Lipidomic Profiling Reveals Biological Differences between Tumors of Self-Identified African Americans and Non-Hispanic Whites with Cancer

In the US, the incidence and mortality of many cancers are disproportionately higher in African Americans (AA). Yet, AA remain poorly represented in molecular studies investigating the roles that biological factors might play in the development, progression, and outcomes of many cancers. Given that sphingolipids, key components of mammalian cellular membranes, have well-established roles in the etiology of cancer progression, malignancy, and responses to therapy, we conducted a robust mass spectrometry analysis of sphingolipids in normal adjacent uninvolved tissues and tumors of self-identified AA and non-Hispanic White (NHW) males with cancers of the lung, colon, liver, and head and neck and of self-identified AA and NHW females with endometrial cancer. In these cancers, AA have worse outcomes than NHW. The goal of our study was to identify biological candidates to be evaluated in future preclinical studies targeting race-specific alterations in the cancers of AA. We have identified that various sphingolipids are altered in race-specific patterns, but more importantly, the ratios of 24- to 16-carbon fatty acyl chain-length ceramides and glucosylceramides are higher in the tumors of AA. As there is evidence that ceramides with 24-carbon fatty acid chain length promote cellular survival and proliferation, whereas 16-carbon chain length promote apoptosis, these results provide important support for future studies tailored to evaluate the potential roles these differences may play in the outcomes of AA with cancer.

Spatial Transcriptomic Analysis of a Diverse Patient Cohort Reveals a Conserved Architecture in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is an aggressive disease that disproportionately affects African American (AA) women. Limited targeted therapeutic options exist for patients with TNBC. Here, we employ spatial transcriptomics to interrogate tissue from a racially diverse TNBC cohort to comprehensively annotate the transcriptional states of spatially resolved cellular populations. A total of 38,706 spatial features from a cohort of 28 sections from 14 patients were analyzed. Intratumoral analysis of spatial features from individual sections revealed heterogeneous transcriptional substructures. However, integrated analysis of all samples resulted in nine transcriptionally distinct clusters that mapped across all individual sections. Furthermore, novel use of join count analysis demonstrated nonrandom directional spatial dependencies of the transcriptionally defined shared clusters, supporting a conserved spatio-transcriptional architecture in TNBC. These findings were substantiated in an independent validation cohort comprising 17,861 spatial features representing 15 samples from 8 patients. Stratification of samples by race revealed race-associated differences in hypoxic tumor content and regions of immune-rich infiltrate. Overall, this study combined spatial and functional molecular analyses to define the tumor architecture of TNBC, with potential implications in understanding TNBC disparities.

SIGNIFICANCE

Spatial transcriptomics profiling of a diverse cohort of triple-negative breast cancers and innovative informatics approaches reveal a conserved cellular architecture across cancers and identify proportional differences in tumor cell composition by race.

Abstract 2032: Comprehensive spatial transcriptomic analysis of an integrated, diverse cohort reveals distinct molecular topographic patterns in triple negative breast cancer

Background: Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer that disproportionately affects African-American and black (AAB) women, who have higher rates of incidence and mortality. To understand this disparity, we must apply advanced molecular profiling to racially diverse cohorts. We propose the use of spatial transcriptomics to map whole transcriptome data to several thousand coordinates within tissue sections, for comprehensive and unbiased characterization of TNBC tumors and their microenvironment.

Methods: We applied the Visium Spatial Gene Expression method (10x Genomics) to 28 fresh frozen TNBC tissue sections obtained from 14 patients (7 AAB and 7 Non-Hispanic White). Sections were stained with H&E, and regions of tumor and stroma were annotated by a pathologist. The assay yielded whole transcriptome data from over 36,000 spatially-defined features, averaging 1,380 features per section. Expression data from each sample was normalized and subject to dimensionality reduction and clustering analysis. All sections were also integrated into a single dataset, from which integrated clusters (IC) were defined. Several bioinformatics tools were used to annotate the data at the feature, cluster, and IC level. Join count statistical analysis was employed to quantify patterns of spatial aggregation or dispersion of ICs across samples.

Results: Clustering analysis revealed that all samples exhibited a great deal of heterogeneity; most contained several transcriptionally distinct regions of both tumor and stroma. Application of the ESTIMATE gene sets at the feature level accurately defined tumor and non-malignant regions when compared to histopathological annotation. Gene set enrichment analysis at the cluster level allowed further classification of biological processes within each sample. Following integration of all 28 samples, 9 ICs were defined from transcriptional data. Although all ICs were present in all samples, IC5 - characterized by a strong hypoxic signature - was overrepresented in AAB samples. ICs were then mapped back to individual samples and subject to join count statistics. This revealed strong spatial autocorrelation within each IC, as well as significant spatial pairings of ICs. The fibrotic clusters IC3 and IC7 were strongly contiguous in all samples (z-score > 5), as were tumor clusters IC1 and IC4. Conversely, we found spatial exclusion between IC3 and tumor clusters IC5 and IC2.

Conclusion: Our study provides novel evidence of spatially related populations across diverse TNBC samples. Our findings suggest that, while TNBC tumors are highly heterogeneous, they exhibit elements of a common spatio-transcriptional architecture. Moreover, this provides a new framework in which to evaluate transcriptional differences between racial groups within a broader spatial context.

Citation Format: Rania Bassiouni, Michael Idowu, Lee D. Gibbs, Pamela J. Grizzard, Michelle G. Webb, Ashley Noriega, Valentina Robila, David W. Craig, John D. Carpten. Comprehensive spatial transcriptomic analysis of an integrated, diverse cohort reveals distinct molecular topographic patterns in triple negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2032.

A simple method for sphingolipid analysis of tissues embedded in optimal cutting temperature compound

MS-assisted lipidomic tissue analysis is a valuable tool to assess sphingolipid metabolism dysfunction in disease. These analyses can reveal potential pharmacological targets or direct mechanistic studies to better understand the molecular underpinnings and influence of sphingolipid metabolism alterations on disease etiology. But procuring sufficient human tissues for adequately powered studies can be challenging. Therefore, biorepositories, which hold large collections of cryopreserved human tissues, are an ideal retrospective source of specimens. However, this resource has been vastly underutilized by lipid biologists, as the components of OCT compound used in cryopreservation are incompatible with MS analyses. Here, we report results indicating that OCT compound also interferes with protein quantification assays, and that the presence of OCT compound impacts the quantification of extracted sphingolipids by LC-ESI-MS/MS. We developed and validated a simple and inexpensive method that removes OCT compound from OCT compound-embedded tissues. Our results indicate that removal of OCT compound from cryopreserved tissues does not significantly affect the accuracy of sphingolipid measurements with LC-ESI-MS/MS. We used the validated method to analyze sphingolipid alterations in tumors compared with normal adjacent uninvolved lung tissues from individuals with lung cancer and to determine the long-term stability of sphingolipids in OCT compound-cryopreserved normal lung tissues. We show that lung cancer tumors have significantly altered sphingolipid profiles and that sphingolipids are stable for up to 16 years in OCT compound-cryopreserved normal lung tissues. This validated sphingolipidomic OCT compound-removal protocol should be a valuable addition to the lipid biologist's toolbox.