Randomized Phase II Study of Gemcitabine With or Without ATR Inhibitor Berzosertib in Platinum-Resistant Ovarian Cancer: Final Overall Survival and Biomarker Analyses.

PURPOSE: The multicenter, open-label, randomized phase 2 NCI-9944 study (NCT02595892) demonstrated that addition of ATR inhibitor (ATRi) berzosertib to gemcitabine increased progression-free survival (PFS) compared to gemcitabine alone (hazard ratio [HR]=0.57, one-sided log-rank P = .044, which met the one-sided significance level of 0.1 used for sample size calculation). METHODS: We report here the final overall survival (OS) analysis and biomarker correlations (ATM expression by immunohistochemistry, mutational signature 3 and a genomic biomarker of replication stress) along with post-hoc exploratory analyses to adjust for crossover from gemcitabine to gemcitabine/berzosertib. RESULTS: At the data cutoff of January 27, 2023 (>30 months of additional follow-up from the primary analysis), median OS was 59.4 weeks with gemcitabine/berzosertib versus 43.0 weeks with gemcitabine alone (HR 0.79, 90% CI 0.52 to 1.2, one-sided log-rank P = .18). An OS benefit with addition of berzosertib to gemcitabine was suggested in patients stratified into the platinum-free interval ≤3 months (N = 26) subgroup (HR, 0.48, 90% CI 0.22 to 1.01, one-sided log-rank P =.04) and in patients with ATM-negative/low (N = 24) tumors (HR, 0.50, 90% CI 0.23 to 1.08, one-sided log-rank P = .06). CONCLUSION: The results of this follow-up analysis continue to support the promise of combined gemcitabine/ATRi therapy in platinum resistant ovarian cancer, an active area of investigation with several ongoing clinical trials.

Chromosome evolution screens recapitulate tissue-specific tumor aneuploidy patterns.

Whole chromosome and arm-level copy number alterations occur at high frequencies in tumors, but their selective advantages, if any, are poorly understood. Here, utilizing unbiased whole chromosome genetic screens combined with in vitro evolution to generate arm- and subarm-level events, we iteratively selected the fittest karyotypes from aneuploidized human renal and mammary epithelial cells. Proliferation-based karyotype selection in these epithelial lines modeled tissue-specific tumor aneuploidy patterns in patient cohorts in the absence of driver mutations. Hi-C-based translocation mapping revealed that arm-level events usually emerged in multiples of two via centromeric translocations and occurred more frequently in tetraploids than diploids, contributing to the increased diversity in evolving tetraploid populations. Isogenic clonal lineages enabled elucidation of pro-tumorigenic mechanisms associated with common copy number alterations, revealing Notch signaling potentiation as a driver of 1q gain in breast cancer. We propose that intrinsic, tissue-specific proliferative effects underlie tumor copy number patterns in 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.

A Panel-Based Mutational Signature of Mismatch Repair Deficiency is Associated With Durable Response to Pembrolizumab in Metastatic Castration-Resistant Prostate Cancer.

INTRODUCTION/BACKGROUND: Immune checkpoint inhibitors (ICIs) have limited efficacy in prostate cancer (PCa). Better biomarkers are needed to predict responses to ICIs. We sought to demonstrate that a panel-based mutational signature identifies mismatch repair (MMR) deficient (MMRd) PCa and is a biomarker of response to pembrolizumab. PATIENTS AND METHODS: Clinico-genomic data was obtained for 2664 patients with PCa sequenced at Dana-Farber Cancer Institute (DFCI) and Memorial Sloan Kettering (MSK). Clinical outcomes were collected for patients with metastatic castration-resistant PCa (mCRPC) treated with pembrolizumab at DFCI. SigMA was used to characterize tumors as MMRd or MMR proficient (MMRp). The concordance between MMRd with microsatellite instability (MSI-H) was assessed. Radiographic progression-free survival (rPFS) and overall survival (OS) were collected for patients treated with pembrolizumab. Event-time distributions were estimated using Kaplan-Meier methodology. RESULTS: Across both cohorts, 100% (DFCI: 12/12; MSK: 43/43) of MSI-H tumors were MMRd. However, 14% (2/14) and 9.1% (6/66) of MMRd tumors in the DFCI and MSK cohorts respectively were microsatellite stable (MSS), and 26% (17/66) were MSI-indeterminate in the MSK cohort. Among patients treated with pembrolizumab, those with MMRd (n = 5) versus MMRp (n = 14) mCRPC experienced markedly improved rPFS (HR = 0.088, 95% CI: 0.011-0.70; P = .0064) and OS (HR = 0.11, 95% CI: 0.014-0.80; P = .010) from start of treatment. Four patients with MMRd experienced remissions of >= 2.5 years. CONCLUSION: SigMA detects additional cases of MMRd as compared to MSI testing in PCa and identifies patients likely to experience durable response to pembrolizumab.

Predicting response to immune checkpoint blockade therapy among mismatch repair-deficient patients using mutational signatures.

Despite the overall efficacy of immune checkpoint blockade (ICB) for mismatch repair deficiency (MMRD) across tumor types, a sizable fraction of patients with MMRD still do not respond to ICB. We performed mutational signature analysis of panel sequencing data (n = 95) from MMRD cases treated with ICB. We discover that T>C-rich single base substitution (SBS) signatures-SBS26 and SBS54 from the COSMIC Mutational Signatures catalog-identify MMRD patients with significantly shorter overall survival. Tumors with a high burden of SBS26 show over-expression and enriched mutations of genes involved in double-strand break repair and other DNA repair pathways. They also display chromosomal instability (CIN), likely related to replication fork instability, leading to copy number losses that trigger immune evasion. SBS54 is associated with transcriptional activity and not with CIN, defining a distinct subtype. Consistently, cancer cell lines with a high burden of SBS26 and SBS54 are sensitive to treatments targeting pathways related to their proposed etiology. Together, our analysis offers an explanation for the heterogeneous responses to ICB among MMRD patients and supports an SBS signature-based predictor as a prognostic biomarker for differential ICB response.

De novo identification of expressed cancer somatic mutations from single-cell RNA sequencing data.

Identifying expressed somatic mutations from single-cell RNA sequencing data de novo is challenging but highly valuable. We propose RESA - Recurrently Expressed SNV Analysis, a computational framework to identify expressed somatic mutations from scRNA-seq data. RESA achieves an average precision of 0.77 on three in silico spike-in datasets. In extensive benchmarking against existing methods using 19 datasets, RESA consistently outperforms them. Furthermore, we applied RESA to analyze intratumor mutational heterogeneity in a melanoma drug resistance dataset. By enabling high precision detection of expressed somatic mutations, RESA substantially enhances the reliability of mutational analysis in scRNA-seq. RESA is available at https://github.com/ShenLab-Genomics/RESA .

Hyper-Dependence on NHEJ Enables Synergy between DNA-PK Inhibitors and Low-Dose Doxorubicin in Leiomyosarcoma.

PURPOSE: Leiomyosarcoma (LMS) is an aggressive sarcoma for which standard chemotherapies achieve response rates under 30%. There are no effective targeted therapies against LMS. Most LMS are characterized by chromosomal instability (CIN), resulting in part from TP53 and RB1 co-inactivation and DNA damage repair defects. We sought to identify therapeutic targets that could exacerbate intrinsic CIN and DNA damage in LMS, inducing lethal genotoxicity. EXPERIMENTAL DESIGN: We performed clinical targeted sequencing in 287 LMS and genome-wide loss-of-function screens in 3 patient-derived LMS cell lines, to identify LMS-specific dependencies. We validated candidate targets by biochemical and cell-response assays in vitro and in seven mouse models. RESULTS: Clinical targeted sequencing revealed a high burden of somatic copy-number alterations (median fraction of the genome altered =0.62) and demonstrated homologous recombination deficiency signatures in 35% of LMS. Genome-wide short hairpin RNA screens demonstrated PRKDC (DNA-PKcs) and RPA2 essentiality, consistent with compensatory nonhomologous end joining (NHEJ) hyper-dependence. DNA-PK inhibitor combinations with unconventionally low-dose doxorubicin had synergistic activity in LMS in vitro models. Combination therapy with peposertib and low-dose doxorubicin (standard or liposomal formulations) inhibited growth of 5 of 7 LMS mouse models without toxicity. CONCLUSIONS: Combinations of DNA-PK inhibitors with unconventionally low, sensitizing, doxorubicin dosing showed synergistic effects in LMS in vitro and in vivo models, without discernable toxicity. These findings underscore the relevance of DNA damage repair alterations in LMS pathogenesis and identify dependence on NHEJ as a clinically actionable vulnerability in LMS.

ERα-associated translocations underlie oncogene amplifications in breast cancer.

Focal copy-number amplification is an oncogenic event. Although recent studies have revealed the complex structure1-3 and the evolutionary trajectories4 of oncogene amplicons, their origin remains poorly understood. Here we show that focal amplifications in breast cancer frequently derive from a mechanism-which we term translocation-bridge amplification-involving inter-chromosomal translocations that lead to dicentric chromosome bridge formation and breakage. In 780 breast cancer genomes, we observe that focal amplifications are frequently connected to each other by inter-chromosomal translocations at their boundaries. Subsequent analysis indicates the following model: the oncogene neighbourhood is translocated in G1 creating a dicentric chromosome, the dicentric chromosome is replicated, and as dicentric sister chromosomes segregate during mitosis, a chromosome bridge is formed and then broken, with fragments often being circularized in extrachromosomal DNAs. This model explains the amplifications of key oncogenes, including ERBB2 and CCND1. Recurrent amplification boundaries and rearrangement hotspots correlate with oestrogen receptor binding in breast cancer cells. Experimentally, oestrogen treatment induces DNA double-strand breaks in the oestrogen receptor target regions that are repaired by translocations, suggesting a role of oestrogen in generating the initial translocations. A pan-cancer analysis reveals tissue-specific biases in mechanisms initiating focal amplifications, with the breakage-fusion-bridge cycle prevalent in some and the translocation-bridge amplification in others, probably owing to the different timing of DNA break repair. Our results identify a common mode of oncogene amplification and propose oestrogen as its mechanistic origin in breast cancer.

Optimized detection of homologous recombination deficiency improves the prediction of clinical outcomes in cancer.

Homologous recombination DNA-repair deficiency (HRD) is a common driver of genomic instability and confers a therapeutic vulnerability in cancer. The accurate detection of somatic allelic imbalances (AIs) has been limited by methods focused on BRCA1/2 mutations and using mixtures of cancer types. Using pan-cancer data, we revealed distinct patterns of AIs in high-grade serous ovarian cancer (HGSC). We used machine learning and statistics to generate improved criteria to identify HRD in HGSC (ovaHRDscar). ovaHRDscar significantly predicted clinical outcomes in three independent patient cohorts with higher precision than previous methods. Characterization of 98 spatiotemporally distinct metastatic samples revealed low intra-patient variation and indicated the primary tumor as the preferred site for clinical sampling in HGSC. Further, our approach improved the prediction of clinical outcomes in triple-negative breast cancer (tnbcHRDscar), validated in two independent patient cohorts. In conclusion, our tumor-specific, systematic approach has the potential to improve patient selection for HR-targeted therapies.

Mutational Signature 3 Detected from Clinical Panel Sequencing is Associated with Responses to Olaparib in Breast and Ovarian Cancers.

PURPOSE: The identification of patients with homologous recombination deficiency (HRD) beyond BRCA1/2 mutations is an urgent task, as they may benefit from PARP inhibitors. We have previously developed a method to detect mutational signature 3 (Sig3), termed SigMA, associated with HRD from clinical panel sequencing data, that is able to reliably detect HRD from the limited sequencing data derived from gene-focused panel sequencing. EXPERIMENTAL DESIGN: We apply this method to patients from two independent datasets: (i) high-grade serous ovarian cancer and triple-negative breast cancer (TNBC) from a phase Ib trial of the PARP inhibitor olaparib in combination with the PI3K inhibitor buparlisib (BKM120; NCT01623349), and (ii) TNBC patients who received neoadjuvant olaparib in the phase II PETREMAC trial (NCT02624973). RESULTS: We find that Sig3 as detected by SigMA is positively associated with improved progression-free survival and objective responses. In addition, comparison of Sig3 detection in panel and exome-sequencing data from the same patient samples demonstrated highly concordant results and superior performance in comparison with the genomic instability score. CONCLUSIONS: Our analyses demonstrate that HRD can be detected reliably from panel-sequencing data that are obtained as part of routine clinical care, and that this approach can identify patients beyond those with germline BRCA1/2mut who might benefit from PARP inhibitors. Prospective clinical utility testing is warranted.

Single-cell genome sequencing of human neurons identifies somatic point mutation and indel enrichment in regulatory elements.

Accurate somatic mutation detection from single-cell DNA sequencing is challenging due to amplification-related artifacts. To reduce this artifact burden, an improved amplification technique, primary template-directed amplification (PTA), was recently introduced. We analyzed whole-genome sequencing data from 52 PTA-amplified single neurons using SCAN2, a new genotyper we developed to leverage mutation signatures and allele balance in identifying somatic single-nucleotide variants (SNVs) and small insertions and deletions (indels) in PTA data. Our analysis confirms an increase in nonclonal somatic mutation in single neurons with age, but revises the estimated rate of this accumulation to 16 SNVs per year. We also identify artifacts in other amplification methods. Most importantly, we show that somatic indels increase by at least three per year per neuron and are enriched in functional regions of the genome such as enhancers and promoters. Our data suggest that indels in gene-regulatory elements have a considerable effect on genome integrity in human neurons.

Computational analysis of cancer genome sequencing data.

Distilling biologically meaningful information from cancer genome sequencing data requires comprehensive identification of somatic alterations using rigorous computational methods. As the amount and complexity of sequencing data have increased, so has the number of tools for analysing them. Here, we describe the main steps involved in the bioinformatic analysis of cancer genomes, review key algorithmic developments and highlight popular tools and emerging technologies. These tools include those that identify point mutations, copy number alterations, structural variations and mutational signatures in cancer genomes. We also discuss issues in experimental design, the strengths and limitations of sequencing modalities and methodological challenges for the future.

Similarity of gaze patterns across physical and virtual versions of an installation artwork.

An experiment was conducted to compare museum visitors' gaze patterns using mobile eye-trackers, whilst they were engaging with a physical and a virtual reality (VR) installation of Piet Mondrian's Neo-plasticist room design. Visitors' eye movements produced approximately 25,000 fixations and were analysed using linear mixed-effects models. Absolute and area-normalized dwell time analyses yielded mostly non-significant main effects of the environment, indicating similarity of visual exploration patterns between physical and VR settings. One major difference observed was the decrease of average fixation duration in VR, where visitors tended to more rapidly switch focus in this environment with shorter bursts of attentional focus. The experiment demonstrated the ability to compare gaze data between physical and virtual environments as a proxy to measure the similarity of aesthetic experience. Similarity of viewing patterns along with questionnaire results suggested that virtual galleries can be treated as ecologically valid environments that are parallel to physical art galleries.

A Replication stress biomarker is associated with response to gemcitabine versus combined gemcitabine and ATR inhibitor therapy in ovarian cancer.

In a trial of patients with high grade serous ovarian cancer (HGSOC), addition of the ATR inhibitor berzosertib to gemcitabine improved progression free survival (PFS) compared to gemcitabine alone but biomarkers predictive of treatment are lacking. Here we report a candidate biomarker of response to gemcitabine versus combined gemcitabine and ATR inhibitor therapy in HGSOC ovarian cancer. Patients with replication stress (RS)-high tumors (n = 27), defined as harboring at least one genomic RS alteration related to loss of RB pathway regulation and/or oncogene-induced replication stress achieve significantly prolonged PFS (HR = 0.38, 90% CI, 0.17-0.86) on gemcitabine monotherapy compared to those with tumors without such alterations (defined as RS-low, n = 30). However, addition of berzosertib to gemcitabine benefits only patients with RS-low tumors (gemcitabine/berzosertib HR 0.34, 90% CI, 0.13-0.86) and not patients with RS-high tumors (HR 1.11, 90% CI, 0.47-2.62). Our findings support the notion that the exacerbation of RS by gemcitabine monotherapy is adequate for lethality in RS-high tumors. Conversely, for RS-low tumors addition of berzosertib-mediated ATR inhibition to gemcitabine is necessary for lethality to occur. Independent prospective validation of this biomarker is required.

The origins and genetic interactions of KRAS mutations are allele- and tissue-specific.

Mutational activation of KRAS promotes the initiation and progression of cancers, especially in the colorectum, pancreas, lung, and blood plasma, with varying prevalence of specific activating missense mutations. Although epidemiological studies connect specific alleles to clinical outcomes, the mechanisms underlying the distinct clinical characteristics of mutant KRAS alleles are unclear. Here, we analyze 13,492 samples from these four tumor types to examine allele- and tissue-specific genetic properties associated with oncogenic KRAS mutations. The prevalence of known mutagenic mechanisms partially explains the observed spectrum of KRAS activating mutations. However, there are substantial differences between the observed and predicted frequencies for many alleles, suggesting that biological selection underlies the tissue-specific frequencies of mutant alleles. Consistent with experimental studies that have identified distinct signaling properties associated with each mutant form of KRAS, our genetic analysis reveals that each KRAS allele is associated with a distinct tissue-specific comutation network. Moreover, we identify tissue-specific genetic dependencies associated with specific mutant KRAS alleles. Overall, this analysis demonstrates that the genetic interactions of oncogenic KRAS mutations are allele- and tissue-specific, underscoring the complexity that drives their clinical consequences.

The landscape of somatic mutation in cerebral cortex of autistic and neurotypical individuals revealed by ultra-deep whole-genome sequencing.

We characterize the landscape of somatic mutations-mutations occurring after fertilization-in the human brain using ultra-deep (~250×) whole-genome sequencing of prefrontal cortex from 59 donors with autism spectrum disorder (ASD) and 15 control donors. We observe a mean of 26 somatic single-nucleotide variants per brain present in ≥4% of cells, with enrichment of mutations in coding and putative regulatory regions. Our analysis reveals that the first cell division after fertilization produces ~3.4 mutations, followed by 2-3 mutations in subsequent generations. This suggests that a typical individual possesses ~80 somatic single-nucleotide variants present in ≥2% of cells-comparable to the number of de novo germline mutations per generation-with about half of individuals having at least one potentially function-altering somatic mutation somewhere in the cortex. ASD brains show an excess of somatic mutations in neural enhancer sequences compared with controls, suggesting that mosaic enhancer mutations may contribute to ASD risk.

Heterogeneity and Clonal Evolution of Acquired PARP Inhibitor Resistance in TP53- and BRCA1-Deficient Cells.

Homologous recombination (HR)-deficient cancers are sensitive to poly-ADP ribose polymerase inhibitors (PARPi), which have shown clinical efficacy in the treatment of high-grade serous cancers (HGSC). However, the majority of patients will relapse, and acquired PARPi resistance is emerging as a pressing clinical problem. Here we generated seven single-cell clones with acquired PARPi resistance derived from a PARPi-sensitive TP53 -/- and BRCA1 -/- epithelial cell line generated using CRISPR/Cas9. These clones showed diverse resistance mechanisms, and some clones presented with multiple mechanisms of resistance at the same time. Genomic analysis of the clones revealed unique transcriptional and mutational profiles and increased genomic instability in comparison with a PARPi-sensitive cell line. Clonal evolutionary analyses suggested that acquired PARPi resistance arose via clonal selection from an intrinsically unstable and heterogenous cell population in the sensitive cell line, which contained preexisting drug-tolerant cells. Similarly, clonal and spatial heterogeneity in tumor biopsies from a clinical patient with BRCA1-mutant HGSC with acquired PARPi resistance was observed. In an imaging-based drug screening, the clones showed heterogenous responses to targeted therapeutic agents, indicating that not all PARPi-resistant clones can be targeted with just one therapy. Furthermore, PARPi-resistant clones showed mechanism-dependent vulnerabilities to the selected agents, demonstrating that a deeper understanding on the mechanisms of resistance could lead to improved targeting and biomarkers for HGSC with acquired PARPi resistance. SIGNIFICANCE: This study shows that BRCA1-deficient cells can give rise to multiple genomically and functionally heterogenous PARPi-resistant clones, which are associated with various vulnerabilities that can be targeted in a mechanism-specific manner.