An inflection point in high-throughput proteomics with Orbitrap Astral: analysis of biofluids, cells, and tissues.

This technical note presents a comprehensive proteomics workflow for the new combination of Orbitrap and Astral mass analyzers across biofluids, cells, and tissues. Central to our workflow is the integration of Adaptive Focused Acoustics (AFA) technology for cells and tissue lysis, to ensure robust and reproducible sample preparation in a high-throughput manner. Furthermore, we automated the detergent-compatible single-pot, solid-phase-enhanced sample Preparation (SP3) method for protein digestion, a technique that streamlines the process by combining purification and digestion steps, thereby reducing sample loss and improving efficiency. The synergy of these advanced methodologies facilitates a robust and high-throughput approach for cells and tissue analysis, an important consideration in translational research. This work disseminates our platform workflow, analyzes the effectiveness, demonstrates reproducibility of the results, and highlights the potential of these technologies in biomarker discovery and disease pathology. For cells and tissues (heart, liver, lung, and intestine) proteomics analysis by data-independent acquisition mode, identifications exceeding 10,000 proteins can be achieved with a 24-minute active gradient. In 200ng injections of HeLa digest across multiple gradients, an average of more than 80% of proteins have a CV less than 20%, and a 45-minute run covers ~90% of the expressed proteome. In plasma samples including naive, depleted, perchloric acid precipitated, and Seer nanoparticle captured, all with a 24-minute gradient length, we identified 87, 108, 96 and 137 out of 216 FDA approved circulating protein biomarkers, respectively. This complete workflow allows for large swaths of the proteome to be identified and is compatible across diverse sample types.

Assessment of a 60-Biomarker Health Surveillance Panel (HSP) on Whole Blood from Remote Sampling Devices by Targeted LC/MRM-MS and Discovery DIA-MS Analysis.

Telehealth, accessing healthcare and wellness remotely, should be a cost-effective and efficient way for individuals to receive care. The convenience of having a reliable remote collection device for blood tests will facilitate access to precision medicine and healthcare. Herein, we tested a 60-biomarker health surveillance panel (HSP), containing 35 FDA/LDT assays and covering at least 14 pathological states, on 8 healthy individuals' ability to collect their own capillary blood from a lancet finger prick and directly compared it to the traditional phlebotomist venous blood and plasma collection methods. All samples were spiked with 114 stable-isotope-labeled (SIL) HSP peptides and quantitatively analyzed by liquid chromatography-multiple reaction monitoring-mass spectrometry (LC/MRM-MS) scheduled method targeting 466 transitions from 114 HSP peptides and by a discovery data-independent acquisition mass spectrometry (DIA-MS) method. The average peak area ratio (PAR) of the HSP quantifier peptide transitions from all 8 volunteers' capillary blood (n = 48), venous blood (n = 48), and matched plasma (n = 24) was <20% coefficients of variation (CV). Heat map analysis of all 8 volunteers demonstrated that each individual had a unique biosignature. Biological replicates from capillary blood and venous blood clustered within each volunteer in k-means clustering analysis. Pearson statistical analysis of the three biofluids indicated that there was >90% similarity. Discovery DIA-MS analysis of the same samples using a plasma spectral library and a pan-human spectral library identified 1121 and 4661 total proteins, respectively. In addition, at least 122 FDA-approved biomarkers were identified. DIA-MS analysis reproducibly quantitated (<30% CV) ∼600-700 proteins in capillary blood, ∼800 proteins in venous blood, and ∼300-400 proteins in plasma, demonstrating that an expansive biomarker panel is possible with current mass spectrometry technology. Both targeted LC/MRM-MS and discovery DIA-MS analysis of whole blood collected on remote sampling devices are viable options for personal proteome biosignature stratification in precision medicine and precision health.

The Maine Cancer Genomics Initiative: Implementing a Community Cancer Genomics Program Across an Entire Rural State.

PURPOSE: The Maine Cancer Genomics Initiative (MCGI) aimed to overcome patient- and provider-level barriers to using genomic tumor testing (GTT) in rural practices by providing genomic tumor boards (GTBs), clinician education, and access to comprehensive large-panel next-generation sequencing to all patients with cancer in Maine. This paper describes the successful implementation of the initiative and three key services made operative between 2016 and 2020. METHODS: A community-inclusive, hub-and-spoke approach was taken to implement the three program components: (1) a centralized GTB program; (2) a modular online education program, designed using an iterative approach with broad clinical stakeholders; and (3) GTT free of charge to clinicians and patients. Implementation timelines, participation metrics, and survey data were used to describe the rollout. RESULTS: The MCGI was launched over an 18-month period at all 19 oncology practices in the State. Seventy-nine physicians (66 medical oncologists, 5 gynecologic oncologists, 1 neuro-oncologist, and 7 pediatric oncologists) enrolled on the study, representing 100% of all practicing oncologists in Maine. Between July 2017 and September 2020, 1610 patients were enrolled. A total of 515 cases were discussed by 47 (73%) clinicians in 196 GTBs. Clinicians who participated in the GTBs enrolled significantly more patients on the study, stayed in Maine, and reported less time spent in clinical patient care. CONCLUSION: The MCGI was able to engage geographically and culturally disparate cancer care practices in a precision oncology program using a hub-and-spoke model. By facilitating access to GTT, structured education, and GTBs, we narrowed the gap in the implementation of precision oncology in one of the most rural states in the country.

A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer.

Precision oncology relies on accurate discovery and interpretation of genomic variants, enabling individualized diagnosis, prognosis and therapy selection. We found that six prominent somatic cancer variant knowledgebases were highly disparate in content, structure and supporting primary literature, impeding consensus when evaluating variants and their relevance in a clinical setting. We developed a framework for harmonizing variant interpretations to produce a meta-knowledgebase of 12,856 aggregate interpretations. We demonstrated large gains in overlap between resources across variants, diseases and drugs as a result of this harmonization. We subsequently demonstrated improved matching between a patient cohort and harmonized interpretations of potential clinical significance, observing an increase from an average of 33% per individual knowledgebase to 57% in aggregate. Our analyses illuminate the need for open, interoperable sharing of variant interpretation data. We also provide a freely available web interface (search.cancervariants.org) for exploring the harmonized interpretations from these six knowledgebases.

Cisplatin-resistant triple-negative breast cancer subtypes: multiple mechanisms of resistance.

BACKGROUND: Understanding mechanisms underlying specific chemotherapeutic responses in subtypes of cancer may improve identification of treatment strategies most likely to benefit particular patients. For example, triple-negative breast cancer (TNBC) patients have variable response to the chemotherapeutic agent cisplatin. Understanding the basis of treatment response in cancer subtypes will lead to more informed decisions about selection of treatment strategies. METHODS: In this study we used an integrative functional genomics approach to investigate the molecular mechanisms underlying known cisplatin-response differences among subtypes of TNBC. To identify changes in gene expression that could explain mechanisms of resistance, we examined 102 evolutionarily conserved cisplatin-associated genes, evaluating their differential expression in the cisplatin-sensitive, basal-like 1 (BL1) and basal-like 2 (BL2) subtypes, and the two cisplatin-resistant, luminal androgen receptor (LAR) and mesenchymal (M) subtypes of TNBC. RESULTS: We found 20 genes that were differentially expressed in at least one subtype. Fifteen of the 20 genes are associated with cell death and are distributed among all TNBC subtypes. The less cisplatin-responsive LAR and M TNBC subtypes show different regulation of 13 genes compared to the more sensitive BL1 and BL2 subtypes. These 13 genes identify a variety of cisplatin-resistance mechanisms including increased transport and detoxification of cisplatin, and mis-regulation of the epithelial to mesenchymal transition. CONCLUSIONS: We identified gene signatures in resistant TNBC subtypes indicative of mechanisms of cisplatin. Our results indicate that response to cisplatin in TNBC has a complex foundation based on impact of treatment on distinct cellular pathways. We find that examination of expression data in the context of heterogeneous data such as drug-gene interactions leads to a better understanding of mechanisms at work in cancer therapy response.

Utility of the JAX Clinical Knowledgebase in capture and assessment of complex genomic cancer data.

Cancer genomic data is continually growing in complexity, necessitating improved methods for data capture and analysis. Tumors often contain multiple therapeutically relevant alterations, and co-occurring alterations may have a different influence on therapeutic response compared to if those alterations were present alone. One clinically important example of this is the existence of a resistance conferring alteration in combination with a therapeutic sensitizing mutation. The JAX Clinical Knowledgebase (JAX-CKB) (https://ckb.jax.org/) has incorporated the concept of the complex molecular profile, which enables association of therapeutic efficacy data with multiple genomic alterations simultaneously. This provides a mechanism for rapid and accurate assessment of complex cancer-related data, potentially aiding in streamlined clinical decision making. Using the JAX-CKB, we demonstrate the utility of associating data with complex profiles comprising ALK fusions with another variant, which have differing impacts on sensitivity to various ALK inhibitors depending on context.

High-resolution deconstruction of evolution induced by chemotherapy treatments in breast cancer xenografts.

The processes by which tumors evolve are essential to the efficacy of treatment, but quantitative understanding of intratumoral dynamics has been limited. Although intratumoral heterogeneity is common, quantification of evolution is difficult from clinical samples because treatment replicates cannot be performed and because matched serial samples are infrequently available. To circumvent these problems we derived and assayed large sets of human triple-negative breast cancer xenografts and cell cultures from two patients, including 86 xenografts from cyclophosphamide, doxorubicin, cisplatin, docetaxel, or vehicle treatment cohorts as well as 45 related cell cultures. We assayed these samples via exome-seq and/or high-resolution droplet digital PCR, allowing us to distinguish complex therapy-induced selection and drift processes among endogenous cancer subclones with cellularity uncertainty <3%. For one patient, we discovered two predominant subclones that were granularly intermixed in all 48 co-derived xenograft samples. These two subclones exhibited differential chemotherapy sensitivity-when xenografts were treated with cisplatin for 3 weeks, the post-treatment volume change was proportional to the post-treatment ratio of subclones on a xenograft-to-xenograft basis. A subsequent cohort in which xenografts were treated with cisplatin, allowed a drug holiday, then treated a second time continued to exhibit this proportionality. In contrast, xenografts from other treatment cohorts, spatially dissected xenograft fragments, and cell cultures evolved in diverse ways but with substantial population bottlenecks. These results show that ecosystems susceptible to successive retreatment can arise spontaneously in breast cancer in spite of a background of irregular subclonal bottlenecks, and our work provides to our knowledge the first quantification of the population genetics of such a system. Intriguingly, in such an ecosystem the ratio of common subclones is predictive of the state of treatment susceptibility, showing how measurements of subclonal heterogeneity could guide treatment for some patients.

Barriers preventing the adoption of comprehensive cancer genomic profiling in the clinic.

INTRODUCTION: Comprehensive cancer genomic profiling provides the opportunity to expose the various molecular aberrations potentially driving tumor progression. Consequently, the identity of these genetic drivers can be utilized to match a patient to the most appropriate targeted therapy, thereby increasing the probability of improved clinical outcome. Despite its capability of informing patient care, the adoption of comprehensive cancer genomic profiling in the clinic has not been widespread. The barriers surrounding its universal acceptance are attributed to both physician and patient perspectives. Areas covered: The following report discusses the various obstacles in place, including those related to clinical utility, education, insurance coverage, and clinical trials, which can deter physicians and patients from utilizing genomic profiling for therapeutic decision-making. Expert commentary: The authors review the recent growth and potential of clinical utility studies over the last two years, provide a suggestive framework for educational support, and comment on the use of social media to enhance clinical trial recruitment.

Mutations in TP53, PIK3CA, PTEN and other genes in EGFR mutated lung cancers: Correlation with clinical outcomes.

INTRODUCTION: The degree and duration of response to epidermal growth factor receptor (EGFR) inhibitors in EGFR mutated lung cancer are heterogeneous. We hypothesized that the concurrent genomic landscape of these tumors, which is currently unknown in view of the prevailing single gene assay diagnostic paradigm in clinical practice, could play a role in clinical outcomes and/or mechanisms of resistance. METHODS: We retrospectively probed our institutional lung cancer database for tumors with EGFR kinase domain mutations that were also evaluated by more comprehensive molecular profiling, and evaluated tumor response to EGFR tyrosine kinase inhibitors (TKIs). RESULTS: Out of 171 EGFR mutated tumor-patient cases, 20 were sequenced using at least a limited comprehensive genomic profiling platform. 50% harbored concurrent TP53 mutation, 10% PIK3CA mutation, 5% PTEN mutation, among others. The response rate to EGFR TKIs, the median progression-free survival (PFS) to TKIs, the percentage of EGFR-T790M TKI resistance and survival had higher trends in EGFR mutant/TP53 wild-type cases when compared to EGFR mutant/TP53 mutant tumors (all p >0.05 without statistical significance); with a significantly longer median PFS in EGFR-exon 19 deletion mutant/TP53 wild-type cancers treated with 1st generation EGFR TKIs (p=0.035). CONCLUSIONS: Concurrent mutations, specifically TP53, are common in EGFR mutated lung cancer and may alter clinical outcomes. Additional cohorts will be needed to determine if comprehensive molecular profiling adds clinically relevant information to single gene assay identification in oncogene-driven lung cancers.

mTOR Inhibitors in Castration-Resistant Prostate Cancer: A Systematic Review.

BACKGROUND: The progression of prostate cancer to castration-resistant prostate cancer (CRPC) is often a result of somatic alterations in the PI3K/Akt/mTOR (mammalian target of rapamycin) pathway, suggesting that therapies targeting this pathway might lead to improved survival and efficacy. Here, we systematically evaluate the results of clinical trials investigating mTOR inhibition in CRPC and utilize preclinical data to predict clinical outcomes. METHODS: Trials included in the study were identified through PubMed and via review of conference abstracts cited by relevant review articles. The eligibility of trials was independent of sample size, clinical setting, or date. RESULTS: A total of 14 studies were eligible for qualitative analysis. The clinical setting was variable among studies, and all utilized an allosteric mTOR inhibitor as either a monotherapy or in combination. Molecular criteria were evaluated in three trials. Among most studies, the prostate-specific antigen level declined during treatment, but often increased shortly thereafter. Partial responses to treatment were minimal, and no complete responses were reported. Two studies exploring therapy with an mTOR inhibitor in combination with bicalutamide resulted in minimal efficacy. Overall, allosteric mTOR inhibition was deemed to be inadequate for the treatment of CRPC. CONCLUSION: Preclinical data suggest that a reciprocal feedback mechanism between PI3K and androgen receptor signaling is a potential mechanism behind the clinical inefficacy of mTOR inhibitors in CRPC, indicating combinatorial targeting of PI3K, mTORC1/2, and the androgen receptor might be more effective. Comprehensive analysis of preclinical data to assess clinical trial targets and efficacy may reduce the number of unproductive trials and identify potentially beneficial combinatorial therapies for resistant disease.

The clinical trial landscape in oncology and connectivity of somatic mutational profiles to targeted therapies.

BACKGROUND: Precision medicine in oncology relies on rapid associations between patient-specific variations and targeted therapeutic efficacy. Due to the advancement of genomic analysis, a vast literature characterizing cancer-associated molecular aberrations and relative therapeutic relevance has been published. However, data are not uniformly reported or readily available, and accessing relevant information in a clinically acceptable time-frame is a daunting proposition, hampering connections between patients and appropriate therapeutic options. One important therapeutic avenue for oncology patients is through clinical trials. Accordingly, a global view into the availability of targeted clinical trials would provide insight into strengths and weaknesses and potentially enable research focus. However, data regarding the landscape of clinical trials in oncology is not readily available, and as a result, a comprehensive understanding of clinical trial availability is difficult. RESULTS: To support clinical decision-making, we have developed a data loader and mapper that connects sequence information from oncology patients to data stored in an in-house database, the JAX Clinical Knowledgebase (JAX-CKB), which can be queried readily to access comprehensive data for clinical reporting via customized reporting queries. JAX-CKB functions as a repository to house expertly curated clinically relevant data surrounding our 358-gene panel, the JAX Cancer Treatment Profile (JAX CTP), and supports annotation of functional significance of molecular variants. Through queries of data housed in JAX-CKB, we have analyzed the landscape of clinical trials relevant to our 358-gene targeted sequencing panel to evaluate strengths and weaknesses in current molecular targeting in oncology. Through this analysis, we have identified patient indications, molecular aberrations, and targeted therapy classes that have strong or weak representation in clinical trials. CONCLUSIONS: Here, we describe the development and disseminate system methods for associating patient genomic sequence data with clinically relevant information, facilitating interpretation and providing a mechanism for informing therapeutic decision-making. Additionally, through customized queries, we have the capability to rapidly analyze the landscape of targeted therapies in clinical trials, enabling a unique view into current therapeutic availability in oncology.

Molecular Genetic Analysis of Ovarian Brenner Tumors and Associated Mucinous Epithelial Neoplasms: High Variant Concordance and Identification of Mutually Exclusive RAS Driver Mutations and MYC Amplification.

Benign ovarian Brenner tumors often are associated with mucinous cystic neoplasms, which are hypothesized to share a histogenic origin and progression, however, supporting molecular characterization is limited. Our goal was to identify molecular mechanisms linking these tumors. DNA from six Brenner tumors with paired mucinous tumors, two Brenner tumors not associated with a mucinous neoplasm, and two atypical proliferative (borderline) Brenner tumors was extracted from formalin-fixed, paraffin-embedded tumor samples and sequenced using a 358-gene next-generation sequencing assay. Variant calls were compared within tumor groups to assess somatic mutation profiles. There was high concordance of the variants between paired samples (40% to 75%; P < 0.0001). Four of the six tumor pairs showed KRAS hotspot driver mutations specifically in the mucinous tumor. In the two paired samples that lacked KRAS mutations, MYC amplification was detected in both of the mucinous and the Brenner components; MYC amplification also was detected in a third Brenner tumor. Five of the Brenner tumors had no reportable potential driver alterations. The two atypical proliferative (borderline) Brenner tumors both had RAS mutations. The high degree of coordinate variants between paired Brenner and mucinous tumors supports a shared origin or progression. Differences observed in affected genes and pathways, particularly involving RAS and MYC, may point to molecular drivers of a divergent phenotype and progression of these tumors.

Clinical Trials in Precision Oncology.

BACKGROUND: Availability of genomic information used in the management of cancer treatment has outpaced both regulatory and reimbursement efforts. Many types of clinical trials are underway to validate the utility of emerging genome-based biomarkers for diagnostic, prognostic, and predictive applications. Clinical trials are a key source of evidence required for US Food and Drug Administration approval of therapies and companion diagnostics and for establishing the acceptance criteria for reimbursement. CONTENT: Determining the eligibility of patients for molecular-based clinical trials and the interpretation of data emerging from clinical trials is significantly hampered by 2 primary factors: the lack of specific reporting standards for biomarkers in clinical trials and the lack of adherence to official gene and variant naming standards. Clinical trial registries need specifics on the mutation required for enrollment as opposed to allowing a generic mutation entry such as, "EGFR mutation." The use of clinical trials data in bioinformatics analysis and reporting is also gated by the lack of robust, state of the art programmatic access support. An initiative is needed to develop community standards for clinical trial descriptions and outcome reporting that are modeled after similar efforts in the genomics research community. SUMMARY: Systematic implementation of reporting standards is needed to insure consistency and specificity of biomarker data, which will in turn enable better comparison and assessment of clinical trial outcomes across multiple studies. Reporting standards will facilitate improved identification of relevant clinical trials, aggregation and comparison of information across independent trials, and programmatic access to clinical trials databases.

Development and validation of the JAX Cancer Treatment Profile™ for detection of clinically actionable mutations in solid tumors.

BACKGROUND: The continued development of targeted therapeutics for cancer treatment has required the concomitant development of more expansive methods for the molecular profiling of the patient's tumor. We describe the validation of the JAX Cancer Treatment Profile™ (JAX-CTP™), a next generation sequencing (NGS)-based molecular diagnostic assay that detects actionable mutations in solid tumors to inform the selection of targeted therapeutics for cancer treatment. METHODS: NGS libraries are generated from DNA extracted from formalin fixed paraffin embedded tumors. Using hybrid capture, the genes of interest are enriched and sequenced on the Illumina HiSeq 2500 or MiSeq sequencers followed by variant detection and functional and clinical annotation for the generation of a clinical report. RESULTS: The JAX-CTP™ detects actionable variants, in the form of single nucleotide variations and small insertions and deletions (≤50 bp) in 190 genes in specimens with a neoplastic cell content of ≥10%. The JAX-CTP™ is also validated for the detection of clinically actionable gene amplifications. CONCLUSIONS: There is a lack of consensus in the molecular diagnostics field on the best method for the validation of NGS-based assays in oncology, thus the importance of communicating methods, as contained in this report. The growing number of targeted therapeutics and the complexity of the tumor genome necessitate continued development and refinement of advanced assays for tumor profiling to enable precision cancer treatment.

The Comparative Toxicogenomics Database: update 2011.

The Comparative Toxicogenomics Database (CTD) is a public resource that promotes understanding about the interaction of environmental chemicals with gene products, and their effects on human health. Biocurators at CTD manually curate a triad of chemical-gene, chemical-disease and gene-disease relationships from the literature. These core data are then integrated to construct chemical-gene-disease networks and to predict many novel relationships using different types of associated data. Since 2009, we dramatically increased the content of CTD to 1.4 million chemical-gene-disease data points and added many features, statistical analyses and analytical tools, including GeneComps and ChemComps (to find comparable genes and chemicals that share toxicogenomic profiles), enriched Gene Ontology terms associated with chemicals, statistically ranked chemical-disease inferences, Venn diagram tools to discover overlapping and unique attributes of any set of chemicals, genes or disease, and enhanced gene pathway data content, among other features. Together, this wealth of expanded chemical-gene-disease data continues to help users generate testable hypotheses about the molecular mechanisms of environmental diseases. CTD is freely available at http://ctd.mdibl.org.

Building resilience in children of mothers who have co-occurring disorders and histories of violence: intervention model and implementation issues.

Historically, children of parents with co-occurring substance abuse and mental health disorders and histories of violence/trauma have been overlooked in behavioral health treatment systems. The Women, Co-occurring Disorders and Violence Study (WCDVS) was a 5-year initiative funded by the United States Substance Abuse and Mental Health Services Administration (SAMHSA) that included a Children's Study that explored the treatment needs of children of women with these multiple disorders. This article describes the development of the Children's Study intervention that included clinical assessment, group intervention, and resource coordination/advocacy for children aged 5-10 to build resilience through increasing coping skills, improving interpersonal relationships, and helping coalesce positive identity and self-esteem. Innovative procedures, including the participation of consumer/survivor/recovering women and mothers, in the planning, implementation, and administrative applications of this intervention and study are also highlighted. It is recommended that programs begin to implement family-focused integrated treatment approaches that can potentially increase protective factors for children affected by parental mental illness, substance abuse, and violence.

Mechanism of SNARE protein binding and regulation of Cav2 channels by phosphorylation of the synaptic protein interaction site.

Ca(v)2.1 and Ca(v)2.2 channels conduct P/Q-type and N-type Ca(2+) currents that initiate neurotransmission and bind SNARE proteins through a synaptic protein interaction (synprint) site. PKC and CaMKII phosphorylate the synprint site and inhibit SNARE protein binding in vitro. Here we identify two separate microdomains that each bind syntaxin 1A and SNAP-25 in vitro and are regulated by PKC phosphorylation at serines 774 and 898 and CaMKII phosphorylation at serines 784 and 896. Activation of PKC resulted in its recruitment to and phosphorylation of Ca(V)2.2 channels, but PKC phosphorylation did not dissociate Ca(V)2.2 channel/syntaxin 1A complexes. Chimeric Ca(V)2.1a channels containing the synprint site of Ca(v)2.2 gain modulation by syntaxin 1A, which is blocked by PKC phosphorylation at the sites identified above. Our results support a bipartite model for the synprint site in which each SNARE-binding microdomain is controlled by a separate PKC and CaMKII phosphorylation site that regulates channel modulation by SNARE proteins.