Advancing Cancer Research: The Role of scRNA-seq in Unraveling Complexity and Driving Progress

Cancer remains one of the most challenging and biologically complex diseases of our time.

As remarkably complex organisms, humans are composed of a myriad of cells, tissues and organs, each cell representing an individual unit within a vast network of switches, with different genetic, transcriptional and cellular processes. These switches can be flipped in countless combinations, leading to the development, growth, propagation, and resilience of cancer.

Despite scientific and medical advancements, there are still significant gaps in our understanding of the complex biology of cancer, especially as cancer and the cells that make up tumors continue to evolve and develop resistance to therapies, leading to disease progression and metastasis.

Accelerated discovery of biomarkers applicable in the diagnosis, prognosis and response to therapies are crucial for the evolution and democratization of personalized cancer treatments.

To effectively navigate this network and identify key targets for intervention, researchers must employ high-throughput, high-resolution technologies.

Single cell RNA sequencing (scRNA-seq) allows scientists to analyze the gene expression of individual cancer cells, providing a detailed map of the cellular landscape within a tumor. By examining the unique genetic signatures of each cell, scRNA-seq generates a wealth of data that can disentangle the web of intra- and inter-cellular interactions. This detailed view reveals how different genetic profiles drive cancer progression and contribute to drug resistance, ultimately accelerating the identification of actionable biomarkers.

Given the diversity of scRNA-seq technologies, selecting the proper platform to help uncover the vast complexity of different cell types in a tumor is paramount, with plate-based, scalable approaches like Evercode™ being an obvious choice. Such a platform can efficiently sequence highly heterogeneous tissues without limitations related to cell size or sample size, making it ideal for analyzing complex biological samples.

With this powerful technology in their multi-omics toolbox, researchers are better equipped to tackle a wide range of cancers — from the most common to the rarest and deadliest.

A key feature of malignant cells is their ability to develop resistance to therapies through various signals that induce changes in gene expression and protein activity. Drug-resistant cancer cells survive and continue to grow despite treatment, leading to disease progression and/or metastasis.

Modern therapeutic approaches target the Hallmarks of Cancer by addressing multiple aspects of cell proliferation. These approaches include — but are not limited to — using target therapies, blocking signals that cause cancer cells to grow uncontrollably and thrive, preventing the formation of new blood vessels that supply nutrients to tumors.

Despite these advancements, it is estimated that 90% of cancer deaths are a consequence of drug resistance’ development. Drug resistance can be categorized as intrinsic or acquired.

Intrinsic resistance is present before treatment. It can result from pre-existing genetic mutations that render the cells less responsive, or from small clonal subset of cancer stem cells, programmed to escape treatment and later leading to relapse.

Acquired resistance develops after treatment and can be caused by the activation of new proto-oncogenes, mutations that alter drug response, or changes in the tumor microenvironment.

Drug resistance is associated with various mechanisms, including enhanced drug efflux, genetic factors, increased DNA repair capacity, and elevated metabolism of xenobiotics.

Understanding the complexity of drug resistance requires a technology like scRNA-seq that can delve into tissue heterogeneity and identify specific mechanisms contributing to resistance. Moreover, as the tumor microenvironment plays a critical role in harboring multidrug resistance (MDR), scRNA-seq can decipher the interactions between cells.

Recent studies have demonstrated the power of scRNA-seq in understanding drug resistance.

In this fascinating study from a team in Athens, in triple-negative breast cancer (TNBC), scRNA-seq detected low-abundance gene expression changes in drug-resistant cells that were not visible in bulk RNA sequencing. Notably, genes strongly upregulated in drug-resistant cells were already expressed in rare cell pools before treatment, suggesting the pre-existence of drug-resistant subpopulations.

In a study from Harvard, researchers applied a combination of spatial transcriptomics and combinatorial barcoding single-nuclei RNA sequencing to study how cell intrinsic properties and interactions with the tumor microenvironment modulate therapeutic response. The study revealed that treatment induced significant remodeling of the tumor microenvironment, altered interactions between cancer-associated fibroblasts and malignant cells, and enriched IL-6 family signaling in treated tumors.

These alterations may contribute to chemoresistance through mechanisms such as modified signaling pathways, shifts in cell populations, and alterations in the extracellular matrix.

Biomarkers play a crucial role in drug development and in cancer treatment and management. They can be DNA, RNA, proteins, or metabolites specific to the tumor.

Cancer researchers use them to identify cancer type or subtype, its occurrence or recurrence. In drug testing, biomarkers are used to select patients, predict therapeutic effectiveness and toxicity, and to measure the drug metabolism in the body.

While traditionally biomarkers have been identified using low-throughout laboratory techniques, scRNA-seq provides the ideal tool for high-throughput and yet focused discovery of new biomarkers.

Several deadly cancers do not have identifiable biomarkers.

Take lung cancer for example. It represents close to 50% of all cancers diagnosed each year in north America, and it has about 19% survival rate at 5 years as opposed to 55% at early stage, emphasizing the need for more early biomarkers driving diagnosis and therapy as the already known biomarkers informing targeted therapies in this cancer only modestly have improved overall survival.

ScRNA-seq has proven valuable in identifying potential biomarkers, as demonstrated in a Canadian study on lung cancer.

The analysis revealed elevated levels of the chemokines CXCL1 and CXCL2, along with the microRNA miR-532-5p that regulates their expression, during the early stages of lung cancer. These molecules emerged as promising candidates for early diagnostic biomarkers.

Additionally, increased expression of CXCR2 — the receptor for CXCL1 and CXCL2 — correlated with improved survival probability in late-stage patients.

This comprehensive work not only provides a framework for developing early-stage diagnostic tools but also contributes significantly to advancing precision medicine approaches for lung cancer treatment.

The NIH defines as “rare cancers” those affecting less than 40,000 people per year in the U.S. They account for 24% of all cancers and 25% of cancer deaths, which paradoxically makes them collectively a very large group, as underlined by this article in introducing the PLOS Collection on Rare Cancers. Despite their collective significance, rare cancers remain understudied due to challenges in obtaining clinical samples and lower funding compared to more common types.

Neuroblastoma is a rare childhood cancer driven by genomic rearrangements and chromosomal copy number alterations that arises in-uterus and leads to uncontrolled proliferation.

This study from an Austrian team used embryonic stem cells with neuroblastoma-associated chromosomal aberrations to model how these genetic changes impact neural crest development and potentially contribute to neuroblastoma initiation.

The study revealed that the overexpression of MYCN, a gene often amplified in neuroblastoma, exacerbated the differentiation defects when combined with the chromosomal aberrations.

Cells with the aberrations and MYCN overexpression acquired tumorigenic hallmarks like increased proliferation and could form tumors in xenografts.
The study suggests chromosomal aberrations may prime cells for transformation by disrupting normal differentiation, with MYCN amplification then triggering tumor initiation.

Providing insights into tumor initiation, and identifying potential therapeutic targets, this paper bridges basic developmental biology with cancer research potentially impacting how researchers approach treatment of this challenging pediatric cancer.

Despite rapid scientific advancements, cancer remains a major challenge due to its ability to evolve and resist therapies.

Continued innovation and collaboration are essential. ScRNA-seq is playing a vital role in revealing new complexities, offering insights into cancer stem cells, tumor environments, drug resistance, and biomarkers, leading to more targeted treatments.

The potential of scRNA-seq to uncover previously unseen layers of complexity in cancer underscores the importance of adopting such technologies to outpace the disease’s rapid evolution, stay one step ahead of cancer’s evolving nature, and ultimately improve outcomes for patients.