Cohort Of Colorectal Cancer Patients Research Articles

AMIGO2 characterizes cancer-associated fibroblasts in metastatic colon cancer and induces the release of paracrine active tumorigenic secretomes.

Secretomes of cancer-associated fibroblasts (CAFs) in colorectal cancer (CRC) contribute to malignancy. Detailed knowledge is available on the components and functions of CAF secretomes. Little is known about the regulation of CAF secretomes. Here, we searched for receptor-like membrane-bound molecules in CAFs, which may regulate the production and release of tumor-activating secretomes. The adhesion molecule with Ig-like domain 2 (AMIGO2) was significantly upregulated in cultivated CAFs compared to normal tissue-associated fibroblasts (NAFs), and this was confirmed in patient-derived tissues. AMIGO2 expression was low or absent in healthy colon, significantly increased in fibroblasts of primary CRC, and highest in the stromal tissues of CRC-derived liver metastases. AMIGO2 expression in CAFs correlated with a higher T-category, increased lymph node metastasis, progressed tumor stages and was associated with reduced survival in different cohorts of CRC patients. Interestingly, AMIGO2 expression was induced by transforming growth factor-β and higher in female patients, who exhibit a more aggressive disease course. In functional studies, conditioned media of NAFs with experimentally induced AMIGO2 overexpression enhanced proliferation and migration of different CRC tumor cells, while siRNA-mediated inhibition of AMIGO2 in CAFs attenuated these effects. Accordingly, therapeutic inhibition of the receptor-like AMIGO2 protein in CRC CAFs could prevent tumorigenic secretomes in CRC. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Metagenomic analysis during capecitabine therapy reveals microbial chemoprotective mechanisms and predicts drug toxicity in colorectal cancer patients.

Unpredictable chemotherapy side effects are a major barrier to successful treatment. Cell culture and mouse experiments indicate that the gut microbiota is influenced by and influences anti-cancer drugs. However, metagenomic data from patients paired to careful side effect monitoring remains limited. Herein, we focus on the oral fluoropyrimidine capecitabine (CAP). We investigate CAP-microbiome interactions through metagenomic sequencing of longitudinal stool sampling from a cohort of advanced colorectal cancer (CRC) patients. We established a prospective cohort study including 56 patients with advanced CRC treated with CAP monotherapy across 4 centers in the Netherlands. Stool samples and clinical questionnaires were collected at baseline, during cycle 3, and post-treatment. Metagenomic sequencing to assess microbial community structure and gene abundance was paired with transposon mutagenesis, targeted gene deletion, and media supplementation experiments. An independent US cohort was used for model validation. CAP treatment significantly altered gut microbial composition and pathway abundance, enriching for menaquinol (vitamin K2) biosynthesis genes. Transposon library screens, targeted gene deletions, and media supplementation confirmed that menaquinol biosynthesis protects Escherichia coli from drug toxicity. Microbial menaquinol biosynthesis genes were associated with decreased peripheral sensory neuropathy. Machine learning models trained in this cohort predicted hand-foot syndrome and dose reductions in an independent cohort. These results suggest treatment-associated increases in microbial vitamin biosynthesis serve a chemoprotective role for bacterial and host cells, with implications for toxicities outside the gastrointestinal tract. We provide a proof-of-concept for the use of microbiome profiling and machine learning to predict drug toxicities across independent cohorts. These observations provide a foundation for future human intervention studies, more in-depth mechanistic dissection in preclinical models, and extension to other cancer treatments.

Harnessing the power of AI in precision medicine: NGS-based therapeutic insights for colorectal cancer cohort.

Developing innovative precision and personalized cancer therapeutics is essential to enhance cancer survivability, particularly for prevalent cancer types such as colorectal cancer. This study aims to demonstrate various approaches for discovering new targets for precision therapies using artificial intelligence (AI) on a Polish cohort of colorectal cancer patients. We analyzed 71 patients with histopathologically confirmed advanced resectional colorectal adenocarcinoma. Whole exome sequencing was performed on tumor and peripheral blood samples, while RNA sequencing (RNAseq) was conducted on tumor samples. We employed three approaches to identify potential targets for personalized and precision therapies. First, using our in-house neoantigen calling pipeline, ARDentify, combined with an AI-based model trained on immunopeptidomics mass spectrometry data (ARDisplay), we identified neoepitopes in the cohort. Second, based on recurrent mutations found in our patient cohort, we selected corresponding cancer cell lines and utilized knock-out gene dependency scores to identify synthetic lethality genes. Third, an AI-based model trained on cancer cell line data was employed to identify cell lines with genomic profiles similar to selected patients. Copy number variants and recurrent single nucleotide variants in these cell lines, along with gene dependency data, were used to find personalized synthetic lethality pairs. We identified approximately 8,700 unique neoepitopes, but none were shared by more than two patients, indicating limited potential for shared neoantigenic targets across our cohort. Additionally, we identified three synthetic lethality pairs: the well-known APC-CTNNB1 and BRAF-DUSP4 pairs, along with the recently described APC-TCF7L2 pair, which could be significant for patients with APC and BRAF variants. Furthermore, by leveraging the identification of similar cancer cell lines, we uncovered a potential gene pair, VPS4A and VPS4B, with therapeutic implications. Our study highlights three distinct approaches for identifying potential therapeutic targets in cancer patients. Each approach yielded valuable insights into our cohort, underscoring the relevance and utility of these methodologies in the development of precision and personalized cancer therapies. Importantly, we developed a novel AI model that aligns tumors with representative cell lines using RNAseq and methylation data. This model enables us to identify cell lines closely resembling patient tumors, facilitating accurate selection of models needed for in vitro validation.

Associations of KRAS Mutations and Clinical Characteristics of Colorectal Cancer Patients in Indonesia.

Colorectal cancer (CRC) remains a major burden worldwide, ranking third and second in incidence and mortality respectively. Detection of biomarkers including KRAS mutations can help predict prognosis and response to therapy in CRC, thus this study evaluated the frequency of KRAS mutations among Indonesian patients and their associations with clinicopathologic characteristics. Fifty-three CRC samples were collected from January to September 2022 in the Department of Surgery, Dr. Hasan Sadikin General Hospital, Bandung, Indonesia. KRAS mutations were analyzed using PCR followed by Sanger sequencing. Associations between KRAS mutations were evaluated using binary logistic regression analysis. KRAS mutations were detected in 52.8% of patients (n=28), of which 3.6% were p.Gly12Ser (n=1), 32.1% were p.Gly12Asp (n=9), 7.1% were p.Gly13Asp (n=2), 3.6% were p.Gln61His (n=1), 3.6% were p.Asp126His (n=1), and 3.6% were p.Lys169Glu (n=1). The p.Asp73= polymorphism was detected in 57.1% of the samples (n=16). KRAS mutation status did not differ significantly between the groups based on the age of onset, sex, tumor location, tumor histology, stage, and family history. KRAS mutations are present in high frequency in this cohort of CRC patients in a tertiary hospital in West Java, Indonesia. However, KRAS mutation status is not associated with the age of onset, sex, tumor location, tumor histology, stage, and family history.

Copy number amplification-induced overexpression of lncRNA LOC101927668 facilitates colorectal cancer progression by recruiting hnRNPD to disrupt RBM47/p53/p21 signaling

BackgroundSomatic copy number alterations (SCNAs) are pivotal in cancer progression and patient prognosis. Dysregulated long non-coding RNAs (lncRNAs), modulated by SCNAs, significantly impact tumorigenesis, including colorectal cancer (CRC). Nonetheless, the functional significance of lncRNAs induced by SCNAs in CRC remains largely unexplored.MethodsThe dysregulated lncRNA LOC101927668, induced by copy number amplification, was identified through comprehensive bioinformatic analyses utilizing multidimensional data. Subsequent in situ hybridization was employed to ascertain the subcellular localization of LOC101927668, and gain- and loss-of-function experiments were conducted to elucidate its role in CRC progression. The downstream targets and signaling pathway influenced by LOC101927668 were identified and validated through a comprehensive approach, encompassing RNA sequencing, RT-qPCR, Western blot analysis, dual-luciferase reporter assay, evaluation of mRNA and protein degradation, and rescue experiments. Analysis of AU-rich elements (AREs) within the mRNA 3’ untranslated region (UTR) of the downstream target, along with exploration of putative ARE-binding proteins, was conducted. RNA pull-down, mass spectrometry, RNA immunoprecipitation, and dual-luciferase reporter assays were employed to elucidate potential interacting proteins of LOC101927668 and further delineate the regulatory mechanism between LOC101927668 and its downstream target. Moreover, subcutaneous xenograft and orthotopic liver xenograft tumor models were utilized to evaluate the in vivo impact of LOC101927668 on CRC cells and investigate its correlation with downstream targets.ResultsSignificantly overexpressed LOC101927668, driven by chr7p22.3-p14.3 amplification, was markedly correlated with unfavorable clinical outcomes in our CRC patient cohort, as well as in TCGA and GEO datasets. Moreover, we demonstrated that enforced expression of LOC101927668 significantly enhanced cell proliferation, migration, and invasion, while its depletion impeded these processes in a p53-dependent manner. Mechanistically, nucleus-localized LOC101927668 recruited hnRNPD and translocated to the cytoplasm, accelerating the destabilization of RBM47 mRNA, a transcription factor of p53. As a nucleocytoplasmic shuttling protein, hnRNPD mediated RBM47 destabilization by binding to the ARE motif within RBM47 3'UTR, thereby suppressing the p53 signaling pathway and facilitating CRC progression.ConclusionsThe overexpression of LOC101927668, driven by SCNAs, facilitates CRC proliferation and metastasis by recruiting hnRNPD, thus perturbing the RBM47/p53/p21 signaling pathway. These findings underscore the pivotal roles of LOC101927668 and highlight its therapeutic potential in anti-CRC interventions.

Development of a Novel Prognostic Panel for Colorectal Cancer Based on Cancer Functional Status, and Validation of STC2 as a Promising Biomarker.

Improving the clinical outcome of colorectal cancer (CRC) patients remains a major challenge. This study aimed to develop a new predictive classifier for CRC and to examine its relationship with the immune environment and therapeutic response. A comprehensive bioinformatics analysis was applied to develop a risk panel comprised of cancer function status-related genes (CFSRGs). This panel was evaluated for prognostic utility by Area Under the Curve (AUC) and Kaplan-Meier (KM) analyses. Differences between high- and low-risk groups were subsequently investigated using multi-omics data. Immunohistochemistry (IHC), quantitative real-time polymerase chain reaction (qRT-PCR), and cell phenotype assays were also employed to ascertain the clinical value of STC2 expression. Significant differences were observed in the survival rate between high- and low-risk groups defined by our 7-CFSRG panel, both in internal and external CRC patient cohorts. The AUC for prediction of survival at 1-, 3- and 5-years was satisfactory in all cohorts. Detailed analysis revealed that tumor mutation burden, drug sensitivity, and pathological stage were closely associated with the risk score. Elevated expression of STC2 in CRC tissues relative to normal paraneoplastic tissues was associated with less favorable patient outcomes. qRT-PCR experiments confirmed that STC2 expression was significantly upregulated in several CRC cell lines (HCT116, SW480, and LOVO) compared to a normal intestinal epithelial cell line (NCM460). The proliferation, migration, and invasion of CRC cells were all significantly inhibited by knockdown of STC2. Our 7-CFSRG panel is a promising classifier for assessing the prognosis of CRC patients. Moreover, the targeting of STC2 may provide a novel therapeutic approach for improving patient outcomes.

A consensus molecular subtypes classification strategy for clinical colorectal cancer tissues.

Consensus Molecular Subtype (CMS) classification of colorectal cancer (CRC) tissues is complicated by RNA degradation upon formalin-fixed paraffin-embedded (FFPE) preservation. Here, we present an FFPE-curated CMS classifier. The CMSFFPE classifier was developed using genes with a high transcript integrity in FFPE-derived RNA. We evaluated the classification accuracy in two FFPE-RNA datasets with matched fresh-frozen (FF) RNA data, and an FF-derived RNA set. An FFPE-RNA application cohort of metastatic CRC patients was established, partly treated with anti-EGFR therapy. Key characteristics per CMS were assessed. Cross-referenced with matched benchmark FF CMS calls, the CMSFFPE classifier strongly improved classification accuracy in two FFPE datasets compared with the original CMSClassifier (63.6% versus 40.9% and 83.3% versus 66.7%, respectively). We recovered CMS-specific recurrence-free survival patterns (CMS4 versus CMS2: hazard ratio 1.75, 95% CI 1.24-2.46). Key molecular and clinical associations of the CMSs were confirmed. In particular, we demonstrated the predictive value of CMS2 and CMS3 for anti-EGFR therapy response (CMS2&3: odds ratio 5.48, 95% CI 1.10-27.27). The CMSFFPE classifier is an optimized FFPE-curated research tool for CMS classification of clinical CRC samples.

Propensity score matching as an effective strategy for biomarker cohort design and omics data analysis.

Analysis of omics data that contain multidimensional biological and clinical information can be complex and make it difficult to deduce significance of specific biomarker factors. We explored the utility of propensity score matching (PSM), a statistical technique for minimizing confounding factors and simplifying the examination of specific factors. We tested two datasets generated from cohorts of colorectal cancer (CRC) patients, one comprised of immunohistochemical analysis of 12 protein markers in 544 CRC tissues and another consisting of RNA-seq profiles of 163 CRC cases. We examined the efficiency of PSM by comparing pre- and post-PSM analytical results. Unlike conventional analysis which typically compares randomized cohorts of cancer and normal tissues, PSM enabled direct comparison between patient characteristics uncovering new prognostic biomarkers. By creating optimally matched groups to minimize confounding effects, our study demonstrates that PSM enables robust extraction of significant biomarkers while requiring fewer cancer cases and smaller overall patient cohorts. PSM may emerge as an efficient and cost-effective strategy for multiomic data analysis and clinical trial design for biomarker discovery.

Abstract LB386: Weakly-supervised prediction of tumor infiltrating lymphocytes per high power field from colorectal cancer histopathology slides using regression transformers

Abstract Tumor infiltrating lymphocytes (TILs)-based biomarkers have emerged as a robust method for predicting treatment efficacy and outcome in colorectal cancer (CRC). However, the quantification of TILs remains a strenuous task for pathologists and is susceptible to inter-pathologist variations. Deep learning (DL) can predict cancer biomarkers directly from routine hematoxylin and eosin (H&E) pathology slides, enabling the automated and consistent quantification of TILs for clinical decision-making. Our study focuses on the prediction of TILs per high-power field (HPF) on two large cohorts of CRC patients. We developed a weakly-supervised, transformer-based deep regression model to predict TILs per HPF from routine H&E-stained histology slides. We trained the model using 5-fold cross-validation on a large cohort of CRC patients (n=1,738), and validated its performance on an external cohort of CRC patients (n=223). The model was evaluated using the Pearson’s correlation coefficient r. Moreover, pathologist-determined TILs per HPF was categorized into low (<2) and high (≥2), enabling evaluation via the area under the receiver operating characteristic curve (AUROC). Our model achieved a significant correlation coefficient of 0.60 (p<0.0001) for the predicted TILs per HPF in the holdout test sets of the internal cohort, and a significant correlation coefficient of 0.57 (p<0.0001) on the external validation cohort. Using the thresholds for low and high TILs per HPF, we found that the model accurately predicted the presence of high TILs per HPF in both the internal and external test cohorts, yielding AUROCs of 0.76 and 0.81, respectively. These findings underscore the efficacy of our deep learning model in predicting TILs per HPF from routine pathology slides. This approach holds promise for cost-effective, efficient and uniform quantification of TILs per HPF in CRC, potentially across various cancer types. Citation Format: Omar S. El Nahhas, Joseph D. Bonner, Joel K. Greenson, Daniel B. Schmolze, Lawrence Shaktah, Jonathan Salazar, Lorena Reynaga, Sidney Lindsey, Jenny Lu, Victor Moreno, Stephanie L. Schmit, Ya-Yu Tsai, Stanley R. Hamilton, Gad Rennert, Jakob N. Kather, Stephen B. Gruber. Weakly-supervised prediction of tumor infiltrating lymphocytes per high power field from colorectal cancer histopathology slides using regression transformers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB386.

Therapy-induced senescent tumor cell-derived extracellular vesicles promote colorectal cancer progression through SERPINE1-mediated NF-κB p65 nuclear translocation

BackgroundCellular senescence frequently occurs during anti-cancer treatment, and persistent senescent tumor cells (STCs) unfavorably promote tumor progression through paracrine secretion of the senescence-associated secretory phenotype (SASP). Extracellular vesicles (EVs) have recently emerged as a novel component of the SASP and primarily mediate the tumor-promoting effect of the SASP. Of note, the potential effect of EVs released from STCs on tumor progression remains largely unknown.MethodsWe collected tumor tissues from two cohorts of colorectal cancer (CRC) patients to examine the expression of p16, p21, and SERPINE1 before and after anti-cancer treatment. Cohort 1 included 22 patients with locally advanced rectal cancer (LARC) who received neoadjuvant therapy before surgical resection. Cohort 2 included 30 patients with metastatic CRC (mCRC) who received first-line irinotecan-contained treatment. CCK-8, transwell, wound-healing assay, and tumor xenograft experiments were carried out to determine the impacts of EVs released from STCs on CRC progression in vitro and in vivo. Quantitative proteomic analysis was applied to identify protein cargo inside EVs secreted from STCs. Immunoprecipitation and mass spectrometer identification were utilized to explore the binding partners of SERPINE1. The interaction of SERPINE1 with p65 was verified by co-immunoprecipitation, and their co-localization was confirmed by immunofluorescence.ResultsChemotherapeutic agents and irradiation could potently induce senescence in CRC cells in vitro and in human CRC tissues. The more significant elevation of p16 and p21 expression in patients after anti-cancer treatment displayed shorter disease-free survival (DFS) for LARC or progression-free survival (PFS) for mCRC. We observed that compared to non-STCs, STCs released an increased number of EVs enriched in SERPINE1, which further promoted the progression of recipient cancer cells. Targeting SERPINE1 with a specific inhibitor, tiplaxtinin, markedly attenuated the tumor-promoting effect of STCs-derived EVs. Additionally, the patients with greater increment of SERPINE1 expression after anti-cancer treatment had shorter DFS for LARC or PFS for mCRC. Mechanistically, SERPINE1 bound to p65, promoting its nuclear translocation and subsequently activating the NF-κB signaling pathway.ConclusionsWe provide the in vivo evidence of the clinical prognostic implications of therapy-induced senescence. Our results revealed that STCs were responsible for CRC progression by producing large amounts of EVs enriched in SERPINE1. These findings further confirm the crucial role of therapy-induced senescence in tumor progression and offer a potential therapeutic strategy for CRC treatment.

Abstract 3779: Genomic and clinical characterization of metastatic patterns using real-word data from a large cohort of colorectal cancer patients

Abstract Background: Colorectal cancers (CRCs) can exhibit disparate metastatic patterns that affect outcomes. We investigated associations between genomic features and organ-specific metastatic tropism and we compared the frequency of actionable alterations detected in patients undergoing longitudinal clinical sequencing. Methods: We analyzed data for 6574 tumors from 6153 CRC patients, including 4510 primary and 2064 metastatic specimens. All patients had microsatellite stable (MSS) disease and were treated at Memorial Sloan Kettering. Paired primary and metastatic samples were available for 203 patients. Tumors were sequenced with MSK-IMPACT, a targeted DNA sequencing assay that identifies genomic alterations in 341-505 genes. Clinical annotations included sex, stage at diagnosis (Dx), and primary tumor location. History of metastatic disease was automatically retrieved from radiology reports using validated natural language processing methods; time to specific-site metastasis was modeled with Cox regression. False discovery rate (FDR) was used to correct for multiple hypothesis testing. The OncoKB knowledge base was used to identify clinically actionable alterations. Results: Liver (n=1068, 51.7%), peritoneal (n=269, 13.0%) and lung metastases (n=263, 12.7%) accounted for the majority of non-primary sequenced specimens. The frequency of actionable alterations (OncoKB Level≥3A) did not vary between unmatched metastatic and primary samples (12.3% vs 11.4%, p=0.302). In primary tumor samples from patients with localized disease at the time of diagnosis, TGFB pathway alterations were associated with increased risk of metastasis to the brain (HR=2.41, p=0.028), bone (HR=2.10, p<0.001), peritoneum (HR=1.82, p=0.001) and liver (HR=1.42, p=0.049). Alterations in the RAS pathway were associated with increased risk of lung (HR=1.47, p=0.009), peritoneum (HR=1.54, p=0.021) and liver (HR=1.44, p=0.026) metastases. By contrast, WNT pathway alterations were associated with a lower risk of developing lung (HR=0.69, p=0.033) and peritoneal metastasis (HR=0.68, p=0.081). Among patients with paired primary and metastatic samples, no significant difference was observed between the frequency of clinically actionable alterations in primary vs. metastatic specimens (16.7% vs. 18.2%, p=0.794). Presence of metastases-private or primary-private alterations did not correlate with site-specific metastasis risk. Conclusions: The risk of developing metastatic disease and organ-specific dissemination might be linked to genomic abnormalities detectable at the localized stage. No significant difference in the frequency of actionable alterations was observed between primary and metastatic CRC samples. Citation Format: Paolo Manca, Ayush V. Kris, Henry Walch, Christopher Fong, Justin Jee, Karl Pichotta, Nikolaus Schultz, Walid K. Chatila, Rona Yaeger, Francisco Sanchez-Vega. Genomic and clinical characterization of metastatic patterns using real-word data from a large cohort of colorectal cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3779.

Abstract 4634: Inhibitory-κB kinase alpha as a biomarker and therapeutic target in colorectal cancer

Abstract Introduction/Aims: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality. The canonical NF-κB pathway driven by IKKβ has been implicated in CRC development and progression, however less research has focused on non-canonical NF-κB signaling, regulated by inhibitory-κB kinase alpha (IKKα). This project aimed to assess IKKα, phospho-IKKα (pIKKαs176) and IKKβ expression in a retrospective CRC cohort to establish association with survival outcomes. Subsequently, this project aimed to determine the effect of abrogating IKKα activity without perturbing the canonical NF-κB pathway controlled by IKKβ using a first-in-class selective IKKα inhibitor in vitro/ex vivo. Methods: Immunohistochemical staining for IKKα/pIKKα s176/IKKβ was performed using tissue microarrays from a CRC patient cohort (n=787). QuPath® software was used to semi-quantitively assess expression levels and scores were analyzed for association with cancer-specific survival (CSS). CRC cell lines (n=3), patient-derived organoids (PDOs; n=5) and patient-derived explants (n=5) were treated with novel IKKα inhibitor SU1644 and assessed for cell viability and proliferation. Results: Positive staining for IKKα, pIKKαs176 and IKKβ was detected in tumor specimens. High cytoplasmic expression of IKKα within tumor cells was associated with reduced CSS in patients with right-sided colon cancer (HR=3.091, 95%CI; 1.128-9.467, log rank p=0.021). Conversely, high IKKβ expression was a marker of good prognosis (HR=0.627, 95%CI; 0.457-0.861, log rank p=0.004). A high ratio of IKKα to IKKβ was associated with reduced CSS in the full cohort (HR=1.404, 95%CI; 1.050-1.879, log rank p=0.021) and this was potentiated in right-sided colon cases (HR=1.772, 95%CI; 1.107-2.837, log rank p=0.016). Selective inhibition of IKKα using 1µM SU1644 in vitro caused a significant reduction in HT29 colony formation (p=0.012) and cell viability (p=0.039). PDOs showed altered cell morphology, reduced cell viability and proliferation when treated with SU1644. In the patient-derived explant model, Ki67 expression was reduced in tumor explants treated with SU1644. Conclusions: These data establish high cytoplasmic IKKα expression within tumor cells as a marker of poor prognosis in CRC and conversely high IKKβ expression as a marker of good prognosis. This highlights the importance of development of selective IKKα inhibitor SU1644. IKKα inhibition using SU1644 demonstrated anti-cancer activity in recapitulative CRC disease models. Citation Format: Kathryn A. Pennel, Molly McKenzie, Guang-Yu Lian, Jean A. Quinn, Sara Samir Foad Al-Badran, Campbell S. Roxburgh, Simon P. Mackay, Joanna Birch, Joanne Edwards. Inhibitory-κB kinase alpha as a biomarker and therapeutic target in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4634.

Abstract 4788: Noninvasive longitudinal monitoring of residual disease in chemotherapy-treated colorectal cancer patients

Abstract Noninvasive monitoring of cancer shows great promise in assessing therapy response and improving patient outcomes. Recently, various groups have developed methods that detect circulating tumor DNA (ctDNA) in the plasma to measure minimal or molecular residual disease (MRD). Aberrant DNA methylation patterns are a hallmark of cancers, and robust signals can be detected by sensitive ctDNA assays. Here, we present a methylation-based approach for longitudinal monitoring of tumor burden that is tumor-naive, i.e., with no reliance on prior characterization of tumor molecular characteristics. We assess the effectiveness of our approach in a cohort of colorectal cancer (CRC) patients receiving chemotherapy with or without additional targeted agents. Longitudinal blood samples were collected from patients (n = 57) while on therapy, which averaged 4.9 months, for a total of 239 sample collection time points (median per patient = 5). Based on RECIST status, 16 patients were classified as complete responders (CR) at the end of treatment. We generated plasma cell free DNA-derived libraries for methylation sequencing targeting regions relevant to CRC. Next, we computed a disease burden score for each sample and related these scores to clinical response (CR vs. non-CR). We trained a classifier on an independent cohort of CRC and healthy donor plasma cfDNA samples, and used this classifier to check for residual disease at the end of treatment for each of our 57 patients. The classifier detected residual disease in only 3/16 CRs (19%) but 35/41 non-CRs (85%). Two of the non-CR patients were initially assessed as CRs at earlier time points. In both cases, our method successfully detected residual disease at or prior to the CR assessment and consistently showed residual disease in all follow up samples. This suggests improved sensitivity relative to RECIST and highlights the potential of using noninvasive blood tests for continuous monitoring of CRC patients receiving therapy. Citation Format: Alison D. Tang, Rebecca Gupte, Victoria Cheung, Tao Qing, Austin Cauwels, Emily Leff, Kimberly Walter, Ehsan Tabari, Alex Lovejoy, Jimmy C. Lin. Noninvasive longitudinal monitoring of residual disease in chemotherapy-treated colorectal cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4788.

Abstract 67: Predicting colorectal patient prognoses by functional characterisation of heterogeneous cell types and their spatial interaction using a new technique: Whole slide imaging mass cytometry

Abstract Immunotherapies stimulate T cell function in the tumor microenvironment (TME). CD3+ and CD8+ T cell infiltration can predict disease recurrence in colorectal cancer (CRC) patients and has been validated as Immunoscore® (IS). The TME comprises multiple heterogeneous populations of immune cells, including T cells and cancer-associated fibroblasts (CAFs); CRC tumors are also morphologically diverse. Standard BioTools™ (SBI) has developed a novel whole slide Imaging Mass Cytometry™ technique that allows complete analysis of cell population heterogeneity in the TME using >40 markers. We hypothesised there are multiple heterogeneous subtypes of CAFs within CRC tumors and that they modulate T cell infiltration and patient outcome. In collaboration with SBI, we studied a cohort of CRC patients stratified based on T cell infiltrate and disease recurrence. We identified multiple CAF populations that interact with tumor-infiltrating T cell populations. Slides from 10 CRC patients with high or low CD3+CD8+ T cell infiltrate (IS) were stained with a panel encompassing markers for CAF and T cell heterogeneity, function, and metabolism. Slides were imaged using the Hyperion XTi™ Imaging System at SBI. Using a scan mode called Preview Mode, the whole slide was imaged in minutes to identify CAF and T cell phenotypic regions of interest. Next, the same slide was imaged at 1 μm resolution using Cell Mode (CM). Finally, for each sample, an additional serial section was imaged using a slightly lower resolution called Tissue Mode (TM). TM allowed us to image the samples in several hours instead of days while capturing the full heterogeneity of the entire tissue sample. We used clustering to identify phenotype clusters and neighbourhood analysis to study spatial enrichment. We also compared results between CM and TM. We report: Identification of heterogeneous CAF subtypes in CRC patients with high or low IS; determination of CAF populations that spatially interact with T cells in patients with high or low IS; and examination of consistent spatial interactions between CAF and T cells in CRC, and whether these interactions differ in patients with high or low IS. TM revealed several heterogeneous cellular populations that differed between patients with high or low IS; importantly, low IS tumors had more podoplanin+αSMA+ CAF populations and fewer podoplanin+αSMA- cell populations compared with high IS tumors. High IS tumors had more PD-1+CD8+ T cells compared with low IS tumors; these PD-1+CD8+ T cells spatially interacted with podoplanin+αSMA- CAF populations in high IS tumors. CAF-PD-1+CD8+ T cell interactions were absent from low IS tumors. Thus, CAF-PD-1+CD8+ T cell interactions are important in CRC patients with high IS, and these cellular interactions require further investigation. Citation Format: Rory M. Costello, Sonya Fenton, Helen McGuire, Liang Lim, David Howell, Qanber Raza, Jyh Yun Chwee, Roslyn Kemp. Predicting colorectal patient prognoses by functional characterisation of heterogeneous cell types and their spatial interaction using a new technique: Whole slide imaging mass cytometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 67.

Glycemic traits and colorectal cancer survival in a cohort of South Korean patients: A Mendelian randomization analysis.

Clinical diabetic traits have been reported to be associated with increased colorectal cancer (CRC) risk in observational studies. Using the Mendelian randomization (MR) analysis method, we examined the causal association between glycemic traits, such as fasting glucose (FG), fasting insulin (FI), and glycosylated hemoglobin A1c (HbA1c), and survival in a cohort of CRC patients. We conducted a two-sample MR analysis among a cohort of patients with locally advanced CRC at Seoul National University Hospital. Single-nucleotide polymorphisms robustly associated (p < 5 × 10-8 ) with the three glycemic traits were obtained from the Meta-Analyses of Glucose and Insulin-related traits Consortium, Asian Genetic Epidemiology Network, and Korea Biobank Array. Three-year and 5-year overall survival (OS) and progression-free survival (PFS) were used as outcomes. Survival analysis was conducted using subgroup analysis by cancer stage and subsite in a multivariate Cox proportional hazards model adjusted for age and sex to examine whether glycemic traits affected survival. A total of 509 patients were included in our final analysis. MR analysis showed that HbA1c levels were associated with poor 3-year OS (β = 4.20, p = 0.02). Sensitivity analyses did not show evidence of any violations of the MR assumptions. In the cancer subgroup analysis of the Cox proportional hazards model, pooled hazard ratios for FG were significantly associated with poor 3-year OS and PFS regardless of cancer stage. FI was not significantly associated with any 3-year survival endpoints. Among Stage III patients, three glycemic traits were significantly associated with both 5-year OS and PFS. Location-specific subgroup analysis showed a significant association between three glycemic traits and 5-year PFS in patients with left-sided colon cancer. FG was associated with poor 3-year survival for colon cancer but not rectal cancer. Our results suggest that FG and HbA1c could be used to predict prognosis in CRC patients. Lifestyle and/or pharmacological interventions targeting glycemic traits could help improve survival for CRC patients.

JAK/STAT3 represents a therapeutic target for colorectal cancer patients with stromal-rich tumors

Colorectal cancer (CRC) is a heterogenous malignancy underpinned by dysregulation of cellular signaling pathways. Previous literature has implicated aberrant JAK/STAT3 signal transduction in the development and progression of solid tumors. In this study we investigate the effectiveness of inhibiting JAK/STAT3 in diverse CRC models, establish in which contexts high pathway expression is prognostic and perform in depth analysis underlying phenotypes. In this study we investigated the use of JAK inhibitors for anti-cancer activity in CRC cell lines, mouse model organoids and patient-derived organoids. Immunohistochemical staining of the TransSCOT clinical trial cohort, and 2 independent large retrospective CRC patient cohorts was performed to assess the prognostic value of JAK/STAT3 expression. We performed mutational profiling, bulk RNASeq and NanoString GeoMx® spatial transcriptomics to unravel the underlying biology of aberrant signaling. Inhibition of signal transduction with JAK1/2 but not JAK2/3 inhibitors reduced cell viability in CRC cell lines, mouse, and patient derived organoids (PDOs). In PDOs, reduced Ki67 expression was observed post-treatment. A highly significant association between high JAK/STAT3 expression within tumor cells and reduced cancer-specific survival in patients with high stromal invasion (TSPhigh) was identified across 3 independent CRC patient cohorts, including the TrasnSCOT clinical trial cohort. Patients with high phosphorylated STAT3 (pSTAT3) within the TSPhigh group had higher influx of CD66b + cells and higher tumoral expression of PDL1. Bulk RNAseq of full section tumors showed enrichment of NFκB signaling and hypoxia in these cases. Spatial deconvolution through GeoMx® demonstrated higher expression of checkpoint and hypoxia-associated genes in the tumor (pan-cytokeratin positive) regions, and reduced lymphocyte receptor signaling in the TME (pan-cytokeratin- and αSMA-) and αSMA (pan-cytokeratin- and αSMA +) areas. Non-classical fibroblast signatures were detected across αSMA + regions in cases with high pSTAT3. Therefore, in this study we have shown that inhibition of JAK/STAT3 represents a promising therapeutic strategy for patients with stromal-rich CRC tumors. High expression of JAK/STAT3 proteins within both tumor and stromal cells predicts poor outcomes in CRC, and aberrant signaling is associated with distinct spatially-dependant differential gene expression.

Regression-based Deep-Learning predicts molecular biomarkers from pathology slides

Deep Learning (DL) can predict biomarkers from cancer histopathology. Several clinically approved applications use this technology. Most approaches, however, predict categorical labels, whereas biomarkers are often continuous measurements. We hypothesize that regression-based DL outperforms classification-based DL. Therefore, we develop and evaluate a self-supervised attention-based weakly supervised regression method that predicts continuous biomarkers directly from 11,671 images of patients across nine cancer types. We test our method for multiple clinically and biologically relevant biomarkers: homologous recombination deficiency score, a clinically used pan-cancer biomarker, as well as markers of key biological processes in the tumor microenvironment. Using regression significantly enhances the accuracy of biomarker prediction, while also improving the predictions’ correspondence to regions of known clinical relevance over classification. In a large cohort of colorectal cancer patients, regression-based prediction scores provide a higher prognostic value than classification-based scores. Our open-source regression approach offers a promising alternative for continuous biomarker analysis in computational pathology.

Loss of the epithelial marker CDX1 predicts poor prognosis in early-stage CRC patients

BackgroundWe have previously shown that non-curative chemotherapy imposes fetal conversion and high metastatic capacity to cancer cells. From the set of genes differentially expressed in Chemotherapy Resistant Cells, we obtained a characteristic fetal intestinal cell signature that is present in a group of untreated tumors and is sufficient to predict patient prognosis. A feature of this fetal signature is the loss of CDX1. MethodsWe have analyzed transcriptomic data in public datasets and performed immunohistochemistry analysis of paraffin embedded tumor samples from two cohorts of colorectal cancer patients. ResultsWe demonstrated that low levels of CDX1 are sufficient to identify patients with poorest outcome at the early tumor stages II and III. Presence tumor areas that are negative for CDX1 staining in stage I cancers is associated with tumor relapse. ConclusionsOur results reveal the actual possibility of incorporating CDX1 immunostaining as a valuable biomarker for CRC patients.

DNA base oxidation in relation to TNM stages and chemotherapy treatment in colorectal cancer patients 2–9 months post-surgery

Accumulation of DNA damage is a critical feature of genomic instability, which is a hallmark of various cancers. The enzyme-modified comet assay is a recognized method to detect specific DNA lesions at the level of individual cells. In this cross-sectional investigation, we explore possible links between clinicopathological and treatment related factors, nutritional status, physical activity and function, and DNA damage in a cohort of colorectal cancer (CRC) patients with non-metastatic disease. Levels of DNA damage in peripheral mononuclear blood cells (PBMCs) assessed 2–9 months post-surgery, were compared across tumour stage (localized (stage I-II) vs. regional (stage III) disease), localization (colon vs. rectosigmoid/rectum cancer), and adjuvant chemotherapy usage, with the last dosage administrated 2–191 days prior to sampling. Associations between DNA damage and indicators of nutritional status, physical activity and function were also explored. In PBMCs, DNA base oxidation was higher in patients diagnosed with regional compared with localized tumours (P = 0.03), but no difference was seen for DNA strand breaks (P > 0.05). Number of days since last chemotherapy dosage was negatively associated with DNA base oxidation (P < 0.01), and patients recently receiving chemotherapy (<15 days before blood collection) had higher levels of DNA base oxidation than those not receiving chemotherapy (P = 0.03). In the chemotherapy group, higher fat mass (in kg and %) as well as lower physical activity were associated with greater DNA base oxidation (P < 0.05). In conclusion, DNA base oxidation measured with the enzyme-modified comet assay varies according to tumour and lifestyle related factors in CRC patients treated for non-metastatic disease.

The association of tumor-expressed REG4, SPINK4 and alpha-1 antitrypsin with cancer-associated thrombosis in colorectal cancer.

Novel biomarkers are needed to improve current imperfect risk prediction models for cancer-associated thrombosis (CAT). We recently identified an RNA-sequencing profile that associates with CAT in colorectal cancer (CRC) patients, with REG4, SPINK4, and SERPINA1 as the top-3 upregulated genes at mRNA level. In the current study, we investigated whether protein expression of REG4, SPINK4 and alpha-1 antitrypsin (A1AT, encoded by SERPINA1) in the tumor associated with CAT in an independent cohort of CRC patients. From 418 patients with resected CRC, 18 patients who developed CAT were age, sex, and tumor stage-matched to 18 CRC patients without CAT. Protein expression was detected by immunohistochemical staining and scored blindly by assessing the H-score (percentage positive cells*scoring intensity). The association with CAT was assessed by means of logistic regression, using patients with an H-score below 33 as reference group. The odds ratios (ORs) for developing CAT for patients with A1AThigh, REG4high, SPINK4high tumors were 3.5 (95%CI 0.8-14.5), 2.0 (95%CI 0.5-7.6) and 2.0 (95%CI 0.5-7.4) when compared to A1ATlow, REG4low, SPINK4low, respectively. The OR was increased to 24.0 (95%CI 1.1-505.1) when two proteins were combined (A1AThigh/REG4high). This nested case-control study shows that combined protein expression of A1AT and REG4 associate with CAT in patients with colorectal cancer. Therefore, REG4/A1AT are potential biomarkers to improve the identification of patients with CRC who may benefit from thromboprophylaxis.