Transcriptional Heterogeneity in Thousands of Tumors

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Summary

The complex mosaic of cellular states within each tumor, central to the concept of intra-tumor heterogeneity (ITH), presents a formidable challenge in oncology. Numerous studies, using single-cell RNA sequencing, have embarked on the journey to decipher ITH, yet their analysis is often confined to a narrow tumor segment. This scholarly contribution assimilates, contextualizes, and unifies data from 77 unique studies, illuminating transcriptional ITH patterns across an impressive 1163 tumor samples spanning 24 cancer categories. They pinpoint 41 consensus meta-programs (MPs) within malignancies, conglomerates of genes showing coordinated upregulation across various tumors. Intriguingly, these malignant MPs bear resemblance to non-neoplastic epithelial cells, hinting at the potential mutability of a significant swathe of malignant ITH pre-tumorigenesis. This exploration extends into six prevalent non-malignant cell types, mapping intercellular relationships within the tumor microenvironment. An exhaustive pancreatic cancer scRNA-seq dataset is also compiled and employed to systematically profile transcriptional ITH.

Research Criteria

The intellectual impetus behind this scholarly exposition rested upon the meticulous deciphering of transcriptional intra-tumor heterogeneity (ITH) patterns, achieved through a comprehensive and varied compendium of single-cell RNA sequencing (scRNA-seq) datasets derived from a multitude of cancer classifications.

Fig.1 Experimental design. (Gavish, 2023)

Sample Type

scRNA-seq data from 77 different studies, and 24 different tumor types.

Result—Defining and Annotating MPs

The study astutely exploits 3CA to dissect ITH within malignant cells. Circumventing the data amalgamation hurdles posed by disparate methodologies, it draws the lens to individual tumor variability, thereby defining expression programs within each neoplasm without dataset integration. Non-negative matrix factorization (NMF) was employed to discern ITH programs exhibiting variation among malignant cells within each tumor, unearthing 5,547 resilient malignant NMF programs. Further analysis revealed recurring ITH patterns by aggregating the robust NMF programs based on gene commonalities, creating 41 clusters. These embodied 66% of all robust NMF programs, implying a majority of ITH mirrors recurrent patterns encapsulated by malignant programs (MPs). The researchers further annotated MPs via functional enrichments, coalescing related functions into 11 MP clusters. A handful of MPs mirrored known ITH patterns, while others presented as novel, attesting to the method's sensitivity in identifying recurrent ITH programs within an extensive, diverse dataset.

Fig.2 MPs and their functional annotations. (Gavish, 2023)

Result—MPs of Non-malignant TME Cell Types

Through an exhaustive exploration of 1,199,312 non-neoplastic cells spanning 38 tumor microenvironment (TME) cell types, the investigation meticulously delineated and annotated malignant programs (MPs) within the six preeminent cell types. Intriguingly, the bulk of malignant MPs bore striking resemblance to non-neoplastic epithelial MPs, suggesting that the heterogeneity discerned within malignant cells could be innately encoded in their progenitor cells. Notwithstanding these similarities, there were discernible disparities between malignant and non-neoplastic epithelial MPs, highlighting cancer-specific idiosyncrasies. Some of these variances mirrored context-specific associations between cognate pathways. For instance, in malignant cells, processes of differentiation and secretion, which are typically disparate in non-neoplastic cells, were found to be interlinked, hinting at a potential aberrant senescence response.

Fig.3 Non-malignant MPs and their resemblance to malignant MPs. (Gavish, 2023)

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At Creative Biolabs, we acknowledge the prevalent phenomena of cellular asynchrony and heterogeneity. To address this intricacy, we utilize single-cell RNA sequencing methodologies, unraveling transcriptomic diversity within heterogeneous biological samples. Our meticulous approach comprises sample processing, library construction, and nuanced data interpretation, enhancing our project's adaptability, rapidity, and accuracy. Our steadfast commitment guarantees the highest echelon of outcomes delivered via our services.

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Reference

1. Gavish, A.; et al. Hallmarks of transcriptional intratumor heterogeneity across a thousand tumors. Nature. 2023, 618(7965): 598-606.