Abstract Background Rectal adenocarcinoma (READ) is one of the deadliest malignancies, and the molecular mechanisms underlying the initiation and development of READ remain largely unknown. In this study, we aimed to find key long noncoding RNAs (lncRNAs) and mRNAs in READ by RNA sequencing. Methods RNA sequencing was performed to identify differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) between READ and normal tissue. READ‐specific protein‐protein interaction (PPI), DElncRNA‐DEmRNA coexpression, and DElncRNA‐nearby DEmRNA interaction networks were constructed. DEmRNAs and DEmRNAs coexpressed with DElncRNAs were functionally annotated. Results A total of 2113 DEmRNAs and 150 DElncRNAs between READ and normal tissue were identified. The PPI network identified several hub proteins, including CDK1, AURKB, CDC6, FOXQ1, NUF2, and TOP2A. The DElncRNA‐DEmRNA coexpression and DElncRNA‐nearby DEmRNA interaction networks identified some hub lncRNAs, including CCAT1, LOC105374879, GAS5, and B3GALT5‐AS1. The colorectal cancer pathway, the intestinal immune network for IgA production and the p53 signaling pathway were three pathways significantly enriched in DEmRNAs and DEmRNAs coexpressed with DElncRNAs. MSH6 coexpressed with two DElncRNAs (LOC105374879 and CASC15) and BCL2 coexpressed with B3GALT5‐AS1 were significantly enriched in the colorectal cancer signaling pathway. TNFRSF17 coexpressed with B3GALT5‐AS1 was enriched in the intestinal immune network for IgA production. CCNB2 coexpressed with LOC105374879 was enriched in the p53 signaling pathway. Conclusion A total of four DEmRNAs (MSH6, BCL2, TNFRSF17, and CCNB2) and three DElncRNAs (LOC105374879, CASC15, and B3GALT5‐AS1) may be involved in the pathogenesis of READ; this data may contribute to understanding the mechanisms of READ and the development of therapeutic strategies for READ. Keywords: DElncRNA‐DEmRNA coexpression, DElncRNAs, DEmRNAs, rectal adenocarcinoma, RNA sequencing 1. INTRODUCTION Colorectal cancer is one of the most common malignant tumors causing cancer‐related deaths and has one of the highest incidence rates among all types of cancer worldwide.[36]1 Rectal adenocarcinoma (READ) is a common type of colorectal cancer.[37]2 Although advancements in treatments and the prognosis and diagnosis of READ have been achieved through research, its mortality remains high, which may be due to the lack of efficient biomarkers for READ and the unclear mechanisms underlying READ. Hence, identifying efficient biomarkers and deciphering the detailed molecular mechanisms underlying READ are urgently required. In the field of gene‐gene network analysis, the construction of coexpression networks has opened up enormous possibilities for exploring the role of genes in biological processes.[38]3 Coexpression analysis of lncRNAs‐mRNAs is the most commonly used approach to screen potential target genes of lncRNAs and further research on the biological functions of lncRNAs in many kinds of diseases.[39]4, [40]5 The advent of high‐throughput genetic analysis means that a large portion of the genome can be transcribed, resulting in the discovery of the extensive transcription of large RNA transcripts named long noncoding RNAs (lncRNAs).[41]6, [42]7 Accumulating numbers of reports of aberrant lncRNA expression have demonstrated that lncRNAs may potentially serve as novel independent biomarkers for the early diagnosis and prognosis of and metastasis prediction in various cancer types.[43]8, [44]9, [45]10, [46]11 Recently, lncRNA profiling has been performed in several other types of colorectal cancer, which identified novel candidate diagnostic and prognostic biomarkers, such as SNHG6, PVT1, ZFAS1, LINC01555, RP11‐610P16.1, RP11, 108K3.1, and LINC01207.[47]12, [48]13 However, research on lncRNA biomarkers in READ is rare. Owing to the limited research linking lncRNAs with READ, this study aimed to further investigate this issue. In this study, RNA sequencing was performed to identify DEmRNAs and DElncRNAs between READ and normal tissue. READ‐specific protein‐protein interaction (PPI), DElncRNA‐DEmRNA coexpression, and DElncRNA‐nearby DEmRNA interaction networks were constructed. The functional annotation of DEmRNAs and DEmRNAs coexpressed with DElncRNAs was performed. Our study identified potential key genes and lncRNAs in READ and provides further insights into the mechanisms and predictive capacity of lncRNAs in READ. 2. MATERIALS AND METHODS 2.1. Patients Three patients with READ were enrolled in our study. Three tissue samples and three paired adjacent normal samples were selected from three cases of READ. The tissue samples were biopsy samples obtained from surgery. The detailed characteristics of the patients are displayed in Table [49]1. All the participants submitted signed informed consent forms, and the protocols were approved by the ethical committee of our hospital. Table 1. Patient characteristics Case 1 Case 2 Case 3 Age (years) 83 82 52 Gender Male Female Male Diagnostic method Colonoscopy Surgery Colonoscopy TNM stage T3N1M0 T4N2M1 T4N2M1 Tumor infiltration Serosa Serosa Serosa Tumor differentiation Medium‐grade Medium low‐grade Medium low‐grade [50]Open in a new tab 2.2. RNA isolation, library construction, and sequencing Total RNA was extracted from the samples using TRIzol reagent (Invitrogen, Carlsbad, CA). A Nanodrop ND‐2000 spectrophotometer (Thermo Scientific, Wilmington, DE) was applied to check the RNA concentration and purity. The integrity of the RNA was detected by agarose gel electrophoresis. The RIN value was obtained by an Agilent 2100 Bioanalyzer. The criteria for cDNA library construction were as follows: (a) total RNA >5 μg; (b) concentration of RNA ≥200 ng/μL; and (3) an OD 260/280 value of 1.8‐2.2. Ribosomal RNA was removed with a Ribo‐Zero Magnetic kit (EpiCentre, Madison, WI), and the RNA was purified and fragmented into 200‐500‐base pair fragments. The RNA fragments were primed with random hexameric primers, and the first cDNA strand was synthesized, with the second cDNA strand synthesized with dUTP instead of dTTP. After purification with AMPure XP Beads (Beckman Coulter, Brea, CA), end repair, adenylation of the 3′ ends and adapter ligation were performed. Polymerase chain reaction (PCR) was performed to construct a library for the high‐throughput sequencing of lncRNA, and the mRNA from the second cDNA strand was digested using UNG enzyme (Illumina, Inc, San Diego, CA). All libraries used for the high‐throughput sequencing of lncRNAs and mRNAs were amplified by 15 cycles of PCR. The quality of the library was assessed using the Agilent 2100 Bioanalyzer and ABI StepOnePlus Real‐Time PCR System. The sequencing of lncRNAs and mRNAs was performed on an Illumina HiSeq Xten platform (Illumina, San Diego, CA). 2.3. Quality control of raw sequences and mapping of clean reads FASTQ sequence data were obtained from the RNA‐seq data using Base Calling V 0.11.4 ([51]http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Low‐quality reads, including adaptor sequences, sequences with a quality score <20, and sequences with an N base percentage of the raw reads >10% were removed using Cutadapt V 1.9.1 ([52]https://cutadapt.readthedocs.io/en/stable/) with TopHat ([53]http://tophat.cbcb.umd.edu/) and Ensembl gene annotation. The clean reads were aligned with the human reference genome, Ensembl GRCh38.p7 ([54]ftp://ftp.ncbi.nlm.nih.gov/genomes/Homo_sapiens). The expression of mRNAs and lncRNAs was determined using Cuffquant V 2.2.1. 2.4. Differential expression analysis of mRNAs and lncRNAs The mRNAs and lncRNAs were quantified using Cuffquant V 2.2.1. Cuffdiff ([55]http://cufflinks.cbcb.umd.edu/) uses the quantitative results of Cuffquant to compare differences in the expression of each mRNA and lncRNA in READ and normal tissue. mRNAs and lncRNAs with a P‐value <0.05 and |log[2] fold change |>1 were significantly differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs), respectively. A heat map of the DEmRNAs and DElncRNAs in READ was obtained by heatmap.2 ([56]http://127.0.0.1:28428/library/gplots/html/heatmap.2.html). 2.5. Functional annotation GeneCodis 3 ([57]http://genecodis.cnb.csic.es/analysis) is an online software tool for functional annotation analysis used to reveal the biological functions related to large lists of genes. Gene Ontology (GO) classification (biological process, cellular component, and molecular function) is a major bioinformatics analysis method for annotating genes. The Kyoto Encyclopedia of Genes and Genomes (KEGG) is a database used to determine the biological systems associated with the output of high‐throughput experimental technologies. GO classification and KEGG pathway enrichment analyses were performed using GeneCodis 3. An false discovery rate (FDR) <0.05 was used to indicate statistical significance. 2.6. PPI network construction The top 100 upregulated or downregulated DEmRNAs in READ were used to build a PPI network using Biological General Repository for Interaction Datasets (BioGRID) ([58]http://thebiogrid.org/) and Cytoscape 3.5.0 ([59]http://www.cytoscape.org/). We used nodes to represent proteins and edges to represent the interactions between two proteins. 2.7. DEmRNA‐DElncRNA interaction analysis To identify DEmRNAs near DElncRNAs with cis‐regulatory effects, DEmRNAs transcribed within a 100 kb window up‐ or downstream of DElncRNAs in READ and normal controls were identified. In addition, DEmRNAs coexpressed with DElncRNAs were identified. Pairwise Pearson correlation coefficients between DEmRNAs and DElncRNAs were calculated. DElncRNA‐DEmRNA pairs with P < 0.001 and | r | ≥0.98 were defined as significant mRNA‐lncRNA coexpression pairs. 3. RESULTS 3.1. DEmRNAs and DElncRNAs in READ The raw data has been uploaded to Gene Expression Omnibus (GEO) ([60]GSE128969, [61]https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE128969). A total of 2113 DEmRNAs (809 downregulated and 1304 upregulated mRNAs) and 150 DElncRNAs (81 downregulated and 69 upregulated lncRNAs) between READ and normal tissue were identified with an FDR < 0.05 and a |Log[2]fold change|>1. The top 20 most significant DEmRNAs and DElncRNAs are displayed in Tables [62]2 and [63]3, respectively. Heatmaps of the top 100 DEmRNAs and all of DElncRNAs between READ and normal tissue are shown in Figure [64]1A,B, respectively. Circos plots representing the distribution of DElncRNAs and DEmRNAs on chromosomes are shown in Figure [65]1C. Table 2. The top 20 DEmRNAs andin READ ID Symbol log[2]FC P‐value FDR Up/down 3854 KRT6B 7.73832 5.00E‐05 0.002611 Up 342667 STAC2 6.74383 5.00E‐05 0.002611 Up 28234 SLCO1B3 6.69561 5.00E‐05 0.002611 Up 5655 KLK10 5.91643 5.00E‐05 0.002611 Up 221416 C6orf223 5.08019 5.00E‐05 0.002611 Up 90161 HS6ST2 5.06794 5.00E‐05 0.002611 Up 1800 DPEP1 5.02634 5.00E‐05 0.002611 Up 1767 DNAH5 4.95572 5.00E‐05 0.002611 Up 990 CDC6 4.9442 5.00E‐05 0.002611 Up 9271 PIWIL1 4.94295 5.00E‐05 0.002611 Up 55532 SLC30A10 −4.3053 5.00E‐05 0.002611 Down 229 ALDOB −4.02838 5.00E‐05 0.002611 Down 2346 FOLH1 −4.01874 5.00E‐05 0.002611 Down 374569 ASPG −3.97546 5.00E‐05 0.002611 Down 10022 INSL5 −3.84557 5.00E‐05 0.002611 Down 5320 PLA2G2A −3.76694 5.00E‐05 0.002611 Down 6689 SPIB −3.67292 5.00E‐05 0.002611 Down 8115 TCL1A −3.46401 5.00E‐05 0.002611 Down 1380 CR2 −3.36749 5.00E‐05 0.002611 Down 266675 BEST4 −3.34166 5.00E‐05 0.002611 Down [66]Open in a new tab Table 3. The top 20 DElncRNAs. in READ ID Symbol log[2]FC P‐value FDR Up/down 503638 LINC01296 5.37396 5.00E‐05 0.002611 Up 652995 UCA1 4.39663 5.00E‐05 0.002611 Up 105369370 LOC105369370 4.23597 5.00E‐05 0.002611 Up 102723961 LOC102723961 3.53756 5.00E‐05 0.002611 Up 100507056 CCAT1 3.34382 5.00E‐05 0.002611 Up 105374879 LOC105374879 2.59434 5.00E‐05 0.002611 Up 407975 MIR17HG 2.18303 5.00E‐05 0.002611 Up 105370108 LOC105370108 4.57119 0.0001 0.004682 Up 105376380 LOC105376380 3.45882 0.0002 0.007904 Up 60674 GAS5 1.20787 0.0002 0.007904 Up 105377567 LOC105377567 −2.77552 0.0001 0.004682 Down 283422 LINC01559 −1.28123 0.00015 0.006442 Down 283663 LINC00926 −2.10879 0.00035 0.011778 Down 114041 B3GALT5‐AS1 −1.89195 0.0004 0.012989 Down 284185 LINC00482 −1.90215 0.00055 0.016205 Down – LOC101926893 −3.61245 0.0006 0.017319 Down – LOC100507616 −2.896 0.0007 0.019391 Down 149837 LINC00654 −1.49029 0.0007 0.019391 Down 100289019 SLC25A25‐AS1 −1.13489 0.0008 0.021382 Down – LOC389332 −1.9268 0.00095 0.023864 Down [67]Open in a new tab Figure 1. Figure 1 [68]Open in a new tab Heat map of the top 100 DEmRNAs and all of DElncRNAs between READ and normal tissues. (A) DEmRNAs. (B) DElncRNAs. Rows and columns represent DElncRNAs/DEmRNAs and tissue samples, respectively. The color scale indicates expression levels. (C) Circos plots representing the distribution of DElncRNAs and DEmRNAs on chromosomes. The outer layer cycle is the chromosome map of the human genome. The inner layers represent the distribution of DEmRNAs and DElncRNAs on different chromosomes, respectively. Red and blue colors represent up‐ and downregulation, respectively 3.2. Functional annotation of DEmRNAs in READ DEmRNAs were used for GO and KEGG enrichment analyses. GO enrichment analysis showed that the DEmRNAs were significantly enriched in the mitotic cell cycle (FDR = 3.62E‐38), cell division (FDR = 4.10E‐28), cytoplasm (FDR = 1.70E‐75), nucleus (FDR = 5.13E‐ 75), protein binding (FDR = 2.82E‐72), and ATP binding (FDR = 4.42E‐51) terms. The top 15 GO terms for the DEmRNAs in READ are displayed in Figure [69]2A‐C. KEGG pathway enrichment analysis revealed that the p53 signaling pathway (FDR = 2.05E‐08), intestinal immune network for IgA production (FDR = 9.91E‐04), and colorectal cancer (FDR = 3.49E‐03) pathway were three significantly enriched pathways in READ. The top 15 most significantly enriched KEGG pathways for the DEmRNAs in READ are shown in Figure [70]2D. Figure 2. Figure 2 [71]Open in a new tab The top 15 significantly enriched GO terms and KEGG pathways for DEmRNAs in READ. The x‐axis shows ‐log FDR, and the y‐axis shows GO terms or KEGG pathways. (A) Biological process. (B) Cellular component. (C) Molecular function. (D) KEGG pathways 3.3. READ‐specific PPI network construction A PPI network of the top 100 up‐ and downregulated DEmRNAs consisted of 464 nodes and 591 edges (Figure [72]3). CDK1 (degree = 67), AURKB (degree = 34), CDC6 (degree = 20), FOXQ1 (degree = 20), NUF2 (degree = 19), and TOP2A (degree = 18) were considered hub proteins. Figure 3. Figure 3 [73]Open in a new tab READ‐specific PPI network. Ellipses are used to represent nodes, and lines are used to represent edges. Red and blue represent up‐ and downward adjustments, respectively. The black border indicates the top 10 up‐ and downregulated proteins 3.4. DElncRNA‐DEmRNA coexpression network A total of 5122 DElncRNA‐DEmRNA coexpression pairs including 150 DElncRNAs and 2110 DEmRNAs were identified with an absolute value of the Pearson correlation coefficient | r | ≥ 0.98 and a P‐value <0.001. We obtained a total of 3293 lncRNA‐mRNA pairs that were positively coexpressed and 1829 lncRNA‐mRNA pairs that were negatively coexpressed. The positively coexpressed DElncRNA‐DEmRNA network (Figure [74]4) consisted of 1364 nodes and 3293 edges, and its hub lncRNAs were CCAT1 (degree = 87), LOC105374879 (degree = 164), MIR17HG (degree = 72), UCA1 (degree = 35), and B3GALT5‐AS1 (degree = 141). Figure 4. Figure 4 [75]Open in a new tab Positively coexpressed DElncRNA‐DEmRNA network. Ellipses and inverted triangles represent DEmRNAs and DElncRNAs, respectively. Red and blue colors represent up‐ and downregulation, respectively. The black border indicates the top 10 up‐ and downregulated DElncRNAs and DEmRNAs The negatively coexpressed DElncRNA‐DEmRNA network (Figure [76]5) consisted of 1049 nodes and 1829 edges, and its hub lncRNAs were LOC105374879 (degree = 33), LINC00482 (degree = 42), B3GALT5‐AS1 (degree = 31), and MIR17HG (degree = 55). Figure 5. Figure 5 [77]Open in a new tab Negatively coexpressed DElncRNA‐DEmRNA network. Ellipses and inverted triangles represent DEmRNAs and DElncRNAs, respectively. Red and blue colors represent up‐ and downregulation, respectively. The black border indicates the top 10 up‐ and downregulated DElncRNAs and DEmRNAs 3.5. Functional annotation of DEmRNAs coexpressed with DElncRNAs According to the GO enrichment analysis of DEmRNAs with an FDR < 0.05, the mitotic cell cycle (FDR = 8.66E‐21), DNA replication (FDR = 8.36E‐19), nucleus (FDR = 5.30E‐60), cytoplasm (FDR = 6.70E‐53), protein binding (FDR = 2.47E‐50), and ATP binding (FDR = 5.58E‐41) terms were the most significantly enriched GO terms. The top 15 GO terms of the DEmRNAs in READ are displayed in Figure [78]6A‐C. After KEGG pathway enrichment analysis (FDR < 0.05), we found that the cell cycle (FDR = 1.36E‐12), purine metabolism (FDR = 2.74E‐12), and DNA replication (FDR = 5.16E‐12) pathways were the three most significantly enriched pathways in READ. The top 15 most significantly enriched KEGG pathways for DEmRNAs in READ are shown in Figure [79]6D. The p53 signaling pathway (FDR = 0.0023), intestinal immune network for IgA production (FDR = 0.0084), and colorectal cancer pathway (FDR = 0.0014) were three READ‐related pathways. The p53 signaling pathway, intestinal immune network for IgA production and colorectal cancer pathway are displayed in Figure [80]7. Figure 6. Figure 6 [81]Open in a new tab Top 15 significantly enriched GO terms and KEGG pathways for DEmRNAs coexpressed with DElncRNAs in READ. The x‐axis shows ‐log FDR, and the y‐axis shows GO terms or KEGG pathways. (A) Biological process. (B) Cellular component. (C) Molecular function. (D) KEGG pathways Figure 7. Figure 7 [82]Open in a new tab READ pathways (p53 signaling pathway, intestinal immune network for IgA production, and colorectal cancer pathway) enriched in DEmRNAs during READ. The red and green rectangles represent components regulated by DEmRNAs that are enriched in READ 3.6. DElncRNA‐nearby DEmRNA interaction network The functions of most lncRNAs remain unknown. We hypothesized that lncRNAs may exert their functions by regulating nearby genes. A total of 75 DElncRNA‐nearby target DEmRNA pairs were obtained that consisted of 54 DElncRNAs and 69 DEmRNAs (Figure [83]8A). Ten DElncRNAs with the closest DEmRNAs were CCAT1, LOC102723961, LOC105369370, LOC105374879, MIR17HG, UCA1, GAS5, LINC00926, B3GALT5‐AS1, and LINC00482, which were nearby 1, 2, 1, 2, 1, 1, 1, 1, 1, and 2 DEmRNAs, respectively. The DElncRNA‐nearby DEmRNA pairs in which the DEmRNA was coexpressed with the DElncRNA are displayed in Table [84]4. After looking for overlaps in the DElncRNA‐DEmRNA coexpression network and the DElncRNAs‐nearby DEmRNAs interaction network, we obtained a total of five lncRNA‐mRNA pairs including five DElncRNAs and five DEmRNAs (Figure [85]8B). Among these, LOC105369370 was within the top 10 DElncRNAs. Moreover, MYEOV was not only an DEmRNA nearby LOC105369370 but was also coexpressed with LOC105369370. Figure 8. Figure 8 [86]Open in a new tab DElncRNA‐nearby DEmRNA interaction network in READ. (A) DElncRNA‐nearby DEmRNA interaction network. (B) Interaction network showing the overlap of the DElncRNA‐DEmRNA coexpression network with the DElncRNA‐nearby DEmRNA interaction network. Ellipses and inverted triangles represent DEmRNAs and DElncRNAs, respectively. Red and blue colors represent up‐ and downregulation, respectively. The black border indicates the top 10 up‐ and downregulated Table 4. The DElncRNAs‐nearby DEmRNAs pairs Chr lncRNA mRNA Symbol Start − 100kb End + 100kb Symbol Start End chr8 CCAT1 127107381 127319268 POU5F1B 127244636 127482139 chr17 LOC102723961 79715942 79923284 CBX2 79776253 79787650 chr17 LOC102723961 79715942 79923284 CBX8 79794376 79797116 chr11 LOC105369370 69266824 69472512 MYEOV 69294137 69297287 chr6 LOC105374879 1184930 1391486 FOXQ1 1312439 1314758 chr6 LOC105374879 1184930 1391486 FOXF2 1389833 1395597 chr13 MIR17HG 91247819 91454575 GPC5 91398618 92867237 chr19 UCA1 15727044 15936321 CYP4F2 15878023 15898120 chr1 GAS5 173763247 173967987 CENPL 173799549 173824639 chr11 SNHG1 62751987 62955888 WDR74 62832233 62841809 chr15 LINC00926 57200364 57407769 CGNL1 57376486 57550727 chr21 B3GALT5‐AS1 39497146 39712822 B3GALT5 39612939 39662889 chr17 LINC00482 81202823 81409248 LOC100130370 81375496 81392947 chr17 LINC00482 81202823 81409248 BAHCC1 81395430 81466332 chr7 SNHG15 44883027 45086660 MYO1G 44962660 44979105 chr8 LOC105375752 127040057 127269518 POU5F1B 127244636 127482139 chr8 LOC105375752 127040057 127269518 FAM84B 126552437 127049451 chr8 PVT1 127694532 128201253 MYC 127736068 127741434 chr17 SNHG16 76457763 76665348 ST6GALNAC1 76617768 76643838 chr7 LOC105375431 100842058 101069565 TRIP6 100867327 100873454 chr7 LOC105375431 100842058 101069565 MUC12 100969622 101018949 chr7 LOC105375431 100842058 101069565 MUC3A 100942058 100969565 chr6 SNHG5 85577006 85778733 SYNCRIP 85607783 85643862 chr19 LOC400706 45957677 46177629 IGFL2 46078512 46203062 chr1 BLACAT1 205273251 205556086 LEMD1 205373251 205456086 chr6 CASC15 21566443 22294400 SOX4 21593740 21598619 chr4 DANCR 52612149 52823436 ERVMER34‐1 52743516 52753572 chr17 MAFG‐AS1 81827828 82030753 ALYREF 81887834 81900533 chr17 MAFG‐AS1 81827828 82030753 MYADML2 81939644 81947233 chr17 MAFG‐AS1 81827828 82030753 PYCR1 81932383 81937328 chr17 MAFG‐AS1 81827828 82030753 NOTUM 81952506 81961181 chr12 LOC105369827 70368087 70616501 KCNMB4 70366219 70434292 chr19 LOC101927522 35305606 35534730 FFAR2 35447964 35451767 chr19 LOC101927522 35305606 35534730 CD22 35329165 35347361 chr19 LOC101927522 35305606 35534730 DMKN 35497216 35513678 chr19 LOC101927522 35305606 35534730 TMEM147 35533337 35547527 chr1 LOC105378625 31348257 31549586 SERINC2 31409564 31434680 chr16 LOC105371100 16049564 16323616 ABCC6 16149564 16223616 chr3 LOC101928405 165050005 165258164 SI 164978897 165083824 chr17 LOC105371919 79723794 79927704 CBX2 79776253 79787650 chr17 LOC105371919 79723794 79927704 CBX8 79794376 79797116 chr1 LOC105378687 43254683 43458673 C1orf210 43281864 43285840 chr1 LOC105378687 43254683 43458673 CDC20 43358954 43363203 chr4 LOC105377400 120972758 121181901 NDNF 121035626 121072518 chr14 LOC101928957 91420514 91677823 CATSPERB 91580773 91732086 chr3 LOC105377068 46314778 46524092 LTF 46436004 46485234 chr4 LOC105374527 23669093 23883980 PPARGC1A 23792020 24472975 chr15 LOC100996255 32436758 32680609 ARHGAP11A 32615143 32639949 chr1 LOC105378728 53126891 53428149 SLC1A7 53087178 53142632 chr1 LOC105378728 53126891 53428149 LRP8 53226891 53328149 chr6 LINC01268 113768012 113980812 HDAC2 113936155 114342388 chr21 AATBC 43705757 43912567 RRP1 43789536 43804102 chr12 LOC100506691 121963289 122168560 WDR66 121918556 122003927 chr17 LOC105371811 48632983 48843465 HOXB13 48724762 48728749 chr17 LOC105371811 48632983 48843465 TTLL6 48762230 48817253 chr16 LOC105371058 2977271 3187993 PAQR4 2969244 2980539 chr16 LOC105371058 2977271 3187993 PKMYT1 2969244 2980539 chr16 LOC105371058 2977271 3187993 CLDN9 3012455 3014505 chr16 LOC105371058 2977271 3187993 TNFRSF12A 3020311 3022383 chr3 LINC01279 112496793 112701969 BTLA 112458789 112499756 chr4 LOC105374343 936210 1151506 FGFRL1 1011821 1026898 chr14 LINC00341 95307265 95510090 SYNE3 95416082 95519720 chr2 LOC105373774 183111202 183319628 NUP35 183117489 183161684 chr16 ATP2A1‐AS1 28778487 29025211 CD19 28931734 28939347 chr7 LINC00996 150333653 150548140 GIMAP7 150514856 150521073 chr1 LOC105378604 2969024 3538621 MEGF6 3487941 3624757 chr8 LOC105379219 8001046 8328352 SGK223 8317730 8386444 chr14 LOC105370503 53250170 53950877 BMP4 53949735 53956862 chr11 H19 1847271 2113176 LSP1 1852969 1892263 chr12 LOC105369763 49842673 50046888 FAIM2 49866895 49904275 chr12 LOC105369763 49842673 50046888 RACGAP1 49989161 50033136 chr1 LOC105378726 53126891 53428149 SLC1A7 53087178 53142632 chr1 LOC105378726 53126891 53428149 LRP8 53226891 53328149 chr7 ABHD11‐AS1 73635068 73836000 STX1A 73699204 73719702 chr4 LOC105374528 23617859 23869047 PPARGC1A 23792020 24472975 [87]Open in a new tab 4. DISCUSSION READ is one of the deadliest malignancies, and the molecular mechanisms underlying the initiation and development of READ remain largely unknown. Hence, comprehensive detailing of its mechanisms is critical. An increasing number of studies have explored the important regulatory effects of lncRNAs on tumor formation and metastasis. Here, DEmRNAs and DElncRNAs in READ were studied using RNA sequencing. A total of 2113 DEmRNAs (809 downregulated and 1304 upregulated mRNAs) and 150 DElncRNAs (81 downregulated and 69 upregulated lncRNAs) between READ and normal tissue were identified. Additionally, we constructed a READ‐specific PPI network, a DElncRNA‐DEmRNA coexpression network and a DElncRNA‐nearby DEmRNA interaction network. In addition, DEmRNAs and DEmRNAs coexpressed with DElncRNAs were functionally annotated. Coexpression networks have been used in other studies to identify important modules associated with cancer and the functions of the lncRNAs involved within them.[88]14 Herein, construction of the DElncRNA‐nearby DEmRNA interaction network showed that the top ten DElncRNAs with the closest DEmRNAs were CCAT1, LOC102723961, LOC105369370, LOC105374879, MIR17HG, UCA1, GAS5, LINC00926, B3GALT5‐AS1, and LINC00482. To our knowledge, besides CCAT1, MIR17HG, UCA1, and GAS5, three upregulated DElncRNAs (LOC102723961, LOC105369370, and LOC105374879) and three downregulated DElncRNAs (LINC00926, B3GALT5‐AS1, and LINC00482) in READ have been reported for the first time, and their biological functions remain unclear. Most network construction techniques can only address positive correlations in gene expression data, whereas biologically significant genes exhibit both positive and negative correlations.[89]3 In this study, positively correlated DEmRNAs and DE1ncRNAs in READ were defined as positively coexpressed DElncRNA‐DEmRNA pairs, and negatively correlated DEmRNAs and DE1ncRNAs were defined as negatively coexpressed DE1ncRNA‐DEmRNA pairs. CDK1, AURKB, CDC6, FOXQ1, NUF2, and TOP2A were the hub proteins of the READ‐specific PPI network. CDK1, a member of the CDKs, is a serine/threonine kinase that promotes the G2‐M transition and regulates G1 progression and G1‐S transition.[90]15 CDK1 is overexpressed in human colorectal cancers and relevant to the clinical behavior of human colorectal cancers, which was shown by the association between a high ratio of CDK1 nuclear to cytoplasmic expression and poor overall survival and that CDK1 was an independent risk factor for outcome.[91]16, [92]17 AURKB, a member of the aurora kinase family, is an important diagnostic and prognostic marker involved in the carcinogenesis of colorectal cancers.[93]18 FOXQ1 is frequently upregulated in colorectal cancers, and FOXQ1 knockdown suppressed cell proliferation and the migration and invasion of colorectal cancers.[94]19 TOP2A is a potential predictive biomarker for anthracycline and irinotecan treatment in colorectal cancer, and high frequency of gene gains for the TOP1 and TOP2A genes were reported in colorectal cancers.[95]20 Elevated NUF2 expression was associated with poor prognosis in colorectal cancer, and the knockdown of NUF2 expression suppressed the growth of tumor cells.[96]21 Therefore, we speculated that CDK1, AURKB, FOXQ1, NUF2, and TOP2A might play important roles in READ. Interaction network analysis showed that AURKB was coexpressed with SNHG5 and that FOXQ1 was coexpressed with LOC105374879. Hence, we further hypothesized that SNHG5 and LOC105374879 might play important roles in READ by regulating AURKB and FOXQ1, respectively. CCAT1 is upregulated in colorectal cancer but not in normal tissue.[97]22 A CCAT1‐specific peptide nucleic acid‐based molecular beacon was reported to serve as a powerful diagnostic tool for the specific identification of colorectal cancer.[98]23 GAS5 is associated with not only susceptibility to colorectal cancer but also the metastasis of colorectal cancer to the lymph node.[99]24SLCO1B3, a solute carrier organic anion transporter family member, is upregulated in colorectal cancer.[100]25 The overexpression of SLCO1B3 changed p53‐dependent pathways and conferred apoptotic resistance in colorectal cancer.[101]26 SLCO1B3 protein expression was significantly correlated with proximal tumor location and the expression of mismatch repair genes, and SLCO1B3 was identified as a cell‐surface marker differentially expressed in colon adenocarcinoma relative to its expression in the surrounding normal colon tissue.[102]27 In this study, SLCO1B3 was coexpressed with CCAT1 and GAS5. Therefore, we presumed that both CCAT1 and GAS5 might be involved in the development of READ by regulating SLCO1B3. According to KEGG pathway enrichment analysis of DEmRNAs and DEmRNAs coexpressed with DElncRNAs, the p53 signaling pathway, intestinal immune network for IgA production and colorectal cancer pathway were three READ‐related pathways. MSH6 coexpressed with two DElncRNAs (LOC105374879 and CASC15) and BCL2 coexpressed with B3GALT5‐AS1 were significantly enriched in the colorectal cancer signaling pathway. TNFRSF17 coexpressed with B3GALT5‐AS1 was enriched in the intestinal immune network for IgA production. CCNB2 coexpressed with LOC105374879 was enriched in the p53 signaling pathway. MSH6 is a mismatch repair gene involved in colorectal cancers, and it was reported that most patients with colorectal cancer carrying an MSH6 mutation were diagnosed after the age of 50 and had distally localized tumors. TNFRSF17 may be a candidate gene associated with the pathogenesis of colon cancer, and the haplotypes of TNFRSF17 polymorphisms might be markers for colon cancer susceptibility.[103]28 BCL2 is a well‐known protein that prevents apoptosis in many kinds of tumors and is routinely assayed as a diagnostic marker in the clinical practice of pathology. Very recent studies found that BCL2 was downregulated in early‐stage colon adenocarcinoma and that BCL2 was involved in the metastasis of colon adenocarcinoma to the lymph nodes.[104]29, [105]30 In our study, BCL2 was reduced in READ, which indicated that BCL2 might regulate READ as well. Therefore, we hypothesized that LOC105374879, CASC15, and B3GALT5‐AS1 might play pivotal roles in READ by regulating the colorectal cancer signaling pathway, the intestinal immune network for IgA production and the p53 signaling pathway. In summary, we identified 2113 DEmRNAs and 150 DElncRNAs in READ compared to their expression in normal tissues. The PPI network identified several hub proteins including CDK1, AURKB, CDC6, FOXQ1, NUF2, and TOP2A. DElncRNA‐DEmRNA coexpression and DElncRNA‐nearby DEmRNA interaction networks were constructed to identify hub lncRNAs, including CCAT1, LOC105374879, GAS5, and B3GALT5‐AS1. The colorectal cancer pathway, intestinal immune network for IgA production, and p53 signaling pathway were three significantly enriched pathways for DEmRNAs and DEmRNAs coexpressed with DElncRNAs. MSH6 coexpressed with two DElncRNAs (LOC105374879 and CASC15) and BCL2 coexpressed with B3GALT5‐AS1 were significantly enriched in the colorectal cancer signaling pathway of. TNFRSF17 coexpressed with B3GALT5‐AS1 was enriched in the intestinal immune network for IgA production. CCNB2 coexpressed with LOC105374879 was enriched in the p53 signaling pathway. Our results warrant further studies on these mRNAs and lncRNAs to improve our understanding of the mechanisms associated with the pathogenesis and progression of READ. However, there are limitations to our study. First, the sample size for RNA sequencing was small, and large numbers of READ samples are needed for further research. Second, DEmRNAs and DElncRNAs in READ were identified, but their biological functions were not studied. Therefore, in vivo and in vitro experiments are necessary to elucidate the biological roles of DEmRNAs and DElncRNAs in READ in future work. 5. CONFLICT OF INTEREST STATEMENT The authors declare that they have no conflict of interest. No competing financial interests exist. DATA AVAILABILITY STATEMENT The dataset supporting the conclusions of this article is included within the article. ACKNOWLEDGMENTS