Stromal contribution to the colorectal cancer transcriptome

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.

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.

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.

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.

EMP1-positive cells found guilty of metastatic relapse in colorectal cancer

Metastatic recurrence develops in 30%-40% of colorectal cancer (CRC) patients in the years that follow surgical removal of the primary tumor. In a recent issue of Nature, Cañellas-Socias et al. identify a distinct population of CRC cells, marked with epithelial membrane protein 1 (EMP1), accountable for metastatic relapse.

Ex vivo explant model of adenoma and colorectal cancer to explore mechanisms of action and patient response to cancer prevention therapies

Colorectal cancer (CRC) is the second leading cause of cancer death in the UK. Novel therapeutic prevention strategies to inhibit the development and progression of CRC would be invaluable. Potential contenders include low toxicity agents such as dietary-derived agents or repurposed drugs. However, in vitro and in vivo models used in drug development often do not take into account the heterogeneity of tumours or the tumour microenvironment. This limits translation to a clinical setting. Our objectives were to develop an ex vivo method utilizing CRC and adenoma patient-derived explants (PDEs) which facilitates screening of drugs, assessment of toxicity, and efficacy. Our aims were to use a multiplexed immunofluorescence approach to demonstrate the viability of colorectal tissue PDEs, and the ability to assess immune cell composition and interactions. Using clinically achievable concentrations of curcumin, we show a correlation between curcumin-induced tumour and stromal apoptosis (P < .001) in adenomas and cancers; higher stromal content is associated with poorer outcomes. B cell (CD20+ve) and T cell (CD3+ve) density of immune cells within tumour regions in control samples correlated with curcumin-induced tumour apoptosis (P < .001 and P < .05, respectively), suggesting curcumin-induced apoptosis is potentially predicted by baseline measures of immune cells. A decrease in distance between T cells (CD3+ve) and cytokeratin+ve cells was observed, indicating movement of T cells (CD3+ve) towards the tumour margin (P < .001); this change is consistent with an immune environment associated with improved outcomes. Concurrently, an increase in distance between T cells (CD3+ve) and B cells (CD20+ve) was detected following curcumin treatment (P < .001), which may result in a less immunosuppressive tumour milieu. The colorectal tissue PDE model offers significant potential for simultaneously assessing multiple biomarkers in response to drug exposure allowing a greater understanding of mechanisms of action and efficacy in relevant target tissues, that maintain both their structural integrity and immune cell compartments.

Activation of innate-adaptive immune machinery by poly(I:C) exposes a therapeutic vulnerability to prevent relapse in stroma-rich colon cancer

OBJECTIVE

Stroma-rich tumours represent a poor prognostic subtype in stage II/III colon cancer (CC), with high relapse rates and limited response to standard adjuvant chemotherapy.

DESIGN

To address the lack of efficacious therapeutic options for patients with stroma-rich CC, we stratified our human tumour cohorts according to stromal content, enabling identification of the biology underpinning relapse and potential therapeutic vulnerabilities specifically within stroma-rich tumours that could be exploited clinically. Following human tumour-based discovery and independent clinical validation, we use a series of in vitro and stroma-rich in vivo models to test and validate the therapeutic potential of elevating the biology associated with reduced relapse in human tumours.

RESULTS

By performing our analyses specifically within the stroma-rich/high-fibroblast (HiFi) subtype of CC, we identify and validate the clinical value of a HiFi-specific prognostic signature (HPS), which stratifies tumours based on STAT1-related signalling (High-HPS v Low-HPS=HR 0.093, CI 0.019 to 0.466). Using in silico, in vitro and in vivo models, we demonstrate that the HPS is associated with antigen processing and presentation within discrete immune lineages in stroma-rich CC, downstream of double-stranded RNA and viral response signalling. Treatment with the TLR3 agonist poly(I:C) elevated the HPS signalling and antigen processing phenotype across in vitro and in vivo models. In an in vivo model of stroma-rich CC, poly(I:C) treatment significantly increased systemic cytotoxic T cell activity (p<0.05) and reduced liver metastases (p<0.0002).

CONCLUSION

This study reveals new biological insight that offers a novel therapeutic option to reduce relapse rates in patients with the worst prognosis CC.

Transcriptional Profiling Reveals Mesenchymal Subtypes of Small Cell Lung Cancer with Activation of the Epithelial-to-Mesenchymal Transition and Worse Clinical Outcomes

While molecular subtypes of small cell lung cancers (SCLC) based on neuroendocrine (NE) and non-NE transcriptional regulators have been established, the association between these molecular subtypes and recently recognized SCLC-inflamed (SCLC-I) tumors is less understood. In this study, we used gene expression profiles of SCLC primary tumors and cell lines to discover and characterize SCLC-M (mesenchymal) tumors distinct from SCLC-I tumors for molecular features, clinical outcomes, and cross-species developmental trajectories. SCLC-M tumors show elevated epithelial-to-mesenchymal transformation (EMT) and YAP1 activity but a low level of anticancer immune activity and worse clinical outcomes than SCLC-I tumors. The prevalence of SCLC-M tumors was 3.2-7.4% in primary SCLC cohorts, which was further confirmed by immunohistochemistry in an independent cohort. Deconvoluted gene expression of tumor epithelial cells showed that EMT and increased immune function are tumor-intrinsic characteristics of SCLC-M and SCLC-I subtypes, respectively. Cross-species analysis revealed that human primary SCLC tumors recapitulate the NE-to-non-NE progression murine model providing insight into the developmental relationships among SCLC subtypes, e.g., early NE (SCLC-A and -N)- vs. late non-NE tumors (SCLC-M and -P). Newly identified SCLC-M tumors are biologically and clinically distinct from SCLC-I tumors which should be taken into account for the diagnosis and treatment of the disease.

Gene interaction perturbation network deciphers a high-resolution taxonomy in colorectal cancer

Molecular subtypes of colorectal cancer (CRC) are currently identified via the snapshot transcriptional profiles, largely ignoring the dynamic changes of gene expressions. Conversely, biological networks remain relatively stable irrespective of time and condition. Here, we introduce an individual-specific gene interaction perturbation network-based (GIN) approach and identify six GIN subtypes (GINS1-6) with distinguishing features: (i) GINS1 (proliferative, 24%~34%), elevated proliferative activity, high tumor purity, immune-desert, PIK3CA mutations, and immunotherapeutic resistance; (ii) GINS2 (stromal-rich, 14%~22%), abundant fibroblasts, immune-suppressed, stem-cell-like, SMAD4 mutations, unfavorable prognosis, high potential of recurrence and metastasis, immunotherapeutic resistance, and sensitive to fluorouracil-based chemotherapy; (iii) GINS3 (KRAS-inactivated, 13%~20%), high tumor purity, immune-desert, activation of EGFR and ephrin receptors, chromosomal instability (CIN), fewer KRAS mutations, SMOC1 methylation, immunotherapeutic resistance, and sensitive to cetuximab and bevacizumab; (iv) GINS4 (mixed, 10%~19%), moderate level of stromal and immune activities, transit-amplifying-like, and TMEM106A methylation; (v) GINS5 (immune-activated, 12%~24%), stronger immune activation, plentiful tumor mutation and neoantigen burden, microsatellite instability and high CpG island methylator phenotype, BRAF mutations, favorable prognosis, and sensitive to immunotherapy and PARP inhibitors; (vi) GINS6, (metabolic, 5%~8%), accumulated fatty acids, enterocyte-like, and BMP activity. Overall, the novel high-resolution taxonomy derived from an interactome perspective could facilitate more effective management of CRC patients.

Pseudogenes and the associated ceRNA network as potential prognostic biomarkers for colorectal cancer

Colorectal cancer (CRC) is one of the most common and malignant carcinomas. Many long noncoding RNAs (lncRNAs) have been reported to play important roles in the tumorigenesis of CRC by influencing the expression of some mRNAs via competing endogenous RNA (ceRNA) networks and interacting with miRNAs. Pseudogene is one kind of lncRNA and can act as RNA sponges for miRNAs and regulate gene expression via ceRNA networks. However, there are few studies about pseudogenes in CRC. In this study, 31 differentially expressed (DE) pseudogenes, 17 DE miRNAs and 152 DE mRNAs were identified by analyzing the expression profiles of colon adenocarcinoma obtained from The Cancer Genome Atlas. A ceRNA network was constructed based on these RNAs. Kaplan-Meier analysis showed that 7 pseudogenes, 4 miRNAs and 30 mRNAs were significantly associated with overall survival. Then multivariate Cox regression analysis of the ceRNA-related DE pseudogenes was performed and a 5-pseudogene signature with the greatest prognostic value for CRC was identified. Moreover, the results were validated by the Gene Expression Omnibus database, and quantitative real-time PCR in 113 pairs of CRC tissues and colon cancer cell lines. This study provides a pseudogene-associated ceRNA network, 7 prognostic pseudogene biomarkers, and a 5-pseudogene prognostic risk signature that may be useful for predicting the survival of CRC patients.

Characterization of sialylation-related long noncoding RNAs to develop a novel signature for predicting prognosis, immune landscape, and chemotherapy response in colorectal cancer

Aberrant sialylation plays a key biological role in tumorigenesis and metastasis, including tumor cell survival and invasion, immune evasion, angiogenesis, and resistance to therapy. It has been proposed as a possible cancer biomarker and a potential therapeutic target of tumors. Nevertheless, the prognostic significance and biological features of sialylation-related long noncoding RNAs (lncRNAs) in colorectal cancer (CRC) remain unclear. This study aimed to develop a novel sialylation-related lncRNA signature to accurately evaluate the prognosis of patients with CRC and explore the potential molecular mechanisms of the sialylation-related lncRNAs. Here, we identified sialylation-related lncRNAs using the Pearson correlation analysis on The Cancer Genome Atlas (TCGA) dataset. Univariate and stepwise multivariable Cox analysis were used to establish a signature based on seven sialylation-related lncRNAs in the TCGA dataset, and the risk model was validated in the Gene Expression Omnibus dataset. Kaplan-Meier curve analysis revealed that CRC patients in the low-risk subgroup had a better survival outcome than those in the high-risk subgroup in the training set, testing set, and overall set. Multivariate analysis demonstrated that the sialylation-related lncRNA signature was an independent prognostic factor for overall survival, progression-free survival, and disease-specific survival prediction. The sialylation lncRNA signature-based nomogram exhibited a robust prognostic performance. Furthermore, enrichment analysis showed that cancer hallmarks and oncogenic signaling were enriched in the high-risk group, while inflammatory responses and immune-related pathways were enriched in the low-risk group. The comprehensive analysis suggested that low-risk patients had higher activity of immune response pathways, greater immune cell infiltration, and higher expression of immune stimulators. In addition, we determined the sialylation level in normal colonic cells and CRC cell lines by flow cytometry combined with immunofluorescence, and verified the expression levels of seven lncRNAs using real-time quantitative polymerase chain reaction. Finally, combined drug sensitivity analysis using the Genomics of Drug Sensitivity in Cancer, Cancer Therapeutics Response Portal, and Profiling Relative Inhibition Simultaneously in Mixtures indicated that the sialylation-related lncRNA signature could serve as a potential predictor for chemosensitivity. Collectively, this is the first sialylation lncRNA-based signature for predicting the prognosis, immune landscape, and chemotherapeutic response in CRC, and may provide vital guidance to facilitate risk stratification and optimize individualized therapy for CRC patients.

Inhibition of HCK in myeloid cells restricts pancreatic tumor growth and metastasis

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with a low 5-year survival rate and is associated with poor response to therapy. Elevated expression of the myeloid-specific hematopoietic cell kinase (HCK) is observed in PDAC and correlates with reduced patient survival. To determine whether aberrant HCK signaling in myeloid cells is involved in PDAC growth and metastasis, we established orthotopic and intrasplenic PDAC tumors in wild-type and HCK knockout mice. Genetic ablation of HCK impaired PDAC growth and metastasis by inducing an immune-stimulatory endotype in myeloid cells, which in turn reduced the desmoplastic microenvironment and enhanced cytotoxic effector cell infiltration. Consequently, genetic ablation or therapeutic inhibition of HCK minimized metastatic spread, enhanced the efficacy of chemotherapy, and overcame resistance to anti-PD1, anti-CTLA4, or stimulatory anti-CD40 immunotherapy. Our results provide strong rationale for HCK to be developed as a therapeutic target to improve the response of PDAC to chemo- and immunotherapy.

Feasibility of a novel non-invasive swab technique for serial whole-exome sequencing of cervical tumors during chemoradiation therapy

Background

Clinically relevant genetic predictors of radiation response for cervical cancer are understudied due to the morbidity of repeat invasive biopsies required to obtain genetic material. Thus, we aimed to demonstrate the feasibility of a novel noninvasive cervical swab technique to (1) collect tumor DNA with adequate throughput to (2) perform whole-exome sequencing (WES) at serial time points over the course of chemoradiation therapy (CRT).

Methods

Cervical cancer tumor samples from patients undergoing chemoradiation were collected at baseline, at week 1, week 3, and at the completion of CRT (week 5) using a noninvasive swab-based biopsy technique. Swab samples were analyzed with whole-exome sequencing (WES) with mutation calling using a custom pipeline optimized for shallow whole-exome sequencing with low tumor purity (TP). Tumor mutation changes over the course of treatment were profiled.

Results

216 samples were collected and successfully sequenced for 70 patients (94% of total number of tumor samples collected). A total of 33 patients had a complete set of samples at all four time points. The mean mapping rate was 98% for all samples, and the mean target coverage was 180. Estimated TP was greater than 5% for all samples. Overall mutation frequency decreased during CRT but mapping rate and mean target coverage remained at >98% and >180 reads at week 5.

Conclusion

This study demonstrates the feasibility and application of a noninvasive swab-based technique for WES analysis which may be applied to investigate dynamic tumor mutational changes during treatment to identify novel genes which confer radiation resistance.

Towards precision oncology with patient-derived xenografts

Under the selective pressure of therapy, tumours dynamically evolve multiple adaptive mechanisms that make static interrogation of genomic alterations insufficient to guide treatment decisions. Clinical research does not enable the assessment of how various regulatory circuits in tumours are affected by therapeutic insults over time and space. Likewise, testing different precision oncology approaches informed by composite and ever-changing molecular information is hard to achieve in patients. Therefore, preclinical models that incorporate the biology and genetics of human cancers, facilitate analyses of complex variables and enable adequate population throughput are needed to pinpoint randomly distributed response predictors. Patient-derived xenograft (PDX) models are dynamic entities in which cancer evolution can be monitored through serial propagation in mice. PDX models can also recapitulate interpatient diversity, thus enabling the identification of response biomarkers and therapeutic targets for molecularly defined tumour subgroups. In this Review, we discuss examples from the past decade of the use of PDX models for precision oncology, from translational research to drug discovery. We elaborate on how and to what extent preclinical observations in PDX models have confirmed and/or anticipated findings in patients. Finally, we illustrate emerging methodological efforts that could broaden the application of PDX models by honing their predictive accuracy or improving their versatility.

Peritumoral tertiary lymphoid structure and tumor stroma percentage predict the prognosis of patients with non-metastatic colorectal cancer

Background

Tertiary lymphoid structures (TLSs) are crucial in promoting and maintaining positive anti-tumor immune responses. The tumor stroma has a powerful immunosuppressive function that could exclude tumor-infiltrating lymphocytes from the tumor beds and lead to a “cold” phenotype. TLSs and tumor stroma percentage (TSP) are significantly associated with the prognosis of patients with certain cancers. However, the exact roles of TLSs and TSP and their intrinsic relationship are still largely unknown in colorectal cancer (CRC).

Methods

TLSs and TSP were assessed using hematoxylin-eosin (H&amp;E) and/or immunohistochemistry (IHC) staining from 114 CRC patients in the training set and 60 CRC patients in the external validation set. The correlation between TILs, TLS and clinicopathological characteristics and their prognostic values were assessed. Finally, we plotted a Nomogram including the TLS, TSP and tumor-node-metastasis (TNM) stage to predict the probability of recurrence-free survival (RFS) at 2- and 5-years in non-metastatic colorectal cancer (nmCRC) patients.

Results

Peritumoral TLS (P-TLS), intratumoral TLS (In-TLS) and high TSP (H-TSP, &gt;50%) were present in 99.1%, 26.3% and 41.2% patients, respectively. H-TSP tumor tends to be associated with lower P-TLS density (P =0.0205). The low P-TLS density (&lt; 0.098/mm2) was significantly associated with reduced RFS (HR=6.597 95% CI: 2.882-15.103, P &lt;0.001) and reduced overall survival (OS) (HR=6.628 95% CI: 2.893-15.183, P &lt; 0.001) of nmCRC patients. In-TLS was not of significance in evaluating the clinical outcomes of nmCRC patients. H-TSP was significantly associated with reduced RFS (HR=0.126 95% CI: 0.048-0.333, P &lt;0.001) and reduced OS (HR=0.125 95% CI: 0.047-0.332, P &lt;0.001) of nmCRC patients. The 5-year RFS of the high P-TLS, low-TLS, H-TSP, and L-TSP groups were 89.7%, 47.2%, 53.2%, and 92.5%, respectively. The P-TLS density, TSP and TNM stage were independent prognosis factors of nmCRC patients. The Nomogram, including the P-TLS density, TSP and TNM stage, outperformed the TNM stage.

Conclusions

High P-TLS density and low TSP (L-TSP) were independent and favorable prognostic factors of nmCRC patients, which might provide new directions for targeted therapy in the CRC tumor microenvironment, especially the tumor immune microenvironment.

Biological Misinterpretation of Transcriptional Signatures in Tumor Samples Can Unknowingly Undermine Mechanistic Understanding and Faithful Alignment with Preclinical Data

PURPOSE

Precise mechanism-based gene expression signatures (GES) have been developed in appropriate in vitro and in vivo model systems, to identify important cancer-related signaling processes. However, some GESs originally developed to represent specific disease processes, primarily with an epithelial cell focus, are being applied to heterogeneous tumor samples where the expression of the genes in the signature may no longer be epithelial-specific. Therefore, unknowingly, even small changes in tumor stroma percentage can directly influence GESs, undermining the intended mechanistic signaling.

EXPERIMENTAL DESIGN

Using colorectal cancer as an exemplar, we deployed numerous orthogonal profiling methodologies, including laser capture microdissection, flow cytometry, bulk and multiregional biopsy clinical samples, single-cell RNA sequencing and finally spatial transcriptomics, to perform a comprehensive assessment of the potential for the most widely used GESs to be influenced, or confounded, by stromal content in tumor tissue. To complement this work, we generated a freely-available resource, ConfoundR; https://confoundr.qub.ac.uk/, that enables users to test the extent of stromal influence on an unlimited number of the genes/signatures simultaneously across colorectal, breast, pancreatic, ovarian and prostate cancer datasets.

RESULTS

Findings presented here demonstrate the clear potential for misinterpretation of the meaning of GESs, due to widespread stromal influences, which in-turn can undermine faithful alignment between clinical samples and preclinical data/models, particularly cell lines and organoids, or tumor models not fully recapitulating the stromal and immune microenvironment.

CONCLUSIONS

Efforts to faithfully align preclinical models of disease using phenotypically-designed GESs must ensure that the signatures themselves remain representative of the same biology when applied to clinical samples.

Detection of Experimental Colorectal Peritoneal Metastases by a Novel PDGFRβ-Targeting Nanobody

Simple Summary

Colorectal cancer can metastasize to multiple distant sites. Metastases growing within the peritoneal cavity cause a high degree of morbidity and are associated with very poor survival. Moreover, peritoneal metastases are difficult to detect using conventional imaging methods. Consequently, peritoneal metastases are generally under-diagnosed and their response to therapy is difficult to assess. An extensive molecular and cellular analysis of colorectal peritoneal metastases revealed that these lesions express very high levels of specific markers that could serve as targets for imaging-based diagnosis and treatment. In the present report, we explore the potential value of one such marker, PDGFRB, to serve as a target for peritoneal metastasis detection by molecular imaging. Therefore, we generated a PDGFRB-binding llama nanobody and demonstrate its utility in detecting peritoneal metastases in mice. The clinical development of PDGFRB-targeting tracers may help to improve the diagnosis of peritoneal metastases and the clinical management of this highly aggressive disease entity.

Abstract

Peritoneal metastases in colorectal cancer (CRC) belong to Consensus Molecular Subtype 4 (CMS4) and are associated with poor prognosis. Conventional imaging modalities, such as Computed Tomography (CT) and Fluorodeoxyglucose-Positron Emission Tomography (FDG-PET), perform very poorly in the detection of peritoneal metastases. However, the stroma-rich nature of these lesions provides a basis for developing molecular imaging strategies. In this study, conducted from 2019 to 2021, we aimed to generate a Platelet-Derived Growth Factor Receptor beta (PDGFRB)-binding molecular imaging tracer for the detection of CMS4 CRC, including peritoneal metastases. The expression of PDGFRB mRNA discriminated CMS4 from CMS1-3 (AUROC = 0.86 (95% CI 0.85–0.88)) and was associated with poor relapse-free survival. PDGFRB mRNA and protein levels were very high in all human peritoneal metastases examined (n = 66). Therefore, we generated a PDGFRB-targeting llama nanobody (VHH1E12). Biotin-labelled VHH1E12 bound to immobilized human and mouse PDGFRB with high affinity (EC50 human PDGFRB = 7 nM; EC50 murine PDGFRB = 0.8 nM), and to PDGFRB-expressing HEK293 cells grown in vitro. A pharmacokinetic analysis of IRDye-800CW-conjugated VHH1E12 in mice showed that the plasma half-life was 6 min. IRDye-800CW-conjugated VHH1E12 specifically accumulated in experimentally induced colorectal cancer peritoneal metastases in mice. A tissue analysis subsequently demonstrated co-localization of the nanobody with PDGFRB expression in the tumour stroma. Our results demonstrate the potential value of PDGFRB-targeted molecular imaging as a novel strategy for the non-invasive detection of CMS4 CRC, in particular, peritoneal metastases.

Consensus molecular subtype 4 (CMS4)-targeted therapy in primary colon cancer: A proof-of-concept study

Background

Mesenchymal Consensus Molecular Subtype 4 (CMS4) colon cancer is associated with poor prognosis and therapy resistance. In this proof-of-concept study, we assessed whether a rationally chosen drug could mitigate the distinguishing molecular features of primary CMS4 colon cancer.

Methods

In the ImPACCT trial, informed consent was obtained for molecular subtyping at initial diagnosis of colon cancer using a validated RT-qPCR CMS4-test on three biopsies per tumor (Phase-1, n=69 patients), and for neoadjuvant CMS4-targeting therapy with imatinib (Phase-2, n=5). Pre- and post-treatment tumor biopsies were analyzed by RNA-sequencing and immunohistochemistry. Imatinib-induced gene expression changes were associated with molecular subtypes and survival in an independent cohort of 3232 primary colon cancer.

Results

The CMS4-test classified 52/172 biopsies as CMS4 (30%). Five patients consented to imatinib treatment prior to surgery, yielding 15 pre- and 15 post-treatment samples for molecular analysis. Imatinib treatment caused significant suppression of mesenchymal genes and upregulation of genes encoding epithelial junctions. The gene expression changes induced by imatinib were associated with improved survival and a shift from CMS4 to CMS2.

Conclusion

Imatinib may have value as a CMS-switching drug in primary colon cancer and induces a gene expression program that is associated with improved survival.

KIT promotes tumor stroma formation and counteracts tumor-suppressive TGFβ signaling in colorectal cancer

Expression profiling has identified four consensus molecular subtypes (CMS1-4) in colorectal cancer (CRC). The receptor tyrosine kinase KIT has been associated with the most aggressive subtype, CMS4. However, it is unclear whether, and how, KIT contributes to the aggressive features of CMS4 CRC. Here, we employed genome-editing technologies in patient-derived organoids (PDOs) to study KIT function in CRC in vitro and in vivo. CRISPR-Cas9-mediated deletion of the KIT gene caused a partial mesenchymal-to-epithelial phenotype switch and a strong reduction of intra-tumor stromal content. Vice versa, overexpression of KIT caused a partial epithelial-to-mesenchymal phenotype switch, a strong increase of intra-tumor stromal content, and high expression of TGFβ1. Surprisingly, the levels of phosphorylated SMAD2 were significantly lower in KIT-expressing versus KIT-deficient tumor cells. In vitro analyses showed that TGFβ signaling in PDOs limits their regenerative capacity. Overexpression of KIT prevented tumor-suppressive TGFβ signaling, while KIT deletion sensitized PDOs to TGFβ-mediated growth inhibition. Mechanistically, we found that KIT expression caused a strong reduction in the expression of SMAD2, a central mediator of canonical TGFβ signaling. We propose that KIT induces a pro-fibrotic tumor microenvironment by stimulating TGFβ expression, and protects the tumor cells from tumor-suppressive TGFβ signaling by inhibiting SMAD2 expression.

Digital image analysis provides robust tissue microenvironment-based prognosticators in stage I-IV colorectal cancer patients

AIMS

In colorectal cancer (CRC) patients, a promising marker is tumor-stroma ratio (TSR). Quantification issues highlight the importance of precise assessment that might be solved by artificial intelligence (AI)-based digital image analysis systems. Some alternatives have been offered so far, although these platforms are either proprietary developments or require additional programming skills. Our aim was to validate a user-friendly, commercially available software running in everyday computational environment to improve TSR assessment and also to compare the prognostic value of assessing TSR in three distinct regions of interests (ROIs), like hotspot, invasive front and whole tumor. Furthermore, we compared the prognostic power of TSR with newly suggested carcinoma percentage (CP) and carcinoma-stroma percentage (CSP).

METHODS AND RESULTS

Slides of 185 stage I-IV CRC patients with clinical follow up data were scanned and evaluated by a senior pathologist. A machine learning-based digital pathology software was trained to recognize tumoral and stromal compartments. The aforementioned parameters were evaluated in the hotspot, invasive front and whole tumor area, both visually and by machine learning. Patients were classified based on TSR, CP and CSP values. On multivariate analysis, TSR-hotspot was found to be an independent prognostic factor of overall survival (hazard ratio for TSR-hotspot_software: 2.005 (95% confidence interval (CI): 1.146-3.507), p=0.011, for TSR-hostpot_visual: 1.781 (CI: 1.060-2.992) p=0.029). Also, TSR was an independent predictor for distant metastasis and local relapse in most settings. Generally, software performance was comparable to visual evaluation and delivered reliable prognostication in more settings also with CP and CSP values.

CONCLUSIONS

This study presents that software assisted evaluation is a robust prognosticator. Our approach used a less sophisticated and thus easily accessible software without the aid of convolutional neural network; however, it was still effective enough to deliver reliable prognostic information.

Dynamic Co-Evolution of Cancer Cells and Cancer-Associated Fibroblasts: Role in Right- and Left-Sided Colon Cancer Progression and Its Clinical Relevance

Simple Summary

The versatile crosstalk between cancer cells and cancer-associated fibroblasts (CAFs) of the tumour microenvironment (TME) drives colorectal carcinogenesis and heterogeneity. Colorectal cancer (CRC) can be classified by the anatomical sites from which the cancer arises, either from the right or left colon. Although the cancer cell–CAF interaction is being widely studied, its role in the progression of cancer in the right and left colon and cancer heterogeneity are still yet to be elucidated. Further insight into the complex interaction between different cellular components in the cancer niche, their evolutionary process and their influence on cancer progression would propel the discovery of effective targeted CRC therapy.

Abstract

Cancer is a result of a dynamic evolutionary process. It is composed of cancer cells and the tumour microenvironment (TME). One of the major cellular constituents of TME, cancer-associated fibroblasts (CAFs) are known to interact with cancer cells and promote colorectal carcinogenesis. The accumulation of these activated fibroblasts is linked to poor diagnosis in colorectal cancer (CRC) patients and recurrence of the disease. However, the interplay between cancer cells and CAFs is yet to be described, especially in relation to the sidedness of colorectal carcinogenesis. CRC, which is the third most commonly diagnosed cancer globally, can be classified according to the anatomical region from which they originate: left-sided (LCRC) and right-sided CRC (RCR). Both cancers differ in many aspects, including in histology, evolution, and molecular signatures. Despite occurring at lower frequency, RCRC is often associated with worse diagnosis compared to LCRC. The differences in molecular profiles between RCRC and LCRC also influence the mode of treatment that can be used to specifically target these cancer entities. A better understanding of the cancer cell–CAF interplay and its association with RCRC and LRCR progression will provide better insight into potential translational aspects of targeted treatment for CRC.

Targeting IL-34/MCSF-1R Axis in Colon Cancer

Colorectal carcinoma (CRC) is one of the most common neoplasias in the Western world and it is still one of the most deadly cancers worldwide mainly due to the fact that metastatic CRC is not responsive to current pharmacologic treatment. Identification of pathways that sustain CRC cell behaviour could help develop effective therapeutic compounds. A large body of evidence indicates that colon carcinogenesis is a dynamic process in which multiple cell types present in the tumor microenvironment either stimulate or suppress CRC cell growth, survival, and diffusion mainly via the production of cytokines. Interleukin-34 (IL-34), a cytokine initially known for its ability to regulate monocyte/macrophage survival and function, is highly produced in human CRC by both cancer cells and non-tumoral cells. IL-34 function is mainly mediated by interaction with the macrophage colony-stimulating factor-1 receptor (MCSF-1R), which is also over-expressed by CRC cells as well as by tumour-associated macrophages (TAMs) and cancer-associated fibroblasts. IL-34-driven MCSF-1R activation triggers several pro-tumoral functions in the colon. In this article, we review the current understanding of the involvement of IL-34 and its receptor in CRC, with particular attention to the available evidence about the IL-34/MCSF-1R axis-mediated regulation of TAMs and the role of IL-34 and MCSF-1R in promoting cancer resistance to chemotherapy and immunotherapy

Therapeutic inhibition of the SRC-kinase HCK facilitates T cell tumor infiltration and improves response to immunotherapy

Although immunotherapy has revolutionized cancer treatment, many immunogenic tumors remain refractory to treatment. This can be largely attributed to an immunologically "cold" tumor microenvironment characterized by an accumulation of immunosuppressive myeloid cells and exclusion of activated T cells. Here, we demonstrate that genetic ablation or therapeutic inhibition of the myeloid-specific hematopoietic cell kinase (HCK) enables activity of antagonistic anti-programmed cell death protein 1 (anti-PD1), anti-CTLA4, or agonistic anti-CD40 immunotherapies in otherwise refractory tumors and augments response in treatment-susceptible tumors. Mechanistically, HCK ablation reprograms tumor-associated macrophages and dendritic cells toward an inflammatory endotype and enhances CD8⁺ T cell recruitment and activation when combined with immunotherapy in mice. Meanwhile, therapeutic inhibition of HCK in humanized mice engrafted with patient-derived xenografts counteracts tumor immunosuppression, improves T cell recruitment, and impairs tumor growth. Collectively, our results suggest that therapeutic targeting of HCK activity enhances response to immunotherapy by simultaneously stimulating immune cell activation and inhibiting the immunosuppressive tumor microenvironment.

Comprehensive Analysis of a Cancer-Immunity Cycle-Based Signature for Predicting Prognosis and Immunotherapy Response in Patients With Colorectal Cancer

Immune checkpoint blockade (ICB) has been recognized as a promising immunotherapy for colorectal cancer (CRC); however, most patients have little or no clinical benefit. This study aimed to develop a novel cancer-immunity cycle–based signature to stratify prognosis of patients with CRC and predict efficacy of immunotherapy. CRC samples from The Cancer Genome Atlas (TCGA) were used as the training set, while the RNA data from Gene Expression Omnibus (GEO) data sets and real-time quantitative PCR (RT-qPCR) data from paired frozen tissues were used for validation. We built a least absolute shrinkage and selection operator (LASSO)-Cox regression model of the cancer-immunity cycle–related gene signature in CRC. Patients who scored low on the risk scale had a better prognosis than those who scored high. Notably, the signature was an independent prognostic factor in multivariate analyses, and to improve prognostic classification and forecast accuracy for individual patients, a scoring nomogram was created. The comprehensive results revealed that the low-risk patients exhibited a higher degree of immune infiltration, a higher immunoreactivity phenotype, stronger expression of immune checkpoint–associated genes, and a superior response to ICB therapy. Furthermore, the risk model was closely related to the response to multiple chemotherapeutic drugs. Overall, we developed a reliable cancer-immunity cycle–based risk model to predict the prognosis, the molecular and immune status, and the immune benefit from ICB therapy, which may contribute greatly to accurate stratification and precise immunotherapy for patients with CRC.

The Love-Hate Relationship Between TGF-β Signaling and the Immune System During Development and Tumorigenesis

Since TGF-β was recognized as an essential secreted cytokine in embryogenesis and adult tissue homeostasis a decade ago, our knowledge of the role of TGF-β in mammalian development and disease, particularly cancer, has constantly been updated. Mounting evidence has confirmed that TGF-β is the principal regulator of the immune system, as deprivation of TGF-β signaling completely abrogates adaptive immunity. However, enhancing TGF-β signaling constrains the immune response through multiple mechanisms, including boosting Treg cell differentiation and inducing CD8⁺ T-cell apoptosis in the disease context. The love-hate relationship between TGF-β signaling and the immune system makes it challenging to develop effective monotherapies targeting TGF-β, especially for cancer treatment. Nonetheless, recent work on combination therapies of TGF-β inhibition and immunotherapy have provide insights into the development of TGF-β-targeted therapies, with favorable outcomes in patients with advanced cancer. Hence, we summarize the entanglement between TGF-β and the immune system in the developmental and tumor contexts and recent progress on hijacking crucial TGF-β signaling pathways as an emerging area of cancer therapy.

Deep-frying oil induces cytotoxicity, inflammation and apoptosis on intestinal epithelial cells

BACKGROUND

Deep-frying oil has been found to cause inflammatory bowel disease (IBD). However, the molecular mechanism of the effect of deep-frying palm oil on IBD still remains undetermined.

RESULTS

In the present study, bioinformatics and cell biology were used to investigate the functions and signal pathway enrichments of differentially expressed genes. The bioinformatics analysis of three original microarray datasets (GSE73661, GSE75214 and GSE126124) in the NCBI-Gene Expression Omnibus database showed 17 down-regulated genes (logFC < 0) and 2 up-regulated genes (logFC > 0) existed in the enteritis tissue. Meanwhile, pathway enrichment and protein-protein interaction network analysis suggested that IBD is relevant to cytotoxicity, inflammation and apoptosis. Furthermore, Caco-2 cells were treated with the main oxidation products of deep-frying oil-total polar compounds (TPC) and its components (polymerized triglyceride, oxidized triglycerides and triglyceride degradation products) isolated from deep-frying oil. The flow cytometry experiment revealed that TPC and its components could induce apoptosis, especially for oxidized triglyceride. A quantitative polymerase chain reaction analysis demonstrated that TPC and its component could induce Caco-2 cell apoptosis through AQP8/CXCL1/TNIP3/IL-1.

CONCLUSION

The present study provides fundamental knowledge for understanding the effects of deep-frying oils on the cytotoxic and inflammatory of Caco-2 cells, in addition to clarifying the molecular function mechanism of deep-frying oil in IBD. © 2021 Society of Chemical Industry.

Cancer-Associated Fibroblasts and Squamous Epithelial Cells Constitute a Unique Microenvironment in a Mouse Model of Inflammation-Induced Colon Cancer

The tumor microenvironment plays a key role in the pathogenesis of colorectal tumors and contains various cell types including epithelial, immune, and mesenchymal cells. Characterization of the interactions between these cell types is necessary for revealing the complex nature of tumors. In this study, we used single-cell RNA-seq (scRNA-seq) to compare the tumor microenvironments between a mouse model of sporadic colorectal adenoma (Lrig1^CreERT2/+;Apc^2lox14/+) and a mouse model of inflammation-driven colorectal cancer induced by azoxymethane and dextran sodium sulfate (AOM/DSS). While both models develop tumors in the distal colon, we found that the two tumor types have distinct microenvironments. AOM/DSS tumors have an increased abundance of two populations of cancer-associated fibroblasts (CAFs) compared with APC tumors, and we revealed their divergent spatial association with tumor cells using multiplex immunofluorescence (MxIF) imaging. We also identified a unique squamous cell population in AOM/DSS tumors, whose origins were distinct from anal squamous epithelial cells. These cells were in higher proportions upon administration of a chemotherapy regimen of 5-Fluorouracil/Irinotecan. We used computational inference algorithms to predict cell-cell communication mediated by ligand-receptor interactions and downstream pathway activation, and identified potential mechanistic connections between CAFs and tumor cells, as well as CAFs and squamous epithelial cells. This study provides important preclinical insight into the microenvironment of two distinct models of colorectal tumors and reveals unique roles for CAFs and squamous epithelial cells in the AOM/DSS model of inflammation-driven cancer.

Targeting of the Peritumoral Adipose Tissue Microenvironment as an Innovative Antitumor Therapeutic Strategy

The tumor microenvironment (TME) plays a key role in promoting and sustaining cancer growth. Adipose tissue (AT), due to its anatomical distribution, is a prevalent component of TME, and contributes to cancer development and progression. Cancer-associated adipocytes (CAAs), reprogrammed by cancer stem cells (CSCs), drive cancer progression by releasing metabolites and inflammatory adipokines. In this review, we highlight the mechanisms underlying the bidirectional crosstalk among CAAs, CSCs, and stromal cells. Moreover, we focus on the recent advances in the therapeutic targeting of adipocyte-released factors as an innovative strategy to counteract cancer progression.

Metastatic colorectal carcinoma-associated fibroblasts have immunosuppressive properties related to increased IGFBP2 expression

Fibroblasts are the most abundant stromal constituents of the tumour microenvironment in primary as well as metastatic colorectal cancer (CRC). Their supportive effect on tumour cells is well established. There is growing evidence that stromal fibroblasts also modulate the immune microenvironment in tumours. Here, we demonstrate a difference in fibroblast-mediated immune modulation between primary CRC and peritoneal metastasis. Cancer-associated fibroblasts (CAFs) were isolated from primary cancer and from peritoneal metastases (MAFs) from a total of 17 patients. The ectoenzyme CD38 was consistently expressed on the surface of all MAFs, while it was absent from CAFs. Furthermore, MAFs secreted higher levels of IGFBP2, CXCL2, CXCL6, CXCL12, PDGF-AA, FGFb, and IL-6. This was associated with a decreased activation of macrophages and a suppression of CD25 expression and proliferation of co-cultivated T-cells. Downregulation of IGFBP2 abolished these immunosuppressive effects of MAFs. Taken together, these results show that MAFs contribute to an immunosuppressive tumour microenvironment in CRC metastases by modulating the phenotype of immune cells through an IGFBP2-dependent mechanism.

Refining colorectal cancer classification and clinical stratification through a single-cell atlas

BACKGROUND

Colorectal cancer (CRC) consensus molecular subtypes (CMS) have different immunological, stromal cell, and clinicopathological characteristics. Single-cell characterization of CMS subtype tumor microenvironments is required to elucidate mechanisms of tumor and stroma cell contributions to pathogenesis which may advance subtype-specific therapeutic development. We interrogate racially diverse human CRC samples and analyze multiple independent external cohorts for a total of 487,829 single cells enabling high-resolution depiction of the cellular diversity and heterogeneity within the tumor and microenvironmental cells.

RESULTS

Tumor cells recapitulate individual CMS subgroups yet exhibit significant intratumoral CMS heterogeneity. Both CMS1 microsatellite instability (MSI-H) CRCs and microsatellite stable (MSS) CRC demonstrate similar pathway activations at the tumor epithelial level. However, CD8+ cytotoxic T cell phenotype infiltration in MSI-H CRCs may explain why these tumors respond to immune checkpoint inhibitors. Cellular transcriptomic profiles in CRC exist in a tumor immune stromal continuum in contrast to discrete subtypes proposed by studies utilizing bulk transcriptomics. We note a dichotomy in tumor microenvironments across CMS subgroups exists by which patients with high cancer-associated fibroblasts (CAFs) and C1Q+TAM content exhibit poor outcomes, providing a higher level of personalization and precision than would distinct subtypes. Additionally, we discover CAF subtypes known to be associated with immunotherapy resistance.

CONCLUSIONS

Distinct CAFs and C1Q+ TAMs are sufficient to explain CMS predictive ability and a simpler signature based on these cellular phenotypes could stratify CRC patient prognosis with greater precision. Therapeutically targeting specific CAF subtypes and C1Q + TAMs may promote immunotherapy responses in CRC patients.

Patient-derived xenograft (PDX) models, applications and challenges in cancer research

The establishing of the first cancer models created a new perspective on the identification and evaluation of new anti-cancer therapies in preclinical studies. Patient-derived xenograft models are created by tumor tissue engraftment. These models accurately represent the biology and heterogeneity of different cancers and recapitulate tumor microenvironment. These features have made it a reliable model along with the development of humanized models. Therefore, they are used in many studies, such as the development of anti-cancer drugs, co-clinical trials, personalized medicine, immunotherapy, and PDX biobanks. This review summarizes patient-derived xenograft models development procedures, drug development applications in various cancers, challenges and limitations.

Identification of TPM2 and CNN1 as Novel Prognostic Markers in Functionally Characterized Human Colon Cancer-Associated Stromal Cells

Simple Summary

Non-transformed cells of tumor microenvironment also impact on cancer outgrowth and progression. In colon cancer, a leading cause of cancer-related death worldwide, a high abundance of a heterogeneous cell population generally referred to as cancer-associated fibroblasts (CAFs) or tumor-associated stromal cells (TASCs) is associated with poor prognosis. The identification of TASC-specific markers could help to select patients for additional treatments and may provide novel targets for innovative therapies. Some markers have been proposed, but their prognostic significance is modest. We successfully expanded TASCs from human colon cancers and demonstrated their capacity to promote tumor growth and metastatic spread in vitro and in in vivo models. By comparing TASC whole protein expression, the so-called “proteome”, with that of stromal cells derived from matched healthy colon tissues, we identified two novel markers highly significantly associated with severe prognosis. Our results might help to identify patients at risk and might suggest new treatment options.

Abstract

Stromal infiltration is associated with poor prognosis in human colon cancers. However, the high heterogeneity of human tumor-associated stromal cells (TASCs) hampers a clear identification of specific markers of prognostic relevance. To address these issues, we established short-term cultures of TASCs and matched healthy mucosa-associated stromal cells (MASCs) from human primary colon cancers and, upon characterization of their phenotypic and functional profiles in vitro and in vivo, we identified differentially expressed markers by proteomic analysis and evaluated their prognostic significance. TASCs were characterized by higher proliferation and differentiation potential, and enhanced expression of mesenchymal stem cell markers, as compared to MASCs. TASC triggered epithelial–mesenchymal transition (EMT) in tumor cells in vitro and promoted their metastatic spread in vivo, as assessed in an orthotopic mouse model. Proteomic analysis of matched TASCs and MASCs identified a panel of markers preferentially expressed in TASCs. The expression of genes encoding two of them, calponin 1 (CNN1) and tropomyosin beta chain isoform 2 (TPM2), was significantly associated with poor outcome in independent databases and outperformed the prognostic significance of currently proposed TASC markers. The newly identified markers may improve prognostication of primary colon cancers and identification of patients at risk.

Downregulation of KRAB zinc finger proteins in 5-fluorouracil resistant colorectal cancer cells

Radio-chemotherapy with 5-flu orouracil (5-FU) is the standard of care treatment for patients with colorectal cancer, but it is only effective for a third of them. Despite our understanding of the mechanism of action of 5-FU, drug resistance remains a significant limitation to the clinical use of 5-FU, as both intrinsic and acquired chemoresistance represents the major obstacles for the success of 5-FU-based chemotherapy. In order to identify the mechanism of acquired resistance, 5-FU chemoresistance was induced in CRC cell lines by passaging cells with increasing concentrations of 5-FU. To study global molecular changes, quantitative proteomics and transcriptomics analyses were performed on these cell lines, comparing the resistant cells as well as the effect of chemo and radiotherapy. Interestingly, a very high proportion of downregulated genes were annotated as transcription factors coding for Krüppel-associated box (KRAB) domain-containing zinc-finger proteins (KZFPs), the largest family of transcriptional repressors. Among nearly 350 KRAB-ZFPs, almost a quarter were downregulated after the induction of a 5-FU-resistance including a common one between the three CRC cell lines, ZNF649, whose role is still unknown. To confirm the observations of the proteomic and transcriptomic approaches, the abundance of 20 different KZFPs and control mRNAs was validated by RT-qPCR. In fact, several KZFPs were no longer detectable using qPCR in cell lines resistant to 5-FU, and the KZFPs that were downregulated only in one or two cell lines showed similar pattern of expression as measured by the omics approaches. This proteomic, transcriptomic and genomic analysis of intrinsic and acquired resistance highlights a possible new mechanism involved in the cellular adaptation to 5-FU and therefore identifies potential new therapeutic targets to overcome this resistance.

The Comparable Microenvironment Shared by Colorectal Adenoma and Carcinoma: An Evidence of Stromal Proteomics

Tumor microenvironment (TME) is a key factor involved in cancer development and metastasis. In the TME of colorectal cancer (CRC), the gene expression status of stromal tissues could influence the CRC process from normal to adenoma then carcinoma; however, the expression status at the protein level has not yet been well evaluated. A total of 22 CRC patients were recruited for this study, and the tissue regions corresponding with adjacent, adenoma, and carcinoma were carefully excised by laser capture microdissection (LCM), including a patient with adenoma and carcinoma. The individual proteomes of this cohort were implemented by high-resolution mass spectrometer under data-independent acquisition (DIA) mode. A series of informatic analysis was employed to statistically seek the proteomic characteristics related with the stroma at different stages of CRC. The identified proteins in the colorectal stromal tissues were much less than and almost overlapped with that in the corresponding epithelial tissues; however, the patterns of protein abundance in the stroma were very distinct from those in the epithelium. Although qualitative and quantitative analysis delineated the epithelial proteins specifically typified in the adjacent, adenoma, and carcinoma, the informatics in the stroma led to another deduction that such proteomes were only divided into two patterns, adjacent- and adenoma/carcinoma-dependent. The comparable proteomes of colorectal adenoma and carcinoma were further confirmed by the bulk preparation- or individual LCM-proteomics. The biochemical features of the tumor stromal proteomes were characterized as enrichment of CD4+ and CD8+ T cells, upregulated pathways of antigen presentation, and enhancement of immune signal interactions. Finally, the features of lymphoid lineages in tumor stroma were verified by tissue microarray (TMA). Based on the proteomic evidence, a hypothesis was raised that in the colorectal tissue, the TME of adenoma and carcinoma were comparable, whereas the key elements driving an epithelium from benign to malignant were likely decided by the changes of genomic mutations or/and expression within it.

Identification and validation of a seven-gene prognostic marker in colon cancer based on single-cell transcriptome analysis

Colon cancer (CC) is one of the most commonly diagnosed tumours worldwide. Single-cell RNA sequencing (scRNA-seq) can accurately reflect the heterogeneity within and between tumour cells and identify important genes associated with cancer development and growth. In this study, scRNA-seq was used to identify reliable prognostic biomarkers in CC. ScRNA-seq data of CC before and after 5-fluorouracil treatment were first downloaded from the Gene Expression Omnibus database. The data were pre-processed, and dimensionality reduction was performed using principal component analysis and t-distributed stochastic neighbour embedding algorithms. Additionally, the transcriptome data, somatic variant data, and clinical reports of patients with CC were obtained from The Cancer Genome Atlas database. Seven key genes were identified using Cox regression analysis and the least absolute shrinkage and selection operator method to establish signatures associated with CC prognoses. The identified signatures were validated on independent datasets, and somatic mutations and potential oncogenic pathways were further explored. Based on these features, gene signatures, and other clinical variables, a more effective predictive model nomogram for patients with CC was constructed, and a decision curve analysis was performed to assess the utility of the nomogram. A prognostic signature consisting of seven prognostic-related genes, including CAV2, EREG, NGFRAP1, WBSCR22, SPINT2, CCDC28A, and BCL10, was constructed and validated. The proficiency and credibility of the signature were verified in both internal and external datasets, and the results showed that the seven-gene signature could effectively predict the prognosis of patients with CC under various clinical conditions. A nomogram was then constructed based on features such as the RiskScore, patients' age, neoplasm stage, and tumor (T), nodes (N), and metastases (M) classification, and the nomogram had good clinical utility. Higher RiskScores were associated with a higher tumour mutational burden, which was confirmed to be a prognostic risk factor. Gene set enrichment analysis showed that high-score groups were enriched in 'cytoplasmic DNA sensing', 'Extracellular matrix receptor interactions', and 'focal adhesion', and low-score groups were enriched in 'natural killer cell-mediated cytotoxicity', and 'T-cell receptor signalling pathways', among other pathways. A robust seven-gene marker for CC was identified based on scRNA-seq data and was validated in multiple independent cohort studies. These findings provide a new potential marker to predict the prognosis of patients with CC.

Development and Validation of a Novel Prognostic Nomogram Combined With Desmoplastic Reaction for Synchronous Colorectal Peritoneal Metastasis

Purpose

The prognostic value of desmoplastic reaction (DR) has not been investigated in colorectal cancer (CRC) patients with synchronous peritoneal metastasis (SPM). The present study aimed to identify whether DR can predict overall survival (OS) and develop a novel prognostic nomogram.

Methods

CRC patients with SPM were enrolled from a single center between July 2007 and July 2019. DR patterns in primary tumors were classified as mature, intermediate, or immature according to the existence and absence of keloid-like collagen or myxoid stroma. Cox regression analysis was used to identify independent factors associated with OS and a nomogram was developed subsequently.

Results

One hundred ninety-eight and 99 patients were randomly allocated into the training and validation groups. The median OS in the training group was 36, 25, and 12 months in mature, intermediate, and immature DR categories, respectively. Age, T stage, extraperitoneal metastasis, differentiation, cytoreductive surgery (CRS), hyperthermic intraperitoneal chemotherapy (HIPEC), and DR categorization were independent variables for OS, based on which the nomogram was developed. The C-index of the nomogram in the training and validation groups was 0.773 (95% CI 0.734–0.812) and 0.767 (95% CI 0.708–0.826). The calibration plots showed satisfactory agreement between the actual outcome and nomogram-predicted OS probabilities in the training and validation cohorts.

Conclusions

DR classification in the primary tumor is a potential prognostic index for CRC patients with SPM. The novel prognostic nomogram combined with DR classification has good discrimination and accuracy in predicting the OS for CRC patients with SPM.

Tumor bud-derived CCL5 recruits fibroblasts and promotes colorectal cancer progression via CCR5-SLC25A24 signaling

Background

Tumor budding is included in the routine diagnosis of colorectal cancer (CRC) and is considered a tumor prognostic factor independent of TNM staging. This study aimed to identify the fibroblast-mediated effect of tumor bud-derived C–C chemokine ligand 5 (CCL5) on the tumor microenvironment (TME).

Methods

Recruitment assays and a human cytokine array were used to detect the main cytokines that CRC tumor buds secrete to recruit fibroblasts. siRNA transfection and inhibitor treatment were used to investigate the role of fibroblast CCL5 receptors in fibroblast recruitment. Subsequently, transcriptome sequencing was performed to explore the molecular changes occurring in fibroblasts upon stimulation with CCL5. Finally, clinical specimens and orthotopic xenograft mouse models were studied to explore the contribution of CCL5 to angiogenesis and collagen synthesis.

Results

Hematoxylin–eosin staining and immunochemistry revealed a higher number of fibroblasts at the invasive front of CRC tissue showing tumor budding than at sites without tumor budding. In vitro experiments demonstrated that CCL5 derived from tumor buds could recruit fibroblasts by acting on the CCR5 receptors on fibroblasts. Tumor bud-derived CCL5 could also positively regulate solute carrier family 25 member 24 (SLC25A24) expression in fibroblasts, potentially activating pAkt-pmTOR signaling. Moreover, CCL5 could increase the number of α-SMA^high CD90^high FAP^low fibroblasts and thus promote tumor angiogenesis by enhancing VEGFA expression and making fibroblasts transdifferentiate into vascular endothelial cells. Finally, the results also showed that CCL5 could promote collagen synthesis through fibroblasts, thus contributing to tumor progression.

Conclusions

At the invasive front of CRC, tumor bud-derived CCL5 can recruit fibroblasts via CCR5-SLC25A24 signaling, further promoting angiogenesis and collagen synthesis via recruited fibroblasts, and eventually create a tumor-promoting microenvironment. Therefore, CCL5 may serve as a potential diagnostic marker and therapeutic target for tumor budding in CRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02300-w.

Identification of Down-Regulated ADH1C is Associated With Poor Prognosis in Colorectal Cancer Using Bioinformatics Analysis

Colorectal cancer (CRC) is the second most deadly cancer in the whole world, with the underlying mechanisms largely indistinct. Therefore, we aimed to identify significant pathways and genes involved in the initiation, formation and poor prognosis of CRC using bioinformatics methods. In this study, we compared gene expression profiles of CRC cases with those from normal colorectal tissues from three chip datasets (GSE33113, GSE23878 and GSE41328) to identify 105 differentially expressed genes (DEGs) that were common to the three datasets. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that the highest proportion of up-regulated DEGs was involved in extracellular region and cytokine-cytokine receptor interaction pathways. Integral components of membrane and bile secretion pathways were identified as containing down-regulated DEGs. 13 hub DEGs were chosen and their expression were further validated by GEPIA. Only four DEGs (ADH1C, CLCA4, CXCL8 and GUCA2A) were associated with a significantly lower overall survival after the prognosis analysis. Lower ADH1C protein level and higher CXCL8 protein level were verified by immunohistochemical staining and western blot in clinical CRC and normal colorectal tissues. In conclusion, our study indicated that the extracellular tumor microenvironment and bile metabolism pathways play critical roles in the formation and progression of CRC. Furthermore, we confirmed ADH1C being down-regulated in CRC and reported ADH1C as a prognostic predictor for the first time.

Peritoneal metastases from colorectal cancer belong to Consensus Molecular Subtype 4 and are sensitised to oxaliplatin by inhibiting reducing capacity

Background

Peritoneal metastases (PM) in colorectal cancer (CRC) are associated with therapy resistance and poor survival. Oxaliplatin monotherapy is widely applied in the intraperitoneal treatment of PM, but fails to yield clinical benefit. We aimed to identify the mechanism(s) underlying PM resistance to oxaliplatin and to develop strategies overcoming such resistance.

Experimental design

We generated a biobank consisting of 35 primary tumour regions and 59 paired PM from 12 patients. All samples were analysed by RNA sequencing. We also generated a series of PM-derived organoid (PMDO) cultures and used these to design and test strategies to overcome resistance to oxaliplatin.

Results

PM displayed various hallmarks of aggressive CRC biology. The vast majority of PM and paired primary tumours belonged to the Consensus Molecular Subtype 4 (CMS4). PMDO cultures were resistant to oxaliplatin and expressed high levels of glutamate-cysteine ligase (GCLC) causing detoxification of oxaliplatin through glutathione synthesis. Genetic or pharmacological targeting of GCLC sensitised PMDOs to a 1-h exposure to oxaliplatin, through increased platinum-DNA adduct formation.

Conclusions

These results link oxaliplatin resistance of colorectal PM to their CMS4 status and high reducing capacity. Inhibiting the reducing capacity of PM may be an effective strategy to overcome PM resistance to oxaliplatin.

Inflammatory fibroblasts mediate resistance to neoadjuvant therapy in rectal cancer

Standard cancer therapy targets tumor cells without considering possible damage on the tumor microenvironment that could impair therapy response. In rectal cancer patients we find that inflammatory cancer-associated fibroblasts (iCAFs) are associated with poor chemoradiotherapy response. Employing a murine rectal cancer model or patient-derived tumor organoids and primary stroma cells, we show that, upon irradiation, interleukin-1α (IL-1α) not only polarizes cancer-associated fibroblasts toward the inflammatory phenotype but also triggers oxidative DNA damage, thereby predisposing iCAFs to p53-mediated therapy-induced senescence, which in turn results in chemoradiotherapy resistance and disease progression. Consistently, IL-1 inhibition, prevention of iCAFs senescence, or senolytic therapy sensitizes mice to irradiation, while lower IL-1 receptor antagonist serum levels in rectal patients correlate with poor prognosis. Collectively, we unravel a critical role for iCAFs in rectal cancer therapy resistance and identify IL-1 signaling as an attractive target for stroma-repolarization and prevention of cancer-associated fibroblasts senescence.

Obtaining spatially resolved tumor purity maps using deep multiple instance learning in a pan-cancer study

Tumor purity is the percentage of cancer cells within a tissue section. Pathologists estimate tumor purity to select samples for genomic analysis by manually reading hematoxylin-eosin (H&E)-stained slides, which is tedious, time consuming, and prone to inter-observer variability. Besides, pathologists' estimates do not correlate well with genomic tumor purity values, which are inferred from genomic data and accepted as accurate for downstream analysis. We developed a deep multiple instance learning model predicting tumor purity from H&E-stained digital histopathology slides. Our model successfully predicted tumor purity in eight The Cancer Genome Atlas (TCGA) cohorts and a local Singapore cohort. The predictions were highly consistent with genomic tumor purity values. Thus, our model can be utilized to select samples for genomic analysis, which will help reduce pathologists' workload and decrease inter-observer variability. Furthermore, our model provided tumor purity maps showing the spatial variation within sections. They can help better understand the tumor microenvironment.

•

MIL model successfully predicts a sample's tumor purity from histopathology slides

•

MIL model learns to spatially resolve tumor purity from sample-level labels

•

Tumor purity varies spatially within a sample

•

Pathologists’ region selection is vital for correct percentage tumor nuclei estimation

Given some big data and coarse-level labels, extracting fine-level information is a demanding yet rewarding challenge in data science. This study develops a machine learning model utilizing big data and exploiting coarse-level labels to reveal fine-level details within the data. Although it can be applied to different data science tasks with enormous data and coarse labels, we applied it to a computational histopathology task with gigapixel histopathology slides and sample-level labels. Specifically, the model revealed spatial resolution of tumor purity within histopathology slides using only sample-level genomic tumor purity values during training. This can also be extended to other omics features, providing precious information about cancer biology and promising personalized, precision medicine. Such studies are of great clinical importance in discovering imaging biomarkers and better understanding the tumor microenvironment.

Macrophages are primed to transdifferentiate into fibroblasts in malignant ascites and pleural effusions

Cancer-associated fibroblasts (CAFs) play an important role in cancer progression. However, the origin of CAFs remains unclear. This study shows that macrophages in malignant ascites and pleural effusions (cavity fluid-associated macrophages: CAMs) transdifferentiate into fibroblast-like cells. CAMs obtained from gastrointestinal cancer patients were sorted by flow cytometry and cultured in vitro. CD45⁺CD14⁺ CAMs transdifferentiated into CD45^-CD90⁺ fibroblast-like cells that exhibited spindle shapes. Then, cDNA microarray analysis showed that the CD45^-CD90⁺ fibroblast-like cells (macrophage-derived CAFs: MDCAFs) had a fibroblast-specific gene expression signature and produced growth factors for epithelial cell proliferation. Human colon cancer cells transplanted into immunodeficient mice with MDCAFs formed larger tumors than cancer cells alone. Gene ontology analyses showed the involvement of TGFβ signaling and cell-matrix adhesion in MDCAFs, and transdifferentiation of CAMs into MDCAFs was canceled by inhibiting TGFβ and cell adhesion. Furthermore, the acquired genetic alterations in hematopoietic stem cells (HSCs) were shared in CAMs and MDCAFs. Taken together, CAMs could be a source of CAFs and might originate from HSCs. We propose the transdifferentiation process of CAMs into MDCAFs as a new therapeutic target for fibrosis associated with gastrointestinal cancer.

Identifying Potential Biomarkers of Prognostic Value in Colorectal Cancer via Tumor Microenvironment Data Mining

Colorectal cancer (CRC) is a common cancer that has increased rapidly worldwide in the past decades with a relatively high mortality rate. An increasing body of evidence has highlighted the importance of infiltrating immune and stromal cells in CRC. In this study, based on gene expression data of CRC patients in TCGA database we evaluated immune and stromal scores in tumor microenvironment using ESTIMATE method. Results showed there was potential correlation between these scores and the prognosis, and that patients with higher immune score and lower stromal score had longer survival time. We found that immune score was correlated with clinical characteristics including tumor location, tumor stage, and survival time. Specifically, the right-sided colon cancer had markedly elevated immune score, compared to left-sided colon cancer and rectal cancer. These results might be useful for understanding tumor microenvironment in colorectal cancer. Through the differential analysis we got a list of genes significantly associated with immune and stromal scores. Gene Set Enrichment and protein-protein interaction network analysis were used to further illustrate these differentially expressed genes. Finally, 15 hub genes were identified, and three (CXCL9, CXCL10 and SELL) of them were validated with favorable outcomes in CRC patients. Our result suggested that these tumor microenvironment related genes might be potential biomarkers for the prognosis of CRC.

Remodeling Chondroitin-6-Sulfate-Mediated Immune Exclusion Enhances Anti-PD-1 Response in Colorectal Cancer with Microsatellite Stability

Metastatic microsatellite-stable (MSS) colorectal cancer rarely responds to immune checkpoint inhibitors (ICI). Metabolism heterogeneity in the tumor microenvironment (TME) presents obstacles to antitumor immune response. Combining transcriptome (The Cancer Genome Atlas MSS colorectal cancer, n = 383) and digital pathology (n = 96) analysis, we demonstrated a stroma metabolism-immune excluded subtype with poor prognosis in MSS colorectal cancer, which could be attributed to interaction between chondroitin-6-sulfate (C-6-S) metabolites and M2 macrophages, forming the "exclusion barrier" in the invasive margin. Furthermore, C-6-S derived from cancer-associated fibroblasts promoted co-nuclear translocation of pSTAT3 and GLI1, activating the JAK/STAT3 and Hedgehog pathways. In vivo experiments with C-6-S-targeted strategies decreased M2 macrophages and reprogrammed the immunosuppressive TME, leading to enhanced response to anti-PD-1 in MSS colorectal cancer. Therefore, C-6-S-induced immune exclusion represents an "immunometabolic checkpoint" that can be exploited for the application of combination strategies in MSS colorectal cancer ICI treatment.

Transcriptional census of epithelial-mesenchymal plasticity in cancer

Epithelial-mesenchymal plasticity (EMP) contributes to tumor progression, promoting therapy resistance and immune cell evasion. Definitive molecular features of this plasticity have largely remained elusive due to the limited scale of most studies. Leveraging single-cell RNA sequencing data from 266 tumors spanning eight different cancer types, we identify expression patterns associated with intratumoral EMP. Integrative analysis of these programs confirmed a high degree of diversity among tumors. These diverse programs are associated with combinations of various common regulatory mechanisms initiated from cues within the tumor microenvironment. We show that inferring regulatory features can inform effective therapeutics to restrict EMP.

Identification and Validation of Immune-Related Prognostic Genes in the Tumor Microenvironment of Colon Adenocarcinoma

The tumor microenvironment (TME) has been shown to be involved in angiogenesis, tumor metastasis, and immune response, thereby affecting the treatment and prognosis of patients. This study aims to identify genes that are dysregulated in the TME of patients with colon adenocarcinoma (COAD) and to evaluate their prognostic value based on RNA omics data. We obtained 512 COAD samples from the Cancer Genome Atlas (TCGA) database and 579 COAD patients from the independent dataset (GSE39582) in the Gene Expression Omnibus (GEO) database. The immune/stromal/ESTIMATE score of each patient based on their gene expression was calculated using the ESTIMATE algorithm. Kaplan-Meier survival analysis, Cox regression analysis, gene functional enrichment analysis, and protein-protein interaction (PPI) network analysis were performed. We found that immune and stromal scores were significantly correlated with COAD patients' overall survival (log rank p < 0.05). By comparing the high immune/stromal score group with the low score group, we identified 688 intersection differentially expressed genes (DEGs) from the TCGA dataset (663 upregulated and 25 downregulated). The functional enrichment analysis of intersection DEGs showed that they were mainly enriched in the immune process, cell migration, cell motility, Toll-like receptor signaling pathway, and PI3K-Akt signaling pathway. The hub genes were revealed by PPI network analysis. Through Kaplan-Meier and Cox analysis, four TME-related genes that were significantly related to the prognosis of COAD patients were verified in GSE39582. In addition, we uncovered the relationship between the four prognostic genes and immune cells in COAD. In conclusion, based on the RNA expression profiles of 1091 COAD patients, we screened four genes that can predict prognosis from the TME, which may serve as candidate prognostic biomarkers for COAD.

Transcriptomic profiling of adjuvant colorectal cancer identifies three key prognostic biological processes and a disease specific role for granzyme B

Background

Colorectal cancer (CRC) is a leading cause of cancer-related deaths, with a 5% 5-year survival rate for metastatic disease, yet with limited therapeutic advancements due to insufficient understanding of and inability to accurately capture high-risk CRC patients who are most likely to recur. We aimed to improve high-risk classification by identifying biological pathways associated with outcome in adjuvant stage II/III CRC.

Methods and findings

We included 1062 patients with stage III or high-risk stage II colon carcinoma from the prospective three-arm randomized phase 3 AVANT trial, and performed expression profiling to identify a prognostic signature. Data from validation cohort GSE39582, The Cancer Genome Atlas, and cell lines were used to further validate the prognostic biology. Our retrospective analysis of the adjuvant AVANT trial uncovered a prognostic signature capturing three biological functions—stromal, proliferative and immune—that outperformed the Consensus Molecular Subtypes (CMS) and recurrence prediction signatures like Oncotype Dx in an independent cohort. Importantly, within the immune component, high granzyme B (GZMB) expression had a significant prognostic impact while other individual T-effector genes were less or not prognostic. In addition, we found GZMB to be endogenously expressed in CMS2 tumor cells and to be prognostic in a T cell independent fashion. A limitation of our study is that these results, although robust and derived from a large dataset, still need to be clinically validated in a prospective study.

Conclusions

This work furthers our understanding of the underlying biology that propagates stage II/III CRC disease progression and provides scientific rationale for future high-risk stratification and targeted treatment evaluation in biomarker defined subpopulations of resectable high-risk CRC. Our results also shed light on an alternative GZMB source with context-specific implications on the disease’s unique biology.