Colorectal cancer (CRC) still remains the leading cause of cancer death worldwide. This study aimed to profile the metabolic differences of colorectal cancer tissues (CCT) at different stages and sites, as compared with their distant noncancerous tissues (DNT), to investigate the temporal and spatial heterogeneities of metabolic characterization. Our NMR-based metabolomics fingerprinting revealed that many of the metabolite levels were significantly altered in CCT compared to DNT and esophageal cancer tissues, indicating deregulations of glucose metabolism, one-carbon metabolism, glutamine metabolism, amino acid metabolism, fatty acid metabolism, TCA cycle, choline metabolism, and so forth. A total of five biomarker metabolites, including glucose, glutamate, alanine, valine and histidine, were identified to distinguish between early and advanced stages of CCT. Metabolites that distinguish the different anatomical sites of CCT include glucose, glycerol, glutamine, inositol, succinate, and citrate. Those significant metabolic differences in CRC tissues at different pathological stages and sites suggested temporal and spatial heterogeneities of metabolic characterization in CCT, providing a metabolic foundation for further study on biofluid metabolism in CRC early detection.

BRAF mutations in colorectal cancer comprise three functional classes: class 1 (V600E) with strong constitutive activation, class 2 with pathogenic kinase activity lower than that of class 1, and class 3 which paradoxically lacks kinase activity. Non-class 1 mutations associate with better prognosis, microsatellite stability, distal tumor location, and better anti-EGFR response. An analysis of 13 colorectal cancer cohorts (n = 6,605 tumors) compared class 1 (n = 709, 10.7% of colorectal cancers), class 2 (n = 31, 0.47%), and class 3 (n = 81, 1.22%) mutations. Class 2-mutant and class 3-mutant colorectal cancers frequently co-occurred with additional Ras pathway mutations (29.0% and 45.7%, respectively, vs. 2.40% in class 1; P < 0.001), often at atypical sites (KRAS noncodon 12/13/61, NRAS, or NF1). Ras pathway activation was highest in class 1 and lowest in class 3, with a greater distal expression of EGFR ligands (amphiregulin/epiregulin) supporting weaker BRAF driver mutations. Unlike class 1 mutants, class 3 tumors resembled chromosomally unstable colorectal cancers in mutation burdens, signatures, driver mutations, and transcriptional subtypes, whereas class 2 mutants displayed intermediate characteristics. Atypical BRAF mutations were associated with longer overall survival than class 1 mutations (HR = 0.25; P = 0.011) but lost this advantage in cancers with additional Ras mutations (HR = 0.94; P = 0.86). This study supports the suggestion that class 3 BRAF mutations amplify existing Ras signaling in a two-mutation model and that the enhancement of weak/atypical Ras mutations may suffice for tumorigenesis, with potentially clinically important heterogeneity in the class 2/3 subgroup. Implications: The heterogeneous nature of BRAF-mutant colorectal cancers, particularly among class 2/3 mutations which frequently harbor additional Ras mutations, highlights the necessity of comprehensive molecular profiling.

Lysine acetyltransferase 2 A (KAT2A) plays a pivotal role in epigenetic gene regulation across various types of cancer. In colorectal cancer (CRC), increased KAT2A expression is associated with a more aggressive phenotype. Our study aims to elucidate the molecular underpinnings of KAT2A dependency in CRC and assess the consequences of KAT2A depletion. We conducted a comprehensive analysis by integrating CRISPR-Cas9 screening data with genomics, transcriptomics, and global acetylation patterns in CRC cell lines to pinpoint molecular markers indicative of KAT2A dependency. Additionally, we characterized the phenotypic effect of a CRISPR-interference-mediated KAT2A knockdown in CRC cell lines and patient-derived 3D spheroid cultures. Moreover, we assessed the effect of KAT2A depletion within a patient-derived xenograft mouse model in vivo. Our findings reveal that KAT2A dependency is closely associated with microsatellite stability, lower mutational burden, and increased molecular differentiation signatures in CRC, independent of the KAT2A expression levels. KAT2A-dependent CRC cells display higher gene expression levels and enriched H3K27ac marks at gene loci linked to enterocytic differentiation. Furthermore, loss of KAT2A leads to decreased cell growth and viability in vitro and in vivo, downregulation of proliferation- and stem cell-associated genes, and induction of differentiation markers. Altogether, our data show that a specific subset of CRCs with a more differentiated phenotype relies on KAT2A. For these CRC cases, KAT2A might represent a promising novel therapeutic target.

The recent global pandemic illustrates the importance of understanding the host cellular infection processes of emerging zoonotic viruses. Nipah virus (NiV) is a deadly zoonotic biosafety level 4 encephalitic and respiratory paramyxovirus. Our knowledge of the molecular cell biology of NiV infection is extremely limited. This study identified changes in cellular components during NiV infection of human cells using a multi-platform, high-throughput transcriptomics, proteomics, lipidomics, and metabolomics approach. Remarkably, validation via multi-disciplinary approaches implicated viral glycoproteins in enriching mitochondria-associated proteins despite an overall decrease in protein translation. Our approach also allowed the mapping of significant fluctuations in the metabolism of glucose, lipids, and several amino acids, suggesting periodic changes in glycolysis and a transition to fatty acid oxidation and glutamine anaplerosis to support mitochondrial ATP synthesis. Notably, these analyses provide an atlas of cellular changes during NiV infections, which is helpful in designing therapeutics against the rapidly growing Henipavirus genus and related viral infections.

Mass spectrometry-based phosphoproteomics offers a comprehensive view of protein phosphorylation, yet our limited knowledge about the regulation and function of most phosphosites hampers the extraction of meaningful biological insights. To address this challenge, we integrate machine learning with phosphoproteomic data from 1195 tumor specimens spanning 11 cancer types to construct CoPheeMap, a network that maps the co-regulation of 26,280 phosphosites. By incorporating network features from CoPheeMap into a second machine learning model, namely CoPheeKSA, we achieve superior performance in predicting kinase-substrate associations. CoPheeKSA uncovers 24,015 associations between 9399 phosphosites and 104 serine/threonine kinases, shedding light on many unannotated phosphosites and understudied kinases. We validate the accuracy of these predictions using experimentally determined kinase-substrate specificities. Through the application of CoPheeMap and CoPheeKSA to phosphosites with high computationally predicted functional significance and those associated with cancer, we demonstrate their effectiveness in systematically elucidating phosphosites of interest. These analyses unveil dysregulated signaling processes in human cancer and identify understudied kinases as potential therapeutic targets.

Clonal hematopoiesis (CH)-the expansion of somatically mutated hematopoietic cells-is common in solid cancers. CH is associated with systemic inflammation, but its impact on tumor biology is underexplored. Here, we report the effects of CH on the tumor microenvironment (TME) using 1,550 treatment-naive patient samples from the Clinical Proteomics Tumor Analysis Consortium (CPTAC) cohort. CH is present in 18.3% of patients, with one-third of CH mutations also detectable in tumor-derived DNA from the same individual (CH-Tum), reflecting CH-mutant leukocyte infiltration. Across cancers, the presence of CH-Tum is associated with worse survival outcomes. Molecular analyses reveal an association between CH-Tum and an immune-rich, inflammatory TME that is notably distinct from age-related gene expression changes. These effects are most prominent in glioblastoma, where CH correlates with pronounced macrophage infiltration, inflammation, and an aggressive, mesenchymal phenotype. Our findings demonstrate that CH shapes the TME, with potential applications as a biomarker in precision oncology.

Proteins play a central role in cancer biology, as are the most common drug targets and biomarkers. Sex influences the proteome in many diseases, ranging from neurological to cardiovascular. In cancer, sex is associated with incidence, progression and therapeutic response, as well as characteristics of the tumour genome and transcriptome. The extent to which sex differences impact the cancer proteome remains largely unknown. To fill this gap, we quantified sex differences across 1,590 proteomes from eight cancer types, identifying 39 genes with sex-differential proteins abundance in adenocarcinomas of the lung and 15 genes in hepatocellular carcinomas, clear cell cancers of the kidney and adenocarcinomas of the pancreas. A subset of these protein differences could be rationalized by sex-differential copy number aberrations. Pathway analysis showed that sex-differential proteins in lung adenocarcinoma were enriched in MYC and E2F target pathways. These findings highlight the modest impact of sex on the cancer proteome, but the very limited power of existing proteomics cohorts for these analyses.

We report proteogenomic analysis of locally advanced cervical cancer (LACC). Exome-seq data revealed predominant alterations of keratinization-TP53 regulation and O-glycosylation-TP53 regulation axes in squamous and adeno-LACC, respectively, compared to in early-stage cervical cancer. Integrated clustering of mRNA, protein, and phosphorylation data identified six subtypes (Sub1-6) of LACC among which Sub3, 5, and 6 showed the treatment-resistant nature with poor local recurrence-free survival. Elevated immune and extracellular matrix (ECM) activation mediated by activated stroma (PDGFD and CXCL1high fibroblasts) characterized the immune-hot Sub3 enriched with MUC5AChigh epithelial cells (ECs). Increased epithelial-mesenchymal-transition (EMT) and ECM remodeling characterized the immune-cold squamous Sub5 enriched with PGK1 and CXCL10high ECs. We further demonstrated that CIC mutations could trigger EMT activation by upregulating ETV4, and the elevation of the immune checkpoint PVR and neutrophil-like myeloid-derived suppressive cells (FCN1 and FCGR3Bhigh macrophages) could cause suppression of T-cell activation in Sub5. Increased O-linked glycosylation of mucin characterized adeno-LACC Sub6 enriched with MUC5AChigh ECs. These results provide a battery of somatic mutations, cellular pathways, and cellular players that can be used to predict treatment-resistant LACC subtypes and can serve as potential therapeutic targets for these LACC subtypes.

Understanding the proteomic-level heterogeneity of the tumor microenvironment (TME) in colorectal cancer (CRC) is crucial due to its well-known heterogeneity. While heterogenous CRC has been extensively characterized at the molecular subtype level, research into the functional heterogeneity of fibroblasts, particularly their relationship with extracellular matrix (ECM) alterations, remains limited. Addressing this gap is essential for a comprehensive understanding of CRC progression and the development of targeted therapies.

24 tissue samples from 21 CRC patients, along with adjacent normal tissues (NAT), were collected and decellularized using a detergent-based method to enrich the ECM component. Proteomic analysis of ECM-enriched samples was performed using tandem mass tag (TMT) spectrometry, followed by statistical analysis including differential expression protein (DEP) analysis. Single-cell RNA sequencing (scRNA-Seq) data from public datasets were integrated and analyzed to delineate cell states within the TME. Bulk tissue RNA-Seq and bioinformatics analysis, including consensus molecular subtype (CMS) classification and single-cell level deconvolution of TCGA bulk RNA-seq data, were conducted to further explore gene expression patterns and TME composition.

Differential cellular origin of the NAT and tumorous ECM proteins were identified, revealing 110 ECM proteins enriched in NAT and 28 ECM proteins in tumor tissues. Desmoplastic and WNT5A+ inflammatory fibroblasts were indicated as the sources of tumor-enriched ECM proteins, while ADAMDEC1+ expressing fibroblasts and PI16+ expressing fibroblast were identified as the sources of NAT-enriched ECM proteins. Deconvolution of bulk RNA-seq of CRC tissues discriminated CMS-specific fibroblast state, reflecting the biological traits of each CMS subtype. Specially, seven ECM genes specific to mesenchymal subtype (CMS4), including PI16+ fibroblast-related 4 genes (SFRP2, PRELP, OGN, SRPX) and desmoplastic fibroblast-related 3 genes (THBS2, CTHRC1, BGN), showed a significant association with poorer survival in patient with CRC.

We conducted an extracellular matrix (ECM)-focused profiling of the TME by integrating quantitative proteomics with single-cell RNA sequencing (scRNA-seq) data from CRC patients. We identified the ECM proteins of NAT and tumor tissue, and established a cell-matrisome database. We defined mesenchymal subtype-specific molecules associated with specific fibroblast subtypes showing a significant association with poorer survival in patients with CRC. Our ECM-focused profiling of tumor stroma provides new insights as indicators for biological processes and clinical endpoints.

Understanding dysregulated genes and pathways in cancer is critical for precision oncology. Integrating mass spectrometry-based proteomic data with transcriptomic data presents unique opportunities for systematic analyses of dysregulated genes and pathways in pan-cancer. Here, we compiled a comprehensive set of datasets, encompassing proteomic data from 2404 samples and transcriptomic data from 7752 samples across 13 cancer types. Comparisons between normal or adjacent normal tissues and tumor tissues identified several dysregulated pathways including mRNA splicing, interferon pathway, fatty acid metabolism, and complement coagulation cascade in pan-cancer. Additionally, pan-cancer upregulated and downregulated genes (PCUGs and PCDGs) were also identified. Notably, RRM2 and ADH1B, two genes which belong to PCUGs and PCDGs, respectively, were identified as robust pan-cancer diagnostic biomarkers. TNM stage-based comparisons revealed dysregulated genes and biological pathways involved in cancer progression, among which the dysregulation of complement coagulation cascade and epithelial-mesenchymal transition are frequent in multiple types of cancers. A group of pan-cancer continuously upregulated and downregulated proteins in different tumor stages (PCCUPs and PCCDPs) were identified. We further constructed prognostic risk stratification models for corresponding cancer types based on dysregulated genes, which effectively predict the prognosis for patients with these cancers. Drug prediction based on PCUGs and PCDGs as well as PCCUPs and PCCDPs revealed that small molecule inhibitors targeting CDK, HDAC, MEK, JAK, PI3K, and others might be effective treatments for pan-cancer, thereby supporting drug repurposing. We also developed web tools for cancer diagnosis, pathologic stage assessment, and risk evaluation. Overall, this study highlights the power of combining proteomic and transcriptomic data to identify valuable diagnostic and prognostic markers as well as drug targets and treatments for cancer.

Chemoresistance is one main cause of failure in colorectal cancer (CRC) treatment. The role of transcription factor Ras-responsive element binding protein 1 (RREB1) remains unclarified in CRC chemoresistance. Herein, we reveal that RREB1 functions as an oncogene to promote cell proliferation and 5-fluorouracil (5-FU) chemoresistance in CRC, and SUMOylation is required for RREB1 to exert its oncogenic role in CRC. RREB1 induced cell cycle arrest at the S-phase and a decreased apoptosis rate under 5-FU exposure. Mechanistically, the interaction of RREB1 with lysine demethylase 1A (KDM1A) elevated expression of 5-FU targeting proteins thymidylate synthase (TS) and thymidine kinase (TK1) to maintain the nucleotide pool balance under 5-FU treatment, and enhanced activation of Chk1-mediated DNA damage response (DDR) pathway. The deSUMOylation of RREB1 resulted in a reduced interaction of RREB1 with KDM1A, contributing to a downregulation of TS expression and a less activation of DDR pathway. Moreover, KDM1A knockdown improved the DNA damage and reduced RREB1-mediated resistance to 5-FU. These findings provide new insights into RREB1-mediated chemotherapy responses in CRC and indicate RREB1 is a potential target for overcoming 5-FU resistance.

Protein phosphorylation plays a crucial role in regulating diverse biological processes. Perturbations in protein phosphorylation are closely associated with downstream pathway dysfunctions, whereas alterations in protein expression could serve as sensitive indicators of pathological status. However, there are currently few methods that can accurately identify the regulatory links between protein phosphorylation and expression, given issues like reverse causation and confounders. Here, we present Phoslink, a causal inference model to infer causal effects between protein phosphorylation and expression, integrating prior evidence and multiomics data. We demonstrated the feasibility and advantages of our method under various simulation scenarios. Phoslink exhibited more robust estimates and lower false discovery rate than commonly used Pearson and Spearman correlations, with better performance than canonical instrumental variable selection methods for Mendelian randomization. Applying this approach, we identified 345 causal links involving 109 phosphosites and 310 proteins in 79 lung adenocarcinoma (LUAD) samples. Based on these links, we constructed a causal regulatory network and identified 26 key regulatory phosphosites as regulators strongly associated with LUAD. Notably, 16 of these regulators were exclusively identified through phosphosite-protein causal regulatory relationships, highlighting the significance of causal inference. We explored potentially druggable phosphoproteins and provided critical clues for drug repurposing in LUAD. We also identified significant mediation between protein phosphorylation and LUAD through protein expression. In summary, our study introduces a new approach for causal inference in phosphoproteomics studies. Phoslink demonstrates its utility in potential drug target identification, thereby accelerating the clinical translation of cancer proteomics and phosphoproteomic data.

Noninvasive prognostic markers are needed to improve the survival of colorectal cancer (CRC) patients. Toward this goal, we applied untargeted systems glycobiology approaches to snap-frozen and formalin-fixed paraffin-embedded tumor tissues and peripheral blood mononuclear cells from CRC patients spanning different disease stages and matching controls to faithfully uncover molecular changes associated with CRC. Quantitative glycomics and immunohistochemistry revealed that noncanonical paucimannosidic N-glycans are elevated in CRC tumors relative to normal adjacent tissues. Cell origin-focused glycoproteomics enabled using the well-curated Human Protein Atlas combined with immunohistochemistry of CRC tumor tissues recapitulated these findings and indicated that the paucimannosidic proteins were in part from tumor-infiltrating monocytes (e.g., MPO, AZU1) and of CRC cell origin (e.g., LGALS3BP, PSAP). Biosynthetically explaining these observations, N-acetyl-β-D-hexosaminidase (Hex) subunit β (HEXB) was found to be overexpressed in CRC tissues relative to normal adjacent colorectal tissues and colocalization and enzyme inhibition studies confirmed that HEXB facilitates paucimannosidic protein biosynthesis in CRC cells. Employing a sensitive, quick, and robust enzyme activity assay, we then showed that Hex activity was elevated in plasma and peripheral blood mononuclear cells from patients with advanced CRC relative to controls and those with early-stage disease. Surveying a large donor cohort, the plasma Hex activity was found to be raised in CRC patients relative to normal controls and correlated with the 5-year survival of CRC patients indicating that elevated plasma Hex activity is a potential disease risk marker for patient outcome. Our glycoproteomics-driven findings open avenues for better prognostication and disease risk stratification in CRC.

Most patients with colorectal cancer do not achieve durable clinical benefits from immunotherapy, underscoring the existence of alternative immunosuppressive mechanisms. Here we found that activation of the lactate receptor HCAR1 signaling pathway induced the expression of chemokines CCL2 and CCL7 in colorectal tumor cells, leading to the recruitment of immunosuppressive CCR2+ polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) to the tumor microenvironment. Ablation of Hcar1 in mice with colorectal tumors significantly decreased the abundance of tumor-infiltrating CCR2+ PMN-MDSCs, enhanced the activation of CD8+ T cells and, consequently, reduced tumor burden. We detected immunosuppressive CCR2+ PMN-MDSCs in tumor specimens from individuals with colorectal and other cancers. The US Food and Drug Administration-approved drug reserpine suppressed lactate-mediated HCAR1 activation, impaired the recruitment of CCR2+ PMN-MDSCs, boosted CD8+ T cell-dependent antitumor immunity and sensitized immunotherapy-resistant tumors to programmed cell death protein 1 antibody therapy in mice with colorectal tumors. Altogether, we described HCAR1-driven recruitment of CCR2+ PMN-MDSCs as a mechanism of immunosuppression.

Advancements in molecular characterization technologies have accelerated targeted cancer therapy research at unprecedented resolution and dimensionality. Integrating comprehensive multi-omic molecular profiling of a tumor, proteogenomics, marks a transformative milestone for preclinical cancer research. In this paper, we initially provided an overview of proteogenomics in cancer research, spanning genomics, transcriptomics, and proteomics. Subsequently, the applications were introduced and examined from different perspectives, including but not limited to genetic alterations, molecular quantifications, single-cell patterns, different post-translational modification levels, subtype signatures, and immune landscape. We also paid attention to the combined multi-omics data analysis and pan-cancer analysis. This paper highlights the crucial role of proteogenomics in preclinical targeted cancer therapy research, including but not limited to elucidating the mechanisms of tumorigenesis, discovering effective therapeutic targets and promising biomarkers, and developing subtype-specific therapies.

Fewer than 50% of metastatic deficient mismatch repair (dMMR) colorectal cancer (CRC) patients respond to immune checkpoint inhibition (ICI). Identifying and expanding this patient population remains a pressing clinical need. Here, we report that an interferon-high immunophenotype locally enriched in cytotoxic lymphocytes and antigen-presenting macrophages is required for response. This immunophenotype is not exclusive to dMMR CRCs but comprises a subset of MMR proficient (pMMR) CRCs. Single-cell spatial analysis and in vitro cell co-cultures indicate that interferon-producing cytotoxic T cells induce overexpression of antigen presentation in adjacent macrophages and tumor cells, including MHC class II invariant chain CD74. dMMR CRCs expressing high levels of CD74 respond to ICI and a subset of CD74 high pMMR CRC patients show better progression free survival when treated with ICI. Therefore, CD74 abundance can identify the constitutive interferon-high immunophenotype determining clinical benefit in CRC, independently of tumor mutational burden or MMR status.

Comprehensive protein profiling in intestinal tissues provides detailed information about the pathogenesis of colorectal cancer (CRC). This study quantified the expression levels of 92 oncology-related proteins in tumors, paired para-carcinoma tissues, and remote normal tissues from a cohort of 52 CRC patients utilizing the Olink technology. The proteomic profile of normal tissues closely resembled that of para-carcinoma tissues while distinctly differing from that of tumors. Among the 68 differentially expressed proteins (DEPs) identified between the tumor and normal tissues, WISP-1, ESM-1, and TFPI-2 showed the most pronounced alterations and exhibited relatively strong correlations. These markers also presented the highest AUC values for distinguishing between tissue types. Bioinformatic analysis of the DEPs revealed that the plasma membrane and the PI3K-AKT signaling pathway were among the most enriched GO terms and KEGG pathways. Furthermore, although TFPI-2 is typically recognized as a tumor suppressor, both Olink and enzyme linked immunosorbent assay (ELISA) analyses have demonstrated that its expression is significantly elevated in tumors compared with paired normal tissues. To the best of our knowledge, this is the first study to profile the proteome of intestinal tissue using the Olink technology. This work offers valuable insights into potential biomarkers and therapeutic targets for CRC, complementing the Olink profiling of circulating proteins.

Type 2 diabetes mellitus (T2DM) has been confirmed as an independent risk factor for colorectal cancer (CRC) in many studies. However, the mechanisms behind T2DM's role in the progression of CRC remain unclear. This study aims to explore the potential biomarkers and molecular mechanisms involved in T2DM-promoted CRC progression. The limma package was used to identify differentially expressed genes in tumor tissue from CRC patients with or without T2DM. The key biological processes were screened by gene ontology and gene set enrichment analysis. A diagnostic model for co-morbidities was constructed by logistic regression model with least absolute shrinkage and selection operator (Lasso) regularization method. The diagnostic performance was assessed by supplementing external datasets to draw ROC curves on the diagnostic model. The diagnostic model was further screened for key genes by prognostic analysis. The relationship of key genes with immune cells and other cells was evaluated by immune infiltration algorithm and single-cell transcription analysis. Drug prediction was performed by cMAP and the obtained drugs were molecularly docked with the key genes. The differentially expressed genes of T2DM-promoted CRC progression were mainly enriched to O-linked glycosylation-related processes. The diagnostic model constructed based on Lasso logistic regression had good diagnostic performance (AUC > 0.8). COX11 was the key gene for co-morbidities: in tumor tissues, COX11 expression was significantly higher than that in normal colon tissues. However, COX11 gene expression was significantly lower in patients with comorbidities than in patients without T2DM in tumor tissue. External datasets confirmed from both mRNA and protein expression levels that low COX11 expression was significantly associated with poor CRC prognosis. Immune infiltration analysis suggested that its expression related to the proportion of M2 macrophages. Single-cell transcriptome analysis revealed a close association of COX11 expression with endothelial cells and macrophages. The top4 drugs predicted bound well to COX11. Our study revealed that the pathogenesis of T2DM-promoted CRC progression related to O-linked glycosylation. We constructed a diagnostic model for T2DM-CRC co-morbidity. Meanwhile, we identified COX11 as a potential immune-related molecular marker closely associated with T2DM-promoted CRC progression. These mechanisms and molecular markers may provide new ideas for further studies of T2DM-promoted CRC progression and contribute to drug discovery for the treatment of co-morbidities.

Although immune checkpoint inhibitor (ICI) therapy is currently the standard of care in microsatellite-unstable (MSI) metastatic colorectal cancer (CRC), ICI therapy, alone or in combination with other therapies, is not a treatment approach in microsatellite-stable (MSS) CRC, which is present in 95% of patients. In this review, we focus on metabolic singularities-at the transcriptomic (either bulk or single cell), proteomic, and post-translational modification levels-that induce immunosuppression in cancer and specifically in MSS CRC. First, we evaluate the current efficacy of ICIs in limited and metastatic disease in MSS CRC. Second, we discuss the latest findings on the potential biomarkers for evaluating ICI efficacy in MSS CRC using strict REMARK criteria. Third, we review the current evidence on metabolic patterns in CRC tumors and immune cell metabolism to advance our understanding of metabolic crosstalk and to pave the way for the development of combination strategies to enhance ICI efficacy.

The effectiveness of radiotherapy in colorectal cancer (CRC) relies on its ability to induce cell death via the generation of reactive oxygen species (ROS). However, genes responsible for mitigating oxidative stress can impede radiotherapy's efficacy. In this study, we elucidate a significant association between the nucleolar protein Fibrillarin (FBL) and the oxidative stress response in CRC tumors. Our findings reveal elevated expression of FBL in colorectal cancer, which positively correlates with oxidative stress levels. Mechanistically, FBL demonstrates direct accumulation at DNA damage sites under the regulation of PARP1. Specifically, the N-terminal GAR domain of FBL is susceptible to PARylation by PARP1, enabling FBL to recognize PARylated proteins. The accumulation of damaged FBL plays a pivotal role in facilitating short-patched base excision repair by recruiting Ligase III and disassociating PCNA and FEN1. Moreover, tumors with heightened FBL expression exhibit reduced DNA damage levels but increased sensitivity to combined low-dose radiotherapy and olaparib treatment. This underscores the potential of leveraging PARP inhibitors to augment radiotherapy sensitivity in CRC cases characterized by elevated FBL expression, offering a promising therapeutic avenue.

Colorectal cancer (CRC) patients with microsatellite-stable (MSS) tumors are mostly treated with chemotherapy. Clinical benefits of targeted therapies depend on mutational states and tumor location. Many tumors carry mutations in KRAS proto-oncogene, GTPase (KRAS) or B-Raf proto-oncogene, serine/threonine kinase (BRAF), rendering them more resistant to therapies. We performed whole-exome sequencing and RNA-Sequencing of 28 tumors of the Athens Comprehensive Cancer Center CRC cohort, and molecularly characterized CRC patients based on their microsatellite instability (MSI) status, single-nucleotide variations (SNVs)/copy number alterations (CNAs), and pathway/transcription factor activities at the individual patient level. Variants were classified using a computational score for integrative cancer variant annotation and prioritization. Complementing this with public multi-omics datasets, we identified activation of transforming growth factor beta (TGFβ) signaling to be more strongly activated in MSS patients, whereas Janus kinase (JAK)-signal transducer and activator of transcription (STAT) and mitogen-activated protein kinase (MAPK) molecular cascades were activated specifically in MSI tumors. We unraveled mechanisms consistently perturbed in the transcriptional and mutational circuits and identified Runt-related transcription factors (RUNX transcription factors) as putative biomarkers in CRC, given their role in the regulation of pathways involved in tumor progression and immune evasion. Assessing the immunogenicity of CRC tumors in the context of RAS/RAF mutations and MSI/MSS status revealed a critical impact that KRAS mutations have on immunogenicity, particularly in the MSS patient subgroup, with implications for diagnosis and treatment.

Pathology, traditionally focused on classification and diagnosis, is continuously evolving through new technologies. Advances in proteomics, epigenetics, tissue staining, and 3D imaging expand the possibilities of classical morphology.

The aim of this study was to investigate how modern technologies can improve diagnostic accuracy and therapy selection and how they can be integrated into pathologic routine diagnostics.

Recent studies in proteomics, epigenetics, multiplex tissue staining, and 3D tissue imaging were analyzed to assess their application and the challenges of clinical implementation.

The analysis shows significant potential for pathologic diagnostics. Proteomics provides a deeper understanding of the molecular architecture of tumors, while epigenetics and 3D genome architecture offer new insights into genetic regulation and tumor heterogeneity. Multiplex tissue staining and 3D tissue imaging improve spatial tissue analysis.

Despite the potential to improve diagnostics, high costs, technical complexity, and lack of standardization hinder integration into clinical practice. Nevertheless, these technologies offer promising approaches for optimizing diagnostics and therapy selection. Research and interdisciplinary collaboration are crucial to successfully integrating these innovations into routine clinical practice.

The integrative multiomics characterization of minute amounts of clinical tissue specimens has become increasingly important. Here, we present an approach called Integral-Omics, which enables sequential extraction of metabolites, lipids, genomic DNA, total RNA, proteins, and phosphopeptides from a single biopsy-level tissue specimen. We benchmarked this method with various samples, applied the workflow to perform multiomics profiling of tissues from six patients with colorectal cancer, and found that tumor tissues exhibited suppressed ferroptosis pathways at multiomics levels. Together, this study presents a methodology that enables sequential extraction and profiling of metabolomics, lipidomics, genomics, transcriptomics, proteomics, and phosphoproteomics using biopsy tissue specimens.

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk tissues. However, such bulk measurement lacks spatial resolution and obscures tissue heterogeneity, precluding proteome mapping of tissue microenvironment. Here we report an integrated wet collection of single microscale tissue voxels and Surfactant-assisted One-Pot voxel processing method termed wcSOP for robust label-free single voxel proteomics. wcSOP capitalizes on buffer droplet-assisted wet collection of single voxels dissected by LCM to the tube cap and SOP voxel processing in the same collection cap. This method enables reproducible, label-free quantification of approximately 900 and 4600 proteins for single voxels at 20 µm × 20 µm × 10 µm (~1 cell region) and 200 µm × 200 µm × 10 µm (~100 cell region) from fresh frozen human spleen tissue, respectively. It can reveal spatially resolved protein signatures and region-specific signaling pathways. Furthermore, wcSOP-MS is demonstrated to be broadly applicable for OCT-embedded and FFPE human archived tissues as well as for small-scale 2D proteome mapping of tissues at high spatial resolutions. wcSOP-MS may pave the way for routine robust single voxel proteomics and spatial proteomics.

Ampullary adenocarcinoma (AMPAC) is a rare and heterogeneous malignancy. Here we performed a comprehensive proteogenomic analysis of 198 samples from Chinese AMPAC patients and duodenum patients. Genomic data illustrate that 4q loss causes fatty acid accumulation and cell proliferation. Proteomic analysis has revealed three distinct clusters (C-FAM, C-AD, C-CC), among which the most aggressive cluster, C-AD, is associated with the poorest prognosis and is characterized by focal adhesion. Immune clustering identifies three immune clusters and reveals that immune cluster M1 (macrophage infiltration cluster) and M3 (DC cell infiltration cluster), which exhibit a higher immune score compared to cluster M2 (CD4+ T-cell infiltration cluster), are associated with a poor prognosis due to the potential secretion of IL-6 by tumor cells and its consequential influence. This study provides a comprehensive proteogenomic analysis for seeking for better understanding and potential treatment of AMPAC.

Cancer mutations are often assumed to alter proteins, thus promoting tumorigenesis. However, how mutations affect protein expression-in addition to gene expression-has rarely been systematically investigated. This is significant as mRNA and protein levels frequently show only moderate correlation, driven by factors such as translation efficiency and protein degradation. Proteogenomic datasets from large tumor cohorts provide an opportunity to systematically analyze the effects of somatic mutations on mRNA and protein abundance and identify mutations with distinct impacts on these molecular levels.

We conduct a comprehensive analysis of mutation impacts on mRNA- and protein-level expressions of 953 cancer cases with paired genomics and global proteomic profiling across 6 cancer types. Protein-level impacts are validated for 47.2% of the somatic expression quantitative trait loci (seQTLs), including CDH1 and MSH3 truncations, as well as other mutations from likely "long-tail" driver genes. Devising a statistical pipeline for identifying somatic protein-specific QTLs (spsQTLs), we reveal several gene mutations, including NF1 and MAP2K4 truncations and TP53 missenses showing disproportional influence on protein abundance not readily explained by transcriptomics. Cross-validating with data from massively parallel assays of variant effects (MAVE), TP53 missenses associated with high tumor TP53 proteins are more likely to be experimentally confirmed as functional.

This study reveals that somatic mutations can exhibit distinct impacts on mRNA and protein levels, underscoring the necessity of integrating proteogenomic data to comprehensively identify functionally significant cancer mutations. These insights provide a framework for prioritizing mutations for further functional validation and therapeutic targeting.

With the increasing demand for precision medicine in cancer patients, radiogenomics emerges as a promising frontier. Radiogenomics is originally defined as a methodology for associating gene expression information from high-throughput technologies with imaging phenotypes. However, with advancements in medical imaging, high-throughput omics technologies, and artificial intelligence, both the concept and application of radiogenomics have significantly broadened. In this review, the history of radiogenomics is enumerated, related omics technologies, the five basic workflows and their applications across tumors, the role of AI in radiogenomics, the opportunities and challenges from tumor heterogeneity, and the applications of radiogenomics in tumor immune microenvironment. The application of radiogenomics in positron emission tomography and the role of radiogenomics in multi-omics studies is also discussed. Finally, the challenges faced by clinical transformation, along with future trends in this field is discussed.

Digestive system neoplasms are highly heterogeneous and exhibit complex resistance mechanisms that render anti-programmed cell death protein (PD) therapies poorly effective. The tumor microenvironment (TME) plays a pivotal role in tumor development, apart from supplying energy for tumor proliferation and impeding the body's anti-tumor immune response, the TME actively facilitates tumor progression and immune escape via diverse pathways, which include the modulation of heritable gene expression alterations and the intricate interplay with the gut microbiota. In this review, we aim to elucidate the mechanisms underlying drug resistance in digestive tumors, focusing on immune-mediated resistance, microbial crosstalk, metabolism, and epigenetics. We will highlight the unique characteristics of each digestive tumor and emphasize the significance of the tumor immune microenvironment (TIME). Furthermore, we will discuss the current therapeutic strategies that hold promise for combination with cancer immune normalization therapies. This review aims to provide a thorough understanding of the resistance mechanisms in digestive tumors and offer insights into potential therapeutic interventions.

Large-scale omics profiling has uncovered a vast array of somatic mutations and cancer-associated proteins, posing substantial challenges for their functional interpretation. Here we present a network-based approach centered on FunMap, a pan-cancer functional network constructed using supervised machine learning on extensive proteomics and RNA sequencing data from 1,194 individuals spanning 11 cancer types. Comprising 10,525 protein-coding genes, FunMap connects functionally associated genes with unprecedented precision, surpassing traditional protein-protein interaction maps. Network analysis identifies functional protein modules, reveals a hierarchical structure linked to cancer hallmarks and clinical phenotypes, provides deeper insights into established cancer drivers and predicts functions for understudied cancer-associated proteins. Additionally, applying graph-neural-network-based deep learning to FunMap uncovers drivers with low mutation frequency. This study establishes FunMap as a powerful and unbiased tool for interpreting somatic mutations and understudied proteins, with broad implications for advancing cancer biology and informing therapeutic strategies.

Ribosomal protein L36A (RPL36A) was one of the most upregulated proteins in colorectal cancer (CRC), yet its role in colorectal cancer (CRC) remains largely unexplored, with limited studies investigating its expression and biological functions. In this investigation, we confirmed a marked upregulation of RPL36A in CRC tissues, correlating with an adverse prognosis. Silencing RPL36A markedly attenuated CRC cell malignant properties and tumor xenograft growth. Further mechanistic analysis indicated that RPL36A depletion diminished phosphorylated ERK levels, subsequently impacting the expression of c-Myc and ELK1, key downstream effectors in the MAPK/ERK pathway. Notably, the tumor-suppressive effects of RPL36A knockdown could be negated by an ERK activator. Collectively, our findings underscore the oncogenic function of RPL36A in CRC and propose it as a potential target for therapeutic intervention.

Chromosomal Instability (CIN) encompasses approximately 65 %-70 % of colorectal cancer (CRC) patients, playing a pivotal role in tumor progression. However, controversies persist regarding the molecular characteristics and treatment strategies associated with these patients. Integrative colorectal cancer proteogenomic analysis identified DDX18 in colorectal cancer. We investigated the molecular mechanisms underlying the regulation of colorectal cancer by the R-loop binding protein DDX18 using colon cancer tissues, cell lines and patient-derived organoids. Our findings revealed that DDX18 expression positively correlates with the expression of genomic instability marker R-loops. Moreover, heightened DDX18 expression delays the completion of DNA damage repair, leading to an increase in double-strand DNA breaks, thereby promoting genomic instability. Notably, the upregulation of DDX18 enhances sensitivity to DNA-damaging. This study elucidated DDX18 beyond participating in fundamental physiological functions, may play a crucial role in the regulation of genomic stability, and also provides a powerful resource for further functional exploration of DDX18 in cancer progression and therapeutic application.

The retinoblastoma (RB) protein which is encoded by RB gene selectively provides a cell type-specific function in malignancies. In colorectal carcinoma, RB has been highly expressed and related cyclin/cyclin-dependent kinase 4/6 inhibitors have shown improved therapeutic effects in some patients. However, little is known about RB in small intestinal adenocarcinoma (SIAC).

Here, we conducted a multi-institutional study of RB expression in 229 surgically resected SIACs to explore the clinicopathologic and prognostic implications and the relationship with microsatellite instability (MSI) status and KRAS mutations.

High RB expression (RBHigh) was more commonly observed in SIACs (76/229, 33%) than in normal small intestinal mucosa (27/188, 14%; P < 0.001). RBHigh was associated with nodular growth patterns (P = 0.028), the absence of lymphovascular (P = 0.001) and perineural invasion (P = 0.048), and a lower T category (P = 0.042) and indicated better overall survival (P = 0.003). In multivariate analysis, RBHigh (P = 0.049) was an independent prognostic predictor of better prognosis, along with younger patient age (P = 0.049), the absence of retroperitoneal seeding (P = 0.004), lower tumor stage (P < 0.001), and MSI (P = 0.005). The prognostic impact of RB expression was consistently observed regardless of MSI status and specifically persistent in SIACs with lower stages (stages I and II).

RBHigh was related to favorable clinicopathologic SIAC characteristics and indicated better patient prognosis. The prognostic predictability of RB was found in SIACs with lower stages, independent of MSI status. RB expression is a reliable and potent prognostic indicator for SIAC and may aid in selecting chemotherapy for patients.

Non-small cell lung cancer (NSCLC) is the main histological subtype of lung cancer. For locally advanced and advanced NSCLC, epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI)-targeted therapy has been the first choice for NSCLC patients with EGFR mutations. TKIs, as targeted drugs, inhibit kinase activity and autophosphorylation by competitively binding to the ATP binding site of the EGFR tyrosine kinase domain, which blocks the signal transduction mediated by EGFR and thus inhibits the proliferation of tumor cells. However, drug resistance to TKIs is inevitable. EGFR is also a highly glycosylated receptor tyrosine kinase, and a wide range of crosstalk occurs between phosphorylation and glycosylation. Therefore, can the phosphorylation state be altered by glycosylation to improve drug resistance? In this review, we summarize phosphorylation, glycosylation and the crosstalk between these processes as well as the current research status and methods. We also summarize the autophosphorylation and glycosylation sites of the EGFR protein and their crosstalk. By exploring the relationship between EGFR glycosylation and autophosphorylation in targeted TKI therapy, we find that research on EGFR glycosylation is crucial for targeted NSCLC treatment and will become a research direction for identifying potential targets related to regulating TKI drug sensitivity.