Subtypes Of Colorectal Cancer Research Articles

Identifying essential genes in genome-scale metabolic models of consensus molecular subtypes of colorectal cancer.

Identifying essential targets in the genome-scale metabolic networks of cancer cells is a time-consuming process. The present study proposed a fuzzy hierarchical optimization framework for identifying essential genes, metabolites and reactions. On the basis of four objectives, the present study developed a framework for identifying essential targets that lead to cancer cell death and evaluating metabolic flux perturbations in normal cells that have been caused by cancer treatment. Through fuzzy set theory, a multiobjective optimization problem was converted into a trilevel maximizing decision-making (MDM) problem. We applied nested hybrid differential evolution to solve the trilevel MDM problem to identify essential targets in genome-scale metabolic models for five consensus molecular subtypes (CMSs) of colorectal cancer. We used various media to identify essential targets for each CMS and discovered that most targets affected all five CMSs and that some genes were CMS-specific. We obtained experimental data on the lethality of cancer cell lines from the DepMap database to validate the identified essential genes. The results reveal that most of the identified essential genes were compatible with the colorectal cancer cell lines obtained from DepMap and that these genes, with the exception of EBP, LSS, and SLC7A6, could generate a high level of cell death when knocked out. The identified essential genes were mostly involved in cholesterol biosynthesis, nucleotide metabolisms, and the glycerophospholipid biosynthetic pathway. The genes involved in the cholesterol biosynthetic pathway were also revealed to be determinable, if a cholesterol uptake reaction was not induced when the cells were in the culture medium. However, the genes involved in the cholesterol biosynthetic pathway became non-essential if such a reaction was induced. Furthermore, the essential gene CRLS1 was revealed as a medium-independent target for all CMSs.

Principles of Molecular Utility for CMS Classification in Colorectal Cancer Management

Colorectal cancer (CRC) is the second cause of cancer-related deaths in both sexes globally and presents different clinical outcomes that are described by a range of genomic and epigenomic alterations. Despite the advancements in CRC screening plans and treatment strategies, the prognosis of CRC is dismal. In the last two decades, molecular biomarkers predictive of prognosis have been identified in CRC, although biomarkers predictive of treatment response are only available for specific biological drugs used in stage IV CRC. Translational clinical trials mainly based on “omic” strategies allowed a better understanding of the biological heterogeneity of CRCs. These studies were able to classify CRCs into subtypes mainly related to prognosis, recurrence risk, and, to some extent, also to treatment response. Accordingly, the comprehensive molecular characterizations of CRCs, including The Cancer Genome Atlas (TCGA) and consensus molecular subtype (CMS) classifications, were presented to improve the comprehension of the genomic and epigenomic landscapes of CRCs for a better patient management. The CMS classification obtained by the CRC subtyping consortium categorizes CRC into four consensus molecular subtypes (CMS1–4) characterized by different prognoses. In this review, we discussed the CMS classification in different settings with a focus on its relationships with precursor lesions, tumor immunophenotype, and gut microbiota, as well as on its role in predicting prognosis and/or response to pharmacological treatments, as a crucial step towards precision medicine.

Increased Fusobacterium tumoural abundance affects immunogenicity in mucinous colorectal cancer and may be associated with improved clinical outcome

There is currently an urgent need to identify factors predictive of immunogenicity in colorectal cancer (CRC). Mucinous CRC is a distinct histological subtype of CRC, associated with a poor response to chemotherapy. Recent evidence suggests the commensal facultative anaerobe Fusobacterium may be especially prevalent in mucinous CRC. The objectives of this study were to assess the association of Fusobacterium abundance with immune cell composition and prognosis in mucinous CRC. Our study included two independent colorectal cancer patient cohorts, The Cancer Genome Atlas (TCGA) cohort, and a cohort of rectal cancers from the Beaumont RCSI Cancer Centre (BRCC). Multiplexed immunofluorescence staining of a tumour microarray (TMA) from the BRCC cohort was undertaken using Cell DIVE technology. Our cohorts included 87 cases (13.3%) of mucinous and 565 cases (86.7%) of non-mucinous CRC. Mucinous CRC in the TCGA dataset was associated with an increased proportion of CD8 + lymphocytes (p = 0.018), regulatory T-cells (p = 0.001) and M2 macrophages (p = 0.001). In the BRCC cohort, mucinous RC was associated with enhanced CD8 + lymphocyte (p = 0.022), regulatory T-cell (p = 0.047), and B-cell (p = 0.025) counts. High Fusobacterium abundance was associated with an increased proportion of CD4 + lymphocytes (p = 0.031) and M1 macrophages (p = 0.006), whilst M2 macrophages (p = 0.043) were under-represented in this cohort. Patients with increased Fusobacterium relative abundance in our mucinous CRC TCGA cohort tended to have better clinical outcomes (DSS: likelihood ratio p = 0.04, logrank p = 0.052). Fusobacterium abundance may be associated with improved outcomes in mucinous CRC, possibly due to a modulatory effect on the host immune response.Key messages• Increased Fusobacterium relative abundance was not found to be associated with microsatellite instability in mucinous CRC.• Increased Fusobacterium relative abundance was associated with an M2/M1 macrophage switch, which is especially significant in mucinous CRC, where M2 macrophages are overexpressed.• Increased Fusobacterium relative abundance was associated with a significant improvement in disease specific survival in mucinous CRC.• Our findings were validated at a protein level within our own in house mucinous and non-mucinous rectal cancer cohorts.

An integrated model for predicting KRAS dependency.

The clinical approvals of KRAS G12C inhibitors have been a revolutionary advance in precision oncology, but response rates are often modest. To improve patient selection, we developed an integrated model to predict KRAS dependency. By integrating molecular profiles of a large panel of cell lines from the DEMETER2 dataset, we built a binary classifier to predict a tumor's KRAS dependency. Monte Carlo cross validation via ElasticNet within the training set was used to compare model performance and to tune parameters α and λ. The final model was then applied to the validation set. We validated the model with genetic depletion assays and an external dataset of lung cancer cells treated with a G12C inhibitor. We then applied the model to several Cancer Genome Atlas (TCGA) datasets. The final "K20" model contains 20 features, including expression of 19 genes and KRAS mutation status. In the validation cohort, K20 had an AUC of 0.94 and accurately predicted KRAS dependency in both mutant and KRAS wild-type cell lines following genetic depletion. It was also highly predictive across an external dataset of lung cancer lines treated with KRAS G12C inhibition. When applied to TCGA datasets, specific subpopulations such as the invasive subtype in colorectal cancer and copy number high pancreatic adenocarcinoma were predicted to have higher KRAS dependency. The K20 model has simple yet robust predictive capabilities that may provide a useful tool to select patients with KRAS mutant tumors that are most likely to respond to direct KRAS inhibitors.

Dissecting the heterogeneities of the tumor microenvironment between metastatic and nonmetastatic primary colorectal cancer patients by single-cell RNA sequencing

One of the main factors hampering the long-term prognosis of colorectal cancer (CRC) patients is distant metastasis. However, the driving factors of CRC metastasis have not been clarified at the single-cell level, which limits the in-depth study of accurate prediction and prevention of CRC metastasis to improve the prognosis. Heterogeneities in the tumor microenvironment (TME) between metastatic and nonmetastatic CRC were investigated by single-cell RNA (scRNA) sequencing data. In detail, 50,462 single cells from 20 primary CRC samples, including 40,910 cells from nonmetastatic CRC (M0 group) and 9552 cells from metastatic CRC (M1 group), were systematically analyzed in this study. Based on the single-cell atlas, we revealed that cancer cells and fibroblasts accounted for relatively high proportions in metastatic CRC compared with nonmetastatic CRC. Moreover, two specific cancer cell subtypes (FGGY+SLC6A6+ and IGFBP3+KLK7+ cancer cells) and three specific fibroblast subtypes (ADAMTS6+CAPG+, PIM1+SGK1+ and CA9+UPP1+ fibroblasts) in metastatic CRC were identified. The functional and differentiation characteristics of these specific cell subclusters were elucidated by enrichment and trajectory analyses. These results provide fundamental knowledge for future in-depth research to screen effective methods and drugs to predict and prevent CRC metastasis to improve prognosis.

MC‐KV: A Prognosis‐Oriented Classifier Based on Semi‐Supervised Learning for Molecular Subtyping of Colorectal Cancer

AbstractColorectal cancer (CRC) is the second leading cause of cancer‐related death worldwide. Many molecular classification strategies are proposed for CRC but few studies include survival data in their models. Herein a prognosis‐oriented CRC classifier is constructed by adapting the natural partially labeled censored survival data into a customized semi‐supervised learning algorithm, which is called Monte‐Carlo K‐nearest neighbor voting (MC‐KV) classifier. Three CRC subtypes with distinct prognoses are identified by this classifier using the data from the cancer genome atlas. Furthermore, a six‐gene risk model is constructed by combining weighted gene coexpression network analysis and least absolute selection and shrinkage operator for variable selection and four algorithms (random survival forest, support vector machine, Adaboost, and logistic regression) for optimization. The optimized model shows great performance in distinguishing high‐risk from low‐risk patients with a maximum area under curve of 0.869, 0.906, and 0.921 in 1‐, 3‐, and 5‐year survival, respectively. Additionally, the six‐gene signature identified by MC‐KV exhibits great predictive efficiency for other cancer types. Overall, a tool, Monte‐Carlo K‐nearest neighbor voting (MC‐KV), is provided to identify molecular subtyping of CRC, which suggests the potential contribution of semi‐supervised algorithms and the inclusion of patient‐level survival data in cancer classification.

Abstract LB142: Metabolically defined body size phenotypes in relation to subsequent colorectal cancer risk

Abstract Overweight and obesity have been linked to increased risk of several diseases, including colorectal cancer, but the underlying mechanisms are not fully known. An earlier study analyzed metabolically defined body size phenotypes in relation to colorectal cancer risk, using combinations of C-peptide (a marker of insulin resistance) and body mass index (BMI). Higher serum C-peptide concentrations were associated with higher colorectal cancer risk in both overweight and normal weight individuals compared to individuals with low levels of C-peptide and normal weight. The aim of the present study was to see if these results could be replicated and to further explore the role of metabolism and body size phenotypes in colorectal cancer subtypes. We conducted a nested case-control study of 1010 individuals with colorectal cancer and 1010 individually matched (age, sex, cohort, year of blood sampling and data collection, number of freeze-thaw cycles of plasma samples and fasting status at blood sampling) control participants from the population-based Northern Sweden Health and Disease Study. The blood samples and data used in our analyses were collected at a mean of 9.7 years prior to case diagnosis. Participants were categorized as (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), or (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2), where metabolically healthy was defined as C-peptide in the lowest tertile, as in the previous study. We used multivariable conditional logistic regression to calculate odds ratios and confidence intervals and adjusted for tobacco smoking, recreational physical activity and alcohol consumption as potential confounders. In our preliminary results, metabolically unhealthy/overweight individuals had a significantly higher risk of developing colorectal cancer compared to metabolically healthy/normal weight individuals (adjusted odds ratio =1.44, 95% CI 1.13-1.85). The odds ratio for metabolically unhealthy/normal weight individuals was 1.23 (95% CI 0.92-1.65) and for metabolically healthy/overweight individuals 1.23 (95% CI 0.89-1.70). These results support the potential of a more nuanced analysis of metabolism and body size to better understand their etiological contribution to colorectal cancer development. To gain more knowledge about how the role of metabolism and body size might differ between tumor subtypes, we will also analyze body size phenotypes in relation to subtypes of colorectal cancer based on anatomical tumor site, KRAS and BRAF mutations and microsatellite instability status of the tumor. Citation Format: Linda Vidman, Simon Knekta, Björn Gylling, Carl Zingmark, Anna Löfgren-Burström, Richard Palmqvist, Sophia Harlid, Bethany Van Guelpen. Metabolically defined body size phenotypes in relation to subsequent colorectal cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB142.

Abstract LB177: Tumor sideomics: spatial characteristics and functional deregulation in colorectal cancer

Abstract Clinical evidence suggests that right-sided colorectal cancer (CRC) tends to have a worse prognosis compared to left-sided CRC. The distinct functional mechanisms underlying this “sidedness” remain cryptic and poorly understood. Thus, molecular classification of CRC is of paramount in targeting specific subtypes and personalizing treatment for patients. To identify targetable molecular features to improve treatment regimens, we performed multi-faceted network analyses of hundreds of CRC patients. In our network model, epigenetic features, differential expression of transcript abundance, and mutational frequency were used to identify widespread gene dysregulation and perturbed pathways to reveal disrupted networks distinct to right or left sided colorectal cancer. We discovered histone related genes and distinct epigenetic signals are at play in right-sided CRC. Additionally, our studies reveal “at risk” patient characteristics suggestive of survival differences, to improve diagnostic predictors based on CRC sidedness. Overall, our integrative approach serves to link molecular profiles distinct between left and right sided colorectal cancer, while improving upon previous models of CRC and paving the way towards identifying more effective treatment alternatives from a previously overlooked, readily characterized subtype of colorectal cancer. Citation Format: Brandon Burgman, Xingxin Pan, S. Stephen Yi. Tumor sideomics: spatial characteristics and functional deregulation in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB177.

Abstract 1750: Removal of mucin glycans by Bifidobacterium bifidum enhances chemotherapy-mediated cell death in mucinous adenocarcinomas

Abstract Background: Mucinous colorectal adenocarcinoma, a subtype of colorectal cancer, is characterized by mucin production and increased resistance to several chemotherapeutic interventions; resulting in a poorer prognosis compared to non-mucus secreting cancers. Advances in treatment are stymied by the limited number of efficacious chemotherapeutic agents. The most common drug used to treat colorectal cancer is 5-Fluorouracil (5-FU), but less than 10% of mucinous tumors respond to this drug. The production of mucus has been theorized to limit the uptake of chemotherapeutic agents via charge repulsion and size exclusion, thereby promoting chemo-resistance and driving poor outcomes. Hypothesis: We predict that mucin-degrading microbes secrete glycosyl hydrolase enzymes which cleave mucin glycans and promote the uptake of chemotherapeutic agents and enhance cell death. Methods & Results: We queried the human gut microbiota and identified multiple diverse microbes which encode enzymes to degrade mucin glycans. Among the mucin-degrading bacteria, we found that Bifidobacterium bifidum harbored one of the most extensive repertoires of mucin-degrading enzymes. B. bifidum was grown in a chemically defined medium with or without porcine intestinal mucus and the secreted products were then added to mucus-producing adenocarcinoma cell lines: HT29-MTX and T84 cells. Supernatant from cultures with mucus removed sialic acid residues and enhanced 5-FU uptake after 48 hrs in both cell lines. Supernatant without mucus also promoted 5-FU mediated cell death; although to a lesser degree than supernatant from cultures incubated with mucus. Gene expression analysis and immunostaining revealed decreased MUC13 gene expression and protein in B. bifidum metabolite treated cell lines compared to media controls. In contrast, we found that secreted products from B. dentium, which is unable to degrade mucus, had no effect on 5-FU induced cell death. Conclusions: Our data suggests that B. bifidum elicits chemo-sensitivity via the production of mucin-degrading enzymes, which cleave negatively charged sialic acid, increasing the activity of 5-FU in these cancers as well as by lowering the expression of adherent mucins. This work points to a novel role of mucin-degrading microbes to promote 5-FU penetration of mucinous colorectal adenocarcinoma. This strategy has the potential to provide unique treatment strategies for patients with mucinous colorectal cancer. Citation Format: Leah K. Stripe, Amy C. Engevik, Mindy A. Engevik. Removal of mucin glycans by Bifidobacterium bifidum enhances chemotherapy-mediated cell death in mucinous adenocarcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1750.

Abstract 4205: Profiling symptom burden of RAS and BRAF mutations in patients with colorectal cancer: Results from the ColoCare Study

Abstract Background: Colorectal cancer (CRC) is a complex and heterogeneous disease characterized by distinct molecular features such as RAS and BRAF mutations. Assessing these molecular aberrations provides clinical guidance for selecting and predicting response with therapeutic modalities. Few reports have suggested that patient symptom burden at diagnosis differs across molecular subtypes of CRC. However, the association of RAS and BRAF mutations and symptom burden post-diagnosis in CRC patients has yet to be examined in a prospective cohort. Methods: We assessed CRC patients, stage I-IV, enrolled in the Moffitt ColoCare Study site with clinical molecular testing results and who completed a six-month questionnaire. Tumor mutation (MT) status (RAS/BRAF/Wildtype (WT)) was abstracted from the medical record. The MD Anderson Symptom Inventory (MDASI) was used to assess the severity of 13 cancer-related symptoms on a 1-to-10 scale. Mean scores in mutation subgroups were compared with one-way ANOVA. Linear regression analysis evaluated the association between symptom burden and mutation status. Multivariable regression models were adjusted for age, sex, stage at diagnosis, treatment, and microsatellite instability (MSI). Results: Among the 158 patients, the mean age at diagnosis was 60.9 ± 11.58 years. The prevalence of RAS and BRAF mutations was 30.4% (N=48) and 6.3% (N=10), respectively. Statistically significant mean differences between the mutation subgroups were distress (p=0.005), difficulty remembering (p=0.015), lack of appetite (p=0.042), and sadness (p=0.007). Patients with a BRAF-MT reported significantly more distress (p=0.001), difficulty remembering (p=0.029), and sadness (p=0.002) at six months compared to RAS-MT or RAS/BRAF-WT. Patients with a RAS-MT reported an increased lack of appetite (p=0.038) compared to BRAF-MT or RAS/BRAF-WT. Patients with a BRAF-MT reported higher severity of symptoms interfering with the enjoyment of life (p<0.001), work (p=0.005), and mood (p<0.001) compared to RAS-MT or RAS/BRAF-WT. In an adjusted multivariable model, patients with BRAF-MT tumors reported significantly greater distress compared with RAS/BRAF-WT patients [β = 3.18 per unit increase in severity, 95% CI (1.30 - 5.07), p=0.001)]. Overall symptom burden was associated with greater interference with daily activities for BRAF-MT patients when compared to RAS/BRAF-WT patients [β = 2.95, 95% CI (1.42 - 4.48), p<0.001)]. Conclusions: Tumors with BRAF-MT are molecularly classified into the serrated pathway, which has distinct clinical characteristics and risk factor profile. In this study, patients with tumors harboring BRAF-MT reported a higher symptom burden six months post-diagnosis than those with RAS-MT or RAS/BRAF-WT tumors. While the prevalence of BRAF-MT was low in this population, these findings warrant further investigation in a larger cohort. Citation Format: Gazelle Rouhani, Amanda M. Bloomer, Maria F. Gomez, Gillian K. Trujillo, Devon N. Conant, Seth I. Felder, Cornelia M. Ulrich, Christopher I. Li, Jane C. Figueiredo, Adetunji T. Toriola, Biljana Gigic, Martin Schneider, David Shibata, Erin M. Siegel. Profiling symptom burden of RAS and BRAF mutations in patients with colorectal cancer: Results from the ColoCare Study. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4205.

Abstract 160: Derivation and long-term maintenance of patient-derived tumoroid lines in a defined, serum-free medium

Abstract In vitro cancer research often fails to translate to the clinic, in part due to the use of traditional 2D cancer cell lines as models, which fail to resemble primary cancer cells by a variety of measures, including high mutational burden. An emerging solution to this problem is to replace traditional cell lines with patient tissue-derived cells expanded in 3D, also known as tumoroids or cancer organoids. We developed a defined, serum- and conditioned medium-free system, GibcoTM OncoProTM Tumoroid Culture Medium, that can be used to derive stable tumoroid lines from a variety of tissue sources and maintains the phenotype and genotype of patient-derived tumor cells. By supplementing the base medium with indication-specific growth factors, tumoroid lines were derived from colorectal, lung, and endometrial cancers from both fresh surgical resections and cryopreserved primary cancer cells. To demonstrate the utility of these patient-derived cells as long-term in vitro models, colorectal and lung tumoroid lines were derived from multiple donors and cultured for up to 50 passages. Brightfield microscopy, cell counts, and next-generation sequencing were used to assess maintenance of tumoroid morphology, growth rate, gene expression patterns, and genomic mutations. Patient-derived tumoroid cultures adopted donor-specific morphologies that were maintained during long-term culture. Cell doubling time tended to stabilize within the first few passages as cultures established, was donor-dependent, and averaged around 65 hours for colorectal tumoroids - on par with that of traditional 2D cancer cell lines - and 90-100 hours for lung and endometrial tumoroids, respectively. Importantly, tumoroid lines maintained their gene expression pattern for over 20,000 human RefSeq genes during long-term culture, with correlation between initial tumor material and late-passage samples of R>0.8. Distinct molecular subtypes of colorectal cancer were preserved in cultured tumoroids. The allelic frequency of single nucleotide variations (SNVs) in 161 highly relevant cancer genes was also highly correlated (R>0.9) between uncultured tissue and late-passage tumoroids. Within SNVs, transition/transversion mutation ratios were conserved. Tumoroids were cryopreserved and recovered during this study, demonstrating that biobanking of colorectal and lung tumoroids should not impact their long-term stability. Finally, a subset of the derived colorectal and lung tumoroids were tested and shown to be tumorigenic in mice, where subsequent histology of the tumor was similar to that of in vitro cultures. Altogether, tumoroid derivation and culture in this novel medium enables the long-term preservation of patient-specific cellular genotype and phenotype, which should allow for expansion, biobanking, and performance of experimental repeats within the same patient tissue-derived cultures across labs and over time. Citation Format: Chris Yankaskas, Brittany Balhouse, Colin Paul, Shyanne Salen, Sybelle Djikeng, Pradip Shahi Thakuri, Mark Kennedy, Matt Dallas, David Kuninger. Derivation and long-term maintenance of patient-derived tumoroid lines in a defined, serum-free medium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 160.

An immunometabolism subtyping system identifies S100A9+ macrophage as an immune therapeutic target in colorectal cancer based on multiomics analysis

Immunometabolism in the tumor microenvironment (TME) and its influence on the immunotherapy response remain uncertain in colorectal cancer (CRC). We perform immunometabolism subtyping (IMS) on CRC patients in the training and validation cohorts. Three IMS subtypes of CRC, namely, C1, C2, and C3, are identified with distinct immune phenotypes and metabolic properties. The C3 subtype exhibits the poorest prognosis in both the training cohort and the in-house validation cohort. The single-cell transcriptome reveals that a S100A9+ macrophage population contributes to the immunosuppressive TME in C3. The dysfunctional immunotherapy response in the C3 subtype can be reversed by combination treatment with PD-1 blockade and an S100A9 inhibitor tasquinimod. Taken together, we develop an IMS system and identify an immune tolerant C3 subtype that exhibits the poorest prognosis. A multiomics-guided combination strategy by PD-1 blockade and tasquinimod improves responses to immunotherapy by depleting S100A9+ macrophages invivo.

Towards targeted colorectal cancer biopsy based on tissue morphology assessment by compression optical coherence elastography.

Identifying the precise topography of cancer for targeted biopsy in colonoscopic examination is a challenge in current diagnostic practice. For the first time we demonstrate the use of compression optical coherence elastography (C-OCE) technology as a new functional OCT modality for differentiating between cancerous and non-cancerous tissues in colon and detecting their morphological features on the basis of measurement of tissue elastic properties. The method uses pre-determined stiffness values (Young's modulus) to distinguish between different morphological structures of normal (mucosa and submucosa), benign tumor (adenoma) and malignant tumor tissue (including cancer cells, gland-like structures, cribriform gland-like structures, stromal fibers, extracellular mucin). After analyzing in excess of fifty tissue samples, a threshold stiffness value of 520 kPa was suggested above which areas of colorectal cancer were detected invariably. A high Pearson correlation (r =0.98; p <0.05), and a negligible bias (0.22) by good agreement of the segmentation results of C-OCE and histological (reference standard) images was demonstrated, indicating the efficiency of C-OCE to identify the precise localization of colorectal cancer and the possibility to perform targeted biopsy. Furthermore, we demonstrated the ability of C-OCE to differentiate morphological subtypes of colorectal cancer - low-grade and high-grade colorectal adenocarcinomas, mucinous adenocarcinoma, and cribriform patterns. The obtained ex vivo results highlight prospects of C-OCE for high-level colon malignancy detection. The future endoscopic use of C-OCE will allow targeted biopsy sampling and simultaneous rapid analysis of the heterogeneous morphology of colon tumors.

Oncomicrobial Community Profiling Identifies Clinicomolecular and Prognostic Subtypes of Colorectal Cancer

Dysbiosis of gut microbiota is linked to the development of colorectal cancer (CRC). However, microbiota-based stratification of CRC tissue and how this relates to clinicomolecular characteristics and prognosis remains to be clarified. Tumor and normal mucosa from 423 patients with stage I to IV CRC were profiled by bacterial 16S rRNA gene sequencing. Tumors were characterized for microsatellite instability (MSI), CpG island methylator phenotype (CIMP), APC, BRAF, KRAS, PIK3CA, FBXW7, SMAD4, and TP53 mutations, subsets for chromosome instability (CIN), mutation signatures, and consensus molecular subtypes (CMS). Microbial clusters were validated in an independent cohort of 293 stage II/III tumors. Tumors reproducibly stratified into 3 oncomicrobial community subtypes (OCSs) with distinguishing features: OCS1 (Fusobacterium/oral pathogens, proteolytic, 21%), right-sided, high-grade, MSI-high, CIMP-positive, CMS1, BRAF V600E, and FBXW7 mutated; OCS2 (Firmicutes/Bacteroidetes, saccharolytic, 44%), and OCS3 (Escherichia/Pseudescherichia/Shigella, fatty acid β-oxidation, 35%) both left-sided and exhibiting CIN. OCS1 was associated with MSI-related mutation signatures (SBS15, SBS20, ID2, and ID7) and OCS2 and OCS3 with SBS18 related to damage by reactive oxygen species. Among stage II/III patients, OCS1 and OCS3 both had poorer overall survival compared with OCS2 for microsatellite stable tumors (multivariate hazard ratio [HR], 1.85; 95% confidence interval [CI], 1.15-2.99; P= .012; and HR, 1.52; 95% CI 1.01-2.29; P= .044, respectively) and left-sided tumors (multivariate HR, 2.66; 95% CI, 1.45-4.86; P= .002; and HR, 1.76; 95% CI, 1.03-3.02; P= .039, respectively). OCS classification stratified CRCs into 3 distinct subgroups with different clinicomolecular features and outcomes. Our findings provide a framework for a microbiota-based stratification of CRC to refine prognostication and to inform the development of microbiota-targeted interventions.

Phenotypic subtypes predict outcomes in colorectal cancer

BackgroundColorectal cancer (CRC) is the second leading cause of cancer-related deaths globally. The Colorectal Cancer Subtyping Consortium used the transcriptome-based method to classify CRC according to four molecular subtypes, each showing different genomic alterations and prognoses: CMS1 (microsatellite instable [MSI] immune), CMS2 (canonical), CMS3 (metabolic), and CMS4 (mesenchymal). To expedite the clinical implementation of such methods, easier and preferably tumor phenotype–based methods are needed. In this study, we describe a method to divide patients into four phenotypic subgroups using immunohistochemistry. Moreover, we analyze disease-specific survival (DSS) among different phenotypic subtypes and the associations between the phenotypic subtypes and clinicopathological variables.MethodsWe categorized 480 surgically treated CRC patients into four phenotypic subtypes (immune, canonical, metabolic, and mesenchymal) using the immunohistochemically determined CD3–CD8 tumor–stroma index, proliferation index, and tumor–stroma percentage. We analyzed survival rates for the phenotypic subtypes in different clinical patient subgroups using the Kaplan–Meier method and Cox regression analysis. Associations between phenotypic subtypes and clinicopathological variables were examined using the chi-square test.ResultsPatients with immune subtype tumors exhibited the best 5-year DSS, while mesenchymal subtype tumors accompanied the worst prognosis. The prognostic value of the canonical subtype showed wide variation among different clinical subgroups. Immune subtype tumors were associated with being female, stage I disease, and a right-side colon location. Metabolic tumors, however, were associated with pT3 and pT4 tumors, and being male. Finally, a mesenchymal subtype associated with stage IV disease, a mucinous histology, and a rectal tumor location.ConclusionsPhenotypic subtype predicts patient outcome in CRC. Associations and prognostic values for subtypes resemble the transcriptome-based consensus molecular subtypes (CMS) classification. In our study, the immune subtype stood out with its exceptionally good prognosis. Moreover, the canonical subtype showed wide variability among clinical subgroups. Further studies are needed to investigate the concordance between transcriptome-based classification systems and the phenotypic subtypes.

Construction of a TTN Mutation-Based Prognostic Model for Evaluating Immune Microenvironment, Cancer Stemness, and Outcomes of Colorectal Cancer Patients.

Colorectal cancer (CRC) is one of the commonest cancers worldwide. As conventional biomarkers cannot clearly define the heterogeneity of CRC, it is essential to establish novel prognostic models. For the training set, data pertaining to mutations, gene expression profiles, and clinical parameters were obtained from the Cancer Genome Atlas. Consensus clustering analysis was used to identify the CRC immune subtypes. CIBERSORT was used to analyze the immune heterogeneity across different CRC subgroups. Least absolute shrinkage and selection operator regression was used to identify the genes for constructing the immune feature-based prognostic model and to determine their coefficients. A gene prognostic model was then constructed to predict patient outcomes; the model was then externally validated using data from the Gene Expression Omnibus. As a high-frequency somatic mutation, the titin (TTN) mutation has been identified as a risk factor for CRC. Our results demonstrated that TTN mutations have the potential to modulate the tumor microenvironment, converting it into the immunosuppressive type. In this study, we identified the immune subtypes of CRC. Based on the identified subtypes, 25 genes were selected for prognostic model construction; a prediction model was also constructed, and its prediction accuracy was tested using the validation dataset. The potential of the model in predicting immunotherapy responsiveness was then explored. TTN-mutant and TTN-wild-type CRC demonstrated different microenvironment features and prognosis. Our model provides a robust immune-related gene prognostic tool and a series of gene signatures for evaluating the immune features, cancer stemness, and prognosis of CRC.

SHP2 deneddylation mediates tumor immunosuppression in colon cancer via the CD47/SIRPα axis.

SIPRα on macrophages binds with CD47 to resist proengulfment signals, but how the downstream signal of SIPRα controls tumor-infiltrating macrophages (TIMs) is still poorly clarified. Here, we report that the CD47/signal regulatory protein α (SIRPα) axis requires the deneddylation of tyrosine phosphatase SHP2. Mechanistically, Src homology region 2-containing protein tyrosine phosphatase 2 (SHP2) was constitutively neddylated on K358 and K364 sites; thus, its autoinhibited conformation was maintained. In response to CD47-liganded SIRPα, SHP2 was deneddylated by sentrin-specific protease 8 (SENP8), which led to the dephosphorylation of relevant substrates at the phagocytic cup and subsequent inhibition of macrophage phagocytosis. Furthermore, neddylation inactivated myeloid-SHP2 and greatly boosted the efficacy of colorectal cancer (CRC) immunotherapy. Importantly, we observed that supplementation with SHP2 allosteric inhibitors sensitized immune treatment-resistant CRC to immunotherapy. Our results emphasize that the CRC subtype that is unresponsive to immunotherapy relies on SIRPαhiSHP2hiNEDD8lo TIMs and highlight the need to further explore the strategy of SHP2 targeting in CRC therapy.

Impact of genome and epigenome on intratumor heterogeneity in colorectal cancer

Impact of genome and epigenome on intratumor heterogeneity in colorectal cancer

The past, present, and future of immunotherapy for colorectal cancer

Colorectal cancer is prevalent worldwide, with various factors influencing the survival rate of late-stage metastatic cases. Current standard treatments include surgical removal, adjuvant chemotherapy, and neoadjuvant chemotherapy. Novel immunotherapy research shows promising results for various cancer types, including colorectal cancer. Current immunotherapy options are limited to specific molecular subtypes of colorectal cancer, while the remaining are limited to standard protocol. This review article summarizes approved, developing, and potential sources for novel colorectal cancer immunotherapy treatment through active-specific, checkpoint inhibitor, cytokine, cytotoxic, and adoptive T-cell immunotherapy. Such a study would be beneficial to patients with colorectal cancer.

An antibody-drug conjugate targeting GPR56 demonstrates efficacy in preclinical models of colorectal cancer.

Long-term prognosis remains poor for colorectal cancer (CRC) patients with advanced disease due to treatment resistance. The identification of novel targets is essential for the development of new therapeutic approaches. GPR56, an adhesion GPCR, is highly expressed in CRC tumours and correlates with poor survival. Here, we describe the generation and preclinical evaluation of a novel ADC consisting of an anti-GPR56 antibody (10C7) conjugated with the DNA-damaging payload duocarmycin. RNA-seq dataset analysis was performed to determine GPR56 expression in CRC subtypes. The specificity of binding, epitope mapping, and internalisation of 10C7 was examined. 10C7 was conjugated to payload and ADC cytotoxicity was assessed against a panel of CRC cell lines and tumour organoids. Antitumour efficacy was evaluated in xenograft models of CRC cell lines and patient-derived tumours. High GPR56 was shown to be associated with the microsatellite stable (MSS) subtype that accounts for 80-85% of CRC. GPR56 ADC selectively induced cytotoxicity in CRC cells and tumour organoids at low nanomolar potency in a GPR56-dependent manner and showed significant antitumour efficacy against GPR56-expressing xenograft models. This study provides the rationale for the future development of a GPR56-targeted ADC approach to potentially treat a large fraction of MSS CRC patients.