Junjie Peng

Organoids are innovative three‐dimensional (3D) cellular constructs, offering a unique platform to replicate the architectural and functional complexity of organs and tissues. In oncology, the tumor microenvironment (TME) dictates tumor evolution and therapeutic resistance. Consequently, therapies targeting TME components have emerged as a burgeoning frontier in cancer treatment. However, accurately recapitulating the dynamic, multicellular crosstalk of TME remains a significant hurdle for clinical translation. This review encapsulates the spectrum of current organoid coculture methodologies, ranging from direct coculture and air–liquid interface to advanced microfluidics and 3D bioprinting. These models not only deepen our understanding of the fundamental mechanisms at play in cancer but also evaluate emerging therapeutic modalities, such as antibody–drug conjugates and immunotherapy. By closely mimicking the in vivo tumor milieu, organoid cocultures enhance our ability to predict therapeutic outcomes and pave the way for the development of precision medicine approaches, thereby propelling forward the frontiers of oncology. This review aims to provide a comprehensive overview of organoid coculture models, spanning from construction methodologies to clinical applications. We envision this work serving as a definitive guide for the field, ultimately accelerating the transition from theoretical research to clinical practice.

Background: Microsatellite stability (MSS) colorectal cancers (CRCs) have a limited response to immune checkpoint inhibitors (ICIs) compared to microsatellite instability-high (MSI-H) CRCs. Nevertheless, previous studies have shown that some MSS CRCs are sensitive to ICIs, although established criteria for treatment justification are still lacking. Objective: This study aimed to test the tumor-infiltrating lymphocyte (TIL) features of MSS and develop a novel computational tool for the similarity prediction between MSS and MSI-H status in patients with CRC based on multiple factors. Methods: We collected and analyzed data from 188 patients with CRC, including MSI status, immune cell distributions, clinical features, and gene mutations, using statistical methods and Cox regression. An ensemble machine learning–based MSI-H score was developed using stacked extreme gradient boosting classifiers to quantify the similarity of patient data to MSI-H data based on immune cell distributions, clinical features, and gene mutations. The model was robust and could address missing input data for immune cell distributions and gene mutations. Results: The scorer performed well (mean Cohen κ of 0.40, SD 0.05, over 10 random seeds) in identifying MSI-H–like MSS samples with TIL distributions similar to genuine MSI-H CRCs. No significant difference was observed between the TIL features of MSI-H–like MSS CRCs and MSI-H CRCs. The disparity between MSI-H–like MSS CRCs and MSS CRCs potentially lies in the T regulatory cells (P=.09) and macrophage (P=.16) populations within the tumor stromal region. Conclusions: Some patients with MSS CRC presented similar immune cell distributions with high immunoactivity compared to patients with MSI-H CRC. The MSI-H score serves as a metric to quantify the similarity of MSS CRCs to MSI-H CRCs and presents a promising avenue for more personalized and effective cancer immunotherapy treatment, offering a clinical reference for potential ICI targets in MSS CRCs.

Background: Size and number of lymph nodes (LNs) were reported to be associated with the prognosis of stage II colorectal cancer (CRC). The purpose of this study was to determine the prognostic role of the size of LNs (SLNs) measured by computer tomography (CT) and the number of retrieved LNs (NLNs) in the relapse-free survival (RFS) and overall survival (OS) among stage II CRC patients. Methods: Consecutive patients diagnosed with stage II CRC at Fudan University Shanghai Cancer Center (FUSCC) from January 2011 to December 2015 were reviewed, and 351 patients were randomly divided into two cohorts for cross-validation. The optimal cut-off values were obtained using X-tile program. Kaplan-Meier curves and Cox regression analyses were conducted for the two cohorts. Results: Data from 351 stage II CRC patients were analyzed. The cut-off values for SLNs and NLNs were 5.8 mm and 22, respectively, determined by the X-tile in the training cohort. In the validation cohort, Kaplan-Meier curves demonstrated SLNs (P = 0.0034) and NLNs (P = 0.0451) were positively correlated with RFS but not with OS. The median follow-up time in the training cohort and the validation cohort were 60.8 months and 61.0 months respectively. Univariate and multivariate analysis revealed that both SLNs (training cohort: Hazard Ratio (HR) = 2.361, 95% Confidence interval (CI): 1.044–5.338, P = 0.039; validation cohort: HR = 2.979, 95%CI: 1.435–5.184, P = 0.003) and NLNs (training cohort: HR = 0.335, 95%CI: 0.113–0.994, P = 0.049; validation cohort: HR = 0.375, 95%CI: 0.156-0.900, P = 0.021) were independent prognostic factors for RFS whereas not for OS. Conclusion: SLNs and NLNs are independent prognostic factors for patients with stage II CRC. Patients with SLNs > 5.8 mm and NLNs ≤ 22 are apt to have higher risk of recurrence.

Introduction: Most advanced colorectal cancers are aggressive, and there is a lack of effective methods for selecting appropriate anticancer regimens. Patient-derived organoids (PDOs) have emerged as preclinical platforms for modeling clinical responses to cancer therapy.Methods: In this study, we successfully constructed a living biobank with 42 organoids derived from primary and metastatic lesions of metastatic colorectal cancer patients. Tumor tissue was obtained from patients undergoing surgical resection of the primary or metastatic lesion and then used to establish PDOs. Immunohistochemistry (IHC) and drug sensitivity assays were performed to analyze the properties of these organoids.Results: The mCRC organoids were successfully established with an 80% success rate. The PDOs maintained the genetic and phenotypic heterogeneity of their parental tumors. The IC50 values of5-fluorouracil (5-FU), oxaliplatin, and irinotecan (CPT11) were determined for mCRC organoids using drug sensitivity assays. The in vitro chemosensitivity data revealed the potential value of PDOs for clinical applications in predicting chemotherapy response and clinical outcomes in mCRC patients.Discussion: In summary, the PDO model is an effective platform for in vitro assessment of patient-specific drug sensitivity, which can guide personalized treatment decisions for patients with end-stage CRC.

Background: To study the pattern and treatment outcome of rectal cancer (RC) with concurrent locoregional recurrence (LR) and distant metastasis (DM) after total mesorectal excision (TME) and to identify patient-, disease-, and treatment-related factors associated with differences in prognosis after concurrent LR and DM. Methods: RC patients who were diagnosed with concurrent LR and DM after TME from May 2015 to June 2019 were included in our study. All patients received single or multiple treatment modalities under the guidance of multidisciplinary team (MDT) of colorectal cancer in Fudan University Shanghai Cancer Center. The prognostic value of various clinicopathological factors for survival were calculated by Kaplan–Meier curves and Cox regression analyses. Results: A total of 74 RC patients with concurrent LR and DM who had undergone TME with a median follow-up of 27 months were eligible for analysis. The median survival of the included patients was 34 months, and 30 patients (41%) died. Fifty-nine patients (80%) underwent comprehensive treatments. Patients with oligometastatic disease (OMD) achieved no evidence of disease (NED) status more frequently than those with multiple metastases (P = 0.003). In the univariate analysis, patients achieving NED, diagnosed with OMD and five or less peritoneal metastases tended to have longer survival after LR and DM diagnosis (P < 0.05). In the multivariate analysis, attaining NED status was the only independent factor for survival (hazard ratio (HR), 2.419; P = 0.032). Survival after concurrent LR and DM in the non-NED group was significantly shorter than that in the NED group (median survival, 32 vs. 46 months; HR, 2.7; P = 0.014). Conclusions: The pattern and treatment outcome of RC with concurrent LR and DM after TME has changed with the development of multiple treatment modalities. Although the prognosis remains poor, pursuing NED status through comprehensive treatments may improve the survival of RC patients with concurrent LR and DM after TME.

Early detection can benefit cancer patients with more effective treatments and better prognosis, but existing early screening tests are limited, especially for multi-cancer detection. This study investigated the most prevalent and lethal cancer types, including primary liver cancer (PLC), colorectal adenocarcinoma (CRC), and lung adenocarcinoma (LUAD). Leveraging the emerging cell-free DNA (cfDNA) fragmentomics, we developed a robust machine learning model for multi-cancer early detection. 1,214 participants, including 381 PLC, 298 CRC, 292 LUAD patients, and 243 healthy volunteers, were enrolled. The majority of patients (N = 971) were at early stages (stage 0, N = 34; stage I, N = 799). The participants were randomly divided into a training cohort and a test cohort in a 1:1 ratio while maintaining the ratio for the major histology subtypes. An ensemble stacked machine learning approach was developed using multiple plasma cfDNA fragmentomic features. The model was trained solely in the training cohort and then evaluated in the test cohort. Our model showed an Area Under the Curve (AUC) of 0.983 for differentiating cancer patients from healthy individuals. At 95.0% specificity, the sensitivity of detecting all cancer reached 95.5%, while 100%, 94.6%, and 90.4% for PLC, CRC, and LUAD, individually. The cancer origin model demonstrated an overall 93.1% accuracy for predicting cancer origin in the test cohort (97.4%, 94.3%, and 85.6% for PLC, CRC, and LUAD, respectively). Our model sensitivity is consistently high for early-stage and small-size tumors. Furthermore, its detection and origin classification power remained superior when reducing sequencing depth to 1× (cancer detection: ≥ 91.5% sensitivity at 95.0% specificity; cancer origin: ≥ 91.6% accuracy). In conclusion, we have incorporated plasma cfDNA fragmentomics into the ensemble stacked model and established an ultrasensitive assay for multi-cancer early detection, shedding light on developing cancer early screening in clinical practice.

Purpose Colorectal cancer (CRC) is one of the leading causes of cancer-related death worldwide. After resection, patients need extensive follow-up to detect asymptomatic recurrences as early as possible to obtain optimal treatment. This study evaluated the prognostic value of circulating tumor DNA (ctDNA) for CRC recurrence. Methods Two investigators independently conducted a systematic literature search of peer-reviewed studies that investigated the prognostic value of ctDNA in CRC. Fixed effects or random effects models were applied for all analyses based on the assessment of heterogeneity. Results A total of 189 studies were initially retrieved from all databases; ultimately, eight studies with 879 CRC patients were included in this analysis. The pooled median recurrence-free survival was 11.36 months for ctDNA-positive patients. Meta-analysis of hazard ratio (HR) suggested that postoperative ctDNA-positive patients were more likely to experience cancer recurrence than ctDNA-negative patients (pooled HR: 5.41; 95% confidence interval (CI): 2.37–8.45). Conclusions Successive monitoring of ctDNA status and follow-up with postoperative computed tomography (CT)/magnetic resonance imaging (MRI) are useful tools to detect early recurrence in postoperative ctDNA-positive patients.

Objective To study the pattern and treatment outcome of rectal cancer (RC) with concurrent locoregional recurrence (LR) and distant metastasis (DM) after total mesorectal excision (TME) and to identify patient-, disease-, and treatment-related factors associated with differences in prognosis after concurrent LR and DM. Methods RC patients who were diagnosed with concurrent LR and DM after TME from May 2015 to June 2019 were included in our study. All patients received single or multiple treatment modalities under the guidance of multidisciplinary team (MDT) of colorectal cancer in Fudan University Shanghai Cancer Center.The prognostic of various clinicopathological factors for survival calculated by Kaplan-Meier curves and Cox regression analysis. Results A total of 74 RC patients with conurrent LR and DM after TME were eligible for analysis with median follow-up of 27 months. Median survival of patients included was 34 months and 30 patients (41%) died. 59 patients (80%) underwent comprehensive treatments. Patients with oligometastatic disease (OMD) achieved no evidence of disease (NED) status more frequently than those with multiple metastases (P = 0.003). In the univariate analysis, patients achieving NED, diagnosed with OMD and five or less peritoneal metastases tended to have longer survival after LR and DM diagnosis (P < 0.05). In the multivariate analysis, attaining NED status was the only independent factor for survival (hazard ratio (HR), 2.419; P = 0.032). Survival after concurrent LR and DM in the non-NED group was significantly shorter than in the NED group (median survival, 32 vs 46 months; HR, 2.7; P = 0.014). Conclusion The pattern and treatment outcome of RC with concurrent LR and DM after TME has changed with development of multiple treatment modalities. Although the prognosis is still poor, pursuing NED status through comprehensive treatments may improve the survival of RC patients with concurrent LR and DM after TME.