Background: This study systematically evaluated the expression profile and functional significance of minichromosome maintenance 10 (MCM10) in colorectal cancer (CRC), assessed its association with the tumor immune microenvironment, and investigated its role in regulating cellular proliferation, migration, invasion, and stemness, thereby highlighting its potential as a therapeutic candidate. Methods: Transcriptomic datasets were accessed from publicly available databases (GEO and TCGA). The data were analyzed to determine MCM10 expression and assess its association with immune cell infiltration. Functional enrichment profiling and molecular network modeling were performed to uncover underlying mechanisms. Furthermore, in vitro validation, including quantitative real-time polymerase chain reaction (qRT-PCR), Western blot analysis, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) proliferation assays, Transwell migration and invasion assays, and tumor sphere formation assays, was conducted to determine the biological effects of MCM10 on CRC cells. Results: MCM10 was upregulated in CRC tissues and demonstrated a positive association with immune-cell infiltration, particularly helper T cells and T helper 2 (Th2) cells. Notably, MCM10 expression was substantially higher in CRC tissues compared with adjacent normal tissues (p < 0.001), consistent with TCGA and GTEx cohort analyses. Furthermore, MCM10 was enriched in cancer-related signaling pathways and immune regulatory processes. Functional assays demonstrated that MCM10 overexpression promoted CRC cell proliferation, migration, invasion, and stemness, while its knockdown produced the opposite effects. Conclusion: Our findings confirm a pivotal role of MCM10 in CRC, suggesting its potential as a diagnostic biomarker and therapeutic target. The findings offer promising insights into the molecular biology of CRC and provide a foundation for the development of precision treatment strategies.

Standard neoadjuvant chemoradiotherapy for locally advanced rectal cancer (LARC) is associated with significant toxicity and limited pathological responses. We retrospectively compared a radiotherapy‑free regimen of camrelizumab plus modified FOLFOXIRI versus modified FOLFOXIRI alone in consecutive patients with clinical stage II-III LARC treated from 2022-2025 (n = 146). All patients received ≥3 cycles of neoadjuvant therapy; surgery or watch‑and‑wait was determined by a multidisciplinary team. Baseline characteristics were well balanced. Among surgical patients, pCR rates were 29.8% with camrelizumab plus FOLFOXIRI and 19.6% with FOLFOXIRI alone. Radiologic objective response rates were 70.7% and 53.5%, respectively, and mean neoadjuvant rectal scores were lower with camrelizumab (13.95 vs 23.77; P < 0.02). Disease‑free survival was significantly improved in the camrelizumab group, while overall survival was similar at current follow‑up. Grade 3-4 hematologic and gastrointestinal toxicities were comparable, and no unexpected immune‑related events occurred. Camrelizumab plus FOLFOXIRI appears to be an active, tolerable radiotherapy‑free neoadjuvant option for LARC.

The intratumoral microbiota has been identified as an indispensable part of the tumor microenvironment (TME). However, the relationship between the intratumoral microbiota and host gene expression, as well as its impact on prognosis and TME immunity, remains unclear. We utilized a machine learning-based framework to identify microbiota-host gene associations across 14 tumors from The Cancer Genome Atlas (TCGA) and validated them in 11 tumors from the Gene Expression Omnibus. By calculating immune scores and identifying immune-related microbiota, we developed both a pan-cancer Immune and Prognosis-Related Microbial Score (IPRMS) and cancer-specific IPRMSs and analyzed the relationship between the cancer-specific IPRMSs and immune infiltration at bulk level and single-cell level. Furthermore, we systematically analyzed the potential mechanisms in which the intratumoral microbiota might affect prognosis using survival mediation analyses (SMAs). We identified gene subsets associated with microbiota, which were predominantly enriched in immune-related and cell signaling regulation pathways. Subsequently, we constructed the overall survival-related IPRMS and found that high-IPRMS patients had poorer prognosis in pan-cancer and increased presence of macrophage and cancer-associated fibroblasts. In contrast, low-IPRMS patients showed enrichment in tumor-infiltrating lymphocytes. SMAs suggest that intratumoral microbiota may influence prognosis by affecting immune cells, pathways, and host genes. High-IPRMSs were consistently associated with poorer prognosis and lower abundance of tumor-infiltrating lymphocytes. At the single-cell level, cancer-associated fibroblasts were predominantly enriched in the high-IPRMS group, while tumor-infiltrating lymphocytes were also mainly enriched in the low-IPRMS group. Our research indicates that the intratumoral microbiota was associated with immune and prognosis, which may impact the cancer prognosis by modifying immune cells, pathways, and host gene expression. IMPORTANCE:The intratumoral microbiota is a vital part of the tumor microenvironment, yet its interplay with host gene expression and immune regulation remains unclear. Based on a machine learning framework for the interaction analysis of intratumoral microbiota and host genes, as well as the construction of the Immune and Prognosis-Related Microbial Score, our findings suggest that intratumoral microbiota may influence gene expression by affecting host pathways, especially immune-related pathways. Moreover, immune-related intratumoral microbiota are significantly associated with patient survival and TME immunity and may influence prognosis by affecting immune cells, pathways, or gene expression, offering new perspectives and potential biomarkers for predicting personalized patient prognosis in the future.

The tertiary lymphoid structures (TLSs) are positively correlated with the prognosis of many solid tumors, including colorectal cancer. However, their prognostic significance in patients with locally advanced rectal cancer (LARC) after neoadjuvant chemotherapy remains unclear. This study aimed to explore the correlation between TLS parameters and the prognosis of LARC patients receiving neoadjuvant chemotherapy. This retrospective study included patients with LARC treated at the Harbin Medical University Cancer Hospital from 2012 to 2021. The quantity, area, and density of TLSs in the tumor, normal, and total tissues from surgical specimens were determined. Overall survival (OS) was calculated from surgery to death from any cause. The correlation between TLS parameters and prognosis was assessed using Kaplan-Meier survival analysis and Cox regression analysis. Multiplex immunofluorescence (mIF) staining was used to analyze TLS maturity and immune composition. This study included 114 patients, of whom 46.5

Radiotherapy is essential in the treatment of colorectal cancer (CRC), but the presence of drug resistance leads to poor prognosis for CRC patients. Identifying targets and mechanisms for regulating radiotherapy resistance has high clinical value. This study identifies CCR4-NOT transcription complex subunit 7 (CNOT7) as a key factor mediating radiotherapy resistance in CRC by stabilizing XRCC6 protein and enhancing non-homologous end joining (NHEJ) mediated DNA damage repair (DDR) pathway. Proteomic analysis of 45 CRC tissues revealed that elevated CNOT7 expression correlates with poorer responses to neoadjuvant radiotherapy and lower disease control rate (DCR). We demonstrated that CNOT7 knockdown enhances radiosensitivity by impairing NHEJ mediated double-strand breaks (DSBs) repair and promoting apoptosis in vitro and in vivo. Mechanistically, CNOT7 interacts with XRCC6 to stabilize its protein levels by inhibiting TRIM21-mediated K48-linked ubiquitination at lysine 526, thereby facilitating efficient DNA repair. CNOT7 accelerates degradation of TRIM21 mRNA through its deadenylase activity. Additionally, the combination of STL127705, an inhibitor of the XRCC6/XRCC5 heterodimer, with radiotherapy notably suppressed tumor growth in patient-derived xenograft (PDX) and cell line mouse transplant tumor models, especially in the context of CNOT7 deficiency. These findings elucidate the function of CNOT7 in promoting DNA repair and radiotherapy resistance in CRC, highlighting that targeting the CNOT7-TRIM21-XRCC6 axis provides a promising therapeutic approach to overcome radiotherapy resistance and improve clinical outcomes for CRC patients.

Cancer is one of the leading causes of cancer-related deaths worldwide and is also among the most common malignant tumors of the digestive system. With the decreasing age of onset, there is an urgent need to develop effective therapeutic strategies to improve patient survival. RAN-binding protein 9 (RANBP9) has been identified as an oncogene involved in several cancers, including colon cancer, gastric cancer, and lung cancer. It plays a crucial role in inhibiting tumor metastasis and enhancing chemotherapy sensitivity. In this study, we synthesized a novel two-dimensional layered coordination polymer, CP1, by reacting Co(NO3)(2)6H(2)O, HL, and NH(CN)(2) under solvothermal conditions at 120 degrees C. The compound crystallizes in the monoclinic C2/m space group, with its asymmetric unit containing two Co(II) ions, two half N(CN)(2)(-) ligands, and one HL ligand. The Co(II) ions coordinate with N(CN)(2)(-) ligands to form a one-dimensional chain, which is further interconnected by HL ligands to form a two-dimensional layered structure. These layers interdigitate through van der Waals interactions, resulting in a three-dimensional supramolecular framework (CP1). To enhance drug delivery and therapeutic effects, compound I was encapsulated within the conductive polymer PEDOP (poly(3,4-ethylenedioxythiophene)) along with CP1. PEDOP, a well-known conductive polymer, is highly conductive and stable, making it an ideal candidate for drug delivery systems. The resulting PEDOP-CP1@I nanocarrier significantly inhibited the cellular activity of HT29 colorectal cancer (CRC) cells, upregulated RANBP9 expression, and modulated the expression of apoptosis-related genes Bax and Bcl-2, thereby inducing apoptosis in CRC cells. These findings highlight the potential of PEDOP-CP1@I as a promising strategy for cancer therapy.

Transcriptome sequencing has become essential in clinical tumor research, providing in-depth insights into the biology and functionality of tumor cells. However, the vast amount of data generated and the complex relationships between gene expressions make it challenging to effectively identify clinically relevant information. In this study, we developed a method called Gene Swin Transformer to address these challenges. This approach converts transcriptomic data into Synthetic Image Elements (SIEs). We utilized data from 12 datasets, including GSE17536-GSE103479 datasets (n = 1771) and The Cancer Genome Atlas (n = 459), to generate SIEs. These elements were then classified based on survival time using deep learning algorithms to predict colorectal cancer prognosis and build a reliable prognostic model. We trained and evaluated four deep learning models—BeiT, ResNet, Swin Transformer, and ViT Transformer—and compared their performance. The enhanced Swin-T model outperformed the other models, achieving weighted precision, recall, and F1 scores of 0.708, 0.692, and 0.705, respectively, along with area under the curve values of 80.2%, 72.7%, and 76.9% across three datasets. This model demonstrated the strongest prognostic prediction capabilities among those evaluated. Additionally, the PEX10 gene was identified as a key prognostic marker through both visual attention matrix analysis and bioinformatics methods. Our study demonstrates that the Gene Swin model effectively transforms Ribonucleic Acid (RNA) sequencing data into SIEs, enabling prognosis prediction through attention-based algorithms. This approach supports the development of a data-driven, unified, and automated model, offering a robust tool for classification and prediction tasks using RNA sequencing data. This advancement presents a novel clinical strategy for cancer treatment and prognosis forecasting.

BACKGROUND:Preoperative neoadjuvant chemoradiation (NACR) benefits disease control in most locally advanced rectal cancer (LARC) patients. However, effective biomarkers predicting response to NACR are still not accessible. This study aimed to find potential biomarkers to assess therapy response and susceptibility to LARC. MATERIALS AND METHODS:Differentially expressed genes (DEGs) between NACR-sensitive and resistant patients were screened using GEO database. STRING and Cytoscape were utilized to construct PPI networks and identify hub genes. Based on CIBERSORT, TCGA, GTEx, GSEA and ROC curves, the connections between hub genes and specific signaling pathways, immune cell infiltration, prognosis value and miRNA-transcription factor (TF)-target network were investigated. Human Protein Atlas (HPA) database was used to visualize hub gene expression in clinical samples. RESULTS:We identified 2619 up- and 2466 down-regulated genes between NACR-sensitive and resistant patients. The up-regulated DEGs were searched for highly expressed genes in the NACR-resistant, TCGA and GTEx-related datasets compared to the NACR-sensitive group, yielding six hub genes (RRM2, HNRNPL, EZH2, METTL1, NHP2L1 and ASF1B). ROC curves demonstrated the predictive utility of the six genes in NACR sensitivity. Immune infiltration research revealed no significant relationship between NACR sensitivity and immune cell infiltration extent. The miRNA-TF-target network of hub genes was established. Finally, HPA database results showed that six genes were expressed at variable levels in rectal cancer patients. CONCLUSIONS:This study identified six hub genes (RRM2, HNRNPL, EZH2, METTL1, NHP2L1 and ASF1B) up-regulated in LARC and valuable for predicting patient susceptibility and response to NACR.

AIMS:Colorectal cancer (CRC) remains one of the most common malignancies worldwide characterized by poor prognosis, and its mechanism is unclear. Small heat shock protein 6 (HSPB6) plays an important role in cardiovascular diseases. However, the role of HSPB6 in CRC remain poorly understood. MATERIALS AND METHODS:We performed whole-genome methylation, RNA sequencing and proteomics analysis, combined with external database, to identify and validate the role of HSPB6 in CRC. We detected HSPB6 in CRC through in vitro and in vivo experiments. The downstream regulatory mechanism of HSPB6 was explored using RNA sequencing and immunoprecipitation mass spectrometry. The drug sensitivity assay conducted to evaluate the effect of HSPB6 expression on chemosensitivity. KEY FINDINGS:HSPB6 was hypermethylated and downregulated in CRC tissues, and its expression level was correlated with poor patient prognosis. Both the methylation and expression of HSPB6 showed high diagnostic value. Overexpression of HSPB6 inhibited proliferation, migration and invasion of CRC cells and suppress tumor growth in mice. HSPB6 directly interacted with Heat shock protein family A member 6 (HSPA6), leading to inhibition of the JNK-JUND axis. Additionally, HSPB6 overexpression increased sensitivity to oxaliplatin. SIGNIFICANCE:HSPB6 may serve as a valuable diagnostic and prognostic biomarker, and as a putative tumor suppressor in CRC by downregulating HSPA6 and inhibiting the JNK-JUND signaling axis. Our findings suggest a novel therapeutic strategy for CRC patients exhibiting high HSPB6 expression, particularly in the context of oxaliplatin treatment.

AIMS:Explore the role of mitochondrial membrane permeability transition (MPT) in colon adenocarcinoma (COAD). BACKGROUND:Further exploration of risk stratification for COAD prognostic assessment has important clinical value. MPT-related pathways play a key role in the pathogenesis of many human diseases, including tumorigenesis. Its impact on COAD is still unknown. OBJECTIVE:Bioinformatics analysis was conducted by analyzing the GEO database and TCGA database, and the bioinformatics results were verified by in vitro experiments. METHODS:Through the analysis of the transcriptome data of 1008 COAD samples in the GEO database and TCGA database, the differential expressions of MPT-related genes in COAD were explored, followed by molecular subtype analysis based on MPT characteristics by univariate Cox algorithm analysis and the consensus clustering algorithm. The gene signature associated with MPT molecular subtypes was further identified and the MPT scoring system was established by the LASSO-univariate Cox analysis algorithm. After evaluating the prognostic value of the MPT scoring system in COAD patients via nomogram establishment, the clinical value of the MPT scoring system was comprehensively analyzed through somatic mutation characteristics analysis, immunotherapy response analysis, immunoinfiltration analysis, and drug sensitivity analysis. CCK-8, WB, PCR, colony formation method, and Transwell method were used to verify the effect of the screened target on the proliferation and invasion of COAD cells. RESULTS:We successfully established a scoring system related to MPT and validated the prognostic value of COAD patients. The potential clinical value of the MPT scoring system was also analyzed. VSIG4 was selected for further in vitro experiments to verify the effect of the screened targets on the proliferation and invasion ability of COAD cells. CONCLUSION:We established an MPT scoring system for effective risk stratification of COAD patients, demonstrating the impact of MPT on the development of COAD and its potential value as an intervention factor.

Background:Stage III colon cancer (CC) presents a critical therapeutic challenge due to its high recurrence risk. Identifying robust prognostic biomarkers to guide adjuvant therapy decisions is urgently needed in clinical practice. Tertiary lymphoid structures (TLSs), as immune aggregates within the tumor microenvironment, have emerged as potential indicators of immunological activity and treatment response. The objective of this study is to evaluate the role of TLSs in stage III CC, focusing on their potential as prognostic markers and their influence on patient outcomes, particularly in relation to chemotherapy response. Methods:This retrospective cohort study enrolled 613 patients with pathologically confirmed stage III CC from two cohorts: 374 from Harbin Medical University and 239 from The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) external validation cohort. Overall survival (OS) was the primary outcome, with a median follow-up period of 62 months. TLSs were assessed via immunohistochemistry and categorized by density and location [intratumoral (T score), peritumoral (P score)]. Prognostic significance was evaluated using multivariate Cox regression. A murine model was used to assess the immunomodulatory effects of folinic acid, oxaliplatin, and 5-fluorouracil (FOLFOX) chemotherapy on TLS formation. Results:TLSs were present in 54.0% and 50.2% of patients in Cohorts 1 and 2, respectively. TLSs enriched with CD8+ T cells and CD20+ B cells were associated with improved OS. Multivariate analysis identified TLS presence as an independent predictor of better survival [hazard ratio (HR) =0.256, 95% confidence interval (CI): 0.093-0.707; P=0.009]. Higher intratumoral TLS density (T score) correlated with lower mortality risk (T2 vs. T0: HR =0.173, P=0.003), whereas higher peritumoral TLS density (P3) predicted worse prognosis (HR =5.887, P=0.04). In vivo experiments confirmed that FOLFOX treatment enhanced TLS formation and increased infiltration of immune cells including B cells, CD4+/CD8+ T cells, and dendritic cells. Conclusions:TLSs serve as a reliable, independent prognostic biomarker in stage III CC. Their spatial distribution carries distinct prognostic implications, and FOLFOX-induced TLS formation suggests a dual role in cytotoxicity and immune activation. Incorporating TLS assessment into clinical workflows may improve risk stratification and guide personalized treatment, especially in designing immunochemotherapy strategies.

The epidemiological associations between central nervous system diseases and cancers have been widely studied, but the shared genetic basis and etiology between these joint phenotypes remain unclear. To explore this issue, we utilized genome-wide association study summary data to investigate the shared genetic architecture and causality between 10 central nervous system diseases and 14 cancers. We employed multiple statistical genetic approaches, including global and local genetic correlation, Mendelian randomization, shared loci and genes, and shared tissues and cell-types to systematically and robustly explore the common genetic basis and causal relationships between central nervous system diseases and cancers. Our results revealed genetic correlations between schizophrenia and both lung cancer and breast cancer, including estrogen receptor-positive breast cancer, as well as between neuroticism and both lung cancer and ovarian cancer, including serous ovarian cancer. We found causal relationships between schizophrenia and lung cancer (OR = 1.14, P = 0.009) and breast cancer (OR = 1.05, P = 3.00 × 10-5). When the whole genome was partitioned, significant local correlations of schizophrenia with breast cancer and lung cancer were further discovered within 14 specific genomic regions. Using cross-trait meta-analysis, we identified 24 pleiotropic loci associated with the two joint phenotypes. Using summary-data-based Mendelian randomization, we further identified eight functional genes shared between schizophrenia and both breast cancer and lung cancer, neuroticism and ovarian cancer. Additionally, we observed consistent patterns of single-nucleotide polymorphism heritability enrichment for schizophrenia and lung cancer in T lymphocytes. Our study provides insights into the genetic underpinnings and causal relationships of comorbidities between central nervous system diseases and cancers.

Introduction : Robotic-assisted complete mesorectal excision (RATME) is increasingly being used by colorectal surgeons. Most surgeons consider RATME a safe method, and believe it can facilitate total mesorectal excision (TME) in rectal cancer, and may potentially have advantages over intersphincteric resection (ISR) and anus preservation. Therefore, this trial was designed to investigate whether RATME has technical advantages and can increase the ISR rate compared with laparoscopic-assisted TME (LATME) in patients with middle and low rectal cancer. Methods and analysis : This is a multicenter, superiority, randomized controlled trial designed to compare RATME and LATME in middle and low rectal cancer. The primary endpoint is the ISR rate. The secondary endpoints are coloanal anastomosis (CAA) rate, conversion to open surgery, conversion to transanal TME (TaTME), abdominoperineal resection (APR) rate, postoperative morbidity and mortality within 30 days, pathological outcomes,long-term survival outcomes, functional outcomes,and quality of life. In addition, certain measurements will be conducted to ensure quality and safety, including centralized photography review and semiannual assessment. Discussion : This trial will clarify if RATME improves ISR and promotes anus preservation in patients with mid- and low-rectal cancer. Furthermore, this trial will provide evidence on the optimal treatment strategies for RATME and LATME in patients with mid- and low-rectal cancer regarding improved operational safety. Trial registration : The trial has been registered on ClinicalTrials.gov website, NCT06105203.

Methods Using Medical Subject Headings (MeSH) terms and keywords, a comprehensive electronic literature search was performed of the Embase, Medline, and the Cochrane Library databases from the inception of each database until October 04, 2023, in order to identify randomized controlled trials (RCTs) comparing AI-assisted with standard colonoscopy for detecting colorectal neoplasia. Primary outcomes included AMR, ADR, and adenomas detected per colonoscopy (APC). Secondary outcomes comprised the poly missed detection rate (PMR), poly detection rate (PDR), and poly detected per colonoscopy (PPC). We utilized random-effects meta-analyses with Hartung-Knapp adjustment to consolidate results. The prediction interval (PI) and I2 statistics were utilized to quantify between-study heterogeneity. Moreover, meta-regression and subgroup analyses were performed to investigate the potential sources of heterogeneity. This systematic review and meta-analysis is registered with PROSPERO (CRD42023428658). Findings This study encompassed 33 trials involving 27,404 patients. Those undergoing AI-aided colonoscopy experienced a significant decrease in PMR (RR, 0.475; 95% CI, 0.294-0.768; I2 = 87.49%) and AMR (RR, 0.495; 95% CI, 0.390-0.627; I2 = 48.76%). Additionally, a significant increase in PDR (RR, 1.238; 95% CI, 1.158-1.323; I2 = 81.67%) and ADR (RR, 1.242; 95% CI, 1.159-1.332; I2 = 78.87%), along with a significant increase in the rates of PPC (IRR, 1.388; 95% CI, 1.270-1.517; I2 = 91.99%) and APC (IRR, 1.390; 95% CI, 1.277-1.513; I2 = 86.24%), was observed. This resulted in 0.271 more PPCs (95% CI, 0.144-0.259; I2 = 65.61%) and 0.202 more APCs (95% CI, 0.144-0.259; I2 = 68.15%).Interpretation AI-aided colonoscopy significantly enhanced the detection of colorectal neoplasia detection, likely by reducing the miss rate. However, future studies should focus on evaluating the cost-effectiveness and long-term benefits of AI-aided colonoscopy in reducing cancer incidence. Copyright (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

IntroductionColon cancer is the 3rd most prevalent cancer worldwide, with more than 900,000 deaths annually. Chemotherapy, targeted treatment, and immunotherapeutic treatment are the three cornerstones of colon cancer treatment; however, the occurrence of immune therapy resistance is the most pressing problem to solve. Copper is a mineral nutrient that is both beneficial and potentially toxic to cells and is increasingly implicated in cell proliferation and death pathways. Cuproplasia is characterized by copper-dependent cell growth and proliferation. This term encompasses both neoplasia and hyperplasia and describes the primary and secondary effects of copper. The connection between copper and cancer has been noted for decades. However, the relationship between cuproplasia and colon cancer prognosis remains unclear.MethodIn this study, we applied bioinformatics approaches including WGCNA, GSEA and etc. to delineate cuproplasia characterization of colon cancer, set up a robust Cu_riskScore model based on cuproplasia-relevant genes and found its relevant biological processes use qRT-pCR to validate our results on our cohort.ResultThe Cu_riskScore is found to be relevant to Stage and MSI-H subtype, and some biological processes including MYOGENESIS and MYC TARGETS. The Cu_riskScore high and low groups also showed different immune infiltration pattern and genomic traits. Finally, the result of our cohort showed the Cu_riskScore gene RNF113A has a marked effect in predicting immunotherapy response.DiscussionIn conclusion, we identified a cuproplasia-related gene expression signature consisting of six genes and studied the landscape of the clinical and biological characterization of this model in Colon Cancer. Furthermore, the Cu_riskScore was demonstrated to be a robust prognostic indicator and predictive factor for the benefits of immunotherapy.

Dear Editor, Colorectal cancer (CRC) is one of the most commonly diagnosed cancers and cancer-related causes of death worldwide.1 Early diagnosis is critical to provide curable treatment and improving survival rates for CRC patients.2 Circulating-free DNA (cfDNA) carrying cancer-specific methylation signature is a promising specific marker for cancer diagnosis.3 However, previous studies were based either on high-throughput sequencing or did not consider the specificity of the methylation pattern for different cancers. We aim to discover and validate a noninvasive method with type-specific DNA methylation patterns for the diagnosis of CRC. The workflow is illustrated in Figure 1 (details of the sample sources and analysis process can be found in the Supporting information). Briefly, we first compared the differentially methylated CpG sites (DMCs) between 395 CRC and 45 adjacent normal tissues from the cancer genome atlas (TCGA) dataset, and a total of 37,132 DMCs were selected based on |Δβ| > 0.20 and FDR < 0.05. We further filtered out 27,063 CpG sites due to potential noise of DNA methylation (average beta > 0.1 or < 0.9) in 1,246 samples of white blood cells (WBCs) of healthy individuals from two Gene Expression Omnibus (GEO) datasets. Finally, with the same filtering criteria as WBCs, 15 CRC-specifically hypermethylated CpG sites with average methylation levels less than 0.1 in 8,629 tissue samples from 28 other cancer types in the TCGA dataset were retained, and no CRC-specific hypomethylated CpG sites met the criteria and were retained. The heatmap showed that the 15 CpG sites (located on B3GALNT1, C6orf97, FAM72A, FAM72B, LIFR, OSMR, ZNF264, and ZNF543) well-distinguished CRC from adjacent normal tissues (Figure 2A), WBCs (Figure 2B), and 28 other types of cancer (Figure 2C) in TCGA, as well as 23 other types of cancer in GEO (Supporting information). In addition, DNA methylation has a potential role in regulating gene expression, and CpG sites, including cg14786398, were negatively correlated with their corresponding gene expression (r = −0.691, p < 0.001, Figure 2D, Supporting information). The area under curve (AUC) of the 15 CRC-specific CpG sites ranged from 0.643 to 0.903, similar to the frequently reported CpG sites of SEPT9 (0.846 to 0.967). Compared with the SEPT9, our markers have higher CRC specificity, and the misclassification rate of the 15 CpG sites in 28 other types of tumor tissues ranged from 0% to 20%, while the misclassification rates of 11 CpG sites in SEPT9 ranged from 0% to 92% (Supporting information). Furthermore, the methylation status of selected CRC-specific markers was evaluated by MethylTarget sequencing (Genesky) in CRC tissue (N = 227), adjacent normal tissue (N = 24), WBC (N = 52) and cfDNA (N = 14) samples from CRC patients and healthy controls. The candidate CpG sites of ZNF543 were significantly hypermethylated in tissues and cfDNA from CRC compared to normal tissues and cfDNA from healthy controls and were unmethylated in WBCs from both CRC and healthy controls (Figure 2E). Candidate CpG sites of B3GALNT1, C6orf97, LIFR, and ZNF264 were also hypermethylated in CRC tissues but unmethylated in normal tissues and WBCs (Supporting information). We successfully designed primers and probes for six CRC-specific markers (FAM72A, FAM72B, LIFR, OSMR, ZNF264 and ZNF543) covering 10 of 15 CpGs for further testing the methylation level of cfDNA with ddPCR-based assays (Figure 3A; Supporting information). The established three multiplex ddPCR assays (mddPCR, Assay 1, 2, 3) have superior detection sensitivity compared with traditional multiplex MethyLight (mqPCR). mqPCR assay 1 detected one methylated allele in a background of 125 unmethylated alleles (Figure 3B; limit of quantification (LOQ) = 0.8%, R2 = 0.957). In contrast, the LOQ of Assay 1 was 25-fold lower than that of mqPCR assay 1 (Figure 3C,D, Supporting information). A total of 370 blood samples were collected from 195 patients with CRC, 6 patients with hyperplastic polyps, 22 patients with advanced adenomas (AAs), 103 healthy controls, and 44 non-CRC patients with benign or malignant tumours of breast or lung. The AUCs of the three mddPCR assays for distinguishing CRC patients from healthy controls were 0.767, 0.847 and 0.771 (Figure 4A–C), respectively. Samples with detected methylated molecules were judged as positive, with a sensitivity of 57.9% for Assay 1, 71.8% for Assay 2 and 57.9% for Assay 3. The corresponding specificities were 92.2%, 94.2% and 95.1%, respectively. Furthermore, elevated methylated molecule copies were also detected in patients with AA, with positive rates of 31.8%, 22.7% and 31.8% of the three mddPCR assays. Next, we combined three mddPCR assays to evaluate the combined diagnostic performance. The AUCs of the four combination panels were 0.884, 0.821, 0.870 and 0.892, respectively (Figure 4D). Based on the optimal cutoff values, the sensitivities of the four panels were 81.5%, 70.3%, 77.9% and 84.1%, and the corresponding specificities were 89.3%, 88.3%, 90.3% and 85.4%, respectively (Figure 4D). Furthermore, the AUCs for diagnosis of non-CRC were relatively low, ranging from 0.541 to 0.599. Identification of the origin of cfDNA and the location of the cancer is critical for guiding clinical diagnosis. Currently, mSEPT9 is the only blood assay in the clinical setting for CRC screening, but its clinical usefulness is limited by its low sensitivity in early-stage CRC.4 Moreover, mSEPT9 is not a CRC-specific marker because of overlapping aberrant methylation across multiple cancers.5, 6 Recent evidence suggests that the use of tissue-specific methylation signatures will allow for tracing tissue of origin in cfDNA.7, 8 In marker discovery, we eliminated the possible confounding interference of cfDNA released by other cancer tissues or WBCs on the detection of ctDNA methylation levels in CRC. Moreover, our inhouse validation study suggested that such CRC-specific methylation patterns could be detected in tissues and cfDNA but not in WBCs. This study has several limitations. First, most of the healthy controls and non-CRC patients of our inhouse cfDNA cohort were not confirmed by colorectal endoscopy, thus, those positive results were classified as false-positives to more closely reflect the situation in the natural population in the real world, and this could have resulted in an underestimation of diagnostic performance of our mddPCR assays to a certain extent. Second, we collected a small subset of cfDNA samples from patients with AA and other non-CRC diseases, suggesting that our arrays need to be further optimized and validated in studies including more participants in the future. In conclusion, we identified a panel of CRC-specific methylation patterns by pan-cancer analysis and developed three cfDNA multiplex ddPCR assays. Our findings suggested that cfDNA methylation assays have the potential to detect early-stage CRC and its advanced precursors. However, the diagnostic performance of these arrays requires more validation before clinical implementation. This work was supported by the National Natural Science Foundation of China (Grant numbers 82073643, 81773503, and 81473055), the Heilongjiang Provincial Natural Science Foundation of China (Grant numbers ZD2021H001) and Heilongjiang Province Applied Technology Research and Development (No. GA20C016). The authors declare no conflicts of interest. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Purpose Colorectal cancer is a common malignant tumor worldwide. In China, the ratio of rectal cancer to colon cancer in terms of incidence is close to 1: 1. Low rectal cancer accounts for more than half of all cases of rectal cancer. In recent years, the proportion of rectal cancer has trended downward, however the incidence of rectal cancer in younger adults is increasing. The CACA Guidelines for Holistic Integrative Management of Rectal Cancer were edited to help improve the diagnosis and comprehensive treatment in China. Methods This guideline has been prepared by consensuses reached by the CACA Committee of Colorectal Cancer Society, based on a careful review of the latest evidence including China’s studies, and referred to domestic and international relative guidelines, also considered China’s specific national conditions and clinical practice. Results The CACA Guidelines for Holistic Integrative Management of Rectal Cancer include the epidemiology of rectal cancer, prevention and screening, diagnosis, treatment of nonmetastatic and metastatic rectal cancer, follow-up, and whole-course rehabilitation management. Conclusion Committee of Colorectal Cancer Society, Chinese Anti-Cancer Association, standardizes the diagnosis and treatment of rectal cancer in China through the formulation of the CACA Guidelines.

Background This study aimed to establish a novel quantification system of ferroptosis patterns and comprehensively analyze the relationship between ferroptosis score (FS) and the immune cell infiltration (ICI) characterization, tumor mutation burden (TMB), prognosis, and therapeutic sensitivity in left-sided and right-sided colon cancers (LCCs and RCCs, respectively). Methods We comprehensively evaluated the ferroptosis patterns in 444 LCCs and RCCs based on 59 ferroptosis-related genes (FRGs). The FS was constructed to quantify ferroptosis patterns by using principal component analysis algorithms. Next, the prognostic value and therapeutic sensitivities were evaluated using multiple methods. Finally, we performed weighted gene co-expression network analysis (WGCNA) to identify the key FRGs. The IMvigor210 cohort, TCGA-COAD proteomics cohort, and Immunophenoscores were used to verify the predictive abilities of FS and the key FRGs. Results Two ferroptosis clusters were determined. Ferroptosis cluster B demonstrated a high degree of congenital ICI and stromal-related signal enrichment with a poor prognosis. The prognosis, response of targeted inhibitors, and immunotherapy were significantly different between high and low FS groups (HSG and LSG, respectively). HSG was characterized by high TMB and microsatellite instability-high subtype with poor prognosis. Meanwhile, LSG was more likely to benefit from immunotherapy. ALOX5 was identified as a key FRG based on FS. Patients with high protein levels of ALOX5 had poorer prognoses. Conclusion This work revealed that the evaluation of ferroptosis subtypes will contribute to gaining insight into the heterogeneity in LCCs and RCCs. The quantification for ferroptosis patterns played a non-negligible role in predicting ICI characterization, prognosis, and individualized immunotherapy strategies.

Abstract Background Colorectal cancer (CRC) represents a common malignancy in gastrointestinal tract. Iodine-125 (125I) seed implantation is an emerging treatment technology for unresectable tumors. This study investigated the mechanism of 125I seed in the function of CRC cells. Methods The CRC cells were irradiated with different doses of 125I seed (0.4, 0.6 and 0.8 mCi). miR-615 expression in CRC tissues and adjacent tissues was detected by RT-qPCR. miR-615 expression was intervened with miR-615 mimic or miR-615 inhibitor, and then the CRC cells were treated with 5-AZA (methylation inhibitor). The CRC cell growth, invasion and apoptosis were measured. The methylation level of miR-615 promoter region was detected. The xenograft tumor model irradiated by 125I seed was established in nude mice. The methylation of miR-615, Ki67 expression and CRC cell apoptosis were detected. Results 125I seed irradiation repressed the growth and facilitated apoptosis of CRC cells in a dose-dependent manner. Compared with adjacent tissues, miR-615 expression in CRC tissues was downregulated and miR-615 was poorly expressed in CRC cells. Overexpression of miR-615 suppressed the growth of CRC cells. 125I seed-irradiated CRC cells showed increased miR-615 expression, reduced growth rate and enhanced apoptosis. The methylation level of miR-615 promoter region in CRC cells was decreased after 125I seed treatment. In vivo experiments confirmed that 125I seed-irradiated xenograft tumors showed reduced methylation of the miR-615 promoter and increased miR-615 expression, as well as decreased Ki67 expression and enhanced apoptosis. The target genes of miR-615 and its regulatory downstream pathway were further predicted by bioinformatics analysis. Conclusions 125I seed repressed the growth and facilitated the apoptosis of CRC cells by suppressing the methylation of the miR-615 promoter and thus activating miR-615 expression. The possible mechanism was that miR-615-5p targeted MAPK13, thus affecting the MAPK pathway and the progression of CRC.

Introduction:This study aimed to identified the key genes and sequencing metrics for predicting prognosis and efficacy of neoadjuvant chemotherapy (nCT) in rectal cancer (RC) based on genomic DNA sequencing in samples with different origin and multi-omics association database.Methods:We collected 16 RC patients and obtained DNA sequencing data from cancer tissues and plasma cell-free DNA before and after nCT. Various gene variations were analyzed, including single nucleotide variants (SNV), copy number variation (CNV), tumor mutation burden (TMB), copy number instability (CNI) and mutant-allele tumor heterogeneity (MATH). We also identified genes by which CNV level can differentiate the response to nCT. The Cancer Genome Atlas database and the Clinical Proteomic Tumor Analysis Consortium database were used to further evaluate the specific role of therapeutic relevant genes and screen out the key genes in multi-omics levels. After the intersection of the screened genes from differential expression analysis, survival analysis and principal components analysis dimensionality reduction cluster analysis, the key genes were finally identified.Results:The genes CNV level of principal component genes in baseline blood and cancer tissues could significantly distinguish the two groups of patients. The CNV of HSP90AA1, EGFR, SRC, MTOR, etc. were relatively gained in the better group compared with the poor group in baseline blood. The CNI and TMB was significantly different between the two groups. The increased expression of HSP90AA1, EGFR, and SRC was associated with increased sensitivity to multiple chemotherapeutic drugs. The nCT predictive score obtained by therapeutic relevant genes could be a potential prognostic indicator, and the combination with TMB could further refine prognostic prediction for patients. After a series of analysis in multi-omics association database, EGFR and HSP90AA1 with significant differences in multiple aspects were identified as the key predictive genes related to prognosis and the sensitivity of nCT.Discussion:This work revealed that effective combined application and analysis in multi-omics data are critical to search for predictive biomarkers. The key genes EGFR and HSP90AA1 could serve as an effective biomarker to predict prognose and neoadjuvant chemosensitivity.