Cancer develops as cells accumulate genetic and molecular changes that alter how they grow, divide and interact with surrounding tissues. In prostate cancer, researchers have identified many changes in DNA that contribute to tumor development and progression. However, less is known about genetic differences that can be detected in the RNA molecules actually being produced by prostate cancer cells.

Researchers at the University of Illinois Chicago investigated these RNA-level differences in primary human prostate cancer cells, with a particular focus on cancer stem cells.

The researchers used both bulk RNA sequencing and single-cell RNA sequencing to identify what they call transcriptional alleles. These are sequence variations detected in RNA transcripts that can provide information about which genetic variants are being actively expressed by cells.

Schematic overview of the computational pipeline for identifying variant calls by RNA-seq and strategy for verification of cancer-associated alleles

(a) Raw sequencing reads from bulk RNA-seq and single-cell RNA-seq were aligned to the human reference genome (hg38) using STAR. Variants were called from aligned BAM files and annotated with ANNOVAR to determine genomic location, predicted functional consequences, and deleteriousness (SIFT score for non-synonymous variants). (b) Variant calls from prostate cancer cells were compared directly with matched benign epithelial cells derived from non-malignant regions from the same patient. Only alleles uniquely detected in cancer samples were retained for downstream analyses, as described.

Comparing cancer cells with normal prostate cells

One strength of the research was its use of matched samples. The investigators compared prostate cancer cells with benign epithelial cells collected from noncancerous areas of the same patients.

This approach helps researchers distinguish changes associated with cancer from normal genetic differences between individuals. Because the cancer and benign cells came from the same person, many inherited genetic differences are shared between the two samples.

RNA sequencing reads from the cells were aligned to the human reference genome, and sequence differences were identified and classified. Most of the detected transcriptional alleles occurred in noncoding regions of RNA, particularly the 3′ and 5′ untranslated regions. These regions do not directly encode proteins, but they can influence RNA stability, localization and regulation.

Single-nucleotide variants, changes involving a single nucleotide, were the most common type of alteration. Among these, changes from cytosine to thymine, known as C>T substitutions, occurred most frequently.

Identifying cancer-associated transcriptional alleles

When the researchers compared cancer cells with matched benign cells from three patients, they identified 223 genes containing cancer-associated transcriptional alleles that were consistently detected across all three individuals.

Some of these changes could potentially affect how proteins function. Nineteen genes contained nonsynonymous alleles, meaning that the sequence variation could change an amino acid in the protein encoded by the gene. Eleven of these alterations were predicted to have potentially damaging effects.

Two genes, ATF6 and KDM3A, emerged as candidates of particular interest.

ATF6 is involved in the cellular response to stress within the endoplasmic reticulum, the structure responsible for processing many newly produced proteins. KDM3A encodes an enzyme involved in regulating gene activity through modifications to proteins associated with DNA. The findings identify both genes as candidates for additional experiments rather than establishing that either alteration directly causes prostate cancer.

Looking specifically at cancer stem cells

The researchers were also interested in cancer stem cells, or CSCs. These are subpopulations of tumor cells with stem-like characteristics, including the ability to renew themselves and generate other types of cancer cells.

Cancer stem cells are important to investigate because they may contribute to tumor growth, treatment resistance and cancer recurrence.

The researchers compared cancer stem cell populations with non-stem cancer cells and identified seven genes that both carried cancer-associated transcriptional alleles and showed differences in gene expression between these populations.

This suggests that examining genetic variation and gene expression together may reveal molecular differences that would be difficult to detect using either type of information alone.

Single-cell RNA sequencing reveals cellular differences

Single-cell RNA sequencing allowed the researchers to examine transcriptional alleles at the level of individual cells rather than averaging the signals from a large population.

The analysis showed that the number and distribution of detected transcriptional alleles varied depending on how the prostate cancer cells were grown.

Cells grown in conventional two-dimensional cultures had more total transcriptional alleles, more alleles in protein-coding regions and more nonsynonymous alleles than cells grown as three-dimensional spheroids enriched for cancer stem cells.

Cancer stem cell populations also contained fewer detected transcriptional alleles than non-cancer stem cell populations.

These differences demonstrate that the transcriptional allele landscape is not necessarily uniform throughout a tumor cell population. Different cellular states and growth conditions can produce different patterns of detectable RNA variants.

Understanding heterogeneity within prostate cancer

Tumors contain mixtures of cells that can differ genetically and biologically. This heterogeneity is one reason cancer can be difficult to characterize and treat.

Combining bulk and single-cell RNA sequencing provides researchers with different views of that complexity. Bulk RNA sequencing can identify recurring changes across a larger cell population, while single-cell RNA sequencing can show how those changes are distributed among individual cells and cellular subpopulations.

By comparing cancer cells directly with matched benign cells and examining cancer stem cells separately from other tumor cells, the researchers created a framework for investigating transcriptional allele heterogeneity within prostate cancer.

Further functional experiments will be needed to determine whether candidate alterations such as those associated with ATF6 and KDM3A contribute directly to cancer stem cell behavior or prostate cancer progression.