De novo transcriptomic subtyping of colorectal cancer liver metastases in the context of tumor heterogeneity

CCL19-producing fibroblasts promote tertiary lymphoid structure formation enhancing anti-tumor IgG response in colorectal cancer liver metastasis

Tertiary lymphoid structures (TLSs) are associated with enhanced immunity in tumors. However, their formation and functions in colorectal cancer liver metastasis (CRLM) remain unclear. Here, we reveal that intra- and peri-tumor mature TLSs (TLS+) are associated with improved clinical outcomes than TLS- tumors. Using single-cell-RNA-sequencing and spatial-enhanced-resolution-omics-sequencing (Stereo-seq), we reveal that TLS+ tumors are enriched with IgG+ plasma cells (PCs), while TLS- tumors are characterized with IgA+ PCs. By generating TLS-associated PC-derived monoclonal antibodies in vitro, we show that TLS-PCs secrete tumor-targeting antibodies. As the proof-of-concept, we demonstrate the anti-tumor activities of TLS-PC-mAb6 antibody in humanized mouse model of colorectal cancer. We identify a fibroblast lineage secreting CCL19 that facilitates lymphocyte trafficking to TLSs. CCL19 treatment promotes TLS neogenesis and prevents tumor growth in mice. Our data uncover the central role of CCL19+ fibroblasts in TLS formation, which in turn generates therapeutic antibodies to restrict CRLM.

Changes In Serum CXCL13 Levels Are Associated With Outcomes of Colorectal Cancer Patients Undergoing First-Line Oxaliplatin-Based Treatment

Metastatic colorectal cancer (mCRC) currently lacks reliable biomarkers for precision medicine, particularly for chemotherapy-based treatments. This study examines the behavior of 11 CXC chemokines in the blood of 104 mCRC patients undergoing first-line oxaliplatin-based treatment to pinpoint predictive and prognostic markers. Serum samples were collected before treatment, at response evaluation (EVAR), and at disease progression or last follow-up. Chemokines were assessed in all samples using a Luminex® custom panel. CXCL13 levels increased at EVAR in responders, while in non-responders it decreased. Increasing levels of CXCL13 at EVAR, independently correlated with improved progression-free survival (PFS) and overall survival (OS). Nanostring® analysis in primary tumor samples showed CXCL13 gene expression's positive correlation not only with gene profiles related to an immunogenic tumor microenvironment, increased B cells and T cells (mainly CD8+) but also with extended OS. In silico analysis using RNAseq data from liver metastases treated or not with neoadjuvant oxaliplatin-based combinations, and deconvolution analysis using the MCP-counter algorithm, confirmed CXCL13 gene expression's association with increased immune infiltration, improved OS, and Tertiary Lymphoid Structures (TLSs) gene signatures, especially in neoadjuvant-treated patients. CXCL13 analysis in serum from 36 oxaliplatin-treated patients from the METIMMOX study control arm, reported similar findings. In conclusion, the increase of CXCL13 levels in peripheral blood and its association with the formation of TLSs within the metastatic lesions, emerges as a potential biomarker indicative of the therapeutic efficacy in mCRC patients undergoing oxaliplatin-based treatment.

Biomarker Profile of Colorectal Cancer: Current Findings and Future Perspective

OBJECTIVE

Breakthroughs in omics technology have led to a deeper understanding of the fundamental molecular changes that play a critical role in the development and progression of cancer. This review delves into the hidden molecular drivers of colorectal cancer (CRC), offering potential for clinical translation through novel biomarkers and personalized therapies.

METHODS

We summarizes recent studies utilizing various omics approaches, including genomics, transcriptomics, proteomics, epigenomics, metabolomics and data integration with computational algorithms, to investigate CRC.

RESULTS

Integrating multi-omics data in colorectal cancer research unlocks hidden biological insights, revealing new pathways and mechanisms. This powerful approach not only identifies potential biomarkers for personalized prognosis, diagnosis, and treatment, but also predicts patient response to specific therapies, while computational tools illuminate the landscape by deciphering complex datasets.

CONCLUSIONS

Future research should prioritize validating promising biomarkers and seamlessly translating them into clinical practice, ultimately propelling personalized CRC management to new heights.

Mechanisms of metastatic colorectal cancer

Despite extensive research and improvements in understanding colorectal cancer (CRC), its metastatic form continues to pose a substantial challenge, primarily owing to limited therapeutic options and a poor prognosis. This Review addresses the emerging focus on metastatic CRC (mCRC), which has historically been under-studied compared with primary CRC despite its lethality. We delve into two crucial aspects: the molecular and cellular determinants facilitating CRC metastasis and the principles guiding the evolution of metastatic disease. Initially, we examine the genetic alterations integral to CRC metastasis, connecting them to clinically marked characteristics of advanced CRC. Subsequently, we scrutinize the role of cellular heterogeneity and plasticity in metastatic spread and therapy resistance. Finally, we explore how the tumour microenvironment influences metastatic disease, emphasizing the effect of stromal gene programmes and the immune context. The ongoing research in these fields holds immense importance, as its future implications are projected to revolutionize the treatment of patients with mCRC, hopefully offering a promising outlook for their survival.

Multiregional transcriptomics identifies congruent consensus subtypes with prognostic value beyond tumor heterogeneity of colorectal cancer

Intra-tumor heterogeneity compromises the clinical value of transcriptomic classifications of colorectal cancer. We investigated the prognostic effect of transcriptomic heterogeneity and the potential for classifications less vulnerable to heterogeneity in a single-hospital series of 1093 tumor samples from 692 patients, including multiregional samples from 98 primary tumors and 35 primary-metastasis sets. We show that intra-tumor heterogeneity of the consensus molecular subtypes (CMS) is frequent and has poor-prognostic associations independently of tumor microenvironment markers. Multiregional transcriptomics uncover cancer cell-intrinsic and low-heterogeneity signals that recapitulate the intrinsic CMSs proposed by single-cell sequencing. Further subclassification identifies congruent CMSs that explain a larger proportion of variation in patient survival than intra-tumor heterogeneity. Plasticity is indicated by discordant intrinsic phenotypes of matched primary and metastatic tumors. We conclude that multiregional sampling reconciles the prognostic power of tumor classifications from single-cell and bulk transcriptomics in the context of intra-tumor heterogeneity, and phenotypic plasticity challenges the reconciliation of primary and metastatic subtypes.

Role of Epithelial to Mesenchymal Transition in Colorectal Cancer

The epithelial-mesenchymal transition (EMT) is a cellular reprogramming process that occurs during embryonic development and adult tissue homeostasis. This process involves epithelial cells acquiring a mesenchymal phenotype. Through EMT, cancer cells acquire properties associated with a more aggressive phenotype. EMT and its opposite, mesenchymal-epithelial transition (MET), have been described in more tumors over the past ten years, including colorectal cancer (CRC). When EMT is activated, the expression of the epithelial marker E-cadherin is decreased and the expression of the mesenchymal marker vimentin is raised. As a result, cells temporarily take on a mesenchymal phenotype, becoming motile and promoting the spread of tumor cells. Epithelial-mesenchymal plasticity (EMP) has become a hot issue in CRC because strong inducers of EMT (such as transforming growth factor β, TGF-β) can initiate EMT and regulate metastasis, microenvironment, and immune system resistance in CRC. In this review, we take into account the significance of EMT-MET in CRC and the impact of the epithelial cells' plasticity on the prognosis of CRC. The analysis of connection between EMT and colorectal cancer stem cells (CCSCs) will help to further clarify the current meager understandings of EMT. Recent advances affecting important EMT transcription factors and EMT and CCSCs are highlighted. We come to the conclusion that the regulatory network for EMT in CRC is complicated, with a great deal of crosstalk and alternate paths. More thorough research is required to more effectively connect the clinical management of CRC with biomarkers and targeted treatments associated with EMT.

Transcriptomic Maps of Colorectal Liver Metastasis: Machine Learning of Gene Activation Patterns and Epigenetic Trajectories in Support of Precision Medicine

The molecular mechanisms of the liver metastasis of colorectal cancer (CRLM) remain poorly understood. Here, we applied machine learning and bioinformatics trajectory inference to analyze a gene expression dataset of CRLM. We studied the co-regulation patterns at the gene level, the potential paths of tumor development, their functional context, and their prognostic relevance. Our analysis confirmed the subtyping of five liver metastasis subtypes (LMS). We provide gene-marker signatures for each LMS, and a comprehensive functional characterization that considers both the hallmarks of cancer and the tumor microenvironment. The ordering of CRLMs along a pseudotime-tree revealed a continuous shift in expression programs, suggesting a developmental relationship between the subtypes. Notably, trajectory inference and personalized analysis discovered a range of epigenetic states that shape and guide metastasis progression. By constructing prognostic maps that divided the expression landscape into regions associated with favorable and unfavorable prognoses, we derived a prognostic expression score. This was associated with critical processes such as epithelial-mesenchymal transition, treatment resistance, and immune evasion. These factors were associated with responses to neoadjuvant treatment and the formation of an immuno-suppressive, mesenchymal state. Our machine learning-based molecular profiling provides an in-depth characterization of CRLM heterogeneity with possible implications for treatment and personalized diagnostics.

Tumor heterogeneity: An oncogenic driver of PDAC progression and therapy resistance under stress conditions

Pancreatic ductal adenocarcinoma (PDAC) is a clinically challenging disease usually diagnosed at advanced or metastasized stage. By this year end, there are an expected increase in 62,210 new cases and 49,830 deaths in the United States, with 90% corresponding to PDAC subtype alone. Despite advances in cancer therapy, one of the major challenges combating PDAC remains tumor heterogeneity between PDAC patients and within the primary and metastatic lesions of the same patient. This review describes the PDAC subtypes based on the genomic, transcriptional, epigenetic, and metabolic signatures observed among patients and within individual tumors. Recent studies in tumor biology suggest PDAC heterogeneity as a major driver of disease progression under conditions of stress including hypoxia and nutrient deprivation, leading to metabolic reprogramming. We therefore advance our understanding in identifying the underlying mechanisms that interfere with the crosstalk between the extracellular matrix components and tumor cells that define the mechanics of tumor growth and metastasis. The bilateral interaction between the heterogeneous tumor microenvironment and PDAC cells serves as another important contributor that characterizes the tumor-promoting or tumor-suppressing phenotypes providing an opportunity for an effective treatment regime. Furthermore, we highlight the dynamic reciprocating interplay between the stromal and immune cells that impact immune surveillance or immune evasion response and contribute towards a complex process of tumorigenesis. In summary, the review encapsulates the existing knowledge of the currently applied treatments for PDAC with emphasis on tumor heterogeneity, manifesting at multiple levels, impacting disease progression and therapy resistance under stress.

Localization and density of tertiary lymphoid structures associate with molecular subtype and clinical outcome in colorectal cancer liver metastases

BACKGROUND

Tertiary lymphoid structures (TLSs) have been proposed to assess the prognosis of patients with cancer. Here, we investigated the prognostic value and relevant mechanisms of TLSs in colorectal cancer liver metastases (CRCLM).

METHODS

603 patients with CRCLM treated by surgical resection from three cancer centers were included. The TLSs were categorized according to their anatomic subregions and quantified, and a TLS scoring system was established for intratumor region (T score) and peritumor region (P score). Differences in relapse-free survival (RFS) and overall survival (OS) between groups were determined. Multiplex immunohistochemical staining (mIHC) was used to determine the cellular composition of TLSs in 40 CRCLM patients.

RESULTS

T score positively correlated with superior prognosis, while P score negatively associated with poor survival (all p<0.05). Meanwhile, T score was positively associated with specific mutation subtype of KRAS. Furthermore, TLSs enrichment gene expression was significantly associated with survival and transcriptomic subtypes of CRCLM. Subsequently, mIHC showed that the densities of Treg cells, M2 macrophages and Tfh cells were significantly higher in intratumor TLSs than in peritumor TLSs (p=0.029, p=0.047 and p=0.041, respectively), and the frequencies of Treg cells and M2 macrophages were positively correlated with P score, while the frequencies of Tfh cells were positively associated with T scores in intratumor TLSs (all p<0.05). Next, based on the distribution and abundance of TLSs, an Immune Score combining T score and P score was established which categorized CRCLM patients into four immune classes with different prognosis (all p<0.05). Among them, patients with higher immune class have more favorable prognoses. The C-index of Immune Class for RFS and OS was higher than Clinical Risk Score statistically. These results were also confirmed by the other two validation cohorts.

CONCLUSIONS

The distribution and abundance of TLSs is significantly associated with RFS and OS of CRCLM patients, and a novel immune class was proposed for predicting the prognosis of CRCLM patients.

DrugMAP: molecular atlas and pharma-information of all drugs

The efficacy and safety of drugs are widely known to be determined by their interactions with multiple molecules of pharmacological importance, and it is therefore essential to systematically depict the molecular atlas and pharma-information of studied drugs. However, our understanding of such information is neither comprehensive nor precise, which necessitates the construction of a new database providing a network containing a large number of drugs and their interacting molecules. Here, a new database describing the molecular atlas and pharma-information of drugs (DrugMAP) was therefore constructed. It provides a comprehensive list of interacting molecules for >30 000 drugs/drug candidates, gives the differential expression patterns for >5000 interacting molecules among different disease sites, ADME (absorption, distribution, metabolism and excretion)-relevant organs and physiological tissues, and weaves a comprehensive and precise network containing >200 000 interactions among drugs and molecules. With the great efforts made to clarify the complex mechanism underlying drug pharmacokinetics and pharmacodynamics and rapidly emerging interests in artificial intelligence (AI)-based network analyses, DrugMAP is expected to become an indispensable supplement to existing databases to facilitate drug discovery. It is now fully and freely accessible at: https://idrblab.org/drugmap/.

Establishment of a novel prognostic signature based on an identified expression profile of integrin superfamily to predict overall survival of patients with colorectal adenocarcinoma

The abnormal expression of integrin superfamily members commonly related to kinds of malignancies. However, the role of integrins in predicting the prognosis of cancers is still little known, especially for colorectal cancer that is one of the leading causes of cancer-related death. RNA-seq data and clinical features of colorectal adenocarcinoma (COAD) patients were derived from The Cancer Genome Atlas (TCGA), used to analyze the expression pattern and genomic alterations of integrin genes in the COAD cohort. Unsupervised hierarchical clustering divided COAD patients into two clusters (clusters 1 & 2), and we observed that patients in cluster 2 with high expressions of most integrin genes had worse clinical features and shorter overall survival (a median OS: 67.25 months vs 99.93 months, p = 0.012), compared to those in cluster 1. Combined with univariate Cox regression analysis, Pearson Correlation Coefficients (PCC), and Principal Component Analysis (PCA), an integrin-related signature was established, including ITGA1, ITGA5, ITGA7, ITGA11, ITGAX, ITGAM, ITGB1, and ITGB5. And the AUC values for OS at 1, 3, and 5 years was 0.61, 0.59, and 0.56, further demonstrating the predicting capacity of our signature. Furthermore, overexpression of which also significantly correlated with poorer prognosis of colon cancer patients in a separate validation cohort, GSE17536 (p < 0.05). Meanwhile, the AUC values for OS in the validation cohort at 1, 3, and 5 years was 0.62, 0.59, and 0.59. Additionally, enrichment analysis indicated significant differences between cluster 1 and cluster 2 in the biological processes of cell adhesion, signal transduction, extracellular matrix, immune system, and in tumor microenvironment (TME), which were crucial to the progression of tumor. The findings supplied compelling evidence that our signature could be a novel prognostic biomarker for COAD patients, and these genes had the potential to be therapeutic targets.