Downstream Revenue Generated by Patients With Hereditary Cancer in the Multigene Panel Testing Era.

PURPOSE: Patients with hereditary cancer syndromes face increased medical management recommendations to address their cancer risks. As multigene panels are the standard of testing today, more patients needing clinical intervention are being identified. This study calculates the downstream revenue (DSR) generated by patients ascertained by a genetic counselor (GC) with a hereditary cancer likely pathogenic/pathogenic variant (LPV/PV). METHODS: Retrospective chart review was performed for patients seen in a high-volume cancer genetics clinic between October 1, 2009, and December 31, 2021, with LPV/PVs in hereditary cancer predisposition genes. DSR and work relative value units (wRVUs) were calculated for each patient before and after they met with a GC. Subgroup analyses calculated DSR/wRVUs from patients affected and unaffected with cancer and those whose genetic counseling visit was the first at the institution (naїve). RESULTS: A total of 978 patients were available for analysis after exclusions were applied. Patients generated $73.06 million (M) in US dollars (USD) in DSR and 54,814 wRVUs after their initial genetic counseling visit. Unaffected patients (n = 370, 37.8%) generated $11.38M (USD) and 13,879 wRVUs; affected patients (n = 608, 62.2%) generated $61.68M (USD) and 40,935 wRVUs. Naïve patients (n = 367, 37.5%) generated $15.39M (USD) and 11,811 wRVUs; established patients (n = 611, 62.5%) generated $57.67M (USD) and 43,003 wRVUs. Unaffected, naïve patients (n = 204, 20.9%) generated $5.48M (USD) and 5,186 wRVUs. CONCLUSION: By identifying patients with hereditary cancer, GCs can bring in substantial DSR for their institution. Naïve and unaffected patients provide the greatest GC value-add as these patients represent new business and revenue sources to the institution. As multigene panels continue to expand, the number of patients needing downstream services will increase. Recognizing patients at increased cancer risk will improve patient outcomes while simultaneously providing DSR for institutions.

Large-scale Pan-cancer Cell Line Screening Identifies Actionable and Effective Drug Combinations.

Oncology drug combinations can improve therapeutic responses and increase treatment options for patients. The number of possible combinations is vast and responses can be context-specific. Systematic screens can identify clinically relevant, actionable combinations in defined patient subtypes. We present data for 109 anticancer drug combinations from AstraZeneca's oncology small molecule portfolio screened in 755 pan-cancer cell lines. Combinations were screened in a 7 × 7 concentration matrix, with more than 4 million measurements of sensitivity, producing an exceptionally data-rich resource. We implement a new approach using combination Emax (viability effect) and highest single agent (HSA) to assess combination benefit. We designed a clinical translatability workflow to identify combinations with clearly defined patient populations, rationale for tolerability based on tumor type and combination-specific "emergent" biomarkers, and exposures relevant to clinical doses. We describe three actionable combinations in defined cancer types, confirmed in vitro and in vivo, with a focus on hematologic cancers and apoptotic targets. SIGNIFICANCE: We present the largest cancer drug combination screen published to date with 7 × 7 concentration response matrices for 109 combinations in more than 750 cell lines, complemented by multi-omics predictors of response and identification of "emergent" combination biomarkers. We prioritize hits to optimize clinical translatability, and experimentally validate novel combination hypotheses. This article is featured in Selected Articles from This Issue, p. 695.

Pan-cancer proteomic map of 949 human cell lines.

The proteome provides unique insights into disease biology beyond the genome and transcriptome. A lack of large proteomic datasets has restricted the identification of new cancer biomarkers. Here, proteomes of 949 cancer cell lines across 28 tissue types are analyzed by mass spectrometry. Deploying a workflow to quantify 8,498 proteins, these data capture evidence of cell-type and post-transcriptional modifications. Integrating multi-omics, drug response, and CRISPR-Cas9 gene essentiality screens with a deep learning-based pipeline reveals thousands of protein biomarkers of cancer vulnerabilities that are not significant at the transcript level. The power of the proteome to predict drug response is very similar to that of the transcriptome. Further, random downsampling to only 1,500 proteins has limited impact on predictive power, consistent with protein networks being highly connected and co-regulated. This pan-cancer proteomic map (ProCan-DepMapSanger) is a comprehensive resource available at https://cellmodelpassports.sanger.ac.uk.

A suspension technique for efficient large-scale cancer organoid culturing and perturbation screens.

Organoid cell culture methodologies are enabling the generation of cell models from healthy and diseased tissue. Patient-derived cancer organoids that recapitulate the genetic and histopathological diversity of patient tumours are being systematically generated, providing an opportunity to investigate new cancer biology and therapeutic approaches. The use of organoid cultures for many applications, including genetic and chemical perturbation screens, is limited due to the technical demands and cost associated with their handling and propagation. Here we report and benchmark a suspension culture technique for cancer organoids which allows for the expansion of models to tens of millions of cells with increased efficiency in comparison to standard organoid culturing protocols. Using whole-genome DNA and RNA sequencing analyses, as well as medium-throughput drug sensitivity testing and genome-wide CRISPR-Cas9 screening, we demonstrate that cancer organoids grown as a suspension culture are genetically and phenotypically similar to their counterparts grown in standard conditions. This culture technique simplifies organoid cell culture and extends the range of organoid applications, including for routine use in large-scale perturbation screens.

Effective drug combinations in breast, colon and pancreatic cancer cells.

Combinations of anti-cancer drugs can overcome resistance and provide new treatments1,2. The number of possible drug combinations vastly exceeds what could be tested clinically. Efforts to systematically identify active combinations and the tissues and molecular contexts in which they are most effective could accelerate the development of combination treatments. Here we evaluate the potency and efficacy of 2,025 clinically relevant two-drug combinations, generating a dataset encompassing 125 molecularly characterized breast, colorectal and pancreatic cancer cell lines. We show that synergy between drugs is rare and highly context-dependent, and that combinations of targeted agents are most likely to be synergistic. We incorporate multi-omic molecular features to identify combination biomarkers and specify synergistic drug combinations and their active contexts, including in basal-like breast cancer, and microsatellite-stable or KRAS-mutant colon cancer. Our results show that irinotecan and CHEK1 inhibition have synergistic effects in microsatellite-stable or KRAS-TP53 double-mutant colon cancer cells, leading to apoptosis and suppression of tumour xenograft growth. This study identifies clinically relevant effective drug combinations in distinct molecular subpopulations and is a resource to guide rational efforts to develop combinatorial drug treatments.

Drug mechanism-of-action discovery through the integration of pharmacological and CRISPR screens.

Low success rates during drug development are due, in part, to the difficulty of defining drug mechanism-of-action and molecular markers of therapeutic activity. Here, we integrated 199,219 drug sensitivity measurements for 397 unique anti-cancer drugs with genome-wide CRISPR loss-of-function screens in 484 cell lines to systematically investigate cellular drug mechanism-of-action. We observed an enrichment for positive associations between the profile of drug sensitivity and knockout of a drug's nominal target, and by leveraging protein-protein networks, we identified pathways underpinning drug sensitivity. This revealed an unappreciated positive association between mitochondrial E3 ubiquitin-protein ligase MARCH5 dependency and sensitivity to MCL1 inhibitors in breast cancer cell lines. We also estimated drug on-target and off-target activity, informing on specificity, potency and toxicity. Linking drug and gene dependency together with genomic data sets uncovered contexts in which molecular networks when perturbed mediate cancer cell loss-of-fitness and thereby provide independent and orthogonal evidence of biomarkers for drug development. This study illustrates how integrating cell line drug sensitivity with CRISPR loss-of-function screens can elucidate mechanism-of-action to advance drug development.

Cell Model Passports-a hub for clinical, genetic and functional datasets of preclinical cancer models.

In vitro cancer cell cultures are facile experimental models used widely for research and drug development. Many cancer cell lines are available and efforts are ongoing to derive new models representing the histopathological and molecular diversity of tumours. Cell models have been generated by multiple laboratories over decades and consequently their annotation is incomplete and inconsistent. Furthermore, the relationships between many patient-matched and derivative cell lines have been lost, and accessing information and datasets is time-consuming and difficult. Here, we describe the Cell Model Passports database; cellmodelpassports.sanger.ac.uk, which provides details of cell model relationships, patient and clinical information, as well as access to associated genetic and functional datasets. The Passports database currently contains curated details and standardized annotation for >1200 cell models, including cancer organoid cultures. The Passports will be updated with newly derived cell models and datasets as they are generated. Users can navigate the database via tissue, cancer-type, genetic feature and data availability to select a model most suitable for specific applications. A flexible REST-API provides programmatic data access and exploration. The Cell Model Passports are a valuable tool enabling access to high-dimensional genomic and phenotypic cancer cell model datasets empowering diverse research applications.

HRG1 is essential for heme transport from the phagolysosome of macrophages during erythrophagocytosis.

Adult humans have about 25 trillion red blood cells (RBCs), and each second we recycle about 5 million RBCs by erythrophagocytosis (EP) in macrophages of the reticuloendothelial system. Despite the central role for EP in mammalian iron metabolism, the molecules and pathways responsible for heme trafficking during EP remain unknown. Here, we show that the mammalian homolog of HRG1, a transmembrane heme permease in C. elegans, is essential for macrophage iron homeostasis and transports heme from the phagolysosome to the cytoplasm during EP. HRG1 is strongly expressed in macrophages of the reticuloendothelial system and specifically localizes to the phagolysosomal membranes during EP. Depletion of Hrg1 in mouse macrophages causes attenuation of heme transport from the phagolysosomal compartment. Importantly, missense polymorphisms in human HRG1 are defective in heme transport. Our results reveal HRG1 as the long-sought heme transporter for heme-iron recycling in macrophages and suggest that genetic variations in HRG1 could be modifiers of human iron metabolism.

Coupling of DNA synthesis and histone synthesis in S phase independent of cyclin/cdk2 activity.

DNA and histone synthesis are both triggered at the beginning of S phase by cyclin/cdk2 activity. Previous studies showed that inhibition of DNA synthesis with hydroxyurea or cytosine arabinoside (AraC) triggers a concerted repression of histone synthesis, indicating that sustained histone synthesis depends on continued DNA synthesis. Here we show that ectopic expression of HIRA, the likely human ortholog of two cell cycle-regulated repressors of histone gene transcription in yeast (Hir1p and Hir2p), represses transcription of histones and that this, in turn, triggers a concerted block of DNA synthesis. Thus, in mammalian cells sustained DNA synthesis and histone synthesis are mutually dependent on each other during S phase. Although cyclin/cdk2 activity drives activation of both DNA and histone synthesis at the G1/S transition of cycling cells, concerted repression of DNA or histone synthesis in response to inhibition of either one of these is not accompanied by prolonged inhibition of cyclin A/cdk2 or E/cdk2 activity. Therefore, during S phase coupling of DNA and histone synthesis occurs, at least in part, through a mechanism that is independent of cyclin/cdk2 activity. Coupling of DNA and histone synthesis in S phase presumably contributes to the prompt and orderly assembly of newly replicated DNA into chromatin.