ARTICLE | doi:10.20944/preprints202202.0133.v1
Subject: Biology, Other Keywords: Intratumoral heterogeneity; Triple negative breast cancer (TNBC); Macc1; Phenotypic heteroge-neity
Online: 9 February 2022 (10:40:54 CET)
The triple-negative breast cancer (TNBC) subtype is one of the most aggressive forms of breast cancer that has poor clinical outcome and still remains as an unmet clinical challenge. Accumulating evidence suggests that intratumoral heterogeneity or the presence of phenotypically heterogeneous cell populations within a tumor plays a crucial role in chemoresistance, tumor progression and metastasis. Increased understanding of the molecular regulators of intratumoral heterogeneity will enable the development of effective therapeutic strategies in TNBC. We have identified a molecular mediator involved in intratumoral heterogeneity in breast cancer using an unbiased approach. We isolated two heterogeneous tumor cell populations from the 4T1 TNBC tumor model and phenotypic characterization revealed that the cells are distinct in terms of their morphology, proliferation and self-renewal ability in vitro; as well as primary tumor formation and metastatic potential in vivo. Further, RNA sequencing on both cell populations was performed to identify the molecular mediators underlying this heterogeneity. Bioinformatic analysis performed on the differentially expressed genes along with the Kaplan-Meier survival analysis in TNBC patients identified Metastasis associated colon cancer 1 (Macc1) as the top candidate gene mediating the aggressive phenotype. The role of Macc1 in regulating the proliferative phenotype was validated using siRNA mediated gene knockdown. The role of Macc1 in the aggressive cancer cell phenotypes and disease progression is being studied further using a small molecule transcriptional inhibitor of Macc1 in cell line and animal models, thus increasing our understanding of the molecular underpinnings of intratumoral heterogeneity in breast cancer that is critical to the improvement in the treatment of women currently living with the highly aggressive TNBC subtype.
REVIEW | doi:10.20944/preprints202202.0004.v1
Subject: Life Sciences, Biotechnology Keywords: Spatial transcriptomics; Molecular imaging; single-cell RNA-seq; intratumoral heterogeneity
Online: 1 February 2022 (11:08:51 CET)
Intratumoral heterogeneity associates with more aggressive disease progression and worse patient outcomes. Understanding the reasons enabling the emergence of such heterogeneity remains incomplete, which restricts our ability to manage it from a therapeutic perspective. Technological advancements such as high-throughput molecular imaging, single-cell omics and spatial transcriptomics now allow recording the patterns of spatiotemporal heterogeneity in a longitudinal manner, thus offering insights into the multi-scale dynamics of its evolution. Here, we review latest technological trends and biological insights from molecular diagnostics as well as spatial transcriptomics, both of which have witnessed a burgeoning growth in recent past in terms of mapping heterogeneity within tumor cell types as well as stromal constitution. We also discuss ongoing challenges, indicating possible ways to integrate insights across these methods to have a systems-level spatiotemporal map of heterogeneity in each tumor, and a more systematic investigation of implications of heterogeneity for the patient outcomes.
ARTICLE | doi:10.20944/preprints202205.0201.v1
Subject: Medicine & Pharmacology, Oncology & Oncogenics Keywords: cancer stem cells; colorectal cancer; label-free cell sorting; chemoresistance; intratumoral cellular heterogeneity
Online: 16 May 2022 (09:11:01 CEST)
Cancer stem cells play a crucial role in tumor initiation, metastasis and therapy resistance. Cellular heterogeneity and plasticity challenge the isolation of cancer stem cells. The impact of intratumoral cellular heterogeneity in the context of treatment resistance using a label-free approach remains understudied. Here, we use the sedimentation field-flow fractionation technique to separate, without labeling, cell subpopulations of colorectal cancer cell lines and primary cultures according to their biophysical properties. One of the three cell subpopulations sorted by SdFFF exhibits cancer stem cell traits, including high tumorigenicity in vivo, and a higher frequency of tumor-initiating cells compared to the other subpopulations. In vitro two- and three-dimensional chemosensitivity assays emphasize the therapeutic relevance of this cancer stem cell-like subpopulation due to its chemoresistance. Therefore, our findings highlight a label-free cell sorting approach to reveal intratumoral cellular heterogeneity and its implication in therapy resistance. This approach enables the study of the individualized response of each sorted cell subpopulation by breaking down the tumor, thus offering new perspectives for personalized therapy.
REVIEW | doi:10.20944/preprints202207.0031.v1
Subject: Life Sciences, Biophysics Keywords: Cell-state transitions; Phenotypic plasticity; Cancer Stem Cells; Intratumoral heterogeneity; Lamarckian Induction; Drug resistance
Online: 4 July 2022 (04:56:00 CEST)
Intratumoral heterogeneity can exist along multiple axes: Cancer Stem Cells (CSCs)/non-CSCs, drug-sensitive/drug-tolerant states and a spectrum of epithelial-hybrid-mesenchymal phenotypes. Further, these diverse cell-states can switch reversibly among one another, thereby posing a major challenge to therapeutic efficacy. Therefore, understanding the origins of phenotypic plasticity and heterogeneity remains an active area of investigation. While genomic components (mutations, chromosomal instability) driving heterogeneity have been well-studied, recent reports highlight the role of non-genetic mechanisms in enabling both phenotypic plasticity and heterogeneity. Here, we discuss various processes underlying phenotypic plasticity such as stochastic gene expression, chromatin reprogramming, asymmetric cell division and the presence of multiple “attractors”. These processes can facilitate a dynamically evolving cell population such that a subpopulation of (drug-tolerant) cells can survive lethal drug exposure and recapitulate population heterogeneity on drug withdrawal, leading to relapse. These drug-tolerant cells can be both pre-existing and also induced by the drug itself through cell-state reprogramming. The dynamics of cell-state transitions both in absence and presence of the drug can be quantified through mathematical models. Such a dynamical systems approach to elucidating patterns of intratumoral heterogeneity by integrating longitudinal experimental data with mathematical models can help design effective combinatorial and/or sequential therapies for better clinical outcomes.