Journal of gastrointestinal oncology最新文献

Background: In China, transarterial chemoembolization (TACE) and systemic therapy are the primary treatment for patients with advanced hepatocellular carcinoma (HCC). Hepatic arterial infusion chemotherapy (HAIC) is more effective than TACE in treating large HCC (largest diameter ≥7 cm) without macrovascular invasion or extrahepatic spread. Additionally, HAIC in combination with camrelizumab and apatinib has shown promising efficacy and safety in the Barcelona Clinic Liver Cancer stage C (BCLC-C) HCC. The efficacy and safety of the modality of HAIC followed by TACE combined with camrelizumab and apatinib for the treatment of large HCC remains unknown. We present the first case of long-term survival after short-course HAIC followed by TACE combined with camrelizumab and apatinib in large HCC.

Case description: In April 2020, a 50-year-old Chinese woman was diagnosed with BCLC-C HCC. Magnetic resonance imaging (MRI) showed intrahepatic lesions involving the right and left lobes, with a total lesion size of 19 cm × 9 cm. After 3 cycles of HAIC with oxaliplatin, fluorouracil, and leucovorin (HAIC-FOLFOX) plus camrelizumab and apatinib, followed by 2 cycles of TACE plus camrelizumab and apatinib, the efficacy was evaluated as a partial response (PR), with a total lesion size of 6.7 cm × 4.6 cm. The patient continued to take apatinib orally for 1.5 months after the last cycle of TACE but discontinued any antitumor therapy for financial reasons. Subsequent imaging consultation showed an efficacy evaluation of complete response (CR) per the modified Response Evaluation Criteria in Solid Tumors (mRECIST). The patient did not experience any serious adverse events during treatment. As of September 2024, the patient's progression-free survival (PFS) has reached 53 months.

Conclusions: The treatment modality of short-course HAIC followed by TACE combined with camrelizumab and apatinib for large HCC is safe and effective, and long-term survival may be expected in patients who achieve a CR.

Background: Progranulin (PGRN), also identified as Precursor cell-derived growth factor (PCDGF), is a glycoprotein that is expressed and released ubiquitously. PGRN is plays a crucial role in regulating cell proliferation, differentiation, and pathological pathways. PGRN overexpression has been noted in many cancers and plays an important role in wound healing. Surgery's impact on PGRN levels is unknown. The aim of this study was to assess the levels of plasma PGRN before during the first month after minimally invasive colorectal resection (MICR) for colorectal cancer (CRC) resection.

Methods: CRC patients who were enrolled in a data/plasma bank approved by an Institutional Review Board and underwent MICR for whom adequate plasma samples were available were studied. Blood samples were obtained before surgery and at different time intervals after the operation and late samples were grouped into 7-day blocks and considered as single time points. PGRN levels (pg/mL) were determined in duplicate via ELISA and reported as median and 95% confidence interval (95% CI) values. The paired t-test was used for statistical analysis.

Results: Preoperative and 1 or more late postoperative plasma sample were available for 93 MICR CRC patients. The distribution of cancer stages in the final analysis was: stage I accounted for 37% of cases, stage II for 27%, stage III for 32%, and stage IV for 4%. The median preoperative PGRN level was 50.69 pg/mL, 95% CI: 47.71-56.30, n=93. When compared to preoperative levels, significantly elevated (P<0.001) median levels (pg/mL) were noted on postoperative day (POD) 1 (64.78, 95% CI: 60.86-68.83, n=92), POD 3 (69.15, 95% CI: 66.43-74.32, n=85), POD 7-13 (63.93, 95% CI: 59.62-68.35, n=68), and POD 14-20 (68.19, 95% CI: 60.12-73.37, n=26), POD 21-27 (67.38, 95% CI: 60.30-76.65, n=20) and on POD 28-41 (75.13, 95% CI: 54.02-83.16, n=22; P<0.01).

Conclusions: Following surgery for CRC, plasma PGRN levels showed a significant increase compared to baseline levels, persisting for a duration of one month. This initial surge post-operation could potentially be attributed to the transient acute inflammatory response. The elevation observed in weeks 2 and 4 could potentially be attributed to the process of wound healing, as PGRN has been shown to enhance the accumulation of fibroblasts and facilitate angiogenesis within wounds. Additional investigation is warranted.

Background: PANoptosis is a cell death pathway involved in pyroptosis, apoptosis and necrosis, and plays a key role in the development of malignant tumors. However, the molecular signature of PANoptosis in colorectal cancer (CRC) prognosis has not been thoroughly explored. The present study aimed to develop a novel prognostic model based on PANoptosis-related genes in CRC.

Methods: We initially included transcriptome data of 404 CRC samples from The Cancer Genome Atlas (TCGA) cohort and identified differentially expressed genes related to PANoptosis. We then employed Cox, least absolute shrinkage and selection operator (LASSO) regression, and Random Forest methods to determine the prognostic value and constructed a PANoptosis prognostic model, followed by the validation on both internal (TCGA) and external datasets [Nanjing Colorectal Cancer (NJCRC) and Gene Expression Omnibus (GEO), n=635]. We performed immune infiltration analysis and gene set enrichment analysis to reveal biological processes and pathways against differential risk score. Ultimately, we carried out drug sensitivity analysis to predict the response of CRC patients to diverse treatment strategies.

Results: We constructed a predictive model based on four PANoptosis-related genes (TIMP1, CDKN2A, CAMK2B, and TLR3), with a high performance [area under the curve (AUC)_1-year =0.702, AUC_3-year =0.725, AUC_5-year =0.668] and being an independent prognostic factor in predicting the prognosis of CRC patients. Notably, colorectal tumor with high PANoptosis risk score performed higher levels of macrophage infiltration and immune scores, but a greater reduction of Tumor Microenvironment Score (TMEscore) and DNA replication. Particularly, patients in high-risk group exhibited higher sensitivity to fluorouracil, oxaliplatin and lapatinib compared to the low-risk group.

Conclusions: This study highlights the prognostic potential of PANoptosis-related features in CRC, demonstrating their role as key biomarkers significantly associated with patient survival and aiding in the identification of high-risk patients, thereby advancing immunotherapy approaches.

Background: Colonoscopy remains the predominant diagnostic modality for colorectal cancer (CRC), as the diagnostic performance of tumor markers in alone, particularly in the early stages of the disease, is limited. This study sought to develop a diagnostic model for CRC that integrated various laboratory parameters.

Methods: One hundred patients with CRC were assigned to an experimental group while 114 with benign colorectal diseases and 101 healthy individuals were assigned to a control group. The clinical and laboratory data, including the tumor markers such as carcinoembryonic antigen (CEA), glycan carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 242 (CA242), blood count parameters, blood biochemical parameters, and coagulation parameters, were collected for each participant. Three machine-learning models [multilayered perceptron (MLP), eXtreme Gradient Boosting (XGBoost), and random forest (RF)] were used to construct CRC diagnostic models. The performance of each model was evaluated based on its area under the curve (AUC), sensitivity, and specificity.

Results: There are 12 parameters: including CEA, CA19-9, CA242, absolute neutrophil value (NEUT), hemoglobin, the neutrophil/lymphocyte ratio, the platelet/lymphocyte ratio, alanine aminotransferase, alkaline phosphatase, aspartate aminotransferase, albumin, and prothrombin time, were selected to build the diagnostic model. For the validation set, the RF machine-learning model achieved the highest performance in identifying CRC [AUC: 0.902 (95% confidence interval: 0.812-0.989), accuracy: 0.803, sensitivity: 0.908, specificity: 0.772, positive predictive value: 0.664, negative predictive value: 0.890, and F1 score: 0.763]. The AUC, sensitivity, specificity, and Youden's index for the combined diagnosis of tumor markers CEA, CA19-9, and CA242 were 0.761, 0.486, 0.983, and 0.469, respectively. The RF diagnostic model showed better diagnostic efficacy than the combined diagnosis model of tumor markers CEA, CA19-9 and CA242.

Conclusions: The use of machine learning combined with multiple laboratory parameters effectively improved the diagnostic efficiency of CRC and provided more accurate results for clinical diagnosis.

Background: The occurrence of colorectal cancer (CRC) is increasing among young adults, but the etiology is still largely unknown. In addition to germline monogenetic variants also polygenic risk scores (PRS) have been proven to correctly estimate the risk of CRC.

Case description: We present a 24-year-old male with disseminated colon cancer who carried a germline duplication on chromosome 1 spanning 200 kb and covering CD101, TTF2, MIR942, TRIM45, and parts of PTGFRN and VTCN1. The duplication was located in tandem. A similar duplication was previously reported in a family with CRC among two brothers aged 52 and 61 years old at diagnosis. Particularly, MIR942 was an interesting finding as it is involved in the regulation of the Wnt signaling pathway. Disruption of the Wnt pathway is known to cause CRC. However, in our case the duplication did not segregate with disease in the family. Calculation of a PRS in our patient found an average PRS for CRC.

Conclusions: Our findings do not support that this duplication is a monogenetic cause of CRC, nor did a PRS point towards an increased risk in this 24-year-old male. Whether the duplication is a risk factor in combination with other genetic and non-genetic risk factors requires further studies.

Background: The incidence of elderly-onset pancreatic neuroendocrine carcinoma (PanNEC) is increasing. This study investigated independent risk factors affecting cancer-specific survival (CSS) and constructed a nomogram to predict CSS in patients with elderly-onset PanNEC.

Methods: PanNEC patients older than 50 years from the Surveillance, Epidemiology, and End Results database were retrospectively selected from 2010 to 2021 and were randomly divided into a training set and a validation set. Independent factors affecting CSS were selected by univariate and multivariate analyses. The nomogram was built using significant variables. The discrimination and calibration of the nomogram were evaluated by the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis.

Results: A total of 407 patients were selected and randomly assigned to a training set or a validation set at a 6:4 ratio. In the selected population, 227 individuals (55.8%) were male, 313 (76.9%) were white, with a mean age of 69.4 years. Among them, 318 individuals (78.1%) died due to the tumor, with a CSS time of 6 months. Multivariate Cox analysis showed that age [hazard ratio (HR): 1.56, 95% confidence interval (CI): 1.10-2.22, P=0.01], surgery (HR: 2.32, 95% CI: 1.27-4.23, P=0.006), chemotherapy (HR: 2.39, 95% CI: 1.68-3.38, P<0.001), tumor, nodes, and metastasis (TNM) stage (HR: 3.96, 95% CI: 1.19-13.19, P=0.03), and liver metastasis (HR: 1.75, 95% CI: 1.16-2.65, P=0.008) were independent risk factors that shortened CSS. The AUCs of the nomogram for the 6-month, 1-year, and 2-year CSS were 0.826, 0.791, and 0.8 in the training set and 0.848, 0.775, and 0.781 in the validation set, respectively. Calibration curves showed that the nomogram could accurately predict the 6-month, 1-year, and 2-year CSS in both datasets. Furthermore, decision curve analysis indicated that the nomogram had clinical benefits.

Conclusions: The nomogram for CSS in patients with elderly-onset PanNEC showed good predictive power, enabling clinicians to understand patient's prognosis and make appropriate decisions.

Background: Esophageal mucinous adenocarcinoma (MAC) is a rare adenocarcinoma (AC) subtype. Limited research exists on its incidence, survival rates, and treatment responses. This study utilized the Surveillance, Epidemiology, and End Results (SEER) database to compare the clinical characteristics and prognoses of patients with esophageal MAC, AC, and signet-ring cell carcinoma (SRC), and developed nomograms to predict outcomes.

Methods: Patient information was retrieved from the SEER database from 2004 to 2015. The baseline characteristics were balanced using propensity score matching (PSM). Prognostic factors for esophageal MAC patients were identified by univariate and multivariate Cox analyses.

Results: A total of 497 esophageal MAC, 21,109 esophageal AC and 1,144 esophageal SRC patients were selected. MAC patients were more likely to have a higher pathological grade (P<0.001), and later T stage (P<0.001) and American Joint Committee on Cancer (AJCC) stage (P=0.003) than AC patients. The proportion of grade I-II MAC patients was higher than that of SRC patients. The overall survival (OS) and cancer-specific survival (CSS) of MAC patients were similar to those of AC patients. However, MAC patients had significantly better OS and CSS than SRC patients. After PSM analysis, the OS and CSS of MAC patients were similar to those of AC and SRC patients (all P>0.05). In MAC patients, N stage, M stage, and surgery were independent predictive factors for both OS and CSS. The area under the curve (AUC) and calibration curves demonstrated high precision and discrimination. Decision curve analysis (DCA) demonstrated that the CSS and OS nomograms have high potential clinical value.

Conclusions: Esophageal MAC patients had similar survival compared with esophageal AC and esophageal SRC patients. The nomograms provide OS and CSS predictions for MAC patients, to aid clinicians in predicting patients' prognoses.