particular in cancers with DNA damage repair deficiency. Polyclonal dissemination was predicted to occur predominantly as a single and rapid wave, but chemotherapy exposure was associated with higher genomic diversity of disseminated clones. In conclusion, we described three common evolutionary dissemination modes across HGSCs and proposed factors associated with dissemination diversity.

Deciphering cancer genomes with GenomeSpy: a grammar-based visualization toolkit

BACKGROUND

Visualization is an indispensable facet of genomic data analysis. Despite the abundance of specialized visualization tools, there remains a distinct need for tailored solutions. However, their implementation typically requires extensive programming expertise from bioinformaticians and software developers, especially when building interactive applications. Toolkits based on visualization grammars offer a more accessible, declarative way to author new visualizations. Yet, current grammar-based solutions fall short in adequately supporting the interactive analysis of large datasets with extensive sample collections, a pivotal task often encountered in cancer research.

FINDINGS

We present GenomeSpy, a grammar-based toolkit for authoring tailored, interactive visualizations for genomic data analysis. By using combinatorial building blocks and a declarative language, users can implement new visualization designs easily and embed them in web pages or end-user-oriented applications. A distinctive element of GenomeSpy's architecture is its effective use of the graphics processing unit in all rendering, enabling a high frame rate and smoothly animated interactions, such as navigation within a genome. We demonstrate the utility of GenomeSpy by characterizing the genomic landscape of 753 ovarian cancer samples from patients in the DECIDER clinical trial. Our results expand the understanding of the genomic architecture in ovarian cancer, particularly the diversity of chromosomal instability.

CONCLUSIONS

GenomeSpy is a visualization toolkit applicable to a wide range of tasks pertinent to genome analysis. It offers high flexibility and exceptional performance in interactive analysis. The toolkit is open source with an MIT license, implemented in JavaScript, and available at https://genomespy.app/.

HRD related signature 3 predicts clinical outcome in advanced tubo-ovarian high-grade serous carcinoma

OBJECTIVES

We evaluated usability of single base substitution signature 3 (Sig3) as a biomarker for homologous recombination deficiency (HRD) in tubo-ovarian high-grade serous carcinoma (HGSC).

MATERIALS AND METHODS

This prospective observational trial includes 165 patients with advanced HGSC. Fresh tissue samples (n = 456) from multiple intra-abdominal areas at diagnosis and after neoadjuvant chemotherapy (NACT) were collected for whole-genome sequencing. Sig3 was assessed by fitting samples independently with COSMIC v3.2 reference signatures. An HR scar assay was applied for comparison. Progression-free survival (PFS) and overall survival (OS) were studied using Kaplan-Meier and Cox regression analysis.

RESULTS

Sig3 has a bimodal distribution, eliminating the need for an arbitrary cutoff typical in HR scar tests. Sig3 could be assessed from samples with low (10%) cancer cell proportion and was consistent between multiple samples and stable during NACT. At diagnosis, 74 (45%) patients were HRD (Sig3+), while 91 (55%) were HR proficient (HRP, Sig3-). Sig3+ patients had longer PFS and OS than Sig3- patients (22 vs. 13 months and 51 vs. 34 months respectively, both p < 0.001). Sig3 successfully distinguished the poor prognostic HRP group among BRCAwt patients (PFS 19 months for Sig3+ and 13 months for Sig3- patients, p < 0.001). However, Sig3 at diagnosis did not predict chemoresponse anymore in the first relapse. The patient-level concordance between Sig3 and HR scar assay was 87%, and patients with HRD according to both tests had the longest median PFS.

CONCLUSIONS

Sig3 is a prognostic marker in advanced HGSC and useful tool in patient stratification for HRD.

Personalization of Therapy in High-Grade Serous Tubo-Ovarian Cancer-The Possibility or the Necessity?

High-grade serous tubo-ovarian cancer (HGSTOC) is the most lethal tumor of the female genital tract. The foregoing therapy consists of cytoreduction followed by standard platinum/taxane chemotherapy; alternatively, for primary unresectable tumors, neo-adjuvant platinum/taxane chemotherapy followed by delayed interval cytoreduction. In patients with suboptimal surgery or advanced disease, different forms of targeted therapy have been accepted or tested in clinical trials. Studies on HGSTOC discovered its genetic and proteomic heterogeneity, epigenetic regulation, and the role of the tumor microenvironment. These findings turned attention to the fact that there are several distinct primary tumor subtypes of HGSTOC and the unique biology of primary, metastatic, and recurrent tumors may result in a differential drug response. This results in both chemo-refractoriness of some primary tumors and, what is significantly more frequent and destructive, secondary chemo-resistance of metastatic and recurrent HGSTOC tumors. Treatment possibilities for platinum-resistant disease include several chemotherapeutics with moderate activity and different targeted drugs with difficult tolerable effects. Therefore, the question appears as to why different subtypes of ovarian cancer are predominantly treated based on the same therapeutic schemes and not in an individualized way, adjusted to the biology of a specific tumor subtype and temporal moment of the disease. The paper reviews the genomic, mutational, and epigenetic signatures of HGSTOC subtypes and the tumor microenvironment. The clinical trials on personalized therapy and the overall results of a new, comprehensive approach to personalized therapy for ovarian cancer have been presented and discussed.

GIInger predicts homologous recombination deficiency and patient response to PARPi treatment from shallow genomic profiles

Homologous recombination deficiency (HRD) is a predictive biomarker for poly(ADP-ribose) polymerase 1 inhibitor (PARPi) sensitivity. Routine HRD testing relies on identifying BRCA mutations, but additional HRD-positive patients can be identified by measuring genomic instability (GI), a consequence of HRD. However, the cost and complexity of available solutions hamper GI testing. We introduce a deep learning framework, GIInger, that identifies GI from HRD-induced scarring observed in low-pass whole-genome sequencing data. GIInger seamlessly integrates into standard BRCA testing workflows and yields reproducible results concordant with a reference method in a multisite study of 327 ovarian cancer samples. Applied to a BRCA wild-type enriched subgroup of 195 PAOLA-1 clinical trial patients, GIInger identified HRD-positive patients who experienced significantly extended progression-free survival when treated with PARPi. GIInger is, therefore, a cost-effective and easy-to-implement method for accurately stratifying patients with ovarian cancer for first-line PARPi treatment.

Association between copy number alterations estimated using low-pass whole genome sequencing of formalin-fixed paraffin-embedded prostate tumor tissue and cancer-specific clinical parameters

Copy number alterations (CNAs) are frequently observed in early-stage prostate cancer and are associated with disease recurrence and tumor aggressiveness. Cost-effective assessment of CNAs could enhance clinical utility of CNAs. Here, we combined the cost-effectiveness of low-pass (low coverage) whole genome sequencing (LPWGS) and the routine availability of formalin-fixed paraffin-embedded (FFPE) tumor tissue for assessing CNAs in a cohort of 187 men with early-stage localised prostate cancer. We detected well known CNAs in 8p, 8q, 13q and 16q and recurrent gains of the oncogene MYC and losses of the tumor suppressor genes NKX3-1, PTEN and RB1, indicating assay reliability. The estimated burden of CNAs was significantly associated with Gleason score, pathological T stage, surgical margin status and biochemical recurrence. Further, genomic losses or gains in specific chromosomal arms were significantly associated with worse BCR-free survival. Copy number signatures extracted from the LPWGS data showed potential for risk stratifying patients, where signatures S1 and S2 showed significant association to worse BCR-free survival compared to S3. Our study provides clinical validation of the associations between CNAs and tumor aggressiveness in an independent and representative RP cohort, while demonstrating the feasibility of performing LPWGS of FFPE tumor tissue for cost-effective assessment of CNAs.