Background: High throughput parallel sequencing, RNA-Seq, has recently emerged as an appealing alternative to microarray in identifying differentially expressed genes (DEG) between biological groups. However, there still exists considerable discrepancy on gene expression measurements and DEG results between the two platforms. The objective of this study was to compare parallel paired-end RNA-Seq and microarray data generated on 5-azadeoxy-cytidine (5-Aza) treated HT-29 colon cancer cells with an additional simulation study.Methods: We first performed general correlation analysis comparing gene expression profiles on both platforms. An Errors-In-Variables (EIV) regression model was subsequently applied to assess proportional and fixed biases between the two technologies. Then several existing algorithms, designed for DEG identification in RNA-Seq and microarray data, were applied to compare the cross-platform overlaps with respect to DEG lists, which were further validated using qRT-PCR assays on selected genes. Functional analyses were subsequently conducted using Ingenuity Pathway Analysis (IPA).Results: Pearson and Spearman correlation coefficients between the RNA-Seq and microarray data each exceeded 0.80, with 66%~68% overlap of genes on both platforms. The EIV regression model indicated the existence of both fixed and proportional biases between the two platforms. The DESeq and baySeq algorithms (RNA-Seq) and the SAM and eBayes algorithms (microarray) achieved the highest cross-platform overlap rate in DEG results from both experimental and simulated datasets. DESeq method exhibited a better control on the false discovery rate than baySeq on the simulated dataset although it performed slightly inferior to baySeq in the sensitivity test. RNA-Seq and qRT-PCR, but not microarray data, confirmed the expected reversal ofSPARCgene suppression after treating HT-29 cells with 5-Aza. Thirty-three IPA canonical pathways were identified by both microarray and RNA-Seq data, 152 pathways by RNA-Seq data only, and none by microarray data only.Conclusions: These results suggest that RNA-Seq has advantages over microarray in identification of DEGs with the most consistent results generated from DESeq and SAM methods. The EIV regression model reveals both fixed and proportional biases between RNA-Seq and microarray. This may explain in part the lower cross-platform overlap in DEG lists compared to those in detectable genes.

Colorectal cancer (CRC) incidence and mortality are higher in African Americans (AAs) than in Caucasian Americans (CAs) and microRNAs (miRNAs) have been found to be dysregulated in colonic and other neoplasias. The aim of this exploratory study was to identify candidate miRNAs that could contribute to potential biological differences between AA and CA colon cancers. Total RNA was isolated from tumor and paired adjacent normal colon tissue from 30 AA and 31 CA colon cancer patients archived at Stony Brook University (SBU) and Washington University (WU)‑St. Louis Medical Center. miRNA profiles were determined by probing human genome-wide miRNA arrays with RNA isolated from each sample. Using repeated measures analysis of variance (RANOVA), miRNAs were selected that exhibited significant (p1.5, p<0.05) main effects of race and/or tumor. Quantitative polymerase chain reaction (q-PCR) was used to confirm miRNAs identified by microarray analysis. Candidate miRNA targets were analyzed using immunohistochemistry. RANOVA results indicated that miR-182, miR152, miR-204, miR-222 and miR-202 exhibited significant race and tumor main effects. Of these miRNAs, q-PCR analysis confirmed that miR-182 was upregulated in AA vs. CA tumors and exhibited significant race:tumor interaction. Immunohistochemical analysis revealed that the levels of FOXO1 and FOXO3A, two potential miR-182 targets, are reduced in AA tumors. miRNAs may play a role in the differences between AA and CA colon cancer. Specifically, differences in miRNA expression levels of miR-182 may contribute to decreased survival in AA colon cancer patients.

Background: Colorectal cancer is the third most deadly cancer among African Americans (AA). When compared to Caucasian Americans (CA), AA present with more advanced disease and lower survival rates. Here, we investigated if differences in tumor immunology could be contributive to disparities observed between these populations. Methods: We examined gene expression of tumor and non-tumor adjacent tissues from AA and CA by whole transcriptome sequencing, and generated scores for immune cell populations by NanoString. In addition, we utilized “The Cancer Genome Atlas” (TCGA) database from AA and CA as a validation cohort. Finally, we measured the secretion of cytokines characteristic of effector T helper cell (Th) subsets by ELISA using plasma from each AA and CA participant. Results: Colon tumors from AA patients showed significant fold-change increase in gene expression when compared to CA for FOXP3 (6.22 vs. 3.22), IL1B (103 vs. 11.4) and IL8 (220 vs. 28.9) (p < 0.05). In contrast, among CA we observed statistically higher gene expression of markers associated with antitumor activity such as GZMB (Granzyme B), IFNG and the immunotherapy targets PDL1 (CD274) and CTLA4 (p < 0.05). TCGA data validated our observed higher gene expression of GZMB and PDL1 in CA patients when compared to AA. Notably, our observations on immune cell populations show that AA tumors have significantly higher number of exhausted CD8+ cells (p < 0.01), mast cells (p < 0.02) and increased T regulatory cells when compared to CA. AA colon cancer patients differed from CA in cytokine production patterns in plasma (i.e. reduced IL-12). Conclusions: Our study demonstrates significant differences of the immunological profiles of colon tumors from AA compared to CA that suggest a deficiency of appropriate immune defense mechanisms in terms of gene expression, recruitment of immune cells and systemic secretion of cytokines. As such, these immune differences could be mitigated through population-specific therapeutic approaches.

Incidence and mortality rates of colorectal carcinoma (CRC) are higher in African Americans (AAs) than in Caucasian Americans (CAs). Deficient micronutrient intake due to dietary restrictions in racial/ethnic populations can alter genetic and molecular profiles leading to dysregulated methylation patterns and the inheritance of somatic to germline mutations. Total DNA and RNA samples of paired tumor and adjacent normal colon tissues were prepared from AA and CA CRC specimens. Reduced Representation Bisulfite Sequencing (RRBS) and RNA sequencing were employed to evaluate total genome methylation of 5’-regulatory regions and dysregulation of gene expression, respectively. Robust analysis was conducted using a trimming-and-retrieving scheme for RRBS library mapping in conjunction with the BStool toolkit. DNA from the tumor of AA CRC patients, compared to adjacent normal tissues, contained 1,588 hypermethylated and 100 hypomethylated differentially methylated regions (DMRs). Whereas, 109 hypermethylated and 4 hypomethylated DMRs were observed in DNA from the tumor of CA CRC patients; representing a 14.6-fold and 25-fold change, respectively. Specifically; CHL1, 4 anti-inflammatory genes (i.e., NELL1, GDF1, ARHGEF4, and ITGA4), and 7 miRNAs (of which miR-9-3p and miR-124-3p have been implicated in CRC) were hypermethylated in DNA samples from AA patients with CRC. From the same sample set, RNAseq analysis revealed 108 downregulated genes (including 14 ribosomal proteins) and 34 upregulated genes (including POLR2B and CYP1B1 [targets of miR-124-3p]) in AA patients with CRC versus CA patients. DNA methylation profile and/or products of its downstream targets could serve as biomarker(s) addressing racial health disparity.

Background: Non-Small Cell Lung Cancer (NSCLC), the leading cause of cancer-related death in the United States, is the most diagnosed form of lung cancer. While lung cancer incidence has steadily declined over the last decade, disparities in incidence and mortality rates persist among African American (AA), Caucasian American (CA), and Hispanic American (HA) populations. Researchers continue to explore how genetic ancestry may influence differential outcomes in lung cancer risk and development. The purpose of this evaluation is to highlight experimental research that investigates the differential impact of genetic mutations and ancestry on NSCLC incidence.Methods: This systematic review was conducted using PubMed and Google Scholar search engines. The following key search terms were used to select articles published between 2011 and 2022: “African/European/Latin American Ancestry NSCLC”; “Racial Disparities NSCLC”; “Genetic Mutations NSCLC”; “NSCLC Biomarkers”; “African Americans/Hispanic Americans/Caucasian Americans NSCLC incidence.” Systematic reviews, meta-analyses, and studies outside of the US were excluded. A total of 195 articles were initially identified and after excluding 156 which did not meet eligibility criteria, 38 were included in this investigation.Results: Studies included in this analysis focused on racial/ethnic disparities in the following common genetic mutations observed in NSCLC: KRAS, EGFR, TP53, PIK3CA, ALK Translocations, ROS-1 Rearrangements, STK11, MET, and BRAF. Results across studies varied with respect to absolute differential expression. No significant differences in frequencies of specific genetic mutational profiles were noted between racial/ethnic groups. However, for HAs, lower mutational frequencies in KRAS and STK11 genes were observed. In genetic ancestry level analyses, multiple studies suggest that African ancestry is associated with a higher frequency of EGFR mutations. Conversely, Latin ancestry is associated with TP53 mutations. At the genomic level, several novel predisposing variants associated with African ancestry and increased risk of NSCLC were discovered. Family history among all racial/ethnic groups was also considered a risk factor for NSCLC.Conclusion: Results from racially and ethnically diverse studies can elucidate driving factors that may increase susceptibility and subsequent lung cancer risk across different racial/ethnic groups. Identification of biomarkers that can be used as diagnostic, prognostic, and therapeutic tools may help improve lung cancer survival among high-risk populations.

Introduction: Colorectal cancer (CRC) is the third most commonly diagnosed cancer in the United States (U.S.). Mississippi has the highest rate of CRC incidence in the U.S. and has large populations of black and white individuals, allowing for studies of racial disparities. Methods: We conducted an ecological study using the county as the unit of analysis. CRC incidence data at the county level for black and white populations in Mississippi, covering the years 2003 to 2020, were retrieved from the Mississippi Cancer Registry. Age-adjusted incidence rate differences and their corresponding 95% confidence intervals (CIs) were then calculated for these groups. Getis–Ord Gi* hot and cold spot analysis of CRC incidence rate racial disparities was performed using ArcGIS Pro. We used global ordinary least square regression and geographically weighted regression (MGWR version 2.2) to identify factors associated with racial differences in CRC incidence rates. Results: Age-adjusted CRC incidence rate in the black population (median = 58.12/100,000 population) and in the white population (median = 46.44/100,000 population) varied by geographical area. Statistically significant racial differences in CRC incidence rates were identified in 28 counties, all of which showed higher incidence rates among the black population compared to the white population. No hot spots were detected, indicating that there were no spatial clusters of areas with pronounced racial disparities. As a post hoc analysis, after considering multicollinearity and a directed acyclic graph, a parsimonious multiple regression model showed an association (β = 0.93, 95% CI: 0.25, 1.62) indicating that a 1% increase in food insecurity was associated with a 0.93/100,000 differential increase in the black–white CRC incidence rate. Geographically weighted regression did not reveal any local patterns in this association. Conclusions: Black–white racial disparities in CRC incidence were found in 28 counties in Mississippi. The county-level percentage of food insecurity emerged as a possible predictor of the observed black–white racial disparities in CRC incidence rates. Individual-level studies are needed to clarify whether food insecurity is a driver of these disparities or a marker of systemic disadvantage in these counties.