Chemotherapy-induced splenic volume increase is independently associated with major complications after hepatic resection for metastatic colorectal cancer

Energy-efficient high-fidelity image reconstruction with memristor arrays for medical diagnosis

Medical imaging is an important tool for accurate medical diagnosis, while state-of-the-art image reconstruction algorithms raise critical challenges in massive data processing for high-speed and high-quality imaging. Here, we present a memristive image reconstructor (MIR) to greatly accelerate image reconstruction with discrete Fourier transformation (DFT) by computing-in-memory (CIM) with memristor arrays. A high-accuracy quasi-analogue mapping (QAM) method and generic complex matrix transfer (CMT) scheme was proposed to improve the mapping precision and transfer efficiency, respectively. High-fidelity magnetic resonance imaging (MRI) and computed tomography (CT) image reconstructions were demonstrated, achieving software-equivalent qualities and DICE scores after segmentation with nnU-Net algorithm. Remarkably, our MIR exhibited 153× and 79× improvements in energy efficiency and normalized image reconstruction speed, respectively, compared to graphics processing unit (GPU). This work demonstrates MIR as a promising high-fidelity image reconstruction platform for future medical diagnosis, and also largely extends the application of memristor-based CIM beyond artificial neural networks.

aiWave: Volumetric Image Compression With 3-D Trained Affine Wavelet-Like Transform

Volumetric image compression has become an urgent task to effectively transmit and store images produced in biological research and clinical practice. At present, the most commonly used volumetric image compression methods are based on wavelet transform, such as JP3D. However, JP3D employs an ideal, separable, global, and fixed wavelet basis to convert input images from pixel domain to frequency domain, which seriously limits its performance. In this paper, we first design a 3-D trained wavelet-like transform to enable signal-dependent and non-separable transform. Then, an affine wavelet basis is introduced to capture the various local correlations in different regions of volumetric images. Furthermore, we embed the proposed wavelet-like transform to an end-to-end compression framework called aiWave to enable an adaptive compression scheme for various datasets. Last but not least, we introduce the weight sharing strategies of the affine wavelet-like transform according to the volumetric data characteristics in the axial direction to reduce the number of parameters. The experimental results show that: 1) when cooperating our trained 3-D affine wavelet-like transform with a simple factorized entropy coding module, aiWave performs better than JP3D and is comparable in terms of encoding and decoding complexities; 2) when adding a context module to remove signal redundancy further, aiWave can achieve a much better performance than HEVC.

Natural Language Processing of Large-Scale Structured Radiology Reports to Identify Oncologic Patients With or Without Splenomegaly Over a 10-Year Period

PURPOSE

To assess the accuracy of a natural language processing (NLP) model in extracting splenomegaly described in patients with cancer in structured computed tomography radiology reports.

METHODS

In this retrospective study between July 2009 and April 2019, 3,87,359 consecutive structured radiology reports for computed tomography scans of the chest, abdomen, and pelvis from 91,665 patients spanning 30 types of cancer were included. A randomized sample of 2,022 reports from patients with colorectal cancer, hepatobiliary cancer (HB), leukemia, Hodgkin lymphoma (HL), and non-HL patients was manually annotated as positive or negative for splenomegaly. NLP model training/testing was performed on 1,617/405 reports, and a new validation set of 400 reports from all cancer subtypes was used to test NLP model accuracy, precision, and recall. Overall survival was compared between the patient groups (with and without splenomegaly) using Kaplan-Meier curves.

RESULTS

The final cohort included 3,87,359 reports from 91,665 patients (mean age 60.8 years; 51.2% women). In the testing set, the model achieved accuracy of 92.1%, precision of 92.2%, and recall of 92.1% for splenomegaly. In the validation set, accuracy, precision, and recall were 93.8%, 92.9%, and 86.7%, respectively. In the entire cohort, splenomegaly was most frequent in patients with leukemia (32.5%), HB (17.4%), non-HL (9.1%), colorectal cancer (8.5%), and HL (5.6%). A splenomegaly label was associated with an increased risk of mortality in the entire cohort (hazard ratio 2.10; 95% CI, 1.98 to 2.22; P < .001).

CONCLUSION

Automated splenomegaly labeling by NLP of radiology report demonstrates good accuracy, precision, and recall. Splenomegaly is most frequently reported in patients with leukemia, followed by patients with HB.

Fully Automatic Volume Measurement of the Spleen at CT Using Deep Learning

Purpose

To develop a fully automated algorithm for spleen segmentation and to assess the performance of this algorithm in a large dataset.

Materials and Methods

In this retrospective study, a three-dimensional deep learning network was developed to segment the spleen on thorax-abdomen CT scans. Scans were extracted from patients undergoing oncologic treatment from 2014 to 2017. A total of 1100 scans from 1100 patients were used in this study, and 400 were selected for development of the algorithm. For testing, a dataset of 50 scans was annotated to assess the segmentation accuracy and was compared against the splenic index equation. In a qualitative observer experiment, an enriched set of 100 scan-pairs was used to evaluate whether the algorithm could aid a radiologist in assessing splenic volume change. The reference standard was set by the consensus of two other independent radiologists. A Mann-Whitney U test was conducted to test whether there was a performance difference between the algorithm and the independent observer.

Results

The algorithm and the independent observer obtained comparable Dice scores (P = .834) on the test set of 50 scans of 0.962 and 0.964, respectively. The radiologist had an agreement with the reference standard in 81% (81 of 100) of the cases after a visual classification of volume change, which increased to 92% (92 of 100) when aided by the algorithm.

Conclusion

A segmentation method based on deep learning can accurately segment the spleen on CT scans and may help radiologists to detect abnormal splenic volumes and splenic volume changes.Supplemental material is available for this article.© RSNA, 2020.

Evaluation of multislice inputs to convolutional neural networks for medical image segmentation

PURPOSE

When using convolutional neural networks (CNNs) for segmentation of organs and lesions in medical images, the conventional approach is to work with inputs and outputs either as single slice [two-dimensional (2D)] or whole volumes [three-dimensional (3D)]. One common alternative, in this study denoted as pseudo-3D, is to use a stack of adjacent slices as input and produce a prediction for at least the central slice. This approach gives the network the possibility to capture 3D spatial information, with only a minor additional computational cost.

METHODS

In this study, we systematically evaluate the segmentation performance and computational costs of this pseudo-3D approach as a function of the number of input slices, and compare the results to conventional end-to-end 2D and 3D CNNs, and to triplanar orthogonal 2D CNNs. The standard pseudo-3D method regards the neighboring slices as multiple input image channels. We additionally design and evaluate a novel, simple approach where the input stack is a volumetric input that is repeatably convolved in 3D to obtain a 2D feature map. This 2D map is in turn fed into a standard 2D network. We conducted experiments using two different CNN backbone architectures and on eight diverse data sets covering different anatomical regions, imaging modalities, and segmentation tasks.

RESULTS

We found that while both pseudo-3D methods can process a large number of slices at once and still be computationally much more efficient than fully 3D CNNs, a significant improvement over a regular 2D CNN was only observed with two of the eight data sets. triplanar networks had the poorest performance of all the evaluated models. An analysis of the structural properties of the segmentation masks revealed no relations to the segmentation performance with respect to the number of input slices. A post hoc rank sum test which combined all metrics and data sets yielded that only our newly proposed pseudo-3D method with an input size of 13 slices outperformed almost all methods.

CONCLUSION

In the general case, multislice inputs appear not to improve segmentation results over using 2D or 3D CNNs. For the particular case of 13 input slices, the proposed novel pseudo-3D method does appear to have a slight advantage across all data sets compared to all other methods evaluated in this work.

Multi-Organ Segmentation Over Partially Labeled Datasets With Multi-Scale Feature Abstraction

Shortage of fully annotated datasets has been a limiting factor in developing deep learning based image segmentation algorithms and the problem becomes more pronounced in multi-organ segmentation. In this paper, we propose a unified training strategy that enables a novel multi-scale deep neural network to be trained on multiple partially labeled datasets for multi-organ segmentation. In addition, a new network architecture for multi-scale feature abstraction is proposed to integrate pyramid input and feature analysis into a U-shape pyramid structure. To bridge the semantic gap caused by directly merging features from different scales, an equal convolutional depth mechanism is introduced. Furthermore, we employ a deep supervision mechanism to refine the outputs in different scales. To fully leverage the segmentation features from all the scales, we design an adaptive weighting layer to fuse the outputs in an automatic fashion. All these mechanisms together are integrated into a Pyramid Input Pyramid Output Feature Abstraction Network (PIPO-FAN). Our proposed method was evaluated on four publicly available datasets, including BTCV, LiTS, KiTS and Spleen, where very promising performance has been achieved. The source code of this work is publicly shared at https://github.com/DIAL-RPI/PIPO-FAN to facilitate others to reproduce the work and build their own models using the introduced mechanisms.

Oxaliplatin-induced haematological toxicity and splenomegaly in mice

PURPOSE

Haematological toxicities occur in patients receiving oxaliplatin. Mild anaemia (grade 1-2) is a common side effect and approximately 90% of recipients develop measurable spleen enlargement. Although generally asymptomatic, oxaliplatin-induced splenomegaly is independently associated with complications following liver resection for colorectal liver metastasis and separately with poorer patient outcomes. Here, we investigated oxaliplatin-induced haematological toxicities and splenomegaly in mice treated with escalating dosages comparable to those prescribed to colorectal cancer patients.

METHODS

Blood was analysed, and smears assessed using Wright-Giemsa staining. Paw coloration was quantified as a marker of anaemia. Spleen weight and morphology were assessed for abnormalities relating to splenomegaly and a flow cytometry and multiplex cytokine array assessment was performed on splenocytes. The liver was assessed for sinusoidal obstructive syndrome.

RESULTS

Blood analysis showed dose dependent decreases in white and red blood cell counts, and significant changes in haematological indices. Front and hind paws exhibited dose dependent and dramatic discoloration indicative of anaemia. Spleen weight was significantly increased indicating splenomegaly, and red pulp tissue exhibited substantial dysplasia. Cytokines and chemokines within the spleen were significantly affected with temporal upregulation of IL-6, IL-1α and G-CSF and downregulation of IL-1β, IL-12p40, MIP-1β, IL-2 and RANTES. Flow cytometric analysis demonstrated alterations in splenocyte populations, including a significant reduction in CD45+ cells. Histological staining of the liver showed no evidence of sinusoidal obstructive syndrome but there were signs suggestive of extramedullary haematopoiesis.

CONCLUSION

Chronic oxaliplatin treatment dose dependently induced haematological toxicity and splenomegaly characterised by numerous physiological and morphological changes, which occurred independently of sinusoidal obstructive syndrome.

Human splenic polymorphonuclear myeloid-derived suppressor cells (PMN-MDSC) are strategically located immune regulatory cells in cancer

In contrast to the mouse, functional assets of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSC) in the human spleen remain to be better elucidated. Here, we report that the spleen in gastric and pancreatic cancer adopts an immune regulatory character, harbors excessive amount of PMN-MDSC, and anatomically enables their interaction with T cells. Compared to the peripheral blood, the spleen from cancer patients contained significantly higher levels of low-density PMN-MDSC, but not early-stage MDSC (e-MDSC) and monocytic-MDSC (M-MDSC). Low-density fraction of polymorphonuclear (PMN) cells was enriched in immature myeloid cells and displayed higher levels of CD10, CD16, and ROS than their blood-derived counterparts. They were also positive for PD-L1, LOX-1, and pSTAT3. The white pulp and periarteriolar lymphoid sheath (PALS) were strategically surrounded by PMN cells that were in contact with T cells. Unlike those from the blood, both low-density and normal-density PMN cells from the human spleen suppressed T cell proliferation and IFN-γ production. Independent of clinical grade, high PMN-MDSC percentages were associated with decreased survival in gastric cancer. In summary, our results outline the immune regulatory role of the spleen in cancer where neutrophils acquire MDSC functions and feasibly interact with T cells.

The Impact of Modern Chemotherapy and Chemotherapy-Associated Liver Injuries (CALI) on Liver Function: Value of 99mTc-Labelled-Mebrofenin SPECT-Hepatobiliary Scintigraphy

BACKGROUND

Chemotherapy is increasingly used before hepatic resection, with controversial impact regarding liver function. This study aimed to assess the capacity of 99mTc-labelled-mebrofenin SPECT-hepatobiliary scintigraphy (HBS) to predict liver dysfunction due to chemotherapy and/or chemotherapeutic-associated liver injuries (CALI), such as sinusoidal obstruction syndrome (SOS) and nonalcoholic steatohepatitis (NASH) activity score (NAS).

METHODS

From 2011 to 2015, all consecutive noncirrhotic patients scheduled for a major hepatectomy (≥ 3 segments) gave informed consent for preoperative SPECT-HBS allowing measurements of segmental liver function. As primary endpoint, HBS results were compared between patients with versus without (1) preoperative chemotherapy (≤ 3 months); and (2) CALI, mainly steatosis, NAS (Kleiner), or SOS (Rubbia-Brandt). Secondary endpoints were (1) other factors impairing function; and (2) impact of chemotherapy, and/or CALI on hepatocyte isolation outcome via liver tissues.

RESULTS

Among 115 patients, 55 (47.8%) received chemotherapy. Sixteen developed SOS and 35 NAS, with worse postoperative outcome. Overall, chemotherapy had no impact on liver function, except above 12 cycles. In patients with CALI, a steatosis ≥ 30% significantly compromised function, as well as NAS, especially grades 2-5. Conversely, SOS had no impact, although subjected to very low patients number with severe SOS. Other factors impairing function were diabetes, overweight/obesity, or fibrosis. Similarly, chemotherapy in 73 of 164 patients had no effect on hepatocytes isolation outcome; regarding CALI, steatosis ≥ 30% and NAS impaired the yield and/or viability of hepatocytes, but not SOS.

CONCLUSIONS

In this first large, prospective study, HBS appeared to be a valuable tool to select heavily treated patients at risk of liver dysfunction through steatosis or NAS.

Splenic enlargement induced by preoperative chemotherapy is a useful indicator for predicting liver regeneration after resection for colorectal liver metastases

Background

Conversion chemotherapy may downsize unresectable colorectal liver metastases (CRLMs), but may cause liver injury and splenic enlargement. The effect of preoperative chemotherapy on liver regeneration after liver resection remains undetermined. The aim of this study was to examine whether splenic enlargement induced by preoperative chemotherapy is an indicator to identify high-risk patients for impaired liver regeneration and liver dysfunction after resection.

Methods

We retrospectively reviewed 118 Japanese patients with CRLMs. Fifty-one patients had conversion chemotherapy. The other 67 patients underwent up-front liver resection. We clarified effects of conversion chemotherapy on splenic volume, liver function, and postoperative liver regeneration. Perioperative outcome was also analyzed.

Results

A ratio of the splenic volume before and after chemotherapy (SP index) in the oxaliplatin-based chemotherapy group was significantly greater than other chemotherapy groups after 9 or more chemotherapy cycles. Patients whose SP index was 1.2 or more had significantly higher indocyanine green retention rate at 15 min (ICG-R15) than patients without chemotherapy. Analyses of covariance showed liver regeneration rate after resection was decreased in patients whose SP index was 1.2 or more. The incidence of postoperative liver dysfunction in patients whose SP index was 1.2 or more was significantly greater than patients without chemotherapy. Multivariate analysis showed SP index was a significant predictive factor of impaired liver regeneration.

Conclusions

Splenic enlargement induced by preoperative chemotherapy was a useful indicator for impaired liver regeneration after resection and a decision-making tool of treatment strategy for unresectable CRLMs.

Correlation of postoperative splenic volume increase with prognosis of hepatocellular carcinoma after curative hepatectomy

Background

Previous studies have reported a close connection between the spleen and hepatic tumours. We investigated the prognostic value of postoperative splenic volume increase (PSVI) in patients with hepatocellular carcinoma after curative hepatectomy.

Methods

This was a retrospective study of adult patients with hepatocellular carcinoma who underwent hepatectomy between January 2007 and May 2013. We categorized patients into 2 groups according to the cut-off value of the receiver operating characteristic curve: group A (PSVI < 19.0%) and group B (PSVI ≥ 19.0%). We compared the clinicopathological data, overall survival and disease-free survival between the 2 groups. We performed univariate and multivariate analyses to identify factors associated with disease-free and overall survival.

Results

There were 275 patients in group A and 196 patients in group B. The 1-, 3- and 5-year overall survival rates were 98.9%, 74.9% and 63.6%, respectively, for patients in group A, and 97.4%, 65.3% and 49.8%, respectively, for patients in group B (p = 0.004). The corresponding disease-free survival rates were 69.5%, 48.0% and 40.3%, and 58.1%, 36.5%, and 29.8% (p = 0.01). On multivariate analysis, PSVI was an independent predictor of overall (p = 0.01) and disease-free (p = 0.03) survival.

Conclusion

Postoperative splenic volume increase correlates with poor prognosis of patients with hepatocellular carcinoma after curative hepatectomy.

Splenic volume as a biomarker of hepatic damage after chemotherapy in patients with resected colorectal liver metastases (CRLM)

BACKGROUND

Chemotherapy-associated liver injury (CALI) is a matter of concern for hepatobiliary surgeons as it can entail postoperative liver failure after an extensive hepatectomy. Recent studies have taken special interest in liver function parameters which can correlate with CALI to decrease this adverse event. Therefore, the current study investigates the usefulness of splenic volume as a biomarker of CALI through a portal hypertension mechanism, in patients with colorectal liver metastases (CRLM).

STUDY DESIGN

We carried out a study in patients with CRLM operated on between 2009 and 2014 in our center. All samples of healthy liver were graded for non-alcoholic fatty liver disease (NAFLD) and sinusoidal obstructive syndrome. Computarized tomography scans for spleen volumetry were analyzed for each patient at CRLM diagnosis, after neoadjuvant chemotherapy, 1 and 6 months after resection.

RESULTS

A group of 65 consecutive patients with CRLM of large bowel adenocarcinoma submitted to liver resection were included. Patients receiving neoadjuvant chemotherapy had a greater spleen volume increase than those who did not receive treatment (p = 0.053), finding a statistically significant spleen growth in patients with NAFLD (p = 0.036). There was no correlation between spleen enlargement and postoperative complications or average stay. However, survival was decreased in patients with spleen growth and CALI.

CONCLUSIONS

Patients who receive neoadjuvant chemotherapy for liver metastasis surgery have a greater splenic volume increase, which correlates with NAFLD and a lower survival.

Recent Findings on Nanotechnology-based Therapeutic Strategies Against Hepatocellular Carcinoma

Background:

Nanotechnology-based therapies are emerging as a promising new anticancer approach. Early clinical studies suggest that nanoparticle-based therapeutics can show enhanced efficacy while reducing side effects minimal, owing to targeted delivery and active intracellular uptake.

Methods:

To overcome the problems of gene and drug delivery, nanotechnology based delivery system gained interest in the last two decades. Encouraging results from Nano formulation based drug delivery systems revealed that these emerging restoratives can efficiently lead to more effective, targeted, selective and efficacious delivery of chemotherapeutic agents to the affected target cells.

Results:

Nanotechnology not only inhibits targeted gene products in patients with cancer, but also taught us valuable lessons regarding appropriate dosages and route of administrations. Besides, nanotechnology based therapeutics holds remarkable potential as an effective drug delivery system. We critically highlight the recent findings on nanotechnology mediated therapeutics strategies to combat hepatocellular carcinoma and discuss how nanotechnology platform can have enhanced anticancer effects compared with the parent therapeutic agents they contain.

Conclusion:

In this review, we discussed the key challenges, recent findings and future perspective in the development of effective nanotechnology-based cancer therapeutics. The emphasis here is focused on nanotechnology-based therapies that are likely to affect clinical investigations and their implications for advancing the treatment of patients with hepatocellular carcinoma.

Preoperative Aspartate Aminotransferase-to-Platelet Ratio Index Predicts Perioperative Liver-Related Complications Following Liver Resection for Colorectal Cancer Metastases

BACKGROUND AND AIMS

There are limited data on the potential role of preoperative non-invasive markers, specifically the aspartate-to-alanine aminotransferase ratio and the aspartate aminotransferase-to-platelet ratio index, in predicting perioperative liver-related complications after hepatectomy for colorectal cancer metastases.

METHODS

Patients undergoing liver resection for colorectal cancer metastases in a European institution during 2003-2010 were retrospectively enrolled. Relevant data, such as neoadjuvant chemotherapy, preoperative liver function tests, and perioperative complications, were collected from medical records. The nontumorous liver parenchyma in the surgical specimens of 31 patients was re-evaluated.

RESULTS

Overall, 215 patients were included. In total, 40% underwent neoadjuvant chemotherapy and 47% major resection, while 47% had perioperative complications (6% liver-related). In multivariate regression analysis, the aspartate aminotransferase-to-platelet ratio index was independently associated with liver-related complications (odds ratio: 1.149, p = 0.003) and perioperative liver failure (odds ratio: 1.155, p = 0.012). The latter was also true in the subcohort of patients with neoadjuvant chemotherapy (odds ratio: 1.157, p = 0.004) but not in those without such therapy (p = 0.062). The aspartate-to-alanine aminotransferase ratio was not related to liver-related complications (p = 0.929). The area under the receiver operating characteristics curve for the aspartate aminotransferase-to-platelet ratio index as a predictor of liver-related complications was 0.857 (p = 0.008) in patients with neoadjuvant chemotherapy. Increasing aspartate aminotransferase-to-platelet ratio index was observed with an increase in degrees of sinusoidal obstruction syndrome (p = 0.01) but not for fibrosis (p = 0.175) or steatosis (p = 0.173) in the nontumorous liver in surgical specimens.

CONCLUSION

The preoperative aspartate aminotransferase-to-platelet ratio index, but not the aspartate-to-alanine aminotransferase ratio, predicts perioperative liver-related complications following hepatectomy due to colorectal cancer metastases, in particular after neoadjuvant chemotherapy. The aspartate aminotransferase-to-platelet ratio index is related to sinusoidal obstruction syndrome in the nontumorous liver.

Astragaloside IV Enhances Cisplatin Chemosensitivity in Human Colorectal Cancer via Regulating NOTCH3

Although astragaloside IV exhibits anti-inflammation, immunoregulatory, and anticancer properties, the chemosensitization effects of astragaloside IV in colorectal cancer have never been reported. Our study tested whether astragaloside could increase cisplatin sensitivity in colorectal cancer. CCK-8 assay was used to measure the cell viability of colorectal cancer cells. Quantitative real-time PCR and Western blot were performed to determine the mRNA and protein expression, respectively. Our data revealed that astragaloside IV administration significantly suppressed the cell growth of colorectal cancer cells, whereas no obvious cytotoxicity of astragaloside IV was observed in nonmalignant colonic cells. In addition, combined treatment with astragaloside IV dramatically elevated the chemosensitivity of colorectal cancer cells to cisplatin. Mechanical investigation revealed that the mRNA and protein expression of NOTCH3 was significantly lower in cisplatin and astragaloside IV-treated cells compared with cells treated with cisplatin alone. On the contrary, no obvious changes in tumor cell growth were shown after upregulation of NOTCH3 whether in the presence or absence of astragaloside IV. Thus, our data demonstrate that astragaloside IV increases the chemosensitivity of colorectal cancer cells to cisplatin, at least partly, through inhibition of NOTCH3. This study suggests that combined therapy with astragaloside IV might be a novel therapeutic approach for colorectal cancer.

Assessing splenic enlargement on CT by unidimensional measurement changes in patients with colorectal liver metastases

PURPOSE

The aim of this study was to assess splenic volume and to correlate unidimensional measurements with reference volumetric changes in chemotherapy-treated patients with colorectal cancer (CRC) liver metastases.

METHODS

Forty consecutive patients were selected from the cohort of a previously reported study of chemotherapy-related morbidity following major hepatectomy for CRC liver metastases. Patients were treated for 6 months prior to resection, with imaging performed at baseline and after 6 months of chemotherapy. Three unidimensional spleen measurements were recorded-width, thickness, and height (W, T, and H). Reference splenic volume was measured at baseline and after chemotherapy. The best unidimensional splenic measurement was determined by regression analysis. The 95% CI for the predicted values and R (2) values was calculated for each regression. The percentage of volume increase at 6 months was calculated.

RESULTS

W and H showed the highest correlation with splenic volume prior to and following chemotherapy (R (2) = 0.65-0.74, p < 0.001), while T showed a low correlation (R (2) = 0.11 and 0.18, p < 0.05). The mean reference splenic volume increased after 6 months of chemotherapy compared to baseline (326 vs. 278 mL). Splenic volume changes showed the highest correlation with changes in W (R (2) = 0.56, p < 0.001), then H (R (2) = 0.40, p < 0.001), but were not significantly correlated with changes in T (R (2) = 0.01, p = 0.055).

CONCLUSIONS

Our results show the potential utility of measuring changes in splenic width to predict clinically significant changes in splenic volume in chemotherapy-treated patients with CRC liver metastases.

Weighted gene co-expression network analysis of colorectal cancer liver metastasis genome sequencing data and screening of anti-metastasis drugs

Approximately 9% of cancer-related deaths are caused by colorectal cancer (CRC). CRC patients are prone to liver metastasis, which is the most important cause for the high CRC mortality rate. Understanding the molecular mechanism of CRC liver metastasis could help us to find novel targets for the effective treatment of this deadly disease. Using weighted gene co-expression network analysis on the sequencing data of CRC with and with metastasis, we identified 5 colorectal cancer liver metastasis related modules which were labeled as brown, blue, grey, yellow and turquoise. In the brown module, which represents the metastatic tumor in the liver, gene ontology (GO) analysis revealed functions including the G-protein coupled receptor protein signaling pathway, epithelial cell differentiation and cell surface receptor linked signal transduction. In the blue module, which represents the primary CRC that has metastasized, GO analysis showed that the genes were mainly enriched in GO terms including G-protein coupled receptor protein signaling pathway, cell surface receptor linked signal transduction, and negative regulation of cell differentiation. In the yellow and turquoise modules, which represent the primary non-metastatic CRC, 13 downregulated CRC liver metastasis-related candidate miRNAs were identified (e.g. hsa-miR-204, hsa-miR-455, etc.). Furthermore, analyzing the DrugBank database and mining the literature identified 25 and 12 candidate drugs that could potentially block the metastatic processes of the primary tumor and inhibit the progression of metastatic tumors in the liver, respectively. Data generated from this study not only furthers our understanding of the genetic alterations that drive the metastatic process, but also guides the development of molecular-targeted therapy of colorectal cancer liver metastasis.

Intraductal Papillary Mucinous Neoplasms and the Risk of Diabetes Mellitus in Patients Undergoing Resection Versus Observation

OBJECTIVE

The aim of this study is to determine the prevalence of diabetes mellitus (DM) in patients with intraductal papillary mucinous neoplasm of the pancreas (IPMN) and compare rates of new/progressive DM between IPMN patients undergoing pancreatectomy versus observation.

METHODS

Patients diagnosed with IPMN were identified from institutional databases, divided into two groups based on treatment type, pancreatectomy versus clinical observation, and subsequently evaluated. Standard demographic and clinicopathologic variables, fasting glucose, diabetic status, and pancreatic volume data, were obtained and compared between groups.

RESULTS

One hundred thirty-four IPMN patients were identified; 103 (77 %) underwent pancreatectomy and 31 (23 %) were observed. Baseline DM rate was 18 % (24/134). This was not different between groups [17 % (17/103) resected vs. 23 % (7/31) observed, p = 0.51]. Median follow-up was 53 months and new/progressive DM occurred in 37 (28 %) patients with no difference between groups [29 (28 %) resected vs. 8 (26 %) observed, p = 0.74]. Among resected patients, degree of dysplasia was associated with increase risk of new/progressive DM [moderate dysplasia OR 5.76 (1.24-26.79) and severe dysplasia OR 9.43 (1.54-57.74), p = 0.04], while procedure type and remnant volume were not.

CONCLUSIONS

The incidence and prevalence of DM among patients with IPMN was high and did not differ between resected and observed groups. Degree of dysplasia, not the amount of resected pancreas, was associated with increased risk of DM, suggesting that the presence or development of DM may be a marker of malignant progression. Confirmatory studies are required.