Co-occurrence and mutual exclusivity of genomic alterations may reflect the existence of genetic interactions, potentially shaping distinct biological phenotypes and impacting therapeutic response in breast cancer. However, our understanding of them remains limited. Herein, we investigate a large-scale multi-omics cohort (n = 873) and a real-world clinical sequencing cohort (n = 4,405) including several clinical trials with detailed treatment outcomes and perform functional validation in patient-derived organoids, tumor fragments, and in vivo models. Through this comprehensive approach, we construct a network comprising co-alterations and mutually exclusive events and characterize their therapeutic potential and underlying biological basis. Notably, we identify associations between TP53mut-AURKAamp and endocrine therapy resistance, germline BRCA1mut-MYCamp and improved sensitivity to PARP inhibitors, and TP53mut-MYBamp and immunotherapy resistance. Furthermore, we reveal that precision treatment strategies informed by co-alterations hold promise to improve patient outcomes. Our study highlights the significance of genetic interactions in guiding genome-informed treatment decisions beyond single driver alterations.

Variant detection from long-read genome sequencing (lrGS) has proven to be considerably more accurate and comprehensive than variant detection from short-read genome sequencing (srGS). However, the rate at which lrGS can increase molecular diagnostic yield for rare disease is not yet precisely characterized. We performed lrGS using Pacific Biosciences \"HiFi\" technology on 96 short-read-negative probands with rare disease that were suspected to be genetic. We generated hg38-aligned variants and de novo phased genome assemblies, and subsequently annotated, filtered, and curated variants using clinical standards. New disease-relevant or potentially relevant genetic findings were identified in 16/96 (16.7%) probands, eight of which (8/96, 8.33%) harbored pathogenic or likely pathogenic variants. Newly identified variants were visible in both srGS and lrGS in nine probands (~9.4%) and resulted from changes to interpretation mostly from recent gene-disease association discoveries. Seven cases included variants that were only interpretable in lrGS, including copy-number variants, an inversion, a mobile element insertion, two low-complexity repeat expansions, and a 1 bp deletion. While evidence for each of these variants is, in retrospect, visible in srGS, they were either: not called within srGS data, were represented by calls with incorrect sizes or structures, or failed quality-control and filtration. Thus, while reanalysis of older data clearly increases diagnostic yield, we find that lrGS allows for substantial additional yield (7/96, 7.3%) beyond srGS. We anticipate that as lrGS analysis improves, and as lrGS datasets grow allowing for better variant frequency annotation, the additional lrGS-only rare disease yield will grow over time.

Using next generation sequencing (NGS), The Cancer Genome Atlas (TCGA) found that endometrial carcinomas (ECs) fall under one of four molecular subtypes, and a POLE mutation status, mismatch repair (MMR) and p53 immunohistochemistry (IHC)-based surrogate has been developed. We sought to retrospectively classify and characterize a large series of unselected ECs that were prospectively subjected to clinical sequencing by utilizing clinical molecular and IHC data.
All patients with EC with clinical tumor-normal MSK-IMPACT NGS from 2014 to 2020 (n = 2115) were classified by integrating molecular data (i.e., POLE mutation, TP53 mutation, MSIsensor score) and MMR and p53 IHC results. Survival analysis was performed for primary EC patients with upfront surgery at our institution.
Utilizing our integrated approach, significantly more ECs were molecularly classified (1834/2115, 87%) as compared to the surrogate (1387/2115, 66%, p < 0.001), with an almost perfect agreement for classifiable cases (Kappa 0.962, 95% CI 0.949-0.975). Discrepancies were primarily due to TP53 mutations in p53-IHC-normal ECs. Of the 1834 ECs, most were of copy number (CN)-high molecular subtype (40%), followed by CN-low (32%), MSI-high (23%) and POLE (5%). Histologic and genomic variability was present amongst all molecular subtypes. Molecular classification was prognostic in early- and advanced-stage disease, including early-stage endometrioid EC.
The integration of clinical NGS and IHC data allows for an algorithmic approach to molecularly classifying newly diagnosed EC, while overcoming issues of IHC-based genetic alteration detection. Such integrated approach will be important moving forward given the prognostic and potentially predictive information afforded by this classification.

The repair of DNA double-stranded breaks relies on the homologous recombination repair pathway and is critical to cell function. However, this pathway can be lost in some cancers such as breast, ovarian, endometrial, pancreatic, and prostate cancers. Cancer cells with homologous recombination deficiency (HRD) are sensitive to targeted inhibition of poly-ADP ribose polymerase (PARP), a key component of alternative backup DNA repair pathways. Identifying patients with cancer with HRD biomarkers allows the identification of patients likely to benefit from PARP inhibitor therapies. In this study, we describe the causes of HRD, the underlying molecular changes resulting from HRD that form the basis of different molecular HRD assays, and discuss the issues around their clinical use. This overview is directed toward practicing pathologists wishing to be informed of this new predictive biomarker, as PARP inhibitors are increasingly used in standard care settings.

Can the embryo tracking system (ETS) increase safety, efficacy and scalability of massively parallel sequencing-based preimplantation genetic testing (PGT)?
Applying ETS-PGT, the chance of sample switching is decreased, while scalability and efficacy could easily be increased substantially.
Although state-of-the-art sequencing-based PGT methods made a paradigm shift in PGT, they still require labor intensive library preparation steps that makes PGT cost prohibitive and poses risks of human errors. To increase the quality assurance, efficiency, robustness and throughput of the sequencing-based assays, barcoded DNA fragments have been used in several aspects of next-generation sequencing (NGS) approach.
We developed an ETS that substantially alleviates the complexity of the current sequencing-based PGT. With (n = 693) and without (n = 192) ETS, the downstream PGT procedure was performed on both bulk DNA samples (n = 563) and whole-genome amplified (WGAed) few-cell DNA samples (n = 322). Subsequently, we compared full genome haplotype landscapes of both WGAed and bulk DNA samples containing ETS or no ETS.
We have devised an ETS to track embryos right after whole-genome amplification (WGA) to full genome haplotype profiles. In this study, we recruited 322 WGAed DNA samples derived from IVF embryos as well as 563 bulk DNA isolated from peripheral blood of prospective parents. To determine possible interference of the ETS in the NGS-based PGT workflow, barcoded DNA fragments were added to DNA samples prior to library preparation and compared to samples without ETS. Coverages and variants were determined.
Current PGT protocols are quality sensitive and prone to sample switching. To avoid sample switching and increase throughput of PGT by sequencing-based haplotyping, six control steps should be carried out manually and checked by a second person in a clinical setting. Here, we developed an ETS approach in which one step only in the entire PGT procedure needs the four-eyes principal. We demonstrate that ETS not only precludes error-prone manual checks but also has no effect on the genomic landscape of preimplantation embryos. Importantly, our approach increases efficacy and throughput of the state-of-the-art PGT methods.
Even though the ETS simplified sequencing-based PGT by avoiding potential errors in six steps in the protocol, if the initial assignment is not performed correctly, it could lead to cross-contamination. However, this can be detected in silico following downstream ETS analysis. Although we demonstrated an approach to evaluate purity of the ETS fragment, it is recommended to perform a pre-PGT quality control assay of the ETS amplicons with non-human DNA, such that the purity of each ETS molecule can be determined prior to ETS-PGT.
The ETS-PGT approach notably increases efficacy and scalability of PGT. ETS-PGT has broad applicative value, as it can be tailored to any single- and few-cell sequencing approach where the starting specimen is scarce, as opposed to other methods that require a large number of cells as the input. Moreover, ETS-PGT could easily be adapted to any sequencing-based diagnostic method, including PGT for structural rearrangements and aneuploidies by low-pass sequencing as well as non-invasive prenatal testing.
M.Z.E. is supported by the EVA (Erfelijkheid Voortplanting & Aanleg) specialty program (grant no. KP111513) of Maastricht University Medical Centre (MUMC+), and the Horizon 2020 innovation (ERIN) (grant no. EU952516) of the European Commission.
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With the advent of new molecular diagnostic techniques, retrieving DNA from the formalin-fixed paraffin-embedded (FFPE) tissues has become an essential yet challenging step for efficient downstream processes. Owing to low quality and quantity of DNA retrieved from the FFPE sections, the process is often impractical and needs significant improvements. Here, we established an efficient method for the purification of DNA from FFPE specimens by optimizing incubation temperature, incubation time, and the concentration of a formalin scavenger tris(hydroxymethyl)aminomethane (Tris) for reverse-crosslinking. The optimized method, named \"Highly concentrated Tris-mediated DNA extraction\" (HiTE), yielded three times the DNA yield per tissue slice compared with a representative DNA extraction kit. Moreover, the use of HiTE-extracted DNA increased the yield of the sequencing library three times and accordingly yielded a log higher and more reproducible sequencing library compared with that obtained using the commonly used commercial kit. The sequencing library prepared from HiTE-extracted FFPE-DNA had longer inserts and produced reads that evenly covered the reference genome. Successful application of HiTE-extracted FFPE-DNA for whole-genome and targeted gene panel sequencing indicates its practical usability.

Tumor heterogeneity has been known to cause inter-assay discordance among next-generation sequencing (NGS) results. However, whether preclinical factors such as sample type, sample quality and analytical features of gene panel can affect the concordance between two different assays remains largely unexplored.
Replicate sets of DNA samples extracted from formalin-fixed paraffin-embedded tissues (FFPE) (n = 20) and fresh frozen (FF) tissues (n = 10) were herein analyzed using a tumor-only (TO) and paired tumor-normal (TN) gene panel in laboratories certified by the Clinical Laboratory Improvement Amendment. Reported variants from the TO and TN panels were then compared. Furthermore, additional FFPE samples were sequentially sliced from the same FFPE block and submitted to another TN panel assay.
Substantial discordance (71.8%) was observed between the results of the two panels despite using identical DNA samples, with the discordance rate being significantly higher for FFPE samples (p < 0.05). Among the 99 variants reported only in the TO panel, 32.3% were consistent with germline variants, which were excluded in the TN panel, while 30.3% had an allele frequency of less than 5%, some of which were highly likely to be artificial calls. The comparison of two independent TN panel assay results from the same FFPE block also showed substantial discordance rate (55.3%).
In the context of clinical settings, our comparative analysis revealed that inter-NGS assay discordance commonly occurred due to sample types and the different analytical features of each panel.

Next generation sequencing for oncology patient management is now routine in clinical pathology laboratories. Although wet lab, sequencing and pipeline tasks are largely automated, the analysis of variants for clinical reporting remains largely a manual task. The increasing volume of sequencing data and the limited availability of genetic experts to analyse and report on variants in the data is a key scalability limit for molecular diagnostics.
To determine the impact and size of the issue, we examined the longitudinally compiled genetic variants from 48,036 cancer patients over a six year period in a large cancer hospital from ten targeted cancer panel tests in germline, solid tumour and haematology contexts using hybridization capture and amplicon assays. This testing generated 24,168,398 sequenced variants of which 23,255 (8214 unique) were clinically reported.
Of the reported variants, 17,240 (74.1%) were identified in more than one assay which allowed curated variant data to be reused in later reports. The remainder, 6015 (25.9%) were not subsequently seen in later assays and did not provide any reuse benefit. The number of new variants requiring curation has significantly increased over time from 1.72 to 3.73 variants per sample (292 curated variants per month). Analysis of the 23,255 variants reported, showed 28.6% (n = 2356) were not present in common public variant resources and therefore required de novo curation. These in-house only variants were enriched for indels, tumour suppressor genes and from solid tumour assays.
This analysis highlights the significant percentage of variants not present within common public variant resources and the level of non-recurrent variants that consequently require greater curation effort. Many of these variants are unique to a single patient and unlikely to appear in other patients reflecting the personalised nature of cancer genomics. This study depicts the real-world situation for pathology laboratories faced with curating increasing numbers of low-recurrence variants while needing to expedite the process of manual variant curation. In the absence of suitably accurate automated methods, new approaches are needed to scale oncology diagnostics for future genetic testing volumes.

Cancer immunotherapy holds great promise and has shown durable responses in many patients; however, these responses are not uniform in all patients or all tumour streams. There is an ongoing clinical need for objective diagnostic biomarkers to identify patients that will respond to immunotherapies. Tumour mutational burden (TMB) is a diagnostic biomarker that can stratify cancer patients for response to immune checkpoint inhibitor therapies. It is commonly defined as the average number of somatic mutations per megabase in a tumour exome. Here we describe the TMB biomarker, how it is determined, its underlying molecular basis, the relationship to neoantigens and the issues around its clinical use. This overview is directed toward practising pathologists wishing to be informed of this predictive biomarker.

Metastatic progression is the main cause of death in cancer patients, whereas the underlying genomic mechanisms driving metastasis remain largely unknown. Here, we assembled MSK-MET, a pan-cancer cohort of over 25,000 patients with metastatic diseases. By analyzing genomic and clinical data from this cohort, we identified associations between genomic alterations and patterns of metastatic dissemination across 50 tumor types. We found that chromosomal instability is strongly correlated with metastatic burden in some tumor types, including prostate adenocarcinoma, lung adenocarcinoma, and HR+/HER2+ breast ductal carcinoma, but not in others, including colorectal cancer and high-grade serous ovarian cancer, where copy-number alteration patterns may be established early in tumor development. We also identified somatic alterations associated with metastatic burden and specific target organs. Our data offer a valuable resource for the investigation of the biological basis for metastatic spread and highlight the complex role of chromosomal instability in cancer progression.