Representativeness of Study Participants

Supplementary Material 5. Summary of patient characteristics (grouped by baseline ctDNA status).

Supplementary Material 4. Criteria of the pathological tumor regression grade (pTRG).

Supplementary Material 9. Univariate and multivariate analysis for poor responders to neoadjuvant chemotherapy and dynamic ctDNA satus: subgroup analysis between low-risk and recurred ctDNA positive groups.

Supplementary Material 7. Univariate and multivariate analysis for poor responders to neoadjuvant chemotherapy and dynamic ctDNA status.

Supplementary Material 2. The list of 769 genes in the NGS panel.

Supplementary Material 1. Details of the inclusion, exclusion, and withdrawal criteria.

Supplementary Material 3. Methods for Bioinformatical analysis

Supplementary Material 10. Univariate and multivariate analysis for poor responders to neoadjuvant chemotherapy and preoperative ctDNA status.

Supplementary Material 8. Univariate and multivariate analysis for poor responders to neoadjuvant chemotherapy and dynamic ctDNA status: subgroup analysis between low-risk and delayed/no clearance groups.

Supplementary Material 6. Distribution of dynamtic ctDNA status.

PURPOSE:High-risk locally advanced rectal cancer (LARC) carries a substantial risk of distant recurrence, which limits disease-free survival (DFS). We compared total neoadjuvant therapy (TNT) integrating long-course radiotherapy (LCRT) with uninterrupted doublet chemotherapy (doublet-LC TNT) versus conventional neoadjuvant chemoradiotherapy (nCRT). METHODS:In this multicenter, randomized, phase III trial, patients with stage II/III LARC and at least 1 high-risk feature (cT4a-b, cN2, mesorectal fascia involvement, or cT3c-d with extramural vascular invasion) were enrolled. Patients were assigned to doublet-LC TNT (induction, concurrent, and consolidation capecitabine plus oxaliplatin with LCRT) before surgery or nCRT (capecitabine with LCRT) followed by surgery and adjuvant chemotherapy. The primary end point was DFS (ClinicalTrials.gov identifier: NCT03177382). RESULTS:Between June 6, 2017, and December 27, 2023, 458 patients were randomly assigned to doublet-LC TNT (n = 232) or nCRT (n = 226). At a median follow-up of 51 months, doublet-LC TNT improved 3-year DFS (74.8% v 66.0%; hazard ratio [HR], 0.674 [95% CI, 0.489 to 0.929]; P = .016). Metastasis-free survival (MFS; 77.7% v 67.6%; HR, 0.655 [95% CI, 0.469 to 0.915]) and pathologic complete response rates (pCR; 26.37% v 9.80%; P < .001) were higher with doublet-LC TNT, whereas locoregional failure remained low and comparable (6.03% v 6.19%; P = .943). Although grade ≥3 adverse events during the neoadjuvant phase were more frequent with doublet-LC TNT (27.59% v 8.56%; P < .001), severe toxicities during the entire treatment course (28.02% v 24.32%; P = .371) and major postoperative complications (3.98% v 2.94%; P = .567) were comparable. CONCLUSION:Compared with conventional nCRT, doublet-LC TNT improved DFS, MFS, and pCR rates with manageable toxicity. These findings support this intensified, doublet-based regimen as a standard option within the modern TNT paradigm. Further comparative studies are warranted to evaluate these results against other short-course radiotherapy‑based or nondoublet-concurrent TNT regimens.

ObjectiveColorectal cancer (CRC) ranks among the most prevalent malignancies, with increasing incidence and mortality rates presenting a substantial public health challenge. While insulin growth factor like family member 1 (IGFL1) has been implicated in the regulation of various diseases, its functional role in colorectal cancer remains poorly characterised. This study therefore aims to elucidate the involvement of IGFL1 in CRC through an integrated approach combining bioinformatics analysis and experimental validation.MethodsThe expression of IGFL1 in CRC and its association with clinicopathological features, diagnostic relevance, and patient prognosis were evaluated using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Immunohistochemistry was performed to validate IGFL1 protein expression in CRC tissue samples. Immune cell infiltration levels and immune microenvironment scores related to IGFL1 expression were analysed using multiple computational algorithms, including CIBERSORT, ssGSEA, ESTIMATE, EPIC, MCP-counter, quanTIseq, TIMER, xCell, and CIBERSOR. Furthermore, IGFL1 expression patterns across distinct cellular subpopulations were examined using single-cell RNA sequencing datasets from the Tumor Immune Single-cell Hub (TISCH) database. The TIDE algorithm was applied to assess the potential clinical efficacy of immunotherapy in groups with high versus low IGFL1 expression, in addition to investigating correlations between IGFL1 expression and immune checkpoint markers. Genetic alterations of IGFL1 were analysed via cBioPortal, while the TIMER2.0 database was used to explore relationships between IGFL1 expression and key gene mutations in CRC. The CTRP and GDSC databases were employed to investigate associations between IGFL1 expression and sensitivity to conventional chemotherapy drugs. Finally, phenotypic validation and mechanistic studies were conducted using the CRC cell lines SW620 and HCT116.ResultsOur study demonstrates that IGFL1 expression is significantly up-regulated in CRC and possesses considerable diagnostic value. Elevated IGFL1 levels were consistently observed in clinical specimens, where high expression correlated with adverse clinicopathological features, poorer prognosis, and mutations in key oncogenes. Within the tumour microenvironment, IGFL1 appears to play a critical role in modulating the infiltration of diverse immune cell populations. Furthermore, IGFL1 expression influences both immunotherapy responsiveness and chemotherapy sensitivity in CRC patients. Genetic knockdown of IGFL1 markedly attenuated the malignant phenotype of CRC cells. RNA-sequencing analysis revealed that IGFL1 is closely linked to cholesterol metabolism, autophagy pathways, and ATP hydrolysis activity. Functionally, inhibition of IGFL1 enhanced lipophagy in CRC cells. Collectively, these findings indicate that IGFL1 promotes CRC pathogenesis and progression through the suppression of lipophagy.ConclusionsIGFL1 exhibits oncogenic properties in colorectal cancer and may represent a potential therapeutic target.

PURPOSE:Neoadjuvant chemotherapy (NCT) has been accepted as the standard management for locally advanced rectal cancer (LARC) without high-risk factors. However, many patients experience poor pathologic response, necessitating early-prediction tools. We investigated dynamic circulating tumor DNA (ctDNA) analysis for early response monitoring in patients with LARC undergoing NCT. EXPERIMENTAL DESIGN:In this biomarker substudy of the multicenter randomized COPEC trial, 153 patients with low-/intermediate-risk LARC were enrolled. Plasma samples (n = 526) were collected at baseline and after each cycle of NCT. ctDNA was analyzed via tumor-informed sequencing. Patients were classified by dynamic status into high-risk (delayed/no clearance and recurred positive) and low-risk (early clearance and persistent negative) groups. Poor response was defined as pathologic tumor regression grade (pTRG) 3 or distant metastasis. The association between ctDNA status and responses was analyzed. RESULTS:No patient with high-risk ctDNA dynamics achieved a major pathologic response (pTRG 0-1). The poor response rate was 59.4% in the high-risk group versus 12.4% in the low-risk group (P < 0.001). High-risk dynamic ctDNA status was a strong independent predictor of poor response (OR = 11.69; 95% confidence interval, 5-27.25; P < 0.001). Both delayed/no clearance (OR = 12.64; P < 0.001) and recurred positivity (OR = 8.91; P < 0.001) were significant risk factors. A single preoperative ctDNA-positive result also predicted poor response (OR = 11.27; P < 0.001). CONCLUSIONS:Dynamic ctDNA monitoring identifies patients with LARC at high risk for NCT failure as early as two cycles into treatment, which can form the basis for an adaptive trial design and eventual personalization of therapy selection.

Background Immune checkpoint inhibitors have improved the survival of colorectal cancer (CRC) patients. Patients who respond well to preoperative immunotherapy and achieve a complete response may potentially avoid surgery. Leveraging whole slide images (WSIs) from endoscopic biopsies, this study aims to construct a predictive model using a deep learning approach to identify potential pathological complete response (pCR) in CRC patients undergoing preoperative immunotherapy. Methods CRC patients who received preoperative immunotherapy from West China Hospital, Sichuan University were retrospectively included and randomized into the training and the validation sets at a 3:1 ratio. Using pathological outcomes as the reference standard, a predictive model was developed based on the H&E-stained WSIs of endoscopic biopsy, incorporating the Swin Transformer architecture and a self-attention mechanism augmented by convolutional neural networks (CNNs). And the Clustering-constrained Attention Multiple Instance Learning (CLAM) framework was used to optimize pathological image analysis. Through attention-based visualization, the top 5 % of patches most influential for determining tumor response to preoperative immunotherapy were identified. Results The pCR rate was 30.6 % (22/72) in the training cohort and 30.4 % (7/23) in the validation cohort. The predictive model yielded an area under curve (AUC) of 0.830. Attention-based visualization in the validation set revealed that among the top 5 % of patches contributing to the prediction, 62.25 % were tumor patches and 37.75 % were non-tumor patches. Conclusions A deep learning-based pathomics model, which distinctly focuses on both tumor and non-tumor regions, has the potential to predict tumor response to preoperative immunotherapy in CRC patients.

Visceral white-nodules disease (VWND) causes significant economic losses in L. crocea farming. Selection and breeding for disease resistance is a useful tool in preventing or reducing disease outbreaks, and genomic selection (GS) is an effective method that uses genome-wide markers and phenotype information to predict genomic estimated breeding values (GEBVs) of parent fish. In this study, we evaluated the effect of the genomic selection with 600 L. crocea challenged with Pseudomonas plecoglossicida based on binary survival (BS) and time to death (DT) phenotypes as well as 10,586,121 high quality SNPs. Four statistical models (BayesA, BayesB, BayesC pi, and GBLUP) were used to explore the feasibility of genomic selection for genetic improvement of VWND in L. crocea. The accuracy of the different GS methods was assessed using a five-fold cross-validation scheme with different schemes, including SNP densities, sample sizes, and case-control ratio. The results showed that the heritability estimates ranged from 0.46 to 0.69; the four models performed similarly in predicting the genomic estimated breeding value (GEBV) when the SNP density reached 50 K, and the prediction accuracy reached stability (0.22-0.32) and BayesB was more sensitive to decreasing SNP density than the other three models. We also found that the case-control ratio had a significant impact on the design of the case-control experiment, and the prediction accuracy of GEBV was highest when the number of cases was equal to the control ratio (0.24-0.27). We systemically assessed the accuracy of GEBV and explored the potential of GS in improving resistance to VWND in L. crocea, which will lay the foundation for optimizing experiment design for GS of VWND in L. crocea.

3535 Background: Multiple large-scale prospective studies have confirmed that neoadjuvant chemotherapy (NCT) alone can achieve optimal distant and local control in locally advanced rectal cancers (LARC) without high risks. However, due to the potentially lower overall response rate compared to chemo-radiotherapy, it is rational to discontinue ineffective NCT in chemo-resistant patients. In our phase II study, we applied 4 cycles of Capox in LARC patients with low to intermediate risks, observing a considerable patho-clinical response rate and an accuracy of 0.89 in predicting non-responders using MRI features after two cycles of Capox. To determine the optimal number of NCT cycles and prevent unnecessary prolonged treatment, we conducted this phase III trial to assess the non-inferiority of two cycles of NCT compared to four cycles with respect to the final pathological tumor response grade (pTRG) of 3. Methods: This multicenter, non-inferiority, phase III randomized controlled trial was conducted at 14 centers across China. Eligible patients with low- to intermediate-risk stage II/III rectal cancer were randomized to receive either 2 or 4 cycles of CAPOX, followed by total mesorectal excision (TME) surgery. The primary endpoint was the proportion of patients with a poor pathological response to NCT (pTRG 3). Secondary outcomes included the accuracy of MRI in predicting tumor response, treatment-related adverse events, and 3-year survival outcomes. Results: From August 6, 2021, to May 27, 2024, a total of 573 patients were enrolled. Ultimately, 527 patients (2-cycle group, 266 vs. 4-cycle group, 261) were included in the primary analysis. The pTRG 3 rate in the 2-cycle group (27.8%, 74/266) was non-inferior to that in the 4-cycle group (26.4%, 69/261, p = 0.722). Better lymph node response was observed in the 4-cycle group (pN negative: 83.1%, 217/261 vs. 72.5%, 193/266, p = 0.011). The incidence of major adverse events (grade ≥3, according to CTCAE 5.0) was comparable between the two groups (37.9% vs. 44.8%, p = 0.094). A tumor longitudinal length reduction rate (TLLR) of less than 30% on MRI predicted pathological poor responders with a high positive predictive value of 0.918 after two cycles of NCT in the two-cycle group, 0.864 after two cycles of NCT in the four-cycle group, and 0.841 after four cycles of NCT in the four-cycle group. Conclusions: Four cycles of NCT do not result in a greater reduction in poor pathological response compared to two cycles, highlighting the importance of early response assessment. MRI evaluation of tumor response after 2 cycles predict the final pathological results with considerable accuracy. These findings lay the groundwork for future studies exploring response-guided treatment approaches in rectal cancer. Clinical trial information: NCT04922853 .

Deep phenotyping can enhance the power of genetic analysis such as genome-wide association study (GWAS), but recurrence of missing phenotypes compromises the potentials of such resources. Although many phenotypic imputation methods have been developed, accurate imputation for millions of individuals still remains extremely challenging. In the present study, leveraging efficient machine learning (ML)-based algorithms, we developed a novel multi-phenotype imputation method based on mixed fast random forest (PIXANT), which is several orders of magnitude in runtime and computer memory usage than the state-of-the-art methods when applied to the UK Biobank (UKB) data and scalable to cohorts with millions of individuals. Our simulations with hundreds of individuals showed that PIXANT was superior to or comparable to the most advanced methods available in terms of accuracy. We also applied PIXANT to impute 425 phenotypes for the UKB data of 277,301 unrelated white British citizens and performed GWAS on imputed phenotypes, and identified a 15.6% more GWAS loci than before imputation (8,710 vs 7,355). Due to the increased statistical power of GWAS, a certain proportion of novel genes were rediscovered, such as RNF220 , SCN10A and RGS6 that affect heart rate, demonstrating the use of imputed phenotype data in a large cohort to discover novel genes for complex traits.

BackgroundGallbladder neuroendocrine carcinoma (GB-NEC) is an exceptionally rare and highly aggressive malignancy, accounting for only 0.2% of gastrointestinal neuroendocrine neoplasms and 2.3% of gallbladder cancers. Due to its nonspecific clinical presentation and diagnostic challenges, most patients present with advanced disease at diagnosis, resulting in poor prognosis with median survival typically under 12 months. This study aimed to analyze clinicopathological characteristics and identify independent prognostic factors in GB-NEC patients.MethodsWe conducted a retrospective cohort study of 31 histologically confirmed GB-NEC cases treated at a tertiary referral center between 2015-2024. Comprehensive data including demographic characteristics, tumor markers, pathological features (differentiation, Ki-67 index, invasion patterns), treatment modalities (surgical approach, chemotherapy regimens), and survival outcomes were analyzed. Statistical methods included Kaplan-Meier survival analysis, log-rank tests, and multivariate Cox proportional hazards regression models.ResultsThe cohort demonstrated median progression-free survival of 12 months and overall survival of 36 months. Multivariate analysis identified three independent poor prognostic factors: elevated alpha-fetoprotein (AFP) (HR 1.01, p=0.034), mixed neuroendocrine-non-neuroendocrine histology (HR 3.90, p=0.042), and delayed adjuvant chemotherapy (HR 15.62, p=0.006).DiscussionThis study establishes AFP elevation, mixed histology, and delayed chemotherapy as critical determinants of poor prognosis in GB-NEC. Our findings emphasize the importance of early diagnosis, aggressive surgical resection, and timely initiation of platinum-based adjuvant therapy.

BACKGROUND:Scant data are available on heterogenous staining of mismatch repair protein in colorectal cancer. OBJECTIVE:This study aimed to improve insights into clinicopathologic features and prognosis of colorectal cancer harboring heterogenous mismatch repair protein staining. DESIGN:A single-center retrospective observational study. SETTING:This study was conducted in a tertiary referral center in China between 2014 and 2018. PATIENTS:Patients with colorectal cancers with heterogenous staining of mismatch repair protein were included. MAIN OUTCOME MEASURES:Clinicopathologic and molecular features and survival outcomes were analyzed. RESULTS:A total of 151 of 6721 colorectal cancers (2.2%) exhibited heterogenous staining for at least 1 mismatch repair protein, with intraglandular heterogeneity being the most common pattern (89.4%). Heterogenous mutL homolog 1 staining was significantly associated with distant metastasis (p = 0.03), whereas heterogenous mutS homolog 2 staining was associated with left-sided (p = 0.03) and earlier pT stage tumors (p = 0.02). The rates of microsatellite instability-high, K-ras and BRAF mutation were 12.6%, 47.3%, and 3.4%, respectively. Microsatellite instability-high was significantly associated with higher intraglandular mutS homolog 6 heterogeneity frequency (p < 0.001) and decreased mutS homolog 6 expression level (<27.5%, p = 0.01). BRAF mutation was associated with the coexistence of intraglandular and clonal heterogeneity (p = 0.003) and decreased PMS1 homolog 2 expression level (p = 0.01). Multivariable analysis revealed that progression-free survival was significantly associated with tumor stage (p = 0.003), stroma fraction (p = 0.004), and heterogenous PMS1 homolog 2 staining (p = 0.02). Overall survival was linked to tumor stage (p = 0.006) and BRAF mutation (p = 0.01). LIMITATIONS:The limitations of this study include the absence of testing for mutL homolog 1 promoter methylation and mismatch repair gene mutations, its retrospective design, and insufficient data related to direct comparison with deficient mismatch repair and proficient mismatch repair colorectal cancer. CONCLUSIONS:Heterogenous mismatch repair protein staining in colorectal cancer exhibits distinct associations with tumor location, stage, microsatellite instability, BRAF mutation, and prognosis. It is recommended to report mutS homolog 6 heterogeneity as it may indicate microsatellite instability-high.