Non-genetic intra-tumor heterogeneity is a major predictor of phenotypic heterogeneity and ongoing evolutionary dynamics in lung tumors

Sharma, Anchal; Merritt, Elise; Cruz, Angelique; Jiang, Chuan; Sarkodie, Halle; Zhou, Zhan; Malhotra, Jyoti; Riedlinger, Gregory; De, Subhajyoti

doi:10.1101/698845

Cited by 18 publications

(20 citation statements)

References 54 publications

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“…Such plasticity during metastasis can lead to phenotypic (non-genetic) heterogeneity, as witnessed in circulating tumour cells (CTCs) across cancer types (Bocci et al, 2021;Yu et al, 2013). Consistent with observed impact of plasticity on evolvability of cellular traits (Fierst, 2011), non-genetic heterogeneity has been identified to impact evolutionary dynamics in lung cancer beyond genetic heterogeneity as well (Sharma et al, 2019).…”

Section: Are Mutations Necessary For Cancer Progression?mentioning

confidence: 81%

Cancer: More Than a Geneticist’s Pandora’s Box

Saxena¹,

Subbalakshmi²,

Kulkarni³

et al. 2021

Preprint

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Despite identical genetic constitution, a cancer cell population can exhibit phenotypic variations termed as non-genetic/non-mutational heterogeneity. Such heterogeneity – a ubiquitous nature of biological systems – has been implicated in metastasis, therapy resistance and tumour relapse. Here, we review the evidence for existence, sources and implications of non-genetic heterogeneity in multiple cancer types. Stochasticity/ noise in transcription, protein conformation and/or external microenvironment can underlie such heterogeneity. Moreover, the existence of multiple possible cell states (phenotypes) as a consequence of the emergent dynamics of gene regulatory networks may enable reversible cell-state transitions (phenotypic plasticity) that can facilitate adaptive drug resistance and higher metastatic fitness. Finally, we highlight how computational and mathematical models can drive a better understanding of non-genetic heterogeneity and how a systems-level approach integrating mathematical modelling and in vitro/in vivo experiments can map the diverse phenotypic repertoire, and identify therapeutic vulnerabilities of an otherwise clonal cell population.

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Section: Are Mutations Necessary For Cancer Progression?mentioning

confidence: 81%

Cancer: More Than a Geneticist’s Pandora’s Box

Saxena¹,

Subbalakshmi²,

Kulkarni³

et al. 2021

Preprint

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“…have not yet demonstrated disease-associated PRSS3 variants (https://www.nextprot.org/entry/NX_P35030/medical). Alternative splicing forms dynamic interactome offering precise therapeutic approaches to correcting cancer-speci c defects caused by mis-splicing regulation, in which epigenetics plays an essential role [9,11,12,49,[52][53][54]. Our previously study showed epigenetic silencing of PRSS3 in HCC [35], we reasoned epigenetic regulation of PRSS3-SVs contributing to non-genetic heterogeneity in HCC.…”

Section: Discussionmentioning

confidence: 99%

Epigenetic Dysregulation of the Expression of PRSS3 Splice Variants Increases the Heterogeneity of Transcripts and Functionality in Human Hepatocellular Carcinoma

Lin¹,

Xu²,

Pang³

et al. 2021

Preprint

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Background Hepatocellular carcinoma (HCC) is one of the most lethal human tumors with extensive heterogeneity. Serine protease 3 (PRSS3) is an indispensable member of the trypsin family and has been implicated in the pathogenesis of several malignancies including HCC. However, paradoxical effects of PPRSS3 on carcinogenesis impede the utilization of its biomarker potential. We hereby systematically dissected the expression of four known splice variants of PRSS3 (PRSS3-SVs) and their functional relevance to HCC. Methods The expression and DNA methylation of PRSS3 transcripts and their associated clinical relevance in HCC were analyzed using several publicly available datasets and were validated using qPCR-based assays. Functional assays were performed on gain- and loss-of-function cell models, in which PRSS3 transcript constructs were separately transfected after PRSS3 expression was knocked out by CRISPR-Cas9 editing. Results PRSS3 expression was differentially decreased in HCC cell lines and tissues attributable to aberrant expression of PRSS3-SVs towards bipolarity, in which PRSS3-V2 and then -V1 were dominantly expressed whereas PRSS3-V3 and -V4 were rarely or minimally expressed. The expression of PRSS3-V2 or -V1 was reversely associated with site-specific CpG methylation and was distinct between lowly-expressed PRSS3-SVs with hypermethylation (mPRSS3Low) and highly-expressed PRSS3-SVs with hypomethylation (umPRSS3High). Function analysis revealed that PRSS3-V2 exhibited oncogenic functions distinct from a tumor-suppressive role of ectopic PRSS3-V1 or -V3, or PRSS3-V4 with inhibitory effects in PRSS3 knockout HCC cells. Clinically, aberrant expression of PRSS3-SVs was translated into divergent relevance in patients with HCC, in which significant epigenetic downregulation of PRSS3-V2 was seen in early HCC and was associated with favorable patient outcome. Conclusions Aberrant expression of divergent PRSS3-SVs disrupted by CpG methylation may integrate the effects of oncogenic PRSS3-V2 and tumor-suppressive PRSS3-V1, resulting in the molecular diversity and functional plasticity of HCC. Dysregulated expression of PRSS3-V2 by site-specific CpG methylation may have potential diagnostic value for patients with early HCC.

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“…While genomic heterogeneity in tumors has been extensively studied, quantifying non-genetic (i.e. phenotypic) heterogeneity has been possible only recently through investigating cell-tocell variability in isogenic populations [40][41][42][43]. Higher phenotypic heterogeneity may encourage cancer invasion [44] as well as the evolution of therapy resistance [45].…”

Section: Discussionmentioning

confidence: 99%

Gene expression profiles of inflammatory breast cancer reveal high heterogeneity across the epithelial-hybrid-mesenchymal spectrum

Chakraborty

George

Woodward

et al. 2020

Preprint

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Inflammatory breast cancer (IBC) is a highly aggressive breast cancer that metastasizes largely via tumor emboli, and has a 5-year survival rate of less than 30%. No unique genomic signature has yet been identified for IBC nor has any specific molecular therapeutic been developed to manage the disease. Thus, identifying gene expression signatures specific to IBC remains crucial. Here, we compare various gene lists that have been proposed as molecular footprints of IBC using different clinical samples as training and validation sets and using independent training algorithms, and determine their accuracy in identifying IBC samples in three independent datasets. We show that these gene lists have little to no mutual overlap, and have limited predictive accuracy in identifying IBC samples. Despite this inconsistency, single-sample gene set enrichment analysis (ssGSEA) of IBC samples correlate with their position on the epithelial-hybrid-mesenchymal spectrum. This positioning, together with ssGSEA scores, improves the accuracy of IBC identification across the three independent datasets. Finally, we observed that IBC samples robustly displayed a higher coefficient of variation in terms of EMT scores, as compared to non-IBC samples. Pending verification that this patient-to-patient variability extends to intratumor heterogeneity within a single patient, these results suggest that higher heterogeneity along the epithelial-hybrid-mesenchymal spectrum can be regarded to be a hallmark of IBC and a possibly useful biomarker.

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Non-genetic intra-tumor heterogeneity is a major predictor of phenotypic heterogeneity and ongoing evolutionary dynamics in lung tumors

Cited by 18 publications

References 54 publications

Cancer: More Than a Geneticist’s Pandora’s Box

Cancer: More Than a Geneticist’s Pandora’s Box

Epigenetic Dysregulation of the Expression of PRSS3 Splice Variants Increases the Heterogeneity of Transcripts and Functionality in Human Hepatocellular Carcinoma

Gene expression profiles of inflammatory breast cancer reveal high heterogeneity across the epithelial-hybrid-mesenchymal spectrum

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