Gliomas, the most prevalent malignant primary brain tumors in adults, represent a heterogeneous group of neoplasms characterized by poor prognosis and limited therapeutic options, particularly in high-grade cases. Understanding the molecular mechanisms underlying glioma pathogenesis is crucial for developing novel and effective treatment strategies. In recent years, increasing attention has been directed toward the tripartite motif (TRIM) family of proteins, a class of E3 ubiquitin ligases, due to their significant roles in glioma development and progression. This review comprehensively explores the diverse functions of TRIM proteins in gliomas, including their expression patterns, prognostic significance, and mechanisms of action that are both ubiquitination-dependent and -independent. By synthesizing current knowledge, we aim to elucidate the role of TRIM proteins in glioma pathogenesis and identify potential therapeutic targets within this protein family.

Immune checkpoint inhibition (ICI) has revolutionized oncology, offering extended survival and long-term remission in previously incurable cancers. While highly effective in tumors with high mutational burden, lowly mutated cancers, including pediatric malignancies, present low response rate and limited predictive biomarkers.

We present a framework for the identification and validation of tumor-reactive T cells as a biomarker to quantify ICI efficacy and as candidates for a personalized TCR-T cell therapy. Therefore, we profiled a pediatric malignant rhabdoid tumor patient with complete remission after ICI therapy using deep single-cell T cell receptor (TCR) repertoire sequencing of the tumor microenvironment (TME) and the peripheral blood.

Tracking T cell dynamics longitudinally from the tumor to cells in circulation over a time course of 12 months revealed a systemic response and durable clonal expansion of tumor-resident and ICI-induced TCR clonotypes. We functionally validated tumor reactivity of TCRs identified from the TME and the blood by co-culturing patient-derived tumor cells with TCR-engineered autologous T cells. Here, we observed unexpectedly high frequencies of tumor-reactive TCR clonotypes in the TME and confirmed T cell dynamics in the blood post-ICI to predict tumor-reactivity.

These findings strongly support spatio-temporal tracking of T cell activity in response to ICI to inform therapy efficacy and to serve as a source of tumor-reactive TCRs for personalized TCR-T designs.

Colon adenocarcinoma (COAD) is a globally prevalent and deadly malignancy of the digestive system. Recently, migrasomes have gained significant attention as important regulators of tumor cell migration and metastasis. The current research developed a highly accurate prognostic model using migrasome-related long non-coding RNAs (lncRNAs) in COAD, providing new insights for prognostic assessment and immunotherapy of COAD patients.

RNA sequencing data from COAD patients were acquired from The Cancer Genome Atlas Program (TCGA) database to construct a prognostic lncRNA model based on known migrasome-related genes (MRGs). The model's predictive accuracy was then assessed using concordance index (C-index) analysis, nomograms, principal component analysis, and receiver operating characteristic curves. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to identify significant differences in biological functions and signaling pathways associated with differentially expressed genes in the high-risk subgroup. A comprehensive evaluation of the model incorporated clinical-pathological features, tumor microenvironment, and chemotherapy sensitivity. The expression levels of prognostic genes in COAD patients were validated via quantitative reverse transcription polymerase chain reaction (RT-qPCR). Furthermore, the role of LCMT1-AS1 in colorectal cancer was examined through CCK-8 assays, colony formation assays, and Transwell experiments.

Migrasome-related lncRNAs were identified as robust prognostic predictors for COAD. Multivariate analysis revealed that the risk score derived from these lncRNAs is an independent prognostic factor for COAD. Patients in the low-risk group exhibited significantly longer overall survival (OS) compared to those in the high-risk group. Accordingly, the nomogram prediction model we developed, which integrates clinical features and risk scores, demonstrated excellent prognostic performance. In vitro experiments further showed that LCMT1-AS1 promotes the proliferation and migration of COAD cells.

The important function of microbiota as therapeutic modulators and diagnostic biomarkers in cancer has been shown by recent developments in microbiome research. The intricate interplay between the gut microbiota and the development of cancer, especially in colorectal and breast cancers, emphasizes how microbial profiling may be used for precision treatment and early diagnosis. Important microbial signatures, including Bacteroides fragilis and Fusobacterium nucleatum, have been linked to the development and progression of cancer, providing important information on the processes behind carcinogenesis. Additionally, the influence of microbiota on the effectiveness of treatments such as immunotherapy and chemotherapy highlights its dual function in improving treatment outcomes and reducing side effects. To optimize treatment results, strategies including dietary changes and fecal microbiota transplantation (FMT) are being investigated. Despite these developments, there are still issues, such as individual variations in microbial composition, a lack of standardized procedures, and the requirement for reliable biomarkers. Integrating microbiome-based diagnostics with conventional approaches, such as liquid biopsies and machine learning algorithms, could revolutionize cancer detection and management. This review provides an overview of the current understanding of the host-microbe immunological axis and discusses emerging therapeutic strategies centered on microbiota modulation to support human health. Further research is essential to overcome existing challenges and fully realize the promise of microbiota-driven innovations in oncology.

Colorectal cancer (CRC) is still one of the leading causes of cancer deaths worldwide. Even though there has been progress in cancer immunotherapy, the results of applying immune checkpoint inhibitors (ICIs) have been unsatisfactory, especially in microsatellite stable (MSS) CRC. Single-agent ICIs that target programmed cell death-1 (PD-1)/ PD-L1, cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), T cell Ig- and mucin-domain-containing molecule-3 (TIM-3), and lymphocyte activation gene (LAG)-3 have emerged as having specific benefits. However, many primary and secondary resistance mechanisms are available in the tumor microenvironment (TME) that prevent it from happening. Combination strategies, such as the use of anti-PD-1 and anti-CTLA-4, can be effective in overcoming these resistance pathways, but toxicities remain a significant concern. Moreover, ICIs have been integrated with various treatment modalities, including chemotherapy, radiotherapy, antibiotics, virotherapy, polyadenosine diphosphate-ribose polymerase (PARP) inhibitors, and heat shock protein 90 (HSP90) inhibitors. The outcomes observed in both preclinical and clinical settings have been encouraging. Interestingly, manipulating gut microbiota via fecal microbiota transplantation (FMT) has been identified as a new strategy to increase the efficacy of immunotherapy in CRC patients. Therefore, integrating ICIs with other treatment approaches holds promise in enhancing the prognosis of CRC patients. This review focuses on the unmet need for new biomarkers to select patients for combination therapies and the ongoing work to overcome resistance and immune checkpoint blockade.

Mutations in the ARID1A gene, an integral component of the SWI/SNF complex, are prevalent, affecting prognosis and immune response in several malignancies, including gastric cancer (GC). The aim of this study was to identify ARID1A mutation-associated immune genes to construct an ARID1A-related immune gene risk model (ARM).

GSEA and ssGSEA were used to explore the involved biological pathways and the degree of immune cell infiltration, respectively. The prognosis model was constructed by lasso-COX. Protein expression level in tissue was verified by immunohistochemistry. Small molecule compounds were screened using molecular docking techniques and their anticancer value was validated in vitro and in vivo experiment.

This study revealed immune-related pathways and infiltration level of multiple immune cell types were enriched in the ARID1AMUT group compared to the ARID1AWT group. ARID1A mutations were correlated with an improved prognosis in individuals treated with immune checkpoint inhibitor (ICI) analyzed via Cbioportal website. TCGA-STAD cohort was randomly divided into a training-group and a testing-group. Additionally, ARM was developed in the training group, which identified APOD and PROC from ARID1A mutation-associated differential immunity genes. A significantly poorer prognosis in the high-risk group compared to the low-risk group, which was consistent across TCGA-training/testing/all cohorts, five GEO cohorts and 55 GC patients from Hainan General Hospital. Furthermore, the immune microenvironment components and ICI therapeutic efficacy markers were different between the two groups. Meanwhile, APOD and PROC expression was higher in GC tissues compared to para-cancerous tissues. Baicalin and capsaicin inhibited the proliferation and metastatic ability of GC cells.

ARM provides valuable insights into the prognosis and the effectiveness of ICI, thereby offering a novel strategy for clinical decision. Baicalin and capsaicin are promising potential drugs for GC treatment.

Colon adenocarcinoma (COAD) is a leading cause of cancer-related mortality, with limited therapies for advanced stages. Efferocytosis, the clearance of apoptotic cells, modulates tumor immunity and progression. We investigated efferocytosis-related genes (ERRGs) in COAD through multiomics integration.

We analyzed multiomics data from public databases to identify differentially expressed ERRGs and their molecular subtypes. An ERRG score index was developed using integrated machine learning algorithms to evaluate its predictive capacity. Single-cell sequencing and in vitro functional assays were performed to validate key findings.

Among 162 ERRGs, 22 were dysregulated in COAD. Three molecular subtypes exhibited distinct prognoses, immune profiles, and therapy responses. The ERRG score system accurately predicted clinical outcomes, with low scores correlating with improved survival and sensitivity to certain drugs. Single-cell analysis highlighted TIMP1 as a key regulator, confirmed by its knockdown suppressing tumor proliferation and migration in vitro.

ERRGs demonstrate prognostic and therapeutic relevance in COAD, providing insights into molecular subtyping and immunotherapy prediction. TIMP1 emerges as a potential therapeutic target, warranting further clinical validation.

Colorectal cancer (CRC) is ranked as the third most prevalent malignancy and is a leading cause of cancer-related mortality globally, significantly affecting the health and longevity of middle-aged individuals and the elderly. The primary risk factors for CRC are mainly due to unhealthy dietary habits and lifestyle choices, and they have been shown to profoundly influence the composition of the gut microbiota. Given that dietary patterns are critical determinants of gut microbial diversity, a compelling association exists between gut microbiota and the pathogenesis of CRC. Recent research has increasingly focused on the intricate interplay between gut microbiota and CRC, exploring its role in disease initiation, progression, and the modulation of host immune responses. Investigations have demonstrated that certain specific microbial communities can promote inflammation, disrupt metabolic pathways, and produce carcinogenic compounds, thereby contributing to the development of CRC. Conversely, a diverse and balanced gut microbiome may confer protective effects against cancer through mechanisms such as the production of short-chain fatty acids and the enhancement of intestinal barrier integrity. This article provides a comprehensive overview of the characteristics of the gut microbial community and its complex relationship with CRC. It highlights potential mechanisms through which gut microbiota may influence CRC pathogenesis, including chronic inflammation, toxins, metabolites, epigenetic dysregulation, and immune regulatory dysfunction. Additionally, this review summarizes innovative strategies for CRC prevention and treatment, emphasizing the therapeutic potential of probiotics and natural plant extracts. By elucidating these connections, this work aims to enhance the understanding of the gut microbiome's role in CRC.

Mismatch repair deficiency (dMMR), also known as high-grade microsatellite instability (MSI-H), is a well-established biomarker for predicting the immunotherapy response in endometrial cancer (EC) and colorectal cancer (CRC). Tumor mutational burden (TMB) has also emerged as an important quantitative genomic biomarker for assessing the efficacy of immune checkpoint inhibitors. Although next-generation sequencing (NGS) can be used to assess MSI and TMB, the high costs, low sample throughput, and significant DNA requirements make NGS impractical for routine clinical screening. In this study, an interpretable, multi-stage attention deep learning (DL) network is introduced to predict pathological subtypes, MSI, TP53 mutations, and TMB directly from low-cost, routinely used histopathological whole slide images of EC and CRC slides. Experimental results showed that this method consistently outperformed seven state-of-the-art approaches in cancer subtyping and molecular status prediction across EC and CRC datasets. Fisher's Least Significant Difference test confirmed a strong correlation between model predictions and actual molecular statuses (MSI, TP53, and TMB) (p<0.001). Furthermore, Kaplan-Meier disease-free survival analysis revealed that CRC patients with model-predicted high TMB had significantly longer disease-free survival than those with low TMB (p<0.05). These findings demonstrate that the proposed DL-based approach holds significant potential for directly predicting immunotherapy-related pathological diagnoses and molecular statuses from routine WSIs, supporting personalized cancer immunotherapy treatment decisions in EC and CRC.

Background/Objectives: Worldwide, colon cancer is a major cause of cancer-related mortality, with an increasing incidence influenced by genetic, environmental, and lifestyle factors. Despite advances in diagnosis and personalized treatments, challenges remain in improving patient prognosis, particularly in metastatic colorectal cancer (mCRC). Bevacizumab (BEV), a monoclonal antibody, is widely used in colorectal cancer treatment. This study aimed to analyze adverse events associated with BEV compared with other therapies based on data from the EudraVigilance (EV) database. Methods: A descriptive and disproportionality analysis was conducted on signals reported in the EV database related to BEV. The study included comparisons with other antineoplastic treatments, such as chemotherapy, targeted therapy, and immunotherapy. Patient demographics, severity of adverse drug reactions (ADRs), and distribution patterns were analyzed to assess the safety profile of BEV in colorectal cancer treatment. Results: The majority of the signals for BEV were from patients aged 18-64 years (39.42%) and 65-85 years (34.08%). Hypertension, thromboembolism, proteinuria, and gastrointestinal disorders have been the most frequently reported. Serious ADRs, including gastrointestinal perforations, hemorrhage, and arterial thromboembolism, were observed in 93.74% of Individual Case Safety Reports. BEV was associated with a higher likelihood of vascular and endocrine disorders compared with chemotherapy and other targeted therapies. Immunotherapy was linked to increased immunological ADRs, while BEV demonstrated fewer immune-related toxicities. Conclusions: Continuous monitoring is necessary to optimize patient management, particularly in elderly patients or those with cardiovascular comorbidities. Understanding BEV's safety profile allows for better personalization of treatment strategies, minimizing risks while enhancing therapeutic outcomes.

Vitamin C (VitC) has elicited considerable interest regarding its potential role in cancer therapy; however, its effects on tumor immunity remain unclear. In colorectal cancer (CRC), although anti-PD-1/PD-L1 therapies demonstrate promise, their efficacy is still constrained. Our prior research demonstrated that VitC can inhibit tumor growth by suppressing the Warburg effect. This study aims to explore the effects of high-dose VitC on PD-L1 expression in CRC, focusing on its underlying mechanisms and potential for enhancing immunotherapy. We found that VitC inhibits aerobic glycolysis in HCT116 cells while also downregulating PD-L1 expression. Further investigations indicated that this process is mediated by VitC's activation of AMPK, which downregulates HK2 and NF-κB, ultimately resulting in reduced PD-L1 expression and increased T cell infiltration. Notably, we observed that VitC and the PD-L1 monoclonal antibody atezolizumab exhibit comparable tumor-inhibiting abilities, and their combined use further enhances this efficacy. In conclusion, our results demonstrate that high-dose VitC activates AMPK, downregulates PD-L1 expression, mitigates immune evasion, and suppresses tumor growth. This provides a promising strategy for optimizing immunotherapy in CRC.

Cancer ranks among the most lethal diseases worldwide. Tissue biopsy is currently the primary method for the diagnosis and biological analysis of various solid tumors. However, this method has some disadvantages related to insufficient tissue specimen collection and intratumoral heterogeneity. Liquid biopsy is a noninvasive approach for identifying cancer-related biomarkers in peripheral blood, which allows for repetitive sampling across multiple time points. In the field of liquid biopsy, representative biomarkers include circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and exosomes. Many studies have evaluated the prognostic and predictive roles of CTCs and ctDNA in various solid tumors. Although these studies have limitations, the results of most studies appear to consistently demonstrate the correlations of high CTC counts and ctDNA mutations with lower survival rates in cancer patients. Similarly, a reduction in CTC counts throughout therapy may be a potential prognostic indicator related to treatment response in advanced cancer patients. Moreover, the biochemical characteristics of CTCs and ctDNA can provide information about tumor biology as well as resistance mechanisms against targeted therapy. This review discusses the current clinical applications of liquid biopsy in cancer patients, emphasizing its possible utility in outcome prediction and treatment decision-making.

Immunotherapy is becoming a promising strategy for treating diverse cancers. However, it benefits only a selected group of gastric cancer (GC) patients since they have highly heterogeneous immunosuppressive microenvironments. Thus, a more sophisticated immunological subclassification and characterization of GC patients is of great practical significance for mRNA vaccine therapy. This study aimed to find a new immunological subclassification for GC and further identify specific tumor antigens for mRNA vaccine development. First, deep autoencoder (AE)-based clustering was utilized to construct the immunological profile and to uncover four distinct immune subtypes of GC, labeled as Subtypes 1, 2, 3, and 4. Then, in silico prediction using machine learning methods was performed for accurate discrimination of new classifications with an average accuracy of 97.6%. Our results suggested significant clinicopathology, molecular, and immune differences across the four subtypes. Notably, Subtype 4 was characterized by poor prognosis, reduced tumor purity, and enhanced immune cell infiltration and activity; thus, tumor-specific antigens associated with Subtype 4 were identified, and a customized mRNA vaccine was developed using immunoinformatic tools. Finally, the influence of the tumor microenvironment (TME) on treatment efficacy was assessed, emphasizing that specific patients may benefit more from this therapeutic approach. Overall, our findings could help to provide new insights into improving the prognosis and immunotherapy of GC patients.

SLC25A13, a pivotal component of the mitochondrial aspartate-glutamate carrier, is integral to cellular metabolism and has been linked to various diseases. However, its role in cancer biology remains largely unexplored. In this study, we employed multi-omics data to elucidate the genetic landscape, expression profile, and prognostic value of SLC25A13 in a pan-cancer context. Additionally, we examined the correlation between SLC25A13 and the immune microenvironment across various cancers. By applying multiple machine learning methods, we identified seven core SLC25A13 co-expressed genes and developed a nomogram to predict the prognosis of glioma patients, validating its efficacy across multiple independent datasets. Furthermore, in vitro and in vivo experiments demonstrated that SLC25A13 is significantly overexpressed in glioblastoma tissues compared to paraneoplastic tissues, promoting glioblastoma cell proliferation and migration while inhibiting apoptosis. Collectively, our study positions SLC25A13 as a promising biomarker for cancer prognosis and a potential therapeutic target, particularly in glioma, thereby laying the groundwork for future research into its therapeutic exploitation in cancer.

ADAM12, part of the adisintegrin and metalloproteases (ADAMs) family, has been widely reported in recent years to be associated with various malignant tumor behaviors, including migration, invasion, and treatment resistance. However, its role at the pan-cancer level remains insufficiently characterized. In this study, pan-cancer data were utilized to elucidate the expression patterns, prognostic significance, and potential roles of ADAM12 within the tumor immune microenvironment. An in-depth analysis of ADAM12 in gliomas was also conducted. Our findings revealed that ADAM12 expression is markedly overexpressed in glioma tissues, enhances glioma cell malignancy, and is associated with a worse prognosis. These results suggest that ADAM12 may serve as a biomarker for predicting glioma malignancy and patient prognosis, as well as a potential therapeutic target in glioma treatment.

The advent of immunotherapy has transformed the therapeutic landscape for advanced non-small cell lung cancer (NSCLC); nonetheless, the emergence of resistance to immunotherapy poses a considerable obstacle. Our research sought to identify factors contributing to immunotherapy resistance and to assess the effectiveness of subsequent treatments in patients with advanced NSCLC who have been exposed to immune checkpoint inhibitors (ICIs).

This retrospective study analyzed data from 232 individuals with advanced NSCLC who were treated with ICIs during January 2020 to December 2023. Based on their response to ICIs, these patients were classified into two groups: immunoresistance group (IM group) and non-immunoresistance group (NIM group). Data collected included demographics, clinical parameters, cytokine profiles, tumor mutational burden (TMB), PD-L1 expression, overall survival (OS), progression-free survival (PFS), and adverse events. The association between risk factors and immunoresistance were assessed, and second-line treatment outcomes were evaluated.

Key risk factors for immunoresistance included lower TMB, higher levels of interleukin-10 (IL-10), and PD-L1 expression ≥ 50%. TMB was inversely correlated with immunoresistance (rho = -0.838, P < 0.001). In multivariate analysis, IL-10 remained a significant risk factor (OR = 33.654, P = 0.021), whereas TMB was protective (OR = 0.786, P < 0.001). Second-line targeted therapy significantly improved OS (8.72 ± 2.02 months) and PFS (5.37 ± 2.15 months) compared to chemotherapy (OS: 7.93 ± 2.13 months; PFS: 4.86 ± 1.68 months) (P < 0.05). The targeted therapy group experienced distinct side effects, notably increased hypertension and hand-foot syndrome, while chemotherapy group had higher rates of fatigue (P < 0.05).

Immunoresistance in advanced NSCLC is influenced by IL-10, TMB, and PD-L1 expression. Targeted therapies offer superior outcomes than chemotherapy, though side effect management remains crucial.

Considering the high degree of malignancy, recurrence rate and poor prognosis, exploring promising targets is an imperious strategy for colorectal carcinoma therapy. Recent studies have indicated that GABPα plays a role in cancer aggressiveness, but its exact function and regulatory mechanisms in colorectal cancer progression remain unclear. This study aims to explore the biological role of GABPα and its upstream regulator, miR-378a-5p, in modulating cancer progression. The expression levels of GABPα and miR-378a-5p were analyzed through comprehensive data mining and qPCR assays. The functional effects of GABPα were assessed using CCK-8, wound healing, transwell invasion assay, tube formation and xenograft model in nude mice. A co-transfection assay was also performed to investigate the regulatory relationship between miR-378a-5p and GABPα. We found that GABPα expression was significantly downregulated in human colorectal cancer tissues and cell lines. Functional assays revealed that GABPα overexpression suppressed the proliferation, migration, invasion and angiogenesis of colorectal cancer cells, and in vivo experiments further confirmed the inhibitory role of GABPα. Additionally, miR-378a-5p was upregulated in colorectal cancer, and GABPα was identified as a direct target of miR-378a-5p, as confirmed by luciferase reporter assays. Furthermore, overexpression of GABPα partially counteracted the enhanced malignant behaviors of cancer cells induced by miR-378a-5p. Our findings suggest that miR-378a-5p promotes the aggressive progression of colorectal cancer by directly targeting GABPα, highlighting this regulatory axis as a potential therapeutic target for colorectal carcinoma.

Colorectal cancer (CRC) remains one of the leading causes of cancer-related morbidity and mortality around the world. Despite advances in surgery, chemotherapy, and targeted therapies, the prognosis for patients with metastatic or advanced CRC remains poor. Immunotherapies comprising immune checkpoint inhibitors showed disappointing responses in metastatic CRC (mCRC). However, cellular immunotherapy, specifically using classical dendritic cells (cDCs), may hold unique promise in immune recognition for CRC antigens. cDCs are substantial players in immune recognition and are instrumental in orchestrating innate and adaptive immune responses by processing and presenting tumor antigens to effector cells. Natural killer T (NKT) cells are insufficiently studied but unique effector cells because of their ability to bridge innate and adaptive immune reactions and the crosstalk with dendritic cells in cancer. This review explores the therapeutic potential of using both cDCs and NKT cells as a synergistic therapy in CRC, focusing on their biological roles, strategies for harnessing their capabilities, clinical applications, and the challenges within the tumor microenvironment. Both cDCs and NKT cells can be used as a new effective approach for cell-based therapies in cancers to provide a new hope for CRC patients that are challenging to treat.

Colorectal cancer (CRC) is characterized by an extremely high mortality rate, mainly caused by the high metastatic potential of this type of cancer. To date, chemotherapy remains the backbone of the treatment of metastatic colorectal cancer. Three main chemotherapeutic drugs used for the treatment of metastatic colorectal cancer are 5-fluorouracil, oxaliplatin and irinotecan which is metabolized to an active compound SN-38. The main goal of this study was to find the genes connected to the resistance to the aforementioned drugs and to construct a predictive gene expression-based classifier to separate responders and non-responders.

In this study, we analyzed gene expression profiles of seven patient-derived CRC organoids and performed correlation analyses between gene expression and IC50 values for the three standard-of-care chemotherapeutic drugs. We also included in the study publicly available datasets of colorectal cancer cell lines, thus combining two different in vitro models relevant to cancer research. Logistic regression was used to build gene expression-based classifiers for metastatic Stage IV and non-metastatic Stage II/III CRC patients. Prognostic performance was evaluated through Kaplan-Meier survival analysis and log-rank tests, while independent prognostic significance was assessed using multivariate Cox proportional hazards modeling.

A small set of genes showed consistent correlation with resistance to chemotherapy across different datasets. While some genes were previously implicated in cancer prognosis and drug response, several were linked to drug resistance for the first time. The resulting gene expression signatures successfully stratified Stage II/III and Stage IV CRC patients, with potential clinical utility for improving treatment outcomes after further validation.

This study highlights the advantages of integrating diverse experimental models, such as organoids and cell lines, to identify novel prognostic biomarkers and enhance the understanding of chemotherapy resistance in CRC.

Inflammation can influence the development of CRC as well as immunotherapy and plays a key role in CRC. Therefore, this study aimed to investigate the potential of inflammation-related genes in CRC risk prediction. Inflammation gene models were constructed and validated by combining transcriptomic and single-cell data from TCGA and GEO databases, and the expression of inflammation-related genes was verified by RT-qPCR. We identified two molecular subtypes and three genetic subtypes, two risk subgroups according to median risk values, constructed a prognostic model including thirteen genes (TIMP1, GDF15, UCN, KRT4, POU4F1, NXPH1, SIX2, NPC1L1, KLK12, IGFL1, FOXD1, ASPG, and CYP4F8), and validated the performance of each aspect of the model in an external database. Patients in the high-risk group had worse survival with reduced immune cell infiltration and a greater tumor mutational load. The risk score correlated strongly with the immune checkpoints PD1, PDL1, PDL2, and CTLA4, and it is possible that high-risk patients are more sensitive to treatment involving immune checkpoints. In the single-cell data, GDF15 was most significantly expressed in cancer cell populations. Therefore, we further validated their expression in cells and tissues using qPCR. In summary, we developed a prognostic marker associated with inflammatory genes to provide new directions for subsequent studies and to help clinicians assess the prognosis of CRC patients as well as to develop personalized treatment strategies.

In endometrial cancer (EC) and colorectal cancer (CRC), in addition to microsatellite instability, tumor mutational burden (TMB) has gradually gained attention as a genomic biomarker that can be used clinically to determine which patients may benefit from immune checkpoint inhibitors. High TMB is characterized by a large number of mutated genes, which encode aberrant tumor neoantigens, and implies a better response to immunotherapy. Hence, a part of EC and CRC patients associated with high TMB may have higher chances to receive immunotherapy. TMB measurement was mainly evaluated by whole-exome sequencing or next-generation sequencing, which was costly and difficult to be widely applied in all clinical cases. Therefore, an effective, efficient, low-cost and easily accessible tool is urgently needed to distinguish the TMB status of EC and CRC patients. In this study, we present a deep learning framework, namely Ensemble Transformer-based Multiple Instance Learning with Self-Supervised Learning Vision Transformer feature encoder (ETMIL-SSLViT), to predict pathological subtype and TMB status directly from the H&E stained whole slide images (WSIs) in EC and CRC patients, which is helpful for both pathological classification and cancer treatment planning. Our framework was evaluated on two different cancer cohorts, including an EC cohort with 918 histopathology WSIs from 529 patients and a CRC cohort with 1495 WSIs from 594 patients from The Cancer Genome Atlas. The experimental results show that the proposed methods achieved excellent performance and outperforming seven state-of-the-art (SOTA) methods in cancer subtype classification and TMB prediction on both cancer datasets. Fisher's exact test further validated that the associations between the predictions of the proposed models and the actual cancer subtype or TMB status are both extremely strong (p<0.001). These promising findings show the potential of our proposed methods to guide personalized treatment decisions by accurately predicting the EC and CRC subtype and the TMB status for effective immunotherapy planning for EC and CRC patients.

The relative outcomes following the resection of screen-detected right-sided colon cancer compared to symptomatic cases are unknown. In this study, short and long-term outcomes after right-sided colectomy in screen-detected colon cancer are compared with symptomatic cases, both emergency and elective.

A prospective observational cohort study of patients, including both screen-detected and symptomatic patients (elective and emergency resections), undergoing right-sided colectomy for colon cancer (2010-2020) in a tertiary care unit was conducted. Each patient was followed up for long-term recurrence and survival.

A total of 909 patients (median age, 70; IQR, 58-82; male, 52%) were included (151 patients (16.6%) screen-detected; 598 (65.8%) elective and 160 (17.6%) emergency). Screen-detected patients were more likely to have T1 or T2 lesions compared to elective and emergency groups (T1: 14.6% vs. 3.8% vs. 0.6% p < 0.001; T2: 16.6% vs. 8.9% vs. 3.1% p < 0.001), but were less likely to have T3 or T4 lesions (p < 0.001), respectively. Rates of N0 were higher in the screen-detected group (68.9% vs. 63.5% vs. 41.9%, respectively; p < 0.001). 98% of the screen-detected group achieved R0 resection compared to 93.3% of elective and 79.4% of emergency patients (p < 0.001). At 5-years following resection, overall survival for the screen-detected, elective, and emergency groups were 85.4%, 75.4%, and 53.1%, respectively (p < 0.001). Recurrence at 5-year post-resection were 8%, 15.1%, and 22.5% for the screen-detected, elective, and emergency groups, respectively (p < 0.001).

When considering right-sided colon cancer alone, screen-detected cancers have a lower long-term recurrence rate, lower rates of postoperative complication, and superior survival compared to symptomatic groups following resection.

Colorectal cancer (CRC) is among the most prevalent malignancies globally, with a rising incidence observed in younger demographics. Despite surgical resection remaining the cornerstone of treatment, metastatic CRC poses significant therapeutic challenges. Immunotherapy, a mode of treatment that leverages the patient's immune system, presents a promising frontier in CRC management, particularly for late-stage cases with limited treatment options. The study was aimed to elucidate the relationships between genetic profiles and predictive biomarkers in CRC patients to inform immunotherapy decisions and improve outcomes.

We conducted a large-scale study involving 660 patients with CRC, analyzing genetic profiles and predictive biomarkers for immune checkpoint inhibitors (ICIs) using next-generation sequencing (NGS) and immunohistochemistry (IHC). The study focused on assessing the association between gene mutations and markers such as microsatellite instability (MSI) status, tumor mutational burden (TMB), and programmed death ligand 1 (PD-L1) expression.

Analysis revealed a diverse mutational landscape in CRC, with TP53 (73.64%), APC (67.58%), and KRAS (46.82%) being the most frequently mutated genes. We observed significant associations between KRAS mutations and co-occurrences with FBXW7, PIK3CA, and SMAD4 mutations, while KRAS mutations were mutually exclusive with TP53 mutations. KRAS mutations were enriched in the PD-L1 tumor proportion score (TPS) ≥1% population (P=0.03), whereas APC mutations were enriched in the PD-L1 TPS <1% population (P=0.10) as compared to their wild types. Additionally, specific mutations such as KRAS p.A146T, PIK3CA p.H1047R, and BRAF p.V600E were significantly associated with higher TMB and MSI-high status, indicating potential benefits from ICI therapy.

Our findings underscore the importance of genetic profiling in guiding treatment decisions for patients with CRC, particularly in the era of immunotherapy. Understanding the complex interplay between genetic alterations and immune markers is critical for optimizing therapeutic strategies and improving clinical outcomes. Further research is warranted to validate these findings and explore personalized treatment approaches in CRC.

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Metastatic colorectal cancer (mCRC) continues to present significant challenges, particularly in patients with proficient mismatch repair/microsatellite stable (pMMR/MSS) tumors. This narrative review aims to provide recent developments in immunotherapy for CRC treatment, focusing on its efficacy and challenges.

This review discussed the various immunotherapeutic strategies for CRC treatment, including immune checkpoint inhibitors (ICIs) targeting PD-1 and PD-L1, combination therapies involving ICIs with other modalities, chimeric antigen receptor T-cell (CAR-T) cell therapy, and cancer vaccines. The role of the tumor microenvironment and immune evasion mechanisms was also explored to understand their impact on the effectiveness of these therapies.

This review provides a comprehensive update of recent advancements in immunotherapy for CRC, highlighting the potential of various immunotherapeutic approaches, including immune checkpoint inhibitors, combination therapies, CAR-T therapy, and vaccination strategies. The results of checkpoint inhibitors, particularly in patients with MSI-H/dMMR tumors, which have significant improvements in survival rates have been observed. Furthermore, this review also addresses the challenges faced in treating pMMR/MSS CRC, which remains resistant to immunotherapy.

Immunotherapy plays a significant role in the treatment of CRC, particularly in patients with MSI-H/dMMR tumors. However, many challenges remain, especially in treating pMMR/MSS CRC. This review discussed the need for further research into combination therapies, biomarker development, CAR-T cell therapy, and a deeper understanding of immune evasion mechanisms for CRC treatment.

Colon cancer (COAD) poses great challenges to clinical treatment due to its heterogeneity and complex immune microenvironment. M2-like macrophages significantly influence COAD's onset, progression, and treatment. Yet, existing M2-like macrophage markers are limited in prognostic efficacy, prompting the exploration of new M2 signatures. Extensive data analysis aimed to unveil prognosis-associated M2-derived signatures. Bulk transcriptome, single-cell RNA sequencing, and clinical data from The Cancer Genome Atlas and Gene Expression Omnibus databases for patients with COAD were amassed. Cell-Type Identification by Estimating Relative Subsets of RNA Transcripts identified immune cell infiltration, and the Kaplan-Meier test identified crucial immune populations associated with prognosis. Genetic signatures linked to M2 tumor-associated macrophage were crafted utilizing weighted gene coexpression network analysis, least absolute shrinkage and selection operator, and Cox regression. The M2 tumor-associated macrophage gene signature was validated in GSE17536. The expression profile of the M2 gene signature was investigated in single-cell RNA sequencing dataset GSE166555. Systemic immune profile identified that M2-like macrophage has the most significant prognostic significance in The Cancer Genome Atlas-COAD. The core genes related to M2 macrophage infiltration were extracted by weighted gene coexpression network analysis. Least absolute shrinkage and selection operator-stepwise COX regression-derived M2-derived signatures (snail family zinc finger 1, gastrin-releasing peptide, gamma-aminobutyric acid type A receptor delta subunit, cluster of differentiation 1B, poly(A)-binding protein cytoplasmic 2, manic fringe, and death-associated protein kinase 1) as a risk model, which was confirmed as independent prognosis factors, validated by external dataset. This M2-based prognostic model reflected M2 macrophage infiltration. Mendelian randomization established cytotoxic T lymphocyte associate protein-4 and cluster of differentiation 274 immune checkpoints' causality with COAD. In conclusion, our study developed novel markers for discriminating M2-like macrophages and predicting the prognosis of patients with COAD, offering fresh perspectives for clinical interventions.

UCHL5 was initially recognized as a multifunctional molecule. While recent research has highlighted its involvement in tumor malignant biological behaviors, its specific role in promoting tumor cell apoptosis has drawn particular attention. However, the precise relationship between UCHL5 and various tumor types, as well as its influence within the immune microenvironment, remains unclear.

The transcriptomic data and clinicopathological parameters across 33 cancer types were obtained from TCGA. Clinical pathological parameters of tumor patients, including gender, age, survival time, and staging, are utilized to evaluate the association between UCHL5 and pan-cancer characteristics. The prognostic significance of UCHL5 was evaluated through Cox analysis and Kaplan-Meier (K-M) methods. Protein expression data for UCHL5 were obtained from The Human Protein Atlas database, and its subcellular localization was further investigated. Additionally, potential correlations between UCHL5 and factors such as tumor-infiltrating immune cells, immunomodulators, microsatellite instability (MSI), and tumor mutation burden (TMB) were explored. The relationship between UCHL5 and immunotherapy efficacy was also assessed in independent cohorts, including IMvigor210, GSE78220, GSE67501, and GSE168204. Finally, the impact of UCHL5 on the malignant biological behavior of cervical cancer cells was investigated through in vitro experiments, along with an exploration of the underlying mechanisms.

We observed that UCHL5 expression levels were elevated in 11 types of cancer tissues compared to their corresponding normal tissues, while levels were lower in five tumor types. Additionally, UCHL5 expression displayed a significant correlation with tumor stage in BRCA, KIRC, LUAD, and TGCT. Cox and K-M analysis indicated that UCHL5 expression was significantly associated with prognosis in KIRC, KICH, CESC, ACC, and UVM. UCHL5 expression was negatively associated with stromal and immune scores in certain cancers. In terms of immune cell infiltration, UCHL5 expression in UCEC, SKCM, and COAD showed a negative correlation with regulatory T cells (Tregs). Furthermore, UCHL5 was widely associated with three types of immunomodulators. It also demonstrated a significant relationship with MSI and TMB in certain cancers and was connected to the immunotherapy efficacy. Finally, in vitro experiments confirmed that UCHL5 knockout enhances apoptosis in cervical cancer cells and disrupts Wnt/β-catenin signaling.

Pan-cancer analysis indicates that UCHL5 is dysregulated in various tumor tissues and is closely associated with survival prognosis, the tumor immune microenvironment, and the efficacy of immunotherapy in certain cancer types. UCHL5 shows promise as a predictive biomarker, and its specific regulatory mechanisms across different cancers warrant further investigation.

Environmental pollution poses a significant risk to public health, as demonstrated by the bioaccumulation of aluminum (Al) in colorectal cancer (CRC). This study aimed to investigate the potential mutagenic effect of Al bioaccumulation in CRC samples, linking it to the alteration of key mediators of cancer progression, including immune response biomarkers. Aluminum levels in 20 CRC biopsy samples were analyzed using inductively coupled plasma mass spectrometry (ICP-MS). The results indicated that Al bioaccumulation occurred in 100% of the cases. A correlation between Al levels and tumor mutation burden was observed. Furthermore, RNA sequencing revealed a significant association between Al concentration and the expression of the immune checkpoint molecule CTLA-4. Although correlations with PD-1 and PD-L1 were not statistically significant, a trend was observed. Additionally, a correlation between Al levels and both the presence of myeloid cells and IFNγ expression was detected, linking Al exposure to inflammatory responses within the tumor microenvironment. These findings suggested that Al can play a role in CRC progression by promoting both genetic mutations and immune evasion. Given the ubiquitous presence of Al in industrial and consumer products, dietary sources, and environmental pollutants, these results underscored the need for stricter regulatory measures to control Al exposure.

To explore the efficacy and safety of the combination of irinotecan, trifluridine/tipiracil (TAS-102), and bevacizumab in a later-line setting for metastatic colorectal cancer (mCRC) patients.

This was a single-center, phase II trial. The mCRC patients who are refractory to standard first-line and second-line treatment are eligible. Patients who previously received irinotecan while progressing during maintenance therapy are also eligible. The primary endpoint was the objective response rate (ORR).

Between August 1, 2022, and September 30, 2023, 35 patients were enrolled, and 31 of them were evaluable for efficacy. The ORR was 25.8% (8/31), and the disease control rate (DCR) was 93.5% (29/31). As of April 30, 2024, the median progression-free survival (PFS) was 9.2 months (95% CI 6.285-12.115), whereas the median overall survival (OS) was not reached with the 1-year OS rate of 73.5%. The most common grade 3/4 treatment-related adverse events were neutropenia (34.3%), anemia (17.1%), and thrombocytopenia (8.6%).

Irinotecan, TAS-102 plus bevacizumab regimen preliminarily demonstrated promising efficacy with tolerable toxicity for mCRC patients as later-line treatment. This regimen warrants further exploration in refractory mCRC patients.

Although immune-checkpoint inhibitors (ICIs) have significantly improved cancer treatment, their effectiveness is limited by primary or acquired resistance in many patients. The gut microbiota, through its production of metabolites and regulation of immune cell functions, plays a vital role in maintaining immune balance and influencing the response to cancer immunotherapies. This review highlights evidence linking specific gut microbial characteristics to increased therapeutic efficacy in a variety of cancers, such as gastrointestinal cancers, melanoma, lung cancer, urinary system cancers, and reproductive system cancers, suggesting the gut microbiota's potential as a predictive biomarker for ICI responsiveness. It also explores the possibility of enhancing ICI effectiveness through fecal microbiota transplantation, probiotics, prebiotics, synbiotics, postbiotics, and dietary modifications. Moreover, the review underscores the need for extensive randomized controlled trials to confirm the gut microbiota's predictive value and to establish guidelines for microbiota-targeted interventions in immunotherapy. In summary, the article suggests that a balanced gut microbiota is key to maximizing immunotherapy benefits and calls for further research to optimize microbiota modulation strategies for cancer treatment. It advocates for a deeper comprehension of the complex interactions between gut microbiota, host immunity, and cancer therapy, aiming for more personalized and effective treatment options.

Tumor Mutational Burden (TMB) have emerged as pivotal predictive biomarkers in determining prognosis and response to immunotherapy in colorectal cancer (CRC) patients. While Whole Exome Sequencing (WES) stands as the gold standard for TMB assessment, carry substantial costs and demand considerable time commitments. Additionally, the heterogeneity among high-TMB patients remains poorly characterized.

We employed eight advanced machine learning algorithms to develop gene-panel-based models for TMB estimation. To rigorously compare and validate these TMB estimation models, four external cohorts, involving 1,956 patients, were used. Furthermore, we computed the Pearson correlation coefficient between the estimated TMB and tumor neoantigen levels to elucidate their association. CD8+ tumor-infiltrating lymphocyte (TIL) density was assessed via immunohistochemistry.

The TMB estimation model based on the Lasso algorithm, incorporating 20 genes, exhibiting satisfactory performance across multiple independent cohorts (R2 ≥ 0.859). This 20-gene TMB model proved to be an independent prognostic indicator for the progression-free survival (PFS) of CRC patients (p = 0.001). DNAH5 mutations were associated with a more favorable prognosis in high-TMB CRC patients, and correlated strongly with tumor neoantigen levels and CD8+ TIL density.

The 20-gene model offers a cost-efficient approach to precisely estimating TMB, providing prognosis in patients with CRC. Incorporating DNAH5 within this model further refines the categorization of patients with elevated TMB. Utilizing the 20-gene model facilitates the stratification of patients with CRC, enabling more precise treatment planning.

TROP2 (TACSTD2) expression is associated with decreased overall survival (OS) in some solid tumors, and the TROP2-targeting antibody-drug conjugate (ADC) sacituzumab govitecan has been approved in breast and urothelial carcinomas. We aimed to explore the multi-omic landscape associated with TACSTD2 gene expression in various solid tumors to identify patients most likely to benefit from this approach.

Breast (N = 11 246), colorectal (N = 15 425), hepatocellular (N = 433), pancreatic (N = 5488), and urothelial (N = 4125) tumors were stratified into quartiles by TACSTD2 gene expression, analyzed by next-generation DNA sequencing, whole transcriptome sequencing, and immunohistochemistry at Caris Life Sciences (Phoenix, AZ). Survival data were obtained from insurance claims, and Kaplan-Meier estimates were calculated for molecularly defined cohorts.

Several pathogenic mutations were associated with TACSTD2-high tumors, including TP53 in breast, colorectal (CRC), pancreatic, and hepatocellular cancers; KRAS in pancreatic and CRC cancers; ARID1A and FGFR3 in urothelial cancer; and CTNNB1 in hepatocellular cancer. TACSTD2-low breast tumors were enriched for copy number amplifications in CCND1 and FGF/R family member genes. TACSTD2 high was generally associated with more immune cell infiltration and greater T-cell inflammation scores. Patients with TACSTD2-high breast, CRC, and pancreatic cancers demonstrated a significantly shorter OS than TACSTD2-low tumors. This was restricted to CRC with microsatellite stable tumors and patients with pancreatic cancer with KRAS-mutant tumors. Patients with breast cancer with TACSTD2-high tumors also experienced significantly worse OS following immune checkpoint inhibitors.

TACSTD2 expression is associated with key driver alterations and a more active immune microenvironment, suggesting possible combinatorial strategies with TROP2-targeting ADCs plus immunotherapy in various solid tumors.

FOLFOX, composed of 5-FU, oxaliplatin and leucovorin, is a first line chemotherapy regimen for colorectal cancer (CRC) treatment. In this study, we show that 5-FU and oxaliplatin induce DNA damage and activate cGAS/STING signaling leading to enhanced expression of interferon (IFN) β, IFN-stimulated genes and inflammatory cytokines in mouse and human colon cancer cells as well as increased intratumoral CD8+ T cells in mice. Crucially, 5-FU and oxaliplatin increase PD-L1 expression at the mRNA and protein levels, which has been shown to inhibit CD8+ T cell function. Depletion of cGAS, STING, IRF3, or IFNα/β receptor 1 (IFNAR1) abolishes this increase, indicating that 5-FU/oxaliplatin mediated upregulation of PD-L1 expression is dependent on tumor cell intrinsic cGAS/STING signaling. These results imply opposing roles for FOLFOX during cancer treatment. On one hand, 5-FU and oxaliplatin activate the innate immune response to facilitate anti-tumor immunity, and conversely upregulate PD-L1 expression to evade immune surveillance. Analysis of TCGA colon cancer dataset shows a positive correlation between expression of PD-L1 and components of the cGAS/STING pathway, supporting a role for cGAS/STING signaling in upregulating PD-L1 expression in colon cancer patients. Tumor studies in syngeneic immune competent mice demonstrate that the combination of 5-FU/oxaliplatin and anti-PD-1 significantly reduced tumor growth of colon cancer cells compared to 5-FU/oxaliplatin treatment alone. Taken together, our studies have identified a unique pathway leading to chemoresistance and provide a rationale to combine FOLFOX with anti-PD-1/PD-L1 as an effective CRC treatment.

Lymphocyte activation gene 3 (LAG3), an inhibitory receptor in T-cell activation, is a negative prognostic factor. However, its impact on tumours has yet to be comprehensively elucidated on a pan-cancer scale. Thus, we aim to reveal its role at the pan-cancer level.

We performed IHC staining on a retrospective cohort of 370 patients. Then we assessed the prognostic effect of LAG3 using Kaplan-Meier survival analysis and multivariate Cox regression analysis. In pan-cancer analysis, we constructed competing endogenous RNA and protein-protein interaction networks, conducted gene set enrichment analysis and identified correlations between LAG3 gene expression and various factors, including clinical characteristics, tumour purity, mutations, tumour immunity and drug sensitivity across 33 cancer types.

LAG3 was expressed higher in normal kidney tissues than in tumours. A high level of LAG3 gene expression was an independent prognostic factor for OS (HR = 6.60, 95% CI = 2.43-17.90, P < 0.001) and PFS (HR = 3.44, 95% CI = 1.68-7.10, P < 0.001). In pan-cancer analysis, LAG3 exhibited robust correlations with survival and tumour stages in various cancers. Moreover, LAG3 was strongly associated with immune-related genes, proteins and signalling pathways. LAG3 gene expression was positively associated with increased infiltration of activated immune cells and decreased infiltration of several resting cells. LAG3 gene expression was associated with tumour mutation burden and microsatellite instability in multiple cancers.

High LAG3 gene expression was an independent risk factor in kidney neoplasms. It also functioned as a biomarker for prognosis, TIME and immunotherapy efficacy in the pan-cancer dimension.

Colon cancer is a malignant tumor with high malignancy and a low survival rate whose heterogeneity limits systemic immunotherapy. Transforming growth factor-β (TGF-β) signaling pathway-related genes are associated with multiple tumors, but their role in prognosis prediction and tumor microenvironment (TME) regulation in colon cancer is poorly understood. Using bioinformatics, this study aimed to construct a risk prediction signature for colon cancer, which may provide a means for developing new effective treatment strategies.

Using consensus clustering, patients in The Cancer Genome Atlas (TCGA) with colon adenocarcinoma were classified into several subtypes based on the expression of TGF-β signaling pathway-related genes, and differences in survival, molecular, and immunological TME characteristics and drug sensitivity were examined in each subtype. Ten genes that make up a TGF-β-related predictive signature were found by least absolute shrinkage and selector operation (LASSO) regression using colon cancer data from the TCGA database and confirmed using a Gene Expression Omnibus (GEO) dataset. A nomogram incorporating risk scores and clinicopathologic factors was developed to stratify the prognosis of patients with colon cancer for accurate clinical diagnosis and therapy.

Two TGF-β subtypes were identified, with the TGF-β-high subtype being associated with a poorer prognosis and superior sensitivity to immunotherapy. Mutation analyses showed a high incidence of gene mutations in the TGF-β-high subtype. After completing signature construction, patients with colon cancer were categorized into high- and low-risk subgroups based on the median risk score of the TGF-β-related predictive signature. The risk score exhibited superior predictive performance relative to age, gender, and stage, as evidenced by its AUC of 0.686. Patients in the high-risk subgroup had higher levels of immunosuppressive cell infiltration and immune checkpoints in the TME, suggesting that these patients had better responses to immunotherapy.

Patients with colon cancer were divided into two subtypes with different survival and immune characteristics using consensus clustering analysis based on TGF-β signaling pathway-related genes. The constructed risk prediction signature may show promise as a biomarker for evaluating the prognosis of colon cancer, with potential utility for screening individuals for immunotherapy.