An omic and multidimensional spatial atlas from serial biopsies of an evolving metastatic breast cancer

Johnson, Brett; Creason, Allison; Stommel, Jayne M.; Keck, Jamie M.; Parmar, Swapnil; Betts, Courtney B.; Blucher, Aurora; Boniface, Christopher; Bucher, Elmar; Burlingame, Erik A.; Camp, Todd; Chin, Koei; Eng, Jennifer; Estabrook, Joseph; Feiler, Heidi S.; Heskett, Michael B.; Hu, Zhi; Kolodzie, Annette; Kong, Ben; Labrie, Marilyne; Lee, Jinho; Leyshock, Patrick; Mitri, Souraya; Riesterer, Jessica L.; Sivagnanam, Shamilene; Somers, Julia; Sudar, Damir; Thibault, Guillaume; Weeder, Benjamin R.; Zheng, Christina; Nan, Xiaolin; Thompson, Reid F.; Heiser, Laura M.; Spellman, Paul T.; Thomas, George V.; Demir, Emek; Chang, Young Hwan; Coussens, Lisa M.; Guimarães, Alexander R.; Corless, Christopher L.; Goecks, Jeremy; Bergan, Raymond C.; Mitri, Zahi; Mills, Gordon B.; Gray, Joe W.

doi:10.1016/j.xcrm.2022.100525

Cited by 32 publications

(18 citation statements)

References 130 publications

(205 reference statements)

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“…A recently published study by our lab found that a metastatic breast cancer patient had increased ctDNA levels while receiving palliative radiation therapy. Deep sequencing using a 53-mutation panel representative of both clonal and subclonal mutations, which were previously identified from WES of multiple tumors, revealed differential response in ctDNA levels for various subclones with sample collection every 48-hour during RT ( 104 ). Differential response in subclonal ctDNA abundance is suggestive of varying sensitivity in irradiated tumor cell subpopulations and/or an abscopal response.…”

Section: The Effect Of Treatment On Circulating Tumor Dna Abundancementioning

confidence: 99%

Blood, Toil, and Taxoteres: Biological Determinants of Treatment-Induced ctDNA Dynamics for Interpreting Tumor Response

Boniface¹,

Spellman²

2022

Pathol. Oncol. Res.

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Collection and analysis of circulating tumor DNA (ctDNA) is one of the few methods of liquid biopsy that measures generalizable and tumor specific molecules, and is one of the most promising approaches in assessing the effectiveness of cancer care. Clinical assays that utilize ctDNA are commercially available for the identification of actionable mutations prior to treatment and to assess minimal residual disease after treatment. There is currently no clinical ctDNA assay specifically intended to monitor disease response during treatment, partially due to the complex challenge of understanding the biological sources of ctDNA and the underlying principles that govern its release. Although studies have shown pre- and post-treatment ctDNA levels can be prognostic, there is evidence that early, on-treatment changes in ctDNA levels are more accurate in predicting response. Yet, these results also vary widely among cohorts, cancer type, and treatment, likely due to the driving biology of tumor cell proliferation, cell death, and ctDNA clearance kinetics. To realize the full potential of ctDNA monitoring in cancer care, we may need to reorient our thinking toward the fundamental biological underpinnings of ctDNA release and dissemination from merely seeking convenient clinical correlates.

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Section: The Effect Of Treatment On Circulating Tumor Dna Abundancementioning

confidence: 99%

Blood, Toil, and Taxoteres: Biological Determinants of Treatment-Induced ctDNA Dynamics for Interpreting Tumor Response

Boniface¹,

Spellman²

2022

Pathol. Oncol. Res.

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“…These protein z-scores were used for all downstream analysis. Protein pathway activity scores were developed using previously described predictors (Johnson et al 2022; Labrie et al 2019). Pathway scores were computed for each sample by taking the summation of each protein predictor in a defined pathway set, times their assigned weight (positive or negative), divided by the total number of predictors in that set ( Supplemental Table 3 ).…”

Section: Analysis Methodsmentioning

confidence: 99%

“…In previous work, we presented an omic and multidimensional spatial (OMS) atlas of a metastatic HR+ breast cancer patient treated with CDK4/6i and other therapies (Johnson et al 2022). That atlas was created by linking detailed, longitudinal clinical metadata to clinical and exploratory multiscale molecular data analyses from four serial biopsies.…”

Section: Introductionmentioning

confidence: 99%

“Longitudinal and multimodal auditing of tumor adaptation to CDK4/6 inhibitors in HR+ metastatic breast cancers”

Creason,

Egger,

Watson

et al. 2023

Preprint

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CDK4/6 inhibitors (CDK4/6i) have transformed the treatment of hormone receptor-positive (HR+), HER2-negative (HR+) breast cancers as they are effective across all clinicopathological, age, and ethnicity subgroups for metastatic HR+ breast cancer. In metastatic ER+ breast cancer, CDK4/6i lead to strong and consistent improvement in survival across different lines of therapy. To understand how metastatic HR+ breast cancers become refractory to CDK4/6i, we have created a multimodal and longitudinal tumor atlas to investigate therapeutic adaptations in malignant cells and in the tumor immune microenvironment. This atlas is part of the NCI Cancer Moonshot Human Tumor Atlas Network and includes seven pairs of pre- and on-progression biopsies from five metastatic HR+ breast cancer patients treated with CDK4/6i. Biopsies were profiled with bulk genomics, transcriptomics, and proteomics as well as single-cell ATAC-seq and multiplex tissue imaging for spatial, single-cell resolution. These molecular datasets were then linked with detailed clinical metadata to create an atlas for understanding tumor adaptations during therapy. Analysis of our atlas datasets revealed a diverse but tractable set of tumor adaptations to CDK4/6i therapy. Malignant cells adapted to therapy via mTORC1 activation, cell cycle bypass, and increased replication stress. The tumor immune microenvironment displayed evidence of both immune activation and immune suppression, including increased PD-1 expression, features of T cell dysfunction, and CD163+macrophage infiltration. Together, our metastatic ER+ breast cancer atlas represents a rich multimodal resource to understand tumor therapeutic adaptations to CDK4/6i therapy.

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“…Network analysis has provided a platform for the discovery of disease mechanisms, like the identification of causal genes and pathways in disease pathogenesis [27][28][29]. Diseasespecific network modules have been used to predict clinically relevant phenotypes, like metastasis in breast cancer tumors [30] or to detect signatures of tumor evolution in response to therapy [31].…”

Section: Modern Omics Technologies and The Interpretation Of Their Re...mentioning

confidence: 99%

A framework for considering prior information in network‐based approaches to omics data analysis

Somers,

Fenner,

Kong

et al. 2023

Proteomics

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For decades, molecular biologists have been uncovering the mechanics of biological systems. Efforts to bring their findings together have led to the development of multiple databases and information systems that capture and present pathway information in a computable network format. Concurrently, the advent of modern omics technologies has empowered researchers to systematically profile cellular processes across different modalities. Numerous algorithms, methodologies, and tools have been developed to use prior knowledge networks (PKNs) in the analysis of omics datasets. Interestingly, it has been repeatedly demonstrated that the source of prior knowledge can greatly impact the results of a given analysis. For these methods to be successful it is paramount that their selection of PKNs is amenable to the data type and the computational task they aim to accomplish. Here we present a five‐level framework that broadly describes network models in terms of their scope, level of detail, and ability to inform causal predictions. To contextualize this framework, we review a handful of network‐based omics analysis methods at each level, while also describing the computational tasks they aim to accomplish.

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An omic and multidimensional spatial atlas from serial biopsies of an evolving metastatic breast cancer

Cited by 32 publications

References 130 publications

Blood, Toil, and Taxoteres: Biological Determinants of Treatment-Induced ctDNA Dynamics for Interpreting Tumor Response

Blood, Toil, and Taxoteres: Biological Determinants of Treatment-Induced ctDNA Dynamics for Interpreting Tumor Response

“Longitudinal and multimodal auditing of tumor adaptation to CDK4/6 inhibitors in HR+ metastatic breast cancers”

A framework for considering prior information in network‐based approaches to omics data analysis

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