The Effect of High CDC6 Levels on Predicting Poor Prognosis in Colorectal Cancer

<b><i>Introduction:</i></b> We investigated the function of cell division cycle 6 (CDC6) on the prognosis in colorectal carcinoma (CRC). <b><i>Methods:</i></b> CDC6 protein expression levels in 121 patients with colorectal cancer and adjacent normal mucosa were detected by immunohistochemistry. <b><i>Results:</i></b> Compared to adjacent normal tissues, CDC6 mRNA level was overexpressed in CRC tissues. Moreover, CDC6 protein levels were expressed up to 93.39% (113/121) in CRC tissues in the cell nucleus or cytoplasm. However, there were only 5.79% (7/121) in normal mucosal tissues with nuclear expression. CDC6 expression was significantly correlated with TNM stage and tumor metastasis. The 5-year survival rate was lower in the high CDC6 expression group than the low group. After silencing of CDC6 expression in SW620 cells, cell proliferation was slowed, the tumor clones were decreased, and the cell cycle was arrested in G1 phase. In multivariate analysis, increased CDC6 protein expression levels in colon cancer tissues were associated with cancer metastasis, TNM stage, and patient survival time. <b><i>Conclusion:</i></b> CDC6 is highly expressed in CRC, and downregulation of CDC6 can slow the growth of CRC cells in vitro. It is also an independent predictor for poor prognosis and may be a useful biomarker for targeted therapy and prognostic evaluation.

Identification of a Novel Five-Gene Signature as a Prognostic and Diagnostic Biomarker in Colorectal Cancers

Colorectal cancer (CRC) is one of the leading causes of cancer-related mortality worldwide. The current TNM (Tumor, Node, and Metastasis) classification approach is suboptimal in determining the prognosis of CRC patients. The prognosis for CRC is affected by a variety of features that are present at the initial diagnosis. Herein, we performed a systematic exploration and established a novel five-panel gene signature as a prognostic and early diagnosis biomarker after performing differential gene expression analyses in five independent in silico CRCs cohort and independently validating it in one clinical cohort, using immunohistochemistry. Four genes (BDNF, PTGS2, GSK3B, and CTNNB1) were significantly upregulated and one gene (HPGD) was significantly downregulated in primary tumor tissues compared with adjacent normal tissues throughout all the five in silico datasets. The univariate CoxPH analysis yielded a five-gene signature that accurately predicted overall survival (OS) and recurrence-free survival (RFS) in the in silico training (AUC = 0.73 and 0.69, respectively) and one independent in silico validation cohort (AUC = 0.69 and 0.74, respectively). This five-gene signature demonstrated significant associations with poor OS in independent clinical validation cohorts of colon cancer (CC) patients (AUC = 0.82). Intriguingly, a risk stratification model comprising of the five-gene signature together with TNM stage and gender status achieved an even superior AUC of 0.89 in the clinical cohorts. On the other hand, the circulating mRNA expression of the upregulated four-gene signature achieved a robust AUC = 0.83 with high sensitivity and specificity as a diagnosis marker in plasma from CRC patients. We have identified a novel, five-gene signature as an independent predictor of OS, which in combination with TNM stage and gender offers an easy-to-translate and facile assay for the personalized risk-assessment in CRC patients.

Lipoxins and Resolvins in Patients With Pancreatic Cancer: A Preliminary Report

Eicosanoids are bioactive lipids derived from arachidonic acid, which have emerged as key regulators of a wide variety of pathophysiological processes in recent times and are implicated as mediators of gastrointestinal cancer. In this study, we investigated the systemic levels of lipoxygenase (LOX)-derived lipoxin A4 and B4, together with resolvin D1 and D2 in patients with pancreatic adenocarcinoma (n = 68), as well as in healthy individuals (n = 32). Systemic concentrations of the aforementioned immunoresolvents were measured using an enzyme-linked immunosorbent assay (ELISA). In this study, we observed that compared with concentrations in healthy individuals, the peripheral concentrations of the aforementioned eicosanoids were significantly elevated (2- to 10-fold) in patients with pancreatic cancer (in all cases p&lt;0.00001). No significant association was observed between eicosanoid levels and the TNM clinical staging. Furthermore, we observed no significant differences in concentrations of the analyzed bioactive lipids between patients diagnosed with early-stage (TNM stage I-II) and more advanced disease (TNM stage III-IV). Receiver operating characteristic (ROC) curve analysis of each aforementioned immunoresolvent showed area under the curve values ranging between 0.79 and 1.00. Sensitivity, specificity, as well as positive and negative predictive values of the eicosanoids involved in the detection/differentiation of pancreatic adenocarcinoma ranged between 56.8% and 100%. In summary, our research is the first study that provides clinical evidence to support a systemic imbalance in LOX-derived lipoxins and resolvins as the mechanism underlying the pathogenesis of pancreatic adenocarcinoma. This phenomenon occurs regardless of the clinical TNM stage of the disease. Furthermore, our study is the first to preliminarily highlight the role of peripheral levels of immunoresolvents, particularly resolvin D1, as potential novel biomarkers of pancreatic cancer in humans.

New Prognostic Frontiers for Lung Neuroendocrine Tumors

Purpose Well-differentiated lung neuroendocrine tumors (Lu-NET) are classified as typical (TC) and atypical (AC) carcinoids, based on mitotic counts and necrosis. However, prognostic factors, other than tumor node metastasis (TNM) stage and the histopathological diagnosis, are still lacking. The current study is aimed to identify potential prognostic factors to better stratify lung NET, thus, improving patients’ treatment strategy and follow-up. Methods A multicentric retrospective study, including 300 Lung NET, all surgically removed, from Italian and Spanish Institutions. Results Median age 61 years (13-86), 37.7% were males, 25.0% were AC, 42.0% were located in the lung left parenchyma, 80.3% presented a TNM stage I-II. Mitotic count was ≥2 per 10 high power field (HPF) in 24.7%, necrosis in 13.0%. Median overall survival (OS) was 46.1 months (0.6-323), median progression free survival (PFS) was 36.0 months (0.3-323). Female sex correlated with a more indolent disease (T1; N0; lower Ki67; lower mitotic count and the absence of necrosis). Left-sided primary tumors were associated with higher mitotic count and necrosis. At Cox multivariate regression model, age, left-sided tumors and nodal (N) positive status resulted independent negative prognostic factors for OS and PFS. Conclusions This study confirms the prognostic relevance of TNM stage and diagnosis to stratify LuNET. However, the current analysis suggests a wider spectrum of clinical and pathological prognostic factors, including age and primary tumor’s location. These parameters could help clinicians to personalize the management of Lu-NET.

Tumor Macroscopic Morphology Is an Important Prognostic Factor in Predicting Chemotherapeutic Efficacy and Clinical Outcomes of Patients With Colorectal Neuroendocrine Neoplasms, One Multicenter Retrospective Cohort Study

Background and AimsLocally advanced and metastatic colorectal neuroendocrine neoplasm (NEN) is a rare disease with a dismal prognosis. We aimed to explore the value of the macroscopic morphology of NENs in the management of TNM stage II-IV colorectal NENs, which has not been fully elucidated in previous reports.MethodsWe retrospectively enrolled 125 eligible patients with TNM stage II-IV colorectal NENs who were diagnosed between 2000 and 2020 from three Chinese hospitals. All were categorized into either protruding or ulcerative NEN groups through endoscopic evaluation of their macroscopic morphology. Clinicopathological data were collected and compared between the two groups. Survival analysis was performed to assess the survival outcomes between the two groups.ResultsA total of 77 and 48 patients had protruding and ulcerative NENs, respectively. Patients with ulcerative NENs had a larger median tumor size (P&lt;0.001) and higher median Ki-67 index (P&lt;0.001), and a larger proportion of these patients had grade G3 disease (P=0.001) and poorly differentiated neoplasms (P=0.001), as well as higher frequencies of T3 and T4 tumors (P=0.006) than patients with protruding NENs. In addition, patients with ulcerative NENs showed a much lower response to first-line chemotherapy [50% (95% CI: 27.3% - 72.7%) versus 20% (95% CI: 3.1% - 36.9%), P=0.03] and a worse 3-year progression-free survival (PFS) rate [19.7% (95% CI: 7.2% - 32.2%) versus 49.5% (95% CI: 37.5% - 61.5%), P=0.001] and 3-year overall survival (OS) rate [30.7% (95% CI: 15.6% - 45.8%) versus 76.9% (95% CI: 66.5% - 87.3%), P&lt;0.001] than those with protruding NENs. The multivariate analysis results indicated that the macroscopic shape of NENs was an independent prognostic factor affecting both PFS (HR = 1.760, 95% CI: 1.024 – 3.026, P = 0.04) and OS (HR = 2.280, 95% CI: 1.123 – 4.628, P = 0.02).ConclusionsUlcerative NENs were more malignant and chemotherapy resistant than protruding NENs. Tumor macroscopic morphology is a valuable prognostic factor for stage II-IV colorectal NENs.

A Novel Preoperative Inflammation Score System Established for Postoperative Prognosis Predicting of Intrahepatic Cholangiocarcinoma

BackgroundInflammation has been implicated in tumorigenesis and has been reported as an important prognostic factor in cancers. In this study, we aimed to develop and validate a novel inflammation score (IFS) system based on 12 inflammatory markers and explore its impact on intrahepatic cholangiocarcinoma (ICC) survival after hepatectomy.MethodsClinical data of 446 ICC patients underwent surgical treatment were collected from the Primary Liver Cancer Big Data, and then served as a training cohort to establish the IFS. Furthermore, an internal validation cohort including 175 patients was used as internal validation cohort of the IFS. A survival tree analysis was used to divide ICC patients into three groups (low-, median-, and high- IFS-score groups) according to different IFS values. Kaplan-Meier (KM) curves were used to compare the overall survival (OS) and recurrence-free survival (RFS) rates among three different groups. Cox regression analyses were applied to explore the independent risk factors influencing OS and RFS.ResultsIn the training cohort, 149 patients were in the low-IFS-score group, 187 in the median-IFS-score group, and 110 in the high-IFS-score group. KM curves showed that the high-IFS-score group had worse OS and RFS rates than those of the low- and median-IFS-score groups (P<0.001) in both the training and validation cohorts. Moreover, multivariable Cox analyses identified high IFS as an independent risk factor for OS and RFS in the training cohort. The area under the curve values for OS prediction of IFS were 0.703 and 0.664 in the training and validation cohorts, respectively, which were higher than those of the AJCC 7th edition TNM stage, AJCC 8th edition TNM stage, and the Child-Pugh score. ConclusionsOur results revealed IFS was an independent risk factor for OS and RFS in patients with ICC after hepatectomy and could serve as an effective prognostic prediction system in daily clinical practice.

Computed tomography radiomics for the prediction of thymic epithelial tumor histology, TNM stage and myasthenia gravis

Objectives To evaluate CT-derived radiomics for machine learning-based classification of thymic epithelial tumor (TET) stage (TNM classification), histology (WHO classification) and the presence of myasthenia gravis (MG). Methods Patients with histologically confirmed TET in the years 2000–2018 were retrospectively included, excluding patients with incompatible imaging or other tumors. CT scans were reformatted uniformly, gray values were normalized and discretized. Tumors were segmented manually; 15 scans were re-segmented after 2 weeks by two readers. 1316 radiomic features were calculated (pyRadiomics). Features with low intra-/inter-reader agreement (ICC<0.75) were excluded. Repeated nested cross-validation was used for feature selection (Boruta algorithm), model training, and evaluation (out-of-fold predictions). Shapley additive explanation (SHAP) values were calculated to assess feature importance. Results 105 patients undergoing surgery for TET were identified. After applying exclusion criteria, 62 patients (28 female; mean age, 57±14 years; range, 22–82 years) with 34 low-risk TET (LRT; WHO types A/AB/B1), 28 high-risk TET (HRT; WHO B2/B3/C) in early stage (49, TNM stage I-II) or advanced stage (13, TNM III-IV) were included. 14(23%) of the patients had MG. 334(25%) features were excluded after intra-/inter-reader analysis. Discriminatory performance of the random forest classifiers was good for histology(AUC, 87.6%; 95% confidence interval, 76.3–94.3) and TNM stage(AUC, 83.8%; 95%CI, 66.9–93.4) but poor for the prediction of MG (AUC, 63.9%; 95%CI, 44.8–79.5). Conclusions CT-derived radiomic features may be a useful imaging biomarker for TET histology and TNM stage.

Prognostic Value of Pretreatment Lymphocyte-to-Monocyte Ratio and Development of a Nomogram in Breast Cancer Patients

PurposeThe objective of this study was to explore the prognostic significance of pretreatment hematologic parameters in predicting disease-free survival (DFS) of breast cancer patients.Materials and MethodsThe medical records of 440 breast cancer patients in Shandong Cancer Hospital and Institute from 2003 to 2013 were analyzed retrospectively. Through the results of blood routine before treatment, the absolute lymphocyte count (ALC), absolute neutrophil count (ANC), absolute monocyte count (AMC), and absolute platelet count (APC) in peripheral blood were collected. The lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and neutrophil-to-monocyte ratio (NMR) were calculated. Cox proportional hazard model was used for univariate and multivariate analysis. The DFS was compared using Kaplan–Meier method. The prognostic nomogram of patients with breast cancer was developed.ResultsThe median DFS for all patients was 64.10 months. Univariate analysis showed that the DFS was associated with surgical approach, TNM stage, molecular subtype, neoadjuvant chemotherapy, radiotherapy, and LMR (p &lt; 0.05). TNM stage, molecular subtype, and LMR were independent prognostic factors of breast cancer in multivariate analysis (p &lt; 0.05). According to the Kaplan–Meier survival curve analysis, patients with higher LMR (≥4.85) were associated with longer median DFS (median DFS, 85.83 vs. 60.90, p &lt; 0.001). The proposed nomogram that incorporated LMR, TNM stage, and molecular subtype got a concordance index (c-index) of 0.69 in predicting 5-year DFS.ConclusionIn breast cancer patients, higher LMR was associated with longer median DFS and the nomogram including LMR, TNM stage, and molecular subtype could accurately predict the prolonged 5-year DFS of breast cancer patients.