Targeting AKR1B10 by drug repurposing with epalrestat overcomes chemoresistance in non-small cell lung cancer patient-derived tumor organoids.

PURPOSE: Systemic treatments given to non-small cell lung cancer (NSCLC) patients are often ineffective due to drug resistance. In the present study, we investigated patient-derived tumor organoids (PDTOs) and matched tumor tissues from surgically treated NSCLC patients to identify drug repurposing targets to overcome resistance towards standard-of-care platinum-based doublet chemotherapy. EXPERIMENTAL DESIGN: PDTOs were established from ten prospectively enrolled non-metastatic NSCLC patients from resected tumors. PDTOs were compared with matched tumor tissues by histopathology/immunohistochemistry, whole exome and transcriptome sequencing. PDTO growths and drug responses were determined by measuring 3D tumoroid volumes, cell viability, and proliferation/apoptosis. Differential gene expression analysis identified drug-repurposing targets. Validations were performed with internal/external NSCLC patient data sets. NSCLC cell lines were used for aldo-keto reductase 1B10 (AKR1B10) knockdown studies and xenograft models to determine the intratumoral bioavailability of epalrestat. RESULTS: PDTOs retained histomorphology and pathological biomarker expression, mutational/transcriptomic signatures, and cellular heterogeneity of the matched tumor tissues. Five (50%) PDTOs were chemoresistant towards carboplatin/paclitaxel. Chemoresistant PDTOs and matched tumor tissues demonstrated overexpression of AKR1B10. Epalrestat, an orally available AKR1B10 inhibitor in clinical use for diabetic polyneuropathy, was repurposed to overcome chemoresistance of PDTOs. In vivo efficacy of epalrestat to overcome drug resistance corresponded to intratumoral epalrestat levels. CONCLUSIONS: PDTOs are efficient preclinical models recapitulating the tumor characteristics and are suitable for drug testing. AKR1B10 can be targeted by repurposing epalrestat to overcome chemoresistance in NSCLC. Epalrestat has the potential to advance to clinical trials in drug-resistant NSCLC patients due to favorable toxicity, pharmacological profile, and bioavailability.

Identifying gene expression programs in single-cell RNA-seq data using linear correlation explanation.

OBJECTIVE: Gene expression analysis through single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of gene regulation in diverse cell types, tissues, and organisms. While existing methods primarily focus on identifying cell type-specific gene expression programs (GEPs), the characterization of GEPs associated with biological processes and stimuli responses remains limited. In this study, we aim to infer biologically meaningful GEPs that are associated with both cellular phenotypes and activity programs directly from scRNA-seq data. METHODS: We applied linear CorEx, a machine-learning-based approach, to infer GEPs by grouping genes based on total correlation optimization function in simulated and real-world scRNA-seq datasets. Additionally, we utilized a transfer learning approach to project CorEx-inferred GEPs to other scRNA-seq datasets. RESULTS: By leveraging total correlation optimization, linear CorEx groups genes and demonstrates superior performance in identifying cell types and activity programs compared to similar methods using simulated data. Furthermore, we apply this same approach to real-world scRNA-seq data from the mouse dentate gyrus and embryonic colon development, uncovering biologically relevant GEPs related to cell types, developmental ages, and cell cycle programs. We also demonstrate the potential for transfer learning by evaluating similar datasets, showcasing the cross-species sensitivity of linear CorEx. CONCLUSION: Our findings validate linear CorEx as a valuable tool for comprehensively analyzing complex signals in scRNA-seq data, leading to deeper insights into gene expression dynamics, cellular heterogeneity, and regulatory mechanisms.

Colorectal Cancer-Associated Myofibroblasts Exhibit Enhanced Angiogenin Expression and Signaling via the PLXNB2 Receptor.

INTRODUCTION: Dynamic cell-cell interactions shape the tumor microenvironment to regulate tumor growth and invasiveness. Myofibroblasts are gastrointestinal stromal cells that are upregulated in the setting of colorectal cancer (CRC) and may play an important role in tumor-stromal cell communication. Angiogenin is a 14-kDa ribonuclease that regulates myofibroblast function and has been implicated in myofibroblast-CRC cell communication in mouse models. However, its role in human patients has not been well established. METHODS: Open access, annotated single-cell RNA sequencing data of paired normal human colon and CRC tissue were available in the National Center for Biotechnology Information Gene Expression Omnibus Database. We supplemented and verified these data by analyzing scRNA-seq data from an independent set of paired normal human colon and CRC tissue. CellChat was used to quantitatively infer biologically meaningful cell-cell communication networks from scRNA-seq data. PLXNB2 and α-2 actin (ACTA2) are cell surface angiogenin receptors that regulate angiogenin signaling. Ligand-receptor interactions involving angiogenin, PLXNB2, and ACTA2 were analyzed between cell populations in each sample. RESULTS: We found no difference in overall angiogenin expression comparing normal colon and CRC tissue. In normal colon tissue, myofibroblasts do not express angiogenin or the PLXNB2 receptor. In the presence of CRC, there was a striking increase in the number of myofibroblast cells within the surrounding stroma. CRC-associated myofibroblasts were characterized by a significant upregulation of both angiogenin and PLXNB2 receptor expression (P < 0.05), while no difference was seen in ACTA2. CRC cells not only use angiogenin for autocrine signaling but also communicate with myofibroblasts via the PLXNB2 receptor. CONCLUSIONS: Compared to normal human colon tissue, CRC tissue is associated with an enrichment of myofibroblasts that exhibit upregulated expression of angiogenin and the angiogenin receptor PLXNB2. CRC cells engage in autocrine signaling via angiogenin and paracrine signaling with myofibroblasts via PLXNB2. Angiogenin appears to be directly involved in tumor-stromal cell communication in human CRC tissue and may play an important role in disease progression.

TBX21 Methylation as a Potential Regulator of Immune Suppression in CMS1 Subtype Colorectal Cancer.

Cytotoxic T lymphocyte (CTL) infiltration is associated with survival, recurrence, and therapeutic response in colorectal cancer (CRC). Immune checkpoint inhibitor (ICI) therapy, which requires CTLs for response, does not work for most CRC patients. Therefore, it is critical to improve our understanding of immune resistance in this disease. We utilized 2391 CRC patients and 7 omics datasets, integrating clinical and genomic data to determine how DNA methylation may impact survival and CTL function in CRC. Using comprehensive molecular subtype (CMS) 1 patients as reference, we found TBX21 to be the only gene with altered expression and methylation that was associated with CTL infiltration. We found that CMS1 patients with high TBX21 expression and low methylation had a significant survival advantage. To confirm the role of Tbx21 in CTL function, we utilized scRNAseq data, demonstrating the association of TBX21 with markers of enhanced CTL function. Further analysis using pathway enrichment found that the genes TBX21, MX1, and SP140 had altered expression and methylation, suggesting that the TP53/P53 pathway may modify TBX21 methylation to upregulate TBX21 expression. Together, this suggests that targeting epigenetic modification more specifically for therapy and patient stratification may provide improved outcomes in CRC.

Tumorigenic circulating tumor cells from xenograft mouse models of non-metastatic NSCLC patients reveal distinct single cell heterogeneity and drug responses.

BACKGROUND: Circulating tumor cells (CTCs) are liquid biopsies that represent micrometastatic disease and may offer unique insights into future recurrences in non-small cell lung cancer (NSCLC). Due to CTC rarity and limited stability, no stable CTC-derived xenograft (CDX) models have ever been generated from non-metastatic NSCLC patients directly. Alternative strategies are needed to molecularly characterize CTCs and means of potential future metastases in this potentially curable patient group. METHODS: Surgically resected NSCLC primary tumor tissues from non-metastatic patients were implanted subcutaneously in immunodeficient mice to establish primary tumor patient-derived xenograft (ptPDX) models. CTCs were isolated as liquid biopsies from the blood of ptPDX mice and re-implanted subcutaneously into naïve immunodeficient mice to generate liquid biopsy CTC-derived xenograft (CDX) tumor models. Single cell RNA sequencing was performed and validated in an external dataset of non-xenografted human NSCLC primary tumor and metastases tissues. Drug response testing in CDX models was performed with standard of care chemotherapy (carboplatin/paclitaxel). Blockade of MYC, which has a known role in drug resistance, was performed with a MYC/MAX dimerization inhibitor (10058-F4). RESULTS: Out of ten ptPDX, two (20%) stable liquid biopsy CDX mouse models were generated. Single cell RNA sequencing analysis revealed an additional regenerative alveolar epithelial type II (AT2)-like cell population in CDX tumors that was also identified in non-xenografted NSCLC patients' metastases tissues. Drug testing using these CDX models revealed different treatment responses to carboplatin/paclitaxel. MYC target genes and c-MYC protein were upregulated in the chemoresistant CDX model, while MYC/MAX dimerization blocking could overcome chemoresistance to carboplatin/paclitaxel. CONCLUSIONS: To overcome the lack of liquid biopsy CDX models from non-metastatic NSCLC patients, CDX models can be generated with CTCs from ptPDX models that were originally established from patients' primary tumors. Single cell analyses can identify distinct drug responses and cell heterogeneities in CDX tumors that can be validated in NSCLC metastases tissues. CDX models deserve further development and study to discover personalized strategies against micrometastases in non-metastatic NSCLC patients.

Current and Prospective Methods for Assessing Anti-Tumor Immunity in Colorectal Cancer.

Colorectal cancer (CRC) remains one of the deadliest malignancies worldwide despite recent progress in treatment strategies. Though immune checkpoint inhibition has proven effective for a number of other tumors, it offers benefits in only a small group of CRC patients with high microsatellite instability. In general, heterogenous cell groups in the tumor microenvironment are considered as the major barrier for unveiling the causes of low immune response. Therefore, deconvolution of cellular components in highly heterogeneous microenvironments is crucial for understanding the immune contexture of cancer. In this review, we assimilate current knowledge and recent studies examining anti-tumor immunity in CRC. We also discuss the utilization of novel immune contexture assessment methods that have not been used in CRC research to date.