A single-cell atlas characterizes dysregulation of the bone marrow immune microenvironment associated with outcomes in multiple myeloma.

Multiple Myeloma (MM) remains incurable despite advances in treatment options. Although tumor subtypes and specific DNA abnormalities are linked to worse prognosis, the impact of immune dysfunction on disease emergence and/or treatment sensitivity remains unclear. We established a harmonized consortium to generate an Immune Atlas of MM aimed at informing disease etiology, risk stratification, and potential therapeutic strategies. We generated a transcriptome profile of 1,149,344 single cells from the bone marrow of 263 newly diagnosed patients enrolled in the CoMMpass study and characterized immune and hematopoietic cell populations. Associating cell abundances and gene expression with disease progression revealed the presence of a proinflammatory immune senescence-associated secretory phenotype in rapidly progressing patients. Furthermore, signaling analyses suggested active intercellular communication involving APRIL-BCMA, potentially promoting tumor growth and survival. Finally, we demonstrate that integrating immune cell levels with genetic information can significantly improve patient stratification.

Combining the Tyrosine Kinase Inhibitor Cabozantinib and the mTORC1/2 Inhibitor Sapanisertib Blocks ERK Pathway Activity and Suppresses Tumor Growth in Renal Cell Carcinoma.

Current treatment approaches for renal cell carcinoma (RCC) face challenges in achieving durable tumor responses due to tumor heterogeneity and drug resistance. Combination therapies that leverage tumor molecular profiles could offer an avenue for enhancing treatment efficacy and addressing the limitations of current therapies. To identify effective strategies for treating RCC, we selected ten drugs guided by tumor biology to test in six RCC patient-derived xenograft (PDX) models. The multitargeted tyrosine kinase inhibitor (TKI) cabozantinib and mTORC1/2 inhibitor sapanisertib emerged as the most effective drugs, particularly when combined. The combination demonstrated favorable tolerability and inhibited tumor growth or induced tumor regression in all models, including two from patients who experienced treatment failure with FDA-approved TKI and immunotherapy combinations. In cabozantinib-treated samples, imaging analysis revealed a significant reduction in vascular density, and single-nucleus RNA sequencing (snRNA-seq) analysis indicated a decreased proportion of endothelial cells in the tumors. SnRNA-seq data further identified a tumor subpopulation enriched with cell-cycle activity that exhibited heightened sensitivity to the cabozantinib and sapanisertib combination. Conversely, activation of the epithelial-mesenchymal transition pathway, detected at the protein level, was associated with drug resistance in residual tumors following combination treatment. The combination effectively restrained ERK phosphorylation and reduced expression of ERK downstream transcription factors and their target genes implicated in cell-cycle control and apoptosis. This study highlights the potential of the cabozantinib plus sapanisertib combination as a promising treatment approach for patients with RCC, particularly those whose tumors progressed on immune checkpoint inhibitors and other TKIs. SIGNIFICANCE: The molecular-guided therapeutic strategy of combining cabozantinib and sapanisertib restrains ERK activity to effectively suppress growth of renal cell carcinomas, including those unresponsive to immune checkpoint inhibitors.

Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages.

Breast cancer is a heterogeneous disease, and treatment is guided by biomarker profiles representing distinct molecular subtypes. Breast cancer arises from the breast ductal epithelium, and experimental data suggests breast cancer subtypes have different cells of origin within that lineage. The precise cells of origin for each subtype and the transcriptional networks that characterize these tumor-normal lineages are not established. In this work, we applied bulk, single-cell (sc), and single-nucleus (sn) multi-omic techniques as well as spatial transcriptomics and multiplex imaging on 61 samples from 37 breast cancer patients to show characteristic links in gene expression and chromatin accessibility between breast cancer subtypes and their putative cells of origin. We applied the PAM50 subtyping algorithm in tandem with bulk RNA-seq and snRNA-seq to reliably subtype even low-purity tumor samples and confirm promoter accessibility using snATAC. Trajectory analysis of chromatin accessibility and differentially accessible motifs clearly connected progenitor populations with breast cancer subtypes supporting the cell of origin for basal-like and luminal A and B tumors. Regulatory network analysis of transcription factors underscored the importance of BHLHE40 in luminal breast cancer and luminal mature cells, and KLF5 in basal-like tumors and luminal progenitor cells. Furthermore, we identify key genes defining the basal-like ( PRKCA , SOX6 , RGS6 , KCNQ3 ) and luminal A/B ( FAM155A , LRP1B ) lineages, with expression in both precursor and cancer cells and further upregulation in tumors. Exhausted CTLA4-expressing CD8+ T cells were enriched in basal-like breast cancer, suggesting altered means of immune dysfunction among breast cancer subtypes. We used spatial transcriptomics and multiplex imaging to provide spatial detail for key markers of benign and malignant cell types and immune cell colocation. These findings demonstrate analysis of paired transcription and chromatin accessibility at the single cell level is a powerful tool for investigating breast cancer lineage development and highlight transcriptional networks that define basal and luminal breast cancer lineages.

Epigenetic regulation during cancer transitions across 11 tumour types.

Chromatin accessibility is essential in regulating gene expression and cellular identity, and alterations in accessibility have been implicated in driving cancer initiation, progression and metastasis1-4. Although the genetic contributions to oncogenic transitions have been investigated, epigenetic drivers remain less understood. Here we constructed a pan-cancer epigenetic and transcriptomic atlas using single-nucleus chromatin accessibility data (using single-nucleus assay for transposase-accessible chromatin) from 225 samples and matched single-cell or single-nucleus RNA-sequencing expression data from 206 samples. With over 1 million cells from each platform analysed through the enrichment of accessible chromatin regions, transcription factor motifs and regulons, we identified epigenetic drivers associated with cancer transitions. Some epigenetic drivers appeared in multiple cancers (for example, regulatory regions of ABCC1 and VEGFA; GATA6 and FOX-family motifs), whereas others were cancer specific (for example, regulatory regions of FGF19, ASAP2 and EN1, and the PBX3 motif). Among epigenetically altered pathways, TP53, hypoxia and TNF signalling were linked to cancer initiation, whereas oestrogen response, epithelial-mesenchymal transition and apical junction were tied to metastatic transition. Furthermore, we revealed a marked correlation between enhancer accessibility and gene expression and uncovered cooperation between epigenetic and genetic drivers. This atlas provides a foundation for further investigation of epigenetic dynamics in cancer transitions.

OutcropHyBNet: Hybrid Backbone Networks with Data Augmentation for Accurate Stratum Semantic Segmentation of Monocular Outcrop Images in Carbon Capture and Storage Applications.

The rapid advancement of climate change and global warming have widespread impacts on society, including ecosystems, water security, food production, health, and infrastructure. To achieve significant global emission reductions, approximately 74% is expected to come from cutting carbon dioxide (CO2) emissions in energy supply and demand. Carbon Capture and Storage (CCS) has attained global recognition as a preeminent approach for the mitigation of atmospheric carbon dioxide levels, primarily by means of capturing and storing CO2 emissions originating from fossil fuel systems. Currently, geological models for storage location determination in CCS rely on limited sampling data from borehole surveys, which poses accuracy challenges. To tackle this challenge, our research project focuses on analyzing exposed rock formations, known as outcrops, with the goal of identifying the most effective backbone networks for classifying various strata types in outcrop images. We leverage deep learning-based outcrop semantic segmentation techniques using hybrid backbone networks, named OutcropHyBNet, to achieve accurate and efficient lithological classification, while considering texture features and without compromising computational efficiency. We conducted accuracy comparisons using publicly available benchmark datasets, as well as an original dataset expanded through random sampling of 13 outcrop images obtained using a stationary camera, installed on the ground. Additionally, we evaluated the efficacy of data augmentation through image synthesis using Only Adversarial Supervision for Semantic Image Synthesis (OASIS). Evaluation experiments on two public benchmark datasets revealed insights into the classification characteristics of different classes. The results demonstrate the superiority of Convolutional Neural Networks (CNNs), specifically DeepLabv3, and Vision Transformers (ViTs), particularly SegFormer, under specific conditions. These findings contribute to advancing accurate lithological classification in geological studies using deep learning methodologies. In the evaluation experiments conducted on ground-level images obtained using a stationary camera and aerial images captured using a drone, we successfully demonstrated the superior performance of SegFormer across all categories.

Epigenetic and transcriptomic characterization reveals progression markers and essential pathways in clear cell renal cell carcinoma.

Identifying tumor-cell-specific markers and elucidating their epigenetic regulation and spatial heterogeneity provides mechanistic insights into cancer etiology. Here, we perform snRNA-seq and snATAC-seq in 34 and 28 human clear cell renal cell carcinoma (ccRCC) specimens, respectively, with matched bulk proteogenomics data. By identifying 20 tumor-specific markers through a multi-omics tiered approach, we reveal an association between higher ceruloplasmin (CP) expression and reduced survival. CP knockdown, combined with spatial transcriptomics, suggests a role for CP in regulating hyalinized stroma and tumor-stroma interactions in ccRCC. Intratumoral heterogeneity analysis portrays tumor cell-intrinsic inflammation and epithelial-mesenchymal transition (EMT) as two distinguishing features of tumor subpopulations. Finally, BAP1 mutations are associated with widespread reduction of chromatin accessibility, while PBRM1 mutations generally increase accessibility, with the former affecting five times more accessible peaks than the latter. These integrated analyses reveal the cellular architecture of ccRCC, providing insights into key markers and pathways in ccRCC tumorigenesis.

Somatic mutations can induce a noninflamed tumour microenvironment via their original gene functions, despite deriving neoantigens.

BACKGROUND: Identifying biomarkers to predict immune checkpoint inhibitor (ICI) efficacy is warranted. Considering that somatic mutation-derived neoantigens induce strong immune responses, patients with a high tumour mutational burden reportedly tend to respond to ICIs. However, there are several conflicting data. Therefore, we focused on the original function of neoantigenic mutations and their impact on the tumour microenvironment (TME). METHODS: We evaluated 88 high-frequency microsatellite instability (MSI-H) colorectal cancers and analysed the function of the identified neoantigenic mutations and their influence on programmed cell death 1 (PD-1) blockade efficacy. The results were validated using The Cancer Genome Atlas (TCGA) datasets. RESULTS: We identified frameshift mutations in RNF43 as a common neoantigenic gene mutation in MSI-H tumours. However, loss-of-function RNF43 mutations induced noninflamed TME by activating the WNT/ß-catenin signalling pathway. In addition, loss of RNF43 function induced resistance to PD-1 blockade even in neoantigen-rich tumours. TCGA dataset analyses demonstrated that passenger rather than driver gene mutations were related to the inflamed TME in diverse cancer types. CONCLUSIONS: We propose a novel concept of "paradoxical neoantigenic mutations" that can induce noninflamed TME through their original gene functions, despite deriving neoantigens, suggesting the significance of qualities as well as quantities in neoantigenic mutations.

Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer.

Pancreatic ductal adenocarcinoma is a lethal disease with limited treatment options and poor survival. We studied 83 spatial samples from 31 patients (11 treatment-naïve and 20 treated) using single-cell/nucleus RNA sequencing, bulk-proteogenomics, spatial transcriptomics and cellular imaging. Subpopulations of tumor cells exhibited signatures of proliferation, KRAS signaling, cell stress and epithelial-to-mesenchymal transition. Mapping mutations and copy number events distinguished tumor populations from normal and transitional cells, including acinar-to-ductal metaplasia and pancreatic intraepithelial neoplasia. Pathology-assisted deconvolution of spatial transcriptomic data identified tumor and transitional subpopulations with distinct histological features. We showed coordinated expression of TIGIT in exhausted and regulatory T cells and Nectin in tumor cells. Chemo-resistant samples contain a threefold enrichment of inflammatory cancer-associated fibroblasts that upregulate metallothioneins. Our study reveals a deeper understanding of the intricate substructure of pancreatic ductal adenocarcinoma tumors that could help improve therapy for patients with this disease.

Visualization and Semantic Labeling of Mood States Based on Time-Series Features of Eye Gaze and Facial Expressions by Unsupervised Learning.

This study is intended to develop a stress measurement and visualization system for stress management in terms of simplicity and reliability. We present a classification and visualization method of mood states based on unsupervised machine learning (ML) algorithms. Our proposed method attempts to examine the relation between mood states and extracted categories in human communication from facial expressions, gaze distribution area and density, and rapid eye movements, defined as saccades. Using a psychological check sheet and a communication video with an interlocutor, an original benchmark dataset was obtained from 20 subjects (10 male, 10 female) in their 20s for four or eight weeks at weekly intervals. We used a Profile of Mood States Second edition (POMS2) psychological check sheet to extract total mood disturbance (TMD) and friendliness (F). These two indicators were classified into five categories using self-organizing maps (SOM) and U-Matrix. The relation between gaze and facial expressions was analyzed from the extracted five categories. Data from subjects in the positive categories were found to have a positive correlation with the concentrated distributions of gaze and saccades. Regarding facial expressions, the subjects showed a constant expression time of intentional smiles. By contrast, subjects in negative categories experienced a time difference in intentional smiles. Moreover, three comparative experiment results demonstrated that the feature addition of gaze and facial expressions to TMD and F clarified category boundaries obtained from U-Matrix. We verify that the use of SOM and its two variants is the best combination for the visualization of mood states.

Exploration of predictive biomarkers for postoperative recurrence of stage II/III colorectal cancer using genomic sequencing.

Postoperative recurrence of colorectal cancer (CRC) eventually leads to therapeutic failure; therefore, treatment strategies based on accurate prediction of recurrence are urgently required. To identify biomarkers that can predict treatment outcomes, we compared the mutational profiles of surgically resected specimens from patients with recurrent cancer with those from patients with non-recurrent cancer. Target sequencing, whole-exome sequencing (WES), or whole-genome sequencing (WGS) was performed on 89 and 58 tumors from recurrent and non-recurrent cases, respectively. WGS revealed the driver mutations that were not detected with target sequencing or WES, including the structural variations affecting ZFP36L2. Loss of function of ZFP36L2 was frequently observed in primary tumors from recurrent cases. Furthermore, the recurrence-free survival of patients with loss of function of ZFP36L2 was significantly shorter relative to patients with no loss of ZFP36L2 function. In summary, the study demonstrated that detailed genomic analysis could help improve precision medicine for CRC.

HLA Class I Analysis Provides Insight Into the Genetic and Epigenetic Background of Immune Evasion in Colorectal Cancer With High Microsatellite Instability.

BACKGROUND & AIMS: A detailed understanding of antitumor immunity is essential for optimal cancer immune therapy. Although defective mutations in the B2M and HLA-ABC genes, which encode molecules essential for antigen presentation, have been reported in several studies, the effects of these defects on tumor immunity have not been quantitatively evaluated. METHODS: Mutations in HLA-ABC genes were analyzed in 114 microsatellite instability-high colorectal cancers using a long-read sequencer. The data were further analyzed in combination with whole-exome sequencing, transcriptome sequencing, DNA methylation array, and immunohistochemistry data. RESULTS: We detected 101 truncating mutations in 57 tumors (50%) and loss of 61 alleles in 21 tumors (18%). Based on the integrated analysis that enabled the immunologic subclassification of microsatellite instability-high colorectal cancers, we identified a subtype of tumors in which lymphocyte infiltration was reduced, partly due to reduced expression of HLA-ABC genes in the absence of apparent genetic alterations. Survival time of patients with such tumors was shorter than in patients with other tumor types. Paradoxically, tumor mutation burden was highest in the subtype, suggesting that the immunogenic effect of accumulating mutations was counterbalanced by mutations that weakened immunoreactivity. Various genetic and epigenetic alterations, including frameshift mutations in RFX5 and promoter methylation of PSMB8 and HLA-A, converged on reduced expression of HLA-ABC genes. CONCLUSIONS: Our detailed immunogenomic analysis provides information that will facilitate the improvement and development of cancer immunotherapy.

A case report of gallbladder cancer and pancreas cystic neoplasm associated with pancreaticobiliary maljunction.

INTRODUCTION AND IMPORTANCE: Pancreaticobiliary maljunction (PBM) is a rare congenital anomaly that is frequently associated with carcinoma of the biliary tract. However, there is still no clear evidence that PBM is associated with pancreatic tumors. Here we describe a case of gallbladder cancer and intraductal papillary mucinous neoplasm (IPMN) that is associated with PBM. CASE PRESENTATION: A 72-year-old man underwent a cholecystectomy with hepatectomy (S4a + S5) and regional lymph node dissection for gallbladder adenocarcinoma invading the front lobe branch of the hepatic artery. A pylorus-preserving pancreaticodudenectomy was also performed for pancreatic IPMN. CLINICAL DISCUSSION: Presence of mucin type 6 (MUC6) -positive pyloric gland metaplasia in both the dilated pancreatic duct and the gallbladder background mucosa suggests that pancreatic IPMN and gallbladder cancer may have a common phenotypic origin. Additionally, analysis of 41 reported cases of pancreatic cancer associated with PBM revealed that in all metachronous multiple cancer cases, biliary tract cancer preceded the pancreatic cancer with congenital biliary dilatation accompanied by PBM. The analysis also revealed an increased proportion of pancreatic cancer cases with PBM in patients who had not undergone a flow diversion procedure located in pancreatic head. CONCLUSION: We show an interesting relationship between pancreatic/gallbladder cancer and PBM. More comprehensive evaluations of the whole pancreaticobiliary system in follow-up of patients with PBM is required to understand the full extent of this relationship.

Development of Drone-Mounted Multiple Sensing System with Advanced Mobility for In Situ Atmospheric Measurement: A Case Study Focusing on PM2.5 Local Distribution.

This study was conducted using a drone with advanced mobility to develop a unified sensor and communication system as a new platform for in situ atmospheric measurements. As a major cause of air pollution, particulate matter (PM) has been attracting attention globally. We developed a small, lightweight, simple, and cost-effective multi-sensor system for multiple measurements of atmospheric phenomena and related environmental information. For in situ local area measurements, we used a long-range wireless communication module with real-time monitoring and visualizing software applications. Moreover, we developed four prototype brackets with optimal assignment of sensors, devices, and a camera for mounting on a drone as a unified system platform. Results of calibration experiments, when compared to data from two upper-grade PM2.5 sensors, demonstrated that our sensor system followed the overall tendencies and changes. We obtained original datasets after conducting flight measurement experiments at three sites with differing surrounding environments. The experimentally obtained prediction results matched regional PM2.5 trends obtained using long short-term memory (LSTM) networks trained using the respective datasets.

Development of Invisible Sensors and a Machine-Learning-Based Recognition System Used for Early Prediction of Discontinuous Bed-Leaving Behavior Patterns.

This paper presents a novel bed-leaving sensor system for real-time recognition of bed-leaving behavior patterns. The proposed system comprises five pad sensors installed on a bed, a rail sensor inserted in a safety rail, and a behavior pattern recognizer based on machine learning. The linear characteristic between loads and output was obtained from a load test to evaluate sensor output characteristics. Moreover, the output values change linearly concomitantly with speed to attain the sensor with the equivalent load. We obtained benchmark datasets of continuous and discontinuous behavior patterns from ten subjects. Recognition targets using our sensor prototype and their monitoring system comprise five behavior patterns: sleeping, longitudinal sitting, lateral sitting, terminal sitting, and leaving the bed. We compared machine learning algorithms of five types to recognize five behavior patterns. The experimentally obtained results revealed that the proposed sensor system improved recognition accuracy for both datasets. Moreover, we achieved improved recognition accuracy after integration of learning datasets as a general discriminator.

Differential regulation of CpG island methylation within divergent and unidirectional promoters in colorectal cancer.

The silencing of tumor suppressor genes by promoter CpG island (CGI) methylation is an important cause of oncogenesis. Silencing of MLH1 and BRCA1, two examples of oncogenic events, results from promoter CGI methylation. Interestingly, both MLH1 and BRCA1 have a divergent promoter, from which another gene on the opposite strand is also transcribed. Although studies have shown that divergent transcription is an important factor in transcriptional regulation, little is known about its implication in aberrant promoter methylation in cancer. In this study, we analyzed the methylation status of CGI in divergent promoters using a recently enriched transcriptome database. We measured the extent of CGI methylation in 119 colorectal cancer (CRC) clinical samples (65 microsatellite instability high [MSI-H] CRC with CGI methylator phenotype, 28 MSI-H CRC without CGI methylator phenotype and 26 microsatellite stable CRC) and 21 normal colorectal tissues using Infinium MethylationEPIC BeadChip. We found that CGI within divergent promoters are less frequently methylated than CGI within unidirectional promoters in normal cells. In the genome of CRC cells, CGI within unidirectional promoters are more vulnerable to aberrant methylation than CGI within divergent promoters. In addition, we identified three DNA sequence motifs that correlate with methylated CGI. We also showed that methylated CGI are associated with genes whose expression is low in normal cells. Thus, we here provide fundamental observations regarding the methylation of divergent promoters that are essential for the understanding of carcinogenesis and development of cancer prevention strategies.

Fusion Kinases Identified by Genomic Analyses of Sporadic Microsatellite Instability-High Colorectal Cancers.

PURPOSE: Colorectal cancers with microsatellite instability-high (MSI-H) status, due to mismatch repair deficiency, are associated with poor patient outcomes after relapse. We aimed to identify novel therapeutic targets for them. EXPERIMENTAL DESIGN: We performed MSI analyses of over 2,800 surgically resected colorectal tumors obtained from consecutive patients treated in Japan from 1998 through June 2016. Whole-exome sequencing, transcriptome sequencing, and methylation analyses were performed on 149 of 162 tumors showing MSI in BAT25 and BAT26 loci. We analyzed patient survival times using Bonferroni-adjusted log-rank tests. RESULTS: Sporadic MSI-H colorectal cancers with promoter methylation of MLH1 (called MM) had a clinicopathological profile that was distinct from that of colorectal cancers of patients with germline mutations (Lynch syndrome, LS-associated) or somatic, Lynch-like mutations in mismatch repair genes. MM tumors had more insertions and deletions and more recurrent mutations in BRAF and RNF43 than LS-associated or Lynch-like MSI-H tumors. Eleven fusion kinases were exclusively detected in MM MSI-H colorectal cancers lacking oncogenic KRAS/BRAF missense mutations and were associated with worse post-relapse prognosis. We developed a simple method to identify MM tumors and applied it to a validation cohort of 28 MSI-H colorectal cancers, identifying 16 MM tumors and 2 fusion kinases. CONCLUSIONS: We discovered that fusion kinases are frequently observed among sporadic MM MSI-H colorectal cancers. The new method to identify MM tumors enables us to straightforwardly group MSI-H patients into candidates of LS or fusion kinase carriers.

Integrative analysis of genomic alterations in triple-negative breast cancer in association with homologous recombination deficiency.

Triple-negative breast cancer (TNBC) cells do not express estrogen receptors, progesterone receptors, or human epidermal growth factor receptor 2. Currently, apart from poly ADP-ribose polymerase inhibitors, there are few effective therapeutic options for this type of cancer. Here, we present comprehensive characterization of the genetic alterations in TNBC performed by high coverage whole genome sequencing together with transcriptome and whole exome sequencing. Silencing of the BRCA1 gene impaired the homologous recombination pathway in a subset of TNBCs, which exhibited similar phenotypes to tumors with BRCA1 mutations; they harbored many structural variations (SVs) with relative enrichment for tandem duplication. Clonal analysis suggested that TP53 mutations and methylation of CpG dinucleotides in the BRCA1 promoter were early events of carcinogenesis. SVs were associated with driver oncogenic events such as amplification of MYC, NOTCH2, or NOTCH3 and affected tumor suppressor genes including RB1, PTEN, and KMT2C. Furthermore, we identified putative TGFA enhancer regions. Recurrent SVs that affected the TGFA enhancer region led to enhanced expression of the TGFA oncogene that encodes one of the high affinity ligands for epidermal growth factor receptor. We also identified a variety of oncogenes that could transform 3T3 mouse fibroblasts, suggesting that individual TNBC tumors may undergo a unique driver event that can be targetable. Thus, we revealed several features of TNBC with clinically important implications.

Usefulness of preoperative CT colonography for colon cancer.

BACKGROUND: Computed tomographic colonography (CTC) is reported to be feasible for screening of colorectal polyps; however, its efficacy in preoperative workup remains unknown. This study was done to define our CTC methodology and assess CTC's potential for preoperative examination in patients with colon cancer. METHODS: A total of 86 colon cancer patients underwent CTC prior to laparoscopic colectomy in our department from February 2014 to November 2015. The location of primary colon cancer determined by CTC was compared with that confirmed during the surgery. CTC was performed just after preoperative colonoscopy; for a small colon cancer, we performed clipping during colonoscopy to enhance CTC detectability. We classified wall deformities and compared them with the pathological T stage. RESULTS: CTC accurately located all 87 primary colon cancers prior to surgery. No patient experienced complications associated with CTC. The deformity classification correlated significantly with the pathological T stage (p < 0.001, Kruskal-Wallis nonparametric tests). CTC provided reconstructed images depicting the feeding artery of the primary colon cancer; feeding artery information obtained by CTC facilitated precise lymph node dissection. CONCLUSION: CTC appears to be a feasible and useful preoperative examination modality for colon cancer treatment.