EARS2 significantly coexpresses with PALB2 in breast and pancreatic cancer

Reliable RNA-seq analysis from FFPE specimens as a means to accelerate cancer-related health disparities research

Whole transcriptome sequencing (WTS/ RNA-Seq) is a ubiquitous tool for investigating cancer biology. RNA isolated from frozen sources limits possible studies for analysis of associations with phenotypes or clinical variables requiring long-term follow-up. Although good correlations are reported in RNA-Seq data from paired frozen and formalin fixed paraffin embedded (FFPE) samples, uncertainties regarding RNA quality, methods of extraction, and data reliability are hurdles to utilization of archival samples. We compared three different platforms for performing RNA-seq using archival FFPE oropharyngeal squamous carcinoma (OPSCC) specimens stored up to 20 years, as part of an investigation of transcriptional profiles related to health disparities. We developed guidelines to purify DNA and RNA from FFPE tissue and perform downstream RNA-seq and DNA SNP arrays. RNA was extracted from 150 specimens, with an average yield of 401.8 ng/cm2 of tissue. Most samples yielded sufficient RNA reads >13,000 protein coding genes which could be used to differentiate HPV-associated from HPV-independent OPSCCs. Co-isolated DNA was used to identify reliably define patient ancestry which correlated well with patient-reported race. Utilizing the methods described in this study provides a robust, reliable, and standardized means of DNA & RNA extraction from FFPE as well as a means by which to assure the quality of the data generated. Optimized RNA extraction techniques, combined with robust bioinformatic approaches designed to optimize data homogenization, analysis and biological validation can revolutionize our ability to transcriptomically profile large solid tumor sets derived from ancestrally varied patient populations.

Identification of EARS2 as a Potential Biomarker with Diagnostic, Prognostic, and Therapeutic Implications in Colorectal Cancer

Purpose

Colorectal cancer (CRC) is a prevalent malignancy, and lactate metabolism significantly influences tumorigenesis and progression. This study identifies key genes associated with lactic acid metabolism and explore their impact on CRC.

Patients and Methods

This study utilized data from The Cancer Genome Atlas, Gene Expression Omnibus, other public databases, and our institutional resources. Machine learning identified key lactate metabolism-related genes. Receiver Operating Characteristic analysis, Kaplan-Meier analysis, and the construction of a nomogram model were conducted to assess the diagnostic and prognostic significance of the key lactate metabolism-related gene EARS2. EARS2 expression in colorectal tissue was validated using both publicly available external data and samples from our institution. To investigate the mechanisms underlying EARS2 in CRC, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Gene Set Enrichment Analysis, and Protein-Protein Interaction analyses were performed, alongside the construction of miRNA-mRNA interaction networks. Additionally, the relationships between EARS2 and immune cell infiltration, as well as responses to drug therapy, were examined. Following the knockdown of EARS2, we assessed cell proliferation, migration capabilities, and apoptosis. Statistical analyses were conducted using R and GraphPad Prism software.

Results

ERAS2 was overexpressed in CRC tissues compared to normal and adenoma tissues, with higher expression levels correlating with aberrant lactate metabolism and poorer patient prognosis. EARS2 was involved in pathways such as neuroactive ligand-receptor interactions, protein digestion, and cholesterol metabolism, and it was associated with immune cell infiltration and responses to drug treatment. Additionally, the knockdown of EARS2 inhibited the proliferation, migration, and invasion of CRC cells while enhancing their apoptosis.

Conclusion

Elevated expression of EARS2 is associated with abnormal lactate metabolism, immune cell infiltration, altered therapeutic sensitivity, and poorer survival outcomes in CRC. This correlation suggests that EARS2 may serve as a potential target for the diagnosis, prognosis, and therapeutic intervention in CRC.

A proteome-wide association study identifies putative causal proteins for breast cancer risk

BACKGROUND

Genome-wide association studies (GWAS) have identified more than 200 breast cancer risk-associated genetic loci, yet the causal genes and biological mechanisms for most loci remain elusive. Proteins, as final gene products, are pivotal in cellular function. In this study, we conducted a proteome-wide association study (PWAS) to identify proteins in breast tissue related to breast cancer risk.

METHODS

We profiled the proteome in fresh frozen breast tissue samples from 120 cancer-free European-ancestry women from the Susan G. Komen Tissue Bank (KTB). Protein expression levels were log2-transformed then normalized via quantile and inverse-rank transformations. GWAS data were also generated for these 120 samples. These data were used to build statistical models to predict protein expression levels via cis-genetic variants using the elastic net method. The prediction models were then applied to the GWAS summary statistics data of 133,384 breast cancer cases and 113,789 controls to assess the associations of genetically predicted protein expression levels with breast cancer risk overall and its subtypes using the S-PrediXcan method.

RESULTS

A total of 6388 proteins were detected in the normal breast tissue samples from 120 women with a high detection false discovery rate (FDR) p value < 0.01. Among the 5820 proteins detected in more than 80% of participants, prediction models were successfully built for 2060 proteins with R > 0.1 and P < 0.05. Among these 2060 proteins, five proteins were significantly associated with overall breast cancer risk at an FDR p value < 0.1. Among these five proteins, the corresponding genes for proteins COPG1, DCTN3, and DDX6 were located at least 1 Megabase away from the GWAS-identified breast cancer risk variants. COPG1 was associated with an increased risk of breast cancer with a p value of 8.54 × 10-4. Both DCTN3 and DDX6 were associated with a decreased risk of breast cancer with p values of 1.01 × 10-3 and 3.25 × 10-4, respectively. The corresponding genes for the remaining two proteins, LSP1 and DNAJA3, were located in previously GWAS-identified breast cancer risk loci. After adjusting for GWAS-identified risk variants, the association for DNAJA3 was still significant (p value of 9.15 × 10-5 and adjusted p value of 1.94 × 10-4). However, the significance for LSP1 became weaker with a p value of 0.62. Stratification analyses by breast cancer subtypes identified three proteins, SMARCC1, LSP1, and NCKAP1L, associated with luminal A, luminal B, and ER-positive breast cancer. NCKAP1L was located at least 1Mb away from the GWAS-identified breast cancer risk variants. After adjusting for GWAS-identified breast cancer risk variants, the association for protein LSP1 was still significant (adjusted p value of 6.43 × 10-3 for luminal B subtype).

CONCLUSION

We conducted the first breast-tissue-based PWAS and identified seven proteins associated with breast cancer, including five proteins not previously implicated. These findings help improve our understanding of the underlying genetic mechanism of breast cancer development.

Reliable RNA-seq analysis from FFPE specimens as a means to accelerate cancer-related health disparities research

Whole transcriptome sequencing (WTS/ RNA-Seq) is a ubiquitous tool for investigating cancer biology. RNA isolated from frozen sources limits possible studies for analysis of associations with phenotypes or clinical variables requiring long-term follow-up. Although good correlations are reported in RNA-Seq data from paired frozen and formalin fixed paraffin embedded (FFPE) samples, uncertainties regarding RNA quality, methods of extraction, and data reliability are hurdles to utilization of archival samples. We compared three different platforms for performing RNA-seq using archival FFPE oropharyngeal squamous carcinoma (OPSCC) specimens stored up to 20 years, as part of an investigation of transcriptional profiles related to health disparities. We developed guidelines to purify DNA and RNA from FFPE tissue and perform downstream RNA-seq and DNA SNP arrays. RNA was extracted from 150 specimens, with an average yield of 401.8 ng/cm 2 of tissue. Most samples yielded sufficient RNA reads >13,000 protein coding genes which could be used to differentiate HPV-associated from HPV-independent OPSCCs. Co-isolated DNA was used to identify patient ancestry. Utilizing the methods described in this study provides a robust, reliable, and standardized means of DNA & RNA extraction from FFPE as well as a means by which to assure the quality of the data generated.

Proteomic-based stratification of intermediate-risk prostate cancer patients

Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in the Gleason grade group (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or overtreatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B, and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomize prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.

DARS2 promotes the occurrence of lung adenocarcinoma via the ERK/c-Myc signaling pathway

BACKGROUND

DARS2 expression is upregulated in lung adenocarcinoma (LUAD) which correlates with tumor patient stage and prognosis. The mechanism of DARS2 involvement in LUAD still needs to be further explored.

METHODS

In this study, we found that DARS2 expression in LUAD tissue was significantly higher than that in normal tissue. At the same time, the Kaplan-Meier curve showed that the survival prognosis of LUAD patients with high expression of DARS2 was significantly worse than low expression of DARS2. The expression of DARS2 was detected in LUAD and adjacent normal tissues by IHC staining, histochemical scoring and a survival curve was generated. In addition, we demonstrated that the knockdown and overexpression of DARS2 significantly affected the proliferation, invasion, and migration of LUAD cells in vitro and in vivo. Finally, western blot and rescue assay were performed on LUAD cells to further explore and verify the signaling pathway.

RESULTS

DARS2 expression was significantly upregulated in LUAD tissues and cell lines. What is more, the increased expression of DARS2 was closely related to proliferation, invasion and metastasis. The tumorigenic assay in nude mice further showed that the tumorigenic ability of nude mice was significantly improved with the increase in DARS2 expression. Finally, we determined that DARS2 plays its role in LUAD by targeting the ERK/c-Myc signaling pathway.

CONCLUSION

Our data revealed the oncogenic role of DARS2 in LUAD, indicating that DARS2 may be a predictive biomarker and novel therapeutic target for LUAD.