Unraveling the role of tumor sidedness in prognosis of stage II colon cancer.

Background: Stage II colon cancer has varying risks for metastasis, and treatment strategies depend on molecular and clinicopathological features. While tumor-sidedness is a well-accepted prognostic factor for stage III/IV colon cancer, its role in stage II is controversial. Understanding its effect in stage II is crucial for improving treatment strategies. Methods: We analyzed clinical and follow-up data of colon cancer from the Surveillance, Epidemiology, and End Results database (2004-2017). Patients were divided into a primary study cohort (2010-2017) and a validation cohort (2004-2009). The baseline characteristics between right-sided colon cancer (RCC) and left-sided colon cancer (LCC) groups were compared. Moreover, the effect of tumor size on cancer-specific survival (CSS) was evaluated using Kaplan-Meier analysis. Results: The study involved 87,355 patients in the study cohort and 65,858 in the validation cohort. Of the study cohort, 52.3% were diagnosed with RCC. The median age was 64 years old, with 48.5% females and 76.8% of white people. In addition, stage II RCC showed better CSS compared with LCC (5-year CSS 88.0% vs 85.5%, P < 0.001), while stage III/IV RCC demonstrated poorer outcomes. Multivariate Cox regression analysis identified that the right-sidedness was a positive prognostic factor in stages I/II but negative in stages III (HR 1.10, P < 0.001) and IV (HR 1.26, P < 0.001). Chemotherapy rates decreased in RCC, particularly in stage II (RCC vs LCC: 16.2% vs 28.5%, P < 0.001). Subgroup analysis, stratified by T3/T4 stages and chemotherapy status, further highlighted better survival outcomes in RCC. Conclusions: RCC is associated with a significantly better prognosis in stage II. The importance of considering tumor-sidedness in clinical decision-making and the design of future clinical trials should be emphasized.

Advancing urban traffic accident forecasting through sparse spatio-temporal dynamic learning.

Traffic accidents have emerged as one of the most public health safety matters, raising concerns from both the public and urban administrators. The ability to accurately predict traffic accident not only supports the governmental decision-making in advance but also enhances public confidence in safety measures. However, the efficacy of traditional spatio-temporal prediction models are compromised by the skewed distributions and sparse labeling of accident data. To this end, we propose a Sparse Spatio-Temporal Dynamic Hypergraph Learning (SST-DHL) framework that captures higher-order dependencies in sparse traffic accidents by combining hypergraph learning and self-supervised learning. The SST-DHL model incorporates a multi-view spatiotemporal convolution block to capture local correlations and semantics of traffic accidents, a cross-regional dynamic hypergraph learning model to identify global spatiotemporal dependencies, and a two-supervised self-learning paradigm to capture both local and global spatiotemporal patterns. Through experimentation on New York City and London accident datasets, we demonstrate that our proposed SST-DHL exhibits significant improvements compared to optimal baseline models at different sparsity levels. Additionally, it offers enhanced interpretability of results by elucidating complex spatio-temporal dependencies among various traffic accident instances. Our study demonstrates the effectiveness of the SST-DHL framework in accurately predicting traffic accidents, thereby enhancing public safety and trust.

Identifying the Spatial Architecture That Restricts the Proximity of CD8+ T Cells to Tumor Cells in Pancreatic Ductal Adenocarcinoma.

The anti-tumor function of CD8+ T cells is dependent on their proximity to tumor cells. Current studies have focused on the infiltration level of CD8+ T cells in the tumor microenvironment, while further spatial information, such as spatial localization and inter-cellular communication, have not been defined. In this study, co-detection by indexing (CODEX) was designed to characterize PDAC tissue regions with seven protein markers in order to identify the spatial architecture that regulates CD8+ T cells in human pancreatic ductal adenocarcinoma (PDAC). The cellular neighborhood algorithm was used to identify a total of six conserved and distinct cellular neighborhoods. Among these, one unique spatial architecture of CD8+ T and CD4+ T cell-enriched neighborhoods enriched the majority of CD8+ T cells, but heralded a poor prognosis. The proximity analysis revealed that the CD8+ T cells in this spatial architecture were significantly closer to themselves and the CD4+ T cells than to the tumor cells. Collectively, we identified a unique spatial architecture that restricted the proximity of CD8+ T cells to tumor cells in the tumor microenvironment, indicating a novel immune evasion mechanism of pancreatic ductal adenocarcinoma in a topologically regulated manner and providing new insights into the biology of PDAC.

Alternative approaches to modeling heterogeneity to analyze injury severity sustained by motorcyclists in two-vehicle crashes.

The presence of unobserved factors in the motorcycle involved two-vehicle crashes (MV) data could lead to heterogenous associations between observed factors and injury severity sustained by motorcyclists. Capturing such heterogeneities necessitates distinct methodological approaches, of which random and scale heterogeneity models are paramount. Herein, we undertake an empirical evaluation of random and scale heterogeneity models, exploring their efficacy in delineating the influence of external determinants on the degree of injury severity in crashes. Within the effects of scale heterogeneity, this study delves into two dominant models: the scaled multinomial logit model (S-MNL) and its generalized counterpart, the G-MNL, which encompasses both the S-MNL and the random parameters multinomial logit model (RPL). While the random heterogeneity domain is represented by the random parameters multinomial logit and an upgraded variant - the random parameters multinomial logit model with heterogeneity in means and variances (RPLHMV). Motorcycle involved two-vehicle crashes data were extracted from the UK STATS19 dataset from 2016 to 2020. Likelihood ratio tests are computed to assess the temporal variability of the significant factors. The test result demonstrates the temporal variations over a five-year study period. Some very important differences started to show up across the years based on the model estimation results: that the RPLHMV model statistically outperforms the G-MNL model in the 2016, 2018, and 2019 models, while the S-MNL model is statistically superior in the 2017 and 2020 years. These important findings suggest that the origin of heterogeneity in explaining factor weights can be captured by scale effects, not just random heterogeneity. In addition, the model results further show that motorcyclists' injury severities are significantly affected by motorcycle-related characteristics; there is the added factor of external influences, such as non-motorcycle drivers (males, young drivers, and elderly drivers) and vehicles (the moving status, age, and types of vehicles) that collide with motorcycles. The results of this paper are anticipated to help policymakers develop effective strategies to mitigate motorcycle involved two-vehicle crashes by implementing appropriate measures.

High-throughput computational materials screening of transition metal peroxides.

Semiconductor materials of abnormal stoichiometric ratio often exhibit unique properties, yet it is still a challenge to determine the structures of such materials in an efficient way. Herein, we propose a method for structurally biased screening according to the coordination numbers and the numbers of Wyckoff positions, balancing the atom local environment and the global symmetry of structures. Based on first-principles calculations, we have predicted two metastable peroxides P21/c-ScO2 and Pmmn-TiO3 with more than six coordination points. For these two structures, the most stable intrinsic defect is the oxygen vacancy (VO) at the peroxide anion (O2-2), which induces the absence of antibonding orbital formed by O2-2 near the valence band maximum. With the introduction of VO, the decrease of coordination numbers leads to charge recombination, and results in the appearance of an ordered phase TiO2.5 with stronger Ti-O orbital hybridization. The proposed method presents a promising and feasible approach for the screening of novel compounds.

Inflammasome activity is controlled by ZBTB16-dependent SUMOylation of ASC.

Inflammasome activity is important for the immune response and is instrumental in numerous clinical conditions. Here we identify a mechanism that modulates the central Caspase-1 and NLR (Nod-like receptor) adaptor protein ASC (apoptosis-associated speck-like protein containing a CARD). We show that the function of ASC in assembling the inflammasome is controlled by its modification with SUMO (small ubiquitin-like modifier) and identify that the nuclear ZBTB16 (zinc-finger and BTB domain-containing protein 16) promotes this SUMOylation. The physiological significance of this activity is demonstrated through the reduction of acute inflammatory pathogenesis caused by a constitutive hyperactive inflammasome by ablating ZBTB16 in a mouse model of Muckle-Wells syndrome. Together our findings identify an further mechanism by which ZBTB16-dependent control of ASC SUMOylation assembles the inflammasome to promote this pro-inflammatory response.

Generalized Octet Rule with Fractional Occupancies for Boron.

The octet rule is a fundamental theory in the chemical bonding of main-group elements, which achieve stable configurations by gaining, losing, or sharing electrons. However, the conventional octet rule, as depicted through Lewis structures, is inadequate for describing the electron delocalization in boron allotropes and boron-rich compounds due to the electron deficiency of boron. To address this, we introduce the concept of fractional electron occupancies, which more accurately reflect the electron delocalization in boron systems. Based on this, we propose a generalized octet rule that provides a more comprehensive understanding of the complex bonding configurations in boron allotropes and boron-rich compounds. Importantly, our predictions for α-B12 are validated by both first-principles calculations and existing experimental data. Beyond boron, this generalized octet rule is also applicable to systems with multiple resonance structures.

SUMOylation of the ubiquitin ligase component KEAP1 at K39 upregulates NRF2 and its target function in lung cancer cell proliferation.

Nuclear Factor Erythroid 2-Related Factor 2 (NRF2) is important for the expression of genes associated with oxidative stress. The levels of NRF2 are controlled by Kelch-like ECH-associated protein 1 (KEAP1)-dependent degradation. Although oxidative stress is known to suppress KEAP1 activity to stabilize the levels of NRF2, the mechanism for this control is unclear. Here, we identify that KEAP1 is modified by SUMO1 at the lysine residue position 39 (K39). Arginine replacement of this lysine (K39R) in KEAP1 did not affect its stability, subcellular localization, or dimerization but promoted the formation of the Cullin 3 ubiquitin ligase and increased NRF2 ubiquitination. This was accompanied by decreased NRF2 expression. Gene reporter assays showed that the transcription of antioxidant response elements was heightened in KEAP1-WT cells compared to cells expressing the KEAP1-K39R SUMO1 substrate mutant. Consistent with this, chromatin immunoprecipitation assays revealed higher NRF2 binding to the promoter regions of antioxidant genes in cells expressing the KEAP1-WT compared to the KEAP1-K39R mutant protein in H1299 lung cancer cell. The significance of this suppression of KEAP1 activity by its SUMOylation was tested in a subcutaneous tumor model of H1299 lung cancer cell lines that differentially expressed the WT and K39R KEAP1 constructs. This model showed that mutating the SUMOylation site on KEAP1 altered the production of reactive oxygen species and suppressed tumor growth. Taken together, our study recognizes that NRF2-dependent redox control is regulated by the SUMOylation of KEAP1. These findings identify a potential new therapeutic option to counteract oxidative stress.

High Concentration Intrinsic Defects in MnSb2Te4.

MnSb2Te4 has a similar structure to an emerging material, MnBi2Te4. According to earlier theoretical studies, the formation energy of Mn antisite defects in MnSb2Te4 is negative, suggesting its inherent instability. This is clearly in contrast to the successful synthesis of experimental samples of MnSb2Te4. Here, the growth environment of MnSb2Te4 and the intrinsic defects are correspondingly investigated. We find that the Mn antisite defect is the most stable defect in the system, and a Mn-rich growth environment favors its formation. The thermodynamic equilibrium concentrations of the Mn antisite defects could be as high as 15% under Mn-poor conditions and 31% under Mn-rich conditions. It is also found that Mn antisite defects prefer a uniform distribution. In addition, the Mn antisite defects can modulate the interlayer magnetic coupling in MnSb2Te4, leading to a transition from the ideal antiferromagnetic ground state to a ferromagnetic state. The ferromagnetic coupling effect can be further enhanced by controlling the defect concentration.

BRCA genes as candidates for colorectal cancer genetic testing panel: systematic review and meta-analysis.

BACKGROUND: Breast cancer susceptibility gene (BRCA) mutation carriers are at an increased risk for breast, ovarian, prostate and pancreatic cancers. However, the role of BRCA is unclear in colorectal cancer; the results regarding the association between BRCA gene mutations and colorectal cancer risk are inconsistent and even controversial. This study aimed to investigate whether BRCA1 and BRCA2 gene mutations are associated with colorectal cancer risk. METHODS: In this systematic review, we searched PubMed/MEDLINE, Embase and Cochrane Library databases, adhering to PRISMA guidelines. Study quality was assessed using the Newcastle-Ottawa Scale (NOS). Unadjusted odds ratios (ORs) were used to estimate the probability of Breast Cancer Type 1 Susceptibility gene (BRCA1) and Breast Cancer Type 2 Susceptibility gene (BRCA2) mutations in colorectal cancer patients. The associations were evaluated using fixed effect models. RESULTS: Fourteen studies were included in the systematic review. Twelve studies, including seven case-control and five cohort studies, were included in the meta-analysis. A significant increase in the frequency of BRCA1 and BRCA2 mutations was observed in patients with colorectal cancer [OR = 1.34, 95% confidence interval (CI) = 1.02-1.76, P = 0.04]. In subgroup analysis, colorectal cancer patients had an increased odds of BRCA1 (OR = 1.48, 95% CI = 1.10-2.01, P = 0.01) and BRCA2 (OR = 1.56, 95% CI = 1.06-2.30, P = 0.02) mutations. CONCLUSIONS: BRCA genes are one of the genes that may increase the risk of developing colorectal cancer. Thus, BRCA genes could be potential candidates that may be included in the colorectal cancer genetic testing panel.

Evaluating alternate discrete outcome frameworks for modeling riders' red light running behavior.

This paper aims to empirically evaluate the ordered and unordered discrete outcome frameworks to approach riders' red-light running (RLR) decisions and compare the differences in influencing factors between riders' risk-taking and opportunistic RLR behaviors. A total of 2057 cyclist samples approaching the intersections during red signals were observed by video in Beijing, China. To better capture the unobserved heterogeneity, apart from the traditional models, three advanced models including the random thresholds random parameters hierarchical ordered logit (RTRPHOL) model, the random parameters logit model with heterogeneity in means and variances (RPLHMV) model, and the correlated random parameters logit model with heterogeneity in means (CRPLHM), are developed. Results show that: 1) the unordered framework statistically outperformed its ordered counterparts, and the RPLHMV and CRPLHM models are statistically better than others. 2) The female and e-bicycle indicators produce a heterogeneity-in-means effect, and the low-volume and left-side indicators produce a heterogeneity-in-variances effect. 3) e-bike riders and riders from the right side are more inclined to have risk-taking behavior than opportunistic behavior, and both RLR behaviors of cyclists are most susceptible to the number of violating individual indicator. Findings illustrate that multilayer unobserved heterogeneity should be adequately considered in developing precise micro-simulation and practical guidance in traffic safety.

Diagnostic Value of Inflammation-Related Indicators in Distinguishing Early Colon Cancer and Adenomatous Polyps.

BACKGROUND: There are few clinical symptoms in early colorectal cancer, so it is necessary to find a simple and economical tumor detection index for auxiliary diagnosis. This study aims to explore the diagnostic value of preoperative inflammation-related indicators, such as neutrophil, lymphocyte, platelet count, platelet to lymphocyte ratio (PLA), neutrophil to lymphocyte ratio (NLR), and systemic immune-inflammation index (SII), for early colorectal cancer, and determine whether inflammation-related indicators can provide more accurate diagnostic judgment for patients. METHODS: This study was a retrospective study. Patients who were first diagnosed with colorectal cancer or colorectal adenomatous polyp at Beijing Friendship Hospital from October 2016 to October 2017 were retrospectively collected. According to inclusion and exclusion criteria, a total of 342 patients were included, including 216 patients with colorectal cancer and 126 patients with colorectal adenomatous polyp. Fasting venous blood and other clinical features were collected to compare the differences between colorectal cancer and colorectal adenoma. RESULTS: There were statistically significant differences in age, carcinoembryonic antigen, albumin, hemoglobin, mean platelet volume, lymphocyte, monocyte, NLR, PLA, SII, and mean platelet volume to platelet count ratio between colorectal cancer group and colorectal adenoma group (P < .05), and a Nomogram model was established. Using inflammatory markers to differentiate colorectal and colorectal polyps produced greater AUC than using tumor markers alone (.846 vs .695). CONCLUSION: Inflammation-related indicators, such as lymphocyte, monocyte, and mean platelet volume, may serve as potential indicators to assist in the diagnosis of early colorectal cancer.

Room-Temperature Transient Hydrogen Uptake of MgH2 Induced by Nb-Doped TiO2 Solid-Solution Catalysts.

The practical applications of MgH2 as a high-density hydrogen carrier depend heavily on efficient and low-cost catalysts to accelerate the dehydriding/hydriding reactions at moderate temperatures. In the present work, this issue is addressed by synthesizing Nb-doped TiO2 solid-solution-type catalysts that dramatically improve the hydrogen sorption performances of MgH2. The catalyzed MgH2 can absorb 5 wt % of H2 even at room temperature for 20 s, release 6 wt % of H2 at 225 °C within 12 min, and the complete dehydrogenation can be achieved at 150 °C under a dynamic vacuum atmosphere. Density functional theory calculations reveal that Nb doping introduces Nb 4d orbitals with stronger interaction with H 1s into the density of states of TiO2. This considerably enhances both the adsorption and dissociation ability of the H2 molecule on the catalysts surface and the hydrogen diffusion across the specific Mg/Ti(Nb)O2 interface. The successful implementation of solid solution-type catalysts in MgH2 offers a demonstration and inspiration for the development of high-performance catalysts and solid-state hydrogen storage materials.

Exact results for the residual entropy of ice hexagonal monolayer.

Since the problem of the residual entropy of square ice was exactly solved, exact solutions for two-dimensional realistic ice models have been of interest. In this work, we study the exact residual entropy of ice hexagonal monolayer in two cases. In the case that the external electric field along the z-axis exists, we map the hydrogen configurations into the spin configurations of the Ising model on the kagome lattice. By taking the low temperature limit of the Ising model, we derive the exact residual entropy, which agrees with the result determined previously from the dimer model on the honeycomb lattice. In another case that the ice hexagonal monolayer is under the periodic boundary conditions in the cubic ice lattice, the residual entropy has not been studied exactly. For this case, we employ the six-vertex model on the square lattice to represent the hydrogen configurations obeying the ice rules. The exact residual entropy is obtained from the solution of the equivalent six-vertex model. Our work provides more examples of the exactly soluble two-dimensional statistical models.

Sarcobesity, but not visceral fat, is an independent risk factor for complications after radical resection of colorectal cancer.

Background: The influence of body composition on the outcome of colorectal cancer surgery is controversial. The aim of this study was to evaluate the effects of visceral obesity and sarcobesity on the incidence of total and surgical complications after radical resection of colorectal cancer. Methods: We collected a total of 426 patients who underwent elective radical resection of colorectal cancer at Beijing Friendship Hospital, Capital Medical University from January 2017 to May 2018. According to the inclusion and exclusion criteria, 387 patients were finally included. A CT scan at the level of the L3-L4 intervertebral disk was selected to measure the values of visceral fat area and skeletal muscle area. Multivariate analysis was used to explore the independent risk/protective factors affecting postoperative complications. Results: 128 (33.1%) patients developed complications, and 44 (11.4%) patients developed major complications. Among them, 111 patients developed surgical complications and 21 developed medical complications. Visceral fat area (Z = -3.271, p = 0.001), total fat area (Z = -2.613, p = 0.009), visceral fat area to subcutaneous fat area ratio (V/S, Z = -2.633, p = 0.008), and sarcobesity index (Z = -2.282, p = 0.023) were significantly associated with total complications. Visceral fat area (Z = -2.119, p = 0.034) and V/S (Z = -2.010, p = 0.044) were significantly associated with total surgical complications. Sarcobesity index, smoking, stoma, blood loss, surgery time, and American Society of Anesthesiology (ASA) score were selected as risk factors for total postoperative complications according to LASSO regression. Multivariate logistic regression analysis suggested that sarcobesity index was an independent risk factor for postoperative total complications and surgical complications. Subgroup analysis suggested that albumin level was an independent protective factor for postoperative total complications in male patients. Smoking, operative time, and sarcobesity index were independent risk factors, and cholesterol was an independent protective factor for total postoperative complications in female patients. Conclusion: Increased sarcobesity index is an independent risk factor for postoperative complications in patients with colorectal cancer, while visceral fat area is not. For female patients, smoking, operation time, and obesity index are independent risk factors for postoperative complications, while cholesterol is an independent protective factor. For male patients, serum albumin is an independent protective factor for postoperative complications.

Bivariate joint analysis of injury severity of drivers in truck-car crashes accommodating multilayer unobserved heterogeneity.

Truck-involved crashes, especially truck-car crashes, are associated with serious and even fatal injuries, thus necessitating an in-depth analysis. Prior research focused solely on examining the injury severity of truck drivers or developed separate performance models for truck and car drivers. However, the severity of injuries to both drivers in the same truck-car crash may be interrelated, and influencing factors of injury severities sustained by the two parties may differ. To address these concerns, a random parameter bivariate probit model with heterogeneity in means (RPBPHM) is applied to examine factors affecting the injury severity of both drivers in the same truck-car crash and how these factors change over the years. Using truck-car crash data from 2017 to 2019 in the UK, the dependent variable is defined as slight injury and serious injury or fatality. Factors such as driver, vehicle, road, and environmental characteristics are statistically analyzed in this study. According to the findings, the RPBPHM model demonstrated a remarkable statistical fit, and a positive correlation was observed between the two drivers' injury severity in truck-car crashes. More importantly, the effects of the explanatory factors showing relatively temporal stability vary across different types of vehicle crashes. For example, car driver improper actions and lane changing by trucks, have a significant interactive effect on the severity of injuries sustained by drivers involved collisions between trucks and cars. Male truck drivers, young truck drivers, older truck drivers, and truck drivers' improper actions, elevate the estimated odds of only truck drivers; while older car and unsignalized crossing increase the possibility of injury severity of only car drivers. Finally, due to shared unobserved crash-specific factors, the 30-mph speed limit, dark no lights, and head-on collision, significantly affect the severity of injuries sustained by drivers involved in collisions between trucks and cars. The modeling approach provides a novel framework for jointly analyzing truck-involved crash injury severities. The findings will help policymakers take the necessary actions to reduce truck-car crashes by implementing appropriate and accurate safety countermeasures.

Stimuli-activatable PROTACs for precise protein degradation and cancer therapy.

The proteolysis targeting chimeras (PROTACs) approach has attracted extensive attention in the past decade, which represents an emerging therapeutic modality with the potential to tackle disease-causing proteins that are historically challengeable for conventional small molecular inhibitors. PROTAC harnesses the endogenic E3 ubiquitin ligase to degrade protein of interest (POI) via ubiquitin-proteasome system in a cycle-catalytic manner. The event-driven pharmacology of PROTAC is poised to pursue those targets that are conventionally undruggable, which enormously extends the space of drug development. Furthermore, PROTAC has the potential to address drug resistance of small molecular inhibitors by degrading the whole POI. Nevertheless, PROTACs display high-efficiency and always-on properties to degrade POI, they may cause severe side effects due to an "on-target but off-tissue" protein degradation profile at the undesirable tissues and cells. Given that, the stimuli-activatable PROTAC prodrugs have been recently exploited to confine precise protein degradation of the favorable targets, which may conquer the adverse effects of PROTAC due to uncontrollable protein degradation. Herein, we summarized the cutting-edge advances of the stimuli-activatable PROTAC prodrugs. We also overviewed the progress of PROTAC prodrug-based nanomedicine to improve PROTAC delivery to the tumors and precise POI degradation in the targeted cells.

Development of the nonreceptor tyrosine kinase FER-targeting PROTACs as a potential strategy for antagonizing ovarian cancer cell motility and invasiveness.

Aberrant overexpression of nonreceptor tyrosine kinase FER (Fps/Fes Related) has been reported in various ovarian carcinoma-derived tumor cells and is a poor prognosis factor for patient survival. It plays an essential role in tumor cell migration and invasion, acting concurrently in both kinase-dependent and -independent manners, which is not easily suppressed by conventional enzymatic inhibitors. Nevertheless, the PROteolysis-TArgeting Chimera (PROTAC) technology offers superior efficacy over traditional activity-based inhibitors by simultaneously targeting enzymatic and scaffold functions. Hence in this study, we report the development of two PROTAC compounds that promote robust FER degradation in a cereblon-dependent manner. Both PROTAC degraders outperform a Food and Drug Administration-approved drug, brigatinib, in ovarian cancer cell motility suppression. Importantly, these PROTAC compounds also degrade multiple oncogenic FER fusion proteins identified in human tumor samples. These results lay an experimental foundation to apply the PROTAC strategy to antagonize cell motility and invasiveness in ovarian and other types of cancers with aberrant expression of FER kinase and highlight PROTACs as a superior strategy for targeting proteins with multiple tumor-promoting functions.

Identification of calcium and integrin-binding protein 1 as a reprogrammed glucose metabolism mediator to restrict immune cell infiltration in the stromal compartment of pancreatic ductal adenocarcinoma.

An increasing body of evidence has suggested that reprogrammed metabolism plays a critical role in the progression of pancreatic ductal adenocarcinoma (PDAC) by affecting the tumor and stromal cellular components in the tumor microenvironment (TME). By analyzing the KRAS pathway and metabolic pathways, we found that calcium and integrin-binding protein 1 (CIB1) corresponded with upregulation of glucose metabolism pathways and was associated with poor prognosis in patients with PDAC from The Cancer Genome Atlas (TCGA). Elevated CIB1 expression combined with upregulated glycolysis, oxidative phosphorylation (Oxphos), hypoxia pathway activation, and cell cycle promoted PDAC tumor growth and increased tumor cellular com-ponents. Furthermore, we confirmed the mRNA overexpression of CIB1 and co-expression of CIB1 and KRAS mutation in cell lines from the Expression Atlas. Subsequently, immunohistochemistry staining from the Human Protein Atlas (HPA) showed that high expression of CIB1 in tumor cells was associated with an increased tumor compartment and reduced stromal cellular abundance. Furthermore, using multiplexed immunohistochemistry (mIHC), we verified that low stromal abundance was correlated with low infiltration of CD8+ PD-1- T cells which led to suppressed anti-tumor immunity. Overall, our findings identify CIB1 as a metabolic pathway-mediated factor for the restriction of immune cell infiltration in the stromal compartment of PDAC and highlight the potential value of CIB1 as a prognostic biomarker involved in metabolic reprogramming and immune modulation.