Stromal contribution to the colorectal cancer transcriptome

Targeting the devil: Strategies against cancer-associated fibroblasts in colorectal cancer

Cancer-associated fibroblasts (CAFs), as significant constituents of the tumor microenvironment (TME), play a pivotal role in the progression of cancers, including colorectal cancer (CRC). In this comprehensive review, we presented the origins and activation mechanisms of CAFs in CRC, elaborating on how CAFs drive tumor progression through their interactions with CRC cells, immune cells, vascular endothelial cells, and the extracellular matrix within the TME. We systematically outline the intricate web of interactions among CAFs, tumor cells, and other TME components, and based on this complex interplay, we summarize various therapeutic strategies designed to target CAFs in CRC. It is also essential to recognize that CAFs represent a highly heterogeneous group, encompassing various subtypes such as myofibroblastic CAF (myCAF), inflammatory CAF (iCAF), antigen-presenting CAF (apCAF), vessel-associated CAF (vCAF). Herein, we provide a summary of studies investigating the heterogeneity of CAFs in CRC and the characteristic expression patterns of each subtype. While the majority of CAFs contribute to the exacerbation of CRC malignancy, recent findings have revealed specific subtypes that exert inhibitory effects on CRC progression. Nevertheless, the comprehensive landscape of CAF heterogeneity still awaits exploration. We also highlight pivotal unanswered questions that need to be addressed before CAFs can be recognized as feasible targets for cancer treatment. In conclusion, the aim of our review is to elucidate the significance and challenges of advancing in-depth research on CAFs, while outlining the pathway to uncover the complex roles of CAFs in CRC and underscore their significant potential as therapeutic targets.

Investigating the effect of Fusobacterium nucleatum on the aggressive behavior of cancer-associated fibroblasts in colorectal cancer

Fusobacterium nucleatum, (F. nucleatum) as a known factor in inducing oncogenic, invasive, and inflammatory responses, can lead to an increase in the incidence and progression of colorectal cancer (CRC). Cancer-associated fibroblasts (CAF) are also one of the key components of the tumor microenvironment (TME), which lead to resistance to treatment, metastasis, and disease recurrence with their markers, secretions, and functions. This study aimed to investigate the effect of F. nucleatum on the invasive phenotype and function of fibroblast cells isolated from normal and cancerous colorectal tissue. F. nucleatum bacteria were isolated from deep periodontal pockets and confirmed by various tests. CAF cells from tumor tissue and normal fibroblasts (NF) from a distance of 10 cm of tumor tissue were isolated from 5 patients by the explant method and were exposed to secretions and ghosts of F. nucleatum. The expression level of two markers, fibroblast activation protein (FAP), and α-smooth muscle actin (α-SMA), and the amount of production of two cytokines TGF-β and IL-6 from fibroblast cells were measured by flow cytometry and ELISA test, respectively before and after exposure to different bacterial components. The expression of the FAP marker was significantly higher in CAF cells compared to NF cells (P < 0.05). Also, the expression of IL-6 in CAF cells was higher than that of NF cells. In investigating the effect of bacterial components on the function of fibroblastic cells, after comparing the amount of IL-6 produced between the normal tissue of each patient and his tumoral tissue under 4 treated conditions, it was found that the amount of IL-6 production from the CAF cells of patients in the control group, treated with heat-killed ghosts and treated with paraformaldehyde-fixed ghosts had a significant increase compared to NF cells (P < 0.05). Due to the significant increase in FAP marker expression in fibroblast cells of tumor tissue compared to normal tissue, it seems that FAP can be used as a very good therapeutic marker, especially in patients with high levels of CAF cells. Various components of F. nucleatum could affect fibroblast cells differentially and at least part of the effect of this bacterium in the TME is mediated by CAF cells.

Transcriptomic subtyping of gastrointestinal malignancies

Gastrointestinal (GI) cancers are highly heterogeneous at multiple levels. Tumor heterogeneity can be captured by molecular profiling, such as genetic, epigenetic, proteomic, and transcriptomic classification. Transcriptomic subtyping has the advantage of combining genetic and epigenetic information, cancer cell-intrinsic properties, and the tumor microenvironment (TME). Unsupervised transcriptomic subtyping systems of different GI malignancies have gained interest because they reveal shared biological features across cancers and bear prognostic and predictive value. Importantly, transcriptomic subtypes accurately reflect complex phenotypic states varying not only per tumor region, but also throughout disease progression, with consequences for clinical management. Here, we discuss methodologies of transcriptomic subtyping, proposed taxonomies for GI malignancies, and the challenges posed to clinical implementation, highlighting opportunities for future transcriptomic profiling efforts to optimize clinical impact.

Stromal cell-expressed malignant gene patterns contribute to the progression of squamous cell carcinomas across different sites

Background

Squamous cell carcinomas (SCCs) across different anatomical locations possess common molecular features. Recent studies showed that stromal cells may contribute to tumor progression and metastasis of SCCs. Limited by current sequencing technology and analysis methods, it has been difficult to combine stroma expression profiles with a large number of clinical information.

Methods

With the help of transfer learning on the cell line, single-cell, and bulk tumor sequencing data, we identified and validated 2 malignant gene patterns (V1 and V5) expressed by stromal cells of SCCs from head and neck (HNSCC), lung (LUSC), cervix (CESC), esophagus, and breast.

Results

Pattern V5 reflected a novel malignant feature that explained the mixed signals of HNSCC molecular subtypes. Higher expression of pattern V5 was related to shorter PFI with gender and cancer-type specificity. The other stromal gene pattern V1 was associated with poor PFI in patients after surgery in all the three squamous cancer types (HNSCC p = 0.0055, LUSC p = 0.0292, CESC p = 0.0451). Cancer-associated fibroblasts could induce HNSCC cancer cells to express pattern V1. Adjuvant radiotherapy may weaken the effect of high V1 on recurrence and metastasis, depending on the tumor radiosensitivity.

Conclusion

Considering the prognostic value of stromal gene patterns and its universality, we suggest that the genetic subtype classification of SCCs may be improved to a new system that integrates both malignant and non-malignant components.

Oxidized Melanoma Antigens Promote Activation and Proliferation of Cytotoxic T-Cell Subpopulations

Increasing evidence suggests the role of reactive oxygen and nitrogen species (RONS) in regulating antitumor immune effects and immunosuppression. RONS modify biomolecules and induce oxidative post-translational modifications (oxPTM) on proteins that can alarm phagocytes. However, it is unclear if and how protein oxidation by technical means could be a strategy to foster antitumor immunity and therapy. To this end, cold gas plasma technology producing various RONS simultaneously to oxidize the two melanoma-associated antigens MART and PMEL is utilized. Cold plasma-oxidized MART (oxMART) and PMEL (oxPMEL) are heavily decorated with oxPTMs as determined by mass spectrometry. Immunization with oxidized MART or PMEL vaccines prior to challenge with viable melanoma cells correlated with significant changes in cytokine secretion and altered T-cell differentiation of tumor-infiltrated leukocytes (TILs). oxMART promoted the activity of cytotoxic central memory T-cells, while oxPMEL led to increased proliferation of cytotoxic effector T-cells. Similar T-cell results are observed after incubating splenocytes of tumor-bearing mice with B16F10 melanoma cells. This study, for the first time, provides evidence of the importance of oxidative modifications of two melanoma-associated antigens in eliciting anticancer immunity.

Molecular subtypes of colorectal cancer in the era of precision oncotherapy: Current inspirations and future challenges

BACKGROUND

Colorectal cancer (CRC) is among the most hackneyed malignancies. Even patients with identical clinical symptoms and the same TNM stage still exhibit radically different clinical outcomes after receiving equivalent treatment regimens, indicating extensive heterogeneity of CRC. Myriad molecular subtypes of CRC have been exploited for decades, including the most compelling consensus molecular subtype (CMS) classification that has been broadly applied for patient stratification and biomarker-drug combination formulation. Encountering barriers to clinical translation, however, CMS classification fails to fully reflect inter- or intra-tumor heterogeneity of CRC. As a consequence, addressing heterogeneity and precisely managing CRC patients with unique characteristics remain arduous tasks for clinicians.

REVIEW

In this review, we systematically summarize molecular subtypes of CRC and further elaborate on their clinical applications, limitations, and future orientations.

CONCLUSION

In recent years, exploration of subtypes through cell lines, animal models, patient-derived xenografts (PDXs), organoids, and clinical trials contributes to refining biological insights and unraveling subtype-specific therapies in CRC. Therapeutic interventions including nanotechnology, clustered regulatory interspaced short palindromic repeat/CRISPR-associated nuclease 9 (CRISPR/Cas9), gut microbiome, and liquid biopsy are powerful tools with the possibility to shift the immunologic landscape and outlook for CRC precise medicine.

ZEB1-mediated fibroblast polarization controls inflammation and sensitivity to immunotherapy in colorectal cancer

The EMT-transcription factor ZEB1 is heterogeneously expressed in tumor cells and in cancer-associated fibroblasts (CAFs) in colorectal cancer (CRC). While ZEB1 in tumor cells regulates metastasis and therapy resistance, its role in CAFs is largely unknown. Combining fibroblast-specific Zeb1 deletion with immunocompetent mouse models of CRC, we observe that inflammation-driven tumorigenesis is accelerated, whereas invasion and metastasis in sporadic cancers are reduced. Single-cell transcriptomics, histological characterization, and in vitro modeling reveal a crucial role of ZEB1 in CAF polarization, promoting myofibroblastic features by restricting inflammatory activation. Zeb1 deficiency impairs collagen deposition and CAF barrier function but increases NFκB-mediated cytokine production, jointly promoting lymphocyte recruitment and immune checkpoint activation. Strikingly, the Zeb1-deficient CAF repertoire sensitizes to immune checkpoint inhibition, offering a therapeutic opportunity of targeting ZEB1 in CAFs and its usage as a prognostic biomarker. Collectively, we demonstrate that ZEB1-dependent plasticity of CAFs suppresses anti-tumor immunity and promotes metastasis.

Dietary vitamin D intake and risk of colorectal cancer according to vitamin D receptor expression in tumors and their surrounding stroma

BACKGROUND

Colorectal Cancer (CRC) has been molecularly classified into several subtypes according to tumor, stromal, and immune components. Here, we investigated whether the preventive effect of vitamin D on CRC varies with subtypes defined by Vitamin D receptor (VDR) expression in tumors and their surrounding stroma, along with the association of somatic mutations in CRC.

METHODS

In a population-based prospective study of 22,743 Japanese participants, VDR expression levels in tumors and their surrounding stroma were defined in 507 cases of newly diagnosed CRC using immunohistochemistry. Hazard ratios of CRC and its subtypes according to dietary vitamin D intake were estimated using multivariable Cox proportional hazards models.

RESULTS

Dietary vitamin D intake was not associated with CRC or its subtypes defined by VDR expression in tumors. However, an inverse association was observed for CRC with high VDR expression in the stroma (the highest tertile vs the lowest tertile: 0.46 [0.23-0.94], Ptrend = 0.03), but not for CRC with low VDR expression in the stroma (Pheterogeneity = 0.02). Furthermore, CRC with high VDR expression in the stroma had more somatic TP53 and BRAF mutations and fewer APC mutations than those with low VDR expression in the stroma.

CONCLUSIONS

This study provides the first evidence that the preventive effect of vitamin D on CRC depends on VDR expression in the stroma rather than in the tumors. CRC with high VDR expression in the stroma is likely to develop through a part of the serrated polyp pathway, which tends to occur with BRAF but not with APC mutations.

Preclinical efficacy of a HER2 synNotch/CEA-CAR combinatorial immunotherapy against colorectal cancer with HER2 amplification

HER2 amplification occurs in approximately 5% of colorectal cancer (CRC) cases and is associated only partially with clinical response to combined human epidermal growth factor receptor 2 (HER2)/epidermal growth factor receptor (EGFR)-targeted treatment. An alternative approach based on adoptive cell therapy using T cells engineered with anti-HER2 chimeric antigen receptor (CAR) proved to be toxic due to on-target/off-tumor activity. Here we describe a combinatorial strategy to safely target HER2 amplification and carcinoembryonic antigen (CEA) expression in CRC using a synNotch-CAR-based artificial regulatory network. The natural killer (NK) cell line NK-92 was engineered with an anti-HER2 synNotch receptor driving the expression of a CAR against CEA only when engaged. After being transduced and sorted for HER2-driven CAR expression, cells were cloned. The clone with optimal performances in terms of specificity and amplitude of CAR induction demonstrated significant activity in vitro and in vivo specifically against HER2-amplified (HER2amp)/CEA+ CRC models, with no effects on cells with physiological HER2 levels. The HER2-synNotch/CEA-CAR-NK system provides an innovative, scalable, and safe off-the-shelf cell therapy approach with potential against HER2amp CRC resistant or partially responsive to HER2/EGFR blockade.

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.

TGFβ-Responsive Stromal Activation Occurs Early in Serrated Colorectal Carcinogenesis

Activated TGFβ signaling in the tumor microenvironment, which occurs independently of epithelial cancer cells, has emerged as a key driver of tumor progression in late-stage colorectal cancer (CRC). This study aimed to elucidate the contribution of TGFβ-activated stroma to serrated carcinogenesis, representing approximately 25% of CRCs and often characterized by oncogenic BRAF mutations. We used a transcriptional signature developed based on TGFβ-responsive, stroma-specific genes to infer TGFβ-dependent stromal activation and conducted in silico analyses in 3 single-cell RNA-seq datasets from a total of 39 CRC samples and 12 bulk transcriptomic datasets consisting of 2014 CRC and 416 precursor samples, of which 33 were serrated lesions. Single-cell analyses validated that the signature was expressed specifically by stromal cells, effectively excluding transcriptional signals derived from epithelial cells. We found that the signature was upregulated during malignant transformation and cancer progression, and it was particularly enriched in CRCs with mutant BRAF compared to wild-type counterparts. Furthermore, across four independent precursor datasets, serrated lesions exhibited significantly higher levels of TGFβ-responsive stromal activation compared to conventional adenomas. This large-scale analysis suggests that TGFβ-dependent stromal activation occurs early in serrated carcinogenesis. Our study provides novel insights into the molecular mechanisms underlying CRC development via the serrated pathway.

Unselective Measurement of Tumor-to-Stroma Proportion in Colon Cancer at the Invasion Front-An Elusive Prognostic Factor: Original Patient Data and Review of the Literature

The tumor-to-stroma ratio is a highly debated prognostic factor in the management of several solid tumors and there is no universal agreement on its practicality. In our study, we proposed confirming or dismissing the hypothesis that a simple measurement of stroma quantity is an easy-to-use and strong prognostic tool. We have included 74 consecutive patients with colorectal cancer who underwent primary curative abdominal surgery. The tumors have been grouped into stroma-poor (stroma < 10%), medium-stroma (between 10 and 50%) and stroma-rich (over 50%). The proportion of tumor stroma ranged from 5% to 70% with a median of 25%. Very few, only 6.8% of patients, had stroma-rich tumors, 4% had stroma-poor tumors and 89.2% had tumors with a medium quantity of stroma. The proportion of stroma, at any cut-off, had no statistically significant influence on the disease-specific survival. This can be explained by the low proportion of stroma-rich tumors in our patient group and the inverse correlation between stroma proportion and tumor grade. The real-life proportion of stroma-rich tumors and the complex nature of the stroma-tumor interaction has to be further elucidated.

Metabolic difference between patient-derived xenograft model of pancreatic ductal adenocarcinoma and corresponding primary tumor

BACKGROUND

Patients-derived xenograft (PDX) model have been widely used for tumor biological and pathological studies. However, the metabolic similarity of PDX tumor to the primary cancer (PC) is still unknown.

METHODS

In present study, we established PDX model by engrafting primary tumor of pancreatic ductal adenocarcinoma (PDAC), and then compared the tumor metabolomics of PC, the first generation of PDX tumor (PDXG1), and the third generation of PDX tumor (PDXG3) by using 1H NMR spectroscopy. Then, we assessed the differences in response to chemotherapy between PDXG1 and PDXG3 and corresponding metabolomic differences in drug-resistant tumor tissues. To evaluate the metabolomic similarity of PDX to PC, we also compared the metabolomic difference of cell-derived xenograft (CDX) vs. PC and PDX vs. PC.

RESULTS

After engraftment, PDXG1 tumor had a low level of lactate, pyruvate, citrate and multiple amino acids (AAs) compared with PC. Metabolite sets enrichment and metabolic pathway analyses implied that glycolysis metabolisms were suppressed in PDXG1 tumor, and tricarboxylic acid cycle (TCA)-associated anaplerosis pathways, such as amino acids metabolisms, were enhanced. Then, after multiple passages of PDX, the altered glycolysis and TCA-associated anaplerosis pathways were partially recovered. Although no significant difference was observed in the response of PDXG1 and PDXG3 to chemotherapy, the difference in glycolysis and amino acids metabolism between PDXG1 and PDXG3 could still be maintained. In addition, the metabolomic difference between PC and CDX models were much larger than that of PDX model and PC, indicating that PDX model still retain more metabolic characteristics of primary tumor which is more suitable for tumor-associated metabolism research.

CONCLUSIONS

Compared with primary tumor, PDX models have obvious difference in metabolomic level. These findings can help us design in vivo tumor metabolomics research legitimately and analyze the underlying mechanism of tumor metabolic biology thoughtfully.

TSPAN8+ myofibroblastic cancer-associated fibroblasts promote chemoresistance in patients with breast cancer

Cancer-associated fibroblasts (CAFs) are abundant stromal cells in the tumor microenvironment that promote cancer progression and relapse. However, the heterogeneity and regulatory roles of CAFs underlying chemoresistance remain largely unclear. Here, we performed a single-cell analysis using high-dimensional flow cytometry analysis and identified a distinct senescence-like tetraspanin-8 (TSPAN8)+ myofibroblastic CAF (myCAF) subset, which is correlated with therapeutic resistance and poor survival in multiple cohorts of patients with breast cancer (BC). TSPAN8+ myCAFs potentiate the stemness of the surrounding BC cells through secretion of senescence-associated secretory phenotype (SASP)-related factors IL-6 and IL-8 to counteract chemotherapy. NAD-dependent protein deacetylase sirtuin 6 (SIRT6) reduction was responsible for the senescence-like phenotype and tumor-promoting role of TSPAN8+ myCAFs. Mechanistically, TSPAN8 promoted the phosphorylation of ubiquitin E3 ligase retinoblastoma binding protein 6 (RBBP6) at Ser772 by recruiting MAPK11, thereby inducing SIRT6 protein destruction. In turn, SIRT6 down-regulation up-regulated GLS1 and PYCR1, which caused TSPAN8+ myCAFs to secrete aspartate and proline, and therefore proved a nutritional niche to support BC outgrowth. By demonstrating that TSPAN8+SIRT6low myCAFs were tightly associated with unfavorable disease outcomes, we proposed that the combined regimen of anti-TSPAN8 antibody and SIRT6 activator MDL-800 is a promising approach to overcome chemoresistance. These findings highlight that senescence contributes to CAF heterogeneity and chemoresistance and suggest that targeting TSPAN8+ myCAFs is a promising approach to circumvent chemoresistance.

Transcriptional profile and immune infiltration in colorectal cancer reveal the significance of inducible T-cell costimulator as a crucial immune checkpoint molecule

BACKGROUND

Emergence of novel immuno-therapeutics has shown promising improvement in the clinical outcome of colorectal cancer (CRC).

OBJECTIVE

To identify robust immune checkpoints based on expression and immune infiltration profiles of clinical CRC samples.

METHODS

One dataset from The Cancer Genome Atlas database and two from Gene Expression Omnibus were independently employed for the analysis. Genes associated with overall survival were identified, and distribution of each immune checkpoint with respect to different clinical features was determined to explore key immune checkpoints. Multiple staining methods were used to verify the correlation between key immune checkpoint ICOS and clinical pathological features. Differentially expressed mRNA and long non-coding RNA (lncRNA) were then detected for gene set enrichment analysis and gene set variation analysis to investigate the differentially enriched biological processes between low- and high-expression groups. Significant immune-related mRNAs and lncRNA were subjected to competing endogenous RNA (ceRNA) network analysis. Correlation of inducible T-cell costimulator (ICOS) and top 10 genes in ceRNA network were further considered for validation.

RESULTS

ICOS was identified from 14 immune checkpoints as the most highly correlated gene with survival and clinical features in CRC. The expression of ICOS protein in the poorly differentiated group was lower than that in the moderately differentiated group, and the expression in different pathological stages was significant. In addition, the expressions of ICOS were negatively correlated with Ki67. A conspicuous number of immune-related pathways were enriched in differentially expressed genes in the ICOS high- and low-expression groups. Integration with immune infiltration data revealed a multitude of differentially expressed immune-related genes enriched for ceRNA network. Furthermore, expression of top 10 genes investigated from ceRNA network showed high correlation with ICOS.

CONCLUSION

ICOS might serve as a robust immune checkpoint for prognosis with several genes being potential targets of ICOS-directed immunotherapy in CRC.

Stromal Signals Dominate Gene Expression Signature Scores That Aim to Describe Cancer Cell-intrinsic Stemness or Mesenchymality Characteristics

Epithelial-to-mesenchymal transition (EMT) in cancer cells confers migratory abilities, a crucial aspect in the metastasis of tumors that frequently leads to death. In multiple studies, authors proposed gene expression signatures for EMT, stemness, or mesenchymality of tumors based on bulk tumor expression profiling. However, recent studies suggested that noncancerous cells from the microenvironment or macroenvironment heavily influence such signature profiles. Here, we strengthen these findings by investigating 11 published and frequently referenced gene expression signatures that were proposed to describe EMT-related (EMT, mesenchymal, or stemness) characteristics in various cancer types. By analyses of bulk, single-cell, and pseudobulk expression data, we show that the cell type composition of a tumor sample frequently dominates scores of these EMT-related signatures. A comprehensive, integrated analysis of bulk RNA sequencing (RNA-seq) and single-cell RNA-seq data shows that stromal cells, most often fibroblasts, are the main drivers of EMT-related signature scores. We call attention to the risk of false conclusions about tumor properties when interpreting EMT-related signatures, especially in a clinical setting: high patient scores of EMT-related signatures or calls of "stemness subtypes" often result from low cancer cell content in tumor biopsies rather than cancer cell-specific stemness or mesenchymal/EMT characteristics.

SIGNIFICANCE

Cancer self-renewal and migratory abilities are often characterized via gene module expression profiles, also called EMT or stemness gene expression signatures. Using published clinical tumor samples, cancer cell lines, and single cancer cells, we highlight the dominating influence of noncancer cells in low cancer cell content biopsies on their scores. We caution on their application for low cancer cell content clinical cancer samples with the intent to assign such characteristics or subtypes.

Molecular pathological classification of colorectal cancer-an update

Colorectal cancer (CRC) has a broad range of molecular alterations with two major mechanisms of genomic instability (chromosomal instability and microsatellite instability) and has been subclassified into 4 consensus molecular subtypes (CMS) based on bulk RNA sequence data. Here, we update the molecular pathological classification of CRC with an overview of more recent bulk and single-cell RNA data analysis for development of transcriptional classifiers and risk stratification methods, taking into account the marked inter-tumoural and intra-tumoural heterogeneity of CRC. The importance of the stromal and immune components or tumour microenvironment (TME) to prognosis has emerged from these analyses. Attempts to remove the contribution of the tumour microenvironment and reveal neoplastic-specific transcriptional traits involved identification of the CRC intrinsic subtypes (CRIS). The use of immunohistochemistry and digital pathology to implement classification systems are evolving fields. Conventional adenoma versus serrated polyp pathway transcriptomic analysis and characterisation of canonical LGR5+ crypt base columnar stem cell versus ANXA1+ regenerative stem cell phenotypes emerged as key properties for improved understanding of transcriptional signals involved in molecular subclassification of colorectal cancers. Recently, classification by three pathway-derived subtypes (PDS1-3) has been developed, revealing a continuum of intrinsic biology associated with biological, stem cell, histopathological, and clinical attributes.

Stromal localization of inactive CD8+ T cells in metastatic mismatch repair deficient colorectal cancer

BACKGROUND

The determinants of metastasis in mismatch repair deficiency with high levels of microsatellite instability (MSI-H) in colorectal cancer (CRC) are poorly understood. Here, we hypothesized that distinct immune and stromal microenvironments in primary tumors may discriminate between non-metastatic MSI-H CRC and metastatic MSI-H CRC.

METHODS

We profiled 46,727 single cells using high-plex imaging mass cytometry and analyzed both differential cell type abundance, and spatial distribution of fibroblasts and immune cells in primary CRC tumors with or without metastatic capacity. We validated our findings in a second independent cohort using immunohistochemistry.

RESULTS

High-plex imaging mass cytometry and hierarchical clustering based on microenvironmental markers separated primary MSI-H CRC tumors with and without metastatic capacity. Primary tumors with metastatic capacity displayed a high stromal content and low influx of CD8+ T cells, which expressed significantly lower levels of markers reflecting proliferation (Ki67) and antigen-experience (CD45RO) compared to CD8+ T cells in non-metastatic tumors. CD8+ T cells showed intra-epithelial localization in non-metastatic tumors, but stromal localization in metastatic tumors, which was validated in a second cohort.

CONCLUSION

We conclude that localization of phenotypically distinct CD8+ T cells within stroma may predict metastasis formation in MSI-H CRC.

A New Era of Integration between Multiomics and Spatio-Temporal Analysis for the Translation of EMT towards Clinical Applications in Cancer

Epithelial-mesenchymal transition (EMT) is crucial to metastasis by increasing cancer cell migration and invasion. At the cellular level, EMT-related morphological and functional changes are well established. At the molecular level, critical signaling pathways able to drive EMT have been described. Yet, the translation of EMT into efficient diagnostic methods and anti-metastatic therapies is still missing. This highlights a gap in our understanding of the precise mechanisms governing EMT. Here, we discuss evidence suggesting that overcoming this limitation requires the integration of multiple omics, a hitherto neglected strategy in the EMT field. More specifically, this work summarizes results that were independently obtained through epigenomics/transcriptomics while comprehensively reviewing the achievements of proteomics in cancer research. Additionally, we prospect gains to be obtained by applying spatio-temporal multiomics in the investigation of EMT-driven metastasis. Along with the development of more sensitive technologies, the integration of currently available omics, and a look at dynamic alterations that regulate EMT at the subcellular level will lead to a deeper understanding of this process. Further, considering the significance of EMT to cancer progression, this integrative strategy may enable the development of new and improved biomarkers and therapeutics capable of increasing the survival and quality of life of cancer patients.

Molecular portraits of colorectal cancer morphological regions

Heterogeneity of colorectal carcinoma (CRC) represents a major hurdle towards personalized medicine. Efforts based on whole tumor profiling demonstrated that the CRC molecular subtypes were associated with specific tumor morphological patterns representing tumor subregions. We hypothesize that whole-tumor molecular descriptors depend on the morphological heterogeneity with significant impact on current molecular predictors. We investigated intra-tumor heterogeneity by morphology-guided transcriptomics to better understand the links between gene expression and tumor morphology represented by six morphological patterns (morphotypes): complex tubular, desmoplastic, mucinous, papillary, serrated, and solid/trabecular. Whole-transcriptome profiling by microarrays of 202 tumor regions (morphotypes, tumor-adjacent normal tissue, supportive stroma, and matched whole tumors) from 111 stage II-IV CRCs identified morphotype-specific gene expression profiles and molecular programs and differences in their cellular buildup. The proportion of cell types (fibroblasts, epithelial and immune cells) and differentiation of epithelial cells were the main drivers of the observed disparities with activation of EMT and TNF-α signaling in contrast to MYC and E2F targets signaling, defining major gradients of changes at molecular level. Several gene expression-based (including single-cell) classifiers, prognostic and predictive signatures were examined to study their behavior across morphotypes. Most exhibited important morphotype-dependent variability within same tumor sections, with regional predictions often contradicting the whole-tumor classification. The results show that morphotype-based tumor sampling allows the detection of molecular features that would otherwise be distilled in whole tumor profile, while maintaining histopathology context for their interpretation. This represents a practical approach at improving the reproducibility of expression profiling and, by consequence, of gene-based classifiers.

Collagen 1-mediated CXCL1 secretion in tumor cells activates fibroblasts to promote radioresistance of esophageal cancer

Esophageal squamous-cell carcinoma (ESCC) is commonly treated with radiotherapy; however, radioresistance hinders its clinical effectiveness, and the underlying mechanism remains elusive. Here, we develop patient-derived xenografts (PDXs) from 19 patients with ESCC to investigate the mechanisms driving radioresistance. Using RNA sequencing, cytokine arrays, and single-cell RNA sequencing, we reveal an enrichment of cancer-associated fibroblast (CAF)-derived collagen type 1 (Col1) and tumor-cell-derived CXCL1 in non-responsive PDXs. Col1 not only promotes radioresistance by augmenting DNA repair capacity but also induces CXCL1 secretion in tumor cells. Additionally, CXCL1 further activates CAFs via the CXCR2-STAT3 pathway, establishing a positive feedback loop. Directly interfering with tumor-cell-derived CXCL1 or inhibiting the CXCL1-CXCR2 pathway effectively restores the radiosensitivity of radioresistant xenografts in vivo. Collectively, our study provides a comprehensive understanding of the molecular mechanisms underlying radioresistance and identifies potential targets to improve the efficacy of radiotherapy for ESCC.

Mapping the topography of spatial gene expression with interpretable deep learning

Spatially resolved transcriptomics technologies provide high-throughput measurements of gene expression in a tissue slice, but the sparsity of this data complicates the analysis of spatial gene expression patterns such as gene expression gradients. We address these issues by deriving a topographic map of a tissue slice-analogous to a map of elevation in a landscape-using a novel quantity called the isodepth. Contours of constant isodepth enclose spatial domains with distinct cell type composition, while gradients of the isodepth indicate spatial directions of maximum change in gene expression. We develop GASTON, an unsupervised and interpretable deep learning algorithm that simultaneously learns the isodepth, spatial gene expression gradients, and piecewise linear functions of the isodepth that model both continuous gradients and discontinuous spatial variation in the expression of individual genes. We validate GASTON by showing that it accurately identifies spatial domains and marker genes across several biological systems. In SRT data from the brain, GASTON reveals gradients of neuronal differentiation and firing, and in SRT data from a tumor sample, GASTON infers gradients of metabolic activity and epithelial-mesenchymal transition (EMT)-related gene expression in the tumor microenvironment.

TIM-3 Expression and M2 Polarization of Macrophages in the TGFβ-Activated Tumor Microenvironment in Colorectal Cancer

TGFβ signaling in the tumor microenvironment (TME) drives immune evasion and is a negative predictor of immune checkpoint inhibitor (ICI) efficacy in colorectal cancer (CRC). TIM-3, an inhibitory receptor implicated in anti-tumor immune responses and ICI resistance, has emerged as an immunotherapeutic target. This study investigated TIM-3, M2 macrophages and the TGFβ-activated TME, in association with microsatellite instability (MSI) status and consensus molecular subtypes (CMSs). Transcriptomic cohorts of CRC tissues, organoids and xenografts were examined (n = 2240). TIM-3 and a TGFβ-inducible stromal protein, VCAN, were evaluated in CRC specimens using immunohistochemistry (n = 45). TIM-3 expression on monocytes and generated M2 macrophages was examined by flow cytometry. We found that the expression of HAVCR2 (TIM-3) significantly correlated with the transcriptional signatures of TGFβ, TGFβ-dependent stromal activation and M2 macrophage, each of which were co-upregulated in CMS4, CMS1 and MSI CRCs across all datasets. Tumor-infiltrating TIM-3+ immune cells accumulated in TGFβ-responsive cancer stroma. TIM-3 was increased on M2-polarized macrophages, and on monocytes in response to TGFβ treatment. In conclusion, we identified a close association between TIM-3 and M2-like polarization of macrophages in the TGFβ-rich TME. Our findings provide new insights into personalized immunotherapeutic strategies based on the TME for CRCs.

Improved accuracy in colorectal cancer tissue decomposition through refinement of established deep learning solutions

Hematoxylin and eosin-stained biopsy slides are regularly available for colorectal cancer patients. These slides are often not used to define objective biomarkers for patient stratification and treatment selection. Standard biomarkers often pertain to costly and slow genetic tests. However, recent work has shown that relevant biomarkers can be extracted from these images using convolutional neural networks (CNNs). The CNN-based biomarkers predicted colorectal cancer patient outcomes comparably to gold standards. Extracting CNN-biomarkers is fast, automatic, and of minimal cost. CNN-based biomarkers rely on the ability of CNNs to recognize distinct tissue types from microscope whole slide images. The quality of these biomarkers (coined 'Deep Stroma') depends on the accuracy of CNNs in decomposing all relevant tissue classes. Improving tissue decomposition accuracy is essential for improving the prognostic potential of CNN-biomarkers. In this study, we implemented a novel training strategy to refine an established CNN model, which then surpassed all previous solutions . We obtained a 95.6% average accuracy in the external test set and 99.5% in the internal test set. Our approach reduced errors in biomarker-relevant classes, such as Lymphocytes, and was the first to include interpretability methods. These methods were used to better apprehend our model's limitations and capabilities.

Helicase-like transcription factor (HLTF)-deleted CDX/TME model of colorectal cancer increased transcription of oxidative phosphorylation genes and diverted glycolysis to boost S-glutathionylation in lymphatic intravascular metastatic niches

Helicase-like transcription factor (HLTF) also known as SMARCA3, protects genome integrity. A tumor suppressor, HLTF is expressed in tumor cells but not in the tumor microenvironment (TME) in early-stage colorectal cancer (CRC). With disease progression, there is high concordance between epigenetic silencing of HLTF in CRC cells and negligible HLTF expression in the TME. We developed a cell line-derived xenograft (CDX) model and show for the first time that HLTF-deletion in cancer cells and the TME results in metabolic reprogramming that mitigates oxidative stress in lymphatic intravascular metastatic niches. The two metabolic pathways that derive energy from glucose-glycolysis and oxidative phosphorylation (OXPHOS)-are variously utilized by cancer cells depending upon the TME. HIF-1α, a master regulator of glycolysis, was eliminated from a role in reprogramming metabolism to satisfy CDX energetic requirements by RNAseq and spatial transcriptomics. Variability in the gut microbiome, with a putative role in altered metabolism, was also eliminated. HLTF-deleted cancer cells recovered from DNA damage at a transcriptomic level induction of DNA repair and OXPHOS genes linked to an amoeboid-associated phenotype at the tumor border (confocal microscopy). HLTF-deleted cancer and endothelial cells of lymphatic (PDPN) intravascular niches in the TME shared a site-specific protein S-glutathionylation signature (2D DIGE, MALDI-TOF/TOF mass spectrometry) for three glycolytic enzymes (PGK1 Cys379/380, PGAM1 Cys55, ENOA1 Cys119) that diverted glycolysis in support of continued glutathione biosynthesis. The collective absence of HLTF/Hltf from tumor and TME achieved redox homeostasis throughout the CDX and promoted metastasis.

A generalized AI method for pathology cancer diagnosis and prognosis prediction based on transfer learning and hierarchical split

Objective.This study aims to propose a generalized AI method for pathology cancer diagnosis and prognosis prediction based on transfer learning and hierarchical split.Approach.We present a neural network framework for cancer diagnosis and prognosis prediction in pathological images. To enhance the network's depth and width, we employ a hierarchical split block (HS-Block) to create an AI-aided diagnosis system suitable for semi-supervised clinical settings with limited labeled samples and cross-domain tasks. By incorporating a lightweight convolution unit based on the HS-Block, we improve the feature information extraction capabilities of a regular network (RegNet). Additionally, we integrate a Convolutional Block Attention Module into the first and last convolutions to optimize the extraction of global features and local details. To address limited sample labels, we employ a dual-transfer learning (DTL) mechanism named DTL-HS-Regnet, enabling semi-supervised learning in clinical settings.Main results.Our proposed DTL-HS-Regnet model outperforms other advanced deep-learning models in three different types of cancer diagnosis tasks. It demonstrates superior feature extraction ability, achieving an average sensitivity, specificity, accuracy, and F1 score of 0.9987, 1.0000, 1.0000 and 0.9992, respectively. Furthermore, we evaluate the model's capability to directly extract prognosis prediction information from pathological images by constructing patient cohorts. The results show that the correlation between DTL-HS-Regnet predictions and the presence of cancer-associated fibroblasts is comparable to that of pathologists.Significance.Our proposed AI method offers a generalized approach for cancer diagnosis and prognosis prediction in pathology. The outstanding performance of the DTL-HS-Regnet model demonstrates its potential for improving current practices in image digital pathology, expanding the boundaries of cancer treatment in two critical areas.

The Prognostic Value of ASPHD1 and ZBTB12 in Colorectal Cancer: A Machine Learning-Based Integrated Bioinformatics Approach

Introduction: Colorectal cancer (CRC) is a common cancer associated with poor outcomes, underscoring a need for the identification of novel prognostic and therapeutic targets to improve outcomes. This study aimed to identify genetic variants and differentially expressed genes (DEGs) using genome-wide DNA and RNA sequencing followed by validation in a large cohort of patients with CRC. Methods: Whole genome and gene expression profiling were used to identify DEGs and genetic alterations in 146 patients with CRC. Gene Ontology, Reactom, GSEA, and Human Disease Ontology were employed to study the biological process and pathways involved in CRC. Survival analysis on dysregulated genes in patients with CRC was conducted using Cox regression and Kaplan-Meier analysis. The STRING database was used to construct a protein-protein interaction (PPI) network. Moreover, candidate genes were subjected to ML-based analysis and the Receiver operating characteristic (ROC) curve. Subsequently, the expression of the identified genes was evaluated by Real-time PCR (RT-PCR) in another cohort of 64 patients with CRC. Gene variants affecting the regulation of candidate gene expressions were further validated followed by Whole Exome Sequencing (WES) in 15 patients with CRC. Results: A total of 3576 DEGs in the early stages of CRC and 2985 DEGs in the advanced stages of CRC were identified. ASPHD1 and ZBTB12 genes were identified as potential prognostic markers. Moreover, the combination of ASPHD and ZBTB12 genes was sensitive, and the two were considered specific markers, with an area under the curve (AUC) of 0.934, 1.00, and 0.986, respectively. The expression levels of these two genes were higher in patients with CRC. Moreover, our data identified two novel genetic variants-the rs925939730 variant in ASPHD1 and the rs1428982750 variant in ZBTB1-as being potentially involved in the regulation of gene expression. Conclusions: Our findings provide a proof of concept for the prognostic values of two novel genes-ASPHD1 and ZBTB12-and their associated variants (rs925939730 and rs1428982750) in CRC, supporting further functional analyses to evaluate the value of emerging biomarkers in colorectal cancer.

Luciferase Expressing Preclinical Model Systems Representing the Different Molecular Subtypes of Colorectal Cancer

Colorectal cancer (CRC) is a heterogeneous disease. More insight into the biological diversity of CRC is needed to improve therapeutic outcomes. Established CRC cell lines are frequently used and were shown to be representative models of the main subtypes of CRC at the genomic and transcriptomic level. In the present work, we established stable, luciferase expressing derivatives from 10 well-established CRC cell lines, generated spheroids and subcutaneous xenograft tumors in nude mice, and performed comparative characterization of these model systems. Transcriptomic analyses revealed the close relation of cell lines with their derived spheroids and xenograft tumors. The preclinical model systems clustered with patient tumor samples when compared to normal tissue thereby confirming that cell-line-based tumor models retain specific characteristics of primary tumors. Xenografts showed different differentiation patterns and bioluminescence imaging revealed metastatic spread to the lungs. In addition, the models were classified according to the CMS classification system, with further sub-classification according to the recently identified two intrinsic epithelial tumor cell states of CRC, iCMS2 and iCMS3. The combined data showed that regarding primary tumor characteristics, 3D-spheroid cultures resemble xenografts more closely than 2D-cultured cells do. Furthermore, we set up a bioluminescence-based spheroid cytotoxicity assay in order to be able to perform dose-response relationship studies in analogy to typical monolayer assays. Applying the established assay, we studied the efficacy of oxaliplatin. Seven of the ten used cell lines showed a significant reduction in the response to oxaliplatin in the 3D-spheroid model compared to the 2D-monolayer model. Therapy studies in selected xenograft models confirmed the response or lack of response to oxaliplatin treatment. Analyses of differentially expressed genes in these models identified CAV1 as a possible marker of oxaliplatin resistance. In conclusion, we established a combined 2D/3D, in vitro/in vivo model system representing the heterogeneity of CRC, which can be used in preclinical research applications.

The Effect of Radiotherapy on Cell Survival and Inflammatory Cytokine and Chemokine Secretion in a Co-Culture Model of Head and Neck Squamous Cell Carcinoma and Normal Cells

Radiotherapy (RT) is one of the main treatments for head and neck squamous cell carcinomas (HNSCCs). Unfortunately, radioresistance is observed in many cases of HNSCCs. The effectiveness of RT depends on both the direct effect inducing cell death and the indirect effect of changing the tumor microenvironment (TME). Knowledge of interactions between TME components after RT may help to design a new combined treatment with RT. In the study, we investigated the effect of RT on cell survival and cell secretion in a co-culture model of HNSCCs in vitro. We examined changes in cell proliferation, colony formation, cell cycle phases, type of cell death, cell migration and secretion after irradiation. The obtained results suggest that the presence of fibroblasts and endothelial cells in co-culture with HNSCCs inhibits the function of cell cycle checkpoints G₁/S and G₂/M and allows cells to enter the next phase of the cell cycle. We showed an anti-apoptotic effect in co-culture of HNSCCs with fibroblasts or endothelial cells in relation to the execution phase of apoptosis, although we initially observed increased activation of the early phase of apoptosis in the co-cultures after irradiation. We hypothesize that the anti-apoptotic effect depends on increased secretion of IL-6 and MCP-1.

Mouse models in colon cancer, inferences, and implications

Mouse models of colorectal cancer (CRC) have been crucial in the identification of the role of genes responsible for the full range of pathology of the human disease and have proved to be dependable for testing anti-cancer drugs. Recent research points toward the relevance of tumor, angiogenic, and immune microenvironments in CRC progression to late-stage disease, as well as the treatment of it. This study examines important mouse models in CRC, discussing inherent strengths and weaknesses disclosed during their construction. It endeavors to provide both a synopsis of previous work covering how investigators have defined various models and to evaluate critically how researchers are most likely to use them in the future. Accumulated evidence regarding the metastatic process and the hope of using checkpoint inhibitors and immunological inhibitor therapies points to the need for a genetically engineered mouse model that is both immunocompetent and autochthonous.

Co-cultures of colon cancer cells and cancer-associated fibroblasts recapitulate the aggressive features of mesenchymal-like colon cancer

Background

Poor prognosis in colon cancer is associated with a high content of cancer-associated fibroblasts (CAFs) and an immunosuppressive tumor microenvironment. The relationship between these two features is incompletely understood. Here, we aimed to generate a model system for studying the interaction between cancer cells and CAFs and their effect on immune-related cytokines and T cell proliferation.

Methods

CAFs were isolated from colon cancer liver metastases and were immortalized to prolong lifespan and improve robustness and reproducibility. Established medium and matrix compositions that support the growth of patient-derived organoids were adapted to also support CAF growth. Changes in growth pattern and cellular re-organization were assessed by confocal microscopy, live cell imaging, and immunofluorescence. Single cell RNA sequencing was used to study CAF/organoid co-culture-induced phenotypic changes in both cell types. Conditioned media were used to quantify the production of immunosuppressive factors and to assess their effect on T cell proliferation.

Results

We developed a co-culture system in which colon cancer organoids and CAFs spontaneously organize into superstructures with a high capacity to contract and stiffen the extracellular matrix (ECM). CAF-produced collagen IV provided a basement membrane supporting cancer cell organization into glandular structures, reminiscent of human cancer histology. Single cell RNA sequencing analysis showed that CAFs induced a partial epithelial-to-mesenchymal-transition in a subpopulation of cancer cells, similar to what is observed in the mesenchymal-like consensus molecular subtype 4 (CMS4) colon cancer. CAFs in co-culture were characterized by high expression of ECM components, ECM-remodeling enzymes, glycolysis, hypoxia, and genes involved in immunosuppression. An expression signature derived from CAFs in co-culture identified a subpopulation of glycolytic myofibroblasts specifically residing in CMS1 and CMS4 colon cancer. Medium conditioned by co-cultures contained high levels of the immunosuppressive factors TGFβ1, VEGFA and lactate, and potently inhibited T cell proliferation.

Conclusion

Co-cultures of organoids and immortalized CAFs recapitulate the histological, biophysical, and immunosuppressive features of aggressive mesenchymal-like human CRC. The model can be used to study the mechanisms of immunosuppression and to test therapeutic strategies targeting the cross-talk between CAFs and cancer cells. It can be further modified to represent distinct colon cancer subtypes and (organ-specific) microenvironments.

Multi-label transcriptional classification of colorectal cancer reflects tumor cell population heterogeneity

BACKGROUND

Transcriptional classification has been used to stratify colorectal cancer (CRC) into molecular subtypes with distinct biological and clinical features. However, it is not clear whether such subtypes represent discrete, mutually exclusive entities or molecular/phenotypic states with potential overlap. Therefore, we focused on the CRC Intrinsic Subtype (CRIS) classifier and evaluated whether assigning multiple CRIS subtypes to the same sample provides additional clinically and biologically relevant information.

METHODS

A multi-label version of the CRIS classifier (multiCRIS) was applied to newly generated RNA-seq profiles from 606 CRC patient-derived xenografts (PDXs), together with human CRC bulk and single-cell RNA-seq datasets. Biological and clinical associations of single- and multi-label CRIS were compared. Finally, a machine learning-based multi-label CRIS predictor (ML2CRIS) was developed for single-sample classification.

RESULTS

Surprisingly, about half of the CRC cases could be significantly assigned to more than one CRIS subtype. Single-cell RNA-seq analysis revealed that multiple CRIS membership can be a consequence of the concomitant presence of cells of different CRIS class or, less frequently, of cells with hybrid phenotype. Multi-label assignments were found to improve prediction of CRC prognosis and response to treatment. Finally, the ML2CRIS classifier was validated for retaining the same biological and clinical associations also in the context of single-sample classification.

CONCLUSIONS

These results show that CRIS subtypes retain their biological and clinical features even when concomitantly assigned to the same CRC sample. This approach could be potentially extended to other cancer types and classification systems.

The clinical relevance and prediction efficacy from therapy of tumor microenvironment related signature score in colorectal cancer

Introduction

As the top 3 cancer in terms of incidence and mortality, the first-line treatment for CRC includes FOLFOX, FOLFIRI, Cetuximab or immunotherapy. However, the drug sensitivity of patients to regimens is different. There has been increasing evidence that immune components of TME can affect the sensitivity of patients to drugs. Therefore, it is necessary to define novo molecular subtypes of CRC based on TME immune components, and screen patients who are sensitive to the treatments, to make personalized therapy possible.

Methods

We analyzed the expression profiles and 197 TME-related signatures of 1775 patients using ssGSEA, univariate Cox proportional risk model and LASSO-Cox regression model, and defined a novo molecular subtype (TMERSS) of CRC. Simultaneously, we compared the clinicopathological factors, antitumor immune activity, immune cell abundance and differences of cell states in different TMERSS subtypes. In addition, patients sensitive to the therapy were screened out by correlation analysis between TMERSS subtypes and drug responses.

Results

Compared with low TMERSS subtype, high TMERSS subtype has a better outcome, which may be associated to higher abundance of antitumor immune cell in high TMERSS subtype. Our findings suggested that the high TMERSS subtype may have a higher proportion of respondents to Cetuximab agent and immunotherapy, while the low TMERSS subtype may be more suitable for treatment with FOLFOX and FOLFIRI regimens.

Discussion

In conclusion, the TMERSS model may provide a partial reference for the prognosis evaluation of patients, the prediction of drug sensitivity, and the implementation of clinical decision-making.

Dissecting metastasis using preclinical models and methods

Metastasis has long been understood to lead to the overwhelming majority of cancer-related deaths. However, our understanding of the metastatic process, and thus our ability to prevent or eliminate metastases, remains frustratingly limited. This is largely due to the complexity of metastasis, which is a multistep process that likely differs across cancer types and is greatly influenced by many aspects of the in vivo microenvironment. In this Review, we discuss the key variables to consider when designing assays to study metastasis: which source of metastatic cancer cells to use and where to introduce them into mice to address different questions of metastasis biology. We also examine methods that are being used to interrogate specific steps of the metastatic cascade in mouse models, as well as emerging techniques that may shed new light on previously inscrutable aspects of metastasis. Finally, we explore approaches for developing and using anti-metastatic therapies, and how mouse models can be used to test them.

Clinical molecular subtyping reveals intrinsic mesenchymal reprogramming in gastric cancer cells

The mesenchymal cancer phenotype is known to be clinically related to treatment resistance and a poor prognosis. We identified gene signature-based molecular subtypes of gastric cancer (GC, n = 547) based on transcriptome data and validated their prognostic and predictive utility in multiple external cohorts. We subsequently examined their associations with tumor microenvironment (TME) features by employing cellular deconvolution methods and sequencing isolated GC populations. We further performed spatial transcriptomics analysis and immunohistochemistry, demonstrating the presence of GC cells in a partial epithelial-mesenchymal transition state. We performed network and pharmacogenomic database analyses to identify TGF-β signaling as a driver pathway and, thus, a therapeutic target. We further validated its expression in tumor cells in preclinical models and a single-cell dataset. Finally, we demonstrated that inhibition of TGF-β signaling negated mesenchymal/stem-like behavior and therapy resistance in GC cell lines and mouse xenograft models. In summary, we show that the mesenchymal GC phenotype could be driven by epithelial cancer cell-intrinsic TGF-β signaling and propose therapeutic strategies based on targeting the tumor-intrinsic mesenchymal reprogramming of medically intractable GC.

A novel prognostic signatures based on metastasis- and immune-related gene pairs for colorectal cancer

Background

Metastasis remains the leading cause of mortality in patients diagnosed with colorectal cancer (CRC). The pivotal contribution of the immune microenvironment in the initiation and progression of CRC metastasis has gained significant attention.

Methods

A total of 453 CRC patients from The Cancer Genome Atlas (TCGA) were included as the training set, and GSE39582, GSE17536, GSE29621, GSE71187 were included as the validation set. The single-sample gene set enrichment analysis (ssGSEA) was performed to assess the immune infiltration of patients. Least absolute shrinkage and selection operator (LASSO) regression analysis, Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier analysis were used to construct and validate risk models based on R package. CTSW and FABP4-knockout CRC cells were constructed via CRISPR-Cas9 system. Western-blot and Transwell assay were utilized to explore the role of fatty acid binding protein 4 (FABP4) / cathepsin W (CTSW) in CRC metastasis and immunity.

Results

Based on the normal/tumor, high-/low-immune cell infiltration, and metastatic/non-metastatic group, we identified 161 differentially expressed genes. After random assignment and LASSO regression analysis, a prognostic model containing 3 metastasis- and immune-related gene pairs was constructed and represented good prognostic prediction efficiency in the training set and 4 independent CRC cohorts. According to this model, we clustered patients and found that the high-risk group was associated with stage, T and M stage. In addition, the high-risk group also shown higher immune infiltration and high sensitivity to PARP inhibitors. Further, FABP4 and CTSW derived from the constitutive model were identified to be involved in metastasis and immunity of CRC.

Conclusion

In conclusion, a validated prognosis predictive model for CRC was constructed. CTSW and FABP4 are potential targets for CRC treatment.

Late-stage MC38 tumours recapitulate features of human colorectal cancer - implications for appropriate timepoint selection in preclinical studies

Anti-tumour T cell responses play a crucial role in controlling the progression of colorectal cancer (CRC), making this disease a promising candidate for immunotherapy. However, responses to immune-targeted therapies are currently limited to subpopulations of patients and specific types of cancer. Clinical studies have therefore focussed on identifying biomarkers that predict immunotherapy responses and elucidating the immunological landscapes of different cancers. Meanwhile, our understanding of how preclinical tumour models resemble human disease has fallen behind, despite their crucial role in immune-targeted drug development. A deeper understanding of these models is therefore needed to improve the development of immunotherapies and the translation of findings made in these systems. MC38 colon adenocarcinoma is a widely used preclinical model, yet how it recapitulates human colorectal cancer remains poorly defined. This study investigated the tumour-T cell immune landscape of MC38 tumours using histology, immunohistochemistry, and flow cytometry. We demonstrate that early-stage tumours exhibit a nascent TME, lacking important immune-resistance mechanisms of clinical interest, while late-stage tumours exhibit a mature TME resembling human tumours, with desmoplasia, T cell exhaustion, and T cell exclusion. Consequently, these findings clarify appropriate timepoint selection in the MC38 model when investigating both immunotherapies and mechanisms that contribute to immunotherapy resistance. Overall, this study provides a valuable resource that will enable appropriate application of the MC38 model and expedite the development and clinical translation of new immunotherapies.

Patient-derived xenograft models in cancer therapy: technologies and applications

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.

Subtype-specific kinase dependency regulates growth and metastasis of poor-prognosis mesenchymal colorectal cancer

BACKGROUND

Colorectal cancer (CRC) can be divided into four consensus molecular subtypes (CMS), each with distinct biological features. CMS4 is associated with epithelial-mesenchymal transition and stromal infiltration (Guinney et al., Nat Med 21:1350-6, 2015; Linnekamp et al., Cell Death Differ 25:616-33, 2018), whereas clinically it is characterized by lower responses to adjuvant therapy, higher incidence of metastatic spreading and hence dismal prognosis (Buikhuisen et al., Oncogenesis 9:66, 2020).

METHODS

To understand the biology of the mesenchymal subtype and unveil specific vulnerabilities, a large CRISPR-Cas9 drop-out screen was performed on 14 subtyped CRC cell lines to uncover essential kinases in all CMSs. Dependency of CMS4 cells on p21-activated kinase 2 (PAK2) was validated in independent 2D and 3D in vitro cultures and in vivo models assessing primary and metastatic outgrowth in liver and peritoneum. TIRF microscopy was used to uncover actin cytoskeleton dynamics and focal adhesion localization upon PAK2 loss. Subsequent functional assays were performed to determine altered growth and invasion patterns.

RESULTS

PAK2 was identified as a key kinase uniquely required for growth of the mesenchymal subtype CMS4, both in vitro and in vivo. PAK2 plays an important role in cellular attachment and cytoskeletal rearrangements (Coniglio et al., Mol Cell Biol 28:4162-72, 2008; Grebenova et al., Sci Rep 9:17171, 2019). In agreement, deletion or inhibition of PAK2 impaired actin cytoskeleton dynamics in CMS4 cells and, as a consequence, significantly reduced invasive capacity, while it was dispensable for CMS2 cells. Clinical relevance of these findings was supported by the observation that deletion of PAK2 from CMS4 cells prevented metastatic spreading in vivo. Moreover, growth in a model for peritoneal metastasis was hampered when CMS4 tumor cells were deficient for PAK2.

CONCLUSION

Our data reveal a unique dependency of mesenchymal CRC and provide a rationale for PAK2 inhibition to target this aggressive subgroup of colorectal cancer.

Mimicking Tumor Cell Heterogeneity of Colorectal Cancer in a Patient-derived Organoid-Fibroblast Model

BACKGROUND & AIMS

Patient-derived organoid cancer models are generated from epithelial tumor cells and reflect tumor characteristics. However, they lack the complexity of the tumor microenvironment, which is a key driver of tumorigenesis and therapy response. Here, we developed a colorectal cancer organoid model that incorporates matched epithelial cells and stromal fibroblasts.

METHODS

Primary fibroblasts and tumor cells were isolated from colorectal cancer specimens. Fibroblasts were characterized for their proteome, secretome, and gene expression signatures. Fibroblast/organoid co-cultures were analyzed by immunohistochemistry and compared with their tissue of origin, as well as on gene expression levels compared with standard organoid models. Bioinformatics deconvolution was used to calculate cellular proportions of cell subsets in organoids based on single-cell RNA sequencing data.

RESULTS

Normal primary fibroblasts, isolated from tumor adjacent tissue, and cancer associated fibroblasts retained their molecular characteristics in vitro, including higher motility of cancer associated compared with normal fibroblasts. Importantly, both cancer-associated fibroblasts and normal fibroblasts supported cancer cell proliferation in 3D co-cultures, without the addition of classical niche factors. Organoids grown together with fibroblasts displayed a larger cellular heterogeneity of tumor cells compared with mono-cultures and closely resembled the in vivo tumor morphology. Additionally, we observed a mutual crosstalk between tumor cells and fibroblasts in the co-cultures. This was manifested by considerably deregulated pathways such as cell-cell communication and extracellular matrix remodeling in the organoids. Thrombospondin-1 was identified as a critical factor for fibroblast invasiveness.

CONCLUSION

We developed a physiological tumor/stroma model, which will be vital as a personalized tumor model to study disease mechanisms and therapy response in colorectal cancer.

Improved Delineation of Colorectal Cancer Molecular Subtypes and Functional Profiles with a 62-Gene Panel

Since its establishment in 2015, the transcriptomics-based consensus molecular subtype (CMS) classification has unified our understanding of colorectal cancer. Each of the four CMS exhibited distinctive high-level molecular signatures that correlated well with prognosis and treatment response. Nonetheless, many key aspects of colorectal cancer progression and intra-subtype heterogeneity remain unresolved. This is partly because the bulk transcriptomic data used to define CMS contain substantial interference from non-tumor cells. Here, we propose a concise panel of 62 genes that not only accurately recapitulates all key characteristics of the four original CMS but also identifies three additional subpopulations with unique molecular signatures. Validation on independent cohorts confirms that the new CMS4 intra-subtypes coincide with single-cell-derived intrinsic subtypes and that the panel consists of many immune cell-type markers that can capture the status of tumor microenvironment. Furthermore, a 2D embedding of CMS structure based on the proposed gene panel provides a high-resolution view of the functional pathways and cell-type markers that underlie each CMS intra-subtype and the continuous progression from CMS2 to CMS4 subtypes. Our gene panel and 2D visualization refined the delineation of colorectal cancer subtypes and could aid further discovery of molecular mechanisms in colorectal cancer.

IMPLICATIONS

: Well-selected gene panel and representation can capture both the continuum of cancer cell states and tumor microenvironment status.

Cancer-associated fibroblasts: Versatile mediators in remodeling the tumor microenvironment

Current cancer therapeutic strategies are generally not sufficient to eradicate malignancy, as cancer stroma cells contribute to tumor evasion and therapeutic resistance. Cancer-associated fibroblasts (CAFs) constitute a largely heterogeneous type of stromal cell population and are important components of the tumor microenvironment (TME). CAFs are the most abundant stromal cell type and are actively involved in tumor progression through complex mechanisms involving effects on other cell types. Research conducted in recent years has emphasized an emerging function of CAFs in the remodeling of the TME that promotes tumor progression with effects on response to treatment by various molecular mechanisms. A comprehensive mechanism of tumor-promoting activities of CAFs could facilitate the development of novel diagnostic and therapeutic approaches. In this review, the biological characterization of CAFs and the mechanisms of their effects on TME remodeling are summarized. Furthermore, we also highlight currently available therapeutic strategies targeting CAF in the context of optimizing the success of immunotherapies and briefly discuss possible future perspectives and challenges related to CAF studies.

Regulatory enhancer profiling of mesenchymal-type gastric cancer reveals subtype-specific epigenomic landscapes and targetable vulnerabilities

OBJECTIVE

Gastric cancer (GC) comprises multiple molecular subtypes. Recent studies have highlighted mesenchymal-subtype GC (Mes-GC) as a clinically aggressive subtype with few treatment options. Combining multiple studies, we derived and applied a consensus Mes-GC classifier to define the Mes-GC enhancer landscape revealing disease vulnerabilities.

DESIGN

Transcriptomic profiles of ~1000 primary GCs and cell lines were analysed to derive a consensus Mes-GC classifier. Clinical and genomic associations were performed across >1200 patients with GC. Genome-wide epigenomic profiles (H3K27ac, H3K4me1 and assay for transposase-accessible chromatin with sequencing (ATAC-seq)) of 49 primary GCs and GC cell lines were generated to identify Mes-GC-specific enhancer landscapes. Upstream regulators and downstream targets of Mes-GC enhancers were interrogated using chromatin immunoprecipitation followed by sequencing (ChIP-seq), RNA sequencing, CRISPR/Cas9 editing, functional assays and pharmacological inhibition.

RESULTS

We identified and validated a 993-gene cancer-cell intrinsic Mes-GC classifier applicable to retrospective cohorts or prospective single samples. Multicohort analysis of Mes-GCs confirmed associations with poor patient survival, therapy resistance and few targetable genomic alterations. Analysis of enhancer profiles revealed a distinctive Mes-GC epigenomic landscape, with TEAD1 as a master regulator of Mes-GC enhancers and Mes-GCs exhibiting preferential sensitivity to TEAD1 pharmacological inhibition. Analysis of Mes-GC super-enhancers also highlighted NUAK1 kinase as a downstream target, with synergistic effects observed between NUAK1 inhibition and cisplatin treatment.

CONCLUSION

Our results establish a consensus Mes-GC classifier applicable to multiple transcriptomic scenarios. Mes-GCs exhibit a distinct epigenomic landscape, and TEAD1 inhibition and combinatorial NUAK1 inhibition/cisplatin may represent potential targetable options.

Patient-derived xenograft model in colorectal cancer basic and translational research

Colorectal cancer (CRC) is one of the most popular malignancies globally, with 930 000 deaths in 2020. The evaluation of CRC-related pathogenesis and the discovery of potential therapeutic targets will be meaningful and helpful for improving CRC treatment. With huge efforts made in past decades, the systematic treatment regimens have been applied to improve the prognosis of CRC patients. However, the sensitivity of CRC to chemotherapy and targeted therapy is different from person to person, which is an important cause of treatment failure. The emergence of patient-derived xenograft (PDX) models shows great potential to alleviate the straits. PDX models possess similar genetic and pathological characteristics as the features of primary tumors. Moreover, PDX has the ability to mimic the tumor microenvironment of the original tumor. Thus, the PDX model is an important tool to screen precise drugs for individualized treatment, seek predictive biomarkers for prognosis supervision, and evaluate the unknown mechanism in basic research. This paper reviews the recent advances in constructed methods and applications of the CRC PDX model, aiming to provide new knowledge for CRC basic research and therapeutics.

Radiomics Approaches for the Prediction of Pathological Complete Response after Neoadjuvant Treatment in Locally Advanced Rectal Cancer: Ready for Prime Time?

In recent years, neoadjuvant therapy of locally advanced rectal cancer has seen tremendous modifications. Adding neoadjuvant chemotherapy before or after chemoradiotherapy significantly increases loco-regional disease-free survival, negative surgical margin rates, and complete response rates. The higher complete rate is particularly clinically meaningful given the possibility of organ preservation in this specific sub-population, without compromising overall survival. However, all locally advanced rectal cancer most likely does not benefit from total neoadjuvant therapy (TNT), but experiences higher toxicity rates. Diagnosis of complete response after neoadjuvant therapy is a real challenge, with a risk of false negatives and possible under-treatment. These new therapeutic approaches thus raise the need for better selection tools, enabling a personalized therapeutic approach for each patient. These tools mostly focus on the prediction of the pathological complete response given the clinical impact. In this article, we review the place of different biomarkers (clinical, biological, genomics, transcriptomics, proteomics, and radiomics) as well as their clinical implementation and discuss the most recent trends for future steps in prediction modeling in patients with locally advanced rectal cancer.

Intimate communications within the tumor microenvironment: stromal factors function as an orchestra

Extensive studies of the tumor microenvironment (TME) in the last decade have reformed the view of cancer as a tumor cell-centric disease. The tumor microenvironment, especially termed the "seed and soil" theory, has emerged as the key determinant in cancer development and therapeutic resistance. The TME mainly consists of tumor cells, stromal cells such as fibroblasts, immune cells, and other noncellular components. Within the TME, intimate communications among these components largely determine the fate of the tumor. The pivotal roles of the stroma, especially cancer-associated fibroblasts (CAFs), the most common component within the TME, have been revealed in tumorigenesis, tumor progression, therapeutic response, and tumor immunity. A better understanding of the function of the TME sheds light on tumor therapy. In this review, we summarize the emerging understanding of stromal factors, especially CAFs, in cancer progression, drug resistance, and tumor immunity with an emphasis on their functions in epigenetic regulation. Moreover, the importance of epigenetic regulation in reshaping the TME and the basic biological principles underpinning the synergy between epigenetic therapy and immunotherapy will be further discussed.

Exploring prognostic indicators in the pathological images of ovarian cancer based on a deep survival network

Background: Tumor pathology can assess patient prognosis based on a morphological deviation of tumor tissue from normal. Digitizing whole slide images (WSIs) of tissue enables the use of deep learning (DL) techniques in pathology, which may shed light on prognostic indicators of cancers, and avoid biases introduced by human experience. Purpose: We aim to explore new prognostic indicators of ovarian cancer (OC) patients using the DL framework on WSIs, and provide a valuable approach for OC risk stratification. Methods: We obtained the TCGA-OV dataset from the NIH Genomic Data Commons Data Portal database. The preprocessing of the dataset was comprised of three stages: 1) The WSIs and corresponding clinical data were paired and filtered based on a unique patient ID; 2) a weakly-supervised CLAM WSI-analysis tool was exploited to segment regions of interest; 3) the pre-trained model ResNet50 on ImageNet was employed to extract feature tensors. We proposed an attention-based network to predict a hazard score for each case. Furthermore, all cases were divided into a high-risk score group and a low-risk one according to the median as the threshold value. The multi-omics data of OC patients were used to assess the potential applications of the risk score. Finally, a nomogram based on risk scores and age features was established. Results: A total of 90 WSIs were processed, extracted, and fed into the attention-based network. The mean value of the resulting C-index was 0.5789 (0.5096-0.6053), and the resulting p-value was 0.00845. Moreover, the risk score showed a better prediction ability in the HRD + subgroup. Conclusion: Our deep learning framework is a promising method for searching WSIs, and providing a valuable clinical means for prognosis.

Cancer-associated fibroblasts in gynecological malignancies: are they really allies of the enemy?

Molecular and cellular components of the tumor microenvironment are essential for cancer progression. The cellular element comprises cancer cells and heterogeneous populations of non-cancer cells that satisfy tumor needs. Immune, vascular, and mesenchymal cells provide the necessary factors to feed the tumor mass, promote its development, and favor the spread of cancer cells from the primary site to adjacent and distant anatomical sites. Cancer-associated fibroblasts (CAFs) are mesenchymal cells that promote carcinogenesis and progression of various malignant neoplasms. CAFs act through the secretion of metalloproteinases, growth factors, cytokines, mitochondrial DNA, and non-coding RNAs, among other molecules. Over the last few years, the evidence on the leading role of CAFs in gynecological cancers has notably increased, placing them as the cornerstone of neoplastic processes. In this review, the recently reported findings regarding the promoting role that CAFs play in gynecological cancers, their potential use as therapeutic targets, and the new evidence suggesting that they could act as tumor suppressors are analyzed and discussed.

Hidden patterns of gene expression provide prognostic insight for colorectal cancer

Cancer tissue samples contain cancer cells and non-cancer cells with each biopsied site containing distinct proportions of these populations. Consequently, assigning useful tumor subtypes based on gene expression measurements from clinical samples is challenging. We applied a blind source separation approach to extract cancer cell-intrinsic gene expression patterns within clinical tumor samples of colorectal cancer. After a blind source separation, we found that a cancer cell-intrinsic gene expression program unique to each patient exists in the "residual" expression profile remaining after separation of the gene expression data. We performed a consensus clustering analysis of the extracted gene expression profiles to identify novel and robust cancer cell-intrinsic subtypes. We validated the identified subtypes using an independent clinical gene expression dataset. The cancer cell-intrinsic subtypes are independent of biopsy site and provided prognostic information in addition to currently available clinical and molecular variables. After validating this approach in colorectal cancer, we further identified novel tumor subtypes with unique clinical information across multiple types of cancer. These cancer cell-intrinsic molecular subtypes provide novel prognostic value for clinical assessment of cancer.

The Cancer-Associated Fibroblasts-Related Gene COMP Is a Novel Predictor for Prognosis and Immunotherapy Efficacy and Is Correlated with M2 Macrophage Infiltration in Colon Cancer

BACKGROUND

Colon cancer is characterized by a sophisticated tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs), which make up the majority of the stromal cells in TME, participate in tumor development and immune regulation. Further investigations of CAFs would facilitate an in-depth understanding of its role in colon cancer TME.

METHODS

In this study, we estimated CAF abundance based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases using the Microenvironment Cell Populations-counter (MCP-counter) algorithm. CAF-related genes were identified by differential gene expression analysis combined with weighted gene coexpression network analysis. For further selection, the least absolute shrinkage and selection operator (LASSO)-Cox regression was used, and the prognostic value of the selected gene was confirmed in numerous external cohorts. The function enrichment, immunological characteristics, tumor mutation signature, immunotherapy response, and drug sensitivity of the selected gene were subsequently explored. The bioinformatics analysis results were validated using immunohistochemistry on clinical samples from our institution.

RESULTS

According to our findings, cartilage oligomeric matrix protein (COMP) was uncovered as a candidate CAFs-driven biomarker in colon cancer and plays an important role in predicting prognosis in colon cancer. COMP upregulation was associated with enhanced stromal and immune activation, and immune cell infiltration, especially M2 macrophages. Genes that mutated differently between the high- and low-COMP expression subgroups may be correlated with TME change. Following verification, COMP reliably predicted the immunotherapy response and drug response. In addition, our experimental validation demonstrated that COMP overexpression is associated with colon cancer carcinogenesis and is strongly associated with CAFs and M2 macrophage infiltration.

CONCLUSION

Our study uncovered that COMP was a key CAFs-driven gene associated with M2 macrophage infiltration and acted as a convincing predictor for prognosis and immunotherapy response in colon cancer patients.